Results 131 to 140 of about 29,948 (298)
STransformer is a unified deep learning framework designed to seamlessly accommodate a comprehensive landscape of spatial data. By simultaneously capturing short‐range cellular interactions and tissue‐wide semantic patterns, it extracts robust representations to accurately dissect complex tissue heterogeneity.
Xingyi Li +9 more
wiley +1 more source
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio +6 more
wiley +1 more source
Uncertainty‐Aware Deep Ensembles for Robust and Reliable Chemical Sensor Arrays
A reliability‐aware electronic nose is developed using photothermally anchored metal‐catalyst decorated metal oxide nanofiber sensor arrays combined with deep ensemble learning. Diverse catalytic nanofiber channels generate gas‐specific response patterns, enabling selective identification and quantification of sulfur‐containing gases.
Sungwoo Eo +5 more
wiley +1 more source
This chapter investigates the connection between grade repetition and school dropout. Household data is matched against a panel of academic test scores and the school career of each child inferred from the combined dataset. This chapter uses two original
André, Pierre
core
The Effects of Student Coaching in College: An Evaluation of a Randomized Experiment in Student Mentoring [PDF]
College completion and college success often lag behind college attendance. One theory as to why students do not succeed in college is that they lack key information about how to be successful or fail to act on the information that they have.
Rachel Baker, Eric Bettinger
core
Dropout in postgraduate programs: a underexplored phenomenon – a scoping review
Postgraduate education has become increasingly crucial for nations in recent years, contributing to scientific, technological, and social progress. However, high dropout rates may undermine the benefits of postgraduate education.
Lira Isis Valencia Quecano +2 more
doaj +1 more source
Students’ perspectives on their early dropout of medical school
BACKGROUND: Enrolling in medical school launches a more demanding and stressful way of life for newly admitted students. Some students will struggle academically and will ultimately drop out from medical school. The study aims to understand the perspectives that dropped-out students have and their opinion regarding possible ...
Ashraf F. Hefny +4 more
openaire +3 more sources
SPADE integrates spatial transcriptomics with single‐cell RNA sequencing by using cell–cell communications (CCC) as a guide for spatial mapping. It improves cell‐type localization, enhances sparse gene‐expression signals, and reveals CCC programs at single‐spot resolution.
Xinyi Li, Ning Zhang, Zijie Jin
wiley +1 more source
How Interactive can a Lecture Become?
The uses of technology have been well documented and many people have tried to use the available technology. In an age of increasingly idevices dependent generation where on average students check their portable devices at least every 15 minutes for 15 ...
Koohgilani, Mehran
core
Predicting Student Dropout Using Machine Learning Algorithms
This article comprehensively examines the use of machine learning algorithms to predict and reduce student dropout rates. These methods, developed to monitor and support student achievement in education, also aimedto enhance ...
Köklü, Niğmet +1 more
core +1 more source

