Homeostatic antiviral protection of the neonatal gut epithelium by interferon lambda by Bryan Ramirez Reyes, Shelby Madden, Kimberly A. Meyer, Brenden Bartsch, Austin P. Wright, David A. Constant, Timothy J. Nice

“…This intrinsically programmed antiviral response in early life is particularly important due to the absence of a robust microbiota or protective immune memory at birth, when the risk of enteric infection is high.…”
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Solutions to the Schrödinger Equation: Nonlocal Terms and Geometric Constraints by Irina Petreska, Pece Trajanovski, Trifce Sandev, Jonathan A. M. Almeida Rocha, Antonio Sérgio Magalhães de Castro, Ervin K. Lenzi

“…Specifically, the equation is adapted to account for a backbone structure exhibiting memory effects dependent on both time and spatial position. …”
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Characterization of the C-terminal tail of the Arc protein. by Melissa Boldridge, Jody Shimabukuro, Keith Nakamatsu, Christian Won, Chad Jansen, Helen Turner, Lei Wang

“…The activity-regulated cytoskeleton-associate protein Arc (or Arg3.1) is specifically linked to memory formation and a number of cognitive disorders, including Alzheimer's disease and schizophrenia. …”
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Physical Model versus Artificial Neural Network (ANN) Model: A Comparative Study on Modeling Car-Following Behavior at Signalized Intersections by Lan Yang, Shan Fang, Guoyuan Wu, He Sheng, Zhigang Xu, Mengxiao Zhang, Xiangmo Zhao

“…In this study, two novel Artificial Neural Network (ANN) CF models, the Convolutional Neural Network—Long Short-term Memory (CNN-LSTM) and the Convolution-LSTM (Conv-LSTM)—are first applied to predict CF behaviors at signalized intersections. …”
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RETRACTED: Application of VMD–SSA–BiLSTM algorithm to smart grid financial market time series forecasting and sustainable innovation management by Chengran Yin, Guangming Wang, Jiacheng Liao

“…The resulting singular value spectrum matrices serve as input to a bidirectional long short-term memory (BiLSTM) neural network, which learns the feature representation and prediction model of the smart grid financial market through forward propagation and backpropagation.Results: The experimental results demonstrate that the proposed algorithm effectively predicts the smart grid financial market's time series, achieving high prediction accuracy and stability. …”
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Effect Improved for High-Dimensional and Unbalanced Data Anomaly Detection Model Based on KNN-SMOTE-LSTM by Fuguang Bao, Yongqiang Wu, Zhaogang Li, Yongzhao Li, Lili Liu, Guanyu Chen

“…This paper uses long short-term memory networks (LSTMs) combined with historical sequence data; also, it integrates the synthetic minority oversampling technique (SMOTE) algorithm and K-nearest neighbors (kNN), and it designs and constructs an anomaly detection network model based on kNN-SMOTE-LSTM in accordance with the data characteristic of being unbalanced. …”
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A New Hope in Immunotherapy for Malignant Gliomas: Adoptive T Cell Transfer Therapy by Dong-Sup Chung, Hye-Jin Shin, Yong-Kil Hong

“…Immunotherapy emerged as a promising therapeutic approach to highly incurable malignant gliomas due to tumor-specific cytotoxicity, minimal side effect, and a durable antitumor effect by memory T cells. But, antitumor activities of endogenously activated T cells induced by immunotherapy such as vaccination are not sufficient to control tumors because tumor-specific antigens may be self-antigens and tumors have immune evasion mechanisms to avoid immune surveillance system of host. …”
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Simulating Immune Interference on the Effect of a Bivalent Glycoconjugate Vaccine against Haemophilus influenzae Serotypes “a” and “b” by Angjelina Konini, Mingsong Kang, Seyed M. Moghadas

“…We compared simulation outcomes in the absence of any preexisting immunity with an already primed immune response having specific memory B cells and/or anti-Hib antibodies. Results. …”
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An Artificial Intelligence Approach for the Kinodynamically Feasible Trajectory Planning of a Car-like Vehicle by Vito Antonio Nardi, Marianna Lanza, Filippo Ruffa, Valerio Scordamaglia

“…The proposed solution is validated through numerical simulations, with a focus on the effects of different classificators features and by using two different kinds of artificial intelligence: a support vector machine (SVM) and a long-short term memory (LSTM). Results show up to a 28% reduction in computational effort and the importance of lowering the false negative rate in classification for achieving good planning performance outcomes.…”
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Prediction of Radiation Belts Electron Fluxes at a Low Earth Orbit Using Neural Networks With PROBA‐V/EPT Data by Edith Botek, Viviane Pierrard, Alexandre Winant

