CDKN2A is not the principal target of deletions on the short arm of chromosome 9 in neuroendocrine (Merkel cell) carcinoma of the skin

The majority of small-cell lung cancers (SCLCs) express p16 but not pRb, Given our previous study showing loss of pRb in Merkel cell carcinoma (MCC)/neuroendocrine carcinoma of the skin and the clinicopathological similarities between SCLC acid MCC, we wished to determine if this was also the case in MCC, Twenty-nine MCC specimens from 23 patients were examined for deletions at 10 loci on 9p and I on 9p. No loss of heterozygosity (LO H) was peen in 9 patients including 2 for which tumour and cell line DNAs were examined. Four patients had LOH for all informative loci on 9p, Ten tumours showed more limited regions of loss on 9p, and from these 2 common regions of deletion were determined, Half of all informative cases had LOH at D95168, the most telomeric marker examined, and 3 specimens showed loss of only D9S168, A second region (InFNA-D9S126) showed L0H in 10(44%) cases, and case MCC26 showed LOH for only D9S126, implicating genes centromeric of the CDKN2A locus. No mutations in the coding regions of p16 were seen in 7 cell lines tested, and reactivity to anti-p16 antibody was seen in all Il tumour specimens examined and in 6 of 7 cell lines from 6 patients. Furthermore, all cell lines examined reacted with anti-p 14' antibody, These results suggest that neither transcript of the CDKN2A locus is the target of deletions on 9p in MCC and imply the existence of tumour-suppressor genes mapping both centromeric and telomeric of this locus. (C) 2001 Wiley-Liss, Inc.

Supervisory control of wastewater treatment plants by combining principal component analysis and fuzzy c-means clustering

In this paper a methodology for integrated multivariate monitoring and control of biological wastewater treatment plants during extreme events is presented. To monitor the process, on-line dynamic principal component analysis (PCA) is performed on the process data to extract the principal components that represent the underlying mechanisms of the process. Fuzzy c-means (FCM) clustering is used to classify the operational state. Performing clustering on scores from PCA solves computational problems as well as increases robustness due to noise attenuation. The class-membership information from FCM is used to derive adequate control set points for the local control loops. The methodology is illustrated by a simulation study of a biological wastewater treatment plant, on which disturbances of various types are imposed. The results show that the methodology can be used to determine and co-ordinate control actions in order to shift the control objective and improve the effluent quality.

Adaptive multiscale principal components analysis for online monitoring of wastewater treatment

Fault detection and isolation (FDI) are important steps in the monitoring and supervision of industrial processes. Biological wastewater treatment (WWT) plants are difficult to model, and hence to monitor, because of the complexity of the biological reactions and because plant influent and disturbances are highly variable and/or unmeasured. Multivariate statistical models have been developed for a wide variety of situations over the past few decades, proving successful in many applications. In this paper we develop a new monitoring algorithm based on Principal Components Analysis (PCA). It can be seen equivalently as making Multiscale PCA (MSPCA) adaptive, or as a multiscale decomposition of adaptive PCA. Adaptive Multiscale PCA (AdMSPCA) exploits the changing multivariate relationships between variables at different time-scales. Adaptation of scale PCA models over time permits them to follow the evolution of the process, inputs or disturbances. Performance of AdMSPCA and adaptive PCA on a real WWT data set is compared and contrasted. The most significant difference observed was the ability of AdMSPCA to adapt to a much wider range of changes. This was mainly due to the flexibility afforded by allowing each scale model to adapt whenever it did not signal an abnormal event at that scale. Relative detection speeds were examined only summarily, but seemed to depend on the characteristics of the faults/disturbances. The results of the algorithms were similar for sudden changes, but AdMSPCA appeared more sensitive to slower changes.

