Oral impacts on the daily performance of Brazilians assessed using a sociodental approach: analyses of national data

The aim of this study was to analyze the relationship between oral diseases and their impact on the daily performance of adult and elderly Brazilians, verify the association of oral diseases with socioeconomic and demographic features, and compare the standard estimate of need with the sociodental assessment of these same needs. The authors evaluated data from 17,398 Brazilians aged between 35-44 years and 65-74 years, taken from the cross-sectional Brazilian Oral Health Survey (Saúde Bucal Brasil - SBBrasil). Regression models were applied to assess associations among impacts on daily performance and income, schooling, gender, region, use of dental services, health perception and dental disease status. McNemar’s test was applied to compare standard versus impact-related estimates of need. The prevalence ratio of these impacts was associated with the sociodemographic versus health perceptions (p < 0.001) of adults and the elderly. Adults also had impacts associated with loss of periodontal attachment (p < 0.001). The prevalence of normative needs was 95.39% for adults and 99.76% for the elderly, whereas the impact-related estimate of need was 50.92% and 43.71%, respectively. The impacted-related approach had a statistically significant association with the normative estimate of need (p < 0.001). This study showed a relationship between oral impact on daily performance of adults and educational level. Sociodemographic features were also related to the impacts on both adults and the elderly, and to health perception. The impacts among the adults were related to the loss of periodontal attachment. In addition, the authors found a sizable difference between the standard versus the sociodental approach, in that the sociodental assessment needs were lower than the needs identified by the standard estimate of need.

Performance of the CMS missing transverse momentum reconstruction in pp data at root s=8 TeV

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The Role of CEO Statements of Aggressiveness and the Competitive Aggressiveness of Firms: What is the Impact on Performance?

This research examines the impact of a CEO’s statements of aggressiveness on his or her organization’s competitive moves and subsequent performance. Hypotheses were developed based on previous work in Upper Echelon Theory and competitive dynamics. Based on this prior literature, it was hypothesized aggressive statements by CEOs will be associated with more aggressive organizations. It was also hypothesized these more aggressive organizations would display better performance than less aggressive organizations. A content analysis of letters to shareholders and trade publications was performed. This data was analyzed using multiple regression in SPSS 17 to test the hypotheses that aggressive statements by CEOs are associated with aggressive organizations and higher performance. Aggression scores for the content analysis were generated using the software package DICTION. The sample for the study was the organizations with the most revenue in two industries, automobile manufacturing and retailing. Data collection covered a five-year time span from 2003-2007, with performance data lagged one year. Control variables employed included CEO tenure, CEO background, organization size, and organization age. The findings indicate that CEO statements of aggressiveness do not significantly impact the competitive aggressiveness or the performance of their organizations. The implications of these findings are discussed and potential avenues for future research in the area are outlined.

What Business Reference Librarians Need to Know about Intellectual Property: Presentations sponsored by the Patent and Trademark Depository Library Association (PTDLA) at the American Library Association Annual Conference, New Orleans, June 25, 2006

Presentations sponsored by the Patent and Trademark Depository Library Association (PTDLA) at the American Library Association Annual Conference, New Orleans, June 25, 2006 Speaker #1: Nan Myers Associate Professor; Government Documents, Patents and Trademarks Librarian Wichita State University, Wichita, KS Title: Intellectual Property Roundup: Copyright, Trademarks, Trade Secrets, and Patents Abstract: This presentation provides a capsule overview of the distinctive coverage of the four types of intellectual property – What they are, why they are important, how to get them, what they cost, how long they last. Emphasis will be on what questions patrons ask most, along with the answers! Includes coverage of the mission of Patent & Trademark Depository Libraries (PTDLs) and other sources of business information outside of libraries, such as Small Business Development Centers. Speaker #2: Jan Comfort Government Information Reference Librarian Clemson University, Clemson, SC Title: Patents as a Source of Competitive Intelligence Information Abstract: Large corporations often have R&D departments, or large numbers of staff whose jobs are to monitor the activities of their competitors. This presentation will review strategies that small business owners can employ to do their own competitive intelligence analysis. The focus will be on features of the patent database that is available free of charge on the USPTO website, as well as commercial databases available at many public and academic libraries across the country. Speaker #3: Virginia Baldwin Professor; Engineering Librarian University of Nebraska-Lincoln, Lincoln, NE Title: Mining Online Patent Data for Business Information Abstract: The United States Patent and Trademark Office (USPTO) website and websites of international databases contains information about granted patents and patent applications and the technologies they represent. Statistical information about patents, their technologies, geographical information, and patenting entities are compiled and available as reports on the USPTO website. Other valuable information from these websites can be obtained using data mining techniques. This presentation will provide the keys to opening these resources and obtaining valuable data. Speaker #4: Donna Hopkins Engineering Librarian Renssalaer Polytechnic Institute, Troy, NY Title: Searching the USPTO Trademark Database for Wordmarks and Logos Abstract: This presentation provides an overview of wordmark searching in www.uspto.gov, followed by a review of the techniques of searching for non-word US trademarks using codes from the Design Search Code Manual. These codes are used in an electronic search, either on the uspto website or on CASSIS DVDs. The search is sometimes supplemented by consulting the Official Gazette. A specific example of using a section of the codes for searching is included. Similar searches on the Madrid Express database of WIPO, using the Vienna Classification, will also be briefly described.

