In silico analysis of the use of solanine derivatives as a treatment for Alzheimer's disease.

Alzheimer's disease (AD) is a brain illness that causes cognitive impairment in the elderly, especially females, as a result of genetics, hormones, and life experiences. It becomes more severe with age and is associated with cardiovascular disease, hypertension, and diabetes. Beta-amyloid plaques and hyper phosphorylated Tau protein buildup are common clinical findings.

Performance evaluation of a flighted rotary dryer for lateritic ore in concurrent configuration.

The lateritic ore drying in the Cuban nickel producing industry is realized within flighted rotary dryers. In this investigation, performance indicators in regards to transfer of momentum, heat and mass were evaluated. The dryers operate in a concurrent configuration with combustion gas, at a productivity between 40 t h and 50 t h.

Defining the optimal conditions using FFNNs and NARX neural networks for modelling the extraction of Sc from aqueous solution by Cryptand-2.2.1 and Cryptand-2.1.1.

The main aim of this study is to figure out how well cryptand-2.2.1 (C 2.

Corrigendum to "A comprehensive review on modelling the adsorption process for heavy metal removal from waste water using artificial neural network technique" [Heliyon 9(4) (April 2023) e15455].

[This corrects the article DOI: 10.1016/j.heliyon.

Studying the effect of reactor design on the electrocoagulation treatment performance of oily wastewater.

Several conventional methods are employed to remove numerous pollutants from oily wastewater discharged from oil-field activities. The purpose of this study is to use a new design of an electrocoagulation reactor (ECR) to treat oily wastewater effluents from the Al-Muthanna petroleum plant to minimize a Total Dissolved Solids (TDS) to levels suitable for employment. In a continuous ECR, a One-Sided-Finned cathode tube (1SF) made of aluminum was inserted between a pair of aluminum-cylindrical anodes.

A comprehensive review on modelling the adsorption process for heavy metal removal from waste water using artificial neural network technique.

Water is the most necessary and significant element for all life on earth. Unfortunately, the quality of the water resources is constantly declining as a result of population development, industry, and civilization progress. Due to their extreme toxicity, heavy metals removal from water has drawn researchers' attention.

Prediction of methyl orange dye (MO) adsorption using activated carbon with an artificial neural network optimization modeling.

In this study, methyl orange (MO) dye removal by adsorption utilizing activated carbon made from date seeds (DPAC) was modeled using an artificial neural network (ANN) technique. Instrumental investigations such as X-ray diffraction (XRD), scanning electron microscopy (SEM), and Brunauer-Emmett-Teller (BET) analysis were used to assess the physicochemical parameters of adsorbent. By changing operational parameters including adsorbent dosage (0.

Can electrocoagulation technology be integrated with wastewater treatment systems to improve treatment efficiency?

Considerable amounts of domestic and industrial wastewater that should be treated before reuse are discharged into the environment annually. Electrocoagulation is an electrochemical technology in which electrical current is conducted through electrodes, it is mainly used to remove several types of wastewater pollutants, such as dyes, toxic materials, oil content, chemical oxygen demand, and salinity, individually or in combination with other processes. Electrocoagulation technology used in hybrid systems along with other technologies for wastewater treatment are reviewed in this work, and the articles reviewed herein were published from 2018 to 2021.