“…Abstract We introduce for the first time the PROBA‐V/EPT electron flux data to train a deep learning data‐driven model with the purpose of investigating the Earth’s radiation belts dynamics. The Long‐Short Term Memory Neural Network is employed to predict the electron fluxes between 1 and 8 Earth Radius (RE) along a Low Earth Orbit. …”
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Robustness of performance during domain change in an esport: A study of within-expertise transfer. by Joe Thompson, Justin W O'Camb, Robin C A Barrett, Scott Harrison, Mark R Blair

“…Research on the transfer of skill from the circumstances in which it was learned to partially or completely novel tasks or situations is a foundational topic in the study of learning, memory, education, and expertise. A long history of transfer research has led to the conclusion that skill learning is generally domain specific. …”
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Health promotion for dementia risk reduction in Indigenous populations of Canada, Aotearoa New Zealand, United States of America, and Australia: Scoping review protocol. by Kathryn Meldrum, Yvonne Hornby-Turner, Valda Wallace, Sarah G Russell, Rachel Quigley, Edward Strivens

“…Dementia, a collective name for brain disorders that impact thinking and memory, affects over 55 million people worldwide. …”
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Medical foods in Alzheimer’s disease by Klaus W. Lange, Jianjun Guo, Shigehiko Kanaya, Katharina M. Lange, Yukiko Nakamura, Shiming Li

“…Improvements in symptomatology and regional brain atrophy in AD have been claimed for several medical foods, for example, those providing ketone bodies as alternative energy supply to neurons, those containing precursors believed to improve synaptic function, and those addressing oxidative stress related to memory loss. Many methodological shortcomings render the interpretation of the available findings of medical food trials in AD difficult. …”
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PilotCareTrans Net: an EEG data-driven transformer for pilot health monitoring by Kun Zhao, Xueying Guo

“…However traditional methods like linear models Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) architectures often struggle to capture the complex, non-linear temporal dependencies in EEG signals. …”
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Towards a spectrally multiplexed quantum repeater by Tanmoy Chakraborty, Antariksha Das, Hedser van Brug, Oriol Pietx-Casas, Peng-Cheng Wang, Gustavo Castro do Amaral, Anna L. Tchebotareva, Wolfgang Tittel

“…Many repeater architectures require multiplexed sources of entangled photon pairs, multiplexed quantum memories, and photon detection that distinguishes between the multiplexed modes. …”
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The Prediction of Serum C-Reactive Protein Concentration Using Nonlinear Mixed-Effects Model by Suk Joo Bae, Gyu Ri Kim, Sun Geu Chae, Yeesuk Kim

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Event-Related Potentials in Parkinson’s Disease Patients with Visual Hallucination by Yang-Pei Chang, Yuan-Han Yang, Chiou-Lian Lai, Li-Min Liou

“…The frontal test battery was used to assess attention, visual-spatial function, verbal fluency, memory, higher executive function, and motor programming. …”
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A Bi‐level stacked LSTM‐DNN‐based decoder network for AGC dispatch under regulation market framework in presence of VPP and EV aggregators by Kingshuk Roy, Sanjoy Debbarma, Siddhartha Deb Roy, Liza Debbarma

“…In this context, a bi‐level AGC dispatch approach based on a stacked long short‐term memory (LSTM)‐deep neural network (DNN)‐based decoder framework is proposed for a power system comprising diverse CIGs forming a virtual power plant and electric vehicle aggregators. …”
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Deep Learning-Based Energy Consumption Prediction Model for Green Industrial Parks by Chaoan Lai, Yina Wang, Jianhua Zhu, Xuequan Zhou

“…To overcome the limitations of existing energy consumption forecasting methods, which inadequately consider the specific energy usage characteristics and user behaviors in parks and often perform poorly at predicting extreme values, this study proposes a hybrid energy consumption forecasting model combines Singular Spectrum Analysis (SSA) and Long Short-Term Memory (LSTM) neural networks. Initially, SSA is used to extract the autocorrelation of the electricity consumption series and eliminate the mutual interference caused by component mixing. …”
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Real-Time On-Device Continual Learning Based on a Combined Nearest Class Mean and Replay Method for Smartphone Gesture Recognition by Heon-Sung Park, Min-Kyung Sung, Dae-Won Kim, Jaesung Lee

“…Leveraging the Nearest Class Mean (NCM) classifier coupled with a replay-based update strategy, our method enables continuous adaptation to new gestures under limited computing and memory resources. By employing replay buffer management, we efficiently store and revisit previously learned instances, mitigating catastrophic forgetting and ensuring stable performance as new gestures are added. …”
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