>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
https://phys.org/news/2021-07-tiny-sensors-brain-surgery-implants.html
phys.org
Tiny, injectable sensors could monitor brain activity without surgery or implants
Researchers have developed nanoscale sensors that could be injected into the body to noninvasively track brain activity using light. The approach could one day offer a new way to study the brain or assess ...
https://www.youtube.com/watch?v=60z_hpEAtD8
Old, but gold
Old, but gold
YouTube
A Swift Introduction to Geometric Algebra
This video is an introduction to geometric algebra, a severely underrated mathematical language that can be used to describe almost all of physics. This video was made as a presentation for my lab that I work in. While I had the people there foremost in…
Therapist: МЕССАДЖТАБЛЕ doesn't exist, it can't hurt you
МЕССАДЖТАБЛЕ:
МЕССАДЖТАБЛЕ:
Docs
Ресурс МЕССАЖЕТАБЛЕ - Win32 apps
Определяет идентификатор и файл ресурса таблицы сообщений приложения. Таблицы сообщений — это специальные строковые ресурсы, используемые при ведении журнала событий и с функцией FormatMessage. Файл содержит двоичную таблицу сообщений, созданную компилятором…
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
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
Nature
Network analysis of multivariate data in psychological science
Nature Reviews Methods Primers - Network analysis allows the investigation of complex patterns and relationships by examining nodes and the edges connecting them. Borsboom et al. discuss the...
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
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