Discordant responses to potent antiretroviral treatment in previously naive HIV-1-infected adults initiating treatment in resource-constrained countries: the antiretroviral therapy in low-income countries (ART-LINC) collaboration

OBJECTIVES: To assess the frequency of and risk factors for discordant responses at 6 months on highly active antiretroviral therapy (HAART) in previously treatment-naive HIV patients from resource-limited countries. METHODS: The Antiretroviral Therapy in Low-Income Countries Collaboration is a network of clinics providing care and treatment to HIV-infected patients in Africa, Latin America, and Asia. Patients who initiated therapy between 1996 and 2004, were aged 16 years or older, and had a baseline CD4 cell count were included in this analysis. Responses were defined based on plasma viral load (PVL) and CD4 cell count at 6 months as complete virologic and immunologic (VR(+)IR(+)), virologic only (VR(+)IR(-)), immunologic only (VR(-)IR(+)), and nonresponse (VR(-)IR(-)). Multinomial logistic regression was used to assess the association between therapy responses and clinical and demographic variables. RESULTS: Of the 3111 patients eligible for analysis, 1914 had available information at 6 months of therapy: 1074 (56.1%) were VR(+)IR(+), 364 (19.0%) were VR(+)IR(-), 283 (14.8%) were (VR(-)IR(+)), and 193 (10.1%) were VR(-)IR(-). OF THE 3111 patients eligible for analysis, 1914 had available information at 6 months of therapy: 1074 (56.1%) were VRIR, 364 (19.0%) were VRIR, 283 (14.8%) were (VRIR), and 193 (10.1%) were VRIR. Compared with complete responders, virologic-only responders were older, had a higher baseline CD4 cell count, had a lower baseline PVL, and were more likely to have received a nonstandard HAART regimen; immunologic-only responders were younger, had a lower baseline CD4 cell count, had a higher baseline PVL, and were more likely to have received a protease inhibitor-based regimen. CONCLUSIONS: The frequency of and risk factors for discordant responses were comparable to those observed in developed countries. Longer follow-up is needed to assess the long-term impact of discordant responses on mortality in these resource-limited settings.

Exploring the periodicity of cardiovascular events in Switzerland: Variation in deaths and hospitalizations across seasons, day of the week and hour of the day

Purpose The purpose of this study is to explore the periodical patterns of events and deaths related to cardiovascular disease (CVD), acute myocardial infarction (AMI) and stroke in Swiss adults (≥18years). Methods Mortality data for period 1969–2007 (N=869,863 CVD events) and hospitalization data for period 1997–2008 (N=959,990 CVD events) were used. The annual, weekly and circadian distribution of CVD-related deaths and events were assessed. Multivariate analysis was conducted using multinomial logistic regression adjusting for age, gender and calendar year and considering deaths from respiratory diseases, accidents or other causes as competitive events. Results CVD deaths and hospitalizations occurred less frequently in the summer months. Similar patterns were found for AMI and stroke. No significant weekly variation for CVD deaths was found. Stratification by age and gender showed subjects aged <65years to present a higher probability of dying on Mondays and Saturday, only for men. This finding was confirmed after multivariate adjustment. Finally, a circadian variation in CVD mortality was observed, with a first peak in the morning (8–12am) and a smaller second peak in the late afternoon (2–6pm). This pattern persisted after multivariate adjustment and was more pronounced for AMI than for stroke. Conclusion There is a periodicity of hospitalizations and deaths related to CVD, AMI and stroke in Switzerland. This pattern changes slightly according to the age and sex of the subjects. Although the underlying mechanisms are not fully identified, preventive measures should take into account these aspects to develop better strategies of prevention and management of CVD.

Adult parent-child relationships: Relationship quality, support, and reciprocity

In accordance with Bengtson's model of intergenerational solidarity (e.g. Bengtson & Roberts, 1991), the interrelations between adult daughters' family values, their perception of the relationship quality with their parents, the support they reported to give to and to receive from their parents, and their perception of reciprocity in intergenerational support exchange were investigated for N = 265 middle-aged women in Germany. It was also asked whether the support given to parents and perceived reciprocity are related to daughters' felt burden as a result of their support. Cross-sectional, self-report data were examined with multiple and multinomial logistic regression analyses. The analyses revealed positive relations between family values, relationship quality, and support to parents. Perceived reciprocity was associated with the exchange of intergenerational support and imbalance in support had negative effects on the relationship quality. Felt burden was predicted by the extent of support and the perceived reciprocity. However, specific correlational patterns depending on the kind of support as well as differences in the importance of mother and father occurred. The findings are discussed against the background of the meaning of family obligations and reciprocity in a Western culture.

