Topics in Local Economic Development

This thesis contributes to the current debate in literature about local economic development by considering two different topics: quality of institutions, and the role of clusters in innovation and productivity growth. The research is built upon three papers. The first paper deals with the analysis of the effect of administrative continuity on administrative efficiency. The analysis underlines the importance of different typologies of social capital. Findings reveal a positive impact on administrative efficiency (AE) by administrative continuity (AC) when it is coupled by bridging and linking social capital. On the contrary, bonding social capital influences negatively the effect by AC on AE. The second paper investigates the spatial interaction in levels of quality of government (QoG) among European regions. Notwithstanding the largely recognised role by institutions in the design of regional policies, no study has been conducted about the mechanisms of interaction and diffusion of QoG at regional level. This research wants to overcome this knowledge gap in literature. Findings reveal a heterogeneity in spatial interaction among groups of regions, i.e. ‘leader regions’ (Northern regions) and ‘lagging regions’ (Southern regions), when considering different mechanisms of interaction (learning / imitating competition and pure competition). Moreover, the effect of wealth on the levels of QoG is nonlinear. Finally, the third paper analyses the relation among specialization and productivity within the agricultural sector. In literature, the study of clusters dynamics has long neglected agriculture. The analysis describes the changes in sectorial specialization for eight main crop groups in Italian regions (NUTS 3), assessing the existence of spatial autocorrelations by using an exploratory data analysis. Furthermore, the effect of specialization on productivity is analysed within the main crop groups using a spatial panel data model. Findings reveal a marked tendency to specialization in the Italian agriculture, and a heterogeneous effect by specialization on productivity.

Medallones de carne vacuna : reducción del contenido de sal por incorporación de oleorresinas de especias

Para evaluar la posible disminución de la adición de cloruro de sodio, mediante el agregado de oleorresinas de especias, se elaboró una masa en la que se empleó 85 % de carne vacuna y 15 % de grasa. Se fraccionó en tres lotes, adicionándoles: 1000 mg/kg de oleorresina de Origanum x Majoricum, 750 mg/kg de la de Capsicum annum o de la de Acantholippia seriphioides, respectivamente. Luego se dividieron en cinco porciones iguales y se agregó sal, hasta alcanzar contenidos de 0.00 %; 0.25 %; 0.50 %; 0.75 % y 1.00 %. Se homogeneizaron y se elaboraron medallones de 100 g, que se cocinaron en horno hasta alcanzar una temperatura interna de 72 °C. Se realizó una evaluación sensorial con 15 jueces semientrenados, solicitándoles que asignaran puntajes, mediante escalas estructuradas de siete puntos e indicaran cuál/es rechazarían. Los puntajes asignados por el panel se sometieron a un análisis exploratorio de datos, a las pruebas de Page y de comparaciones múltiples. Los medallones adicionados con los tres tipos de oleorresinas para las dosis de sal ensayadas presentaron diferencias (= 0.05): las dosis de 0 y 1% fueron las menos aceptadas y la de 0.25 % fue la más aceptada. El 50 % de los jueces rechazó el medallón con 0 % de sal, para los tres tipos de oleorresinas. En las condiciones ensayadas, la incorporación de oleorresinas en dosis de 1000 mg/kg para orégano o de 750 mg/kg para pimiento y tomillo mendocino, permite formular medallones de carne vacuna, con bajo contenido de sal y alta aceptación.

Antichagásicos potenciais: síntese e modelagem molecular de híbridos de hidrazonas e liberadores de óxido nítrico

