Results 61 to 70 of about 129,628 (262)

The Effects of Densification and Heat Post-Treatment on Hardness and Morphological Properties of Wood Materials

open access: yesBioResources, 2016
This study investigated the effects of densification and heat post-treatment on the Janka hardness and microscopic structure of relatively low-density Uludağ fir, linden, and black poplar woods.
Mehmet Budakçı   +3 more
doaj   +1 more source

Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif   +17 more
wiley   +1 more source

Efficacy of Pongamia pinnata seed oil as a fumigant in reducing surface infestation by sapstain and mould fungi in bamboo

open access: yesAdvances in Bamboo Science
Sap stain fungi causes discolouration in bamboo, which reduces the aesthetic value of bambooproducts and renders them unfit for any specific use in which appearance is a crucial factor in determining its value besides its durability.
Ajmal Samani   +2 more
doaj   +1 more source

Does Long‐Term Lower Extremity Strength Training in Adults With Knee Osteoarthritis and Varus Alignment Reduce Knee Joint Loading During Gait?

open access: yesArthritis Care &Research, EarlyView.
Objective We examined whether 18 months of strength training in individuals with knee varus alignment and medial tibiofemoral osteoarthritis (OA) reduced knee joint loads during walking compared to an attention control group. Methods This study was a secondary analysis of a randomized clinical trial that compared the effects of strength training to a ...
Stephen P. Messier   +12 more
wiley   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

open access: yesAdvanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch   +3 more
wiley   +1 more source

Microstructure Evolution of a VMnFeCoNi High‐Entropy Alloy After Synthesis, Swaging, and Annealing

open access: yesAdvanced Engineering Materials, EarlyView.
The synthesis and processing (rotary swaging and annealing) of the novel VMnFeCoNi alloy is investigated, alongside the estimation of the grain size effect on hardness. Analysis of a wide grain size range of recrystallized microstructures (12–210 µm) reveals a low annealing twin density.
Aditya Srinivasan Tirunilai   +6 more
wiley   +1 more source

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

open access: yesAdvanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara   +8 more
wiley   +1 more source

Electrochemical Behavior of Flame‐Sprayed Sc‐Doped AlCoCrFeMo High‐Entropy Alloy Coatings in 3.5% Sodium Chloride Solution

open access: yesAdvanced Engineering Materials, EarlyView.
Scandium (Sc)‐doped AlCoCrFeMo HEA coatings are fabricated via flame spraying with 0.1, 0.3, and 0.5 wt% Sc additions. Among these, the HEA‐Sc0.3 coating exhibits the highest corrosion resistance, indicated by a more positive corrosion potential and lower current density.
Pankaj Kumar   +7 more
wiley   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

open access: yesAdvanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer   +4 more
wiley   +1 more source

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