Miracle-dz/UniFAR-FTUs huggingface dataset:
On making robots understand safety: Embedding injury knowledge into control

Enabling robots to safely interact with humans is an essential goal of robotics research. The developments achieved over recent years in mechanical design and control made it possible to have active cooperation between humans and robots in rather complex situations. For this, safe robot behavior even under worst-case situations is crucial and forms also a basis for higher-level decisional aspects. For quantifying what safe behavior really means, the definition of injury, as well as understanding its general dynamics, are essential. This insight can then be applied to design and control robots such that injury due to robot–human impacts is explicitly taken into account. In this paper we approach the problem from a medical injury analysis point of view in order to formulate the relation between robot mass, velocity, impact geometry and resulting injury qualified in medical terms. We transform these insights into processable representations and propose a motion supervisor that utilizes injury knowledge for generating safe robot motions. The algorithm takes into account the reflected inertia, velocity, and geometry at possible impact locations. The proposed framework forms a basis for generating truly safe velocity bounds that explicitly consider the dynamic properties of the manipulator and human injury.
A dynamic slice-resize algorithm for fast H.264/AVC parallel encoder

With development of multi-core system, parallel encoder with fast algorithm is widely used to improve video encoding speed. In this paper, a dynamic slice-resize algorithm is proposed to balance workload and increase encoding speed for slice-level parallel encoder. This algorithm retrieves encoding workload from previous encoded frames and dynamically changes the slice size for the following frames to balance the encoding workload among slices. By applying the proposed algorithm, an average of 21% encoding speed improvement can be achieved for parallel video encoder without loss in objective performance.
Reward Cues in Space: Commonalities and Differences in Neural Coding by Hippocampal and Ventral Striatal Ensembles

Forming place-reward associations critically depends on the integrity of the hippocampal–ventral striatal system. The ventral striatum (VS) receives a strong hippocampal input conveying spatial-contextual information, but it is unclear how this structure integrates this information to invigorate reward-directed behavior. Neuronal ensembles in rat hippocampus (HC) and VS were simultaneously recorded during a conditioning task in which navigation depended on path integration. In contrast to HC, ventral striatal neurons showed low spatial selectivity, but rather coded behavioral task phases toward reaching goal sites. Outcome-predicting cues induced a remapping of firing patterns in the HC, consistent with its role in episodic memory. VS remapped in conjunction with the HC, indicating that remapping can take place in multiple brain regions engaged in the same task. Subsets of ventral striatal neurons showed a “flip” from high activity when cue lights were illuminated to low activity in intertrial intervals, or vice versa. The cues induced an increase in spatial information transmission and sparsity in both structures. These effects were paralleled by an enhanced temporal specificity of ensemble coding and a more accurate reconstruction of the animal's position from population firing patterns. Altogether, the results reveal strong differences in spatial processing between hippocampal area CA1 and VS, but indicate similarities in how discrete cues impact on this processing.
Model of estimation of risk with correction of error of prognosis of volotilnost

In work the problem of construction of model of prognosis of volotilnosti stochastic temporal rows with correction of error is considered, de bene esse got on the current and past informative great number. A model supposes the increase of risk at the increase of degree of volotilnosti. Estimation of volotilnosti row is determined taking into account the error of estimation of model on previous lagah.
Evolving Neural Networks for Pharmaceutical Research

This article presents the application of meta-learning evolutionary artificial neural network (MLEANN) for a pharmaceutical research problem. Designing drugs is a current problem in the pharmaceutical research domain. By designing a drug we mean to choose some variables of drug formulation (inputs), for obtaining optimal characteristics of drug (outputs). To solve such a problem we propose an evolutionary artificial neural network and the performance is compared with a neuro-fuzzy system and an artificial neural network trained using scaled conjugate gradient algorithm. This research used the experimental data obtained from the Laboratory of Pharmaceutical Techniques of the Faculty of Pharmacy in Cluj-Napoca, Romania. Bootstrap techniques were used to generate more samples of data and the number of experimental data is reduced due to the costs and time durations of experimentations. We obtain in this way a better estimation of some drug parameters. Experiment results indicate that the proposed method is efficient
Leveraging Billions of Faces to Overcome Performance Barriers in Unconstrained Face Recognition

