Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding key constraints and practice design in Rugby Union place kicking: Experiential knowledge of professional kickers and experienced coaches

Place kicks present valuable opportunities to score points in Rugby Union, which are typically performed under varying constraints in competitive performance environments. Previous quantitative studies suggest these interacting constraints can influence fluctuations in place kick success. To further the understanding of how fluctuations in place kicking success emerge, our aim was twofold: i) to explore and identify the key constraints that professional place kickers and experienced place kicking coaches perceive to influence the difficulty of a place kick and ii) to understand the level to which current place kicking practice environments represent these key constraints experienced in performance environments. Six professional place kickers and six experienced place kicking coaches were interviewed. Using a deductive thematic analysis, 11 key constraints were identified: individual constraints of expectation for success and fatigue, task constraints of angle and distance to goalposts, environmental constraints of wind, weather, pitch, and crowd, and situational constraints of previous kicking performance, time remaining and current score margin. Place kicking is typically practised individually or with a small number of place kickers in isolation from team sessions. Where possible, coaches should be encouraged to include place kicking in simulated game scenarios during practice to represent key constraints from performance environments. Our study demonstrates how experiential knowledge can enrich the understanding of sport performance and inform the design of practice environments which simulate relevant constraints of competitive performance to enhance skill adaptation of athletes.
Performance characteristics of top-level youth judokas in light- and heavy-weight categories

Professionals involved in training programs for judokas should have access to evidence-based data on various characteristics of these athletes. In the current study, anthropometric (e.g., body height, body mass), physiological (e.g., power based on vertical jump height, maximal handgrip strength), and psychological (e.g., athletic coping skills) characteristics of judokas were examined. The judokas, aged 16-21, were classified into two groups: 30 light weight (males = 19, females = 11) and 27 heavy weight (males = 13, females = 14). Four MANCOVAs separated by sex were performed on the anthropometric, physiological, and psychological data. A discriminant analysis was also carried out. Results showed that heavy-weight males outscored their lighter peers on body height (d = 1.88), arm span (d = 1.88), and maximal handgrip strength. In the females, light-weight judokas outscored their heavier peers on jumping ability (d = 1.02) and peak power bench press (d = 1.20). Female heavy-weight judokas had greater body height (d = 1.46), a longer arm span (d = 1.35), and higher scores on maximal handgrip strength than light-weight judokas. The discriminant analysis revealed that 87.5% and 84.0% of the original grouped male and female judokas, respectively, were correctly classified. No differences in coping skills or self-regulation of learning between categories were observed. It is recommended that professionals involved in training programs may consider these differences in data when developing training programs for young judokas.
Inheritance of Apetalous Flowers in a Mutant of Oilseed Rape

Oilseed rape (Brassica napus L.) genotypes with reduced petal size are thought to have advantages in photosynthetic capacity and in disease resistance. This study was conducted to analyze the inheritance of a completely apetalous mutant that was induced by mutagenic treatment. The mutant ap-Tengbe was crossed with the German winter rapeseed cultivar Falcon. The F 1 , the F 2 , and both backcrosses including reciprocal generations were grown in field experiments at Got-tingen, Germany, in 1997-1998 and at Hangzhou, China, in 1998-1999. The apetalous character of ap-Tengbe is regulated by an interaction of cytoplasmic genes and two pairs of nuclear genes. Completely apetalous flowers are only expressed in genotypes with the ap cytoplasm and two homozygous recessive genes. In conclusion, the mutant ap-Tengbe is useful to produce completely apetalous genotypes, but cytoplasmic effects have to be considered.
A Holistic Approach for Semantic Interpretation of Relational Web tables

