Miracle-dz/UniFAR-FTUs huggingface dataset:
Lattice Boltzmann simulation of channel flow with unsteady lateral overland inflow

This study presents a numerical model for the catchment‐stream problem based on shallow water equations with a lateral source term. A two‐dimensional (2D) lattice Boltzmann equation with an external source term is developed, in which both the mass and momentum are considered. The proposed scheme is validated by a V‐shaped catchment case against analytical solutions and other results from traditional models. The lattice Boltzmann scheme shows good stability at rather low water depths on a mild slope and provides reliable simulated results. Then, the scheme is applied to an open channel flow with a continuous pollutant source, and the impact of the additional lateral momentum on the pollutant distribution is investigated in the stable state.
Ants mediate community composition of root‐associated fungi in an ant‐plant mutualism

Cross‐kingdom interactions with plants were frequently related to microbial pathogens and herbivores. Yet, mutualistic interactions that involve multiple partners can confer cross‐kingdom functional benefits, which have been understudied. Ant gardens (AGs) are recognized as one of the most sophisticated of all symbioses between ants and flowering plants, forming good models to study cross‐kingdom interactions. The aim of this study was to examine whether ant‐plant interactions can influence the community composition of root‐associated fungi. We assessed whether two AG ant species, Camponotus femoratus and Neoponera goeldii, confer different physico‐chemical properties to their nests, and affect root fungal community composition and fungal functional guilds in the bromeliad Aechmea mertensii. The diversity and community composition of root‐associated fungi depended on ant species identity. The two ants had a contrasting influence on the structure and chemistry of the nest, and on the floristic diversity of the AGs. Multiple drivers may therefore determine the root‐associated fungal communities. As the outcome of the ant‐bromeliad interaction depends on the ant species, and because the plants are also involved in interactions with root‐associated symbionts, this study provided evidence that ecologically relevant symbioses can be mediated by cross‐kingdom interactions.
Reduced oscillations based perturb and observe solar maximum power point tracking scheme to enhance efficacy and speed of a photovoltaic system

This paper puts forward a reduced oscillation based perturb and observe (ROP&O) maximum power point (MPP) tracking (MPPT) technique to mitigate the probability of loss of tracking direction and to reduce oscillations around MPP when the solar photovoltaic (PV) array is subjected under periodically changing irradiance. The proposed technique retains the structure of conventional perturb and observe (P&O) technique additionally incorporating a unique structure of dynamic step sizing, along with proportional-integral (PI) controller which potently alters the duty cycle (𝐷) of the DC-DC boost power converter (BPC). The ROP&O MPPT technique is compared with conventional P&O and incremental conductance (IC) schemes in terms of tracking efficacy (𝜂), ripples in PV voltage and PV current, convergence time, and the error rates. The efficacy of the proposed scheme lies between 99.06% to 99.80%. Moreover, the time to obtain MPP is 0.018 sec. which is about five times faster than the P&O technique and fifteen times faster than the IC technique. Also, the proposed MPPT technique is benchmarked using three-phase grid integration, and the power quality of the grid current is observed in terms of total harmonic distortion (THD).
MiRNAs in Systemic Sclerosis Patients with Pulmonary Arterial Hypertension: Markers and Effectors