A doença de Chagas é uma parasitose extremamente negligenciada, cujo agente etiológico é o protozoário Trypanosoma cruzi. Atualmente, 21 países da América Latina são considerados regiões endêmicas, onde 75-90 milhões de pessoas estão expostas à infecção, 6-7 milhões estão infectadas e mais de 41 mil novos casos surgem por ano. Entretanto, apenas os fármacos nifurtimox e benznidazol estão disponíveis no mercado. Estes, além da baixa eficácia na fase crônica da parasitose, apresentam diversos efeitos adversos, sendo que no Brasil apenas o benznidazol é utilizado. Este fato mostra a importância de se ampliar o número de fármacos disponíveis e propor quimioterapia mais eficaz para o tratamento da doença de Chagas. Como forma de contribuir para essa busca, este trabalho objetiva a síntese de compostos híbridos bioisostéricos N-acilidrazônicos e sulfonilidrazônicos, contendo grupo liberador de óxido nítrico, com potencial de interação com cisteíno-proteases parasitárias, tais como a cruzaína. Nestes derivados, os grupos liberadores de óxido nítrico utilizados foram os grupos furoxano (contendo substituinte metílico e fenílico) e éster nitrato. Propôs-se a variação de anéis aromáticos substituídos e não-substituídos, com o intuito de avaliar a possível relação estrutura-atividade (REA) desses análogos. Até o momento, somente os compostos da série N-acilidrazônica tiveram avaliação biológica realizada. Os valores de IC50 dos compostos na forma amastigota do parasita variaram entre >100 a 2,88 µM, sendo este último valor comparável ao fármaco de referência. A atividade inibitória frente à cruzaína foi de 25,2 µM a 2,2 µM. Já a liberação de óxido nítrico foi avaliada pelo método indireto de detecção de nitrato e os valores variaram entre 52,0 µM e 4.232,0 µM. Estes são bem inferiores ao composto padrão, além de não se identificar correlação direta entre a atividade biológica e a liberação de NO. Na sequência, os dois compostos mais ativos (6 e 14) foram submetidos a estudos de permeabilidade e de citotoxicidade. O composto 6 foi considerado o de maior permeabilidade segundo o Sistema de Classificação Biofarmacêutica (SCB) e todos os compostos apresentaram a taxa de fluxo menor que 2, indicando a ausência de mecanismo de efluxo. Na avaliação do potencial citotóxico desses compostos em células humanas, o derivado 6 apresentou índice de seletividade superior ao do benznidazol. Em estudos de modelagem molecular usando análise exploratória de dados (HCA e PCA), propriedades estéricas/geométricas e eletrônicas foram consideradas as mais relevantes para a atividade biológica. Além disso, estudos de docking mostraram que a posição do grupo nitro no anel aromático é importante para a interação com a cruzaína. Ademais o composto 6 não provocou mudanças significativas no ciclo celular e na fragmentação de DNA em células humanas, mostrando-se como líder promissor para futuros estudos in vivo. Atividade tripanomicida, citotoxicidade, potencial de liberação de NO e estudos de permeabilidade dos 23 derivados sulfonilidrazônicos e ésteres nitrato estão sendo avaliados.

Inovação e indústria da moda: um modelo de inovação em estilos e tendências.

Este trabalho tem como intuito propor um modelo de inovação para a indústria da moda feminina. O modelo visa compreender o comportamento de estilos e tendências determinados e difundidos pelas empresas. A construção deste modelo é justificada pela contribuição que um estudo sobre inovação pode proporcionar à indústria da moda, a qual enfrenta baixos padrões de competitividade no mercado externo e interno. Além disso, embora existam muitos artigos sobre o assunto, poucos foram os modelos de inovação para a indústria da moda encontrados por esta pesquisa. Uma avaliação destes modelos indicou que existe espaço para a proposta de um modelo que aborde o comportamento de estilos e tendências ao longo do tempo. A estrutura de composição do modelo é sustentada por três pilares conceituais: teoria econômica neoschumpeteriana, modelos de inovação e modelos de inovação para a indústria da moda. A característica central do modelo é avaliar se existem estilos que permanecem em moda de maneira contínua ou descontínua. Como existe similaridade conceitual entre os estilos, no que se refere à identidade de gênero (androginia e feminilidade), foi efetuada uma aglutinação de alguns estilos dentro desta denominação. Nem todos os estilos se encaixaram nesta classificação. Então, estes estilos foram denominados como neutros. Como a pesquisa tem abordagem fenomenológica, qualitativa e longitudinal, foi adotada a metodologia hipotética dedutiva para a construção do modelo. Para verificação da validade das hipóteses foi usada uma análise exploratória dos dados por meio de estatística descritiva e decomposição da estrutura de variabilidade através de uma análise de componentes principais (PCA). Ambas as análises forneceram evidências a respeito das hipóteses em questão, as quais também foram testadas através de um teste binomial e de uma análise de variância multivariada por meio de permutações. Os resultados comprovaram que existem estilos que permanecem em moda de maneira contínua e que existem períodos de polarização das aglutinações de estilo.