The Web contains vast amounts of semi-structured data in the form of HTML tables found on Web pages which may serve for various applications. One prominent application, which is often referred to Semantic Table Interpretation, is to exploit the semantics of a widely recognized knowledge bases (KB) by matching tabular data, including column headers and cell contents, to semantically rich descriptions of classes, entities and properties in Web KBs. In this paper, we focus on relational tables which are valuable sources of facts about real-world entities (persons, locations, organizations, etc.) and we propose a robust and efficient approach for bridging the gap between millions of Web tables and large-scale Knowledge graphs such as DBpedia. Our approach is holistic and fully unsupervised for semantic interpretation of Web tables based on the DBpedia Knowledge graph. Our approach covers three phases that heavily rely on word and entity pre-trained embeddings to uncover semantics of Web tables. Our experimental evaluation is conducted using the T2D gold standard corpus. Our results are very promising compared to several existing approaches of annotation in web tables.
Lyrics or Audio for Music Recommendation?

Music recommender systems (RS) aim to aid people with finding relevant enjoyable music without having to sort through the enormous amount of available content. Music RS often rely on collaborative filtering methods, which however limits predicting capabilities in cold-start situations or for users who deviate from main-stream music preferences. Therefore, this paper evaluates various content-based music recommendation methods that may be used in combination with collaborative filtering to overcome such issues. Specifically, the paper focuses on the ability of lyrics-based embedding methods such as tf-idf, word2vec or bert to estimate songs similarity compared to state-of-the-art audio and meta-data based embeddings. Results indicate that both audio and lyrics methods perform similarly, which may favor lyrics-based approaches due to the much simpler processing. We also show that although lyrics-based methods do not outperform meta-data based approaches, they provide much more diverse, yet reasonably relevant recommendations, which is suitable in exploration-oriented music RS.
3D Face Recognition using Photometric Stereo and Deep Learning

Illumination variance is one of the largest real-world problems when deploying face recognition systems. Over the last few years much work has gone into the development of novel 3D face recognition methods to overcome this issue. Photometric stereo is a well-established 3D reconstruction technique capable of recovering the normals and albedo of a surface. Although it provides a way to obtain 3D data, the amount of training data available captured using photometric stereo often does not provide sufficient modelling capacity for training state-of-the-art feature extractors, such as deep convolutional neural networks, from scratch. In this work we present a novel approach to utilising the lighting apparatus commonly used for photometric stereo to synthesise data that can act as a biometric. Combining this with deep learning techniques not only did we achieve near state-of-the-art results, but it gave insight into the possibility of using photometric stereo without the need of reconstruction. This could not only simplify the face recognition process but avoid unnecessary error that may arise from reconstruction. Additionally, we utilise the active lighting from photometric stereo to evaluate the effect of illumination on face recognition. We compare our method to the state-of-the-art 3D methods and discuss potential use cases for our system.
Acute effects of aerobic activity, static stretching, and explosive exercises on muscular performance and range of motion of young soccer players

The current study aims to investigate the acute effects of light aerobic activity, static stretching (SS), strengthening and explosive exercises on lower-body muscular performance and range of motion (ROM). Dose-response effect of SS on performance and ROM was also studied. Nineteen young male soccer players (age: 13.9 ± 0.46 years) participated in a cross-over randomized trial. Participants performed 5-minute aerobic activity, followed by seven bouts of SS of calf, quadriceps, adductor and hamstring muscles lasting 20 seconds each. Additionally, two sets of strengthening and explosive exercises were performed after SS in the experimental condition. Power and strength were assessed by counter-movement jump (CMJ) and maximal voluntary contraction of hip adductors, while 3 flexibility tests were used for assessing ROM of lower body. Repeated-measures ANOVA revealed an increase in CMJ performance after aerobic activity, followed by a decrease after SS in a dose-dependent manner that continued to be present 15 minutes post-SS. Strengthening and explosive exercises did not neutralize the acute negative effects of SS on CMJ performance. No significant acute effect of selected interventions on maximal and explosive strength of hip adductors was observed. Finally, sit-and-reach and hip abduction ROM increased after aerobic activity and continued to increase throughout the SS protocol, and was preserved 15 minutes post-SS. Our results confirm that SS can impair lower-body power in young soccer players, and that these negative effects last at least 15 minutes. Excessive use of SS, as performed in this study, should be avoided during warm-up of young soccer players.
SciPuRe: a new Representation of textual data for entity identification from scientific publications

