Results 111 to 120 of about 1,489,144 (280)

Region‐to‐Region Unidirectional Connection In Vitro Brain Model for Studying Directional Propagation of Neuropathologies

Advanced Functional Materials, EarlyView.
A unidirectional cerebral organoid–organoid neural circuit is established using a microfluidic platform, enabling controlled directional propagation of electrical signals, neuroinflammatory cues, and neurodegenerative disease–related proteins between spatially separated organoids.
Kyeong Seob Hwang, Hui‐Wen Liu, Hyogeun Shin, Hyun Wook Kang, Minjin Kang, Jongbaeg Kim, Il‐Joo Cho, Nakwon Choi, Seok Chung, Hong Nam Kim   +9 more
wiley   +1 more source

Chemoselective Sequential Polymerization: An Approach Toward Mixed Plastic Waste Recycling

Advanced Functional Materials, EarlyView.
Inspired by biological protein metabolism, this study demonstrates the closed‐loop recycling of mixed synthetic polymers via ring‐closing depolymerization followed by a chemoselective sequential polymerizations process. The approach recovers pure polymers from mixed feedstocks, even in multilayer formats, highlighting a promising strategy to overcome a
Gadi Slor, Youwei Ma, Hyunwoo Park, Tae‐Lim Choi, Damien Guironnet, Francesco Stellacci   +5 more
wiley   +1 more source

A neural network multi-task learning approach to biomedical named entity recognition

BMC Bioinformatics, 2017
Background Named Entity Recognition (NER) is a key task in biomedical text mining. Accurate NER systems require task-specific, manually-annotated datasets, which are expensive to develop and thus limited in size.
Gamal Crichton, Sampo Pyysalo, Billy Chiu, Anna Korhonen   +3 more
doaj   +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

A review on multi-task metric learning

Big Data Analytics, 2018
Distance metric plays an important role in machine learning which is crucial to the performance of a range of algorithms. Metric learning, which refers to learning a proper distance metric for a particular task, has attracted much attention in machine ...
Peipei Yang, Kaizhu Huang, Amir Hussain
doaj   +1 more source

Predicting Atomic Charges in MOFs by Topological Charge Equilibration

Advanced Functional Materials, EarlyView.
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi, Sumukh Shankar Sharadaprasad, Rochus Schmid   +2 more
wiley   +1 more source

Efficient deep reinforcement learning based task scheduler in multi cloud environment

Scientific Reports
Task scheduling problem (TSP) is huge challenge in cloud computing paradigm as number of tasks comes to cloud application platform vary from time to time and all the tasks consists of variable length, runtime capacities.
Sudheer Mangalampalli, Ganesh Reddy Karri, M. V. Ratnamani, Sachi Nandan Mohanty, Bander A. Jabr, Yasser A. Ali, Shahid Ali, Barno Sayfutdinovna Abdullaeva   +7 more
doaj   +1 more source

Enhancing Synaptic Plasticity and Multistate Retention of Organic Neuromorphic Devices Using Anion‐Excessive Gel Electrolyte

Advanced Functional Materials, EarlyView.
Anion‐excessive gel‐based organic synaptic transistors (AEG‐OSTs) that can maintain electrical neutrality are developed to enhance synaptic plasticity and multistate retention. Key improvement is attributed to the maintenance of electrical neutrality in the electrolyte even after electrochemical doping, which reduces the Coulombic force acting on ...
Yousang Won, Jeongwoo Lee, Hyunwook Kim, Joon Hak Oh   +3 more
wiley   +1 more source

A novel multi-task learning model based on Transformer-LSTM for wind power forecasting

International Journal of Electrical Power & Energy Systems
The integration of multi-task learning into multi-step deterministic and probabilistic prediction frameworks plays a pivotal role in augmenting the accuracy of wind power forecasts and mitigating associated operational uncertainties.
Rongquan Zhang, Siqi Bu, Yuxia Zheng, Gangqiang Li, Xiupeng Wan, Qiangqiang Zeng, Min Zhou   +6 more
doaj   +1 more source

Dual-Balancing for Multi-Task Learning

Neural Networks
Multi-task learning aims to learn multiple related tasks simultaneously and has achieved great success in various fields. However, the disparity in loss and gradient scales among tasks often leads to performance compromises, and the balancing of tasks remains a significant challenge. In this paper, we propose Dual-Balancing Multi-Task Learning (DB-MTL)
Baijiong Lin, Weisen Jiang, Feiyang Ye, Yu Zhang, Pengguang Chen, Ying-Cong Chen, Shu Liu, Ivor W. Tsang, James T. Kwok   +8 more
openaire   +2 more sources