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Copy file name to clipboardexpand all lines: docs/awesome/awesome-agi-cocosci.md
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*[PhotoScout: Synthesis-Powered Multi-Modal Image Search](https://dl.acm.org/doi/full/10.1145/3613904.3642319) - ***ACM SIGCHI'24***, 2024. [[All Versions](https://scholar.google.com/scholar?cluster=6522231014055730719)]. This paper explores a new multi-modal image search approach that allows users to conveniently specify and perform semantic image search tasks. With the tool, PhotoScout, the user interactively provides natural language descriptions, positive and negative examples, and object tags to specify their search tasks. Under the hood, PhotoScout is powered by a program synthesis engine that generates visual queries in a domain-specific language and executes the synthesized program to retrieve the desired images.
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* [Expert-level protocol translation for self-driving labs](https://proceedings.neurips.cc/paper_files/paper/2024/hash/54dd9e0cff6d9214e20d97eb2a3bae49-Abstract-Conference.html) - ***NeurIPS'24***, 2024. [[All Versions](https://scholar.google.com/scholar?cluster=13997597682274906943)]. Recent development in Artificial Intelligence (AI) models has propelled their application in scientific discovery, but the validation and exploration of these discoveries require subsequent empirical experimentation. The concept of self-driving laboratories promises to automate and thus boost the experimental process following AI-driven discoveries. However, the transition of experimental protocols, originally crafted for human comprehension, into formats interpretable by machines presents significant challenges, which, within the context of specific expert domain, encompass the necessity for structured as opposed to natural language, the imperative for explicit rather than tacit knowledge, and the preservation of causality and consistency throughout protocol steps. Presently, the task of protocol translation predominantly requires the manual and labor-intensive involvement of domain experts and information technology specialists, rendering the process time-intensive. To address these issues, this work proposes a framework that automates the protocol translation process through a three-stage workflow, which incrementally constructs Protocol Dependence Graphs (PDGs) that approach structured on the syntax level, completed on the semantics level, and linked on the execution level. Quantitative and qualitative evaluations have demonstrated its performance at par with that of human experts, underscoring its potential to significantly expedite and democratize the process of scientific discovery by elevating the automation capabilities within self-driving laboratories.
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* [Expert-level protocol translation for self-driving labs](https://proceedings.neurips.cc/paper_files/paper/2024/hash/54dd9e0cff6d9214e20d97eb2a3bae49-Abstract-Conference.html) - ***NeurIPS'24***, 2024. [[All Versions](https://scholar.google.com/scholar?cluster=13997597682274906943)]. [[Project]()]. Recent development in Artificial Intelligence (AI) models has propelled their application in scientific discovery, but the validation and exploration of these discoveries require subsequent empirical experimentation. The concept of self-driving laboratories promises to automate and thus boost the experimental process following AI-driven discoveries. However, the transition of experimental protocols, originally crafted for human comprehension, into formats interpretable by machines presents significant challenges, which, within the context of specific expert domain, encompass the necessity for structured as opposed to natural language, the imperative for explicit rather than tacit knowledge, and the preservation of causality and consistency throughout protocol steps. Presently, the task of protocol translation predominantly requires the manual and labor-intensive involvement of domain experts and information technology specialists, rendering the process time-intensive. To address these issues, this work proposes a framework that automates the protocol translation process through a three-stage workflow, which incrementally constructs Protocol Dependence Graphs (PDGs) that approach structured on the syntax level, completed on the semantics level, and linked on the execution level. Quantitative and qualitative evaluations have demonstrated its performance at par with that of human experts, underscoring its potential to significantly expedite and democratize the process of scientific discovery by elevating the automation capabilities within self-driving laboratories.
Copy file name to clipboardexpand all lines: docs/awesome/awesome-angular.md
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*[ngx-translate-router](https://github.com/gilsdav/ngx-translate-router) - Translate routes using `ngx-translate`.
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*[ngx-translate-routes](https://github.com/darioegb/ngx-translate-routes) - This service translates titles and route paths.
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*[@transifex/angular](https://github.com/transifex/transifex-javascript/tree/master/packages/angular/projects/tx-native-angular-sdk) - You can easily localize Angular components using the [@transifex/angular](https://www.npmjs.com/package/@transifex/angular) library extension. This library extends the functionality of [Transifex Native JavaScript SDK](https://developers.transifex.com/docs/javascript-sdk).
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*[doloc](https://doloc.io/) - Instant translations in your [Angular](https://doloc.io/getting-started/frameworks/angular/) workflow.
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#### Module Federation
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*[extreme-angular](https://github.com/joematthews/extreme-angular) - A starter template with pre-configured dev tools that enforce best practices for creating clean, maintainable, and accessible web apps.
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*[ng-advance](https://github.com/ksunny-works/ng-advance) - A modern and fully-configured Angular starter template, empowering developers to quickly bootstrap their Angular projects with tools like Prettier, Jest, Husky, and ESLint.
