Miracle-dz/UniFAR-FTUs huggingface dataset:
Cultural route to the emergence of linguistic categories

Categories provide a coarse-grained description of the world. A fundamental question is whether categories simply mirror an underlying structure of nature or instead come from the complex interactions of human beings among themselves and with the environment. Here, we address this question by modeling a population of individuals who co-evolve their own system of symbols and meanings by playing elementary language games. The central result is the emergence of a hierarchical category structure made of two distinct levels: a basic layer, responsible for fine discrimination of the environment, and a shared linguistic layer that groups together perceptions to guarantee communicative success. Remarkably, the number of linguistic categories turns out to be finite and small, as observed in natural languages.
Impedance control stability properties in common implementations

Various implementations of impedance control have been suggested, usually based on idealized models of the physical system. This work considers the nonideal, practical effects of computation and/or communication delays and manipulator dynamics on the behavior of two primary approaches to impedance control. The results are cast in the form of stability boundaries, i.e. the relationships between desired impedance parameters which cause marginally stable behavior in the overall system. These stability boundaries are compared for the two primary implementations, and relative benefits of each approach are discussed. These comparisons provide the basis for quantitative tradeoffs, allowing selection of control implementation approaches suited for particular manipulators or allowing quantitative decisions to be made in manipulator system design. <<ETX>>
Prediction in signed heterogeneous networks

The problem of prediction is an important task in network analysis, which has attracted more attention from computer science communities. In this paper, prediction in signed heterogeneous networks is addressed, which contains two aspects, link prediction and sign prediction. Most of previous studies focus on non-signed networks that have only positive links or homogeneous networks that have only one type of nodes. However, there are many signed heterogeneous networks in which the nodes and links belong to different types and links can be either positive (indicating relationships such as trust, preferences, friendship, and etc) or negative (indicating relationships such as distrust, dislike, opposition, and etc) in real world. For link prediction, a rule-based methodology called RulePredict is proposed in the paper. In RulePredict, we first extract all features systematically which contain positive features that promote the existence of links and negative ones that reduce the possibility reversely. Then, the weights associated with different features will be learned by a supervised method based on generalized least squares (GLS). For sign prediction, we put forward a new method called HeteSign to calculate the polarity of the links based on the similarity of two objects depends on their linked objects in heterogeneous networks. Experiments are conducted on real networks, the IMDB and Epinions networks, which demonstrate that our approach gets better performance in terms of accuracy.
Understanding software through empirical reliability analysis

The need for improving the reliability of delivered software is becoming increasingly obvious to both the purchasers and producers of today's software systems. As noted by Boehm, the records show many examples of software systems which, when delivered for operational use, either performed in a degraded fashion or failed to perform at all. The results are higher software costs and delays in operational usage.
Morphological and Allozymic Variation in Hynobius boulengeri and H. stejnegeri (Amphibia: Urodela: Hynobiidae)

Abstract We studied morphological and allozymic variation in populations of Japanese salamanders, Hynobius boulengeri and H. stejnegeri. Adult H. boulengeri showed sexual dimorphism, and juveniles differed greatly from adults in many morphological characters. From the results of multivariate analyses of morphological characters, the populations were divided into four groups: (I) H. boulengeri from Honshu, (II) H. boulengeri from Shikoku, (III) H. boulengeri from the Sobo-Katamuki Mountains of Kyushu and H. stejnegeri, and (IV) H. boulengeri from the Amakusa Islands and the Osumi Peninsula. Phenotypic relationships among the four groups were identical to relationships clarified by allozymic analyses, except for group IV, which was included in group III in the allozyme tree. Some morphometric characters were significantly correlated with environmental variables. We consider H. stejnegeri to be a valid species based on its unique color pattern, morphometric characters, and allelic composition, even though it was nested within group III of H. boulengeri by both morphological and allozymic analyses. We propose that group I from Honshu and group II from Shikoku should be treated as H. boulengeri sensu stricto and H. hirosei, respectively. Resolving the taxonomic status of the remaining populations of groups III and IV from Kyushu requires further study.
Integrating Basic and Advanced Fieldwork With Academic Coursework

