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1. BioSimulators: a central registry of simulation engines and services for recommending specific tools

   https://doi.org/10.1093/nar/gkac331  

   Shaikh, Bilal; Smith, Lucian P; Vasilescu, Dan; Marupilla, Gnaneswara; Wilson, Michael; Agmon, Eran; Agnew, Henry; Andrews, Steven S; Anwar, Azraf; Beber, Moritz E; et al (May 2022, Nucleic Acids Research)

   Abstract Computational models have great potential to accelerate bioscience, bioengineering, and medicine. However, it remains challenging to reproduce and reuse simulations, in part, because the numerous formats and methods for simulating various subsystems and scales remain siloed by different software tools. For example, each tool must be executed through a distinct interface. To help investigators find and use simulation tools, we developed BioSimulators (https://biosimulators.org), a central registry of the capabilities of simulation tools and consistent Python, command-line and containerized interfaces to each version of each tool. The foundation of BioSimulators is standards, such as CellML, SBML, SED-ML and the COMBINE archive format, and validation tools for simulation projects and simulation tools that ensure these standards are used consistently. To help modelers find tools for particular projects, we have also used the registry to develop recommendation services. We anticipate that BioSimulators will help modelers exchange, reproduce, and combine simulations. 

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2. Benefits and Drawbacks of Adopting a Secure Programming Language: Rust as a Case Study

   Fulton, Kelsey R.; Chan, Anna; Votipka, Daniel; Hicks, Michael; Mazurek, Michelle L. (August 2021, Symposium on Usable Privacy and Security)

   Programming languages such as Rust and Go were developed to combat common and potentially devastating memory safety-related vulnerabilities. But adoption of new, more secure languages can be fraught and complex. To better understand the benefits and challenges of adopting Rust in particular, we conducted semi-structured interviews with professional, primarily senior software developers who have worked with Rust on their teams or tried to introduce it (n = 16), and we deployed a survey to the Rust development community (n = 178). We asked participants about their personal experiences using Rust, as well as experiences using Rust at their companies. We find a range of positive features, including good tooling and documentation, benefits for the development lifecycle, and improvement of overall secure coding skills, as well as drawbacks including a steep learning curve, limited library support, and concerns about the ability to hire additional Rust developers in the future. Our results have implications for promoting the adoption of Rust specifically and secure programming languages and tools more generally. 

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3. Learning to Scale Multilingual Representations for Vision-Language Tasks

   Andrea Burns, Donghyun Kim (January 2020, European Conference on Computer Vision)

   null (Ed.)

   Current multilingual vision-language models either require a large number of additional parameters for each supported language, or suffer performance degradation as languages are added. In this paper, we-9*6 propose a Scalable Multilingual Aligned Language Representation (SMALR) that supports many languages with few model parameters without sacrificing downstream task performance. SMALR learns a fixed size language-agnostic representation for most words in a multilingual vocabulary, keeping language-specific features for just a few. We use a masked cross-language modeling loss to align features with context from other languages. Additionally, we propose a cross-lingual consistency module that ensures predictions made for a query and its machine translation are comparable. The effectiveness of SMALR is demonstrated with ten diverse languages, over twice the number supported in vision-language tasks to date. We evaluate on multilingual image-sentence retrieval and outperform prior work by 3–4% with less than 1/5th the training parameters compared to other word embedding methods. 

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4. Learning to Scale Multilingual Representations for Vision-Language Tasks

   https://doi.org/10.1007/978-3-030-58548-8  

   Andrea Burns, Donghyun Kim (January 2020, European Conference on Computer Vision)

   null (Ed.)

   Current multilingual vision-language models either require a large number of additional parameters for each supported language, or suffer performance degradation as languages are added. In this paper, we-9*6 propose a Scalable Multilingual Aligned Language Representation (SMALR) that supports many languages with few model parameters without sacrificing downstream task performance. SMALR learns a fixed size language-agnostic representation for most words in a multilingual vocabulary, keeping language-specific features for just a few. We use a masked cross-language modeling loss to align features with context from other languages. Additionally, we propose a cross-lingual consistency module that ensures predictions made for a query and its machine translation are comparable. The effectiveness of SMALR is demonstrated with ten diverse languages, over twice the number supported in vision-language tasks to date. We evaluate on multilingual image-sentence retrieval and outperform prior work by 3–4% with less than 1/5th the training parameters compared to other word embedding methods. 

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5. Cell Modeling in Jupyter Notebook using CompuCell3D

   https://doi.org/10.5281/zenodo.7600786  

   Chung, Trinity; Sego, T. J.; Glazier, James A. (January 2023, Journal of advanced technological education)

   CompuCell3D (CC3D) is an open-source software framework for building and executing multi-cell biological virtual-tissue models. It represents cells using the Glazier–Graner–Hogeweg model, also known as Cellular Potts model. The primary CC3D application consists of two separate tools, a smart model editor (Twedit++) and a tool for model execution, visualization and steering (Player). The CompuCell3D version 4.x release introduces support for Jupyter Notebooks, an interactive computational environment, which brings the benefits of reproducibility, portability, and self-documentation. Since model specifications in CC3D are written in Python and CC3DML and Jupyter supports Python and other languages, Jupyter can naturally act as an integrated development environment (IDE) for CC3D users as well as a live document with embedded text and simulations. This update follows the trend in software to move away from monolithic freestanding applications to the distribution of methodologies in the form of libraries that can be used in conjunction with other libraries and packages. With these benefits, CC3D deployed inJupyter Notebook is a more natural and efficient platform for scientific publishing and education using CC3D. 

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