A systematic investigation of sensorimotor mechanisms with intelligent prostheses in patients with ankle amputation while walking.

It is thought that creating sensorimotor feedback in people with ankle joint amputation can affect motor biomechanics during gait, but there is little evidence or previous research. This study e aim ed to investigate the sensorimotor mechanism of smart prostheses in with ankle amputations while walking. Search in Google Scholar, Scopus, PubMed and Medline databases between April 2017 and February 2023, in addition to a detailed review in specialized clinical and engineering databases, 29 articles were selected based on the inclusion and exclusion criteria. Trials that mainly include; Proprioception, walking process in movement disorders, ankle amputation were included. Qualitative assessments of selected trials using PEDro' scale was used. The review of studies showed that the use of pressure sensors, neural stimulation through encoded algorithms can provide continuous tactile and positional information of the artificial leg in the direction of neural stimulation throughout the entire walking cycle. These findings indicate that restoration of intraneuronal sensory feedback leads to functional and cognitive benefits. With these definitions, different companies and research centers are trying to improve the mechanics of walking, however, movement strategies are unknown despite little research in creating sense and movement in the use of smart prostheses.

An automated pipeline for the discovery of conspiracy and conspiracy theory narrative frameworks: Bridgegate, Pizzagate and storytelling on the web.

Although a great deal of attention has been paid to how conspiracy theories circulate on social media, and the deleterious effect that they, and their factual counterpart conspiracies, have on political institutions, there has been little computational work done on describing their narrative structures. Predicating our work on narrative theory, we present an automated pipeline for the discovery and description of the generative narrative frameworks of conspiracy theories that circulate on social media, and actual conspiracies reported in the news media. We base this work on two separate comprehensive repositories of blog posts and news articles describing the well-known conspiracy theory Pizzagate from 2016, and the New Jersey political conspiracy Bridgegate from 2013. Inspired by the qualitative narrative theory of Greimas, we formulate a graphical generative machine learning model where nodes represent actors/actants, and multi-edges and self-loops among nodes capture context-specific relationships. Posts and news items are viewed as samples of subgraphs of the hidden narrative framework network. The problem of reconstructing the underlying narrative structure is then posed as a latent model estimation problem. To derive the narrative frameworks in our target corpora, we automatically extract and aggregate the actants (people, places, objects) and their relationships from the posts and articles. We capture context specific actants and interactant relationships by developing a system of supernodes and subnodes. We use these to construct an actant-relationship network, which constitutes the underlying generative narrative framework for each of the corpora. We show how the Pizzagate framework relies on the conspiracy theorists' interpretation of "hidden knowledge" to link otherwise unlinked domains of human interaction, and hypothesize that this multi-domain focus is an important feature of conspiracy theories. We contrast this to the single domain focus of an actual conspiracy. While Pizzagate relies on the alignment of multiple domains, Bridgegate remains firmly rooted in the single domain of New Jersey politics. We hypothesize that the narrative framework of a conspiracy theory might stabilize quickly in contrast to the narrative framework of an actual conspiracy, which might develop more slowly as revelations come to light. By highlighting the structural differences between the two narrative frameworks, our approach could be used by private and public analysts to help distinguish between conspiracy theories and conspiracies.