Miracle-dz/UniFAR-FTUs huggingface dataset:
Geometrothermodynamics of the Kehagias–Sfetsos black hole

The application of information geometric ideas to statistical mechanics using a metric on the space of states, as pioneered by Ruppeiner and Weinhold, has proved to be a useful alternative approach to characterizing phase transitions. Some puzzling anomalies become apparent, however, when these methods are applied to the study of black hole thermodynamics. A possible resolution was suggested by Quevedo et al who emphasized the importance of Legendre invariance in thermodynamic metrics. They found physically consistent results for various black holes when using a Legendre invariant metric, which agreed with a direct determination of the properties of phase transitions from the specific heat. Recently, information geometric methods have been employed by Wei et al to study the Kehagias–Sfetsos (KS) black hole in Hořava–Lifshitz gravity. The formalism suggests that a coupling parameter in this theory plays a role analogous to the charge in Reissner–Nordström black holes or angular momentum in the Kerr black hole and the calculation of the specific heat shows a singularity which may be interpreted as a phase transition. When the curvature of the Ruppeiner metric is calculated for such a theory, it does not, however, show a singularity at the phase transition point. We show that the curvature of a particular Legendre invariant (‘Quevedo’) metric for the KS black hole is singular at the phase transition point. We contrast the results for the Ruppeiner, Weinhold and Quevedo metrics and in the latter case investigate the consistency of taking either the entropy or mass as the thermodynamic potential.
Adversarial Attacks on Neural Network Policies

Machine learning classifiers are known to be vulnerable to inputs maliciously constructed by adversaries to force misclassification. Such adversarial examples have been extensively studied in the context of computer vision applications. In this work, we show adversarial attacks are also effective when targeting neural network policies in reinforcement learning. Specifically, we show existing adversarial example crafting techniques can be used to significantly degrade test-time performance of trained policies. Our threat model considers adversaries capable of introducing small perturbations to the raw input of the policy. We characterize the degree of vulnerability across tasks and training algorithms, for a subclass of adversarial-example attacks in white-box and black-box settings. Regardless of the learned task or training algorithm, we observe a significant drop in performance, even with small adversarial perturbations that do not interfere with human perception. Videos are available at this http URL.
Special Needs Teachers’ Perceptions on the Psychometric Test

In this survey a presentation of the difficulties of students with mild intellectual disabilities is performed. Intellectual disability is a neurodevelopment diagnosis and it refers to children who have developmental, adaptive behavioural and cognitive difficulties compared to their peers. Intellectual disabilities are categorized by their severity into: mild, moderate, severe, or profound. The purpose of this research is to construct a psychometric instrument for detecting intellectual disabilities in high school and specifically high school students aged 13-17. In order to find out if the specific psychometric test is appropriate to detect Intellectual disability, questionnaires have been given to special needs teachers. The research findings illustrate that the specific psychometric test is appropriate in order to detect intellectual disability.
Gene expression pattern Expression of three Rx homeobox genes in embryonic and adult zebrafish

The paired-class homeobox gene, Rx, is important in eye development. In this study we analyze expression patterns of three zebrafish Rx genes (Zrx1, 2, 3) in embryos and adults. All three genes show dynamic spatiotemporal patterns of expression. Zrx3 is expressed earliest, in the anteriormost region of the neural plate, in regions that give rise to ventral diencephalon and retinae. As development proceeds, Zrx3 expression is reduced in the lateral optic primordia, and is absent in the optic cup, but is retained at the ventral midline of the diencephalon, and is expressed in hypothalamus in the adult. As the neural retina begins to differentiate, Zrx3 is re-expressed in a subset of cells in the inner nuclear layer, presumably bipolar cells, and this expression is retained in the adult. In contrast, Zrx1/2 have a slightly later onset of expression, are initially coincident with Zrx3, but then become complementary, remaining on in the optic primordia but disappearing from the ventral midline of the diencephalon. Zrx1/2 are down-regulated as the retina differentiates, except in the outer nuclear layer where they continue to be expressed at high levels in cone, but not rod, photoreceptors. This is the first transcription factor described that distinguishes between cone and rod photoreceptors. q 1999 Elsevier Science Ireland Ltd. All rights reserved.
Region Based Adaptive Contrast Enhancement of Medical Ultrasound Images

