Visible light induced photocatalytic degradation of norfloxacin using xC-TiO.

In recent years, antibiotic pollution has become a major environmental concern. The extensive production and widespread use of prescribed antibiotics have significantly impacted ecosystems. The main objective of the present study is to investigate the photocatalytic degradation of the antibiotic norfloxacin (NFX) under visible light.

Cropland expansion links climate extremes and diets in Nigeria.

Climate change threatens smallholder agriculture and food security in the Global South. While cropland expansion is often used to counter adverse climate effects despite ecological trade-offs, the benefits for diets and nutrition remain unclear. This study quantitatively examines relationships between climate anomalies, forest loss from cropland expansion, and dietary outcomes in Nigeria, Africa's most populous country.

Determination of Westcott g-factors for the assay of non-1/v nuclides using k-NAA.

This study examines the impact of the Westcott g-factor on the concentration of elements like In, Ir, Re, Yb, Eu and Lu, measured using neutron capture reactions (n,γ), specifically focusing on those reactions, whose thermal neutron capture cross-sections (σ ) deviate from the conventional '1/v' behaviour. These measurements are quantified using k₀-based neutron activation analysis. The Westcott g-factor for the non-1/v nuclides was calculated using the characterized neutron temperature (T) at PFTS irradiation channel of KAMINI reactor.

Advancing Delirium Treatment Trials in Older Adults: Recommendations for Future Trials From the Network for Investigation of Delirium: Unifying Scientists (NIDUS).

Objectives: To summarize the delirium treatment trial literature, identify the unique challenges in delirium treatment trials, and formulate recommendations to address each in older adults.

Design: A 39-member interprofessional and international expert working group of clinicians (physicians, nurses, and pharmacists) and nonclinicians (biostatisticians, epidemiologists, and trial methodologists) was convened. Four expert panels were assembled to explore key subtopics (pharmacological/nonpharmacologic treatment, methodological challenges, and novel research designs).

SVM directed machine learning classifier for human action recognition network.

Understanding human behavior and human action recognition are both essential components of effective surveillance video analysis for the purpose of guaranteeing public safety. However, existing approaches such as three-dimensional convolutional neural networks (3D CNN) and two-stream neural networks (2SNN) have computational hurdles due to the significant parameterization they require. In this paper, we offer HARNet, a specialized lightweight residual 3D CNN that is built on directed acyclic graphs and was created expressly to handle these issues and achieve effective human action detection.