In this paper, numerical and experimental studies on the elastic behavior of glass fiber reinforced ‎polymer (GFRP) with stiffeners in the GFRP section's web (to prevent local buckling) are presented. ‎The GFRP profiles‎ were connected to the concrete deck slab by shear connectors. Two full-scale simply supported ‎composite beams (with and without stiffeners) were tested under impact load (three-point load) to ‎assess its structural response. The results ‎proved that the maximum impact force, maximum ‎deflection, damping time, and ‎damping ratio of the composite beam were affected by the GFRP ‎stiffeners‎. The experimental results indicated that the damping ratio and deflection were diminished compare

The inelastic C2 form factors and the charge density distribution (CDD) for ^58,60,62Ni and ^64,66,68Zn nuclei has been investigated by employing the Skyrme-Hartree-Fock method with (Sk35-Skzs*) parametrization. The inelastic C2 form factor is calculated by using the shape of Tassie and Bohr-Mottelson models with appropriate proton and neutron effective charges to account for the core-polarization effects contribution. The comparison of the predicted theoretical values was conducted with the available measured data for C2 and CDD form factors and showed very good agreement.

Three new polyphosphates were synthesized in good yields by reacting diethylenetriamine with the appropriate phosphate ester in ethanol under acidic conditions. The polyphosphate structures were determined using FT-IR and 1H-NMR spectroscopies, and their elemental compositions were confirmed by EDX spectroscopy. Polyphosphates were added to poly(vinyl chloride) (PVC) at low concentrations to fabricate thin films. The PVC films were irradiated with ultraviolet light for long periods, and the effect of polyphosphates as the photostabilizer was investigated by determining changes in the infrared spectra (intensity of specific functional group peaks), reduction in molecular weight, weight loss, and surface morphology. Minimal changes we

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,

Abstract

To evaluate the effectiveness of Phenolic Compound of Salvia Frigida on induced atopic dermatitis (AD) of mice. Forty mice were included in the study, divided in to four groups (10 mice/group): apparently healthy, induced AD without treatment, induced AD treated with tacrolimus 0.1% ointment, and induced AD treated with Phenolic Compound of Salvia Frigida cream 5%. Examination of histopathology was done and skin homogenates levels also measured. Levels of WBC, Eosinophil, skin tissue homogenate of IL-13 and IL-4, serum IgE, and histopathological scores were significantly increased among induced non treated AD group in comparison with control group. Comparisons of non-treated induced AD

This search that addressed with (( The Impact of Cultural Dimensions in multicultural Project Teams )) tagged is important variables in the project environment that rare has been adverted in Arabic studies .  The search problem is reflected in missing of awareness towards a cultural dimensions of the Diyala bridge area project team and their impact in project communications ، as well as weak project management interest in adopting a clear and scientific approach in the management and organization of project communications in order to reach the objective of the study ، was used questionnaire that built depending on previous global studies and has been adapted to accommodate Iraqi business e

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo