Miracle-dz/UniFAR-FTUs huggingface dataset:
An epidemiologic study of behavior characteristics in children.

ONE OF the great psychiatric dilemmas of our time is the decision as to what is iformal and what is abnormal in human behavior. Lacking specific tests to make the distinction, the diagnostician has recourse mainly to his clinical judgment which rests on his training, experience, perceptiveness, and theoretical persuasion. These in turn are limited by the present level of scientific knowledge, which has made it possible for hypotheses regarding the pathologic import of certain symptoms to be accepted without sufficient testing or validation, to be passed from teacher to pupil, to persevere in the literature, and to influence a succession of therapies. In child psychiatry, Leo Kanner points out that recorded symptoms "are of necessity those of selected groups and not of the total population of children"; and, he continues, "This selectiveness, in the absence of 'normal controls' has often resulted in a tendency to attribute to single behavior items an exaggerated 'seriousness' with regard to their intrinsic psychopathologic significance. The seriousness becomes attached to the signal regardless of what it announces and who announces it. The high annoyance threshold of many fond and fondly resourceful parents keeps away from clinics and out of the reach of statistics a multitude of early breath holders, nail biters, nose pickers and casual masturbators who, largely because of this kind of parental attitude, develop into reasonably happy and well-adjusted adults. " 1 The two major issues besetting all research workers concerned with the differentiation of the psychiatrically well child from the psychiatrically sick child are brought out in Dr. Kanner's statement, namely, the problems of method and definition. These issues are the focus of the present study which represents the exploratory phase of an effort to penetrate the barriers of selection and to broaden knowledge about the behavior, function, and adjustment of children who are not likely to be picked out of the community for psychiatric examination and therefore have little chance of contributing to the statistics of symptoms. The methodologic difficulties in designing a study of the spectrum of child behavior and symptomatology are great. Most previous studies with similar objectives have utilized nonrepresentative samples and/or methods which cannot be replicated on other groups. This is
Stability Analysis of AC Microgrids With Constant Power Loads Based on Popov's Absolute Stability Criterion

This brief considers nonlinear stability analysis of ac microgrids with constant power loads (CPLs). A microgrid is a subsystem consisting of small electrical resources, local loads, and power electronic devices. It should be noted that the presence of a CPL as a sink in a microgrid results in nonlinear behavior of the microgrid. CPLs are generally connected to an ac microgrid through a controlled rectifier and/or dc-dc converters. We model an ac microgrid with local RLC load and a CPL with power converter subsystem, which results in a set of nonlinear state-space equations. Then, Popov's absolute stability theorem is utilized to analyze stability conditions for an ac microgrid in the presence of CPL. Simulation results are presented, which are in agreement with the analytical approach.
CULTURE AMBIENCE AND COLLECTIVE CONTROLS IN CO-OPERATIVES

This paper is based on the data gathered from 677 members of 54 organisations from Uttar Pradesh and Rajasthan in North India and Andhra Pradesh, Tamil Nadu and Kerala in South India, All these organisations are primary level grass-root organisations involved in collective action, half of them are co-operatives. The data captures nine cultural attributes and values, and three mechanisms of participation in and control of decisions of these chosen organisations. These have been related to two measures of performance: member satisfaction and member usage. It adduces statistical and qualitative evidence to show that satisfaction in all such collective primary level organisations is strongly conditioned by cultural factors whereas the level of usage is conditioned by control factors. Satisfaction does not necessarily flow from high usage. It is seen that almost identical civic cultures have different impacts on co-operatives and non-co-operatives, due to several reasons. Generally, performance in co-operatives are relatively conditioned more by controls than by culture; among controls, the market type of controls appear to be significant, Thus, performance in co-operatives often depends on the market environment external to the organisation. It also very tentatively suggests that ‘voting intensity’ in elections is likely to be low in organisations with very low level or very high levels of satisfaction and high where satisfaction is moderate. Lastly, it adduces evidence (subject to limitations of the sample size), to show higher belief in democracy and higher trust in village leadership in the South than in the North. This should have produced higher levels of performance. It generally did not due to several countervailing factors, the most significant being the absence of the level of “aggressiveness” required for effective performance in the South. In interpreting the data, a new framework is proposed, which bypasses some of the existing wellknown frameworks for analysing collective action. These frameworks are based on a non-Indian picture of man. The paper, without totally discarding the concept of the economic nature of man, uses five strands of research drawn from different disciplines: civic culture, theory of the firm, theory of democracy, current theories of management controls and evaluator studies of cooperatives. The link between facts and theory is by inductive reasoning and therefore, tentative and not conclusive. ***
Investigating Reading Techniques for Framework Learning

