Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of interactions between potent inhibitors of ATP sulfurylase via molecular dynamics

The dynamic behaviour of adenosine triphosphate sulfurylase (ATPs) is analysed to investigate its energetic interactions with inhibitors recently studied theoretically and tested experimentally. The interactions between ATPs and three inhibitors namely, 2,2′-azino-di-(3-ethylbenzothiazoline)-6-sulfonic acid (ABTS), butylated hydroxytoluene (BHT), and 3-tert-butyl-4-hydroxyanisole (BHA) in aqueous solution were studied via molecular dynamics simulations. The results of the absolute and relative free energies reveal the existence of synergism in the system. Additionally, the system demonstrates strong steric effect between ABTS and BHA that is not only due to the size of these inhibitors but also their surroundings.
Dynamical Properties and Conceptual Interpretation of Latent Change Score Models

Latent Change Score models (LCS) are a popular tool for the study of dynamics in longitudinal research. They represent processes in which the short-term dynamics have direct and indirect consequences on the long-term behavior of the system. However, this dual interpretation of the model parameters is usually overlooked in the literature, and researchers often find it difficult to see the connection between parameters and specific patterns of change. The goal of this paper is to provide a comprehensive examination of the meaning and interpretation of the parameters in LCS models. Importantly, we focus on their relation to the shape of the trajectories and explain how different specifications of the LCS model involve particular assumptions about the mechanisms of change. On a supplementary website, we present an interactive Shiny App that allows users to explore different sets of parameter values and examine their effects on the predicted trajectories. We also include fully explained code to estimate some of the most relevant specifications of the LCS model with the R-packages lavaan and OpenMx.
Neutrophil-to-Lymphocyte Ratio as a Predictive Biomarker for Stroke Severity and Short-Term Prognosis in Acute Ischemic Stroke With Intracranial Atherosclerotic Stenosis

Background: Neutrophil-to-lymphocyte ratio (NLR) is an indicator of poor prognosis in acute ischemic stroke (AIS), but associations between NLR with stroke severity and prognosis of intracranial atherosclerotic stenosis (ICAS)-related ischemic events have not been well-elucidated; therefore, we aimed to evaluate whether admission NLR levels correlate with the early stroke severity and short-term functional prognosis in patients with symptomatic intracranial atherosclerotic stenosis (sICAS). Methods: This retrospective study enrolled 899 consecutive patients with AIS attributed to ICAS at Xiangya Hospital stroke center between May 2016 and September 2020. The initial stroke severity was rated by the admission National Institutes of Health Stroke Scale (NIHSS) scores, and the short-term prognosis was evaluated using the 14-day modified Rankin Scale (mRS) scores after stroke onset. A severe stroke was defined as NIHSS >8; an unfavorable functional outcome was defined as mRS scores of 3–6. Admission NLR was determined based on circulating neutrophil and lymphocyte counts. Results: The median admission NLR of all patients was 2.80 [interquartile range (IQR), 2.00–4.00]. In univariate analysis, admission NLR was significantly elevated in patients with severe stroke and poor short-term prognosis. After multivariate adjustment, admission NLR levels were significantly correlated with severe stroke [odds ratio (OR), 1.132; 95% confidence interval (95% CI), 1.038–1.234; P = 0.005] and unfavorable short-term prognosis (OR, 1.102; 95% CI, 1.017–1.195; P = 0.018) in Model 1. In Model 2, the highest NLR tertile (≥3.533) remained an independent predictor of severe stroke (OR, 2.736; 95% CI, 1.590–4.708; P < 0.001) and unfavorable functional outcome (OR, 2.165; 95% CI, 1.416–3.311; P < 0.001) compared with the lowest NLR tertile (<2.231). The receiver operating characteristic (ROC) curves showed the predictability of NLR regarding the stroke severity [area under the curve (AUC), 0.659; 95% CI, 0.615–0.703; P < 0.001] and short-term prognosis (AUC, 0.613; 95% CI, 0.575–0.650; P < 0.001). The nomograms were constructed to create the predictive models of the severity and short-term outcome of sICAS. Conclusions: Elevated admission NLR levels were independently associated with the initial stroke severity and could be an early predictor of severity and poor short-term prognosis in AIS patients with ICAS, which might help us identify a target group timely for preventive therapies.
Re-evaluating Renal Angina Index: An Authentic, Evidence-Based Instrument for Acute Kidney Injury Assessment: Critical Appraisal

