Miracle-dz/UniFAR-FTUs huggingface dataset:
Uncovering common pathobiological processes between COVID‐19 and pulmonary arterial hypertension by integrating Omics data

Abstract Coronavirus disease 2019 (COVID‐19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), which led to the current pandemic. Many factors, including age and comorbidities, influence the severity and mortality of COVID‐19. SARS‐CoV‐2 infection can cause pulmonary vascular dysfunction. The COVID‐19 case‐fatality rate in patients with pulmonary arterial hypertension (PAH) is higher in comparison with the general population. In this study, we aimed to identify pathobiological processes common to COVID‐19 and PAH by utilizing the human protein–protein interactome and whole‐genome transcription data from peripheral blood mononuclear cells (PBMCs) and from lung tissue. We found that there are significantly more interactions between SARS‐CoV‐2 targets and PAH disease proteins than expected by chance, suggesting that the PAH disease module is in the neighborhood of SARS‐CoV‐2 targets in the human interactome. In addition, SARS‐CoV‐2 infection‐induced changes in gene expression significantly overlap with PAH‐induced gene expression changes in both tissues, indicating SARS‐CoV‐2 and PAH may share common transcriptional regulators. We identified many upregulated genes and downregulated genes common to COVID‐19 and PAH. Interestingly, we observed different co‐regulation patterns and dysfunctional signaling pathways in PBMCs versus lung tissue. Endophenotype enrichment analysis revealed that genes regulating fibrosis, inflammation, hypoxia, oxidative stress, immune response, and thromboembolism are significantly enriched in the COVID‐19‐PAH co‐expression modules. We examined the network proximity of the targets of repositioned drugs for COVID‐19 to the co‐expression modules in PBMCs and lung tissue, and identified 42 drugs that can be potentially used for COVID‐19 patients with PAH as a comorbidity. The uncovered common pathobiological pathways are crucial for discovering therapeutic targets and designing tailored treatments for COVID‐19 patients who also have PAH.
Diffusion of electromagnetic fields into a two-dimensional earth; a finite-difference approach

We describe a numerical method for time‐stepping Maxwell’s equations in the two‐dimensional (2-D) TE‐mode, which in a conductive earth reduces to the diffusion equation. The method is based on the classical DuFort‐Frankel finite‐difference scheme, which is both explicit and stable for any size of the time step. With this method, small time steps can be used at early times to track the rapid variations of the field, and large steps can be used at late times, when the field becomes smooth and its rates of diffusion and decay slow down. The boundary condition at the earth‐air interface is handled explicitly by calculating the field in the air from its values at the earth’s surface with an upward continuation based on Laplace’s equation. Boundary conditions in the earth are imposed by using a large, graded grid and setting the values at the sides and bottom to those for a haft‐space. We use the 2-D model to simulate transient electromagnetic (TE) surveys over a thin vertical conductor embedded in a half‐space.
Evaluation of Patient Satisfaction With the New Web-Based Medical Appointment Systems “Mawid” at Primary Health Care Level in Southwest Saudi Arabia: A Cross-Sectional Study

Background Patient satisfaction has become an influential corner in the health services process. Web-based appointment scheduling has been expanded for its benefits and has become a popular research topic. This study’s objectives were to assess patients’ satisfaction and perception with the new Web-Based Medical Appointment System “Mawid” program and determine the associated factors at the Primary Health Care Centers level in Jazan Southwest Saudi Arabia. Methods An observational cross-sectional survey was implemented among 424 adults aged 18 years and above, attending a randomly selected 12 primary health care centers in the Jizan region, Southwest Saudi Arabia. The study instrument included socio-demographic background information, perception, and level of satisfaction with the new appointment system. Responses were analyzed using the SPSS program by applying descriptive and inferential statistical techniques. Results The overall level of satisfaction was very high at 94.3% with 95% C.I. (91.7-96.1). A large proportion of study participants were highly satisfied with the new Web-Based Medical appointment System “Mawid” as nine satisfaction items scored a level of satisfaction of 90% and above. Regarding the perception, 89.1% of the participants agreed that the appointment booking system regulates the number of patients, while 87.7% of participants considered that the appointment system reduces clinic crowding. More than half of respondents (61.8%) agreed that the community culture might limit the scheduling system’s use. Univariate and multivariate logistic regression analysis suggested that male patients were more likely to have a higher level of satisfaction as compared with female (COR= 2.95, 95% C.I.:1.15-7.60, p = 0.025) and (AOR= 3.12, 95% C.I:1.14-8.52, p = 0.026), respectively. Conclusions In conclusion, this study revealed a high level of satisfaction among study the participants with the new Web-Based Medical Appointment System “Mawid. ” The system effectively improved patients’ satisfaction with registration and reduced waiting times. Patients' satisfaction can be assessed regularly and used systematically as a quality and benchmarking instrument in primary health care.
Studying the Role of Potato Powder on the Physicochemical Properties and Dough Characteristics of Wheat Flour