Background: Pulmonary arterial hypertension (PAH) is a major cause of death in systemic sclerosis (SSc). Early detection may improve patient outcomes. Methods: We searched for circulating miRNAs that would constitute biomarkers in SSc patients with PAH (SSc-PAH). We compared miRNA levels and laboratory parameters while evaluating miRNA levels in white blood cells (WBCs) and myofibroblasts. Results: Our study found: 1) miR-26 and miR-let-7d levels were significantly lower in SSc-PAH (n = 12) versus SSc without PAH (SSc-noPAH) patients (n = 25); 2) a positive correlation between miR-26 and miR-let-7d and complement-C3; 3) GO-annotations of genes that are miR-26/miR-let-7d targets and that are expressed in myofibroblast cells, suggesting that these miRNAs regulate the TGF-β-pathway; 4) reduced levels of both miRNAs accompanied fibroblast differentiation to myofibroblasts, while macitentan (endothelin receptor-antagonist) increased the levels. WBCs of SSc-noPAH and SSc-PAH patients contained equal amounts of miR-26/miR-let-7d. During the study, an echocardiograph that predicted PAH development, showed increased pulmonary artery pressure in three SSc-noPAH patients. At study initiation, those patients and an additional SSc-noPAH patient, who eventually developed PAH, had miR-let-7d/miR-26 levels similar to those of SSc-PAH patients. This implies that reduced miR-let-7d/miR-26 levels might be an early indication of PAH. Conclusions: miR-26 and miR-let-7d may be serological markers for SSc-PAH. The results of our study suggest their involvement in myofibroblast differentiation and complement pathway activation, both of which are active in PAH development.
MiniControl 2.0: Co-Synthesis of Flow and Control Layers for Microfluidic Biochips With Strictly Constrained Control Ports

Recent advances in continuous-flow microfluidics have enabled highly integrated lab-on-a-chip biochips. These chips can execute complex biochemical applications precisely and efficiently within a tiny area, but they require a large number of control ports and the corresponding control logic to generate required pressure patterns for flow control, which, consequently, offset their advantages and prevent their wide adoption. In this article, we propose the first flow-control layer co-synthesis flow called MiniControl, for continuous-flow microfluidic biochips under strict constraints for control ports, incorporating high-level synthesis, physical design, and control system design simultaneously, which has never been considered in previous work. With the maximum number of allowed control ports specified in advance, this synthesis flow aims to generate biochip architectures with high execution efficiency and the corresponding control systems with optimized timing performance. Besides, the overall cost of a biochip can be reduced and the tradeoff between a control system and execution efficiency of biochemical applications can be evaluated for the first time. The experimental results demonstrate that MiniControl leads to high execution efficiency, low platform cost, as well as excellent timing performance, while strictly satisfying the given control-port constraints.
AFall: Wi-Fi-Based Device-Free Fall Detection System Using Spatial Angle of Arrival

Falling is a common health problem for elderly people. Early detection of falls allows earlier rescue measures to be implemented. Most existing Wi-Fi-based fall detection systems employ learning-based methods, which require large amounts of labeled data for prior training. To address this issue, we in this paper present AFall, a robust model-based fall detection system that does not require prior training for a single person based on Wi-Fi Channel State Information (CSI). Different from previous Wi-Fi-based fall detection systems, we model the relationship between human falls and changes of Angle of Arrival (AoA) of Wi-Fi signals reflected from human body by multiple signal classification (MUSIC) algorithm. In particular, we deploy two receivers in orthogonal spatial layouts to capture diversified AoA information. Since AoA reflected from human body is independent of environments and subjects, the performance of AFall can remain stable when the environment changes slightly, which can meet the daily needs of the elderly people. We implement AFall using commodity Wi-Fi devices and evaluate it in five different indoor environments. The experimental results demonstrate that AFall achieves an average accuracy of 84.31% and an average F1 score of 84.56%.
Measurement and Evaluating of Elite Male youth volleyball Athletes’Physical Fitness

By using the method of documentary ,expert interview and statistics Physical fitness data have been collected from the Chinese elite male football players and then six indexes have been established the evaluating norm . Studies indicate the influence on physical fitness is different, and thus all the players were evaluated comprehensively to provide coaches with reasonable control over the process of realizing physical fitness training.
Hardware Implementation of a MIMO Decoder Using Matrix Factorization Based Channel Estimation

