Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of range overlap on ecological niche divergence depends on spatial scale in monkeyflowers

Patterns of niche divergence and geographical range overlap of closely related species provide insights into the evolutionary dynamics of ecological niches. When ranges overlap, shared selective pressures may preserve niche similarity along coarse‐scale macrohabitat axes (e.g., bioclimates). Alternatively, competitive interactions may drive greater divergence along local‐scale microhabitat axes (e.g., micro‐topographical features). We tested these hypotheses in 16 species pairs of western North American monkeyflowers (Erythranthe and Diplacus, formerly Mimulus) with estimations of species’ niches, geographic ranges, and a robust phylogeny. We found that macrohabitat niche divergence decreased with increasing range overlap, consistent with convergent selection operating at a coarse scale. No significant relationship was detected for microhabitat niches. Additionally, niche divergence was greater for recently diverged pairs along all macrohabitat niche axes, but greater for distantly diverged pairs along one microhabitat axis related to vegetation cover. For species pairs with partially overlapping ranges, greater microhabitat divergence was detected in sympatry than in allopatry for at least one niche axis for three of four pairs, consistent with character displacement in sympatry. Thus, coarse‐ and local‐scale niche divergence show dissimilar patterns in relation to range overlap and divergence time, perhaps because the relative importance of convergent versus divergent selection depends on spatial scale.
SYNODE: Understanding and Automatically Preventing Injection Attacks on NODE.JS

The Node.js ecosystem has lead to the creation of many modern applications, such as serverside web applications and desktop applications. Unlike client-side JavaScript code, Node.js applications can interact freely with the operating system without the benefits of a security sandbox. As a result, command injection attacks can cause significant harm, which is compounded by the fact that independently developed Node.js modules interact in uncontrolled ways. This paper presents a large-scale study across 235,850 Node.js modules to explore injection vulnerabilities. We show that injection vulnerabilities are prevalent in practice, both due to eval, which was previously studied for browser code, and due to the powerful exec API introduced in Node.js. Our study suggests that thousands of modules may be vulnerable to command injection attacks and that fixing them takes a long time, even for popular projects. Motivated by these findings, we present Synode, an automatic mitigation technique that combines static analysis and runtime enforcement of security policies to use vulnerable modules in a safe way. The key idea is to statically compute a template of values passed to APIs that are prone to injections, and to synthesize a grammar-based runtime policy from these templates. Our mechanism is easy to deploy: it does not require any modification of the Node.js platform, it is fast (sub-millisecond runtime overhead), and it protects against attacks of vulnerable modules, while inducing very few false positives (less than 10%).
Readability and Precision in Pictorial Bar Charts

Bar charts embellished with unique artistic styles, or made to look like real objects, are common in information graphics. Embellishments are typically considered detrimental to readability and accuracy, since they add clutter and noise. Previous work has found that some of the shapes used, like rounded tops, triangles, etc., decreased accuracy when judging relative and absolute sizes, while T-shaped bars even showed a slight increase relative to the basic bar chart. In this paper, we report on a study that adds pictorial elements to bar charts of four different shapes tested previously, thus also including the elements of color and texture. We ﬁnd that pictorial bar charts reduce accuracy, but not beyond the effect already observed for their shape. They also do not signiﬁcantly increase response time. Embellished bar charts may not be as problematic as commonly assumed.
Building a Kannada POS Tagger Using Machine Learning and Neural Network Models

POS Tagging serves as a preliminary task for many NLP applications. Kannada is a relatively poor Indian language with very limited number of quality NLP tools available for use. An accurate and reliable POS Tagger is essential for many NLP tasks like shallow parsing, dependency parsing, sentiment analysis, named entity recognition. We present a statistical POS tagger for Kannada using different machine learning and neural network models. Our Kannada POS tagger outperforms the state-of-the-art Kannada POS tagger by 6%. Our contribution in this paper is three folds - building a generic POS Tagger, comparing the performances of different modeling techniques, exploring the use of character and word embeddings together for Kannada POS Tagging.
Tuberculosis Detection using Optical Flow and the Activity Description Vector

