Miracle-dz/UniFAR-FTUs huggingface dataset:
Contribution of Genome-Wide Association Studies to Scientific Research: A Pragmatic Approach to Evaluate Their Impact

The factual value of genome-wide association studies (GWAS) for the understanding of multifactorial diseases is a matter of intense debate. Practical consequences for the development of more effective therapies do not seem to be around the corner. Here we propose a pragmatic and objective evaluation of how much new biology is arising from these studies, with particular attention to the information that can help prioritize therapeutic targets. We chose multiple sclerosis (MS) as a paradigm disease and assumed that, in pre-GWAS candidate-gene studies, the knowledge behind the choice of each gene reflected the understanding of the disease prior to the advent of GWAS. Importantly, this knowledge was based mainly on non-genetic, phenotypic grounds. We performed single-gene and pathway-oriented comparisons of old and new knowledge in MS by confronting an unbiased list of candidate genes in pre-GWAS association studies with those genes exceeding the genome-wide significance threshold in GWAS published from 2007 on. At the single gene level, the majority (94 out of 125) of GWAS-discovered variants had never been contemplated as plausible candidates in pre-GWAS association studies. The 31 genes that were present in both pre- and post-GWAS lists may be of particular interest in that they represent disease-associated variants whose pathogenetic relevance is supported at the phenotypic level (i.e. the phenotypic information that steered their selection as candidate genes in pre-GWAS association studies). As such they represent attractive therapeutic targets. Interestingly, our analysis shows that some of these variants are targets of pharmacologically active compounds, including drugs that are already registered for human use. Compared with the above single-gene analysis, at the pathway level GWAS results appear more coherent with previous knowledge, reinforcing some of the current views on MS pathogenesis and related therapeutic research. This study presents a pragmatic approach that helps interpret and exploit GWAS knowledge.
Hand target extraction from infrared images based on the danger theory

The gray distribution of infrared thermal image is uneven, which brings difficulties to image segmentation. In this paper, based on the “the danger theory” of immunology, a method for hand segmentation is proposed. By using the dual-threshold of immune genetic algorithm, the image is segmented into a target pixel set, a background pixel set and a blurred pixel set. According to the timing characteristics of trace images, the 3D template is designed to extract features. According to the template characteristics, the danger signal is defined and the danger theory is used to identify the blurred pixel set. The proposed algorithm is compared with watershed method, active contour model and recent research achievements. Experimental results show that the proposed algorithm has a better performance of target extraction rate, coincidence with reference standard, and less absolute error rate.
Promoting Social Connectedness through Human Activity-Based Ambient Displays

Existing research in ambient assisted living (AAL) confirms the success of context aware applications in conveying feelings of connectedness and creating a sense of co-presence. Awareness of an elder's activities could trigger emotional responses and reveal pertinent information concerning their health, moods and habits. This paper presents a bidirectional ambient display platform, enabling asynchronous viewing of activity levels to create awareness and enhance social connectedness. An automatic smartphone based human activity recognition (HAR) system reveals activities of the elderly and caregivers in their daily lives. The results suggest that perception of activity levels is useful for fostering social connectedness and strengthening engagement between caregivers and their elderly counterparts. These findings may help interaction designers tailor AAL solutions for increased social interaction and context awareness.
Effects of lexical frequency and syntactic complexity in spoken-language comprehension: Evidence from the auditory moving-window technique.

