bluuebunny/crossref_metadata_2025 huggingface dataset:
Clinical and demographic predictors of antiretroviral efficacy in HIV–HBV co-infected patients
Authors: Rana Urvi , Driedger Matt , Sereda Paul , Pan Shenyi , Ding Erin , Wong Alex , Walmsley Sharon , Klein Marina , Kelly Deborah , Loutfy Mona , Thomas Rejean , Sanche Stephen , Kroch Abigail , Machouf Nima , Roy-Gagnon Marie-Héléne , Hogg Robert , Cooper Curtis L
Published: May 2021

Background: The clinical and demographic characteristics that predict antiretroviral efficacy among patients co-infected with HIV and hepatitis B virus (HBV) remain poorly defined. We evaluated HIV virological suppression and rebound in a cohort of HIV–HBV co-infected patients initiated on antiretroviral therapy. Methods: A retrospective cohort analysis was performed with Canadian Observation Cohort Collaboration data. Cox proportional hazards models were used to determine the factors associated with time to virological suppression and time to virological rebound. Results: HBV status was available for 2,419 participants. A total of 8% were HBV co-infected, of whom 95% achieved virological suppression. After virological suppression, 29% of HIV–HBV co-infected participants experienced HIV virological rebound. HBV co-infection itself did not predict virological suppression or rebound risk. The rate of virological suppression was lower among patients with a history of injection drug use or baseline CD4 cell counts of <199 cells per cubic millimetre. Low baseline HIV RNA and men-who-have-sex-with-men status were significantly associated with a higher rate of virological suppression. Injection drug use and non-White race predicted viral rebound. Conclusions: HBV co-infected HIV patients achieve similar antiretroviral outcomes as those living with HIV mono-infection. Equitable treatment outcomes may be approached by targeting resources to key subpopulations living with HIV–HBV co-infection.
A Phase II Dose Escalation Study of Intraarterial (Hepatic) Adult Human Bone Marrow Derived, Cultured, Pooled, Allogeneic Mesenchymal Stromal Cells (Stempeucel®) in Patients with Alcoholic Liver Cirrhosis
Authors: Gupta Pawan Kumar , Gupta Pawan Kumar , Chullikana Anoop , NS Raviraja , K Uday kumar , P Shivashankar , Viswanathan Pachaiyappan , Chandrashekar Mithun , Thej Charan , KV Prasanth , Abraham Jijy , Majumdar Anish Sen
Published: May 2021

Background: Alcoholic liver cirrhosis is an end-stage alcoholic liver disease with a poor prognosis. The definitive treatment of alcoholic liver cirrhosis is orthotopic liver transplantation, which is expensive, requires long-term immunosuppression and is limited by the supply of organs. Being an unmet medical need, cell therapy is under investigation for alcoholic liver cirrhosis.
Aims: This study was designed primarily for assessing the safety and feasibility of administering stempeucel® through the hepatic artery in alcoholic liver cirrhosis and secondarily to assess possible efficacy and dose-response.
Methods: Sixty patients with alcoholic cirrhosis (18-65 years/Child-Pugh class B or C/Model for End-Stage Liver Disease score of minimum 10) were planned to be included in 6 groups: 2.5 million cells/kg Body Weight (2.5M Cell) and respective control (2.5M Control); 5 million cells/kg Body Weight (5M Cell) and respective control (5M Control); 7.5 million cells/kg Body Weight (5M Cell) and respective control (7.5M Control) with 10 patients in each group. Cell groups received stempeucel® administered via hepatic artery by catheterization through the femoral artery (Seldinger technique) and Standard Protocol of Care. The control group received Standard Protocol of Care. Patients were followed up at 1 week, 1 month, 3 months and 6 months. Efficacy evaluations included liver function test, Model for End-Stage Liver Disease score, Child-Pugh score, Short Form-36 questionnaire, liver stiffness using Fibroscan (Transient Elastography), and liver volume using Computerized Tomography scan.
Results: Stempeucel® injection was well tolerated. Common treatment-emergent adverse events were gastrointestinal disorders, general disorders and administration site conditions and infections and infestations. Most of the treatment-emergent adverse events were unrelated / remotely related to stempeucel®. Thirty serious adverse events occurred in 10 patients (3 in 2.5M Cell, 5 in 5M Cell and one each in control groups). Three patients died due to SAEs: Two in 2.5M and one in 5M Cell group, none were related to stempeucel®. Statistically significant improvement was seen in 2.5M group compared to the control group in Short Form-36 score: bodily pain, mental component summary, vitality and social functioning.
Conclusion: Stempeucel® was safe, well-tolerated and subjective improvement in Short Form-36 (bodily pain, mental component summary, vitality and social functioning and mental health) score was seen in the 2.5M cell group.
L’impact du droit de l’Union européenne sur la fiscalité environnementale française
Authors: Viessant Céline
Published: May 2021

