From local to global importance measures of uncertainty propagation in composite structures

The influence of uncertainties of input parameters on output response of composite structures is investigated in this paper. In particular, the effects of deviations in mechanical properties, ply angles, ply thickness and on applied loads are studied. The uncertainty propagation and the importance measure of input parameters are analysed using three different approaches: a first-order local method, a Global Sensitivity Analysis (GSA) supported by a variance-based method and an extension of local variance to estimate the global variance over the domain of inputs. Sample results are shown for a shell composite laminated structure built with different composite systems including multi-materials. The importance measures of input parameters on structural response based on numerical results are established and discussed as a function of the anisotropy of composite materials. Needs for global variance methods are discussed by comparing the results obtained from different proposed methodologies. The objective of this paper is to contribute for the use of GSA techniques together with low expensive local importance measures.

Filters method in direct search optimization, new measures to admissibility

Constrained nonlinear optimization problems are usually solved using penalty or barrier methods combined with unconstrained optimization methods. Another alternative used to solve constrained nonlinear optimization problems is the lters method. Filters method, introduced by Fletcher and Ley er in 2002, have been widely used in several areas of constrained nonlinear optimization. These methods treat optimization problem as bi-objective attempts to minimize the objective function and a continuous function that aggregates the constraint violation functions. Audet and Dennis have presented the rst lters method for derivative-free nonlinear programming, based on pattern search methods. Motivated by this work we have de- veloped a new direct search method, based on simplex methods, for general constrained optimization, that combines the features of the simplex method and lters method. This work presents a new variant of these methods which combines the lters method with other direct search methods and are proposed some alternatives to aggregate the constraint violation functions.

Optimizing the renewable generation mix in the portuguese power system based on temporal and spatial diversity

Renewable energy sources (RES) have unique characteristics that grant them preference in energy and environmental policies. However, considering that the renewable resources are barely controllable and sometimes unpredictable, some challenges are faced when integrating high shares of renewable sources in power systems. In order to mitigate this problem, this paper presents a decision-making methodology regarding renewable investments. The model computes the optimal renewable generation mix from different available technologies (hydro, wind and photovoltaic) that integrates a given share of renewable sources, minimizing residual demand variability, therefore stabilizing the thermal power generation. The model also includes a spatial optimization of wind farms in order to identify the best distribution of wind capacity. This methodology is applied to the Portuguese power system.

A Clinical Support System Based on Quality of Life Estimation

Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual's daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt's sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.

An agent-based simulator to estimate domestic energy use

Throughout recent years, there has been an increase in the population size, as well as a fast economic growth, which has led to an increase of the energy demand that comes mainly from fossil fuels. In order to reduce the ecological footprint, governments have implemented sustainable measures and it is expected that by 2035 the energy produced from renewable energy sources, such as wind and solar would be responsible for one-third of the energy produced globally. However, since the energy produced from renewable sources is governed by the availability of the respective primary energy source there is often a mismatch between production and demand, which could be solved by adding flexibility on the demand side through demand response (DR). DR programs influence the end-user electricity usage by changing its cost along the time. Under this scenario the user needs to estimate the energy demand and on-site production in advance to plan its energy demand according to the energy price. This work focuses on the development of an agent-based electrical simulator, capable of: (a) estimating the energy demand and on-site generation with a 1-min time resolution for a 24-h period, (b) calculating the energy price for a given scenario, (c) making suggestions on how to maximize the usage of renewable energy produced on-site and to lower the electricity costs by rescheduling the use of certain appliances. The results show that this simulator allows reducing the energy bill by 11% and almost doubling the use of renewable energy produced on-site.

Diabetes care in Switzerland: good, but perfectible: a population-based cross-sectional survey.

BACKGROUND: While Switzerland invests a lot of money in its healthcare system, little is known about the quality of care delivered. The objective of this study was to assess the quality of care provided to patients with diabetes in the Canton of Vaud, Switzerland. METHODS: Cross-sectional study of 406 non-institutionalized adults with type 1 or 2 diabetes. Patients' characteristics, diabetes and process of care indicators were collected using a self-administered questionnaire. Process indicators (past 12 months) included HbA1C check among HbA1C-aware patients, eye assessment by ophtalmologist, microalbuminuria check, feet examination, lipid test, blood pressure and weight measurement, influenza immunization, physical activity recommendations, and dietary recommendations. Item-by-item (each process of care indicator: percentage of patients having received it), composite (mean percentage of recommended care: sum of received processes of care / sum of possible recommended care), and all-or-none (percentage of patients receiving all specified recommended care) measures were computed. RESULTS: Mean age was 64.4 years; 59% were men. Type 1 and type 2 diabetes were reported by 18.2% and 68.5% of patients, respectively, but diabetes type remained undetermined for almost 20% of patients. Patients were treated with oral anti-diabetic drugs (50%), insulin (23%) or both (27%). Of 219 HbA1C-aware patients, 98% reported ≥ one HbA1C check during the last year. Also, ≥94% reported ≥ one blood pressure measurement, ≥ one weight measurement or lipid test, and 68%, 64% and 56% had feet examination, microalbuminuria check and eye assessment, respectively. Influenza immunization was reported by 62% of the patients.The percentage of patients receiving all processes of care ranged between 14.2%-16.9%, and 46.6%-50.7%, when considering ten and four indicators, respectively. Ambulatory care utilization showed little use of multidisciplinary care, and low levels of participation in diabetes-education classes. CONCLUSIONS: While routine processes-of-care were performed annually in most patients, diabetes-specific risk screenings, influenza immunization, physical activity and dietary recommendations were less often reported; this was also the case for multidisciplinary care and participation in education classes. There is room for diabetes care improvement in Switzerland. These results should help define priorities and further develop country-specific chronic disease management initiatives for diabetes.