In 2 experiments, a new technique called the auditory moving window was used to investigate aspects of spoken-language processing. Participants paced their way through spoken sentences divided into word or wordlike segments, and their processing time for each segment was recorded. The 1st experiment demonstrated that high-frequency words in spoken sentences require less time to process than do low-frequency words. The 2nd experiment demonstrated that words in syntactically demanding contexts (i.e., the disambiguating word of so-called garden-path sentences) are processed longer than the same words in syntactically simpler contexts. Helpful prosodic information appeared to facilitate reanalysis of garden-path structures but did not seem to prevent the misanalysis. The implications of these findings for issues in spoken-language comprehension are discussed. The authors conclude that the auditory moving-window technique provides a useful tool for addressing largely unexplored issues in spoken-language comprehension.
A fragment-decoding plus missing-data imputation ASR system evaluated on the 2nd CHiME Challenge

This paper reports on our entry to the small-vocabulary, moving-talker track of the 2nd CHiME challenge. The system we employ is based on the one that we developed for the 1st CHiME challenge, the latest results of which are reported in (Ma and Barker, 2012). Our motivation is to benchmark the system on the new CHiME challenge and to measure the extent to which it is robust against speaker motion, a feature of the second challenge that was absent in the first. The paper presents a brief overview of our fragment-decoding plus missingdata imputation system and then makes a component-bycomponent analysis of the system performance on both the 1st and 2nd CHiME challenge datasets. We conclude that due to its reliance on pitch and spectral cues the system is robust against the introduction of small speaker motions. We achieve an average keyword recognition score of 85.9% compared to 86.3% for the stationary speaker condition.
A novel CoS-enabled path selection algorithm with traffic grooming function for multi-layer optical networks

Aiming at resolving the problem of Class of Service (CoS) and traffic grooming, a CoS-enabled path selection algorithm with traffic grooming function (CPSATG) is proposed in this paper. Simulations are conducted to compare the proposed scheme with methods which have not considered CoS and traffic redundancy. Results show that CPSATG has a much better blocking probability performance and effective resource utilization than the existing methods with almost the same cost of network nodes.
An Isolated Quasi-Resonant Multiphase Single-Stage Topology for 48-V VRM Applications

In order to increase the efficiency of modern microprocessors power supplies used in data centers, the 48-V dc distribution bus is gaining growing attention. For such applications, voltage regulation modules (VRMs) are currently obtained using two-stage conversion systems with an intermediate 12-V dc bus. This paper presents an innovative single-stage approach for the 48-V VRM based on a quasi-resonant constant on-time (COT) operation. The proposed topology inherently integrates the multiphase approach, providing fast phase shedding and flat high-efficiency curves even at light load conditions. This is a unique advantage, usually not available in the two-stage approach, that is very important in server architectures, where high efficiency is required even at light load conditions. The paper analyses the circuit topology, and proposes a control architecture for fast transient response, including the current sharing capabilities, and a solution for implementing the integrated magnetics. The digital controller has been implemented in 0.16-$\mu$ m lithography together with a digital pulse-width-modulation with a 195 ps resolution, and a 40 MS/s, 7-bit ADC. Experimental results show an efficiency of 93.1% for a 250 A, 1.8 V VRM, and of 93.2% for a 102 A, 1.2-V double data rate (DDR) power supply.
Pheromone-sensing neurons regulate peripheral lipid metabolism in Caenorhabditis elegans

It is now established that the central nervous system plays an important role in regulating whole body metabolism and energy balance. However, the extent to which sensory systems relay environmental information to modulate metabolic events in peripheral tissues has remained poorly understood. In addition, it has been challenging to map the molecular mechanisms underlying discrete sensory modalities with respect to their role in lipid metabolism. In previous work our lab has identified instructive roles for serotonin signaling as a surrogate for food availability, as well as oxygen sensing, in the control of whole body metabolism. In this study, we now identify a role for a pair of pheromone-sensing neurons in regulating fat metabolism in C. elegans, which has emerged as a tractable and highly informative model to study the neurobiology of metabolism. A genetic screen revealed that GPA-3, a member of the Gα family of G proteins, regulates body fat content in the intestine, the major metabolic organ for C. elegans. Genetic and reconstitution studies revealed that the potent body fat phenotype of gpa-3 null mutants is controlled from a pair of neurons called ADL(L/R). We show that cAMP functions as the second messenger in the ADL neurons, and regulates body fat stores via the neurotransmitter acetylcholine, from downstream neurons. We find that the pheromone ascr#3, which is detected by the ADL neurons, regulates body fat stores in a GPA-3-dependent manner. We define here a third sensory modality, pheromone sensing, as a major regulator of body fat metabolism. The pheromone ascr#3 is an indicator of population density, thus we hypothesize that pheromone sensing provides a salient 'denominator' to evaluate the amount of food available within a population and to accordingly adjust metabolic rate and body fat levels.
The q-Exponential Probability Discounting of Gain and Loss

