A review on impacts of COVID-19 on global agricultural system and Scope for Bangladesh after pandemic

Environmental Science and Pollution Research - COVID-19 pandemic has had a devastating effect on the global food production system. Large-scale food producing countries restricted exports for food...     

Potential mechanisms of Na+/K+-ATPase attenuation by heat and pesticides co-exposure in goldfish: role of cellular apoptosis,oxidative/nitrative stress,and antioxidants in gills

Environmental Science and Pollution Research - In this study, we examined the dose-dependent effects of an environmentally relevant pesticide cocktail (metalachlor, linuron, isoproturon,...     

On the origin of forces in the wake of an elliptical cylinder at low Reynolds number

Environmental Fluid Mechanics - An analysis of forces for flow around an elliptic cylinder at low Reynolds number has been presented in this work. The finite-volume based open source code OpenFOAM...     

Multiple health benefits of curcumin and its therapeutic potential

Environmental Science and Pollution Research - Turmeric, or Curcuma longa as it is formally named, is a multifunctional plant with numerous names. It was dubbed “the golden spice” and...     

Feature selection approaches for predictive modelling of cadmium sources and pollution levels in water springs

The World Health Organization lists cadmium (Cd) as one of the top ten chemicals of public health concern. Cd is toxic at relatively low exposure levels and has acute and chronic effects on both health and the environment. In this study, we investigate a suite of data-driven methods that could assist decision-makers in estimating Cd levels in water springs, and in identifying polluting sources. Machine learning (ML) regression models were used to identify sources of contamination and predict Cd levels based on support vector machines and a variety of tree-based models, including Random Forests, M5Tree, CatBoost, and gradient boosting. Feature selection analysis revealed that heavy traffic and distance to a major power plant in the sampled area play a leading role in springs Cd contamination, together with precipitation levels and average of slopes of the closest waste dumps upstream to sampled springs. Our best performing ML model was the Adaboost regression tree using all the features (RMSE = 19.36, R^2 = 0.64). Our findings highlight the effectiveness of predictive data-driven modeling in addressing environmental challenges, particularly in high-risk areas with low resources.

     

An Overview on Starch-Based Sustainable Hydrogels: Potential Applications and Aspects

Hydrogels are a kind of three dimensional polymeric network system which has a significant amount of water imbibing capacity despite being soluble in it. Because of the potential applications of hydrogels in different fields such as biomedical, pharmaceutical, personal care products, biosensors, and cosmetics, it has become a very popular area of research in recent decades. Hydrogels, prepared from synthetic polymers and petrochemicals are not ecofriendly. For preparing biodegradable hydrogels, most available plant polysaccharides like starch are utilized. In its structure, starch has a large number of hydroxyl groups that aid in hydrogel networking. For their easy availability and applications, starch-based hydrogels (SHs) have gained huge attention. Moreover, SHs are non-toxic, biocompatible, and cheap. For these reasons, SHs can be an alternative to synthetic hydrogels. The main focus of this review is to provide a comprehensive summary of the structure and characteristics of starch, preparation, and characterization of SHs. This review also addresses several potential multidimensional applications of SHs and shows some future aspects in accordance.

Graphic abstract