Firm Market Performance and Volatility in a National Real Estate Sector

We present empirical evidence using daily data for stock prices for 17 real estate companies traded in the Sao Paulo, Brazil stock exchange. from August 26, 2006 to March 31, 2010. We use the U.S. house price bubble, financial crisis and risk measures to instrument for momentums and reversals in the domestic real estate sector. We find evidence of conditional premium persistence and conditional volatility persistence in the market. We find that the conditional risk-return relationship in the sector is consistent with the prospect theory of risk attitudes in this period. Certain companies seem to be operating on a perceived potential industry return above the target, while most others are below the target, and the whole sector is below target on average. (C) 2011 Elsevier Inc. All rights reserved.

Normative Data for Healthy Middle-Aged and Elderly Performance on the Addenbrooke Cognitive Examination-Revised

Objective: To provide normative data for healthy middle-aged and elderly Brazilians' performance on the Addenbrooke Cognitive Examination-Revised (ACE-R) and to investigate the effects of age, sex, and schooling on test performance. Background: The ACE-R is a brief cognitive battery that assesses various aspects of cognition. Its 5 subdomains (Attention and Orientation, Memory, Verbal Fluency, Language, and Visuospatial Abilities) are commonly impaired in Alzheimer disease or frontotemporal dementia. Methods: We evaluated 144 cognitively healthy volunteers (50% men, 50% women) aged 50 to 93 years, with 4 to 24 years of schooling. We divided the participants into 4 age groups, each of which was then stratified into 3 groups according to years of education. We assessed all participants with the ACE-R, the Mattis Dementia Rating Scale, and the Cornell Scale for Depression in Dementia. Results: Years of education affected all ACE-R subscores. Age influenced the Verbal Fluency subscore (P < 0.001) and the ACE-R total score (P < 0.05). Sex affected the Attention and Orientation (P = 0.037) and Mini-Mental State Examination subscores (P = 0.048), but not the ACE-R total score (P > 0.05). Conclusions: The performance of healthy middle-aged and elderly individuals on the ACE-R battery is strongly influenced by education and, to a lesser extent, by age. These findings are of special relevance in countries with populations that have marked heterogeneity in educational levels.

Frailty criteria and cognitive performance are related: data from the fibra study in Ermelino Matarazzo, São Paulo, Brazil

Objectives: To assess the relationship between the CHS frailty criteria (Fried et al., 2001) and cognitive performance. Design: Cross sectional and population-based. Setting: Ermelino Matarazzo, a poor sub district of the city of Sao Paulo, Brazil. Participants: 384 community dwelling older adults, 65 and older. Measurements: Assessment of the CHS frailty criteria, the Brief Cognitive Screening Battery (memorization of 10 black and white pictures, verbal fluency animal category, and the Clock Drawing Test) and the Mini-Mental State Examination (MMSE). Results: Frail older adults performed significantly lower than non-frail and pre frail elderly in most cognitive variables. Grip strength and age were associated to MMSE performance, age was associated to delayed memory recall, gait speed was associated to verbal fluency and CDT performance, and education was associated to CDT performance. Conclusion: Being frail may be associated with cognitive decline, thus, gerontological assessments and interventions should consider that these forms of vulnerability may occur simultaneously.

