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Question: What is the effect of accounting for path preference on the robot's belief update?

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Context 1: Paper Info

Title: Incorporating Human Path Preferences in Robot Navigation with Minimal Interventions
Publish Date: 16 Mar 2023
Author List: Oriana Peltzer, Dylan Asmar, Mac Schwager, Mykel Kochenderfer

Figure

Hyperplane arrangement of a twodimensional space containing two obstacles (colored in gray) The robot is located inside the pink polytope, surrounded by three adjacent obstacle-free polytopes Each hyperplane on the boundary of the robot's polytope corresponds to one of the nonredundant constraints in eq (4) (b)Graph derived from the hyperplane arrangement The nodes on the graph designate polytopes, and edges designate transitions to adjacent polytopes To estimate the human's preference, the robot updates a posterior over the goal and over which of the graph transitions φ 1 , φ 2 and φ 3 is preferred by the human (c)Example preference defined over the graph The location of the goal is indicated in yellow in the lower right polytope For each node, the outgoing pink arrow designates the edge on the graph corresponding to the preferred transition between polytopes 
Simple, 10 × 10, 8 polytopes (b) Map 2: Office, 10 × 10, 56 polytopes (c) Map 3: Classroom, 20 × 20, 73 polytopes (d) Sampled observations and robot's executed trajectories 
Fig 5: Maps used for simulating the robot navigation problem with path preferences In (d), the heading angles observed are indicated with arrows The goal is indicated with a pink circle, and the orange robot corresponds to the starting location The blue robot follows a policy that accounts for path preference, while the green robot does not The opacity of the robots increases with time 
Map 1 problem setup and example realizations for goal-only (green) and path preference (blue) solution methods The robot starts at the lower left corner of the environment, and the goal of the task (pink circle) is in the upper left area The robot does not know which goal, among 10 options (shown in light blue squares), is the correct goal The human provides noisy observations, indicated by arrows, at each iteration The green robot selects actions according to the goal-only baseline, and the blue robot uses our proposed method to infer path preferences The polytopes composing G are drawn in blue Probability of correct goal WLPHVWHS +J (c) Entropy of goal distribution g 
Fig  6: Probability of the correct goal, fig 6b, and entropy of the goal belief distribution P (g), fig 6c, for the same problem setup, fig 6a In this problem instance, the human's preference is to go to the goal by passing on the right side of the obstacle Results are averaged over 50 runs and the area filled represents one standard deviation above and below the mean value The goal-only baseline shows an over-confident prediction (shown by the strong reduction in belief entropy) that the correct goal is less likely, making it more difficult to reach the correct goal compared to a method that accounts for path preference 
Success rates in the simple environment (Map 1) The results are averaged over 6 randomly sampled problem instances (start location, goal location, and goal possibilities), and over 50 runs per problem instance ∆T is the number of time steps separating two consecutive human inputs The robot's mission time is Tmax = 30 time steps We selected γ h = 1 5, corresponding to relatively noisy human inputs and making the problem more difficult to solve for the robot 
Computation times for Goal Only and Path Preference methods on Map 1 (fig 5a),Map 2 (fig 5b), and Map 3 (fig 5c),averaged over 100 runs with randomly sampled problem instances The 95 % confidence interval is provided with the mean We evaluate computation time at the first iteration of each run (where the search depth takes on its highest value Tmax) 

abstract

Robots that can effectively understand human intentions from actions are crucial for successful human-robot collaboration  In this work, we address the challenge of a robot navigating towards an unknown goal while also accounting for a human's preference for a particular path in the presence of obstacles 
This problem is particularly challenging when both the goal and path preference are unknown a priori  To overcome this challenge, we propose a method for encoding and inferring path preference online using a partitioning of the space into polytopes  Our approach enables joint inference over the goal and path preference using a stochastic observation model for the human 
We evaluate our method on an unknown-goal navigation problem with sparse human interventions, and find that it outperforms baseline approaches as the human's inputs become increasingly sparse  We find that the time required to update the robot's belief does not increase with the complexity of the environment, which makes our method suitable for online applications 

INTRODUCTION

Collaboration between humans and robots has become increasingly important and one key aspect of this collaboration is the ability for robots to adapt to human decisions  In many scenarios, such as a robot navigating through a busy room to deliver an item, it is important for the robot to take into account human preferences 
For instance, humans may prefer a specific path that would allow their colleagues to notice the item being delivered, but this preference may change dynamically based on various factors such as changes in the environment or unforeseen circumstances  While some preferences can be incorporated into the path-planning process, accommodating dynamic user preferences in real-time remains challenging 
In this paper, we propose a way to enable robots to adapt to human preferences dynamically by leveraging real-time feedback to inform decision-making  In this work, we tackle the problem of robot navigation in which the robot cannot observe the goal or the preferred path to the goal, but must make navigation decisions that are influenced by humans through recommended actions 
Prior work has explored how to adapt to a human's preference through feedback, but such approaches often require a high level of intervention, which can be time-consuming and impractical in real-world scenarios  To optimize the use of human input and quickly infer the human's preference, Fig  : An autonomous robot navigates in a simulated classroom towards a goal location (pink circle) 
At the start of its mission, it receives direction indications (arrows) from a human that indicate which path it should take to get to the goal  In this scenario, the human wants the robot to go around the desks on the right side of the classroom  A robot that does not reason over path preferences (green) will take the shortest path to the goal regardless of the human's input 
Our method (blue) infers the human's path preference from these indications and adapts to their recommendations  we propose an approach that leverages probabilistic representations of human preference and incorporates real-time feedback  Previous research by Bajcsy et al  considered an online adaptation problem in a manipulation task, where the person can apply forces to the robot to indicate their preferences 
By allowing the robot to continue its task while taking into account a probabilistic representation of human preference, their approach does not require frequent inputs  Building on this idea, we adopt a similar approach to adapt to a human's preference in the context of a robot autonomously navigating through a known environment, such as a cluttered office space 
Specifically, we focus on allowing the human to influence the robot's trajectory with respect to obstacles, by providing guidance on preferred routes or paths, while the robot continues to execute its task  Paths can be represented using homotopy classes   However, homotopies can pose computational challenges when used to encode and infer human preferences 
When the robot maintains a belief over homotopy classes, the inference problem can become exponentially complex with the number of obstacles in the space  Additionally, when the goal is unknown, the number of variables increases with the number of candidate destinations  This complexity can render the decision-making problem intractable 
Our solution is to encode path preference based on a partitioning of the environment into polytopes   This representation allows path preferences to be expressed as sets of preferred transitions between adjacent polytopes  Paths belonging to different homotopy classes correspond to different sequences of transitions 
By leveraging conditional independence assumptions, we can make the Bayesian inference problem tractable  These assumptions exploit the fact that human actions provide information about the path in a piece-wise manner  For example, indicating a preference for navigating around a particular obstacle only provides information about the local area and not the entire path 
Finally, after updating its belief representation over the human's preference, the robot can adapt to indications by replanning online  Our contributions are as follows  • We formulate the human-robot collaboration problem as a Partially Observable Markov Decision Process (POMDP) where both the goal of the task and the human's path preference are unknown random variables 
• We propose an encoding of a human's path preference using a partitioning of the environment into polytopes, along with conditional independence assumptions that make the Bayesian inference problem tractable to infer the task goal and path preference online  • Through simulations in two environments of different sizes and complexity, we show that our method is effective for solving problems where the robot must reach a goal that is unknown a-priori while simultaneously adapting to a human's indications 
Our method shows higher success rates compared to baseline approaches when the human inputs are sparse  Our approach enables a robot to make effective navigation decisions in collaboration with a human, even when the goal and path preference are not known in advance, and with minimal human input  In recent years, there has been a growing interest in shared autonomy and interactive systems, where humans and robots work together to accomplish tasks 
Several approaches have been proposed to address the challenge of enabling effective collaboration between human and robot agents while still achieving high task performance  Losey et al  and Jeon, Losey, and Sadigh propose a framework where a human operator is given control of a task-relevant latent action space while an autonomous system handles the rest 
Dragan and Srinivasa present a formalism for arbitrating between a user's input and a robot's policy when both human and robot share control of the same action space  Cognetti et al  [7] provide a method for real-time modifications of a path,       Fig  : We model the intent inference problem with the above diagram 
At each step in time, the robot receives an observation ot from the human conditioned on its current location st, the intended goal g, and the human's path preference θ  The robot updates its belief over g and θ and transitions to a next location st+1  while Hagenow et al  present a method that allows an outside agent to modify key robot state variables and blends the changes with the original control 
However, a common challenge of these approaches is the high level of intervention required from humans  Best and Fitch propose a method for predicting an agent's intended trajectory from observations  Rather than maintaining a belief over the agent's future path, they infer the agent's intended goal among a set of candidate locations at the boundary of the space 
This approach provides information on where the agent is heading and generates a distribution of candidate future trajectories for the agent  Inferring the goal of the task among a discrete set of candidates is also relevant to the area of shared autonomy  Javdani, Srinivasa, and Bagnell propose a formalism for shared control of a robotic arm, where the robot must assist the human in picking up an object but needs to infer which object the human has chosen from joystick inputs 
Planning with homotopy class constraints is useful in problems where the robot's requirements are given with respect to obstacles, and Yi, Goodrich, and Seppi consider topological constraints provided by human operators  Bhattacharya propose an efficient algorithm for solving pathplanning problems under homotopic constraints 
However, the number of homotopy classes for a given problem can be infinite, and as the robot changes location and updates its representation of the world, carrying out inference over homotopy classes in a dynamic environment requires recomputing the set of homotopies at every iteration, making the belief update challenging 
Prior work has addressed the challenge of shared autonomy by considering how robots can infer a human's intended goal, or how they can infer the preferred path to a goal  However, we argue that inferring the goal and the path as separate problems can lead to over-confidence in incorrect beliefs about the user's preferences 
To illustrate this point, consider the following scenario: a robot and a human are collaborating to move an object from one end of a room to Fig  : Using the hyperplanes composing the H-representation of each obstacle, we construct a hyperplane arrangement of the obstacle-free space (a)  We define the human's preference for the robot's one step action choices as the posterior distribution (given all human input up to that point) over transitions from the current to the neighboring polytopes, i e  edges on the graph 
Each time the robot transitions to a new polytope, the set of neighbor polytopes and the distribution over human preferences are updated  another, but there is an obstacle in the way  The human would like the robot to take a path around the obstacle on the left, even though the goal is on the right  If the robot only infers the goal from the human's inputs, it may incorrectly assume that the goal is on the right, and become over-confident in this belief 
On the other hand, if the robot only infers the preferred path, it may mistakenly assume that the goal is on the left, leading to a failure in completing the task  To overcome these challenges, our work proposes a joint inference approach that considers both the human's intended goal and their preferred path to that goal 
Specifically, we model the human's preference over different homotopy classes and leverage a conditional independence assumption to provide a tractable solution  In our approach, we assume that the human's inputs are noisily rational conditioned on both the goal and the preference  By jointly inferring the goal and path preference, we can avoid over-confidence in incorrect beliefs about the user's preferences, leading to improved system performance 
We consider the problem of robot navigation in a known environment to an unknown destination, where a human can intervene and provide a heading direction to the robot using a joystick or force cues  The human also has a preference on which path the robot should take with respect to obstacles, and our objective is for the robot to understand the human's intentions and execute the task with minimal interventions 
Let g be a discrete random variable denoting the goal of the task, belonging to a set of candidates Ω g , and let θ be a discrete-valued random variable representing the human's path preference, belonging to a set of possible preferences Θ  The physical location of the robot at time index t is denoted by s t ∈ R 2 , and the robot's action at time index t, belonging to some action space A, is denoted by a t  
The transition model T (s t+1 | s t , a t ) is deterministic, meaning the robot has full control over its future location  At any time step, the human may provide an observation to the robot  When the human intervenes, the robot receives a direction (heading angle) that can be mapped to a future location in space 
More specifically, we map the direction to an intended location, which is the resulting robot location after advancing in the indicated direction for one time step  For simplicity, we consider that the robot directly makes an observation o t of the location indicated by the human  We assume that the robot has a stochastic observation model for the human P (o t | s t , g, θ) that is conditioned on both the goal of the task g and the human's preferred path θ 
We further assume that having chosen a goal and path preference, the human takes actions to noisily minimize a cost function C g,θ that measures the cost of moving from the robot's current location to the goal along the preferred path  For example, C g,θ (s t , o t ) can be the length of the shortest path from location s t to the goal g after taking a first step to o t , and constrained by path preference θ 
We use C g,θ to induce a probability distribution over observations, given by: where γ h is a hyperparameter that designates the rationality coefficient  This model assumes the human will pick the lowest cost action with the highest probability and the likelihood of an action decreases exponentially with the increase in cost  
Our inclusion of the path preference θ sets our approach apart from   The model is shown in fig  represented as a Bayesian Network 

Inference

At each time step where the human provides an observation, the posterior P (g, θ) is given through the Bayesian update We note that the number of Bayesian updates required at each iteration to update the belief is equal to the cardinality of Ω g × Θ  In addition, each Bayesian update involves computing C g,θ (  
,   ) in eq  ( ), which involves solving an optimization problem (such as a shortest path problem)  In section IV, we propose a specific encoding of preference θ for resolving eq  ( ), while ensuring the number of computations of the cost C g,θ ( ,  ) per update does not grow exponentially with the number of obstacles 