Characterization of microsatellite loci in Anopheles flavirostris, the principal malaria vector in the Philippines

Microsatellites were isolated and characterized from Anopheles flavirostris, the principal malaria vector in the Philippines. Fifty of the 150 positive clones sequenced contained mostly dinucleotide microsatellites and only 16 had trinucleotide repeats. We designed primers from the unique sequences flanking 18 microsatellite loci. Of these, 11 loci produced successful amplification and revealed high levels of polymorphism; 86 alleles were detected with allele number ranging from 2 to 16 at each locus. The high allelic variability will make these microsatellite loci very useful for taxonomic and population genetic studies.

Find It - An Assistant Home Agent

Cognitive impaired population face with innumerable problems in their daily life. Surprisingly, they are not provided with any help to perform those tasks for which they have difficulties. As a consequence, it is necessary to develop systems that allow those people to live independently and autonomously. Living in a technological era, people could take advantage of the available technology, being provided with some solutions to their needs. This paper presents a platform that assists users with remembering where their possessions are. Mainly, an object recognition process together with an intelligent scheduling applications are integrated in an Ambient Assisted Living (AAL) environment.

Medicis: a personal health care assistant

The relation between patient and physician in most modern Health Care Systems is sparse, limited in time and very inflexible. On the other hand, and in contradiction with several recent studies, most physicians do not rely their patient diagnostics evaluations on intertwined psychological and social nature factors. Facing these problems and trying to improve the patient/physician relation we present a mobile health care solution to improve the interaction between the physician and his patients. The solution serves not only as a privileged mean of communication between physicians and patients but also as an evolutionary intelligent platform delivering a mobile rule based system.

As escolhas públicas orçamentárias federais no PPA 2008-2011: uma análise da perspectiva do modelo principal-agente

O objetivo deste estudo é analisar o comportamento assumido pelo Executivo e pelo Legislativo durante a gestão do PPA 2008-2011 da perspectiva do modelo principal-agente. Por meio da aplicação dos testes de Friedman, Kendall e Spearman e tendo como objeto empírico todos os programas constantes no PPA 2008-2011, observou-se que entre 2008 e 2011: as etapas de Elaboração e de Execução Orçamentária e Financeira da Lei Orçamentária Anual, cujo ator principal é o Poder Executivo, apresentaram concordância muito forte; enquanto a etapa de Discussão, Votação e Aprovação, cujo ator principal é o Poder Legislativo, apresentou concordância moderada. Quando se considerou a interação no mesmo ciclo entre todas as etapas, a concordância foi menor. Além disso, como resultado mais expressivo do estudo, identificou-se que a relação externa (entre governo e cidadãos) possui concordância maior que a relação interna (entre políticos e burocratas).

Estudo médico-social dos fatores contribuintes para os acidentes das aeronaves executivas convencionais registrados entre 1971 e 1975, no Estado de São Paulo, Brasil: I - Época e hora da ocorrência e principal fator contribuinte

Em estudo sobre os acidentes aeronáuticos ocorridos de 1971 à 1975 com aeronaves executivas convencionais na área do IV Comando Aéreo Regional, foram analisados diversos fatores contribuintes para esse fato. Foram examinados a época da ocorrência e o principal fator contribuinte, concluindo-se que o período do dia em que se verificou maior número de acidentes foi à tarde entre 14 e 18 h., e que o fator operacional, devido ao piloto, está associado estatisticamente com a ocorrência dos acidentes. Não foi possível comprovar maior índice de ocorrência de acidentes com referência aos meses do ano.

