Results 81 to 90 of about 4,399 (316)

Simulations for Event-Clock Automata [PDF]

Logical Methods in Computer Science
Event-clock automata (ECA) are a well-known semantic subclass of timed automata (TA) which enjoy admirable theoretical properties, e.g., determinizability, and are practically useful to capture timed specifications.
S Akshay, Paul Gastin, R Govind, B Srivathsan   +3 more
doaj   +1 more source

Macrophage–Derived Ferritin Exacerbates Silica‐Induced Pulmonary Fibrosis via PIK3R2‐Mediated Fibroblast Differentiation

Advanced Science, EarlyView.
This study identifies ferritin as a pivotal mediator of silica‐induced pulmonary fibrosis. Macrophage‐derived ferritin drives fibroblast‐to‐myofibroblast differentiation via the PIK3R2/SMAD pathway, while ferritin knockdown alleviates fibrosis. These findings define ferritin as both a biomarker and pathogenic driver, highlighting ferritin‐PIK3R2 ...
Liqun Wang, Xuxi Chen, Hongying Quan, Rui Qian, Shuyu Gong, Qiurong He, Ying Gao, Ajia Axi, Manyu Zhao, Qin Zhang, Ling Zhang, Lijun Peng, Xin Sun, Ben Zhang, Yuqin Yao   +14 more
wiley   +1 more source

Safety and Liveness of Quantitative Properties and Automata [PDF]

Logical Methods in Computer Science
Safety and liveness stand as fundamental concepts in formal languages, playing a key role in verification. The safety-liveness classification of boolean properties characterizes whether a given property can be falsified by observing a finite prefix of an
Udi Boker, Thomas A. Henzinger, Nicolas Mazzocchi, N. Ege Saraç   +3 more
doaj   +1 more source

How AI Shapes the Future Landscape of Sustainable Building Design With Climate Change Challenges?

Advanced Science, EarlyView.
This review examines how artificial intelligence reshapes sustainable building design faced with climate change challenges. The authors synthesize existing studies to demonstrate AI's transformative potential across design lifecycle phases from climate‐aware form generation to performance optimization.
Pengyuan Shen, Xiaoni Gao, Shuai Lu, Yi Zhang, Xing Zheng, Matthaios Santamouris   +5 more
wiley   +1 more source

Citizen Engagement for Social and Technological Innovation in Sustainable Energy Systems

Advanced Energy and Sustainability Research, EarlyView.
This study underscores the potential of citizen participation in the energy transition by providing insights to foster citizen‐driven innovation. An analysis of energy communities, one of the most dynamic innovations in the energy sector, reveals that these models can be citizen‐led initiatives regarding their operational and organizational structure ...
Ana Belén Cristóbal, Cristina Sanz‐Cuadrado, Kiane Alves e Silva, Luis Narvarte   +3 more
wiley   +1 more source

Heterogeneity in Food Price Inflation Convergence Across the EU: Evidence From Club Dynamics and Structural Breaks

Agribusiness, EarlyView.
ABSTRACT This study examines food price inflation rate convergence among EU27 Member States from 2005 to 2024, focusing on structural breaks, external shocks, and regional disparities. Using panel unit root tests and club convergence analysis, the findings reveal no overall convergence but identify multiple convergence clubs.
Tibor Bareith, Imre Fertő
wiley   +1 more source

Construction of a Feedback Comment Analysis Model for Evaluation of Endoscopic Surgical Skill

Annals of Gastroenterological Surgery, EarlyView.
ABSTRACT Background Surgical education and skill assessments are important in improving surgical skills. However, instructors' comments tend to be complex and unorganized, with varying content and categories. This study aimed to develop a natural language processing (NLP) model to automatically classify feedback comments on surgical procedures and ...
Shusaku Iwai, Shin Takenaka, Daichi Kitaguchi, Hiroki Matsuzaki, Kei Nakajima, Yuya Takabe, Nobuyoshi Takeshita, Masaaki Ito   +7 more
wiley   +1 more source

Which Method Best Predicts Postoperative Complications: Deep Learning, Machine Learning, or Conventional Logistic Regression?

Annals of Gastroenterological Surgery, EarlyView.
Deep learning has shown promise in predicting postoperative complications, particularly when using image or time‐series data. However, on tabular clinical data such as the NCD, it often underperforms compared to conventional machine learning. Integrating multimodal data may enhance predictive accuracy and interpretability in surgical care.
Ryosuke Fukuyo, Masanori Tokunaga, Hiroyuki Yamamoto, Hideki Ueno, Yusuke Kinugasa   +4 more
wiley   +1 more source

Psoas Muscle Volume as a Predictor of Postoperative Complications in Patients Undergoing Emergency Surgery for Strangulated Small Bowel Obstruction: A Retrospective Single‐Center Study

Annals of Gastroenterological Surgery, EarlyView.
This retrospective study identified low preoperative psoas muscle volume, measured by computed tomography, as an independent predictor of postoperative complications in patients undergoing emergency surgery for strangulated small bowel obstruction. Low psoas muscle volume, particularly in older adults, was associated with cardiopulmonary and systemic ...
Takuya Shiraishi, Chika Katayama, Yuta Shibasaki, Chika Komine, Takuhisa Okada, Akihiko Sano, Makoto Sakai, Hiroomi Ogawa, Ken Shirabe, Hiroshi Saeki   +9 more
wiley   +1 more source

A collection of tools for making automata theory and formal languages come alive [PDF]

, 1997
Susan H. Rodger, Anna Bilska‐Kos, Kenneth H. Leider, Magdalena Procopiuc, Octavian Procopiuc, Jason R. Salemme, Edwin Tsang   +6 more
openalex   +1 more source