Using spatial linear models with SAR and CAR structure to examine Texas lung cancer incidence rates

Scholars have found that socioeconomic status was one of the key factors that influenced early-stage lung cancer incidence rates in a variety of regions. This thesis examined the association between median household income and lung cancer incidence rates in Texas counties. A total of 254 individual counties in Texas with corresponding lung cancer incidence rates from 2004 to 2008 and median household incomes in 2006 were collected from the National Cancer Institute Surveillance System. A simple linear model and spatial linear models with two structures, Simultaneous Autoregressive Structure (SAR) and Conditional Autoregressive Structure (CAR), were used to link median household income and lung cancer incidence rates in Texas. The residuals of the spatial linear models were analyzed with Moran's I and Geary's C statistics, and the statistical results were used to detect similar lung cancer incidence rate clusters and disease patterns in Texas.^

Regression with autocorrelated data: A study of time trend of global infant mortality rate

The infant mortality rate (IMR) is considered to be one of the most important indices of a country's well-being. Countries around the world and other health organizations like the World Health Organization are dedicating their resources, knowledge and energy to reduce the infant mortality rates. The well-known Millennium Development Goal 4 (MDG 4), whose aim is to archive a two thirds reduction of the under-five mortality rate between 1990 and 2015, is an example of the commitment. ^ In this study our goal is to model the trends of IMR between the 1950s to 2010s for selected countries. We would like to know how the IMR is changing overtime and how it differs across countries. ^ IMR data collected over time forms a time series. The repeated observations of IMR time series are not statistically independent. So in modeling the trend of IMR, it is necessary to account for these correlations. We proposed to use the generalized least squares method in general linear models setting to deal with the variance-covariance structure in our model. In order to estimate the variance-covariance matrix, we referred to the time-series models, especially the autoregressive and moving average models. Furthermore, we will compared results from general linear model with correlation structure to that from ordinary least squares method without taking into account the correlation structure to check how significantly the estimates change.^

Assessing the patterns of colorectal cancer treatment, adherence to treatment guidelines and survival in Texas

Colorectal cancer (CRC) is the third leading cancer in both incidence and mortality in Texas. This study investigated the adherence of CRC treatment to standard treatment guidelines and the association between standard treatment and CRC survival in Texas. The author used Texas Cancer Registry (TCR) and Medicare linked data to study the CRC treatment patterns and factors associated with standard treatment in patients who were more than 65 years old and were diagnosed in 2001 through 2007. We also determined whether adherence to standard treatment affect patients' survival. Multiple logistic regression and Cox regression analysis were used to analyze our data. Both regression models are adjusted for demographic characteristics and tumor characteristics. We found that for the 3977 regional colon cancer patients 80 years old or younger, 60.2% of them received chemotherapy, in adherence to the recommended treatment guidelines. People with younger age, female gender, higher education and lower comorbidity score are more likely adherent to this surgery guideline. Patients' adherence to chemotherapy in this cohort have better survival compared to those who are not (HR: 0.76, 95% CI: 0.68-0.84). For the 12709 colon cancer patients treated with surgery, 49.3% have more than 12 lymph nodes removed, in adherence to the treatment guidelines. People with younger age, female gender, higher education, regional stage, lager tumor size and lower comorbidity score are more likely to adherent to this surgery guideline. Patients with more than 12 lymph nodes removed in this cohort have better survival (HR: 0.86, 95% CI: 0.82-0.91). For the 1211 regional rectal cancer patients 80 years old or younger, 63.2% of them were adherent to radiation treatment. People with smaller tumor size and lower comorbidity score are more likely to adherent to this radiation guideline. There is no significant survival difference between radiation adherent patients and non-adherent patients (HR: 1.03, 95% CI: 0.82-1.29). For the 1122 regional rectal cancer patients 80 years old or younger who were treated with surgery, 76.0% of them received postoperative chemotherapy, in adherence to the treatment guidelines. People with younger age and smaller comorbidity score are related with higher adherence rate. Patients adherent with adjuvant chemotherapy in this cohort have better survival than those were not adherent (HR: 0.60, 95% CI: 0.45-0.79).^

