Miracle-dz/UniFAR-FTUs huggingface dataset:
A comprehensive framework for synthesizing stencil algorithms on FPGAs using OpenCL model

Iterative stencil algorithms find applications in a wide range of domains. FPGAs have long been adopted for computation acceleration due to its advantages of dedicated hardware design. Hence, FPGAs are a compelling alternative for executing iterative stencil algorithms. However, efficient implementation of iterative stencil algorithms on FPGAs is very challenging due to the data dependencies between iterations and elements in the stencil algorithms, programming hurdle of FPGAs, and large design space. In this paper, we present a comprehensive framework that synthesizes iterative stencil algorithms on FPGAs efficiently. We leverage the OpenCL-to-FPGA toolchain to generate accelerator automatically and perform design space exploration at the high level. We propose to bridge the neighboring tiles through pipe and enable data sharing among them to improve computation efficiency. Then, we extend the equal tile size design to a heterogeneous design with different tile size to balance the computation among different tiles. We also develop analytical performance models to explore the complex design space. Experiments using a wide range of stencil applications demonstrate that on average our heterogeneous implementations achieve 1.65X performance speedup but with less hardware resource compared to the state-of-the-art.
Determinants of users' information dissemination behavior on social networking sites: An elaboration likelihood model perspective

As a new communication paradigm, social networking sites (SNS) have boosted information diffusion and viral marketing. Prior researchers have identified various factors affecting information dissemination on SNS. However, they often focus on limited factors and there is a lack of an integrated theoretical framework that explains aspects of relevant factors. Besides, the research on the impacts of relationships on individual retweeting behavior is still controversial. The purpose of this paper is to propose a theoretical framework to systematically investigate the determinants of individual dissemination behavior on SNS based on the elaboration likelihood model (ELM). Moreover, the authors also examine the relative importance of those relevant factors. ,The authors randomly selected 1,250 members of Twitter and crawled posts published by each member since he/she created the Twitter account using Twitter API. The authors processed the data to create panel data and tested hypotheses with the panel logit model. ,Factors both on the central route and on the peripheral route of ELM have positive impacts on individual dissemination behavior. Among them, information receiver-related factor and relationships-related factors are the most influential. Contrastingly, source-related factors are the least influential. Furthermore, the authors find that social tie strength mediates almost 50 percent of the effect of value homophily on individual dissemination behavior. ,The authors are the first to directly apply ELM to examine individual dissemination behavior on SNS. By integrating factors into the two information processing routes, They incorporate relevant factors into the model and systematically analyze their impacts on individual retweeting behavior on SNS. The research offers at least one explanation for the contradictory findings about the effect of homophily on individual sharing behavior in previous research. The authors propose new variables that gauge topical relevance and interpersonal value homophily on SNS.
School Principals’ Authentic Leadership and Teachers’ Psychological Capital: Teachers’ Perspectives

This study examined teachers’ perceptions of principals’ authentic leadership and the relationship of authentic leadership to teachers’ psychological capital in Taiwan. A total of 1,429 elementary and secondary school teachers were surveyed. The results showed that teachers perceived their principals’ authentic leadership as moderate and that the principals’ practice of authentic leadership was influenced by culture. Moreover, the principals’ authentic leadership was found to be positively and significantly associated with teachers’ psychological capital. This study provides empirical evidence to support a theoretical argument suggesting that authentic leadership fosters positive psychological capital among the members of an organization.
Learning event-related potentials (ERPs) from multichannel EEG recordings: A spatio-temporal modeling framework with a fast estimation algorithm

Extracting event-related potentials (ERPs) from multichannel EEG recordings remains a challenge due to the poor signal-to-noise ratio (SNR). This paper presents a multivariate statistical model of ERPs by exploiting the existing knowledge about their spatio-temporal properties. In particular, a computationally efficient algorithm is derived for fast model estimation. The algorithm, termed SIM, can be intuitively interpreted as maximizing the signal-to-noise ratio in the source space. Using both simulated and real EEG data, we show that the algorithm achieves excellent estimation performance and substantially outperforms a state-of-the-arts algorithm in classification accuracies in a P300 target detection task. The results demonstrate that the proposed modeling framework offers a powerful tool for exploring the spatio-temporal patterns of ERPs as well as learning spatial filters for decoding brain states.
Rational integration of noisy evidence and prior semantic expectations in sentence interpretation

