Stakeholder perspectives on the costs and benefits of circular construction.

The construction industry significantly impacts the environment through natural resource depletion and energy consumption, leading to environmental degradation. Circular Economy (CE) material efficiency strategies-such as material reuse, design for disassembly, prefabrication, and recycling-offer promising solutions for reducing resource consumption and waste. This paper explores stakeholders' perspectives on the costs and benefits of implementing CE material efficiency strategies in the construction industry, using the 3-R (Reduce, Reuse, Recycle) framework.

Deep-m5U: a deep learning-based approach for RNA 5-methyluridine modification prediction using optimized feature integration.

Background: RNA 5-methyluridine (m5U) modifications play a crucial role in biological processes, making their accurate identification a key focus in computational biology. This paper introduces Deep-m5U, a robust predictor designed to enhance the prediction of m5U modifications. The proposed method, named Deep-m5U, utilizes a hybrid pseudo-K-tuple nucleotide composition (PseKNC) for sequence formulation, a Shapley Additive exPlanations (SHAP) algorithm for discriminant feature selection, and a deep neural network (DNN) as the classifier.

The social determinants of distress in South Asian men with long-term conditions: a qualitative study.

Background: People with long-term physical conditions are more likely to experience distress, depression or anxiety. Physical-mental comorbidity is associated with lower quality of life, poorer clinical outcomes, and increased mortality than physical conditions alone. South Asians (SAs) are the largest minority group in the UK, and more likely to have long-term conditions (LTCs) such as diabetes and heart disease.