Since the dawn of computerization of medical science, ultrasonic imaging has been an active research area and impacts important applications in the medical field. Ultrasound images have low contrast due to various artifacts. In most of the existing region growing contrast enhancement techniques, selection of seed point and threshold value is a challenging task. In this paper, an adaptive region based contrast enhancement technique based on the region growing segmentation concept is proposed. In the proposed work, automatic selection of seed point from the region of interest of an image is done followed by computation of threshold value to segment foreground and background pixels where the prime focus is to enhance foreground areas of an image. Qualitative and quantitative evaluation of the results of the proposed technique has been performed and results are very promising when compared with state-of-the-art techniques.
Mapping the Mechanome of Live Stem Cells Using a Novel Method to Measure Local Strain Fields In Situ at the Fluid-Cell Interface

During mesenchymal condensation, the initial step of skeletogenesis, transduction of minute mechanical forces to the nucleus is associated with up or down-regulation of genes, ultimately resulting in formation of the skeletal template and appropriate cell lineage commitment. The summation of these biophysical cues affects the cell's shape and fate. Here, we predict and measure surface strain, in live stem cells, in response to controlled delivery of stresses, providing a platform to direct short-term structure - function relationships and long-term fate decisions. We measure local strains on stem cell surfaces using fluorescent microbeads coated with Concanavalin A. During delivery of controlled mechanical stresses, 4-Dimensional (x,y,z,t) displacements of the bound beads are measured as surface strains using confocal microscopy and image reconstruction. Similarly, micro-particle image velocimetry (μ-piv) is used to track flow fields with fluorescent microspheres. The measured flow velocity gradient is used to calculate stress imparted by fluid drag at the surface of the cell. We compare strain measured on cell surfaces with those predicted computationally using parametric estimates of the cell's elastic and shear modulus. Finally, cross-correlating stress - strain data to measures of gene transcription marking lineage commitment enables us to create stress - strain - fate maps, for live stem cells in situ. The studies show significant correlations between live stem cell stress - strain relationships and lineage commitment. The method presented here provides a novel means to probe the live stem cell's mechanome, enabling mechanistic studies of the role of mechanics in lineage commitment as it unfolds.
Kinetic Models for Thermal Degradation of Strength of Fire-Retardant-Treated Wood

Several types of kinetics-based thermal degradation models were evaluated to predict strength loss of fire-retardant-treated wood as a function of cumulative thermal exposure. The data were taken from previous tests and reports on small, clear specimens of southern pine treated with six different fire-retardant chemicals and subjected to various durations of a steady-state exposure at different temperatures and relative humidity levels. We found that the single-stage full model approach was superior to traditional two-stage approaches. When constrained to using a two-stage approach, the best alternative two-stage model was a nonlinear model with additive error for each temperature, followed by a weighted regression across temperatures. The advantages of the nonlinear-weighted two-stage model were the maximized fit and more random error structure when compared to other two-stage models.
PARTICIPATION IN AFTERSCHOOL SPORT: RELATIONSHIP TO PERCEIVED NEED SUPPORT, NEED SATISFACTION, AND MOTIVATION IN PHYSICAL EDUCATION

The purpose of this study was to examine the differences in the perceptions of self-determination theory-based constructs such as the psychological needs support from the teacher and one’s peers, perceived satisfaction of the needs for competence, autonomy, relatedness, as well as different types of motivation in physical education among students with different organized afterschool sport experiences. Six hundred and fifty-nine Estonian secondary-school students completed questionnaires assessing the key variables of interest. Results indicated that boys who did afterschool sport scored significantly higher on perceived autonomy and relatedness support from the teacher and relatedness support from their peers, perceived satisfaction of the needs for autonomy, competence, and relatedness and external regulation than boys without afterschool sport experiences. Girls who did afterschool sport scored significantly higher on perceived competence and relatedness support from their peers as well as perceived satisfaction of the needs for autonomy and competence compared to girls without afterschool sport experiences.
An Adaptive Architecture for Hierarchical Vision Systems

We describe a machine learning architecture for hierarchical vision systems. These vision systems work by successively grouping visual constructs at one level, selecting the most promising, and passing them up to higher levels of processing. This continues from the pixel-level of the image to the object-model level. Traditionally, researchers have used static heuristics at each level to select the best constructs. In practice, this approach is brittle, because people have not been successful at surveying the evidence necessary for robust performance, and is static, because designers have not incorporated learning mechanisms that would let the system improve its performance with the aid of user feedback. The machine learning architecture proposed herein is an attempt to address both of these issues.
Gephi: An Open Source Software for Exploring and Manipulating Networks

Gephi is an open source software for graph and network analysis. It uses a 3D render engine to display large networks in real-time and to speed up the exploration. A flexible and multi-task architecture brings new possibilities to work with complex data sets and produce valuable visual results. We present several key features of Gephi in the context of interactive exploration and interpretation of networks. It provides easy and broad access to network data and allows for spatializing, filtering, navigating, manipulating and clustering. Finally, by presenting dynamic features of Gephi, we highlight key aspects of dynamic network visualization.
'Outside-in" Design for Interdisciplinary HRI Research