The empirical study described in this paper addresses software reading for construction: how application developers obtain an understanding of a software artifact for use in new system development. This study focuses on the processes developers would engage in when learning and using object-oriented frameworks. We analyzed 15 student software development projects using both qualitative and quantitative methods to gain insight into what processes occurred during framework usage. The contribution of the study is not to test predefined hypotheses but to generate well-supported hypotheses for further investigation. The main hypotheses we produce are that example-based techniques are well suited to use by beginning learners while hierarchy-based techniques are not because of a larger learning curve. Other more specific hypotheses are proposed and discussed.
THE ENZYMATIC IODINATION OF THE RED CELL MEMBRANE

An enzymatic iodination procedure utilizing lactoperoxidase (LPO), radioactive iodide, and hydrogen peroxide generated by a glucose oxidase-glucose system has been described and utilized for a study of the red cell membrane. 97% of the incorporated isotope is in the erythrocyte ghost and 3% is associated with hemoglobin. No significant labeling of the red cell membrane occurs in the absence of LPO or by the deletion of any of the other reagents. A 6 million-fold excess of chloride ions inhibits iodination by no more than 50%. Incorporation of up to 1 x 106 iodide atoms into a single erythrocyte membrane results in no significant cell lysis. The incorporated label is exclusively in tyrosine residues as monoiodotyrosine. 10–15% of the trichloroacetic acid-precipitable radioactivity can be extracted with lipid solvents but is present as either labeled protein or 125I. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis of solubilized membrane proteins reveals only two labeled protein bands out of the 15 present, and the presence of 50-1 x 106 iodide atoms per ghost does not alter this pattern. Component a has a molecular weight of 110,000, is carbohydrate poor, and represents 40% of the total label. Component b has an apparent molecular weight of 74,000, contains all of the demonstrable sialic acid, and accounts for 60% of the total label. Trypsinization of iodinated, intact red cells results in the disappearance of only component b, the appearance of labeled glycopeptides in the medium, and the absence of smaller, labeled peptides remaining in the membrane. Pronase treatment hydrolyzes component b in a similar fashion, but also cleaves component a to a 72,000 mol wt peptide which is retained in the membrane. A combination of protease treatment and double labeling with 125I and 131I does not reveal the appearance of previously unexposed proteins.
The costs and benefits of testing text materials

Tests have been shown to improve the later recall of tested information, a result known as the testing effect. Tests, however, can also impair the later recall of related information, an effect known as retrieval-induced forgetting. Although retrieval-induced forgetting has been demonstrated using a wide variety of materials, recent work suggests that learning information in the context of a coherent text passage may afford protection from retrieval-induced forgetting. In four experiments we explored the conditions under which retrieval-induced forgetting does and does not occur with such materials. We found that two factors—the coherence of the to-be-learned material and the competitiveness of retrieval practice—are important in determining whether retrieval-induced forgetting does or does not occur. Furthermore, even if retrieval-induced forgetting does occur, having the opportunity to restudy the forgotten information can prevent that forgetting from persisting. Taken together, these findings provide greater understanding of the costs and benefits of testing text materials, with possible implications for the optimisation of testing as a tool for learning in educational contexts.
General Introduction Box 1. Antisocial Behavior the Current Study Data Collection

Introduction There is a long history on how to 'treat' criminal behavior. Ranging from strongly religion-oriented programs in the early 1900s, to the raise of individualized intervention programs in 1960, through the rejection of nearly all treatment programs by many political parties in the 1970s as hardly any program appeared to be effective in reducing crime (for a historical overview see, Cullen & Gendreau, 2000). However, these former rehabilitation programs were not guided by underlying, coherent frameworks, or theoretical bases. During the 1980s and 1990s, meta-analytic methods were introduced, revealing several factors that were positively related to recidivism reduction. Since then, there has been a shift in criminal justice thinking from nothing works to models were introduced, aiming to target these specific recidivism-related factors, including criminogenic needs, such as substance abuse and family factors. Of these models, the 'Risk-Need-Responsivity' (RNR) model is currently most prominent in guiding The RNR model is characterized by a strong basis in personality and psychosocial perspectives on human behavior and suggests that behavioral intervention programs, especially those based on cognitive-behavioral therapy (CBT) techniques, are most effective in influencing factors that are known to predict recidivism (Andrews & Bonta, 2010). Indeed, meta-analytic studies confirm the positive influence of CBT-derived interventions on recidivism rates in both adolescents and adults All in all, the historical struggle with correctional rehabilitation programs seems to have ended with a moderately effective intervention approach for criminals. Nevertheless, meta-analytic research does not only show the average positive effects of CBT-based intervention programs on recidivism rates, but there also appears to be a large amount of variation in effectiveness across different interventions and different studies. In fact, some studies revealed almost a 50% reduction, while others found less than 10% decrease in criminal recidivism (for meta-analysis see, Lipsey & Cullen, 2007). Of course, a certain amount of that variability reflects statistical noise and unsystematic differences in study procedures and methods. However, Lipsey and Cullen (2007) stated that much of it is related to substantive characteristics of the treatment and offender samples to which the interventions are applied. Overall, the varying results suggest that there is still a relatively large group of offenders who do not benefit from correctional intervention. There are serious political, societal, and scientific needs to unravel why some offenders benefit from intervention, and others do not in order to develop effective intervention methods to reduce criminal recidivism rates. While the historical …
Encoding Tree Pair-Based Graphs in Learning Algorithms: The Textual Entailment Recognition Case