Background/Introduction: Renal angina index (RAI) used to calculate and accurately predict risk for the development of acute kidney injury (AKI) has been heavily explored. AKI is traditionally diagnosed by an increase in serum creatinine (SCr) concentration or oliguria, both of which are neither specific nor sensitive, especially among children. An RAI score may be calculated by combining objective signs of kidney dysfunction (such as SCr) and patient context, such as AKI risk factors, thus potentially serving as a more accurate indicator for AKI. Objective: Due to the propitious and novel nature of RAI, this editorial commentary aims to analyze the current literature on RAI and determine how well RAI serves as a predictor of AKI outcomes. Method: A comprehensive literature search was conducted in PubMed/Medline and Google Scholar between January 2012 and July 2020. Literature included the prognostic aspect of early prediction of AKI in the pediatric and adult population via RAI. Results: The initial literature search included 149 studies, and a total of 10 studies reporting the outcomes of interest were included. The overall sample size across these studies was 11,026. The predictive ability of RAI had a pooled (95% CI) sensitivity of 79.21%, specificity of 73.22%, and negative predictive value of 94.83%. Conclusion: RAI shows benefit in the prediction of AKI among adult and pediatric populations. However, there is a lack of sufficient data, and further prospective studies are needed in pediatric populations to use RAI as a principal AKI indicator among clinicians.
A CT-Based Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Periampullary Carcinomas

Purpose To establish and validate a radiomics nomogram for preoperatively predicting lymph node (LN) metastasis in periampullary carcinomas. Materials and Methods A total of 122 patients with periampullary carcinoma were assigned into a training set (n = 85) and a validation set (n = 37). The preoperative CT radiomics of all patients were retrospectively assessed and the radiomic features were extracted from portal venous-phase images. The one-way analysis of variance test and the least absolute shrinkage and selection operator regression were used for feature selection. A radiomics signature was constructed with logistic regression algorithm, and the radiomics score was calculated. Multivariate logistic regression model integrating independent risk factors was adopted to develop a radiomics nomogram. The performance of the radiomics nomogram was assessed by its calibration, discrimination, and clinical utility with independent validation. Results The radiomics signature, constructed by seven selected features, was closely related to LN metastasis in the training set (p < 0.001) and validation set (p = 0.017). The radiomics nomogram that incorporated radiomics signature and CT-reported LN status demonstrated favorable calibration and discrimination in the training set [area under the curve (AUC), 0.853] and validation set (AUC, 0.853). The decision curve indicated the clinical utility of our nomogram. Conclusion Our CT-based radiomics nomogram, incorporating radiomics signature and CT-reported LN status, could be an individualized and non-invasive tool for preoperative prediction of LN metastasis in periampullary carcinomas, which might assist clinical decision making.
Channeling of Carbon Flux Towards Carotenogenesis in Botryococcus braunii: A Media Engineering Perspective

