Results 131 to 140 of about 19,047 (251)
This work presents lightweight, lignin‐derived carbon fiber current collectors that enable controlled lithium deposition. Structural defects and intermediate‐sized pores stabilize pre‐nucleation quasi‐metallic lithium clusters, promoting uniform lithium plating and stripping.
Samantha L. S. Southern +13 more
wiley +1 more source
Using Indoor Movement Complexity in Smart Homes to Detect Frailty in Older Adults: Multiple-Methods Case Series Study. [PDF]
Wuestney K, Cook D, Van Son C, Fritz R.
europepmc +1 more source
Unleashing the Power of IoT: A Comprehensive Review of IoT Applications and Future Prospects in Healthcare, Agriculture, Smart Homes, Smart Cities, and Industry 4.0. [PDF]
Chataut R, Phoummalayvane A, Akl R.
europepmc +1 more source
ABSTRACT Amidst a recent surge in US goat meat imports to meet growing demand, this study contributes to the meat demand literature by examining consumer preferences for goat meat, a relatively healthy and environmentally friendly alternative to other popular meats.
Binod Khanal +2 more
wiley +1 more source
Adaptive energy management in smart homes through fuzzy reinforcement learning and metaheuristic optimization algorithms to minimize costs. [PDF]
Hamedani MMK +3 more
europepmc +1 more source
Domotics, Smart Homes, and Parkinson's Disease. [PDF]
Simonet C, Noyce AJ.
europepmc +1 more source
Diwakaran S +3 more
openaire +1 more source
Flexible Memory: Progress, Challenges, and Opportunities
Flexible memory technology is crucial for flexible electronics integration. This review covers its historical evolution, evaluates rigid systems, proposes a flexible memory framework based on multiple mechanisms, stresses material design's role, presents a coupling model for performance optimization, and points out future directions.
Ruizhi Yuan +5 more
wiley +1 more source
An incentive-aware federated bargaining approach for client selection in decentralized federated learning for IoT smart homes. [PDF]
L JV.
europepmc +1 more source
Deep Learning‐Assisted Design of Mechanical Metamaterials
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source

