Miracle-dz/UniFAR-FTUs huggingface dataset:
Rich morphosyntactic descriptors for factored machine translation with highly inflected languages as target

The baseline phrase-based translation approach has limited success on translating between languages with very different syntax and morphology, especially when the translation direction is from a language with fixed word structure to a highly inflected language. There are two main points to improve on: morphological translation equivalence and long range reordering. Translating the correct surface form realization of a word is dependent not only on the source word-form, but it also depends on additional morpho-syntactic information. In addition, the rich morphology of a highly inflected language permits a flexible word order, thus making difficult to model long range word order differences between languages.
CTLA4 and generalized vitiligo: two genetic association studies and a meta‐analysis of published data

Several lines of evidence have implicated the gene encoding cytotoxic T lymphocyte antigen 4 (CTLA4) in susceptibility to various autoimmune diseases. However, published studies of genetic association between CTLA4 polymorphisms and vitiligo have yielded conflicting results. Here, we describe two new genetic association studies of CTLA4 single‐nucleotide polymorphisms (SNPs) and generalized vitiligo in two independent Romanian Caucasian (CEU) case‐control cohorts. The first study, of SNPs rs1863800, rs231806, rs231775, rs3087243, rs11571302, rs11571297, and rs10932037, showed no allelic, genotypic, or haplotypic association with generalized vitiligo. The second study, of SNP rs231775, likewise showed no significant association. To enhance statistical power over that of any individual study, we carried out a meta‐analysis that incorporated these two new studies and all other published genetic association studies of CTLA4 SNPs and vitiligo in CEU populations. While there was no association with vitiligo overall, the meta‐analysis showed significant association of SNP rs231775 in that subgroup of vitiligo patients who also had other concomitant autoimmune diseases. Similarly, there was near‐significant association in this same patient subgroup with several other CTLA4 SNPs that are in linkage disequilibrium with rs231775. Our results indicate that the association of CTLA4 with vitiligo is weak, and indeed may be secondary, driven by primary genetic association of CTLA4 with other autoimmune diseases that are epidemiologically associated with vitiligo.
Forestry Scene Geometry Estimation Via Statistical Learning

In the context of a forest inventory application, given preprocessing of the 2D airborne images of a forest plot, we focus on estimating the parameters which control the 3D geometry of trees, in order to generate a virtual forest. The major contribution of this paper lies in the proposed probabilistic graphical model and the novel sampling scheme for solving this data fusion problem. To deal with the variability introduced from both the image data and the preprocessing procedures, we adopt a Jump-Diffusion Markov Chain Monte Carlo sampling paradigm to traverse the possible state spaces. Within each state space, a stochastic version of the Expectation Maximization algorithm is employed to explore the plausible parameters and latent scene geometry by finding the local maxima. Therefore, the propose algorithm estimates the number of trees and the associated parameters, and also infer the 3D scene geometry that is consistent with the preprocessed data and the expert prior knowledge. Experiments on both synthetic and real forestry data show promising results.
Measuring tie strength in multidimensional networks

Online social networks have allowed us to build massive networks of weak ties: acquaintances and nonintimate ties we use all the time to spread information and thoughts. Conversely, strong ties are people we really trust, persons most like us and whose social circles tightly overlap with our own. Unfortunately, social media do not incorporate tie strength in the creation and management of relationships, and treat all users the same: friend or stranger, with little or nothing in between. In the current work, we address the challenging issue of detecting on online social networks the strong and intimate ties from the huge mass of such mere social contacts. In order to do so, we propose a novel multidimensional deﬁnition of tie strength which exploits the existence of multiple online social links between two individuals. We test our deﬁnition on a multidimensional network constructed over users in Foursquare, Twitter and Facebook, analyzing the structural role of strong e weak links, and the correlations with the most common similarity measures.
Coupled dictionary learning and feature mapping for cross-modal retrieval

