Controlling dispersed state and exfoliation process of clay in polymer matrix

In the present review, the authors do not try to provide a comprehensive review of researches on polymer/clay nanocomposites (PCNs), but some examples to demonstrate different exfoliation processes of the clay in various polymer matrixes and the dispersed state of clay. Interaction between polymers and layered silicates plays an important role in adjusting the exfoliation process of layered silicates and the microstructure of polymer nanocomposites. Properties of polymer/layered silicate nanocomposites mainly depend on the dispersed state of layered silicates. The authors will also address the outline of the present research in the direction of PCNs including the discussion of technical problems and their possible solutions.

The nonlinear effective dielectric response of graded composites

The perturbation method is developed to deal with the effective nonlinear dielectric responses of weakly nonlinear graded composites, which consist of the graded inclusion with a linear dielectric function of spatial variables of inclusion material. For Kerr-like nonlinear graded composites, as an example in two dimensions, we have used the perturbation method to solve the boundary value problems of potentials, and studied the effective responses of nonlinear graded composites, where a cylindrical inclusion with linear dielectric function and nonlinear dielectric constant is randomly embedded in a homogeneous host with linear and nonlinear dielectric constants. For the exponential function and the power-law dielectric profiles of cylindrical inclusions, in the dilute limit, we have derived the formulae of effective nonlinear responses of both graded nonlinear composites.

顿悟中的蔡格尼克效应：左右脑在解题失败与提示信息加工时的活动差异

Zeigarnik effect refers to the enhanced memory performance for unfinished tasks and studies on insight using hemi-visual field presentation technology also find that after failing to solve an problem, hints to the problem are more effective received and lead to insight experience when presented to the left-visual field (Right hemisphere) than presented to the right-visual field, especial when the hints appeared with a delay. Thus, it seems that right hemisphere may play an important role in preserving information of unsolved problems and processing related cues. To further examine the finding above, we introduce an Chinese character chunking task to investigate the brain activities during the stage of failure to resolve problems and of hint presentation using Event-Related Potentials (ERP) and functional MRI technology. Our FMRI results found that bilateral BA10 showed more activation when seeing hints for unsolved problems and we proposed that it may reflect the processes of information to failure problems, howerver, there was no hemispheric difference. The ERP results after the effort to the problems showed that unsolved problems elicited a more positive P150 over the right frontal cortex while solved problems demonstrated a left hemispheric advantage of P150. When hints present, P2 amplitudes of hints were modulated by the status of problem only in the right hemisphere but not in the left hemisphere. Our results confirmed the hypothesis that failure to solve problems would trigger the perseverance processes in right hemisphere, which would make right hemisphere more sensitive to related information of failure problems.

Probabilistic Solution of Inverse Problems

In this thesis we study the general problem of reconstructing a function, defined on a finite lattice from a set of incomplete, noisy and/or ambiguous observations. The goal of this work is to demonstrate the generality and practical value of a probabilistic (in particular, Bayesian) approach to this problem, particularly in the context of Computer Vision. In this approach, the prior knowledge about the solution is expressed in the form of a Gibbsian probability distribution on the space of all possible functions, so that the reconstruction task is formulated as an estimation problem. Our main contributions are the following: (1) We introduce the use of specific error criteria for the design of the optimal Bayesian estimators for several classes of problems, and propose a general (Monte Carlo) procedure for approximating them. This new approach leads to a substantial improvement over the existing schemes, both regarding the quality of the results (particularly for low signal to noise ratios) and the computational efficiency. (2) We apply the Bayesian appraoch to the solution of several problems, some of which are formulated and solved in these terms for the first time. Specifically, these applications are: teh reconstruction of piecewise constant surfaces from sparse and noisy observationsl; the reconstruction of depth from stereoscopic pairs of images and the formation of perceptual clusters. (3) For each one of these applications, we develop fast, deterministic algorithms that approximate the optimal estimators, and illustrate their performance on both synthetic and real data. (4) We propose a new method, based on the analysis of the residual process, for estimating the parameters of the probabilistic models directly from the noisy observations. This scheme leads to an algorithm, which has no free parameters, for the restoration of piecewise uniform images. (5) We analyze the implementation of the algorithms that we develop in non-conventional hardware, such as massively parallel digital machines, and analog and hybrid networks.

