Reactivating and reorganizing activity-silent working memory: two distinct mechanisms underlying pinging the brain by Yang, C, He, X, Cai, Y

“…Recent studies have proposed that visual information in working memory (WM) can be maintained in an activity-silent state and reactivated by task-irrelevant high-contrast visual impulses (“ping”). Although pinging the brain has become a popular tool for exploring activity-silent WM, its underlying mechanisms remain unclear. …”

Development of hybrid robot-gripper for picking foods by Tee, Isaac

“…One such example is the picking and placing of food in large quantities. …”
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Surge in SpikeProp algorithm by Zhang, Zhengyang

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Large-scale tests of hinged slender reinforced concrete columns under eccentric loading by Chuang, Poon Hwei., Kong, Fung Kew.

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Niemann-Pick type c disease: pathogenesis and therapy by Colaco, A

“…<p>Niemann-Pick disease Type C is a rare, lysosomal storage disorder caused by defects in either <em>NPC1</em> (95% of cases) or <em>NPC2</em>, and characterized by progressive neurodegeneration that ultimately results in premature death. …”

Competitive strategies for small business in optical pick-up manufacturing by Ge, Guo Zheng, Zhang, Jing

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Discovering genetic modifiers in Niemann-Pick Disease Type C by Rodriguez-Gil, J

“…<p>Niemann-Pick Disease, Type C (NPC) is a rare, fatal neurodegenerative disorder characterized by lysosomal accumulation of unesterified cholesterol and sphingolipids. …”

A spiking neural network for pattern recognition by Nurin Atikah Bohari

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Robustness to training disturbances in SpikeProp Learning by Shrestha, Sumit Bam, Song, Qing

“…Stability is a key issue during spiking neural network training using SpikeProp. The inherent nonlinearity of Spiking Neuron means that the learning manifold changes abruptly; therefore, we need to carefully choose the learning steps at every instance. …”
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Development of an automatic fruit picking robot based on object detection algorithm by Wan, Jiaxin

“…In the agricultural field, especially in the process of harvest, it needs a lot of human resources to perform various tasks, such as picking fruits, which may be labor intensive. An effective robotics picking system can solve this problem to a large extent. …”
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Impact of spike anneal on ultra shallow junction formation by Lai, Chung Woh

“…This report explains the need for ultra shallow junctions for modern day CMOS devices, how spike anneal can help achieve this, reviews the important parameters if this process and how these parameters affect the performances of the CMOS transistors.…”
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Automated spike detection using cascade of simple classifiers by Guo, Jingyao

“…The infinite variety of spike morphologies and the similarity of spikes to normal EEG and artifacts also make the detection of spikes difficult. …”
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Pick one, but be quick : 5' splice sites and the problems of too many choices by Roca, Xavier, Krainer, Adrian R., Eperon, Ian C.

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Designing a spiking neural network system for object recognition by Thong, Jing Yuan

“…Widely touted as the 3rd generation of neural networks, Spiking Neural Networks were introduced as an enhanced representation of working memory. …”
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Dissipative solitons with extreme spikes in the normal and anomalous dispersion regimes by Akhmediev, N., Soto-Crespo, J. M., Vouzas, Peter, Devine, N., Chang, Wonkeun

“…In this paper, one recent example is considered—dissipative solitons with extreme spikes (DSESs). It was found that DSESs exist in large regions of the parameter space of the complex cubic–quintic Ginzburg–Landau equation. …”
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Bayesian lesion estimation with a structured spike-and-slab prior by Menacher, A, Nichols, T, Holmes, C, Ganjgahi, H

“…Our method also accounts for underestimation of posterior variance due to variational inference by providing an approximate posterior sampling approach based on Bayesian bootstrap ideas and spike-and-slab priors with random shrinkage targets. …”

FPGA implementation of spiking convolutional neural networks for voice keyword recognition by Ng, Wei Soon

“…The spiking convolutional neural network (SCNN) is a hybrid model of both the spiking neural network (SNN) and convolutional neural network (CNN). …”
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Filamentous oligomer structure reconstruction and a new filament picking method for Cryo-EM micrographs by Xu, Chenrui

“…Recognizing the bottleneck step of this process, the filament picking, we developed a rapid and easy-to-use software. …”
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Robust service restoration of distribution systems towards coordinated parallel network reconstruction and cold load pick-up by Xie, Dunjian, Xu, Yan, Zhang, Cuo

“…This paper proposed a robust service restoration method coordinating parallel network reconstruction and load restoration decisions considering cold load pick-up (CLPU) effects. Firstly, a novel parallel network reconstruction model is proposed, which can simultaneously guarantee the radiality of each subsystem and the feasibility of the restoration sequence. …”
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Bio-inspired categorization using event-driven feature extraction and spike-based learning by Zhao, Bo, Chen, Shoushun, Tang, Huajin

“…Bio-inspired, cortex-like, spikebased features are obtained through event-driven convolution and neural competition. The extracted spike feature patterns are then classified by a network of leaky integrate-and-fire (LIF) spiking neurons, in which the weights are trained using tempotron learning rule. …”
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