Retrieving entities associated with experimental data in the textual content of scientific documents faces numbers of challenges. One of them is the assessment of the extracted entities for further process, especially the identification of false positives. We present in this paper SciPuRe (Scientific Publication Representation): a new representation of entities. The extraction process presented in this paper is driven by an Ontological and Terminological Resource (OTR). It is applied to the extraction of entities associated with food packaging permeabilities, that can be symbolic (e.g. the Packaging "low density polyethylene") or quantitative (e.g. the Temperature "25", "°C" or the H20_Permeability "4.34 * 10-3", "cm3 μm-2 d-1 kPa"). A representation of each entity, composed of a set of features, is built during the extraction process. These features can be gathered in three categories: Ontological, Lexical and Structural. The features of SciPuRe are used to compute Relevance scores that consider the different information available for each entity extracted. Such Relevance scores inform the usefulness of SciPuRe and can then be used to rank the extraction results and discard false positives.
Segmentation Based Mesh Denoising

Feature-preserving mesh denoising has received noticeable attention recently. Many methods often design great weighting for anisotropic surfaces and small weighting for isotropic surfaces, to preserve sharp features. However, they often disregard the fact that small weights still pose negative impacts to the denoising outcomes. Furthermore, it may increase the difficulty in parameter tuning, especially for users without any background knowledge. In this paper, we propose a novel clustering method for mesh denoising, which can avoid the disturbance of anisotropic information and be easily embedded into commonly-used mesh denoising frameworks. Extensive experiments have been conducted to validate our method, and demonstrate that it can enhance the denoising results of some existing methods remarkably both visually and quantitatively. It also largely relaxes the parameter tuning procedure for users, in terms of increasing stability for existing mesh denoising methods.
Classifying News Media Coverage for Corruption Risks Management with Deep Learning and Web Intelligence

A substantial number of international corporations have been affected by corruption. The research presented in this paper introduces the Integrity Risks Monitor, an analytics dashboard that applies Web Intelligence and Deep Learning to english and german-speaking documents for the task of (i) tracking and visualizing past corruption management gaps and their respective impacts, (ii) understanding present and past integrity issues, (iii) supporting companies in analyzing news media for identifying and mitigating integrity risks. Afterwards, we discuss the design, implementation, training and evaluation of classification components capable of identifying English documents covering the integrity topic of corruption. Domain experts created a gold standard dataset compiled from Anglo-American media coverage on corruption cases that has been used for training and evaluating the classifier. The experiments performed to evaluate the classifiers draw upon popular algorithms used for text classification such as Naïve Bayes, Support Vector Machines (SVM) and Deep Learning architectures (LSTM, BiLSTM, CNN) that draw upon different word embeddings and document representations. They also demonstrate that although classical machine learning approaches such as Naïve Bayes struggle with the diversity of the media coverage on corruption, state-of-the art Deep Learning models perform sufficiently well in the project's context.
Advanced Design and Manufacture of Mechanoactive Materials Inspired by Skin, Bones, and Skin-on-Bones

