Miracle-dz/UniFAR-FTUs huggingface dataset:
Asymmetric Influence of Dual-Task Interference on Anticipatory Postural Adjustments in One-Leg Stance

This study investigated the differences of anticipatory postural adjustments (APAs) in a one-leg stance (OLS) that appear according to lower-extremity dominance and dual-task interference. Thirteen young, healthy, male volunteers performed the OLS task under the following six conditions: (1) dominant leg (DL), single-task; (2) DL, dual-task, with a low level of cognitive load (DT1/2); (3) DL, dual-task, with a high level of cognitive load (DT + 1); (4) non-dominant leg (NDL), single-task; (5) NDL, DT1/2; and (6) NDL, DT + 1. In order to measure the subjects’ APA, we used the medial–lateral displacement of their centers of pressure and gravity from the force plate and the time-series data of joint angular motions, recorded using a 3D motion analysis system. In the NDL under the dual-task condition, the onset of APA was delayed and the amplitude declined, which resulted in an increase in the duration of the APA period. The number of components identified by principal component analysis differed according to the dominant foot, and the change caused by cognitive load was found only in the NDL. As the cognitive load increased, the variance of the principal component decreased. These findings show that dual-task interference asymmetrically influences APA according to limb dominance, which reorganizes the coordination strategy of joints’ angular motion.
Does Non-Immersive Virtual Reality Improve Attention Processes in Severe Traumatic Brain Injury? Encouraging Data from a Pilot Study

Traumatic brain injury (TBI) is a sudden injury that causes damage to the brain. Rehabilitation therapies include specific training, such as attention process training (APT) programs using either standard or innovative approaches. The aim of this study is to evaluate the effects of a non-immersive virtual reality-based attention training to stimulate attention processes and mood in TBI patients. Thirty subjects with TBI were enrolled at the Neurorehabilitation Unit of the IRCCS Neurolesi Center and divided into either the Conventional Attention Process Training Group (C_APT: n = 15) or the Virtual-Based Attention Processes Training Group (VB_APT: n = 15), treated with the Virtual Reality Rehabilitation System (VRRS-Evo). All of the patients were evaluated with a specific psychometric battery before (T0) and after the end (T1) of each program. We found statistically significant differences between the two groups, in particular concerning global cognitive status (p < 0.02), attention processes (p < 0.03), depression symptoms (p < 0.04) and visual attention (p < 0.01). Experimental intragroup analysis showed great statistical significances in all psychometric tests, i.e., the Montreal Cognitive Assessment (p < 0.0006), Attention Matrices (p < 0.0007), the Hamilton Rating Scale-Depression (p < 0.004), the Trail Making Test-A (p < 0.0007), the Trail Making Test-B (p < 0.0007), and the Trail Making test-BA (p < 0.007). Our results suggest that non-immersive virtual reality may be a useful and effective approach for the attention processes recovery and mood of TBI patients, leading to better cognitive and behavioral outcomes.
Management and Control of Enterprise Negative Network Public Opinion Dissemination Based on the Multi-Stakeholder Game Mechanism in China

With the rapid growth of Chinese social network users, the open yet anonymous cyberspace makes the Chinese public more inclined to express their feelings and opinions freely on the Internet, and thus generate opinions that are not conducive to the survival and development of Chinese enterprises, i.e., enterprise negative network public opinion. Based on this, this paper takes a Chinese enterprise’s negative network public opinion as the research object. First, our research identifies the stakeholders involved in the dissemination process of public opinion information. Secondly, we model the decision-making behaviors of stakeholders in different stages to obtain the evolutionarily stable strategy. After that, the simulation experiment is conducted to analyze the key points of enterprise strategy adjustment in different stages of negative network public opinion dissemination. The experimental results show that: (1) In its formation stage, opinion leaders usually do not participate in the event, and thus enterprises need to focus on the active ordinary Internet users; (2) In its development stage, if an enterprise wants to reduce the loss caused by negative events, it needs to make use of online media to give corresponding positive guidance; (3) In its control stage, enterprises should take corresponding legal measures to netizens who make improper remarks on the Internet, increase the risk cost of these netizens group, and cooperate with the government’s control work to guide the negative public opinion to turn in a beneficial direction. Finally, the rationality and effectiveness of the proposed model are verified using a practical case.
Molecular Typing Reveals Environmental Dispersion of Antibiotic-Resistant Enterococci under Anthropogenic Pressure

