Self-mated tribological systems based on multilayer micro/nanocrystalline CVD diamond coatings

The tribological response of multilayer micro/nanocrystalline diamond coatings grown by the hot filament CVD technique is investigated. These multigrade systems were tailored to comprise a starting microcrystalline diamond (MCD) layer with high adhesion to a silicon nitride (Si3N4) ceramic substrate, and a top nanocrystalline diamond (NCD) layer with reduced surface roughness. Tribological tests were carried out with a reciprocating sliding configuration without lubrication. Such composite coatings exhibit a superior critical load before delamination (130–200 N), when compared to the mono- (60–100 N) and bilayer coatings (110 N), considering ∼10 µm thick films. Regarding the friction behaviour, a short-lived initial high friction coefficient was followed by low friction regimes (friction coefficients between 0.02 and 0.09) as a result of the polished surfaces tailored by the tribological solicitation. Very mild to mild wear regimes (wear coefficient values between 4.1×10−8 and 7.7×10−7 mm3 N−1 m−1) governed the wear performance of the self-mated multilayer coatings when subjected to high-load short-term tests (60–200 N; 2 h; 86 m) and medium-load endurance tests (60 N; 16 h; 691 m).

Host-Guest interaction between herbicide oxadiargyl and hydroxypropyl-β-cyclodextrin

In the face of a growing human population and increased urbanization, the demand for pesticides will simply rise. Farmers must escalate yields on increasingly fewer farm acres. However, the risks of pesticides, whether real or perceived, may force changes in the way these chemicals are used. Scientists are working toward pest control plans that are environmentally sound, effective, and profitable. In this context the development of new pesticide formulations which may improve application effectiveness, safety, handling, and storage can be pointed out as a solution. As a contribution to the area, the microencapsulation of the herbicide oxadiargyl (OXA) in (2-hydroxypropyl)-β-cyclodextrin (HP-β-CD) was performed. The study was conducted in different aqueous media (ultrapure water and in different pH buffer solutions). In all cases an increment of the oxadiargyl solubility as a function of the HP-β-CD concentration that has been related to the formation of an inclusion complex was verified. UV-Vis and NMR experiments allowed concluding that the stoichiometry of the OXA/HP-β-CD complex formed is 1 : 1. The gathered results can be regarded as an important step for its removal from industrial effluents and/or to increase the stabilizing action, encapsulation, and adsorption in water treatment plants.

Association between tooth loss and obesity in Brazilian adults: a population-based study

OBJECTIVE: To examine the association between tooth loss and general and central obesity among adults. METHODS: Population-based cross-sectional study with 1,720 adults aged 20 to 59 years from Florianópolis, Southern Brazil. Home interviews were performed and anthropometric measures were taken. Information on sociodemographic data, self-reported diabetes, self-reported number of teeth, central obesity (waist circumference [WC] > 88 cm in women and > 102 cm in men) and general obesity (body mass index [BMI] ≥ 30 kg/m²) was collected. We used multivariable Poisson regression models to assess the association between general and central obesity and tooth loss after controlling for confounders. We also performed simple and multiple linear regressions by using BMI and WC as continuous variables. Interaction between age and tooth loss was also assessed. RESULTS: The mean BMI was 25.9 kg/m² (95%CI 25.6;26.2) in men and 25.4 kg/m2 (95%CI 25.0;25.7) in women. The mean WC was 79.3 cm (95%CI 78.4;80.1) in men and 88.4 cm (95%CI 87.6;89.2) in women. A positive association was found between the presence of less than 10 teeth in at least one arch and increased mean BMI and WC after adjusting for education level, self-reported diabetes, gender and monthly per capita income. However, this association was lost when the variable age was included in the model. The prevalence of general obesity was 50% higher in those with less than 10 teeth in at least one arch when compared with those with 10 or more teeth in both arches after adjusting for education level, self-reported diabetes and monthly per capita family income. However, the statistical significance was lost after controlling for age. CONCLUSIONS: Obesity was associated with number of teeth, though it depended on the participants' age groups.

Self-reported hearing performance in workers exposed to solvents

OBJECTIVE: To compare hearing performance relating to the peripheral and central auditory system between solvent-exposed and non-exposed workers. METHODS: Forty-eight workers exposed to a mixture of solvents and 48 non-exposed control subjects of matched age, gender and educational level were selected to participate in the study. The evaluation procedures included: pure-tone audiometry (500 - 8,000 Hz), to investigate the peripheral auditory system; the Random Gap Detection test, to assess the central auditory system; and the Amsterdam Inventory for Auditory Disability and Handicap, to investigate subjects' self-reported hearing performance in daily-life activities. A Student t test and analyses of covariance (ANCOVA) were computed to determine possible significant differences between solvent-exposed and non-exposed subjects for the hearing level, Random Gap Detection test and Amsterdam Inventory for Auditory Disability and Handicap. Pearson correlations among the three measures were also calculated. RESULTS: Solvent-exposed subjects exhibited significantly poorer hearing thresholds for the right ear than non-exposed subjects. Also, solvent-exposed subjects exhibited poorer results for the Random Gap Detection test and self-reported poorer listening performance than non-exposed subjects. Results of the Amsterdam Inventory for Auditory Disability and Handicap were significantly correlated with the binaural average of subject pure-tone thresholds and Random Gap Detection test performance. CONCLUSIONS: Solvent exposure is associated with poorer hearing performance in daily life activities that relate to the function of the peripheral and central auditory system.

