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In this article the authors investigate whether there is a correlation between age of a person and their outlook on global issues such as technology, politics, and environment. They find a correlation between increased age and decreased optimism. However regardless of age, they find that respondents believe certain characteristics such as technology and willingness to change are essential for improvements.

Domestic waste classification using convolutional neural network

Habitat loss and global warming remain present-day issues that continue to place pressures on various ecosystems and their species. The authors of this paper performed studies over two years to understand whether birds feed more from wooded or exposed areas.

There have been several issues concerning the water quality in Ulaanbaatar, Mongolia in the past few years. This study, we collected 28 samples from 6 districts of Ulaanbaatar to check if the water supply quality met the standards of the World Health Organization, the Environmental Protection Agency, and a Mongolian National Standard. Only three samples fully met all the requirements of the global standards. Samples in Zaisan showed higher hardness (>120 ppm) and alkalinity levels (20–200 ppm) over the other districts in the city. Overall, the results show that it is important to ensure a safe and accessible water supply in Ulaanbaatar to prevent future water quality issues.

he rapid growth of the human population is driving food crises in Thailand and Southeast Asia, while contributing to global food insecurity and a larger carbon footprint. One potential solution is cultivating duckweed (Wolffia globosa) for consumption, as it grows quickly and can provide an alternative protein source. This research explored two methods to optimize duckweed cultivation: using phosphorus- and nitrogen-rich growing media and plant growth-promoting bacteria (PGPB).

This article investigates differences in gene expression in the brains of patients with and without Parkinson's disease. The authors identify a crucial transcriptional regulator may be a relevant target for future therapeutic treatment for Parkinson's disease.

The global issue of water quality has led to the use of machine learning models, like ANN and SVM, to predict water potability. However, these models can be complex and resource-intensive. This research aimed to find a simpler, more efficient model for water quality prediction.

Arsenic contamination in rice, caused by the use of arsenic-laden groundwater for irrigation, is a growing global concern, affecting over 150 million people. To address this, researchers hypothesized that genetically modifying rice plants with arsenic-resistant genes could reduce arsenic uptake and allow the plants to detoxify arsenic, making them safer to consume.

Using machine learning to predict the risk of algae bloom

Childhood abuse has severe and lasting effects throughout an individual's life, and may even have long-term biological effects on individuals who suffer it. To learn more about the effects of abuse in childhood, Li and Yearwood analyze gene expression data to look for genes differentially expressed genes in individuals with a history of childhood abuse.