We employ the face recognition technology developed in house at face.com to a well accepted benchmark and show that without any tuning we are able to considerably surpass state of the art results. Much of the improvement is concentrated in the high-valued performance point of zero false positive matches, where the obtained recall rate almost doubles the best reported result to date. We discuss the various components and innovations of our system that enable this significant performance gap. These components include extensive utilization of an accurate 3D reconstructed shape model dealing with challenges arising from pose and illumination. In addition, discriminative models based on billions of faces are used in order to overcome aging and facial expression as well as low light and overexposure. Finally, we identify a challenging set of identification queries that might provide useful focus for future research.
Using parallel partitioning strategy to create diversity for ensemble learning

Divide-and-conquer principle is a fashionable strategy to handle large-scale classification problems. However, many works have revealed that generalization ability is decreased by partitioning training set in most cases, because partitioning training set can lead to losing classification information. Aiming to handle this problem, an ensemble learning algorithm was proposed. It used many sets of parallel hyperplanes to partition training set on which each base classifier was trained by the SVM modular network algorithm and all these base classifiers were combined by majority voting strategy when testing. The experimental results on 4 classification problems illustrate that ensemble learning can effectively reduce the descent of generalization ability for the reason of increasing classifier's diversity.
The AGNP-TDM Expert Group Consensus Guidelines: focus on therapeutic monitoring of antidepressants

Therapeutic drug monitoring (TDM) of psychotropic drugs such as antidepressants has been widely introduced for optimization of pharmacotherapy in psychiatric patients. The interdisciplinary TDM group of the Arbeitsgemeinschaft für Neuropsychopharmakologie und Pharmakopsychiatrie (AGNP) has worked out consensus guidelines with the aim of providing psychiatrists and TDM laboratories with a tool to optimize the use of TDM. Five research-based levels of recommendation were defined with regard to routine monitoring of drug plasma concentrations: (i) strongly recommended; (ii) recommended; (iii) useful; (iv) probably useful; and (v) not recommended. In addition, a list of indications that justify the use of TDM is presented, eg, control of compliance, lack of clinical response or adverse effects at recommended doses, drug interactions, pharmacovigilance programs, presence of a genetic particularity concerning drug metabolism, and children, adolescents, and elderly patients. For some drugs, studies on therapeutic ranges are lacking, but target ranges for clinically relevant plasma concentrations are presented for most drugs, based on pharmacokinetic studies reported in the literature. For many antidepressants, a thorough analysis of the literature on studies dealing with the plasma concentration–clinical effectiveness relationship allowed inclusion of therapeutic ranges of plasma concentrations. In addition, recommendations are made with regard to the combination of pharmacogenetic (phenotyping or genotyping) tests with TDM, Finally, practical instructions are given for the laboratory practitioners and the treating physicians how to use TDM: preparation of TDM, drug analysis, reporting and interpretation of results, and adequate use of information for patient treatment. TDM is a complex process that needs optimal interdisciplinary coordination of a procedure implicating patients, treating physicians, clinical pharmacologists, and clinical laboratory specialists. These consensus guidelines should be helpful for optimizing TDM of antidepressants.
Analysing Security and Software Requirements using Multi-Layered Iterative Model

Nowadays, security is of great concern for any organization developing software systems for various requirements. Moreover, the same becomes more complicated during integration of security measures with agile software development methodology due to its lightweight informal nature. The requirements engineering is considered as one of the key element associated with any software development process. This motivates us to suggest a FLAMIRA model that provides seamless integration of security needs with software requirements in an iterative manner. In agile processes, requirements are recorded in the form of user stories developed jointly by customer’s representative and the development team. User stories are useful for agile processes as they define requirements using a low-cost, user centric and flexible approach. Keeping this aspect in mind we are integrating abuser stories for security requirements with user stories. FLAMIRA is a multi-layered model which shows us the path to be followed right from the identification of the user stories till the formulation of abuser stories. This paper concludes with a set of user stories and abuser stories to be followed in each iteration. Keywords— Agile Methods, User Stories, Abuser Stories, Requirement engineering.
Design and implementation of a visual query language for large spatial databases

