Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Simulation Techniques and Applications
Abstract
This paper investigates the algorithmic complexity of parallel simulations of complex systems, aiming to develop a novel algorithm that significantly reduces computational costs while maintaining accuracy. Complex systems, such as protein folding and climate modeling, demand substantial computational resources. Existing simulation techniques often struggle with scalability, limiting the size and complexity of these models. This research explores a new approach – "parallel branching" – designed to intelligently distribute computational tasks across multiple cores, minimizing memory requirements and accelerating simulation times. The core mechanism centers around strategically partitioning problem space to optimize performance. We analyze the algorithm's complexity using established metrics and demonstrate its potential to substantially improve simulation efficiency compared to traditional methods. The findings highlight the importance of algorithmic optimization in tackling complex system simulations, offering a potentially transformative step toward more realistic and computationally feasible models.
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
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This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
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This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.
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This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.
Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson· International Conference on...· 44 citations· ⚡5
It is demonstrated that linker-free PROTACs can outperform traditional designs, marking a paradigm shift in PROTAC development for targeted protein degradation.
Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or sequence constraints.
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.
