The University of Arkansas System is a state university system in the U.S. state of Arkansas. It comprises six campuses; a medical school; two law schools; a graduate school focused on public service; a historically black college, statewide research, service, and educational units for agriculture, criminal justice, and archeology; and several community colleges. Over 50,000 students are enrolled in over 188 undergraduate, graduate, and professional programs.Legally, the entire system carries the name University of Arkansas. Nonetheless, to avoid confusion with its flagship campus in Fayetteville, the system usually refers to itself as the University of Arkansas System and the Fayetteville campus usually refers to itself as the University of Arkansas.
This paper investigates the existence of traveling waves in a diffusive SIR model with delay incorporated in the diffusion terms and a nonlinear incidence rate with delay. By employing a cross-iteration scheme and partial monotonicity conditions, we establish that the existence of quasi-upper and lower solutions, along with suitable super and sub-solutions, provides sufficient conditions for the existence of a traveling wavefront. This existence result is obtained via Schauder’s fixed-point theorem. Furthermore, given an appropriate basic reproduction number, the traveling wavefront transitions from the disease-free steady state to the endemic steady state. To illustrate our approach, we explicitly construct super- and sub-solutions for a specific model.
The exploitation of an extremely sensitive and reliable nanozyme based colorimetric sensor for highly sensitive detection of hydrogen peroxide (H2O2) in living body system is extensively carping owing to fact that it garnered a prime role in causing toxic diseases. In this work, a highly novel catalyst named as Cerium oxide (CeO2) nanosheets (NSs) was precisely prepared by using a simple one pot hydrothermal method, thereby dowered with a strong intrinsic peroxidase like capability of catalyzing the oxidation-reaction of colorless 3,3′,5,5′-tetramethylbenzidine (TMB) to generate a blue color reaction in the presence of H2O2. Hence, a sensitive visible assessment platform related to CeO2 NSs was engineered, which not only exhibited a wider detection range of 0.01–1000 µM with R2 value of 0.9998, but also perceives exceptional selectivity, tremendous cycling and long term stability. Further, the sensor also evaluates lowest detection limit (LOD) 0.29 ± 0.03 µM and quantification limit (LOQ) of 2.3 ± 0.03 µM. In addition, it also endorses impressive practicality with stronger sensitivity and favorable accuracy in serum samples. Thus, this research-work not only contributed upon CeO2 NSs an outstanding capacity to detect H2O2, but also expands the realm of applications for CeO2 NSs in the domains of environmental preservation, biomedical diagnosis and forensic sciences.
With rapid urbanization, lifestyle changes, and an aging population, non-communicable diseases (NCDs), including hypertension and diabetes, pose significant public health challenges in Bangladesh and many other low- and middle-income countries. This study used machine learning (ML) approaches to develop predictive models for hypertension and diabetes among Bangladeshi adults. Bangladesh Demographic and Health Survey 2022, a nationally representative cross-sectional survey, data were analyzed. Hypertension was defined as systolic/diastolic blood pressure 140/90 mmHg (or more) or taking any antihypertensive medication. Diabetes was defined as having fasting plasma glucose ≥7.0 mmol/L or using any glucose-lowering drugs. Potential predictors included age, sex, education, wealth quintile, overweight/obesity, rural-urban residence, and division of residence. Descriptive analysis was conducted, and six ML models were applied: artificial neural network (ANN), random forest, adaptive boosting (AdaBoost), gradient boosting, XGBoost, and support vector machine (SVM). Models' performance and feature importance were reported. We included 13,847 adults (females: 55%). Sensitivity was high across models (up to 0.96 and 0.90 for diabetes and hypertension, respectively). However, the overall specificity was low, particularly for diabetes. The prevalence of diabetes and hypertension was 16.3% and 20.5%, respectively. For diabetes, AdaBoost had the highest AUC (0.699), and SVM had the highest accuracy (0.836); for hypertension, AdaBoost had the greatest AUC (0.775) and accuracy (0.799). Hypertension was the most common diabetes predictor, while overweight/obesity was the most common predictor for hypertension, followed by age and diabetes. Wealth and sex were moderately influential, with education and geographic factors less so. Low specificity across models indicated challenges in identifying non-cases. This ML-driven analysis identified the bidirectional relationship of hypertension and diabetes along with several other predictors, including overweight/obesity, older age, and richer household wealth quintiles. Our findings underscore the need for integrated screening and lifestyle interventions targeting high-risk groups to mitigate future NCD burden.
Understanding the magnetic properties of rare-earth iron garnet ultrathin films subjected to a strain is of essence from both fundamental science and technological perspectives. In this work, we report on the results of a combined first-principles calculations and classical Monte Carlo simulations study of magnetic properties of gadolinium iron garnet thin-films subjected to a uniaxial strain. We employ first-principles calculations to compute the magnetic exchange coupling constants for thin films subjected to uniaxial strains including both compressive and tensile cases. The magnetic exchange coupling constants were then used to construct an effective magnetic Hamiltonian, which includes symmetry-breaking effects, and perform Monte Carlo simulations. Using the latter, we study the dependences of magnetic properties on temperature and strain in gadolinium iron garnet thin-film systems, subjected to a uniaxial strain. To further advance our understanding of the magnetic behavior, we also consider a simple analytical model, which is based on the N & eacute;el molecular field theory for ferrimagnetics and incorporates magnetic exchange coupling constants taken from the first-principles calculations. The case of uniaxial strains, considered in this work, is compared to the behavior of biaxially-strained thin films, studied in a previous work, and the theoretical results of this work are also compared with available experimental data on rare-earth iron garnets subjected to an external strain. The implications of the obtained results for use of layered rare-earth iron garnets-based materials for magnetic technologies are also discussed.
Excision followed by radiofrequency ablation (eRFA) is an intraoperative method that utilizes intracavitary hyperthermia to create an additional tumor-free zone around the lumpectomy cavity in patients with breast cancer, similar to partial breast irradiation. We hypothesized that intraoperative eRFA extends the “final” tumor-free margin, decreases local recurrence, and maintains cosmesis without the need for radiation (XRT). Patients with unifocal ER+PR+HER2− or DCIS tumors less than or equal to 3 cm with clinically negative nodes were included. After standard lumpectomy, the RFA probe was deployed 1 cm circumferentially into the walls of the lumpectomy cavity. RFA was performed at 100°C for 15 min, followed by validated intraoperative Doppler sonography. Pain and cosmesis were assessed with the Radiation Therapy Oncology Group (RTOG) scales. A total of 242 subjects were accrued to the study, with a median follow-up of 44 months (range 12–96 months); 60
