48 research outputs found
Statistical Signatures of Structural Organization: The case of long memory in renewal processes
Identifying and quantifying memory are often critical steps in developing a
mechanistic understanding of stochastic processes. These are particularly
challenging and necessary when exploring processes that exhibit long-range
correlations. The most common signatures employed rely on second-order temporal
statistics and lead, for example, to identifying long memory in processes with
power-law autocorrelation function and Hurst exponent greater than .
However, most stochastic processes hide their memory in higher-order temporal
correlations. Information measures---specifically, divergences in the mutual
information between a process' past and future (excess entropy) and minimal
predictive memory stored in a process' causal states (statistical
complexity)---provide a different way to identify long memory in processes with
higher-order temporal correlations. However, there are no ergodic stationary
processes with infinite excess entropy for which information measures have been
compared to autocorrelation functions and Hurst exponents. Here, we show that
fractal renewal processes---those with interevent distribution tails ---exhibit long memory via a phase transition at .
Excess entropy diverges only there and statistical complexity diverges there
and for all . When these processes do have power-law
autocorrelation function and Hurst exponent greater than , they do not
have divergent excess entropy. This analysis breaks the intuitive association
between these different quantifications of memory. We hope that the methods
used here, based on causal states, provide some guide as to how to construct
and analyze other long memory processes.Comment: 13 pages, 2 figures, 3 appendixes;
http://csc.ucdavis.edu/~cmg/compmech/pubs/lrmrp.ht
Social recovery therapy: a treatment manual
Social Recovery Therapy is an individual psychosocial therapy developed for people with psychosis. The therapy aims to improve social recovery through increasing the amount of time individuals spend in meaningful structured activity. Social Recovery Therapy draws on our model of social disability arising as functional patterns of withdrawal in response to early socio-emotional difficulties and compounded by low hopefulness, self-agency and motivation. The core components of Social Recovery Therapy include using an assertive outreach approach to promote a positive therapeutic relationship, with the focus of the intervention on using active behavioural work conducted outside the clinical room and promoting hope, values, meaning, and positive schema. The therapy draws on traditional Cognitive Behavioural Therapy techniques but differs with respect to the increased use of behavioural and multi-systemic work, the focus on the development of hopefulness and positive self, and the inclusion of elements of case management and supported employment. Our treatment trials provide evidence for the therapy leading to clinically meaningful increases in structured activity for individuals experiencing first episode and longer-term psychosis. In this paper, we present the core intervention components with examples in order to facilitate evaluation and implementation of the approach
Probabilistic Daily ILI Syndromic Surveillance with a Spatio-Temporal Bayesian Hierarchical Model
BACKGROUND: For daily syndromic surveillance to be effective, an efficient and sensible algorithm would be expected to detect aberrations in influenza illness, and alert public health workers prior to any impending epidemic. This detection or alert surely contains uncertainty, and thus should be evaluated with a proper probabilistic measure. However, traditional monitoring mechanisms simply provide a binary alert, failing to adequately address this uncertainty. METHODS AND FINDINGS: Based on the Bayesian posterior probability of influenza-like illness (ILI) visits, the intensity of outbreak can be directly assessed. The numbers of daily emergency room ILI visits at five community hospitals in Taipei City during 2006-2007 were collected and fitted with a Bayesian hierarchical model containing meteorological factors such as temperature and vapor pressure, spatial interaction with conditional autoregressive structure, weekend and holiday effects, seasonality factors, and previous ILI visits. The proposed algorithm recommends an alert for action if the posterior probability is larger than 70%. External data from January to February of 2008 were retained for validation. The decision rule detects successfully the peak in the validation period. When comparing the posterior probability evaluation with the modified Cusum method, results show that the proposed method is able to detect the signals 1-2 days prior to the rise of ILI visits. CONCLUSIONS: This Bayesian hierarchical model not only constitutes a dynamic surveillance system but also constructs a stochastic evaluation of the need to call for alert. The monitoring mechanism provides earlier detection as well as a complementary tool for current surveillance programs
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Safety and Tolerability of SRX246, a Vasopressin 1a Antagonist, in Irritable Huntington\u27s Disease Patients-A Randomized Phase 2 Clinical Trial.
SRX246 is a vasopressin (AVP) 1a receptor antagonist that crosses the blood-brain barrier. It reduced impulsive aggression, fear, depression and anxiety in animal models, blocked the actions of intranasal AVP on aggression/fear circuits in an experimental medicine fMRI study and demonstrated excellent safety in Phase 1 multiple-ascending dose clinical trials. The present study was a 3-arm, multicenter, randomized, placebo-controlled, double-blind, 12-week, dose escalation study of SRX246 in early symptomatic Huntington\u27s disease (HD) patients with irritability. Our goal was to determine whether SRX246 was safe and well tolerated in these HD patients given its potential use for the treatment of problematic neuropsychiatric symptoms. Participants were randomized to receive placebo or to escalate to 120 mg twice daily or 160 mg twice daily doses of SRX246. Assessments included standard safety tests, the Unified Huntington\u27s Disease Rating Scale (UHDRS), and exploratory measures of problem behaviors. The groups had comparable demographics, features of HD and baseline irritability. Eighty-two out of 106 subjects randomized completed the trial on their assigned dose of drug. One-sided exact-method confidence interval tests were used to reject the null hypothesis of inferior tolerability or safety for each dose group vs. placebo. Apathy and suicidality were not affected by SRX246. Most adverse events in the active arms were considered unlikely to be related to SRX246. The compound was safe and well tolerated in HD patients and can be moved forward as a candidate to treat irritability and aggression
Paracompactness And Full Normality In Ditopological Texture Spaces
In this paper the authors lay the foundation for a theory of dicovers of ditopological texture spaces and use this to define notions of paracompactness and full normality. Some applications to fuzzy topology are also mentioned. (C) 1998 Academic Press.WoSScopu