Miracle-dz/UniFAR-FTUs huggingface dataset:
Early Exposure to Soy Isoflavones and Effects on Reproductive Health: A Review of Human and Animal Studies

Soy isoflavones are phytoestrogens with potential hormonal activity due to their similar chemical structure to 17-β-estradiol. The increasing availability of soy isoflavones throughout the food supply and through use of supplements has prompted extensive research on biological benefits to humans in chronic disease prevention and health maintenance. While much of this research has focused on adult populations, infants fed soy protein based infant formulas are exposed to substantial levels of soy isoflavones, even when compared to adult populations that consume a higher quantity of soy-based foods. Infant exposure, through soy formula, primarily occurs from birth to one year of life, a stage of development that is particularly sensitive to dietary and environmental compounds. This has led investigators to study the potential hormonal effects of soy isoflavones on later reproductive health outcomes. Such studies have included minimal human data with the large majority of studies using animal models. This review discusses key aspects of the current human and animal studies and identifies critical areas to be investigated as there is no clear consensus in this research field.
Processing online news streams for large-scale semantic analysis

While Internet has enabled us to access a vast amount of online news articles originating from thousands of different sources, the human capability to read all these articles has stayed rather constant. Usually, the publishing industry takes over the role of filtering this enormous amount of information and presenting it in an appropriate way to the group of their subscribers. In this paper, the semantic analysis of such news streams is discussed by introducing a system that streams online news collected by the Europe Media Monitor to our proposed semantic news analysis system. Thereby, we describe in detail the emerging challenges and the corresponding engineering solutions to process incoming articles close to real-time. To demonstrate the use of our system, the case studies show a) temporal analysis of entities, such as institutions or persons, and b) their co-occurence in news articles.
Teens in Rice County Are More Interdependent and Think More Holistically Than Nearby Wheat County

China’s smallest province Ningxia sits in North Central China. Surrounded by herding cultures to the north and wheat farmers to the south, Qingtongxia is a small outpost of rice farming fed by the Yellow River. We test the hypothesis that rice-farming cultures are more interdependent by comparing high school students from Qingtongxia (N = 190) to students in a nearby wheat district, Yuanzhou (N = 223). Comparing two nearby counties provides a natural test case that controls for third variables. Students in the rice county thought more holistically, treated a close friend better than a stranger, and showed lower implicit individualism. Students in the rice area showed more relative perception than students from the wheat areas on the practice trials of the framed line task, but differences were nonsignificant on the main trials. Differences between teenagers—born after the year 2000—suggest that rice–wheat differences continue among China’s next generation.
pubmed2ensembl: A Resource for Mining the Biological Literature on Genes

Background The last two decades have witnessed a dramatic acceleration in the production of genomic sequence information and publication of biomedical articles. Despite the fact that genome sequence data and publications are two of the most heavily relied-upon sources of information for many biologists, very little effort has been made to systematically integrate data from genomic sequences directly with the biological literature. For a limited number of model organisms dedicated teams manually curate publications about genes; however for species with no such dedicated staff many thousands of articles are never mapped to genes or genomic regions. Methodology/Principal Findings To overcome the lack of integration between genomic data and biological literature, we have developed pubmed2ensembl (http://www.pubmed2ensembl.org), an extension to the BioMart system that links over 2,000,000 articles in PubMed to nearly 150,000 genes in Ensembl from 50 species. We use several sources of curated (e.g., Entrez Gene) and automatically generated (e.g., gene names extracted through text-mining on MEDLINE records) sources of gene-publication links, allowing users to filter and combine different data sources to suit their individual needs for information extraction and biological discovery. In addition to extending the Ensembl BioMart database to include published information on genes, we also implemented a scripting language for automated BioMart construction and a novel BioMart interface that allows text-based queries to be performed against PubMed and PubMed Central documents in conjunction with constraints on genomic features. Finally, we illustrate the potential of pubmed2ensembl through typical use cases that involve integrated queries across the biomedical literature and genomic data. Conclusion/Significance By allowing biologists to find the relevant literature on specific genomic regions or sets of functionally related genes more easily, pubmed2ensembl offers a much-needed genome informatics inspired solution to accessing the ever-increasing biomedical literature.
Noise-Robust ASR for the third 'CHiME' Challenge Exploiting Time-Frequency Masking based Multi-Channel Speech Enhancement and Recurrent Neural Network