Principal components and generalized linear modeling in the correlation between hospital admissions and air pollution

OBJECTIVE To analyze the association between concentrations of air pollutants and admissions for respiratory causes in children. METHODS Ecological time series study. Daily figures for hospital admissions of children aged < 6, and daily concentrations of air pollutants (PM10, SO2, NO2, O3 and CO) were analyzed in the Região da Grande Vitória, ES, Southeastern Brazil, from January 2005 to December 2010. For statistical analysis, two techniques were combined: Poisson regression with generalized additive models and principal model component analysis. Those analysis techniques complemented each other and provided more significant estimates in the estimation of relative risk. The models were adjusted for temporal trend, seasonality, day of the week, meteorological factors and autocorrelation. In the final adjustment of the model, it was necessary to include models of the Autoregressive Moving Average Models (p, q) type in the residuals in order to eliminate the autocorrelation structures present in the components. RESULTS For every 10:49 μg/m3 increase (interquartile range) in levels of the pollutant PM10 there was a 3.0% increase in the relative risk estimated using the generalized additive model analysis of main components-seasonal autoregressive – while in the usual generalized additive model, the estimate was 2.0%. CONCLUSIONS Compared to the usual generalized additive model, in general, the proposed aspect of generalized additive model − principal component analysis, showed better results in estimating relative risk and quality of fit.

PETCHA: a Programming Exercises Teaching Assistant

This paper presents a tool called Petcha that acts as an automated Teaching Assistant in computer programming courses. The ultimate objective of Petcha is to increase the number of programming exercises effectively solved by students. Petcha meets this objective by helping both teachers to author programming exercises and students to solve them. It also coordinates a network of heterogeneous systems, integrating automatic program evaluators, learning management systems, learning object repositories and integrated programming environments. This paper presents the concept and the design of Petcha and sets this tool in a service oriented architecture for managing learning processes based on the automatic evaluation of programming exercises. The paper presents also a case study that validates the use of Petcha and of the proposed architecture.

Forest soil short term response to prescribed fire: an approach by Principal Components Analysis

In the current context of serious climate changes, where the increase of the frequency of some extreme events occurrence can enhance the rate of periods prone to high intensity forest fires, the National Forest Authority often implements, in several Portuguese forest areas, a regular set of measures in order to control the amount of fuel mass availability (PNDFCI, 2008). In the present work we’ll present a preliminary analysis concerning the assessment of the consequences given by the implementation of prescribed fire measures to control the amount of fuel mass in soil recovery, in particular in terms of its water retention capacity, its organic matter content, pH and content of iron. This work is included in a larger study (Meira-Castro, 2009(a); Meira-Castro, 2009(b)). According to the established praxis on the data collection, embodied in multidimensional matrices of n columns (variables in analysis) by p lines (sampled areas at different depths), and also considering the quantitative data nature present in this study, we’ve chosen a methodological approach that considers the multivariate statistical analysis, in particular, the Principal Component Analysis (PCA ) (Góis, 2004). The experiments were carried out in a soil cover over a natural site of Andaluzitic schist, in Gramelas, Caminha, NW Portugal, who was able to maintain itself intact from prescribed burnings from four years and was submit to prescribed fire in March 2008. The soils samples were collected from five different plots at six different time periods. The methodological option that was adopted have allowed us to identify the most relevant relational structures inside the n variables, the p samples and in two sets at the same time (Garcia-Pereira, 1990). Consequently, and in addition to the traditional outputs produced from the PCA, we have analyzed the influence of both sampling depths and geomorphological environments in the behavior of all variables involved.

Multiple linear and principal component regressions for modelling ecotoxicity bioassay response

The ecotoxicological response of the living organisms in an aquatic system depends on the physical, chemical and bacteriological variables, as well as the interactions between them. An important challenge to scientists is to understand the interaction and behaviour of factors involved in a multidimensional process such as the ecotoxicological response.With this aim, multiple linear regression (MLR) and principal component regression were applied to the ecotoxicity bioassay response of Chlorella vulgaris and Vibrio fischeri in water collected at seven sites of Leça river during five monitoring campaigns (February, May, June, August and September of 2006). The river water characterization included the analysis of 22 physicochemical and 3 microbiological parameters. The model that best fitted the data was MLR, which shows: (i) a negative correlation with dissolved organic carbon, zinc and manganese, and a positive one with turbidity and arsenic, regarding C. vulgaris toxic response; (ii) a negative correlation with conductivity and turbidity and a positive one with phosphorus, hardness, iron, mercury, arsenic and faecal coliforms, concerning V. fischeri toxic response. This integrated assessment may allow the evaluation of the effect of future pollution abatement measures over the water quality of Leça River.

