24 papers · ranked by Valyu relevance
Marek Babiuch, Petr Foltynek, Francesco Mercaldo
This article focuses on the area of software development for microcontrollers and details the implementation of modern programming practices and principles in embedded systems and IoT applications. This article explains how we implemented previously unimplemented principles and applied design patterns for quality…
Marek Babiuch, Petr Foltynek, SungJin Yu, KiSung Park
As part of our research for microcontroller software support, we have developed a modular framework that utilizes previously unimplemented architectural principles for developing applications on microcontrollers. These principles are still a privilege of enterprise and server applications. The paper describes the…
J. Masison, J. Beezley, Y. Mei, HAL Ribeiro + 9 more
'L. Sordo Vieira' 'B. Adhikari' 'Y. Scindia' 'M. Grauer' 'B. Helba' 'W. Schroeder' 'B. Mehrad' 'R. Laubenbacher'] Title: Significance The digital twin paradigm holds great promise for medicine, even though many technical and scientific challenges remain to be overcome, most importantly the efficient integration of many…
Ruoyu Su, Xiaozhou Li
Recently modular monolith architecture has attracted the attention of practitioners, as Google proposed "Service Weaver" framework to enable developers to write applications as modular monolithic and deploy them as a set of microservices. Google considered it as a framework that has the best of both worlds and it seems…
Jenkin Tsui, Naila Adam, Woongcheol Choi, Luna Y. Liu + 10 more
Imaging-based spatial transcriptomics technologies have opened new avenues for studying cellular organization and gene expression within intact tissues. However, the accuracy of downstream analyses depends critically on the decoding step that reconstructs barcodes from fluorescence patterns and maps them to gene…
Chuyi Chen, Zhe Zhang, Yanchao Zhao
—Federated learning (FL) has been widely adopted across various applications, such as healthcare, finance, and smart cities. However, as experimental scenarios become more complex, existing FL frameworks and benchmarks have struggled to keep pace. This paper introduces FedModule1 , a flexible and extensible FL…
Frederico Vicente, Cláudia Soares, Dušan Jakovetić
Federated Learning (FL) enables distributed machine learning training while preserving privacy, representing a paradigm shift for data-sensitive and decentralized environments. Despite its rapid advancements, FL remains a complex and multifaceted field, requiring a structured understanding of its methodologies…
Alessandro Salatiello
The remarkable performance of modern AI systems has been driven by unprecedented scales of data, computation, and energy—far exceeding the resources required by human intelligence. This disparity highlights the need for new guiding principles and motivates drawing inspiration from the fundamental organizational…
Babak Heydari, Mohsen Mosleh, Kia Dalili
This paper introduces a conceptual, yet quantifiable, architecture framework by extending the notion of system modularity in its broadest sense. Acknowledging that modularity is not a binary feature and comes in various types and levels, the proposed framework introduces higher levels of modularity that naturally…
Michael Pan, Peter J. Gawthrop, Joseph Cursons, Edmund J. Crampin
It is widely acknowledged that the construction of large-scale dynamic models in systems biology requires complex modelling problems to be broken up into more manageable pieces. To this end, both modelling and software frameworks are required to enable modular modelling. While there has been consistent progress in the…
Simon Boothroyd, Lee-Ping Wang, David Mobley, John Chodera + 1 more
Developing accurate classical force field representations of molecules is key to realizing the full potential of molecular simulations, both as a powerful route to gaining fundamental insight into a broad spectrum of chemical and biological phenomena, and for predicting physicochemical and mechanical properties of…
Maxwell L. Neal, Michael T. Cooling, Lucian P. Smith, Christopher T. Thompson + 5 more
Biological researchers increasingly rely on computational models to integrate biological systems knowledge, test hypotheses, and forecast system behavior. The expanding size of these models requires solutions for managing their complexity. Modularity, a time-tested design principle for managing complexity, can be…
Filip Milisav, Andrea I. Luppi, Laura E. Suárez, Guillaume Lajoie + 1 more
Modularity is a fundamental principle of brain organization, reflected in the presence of segregated sub-networks that enable specialized information processing. These small, densely connected modules are often nested within larger, higher-order modules, giving rise to a hierarchical modular architecture. This…
Sergio Garcia, Cong T. Trinh
Living cells optimize their fitness against constantly changing environments to survive. Goal attainment optimization is a mathematical framework to describe the simultaneous optimization of multiple conflicting objectives that must all reach a performance above a threshold or goal. In this study, we applied goal…
Bob Diertens
We introduce composition in the function-behaviour-structure framework for design, as described by John Gero, in order to deal with complexity. We do this by connecting the frameworks for the design of several models, in which one is constrained by the others. The result is a framework for the design of an object that…
Helle W. van den Maagdenberg, Martin Šícho, David Alencar Araripe, Sohvi Luukkonen + 9 more
Building reliable and robust quantitative structure-property relationship (QSPR) models is a challenging task. First, the experimental data needs to be obtained, analyzed and curated. Second, the number of available methods is continuously growing and evaluating different algorithms and methodologies can be arduous.…
Diego Alonso, Francisco Sánchez-Ledesma, Pedro Sánchez, Juan A. Pastor + 1 more
'Juan A. Pastor' 'Bárbara Álvarez'] The use of frameworks and components has been shown to be effective in improving software productivity and quality. However, the results in terms of reuse and standardization show a dearth of portability either of designs or of component-based implementations. This paper, which is…
Christopher Schölzel, Valeria Blesius, Gernot Ernst, Andreas Dominik
Reproducible, understandable models that can be reused and combined to true multi-scale systems are required to solve the present and future challenges of systems biology. However, many mathematical models are still built for a single purpose and reusing them in a different context can be challenging due to an…
Anna Matuszyńska, Oliver Ebenhöh, Matias D. Zurbriggen, Daniel C. Ducat + 1 more
Synthetic biology designs and constructs new biological parts, devices and systems with predetermined functionalities. With the unlimited ability to synthesise any DNA and RNA and transfer it to almost any organism, we are at the dawn of a new era in which biology is being recreated in ways never before possible. It…
Niloofar Shahidi, Michael Pan, Kenneth Tran, Edmund J Crampin + 1 more
The Systems Biology Markup Language (SBML) is a popular software-independent XML-based format for describing models of biological phenomena. The BioModels Database is the largest online repository of SBML models. Several tools and platforms are available to support the reuse and composition of SBML models. However…
Authors not listed
The exponential growth of chemical literature necessitates the development of automated tools for extracting and curating molecular information from unstructured scientific publications into open-access chemical databases. Current optical chemical structure recognition (OCSR) and named entity recognition solutions…
Authors not listed
Rapid and robust simulation of chemical processes is critical to conduct process design, optimization, techno-economic analysis, and sustainability analysis. Yet, efficiently solving simulation models remains a challenge due to the highly coupled and nonlinear nature of the underlying algebraic equations that capture…
Authors not listed
The widespread adoption of open-source cheminformatics toolkits remains constrained by technical implementation barriers, including complex installation procedures, dependency management, and integration challenges. Here, we present Cheminformatics Microservice V3, a significant update to the existing platform that…
Authors not listed
The increasing importance and predictive power of modern molecular modeling, driven by physics- and machine learning-based methods, necessitates a new collaborative architecture to replace the isolated, traditional model of software development. The traditional approach often led to redundant engineering effort, high…