Reservoir characterization is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling. This comprehensive research paper delves into the complex interplay of rock materials, rock formation techniques, and geological modeling techniques for improving reservoir quality. The research plays an important role dominated by petrophysical factors such as porosity, shale volume, water content, and permeability—as important indicators of reservoir properties, fluid behavior, and hydrocarbon potential. It examines various rock cataloging techniques, focusing on rock aggregation techniques and self-organizing maps (SOMs) to identify specific and

Hydroxide upon the chemical composition and dry matter(DM) and organic matter(OM) digestibility . Rice straw was treated with 4% sodium hydroxide using 30% of DM basis moisture, and incubated at 40 ºC for 40 days., DM digestibility (DMD) was significantly affected (P<0.01) by the treatment , where DMD increased The objective of this experiment was to study the effect of physical form (long ,chopped and ground ) and washing rice straw treated with sodium from 42.32 to 45.41% , OM digestibility (OMD) and total digestible nutrient (TDN) increased(P<0.05) from 47.38 and 49.33 to 49.67 and 52.83% ,respectively. While hemicellulose content increased (P<0.05 ) from 261.71 to 268.17 gm/kg DM ,and metabolizable energy (ME) from 7.11 to 7.48 MJ/

The present work presents design and implementation of an automated two-axis solar tracking system using local materials with minimum cost, light weight and reliable structure. The tracking system consists of two parts, mechanical units (fixed and moving parts) and control units (four LDR sensors and Arduino UNO microcontroller to control two DC servomotors). The tracking system was fitted and assembled together with a parabolic trough solar concentrator (PTSC) system to move it according to information come from the sensors so as to keep the PTSC always perpendicular to sun rays. The experimental tests have been done on the PTSC system to investigate its thermal performance in two cases, with tracking system (case 1) and without trackin

Antibiotics are essential for treating infectious diseases, but their overuse and adverse effects are raising concerns about global public health. The pervasiveness of antibiotic contamination in aquatic environments has drawn increased attention in recent years. The primary concern regarding the release of antibiotics into the environment is the potential for microorganisms to become resistant to antibiotics. This review article summarizes the analytical methods used to determine the presence of trimethoprim and metronidazole in various environmental samples. These antibiotics have traditionally been analyzed using tandem mass spectrometry or high-performance liquid chromatography coupled to mass spectrometry; fluorescence or ultrav

Abstract

Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n^-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

Pseudomonas aeruginosa is emerging opportunistic clinical pathogens. Clinical isolates of P. aeruginosaresist wide spectrum of antibiotics and form biofilm. The comparison study between clinical and environmental of P. aeruginosa in terms of biofilm formation and antibiotic resistance is very scanty. Thus, in current study microtiter plate technique was used to measure the biofilm formation by several clinical and environmental isolates. Moreover, the antibiotic susceptibility of these bacteria was evaluated by VITIK 2 techniques. The relationship between the antibiotic susceptibility and biofilm formation was evaluated for clinical and environmental isolates. Clinical and environm

This paper predicts the resilient modulus (Mr) for warm mix asphalt (WMA) mixtures prepared using aspha-min. Various predictor variables were analyzed, including asphalt cement types, asphalt contents, nominal maximum aggregate sizes (NMAS), filler content, test temperatures, and loading times. Univariate and multivariate analyses were conducted to examine the behavior of each predictor variable individually and collectively. Through univariate analysis, it was observed that Mr exhibited an inverse trend with asphalt cement grade, NMAS, test temperature, and load duration. Although Mr increased slightly with higher filler and asphalt content, the magnitude of this increase was minimal. Multivariate analysis revealed that the rate of change