Il convient d’apprécier l’impact du droit de l’Union européenne (UE) sur la fiscalité environnementale française, d’analyser les contraintes pesant sur le législateur français lorsqu’il envisage de protéger l’environnement en utilisant l’instrument fiscal tout en constatant que les avancées en la matière ne ressortissent pas forcément à des normes contraignantes mais à une influence certaine des travaux européens sur le législateur français. Or, le degré de contrainte est variable : le législateur est libre d’utiliser l’instrument fiscal pour protéger l’environnement et les contraintes n’apparaissent que lorsqu’il fait ce choix.
L’encadrement de la fiscalité environnementale par le droit interne : un barrage pacifique
Authors: Beaufils Cyrille
Published: May 2021

Si diverses normes constitutionnelles sont susceptibles d’inspirer la création d’impositions environnementales, elles sont davantage sources de contraintes que de protection des dispositions législatives les mettant en oeuvre. Les principes classiques du droit budgétaire et fiscal ne limitent guère la marge de manoeuvre en la matière, à l’exception du principe d’égalité qui s’avère, comme pour tout le droit fiscal, la norme de référence la plus exigeante.
Le « casse-tête » de la déclaration sociale du travailleur indépendant
Authors: Hernu Paul
Published: May 2021

La complexité de la déclaration sociale des indépendants, qu’ils doivent adresser chaque année à l’URSSAF, résulte de la liaison établie entre les règles fiscales et les données à reporter dans la déclaration sociale et du mode de détermination de l’assiette des cotisations et des contributions sociales.
Plant Philosophy and Interpretation: Making Sense of Contemporary Plant Intelligence Debates
Authors: Hendlin Yogi H.
Published: May 2021

Plant biologists widely accept plants demonstrate capacities for intelligence. However, they disagree over the interpretive, ethical and nomenclatural questions arising from these findings: how to frame the issue and how to signify the implications. Through the trope of ‘plant neurobiology’ describing plant root systems as analogous to animal brains and nervous systems, plant intelligence is mobilised to raise the status of plants. In doing so, however, plant neurobiology accepts an anthropocentric moral extensionist framework requiring plants to anthropomorphically meet animal standards to be deserving of moral respect. I argue this strategy is misguided because moral extensionism is an erroneous ontological foundation for ethics.
The Role of Mobile-assisted Language Learning (MALL) in Enhancing the Writing Skills of Intermediate IEP Students: Expectations vs Reality
Authors: Al-Shehab Mariam Al-Shehab
Published: May 2021

Despite extensive research into the effectiveness of mobile-assisted language learning (MALL) in ESL/EFL language learning, there is insufficient evidence to conclude that supplementing conventional teaching methods of the writing process approach with MALL significantly improves the English writing performance of native Arabic speakers. This study investigates the role of mobile-assisted language learning in enhancing the writing skills of forty female intermediate-level Intensive English Program (IEP) students at an intermediate level at Kuwait University. Participants were tested using a variety of mobile applications and websites (i.e. the Microsoft Word application, an English dictionary application, and internet search engines). The researcher utilized questionnaires, observation notes, and other qualitative methods from student assignments for data collection. Results of the data analysis indicate that smartphones are indeed an effective teaching tool, with multiple positive effects on student agency. However, due to its nature and complexity, a cautious approach was used to interpret the findings of this study. The ultimate goal of the research was to compare the traditional approach to the teaching of process writing to a mobile-assisted approach. Study findings are discussed in details and options for future research are explored. Overall, results suggest that learner autonomy is improved by engaging in the writing process both inside and outside of the classroom. The results also suggest implications for increasing motivation and peer collaboration via the use of mobile technology.
Variables asociadas de malestar psicológico y funcionamiento de personas con dolor crónico
Authors: Lami Hernandez Maria José , Zambolin M. Vitoria , Carabajar Maria Jose
Published: May 2021

Up to 40% of the world's adult population suffer from chronic pain. This condition is associated with significant distress, less functioning and quality of life. The aim of the present study is to evaluate the core variables in two psychological models: Fear-Avoidance model and Psychological Flexibility model. 67 people with chronic pain were evaluated, measures of anxiety and depression (HADS), daily functioning (IDF), catastrophization of pain (PCS), hypervigilance and pain awareness (PVAQ), acceptance of the chronic pain (CPAQ), psychological inflexibility (PIPS) and mindfulness (FFMI). The results show moderate levels of anxiety and depression. And the correlations (Pearson's r) between the mentioned variables are analyzed. The functioning in this group of patients is associated with acceptance of pain and mindfulness. Likewise, significant association were found between anxiety and depression and the core variables involved in the abovementioned models. The results are discussed in relation to the psychological practice.
Análisis intercultural del trastorno por uso de alcohol: criterios diagnósticos en universitarios
Authors: Conde Karina , Gimenez Paula Victoria , Cremonte Mariana , Díaz-Castela María del Marb , Ortega-Martinez Ana
Published: May 2021

