Colorectal cancer (CRC) is the most common gastrointestinal malignancy and one of the top ten common cancers worldwide with approximately 2 million cases. There are multiple risk factors that could lead to CRC emergence; of which are genetic polymorphisms. Excision repair cross-complementing group 2 (ERCC2) gene encodes for ERCC2 enzyme which plays a crucial role in maintaining genomic integrity by removing DNA adducts. Several studies suggested that there could be a link between genetic polymorphisms of ERCC2 gene and the risk of CRC development. Hence the present study aims to validate the relationship between the following ERCC2 single nucleotide polymorphisms (rs13181, rs149943175, rs530662943, and rs1799790) and CRC susceptibility. A t

A novel demountable shear connector is proposed to link a concrete slab to steel sections in a way that resulting steel-concrete composite floor is demountable, i.e. it can be easily dismantled at the end of its service life. The proposed connectors consist of two parts: the first part is a hollow steel tube with internal threads at its lower end. The second part is a compatible partially threaded bolted stud. After linking the stud to the steel section, the hollow steel tube can be fastened over the threaded stud, which create a complete demountable shear connector. The connector is suitable for use in both composite bridges and buildings, and using cast in-situ slabs, precast solid slabs, or hollow-core precast slabs. A series of push-off

The increasing demand for energy has encouraged the development of renewable resources and environmentally benign fuel such as biodiesel. In this study, ethyl fatty esters (EFEs), a major component of biodiesel fuel, were synthesized from soybean oil using sodium ethoxide as a catalyst. By-products were glycerol and difatty acyl urea (DFAU), which has biological characteristics, as antibiotics and antifungal medications. Both EFEs and DFAU have been characterized using Fourier transform infrared (FTIR) spectroscopy, and 1H nuclear magnetic resonance (NMR) technique. The optimum conditions were studied as a function of reaction time, reactant molar ratios, catalyst percentage and the effect of organic solvents. The conversion ratio of soybea

The current study shows the cytotoxicity effect of the Crassula ovata n-hexane extract on esophagus can¬cer. C. ovata is a perennial succulent plant belonging to the Crassulaceae family. In Africa, the leaves were used medicinally to cure epilepsy and diarrhoea by boiling them in milk. The hexane fraction, which is obtained through the maceration method, demonstrates the presence of many compounds that have an anticancer effect, which are ob¬tained by gas chromatography - mass spectroscopy. The phytosterol compound was isolated by a preparative thin layer chromato¬graph and was identified by liquid chromatography - mass spectroscopy. The hexane fraction was found to possess a strong anticancer effect against esophagus cancer. The

The New Schiff base ligand 4,4'-[(1,1'-Biphenyl)-4,4'-diyl,bis-(azo)-bis-[2-Salicylidene thiosemicarbazide](HL)(BASTSC)and its complexes with Co(II), Ni(II), and Cu(II) were prepared and characterized by elemental analysis, electronic, FTIR, magnetic susceptibility measurements. The analytical and spectral data showed, the stiochiometry of the complexes to be 1:1 (metal: ligand). FTIR spectral data showed that the ligand behaves as dibasic hexadentate molecule with (N, S, O) donor sequence towards metal ions. The octahedral geometry for Co(II), Ni(II), and Cu(II) complexes and non electrolyte behavior was suggested according to the analysis data.

Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par