In this paper a visual approach to querying in large spatial databases is presented. A diagrammatic technique utilising a dataflow metaphor is used to express different kinds of spatial and non-spatial constraints. Basic filters are designed to represent the various types of queries in such systems. Icons for different types of spatial relations are used to denote the filters. Different granularities of the relations are presented in a hierarchical fashion when selecting the spatial constraints. The language constructs are presented and examples are used to demonstrate the expressiveness of the approach in representing different kinds of queries, including spatial joins and composite spatial queries. The implementation prototype of the language is also described and its features evaluated against a general purpose GIS package.
Iterative probabilistic scheduling of IP traffic

Output Queuing (OQ) and Input Queuing (IQ) are the two basic queuing strategies implemented in routers. IQ has been identified as the simplest and the most scalable. However, the IQ only achieves 58.6% throughput due to the Head Of Line (HOL) blocking effect. The Virtual Output Queuing (VOQ) strategy is a proffered solution to the HOL blocking. It has been shown that VOQ can achieve a 100% throughput with an effective scheduling algorithm. This paper proposes a Multi stage Queuing and Scheduling architecture in which VOQ is implemented at the input and OQ at the output. The scheduling algorithm for the VOQ presented in this paper is an Iterative Probabilistic Scheduling.
Between Main and Sideline Occupations: A Survey of the “Income-Generating” Activities of Rural Junior High School Teachers

Abstract The Ministry of Education banned the “income-generating” activities of urban primary and secondary school teachers obtaining extra income by conducting paid supplemental classes, due to their social impact. Other than examining the policy provisions, however, there has not been much research by domestic scholars on urban teachers conducting paid supplemental classes. There is also a lack of reliable descriptions of whether rural junior high school teachers engage in income-generating activities and what those activities are. Based on a follow-up survey at a rural junior high school, this study describes the use of income-generating models by junior high school teachers in rural China, either “farming as a sideline” or “business as a sideline. ” On this foundation, the author explores the relationships between the factors of age, family origin, and family structure and the teachers’ income-generating activities.
Perception of quality in sport – qualitative and quantitative approach

Celem pracy byla proba systemowego (holistycznego) ujecia problematyki jakości w sporcie, uwzgledniając jego roznorodnośc, zlozonośc, wielowymiarowośc. Odniesiono sie do interpretacji pojecia jakości, charakterystyki uwarunkowan jej postrzegania, jak i sposobow oceny jakości w sporcie. Praca ma charakter koncepcyjny (projektowy). Projektowanie modeli jakości w sporcie poprzedzily studia literatury zorientowanej na problematyke jakości. Nastepnie wykorzystano systemowy model uporządkowan strukturalnych zjawisk, pozwalający na wyodrebnienie glownych obszarow sportu i ich ujecie w roznych skalach i wymiarach. Dalej opisano rozne aspekty oceny jakości w sporcie ze wskazaniem kryteriow, miar i sposobow oceny. Podkreślono szczegolnie zasadnośc ujecia prakseologicznego, w ktorym jakośc w sporcie moze byc odniesiona do efektywności dzialan. W dalszej cześci opisano emocjonalny (jakościowy) i rzeczowy (ilościowy) wymiar towarzyszący ocenie jakości widowisk sportowych. Opisano takze wspolczesne tendencje przenikania sie aspektow jakościowych i ilościowych w percepcji widowisk sportowych. Abstract The main purpose of the article is to present a problem of quality in sport from the system (holistic) perspective and reveal its diversity, complexity and multidimensionality. The author presents an extensive review of different approaches and concepts of quality in the literature as well as methods of measurement in sport. The article is conceptual and demonstrates a model of quality, which was preceded by a literature review. The author describes a model of structural orders, indicates crucial sport areas and presents its different aspects of measurement quality in sport: dimensions, scales, criteria and measures. In this part, the praxeological approach (with effectiveness criteria) is distinguished and justified. In the next part of the article, the emotional (qualitative) and material (quanitative) dimensions of quality of sport spectacles are discussed as well as contemporary trends of those dimensions diffusion.
GSM system implementation for academic purposes