Potato flour (PF) is rich in health-promoting compounds that can improve the nutritional benefits of food products after blending with wheat flour. However, the incorporation of PF may influence the processing characteristics of mixed powders and the quality properties of products. In this study, the physicochemical properties, processing characteristics, and structures of mixed powders and their corresponding doughs with different PF content (0%, 10%, 20%, 30%, 40%, 60%, 80%, and 100%) were investigated. The addition of PF dramatically increased the fiber content from 0.09 to 1.10 g·kg−1 but diluted the protein in wheat flour. The peak and final viscosity of mixed powders decreased (from 5111.00 to 1806.33 cP and 5195.33 to 2135.33 cP, respectively) with an increase in PF fraction. The incorporation of PF significantly increased gelatinization temperature. The rapidly digestible starch decreased from 30.48% to 19.67%, and resistant starch increased from 16.93% to 41.84% when the PF content increased from 0% to 100%. The water absorption, stability time, and development time decreased with an increase in PF levels. The G′ and G″ of the dough decreased as the addition amount of PF increased, while tan δ presented a complex change tendency. Due to the decrease in protein content in the mixed powders, the addition of PF in wheat flour notably decreased the Hm values of doughs and total carbon dioxide volume produced during fermentation. Additionally, the SH and S–S contents decreased with an increase in PF fraction. Scanning electron microscopy results showed that when the PF content reached up to 80%, a poor and discontinuous gluten framework was formed in the dough. Results showed that PF affected the processing characteristics and gluten structures of wheat dough and was related to the interaction or competition for water molecules between protein and starch, as well as potato starch and wheat starch. Thus, the results of the present study can provide insights into the optimal level of addition of PF during the development of potato-based food products.
Fast Training Data Generation for Machine Learning Analysis of Cosmic Ray Showers

Applying Machine Learning (ML) methods for the analysis of muon lateral distributions in Extensive Air Showers detected by citizen science projects, while taking into account the spatial distribution of detectors requires enormous training data sets. Therefore, generating these data sets with typical Monte Carlo (MC) generators like CORSIKA is computationally prohibitive. Here we present a method which by the application of special augmentation procedures produces the training dataset that is compatible in all essential aspects to the data produced with regular MC computations while avoiding their time overhead. We utilize the Nakamura-Kamata-Greisen (NKG) distribution which was proven to be an attractive alternative to full-fledged simulations. The simulation of <inline-formula> <tex-math notation="LaTeX">$10^{4}$ </tex-math></inline-formula> muons at the ground level takes just a few seconds using our implementation of the NKG approach. For <inline-formula> <tex-math notation="LaTeX">$10^{6}$ </tex-math></inline-formula> muons this figure is still around 1 minute. For comparison, CORSIKA based simulation performed on Prometheus supercomputer at CYFRONET computing center an ensemble of <inline-formula> <tex-math notation="LaTeX">$\sim 100$ </tex-math></inline-formula> showers initiated by a particle of <inline-formula> <tex-math notation="LaTeX">$10^{16} eV$ </tex-math></inline-formula> resulted in <inline-formula> <tex-math notation="LaTeX">$\sim 10^{4}$ </tex-math></inline-formula> muons and <inline-formula> <tex-math notation="LaTeX">$\sim 10^{5}$ </tex-math></inline-formula> electrons required computation time of the order of a few days.
Tracking Control for Output Probability Density Function of Stochastic Systems Using FPD Method