The theory of on-line learning: a statistical physics approach

In this paper we review recent theoretical approaches for analysing the dynamics of on-line learning in multilayer neural networks using methods adopted from statistical physics. The analysis is based on monitoring a set of macroscopic variables from which the generalisation error can be calculated. A closed set of dynamical equations for the macroscopic variables is derived analytically and solved numerically. The theoretical framework is then employed for defining optimal learning parameters and for analysing the incorporation of second order information into the learning process using natural gradient descent and matrix-momentum based methods. We will also briefly explain an extension of the original framework for analysing the case where training examples are sampled with repetition.

Facets of operational performance in an emergency room (ER)

This paper, using detailed time measurements of patients complemented by interviews with hospital management and staff, examines three facets of an emergency room's (ER) operational performance: (1) effectiveness of the triage system in rationing patient treatment; (2) factors influencing ER's operational performance in general and the trade-offs in flow times, inventory levels (that is the number of patients waiting in the system), and resource utilization; (3) the impacts of potential process and staffing changes to improve the ER's performance. Specifically, the paper discusses four proposals for streamlining the patient flow: establishing designated tracks (fast track, diagnostic track), creating a holding area for certain type of patients, introducing a protocol that would reduce the load on physicians by allowing a registered nurse to order testing and treatment for some patients, and potentially and in the longer term, moving from non-ER specialist physicians to ER specialists. The paper's findings are based on analyzing the paths and flow times of close to two thousand patients in the emergency room of the Medical Center of Leeuwarden (MCL), The Netherlands. Using exploratory data analysis the paper presents generalizable findings about the impacts of various factors on ER's lead-time performance and shows how the proposals fit with well-documented process improvement theories. © 2010 Elsevier B.V. All rights reserved.

The experience of teaching statistics to non-specialist students in Saudi universities