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*[@wlucha/angular-starter](https://github.com/wlucha/angular-starter) - Angular 19 Starter with Storybook, Transloco, Jest, Cypress, Docker, ESLint, Material, & Prettier.
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*[angular-clean-architecture](https://github.com/carlossalasamper/angular-clean-architecture) - An Angular scaffold with a clean architecture that is easy to understand.
*[Jet](https://docs.jetproject.dev/) - Jet is the ultimate Angular + Material Design boilerplate to build ambitious, robust web apps. Jet satisfies 60+ functional and non-functional stories.
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*[Vortex](https://template.giacomobellazzi.com/) - A high-performance web application template built with Angular and Java, designed to deliver seamless user experiences and powerful backend solutions.
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#### Testing
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*[ngx-windows](https://github.com/mateuszbilicz/ngx-windows) - Angular Windows Components and Services.
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*[ngx-speculative-link](https://github.com/push-based/ngx-speculative-link) - An Angular implementation of [Speculative Rules API](https://developer.mozilla.org/en-US/docs/Web/API/Speculation_Rules_API) inspired by [quicklink](https://github.com/GoogleChromeLabs/quicklink) and ngx-quicklink.
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*[ngx-signal-pipes](https://github.com/wassim-k/ngx-signal-pipes) - Transform Angular signals with functional pipes.
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*[ng-gd](https://github.com/luisalejandrofigueredo/ng-gd) - An easy way to manage a canvas element with support for mouse or tablet events.
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#### Drag and Drop
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*[ngx-fileupload](https://github.com/r-hannuschka/ngx-fileupload) - [ngx-file-upload/core](https://github.com/r-hannuschka/ngx-fileupload/tree/master/src/projects/core) only contains services and classes to enable file upload with Angular. [ngx-file-upload/ui](https://github.com/r-hannuschka/ngx-fileupload/tree/master/src/projects/ui) contains components and pipes to provide a UI.
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*[ngx-file-preview](https://github.com/wh131462/ngx-file-preview) - A powerful preview tool for many file types.
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*[ngx-image-upload](https://github.com/osmanabdelsalam/ngx-image-upload) - A lightweight, customizable library for image uploads with preview, validation, and smooth animations. Supports Reactive Forms and `ngTemplate` for full flexibility.
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*[filestack-angular](https://github.com/filestack/filestack-angular) - Integrate [Filestack](https://www.filestack.com/) into your Angular app for a faster, safer, and more reliable file upload experience.
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*[mutates](https://github.com/IKatsuba/mutates) - A powerful toolset for mutating the Abstract Syntax Tree (AST) of TypeScript files. It is a fork of [ng-morph](https://github.com/taiga-family/ng-morph), with a broader focus beyond Angular-specific transformations, allowing for extensive AST modifications in any TypeScript project.
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*[type-fest](https://github.com/sindresorhus/type-fest) - A collection of essential TypeScript types. Either add the package as a dependency or copy-paste the needed types.
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*[ts-serializer](https://github.com/paddls/ts-serializer) - Serialize your models into strongly typed Typescript classes.
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*[tsconfig](https://github.com/smartrecruiters/tsconfig) - SmartRecruiters’ tsconfig contains all strict rules and improves your project type-safety.
Copy file name to clipboardexpand all lines: docs/awesome/awesome-annual-security-reports.md
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-[Deepwatch](https://www.deepwatch.com/2024-ati-threat-report/) - [Annual Threat Report](https://github.com/jacobdjwilson/awesome-annual-security-reports/blob/master/Annual%20Security%20Reports/2024/Deepwatch-Annual-Threat-Report-2024.pdf) (2024) - Analyzes cybersecurity trends, observations, and metrics to provide insights and forecasts for the upcoming year.
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-[Department of Homeland Security](https://www.dhs.gov/publication/homeland-threat-assessment) - [Threat Assessment](https://github.com/jacobdjwilson/awesome-annual-security-reports/blob/master/Annual%20Security%20Reports/2025/DHS-Threat-Assessment-2025.pdf) (2025) - Outlines key threats to the U.S. homeland, including public safety, terrorism, illegal drugs, and nation-state influence, aiming to safeguard American people, homeland, and values.
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-[DNSFilter](https://explore.dnsfilter.com/2025-annual-security-report) - [Annual Security Report](https://github.com/jacobdjwilson/awesome-annual-security-reports/blob/master/Annual%20Security%20Reports/2025/DNSFilter-Annual-Security-Report-2025.pdf) (2025) - Analyzes trends in DNS-based cyber threats, highlighting phishing, malware distribution, and evasive techniques used by adversaries, along with recommendations for improving domain-layer security.
