This work predicts the effect of thermal load distribution in polymer melt inside a mold and a die during injection and extrusion processes respectively on the structure properties of final product. Transient thermal and structure models of solidification process for polycarbonate polymer melt in a steel mold and die are studied in this research. Thermal solution obtained according to solidify the melt from 300 to 30Cand Biot number of 16 and 112 respectively for the mold and from 300 to 30 Cand Biot number of 16 for die. Thermal conductivity, and shear and Young Modulus of polycarbonate are temperature depending. Bonded contact between the polycarbonate and the steel surfaces is suggested to transfer the thermal load. The temperatures distribution produces in thermal model importing as load and boundary conditions to solve the structure model. 3D mold and die are built to simulate the thermal and structure behavior using ANSYS 12.1 program. The results show that the temperatures and residual stresses decreases with the distance from the center to surfaces for the mold ,while for the die the temperatures and stresses decreases with the distance from the inlet to the outlet. The temperatures and stresses decreases with the time increasing for both mold and die. Also the thermal strain compatible with the temperatures distribution in the mold and the die. The total deformation concentrated at the left and right edge of polycarbonate in the mold, while starting in the center of the polymer at the outlet and then transfer to the entry of the die with the time increasing.
Meta stable phase of SnO as stoichiometric compound is deposited utilizing thermal evaporation technique under high vacuum onto glass and p-type silicon. These films are subjected to thermal treatment under oxygen for different temperatures (150,350 and 550 °C ). The Sn metal transformed to SnO at 350 oC, which was clearly seen via XRD measurements, SnO was transformed to a nonstoichiometric phase at 550 oC. AFM was used to obtain topography of the deposited films. The grains are combined compactly to form ridges and clusters along the surface of the SnO and Sn3O3 films. Films were transparent in the visible area and the values of the optical band gap for (150,350 and 550 °C ) 3.1,
The mixed ligand complexes of Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II) and Hg(II) with alanine and 8-hydroxyqinoline (Oxine) were synthesized and characterized by FT-IR ,spectra electronic, flam-AAS] along with conductivity measurements , solubility , melting point, magnetic susceptipibility.The synthesized complexes were tested in vitro for antimicrobial activity. The results obtained indicated that some of these complexes are more active than with others.
Salicylaldehyde was react with 4-amino-2,3-dimethyl-1-phenyl-3-pyrazoline-5-on to produce the Schiff base ligand 2,3-dimethyl-1-phenyl-4-salicylidene-3-pyrazoline-5-on (L). The prepared ligand was identified by Microelemental Analysis, and FT.IR, UV-Vis spectroscopic techniques. A new complexes of Fe(III),Co(II),Ni(II),Cu(II),Ce(III) and Pb(II) with mixed ligands of dithizone (DTZ) and Schiff base were prepared in aqueous ethanol with a 2:2:1 M:L:DTZ. The prepared complexes were characterized using flame atomic absorption, (C.H.N) Analysis, FT.IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. In addition biological activity of the ligands and complexes against two selected type of bacteria
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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
... Show MoreIn this paper a prey-predator-scavenger food web model is proposed and studied. It is assumed that the model considered the effect of harvesting and all the species are infected by some toxicants released by some other species. The stability analysis of all possible equilibrium points is discussed. The persistence conditions of the system are established. The occurrence of local bifurcation around the equilibrium points is investigated. Numerical simulation is used and the obtained solution curves are drawn to illustrate the results of the model. Finally, the nonexistence of periodic dynamics is discussed analytically as well as numerically.
The effect of metal nanoparticles on the anaerobic digestion of sludge and the sludge bacterial community are still not well-understood, and both improvements and inhibitions have been reported. This study investigated the impact of 2, 10, and 30 mg/g TS silver and copper oxide nanoparticles (AgNPs and CuONPs) on the mesophilic anaerobic digestion of sludge and the bacterial community structure. The reactors were monitored for changes in tCOD, sCOD, TS, VS, biogas generation, and cell viability. Also, the relative abundance and taxonomic distribution of the bacterial communities were analyzed at the phylum and genus levels, including the genera involved in anaerobic digestion. Both AgNPs and CuONPs exhibited some inhibition on anaer
... Show MoreThe present study was conducted to estimate the incidence, clinical findings, cytological and histopathological characteristics of spontaneously occurring skin neoplasms in dogs. A total of 40 grossly suspected cases of cutaneous and subcutaneous tumors were gathered during the period from July 2016 to August 2018 from male and female dogs in Baghdad city. Dogs with skin neoplasia revealed various clinical signs, and their ages were older than 5 years to 15 years. German shepherd 30% followed by Terrier dogs 25% were more influenced than other breeds. Concerning tumor features, the majority of neoplasms had solitary lesion 70%, regular shapes 65% with black color 55%. The tumors frequently occurred on fore-limbs and abdomen, and 80% of them
... Show MoreObjective: This study involved the synthesis of new Schiff bases and 1,3-oxazepine derivatives from the baclofen drug and study the anticancer activities. Methods: Baclofen was initially reacted with aromatic aldehydes to create Schiff base derivatives (Ia–Ib), which were then closed in the next step using anhydrous acids to form oxazepine derivatives (IIa–IId). Results: The title compounds were synthesized successfully and identified using FT-IR, 1H NMR, and 13C NMR spectroscopy. Additionally, compound (IIc)’s (3-(4-chloro-phenyl)-4-[2-(4nitro-phenyl)-4,7-dioxo-4,7-dihydro-[1,3] oxazepin-3-yl]butyric acid) anticancer activity was assessed using MTT assay against FTC-133 (thyroid cancer) compared with WRL-68 (normal cell line). Discus
... Show MoreThis study was aimed to assess the impact of vermicompost, glutathione, and their interaction on beetroot (Beta vulgaris L.) growth, yield, and antioxidant traits. The experiment carried out at vegetable field of the College of Agricultural Engineering Sciences - University of Baghdad during fall season 2019. The experiment was conducted using factorial arrangement within Randomized Complete Block Design with two factors and three replicates (3X3X3). Applying vermicompost before cultivation represented the first factor (0, 15, 30 ton.ha-1), which symbolized (V0, V1, V2). Glutathione (0, 75, 150 mg.L-1) which symbolized (G0, G1, G2) represented the second factor. Results showed the superiority of secondary interaction treatment V2G2
... Show MoreConvolutional 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,
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