A Non-invasive Method for Biological Age Estimation Using Frailty Phenotype Assessment

The human body has two different ages: a Chronological Age (CA), the actual time a person has been alive, and a Biological Age (BA), the real age that indicate the decline in health and in function ability during aging. Among previous studies, some authors proposed methodologies to estimate the Biological Age starting from non-invasive frailty measurements to evaluate the Frailty Index, others proposed invasive and expensive methods to measure the biological aging. Conversely, in this paper we propose a method to estimate the BA of a subject based on the assessment of the Frailty Phenotype. This type of evolution allows an efficient estimation of the frailty in contrast with the Frailty Index which is composed by a long checklist of clinical conditions and diseases to be evaluated from medical staff. We developed a cloud application, able to store and elaborate the data acquired during the evaluation protocol of the Frailty Phenotype, and also able to automatically provide the state of phenotypic fragility, and finally the Biological Age of a subject

Efficient Evaluation and Learning in Multilevel Parallel Constraint Grammars

In multilevel parallel Optimality Theory grammars, the number of candidates (possible paths from the input to the output level) increases exponentially with the number of levels of representation. The problem with this is that with the customary strategy of listing all candidates in a tableau, the computation time for evaluation (i.e., choosing the winning candidate) and learning (i.e., reranking the constraints on the basis of language data) increases exponentially with the number of levels as well. This article proposes instead to collect the candidates in a graph in which the number of nodes and the number of connections increase only linearly with the number of levels of representation. As a result, there exist procedures for evaluation and learning that increase only linearly with the number of levels. These efficient procedures help to make multilevel parallel constraint grammars more feasible as models of human language processing. We illustrate visualization, evaluation, and learning with a toy grammar for a traditional case that has already previously been analyzed in terms of parallel evaluation, namely, French liaison