Probability discounting is defined as the devaluation of outcomes as the probability of receiving or paying those decreases. A q-exponential probability discounting model based on Tsallis’ statistics has been proposed in econophysics (Takahashi, 2007, Physica A). We examined (a) fitness of the models to behavioral data of probability discounting of both gain and loss; and (b) relationships between parameters in the q-exponential probability discounting model across gain and loss. Our results demonstrated that, for both gain and loss, the q-exponential model better fits the behavioral data than exponential and hyperbolic functions, and there is the sign effect in q-exponential probability discounting. Relationships between Kahneman-Tversky’s prospect theory in behavioral economics and the q-exponential probability discounting are high-lightened.
Wireless network-level partial relay cooperation: A stable throughput analysis

In this work, we study the benefit of partial relay cooperation. We consider a two-node system consisting of one source and one relay node transmitting information to a common destination. The source and the relay have external traffic and in addition, the relay is equipped with a flow controller to regulate the incoming traffic from the source node. The cooperation is performed at the network level. A collision channel with erasures is considered. We provide an exact characterization of the stability region of the system and we also prove that the system with partial cooperation is always better or at least equal to the system without the flow controller.
Pilot Enhancement of the Arthritis Foundation Exercise Program with a Healthy Aging Program.

Older adults with arthritis or joint pain were targeted for a pilot program enhancing the Arthritis Foundation Exercise Program with the 10 Keys™ to Healthy Aging Program. Using a one-group, pre-post design, feasibility was examined and improvements in preventive behaviors, arthritis outcomes, and cardiometabolic outcomes were explored. A 10-week program was developed, instructors were recruited and trained, and four sites and 51 participants were recruited. Measures included attendance, adherence, satisfaction, preventive behaviors, Western Ontario and McMaster Universities Osteoarthritis Index (pain and stiffness), glucose, and cholesterol. Three fourths of participants attended >50% of the sessions. At 6 and 12 months, more than one half performed the exercises 1 to 2 days per week, whereas 28% and 14% exercised 3 to 7 days per week, respectively. Participants (92%) rated the program as excellent/very good. Nonsignificant changes were observed in expected directions. Effect sizes were small for arthritis and cardiometabolic outcomes. This program engaged community partners, demonstrated feasibility, and showed improvements in some preventive behaviors and health risk profiles. [Res Gerontol Nurs. 2016; 9(3):123-132. ].
Novel Multiplex PageRank in Multilayer Networks

Multilayer networks are described as complex networks in which each node is related to all other nodes in distinct layers. These layers form a class of cooperating and interacting networks. Examples of such multilayer networks are transport networks, where people can move from one city to another through various modes of transportation. The ranking of nodes in multilayer networks is one of the most challenging and demanding tasks on complex networks. Since pairs of nodes are related through various types of links in multilayers, the ranking of nodes should inevitably reveal the weights of nodes in all corresponding layers. In this paper, we exploit the concept of populations’ random migration in a multiplex transport network to propose a new Multiplex PageRank centrality measure, where the effects of influence and feedback between networks on the centrality of nodes are directly considered. We apply the proposed measure to an artificial duplex network. Findings indicate that considering the network with multilayers helps uncover the rankings of nodes, which are different from the rankings in a monotonous network. Moreover, the Multiplex PageRank centrality measure of dynamical network models is discussed for further practical application and applied to an urban transport network. The results demonstrate the effectiveness of our measure in the dynamical network.
Increased burden of deleterious variants in essential genes in autism spectrum disorder

