The Early Psychosis Screener (EPS): Quantitative validation against the SIPS using machine learning

Machine learning techniques were used to identify highly informative early psychosis self-report items and to validate an early psychosis screener (EPS) against the Structured Interview for Psychosis-risk Syndromes (SIPS). The Prodromal Questionnaire–Brief Version (PQ-B) and 148 additional items were administered to 229 individuals being screened with the SIPS at 7 North American Prodrome Longitudinal Study sites and at Columbia University. Fifty individuals were found to have SIPS scores of 0, 1, or 2, making them clinically low risk (CLR) controls; 144 were classified as clinically high risk (CHR) (SIPS 3–5) and 35 were found to have first episode psychosis (FEP) (SIPS 6). Spectral clustering analysis, performed on 124 of the items, yielded two cohesive item groups, the first mostly related to psychosis and mania, the second mostly related to depression, anxiety, and social and general work/school functioning. Items within each group were sorted according to their usefulness in distinguishing between CLR and CHR individuals using the Minimum Redundancy Maximum Relevance procedure. A receiver operating characteristic area under the curve (AUC) analysis indicated that maximal differentiation of CLR and CHR participants was achieved with a 26-item solution (AUC = 0.899 ± 0.001). The EPS-26 outperformed the PQ-B (AUC = 0.834 ± 0.001). For screening purposes, the self-report EPS-26 appeared to differentiate individuals who are either CLR or CHR approximately as well as the clinician-administered SIPS. The EPS-26 may prove useful as a self-report screener and may lead to a decrease in the duration of untreated psychosis. A validation of the EPS-26 against actual conversion is underway

On the Communication Complexity of Distributed Name-Independent Routing Schemes

We present a distributed asynchronous algorithm that, for every undirected weighted n-node graph G, constructs name-independent routing tables for G. The size of each table is Õ(√n), whereas the length of any route is stretched by a factor of at most 7 w.r.t. the shortest path. At any step, the memory space of each node is Õ(√n). The algorithm terminates in time O(D), where D is the hop-diameter of G. In synchronous scenarios and with uniform weights, it consumes Õ(m √ n + n 3/2 min {D, √ n}) messages, where m is the number of edges of G. In the realistic case of sparse networks of poly-logarithmic diameter, the communication complexity of our scheme, that is Õ(n3/2), improves by a factor of √ n the communication complexity of any shortest-path routing scheme on the same family of networks. This factor is provable thanks to a new lower bound of independent interest

Llibre blanc de les xarxes socials de la Universitat de Barcelona [2012]

Enabling the interoperability between applications requires agreement in the format and meaning (syntax and semantics) of exchanged data including the ordering of message exchanges. However, today’s researchers argue that these are not enough to achieve a complete, effective and meaningful collaboration – the use of data (pragmatics) is important as well. Pragmatic interoperability requires mutual understanding in the use of data between collaborating systems. However, we observe that the notion of pragmatic interoperability is still largely unsettled, as evidenced by the various proposed definitions and the lack of a canonical understanding. Therefore, our objective is to contribute to a more thorough understanding of this concept through a systematic review of published definitions. Our results show that, indeed, various interpretations of pragmatic interoperability exist. Categorizing the derivable concepts from these definitions, we see two broad groups: system level and business level. Within each of these individual levels, we see some degree of agreement among the definitions. However, comparing the definitions across these levels, we observe no general agreement. At the system level, pragmatic interoperability essentially means sharing the same understanding of the intended and actual use of exchanged system message in a given context. At the business level, pragmatic interoperability goes beyond service use by considering also the compatibility of business intentions, business rules, organizational policies, and the establishment and maintenance of trust and reputation mechanisms between collaborating business parties