In this paper, we investigate the problem of modeling images and associated text for cross-modal retrieval tasks such as text-to-image search and image-to-text search. To make the data from image and text modalities comparable, previous cross-modal retrieval methods directly learn two projection matrices to map the raw features of the two modalities into a common subspace, in which cross-modal data matching can be performed. However, the different feature representations and correlation structures of different modalities inhibit these methods from efficiently modeling the relationships across modalities through a common subspace. To handle the diversities of different modalities, we first leverage the coupled dictionary learning method to generate homogeneous sparse representations for different modalities by associating and jointly updating their dictionaries. We then use a coupled feature mapping scheme to project the derived sparse representations from different modalities into a common subspace in which cross-modal retrieval can be performed. Experiments on a variety of cross-modal retrieval tasks demonstrate that the proposed method outperforms the state-of-the-art approaches.
Electronic circuit model for evaluating S-kink distorted current-voltage curves

So-called S-kink current vs. voltage (J-V) curves have been reported for solar cells based on numerous different materials and architectures, including but not limited to devices based on organic materials, chalcogenides including CIGS and CdTe, and passivated c-Si heterojunction devices. Reports frequently attribute the behavior to the presence of non-ideal energy offsets at one or both contacts. We report a method for modeling S-Kink behavior through the use of a modified diode circuit design for which an anti-parallel diode pair, in series with the main p-n heterojunction diode, serves to limit the current flow at voltage bias values near VOC. The model provides a means to extract diode parameters from J-V plots exhibiting S-Kink behavior.
Physical layer implementation of network coding in two-way relay networks

Network coding, which works in the network layer, is an effective technology to improve the throughput of two-way relay networks. In this paper, we compare the existing network coding schemes: traditional network coding (NC) scheme, physical-layer network coding (PNC) scheme and soft network coding (SNC) scheme, and propose a new physical layer scheme which can be seen as the implementation of network coding in two-way relay networks. Relay nodes combine the received signals from two source nodes before demodulation and channel decoding. The computational complexity and BER performance of the proposed scheme are analyzed compared with the previous schemes. Theoretical analysis show that the proposed scheme can save 50% computational cost of demodulation and channel decoding processes compared with NC scheme, meanwhile increase the power efficiency of the relay nodes in two-way relay networks significantly. Future works with the proposed scheme are also discussed.
High cardiometabolic risk in healthy Chilean adolescents: associations with anthropometric, biological and lifestyle factors

Abstract Objective To analyse the prevalence of cardiovascular risk factors in healthy adolescents of low to middle socio-economic status and to study the influence of anthropometric, biological and lifestyle factors on the risk of metabolic syndrome (MetS). Design Cross-sectional study. BMI, waist circumference, blood pressure, fat and lean mass (by dual-energy X-ray absorptiometry), TAG, HDL-cholesterol, glucose, insulin, homeostatic model assessment–insulin resistance index (HOMA-IR), food intake and physical activity were measured. Cardiovascular risk factors were defined using the International Diabetes Federation criteria and insulin resistance using HOMA-IR ≥2·6. Bivariate and multivariate regressions examined the associations between MetS and anthropometric, biological and lifestyle factors. Setting Observational cohort study including Chilean adolescents, who were part of a follow-up study beginning in infancy. Subjects Adolescents aged 16–17 years (n 667). Results In the sample, 16·2 % had obesity and 9·5 % had MetS. Low HDL-cholesterol (69·9 %), abdominal obesity (33·3 %) and fasting hyperglycaemia (8·7 %) were the most prevalent cardiovascular risk factors. In males, obesity (OR=3·7; 95 % CI 1·2, 10·8), insulin resistance (OR=3·0; 95 % CI 1·1, 8·2), physical inactivity (OR=2·9; 95 % CI 1·1, 7·7) and sarcopenia (OR=21·2; 95 % CI 4·2, 107·5) significantly increased the risk of MetS. In females, insulin resistance (OR=4·9; 95 % CI 1·9, 12·6) and sarcopenia (OR=3·6; 95 % CI 1·1, 11·9) were significantly associated with MetS. Conclusions High prevalences of obesity, abdominal obesity, dyslipidaemia, fasting hyperglycaemia and MetS were found in healthy adolescents. In both sexes, sarcopenia and insulin resistance were important risk factors of MetS. Promotion of active lifestyles at the school level and regulation of the sale of energy-dense foods are needed.
Sperm performance in conspecific and heterospecific female fluid