Significance Essential genes (EGs) are necessary for survival and the development of an organism. Our study is focused on investigating the role of EGs in autism spectrum disorder (ASD). With a comprehensive catalog of 3,915 mammalian EGs, we show that there is both an elevated burden of damaging mutations in EGs in ASD probands and also, an enrichment of EGs in known ASD risk genes. Moreover, the analysis of EGs in the developing brain identified clusters of coexpressed EGs implicated in ASD. Overall, we provide evidence that genes that are essential for survival and fitness also contribute to ASD risk and lead to the disruption of normal social behavior. Autism spectrum disorder (ASD) is a heterogeneous, highly heritable neurodevelopmental syndrome characterized by impaired social interaction, communication, and repetitive behavior. It is estimated that hundreds of genes contribute to ASD. We asked if genes with a strong effect on survival and fitness contribute to ASD risk. Human orthologs of genes with an essential role in pre- and postnatal development in the mouse [essential genes (EGs)] are enriched for disease genes and under strong purifying selection relative to human orthologs of mouse genes with a known nonlethal phenotype [nonessential genes (NEGs)]. This intolerance to deleterious mutations, commonly observed haploinsufficiency, and the importance of EGs in development suggest a possible cumulative effect of deleterious variants in EGs on complex neurodevelopmental disorders. With a comprehensive catalog of 3,915 mammalian EGs, we provide compelling evidence for a stronger contribution of EGs to ASD risk compared with NEGs. By examining the exonic de novo and inherited variants from 1,781 ASD quartet families, we show a significantly higher burden of damaging mutations in EGs in ASD probands compared with their non-ASD siblings. The analysis of EGs in the developing brain identified clusters of coexpressed EGs implicated in ASD. Finally, we suggest a high-priority list of 29 EGs with potential ASD risk as targets for future functional and behavioral studies. Overall, we show that large-scale studies of gene function in model organisms provide a powerful approach for prioritization of genes and pathogenic variants identified by sequencing studies of human disease.
Opinion mining approaches on Amazon product reviews: A comparative study

The process of extracting of people's opinion, experience and emotions from reviews, blogs and other sources is known as opinion mining. This paper compares our lexicon dictionary based approach with n-grams with three famous Machine Leaning (ML) algorithms, which are random forest learner with word vector, decision tree learner with document vector, and random forest with n-gram. To predict positive and negative sentiments, Amazon's Product Review dataset has been used. Accuracy of each of these algorithms is calculated by using ROC curve in order to compare which algorithm performs best on a given Amazon dataset. Experimental result shows that lexicon based approach outperforms other machine learning techniques.
The impact of long-chain n-3 polyunsaturated fatty acids on human health

Abstract A considerable literature has been published on the health benefits of fish, oil-rich fish and fish oils and their constituent long-chain (LC) n-3 PUFA. Evidence from epidemiological studies highlights the cardioprotective attributes of diets rich in fish, especially oil-rich fish. Data from intervention trials are consistent in suggesting that LC n-3 PUFA lower the risk of CVD, probably by the multiple mechanisms of lowering serum triacylglycerols, improving the LDL:HDL ratio, anti-arrhythmic effects on heart muscle, improved plaque stability, anti-thrombotic effects and reduced endothelial activation. Research indicates LC n-3 PUFA provision has an impact during development, and there is preliminary evidence that docosahexaenoic acid supplementation during pregnancy could optimise brain and retina development in the infant. LC n-3 PUFA are also postulated to ameliorate behavioural and mental health disturbances such as depression, schizophrenia, dementia and attention deficit hyperactivity disorder. However, despite some positive evidence in each of these areas, use of LC n-3 PUFA in these conditions remains at the experimental stage. In the case of immune function, there is little doubt that LC n-3 PUFA have a positive effect. Although intervention trials in rheumatoid arthritis show strong evidence of benefit, evidence for efficacy in other inflammatory conditions, including Crohn's disease, ulcerative colitis, psoriasis, lupus, multiple sclerosis, cystic fibrosis and asthma, is inconsistent or inadequate. More promising evidence in some conditions may come from studies which attempt to modify the fetal environment using LC n-3 PUFA supplementation during pregnancy.
diffuStats: an R package to compute diffusion‐based scores on biological networks

