Miracle-dz/UniFAR-FTUs huggingface dataset:
Complainant’s physical attractiveness and juristic judgments of blame and punishment in physical, domestic, and sexual assault scenarios

ABSTRACT Extralegal factors, including physical attractiveness, may bias juristic opinions. The present study provided 450 university students with hypothetical scenarios of physical, domestic, and sexual assault in which complainant’s attractiveness and other legal and extralegal characteristics were independently varied. Results indicate complainant’s attractiveness mattered in sexual assault scenarios only for guilt of the defendant, but not for physical or domestic assault. Complainant’s attractiveness was not related to perceptions of blameworthiness of complainant or punishment of defendant. Overall, legal factors of injury level, prior offending, and intoxication mattered more than attractiveness or race of the victim. Implications are discussed.
Nonthermal emission from clusters of galaxies

We show that the spectral and radial distribution of the nonthermal emission of massive, M>10^{14.5}M_sun, galaxy clusters (GCs) may be approximately described by simple analytic expressions, which depend on the GC thermal X-ray properties and on two model parameter, beta_{core} and eta_e. beta_{core} is the ratio of CR energy density (within a logarithmic CR energy interval) and the thermal energy density at the GC core, and eta_{e(p)} is the fraction of the thermal energy generated in strong collisionless shocks, which is deposited in CR electrons (protons). Using a simple analytic model for the evolution of ICM CRs, which are produced by accretion shocks (primary CRs), we find that beta_{core} ~ eta_{p}/200, nearly independent of GC mass and with a scatter Delta ln(beta_{core}) ~ 1 between GCs of given mass. We show that the HXR and gamma-ray luminosities produced by IC scattering of CMB photons by primary electrons exceed the luminosities produced by secondary particles (generated in hadronic interactions within the GC) by factors ~500(eta_e/eta_p)(T/10 keV)^{-1/2} and ~150(eta_e/eta_p)(T/10 keV)^{-1/2} respectively, where T is the GC temperature. Secondary particle emission may dominate at the radio and VHE (> 1 TeV) gamma-ray bands. Our model predicts, in contrast with some earlier work, that the HXR and gamma-ray emission from GCs are extended, since the emission is dominated at these energies by primary electrons. Our predictions are consistent with the observed nonthermal emission of the Coma cluster for eta_peta_e ~ 0.1. The implications of our predictions to future HXR observations (e.g. by NuStar, Simbol-X) and to (space/ground based) gamma-ray observations (e.g. by Fermi, HESS, MAGIC, VERITAS) are discussed. Finally, we show that our model's results agree with results of detailed numerical calculations.
Robust Construction of the Voronoi Diagram of a Polyhedron

This paper describes a practical algorithm for the construction of the Voronoi diagram of a three dimensional polyhedron using approximate arithmetic. This algorithm is intended to be implemented in oating point arithmetic. The full two-dimensional version and sig-niicant portions of the three-dimensional version have been implemented and tested. The running time 1 of this algorithm is O(npnv log 2 b), where np is the size of the input polyhedron, nv is the size of the output Voronoi diagram, and b is the number of desired bits of precision. This algorithm can be made more practical with the use of a binary partition of space. In the worst case, binary partition does not improve the running time, but it should reduce the running time to O(nvb) on well-behaved inputs. Since b is constant, this eliminates a factor of np. The algorithm can be generalized to higher dimensions and the order k Voronoi diagram.
Strengthening Exercises Improve Symptoms and Quality of Life but Do Not Change Autonomic Modulation in Fibromyalgia: A Randomized Clinical Trial

