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<p>Sugar has been using GTK2 as its primary toolkit, for many years. But recently major changes have occurred in the sugar’s technology which includes an upgrade to a newer version of GTK+ i.e. the GTK3 toolkit and PyGI. Because of these changes in technology sugar is divided on these old and new distributions.</p> <p>This project is all about porting a dozen of major and minor activities of sugar which were based on “GTK2 and GST0”.10 to “GTK3 and GST1.0” in order for sugar to remain innovative stable and fully updated with newer technology.</p> <p>These are the 12 activities whose refactoring will be done : Turtleart, Record, Chat, Calculate, Colors, Stopwatch, Dots and Boxes, Slider-puzzle-branch, Classroom broadcast, Convert, Arithmetic, Pukllanapac.</p>

<p><a href="https://github.com/deislabs/smi-metrics" target="_blank">SMI-Metrics</a> aims to have a commen interface to get metrics from servish mesh implementations. Applications, Tools can be built targeting this interface without having to write anything specific to an implementation. Users also don't have to learn the APIs of each mesh but rather have this shim in their kubernetes cluster which provides a common API. As the <a href="https://github.com/deislabs/smi-metrics" target="_blank">smi-metrics</a> repo is pretty new, my work is to take care of this whole repository i.e CI, bugs, etc while also implementing the support for Istio and Consul Connect Service Meshes.</p>

Sugar Activity on Demand addresses a key barrier in Sugar Labs: the difficulty learners face in creating their own activities due to the need for programming knowledge. This limits access to constructionist learning, where students learn best by building meaningful projects. This project introduces an AI-assisted system that allows learners to describe an activity in natural language and receive a fully functional, installable Sugar activity. The system combines a model-agnostic LLM pipeline, a retrieval-augmented knowledge base built from real Sugar Activity source code, and an AST-based validator to ensure that generated Python code is both correct and safe. Activities are generated with proper GTK3 interfaces, toolbar integration, and Journal support, ensuring they are fully compatible with the Sugar ecosystem. Beyond generation, the project emphasizes learning through a Reflective Studio, where learners explore, understand, and modify the generated code. Using scaffolded challenges, inline annotations, and reflection prompts, the system follows the constructionist Use → Modify → Create progression, enabling learners to gradually take ownership of their creations rather than passively consuming generated output. Deliverables AI-powered activity generation pipeline (prompt → plan → code → installable bundle) RAG-based knowledge system using real Sugar Activity examples AST-based security validation and safe code generation framework Interactive Reflective Studio with guided editing, annotations, and challenges Integration into Sugar’s Home View with a seamless “Create with AI” entry point Support for iterative refinement, version history, and sharing via the Sugar Journal This project aligns with Sugar Labs’ constructionist philosophy by transforming AI from a passive generator into an active learning partner, empowering learners not just to use software, but to understand and create it.

Genomic data sharing is slowed by manually cross-checking consent and data-use language against dense GA4GH and related policy text, while generic LLMs risk hallucinated citations. This project extends GA4GH-RegBot, an open-source RAG assistant that ingests policy PDFs into a Chroma vector store with a BM25 manifest, retrieves with dense embeddings plus BM25 fused via reciprocal rank fusion, and generates structured compliance JSON with hard grounding: chunk-ID allow-list verification with automatic retries and token-overlap filtering on the LLM path. Deliverables across the GSoC period include hierarchy-aware parsing and richer metadata for GA4GH PDFs, cross-encoder re-ranking on top of the existing hybrid stack, an open-source LLM path alongside the current OpenAI integration, Streamlit and CLI updates, Ragas or TruLens-based evaluation with documented thresholds, expanded tests and CI, and polished documentation for contributors and REWS stakeholders.

My proposal is centered around integrating GitHub discussions seamlessly into the leaderboard repository while concurrently enhancing the scraper's type safety. This comprehensive approach will involve a meticulous refactoring of the existing Python-based scraper to TypeScript, ensuring a robust and type-safe codebase. Leveraging the power of Octokit and GraphQL, I intend to optimize the process of scraping GitHub data, enhancing efficiency and reliability. Furthermore, I aim to introduce an innovative reward system for contributors, incentivizing active participation and fostering a collaborative environment. This system will recognize and reward contributors when their discussions are marked as answered, along with receiving an empathy badge as an acknowledgment of their valuable contribution. Overall, this proposal represents a strategic amalgamation of technical refinement and community enrichment, aligning with the overarching objectives of the project while enhancing its functionality and user experience.

