Miracle-dz/UniFAR-FTUs huggingface dataset:
Human Brain Connectomics : Networks , Techniques , and Applications

T he human brain is organized into a collection of interacting networks with specialized functions to support various cognitive functions. The word “connectome” first burst on the scene with the work of Sporns et al. [1], who urged brain researchers to advance a comprehensive structural description of the elements and connections forming the human brain. An increasing body of evidence indicates that schizophrenia, multiple sclerosis, and autism exhibit abnormal brain connections. Changes in connectivity also appear to occur as a consequence of neuron degeneration, either from natural aging or diseases such as Alzheimer’s disease. A connectome is hence fundamentally important for understanding brain growth, aging, and abnormality. At the micro level, the brain elements consist of single neurons, the amount of which often treads the realm of hundreds of billions, and possible connections between them numbering in the order of 10. At a more macro (and more manageable) level, the brain is parcellated into a number of regions, where each region accounts for the activity and coactivity of a population of neurons. The colossal task of constructing a connectome calls for powerful tools for handling the vast amount of information given by advanced imaging techniques. In this article, we provide an overview of the fundamental concepts involved, the necessary techniques, and applications to date.
Dynamic Mirror-Symmetry Breaking in Bicontinuous Cubic Phases**

Chiral segregation of enantiomers or chiral conformers of achiral molecules during self-assembly in well-ordered crystalline superstructures has fascinated chemists since Pasteur. Here we report spontaneous mirror-symmetry breaking in cubic phases formed by achiral multichain-terminated diphenyl-2,2′-bithiophenes. It was found that stochastic symmetry breaking is a general phenomenon observed in bicontinuous cubic liquid crystal phases of achiral rod-like compounds. In all compounds studied the ${{\it Im}\bar 3m}$ cubic phase is always chiral, while the ${Ia\bar 3d}$ phase is achiral. These intriguing observations are explained by propagation of homochiral helical twist across the entire networks through helix matching at network junctions. In the ${Ia\bar 3d}$ phase the opposing chiralities of the two networks cancel, but not so in the three-networks ${{\it Im}\bar 3m}$ phase. The high twist in the ${{\it Im}\bar 3m}$ phase explains its previously unrecognized chirality, as well as the origin of this complex structure and the transitions between the different cubic phases.
Alias-Suppressed Oscillators Based on Differentiated Polynomial Waveforms

An efficient approach to the generation of classical synthesizer waveforms with reduced aliasing is proposed. This paper introduces two new classes of polynomial waveforms that can be differentiated one or more times to obtain an improved version of the sampled sawtooth and triangular signals. The differentiated polynomial waveforms (DPW) extend the previous differentiated parabolic wave method to higher polynomial orders, providing improved alias-suppression. Suitable polynomials of order higher than two can be derived either by analytically integrating a previous lower order polynomial or by solving the polynomial coefficients directly from a set of equations based on constraints. We also show how rectangular waveforms can be easily produced by differentiating a triangular signal. Bandlimited impulse trains can be obtained by differentiating the sawtooth or the rectangular signal. An objective evaluation using masking and hearing threshold models shows that a fourth-order DPW method is perceptually alias-free over the whole register of the grand piano. The proposed methods are applicable in digital implementations of subtractive sound synthesis.
The effect of demographic and spatial variability on epidemics: A comparison between Beijing, Delhi, and Los Angeles

A social network is a critical infrastructure for the propagation of an infectious disease in a population. It is important to study the structural properties of the social network for identifying feasible public health interventions that can effectively contain a potential epidemic outbreak. In this work, we focus on flu-like diseases and corresponding people-people social contact networks. We study such social infrastructures of three cities: Los Angeles, USA, Beijing, China and Delhi, India. These contact networks are different due to different construction methodologies and the fact that the populations inherently have very different demographic structures and activity patterns. We compare them in terms of static structural properties (such as clustering coefficient, degree distribution), as well as disease dynamics and efficacy of intervention (e.g., school closure). The comparison between synthetic populations and social contact networks from different regions of the world can provide valuable insight on creating a global synthetic population and social infrastructure for studying public health problems.
DEVELOPMENTAL DECOUPLING OF ALTERNATIVE PHENOTYPES: INSIGHTS FROM THE TRANSCRIPTOMES OF HORN‐POLYPHENIC BEETLES

Developmental mechanisms play an important role in determining the costs, limits, and evolutionary consequences of phenotypic plasticity. One issue central to these claims is the hypothesis of developmental decoupling, where alternate morphs result from evolutionarily independent developmental pathways. We address this assumption through a microarray study that tests whether differences in gene expression between alternate morphs are as divergent as those between sexes, a classic example of developmental decoupling. We then examine whether genes with morph‐biased expression are less conserved than genes with shared expression between morphs, as predicted if developmental decoupling relaxes pleiotropic constraints on divergence. We focus on the developing horns and brains of two species of horned beetles with impressive sexual‐ and morph‐dimorphism in the expression of horns and fighting behavior. We find that patterns of gene expression were as divergent between morphs as they were between sexes. However, overall patterns of gene expression were also highly correlated across morphs and sexes. Morph‐biased genes were more evolutionarily divergent, suggesting a role of relaxed pleiotropic constraints or relaxed selection. Together these results suggest that alternate morphs are to some extent developmentally decoupled, and that this decoupling has significant evolutionary consequences. However, alternative morphs may not be as developmentally decoupled as sometimes assumed and such hypotheses of development should be revisited and refined.
Dark Matter

Rotation Curve of Galaxy How do we measure the amount of mass in the Universe? We measure gravity, indirectly by measuring motion and apply Newton's law of gravity. The orbital period of the Sun around the Galaxy gives us a mean mass for the amount of material inside the Sun's orbit. But a detailed plot of the orbital speed of the Galaxy as a function of radius reveals the distribution of mass within the Galaxy. The simplest type of rotation is wheel rotation shown below.
An Extension of MATLAB to Continuous Functions and Operators

An object-oriented MATLAB system is described for performing numerical linear algebra on continuous functions and operators rather than the usual discrete vectors and matrices. About eighty MATLAB functions from plot and sum to svd and cond have been overloaded so that one can work with our "chebfun" objects using almost exactly the usual MATLAB syntax. All functions live on [-1,1] and are represented by values at sufficiently many Chebyshev points for the polynomial interpolant to be accurate to close to machine precision. Each of our overloaded operations raises questions about the proper generalization of familiar notions to the continuous context and about appropriate methods of interpolation, differentiation, integration, zerofinding, or transforms. Applications in approximation theory and numerical analysis are explored, and possible extensions for more substantial problems of scientific computing are mentioned.
On spectral representation of coalgebras and Hopf algebroids

In this paper we establish a duality between etale Lie groupoids and a class of non-necessarily commutative algebras with a Hopf algebroid structure. For any etale Lie groupoid G over a manifold M, the groupoid algebra C_c(G) of smooth functions with compact support on G has a natural coalgebra structure over C_c(M) which makes it into a Hopf algebroid. Conversely, for any Hopf algebroid A over C_c(M) we construct the associated spectral etale Lie groupoid G_sp(A) over M such that G_sp(C_c(G)) is naturally isomorphic to G. Both these constructions are functorial, and C_c is fully faithful left adjoint to G_sp. We give explicit conditions under which a Hopf algebroid is isomorphic to the Hopf algebroid C_c(G) of an etale Lie groupoid G. We also demonstrate that an analogous duality exists between sheaves on M and a class of coalgebras over C_c(M).
Decision, Risk and Operations Working Papers Series Dynamic Leadtime Management in Supply Chains Dynamic Leadtime Management in Supply Chains

One way to hedge against random fluctuations of demand in supply chains is to keep inventories at various points in the chain. Another is to actually modify the leadtimes in the system dynamically. Working with multiple suppliers, using multiple transportation options, having the option to expedite certain processes, or having different possible routes for a unit to go through the supply chain are all examples of having flexibility in the supply chain leadtimes. In this paper, we study a serial inventory system with complete leadtime flexibility. For expositional purposes, we use a terminology that corresponds to making shipment (routing) decisions in the supply chain, however, the model can represent many different types of leadtime flexibility, such as the ones described above. In particular, we allow the option of shipping units from any stage in the supply chain to any downstream stage. This option gives the manager an additional flexibility that can be utilized as the uncertain demand is revealed. The shipments incur origin-destination dependent costs. Under a certain supermodularity assumption on the shipment costs, we show that optimal policies can be characterized as extended echelon base stock policies, which is a natural generalization of the well known echelon base stock policies.
RecBench

Traditionally, recommender systems have been "hand-built", implemented as custom applications hard-wired to a particular recommendation task. Recently, the database community has begun exploring alternative DBMS-based recommender system architectures, whereby a database both stores the recommender system data (e.g., ratings data and the derived recommender models) and generates recommendations using SQL queries. In this paper, we present a comprehensive experimental comparison of both architectures. We define a set of benchmark tasks based on the needs of a typical recommender-powered e-commerce site. We then evaluate the performance of the "hand-built" MultiLens recommender application against two DBMS-based implementations: an unmodified DBMS and RecStore, a DBMS modified to improve efficiency in incremental recommender model updates. We employ two non-trivial data sets in our study: the 10 million rating MovieLens data, and the 100 million rating data set used in the Netflix Challenge. This study is the first of its kind, and our findings reveal an interesting trade-off: "hand-built" recommenders exhibit superior performance in model-building and pure recommendation tasks, while DBMS-based recommenders are superior at more complex recommendation tasks such as providing filtered recommendations and blending text-search with recommendation prediction scores.
Semi-Supervised Classification by Low Density Separation

