Miracle-dz/UniFAR-FTUs huggingface dataset:
KCS-FCnet: Kernel Cross-Spectral Functional Connectivity Network for EEG-Based Motor Imagery Classification

This paper uses EEG data to introduce an approach for classifying right and left-hand classes in Motor Imagery (MI) tasks. The Kernel Cross-Spectral Functional Connectivity Network (KCS-FCnet) method addresses these limitations by providing richer spatial-temporal-spectral feature maps, a simpler architecture, and a more interpretable approach for EEG-driven MI discrimination. In particular, KCS-FCnet uses a single 1D-convolutional-based neural network to extract temporal-frequency features from raw EEG data and a cross-spectral Gaussian kernel connectivity layer to model channel functional relationships. As a result, the functional connectivity feature map reduces the number of parameters, improving interpretability by extracting meaningful patterns related to MI tasks. These patterns can be adapted to the subject’s unique characteristics. The validation results prove that introducing KCS-FCnet shallow architecture is a promising approach for EEG-based MI classification with the potential for real-world use in brain–computer interface systems.
Novel Cooperative Scheme Based on Joint Band Assignment and Power Allocation for a Coexisting Radar-Communications System

In this paper, we present a novel cooperative scheme of joint optimal resource allocation, such that the overall performance of the coexisting radar-communications (CRC) system can be improved. In our proposed scheme, target detection and multiuser communication are performed by radar and communication subsystems at the same time, as well as a control center, which is responsible for joint resource management. We aim to minimize the ISLR for target detection and maximize the sum-rate for communications simultaneously by jointly optimizing the band assignment and transmit power allocation. Since the resulting optimization problem involving two performance metrics and a binary constraint is a multiobjective nonconvex problem, a two-tier iterative decomposition (TT-ID) approach is devised to obtain the globally optimal solution. However, compared with the conventional radar signals, the autocorrelation function of the devised radar signal may still have relatively high sidelobes. In particular, when the data transmission becomes the primary purpose of the CRC system, the sidelobe performance gets worse. As a consequence, some weak targets are most likely overshadowed by the adjacent strong targets through the matched filtering at the radar receiver. To address this, a spectral estimation algorithm based on the Bayes Cauchy–Gaussian (Bayes–CG) model is employed to further reduce the range sidelobes of the matched filter output at the radar receiver according to the prior distribution of the desired autocorrelation. Finally, several numerical results are provided to show the merits of the proposed method.
LES of Premixed V-Flame Using Anisotropic SGS Scalar Flux Model

The present paper describes the evaluation of the n ewly developed Sub Grid Scale(SGS) scalar flux models on rod stabilized premixed methane V-fl ame. LES simulations are performed with the dynamic Smagorinsky SGS model for the flow field. The SGS scalar flux has been modelled by the recently proposed Eddy diffusivity, Anisotropic model together with using dynamic coefficients. In this work combustion is mo delled by flamelet generated manifold (FGM)-tabulated chemistry approach, in which a variable local equivalence ratio due to a possible entrainment of the environment air is incl uded through a mixture fraction variable, is integrated into an appropriate complete model. To a ssess the model capability, LES results of the rod stabilized flame are compared against exper imental data. A satisfactory agreement for the flow field quantities and species concentration s is achieved along with an assessment of the SGS scalar fluxes.
An outside perspective for those within: The presentation of European states in Arab professional online news consumed by Arabic-speaking audiences in Europe

Arab migration to Europe has triggered vast public debate on immigration and European identity. But how do Arabic-speaking groups perceive their European resident countries? This study departs from the crucial role of media arenas in orienting perceptions. Adopting the approach of agenda-setting theory, it analyses news coverage on France and Germany, performing a multilevel text analysis of 3109 news articles in Arabic and relating them to usage data. The analysis of issues showed that France is presented as an active stakeholder in foreign politics, whereas Germany is more strongly depicted in the realm of domestic politics.
Validation of a Finite Element Simulation for Predicting Individual Knee Joint Kinematics