Milvus currently lacks a Debezium source connector, meaning data can flow into Milvus (via sink connectors) but not out of it into the broader data ecosystem. This critical gap forces users into manual workarounds for data replication, auditing, and prevents the creation of hybrid pipelines that join vector search results with relational data. The plan is to implement a Hybrid strategy focused exclusively on the future-proof Milvus 2.6+ StreamingNode architecture. This approach will leverage two separate sources to guarantee a complete and ordered change stream: Woodpecker Streaming Service (WAL): Used as the only source for all Data Manipulation Language (DML) events (inserts and deletes). Etcd Watch: Used as the cleanest source for all Data Definition Language (DDL) events (schema changes), which simplifies parsing and aligns with Debezium's schema history mechanism.

<p>The goal of this project is to implement the support for Research Object specification into Nextflow workflow framework, with the aim to improve the reproducibility and transparency of the resulting data-analysis and computational workflows based on such tool.</p>

<p>This project is about extending Ruma's API coverage. The final goal for this project is to have a more complete coverage of the Matrix spec, along with implementation of two recent MSCs in Ruma.</p> <p>The three main milestones for the project are the following:</p> <ol> <li>finishing <a href="https://github.com/ruma/ruma/milestone/3" target="_blank">identity-service-api</a></li> <li>implementing <a href="https://github.com/ruma/ruma/issues/479" target="_blank">MSC2403 (Add "knock" feature)</a></li> <li>implementing <a href="https://github.com/ruma/ruma/issues/478" target="_blank">MSC1946 (Secure Secret Storage and Sharing)</a></li> </ol> <p>However, other tasks are part of the project schedule. These are of a smaller scale, but aim to help me get more familiar with the code base, or just generally improve Ruma.</p>

Crypt4GH is a file format developed by GA4GH that keeps genomic data encrypted at rest and in transit. Currently, implementations of the TES API do not support processing Crypt4GH files. I propose an implementation of the TES API that handles Crypt4GH files through the use of middleware that alters the initial TES request in order decrypt Crypt4GH files before processing. First, I will create a "TES playground" that is able to run a simple task. Then, I will add to the functionality of this playground in order to demonstrate an implementation of the TES API that can handle a Crypt4GH-encrypted file as an input. This project will hopefully serve as a proof-of-concept to inform future standard-setting works.

The cBioPortal provides access to a wealth of cancer genomics data, but new users often struggle to navigate its features, and existing users may not be aware of all available tools. This project aims to enhance the user experience of the cBioPortal for Cancer Genomics by implementing an interactive web tour feature. The objective is to guide new users on how to use the portal and to showcase new features to experienced users. The project proposes using reactour for implementing the web tour and local storage to record the tour progress. The deliverables include implementing the web tour feature for the group comparison tool, allowing users to disable hints, and addressing difficulties such as automatically filling input boxes and continuing tour steps after jumping to other pages.

The goal of this project is to enhance the usability of Decorator Command Set (DCS) data by developing a utility/method to convert verbose, complex JSON formats into a more human readable YAML representation and back again. Currently, it is highly verbose to read, write, and edit DCS JSON files. The plan is to implement a converter that turns DCS JSON objects into a simple YAML format and back again. The new YAML will be less verbose and more readable, helping people work with DCS better. By the end, a fully integrated converter will be delivered, complete with tests and proper documentation.

The field of bioinformatics has used many different extensions to express genomics data throughout its history, most of them focusing on simplicity to work and on human-readability. However, with the recent research on big data analysis, formats that focus on performance would greatly improve the potential to work with big genomics datasets. This project aims to be a step towards discovering the advantages of the many possible formats in many possible scenarios, by making it easy to translate any one of them to another. Such an objective seems useful for: Discovering the optimal format for performance critical applications. Easy conversion from one tool to another, for bioinformatics researchers and hackers. We will achieve that by using an Internal Representation of the different possible semantic data represented in each format, that will then allow translation from one format to another. This IR will probably be built in one of the widely used standard file formats, such as Protocol Buffers or Amazon’s Ion, since these technologies are already being widely used and already have great performance and a lot of features built into them.

<p>The project is aimed to design and implement the JSON API to programmatically query the BookBrainz database. Since the existing backend of BookBrainz website is written using node.js and its framework express.js, therefore we will also use the node.js and express.js to implement this project. This API will use the current BookBrainz ORM bookbrainz-data-js to access the database.</p>

Work on the fluffychat and matrix dart sdk calling functionality and make it stable for everyday use. Along with this the UI of the call screens will also be updated and calling should work in background and terminated states of the app as well.

