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Water being a precious commodity for every person around the world needs to be quality monitored continuously for ensuring safety whilst usage. The water data collected from sensors in water plants are used for water quality assessment. The anomaly present in the water data seriously affects the performance of water quality assessment. Hence it needs to be addressed. In this regard, water data collected from sensors have been subjected to various anomaly detection approaches guided by Machine Learning (ML) and Deep Learning framework. Standard machine learning algorithms have been used extensively in water quality analysis and these algorithms in general converge quickly. Considering the fact that manual feature selection has to be done for ML algorithms, Deep Learning (DL) algorithm is proposed which involve implicit feature learning. A hybrid model is formulated that takes advantage of both and presented it is data invariant too. This novel Hybrid Convolutional Neural Network (CNN) and Extreme Learning Machine (ELM) approach is used to detect presence of anomalies in sensor collected water data. The experiment of the proposed CNN-ELM model is carried out using the publicly available dataset GECCO 2019. The findings proved that the model has improved the water quality assessment of the sensor water data collected by detecting the anomalies efficiently and achieves F1 score of 0.92. This model can be implemented in water quality assessment.

The management of water pollution has been one of the main problems as people pay more and more attention in the current society to the preservation and repair of the natural environment. In this paper, natural montmorillonite was modified with starch as well as lanthanum chloride. The removal efficiency of various modified montmorillonites on pollutants was examined by simulating the water quality conditions of heavily polluted lake reservoirs in order to provide new eco-friendly and effective materials for the treatment of heavily polluted lakes and reservoirs. The experimental results showed that: The nitrogen removal rates of Na-Mont, St-Mont, La-Mont, St-La-Mont and La-St-Mont for 2 mg/L TN solution were 28.48%, 5.18%, 59.55%, 98.39%, 64.73%, respectively, and total phosphorus removal rates for 10 mg/L TP contaminated solution were 6.24%, 4.16%, 87.41%, 93.66%, 91.58% and for 100 mg/L COD solution the removal rates were 32.37%, 41.46%, 51.68%, 86.89%, 77.8%, respectively. By exploring the effect of La6-Mont adsorption for Cr6+ removal at different temperatures as well as reaction times, the results showed that the Cr6+ removal at saturation of La6-Mont adsorption was 76%, 80.5%, and 82.5% at the reaction temperatures of 15℃, 25℃, and 35℃, respectively. Among them, the removal rates of St-La-Mont reached more than 85%, 50% and 70% for COD, TN and for TP, respectively, and can be applied as fillers for enhanced artificial fast infiltration systems. The light rare earth composites La-St-Mont and LaCl3-Mont have achieved removal rates of 35%, 50% and more than 90% for COD, TN and for TP, respectively, and can be used as effective purification materials for treating water quality of heavily polluted lakes and reservoirs. Meanwhile, La6-Mont can effectively fix heavy metal ions and avoid the release of endogenous pollution in the bottom mud, which can be used as a material for the treatment of bottom mud in lake reservoirs. This shown that lanthanum, a light rare earth element, modified montmorillonite can not only remove a range of pollutants from water bodies but also has excellent removal rates. Additionally Besides, starch, lanthanum and montmorillonite are widely available materials with high economic benefits. Therefore, further studies on St-La-Mont, La-St-Mont, LaCl3-Mont and La6-Mont can provide new materials for the treatment of pollution in heavily polluted lakes and reservoirs.

This study utilized a series of experimental tests, including the Atterberg limit, standard Proctor, permeability, and direct shear tests. Three composites were investigated: 85% fly ash-10% bentonite (V1), 90% fly ash-5% bentonite (V2), and 95% fly ash-0% bentonite (V3). All composites contained 5% coconut fiber. The plasticity index (PI) increased significantly from 19.10% to 22.15%, with a change in bentonite content from 0% to 10%. All composite met the landfill liner plasticity index standards. The permeability values were low and satisfied local criteria, namely 1.052 x 10-5 (V1), 1.260 x 10-5 (V2), and 1.394 x 10-5 (V3). Composite V2 has the best value with a cohesion value of 55 kPa and a shear angle of 22°.Therefore, composite V3 was the most promising composite as an alternative covering material for landfills because it has the lowest atterberg limits results, the lowest OMC, and the results from the direct shear test that meet the criteria even though it is not the best result among the three variations. However, by supporting the OMC value and good plasticity, the V3 composite was chosen. This study is beneficial and valuable in the engineering, selection, and design of materials used for the construction of landfill liners. .

Nanotechnology exemplifies advancement in the field of research and development by enhancing product efficacy through the introduction of novel solutions. In the field of cosmeceuticals, the use of nanotechnology is increasing to solve some of the limitations associated with conventional goods. Cosmeceuticals are the fastest-growing section of the personal care market, and their use has skyrocketed in recent years. Nanocosmeceuticals are a type of skin, hair, nail, and lip care product that is used to cure wrinkles, photoaging, hyperpigmentation, dandruff, and hair damage. However, nanotoxicological studies have raised concerns about the impact of expanding nanoparticle use in cosmeceuticals, as nanoparticles have the potential to permeate skin and create health problems. The research on nanotechnology in cosmeceuticals focuses on the multiple unique carriers utilized for cosmeceutical delivery, their good and negative aspects, marketed formulations, toxicity, and nanocosmeceutical restrictions. The primary goal of this editorial is to highlight the advantages and disadvantages of nanoparticles used in cosmetics.