This study aimed to examine the clinical manifestations of Alcohol Use Disorder (AUD) in university students from countries with different drinking practices, and the potential of a drinking measure as an AUD marker. University students from Argentina (N = 2157), Spain (N = 320), and Brazil (N = 149) participated in the study. The TUA criteria and the cut off-points were compatible with the DSM 5, and a measure of binge drinking was evaluated. Descriptive and latent class analyses were performed. In general, the severe AUD is characterized by the endorsement of all criteria; the moderate-mild, by tolerance, loss of control (quit/cut), interpersonal problems, and role impairment. In countries with a wet drinking pattern (Argentina and Spain), the criteria of hazardous use and psychological or physical problems due to use were characteristic of different severity levels. The binge drinking measure showed potential as a marker of TUA.
Mediating role of poverty in the association between environmental factors and cognitive performance in preschoolers
Authors: Fracchia Carolina , Segretin María Soledad , Hermida María Julia , Prats Lucía , Lipina Sebastián J.
Published: May 2021

TThe association between environmental factors and cognitive performance during childhood could be mediated by poverty (i.e., households with Unsatisfied or Satisfied Basic Needs). This study explored such mediating roles in preschoolers from different socioeconomic backgrounds. Tasks to assess executive attention, working memory, inhibitory control, planning, and fluid reasoning were administered to 250 children aged 4 and 5 years. The results suggested that poverty mediated the effects of family composition, child health, health risk factors, children and adults at home, maternal age, and literacy activities on the performance of executive attention, fluid reasoning, and inhibitory control. These results contribute to our understanding of the relationship between environmental factors and cognitive development through the identification of the mediating role of poverty.
Contextos sociais na formação de treinadoras de ginástica rítmica: a aprendizagem ao longo da vida
Authors: Breggue da Silva Sampaio Gabriela , Milistetd Michel , De la Rocha Freitas Cintia , Milan Fabrício João , Vaz de Campos Pereira Marcos Paulo , Oliveira Farias Gelcemar
Published: May 2021

The objective was to analyze the influence of the social contexts of Rhythmic Gymnastics trainers, considering the learning acquired throughout life. Five trainers participated in the study. Data were collected from a semi-structured interview. The influence of the family is significant for the insertion and maintenance in the sport, besides the prominence in the school, sport and professional environment as informal contexts of relevance for the professional choice. It is concluded that the environment and learning contexts become opportunities to acquire knowledge, values ​​and beliefs that influence the personal and professional trajectory of the trainers.
Validez sustantiva en el marco de la validez de contenido: Aplicación en la escala de Carga de Trabajo
Authors: Merino Soto Cesar , Calderón-De la Cruz Gustavo , Gil-Monte Pedro , Arturo Juárez-García
Published: May 2021

The aim of the study was to use the substantive validity strategy to evaluate the content of the UNIPSICO’s workload scale. 30 workers from Lima (Perú) with undergraduate or graduate studies and with one year of work experience participated. Participants judged the correspondence of the workload items with their construct, and it was also contrasted with other constructs (role conflict, coping and labor self-efficacy); additionally, the clarity of the items was evaluated. High levels of item’s clarity was found; and substantive validity of all items was satisfactory to evaluate the divergence with other constructs. We discuss the importance of including non-expert participants in content validity methods, conceptual differentiation of items, and in constructs associated with psychosocial factors.
Aplicaciones móviles para ansiedad: una revisión en Argentina
Authors: Celleri Milagros , Garay Cristian Javier
Published: May 2021

The use of smartphones for the prevention and treatment of health problems is based on its increasing use and the development of apps. Given the high prevalence of anxiety disorders, the aim of this paper is to review the available apps in Argentina for this clinical problem. It was made a search of apps with the terms “anxiety” and “stress” in its description. It was included apps developed by mental health professionals, based on a psychological model and available in Spanish. It has found five apps, none of them made in Argentina. Two apps were presented merely chats with psychologists. The true three mobile applications are described and their characteristics are discussed. According to other studies, the apps aren’t based on efficacy studies. It emphasizes the need of Argentinean apps for the people affected by anxiety disorders.
Trastorno Narcisista de la Personalidad y Esquemas Maladaptativos Tempranos en una población femenina de bajos recursos socioeconómicos
Authors: Sarti Narella Paula , Vidal Bárbara Rocío , Spinetto Marcela
Published: May 2021

In order to achieve a better understanding of Narcissistic Personality Disorder (NPD), the aim of this study was to analyze the relationship between this pathology and specific Early Maladaptive Schemas (EMS) discovered by J. Young. With this aim, one hundred women of low socioeconomic status, who lived in Buenos Aires (Argentina), were assessed with the SCID-II psychiatric interview and the AMAI-2018 and YSQ-L2 questionnaires. Results indicated significant differences in the Emotional Deprivation, Mistrust/Abuse, Unrelenting Standards, Insufficient Self-Control and Entitlement/Grandiosity schemas among women with NPD (n = 65). The presence of these schemas in the group with NPD suggests paranoid tendencies, empathic difficulties, impulsivity, feelings of superiority and the development of utilitarian interpersonal relationships. These characteristics would constitute one of the most severe presentations of NPD.
Validez de contenido de la Escala de Autoeficacia Colectiva Docente
Authors: Sánchez-Rosas Javier , Dyzenchauz Malena , Dominguez-Lara Sergio
Published: May 2021

