Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel Self-expanding Shape-Memory Bioresorbable Peripheral Stent Displays Efficient Delivery, Accelerated Resorption, and Low Luminal Loss in a Porcine Model

Objective and Design: The search for improved stenting technologies to treat peripheral artery disease is trending toward biodegradable self-expanding shape-memory stents that, as of now, still suffer from the acute trade-off between deliverability and luminal stability: Higher deliverability leads to lower lumen stability, vessel recoil, and stent breakage. This study was aimed at the development and testing of a self-expanding bioresorbable poly(l,l-lactide-co-ε-caprolactone) stent that was designed to produce confident self-expansion after efficient crimping, as well as quick bioresorption, and sufficient radial force. Materials and Methods: Bench tests were employed to measure shape-memory properties, radial force, and hydrolytic degradation of the stent. The porcine model was employed to study deliverability, lumen stability, biocompatibility, and stent integrity. A total of 32 stents were implanted in the iliac arteries of 16 pigs with 15 to 180 day follow-up periods. The stented vessels were studied by angiography and histological evaluation. Results: Recovery of the diameter of the stent due to shape-memory effect was equal to 90.6% after 6Fr crimping and storage in refrigeration for 1 week. Radial force measured after storage was equal to 0.7 N/mm. Technical success of implantation in pigs (after the delivery implemented by pusher) was 94%. At 180 days, no implanted stents were found to be fragmented: All of the devices remained at the site of implantation with no stent migration and all stents retained their luminal support. Only moderate inflammation and neoepithelialization were detected by histological assessment at 60, 90, 120, and 180 days. Lumen loss at 180 days was less than 25% of the vessel diameter. Conclusions: The stent with the mechanical and chemical properties described in this study may present the optimal solution of the trade-off between deliverability and luminal stability that is necessary for designing the next generation stent for endovascular therapy of peripheral arterial disease.
An NHC‐Mediated Metal‐Free Approach towards an NHC‐Coordinated Endocyclic Disilene

Abstract A convenient metal‐free approach towards an N‐heterocyclic carbene (NHC)‐coordinated disilene 2 is described. Compound 2, featuring the disilene incorporated in cyclopolysilane framework, was obtained in good yield and characterized using NMR spectroscopy and X‐ray crystallography. Density functional theory (DFT) calculations of the reaction mechanism provide a rationale for the observed reactivity and give detailed information on the bonding situation of the base‐stabilized disilene. Compound 2 undergoes thermal or light‐ induced (λ=456 nm) NHC loss, and a dimerization process to give a corresponding dimer with a Si10 skeleton. In order to shed light on the dimerization mechanism, DFT calculations were performed. Moreover, the reactivity of 2 was examined with selected examples of transition metal carbonyl compounds.
An exploration of the political, social, economic and cultural factors affecting how different global regions initially reacted to the COVID-19 pandemic

Responses to the early (February–July 2020) COVID-19 pandemic varied widely, globally. Reasons for this are multiple but likely relate to the healthcare and financial resources then available, and the degree of trust in, and economic support provided by, national governments. Cultural factors also affected how different populations reacted to the various pandemic restrictions, like masking, social distancing and self-isolation or self-quarantine. The degree of compliance with these measures depended on how much individuals valued their needs and liberties over those of their society. Thus, several themes may be relevant when comparing pandemic responses across different regions. East and Southeast Asian populations tended to be more collectivist and self-sacrificing, responding quickly to early signs of the pandemic and readily complied with most restrictions to control its spread. Australasian, Eastern European, Scandinavian, some Middle Eastern, African and South American countries also responded promptly by imposing restrictions of varying severity, due to concerns for their wider society, including for some, the fragility of their healthcare systems. Western European and North American countries, with well-resourced healthcare systems, initially reacted more slowly, partly in an effort to maintain their economies but also to delay imposing pandemic restrictions that limited the personal freedoms of their citizens.
Evaluation of Review Summaries via Question-Answering

Summarisation of reviews aims at compressing opinions expressed in multiple review documents into a concise form while still covering the key opinions. Despite the advancement in summarisation models, evaluation metrics for opinionated text summaries lag behind and still rely on lexical-matching metrics such as ROUGE. In this paper, we propose to use the question-answering(QA) approach to evaluate summaries of opinions in reviews. We propose to identify opinion-bearing text spans in the reference summary to generate QA pairs so as to capture salient opinions. A QA model is then employed to probe the candidate summary to evaluate information overlap between candidate and reference summaries. We show that our metric RunQA, Review Summary Evaluation via Question Answering, correlates well with human judgments in terms of coverage and focus of information. Finally, we design an adversarial task and demonstrate that the proposed approach is more robust than metrics in the literature for ranking summaries.
Exploring the Vulnerability of Natural Language Processing Models via Universal Adversarial Texts