Undoubtedly, statistics has become one of the most important subjects in the modern world, where its applications are ubiquitous. The importance of statistics is not limited to statisticians, but also impacts upon non-statisticians who have to use statistics within their own disciplines. Several studies have indicated that most of the academic departments around the world have realized the importance of statistics to non-specialist students. Therefore, the number of students enrolled in statistics courses has vastly increased, coming from a variety of disciplines. Consequently, research within the scope of statistics education has been able to develop throughout the last few years. One important issue is how statistics is best taught to, and learned by, non-specialist students. This issue is controlled by several factors that affect the learning and teaching of statistics to non-specialist students, such as the use of technology, the role of the English language (especially for those whose first language is not English), the effectiveness of statistics teachers and their approach towards teaching statistics courses, students’ motivation to learn statistics and the relevance of statistics courses to the main subjects of non-specialist students. Several studies, focused on aspects of learning and teaching statistics, have been conducted in different countries around the world, particularly in Western countries. Conversely, the situation in Arab countries, especially in Saudi Arabia, is different; here, there is very little research in this scope, and what there is does not meet the needs of those countries towards the development of learning and teaching statistics to non-specialist students. This research was instituted in order to develop the field of statistics education. The purpose of this mixed methods study was to generate new insights into this subject by investigating how statistics courses are currently taught to non-specialist students in Saudi universities. Hence, this study will contribute towards filling the knowledge gap that exists in Saudi Arabia. This study used multiple data collection approaches, including questionnaire surveys from 1053 non-specialist students who had completed at least one statistics course in different colleges of the universities in Saudi Arabia. These surveys were followed up with qualitative data collected via semi-structured interviews with 16 teachers of statistics from colleges within all six universities where statistics is taught to non-specialist students in Saudi Arabia’s Eastern Region. The data from questionnaires included several types, so different techniques were used in analysis. Descriptive statistics were used to identify the demographic characteristics of the participants. The chi-square test was used to determine associations between variables. Based on the main issues that are raised from literature review, the questions (items scales) were grouped and five key groups of questions were obtained which are: 1) Effectiveness of Teachers; 2) English Language; 3) Relevance of Course; 4) Student Engagement; 5) Using Technology. Exploratory data analysis was used to explore these issues in more detail. Furthermore, with the existence of clustering in the data (students within departments within colleges, within universities), multilevel generalized linear models for dichotomous analysis have been used to clarify the effects of clustering at those levels. Factor analysis was conducted confirming the dimension reduction of variables (items scales). The data from teachers’ interviews were analysed on an individual basis. The responses were assigned to one of the eight themes that emerged from within the data: 1) the lack of students’ motivation to learn statistics; 2) students' participation; 3) students’ assessment; 4) the effective use of technology; 5) the level of previous mathematical and statistical skills of non-specialist students; 6) the English language ability of non-specialist students; 7) the need for extra time for teaching and learning statistics; and 8) the role of administrators. All the data from students and teachers indicated that the situation of learning and teaching statistics to non-specialist students in Saudi universities needs to be improved in order to meet the needs of those students. The findings of this study suggested a weakness in the use of statistical software applications in these courses. This study showed that there is lack of application of technology such as statistical software programs in these courses, which would allow non-specialist students to consolidate their knowledge. The results also indicated that English language is considered one of the main challenges in learning and teaching statistics, particularly in institutions where English is not used as the main language. Moreover, the weakness of mathematical skills of students is considered another major challenge. Additionally, the results indicated that there was a need to tailor statistics courses to the needs of non-specialist students based on their main subjects. The findings indicate that statistics teachers need to choose appropriate methods when teaching statistics courses.

Quantificação de açúcares com uma língua eletrónica: calibração multivariada com seleção de sensores

Este trabalho incide na análise dos açúcares majoritários nos alimentos (glucose, frutose e sacarose) com uma língua eletrónica potenciométrica através de calibração multivariada com seleção de sensores. A análise destes compostos permite contribuir para a avaliação do impacto dos açúcares na saúde e seu efeito fisiológico, além de permitir relacionar atributos sensoriais e atuar no controlo de qualidade e autenticidade dos alimentos. Embora existam diversas metodologias analíticas usadas rotineiramente na identificação e quantificação dos açúcares nos alimentos, em geral, estes métodos apresentam diversas desvantagens, tais como lentidão das análises, consumo elevado de reagentes químicos e necessidade de pré-tratamentos destrutivos das amostras. Por isso se decidiu aplicar uma língua eletrónica potenciométrica, construída com sensores poliméricos selecionados considerando as sensibilidades aos açucares obtidas em trabalhos anteriores, na análise dos açúcares nos alimentos, visando estabelecer uma metodologia analítica e procedimentos matemáticos para quantificação destes compostos. Para este propósito foram realizadas análises em soluções padrão de misturas ternárias dos açúcares em diferentes níveis de concentração e em soluções de dissoluções de amostras de mel, que foram previamente analisadas em HPLC para se determinar as concentrações de referência dos açúcares. Foi então feita uma análise exploratória dos dados visando-se remover sensores ou observações discordantes através da realização de uma análise de componentes principais. Em seguida, foram construídos modelos de regressão linear múltipla com seleção de variáveis usando o algoritmo stepwise e foi verificado que embora fosse possível estabelecer uma boa relação entre as respostas dos sensores e as concentrações dos açúcares, os modelos não apresentavam desempenho de previsão satisfatório em dados de grupo de teste. Dessa forma, visando contornar este problema, novas abordagens foram testadas através da construção e otimização dos parâmetros de um algoritmo genético para seleção de variáveis que pudesse ser aplicado às diversas ferramentas de regressão, entre elas a regressão pelo método dos mínimos quadrados parciais. Foram obtidos bons resultados de previsão para os modelos obtidos com o método dos mínimos quadrados parciais aliado ao algoritmo genético, tanto para as soluções padrão quanto para as soluções de mel, com R²ajustado acima de 0,99 e RMSE inferior a 0,5 obtidos da relação linear entre os valores previstos e experimentais usando dados dos grupos de teste. O sistema de multi-sensores construído se mostrou uma ferramenta adequada para a análise dos iii açúcares, quando presentes em concentrações maioritárias, e alternativa a métodos instrumentais de referência, como o HPLC, por reduzir o tempo da análise e o valor monetário da análise, bem como, ter um preparo mínimo das amostras e eliminar produtos finais poluentes.

