Miracle-dz/UniFAR-FTUs huggingface dataset:
COVID-19 Infection Prediction Using Efficient Machine Learning Techniques Based on Clinical Data

COVID-19 (coronavirus disease) has spread worldwide and has become a pandemic, which causes by the SARS-CoV2 virus. Because the number of cases increases daily, interpreting the laboratory findings takes time, resulting in limitations of findings. Because of these limitations, the need for a clinical decision-making system with predictive algorithms has arisen. By identifying diseases, predictive algorithms would be able to reduce the strain on healthcare systems. In this work, we developed clinical predictive models using machine learning techniques with the help SMOTE+ENN Hybrid technique and laboratory data to develop models that can accurately predict which patients will receive COVID-19. To evaluate our prediction models in this work, precision, F1-score, recall AUC, and Accuracy evaluation metrics are employed. From 600 patients and 10 laboratory findings, the different models are tested and validated with 10-fold cross-validation and holdout cross-validation approaches. The experimental results show that our predictive models can correctly identify patients with COVID-19 with an accuracy of 98.28%, an F1-score of 98.27%, a precision of 98.23%, a recall of 98.32%, and an AUC of 98.32% in the holdout cross-validation approach, and an accuracy of 97.42%, and F1-score of 97.82%, a precision of 97.63%, a recall of 98.05%, and an AUC of 92.66% in 10-fold cross-validation approach. The results of the experiments showed that all machine learning models in the holdout cross-validation approach outperformed the 10-fold cross-validation approach. Finally, to help medical experts with accurately prioritizing resources, predictive models based on laboratory findings have been discovered that can assist in predicting COVID-19 infection and assisting medical professionals to identify which medical resources are most valuable. © 2022 J. Adv. Inf. Technol.
Application of the classical implicit function theorem in sensitivity analysis of parametric optimal control

A family {(Oh)} of parametric optimal control problems for uonlinear ODEs is considered. The problems arc subject. to pointwise ineq7J.ality type state constraints. It is assumed that the reference solution is regular. The original problems (Oh) arc substituted by problems (Oh) subject to equality type constraints with the sets of activity depending on the parameter. Usiug the classical implicit function theorem, conditions are derived uucler which stationary points of (Oh) arc Frcchet differentiable functions of the parameter. It is shown that , under additional conditions, the stationary points of (Oh) correspond to the solutions and Lagrange multipliers of (Oh)·
Tail equivalence of distribution functions belonging to the max domains of attraction of multivariate p-max stable laws

Reviews:A definition and characterization of the multivariate domain of attraction for maxima are given. The latter involves the notion of multivariate tail equivalence. The author seems to be unaware of the vast literature on multivariate regular variation as is for instance to be found in a book by N. H. Bingham, C. M. Goldie and J. L. Teugels [Regular variation, Cambridge Univ. Press, Cambridge, 1987; MR0898871 (88i:26004)] and E. Omey [Multivariate regular variation and applications in probability theory, Econom. Hogeschool Saint-Aloysius, Brussels, 1989; per revr. ]. For a textbook treatment of multivariate extremes, see a book by S. I. Resnick [Extreme values, regular variation, and point processes, Springer, New York, 1987; MR0900810 (89b:60241)].
Neutrino mixing with nonzero θ13 and CP violation in the 3-3-1 model based on S4 flavor symmetry

We propose a 3-3-1 model with neutral fermions based on A4 flavor symmetry responsible for fermion masses and mixings with nonzero θ13. To get realistic neutrino mixing, we just add a new SU(3)L triplet being in 3 under A4. The neutrinos get small masses from two SU(3)L antisextets and one SU(3)L triplet. The model can fit the present data on neutrino masses and mixing as well as the effective mass governing neutrinoless double beta decay. Our results show that the neutrino masses are naturally small and a little deviation from the tri-bimaximal neutrino mixing form can be realized. The Dirac CP violation phase δ is predicted to either 5.41∘ or 354.59∘ with θ23≠π 4.
Feasibility study of probing the high energy end of the primary cosmic electron spectrum by detecting geo-synchrotron X-rays