Cochineal, a precious source of red: cochineal dyes characterization by high performance liquid chromatography with diode array detection and principal component analysis

Presented at Faculdade de Ciências e Tecnologias, Universidade de Lisboa, to obtain the Master Degree in Conservation and Restoration of Textiles

Avaliação do Desempenho Energético e da Qualidade do Ar Interior do Edifício Principal do Parque Biológico de Vila Nova de Gaia

A presente dissertação tem como principal propósito avaliar o desempenho energético e a qualidade do ar interior do edifício principal do Parque Biológico de Vila Nova de Gaia (PBG). Para esse efeito, este estudo relaciona os termos definidos na legislação nacional em vigor até à presente data, e referentes a esta área de atuação, em particular, os presentes no SCE, RSECE, RCCTE e RSECE-QAI. Para avaliar o desempenho energético, procedeu-se numa primeira fase ao processo de auditoria no local e posteriormente à realização de uma simulação dinâmica detalhada, cuja modelação do edifício foi feita com recurso ao software DesignBuilder. Após a validação do modelo simulado, por verificação do desvio entre os consumos energéticos registados nas faturas e os calculados na simulação, igual a 5,97%, foi possível efetuar a desagregação dos consumos em percentagem pelos diferentes tipos de utilizações. Foi também possível determinar os IEE real e nominal, correspondendo a 29,9 e 41.3 kgep/m2.ano, respetivamente, constatando-se através dos mesmos que o edifício ficaria dispensado de implementar um plano de racionalização energética (PRE) e que a classe energética a atribuir é a C. Contudo, foram apresentadas algumas medidas de poupança de energia, de modo a melhorar a eficiência energética do edifício e reduzir a fatura associada. Destas destacam-se duas propostas, a primeira propõe a alteração do sistema de iluminação interior e exterior do edifício, conduzindo a uma redução no consumo de eletricidade de 47,5 MWh/ano, com um período de retorno de investimento de 3,5 anos. A segunda está relacionada com a alteração do sistema de produção de água quente para o aquecimento central, através do incremento de uma caldeira a lenha ao sistema atual, que prevê uma redução de 50 MWh no consumo de gás natural e um período de retorno de investimento de cerca de 4 anos. Na análise realizada à qualidade do ar interior (QAI), os parâmetros quantificados foram os exigidos legalmente, excetuando os microbiológicos. Deste modo, para os parâmetros físicos, temperatura e humidade relativa, obtiveram-se os resultados médios de 19,7ºC e 66,9%, respetivamente, ligeiramente abaixo do previsto na legislação (20,0ºC no período em que foi feita a medição, inverno). No que diz respeito aos parâmetros químicos, os valores médios registados para as concentrações de dióxido de carbono (CO2), monóxido de carbono (CO), ozono (O3), formaldeído (HCHO), partículas em suspensão (PM10) e radão, foram iguais a 580 ppm, 0,2 ppm, 0,06 ppm, 0,01 ppm, 0,07 mg/m3 e 196 Bq/m3, respetivamente, verificando-se que estão abaixo dos valores máximos de referência presentes no regulamento (984 ppm, 10,7 ppm, 0,10 ppm, 0,08 ppm, 0,15 mg/m3 e 400 Bq/m3). No entanto, o parâmetro relativo aos compostos orgânicos voláteis (COV) teve um valor médio igual a 0,84 ppm, bastante acima do valor máximo de referência (0,26 ppm). Neste caso, terá que ser realizada uma nova série de medições utilizando meios cromatográficos, para avaliar qual(ais) são o(s) agente(s) poluidor(es), de modo a eliminar ou atenuar as fontes de emissão.