Results 91 to 100 of about 6,287,224 (283)

The Power Mean Test

open access: yesThe PUMP Journal of Undergraduate Research, 2020
We devise a new test for convergence or divergence of an infinite series — the Power Mean Test. We explore the strength of this test relative to that of the Ratio and Root Tests and provide a family of series where the Power Mean Test is the most useful of the three tests.
Travis E Kulhanek, Vadim Ponomarenko
openaire   +1 more source

Dammarenediol II enhances etoposide‐induced apoptosis by targeting O‐GlcNAc transferase and Akt/GSK3β/mTOR signaling in liver cancer

open access: yesMolecular Oncology, EarlyView.
Etoposide induces DNA damage, activating p53‐dependent apoptosis via caspase‐3/7, which cleaves PARP1. Dammarenediol II enhances this apoptotic pathway by suppressing O‐GlcNAc transferase activity, further decreasing O‐GlcNAcylation. The reduction in O‐GlcNAc levels boosts p53‐driven apoptosis and influences the Akt/GSK3β/mTOR signaling pathway ...
Jaehoon Lee   +8 more
wiley   +1 more source

Identification of serum protein biomarkers for pre‐cancerous lesions associated with pancreatic ductal adenocarcinoma

open access: yesMolecular Oncology, EarlyView.
This work identified serum proteins associated with pancreatic epithelial neoplasms (PanINs) and early‐stage PDAC. Proteomics screens assessed genetically engineered mice with abundant PanINs, KPC mice (Lox‐STOP‐Lox‐KrasG12D/+ Lox‐STOP‐Lox‐Trp53R172H/+ Pdx1‐Cre) before PDAC development and also early‐stage PDAC patients (n = 31), compared to benign ...
Hannah Mearns   +10 more
wiley   +1 more source

Subtype‐specific enhancer RNAs define transcriptional regulators and prognosis in breast cancers

open access: yesMolecular Oncology, EarlyView.
This study employed machine learning methodologies to perform the subtype‐specific classification of RNA‐seq data sets, which are mapped on enhancers from TCGA‐derived breast cancer patients. Their integration with gene expression (referred to as ProxCReAM eRNAs) and chromatin accessibility profiles has the potential to identify lineage‐specific and ...
Aamena Y. Patel   +6 more
wiley   +1 more source

How users' moving in a cell affects the necessary base station power [PDF]

open access: yesTehnika, 2019
In this paper it is analyzed the influence of user moving in the base station cell where power control is implemented on the change of transmitted base station energy comparing to the energy, which is necessary for stationary user.
Mitić Dragan S.   +3 more
doaj  

One kind sixth power mean of the three-term exponential sums

open access: yesOpen Mathematics, 2017
In this paper, we use the estimate for trigonometric sums and the properties of the congruence equations to study the computational problem of one kind sixth power mean of the three-term exponential sums.
Wang Xiaoying, Li Xiaoxue
doaj   +1 more source

Power spectral density analysis [PDF]

open access: yes
Equations for power spectral density function, and for root mean square of power spectral density ...
Hayes, C. D.
core   +1 more source

Targeted modulation of IGFL2‐AS1 reveals its translational potential in cervical adenocarcinoma

open access: yesMolecular Oncology, EarlyView.
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

On a result of Cartwright and Field

open access: yesJournal of Inequalities and Applications, 2018
Let Mn,r=(∑i=1nqixir)1r $M_{n,r}=(\sum_{i=1}^{n}q_{i}x_{i}^{r})^{\frac{1}{r}}$, r≠0 $r\neq 0$, and Mn,0=limr→0Mn,r $M_{n,0}= \lim_{r \rightarrow 0}M_{n,r}$ be the weighted power means of n non-negative numbers xi $x_{i}$, 1≤i≤n $1 \leq i \leq n$, with qi>
Peng Gao
doaj   +1 more source

A nonparametric adjustment for tests of changing mean [PDF]

open access: yes
When testing for a change in mean of a time series, the null hypothesis is no change in mean. However, a change in mean causes a bias in the estimation of serial correlation parameters.
Ted Juhl
core  

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