Output probability density function (PDF) tracking control of stochastic systems has always been a challenging problem in both theoretical development and engineering practice. Focused on this challenge, this work proposes a novel stochastic control framework so that the output PDF can track a given time-varying PDF. Firstly, the output PDF is characterised by the weight dynamics following the B-spline model approximation. As a result, the PDF tracking problem is transferred to a state tracking problem for weight dynamics. In addition, the model error of the weight dynamics is described by the multiplicative noises to more effectively establish its stochastic dynamics. Moreover, to better reflect the practical applications in the real world, the given tracking target is set to be time-varying rather than static. Thus, an extended fully probabilistic design (FPD) is developed based on the conventional FPD to handle multiplicative noises and to track the time-varying references in a superior way. Finally, the proposed control framework is verified by a numerical example, and a comparison simulation with the linear–quadratic regulator (LQR) method is also included to illustrate the superiority of our proposed framework.
Long-lag identity priming in the absence of long-lag morphological priming: evidence from Mandarin tone alternation

The present study tested whether listeners hearing one form of a morpheme activate other forms of the same morpheme. Listeners performed lexical decisions while hearing Mandarin monosyllables; crucially, critical targets could be primed by related syllables that occurred 18–52 trials earlier (long-lag priming). The use of long-lag priming ensures that any facilitation effects are due to morphological relatedness and not to semantic or form relationships, which do not prime lexical decisions at long lags. Across three experiments (total N = 458), we consistently found that lexical decisions were primed when the same pronunciation of a morpheme occurred as prime and target (e.g., shiL – shiL) but were not primed when two different variants of the same morpheme occurred as prime and target (e.g., shiR – shiL, where both of these syllables are potential pronunciations of the same morpheme). In other words, we observed identity priming but not morphological priming, unlike other long-lag priming experiments, which almost invariably observe intramodal morphological priming if they test it. This surprising finding suggests that there are boundary conditions on the elicitation of long-lag morphological priming effects.
Experiments on gravity currents propagating down slopes. Part 1. The release of a fixed volume of heavy fluid from an enclosed lock into an open channel

Gravity currents formed by the release of heavy fluid from an enclosed lock on a sloping open channel were investigated experimentally. The experiments were conducted in a channel that had a running length of 13 lock depths, and could be inclined to a maximum angle of 17°. The release of heavy dyed salt solution from a lock with an aspect ratio (height to length) of 0.5, was examined using video images to determine the front velocity, and a particle-tracking technique was used to measure the two-dimensional velocity field in a vertical slice through the centre of the evolving current. The gravity current head velocity increased with time and downstream distance to a maximum at approximately 10 lock depths from the front of the lock. Flow visualization and the velocity measurements have shown that during the acceleration phase the head was being fed by a following current that increased its buoyancy as it propagated downstream. A modified version of the theory of P. Beghin, E. J. Hopfinger and R. E. Britter (J. Fluid Mech. vol. 107, 1981, p. 407) in which the measured increase in buoyancy was used, instead of the original assumption of constant buoyancy, gave results that agreed closely with the experimental velocity versus time histories.
Machine learning with neuroimaging biomarkers: Application in the diagnosis and prediction of drug addiction

