Miracle-dz/UniFAR-FTUs huggingface dataset:
On Improving the Performance of Multi-threaded CUDA Applications with Concurrent Kernel Execution by Kernel Reordering

General-purpose graphics processing units (GPUs) have been found to be viable solutions for large-scale numerical computations with an inherent potential for massive parallelism. In contrast, only few is known about using GPUs for small-scale computations. To have the GPU not be under-utilized for small problem sizes, a meaningful approach is to perform as many small-scale computations as possible in a concurrent manner. On NVIDIA Fermi GPUs, the concept of Concurrent Kernel Execution (CKE) allows for the execution of up to 16 GPU kernels on a single device. While using CKE in single-threaded CUDA programs is straightforward, for multi-threaded programs it might become a challenge to manage multiple host threads interacting with the GPU device, and in addition to have the CKE concept work properly. It can be observed that CKE performance breaks down when multiple host threads each invoke multiple GPU kernels in succession without synchronizing their actions. Since in real-world applications it is common that multiple host threads process their data independently, a mechanism is needed that helps avoiding CKE breakdown. We propose a producer-consumer principle approach to manage GPU kernel invocations from within parallel host regions by reordering the respective GPU kernels before actually invoking them. We are able to demonstrate significant performance improvements with this technique in a strong scaling simulation of a small molecule solvated within a nanodroplet.
Cell Contact Regulates Fate Choice by Cortical Stem Cells

Cell fate is determined by intrinsic programs and external cues, such as soluble signals and cell–cell contact. Previous studies have demonstrated the roles of soluble factors in the proliferation and differentiation of cortical stem cells and cell–cell contact in maintaining stem cells in a proliferative state. In the present study, we focused on the effect of cell–cell interaction on cell-fate determination. We found that density could exert a strong influence on the cell-type composition when cortical stem cells differentiate. Multipotent stem cells, which normally gave rise to neurons, astrocytes, and oligodendrocytes under high-density culture condition, differentiated almost exclusively into smooth muscle at low density. Clonal analysis indicated that smooth muscle and astrocytes were derived from a common precursor and that the density effect on cell types used an instructive mechanism on the choice of fate rather than an effect of selective survival and/or proliferation. This instructive mechanism depended on the local and not the average density of the cells. This local signal could be mimicked by membrane extract. These findings demonstrate the importance of membrane-bound signals in specifying lineage and provide the first evidence for a short-range regulatory mechanism in cortical stem cell differentiation.
2 A Compact Sensor for Visual Motion Detection

Videre: Journal of Computer Vision Research (ISSN 1089-2788) is a quarterly journal published electronically on the Internet by The MIT Press, Cambridge, Massachusetts, 02142. Subscriptions and address changes should be addressed to MIT Press Journals, Five Cambridge Center, Cambridge, MA 02142; phone: (617) 253-2889; fax: (617) 577-1545; e-mail: journals-orders@mit.edu. Subscription rates are: Individuals $30.00, Institutions $125.00. Canadians add additional 7% GST. Prices subject to change without notice.
Avalanches in Self-Organized Critical Neural Networks: A Minimal Model for the Neural SOC Universality Class

The brain keeps its overall dynamics in a corridor of intermediate activity and it has been a long standing question what possible mechanism could achieve this task. Mechanisms from the field of statistical physics have long been suggesting that this homeostasis of brain activity could occur even without a central regulator, via self-organization on the level of neurons and their interactions, alone. Such physical mechanisms from the class of self-organized criticality exhibit characteristic dynamical signatures, similar to seismic activity related to earthquakes. Measurements of cortex rest activity showed first signs of dynamical signatures potentially pointing to self-organized critical dynamics in the brain. Indeed, recent more accurate measurements allowed for a detailed comparison with scaling theory of non-equilibrium critical phenomena, proving the existence of criticality in cortex dynamics. We here compare this new evaluation of cortex activity data to the predictions of the earliest physics spin model of self-organized critical neural networks. We find that the model matches with the recent experimental data and its interpretation in terms of dynamical signatures for criticality in the brain. The combination of signatures for criticality, power law distributions of avalanche sizes and durations, as well as a specific scaling relationship between anomalous exponents, defines a universality class characteristic of the particular critical phenomenon observed in the neural experiments. Thus the model is a candidate for a minimal model of a self-organized critical adaptive network for the universality class of neural criticality. As a prototype model, it provides the background for models that may include more biological details, yet share the same universality class characteristic of the homeostasis of activity in the brain.
Reinforcement learning using associative memory networks