Sentence processing theories typically assume that the input to our language processing mechanisms is an error-free sequence of words. However, this assumption is an oversimplification because noise is present in typical language use (for instance, due to a noisy environment, producer errors, or perceiver errors). A complete theory of human sentence comprehension therefore needs to explain how humans understand language given imperfect input. Indeed, like many cognitive systems, language processing mechanisms may even be “well designed”–in this case for the task of recovering intended meaning from noisy utterances. In particular, comprehension mechanisms may be sensitive to the types of information that an idealized statistical comprehender would be sensitive to. Here, we evaluate four predictions about such a rational (Bayesian) noisy-channel language comprehender in a sentence comprehension task: (i) semantic cues should pull sentence interpretation towards plausible meanings, especially if the wording of the more plausible meaning is close to the observed utterance in terms of the number of edits; (ii) this process should asymmetrically treat insertions and deletions due to the Bayesian “size principle”; such nonliteral interpretation of sentences should (iii) increase with the perceived noise rate of the communicative situation and (iv) decrease if semantically anomalous meanings are more likely to be communicated. These predictions are borne out, strongly suggesting that human language relies on rational statistical inference over a noisy channel.
Simulated magnetic field expulsion in neutron star cores

J.G. E. and N.R. are funded by an NWO Vidi grant (PI: Rea). J.A. P. is funded by the grants AYA2013-42184-P and Prometeu/2014/6. N.R. and D.V. acknowledge support from the grants AYA2012-39303 and SGR 2014-1073. K.G. is supported by the Ramon y Cajal Programme of the Spanish Ministerio de Ciencia e Innovacion. Authors also wish to acknowledge NewCompStar, COST action MP1304 for partial funding of this research.
The ANT in a Russian Sample: Testing the Independence of Attention Networks

The Attention Network Test (ANT) is a measure that allows the assessment of three different attention networks postulated by Posner – alerting, orienting, and executive control. The alerting network is responsible for the maintenance of a vigilant and alert state; the orienting network allows the shift of attention to sensory events appearing in the perceptual field and is responsible for the selection of information from sensory input; the executive control network allows for resolving conflicts among responses. The ANT became a popular tool for assessing attention networks functioning thanks to its simplicity, relative briefness, and accessibility for researchers. This paper reports data obtained with the ANT in a Russian sample. The analysis was focused on the problem of the independence of the attention networks. No significant correlations between the attention networks were found. A repeated-measures analysis of variance yielded a significant interaction between the cue types and the flanker types. The character of this interaction indicates that the orienting and executive control networks are not independent.
Bayesian Analysis of the Heterogeneity Model

We consider Bayesian estimation of a finite mixture of models with random effects, which is also known as the heterogeneity model. First, we discuss the properties of various Markov chain Monte Carlo samplers that are obtained from full conditional Gibbs sampling by grouping and collapsing. Whereas full conditional Gibbs sampling turns out to be sensitive to the parameterization chosen for the mean structure of the model, the alternative sampler is robust in this respect. However, the logical extension of the approach to the sampling of the group variances does not further increase the efficiency of the sampler. Second, we deal with the identifiability problem due to the arbitrary labeling within the model. Finally, a case study involving metric conjoint analysis serves as a practical illustration.
Lifelong Information-Driven Exploration to Complete and Refine 4-D Spatio-Temporal Maps

This letter presents an exploration method that allows mobile robots to build and maintain spatio-temporal models of changing environments. The assumption of a perpetually changing world adds a temporal dimension to the exploration problem, making spatio-temporal exploration a never-ending, life-long learning process. We address the problem by application of information-theoretic exploration methods to spatio-temporal models that represent the uncertainty of environment states as probabilistic functions of time. This allows to predict the potential information gain to be obtained by observing a particular area at a given time, and consequently, to decide which locations to visit and the best times to go there. To validate the approach, a mobile robot was deployed continuously over 5 consecutive business days in a busy office environment. The results indicate that the robot's ability to spot environmental changes improved as it refined its knowledge of the world dynamics.
Extratropical forcing of ENSO

We present evidence that sea surface temperatures in the North Pacific, South Atlantic, and South Indian Oceans during late boreal winter offer another important source of predictability for El Niño Southern Oscillation (ENSO). This new SST predictor may provide accurate prediction of the amplitude of ENSO events before their onset, for both El Niño and La Niña events which occurred during recent decades.
Optimism and self-efficacy mediate the association between shyness and subjective well-being among Chinese working adults

The aim of the current study was to investigate whether optimism and self-efficacy mediated the association between shyness and subjective well-being in a sample of Chinese working adults. Two hundred and eight participants completed the Revised Cheek and Buss Shyness Scale, Life Orientation Rest-Revised, Satisfaction with Life Scale, and Positive and Negative Affect Scale. Structural equation modeling results showed that optimism mediated the relationship between shyness and measures of subjective well-being (life satisfaction, positive and negative affect). Self-efficacy mediated the association between shyness and positive subjective well-being (life satisfaction and positive affect). These results suggest that optimism and self-efficacy play unique mediating roles in the relationship between shyness and subjective well-being. They also have important implications for the development of intervention programs aimed at promoting subjective well-being of Chinese working adults through enhancing self-efficacy and optimism.
Neutrophils in Gliomas