This paper presents an academic implementation of a GSM system that guarantees communication across GSM air interface and interconnection with other networks using a joint operation of USRP as hardware platform and GNU Radio, OpenBTS and Asterisk as software platforms and applications. That solution will be useful in academic environments where telecommunication infrastructure is limited for operation. In addition, some tools like Wireshark and AirProbe are used to complement the whole solution and to develop a low cost laboratory platform.
Contrasting seasonal niche separation between rare and abundant taxa conceals the extent of protist diversity

With the advent of molecular methods, it became clear that microbial biodiversity had been vastly underestimated. Since then, species abundance patterns were determined for several environments, but temporal changes in species composition were not studied to the same level of resolution. Using massively parallel sequencing on the 454 GS FLX platform we identified a highly dynamic turnover of the seasonal abundance of protists in the Austrian lake Fuschlsee. We show that seasonal abundance patterns of protists closely match their biogeographic distribution. The stable predominance of few highly abundant taxa, which previously led to the suggestion of a low global protist species richness, is contrasted by a highly dynamic turnover of rare species. We suggest that differential seasonality of rare and abundant protist taxa explains the—so far—conflicting evidence in the ‘everything is everywhere’ dispute. Consequently temporal sampling is basic for adequate diversity and species richness estimates.
Project-Team IPSO Invariant Preserving Solvers

There is a large demand in biomolecular modeling for models that integrate microscopic molecular dynamics simulation into statistical macroscopic quantities. These simulations involve huge systems of ordinary differential equations over very long time intervals. This is a typical situation where the determination of accurate trajectories is out of reach and where one has to rely on the good qualitative behavior of structure-preserving integrators. Due to the complexity of the problem, more efﬁcient numerical schemes need to be developed. The demand for new models and/or new structure-preserving schemes is also quite large in laser simulations. The propagation of lasers induces, in most practical cases, several well-separated scales: the intrinsically highly-oscillatory waves travel over long distances. In this situation, ﬁltering the oscillations in order to capture the long-term trend is what is required by physicists and engineers. or FEM ﬁnite dimensional space of functions in x ) may exhibit Hamiltonian or Poisson structure, whose long-time properties turn out to be more tractable. the Helmholtz equation takes into account at once the propagation of waves over inﬁnitely long time intervals. Qualitatively, in order to have a good understanding of the signal observed in some bounded region of space, one readily needs to be able to describe the propagative phenomena in the whole space, up to inﬁnity. In other words, the “rays” we refer to above need to be understood from the initial time up to inﬁnity. This is a central difﬁculty in the analysis of the high-frequency behaviour of the Helmholtz equation.
Efficient Constellation Design Based on Improved Non-dominated Sorting Genetic Algorithm-II

Constellation design is a typical multiple peaks, multiple valleys and non-linear multi-objective optimization problem. How to design satellite constellation is one of the key sectors of research in the aerospace field. In this paper, in order to improve the global convergence and diversity performance of traditional constellation optimization algorithm, multi-parent arithmetic crossover and SBX crossover operator of NSGA-II are used to improve searching capability of this algorithm. Meanwhile, Gaussian mutation and Cauchy mutation, with diversity of population, make the algorithm get better behaviors in convergence and diversity of finding solutions. Based on the methods, an improvement NSGA-II is presented to design constellation in the paper. The algorithm uses fixed length chromosome representation. Real coding is adopted for that the problem has both integer continuous variables. Combining the coverage assessment criterions, an orbit parameters optimization framework based on non-dominated sorting genetic algorithm (NSGA-II) was proposed. This method is applied to a detailed example, and result shows that a group of Pareto solutions with good spread can be achieved, which gives strong support to constellation scheme determination.
Utilization-Based Schedulability Test of Real-Time Systems on Virtual Multiprocessors