Network-based high level data classification

Traditional supervised data classification considers only physical features (e. g., distance or similarity) of the input data. Here, this type of learning is called low level classification. On the other hand, the human (animal) brain performs both low and high orders of learning and it has facility in identifying patterns according to the semantic meaning of the input data. Data classification that considers not only physical attributes but also the pattern formation is, here, referred to as high level classification. In this paper, we propose a hybrid classification technique that combines both types of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features or class topologies, while the latter measures the compliance of the test instances to the pattern formation of the data. Our study shows that the proposed technique not only can realize classification according to the pattern formation, but also is able to improve the performance of traditional classification techniques. Furthermore, as the class configuration's complexity increases, such as the mixture among different classes, a larger portion of the high level term is required to get correct classification. This feature confirms that the high level classification has a special importance in complex situations of classification. Finally, we show how the proposed technique can be employed in a real-world application, where it is capable of identifying variations and distortions of handwritten digit images. As a result, it supplies an improvement in the overall pattern recognition rate.

Knowledge management and strategic orientation: leveraging innovativeness and performance

Purpose - The aim of this study is to investigate whether knowledge management (KM) contributes to the development of strategic orientation and to enhance innovativeness, and whether these three factors contribute to improve business performance. Design/methodology/approach - A sample of 241 Brazilian companies was surveyed, using Web-based questionnaires with 54 questions, using ten-point scales to measure the degree of agreement on each item of each construct. Structural equation modeling techniques were applied for model assessment and analysis of the relationships among constructs. Exploratory factor analysis, confirmatory factor analysis, and path analysis using the technique of structural equation modeling were applied to the data. Findings - Effective KM contributes positively to strategic orientation. Although there is no significant direct effect of KM on innovativeness, the relationship is significant when mediated by strategic orientation. Similarly effective KM has no direct effect on business performance, but this relationship becomes statistically significant when mediated by strategic orientation and innovativeness. Research limitations/implications - The findings indicate that KM permeates all relationships among the constructs, corroborating the argument that knowledge is an essential organizational resource that leverages all value-creating activities. The results indicate that both KM and innovativeness produce significant impacts on performance when they are aligned with a strategic orientation that enables the organization to anticipate and respond to changing market conditions. Originality/value - There is a substantial body of research on several types of relationships involving KM, strategic orientation, innovativeness and performance. This study offers an original contribution by analyzing all of those constructs simultaneously using established scales so that comparative studies are possible.

Organization Performance Evaluation Using System Thinking: A Study in Brazilian Chemical Organizations Models

System thinking allows companies to use subjective constructs indicators like recursiveness, cause-effect relationships and autonomy to performance evaluation. Thus, the question that motivates this paper is: Are Brazilian companies searching new performance measurement and evaluation models based on system thinking? The study investigates models looking for system thinking roots in their framework. It was both exploratory and descriptive based on a multiple four case studies strategy in chemical sector. The findings showed organizational models have some characteristics that can be related to system thinking as system control and communication. Complexity and autonomy are deficiently formalized by the companies. All data suggest, inside its context, that system thinking seems to be adequate to organizational performance evaluation but remains distant from the management proceedings.

On the impact of disproportional samples in credit scoring models: An application to a Brazilian bank data

Statistical methods have been widely employed to assess the capabilities of credit scoring classification models in order to reduce the risk of wrong decisions when granting credit facilities to clients. The predictive quality of a classification model can be evaluated based on measures such as sensitivity, specificity, predictive values, accuracy, correlation coefficients and information theoretical measures, such as relative entropy and mutual information. In this paper we analyze the performance of a naive logistic regression model (Hosmer & Lemeshow, 1989) and a logistic regression with state-dependent sample selection model (Cramer, 2004) applied to simulated data. Also, as a case study, the methodology is illustrated on a data set extracted from a Brazilian bank portfolio. Our simulation results so far revealed that there is no statistically significant difference in terms of predictive capacity between the naive logistic regression models and the logistic regression with state-dependent sample selection models. However, there is strong difference between the distributions of the estimated default probabilities from these two statistical modeling techniques, with the naive logistic regression models always underestimating such probabilities, particularly in the presence of balanced samples. (C) 2012 Elsevier Ltd. All rights reserved.

Synthesis and photovoltaic performance of a fluorene-bithiophene copolymer

We present the synthesis of a copolymer structure, poly(9,9′-n-di-hexyl-2,7-fluorene-alt-2,5- bithiophene), referred to herein as LaPPS43, and its physico-chemical characterization. Thin films of this polymer mixed with phenyl-C61-butyric acid methyl ester (PCBM) were used as the active layer in photovoltaic devices using the ITO/PEDOT:PSS/LaPPS43: PCBM/Ca/Al bulk heterojunction structure. The devices of different active layer thicknesses were electrically studied using J-V curves and the Photo-Celiv technique. The obtained results show that LaPPS43 combined with PCBM is a promising system for photovoltaic devices. Device performance is discussed in terms of the mean drift distance x for charge carriers. Photophysical data showed that the excitonic species are all localized in the aggregated forms. The mechanism of exciton formation and dissociation is also discussed.

