Results 111 to 120 of about 68,998 (258)

Blockchain‐Based Smart Contracts in US Specialty Crop Marketing: Grower Preferences and Adoption Potential

Agribusiness, EarlyView.
ABSTRACT Using survey and discrete choice experiment data, we examined US specialty crop growers' preferences for marketing contract attributes in the context of emerging blockchain‐based technologies and expanding traceability initiatives. Results show that farmers preferred traditional written contracts but might be willing to accept digital ...
Elizabeth Canales, Alba J. Collart, Matthew G. Interis, Esther Mmenaa Agyemang‐Duah   +3 more
wiley   +1 more source

Weather Attention in Online Discourse and Price Uncertainty in Agricultural Futures Markets

Agribusiness, EarlyView.
ABSTRACT Weather is a central determinant of production risk in agricultural markets, but markets respond not only to weather conditions themselves, but also to how those conditions are noticed, framed, and interpreted in public discourse. In this setting, real‐time online weather discussions may shape price uncertainty by influencing how market ...
Mario A. Ortez, Olga Isengildina Massa, Michael Liam Smith, Nicole Olynk Widmar   +3 more
wiley   +1 more source

The extended model of online privacy concern

, 2019
U knjizi se opisuje istraživanje provedeno na projektu Sveobuhvatni model zabrinutosti za privatnost u online okruženju (PRICON). Nakon pregleda literature i definicije privatnosti i zabrinutosti za privatnost u općem i komercijalnom okruženju, autori razlažu pitanje definicije online privatnosti.
openaire   +1 more source

Regional Disparities in Case Volumes and Surgeon Distribution in Gastroenterological Surgery

Annals of Gastroenterological Surgery, EarlyView.
ABSTRACT Background Regional disparities in surgical resources may influence the delivery and sustainability of gastroenterological surgery, particularly in countries experiencing rapid population aging and depopulation. Methods This nationwide cross‐sectional study used data from the Japanese National Clinical Database to examine temporal trends (2013–
Hiroshi Hasegawa, Hiraku Kumamaru, Momoko Ara, Yoshihiro Kakeji, Hideko Yamauchi, Masafumi Inomata, Sadako Akashi‐Tanaka, Koji Ito, Shinji Itoh, Hidetoshi Eguchi, Kazumi Kawase, Yoshiaki Kinoshita, Yuki Kiyozumi, Shogo Kobayashi, Ikuko Shibasaki, Chiyoe Shirota, Hiroyuki Suzuki, Chie Takasu, Aoi Fujikawa, Saki Bessho, Kiyomi Horiuchi, Kosei Maemura, Ayako Maruo, Takuya Miura, Yuji Miyamoto, Toshiki Yajima, Ayuko Yasuda, Toshiharu Yamaguchi, Tadashi Iwanaka, Hideo Baba, Akinobu Taketomi   +30 more
wiley   +1 more source

Return‐To‐Work and Working Status After Surgery for Gastric and Esophageal Cancer: A Prospective Observational Study

Annals of Gastroenterological Surgery, EarlyView.
In this multicenter prospective study of 158 working‐age patients undergoing curative‐intent surgery for gastric or esophageal cancer, 78.5% were working at 18 months. Postoperative appetite loss, financial difficulties, and ≥ 10% weight loss at 6 months were associated with non‐working status.
Kentaro Goto, Shigeo Hisamori, Kohei Ueno, Hiroyasu Abe, Ryosuke Okamura, Hisahiro Hosogi, Yoshito Yamashita, Dai Manaka, Hiroaki Hata, Tatsuto Nishigori, Sanae Nakajima, Michihiro Yamamoto, Koichi Kinoshita, Shintaro Okumura, Masazumi Sakaguchi, Shigeru Tsunoda, Yu Sakagami, Koya Hida, Kazutaka Obama   +18 more
wiley   +1 more source

Accelerating Primary Screening of USP8 Inhibitors from Drug Repurposing Databases with Tree‐Based Machine Learning

Advanced Intelligent Discovery, EarlyView.
This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng, Sharon Ai Er Lam, Wei Chun Lim, Hannah Hui Min Toh, Shi Jun Ang   +4 more
wiley   +1 more source

Machine Learning‐Enhanced Random Matrix Theory Design for Human Immunodeficiency Virus Vaccine Development

Advanced Intelligent Discovery, EarlyView.
This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah, Muhammad Zulqarnain Zeb, Muhammad Husnain Zeb, Babar Shabbir   +3 more
wiley   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Talk to Your Data: An Agentic Artificial Intelligence‐Driven Decision‐Support Framework for Prosumer Energy Optimization and Recommendations

Advanced Intelligent Systems, EarlyView.
An agentic AI‐driven decision‐support framework for prosumers is proposed, integrating PV generation, load profiling, and multihorizon optimization within a four‐agent architecture. The approach significantly reduces grid dependence, enhances self‐sufficiency and prevents system oversizing.
Adela BÂRA, Simona‐Vasilica OPREA
wiley   +1 more source

Integrating Reinforcement Learning With Explainable Artificial Intelligence for Real‐Time Clinical Decision Support in Dynamic Healthcare Environments

Advanced Intelligent Systems, EarlyView.
A hybrid Reinforcement Learning–Explainable AI framework integrates SHAP and LIME explanations directly into a Deep Q‐Network inference loop for real‐time ICU decision support. Trained on 18 142 mechanically ventilated stays from the eICU database, the system attains 93.0% decision accuracy, 20% fewer errors than RL alone, and a 91% clinician trust ...
Jannatul Ferdaus Disha, MD Faiaz Zaman Dehan, Kazi Md. Tanvir Anzum   +2 more
wiley   +1 more source