Early detection of tuberculosis can save many lives as it remains one of the leading causes of death, half a century after its discovery. The analysis of chest CT scanned images can be a quick and economic mechanism for detecting not only the type of tuberculosis, but also differentiating whether or not the disease is multi-drug resistant. These are two of the objectives of the ImageClef Tuberculosis task of 2018, and are the ones studied by the group of the University of Alicante in this edition. We have carried out two work approaches, one based exclusively on the use of Deep Learning techniques on a sequence of 2D images extracted from a 3D tomography and on a second approach using Optical Flow to convert the 3D tomography into a motion representation in order to calculate the ADV (a previous descriptor provided by the group). This descriptor is able to synthesize the information of a sequence into one image. This article presents the experiments carried out and the results obtained within the task.
Neural Network-Based Muscle Torque Estimation Using Mechanomyography During Electrically-Evoked Knee Extension and Standing in Spinal Cord Injury

This study sought to design and deploy a torque monitoring system using an artificial neural network (ANN) with mechanomyography (MMG) for situations where muscle torque cannot be independently quantified. The MMG signals from the quadriceps were used to derive knee torque during prolonged functional electrical stimulation (FES)-assisted isometric knee extensions and during standing in spinal cord injured (SCI) individuals. Three individuals with motor-complete SCI performed FES-evoked isometric quadriceps contractions on a Biodex dynamometer at 30° knee angle and at a fixed stimulation current, until the torque had declined to a minimum required for ANN model development. Two ANN models were developed based on different inputs; Root mean square (RMS) MMG and RMS-Zero crossing (ZC) which were derived from MMG. The performance of the ANN was evaluated by comparing model predicted torque against the actual torque derived from the dynamometer. MMG data from 5 other individuals with SCI who performed FES-evoked standing to fatigue-failure were used to validate the RMS and RMS-ZC ANN models. RMS and RMS-ZC of the MMG obtained from the FES standing experiments were then provided as inputs to the developed ANN models to calculate the predicted torque during the FES-evoked standing. The average correlation between the knee extension-predicted torque and the actual torque outputs were 0.87 ± 0.11 for RMS and 0.84 ± 0.13 for RMS-ZC. The average accuracy was 79 ± 14% for RMS and 86 ± 11% for RMS-ZC. The two models revealed significant trends in torque decrease, both suggesting a critical point around 50% torque drop where there were significant changes observed in RMS and RMS-ZC patterns. Based on these findings, both RMS and RMS-ZC ANN models performed similarly well in predicting FES-evoked knee extension torques in this population. However, interference was observed in the RMS-ZC values at a time around knee buckling. The developed ANN models could be used to estimate muscle torque in real-time, thereby providing safer automated FES control of standing in persons with motor-complete SCI.
Microproteomic Profiling of High‐Grade Squamous Intraepithelial Lesion of the Cervix: Insight into Biological Mechanisms of Dysplasia and New Potential Diagnostic Markers

High‐grade squamous intraepithelial lesion (HSIL) is a known precursor for squamous cell carcinoma of uterine cervix. Although it is known that SILs are associated to infection by human papillomavirus, downstream biological mechanisms are still poorly described. In this study, we compared the microproteomic profile of HSIL to normal tissues: ectocervix (ectoC) and endocervix (endoC).
Combination therapies for hypertension – why we need to look beyond RAS blockers

ABSTRACT Introduction: Hypertension is the leading cause of mortality and disability worldwide. Despite the proven benefits of blood pressure (BP) reduction, lack of BP pressure control continues to be the most important clinical problem in hypertension management. Areas covered: Factors involved in the lack of BP control and strategies to improve such control have been reviewed, with special focus on the usefulness of combination therapies, those types of combination which include a renin-angiotensin system (RAS) blocker, with diuretics, calcium channel blockers, or both. Expert commentary: Combination therapy is required for BP control in most hypertensive patients. RAS blockers should be included in such combinations, except contraindicated. Diuretics, and especially calcium channel blockers are the drugs of choice for double or triple combinations. Diuretics stimulate RAS and enhance the effect of RAS blockers, while minimizing the undesirable metabolic effects of diuretics. RAS blockers and calcium channel blockers have synergistic protective effects on the vascular wall and have demonstrated to be superior to other types of combinations, thus becoming the preferred initial treatment for most hypertensive patients. The use of single-pill combinations is associated with better treatment adherence, thus facilitating the achievement of adequate BP control.
Barbell Hip-Thrust Exercise: Test-Retest Reliability and Correlation With Isokinetic Performance.