Effect of school based physical activity programme (KISS) on fitness and adiposity in primary schoolchildren: cluster randomised controlled trial.

To assess the effectiveness of a school based physical activity programme during one school year on physical and psychological health in young schoolchildren. Cluster randomised controlled trial. 28 classes from 15 elementary schools in Switzerland randomly selected and assigned in a 4:3 ratio to an intervention (n=16) or control arm (n=12) after stratification for grade (first and fifth grade), from August 2005 to June 2006. 540 children, of whom 502 consented and presented at baseline. Children in the intervention arm (n=297) received a multi-component physical activity programme that included structuring the three existing physical education lessons each week and adding two additional lessons a week, daily short activity breaks, and physical activity homework. Children (n=205) and parents in the control group were not informed of an intervention group. For most outcome measures, the assessors were blinded. Primary outcome measures included body fat (sum of four skinfolds), aerobic fitness (shuttle run test), physical activity (accelerometry), and quality of life (questionnaires). Secondary outcome measures included body mass index and cardiovascular risk score (average z score of waist circumference, mean blood pressure, blood glucose, inverted high density lipoprotein cholesterol, and triglycerides). 498 children completed the baseline and follow-up assessments (mean age 6.9 (SD 0.3) years for first grade, 11.1 (0.5) years for fifth grade). After adjustment for grade, sex, baseline values, and clustering within classes, children in the intervention arm compared with controls showed more negative changes in the z score of the sum of four skinfolds (-0.12, 95 % confidence interval -0.21 to -0.03; P=0.009). Likewise, their z scores for aerobic fitness increased more favourably (0.17, 0.01 to 0.32; P=0.04), as did those for moderate-vigorous physical activity in school (1.19, 0.78 to 1.60; P<0.001), all day moderate-vigorous physical activity (0.44, 0.05 to 0.82; P=0.03), and total physical activity in school (0.92, 0.35 to 1.50; P=0.003). Z scores for overall daily physical activity (0.21, -0.21 to 0.63) and physical quality of life (0.42, -1.23 to 2.06) as well as psychological quality of life (0.59, -0.85 to 2.03) did not change significantly. A school based multi-component physical activity intervention including compulsory elements improved physical activity and fitness and reduced adiposity in children. Trial registration Current Controlled Trials ISRCTN15360785.

High expectation in non-evidence-based smoking cessation interventions among smokers--the CoLaus study.

To assess the preferred methods to quit smoking among current smokers. Cross-sectional, population-based study conducted in Lausanne between 2003 and 2006 including 988 current smokers. Preference was assessed by questionnaire. Evidence-based (EB) methods were nicotine replacement, bupropion, physician or group consultations; non-EB-based methods were acupuncture, hypnosis and autogenic training. EB methods were frequently (physician consultation: 48%, 95% confidence interval (45-51); nicotine replacement therapy: 35% (32-38)) or rarely (bupropion and group consultations: 13% (11-15)) preferred by the participants. Non-EB methods were preferred by a third (acupuncture: 33% (30-36)), a quarter (hypnosis: 26% (23-29)) or a seventh (autogenic training: 13% (11-15)) of responders. On multivariate analysis, women preferred both EB and non-EB methods more frequently than men (odds ratio and 95% confidence interval: 1.46 (1.10-1.93) and 2.26 (1.72-2.96) for any EB and non-EB method, respectively). Preference for non-EB methods was higher among highly educated participants, while no such relationship was found for EB methods. Many smokers are unaware of the full variety of methods to quit smoking. Better information regarding these methods is necessary.

Disease identification based on ambulatory drugs dispensation and in-hospital ICD-10 diagnoses: a comparison.