A Visual Analytics Approach to Comparing Cohorts of Event Sequences

Sequences of timestamped events are currently being generated across nearly every domain of data analytics, from e-commerce web logging to electronic health records used by doctors and medical researchers. Every day, this data type is reviewed by humans who apply statistical tests, hoping to learn everything they can about how these processes work, why they break, and how they can be improved upon. To further uncover how these processes work the way they do, researchers often compare two groups, or cohorts, of event sequences to find the differences and similarities between outcomes and processes. With temporal event sequence data, this task is complex because of the variety of ways single events and sequences of events can differ between the two cohorts of records: the structure of the event sequences (e.g., event order, co-occurring events, or frequencies of events), the attributes about the events and records (e.g., gender of a patient), or metrics about the timestamps themselves (e.g., duration of an event). Running statistical tests to cover all these cases and determining which results are significant becomes cumbersome. Current visual analytics tools for comparing groups of event sequences emphasize a purely statistical or purely visual approach for comparison. Visual analytics tools leverage humans' ability to easily see patterns and anomalies that they were not expecting, but is limited by uncertainty in findings. Statistical tools emphasize finding significant differences in the data, but often requires researchers have a concrete question and doesn't facilitate more general exploration of the data. Combining visual analytics tools with statistical methods leverages the benefits of both approaches for quicker and easier insight discovery. Integrating statistics into a visualization tool presents many challenges on the frontend (e.g., displaying the results of many different metrics concisely) and in the backend (e.g., scalability challenges with running various metrics on multi-dimensional data at once). I begin by exploring the problem of comparing cohorts of event sequences and understanding the questions that analysts commonly ask in this task. From there, I demonstrate that combining automated statistics with an interactive user interface amplifies the benefits of both types of tools, thereby enabling analysts to conduct quicker and easier data exploration, hypothesis generation, and insight discovery. The direct contributions of this dissertation are: (1) a taxonomy of metrics for comparing cohorts of temporal event sequences, (2) a statistical framework for exploratory data analysis with a method I refer to as high-volume hypothesis testing (HVHT), (3) a family of visualizations and guidelines for interaction techniques that are useful for understanding and parsing the results, and (4) a user study, five long-term case studies, and five short-term case studies which demonstrate the utility and impact of these methods in various domains: four in the medical domain, one in web log analysis, two in education, and one each in social networks, sports analytics, and security. My dissertation contributes an understanding of how cohorts of temporal event sequences are commonly compared and the difficulties associated with applying and parsing the results of these metrics. It also contributes a set of visualizations, algorithms, and design guidelines for balancing automated statistics with user-driven analysis to guide users to significant, distinguishing features between cohorts. This work opens avenues for future research in comparing two or more groups of temporal event sequences, opening traditional machine learning and data mining techniques to user interaction, and extending the principles found in this dissertation to data types beyond temporal event sequences.

STORM - a novel information fusion and cluster interpretation technique

Analysis of data without labels is commonly subject to scrutiny by unsupervised machine learning techniques. Such techniques provide more meaningful representations, useful for better understanding of a problem at hand, than by looking only at the data itself. Although abundant expert knowledge exists in many areas where unlabelled data is examined, such knowledge is rarely incorporated into automatic analysis. Incorporation of expert knowledge is frequently a matter of combining multiple data sources from disparate hypothetical spaces. In cases where such spaces belong to different data types, this task becomes even more challenging. In this paper we present a novel immune-inspired method that enables the fusion of such disparate types of data for a specific set of problems. We show that our method provides a better visual understanding of one hypothetical space with the help of data from another hypothetical space. We believe that our model has implications for the field of exploratory data analysis and knowledge discovery.

