Results 111 to 120 of about 502,131 (289)

Soft Ionic and Electronic Triboelectric Nanogenerators: Toward Attachable and Implantable Biomedical Applications

Advanced Materials, EarlyView.
This review provides an overview of triboelectric nanogenerator (TENG)–based biomedical applications by classifying studies into electronic and ionic systems across attachable and implantable platforms. It summarizes key material choices, device structures, and working mechanisms that characterize current TENG‐based research, and outlines six future ...
Kyongtae Choi, Jimin Park, Won Jun Song, Soohwan An, Seonggyu Choe, Byeong‐Rak Keum, Min Young Kim, Dae Hee Hwang, Young‐Geun Park, Sung‐Won Kim, Sangyul Baik, Gwang‐Bum Im, Younghoon Lee   +12 more
wiley   +1 more source

Evaluating the Effectiveness of Personalized Learning Approaches in TVET Colleges

International Journal of Home Economics, Hospitality and Allied Research
This review examines how personalized learning strategies affect Technical and Vocational Education and Training (TVET) colleges. Personalized learning is an adaptive instructional model that tailors educational experiences to meet the unique needs of ...
Chika Oliver Ujah
doaj   +1 more source

Bottom‐Up Programming of Cell States in Cancer Organoids with Defined Synthetic Adhesion Cues

Advanced Materials, EarlyView.
A bottom‐up biomaterial platform is developed to program transcriptomic states in pancreatic cancer organoids by tuning adhesion cues within synthetic matrices. By combining a Design of Experiments framework with multiobjective optimization, matrix compositions are identified that enrich specific cellular programs like EMT.
Ali Nadernezhad, Verena J. Kast, Dagmar Pette, Franziska Baenke, Daniel E. Stange, Carsten Werner, Daniela Loessner   +6 more
wiley   +1 more source

Personalized learning policies and strategies in K–12 education: Where, when, and for what?

Smart Learning Environments
Scant information exists about the distribution of national personalized learning policies/strategies worldwide and their focus. To address this research gap, this study conducts a narrative review of personalized learning policies/strategies in the ...
Mouna Denden, Mourad Abed
doaj   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Redefining personalized learning in the artificial intelligence era: an updated systematic review from 2019 to 2025

Smart Learning Environments
The integration of artificial intelligence (AI) in education is prompting a reevaluation of personalized learning terminology and its impact on teaching practices and learner engagement.
Fatima Khalifeh, Raúl Santiago, Ramon Palau   +2 more
doaj   +1 more source

On the promise of personalized learning for educational equity. [PDF]

NPJ Sci Learn, 2023
Dumont H, Ready DD.
europepmc   +1 more source

End‐to‐End Sensing Systems for Breast Cancer: From Wearables for Early Detection to Lab‐Based Diagnosis Chips

Advanced Materials Technologies, EarlyView.
This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane, Lyn I. Jones, Richard M. Martin, Helen Winter, Faezeh Arab Hassani   +4 more
wiley   +1 more source

PROGRESSIVE MEDICAL SIMULATION: AN ANALYSIS OF THE INTEGRATION OF PROGRESSIVE AND PERSONALIZED LEARNING IN CENTRAL LINE SIMULATORS. [PDF]

Proc Hum Factors Ergon Soc Annu Meet, 2023
Elsaadany IK, Gonzalez-Vargas JM, Moore JZ, Miller SR.   +3 more
europepmc   +1 more source

Transducers Across Scales and Frequencies: A System‐Level Framework for Multiphysics Integration and Co‐Design

Advanced Materials Technologies, EarlyView.
Transducers convert physical signals into electrical and optical representations, yet each mechanism is bounded by intrinsic trade‐offs across bandwidth, sensitivity, speed, and energy. This review maps transduction mechanisms across physical scale and frequency, showing how heterogeneous integration and multiphysics co‐design transform isolated ...
Aolei Xu, Mengyao Xiao, Zhouli Sui, Yinpeng Wang, Daoye Zheng, Yuxin Liu, Luwei Wang, Huajun Liu, Chengkuo Lee   +8 more
wiley   +1 more source