Collective teacher self-efficacy, understood as the shared perceptions of the teachers of a school that, together, they will be able to organize and execute the necessary actions to produce a positive effect on the students, was related to different variables associated to education. Despite the importance it has acquired in recent years, the instruments created to measure it have limitations. For this reason, the present work sets out to develop an instrument to evaluate it and obtain evidence of content validity. To do this, the items were written together with teachers and researchers, according to the six dimensions of teacher self-efficacy proposed by Bandura (2006). Then, an expert judgment test was prepared with a sample of teachers and another one with a sample of researchers. The items proved to be valid in terms of their relevance and clarity, although significant differences were found between the evaluations of both samples.
Actitudes hacia la cuarentena en adultos argentinos: asociaciones con variables sociodemográficas y psicológicas
Authors: Gago Galvagno Lucas , De Grandis Carolina , Ferrero Florencia , Loss Julián , Castrillón Diego , Celleri Milagros , Mustaca Alba
Published: May 2021

Due to the pandemic by COVID-19, on March 20 in Argentina, preventive and compulsory social isolation was decreed. The objective was to analyze attitudes towards quarantine and relate them to sociodemographic and psychological variables, in 1,066 adults. The Scale of Negative Attitudes towards quarantine (NA), Scale of Frustration Intolerance (FI), Scale of Cognitive Emotional Regulation (CERQ) and ad-hoc sociodemographic questionnaire were used. The surveys were sent online during the first month of compulsory isolation. Supporting the hypotheses raised, it was found that 80% of the participants reported complying with the quarantine, and the NA increased according to: high levels of FI and non-adaptative ER, days of confinement, gender, age, in those who did not comply 100% with isolation and in the unemployed ones. Although, results suggest that associations were found, longitudinal studies after the first phase of quarantine are necessary.
New recommendations of the American College of Rheumatology for the patient management with gout (2020). Review on some points
Authors:   Pirogov Russian National Research Medical University, Moscow, Russian Federation, Gromova M.A. , Tsurko V.V. ,   Pirogov Russian National Research Medical University, Moscow, Russian Federation,   I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russian Federation
Published: May 2021

In May 2020, the updated recommendations of the American College of Rheumatology on the patient management with gout were published. The focus was on the indications for urate-lowering therapy (ULT) and its optimal use, treatment of gout flares, and the importance of lifestyle. A consensus based on current literature and patient preferences resulted in 42 recommendations. The sixteen highly recommended provisions included the following: ULT should be prescribed to all patients with tophi, radiological signs of joint damage or frequent gout flares; allopurinol should be preferred as a ULT first-line drug, including for patients with chronic kidney disease (CKD) above stage III; ULT regimen should begin at a low initial dose of allopurinol (<100 mg/day and below in CKD) or febuxostat (<40 mg/day); the treatment tactics should achieve the goal with dose titration under the control of the serum uric acid (SUA) level to maintain <6 mg/dL (<360 mmol/L). At the beginning of treatment, concomitant anti-inflammatory prophylactic therapy of at least 3–6 months was strongly recommended. Colchicine, nonsteroidal anti-inflammatory drugs or glucocorticoids (oral, intra-articular, or intramuscular) were suggested for the treatment of gout flares. The purpose of this publication was to inform physicians decision-making on the gout treatment about the patient management algorithm and the need to achieve the target level of SUA to prevent flares and complications of the disease. KEYWORDS: gout, hyperuricemia, clinical recommendations, urate-lowering therapy, diet, lifestyle, food, treatment. FOR CITATION: Gromova M.A., Tsurko V.V. New recommendations of the American College of Rheumatology for the patient management with gout (2020). Review on some points. Russian Medical Inquiry. 2021;5(2):89–95. DOI: 10.32364/2587-6821-2021-5-2-89-95.
Reconstruction of Total Solar Irradiance by Deep Learning
Authors: Abduallah Yasser , Wang Jason T. L. , Shen Yucong , Alobaid Khalid A. , Criscuoli Serena , Wang Haimin
Published: May 2021

The Earth's primary source of energy is the radiant energy generated by the Sun, which is referred to as solar irradiance, or total solar irradiance (TSI) when all of the radiation is measured. A minor change in the solar irradiance can have a significant impact on the Earth's climate and atmosphere. As a result, studying and measuring solar irradiance is crucial in understanding climate changes and solar variability. Several methods have been developed to reconstruct total solar irradiance for long and short periods of time; however, they are physics-based and rely on the availability of data, which does not go beyond 9,000 years. In this paper we propose a new method, called TSInet, to reconstruct total solar irradiance by deep learning for short and long periods of time that span beyond the physical models' data availability. On the data that are available, our method agrees well with the state-of-the-art physics-based reconstruction models. To our knowledge, this is the first time that deep learning has been used to reconstruct total solar irradiance for more than 9,000 years.
The Semantics and Collocations Relation in Food Reviews
Authors: Keshtkar Fazel , Shi Ledong , Bukhari Syed Ahmad Chan
Published: May 2021