Objective Autonomic dysfunction is an important mechanism that could explain many symptoms observed in fibromyalgia (FM). Exercise is an effective treatment, with benefits potentially mediated through changes in autonomic modulation. Strengthening is one of the less studied exercises in FM, and the acute and chronic effects of strengthening on the autonomic system remain unknown. The objective of this study was to assess the chronic effects of strengthening exercises (STRE) on autonomic modulation, pain perception and the quality of life (QOL) of FM patients. Methods Eighty sedentary women with FM (ACR 1990) were randomly selected to participate in STRE or flexibility (FLEX) exercises in a blinded controlled trial. The intensity of STRE was set at 45% of the estimated load of 1 Repetition Maximum (RM) in 12 different exercises. Outcomes were Visual Analog Scale (VAS) for pain, Heart Rate Variability (HRV) analysis, treadmill test, the sit and reach test (Wells and Dillon’s Bench), maximal repetitions test and handgrip dynamometry; and quality of life by the Fibromyalgia Impact Questionnaire (FIQ), the Beck and Idate Trait-State Inventory (IDATE), a short-form health survey (SF-36). Results The STRE group was more effective to strength gain for all muscles and pain control after 4 and 16 weeks (p<0.05). The FLEX group showed higher improvements in anxiety (p<0.05). Both groups showed improvements in the QOL, and there was no significant difference observed between the groups. There was no change in the HRV of the STRE and FLEX groups. Conclusions Strengthening exercises show greater and more rapid improvements in pain and strength than flexibility exercises. Despite the benefits in fitness, pain, depression, anxiety and quality of life, no effect was observed on the autonomic modulation in both groups. This observation suggests that changes in autonomic modulation are not a target tobe clinically achieved in fibromyalgia. Trial Registration ClinicalTrials.gov NCT02004405
Membrane potential-dependent binding of polysialic acid to lipid monolayers and bilayers

Polysialic acids are linear polysaccharides composed of sialic acid monomers. These polyanionic chains are usually membrane-bound, and are expressed on the surfaces of neural, tumor and neuroinvasive bacterial cells. We used toluidine blue spectroscopy, the Langmuir monolayer technique and fluorescence spectroscopy to study the effects of membrane surface potential and transmembrane potential on the binding of polysialic acids to lipid bilayers and monolayers. Polysialic acid free in solution was added to the bathing solution to assess the metachromatic shift in the absorption spectra of toluidine blue, the temperature dependence of the fluorescence anisotropy of DPH in liposomes, the limiting molecular area in lipid monolayers, and the fluorescence spectroscopy of oxonol V in liposomes. Our results show that both a positive surface potential and a positive transmembrane potential inside the vesicles can facilitate the binding of polysialic acid chains to model lipid membranes. These observations suggest that these membrane potentials can also affect the polysialic acid-mediated interaction between cells.
Annual hydroclimatology of the United States

An overview of the annual hydroclimatology of the United States is provided. Time series of monthly streamflow, temperature, and precipitation are developed for 1337 watersheds in the United States. This unique data set is then used to evaluate several approaches for estimating the long‐term water balance and the interannual variability of streamflow. Traditional relationships which predict either actual evapotranspiration or the interannual variability of streamflow from an aridity index are shown to perform poorly for basins with low soil moisture storage capacity. A water balance model is used to formulate new relationships for predicting actual evapotranspiration and the interannual variability of streamflow. These relationships depend on both the aridity index and a new soil moisture storage index. A physically based approach for estimating the soil moisture storage index is introduced which requires monthly time series of precipitation, potential evapotranspiration, and an estimate of maximum soil moisture holding capacity. The net results are improved expressions for the long‐term water balance and the interannual variability of streamflow which do not require either calibration or streamflow data.
TIPMerge: recommending experts for integrating changes across branches

Parallel development in branches is a common software practice. However, past work has found that integration of changes across branches is not easy, and often leads to failures. Thus far, there has been little work to recommend developers who have the right expertise to perform a branch integration. We propose TIPMerge, a novel tool that recommends developers who are best suited to perform merges, by taking into consideration developers’ past experience in the project, their changes in the branches, and de-pendencies among modified files in the branches. We evaluated TIPMerge on 28 projects, which included up to 15,584 merges with at least two developers, and potentially conflicting changes. On average, 85% of the top-3 recommendations by TIPMerge correctly included the developer who performed the merge. Best (accuracy) results of recommendations were at 98%. Our inter-views with developers of two projects reveal that in cases where the TIPMerge recommendation did not match the actual merge developer, the recommended developer had the expertise to per-form the merge, or was involved in a collaborative merge session.
Estimation of B-spline Nonparametric Regression Models using Information Criteria