Drug abuse is a serious problem worldwide. Owing to intermittent intake of certain substances and the early inconspicuous clinical symptoms, this brings huge challenges for timely diagnosing addiction status and preventing substance use disorders (SUDs). As a non‐invasive technique, neuroimaging can capture neurobiological signatures of abnormality in multiple brain regions caused by drug consumption in each clinical stage, like parenchymal morphology alteration as well as aberrant functional activity and connectivity of cerebral areas, making it realizable to diagnosis, prediction and even preemptive therapy of addiction. Machine learning (ML) algorithms primarily used for classification have been extensively applied in analysing medical imaging datasets. Significant neurobiological characteristics employed and revealed by classifiers were used to diagnose addictive states and predict initiation and vulnerability to drug usage, treatment abstinence, relapse and resilience of addicts and the risk of SUD. In this review, we summarize application of ML methods in neuroimaging focusing on addicts' diagnosis of clinical status and risk prediction and elucidate the discriminative neurobiological features from brain electrophysiological, morphological and functional perspectives that contribute most to the classifier, finally highlighting the auxiliary role of ML in addiction treatment.
Flow Passage Arrangement and Surface Selection in Multistream Plate-Fin Heat Exchangers

This paper presents a general design methodology for multistream plate-fin heat exchangers that incorporates the consideration of operability aspects through the manipulation of stream flow passage arrangement. The main features of the design approach are uniform heat load per passage and secondary surface or fin selection. Surface selection is implemented as a means to achieve uniformity in the heat transfer rate of the various streams that take part in the heat exchange process. Uniform heat load content per passage is a design consideration through which an equal number of hot and cold passages is achieved. Under these conditions, the number of passages allocated to a given stream is directly proportional to its heat capacity mass flow rate. A simple model for the steady-state simulation of multistream exchangers is also presented. This model can be used to determine the exchanger response to changes in temperature and flow rate that may take place during operation. Results indicate that flow passage arrangement is a design consideration that can be manipulated to reduce the effect of these types of disturbances upon the target temperatures of specific streams.
Finite Amplitude Free Convection as an Initial Value Problem—I

Abstract The Oberbeck-Boussinesq equations are reduced to a two-dimensional form governing “roll” convection between two free surfaces maintained at a constant temperature difference. These equations are then transformed to a set of ordinary differential equations governing the time variations of the double-Fourier coefficients for the motion and temperature fields. Non-linear transfer processes are retained and appear as quadratic interactions between the Fourier coefficients. Energy and heat transfer relations appropriate to this Fourier resolution, and a numerical method for solution from arbitrary initial conditions are given. As examples of the method, numerical solutions for a highly truncated Fourier representation are presented. These solutions, which are for a fixed Prandtl number and variable Rayleigh numbers, show the transient growth of convection from small perturbations, and in all cases studied approach steady states. The steady states obtained agree favorably with steady-state solutions ob.
L-R smash products for bimodule algebras

Abstract In this paper, we prove that the L-R smash product A ♮ H is exactly the twisted smash product A * H if H is a finite dimensional cocommutative Hopf algebra, and give a sufficient and necessary condition for L-R smash products to be bialgebras (Hopf algebras). For any finite dimensional coquasitriangular Hopf algebra (H, σ), we prove that the L-R smash product H ♮ H is semisimple Artinian if H is semisimple and H* is unimodular. In particular, the L-R smash product D(H)* ♮D(H) * semisimple Artinian if the Drinfel’d double D(H) is semisimple. * Supported by National Natural Science Foundation of China (Grant No. 10571153), the Postdoctoral Science Foundation of China (Grant No. 2005037713), and the Postdoctoral Science Foundation of Jiangsu (Grant No. 0203003403)
Efficient Laplace Inversion, Wiener-Hopf Factorization and Pricing Lookbacks

We construct fast and accurate methods for (a) approximate Laplace inversion, (b) approximate calculation of the Wiener-Hopf factors for wide classes of Levy processes with exponentially decaying Levy densities, and (c) approximate pricing of lookback options. In all cases, we use appropriate conformal change-of-variable techniques, which allow us to apply the simplified trapezoid rule with a small number of terms (the changes of variables in the outer and inner integrals and in the formulas for the Wiener-Hopf factors must be compatible in a certain sense). The efficiency of the method stems from the properties of functions analytic in a strip (these properties were explicitly used in finance by Feng and Linetsky 2008). The same technique is applicable to the calculation of the pdfs of supremum and infimum processes, and to the calculation of the prices and sensitivities of options with lookback and barrier features.
Thin and Subvisual Tropopause Tropical Cirrus: Observations and Radiative Impacts