Neutrophils are the most abundant white blood cells and are the first recruited to inflammatory sites. Neutrophils are an important component of the tumor stroma and can exert both anti-tumoral and pro-tumoral activities, depending on their maturation and activation state. In human gliomas, the number of circulating and infiltrating neutrophils correlates with the severity of the disease, indicating a prognostic and possible pro-tumoral role for these leukocytes. In glioma preclinical models, neutrophils promote tumor growth and orchestrate the resistance to anti-angiogenic therapies. Nevertheless, recent data indicate that neutrophils can be activated to directly kill tumor cells or to orchestrate the anti-tumoral response. Here, we review current knowledge about the role of neutrophils in glioma and their possible involvement in new strategies to improve current cancer therapies.
Spike Encoding of Neurotransmitter Release Timing by Spiral Ganglion Neurons of the Cochlea

Mammalian cochlear spiral ganglion neurons (SGNs) encode sound with microsecond precision. Spike triggering relies upon input from a single ribbon-type active zone of a presynaptic inner hair cell (IHC). Using patch-clamp recordings of rat SGN postsynaptic boutons innervating the modiolar face of IHCs from the cochlear apex, at room temperature, we studied how spike generation contributes to spike timing relative to synaptic input. SGNs were phasic, firing a single short-latency spike for sustained currents of sufficient onset slope. Almost every EPSP elicited a spike, but latency (300–1500 μs) varied with EPSP size and kinetics. When current-clamp stimuli approximated the mean physiological EPSC (≈300 pA), several times larger than threshold current (rheobase, ≈50 pA), spikes were triggered rapidly (latency, ≈500 μs) and precisely (SD, <50 μs). This demonstrated the significance of strong synaptic input. However, increasing EPSC size beyond the physiological mean resulted in less-potent reduction of latency and jitter. Differences in EPSC charge and SGN baseline potential influenced spike timing less as EPSC onset slope and peak amplitude increased. Moreover, the effect of baseline potential on relative threshold was small due to compensatory shift of absolute threshold potential. Experimental first-spike latencies in response to a broad range of stimuli were predicted by a two-compartment exponential integrate-and-fire model, with latency prediction error of <100 μs. In conclusion, the close anatomical coupling between a strong synapse and spike generator along with the phasic firing property lock SGN spikes to IHC exocytosis timing to generate the auditory temporal code with high fidelity.
The importance of understanding self-governance efforts in coastal fisheries in Peru: insights from La Islilla and Ilo

Understanding self-governance efforts in small-scale coastal fisheries may hold the clue to establishing effective coastal fisheries policies or strengthening existing ones. Here, we explored the diversity and the rationale behind the self-devised control rules implemented by two groups of coastal fishers in Peru, and the pathways to promote compliance under self-governance systems, as a prerequisite to sustain such efforts. We drew on an exploratory methodological approach and used semi-structured interviews and a questionnaire, designed following Ostrom's socio-ecological system (SES) framework, to characterize each experience. A compliance framework was used to identify the pathways and factors driving compliance. Results showed a variety of informal control rules have been set and used by fishers, from catch limits to patrolling activities. Each addresses specific fisheries governance and management issues. Results also showed that setting control rules has not been a one-time event; instead, it is an evolving learning process. Furthermore, both traditional (La Islilla) and non-traditional (Ilo) SES frameworks have built their own ways to promote compliance and sustain self-governance efforts. These two experiences provide insights for understanding self-governance of coastal fisheries, with particular attention to identifying ways to improve the governability of small-scale fisheries through cogovernance type arrangements.
Too much salt , too little soda : cystic fibrosis

Cystic fibrosis (CF) of the pancreas is the most widely accepted name of the most common fatal inherited single gene defect disease among Caucasians. Its incidence among other races is thought to be significantly less, but mutations in the gene have been reported in most, if not all, major populations. This review is intended to give general concepts of the molecular as well as physiological basis of the pathology that develops in the disease. First, an overview of the organ pathology and genetics is presented, followed by the molecular structure of the gene product (cystic fibrosis transmembrane conductance regulator, CFTR), its properties, functions, and controls as currently understood. Second, since mutations appear to be expressed primarily as a defect in electrolyte transport, effects and mechanisms of pathology are presented for two characteristically affected organs where the etiology is best described: the sweat gland, which excretes far too much NaCl (“salt”) and the pancreas, which excretes far too little HCO3 (“soda”). Unfortunately, morbidity and mortality in CF develop principally from refractory airway infections, the basis of which remains controversial. Consequently, we conclude by considering possible mechanisms by which defects in anion transport might predispose the CF lung to
Doing the MATH: is the mouse a good model for fly development?