Nonparametric regression modelling has received considerable attention and many methods have been proposed to draw information from data with complex structure. We consider the use of B-spline nonparametric regression models estimated by penalized likelihood methods. A crucial point in constructing the models is in the choice of a smoothing parameter and the number of knots, for which several attempts have been made by using cross-validation and Akaike's (1973) information criterion. We investigate this problem from information-theoretic point of view, and introduce a criterion for evaluating B-spline nonparametric regression models in the context of generalized linear models. The proposed criterion is applied to choose the optimal value of a smoothing parameter and the number of knots. We compare various types of criteria to examine their properties, using Monte Carlo simulations.
Modal Specifications for Probabilistic Timed Systems

Modal automata are a classic formal model for component-based systems that comes equipped with a rich specification theory supporting abstraction, refinem ent and compositional reasoning. In recent years, quantitative variants of modal automata were introduced for specifying and reasoning about component-based designs for embedded and mobile systems. These respectively generalize modal specification theories for timed and probabilistic sy stems. In this paper, we define a modal specification language for combined probabilistic timed sy stems, called abstract probabilistic timed automata, which generalizes existing formalisms. We introduce appropriate syntactic and semantic refinement notions and discuss consistency of our specificat ion language, also with respect to timedivergence. We identify a subclass of our models for which we define the fundamental operations for
Cortical Geometry Network and Topology Markers for Parkinson's Disease

Neurodegeneration affects cortical gray matter leading to loss of cortical mantle volume. As a result of such volume loss, the geometrical arrangement of the regions on the cortical surface is expected to be altered in comparison to healthy brains. Here we present a novel method to study the alterations in brain cortical surface geometry in Parkinson's disease (PD) subjects with a \emph{Geometry Networks (GN)} framework. The local geometrical arrangement of the cortical surface is captured as the 3D coordinates of the centroids of anatomically defined parcels on the surface. The inter-regional distance between cortical patches is the signal of interest and is captured as a geometry network. We study its topology by computing the dimensionality of simplicial complexes induced on a filtration of binary undirected networks for each geometry network. In a permutation statistics test, a statistically significant ($p<0.05$) difference was observed in the homology features between PD and healthy control groups highlighting its potential to differentiate between the groups and their potential utility in disease diagnosis.
A robust speech endpoint detection algorithm based on wavelet packet and energy entropy

The robust speech endpoint detection is important in many areas of speech processing. In this work, a robust speech endpoint detection algorithm is proposed based on wavelet packet and energy entropy. The proposed method is tested using speech utterances under four different background noise: White, Pink, Babble and Volvo with different SNR (-5db, 0db, 10db, 20db). The results are compared with traditional short-time energy plus short-time zero crossing rate method. The experiment results indicate that the presented algorithm achieve higher endpoint detection accuracies than traditional method. The correct detection rates reach up to 97.5% for noise-free speech, and range from 80.72% to 93.87% according to different types of background noise.
Non-LTE line formation for heavy elements in four very metal-poor stars

