Results 111 to 120 of about 45,420 (307)

Traction Force Microscopy for Viscoelastic Substrates: A Semi‐Analytical Method

open access: yesAdvanced Science, EarlyView.
A semi‐analytical viscoelastic traction force microscopy framework is introduced for quantifying time‐resolved cell tractions on flat finite‐thickness substrates. The method generalizes elastic traction force microscopy to Generalized Maxwell materials, identifies when elastic approximations remain valid and, when they do not, shows that inferred ...
Adrià Villacrosa‐Ribas   +10 more
wiley   +1 more source

Optimally Localized Wavelets and Smoothing Kernels

open access: yes, 2011
It is well-known that the Gaussian functions and, more generally, their modulations-translations (the Gabor functions) have the unique property of being optimally localized in space and frequency in the sense of Heisenberg's uncertainty principle.
openaire   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

open access: yesAdvanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray   +3 more
wiley   +1 more source

Temporal Interference Stimulation Enhances Neural Regeneration

open access: yesAdvanced Science, EarlyView.
Temporal interference (TI) stimulation is proposed as a non‐invasive approach to enhance neural regeneration in the deep brain. Theta‐band TI modulation selectively promotes neural progenitor cell differentiation in vitro and augments hippocampal neurogenesis in amouse model of Alzheimer's disease‐like amyloidosis.
Sofia Peressotti   +15 more
wiley   +1 more source

sparr: Analyzing Spatial Relative Risk Using Fixed and Adaptive Kernel Density Estimation in R

open access: yes
The estimation of kernel-smoothed relative risk functions is a useful approach to examining the spatial variation of disease risk. Though there exist several options for performing kernel density estimation in statistical software packages, there have ...
Tilman M. Davies   +2 more
core  

Comparing shapes of engel curves [PDF]

open access: yes
We measure how different the shapes of Engel curves are across 59 commodity groups. The same analysis is carried out for their derivatives and variances.
Alessio Moneta, Andreas Chai
core  

Adaptive kernel smoothing regression using vector quantization

open access: yes, 2011
A Method for Performing Kernel Smoothing Regression in an Online Adaptive Manner is Presented. the Approach Proposed is to Apply Kernel Smoothing Regression on an Incremental Estimation of the (Evolving) Probability Distribution of the Incoming Data ...
Amaury Lendasse   +3 more
core   +1 more source

Transferable Deep Reinforcement Learning With Edge‐Contour‐Depth Fusion for Autonomous Wireless Capsule Endoscopy Navigation

open access: yesAdvanced Science, EarlyView.
This study presents an anatomical landmark‐guided DRL framework for autonomous wireless capsule endoscopy navigation. Using a lightweight edge‐contour‐depth fusion module, it achieves over 97% coverage across diverse gastric anatomies. To ensure reliability, a two‐stage sim‐to‐real pipeline with an adaptive dynamic programming controller mitigates ...
Haoxuan Wu   +16 more
wiley   +1 more source

A High‐Throughput Live Imaging Platform to Investigate Circuit‐Dependent Regulation of Circadian Rhythms in Brain Tissue

open access: yesAdvanced Science, EarlyView.
Biological rhythms coordinate physiology, from genes to behavior. Study of circadian rhythms in brain tissue is constrained by limited throughput and spatial and temporal information quality. A new platform for high‐throughput, long‐term multiplexed fluorescent live imaging of circadian rhythms in brain slices is introduced.
Marco Ferrari   +3 more
wiley   +1 more source

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