Genotype-specific risk factors for Staphylococcus aureus in Swiss dairy herds with an elevated yield-corrected herd somatic cell count

Bovine mastitis is a frequent problem in Swiss dairy herds. One of the main pathogens causing significant economic loss is Staphylococcus aureus. Various Staph. aureus genotypes with different biological properties have been described. Genotype B (GTB) of Staph. aureus was identified as the most contagious and one of the most prevalent strains in Switzerland. The aim of this study was to identify risk factors associated with the herd-level presence of Staph. aureus GTB and Staph. aureus non-GTB in Swiss dairy herds with an elevated yield-corrected herd somatic cell count (YCHSCC). One hundred dairy herds with a mean YCHSCC between 200,000 and 300,000cells/mL in 2010 were recruited and each farm was visited once during milking. A standardized protocol investigating demography, mastitis management, cow husbandry, milking system, and milking routine was completed during the visit. A bulk tank milk (BTM) sample was analyzed by real-time PCR for the presence of Staph. aureus GTB to classify the herds into 2 groups: Staph. aureus GTB-positive and Staph. aureus GTB-negative. Moreover, quarter milk samples were aseptically collected for bacteriological culture from cows with a somatic cell count ≥150,000cells/mL on the last test-day before the visit. The culture results allowed us to allocate the Staph. aureus GTB-negative farms to Staph. aureus non-GTB and Staph. aureus-free groups. Multivariable multinomial logistic regression models were built to identify risk factors associated with the herd-level presence of Staph. aureus GTB and Staph. aureus non-GTB. The prevalence of Staph. aureus GTB herds was 16% (n=16), whereas that of Staph. aureus non-GTB herds was 38% (n=38). Herds that sent lactating cows to seasonal communal pastures had significantly higher odds of being infected with Staph. aureus GTB (odds ratio: 10.2, 95% CI: 1.9-56.6), compared with herds without communal pasturing. Herds that purchased heifers had significantly higher odds of being infected with Staph. aureus GTB (rather than Staph. aureus non-GTB) compared with herds without purchase of heifers. Furthermore, herds that did not use udder ointment as supportive therapy for acute mastitis had significantly higher odds of being infected with Staph. aureus GTB (odds ratio: 8.5, 95% CI: 1.6-58.4) or Staph. aureus non-GTB (odds ratio: 6.1, 95% CI: 1.3-27.8) than herds that used udder ointment occasionally or regularly. Herds in which the milker performed unrelated activities during milking had significantly higher odds of being infected with Staph. aureus GTB (rather than Staph. aureus non-GTB) compared with herds in which the milker did not perform unrelated activities at milking. Awareness of 4 potential risk factors identified in this study guides implementation of intervention strategies to improve udder health in both Staph. aureus GTB and Staph. aureus non-GTB herds.

Übergangslösungen beim Eintritt in die Schweizer Berufsbildung: Brückenschlag oder Sackgasse?

In der Schweiz finden viele Jugendliche keinen direkten Zugang zu einer beruflichen Grundbildung; vielmehr durchlaufen sie zunächst eine so genannte Übergangslösung oder ein Brückenangebot wie z.B. ein zehntes Schuljahr. Wir beleuchten in diesem Beitrag zum einen, wie schulische, individuelle, familiäre und kontextuell-systemische Faktoren den Übertritt in solche Brückenangebote beeinflussen. Zum anderen gehen wir der Frage nach, wie sich ein verzögerter Einstieg via ein Brückenangebot auf die Chance auswirkt, einen Abschluss der Sekundarstufe II zu erwerben. Die empirische Analyse stützt sich auf die TREE-Studie, welche eine Kohorte von Schulentlassenen des Jahres 2000 längsschnittlich beobachtet. Wir modellieren dabei zunächst die interessierenden Übertrittsprozesse mittels einer multinomialen logistischen Regression, um dann mittels Propensity Score Matching deren Wirkung auf die nachobligatorischen Bildungschancen abzuschätzen.

An analysis of IN.PACT DEEP randomized trial on the limitations of the societal guidelines-recommended hemodynamic parameters to diagnose critical limb ischemia.