We believe that the cluster assumption is key to successful semi-supervised learning. Based on this, we propose three semi-supervised algorithms: 1. deriving graph-based distances that emphazise low density regions between clusters, followed by training a standard SVM; 2. optimizing the Transductive SVM objective function, which places the decision boundary in low density regions, by gradient descent; 3. combining the ﬂrst two to make maximum use of the cluster assumption. We compare with state of the art algorithms and demonstrate superior accuracy for the latter two methods.
Optimization of multiclass queuing networks: polyhedral and nonlinear characterizations of achievable performance

We consider open and closed multiclass queueing networks, with Poisson arrivals (for open networks), exponentially distributed class dependent service times and class dependent deterministic or probabilistic routing. The performance objective is to minimize, over all sequencing and routing policies, a weighted sum of the expected response times of different classes. Using a powerful technique involving quadratic or higher order potential functions, we propose methods for deriving polyhedral and nonlinear sets that contain the set of achievable response times under stable and preemptive scheduling policies. By optimizing over these sets, we obtain lower bounds on achievable performance. In the special case of single station networks (multiclass queues and Klimov's model) and homogeneous multiclass networks, the polyhedron derived is exactly equal to the achievable region. Consequently, the proposed method can be viewed as the natural extension of conservation laws to multiclass queueing networks. We apply the same approach to closed networks to obtain upper bounds on the optimal throughput. We check the tightness of our bounds by simulating heuristic policies and we find that the first order approximation of our method is at least as good as simulation-based existing methods. In terms of computational complexity and in contrast to simulation-based existing methods, the calculation of our first order bounds consists of solving a linear programming problem with a number of variables and constraints that is polynomial (quadratic) in the number of classes in the network. The ith order approximation leads to a convex programming problem in dimension O(Ri'+ ), where R is the number of classes in the network, and can be solved efficiently using techniques from semidefinite programming.
Black Spots' in Capital Structure Studies: The Case of Non-Existing Debt

This study focuses on what can be characterized as “black spots” in the existing studies the selection issue, which is manifested in the fact that a nontrivial number of companies occasionally do not have any debt on their balance sheet. The problem of zero debt is akin to truncated and censored regression models, which are useful when the dependent variable is observed in some ranges but not in others. We find strong evidence that the results of the target adjustment studies of capital structure, which use fitted values of debt ratios, can be potentially biased due to failure to correct for censoring due to zero-leverage observations. This paper also looks at the issue of dynamic properties of capital structure choice and the persistence in the capital structure choice and examines the effect of the 2008 global financial crisis on Russian firms’ capital structure choice.
Short circuit current calculation of non full measured distribution network based on modified power flow algorithm

According to the characteristics of non full measured distribution network, a short circuit current calculation method based on modified power flow algorithm is proposed. It uses measured voltages to initialize the voltages of all nodes and introduces the static voltage characteristic model to decide the power of all loads, through the forward and backward substitution calculation of voltages, the voltages of all nodes in normal state are obtained. Then, base on the results of power flow calculation and the parameters of short circuit fault, to establish the node voltage Eq. of fault system, the short circuit current can be calculated by solving the Eq. From the example of a 15 nodes non full measured system, the calculation results of four kind short circuit faults are very similar to the results of simulation on the Matlab; this indicates the feasibility and validity of the algorithm.
Hashing for Distributed Data

Recently, hashing based approximate nearest neighbors search has attracted much attention. Extensive centralized hashing algorithms have been proposed and achieved promising performance. However, due to the large scale of many applications, the data is often stored or even collected in a distributed manner. Learning hash functions by aggregating all the data into a fusion center is infeasible because of the prohibitively expensive communication and computation overhead. In this paper, we develop a novel hashing model to learn hash functions in a distributed setting. We cast a centralized hashing model as a set of subproblems with consensus constraints. We find these subproblems can be analytically solved in parallel on the distributed compute nodes. Since no training data is transmitted across the nodes in the learning process, the communication cost of our model is independent to the data size. Extensive experiments on several large scale datasets containing up to 100 million samples demonstrate the efficacy of our method.
Coupling conditions for the 3 x 3 Euler system

