Constructive Conversation Analysis in psychotherapy: cognitive relevance of actants in terms of linguistic constructions

Pychotherapists produce pseudo-structured discourse with their clients that can be analysed with linguistics and pragmatics. Conversation Analysis is often qualitative, non-sistematic. The Therapeutic Cycles Model (TCM) uses ad-hoc software to perform textual analysis of psychoterapeutic transcripts, in order to elicit significant elements in the therapeutic interaction, but it does not consider linguistic constructions as units of analysis. Constructive Adpositional Grammars (CxAdGrams) are the ground for the Conversation Analysis so to fill the gap left by the TCM

Bioinspired Networks of Communicating Synthetic Protocells

The bottom-up synthesis of cell-like entities or protocells from inanimate molecules and materials is one of the grand challenges of our time. In the past decade, researchers in the emerging field of bottom-up synthetic biology have developed different protocell models and engineered them to mimic one or more abilities of biological cells, such as information transcription and translation, adhesion, and enzyme-mediated metabolism. Whilst thus far efforts have focused on increasing the biochemical complexity of individual protocells, an emerging challenge in bottom-up synthetic biology is the development of networks of communicating synthetic protocells. The possibility of engineering multi-protocellular systems capable of sending and receiving chemical signals to trigger individual or collective programmed cell-like behaviours or for communicating with living cells and tissues would lead to major scientific breakthroughs with important applications in biotechnology, tissue engineering and regenerative medicine. This mini-review will discuss this new, emerging area of bottom-up synthetic biology and will introduce three types of bioinspired networks of communicating synthetic protocells that have recently emerged

Principal Component Analysis Applied to Surface Electromyography: A Comprehensive Review

© 2016 IEEE. Surface electromyography (sEMG) records muscle activities from the surface of muscles, which offers a wealth of information concerning muscle activation patterns in both research and clinical settings. A key principle underlying sEMG analyses is the decomposition of the signal into a number of motor unit action potentials (MUAPs) that capture most of the relevant features embedded in a low-dimensional space. Toward this, the principal component analysis (PCA) has extensively been sought after, whereby the original sEMG data are translated into low-dimensional MUAP components with a reduced level of redundancy. The objective of this paper is to disseminate the role of PCA in conjunction with the quantitative sEMG analyses. Following the preliminaries on the sEMG methodology and a statement of PCA algorithm, an exhaustive collection of PCA applications related to sEMG data is in order. Alongside the technical challenges associated with the PCA-based sEMG processing, the envisaged research trend is also discussed

Machine Learning Nucleation Collective Variables with Graph Neural Networks

The efficient calculation of nucleation collective variables (CVs) is one of the main limitations to the application of enhanced sampling methods to the investigation of nucleation processes in realistic environments. Here we discuss the development of a graph-based model for the approximation of nucleation CVs that enables orders-of-magnitude gains in computational efficiency in the on-the-fly evaluation of nucleation CVs. By performing simulations on a nucleating colloidal system mimicking a multistep nucleation process from solution, we assess the model's efficiency in both postprocessing and on-the-fly biasing of nucleation trajectories with pulling, umbrella sampling, and metadynamics simulations. Moreover, we probe and discuss the transferability of graph-based models of nucleation CVs across systems using the model of a CV based on sixth-order Steinhardt parameters trained on a colloidal system to drive the nucleation of crystalline copper from its melt. Our approach is general and potentially transferable to more complex systems as well as to different CVs

The COMPASS Event Store in 2002

COMPASS, the fixed-target experiment at CERN studying the structure of the nucleon and spectroscopy, collected over 260 TB during summer 2002 run. All these data, together with reconstructed events information, were put from the beginning in a database infrastructure based on Objectivity/DB and on the hierarchical storage manager CASTOR. The experience in the usage of the database is reviewed and the evolution of the system outlined.Comment: Talk from the 2003 conference: "Computing in High Energy and Nuclear Physics" (CHEP03), La Jolla, Ca, USA, March 2003, 6 pages. PSN MOKT01

Effectiveness of 3D-printed orthoses for traumatic and chronic hand conditions: A scoping review

Background In the field of orthotics, the use of three-dimensional (3D) technology as an alternative to the conventional production process of orthoses is growing. Purpose This scoping review aimed to systematically map and summarize studies assessing the effectiveness of 3D-printed orthoses for traumatic and chronic hand conditions, and to identify knowledge gaps. Methods The Cochrane Library, PubMed, EMBASE, CINAHL, Web of Science, IEEE, and PEDro were searched for studies of any type of 3D-printed orthoses for traumatic and chronic hand conditions. Any outcome related to the effectiveness of 3D-printed orthoses was considered. Two reviewers selected eligible studies, charted data on study characteristics by impairment type, and critically appraised the studies, except for case reports/series. Results Seventeen studies were included: Four randomized controlled trials, four uncontrolled trials, four case series and five case reports. Only three studies had a sample size >20. Impairments described were forearm fractures (n = 5), spasticity (n = 5), muscle weakness (n = 4), joint contractures (n = 2) and pain (n = 1). Four poor to fair quality studies on forearm fractures supported the effectiveness of 3D-printed orthoses on hand function, functionality, and satisfaction. One good quality study on spasticity demonstrated the effectiveness of 3D-printed orthoses on hand function. One poor quality pain study reported limited positive effects on satisfaction. Studies on muscle weakness and joint contractures showed no benefits. Conclusion Current literature addressing the effectiveness of 3D-printed orthoses for traumatic and chronic hand conditions consists primarily of small and poor methodological quality studies. There is a need for well-designed controlled trials including patient-related outcomes, production time and cost analyses