Hypothesis Formation and Evaluation in Medical Diagnosis

This thesis describes some aspects of a computer system for doing medical diagnosis in the specialized field of kidney disease. Because such a system faces the spectre of combinatorial explosion, this discussion concentrates on heuristics which control the number of concurrent hypotheses and efficient "compiled" representations of medical knowledge. In particular, the differential diagnosis of hematuria (blood in the urine) is discussed in detail. A protocol of a simulated doctor/patient interaction is presented and analyzed to determine the crucial structures and processes involved in the diagnosis procedure. The data structure proposed for representing medical information revolves around elementary hypotheses which are activated when certain disposing of findings, activating hypotheses, evaluating hypotheses locally and combining hypotheses globally is examined for its heuristic implications. The thesis attempts to fit the problem of medical diagnosis into the framework of other Artifcial Intelligence problems and paradigms and in particular explores the notions of pure search vs. heuristic methods, linearity and interaction, local vs. global knowledge and the structure of hypotheses within the world of kidney disease.

Tolerance-based and Fuzzy-Rough Feature Selection.

R. Jensen and Q. Shen, 'Tolerance-based and Fuzzy-Rough Feature Selection,' Proceedings of the 16th International Conference on Fuzzy Systems (FUZZ-IEEE'07), pp. 877-882, 2007.

Rings around the World: Notes on the Challenges, Problems & Possibilities of International Audience Projects

Egan, K., Barker, M. (2006). Rings around the World: Notes on the Challenges, Problems & Possibilities of International Audience Projects. Participations: Journal of Audience & Reception Studies, 3 (2). Sponsorship: This research was made possible by a grant from the Economic and Social Research Council (ESRC Grant No. 000-22-0323)

Adaptive capacity and learning to learn as leverage for social-ecological resilience

Ioan Fazey, John A. Fazey, Joern Fischer, Kate Sherren, John Warren, Reed F. Noss, Stephen R. Dovers (2007) Adaptive capacity and learning to learn as leverage for social?ecological resilience. Frontiers in Ecology and the Environment 5(7),375-380. RAE2008

Issues in the prescribing of psychotropic and psychoactive medication for persons with learning disability: quantitative and qualitative perspectives

The administration of psychotropic and psychoactive medication for persons with learning disability and accompanying mental illness and/or challenging behaviour has undergone much critical review over the past two decades. Assessment and diagnosis of mental illness in this population continues to be psychopharmacological treatment include polypharmacy, irrational prescription procedures and frequent over-prescription. It is clear that all forms of treatment including non-pharmacological interventions need to be driven by accurate and appropriate diagnoses. Where a psychiatric diagnosis has been identified, it greatly aides the selection of appropriate medication, although a specific medication for each diagnosis, as was once hoped, is simply no longer a reality in practice. Part one of the present thesis seeks to address many of the current issues in mental health problems and pharmacological treatment to date. The author undertook a drug prevalence study within both residential and community facilities for persons with learning disability within the Mid-West region of Ireland in order to ascertain the current level of prescribing of psychotropic and psychoactive medications for this population. While many attempts have been made to account for the variation in prescribing, little systematic and empirical research has been undertaken to investigate the factors thought to influence such prescribing. While studies investigating the prescribing behaviours of General Practitioners (GP's) have illustrated the complex nature of the decision making process in the context of general practice, no similar efforts have yet been directed at examining the prescribing behaviours of Consultant Psychiatrists. Using The Critical Incident Technique, the author interviewed Consultant Psychiatrists in the Republic of Ireland to gather information relating not only to their patterns of prescribing for learning disabled populations, but also to examine reasons influencing their prescribing in addition to several related factors. Part two of this thesis presents the findings from this study and a number of issues are raised, not only in relation to attempting to account for the findings from part one of the thesis, but also with respect to implications for improved management and clinical practice.