Life is mechanobiological. Natural living materials exhibit remarkable, emergent and smart properties under mechanical loading. Such materials are classified as mechanoactive, in contrast to electroactive polymers and materials that exhibit advanced properties when subjected to electrical stimulation. Cutting edge, multiscale imaging technologies have proven enabling for the elucidation of molecular to meso-scale structure and function of natural mechanoactive materials. Using Microscopy-Aided Design And ManufacturE, (MADAME) this perspective article describes mechanoactive properties of natural materials including skin-on-bones (periosteum) and bone itself. In so doing, it demonstrates the principle to emulate natural smart properties using recursive logic, the basis of many computer algorithms, and to design and manufacture mechanoactive materials and products using advanced manufacturing methods that also incorporate principles of recursive logic. In sum, the MADAME approach translates physically the computer science paradigm of recursion by implementing Jacquard textile methods, which themselves form a historical basis for computing machines, together with additive manufacturing methods including multidimensional printing, stereolithography, laser sintering, etc. These integrated methods provide a foundation and translational pathway for scaled-up manufacture of disruptive mechanoactive materials that will find use in fields as varied as medicine, safety, transport and sports, for internal (implants) and external (wearables) applications.
Modeling Salmonella Spread in Broiler Production: Identifying Determinants and Control Strategies

The presence of Salmonella spp. in broiler production is a food safety concern as the bacterium can be transmitted to humans via contaminated meat and derived products. Salmonella detection in litter at the pre-slaughter period has been linked to increased odds of contaminated broiler carcasses and meat derived products. To determine risk factors related to farm and broiler house characteristics and management practices, this study uses a unique longitudinal data set from a Brazilian integrated broiler enterprise, which contains official results of Salmonella spp. isolation from drag swabs collected at the end of the grow-out period. A Bayesian hierarchical spatio-temporal model found significant spatial and time influence on the odds of isolating Salmonella spp. from litter as well as significant effects from the size of a broiler house, total housing area per farm, type of broiler house, and number of litter recycles. Results indicate that recycling litter beyond 6 rearing cycles significantly increased the odds of isolating Salmonella before slaughter, and the bacterium was more likely to persist in conventional broiler houses, compared to broiler houses with controlled environment. Evidence of a potential principal-agent problem was also found in setting strategies to control the bacterium from litter, which suggests strong incentives to adopt the strategies aiming to reduce prevalence of the bacterium in the integrated enterprise. Our findings could be used to develop alternative measures to reduce the risk of persistence of the bacterium in the broiler production chain.
Non-invasive Drug Monitoring of β-Lactam Antibiotics Using Sweat Analysis—A Pilot Study

Background: Antimicrobial resistance is a major challenge in treating infectious diseases. Therapeutic drug monitoring (TDM) can optimize and personalize antibiotic treatment. Previously, antibiotic concentrations in tissues were extrapolated from skin blister studies, but sweat analyses for TDM have not been conducted. Objective: To investigate the potential of sweat analysis as a non-invasive, rapid, and potential bedside TDM method. Methods: We analyzed sweat and blood samples from 13 in-house patients treated with intravenous cefepime, imipenem, or flucloxacillin. For cefepime treatment, full pharmacokinetic sampling was performed (five subsequent sweat samples every 2 h) using ultra-high-performance liquid chromatography coupled with triple quadrupole mass spectrometry. The ClinicalTrials.gov registration number is NCT03678142. Results: In this study, we demonstrated for the first time that flucloxacillin, imipenem, and cefepime are detectable in sweat. Antibiotic concentration changes over time demonstrated comparable (age-adjusted) dynamics in the blood and sweat of patients treated with cefepime. Patients treated with standard flucloxacillin dosage showed the highest mean antibiotic concentration in sweat. Conclusions: Our results provide a proof-of-concept that sweat analysis could potentially serve as a non-invasive, rapid, and reliable method to measure antibiotic concentration and as a surrogate marker for tissue penetration. If combined with smart biosensors, sweat analysis may potentially serve as the first lab-independent, non-invasive antibiotic TDM method.
Construction and Application of Efficient Ac-Ds Transposon Tagging Vectors in Rice

