The central role of tilted anisotropy for field-free spin–orbit torque switching of perpendicular magnetization by Chen-Yu Hu, Wei-De Chen, Yan-Ting Liu, Chao-Chung Huang, Chi-Feng Pai

“…Abstract The discovery of efficient magnetization switching upon device activation by spin Hall effect (SHE)-induced spin–orbit torque (SOT) changed the course of magnetic random-access memory (MRAM) research and development. However, for electronic systems with perpendicular magnetic anisotropy (PMA), the use of SOT is still hampered by the necessity of a longitudinal magnetic field to break magnetic symmetry and achieve deterministic switching. …”
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MAF-CNER : A Chinese Named Entity Recognition Model Based on Multifeature Adaptive Fusion by Xuming Han, Feng Zhou, Zhiyuan Hao, Qiaoming Liu, Yong Li, Qi Qin

“…The model uses bidirectional long short-term memory (BiLSTM) neural network to extract stroke and radical features and adopts a weighted concatenation method to fuse two sets of features adaptively. …”
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The Story of CD4+CD28− T Cells Revisited: Solved or Still Ongoing? by Kathrin Maly, Michael Schirmer

“…CD4+CD28− T cells present as effector/memory cells with increased replicative history and oligoclonality but reduced apoptosis. …”
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Development of Embedded Boot Software for a Satellite Instrument Control Unit: Lessons Learned by Jesús Fernández-Conde, Jaime Gómez-Saez-de-Tejada, David Pérez-Lizán, Rafael Toledo-Moreo

“…The ICU BSW is a nonpatchable, stand-alone, real-time software package that initializes the ICU HW, performs self-tests, and waits for CDMU commands to maintain on-board memory and ultimately start a patchable application software (ASW), which is responsible for execution of the nominal tasks assigned to the ICU (control of the satellite instrument being the most important one). …”
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Enhanced early prediction of Li-ion battery degradation using multicycle features and an ensemble deep learning model by Meilia Safitri, Teguh Bharata Adji, Adha Imam Cahyadi

“…This study introduces a GRU-LSTM ensemble model that combines Gated Recurrent Units (GRU) and Long Short-Term Memory (LSTM) networks to forecast the end-of-life (EoL) of LIBs. …”
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Isolation of Pleurotus florida derived acetylcholinesterase inhibitor for the treatment of cognitive dysfunction in mice by Kudrat Randhawa, Varinder Singh, Sanimardeep Kaur, Ravinder Kaur, Suresh Kumar, Richa Shri

“…Morris water maze test was used for evaluating memory, followed by biochemical estimations and histopathological studies. …”
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Imputation based wind speed forecasting technique during abrupt changes in short term scenario by Karan Sareen, Bijaya Ketan Panigrahi, Tushar Shikhola, Ravi Nath Tripathi, Ashok Kumar Rajput

“…Furthermore, the bi‐directional long‐short term memory deep learning approach is tied with convolution neural network to increase prediction accuracy and anticipating the sudden/abrupt changes in wind speed accurately. …”
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Prediction of the transient coolant jet released from the nose cone at supersonic flow via machine learning by A. B. Ali, M. Yasiri, Pooya Ghodratallah, Kamal Sharma, Nimesh Raj, S. Abdul Ameer, Mohammed Yaseen Abdullah, Abbas Hameed Abdul Hussein, Mohammed Y. Al-Khuzaie, M. Ahmedi

“…Abstract In this paper, the usage of a predictive surrogate model for the estimate of flow variables in the transient phase of coolant injection from the nose cone by combining the Long Short-Term Memory (LSTM) and Proper Orthogonal Decomposition (POD) technique. …”
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Soft Error-Tolerant and Highly Stable Low-Power SRAM for Satellite Applications by Jong-Yeob Oh, Sung-Hun Jo

“…As CMOS technology has advanced, the transistor integration density of static random-access memory (SRAM) cells has increased. This has led to a reduction in the critical charge of sensitive nodes, making the SRAM cells more susceptible to soft errors. …”
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Cognitive Impairment in Heart Failure by Efthimios Dardiotis, Gregory Giamouzis, Dimos Mastrogiannis, Christina Vogiatzi, John Skoularigis, Filippos Triposkiadis, Georgios M. Hadjigeorgiou