This paper presents a model for integrating academic and clinical learning in allied health. In this model (which is based on the TAR - teaching, application, reinforcement - approach) two levels of fieldwork are used: an introductory level which begins prior to and continues throughout a theory course, and an advanced level which follows successful completion of that course. Both levels are linked to the theory course through a series of workbooks, clinical exercises, and seminars. The introductory level fieldwork begins as a one-week full-time clinical placement, with structured activities focusing on the observation of five basic concepts. These concepts are then explored theoretically in the first part of the theory course, applied during the weekly continuation of the introductory fieldwork, and reinforced in a weekly seminar. Mastery of the five basic concepts provides a foundation for related advanced concepts presented in the latter part of the theory course, applied through specific assignments a.
Biases in the quantitative measurement of values for public decisions

Measurement of personal values in terms of money or utility can promote efficient public decisions about environmental and risk regulation, health care, and so forth. Current measures are subject to several biases. Quantitative judgments of value are often based on a concept of importance that ignores the quantity of the good being valued. They are sensitive to irrelevant factors, such as cost of the good (vs. its benefit) and whether it has been reduced by human action or nature. Some judgments are based on moral opinions about actions rather than on the value of consequences. Some of these problems seem solvable by methods that remove irrelevant information or force attention to relevant information. Other problems are less tractable. Their solution should be a high priority for research.
Building Parliamentary Human Capital

The emphasis on quality, efficiency and effectiveness in organisations as a way of increasing performance, effectiveness and outcomes has been a central theme in the contemporary management theory. It has also been a logical progression in the development of more accountable organisational systems in ensuing effective resource management, be they public, NGOs or private organisations. In the same way, Parliaments need to fulfil their functions efficiently and effectively in an increasingly complex and globalised world. This approach is increasingly being focused on the quality of the human resources within organisations. However, there has been little research on these issues from a parliamentary perspective. Considering the important role of Parliaments and parliamentarians, and the fact that there are no prerequisite qualifications to become a parliamentarian, the case for a more professional and managerial approach in these institutions is increasingly strong. This paper provides a theoretical overview with regard to parliamentary understanding and development of benchmarks as foundations for improvement in the performance of its functions. The paper also reports on the preliminary findings of a global study examining capacity building programmes for parliamentarians.
BCPNN Implemented with Fixed-Point Arithmetic

A fixed-point arithmetic implementation of the BCPNN (Bayesian Confidence Propagating Neural Network) is described, implemented, and evaluated. Moving averages (MAs) that operate on a logarithmic scale are described. Probabilistic fractional bits (PFB) are used to save precision in the implementation. The results show that the BCPNN implemented with integers and fixed-point arithmetic has a storage capacity as good as the floating-point arithmetic implementation given enough precision, e.g. 8 bits. The precision used in the connections can be traded for the number of connections. The scaling properties of the implementation are evaluated.
Boundary Conditions for the Microscopic FENE Models

We consider the microscopic equation of finite extensible nonlinear elasticity (FENE) models for polymeric fluids under a steady flow field. It is shown that for the underlying Fokker–Planck type of equations, any preassigned distribution on the boundary will become redundant once the nondimensional number $\text{{\it Li\/}} := \frac{Hb}{k_BT} \geq 2$, where H is the elasticity constant, $\sqrt{b}$ is the maximum dumbbell extension, T is the temperature, and $k_B$ is the usual Boltzmann constant. Moreover, if the probability density function is regular enough for its trace to be defined on the sphere $|m| = \sqrt{b}$, then the trace is necessarily zero when $\text{{\it Li\/}} > 2$. These results are consistent with our numerical simulations as well as some recent well-posedness results by preassuming a zero boundary distribution.
HOG: Distributed Hadoop MapReduce on the Grid

