Miracle-dz/UniFAR-FTUs huggingface dataset:
PARALLEL CLUSTERING AND DIMENSIONAL SCALING ON MULTICORE SYSTEMS

Technology advances suggest that the data deluge, network bandwidth and computers performance will continue their exponential increase. Computers will exhibit 64-128 cores in some 5 years. Consequences include a growing importance of data mining and data analysis capabilities that need to perform well on both parallel and distributed Grid systems. We discuss a class of such algorithms important in Chemoinformatics, bioinformatics and demographic studies. We present a unified formalism and initial performance results for clustering and dimension reduction algorithm using annealing to avoid local minima. This uses a runtime CCR/DSS that combine the features of both MPI, parallel threaded and service paradigms.
Genetic isolation of a now extinct population of bottlenose dolphins (Tursiops truncatus)

A number of dolphin species, though highly mobile, show genetic structure among parapatric and sometimes sympatric populations. However, little is known about the temporal patterns of population structure for these species. Here, we apply Bayesian inference and data from ancient DNA to assess the structure and dynamics of bottlenose dolphin (Tursiops truncatus) populations in the coastal waters of the UK. We show that regional population structure in UK waters is consistent with earlier studies suggesting local habitat dependence for this species in the Mediterranean Sea and North Atlantic. One genetically differentiated UK population went extinct at least 100 years ago and has not been replaced. The data indicate that this was a local extinction, and not a case of historical range shift or contraction. One possible interpretation is a declining metapopulation and conservation need for this species in the UK.
An Adaptive Mechanism for Accurate Query Answering under Differential Privacy

We propose a novel mechanism for answering sets of counting queries under differential privacy. Given a workload of counting queries, the mechanism automatically selects a different set of "strategy" queries to answer privately, using those answers to derive answers to the workload. The main algorithm proposed in this paper approximates the optimal strategy for any workload of linear counting queries. With no cost to the privacy guarantee, the mechanism improves significantly on prior approaches and achieves near-optimal error for many workloads, when applied under (e, δ)-differential privacy. The result is an adaptive mechanism which can help users achieve good utility without requiring that they reason carefully about the best formulation of their task.
Statistical physics of neural systems with non-additive dendritic coupling

How neurons process their inputs crucially determines the dynamics of biological and artificial neural networks. In such neural and neural-like systems, synaptic input is typically considered to be merely transmitted linearly or sublinearly by the dendritic compartments. Yet, single-neuron experiments report pronounced supralinear dendritic summation of sufficiently synchronous and spatially close-by inputs. Here, we provide a statistical physics approach to study the impact of such non-additive dendritic processing on single neuron responses and the performance of associative memory tasks in artificial neural networks. First, we compute the effect of random input to a neuron incorporating nonlinear dendrites. This approach is independent of the details of the neuronal dynamics. Second, we use those results to study the impact of dendritic nonlinearities on the network dynamics in a paradigmatic model for associative memory, both numerically and analytically. We find that dendritic nonlinearities maintain network convergence and increase the robustness of memory performance against noise. Interestingly, an intermediate number of dendritic branches is optimal for memory functionality.
Ehd4 Encodes a Novel and Oryza-Genus-Specific Regulator of Photoperiodic Flowering in Rice

Land plants have evolved increasingly complex regulatory modes of their flowering time (or heading date in crops). Rice (Oryza sativa L.) is a short-day plant that flowers more rapidly in short-day but delays under long-day conditions. Previous studies have shown that the CO-FT module initially identified in long-day plants (Arabidopsis) is evolutionary conserved in short-day plants (Hd1-Hd3a in rice). However, in rice, there is a unique Ehd1-dependent flowering pathway that is Hd1-independent. Here, we report isolation and characterization of a positive regulator of Ehd1, Early heading date 4 (Ehd4). ehd4 mutants showed a never flowering phenotype under natural long-day conditions. Map-based cloning revealed that Ehd4 encodes a novel CCCH-type zinc finger protein, which is localized to the nucleus and is able to bind to nucleic acids in vitro and transactivate transcription in yeast, suggesting that it likely functions as a transcriptional regulator. Ehd4 expression is most active in young leaves with a diurnal expression pattern similar to that of Ehd1 under both short-day and long-day conditions. We show that Ehd4 up-regulates the expression of the “florigen” genes Hd3a and RFT1 through Ehd1, but it acts independently of other known Ehd1 regulators. Strikingly, Ehd4 is highly conserved in the Oryza genus including wild and cultivated rice, but has no homologs in other species, suggesting that Ehd4 is originated along with the diversification of the Oryza genus from the grass family during evolution. We conclude that Ehd4 is a novel Oryza-genus-specific regulator of Ehd1, and it plays an essential role in photoperiodic control of flowering time in rice.
Promoting reflective interactions in a computer-supported collaborative learning environment

