Results 121 to 130 of about 8,804,924 (318)

Spectral Predictors

open access: yes2007 Data Compression Conference (DCC'07), 2007
Many scientific, imaging, and geospatial applications produce large high-precision scalar fields sampled on a regular grid. Lossless compression of such data is commonly done using predictive coding, in which weighted combinations of previously coded samples known to both encoder and decoder are used to predict subsequent nearby samples.
Ibarria, L, Lindstrom, P, Rossignac, J
openaire   +2 more sources

Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system

open access: yesFEBS Letters, EarlyView.
Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley   +1 more source

Self-Reported Morbidity and Health-Seeking Behavior and its Predictors Among a Geriatric Population in Western Ethiopia: Community-Based Cross-Sectional Study

open access: yesInternational Journal of General Medicine, 2020
Beshadu Bedada Feyisa,1 Seble Fekadu Deyaso,2 Gosaye Mekonen Tefera3 1Department of Public Health, College of Medicine and Health Sciences, Ambo University, Ambo, Ethiopia; 2Department of Sociology, College of Social Sciences and Humanities, Ambo ...
Feyisa BB, Deyaso SF, Tefera GM
doaj  

Why Can't We Accurately Predict Others' Decisions? Prediction Discrepancy in Risky Decision-Making

open access: yesFrontiers in Psychology, 2018
Individuals often fail to accurately predict others' decisions in a risky environment. In this paper, we investigate the characteristics and causes of this prediction discrepancy.
Qingzhou Sun   +3 more
doaj   +1 more source

A methionine‐lined active site governs carbocation stabilization and product specificity in a bacterial terpene synthase

open access: yesFEBS Letters, EarlyView.
This study reveals a unique active site enriched in methionine residues and demonstrates that these residues play a critical role by stabilizing carbocation intermediates through novel sulfur–cation interactions. Structure‐guided mutagenesis further revealed variants with significantly altered product profiles, enhancing pseudopterosin formation. These
Marion Ringel   +13 more
wiley   +1 more source

Predictors of second revascularization in patients with history of coronary artery bypass graft

open access: yesResearch in Cardiovascular Medicine, 2018
Objective: The number of individuals with a history of coronary artery bypass graft surgery (CABG) who may require a second revascularization intervention is growing.
Gholamreza Davoodi   +3 more
doaj   +1 more source

Aggressive prostate cancer is associated with pericyte dysfunction

open access: yesMolecular Oncology, EarlyView.
Tumor‐produced TGF‐β drives pericyte dysfunction in prostate cancer. This dysfunction is characterized by downregulation of some canonical pericyte markers (i.e., DES, CSPG4, and ACTA2) while maintaining the expression of others (i.e., PDGFRB, NOTCH3, and RGS5).
Anabel Martinez‐Romero   +11 more
wiley   +1 more source

Beyond conformal predictors: Adaptive Conformal Inference with confidence predictors

open access: yesPattern Recognition
28 pages, 5 ...
Johan Hallberg Szabadváry   +1 more
openaire   +2 more sources

The neural crest‐associated gene ERRFI1 is involved in melanoma progression and resistance toward targeted therapy

open access: yesMolecular Oncology, EarlyView.
ERRFI1, a neural crest (NC)‐associated gene, was upregulated in melanoma and negatively correlated with the expression of melanocytic differentiation markers and the susceptibility of melanoma cells toward BRAF inhibitors (BRAFi). Knocking down ERRFI1 significantly increased the sensitivity of melanoma cells to BRAFi.
Nina Wang   +8 more
wiley   +1 more source

Combining Predictors

open access: yesDAIMI Report Series, 2000
The most important theoretical tool in connection with machine learning is the bias/variance decomposition of error functions. Together with Tom Heskes, I have found the family of error functions with a natural bias/variance decomposition that has target independent variance.
openaire   +2 more sources

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