Decision Making

We consider a navigation problem where the robot receives reward according to the model R(s t , g, θ, a t )  We wish to find the optimal policy π that maximizes the expected discounted sum of future rewards, with discount factor γ  The above problem is a Partially Observable Markov Decision Process (POMDP)  
In this section, we propose an encoding of human's path preference θ for computing the posterior in eq  ( )  Devifrom the concept of homotopy classes, we define the preference according to a partitioning of the environment into polytopes, as shown in fig  , creating a hyperplane arrangement of the space 
Hyperplane arrangements have been used by Vincent and Schwager in the context of Neural Network verification  In our setting, we leverage this representation to define path preferences as preferred transitions between adjacent regions of the space 

Hyperplane Arrangement

We assume a two-dimensional environment composed of m polytopic obstacles, each defined by their half-space representation (H-representation) where A i ∈ R di×2 and b i ∈ R di , and where d i is the number of edges (hyperplanes) composing polytope i  Let n = i d i be the total number of hyperplanes  We leverage each obstacle's H-representation to construct a hyperplane arrangement of the environment as shown in fig 
 e  a partitioning of the space into polytopes  More specifically, each location in space belongs to a polytope j for which we can write an H-representation of the form where α j i ∈ {−1, 1} di is a vector specific to polytope j and obstacle i corresponding to the relative position of any point in the set with respect to each hyperplane in O i  
Fig  : Intent inference model in a hyperplane arrangement of the obstacle free space  We spatially decompose the preference θ into a set of preferred neighboring polytopes per region of the space  Within each polytope j, the human preference pj is a discrete distribution over the preferred neighbor in N (j) 
We assume that for a location st belonging to polytope j, and given goal g and preference pj, the observation ot and any other preference p i,i =j are conditionally independent  Concatenating elements from each obstacle's Hrepresentation, we can write polytope j's H-representation as where Some of the constraints in eq  ( ) (corresponding to rows of A, b and α j ) are redundant, i e  the set P j does not change upon their removal 
We can further reduce the Hrepresentation of a polytope to include only non-redundant constraints  By removing the rows corresponding to redundant constraints, we obtain new matrices A j e , b j e and α j e such that we can write the polytope's reduced H-representation as The non-redundant constraints correspond to edges of the polytope 
In other words, as the robot continually moves in space, the first hyperplane that it will cross upon exiting the polytope will correspond to one of the polytope's nonredundant constraints  Vincent and Schwager outline an iterative method for removing redundant constraints by solving n linear programs 
We use this method in practice for computing α j e for each polytope  We can now characterize each polytope by a vector α j e ∈ {−1, 1} n j e , where n j e ≤ n is the number of essential constraints of the polytope  The polytopes P j partition the environment into a hyperplane arrangement 

Path Preference

In this section, we provide a definition of preference θ according to a graphical representation of the environment based on the hyperplane arrangement  Under this representation, a path preference corresponds to a set of preferred transitions  In other words, for each polytope in the space, the human will have a preference to which neighboring polytope they wish to transition 
Let G := (V, E) be an undirected graph, where vertices are obstacle-free polytopes, and edges connect two adjacent polytopes  Each polytope is described by a unique vector α j as defined in eq  ( )  Two polytopes are adjacent if they share non-redundant constraints (rows in eq  ( )) corresponding to the same hyperplane (i e  they are on opposite sides of the hyperplane) 
Let N (v) be the set of neighbors of a vertex v  For each vertex, we denote p v the discrete-valued random variable describing which edge in N (v) the human intends to transition to  Using this formalism, we define a path preference as the set of preferred transitions over all nodes in the graph, Let m θ = v∈V |N (v)| be the cardinality of Θ, and m g = |Ω g | the number of possible goals 
A priori, the number of Bayesian updates required to update the belief at every iteration should be m θ × m g   Now, let us assume the conditional independence relationships described by the new problem diagram in fig    More specifically, we introduce the assumption that conditioned on a robot location s t , the goal g, and the preference for the corresponding vertex p v in the graph, the observation o t and the preference for any other vertex are conditionally independent 
In other words, the observations the human provides can be defined conditioned only on the robot location, the goal, and the human's preference for its current vertex p v   By introducing this assumption, each update step only requires updating the joint (p v , g), reducing the number of cost computations to |N (v)| × m g  
We can notice that by introducing this assumption, we removed the direct relationship between the number of polytopes in the environment and the complexity of the Bayesian update in eq  ( )  In practice, components of θ are not mutually independent  For example, if the human preference at a vertex v 1 is
, it is unlikely that the human will also prefer p v2 = (v 2 , v 1 ) (turning back)  We can improve our model by assuming a dependent relationship between preferences for adjacent edges, which does not significantly increase the complexity of the inference problem  An interesting property of our encoding is that any two paths that belong to different homotopy classes will cross different sequences of polytopes, i e  they correspond to a different sequence of edges on G 
This can be proved by contradiction  Let us suppose that two continuous trajectories ξ 1 and ξ 2 , with the same start and end points and that do not intersect any obstacle, traverse the same regions in G in the same order  From the construction of the hyperplane arrangement, each polytope that the paths traverse through is obstacle-free 
Therefore, within each polytope, there is no obstacle in the area located in between the portions of ξ 1 and ξ 2 that belong to the region  A smooth transformation of ξ 1 into ξ 2 can be obtained by transforming each portion of ξ 1 belonging to the polytopes it intersects into the corresponding portion of ξ 2 for the same polytopes, where the extremities of the trajectory portions are connected to one another along the polytope's edges (where the same edge is crossed by both paths) 
Along this transformation, the paths do not intersect any obstacle, and therefore ξ 1 and ξ 2 belong to the same homotopy class 

EXPERIMENTS

We evaluate our model on a simulated navigation task where the robot must reach a goal that is unknown a priori while respecting the path preferences indicated by a human  The robot navigates in a grid world containing obstacles  The transition model is deterministic: the robot selects an adjacent location on the grid to reach at the next time step 
The robot is also allowed to take diagonal actions  Each location s t in the map can be mapped to a vertex v t ∈ G  Therefore, the actions leading to locations mapped to different vertices correspond to edges on the graph  We note f (s t , a t ) the edge crossed by taking action a t from location s t  
The robot is given a mission time limit T max for reaching the goal  In this problem, we assume that the human selects actions to noisily minimize a cost function C g,θ , where θ is defined as per eq  ( ), corresponding to the length of the shortest path to the goal constrained by the preference (where the robot is only allowed to make transitions on G along preferred edges) 
More specifically, where δ(s t , g | o t , p vt ) designates the length of the shortest path from s t to g passing by o t and constrained by preference p vt   This is a slight variant of the cost function proposed by Best and Fitch , where we add in a conditioning on the path preference  We compute costs by running the A path planning algorithm on the environment maps (grid worlds with diagonal actions) and impose preference constraints by pruning invalid transitions from the search tree 
Reward model  At each step in time, the robot receives a reward which is a sum of three components: a goal-specific reward a preference-specific reward or penalty We compute solutions to the POMDP defined in section III-B with the online solver POMCP , and with the particularity that within the rollouts, the robot does not expect to collect human inputs 
Each time a solution is computed, the robot takes an action and may receive an observation  If it does, it updates its belief distribution over the unknown problem variables and resolves the POMDP over a receding horizon 

Baselines

• Goal only  The robot solves the POMDP while ignoring the effects of path preference  Similarly to , we assume the human is taking action to minimize a goaldependent cost C g (s t , o t ) = δ(s t , g | o t ), where the conditioning on the preference is removed  We also omit the path preference's contribution to the reward R pref  
• Compliant  The robot complies with the human input, but does not take an initiative  If the user stops providing information, the robot continues in the last direction indicated for 5 time steps (conserving its momentum), then stops  • Blended  We designed an arbitration function to decide between our proposed policy (accounting for path preferences) and the user's recommendation when the robot receives inputs 
Our metric to evaluate confidence in the robot's prediction for the purpose of arbitration is the entropy of the intention distribution H(g, p i ), where p i denotes the preferred neighbor for the current region  Because our representation of the world is discrete, the arbitration is given by a step function 
Denoted by U , the action corresponding to the human's input, and P , the robot's prediction for the optimal action, we write the policy where we chose h = 1 6 as the confidence threshold 

