Presence and rehabilitation: toward second-generation virtual reality applications in neuropsychology

Virtual Reality (VR) offers a blend of attractive attributes for rehabilitation. The most exploited is its ability to create a 3D simulation of reality that can be explored by patients under the supervision of a therapist. In fact, VR can be defined as an advanced communication interface based on interactive 3D visualization, able to collect and integrate different inputs and data sets in a single real-like experience. However, "treatment is not just fixing what is broken; it is nurturing what is best" (Seligman & Csikszentmihalyi). For rehabilitators, this statement supports the growing interest in the influence of positive psychological state on objective health care outcomes. This paper introduces a bio-cultural theory of presence linking the state of optimal experience defined as "flow" to a virtual reality experience. This suggests the possibility of using VR for a new breed of rehabilitative applications focused on a strategy defined as transformation of flow. In this view, VR can be used to trigger a broad empowerment process within the flow experience induced by a high sense of presence. The link between its experiential and simulative capabilities may transform VR into the ultimate rehabilitative device. Nevertheless, further research is required to explore more in depth the link between cognitive processes, motor activities, presence and flow

The snail lemma for internal groupoids

We establish a generalized form both of the Gabriel-Zisman exact sequence associated with a pointed functor between pointed groupoids, and of the Brown exact sequence associated with a fibration of pointed groupoids. Our generalization consists in replacing pointed groupoids with groupoids internal to a pointed regular category with reflexive coequalizer

Being There: Understanding the Feeling of Presence in a Synthetic Environment and its Potential for Clinical Change

Anatom

A push forward construction and the comprehensive factorization for internal crossed modules

In a semi-abelian category, we give a categorical construction of the push forward of an internal pre-crossed module, generalizing the pushout of a short exact sequence in abelian categories. The main properties of the push forward are discussed. A simplified version is given for action accessible categories, providing examples in the categories of rings and Lie algebras. We show that push forwards can be used to obtain the crossed module version of the comprehensive factorization for internal groupoids

α-aldehyde terminally functional methacrylic polymers from living radical polymerization : application in protein conjugation “pegylation”

Application of proteins and peptides as human therapeutics is expanding rapidly as drug discovery becomes more prevalent. Conjugation of polymers to proteins can circumvent many problems and pegylation of proteins is now emerging as acceptable practice. This paper describes the synthesis of α-aldehyde-terminated poly(methoxyPEG)methacrylates from Cu(I) mediated living radical polymerization (Mn = 11 000, 22 000 and 32 000; PDi < 1.15), and their efficient conjugation to lysozyme, as a model protein. This offers an attractive and flexible alternative to linear poly(ethylene glycol) opening up the possibility of using the full power of living radical polymerization

OpenML Benchmarking Suites

Machine learning research depends on objectively interpretable, comparable, and reproducible algorithm benchmarks. Therefore, we advocate the use of curated, comprehensive suites of machine learning tasks to standardize the setup, execution, and reporting of benchmarks. We enable this through software tools that help to create and leverage these benchmarking suites. These are seamlessly integrated into the OpenML platform, and accessible through interfaces in Python, Java, and R. OpenML benchmarking suites are (a) easy to use through standardized data formats, APIs, and client libraries; (b) machine-readable, with extensive meta-information on the included datasets; and (c) allow benchmarks to be shared and reused in future studies. We also present a first, carefully curated and practical benchmarking suite for classification: the OpenML Curated Classification benchmarking suite 2018 (OpenML-CC18)