<italic>Goal:</italic> We introduce an in-vivo validated finite element (FE) simulation approach for predicting individual knee joint kinematics. Our vision is to improve clinicians' understanding of the complex individual anatomy and potential pathologies to improve treatment and restore physiological joint kinematics. <italic>Methods:</italic> Our 3D FE modeling approach for individual human knee joints is based on segmentation of anatomical structures extracted from routine static magnetic resonance (MR) images. We validate the predictive abilities of our model using static MR images of the knees of eleven healthy volunteers in dedicated knee poses, which are achieved using a customized MR-compatible pneumatic loading device. <italic>Results:</italic> Our FE simulations reach an average translational accuracy of 2 mm and an average angular accuracy of 1<inline-formula><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> compared to the reference knee pose. <italic>Conclusions:</italic> Reaching high accuracy, our individual FE model can be used in the decision-making process to restore knee joint stability and functionality after various knee injuries.
Implementation Of Work Stress In Moderating Work-Life Balance And Flexible Work Arrangements For Job Satisfaction During The Covid-19 Pandemic

Teachers as human resources in schools have demands that the implementation and work-life balance and flexible work arrangement can be balanced and minimize work stress. The implementation of online learning systems that can make teachers do work-life balance and flexible work arrangements should be able to reduce stress and increase job satisfaction. But the reality in the field is that many teachers do not get job satisfaction. The purpose of this study was to analyze the description and effect of work-life balance, flexible work arrangement, job satisfaction and job stress. The object of this research is the State Senior High School PNS Teachers in Pematang Siantar City who have been certified as many as 168 people. Data analysis techniques used are normality test, regression analysis, correlation coefficient and determination and hypothesis testing. The test was carried out using the SPSS Statistic version 20 program. The results showed are Jjb satisfaction, work-life balance, flexible work arrangement and work stress were in the answers with the criteria of agree/satisfied. The practice of flexible work arrangements affects work-life balance. The results of the regression have a positive influence between each variable. The results of the correlation coefficient analysis obtained a strong and positive relationship. The results of hypothesis testing show a positive and significant effect. Work stress variable is not a moderating variable. It is concluded that the application of work-life balance and flexible work arrangements can increase job satisfaction and work stress is a debilitating variable.
Deep Reinforcement Learning-Based Air-to-Air Combat Maneuver Generation in a Realistic Environment

Artificial intelligence is becoming increasingly important in the air combat domain. Most air combat research now assumes that all aircraft information is known. In practical applications, however, some aircraft information, such as their position, attitude, velocity, etc., can be incorrect or impossible to obtain due to realistic limitations and sensor errors. In this paper, we propose a deep reinforcement learning-based framework for developing a model capable of performing within visual range (WVR) air-to-air combat under the conditions of a partially observable Markov decision process (POMDP) with insufficient information. To deal robustly with such a situation, we use recurrent neural networks and apply a soft actor-critic (SAC) algorithm to cope effectively with realistic limitations and sensor errors. Additionally, to raise the efficiency and effectiveness of learning, we apply the curriculum learning technique to restrict the scope of exploration in state space. Finally, simulations and experiments show that the proposed techniques can deal with practical problems caused by sensor limitations and errors in a noisy environment while also being efficient and effective in reducing the training time for learning.
A Type System for OpenMath

This document describes one possible type system for OpenMath that is an adaptation of the Extended Calculus of Constructions. Including formally specified type information in OpenMath Content Dictionaries allows to assign precise semantical meaning to OpenMath objects corresponding to mathematical notions and therefore to perform automatic validation on OpenMath objects. A Type System for OpenMath (Task: 1.3) iii ESPRIT project 24969: OpenMath iv A Type System for OpenMath (Task: 1.3) ESPRIT project 24969: OpenMath
Novel Oxidative Stress Biomarkers with Risk Prognosis Values in Heart Failure