Finding our favorite dishes have became a hard task since restaurants are providing more choices and va- rieties. On the other hand, comments and reviews of restaurants are a good place to look for the answer. The purpose of this study is to use computational linguistics and natural language processing to categorise and find semantic relation in various dishes based on reviewers’ comments and menus description. Our goal is to imple- ment a state-of-the-art computational linguistics meth- ods such as, word embedding model, word2vec, topic modeling, PCA, classification algorithm. For visualiza- tions, t-Distributed Stochastic Neighbor Embedding (t- SNE) was used to explore the relation within dishes and their reviews. We also aim to extract the common pat- terns between different dishes among restaurants and reviews comment, and in reverse, explore the dishes with a semantics relations. A dataset of articles related to restaurant and located dishes within articles used to find comment patterns. Then we applied t-SNE visual- izations to identify the root of each feature of the dishes. As a result, to find a dish our model is able to assist users by several words of description and their inter- est. Our dataset contains 1,000 articles from food re- views agency on a variety of dishes from different cul- tures: American, i.e. ’steak’, hamburger; Chinese, i.e. ’stir fry’, ’dumplings’; Japanese, i.e., ’sushi’.
Reducing Efficiency Degradation Due to Scheduled Agent Suspensions by Task Handover in Multi-Agent Cooperative Patrol Problems
Authors: Tsuiki Sota , Yoneda Keisuke , Sugawara Toshiharu
Published: May 2021

This paper proposes a method to mitigate the significant performance degradation due to planned suspensions in the multi-agent cooperative patrol problem. In recent years, there has been an increased demand to utilize multiple intelligent agents that control robots. Furthermore, cooperation between multiple agents is required for performing tasks that are complex and/or cover large spaces. However, since robots are machines, they must be periodically inspected or replaced with new ones to prevent unintended breakdowns for continuous operation and to prolong the lifetime of agents as much as possible. However, such suspension of agents for inspection can cause a sudden deterioration in performance, which is not ignorable in some applications. Meanwhile, such suspensions are usually planned; thus, we can know in advance which agents will stop, and when, to anticipate a preparation period before the actual suspension time. Thus, we introduce a negotiation method in which the agents that are scheduled to be suspended hand over some responsible and important tasks to other agents to reduce the impact of a sudden performance degradation. The experimental results show that the proposed method considerably reduces the performance degradation, especially for security patrol applications.
Towards EEG-based Emotion Recognition During Video Viewing
Authors: Christoforou Christoforos , Theodorou Maria
Published: May 2021

Emotions affect our decisions, experiences, preferences, and perceptions. Understanding the neural underpinning of human emotions is a fundamental goal of neuroscience research. Moreover, EEG-based emotion recognition is a key component towards the development of affective-aware intelligent systems. However, characterizing the neural basis of emotions elicited during video viewing has been proven a challenging task. In this paper, we propose a novel machine-learning approach to isolate neural components in EEG signals that are informative of the affective content of emotionally-loaded videos. Based on these components, we define a set of neural metrics and evaluate them as potential indicators of the overall emotional content of each video. We demonstrate the predictive power of the proposed metrics, on the DEAP benchmark dataset for EEG-based emotion recognition. Our results provide novel empirical evidence that the neural components extracted by our method can serve as an informative metric in EEG-based emotion recognition during video viewing and achieving a 4-fold increase in predictive power compared to traditional frequency-based metrics. Moreover, each extracted component is associated with a spatial and a temporal profile, that allows researchers to inspect and interpret the spatiotemporal origins of the underlying neural activity. Thus, our method a framework that facilitates the study of neural correlates of emotion during video viewing.
Bias Adaptive Statistical Inference Learning Agents for Learning from Human Feedback
Authors: Watson Jonathan I
Published: May 2021

We present a novel technique for learning behaviors from ahuman provided feedback signal that is distorted by system-atic bias. Our technique, which we refer to as BASIL, modelsthe feedback signal as being separable into a heuristic evalu-ation of the utility of an action and a bias value that is drawnfrom a parametric distribution probabilistically, where thedistribution is defined by unknown parameters. We presentthe general form of the technique as well as a specific algo-rithm for integrating the technique with the TAMER algo-rithm for bias values drawn from a normal distribution. Wetest our algorithm against standard TAMER in the domain ofTetris using a synthetic oracle that provides feedback undervarying levels of distortion. We find our algorithm can learnvery quickly under bias distortions that entirely stymie thelearning of classic TAMER.
A study of Media Polarization with Stylometry Methods
Authors: Hu Yifei , Rayz Julia
Published: May 2021

This research investigated the U.S. media polarization with stylometry approaches, creating classification models to identify the political leanings of news articles based on their writing style. We tested the models of authorship attribution, while controlling for topic, stance, and style, and applied them to media companies and their identity within a political spectrum. We tested style features that could include semantic and/or sentiment-related information, such as stance taking, with features that seemingly do not capture it. We were able to successfully classify articles as left-leaning or right-learning regardless of stance. Finally, we provide an analysis of some of the patterns that we found.
Mask Recognition with Computer Vision in the Age of a Pandemic
Authors: Jones Daniel , Christoforou Christoforos
Published: May 2021

