Certifying derivation of state machines from coroutines

One of the biggest implementation challenges in security-critical network protocols is nested state machines. In practice today, state machines are either implemented manually at a low level, risking bugs easily missed in audits; or are written using higher-level abstractions like threads, depending on runtime systems that may sacrifice performance or compatibility with the ABIs of important platforms (e.g., resource-constrained IoT systems). We present a compiler-based technique allowing the best of both worlds, coding protocols in a natural high-level form, using freer monads to represent nested coroutines , which are then compiled automatically to lower-level code with explicit state. In fact, our compiler is implemented as a tactic in the Coq proof assistant, structuring compilation as search for an equivalence proof for source and target programs. As such, it is straightforwardly (and soundly) extensible with new hints, for instance regarding new data structures that may be used for efficient lookup of coroutines. As a case study, we implemented a core of TLS sufficient for use with popular Web browsers, and our experiments show that the extracted Haskell code achieves reasonable performance.

Applications of Web Scraping in Economics and Finance

The 21st-century economy is increasingly built around data. Firms and individuals upload and store enormous amount of data. Most of the produced data is stored on private servers, but a considerable part is made publicly available across the 1.83 billion websites available online. These data can be accessed by researchers using web-scraping techniques. Web scraping refers to the process of collecting data from web pages either manually or using automation tools or specialized software. Web scraping is possible and relatively simple thanks to the regular structure of the code used for websites designed to be displayed in web browsers. Websites built with HTML can be scraped using standard text-mining tools, either scripts in popular (statistical) programming languages such as Python, Stata, R, or stand-alone dedicated web-scraping tools. Some of those tools do not even require any prior programming skills. Since about 2010, with the omnipresence of social and economic activities on the Internet, web scraping has become increasingly more popular among academic researchers. In contrast to proprietary data, which might not be feasible due to substantial costs, web scraping can make interesting data sources accessible to everyone. Thanks to web scraping, the data are now available in real time and with significantly more details than what has been traditionally offered by statistical offices or commercial data vendors. In fact, many statistical offices have started using web-scraped data, for example, for calculating price indices. Data collected through web scraping has been used in numerous economic and finance projects and can easily complement traditional data sources.

Online tools to easily build augmented reality models of biomolecules that run right on the web

Several groups developed in the last years augmented and virtual reality (AR/VR) programs and apps to visualize 3D molecules, most rather static, limited in content, and requiring software installs, some even requiring expensive hardware. During the Covid-19 pandemic, our team launched moleculARweb (https://molecularweb.epfl.ch), a website that offers interactive content for chemistry and structural biology education through commodity web-based AR that works on consumer devices like smartphones, tablets and laptops. Among thousands of users, teachers increasingly request more biological macromolecules to be available, a demand that we cannot satisfy individually. Therefore, to allow users to build their own material, we built a web interface where any user can build any online AR experience in few steps starting from a PDB structure or from virtual objects/scenes exported from VMD. The website also returns a WebXR session for viewing and manipulating the model in high-end immersive VR headsets with web browsers, here tested on the ~400 USD Oculus Quest 2. The tool is accessible at https://molecularweb.epfl.ch/pages/pdb2ar.html.

Precise display time measurement in JavaScript for web-based experiments

Conducting research via the internet is a formidable and ever-increasingly popular option for behavioral scientists. However, it is widely acknowledged that web-browsers are not optimized for research: In particular, the timing of display changes (e.g., a stimulus appearing on the screen), still leaves room for improvement. So far, the typically recommended best (or least worst) timing method has been a single requestAnimationFrame (RAF) JavaScript function call within which one would give the display command and obtain the time of that display change. In our Study 1, we assessed two alternatives: Calling the RAF twice consecutively, or calling the RAF during a continually ongoing independent loop of recursive RAF calls. While the former has shown little or no improvement as compared to single RAF calls, with the latter we significantly and substantially improved overall precision, and achieved practically faultless precision in most practical cases. In Study 2, we reassessed this “RAF loop” timing method with images in combination with three different display methods: We found that the precision remained high when using either visibility or opacity changes – while drawing on a canvas element consistently led to comparatively lower precision. We recommend the “RAF loop” display timing method for improved precision in future studies, and visibility or opacity changes when using image stimuli. We have also shared, in public repositories, the easy-to-use code for this method, exactly as employed in our studies.

Social aspects of Artificial Intelligence – selected issues

The paper presents findings regarding AI and Machine Learning and how “thinking machines” differ from human beings? In the next part the paper presents the issue of AI and Machine Learning’s impact on day-to-day activities in the following areas: 1. Microtargetting and psychometrics – with the examples from the business and politics; 2. Surveillance systems, biometric identification, COVID 19 tracing apps etc. – the issue of privacy in the digital era; 3. The question of choice optimization (AI-driven Web browsers and dating apps, chatbots and virtual assistants etc.); whether free will still exist in the AI supported on-line environment? The article is summed up with conclusions.

Browsers’ Private Mode: Is It What We Were Promised?

Web browsers are one of the most used applications on every computational device in our days. Hence, they play a pivotal role in any forensic investigation and help determine if nefarious or suspicious activity has occurred on that device. Our study investigates the usage of private mode and browsing artefacts within four prevalent web browsers and is focused on analyzing both hard disk and random access memory. Forensic analysis on the target device showed that using private mode matched each of the web browser vendors’ claims, such as that browsing activity, search history, cookies and temporary files that are not saved in the device’s hard disks. However, in volatile memory analysis, a majority of artefacts within the test cases were retrieved. Hence, a malicious actor performing a similar approach could potentially retrieve sensitive information left behind on the device without the user’s consent.

CorDiffViz: an R package for visualizing multi-omics differential correlation networks

Background Differential correlation networks are increasingly used to delineate changes in interactions among biomolecules. They characterize differences between omics networks under two different conditions, and can be used to delineate mechanisms of disease initiation and progression. Results We present a new R package, , that facilitates the estimation and visualization of differential correlation networks using multiple correlation measures and inference methods. The software is implemented in , and , and is available at https://github.com/sqyu/CorDiffViz. Visualization has been tested for the Chrome and Firefox web browsers. A demo is available at https://diffcornet.github.io/CorDiffViz/demo.html. Conclusions Our software offers considerable flexibility by allowing the user to interact with the visualization and choose from different estimation methods and visualizations. It also allows the user to easily toggle between correlation networks for samples under one condition and differential correlations between samples under two conditions. Moreover, the software facilitates integrative analysis of cross-correlation networks between two omics data sets.