Miracle-dz/UniFAR-FTUs huggingface dataset:
Applying Social Cognitive Theory in Coaching Athletes: The Power of Positive Role Models

The purpose of this article is to help coaches apply specific principles of psychology to the coaching process. More specifically, the work of Albert Bandura and his social cognitive theory form the basis for the article. This article begins with a brief overview of Bandura's social cognitive theory. It then examines four types of behaviors worthy of imitation and provides practical examples of each. Thereafter, the article defines and outlines various models that coaches need to be aware of and the power of modeling. It concludes with an examination of four processes of observational learning, and most importantly, the actual practical application of social cognitive theory as it relates to coaching athletes. By exploring and developing a better understanding of the basic tenets of social cognitive theory and its applications, coaches can add to and enhance their “coaching toolbox,” and ultimately improve their practice.
Voltage and lamp flicker issues: should the IEEE adopt the IEC approach?

This paper is intended to provide an overview of the IEC flicker measurement and assessment procedures. The IEC procedures are correlated with existing IEEE flicker standards to show the benefits of the IEC methodology. Application issues, such as customer impact assessment, are also discussed. Three case studies, two field tests, and one EMTP analysis are provided to show the correlation of IEC flickermeter output values with documented customer complaints. The case studies also provide areas where modifications to the IEC flicker standards may be necessary when developing a new IEEE flicker standard.
Conformal blocks for the four-point function in conformal quantum mechanics

Extending previous work on 2 -- and 3 -- point functions, we study the 4 -- point function and its conformal block structure in conformal quantum mechanics CFT$_1$, which realizes the SO(2,1) symmetry group. Conformal covariance is preserved even though the operators with which we work need not be primary and the states are not conformally invariant. We find that only one conformal block contributes to the four-point function. We describe some further properties of the states that we use and we construct dynamical evolution generated by the compact generator of SO(2.1).
Effect of Schistosomiasis and Soil-Transmitted Helminth Infections on Physical Fitness of School Children in Côte d'Ivoire

Background Schistosomiasis and soil-transmitted helminthiasis are important public health problems in sub-Saharan Africa causing malnutrition, anemia, and retardation of physical and cognitive development. However, the effect of these diseases on physical fitness remains to be determined. Methodology We investigated the relationship between schistosomiasis, soil-transmitted helminthiasis and physical performance of children, controlling for potential confounding of Plasmodium spp. infections and environmental parameters (i.e., ambient air temperature and humidity). A cross-sectional survey was carried out among 156 school children aged 7–15 years from Côte d'Ivoire. Each child had two stool and two urine samples examined for helminth eggs by microscopy. Additionally, children underwent a clinical examination, were tested for Plasmodium spp. infection with a rapid diagnostic test, and performed a maximal multistage 20 m shuttle run test to assess their maximal oxygen uptake (VO2 max) as a proxy for physical fitness. Principal Findings The prevalence of Schistosoma haematobium, Plasmodium spp. , Schistosoma mansoni, hookworm and Ascaris lumbricoides infections was 85.3%, 71.2%, 53.8%, 13.5% and 1.3%, respectively. Children with single, dual, triple, quadruple and quintuple species infections showed VO2 max of 52.7, 53.1, 52.2, 52.6 and 55.6 ml kg−1 min−1, respectively. The VO2 max of children with no parasite infections was 53.5 ml kg−1 min−1. No statistically significant difference was detected between any groups. Multivariable analysis revealed that VO2 max was influenced by sex (reference: female, coef. = 4.02, p<0.001) and age (years, coef. = −1.23, p<0.001), but not by helminth infection and intensity, Plasmodium spp. infection, and environmental parameters. Conclusion/Significance School-aged children in Côte d'Ivoire showed good physical fitness, irrespective of their helminth infection status. Future studies on children's physical fitness in settings where helminthiasis and malaria co-exist should include pre- and post-intervention evaluations and the measurement of hemoglobin and hematocrit levels and nutritional parameters as potential co-factors to determine whether interventions further improve upon fitness.
License plate tracking for car following with a single camera

In this article we present a new approach for car following. Generally, car following systems use active sensors or a stereoscopic system for 3D car localization. In this paper, we present a method that uses a license plate as an inherent car feature that can be tracked in real time. This visual information is then exploited to get the exact relative car localization needed by the car following system.
Understanding Change Requests to Predict Software Impact