In the current age of coronavirus, monitoring and enforcing correct mask-wearing regulation in public spaces is of para- mount importance. Specifically, there is a need to monitor whether people wear masks and whether they wear them cor- rectly. However, there is a lack of automated systems to rec- ognize correct mask-wearing compliance. In this paper, we propose a computer-vision-based solution to the problem of mask-wearing monitoring. In particular, we propose a convo- lutional neural network to recognize images of people wear- ing masks correctly, people wearing masks incorrectly, and people not wearing masks at all. Our proposed model is shown to predict correct mask-wearing practices with over 98% accuracy. The model can be easily deployed as an auto- mated system to screen people entering indoor spaces, and can replace current manual, time-consuming, temperature- screening practices. Such applications can serve as an im- portant tool to help reduce transmission rates during the cur- rent pandemic.
CovidBERT-Biomedical Relation Extraction for Covid-19
Authors: Hebbar Shashank , Xie Ying
Published: May 2021

Given the ongoing pandemic of Covid-19 which has had a devastating impact on society and the economy, and the explosive growth of biomedical literature, there has been a growing need to find suitable medical treatments and therapeutics in a short period of time. Developing new treatments and therapeutics can be expensive and a time consuming process. It can be practical to re-purpose existing approved drugs and put them in clinical trial. Hence we propose CovidBERT, a biomedical relationship extraction model based on BERT that extracts new relationships between various biomedical entities, namely gene-disease and chemical-disease relationships. We use the transformer architecture to train on Covid-19 related literature and fine-tune it using standard annotated datasets to show improvement in performance from baseline models. This research uses the transformer BERT model as its foundation and extracts relations from newly published biomedical papers.
The Role of Model Selection in Preference Learning
Authors: Huelsman Michael Andrew , Truszczynski Miroslaw
Published: May 2021

Learning preferences of an agent requires choosing which preference representation to use. This formalism should be expressive enough to capture a significant part of the agent's preferences. Selecting the right formalism is generally not easy, as we have limited access to the way the agent makes her choices. It is then important to understand how ``universal" particular preference representation formalisms are, that is, whether they can perform well in learning preferences of agents with a broad spectrum of preference orders. In this paper, we consider several preference representation formalisms from this perspective: lexicographic preference models, preference formulas, sets of (ranked) preference formulas, and neural networks. We find that the latter two show a good potential as general preference representation formalisms. We show that this holds true when learning preferences of a single agent but also when learning models to represent consensus preferences of a group of agents.
Covid-19 News Clustering using MCMC-Based Learing of finite EMSD Mixture Models
Authors: Su Xuanbo , Bouguila Nizar , Zamzami Nuha
Published: May 2021

With the growth of social media information on the Web, performing clustering on different types of data is a challenging task.Statistical approaches are widely used to tackle this task. Among the successful statistical approaches, finite mixture models have received a lot attention thanks to their flexibility. There are already many finite mixture models to cope with this task, but the Exponential Multinomial Scaled Dirichlet Distributions (EMSD) has recently shown to attain higher accuracy compared to other state-of-the-art generative models for count data clustering. Thus, in this paper, we present a Bayesian learning method based on Markov Chain Monte Carlo and Metropolis-Hastings algorithm for learning this model parameters. This proposed method is validated via extensive simulations and comparison with multinomial based mixture models.
Critique Generation to Increase Diversity in Conversational Recipe Recommender System
Authors: Abbas Fakhri G , Najjar Nadia , Wilson David
Published: May 2021

Conversational recommender systems help to guide users in exploring the search space in order to discover items of interest. During the exploration process, the user provides feedback on recommended items to refine subsequent recommendations. Critiquing as a way of feedback has proven effective for conversational interactions. In addition, diversifying the recommended items during exploration can help to increase user understanding of the search space, which critiquing alone will not achieve. Both aspects are important elements for recommender applications in the food domain. Diversity in diet has been shown to predict nutritional health, and conversational exploration can help to introduce new food items. In this paper, we introduce a novel approach that brings together critique and diversity to support conversational recommendation in the recipe domain. Initial evaluation in comparison to a baseline similarity-based recommender shows that the proposed approach increases diversity during the exploration process.
Mutual Implication as a Measure of Textual Equivalence
Authors: Nighojkar Animesh , Licato John
Published: May 2021

Semantic Textual Similarity (STS) and paraphrase de- tection are two NLP tasks that have a high focus on the meaning of sentences, and current research in both re- lies heavily on comparing fragments of text. Little to no work has been done in studying inference-centric ap- proaches to solve these tasks. We study the relation be- tween existing work and what we call mutual implica- tion (MI), a binary relationship between two sentences that holds when they textually entail each other. MI thus shifts the focus of STS and paraphrase detection to un- derstanding the meaning of a sentence in terms of its in- ferential properties. We study the comparison between MI, paraphrasing, and STS work. We then argue that MI should be considered a complementary evaluation met- ric for advancing work in areas as diverse as machine translation, natural language inference, etc. Finally, we study the limitations of MI and discuss possibilities for overcoming them.
Complementary Document Representations for Information Retrieval
Authors: Melzer Sylvia
Published: May 2021