Transposons are effective mutagens alternative to T-DNA for the generation of insertional mutants in many plant species including those whose transformation is inefficient. The current strategies of transposon tagging are usually slow and labor-intensive and yield low frequency of tagged lines. We have constructed a series of transposon tagging vectors based on three approaches:(i) AcTPase controlled by glucocorticoid binding domain/VP16 acidic activation domain/Gal4 DNA-binding domain (GVG) chemical-inducible expression system; (ii) deletion of AcTPase via Cre-lox site-specific recombination that was initially triggered by Ds excision; and (iii) suppression of early transposition events in transformed rice callus through a dual-functional hygromycin resistance gene in a novel Ds element (HPT-Ds). We tested these vectors in transgenic rice and characterized the transposition events. Our results showed that these vectors are useful resources for functional genomics of rice and other crop plants. The vectors are freely available for the community.
Discriminant Analysis on Preconciousness of Chinese Mitten Crab , Eriocheir sinensis

Combined gonad histology with morphology study of Chinese mitten crabs, twenty two morphological characters were compared between the preconcious crabs and normal ones. Three characters contributed mostly to discriminate preconcious crabs were selected by sex. Different discriminants were established by sex. The accuracy of discriminant analysis was 90.9% for female, and 96.9% for male.
Prediction Models in Veterinary and Human Epidemiology: Our Experience With Modeling Sars-CoV-2 Spread

The worldwide outbreak of Sars-CoV-2 resulted in modelers from diverse fields being called upon to help predict the spread of the disease, resulting in many new collaborations between different institutions. We here present our experience with bringing our skills as veterinary disease modelers to bear on the field of human epidemiology, building models as tools for decision makers, and bridging the gap between the medical and veterinary fields. We describe and compare the key steps taken in modeling the Sars-CoV-2 outbreak: criteria for model choices, model structure, contact structure between individuals, transmission parameters, data availability, model validation, and disease management. Finally, we address how to improve on the contingency infrastructure available for Sars-CoV-2.
Increased Right Posterior STS Recruitment Without Enhanced Directional-Tuning During Tactile Motion Processing in Early Deaf Individuals

Upon early sensory deprivation, the remaining modalities often exhibit cross-modal reorganization, such as primary auditory cortex (PAC) recruitment for visual motion processing in early deafness (ED). Previous studies of compensatory plasticity in ED individuals have given less attention to tactile motion processing. In the current study, we aimed to examine the effects of early auditory deprivation on tactile motion processing. We simulated four directions of tactile motion on each participant’s right index finger and characterized their tactile motion responses and directional-tuning profiles using population receptive field analysis. Similar tactile motion responses were found within primary (SI) and secondary (SII) somatosensory cortices between ED and hearing control groups, whereas ED individuals showed a reduced proportion of voxels with directionally tuned responses in SI contralateral to stimulation. There were also significant but minimal responses to tactile motion within PAC for both groups. While early deaf individuals show significantly larger recruitment of right posterior superior temporal sulcus (pSTS) region upon tactile motion stimulation, there was no evidence of enhanced directional tuning. Greater recruitment of right pSTS region is consistent with prior studies reporting reorganization of multimodal areas due to sensory deprivation. The absence of increased directional tuning within the right pSTS region may suggest a more distributed population of neurons dedicated to processing tactile spatial information as a consequence of early auditory deprivation.
Reduction of COVID-19 Anxiety Levels Through Relaxation Techniques: A Study Carried Out in Northern Spain on a Sample of Young University Students

Since March 14, 2020, Spain has been in a state of alarm due to the crisis created by the outbreak of COVID-19. This measure has led to strict levels of lockdown. This situation has led to an increase in anxiety levels among the younger population. For this reason, an intervention was carried out on university voluntary participants in order to help lower their anxiety levels. Specifically, a telematic workshop was implemented to teach emotional literacy and relaxation techniques combined with the practice of the techniques in an autonomous manner. Anxiety measurements were taken before and after the workshop using the Generalized Anxiety Disorder – 7 (GAD-7) scale. The results show that Jacobson’s progressive relaxation techniques, Schultz’s autogenic training, abdominal relaxations, and visualizations are effective in lowering the anxiety levels of university students as an alternative to pharmacotherapy.