Results 81 to 90 of about 212,881 (293)

Predicting Atomic Charges in MOFs by Topological Charge Equilibration

Advanced Functional Materials, EarlyView.
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi, Sumukh Shankar Sharadaprasad, Rochus Schmid   +2 more
wiley   +1 more source

Redefining Therapies for Drug‐Resistant Tuberculosis: Synergistic Effects of Antimicrobial Peptides, Nanotechnology, and Computational Design

Advanced Healthcare Materials, EarlyView.
Antimicrobial peptide (AMP)‐loaded nanocarriers provide a multifunctional strategy to combat drug‐resistant Mycobacterium tuberculosis. By enhancing intracellular delivery, bypassing efflux pumps, and disrupting bacterial membranes, this platform restores phagolysosome fusion and macrophage function.
Christian S. Carnero Canales, Jessica Ingrid Marquez Cazorla, Renzo Marianito Marquez Cazorla, Aline Martins dos Santos, Jonatas Lobato Duarte, Letícia Oliveira Catarin Nunes, Túlio Custódio Reis, Lara Cerazi Salvador, Norival Alves Santos‐Filho, Rafael Miguel Sábio, Hélder A. Santos, Fernando Rogério Pavan   +11 more
wiley   +1 more source

Hyperparameter optimization with approximate gradient

, 2016
Most models in machine learning contain at least one hyperparameter to control for model complexity. Choosing an appropriate set of hyperparameters is both crucial in terms of model accuracy and computationally challenging.
Pedregosa, Fabian
core  

In Vivo Skin 3‐D Surface Reconstruction and Wrinkle Depth Estimation Using Handheld High Resolution Tactile Sensing

Advanced Healthcare Materials, EarlyView.
A compact handheld GelSight probe reconstructs in vivo 3‐D skin topography with micron‐level precision using a custom elastic gel and a learning‐based surface normal to height map pipeline. The device quantifies wrinkle depth across various body locations and detects changes in wrinkle depth following moisturizer application.
Akhil Padmanabha, Arpit Agarwal, Catherine Li, Austin Williams, Dinesh K. Patel, Sankalp Chopkar, Achu Wilson, Ahmet Ozkan, Wenzhen Yuan, Sonal Choudhary, Arash Mostaghimi, Zackory Erickson, Carmel Majidi   +12 more
wiley   +1 more source

A Photosynthetic Rate Prediction Model for Cucumber Based on a Machine Learning Algorithm and Multi-Factor Environmental Analysis

Horticulturae
Plant photosynthetic rate prediction models have the potential to enhance production efficiency and advance intelligent control in protected agriculture.
Yanxiu Miao, Liyuan Liu, Miaoyu Wang, Zhihao Zeng, Jun Zhang, Yongsan Cheng, Bin Li   +6 more
doaj   +1 more source

Alpha MAML: Adaptive Model-Agnostic Meta-Learning

, 2019
Model-agnostic meta-learning (MAML) is a meta-learning technique to train a model on a multitude of learning tasks in a way that primes the model for few-shot learning of new tasks.
Baydin, Atılım Güneş, Behl, Harkirat Singh, Torr, Philip H. S.   +2 more
core  

Unveiling the Role of Curvature in Carbon for Improved Energy Release of Ammonium Perchlorate

Advanced Materials, EarlyView.
High‐curvature carbon materials identified via machine learning and simulation can enhance the heat release and combustion performance of ammonium perchlorate. ABSTRACT The catalytic role of carbon curvature in the thermal decomposition of ammonium perchlorate (AP) remains largely unexplored. To address this gap, this study employs machine learning and
Dan Liu, Keliang Song, Haorui Zhang, Zhipeng Liu, Guansong He, Junru Wang, Wenming Yang, Xu Zhao, Zhijian Yang   +8 more
wiley   +1 more source

Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll, Ivan Pinto‐Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, Yann‐Michel Niquet, Martin Børstad Eriksen, Sara Martí‐Sánchez, Georgios Katsaros, Giordano Scappucci, Peter Krogstrup, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Pablo Ordejón, Stephan Roche, Vincenzo Grillo, Jordi Arbiol   +19 more
wiley   +1 more source

Enhancing Short-Term Load Forecasting Using Hyperparameter-Optimized Deep Learning Approaches

Energies
The reliability and efficiency of power system operations, especially in smart grid scenarios, depend on accurate load demand forecasting. Electrical load forecasting is crucial for power system design, fault protection and diversification as it reduces ...
Nazmun Nahar Karima, Shameem Ahmad, Amirul Islam, A.S. Nazmul Huda, Lilik Jamilatul Awalin, Syahirah Abd Halim, Hazlie Mokhlis, Mohd Syukri Ali, Syahril Mubarok   +8 more
doaj   +1 more source

Hyperparameter Tuning Deep Learning for Diabetic Retinopathy Fundus Image Classification

IEEE Access, 2020
Diabetic retinopathy (DR) is a major reason for the increased visual loss globally, and it became an important cause of visual impairment among people in 25-74 years of age.
K. Shankar, Yizhuo Zhang, Yiwei Liu, Ling Wu, Chi-Hua Chen   +4 more
doaj   +1 more source