Results

When evaluating the algorithm, we consider that a run is successful if the robot reached the goal within its allocated mission time T max and only made transitions between graph vertices corresponding to the human's preferences  We vary the time delay between human inputs, from constant guidance (∆ T = 1) to only a single observation (∆ T ≥ T max ) 
Success rates  Table I reports the success rates for experiments conducted over six randomly sampled problem instances and 50 runs per instance in Map 1 (fig  )  When the human provides inputs at every iteration, the compliant policy shows the highest success rates  However, as ∆ T increases, the compliant robot is not able to accomplish the task within the allotted time as it does not receive sufficient inputs to do so, and performance decreases compared to the autonomous baselines 
We find that in these runs, accounting for path preference consistently improves performance compared with the goal-only baseline  Results also show that blending the user's input with the robot's policy (Path Preference + Blend) when the human provides information leads to improved performance  Belief entropy 
Figure shows a challenging problem instance where the directions the human provides do not align directly with the shortest path to the goal  By ignoring the effects of preferences in the problem model (goal only), the robot quickly infers from observations that the upper left goal is less likely than others (P (g) drops) 
The strong decrease in entropy shows that the robot becomes overconfident in this prediction  Overconfidence in an incorrect goal will prevent the agent from finding the correct goal once the human's indications directly align with it, as it needs to correct for the wrong predictions, as shown in the path realization (fig 
)  In this realization, the goal-only method (green robot) fails to search the upper left area within the allotted time  By accounting for path preferences in its model, the blue robot's entropy over the goal distribution decreases more steadily, allowing for it to leverage the human's latest observations and reach the goal successfully 
shows an over-confident prediction (shown by the strong reduction in belief entropy) that the correct goal is less likely, making it more difficult to reach the correct goal compared to a method that accounts for path preference  Computation time  In table II we provide the time required to solve the POMDP, and the time required to update the robot's belief as it receives new observations 
We compute solutions on three maps: a simple 10 × 10 grid world with 8 polytopes (fig  ), a 10 × 10 grid world with 56 polytopes (fig  ), and a 20×20 grid world with 73 polytopes (fig  )  The latter environment being larger, we increase the mission time and the depth of the search tree in POMCP from T max = 30 (Map 1 and Map 2) to T max = 60 (Map 3) 
We do not notice an increase in the time required to update the robot's belief with an increase in problem complexity, which is consistent with our observation that the complexity of the Bayesian update should not increase with the number of obstacles or polytopes  On the contrary, the belief update time on Map 2 and Map 3, containing more obstacles, is reduced compared to the first map 
More obstacles result in fewer iterations when solving the constrained shortest path problem with A   Adding constraints due to the obstacles and polytopes reduces the size of the A search tree  C  Limitations Simulation environments  In our simulations, we hardcoded the preference policy over the maps (e g  in Map 1, go around the table counter-clockwise) 
We randomly sampled problem instances (start and goal locations, and goal options) to reduce the bias introduced by these preference choices  To best evaluate and compare the different approaches, it would be best to sample preferences among a distribution of preferences chosen by a human (for example, from benchmarks resulting from a collection of data) 
Creating such a benchmark is an interesting direction for future work  Hyperplane arrangement construction  The main limitation of our approach is that the size and geometry of each polytope depends strongly on the geometry of the obstacles, as seen in fig    Because of this, the robot can make predictions over preferences that are too refined compared with the topology of the environment 
A direct consequence is that when the size of the polytopes is small, the information provided by the human can be incorrectly interpreted as a preference on the robot's immediate action  Our method can be improved by changing the structure of the hyperplane arrangement so that it relies on the topology of the environment, but does not vary strongly with the geometry of the features in the environment 
For this purpose, topometric maps and region construction algorithms are promising directions  We presented an approach for encoding and inferring a human's path preference in an environment with obstacles  By leveraging a partitioning of the space into polytopes and a stochastic observation model, our method allows for joint inference over the goal and path preference even when both are unknown a-priori 
Our experiments on an unknown-goal navigation problem with sparse human interventions demonstrate the effectiveness of our approach and its suitability for online applications  The time required to update the robot's belief does not increase with the complexity of the environment, which further highlights the practicality of our method 
Context 2: Thalassaemia minor | definition of Thalassaemia minor by Medical dictionary
Thalassaemia minor | definition of Thalassaemia minor by Medical dictionary
https://medical-dictionary thefreedictionary com/Thalassaemia+minor
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Related to Thalassaemia minor: thalassaemia major
Thalassemia describes a group of inherited disorders characterized by reduced or absent amounts of hemoglobin, the oxygen-carrying protein inside the red blood cells  There are two basic groups of thalassemia disorders: alpha thalassemia and beta thalassemia  These conditions cause varying degrees of anemia, which can range from insignificant to life threatening 
All types of thalassemias are considered quantitative diseases of hemoglobin, because the quantity of hemoglobin produced is reduced or absent  Usual adult hemoglobin is made up of three components: alpha globin, beta globin, and heme  Thalassemias are classified according to the globin that is affected, hence the names alpha and beta thalassemia  Although both classes of thalassemia affect the same protein, the alpha and beta thalassemias are distinct diseases that affect the body in different ways 
Beta thalassemia may be the most best-known type of thalassemia and is also called Cooley's anemia  It is caused by a change in the gene for the beta globin component of hemoglobin  Beta thalassemia causes variable anemia that can range from moderate to severe, depending in part on the exact genetic change underlying the disease  Beta thalassemia can be classified based on clinical symptoms  Beta thalassemia major usually causes severe anemia that can occur within months after birth  If left untreated, severe anemia can result in insufficient growth and development, as well as other common physical complications that can lead to a dramatically decreased life-expectancy  Fortunately, in developed countries beta thalassemia is usually identified by screening in the newborn period, before symptoms have developed  Children who are identified early can be started on ongoing blood transfusion therapy as needed  Although transfusion therapy prevents many of the complications of severe anemia, the body is unable to eliminate the excess iron contained in the transfused blood  Over time, the excess iron deposits in tissues and organs, resulting in damage and organ failure  Another medication must be administered to help the body eliminate the excess iron and prevent iron-over-load complications  Beta thalassemia intermedia describes the disease in individuals who have moderate anemia that only requires blood transfusions intermittently, if at all 
Alpha thalassemia is the result of changes in the genes for the alpha globin component of hemoglobin  There are two main types of alpha thalassemia disease: hemoglobin H disease and alpha thalassemia major  The two diseases are quite different from beta thalassemia as well as from one another  Individuals with hemoglobin H disease can experience events of hemolytic anemia—anemia caused by the rapid breakdown of the red blood cells  These events are thought to be triggered by various environmental causes, such as infection and/or exposure to certain chemicals  Hemoglobin H disease is in most cases milder than beta thalassemia  It does not generally require transfusion therapy  Alpha thalassemia major is a very serious disease that results in severe anemia that begins even before birth  Most affected babies do not survive to be born or die shortly after birth 
The thalassemias are among the most common genetic diseases worldwide  Both alpha and beta thalassemia have been described in individuals of almost every ancestry, but the conditions are more common among certain ethnic groups  Unaffected carriers of all types of thalassemia traits do not experience health problems  In fact, the thalassemia trait is protective against malaria, a disease caused by blood-borne parasites transmitted through mosquito bites  According to a widely accepted theory, most genetic changes—mutations—that cause thalassemia occurred multiple generations ago  Coincidentally, these mutations increased the likelihood that carriers would survive malaria infection  Survivors passed the mutation onto their offspring, and the trait became established throughout areas where malaria is common  As populations migrated, so did the thalassemia traits 
Beta thalassemia trait is seen most commonly in people with the following ancestry: Mediterranean (including North African, and particularly Italian and Greek), Middle Eastern, Indian, African, Chinese, and Southeast Asian (including Vietnamese, Laotian, Thai, Singaporean, Filipino, Cambodian, Malaysian, Burmese, and Indonesian)  Alpha-thalassemia trait is seen with increased frequency in the same ethnic groups  However, there are different types of alpha thalassemia traits within these populations  The frequency of hemoglobin H disease and alpha thalassemia major depends on the type of alpha thalassemia trait  The populations in which alpha thalassemia diseases are most common include Southeast Asians and Chinese (particularly Southern Chinese) 
It is difficult to obtain accurate prevalence figures for various types of thalassemia within different populations  This difficulty arises due to testing limitations in determining exact genetic diagnoses, as well as the fact that many studies have focused on small, biased hospital populations 
Two studies reflect prevalence figures that can be helpful counseling families and determining who to screen for beta thalassemia  Between the years of 1990 and 1996, the State of California screened more than 3 1 million infants born in the state for beta thalassemia  Approximately 1 in 114,000 infants had beta thalassemia major, with prevalence rates being highest among Asian Indians (about one in 4,000), Southeast Asians (about one in 10,000), and Middle Easterners (about one in 7,000)  Another type of beta thalassemia disease, E/beta thalassemia, was represented in approximately one in 110,000 births, all of which occurred in families of Southeast Asian ancestry  Among Southeast Asians, the prevalence of E/beta thalassemia was approximately one in 2,600 births  This is in keeping with the observation that hemoglobin E trait carrier rates are relatively high within the Southeast Asian population: 16% in a study of 768 immigrants to California, and up to 25% in some specific Southeast Asian populations such as Cambodians  While these California studies address some of the limitations of earlier population studies, the pattern observed in California is expected to be different in other areas of the United States and the world  For example, Italians are underrepresented in this population when compared to the population of the East Coast of the United States 
Determining prevalence figures for alpha thalassemia is even more difficult due to increased limitations in diagnostic testing  All types of alpha thalassemia disease are most common among people of Southeast Asian and Chinese descent, for reasons that become clearer with an understanding of the underlying genetics of alpha thalassemia  One study of 500 pregnant women in Northern Thailand estimated a frequency of one in 500 pregnancies affected by alpha thalassemia major, for example  Prevalence of alpha thalassemia disease is significantly lower in the United States primarily because of immigration patterns; although at least one state, California, has observed growing hemoglobin H disease incidence rates that are high enough to justify universal newborn screening for the condition 
Humans normally make several types of the oxygen-carrying protein hemoglobin  An individual's stage in development determines whether he or she makes primarily embryonic, fetal, or adult hemoglobins  All types of hemoglobin are made of three components: heme, alpha (or alpha-like) globin, and beta (or beta-like) globin  All types of thalassemia are caused by changes in either the alpha- or beta-globin gene  These changes cause little or no globin to be produced  The thalassemias are, therefore, considered quantitative hemoglobin diseases  All types of thalassemias are recessively inherited, meaning that a genetic change must be inherited from both the mother and the father  The severity of the disease is influenced by the exact thalassemia mutations inherited, as well as other genetic and environmental factors  There are rare exceptions, notably with beta thalassemia, where globin gene mutations exhibit a dominant pattern of inheritance in which only one gene needs to be altered in order to see disease expression  Scientists continue to study the causes  For instance, a new mutation for alpha-thalassemia was discovered for the first time among Iranian patients in 2004 
BETA-THALASSEMIA  Most individuals have two normal copies of the beta globin gene, which is located on chromosome 11 and makes the beta globin component of normal adult hemoglobin, hemoglobin A  There are approximately 100 genetic mutations that have been described that cause beta thalassemia, designated as either beta0 or beta + mutations  No beta globin is produced with a beta0 mutation, and only a small fraction of the normal amount of beta globin is produced with a beta + mutation 
When an individual has one normal beta globin gene and one with a beta thalassemia mutation, he or she is said to carry the beta thalassemia trait  Beta thalassemia trait, like other hemoglobin traits, is protective against malaria infection  Trait status is generally thought not to cause health problems, although some women with beta thalassemia trait may have an increased tendency toward anemia during pregnancy 
When two members of a couple carry the beta thalassemia trait, there is a 25% chance that each of their children will inherit beta thalassemia disease by inheriting two beta thalassemia mutations, one from each parent  The clinical severity of the beta thalassemia disease—whether an individual has beta thalassemia intermedia or beta thalassemia major—will depend largely on whether the mutations inherited are beta0 thalassemia or beta + thalassemia mutations  Two beta0 mutations generally lead to beta thalassemia major, and two beta+ thalassemia mutations generally lead to beta thalassemia intermedia  Inheritance of one beta0 and one beta + thalassemia mutation tends to be less predictable 
Although relatively uncommon, there are other thalassemia-like mutations that can affect the beta globin gene  Hemoglobin E is the result of a substitution of a single nucleotide  This change results in a structurally altered hemoglobin that is produced in decreased amounts  Therefore, hemoglobin E is unique in that it is both a quantitative (i e  thalassemia-like) and qualitative trait  When co-inherited with a beta thalassemia trait, it causes a disease that is almost indistinguishable from beta thalassemia disease  Large deletions around and including the beta globin gene can lead to delta/beta thalassemia or hereditary persistence of fetal hemoglobin (HPFH)  Interestingly, delta/beta thalassemia trait behaves very similarly to beta thalassemia trait in its clinical manifestations  However, HPFH trait does not tend to cause hemoglobin disease when co-inherited with a second thalassemia or other beta globin mutation 
ALPHA-THALASSEMIA  Most individuals have four normal copies of the alpha globin gene, two copies on each chromosome 16  These genes make the alpha globin component of normal adult hemoglobin, which is called hemoglobin A  Alpha globin is also a component of fetal hemoglobin and the other major adult hemoglobin called hemoglobin A2  Mutations of the alpha globin genes are usually deletions of the gene, resulting in absent production of alpha globin  Since there are four genes (instead of the usual two) to consider when looking at alpha globin gene inheritance, there are several alpha globin types that are possible 
Absence of one alpha globin gene leads to a condition known as silent alpha thalassemia trait  This condition causes no health problems and can be detected only by special genetic testing  Alpha thalassemia trait occurs when two alpha globin genes are missing  This can occur in two ways  The genes may be deleted from the same chromosome, causing the 'cis' type of alpha thalassemia trait  Alternately, they may be deleted from different chromosomes, causing the 'trans' type of alpha thalassemia trait  In both instances, there are no associated health problems, although the trait status may be detected by more routine blood screening 
Hemoglobin H disease results from the deletion of three alpha globin genes, such that there is only one functioning gene  Typically, this can occur when one parent carries the silent alpha thalassemia trait, and the other parent carries the 'cis' type of the alpha thalassemia trait  In this situation, there is a 25% chance for hemoglobin H disease in each of such a couple's children 
Hemoglobin H disease-like symptoms can also be a part of a unique condition called alpha thalassemia mental retardation syndrome  Alpha thalassemia mental retardation syndrome can be caused by a deletion of a significant amount of chromosome 16, affecting the alpha globin genes  This is usually not inherited, but rather occurs sporadically in the affected individual  Affected individuals have mild hemoglobin H disease, mild-to-moderate mental retardation, and characteristic facial features  This syndrome can also occur as a sex-linked form in which a mutation is inherited in a particular gene on the X-chromosome  This gene influences alpha globin production, as well as various other developmental processes  Individuals affected with this form of the syndrome tend to have more severe mental retardation, delayed development, nearly absent speech, characteristic facial features, and genital-urinary abnormalities  The remaining discussion will focus only on aspects of hemoglobin H disease 
Alpha thalassemia major results from the deletion of all four alpha globin genes, such that there are no functioning alpha globin genes  This can occur when both parents carry the 'cis' type of the alpha thalassemia trait  In this situation, there is a 25% chance for alpha thalassemia major in each of such a couple's children 
Beta thalassemia major is characterized by severe anemia that can begin months after birth  In the United States and other developed countries beta thalassemia is identified and treated early and effectively  Therefore, the following discussion of symptoms applies primarily to affected individuals in the past and unfortunately in some underdeveloped countries now  If untreated, beta thalassemia major can lead to severe lethargy, paleness, and delays in growth and development  The body attempts to compensate by producing more blood, which is made inside the bones in the marrow  However, this is ineffective without the needed genetic instructions to make enough functioning hemoglobin  Instead, obvious bone expansion and changes occur that cause characteristic facial and other changes in appearance, as well as increased risk of fractures  Severe anemia taxes other organs in the body—such as the heart, spleen, and liver—which must work harder than usual  This can lead to heart failure, as well as enlargement and other problems of the liver and spleen  When untreated, beta thalassemia major generally results in childhood death, usually due to heart failure  In 2004, the first known heart attack associated with beta thalassemia major was reported  Fortunately, in developed countries diagnosis is usually made early, often before symptoms have begun  This allows for treatment with blood transfusion therapy, which can prevent most of the complications of the severe anemia caused by beta thalassemia major  Individuals with beta thalassemia intermedia have a more moderate anemia that may only require treatment with transfusion intermittently, such as when infections occur and stress the body  As a person with beta thalassemia intermedia gets older, however, the need for blood transfusions may increase to the point that they are required on a regular basis  When this occurs their disease becomes more similar to beta thalassemia major  Other genetic and environmental factors can influence the course of the disease as well  For example, co-inheritance of one or two alpha thalassemia mutations can tend to ameliorate some of the symptoms of beta thalassemia disease, which result in part from an imbalance in the amount of alpha- and beta-globin present in the red blood cells 
Hemoglobin h disease
Absence of three alpha globin genes causes an imbalance of alpha and beta globin proteins in the red blood cells  The excess beta globin proteins tend to come together to form hemoglobin H, which is unable to release oxygen to the tissues  In addition, hemoglobin H tends to precipitate out in the cells, causing damage to the red blood cell membrane  When affected individuals are exposed to certain drugs and chemicals known to make the membrane more fragile, the cells are thought to become vulnerable to breakdown in large numbers, a complication called hemolytic anemia  Fever and infection are also considered to be triggers of hemolytic anemia in hemoglobin H disease  This can result in fatigue, paleness, and a yellow discoloration of the skin and whites of eyes called jaundice  Usually, the anemia is mild enough not to require treatment  Severe anemia events may require blood transfusion, however, and are usually accompanied by such other symptoms as dark feces or urine and abdominal or back pain  These events are uncommon in hemoglobin H disease, although they occur more frequently in a more serious type of hemoglobin H disease called hemoglobin H/Constant Spring disease  Individuals effected with this type of hemoglobin H disease are also more likely to have enlargement of and other problems with the spleen 
Alpha thalassemia major
Because alpha globin is a necessary component of all major hemoglobins and some minor hemoglobins, absence of all functioning alpha globin genes leads to serious medical consequences that begin even before birth  Affected fetuses develop severe anemia as early as the first trimester of pregnancy  The placenta, heart, liver, spleen, and adrenal glands may all become enlarged  Fluid can begin collecting throughout the body as early as the start of the second trimester, causing damage to developing tissues and organs  Growth retardation is also common  Affected fetuses usually miscarry or die shortly after birth  In addition, women carrying affected fetuses are at increased risk of developing complications of pregnancy and delivery  Up to 80% of such women develop toxemia, a disturbance of metabolism that can potentially lead to convulsions and coma  Other maternal complications include premature delivery and increased rates of delivery by cesarean section, as well as hemorrhage after delivery 
Thalassemia may be suspected if an individual shows signs that are suggestive of the disease  In all cases, however, laboratory diagnosis is essential to confirm the exact diagnosis and to allow for the provision of accurate genetic counseling about recurrence risks and testing options for parents and affected individuals  Screening is likewise recommended to determine trait status for individuals of high-risk ethnic groups 
The following tests are used to screen for thalassemia disease and/or trait:
hemoglobin electrophoresis with quantitative hemoglobin A2 and hemoglobin F
free erythrocyte-protoporphyrin (or ferritin or other studies of serum iron levels)
A complete blood count will identify low levels of hemoglobin, small red blood cells, and other red blood cell abnormalities that are characteristic of a thalassemia diagnosis  Since thalassemia trait can sometimes be difficult to distinguish from iron deficiency, tests to evaluate iron levels are important  A hemoglobin electrophoresis is a test that can help identify the types and quantities of hemoglobin made by an individual  This test uses an electric field applied across a slab of gel-like material  Hemoglobins migrate through this gel at various rates and to specific locations, depending on their size, shape, and electrical charge  Isoelectric focusing and high-performance liquid chromatography (HPLC) use similar principles to separate hemoglobins and can be used instead of or in various combinations with hemoglobin electrophoresis to determine the types and quantities of hemoglobin present  Hemoglobin electrophoresis results are usually within the normal range for all types of alpha thalassemia  However, hemoglobin A2 levels and sometimes hemoglobin F levels are elevated when beta thalassemia disease or trait is present  Hemoglobin electrophoresis can also detect structurally abnormal hemoglobins that may be co-inherited with a thalassemia trait to cause thalassemia disease (i e , hemoglobin E) or other types of hemoglobin disease (i e , sickle hemoglobin)  Sometimes DNA testing is needed in addition to the above screening tests  This can be performed to help confirm the diagnosis and establish the exact genetic type of thalassemia 
Diagnosis of thalassemia can occur under various circumstances and at various ages  Several states offer thalassemia screening as part of the usual battery of blood tests done for newborns  This allows for early identification and treatment  Thalassemia can be identified before birth through the use of prenatal diagnosis  Chorionic villus sampling (CVS) can be offered as early as 10 weeks of pregnancy and involves removing a sample of the placenta made by the baby and testing the cells  CVS carries a risk of causing a miscarriage that is between 0 5%-1%  Amniocentesis is generally offered between 15 and 22 weeks of pregnancy, but can sometimes be offered earlier  Two to three tablespoons of the fluid surrounding the baby is removed  This fluid contains fetal cells that can be tested  The risk of miscarriage associated with amniocentesis ranges from 0 33-0 5%  Pregnant woman and couples may choose prenatal testing in order to prepare for the birth of a baby that may have thalassemia  Alternately, knowing the diagnosis during pregnancy allows for the option of pregnancy termination  Preimplantation genetic diagnosis (PGD) is a relatively new technique that involves in-vitro fertilization followed by genetic testing of one cell from each developing embryo  Only the embryos unaffected by sickle cell disease are transferred back into the uterus  PGD is currently available on a research basis only and is relatively expensive 
Individuals with beta thalassemia major receive regular blood transfusions, usually on a monthly basis  This helps prevent severe anemia and allows for more normal growth and development  Transfusion therapy does have limitations, however  Individuals can develop reactions to certain proteins in the blood—called a transfusion reaction



