Results 151 to 160 of about 24,814 (240)
Semi-Supervised Clustering of Sparse Graphs: Crossing the Information-Theoretic Threshold. [PDF]
Sheng J, Strohmer T.
europepmc +1 more source
When Does Top Management Team Diversity Matter in Large Organizations?
ABSTRACT Top management teams (TMTs) drive strategic leadership, but there is little clarity on when the composition of these upper echelons most impacts organization performance. Drawing from the categorization‐elaboration model, we study an 18‐year sample of approximately 4500 organizations and over 32 000 executives and find a positive relationship ...
Frances Fabian +2 more
wiley +1 more source
The Thermomajorization Polytope and Its Degeneracies. [PDF]
Vom Ende F, Malvetti E.
europepmc +1 more source
ABSTRACT As organizations increasingly adopt human‐AI teams (HATs), understanding how to enhance team performance is paramount. A crucially underexplored area for supporting HATs is training, particularly helping human teammates to work with these inorganic counterparts.
Caitlin M. Lancaster +5 more
wiley +1 more source
k-Clique counting on large scale-graphs: a survey. [PDF]
Çalmaz B, Ergenç Bostanoğlu B.
europepmc +1 more source
Fast Simulation of Wide‐Angle Coherent Diffractive Imaging
The propagation multi‐slice Fourier transform method is introduced as an accurate and efficient approach for describing light scattering for arbitrarily shaped objects. Its exceptional suitability for simulating coherent diffractive imaging of nanoparticles in the XUV and soft X‐ray range is demonstrated.
Paul Tuemmler +3 more
wiley +1 more source
The findings presented in this manuscript recommend the Ti‐22Zr‐11Nb‐2Sn alloy as a possible alternative to Nitinol for use in biomedical devices, especially in the large‐scale manufacturing of self‐expandable vascular stents used in angioplasty. ABSTRACT Nowadays, for applications such as coronary stents, the most widely used materials are Nitinol or ...
Gaëtan Cabon +6 more
wiley +1 more source
Machine Learning for Predictive Modeling in Nanomedicine‐Based Cancer Drug Delivery
The integration of AI/ML into nanomedicine offers a transformative approach to therapeutic design and optimization. Unlike conventional empirical methods, AI/ML models (such as classification, regression, and neural networks) enable the analysis of complex clinical and formulation datasets to predict optimal nanoparticle characteristics and therapeutic
Rohan Chand Sahu +3 more
wiley +1 more source