As a consequence of global demographic challenges, both the artificial and the natural environment are increasingly impacted by contaminants of emerging concern, such as bacterial pathogens and their antibiotic resistance genes (ARGs). The aim of this study was to determine the extent to which anthropogenic contamination contributes to the spread of antibiotic resistant enterococci in aquatic compartments and to explore genetic relationships among Enterococcus strains. Antimicrobial susceptibility testing (ampicillin, imipenem, norfloxacin, gentamycin, vancomycin, erythromycin, tetracycline, trimethoprim-sulfamethoxazole) of 574 isolates showed different rates of phenotypic resistance in bacteria from wastewaters (91.9–94.4%), hospital effluents (73.9%), surface waters (8.2–55.3%) and groundwater (35.1–59.1%). The level of multidrug resistance reached 44.6% in enterococci from hospital effluents. In all samples, except for hospital sewage, the predominant species were E. faecium and E. faecalis. In addition, E. avium, E. durans, E. gallinarum, E. aquimarinus and E. casseliflavus were identified. Enterococcus faecium strains carried the greatest variety of ARGs (blaTEM-1, aac(6′)-Ie-aph(2″), aac(6′)-Im, vanA, vanB, ermB, mefA, tetB, tetC, tetL, tetM, sul1), while E. avium displayed the highest ARG frequency. Molecular typing using the ERIC2 primer revealed substantial genetic heterogeneity, but also clusters of enterococci from different aquatic compartments. Enterococcal migration under anthropogenic pressure leads to the dispersion of clinically relevant strains into the natural environment and water resources. In conclusion, ERIC-PCR fingerprinting in conjunction with ARG profiling is a useful tool for the molecular typing of clinical and environmental Enterococcus species. These results underline the need of safeguarding water quality as a strategy to limit the expansion and progression of the impending antibiotic-resistance crisis.
Clouds and Hazes in Exoplanet Atmospheres

Clouds and hazes are commonplace in the atmospheres of solar system planets and are likely ubiquitous in the atmospheres of extrasolar planets as well. Clouds affect every aspect of a planetary atmosphere, from the transport of radiation, to atmospheric chemistry, to dynamics and they influence - if not control - aspects such as surface temperature and habitability. In this review we aim to provide an introduction to the role and properties of clouds in exoplanetary atmospheres. We consider the role clouds play in influencing the spectra of planets as well as their habitability and detectability. We briefly summarize how clouds are treated in terrestrial climate models and consider the far simpler approaches that have been taken so far to model exoplanet clouds, the evidence for which we also review. Since clouds play a major role in the atmospheres of certain classes of brown dwarfs we briefly discuss brown dwarf cloud modeling as well. We also review how the scattering and extinction efficiencies of cloud particles may be approximated in certain limiting cases of small and large particles in order to facilitate physical understanding. Since clouds play such important roles in planetary atmospheres, cloud modeling may well prove to be the limiting factor in our ability to interpret future observations of extrasolar planets.
High NF-κB and RAGE Expression in Fetal Membrane of Premature Rupture of Membrane (PROM) Subject

