The slaughterhouse industry generates substantial wastewater rich in proteins, lipids, fibers, and carbohydrates. This study integrates experimental investigations into artificial neural network (ANN) optimization and commerce design studies for treating slaughterhouse and meat processing wastewater (SMW). Batch coagulation/flocculation experiments identified optimal conditions for three

Purpose: The use of recycled coarse aggregate in concrete structures promotes environmental sustainability; however, performance of these structures might be negatively impacted when it is used as a replacement to traditional aggregate. This paper aims to simulate recycled concrete beams strengthened with carbon fiber-reinforced polymer (CFRP), to advance the modeling and use of recycled concrete

This study aimed to identify the interactions between the sub-systems of the supply chain system of milled grain products, in South Africa, namely: (1) farming (agricultural); (2) transport (transportation); (3) manufacturing (milling); and (4) trade (retail). Furthermore, this paper investigated how these sub-systems are affected by economic and natural external factors namely: (1) the exchange

Gallbladder cancer (GBC) is an aggressive and lethal malignancy with a poor prognosis. Long noncoding RNAs (lncRNAs) and natural products have emerged as key orchestrators of cancer pathogenesis through widespread dysregulation across GBC transcriptomes. Functional studies have revealed that lncRNAs interact with oncoproteins and tumor suppressors to control proliferation, invasion, metastasis

The importance of technology and managerial risk management in banks has increased due to the financial crisis. Banks are the most affected since there are so many of them with poor financial standing. Due to this problem, an unstable and inefficient financial system causes economic stagnation in both the banking sector and overall economy. Data envelopment analysis (DEA) has been used to examine

Hepatocellular carcinoma (HCC) is a leading liver cancer that significantly impacts global life expectancy and remains challenging to treat due to often late diagnoses. Despite advances in treatment, the prognosis is still poor, especially in advanced stages. Studies have pointed out that investigations into the molecular mechanisms underlying HCC, including mitochondrial dysfunction and

One of the inevitable challenges that face the construction industry is the delay of project completion. The current state of the industry makes the need for delay analysis apparent, however the process of choosing the most reliable delay analysis technique can get very complex in some situations. This research aims to develop a framework to identify and analyze the most important factors to

Medical image segmentation is indicated in a number of treatments and procedures, such as detecting pathological changes and organ resection. However, it is a time-consuming process when done manually. Automatic segmentation algorithms like deep learning methods overcome this hurdle, but they are data-hungry and require expert ground-truth annotations, which is a limitation, particularly in

Introduction: With the increasing prevalence of type 2 diabetes mellitus (T2DM), there is an urgent need to discover effective therapeutic targets for this complex condition. Coding and non-coding RNAs, with traditional biochemical parameters, have shown promise as viable targets for therapy. Machine learning (ML) techniques have emerged as powerful tools for predicting drug responses. Method: In

Multiple Sclerosis (MS) is a long-term autoimmune disorder affecting the central nervous system, marked by inflammation, demyelination, and neurodegeneration. While the exact cause of MS remains unknown, recent research indicates that environmental factors, particularly diet, may influence the disease's risk and progression. As a result, the potential neuroprotective effects of coffee, one of the