Abstract Divergent sexual selection within allopatric populations may result in divergent sexual phenotypes, which can act as reproductive barriers between populations upon secondary contact. This hypothesis has been most tested on traits involved in precopulatory sexual selection, with less work focusing on traits that act after copulation and before fertilization (i.e., postcopulatory prezygotic traits), particularly in internally fertilizing vertebrates. However, postcopulatory sexual selection within species can also drive trait divergence, resulting in reduced performance of heterospecific sperm within the female reproductive tract. Such incompatibilities, arising as a by‐product of divergent postcopulatory sexual selection in allopatry, can represent reproductive barriers, analogous to species‐assortative mating preferences. Here, we tested for postcopulatory prezygotic reproductive barriers between three pairs of taxa with diverged sperm phenotypes and moderate‐to‐high opportunity for postcopulatory sexual selection (barn swallows Hirundo rustica versus sand martins Riparia riparia, two subspecies of bluethroats, Luscinia svecica svecica versus L. s. namnetum, and great tits Parus major versus blue tits Cyanistes caeruleus). We tested sperm swimming performance in fluid from the outer reproductive tract of females, because the greatest reduction in sperm number in birds occurs as sperm swim across the vagina. Contrary to our expectations, sperm swam equally well in fluid from conspecific and heterospecific females, suggesting that postcopulatory prezygotic barriers do not act between these taxon pairs, at this stage between copulation and fertilization. We therefore suggest that divergence in sperm phenotypes in allopatry is insufficient to cause widespread postcopulatory prezygotic barriers in the form of impaired sperm swimming performance in passerine birds.
FlashFQ: A Fair Queueing I/O Scheduler for Flash-Based SSDs

On Flash-based solid-state disks (SSDs), different I/O operations (reads vs. writes, operations of different sizes) incur substantially different resource usage. This presents challenges for fair resource management in multi-programmed computer systems and multitenant cloud systems. Existing timeslice-based I/O schedulers achieve fairness at the cost of poor responsiveness, particularly when a large number of tasks compete for I/O simultaneously. At the same time, the diminished benefits of I/O spatial proximity on SSDs motivate fine-grained fair queueing approaches that do not enforce task-specific timeslices. This paper develops a new Flash I/O scheduler called FlashFQ. It enhances the start-time fair queueing schedulers with throttled dispatch to exploit restricted Flash I/O parallelism without losing fairness. It also employs I/O anticipation to minimize fairness violation due to deceptive idleness. We implemented FlashFQ in Linux and compared it with several existing I/O schedulers--Linux CFQ [2], an Argon [19]-inspired quanta scheduler, FIOS timeslice scheduler [17], FIOS with short timeslices, and 4-Tag SFQ(D) [11]. Results on synthetic I/O benchmarks, the Apache web server, and Kyoto Cabinet key-value store demonstrate that only FlashFQ can achieve both fairness and high responsiveness on Flash-based SSDs.
Brain‐derived neurotrophic factor but not vesicular zinc promotes TrkB activation within mossy fibers of mouse hippocampus in vivo