In this paper, the Lingban entry to the third 'CHiME' speech separation and recognition challenge is presented. A time-frequency masking based speech enhancement front-end is proposed to suppress the environmental noise utilizing multi-channel coherence and spatial cues. The state-of-the-art speech recognition techniques, namely recurrent neural network based acoustic and language modeling, state space minimum Bayes risk based discriminative acoustic modeling, and i-vector based acoustic condition modeling, are carefully integrated into the speech recognition back-end. To further improve the system performance by fully exploiting the advantages of different technologies, the final recognition results are obtained by lattice combination and rescoring. Evaluations carried out on the official dataset prove the effectiveness of the proposed systems. Comparing with the best baseline result, the proposed system obtains consistent improvements with over 57% relative word error rate reduction on the real-data test set.
Control of quantized multi-agent systems with linear nearest neighbor rules: A finite field approach

We study the problem of controlling a multi-agent system where each agent is only allowed to be in a discrete and finite set of states. Each agent is capable of updating its state based on the states of its neighbors, and there is a leader agent in the network that is allowed to update its state in arbitrary ways (within the discrete set) in order to put all agents in a desired state. We present a novel solution to this problem by viewing the discrete states of the system as elements of a finite field. Specifically, we develop a theory of structured linear systems over finite fields, and show that such systems will be controllable provided that the size of the finite field is sufficiently large, and that the graph associated with the system satisfies certain properties. We then use these results to show that a multi-agent system with a leader node is controllable via a linear nearest-neighbor update as long as there is a path from the leader to every node, and that the number of discrete states for each node is large enough.
OpenQoS: An OpenFlow controller design for multimedia delivery with end-to-end Quality of Service over Software-Defined Networks

OpenFlow is a Software Defined Networking (SDN) paradigm that decouples control and data forwarding layers of routing. In this paper, we propose OpenQoS, which is a novel OpenFlow controller design for multimedia delivery with end-to-end Quality of Service (QoS) support. Our approach is based on QoS routing where the routes of multimedia traffic are optimized dynamically to fulfill the required QoS. We measure performance of OpenQoS over a real test network and compare it with the performance of the current state-of-the-art, HTTP-based multi-bitrate adaptive streaming. Our experimental results show that OpenQoS can guarantee seamless video delivery with little or no video artifacts experienced by the end-users. Moreover, unlike current QoS architectures, in OpenQoS the guaranteed service is handled without having adverse effects on other types of traffic in the network.
Adaptive Identification and Recovery of Jointly Sparse Vectors

In this paper we present a novel approach to the solution of a sequence of SMV problems with a joint support. This type of problem arises in a number of applications such as multiband signal reconstruction and source localization. The approach we present is adaptive in that it solves it as a sequence of weighted SMV problems rather than collecting the measurement vectors and solving an MMV problem. The weights are adaptively updated from one instance to the next. This approach avoids delays and large memory requirements (at the cost of increased computational load) with the added capability of tracking changes in joint signal supports.
Ergonomic Assessment of Mental Workload in Higher Education. Effects of Education System on Student’s Workload Perception

Adaptation to the European Higher Education Area (EHEA) has meant a significant change in the workload of students. The main objective of this study is to evaluate and compare the perception of the workload of adapted and no-adapted to EHEA students in Psychology, and to analyze the nature of the changes produced by this adaptation considering several academic activities: attending theoretical classes, attending practical classes, conducting group work outside the classroom, searching for material and bibliography, studying and personal work, attending tutorials and other activities (attending seminars, conferences, etc.). The sample consisted of 645 students (397 no-adapted and 248 adapted). To measure the perceived workload, the NASA-TLX scale was used. The scale permits to distinguish six workload dimensions: effort, mental demand, temporal demand, physical demand, performance and frustration. The results show a significant increase in the perceived workload of attending practical classes and specially in performing group work outside the classroom. It is concluded that the adaptation to the EHEA has meant an increase in the perception of students' workload, which points out the need to develop training programs and evaluation of the teamwork competence, one of the most important transversal competence indicated in the professional profile of the degree in psychology.
Exploring Patterns of Change Processes Over Distinct In-Treatment Phases of Cognitive and Exposure Therapies for Electronic Gaming Machine Problem Gamblers

Abstract Little is known about the change processes in gambling disorder-specific cognitive therapy (CT) and exposure therapy (ET). These therapies are underpinned by the cognitive approach (i.e., restructuring gambling cognitions) and the psychobiological approach (i.e., elimination of gambling urges) to treating problem gambling. Here, piecewise-linear modelling is used in a secondary analysis of randomised trial data for a CT group (n = 44) versus an ET group (n = 43) with the aim to open a discourse on how individuals respond to CT and ET relative to theory. Measures were administered between therapy sessions (average = 6.2 per individual) across 18 weeks for gambling urge (GUS) and gambling cognitions (GRCS). Results indicated the ET group had a stronger reduction in GUS (p < .01) in the first 4 weeks of treatment. Between 4–12 weeks, improvement in GUS (p < .01) and GRCS (p = .02) was more rapid in the CT group. Both groups experienced comparable improvements from 12–18 weeks. These findings have implications for further treatment development, including a combined cognitive and exposure approach that is flexibly adapted to the patient. A larger trial is needed to formally establish change processes and identify differences in problem gambler subgroups. This would provide therapists capacity to offer each patient a clear direction and an expedited pathway to their preferred outcome.
DPLL with a Trace: From SAT to Knowledge Compilation