ground_truth: The belief entropy decreases more steadily.

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Question: What are the symptoms of alpha thalassemia major?

Read the following text and answer briefly.

Context 2:  This can make locating appropriately matched donor blood more difficult  Although blood supplies in the United States are very safe, particularly relative to the past and to other areas of the world, there remains an increased risk of exposure to such blood-borne infections as hepatitis  Additionally, the body is not able to get rid of the excess iron that accompanies each transfusion  An additional medication called desferoxamine is administered, usually five nights per week over a period of several hours, using an automatic pump that can be used during sleep or taken anywhere the person goes  This medication is able to bind to the excess iron, which can then be eliminated through urine  If desferoxamine is not used regularly or is unavailable, iron overload can develop and cause tissue damage and organ damage and failure  The heart, liver, and endocrine organs are particularly vulnerable  Desferoxamine itself may rarely produce allergic or toxic side effects, including hearing damage  Signs of desferoxamine toxicity are screened for and generally develop in individuals who overuse the medication when body iron levels are sufficiently low  Overall, however, transfusion and desferoxamine therapy have increased the life expectancy of individuals with the most severe types of beta thalassemia major to the 4th or 5th decade  This can be expected to improve with time and increased developments in treatment, as well as for those with more mild forms of the disease 
New treatments offer additional options for some individuals with beta thalassemia major  There are various medications that target the production of red blood cells (i e  erythropoeitin) or fetal hemoglobin (i e  hydroxyurea and butyrate)  Their effectiveness in ameliorating the severity of beta thalassemia is currently being investigated  Another promising new treatment is bone marrow transplantation, in which the bone marrow of an affected individual is replaced with the bone marrow of an unaffected donor  If successful, this treatment can provide a cure  However, there is an approximately 10-15% chance the procedure could be unsuccessful (i e  the thalassemia returns); result in complications (i e  graft-versus-host disease); or result in death  The risk for specific individuals depends on current health status, age, and other factors  Because of the risks involved and the fact that beta thalassemia is a treatable condition, transplant physicians require a brother or sister donor who has an identically matched tissue type, called HLA type  HLA type refers to the unique set of proteins present on each individual's cells, which allows the immune system to recognize "self" from "foreign " HLA type is genetically determined, so there is a 25% chance for two siblings to be a match  Transplant physicians and researchers are also investigating ways to improve the safety and effectiveness of bone marrow transplantation  Using newborn sibling umbilical cord blood—the blood from the placenta that is otherwise discarded after birth but contains cells that can go on to make bone marrow—seems to provide a safer and perhaps more effective source of donor cells  Donors and recipients may not have to be perfect HLA matches for a successful transplant using cord blood cells  Trials are also underway to determine the effectiveness of "partial transplants," in which a safer transplant procedure is used to replace only a percentage of the affected individual's bone marrow  Other possible treatments on the horizon may include gene therapy techniques aimed at increasing the amount of normal hemoglobin the body is able to make 
Hemoglobin H disease is a relatively mild form of thalassemia that may go unrecognized  It is not generally considered a condition that will reduce one's life expectancy  Education is an important part of managing the health of an individual with hemoglobin H disease  It is important to be able to recognize the signs of severe anemia that require medical attention  It is also important to be aware of the medications, chemicals, and other exposures to avoid due to the theoretical risk they pose of causing a severe anemia event  When severe anemia occurs, it is treated with blood transfusion therapy  For individuals with hemoglobin H disease, this is rarely required  For those with the hemoglobin H/Constant Spring form of the disease, the need for transfusions may be intermittent or ongoing, perhaps on a monthly basis and requiring desferoxamine treatment  Individuals with this more severe form of the disease may also have an increased chance of requiring removal of an enlarged and/or overactive spleen 
Anemia — A blood condition in which the level of hemoglobin or the number of red blood cells falls below normal values  Common symptoms include paleness, fatigue, and shortness of breath 
Bilirubin — A yellow pigment that is the end result of hemoglobin breakdown  This pigment is metabolized in the liver and excreted from the body through the bile  Bloodstream levels are normally low; however, extensive red cell destruction leads to excessive bilirubin formation and jaundice 
Bone marrow — A spongy tissue located in the hollow centers of certain bones, such as the skull and hip bones  Bone marrow is the site of blood cell generation 
Bone marrow transplantation — A medical procedure used to treat some diseases that arise from defective blood cell formation in the bone marrow  Healthy bone marrow is extracted from a donor to replace the marrow in an ailing individual  Proteins on the surface of bone marrow cells must be identical or very closely matched between a donor and the recipient 
Desferoxamine — The primary drug used in iron chelation therapy  It aids in counteracting the life-threatening buildup of iron in the body associated with long-term blood transfusions 
Globin — One of the component protein molecules found in hemoglobin  Normal adult hemoglobin has a pair each of alpha-globin and beta-globin molecules 
Heme — The iron-containing molecule in hemoglobin that serves as the site for oxygen binding 
Hemoglobin — Protein-iron compound in the blood that carries oxygen to the cells and carries carbon dioxide away from the cells 
Hemoglobin A — Normal adult hemoglobin that contains a heme molecule, two alpha-globin molecules, and two beta-globin molecules 
Hemoglobin electrophoresis — A laboratory test that separates molecules based on their size, shape, or electrical charge 
Hepatomegaly — An abnormally large liver 
HLA type — Refers to the unique set of proteins called human leukocyte antigens  These proteins are present on each individual's cell and allow the immune system to recognize 'self' from 'foreign'  HLA type is particularly important in organ and tissue transplantation 
Hydroxyurea — A drug that has been shown to induce production of fetal hemoglobin  Fetal hemoglobin has a pair of gamma-globin molecules in place of the typical beta-globins of adult hemoglobin  Higher-than-normal levels of fetal hemoglobin can ameliorate some of the symptoms of thalassemia 
Iron overload — A side effect of frequent blood transfusions in which the body accumulates abnormally high levels of iron  Iron deposits can form in organs, particularly the heart, and cause life-threatening damage 
Jaundice — Yellowing of the skin or eyes due to excess of bilirubin in the blood 
Mutation — A permanent change in the genetic material that may alter a trait or characteristic of an individual, or manifest as disease, and can be transmitted to offspring 
Placenta — The organ responsible for oxygen and nutrition exchange between a pregnant mother and her developing baby 
Red blood cell — Hemoglobin-containing blood cells that transport oxygen from the lungs to tissues  In the tissues, the red blood cells exchange their oxygen for carbon dioxide, which is brought back to the lungs to be exhaled 
Screening — Process through which carriers of a trait may be identified within a population 
Splenomegaly — Enlargement of the spleen 
Because alpha thalassemia major is most often a condition that is fatal in the prenatal or newborn period, treatment has previously been focused on identifying affected pregnancies in order to provide appropriate management to reduce potential maternal complications  Pregnancy termination provides one form of management  Increased prenatal surveillance and early treatment of maternal complications is an approach that is appropriate for mothers who wish to continue their pregnancy with the knowledge that the baby will most likely not survive  In recent years, there have been a handful of infants with this condition who have survived long-term  Most of these infants received experimental treatment including transfusions before birth, early delivery, and even bone marrow transplantation before birth, although the latter procedure has not yet been successful  For those infants that survive to delivery, there seems to be an increased risk of developmental problems and physical effects, particularly heart and genital malformations  Otherwise, their medical outlook is similar to a child with beta thalassemia major, with the important exception that ongoing, life-long blood transfusions begin right at birth 
As discussed above, the prognosis for individuals with the most serious types of thalassemia has improved drastically in the last several years following recent medical advances in transfusion, chemo-, and transplantation therapy  Advances continue and promise to improve the life expectancy and quality of life further for affected individuals 
"First Known Heart Attack Associated With Beta-thalassemia Major Reported " Heart Disease Weekly February 22, 2004: 10 
"Novel Alpha-thalassemia Mutations Identified " Hematology Week January 26, 2004: 19 
Children's Blood Foundation  333 East 38th St , Room 830, New York, NY 10016-2745  (212) 297-4336  cfg@nyh med cornell edu 
Cooley's Anemia Foundation, Inc  129-09 26th Ave  #203, Flushing, NY 11354  (800) 522-7222 or (718) 321-2873  http://www thalassemia org 
March of Dimes Birth Defects Foundation  1275 Mamaroneck Ave , White Plains, NY 10605  (888) 663-4637  resourcecenter@modimes org  http://www modimes org 
National Heart, Lung, and Blood Institute  PO Box 30105, Bethseda, MD 20824-0105  (301) 592-8573  nhlbiinfo@rover nhlbi nih gov  http://www nhlbi nih gov 
National Organization for Rare Disorders (NORD)  PO Box 8923, New Fairfield, CT 06812-8923  (203) 746-6518 or (800) 999-6673  Fax: (203) 746-6481  http://www rarediseases org 
Bojanowski J  "Alpha Thalassemia Major: The Possibility of Long-Term Survival " Pamphlet from the Northern California Comprehensive Thalassemia Center  (1999) 
Children's Hospital Oakland, Northern California Comprehensive Thalassemia Center website  http://www thalassemia com 
Cooley's Anemia Foundation, Inc  website  http://www thalassemia org/gohome html 
Joint Center for Sickle Cell and Thalassemic Disorders website  http://cancer mgh harvard edu/medOnc/sickle htm 
[thal″ah-se´me-ah]
a heterogeneous group of hereditary hemolytic anemias marked by a decreased rate of synthesis of one or more hemoglobin polypeptide chains, classified according to the chain involved (α, β, δ); the two major categories are α- and β-thalassemia 
α-thalassemia (alpha-thalassemia) that caused by diminished synthesis of alpha chains of hemoglobin  The homozygous form is incompatible with life, the stillborn infant displaying severe hydrops fetalis  The heterozygous form may be asymptomatic or marked by mild anemia 
β-thalassemia (beta-thalassemia) that caused by diminished synthesis of beta chains of hemoglobin  The homozygous form is called t  major and the heterozygous form is called t  minor 
thalassemia ma´jor the homozygous form of β-thalassemia, in which hemoglobin A is completely absent; it appears in the newborn period and is marked by hemolytic, hypochromic, microcytic anemia; hepatosplenomegaly; skeletal deformation; mongoloid facies; and cardiac enlargement 
thalassemia mi´nor the heterozygous form of β-thalassemia; it is usually asymptomatic, but there may be mild anemia 
sickle cell–thalassemia a hereditary anemia involving simultaneous heterozygosity for hemoglobin S and thalassemia 
thal·as·se·mi·a
, thalassanemia (thal'ă-sē'mē-ă, thă-las-ă-nē'mē-ă),
Any of a group of inherited disorders of hemoglobin metabolism in which there is impaired synthesis of one or more of the polypeptide chains of globin; several genetic types exist, and the corresponding clinical picture may vary from barely detectable hematologic abnormality to severe and fatal anemia 
[G  thalassa, the sea, + haima, blood]
/thal·as·se·mia/ (thal″ah-se´me-ah) a heterogeneous group of hereditary hemolytic anemias marked by a decreased rate of synthesis of one or more hemoglobin polypeptide chains, classified according to the chain involved (α, β, δ); the two major categories are α- and β-thalassemia 
α-thalassemia that caused by diminished synthesis of alpha chains of hemoglobin  The homozygous form is incompatible with life, the stillborn infant displaying severe hydrops fetalis  The heterozygous form may be asymptomatic or marked by mild anemia 
β-thalassemia that caused by diminished synthesis of beta chains of hemoglobin  The homozygous form is called t  major and the heterozygous form is called t  minor 
thalassemia ma´jor the homozygous form of &#x03B2;, in which hemoglobin A is completely absent; it appears in the newborn period and is marked by hemolytic, hypochromic, microcytic anemia, hepatosplenomegaly, skeletal deformation, mongoloid facies, and cardiac enlargement 
thalassemia mi´nor the heterozygous form of &#x03B2;, usually asymptomatic, although there is sometimes mild anemia 
(thăl′ə-sē′mē-ə)
An inherited form of anemia occurring chiefly among people of Mediterranean descent, caused by faulty synthesis of part of the hemoglobin molecule  Also called Mediterranean anemia 
thal′as·se′mic adj 
[thal′əsē′mē·ə]
Etymology: Gk, thalassa, sea, a + haima, without blood
production and hemolytic anemia characterized by microcytic, hypochromic red blood cells  Thalassemia is caused by inherited deficiency of alpha- or beta-globin synthesis  See also hemochromatosis, hemosiderosis 
Beta thalassemia, clinical thalassemia, Cooley's anemia, Mediterranean anemia, thalassemia major Hematology A group of genetic diseases by underproduction of hemoglobin due to mutations in the beta globin gene, which is more common in Mediterraneans Heredity Parents are carriers–heterozygotes; one in 4 children is homozygous for the mutation and thus has full-blown disease Clinical See Anemia  Cf Sickle cell anemia 
α-thalassemia
Hemoglobin Barts Hematology An inherited condition caused by a defect in the synthesis of the Hb α chain; Hb Barts hemoglobinopathy is characterized by the presence of 4 gamma chains; it is more common in southeast Asians; the most severe form of alpha thalassemia causes stillbirth due to hydrops fetalis Heredity Parents are carriers–heterozygotes; one in 4 children is homozygous for the mutation and thus has full-blown disease Clinical Pallor, fatiguability, FTT, fever, infections, diarrhea Management Transfusions
Thalassemia major Hematology A hemoglobinopathy caused by a defect in the synthesis of Hb β chain Clinical Pallor, fatigability, FTT, fever due to infections, diarrhea, bone deformities, hepatosplenomegaly Management Transfusions, but iron overload can damage the heart, liver, and endocrine systems, ergo iron chelation–early use of deferiprone, deferoxamine ↓ transfusion-related iron overload and may protect against DM, cardiac disease, early death
δ-thalassemia
Hematology A condition characterized by a defect of Hb A2–α2δ2; because Hb A2 comprises only 3% of the circulating Hb, even its complete absence; δ-thalassemia has little clinical or hematologic impact
γ-thalassemia
Hematology A condition characterized by a defect of gamma–γ Hb chains found in Hb F–α2γ2; because Hb F is present primarily in the fetus and newborns, it is rarely seen outside of the neonatal period, but may cause transient neonatal hemolytic anemia 
, thalassanemia (thal'ă-sē'mē-ă, -ă-să-nē'mē-ă)
Any of a group of inherited disorders of hemoglobin metabolism in which there is impaired synthesis of one or more of the polypeptide chains of globin; several genetic types exist, and the corresponding clinical picture may vary from barely detectable hematologic abnormality to severe and fatal anemia  People of Mediterranean, extraction are more often affected than others by this type of anemia 
Synonym(s): thalassaemia, thalassanaemia 
Any of a group of inherited disorders of hemoglobin metabolism with impaired synthesis of one or more polypeptide chains of globin; several genetic types exist 
<a href="https://medical-dictionary thefreedictionary com/Thalassaemia+minor">thalassemia</a>
Barts hemoglobin
beta hemoglobinopathy
beta-delta thalassemia
beta-thalassaemia
Bite Cell
black gallstone
I know of a couple, totally unrelated and unbeknownst to them, who are silent carriers of Thalassaemia minor 
Pakistan: Genetic factor: All in the genes
But, unfortunately, when one person with thalassaemia minor carrier happens to marry another with the same diagnosis, there is a strong possibility that their child would be thalassaemia major, as happened in the case of Taneja 
' My life depends upon a monthly blood transfusion '
0] thalassaemia demonstrates variable severity, ranging from a condition similar to [beta] thalassaemia minor to something approaching thalassaemia major 
A retrospective review of homozygous haemoglobin E patients
Thal, Alan P 
thalame
thalamencephalic
thalamencephalon
thalamic
thalamic fasciculus
thalamic nucleus
thalamic pain syndrome
thalamic peduncle
thalamic radiation
thalamo-
thalamocoele
thalamocortical
thalamocortical fibers
thalamogeniculate artery
thalamolenticular
thalamoperforating artery
thalamostriate radiation
thalamotuberal artery
Thalassaemia minor
thalassaemiaor Cooley's disease
thalassemic facies
thalasso-
Thalassobacter