BACKGROUND: Premature Rupture of Membranes (PROM) is significantly linked to the infections-related maternal deaths. In the inflammatory process, the influencing stressor will stimulate the activation of Nuclear Factor Kappa B (NF-κB) and Receptor of Advanced Gyclation End product (RAGE). Yet up to date, the expression of NF-κB and RAGE in pregnant women with PROM are still rarely studied. Therefore, this study aimed to observe the differences of NF-κB and RAGE expression from PROM and non-PROM subjects.METHODS: This was a cross-sectional study involving 20 PROM subjects and 20 non-PROM subjects with infections and complications. Samples from the fetal membrane tissue of subjects were obtained and put into paraffin block preparation for the determination of NF-κB and RAGE expression. The detection of NF-κB and RAGE expression was conducted using immunohistochemical staining and observed under an upright light microscope. The expressions were later calculated using ImageJ software. RESULTS: Both NF-κB and RAGE expression were found to be higher in PROM subjects compare to the non-PROM subjects. The median of NF-κB in PROM and non-PROM subjects were 32.47±1.22 and 5.59±1.09, respectively (p=0.000). While the median of RAGE in PROM subjects was 53.58±3.46, and in non-PROM subjects was 11.64±2.49 (p=0.013). CONCLUSION: There is significant difference between NF-κB and RAGE expression in fetal membranes of PROM and non-PROM subjects. Therefore, the increased of NF-κB and RAGE expression can be used as a potential marker to detect complication of PROM.KEYWORDS: premature ruptures of membrane, non-premature ruptures of membrane, expression of NF-κB
Evolution of the Ace-1 and Gste2 Mutations and Their Potential Impact on the Use of Carbamate and Organophosphates in IRS for Controlling Anopheles gambiae s.l., the Major Malaria Mosquito in Senegal

Widespread of insecticide resistance amongst the species of the Anopheles gambiae complex continues to threaten vector control in Senegal. In this study, we investigated the presence and evolution of the Ace-1 and Gste2 resistance genes in natural populations of Anopheles gambiae s.l. , the main malaria vector in Senegal. Using historical samples collected from ten sentinel health districts, this study focused on three different years (2013, 2017, and 2018) marking the periods of shift between the main public health insecticides families (pyrethroids, carbamates, organophosphates) used in IRS to track back the evolutionary history of the resistance mutations on the Ace-1 and Gste2 loci. The results revealed the presence of four members of the Anopheles gambiae complex, with the predominance of An. arabiensis followed by An. gambiae, An. coluzzii, and An. gambiae–coluzzii hybrids. The Ace-1 mutation was only detected in An. gambiae and An. gambiae–coluzzii hybrids at low frequencies varying between 0.006 and 0.02, while the Gste2 mutation was found in all the species with a frequency ranging between 0.02 and 0.25. The Ace-1 and Gste2 genes were highly diversified with twenty-two and thirty-one different haplotypes, respectively. The neutrality tests on each gene indicated a negative Tajima’s D, suggesting the abundance of rare alleles. The presence and spread of the Ace-1 and Gste2 resistance mutations represent a serious threat to of the effectiveness and the sustainability of IRS-based interventions using carbamates or organophosphates to manage the widespread pyrethroids resistance in Senegal. These data are of the highest importance to support the NMCP for evidence-based vector control interventions selection and targeting.
Alveolar Nitric Oxide in Chronic Obstructive Pulmonary Disease—A Two-Year Follow-Up

Chronic obstructive pulmonary disease (COPD) affects the airways and gas exchange areas. Nitric oxide (NO) production from the airways is presented as FENO50 and from the gas exchange areas as alveolar NO (CANO). We aimed to evaluate, over two years, the consistency of the CANO estimations in subjects with COPD. A total of 110 subjects (45 men) who completed the study were included from primary and secondary care settings. CANO was estimated using the two-compartment model. CANO increased slightly during the two-year follow-up (p = 0.01), but FENO50 remained unchanged (p = 0.24). Among the subjects with a low CANO (<1 ppb) at inclusion, only 2% remained at a low level. For those at a high level (>2 ppb), 29% remained so. The modified Medical Research Council dyspnoea scale (mMRC) score increased at least one point in 29% of the subjects, and those subjects also increased in CANO from 0.9 (0.5, 2.1) ppb to 1.8 (1.1, 2.3) ppb, p = 0.015. We conclude that alveolar NO increased slightly over two years, together with a small decline in lung function. The increase in CANO was found especially in those whose levels of dyspnoea increased over time.
Parametric Optimization and Modeling for Flank Wear of Tisin-Tialn Nanolaminate Cutting Insert

