Results 71 to 80 of about 379,670 (274)

Investigation of Laser Ablation and Brush Pre‐Treatments for AlCu Cold Roll Bonding in Oxygen‐Free Conditions

open access: yesAdvanced Engineering Materials, EarlyView.
It is shown that laser ablation pretreatment under oxygen‐free conditions enables copper–aluminium bonding at significantly lower deformation degrees and improved properties compared to mechanical brushing. Laser ablation further increases interface contact area and induces favourable residual stress states and microstructural compatibility ...
Khemais Barienti   +11 more
wiley   +1 more source

Interspecific hybridization of Vigna radiata x 13 wild Vigna species for developing MYMV donar [PDF]

open access: yesElectronic Journal of Plant Breeding, 2010
Mungbean (Vigna radiata (L.) Wilczek) is having a desirable characters like short duration, high protein, less anti nutritionalfactors, nitrogen fixing capacity, suitable for inter cropping, making many kinds of foods for higher human consumption ...
M. Pandiyan , N.Senthil, N. Ramamoorthi, AR.Muthiah, N.Tomooka V.Duncan and T.Jayaraj
doaj  

Modeling Conditional Skewness in Stock Returns [PDF]

open access: yes
In this paper we propose a new GARCH-in-Mean (GARCH-M) model allowing for conditional skewness. The model is based on the so-called z distribution capable of modeling moderate skewness and kurtosis typically encountered in stock return series.
Markku Lanne, Pentti Saikkonen
core  

Engineered Mycelial Scaffolds With Tunable Ultraviolet Protection, Wettability, Thermal Stability, and Spatial Mechanics

open access: yesAdvanced Engineering Materials, EarlyView.
Fungal mycelia grown into biodegradable scaffolds and infused with titania nanoparticles show enhanced ultraviolet shielding, thermal protection, and surface nonwettability. Properties were tuned by drying methods, revealing structure–function relationships.
Juwon S. Afolayan   +2 more
wiley   +1 more source

skew

open access: yes, 2014
Citation: 'skew' in the IUPAC Compendium of Chemical Terminology, 3rd ed.; International Union of Pure and Applied Chemistry; 2006. Online version 3.0.1, 2019. 10.1351/goldbook.S05709 • License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International for individual terms. Requests for commercial usage of
openaire   +2 more sources

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

open access: yesAdvanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone   +11 more
wiley   +1 more source

Modelling the Distribution of Cognitive Outcomes for Early-Stage Neurocognitive Disorders: A Model Comparison Approach

open access: yesBiomedicines
Background: Cognitive assessments for patients with neurocognitive disorders are mostly measured by the Montreal Cognitive Assessment (MoCA) and Visual Cognitive Assessment Test (VCAT) as screening tools.
Seyed Ehsan Saffari   +5 more
doaj   +1 more source

Modelling the Density of Inflation Using Autoregressive Conditional Heteroscedasticity, Skewness, and Kurtosis Models [PDF]

open access: yes
The paper aimed at modelling the density of inflation based on time-varying conditional variance, skewness and kurtosis model developed by Leon, Rubio, and Serna (2005) who model higher-order moments as GARCH-type processes by applying a Gram-Charlier ...
Doaa Akl Ahmed
core  

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

open access: yesAdvanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore   +7 more
wiley   +1 more source

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