Microalgae, due to their unique properties, gained attention for producing promising feedstocks having high contents of proteins, antioxidants, carotenoids, and terpenoids for applications in nutraceutical and pharmaceutical industries. Optimizing production of the high-value renewables (HVRs) in microalgae requires an in-depth understanding of their functional relationship of the genes involved in these metabolic pathways. In the present study, bioinformatic tools were employed for characterization of the protein-encoding genes of methyl erythritol phosphate (MEP) pathway involved in carotenoid and squalene biosynthesis based upon their conserved motif/domain organization. Our analysis demonstrates nearly 200 putative genes showing a conservation pattern within divergent microalgal lineages. Furthermore, phylogenomic studies confirm the close evolutionary proximity among these microalgal strains in the carotenoid and squalene biosynthetic pathways. Further analysis employing STRING predicts interactions among two rate-limiting genes, i.e., phytoene synthase (PSY) and farnesyl diphosphate farnesyl synthase (FPPS), which are specifically involved in the synthesis of carotenoids and squalene. Experimentally, to understand the carbon flux of these rate-limiting genes involved in carotenogenesis, an industrial potential strain, namely, Botryococcus braunii, was selected in this study for improved biomass productivity (i.e., 100 mg L–1 D–1) along with enhanced carotenoid content [0.18% dry cell weight (DCW)] when subjected to carbon supplementation. In conclusion, our approach of media engineering demonstrates that the channeling of carbon flux favors carotenogenesis rather than squalene synthesis. Henceforth, employing omics perspectives will further provide us with new insights for engineering regulatory networks for enhanced production of high-value carbon biorenewables without compromising growth.
Physiological Effects and Inter-Individual Variability to 12 Weeks of High Intensity-Interval Training and Dietary Energy Restriction in Overweight/Obese Adult Women

Background: Human adaptive response to exercise interventions is often described as group average and SD to represent the typical response for most individuals, but studies reporting individual responses to exercise show a wide range of responses. Objective: To characterize the physiological effects and inter-individual variability on fat mass and other health-related and physical performance outcomes after 12 weeks of high-intensity interval training (HIIT) and dietary energy restriction in overweight/obese adult women. Methods: Thirty untrained adult overweight and obese women (age = 27.4 ± 7.9 years; BMI = 29.9 ± 3.3 kg/m2) successfully completed a 12-week supervised HIIT program and an individually prescribed home hypocaloric diet (75% of daily energy requirements) throughout the whole intervention. High and low responders to the intervention were those individuals who were able to lose ≥ 10 and < 10% of initial absolute fat mass (i.e., kilograms), respectively. Results: The prevalence for high and low responders was 33% (n = 11) and 66% (n = 19), respectively. At the whole group level, the intervention was effective to reduce the absolute fat mass (30.9 ± 7.2 vs. 28.5 ± 7.2 kg; p < 0.0001), body fat percentage (39.8 ± 4.3 vs. 37.8 ± 4.9%; p < 0.0001), and total body mass (76.7 ± 10.1 vs. 74.4 ± 9.9 kg; p < 0.0001). In addition, there were improvements in systolic blood pressure (SBP; Δ% = −5.1%), diastolic blood pressure (DBP; Δ% = −6.4%), absolute VO2peak (Δ% = +14.0%), relative VO2peak (Δ% = +13.8%), peak power output (PPO; Δ% = +19.8%), anaerobic threshold (AT; Δ% = +16.7%), maximal ventilation (VE; Δ% = +14.1%), and peak oxygen pulse (O2 pulse; Δ% = +10.4%). However, at the individual level, a wide range of effects were appreciated on all variables, and the magnitude of the fat mass changes did not correlate with baseline body mass or fat mass. Conclusion: A 12-week supervised HIIT program added to a slight dietary energy restriction effectively improved fat mass, body mass, blood pressure, and cardiorespiratory fitness (CRF). However, a wide range of inter-individual variability was observed in the adaptative response to the intervention. Furthermore, subjects classified as low responders for fat mass reduction could be high responders (HiRes) in many other health-related and physical performance outcomes. Thus, the beneficial effects of exercise in obese and overweight women go further beyond the adaptive response to a single outcome variable such as fat mass or total body mass reduction.
Systematic Review of Integration and Radicalization Prevention Programs for Migrants in the US, Canada, and Europe