Selection of machining parameters and better prediction for cutting tool flank wear is indispensable in hard machining as flank wear is directly influences the quality of machined surface. In the current study, parametric optimization and predictive model were carried out for the flank wear of TiSiN-TiAlN nanolaminate cutting insert in hard turning of 58 HRC AISI 1045 medium carbon steel which is an unexplored area. Taguchi’s method was employed for parametric optimization and predictive model was established for flank wear by response surface methodology (RSM) based regression analysis. Cutting speed = 40 m/min, feed rate = 0.3 mm/rev and depth of cut = 75µm generates optimum value of flank wear 0.07 mm. In conclusion, verification test was carried out to validate the optimal set of parameters and the result was shown a great reduction of 81.42% in the flank wear. The predictive model elaborated for flank wear was dependable and helps to make better prediction to the manufacturing industries within specified range of the experimentation.
Effective Method for a Graphene Oxide with Impressive Selectivity in Carboxyl Groups

The development of new applications of graphene oxide in the biomedical field requires the covalent bonding of bioactive molecules to a sheet skeleton. Obtaining a large carboxyl group population over the surface is one of the main targets, as carboxyl group concentration in conventional graphene oxide is low among a majority of non-useful sp3-C-based functionalities. In the present work, we propose a selective method that yields an impressive increase in carboxyl group population using single-layer, thermally reduced graphene oxide as a precursor in a conventional Hummers–Offemann reaction. When starting with a reduced graphene oxide with no interlayer registry, sulfuric acid cannot form a graphite intercalated compound. Then, potassium permanganate attacks in in-plane (vacancies or holes) structural defects, which are numerous over a thermally reduced graphene oxide, as well as in edges, yielding majorly carboxyl groups without sheet cutting and unzipping, as no carbon dot formation was observed. A single-layer precursor with no ordered stacking prevents the formation of an intercalated compound, and it is this mechanism of the potassium permanganate that results in carboxyl group formation and the hydrophilic character of the compound.
Capturing the Complexity of COVID-19 Research: Trend Analysis in the First Two Years of the Pandemic Using a Bayesian Probabilistic Model and Machine Learning Tools

Publications about COVID-19 have occurred practically since the first outbreak. Therefore, studying the evolution of the scientific publications on COVID-19 can provide us with information on current research trends and can help researchers and policymakers to form a structured view of the existing evidence base of COVID-19 and provide new research directions. This growth rate was so impressive that the need for updated information and research tools become essential to mitigate the spread of the virus. Therefore, traditional bibliographic research procedures, such as systematic reviews and meta-analyses, become time-consuming and limited in focus. This study aims to study the scientific literature on COVID-19 that has been published since its inception and to map the evolution of research in the time range between February 2020 and January 2022. The search was carried out in PubMed extracting topics using text mining and latent Dirichlet allocation modeling and a trend analysis was performed to analyze the temporal variations in research for each topic. We also study the distribution of these topics between countries and journals. 126,334 peer-reviewed articles and 16 research topics were identified. The countries with the highest number of scientific publications were the United States of America, China, Italy, United Kingdom, and India, respectively. Regarding the distribution of the number of publications by journal, we found that of the 7040 sources Int. J. Environ. Res. Public Health, PLoS ONE, and Sci. Rep., were the ones that led the publications on COVID-19. We discovered a growing tendency for eight topics (Prevention, Telemedicine, Vaccine immunity, Machine learning, Academic parameters, Risk factors and morbidity and mortality, Information synthesis methods, and Mental health), a falling trend for five of them (Epidemiology, COVID-19 pathology complications, Diagnostic test, Etiopathogenesis, and Political and health factors), and the rest varied throughout time with no discernible patterns (Therapeutics, Pharmacological and therapeutic target, and Repercussion health services).
Mode Group Division Multiplexing in 5 Mode-Group FMF Enabling MIMO-Free Solutions

We propose mode-group (MG) division multiplexing in a MIMO-free configuration to increase the capacity and the flexibility in reduced-complexity spatial division multiplexed metro networks. We take in account innovative few mode fibers (FMFs) supporting a large number of spatial modes, which allow to select suitable combinations of MGs providing limited crosstalk. Network provisioning in metro rings is investigated starting from experiments with up to 48-Tb/s capacity in a 5 MG FMF employing also a purposely developed quality of transmission tool.
Efficient Learning Algorithms.

