This work reports the study of heat treatment effect on the structural, morphological, optical and electrical properties of poly [3-hexylthiophene] and its blend with [6,6]-phenyl C61 butyric acid methyl ester ( P3HT:PC61BM). X-ray diffraction (XRD) measurements show that the crystallinity of the films increased with annealing. The evaluation of surface roughness and morphology was investigated using atomic force microscope (AFM), and field emission scanning microscope(FESEM). The optical properties were emphasized a strong optical absorption of P3HT compared with the blend. Hall effect measurement was used to study the electrical properties which revealed there is an increase in the electrical conductivity and Hall mobility of th

In this study, experimental mortar combinations with 1% micro steel fibers, were examined to create geopolymer mortars. To test the effect of the fibers on the mortar's resistance, the geopolymer mortar was designed with various proportions of more environmentally friendly materials fly ash and slag. The percentage of fly ash by weight was 50, 60, and 70% of the slag. The best results were obtained when a 50:50 ratio of fly ash and slag were mixed with 1% micro steel fibers. The results showed that the mixtures containing fibers performed better in the considered tests (toughness index, ductility index, and resilience index). In the impact resistance test, the mixture contained 50% fly ash by weight of the slag with a temperature of

The purpose of this paper is to identifying some of the physical, kinetic and electrical capabilities of the working muscles of patients with simple hemiplegic cerebral palsy, preparation of special exercises (rehabilitation and water) accompanied by symmetrical electrical stimulation in the rehabilitation of working muscles for patients with simple hemiplegic cerebral palsy, and identifying the effect of exercises, especially (rehabilitation and water), accompanied by symmetrical electrical stimulation, on some physical, kinetic and electrical capabilities in rehabilitating working muscles for patients with simple hemiplegic cerebral palsy. The researcher used the experimental approach with a one-group design with two pre and post-tests du

Background: techniques of image analysis have been used extensively to minimize interobserver variation of immunohistochemical scoring, yet; image acquisition procedures are often demanding, expensive and laborious. This study aims to assess the validity of image analysis to predict human observer’s score with a simplified image acquisition technique. Materials and methods: formalin fixed- paraffin embedded tissue sections for ameloblastomas and basal cell carcinomas were immunohistochemically stained with monoclonal antibodies to MMP-2 and MMP-9. The extent of antibody positivity was quantified using Imagej® based application on low power photomicrographs obtained with a conventional camera. Results of the software were employed

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

The research targets study of influence of additives on sand mold’s properties and, consequently, on
that of carbon steel CK45 casts produced by three molds. Three materials were selected for addition
to sand mix at weight percentages. These are sodium carbonates, glycerin and oat flour. Sand molds
of studied properties were produced to get casts from such molds. The required tests were made to
find the best additives with respect to properties of cast. ANSYS software is used to demonstrate
the stresses distribution of each produced materials. It is shown that the mechanical properties of
casts produced is improved highly with sodium carbonates and is less with oat flour and it is seem a
few with glycerin additives

Porosity and permeability are the most difficult properties to determine in subsurface reservoir characterization. The difficulty of estimating them arising from the fact that porosity and permeability may vary significantly over the reservoir volume, and can only be sampled at well location. Secondly, the porosity values are commonly evaluated from the well log data, which are usually available from most wells in the reservoir, but permeability values, which are generally determined from core analysis, are not usually available. The aim of this study is: First, to develop correlations between the core and the well log data which can be used to estimate permeability in uncored wells, these correlations enable to estimate reservoir permeabil