Análisis de los impactos del uso del teléfono móvil en los estilos de vida [ocio y tiempo libre, relaciones sociales, y conductas sedentarias] de los adolescentes en enseñanza secundaria obligatoria de la Comunidad Autónoma de Aragón, España

La presente investigación tuvo como objetivo analizar los impactos del uso del teléfono móvil en los estilos de vida (ocio y tiempo libre, relaciones sociales, y conductas sedentarias) de los adolescentes en enseñanza secundaria obligatoria de la comunidad autónoma de Aragón (España). Comenzamos por revisar conceptualizaciones, revisamos acerca del bienestar y de los hábitos de vida de los adolescentes, el teléfono móvil y sus implicancias para la salud y estilos de vida, sus usos y representationes. Metodológicamente, se trata de un estudio descriptivo y cuantitativo. Realizamos un análisis exploratorio de los datos, y complementariamente testeamos la relación entre variables. En conclusión, podemos afirmar que los adolescentes en Aragón: Tienen una visión positiva de su salud; Entre las conductas sedentarias asociadas a las pantallas, prevalece el uso del teléfono móvil en el fin de semana; La seguridad es la función referencial (valor simbólico) más valorizada del teléfono móvil; Poder comunicarse con los amigos, es la principal razón para querer tener su primer teléfono móvil; Enviar o recibir mensajes de los amigos/as, es la función comunicativa (valor instrumental) más valorizada del teléfono móvil; Escuchar música o la radio, es el mayor uso de la función lúdico-expresiva-organizativa (valor instrumental) del teléfono móvil.

Integrated Omics for the global mapping of biomolecules in LDL

Circulating low density lipoproteins (LDL) are thought to play a crucial role in the onset and development of atherosclerosis, though the detailed molecular mechanisms responsible for their biological effects remain controversial. The complexity of biomolecules (lipids, glycans and protein) and structural features (isoforms and chemical modifications) found in LDL particles hampers the complete understanding of the mechanism underlying its atherogenicity. For this reason the screening of LDL for features discriminative of a particular pathology in search of biomarkers is of high importance. Three major biomolecule classes (lipids, protein and glycans) in LDL particles were screened using mass spectrometry coupled to liquid chromatography. Dual-polarity screening resulted in good lipidome coverage, identifying over 300 lipid species from 12 lipid sub-classes. Multivariate analysis was used to investigate potential discriminators in the individual lipid sub-classes for different study groups (age, gender, pathology). Additionally, the high protein sequence coverage of ApoB-100 routinely achieved (≥70%) assisted in the search for protein modifications correlating to aging and pathology. The large size and complexity of the datasets required the use of chemometric methods (Partial Least Square-Discriminant Analysis, PLS-DA) for their analysis and for the identification of ions that discriminate between study groups. The peptide profile from enzymatically digested ApoB-100 can be correlated with the high structural complexity of lipids associated with ApoB-100 using exploratory data analysis. In addition, using targeted scanning modes, glycosylation sites within neutral and acidic sugar residues in ApoB-100 are also being explored. Together or individually, knowledge of the profiles and modifications of the major biomolecules in LDL particles will contribute towards an in-depth understanding, will help to map the structural features that contribute to the atherogenicity of LDL, and may allow identification of reliable, pathology-specific biomarkers. This research was supported by a Marie Curie Intra-European Fellowship within the 7th European Community Framework Program (IEF 255076). Work of A. Rudnitskaya was supported by Portuguese Science and Technology Foundation, through the European Social Fund (ESF) and "Programa Operacional Potencial Humano - POPH".

Uso da espectroscopia de reflectância do infravermelho próximo (NIRS) para previsão da composição bromatológica de vagens de algaroba e palma forrageira.