BACKGROUND: Pharmacy-based case mix measures are an alternative source of information to the relatively scarce outpatient diagnoses data. But most published tools use national drug nomenclatures and offer no head-to-head comparisons between drugs-related and diagnoses-based categories. The objective of the study was to test the accuracy of drugs-based morbidity groups derived from the World Health Organization Anatomical Therapeutic Chemical Classification of drugs by checking them against diagnoses-based groups. METHODS: We compared drugs-based categories with their diagnoses-based analogues using anonymous data on 108,915 individuals insured with one of four companies. They were followed throughout 2005 and 2006 and hospitalized at least once during this period. The agreement between the two approaches was measured by weighted kappa coefficients. The reproducibility of the drugs-based morbidity measure over the 2 years was assessed for all enrollees. RESULTS: Eighty percent used a drug associated with at least one of the 60 morbidity categories derived from drugs dispensation. After accounting for inpatient under-coding, fifteen conditions agreed sufficiently with their diagnoses-based counterparts to be considered alternative strategies to diagnoses. In addition, they exhibited good reproducibility and allowed prevalence estimates in accordance with national estimates. For 22 conditions, drugs-based information identified accurately a subset of the population defined by diagnoses. CONCLUSIONS: Most categories provide insurers with health status information that could be exploited for healthcare expenditure prediction or ambulatory cost control, especially when ambulatory diagnoses are not available. However, due to insufficient concordance with their diagnoses-based analogues, their use for morbidity indicators is limited.

Medication use in pregnancy: a cross-sectional, multinational web-based study.

OBJECTIVES: Intercountry comparability between studies on medication use in pregnancy is difficult due to dissimilarities in study design and methodology. This study aimed to examine patterns and factors associated with medications use in pregnancy from a multinational perspective, with emphasis on type of medication utilised and indication for use. DESIGN: Cross-sectional, web-based study performed within the period from 1 October 2011 to 29 February 2012. Uniform collection of drug utilisation data was performed via an anonymous online questionnaire. SETTING: Multinational study in Europe (Western, Northern and Eastern), North and South America and Australia. PARTICIPANTS: Pregnant women and new mothers with children less than 1 year of age. PRIMARY AND SECONDARY OUTCOME MEASURES: Prevalence of and factors associated with medication use for acute/short-term illnesses, chronic/long-term disorders and over-the-counter (OTC) medication use. RESULTS: The study population included 9459 women, of which 81.2% reported use of at least one medication (prescribed or OTC) during pregnancy. Overall, OTC medication use occurred in 66.9% of the pregnancies, whereas 68.4% and 17% of women reported use of at least one medication for treatment of acute/short-term illnesses and chronic/long-term disorders, respectively. The extent of self-reported medicated illnesses and types of medication used by indication varied across regions, especially in relation to urinary tract infections, depression or OTC nasal sprays. Women with higher age or lower educational level, housewives or women with an unplanned pregnancy were those most often reporting use of medication for chronic/long-term disorders. Immigrant women in Western (adjusted OR (aOR): 0.55, 95% CI 0.34 to 0.87) and Northern Europe (aOR: 0.50, 95% CI 0.31 to 0.83) were less likely to report use of medication for chronic/long-term disorders during pregnancy than non-immigrants. CONCLUSIONS: In this study, the majority of women in Europe, North America, South America and Australia used at least one medication during pregnancy. There was a substantial inter-region variability in the types of medication used.

Treatment intensification and risk factor control: toward more clinically relevant quality measures.

BACKGROUND: Intensification of pharmacotherapy in persons with poorly controlled chronic conditions has been proposed as a clinically meaningful process measure of quality. OBJECTIVE: To validate measures of treatment intensification by evaluating their associations with subsequent control in hypertension, hyperlipidemia, and diabetes mellitus across 35 medical facility populations in Kaiser Permanente, Northern California. DESIGN: Hierarchical analyses of associations of improvements in facility-level treatment intensification rates from 2001 to 2003 with patient-level risk factor levels at the end of 2003. PATIENTS: Members (515,072 and 626,130; age >20 years) with hypertension, hyperlipidemia, and/or diabetes mellitus in 2001 and 2003, respectively. MEASUREMENTS: Treatment intensification for each risk factor defined as an increase in number of drug classes prescribed, of dosage for at least 1 drug, or switching to a drug from another class within 3 months of observed poor risk factor control. RESULTS: Facility-level improvements in treatment intensification rates between 2001 and 2003 were strongly associated with greater likelihood of being in control at the end of 2003 (P < or = 0.05 for each risk factor) after adjustment for patient- and facility-level covariates. Compared with facility rankings based solely on control, addition of percentages of poorly controlled patients who received treatment intensification changed 2003 rankings substantially: 14%, 51%, and 29% of the facilities changed ranks by 5 or more positions for hypertension, hyperlipidemia, and diabetes, respectively. CONCLUSIONS: Treatment intensification is tightly linked to improved control. Thus, it deserves consideration as a process measure for motivating quality improvement and possibly for measuring clinical performance.