Oxidative stress (OS) is mediated by reactive oxygen species (ROS), which in cardiovascular and other disease states, damage DNA, lipids, proteins, other cellular and extra-cellular components. OS is both initiated by, and triggers inflammation, cardiomyocyte apoptosis, matrix remodeling, myocardial fibrosis, and neurohumoral activation. These have been linked to the development of heart failure (HF). Circulating biomarkers generated by OS offer potential utility in patient management and therapeutic targeting. Novel OS-related biomarkers such as NADPH oxidases (sNox2-dp, Nrf2), advanced glycation end-products (AGE), and myeloperoxidase (MPO), are signaling molecules reflecting pathobiological changes in HF. This review aims to evaluate current OS-related biomarkers and their associations with clinical outcomes and to highlight those with greatest promise in diagnosis, risk stratification and therapeutic targeting in HF.
Justification Logic And Type Theory: First Steps Towards Justified Typed Modality

In this work, I will present the preliminary concepts of my research topic which rests in the intersection of Justification Logic, Constructive Modality and Type Theory. This is a survey paper towards the second exam requirement for my Phd candidacy under the supervision of Distinguished Professor Sergei Artemov at the Department of Computer Science of the Graduate Center at City University of New York.
Efficient synthesis of furfurylamine from biomass via a hybrid strategy in an EaCl:Gly–water medium

The objective of this work was to develop an efficient approach for chemoenzymatically transforming biomass to furfurylamine by bridging chemocatalysis and biocatalysis in a deep eutectic solvent of EaCl:Gly–water. Using hydroxyapatite (HAP) as support, heterogeneous catalyst SO4 2−/SnO2–HAP was synthesized for transforming lignocellulosic biomass into furfural using organic acid as a co-catalyst. The turnover frequency (TOF) was correlated with the pKa value of the used organic acid. Corncob was transformed by oxalic acid (pKa = 1.25) (0.4 wt%) plus SO4 2−/SnO2–HAP (2.0 wt%) to produce furfural with a yield of 48.2% and a TOF of 6.33 h-1 in water. In deep eutectic solvent EaCl:Gly–water (1:2, v/v), co-catalysis with SO4 2−/SnO2–HAP and oxalic acid was utilized to transform corncob, rice straw, reed leaf, and sugarcane bagasse for the production of furfural with the yield of 42.4%–59.3% (based on the xylan content) at 180°C after 10 min. The formed furfural could be efficiently aminated to furfurylamine with E. coli CCZU-XLS160 cells in the presence of NH4Cl (as an amine donor). As a result of the biological amination of furfural derived from corncob, rice straw, reed leaf, and sugarcane bagasse for 24 h, the yields of furfurylamine reached >99%, with a productivity of 0.31–0.43 g furfurylamine per g xylan. In EaCl:Gly–water, an efficient chemoenzymatic catalysis strategy was employed to valorize lignocellulosic biomass into valuable furan chemicals.
Simulation research on knowledge flow in a collaborative innovation network

This study takes diffusion capacity, absorptive capacity, and relationship strength as the main influencing factors, constructs models of knowledge flow in small‐world networks and scale‐free networks, and uses numerical simulation to observe the flow characteristics of explicit knowledge and tacit knowledge in different networks. The knowledge of explicit flow in different networks exhibits the phenomenon of knowledge emergence, but this phenomenon is more obvious in a small‐world network. The flow of tacit knowledge in a small‐world network has a better effect. In a scale‐free network, the quantity and frequency of knowledge flow are significantly higher than those in a small‐world network. The reason for this phenomenon is the differences in the response, connection and structure of different networks. The quantity and frequency of the flow of explicit knowledge in the same network are significantly higher than those of tacit knowledge. The reason for this phenomenon is the different types of knowledge flow in different modes, with different levels of flow difficulty and flow sustainability. First, this study visually compares the differences in flow between the two types of knowledge. Second, flow models of the two types of knowledge are constructed, and the flow characteristics of the two types of knowledge in different networks are simulated. Finally, the reasons for the differences in flow between the two types of knowledge are explained by using loosely coupled theory.
Determinants of visit-to-visit systolic blood pressure variability among Ghanaians with hypertension and diabetes mellitus