Abstract : We have worked on refining and generalizing the PAC learning model introduced by Valiant. Measures of performance for learning algorithms that we have examined include computational complexity, sample complexity, probability of misclassification (learning curves) and worst case total number of misclassifications or hypothesis updates. In some cases we have been able to give theoretically optimal bounds on these performance measures, and exhibit learning algorithms that achieve these bounds. Learning problems we have examined include those for decision trees and decision lists, neural networks, finite automata, hidden Markov models, conjunctive concepts on structural domains, and various classes of Boolean functions. We have developed new techniques for boosting the accuracy of learning algorithms, further explored the relationship between learning and data compression, developed and analyzed new learning algorithms based on weighted majority voting techniques, and studied the problems of learning a probability distribution, learning multivalued functions, and learning stochastic, functions.
‘This disease is not meant for the hospital, it is Asram’: Implications of a traditionally-defined illness on healthcare seeking for children under-5 in rural Ashanti, Ghana

Every child has the right to survive, grow and develop. However, in spite of the considerable global gains that have been made in child survival, Sub-Saharan Africa still has the highest child mortality rates and accounts for the greatest burden of mortality globally. The majority of these children die without ever reaching a health facility. The practice of appropriate healthcare-seeking behaviour has a great potential to reduce the occurrence of severe and life‐threatening childhood illnesses. Several factors, however, influence healthcare-seeking behaviour, including perceptions of the cause of illness and socio-cultural perspectives. This study seeks to understand local concepts of a traditionally-defined illness complex, Asram, and its influence on healthcare seeking behavior of mothers/caregivers. This qualitative study was conducted from October 2019 to February 2020. Four Focus Group Discussions were conducted with mothers/caregivers of children under-5 and 22 Key Informant Interviews with mothers/caregivers of children who had Asram, health workers at district, facility, and community levels, and Asram healers. Participants were selected from two rural communities, Akutuase and Wioso of the Asante Akim North district in the Ashanti region of Ghana. Data analysis was carried out iteratively throughout data collection, using a thematic analysis approach. The study shows that Asram is a childhood illness complex that is perceived to have been acquired spiritually and/or inherited. Nine types of Asram were described. This childhood illness was said to be treatable by Asram healers who had sub-specialties in treatment approaches that were determined by the Asram type reported. Mothers/caregivers trusted Asram healers and preferred to call on them first. This was found to be the main reason for delays in seeking healthcare for children under-5 who showed symptoms of Asram. Asram is a childhood illness complex that is believed to be better managed outside the health facility setting. This study complements existing knowledge and creates opportunities for further research and the introduction of more effective interventions in the effort to improve child survival in rural communities.
Dynamics of Nano-Particles Inside an Optical Cavity in the Quantum Regime

We investigate the optomechanical effect on a single nano-particle inside an optical cavity, by deriving the optical forces acting on the nano-particle by the cavity from quantum theory. We obtain the steady state of the system and found that the force contains three terms associated with the gradient force, the back-action force resulting from the intra-cavity photon energy change, as well as the reactive force associated with the coupling between the external field and the cavity. Moreover, we solve the dynamical system for a dielectric particle in a small mode volume cavity, which is characterized by a quasi-periodic pattern. These results are important for understanding the control of various types of levitated nano-particles through optomechanical coupling.
Edge-Preserving Consensus via Non-Recursive Filters: A Parallel System Design

This brief studies the edge-preserving consensus problem in discrete-time multi-agent systems. An edge-based parallel system design method is proposed for designing the channel filters, which consist of the nominal elements and the masking elements. Firstly, the design criterions for the edge-preserving protocols are provided by discussing the edge sensitivity matrix of the stuided multi-agent system. It is shown that the design of the masking element is based on the single parameter of the nominal element and the $\mathcal {H}_{\infty }$ norm of a collapsed system. Then, an algorithm for designing the heterogenous channel filters is provided, which is based on adopting a cascade realization of several subsystems.