Miracle-dz/UniFAR-FTUs huggingface dataset:
Physical Functions among Children before and during the COVID-19 Pandemic: A Prospective Longitudinal Observational Study (Stage 1)

One major impact of the COVID-19 pandemic on children’s lifestyles is the lack of exercise owing to activity restrictions. However, information regarding the way in which physical functions among children decline under these circumstances remains scarce. In this study, we compared the physical functions and life habits among children before and during the COVID-19 pandemic in Japan. The participants involved 40 children aged between 9–15 years (23 girls and 17 boys) who were examined medically both before and during the pandemic. The compared variables included muscle strength, static and dynamic balance functions, gait speed, body fat percentage, screen and sleep times, quality of life, and physical activity time. During the pandemic, compared to before the pandemic, children had lower levels of dynamic balance functions (p = 0.039), increased body fat percentages (p < 0.0001), longer screen time per day (p = 0.002), and shorter sleep time per day (p < 0.0001). Between the two periods, there were no significant differences in muscle strength, static balance functions, gait speed, quality of life, and physical activity time. The activity restrictions imposed as a result of the COVID-19 pandemic negatively affect dynamic balance functions, body-fat levels, and life habits among children.
Comparison of Four Real-Time Polymerase Chain Reaction Assays for the Detection of SARS-CoV-2 in Respiratory Samples from Tunja, Boyacá, Colombia

Coronavirus disease (COVID-19) is an infectious disease caused by SARS-CoV-2. In Colombia, many commercial methods are now available to perform the RT-qPCR assays, and laboratories must evaluate their diagnostic accuracy to ensure reliable results for patients suspected of being positive for COVID-19. The purpose of this study was to compare four commercial RT-qPCR assays with respect to their ability to detect the SARS-CoV2 virus from nasopharyngeal swab samples referred to Laboratorio Carvajal IPS, SAS in Tunja, Boyacá, Colombia. We utilized 152 respiratory tract samples (Nasopharyngeal Swabs) from patients suspected of having SARS-CoV-2. The diagnostic accuracy of GeneFinderTM COVID-19 Plus RealAmp (In Vitro Diagnostics) (GF-TM), One-Step Real-Time RT-PCR (Vitro Master Diagnostica) (O-S RT-qPCR), and the Berlin modified protocol (BM) were assessed using the gold-standard Berlin protocol (Berlin Charité Probe One-Step RT-qPCR Kit, New England Biolabs) (BR) as a reference. Operational characteristics were estimated in terms of sensitivity, specificity, agreement, and predictive values. Using the gold-standard BR as a reference, the sensitivity/specificity of the diagnostic tests was found to be 100%/92.7% for GF-TM, 92.75%/67.47% for O-S RT-qPCR, and 100%/96.39% for the BM protocol. Using BR as a reference, the sensitivity/specificity for the diagnostic tests were found to be 100%/92.7% for the GF-TM assay, 92.72%/67.47% for the O-S RT-qPCR, and 100%/96.39% for BM. Relative to the BR reference protocol, the GF-TM and BM RT-PCR assays obtained similar results (k = 0.92 and k = 0.96, respectively), whereas the results obtained by O-S-RT-qPCR were only moderately similar. We conclude that the GF-TM and BM protocols offer the best sensitivity and specificity, with similar results in comparison to the gold-standard BR protocol. We recommend evaluating the diagnostic accuracy of the OS-RT-qPCR protocol in future studies with a larger number of samples.
Development of GNSS software for Ghana Survey and Mapping Division