Summary Objective To identify the determinants of systolic blood pressure variability (SBPV) among Ghanaians. Design We undertook a secondary analysis of data collected in a prospective study Setting The study involved patients with hypertension and or diabetes receiving care in five hospitals in Ghana Main outcome measures We assessed determinants of SBPV among 2,785 Ghanaian patients. We calculated the standard deviation (SD) of systolic BP recordings of 3 to 10 visits per patient over 18 months as a measure of SBPV. A multivariate linear regression analysis was fitted to identify factors independently associated with risk visit-to-visit SBP standard deviation. Results The mean SD of individual patient visit-to-visit SBP overall was 14.8± 6.3 mm Hg. Those with hypertension and diabetes had the highest SD of 15.4 ±6.2 mm Hg followed by 15.2 ±6.5 mm Hg among those with hypertension only and then 12.0 ± 5.2 mm Hg among those with diabetes only, p<0.0001. Factors independently associated with SBPV with adjusted β coefficients (95% CI) included age: 0.06 (0.03 – 0.08) for each year rise in age, eGFR -0.03 (-0.05 - -0.02) for each ml/min rise, low monthly income of <210 Ghana cedis 1.45 (0.43-2.46), and secondary level of education -1.10 (-1.69, -0.50). Antihypertensive classes were associated with SBPV, the strongest associations being hydralazine 2.35 (0.03 – 4.68) and Methyldopa 3.08 (2.39 – 3.77). Conclusion Several socio-demographic and clinical factors are associated with SBPV. Future studies should assess the contribution of SBPV to CVD outcomes among indigenous Africans and identify actionable targets. Funding Funding for this study was provided by MSD, Novartis, Pfizer, Sanofi (each a Participant Company) and the Bill and Melinda Gates Foundation (collectively, the Funders) through the New Venture Fund (NVF). FSS and BO are also supported by funding from the National Heart, Lung, and Blood Institute (R01HL152188).
Serum creatinine levels, traditional cardiovascular risk factors and 10-year cardiovascular risk in Chinese patients with hypertension

Background Serum creatinine is associated with cardiovascular risk and cardiovascular events, however, the relationship between serum creatinine levels and cardiovascular risk is not well established in hypertensive population in Jiangsu Province. We aimed to evaluate the association of serum creatinine levels with traditional cardiovascular risk factors and 10-year cardiovascular risk in a Chinese hypertensive population. Methods Participants were patients with hypertension registered and enrolled in health service centers in 5 counties or districts from January 2019 to May 2020 in Jiangsu Province of China followed strict inclusion and exclusion criteria, demographics as well as clinical indicators and disease history and lifestyle were collected. Participants were divided into four groups according to quartiles of serum creatinine levels, then the China-PAR model was used to calculate 10-year cardiovascular risk for each individual. Results A total of 9978 participants were enrolled in this study, 4173(41.82%) were males. The blood pressure level and prevalence of dyslipidemia, elderly, current smokers and drinking as well as obesity were higher in the Q4 group than the Q1 group (all P < 0.05). Multivariable logistic regression showed that serum creatinine in the Q4 group compared with that in the Q1 group was positively associated with overweight and obesity (OR=1.432, 95% CI 1.237-1.658, P<0.001), while negatively associated with physical activity (OR=0.189, 95%CI 0.165-0.217, P<0.001), and so on. Multiple linear regression showed 10-year cardiovascular risk is positively associated with serum creatinine levels after adjusting for multiple risk factors (β=0.432, P< 0.001). Conclusion Serum creatinine was associated with several traditional cardiovascular risk factors and the 10-year cardiovascular risk in hypertensive patients. Creatinine-reduction and kidney-sparing therapy are essential for patients with hypertension to optimize control of cardiovascular risk.
On the Development of Clinical Statistical Systems for Psychiatry