Abstract This paper presents an efficient hardware realization of multiple-input multiple-output (MIMO) wireless communication decoder that utilizes the available resources by adopting the technique of parallelism. The hardware is designed and implemented on Xilinx Virtex™-4 XC4VLX60 field programmable gate arrays (FPGA) device in a modular approach which simplifies and eases hardware update, and facilitates testing of the various modules independently. The decoder involves a proficient channel estimation module that employs matrix factorization on least squares (LS) estimation to reduce a full rank matrix into a simpler form in order to eliminate matrix inversion. This results in performance improvement and complexity reduction of the MIMO system. Performance evaluation of the proposed method is validated through MATLAB simulations which indicate 2 dB improvement in terms of SNR compared to LS estimation. Moreover complexity comparison is performed in terms of mathematical operations, which shows that the proposed approach appreciably outperforms LS estimation at a lower complexity and represents a good solution for channel estimation technique.
Systematic Review of Machine Learning Approaches for Detecting Developmental Stuttering

A systematic review of the literature on statistical and machine learning schemes for identifying symptoms of developmental stuttering from audio recordings is reported. Twenty-seven papers met the quality standards that were set. Comparison of results across studies was not possible because training and testing data, model architecture and feature inputs varied across studies. The limitations that were identified for comparison across studies included: no indication of application for the work, data were selected for training and testing models in ways that could lead to biases, studies used different datasets and attempted to locate different symptom types, feature inputs were reported in different ways and there was no standard way of reporting performance statistics. Recommendations were made about how these problems can be addressed in future work on this topic.
Employee green behavior: A
 meta‐analysis

Due to climate change, the need to protect biodiversity and reduce pollution, and governmental regulations, many organizations are aiming to become more environmentally sustainable. In this context, researchers and practitioners are increasingly interested in the construct of employee green behavior (EGB). EGB has been considered by numerous empirical studies over the last two decades and its associations with demographic characteristics, individual differences, work-related perceptions, and job attitudes. To systematically synthesize the rapidly growing literature on EGB, we conducted a meta-analysis ( k = 135 independent samples; total N = 47,442 employees). Results showed positive associations between EGB and, for example, pro-environmental attitudes, corporate social responsibility, and green psychological climate. We further report the results of a meta-analytic path model based on the theory of planned behavior, which showed that pro-environmental attitude, norms, perceived behavioral control, and intentions positively predicted EGB.
Clustering Diagnoses From 58 Million Patient Visits in Finland Between 2015 and 2018

Background Multiple chronic diseases in patients are a major burden on the health service system. Currently, diseases are mostly treated separately without paying sufficient attention to their relationships, which results in the fragmentation of the care process. The better integration of services can lead to the more effective organization of the overall health care system. Objective This study aimed to analyze the connections between diseases based on their co-occurrences to support decision-makers in better organizing health care services. Methods We performed a cluster analysis of diagnoses by using data from the Finnish Health Care Registers for primary and specialized health care visits and inpatient care. The target population of this study comprised those 3.8 million individuals (3,835,531/5,487,308, 69.90% of the whole population) aged ≥18 years who used health care services from the years 2015 to 2018. They had a total of 58 million visits. Clustering was performed based on the co-occurrence of diagnoses. The more the same pair of diagnoses appeared in the records of the same patients, the more the diagnoses correlated with each other. On the basis of the co-occurrences, we calculated the relative risk of each pair of diagnoses and clustered the data by using a graph-based clustering algorithm called the M-algorithm—a variant of k-means. Results The results revealed multimorbidity clusters, of which some were expected (eg, one representing hypertensive and cardiovascular diseases). Other clusters were more unexpected, such as the cluster containing lower respiratory tract diseases and systemic connective tissue disorders. The annual cost of all clusters was €10.0 billion, and the costliest cluster was cardiovascular and metabolic problems, costing €2.3 billion. Conclusions The method and the achieved results provide new insights into identifying key multimorbidity groups, especially those resulting in burden and costs in health care services.
Pengenalan Gestur Angka Pada Tangan Menggunakan Arsitektur AlexNet Dan LeNet Pada Metode Convolutional Neural Network

