Results 81 to 90 of about 29,272 (313)

Design and analysis strategies for robust microbiome ageing research

FEBS Letters, EarlyView.
The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik, İsmail Güderer, Yi Wang, Tayyaba Alvi, Prasoon Pandey, Handan Melike Dönertaş   +5 more
wiley   +1 more source

Modelling and forecasting short-term electricity load: a two step methodology [PDF]

The goal of this paper is to develop a forecasting model of the hourly electricity load demand in the area covered by an utility company located in the southeast of Brazil.
Lacir J. Soares, Marcelo Cunha Medeiros
core  

Forecasting Daily Gas Load with OIHF-Elman Neural Network

, 2011
To improve the forecasting accuracy, a model for forecasting daily gas load with OIHF-Elman network involving factors such as weather, temperature and data type is proposed.
Gang Su, Hong Zhou, Zhou, Hong, Su, Gang, Li, Guofang, Guofang Li   +5 more
core   +1 more source

Reconstructing enzyme evolution by protein engineering

FEBS Letters, EarlyView.
Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler, Markus R. Busch, Reinhard Sterner   +2 more
wiley   +1 more source

The role of miR‐335‐5p in the redifferentiation of BRAF p.V600E thyroid cancers

Molecular Oncology, EarlyView.
The BRAF p.V600E mutation promotes thyroid cancer dedifferentiation and radioiodine resistance. Using a network approach, we identified miR‐335‐5p as a key regulator of BRAF‐mutated thyroid tumors. Restoring miR‐335‐5p increased thyroid‐specific gene expression and iodine uptake in cells and organoids.
Valeria Pecce, Simone Bini, Marialuisa Sponziello, Giorgio Grani, Giulia Fiscon, Paola Paci, Lorenzo Farina, Rosa Falcone, Valentina Maggisano, Sebastiano Filetti, Cosimo Durante, Antonella Verrienti   +11 more
wiley   +1 more source

Short-term load forecasting of urban gas using a hybrid model based on improved fruit fly optimization algorithm and support vector machine

Energy Reports, 2019
The accurate forecasting of short-term load for urban gas is the premise of gas supply sales, pipe network planning, and energy optimization scheduling.
Hongfang Lu, Mohammadamin Azimi, Tom Iseley   +2 more
doaj   +1 more source

Short-term load forecasting based on a semi-parametric additive model [PDF]

Short-term load forecasting is an essential instrument in power system planning, operation and control. Many operating decisions are based on load forecasts, such as dispatch scheduling of generating capacity, reliability analysis, and maintenance ...
Rob Hyndman, Shu Fan
core  

TRAIL‐PEG‐Apt‐PLGA nanosystem as an aptamer‐targeted drug delivery system potential for triple‐negative breast cancer therapy using in vivo mouse model

Molecular Oncology, EarlyView.
Aptamers are used both therapeutically and as targeting agents in cancer treatment. We developed an aptamer‐targeted PLGA–TRAIL nanosystem that exhibited superior therapeutic efficacy in NOD/SCID breast cancer models. This nanosystem represents a novel biotechnological drug candidate for suppressing resistance development in breast cancer.
Gulen Melike Demirbolat, Aslihan Kucuk, Omer Erdogan, Samed Ozer, Bensu Kozan, Tugba Cuceli, Erkan Gumus, Evrim Cevik, Ozge Cevik   +8 more
wiley   +1 more source

Differentially Private Clustered Federated Load Prediction Based on the Louvain Algorithm

Algorithms
Load forecasting plays a fundamental role in the new type of power system. To address the data heterogeneity and security issues encountered in load forecasting for smart grids, this paper proposes a load-forecasting framework suitable for residential ...
Tingzhe Pan, Jue Hou, Xin Jin, Chao Li, Xinlei Cai, Xiaodong Zhou   +5 more
doaj   +1 more source

Automated Deep Learning for Load Forecasting

CoRR
Accurate forecasting of electricity consumption is essential to ensure the performance and stability of the grid, especially as the use of renewable energy increases. Forecasting electricity is challenging because it depends on many external factors, such as weather and calendar variables.
Keisler, Julie, Claudel, Sandra, Cabriel, Gilles, Brégère, Margaux   +3 more
openaire   +5 more sources