The essential purposes of this presentation are to state briefly some of the basic properties of the data of clinical psychiatry and the implications that these properties have for the application of statistical methodology and inference to such data. One of the most important properties of data relevant to the study of psychopathological processes is that of a general underlying variability within the individual patient-state from one week to the next, or from one day to the next, or even from moment to moment, with respect to a large number of variables which are considered to be important in the description and characterization of mental illness. The realization of such variability as a fundamental property of psychiatric data leads to the conclusion that an observation of a patient-state at a single point in time or with respect to a short time interval cannot in general be expected to provide anywhere near as precise or statistically definitive a description of the patient-state as can be obtained from repeated observations of the same patient taken at relatively close intervals and over a period of sufficient duration. Thus if X represents a vector whose respective components are descriptive of various aspects of the patient-state as observed at a single point in time, then we are interested in estimating the distribution of X for each patient over an adequate period of time rather than in obtaining a single reading of X. This is with respect to obtaining an adequate description of the patient-state per se in statistical-clinical terms even before one uses such a description within a clinical experimental design such as might be used in the evaluation of two or more tranquilizers. The description of patient-states in terms of probabilities estimated from sequences of momentary or short-term states will in general include transition probabilities, i.e., probabilities that are dependent on the previous state. This concept of a stochastic definition of the pa-
Geometrical analysis of spatio-temporal planning problems

In this thesis I represent and analyze spatially and temporally constrained multi-agent planning problems using tools from geometry and advanced calculus. The two problems considered in this thesis are multi-agent rendezvous and dynamic sensor coverage. Together, these problems encompass the cooperation, constraint representation,and task scheduling aspects of multi-agent planning problems. I have represented the constraint of the rendezvous problem on the phase space and shown that the fulfilment of rendezvous constraints is equivalent to certain conical regions being invariant. Alternatively, for the dynamic coverage problem, the constraints can be adequately represented on the uncertainty space and sensor motion laws can be obtained by partitioning the uncertainty space and making decisions based on which partition the uncertainty lies in. I have examined convergence behavior of sensor motion under such laws.
Wavy regime of a power-law film flow

Abstract We consider a power-law fluid flowing down an inclined plane under the action of gravity. The divergence of the viscosity at zero strain rate is taken care of by introducing a Newtonian plateau at small strain rate. Two-equation models are formulated within the framework of lubrication theory in terms of the exact mass balance and an averaged momentum equation, which form a set of evolution equations for the film thickness $h$, a local velocity amplitude or the flow rate $q$. The models account for the streamwise diffusion of momentum. Comparisons with Orr–Sommerfeld stability analysis and with direct numerical simulation (DNS) show convincing agreement in both linear and nonlinear regimes. The influence of shear-thinning or shear-thickening on the primary instability is shown to be non-trivial. A destabilization of the base flow close to threshold is promoted by the shear-thinning effect, whereas, further from threshold, it tends to stabilize the base flow when the viscous damping of short waves becomes dominant. A reverse situation is observed in the case of shear-thickening fluids. Shear-thinning accelerates solitary waves and promotes a subcritical onset of travelling waves at larger wavenumber than the linear cut-off wavenumber. A conditional stability of the base flow is thus observed. This phenomenon results from a reduction of the effective viscosity at the free surface. When compared with DNS, simulations of the temporal response of the film based on weighted residual models satisfactorily capture the conditional stability of the film.
A SURVEY FOR RR LYRAE VARIABLES IN FIVE SMALL MAGELLANIC CLOUD CLUSTERS

Results are presented of a search for RR Lyrae variables in the SMC clusters NGC 121, Lindsay 1, Kron 3, Kron 7, and Kron 44. The techniques used rediscovered the four RR Lyraes in NGC 121, but no variables were found in the other clusters. It is concluded that RR Lyraes do not occur in SMC clusters younger than, ~ 11 Gyr.