Results 141 to 150 of about 95,488 (287)

Beyond Visible Differences: An Experimental Investigation Into the Role of Cognitive Diversity Awareness in Shaping Team Dynamics

Strategic Change, EarlyView.
ABSTRACT The relationship between team composition and organizational outcomes is a critical topic in many managerial and business contexts. In this study, we utilize an experimental research method to examine the impact of cognitive diversity on team dynamics.
Jantunen Ari, Mittone Luigi, Morreale Azzurra, Tuppura Anni, Tarkiainen Anssi, Vu Thi‐Thanh‐Tam   +5 more
wiley   +1 more source

Predicting externalizing symptom trajectories in U.S. National Guard recruits: The role of adverse childhood experiences

Journal of Traumatic Stress, EarlyView.
Abstract Adverse childhood experiences (ACEs) are strongly associated with increased risk of externalizing problems. Despite their prevalence in military populations, limited research links ACEs to longitudinal externalizing problem trajectories during military service transition.
Ali F. Sloan, Tristan Bron, Craig A. Marquardt, Seth G. Disner, Siamak Noorbaloochi, Melissa A. Polusny, Jonathan D. Schaefer   +6 more
wiley   +1 more source

Machine Learning for Predictive Modeling in Nanomedicine‐Based Cancer Drug Delivery

Med Research, EarlyView.
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, Sanchit Arora, Dinesh Kumar, Ashish Kumar Agrawal   +3 more
wiley   +1 more source

Extending the hyper‐logistic model to the random setting: New theoretical results with real‐world applications

Mathematical Methods in the Applied Sciences, EarlyView.
We develop a full randomization of the classical hyper‐logistic growth model by obtaining closed‐form expressions for relevant quantities of interest, such as the first probability density function of its solution, the time until a given fixed population is reached, and the population at the inflection point.
Juan Carlos Cortés, Ana Navarro‐Quiles, Sorina Madalina Sferle   +2 more
wiley   +1 more source

Enhancing vehicle-mountable multiple object tracking systems with embeddable Ising machines. [PDF]

Nat Commun
Tatsumura K, Hamakawa Y, Yamasaki M, Oya K, Fujimoto H.   +4 more
europepmc   +1 more source

The Linearized Inverse Boundary Value Problem in Strain Gradient Elasticity

Mathematical Methods in the Applied Sciences, EarlyView.
ABSTRACT In this paper we study the linearized version of the strain gradient elasticity equation in ℝ2$$ {\mathbb{R}}^2 $$ with constant coefficients and we prove that one can determine the two Lamé coefficients λ,μ$$ \lambda, \mu $$ as well as the internal strain gradient parameter g$$ g $$, as indicated by Mindlin in his revolutionary papers in 1963–
Antonios Katsampakos, Antonios Charalambopoulos   +1 more
wiley   +1 more source

Human-Inspired Holistic Control for Mobile Humanoid Robots. [PDF]

Biomimetics (Basel)
Wang Z, Ren X, Tang H, Jin H, Zhao J.
europepmc   +1 more source

Calibration‐Free GRAPE pTx Pulses for Homogeneous Spatial‐Selective Excitation at 7T

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose Extend the universal pulse GRAPE formalism to pulses with a defined spectral response, and apply the concept to spatial selection. Methods We added Bloch simulations at several frequencies for each voxel to the pulse calculation to create universal spectrally‐selective GRAPE pulses.
Daniel Löwen, Eberhard D. Pracht, Marten Veldmann, Vincent Gras, Franck Mauconduit, Nicolas Boulant, Tony Stöcker   +6 more
wiley   +1 more source

Latent trajectories in autistic individuals: A systematic review. [PDF]

Autism
Hiralal KR, Dieleman GC, Kok BR, Diederen LD, Duman RP, Hillegers MH, Mous SE.   +6 more
europepmc   +1 more source

Dynamics Modeling of Robot Manipulators Based on Deep Lagrangian Network and Torque Separation Technique

International Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT In recent years, learning robot manipulator dynamics with deep networks has been extensively studied, as it avoids deriving the analytical expression of the robot dynamics equations. In particular, deep Lagrangian networks that incorporate the prior knowledge of Lagrangian mechanics into the deep networks have shown prominent advantages in ...
Xianglong Liang, Tianyu Gao, Zhikai Yao, Jianyong Yao   +3 more
wiley   +1 more source