In this paper, we present an approach for combining different document representations to support retrieval systems to deliver similar documents from different views.
Automated Assessment of Quality of Jupyter Notebooks Using Artificial Intelligence and Big Code
Authors: Oli Priti , Banjade Rabin , Tamang Lasang Jimba , Rus Vasile
Published: May 2021

We present in this paper an automated method to assess the quality of Jupyter notebooks. The quality of notebooks is assessed in terms of reproducibility and executability. Specifically, we automatically extract a number of expert-defined features for each notebook, perform a feature selection step, and then trained supervised binary classifiers to predict whether a notebook is reproducible and executable, respectively. We also experimented with semantic code embeddings to capture the notebooks' semantics. We have evaluated these methods on a dataset of 306,539 notebooks and achieved an F1 score of 0.87 for reproducibility and 0.96 for executability (using expert-defined features) and an F1 score of 0.81 for reproducibility and 0.78 for executability (using code embeddings). Our results suggest that semantic code embeddings can be used to determine with good performance the reproducibility and executability of Jupyter notebooks, and since they can be automatically derived, they have the advantage of no need for expert involvement to define features.
Competence region estimation for black-box surrogate models
Authors: Shah Tapan
Published: May 2021

With advances in edge applications for industry andhealthcare, machine learning models are increasinglytrained on the edge. However, storage and memory in-frastructure at the edge are often primitive, due to costand real-estate constraints. A simple, effective methodis to learn machine learning models from quantized datastored with low arithmetic precision (1-8 bits). In thiswork, we introduce two stochastic quantization meth-ods, dithering and stochastic rounding. In dithering, ad-ditive noise from a uniform distribution is added tothe sample before quantization. In stochastic rounding,each sample is quantized to the upper level with prob-ability p and to a lower level with probability 1-p. Thekey contributions of the paper are

 For 3 standard machine learning models, Support Vec-tor Machines, Decision Trees and Linear (Logistic)Regression, we compare the performance loss for astandard static quantization and stochastic quantiza-tion for 55 classification and 30 regression datasetswith 1-8 bits quantization.

We showcase that for 4- and 8-bit quantization overregression datasets, stochastic quantization demon-strates statistically significant improvement.

We investigate the performance loss as a function ofdataset attributes viz. number of features, standard de-viation, skewness. This helps create a transfer functionwhich will recommend the best quantizer for a givendataset.

We propose 2 future research areas, a) dynamic quan-tizer update where the model is trained using stream-ing data and the quantizer is updated after each batchand b) precision re-allocation under budget constraintswhere different precision is used for different features.
ДОСЛІДЖЕННЯ СУЧАСНОГО СТАНУ ТА АНАЛІЗ ДЕРЖАВНОГО БОРГУ УКРАЇНИ
Authors: Романькова Оксана
Published: May 2021

У статті розглянуто державний та гарантований державою борг України, його структуру, помісячні платежі за державним боргом у 2021 році. На основі даних Міністерства фінансів України досліджено динаміку державного й гарантованого державою боргу України за період 2009-2021 рр., проведено аналіз. Від способів врегулювання боргової проблеми залежить рівень бюджетного забезпечення держави, стабільність її національної валюти, а, звідси, фінансова підтримка міжнародних фінансових організацій. Необхідні пошуки нових шляхів вдосконалення механізмів управління та обслуговування державного боргу країни, посилення адміністративного контролю за фінансовими потоками з боку держави, використання найкращих світових практик, а також залучення іноземних інвесторів, що створить в майбутньому сприятливий інвестиційний клімат.
ВПЛИВ РЕФОРМИ ДЕЦЕНТРАЛІЗАЦІЇ ТА БЮДЖЕТНОЇ ЕФЕКТИВНОСТІ ТЕРИТОРІЙ
Authors: Стащук Олена , Жук Марія
Published: May 2021

У статті встановлено роль бюджетної ефективності територій у їх комплексному соціально-економічному розвитку та наголошено на особливій вагомості такого дослідження в процесі децентралізації. Проаналізовано сутність бюджетної ефективності та її особливості в умовах проведення реформи децентралізації. Встановлено, що однією з центральних проблем забезпечення бюджетної ефективності територій є впорядкування джерел формування їх бюджетів та ефективності використання фінансових ресурсів. Досліджено змістовну сутність понять «бюджетна ефективність», «децентралізація», «фінансова децентралізація». Сформовано типові характеристики бюджетної ефективності територій та запропоновано авторський підхід до розуміння поняття «бюджетна ефективність територій». Сформовано окремі висновки щодо проведеної реформи децентралізації на основі аналізу статистичних даних.
ELECTROFLOTATION TREATMENT OF DAIRY WASTEWATER: CHEMICAL-TECHNOLOGICAL ASPECTS
Authors: Makarov Ye.
Published: May 2021

