Results 161 to 170 of about 43,164 (298)

Marine silicon for biomedical sustainability

BMEMat, EarlyView.
Schematic illustrating marine silicon for biomedical engineering. Abstract Despite momentous divergence from oceanic origin, human beings and marine organisms exhibit elemental homology through silicon utilization. Notably, silicon serves as a critical constituent in multiple biomedical processes.
Yahui Han, Zhibo Yang, Wei Xia, Chengtie Wu   +3 more
wiley   +1 more source

Corrigendum: Optoelectronic integrated circuits for analog optical computing: Development and challenge

Frontiers in Physics, 2023
Yihang Dan, Yihang Dan, Zeyang Fan, Qi Chen, Yihang Lai, Xiaojuan Sun, Xiaojuan Sun, Tian Zhang, Kun Xu   +8 more
doaj   +1 more source

Loss, persistence and reversal of phenotypic traits

Biological Reviews, EarlyView.
ABSTRACT The irreversibility of complex trait loss has long been a tenet of evolutionary biology. However, this idea is increasingly at odds with the numerous documented exceptions across the Tree of Life. We synthesise this growing body of evidence across a diverse array of taxa and traits, exploring the evolutionary conditions that enable ...
Giobbe Forni, Giuseppe Fusco, Filippo Nicolini, Heather Bruce, Andrea Luchetti   +4 more
wiley   +1 more source

When Do Robots Go Green? Unveiling Mechanisms, Thresholds, and Spillovers of Industrial Robotics on Global Ecological Capacity

Business Strategy and the Environment, EarlyView.
ABSTRACT This paper examines the relationship between industrial robotics adoption and ecological capacity, measured by biocapacity, using panel data from 50 countries over the period 2000–2024. We investigate the transmission mechanisms, non‐linearities, spatial spillovers, and heterogeneity characterizing this relationship.
Brahim Bergougui, Hamid Ghazi H. Sulimany   +1 more
wiley   +1 more source

Requirements on bit resolution in optical Ising machine implementations [PDF]

Toon Sevenants, Guy Van der Sande, Guy Verschaffelt   +2 more
openalex   +1 more source

Why Are Consumers Ambivalent About AI‐Generated Images? The Moderating Role of Commercial Versus Noncommercial Content Type

Journal of Consumer Behaviour, EarlyView.
ABSTRACT Grounded in ambivalence theories, this research examined factors shaping consumer ambivalence toward AI‐generated content and investigated differences between commercial and noncommercial contexts. As a preliminary study, sentiment analysis of Reddit data using a support vector machine (SVM) revealed that most consumer sentiment toward AI ...
Garim Lee, Jinsu Park, Hye‐Young Kim, Divya Manoj   +3 more
wiley   +1 more source

Scalable Ising machine composed entirely of Si transistors. [PDF]

Sci Adv
Yun SY, Kim JP, Jeong J, Lee SW, Chung YS, Kim S, Choi YK.   +6 more
europepmc   +1 more source

Effects of Simultaneous Sitophilus zeamais and Prostephanus truncatus During Storage of Maize in Hermetic and Non‐Hermetic Conditions

Cereal Chemistry, EarlyView.
ABSTRACT Background Sitophilus zeamais (Mostschulsky), the maize weevil, and Prostephanus truncatus (Horn), the larger grain borer, are two notorious insect pests of farm‐stored products in Sub‐Saharan Africa (SSA). The goal of this study was to determine whether there were interactions between P. truncatus and S. zeamais during storage.
Rashid Suleiman, Kurt A. Rosentrater
wiley   +1 more source

Three‐Layer‐Structured Garnet‐Dominant Composite Solid Electrolyte for Solid‐State Batteries

Carbon Energy, EarlyView.
The three‐layer‐structured garnet‐dominant composite solid electrolyte (GD‐CSE) is designed for solid‐state batteries. The GD‐CSE is composed of over 80 wt. % contents of LGLZO. This three‐layer CSE has high ionic conductivity and high potential stability.
Wooyoung Lee, Jongmin Lee, Seohye Jeon, Joonsoo Kim, Ji Haeng Yu, Kyong Sik Yun, Jung Hyun Lee, Jungjoon Yoo, Tae Woo Kim, Sinho Choi, Yu‐Jin Han, Sang‐Hoon Park, Boyun Jang, Daeil Kim   +13 more
wiley   +1 more source

Machine Learning Paradigm for Advanced Battery Electrolyte Development

Carbon Energy, EarlyView.
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su, Mengfan Pei, Keyu Chen, Xigao Jian, Fangyuan Hu   +4 more
wiley   +1 more source