Processing of Global Navigational Satellite System (GNSS) data forms the basis for the usage of differential systems for obtaining spatial data. All open sources or commercial software packages developed for data processing give specific details to suit the intended purpose of the software. To obtain a uniform format for submitted survey data, Survey and Mapping Division (SMD) in various jurisdictions have specified formats for data submission for all kinds of surveys. In this regard, “GNSS Ghana” Software (GGS), a GNSS standalone Windows-based application with a modern user-friendly interface was developed for geodetic applications such as, projection and datum transformation worldwide, GNSS data post-processing of Receiver Independent Exchange Format (RINEX) files, and generating reports to meet Ghana SMD reporting standards including cadastral computations and reports for submission. To assess the developed software, GNSS data from two International GNSS Service (IGS) stations (BJCO and YKRO) were processed using GGS and three other commercial software such as GNSS Solution Software (GSS), Spectrum Survey Software (SSS), and Leica Geo Office (LGO), and the positional results compared against the existing coordinate. The results revealed that the GGS outperformed the remaining three commercial software packages with a sub-meter level of accuracy. Further assessment was conducted on datum transformation using the coordinates of 21 existing geodetic control points in Ghana. Utilizing the 7-transformation parameters of Ghana, the results gave uncertainties of [0.10ft. ± 0.99ft. ] in the eastings and [0.02ft. ± 1.61ft. ] in the northings with a 99% confidence level.
Additional dinoflagellates and acritarchs from grey shale member of Dalmiapuram formation, South India

The present communication is a continuation of two previous reports published by Jain and Subba-raman (1969) and Jain and Taugourdeau-Lantz (1973). Additional palaeophytoplankton taxa described from the present material, alongwith the known ones project a complete picture of dinoflagellate and acritarch assemblage from the Grey Shale Member of Dalmiapuram Formation, South India. Fluctuations in the environment of deposition within the exposed section have been indicated. The present microplankton assemblage includes 38 genera and 59 distinct species, out of these 13 species are new. The Grey Shale Member has been assigned an Early Albian age.
Deep Transformer Network for Hyperspectral Image Classification

: Different from the existing CNN-based models, a novel method based on the transformer model is proposed in this paper, to further improve the classification accuracy of hyperspectral image (HSI). Specifically, a deep network model is constructed with the Transformer-iN-Transformer (TNT) modules, to carry out end-to-end classification. The outer and inner transformer models in the TNT module can extract the patch-level and pixel-level features respectively, to make full use of the global and local information in the input cubes. Experimental results show that the proposed method can achieve better classification performance than the existing CNN-based models. In addition, using the transformer-baesd deep model without convolution to classify HSI provides a new idea for the related researches.
• HOW IS PERCEIVED THE FINANCIAL MATHEMATICS TEACHING PROCESS MEDIATED BY ICT? (Differs by type of students and university?)

T his study aims to determine whether there are mean differences in the theoretical model of Universidad Cristobal Colon (UCC) and the Universidad Autonoma de San Luis Potosi (UASLP) which explains the perception towards financial mathematics. 512 students were surveyed: 298 belong to the UCC and 214 to UASLP. The test perception was applied towards to financial mathematics scale (APTFMS) by Garcia and Edel (2008) composed of six factors: history of mathematics, workshop type class, spreadsheet programming, financial simulators design, computer platforms and virtual learning communities. In applying multigroup analysis of means and covariance structures to the data, the results show there is a difference among the perception of students toward to a discipline object of study and to demonstrate that UCC students seem to have a better perception than UASLP students.
Early Biomarker-Guided Prediction of Bloodstream Infection in Critically Ill Patients: C-Reactive Protein, Procalcitonin, and Leukocytes

Abstract Background Bloodstream infections (BSIs) often lead to critical illness and death. The primary aim of this study was to determine the diagnostic accuracy of the biomarkers C-reactive protein (CRP), procalcitonin (PCT), and leukocyte count for the diagnosis of BSI in critically ill patients. Methods This was a nested case–control study based on the Procalcitonin And Survival Study (PASS) trial (n = 1200). Patients who were admitted to the intensive care unit (ICU) <24 hours, and not expected to die within <24 hours, were recruited. For the current study, we included patients with a BSI within ±3 days of ICU admission and matched controls without a BSI in a 1:2 ratio. Diagnostic accuracy for BSI for the biomarkers on days 1, 2, and 3 of ICU admission was assessed. Sensitivity, specificity, and negative and positive predictive values were calculated for prespecified thresholds and for a data-driven cutoff. Results In total, there were 525 patients (n = 175 cases, 350 controls). The fixed low threshold for all 3 biomarkers (CRP = 20 mg/L; leucocytes = 10 × 109/L; PCT = 0.4 ng/mL) resulted in negative predictive values on day 1: CRP = 0.91; 95% CI, 0.75–1.00; leukocyte = 0.75; 95% CI, 0.68–0.81; PCT = 0.91; 95% CI, 0.84–0.96). Combining the 3 biomarkers yielded similar results as PCT alone (P = .5). Conclusions CRP and PCT could in most cases rule out BSI in critically ill patients. As almost no patients had low CRP and ∼20% had low PCT, a low PCT could be used, along with other information, to guide clinical decisions.
Effective energy management strategy based on deep reinforcement learning for fuel cell hybrid vehicle considering multiple performance of integrated energy system

