Results 61 to 70 of about 55,699 (240)

High‐Resolution Multispectral Photovoltaic Imagers from Visible to Short‐Wave Infrared

Advanced Science, EarlyView.
We demonstrate a monolithic quad‐spectral imager that seamlessly integrates visible and short‐wave infrared detection on a single chip. Through direct photopatterning of an all‐polymer bulk heterojunction and colloidal quantum dots, the device achieves high‐resolution (640 × 512) imaging across 350–2400 nm, enabling multispectral capture for ...
Wanqing Li, Cheng Bi, Min He, Xiaolong Zheng, Yuning Luo, Yimei Tan, Chenxi Liu, Salihuojia Talanti, Yanfei Liu, Ge Mu, Qun Hao, Kangkang Weng, Xin Tang   +12 more
wiley   +1 more source

Sufficient conditions for symmetric matrices to have exactly one positive eigenvalue

Special Matrices, 2020
Let A = [aij] be a real symmetric matrix. If f : (0, ∞) → [0, ∞) is a Bernstein function, a sufficient condition for the matrix [f (aij)] to have only one positive eigenvalue is presented.
Al-Saafin Doaa, Garloff Jürgen
doaj   +1 more source

PAIR: Reconstructing Single‐Cell Open‐Chromatin Landscapes for Transcription Factor Regulome Mapping

Advanced Science, EarlyView.
scATAC‐seq analysis is often constrained by limited sequencing depth, extreme sparsity, and pervasive technical missingness. PAIR is a probabilistic framework that restores scATAC‐seq accessibility profiles by directly modeling the native cell–peak bipartite structure of chromatin accessibility.
Yanchi Su, Qi Qi, Yi Fan, Yubo Wang, Gaoyang Hao, Ka‐Chun Wong, Yunhe Wang, Xiangtao Li   +7 more
wiley   +1 more source

Robust optimisation algorithm for the measurement matrix in compressed sensing

CAAI Transactions on Intelligence Technology, 2018
The measurement matrix which plays an important role in compressed sensing has got a lot of attention. However, the existing measurement matrices ignore the energy concentration characteristic of the natural images in the sparse domain, which can help to
Ying Zhou, Quansen Sun, Jixin Liu
doaj   +1 more source

Real‐time fault detection in multicomponent nuclear‐waste slurries through data fusion of spectroscopic sensors

AIChE Journal, EarlyView.
Abstract Three instruments–Raman spectroscopy, attenuated total reflectance–Fourier transform infrared spectroscopy, and focused beam reflectance measurement–were used to detect sensor faults, mixing faults, and unanticipated chemistry in a system of multicomponent slurries.
Steven H. Crouse, Ronald W. Rousseau, Martha A. Grover   +2 more
wiley   +1 more source

Equivalences of Zt×Z22-cocyclic Hadamard matrices [PDF]

, 2015
One of the most promising structural approaches to resolving the Hadamard Conjecture uses the family of cocyclic matrices over Zt × Z2 2. Two types of equivalence relations for classifying cocyclic matrices over Zt × Z2 2 have been found.
Gudiel Rodríguez, Félix, Güemes Alzaga, María Belén, Horadam, K.J., Rao, A., Álvarez Solano, Víctor   +4 more
core  

Hybrid kernels integrating genomic and multispectral data improve wheat genomic prediction accuracy. [PDF]

Plant Genome
Abstract Genomic selection (GS) is transforming plant breeding by enabling more accurate and efficient identification of superior genotypes. However, its practical implementation remains challenging, as achieving high prediction accuracy is critical for its success. Several factors—including sample size, the degree of relatedness among individuals, and
Montesinos-López OA, Martínez-Regalado JA, Murillo-Avalos CL, Herr AW, Montesinos-López A, Delgado-Enciso I, Cuevas J, Crossa J, Carter AH.   +8 more
europepmc   +2 more sources

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

Spin models constructed from Hadamard matrices

, 2011
A spin model (for link invariants) is a square matrix $W$ which satisfies certain axioms. For a spin model $W$, it is known that $W^TW^{-1}$ is a permutation matrix, and its order is called the index of $W$. F. Jaeger and K.
Ikuta, Takuya, Munemasa, Akihiro
core   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source