Results 101 to 110 of about 1,664,848 (287)

Analyzing Electronic Excitations and Exciton Binding Energies in Y6 Films

Advanced Functional Materials, EarlyView.
The Y6 molecule is used for increasing the efficiency of organic solar cells. The exciton binding energy is calculated for ensembles of Y6 molecules that are representative of the typically used films. The calculations show that the excitons typically spread out over many molecules.
Sahar Javaid Akram, Sophie Meißner, Stephan Kümmel   +2 more
wiley   +1 more source

Artificial Neural Network Based Ensemble Approach for Multicultural Facial Expressions Analysis

IEEE Access, 2020
Facial expressions convey exhaustive information about human emotions and the most interactive way of social collaborations, despite differences in ethnicity, culture, and geography. Due to cultural differences, the variations in facial structure, facial
Ghulam Ali, Amjad Ali, Farman Ali, Umar Draz, Fiaz Majeed, Sana Yasin, Tariq Ali, Noman Haider   +7 more
doaj   +1 more source

Fast‐Responding O2 Gas Sensor Based on Luminescent Europium Metal‐Organic Frameworks (MOF‐76)

Advanced Functional Materials, EarlyView.
Luminescent MOF‐76 materials based on Eu(III) and mixed Eu(III)/Y(III) show rapid and reversible changes in emission intensity in response to O2 with very short response times. The effect is based on triplet quenching of the linker ligands that act as photosensitizers. Average emission lifetimes of a few milliseconds turn out to be mostly unaffected by
Zhenyu Zhao, Christian Weinberger, Jakob Steube, Matthias Bauer, Martin Brehm, Michael Tiemann   +5 more
wiley   +1 more source

Robust Ensemble Classification Methodology for I123-Ioflupane SPECT Images and Multiple Heterogeneous Biomarkers in the Diagnosis of Parkinson's Disease

Frontiers in Neuroinformatics, 2018
In last years, several approaches to develop an effective Computer-Aided-Diagnosis (CAD) system for Parkinson's Disease (PD) have been proposed. Most of these methods have focused almost exclusively on brain images through the use of Machine-Learning ...
Diego Castillo-Barnes, Javier Ramírez, Fermín Segovia, Francisco J. Martínez-Murcia, Diego Salas-Gonzalez, Juan M. Górriz   +5 more
doaj   +1 more source

Falsification‐Oriented Signature‐Based Evaluation for Guiding the Development of Land Surface Models and the Enhancement of Observations

Journal of Advances in Modeling Earth Systems, 2020
We develop a novel framework for rigorously evaluating land surface models (LSMs) against observations by recognizing the asymmetry between verification‐ and falsification‐oriented approaches. The former approach cannot completely verify LSMs even though
Hui Zheng, Zong‐Liang Yang, Peirong Lin, Wen‐Ying Wu, Lingcheng Li, Zhongfeng Xu, Jiangfeng Wei, Long Zhao, Qingyun Bian, Shu Wang   +9 more
doaj   +1 more source

MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance

Advanced Functional Materials, EarlyView.
Metal‐organic frameworks (MOFs) and covalent organic frameworks (COFs) hold promise for advanced electronics. However, discrepancies in reported electrical conductivities highlight the importance of measurement methodologies. This review explores intrinsic charge transport mechanisms and extrinsic factors influencing performance, and critically ...
Jonas F. Pöhls, R. Thomas Weitz
wiley   +1 more source

Humeral head size predicts baseplate lateralization in reverse shoulder arthroplasty: a comparative computer model study

JSES International
Background: In reverse shoulder arthroplasty (RSA), the ideal combination of baseplate lateralization (BL), glenosphere size (GS), and glenosphere overhang (GOH) with a commonly used 145° neck shaft angle (NSA) is unclear.
Stefan Bauer, MD, William G. Blakeney, MD, Arnaud Meylan, MD, Jaad Mahlouly, MD, Allan W Wang, MD, Arnaud Walch, MD, Luca Tolosano, MD   +6 more
doaj   +1 more source

Analysis of Multiobjective Algorithms for the Classification of Multi-Label Video Datasets

IEEE Access, 2020
It is of great importance to extract and validate an optimal subset of non-dominated features for effective multi-label classification. However, deciding on the best subset of features is an NP-Hard problem and plays a key role in improving the ...
Gizem Nur Karagoz, Adnan Yazici, Tansel Dokeroglu, Ahmet Cosar   +3 more
doaj   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced 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, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Tuning the Selectivity of the CO2 Reduction Reaction by Means of Synergistic Interactions in the Cu, Ag, Ce System

Advanced Functional Materials, EarlyView.
Multi‐metal Cu─Ce─Ag nanoparticles harness synergistic interactions to drive efficient electrochemical CO2 reduction reaction toward C2+ products at high current densities. Ag enhances CO production, Ce modulates Cu oxidation states, and together they boost *CO coverage and local pH to enhance C─C coupling, enabling record C2+ yields with suppressed ...
Nini Zhang, Muhammad Adib Abdillah Mahbub, Bashir Eid, Thomas Quast, Jian Zhang, Ridha Zerdoumi, Xin Wang, Sabine Seisel, Wangcheng Zhan, Wolfgang Schuhmann   +9 more
wiley   +1 more source