1,318 research outputs found

    A memetic particle swarm optimisation algorithm for dynamic multi-modal optimisation problems

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    Copyright @ 2011 Taylor & Francis.Many real-world optimisation problems are both dynamic and multi-modal, which require an optimisation algorithm not only to find as many optima under a specific environment as possible, but also to track their moving trajectory over dynamic environments. To address this requirement, this article investigates a memetic computing approach based on particle swarm optimisation for dynamic multi-modal optimisation problems (DMMOPs). Within the framework of the proposed algorithm, a new speciation method is employed to locate and track multiple peaks and an adaptive local search method is also hybridised to accelerate the exploitation of species generated by the speciation method. In addition, a memory-based re-initialisation scheme is introduced into the proposed algorithm in order to further enhance its performance in dynamic multi-modal environments. Based on the moving peaks benchmark problems, experiments are carried out to investigate the performance of the proposed algorithm in comparison with several state-of-the-art algorithms taken from the literature. The experimental results show the efficiency of the proposed algorithm for DMMOPs.This work was supported by the Key Program of National Natural Science Foundation (NNSF) of China under Grant no. 70931001, the Funds for Creative Research Groups of China under Grant no. 71021061, the National Natural Science Foundation (NNSF) of China under Grant 71001018, Grant no. 61004121 and Grant no. 70801012 and the Fundamental Research Funds for the Central Universities Grant no. N090404020, the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant no. EP/E060722/01 and Grant EP/E060722/02, and the Hong Kong Polytechnic University under Grant G-YH60

    The DUNDRUM Quartet: validation of structured professional judgement instruments DUNDRUM-3 assessment of programme completion and DUNDRUM-4 assessment of recovery in forensic mental health services

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    <p>Abstract</p> <p>Background</p> <p>Moving a forensic mental health patient from one level of therapeutic security to a lower level or to the community is influenced by more than risk assessment and risk management. We set out to construct and validate structured professional judgement instruments for consistency and transparency in decision making</p> <p>Methods</p> <p>Two instruments were developed, the seven-item DUNDRUM-3 programme completion instrument and the six item DUNDRUM-4 recovery instrument. These were assessed for all 95 forensic patients at Ireland's only forensic mental health hospital.</p> <p>Results</p> <p>The two instruments had good internal consistency (Cronbach's alpha 0.911 and 0.887). Scores distinguished those allowed no leave or accompanied leave from those with unaccompanied leave (ANOVA F = 38.1 and 50.3 respectively, p < 0.001). Scores also distinguished those in acute/high security units from those in medium or in low secure/pre-discharge units. Each individual item distinguished these levels of need significantly. The DUNDRUM-3 and DUNDRUM-4 correlated moderately with measures of dynamic risk and with the CANFOR staff rated unmet need (Spearman r = 0.5, p < 0.001).</p> <p>Conclusions</p> <p>The DUNDRUM-3 programme completion items distinguished significantly between levels of therapeutic security while the DUNDRUM-4 recovery items consistently distinguished those given unaccompanied leave outside the hospital and those in the lowest levels of therapeutic security. This data forms the basis for a prospective study of outcomes now underway.</p

    DUNDRUM-2: Prospective validation of a structured professional judgment instrument assessing priority for admission from the waiting list for a forensic mental health hospital

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    <p>Abstract</p> <p>Background</p> <p>The criteria for deciding who should be admitted first from a waiting list to a forensic secure hospital are not necessarily the same as those for assessing need. Criteria were drafted qualitatively and tested in a prospective 'real life' observational study over a 6-month period.</p> <p>Methods</p> <p>A researcher rated all those presented at the weekly referrals meeting using the DUNDRUM-1 triage security scale and the DUNDRUM-2 triage urgency scale. The key outcome measure was whether or not the individual was admitted.</p> <p>Results</p> <p>Inter-rater reliability and internal consistency for the DUNDRUM-2 were acceptable. The DUNDRUM-1 triage security score and the DUNDRUM-2 triage urgency score correlated r = 0.663. At the time of admission, after a mean of 23.9 (SD35.9) days on the waiting list, those admitted had higher scores on the DUNDRUM-2 triage urgency scale than those not admitted, with no significant difference between locations (remand or sentenced prisoners, less secure hospitals) at the time of admission. Those admitted also had higher DUNDRUM-1 triage security scores. At baseline the receiver operating characteristic area under the curve for a combined score was the best predictor of admission while at the time of admission the DUNDRUM-2 triage urgency score had the largest AUC (0.912, 95% CI 0.838 to 0.986).</p> <p>Conclusions</p> <p>The triage urgency items and scale add predictive power to the decision to admit. This is particularly true in maintaining equitability between those referred from different locations.</p

    Fast Economic Development Accelerates Biological Invasions in China

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    Increasing levels of global trade and intercontinental travel have been cited as the major causes of biological invasion. However, indirect factors such as economic development that affect the intensity of invasion have not been quantitatively explored. Herein, using principal factor analysis, we investigated the relationship between biological invasion and economic development together with climatic information for China from the 1970s to present. We demonstrate that the increase in biological invasion is coincident with the rapid economic development that has occurred in China over the past three decades. The results indicate that the geographic prevalence of invasive species varies substantially on the provincial scale, but can be surprisingly well predicted using the combination of economic development (R2 = 0.378) and climatic factors (R2 = 0.347). Economic factors are proven to be at least equal to if not more determinant of the occurrence of invasive species than climatic factors. International travel and trade are shown to have played a less significant role in accounting for the intensity of biological invasion in China. Our results demonstrate that more attention should be paid to economic factors to improve the understanding, prediction and management of biological invasions

    Can We Really Prevent Suicide?