The neurotrophin receptor, TrkB receptor tyrosine kinase, is critical to central nervous system (CNS) function in health and disease. Elucidating the ligands mediating TrkB activation in vivo will provide insights into its diverse roles in the CNS. The canonical ligand for TrkB is brain‐derived neurotrophic factor (BDNF). A diversity of stimuli also can activate TrkB in the absence of BDNF, a mechanism termed transactivation. Zinc, a divalent cation packaged in synaptic vesicles along with glutamate in axons of mammalian cortical neurons, can transactivate TrkB in neurons and heterologous cells in vitro. Yet the contributions of BDNF and zinc to TrkB activation in vivo are unknown. To address these questions, we conducted immunohistochemical (IHC) studies of the hippocampal mossy fiber axons and boutons using an antibody selective for pY816 of TrkB, a surrogate measure of TrkB activation. We found that conditional deletion of BDNF resulted in a reduction of pY816 in axons and synaptic boutons of hippocampal mossy fibers, thereby implicating BDNF in activation of TrkB in vivo. Unexpectedly, pY816 immunoreactivity was increased in axons but not synaptic boutons of mossy fibers in ZnT3 knockout mice that lack vesicular zinc. Marked increases of BDNF content were evident within the hippocampus of ZnT3 knockout mice and genetic elimination of BDNF reduced pY816 immunoreactivity in these mice, implicating BDNF in enhanced TrkB activation mediated by vesicular zinc depletion. These findings support the conclusion that BDNF but not vesicular zinc activates TrkB in hippocampal mossy fiber axons under physiological conditions. J. Comp. Neurol. 522:3885–3899, 2014. © 2014 Wiley Periodicals, Inc.
Self-adaptive differential evolution with neighborhood search

In this paper we investigate several self-adaptive mechanisms to improve our previous work on NSDE, which is a recent DE variant for numerical optimization. The self-adaptive methods originate from another DE variant, SaDE, but are remarkably modified and extended to fit our NSDE. And thus a self-adaptive NSDE (SaNSDE) is proposed to improve NSDEpsilas performance. Three self-adaptive mechanisms are utilized in SaNSDE: self-adaptation for two candidate mutation strategies, self-adaptations for controlling scale factor F and crossover rate CR, respectively. Experimental studies are carried out on a broad range of different benchmark functions, and the proposed SaNSDE has shown significant superiority over NSDE.
Using Graph-Based Ensemble Learning to Classify Imbalanced Data

The class imbalance problems have attracted considerable attention from researchers of different fields. Ensemble learning has emerged as a powerful approach to address the imbalanced data and improved accuracy and robustness over the single model. In this paper, we present a novel ensemble method based on a bipartite graph (GraphEL) by maximizing the consensus among the multiple binary models. In this bipartite graph, we take into account the probability offered by the multiple classifiers and the average distance provided by the original data, which appear in the graph in the form of weights. Experimental results on 22 imbalanced data sets demonstrate the benefits of the proposed method over the conventional imbalance data handing methods.
Scheduling Architecture and Algorithms within the ICENI Grid Middleware

The ICENI Grid Middleware system enables the use of component based applications in a distributed heterogeneous environment and is implemented as a layered service oriented architecture. The scheduling of component applications across this environment takes place though the ICENI Scheduling Framework which allows ‘pluggable’ scheduling algorithms and platform specific launchers. The architecture of the Scheduling Framework is described, which decouples the scheduling algorithm from both the application and the architecture. Four scheduling algorithms (game theory, simulated annealing, random and best of n random) are presented and compared under the criteria of time and cost optimisation. We show that the simulated annealing scheduler produces more optimal results in the case of both time and cost
Objective video quality metrics for HDTV services: A survey

The exponential growth of video traffic is expected to reach 62% of the global Internet traffic by the end of 2015 [1]. This presents as a significant challenge for the television service providers who need to employ networking technologies to monitor specific Quality of Service (QoS) parameters such as packet loss rate, jitter and delay, to ensure an acceptable level of quality. However, recent research has demonstrated that the quality experienced by the end-user does not correlate to the QoS parameters employed by most service providers [2]. This paper investigates the correlation between the QoS parameters and the quality perceived by the end. user. These results indicate that although the QoS parameters may sometimes achieve high correlation with respect to the quality perceived by the viewer, they still have large variances. This suggests that the QoS parameters are not enough to quantify the subjective quality with a high level of confidence. This work further compares a number of existing objective video quality metrics. The results presented in this paper show that the Full-Reference Motion based Video Integrity Evaluation (MOVIE) metric and the Spatio-Temporal Reduced Reference Entropic Differences (STRRED) metric achieve excellent correlation with the subjective scores. This research also demonstrates that the STRRED metric and its derivatives have several advantages over the MOVIE metric since less information needs to be transmitted and it is less computationally intensive.
O‐ethylthymidine adducts are the most relevant damages for mutation induced by N‐ethyl‐N‐nitrosourea in female germ cells of Drosophila melanogaster