During its lifecycle, software experiences numerous changes that are either due to bug fixes or to the incorporation of new features. Implementing such changes is often more difficult than expected, which frequently leads to underestimation of the associated implementation effort. This paper describes work that aims to understand change impact based on the visualization of the characteristics of change requests using standard diagrams (e.g. UML diagrams). Each diagram depicts different aspects of a software system and can illustrate factors that might drive the implementation effort. Using examples, in which we analyze three change requests, we describe how we determined the characteristics of the change requests. We furthermore discuss how the impact of change requests on diagrams relates to the implementation effort. Our overall goal is to develop a new impact analysis approach that helps determine software change impact based on the use of specific diagrams
Near-Optimal Herding

Herding is an algorithm of recent interest in the machine learning community, motivated by inference in Markov random fields. It solves the following sampling problem: given a setX R d with mean , construct an infinite sequence of points fromX such that, for every t 1, the mean of the first t points in that sequence lies within Euclidean distance O(1=t) of . The classic Perceptron boundedness theorem implies that such a result actually holds for a wide class of algorithms, although the factors suppressed by the O(1=t) notation are exponential in d. Thus, to establish a non-trivial result for the sampling problem, one must carefully analyze the factors suppressed by theO(1=t) error bound. This paper studies the best error that can be achieved for the sampling problem. Known analysis of the Herding algorithm give an error bound that depends on geometric properties ofX but, even under favorable conditions, this bound depends linearly on d. We present a new polynomialtime algorithm that solves the sampling problem with error O p d log 2:5 jXj=t assuming thatX is finite. Our algorithm is based on recent algorithmic results in discrepancy theory. We also show that any algorithm for the sampling problem must have error ( p d=t). This implies that our
Separability of parallel Gaussian MIMO broadcast channels with shaping constraints

It is well known that separate coding on each carrier is capacity-achieving in parallel Gaussian multiple-input multiple-output (MIMO) broadcast channels in the sense that the sum rate capacity under a sum power constraint is achievable with separate coding if the noise is independent on each carrier. In this paper, we generalize this statement by proving that the optimality of separate coding also holds under per-carrier shaping constraints, i.e., a sum covariance constraint on each carrier instead of a sum power constraint. Moreover, we show that not only the sum rate optimal point, but the whole capacity region can be achieved with separate coding. Finally, we prove that the worst-case noise in a MIMO broadcast channel with shaping constraints is independent across carriers.
The characteristics of digital video and considerations of designing video databases

In this paper, a generic architecture of interactive video databases is proposed. It is a platform for video applications. It consists of six major modules : Video Indexing, Interactive Browser, Object Annotator, Query Processing Tool, Video Management Module and Content Retrieval Module. The considerations and requirements of the video database in the aspects of video data management, annotation capability, content-based query and browsing interfaces are described. This paper also describes a Video Object Description Model (VODM) for annotations. The notion of VODM is based on the Entity-Relationship model for the database conceptual level organization. Unlike keyword or framebased knowledge representation, VODM can record the detail attribute information about video objects, store and retrieve annotations in many different video files. To construct VODM, we give a recursive definition of the video object and describe the operations of annotation storage structures. A two-step query processing method is introduced that can reduce the processing time of each video object query.
FireµSat: An algorithm to detect microsatellites in DNA

In the context of this paper microsatellites (short approximate tandem repeats) refer to consecutive patterns contained in genomic sequences. A new algorithm to detect such microsatellites in DNA is proposed. The algorithm relies on the construction of finite automata originating from the Moore machine paradigm. The proposed finite automata contain “counting states”. The overall algorithm is designed to support user requirements as expressed by the typical geneticist.
Analysis and Classification Technique Based On ANN for EEG Signals

This paper presents an ANN approach for classification of EEG signals. Epilepsy is one of the most common and frequent neurological disorders. Actually, epilepsy is a disease of the nervous system, in which the patient falls to the ground in a state of insensibility, with general convulsion of the muscles and bubbling at the mouth. Electroencephalogram (EEG) signal analysis is the main method that is used in epilepsy diagnosis. For seizure detection and prediction by extracting different features of the EEG signal discrete wavelet transformation is used. The proposed approach is found to achieve classification accuracies of 93.62% and 93.08% for the epileptic EEG data. KeywordsClassification of Electroencephalogram (EEG), Committee Neural Network, Artificial Neural Network.
Systematic Comparisons of Formulations of Linear Oligolysine Peptides with siRNA and Plasmid DNA

