Analysis and comparative study of a deterministic mathematical model of SARS-COV-2 with fractal-fractional operators: a case study.

In this paper, we investigate a fractal-fractional-order mathematical model with the influence of hospitalized patients and the impact of vaccination with fractal-fractional operators. The respective derivatives are considered in the Caputo, Caputo Fabrizio, and Atangana-Baleanu senses of fractional order α and fractal dimension τ . For the proposed problem, some results regarding basic reproduction number and stability are given. Using the next-generation matrix approach, we have investigated the global and local stability of several types of equilibrium points. We provide a detailed analysis of the existence and uniqueness of the solution. Moreover, we fit the model with the real data of Pakistan from June 01, 2020, till March 24, 2021. Then, we use the fractal-fractional derivative to find a numerical solution for the model. MATLAB software is used for numerical illustration. Graphical presentations corresponding to different parameteric values are given as well.

Enhancing lung cancer detection through hybrid features and machine learning hyperparameters optimization techniques.

Machine learning offers significant potential for lung cancer detection, enabling early diagnosis and potentially improving patient outcomes. Feature extraction remains a crucial challenge in this domain. Combining the most relevant features can further enhance detection accuracy. This study employed a hybrid feature extraction approach, which integrates both Gray-level co-occurrence matrix (GLCM) with Haralick and autoencoder features with an autoencoder. These features were subsequently fed into supervised machine learning methods. Support Vector Machine (SVM) Radial Base Function (RBF) and SVM Gaussian achieved perfect performance measures, while SVM polynomial produced an accuracy of 99.89% when utilizing GLCM with an autoencoder, Haralick, and autoencoder features. SVM Gaussian achieved an accuracy of 99.56%, while SVM RBF achieved an accuracy of 99.35% when utilizing GLCM with Haralick features. These results demonstrate the potential of the proposed approach for developing improved diagnostic and prognostic lung cancer treatment planning and decision-making systems.

On the implementation of a new version of the Weibull distribution and machine learning approach to model the COVID-19 data.

Statistical methodologies have broader applications in almost every sector of life including education, hydrology, reliability, management, and healthcare sciences. Among these sectors, statistical modeling and predicting data in the healthcare sector is very crucial. In this paper, we introduce a new method, namely, a new extended exponential family to update the distributional flexibility of the existing models. Based on this approach, a new version of the Weibull model, namely, a new extended exponential Weibull model is introduced. The applicability of the new extended exponential Weibull model is shown by considering two data sets taken from the health sciences. The first data set represents the mortality rate of the patients infected by the coronavirus disease 2019 (COVID-19) in Mexico. Whereas, the second set represents the mortality rate of COVID-19 patients in Holland. Utilizing the same data sets, we carry out forecasting using three machine learning (ML) methods including support vector regression (SVR), random forest (RF), and neural network autoregression (NNAR). To assess their forecasting performances, two statistical accuracy measures, namely, root mean square error (RMSE) and mean absolute error (MAE) are considered. Based on our findings, it is observed that the RF algorithm is very effective in predicting the death rate of the COVID-19 data in Mexico. Whereas, for the second data, the SVR performs better as compared to the other methods.

Forced convection of non-darcy flow of ethylene glycol conveying copper(II) oxide and titanium dioxide nanoparticles subject to lorentz force on wedges: Non-newtonian casson model.

The topic of two-dimensional steady laminar MHD boundary layer flow across a wedge with non-Newtonian hybrid nanoliquid (CuO-TiO2/C2H6O2) with viscous dissipation and radiation is taken into consideration. The controlling partial differential equations have been converted to non-linear higher-order ordinary differential equations using the appropriate similarity transformations. It is demonstrated that a number of thermo-physical characteristics govern the transmuted model. The issue is then mathematically resolved. When the method's accuracy is compared to results that have already been published, an excellent agreement is found. While the thermal distribution increases with an increase in Eckert number, radiation and porosity parameters, the velocity distribution decreases as porosity increases.