We show that the trace of an exhaustive DPLL search can be viewed as a compilation of the propositional theory. With different constraints imposed or lifted on the DPLL algorithm, this compilation will belong to the language of d-DNNF, FBDD, and OBDD, respectively. These languages are decreasingly succinct, yet increasingly tractable, supporting such polynomial-time queries as model counting and equivalence testing. Our contribution is thus twofold. First, we provide a uniform framework, supported by empirical evaluations, for compiling knowledge into various languages of interest. Second, we show that given a particular variant of DPLL, by identifying the language membership of its traces, one gains a fundamental understanding of the intrinsic complexity and computational power of the search algorithm itself. As interesting examples, we unveil the "hidden power" of several recent model counters, point to one of their potential limitations, and identify a key limitation of DPLL-based procedures in general.
Control of modular aerial robots: Combining under- and fully-actuated behaviors

This work presents the design of flight control algorithms for set-point stabilization of a class of modular aerial vehicles obtained by rigidly interconnecting a number of single ducted-fan aircraft. Interestingly enough, for such a modular configuration, certain types of interconnection structure between the different modules may lead to redundancy both in term of the overall number of actuators available onboard and in the number of degrees of freedom that can be actually governed simultaneously. The design of the control policy for such a complex dynamical behavior is handled by defining specific control allocation algorithms for each possible case (for which a taxonomy is given in the paper) and by deriving an overall control structure capable to switch among these policies according to the properties of the selected configuration. This approach results in an architecture that combines classical control schemes for under-actuated air vehicles - such as those employed in most Vertical Take-Off and Landing (VTOL) aircraft - with control strategies for fully-actuated vehicles.
Causal Inference in Statistics and the Quantitative Sciences

Causal inference attempts to uncover the structure of the data and eliminate all non-causative explanations for an observed association. The goal of most, if not all, statistical inference is to uncover causal relationships. However it is not in general possible to conclude causality from a standard statistical inference procedure, it is merely possible to conclude that the observed association between two variables is not due to chance. Statistical inference procedures do not provide any information about which variable causes the other, or whether the apparent relationship between the two variables is due to another, confounding variable. An explicit introduction of the philosophy of and approaches to causation was first brought into the statistical sciences in 1986 by Paul Holland [1], although references to causal approaches exist in the literature up to 60 years prior (see, for example, [2, 3]). Since then, there has been an explosion of research into the area in a variety of disciplines including statistics (particularly biostatistics), computer science, and economics. Causal inference in statistics is a broad area of research, under which many topics fall. In particular, the following themes were considered:
Personal efficacy, attitudes towards immigrants, and voting behavior among latino and white university students

This study tests a model linking attitudes towards immigrants with personal efficacy and voting behavior on proposition 187 (an endorsement of an anti-immigrant ballot initiative in California). Using a sample of 218 White and Latino university student results indicated that whites endorsed greater negative attitudes towards immigrants (on the Attitudes Towards Immigrants Scale) as compared to Latinos. In addition, Latinos were more internal in their personal efficacy (on the Spheres of Control Scale) when compared to Whites. Consistent with research drawn from a subset of attribution theory, we also found that for Whites, greater internal personal efficacy was associated with more negative attitudes towards immigrants. Also supporting a subset of research in attribution theory, for Whites, greater internal personal efficacy was associated with support for proposition 187. For both Whites and Latinos, those who held more negative attitudes towards immigrants were more likely to report having voted for proposition 187. For Latinos, no relationships were found between personal efficacy and neither attitudes towards immigrants nor voting behavior. Study implications are discussed.
Small-Scale Crisis in Cosmology – Sterile Neutrinos to the Rescue?

