Miracle-dz/UniFAR-FTUs huggingface dataset:
The “News Web Easy” news service as a resource for teaching and learning Japanese: An assessment of the comprehension difficulty of Japanese sentence-end expressions

Japan’s public broadcasting corporation, NHK, launched “News Web Easy” in April 2012 1 . It provides users with five simplified news scripts (easy Japanese news) on a daily basis. This web service provides users with five daily simplified news scripts of “easy” Japanese news. Since its inception, this service has been favorably received both in Japan and overseas. Users particularly appreciate its value as a Japanese learning and teaching resource. In this paper, we discuss this service and its possible contribution to language education. We focus on difficulty levels of sentence-end expressions, compiled from the news, that create ambiguity and problems when rewriting news items. These are analyzed and compared within regular news and News Web Easy, and their difficulty is assessed based on Japanese learners’ reading comprehension levels. Our results revealed that current rewriting of sentence-end expressions in News Web Easy is appropriate. We further identified features of these expressions that contribute to difficulty in comprehension.
Identification of Calcineurin as a Key Signal in the Extinction of Fear Memory

Memory extinction refers to a gradual decrease of the previously acquired response when exposed to conditional stimulus without pairing with unconditional stimulus. Here we show for the first time that fear training-induced phosphorylation of specific substrates in the rat amygdala is reduced after extinction trials and is accompanied by an increase in the protein level and enzymatic activity of calcineurin. In parallel, calcineurin inhibitors prevented extinction-induced protein dephosphorylation as well as extinction of fear memory. Thus, extinction training increased phosphatase activity likely via an expression of calcineurin. Calcineurin then created a negative-feedback loop and directly or indirectly dephosphorylated specific substrates, which, in their phosphorylated state, were required for memory consolidation. Accordingly, in our experimental condition, extinction could be ascribed at least in part to a weakening of the original signaling.
Evidence for Broad Versus Segregated Projections from Cholinergic and Noradrenergic Nuclei to Functionally and Anatomically Discrete Subregions of Prefrontal Cortex

The prefrontal cortex (PFC) is implicated in a variety of cognitive and executive operations. However, this region is not a single functional unit; rather, it is composed of several functionally and anatomically distinct networks, including anterior cingulate cortex (ACC), medial prefrontal cortex (mPFC), and orbitofrontal cortex (OFC). These prefrontal subregions serve dissociable behavioral functions, and are unique in their afferent and efferent connections. Each of these subregions is innervated by ascending cholinergic and noradrenergic systems, each of which likewise has a distinct role in cognitive function; yet the distribution and projection patterns of cells in the source nuclei for these pathways have not been examined in great detail. In this study, fluorescent retrograde tracers were injected into ACC, mPFC, and OFC, and labeled cells were identified in the cholinergic nucleus basalis of Meynert (NBM) and noradrenergic nucleus locus coeruleus (LC). Injections into all three cortical regions consistently labeled cells primarily ipsilateral to the injection site with a minimal contralateral component. In NBM, retrogradely labeled neurons were scattered throughout the rostral half of the nucleus, whereas those in LC tended to cluster in the core of the nucleus, and were rarely localized within the rostral or caudal poles. In NBM, more than half of all retrogradely labeled cells possessed axon collaterals projecting two or more PFC subregions. In LC, however, only 4.3% of retrogradely labeled neurons possessed collaterals targeting any two prefrontal subregions simultaneously, and no cells were identified that projected to all three regions. Of all labeled LC neurons, 49.3% projected only to mPFC, 28.5% projected only to OFC, and 18.0% projected only to ACC. These findings suggest that subsets of LC neurons may be capable of modulating neuronal activity in individual prefrontal subregions independently, whereas assemblies of NBM cells may exert a more unified influence on the three areas, simultaneously. This work emphasizes unique aspects of the cholinergic and noradrenergic projections to functionally and anatomically distinct subregions of PFC and provides insights regarding global versus segregated regulation of prefrontal operations by these neuromodulatory pathways.
Automated Choreographer Synthesis for Web Services Composition Using I/O Automata

