Results 211 to 220 of about 907,408 (299)

Deep learning-based differential diagnosis of major depression and bipolar disorder using microglia-cellular sensors and patient-derived small extracellular vesicles. [PDF]

Sci Rep
Zambrano J, Luarte A, Contreras J, Perez JP, Yantén-Fuentes L, Prieto M, Lazcano P, Wyneken U, Perez CA.   +8 more
europepmc   +1 more source

Family Ownership and ESG Performance: The Moderating Role of Sustainability Committee and ESG‐Linked Executive Compensation

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Grounded in agency theory, this article examines the relationship between family ownership concentration and environmental, social, and governance (ESG) performance, and analyzes the moderating role of sustainable governance mechanisms. Specifically, it assesses whether sustainability committees and ESG‐linked executive compensation moderate ...
Pasquale Latella, Roberta Pisani, Fabio Quarato, Paolo Tenuta   +3 more
wiley   +1 more source

Social capital's association with self-reported health outcomes in the rural south: variations by demographic subgroup. [PDF]

Front Public Health
Bigger LM, McGee RE, Smith A, Haardörfer R, Hermstad A, Kegler MC.   +5 more
europepmc   +1 more source

CEO Duality and Corporate Social Responsibility. A Literature Review With a Focus on Country Effects

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT In recent years, many researchers have become interested in the relationship between CEO duality (where one individual serves as both CEO and board chair) and CSR outcomes. Given the varied research results, this structured literature review concentrates on the country effects of this dynamic link.
Patrick Velte
wiley   +1 more source

Identifying strategies to characterize the diversity of the MS population in Canada: a nominal group study. [PDF]

Front Neurol
Marrie RA, Fakolade A, Maxwell CJ, Rotstein DL, Tremlett H, Yeh EA, Finlayson M.   +6 more
europepmc   +1 more source

EventFlow: Real‐time neuromorphic event‐driven classification of two‐phase boiling flow regimes

Droplet, EarlyView.
We present a real‐time flow regime classification framework that integrates neuromorphic event‐driven sensing with deep recurrent neural networks. Unlike traditional frame‐based approaches, our system captures sparse event streams from an event‐based camera, representing only the dynamic brightness changes at the individual pixel level.
Sanghyeon Chang, Srikar Arani, Nishant Sai Nuthalapati, Youngjoon Suh, Nicholas Choi, Siavash Khodakarami, Md Rakibul Hasan Roni, Nenad Miljkovic, Aparna Chandramowlishwaran, Yoonjin Won   +9 more
wiley   +1 more source

Capitalising (on) industrial epidemics: examining the influence of the 'Big Three' asset managers on corporate governance in key health-harming commodity industries. [PDF]

Global Health
Wood B, Slater S, Friel S, Schram A, Frank N, Sacks G.   +5 more
europepmc   +1 more source

Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN

Deep Underground Science and Engineering, EarlyView.
A data preprocessing workflow is proposed to address challenges in rockburst data analysis. Coupled algorithms preprocess the data set, and hyperband optimization is used to enhance RNN performance. Results show that preprocessing improves accuracy, while dense layers enhance model stability and prediction performance.
Yong Fan, Chenxi Yin, Guangdong Yang, Shengyong Ding, Bin Tian   +4 more
wiley   +1 more source

Methodological review: Prioritizing a future research agenda for overcoming immunization implementation barriers in Pakistan. [PDF]

Public Health Pract (Oxf)
Ahmed W, Ummad A, Tahir M, Sharkey A, Bhurgri AK, Naseer O, Habib S, Memon Z.   +7 more
europepmc   +1 more source

Real‐time lithology identification while drilling based on drill cuttings image analysis with ensemble learning

Deep Underground Science and Engineering, EarlyView.
A lithology identification while drilling method was developed, integrating an automated cuttings sampling system, a smart drilling rig, and an ensemble learning model. Underground trials achieved 97.42% accuracy in real‐time identification of cuttings lithology and composition, enhancing hazard management and supporting unmanned drilling technology in
Kun Li, Ting Ren, Ningping Yao, Jon Roberts, Haitao Song, Zhongbei Li, Xueqiu He, Liang Zhao   +7 more
wiley   +1 more source