Abstract In situ microphysical, remote sensing, and satellite observations of thin and subvisible cirrus have been used to establish their frequency of occurrence, determine their mean optical depths and radiative forcings, and to analyze their association with deep convection. A spatially thin layer of cirrus, with both base and top above 15 km, was observed in the central Pacific Tropics 29% of the time, with a mean thickness of 0.47 km, using a nadir-pointing Nd:YAG lidar operating at 1.064 μm during the Central Equatorial Pacific Experiment (CEPEX). In situ microphysical data collected in the mid-1970s and mid-1980s by a WB-57 and Learjet near Kwajalein, Marshall Islands, are revisited to determine typical ice crystal sizes and shapes that occur in this cloud type. Three observed vertical profiles, obtained from ascents/descents through cloud, are used with a δ-four-stream radiative transfer model to calculate observed heating rates of up to 1.0 K day−1, principally in the infrared, and cloud radiativ.
A Hybrid Method Based on Differential Evolution and Continuous Ant Colony Optimization and its Application on Wideband Antenna Design

An evolutionary learning algorithm based on difierential evolution strategy (DES) and continuous ant colony optimization (CACO) for wideband antenna design is proposed. The advantages of this hybrid method are demonstrated with several mathematical functions and a linear array pattern synthesis. This method is applied to design an E-shaped wideband patch antenna, which achieves the impedance bandwidth 4:8 » 6:53GHz. We compare the hybrid method with the traditional DES and CACO optimization algorithms, and the advantage of this hybrid method over the DES and the CACO is also demonstrated.
Estimation of Linear Models with Incomplete Data

In estimating linear models, it is often necessary to combine data from two or more samples or subsamples, each with a somewhat different set of variables. Conventional methods for doing this are statistically inefficient or have unknown statistical properties. This paper describes a maximum likelihood method that is both consistent and efficient and that can be implemented with LISREL. Unlike other maximum likelihood algorithms, this method can estimate overidentified models, and it produces consistent estimates of standard errors. Using this approach, one can
The Superiorities of Bayes Linear Minimum Risk Estimation in Linear Model

In this article, the Bayes linear minimum risk estimator (BLMRE) of parameters is derived in linear model. The superiorities of the BLMRE over ordinary least square estimator (LSE) is studied in terms of the mean square error matrix (MSEM) criterion and Pitman closeness (PC) criterion.
Supersoluble groups of automorphisms of compact Riemann surfaces

Given an integer g ≥ 2 and a class of finite groups let N(g, ) denote the order of the largest group in that a compact Riemann surface of genus g admits as a group of automorphisms. For the classes of all finite groups, cyclic groups, abelian groups, nilpotent groups, p-groups (given p), soluble groups and finally for metabelian groups, an upper bound for N(g, ) as well as infinite sequences for g for which this bound is attained were found in [5, 6, 7, 8, 13], [4], [10], [15], [16], [1], [2] respectively. This paper deals with that problem for the class of finite supersoluble groups i.e. groups with an invariant series all of whose factors are cyclic. In addition, it goes further by describing exactly those values of g for which the bound is attained. More precisely we prove:
An algebraic model for nonisotropic turbulent dissipation rate in Reynolds stress closures

A method to account for effects of an anisotropic dissipation rate in second‐order moment closures of turbulent flows is presented. The modeled transport equations for the Reynolds stresses and the scalar dissipation rate are supplemented by nonlinear algebraic relations, in which the anisotropies of the dissipation rate tensor are expressed in the anisotropies of the Reynolds stress tensor. Symmetry and other constraints reduce the number of undetermined coefficients to one. It is shown that the model correctly describes the initial behavior of a suddenly distorted turbulence provided that the model parameter assumes a value of (3)/(4) . The model is compared with full numerical simulations of three basic types of strained homogeneous turbulence, and is shown to give good agreement with these data. The present approach of isolating the effects of anisotropic dissipation rate in second‐order moment closures is a step toward improved modeling of the energy redistribution terms in the Reynolds stress transp.