Dello Iacono, A, Padulo, J, Bešlija, T, and Halperin, I. Barbell hip-thrust exercise: Test-retest reliability and correlation with isokinetic performance. J Strength Cond Res XX(X): 000-000, 2018-The barbell hip-thrust (BHT) exercise is growing in popularity as evident by the large increase in research outputs investigating its utility as a training intervention and a testing tool. The aim of this study was to examine the test-retest reliability of the BHT and its correlation with isokinetic performance. Test-retest reliability was established by correlating the peak force and power outcomes measured with the BHT force-velocity profile test of 20 handball athletes on 2 separate days. The peak force and power measured with the BHT force-velocity profile test of 49 handball athletes were correlated with peak concentric force of the knee flexors and hip extensors measured with an isokinetic device at 2 different velocities (60-180°·s). The correlation between the isokinetic testing scores and the BHT force-velocity profile tests were moderate to large (Pearson r ranges: 0.45-0.86, all p values <0.001). Test-retest reliability of the BHT force-velocity profile was very high as shown with intraclass correlations of 0.94 and 0.99 for peak force and 0.97 and 0.99 for peak power measures. The BHT force-velocity profile can serve as a tentative substitute in cases that athletes do not have access to an isokinetic device, given the moderate to large correlations between them. Moreover, the BHT force-velocity profile was shown to be very reliable, thus providing coaches and scientists a range of day-to-day performance variability in this exercise.
Calcium in Brugada Syndrome: Questions for Future Research

The Brugada syndrome (BrS) is characterized by coved-type ST-segment elevation in the right precordial leads on the electrocardiogram (ECG) and increased risk of sudden cardiac death (SCD). While it is an inheritable disease, determining the true prevalence is a challenge, since patients may report no known family history of the syndrome, present with a normal spontaneous ECG pattern at the time of examination, and test negative for all known BrS-causative genes. In fact, SCD is often the first indication that a person is affected by the syndrome. Men are more likely to be symptomatic than women. Abnormal, low-voltage, fractionated electrograms have been found in the epicardium of the right ventricular outflow tract (RVOT). Ablation of this area abolishes the abnormal electrograms and helps to prevent arrhythmic recurrences. BrS patients are more likely to experience ventricular tachycardia/fibrillation (VT/VF) during fever or during an increase in vagal tone. Isoproterenol helps to reverse the ECG BrS phenotype. In this review, we discuss roles of calcium in various conditions that are relevant to BrS, such as changes in temperature, heart rate, and vagal tone, and the effects of gender and isoproterenol on calcium handling. Studies are warranted to further investigate these mechanisms in models of BrS.
Time-Ray Maps: Visualization of Spatial and Temporal Evolution of News Stories

Time-Ray maps (see Figure 1) are designed to represent the temporal and spatial evolution of the reporting of a single news story. The visualization presents a compact representation that tells the story of the story in one glance. We show how our visualization can provide an imprint for different types of stories, enabling both comparison to other stories and means for analysis of the inﬂuence and evolution of a story. We demonstrate our technique on data coming from an online news aggregator platform. While speciﬁcally designed for news events, the method is also applicable for various types of time-series data that include intervening evolving events.
Who Tests the Testers? ∗ Avoiding the Perils of Automated Testing

Instructors routinely use automated assessment methods to evaluate the semantic qualities of student implementations and, some-times, test suites. In this work, we distill a variety of automated assessment methods in the literature down to a pair of assessment models. We identify pathological assessment outcomes in each model that point to underlying methodological flaws. These theoretical flaws broadly threaten the validity of the techniques, and we actually observe them in multiple assignments of an introductory programming course. We propose adjustments that remedy these flaws and then demonstrate, on these same assignments, that our interventions improve the accuracy of assessment. We believe that with these adjustments, instructors can greatly improve the accuracy of automated assessment
Nutrient composition and dietary diversity of on-site lunch meals, and anthropometry of beneficiary children in private and public primary schools in Ghana