Universal adversarial texts (UATs) refer to short pieces of text units that can largely affect the predictions of NLP models. Recent studies on universal adversarial attacks assume the accessibility of datasets for the task, which is not realistic. We propose two types of Data-Free Adjusted Gradient (DFAG) attacks to show that it is possible to generate effective UATs with only one arbitrary example which could be manually crafted. Based on the proposed DFAG attacks, this paper explores the vulnerability of commonly used NLP models in terms of two factors: network architectures and pre-trained embeddings. Our empirical studies on three text classification datasets reveal that: 1) CNN based models are more extremely vulnerable to UATs while self-attention models show the most robustness, 2) the vulnerability of CNN and LSTM models and robustness of self-attention models could be attributed to whether they rely on training data artifacts for their predictions, and 3) the pre-trained embeddings could expose vulnerability to both universal adversarial attack and the UAT transfer attack.
BERT’s The Word : Sarcasm Target Detection using BERT

In 2019, the Australasian Language Technology Association (ALTA) organised a shared task to detect the target of sarcastic comments posted on social media. However, there were no winners as it proved to be a difficult task. In this work, we revisit the task posted by ALTA by using transformers, specifically BERT, given the current success of the transformer-based model in various NLP tasks. We conducted our experiments on two BERT models (TD-BERT and BERT-AEN). We evaluated our model on the data set provided by ALTA (Reddit) and two additional data sets: ‘book snippets’ and ‘Tweets’. Our results show that our proposed method achieves a 15.2 % improvement from the current state-of-the-art system on the Reddit data set and 4 % improvement on Tweets.
Overview of the 2021 ALTA Shared Task: Automatic Grading of Evidence, 10 years later

The 2021 ALTA shared task is the 12th instance of a series of shared tasks organised by ALTA since 2010. Motivated by the advances in machine learning in the last 10 years, this yearï¿½s task is a re-visit of the 2011 ALTA shared task. Set within the framework of Evidence Based Medicine (EBM), the goal is to predict the qual-ity of the clinical evidence present in a set of documents. This yearï¿½s participant results didnot improve over those of participants from 2011.
Principled Analysis of Energy Discourse across Domains with Thesaurus-based Automatic Topic Labeling

With the increasing impact of Natural Language Processing tools like topic models in social science research, the experimental rigor and comparability of models and datasets has come under scrutiny. Especially when contributing to research on topics with worldwide impacts like energy policy, objective analyses and reliable datasets are necessary. We contribute toward this goal in two ways: first, we release two diachronic corpora covering 23 years of energy discussions in the U.S. Energy Information Administration. Secondly, we propose a simple and theoretically sound method for automatic topic labelling drawing on political thesauri. We empirically evaluate the quality of our labels, and apply our labelling to topics induced by diachronic topic models on our energy corpora, and present a detailed analysis.
Evaluating Hierarchical Document Categorisation

Hierarchical document categorisation is a special case of multi-label document categorisation, where there is a taxonomic hierarchy among the labels. While various approaches have been proposed for hierarchical document categorisation, there is no standard benchmark dataset, resulting in different methods being evaluated independently and there being no empirical consensus on what methods perform best. In this work, we examine different combinations of neural text encoders and hierarchical methods in an end-to-end framework, and evaluate over three datasets. We find that the performance of hierarchical document categorisation is determined not only by how the hierarchical information is modelled, but also the structure of the label hierarchy and class distribution.
Interacting Constraints and Relative Age Effect in Elite Cross-Country Skiers and Freeskiers

Abstract Different characteristics of sports disciplines potentially lead to skewness in birth month distribution (relative age effect, RAE). These characteristics can be considered from a constraint-based approach with interacting environmental, task, and individual constraints as a theoretical framework with which to examine variations in RAE. The main aim of the present study was to examine the theoretical predictions of the constraint-based framework by investigating the birth month distribution in cross-country skiers and freeskiers at elite junior and senior levels. The sample was comprised of top ranked Norwegian U15–U19/20 cross-country skiers and junior-level freeskiers. Birth months of top ranked international senior-level skiers in cross-country and freeskiing were also collected. Results indicated an over-representation of skiers born in the first half versus the second half of the year at all junior ages in cross-country skiing. There was no significant difference in the distribution of birth months in freeskiing or in senior cross-country skiers or freeskiers. Based upon the interacting constraint framework, the skewness towards more early-born athletes in junior cross-country skiing could be due to strict age-grouped and results-oriented developmental programs beginning at an early age (environmental constraints) as well as high-demand for physical capabilities (task constraints) that favour more physically mature athletes (individual constraints). For freeskiing, the interacting environmental (less structured and more individualistic-oriented development), task (high technical/motor skill demands), and individual (no advantage of advanced physical maturation) constraints potentially operate in the opposite direction compared to cross-country skiing.
A Log-Linear Analysis of Efficiency in Wheelchair Basketball According To Player Classification