We study the problem of synthesis of a choreographer in Web service composition for a given set of services and a goal. Services and goal are represented using I/O automata which can succinctly and precisely describe the interfaces of the services. Our technique considers existence and synthesis of two types of the choreographers: a simple choreographer capable of only relaying outputs from one service to input of another and a transducing choreographer which is capable of storing and reusing inputs/outputs from the services. The central theme of our technique relies on generating I/O automata representation of all possible choreographed behavior of existing services (captured in form of universal service automaton, a concept introduced in this paper) and verifying that the goal can be simulated by the universal set of choreographed behaviors.
Effects of prior acute exercise on circulating cytokine concentration responses to a high-fat meal

High‐fat meal consumption alters the circulating cytokine profile and contributes to cardiometabolic diseases. A prior bout of exercise can ameliorate the triglyceride response to a high‐fat meal, but the interactive effects of exercise and high‐fat meals on cytokines that mediate cardiometabolic risk are not fully understood. We investigated the effects of prior exercise on the responses of circulating tumor necrosis factor‐α (TNF‐α), interleukin‐6 (IL‐6), IL‐8, leptin, retinol‐binding protein 4 (RBP4), vascular endothelial growth factor (VEGF), basic fibroblast growth factor (bFGF), placental growth factor (PlGF), and soluble fms‐like tyrosine kinase‐1 (sFlt‐1) to a high‐fat meal. Ten healthy men were studied before and 4 h after ingestion of a high‐fat meal either with or without ~50 min of endurance exercise at 70% of VO2 max on the preceding day. In response to the high‐fat meal, lower leptin and higher VEGF, bFGF, IL‐6, and IL‐8 concentrations were evident (P < 0.05 for all). There was no effect of the high‐fat meal on PlGF, TNF‐α, or RBP4 concentrations. We found lower leptin concentrations with prior exercise (P < 0.05) and interactive effects of prior exercise and the high‐fat meal on sFlt‐1 (P < 0.05). The high‐fat meal increased IL‐6 by 59% without prior exercise and 218% with prior exercise (P < 0.05). In conclusion, a prior bout of endurance exercise does not affect all high‐fat meal–induced changes in circulating cytokines, but does affect fasting or postprandial concentrations of IL‐6, leptin, and sFlt‐1. These data may reflect a salutary effect of prior exercise on metabolic responses to a high‐fat meal.
Mutant Prevention Concentration-Based Pharmacokinetic/Pharmacodynamic Indices as Dosing Targets for Suppressing the Enrichment of Levofloxacin-Resistant Subpopulations of Staphylococcus aureus

ABSTRACT MIC- and mutant prevention concentration (MPC)-based pharmacokinetic/pharmacodynamic (PK/PD) indices were compared for suitability as attainment targets for restricting amplification of levofloxacin-resistant mutant subpopulations. When three Staphylococcus aureus strains were examined with a hollow-fiber PK/PD model, area under the concentration-time curve over 24 h (AUC24)/MPC values of >25 and maximum concentration of drug in serum (Cmax)/MPC values of >2.2 predicted resistance outcome among different isolates with an interisolate kappa coefficient of 1. MIC-based mutant-restrictive PK/PD values varied >8-fold and exhibited only a moderate interisolate agreement (kappa coefficient of 0.5). Thus, MPC-based PK/PD indices are more suitable than MIC-based indices for predicting mutant-restricting fluoroquinolone doses when multiple bacterial isolates are considered.
Distributed Privacy-Aware Fast Selection Algorithm for Large-Scale Data