A dynamical system approach to data assimilation in chaotic models

The Assimilation in the Unstable Subspace (AUS) was introduced by Trevisan and Uboldi in 2004, and developed by Trevisan, Uboldi and Carrassi, to minimize the analysis and forecast errors by exploiting the flow-dependent instabilities of the forecast-analysis cycle system, which may be thought of as a system forced by observations. In the AUS scheme the assimilation is obtained by confining the analysis increment in the unstable subspace of the forecast-analysis cycle system so that it will have the same structure of the dominant instabilities of the system. The unstable subspace is estimated by Breeding on the Data Assimilation System (BDAS). AUS- BDAS has already been tested in realistic models and observational configurations, including a Quasi-Geostrophicmodel and a high dimensional, primitive equation ocean model; the experiments include both fixed and“adaptive”observations. In these contexts, the AUS-BDAS approach greatly reduces the analysis error, with reasonable computational costs for data assimilation with respect, for example, to a prohibitive full Extended Kalman Filter. This is a follow-up study in which we revisit the AUS-BDAS approach in the more basic, highly nonlinear Lorenz 1963 convective model. We run observation system simulation experiments in a perfect model setting, and with two types of model error as well: random and systematic. In the different configurations examined, and in a perfect model setting, AUS once again shows better efficiency than other advanced data assimilation schemes. In the present study, we develop an iterative scheme that leads to a significant improvement of the overall assimilation performance with respect also to standard AUS. In particular, it boosts the efficiency of regime’s changes tracking, with a low computational cost. Other data assimilation schemes need estimates of ad hoc parameters, which have to be tuned for the specific model at hand. In Numerical Weather Prediction models, tuning of parameters — and in particular an estimate of the model error covariance matrix — may turn out to be quite difficult. Our proposed approach, instead, may be easier to implement in operational models.

Business Clusters in Eastern Europe: Policy Analysis and Cluster Performance

Clusters have increasingly become an essential part of policy discourses at all levels, EU, national, regional, dealing with regional development, competitiveness, innovation, entrepreneurship, SMEs. These impressive efforts in promoting the concept of clusters on the policy-making arena have been accompanied by much less academic and scientific research work investigating the actual economic performance of firms in clusters, the design and execution of cluster policies and going beyond singular case studies to a more methodologically integrated and comparative approach to the study of clusters and their real-world impact. The theoretical background is far from being consolidated and there is a variety of methodologies and approaches for studying and interpreting this phenomenon while at the same time little comparability among studies on actual cluster performances. The conceptual framework of clustering suggests that they affect performance but theory makes little prediction as to the ultimate distribution of the value being created by clusters. This thesis takes the case of Eastern European countries for two reasons. One is that clusters, as coopetitive environments, are a new phenomenon as the previous centrally-based system did not allow for such types of firm organizations. The other is that, as new EU member states, they have been subject to the increased popularization of the cluster policy approach by the European Commission, especially in the framework of the National Reform Programmes related to the Lisbon objectives. The originality of the work lays in the fact that starting from an overview of theoretical contributions on clustering, it offers a comparative empirical study of clusters in transition countries. There have been very few examples in the literature that attempt to examine cluster performance in a comparative cross-country perspective. It adds to this an analysis of cluster policies and their implementation or lack of such as a way to analyse the way the cluster concept has been introduced to transition economies. Our findings show that the implementation of cluster policies does vary across countries with some countries which have embraced it more than others. The specific modes of implementation, however, are very similar, based mostly on soft measures such as funding for cluster initiatives, usually directed towards the creation of cluster management structures or cluster facilitators. They are essentially founded on a common assumption that the added values of clusters is in the creation of linkages among firms, human capital, skills and knowledge at the local level, most often perceived as the regional level. Often times geographical proximity is not a necessary element in the application process and cluster application are very similar to network membership. Cluster mapping is rarely a factor in the selection of cluster initiatives for funding and the relative question about critical mass and expected outcomes is not considered. In fact, monitoring and evaluation are not elements of the cluster policy cycle which have received a lot of attention. Bulgaria and the Czech Republic are the countries which have implemented cluster policies most decisively, Hungary and Poland have made significant efforts, while Slovakia and Romania have only sporadically and not systematically used cluster initiatives. When examining whether, in fact, firms located within regional clusters perform better and are more efficient than similar firms outside clusters, we do find positive results across countries and across sectors. The only country with negative impact from being located in a cluster is the Czech Republic.