Abstract Within the framework of observational methodology, we conducted a log-linear analysis to study efficiency in relation to players’ functional ability in wheelchair basketball by analyzing associations between the position of the last pass before a shot, a shot position, and a shot result (favorable or unfavorable). The observation sample contained all offensive sequences ending in a shot by the US men’s wheelchair basketball team, who won the gold medal at the 2016 Paralympic Games in Rio de Janeiro. Data were annotated and coded in the Lince software program and their reliability confirmed by measuring interobserver agreement using Cohen’s kappa statistics. Log-linear modeling showed that the models generated to explain offensive sequences ending in a shot by players with greater functional ability were closest to models observed for professional basketball players and were the only models to show significant effects in terms of efficiency.
Are Teams Whose Players Are More Committed To the Team More Resilient? the Role of Intra-Group Conflict

Abstract The study aimed to analyze the relationship between commitment to the team and team resilience factors (characteristics of resilience and vulnerability under pressure), and to examine whether the task and social intra-group conflict act as mediators between commitment to the team and team resilience factors. One hundred seventy (170) male soccer players (16-38 years; M = 18.35; SD = 4.72) of the national teams of Argentina, Costa Rica, and Mexico participated in the study. The path analytic model was used to test mediating pathways. First, the results revealed that commitment to the team was positively related to characteristics of resilience and negatively to vulnerability under pressure. Second, bootstrap mediation analysis showed that athletes’ perceptions of the task and social intra-group conflict mediated the association between their perception of commitment to the team and team resilience factors. Findings provide initial evidence for a link between commitment to the team and team resilience in national teams and also suggest that intra-group conflict can improve the association between commitment to the team and team resilience. Therefore, the main conclusion of this study is that practioners should promote players’ commitment to the team and avoid intra-group conflicts within teams to have a resilient team that copes with problems more easily.
The Effect of Inspiratory Muscle Training on The Pulmonary Function in Mixed Martial Arts and Kickboxing Athletes

Abstract Inspiratory muscle training (IMT) has found its way into athletes’ routine as a promising way of improving pulmonary function in combination with standard training. The objective of the study was to examine the effects of resistive IMT on the pulmonary function variables in athletes of two combat sports, i.e., mixed martial arts (MMA) and kickboxing. Fourteen kickboxing and 12 MMA male athletes qualified for the study. They were randomly assigned into experimental and control groups. While both groups participated in their standard training, the experimental group additionally participated in IMT which consisted of 30 breaths twice a day for 6 weeks. The pulmonary functions were measured at baseline and after 6 weeks of IMT. The addition of IMT to standard training increased significantly the forced expiratory volume in the first second to vital capacity ratio (FEV1/VC), and the maximum voluntary ventilation (MVV) (p < 0.05) with changes of 5.7%, and 28.6%, respectively, in MMA athletes. The kickboxing group showed no significant changes. The interaction of the sport discipline and IMT intervention yielded a strong significant change in the MVV (F(1, 11) = 14.53, p < 0.01), and FEV1/VC (F(1, 11) = 20.67, p < 0.01) to the benefit of MMA athletes in comparison with kickboxing athletes. Combining resistive IMT for 6 weeks with standard training was effective to improve some pulmonary functions in MMA athletes, but did not lead to additional gains in kickboxing athletes.
Vibration analysis for predictive maintenance and improved reliability of rotating machines in ETRR-2 research reactor

Abstract In this work, both hardware and software modifications in a typical research reactor protection system (RPS) is proposed. The reactor cooling pumps are tripped based on vibrations safety signals of the pumps while the reactor SCRAM signal is initiated based on low flow rate and pressure drop across the reactor core which is a direct result of pumps trip. The main objective of this work is to develop reactor SCRAM signal based of core cooling pumps vibration signals. The early shutdown of the reactor based on pumps vibration signals is of significant importance not only in cooling the decay power of the reactor core after shutdown but also to prevent pumps failure. In the hardware model, the core cooling pumps vibration signals are feed to RPS to initiate reactor SCRAM signal. In the software model, a modular artificial neural network (ANN) is used in modeling the vibration monitoring of the research reactor (ETRR-2). The input and the output signals of the vibration transducer are used as a source data for training the neural network model. The type of the network used in this methodology is the supervised Multilayer Feed-Forward Neural Networks with the back-propagation (BP) algorithm. Vibration analysis programs are used in research reactors (RRs) to identify faults in machinery, plan machinery repairs, and keep machinery functioning for as long as possible without failure. The vibration severity limits are determined based on the International Organization for Standardization (ISO) 10816. The ANNs were designed using two different methods; one is by using hardware application contained two out of three voting and dynamic modules for trip signal by using ANNs. The current model classifies the vibration signals into five ranges low, good, satisfactory, unsatisfactory, and unacceptable vibration. The ANN is trained to detect the signal and vote to take the correct and safe action. The results demonstrate that the ANN can help in taking predictive actions for the safe core coolant pumps operation.
Interactive Three-Phase Structure for Table Tennis Performance Analysis: Application To Elite Men’s Singles Matches