Finding the <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives> <inline-graphic xlink:href="chen-ieq1-2761344.gif"/></alternatives></inline-formula> smallest/largest element of a large array, i.e., <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives> <inline-graphic xlink:href="chen-ieq2-2761344.gif"/></alternatives></inline-formula>-selection is a fundamental supporting algorithm in data analysis. Due to the fact that big data born in geo-distributed environments, it especially requires communication-efficient distributed <inline-formula><tex-math notation="LaTeX">$k$</tex-math> <alternatives><inline-graphic xlink:href="chen-ieq3-2761344.gif"/></alternatives></inline-formula>-selection, besides typical computation and memory efficiency. Moreover, sensitive organizations make data privacy a rigorous precondition for their participation in such distributed statistical analysis for common profit. To this end, we propose a <italic> Distributed Privacy-Aware Median (DPAM) selection algorithm</italic> for median selection in distributed large-scale data while preserving local statistics privacy, and extend it to arbitrary <inline-formula><tex-math notation="LaTeX"> $k$</tex-math><alternatives><inline-graphic xlink:href="chen-ieq4-2761344.gif"/></alternatives></inline-formula> -selection. DPAM utilizes mean to approximate median, via contraction of the standard deviation. It is the theoretical fastest with a worst computation complexity of <inline-formula><tex-math notation="LaTeX">$\mathcal{O}(N)$</tex-math> <alternatives><inline-graphic xlink:href="chen-ieq5-2761344.gif"/></alternatives></inline-formula>, and also highly efficient in communication overhead (in logarithm of data range). To preserve <inline-formula> <tex-math notation="LaTeX">$\epsilon$</tex-math><alternatives><inline-graphic xlink:href="chen-ieq6-2761344.gif"/> </alternatives></inline-formula>-differential privacy of local statistics, DPAM randomly adds dummy elements (the number follows a rounded Laplacian distribution) to local data. The noise does not degrade the estimation precision or convergence rate. Performance of DPAM is compared with centralized/distributed quick select and optimization, in terms of complexity and privacy preserving ability. Extensive simulation and experiment results show the higher efficiency of DPAM.
Spectral analysis of Bragg gratings written in fluid-infiltrated photonic crystal fibers

The guiding properties of Bragg gratings inscribed in solid core photonic crystal fibers (PCFs) are investigated theoretically using a full vectorial Multipole Method combined with closed form expressions for the reflection response of the Bragg fiber gratings. When the PCF air-holes are infiltrated with different fluids, a downward shift is observed in the power reflectivity spectra. Both relative Bragg shift and grating's bandwidth depend linearly on the effective refractive index which supports the potential use of such photonic crystal fiber Bragg grating (PCFBG) as optofluidic refractive index sensor as well as tunable filter. The influence of the structural parameters of the PCF on the sensitivity and bandwidth of the Bragg grating is also investigated.
Within-class penalty based multi-class support vector machine

Support vector machine (SVM) is a widely used maximum margin classifier, but the classification performance is largely affected by outliers. In this paper, we propose a novel multi-class SVM method to reduce the influence of outliers on the classification performance. Our proposed method includes an efficient optimization model via considering the within-class scatter and an optimization way. Specifically, the method is based on one assumption that penalizing the within-class scatter can reduce the number of misclassified outliers near the decision boundary, because data points of each class could be compacted by the within-class penalty. Experiments on benchmark databases demonstrate the effectiveness of the assumption and the proposed method.
Cardiovascular response to physical exercise in adult patients after atrial correction for transposition of the great arteries assessed with magnetic resonance imaging

Objective: To assess with magnetic resonance imaging (MRI) cardiovascular function in response to exercise in patients after atrial correction of transposition of the great arteries (TGA). Methods: Cardiac function at rest and during submaximal exercise was assessed with MRI in 27 patients with TGA (mean (SD) age 26 (5) years) late (23 (2) years) after atrial correction and in 14 control participants (25 (5) years old). Results: At rest, only right ventricular ejection fraction was significantly lower in patients than in controls (56 (7)% v 65 (7)%, p < 0.05). In response to exercise, increases in right ventricular end diastolic (155 (55) ml to 163 (57) ml, p < 0.05) and right ventricular end systolic volumes (70 (34) ml to 75 (36) ml, p < 0.05) were observed in patients. Furthermore, right and left ventricular stroke volumes and ejection fraction did not increase significantly in patients. Changes in right ventricular ejection fraction with exercise correlated with diminished exercise capacity (r = 0.43, p < 0.05). Conclusions: In patients with atrially corrected TGA, MRI showed an abnormal response to exercise of both systemic right and left ventricles. Exercise MRI provides a tool for close monitoring of cardiovascular function in these patients, who are at risk for late death.
Improved scalar transport for unstructured finite volume methods using simplex superposition

