The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

The present work involved preparation of new substituted and unsubstituted and poly imides (1-17) using reaction of acryloyl chloride with different amides (aliphatic ,aromatic) in the presence of a suitable solvent and amount tri ethyl amine (Et3N) with heating – the structure confirmation of all polymers were proved using FT-IR,1H-NMR,C13NMR and UV spectroscopy ,thermal analysis (TG) for some polymers confirmed their thermal stabilities . Other physical properties including softening and melting points, PH and solubility of the polymers were also measured

Background: Pregnancy is a stressful state of increased inflammatory activity, and pregnancy – associated hormone changes can influence periodontal tissues, these inflammatory activity lead to production of inflammatory mediators. Interleukin 1 beta (IL-1β) is a potent pro-inflammatory cytokines that is consistently associated with periodontal diseases. This study was designed to determine the periodontal health status and detect the serum level of IL-1β in the healthy pregnant women at first, second and third trimester and compare it with healthy non pregnant women, and determine its correlation with different clinical periodontal parameters. M

A linear engine generator with a compact double-acting free piston mechanism allows for full integration of the combustion engine and generator, which provides an alternative chemical-to-electrical energy converter with a higher volumetric power density for the electrification of automobiles, trains, and ships. This paper aims to analyse the performance of the integrated engine with alternative permanent magnet linear tubular electrical machine topologies using a coupled dynamic model in Siemens Simcenter software. Two types of alternative generator configurations are compared, namely long translator-short stator and short translator-long stator linear machines. The dynamic models of the linear engine and linear generator, validated

Background: overweight and obesity are the fifth leadingrisk for global deaths. At least 2.8 million adults die eachyear as a result of being overweight or obese. Numerousstudies show that weight loss, even if only 5-10%,significantly improves dyslipidemia, hypertension, diabetesmellitus, risk for osteoarthritis and its symptoms and risk forselected cancers.Objectives: is to evaluate the effect of diet and exerciseprogram on anthropometric and biochemical status of adultobese patients.Methods: descriptive study. 124 adult obese patientsattending Al Kindy obesity research and therapy unit duringDecember 2012 were included. Measurement of Wt, heightHt and WC performed and BMI was calculated. Laboratorytest analysis, on the fasting state, w

The importance of specifying proper aggregate grading for achieving satisfactory performance in pavement applications has long been recognized. To improve the specifications for superior performance, there is a need to understand how differences in aggregate gradations within the acceptable limits may affect unbound aggregate base behavior. The effects of gradation on strength, modulus, and deformation characteristics of high-quality crushed rock base materials are described here. Two crushed rock types commonly used in constructing heavy-duty granular base layers in the State of Victoria, Australia, with three different gradations each were used in this study. The gradations used represent the lower, medium, and upper gradation li

Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t