Espécies forrageiras adaptadas às condições semiáridas são uma alternativa para reduzir os impactos negativos na cadeia produtiva de ruminantes da região Nordeste brasileira devido à sazonalidade na oferta de forragem, além de reduzir custo com o fornecimento de alimentos concentrados. Dentre as espécies, a vagem de algaroba (Prosopis juliflora SW D.C.) e palma forrageira (Opuntia e Nopalea) ganham destaque por tolerarem o déficit hídrico e produzirem em períodos onde a oferta de forragem está reduzida, além de apresentam bom valor nutricional e serem bem aceitas pelos animais. Porém, devido à variação na sua composição, seu uso na alimentação animal exige o conhecimento profundo da sua composição para a elaboração de dietas balanceadas. No entanto, devido ao custo e tempo para análise, os produtores não fazem uso da prática de análise da composição químico-bromatológica dos alimentos. Por isto, a espectroscopia de reflectância no infravermelho próximo (NIRS) representa uma importante alternativa aos métodos tradicionais. Objetivou-se com este estudo desenvolver e validar modelos de predição da composição bromatológica de vagem de algaroba e palma forrageira baseados em espectroscopia NIRS, escaneadas em dois modelos de equipamentos e com diferentes processamentos da amostra. Foram coletadas amostras de vagem de algaroba nos estados do Ceará, Bahia, Paraíba e Pernambuco, e amostras de palma forrageira nos estados do Ceará, Paraíba e Pernambuco, frescas (in natura) ou pré-secas e moídas. Para obtenção dos espectros utilizaram-se dois equipamentos NIR, Perten DA 7250 e FOSS 5000. Inicialmente os alimentos foram escaneados in natura em aparelho do modelo Perten, e, com o auxílio do software The Unscrambler 10.2 foi selecionado um grupo de amostras para o banco de calibração. As amostras selecionadas foram secas e moídas, e escaneadas novamente em equipamentos Perten e FOSS. Os valores dos parâmetros de referência foram obtidos por meio de metodologias tradicionalmente aplicadas em laboratório de nutrição animal para matéria seca (MS), matéria mineral (MM), matéria orgânica (MO), proteína bruta (PB), estrato etéreo (EE), fibra solúvel em detergente neutro (FDN), fibra solúvel em detergente ácido (FDA), hemicelulose (HEM) e digestibilidade in vitro da matéria seca (DIVMS). O desempenho dos modelos foi avaliado de acordo com os erros médios de calibração (RMSEC) e validação (RMSECV), coeficiente de determinação (R2 ) e da relação de desempenho de desvio dos modelos (RPD). A análise exploratória dos dados, por meio de tratamentos espectrais e análise de componentes principais (PCA), demonstraram que os bancos de dados eram similares entre si, dando segurança de desenvolver os modelos com todas as amostras selecionadas em um único modelo para cada alimento, algaroba e palma. Na avaliação dos resultados de referência, observou-se que a variação dos resultados para cada parâmetro corroboraram com os descritos na literatura. No desempenho dos modelos, aqueles desenvolvidos com pré-processamento da amostra (pré-secagem e moagem) se mostraram mais robustos do que aqueles construídos com amostras in natura. O aparelho NIRS Perten apresentou desempenho semelhante ao equipamento FOSS, apesar desse último cobrir uma faixa espectral maior e com intervalos de leituras menores. A técnica NIR, associada ao método de calibração multivariada de regressão por meio de quadrados mínimos (PLS), mostrou-se confiável para prever a composição químico-bromatológica de vagem de algaroba e da palma forrageira. Abstract: Forage species adapted to semi-arid conditions are an alternative to reduce the negative impacts in the feed supply for ruminants in the Brazilian Northeast region, due to seasonality in forage availability, as well as in the reducing of cost by providing concentrated feedstuffs. Among the species, mesquite pods (Prosopis juliflora SW DC) and spineless cactus (Opuntia and Nopalea) are highlighted for tolerating the drought and producion in periods where the forage is scarce, and have high nutritional value and also are well accepted by the animals. However, its use in animal diets requires a knowledge about its composition to prepare balanced diets. However, farmers usually do not use feed composition analysis, because their high cost and time-consuming. Thus, the Near Infrared Reflectance Spectroscopy in the (NIRS) is an important alternative to traditional methods. The objective of this study to develop and validate predictive models of the chemical composition of mesquite pods and spineless cactus-based NIRS spectroscopy, scanned in two different spectrometers and sample processing. Mesquite pods samples were collected in the states of Ceará, Bahia, Paraiba and Pernambuco, and samples of forage cactus in the states of Ceará, Paraíba and Pernambuco. In order to obtain the spectra, it was used two NIR equipment: Perten DA 7250 and FOSS 5000. sSpectra of samples were initially obtained fresh (as received) using Perten instrument, and with The Unscrambler software 10.2, a group of subsamples was selected to model development, keeping out redundant ones. The selected samples were dried and ground, and scanned again in both Perten and FOSS instruments. The values of the reference analysis were obtained by methods traditionally applied in animal nutrition laboratory to dry matter (DM), mineral matter (MM), organic matter (OM), crude protein (CP), ether extract (EE), soluble neutral detergent fiber (NDF), soluble acid detergent fiber (ADF), hemicellulose ( HEM) and in vitro digestibility of dry matter (DIVDM). The performance of the models was evaluated according to the Root Mean Square Error of Calibration (RMSEC) and cross-validation (RMSECV), coefficient of determination (R2 ) and the deviation of Ratio of performance Deviation of the models (RPD). Exploratory data analysis through spectral treatments and principal component analysis (PCA), showed that the databases were similar to each other, and may be treated asa single model for each feed - mesquite pods and cactus. Evaluating the reference results, it was observed that the variation were similar to those reported in the literature. Comparing the preprocessing of samples, the performance ofthose developed with preprocessing (dried and ground) of the sample were more robust than those built with fresh samples. The NIRS Perten device performance similar to FOSS equipment, although the latter cover a larger spectral range and with lower readings intervals. NIR technology associate do multivariate techniques is reliable to predict the bromatological composition of mesquite pods and cactus.