The effects of lysine peptide lengths on DNA and siRNA packaging and delivery were studied using four linear oligolysine peptides with 8 (K8), 16 (K16), 24 (K24) and 32 (K32) lysines. Oligolysine peptides with 16 lysines or longer were effective for stable monodisperse particle formation and optimal transfection efficiency with plasmid DNA (pDNA), but K8 formulations were less stable under anionic heparin challenge and consequently displayed poor transfection efficiency. However, here we show that the oligolysines were not able to package siRNA to form stable complexes, and consequently, siRNA transfection was unsuccessful. These results indicate that the physical structure and length of cationic peptides and their charge ratios are critical parameters for stable particle formation with pDNA and siRNA and that without packaging, delivery and transfection cannot be achieved.
A Model of Communicative and Hierarchical Foundations of High Reliability Organizing in Wildland Firefighting Teams

Organizational hierarchy is an inescapable aspect of many exemplary high reliability organizations (HROs). As organizations begin to adopt HRO theorizing to improve practice, it is increasingly important to explain how HRO principles—which assume the hallmarks of a flat hierarchy—can be understood and enacted in rigidly stratified organizations. We propose a preliminary theoretical model suggesting how various supervisor–subordinate and work group communication patterns and practices enable members to navigate hierarchy to achieve high reliability. We test the model using structural equation modeling on a sample of N = 574 U.S. wildland firefighters from three federal agencies. Results suggest how organizational members might overcome common hierarchy-based constraints to HRO through considering how leaders throughout a chain of command communicate to cultivate the necessary cross-level awareness of an operation, and ways in which supervisors, members, and groups might cultivate interactional cultures with respectful affect.
INFORMATION EXTRACTION FROM BIOMEDICAL TEXT : THE BIOTEXT PROJECT

We study information extraction for identifying protein-protein interactions stated in biomedical text. In this paper, we present an architecture for an information extraction system and discuss our improvements and results pertaining to several components of the system, including information retrieval, named entity recognition, syntactic analysis, and domain analysis. The individual results are discussed in the context of the whole system, and domain adaptations and differences from classical approaches are considered. We combine structural natural language processing with machine learning methods to address the general and domain-specific challenges of information extraction targeting protein-protein interactions.
Alignment or Drift? Loose Coupling over Time in NASA's ERP Implementation

Through a grounded analysis of NASA's ERP implementation that spans the four years after the system went live, we motivate the importance of loose coupling to the study of enterprise systems, identify three forms of loose coupling associated with enterprise systems, and detail the evolution of activity that is loosely coupled from the system. We conclude by suggesting that loose coupling that is mediated by either system or human intermediaries follows a process of mutual adaptation and may result in a state of loosely coupled equilibrium that can be beneficial to the organization and its knowledge workers. Loose coupling that is mediated by human interpretation, on the other hand, results in drift that can enable individual flexibility and situated action, but may undermine imperatives of control and may render data in the enterprise system less meaningful.
Partial Copy Detection in Videos: A Benchmark and an Evaluation of Popular Methods

The goal of partial video copy detection is to find one or more segments of a query video which have (transformed) copies in a large dataset. Previous related research in this field used either small-scale datasets or large datasets with simulated partial copies by imposing several pre-defined transformations (e.g., photometric changes) due to the extremely time-consuming annotation of real copies. It is still unknown how well the techniques developed on simulated datasets perform on real copies, which are much more challenging and too complex to be simulated. In this paper, we introduce a large-scale video copy database (VCDB) with over 100,000 videos, and more than 9,000 copy pairs found by manual annotation. A state-of-the-art system of video copy detection is evaluated on VCDB to show the limitations of existing techniques. We also evaluate deep learning features learned by two neural networks: one is independently trained on a different dataset and the other is tailored to deal with the copy detection task. Our evaluation suggests that all the existing techniques, including the deep learning features, are far from satisfactory in detecting complex real copies.
Applying Data Mining to Explore Students' Self-Regulation in Learning Contexts

The theory of self-regulation, which includes cognitive, motivational, and behavioral dimensions, is useful for understanding the relationships between motivations, learning strategies, and the learner in the context of learning. The critical attributes, such as planning, metacognitive monitoring, and self-reflection, provide valuable information to clarify why some students perform better than others. In order to extract significant attributes for successful learners, the supervised learning method is applied to 131 students of Tunghai University in Taiwan. The mining results indicate that successful students normally spend time on the unclear concepts and put more emphasis on difficult learning materials during the course of learning. The findings provide further information for understanding how students deploy their self-regulatory behaviors in the learning contexts.
SLAM and Exploration using Differential Evolution and Fast Marching