Reasoning with sorted-pareto dominance and other qualitative and partially ordered preferences in soft constraints

In decision making problems where we need to choose a particular decision or alternative from a set of possible choices, we often have some preferences which determine if we prefer one decision over another. When these preferences give us an ordering on the decisions that is complete, then it is easy to choose the best or one of the best decisions. However it often occurs that the preferences relation is partially ordered, and we have no best decision. In this thesis, we look at what happens when we have such a partial order over a set of decisions, in particular when we have multiple orderings on a set of decisions, and we present a framework for qualitative decision making. We look at the different natural notions of optimal decision that occur in this framework, which gives us different optimality classes, and we examine the relationships between these classes. We then look in particular at a qualitative preference relation called Sorted-Pareto Dominance, which is an extension of Pareto Dominance, and we give a semantics for this relation as one that is compatible with any order-preserving mapping of an ordinal preference scale to a numerical one. We apply Sorted-Pareto dominance to a Soft Constraints setting, where we solve problems in which the soft constraints associate qualitative preferences to decisions in a decision problem. We also examine the Sorted-Pareto dominance relation in the context of our qualitative decision making framework, looking at the relevant optimality classes for the Sorted-Pareto case, which gives us classes of decisions that are necessarily optimal, and optimal for some choice of mapping of an ordinal scale to a quantitative one. We provide some empirical analysis of Sorted-Pareto constraints problems and examine the optimality classes that result.

Developmental cascades of peer rejection, social information processing biases, and aggression during middle childhood.

This study tested a developmental cascade model of peer rejection, social information processing (SIP), and aggression using data from 585 children assessed at 12 time points from kindergarten through Grade 3. Peer rejection had direct effects on subsequent SIP problems and aggression. SIP had direct effects on subsequent peer rejection and aggression. Aggression had direct effects on subsequent peer rejection. Each construct also had indirect effects on each of the other constructs. These findings advance the literature beyond a simple mediation approach by demonstrating how each construct effects changes in the others in a snowballing cycle over time. The progressions of SIP problems and aggression cascaded through lower liking, and both better SIP skills and lower aggression facilitated the progress of social preference. Findings are discussed in terms of the dynamic, developmental relations among social environments, cognitions, and behavioral adjustment.

Peace and war: trajectories of posttraumatic stress disorder symptoms before, during, and after military deployment in Afghanistan.

In the study reported here, we examined posttraumatic stress disorder (PTSD) symptoms in 746 Danish soldiers measured on five occasions before, during, and after deployment to Afghanistan. Using latent class growth analysis, we identified six trajectories of change in PTSD symptoms. Two resilient trajectories had low levels across all five times, and a new-onset trajectory started low and showed a marked increase of PTSD symptoms. Three temporary-benefit trajectories, not previously described in the literature, showed decreases in PTSD symptoms during (or immediately after) deployment, followed by increases after return from deployment. Predeployment emotional problems and predeployment traumas, especially childhood adversities, were predictors for inclusion in the nonresilient trajectories, whereas deployment-related stress was not. These findings challenge standard views of PTSD in two ways. First, they show that factors other than immediately preceding stressors are critical for PTSD development, with childhood adversities being central. Second, they demonstrate that the development of PTSD symptoms shows heterogeneity, which indicates the need for multiple measurements to understand PTSD and identify people in need of treatment.

Substance use disorders and co-morbidities among Asian Americans and Native Hawaiians/Pacific Islanders

© Cambridge University Press 2014.Background Asian Americans (AAs) and Native Hawaiians/Pacific Islanders (NHs/PIs) are the fastest growing segments of the US population. However, their population sizes are small, and thus AAs and NHs/PIs are often aggregated into a single racial/ethnic group or omitted from research and health statistics. The groups' substance use disorders (SUDs) and treatment needs have been under-recognized. Method We examined recent epidemiological data on the extent of alcohol and drug use disorders and the use of treatment services by AAs and NHs/PIs. Results NHs/PIs on average were less educated and had lower levels of household income than AAs. Considered as a single group, AAs and NHs/PIs showed a low prevalence of substance use and disorders. Analyses of survey data that compared AAs and NHs/PIs revealed higher prevalences of substance use (alcohol, drugs), depression and delinquency among NHs than among AAs. Among treatment-seeking patients in mental healthcare settings, NHs/PIs had higher prevalences of DSM-IV diagnoses than AAs (alcohol/drug, mood, adjustment, childhood-onset disruptive or impulse-control disorders), although co-morbidity was common in both groups. AAs and NHs/PIs with an SUD were unlikely to use treatment, especially treatment for alcohol problems, and treatment use tended to be related to involvement with the criminal justice system. Conclusions Although available data are limited by small sample sizes of AAs and NHs/PIs, they demonstrate the need to separate AAs and NHs/PIs in health statistics and increase research into substance use and treatment needs for these fast-growing but understudied population groups.