This paper is devoted to the extension to the full $3\times3$ Euler system of the basic analytical properties of the equations governing a fluid flowing in a duct with varying section. First, we consider the Cauchy problem for a pipeline consisting of 2 ducts joined at a junction. Then, this result is extended to more complex pipes. A key assumption in these theorems is the boundedness of the total variation of the pipe's section. We provide explicit examples to show that this bound is necessary.
Proof-Theoretic Strength of the Stable Marriage Theorem and Other Problems

We study the proof theoretic strength of several infinite versions of finite combinatorial theorem with respect to the standard Reverse Mathematics hierarchy of systems of second order arithmetic. In particular, we study three infinite extensions of the stable marriage theorem of Gale and Shapley. Other theorems studied include some results on partially ordered sets due to Dilworth and to Dushnik and Miller.
Modelli intonativi dell'interrogazione in una varietà di italiano meridionale (Cosenza)

This article describes the question intonation of the regional Italian spoken in Cosenza. A wide corpus of wh-, yes/no and disgiuntive questions is investigated both phonetically and phonologically. The analysis performed points out a serie of significant differences. First of all, the questions considered show a different placement of the nuclear pitch accent. As a rule, the nucleus is placed on the final word of the utterance in yes/no questions, on the verb and sometimes on the wh-word in the wh-questions, on the first lexical option in the alternative questions. Intonation plays a considerable role, however, the absence of prosodic underspecification is significant: the three types of questions share a same biotonal accent, L+H * , and an identical boundary tone, L%. Nevertheless, several variants of the same tonal sequence are observed. They are phonetically characterized by a different peak alignment with respect to the edges of the stressed syllable. We have observed pitch accents in which, on the contrary, both targets are outside of it. The phonological representation of these tones is crucial, since the intonational theory cannot correctly describe them. In the final part of the article, some theoretical interpretations are proposed
NAOSITE : Nagasaki University ' s Academic Output SITE Title Practical implementation of a network-based Stochasticbiochemical simulation system on an FPGA

Stochastic simulation of biochemical reaction networks are widely focused by life scientists to represent stochastic behaviors in cellular processes. Stochastic algorithm has loopand thread-level parallelism, and it is suitable for running on application specific hardware to achieve high performance with low cost. We have implemented and evaluated the FPGAbased stochastic simulator according to theoretical research of the algorithm. This paper introduces an improved architecture for accelerating a stochastic simulation algorithm called the Next Reaction Method. This new architecture has scalability to various size of FPGA. As the result with a middle-range FPGA, 5.38 times higher throughput was obtained compared to software running on a Core 2 Quad Q6600 2.40GHz.
Toward QoI and Energy-Efficiency in Internet-of-Things Sensory Environments

Considering physical sensors with certain sensing capabilities in an Internet-of-Things (IoTs) sensory environment, in this paper, we propose an efficient energy management framework to control the duty cycles of these sensors under quality-of-information (QoI) expectations in a multitask-oriented environment. Contrary to past research efforts, our proposal is transparent and compatible both with the underlying low-layer protocols and diverse applications, and preserving energy-efficiency in the long run without sacrificing the QoI levels attained. In particular, we first introduce the novel concept of QoI-aware sensor-to-task relevancy to explicitly consider the sensing capabilities offered by a sensor to the IoT sensory environments, and QoI requirements required by a task. Second, we propose a novel concept of the critical covering set of any given task in selecting the sensors to service a task over time. Third, energy management decision is made dynamically at runtime, to reach the optimum for long-term application arrivals and departures under the constraint of their service delay. We show a case study to utilize sensors to perform environmental monitoring with a complete set of performance analysis. We further consider the signal propagation and processing latency into the proposal, and provide a thorough analysis on its impact on average measured delay probability.
Object Detection and Avoidance Using Optical Techniques in Uninhabited Aerial Vehicles

Uninhabited Aerial Vehicles will require autonomous collision detection and avoidance capabilities in order to gain wide acceptance and usage in the National Airspace System. The collision detection and avoidance problem is primarily a motion estimation problem, relying on the accuracy of the sensing, processing, actuation and control algorithms onboard the vehicle. Computer vision is a growing field in robotics and autonomous vehicles, and has made vision a feasible technology for object detection in different platforms. In this work, we investigate the feasibility of using optic flow techniques in order to design an altitude hold controller for a fixed wing aircraft flying a nap-of-the-earth trajectory in the presence of variable terrain. Simulated results yield an error of approximately 1.5% in altitude variation for steady level flight (approximately 15 cm) for terrain disturbances of maximum amplitude 4 m. Experimental results obtained from flight data using the UIUC UAV platform are used to validate the controller, and sources of error along with potential improvements in equipment and procedures are cited.