Results 121 to 130 of about 136,469 (280)
The Arcsine Log-Logistic Distribution and Its Applications
This article introduces Arcsine Log-logistic (AL-L) distribution which is a member of Arcsine-G family proposed by Rahman. The different properties of AL-L distribution have been discussed. The distribution of various order statistics are obtained. Maximum Likelihood Estimation (MLE) technique is used to estimate the model parameters.
Md. Aftab Moral +2 more
openaire +1 more source
Blood‐based amino acid patterns measured by 19F NMR reveal hidden metabolic changes in colorectal cancer. By analyzing how these amino acids interact as a network, machine learning models identify patients at higher risk of recurrence and metastasis.
Ji‐Yeon Lee +9 more
wiley +1 more source
Orbitally Stability of Log-Logistic Autoregressive Model with Application
This research aims to study and finding the conditions for stability of the limit cycle of the proposed model (Log-Logistic autoregressive) based on the cumulative function of the Log-Logistic distribution.
Mohammed A. Hamad, Azher A. Mohammad
doaj +1 more source
Tumor‐derived GDF15 drives cancer cachexia and suppresses antitumor immunity. Here, de novo designed minibinders targeting the GDF15–GFRAL interface achieve picomolar affinity and potent pathway blockade. The minibinders alleviate cachexia, restore CD8+ T‐cell infiltration, enhance anti–PD‐1 responsiveness, and provide survival benefits across tumor ...
Haitao Wang +8 more
wiley +1 more source
The Odd generalized exponential log-logistic distribution group acceptance sampling plan
In this manuscript, a group acceptance sampling plan (GASP) is developed when the lifetime of the items follows odd generalized exponential log-logistic distribution (OGELLD), the multiple number of items as a group can be tested simultaneously in a ...
Kalyani, Kruthiventi +3 more
core +1 more source
Detecting Clinical Risk Shift Through log–logistic Hazard Change-Point Model
The change–point problem is about identifying when a pattern or trend shifts in time–ordered data. In survival analysis, change–point detection focuses on identifying alterations in the distribution of time–to–event data, which may be subject to ...
Shobhana Selvaraj Nadar +2 more
doaj +1 more source
CHCHD10 loss in Alzheimer's disease is associated with mitochondrial dysfunction, epigenomic disruption, and tau pathology. Restoration of CHCHD10 shifts DNA methylation toward a non‐disease state and reduces tau and amyloid pathology, with KATNAL2 acting as a downstream effector.
Teresa M. Thomas +13 more
wiley +1 more source
Human neutrophils exist as two epigenetically imprinted subtypes defined by stable CD177 expression or absence — a ratio that persists across time, circadian rhythms, and inflammation. CD177− neutrophils display a distinct molecular landscape enriched in arginase 1 and lipid metabolism markers, accumulate in head‐and‐neck tumors, and associate with ...
Marcel Jung +39 more
wiley +1 more source
A new approach in constructing a univariate absolutely continuous probability model via power transformation is adopted. The proposed distribution appears to subsume several popular univariate continuous probability models that are already existent in ...
Indranil Ghosh +2 more
doaj +1 more source
Exact Discrete Stochastic Simulation With Deep‐Learning‐Scale Gradient Optimization
A 203,796‐parameter gene regulatory network classifies handwritten digits with 98.4% accuracy using exact stochastic dynamics. The framework decouples forward simulation from backward differentiation, making continuous‐time Markov chain models compatible with deep‐learning optimization.
Jose M. G. Vilar, Leonor Saiz
wiley +1 more source

