The coronavirus disease (COVID-19) changed the world’s lifestyle switching many techno-services to be provided remotely instead of direct usual physical interactions between people. This study focused on university students’ perceptions of this virtual technology-engineering change as discrepancies to be analyzed. The research surveyed 777 different students from four Arab middle-east neighboring countries, with related demographics and specifications, expressing full remarkable experiences of e-technology in virtual as well as traditional performances helping reveal overall tolerance possibilities. The study adopted examination technology via ANOVA to test discrepancies within students' perceptions for overall multi-factors deep analysis classification. The exploration highlighted an interesting range of pros and cons remarks including feminism and economic effect as well as other cultural and engineering interaction issues, raising signals to essentially consider and mutually benefit from adequate future generation e-techno adaptation within the region.

We prove the existence of weak solutions of a two-incompressible immiscible wetting and non-wetting fluids phase flow model in porous media with dynamic capillary pressure. This model is a coupled system which includes a nonlinear parabolic saturation equation and an elliptic pressure–velocity equation. In the regularized case, the existence and uniqueness of the weak solution are obtained. We let the regularization parameter be $\eta \to 0$ to prove the existence of weak solutions.

Logistic regression method (LR) is one of the most widely used modeling techniques in various fields of science, especially in clinical medicine where variables are often dichotomous. The factors that cause toxoplasmosis (T. gondii) are well explained by most clinical investigators. Therefore, the main objective of this article is to identify the most significant factors leading to toxoplasmosis infection. The binary logistic regression method has been used to interpret the study's findings. A clustered sampling technique with an informative questionnaire was used in the survey to collect a relevant sample of 508 individuals from the most affected areas, specifically the northern part of Saudi Arabia. SPSS as well as AMOS are the typical statistical analysis tools used to investigate the results. The binary logistic techniques showed that the factors (stillbirth, women’s direct contact with soil, and keeping indoor cats) were the most significant factors influencing infection with toxoplasmosis, without neglecting some other invisible factors. Only 18.9% of the variation in the dependent variable (Toxoplasmosis infection) is attributed to the independent variables (which is moderate, with Nagelkerke’s R square = 0.189). Early medical follow-up and health awareness campaigns should be adopted, especially in remote rural communities.

Families of bivariate distributions with weak dependence between their margins are of practical importance, despite being relatively uncommon. These families can be constructed using specific copulas. This paper introduces a new family, KSEW, developed using the bivariate Kimeldorf-Sampson (KS) copula and the extended Weibull (EW) distributions. The KSEW family is designed for applications requiring marginal distributions with low but significant levels of dependence, positioned above the threshold of independence. Key properties of the KSEW family were derived, including product moments and the correlation coefficient. The study also explored the uniform, power, Weibull, Rayleigh, exponential, and Lomax distributions as specific cases within the EW family, identifying the maximum correlation coefficient for each. Additionally, the reliability function in the dependent stress-strength model under the KS framework was developed. The concomitants of order statistics and associated information measures using the KSEW distribution were also investigated. The practical applicability of the KSEW family was demonstrated through analysis of two real-world datasets, highlighting its suitability for scenarios involving weakly dependent random variables.