Repository Index

Python REMote Interface library. Platform independent. In about 100 Kbytes, perfect for your diet.

• python
• gui-library
• remi
• platform-independent

中文古诗自动作诗机器人，x炸天，基于tensorflow1.10 api，正在积极维护升级中，快star，保持更新！

• tensorflow
• poetry
• lstm
• rnn

🌎 Windows 11 Settings, Tweaks, Scripts

• windows
• windows-11
• windows11
• flighthub

不用官方SDK，利用社交软件移动客户端(微信/QQ/微博/人人/支付宝)分享/登录/支付。

• openshare

「画像処理100本ノック」中文版本！为图像处理初学者设计的 100 个问题。

GDI, OpenGL and Direct3D 9 re-implementation of the DirectDraw API for classic 2D games for better compatibility with Windows ME, 2000, XP, Vista, 7, 8, 10, 11, Wine (Linux/macOS/Android) and Virtual Machines

• borderless
• ddraw
• directdraw
• upscaling

《神经网络与深度学习：案例与实践》第二版：10 章 PyTorch 实践、Notebook、测试与电子书。

• chinese
• deep-learning
• jupyter-notebook
• paddlepaddle

Graph Attention Networks (https://arxiv.org/abs/1710.10903)

• graph-attention-networks
• attention-mechanism
• self-attention
• tensorflow

效果更好的补帧软件，显存占用更小，是DAIN速度的10-25倍，包含抽帧处理，去除动漫卡顿感

• rife
• videoframeinterpolation
• video
• interpolation

15 motion design styles, each made by Claude Opus 5.5 writing code from one prompt: watch the films, copy the prompts, read the full source.

This repository is currently only used for issue tracking for www.regex101.com

Chinese Translation for Machine Learning Infographics

Memory Sparse Attention - A scalable, end-to-end trainable latent-memory framework for 100M-token contexts.

Shopware 6 is an open commerce platform based on Symfony Framework and Vue and supported by a worldwide community and more than 3.100 community extensions

• shopware
• php
• ecommerce
• vuejs

A comprehensive list of new ES features, including ES2015 (ES6), ES2016, ES2017, ES2018, ES2019

• es5
• es6
• es7
• es8

Trying to complete over 100 projects in various categories in golang.

Easy to Use, 100% Open Source Learning Management System

• courses-management-system
• education
• frappe
• learning-management-system

Web app for Scrapyd cluster management, Scrapy log analysis & visualization, Auto packaging, Timer tasks, Monitor & Alert, and Mobile UI. Docs 文档 :point_right:

• scrapy
• scrapyd
• scrapyd-ui
• scrapyd-api

基于NPS 0.26.10 版本二开而来，NPS接力项目。

• nps
• go
• http
• https

A curated list of 100+ libraries and frameworks for AI engineers building with LLMs

A hardware-accelerated video editor built on Rust, Tauri v2, and React 19. Sub-10ms frame decoding, GPU-native rendering, and a frame-accurate timeline — all free and open source under MIT.