MapReduce is a powerful data processing platform for commercial and academic applications. In this paper, we build a novel Hadoop MapReduce framework executed on the Open Science Grid which spans multiple institutions across the United States - Hadoop On the Grid (HOG). It is different from previous MapReduce platforms that run on dedicated environments like clusters or clouds. HOG provides a free, elastic, and dynamic MapReduce environment on the opportunistic resources of the grid. In HOG, we improve Hadoop's fault tolerance for wide area data analysis by mapping data centers across the U.S. to virtual racks and creating multi-institution failure domains. Our modifications to the Hadoop framework are transparent to existing Hadoop MapReduce applications. In the evaluation, we successfully extend HOG to 1100 nodes on the grid. Additionally, we evaluate HOG with a simulated Facebook Hadoop MapReduce workload. We conclude that HOG's rapid scalability can provide comparable performance to a dedicated Hadoop cluster.
Intraventricular Conduction Delay in a Standard 12-Lead Electrocardiogram as a Predictor of Mortality in the General Population

Background— Prolonged duration of QRS complex in a 12-lead ECG is associated with adverse prognosis in patients with cardiac disease, but its significance is not well established in the general population. In particular, there is a paucity of data on the prognostic significance of nonspecific intraventricular conduction delay in apparently healthy subjects. Methods and Results— We evaluated the 12-lead ECGs of 10 899 Finnish middle-aged subjects from the general population (52% of whom were men; mean age 44±8.5 years) between 1966 and 1972 and followed them for 30±11 years. Primary end points were all-cause mortality, cardiac mortality, and arrhythmic death. Prolonged QRS duration was defined as QRS ≥110 ms and intraventricular conduction delay as QRS ≥110 ms, without the criteria of complete or incomplete bundle-branch block. QRS duration ≥110 ms was present in 1.3% (n=147) and intraventricular conduction delay in 0.6% (n=67) of the subjects. Prolonged QRS duration predicted all-cause mortality (multivariate-adjusted relative risk [RR] 1.48; 95% confidence interval [CI] 1.22–1.81; P<0.001), cardiac mortality (RR 1.94; CI 1.44–2.63; P<0.001), and sudden arrhythmic death (RR 2.14; CI 1.38–3.33; P=0.002). Subjects with intraventricular conduction delay had increased all-cause mortality (RR 2.01; CI 1.52–2.66; P<0.001), increased cardiac mortality (RR 2.53; CI 1.64–3.90; P<0.001), and an elevated risk of arrhythmic death (RR 3.11; CI 1.74–5.54; P=0.001). Left bundle-branch block also weakly predicted arrhythmic death (P=0.04), but right bundle-branch block was not associated with increased mortality. Conclusions— Prolonged QRS duration in a standard 12-lead ECG is associated with increased mortality in a general population, with intraventricular conduction delay being most strongly associated with an increased risk of arrhythmic death.
Dropout As A Function Of Discrepancies Between Expectations and Actual Experiences Of The Classroom Social Environment

Prediction and explanation of the dropout phenomenon in adult education have suffered from a lack of theory-based research. In the present inquiry, social environment theory was employed to determine the relation of dropout behavior to the social ecology of the classroom. Research in school settings indicates that discrepancies between students' expectations of a specific classroom environment and their actual experiences in that environment promote dissatisfaction. These findings, coupled with theoretical deduction, suggested the hypothesis that adult dropouts, compared to persisters, would exhibit a greater degree of discrepancy between initial expectations and actual experiences of the classroom environment. Expectations and actual classroom experiences were measured by administering the Classroom Environment Scale to 77 adults enrolled in GED preparation classes. Discrepancy scores were analyzed by t-tests and multiple regression. Dropouts differed significantly from persisters on the subscale of Affiliation. Put briefly, they expected a classroom environment characterized by less social involvement with other students. Twenty-six percent of the variance in drop out behavior was attributed to the CES discrepancy scores
Thinking about Theorizing in Professional Development