The exploration and construction of maps in unknown environments is a challenge for robotics. The proposed method is facing this problem by combining effective techniques for planning, SLAM, and a new exploration approach based on the Voronoi Fast Marching method. The final goal of the exploration task is to build a map of the environment that previously the robot did not know. The exploration is not only to determine where the robot should move, but also to plan the movement, and the process of simultaneous localization and mapping. This work proposes the Voronoi Fast Marching method that uses a Fast Marching technique on the Logarithm of the Extended Voronoi Transform of the environment’s image provided by sensors, to determine a motion plan. The Logarithm of the Extended Voronoi Transform imitates the repulsive electric potential from walls and obstacles, and the Fast Marching Method propagates a wave over that potential map. The trajectory is calculated by the gradient method. The robot is directed towards the most unexplored and free zones of the environment so as to be able to explore all the workspace. Finally, to build the environment map while the robot is carrying out the exploration task, a SLAM (Simultaneous Localization and Modeling) algorithm is implemented, the Evolutive Localization Filter (ELF) based on a differential evolution technique. The combination of these methods provide a new autonomous exploration strategy to construct consistent maps of 2D indoor environments.
A Polyclonal Antibody to the Prepore Loop of Transient Receptor Potential Vanilloid Type 1 Blocks Channel Activation

Transient receptor potential vanilloid type 1 (TRPV1) can be activated by multiple chemical and physical stimuli such as capsaicin, anandamide, protons, and heat. Capsaicin interacts with the binding pocket constituted by transmembrane regions 3 and 4, whereas protons act through residues in the prepore loop of TRPV1. Here, we report on characterization of polyclonal and monoclonal antibodies to the prepore loop of TRPV1. A rabbit anti-rat TRPV1 polyclonal antibody (Ab-156H) acted as a full antagonist of proton activation (IC50 values for pH 5 and 5.5 were 364.68 ± 29.78 and 28.31 ± 6.30 nM, respectively) and as a partial antagonist of capsaicin, heat, and pH 6 potentiated chemical ligand (anandamide and capsaicin) activation (50-79% inhibition). Ab-156H antagonism of TRPV1 is not affected by the conformation of the capsaicin-binding pocket because it is equally potent at wild-type (capsaicin-sensitive) rat TRPV1 and its T550I mutant (capsaicin-insensitive). With the goal of generating monoclonal antagonist antibodies to the prepore region of human TRPV1, we used a recently developed rabbit immunization protocol. Although rabbit polyclonal antiserum blocked human TRPV1 activation, rabbit monoclonal antibodies (identified on the basis of selective binding to Chinese hamster ovary cells expressing human TRPV1) did not block activation by either capsaicin or protons. Thus, rabbit polyclonal antibodies against rat and human TRPV1 prepore region seem to partially lock or stabilize the channel in the closed state, whereas rabbit anti-human TRPV1 monoclonal antibodies bind to the prepore region but do not lock or stabilize the channel conformation.
A Blocker-Tolerant Current Mode 60-GHz Receiver With 7.5-GHz Bandwidth and 3.8-dB Minimum NF in 65-nm CMOS

A current-mode 60-GHz direct-conversion receiver, which can break performance tradeoffs among bandwidth, noise figure (NF), and linearity is designed and realized in 65-nm CMOS. The 60-GHz receiver employs the novel frequency-staggered series resonance common source (FSRCS) stage to extend RF bandwidth with superior noise performance. The receiver's current-mode operation offers excellent out-of-band blocker tolerance and linearity. With on-chip quadrature local oscillator generations, the fabricated receiver simultaneously achieves minimal NF of 3.8 dB, RF bandwidth of 7.5 GHz, output P1 dB of 1 dBm, and maximum conversion gain of 36 dB. The receiver is capable of tolerating out-of-channel blocker up to -9 dBm at 3.5 GHz away. It occupies a silicon area of 1.3 mm2 and draws 25.5 mA of current from a 1-V supply.
Microbial Competition in Reactors with Wall Attachment : A Comparison of Chemostat and Plug Flow Models

The indigenous microflora of the human large intestine is a complex ecosystem consisting of several hundred species of microorganisms [5]. The composition of the microflora is remarkably stable; the species coexist without one or a few becoming dominant [12]. One of its most important contributions to the host is its ability to impede the colonization of the intestinal tract by nonindigenous microorganisms [19]. The term “colonization resistance” [22] is used to describe all mechanisms involved in this function. An understanding of these mechanisms would represent a major contribution to human health. Competition for nutrients and competition for adhesion sites appear to be widely accepted as among the most important components of colonization resistance [4, 12, 13, 14, 19, 20]. The difficulties associated with in vivo studies of the human intestinal microflora are self-evident. A number of in vitro models of bacterial interactions in the gut have been proposed by various authors. Rolfe [19] states that the chemostat, or continuous-stirred tank reactor (CSTR), is likely the best system for the study of bacterial interactions, since complex population levels of several different organisms can be maintained. Freter and his