It is shown that associative memory networks are capable of solving immediate and general reinforcement learning (RL) problems by combining techniques from associative neural networks and reinforcement learning and in particular Q-learning. The modified model is shown to significantly outperform native RL techniques on a stochastic grid world task by developing correct optimal policies. The network contrary to pure RL methods is based on associative memory principles such as distribution of information, pattern completion, Hebbian learning, attractors, and noise tolerance. Because of this, it can be argued that the model possesses more cognitive explanative power than pure reinforcement learning methods or other hybrid models and can be an effective tool for bridging the gap between biological memory models and computational memory models.
Microsatellite Markers Based Genetic Evaluation of Pakistani Cattle Breeds

Animal Genetic Resource of Pakistan is very diverse. There are 15 distinct breeds of cattle in Pakistan all belonging to zebu (humped type) cattle (Bos indicus) for which very little information on genetic architecture is available. Microsatellite markers are being widely used for breed characterization in animals. In the present study 345 individuals of 11 breeds (10 Pakistani cattle breeds and exotic Holstein Friesian breed) were genotyped using 21 fluorescently–labeled microsatellite markers to assess genetic variation and relationships among them. All markers were polymorphic in all studied breeds and observed number of alleles ranged from 6.28 in Tharparker to 10.66 in Dajal with mean value 8.50±1.552. Average values of observed and expected heterozygosity were calculated as 0.4897±0.1538 and 0.8292±0.0744 respectively. Mean values of Fis, Fit, FST and gene flow were 0.2819, 0.3864 and 0.1456 respectively. The average PIC value was 0.81 showing suitability of these markers for forensic analyses. Nei’s genetic distance estimates indicated relatively close genetic identity between Tharparker and Red-Sindhi breeds of Sindh Province of Pakistan while Tharparker and Dajal breeds of Pakistan were found most distinct. The UPGMA-based phylogenetic tree constructed from the genetic distances also indicated that the cattle breeds of Pakistan can be classified into distinct genetic groups based on these markers. This is the first comprehensive report on molecular characterization of Pakistani cattle breeds using microsatellite markers. This study can be helpful for making breed conservation strategies of cattle in Pakistan in future.
Strategic Alliance in Energy Sector & Implications for Economic Growth and Technical Efficiency: The Case of Petrobras and Galp

This study stemmed from the lack of evidence and uncertainties regarding the economic and political effects of a strategic alliance between leading oil companies like Petrobras and Galp on their host economies. This paper investigates whether public and private corporations in the energy sector can influence the economic growth of their respective countries. A Panel data analysis was performed by employing quarterly data from (2006-2013). We also used Data Envelopment Analysis (DEA) approach to measure the technical efficiency (TE) effect of the alliance on the performance of both companies from 1999 to 2012. It was found the exploration and export of oil and gas do not play a significant role in output growth of the home economy and that exploration activities were inflationary, destabilising and inimical to growth, at least in the short-run. On another positive side, both companies showed increased technical efficiencies in the chosen time period. Petrobras enjoyed TE on average of 90% in the variables studied whereas Galp showed an average TE of 70%. These results reflect the corporate strategies of both firms, which focussed on achieving profitable and sustained growth and enhancing their efficiencies in their collective and individual activities. This study stemmed from the lack of evidence and uncertainties regarding the economic and political effects of a strategic alliance between leading oil companies like Petrobras and Galp on their host economies. This paper investigates whether public and private corporations in the energy sector can influence the economic growth of their respective countries. A Panel data analysis was performed by employing quarterly data from (2006-2013). We also used Data Envelopment Analysis (DEA) approach to measure the technical efficiency (TE) effect of the alliance on the performance of both companies from 1999 to 2012. It was found the exploration and export of oil and gas do not play a significant role in output growth of the home economy and that exploration activities were inflationary, destabilising and inimical to growth, at least in the short-run. On another positive side, both companies showed increased technical efficiencies in the chosen time period. Petrobras enjoyed TE on average of 90% in the variables studied whereas Galp showed an average TE of 70%. These results reflect the corporate strategies of both firms, which focussed on achieving profitable and sustained growth and enhancing their efficiencies in their collective and individual activities.
Oligopoly with Hyperbolic Demand and Capital Accumulation 1