This article describes two female beginning teachers from the same teacher education cohort. The two women had many experiences in common, but thought about these experiences quite differently. The article focuses on how their conceptions of students and of themselves as teachers changed over a 5-year period, and explores some of the interactions between their theorizing and their experiences. It also raises issues for teacher educators to consider.
A NEW METHOD FOR VANISHING POINTS DETECTION IN 3 D RECONSTRUCTION FROM A SINGLE VIEW

From a single view that contains a three dimensional scene is possible to obtain substantial information about the object and even its partial reconstruction. This analysis can provide, in the case of Photogrammetry, measures of the original object, and in the case of Computer Vision, useful information to 3D reconstruction. Nevertheless, to carry out this analysis, a critical part of the process is to identify with a high degree of quality, the structural elements of an oblique image, mainly vanishing lines and points. The presence of mini-segments due to the automatism, and the own weakness of the scene’s geometry, provide unfavorable intersection cases. Taking into account the qualitative and quantitative gap of complexity associated to real images corresponding to architectural buildings, this paper aims to present a new method for vanishing points detection that takes a scientific approach combining several proven techniques and which applies three different steps: 1. A Clustering step, in order to cluster the mini-segments in vanishing lines. 2. An Estimation step, which applies a modification of the Gaussian sphere method, in order to obtain an estimation of vanishing points and reject possible erroneous vanishing lines. 3. A Computation step, which applies a re-weighted least square adjustment support by an M-estimator.
Effects of Ghrelin miRNA on Inflammation and Calcium Pathway in Pancreatic Acinar Cells of Acute Pancreatitis

Objectives The study investigated the effects of endogenous targeted inhibition of ghrelin gene on inflammation and calcium pathway in an in vitro pancreatic acinar cell model of acute pancreatitis. Methods Lentiviral expression vector against ghrelin gene was constructed and transfected into AR42J cells. The mRNA and protein expression of each gene were detected by reverse transcription polymerase chain reaction, Western blotting, or enzyme-linked immunosorbent assay. The concentration of intracellular calcium ([Ca2+]i) was determined by calcium fluorescence mark probe combined with laser scanning confocal microscopy. Results Compared with the control group, cerulein could upregulate mRNA and protein expression of inflammatory factors, calcium pathway, ghrelin, and [Ca2+]i. mRNA and protein expression of inflammatory factors increased significantly in cells transfected with ghrelin miRNA compared with the other groups. Intracellular calcium and expression of some calcium pathway proteins decreased significantly in cells transfected with ghrelin miRNA compared with the other groups. Conclusions Targeted inhibition of ghrelin gene in pancreatic acinar cells of acute pancreatitis can upregulate the expression of the intracellular inflammatory factors and alleviate the intracellular calcium overload.
Dopamine enhances duodenal epithelial permeability via the dopamine D5 receptor in rodent

The intestinal barrier is made up of epithelial cells and intercellular junctional complexes to regulate epithelial ion transport and permeability. Dopamine (DA) is able to promote duodenal epithelial ion transport through D1‐like receptors, which includes subtypes of D1 (D1R) and D5 (D5R), but whether D1‐like receptors influence the duodenal permeability is unclear.
Respiratory and olfactory turbinal size in canid and arctoid carnivorans