Thalassobacter utilis
thalassoplankton
thalassoposia
thalidomide neuropathy
Thalidomider
thallium poisoning
Thalarctos
THALAS
Thalasaemia
Thalassaemia Association of Malaysia
thalassaemia major
Thalassaemias
thalassaemic
thalassanaemia
Thalassemia Action Group
Thalassemia Clinical Research Network
thalassemia syndrome
Context 3: What is this game all about? (short version) Do you like the board game RISK®? Then chances are you’ll like QONQR  Your job is to join a faction and help your faction (team) take over the world  QONQR is an artificial intelligence that appeared on the Internet  We don’t know where it came from, or its purpose, but we know it is powerful  The Legion want to destroy QONQR because they believe it will enslave and exterminate humanity  The Swarm believe QONQR will advance the human race, and we should protect it  The Faceless don’t care, and want to steal the technology for their own uses  Pick a side, recruit your friends, and help your faction capture the towns and cities in which you live, work, and play  What is this game all about? (long version) Right now an invisible war is raging all around you  At stake: the Past, Present, and Future  A rogue Artificial Intelligence has been detected infiltrating the world’s networked infrastructure  Initial hacking of the source code has revealed incredible new technology  It is not certain whether this AI seeks to enhance or destroy humanity  It is only certain that it is here, and that is has a name: QONQR Those who first detected the presence of QONQR on the global networks have argued fiercely over its intentions  They have split into viciously rival Factions, each co-opting the known QONQR technologies for their own ends  Even now the Factions battle over the entire globe seeking to gather resources and prepare for the coming power struggle  Whether you accept it or not, the war is here  Your survival, prosperity, and even glory depend on the choices you make and the skill you demonstrate from this point forward  You will be asked to join one of three Factions  The choice should not be made lightly  Your Faction Alignment will define your place in the war over QONQR  THE LEGION unite under the shared goals of destroying QONQR and saving humanity by crushing the nascent AI before it can mature  They are led by AGENT SUNDAY, a former commander of the NSA's Turing Task Force which has been valiantly stamping out dangerous AIs for years  THE SWARM are convinced that QONQR promises an era of unprecedented technological advancement and human prosperity  Nanobot weaponry expert KIMYO NAGUMO leads this faction in the battle to defend QONQR and assemble its future tech, accelerating humanity's path into the future  THE FACELESS are a loosely organized faction of militant hackers who want QONQR's technology for their own ends, but want to prevent the unavoidable nightmare of human slavery they believe it portends  When they choose to communicate, they do so through an anonymous vigilante who goes by the name PROMETHEUS    What do I do first? Create a base, then launch  Launch nanobots until your fingers hurt  How do I create a base? On iOS there is a Base icon in the menu bar  For Windows Phone, you will find a bases button on the home screen  These take you to the Base Screen where you can see how many bases you have available to you  Once you create a base, be sure harvest often by returning to the list of your bases  You can see how full each base is by checking the fill percentage icon  Bases stop collecting once they are full  What is the point of creating bases and harvesting resources? You need bases to earn money  Bases collect rare elements over time which you can then harvest for your faction in exchange for qredits  Qredits can be used to purchase ordinance (like nanomissiles) and upgrades which will help you capture and hold battle zones more easily  What do you mean, “launch nanobots?” Nanobots are the invisible soldiers generated by your device (which has been transformed into “Scope” by advanced QONQR technology)  Nanobots fight for control of the battle zones around you   From the home screen click “Current Zone”  Once you have selected your zone, you will be able to deploy nanobots there   Initially, you are just a level 1 recruit  You are only going to get a small attack formation with a limited range   Other solders have to practice with rifles before they get tanks; you are no different  Once you prove your mettle, you’ll get access to bigger weapons  Soon you’ll be lobbing missiles hundreds of miles  How do I capture a zone? If you play for the Legion and are launching nanobots into a zone controlled by the Swarm, you will capture the zone for the Legion as soon as you have destroyed enough of the enemy that your nonbots outnumber theirs  If you are the person who causes the zone to change control to the Legion, you will be listed as the Capturer of the Zone  The Person with the most nanobots in the zone is the zone leader  What is my current zone? How do you know? Your current zone is determined by your proximity to the nearest zone center  So, while you might be inside the governmental boundaries of a city, your scope (phone) could tell you your current zone is a different city, if that city’s center is closer  So I just keep deploying? Yes, in the early levels of the game, just keep deploying and harvesting your bases  You will earn XP (experience points) proving your loyalty to your Faction 	You will level up quickly and soon have access to many more options  So all I can do is just attack? You only get assault bots to start  They are the most basic type of nanobot formation  As you level up you will get many more options, including bots that are good at defense, energy attacks, long-range deployments, formations that will buff the shields for all your faction-mates in the zone, and many more  My faction already controls this zone should I still attack? Yes, assault bots won’t attack your friends  You will increase the bot counts for that zone, which will deter opponents  Attack bots can defend your zone; they just aren’t very good at it  As you level up you will unlock defensive formations that are better for deploying if your faction already holds the zone  I’ll never knock out my enemy at this rate! In the first few levels your impact might feel minimal, but every deployment helps you gain experience  It won’t take long to level up if you keep at it  If you are unlucky enough to be in a zone where someone has already built up huge defenses, you may be in for a long fight  But remember, your scope moves with you  Go explore the world and find softer targets  Once you level up, it won’t seem like a toy gun against a battleship  You’ll get your big weapons once you prove yourself  We have already seen operatives brag about taking down 1,000,000 nanobots in just a couple days  Nothing is impossible  How do I attack a different zone? As you level up you will unlock more and stronger formations  Those new formations will have range  While at the early levels you can only attack nearby zones, as you level up your attacks will go 10-20 miles (roughly 15-30 Km) and you will eventually gain access to nanomissiles that can go hundreds of miles  What should I buy in the depot first? The smallest thing to buy is a refresh  We give you some of these as you level up so you can try them out  Refreshes will refill (or partially fill depending on the size of your tank) your bot bar or your energy bar  But after that, it depends on your goals  There is much to choose from  Do you want to be able to deploy more nanobots on every launch? Do you want to boost your offensive or defensive bots? Do you want to be able to launch missiles into towns far away? All of these things are possible  Look through the depot and see what you like  Most of the time you will need to buy an upgrade before you can buy the ordinance  For example, missiles are fairly inexpensive, but you need to buy the MX Rack Missile Launcher before you can launch them  Buy the upgrade first  What is the difference between qredits and cubes in the depot? A qredit (aka: credit, which looks like the child of a Q and € ) is the type of currency you earn in the game by harvesting your bases  Cubes (aka: power cubes) are purchased with real money in the Bank section of the Depot  We want everyone to be able to do everything in the game for free, by earning qredits, but for those who want to move a bit faster, you can purchase cubes to speed things along  Purchasing cubes is how QONQR makes money  We very much appreciate your support  Every purchase you make helps us to keep making improvements in the game  Future enhancements will enable you to earn cubes in game  Why can’t I create another base? Additional bases become available as you level up  At the start, you will get a new base every 5 levels  If you don’t have any more bases available to build, you will need to level up  If you have a base available, but aren’t allowed to use it, it is because you already have a base in that zone  You can only have one base in a zone  Get yourself to another zone, then create your base there  My bases are collecting credits at different rates  Your bases collect resources faster if your faction controls the zone  Do your best to either put your bases in zones you can control by yourself, or find zones with strong players in the same faction and put your bases there to maximize your credit collection  The game says I’m in a town that doesn’t exist  QONQR tracks almost 3 million battle zones of varying strategic value in 250 countries  Sometimes those zones include locations that haven’t existed for over 100 years  That’s pretty cool if you ask us  If you find a zone that looks like a duplicate or is just plain wrong, however, let us know on the forums under “Zone Corrections”  How do I move my current position on the map? You might need to take a car, bus, plane or train depending on which zone you are trying to get to, but if you want to move on the map, you need to move in the real world  QONQR is a location-based game, which means you play where you are  However we don't want to make you move to play, we want you to plan when you move  QONQR goes with you as you move through the daily activities in your life  Where do I find the Strategy Guide? Here: http://community qonqr com/index php?/topic/1191-the-official-qonqr-strategy-guide/ How do I win? That is for you to decide  There is still much to discover  We don’t even know if QONQR is good or evil  Why is it here? What is its purpose? Help your faction further its goals and unlock all the secrets of QONQR!
Congratulations to the Swarm on their overwhelming victory in Atlantis in May 2015 -- taking and retaining all Atlantis zones from beginning to end is hard to argue with -- most convincing -- well done Swarm!
Rumor has it that the Duggers have 20 scopes  Some families really do have a wife and ten kids    Ha Anyways     Multi scoping is generally not encouraged, usually if you mention that you do it on the forums or in groupme your not going to be a very liked person, even within your own faction  What tends to happen is if you start multiscoping then your enemies start doing it, then you get into a war where ever person has 6 phones and nobody is happy  I've seen or heard about situations like this in a lot of different locations 
Great job, faceless! It was actually an exciting Atlantis and I prefer it that way  Way to bring your A game 
You know what we need in this game? Nano-Nukes!!
Attention (insert faction here), We, the (insert faction here) are tired of the way you constantly (circle one)   A  Cube rage us B  Bully us with numbers C  Talk mean to us It hurts our feelings because (circle one)   A  We don't cube B  We don't have as many allies C  We have no sense of humor and/or no backbone Please refrain from participating in the above selected actions for above selected reasons so as the game is enjoyable for (insert faction here)  Regards, (insert name and faction here) There we go   this should streamline the entire complaint process of the forums  Copy and reuse as needed  You're welcome 
Silver, you mentioned in a blog that there are levels beyond 150, is it safe to say there is no level limit anymore or is that for us to discover? Another question, I'm not sure if I'm the only one noticing this but it seems like bot decay doesn't work against Zone Assault bots  I've hit two players I know have been inactive for well over 6 months but my attack had the same effect it did yesterday before the update  However I did notice against Deflection bots I am getting 2x the kill power  Also in response to decontaminatoR  Paid gaming isn't just something for adults  When I was 13 the best options for handheld gaming was GameBoy or GameGear and the games at the time cost anywhere between $29-$39 dollars  I had a paper route to pay for my games  So, no offense, but you can afford $0 99 for a game  You don't even need a paper route, just check under your couch cushions and I'm sure you'll find a few quarters 
I want to start by thanking Faceless  This round of Atlantis, Legion and Faceless were doubled in sized and probably spending by Swarm  I contacted some great players from the other side and put together a nonaggression pact, this pact was one of the most impressive agreements I've seen in the more than two years of playing  Hundreds of people worldwide stuck to this agreement and put past feelings behind us  It was awesome to see both sides stick so closely to each other in fighting against Swarm  I want to really thank everyone who showed honor by standing behind me and the faceless command when we suggested that, the people who really gave it a chance and then most importantly, to all the players who honored it  Faceless, thank you very much! We stood no chance of winning without you! The battle came down to literally one launch in one of three zones  I'd say that with that being said everyone fought incredibly hard, so I want to give Swarm the respect they deserve  You guys really show out and play to win  Good game, 2 against 1 is not easy, no matter how large your crew is  And Legion, we had many late, late nights, many very long days  You guys killed it this month! We didn't take home a trophy, but I would say we all have something to be proud of! The other leaders who helped me coordinate everything were awesome! So many great people kept everything moving forward 24 hours a day for the whole week  Thank you to everyone who gave it your all for the whole week even when we saw that Swarm had 4x our bots at the end of just one day  Many people would have given up, but we held in and **** near won! I've won Atlantis battles with Faceless and with Legion but I will say, nothing was as fun or incredible as this round! You guys are fantastic and I can't wait to do it all again next month! Hopefully we have more Legion and Faceless show up for the next round, but I know that even if we don't, we will figure out a way, just as warriors do  PEW! PEW! PEW!
I must start with an announcement: Camels are not the only animal in the middle east  You have overused it already  It's saddens me that anyone would still find it funny  Get a bit of originality  For anyone not wanting to read all this drivel, skip to the end (hint: Bold stuff)  At what point have I bullied anyone? When was the last aggressive or threatening message you or any of your members received from me? Never  Legion and Swarm (in the UK) have teamed up because Faceless are dominating in London  That makes sense  It's a three sided fight and if one force becomes too powerful, the other two can join forces to try and take them down  But: We are dominating in the London area while your alliance is attacking players outside of that area  Then you expect me to sit back and do nothing  You are specifically using me as an excuse for why you have teamed up but then you're attacking players outside of my reach, sometimes with Europe involved  If that is not reason enough to attack you then I'm not sure what is  You lot cube, multiscope and have multi faction accounts and still complain  I don't complain about anything you do  Play the way you want to, ill do the same  I am never rude to anyone, always polite no matter what the message is, never brag about what I do, can do or have done, never threaten anyone, try and keep in touch with the few swarm or legion who are civilised to me, listen to any message form any side and if I can help in any way, I try my best to  Formed agreements with enemy (that I didn't need to) that ended up slapping me in the face  I have even in the past taken the time to find out who some of the younger players are so I know to avoid them  When I'm in a different country I try and find who the bullies are  Those players who threaten and brag and laugh at others  Those are my targets (if they exist in those areas)  I don't see how anyone can think I'm a bully  Is it your money? Its none of your business how I spend it  Either way your numbers are way off  700 dollars a day? Did you just decide to blindly strike the number pad to come up with that figure? Best part of one of your posts is saying that the devs should worry about my welfare  What concerns you about me spending my money? Maybe I'll self harm due to overspending? I wont have enough to buy food because I bought too many cubes? I don't understand what they are supposed to worry about  I have issues? At what point did you deduce this oh mighty psychologist? Wait a minute are you my bank account manager? What do you know about how much I can or cant afford? Random guy spends money on something he enjoys  The end  Told you last time to give up on all the drama but I guess thank you for the concern  You play to make me spend more? And? What do you think that accomplishes? In fact how do you even make me spend? You don't even attack me  You sulk when I'm in the UK and when I fly out and you find out, you call in Europe to help you take an zone or two  As they say, whatever floats your boat  As for Atlantis: Please try again  I quit Atlantis when we were winning  I have on occasion involved myself after I was asked to help out but on the whole I give it a miss  The last time (months ago) was the last 10 minutes of Atlantis and Legion fought hard  We lost  I was not the only Faceless player to quit Atlantis  Quite a few of us thought it lasted too long and had too many zones to fight over  I hear the duration has been reduced  You can't honestly believe I changed my sleeping pattern for the game  I was in California for a month  I was jet lagged  My sleeping pattern was a bit off when I got back  You're not even accurate about when I deploy  Pay attention  You should know this by now: I play as and when I want, sometimes every 20 minutes and sometimes I do long stretches and sometimes I'm busy and don't deploy for hours  You wont always win, and nor will I  Try and get satisfaction form at least trying to win or putting up a good fight  About the limit on cubing  Please  I suggested that last year  Twice  Unfortunately multiscoping is allowed and so prevalent that it kind of ruins the idea  These are the facts: YOU and YOUR side threatened Faceless members who support London  One of the members threatened is actually London based  What do you expect him to do while his city is under attacked? A few of your members don't know when to keep quiet  They sent messages to us threatening specific players and telling them their zones will be dropped just because they have helped London  Basically if they help London then they get their zones wiped  And you have the cheek to call me a bully? We stood up to your members specifically because they were trying to bully  That is the reason we went strong months ago and took those big zones  How is this me bullying you? This is me answering your threats  I didn't attack those zones "just because i can", it's just because I should  Because of your threats  You can blame your members for the loss of those 2 or 3 big zones  These are the basics: You attack one of our zones  We look at the list of attackers and pick one of the players who deployed the most, find a zone of his or hers and attack it  We don't need to justify our attacks with "because there are Faceless players within 30 miles"  What, every time we attack a zone we need to send some letter explaining why? You attack us or we attack you, for any reason  That's the game  When some of you were cheating and you could not win you complained, when you cube and lose you complain, when you invite all of Europe to attack and win you still complain  I just think you like to make a fuss  Last words (for now): You think I attack zones as a means of getting attention? I get enough of it form your threads  The only attention seeker here is you with your victim attitude and pity us posts 
