Eco-Driving with Deep Reinforcement Learning at Signalized Intersections Considering On-the-fly Queue Dissipation Estimation and Lane-Merging Disturbances See

Eco-driving research has grown significantly over the past decade, increasingly incorporating real-world traffic and road conditions such as road gradients, lane changes, and queue effects. However, most existing studies that account for queue effects are limited to single-lane scenarios, without ...

Targeting Runoff Hotspots for Sustainable Rainwater Harvesting in Arid Regions See

Rainwater harvesting (RWH) is a crucial strategy for enhancing water availability in arid regions and supporting local livelihoods, including those of Bedouin communities. Rainwater. This study focuses on Wadi Sudr, located opposite Ras Sudr city in the Sinai Peninsula, to identify optimal&#...

Aquifer-specific flood forecasting using machine learning: A comparative analysis for three distinct sedimentary aquifers See

Accurate flood prediction is critical for avoiding catastrophic impacts, but its difficulty varies by geological location. This study evaluates four machine learning models – TFT, Informer, LSTM, and XGBoost – for multi-horizon flood forecasting (1-4 days), across Limestone, Chalk, and Greensand&...

Flow boiling in micro-pin fin heat exchangers and comparison with correlations See

The thermo-fluid performance of micro-pin fin heat exchangers has recently received extensive attention from the research community engaged in developing thermal management systems for high heat flux devices. Two-phase flow in these geometries could provide better thermal performance compared to ...

Assessing microbially influenced corrosion of titanium as novel canister material for geological disposal facilities See

In response to the growing global inventory of nuclear waste and the urgent need for secure long-term disposal solutions, geological disposal facilities (GDFs), also known as deep geological repositories, are being pursued worldwide. Several national programmes, including those in the UK, Ja...

Investigating the Impact of Musical Soundscapes on Well-being: A Qualitative Focus Group Study Using Arts-Based Methods See

This study explores the impact of musical soundscapes on well-being through a qualitative inductive thematic analysis. Utilizing focus groups and participatory arts-based methods, participants engaged with meditative soundscapes periodically over a week, sharing their responses through text, voice, and...

Hybrid and deep learning architectures for predictive maintenance: Evaluating LSTM, and attention-based LSTM-XGBoost on turbofan engine RUL See

Accurate prediction of a machines Remaining Useful Life (RUL) underpins modern, costeffective predictive-maintenance programmes. This paper proposes a two-stage hybrid pipeline that couples sequence learning with tree-based residual modelling. In stage 1, 50-cycle windows of NASA C-MAPSS sensor data (...

Optimal Set of Features for Leukaemia Images with Extracted Areas of Interest See

Feature extraction was found effective in image classification across various studies. From a dataset containing leukemia images of four main categories 17 features were extracted including Haralick texture features, the size and number of white blood cells, and average colours. The process&...

Inter- and intra-bacterial strain diversity remains the “elephant in the (living) room” See

Acinetobacter baumannii is an opportunistic Gram-negative bacterial pathogen responsible for severe nosocomial infections worldwide. Resistance to last-resort antibiotics causes A. baumannii to be ranked as a top priority for the research and development of new antibiotics by the WHO and an ...