Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Vapor-liquid equilibrium data are presented for the binary systems n-hexane - 1-propanol, benzene - 1-propanol and n-hexane – benzene at 760 mm of mercury pressure. In addition ternary data are presented at selected compositions with respect to the 1-propanol in the 1-propanol, benzene, n-hexane system at 760 mmHg. The results indicate the relative volatility of n-hexane relative to benzene increases appreciably with addition of 1-propanol.

Background: Traumatic ulcerative granuloma with stromal eosinophilia is an impressive benign chronic ulcerative lesion of the oral mucosa with vague etiopathogenesis. It was supposed to represent an oral counterpart of primary cutaneous CD30+ lymphoproliferative disorder. Histopathologically, it is characterized by mixed inflammatory infiltrate predominated by histiocytes, lymphocytes and eosinophils along with presence of scattered large atypical mononuclear cells. It has worrisome clinical presentation. It may heal spontaneously, but in most occasions it persists and never heal unless removed surgically (incisional or excisional biopsy). A rare subset may show worrisome immunohistochemical features. Follow up is highly recommended. Mat

In this study azo dye was prepared by the reaction of m-phenylendidiazonium chloride with methyl salicylate, the resultant compound was used as a ligand for complex formation with Fe+2, Cu+2, Zn+2, Ni+2 and Co+2 ions. The prepared ligand was characterized by H1NMR, UV-Vis., And FTIR spectroscopy, CHN analysis, in addition the complexes were characterized by TGA, UV-Vis., FTIR and conductivity methods. The results indicate that the ligand chelated through phenoxy and carboxyl groups as a O4 quadra dentate ligand, the Co complex complet its hexagon coordination by bonding with chlorine and the complex wouid be electrolytic in opposite with rest complexes.

The syntheses, characterization and experimental solid state X-ray structures of five low-spin paramagnetic 2-pyridyl-(1,2,3)-triazole-copper compounds, [Cu(Ln)2Cl2], are presented in this study, for the following five Ln ligands: L1 = 2-(1-(p-tolyl)-1H-(1,2,3-triazol-4-yl)pyridine), L2 = 2-(1-(4- chlorophenyl)-1H-(1,2,3-triazol-4-yl)pyridine), L3 = 4-(4-(pyridin-2-yl)-1H-(1,2,3-triazol-4-yl)benzonitril), L4 = 2-(1-phenyl-1H-(1,2,3-triazol-4-yl)pyridine) and L5 = 2-(1-(4-(trifluoromethyl)phenyl)-1H-(1,2,3- triazol-4-yl)pyridine). These five [Cu(Ln)2Cl2] complexes each contain two bidentate 2-pyridyl-(1,2,3)- triazole (Ln) and two chloride ions as ligands, with the Cu–N(pyridine) bonds, Cu–N(triazole) and Cu–Cl bonds trans to each othe

Interacting boson model version one has been used in the present

theoretical calculations. The energy levels & their transitions for dynamical  symmetry  0(6),  SU(3),  U(5),  ground-state  band,  Beta­ band, Gamma  band, B(E2), Ot, B(Ml), ,u,gt and  6(£2/Ml)have been  calculated  to  deduce  the  limit  of  Pt-198,  Z=78.  The  present results  confirmed  the  nuclear  behavior  of  this  isotope  lay  in  the

transitional region 0(6), SU(3) U(5). The calculations of 021 + & 022+

showed that the shape of this isotope is oblate according to Q21+  and pr

    Diabetic nephropathy (DN) is the most common microvascular complication that may lead to chronic renal failure in diabetic patients. Till now microalbuminuria, with its restrictions, is the early marker of DN, appeared after the disease exacerbation. Thus, new biomarkers are required to predict the early onset of DN before the appearance of microalbuminuria. The aim of this study is to investigate the possible use of uVDBP in the early prediction of DN. Fifty diabetic patients with DN and 40 diabetic patients without DN for both types of diabetes were enrolled in this study. All patients were tested for uACR, uVDBP (measured by ELISA), and blood HbA1c. The results demonstrated a highly significant elevation of uAC

حضر الليكاند (L) 1-فنيل-3-بردين-2-يل مثيل-ثايويوريا من تفاعل 2-أمينو مثيل بردين مع فنيل ايزوثايوسيانيت وبنسبة 1: 1 وشخص الليكاند بواسطة التحليل الدقيق للعناصر (C, H, N), الأشعة تحت الحمراء، الأشعة فوق البنفسجية–المرئية وطيف الرنين النووي المغناطيسي كما حضرت وشخصت معقدات أملاح بعض ايونات العناصر الثنائية التكافؤ (Co, Ni, Cu, Cd and Hg). استخدمت تقنية الأشعة تحت الحمراء، الأشعه فوق البنفسجية-المرئية, التوصيلية الكهربائية و الا