Background: International migration processes are some of the most important events of our time. Migrating implies a broad range of factors that affect integration, and which may be linked to radicalization. Host countries use different methods for the integration of migrants. The aim of this systematic review is to analyze intervention programs that aim at promoting social integration and preventing the radicalization of migrants, with the objective of studying actions carried out in the US, Canada, and Europe to this effect. Method: Worldwide known bibliographic databases (PsyCINFO, Sociological Abstracts, Psycarticles, Psychology Database, Medline, SCOPUS, and Google Scholar) were used to search studies published before January 2019 and which analyzed integration or radicalization prevention programs with migrants. Results: A total of 601 studies were screened, from which 18 met the inclusion criteria. The analysis of programs addressed to migrant women points to a decrease in loneliness and depression and an increase of migrants' perception of social support and self-esteem. Programs carried out in schools and families improve children's knowledge of their culture and that of others, increase their feelings of inclusion, and reduce their aggressiveness, stress, and anxiety. Language programs promote communication and employment search, as well as improve migrants' quality of life. One of the most effective activities included in these programs is to connect recently arrived migrants with local population and/or long-term residents. The latter act as mentors and teachers, helping recently arrived migrants understand resources and to be more integrated in the new country, as well as reducing discrimination from the local population. Conclusions: The review concluded the importance of intervention programs for integration, migrants' quality of life, prevention of extreme behaviors, and intercultural cohabitation. Future programs must be more detailed regarding participants' information and carry out more comprehensive assessments.
How event information is trusted and shared on social media: a uses and gratification perspective

ABSTRACT This study explored the gratification factors of event-focused social media content that affect information sharing and information trust and ultimately the intention to attend an event. It also investigated how non-content factors moderate these relationships. The findings showed that the gratification factors (i.e., informational, entertaining, remunerative, and relational) of social media content significantly influence event attendees’ intention to share information, perceived information trust, and thus their intention to attend the event. Non-contents (i.e., visual design and information overload) act as a critical moderator altering the effects of the gratification factors on attendees’ intention to share and information trust.
Studying the Evolution of Scientific Topics and their Relationships

We propose a study of the development of scientiﬁc topics through time, as well as the relations between them within the scientiﬁc ﬁeld of computational linguistics and across subﬁelds. We use topic modeling to analyze scientiﬁc texts published in the ACL Anthol-ogy, and introduce a categorization of topics in our ﬁeld into 3 types: tasks, algorithms, and data. In order to understand how topics emerge, evolve, and gradually disappear over time, we analyze the evolution of these topics across time through several case studies. We further include in our analysis papers published in NeurIPS, and try to understand whether there was any inﬂuence between topics in this conference focused on neural meth-ods and computational linguistics conferences, as well as measure the divergence over time between conferences in terms of the topics approached. We additionally look at the relationships between topics, categorizing them into types of competing or cooperating topics.
Refactoring Monolithic Object-Oriented Source Code to Materialize Microservice-oriented Architecture

: The emergence of the microservice-oriented architecture (MSA) has led to increased maintainability, better readability, and better scalability. All these advantages make migrating a monolithic software towards an MSA an attractive prospect for organizations. The migration process is recognized to be complex and consequently risky and costly. This process is composed of two phases: (1) the microservice-based architecture recovery phase and (2) the transformation (i.e. materialization) phase. In this paper, we propose a systematic approach to transform an object-oriented monolithic application towards an MS-oriented one by applying a set of transformation pattern. To validate our approach we automated it with our tool MonoToMicro, and applied it on a set of monolithic Java applications to be migrated towards microservices-based ones.
Catalyst Materials Based on Nb2O5 Supported on SiO2−Al2O3: Preparation and Structural Characterization

Supported niobium pentoxide materials have been effective catalysts for a variety of acid and redox reactions (e.g., dehydration of alcohols, esterifications, etc.). To the best of our knowledge, there are no reports about Nb2O5 supported on silica−alumina. Catalysts of Nb2O5/SiO2−Al2O3 were prepared with 2, 5, 10, 15, 20, and 25 wt % of Nb2O5 by aqueous solution impregnation using ammonium niobium oxalate on silica−alumina. The materials, after being dried at 100 °C, were calcined at 800 °C and characterized by several methods. Investigation through X-ray diffraction showed the typical patterns of crystalline Nb2O5, which were composed of mixtures of orthorhombic and monoclinic phases (T, M, and H, respectively) present in the materials with content higher than 10 wt %. DTA curves displayed an exothermic peak at 1356 °C (average) without mass loss (confirmed by TG), which may be ascribed to a phase transition (H phase formation) of Nb2O5 supported on silica−alumina. Pure Nb2O5·nH2O showed a transition fr.
Investigation of the Secure Paths Set Calculation Approach Based on Vulnerability Assessment

