Results 101 to 110 of about 2,032,232 (300)
Errors-in-variables models: a generalized functions approach [PDF]
Identification in errors-in-variables regression models was recently extended to wide models classes by S. Schennach (Econometrica, 2007) (S) via use of generalized functions. In this paper the problems of non- and semi- parametric identification in such models are re-examined.
openaire +3 more sources
In this explorative study, the abundance of circular RNA molecules in bone marrow stem cells was found to be elevated in patients with high‐risk myelodysplastic neoplasms, and to be associated with an increased risk of progression to acute myeloid leukemia.
Eileen Wedge +17 more
wiley +1 more source
Meta‐transcriptome analysis identified FGF19 as a peptide enteroendocrine hormone associated with colorectal cancer prognosis. In vivo xenograft models showed release of FGF19 into the blood at levels that correlated with tumor volumes. Tumoral‐FGF19 altered murine liver metabolism through FGFR4, thereby reducing bile acid synthesis and increasing ...
Jordan M. Beardsley +5 more
wiley +1 more source
Multiple mental health disorders affect on decisions of people. The disorders are also outcomes of other factors. Health studies commonly follow an inverse propensity weight (IPW) method to address estimation errors associated with the presence of one ...
Bhubaneswor Dhakal +3 more
doaj +1 more source
Goodness-of-fit test in a multivariate errors-in-variables model
We consider a multivariable functional errors-in-variables model $AX\approx B$, where the data matrices A and B are observed with errors, and a matrix parameter X is to be estimated.
Alexander Kukush +1 more
doaj +1 more source
Weather Forecasting Error in Solar Energy Forecasting
As renewable distributed energy resources (DERs) penetrate the power grid at an accelerating speed, it is essential for operators to have accurate solar photovoltaic (PV) energy forecasting for efficient operations and planning.
Foruzan, Elham +5 more
core +1 more source
Influence Assessment in an Heteroscedastic Errors-in-Variables Model
The main goal of this article is to consider influence assessment in models with error-prone observations and variances of the measurement errors changing across observations. The techniques enable to identify potential influential elements and also to quantify the effects of perturbations in these elements on some results of interest.
Galea Rojas, Manuel Jesús +1 more
openaire +6 more sources
Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova +25 more
wiley +1 more source
In-Flight Self-Alignment Method Aided by Geomagnetism for Moving Basement of Guided Munitions
Due to power-after-launch mode of guided munitions of high rolling speed, initial attitude of munitions cannot be determined accurately, and this makes it difficult for navigation and control system to work effectively and validly.
Shuang-biao Zhang +2 more
doaj +1 more source
Targeted modulation of IGFL2‐AS1 reveals its translational potential in cervical adenocarcinoma
Cervical adenocarcinoma patients face worse outcomes than squamous cell carcinoma counterparts despite similar treatment. The identification of IGFL2‐AS1's differential expression provides a molecular basis for distinguishing these histotypes, paving the way for personalized therapies and improved survival in vulnerable populations globally.
Ricardo Cesar Cintra +6 more
wiley +1 more source