OBJECTIVE Recent small single-center data indicate that the current hemodynamic parameters used to diagnose critical limb ischemia are insensitive. We investigated the validity of the societal guidelines-recommended hemodynamic parameters against core laboratory-adjudicated angiographic data from the multicenter IN.PACT DEEP (RandomIzed AmPhirion DEEP DEB vs StAndard PTA for the treatment of below the knee Critical limb ischemia) Trial. METHODS Of the 358 patients in the IN.PACT DEEP Trial to assess drug-eluting balloon vs standard balloon angioplasty for infrapopliteal disease, 237 had isolated infrapopliteal disease with an available ankle-brachial index (ABI), and only 40 of the latter had available toe pressure measurements. The associations between ABI, ankle pressure, and toe pressure with tibial runoff, Rutherford category, and plantar arch were examined according to the cutoff points recommended by the societal guidelines. Abnormal tibial runoff was defined as severely stenotic (≥70%) or occluded and scored as one-, two-, or three-vessel disease. A stenotic or occluded plantar arch was considered abnormal. RESULTS Only 14 of 237 patients (6%) had an ABI <0.4. Abnormal ankle pressure, defined as <50 mm Hg if Rutherford category 4 and <70 mm Hg if Rutherford category 5 or 6, was found only in 37 patients (16%). Abnormal toe pressure, defined as <30 mm Hg if Rutherford category 4 and <50 mm Hg if Rutherford category 5 or 6, was found in 24 of 40 patients (60%) with available measurements. Importantly, 29% of these 24 patients had an ABI within normal reference ranges. A univariate multinomial logistic regression found no association between the above hemodynamic parameters and the number of diseased infrapopliteal vessels. However, there was a significant paradoxic association where patients with Rutherford category 6 had higher ABI and ankle pressure than those with Rutherford category 5. Similarly, there was no association between ABI and pedal arch patency. CONCLUSIONS The current recommended hemodynamic parameters fail to identify a significant portion of patients with lower extremity ulcers and angiographically proven severe disease. Toe pressure has better sensitivity and should be considered in all patients with critical limb ischemia.

Qualifikationsnachfrage und Arbeitsmarkteintritt in der Schweiz: Arbeit im erlernten Beruf, Berufswechsel oder Arbeitslosigkeit

Berufsorientierte Bildungssysteme sind auf die Vermittlung von spezialisierten beruflichen Qualifikationen ausgelegt. Werden diese nach Abschluss einer beruflichen Grundbildung auf dem Arbeitsmarkt wenig nachgefragt, riskieren die Absolventen, die erworbenen berufsspezifischen Qualifikationen nicht verwerten zu können. Dies trifft nicht nur zu, wenn Arbeitsmarkteinsteiger arbeitslos werden, sondern auch, wenn sie den Beruf wechseln müssen. Für die drei verschiedenen Optionen des Arbeitsmarkteinstiegs – Arbeit im erlernten Beruf, Berufswechsel und Arbeitslosigkeit – wird erstens untersucht, welche Bedeutung das individuell passende und das fachfremde Stellenangebot hat. Zweitens wird analysiert, wie eine unterschiedlich ausgeprägte Nachfrage nach fachspezifischen Qualifikationen die Bedeutung ausbildungsbezogener und individueller Merkmale für den Berufseinstieg verändert. Die Schweiz mit ihrem berufsorientierten Bildungssystem und berufsfachlich segmentieren Arbeitsmarkt dient als empirische Referenz. Die multinominalen logistischen Regressionsmodelle basieren auf den Daten des Schweizer Jugendpanels PISA2000/TREE. Die Individualdaten von Lehrabgänger werden auf Berufsebene, zeitpunkt- und regionsspezifisch mit dem individuell passenden und fachfremden Stellenangebot verknüpft, das auf den Stelleninseratendaten des Stellenmarktmonitors Schweiz (SMM) beruht. Dank dieser Verknüpfung von Angebot und Nachfrage nach beruflichen Qualifikationen auf der Mikroebene kann zum ersten Mal die grundlegende Bedeutung der Personalnachfrage für den Berufseinstieg nachgewiesen werden.

Does parental monitoring influence the use of alcohol and drugs among inner city 7th grade students?