To reduce the power burden of the fuel cell system (FCS) in fuel cell hybrid electric vehicles (FCHEVs), battery and supercapacitor are widely used as energy storage system (ESS) in FCHEVs. In this paper, an energy management strategy (EMS) based on deep reinforcement learning is proposed to solve the power allocation problem among three energy sources. Considering that three energy sources increase the complexity of the state action space, this paper proposes an adaptive fuzzy control filter to separate the load demand power to reduce the computational burden of the deep deterministic policy gradient (DDPG) algorithm. Meanwhile, a learning guidance mechanism (LGM) is proposed in this paper to guide the agent in a rational learning direction, and the reward convergence results are presented in this paper. The training results show that the equivalent hydrogen consumption reaches 99.5% of fuzzy logic controlled‐based EMS (FLC‐EMS), the FCS efficiency improves by 5.9%, and the stability of battery and supercapacitor is also significantly improved. Eventually, three different driving conditions are selected to verify the effectiveness of the proposed EMS, the results show that the proposed EMS in this paper outperforms (FLC‐EMS) in all aspects.
ANALYSIS OF X-RAY IMAGE QUALITIES-ACCURACY OF SHAPE AND CLEARNESS OF IMAGE-USING X-RAY DIGITAL TOMOSYNTHESIS

X-ray laminography and DT(digital tomosynthesis) that can form a cross-sectional image of 3-D objects promis to be good solutions for inspecting interior defects of industrial products. DT is a kind of laminography technique and the difference is in the fact that it synthesizes the several projected images by use of the digitized memory and computation. The quality of images acquired from the DT system varies according to image synthesizing methods, the number of images used in image synthesizing, and X-ray projection angles. In this paper, a new image synthesizing method named 'log-root method' is proposed to get clear and accurate cross-sectional images, which can reduce both artifact and blurring generated by materials out of focal plane. To evaluate the quality of cross-sectional images, two evaluating criteria : (1) shape accuracy and (2) clearness of the cross-sectional images are defined. Based on these criteria, a series of simulations are performed, and the results show the superiority of the new synthesizing method over the existing ones such as averaging and minimum methods.
Study of the Effect of a Closed-End Side Branch on Sinusoidally Perturbed Flow of Liquid in a Line

Classical undamped acoustic-wave theory was used to determine analytical relations among sinusoidal perturbations of pressure and flow at the ends of a hydraulic-transmission line having a closed-end branch of arbitrary length attached at an arbitrary point. Experimental data were obtained for the equilateral case (a branch half as long as the main line connected to the main line at the midpoint) at mean flow speeds of 5 to 10 feet per second. Measured pressure-perturbation ratios agreed closely with analytical predictions. As frequencies for which the branch length was an odd multiple of 1/4 wavelength, waves in the main line were almost completely reflected at the junction point.
Similarity and Granger Causality in Polish and Spanish Stock Market Sectors During the COVID–19 Pandemic

Capital markets react almost immediately to crises. Such relationships can be both international and local. The research focuses on the stock markets of two countries: Spain and Poland. These countries are often compared in terms of various economic and social criteria. The research covers the period from March 3, 2019, to March 31, 2021. The aim is to identify sectors and indices similar to each other at the local level and to identify, among pairs of similar indices, those that provide a boost to another sector. The research uses the hierarchical cluster analysis method (Ward’s method) and the Granger causality test. This work presents a novel approach to sectoral comparison at the local level.
Demographic Changes in the Countries of the Western Balkans – A Comparative Analysis with the European Union

