Results 101 to 110 of about 219,190 (262)

Early economic evaluation of magnetic resonance imaging for prostate cancer detection in primary care

BJUI Compass
Objectives To explore the potential impacts of incorporating prebiopsy magnetic resonance imaging into primary care as a triage test within the prostate cancer diagnostic pathway.
Samuel William David Merriel, Peter Buttle, Sarah J. Price, Nick Burns‐Cox, Fiona M. Walter, William Hamilton, Anne E. Spencer   +6 more
doaj   +1 more source

Operations Research‐Based Formalisation and Design of Sustainable Reverse Logistics for E‐Waste Supply Chains

Business Strategy and the Environment, EarlyView.
ABSTRACT This study demonstrates how a profitable, lean, and environmentally responsible e‐waste reverse logistics system can be designed using integrated Operations Research (OR) techniques. Addressing the growing urgency of responsible consumption (UN SDG 12) and the projected rise of the e‐waste sector to USD 137.60 billion by 2029, the research ...
Sheeba Pathak, Hajar Fatorachian
wiley   +1 more source

Advancing Safety and Sustainability in Nanomaterials Industry: Methodological, Business, and Regulatory Implications

Business Strategy and the Environment, EarlyView.
ABSTRACT The rapid proliferation of chemicals and nanomaterials (CNMs) has resulted in significant cross‐sector innovation, delivering product enhancements such as improved UV protection and waterproof textiles. However, these advances present urgent challenges regarding human safety, environmental hazards, and regulatory compliance. Despite the recent
Alessandra Fiorucci, Mario Miozza, Genc Alimehmeti, Alessandra Bonoli, Angelo Paletta   +4 more
wiley   +1 more source

A multi-state dynamic framework for electric ship BMS reliability evaluation: time-interval sequential rules, multi-domain CCF, and closed-form CTMC solutions

Frontiers in Marine Science
IntroductionAiming at the progressive failure and multi-domain coupling risks of battery management systems (BMS) for electric ships operating in marine environments, existing reliability evaluation methods fail to simultaneously characterize multi-state
Hongbin Wei, Hongbin Wei, Yunbo Li
doaj   +1 more source

Harnessing machine learning and optimization for informed chemical engineering decisions: A styrene reactor analysis

The Canadian Journal of Chemical Engineering, EarlyView.
This study shows that integrating multiple machine learning models with optimization and decision‐making improves chemical process design, and that a consensus‐based strategy across models provides more robust and reliable operating recommendations than any single model, especially under limited or noisy data conditions.
Farough Agin, Clémence Fauteux‐Lefebvre, Jules Thibault   +2 more
wiley   +1 more source

Using Cuckoo Search Algorithm to Predict Corporate Financial Risks and Alleviate Economic Uncertainty

International Journal of Computational Intelligence Systems
Predicting financial risk accurately is crucial for maintaining economic sustainability and investor trust in an era of increasing economic volatility and business instability. There are several problems with traditional financial risk assessment models,
Muqiao Cai
doaj   +1 more source

Modified F‐tests for assessing tree radial growth under linear‐circular regression models with correlated errors: A comprehensive toolbox rooted in G. E. P. Box's theorems

Canadian Journal of Statistics, EarlyView.
Abstract Annual tree growth is a complex biological process. Modelling radial growth in the trunk by linear‐circular regression with one mode and correlated errors has allowed the definition and assessment of a preferred direction for 1 and 2 years. Here, modified F$$ F $$‐tests are presented for 3 years, 1 mode/year; 1 year, 2 modes for possible main ...
Pierre Dutilleul, Tomoaki Imoto, Kunio Shimizu   +2 more
wiley   +1 more source

Probabilistic prediction of rate‐dependent rock strength using natural gradient boosting and Gaussian process regression

Deep Underground Science and Engineering, EarlyView.
Probabilistic natural gradient boosting and Gaussian process regression models accurately predict rate‐dependent rock strength across lithologies. Static strength and strain rate dominate, while geometric factors have minimal influence, enabling interpretable and uncertainty‐aware predictions for dynamic geomechanical applications. Abstract The dynamic
Hadi Fathipour‐Azar
wiley   +1 more source

Generative Models in Inorganic Crystals Discovery and Inverse Design

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
Generative inverse‐design samples from the vast inorganic crystal design space by starting from target properties such as band gap, stability, and ion transport. This Review examines the representations, generative models, and validation workflows needed to translate candidate structures into stable, potentially synthesizable materials for applications
Tao Li, Xiaolin Liu, Fei Wang, Yan Xiong, Yu Chen, Yan Zhao   +5 more
wiley   +1 more source

Predictive accuracy of boosted regression model in estimating risk of venous thromboembolism following minimally invasive radical surgery in pharmacological prophylaxis-naïve men with prostate cancer

World Journal of Surgical Oncology
Background Venous thromboembolism (VTE) is a potentially life-threatening but preventable complication after urological surgery. Physicians are faced with the challenges of weighing the risks and benefits of thromboprophylaxis given scanty evidence for ...
Chie Hui Leong, Sushil Rodrigues Ranjan, Anna Javed, Basim S.O. Alsaedi, Ghulam Nabi   +4 more
doaj   +1 more source