Objective. To examine associations between parental monitoring and adolescent alcohol/drug use. ^ Methods. 981 7th grade students from 10 inner-city middle schools were surveyed at the 3 month follow-up of an HIV, STD, and pregnancy prevention program. Data from 549 control subjects were used for analyses. Multinomial logistic regression was used to examine associations between five parental monitoring variables and substance use, coded as: low risk [never drank alcohol or used drugs (0)], moderate risk [drank alcohol, no drug use (1)], and high risk [both drank alcohol and used drugs or just used drugs (2)]. ^ Results. Participants were 58.3% female, 39.6% African American, 43.8% Hispanic, mean age 13.3 years. Lifetime alcohol use was 47.9%. Lifetime drug use was 14.9%. Adjusted for gender, age, race, and family structure, each individual parental monitoring variable (perceived parental monitoring, less permissive parental monitoring, greater supervision (public places), greater supervision (teen clubs), and less time spent with older teens) was significant and protective for the moderate and high risk groups. When all 5 variables were entered into a single model, only perceived parental monitoring was significantly associated (OR=0.40, 95% CI 0.29-0.55) for the moderate risk group. For the high risk group, 3 variables were significantly protective (perceived parental monitoring OR=0.28, CI 0.18-0.42, less time spent with older teens OR=0.75, CI 0.60-0.93, and greater supervision (public places) OR=0.79, CI 0.64-0.99). ^ Conclusion. The association between parental monitoring and substance abuse is complex and varied for different risk levels. Implications for intervention development are addressed. ^

The impact of communication and cultural diversity in utilizing dental services among Saudi Arabian students in U.S.A.

Objectives: The purpose of this study is to understand the perceived effects of patient-dental staff communication and cultural diversity on the utilization of dental services in the U.S. by Saudi Arabian students who live in the U.S. and enrolled into the King Abdullah Scholarship program. Methods: The study design was an analytical cross-sectional study. Data for this study was obtained from the Saudi Dental Servicers Utilization Survey, a voluntary internet survey available online for one month through Facebook. Ordered logistic regression analyses and multinomial logistic regression analyses were used to measure the relationships between patient-dental staff communication and cultural diversity on the utilization of dental services. Results: Eight hundred and forty-seven responses were analyzed for this study. Overall, the majority of Saudi students reported having excellent communication experience with dental providers in the U.S. More than 58% of respondents reported at least one regular dental visit last year. Factors that influenced the use of regular dental care were: dentist's explanation of treatment plan, response of dental staff to patient's needs, respectful and polite dental staff, dental staff kindness, availability of up-to-date equipment, and overall communication with dentist. However, the utilization of emergency dental care was not associated with any measurement of patient-dental provider communication. Overall future utilization of dental care is associated with all aspects of patient-dental staff communication measured in this survey. Furthermore, more utilization of regular dental care was related to respondent's perception of the importance of trustworthiness dental staff and the importance of a dentist's reputation was only marginally associated. Respondent's perception of dentist's reputation was associated with more use of emergency dental services. Respondents are more likely to anticipate using dental care in the future if they perceived trustworthiness dental staff, and the dentist's reputation as influencing factors to their usage of dental services. Conclusions: Patient-dental staff communication was partially associated with utilization of regular dental care, not associated with utilization of emergency dental care, and broadly associated with anticipated future utilization of dental care. In addition, trustworthy dental staff, and a dentist's reputation were considered to be strong influencing factors towards utilization of dental services.^

