Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating Levels of Community Participation in a University-Community Partnership: The Jackson Heart Study

Objective: This research was designed to evaluate the perceptions of the Jackson Heart Study (JHS) community relating to their levels of involvement in JHS activities that were developed to address health disparities and promote health education and health promotion. Methods: The participants for this study comprised 128 community members, who included JHS participants, as well as family members and other friends of the JHS who resided in the JHS community of Hinds, Madison, and Rankin Counties in Mississippi and attended the JHS Annual Celebration of Life. We used the Chi-Square test to analyze the participants’ responses to the survey questions developed to address the six areas of focus: (1) ways to increase participation in community outreach activities; (2) reasons for participating in community outreach activities; (3) interest in research participation; (4) factors influencing engagement; (5) Participants’ preferences for communicating; (6) Chronic disease prevalence. Results: Participants residing in rural counties perceived television and radio as a medium to increase participation; More female respondents cited trust working with the JSU JHS Community Outreach Center (CORC) as a reason for remaining engaged in the community outreach activities; younger participants under 66 years of age recommended social media as a way to increase participation; participants residing in the rural areas saw their participation in the community outreach activities as a way to address community health problems. Conclusions: The knowledge gained from the details provided by the JHS community members can be used to refine research studies in existence, while promoting their sustainability.
A two-step parameter extraction methodology for graphene field-effect transistors

Accurate device models and parameter extraction methods are of utmost importance for characterizing graphene field-effect transistors and for predicting their performance in circuit applications. For DC characterization, accurate extraction of the transconductance parameter (i.e., low-field mobility) and series resistance is of particular importance. In this paper, methods for extraction of these parameters will be discussed.A first-order mobility degradation model that can be used to separate information about mobility degradation and series resistance for a set of graphene field-effect transistors will also be discussed.
Bubble-wall Casimir interaction in fermionic environments

We consider the Casimir interaction, mediated by massless fermions, between a spherical defect and a flat potential barrier, assuming hard (bag-type) boundary conditions at both the barrier and the surface of the sphere. The computation of the quantum interaction energy is carried out using the multiple scattering approach, adapted here to the setup in question. We find an exact integral formula for the energy, from which we extract both the large and short distance asymptotic behaviour. At large distance the fermionic contribution is found to scale as $L^{-3}$, in contrast to that of electromagnetic vacuum fluctuations that, assuming perfectly conducting boundaries, scales as $L^{-4}$. At short distance, we compute the leading and sub-leading contribution to the vacuum energy. The leading one coincides with what it is expected from the proximity force approximation, while the sub-leading term gives, contrary to the electromagnetic case, a positive correction to the proximity force result.
Impact of Artificial Intelligence on Information Security in Business

Cyber security is a critical problem that causes data breaches, identity theft, and harm to millions of people and businesses. As technology evolves, new security threats emerge as a result of a dearth of cyber security specialists equipped with up-to-date information. It is hard for security firms to prevent cyber-attacks without the cooperation of senior professionals. However, by depending on artificial intelligence to combat cyber-attacks, the strain on specialists can be lessened. as the use of Artificial Intelligence (AI) can improve Machine Learning (ML) approaches that can mine data to detect the sources of cyberattacks or perhaps prevent them as an AI method, it enables and facilitates malware detection by utilizing data from prior cyber-attacks in a variety of methods, including behavior analysis, risk assessment, bot blocking, endpoint protection, and security task automation. However, deploying AI may present new threats, therefore cyber security experts must establish a balance between risk and benefit. While AI models can aid cybersecurity experts in making decisions and forming conclusions, they will never be able to make all cybersecurity decisions and judgments.
Environmental Uncertainty: Typology Of Strategy And Strategic Management Accounting Techniques On Company Performance

Uncertain environmental conditions and typology of corporate strategy are the determining factors in improving company performance. This study aims to prove the analysis results of the typology of strategic management accounting techniques on company performance and test the role of environmental uncertainty in moderating the typology of strategies on company performance. This research is quantitative research with data collection using a survey method. The sample in this study was 237 managers of manufacturing companies listed on the Indonesia Stock Exchange (IDX). Sampling using the type of probability sampling. Data analysis in this study used the PLS-SEM (partial least square modeling) analysis method through the SmartPLS 3.0 program. There are three findings in this study, namely. First, the typology of strategy has a significant effect on company performance. Second, strategic management accounting techniques have a substantial impact on company performance. Third, environmental uncertainty has strengthened the influence of strategy typology on company performance. This study also analyzes the results of the 'Fit' contingency test for the prospector, defender, and analyzer strategy typology variables on company performance through crosstab analysis using the SPSS.25 program. Based on the results of the contingency fittest, it has been proven that when conditions of environmental uncertainty are high in a competitive environment, companies can use a strategy typology with a prospector strategy rather than a company with a defender or analyzer strategy. The fittest prospector strategy typology is more appropriate for companies to improve performance.
GARCH-M MODEL AND THE BEHAVIOR OF RISK-RETURN RELATIONSHIP IN INDONESIA STOCK MARKET

