Results 161 to 170 of about 18,286,494 (304)

“Smelltronics”—From Gas to Smell Sensing

Advanced Materials, EarlyView.
The emerging field of smelltronics, encompassing sensing technologies for complex volatile organic compounds, holds significant potential for extracting valuable chemical information. It facilitates the noninvasive, real‐time monitoring of humans, food, and the environment.
Takeshi Ono, Tsunaki Takahashi, Jiangyang Liu, Haruka Honda, Zeng Jing, Wataru Tanaka, Takuro Hosomi, Takeshi Yanagida   +7 more
wiley   +1 more source

Human Resource Management, Complementarity and Hospital Performance: Evidence From the English NHS. [PDF]

Int J Health Plann Manage
Ali M, Salehnejad R, Kawalek P.
europepmc   +1 more source

Human resource management – development tendencies and future perspectives

, 2001
The dynamics with which changes are taking place in companies has led many managers to better appreciate the necessity and the advantages of comprehensive human resource management.
Thom, Norbert
core  

Photoacoustic Nanotagging for In Vivo Tracking and Optimization of Macrophage Immunotherapy in Solid Tumors

Advanced Materials, EarlyView.
Macrophage‐based immunotherapy for solid tumors is limited by poor tracking of cell localization and persistence. This study introduces nanotagged macrophages enabling near‐infrared photoacoustic imaging for real‐time monitoring. IFNγ‐conjugated tags enhance antitumor polarization without harming viability.
Seoyoon Song, Melissa Cadena, Myeongsoo Kim, Euisuk Chung, Jeungyoon Lee, Zlata Brushevich, Seonghun Shin, Paul S. Pelkowski, Stanislav Y. Emelianov   +8 more
wiley   +1 more source

How Does Digital Human Resource Management Foster a Sense of Relaxation Among Generation Z Employees? [PDF]

Behav Sci (Basel)
Zhang H, Hou X, Zhao S.
europepmc   +1 more source

How “Green” is Your Functional Material? Assessing Environmental Impacts of Multi‐Step Synthetic Protocols in Material Sciences at Various Technology Levels

Advanced Materials, EarlyView.
Environmental Synthesis Radar (ESR) evaluates the environmental impact of (early‐stage) multi‐step chemical syntheses, providing a holistic view by using 18 midpoint impact categories. Unlike conventional life‐cycle assessment (LCA) approaches, ESR reveals three complementary metrics: overall impact Vtotal, environmental hotspots VEF, and critical ...
Laura Plein, Alexander Schommer, Florian Dietrich, Moritz Gutsch, Heike Klesper, Kevin Schuller, Lars Jahnke, Jens Leker, Klaus Meerholz   +8 more
wiley   +1 more source

High-Commitment Human Resource Management and Care Workers' Attitudes and Performance Through a Sustainable-Careers Lens: A Multilevel Analysis in Japan. [PDF]

Behav Sci (Basel)
Sugano M.
europepmc   +1 more source

Inverse Design of Nanoparticulate Materials

Advanced Materials, EarlyView.
Inverse design shifts nanomaterial development from empirical trial‐and‐error to predictive model‐driven strategies. It can rely on knowledge‐based, data‐based, or hybrid process and property functions. This perspective article provides a practical framework for applying inverse design based on instructive examples. It discusses which modeling approach
Nabi Etienne Traoré, Annika Mauch, Michelle Berthold, Lukas Pflug, Wolfgang Peukert, Nicolas Vogel   +5 more
wiley   +1 more source

Breaking Bottlenecks in Solid Electrolyte Discovery With Large Artificial Intelligence Models

Advanced Materials, EarlyView.
Large AI models are presented as a route to break key bottlenecks in solid electrolyte discovery by linking materials databases, machine‐learning interatomic potentials, large language models, and autonomous experiments. This perspective highlights how AI can accelerate the identification of solid electrolytes with fast ion transport, stable interfaces,
Eric Jianfeng Cheng, Min Hong, Zhiquan Zeng, Chuanyu Liu, Qian Wang, Melissa Jane Meadowcroft, Vlad Badilita, Carlos Miguel Costa, Senentxu Lanceros‐Méndez, Ying Li, Chenyao Ma, Weibo Gong, Surendra Kumar Martha, Aloysius Soon, Piao Ma, Di Zhang, Teguh Ariyanto, Sudaryanto, Hiroshi Kakinuma, Jie Zhao, Jiayu Peng, Pengfei Ou, Jun Lu, Shin‐ichi Orimo, Hao Li   +24 more
wiley   +1 more source

Artificial intelligence in human resource management: models for recruitment, training, performance, compensation, and retention. [PDF]

Front Artif Intell
Safshekan M, Feili A, Shojaeifard A, Sorooshian S.   +3 more
europepmc   +1 more source