Breast cancer risk factors among Mexican-American women

Introduction: The average age of onset of breast cancer among Hispanic women is 50 years, more than a decade earlier than non-Hispanic white women. Age at diagnosis is an important prognostic factor for breast cancer; younger age at onset is more likely to be associated with advanced disease, poorer prognosis, hormone receptor negative breast tumors, and a greater likelihood of hereditary breast cancer. Studies of breast cancer risk factors including reproductive risk factors, family history of breast cancer, and breast cancer subtype have been conducted predominately in non-Hispanic whites. Breast cancer is a heterogeneous disease with the presence of clinically, biologically, and epidemiologically distinct subtypes that also differ with respect to their risk factors. The associations between reproductive risk factors and family history of breast cancer have been well documented in the literature. However, only a few studies have assessed these associations with breast cancer subtype in Hispanic populations. Methods: To assess the associations between reproductive risk factors and family history of breast cancer we conducted three separate studies. First, we conducted a case-control study of 172 Mexican-American breast cancer cases and 344 age matched controls residing in Harris County, TX to assess reproductive and other risk factors. We conducted logistic regression analysis to assess differences in cases and controls adjusted for age at diagnosis and birthplace and then we conducted a multinomial logistic regression analysis to compare reproductive risk factors among the breast tumor subtypes. In a second study, we identified 139 breast cancer patients with a first- or second-degree family history of breast cancer and 298 without a family history from the ELLA Bi-National Breast Cancer Study. In this analysis, we also computed a multinomial logistic regression to evaluate associations between family history of breast cancer and breast cancer subtypes, and logistic regression to estimate associations between breast cancer screening practices with family history of breast cancer. In the final study, we employed a cross-sectional study design in 7279 Mexican-American women in the Mano a Mano Cohort Study. We evaluated associations with family history of breast cancer and breast cancer risk factors including body mass index (BMI), lifestyle factors, migration history, and adherence to American Cancer Society (ACS) guidelines. Results: In the results of our first analyses, reproductive risk factors differed in the magnitude and direction of associations when stratified by age and birthplace among cases and controls. In our second study, family history of breast cancer, and having at least one relative diagnosed at an early age (<50 years) was associated with triple negative breast cancer (TNBC). Mammography prior to receiving a breast cancer diagnosis was associated with family history of breast cancer. In our third study that assessed lifestyle factors, migration history and family history of breast cancer; we found that women with a first-degree family history of breast cancer were more overweight or obese compared with their counterparts without a family history. There was no indication that having a family history contributed to women practicing healthier lifestyle behaviors and/or adhering to the ACS guidelines for cancer prevention. Conclusions: We observed that among Mexican-American women, reproductive risk factors were associated with breast cancer where the woman was born (US or Mexico). Having a family history of breast cancer, especially having either a first- or second-degree relative diagnosed at a younger age, was strongly associated with TNBC subtype. These results are consistent with other published studies in this area. Further, our results indicate that women with strong family histories of breast cancer are more likely to undertake mammography but not to engage in healthier lifestyle behaviors.^

Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers: An application to predict the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39)

Multi-dimensional Bayesian network classifiers (MBCs) are probabilistic graphical models recently proposed to deal with multi-dimensional classification problems, where each instance in the data set has to be assigned to more than one class variable. In this paper, we propose a Markov blanket-based approach for learning MBCs from data. Basically, it consists of determining the Markov blanket around each class variable using the HITON algorithm, then specifying the directionality over the MBC subgraphs. Our approach is applied to the prediction problem of the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson’s Disease Questionnaire (PDQ-39) in order to estimate the health-related quality of life of Parkinson’s patients. Fivefold cross-validation experiments were carried out on randomly generated synthetic data sets, Yeast data set, as well as on a real-world Parkinson’s disease data set containing 488 patients. The experimental study, including comparison with additional Bayesian network-based approaches, back propagation for multi-label learning, multi-label k-nearest neighbor, multinomial logistic regression, ordinary least squares, and censored least absolute deviations, shows encouraging results in terms of predictive accuracy as well as the identification of dependence relationships among class and feature variables.

Multi-dimensional classification using Bayesian networks for stationary and evolving streaming data