This study examines the risk-return trade-off and volatility behaviour in Indonesia stock market. As the analytical tool this study uses GARCH-M model with symmetric GARCH(1,1). To obtain more reliable results, this study takes daily and weekly stock index as well as 5 individual stock returns from January 2004 to November 2020 as a sample. This study also investigates the results with two alternative mean equations, simple regression and AR(1) model. The first finding of this study is that in Indonesia stock market both in stock index and in individual stocks, the volatilities of return are time varying. From investigating the risk-return relationship the results are mixed. This study finds that positive risk-return relationships in stock market index are observed both in daily and weekly data. A positive risk-return relationhip in stock market index is also found either in AR(1) model of mean equation or in simple regression model. The same results are observed in two stocks investigated. There is one stock where a positive risk return relationship is observed only in daily return data not in weekly return data. A negative risk-return relationships is observed in one stock and there is no evidence of risk-return trade-off in one stock. The conclusion is that a positive risk-return relationship as a postulated by investment theory only exists in stock index and does not exist in all stocks Key words : Indonesia stock market, Risk-return trade-off, GARCH-M, GARCH(1,1), Time-varying volatility.
Practical Model for Residual/Recurrent Cervical Intraepithelial Lesions in Patients with Negative Margins after Cold-Knife Conization

Objective: This study aimed to identify reliable risk factors for residual/recurrent cervical intraepithelial lesions in patients with negative margins after cold-knife conization. Methods: A total of 2352 women with HSILs (high-grade squamous intraepithelial lesions) with negative margins who underwent cold-knife conization between January 2014 and December 2020 were included; in total, 1411 women were assigned to the development cohort, and 941 women were assigned to the validation cohort. Multivariate logistic regression was used to build four predictive models based on the different combinations of follow-up data (Model A: preoperative factors; Model B: first-follow-up data; Model C: second-follow-up data; Model D: data from both follow-ups). The accuracy, sensitivity, specificity, false-positive rate (FPR), false-negative rate (FNR), and area under the receiver operating characteristic curve (AUC) were evaluated on the validation cohort. The predictive power of risk factors was further validated using six machine learning algorithms. Results: Model D demonstrated the highest AUC of 0.91 (95% CI, 0.87 to 0.96) in the validation cohort, whereas Models A, B, and C achieved AUCs of 0.69 (95% CI, 0.59 to 0.78), 0.88 (95% CI, 0.80 to 0.95), and 0.89 (95% CI, 0.81 to 0.97) respectively. The six machine learning methods achieved consistent results. Kaplan-Meier (KM) survival curves demonstrated that our models could effectively stratify patients with all models (p < 0.05 for all models). Conclusion: Our model, which is based on preoperative and follow-up factors, can serve as a complementary screening procedure for the early detection or prediction of recurrence after cold-knife conization in HSIL patients.
A Practical Co-Design of a Scanning 1D-MIMO Array and Parallel Imaging Algorithm for Security Screening

A sparse 1D-MIMO array working around 30 GHz is designed and a precise wavenumber algorithm applicable for scanning imaging is tailored and optimized to meet the realistic personnel screening needs. Simulations show that by utilizing wide-beamwidth antennas, a cross-range resolution better than 5 mm can be reached. With a parallel implementation, a fully focused 3D image of size 1 m $\times {2\mathbf{m}} \times 0.4$ m with $576\times 1000\times 70$ voxels can be obtained within 0.6 seconds.
Assessment of a Calibration-Free Method of Cuffless Blood Pressure Measurement: A Pilot Study

This study proposes a low-cost, high-sensitivity sensor of beat-to-beat local pulse wave velocity (PWV), to be used in a cuffless blood pressure monitor (BPM). Objective: We design an adaptive algorithm to detect the feature of the pulse wave, making it possible for two sensors to measure the local PWV in the radial artery at a short distance. Unlike the cuffless BPM that needs to use a regression model for calibration. Method: We encapsulate the piezoelectric sensor material in a cavity and design an analog front-end circuit. This study used color ultrasound imaging equipment to measure radial arterial parameters, including the diameter and wall thickness, to aid the estimation of blood pressure (BP) using the Moens-Korteweg (MK) equation of hemodynamics. Results: We compared the blood pressure estimated by the MK equation with the reference BP measured using an aneroid sphygmomanometer in a test group of 32 people, resulting in a mean difference of systolic BP of −0.63 mmHg, and a standard deviation of ±5.14 mmHg, a mean difference of mean arterial pressure (MAP) of 0.97 mmHg, with a standard deviation of ±3.54 mmHg, and a mean difference of diastolic BP of −1.14 mmHg, with a standard deviation of ±4.08 mmHg. This study has verified its compliance with ISO 81060-2. Conclusions: A new type of wearable continuous calibration-free BPM can replace the situation that requires the use of traditional ambulatory BPM and reduce patient discomfort. Clinical impact: In this study can provide long-term continuous blood pressure monitoring in the hospital.
An axiomatization of the ô-value

