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OpenACC is a high-level directive-based parallel programming model that can manage the sophistication of heterogeneity in architectures and abstract it from the users. The portability of the model across CPUs and accelerators has gained the…

Software Engineering · Computer Science 2022-08-30 A. M. Jarmusch , A. Liu , C. Munley , D. Horta , V. Ravichandran , J. Denny , S. Chandrasekaran

The operation of instruments and detectors in laboratory or beamline environments presents a complex challenge, requiring stable operation of multiple concurrent devices, often controlled by separate hardware and software solutions. These…

Dielectric structures composed of many inclusions that manipulate light in ways the bulk materials cannot are commonly seen in the field of metamaterials. In these structures, each inclusion depends on a set of parameters such as location…

Computational Physics · Physics 2019-03-05 Boaz Blankrot , Clemens Heitzinger

This paper presents the complete design, control, and experimental validation of a low-cost Stewart platform prototype developed as an affordable yet capable robotic testbed for research and education. The platform combines off the shelf…

Developing soft circuits from individual soft logic gates poses a unique challenge: with increasing numbers of logic gates, the design and implementation of circuits leads to inefficiencies due to mathematically unoptimized circuits and…

The electric field grading of dielectric permittivity gradient devices is an effective way of enhancing their insulation properties. The in-situ electric field-driven assembly is an advanced method for the fabrication of insulation devices…

Materials Science · Physics 2020-09-25 Zikui Shen , Zhenyu Xin , Xilin Wang , Xinyu Wei , Zhidong Jia

Safety- and security-critical systems have to be thoroughly tested against their specifications. The state of practice is to have _natural language_ specifications, from which test cases are derived manually - a process that is slow,…

Software Engineering · Computer Science 2025-11-25 Kuangxiangzi Liu , Dhiman Chakraborty , Alexander Liggesmeyer , Andreas Zeller

The massive cost of 3D acquisition calls for methods to reduce the number of receivers by designing optimal receiver sampling masks. Recent studies on 2D seismic showed that maximizing the spectral gap of the subsampling mask leads to…

Soft robots are powerful tools for manipulating delicate objects, yet their adoption is hindered by two gaps: the lack of integrated tactile sensing and sensor signal distortion caused by actuator deformations. This paper addresses these…

Robotics · Computer Science 2025-12-04 Chengjin Du , Federico Bernabei , Zhengyin Du , Sergio Decherchi , Matteo Lo Preti , Lucia Beccai

Ab initio simulations are capable of providing detailed information of material behavior at the nanoscale. Simulating experimentally relevant situations is, however, often computationally intense. Using hybrid approaches between ab initio…

Computational Physics · Physics 2019-03-26 Michael Sluydts , Michiel Larmuseau , Johan Lauwaert , Stefaan Cottenier

The majority of these machines fabricate from raw material in powder form using a directed energy beam to create a local melt zone. Total hip replacement is recommended for people who have medical issues related to excessive wear of the…

Structure based ligand discovery is one of the most successful approaches for augmenting the drug discovery process. Currently, there is a notable shift towards machine learning (ML) methodologies to aid such procedures. Deep learning has…

Machine Learning · Statistics 2018-06-12 Marta M. Stepniewska-Dziubinska , Piotr Zielenkiewicz , Pawel Siedlecki

The challenge of simulating many-body models with analogue physical systems requires both experimental precision and very low operational temperatures. Atomically precise placement of dopants in Si permits the construction of nanowires by…

Strongly Correlated Electrons · Physics 2018-06-05 Amintor Dusko , Alain Delgado , André Saraiva , Belita Koiller

We propose a robust optimization approach for constructing confidence bands for stochastic processes using a finite number of simulated sample paths. Our approach can be used to quantify uncertainty in realizations of stochastic processes…

Optimization and Control · Mathematics 2025-08-13 Timothy Chan , Jangwon Park , Vahid Sarhangian

Protein Structure Prediction (PSP) is an unsolved problem in the field of computational biology. The problem of protein structure prediction is about predicting the native conformation of a protein, while its sequence of amino acids is…

Biomolecules · Quantitative Biology 2022-06-06 Hossein Parineh , Nasser Mozayani

Simulations of Cardiac Electrophysiology are gaining momentum beyond basic mechanistic studies, as an approach for supporting clinical decision making. The potential for in silico technologies observed from the research community is…

Numerical Analysis · Mathematics 2025-10-22 Paolo Seghetti , Matthias Gsell , Anton Prassk , Martin Bishop , Gernot Plank

Recently, the rapid development of Solid-State LiDAR (SSL) enables low-cost and efficient obtainment of 3D point clouds from the environment, which has inspired a large quantity of studies and applications. However, the non-uniformity of…

Computer Vision and Pattern Recognition · Computer Science 2020-11-18 Jiahe Cui , Jianwei Niu , Zhenchao Ouyang , Yunxiang He , Dian Liu

Adaptation of software components is an important issue in Component Based Software Engineering (CBSE). Building a system from reusable or Commercial-Off-The-Shelf (COTS) components introduces a set of problems, mainly related to…

Software Engineering · Computer Science 2015-05-05 Marco Autili , Paola Inverardi , Massimo Tivoli , David Garlan

Robotic stacking of van der Waals heterostructures has been at the verge thanks to the convergence between artificial intelligence (AI) and two-dimensional (2D) materials research. Key ingredients to fulfill this pursuit often include…

Materials Science · Physics 2026-01-15 Zhili Lin , Luosha Han , Jinkun He , Xiaoxue Fan , Tongyao Zhang , Xiaoxi Li , Baojuan Dong , Kai Zhao

Three-dimensional (3D) deep molecular generative models offer the advantage of goal-directed generation based on 3D-dependent properties, such as binding affinity for structure-based design within binding pockets. Traditional benchmarks…

Quantitative Methods · Quantitative Biology 2024-07-08 Benoit Baillif , Jason Cole , Patrick McCabe , Andreas Bender
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