I've had some very angry emails today from a couple users who are upset their rival achieved the ability to switch factions freely having played for one of the factions for only 1 hour  I've been accused of doing favors, changing the rules, and various other backhanded deals  It appears it comes down reading the rules  You do not have to play for every faction for 60 days in order to earn free switching status  Here is a common scenario many players have used to achieve free switching status and avoiding playing for one faction they despise  1  Start with Swarm 2  Switch to Legion (earn Spy) play for 60 days 3  Switch back to Swarm (earn Double Agent) play for 60 days 4  Switch to Faceless (earn Mercenary) immediately switch back to Swarm or Legion Below is the complete text on the switch nanobots screen  It is the same text that has been there from Day 1 with the exception of the level 100 rules that went into place earlier this year, where you could switch as much as you want before level 100 , but those switches don't count towards the medals  This text has been part of this description since Jan 15, 2013  "Players that earn all three spy awards, may once again switch factions at any time as they could during the training levels 1 through 99 " Prior to Jan 15, the text said this  "Players that earn all three awards may be given the opportunity to switch factions more quickly in future updates (contact support for more information)" I pulled that right out of source control, which includes the entire change history  Here is the complete text from this page  http://portal qonqr    r/SwitchFaction WARNING: Defection has consequences! Self-destruct will be initiated on all your nanobots  Without the self-destruct, you would be required to battle against your former self to regain control of your zones  You will lose the capture and leadership of any zones you currently hold  Lifetime captures will be unaffected  If you are still completing the training levels and have not reached Level 100, you may switch as often as you like to find the faction that suits you best  Once you have reached Level 100 switching factions has rewards, but also has additional consequences beyond the self-destruct of all your nanobots  Defection will usually result in a demotion in rank  This is accomplished through awards with negative rank points  Those awards are: Spy - First switch to an opposing faction (-20 points) Double Agent - Return to a faction from which you had previously defected (-20 points) Mercenary - Become a member of all three factions (-20 points) Other Faction Change Details: You may not switch factions again until at least 60 days have passed since your last faction switch  Defection point penalties are applied only once per award Players that earn all three spy awards, may once again switch factions at any time as they could during the training levels 1 through 99  The decision to switch factions is one that must be made with strong determination  Nanobots cannot be reanimated once destroyed  You will retain your earned experience, level, formations, qredits, cubes, and upgrades  However, as far as your zones go, you will be starting over 
   has got to be one of the funniest moments I've seen in qonqr yet lol 
The **** change operation was a success!
As a relatively new player for faceless in a region dominated by swarm i can understand the OP  However, judging from the numbers i see here on a regular basis i think you are asking a bit much  My idea would be the opposite approach  Why not add a weapon with extremely short range, let's say like 5km that acts like a bomb and make it much stronk? That would add some serious home advantage  Or alternativley make attack formations lose power over range (exclude nanos and plasma)  Maybe something like that would allow newcomers to at least get a foothold in their homezones  It's just an idea, maybe i overlooked something?
This is by design  Some day it is possible (I said someday) we could offer skins for your scope  So we will need a uniform color scheme  You can tell the formation families based on the shape of the box  Trapezoid is attack, diamond is defense, and octagon is support  It will take some time to get comfortable with the change 
Geophysical based game  Anyways, probably not a bad idea but, considering the issues with the three platforms and the development of blue for those platforms, I doubt the resources are available for development on a new platform  Seen the blog? Its Qonqr meets wheel of fortune!
I am happy to announce that today I both completed the training and captured my first zone 
^THIS so now that qonqr has been thoroughly funded, can we have blue now? Or is that not happening still lol 
Atleast I am not legion and there for we can have this intelligent discussion rather than just compete over who has the best words XD ohhhhh someone bring the bill to legion cuz someone just served them extra double order of stir fried SNAPPPPPP If the devs wont make zone dueling for us I hope out there somewhere are those who would empty a zone and challenge one on one to a local battle  I'd like to see the transcript of deployments made / moves made as well that would be neat I think such events would be cool  I suppose if people give up on atlantis as it works now they can schedule their own tournements in empty atlantis zones   have a team clear the zone   put 1 vs 1 or teams vs teams   like fisticuffs challenges   find out what these warriors are really made of!
@Qonqrd everyone you know must face palm every time you make a post  Its embarrassing  Mega cubers or whatever you want to call them are not great for the opposing team surrounding them but are great for the game itself (money) and for the team they are part of  Multiscopers are not not great for the opposing team surrounding them and bring nothing to the game but are great for the team they are part of  Both have a negative impact on enemy teams/players but only one benefits the game itself  Both can make people want to quit out of frustration  And that's not great for the game  @OP unlimited refresh is over powered  Its frustrating to fight against a ridiculous amount of refreshes  Unfortunately i dont see anything changing unless this game gets a lot more people playing  More people might mean more money for the company from various sources  More money from various players might mean they can limit the players who spend a ton and still generate a healthy income  The main issue i see with limiting refreshes is someone multiscoping and spending money  He now has two, three, four accounts to refresh with and gets the advantage  Its tricky 
ey dun new ho to yet it uff 
Yet you complain almost everyday here, on your website, Twitter, and YouTube channel that the game needs to change because cubing has such an impact 
It was fun  Swarm had me scared at first, but it turned into kind of a bullying match between us and legion  Last hour became p obvious which way it was gonna go  Legion rly stepped up their game in the end there, respect 
We are investigating this  Here is what we know: Several of the accounts used the same password  Most of the accounts belonged to people who knew each other personally  The accounts were all switched from the same IP Addresses  The person who logged in, got into each account on the first attempt, so they knew the password for each account  What you should know: QONQR never stores passwords, not even in the logs  Passwords are hashed (one way encrypted) and can never be decrypted When you authenticate to our servers, we hash the password you gave us and compare it to the encrypted password in the database to see if they match  Access to our database in the could is restricted tightly and we are confident no one breached the system  What you should do: Don't use the same password as other people you play with  Don't share your password with anyone 
I heard all the French players fled to the UK after one German player accidentally shot a single missile into France 
Most factions now use GroupMe or Line as their means of communication, the forums are too slow as a means of communication and insecure for specific faction conversations  Think of the forums are more of a gaming information resource rather than a means of communication  Contact the top players of your faction in the leader boards of your state and they will likely point you in the right direction to chatting with your local faction  The developers are also building some sort of new chat system into the game, we don't know much about it but apparently beta testing for the chat will be happening very soon (next couple of weeks) according to their timelines 
A way to honor the dead? Nah, how bout a way to dishonor the dead 
Could just build it up and retain their capture  Remember Bizzy, staq to the heavens 
I just read this entire thread  I am now tuckered 
Does anyone know if Bot Booster has an effect on Seekers and how much dmg they do to attacking players? Also on the topic of seekers, does the amount of skeers in a battlefield have any effect on how much damage they do?
Interactive map of real-time zone captures 
You know that is something I didn't factor in there  Time  The player who can consistently and constantly launch wins against the guy who casually picks up the phone on occasion or has to work away from a cell phone for 8 hours  Good point  And yes I can't argue skill doesn't factor in, it just seems like less of a factor than other games is all 
I cant see why a closed forum, open only to registered Qonqr accounts, cant be used  **** spammers!
Gotta love synclock! I suspect linjin has a problem  Maybe the dvs should look into it 
No, Naamah   I clearly understood what you were trying to convey  I'll even go as far as to agree that what your facing now is, while fully allowed and deemed completely acceptable by the developers, unbalanced and wrong  However  the imbalance isn't in the game and isn't something that, from a business standpoint, is likely to be regulated  The game is fair  the advantages are provided to all players  It's the players themselves that throw the balance into chaos because, as you've said, not everyone can afford spending several thousand bucks a year in only one game  Truthfully, in my opinion, the moment you admitted to buying cubes yourself your complaint became silly  because I'm sure there's a player out there, who has bought NO cubes, who can make this same complaint about you that you are making about others here  I know these things because I've read them so   many   times in this forum  There was likely a time, ages ago when I was a young Massune, that I even posted a few myself  That was the purpose of my post  I was poking fun at addition of yet another cuber/bully/trash talk complaint on the forum  It wasn't directed at your personal plight so much as the idea that someone, yet again, finds it necessary to lobby for a spending cap on the only real way for this game to make money  As to your specific problem  you, like all those that have raised this topic before you, have few options to rectify the issue  Here are a few that seem to have worked for others  fight harder, recruit better, spend less time complaining and more time organizing, budget for more cubes or quit  I'd rather not see you opt for the latter  but to each their own 
I agree, we should find a way to honor the dead, but I don't think keeping their towers infinitely is necessarily the solution  The game must go on  I'm pretty sure the point of bot decay was to clear the game of inactive player bots so that new players can have a chance to rise up, not to dishonor the bots of dead players 
The following are frequently asked questions about the new server update (so far) It still says Training Complete on my iPhone  -	Download the update from iTunes It still says Training Complete on my Android  -	Sorry, Android will not be updated again until the QONQR Blue beta is released My XP per launch keeps going down -	This is XP throttling and is intended to limit the ability for people to leve1 from 1 to 100 in a single day through heavy cubing  The XP throttle was introduced with the original version of QONQR in 2012,and the throttle formula is the same for levels above 100  The throttle resets at midnight UTC every day  How do I buy the Bot Regeneration Accelerator? -	Currently the Bot Regen Accelerator can only be purchased through http://portal qonqr com  Go to the Depot and review your scope upgrades  The new QONQR Blue clients will allow for this purchase to be made in the app using your mobile billing  I don’t have a PayPal account -	For users interested in purchasing the Regen upgrade, but who do not have a PayPal account, PayPal does give you the option to checkout using your billing information without creating an account  PayPal is not allowed in my country, or I don’t have a credit or debit card -	Please contact support@QONQR com for alternate options Is Bot Regen Accelerator counted as part of the 100% scope upgrades? -	Yes, but there is a bug that does not increase scope upgrade percent when you purchase this upgrade, that will be fixed in the coming days  For all other questions, please read the 7 blog posts prior to 7/29/2015 for information on what was included in the update today 
Bye Fack, its been a pleasure being allied and against you 
The two big issues that are both killing the game slowly and keeping it from growing exponentially are cube injustice and new player ramp  The game obviously also needs to provide a consistent and growing revenue stream as well  I think Silver needs to rethink how revenue is generated if he is going to address cube injustice and new player ramp  For revenue generation I would suggest a model that doesn't give a significant combat advantages  Download and play for free from level 0-99 Pay small monthly fee to get full functionality or play for free at 50% of offensive/defensive funtionality Still buy cubes, but cubes are used for following: - Credit Boost: harvest more credits for a period of time - Range Extension: ability to use standard attack/defense formations at extended ranges - Base Share: get 100% credit attainment even in bases owned by another faction - Purchase additional ordinance - Zone Name Change - ability to customize zone names  "Breggland" - Faction Change with Bots - pay for the ability to keep up to 50% of your bots with faction change - Experience Boost: %increase in experienced gained while leveling - Other: anything that helps grow a player or provides enjoyment, but doesn't tip the battle capability of a scope  New Player Ramp/Integration into Game - Offer paid immediate ramp package: one price to become 100 with full upgrades - Like the changes in Blue - Create new zones in Metro areas that only 0-99 level can launch into, with statewide ranges Understand that catering to those who have money and like to use it for an advantage is a good business model and for those people it might be ok to offer very expensive options: - Shield generators: temporary energy shield that adds X% increase to defense or stops X% of damage - EMP's: turns Absorbs off for X minutes  Does not destroy, just turns off - Chain Lighting: Does damage across multiple players in a zone From a development standpoint I have no idea what is possible, easy or hard, but the general idea is to make the playing field more fair for the standard player while maintaining and growing a business revenue stream 
You need to come to the Northeast US  We handle our business like no other 