Responses to genotoxic agents vary not only among organisms, test systems, and cellular stages, but also between sexes; little, however, is known about the mutagenic consequences of chemical exposures to female germ cells. In this study, the mutagenicity of N‐ethyl‐N‐nitrosourea (ENU) was analyzed in female germ cells of Drosophila melanogaster using the recessive‐lethal test and the vermilion system, which simultaneously generates information on induced mutation frequency and mutation spectrum. ENU was mutagenic in all stages of oogenesis, although there were differences among the stages. In mature and immature oocytes, ENU‐induced mutations in the vermilion locus were 43.5% A:T→G:C transitions, 39.1% A:T→T:A transversions, 8.7% G:C→A:T transitions, and 8.7% A:T→C:G transversions, indicating that the most important premutagenic lesions induced by this chemical are O4‐ethylthymine and O2‐ethylthymine. The low frequency of mutation involving O6‐ethylguanine (i.e., G:C→A:T transitions) could be a consequence of the repair of these lesions by O6‐methylguanine DNA methyltransferase. Comparison of these results with those previously obtained in male germ cells stresses the importance of the repair activity of the analyzed cells, because the mutation spectrum in female germ cells was similar to the spectrum obtained with repair‐proficient spermatogonial cells and different from repair‐deficient postmeiotic cells. The results also indicate that studies with female germ cells could be an alternative to the use of premeiotic male germ cells, especially when the analysis of these cells is difficult or almost impossible and when studies of in vivo DNA repair in premeiotic germ cells are performed. Environ. Mol. Mutagen. 40:143–152, 2002. © 2002 Wiley‐Liss, Inc.
Competing risks as a multi-state model

This paper deals with the competing risks model as a special case of a multi-state model. The properties of the model are reviewed and contrasted to the so-called latent failure time approach. The relation between the competing risks model and right-censoring is discussed and regression analysis of the cumulative incidence function briefly reviewed. Two real data examples are presented and a guide to the practitioner is given.
Association of hyperleptinemia with peripheral arterial disease in hypertensive patients

Objective: Hypertension is a risk factor for peripheral artery disease (PAD). Serum leptin plays an important role in promoting endothelial dysfunction. The aim of this study is to investigate whether the leptin level is associated with PAD in hypertensive patients. Materials and Methods: Ninety-eight hypertensive patients were enrolled in this study. Ankle-brachial index (ABI) values were measured using an automated oscillometric device. Patients with an ABI value <0.9 were considered the low ABI group. C-reactive protein (CRP) was measured using standard enzymatic automated methods. Serum levels of human leptin were determined using a commercially available enzyme immunoassay. Results: Eighteen (18.4%) hypertensive patients were included in the low ABI group. Hypertensive patients in the low ABI group had higher serum creatinine (P < 0.001), CRP (P = 0.003), and leptin (P < 0.001) levels, higher prevalence of diabetes (P = 0.036), and current smoking (P = 0.034) than patients in the normal ABI group. Univariate linear regression analyses revealed that body weight (P = 0.014), waist circumference (P = 0.010), body mass index (P = 0.002), and logarithmically transformed CRP (log-CRP,P= 0.001) were positively correlated with serum log-leptin levels in hypertensive patients. Multivariate stepwise linear regression analysis showed that log-leptin (β = 0.439, adjusted R2 change = 0.224,P< 0.001) was also an associated factor of PAD in hypertensive patients. Conclusion: A higher log-leptin value is an independent predictor of PAD in hypertensive patients.