Results 61 to 70 of about 90,983 (296)
The importance of scale in spatially varying coefficient modeling [PDF]
While spatially varying coefficient (SVC) models have attracted considerable attention in applied science, they have been criticized as being unstable. The objective of this study is to show that capturing the "spatial scale" of each data relationship is
Brunsdon, Chris +6 more
core +4 more sources
PD‐1 Inhibits CD4+ TRM‐Mediated cDC1 Mobilization via Suppressing JAML in Human NSCLC
CD4+ tissue‐resident memory T cells (TRMs) in non‐small cell lung cancer recruit conventional type 1 dendritic cells via XCL1‐XCR1 signaling, orchestrating antitumor immunity. The costimulatory molecule JAML is essential for this process. PD‐1 blockade restores JAML expression and cDC1 mobilization, while JAML agonists synergize with anti‐PD‐1 therapy,
Zheyu Shao +16 more
wiley +1 more source
Using machine learning on a mega‐scale global dataset (n = 1,336,840) reveals a robust personality trait architecture beyond the Big Five. A Big Two model, broadly capturing social engagement and internal mentation, defines a geometric space that links personality to neurocognitive profiles.
Kaixiang Zhuang +7 more
wiley +1 more source
Regional Convergence in Germany. A Geographically Weighted Regression Approach [PDF]
Regional convergence of German labour markets represents a politically important question. Different studies have examined convergence processes in Germany. We derive equations to estimate the speed of convergence on the basis of an extended Solow model.
Eckey, Hans-Friedrich +2 more
core
This study investigates the genetic and microbial factors influencing the susceptibility of Diaphorina citri to the citrus greening pathogen Candidatus Liberibacter asiaticus (CLas), employing a microbiome Genome Wide Association Study. The research identifies a key gene encoding an MFS‐type transporter contributing to CLas infectivity and abundance in
Kai Liu +12 more
wiley +1 more source
Geographically Weighted Logistic Regression Applied to Credit Scoring Models
This study used real data from a Brazilian financial institution on transactions involving Consumer Direct Credit (CDC), granted to clients residing in the Distrito Federal (DF), to construct credit scoring models via Logistic Regression and ...
Pedro Henrique Melo Albuquerque +2 more
doaj +1 more source
PEMODELAN PERSENTASE BALITA GIZI BURUK DI JAWA TENGAH DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED REGRESSION PRINCIPAL COMPONENTS ANALYSIS (GWRPCA) [PDF]
Geographically Weighted Regression Principal Components Analysis (GWRPCA) is a combination of method of Principal Components Analysis (PCA) and Geographically Weighted Regression (GWR).
PRATNYANINGRUM, NOVIKA
core
ABSTRACT Gut microbiota dysbiosis promotes colorectal cancer (CRC) tumorigenesis. A global fecal metagenomic analysis identified Gemella morbillorum as a key contributor to the CRC‐associated microbiota. Fluorescence in situ hybridization revealed that Gemella morbillorum is enriched in CRC tumor tissues compared to adjacent normal tissues.
Zhen Wang +8 more
wiley +1 more source
This study analyzes gut bacteria in cholangiocarcinoma patients, revealing distinct microbial signatures that enable accurate disease detection. Species‐based diagnostic models achieved over 98% accuracy in identifying cholangiocarcinoma and distinguished it from other liver diseases. The research demonstrates that specific beneficial bacteria suppress
Benchen Rao +18 more
wiley +1 more source
Geographically Weighted Regression (GWR) is regression model that developed for data modeling with continuous respond variable and considering the spatial or location aspect.
Prima Widayani +3 more
doaj +1 more source