Based on tests of a tentative detector for observing geo-syn chrotron hard X-rays generated by primary electrons, we study the feasibility of probing cosmic electrons above a fe w T V to over 10 TeV. Such high energy electrons are expected to give proof of sources near the Earth (e.g. supern ova remnants such as Vela: age < 105 years located within <1kpc). The idea itself is rather old; a high energy electron e mits synchrotron X-rays successively in the geomagnetic field and thus gives several X-rays aligned on a m eter scale. This feature is a clue to overcome the background problem encountered in other traditional obser vation methods. We critically examine the feasibility of this approach assuming a satellite altitudes observation, and find that it is di fficult to derive a precise energy spectrum of electrons but is possible to get a clear signal of the exist nce of several TeV electrons if the flux is comparable to the level predicted by a class of plausible models. For such o bservations, an exposure > 1m2·year would be needed. It would be attractive to incorporate the present scheme in t he gamma-ray burst observations.
Impact of Heavy Metals and Chemicals on Epigenetic Changes

More than 13 million people die each year as a result of environmental contaminants, and it is estimated that up to 24% of diseases are brought on by avoidable environmental exposures. Different environmental chemicals were discovered in the blood and urine of the US population during a screening sponsored by the US Center for Disease Control and Prevention, revealing the level of human exposure to environmental chemicals. A growing body of research indicates that environmental toxins may affect gene expression in ways that affect the development of diseases. The first stages of gene transcription need dynamic chromatin remodeling, which is accomplished by changing how accessible gene promoters and regulatory regions are. These regulatory procedures involve epigenetic factors such as DNA methylation, histone changes, and microRNAs (miRNAs), which in turn regulate gene expression. Exposure to various environmental toxins has been found to create changes in these epigenetic markers, and some of them have been connected to a variety of diseases, along with their causes, treatments, and preventative measures.
Evaluation of antibacterial activity of black and green tea kombucha

Currently, the search for natural antimicrobial agents has increased. Thereat, plant extracts, products of fermentative processes, and microbial growth have been tested. Kombucha is a fermented beverage that resulted from the fermentation of the infusion of Camellia sinensis. There are reports about biological activities, such as anti-inflammatory, digestibility, antioxidant, antimicrobial, and others. The study aimed to evaluate the antibacterial activity of black and green tea kombucha against eight foodborne pathogenic microorganisms. The antibacterial activity was analyzed using the agar well diffusion method. Each kombucha consisted of three treatments: natural, neutralized, and filtered. The solutions of acetic acid (4% v.v-1) and kanamycin (30 µg.L-1) were used as a control. The black and green tea kombucha beverages, not neutralized, showed antibacterial activity against Escherichia coli serotypes. Black and green tea kombucha did not show antibacterial activity against Staphylococcus aureus, Shigella Flexneri, and Salmonella Typhimurium. The inhibition may be attributed to acetic acid production during the fermentation process. Therefore, it appears that kombucha may have a potential antimicrobial agent. Keywords: Camellia sinensis, fermentation, antimicrobial.
Gradual Elastic Suture (Shoelace Technique) Approximation and Platelet-Rich Plasma Infiltration Technique in the Closure of Open Fracture Wound and Infected Wound With Significant Skin Loss

Infected wounds can be really hard to manage in cases of open fractures, chronic osteomyelitis, and superficial infection. When the skin is damaged, bacteria can quickly enter the underlying tissue and cause a potentially fatal infection. Regular wound dressing with antimicrobial agents has become available in vials as a way to decrease the chance of bacterial colonization and infection and speed up the healing of wounds. In this report, we discuss the shoelace suture technique and platelet-rich plasma (PRP) infiltration in the wound. Due to its ability to stimulate and fasten the healing of wounds, PRP is becoming more and more popular. The progressive suture approximation (the shoelace technique) is an easy and effective technique for gently approximating the skin borders. The cytokines and growth factors in PRP play a critical role in the healing process. Hence, the combination of these two techniques will reduce the need for hospitalization, lead to better aesthetic outcomes, and reduce healthcare costs.
Point-of-Care Echocardiographic Characteristics of COVID-19 Patients with Pulmonary Embolism