The application of second-order finite volume methods to large eddy simulation (LES) is becoming increasingly common. Finite volume methods support the complex geometries associated with most problems of engineering interest, and are also relatively efficient. When finite volume methods are applied to LES, it is common to use symmetric (central difference) discretizations of the convective term in the momentum equations. This reduces the numerical dissipation of the scheme and, for certain discretization choices, leads to a discrete equivalent of kinetic energy conservation in the inviscid, incompressible limit (Mahesh et al. 2004; Ham & Iaccarino 2004). When additional scalars are required (for energy, temperature, species transport, etc.), however, the analogous scalar energy conservation (in the limit of zero diffusion) is normally disregarded, and the associated convective terms are discretized with much more dissipative upwind approaches. This is true even for finite volume methods on high quality structured grids – see for example Pierce & Moin (2004). The reason for this discrepency is that the large dispersion errors associated with second-order central difference scalar transport lead to unacceptable scalar oscillations, often outside of their physical bounds – e.g. negative mixture fractions. Present sub-grid scale models for turbulent diffusion appear unable to address this problem adequately, and dissipative convective discretizations will likely be the norm until models can be improved or dispersion errors reduced. In the present brief, we develop a solution to this problem by presenting a second-order finite volume scheme for general polyhedral grids with significantly reduced dispersion errors. This reduction in error is achieved, in part, by discretizing the time term using a consistent, non-diagonal mass matrix, similar to that used by the Galerkin finite element method with linear elements. The details of the spatial discretization and the production of an appropriate consistent mass matrix for grids of arbitrary polyhedra can be accomplished using the approach of “simplex superposition” described in this brief.
Standard and pegylated interferon therapy of HDV infection: A systematic review and meta- analysis

Background: Hepatitis D virus (HDV) infection is characterized by rapidly progressive liver disease with adverse prognosis in most patients. Although interferon is the only approved anti-HDV therapy, evidence regarding the efficacy and safety of its various regimens is either old or scattered. Materials and Methods: We searched systematically Medline, EMBASE, Scopus, the Cochrane Central Register of Controlled Trials, and ISI. The studies that evaluated treatment of chronic HDV infection with standard or pegylated interferon for at least 48 weeks were identified. Our inclusion criteria were positive anti-HDV antibody for 6 months and positive HDV-PCR at the start of study. We performed a meta-analysis for proportions using the arcsine transformation in random effects model. Sustained virological response (SVR) rate (negative Polymerase chain reaction (PCR) 6 months after cessation of therapy) was the end point of interest. Results: Data were abstracted from 14 studies containing 227 chronic HDV-infected patients who received standard or pegylated interferon alpha-2a or -2b. Twenty-one and 30 patients of 71 and 156 who received standard or peginterferon, respectively, beyond 48 weeks achieved SVR. Pooled SVR rates were 29% [95% confidence interval (CI) 19; 41] and 19% (95% CI 10; 29), respectively. The rates of treatment withdrawal were similar. Conclusion: Our systematic review indicates that the literature lacks sufficient evidence to establish precise recommendations for treatment of HDV infection. Meta-analysis of these studies shows that standard dose of peginterferon is more effective than high dose of standard interferon as anti-HDV therapy.
Cognitive deficits in Tsc1+/−mice in the absence of cerebral lesions and seizures

Tuberous sclerosis complex (TSC) is characterized by brain lesions, epilepsy, increased incidence of mental retardation and autism. The causal link between lesion load and epilepsy on cognitive disabilities has been debated, and these factors explain only part of the intelligence quotient variability. A Tsc2 rat model of the disease provided evidence that the TSC genes are directly involved in neuronal function. However, these lesion‐ and epilepsy‐free animals did not show learning deficits, leaving open the possibility that the presence of brain lesions or epilepsy is a prerequisite for the cognitive deficits to fully develop. Here, we reinvestigated the relation among cerebral lesions, epilepsy, and cognitive function using Tsc1+/−mice.
Integrating Semantic Directional Relationships into Virtual Environments: A Meta-modelling Approach