This paper introduces “outside-in design” as a collaborative approach to social robot design and human-robot interaction research. As an interdisciplinary group of social and computer scientists, we follow an iterative practice of collecting and analyzing data from realworld interaction, designing appropriate robotic perception and control mechanisms, developing models of interaction through automatic coding of behaviors and evaluation by human subjects, and validating the models in embodied human-robot interaction. We apply this approach in the context of shadow puppeteering, a constrained interaction space which allows us to study the foundational elements of synchronous interaction and apply them to a robot. We contribute to both social and computer sciences by combining the study of human social interaction with the design of socially responsive robot control algorithms. Interaction with robotic technologies in the real world poses both social and technical challenges. For a robot to collaborate seamlessly with humans in an everyday activity, it has to be situationally aware, able to take advantage of the human’s knowledge of the world, and adapt its behavior accordingly. To enable a socially interactive robot to perceive and display relevant social behaviors, designers must solve complex problems in real-time perception and control involving multiple mechanical and computational systems. Designing robots for social interaction also calls for expertise in analyzing social behavior to understand the factors that make people respond to robots as social actors. The challenges of social human-robot interaction suggest that it is difficult to neatly ‘divide and conquer’ social robot design through partial solutions bounded off within social and computational disciplines. This paper describes a collaborative practice bringing together computational and social expertise in the exploration and design of social human-robot interaction. We use an “outside-in” 1 design strategy, iterating between real
The Cricket Paralysis Virus Suppressor Inhibits microRNA Silencing Mediated by the Drosophila Argonaute-2 Protein

Small RNAs are potent regulators of gene expression. They also act in defense pathways against invading nucleic acids such as transposable elements or viruses. To counteract these defenses, viruses have evolved viral suppressors of RNA silencing (VSRs). Plant viruses encoded VSRs interfere with siRNAs or miRNAs by targeting common mediators of these two pathways. In contrast, VSRs identified in insect viruses to date only interfere with the siRNA pathway whose effector Argonaute protein is Argonaute-2 (Ago-2). Although a majority of Drosophila miRNAs exerts their silencing activity through their loading into the Argonaute-1 protein, recent studies highlighted that a fraction of miRNAs can be loaded into Ago-2, thus acting as siRNAs. In light of these recent findings, we re-examined the role of insect VSRs on Ago-2-mediated miRNA silencing in Drosophila melanogaster. Using specific reporter systems in cultured Schneider-2 cells and transgenic flies, we showed here that the Cricket Paralysis virus VSR CrPV1-A but not the Flock House virus B2 VSR abolishes silencing by miRNAs loaded into the Ago-2 protein. Thus, our results provide the first evidence that insect VSR have the potential to directly interfere with the miRNA silencing pathway.
An Empirical Study of Online Reputation System Continuance

Online reputation system (ORS) has caught great attention recently because it not only relieved the difficulties of information overload and purchase trust that consumers were facing in the online transaction, but facilitated and stimulated their online purchase willingness. Understanding the determinants of ORS continuance intention was thus crucial for professional ORS Websites in order to bring the ORS benefits into full play. Integrating with the construct of trust, a post- acceptance model of IS continuance was applied in this study. Samples were actual buyers randomly collected from the most famous and biggest e-marketplace in Taiwan, and 950 valid responses were received via the Web-questionnaire survey. Findings confirmed that consumers' disconfirmation towards ORS significantly and positively influenced their perceived usefulness, trust, satisfaction and ORS continuance intention. A critical practical alert was thus raised and suggestions in terms of ORS design and management were proposed for Website practitioners and managers.
Cross-Project Software Defect Prediction Using Feature-Based Transfer Learning

Cross-project defect prediction is taken as an effective means of predicting software defects when the data shortage exists in the early phase of software development. Unfortunately, the precision of cross-project defect prediction is usually poor, largely because of the differences between the reference and the target projects. Having realized the project differences, this paper proposes CPDP, a feature-based transfer learning approach to cross-project defect prediction. The core insight of CPDP is to (1) filter and transfer highly-correlated data based on data samples in the target projects, and (2) evaluate and choose learning schemas for transferring data sets. Models are then built for predicting defects in the target projects. We have also conducted an evaluation of the proposed approach on PROMISE datasets. The evaluation results show that, the proposed approach adapts to cross-project defect prediction in that f-measure of 81.8% of projects can get improved, and AUC of 54.5% projects improved. It also achieves similar f-measure and AUC as some inner-project defect prediction approaches.
Network Structure Shapes Spontaneous Functional Connectivity Dynamics