Geochemistry and kinetic models od Cretaceous samples

The source rock potential of Cretaceous organic rich whole rock samples from deep sea drilling project (DSDP) wells offshore southwestern Africa was investigated using bulk and quantitative pyrolysis techniques. The sample material was taken from organic rich intervals of Aptian, Albian and Turonian aged core samples from DSDP site 364 offshore Angola, DSDP well 530A north of the Walvis Ridge offshore Namibia, and DSDP well 361 offshore South Africa. The analytical program included TOC, Rock-Eval, pyrolysis GC, bulk kinetics and micro-scale sealed vessel pyrolysis (MSSV) experiments. The results were used to determine differences in the source rock petroleum type organofacies, petroleum composition, gas/oil ratio (GOR) and pressure-volume-temperature (PVT) behavior of hydrocarbons generated from these black shales for petroleum system modeling purposes. The investigated Aptian and Albian organic rich shales proved to contain excellent quality marine kerogens. The highest source rock potential was identified in sapropelic shales in DSDP well 364, containing very homogeneous Type II and organic sulfur rich Type IIS kerogen. They generate P-N-A low wax oils and low GOR sulfur rich oils, whereas Type III kerogen rich silty sandstones of DSDP well 361 show a potential for gas/condensate generation. Bulk kinetic experiments on these samples indicate that the organic sulfur contents influence kerogen transformation rates, Type IIS kerogen being the least stable. South of the Walvis Ridge, the Turonian contains predominantly a Type III kerogen. North of the Walvis Ridge, the Turonian black shales contain Type II kerogen and have the potential to generate P-N-A low and high wax oils, the latter with a high GOR at high maturity. Our results provide the first compositional kinetic description of Cretaceous organic rich black shales, and demonstrate the excellent source rock potential, especially of the Aptian-aged source rock, that has been recognized in a number of the South Atlantic offshore basins.

Putting prey and predator into the CO2 equation-qualitative and quantitative effects of ocean acidification on predator-prey interactions

Little is known about the impact of ocean acidification on predator-prey dynamics. Herein, we examined the effect of carbon dioxide (CO(2)) on both prey and predator by letting one predatory reef fish interact for 24 h with eight small or large juvenile damselfishes from four congeneric species. Both prey and predator were exposed to control or elevated levels of CO(2). Mortality rate and predator selectivity were compared across CO(2) treatments, prey size and species. Small juveniles of all species sustained greater mortality at high CO(2) levels, while large recruits were not affected. For large prey, the pattern of prey selectivity by predators was reversed under elevated CO(2). Our results demonstrate both quantitative and qualitative consumptive effects of CO(2) on small and larger damselfish recruits respectively, resulting from CO(2)-induced behavioural changes likely mediated by impaired neurological function. This study highlights the complexity of predicting the effects of climate change on coral reef ecosystems.

Transport Sector and Regional Price Differentials: A SCGE Model for Chinese Provinces

With regression formulas replaced by equilibrium conditions, a spatial CGE model can substantially reduce data requirements. Detailed regional analyses are thus possible in countries where only limited regional statistics are available. While regional price differentials play important roles in multi-regional settings, transport does not receive much attention in existing models. This paper formulates a spatial CGE model that explicitly considers the transport sector and FOB/CIF prices. After describing the model, performance of our model is evaluated by comparing the benchmark equilibrium for China with survey-based regional I-O and interregional I-O tables for 1987. The structure of Chinese economies is summarized using information obtained from the benchmark equilibrium computation. This includes regional and sectoral production distributions and price differentials. The equilibrium for 1997 facilitates discussion of changes in regional economic structures that China has experienced in the decade.

Industrial Clusters in India: Evidence from Automobile Clusters in Chennai and the National Capital Region

This study analyzes the patterns of agglomeration of some modern manufacturing sectors in India, and in particular the Indian automobile sector. It also examines and contrasts the factors that have led to different patterns of cluster development in two leading auto clusters in India-Chennai and the National Capital Region (NCR). Moreover, the study analyzes whether firms in clusters perform better than those that are excluded and whether the relative importance of variables that determine the behavior of firms differs among clusters. Our analyses, which employ a combination of quantitative and qualitative methods, show that Indian industrial clusters are largely concentrated in the three clustered regions: NCR, Mumbai-Pune, and Chennai-Bangalore, across different manufacturing sectors. Our study of the auto clusters in Chennai and the NCR find considerable differences in the patterns of cluster formation, due partly to the historical and policy conditions under which firms, particularly, the lead firms must operate. Moreover, our econometric analyses confirmed that being part of a cluster positively influences the performance of the auto component firms and those belonging to a cluster perform better.

