Results 61 to 70 of about 169,559 (249)

Quality Enhancement of Laser Powder‐Bed Fusion Parts by Acoustically Assisted Additive Manufacturing by Laser Powder‐Bed Fusion and its Application to Lattice Structures

Advanced Engineering Materials, EarlyView.
Additive manufacturing technologies like laser powder‐bed fusion offer great design freedom and individualization of products down to a batch size of one. However, parts fabricated with this technology suffer from poor quality. Acoustic assistance during the build process can minimize these drawbacks.
Oliver Maurer, Dirk Bähre
wiley   +1 more source

Dynamic Control Flow in Large-Scale Machine Learning

, 2018
Many recent machine learning models rely on fine-grained dynamic control flow for training and inference. In particular, models based on recurrent neural networks and on reinforcement learning depend on recurrence relations, data-dependent conditional ...
Abadi, Martín, Barham, Paul, Brevdo, Eugene, Burrows, Mike, Davis, Andy, Dean, Jeff, Ghemawat, Sanjay, Harley, Tim, Hawkins, Peter, Isard, Michael, Kudlur, Manjunath, Monga, Rajat, Murray, Derek, Yu, Yuan, Zheng, Xiaoqiang   +14 more
core   +1 more source

Machine Learning‐Enabled Polymer Discovery for Enhanced Pulmonary siRNA Delivery

Advanced Functional Materials, EarlyView.
This study provides an efficient approach to train a machine learning model by merging heterogeneous literature data to predict suitable polymers for siRNA delivery. Without the need for extensive laboratory synthesis, the machine learning enabled a virtual screening and successfully predicted a polymer that is validated for effective gene silencing in
Felix Sieber‐Schäfer, Min Jiang, Adrian Kromer, Anny Nguyen, Müge Molbay, Simone Pinto Carneiro, David Jürgens, Gerald Burgstaller, Bastian Popper, Benjamin Winkeljann, Olivia Monika Merkel   +10 more
wiley   +1 more source

API design for machine learning software: experiences from the scikit-learn project [PDF]

, 2013
Scikit-learn is an increasingly popular machine learning li- brary. Written in Python, it is designed to be simple and efficient, accessible to non-experts, and reusable in various contexts.
Blondel, Mathieu, Buitinck, Lars, Gramfort, Alexandre, Grisel, Olivier, Grobler, Jaques, Holt, Brian, Joly, Arnaud, Layton, Robert, Louppe, Gilles, Mueller, Andreas, Niculae, Vlad, Pedregosa, Fabian, Prettenhofer, Peter, Vanderplas, Jake, Varoquaux, Gaël   +14 more
core   +3 more sources

SimpleSBML: A Python package for creating and editing SBML models

bioRxiv, 2015
Summary In this technical report we describe a simple extension to python-libSBML that allows users of Python to more easily construct SBML based models. The most commonly used package for constructing SBML models in Python is python-libSBML based on the
Caroline Cannistra, Kyle Medley, H. Sauro   +2 more
semanticscholar   +1 more source

Versatile Green Transfer of Magnetoelectronics with Loss‐Free Performance and High Adhesion for Interactive Electronics

Advanced Functional Materials, EarlyView.
An environmentally friendly transfer printing method of nm‐thick giant magnetoresistive (GMR) sensors is demonstrated. This method, relying on water and biocompatible polyvinyl alcohol (PVA) polymer without the need of complex treatments, allows transferring thin films to a wide range of biological, organic, and inorganic substrates.
Olha Bezsmertna, Rui Xu, Eduardo Sergio Oliveros Mata, Stanislav Avdoshenko, Clemens Voigt, Sindy Mosch, Mykola Vinnichenko, Denys Makarov   +7 more
wiley   +1 more source

Object-oriented implementations of the MPDATA advection equation solver in C++, Python and Fortran

, 2013
Three object-oriented implementations of a prototype solver of the advection equation are introduced. The presented programs are based on Blitz++ (C++), NumPy (Python), and Fortran's built-in array containers. The solvers include an implementation of the
Arabas, Sylwester, Fijałkowski, Maciej, Jarecka, Dorota, Jaruga, Anna   +3 more
core   +2 more sources

Machine Learning Guided Design of Nerve‐On‐A‐Chip Platforms with Promoted Neurite Outgrowth

Advanced Functional Materials, EarlyView.
Compared to labor‐intensive trial‐and‐error experimentation, a machine learning (ML)‐guided workflow, incorporating cell viability assays, data augmentation, ensemble modeling, and model interpretation, is developed to accelerate nerve‐on‐a‐chip optimization and uncover data‐driven design principles.
Tsai‐Chun Chung, Chu‐Chun Liang, Min‐Wei Huang, Tianle Chen, Joshua M. Little, Snehi Shrestha, Yi‐Chen Ethan Li, I‐Chi Lee, Po‐Yen Chen   +8 more
wiley   +1 more source

MatchPy: A Pattern Matching Library

, 2017
Pattern matching is a powerful tool for symbolic computations, based on the well-defined theory of term rewriting systems. Application domains include algebraic expressions, abstract syntax trees, and XML and JSON data.
Barthels, Henrik, Bientinesi, Paolo, Krebber, Manuel   +2 more
core   +1 more source

Battery‐Free, Wireless Multi‐Sensing Platform for Comprehensive Management of Pressure Injury and Hygiene

Advanced Functional Materials, EarlyView.
A battery‐free, wireless device for real‐time monitoring of pressure injury and hygiene integrates pressure (≈10 kPa), temperature (≈40 °C), and NH3 gas sensing with antibacterial functionality. Enabled by near‐field communication, it ensures simultaneous, interference‐free mechanical and chemical monitoring, offering a practical solution for pressure ...
Myungwoo Choi, Sunwoo Lee, Sang Won Kim, Ji Yeon Lee, Younghan Kim, Jewook Kim, Gye Hyeon Lee, Saehan Choi, Seonggwang Yoo, Hak‐Young Ahn, Taehoon Kim, Je‐Sang Lee, Weon Gi Min, Inkyu Park, Young‐Seok Shim, Yoon Sung Nam, Seokwoo Jeon, Jeong‐O Lee, Yong Suk Oh, Donghwi Cho   +19 more
wiley   +1 more source