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Walrasian equilibrium behavior in nature

Abstract:

The interaction between land plants and mycorrhizal fungi (MF) forms perhaps the world’s most prevalent biological market. Most plants participate in such markets, in which MF collect nutrients from the soil and trade them with host plants in exchange for carbon. In a recent study, M. D. Whiteside et al. [Curr. Biol. 29, 2043–2050.e8 (2019)] conducted experiments that allowed them to quantify the behavior of arbuscular MF when trading phosphorus with their host roots. Their experimental techniques enabled the researchers to infer the quantities traded under multiple scenarios involving different amounts of phosphorus resources initially held by different MF patches. We use these observations to confirm a revealed preference hypothesis, which characterizes behavior in Walrasian equilibrium, a centerpiece of general economic equilibrium theory.

https://www.pnas.org/content/118/27/e2020961118

tl;dr - fungi embrace fundamental economic theory as they engage in trading
#abstract
A topological solution to object segmentation and tracking

Abstract:

The world is composed of objects, the ground, and the sky. Visual perception of objects requires solving two fundamental challenges: segmenting visual input into discrete units, and tracking identities of these units despite appearance changes due to object deformation, changing perspective, and dynamic occlusion. Current computer vision approaches to segmentation and tracking that approach human performance all require learning, raising the question: can objects be segmented and tracked without learning? Here, we show that the mathematical structure of light rays reflected from environment surfaces yields a natural representation of persistent surfaces, and this surface representation provides a solution to both the segmentation and tracking problems. We describe how to generate this surface representation from continuous visual input, and demonstrate that our approach can segment and invariantly track objects in cluttered synthetic video despite severe appearance changes, without requiring learning.

https://arxiv.org/abs/2107.02036
In 1984 a researcher named Bloom found that students learning mastery-based and with one-on-one mentorship perform two standard deviations better than those in a conventional classroom.

Incredible to know, but too expensive to do anything about, so nothing changed.

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>Once in the brain, the nanosensors are highly sensitive to local changes in the electric field. In laboratory tests, in vitro prototypes of the NeuroSWARM3 were able to generate a signal-to-noise ratio of over 1,000, a sensitivity level that is suitable for detecting the electrical signal generated when a single neuron fires.

https://phys.org/news/2021-07-tiny-sensors-brain-surgery-implants.html
tl;dr:
OTRv4 > OpenPGP > OMEMO
Network analysis of multivariate data in psychological science

Abstract:

In recent years, network analysis has been applied to identify and analyse patterns of statistical association in multivariate psychological data. In these approaches, network nodes represent variables in a data set, and edges represent pairwise conditional associations between variables in the data, while conditioning on the remaining variables. This Primer provides an anatomy of these techniques, describes the current state of the art and discusses open problems. We identify relevant data structures in which network analysis may be applied: cross-sectional data, repeated measures and intensive longitudinal data. We then discuss the estimation of network structures in each of these cases, as well as assessment techniques to evaluate network robustness and replicability. Successful applications of the technique in different research areas are highlighted. Finally, we discuss limitations and challenges for future research.

https://www.nature.com/articles/s43586-021-00055-w

tl;dr - big 5 questionnaire, but with graph analysis
Physics, Topology, Logic and Computation:
A Rosetta Stone


Abstract:

In physics, Feynman diagrams are used to reason about quantum processes. In the 1980s, it became clear that underlying these diagrams is a powerful analogy between quantum physics and topology: namely, a linear operator behaves very much like a "cobordism". Similar diagrams can be used to reason about logic, where they represent proofs, and computation, where they represent programs. With the rise of interest in quantum cryptography and quantum computation, it became clear that there is extensive network of analogies between physics, topology, logic and computation. In this expository paper, we make some of these analogies precise using the concept of "closed symmetric monoidal category". We assume no prior knowledge of category theory, proof theory or computer science.

https://arxiv.org/pdf/0903.0340.pdf