Many valued algebraic structures as measures of comparison

This thesis studies the properties and usability of operators called t-norms, t-conorms, uninorms, as well as many valued implications and equivalences. Into these operators, weights and a generalized mean are embedded for aggregation, and they are used for comparison tasks and for this reason they are referred to as comparison measures. The thesis illustrates how these operators can be weighted with a differential evolution and aggregated with a generalized mean, and the kinds of measures of comparison that can be achieved from this procedure. New operators suitable for comparison measures are suggested. These operators are combination measures based on the use of t-norms and t-conorms, the generalized 3_-uninorm and pseudo equivalence measures based on S-type implications. The empirical part of this thesis demonstrates how these new comparison measures work in the field of classification, for example, in the classification of medical data. The second application area is from the field of sports medicine and it represents an expert system for defining an athlete's aerobic and anaerobic thresholds. The core of this thesis offers definitions for comparison measures and illustrates that there is no actual difference in the results achieved in comparison tasks, by the use of comparison measures based on distance, versus comparison measures based on many valued logical structures. The approach has been highly practical in this thesis and all usage of the measures has been validated mainly by practical testing. In general, many different types of operators suitable for comparison tasks have been presented in fuzzy logic literature and there has been little or no experimental work with these operators.

Community Recreation and Leisure Activities in Adults with Developmental Disabilities who have Recently Relocated to Community-based Residences in Ontario

In 2009, the Ontario Government closed the last three remaining large-scale institutions for people with Developmental Disabilities (DD). The purpose of this study is to examine the community-based recreation and leisure activities of 87 adults with DD who have recently moved into the community. Study 1 provided a descriptive insight into the community recreation and leisure activities, and revealed that people with DD engage in low levels of community activities, however are reported to have the desire to engage more often. Staff reported that people with DD do not have the opportunities to engage in their preferable activities. Study 2 investigated the prbspective predictors of the number and frequency of community, recreation and leisure activities and found that a higher level of functioning predicted a greater number of community activities ([beta] = .26, P < .05), while both a higher level of functioning ([beta] = .38,p < .001) and greater preference ([beta] = .23. p < .05) predicted more frequent access to community activities. Future research and the implications of the findings for clinical practice and policy development were discussed.

Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.

Single-Molecule Magnets and Multifunctional Molecular Magnetic Materials Based on Polynuclear Metal Complexes

Our work on single molecule magnets and multifunctional magnetic materials is presented in four projects. In the first project we show for first time that heteroatomic-type pseudohalides, such as OCN-, can be employed as structure-directing ligands and ferromagnetic couplers in higher oxidation state metal cluster chemistry. The initial use of cyanato groups in Mn cluster chemistry has afforded structurally interesting MnII/III14 (1) and MnII/III/IV16 (2) clusters in which the end-on bridging cyanates show a preference in binding through their O-atom. The Mn14 compound shows entirely visible out-of-phase alternating currect signals below 5 K and large hysteresis loops below 2 K. Furthermore, the amalgamation of azido groups with the triethanolamine tripodal ligand in manganese carboxylate cluster chemistry has led to the isolation of a new ferromagnetic, high-nuclearity and mixed-valence MnII/III15Na2 (3) cluster with a large ground-state spin value of S = 14. In the second project we demonstrate a new synthetic route to purely inorganic-bridged, transition metal-azido clusters [CoII7 (4) and NiII7 (5)] and coordination polymers [{FeII/III2}n (6)] which exhibit strong ferromagnetic, SMM and long-range magnetic ordering behaviors. We also show that access to such a unique ferromagnetic class of inorganic, N-rich and O-free materials is feasible through the use of Me3SiN3 as the azido-ligand precursor without requiring the addition of any organic chelating/bridging ligand. In the last projects we have tried to bring together molecular magnetism and optics via the synthesis of multifunctional magnetic materials based on 3d- or 4f-metal ions. We decided to approach such challenge from two different directions: firstly, in our third project, by the deliberate replacement of non-emissive carboxylato ligands in known 3d-SMMs with their fluorescent analogues, without perturbing the metal-core structure and SMM properties (complexes 7, 8, and 9). The second route (last project) involves the use of naphthalene or pyridine-based polyalcohol bridging ligands for the synthesis of new polynuclear LnIII metal clusters (Ln = lanthanide) with novel topologies, SMM behaviors and luminescent properties arising from the increased efficiency of the “antenna” organic group. This approach has led us to the isolation of two new families of LnIII8 (complexes 10-13) and LnIII4 (complexes 14-20) clusters.