Tips for Linking Shell Companies to their Secret Owners
Plus, more links to make you a little bit smarter today.
I Learned An Ancient 3-Step Process And Became A Master Meditator
If you’ve tried meditating before, you probably struggled because of the vague information on it online. I hate a lot of the meditation resources online (just sit until you feel like you’re nothing? What??) and I don’t think apps like Calm or Headspace really do a good job of giving you the exact reasons why mediation is so beneficial and honestly kind of cool.
The potential of DAOs for funding and collaborative development in the life sciences
VitaDAO funds longevity research through a blockchain-based decentralized autonomous organization (DAO), showcasing the potential of collaborative, transparent and alternative systems while also highlighting the challenges of coordination, regulation, biases and skepticism in reshaping traditional research financing methods.
Detection of Temporality at Discourse Level on Financial News by Combining Natural Language Processing and Machine Learning
Finance-related news such as Bloomberg News, CNN Business and Forbes are valuable sources of real data for market screening systems. In news, an expert shares opinions beyond plain technical analyses that include context such as political, sociological and cultural factors. In the same text, the expert often discusses the performance of different assets. Some key statements are mere descriptions of past events while others are predictions. Therefore, understanding the temporality of the key statements in a text is essential to separate context information from valuable predictions. We propose a novel system to detect the temporality of finance-related news at discourse level that combines Natural Language Processing and Machine Learning techniques, and exploits sophisticated features such as syntactic and semantic dependencies. More specifically, we seek to extract the dominant tenses of the main statements, which may be either explicit or implicit. We have tested our system on a labelled dataset of finance-related news annotated by researchers with knowledge in the field. Experimental results reveal a high detection precision compared to an alternative rulebased baseline approach. Ultimately, this research contributes to the state-of-the-art of market screening by identifying predictive knowledge for financial decision making.
How Nintendo did the impossible with Tears of the Kingdom's physics system
Tears of the Kingdom technical director Takuhiro Dohta and lead physics programmer Takahiro Takayama share secrets from developing the game's amazingly complex physics system.
Karma: An Experimental Study
A system of non-tradable credits that flow between individuals like karma, hence proposed under that name, is a mechanism for repeated resource allocation that comes with attractive efficiency and fairness properties, in theory. In this study, we test karma in an online experiment in which human subjects repeatedly compete for a resource with time-varying and stochastic individual preferences or urgency to acquire the resource. We confirm that karma has significant and sustained welfare benefits even in a population with no prior training. We identify mechanism usage in contexts with sporadic high urgency, more so than with frequent moderate urgency, and implemented as an easy (binary) karma bidding scheme as particularly effective for welfare improvements: relatively larger aggregate efficiency gains are realized that are (almost) Pareto superior. These findings provide guidance for further testing and for future implementation plans of such mechanisms in the real world.
Tips for Linking Shell Companies to their Secret Owners
For investigative journalists, the search for the actual owners of shell companies and trusts can sometimes seem as elusive and “fuzzy” as popular searches for UFOs. But there are powerful tools out there that can help newcomers to this complex field track breadcrumbs to people who go to great lengths to hide assets that the public should know about.