The number of applications that use virtual systems is growing, and one would like to use this kind of systems also for real-time applications with hard deadlines. Virtual machines with many cores are interesting since the underlying physical infrastructure usually contains many cores. We consider hard real-time tasks that execute on a virtual machine with m cores. Tasks are scheduled globally on the cores using fixed-priority preemptive scheduling. This means that a task can execute on different virtual cores at different instances in time. In order to avoid Dhall's effect, which may cause task sets with even very low utilization to miss deadlines, we classify tasks into two priority classes, namely heavy and light tasks. Heavy tasks have higher priority than light tasks. For light tasks we use rate monotonic priority assignment. In this paper we propose a utilization-based test that shows if a task set is schedulable or not. If the task set is schedulable the test provides the priority for each task. The input to the test is the task set, the number of cores in the virtual machine (m), a period for the virtual machine with m cores, and the blocking time when a virtual machine does not have access to the underlying hardware in each period.
Role of ghrelin in food reward: impact of ghrelin on sucrose self-administration and mesolimbic dopamine and acetylcholine receptor gene expression

The decision to eat is strongly influenced by non‐homeostatic factors such as food palatability. Indeed, the rewarding and motivational value of food can override homeostatic signals, leading to increased consumption and hence, obesity. Ghrelin, a gut‐derived orexigenic hormone, has a prominent role in homeostatic feeding. Recently, however, it has emerged as a potent modulator of the mesolimbic dopaminergic reward pathway, suggesting a role for ghrelin in food reward. Here, we sought to determine whether ghrelin and its receptors are important for reinforcing motivation for natural sugar reward by examining the role of ghrelin receptor (GHS‐R1A) stimulation and blockade for sucrose progressive ratio operant conditioning, a procedure used to measure motivational drive to obtain a reward. Peripherally and centrally administered ghrelin significantly increased operant responding and therefore, incentive motivation for sucrose. Utilizing the GHS‐R1A antagonist JMV2959, we demonstrated that blockade of GHS‐R1A signaling significantly decreased operant responding for sucrose. We further investigated ghrelin's effects on key mesolimbic reward nodes, the ventral tegmental area (VTA) and nucleus accumbens (NAcc), by evaluating the effects of chronic central ghrelin treatment on the expression of genes encoding major reward neurotransmitter receptors, namely dopamine and acetylcholine. Ghrelin treatment was associated with an increased dopamine receptor D5 and acetylcholine receptor nAChRβ2 gene expression in the VTA and decreased expression of D1, D3, D5 and nAChRα3 in the NAcc. Our data indicate that ghrelin plays an important role in motivation and reinforcement for sucrose and impacts on the expression of dopamine and acetylcholine encoding genes in the mesolimbic reward circuitry. These findings suggest that ghrelin antagonists have therapeutic potential for the treatment of obesity and to suppress the overconsumption of sweet food.
Stability Properties of Constrained Jump-diffusion Processes 1

We consider a class of jump-diffusion processes, constrained to a polyhedral cone G ⊂ IRn, where the constraint vector field is constant on each face of the boundary. The constraining mechanism corrects for “attempts” of the process to jump outside the domain. Under Lipschitz continuity of the Skorohod map Γ, it is known that there is a cone C such that the image Γφ of a deterministic linear trajectory φ remains bounded if and only if φ̇ ∈ C. Denoting the generator of a corresponding unconstrained jump-diffusion by L, we show that a key condition for the process to admit an invariant probability measure is that for x ∈ G, L id(x) belongs to a compact subset of Co.