Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Muscle Transcriptome between Pigs with Divergent Meat Quality Phenotypes Identifies Genes Related to Muscle Metabolism and Structure

Background Meat quality depends on physiological processes taking place in muscle tissue, which could involve a large pattern of genes associated with both muscle structural and metabolic features. Understanding the biological phenomena underlying muscle phenotype at slaughter is necessary to uncover meat quality development. Therefore, a muscle transcriptome analysis was undertaken to compare gene expression profiles between two highly contrasted pig breeds, Large White (LW) and Basque (B), reared in two different housing systems themselves influencing meat quality. LW is the most predominant breed used in pig industry, which exhibits standard meat quality attributes. B is an indigenous breed with low lean meat and high fat contents, high meat quality characteristics, and is genetically distant from other European pig breeds. Methodology/Principal Findings Transcriptome analysis undertaken using a custom 15 K microarray, highlighted 1233 genes differentially expressed between breeds (multiple-test adjusted P-value<0.05), out of which 635 were highly expressed in the B and 598 highly expressed in the LW pigs. No difference in gene expression was found between housing systems. Besides, expression level of 12 differentially expressed genes quantified by real-time RT-PCR validated microarray data. Functional annotation clustering emphasized four main clusters associated to transcriptome breed differences: metabolic processes, skeletal muscle structure and organization, extracellular matrix, lysosome, and proteolysis, thereby highlighting many genes involved in muscle physiology and meat quality development. Conclusions/Significance Altogether, these results will contribute to a better understanding of muscle physiology and of the biological and molecular processes underlying meat quality. Besides, this study is a first step towards the identification of molecular markers of pork quality and the subsequent development of control tools.
The role of allergy and nonspecific airway hyperresponsiveness in the pathogenesis of chronic obstructive pulmonary disease.

Although the information that has been reviewed leaves many questions unanswered, some conclusions can be drawn from available data. (1) Smoking appears to increase the risk of sensitization to certain inhaled antigens encountered in the workplace; however, there is no definite evidence that smoking increases the frequency or intensity of allergy to common aeroallergens in the general population. On average, smokers have higher serum total IgE concentrations and blood eosinophil counts than do nonsmokers, but the mechanisms underlying these alterations are not clear. Analysis of these relationships is complicated by observations suggesting that atopic persons are less likely to become and to remain regular cigarette smokers. (2) Long-term cigarette smoking may be associated with increased nonspecific airway responsiveness, although the magnitude of this effect is relatively small when one adjusts for prechallenge level of pulmonary function. This effect of smoking may be more pronounced in atopic persons. (3) Atopy, as assessed by skin testing and serum IgE concentrations, is associated with asthma, nonspecific airway hyperresponsiveness, and reduced pulmonary function level in population data. However, there is no clear evidence that atopy is a risk factor for irreversible airflow obstruction in persons without asthma. Population data do not indicate how much of the reduction in pulmonary function associated with atopy and asthma is potentially reversible. (4) Blood eosinophil count appears inversely related to the level of pulmonary function and directly related to the rate of decline of pulmonary function among nonsmokers. Reports vary concerning whether the relationship of eosinophil count to level of pulmonary function remains after excluding subjects with diagnosed asthma. This relationship may be determined largely by a clinically distinguishable subset of nonsmokers with "asthmatic bronchitis. " Presumably, these observations reflect an adverse impact of eosinophilic inflammation in the airways or lung parenchyma. It is not clear whether this represents an allergic response because skin-test reactivity to common aeroallergens and serum total IgE concentration do not show similar relationships to reduced level and rapid decline of pulmonary function. (5) Among smokers, nonspecific airway hyperresponsiveness appears to be associated with an accelerated longitudinal decline of pulmonary function, although most studies indicating this association are limited by either a retrospective design or lack of adjustment for prechallenge level of pulmonary function. (ABSTRACT TRUNCATED AT 400 WORDS)
Estimation, imagery or computation: low resolution electromagnetic tomography (LORETA) measures brain activity during performance of balance scale tasks

The balance scale task is an often studied topic. Whereas these studies are mainly focused on the solving strategies deduced from behavior, present study examined whether solving strategies, like estimation, imagery and computation, can be inferred from activity in brain areas estimated by Low Resolution Electromagnetic Tomography (LORETA). Using electroencephalography (EEG), brain activation was measured in thirteen physics students and fourteen psychology students during predicting the movement of the balance scale of 120 simple balance scale tasks and 120 conflict balance scale tasks. The results show a difference between physics students and psychology students in number of correct predictions in both simple and conflict balance scale tasks. Physics students had a longer reaction time than psychology students in conflict balance scale tasks. In performing simple balance scale tasks physics students and psychology students both had a greater activity in the left angular gyrus and the left inferior frontal cortex, that seem to be responsible for computation than in brain areas, that are assumed to be responsible for estimation and mental imagery. In addition, there was no difference between physics and psychology students in activity in brain areas involved in imagery. In conflict balance scale tasks, physics students had greater bilateral activation in the inferior and superior parietal lobe, including the intraparietal sulcus and the extrastriate middle occipital gyrus and fusiform gyrus, that seem to be responsible for estimation.
Respiratory muscle work compromises leg blood flow during maximal exercise.

