Results 101 to 110 of about 127,936 (303)

Combining Spatial Multi‐Omics Data to Decipher Spatial Domains and Elucidate Cell Heterogeneity Based on Self‐Supervised Graph Learning

Advanced Science, EarlyView.
A self‐supervised multi‐view graph fusion framework integrates spatial multi‐omics, excelling in domain identification and denoising. It reconstructs spatial pseudo‐expression, jointly analyzes multi‐omics data, infers RNA velocity, predicts spatial omics features from single‐cell multi‐omics, and detects spatially dark genes and transcription factors,
Yuejing Lu, Rui Qiao, Ying Li, Junhong Li, Nuoya Yue, Jing Ge, Jiao Wang, Luonan Chen, Peiluan Li   +8 more
wiley   +1 more source

Processing mathematical thinking through digital pedagogical media: the spreadsheet

, 2008
This study is concerned with the ways mathematical understanding emerges when mathematical phenomena are encountered through digital pedagogical media, the spreadsheet, in particular.
Calder, Nigel Stuart
core  

Decoding Spatial Heterogeneity and Multi‐Omics Regulation with Hierarchical Graph Learning

Advanced Science, EarlyView.
ABSTRACT Recent advances in spatial multi‐omics technologies have enabled the simultaneous profiling of multiple molecular layers within the same tissue slice, providing unprecedented opportunities to investigate tissue spatial organization. However, most existing computational methods identify spatial domains in a purely data‐driven manner, rarely ...
Jiazhou Chen, Jiahui Xie, Yi Liao, Junyu Li, Longqi Liu, Xin Gao, Hongmin Cai   +6 more
wiley   +1 more source

Digitization of chaotic signal for reliable communication in non-ideal channels [PDF]

, 2008
A new method of chaotic communication system based on digitization of the chaotic signal is proposed. The digitally encoded chaotic signal is transmitted through a practical channel and recovered at the receiver.
Ghassemlooy, Zabih, R. Kharel, K. Busawon, Z. Ghassemlooy, Busawon, Krishna, Rajbhandari, Sujan, S. Rajbhandari, Kharel, Rupak   +7 more
core   +1 more source

STAID: A Self‐Refining Deep Learning Framework for Spatial Cell‐Type Deconvolution with Biologically Informed Modeling

Advanced Science, EarlyView.
STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu, Shuli Sun, Zhengliang Lv, Xinyu Liu, Yihua Wang, Bingqiang Liu   +5 more
wiley   +1 more source

Optimization and mathematical modeling of communication networks

, 2019
The main attention is paid to optimization issues, as well as mathematical modeling of systems that are important for the initial stages of the design of communication networks. Examples of solving scalar and vector optimization problems are given taking
Zheng Yu, Bezruk, V. M., Chebotarova, D. V., Guo Qiang, Семенець, В. В., Kaliuzhniy, N. M.   +5 more
core   +1 more source

On simulating the evolution of communication

, 1995
The prospects for modelling the evolution of communi-cation are considered, including the problem of inten-tional explanation, and the possibility of grounding sim-ulation work in theoretical biology.
Jason Noble, Dave Cliff, Cliff, D., Noble, J.   +3 more
core  

Mathematical Communication Ability in SAVI Learning Model with Mathematics Board Game in terms of Mathematical Resilience

This study aims to examine the quality of SAVI learning model implementation with a board game on mathematical communication skills, analyze the effect of mathematical resilience on mathematical communication skills, and describe mathematical ...
Dewi, Nuriana Rachmani, Ainurrachmani, Fitrania, Junaedi, Iwan   +2 more
core   +1 more source

TRIM: Simultaneous Thermometry, Ranging, and Imaging via a Monolithic Metalens

Advanced Science, EarlyView.
ABSTRACT While metasurfaces offer a pathway beyond the discrete architectures of conventional LWIR systems, physically fusing high‐precision thermometry and passive ranging onto a single metalens remains a formidable challenge. Here, we demonstrate a monolithic, dual‐focus metalens capable of simultaneous multidimensional sensing.
Man Yuan, Yuqing Zhang, Wangzhe Zhou, Zhaojian Zhang, Xiaoyun He, Xinpeng Jiang, Yiyi Li, Xin He, Jiagui Wu, Yuanmu Yang, Junbo Yang   +10 more
wiley   +1 more source

Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review

Advanced Science, EarlyView.
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh, Ki‐bum Lee, Junghyeon Lee, Seunghee Cho, Malkeshkumar Patel, Hangfei Li, Yu Wen, Ye Zhou, Joondong Kim   +8 more
wiley   +1 more source