Tight reservoirs have attracted the interest of the oil industry in recent years according to its significant impact on the global oil product. Several challenges are present when producing from these reservoirs due to its low to extra low permeability and very narrow pore throat radius. Development strategy selection for these reservoirs such as horizontal well placement, hydraulic fracture design, well completion, and smart production program, wellbore stability all need accurate characterizations of geomechanical parameters for these reservoirs. Geomechanical properties, including uniaxial compressive strength (UCS), static Young’s modulus (Es), and Poisson’s ratio (υs), were measured experimentally using both static and dynamic met

4-amino-3-(4-(((4-hydroxy-3, 5dimethoxybenzyl) oxy) methyl) phenyl)-1, 2, 4-triazole-5-thione was synthesized by to method the first one from melt reaction of 4-(((4-hydroxy-3, 5-dimethoxybenzyl) oxy) methyl) benzoic acid with Thiocarbonyldihydrazide, the second method from convert the corresponded acid hydrazide to potassium 2-(4-(((4-hydroxy-3, 5-dimethoxybenzyl) oxy) methyl) benzoyl) hydrazinecarbodithioate salt then react with hydrazine hydrate. Newly Schiff base (7a-7f) were synthesized from reaction the 4-amino-1, 2, 4-triazol with substituted hydroxybenzaldehyde. The resulting compounds were characterized by IR, 1H-NMR, 13C-NMR, and HRMS data. 2, 2-Diphenyl-1-picrylhydrazide (DPPH) and ferric reducing antioxidant power (FRAP) assays

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a pandemic of coronavirus disease 2019 (COVID-19) which represents a global public health crisis. Based on recent published studies, this review discusses current evidence related to the transmission, clinical characteristics, diagnosis, management and prevention of COVID-19. It is hoped that this review article will provide a benefit for the public to well understand and deal with this new virus, and give a reference for future researches.

This investigation pertains to the evaluation of water quality in SAWA Lake, located in the Al-Muthanna province of Southern Iraq, from 1977 to 2020. Understanding the water quality and assessments of this Lake is of great importance. The Lake is home to small, transparent, blind fish measuring approximately 10 cm and is often referred to as the "wonderful" or "strange" Lake due to its many unique features. The study focuses on several elements to represent water quality, including total dissolved solids (TDS), electrical conductivity (EC), pH, and temperature (T), which were measured directly in the field. Additionally, scientific concepts such as K⁺, Ca²⁺, Cl^-, HCO

This study was to examine the effect of a mental training program, including a combination of autogenic training and imagery, on a number of mental skills and on the development of personality traits-psychological hardiness as well as conscientiousness, openness to experience, and neuroticism-in Adolescent male volleyball players. 60 adolescent male volleyball players (aged 15–17) participated in a two-group, pretest-posttest design. The experimental group (n = 30) completed 8-week mental skills training program, including imagery, self-talk, attention control, and relaxation, while the control group (n = 30) followed regular training. Psychological hardiness and selected personality traits were measured pre-and post-intervention using va

In this investigation , borax (B) (additive I) and chlorinated paraffin (CP.) (additive II) ,were used as flame retardants for each of epoxy and unsaturated polyester resins in the weight ratios of 2,4,6, & 8% by preparing films of (130×130×3) mm dimensions. Also films of these resins with a mixture of [50%(B.)+50%(CP.)] (additive III) in the same weight ratios were prepared in order to study the synergistic effect of these additives on the flammability of the two resins . Three standard test methods were used to measure the flame retardation which are : 1-ASTM : D-2863 2-ASTM : D-635 3-ASTM : D-3014

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de