Results 81 to 90 of about 752,571 (301)

AGROTOURISM DEVELOPMENT OF MAPPING BRAND POSITIONING AND COMPETITVE LANDSCAPE: UGC (USER GENERATED CONTENT) APPROACH

open access: yesAGRISE, 2021
Starting from 2009-2018 there has been an increase in the number of hotel resorts in Indonesia, so that the level of competition is higher and building a brand positioning agrotourism-based resort hotels can not only by creating regular marketing ...
Annisa Firdauzi   +2 more
doaj   +1 more source

CRISPR targeting of FOXL2 c.402C>G mutation reduces malignant phenotype in granulosa tumor cells and identifies anti‐tumoral compounds

open access: yesMolecular Oncology, EarlyView.
FOXL2 c.402C>G mutation drives granulosa cell tumors. Using CRISPR technology, we selectively corrected this mutation, reducing malignancy and increasing sensitivity to dasatinib and ketoconazole. Transcriptomic changes revealed potential therapeutic targets, demonstrating CRISPR's promise for treating this rare ovarian cancer.
Sandra Amarilla‐Quintana   +17 more
wiley   +1 more source

Assessment of genetic diversity in linseed germplasm using morphological traits

open access: yesElectronic Journal of Plant Breeding, 2021
The genetic diversity among 61 linseed genotypes along with 4 checks was studied in the present investigation at the Experimental Farm of Punjab Agricultural University, Regional Research Station, Gurdaspur.
Naresh Kumar* and Vijay Kumar
doaj   +1 more source

Kernel Principal Component Analysis and its Applications in Face Recognition and Active Shape Models [PDF]

open access: yesarXiv, 2012
Principal component analysis (PCA) is a popular tool for linear dimensionality reduction and feature extraction. Kernel PCA is the nonlinear form of PCA, which better exploits the complicated spatial structure of high-dimensional features. In this paper, we first review the basic ideas of PCA and kernel PCA.
arxiv  

Integration of single‐cell and bulk RNA‐sequencing data reveals the prognostic potential of epithelial gene markers for prostate cancer

open access: yesMolecular Oncology, EarlyView.
Prostate cancer is a leading malignancy with significant clinical heterogeneity in men. An 11‐gene signature derived from dysregulated epithelial cell markers effectively predicted biochemical recurrence‐free survival in patients who underwent radical surgery or radiotherapy.
Zhuofan Mou, Lorna W. Harries
wiley   +1 more source

Breakthrough Solution for Antimicrobial Resistance Detection: Surface‐Enhanced Raman Spectroscopy‐based on Artificial Intelligence

open access: yesAdvanced Materials Interfaces, EarlyView., 2023
This review discusses the use of Surface‐Enhanced Raman Spectroscopy (SERS) combined with Artificial Intelligence (AI) for detecting antimicrobial resistance (AMR). Various SERS studies used with AI techniques, including machine learning and deep learning, are analyzed for their advantages and limitations.
Zakarya Al‐Shaebi   +4 more
wiley   +1 more source

Impact of sample size on principal component analysis ordination of an environmental data set: effects on eigenstructure

open access: yesEkológia (Bratislava), 2016
In this study, we used bootstrap simulation of a real data set to investigate the impact of sample size (N = 20, 30, 40 and 50) on the eigenvalues and eigenvectors resulting from principal component analysis (PCA).
Shaukat S. Shahid   +2 more
doaj   +1 more source

بررسی ویژگی‌های رئولوژیکی و حسی موس شکلاتی حاوی سدیم کازئینات و ژلاتین [PDF]

open access: yesمجله پژوهش‌های علوم و صنایع غذایی ایران, 2016
در این پژوهش اثر مقادیر مختلف ژلاتین (1، 2 و 3گرم) و سدیم کازئینات (1، 2 و 3 گرم) بر ویژگی‌های حسی و رئولوژیکی نمونه‌های موس شکلات بررسی شد. همچنین از روش تجزیه به مولفه‌های اصلی جهت تعیین روابط پارامترهای حسی و بدست آوردن مولفه‌های اصلی استفاده گردید ...
سعید میرعرب رضی   +3 more
doaj   +1 more source

$e$PCA: High Dimensional Exponential Family PCA [PDF]

open access: yesarXiv, 2016
Many applications, such as photon-limited imaging and genomics, involve large datasets with noisy entries from exponential family distributions. It is of interest to estimate the covariance structure and principal components of the noiseless distribution.
arxiv  

A co-kurtosis PCA based dimensionality reduction with nonlinear reconstruction using neural networks [PDF]

open access: yesarXiv, 2023
For turbulent reacting flows, identification of low-dimensional representations of the thermo-chemical state space is vitally important, primarily to significantly reduce the computational cost of device-scale simulations. Principal component analysis (PCA), and its variants, is a widely employed class of methods.
arxiv  

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