في الدراسة الحالية، تم تصنيع جسيمات ZrO2 النانوية باستخدام مستخلص نباتي مشتق من نبات Vitex agnus castus، ووسط قلوي مثل هيدروكسيد الصوديوم. تم استخدام أسلوب التخليق الحيوي لتحضير جزيئات أوكسيد الزركونيوم النانوية لهذا المشروع البحثي. تتميز هذه الطريقة عن غيرها بسبب فعاليتها من حيث التكلفة وبساطتها وقلة المخاطر المحتملة. وتم تشخيص العينات المحضرة باستخدام المجهر الإلكتروني النافذ TEM، المجهر الإلكتروني الماسح SEM، التحليل الطيفي بالأشعة تحت الحمراء بتحويل فورييه FT-IR، التحليل الطيفي فوق البنفسجي المرئي. ، حيود الأشعة السينية، والتحليل الطيفي للأشعة السينية المشتتة من الطاقة EDX. تم تحديد حجم البلورة باستخدام حيود الأشعة السينية من معادلة ديباي-شيرر بقيمة 26.37 نانومتر. تم استخدام المجهر الإلكتروني الماسح والمجهر الإلكتروني النافذ للتأكد من حجم جسيمات ZrO2 النانوية. في هذه الدراسة، أظهرت هذه الجسيمات النانوية مستويات متفاوتة من النشاط ضد نوعين من البكتيريا إيجابية الجرام ( Staphylococcus aurous و Streptococcus pneumonia)، ونوعين من البكتيريا السالبة الجرام (Proteus mirabilis و Escharia coli)، ونوع واحد من الفطريات وهو Candida. ومن المثير للاهتمام، أنه تم الكشف عن الإمكانات المضادة للسرطان لجسيمات أوكسيد الزركونيوم النانوية المركبة من خلال اختبار MTT بتركيز متنوعة لسرطان الرئة A549 من خط الخلية. وأظهرت نسبة التثبيط زيادة مع زيادة التركيز. إن حساب تثبيط نصف الخلايا IC50، والذي كان يساوي (58.4 ملغم/مل)، يشير إلى أن جزيئات أكسيد الزركونيوم النانوية لديها القدرة على الاستفادة منها في علاج السرطان
Moderately, advanced national election technologies have improved political systems. As electronic voting (e-voting) systems advance, security threats like impersonation, ballot tampering, and result manipulation increase. These challenges are addressed through a review covering biometric authentication, watermarking, and blockchain technologies, each of which plays a crucial role in improving the security of e-voting systems. More precisely, the biometric authentication is being examined due to its ability in identify the voters and reducing the risks of impersonation. The study also explores the blockchain technology to decentralize the elections, enhance the transparency and ensure the prevention of any unauthorized alteration or
... Show MoreReservoir 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
... Show MoreAbstract
The study discussed three areas in strategic thinking, namely, (patterns elements, outcomes) , this study aimed to measure extent to which strategic leaders have the type or types of patterns of strategic thinking, and measure the extent of their use of the elements of strategic thinking, and measurement of strategic thinking outcomes for managers at various levels , And to know the relationship between the modes of strategic thinking, elements and outcomes in organizations. the study included five banks and four hospitals and four colleges and universities, has been a research sample consisted of 168 individuals, distributed in positions (Director General , Director of Directorate , Director of
... Show MoreModern statistical techniques offer a range of methodologies for modelling time series data, with conditional and unconditional approaches providing complementary insights that enhance overall model accuracy. This article introduced a modified ARIMA model employing conditional and unconditional parameter estimates. The methodology for the new model based on novel methods is provided. The prediction process, one and two steps ahead, is covered in detail, and a novel algorithm is presented. The best model is picked based on various measurement criteria, such as coefficient of determination (R2), root mean squared error (RMSE), and mean absolute scaled error (MASE). The suggested model is applied to a monthly petrol sales dataset (Jan
... Show MoreIn this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.
Soil water use and water storage vary by vegetative management practices, and these practices affect land productivity and hydrologic processes. This study investigated the effects of agroforestry buffers (AB), grass buffers (GB), and biofuel crops (BC), relative to row crops (RC) on soil water use for a claypan soil in northern Missouri, USA. The experiment located at the Greenley Memorial Research Center included RC, AB, GB, and BC established in 1991, 1997, 1997, and 2012, respectively. Soil water reflectometer sensors installed at 5‐, 10‐, 20‐, and 40‐cm depths monitored soil water from April to November in 2017 and 2018. Results showed significant differences in weekly volumetric water content (VWC) among treatments for all fou
... Show MoreVehicular Ad Hoc Networks (VANETs) are integral to Intelligent Transportation Systems (ITS), enabling real-time communication between vehicles and infrastructure to enhance traffic flow, road safety, and passenger experience. However, the open and dynamic nature of VANETs presents significant privacy and security challenges, including data eavesdropping, message manipulation, and unauthorized access. This study addresses these concerns by leveraging advancements in Fog Computing (FC), which offers lowlatency, distributed data processing near-end devices to enhance the resilience and security of VANET communications. The paper comprehensively analyzes the security frameworks for fog-enabled VANETs, introducing a novel taxonomy that c
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for