Self-similarity principle: the reduced description of randomness

A new general fitting method based on the Self-Similar (SS) organization of random sequences is presented. The proposed analytical function helps to fit the response of many complex systems when their recorded data form a self-similar curve. The verified SS principle opens new possibilities for the fitting of economical, meteorological and other complex data when the mathematical model is absent but the reduced description in terms of some universal set of the fitting parameters is necessary. This fitting function is verified on economical (price of a commodity versus time) and weather (the Earth’s mean temperature surface data versus time) and for these nontrivial cases it becomes possible to receive a very good fit of initial data set. The general conditions of application of this fitting method describing the response of many complex systems and the forecast possibilities are discussed.

Democratic dialogue and collective learning in the context of self-managed teams

This paper provides a longitudinal, empirical view of the multifaceted and reciprocal processes of organizational learning in a context of self-managed teams. Organizational learning is seen as a social construction between people and actions in a work setting. The notion of learning as situated (Brown & Duguid 1989, Lave& Wenger 1991, Gherardi & al. 1998, Easterby-Smith & Araujo 1999, Abma 2003) opens up the possibility for placing the focus of research on learning in the community rather than in individual learning processes. Further, in studying processes in their social context, we cannot avoid taking power relations into consideration (Contu & Willmott 2003). The study is based on an action research with a methodology close to the ‘democratic dialogue’ presented by Gustavsen (2001). This gives a ground for research into how the learning discourse developed in the case study organization over a period of 5 years, during which time the company abandoned a middle management level of hierarchy and the teams had to figure out how to work as self-managed units. This paper discusses the (re)construction of power relations and its role in organizational learning. Power relations are discussed both in vertical and horizontal work relations. A special emphasis is placed on the dialectic between managerial aims and the space for reflection on the side of employees. I argue that learning is crucial in the search for the limits for empowerment and that these limits are negotiated both in actions and speech. This study unfolds a purpose-oriented learning process, constructing an open dialogue, and describes a favourable context for creative, knowledge building communities.

Depressive symptoms in institutionalized older adults

OBJECTIVE To estimate the prevalence of depressive symptoms among institutionalized elderly individuals and to analyze factors associated with this condition. METHODS This was a cross-sectional study involving 462 individuals aged 60 or older, residents in long stay institutions in four Brazilian municipalities. The dependent variable was assessed using the 15-item Geriatric Depression Scale. Poisson’s regression was used to evaluate associations with co-variables. We investigated which variables were most relevant in terms of presence of depressive symptoms within the studied context through factor analysis. RESULTS Prevalence of depressive symptoms was 48.7%. The variables associated with depressive symptoms were: regular/bad/very bad self-rated health; comorbidities; hospitalizations; and lack of friends in the institution. Five components accounted for 49.2% of total variance of the sample: functioning, social support, sensory deficiency, institutionalization and health conditions. In the factor analysis, functionality and social support were the components which explained a large part of observed variance. CONCLUSIONS A high prevalence of depressive symptoms, with significant variation in distribution, was observed. Such results emphasize the importance of health conditions and functioning for institutionalized older individuals developing depression. They also point to the importance of providing opportunities for interaction among institutionalized individuals.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Psychological well-being and perception of disease severity in people with multiple sclerosis, who underwent a program of self-regulation to promote physical activity

Rehabilitation is very important for in the results of treatment in individuals with multiple sclerosis. Rehabilitation processes occur through gradual changes. These changes integrate intrinsic and extrinsic mechanisms of the individual, promoting adaptations to the needs and activities of daily living according to individual goals. Recommendations for exercise in multiple sclerosis: these recommendations apply only to patients with EDSS less than 7; moderate intensity aerobic exercise for a total of 20 to 30 minutes, twice or three times for week; the resistance training with low or moderate intensity is well tolerated by patients with MS; associated with these exercises were recommended flexibility exercises of moderate intensity, as well as strengthening exercises. The aim of this study is to examine the implications of the program of self-regulation in the perception of illness and mental health (psychological well-being domain) in multiple sclerosis patients.

Accessibility and Local Development: Interaction between Cross-border Accessibility and Local Development in Portugal and Spain

One of de EU major concerns is cohesion and cross-border regional development. Usually cross-border regions are less dynamic, acting as bottlenecks mainly in peripheral territories. This paper is focused on the Portuguese-Spanish border using socio-economic and accessibility data. It considers Spatial Econometrics to produce statistical evidence on the relationship between accessibility and development at a local scale. A pilot study is conducted on North and Center region using variables such as population age, graduation characteristics, migrations, unemployment and daily accessibility to main towns in future this evaluation will be applied to the entire cross-border area between Portugal and Spain.