Background: On-site lunch provided through the Ghana School Feeding Programme is expected to be nutritionally adequate thereby contributing to reducing hunger and malnutrition. Aim: The aim of this study was to assess the dietary diversity and nutrient composition of on-site school lunch and estimate the extent to which it met the Food and Agriculture Organization Reference Nutrient Intakes for children aged 3–12 years. Methods: In this cross-sectional food consumption survey, on-site lunch menus were reviewed, dietary diversity assessed and meal preparation/serving observed during a typical school week. Three randomly selected portion sizes were weighed and the average weight (grams) entered into the RIING nutrient software to estimate the nutrient composition. Anthropometry of participants enrolled in seven public (n = 113) and six private (n = 216) primary schools in Hohoe municipality, Ghana was analysed using World Health Organization Anthroplus software. Results: The menu consisted largely of energy-dense staples, some vegetables and fish. Eggs, dairy and fruits were never served. Meals served in the public and private schools were statistically similar. Fat (23.8 vs. 27.7 g), iron (3.0 vs. 2.8 mg), vitamins A (417.3 vs. 280.8 µg retinol equivalent) and C (25.1 vs. 16.5 mg) requirements were fully met. Energy (420.6 vs. 462.2 kcal), protein (6.8 vs. 6.8 g), thiamin (0.18 vs. 0.17 mg) and zinc (1.3 vs. 1.2 mg) were 50–75% met. Calcium (62.6 vs. 61.4 mg), riboflavin (0.09 vs. 0.07 mg) and niacin (1.6 vs. 1.3 mg) were 26–37% met. Concerning nutritional status, prevalence of stunting (8.9% vs. 7.9%), underweight (3.6% vs. 5.7%), thinness (1.8% vs. 3.7%) and overweight/obesity (3.5% vs. 4.2%) were also statistically similar. Conclusion: Enhancing dietary diversity is crucial to achieving nutrient-dense school meals.
Comparative genetic and genomic analysis of the novel fusellovirus Sulfolobus spindle-shaped virus 10

Abstract Viruses that infect thermophilic Archaea are unique in both their structure and genetic makeup. The lemon-shaped fuselloviruses—which infect members of the order Sulfolobales, growing optimally at 80 °C and pH 3—are some of the most ubiquitous and best studied viruses of the thermoacidophilic Archaea. Nonetheless, much remains to be learned about these viruses. In order to investigate fusellovirus evolution, we have isolated and characterized a novel fusellovirus, Sulfolobus spindle-shaped virus 10 (formerly SSV-L1). Comparative genomic analyses highlight significant similarity with both SSV8 and SSV9, as well as conservation of promoter elements within the Fuselloviridae. SSV10 encodes five ORFs with no homology within or outside of the Fuselloviridae, as well as a putatively functional Cas4-like ORF, which may play a role in evading CRISPR-mediated host defenses. Moreover, we demonstrate the ability of SSV10 to withstand mutation in a fashion consistent with mutagenesis in SSV1.
Identifying Protein-Protein Interaction Using Tree LSTM and Structured Attention

Identifying interactions between proteins is important to understand underlying biological processes. Extracting a protein-protein interaction (PPI) from the raw text is often very difficult. Previous supervised learning methods have used handcrafted features on human-annotated data sets. In this paper, we propose a novel tree recurrent neural network with structured attention architecture for doing PPI. Our architecture achieves state of the art results (precision, recall, and F1-score) on the AIMed and BioInfer benchmark data sets. Moreover, our models achieve a significant improvement over previous best models without any explicit feature extraction. Our experimental results show that traditional recurrent networks have inferior performance compared to tree recurrent networks for the supervised PPI problem.
Detection of identical T cell clones in peritumoral pleural effusion and pneumonitis lesions in a cancer patient during immune-checkpoint blockade