Aims. Stellar parameters and abundances of Na, Mg, Al, K, Ca, Sr, Ba, and Eu are determined for four very metal-poor (VMP) stars (−2.15 ≥ [Fe/H] ≥− 2.66). For two of them, HD 84937 and HD 122563, the fraction of the odd isotopes of Ba derived for the first time. Methods. Determination of an effective temperature, surface gravity, and element abundances was based on non-local thermodynamic equilibrium (non-LTE) line formation and analysis of high-resolution (R ∼ 60 000 and 90 000) high signal-to-noise (S/N ≥ 200) observed spectra. A model atom for H i is presented. An effective temperature was obtained from the Balmer Hα and Hβ line wing fits. The surface gravity was calculated from the Hipparcos parallax if available and the non-LTE ionization balance between Ca i and Ca ii. Based on the hyperfine structure affecting the Ba ii resonance line λ 4554, the fractional abundance of the odd isotopes of Ba was derived from a requirement that Ba abundances from the resonance line and subordinate lines of Ba ii must be equal. Results. For each star, non-LTE leads to a consistency of Teff from two Balmer lines and to a higher temperature compared to the LTE case, by up to 60 K. Non-LTE effects are important in spectroscopic determination of surface gravity from the ionization balance between Ca i and Ca ii. For each star with a known trigonometric surface gravity, non-LTE abundances from the lines of two ionization stages, Ca i and Ca ii, agree within the error bars, while a difference in the LTE abundances consists of 0.23 dex to 0.40 dex for different stars. Departures from LTE are found to be significant for all investigated atoms, and they strongly depend on stellar parameters. For HD 84937, the Eu/Ba ratio is consistent with the relative solar system r-process abundances, and the fraction of the odd isotopes of Ba, fodd, equals 0.43 ± 0.14. The latter can serve as an observational constraint on r-process models. The lower Eu/Ba ratio and fodd = 0.22 ± 0.15 found for HD 122563 suggest that the s-process or the unknown process has contributed significantly to the Ba abundance in this star.
TANGLED WEBS Evolutionary Dynamics on Fitness Landscapes with Neutrality

3 After a while your adversaries and competitors will give up trying to think of alternative hypotheses, or else will grow old and die, and then your hypothesis will become accepted. Sounds crazy, we know, but that's how science works! -Numerical Recipes in C Abstract The bulk of research on the dynamics of populations of genotypes evolving on fitness landscapes has concentrated on the rôle of correlation and landscape ruggedness as a putative indicator of the qualitative dynamics. There is, however, a small but growing awareness amongst population geneticists (through Motoo Kimura's Neutral Theory of molecular evolution [16, 3]) and molecular biologists (Eigen, Schuster, et. al.[5, 2, 18]) of the importance of neutral mutation as a significant factor in evolutionary dynamics. This awareness has thus far not extended to the GA community. Of particular interest is the notion of neutral networks of selectively neutral genotypes which percolate a fitness landscape-recent work on RNA folding landscapes characterises their structure in terms of There is at present a lack of computationally tractable abstract models demonstrating neutrality. In this paper we introduce two parametrised families of abstract landscapes: the NKp landscapes, based on the NK family of abstract landscapes [15], allow tuning of the degree of neutrality whilst leaving invariant the auto-correlation function [24, 23, 15]. The RNN (Random Neutral Network) landscapes, constructed by mutually-avoiding random walks, feature percolating neutral networks of specifiable size and neutral dimension. The statistical structure of these landscapes is examined and related to the characteristic dynamics of populations evolving on them. Several conjectures regarding the auto-correlation function on NKp landscapes (relevant also to NK landscapes) are raised. Attention is drawn to the very different nature of population dynamics on landscapes with percolating neutral networks as compared to the dynamics on rugged multi-peaked landscapes. Qualitative similarities between population dynamics on RNN landscapes and RNA folding landscapes are highlighted. Finally, implications for biological research and for the application of GA's to optimisation problems are discussed.
The Cost of Uncore in Throughput-Oriented Many-Core Processors

Achieving performance through traditional techniques such as extracting more instruction level parallelism or increasing clock frequencies are losing their effectiveness due to the power wall. Multi-core processors have been put forth as a more power-performance efficient means of continuing performance scaling while coping with the realities of a power-limited design. Extrapolating the increase in the number of cores leads us to “many-core” systems, potentially containing hundreds of cores. The multi-/many-core approach is no panacea, however. As the number of cores increases, the overall system will need to provide more cache resources to feed all of these cores, and an everincreasingly complex interconnection network to tie all of these cores together. These additional “uncore” components are not free, and, unless carefully controlled, they may limit the effectiveness of many-core systems. We introduce a simple extension to Hill and Marty’s recent Amdahl’s Lawbased multi-core cost/performance model to account for the uncore components. From this model, we conclude that to sustain the scalability of future many-core systems, the uncore components must be designed to scale sub-linearly with respect to the overall core count.
Extracting Protein Names from Biological Literature