ground_truth: Severe anemia that begins even before birth.

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Context 4:  The magnetic field is applied in the film plane  The inset shows the temperature dependence of a sample grown at 130$^{\circ}$C and annealed at 650$^{\circ}$C for 15 minutes  After annealing, the magnetic signal mostly arises from Ge$_{3}$Mn$_{5}$ clusters  (b) ZFC-FC measurements performed on Ge$_{0 93}$Mn$_{0 07}$ samples for different growth temperatures  The in-plane applied field is 0 015 T  The ZFC peak at low temperature ($\leq$150 K) can be attributed to the superparamagnetic nanocolumns  This peak widens and shifts towards high blocking temperatures when increasing growth temperature  The second peak above 150 K in the ZFC curve which increases with increasing growth temperature is attributed to superparamagnetic Ge$_{3}$Mn$_{5}$ clusters  The increasing ZFC-FC irreversibility at $\approx$ 300 K is due to the increasing contribution from large ferromagnetic Ge$_{3}$Mn$_{5}$ clusters  The nanocolumns signal completely vanishes after annealing at 650$^{\circ}$C for 15 minutes }
\label{fig7}
\end{figure}

In Fig  7a, the saturation magnetization at 2 Tesla in $\mu_{B}$/Mn of Ge$_{1-x}$Mn$_{x}$ films with 7 \% of Mn is plotted as a function of temperature for different growth temperatures ranging from $T_{g}$=90$^{\circ}$C up to 160$^{\circ}$C  The inset shows the temperature dependence of the magnetization at 2 Tesla after annealing at 650$^{\circ}$C during 15 minutes  Figure 7b displays the corresponding Zero Field Cooled - Field Cooled (ZFC-FC) curves recorded at 0 015 Tesla  In the ZFC-FC procedure, the sample is first cooled down to 5 K in zero magnetic field and the susceptibility is subsequently recorded at 0 015 Tesla while increasing the temperature up to 400 K (ZFC curve)  Then, the susceptibility is recorded under the same magnetic field while decreasing the temperature down to 5 K (FC curve)  Three different regimes can be clearly distinguished  \\
For $T_{g}\leq$120$^{\circ}$C, the temperature dependence of the saturation magnetization remains nearly the same while increasing growth temperature  The overall magnetic signal vanishing above 200 K is attributed to the nanocolumns whereas the increasing signal below 50 K originates from diluted Mn atoms in the surrounding matrix  The Mn concentration dependence of the saturation magnetization is displayed in figure 8  For the lowest Mn concentration (4 \%), the contribution from diluted Mn atoms is very high and drops sharply for higher Mn concentrations (7 \%, 9 \% and 11 3 \%)  Therefore the fraction of Mn atoms in the diluted matrix decreases with Mn concentration probably because Mn atoms are more and more incorporated in the nanocolumns  In parallel, the Curie temperature of nanocolumns increases with the Mn concentration reaching 170 K for 11 3 \% of Mn  This behavior may be related to different Mn compositions and to the increasing diameter of nanocolumns (from 1 8 nm to 2 8 nm) as discussed in section \ref{structural} 

\begin{figure}[htb]
\center
   \includegraphics[width= 7\linewidth]{ /fig8 eps}
    \caption{Temperature dependence of the saturation magnetization (in $\mu_{B}$/Mn) of Ge$_{1-x}$Mn$_{x}$ films grown at 100$^{\circ}$C plotted for different Mn concentrations: 4 1 \%; 7 \%; 8 9 \% and 11 3 \% }
\label{fig8}
\end{figure}

ZFC-FC measurements show that the nanocolumns are superparamagnetic  The magnetic signal from the diluted Mn atoms in the matrix is too weak to be detected in susceptibility measurements at low temperature  In samples containing 4 \% of Mn, ZFC and FC curves superimpose down to low temperatures  As we do not observe hysteresis loops at low temperature, we believe that at this Mn concentration nanocolumns are  superparamagnetic in the whole temperature range and the blocking temperature cannot be measured  For higher Mn contents, the ZFC curve exhibits a very narrow peak with a maximum at the blocking temperature of 15 K whatever the Mn concentration and growth temperature (see Fig  7b)  Therefore the anisotropy barrier distribution is narrow and assuming that nanocolumns have the same magnetic anisotropy, this is a consequence of the very narrow size distribution of the nanocolumns as observed by TEM  To probe the anisotropy barrier distribution, we have performed ZFC-FC measurements but instead of warming the sample up to 400 K, we stopped at a lower temperature $T_{0}$  

\begin{figure}[htb]
\center
   \includegraphics[width= 6\linewidth]{ /fig9 eps}
\caption{Schematic drawing of the anisotropy barrier distribution n($E_{B}$) of superparamagnetic nanostructures  If magnetic anisotropy does not depend on the particle size, this distribution exactly reflects their magnetic size distribution  In this drawing the blocking temperature ($T_{B}$) corresponds to the distribution maximum  At a given temperature $T_{0}$ such that 25$k_{B}T_{0}$ falls into the anisotropy barrier distribution, the largest nanostructures with an anisotropy energy larger than 25$k_{B}T_{0}$ are blocked whereas the others are superparamagnetic }
\label{fig9}
\end{figure}

If this temperature falls into the anisotropy barrier distribution as depicted in Fig  9, the FC curve deviates from the ZFC curve  Indeed the smallest nanostructures have become superparamagnetic at $T_{0}$ and when decreasing again the temperature, their magnetization freezes along a direction close to the magnetic field and the FC susceptibility is higher than the ZFC susceptibility  Therefore any irreversibility in this procedure points at the presence of superparamagnetic nanostructures  The results are given in Fig  10a  ZFC and FC curves clearly superimpose up to $T_{0}$=250 K thus the nanocolumns are superparamagnetic up to their Curie temperature and no Ge$_{3}$Mn$_{5}$ clusters could be detected  Moreover for low $T_{0}$ values, a peak appears at low temperature in FC curves which evidences strong antiferromagnetic interactions between the nanocolumns \cite{Chan00} 

\begin{figure}[htb]
\center
    \includegraphics[width= 35\linewidth]{ /fig10a eps}
    \includegraphics[width= 63\linewidth]{ /fig10b eps}
\caption{(a) ZFC-FC measurements performed on a Ge$_{0 887}$Mn$_{0 113}$ sample grown at 115$^{\circ}$C  The in-plane applied field is 0 015 T  Magnetization was recorded up to different T$_{0}$ temperatures: 30 K, 50 K, 100 K, 150 K, 200 K and 250 K  Curves are shifted up for more clarity  (b) ZFC-FC curves for in-plane and out-of-plane applied fields (0 015 T) }
\label{fig10}
\end{figure}