We hypothesized that during exercise at maximal O2 consumption (VO2max), high demand for respiratory muscle blood flow (Q) would elicit locomotor muscle vasoconstriction and compromise limb Q. Seven male cyclists (VO2max 64 +/- 6 ml.kg-1.min-1) each completed 14 exercise bouts of 2.5-min duration at VO2max on a cycle ergometer during two testing sessions. Inspiratory muscle work was either 1) reduced via a proportional-assist ventilator, 2) increased via graded resistive loads, or 3) was not manipulated (control). Arterial (brachial) and venous (femoral) blood samples, arterial blood pressure, leg Q (Qlegs; thermodilution), esophageal pressure, and O2 consumption (VO2) were measured. Within each subject and across all subjects, at constant maximal work rate, significant correlations existed (r = 0.74-0.90; P < 0.05) between work of breathing (Wb) and Qlegs (inverse), leg vascular resistance (LVR), and leg VO2 (VO2legs; inverse), and between LVR and norepinephrine spillover. Mean arterial pressure did not change with changes in Wb nor did tidal volume or minute ventilation. For a +/-50% change from control in Wb, Qlegs changed 2 l/min or 11% of control, LVR changed 13% of control, and O2 extraction did not change; thus VO2legs changed 0.4 l/min or 10% of control. Total VO2max was unchanged with loading but fell 9.3% with unloading; thus VO2legs as a percentage of total VO2max was 81% in control, increased to 89% with respiratory muscle unloading, and decreased to 71% with respiratory muscle loading. We conclude that Wb normally incurred during maximal exercise causes vasoconstriction in locomotor muscles and compromises locomotor muscle perfusion and VO2.
Body temperatures of modern and extinct vertebrates from 13C-18O bond abundances in bioapatite

The stable isotope compositions of biologically precipitated apatite in bone, teeth, and scales are widely used to obtain information on the diet, behavior, and physiology of extinct organisms and to reconstruct past climate. Here we report the application of a new type of geochemical measurement to bioapatite, a “clumped-isotope” paleothermometer, based on the thermodynamically driven preference for 13C and 18O to bond with each other within carbonate ions in the bioapatite crystal lattice. This effect is dependent on temperature but, unlike conventional stable isotope paleothermometers, is independent from the isotopic composition of water from which the mineral formed. We show that the abundance of 13C-18O bonds in the carbonate component of tooth bioapatite from modern specimens decreases with increasing body temperature of the animal, following a relationship between isotope “clumping” and temperature that is statistically indistinguishable from inorganic calcite. This result is in agreement with a theoretical model of isotopic ordering in carbonate ion groups in apatite and calcite. This thermometer constrains body temperatures of bioapatite-producing organisms with an accuracy of 1–2 °C. Analyses of fossilized tooth enamel of both Pleistocene and Miocene age yielded temperatures within error of those derived from similar modern taxa. Clumped-isotope analysis of bioapatite represents a new approach in the study of the thermophysiology of extinct species, allowing the first direct measurement of their body temperatures. It will also open new avenues in the study of paleoclimate, as the measurement of clumped isotopes in phosphorites and fossils has the potential to reconstruct environmental temperatures.
Dynamic screening and charge state of fast ions in plasma and solids

This paper addresses the effect of target plasma electrons on the charge state of energetic ions, penetrating a target composed of bound as well as plasma electrons. Dynamic screening of the projectile Coulomb potential by the plasma electrons brings about a depression in the ionization energy of the ionic projectiles, as has been verified experimentally. This in turn makes the ionization cross-sections larger, while making the recombination cross-section smaller, thereby causing an increase in the ion charge state compared to the case of a gas target. The effect of the plasma environment, where the valence electrons are treated as plasma, is illustrated here for a 2 MeV carbon beam penetrating amorphous carbon targets of varying densities.
A bibliometric and network analysis of the field of computational linguistics

The ACL Anthology is a large collection of research papers in computational linguistics. Citation data were obtained using text extraction from a collection of PDF files with significant manual postprocessing performed to clean up the results. Manual annotation of the references was then performed to complete the citation network. We analyzed the networks of paper citations, author citations, and author collaborations in an attempt to identify the most central papers and authors. The analysis includes general network statistics, PageRank, metrics across publication years and venues, the impact factor and h‐index, as well as other measures.
Verilog Implementation Of Da Based Dct With High Accuracy Error-Compensated Adder Tree