Hoy en día, con la evolución continua y rápida de las tecnologías de la información y los dispositivos de computación, se recogen y almacenan continuamente grandes volúmenes de datos en distintos dominios y a través de diversas aplicaciones del mundo real. La extracción de conocimiento útil de una cantidad tan enorme de datos no se puede realizar habitualmente de forma manual, y requiere el uso de técnicas adecuadas de aprendizaje automático y de minería de datos. La clasificación es una de las técnicas más importantes que ha sido aplicada con éxito a varias áreas. En general, la clasificación se compone de dos pasos principales: en primer lugar, aprender un modelo de clasificación o clasificador a partir de un conjunto de datos de entrenamiento, y en segundo lugar, clasificar las nuevas instancias de datos utilizando el clasificador aprendido. La clasificación es supervisada cuando todas las etiquetas están presentes en los datos de entrenamiento (es decir, datos completamente etiquetados), semi-supervisada cuando sólo algunas etiquetas son conocidas (es decir, datos parcialmente etiquetados), y no supervisada cuando todas las etiquetas están ausentes en los datos de entrenamiento (es decir, datos no etiquetados). Además, aparte de esta taxonomía, el problema de clasificación se puede categorizar en unidimensional o multidimensional en función del número de variables clase, una o más, respectivamente; o también puede ser categorizado en estacionario o cambiante con el tiempo en función de las características de los datos y de la tasa de cambio subyacente. A lo largo de esta tesis, tratamos el problema de clasificación desde tres perspectivas diferentes, a saber, clasificación supervisada multidimensional estacionaria, clasificación semisupervisada unidimensional cambiante con el tiempo, y clasificación supervisada multidimensional cambiante con el tiempo. Para llevar a cabo esta tarea, hemos usado básicamente los clasificadores Bayesianos como modelos. La primera contribución, dirigiéndose al problema de clasificación supervisada multidimensional estacionaria, se compone de dos nuevos métodos de aprendizaje de clasificadores Bayesianos multidimensionales a partir de datos estacionarios. Los métodos se proponen desde dos puntos de vista diferentes. El primer método, denominado CB-MBC, se basa en una estrategia de envoltura de selección de variables que es voraz y hacia delante, mientras que el segundo, denominado MB-MBC, es una estrategia de filtrado de variables con una aproximación basada en restricciones y en el manto de Markov. Ambos métodos han sido aplicados a dos problemas reales importantes, a saber, la predicción de los inhibidores de la transcriptasa inversa y de la proteasa para el problema de infección por el virus de la inmunodeficiencia humana tipo 1 (HIV-1), y la predicción del European Quality of Life-5 Dimensions (EQ-5D) a partir de los cuestionarios de la enfermedad de Parkinson con 39 ítems (PDQ-39). El estudio experimental incluye comparaciones de CB-MBC y MB-MBC con los métodos del estado del arte de la clasificación multidimensional, así como con métodos comúnmente utilizados para resolver el problema de predicción de la enfermedad de Parkinson, a saber, la regresión logística multinomial, mínimos cuadrados ordinarios, y mínimas desviaciones absolutas censuradas. En ambas aplicaciones, los resultados han sido prometedores con respecto a la precisión de la clasificación, así como en relación al análisis de las estructuras gráficas que identifican interacciones conocidas y novedosas entre las variables. La segunda contribución, referida al problema de clasificación semi-supervisada unidimensional cambiante con el tiempo, consiste en un método nuevo (CPL-DS) para clasificar flujos de datos parcialmente etiquetados. Los flujos de datos difieren de los conjuntos de datos estacionarios en su proceso de generación muy rápido y en su aspecto de cambio de concepto. Es decir, los conceptos aprendidos y/o la distribución subyacente están probablemente cambiando y evolucionando en el tiempo, lo que hace que el modelo de clasificación actual sea obsoleto y deba ser actualizado. CPL-DS utiliza la divergencia de Kullback-Leibler y el método de bootstrapping para cuantificar y detectar tres tipos posibles de cambio: en las predictoras, en la a posteriori de la clase o en ambas. Después, si se detecta cualquier cambio, un nuevo modelo de clasificación se aprende usando el algoritmo EM; si no, el modelo de clasificación actual se mantiene sin modificaciones. CPL-DS es general, ya que puede ser aplicado a varios modelos de clasificación. Usando dos modelos diferentes, el clasificador naive Bayes y la regresión logística, CPL-DS se ha probado con flujos de datos sintéticos y también se ha aplicado al problema real de la detección de código malware, en el cual los nuevos ficheros recibidos deben ser continuamente clasificados en malware o goodware. Los resultados experimentales muestran que nuestro método es efectivo para la detección de diferentes tipos de cambio a partir de los flujos de datos parcialmente etiquetados y también tiene una buena precisión de la clasificación. Finalmente, la tercera contribución, sobre el problema de clasificación supervisada multidimensional cambiante con el tiempo, consiste en dos métodos adaptativos, a saber, Locally Adpative-MB-MBC (LA-MB-MBC) y Globally Adpative-MB-MBC (GA-MB-MBC). Ambos métodos monitorizan el cambio de concepto a lo largo del tiempo utilizando la log-verosimilitud media como métrica y el