“…Cognitive decline in HF is characterized by deficits in one or more cognition domains, including attention, memory, executive function, and psychomotor speed. …”
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Multifeature Short-Term Power Load Forecasting Based on GCN-LSTM by Houhe Chen, Mingyang Zhu, Xiao Hu, Jiarui Wang, Yong Sun, Jinduo Yang, Baoju Li, Xiangdong Meng

“…To fully exploit the massive information contained in data, based on the graph convolutional network (GCN) and long short-term memory network (LSTM), this paper presents a new short-term load forecasting method for power systems considering multiple factors. …”
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A New Website Fingerprinting Method for Tor Hidden Service by Zihang Hui, Jiangtao Zhai, Shengxian Wang, Weijie Ji

“…To address this problem, a new website fingerprinting method that combines the Bidirectional Encoder Representations from Transformers (BERT) model and a Long Short-Term Memory (LSTM) network was proposed to improve the accuracy of website fingerprinting for Tor hidden services. …”
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Immune Dysregulation after Cardiothoracic Surgery and Incidental Thymectomy: Maintenance of Regulatory T Cells despite Impaired Thymopoiesis by Nancy J. Halnon, Paige Cooper, Diana Yu Hui Chen, M. Ines Boechat, Christel H. Uittenbogaart

“…TCR spectratypes were similar to other memory T cells. These data suggest that thymectomy does not reduce total Treg number but homeostasis is affected with reduced naïve Treg. …”
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Building an Oral Repository of African Immigration Experiences in French: The Griotte Project’s Reparative Historiographic Praxis Through Service-Learning at the University of Cent... by K. Adele Okoli

“…When we occupy and open the archive as a space of experiential learning and shared knowledge creation, we are transforming an institutional site of memory to write a more accurate, just, and inclusive history for the future.…”
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Vision Transformers for Image Classification: A Comparative Survey by Yaoli Wang, Yaojun Deng, Yuanjin Zheng, Pratik Chattopadhyay, Lipo Wang

“…Additionally, transformers excel at capturing long-range dependencies and enabling parallel processing, which allows them to outperform traditional models, such as long short-term memory (LSTM) networks, on sequence-based tasks. In recent years, transformers have been widely adopted in computer vision, driving remarkable advancements in the field. …”
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Parking Volume Forecast of Railway Station Garages Based on Passenger Behaviour Analysis Using the LSTM Network by Songxue Gai, Xiaoqing Zeng, Tengfei Yuan

“…Also, a novel parking volume forecast model based on the long short-term memory (LSTM) is proposed. In this paper, the parking volume data of public parking garages of Hongqiao Railway Station in Shanghai of China is used to verify the model, and the proposed model makes it possible for the accurate and real-time prediction of parking volumes which are divided into different parking duration categories. …”
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Multifaceted neuroprotective effects of (-)-epigallocatechin-3-gallate (EGCG) in Alzheimer’s disease: an overview of pre-clinical studies focused on β-amyloid peptide by Kumju Youn, Chi-Tang Ho, Mira Jun

“…ABSTRACT: Alzheimer’s disease (AD) is the most common neurodegenerative disease characterized by cognitive decline and memory impairment. Many lines of evidence indicate that excessive β-amyloid peptide (Aβ) generation and aggregation play pivotal roles in the initiation of AD, leading to various biochemical alteration including oxidative damage, mitochondrial dysfunction, neuroinflammation, signaling pathway and finally resulting in neuronal death. …”
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Validity and reliability of the executive function scale in Cuban university student by Diego D. Díaz-Guerra, Marena De La C. Hernández-Lugo, Carlos Ramos-Galarza, Yunier Broche-Pérez

“…IntroductionExecutive functions are higher cognitive skills involved in planning, organization, decision-making, impulse control, and working memory. It is essential to have tools that allow for the accurate and reliable assessment of this construct in university students. …”
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Optimal adjustment of deep neural network parameters in estimating lost vital sign data in body wireless sensor networks by Aboulfazl Ebrahimi, Mahboubeh Shamsi, Morteza Mohajjel

“…In order to predict the missing values, a model for estimating lost data based on LSTM (short-term memory) neural network is presented in this paper. …”
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Learning From High-Cardinality Categorical Features in Deep Neural Networks by Mustafa Murat Arat

“…Our proposed approach is low dimensional; thus, it is very efficient in processing time and memory, it can be computed in an online learning setting. …”
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