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Significance and Implications of Diagenetic Nodular Anhydrite on Sandstone Reservoirs Quality

Diagenetic nodular anhydrite observed in fluvio-aeolian-lacustrine and glacial sandstones has significant implications to reservoir quality. This type of nodular cement is spatially and volumetrically variable within these reservoirs. Its presence impacts subsurface formation evaluation and porosity calculations. Thus, the investigation of these nodules was carried out using: core image analysis; thin sections petrography; micro computed tomography (MicroCT) scans; bulk rock X-Ray Diffraction (XRD); sulfur & strontium isotope analyses. Where core was unavailable, geochemical data and resistivity-based image logs were used to expand the anhydrite characterization to derive field wide distributions. Bulk rock XRD and thin section-based petrographic studies indicate that the mineralogy of the study sandstones is dominated by quartz (>90%), with minor clay, and the presence of variable amounts of localized anhydrite as diagenetic nodular cements. The habitat of anhydrite nodules displays a substantial size variation, with nodules ranging from millimeters to several centimeters in scale. The larger nodules are easily identified visually in core samples and on borehole image logs. To investigate the origin of the anhydrite, sulfur and strontium isotope analysis were used to understand the relative timing of the nodule's development within the paragenetic sequence. Results from the sulfur and strontium isotopic analyses are consistent with the understanding that the anhydrite nodules are a late stage emplacement. A semi-quantitative "Anhydrite Abundance Index" (AAI) was calculated across key wells within the fields to establish the anhydrites regional distribution. The AAI uses the dry weight fraction of calcium and sulfur from geochemical logs to determine the volume of anhydrite. These volumes were further calibrated to volumes obtained through geochemical analysis of core samples, which is key to calculating the correct anhydrite volume required for formation evaluation. Regional distribution mapping created from this volume data suggests a widespread presence of the anhydrite nodular cementation. Understanding the relative abundance of anhydrite volumes is important when investigating the reservoir quality, especially if underestimating its presence may affect log-based porosity calculations and subsequently permeability calculations. The in-place quantification of the anhydrite nodular cement in 1D also enabled research to further the understanding of post-depositional, geochemical and geographic controls on the subsurface modelling and reservoir quality prediction.
Roles for Pathogen Interference in Influenza Vaccination, with Implications to Vaccine Effectiveness (VE) and Attribution of Influenza Deaths

Pathogen interference is the ability of one pathogen to alter the course and clinical outcomes of infection by another. With up to 3000 species of human pathogens the potential combinations are vast. These combinations operate within further immune complexity induced by infection with multiple persistent pathogens, and by the role which the human microbiome plays in maintaining health, immune function, and resistance to infection. All the above are further complicated by malnutrition in children and the elderly. Influenza vaccination offers a measure of protection for elderly individuals subsequently infected with influenza. However, all vaccines induce both specific and non-specific effects. The specific effects involve stimulation of humoral and cellular immunity, while the nonspecific effects are far more nuanced including changes in gene expression patterns and production of small RNAs which contribute to pathogen interference. Little is known about the outcomes of vaccinated elderly not subsequently infected with influenza but infected with multiple other non-influenza winter pathogens. In this review we propose that in certain years the specific antigen mix in the seasonal influenza vaccine inadvertently increases the risk of infection from other non-influenza pathogens. The possibility that vaccination could upset the pathogen balance, and that the timing of vaccination relative to the pathogen balance was critical to success, was proposed in 2010 but was seemingly ignored. Persons vaccinated early in the winter are more likely to experience higher pathogen interference. Implications to the estimation of vaccine effectiveness and influenza deaths are discussed.
Development of physical fitness test for mild intellectual disabilities aged 13-15 years