Introduction: Thrombotic complications, such as pulmonary embolism, are common in COVID-19 patients. Point-of-care ultrasound is a highly recommended tool for orientation in critically ill patients with suspected or confirmed complications. Methods: An observational study was conducted on 32 consecutive patients with confirmed pulmonary embolism and COVID-19 infection treated in the Intensive Care Unit of the University Hospital Medical Center “Bežanijska kosa”, Belgrade, Serbia, between April 2021 and March 2022. Predictors of the need for oxygen support were determined, while point-of-care echocardiographic parameters and various anamnestic, laboratory, and clinically significant parameters were correlated with the Pulmonary Embolism Severity Index (PESI) score. Results: More than two-thirds of patients in our study had PE symptoms present at hospital admission (68.8%). The majority of patients had segmental pulmonary embolism (48.4%), with high to very high PESI score values in 31.3% of patients. Pneumonia was present in 68.8% of the study population. The PESI score was negatively correlated with diastolic blood pressure and SaO2 at the time of PE diagnosis, LV ejection fraction, and PVAT. A positive correlation was found between the PESI score, maximum CRP, and D-dimer at the time of PTE diagnosis. A larger right ventricular diameter was associated with a greater need for oxygen support. Conclusion: Point-of-care echocardiography is a valuable tool for the risk assessment of COVID-19 patients with pulmonary embolism. Right ventricular size stood out as a significant marker of disease severity.
One-Loop Maximally Supersymmetric Yang-Mills Scattering Amplitudes to All Orders in the Spacetime Dimension

OF THE DISSERTATION ONE-LOOP MAXIMALLY SUPERSYMMETRIC YANG-MILLS SCATTERING AMPLITUDES TO ALL ORDERS IN THE SPACETIME DIMENSION by ROBERT MORTON SCHABINGER Dissertation Director: Matthew J. Strassler In this thesis we discuss in detail computational methods and new results for one-loop virtual corrections to N = 4 super Yang-Mills scattering amplitudes calculated to all orders in , the dimensional regularization parameter. It is often the case that one-loop gauge theory computations are carried out toO( 0), since higher order in contributions vanish in the → 0 limit. We will show, however, that the higher order contributions are actually quite useful. In the context of maximally supersymmetric Yang-Mills, we consider two examples in detail to illustrate our point. First we will concentrate on computations with gluonic external states and argue thatN = 4 supersymmetry implies a simple relation between all-orders-inone-loop N = 4 super Yang-Mills amplitudes and the first and second stringy corrections to analogous tree-level N = 4 amplitudes. For our second example we will derive a new result for the all-orders-inone-loop superamplitude for planar six-particle NMHV scattering, an object which allows one to easily obtain six-point NMHV amplitudes with arbitrary external states. To make the presentation as self-contained as possible, we extensively review the prerequisites necessary to understand the main results of this thesis.
The Toll-like Receptor 4 Polymorphism Asp299Gly Is Associated with an Increased Risk of Ovarian Cancer

Ovarian cancer (OC) is one of the most common cancers threatening women’s lives around the world. Epithelial ovarian tumors represent the most common ovarian neoplasms. Most OC patients are diagnosed at the advanced stage, and there is an urgent need to identify novel biomarkers of the disease. Single-nucleotide polymorphisms (SNPs) in TLR genes may serve as crucial markers of cancer susceptibility. We investigated the frequency of TLR polymorphisms in a group of 200 women, including 70 with OC. Four SNPs, two each in TLR4 (rs4986790 and rs4986791) and TLR9 (rs187084 and rs5743836), were analyzed using polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP). The digested fragments were separated and identified by multicapillary electrophoresis. The load quantification of human papillomavirus (HPV) types 16/18 was determined using a digital droplet PCR method. We found an increased frequency of heterozygous genotype and minor allele of the TLR4 rs4986790 SNP in women with OC compared with healthy controls, and this result remained highly significant after Bonferroni’s correction for multiple testing (p < 0.0001). No evidence of linkage disequilibrium was found with any of the examined TLR SNPs. The findings suggest that the TLR4 Asp299Gly polymorphism could be a genetic risk factor for the development of OC.
A Novel Bayesian Framework Infers Driver Activation States and Reveals Pathway-Oriented Molecular Subtypes in Head and Neck Cancer

