A field experiment was conducted during winter season of 2021 at a research station of college of agricultural engineering sciences, university of Baghdad to determine the response of active fertility percentage and seed yield and its components of faba bean (Vicia faba L. cv. Aguadulce) to distance between plants and spraying of nano and traditional boron. A Randomized Complete Block Design according to split-plots arrangement was used at three replicates. The main plots were three distances between plants (25, 35 and 45 cm), while the sub plots including spraying of distilled water only (control treatment), spraying of boron at a 100 mg L-1 and spraying of nano boron at two concentrations (10 and 15 mg L-1). The results showed that the 25

Tetragonal compound CuAl0.4Ti0.6Se2 semiconductor has been prepared by
melting the elementary elements of high purity in evacuated quartz tube under low
pressure 10-2 mbar and temperature 1100 oC about 24 hr. Single crystal has been
growth from this compound using slowly cooled average between (1-2) C/hr , also
thin films have been prepared using thermal evaporation technique and vacuum 10-6
mbar at room temperature .The structural properties have been studied for the powder
of compound of CuAl0.4Ti0.6Se2u using X-ray diffraction (XRD) . The structure of the
compound showed chalcopyrite structure with unite cell of right tetragonal and
dimensions of a=11.1776 Ao ,c=5.5888 Ao .The structure of thin films showed

One of these plants utilized in traditional medicine is Lactuca seriolla Linn., which belongs to the Asteraceae family. It goes by a variety of common names in the world, including prickly lettuce, wild lettuce, jagged lettuce, and Kahu and khas. The work aimed to isolate and characterize some bioactive constituent(s) from the aerial part of Lactuca serriola utilizing  Combiflash NEXTGEN and high-performance liquid chromatography (HPLC). Lactuca serriola (aerial part) was extracted with 80% ethanol, then fractionated with hexane. Then 250 mg of hexane extract was mixed with 4 g of silica gel and loaded in cartilage, then bounded to the gold column of combi flash using a solvent system comprised of ethyl acetat

Abstract

The aim of this paper is to model and optimize the fatigue life and hardness of medium carbon steel CK35 subjected to dynamic buckling. Different ranges of shot peening time (STP) and critical points of slenderness ratio which is between the long and intermediate columns, as input factors, were used to obtain their influences on the fatigue life and hardness, as main responses. Experimental measurements of shot peening time and buckling were taken and analyzed using (DESIGN EXPERT 8) experimental design software which was used for modeling and optimization purposes. Mathematical models of responses were obtained and analyzed by ANOVA variance to verify the adequacy of the models. The resul

The importance of the present work falls on the pitting corrosion behavior investigation of 304 SS and 316 SS alloys in 3.5 wt%  of aqueous solution bearing with chloride and bromide anion  at different solutions temperature range starting from (20-50)^oC due to the pitting corrosion tremendous effect on the economic, safety and materials loss due to leakage. The impact of solution temperatures on the pitting corrosion resistance at 3.5wt% (NaCl and  NaBr) solutions for the 304 SS and 316 SS has been investigated utilizing the cyclic polarization techniques at the potential range -400 to1000 mV vs. SCE at 40 mV/sec scan rate followed by the surface characterization employing Scanning Electron&nbs

Abstract      Organic compounds with pyrazole cores have a variety of uses, notably in the pharmaceutical and agrochemical sectors. The interest in creating pyrazole compounds, examining their many features, and looking for potential uses is growing. Our work has concert with synthesis of  chalcones and pyrazolines, then finally pyrazoline-aniline derivatives and evaluation their anti-inflammatory, antibacterial and antifungal activities

Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,