Results 51 to 60 of about 5,621 (256)

Short-Term Load Forecasting Based on Multi-Scale Ensemble Deep Learning Neural Network

IEEE Access, 2023
High-precision load forecasting is crucial for the power system planning and electricity market transactions. Recently, deep learning models have been widely used due to their powerful data mining capabilities. However, the existing research mainly focus
Qin Shen, Li Mo, Guanjun Liu, Jianzhong Zhou, Yongchuan Zhang, Pinan Ren   +5 more
doaj   +1 more source

Epigenetic heterogeneity and plasticity in therapy‐induced tumor states through single‐cell multi‐omics

Molecular Oncology, EarlyView.
Single‐cell multi‐omics reveals epigenetic heterogeneity across therapy‐adaptive tumor states, including quiescent/dormant, drug‐tolerant persister, and EMT‐like phenotypes. By linking regulatory features with state‐associated biomarkers, these approaches inform biomarker‐guided therapeutic strategies for evolving tumors.
Hee Jung Kim, Hwiyeong Lee, Jin Hong, Daechan Park   +3 more
wiley   +1 more source

Promiscuous stimulation of HSP70 ATPase activity by parasite‐derived J‐domains

FEBS Open Bio, EarlyView.
The malaria parasite Plasmodium falciparum exports three highly homologous yet functionally divergent J‐domain proteins into human erythrocytes. Here, we show that J‐domains isolated from all three proteins effectively stimulate the ATPase activity of both endogenous host and exported parasite HSP70 chaperones.
Julian Barth, Moritz Koch, Le‐Han Rössner, Johanna Eichhorn, Denys Pogoryelov, Matthias P. Mayer, Jude M. Przyborski   +6 more
wiley   +1 more source

Ultra Short-Term Power Load Forecasting Based on Similar Day Clustering and Ensemble Empirical Mode Decomposition

Energies, 2023
With the increasing demand of the power industry for load forecasting, improving the accuracy of power load forecasting has become increasingly important.
Wenhui Zeng, Jiarui Li, Changchun Sun, Lin Cao, Xiaoping Tang, Shaolong Shu, Junsheng Zheng   +6 more
doaj   +1 more source

MiR‐513a promotes human erythroid differentiation by modulating c‐Jun

FEBS Open Bio, EarlyView.
During early human erythropoiesis, miR‐513a promoted erythroid differentiation in primary human CD34+ hematopoietic stem‐progenitor cells and human TF‐1 erythroleukemic cells by indirectly decreasing c‐Jun and phospho‐c‐Jun expression, which are associated with increased GATA1 expression.
MinJung Kim, Brittany Taylor, Shannon Bolten, Christian L. Eberly, Mahliya Abdurahman, T. Michael Creed, Acong Yang, Taylor L. Hatchet, Tristan Dyson, Shuo Gu, Curt I. Civin, Tami J. Kingsbury   +11 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

Guiding AlphaFold to predict how Munc13‐1 opens Syntaxin‐1

FEBS Open Bio, EarlyView.
The syntaxin‐1 Habc‐domain (orange), linker (pink) and SNARE motif (yellow) form a closed conformation that binds to Munc18‐1 (violet) and is opened by the Munc13‐1 MUN domain (cyan) to form the SNARE complex that triggers neurotransmitter release.
Madhurima Chattopadhyay, Junjie Xu, Josep Rizo   +2 more
wiley   +1 more source

A data mining method for short‐term load forecasting in power systems

Electrical Engineering in Japan, 2001
AbstractThis paper proposes a method for daily maximum load forecasting in power systems. It is based on the integration of the regression tree and the artificial neural network. In this paper, the regression tree is used to extract knowledge or rules as a data‐mining method. That is useful for the information processing of the complicated data.
Hiroyuki Mori, Noriyuki Kosemura
openaire   +2 more sources

Short-Term Load Forecasting Using a Novel Deep Learning Framework

Energies, 2018
Short-term load forecasting is the basis of power system operation and analysis. In recent years, the use of a deep belief network (DBN) for short-term load forecasting has become increasingly popular. In this study, a novel deep-learning framework based
Xiaoyu Zhang, Rui Wang, Tao Zhang, Yajie Liu, Yabing Zha   +4 more
doaj   +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