Simple Summary Numerous factors, such as genomic mutations, chromosomal changes, transcriptional controls, phosphorylation, and protein–protein interactions, among others, can affect the activation status of proteins. Although each data type only partially reveals the status of a particular gene’s disruption, downstream expression changes ultimately indicate the functional effects of cancer driver protein alterations. By combining data on transcriptome and genomic alterations, we have developed a Bayesian framework to infer driver activation state, and further tested our method to highlight both statistical and biological significance by applying our model to TCGA HNSCC patient data. Abstract Head and neck squamous cell cancer (HNSCC) is an aggressive cancer resulting from heterogeneous causes. To reveal the underlying drivers and signaling mechanisms of different HNSCC tumors, we developed a novel Bayesian framework to identify drivers of individual tumors and infer the states of driver proteins in cellular signaling system in HNSCC tumors. First, we systematically identify causal relationships between somatic genome alterations (SGAs) and differentially expressed genes (DEGs) for each TCGA HNSCC tumor using the tumor-specific causal inference (TCI) model. Then, we generalize the most statistically significant driver SGAs and their regulated DEGs in TCGA HNSCC cohort. Finally, we develop machine learning models that combine genomic and transcriptomic data to infer the protein functional activation states of driver SGAs in tumors, which enable us to represent a tumor in the space of cellular signaling systems. We discovered four mechanism-oriented subtypes of HNSCC, which show distinguished patterns of activation state of HNSCC driver proteins, and importantly, this subtyping is orthogonal to previously reported transcriptomic-based molecular subtyping of HNSCC. Further, our analysis revealed driver proteins that are likely involved in oncogenic processes induced by HPV infection, even though they are not perturbed by genomic alterations in HPV+ tumors.
Comprehensive Review of UAV Detection, Security, and Communication Advancements to Prevent Threats

It has been observed that unmanned aerial vehicles (UAVs), also known as drones, have been used in a very different way over time. The advancements in key UAV areas include detection (including radio frequency and radar), classification (including micro, mini, close range, short range, medium range, medium-range endurance, low-altitude deep penetration, low-altitude long endurance, and medium-altitude long endurance), tracking (including lateral tracking, vertical tracking, moving aerial pan with moving target, and moving aerial tilt with moving target), and so forth. Even with all of these improvements and advantages, security and privacy can still be ensured by researching a number of key aspects of an unmanned aerial vehicle, such as through the jamming of the control signals of a UAV and redirecting them for any high-assault activity. This review article will examine the privacy issues related to drone standards and regulations. The manuscript will also provide a comprehensive answer to these limitations. In addition to updated information on current legislation and the many classes that can be used to establish communication between a ground control room and an unmanned aerial vehicle, this article provides a basic overview of unmanned aerial vehicles. After reading this review, readers will understand the shortcomings, the most recent advancements, and the strategies for addressing security issues, assaults, and limitations. The open research areas described in this manuscript can be utilized to create novel methods for strengthening the security and privacy of an unmanned aerial vehicle.
Grape seed extract promotes Staphyloccous aureus infected skin wound Healing in diabetic rat model