<p>The objective of the problem arises from the reconstruction of gene genealogies problem - from a given genotypes of sequence data from contemporary individuals and an extended pedigree of genealogical relationships among them we have to decide and be very clear about what we should consider to be nodes information in genealogy tree according to kinds of dependencies among these nodes which should be considered to be edges of the tree. This project will focus on the development of novel algorithms for advanced reconstruction of the gene genealogy by performing inference on graphical models, specifically, implementing the greedy approach and loopy belief propagation algorithm on the succinct tree sequences. The implemented algorithms would undoubtedly be of use to integrate into the existing tskit and msprime libraries.</p>

<p>The aim of this project is to use the camera and processing power of modern day cell phones to develop an intuitive and user-friendly application for the detection of cancer biomarkers from a small drop of blood. This will serve as a screening test for the same. The application will allow the user to take images of the blood samples in a set format. The image will then be segmented using a background subtraction algorithm to detect the regions of interest. After noise removal, the intensity of each individual blob will be calculated. A linear curve will be fit through the intensity and known concentration data and the concentrations of the unknown samples will be estimated from the standard curve which will quantify the various molecules present in the sample.</p>

<p>Green Navigation will become a great tool to calculate routes and compare routing algorithms. But imagine a front-end, that shows directions of the route and interesting informations about the current position in real-time! In this proposal I will show how to extend Green Navigation to a complete navigation system.</p> <p>My ideas would not only fit to the front-end project Integration of new features, they will be fit more to the project own idea.</p> <p>The idea is to create a mockup of a smart notification system, which will show directions of the calculated route as well as every other useful information existing in database. The notification could be a paper-card element, which shows up at top of the web app. Furthermore the mockup should be open enough to handle data added in future.</p>

Problems faced while developing labelled data: 1. Annotations made by a single person can include their biases into the data and eventually into the model 2. There are subjective tasks at times, which might not have a clear answer associated with them 3. The size of the dataset might be huge enough for a few people to annotate To resolve this, a solution is to let multiple people annotate the data and then aggregate the annotations based on a consensus. Crowdsourcing has become an essential paradigm for efficiently labelling large datasets, especially in the era of data-driven ML solutions. However, the challenge arises in aggregating the labels from a diverse pool of annotators, each with varying reliability. This project aims to develop solutions to handle the above problems and integrate their solution into CVAT. It

<p>On MusicBrainz, URLs are external links attached to entities; relationships define their role and include metadata like date period, they provide extra information about the entity and inspire users to explore further.</p> <p>Currently, the URL relationship editor on MusicBrainz has many shortcomings. Though it is a relationship, the URL editor has a different UI from other editors. Automatic rules were built to ease the effort, but outdated and buggy rules make them an obstacle in some situations. For better user experience, we would like to enhance the URL relationship editor, to support multiple relationship types for a single link, to provide a unified appearance, better user experience and more flexibility.</p>

<p>Adding end-to-end encryption to libqmatrixclient for future support in Qt/libqmatrixclient-based client like Quaternion.</p>

<p>A key step towards the development of effective personalized cancer treatments is the collection of vast stores of patient data on a variety of tumor types, and cBioPortal has taken these efforts by The Cancer Genome Atlas (TCGA) and provided an accessible visualization tool for biological data discovery. Currently, cBioPortal has a multitude of information on DNA and RNA, but their information on protein levels derives from protein arrays, a technology that has severe limitations relative to mass spectrometry. Clinical Proteomic Tumor Analysis Consortium (CPTAC) has performed mass spectrometry on the patient samples for TCGA tumors and it also includes information on post-translational modifications. I propose to integrate this information with the cBioPortal visualization interface. This involves extending their database with protein abundances and PTMs based on the CPTAC data and updating the cBioPortal interface with a new tab for post-translational modifications and updating existing tabs to accommodate the new protein data. By providing this upgrade, a tool that helps both scientists and doctors see personal and population biology at a glance will gain a new dimension.</p>

Starter repositories and deployment blueprints for full-stack apps on DigitalOcean App Platform.

<p>antiSMASH, a python-based tool to mine micro-organisms genomes, currently uses pyQuery to generate static HTML pages. Consequently, several difficulties are found when improvements/changes need to be performed. This library is commonly described as too verbose, implying most of the times, string concatenations and mixed code for both presentation and logic. Subsequently, it is not much intuitive. In addition, recent patch update from 1.2.9 to 1.2.10 resulted in a backward compatibility break, and as a minor patch should not raise compatibility issues, the trust in this library is somehow compromised. Template Engines overcome the majority of the issues related to output generation. They are powerful tools that allow the developers to speed up their work in an easier and much cleaner way.</p> <p>This project proposes moving antiSMASH to jinja2, a well known, widely used and developer-friendly templating language for Python. With this migration, we intend to facilitate the future development of antiSMASH as well as the onboarding of new developers to the team. Moreover, considering jinja2 enormous user-base and applications, a backwards compatibility break in a minor version is unlikely.</p>