The study analyses the demographic changes in five countries of the Western Balkans – Albania, Bosnia and Herzegovina, Montenegro, North Macedonia, and Serbia – which are associated with and are potential candidates for European Union (EU) member states. Due to a lack of data, Kosovo was excluded. The research was based on selected measures, both static and dynamic. The analysis was conducted against the background of the indicators presented for the EU, with the longest time sample covering the years 1960–2020. The study presents the scope of demographic changes and the advancement of the population ageing of these countries using selected static measures and showing their dynamics. The methods used are based on data analysis and cluster analysis. The results point to the advancement of demographic changes and ageing in the region. The comparison of calculated measures indicates that the demographic structure in the region has shifted towards “old”, with the share of people aged 65 and over higher than 14% in 2020. The most advanced stages concern Bosnia and Herzegovina, where the transformation from a “young” demographic structure to an “old” was very dynamic and deep.
Knee Muscles Composition Using Electrical Impedance Myography and Magnetic Resonance Imaging

We evaluated the correlation of electrical impedance myography (EIM) measurements of knee muscles composition using Skulpt ChiselTM with MRI data retrieved from muscles segmentation. A total of 140 patients (71 females, 52 ± 21 years) underwent knee MRI, EIM with Skulpt®, and clinical evaluation (SARC-F questionnaire). MRIs were reviewed to assess the cross-sectional area (CSA) and skeletal muscle index (SMI = CSA/height2) of vastus medialis, vastus lateralis, biceps, semimembranosus, and sartorius. We tested the correlations of EIM-derived parameters [body fat-percentage (BF%) and muscle quality] with total CSA, CSA of each muscle, SMI, and SARC-F scores (0–10) using Pearson correlation coefficient. We found medium negative correlation of BF% with SMI (r = −0.430, p < 0.001) and total CSA (r = −0.445, p < 0.001), particularly with biceps (r = −0.479, p < 0.001), sartorius (r = −0.440, p < 0.001), and semimembranosus (r = −0.357, p < 0.001). EIM-derived muscle quality showed small-to-medium positive correlation with MRI measurements, ranging from r = 0.234 of biceps (p = 0.006) to r = 0.302 of total CSA (p < 0.001), except for vastus lateralis (r = 0.014, p = 0.873). SARC-F scores showed small correlations with EIM and MRI data, ranging from r = −0.132 (p = 0.121) with EIM muscle quality to r = −0.288 (p = 0.001) with CSA of vastus medialis. Hence, we observed small-to-medium correlations of muscle parameters derived from Skulpt ChiselTM with SARC-F scores and MRI parameters. We recommend using Skulpt ChiselTM with caution for assessing knee skeletal muscles composition.
Stabilizing region of fractional-order proportional integral derivative controllers for interval fractional-order plants

This paper focuses on computing the stabilizing region of fractional-order proportional integral derivative (FOPID) controllers for interval fractional-order plants. In this study, first, a theorem is presented to investigate the robust stability of the given closed-loop system. Then, an algorithm is proposed to solve the problem of robustly stabilizing the interval fractional-order plant using FOPID controllers. Also, two auxiliary functions are proposed to achieve the control requirements on the disturbance rejection and the noise reduction. Finally, four numerical examples are presented to confirm the obtained results.
Ordered exponential fields

Preliminaries on valued and ordered modules Non-archimedean exponential fields Valuation theoretic interpretation of the growth and Taylor axioms The exponential rank Construction of exponential fields Models for the elementary theory of the reals with restricted analytic functions and exponentiation Exponential Hardy fields The model theory of contraction groups Bibliography Index List of notation.
Teacher bias matters: an integrative review of correlates, mechanisms, and consequences