Engaging in reflective activities in interaction, such as explaining, justifying and evaluating problem solutions, has been shown to be potentially productive for learning. Here we address the problem of how these activities may be promoted in the context of computer-mediated communication with respect to a modelling task in physics. We present the design principles of two different communication interfaces. The first allows free text to be exchanged, and the second structures the interaction by providing a restricted set of communicative acts. Comparative analyses of interaction corpora produced with the two communication interfaces are then described. The analyses show that use of the second structured interface in performing the problem-solving task is feasible for students, and that it promotes a taskfocussed and reflective interaction. In conclusion we discuss the different resources provided by different media and the relative degrees of effort that their use requires.
Prevalence of sleep/wake disorders in persons with blindness.

Blind individuals are not only handicapped by their loss of vision, but are also affected because the loss of sight may have a secondary impact on functioning of their biological clock. The objective of the present study was to determine the impact of visual loss on sleep/wake disorders. A prospective 48-item questionnaire survey was distributed to blind individuals through the French Association Valentin Haüy, which serves blind persons. A control group matched by age, sex, geographical location and professional activity/non-activity was obtained from a panel of 20000 households representative of the French population, and this group also completed the questionnaire. From a potential blind population of 1500 subjects, 1073 questionnaires (71.5%) were completed and usable for analysis, and from a potential 1000 control subjects, 794 (79. 4%) of the questionnaires were returned and analysed. Criteria outlined in the Diagnostic and Statistical Manual of Mental Disorders, 4th revision, and the International Classification of Sleep/Wake Disorders (1990) were used to determine pathology. Individuals determined to be 'totally blind' and 'almost blind' (i.e. with less than 10% vision left in only one eye) presented a significantly higher occurrence of sleep/wake disorders than controls. Nocturnal sleep disruption, daytime somnolence, and (to a lesser degree) a 'free-running' condition are significantly more common in blind individuals. There is an increased use of sleeping pills, and a higher incidence of inappropriate involuntary daily naps. In conclusion, individuals with blindness report a significant curtailment of total sleep time and hence resulting daytime somnolence, which impacts on daytime activities. A 'free-running' condition is also a common sleep/wake impairment that may compound the handicap of blindness.
Forecasting Macro-Knowledge Competitiveness ; Integrating Panel Data and Computational Intelligence

This paper is proposing an active framework for forecasting the competitiveness of knowledge based economy (KBE) for nations to serve the public, private, and policy makers. We have used three different forecasting methods including, panel data analysis, artificial neural networks (ANN) and linear multiple regression. By structuring and feeding balanced, panel data to the ANN framework, we were able to produce a better predicted results compared with the panel data fixed effect model and the linear multiple regression. The ANN framework can be applied in the context of forecasting the competitiveness of a KBE for any nation regardless of small time periods, or little data. To achieve this forecasting model, a two steps framework is proposed. The first step was to structure the data as panels, the second step is to create and train a three layers feed-forward ANN. The purpose of the first step was to exploit both the cross sectional and the time series variations on the same economy. The ANN was used to overcome the linearity of all types of regression models used and to create the trained framework which was capable of predicting the knowledge competitiveness and progress in any economy.
Ensemble based active annotation for biomedical named entity recognition

Active Learning is an important prospect of machine learning for information extraction to deal with the problems of high cost of collecting labeled examples. It makes more efficient use of the learner's time by asking them to label only instances that are most useful for the trainer. We propose a novel method for solving this problem and show that it favorably results in the increased performance. Our proposed framework is based on an ensemble approach, where Decision Tree and Memory-based Learner are used as the base learners. The proposed approach is applied for solving the problem of named entity recognition (NER) in biomedical domain. Results show that the proposed technique indeed improves the performance of the system significantly.
Solution of Inverse Problems Using Multilayer Quaternion Neural Networks

Neural network models extended to higher-dimensional numbers have been studied in recent years. In particular, quaternions have an advantage with respect to the expression of rotation in a three-dimensional space. On the other hand, the problem that estimates the cause of an observed result is called an inverse problem, whose solutions have been studied in various engineering fields. In this study, the quaternion network inversion is proposed as a neural network solution of the inverse problem extended to the quaternion. The simulation of the inverse mapping problem is examined to show the effectiveness of the proposed method.
Phosphorylation of the Zebrafish M6Ab at Serine 263 Contributes to Filopodium Formation in PC12 Cells and Neurite Outgrowth in Zebrafish Embryos