In brief, by operating the shifting and addition in parallel, an error-compensated addertree (ECAT) is proposed to deal with the truncation errors and to achieve low-error and high-throughput discrete cosine transform (DCT) design. Instead of the 12 bits used in previous works, 9-bit distributed arithmetic-precision is chosen for this work so as to meet peak-signal-tonoise-ratio (PSNR) requirements. Thus, an areaefficient DCT core is implemented to achieve 1 Gpels/s throughput rate with gate counts of 22.2 K for the PSNR requirements outlined in the
The Strengths of High-Achieving Black High School Students in a Racially Diverse Setting

Abstract:Robert Hill (1972) identified strengths of Black families: strong kinship bonds, strong work orientation, adaptability of family roles, high achievement orientation, and religious orientation. Some suggest these strengths sustain the physical, emotional, social, and spiritual needs of Blacks. This study used narratives and survey data from a cohort of high-achieving Black students in a highly selective honors high school and integrated every element of Hill's Black family strengths-perspective to social/structural inequality and diversity rationale ideologies. Results revealed, upon entering the racially diverse school-setting, Black students demonstrated resilience by working through initial feelings of apprehension and establishing racial and gender solidarity through social clubs. Implications for promoting racial integration, development of resiliency, and the academic success of Black students are provided.
Distributed Cooperative Two-Cell Zero-Forcing Precoding With Local Channel Correlation

This study focuses on local channel correlation based zero-forcing (ZF) precoding design for boosting weighted ergodic sum-rate (WESR) in the cooperative two-cell multiple-input single-output system. We first present that the WESRs of the statistical channel state information (SCSI) aided general eigenvector coordinated beamforming (SCSI-GE) and the conventional ZF beamforming with erroneous instantaneous channel state information (ICSI; eICSI-ZF) saturate to constant values at high SNR due to inter-cell interference. Motivated by this, we develop a ZF coordination framework with local SCSI requirement at the transmitter and low data-sharing backhaul load. Additionally, a low-cost but effective two-dimensional ZF precoding design called 2d-SZF is proposed, which involves only distributed computations based on the local channel correlation. Theoretical analysis and simulation results confirm that the proposed local SCSI-based 2d-SZF scheme yields the most desirable WESR while the WESRs of SCSI-GE and eICSI-ZF both saturate in the high regime of SNR, and are respectively sensitive to the level of spatial channel correlation and ICSI accuracy at finite SNR.
Self-adaptive differential evolution based on best and mean schemes

Differential evolution (DE), one of the evolutionary algorithms (EAs), is well-known for its quality solutions and speed convergence. Just like any EA, the execution of DE depends on the selection of its control parameters consisting of population size, crossover rate and scale factor. DE is operated by two different kinds of search mechanisms, i.e., exploration and exploitation. The selection of control parameters affects these search mechanisms, and thus, the performance of DE. Ranges on setting DE's control parameters are suggested in most studies but it still depends heavily on a user's knowledge and experiences, as well as the types of problems. The common approach adopted by users is the trial-and-error method but this approach consumes time. Since adaptation has been responsible for the search optimal solutions in DE, the adaptability should be further utilized to determine DE's optimal control parameters. Therefore, we proposed a self-adaptive DE which is able to self-determine its control parameters based on an ensemble. An ensemble is operated based on two different parameter selection schemes, i.e., BEST and MEAN. The performances of DEs based on the selection schemes in 20 benchmarks problems are compared based on best-fitness, mean-fitness, crossover rate and scale factor. The experimental results showed that the proposed self-adaptive DEs are able to perform adequately well in the benchmark problems. Besides that, the results have shown an interesting pattern between crossover rate and scale factor when the DE is given freedom to determine its control parameters.
Affective effects of agent proximity in conversational systems

The aim of this study was to investigate, if the simulated proximity level of an anthropomorphic conversational agent and the affective contents in the agent's speech influence the subjects' affective experiences. Eight subjects were exposed to messages given by the agent using synthetic speech. The agent character's simulated proximity level (intimate, personal, social, and public) and the affective contents of the speech message (negative, neutral, and positive) were systematically varied in the experiment. The proximity levels were simulated by displaying the agent on a screen in different sizes. After each speech message, the subjects rated their affective experience on four scales: valence, arousal, dominance, and message intimacy. They also chose a preferred agent proximity level. The results showed that by manipulating the agent's simulated proximity level, experienced dominance could be significantly influenced. Further, by manipulating the affective contents of the speech, experienced valence and intimacy could be significantly influenced. The personal and social proximity levels were preferred by the subjects.
Scaffolding Player Location Awareness through Audio Cues in First-Person Shooters