Name entity recognition is an essential task in extracting biological knowledge. In biological corpus, protein names and other terminologies are mixed in natural language sentences. Sometimes whether an abbreviation is a protein name or not depends on the context. Protein names are often composed of gene names, cell names, or even drug names. Moreover, the number of newly coined protein names is increasing. Even with the assistance of a dictionary, it is still hard to correctly automatically identify all protein names in a biological corpus. We modify a hierarchical model of protein name tokens. On the one hand, we choose rule-base method to improve protein name recognition prediction accuracy rate. On the other hand, we use the N-gram language model to determine the boundary of protein name. Numerous studies mentioned that the hardest part is to identify abbreviations and words beginning with uppercase. In order to enhance the recognition performance, we use a dictionary to strengthen recognition for abbreviations and words beginning with uppercase. Experimental results show that about 10% increase in performance.We use YAPEX corpus and GENIA corpus datasets for experiment. In our study, an F-score can achieve 0.697 on the YAPEX corpus and 0.691 on the GENIA corpus. Finally, strengthening the abbreviation for part recognition, we use the Uniprot dictionary database to recognize, an F-score can achieve 0.797 on the YAPEX corpus and 0.806 on the GENIA corpus.
Wavelet Thresholding with Bayesian False Discovery Rate Control

Summary The false discovery rate (FDR) procedure has become a popular method for handling multiplicity in high‐dimensional data. The definition of FDR has a natural Bayesian interpretation; it is the expected proportion of null hypotheses mistakenly rejected given a measure of evidence for their truth. In this article, we propose controlling the positive FDR using a Bayesian approach where the rejection rule is based on the posterior probabilities of the null hypotheses. Correspondence between Bayesian and frequentist measures of evidence in hypothesis testing has been studied in several contexts. Here we extend the comparison to multiple testing with control of the FDR and illustrate the procedure with an application to wavelet thresholding. The problem consists of recovering signal from noisy measurements. This involves extracting wavelet coefficients that result from true signal and can be formulated as a multiple hypotheses‐testing problem. We use simulated examples to compare the performance of our approach to the Benjamini and Hochberg (1995, Journal of the Royal Statistical Society, Series B57, 289–300) procedure. We also illustrate the method with nuclear magnetic resonance spectral data from human brain.
A system for aircraft recognition in perspective aerial images

Recognition of aircraft in complex, perspective aerial imagery has to be accomplished in presence of clutter, occlusion, shadow, and various forms of image degradation. This paper presents a system for aircraft recognition under real-world conditions that is based on the use of a hierarchical database of object models. The particular approach involves three key processes: (a) The qualitative object recognition process performs model-based symbolic feature extraction and generic object recognition; (b) The refocused matching and evaluation process refines the extracted features for more specific classification with input from (a); and (c) The primitive feature extraction process regulates the extracted features based on their saliency and interacts with (a) and (b). Experimental results showing the qualitative recognition of aircraft in perspective, aerial images are presented. <<ETX>>
Test Generation for Combinational Quantum Cellular Automata (QCA) Circuits

In this paper, we present a test generation framework for testing of quantum cellular automata (QCA) circuits. QCA is a nanotechnology that has attracted significant recent attention and shows immense promise as a viable future technology. This work is motivated by the fact that the stuck-at fault test set of a circuit is not guaranteed to detect all defects that can occur in its QCA implementation. We show how to generate additional test vectors to supplement the stuck-at fault test set to guarantee that all simulated defects in the QCA gates get detected. Since nanotechnologies will be dominated by interconnects, we also target bridging faults on QCA interconnects. The efficacy of our framework is established through its application to QCA implementations of MCNC benchmarks that use majority gates as primitives