The $\Lambda$CDM standard model of cosmology is in excellent agreement with data on large scales but has difficulty explaining all observations on small scales. I discuss a simple particle physics model involving a new MeV-scale gauge boson that mediates dark matter self-interactions and dark matter interactions with a new light fermion. This allows to solve all small-scale problems of $\Lambda$CDM cosmology. It would be very attractive to identify the new light particle with a sterile neutrino, but it appears that this option is disfavored.
Enhanced emotional empathy after psychosocial stress in young healthy men

Abstract Empathy is a core prerequisite for human social behavior. Relatively, little is known about how empathy is influenced by social stress and its associated neuroendocrine alterations. The current study was designed to test the impact of acute stress on emotional and cognitive empathy. Healthy male participants were exposed to a psychosocial laboratory stressor (trier social stress test, (TSST)) or a well-matched control condition (Placebo-TSST). Afterwards they participated in an empathy test measuring emotional and cognitive empathy (multifaceted empathy test, (MET)). Stress exposure caused an increase in negative affect, a rise in salivary alpha amylase and a rise in cortisol. Participants exposed to stress reported more emotional empathy in response to pictures displaying both positive and negative emotional social scenes. Cognitive empathy (emotion recognition) in contrast did not differ between the stress and the control group. The current findings provide initial evidence for enhanced emotional empathy after acute psychosocial stress.
An automatic grasp planning system for service robots

Service robots need many different informations about the objects, to grasp and manipulate them. Besides the physical information such as the geometry and weight, semantic information of the objects is also needed. To model both of these informations, we have constructed a multimodal object modeling center. It can model the physical properties of the object, such as the textures and the 3D geometry, with a digitizer and movable stereo cameras. Other properties of the objects relevant for grasping can also be automatically computed. Further, a human teacher can communicate with the system with multimodal techniques to bring the semantic information about the grasping to the system. The modeled information in this modeling center covers all the information a grasp planning needs. We have implemented a grasp planning system based on the grasp simulator “GraspIt! ” to plan high quality grasps. The semantic information is represented as shape primitives, which are treated by the grasp planning as obstacles or must-touch regions of object to influence the resulted grasps. The modeled physical, semantic and automatically computed information, together with the computed grasps are saved in a database, which provides the service robot the needed knowledge to grasp household objects.
GRB 050717: A Long, Short-Lag, High-Peak Energy Burst Observed by Swift and Konus

The long burst GRB 050717 was observed simultaneously by the Burst Alert Telescope (BAT) on Swift and the Konus instrument on Wind. Significant hard to soft spectral evolution was seen. Early gamma-ray and X-ray emission was detected by both BAT and the X-Ray Telescope (XRT) on Swift. The XRT continued to observe the burst for 7.1 days and detect it for 1.4 days. The X-ray light curve showed a classic decay pattern; the afterglow was too faint for a jet break to be detected. No optical, infrared, or ultraviolet counterpart was discovered despite deep searches within 14 hr of the burst. Two particular features of the prompt emission make GRB 050717 a very unusual burst. First, the peak of the νF(ν) spectrum was observed to be 2401 keV for the main peak, which is the highest value of Epeak ever observed. Second, the spectral lag for GRB 050717 was determined to be 2.5 ± 2.6 ms, consistent with zero and unusually short for a long burst. This lag measurement suggests that this burst has a high intrinsic luminosity and hence is at high redshift (z > 2.7). Despite these unusual features, GRB 050717 exhibits the classic prompt and afterglow behavior of a gamma-ray burst.
50-Gb/s Direct Conversion QPSK Modulator and Demodulator MMICs for Terahertz Communications at 300 GHz

We demonstrate direct quadrature modulator and demodulator monolithic microwave integrated circuits for future terahertz communications at 300 GHz based on the quadrature phase-shift keying (QPSK) modulation format. For the modulating and demodulating signal, we employed half-Gilbert cell mixers, which provide balanced signaling and moderate performance in conversion efficiency with a simple circuit configuration. In order to maintain the balance performance of the modulator and demodulator, passive baluns and couplers are implemented with thin-film microstrip lines, which exhibit less insertion loss than inverted microstrip lines (IMSLs), while the active mixers are based on IMSLs for short interconnections. The half-Gilbert-cell mixers have a wide enough operation bandwidth for high-throughput communications of more than 10% at 300 GHz. According to the static constellation of the modulator, imbalance is expected to be less than approximately ±0.6 dB ∠4°. A nonchip back-to-back experiment was conducted at up to 60 Gb/s, and 50-Gb/s operation was verified with a low bit error rate on the order of 10-8 or less. The results demonstrate that the QPSK modulation scheme can be applied to double the data rate at terahertz frequencies.
A Process for Analyzing Agent-Oriented Patterns

Many agent-oriented patterns have been written to capture agentoriented software engineering experiences over the past ten years. However, there is no unified organization of these patterns and their reuse is almost non existent. In this paper, we present a process for analyzing agent-oriented patterns leading towards the creation of a unified view of these patterns. The process is based on the Two Way classification scheme, a classification scheme designed to provide a comprehensive framework for analyzing, classifying and describing agent-oriented patterns. We have investigated almost 100 patterns and classified 28 of them. This paper demonstrates the use of the process to analyze and classify 4 agent-oriented patterns. We also describe an informal exercise involving 6 agent-oriented patterns to gauge the suitability of other researchers using our analysis process for classifying