Self-reported diabetes in older people: comparison of prevalences and control measures

OBJECTIVE The objective of this study was to analyze the prevalence of diabetes in older people and the adopted control measures.METHODS Data regarding older diabetic individuals who participated in the Health Surveys conducted in the Municipality of Sao Paulo, SP, ISA-Capital, in 2003 and 2008, which were cross-sectional studies, were analyzed. Prevalences and confidence intervals were compared between 2003 and 2008, according to sociodemographic variables. The combination of the databases was performed when the confidence intervals overlapped. The Chi-square (level of significance of 5%) and the Pearson’s Chi-square (Rao-Scott) tests were performed. The variables without overlap between the confidence intervals were not tested.RESULTS The age of the older adults was 60-69 years. The majority were women, Caucasian, with an income of between > 0.5 and 2.5 times the minimum salary and low levels of schooling. The prevalence of diabetes was 17.6% (95%CI 14.9;20.6) in 2003 and 20.1% (95%CI 17.3;23.1) in 2008, which indicates a growth over this period (p at the limit of significance). The most prevalent measure adopted by the older adults to control diabetes was hypoglycemic agents, followed by diet. Physical activity was not frequent, despite the significant differences observed between 2003 and 2008 results. The use of public health services to control diabetes was significantly higher in older individuals with lower income and lower levels of education.CONCLUSIONS Diabetes is a complex and challenging disease for patients and the health systems. Measures that encourage health promotion practices are necessary because they presented a smaller proportion than the use of hypoglycemic agents. Public health policies should be implemented, and aimed mainly at older individuals with low income and schooling levels. These changes are essential to improve the health condition of older diabetic patients.

Dimensions of self-rated health in older adults

OBJECTIVE To analyze the association between negative self-rated health and indicators of health, wellbeing and sociodemographic variables in older adults. METHODS Cross-sectional study that used data from a population-based health survey with a probability cluster sample that was carried out in Campinas, SP, Southeastern Brazil,, in 2008 and 2009. The participants were older adults (≥ 60 years) and the dependent variable was self-rated health, categorized as: excellent, very good, good, bad and very bad. The adjusted prevalence ratios were estimated by means of Poisson multiple regression. RESULTS The highest prevalences of bad/very bad self-rated health were observed in the individuals who never attended school, in those with lower level of schooling, with monthly per capita family income lower than one minimum salary. Individuals who scored five or more in the physical health indicator also had bad self-rated health, as well as those who scored five or more in the Self-Reporting Questionnaire 20 and those who did not refer feeling happiness all the time. CONCLUSIONS The independent effects of material life conditions, physical and mental health and subjective wellbeing, observed in self-rated health, suggest that older adults can benefit by health policies supported by a global and integrative view of old age.

Self-adaptive combination of global tabu search and local search for nonlinear equations

Solving systems of nonlinear equations is a very important task since the problems emerge mostly through the mathematical modelling of real problems that arise naturally in many branches of engineering and in the physical sciences. The problem can be naturally reformulated as a global optimization problem. In this paper, we show that a self-adaptive combination of a metaheuristic with a classical local search method is able to converge to some difficult problems that are not solved by Newton-type methods.

Self-Scheduling for energy and spinning reserve of wind/CSP plants by a MILP approach

This paper is on the self-scheduling for a power producer taking part in day-ahead joint energy and spinning reserve markets and aiming at a short-term coordination of wind power plants with concentrated solar power plants having thermal energy storage. The short-term coordination is formulated as a mixed-integer linear programming problem given as the maximization of profit subjected to technical operation constraints, including the ones related to a transmission line. Probability density functions are used to model the variability of the hourly wind speed and the solar irradiation in regard to a negative correlation. Case studies based on an Iberian Peninsula wind and concentrated solar power plants are presented, providing the optimal energy and spinning reserve for the short-term self-scheduling in order to unveil the coordination benefits and synergies between wind and solar resources. Results and sensitivity analysis are in favour of the coordination, showing an increase on profit, allowing for spinning reserve, reducing the need for curtailment, increasing the transmission line capacity factor. (C) 2014 Elsevier Ltd. All rights reserved.

Scheduling a cutting and treatment stainless steel sheet line with self-management capabilities

With advancement in computer science and information technology, computing systems are becoming increasingly more complex with an increasing number of heterogeneous components. They are thus becoming more difficult to monitor, manage, and maintain. This process has been well known as labor intensive and error prone. In addition, traditional approaches for system management are difficult to keep up with the rapidly changing environments. There is a need for automatic and efficient approaches to monitor and manage complex computing systems. In this paper, we propose an innovative framework for scheduling system management by combining Autonomic Computing (AC) paradigm, Multi-Agent Systems (MAS) and Nature Inspired Optimization Techniques (NIT). Additionally, we consider the resolution of realistic problems. The scheduling of a Cutting and Treatment Stainless Steel Sheet Line will be evaluated. Results show that proposed approach has advantages when compared with other scheduling systems