This study is concerned with semantic modelling of virtual environments (VEs). A semantic model of a VE provides an abstract and high level representation of main aspects of the environment: ontological structures, behaviours and interactions of entities, etc. Furthermore, such a semantic model can be explored by artificial agents to exhibit human-like behaviours or to assist users in the VE. Previous research focused on formalising a knowledge layer that is a conceptual representation of scene content or application's entities. However, there still lacks of a semantic representation of spatial knowledge. This paper proposes to integrate a semantic model of directional knowledge into VEs. Such a directional model allows to specify relationships such as "left", "right", "above" or "north", "south" that are critical in many applications of VEs (e.g., VEs for training, navigation aid systems). We focus particularly on modelling, computing, and visualising directional relationships. First, we propose a theoretical model of direction in VEs that enables the specification of direction both from a first- and third-person perspective. Second, we propose a generic architecture for modelling direction in VEs using a meta-modelling approach. Directional relationships are described in a qualitative manner and at a conceptual level, and thus are abstract from metrical details of VEs. Finally, we show how our semantic model of direction can be used in a cultural heritage application to specify behaviours of artificial agents and to visualise directional constraints.
A Comparison of Preferred Learning Styles, Approaches and Methods between Information Science and Computing Science Undergraduates

Abstract In recent years the two disciplines of Information and Library Studies and Computing Science have drawn closer together to the extent that now there are several Universities where they are combined in a single school of Information and Computing Science or Informatics. Currently, a single Higher Education Academy Subject Centre serves the two disciplines. However, there are marked differences between the disciplines observable immediately in the gender balance of their respective undergraduate cohorts with Computer Science tending to attract males and Information Science, females. This project set out to investigate other less obvious differences by means of an online survey of first year undergraduates’ preferred learning styles, approaches to study and learning environments. 134 first year undergraduates from 6 UK Universities took part in the online survey and results showed that, whilst there was a clear gender imbalance between Computing Science with its almost entirely male population and Information Science with its mostly female population, differences in learning styles and approaches were less clear. There was a wide variety of individual learning styles and approaches in the sample population and it would not be safe to conclude that any one approach would meet the needs of an entire cohort of Information or Computer Scientists as, whenever an overall tendency appeared, there was always a small but significant group who had an opposite preference. Differences in preferred learning methods were clearer. More than twice as many Information Scientists than Computer Scientists preferred talking and discussing as a method of learning whereas Computer Scientists were significantly more likely than Information Scientists (p<.05) to prefer solving problems. Neither group enjoyed reading from journals or lectures. Two key teaching points for lecturers to note arose in the study; the use of advance organisers in teaching both on and offline and the need to prepare students for and support them in the use of journals.
Modeling Content from Human-Verified Blacklists for Accurate Zero-Hour Phish Detection

Abstract : Phishing attacks are a significant security threat to users of the Internet, causing tremendous economic loss every year. Past work in academia has not been adopted by industry in part due to concerns about liability over false positives. However, blacklist-based methods heavily used in industry are slow in responding to new phish attacks, and tend to be easily overwhelmed by phishing techniques such as fast-flux and the proliferation of toolkits. In this paper, we present the design and evaluation of two blacklist-enhanced content-based algorithms. The key insight behind our algorithms is to leverage existing human-verified whitelists and blacklists, and relax them via probabilistic methods to attain high true positive rates while maintaining extremely low false positive rates. Comprehensive experiments over a diverse spectrum of data sources show that our approach currently achieves a false positive rate of 0.0434% with a true positive rate of 87.42%. Our algorithms are able to adapt quickly to new phishing attacks by incremental retraining, and present a new framework that will generalize to evolving attacks.