Anomaly detection in multidimensional time series for water injection pump operations based on LSTMA-AE and mechanism constraints by Mei Wang, Xinyuan Zhu, Guangyue Zhou, Kewen Li, Qingshan Wu, Wankai Fan

“…Abstract Addressing the issues of inadequate information exchange among subsequences in the operational time series of water injection pumps, leading to low accuracy and high false alarm rates in anomaly detection, this paper proposes a multidimensional time series anomaly detection method for water injection pump operations, leveraging Long Short-Term Memory Autoencoder augmented with Attention Mechanism (LSTMA-AE) and mechanistic constraints. …”
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Electrophysiological properties of melanin-concentrating hormone neuron subpopulations defined by anatomical localization and CART expression by Rafiat Damilola Adekunle, Mohammed Sohel Chowdhury, Lisa Z. Fang, Michiru Hirasawa

“…IntroductionMelanin-concentrating hormone (MCH) neurons are essential regulators of energy and glucose homeostasis, sleep–wake behaviors, motivation, learning and memory. These neurons are anatomically distributed across the medial (MH) and lateral hypothalamus (LH), and the adjacent zona incerta (ZI), which may represent functional subgroups with distinct connectivity with different brain regions. …”
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Modeling Terrestrial Net Ecosystem Exchange Based on Deep Learning in China by Zeqiang Chen, Lei Wu, Nengcheng Chen, Ke Wan

“…The model was also compared with the random forest, long short-term memory, deep neural network, and convolutional neural networks (1D) models to distinguish it from previous shallow machine learning models to estimate NEE, and the results show that deep learning models have great potential in NEE modeling. …”
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Exploring the nature of stuttering through a behavioral-neuro-modulation intervention program in bilinguals with stuttering by Chanchal Chaudhary, Samir Kumar Praharaj, Gopee Krishnan

“…Current literature points towards deficits in speech-related motor areas of the brain to abnormalities in linguistic planning and phonological memory playing a role in stuttering. Examining cross-linguistic generalization of treatment gains from treated to untreated language in bilinguals who stutter may provide a unique opportunity to explore the motor and linguistic factors in stuttering. …”
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Software diversification method based on binary rewriting by Benwei HE, Yunfei GUO, Yawen WANG, Qingfeng WANG, Hongchao HU

“…Software diversity is an effective defense against code-reuse attacks, but most existing software diversification technologies are based on source code.Obtaining program source code may be difficult, while binary files are challenging to disassemble accurately and distinguish between code pointers and data constants.This makes binary file diversification difficult to generate high levels of randomization entropy, and easily compromised by attackers.To overcome these challenges, a binary file oriented software diversification method was proposed based on static binary rewriting technology, namely instruction offset randomization.This method inserted NOP instructions of varying byte lengths before program instructions with a certain probability, reducing the number of unintended gadgets in the program and randomly offsetting the original instruction address.This disrupts the program’s original memory layout and increases the cost of code-reuse attacks.At the same time, an optimization strategy based on hot code was designed for this method.The execution times of basic blocks in binary files were obtained by dynamic pile insertion, so as to adjust the NOP instruction insertion probability in each basic block.The higher the execution frequency, the fewer NOP instructions were inserted into the basic block, which can ensure lower performance overhead and produce higher randomization entropy.In the experimental part, the SPEC benchmark program was used to test the optimized method from the aspects of performance overhead, gadget survival rate and file size.The results show that a 15% insertion probability achieves the best effect, with an average gadget survival rate of less than 1.49%, increasing attackers’ difficulty in reusing the same gadget attack chain.Furthermore, only a 4.1% operation overhead and 7.7% space overhead are added, maintaining high levels of security.…”
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LSTM Recurrent Neural Network-Based Frequency Control Enhancement of the Power System with Electric Vehicles and Demand Management by G. Sundararajan, P. Sivakumar

“…This research work investigates a deep learning strategy based on a long short-term memory recurrent neural network to identify active power fluctuations in real-time. …”
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Numerical simulation of MHD Sakiadis flows of convectively heated thixotropic nanofluids in a porous medium using revised transport laws and Wakif-Buongiorno's model by A. Wakif

“…Due to the particular inability of Fourier's and Fick's laws in the realistic quantification of transfer processes that can occur certainly within a flowing biphasic mixture, on the one hand, and the explanation of the memory relaxation features of such a non-homogenous medium, on the other hand, the present scrutinization intends to propose a representative biphasic flow model to reveal the principal demeanors of convectively heated thixotropic nanofluids during their steady two-dimensional flows in the laminar regime over a stretching planar geometry in a Darcy-Forchheimer porous medium under the magnetic impact of an external electromagnetic device. …”
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Neural-field-based image reconstruction for bioluminescence tomography by Xuanxuan Zhang, Xu Cao, Jiulou Zhang, Lin Zhang, Guanglei Zhang

“…Nevertheless, nearly every existing DL-based method utilizes an explicit neural representation for the reconstruction problem, which either consumes much memory space or requires various complicated computations. …”
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A meta-analysis of the effect of protein synthesis inhibitors on rodent fear conditioning by Carneiro, Clarissa F. D., Amorim, Felippe E., Amaral, Olavo B.