Members of the superfamily of basic helix–loop–helix (bHLH) proteins have been shown to play important roles in neurogenesis in many species. Neuronal bHLH proteins can be divided into two families: the Achaete– Scute complex (AS-C) related proteins and the Atonalrelated proteins, or ARPs. In this review we discuss the ARPs, focusing on their functional diversity within each organism and contrasting it with the remarkable conservation of some of the functions across species. In reviewing the current data, three themes emerge. First, the sequence of the basic domain is sufficient to delineate the different groups of ARPs. Second, the structural similarities among the three groups of ARPs, namely the Neurogenin group, the NeuroD group, and the ATO group, appear to reflect functional similarities. Finally, the dual functions of Drosophila proneural ARPs in precursor selection and lineage identity specification may have been uncoupled in vertebrates.
P2Y13 Receptor Regulates HDL Metabolism and Atherosclerosis In Vivo

High-density lipoprotein (HDL) is known to protect against atherosclerosis by promoting the reverse cholesterol transport. A new pathway for the regulation of HDL-cholesterol (HDL-c) removal involving F1-ATPase and P2Y13 receptor (P2Y13R) was described in vitro, and recently in mice. However, the physiological role of F1-ATPase/P2Y13R pathway in the modulation of vascular pathology i.e. in the development of atherosclerotic plaques is still unknown. We designed a specific novel agonist (CT1007900) of the P2Y13R that caused stimulation of bile acid secretion associated with an increased uptake of HDL-c in the liver after single dosing in mice. Repeated dose administration in mice, for 2 weeks, stimulated the apoA-I synthesis and formation of small HDL particles. Plasma samples from the agonist-treated mice had high efflux capacity for mobilization of cholesterol in vitro compared to placebo group. In apoE−/− mice this agonist induced a decrease of atherosclerotic plaques in aortas and carotids. The specificity of P2Y13R pathway in those mice was assessed using adenovirus encoding P2Y13R-shRNA. These results demonstrate that P2Y13R plays a pivotal role in the HDL metabolism and could also be a useful therapeutic agent to decrease atherosclerosis. In this study, the up-regulation of HDL-c metabolism via activation of the P2Y13R using agonists could promote reverse cholesterol transport and promote inhibition of atherosclerosis progression in mice.
Preliminary investigations of polylactic acid (PLA) properties

Additive manufacturing is a technology capable to directly manufacture 3D physical model alongside with their inserted mathematical model in an additive nature, where the materials are fused together to form a product, unlike the traditional manufacturing method. The emergence of 3D printing has secured a shorter cycle time for designing and developing innovative products. One of the most commonly used additive manufacturing technology is Fused deposition modelling (FDM). 3D printing applications has seen an immense growth, where it has included more load bearing parts targeted to fit an intended application as per user’s requirement. Certain level of mechanical property information is being demanded as a benchmark to assess the strength of printed part in whole. This research work aims to investigate the tensile properties of PLA and find the optimum printing parameter combination using low-cost fused filament printer. Two parameters chosen to be varied in this research are raster angle and infill density, with value of 20°, 40°, 60° and 20%, 50%, 80% respectively. Tensile specimens with combination of these two parameters were printed according to ASTM D638 type 1 standard, with having layer height of 0.1mm as a constant. Tensile tests were conducted on the 3D printed PLA specimens to determine the best suited parameter combination that will result in optimum mechanical properties. Three mechanical properties were analysed, namely ultimate tensile strength, elastic modulus and yield strength. From the 9 combinations of parameter, the optimum combination was determined, which are 0.1 mm layer height, 40° raster angle, and 80% infill density of 3rd combination. Its optimum mechanical property is 32.93754MPa for ultimate tensile strength, 807.48931 MPa for elastic modulus and 26.08234 MPa for yield strength.
Differential-Private Data Publishing Through Component Analysis

A reasonable compromise of privacy and utility exists at an "appropriate" resolution of the data. We proposed novel mechanisms to achieve privacy preserving data publishing (PPDP) satisfying ε-differential privacy with improved utility through component analysis. The mechanisms studied in this article are Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). The differential PCA-based PPDP serves as a general-purpose data dissemination tool that guarantees better utility (i.e., smaller error) compared to Laplacian and Exponential mechanisms using the same "privacy budget". Our second mechanism, the differential LDA-based PPDP, favors data dissemination for classification purposes. Both mechanisms were compared with state-of-the-art methods to show performance differences.
Journal of Uncertain Systems, Vol1 No3, 2007, August, World Academic Union (World Academic Press)

This paper emphasizes that numerically correct calculation of economic uncertainty with intervals and fuzzy numbers requires implementation of global optimization techniques in contrast to straightforward application of interval arithmetic. This is demonstrated by both a simple case from managerial economics as well as a real life railway reconstruction project. Based on identical uncertain input data the difference between the probabilistic and the possibilistic approach is highlighted, the latter producing a substantial larger degree of numerical uncertainty due to its non-statistical nature. © 2010 World Academic Press, UK. All rights reserved.