Recently, increasing material prices coupled with more acute environmental awareness and the implementation of regulation has driven a strong movement toward the adoption of sustainable construction technology. In the pavement industry, using low temperature asphalt mixes and recycled concrete aggregate are viewed as effective engineering solutions to address the challenges posed by climate change and sustainable development. However, to date, no research has investigated these two factors simultaneously for pavement material. This paper reports on initial work which attempts to address this shortcoming. At first, a novel treatment method is used to improve the quality of recycled concrete coarse aggregates. Thereafter, the treated recycled

Seismic facies analysis constrained with well log information have been used to predict lithofacies distribution across the Okam Field of Niger Delta. Density and gamma ray logs were cross-plotted and the seismic section was subdivided vertically into different seismic facies. The delineated lithologies, from well logs were correlated with seismic facies signatures using lines of intersection across the wells. Gamma ray and resistivity logs were used to identify the interfaces between the lithofacies and correlated across the field. Structural interpretation was carried out. Time slices were generated and examined at different intervals within the identified reservoirs. Stratigraphic related attribute and envelope were extracted on these

The method of analysis is one of the tools the coach to identify strengths andweaknesses of each player, and how to avoid mistakes that in the course ofperformance on the other hand, Voslob analysis is important for the player, as throughthe analysis will determine the capacity enjoyed by both the coach and player, as wellas being the possibility of progress in a scientific manner thoughtful, and also helps inthe evaluation of physical and skill level and tactical, psychological and trainingcapacity of the coach in order to avoid obstacles and make the coach is movingtowards the right track to improve the good level, and then an investigation tocomplete higher education.Hence the importance of research in the analysis of simple attack and n

Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

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