• clypra
• video-editor
• editor
• tauri-app

RNA vaccines have become a key tool in moving forward through the challenges raised both in the current pandemic and in numerous other public health and medical challenges. With the rollout of vaccines for COVID-19, these synthetic mRNAs have become broadly distributed RNA species in numerous human populations. Despite their ubiquity, sequences are not always available for such RNAs. Standard methods facilitate such sequencing. In this note, we provide experimental sequence information for the RNA components of the initial Moderna (https://pubmed.ncbi.nlm.nih.gov/32756549/) and Pfizer/BioNTech (https://pubmed.ncbi.nlm.nih.gov/33301246/) COVID-19 vaccines, allowing a working assembly of the former and a confirmation of previously reported sequence information for the latter RNA. Sharing of sequence information for broadly used therapeutics has the benefit of allowing any researchers or clinicians using sequencing approaches to rapidly identify such sequences as therapeutic-derived rather than host or infectious in origin. For this work, RNAs were obtained as discards from the small portions of vaccine doses that remained in vials after immunization; such portions would have been required to be otherwise discarded and were analyzed under FDA authorization for research use. To obtain the small amounts of RNA needed for characterization, vaccine remnants were phenol-chloroform extracted using TRIzol Reagent (Invitrogen), with intactness assessed by Agilent 2100 Bioanalyzer before and after extraction. Although our analysis mainly focused on RNAs obtained as soon as possible following discard, we also analyzed samples which had been refrigerated (~4 ℃) for up to 42 days with and without the addition of EDTA. Interestingly a substantial fraction of the RNA remained intact in these preparations. We note that the formulation of the vaccines includes numerous key chemical components which are quite possibly unstable under these conditions-- so these data certainly do not suggest that the vaccine as a biological agent is stable. But it is of interest that chemical stability of RNA itself is not sufficient to preclude eventual development of vaccines with a much less involved cold-chain storage and transportation. For further analysis, the initial RNAs were fragmented by heating to 94℃, primed with a random hexamer-tailed adaptor, amplified through a template-switch protocol (Takara SMARTerer Stranded RNA-seq kit), and sequenced using a MiSeq instrument (Illumina) with paired end 78-per end sequencing. As a reference material in specific assays, we included RNA of known concentration and sequence (from bacteriophage MS2). From these data, we obtained partial information on strandedness and a set of segments that could be used for assembly. This was particularly useful for the Moderna vaccine, for which the original vaccine RNA sequence was not available at the time our study was carried out. Contigs encoding full-length spikes were assembled from the Moderna and Pfizer datasets. The Pfizer/BioNTech data [Figure 1] verified the reported sequence for that vaccine (https://berthub.eu/articles/posts/reverse-engineering-source-code-of-the-biontech-pfizer-vaccine/), while the Moderna sequence [Figure 2] could not be checked against a published reference. RNA preparations lacking dsRNA are desirable in generating vaccine formulations as these will minimize an otherwise dramatic biological (and nonspecific) response that vertebrates have to double stranded character in RNA (https://www.nature.com/articles/nrd.2017.243). In the sequence data that we analyzed, we found that the vast majority of reads were from the expected sense strand. In addition, the minority of antisense reads appeared different from sense reads in lacking the characteristic extensions expected from the template switching protocol. Examining only the reads with an evident template switch (as an indicator for strand-of-origin), we observed that both vaccines overwhelmingly yielded sense reads (>99.99%). Independent sequencing assays and other experimental measurements are ongoing and will be needed to determine whether this template-switched sense read fraction in the SmarterSeq protocol indeed represents the actual dsRNA content in the original material. This work provides an initial assessment of two RNAs that are now a part of the human ecosystem and that are likely to appear in numerous other high throughput RNA-seq studies in which a fraction of the individuals may have previously been vaccinated. ProtoAcknowledgements: Thanks to our colleagues for help and suggestions (Nimit Jain, Emily Greenwald, Lamia Wahba, William Wang, Amisha Kumar, Sameer Sundrani, David Lipman, Bijoyita Roy). Figure 1: Spike-encoding contig assembled from BioNTech/Pfizer BNT-162b2 vaccine. Although the full coding region is included, the nature of the methodology used for sequencing and assembly is such that the assembled contig could lack some sequence from the ends of the RNA. Within the assembled sequence, this hypothetical sequence shows a perfect match to the corresponding sequence from documents available online derived from manufacturer communications with the World Health Organization [as reported by https://berthub.eu/articles/posts/reverse-engineering-source-code-of-the-biontech-pfizer-vaccine/]. The 5’ end for the assembly matches the start site noted in these documents, while the read-based assembly lacks an interrupted polyA tail (A30(GCATATGACT)A70) that is expected to be present in the mRNA.

The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919

• segmentation
• semantic-segmentation
• cityscapes
• pascal-context

100%开源的企业培训系统，界面美观，操作简单，一键部署您的私有化培训平台！

• java
• springboot3