Results 111 to 120 of about 8,161 (262)

The Short-Term Load Forecasting Using an Artificial Neural Network Approach with Periodic and Nonperiodic Factors: A Case Study of Tai'an, Shandong Province, China. [PDF]

Comput Intell Neurosci, 2021
Sun J, Dong H, Gao Y, Fang Y, Kong Y.
europepmc   +1 more source

Location‐Specific Hematoma Volume Predicts Early Neurological Deterioration in Supratentorial ICH

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Early neurological deterioration (END) adversely affects outcomes in patients with intracerebral hemorrhage (ICH). This study aimed to determine the location‐specific hematoma volumes for END in supratentorial ICH patients. Methods We retrospectively analyzed supratentorial ICH patients presenting from two prospective cohorts.
Zuoqiao Li, Guilin Meng, Zijie Wang, Xiao Hu, Jing Cheng, Chu Chen, Tiannan Yang, Jiaxin Luo, Zizhen Meng, Xueyun Liu, Qi Li   +10 more
wiley   +1 more source

Factor Affecting Short Term Load Forecasting [PDF]

Journal of Clean Energy Technologies, 2014
Muhammad Usman Fahad, Naeem Arbab
openaire   +1 more source

Onasemnogene Abeparvovec in Type I Spinal Muscular Atrophy: 24‐Month Follow‐Up From the Italian Registry

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Onasemnogene abeparvovec (OA) is an AAV9‐based gene therapy for spinal muscular atrophy type I (SMA I). Real‐world outcomes show increased response variability compared to clinical trials, and follow‐up data beyond 12–18 months are limited.
Marika Pane, Giorgia Coratti, Chiara Cutrì, Antonio Varone, Riccardo Masson, Adele D'Amico, Valeria Sansone, Sonia Messina, Federica Ricci, Chiara Ticci, Claudio Bruno, Caterina Agosto, Francesca Benedetti, Antonella Pini, Sabrina Siliquini, Massimiliano Filosto, Alberto Zambon, Ilaria Bitetti, Maria Rosaria Manna, Claudia Dosi, Riccardo Zanin, Stefano Parravicini, Roberto De Sanctis, Giulia Stanca, Michela Catteruccia, Michele Tosi, Irene Mizzoni, Emilio Albamonte, Valentina Franchino, Maria Sframeli, Ilaria Cavallina, Elena Procopio, Michele Sacchini, Simone Morando, Noemi Brolatti, Federica Trucco, Gaia Scarpini, Elena Briganti, Beatrice Berti, Concetta Palermo, Daniela Leone, Stefano C. Previtali, Eugenio Mercuri, the ITASMAC working group   +43 more
wiley   +1 more source

A Short-Term Load Forecasting Method Considering Multiple Factors Based on VAR and CEEMDAN-CNN-BILSTM

Energies
Short-term load is influenced by multiple external factors and shows strong nonlinearity and volatility, which increases the forecasting difficulty. However, most of existing short-term load forecasting methods rely solely on the original load data or ...
Bao Wang, Li Wang, Yanru Ma, Dengshan Hou, Wenwu Sun, Shenghu Li   +5 more
doaj   +1 more source

Elevated Connectivity During Language Processing Is Associated With Cognitive Performance in SeLECTS

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Self‐Limited Epilepsy with Centrotemporal Spikes (SeLECTS) is associated with language impairments despite seizures originating in the motor cortex, suggesting aberrant cross‐network interactions. Here we tested whether functional connectivity in SeLECTS during language tasks predicts language performance.
Wendy Qi, Katharine Lee, Kerry C. Nix, Miguel Menchaca, Xiwei Shé, Lorelei Santa Maria, Wei Wu, Zihuai He, Fiona M. Baumer   +8 more
wiley   +1 more source

A Systematic Comparison of Alpha‐Synuclein Seed Amplification Assays for Increasing Reproducibility

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Seed amplification assays (SAAs) enable ultrasensitive detection of misfolded α‐synuclein across biofluids and tissues. Yet, heterogeneity in protocols limits cross‐study comparability and clinical translation. Here, we review α‐synuclein SAA methods and their performance across various biological matrices.
Manuela Amaral‐do‐Nascimento, Daniela F. Santos, Tuane C. R. G. Vieira, Tiago F. Outeiro   +3 more
wiley   +1 more source

Short-term load estimation based on improved DBN-LSTM

Sustainable Energy Research
Aiming at the rapid change and low forecasting accuracy of short-term power load forecasting, a forecasting model based on the improved deep belief network and long short-term memory network is proposed.
Nan Dong, Yuwen Wu, Buyun Su, Zhanzhi Liu   +3 more
doaj   +1 more source

Optimizing Models and Data Denoising Algorithms for Power Load Forecasting

Energies
To handle the data imbalance and inaccurate prediction in power load forecasting, an integrated data denoising power load forecasting method is designed.
Yanxia Li, Ilyosbek Numonov Rakhimjon Ugli, Yuldashev Izzatillo Hakimjon Ugli, Taeo Lee, Tae-Kook Kim   +4 more
doaj   +1 more source

Advancing Age Modulates Associations Between Cognitive Impairment and Brain Volumes in Early MS

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Introduction Cognitive impairment is common in multiple sclerosis (MS), but manifestations following the first demyelinating event are relatively unexplored. We investigated cross‐sectional associations between magnetic resonance imaging (MRI)–derived brain volumes and the presence of cognitive impairment outcomes five years after the first ...
Piriyankan Ananthavarathan, Marco Pitteri, Michael Foster, Sara Collorone, Sara Salama, Elisa Colato, Ferran Prados, Baris Kanber, Marios Yiannakas, Claudia A. M. Gandini Wheeler‐Kingshott, Indran Davagnanam, Frederik Barkhof, Declan Chard, Olga Ciccarelli, Ahmed Toosy   +14 more
wiley   +1 more source