Background: Open wounds leave the wound bed at risk for colonization by opportunistic pathogens. Therefore, the understanding and control of the microbial infections are of great importance for the enhanced healing and management of wounds. Reducing the wound healing time is important as it lowers the risk of infection and decreases possible complications. Grape seed extract is rich in powerful antioxidant compounds. Accordingly, grape seed extract (GSE) alone or in combination with chemical agents might be of beneficial value in wound healing. Objective: The present study aimed to evaluate the topical application of grape seed extract on wound healing of induced Staphylococcus aureus infected skin wound in diabetic rats. Methodology: Ninety male Sprague-Dawley rats weighing 150–200 grams were divided into five groups. All groups were anesthetized, shaved, and exposed to round full-thickness punch biopsy on the back: group I (control); group II (wounded); group III (wounded Staphylococcus aureus infected); group IV (wounded STZ diabetic) and group V (wounded STZ diabetic infected with Staphylococcus aureus). These last four groups were subdivided into Vaseline base treated or GSE- Vaseline treated groups. Macroscopic examination were observed at 0, 1, 3, 6, 8, 12 and 16 days after skin biopsy. Wound contraction data were expressed as a percentage of the initial wound area. Skin homogenates were prepared for determining the immunological parameters TNF-α, IL-10 TGF-β1. Results: Grape seed extract topical application improved the skin homogenate contents of TGF- β1, IL-10 and TNF-α denoting the immunological effect of GSE on wound healing in different experimental groups. Skin histopathological examination was in agreement with the immunological results. Conclusion: Grape seed extract topical application promoted skin wound contraction and closure. Furthermore, it possesses antioxidant and antibacterial properties. Grape seed extract has also strong immunoregulating properties of the skin immune system in Staphylococcus aureus infected diabetic wounded rats.
"Counterpart" method for abundance determinations in HII regions

We suggest a new way of the determining abundances and electron temperatures in HII regions from strong emission lines. Our approach is based on the standard assumption that HII regions with similar intensities of strong emission lines have similar physical properties and abundances. A "counterpart" for a studied HII region may be chosen among HII regions with well-measured abundances (reference HII regions) by comparison of carefully chosen combinations of strong line intensities. Then the abundances in the investigated HII region can be assumed to be the same as that in its counterpart. In other words, we suggest to determine the abundances in HII regions "by precedent". To get more reliable abundances for the considered HII region, a number of reference HII regions is selected and then the abundances in the target HII region is estimated through extra-/interpolation. We will refer to this method of abundance determination as the counterpart method or, for brevity, the C method. We define a sample of reference HII regions and verify the validity of the C method. We find that this method produces reliable abundances. Finally, the C method is used to obtain the radial abundance distributions in the extended discs of the spiral galaxies M83, NGC4625 and NGC 628.
Managerial Practices for the Digital Transformation of Manufacturers

The digital transformation is a complex and multi-faceted phenomenon, which companies hamper to manage effectively. One particular facet of this phenomenon is the role of managers, which is still underrepresented in research. This study aims to identify and explain why and what managerial practices and competencies are particularly needed to effectively govern through this transformation. We choose the case study methodology as the research design with eight manufacturing companies in Western Europe, where we applied within- and cross-case analyses. Specific barriers for digital transformation and four aggregated managerial practices, such as strategy/organization, collaboration, cross-functionality and data-driven use cases, were identified. These were supported by 13 competencies to facilitate digitalization. We explicate these practices based on the change management theory and provide a model describing the impact of these practices on profitability. This study contributes to the emergent change theory by analyzing practices and competencies that managers should be equipped with to foster digitalization.
INITIAL FRAGMENTATION IN THE INFRARED DARK CLOUD G28.53−0.25

To study the fragmentation and gravitational collapse of dense cores in infrared dark clouds (IRDCs), we have obtained submillimeter continuum and spectral line data as well as multiple inversion transitions of NH3 and H2O maser data of four massive clumps in IRDC G28.53−0.25. Combining single-dish and interferometer NH3 data, we derive a rotation temperature of G28.53. We identity 12 dense cores at a 0.1 pc scale based on submillimeter continuum, and obtain their physical properties using NH3 and continuum data. By comparing the Jeans masses of cores with the core masses, we find that turbulent pressure is important for supporting the gas when 1 pc scale clumps fragment into 0.1 pc scale cores. All cores have a virial parameter that is smaller than 1 if we assume an inverse squared radial density profile, suggesting they are gravitationally bound, and the three most promising star-forming cores have a virial parameter that is smaller than 1 even when taking the magnetic field into account. We also associate the cores with star formation activities revealed by outflows, masers, or infrared sources. Unlike what previous studies have suggested, MM1 turns out to harbor a few star-forming cores and is likely a progenitor of a high-mass star cluster. MM5 is intermediate while MM7/8 are quiescent in terms of star formation, but they also harbor gravitationally bound dense cores and have the potential for forming stars, as in MM1.