Gestur merupakan salah satu jenis komunikasi dengan membentuk suatu objek seperti huruf atau angka pada tangan untuk menyampaikan pesan ataupun sebuah informasi, salah satunya gestur angka pada tangan yang memiliki banyak jenisnya dengan pola yang berbeda untuk setiap pergerakan angka yang terbentuk. Salah satu solusi yang dapat dilakukan untuk melakukan pengenalan gestur angka pada tangan kepada komputer adalah menggunakan metode Convolutional Neural Network (CNN) dengan arsitektur AlexNet maupun LeNet. Penelitian ini menggunakan dataset citra gestur angka yang sebelumnya dilakukan tahap pre-processing yang terdiri dari threshold dan resize. Penelitian dilakukan menggunakan 2 pooling layer, yaitu Average Pooling dan Max Pooling kemudian menggunakan optimizer, yaitu SGD, RMSprop, dan Adam. Berdasarkan hasil pengujian yang didapatkan pada penelitian ini, yaitu penggunaan arsitektur AlexNet dengan Average Pooling dan optimizer RMSprop menghasilkan akuras dan f1-score keseluruhan 99,45% serta penggunaan arsitektur LeNet dengan Average Pooling dan optimizer RMSprop menghasilkan akurasi dan f1-score keseluruhan 99,49%. Secara keseluruhan penggunaan Average Pooling dengan optimizer RMSprop mendapatkan tingkat akurasi yang paling baik dibandingkan dengan pengujian yang lainnya.
History of Plant Virology: A Century of Developing a Discipline

Morgan, G. J. 2006. Virus design, 1955–1962: Science meets art. Phytopathology 96:1287-1291. This paper traces the beginnings of structural virology in the mid-20th century, focusing especially on the synergy between models of virus structure and models within art, notably Buckminster Fuller’s geodesic domes and Kenneth Snelson’s tensegrity structures. As Donald Caspar and Aaron Klug sought to extend the Crick-Watson theory of spherical virus structure, they explored analogies between biology and architecture, eventually publishing the classic Caspar-Klug theory of virus structure in 1962.
Identifying SARS-CoV-2 Lineage Mutation Hallmarks and Correlating Them With Clinical Outcomes in Egypt: A Pilot Study

The SARS-CoV-2 pandemic has led to over 4.9 million deaths as of October 2021. One of the main challenges of creating vaccines, treatment, or diagnostic tools for the virus is its mutations and emerging variants. A couple of variants were declared as more virulent and infectious than others. Some approaches were used as nomenclature for SARS-CoV-2 variants and lineages. One of the most used is the Pangolin nomenclature. In our study, we enrolled 35 confirmed SARS-CoV-2 patients and sequenced the viral RNA in their samples. We also aimed to highlight the hallmark mutations in the most frequent lineage. We identified a seven-mutation signature for the SARS-CoV-2 C36 lineage, detected in 56 countries and an emerging lineage in Egypt. In addition, we identified one mutation which was highly negatively correlated with the lineage. On the other hand, we found no significant correlation between our clinical outcomes and the C36 lineage. In conclusion, the C36 lineage is an emerging SARS-CoV-2 variant that needs more investigation regarding its clinical outcomes compared to other strains. Our study paves the way for easier diagnosis of variants of concern using mutation signatures.
Nomophobia and Stress among Vietnamese High School Students in Covid-19 Pandemic: A Mediation Model of Loneliness

Nomophobia is rising among high school students, especially in light of the Covid-19 pandemic, such as social distancing, long-term online learning, and lack of social support. Many studies have also shown that students with high levels of nomophobia have a higher risk of stress. However, very few researchers are interested in studying loneliness as a mediation factor for the relationship between nomophobia and stress. This study investigated whether the loneliness factor is a mediator in the relationship between nomophobia and stress in Vietnamese high school students. Participants include 556 Vietnamese high school students. Participants completed the Nomophobia Scale, Depression Anxiety Stress Scales 21, The UCLA loneliness scale version 3. In this research, to test variable relationships, the mediation analyzing method by the PROCESS macro 3.5 will be applied. The research concludes that for Vietnam high school students, the mediating role of loneliness was identified in the relationship between nomophobia and stress. It is a suggestion through this research that nomophobia preventive and mitigating measures should reduce loneliness in students.
Older Adults’ Engagement in Residential Care: Pitfalls, Potentials, and the Role of ICTs

