Introduction: Although soap industry is known from hundreds of years, the development accompanied with this industry was little. The development implied the mechanical equipment and the additive materials necessary to produce soap with the best specifications of shape, physical and chemical properties. Objectives: This research studies the use of vacuum reactive distillation VRD technique for soap production. Methods: Olein and Palmitin in the ratio of 3 to 1 were mixed in a flask with NaOH solution in stoichiometric amount under different vacuum pressures from -0.35 to -0.5 bar. Total conversion was reached by using the VRD technique. The soap produced by the VRD method was compared with soap prepared by the reaction - only method which

Diazotization reaction between 1-(2,4,6-trihydroxy-phenyl)-ethanone and diazonium salts produced the ligand 4-(3-Acetyl-2,4,6-trihydroxy-phenylazo)-N-(5-methyl-isoxazol-3-yl)- benzenesulfonamide, which in turn reacted with the metal ions (Ni2+, Zn2+, Pd2+ and Pt4+) forming stable complexes with Octahedral geometry suggest of (Ni2+ and Pt4+), Zn2+ complex Tetrahedral and Pd2+ complex Square planer. The creation of such complexes was detected by employing spectroscopic means involving ultraviolet-visible, which proved the obtained geometries; FT-IR confirmed the formation of the azo group and the coordination with metal ions through it. Thermogravimetric analysis studies demonstrated the coordination of water residues (aqua or hydrate) with m

 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

Ensuring reliable data transmission in Network on Chip (NoC) is one of the most challenging tasks, especially in noisy environments. As crosstalk, interference, and radiation were increased with manufacturers' increasing tendency to reduce the area, increase the frequencies, and reduce the voltages.  So many Error Control Codes (ECC) were proposed with different error detection and correction capacities and various degrees of complexity. Code with Crosstalk Avoidance and Error Correction (CCAEC) for network-on-chip interconnects uses simple parity check bits as the main technique to get high error correction capacity. Per this work, this coding scheme corrects up to 12 random errors, representing a high correction capac

This research is a theoretical study that deals with the presentation of the literature of statistical analysis from the perspective of gender or what is called Engendering Statistics. The researcher relied on a number of UN reports as well as some foreign sources to conduct the current study. Gender statistics are defined as statistics that reflect the differences and inequality of the status of women and men overall domains of life, and their importance stems from the fact that it is an important tool in promoting equality as a necessity for the process of sustainable development and the formulation of national and effective development policies and programs. The empowerment of women and the achievement of equality between men and wome

Historical cultural environments are a repository of values and symbols that pass down across generations through spatial experiences. Despite their intellectual and cultural potential, their role in fostering belonging and identity has declined; they are often viewed as silent landmarks, isolated from lived experiences. This highlights the need for an integrated model that makes spatial experience a stimulating process for reinvigorating the meaning inherent in historical contexts and reconnecting the new generation with their cultural roots. This research aims to explore how cultural meaning in historical contexts can be reactivated through spatial experience. To achieve this, the study proposes a triadic model – physical encoun

Resumen

    Sotileza , localismo santandrino de sutileza , es la parte más fina del aparejo de pescar donde va el anzuelo. Es la obra maestro de José María de Pereda.Su ambiente , el Santander viejo, anterior al año 50,evocado emocionadamente - emociόn romántica contenida en los trazos sobrios y firmes de un naturalism psicolόgico y paisajista,el Santander que el autor confiesa poseer en el fondo de su corazόn,«y tenerlo esculpido en la memoria de tal suerte que ,a ojos cerrados,me atrevería a trazarle con todo su perímetro y sus calles, y el color de sus piedras, y el número, y los nombres, y hasta las caras de sus habitantes».Dentro de la grandeza primaria de las criaturas de Pere

This paper offers a systemic review of the deep learning methods to detect violence on campus, which is a critical issue in intelligent surveillance to improve the student safety and prompt cut off of violent accidents. The review reviews studies published 2018-2025, concentrating on model structure to detect fights, bullying, vandalism, and aggressive behavior on problematic campuses due to occlusion and light variations and complicated human interactions. The research design includes a comparative study of different deep learning networks, such as CNNs, RNNs, 3D CNNs, attention-based networks, transformers, graph neural networks, neuro-fuzzy, and multimodal systems and federated learning methods. The paper also assesses benchmark