test de Page-Hinkley. Luego, si se detecta un cambio de concepto, LA-MB-MBC adapta el actual clasificador Bayesiano multidimensional localmente alrededor de cada nodo cambiado, mientras que GA-MB-MBC aprende un nuevo clasificador Bayesiano multidimensional. El estudio experimental realizado usando flujos de datos sintéticos multidimensionales indica los méritos de los métodos adaptativos propuestos. ABSTRACT Nowadays, with the ongoing and rapid evolution of information technology and computing devices, large volumes of data are continuously collected and stored in different domains and through various real-world applications. Extracting useful knowledge from such a huge amount of data usually cannot be performed manually, and requires the use of adequate machine learning and data mining techniques. Classification is one of the most important techniques that has been successfully applied to several areas. Roughly speaking, classification consists of two main steps: first, learn a classification model or classifier from an available training data, and secondly, classify the new incoming unseen data instances using the learned classifier. Classification is supervised when the whole class values are present in the training data (i.e., fully labeled data), semi-supervised when only some class values are known (i.e., partially labeled data), and unsupervised when the whole class values are missing in the training data (i.e., unlabeled data). In addition, besides this taxonomy, the classification problem can be categorized into uni-dimensional or multi-dimensional depending on the number of class variables, one or more, respectively; or can be also categorized into stationary or streaming depending on the characteristics of the data and the rate of change underlying it. Through this thesis, we deal with the classification problem under three different settings, namely, supervised multi-dimensional stationary classification, semi-supervised unidimensional streaming classification, and supervised multi-dimensional streaming classification. To accomplish this task, we basically used Bayesian network classifiers as models. The first contribution, addressing the supervised multi-dimensional stationary classification problem, consists of two new methods for learning multi-dimensional Bayesian network classifiers from stationary data. They are proposed from two different points of view. The first method, named CB-MBC, is based on a wrapper greedy forward selection approach, while the second one, named MB-MBC, is a filter constraint-based approach based on Markov blankets. Both methods are applied to two important real-world problems, namely, the prediction of the human immunodeficiency virus type 1 (HIV-1) reverse transcriptase and protease inhibitors, and the prediction of the European Quality of Life-5 Dimensions (EQ-5D) from 39-item Parkinson’s Disease Questionnaire (PDQ-39). The experimental study includes comparisons of CB-MBC and MB-MBC against state-of-the-art multi-dimensional classification methods, as well as against commonly used methods for solving the Parkinson’s disease prediction problem, namely, multinomial logistic regression, ordinary least squares, and censored least absolute deviations. For both considered case studies, results are promising in terms of classification accuracy as well as regarding the analysis of the learned MBC graphical structures identifying known and novel interactions among variables. The second contribution, addressing the semi-supervised uni-dimensional streaming classification problem, consists of a novel method (CPL-DS) for classifying partially labeled data streams. Data streams differ from the stationary data sets by their highly rapid generation process and their concept-drifting aspect. That is, the learned concepts and/or the underlying distribution are likely changing and evolving over time, which makes the current classification model out-of-date requiring to be updated. CPL-DS uses the Kullback-Leibler divergence and bootstrapping method to quantify and detect three possible kinds of drift: feature, conditional or dual. Then, if any occurs, a new classification model is learned using the expectation-maximization algorithm; otherwise, the current classification model is kept unchanged. CPL-DS is general as it can be applied to several classification models. Using two different models, namely, naive Bayes classifier and logistic regression, CPL-DS is tested with synthetic data streams and applied to the real-world problem of malware detection, where the new received files should be continuously classified into malware or goodware. Experimental results show that our approach is effective for detecting different kinds of drift from partially labeled data streams, as well as having a good classification performance. Finally, the third contribution, addressing the supervised multi-dimensional streaming classification problem, consists of two adaptive methods, namely, Locally Adaptive-MB-MBC (LA-MB-MBC) and Globally Adaptive-MB-MBC (GA-MB-MBC). Both methods monitor the concept drift over time using the average log-likelihood score and the Page-Hinkley test. Then, if a drift is detected, LA-MB-MBC adapts the current multi-dimensional Bayesian network classifier locally around each changed node, whereas GA-MB-MBC learns a new multi-dimensional Bayesian network classifier from scratch. Experimental study carried out using synthetic multi-dimensional data streams shows the merits of both proposed adaptive methods.