A dynamic approach is proposed for the analysis of the Cournot oligopoly game with hyperbolic demand, showing that the adoption of capital accumulation dynamics either à la Solow-Swan or à la Ramsey eliminate the indeterminacy problem characterising the static model when marginal costs are nil. It is proved that the steady state equilibria produced by both models are stable in the saddle point sense. Finally, it is also shown that the solutions of the corresponding feedback problems share analogous properties, although they cannot be fully characterised from an analytical standpoint. JEL Codes: C73, D43, D92, L13
Classification of PICO elements by text features systematically extracted from PubMed abstracts

We propose and evaluate a systematic approach to detect and classify Patient/Problem, Intervention, Comparison and Outcome (PICO) from the medical literature. The training and test corpora were generated systematically and automatically from structured PubMed abstracts. 23,472 sentences by exact pattern match of head words of P-I-O categories. Afterward, the terms with top frequencies were used as the features of Naïve Bayesian classifier. This approach achieves F-measure values of 0.91 for Patient/Problem, 0.75 for Intervention and 0.88 for Outcome, comparable to previous studied based on mixed textural, paragraphical, and semantic features. In conclusion, we show that by stricter pattern matching criteria of training set, detection and classification of PICO elements can be reproducible with minimal expert intervention. The results of this work are higher than previous studies.
An Interconnection Length Estimation for Multi-point Nets

The increasing system complexity imposes high demands on computer aided design (CAD) tools for system synthesis. Especially the layout (placement and routing) of a design has become a problem hard to solve. To find a ‘good’ layout, CAD tools need accurate estimators to predict area requirements, interconnection lengths, power dissipation, etc. In this paper we address the estimation of interconnection lengths. Previous work on interconnection length estimations is primarily based on a technique introduced by Donath [1] which has been improved by Stroobandt et al [2]. However, no previous work on estimating design properties (e.g. interconnection lengths) takes multi-point nets into account. All nets are assumed to be 2-point nets. In this paper, we will estimate the average interconnection length for multi-point nets. This estimation is based on our recent research on the behaviour of multi-point nets during the partitioning process and on the distribution of nets over their net degree [3].
Principles as lexical methods

Current research in lexical semantics has brought into focus (i) the existence of general tendencies (’principles’) ac:o~ languages or inside language families, (ii) the existence of numerous exceptions to these tendencies. To reconcile these two facts, it seems natural to endorle s general conception of principles-withexceptions or ’subregularities ’1, usually cashed on a form of default logic. This leaves open the question of how to identify and manage the exceptions in a more precise way, i.e. not just as marginal by-products of a subregulsr/ty system. In tiffs paper, we analyze different examples where complex cases can be handled explicitly, and show that pzincip|e-bused approaches require, as a natural complement, to be controlled by more local information.
Mining Open Source Software data using regular expressions

The Open Source Software (OSS) management has attracted considerable attention in the last few years. Project management for effective software process improvement must be achieved based on quantitative data. However, because data collection for measurement requires high costs and collaboration with developers, and data dumps may require a huge effort to understand schemas and tables. It is difficult to collect coherent, quantitative data continuously and to utilize the data for practicing software process improvement. In this paper, we report our results of mining data acquired from SourceForge.net, the largest open source software hosting website. In the process we describe Mailing list Crawler (MC) which automatically collects Mailing lists repositories in widely used software development support systems. Providing integrated measurement results graphically, MC can help developers/managers keep projects under control in real time.
Extensional quotients for type theory and the consistency problem for NF