Background Mammalian M6A, a member of the proteolipid protein (PLP/DM20) family expressed in neurons, was first isolated by expression cloning with a monoclonal antibody. Overexpression of M6A was shown to induce filopodium formation in neuronal cells; however, the underlying mechanism of is largely unknown. Possibly due to gene duplication, there are two M6A paralogs, M6Aa and M6Ab, in the zebrafish genome. In the present study, we used the zebrafish as a model system to investigate the role of zebrafish M6Ab in filopodium formation in PC12 cells and neurite outgrowth in zebrafish embryos. Methodology/Principal Findings We demonstrated that zebrafish M6Ab promoted extensive filopodium formation in NGF-treated PC12 cells, which is similar to the function of mammalian M6A. Phosphorylation at serine 263 of zebrafish M6Ab contributed to this induction. Transfection of the S263A mutant protein greatly reduced filopodium formation in PC12 cells. In zebrafish embryos, only S263D could induce neurite outgrowth. Conclusions/Significance Our results reveal that the phosphorylation status of zebrafish M6Ab at serine 263 is critical for its role in regulating filopodium formation and neurite outgrowth.
The Kesten-Stigum Reconstruction Bound Is Tight for Roughly Symmetric Binary Channels

We establish the exact threshold for the reconstruction problem for a binary asymmetric channel on the b-ary tree, provided that the asymmetry is sufficiently small. This is the first exact reconstruction threshold obtained in roughly a decade. We discuss the implications of our result for Glauber dynamics, phylogenetic reconstruction, noisy communication and the so-called "replica symmetry breaking" in spin glasses and random satisfiability problems
Relationships between number skills and cognitive abilities in people with specific arithmetic difficulties and people with dyslexia

numerical codes using power often operators, e.g. the abstract numerical code for three hundred and twenty two is {3} 10EXP2, {2} 10EXP1, {2} 10EXPO. This method of conceptualising the abstract code tells us nothing extra about what the abstract code actually consists of There have been no attempts to explain how it is stored within the brain. The choice of using the power often is also arbitrary and no reasons are given to explain why this was used instead of another base such as binary numbers. The representations of the abstract codes are, in fact, circular. It uses numbers and a power 22 operator to explain and abstract representation of other numbers. This does not add to our understanding of what the elusive abstract codes actually are. In summary, Clark and Campbell (1992) argue that unless there is compelling evidence for the existence of abstract codes (and they do not believe McCloskey & Caramazza supply it), it is more parsimonious to construct a model without them. Clark and Campbell (1991) present empirical evidence that suggests numerical processing operates on format specific representations. For example, digit size has been found to interfere with performance on magnitude comparison tasks (e.g. Besner & Coltheart, 1979; Pavio, 1975). Participants are slower to identify which number is of greater magnitude if it is physically smaller and quicker to identify it if it is physically larger. If, as McCloskey et al suggest, these digits are being converted into abstract numerical codes before comparison, the physical size of the digit should not affect the speed of processing. Clark and Campbell (1991) suggest that that the size incongruence effect can be explained by the physical size of the digit interfering with the analysis of the visual-spatial magnitude code. A further study by Foltz, Poltrock & Potts (1984) suggests that adults process number representations in different formats differently. For digits the effect of digit size incongruence had less of an impact when the magnitude gap was larger. The effect of size incongruence was stable for number words. Neuropsychological evidence is also presented to support the importance of format specific codes in number processing. Left hemisphere damage in dyscalculic patients appears to disrupt numerical processing more than right hemisphere damage (Boller & Grafman, 1983). Patients with left hemisphere damage have been found to have difficulties both with aurally presented computations (Jackson & Warrington, 1986) and number comprehension tasks (Dahmen, Hartje, Bussing & Strum 1982). Furthermore, the vast majority of dyscalculics with left hemisphere damage also have aphasic dysfunctions (Benton, 1987). Although McCloskey & Caramazza (1985) assert such patients have damaged the relevant numerical processing modules, Clark and Campbell (t 991 ) argue it
Using Supervised Learning to Improve Monte Carlo Integral Estimation

Monte Carlo techniques are used to estimate the integrals of a function using randomly generated samples. The interest in uncertainty quantification and robust design makes calculating the expected values of such functions (e.g., performance measures) important. Recent developments in scramjets, aircraft technology forecasting, structural reliability, and robust low-boom aircraft designs use Monte Carlo techniques to ensure the appropriate quantification of uncertainties. Because of high variance and slow convergence, Monte Carlo techniques require a large number of function evaluations, limiting the fidelity of the tools that can be used to predict performance. Stacked Monte Carlo is presented, which is a new method for postprocessing an existing set of Monte Carlo samples to improve integral estimation. Stacked Monte Carlo is based on combining fitting functions with cross-validation and should reduce the variance of any type of Monte Carlo integral estimate (importance sampling, quasi-Monte Carlo, etc.
Intermodulation distortion in high dynamic range microwave fiber-optic links with linearized modulators