Although immune-related adverse events (irAEs) of treatment with immune-checkpoint inhibitors may be due to cellular immunity mediated by T lymphocytes, their pathogenesis has remained unknown. Here we collected bronchoalveolar lavage fluid (BALF) from a cancer patient with nivolumab-induced pneumonitis and isolated mononuclear cells for next-generation sequencing of the complementarity-determining region of the T cell receptor (TCR) β chain. Mononuclear cells in peritumoral pleural effusion isolated from the patient were similarly analyzed, and the results obtained for the two specimens were compared. A substantial number of TCRβ clones in BALF were also identified among lymphocytes in the peritumoral pleural effusion. Such a correlation was not apparent between TCRβ clones in BALF and those in peripheral blood. Moreover, many tumor-associated clones with a read frequency of ≥0.10% were also present in BALF. Our data suggest that irAEs might be induced by drug-activated lymphocytes originating from tumor tissue. Deep sequencing will thus be indispensable for investigations of the immune-based pathogenesis of, and the development of optimal treatments for, irAEs.
A identificação da necessidade de tratamento ortodôntico utilizando os índices de necessidade de tratamento ortodôntico e de estética dental

Os objetivos do presente estudo foram avaliar a aplicabilidade do Indice de Estetica Dental (DAI) e do componente de saude dentaria do Indice de Necessidade de Tratamento Ortodontico (DHC), para diagnostico da ma oclusao e necessidade de tratamento. Comparou-se a capacidade de identificacao de ma oclusao atraves dos dois indices em modelos de estudo de uma clinica de Ortodontia. Inicialmente foi realizada uma revisao narrativa sobre os diversos metodos de obtencao do padrao-ouro para necessidade de tratamento ortodontico, em estudos de validacao de indices de ma oclusao. Posteriormente avaliou-se a validade e a reprodutibilidade do Indice de Estetica Dental (DAI) e do componente de saude dentaria do Indice de Necessidade de Tratamento Ortodontico (DHC), com relacao a decisao de tratamento, e a correlacao entre eles. Alem disso, foi contabilizado o tempo gasto para cada exame, nos dois indices. A amostra calculada consistiu de 131 modelos de estudo dos arcos dentarios, de pacientes com idade de 12 a 15 anos. Os modelos foram selecionados aleatoriamente de um universo de 198 modelos do arquivo da disciplina de ortodontia FO/UFMG. A amostra foi examinada por uma pesquisadora (especialista em ortodontia) para determinacao dos indices DAI e do DHC. Apos trinta dias, foi realizada nova avaliacao para determinacao da capacidade de identificacao da ma oclusao, feita pelo teste qui-quadrado de McNemar e a reprodutibilidade que foi calculada atraves do coeficiente de correlacao intraclasse. Os mesmos modelos de estudo foram examinados por tres experts da area de Ortodontia para determinacao do padrao-ouro das medidas realizadas, estabelecendo o diagnostico por consenso. O exame da especialista foi comparado com o padrao-ouro para que a avaliacao da validade dos indices por meio das medidas de sensibilidade, especificidade, valor preditivo positivo, valor preditivo negativo e acuracia. Os dois indices sao reprodutiveis para avaliar a necessidade de tratamento ortodontico, possuem correlacao moderada e validade ruim. O tempo gasto com o DHC (59,52 segundos) foi inferior ao tempo gasto com o DAI (118,97 segundos). Nao houve diferenca significativa na medicao da necessidade de tratamento entre o DAI e o DHC do IOTN (p>0,05). A acuracia do DHC foi igual a 0,60 (IC95% 0,50-69) e do DAI 0,53 (IC95% 0,43-0,63). Os resultados deste estudo demonstram que os dois indices sao reprodutiveis para avaliar a necessidade de tratamento ortodontico e possuem correlacao moderada. No entanto apresentaram fraca acuracia, em relacao a decisao de tratamento estabelecida pelos especialistas (padrao-ouro). Nao ha consenso na literatura consultada sobre o melhor metodo para se definir o padrao-ouro de necessidade de tratamento ortodontico.