Quine's “New Foundations” (NF) was first presented in Quine [10] and later on in Quine [11]. Ernst Specker [15, 13], building upon a previous result of Ehrenfeucht and Mostowski [5], showed that NF is consistent if and only if there is a model of the Theory of Negative (and positive) Types (TNT) with full extensionality that admits of a “shifting automorphism,” but the existence of such a model remains an open problem. In his [8], Ronald Jensen gave a partial solution to the problem of the consistency of Quine's NF. Jensen considered a version of NF—referred to as NFU—in which the axiom of extensionality is weakened to allow for Urelemente or “atoms. ” He showed, modifying Specker's theorem, that the existence of a model of TNT with atoms admitting of a “shifting automorphism” implies the consistency of NFU, proceeding then to exhibit such a model. This paper presents a reduction of the consistency problem for NF to the existence of a model of TNT with atoms containing certain “large” (unstratified) sets and admitting a shifting automorphism. In particular we show that such a model can be “collapsed” to a model of pure TNT in such a way as to preserve the shifting automorphism. By the above-mentioned result of Specker's, this implies the consistency of NF. Let us take the time to explain the main ideas behind the construction. Suppose we have a certain universe U of sets, built up from certain individuals or “atoms. ” In such a universe we have only a weak version of the axiom of extensionality: two objects are the same if and only if they are both sets having the same members. We would like to obtain a universe U′ that is as close to U as possible, but in which there are no atoms (i.e., the only memberless object is the empty set). One way of doing this is to assign to each atom ξ, a set a (perhaps the empty set), inductively identifying sets that have members that we are already committed to considering “the same. ” In doing this we obtain an equivalence relation ≃ over U that interacts nicely with the membership relation (provided we have accounted for multiplicity of members, i.e., we have allowed sets to contain “multiple copies” of the same object). Then we can take U′ = U/≃, the quotient of U with respect to ≃. It is then possible to define a “membership” relation over U′ in such a way as to have full extensionality. Relations such as ≃ are referred to as “contractions” by Hinnion and “bisimulations” by Aczel.
A spatial econometric model for evaluating conditional β-convergence across EU regions

The aim of this paper is to assess European Union C hesion Policy by estimating a conditional β-convergence model for a sample of 196 EU regions o ver the period 1980-2006, using a spatial econometric perspective and a dista nce-based weight matrix. Under the assumption of substantial coincidence of geographic l and economic periphery in EU-15, the final model combines the identification of two regi mes and spatial dependence. In particular, we consider Objective 1 and non Objective 1 regions , relatively to 1994-1999 period. A spatial auto-regressive model (Anselin, 1988) with two spatial regimes, including crossregressive terms to further investigate the role of geographical spillover effects on regional convergence, was estimated. Moreover, the condition ing variables, the regional employment rate and the agricultural share on total employment , allow for further heterogeneity within each regime. The results of this work support the i mportance of an explicit consideration of spatial effects in convergence analysis (as highlig hted in Piras and Arbia, 2007 and Ramajo et al, 2008). The main finding is that the convergence process among EU regions is affected by a polarization into two different clusters converging separately to different steady states, thus implying relative income differences to be persiste nt. Furthermore, Objective 1 regions are more affected by geographical spillover effects and converge faster to their steady state than non Objective 1 regions. These findings suggest a p ositive role of EU Regional Policy on convergence among Objective 1 regions and, at the s ame time, call for a better consideration of spatial spillover effects in planning Regional P olicy.
The Improved Physical Activity Index for Measuring Physical Activity in EPIC Germany

