Reduced‐Order Probabilistic Emulation of Physics‐Based Ring Current Models: Application to RAM‐SCB Particle Flux by Alfredo A. Cruz, Rashmi Siddalingappa, Piyush M. Mehta, Steven K. Morley, Humberto C. Godinez, Vania K. Jordanova

“…Focusing on a subset of particle flux, we use Principal Component Analysis for dimensionality reduction and Long Short‐Term Memory (LSTM) neural networks to perform dynamic modeling. …”
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CD4+CD25highCD127low/−FoxP3+ Regulatory T Cell Subpopulations in the Bone Marrow and Peripheral Blood of Children with ALL: Brief Report by M. Niedźwiecki, O. Budziło, M. Zieliński, E. Adamkiewicz-Drożyńska, L. Maciejka-Kembłowska, T. Szczepański, P. Trzonkowski

“…By analyzing Treg subpopulations, it was shown that only memory Tregs in contact with leukemic antigens showed statistically significant differences. …”
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Temporal Forecasting of Distributed Temperature Sensing in a Thermal Hydraulic System With Machine Learning and Statistical Models by Stella Pantopoulou, Matthew Weathered, Darius Lisowski, Lefteri H. Tsoukalas, Alexander Heifetz

“…We benchmark performance of long-short term memory (LSTM) network machine learning model and autoregressive integrated moving average (ARIMA) statistical model in temporal forecasting of distributed temperature sensing (DTS). …”
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Comparative Analysis of TPA‐LSTM and Transformer Models for Forecasting GEO Radiation Belt Electron Fluxes by Mengli Tan, Xu Si, Shangchun Teng, Xinming Wu, Xin Tao

“…In this study, we develop and compare two neural networks for persistent high‐time‐resolution prediction: long short‐term memory with temporal pattern attention (TPA‐LSTM) and Transformer. …”
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Self-translation as re-creation: The incipit of a fantasy novel in French (original language) and English by Emma SCHÜTZ

“…After waking up in an alien landscape with no memory of his arrival, Pascal discovers that he is not alone: with him are five other Academy students, as well as Yolanda, a gardener at the university. …”
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An In-Depth Study of Personalized Anesthesia Management Models in Gastrointestinal Endoscopy Based on Multimodal Deep Learning by Hanqi Shi, Hongyu Wang, Xibing Ding, Zheng Dang

“…Based on these findings, a multimodal deep learning model was developed that integrates Long Short-Term Memory (LSTM) networks, hyperparameter geometric manifold optimization (GMO) methods and data-driven sparse matrix classifiers. …”
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System Design for a Prototype Acoustic Network to Deter Avian Pests in Agriculture Fields by Destiny Kwabla Amenyedzi, Micheline Kazeneza, Ipyana Issah Mwaisekwa, Frederic Nzanywayingoma, Philibert Nsengiyumva, Peace Bamurigire, Emmanuel Ndashimye, Anthony Vodacek

“…The prototype was able to make inferences in 53 ms using only 14.8 k of peak RAM and only 43.8 K of flash memory to store the model. Results from the prototype deployment in the field demonstrated successful detection and triggering actions and SMS messaging notifications. …”
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Association of objective and subjective socioeconomic markers with cognitive impairment among older adults: cross-sectional evidence from a developing country by Shobhit Srivastava, T Muhammad, TV Sekher

“…The sample included 31 464 older adults aged 60 years and above.Primary and secondary outcome measures Outcome variable was cognitive impairment, measured through broad domains of memory, orientation, arithmetic function, and visuo-spatial and constructive skills. …”
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Automated Cattle Monitoring System for Calving Time Prediction Using Trajectory Data Embedded Time Series Analysis by Wai Hnin Eaindrar Mg, Thi Thi Zin, Pyke Tin, Masaru Aikawa, Kazayuki Honkawa, Yoichiro Horii

“…Our system incorporates a 4-h forecasting of cattle movement using Euclidean fluctuating summation (EFS) feature combined with our custom long short-term memory model. Experimental results demonstrate a detection accuracy of 98.70%, tracking and identification accuracy of 99.18%, and forecasting with an average error rate of 14.07%. …”
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Intelligent model for forecasting fluctuations in the gold price by Mahdieh Tavassoli, Mahnaz Rabeei, Kiamars Fathi Hafshejani

“…The study also employed Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Multi-Layer Perceptron (MLP) neural network models in deep learning mode to predict gold price fluctuations. …”
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Psychological testing in children with elevated blood lead level: the effect of spirulina by N.I. Hnida, N.H. Lotysh, D.V. Usenko, I.M. Hnidoi, V.N. Kukushkin