Hepatitis B among University Population: Prevalence, Associated Risk Factors, Knowledge Assessment, and Treatment Management.

Background: Very few studies have been reported on hepatitis B in the State of Azad Jammu and Kashmir, Pakistan, and none of them are specific to the prevalence and causes of hepatitis B spread among educational institutes. This study aimed to estimate the prevalence of hepatitis B infection and its associated risk factors among the University of AJ and K population. Methods: An observational, cross-sectional, and analytical study was conducted with 7015 students and employees. Hepatitis B was detected by rapid immunochromatographic tests (ICTs), enzyme-linked immunosorbent assay (ELISA), and real-time quantitative PCR. A questionnaire and interview method was used to assess the disease knowledge and associated risk factors with hepatitis B through Chi-square, Fisher's exact test, and paired t-test. Results: Of the participants, 150 (2.13%) were found positive for the hepatitis B surface antigen (57.3% male and 42.7% female). Only 0.3% participants were found fully vaccinated against the hepatitis B virus. Among ethnic groups, the Syed tribe was found more prevalent for hepatitis B infection (40.6%), while use of contaminated mourning blades (95% CI: p = 0.0001) was found as an overlooked risk factor. Hepatitis preventive awareness sessions were found to be very significant (p = 0.0001). Conclusions: The study showed that an overlooked risk factor is playing a key role in the spread of HBV in a tribe living worldwide, which must be addressed globally to eradicate hepatitis B. In Pakistan, a country-wide annual HBV vaccination program should be launched to control hepatitis B.

A new statistical approach for modeling the bladder cancer and leukemia patients data sets: Case studies in the medical sector.

Statistical methods are frequently used in numerous healthcare and other related sectors. One of the possible applications of the statistical methods is to provide the best description of the data sets in the healthcare sector. Keeping in view the applicability of statistical methods in the medical sector, numerous models have been introduced. In this paper, we also introduce a novel statistical method called, a new modified-G family of distributions. Several mathematical properties of the new modified-G family are derived. Based on the new modified-G method, a new updated version of the Weibull model called, a new modified-Weibull distribution is introduced. Furthermore, the estimators of the parameters of the new modified-G distributions are also obtained. Finally, the applicability of the new modified-Weibull distribution is illustrated by analyzing two medical sets. Using certain analytical tools, it is observed that the new modified-Weibull distribution is the best choice to deal with the medical data sets.

Synthesis and Characterizations of PdNi Carbon Supported Nanomaterials: Studies of Electrocatalytic Activity for Oxygen Reduction in Alkaline Medium.

Electrocatalytic materials offer numerous benefits due to their wide range of applications. In this study, a polyol technique was used to synthesize PdNi nanoparticles (NPs) with different percent atomic compositions (Pd = 50 to 90%) to explore their catalytic efficiency. The produced nanoparticles were characterized using X-ray diffraction (XRD) and electrochemical investigations. According to XRD measurements, the synthesized NPs were crystalline in nature, with crystallite sizes of about 2 nm. The electrochemical properties of the synthesized NPs were studied in alkaline solution through a rotating ring-disk electrode (RRDE) technique of cyclic voltammetry. The PdNi nanoparticles supported on carbon (PdNi/C) were used as electrocatalysts and their activity and stability were compared with the homemade Pd/C and Pt/C. In alkaline solution, PdNi/C electrocatalysts showed improved oxygen reduction catalytic activity over benchmark Pd/C and Pt/C electrocatalysts in all composition ratios. Furthermore, stability experiments revealed that PdNi 50:50 is more stable in alkaline solution than pure Pd and other PdNi compositions.

Mini PCNL: A viable single stage treatment for pediatric nephrolithiasis in resource limited countries.