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-[Dragos](https://www.dragos.com/ot-cybersecurity-year-in-review/) - [OT Cybersecurity Report A Year in Review](https://github.com/jacobdjwilson/awesome-annual-security-reports/blob/master/Annual%20Security%20Reports/2025/Dragos-OT-Cybersecurity-Report-A-Year-in-Review-2025.pdf) (2025) - Analyzes trends in industrial control systems (ICS) and operational technology (OT) vulnerabilities, threats targeting industrial environments, and industry trends from customer engagements worldwide.
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-[ENISA](https://www.enisa.europa.eu/publications/enisa-threat-landscape-2024) - [Threat Landscape Report](https://github.com/jacobdjwilson/awesome-annual-security-reports/blob/master/Annual%20Security%20Reports/2024/ENISA-Threat-Landscape-2024.pdf) (2024) - An annual summary of key cybersecurity threats, trends, and attack techniques. It examines threat actors, motivations, impacts, and suggests mitigation strategies.
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-[Ensign](https://www.ensigninfosecurity.com/resources/threat-insights/cyber-threat-landscape-report-2024) - [Cyber Threat Landscape Report](https://github.com/jacobdjwilson/awesome-annual-security-reports/blob/master/Annual%20Security%20Reports/2024/Ensign-Cyber-Threat-Landscape-Report-2024.pdf) (2024) - Analysis of key cyber threats across Asia, focusing on Singapore, Malaysia, Indonesia, South Korea, Australia, and Greater China.
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-[Expel](https://expel.com/annual-threat-report/) - [Annual Threat Report](https://github.com/jacobdjwilson/awesome-annual-security-reports/blob/master/Annual%20Security%20Reports/2024/Expel-Annual-Threat-Report-2024.pdf) (2024) - Provides an overview of cyber threats and attack trends observed by Expel's security operations team throughout the year.
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-[Microsoft](https://www.microsoft.com/en-us/security/security-insider/intelligence-reports/microsoft-digital-defense-report-2024) - [Digital Defense Report](https://github.com/jacobdjwilson/awesome-annual-security-reports/blob/master/Annual%20Security%20Reports/2024/Microsoft-Digital-Defense-Report-2024.pdf) (2024) - Analyzes global cybersecurity trends, offering insights into threat actor tactics, emerging vulnerabilities, and strategies for improving digital defense.
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-[NCC Group](https://www.nccgroup.com/us/threat-monitor-report-2024/) - [Threat Monitor Report](https://github.com/jacobdjwilson/awesome-annual-security-reports/blob/master/Annual%20Security%20Reports/2024/NCCGroup-Threat-Monitor-Report-2024.pdf) (2024) - Provides an analysis of current cyber threats, offering insights into attack trends, vulnerabilities, and strategies for improving organizational cybersecurity.
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-[NCSC](https://www.ncsc.govt.nz/news/cyber-threat-report-2024) - [Cyber Threat Report](https://github.com/jacobdjwilson/awesome-annual-security-reports/blob/master/Annual%20Security%20Reports/2024/NCSC-Cyber-Threat-Report-2024.pdf) (2024) - Analyzes the Aotearoa New Zealand cyber threat landscape, focusing on incidents impacting individuals and small to medium businesses.
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-[Nozomi](https://www.nozominetworks.com/ot-iot-cybersecurity-trends-insights-february-2025) - [Networks OT IoT Security Report](https://github.com/jacobdjwilson/awesome-annual-security-reports/blob/master/Annual%20Security%20Reports/2025/Nozomi-Networks-OT-IoT-Security-Report-2025.pdf) (2025) - Analyzes cyber risks for industrial and critical infrastructure organizations.
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-[Rapid7](https://www.rapid7.com/research/report/2024-attack-intelligence-report/) - [Attack Intelligence Report](https://github.com/jacobdjwilson/awesome-annual-security-reports/blob/master/Annual%20Security%20Reports/2024/Rapid7-Attack-Intelligence-Report-2024.pdf) (2024) - Analyzes attack patterns and techniques, offering insights into adversary tactics and strategies for improving organizational cyber defense.
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-[RecordedFuture](https://www.recordedfuture.com/research/2024-annual-report) - [Cyber Threat Analysis Report](https://github.com/jacobdjwilson/awesome-annual-security-reports/blob/master/Annual%20Security%20Reports/2024/RecordedFuture-Cyber-Threat-Analysis-Report-2024.pdf) (2024) - Highlights the resilience of cybercriminal networks despite law enforcement actions and the growing complexity of enterprise attack surfaces.
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-[RedCanary](https://redcanary.com/threat-detection-report/) - [Threat Detection Report](https://github.com/jacobdjwilson/awesome-annual-security-reports/blob/master/Annual%20Security%20Reports/2024/RedCanary-Threat-Detection-Report-2024.pdf) (2024) - Examines current attack techniques and detection strategies, offering insights into improving organizational threat detection capabilities.
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