Digital games require players to learn various skills, which is often accomplished through play itself. In multiplayer games, novices can feel overwhelmed if competing against better players, and can fail to improve, which may lead to unsatisfying play and missed social play opportunities. To help novices learn the requisite skills, we first determined how experts accomplish an important task in multiplayer FPS games -- locating their opponent. After determining that an understanding of audio cues and how to leverage them was critical, we designed and evaluated two systems for introducing this skill of locating opponents through audio cues -- a training system, and a modified game interface. We found that both systems improved accuracy and confidence, but that the training system led to more audio cues being recognized. Our work may help people of disparate skill play together, by scaffolding novices to learn and use a strategy commonly employed by experts.
MCU at NTCIR: A Resources Limited Chinese Textual Entailment Recognition System

Recognizing inference in text is the task of f inding the textual entailment relation between the given hypothesis and text fragments. Developing a high-performance text paraphrasing system usually requires rich external knowledge such as syntactic parsing, thesaurus which is limited in Chinese since the Chinese word segmentation problem should be resolve first. In this paper, we go different line. We propose a pattern-based and support vector machine-based trainable text entailment tagging framework under the condition of part-of-speech tagging information is available. We derive two exclusive feature sets for learners. One is the operations between the text pairs, while the other adopted the traditional bag-of-words model. Finally, we train the classifier with the above features. The official results indicate the effectiveness of our method. In terms of accuracy, our method achieves 53.6% for Traditional Chinese MC task (second place) and 55.4% for Traditional Chinese BC task. After the correction, our method in BC task is 67.9% with the same setting.
Neuromotor recovery from stroke: computational models at central, functional, and muscle synergy level

Computational models of neuromotor recovery after a stroke might help to unveil the underlying physiological mechanisms and might suggest how to make recovery faster and more effective. At least in principle, these models could serve: (i) To provide testable hypotheses on the nature of recovery; (ii) To predict the recovery of individual patients; (iii) To design patient-specific “optimal” therapy, by setting the treatment variables for maximizing the amount of recovery or for achieving a better generalization of the learned abilities across different tasks. Here we review the state of the art of computational models for neuromotor recovery through exercise, and their implications for treatment. We show that to properly account for the computational mechanisms of neuromotor recovery, multiple levels of description need to be taken into account. The review specifically covers models of recovery at central, functional and muscle synergy level.
Performance Study of OFDM over Multipath Fading Channels for Next Wireless Communications

Orthogonal Frequency Division Multiplexing (OFDM) is a very efficient multicarrier technique. OFDM is used more and more in recent wideband digital communications. It has numerous advantages such as the ability to handle severe channel conditions, efficient spectral usage, reduced inter symbol interference (ISI), and high data rate. Therefore, it has been utilized in many future wired and wireless communication systems 4G LTE mobile communications. In this paper, mainly focus on the performance evaluation and study of OFDM system over multipath fading channels such as AWGN, Rician and Rayleigh fading channels. Based on simulation results will make us understand some of these effects and signal-to-noise ratios (SNRs), channels are compared together in order to rank them according to the delivered signal. Quality of the signals, bit-error rates (BERs), and peak signal-to-noise ratios (PSNRs) of the received signals are the aspects in which system performance is evaluated.
Mutation Scanning in Wheat by Exon Capture and Next-Generation Sequencing

Targeted Induced Local Lesions in Genomes (TILLING) is a reverse genetics approach to identify novel sequence variation in genomes, with the aims of investigating gene function and/or developing useful alleles for breeding. Despite recent advances in wheat genomics, most current TILLING methods are low to medium in throughput, being based on PCR amplification of the target genes. We performed a pilot-scale evaluation of TILLING in wheat by next-generation sequencing through exon capture. An oligonucleotide-based enrichment array covering ~2 Mbp of wheat coding sequence was used to carry out exon capture and sequencing on three mutagenised lines of wheat containing previously-identified mutations in the TaGA20ox1 homoeologous genes. After testing different mapping algorithms and settings, candidate SNPs were identified by mapping to the IWGSC wheat Chromosome Survey Sequences. Where sequence data for all three homoeologues were found in the reference, mutant calls were unambiguous; however, where the reference lacked one or two of the homoeologues, captured reads from these genes were mis-mapped to other homoeologues, resulting either in dilution of the variant allele frequency or assignment of mutations to the wrong homoeologue. Competitive PCR assays were used to validate the putative SNPs and estimate cut-off levels for SNP filtering. At least 464 high-confidence SNPs were detected across the three mutagenized lines, including the three known alleles in TaGA20ox1, indicating a mutation rate of ~35 SNPs per Mb, similar to that estimated by PCR-based TILLING. This demonstrates the feasibility of using exon capture for genome re-sequencing as a method of mutation detection in polyploid wheat, but accurate mutation calling will require an improved genomic reference with more comprehensive coverage of homoeologues.