-
41
Global Stability of Switched HIV/AIDS Models with Drug Treatment Involving Caputo-Fractional Derivatives
Published 2021-01-01“…Finally, some simulations are employed to support the main results and one future research direction is presented.…”
Get full text
Article -
42
Patient stratification by genetic risk in Alzheimer's disease is only effective in the presence of phenotypic heterogeneity.
Published 2025-01-01“…Case-only designs in longitudinal cohorts are a valuable resource for identifying disease-relevant genes, pathways, and novel targets influencing disease progression. This is particularly relevant in Alzheimer's disease (AD), where longitudinal cohorts measure disease "progression," defined by rate of cognitive decline. …”
Get full text
Article -
43
Insulin in Central Nervous System: More than Just a Peripheral Hormone
Published 2012-01-01“…Insulin signaling in central nervous system (CNS) has emerged as a novel field of research since decreased brain insulin levels and/or signaling were associated to impaired learning, memory, and age-related neurodegenerative diseases. …”
Get full text
Article -
44
-
45
Dystopia, surveillance and the spaces of social control in Jenni Fagan’s The Panopticon (2012)
Published 2022-11-01“…Although Jenni Fagan's The Panopticon (2012) does not qualify as a classic dystopia detailing a possible and undesirable future state of society, the novel shares some traits of the genre, including a protagonist struggling with a system against which she rebels. …”
Get full text
Article -
46
Deep Learning the Forecast of Galactic Cosmic-Ray Spectra
Published 2025-01-01“…We introduce a novel deep learning framework based on long short-term memory networks to predict galactic cosmic-ray spectra on a one-day-ahead basis by leveraging historical solar activity data, overcoming limitations inherent in traditional transport models. …”
Get full text
Article -
47
Stock price prediction with attentive temporal convolution-based generative adversarial network
Published 2025-03-01“…A TCN can achieve extensive sequence memory by utilizing dilated convolutions, enabling it to capture long-term dependencies in time-series data, as well as causal convolution, ensuring that the model does not utilize future information when predicting future values, which is particularly crucial for time-series prediction. …”
Get full text
Article -
48
Bioinformatics insights into mitochondrial and immune gene regulation in Alzheimer's disease
Published 2025-02-01“…These findings provide new insights for research on Alzheimer's disease in the context of mitochondrial–immune interactions, further exploring the pathogenesis of Alzheimer's disease and offering new perspectives for the clinical development of novel drugs. Conclusions Five mitochondrial and immune biomarkers, i.e., TSPO, HIGD1A, NDUFAB1, NT5DC3, and MRPS30, with diagnostic value in Alzheimer's disease, were screened by machine-learning algorithmic models, which will be a guide for future clinical research of Alzheimer's disease in the mitochondria–immunity-related direction.…”
Get full text
Article -
49
Leveraging Quantum LSTM for High-Accuracy Prediction of Viral Mutations
Published 2025-01-01“…In response to these challenges, this study introduces a novel quantum-enhanced LSTM (QLSTM) model designed to predict genetic mutations, specifically focusing on viral protein sequences. …”
Get full text
Article -
50
Leveraging Deep Spatiotemporal Sequence Prediction Network with Self-Attention for Ground-Based Cloud Dynamics Forecasting
Published 2024-12-01“…This paper presents CloudPredRNN++, a novel method for predicting ground-based cloud dynamics, leveraging a deep spatiotemporal sequence prediction network enhanced with a self-attention mechanism. …”
Get full text
Article -
51
-
52
Irisin Exerts Neuroprotective Effects on Cultured Neurons by Regulating Astrocytes
Published 2018-01-01“…Our finding may provide novel evidence for the future application of irisin in the treatment of Alzheimer’s disease and the memory dysfunction in diabetes mellitus.…”
Get full text
Article -
53
-
54
Prediction of the SYM‐H Index Using a Bayesian Deep Learning Method With Uncertainty Quantification
Published 2024-02-01“…Abstract We propose a novel deep learning framework, named SYMHnet, which employs a graph neural network and a bidirectional long short‐term memory network to cooperatively learn patterns from solar wind and interplanetary magnetic field parameters for short‐term forecasts of the SYM‐H index based on 1‐ and 5‐min resolution data. …”
Get full text
Article -
55
The emerging role of glycine receptor α2 subunit defects in neurodevelopmental disorders
Published 2025-02-01“…As a result, microcephaly is observed in newborn Glra2 knockout mice, as well as defects in neuronal morphology, increased susceptibility to seizures, and defects in novel object recognition, motor memory consolidation, righting reflexes, novelty-induced locomotion in the open field test, and motivational reward tasks. …”
Get full text
Article -
56
Numerical Weather Data-Driven Sensor Data Generation for PV Digital Twins: A Hybrid Model Approach
Published 2025-01-01“…Furthermore, the DT systems simulate the operations of the physical systems in real-time based on the data collected from various sensors. To this end, a novel sensor data generation model based on numerical weather prediction (NWP) data is proposed to forecast the future operations of PV systems using DT systems. …”
Get full text
Article -
57
Dual-hybrid intrusion detection system to detect False Data Injection in smart grids.
Published 2025-01-01“…This paper addresses this gap by proposing a novel IDS that utilizes hybrid feature selection and deep learning classifiers to detect FDIAs in smart grids. …”
Get full text
Article -
58
-
59
Development and Evaluation of an AI-based Exergame Training System for Ice-Hockey Players: a Randomized Controlled Trial
Published 2025-01-01“…EF are divided into the three core components cognitive flexibility, inhibition or interference control, and working memory (Diamond, 2013). Elite athletes perform better in EF tasks compared to non-elite athletes (Logan et al., 2023) and higher EF may predict future elite potential in young team sports athletes (Lundgren et al., 2016; Vestberg et al., 2012). …”
Get full text
Article -
60
Vertical Silicon Nanowire Platform for Low Power Electronics and Clean Energy Applications
Published 2012-01-01“…This paper reviews the progress of the vertical top-down nanowire technology platform developed to explore novel device architectures and integration schemes for green electronics and clean energy applications. …”
Get full text
Article