ABSTRACT This integrative review examined correlates, mechanisms, and consequences of teacher bias experienced in pre-kindergarten through twelfth grade in primary and secondary schools in the United States. Education Resource and Information Center, Sociological Abstracts, and Applied Social Science Index & Abstracts were searched to identify peer-reviewed articles published in English from 2000–2020. Thirty-one articles were included. The majority (65%) of studies were qualitative and explored teachers’ and students’ perceptions of teacher bias or differential student treatment. Teacher bias was associated with students’ race, ethnicity, immigration status, obesity, mental and physical disabilities. Behaviors associated with teacher bias included exclusionary discipline, microaggressions, name mispronunciations, and disproportionate gifted and special education referrals. Few studies quantitatively measured teacher bias suggesting methodological limitations in this body of evidence. Future research should employ objective measures of teacher bias. Research synthesis suggests teacher bias plays a significant role in teachers’ perceptions of and behaviors towards diverse students.
Jaynes-Cummings Model

This paper presents Jaynes-Cummings model, the simplest model that describes light-matter interaction. Light-matter interaction is an overlap between condensed matter physics and quantum optics. Thus, this model consists of atomic, electromagnetic field and interaction Hamiltonians. Besides, it describes briefly the experimental realization of light-matter interaction in the strong coupling regime.
Highly Reversible Lithium Host Materials for High‐Energy‐Density Anode‐Free Lithium Metal Batteries

Anode‐free Li metal batteries are one of the finest prospects for increasing energy density beyond that of standard lithium‐ion batteries. Conversely, the absence of Li reservoir generates unwarranted volume expansion, permitting electrolyte depletion and rapid cathode capacity consumption. To address this issue, an anode‐free Li metal battery with an ion‐conductive layer coated Cu current collector Ag/L in typical carbonate‐based electrolytes is presented. The ion‐conducting layer causes stable solid electrolyte interphase development and allows for minimal volume expansion when utilizing stable Li hosts. Via density functional theory calculation and experimental measurements and analysis, the beneficial effect of Li hosting behavior of the ion‐conductive layer is demonstrated. Furthermore, anode‐free electrochemical performance with high discharge capacity retention, which is exceptional in a traditional carbonate electrolyte with LiNi0.8Mn0. 1Co0.1O2 based cathode (4.2 mAh cm−2) and high current density (2.1 mA cm−2) is shown. To prove material compatibility, argyrodite sulfide solid electrolytes instead of liquid electrolytes, which show Coulombic efficiency of 97% at 50 cycles in all‐solid‐state Li half‐cells are used.
Cryptography using dark-bright soliton to generate keys by orthogonal dark-bright soliton pair

A method of optical cryptography by using soliton as dark-bright conversion control within a modified add/drop optical filter is proposed. In principle, the coincidence (orthogonal) dark-bright soliton pair has shown promising behaviors, especially when they propagate into the π2 phase shifter, i.e. beamsplitter, π2 phase shift between bright and dark solitons is occurred and separated. Such behaviors can be used to form the orthogonal light modes (solitons), which can be useful for application of cryptography, where in this case the long distance cryptography can be easily managed. In this work we have derived and presented a concept of multi-orthogonal solitons generated by using dark-bright soliton pulses within the modified add/drop optical filter, which is known as a PANDA ring resonator. A pair of optical keys is randomly generated and transmitted into the transmission line, where finally the corrected keys between Alice (sender) and Bob (receiver) can be retrieved. By using the dark-bright soliton conversion control, the obtained output of the dynamic states can be used to randomly form the multi-orthogonal soliton pairs, which can be available for computer and communication security applications, especially for long distance link.
Research on Segmentation Method of Greening Landscape of Urban Community Based on Improved U-Net Network

Aiming at the problem of low segmentation accuracy of greening landscape of urban community, a segmentation method of greening landscape of urban community based on improved U-Net network is proposed by adding an encoder on U-Net network. In addition, simulation is carried out on the remote sensing image data collected by GPRS network, and the effectiveness of the method is verified. The simulation results show that the result of proposed method is close to that of manual annotation. Compared with the traditional segmentation algorithm SVM and SegNet method, as well as the U-Net network before improvement, the proposed method has higher segmentation accuracy. The segmentation accuracy can reach up to 91%, the intersection ratio can reach 76%, and the mean pixel accuracy and mean intersection ratio can reach 89% and 74%, which indicates that the proposed method has certain validity and practicability.