Results 11 to 20 of about 5,327,787 (369)
Transactions of the American Mathematical Society, 1938 Let \(R\) be any commutative ring with unity, and let \(L\) be the lattice of the ideals of \(R\). It is known that \(L\) is a modular lattice. The authors announce further conditions on \(L\); for example, if \(L\) is complemented, then it is a Boolean algebra -- thus it cannot be a non-trivial projective geometry.
Ward, Morgan, Dilworth, R. P.
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Journal of the European Economic Association, 2018 AbstractSuccesses of law enforcement in apprehending offenders are often publicized events. Such events have been found to result in temporary reductions in offending, or “residual deterrence”. We provide a theory of residual deterrence that accounts for the incentives of both enforcement officials and potential offenders.
Dilmé, Francesc, Garrett, Daniel F.
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Forecasting residue–residue contact prediction accuracy [PDF]
Bioinformatics, 2017 Abstract Motivation Apart from meta-predictors, most of today's methods for residue–residue contact prediction are based entirely on Direct Coupling Analysis (DCA) of correlated mutations in multiple sequence alignments (MSAs).
Wozniak, P.P. +5 more
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Deep Residual Learning for Image Recognition [PDF]
Computer Vision and Pattern Recognition, 2015 Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those used previously.
Kaiming He +3 more
semanticscholar +1 more source
Factors Affecting Incurred Pesticide Extraction in Cereals
Molecules, 2023 This study investigated the effect of milling on the yields of incurred residues extracted from cereals. Rice, wheat, barley, and oat were soaked in nine pesticides (acetamiprid, azoxystrobin, imidacloprid, ferimzone, etofenprox, tebufenozide ...
Xiu Yuan +4 more
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Residual Dense Network for Image Super-Resolution [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 A very deep convolutional neural network (CNN) has recently achieved great success for image super-resolution (SR) and offered hierarchical features as well.
Yulun Zhang +4 more
semanticscholar +1 more source
Aggregated Residual Transformations for Deep Neural Networks [PDF]
Computer Vision and Pattern Recognition, 2016 We present a simple, highly modularized network architecture for image classification. Our network is constructed by repeating a building block that aggregates a set of transformations with the same topology.
Saining Xie +4 more
semanticscholar +1 more source
Residual Attention Network for Image Classification [PDF]
Computer Vision and Pattern Recognition, 2017 In this work, we propose Residual Attention Network, a convolutional neural network using attention mechanism which can incorporate with state-of-art feed forward network architecture in an end-to-end training fashion.
Fei Wang +7 more
semanticscholar +1 more source
Molecules, 2021 We assessed the residual distribution and temporal trend of picarbutrazox sprayed by agricultural multicopters on Chinese cabbage and considered fortification levels and flying speeds. In plot 2, 14 days after the last spraying, the residues decreased by
Chang Jo Kim +7 more
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Molecules, 2020 Tenebrio molitor larvae (mealworm) is an edible insect and is considered a future food. Using liquid chromatography-tandem mass spectrometry (LC-MS/MS), a novel method for simultaneous analysis of 353 target analytes was developed and validated.
Yongho Shin +8 more
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