Within the nasal cavity of mammals is a complex scaffold of paper‐thin bones that function in respiration and olfaction. Known as turbinals, the bones greatly enlarge the surface area available for conditioning inspired air, reducing water loss, and improving olfaction. Given their functional significance, the relative development of turbinal bones might be expected to differ among species with distinct olfactory, thermoregulatory and/or water conservation requirements. Here we explore the surface area of olfactory and respiratory turbinals relative to latitude and diet in terrestrial Caniformia, a group that includes the canid and arctoid carnivorans (mustelids, ursids, procyonids, mephitids, ailurids). Using high‐resolution computed tomography x‐ray scans, we estimated respiratory and olfactory turbinal surface area and nasal chamber volume from three‐dimensional virtual models of skulls. Across the Caniformia, respiratory surface area scaled isometrically with estimates of body size and there was no significant association with climate, as estimated by latitude. Nevertheless, one‐on‐one comparisons of sister taxa suggest that arctic species may have expanded respiratory turbinals. Olfactory surface area scaled isometrically among arctoids, but showed positive allometry in canids, reflecting the fact that larger canids, all of which are carnivorous, had relatively greater olfactory surface areas. In addition, among the arctoids, large carnivorous species such as the polar bear (Ursus maritimus) and wolverine (Gulo gulo) also displayed enlarged olfactory turbinals. More omnivorous caniform species that feed on substantial quantities of non‐vertebrate foods had less expansive olfactory turbinals. Because large carnivorous species hunt widely dispersed prey, an expanded olfactory turbinal surface area may improve a carnivore's ability to detect prey over great distances using olfactory cues.
Taming coincidental correctness: Coverage refinement with context patterns to improve fault localization

Recent techniques for fault localization leverage code coverage to address the high cost problem of debugging. These techniques exploit the correlations between program failures and the coverage of program entities as the clue in locating faults. Experimental evidence shows that the effectiveness of these techniques can be affected adversely by coincidental correctness, which occurs when a fault is executed but no failure is detected. In this paper, we propose an approach to address this problem. We refine code coverage of test runs using control- and data-flow patterns prescribed by different fault types. We conjecture that this extra information, which we call context patterns, can strengthen the correlations between program failures and the coverage of faulty program entities, making it easier for fault localization techniques to locate the faults. To evaluate the proposed approach, we have conducted a mutation analysis on three real world programs and cross-validated the results with real faults. The experimental results consistently show that coverage refinement is effective in easing the coincidental correctness problem in fault localization techniques.
Review – Lichen-Associated Bacteria as a Hot Spot of Chemodiversity: Focus on Uncialamycin, a Promising Compound for Future Medicinal Applications

Abstract This review presents the state of knowledge on the medicinal potential of bacteria associated with lichens. In fact, besides the classical symbiotic partners (photobiont and mycobiont) forming the lichen thallus, associated bacteria have been recently described as a third partner. Various studies demonstrated the diversity of these communities with a predominance of Alphaproteobacteria. Bacterial groups more relevant for secondary metabolite synthesis have also been revealed. This article summarizes studies reporting the abilities of these communities to produce metabolites with relevant bioactivities. The biotechnological interest of these bacteria for drug discovery is highlighted regarding the production of compounds with therapeutic potential. Special focus is given to the synthesis of the most promising compound, uncialamycin, a potent enediyne isolated from a Streptomyces sp. associated with Cladonia uncialis.
Multilinear Supervised Neighborhood Embedding of a Local Descriptor Tensor for Scene/Object Recognition

In this paper, we propose to represent an image as a local descriptor tensor and use a multilinear supervised neighborhood embedding (MSNE) for discriminant feature extraction, which is able to be used for subject or scene recognition. The contributions of this paper include: (1) a novel feature extraction approach denoted as the histogram of orientation weighted with a normalized gradient (NHOG) for local region representation, which is robust to large illumination variation in an image; (2) an image representation framework denoted as the local descriptor tensor, which can effectively combine a moderate amount of local features together for image representation and be more efficient than the popular existing bag-of-feature model; and (3) an MSNE analysis algorithm, which can directly deal with the local descriptor tensor for extracting discriminant and compact features and, at the same time, preserve neighborhood structure in tensor-feature space for subject/scene recognition. We demonstrate the performance advantages of our proposed approach over existing techniques on different types of benchmark database such as a scene data set (i.e., OT8), face data sets (i.e., YALE and PIE), and view-based object data sets (COIL-100 and ETH-80).