This study aims to compile a physical fitness test for mild intellectual disability, test the suitability of the test in terms of suitability, convenience, and safety. The developed tests consist of a bench up and down test, a lying down test, a sitting test and a body mass index test. The stages of development carried out include planning stage, preparation stage, trial, evaluation and revision, and final product. The experimental subjects in this study were children with mild intellectual disabilities aged 13-15 years, totaling 148 people who were divided into limited trial subjects, expanded trial subjects, and validity and reliability test subjects. Validity data analysis technique with two tests using the composite score method and using Doolittle analysis, and reliability data analysis using alpha coefficient analysis. Based on the results of the study, a set of tests was obtained to measure the physical fitness of persons with mild intellectual disabilities with very high validity and reliability tests, where the validity of the test for boys is 0.968 and for girls is 0.914. While the test reliability value for men is 0.896 and for women is 0.883. The physical fitness test was developed according to the characteristics of mild mental retardation which included components on cardiovascular endurance, muscle strength and endurance, flexibility, and body composition.
Observable signature of a background deviating from the Kerr metric

By detecting gravitational wave signals from extreme mass ratio inspiraling sources (EMRIs) we will be given the opportunity to check our theoretical expectations regarding the nature of supermassive bodies that inhabit the central regions of galaxies. We have explored some qualitatively new features that a perturbed Kerr metric induces in its geodesic orbits. Since a generic perturbed Kerr metric does not possess all the special symmetries of a Kerr metric, the geodesic equations in the former case are described by a slightly nonintegrable Hamiltonian system. According to the
Actions of linear algebraic groups on projective manifolds and minimal model program

Let X be a smooth projective variety of dimension n on which a simple Lie group G acts regularly and non trivially. Then X is not minimal in the sense of the Minimal Model Program. In the paper we work out a classification of X via the Minimal Model Program under the assumption that the dimension of X is small with the respect to the dimension of G. More precisely we classify all such X with n smaller or equal to (r_G +1), where r_G is the minimum codimension of the maximal parabolic subgroup of G (for instance r_{SL(m)}= m-1). We consider also the case when G = SL(3) and X is a smooth 4-fold on which G acts with an open orbit.
Operator identities corresponding to inverse problems

The structured operators and corresponding operator identities, which appear in inverse problems for the self-adjoint and skew-selfadjoint Dirac systems with rectangular potentials, are studied in detail. In particular, it is shown that operators with the close to displacement kernels are included in this class. A special case of positive and factorizable operators is dealt with separately.
Multilevel Privacy Preservation Scheme Based on Compressed Sensing

Although the extensive application of the Internet of Things brings great convenience, it raises the concern of privacy leakage in the processes of data acquisition, analyzing, and sharing as well. In this article, multilevel privacy protection via compressed sensing (CS) is proposed, which has the advantages of compressed sampling, protection of data privacy, and controllability of data access. At the data acquisition end, the CS technique suitable for a resource-constrained environment is employed to sample and encrypt signals with the assistance of discriminant component analysis. Then, the encrypted data will be transmitted to the cloud in time. On the cloud service, signals protected by CS rarely disclose private information to malicious attackers, and they will be accessed by two-class authorized entities. One is the semiauthorized user with low privilege who can only get the features from encrypted data for the subsequent inference; the other is the full-authorized user who is capable of reconstructing the original data. We demonstrate the scheme through two case studies of a face recognition system and a human activity recognition system and analyze its performance.
Identifying Factors Predicting Kidney Graft Survival in Chile Using Elastic-Net-Regularized Cox’s Regression

Background and Objectives: We developed a predictive statistical model to identify donor–recipient characteristics related to kidney graft survival in the Chilean population. Given the large number of potential predictors relative to the sample size, we implemented an automated variable selection mechanism that could be revised in future studies as more national data is collected. Materials and Methods: A retrospective multicenter study was conducted to analyze data from 822 adult kidney transplant recipients from adult donors between 1998 and 2018. To the best of our knowledge, this is the largest kidney transplant database to date in Chile. A procedure based on a cross-validated regularized Cox regression using the Elastic Net penalty was applied to objectively identify predictors of death-censored graft failure. Hazard ratios were estimated by adjusting a multivariate Cox regression with the selected predictors. Results: Seven variables were associated with the risk of death-censored graft failure; four from the donor: age (HR = 1.02, 95% CI: 1.00–1.03), male sex (HR = 0.64, 95% CI: 0.46–0.90), history of hypertension (HR = 1.49, 95% CI: 0.98–2.28), and history of diabetes (HR = 2.04, 95% CI: 0.97–4.29); two from the recipient: years on dialysis log-transformation (HR = 1.29, 95% CI: 0.99–1.67) and history of previous solid organ transplantation (HR = 2.02, 95% CI: 1.18–3.47); and one from the transplant: number of HLA mismatches (HR = 1.13, 95% CI: 0.99–1.28). Only the latter is considered for patient prioritization in deceased kidney allocation in Chile. Conclusions: A risk model for kidney graft failure was developed and trained for the Chilean population, providing objective criteria which can be used to improve efficiency in deceased kidney allocation.