“…In children with elevated blood lead level, there was a significant increase in cognitive impairment (memory and attention) compared to control scores. …”
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A Spatio-Temporal Deep Learning Model for Automatic Arctic Sea Ice Classification with Sentinel-1 SAR Imagery by Li Zhao, Yufeng Zhou, Wei Zhong, Cheng Jin, Bo Liu, Fangzhao Li

“…Experimental results demonstrate that our proposed method outperforms the long short-term memory (LSTM) network approach in distinguishing between sea ice types with similar developmental stages. …”
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Capivasertib enhances chimeric antigen receptor T cell activity in preclinical models of B cell lymphoma by Hui-Ju Hsieh, Ryan Urak, Mary C. Clark, Larry W. Kwak, Stephen J. Forman, Xiuli Wang

“…Mechanistically, capivasertib changed gene and protein expression patterns related to the functions of memory and effector CAR T cells. Furthermore, in vivo combination therapy of capivasertib and CD19-specific CAR T cells led to improved early response to and persistence of functional CAR T cells in mice bearing PTEN-deficient lymphoma cells compared to CAR T cells alone. …”
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Longitudinal evaluation of cognition after stroke - A systematic scoping review. by Juan Pablo Saa, Tamara Tse, Carolyn Baum, Toby Cumming, Naomi Josman, Miranda Rose, Leeanne Carey

“…Global cognition was evaluated in 170 reports (66%), followed by higher-level cognitive functioning (29%), memory (28%), language (21%), attention (21%), and perceptual skills (14%). …”
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Learned phenotypes emerge during social stress modifying hippocampal orexin receptor gene expression by Jazmine D. W. Yaeger, Justin K. Achua, Clarissa D. Booth, Delan Khalid, Megan M. John, Leighton J. Ledesma, Trent L. Greschke, Ashley M. Potter, Chase B. Howe, Kevin T. Krupp, Justin P. Smith, Patrick J. Ronan, Cliff H. Summers

“…The hippocampus, studied for its role in learning, is divided into regions that designate the passage of neuronal signaling during memory formation, including dentate gyrus (DG), CA3, CA2, and CA1. …”
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Association of serum neurofilament light chain with cognitive impairment: findings from the National Health and Nutrition Examination Survey by Tianjiao Meng, Qinwen Fei, Tian Lv, Shiqin Chen

“…The nomogram model based on NfL identified by LASSO regression displayed a considerable predicative value for low total-CF, with an area under the curve [AUC = 85.6% (81.6–89.3%)].ConclusionThere is a strong correlation between serum NfL levels and cognitive function, especially DSST, which reflects attention and information processing abilities, as well as overall cognitive function, but not memory and language fluency. Thus, NfL may serve as a serum biomarker for dementia monitoring.…”
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The Ratio of CD226 and TIGIT Expression in Tfh and PD-1+ICOS+Tfh Cells Are Potential Biomarkers for Chronic Antibody-Mediated Rejection in Kidney Transplantation by Ji-wen Fan, Yu Fan, Zheng-li Wan, Lin Yan, Ya-mei Li, Yang-juan Bai, Lan-lan Wang, Jie Chen, Yi Li

“…Compared with stable recipients, CAMR patients had lower naïve B cells and higher unswitched memory B cells, which were also significantly related to renal function (p<0.05). …”
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Investigation into the Prediction of Ship Heave Motion in Complex Sea Conditions Utilizing Hybrid Neural Networks by Yuchen Liu, Xide Cheng, Kunyu Han, Zhechun Liu, Baiwei Feng

“…Consequently, this paper proposes a hybrid neural network method that combines Convolutional Neural Networks (CNNs), Bidirectional Long Short-Term Memory Networks (BiLSTMs), and an Attention Mechanism to predict the heaving motion of ships in moderate to complex sea conditions. …”
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A scoping review on the psychosocial interventions used in day care service for people living with dementia. by Dympna Tuohy, Liz Kingston, Eileen Carey, Margaret Graham, Liz Dore, Owen Doody

“…Within this review, interventions were grouped into five broad types: nature (n = 6 papers), memory/cognitive (n = 11 papers), social (n = 17 papers), animal (n = 4 papers), or physical/sensory (n = 7 papers) based interventions.…”
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SACNN‐IDS: A self‐attention convolutional neural network for intrusion detection in industrial internet of things by Mimonah Al Qathrady, Safi Ullah, Mohammed S. Alshehri, Jawad Ahmad, Sultan Almakdi, Samar M. Alqhtani, Muazzam A. Khan, Baraq Ghaleb

“…For instance, the existing DL approaches necessitate a substantial quantity of data for effective performance, which is not feasible to run on low‐power and low‐memory devices. Imbalanced and fewer data potentially lead to low performance on existing IDS. …”
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