Summary Label propagation and diffusion over biological networks are a common mathematical formalism in computational biology for giving context to molecular entities and prioritizing novel candidates in the area of study. There are several choices in conceiving the diffusion process—involving the graph kernel, the score definitions and the presence of a posterior statistical normalization—which have an impact on the results. This manuscript describes diffuStats, an R package that provides a collection of graph kernels and diffusion scores, as well as a parallel permutation analysis for the normalized scores, that eases the computation of the scores and their benchmarking for an optimal choice. Availability and implementation The R package diffuStats is publicly available in Bioconductor, https://bioconductor.org, under the GPL‐3 license.
Achieving Multiple Functions of Three-Phase Electric Springs in Unbalanced Three-Phase Power Systems Using the Instantaneous Power Theory

Three-phase electric spring (3-ph ES) has recently been proposed as a fast demand response technology for applications in unbalanced power systems fed with a mixture of conventional and renewable power generation. Using the instantaneous power theory as the theoretical framework, this paper presents the criteria and conditions for minimizing the average and oscillating power of the 3-ph ES for the first time. A detailed analysis of the use of 3-ph ES is included for providing multiple control objectives of voltage regulation and power balancing of the 3-ph power system, and minimization of the average and oscillating ac power of the ES. A corresponding control scheme implementable in a single controller is included and explained. The control scheme has been practically verified with experiments.
The relationship between indentation and uniaxial creep in amorphous selenium

Ultralow load indentation techniques can be used to obtain time-dependent mechanical properties, termed indentation creep, of materials. However, the comparison of indentation creep data to that obtained during conventional creep testing is difficult, mainly due to the determination of the strain rate experienced by the material during indentation. Using the power-law creep equation and the equation for Newtonian viscosity as a function of stress and strain rate, a relationship between indentation strain rate, and the effective strain rate occurring during the indentation creep process is obtained. Indentation creep measurements on amorphous selenium in the Newtonian viscous flow regime above the glass transition temperature were obtained. The data were then used to determine that the coefficient relating indentation strain rate to the effective strain rate is equal to 0.09, or.
Morphological : Functional Aspects of Electro-Discharge Machined Surface Textures

This study investigates a set of "non-common" surface topography parameters of Electro-Discharge Machined surfaces that give differing aspects of texture related to morphological characterization and possible tribological applications. The parameters considered are the Abbott (bearing) curve parameter at 10 % of the raw unfiltered and the roughness profile height P tp10% and R tp10% , respectively, the also bearing curve oriented R k family of parameters (ISO 13565-2:1996), the skewness R sk and the kurtosis R ku of the profile height distribution, the mean spacing R sm , and the fractal dimension D. The correlation of the aforementioned parameters with pulse energy is examined to allow appropriate selection of machining conditions for producing functionally desirable Electro-Discharge Machined textures.
Foundations of Silviculture upon an Ecological Basis

IN this manual, Prof. Tourney, of Yale University, deals with silviculture from the point of view of the forests of the United States, a country which, he correctly says, owing to its vast size and diverse character, imposes inevitable limitations. But this is not the only point in which Prof. Tourney's work differs from the usual type of silvicultural manual. He writes:Foundations of Silviculture upon an Ecological Basis.Prof. James W. Toumay. Vol. 1. Pp. xxv + 438. (New York: John Wiley and Sons, Inc.; London: Chapman and Hall, Ltd., 1928.) 20s. net.