DETERMINANTE DE COMPOSIÇÃO DE CONSELHO DE ADMINISTRAÇÃO EM PEQUENAS E MÉDIAS EMPRESAS DE SOCIEDADE ANÔNIMA DE CAPITAL FECHADO DA REGIÃO DO ABC

O principal objetivo deste estudo é analisar os determinantes de composição de Conselho de Administração em pequenas e médias empresas de sociedade anônima de capital fechado da região do ABC paulista. A razão de iniciar este trabalho, surgiu devido à constatação de que no Brasil existem poucos artigos e dissertações que tratam de composição de Conselho e os elaborados no exterior se centralizaram na composição em termos de tamanho e tipos de diretores, de desempenho financeiro, de independência etc., mas nenhum deles focou nas determinantes de composição de pequena e média empresa. Portanto, baseando-se nas observações acima, se efetuou pesquisa de campo para responder à seguinte problemática Que determinante(s) estabelece(m) a composição de Conselho de Administração de Pequenas e Médias Empresas de Sociedade Anônima de Empresas da Região do ABC paulista? Partindo dessa problemática, se estabeleceu as seguintes hipóteses: se o poder e a influência do CEO/Presidente do Conselho em empresas de pequeno e médio porte são grandes, então existem baixas possibilidades de ter Conselheiros Externos; se houver segregação de cargos entre o CEO e o Presidente do Conselho e o CEO estiver interessado em preservar a sua atuação, então há probabilidade de escolher Conselheiros Internos; se houver segregação de cargos entre o CEO e o Presidente do Conselho e o CEO estiver interessado na eficiência, orientação e na necessidade de recursos externos, então há probabilidade de escolher Conselheiros Externos; se a empresa está no Ciclo de Vida Expansão e Maturidade- , então há possibilidades de adotarem Conselheiros Externos.(AU)

DETERMINANTE DE COMPOSIÇÃO DE CONSELHO DE ADMINISTRAÇÃO EM PEQUENAS E MÉDIAS EMPRESAS DE SOCIEDADE ANÔNIMA DE CAPITAL FECHADO DA REGIÃO DO ABC

O principal objetivo deste estudo é analisar os determinantes de composição de Conselho de Administração em pequenas e médias empresas de sociedade anônima de capital fechado da região do ABC paulista. A razão de iniciar este trabalho, surgiu devido à constatação de que no Brasil existem poucos artigos e dissertações que tratam de composição de Conselho e os elaborados no exterior se centralizaram na composição em termos de tamanho e tipos de diretores, de desempenho financeiro, de independência etc., mas nenhum deles focou nas determinantes de composição de pequena e média empresa. Portanto, baseando-se nas observações acima, se efetuou pesquisa de campo para responder à seguinte problemática Que determinante(s) estabelece(m) a composição de Conselho de Administração de Pequenas e Médias Empresas de Sociedade Anônima de Empresas da Região do ABC paulista? Partindo dessa problemática, se estabeleceu as seguintes hipóteses: se o poder e a influência do CEO/Presidente do Conselho em empresas de pequeno e médio porte são grandes, então existem baixas possibilidades de ter Conselheiros Externos; se houver segregação de cargos entre o CEO e o Presidente do Conselho e o CEO estiver interessado em preservar a sua atuação, então há probabilidade de escolher Conselheiros Internos; se houver segregação de cargos entre o CEO e o Presidente do Conselho e o CEO estiver interessado na eficiência, orientação e na necessidade de recursos externos, então há probabilidade de escolher Conselheiros Externos; se a empresa está no Ciclo de Vida Expansão e Maturidade- , então há possibilidades de adotarem Conselheiros Externos.(AU)

Distortion of self-image: risk factor for obesity in children and teenagers

Introduction: Self-image is important in the behaviour and lifestyle of children and adolescents. Analysing the self-image they have and the factors that might influence their distortion, can be used to prevent problems of obesity and anorexia. The main objective of present publication was to analyse the risk factors that may contribute to self-image distortion. Material and Methods: A descriptive survey study was conducted among 659 children and adolescents in two social classes (low and medium-high), measuring height and weight, calculating BMI percentile for age and gender. Body image and self-perception were registered. Results: The percentage of overweight-obesity is higher in scholars (41.8% boys, 28.7% girls) than in adolescents (30.1% and 22.2% respectively), with no difference between socioeconomic classes. The multinomial logistic regression analysis gives a risk of believing thinner higher (p=0.000) among boys OR=2.9(95%CI:1.43-3.37), school (p=0.000) OR=2.42(95%CI:1.56-3.76) and much lower (p=0.000) between normally nourished OR=0.08(95%CI:0.05-0.13), with no differences according to socioeconomic status. The risk of believing fatter is lower (p=0.000) between boys OR=0.28(95%CI:0.14-0.57), school(p=0.072) OR=0.54(95%CI:0.27-1.6), and much higher among underweight (p=0.000) OR=9x108(95% CI:4x108-19x108). Conclusions: Are risk factors of believing thinner: males, being in a group of schoolchildren and overweight-obesity. Conversely, are risk factors of believing fatter: females, teen and above all, be thin.