Experimental researches are carried out and chemical-technological laws of reagent-electroflotation treatment of sewage of dairies are established. The wastewater of the milk processing enterprise of Sumy region was selected for the study. For reagent wastewater treatment, ferric chloride FeCl3 in the form of a 5% aqueous solution is selected. To accelerate the hydrolysis of the reagent as an alkaline additive was used calcium oxide (lime) CaO in dry form and sodium hydroxide NaOH in the form of 5% aqueous solution. To accelerate the formation of sediment (sludge) used flocculant nonionic polyacrylamide (PAA) in the form of 0.05% aqueous solution. The efficiency of treatment was studied by the following indicators of wastewater: hydrogen pH, transparency and amount of ether-soluble substances. It is established that the process of extraction of ether-soluble substances largely depends on the pH of the medium and increases with increasing alkalinity of wastewater. The greatest influence of pH of the environment is observed at concentration of FeCl3 of 100-150mg / dm3. When FeCl3 is added at a concentration of 200mg / dm3, the purification effect does not depend on the pH of the medium. The most effective is the addition of ferric chloride and then lime. Initially, the addition of FeCl3 coagulates proteins and partially demulsifies the fat emulsion. After the introduction of lime into the water, hydrolysis and formation of iron hydroxide Fe(OH)3 occurs, on the surface of which contaminants are adsorbed. The greatest degree of purification from ether-soluble substances 87-88% is provided by addition of ferric chloride FeCl3 in concentration of 150-200mg / dm3 at pH of 9,5-10. It was found that when using lime to increase the pH of wastewater at a concentration of 500mg / dm3, there is a more efficient removal of ether-soluble substances and suspended solids (increased transparency), and less sediment is formed. Summarizing the obtained data, the optimal concentrations of reagents for pre-treatment of wastewater were selected – FeCl3 - 100mg / dm3, CaO - 500mg / dm3 and wastewater pH - 7.2. It is shown that the reduction of the content of ether-soluble substances to 40mg / dm3 (at the maximum permissible concentration for dairy wastewater 50mg / dm3) is possible only at high processing time (20-30 minutes) and density (0.05A / cm2) and voltage (26 V) electric current, which leads to high electricity consumption.
EVALUATION OF LOAD-BEARING CAPACITY OF THE STEEL CONSTRUCTION JOINTS ON THE BASIS OF COMPONENT METHOD
Authors: Solodovnyk Y. , Riumin V. , Nikichanov V.
Published: May 2021

Connections are essential in every kind of steel constructions. Structure is a constructed assembly of joints separated by members which implies the importance of connections. Three basic parameters describe the behavior of connections: strength, stiffness and ductility, and the mechanical behavior of steel joint in those terms are complex phenomena. It must be said that absence in current Ukrainian design codes rules for the load capacity calculation of steel constructions connections led to some difficulties in project decisions. On the basis of component method, which lay in the EC3 design codes load capacity estimation of beam to column connection was made. According to component method beam to column connection divided into basic components. EN 1993 -1-8 provides a good overview of different components. Most important components for bolted steel joints are the plates and bolts which both are considered by the design of a T-stub through the “Equivalent T-stub in tension”. The procedure of load capacity calculation used yield line formulations to determine resistance of the following basic components: column flange in bending, end plate in bending, column flange in bending, column web in tension, column web in compression, beam flange in compression. Failure by this method is described by yield-line models depending on geometry of plates and bolts. Obtained analytical results were compared with the results obtained by means of specialized software and it shown their adequacy. It must be noted that presented in EC3 calculation algorithm of beam to column connection is time consumable for domestic designer also designer must have knowledge about features of connection design in countries of EC. The choice of design procedure depends on the time effort and thereby to the designer preferences.
EXPERIMENTAL-THEORETICAL CALCULATION OF THE STRESS-DEFORMED STATE OF THE BAR ON THE ELASTIC BASIS
Authors: Shatohin V. , Yakovlev E. , Levenko H. , Honcharova Z.
Published: May 2021

Any strip foundation, and sometimes a slab foundation can be consideredas a be a mon an elastic base. And if with calculation of a beam – the tape base problems practically do not a rise because loading on the tape base as a rule is evenly distributed, and means and the base be haves, a sabsolutelyrigid beam. Then when considering a section of the foundation with unevenlyapplied load, some problems may arise.
Today there are many publications on studies of the use of beams with an elastic base in the field of construction and the application of the features of the method of calculating the stress-strain state in the field of design. As is known, from classical soil mechanics, when a load is applied to a flexible slab, its center gives a draft of 1.24-1.57 times greater than the edges. Note that this effect can be explained by the contour work of the base and its uneven stiffness in the central and peripheral zone of the slab foundation.
It should be noted that today in most cases the method of BN Zhemochkin [6] is used as the basis for the analytical solution of the problem of the interaction of the beam with the elastic base, which combines an engineering approach and strict solutions of the theory of elasticity. According to research, the method is based on the replacement of the continuous problem of the interaction of the foundation beam with the soil base, discrete, with a limited number of calculated sections within the beam and approximation of the smooth reactive pressure curve stepped with a constant value within a single section. Such simplifications allow to calculate various engineering problems on interaction of beams and plates, including with difficult geometry with the set degree of accuracy, bypassing difficult differential and integral calculations.