Over the previous years, the residential care sector has gone through a transition from a rather paternalistic approach towards a more democratic way of caregiving. Nevertheless, many care organizations still find it challenging to engage their residents in the process of care. In this study, we investigated the challenges regarding the engagement of older adults in residential care. As recent studies indicated the increasing opportunities of ICTs, we paid particular attention to this in the process of engagement. We followed a participatory action research approach among caregivers and older adults at a somatic care department in a care residence in the Netherlands. Methods used included 15 participants in two homogeneous group sessions, reflections on action in practice, and one mixed focus group. Our findings show that both caregivers and older adults acknowledge the importance of engagement in daily care. However, their different perspectives on how this should take place, made the actual engagement of older adults a challenge. We determined three dilemmas complicating this engagement in care, and labeled these (1) autonomy versus dependence; (2) personal experiences versus privacy; and (3) happiness versus honesty. We found different ways of how caregivers and older adults deal with these dilemma’s in practice and defined these in terms of pitfalls and potentials. ICTs were shown to reinforce both the pitfalls and potentials. Paying attention to these challenges in residential care, including how caregivers and older adults deal with these challenges, will encourage a mutual understanding and actual engagement in decisions on daily care. Further research is recommended on the role of organizations’ management, older adults’ relatives, or older adults with cognitive impairments.
Linear Version of Parseval’s Theorem

Parseval’s theorem states that the energy of a signal is preserved by the discrete Fourier transform (DFT). Parseval’s formula shows that there is a nonlinear invariant function for the DFT, so the total energy of a signal can be computed from the signal or its DFT using the same nonlinear function. In this paper, we try to answer the question of whether there are linear invariant functions for the DFT, and how they can be found, along with their potential applications in digital signal processing. In order to answer this question, we first prove that the only linear equations that are preserved by the DFT are its orthogonal projections. Then, using Hilbert space for adjoint operators, we propose an algorithm that computes all linear invariant functions for the DFT. These linear invariant functions are also shown to be useful and important in a variety of signal-processing applications, particularly for finding some boundaries for transformed signals without explicitly evaluating the DFT, and vice versa. Additionally, using the proposed identities, we demonstrate that the average of a circular auto-correlation function for a large class of signals is preserved by the DFT. Finally, the results reported in this paper are verified for several short-length and long-length DFTs, including a 256-point DFT.
Financial constraints and the financial distress puzzle: Evidence from a frontier market before and during the Covid-19 pandemic

ABSTRACT We are the first ever to examine the financial constraints and distress risk puzzle of listed manufacturing firms in Vietnam. We employ different estimation methods such as portfolio sorting, Fama Macbeth regression, and asset pricing models to analyse a sample containing 27 300 firm-month observations from 2008 to 2021. Our empirical evidence figures out that the Z-score anomaly exists in the Vietnam stock market before the Covid-19 pandemic. The distress risk puzzle also exists after controlling for financial constraints and other firm characteristics. Moreover, the asset pricing model results conjecture that the distress risk is a priced factor. The average raw returns difference and risk-adjusted returns difference between stocks in the highest and lowest Z-score terciles are around 1% per month. However, we figure out that the Z-score puzzle disappears during the pandemic. Finally, our study employs a two-way sorting methodology to examine the causality between the distress puzzle and financial constraints. Our study figures out that distress risks cause higher financial constraints, not the other way around. Our findings support managers and policymakers in managing the default risk, especially during the pandemic.