In this work, Schiff base ligands L1: N, N-bis (2-hydroxy-1-naphthaldehyde) hydrazine, L2: N, N-bis (salicylidene) hydrazine, and L3:N –salicylidene- hydrazine were synthesized by condensation reaction. The prepared ligands were reacted with specific divalent metal ions such as (Mn2+, Fe2+, Ni2+) to prepare their complexes. The ligands and complexes were characterized by C.H.N, FT-IR, UV-Vis, solubility, melting point and magnetic susceptibility measurements. The results show that the ligands of complexes (Mn2+, Fe2+) have octahedral geometry while the ligands of complexes (Ni2+) have tetrahedral geometry.

The polymeric hydrogels composed of poly vinyl alcohol (m.wt 72000) and glutaraldehyde(5%,8% and 10%) , have been thermally prepared for the purpose of studying their swelling and drug release behavior . The swelling ratio was measured for all the hydrogel samples at 37°C, in three different media pH (1.2, 4.7 and 6.8) as a function of time. The results show that the maximum swelling ratios were arranged as follows :pH =6.8 > pH =4.7 > pH =1.2 hydrogels cross linked PVA showed a typical pH responsive behavior such as high pH has maximum swelling while low pH shows minimum swelling.

In this research, new series of Furo-2-quinolone [FQ] compounds have been synthesized. These novel [FQ] compounds were prepared from coumarin derivatives (Furocoumarins: psoralen and isopsoralen).Identifications of these FQ compounds were performed by using infrared spectrum (I.R), Ultraviolet spectrum (U.V) and Nuclear Magnetic Resonance spectrum (H¹-NMR) besides some physical data. The cytotoxic screening involves ;using HEP-2 cell line which gave differential responses against tested compounds : 4,6 Dimethyl furo[2, 3-g] coumarin (C₁), 1-(2`, 4`, Dimethoxy benzylideneimino)-2,6-dimethyl Furo [2, 3-g] quinoline-2-one (C₃) and the angular psoralen of the same derivative

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

In this study, the kinematic analysis including the forward and inverse kinematic developed for a 5 degree of freedom robotic arm. The forward kinematic is elaborated using Denavit-Hartenberg (DH) convention. Inverse Kinematic is established using Deep Neural Network (DNN) model with five hidden layer each contain 50 neurons fully connected using ReLu activation. A data of inputs and outputs are created and trained. The inputs are the end-effector position and orientation. The outputs are the joint angles of the manipulator. The data is generated by the forward kinematics, where a set of joint angles that limited by their corresponding ranges are inserted to the forward kinematic equations to result the end-effector positions and or

Colorectal cancer (CRC) remains a leading cause of cancer-related deaths worldwide, with tumor angiogenesis playing a pivotal role in its progression and metastasis. CD144 (VE-cadherin), a calcium-dependent adhesion molecule, is critical for endothelial cell integrity and has been linked to tumor angiogenesis and cancer stem cell phenotypes. This study aimed to evaluate the immunohistochemical expression of CD144 in benign colorectal lesions, normal adjacent tumor tissue (NRAT), and tumor tissues to elucidate its role in colorectal cancer progression. Multiple techniques, including immunohistochemistry, flow cytometry, Western blot, and qPCR, were used to assess CD144 expression and its association with the VEGF/VEGFR2 signaling pat

This study develops a systematic density functional theory alongside on-site Coulomb interaction correction (DFT + U) and ab initio atomistic thermodynamics approachs for ternary (or mixed transitional metal oxides), expressed in three reservoirs. As a case study, among notable multiple metal oxides, synthesized CoCu2O3 exhibits favourable properties towards applications in solar, thermal and catalytic processes. This progressive contribution applies DFT + U and atomistic thermodynamic approaches to examine the structure and relative stability of CoCu2O3 surfaces. Twenty-five surfaces along the [001], [010], [100], [011], [101], [110] and [111] low-Miller-indices, with varying surface-termination configurations were selected in this study.