Chapter 4 The Challenges in Developing Realistic NEG Simulation Models for East Asia

This chapter attempts to identify some important issues in developing realistic simulation models based on new economic geography, and it suggests a direction for solving the difficulties. Specifically, adopting the IDE Geographical Simulation Model (IDE-GSM) as an example, we discuss some problems in developing a realistic simulation model for East Asia. The first and largest problem in this region is the lack of reliable economic datasets at the sub-national level, and this issue needs to be resolved in the long term. However, to deal with the existing situation in the short term, we utilize some techniques to produce more realistic and reliable simulation models. One key compromise is to use a 'topology' representation of geography, rather than a 'mesh' or 'grid' representation or simple 'straight lines' connecting each city which are used in many other models. In addition to this, a modal choice model that takes into consideration both money and time costs seems to work well.

Lazy Lasso for local regression

Locally weighted regression is a technique that predicts the response for new data items from their neighbors in the training data set, where closer data items are assigned higher weights in the prediction. However, the original method may suffer from overfitting and fail to select the relevant variables. In this paper we propose combining a regularization approach with locally weighted regression to achieve sparse models. Specifically, the lasso is a shrinkage and selection method for linear regression. We present an algorithm that embeds lasso in an iterative procedure that alternatively computes weights and performs lasso-wise regression. The algorithm is tested on three synthetic scenarios and two real data sets. Results show that the proposed method outperforms linear and local models for several kinds of scenarios

Level Set Segmentation with Shape and Appearance Models Using Affine Moment Descriptors

We propose a level set based variational approach that incorporates shape priors into edge-based and region-based models. The evolution of the active contour depends on local and global information. It has been implemented using an efficient narrow band technique. For each boundary pixel we calculate its dynamic according to its gray level, the neighborhood and geometric properties established by training shapes. We also propose a criterion for shape aligning based on affine transformation using an image normalization procedure. Finally, we illustrate the benefits of the our approach on the liver segmentation from CT images.

Modelización del cálculo de Indicadores Ambientales, a partir de sensores ópticos de alta resolución temporal a bordo de satélite

La presente tesis doctoral tiene por objeto el estudio y análisis de técnicas y modelos de obtención de parámetros biofísicos e indicadores ambientales, de manera automatizada a partir de imágenes procedentes de satélite de alta resolución temporal. En primer lugar se revisan los diferentes programas espaciales de observación del territorio, con especial atención a los que proporcionan dicha resolución. También se han revisado las metodologías y procesos que permiten la obtención de diferentes parámetros cuantitativos y documentos cualitativos, relacionados con diversos aspectos de las cubiertas terrestres, atendiendo a su adaptabilidad a las particularidades de los datos. En segundo lugar se propone un modelo de obtención de parámetros ambientales, que integra información proveniente de sensores espaciales y de otras fuentes auxiliares utilizando, en cierta medida, las metodologías presentadas en apartados anteriores y optimizando algunas de las referidas o proponiendo otras nuevas, de manera que se permita dicha obtención de manera eficiente, a partir de los datos disponibles y de forma sistemática. Tras esta revisión de metodologías y propuesta del modelo, se ha procedido a la realización de experimentos, con la finalidad de comprobar su comportamiento en diferentes casos prácticos, depurar los flujos de datos y procesos, así como establecer las situaciones que pueden afectar a los resultados. De todo ello se deducirá la evaluación del referido modelo. Los sensores considerados en este trabajo han sido MODIS, de alta resolución temporal y Thematic Mapper (TM), de media resolución espacial, por tratarse de instrumentos de referencia en la realización de estudios ambientales. También por la duración de sus correspondientes misiones de registro de datos, lo que permite realizar estudios de evolución temporal de ciertos parámetros biofísicos, durante amplios periodos de tiempo. Así mismo. es de destacar que la continuidad de los correspondientes programas parece estar asegurada. Entre los experimentos realizados, se ha ensayado una metodología para la integración de datos procedentes de ambos sensores. También se ha analizado un método de interpolación temporal que permite obtener imágenes sintéticas con la resolución espacial de TM (30 m) y la temporal de MODIS (1 día), ampliando el rango de aplicación de este último sensor. Asimismo, se han analizado algunos de los factores que afectan a los datos registrados, tal como la geometría de la toma de los mismos y los episodios de precipitación, los cuales alteran los resultados obtenidos. Por otro lado, se ha comprobado la validez del modelo propuesto en el estudio de fenómenos ambientales dinámicos, en concreto la contaminación orgánica de aguas embalsadas. Finalmente, se ha demostrado un buen comportamiento del modelo en todos los casos ensayados, así como su flexibilidad, lo que le permite adaptarse a nuevos orígenes de datos, o nuevas metodologías de cálculo. Abstract This thesis aims to the study and analysis of techniques and models, in order to obtain biophysical parameters and environmental indicators in an automated way, using high temporal resolution satellite data. Firstly we have reviewed the main Earth Observation Programs, paying attention to those that provide high temporal resolution. Also have reviewed the methodologies and process flow diagrams in order to obtain quantitative parameters and qualitative documents, relating to various aspects of land cover, according to their adaptability to the peculiarities of the data. In the next stage, a model which allows obtaining environmental parameters, has been proposed. This structure integrates information from space sensors and ancillary data sources, using the methodologies presented in previous sections that permits the parameters calculation in an efficient and automated way. After this review of methodologies and the proposal of the model, we proceeded to carry out experiments, in order to check the behavior of the structure in real situations. From this, we derive the accuracy of the model. The sensors used in this work have been MODIS, which is a high temporal resolution sensor, and Thematic Mapper (TM), which is a medium spatial resolution instrument. This choice was motivated because they are reference sensors in environmental studies, as well as for the duration of their corresponding missions of data logging, and whose continuity seems assured. Among the experiments, we tested a methodology that allows the integration of data from cited sensors, we discussed a proposal for a temporal interpolation method for obtaining synthetic images with spatial resolution of TM (30 m) and temporal of MODIS (1 day), extending the application range of this one. Furthermore, we have analyzed some of the factors that affect the recorded data, such as the relative position of the satellite with the ground point, and the rainfall events, which alter the obtained results. On the other hand, we have proven the validity of the proposed model in the study of the organic contamination in inland water bodies. Finally, we have demonstrated a good performance of the proposed model in all cases tested, as well as its flexibility and adaptability.