In order to derive the magnetic size and anisotropy of the Mn-rich nanocolumns embedded in the Ge matrix, we have fitted the inverse normalized in-plane (resp  out-of-plane) susceptibility: $\chi_{\parallel}^{-1}$ (resp  $\chi_{\perp}^{-1}$)  The corresponding experimental ZFC-FC curves are reported in Fig  10b  Since susceptibility measurements are performed at low field (0 015 T), the matrix magnetic signal remains negligible  In order to normalize susceptibility data, we need to divide the magnetic moment by the saturated magnetic moment recorded at 5 T  However the matrix magnetic signal becomes very strong at 5 T and low temperature so that we need to subtract it from the saturated magnetic moment using a simple Curie function  From Fig  10b, we can conclude that nanocolumns are isotropic  Therefore to fit experimental data we use the following expression well suited for isotropic systems or cubic anisotropy: $\chi_{\parallel}^{-1}= \chi_{\perp}^{-1}\approx 3k_{B}T/M(T)+\mu_{0}H_{eff}(T)$  $k_{B}$ is the Boltzmann constant, $M=M_{s}v$ is the magnetic moment of a single-domain nanostructure (macrospin approximation) where $M_{s}$ is its magnetization and $v$ its volume  The in-plane magnetic field is applied along $[110]$ or $[-110]$ crystal axes  Since the nanostructures Curie temperature does not exceed 170 K, the temperature dependence of the saturation magnetization is also accounted for by writting $M(T)$  Antiferromagnetic interactions between nanostructures are also considered by adding an effective field estimated in the mean field approximation \cite{Fruc02}: $\mu_{0}H_{eff}(T)$ 
The only fitting parameters are the maximum magnetic moment (\textit{i e } at low temperature) per nanostructure: $M$ (in Bohr magnetons $\mu_{B}$) and the maximum interaction field (\textit{i e } at low temperature): $\mu_{0}H_{eff}$ 

\begin{figure}[htb]
\center
   \includegraphics[width= 7\linewidth]{ /fig11 eps}
\caption{Temperature dependence of the inverse in-plane (open circles) and out-of-plane (open squares) normalized susceptibilities of a Ge$_{0 887}$Mn$_{0 113}$ sample grown at 115$^{\circ}$C  Fits were performed assuming isotropic nanostructures or cubic anisotropy  Dashed line is for in-plane susceptibility and solid line for out-of-plane susceptibility }
\label{fig11}
\end{figure}

In Fig  11, the best fits lead to $M\approx$1250 $\mu_{B}$ and $\mu_{0}H_{eff}\approx$102 mT for in-plane susceptibility and $M\approx$1600 $\mu_{B}$ and $\mu_{0}H_{eff}\approx$98 mT for out-of-plane susceptibility  It gives an average magnetic moment of 1425 $\mu_{B}$ per column and an effective interaction field of 100 mT  Using this magnetic moment and its temperature dependence, magnetization curves could be fitted using a Langevin function and $M(H/T)$ curves superimpose for $T<$100 K  However, from the saturated magnetic moment of the columns and their density (35000 $\rm{\mu m}^{-2}$), we find almost 6000 $\mu_{B}$ per column  Therefore, for low growth temperatures, we need to assume that nanocolumns are actually made of almost four independent elongated magnetic nanostructures  The effective field for antiferromagnetic interactions between nanostructures estimated from the susceptibility fits is at least one order of magnitude larger than what is expected from pure magnetostatic coupling  This difference may be due to either an additional antiferromagnetic coupling through the matrix which origin remains unexplained or to the mean field approximation which is no more valid in this strong coupling regime  As for magnetic anisotropy, the nanostructures behave as isotropic magnetic systems or exhibit a cubic magnetic anisotropy  First we can confirm that nanostructures are not amorphous otherwise shape anisotropy would dominate leading to out-of-plane anisotropy  We can also rule out a random distribution of magnetic easy axes since the nanostructures are clearly crystallized in the diamond structure and would exhibit at least a cubic anisotropy (except if the random distribution of Mn atoms within the nanostructures can yield random easy axes)  Since the nanostructures are in strong in-plane compression (their lattice parameter is larger than the matrix one), the cubic symmetry of the diamond structure is broken and magnetic cubic anisotropy is thus unlikely  We rather believe that out-of-plane shape anisotropy is nearly compensated by in-plane magnetoelastic anisotropy due to compression leading to a \textit{pseudo} cubic anisotropy  From the blocking temperature (15 K) and the magnetic volume of the nanostructures , we can derive their magnetic anisotropy constant using $Kv=25k_{B}T_{B}$: K$\approx$10 kJ m$^{-3}$ which is of the same order of magnitude as shape anisotropy 

\begin{figure}[htb]
\center
    \includegraphics[width= 35\linewidth]{ /fig12a eps}
    \includegraphics[width= 63\linewidth]{ /fig12b eps} 
\caption{(a) ZFC-FC measurements performed on a Ge$_{0 93}$Mn$_{0 07}$ sample grown at 122$^{\circ}$C  The in-plane applied field is 0 015 T  Magnetization was recorded up to different T$_{0}$ temperatures: 50 K, 100 K, 150 K, 200 K and 250 K  Curves are shifted up for more clarity  (b) ZFC-FC curves for in-plane and out-of-plane applied fields  (0 015 T) }
\label{fig12}
\end{figure}

For growth temperatures $T_{g}\geq$120$^{\circ}$C and Mn concentrations $\geq$ 7 \%, samples exhibit a magnetic signal above 200 K corresponding to Ge$_{3}$Mn$_{5}$ clusters (see Fig  7a)  As we can see, SQUID measurements are much more sensitive to the presence of Ge$_{3}$Mn$_{5}$ clusters, even at low concentration, than TEM and x-ray diffraction used in section \ref{structural}  We also observe a sharp transition in the ZFC curve (see Fig  7b, Fig  12a and 12b): the peak becomes very large and is shifted towards high blocking temperatures (the signal is maximum at $T=$23 K)  This can be easily understood as a magnetic percolation of the four independent nanostructures obtained at low growth temperatures into a single magnetic nanocolumn  Therefore the magnetic volume increases sharply as well as blocking temperatures  At the same time, the size distribution widens as observed in TEM  In Fig  12a, we have performed ZFC-FC measurements at different $T_{0}$ temperatures  The ZFC-FC irreversibility is observed up to the Curie temperature of $\approx$120 K meaning that a fraction of nanocolumns is ferromagnetic (\textit{i e } $T_{B}\geq T_{C}$) 
In Fig  12b, in-plane and out-of-plane ZFC curves nearly superimpose for $T\leq$150 K due to the isotropic magnetic behavior of the nanocolumns: in-plane magnetoelastic anisotropy is still compensating out-of-plane shape anisotropy  Moreover the magnetic signal above 150 K corresponding to Ge$_{3}$Mn$_{5}$ clusters that start to form in this growth temperature range is strongly anisotropic  This perpendicular anisotropy confirms the epitaxial relation: (0002) Ge$_{3}$Mn$_{5}$ $\parallel$ (002) Ge discussed in Ref \cite{Bihl06}  The magnetic easy axis of the clusters lies along the hexagonal $c$-axis which is perpendicular to the film plane 

\begin{figure}[ht]
\center
   \includegraphics[width= 35\linewidth]{ /fig13a eps}
   \includegraphics[width= 63\linewidth]{ /fig13b eps} 
\caption{(a) ZFC-FC measurements performed on a Ge$_{0 887}$Mn$_{0 113}$ sample grown at 145$^{\circ}$C  The in-plane applied field is 0 015 T  Magnetization was recorded up to different T$_{0}$ temperatures: 50 K, 100 K, 150 K, 200 K, 250 K and 300 K  Curves are shifted up for more clarity  (b) ZFC-FC curves for in-plane and out-of-plane applied fields (0 015 T) }
\label{fig13}
\end{figure}

For growth temperatures $T_{g}\geq$145$^{\circ}$C the cluster magnetic signal dominates (Fig  13b)  Superparamagnetic nanostructures are investigated performing ZFC-FC measurements at different $T_{0}$ temperatures (Fig  13a)  The first ZFC peak at low temperature \textit{i e } $\leq$ 150 K is attributed to  low-$T_{C}$ nanocolumns ($T_{C}\approx$130 K)  This peak is wider than for lower growth temperatures and its maximum is further shifted up to 30 K  These results are in agreement with TEM observations: increasing $T_{g}$ leads to larger nanocolumns (\textit{i e } higher blocking temperatures) and wider size distributions  ZFC-FC irreversibility is observed up to the Curie temperature due to the presence of ferromagnetic columns  The second peak above 180 K in the ZFC curve is attributed to Ge$_{3}$Mn$_{5}$ clusters and the corresponding ZFC-FC irreversibility persisting up to 300 K means that some clusters are ferromagnetic  We clearly evidence the out-of-plane anisotropy of Ge$_{3}$Mn$_{5}$ clusters and the isotropic magnetic behavior of nanocolumns (Fig  13b)  In this growth temperature range, we have also investigated the Mn concentration dependence of magnetic properties  

\begin{figure}[ht]
\center
    \includegraphics[width= 49\linewidth]{ /fig14a eps}
    \includegraphics[width= 49\linewidth]{ /fig14b eps} 
\caption{Temperature dependence of the saturation magnetization (in $\mu_{B}$/Mn) of Ge$_{1-x}$Mn$_{x}$ films grown at 150$^{\circ}$C plotted for different Mn concentrations: 2 3 \%; 4 \%; 7 \%; 9 \%; 11 3 \%  (b) ZFC-FC measurements performed on Ge$_{1-x}$Mn$_{x}$ films grown at 150$^{\circ}$C  The in-plane applied field is 0 025 T for 2 3 \% and 4 \% and 0 015 T for 8 \% and 11 3 \%  }
\label{fig14}
\end{figure}

In Fig  14a, for low Mn concentrations (2 3 \% and 4 \%) the contribution from diluted Mn atoms in the germanium matrix to the saturation magnetization is very high and nearly vanishes for higher Mn concentrations (7 \%, 9 \% and 13 \%) as observed for low growth temperatures  Above 7 \%, the magnetic signal mainly comes from nanocolumns and Ge$_{3}$Mn$_{5}$ clusters  We can derive more information from ZFC-FC measurements (Fig  14b)  Indeed, for 2 3 \% of Mn, ZFC and FC curves nearly superimpose down to low temperature meaning that nanocolumns are superparamagnetic in the whole temperature range  Moreover the weak irreversibility arising at 300 K  means that some Ge$_{3}$Mn$_{5}$ clusters have already formed in the samples even at very low Mn concentrations  For 4 \% of Mn, we can observe a peak with a maximum at the blocking temperature (12 K) in the ZFC curve  We can also derive the Curie temperature of nanocolumns: $\approx$45 K  The irresversibility arising at 300 K still comes from Ge$_{3}$Mn$_{5}$ clusters  Increasing the Mn concentration above 7 \% leads to: higher blocking temperatures (20 K and 30 K) due to larger nanocolumns and wider ZFC peaks due to wider size distributions in agreement with TEM observations (see Fig  3a)  Curie temperatures also increase (110 K and 130 K) as well as the contribution from Ge$_{3}$Mn$_{5}$ clusters \\
Finally when increasing $T_{g}$ above 160$^{\circ}$C, the nanocolumns magnetic signal vanishes and only Ge$_{3}$Mn$_{5}$ clusters and diluted Mn atoms coexist  The overall magnetic signal becomes comparable to the one measured on annealed samples in which only Ge$_{3}$Mn$_{5}$ clusters are observed by TEM (see Fig  7a) \\
The magnetic properties of high-$T_{C}$ nanocolumns obtained for $T_{g}$ close to 130$^{\circ}$C are discussed in detail in Ref \cite{Jame06} \\
In conclusion, at low growth temperatures ($T_{g}\leq$120$^{\circ}$C), nanocolumns are made of almost 4 independent elongated magnetic nanostructures  For $T_{g}\geq$120$^{\circ}$C, these independent nanostructures percolate into a single nanocolumn sharply leading to higher blocking temperatures  Increasing $T_{g}$ leads to larger columns with a wider size distribution as evidenced by ZFC-FC measurements and given by TEM observations  In parallel, some Ge$_{3}$Mn$_{5}$ clusters start to form and their contribution increases when increasing $T_{g}$  Results on magnetic anisotropy seems counter-intuitive  Indeed Ge$_{3}$Mn$_{5}$ clusters exhibit strong out-of-plane anisotropy whereas nanocolumns which are highly elongated magnetic structures are almost isotropic  This effect is probably due to compensating in-plane magnetoelastic coupling (due to the columns compression) and out-of-plane shape anisotropy  

\section{Conclusion}

In this paper, we have investigated the structural and magnetic properties of thin Ge$_{1-x}$Mn$_{x}$ films grown by low temperature molecular beam epitaxy  A wide range of growth temperatures and Mn concentrations have been explored  All the samples contain Mn-rich nanocolumns as a consequence of 2D-spinodal decomposition  However their size, crystalline structure and magnetic properties depend on growth temperature and Mn concentration  For low growth temperatures, nanocolumns are very small (their diameter ranges between 1 8 nm for 1 3 \% of Mn and 2 8 nm for 11 3 \% of Mn), their Curie temperature is rather low ($<$ 170 K) and they behave as almost four uncorrelated superparamagnetic nanostructures  Increasing Mn concentration leads to higher columns densities while diameters remain nearly unchanged  For higher growth temperatures, the nanocolumns mean diameter increases and their size distribution widens  Moreover the 4 independent magnetic nanostructures percolate into a single magnetic nanocolumn  Some columns are ferromagnetic even if Curie temperatures remain quite low  In this regime, increasing Mn concentration leads to larger columns while their density remains nearly the same  In parallel, Ge$_{3}$Mn$_{5}$ nanoclusters start to form in the film with their $c$-axis perpendicular to the film plane  In both temperature regimes, the Mn incorporation mechanism in the nanocolumns and/or in the matrix changes above 5 \% of Mn and nanocolumns exhibit an isotropic magnetic behaviour due to the competing effects of out-of-plane shape anisotropy and in-plane magnetoelastic coupling  Finally for a narrow range of growth temperatures around 130$^{\circ}$C, nanocolumns exhibit Curie temperatures higher than 400 K  Our goal is now to investigate the crystalline structure inside the nanocolumns, in particular the position of Mn atoms in the distorted diamond structure, which is essential to understand magnetic and future transport properties in Ge$_{1-x}$Mn$_{x}$ films 

\section{Aknowledgements}
The authors would like to thank Dr  F  Rieutord for grazing incidence x-ray diffraction measurements performed on the GMT station of BM32 beamline at the European Synchrotron Radiation Facility 





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