Using electronic health record data for substance use Screening, Brief Intervention, and Referral to Treatment among adults with type 2 diabetes: Design of a National Drug Abuse Treatment Clinical Trials Network study.

BACKGROUND: The Affordable Care Act encourages healthcare systems to integrate behavioral and medical healthcare, as well as to employ electronic health records (EHRs) for health information exchange and quality improvement. Pragmatic research paradigms that employ EHRs in research are needed to produce clinical evidence in real-world medical settings for informing learning healthcare systems. Adults with comorbid diabetes and substance use disorders (SUDs) tend to use costly inpatient treatments; however, there is a lack of empirical data on implementing behavioral healthcare to reduce health risk in adults with high-risk diabetes. Given the complexity of high-risk patients' medical problems and the cost of conducting randomized trials, a feasibility project is warranted to guide practical study designs. METHODS: We describe the study design, which explores the feasibility of implementing substance use Screening, Brief Intervention, and Referral to Treatment (SBIRT) among adults with high-risk type 2 diabetes mellitus (T2DM) within a home-based primary care setting. Our study includes the development of an integrated EHR datamart to identify eligible patients and collect diabetes healthcare data, and the use of a geographic health information system to understand the social context in patients' communities. Analysis will examine recruitment, proportion of patients receiving brief intervention and/or referrals, substance use, SUD treatment use, diabetes outcomes, and retention. DISCUSSION: By capitalizing on an existing T2DM project that uses home-based primary care, our study results will provide timely clinical information to inform the designs and implementation of future SBIRT studies among adults with multiple medical conditions.

Gender and racial/ethnic differences in addiction severity, HIV risk, and quality of life among adults in opioid detoxification: results from the National Drug Abuse Treatment Clinical Trials Network.

PURPOSE: Detoxification often serves as an initial contact for treatment and represents an opportunity for engaging patients in aftercare to prevent relapse. However, there is limited information concerning clinical profiles of individuals seeking detoxification, and the opportunity to engage patients in detoxification for aftercare often is missed. This study examined clinical profiles of a geographically diverse sample of opioid-dependent adults in detoxification to discern the treatment needs of a growing number of women and whites with opioid addiction and to inform interventions aimed at improving use of aftercare or rehabilitation. METHODS: The sample included 343 opioid-dependent patients enrolled in two national multi-site studies of the National Drug Abuse Treatment Clinical Trials Network (CTN001-002). Patients were recruited from 12 addiction treatment programs across the nation. Gender and racial/ethnic differences in addiction severity, human immunodeficiency virus (HIV) risk, and quality of life were examined. RESULTS: Women and whites were more likely than men and African Americans to have greater psychiatric and family/social relationship problems and report poorer health-related quality of life and functioning. Whites and Hispanics exhibited higher levels of total HIV risk scores and risky injection drug use scores than African Americans, and Hispanics showed a higher level of unprotected sexual behaviors than whites. African Americans were more likely than whites to use heroin and cocaine and to have more severe alcohol and employment problems. CONCLUSIONS: Women and whites show more psychopathology than men and African Americans. These results highlight the need to monitor an increased trend of opioid addiction among women and whites and to develop effective combined psychosocial and pharmacologic treatments to meet the diverse needs of the expanding opioid-abusing population. Elevated levels of HIV risk behaviors among Hispanics and whites also warrant more research to delineate mechanisms and to reduce their risky behaviors.