Abstract The aim of the current study was twofold: (a) to construct an Interactive Three-Phase Structure for table tennis performance analysis and (b) to apply the proposed structure to the performance analysis of elite men’s singles matches. The current structure makes improvements over the former ones in the following aspects: more comprehensive performance variables consisting of bilateral actions covering the whole rally competing process, a better phase division method fitting to the real match situation and more focused analysis achieved by the designed critical phase. The analysis of 56 elite men’s singles matches (5507 rallies) was conducted using the proposed structure. The results demonstrated that performance variables of the rally competing process ceasing in Phase 2 (initial attack and counterattack phase) were decisive for the rally outcome of elite men’s singles matches. The proposed structure provides practitioners with a better model to enhance the effectiveness of table tennis performance analysis.
Agreement Between Kinovea Video Analysis and The Open Barbell System for Resistance Training Movement Outcomes

Abstract The purpose of this study was to examine the agreement between Kinovea video analysis software and the previously validated Open Barbell System (OBS) for assessing average concentric and eccentric velocity, eccentric duration, peak concentric velocity, height of peak concentric velocity, and concentric and eccentric range of motion. Sixteen resistance-trained males performed 11 repetitions at various intensities (between 60-100% of one-repetition maximum) on both the back squat and the bench press. For each repetition, all outcome measures were assessed with Kinovea and the OBS. Agreement between devices for each outcome measure was analyzed with paired t-tests, intraclass correlation coefficients with 95% confidence intervals, Bland-Altman plots, and folded empirical cumulative distribution plots (Mountain plots). All outcome variables were found to be statistically different (i.e. they did not agree) between the two devices (p < 0.001), except for average eccentric velocity (p = 0.315), as determined by the paired t-tests. Mountain plots had long tails for every outcome measure and Bland-Altman plots showed large limits of agreement for all outcome measures except concentric range of motion and the height of peak concentric velocity, demonstrating low agreement between devices. Based upon these findings and the previous validation of the OBS, these devices should not be used interchangeably.
Coordinating the Mesosystem: An Ecological Approach to Addressing Chronic Absenteeism

ABSTRACT To reduce the number of chronically absent students in schools annually, cities and municipalities across the United States have implemented programs, initiatives, and invested resources into educational reforms that would lead to improvement in school attendance. Drawing on ecological systems theory and interview data, we examined how organizations within Pittsburgh, Pennsylvania directly worked with students, collaborated with each other, and facilitated opportunities to reduce the impact of chronic absenteeism in the local school district. Interview data revealed how organizations leveraged resources to train key personnel, communicate the importance of daily school attendance, and work directly with students on improving school attendance. Our findings highlight how community approaches to absenteeism require various levels of support from organizations.
Performance and Power Estimation of STT-MRAM Main Memory with Reliable System-level Simulation

It is questionable whether DRAM will continue to scale and will meet the needs of next-generation systems. Therefore, significant effort is invested in research and development of novel memory technologies. One of the candidates for next-generation memory is Spin-Transfer Torque Magnetic Random Access Memory (STT-MRAM). STT-MRAM is an emerging non-volatile memory with a lot of potential that could be exploited for various requirements of different computing systems. Being a novel technology, STT-MRAM devices are already approaching DRAM in terms of capacity, frequency, and device size. Although STT-MRAM technology got significant attention of various major memory manufacturers, academic research of STT-MRAM main memory remains marginal. This is mainly due to the unavailability of publicly available detailed timing and current parameters of this novel technology, which are required to perform a reliable main memory simulation on performance and power estimation. This study demonstrates an approach to perform a cycle accurate simulation of STT-MRAM main memory, being the first to release detailed timing and current parameters of this technology from academia—essentially enabling researchers to conduct reliable system-level simulation of STT-MRAM using widely accepted existing simulation infrastructure. The results show a fairly narrow overall performance deviation in response to significant variations in key timing parameters, and the power consumption experiments identify the key power component that is mostly affected with STT-MRAM.