Results 71 to 80 of about 113,463 (315)
Frequency-Constrained Learning for Long-Term Forecasting
CoRRMany real-world time series exhibit strong periodic structures arising from physical laws, human routines, or seasonal cycles. However, modern deep forecasting models often fail to capture these recurring patterns due to spectral bias and a lack of frequency-aware inductive priors.
Menglin Kong +2 more
openaire +2 more sources
Molecular Oncology, EarlyView.Loss of the miR‐214/199a cluster is associated with recurrence in ovarian cancer. Engineered small extracellular vesicles (m214‐sEVs) elevate miR‐214‐3p/miR‐199a‐5p in tumor cells, suppress β‐catenin, TLR4, and YKT6 signaling, reprogram tumor‐derived sEV cargo, reduce chemoresistance and migration, and enhance carboplatin efficacy and survival in ...
Weida Wang +12 more
wiley +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
IET Renewable Power GenerationWith the increasing penetration of grid‐scale wind energy systems, accurate wind power forecasting is critical to optimizing their integration into the power system, ensuring operational reliability, and enabling efficient system asset utilization ...
Mehmet Balci +3 more
doaj +1 more source
ECG Forecasting System Based on Long Short-Term Memory
BioengineeringWorldwide, cardiovascular diseases are some of the primary causes of death; yet the early detection and diagnosis of such diseases have the potential to save many lives.
Henriques Zacarias +4 more
doaj +1 more source
Improving Inflation Forecasts in the Medium to Long Term
Economic Commentary (Federal Reserve Bank of Cleveland), 2013 A simple but powerful technique for incorporating a changing underlying inflation trend into standard statistical time series models can improve forecast accuracy significantly—about 20 percent to 30 percent, two to three years out.
openaire +1 more source
Somatic mutational landscape in von Hippel–Lindau familial hemangioblastoma
Molecular Oncology, EarlyView.The causes of central nervous system (CNS) hemangioblastoma in Von Hippel–Lindau (vHL) disease are unclear. We used Whole Exome Sequencing (WES) on familial hemangioblastoma to investigate events that underlie tumor development. Our findings suggest that VHL loss creates a permissive environment for tumor formation, while additional alterations ...
Maja Dembic +5 more
wiley +1 more source
Forecasting and Combining Competing Models of Exchange rate Determination [PDF]
This paper investigates the out-of-sample forecast performance of a set of competing models of exchange rate determination. We compare standard linear models with models that characterize the relationship between exchange rate and its underlying ...
Paul De Grauwe, Carlo Altavilla
core
To the issue of forecasting price dynamics in the property valuation
Nauka ta progres transportu, 2012 The problems of short-, medium- and long-term forecasting price dynamics are considered. The improvement of short-term forecasting techniques based on exponential smoothing is proposed.
O.N. Gnennyi
doaj
Hippo pathway at the crossroads of stemness and therapeutic resistance in breast cancer
Molecular Oncology, EarlyView.Dysregulation of the Hippo pathway drives nuclear accumulation of YAP/TAZ, activating stemness‐related transcriptional programs that sustain breast cancer stemness and fuel therapeutic resistance across subtypes, underscoring Hippo signaling as a targetable vulnerability. Figure created and edited with BioRender.com.
Giulia Schiavoni +11 more
wiley +1 more source