An approach to the calculation of secure paths based on the routing model taking into account information security risks using the basic vulnerability criticality metrics is proposed and investigated. The approach for calculating route metrics uses obtained expressions, which characterize the information security risk in network links in the case of existing vulnerabilities. The results of the investigation showed that within the approach of calculating secure paths with increasing packet traffic, the paths in the network that contained links with the lowest weights, i.e. had the least weight of compromise, were loaded first. The transmission of the packet flow after overloading the more secure path was carried out in the following paths according to the values of the weights of the communication links. The paths in the network that contained the links with the highest weights were loaded last.
AH-CID: A Tool to Automatically Detect Human-Centric Issues in App Reviews

In modern software development, there is a growing emphasis on creating and designing around the end-user. This has sparked the widespread adoption of human-centred design and agile development. These concepts intersect during the user feedback stage in agile development, where user requirements are re-evaluated and utilised towards the next iteration of development. An issue arises when the amount of user feedback far exceeds the team’s capacity to extract meaningful data. As a result, many critical concerns and issues may fall through the cracks and remain unnoticed, or the team must spend a great deal of time in analysing the data that can be better spent elsewhere. In this paper, a tool is presented that analyses a large number of user reviews from 24 mobile apps. These are used to train a machine learning (ML) model to automatically generate the probability of the existence of human-centric issues, to automate and streamline the user feedback review analysis process. Evaluation shows an improved ability to find human-centric issues of the users.
Keep the Primary, Rewrite the Secondary: A Two-Stage Approach for Paraphrase Generation

Paraphrase generation is an important and challenging NLG problem. In this work, we propose a new Identiﬁcation-then-Aggregation (IA) framework to tackle this task. In the identiﬁcation step, the input tokens are sorted into two groups by a novel Primary/Secondary Identiﬁcation (PSI) algorithm. In the aggregation step, these groups are separately encoded, before being aggregated by a custom designed decoder, which autoregressively generates the para-phrased sentence. In extensive experiments on two benchmark datasets, we demonstrate that our model outperforms previous studies by a notable margin. We also show that the proposed approach can generate paraphrases in an interpretable and controllable way.
User Identification from Time Series of Fitness Data

We explore the threat posed by disclosure of personal fitness information collected by wearable devices. In particular, we study a scenario where an attacker has a list of aggregated records produced by a group of users, which are stored as time series of steps and calories. We introduce a machine learning-based approach to identify one target person in the aggregated data while being in possession of other records from that person. We estimate how accurately an attacker can find the target’s data when aggregated with other users by testing our approach on two public datasets. Our results show that personal fitness data possess identifying capabilities that should be accounted when they are shared or disclosed.
Characterization of a Vertical Submersible Six-stage Pump: Accounting for the Induced Forces and Stresses

This study deals with the numerical investigation on the shaft behavior of a vertical submersible multistage pump in terms of the axial and radial forces, and the stresses due to the liquid flow through the pump while taking into account different conditions of operation, the gap between the impeller and the diffuser, the rotating speed and the number of stages. This is to improve the pump performances while selecting the bearings and/or the bushes of the submersible pumps in a suitable manner with a long operational life and high reliability. From an existing vertical submersible six-stage pump, a pump model is developed. The continuity, the Navier-Stokes, the stresses and the strains equations are applied to obtain by means of the ANSYS-codes the fields of the liquid flow velocity and the pressure, the stresses, the strains, so as the axial and radial forces. Numerical simulations are carried out to analyze the shaft behavior. The results obtained for the pump head and the stress are validated using the experimental results of the pump head and the results from the classical equations of stresses.