INTRODUCTION: There is increasing enthusiasm for the value of mini PCNL for pediatric stone clearance. In developing countries, it is important to arrange a single stage treatment as a significant proportion of patients do not comply with repeated treatments, such as SWL. OBJECTIVE: To assess the safety, feasibility and outcomes of Mini PCNL in a pediatric cohort. MATERIALS AND METHODS: Retrospective analysis was performed of all paediatric patients undergoing Mini-PCNL at our institute between December 2016 and December 2019. Data was collected on stone size, stone clearance rate, complications, fluoroscopic exposure, mean procedural time and length of hospital stay. Follow up data included imaging to assess stone free status at 1 and 3 months postoperatively. RESULTS: Mini PCNL was performed in 113 pediatric patients, a total of 135 procedures, accounting for bilateral disease in 22. The age range was from 1 to 14 years with a mean age of 8.45 ± 3.14 years. The mean stone burden was 2.1 ± 0.4 cm. Partial and complete staghorn stones were observed in 7 and 3 patients, respectively. The mean operative time was 63.8 ± 13.2 min (range: 25 min to 116min) and mean length of stay was 4.3 ± 2.2 days. Primary stone clearance was achieved in 91.1% (123 patients). Ancillary procedures were undertaken in 10 patients resulting in a secondary clearance rate of 97.0% (131 patients) at 3 months. Complications occurred in 16.3% (22 patients) using the modified Clavien Classification. Metabolic abnormalities were seen in 56.7% of patients with hypocitraturia and hypercalciuria being the most common abnormalities. DISCUSSION: Our study reports a clearance rate of 91.1%, whereas, Zeng et al. documented a stone clearance rate of 80.4%. This contrast may be attributed to the difference in followup imaging protocols of the two studies and the energy source used for fragmentation. The incidence of complications with PCNL ranges from 10.6% to 36.3%, we found complications in 16.3% of our cohort. Our study is limited due to its retrospective design with a short follow-up protocol. Computed tomography being gold standard for qualitative and quantitative assessment of stone burden was not used in all patients to assess the preoperative stone size. Furthermore, postoperatively stone clearance was determined on the basis of ultrasound and x-ray films that could limit the accuracy of our stone clearance rate. CONCLUSION: Our study suggests that mini PNCL in pediatrics patients is an effective single stage treatment for definitive stone clearance with an acceptable complication risk.

Left renal mass with venous extension in hemi-azygous vein.

Extension of renal mass (RM) along venous drainage pathways is a well-recognized entity. All previously reported cases of RM show inferior vena cava (IVC), left renal vein and azygous vein involvement. We report a 55-year-old man who had left RM arising from the upper pole with invasion in left renal vein, IVC and hemi-azygous vein. To our knowledge, we report the first case of RM with venous extension in hemi-azygous vein.

MORBIDITY OF SURGERY IN PREVIOUSLY UNDIAGNOSED CIRRHOTIC PATIENTS.

BACKGROUND: Undiagnosed cirrhotic patients are frequently encountered during routine and emergency surgery. These patients have a higher incidence of blood loss & wound infection, resulting in prolonged hospital stay. This study was conducted to highlight the possible complications which result in prolonged hospital stay in these patients. METHODS: A total of 38 patients were incidentally found to have cirrhosis out of a total of 1560 patients who underwent abdominal operation. Diagnosis was confirmed on per-operative liver biopsy and was suspected preoperatively in patient having abnormal liver function test. Per-operative bleeding, postoperative wound infection and hospital stay was compared in cirrhotic and non-cirrhotic patients. RESULTS: The mean blood loss was 310 ml in cirrhotic patients as compared to 205 ml in non-cirrhotic patients which was statistically significant (p-value 0.008). Post-operative infection rate was 21% in cirrhotic patients compared to non-cirrhotic patients 5%. Significance was tested using Pearson Chi square test (0.042). The Average hospital stay was 10 days in cirrhotic patients and 7.5 days in non-cirrhotic patients respectively which was statistically significant (p-value 0.006). CONCLUSION: There is statistically significant difference in per-operative bleeding, wound infection and hospital stay in cirrhotic and non-cirrhotic patients.