In this paper, we provide a statistical machine learning representation of textual entailment via syntactic graphs constituted by tree pairs. We show that the natural way of representing the syntactic relations between text and hypothesis consists in the huge feature space of all possible syntactic tree fragment pairs, which can only be managed using kernel methods. Experiments with Support Vector Machines and our new kernels for paired trees show the validity of our interpretation.
Tracking severe weather storms in Doppler radar images

We describe an automatic storm‐tracking system to help with the forecasting of severe storms. In this article, we present the concepts of fuzzy point, fuzzy vector, fuzzy length of a fuzzy vector, and fuzzy angle between two nonzero fuzzy vectors, that are used in our tracking algorithm. These concepts are used to overcome some of the limitations of our previous work, where fixed center‐of‐mass storm centers did not provide smooth tracks over time, while at the same time, their detection was very threshold sensitive. Our algorithm uses region splitting with dynamic thresholding to determine storm masses in Doppler radar intensity images. We represent the center of a hypothesized storm using a fuzzy point. These fuzzy storm centers are then tracked over time using an incremental relaxation algorithm. We have developed a visualization program using the X11 Athena toolkit for our storm visualization tool. The algorithm was tested on seven real radar image sequences obtained from the Atmospheric Environment Service radar station at King City, Ontario, Canada. We can obtain storm tracks that are long and smooth and which closely match an expert meteorologist's perception. © 1998 John Wiley & Sons, Inc. Int J Imaging Syst Technol, 9, 201–213, 1998
Generating DFA Construction Problems Automatically

Given a particular problem in some domain, an instructor may wish to generate new problems that are "similar" for several reasons: (a) to create personalized workflows for each student (i.e., by offering a harder or easier problem depending on how effectively the student has solved a given problem), (b) to create unique questions for each student on assignments and examinations (in order to minimize the risk of plagiarism), and (c) to avoid legal issues when the original problem is copyrighted material. Manual problem generation is infeasible, particularly in cases (a) and (b) when the number of students is large (e.g., in massive open online courses). Our contributions in this paper are: (1) a method for automatically generating problems in a core area of the undergraduate Computer Science curriculum: the construction of deterministic finite automata (DFA), (2) a measure of "difficulty" for such problems that instructors can easily tune to match the skills of students at their particular institutions, and (3) a tool that takes a given DFA construction problem P as input and generates an arbitrary number of distinct problems P1, P2, ⋯ in decreasing order of similarity to P (in terms of difficulty). The tool's output can be restricted to problems that are easier than, harder than, or about as hard as P. We also describe experimental evidence to validate the quality of problems generated by our tool.
Randomized Kinodynamic Motion Planning with Moving Obstacles

This paper presents a novel randomized motion planner for robots that must achieve a specified goal under kinematic and/or dynamic motion constraints while avoiding collision with moving obstacles with known trajectories. The planner encodes the motion constraints on the robot with a control system and samples the robot's state × time space by picking control inputs at random and integrating its equations of motion. The result is a probabilistic roadmap of sampled state ×time points, called milestones, connected by short admissible trajectories. The planner does not precompute the roadmap; instead, for each planning query, it generates a new roadmap to connect an initial and a goal state×time point. The paper presents a detailed analysis of the planner's convergence rate. It shows that, if the state×time space satisfies a geometric property called expansiveness, then a slightly idealized version of our implemented planner is guaranteed to find a trajectory when one exists, with probability quickly converging to 1, as the number of milestones increases. Our planner was tested extensively not only in simulated environments, but also on a real robot. In the latter case, a vision module estimates obstacle motions just before planning starts. The planner is then allocated a small, fixed amount of time to compute a trajectory. If a change in the expected motion of the obstacles is detected while the robot executes the planned trajectory, the planner recomputes a trajectory on the fly. Experiments on the real robot led to several extensions of the planner in order to deal with time delays and uncertainties that are inherent to an integrated robotic system interacting with the physical world.
Asymptomatic Simian Immunodeficiency Virus Infection Decreases Blood CD4+ T Cells by Accumulating Recirculating Lymphocytes in the Lymphoid Tissues