“…However, other factors proposed as boundary conditions for reconsolidation, such as memory age and training strength, were not associated with effect size. …”
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Exploring Virtual Reality and Exercise Simulator Interventions in Patients With Attention Deficit Hyperactivity Disorder: Comprehensive Literature Review by Gurdeep Sarai, Prem Prakash Jayaraman, Oren Tirosh, Nilmini Wickramasinghe

“…Past research indicates that both VR and simulator-based interventions enhance cognitive functions, such as executive function and memory, though their impacts on attention vary. …”
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Combination of MLFMA and ACA to Accelerate Computation of Scattering from Underground Targets by Zhiwei Liu, Dan Tang, Zhanyang Zhang, Yueyuan Zhang, Xiaoli Wang, Shunli Jie

“…Multilevel fast multipole algorithm (MLFMA) is used to decrease the computation complexity and memory cost. However, the octree used in MLFMA is not applied for rough surfaces and targets together; both the surface and target need to construct octree separately. …”
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Probabilistic Solar Proxy Forecasting With Neural Network Ensembles by Joshua D. Daniell, Piyush M. Mehta

“…In this work, we introduce methods using neural network ensembles with multi‐layer perceptrons (MLPs) and long‐short term memory (LSTMs) to improve on the SET predictions. …”
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Mesenchymal Stromal Cells Suppress Hippocampal Neuron Autophagy Stress Induced by Hypoxic-Ischemic Brain Damage: The Possible Role of Endogenous IL-6 Secretion by Miao Yang, Wuqing Sun, Lu Xiao, Mulan He, Yan Gu, Ting Yang, Jie Chen, Xiaohua Liang

“…In the present study, MSC transplantation effectively ameliorated learning-memory function and suppressed stress-induced hippocampal neuron autophagy in HIBD rats. …”
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Design of a Novel Fractional Whale Optimization-Enhanced Support Vector Regression (FWOA-SVR) Model for Accurate Solar Energy Forecasting by Abdul Wadood, Hani Albalawi, Aadel Mohammed Alatwi, Hafeez Anwar, Tariq Ali

“…The FWOA-SVR model is comprehensively evaluated against traditional SVR, Long Short-Term Memory (LSTM), and Backpropagation Neural Network (BPNN) models using training, validation, and testing datasets. …”
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Multiple Electrophysiological Markers of Visual-Attentional Processing in a Novel Task Directed toward Clinical Use by Julie Bolduc-Teasdale, Pierre Jolicoeur, Michelle McKerral

“…., mild traumatic brain injury or mild cerebrovascular stroke) are at risk to show persistent cognitive symptoms (attention and memory) after the acute postinjury phase. Although studies have shown that those patients perform normally on neuropsychological tests, cognitive symptoms remain present, and there is a need for more precise diagnostic tools. …”
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The Semenov-Znamensky family in Harbin. Materials for the biography by A. N. Steblyanskaya

“…Harbin residents have always tried to preserve the memory of their ancestors. Preserving the history of Russian emigration has a high relevance of the problem. …”
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Fail-Safe Logic Design Strategies Within Modern FPGA Architectures by Priya A. Bhakta, Jim Plusquellic, Andrew Suchanek, Tom J. Mannos

“…The analysis reveals additional vulnerabilities exist within reconfigurable architectures over those in equivalent fail-safe application specific integrated circuit (ASIC), thus requiring a more elaborate network of redundant circuits and checking logic. The configuration memory bits (CMBs), which configure routing and designate logic functions within the LUTs of the FPGA, add complexity to fail-safe design strategies by introducing additional fault conditions and fault propagation paths. …”
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Unraveling the Psyche: A Critical Analysis of Historical and Contemporary Theories in Light of Neuroscientific Advances by Mir Mahmoud Seyyedvalilou, Marziye Alivandi Vafa, Seyed Mahmoud Tabatabaei

“…Conclusions: In conclusion, the mind is recognized as a sophisticated process integrating memory, intelligence, awareness, and philosophical consciousness, arising from complex cerebral interactions and neural dynamics. …”
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A data-driven cluster analysis to explore cognitive reserve and modifiable risk factors in early phases of cognitive decline by Sara Bernini, Alice Valcarenghi, Elena Ballante, Federico Fassio, Marta Picascia, Elena Cavallini, Matteo Cotta Ramusino, Alfredo Costa, Tomaso Vecchi, Cristina Tassorelli, Sara Bottiroli

“…Specifically, Cluster 1 exhibited advantages in: (1) sociodemographic (education, technological skills, and occupation), (2) cognitive (global cognitive functioning, executive functioning, and working memory), and (3) mental health (mood state and quality of life) characteristics. …”
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Speed Distribution Prediction of Freight Vehicles on Mountainous Freeway Using Deep Learning Methods by Yuren Chen, Yu Chen, Bo Yu

“…RNN and its variants including long short-term memory (LSTM) and RNN and gated recurrent units (GRUs) were utilized to predict speed distribution in a spatial-temporal dimension with KL divergence being the loss function. …”
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