Sviluppo di una libreria per la visualizzazione di dati spazio temporali in R

Pacchetto R per il supporto dell'analisi di dati spazio temporali. Il pacchetto fornisce due funzioni, le quali permettono di avviare due applicazioni web, sviluppate con il framework shiny, per la visualizzazione di dati con connotazione spaziale di tipo areale o puntuale. Le applicazioni generano, a partire dai dati caricati dall'utente, due grafici interattivi per la visualizzazione della distribuzione temporale e spaziale del fenomeno che i dati descrivono. Sono previsti, all'interno dell'interfaccia utente delle applicazioni, una serie di componenti che permettono di personalizzare i grafici prodotti.

An exploratory analysis of relationships between socioeconomic, land use, activity participation variables and travel patterns

This paper aims to find relations between the socioeconomic characteristics, activity participation, land use patterns and travel behavior of the residents in the Sao Paulo Metropolitan Area (SPMA) by using Exploratory Multivariate Data Analysis (EMDA) techniques. The variables influencing travel pattern choices are investigated using: (a) Cluster Analysis (CA), grouping and characterizing the Traffic Zones (17), proposing the independent variable called Origin Cluster and, (b) Decision Tree (DT) to find a priori unknown relations among socioeconomic characteristics, land use attributes of the origin TZ and destination choices. The analysis was based on the origin-destination home-interview survey carried out in SPMA in 1997. The DT application revealed the variables of greatest influence on the travel pattern choice. The most important independent variable considered by DT is car ownership, followed by the Use of Transportation ""credits"" for Transit tariff, and, finally, activity participation variables and Origin Cluster. With these results, it was possible to analyze the influence of a family income, car ownership, position of the individual in the family, use of transportation ""credits"" for transit tariff (mainly for travel mode sequence choice), activities participation (activity sequence choice) and Origin Cluster (destination/travel distance choice). (c) 2010 Elsevier Ltd. All rights reserved.