The structural organization of the brain constrains the range of interactions between different regions and shapes ongoing information processing. Therefore, it is expected that large-scale dynamic functional connectivity (FC) patterns, a surrogate measure of coordination between brain regions, will be closely tied to the fiber pathways that form the underlying structural network. Here, we empirically examined the influence of network structure on FC dynamics by comparing resting-state FC (rsFC) obtained using BOLD-fMRI in macaques (Macaca fascicularis) to structural connectivity derived from macaque axonal tract tracing studies. Consistent with predictions from simulation studies, the correspondence between rsFC and structural connectivity increased as the sample duration increased. Regions with reciprocal structural connections showed the most stable rsFC across time. The data suggest that the transient nature of FC is in part dependent on direct underlying structural connections, but also that dynamic coordination can occur via polysynaptic pathways. Temporal stability was found to be dependent on structural topology, with functional connections within the rich-club core exhibiting the greatest stability over time. We discuss these findings in light of highly variable functional hubs. The results further elucidate how large-scale dynamic functional coordination exists within a fixed structural architecture.
Earnings Management to Avoid Debt Covenant Violations and Future Performance

In this study, we examine the trade-offs between earnings management (both accruals and real) and covenant violations by examining how they are associated with future accounting and stock market performance. We analyze a matched-pair sample of covenant violation firms with non-violation firms that have a similar risk of a covenant violation. We have three main findings. First, our evidence indicates that covenant violations are costly events for shareholders as lenders appear to use their control rights in ways that increase the likelihood of loan repayment but impose costs for shareholders. Second, there is limited evidence indicating covenant-related accrual-earnings management activities impose significant costs on shareholders, but we find shareholders are worse off following unsuccessful real earnings management. Third, our evidence indicates that, on average, shareholders at high violation risk firms are better off when their firms successfully engage in accruals earnings management to avoid a violation compared to shareholders at firms that violate a covenant but do not manage earnings. Thus, covenant-related earnings management may be in the best interests of shareholders and is not necessarily evidence of shareholder-manager agency conflicts.
Design of spreading sequences with negative auto-correlations realizable by nonlinear feedback shift registers

Spreading sequences with a negative auto-correlation for time-delay one are designed based on the Bernoulli and tent maps which are well-known one-dimensional chaotic maps. We also show that maximal-period binary sequences with negative auto-correlation based on such maps with finite bits can be generated by a class of nonlinear feedback shift registers (NFSRs). Furthermore, we perform computer simulations of asynchronous DS/CDMA communications using such negatively auto-correlated spreading sequences.
Competitive Pressure and the Decline of the Rust Belt: A Macroeconomic Analysis

No region of the United States fared worse over the postwar period than the "Rust Belt," the heavy manufacturing region bordering the Great Lakes. This paper hypothesizes that the Rust Belt declined in large part due to a lack of competitive pressure in its labor and output markets. We formalize this thesis in a two-region dynamic general equilibrium model, in which productivity growth and regional employment shares are determined by the extent of competition. Quantitatively, the model accounts for much of the large secular decline in the Rust Belt's employment share before the 1980s, and the relative stabilization of the Rust Belt since then, as competitive pressure increased.
Microdomain Ca 2 (cid:49) Activation during Exocytosis in Paramecium Cells. Superposition of Local Subplasmalemmal Calcium Store Activation by Local Ca 2 (cid:49) Influx

In Paramecium tetraurelia , polyamine-trig-gered exocytosis is accompanied by the activation of Ca 2 (cid:49) -activated currents across the cell membrane (Erx-leben, C., and H. Plattner. 1994. J. Cell Biol. 127:935– 945). We now show by voltage clamp and extracellular recordings that the product of current (cid:51) time (As) closely parallels the number of exocytotic events. We suggest that Ca 2 (cid:49) mobilization from subplasmalemmal storage compartments, covering almost the entire cell surface, is a key event. In fact, after local stimulation, Ca 2 (cid:49) imaging with high time resolution reveals rapid, transient, local signals even when extracellular Ca 2 (cid:49) is quenched to or below resting intracellular Ca 2 (cid:49) concentration ([Ca 2 (cid:49) ] e (cid:60) [Ca 2 (cid:49) ] i ). Under these conditions, quenched-flow/freeze-fracture analysis shows that membrane fusion is only partially inhibited. Increasing [Ca 2 (cid:49) ] e alone, i.e., without secretagogue, causes rapid, strong cortical increase of [Ca 2 (cid:49) ] i but no exocytosis. In various cells, the ratio of maximal vs. minimal currents registered during maximal stimulation or single exocytotic events, respectively, correlate nicely with or mode, we could follow