Use of prediction methods for patent and trademark applications in Spain

Patent and trademark offices which run according to principles of new management have an inherent need for dependable forecasting data in planning capacity and service levels. The ability of the Spanish Office of Patents and Trademarks to carry out efficient planning of its resource needs requires the use of methods which allow it to predict the changes in the number of patent and trademark applications at different time horizons. The approach for the prediction of time series of Spanish patents and trademarks applications (1979e2009) was based on the use of different techniques of time series prediction in a short-term horizon. The methods used can be grouped into two specifics areas: regression models of trends and time series models. The results of this study show that it is possible to model the series of patents and trademarks applications with different models, especially ARIMA, with satisfactory model adjustment and relatively low error.

Comparison of dynamic effects of high-speed traffic load on ballasted track using a simplified two-dimensional and full three-dimensional model.

The vertical dynamic actions transmitted by railway vehicles to the ballasted track infrastructure is evaluated taking into account models with different degree of detail. In particular, we have studied this matter from a two-dimensional (2D) finite element model to a fully coupled three-dimensional (3D) multi-body finite element model. The vehicle and track are coupled via a non-linear Hertz contact mechanism. The method of Lagrange multipliers is used for the contact constraint enforcement between wheel and rail. Distributed elevation irregularities are generated based on power spectral density (PSD) distributions which are taken into account for the interaction. The numerical simulations are performed in the time domain, using a direct integration method for solving the transient problem due to the contact nonlinearities. The results obtained include contact forces, forces transmitted to the infrastructure (sleeper) by railpads and envelopes of relevant results for several track irregularities and speed ranges. The main contribution of this work is to identify and discuss coincidences and differences between discrete 2D models and continuum 3D models, as wheel as assessing the validity of evaluating the dynamic loading on the track with simplified 2D models

A methodology for the implementation and continuous improvement of social responsibility (RS) and financial responsibility

This work sets out an innovative methodology that aims to facilitate the implementation and continuous improvement of Social Responsibility. It is a methodology that takes account of strategic-economic, social and environmental questions and allows measuring the impact of each of these aspects on the stakeholders and on each of the value areas. It can be extrapolated to all kinds of organisations regardless of their size and sector and admits scaleable models. A marked feature that sets it aside from other methodologies is that it eliminates subjectivity from the qualitative aspects and introduces an algorithm to quantify them.

Load displacement in grape harvesters: Discrete Element Analysis.

Dynamic weighing of the hopper in grape harvesters is affected by a number of factors. One of them is the displacement of the load inside the hopper as a consequence of the terrain topography. In this work, the weight obtained by a load cell in a grape harvester has been analysed and quantified using the discrete element method (DEM). Different models have been developed considering different scenarios for the terrain.