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    Every year, suicide is among the top 20 leading causes of death globally for all ages. Unfortunately, suicide is difficult to prevent, in large part because the prevalence of risk factors is high among the general population. In this review, clinical and psychological risk factors are examined and methods for suicide prevention are discussed. Prevention strategies found to be effective in suicide prevention include means restriction, responsible media coverage, and general public education, as well identification methods such as screening, gatekeeper training, and primary care physician education. Although the treatment for preventing suicide is difficult, follow-up that includes pharmacotherapy, psychotherapy, or both may be useful. However, prevention methods cannot be restricted to the individual. Community, social, and policy interventions will also be essentia

    Surface pretreatments for medical application of adhesion

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    Medical implants and prostheses (artificial hips, tendono- and ligament plasties) usually are multi-component systems that may be machined from one of three material classes: metals, plastics and ceramics. Typically, the body-sided bonding element is bone. The purpose of this contribution is to describe developments carried out to optimize the techniques , connecting prosthesis to bone, to be joined by an adhesive bone cement at their interface. Although bonding of organic polymers to inorganic or organic surfaces and to bone has a long history, there remains a serious obstacle in realizing long-term high-bonding strengths in the in vivo body environment of ever present high humidity. Therefore, different pretreatments, individually adapted to the actual combination of materials, are needed to assure long term adhesive strength and stability against hydrolysis. This pretreatment for metal alloys may be silica layering; for PE-plastics, a specific plasma activation; and for bone, amphiphilic layering systems such that the hydrophilic properties of bone become better adapted to the hydrophobic properties of the bone cement. Amphiphilic layering systems are related to those developed in dentistry for dentine bonding. Specific pretreatment can significantly increase bond strengths, particularly after long term immersion in water under conditions similar to those in the human body. The bond strength between bone and plastic for example can be increased by a factor approaching 50 (pealing work increasing from 30 N/m to 1500 N/m). This review article summarizes the multi-disciplined subject of adhesion and adhesives, considering the technology involved in the formation and mechanical performance of adhesives joints inside the human body

    Biochemical systems identification by a random drift particle swarm optimization approach

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    BACKGROUND: Finding an efficient method to solve the parameter estimation problem (inverse problem) for nonlinear biochemical dynamical systems could help promote the functional understanding at the system level for signalling pathways. The problem is stated as a data-driven nonlinear regression problem, which is converted into a nonlinear programming problem with many nonlinear differential and algebraic constraints. Due to the typical ill conditioning and multimodality nature of the problem, it is in general difficult for gradient-based local optimization methods to obtain satisfactory solutions. To surmount this limitation, many stochastic optimization methods have been employed to find the global solution of the problem. RESULTS: This paper presents an effective search strategy for a particle swarm optimization (PSO) algorithm that enhances the ability of the algorithm for estimating the parameters of complex dynamic biochemical pathways. The proposed algorithm is a new variant of random drift particle swarm optimization (RDPSO), which is used to solve the above mentioned inverse problem and compared with other well known stochastic optimization methods. Two case studies on estimating the parameters of two nonlinear biochemical dynamic models have been taken as benchmarks, under both the noise-free and noisy simulation data scenarios. CONCLUSIONS: The experimental results show that the novel variant of RDPSO algorithm is able to successfully solve the problem and obtain solutions of better quality than other global optimization methods used for finding the solution to the inverse problems in this study

    A Measurement of Rb using a Double Tagging Method

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    The fraction of Z to bbbar events in hadronic Z decays has been measured by the OPAL experiment using the data collected at LEP between 1992 and 1995. The Z to bbbar decays were tagged using displaced secondary vertices, and high momentum electrons and muons. Systematic uncertainties were reduced by measuring the b-tagging efficiency using a double tagging technique. Efficiency correlations between opposite hemispheres of an event are small, and are well understood through comparisons between real and simulated data samples. A value of Rb = 0.2178 +- 0.0011 +- 0.0013 was obtained, where the first error is statistical and the second systematic. The uncertainty on Rc, the fraction of Z to ccbar events in hadronic Z decays, is not included in the errors. The dependence on Rc is Delta(Rb)/Rb = -0.056*Delta(Rc)/Rc where Delta(Rc) is the deviation of Rc from the value 0.172 predicted by the Standard Model. The result for Rb agrees with the value of 0.2155 +- 0.0003 predicted by the Standard Model.Comment: 42 pages, LaTeX, 14 eps figures included, submitted to European Physical Journal
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