Linearization of integrated optic intensity modulators significantly reduces the two-tone intermodulation distortion. The resulting intermodulation distortion produced by these modulators then varies as the input power to the fifth-order link system, the overall intermodulation product is a combination of third-order and higher-order terms. The authors determine the dynamic range of a cascaded microwave network consisting of a preamplifier, a high-dynamic-range fiber-optic link with a highly linear modulator, and a postamplifier. An expression is found that relates the intermodulation power at the output to the relative suppression from the signal level. As an example, a hypothetical 10-GHz low-distortion fiber-optic link that has a dynamic range of 125 dB in a bandwidth of 1 Hz is cascaded with various preamplifiers, and it is shown that the dynamic range of the system is reduced by as much as 20 dB, depending on the third-order intercept of the amplifier.
Contributing factors of successful software testing outsourcing

Software testing outsourcing is becoming a trend in many organisations nowadays. There are many advantages that are believed to be obtained through software testing outsourcing such as cost savings, access to experts and better technology as well as higher quality software products. Due to its immaturity however, it is still uncertain on what would be the critical aspects that require attention when conducting such outsourcing. This paper aims to address this concern by analysing the existing literature in order to identify the contributing factors of successful software testing outsourcing, including offshore and onshore. The analysis through the use of content analysis method enables the formulation of a conceptual process model that provides some understanding of the current practice. The model could then be used to direct more fruitful initiatives in software testing outsourcing domain in future.
The Effect of Unions on Wage Inequality in the U.S. Labor Market

This study uses Current Population Survey micro data for 1973–74 and 1993 to evaluate the effect of changing union membership on trends in male and female wage inequality. Unionization rates of men fell between the two sample periods, with bigger declines among lower skill groups. These trends account for 15–20% of the rise in male wage inequality. Union membership rates of low-wage women also declined, while unionization increased among higher-wage women. On balance, shifting unionization accounts for very little of the rise in female wage inequality. Economy-wide trends in unionization mask a sharp divergence between the private sector, where unionism was declining, and the public sector, where it was rising. Comparisons across sectors suggest that unionization substantially slowed the growth in wage inequality in the public sector.
Classifying Japanese Polysemous Verbs based on Fuzzy C-means Clustering

This paper presents a method for classifying Japanese polysemous verbs using an algorithm to identify overlapping nodes with more than one cluster. The algorithm is a graph-based unsupervised clustering algorithm, which combines a generalized modularity function, spectral mapping, and fuzzy clustering technique. The modularity function for measuring cluster structure is calculated based on the frequency distributions over verb frames with selectional preferences. Evaluations are made on two sets of verbs including polysemies.
Improving Transition-Based Dependency Parsing with Buffer Transitions

In this paper, we show that significant improvements in the accuracy of well-known transition-based parsers can be obtained, without sacrificing efficiency, by enriching the parsers with simple transitions that act on buffer nodes. First, we show how adding a specific transition to create either a left or right arc of length one between the first two buffer nodes produces improvements in the accuracy of Nivre's arc-eager projective parser on a number of datasets from the CoNLL-X shared task. Then, we show that accuracy can also be improved by adding transitions involving the topmost stack node and the second buffer node (allowing a limited form of non-projectivity). None of these transitions has a negative impact on the computational complexity of the algorithm. Although the experiments in this paper use the arc-eager parser, the approach is generic enough to be applicable to any stack-based dependency parser.
Path Diversity over the Internet: Performance Analysis and Rate Allocation

Path diversity works by setting up multiple parallel connections between the end points using the topological path redundancy of the network. In this paper, Forward Error Correction (FEC) is applied across multiple independent paths to enhance the endto-end reliability. Internet paths are modeled as erasure Gilbert-Elliot channels [1], [2]. First, it is shown that over any erasure channel, Maximum Distance Separable (MDS) codes achieve the minimum probability of irrecoverable loss among all block codes of the same size. Then, based on the adopted model for Internet paths, we prove the probability of irrecoverable loss for MDS codes decays exponentially for the asymptotically large number of paths. Moreover, it is shown that in the optimal rate allocation, each path is assigned a positive rate iff its quality is above a certain threshold. The quality of a path is defined as the percentage of the time it spends in the bad state. In other words, including a redundant path improves the reliability iff this condition is satisfied. Finally, using dynamic programming, a heuristic suboptimal algorithm with polynomial runtime is proposed for rate allocation over the available paths. This algorithm converges to the aymptotically optimal rate allocation when the number of paths is large. The simulation results show that the proposed algorithm approximates the optimal rate allocation very closely, and provides significant performance improvement compared to the alternative schemes of rate allocation.