In the European Investigation into Cancer and Nutrition study (EPIC), physical activity (PA) has been indexed as a cross-tabulation between PA at work and recreational activity. As the proportion of non-working participants increases, other categorization strategies are needed. Therefore, our aim was to develop a valid PA index for this population, which will also be able to express PA continuously. In the German EPIC centers Potsdam and Heidelberg, a clustered sample of 3,766 participants was re-invited to the study center. 1,615 participants agreed to participate and 1,344 participants were finally included in this study. PA was measured by questionnaires on defined activities and a 7-day combined heart rate and acceleration sensor. In a training sample of 433 participants, the Improved Physical Activity Index (IPAI) was developed. Its performance was evaluated in a validation sample of 911 participants and compared with the Cambridge Index and the Total PA Index. The IPAI consists of items covering five areas including PA at work, sport, cycling, television viewing, and computer use. The correlations of the IPAI with accelerometer counts in the training and validation sample ranged r = 0.40–0.43 and with physical activity energy expenditure (PAEE) r = 0.33–0.40 and were higher than for the Cambridge Index and the Total PA Index previously applied in EPIC. In non-working participants the IPAI showed higher correlations than the Cambridge Index and the Total PA Index, with r = 0.34 for accelerometer counts and r = 0.29 for PAEE. In conclusion, we developed a valid physical activity index which is able to express PA continuously as well as to categorize participants according to their PA level. In populations with increasing rates of non-working people the performance of the IPAI is better than the established indices used in EPIC.
Predicting a Tendency to Use Drugs From Child and Adult Attention Deficit Hyperactivity Disorder Symptoms in Adults

Background Adult attention deficit hyperactivity disorder (ADHD) increases the risk of several psychiatric disorders, like substance use disorders (SUDs). Objectives This study aimed to predict the tendency for drug use from child and adult ADHD symptoms in adults among male students from Tabriz University, Iran. Patients and Methods For this purpose, 361 students were selected via a stratified random sampling from different faculties of Tabriz University. The students completed the Conners Adult ADHD Rating Scale self-report form and subscale (CAARS) questionnaire, Addiction Acknowledgment Scale (AAS) and MacAndrew Alcoholism Revised-Scale (MAC-R). Results To analyze the data Pearson correlation and multiple regressions (step by step) were used. Results indicated that there is a significant relationship between scores on the AAS and MAC-R via child and adult ADHD symptoms (P = 0.01). Moreover, we found that those with the highest addiction acknowledgment (13%) exhibited adult ADHD (total) and child ADHD. Alcohol potential (15%) was related to scores of child ADHD and impulsivity. Conclusions According to this result behavioral disorders, especially ADHD, have an effect on the tendency to use drugs and therefore the primary treatment of behavioral disorders could prevent future drug abuse.
New Limonoids and a Dihydrobenzofuran Norlignan from the Roots of Toona sinensis

Two new limonoids, toonins A (1) and B (2), and one new dihydrobenzofuran norlignan, toonin C (3), were isolated from the roots of Toona sinensis together with the ten known compounds 4-methoxy-6-(2′,4′-dihydroxy-6′-methylphenyl)-pyran-2-one (4), bourjotinolone A (5), proceranone (6), matairesinol (7), 4-hydroxy-3-methoxybenzene-ethanol (8), syringic acid (9), isoscopoletin (10), lyoniresinol (11), aloeemodin (12), and β-sitosterol (13). Their structures were elucidated on the basis of one- and two-dimensional spectroscopic analysis. Isolation of compounds 4, 6–13 from this plant is reported here for the first time.
Benchmarking a BI-population CMA-ES on the BBOB-2009 noisy testbed

We benchmark the BI-population CMA-ES on the BBOB-2009 noisy functions testbed. BI-population refers to a multistart strategy with equal budgets for two interlaced restart strategies, one with an increasing population size and one with varying small population sizes. The latter is presumably of little use on a noisy testbed. The BI-population CMA-ES could solve 29, 27 and 26 out of 30 functions in search space dimension 5, 10 and 20 respectively. The time to find the solution ranges between 100 D and 105 D2 objective function evaluations, where D is the search space dimension.