Results 81 to 90 of about 940,462 (236)

Photoswitchable Conductive Metal–Organic Frameworks

open access: yesAdvanced Functional Materials, EarlyView.
A conductive material where the conductivity can be modulated remotely by irradiation with light is presented. It is based on films of conductive metal–organic framework type Cu3(HHTP)2 with embedded photochromic molecules such as azobenzene, diarylethene, spiropyran, and hexaarylbiimidazole in the pores.
Yidong Liu   +5 more
wiley   +1 more source

Testing weight-based conditional discrimination in Goffin's cockatoos, Cacatua goffiniana.

open access: yesPLoS ONE
Discrimination learning tasks are a method for investigating species' perception of and associative learning with a particular stimulus. Goffin's cockatoos previously required surprisingly few trials to differentiate objects based on weight alone in a ...
Poppy J Lambert   +2 more
doaj   +1 more source

Explicit learning in ACT-R [PDF]

open access: yes, 1999
A popular distinction in the learning literature is the distinction between implicit and explicit learning. Although many studies elaborate on the nature of implicit learning, little attention is left for explicit learning.
Taatgen, Niels A.
core  

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

State of the Art in Fair ML: From Moral Philosophy and Legislation to Fair Classifiers

open access: yes, 2018
Machine learning is becoming an ever present part in our lives as many decisions, e.g. to lend a credit, are no longer made by humans but by machine learning algorithms. However those decisions are often unfair and discriminating individuals belonging to
Baumann, Elias, Rumberger, Josef Lorenz
core  

Item statistics derived from three-option versions of multiple-choice questions are usually as robust as four- or five-option versions: implications for exam design. [PDF]

open access: yes, 2018
Different versions of multiple-choice exams were administered to an undergraduate class in human physiology as part of normal testing in the classroom. The goal was to evaluate whether the number of options (possible answers) per question influenced the ...
Loudon, Catherine, Macias-Muñoz, Aide
core  

Selective Benzene Capture by Metal‐Organic Frameworks

open access: yesAdvanced Functional Materials, EarlyView.
Metal‐organic frameworks (MOFs) hold significant potential for capturing benzene from air emissions and hydrocarbon mixtures in liquid phases. This capability stems from their precisely engineered structures, versatile chemistries, and diverse binding interactions.
Zongsu Han   +4 more
wiley   +1 more source

Strains and stressors: an analysis of touchscreen learning in genetically diverse mouse strains.

open access: yesPLoS ONE, 2014
Touchscreen-based systems are growing in popularity as a tractable, translational approach for studying learning and cognition in rodents. However, while mouse strains are well known to differ in learning across various settings, performance variation ...
Carolyn Graybeal   +7 more
doaj   +1 more source

Semi-supervised Multi-sensor Classification via Consensus-based Multi-View Maximum Entropy Discrimination

open access: yes, 2015
In this paper, we consider multi-sensor classification when there is a large number of unlabeled samples. The problem is formulated under the multi-view learning framework and a Consensus-based Multi-View Maximum Entropy Discrimination (CMV-MED ...
Hero III, Alfred O.   +2 more
core   +1 more source

PRELIVE: A Framework for Predicting Lipid Nanoparticles In Vivo Efficacy and Reducing Reliance on Animal Testing

open access: yesAdvanced Functional Materials, EarlyView.
PREdicting LNP In Vivo Efficacy (PRELIVE) framework enables the prediction of lipid nanoparticle (LNPs) organ‐specific delivery through dual modeling approaches. Composition‐based models using formulation parameters and protein corona‐based models using biological fingerprints both achieve high predictive accuracy across multiple organs.
Belal I. Hanafy   +3 more
wiley   +1 more source

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