Results 201 to 210 of about 1,906,785 (292)

Multi-platform integration of brain and CSF proteomes reveals biomarker panels for Alzheimer's disease. [PDF]

Brief Bioinform
Tsai WY, Giesbertz P, Breimann S, Lichtenthaler S, Frishman D.   +4 more
europepmc   +1 more source

Microsphere Autolithography—A Scalable Approach for Arbitrary Patterning of Dielectric Spheres

Advanced Functional Materials, EarlyView.
MicroSphere Autolithography (µSAL) enables scalable fabrication of patchy particles with customizable surface motifs. Focusing light through dielectric microspheres creates well defined, tunable patches via a conformal poly(dopamine) photoresist. Nearly arbitrary surface patterns can be achieved, with the resolution set by the index contrast between ...
Elliott D. Kunkel, Alec G. Burnett, Katherine E. Scheiber, Hans D. Robinson   +3 more
wiley   +1 more source

Bimetallic Nanoreactor Activates cGAS‐STING Pathway via mtDNA Release for Cancer Metalloimmunotherapy

Advanced Functional Materials, EarlyView.
A bimetallic Mn–Ca nanoreactor (MCC) is developed as a non‐nucleotide STING nanoagonist for cancer metalloimmunotherapy. MCC induces Ca2+ overload and hydroxyl radical generation, resulting in mitochondrial damage and mtDNA release. The released mtDNA cooperates with Mn2+ to robustly activate cGAS–STING signaling.
Xin Wang Mo, Nguyen Thi Nguyen, LiLi Guo, Ngoc Man Phan, Hyunsu Shin, Tae‐il Kim, Yu Seok Youn, Jaeyun Kim   +7 more
wiley   +1 more source

An intelligent life prediction approach employing machine learning models for the power transformers. [PDF]

Sci Rep
Nezami MM, Ahmad S, Salamat A, Ansari MF, Alsubait T, Taha IBM, Ghatasheh M, Mohamed Abdelwahab SA, Flah A.   +8 more
europepmc   +1 more source

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

Advanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha, Yingshan Ma, Yong Nam An, Sung‐Un An, Hyeon Hak Jung, Suvi‐Tuuli Varjamo, Jiwon Yoo, Junho Min, Hanvit Kim, Faisal Ahmed, Sang Hoon Chae, Young Min Song, Weiwei Cai, Tawfique Hasan, Zhipei Sun, Dong‐Ho Kang, Hyeon‐Jin Shin, Yunyun Dai, Hoon Hahn Yoon   +18 more
wiley   +1 more source

Digital Discovery of Synthesizable Metal−Organic Frameworks via Molecular Dynamics‑Informed, High‑Fidelity Deep Learning

Advanced Functional Materials, EarlyView.
Tabular foundation model interrogates the synthetic likelihood of metal−organic frameworks. Abstract Metal–organic frameworks (MOFs) are celebrated for their chemical and structural versatility, and in‑silico screening has significantly accelerated their discovery; yet most hypothetical MOFs (hMOFs) never reach the bench because their synthetic ...
Xiaoyu Wu, Rui Zheng, Quan Liu, Jianwen Jiang   +3 more
wiley   +1 more source

Flight delay prediction: Evaluating machine learning algorithms for enhanced accuracy. [PDF]

PLoS One
AlBassam SAA, AlShahrani DN.
europepmc   +1 more source

Oral Dosed Organo‐Silica Nanoparticles Restore Glucose Homeostasis and β‐Cell Function in Diabetes Rats

Advanced Functional Materials, EarlyView.
An oral nanoplatform, MOP@T@D, which can maintain glucose homeostasis and restore islet β cells in diabetic rats is developed. It achieves efficient intestinal absorption and liver‐targeted delivery. The nanoparticle disintegrates only in response to hyperglycemia to release insulin on demand and provides antioxidant protection through selenoprotein ...
Chenxiao Chu, Mingli Wei, Che Bian, Xiaoshuang Bi, Yaxin Deng, Peifu Xiao, Jiansong Zhao, Yuying Wang, Haibing He, Jingxin Gou, Tian Yin, Xing Tang, Li Yang, Hongbo Zhang, Yu Zhang   +14 more
wiley   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source

Lightweight machine learning framework using temporal features for electric vehicle demand response forecasting on edge devices. [PDF]

Sci Rep
Durrani AM, Asar AU, Aziz A, Khan W, Yousaf MZ, Anjam F, Farooq U, Abdullah M, Shabaz M.   +8 more
europepmc   +1 more source