Results 61 to 70 of about 33,499 (259)
Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei +9 more
wiley +1 more source
Some Sources of Misunderstandings in Intercultural Business Communication
It is always a big challenge for all types of companies anywhere in the world to survive in the globalised and accelerated world. Their primary objective is to stay competitive, keep or even enlarge their market share while keeping their costs at a ...
Tímea Lázár
doaj +1 more source
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu +3 more
wiley +1 more source
Book Review: Understanding the Misunderstandings in Pilot-Controller Dialogue
Misunderstandings in any environment can be detrimental, if not counterproductive, to the intentions, expectations, or objective(s) of any communication, but in complex airspace congested by heavy traffic, pilot-controller transmissions, and various ...
Jason M Newcomer
doaj +1 more source
Fundamental misunderstandings [PDF]
P, Rutledge, S, Myles
openaire +2 more sources
Energetic Offset in Organic Solar Cells‐ Importance, Confusion and Outlook
Energetic offsets in organic solar cells (OSCs) remain a subject of debate due to measurement‐ and lab‐dependent discrepancies. This Perspective clarifies the physical origins of these variations and identifies temperature‐dependent electro‐optical methods as a reliable approach to obtain consistent offset values.
Nakul Jain +5 more
wiley +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Trions as Fundamental Species in Chemically Doped Polymer Semiconductors
This work shows that exciton–charge carrier coupling in doped polymer semiconductors gives rise to multi‐particle states, including trions—quasiparticles consisting of two holes and one electron under p‐doping—and bound exciton‐hole pairs, as identified through spectroscopic and theoretical analysis.
Hongmo Li +23 more
wiley +1 more source
Mixed‐cation lead mixed‐halide perovskites suffer from structural instabilities linked to nanoscale heterogeneity. To probe this non‐destructively, a low‐dose, concurrent 4D‐STEM and EDX methodology has been developed. Examining a (FA0.83Cs0.17)Pb(I0.8Br0.2)3 film revealed a complex mosaic of coexisting crystal structures. Crucially, local deficiencies
Jinseok Ryu +6 more
wiley +1 more source
Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback
BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat +4 more
wiley +1 more source