ABSTRACT Declining blood CD4+ T-cell counts mark the progress of simian immunodeficiency virus (SIV) disease in macaques and model the consequences of untreated human immunodeficiency virus infection in humans. However, blood lymphocytes are only a fraction of the recirculating lymphocyte pool, and their numbers are affected by cell synthesis, cell depletion, and distribution among blood and lymphoid tissue compartments. Asymptomatic, SIV-infected macaques maintained constant and nearly normal numbers of recirculating lymphocytes despite the decline in CD4+ T-cell counts. Substantial depletion was detected only when blood CD4+T-cell counts fell below 300/μl. In asymptomatic animals, changes in CD4+ T-cell distribution were more important than lymphocyte depletion for controlling the blood cell levels.
Invited: Heterogeneous datacenters: Options and opportunities

In this paper we present our ongoing study and deployment efforts for enabling FPGAs in datacenters. An important focus is to provide a quantitative evaluation of a wide range of heterogeneous system designs and integration options, from low-power field-programmable SoCs to server-class computer nodes plus high-capacity FPGAs, with real system prototyping and implementation on real-life applications. In the meantime, we develop a cloud-friendly programming interface and a runtime environment for efficient accelerator deployment, scheduling and transparent resource management for integration of FPGAs for large-scale acceleration across different system integration platforms to enable “write once, execute everywhere”.
Robust depth regularization explicitly constrained by camera motion

The objective of our work is to reconstruct the dense structure of a static scene observed by a monocular camera system following a known trajectory. Our main contribution is representated by the proposition of a TV-L1 energy functional that estimates directly the unknown depth field given the camera motion, thus avoiding to estimate as an intermediate step an optical flow field with additional geometric constraints. Our method has two main interests: we highlight a practical minimal parametrization for the given assumptions (static scene, known camera motion) and we solve the resulting variational problem using an efficient, discontinuity preserving formulation.
Adaptive cross-layer resource optimization in heterogeneous wireless networks with multi-homing user equipments

In this paper, we investigate the resource allocation problem in time-varying heterogeneous wireless networks (HetNet) with multi-homing user equipments (UE). The stochastic optimization model is employed to maximize the network utility, which is defined as the difference between the HetNet's throughput and the total energy consumption cost. In harmony with the hierarchical architecture of HetNet, the problem of stochastic optimization of resource allocation is decomposed into two subproblems by the Lyapunov optimization theory, associated with the flow control in transport layer and the power allocation in physical (PHY) layer, respectively. For avoiding the signaling overhead, outdated dynamic information, and scalability issues, the distributed resource allocation method is developed for solving the two subproblems based on the primal-dual decomposition theory. After that, the adaptive resource allocation algorithm is developed to accommodate the time- varying wireless network only according to the current network state information, i.e. the queue state information (QSI) at radio access networks (RAN) and the channel state information (CSI) of RANs-UE links. The tradeoff between network utility and delay is derived, where the increase of delay is approximately linear in V and the increase of network utility is at the speed of 1/V with a control parameter V . Extensive simulations are presented to show the effectiveness of our proposed scheme.
Nonlinear Finite Element Analysis of Beam String Structure

Beam string structure (BSS), which is a new kind of semi-rigid hybrid system, composed of arch, strut and string, has been developed rapidly in long-span steel structures in recent years. Based on the principle of virtual work and Updated Lagrange, the formulas of geometric nonlinear F.E. M. for spatial beam element, cable element and truss element are derived respectively in this paper. Taking the one-way BSS model of the steel roof in Guangzhou International Convention and Exhibition Center as a computational example by using both linear and nonlinear analysis method, the analytical results show that it is appropriate when adopting the straight truss element with two joints and equivalent elastic modulus to simulate the cable element with small sag. Although the linear analysis can meet the requirement of practical engineering due to its weak nonlinearity of BSS, the nonlinear method is also important to improve the precision theoretically. The conclusions obtained may be helpful for the designers in similar projects.
Software Defined Networking: Advanced Software Engineering to Computer Networks

: The paradigm defined networking software is becoming increasingly important and frequently used in the fields of computer networks. It allows us to run the software that manages the entire network. This software becomes more complicated to provide new features that were impossible to imagine before and it requires better performance, better reliability, security and better use of resources will only be possible by advanced software engineering techniques (high availability and distributed systems, optimized Linux kernel, synchronization, validation techniques).