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Unfortunately, monuments all over the world may become discolored and degraded as a result of the growth and activity of fungi. Biodeterioration is an irreversible damage that is caused by microbial colonization on the surface of buildings. Different fungi were isolated from limestone False-door in Kom Aushim museum- El-Fayoum governorate, Egypt. These include; Aspergillus niger, A. fumigatus, A. sulphureus, A. flavus, Alternaria alternata, Alternaria spp., and Cladosporium herbarium. Fungal grow on modern limestone surfaces after 60 days of infection. Transmission electron microscope demonstrated the penetration and presence of fungal threads inside limestone. Environmental Scanning electron microscope attached with EDX Unit revealed an increase in carbon and magnesium ions from 9.16 to 12.17% and 1.41–1.51%, respectively after fungal infection of limestone, while other ions decreased after infection; aluminum from 1.96 to 1.39%, silicon from 7.40 to 3.57%, potassium from 0.44 to 0.41%, calcium from 41.41 to 35.04 % and iron from 1.08 to 0.90 %. p-Chloro-m-crysol is the most potent to inhibit the growth of isolated fungi at MIC 50 ppm for most fungal species.

This work predicts the dynamics of the COVID-19 under widespread vaccination to anticipate the virus's current and future waves. We focused on establishing two population-based models for predictions: the fractional-order model and the fractional-order stochastic model. Based on dose efficacy, which is one of the main imposed assumptions in our study, some vaccinated people will probably be exposed to infection by the same viral wave. We validated the generated models by applying them to the current viral wave in Egypt. We assumed that the Egyptian current wave began on 10th September 2021. Using current actual data and varying our models’ fractional orders, we generate different predicted wave scenarios. The numerical solution of our models is obtained using the fractional Euler method and the fractional Euler Maruyama method. At the end, we compared the current predicted wave under a high vaccination rate with the previous viral wave. Through this comparison, the vaccination control effect is quantified.

In this paper, we investigate the stochastic nature of the COVID-19 temporal dynamics by generating a fractional-order dynamic model and a fractional-order-stochastic model. Initially, we considered the first and second vaccination doses as multiple vaccinations were initiated worldwide. The concerned models are then tested for the Saudi Arabia second virus wave, which is assumed to start on 1st March 2021. Four daily vaccination scenarios for the first and second dose are assumed for 100 days from the wave beginning. One of these scenarios is based on function optimization using the invasive weed optimization algorithm (IWO). After that, we numerically solve the established models using the fractional Euler method and the Euler-Murayama method. Finally, the obtained virus dynamics using the assumed scenarios and the real one started by the government are compared. The optimized scenario using the IWO effectively minimizes the predicted cumulative wave infections with a 4.4 % lower number of used vaccination doses.

Objective: Renographies obtained within 1 h of renal transplantation were studied prospectively to evaluate their technical feasibility and potential clinical impact on successful treatment of immediate posttransplantation complications such as arterial or venous thrombosis, which require prompt diagnosis and management. Subjects and Methods: During December 1996 to December 1998, 127 renal transplants were performed. Ninety-four patients had complete renographic studies within 1 h of surgery. It was not possible to perform renography on 26 patients who were not sent to the Department of Nuclear Medicine within 1 h of transplant and 7 other patients who could not undergo a complete renogram because of their postoperative condition. Results: There was no complication attributed to transporting patients to the Department of Nuclear Medicine for these studies so soon after surgery. Of the 94 renographies obtained immediately following transplant surgery 46 were abnormal. However, when compared with the usual policy of obtaining baseline renograms between 12 and 72 h after surgery, treatment was changed for only 2 patients. Radionuclide renography within 1 h of transplant surgery was technically feasible. Conclusion: Based on the results of this study the clinical utility of obtaining renography within 1 h posttransplant was minimal and hence we recommended that it should not be performed routinely but could be used on an individual basis when imminent intervention is highly likely.Copyright © 2005 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

The article is devoted to the development of digital technologies in the field of healthcare of Kazakhstan. The process of automation of a medical institution hospital is considered. The functionality of the developed information system and the prospects for the implementation of this system in this area are described. The developed information system allows it to accumulate the medical and statistical information in the databases of the hospital and use in practice, automates the management of the hospital workflow. The capabilities of the system consist in registering patients in a hospital, maintaining an electronic medical history and obtaining complete statistical reports. The patient’s electronic medical history contains his personal data, diagnoses, recommended procedures and medications. The introduction of information and communication technologies in the health sector will improve the quality of care and significantly speed up the work of staff.

The rise in everyday internet users worldwide can be ascribed to advancements made to the internet worldwide. Attacks by malware cause data loss, hardware destruction, and large financial losses. As a result, this research creates a novel mathematical compartmental dynamical model that, under both fixed and dynamic size network assumptions, can be utilized to precisely predict malware outbreaks. The modeling processes divided the network into seven distinct states and considered the diverse ways that users of the internet interacted with potentially hazardous links. The Hilfer-Katugampola fractional operator was employed to obtain the intended varied states of networks. The existence, uniqueness, equilibrium, and stability of the provided models are thoroughly examined. Then the best control plan is implemented for every network topology. The controllers' objectives are to minimize the costs of data loss due to infections, malware tracing, and public awareness improvements. Ultimately, we confirm the theoretical results by observing the spread of malware using numerical simulations. Results demonstrated the effectiveness of the enforced control measures in maintaining the necessary goals of malware infection management.

Sufficient conditions for controllability of impulsive nonlinear integro-differential equations with ψ-Hilfer fractional derivative are established. The result are obtained by using fractional calculus and Schaefer’s fixed point theorem. Finally, a numerical examples are then provided to demonstrate the outcomes.

Flashover voltage is considered one of the important factors affect the Power system reliability. Environmental conditions and filling of insulators are parameters should be considered in flashover voltage evaluation. In this work, laboratory studies are carried out on insulator with Alumina Trihydrate [ATH] filling at different concentration and different weather conditions to investigate the flashover voltage. The evaluation of flashover voltage is carried out at three conditions dry, wet and salt wet condition. In each test, four different lengths with different filling concentration are considered. Several curve fitting methods are used to obtain an equation of flashover voltage. The obtained equation first is only function of filling at different insulator lengths with approximately zero errors. Although the accuracy of this method, it gives flashover voltage only at discrete lengths. Thus, for continuous length validation the flashover is fitted again to be a function of both length and filling.

In this paper, COVID-19 dynamics are modelled with three mathematical dynamic models, fractional order modified SEIRF model, stochastic modified SEIRF model, and fractional stochastic modified SEIRF model, to characterize and predict virus behavior. By using Euler method and Euler-Murayama method, the numerical solutions for the considered models are obtained. The considered models are applied to the case study of Egypt to forecast COVID-19 behavior for the second virus wave which is assumed to be started on 15 November 2020. Finally, comparisons between actual and predicted daily infections are presented.