Cenozoic evolution of eastern Iberia: structural data and dynamic model.

Iberia underwent intraplate deformation during the Mesozoic and Cenozoic. In eastem Ibena, compression took place during the Palaeogene and early Miocene, giving rise to the Iberian Chain, and extension started during the early Miocene in the coastal areas and the Valencia trough; during early Miocene compression continued in the western Iberian Chain whereas extension had started in the eastern Iberian Chain. From the kinematic data obtained from the major compressional and extensional structures formed dunng the Cenozoic, a simple dynamic model using Bott's (1959) formula is presented. The results show that both extension and compression may have been produced assuming a main horizontal stress-axis approximately N-S, in a similar direction that the convergence between Europe, Ibena and Afnca dunng the Cenozoic.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

Respiratory health effects of fifteen years of improved collective protection in a wheat-processing worker population.

INTRODUCTION: Occupational exposure to grain dust causes respiratory symptoms and pathologies. To decrease these effects, major changes have occurred in the grain processing industry in the last twenty years. However, there are no data on the effects of these changes on workers' respiratory health. OBJECTIVES: The aim of this study was to evaluate the respiratory health of grain workers and farmers involved in different steps of the processing industry of wheat, the most frequently used cereal in Europe, fifteen years after major improvements in collective protective equipment due to mechanisation. MATERIALS AND METHOD: Information on estimated personal exposure to wheat dust was collected from 87 workers exposed to wheat dust and from 62 controls. Lung function (FEV1, FVC, and PEF), exhaled nitrogen monoxide (FENO) and respiratory symptoms were assessed after the period of highest exposure to wheat during the year. Linear regression models were used to explore the associations between exposure indices and respiratory effects. RESULTS: Acute symptoms - cough, sneezing, runny nose, scratchy throat - were significantly more frequent in exposed workers than in controls. Increased mean exposure level, increased cumulative exposure and chronic exposure to more than 6 mg.m (-3) of inhaled wheat dust were significantly associated with decreased spirometric parameters, including FEV1 and PEF (40 ml and 123 ml.s (-1) ), FEV1 and FVC (0.4 ml and 0.5 ml per 100 h.mg.m (-3) ), FEV1 and FVC (20 ml and 20 ml per 100 h at >6 mg.m (-3) ). However, no increase in FENO was associated with increased exposure indices. CONCLUSIONS: The lung functions of wheat-related workers are still affected by their cumulative exposure to wheat dust, despite improvements in the use of collective protective equipment.

Smoking cessation and the incidence of pre-diabetes and type 2 diabetes: a cohort study.

AIMS: Smoking cessation has been suggested to increase the short-term risk of type 2 diabetes mellitus (T2DM). This study aimed at assessing the association between smoking cessation and incidence of T2DM and impaired fasting glucose (IFG). METHODS: Data from participants in the CoLaus study, Switzerland, aged 35-75 at baseline and followed for 5.5years were used. Participants were classified as smokers, recent (≤5years), long-term (>5years) quitters, and non-smokers at baseline. Outcomes were IFG (fasting serum glucose (FSG) 5.6-6.99mmol/l) and T2DM (FSG ≥7.0mmol/l and/or treatment) at follow up. RESULTS: 3,166 participants (63% women) had normal baseline FSG, of whom 26.7% were smokers, 6.5% recent quitters, and 23.5% long-term quitters. During follow-up 1,311 participants (41.4%) developed IFG (33.6% women, 54.7% men) and 47 (1.5%) developed T2DM (1.1% women, 2.1% men). Former smokers did not have statistically significant increased odds of IFG compared with smokers after adjustment for age, education, physical activity, hypercholesterolemia, hypertension and alcohol intake, with OR of 1.29 [95% confidence interval 0.94-1.76] for recent quitters and 1.03 [0.84-1.27] for long-term quitters. Former smokers did not have significant increased odds of T2DM compared with smokers with multivariable-adjusted OR of 1.53 [0.58-4.00] for recent quitters and 0.64 [0.27-1.48] for long-term quitters. Adjustment for body-mass index and waist circumference attenuated the association between recent quitting and IFG (OR 1.07 [0.78-1.48]) and T2DM (OR 1.28 [0.48-3.40]. CONCLUSION: In this middle-aged population, smoking cessation was not associated with an increased risk of IFG or T2DM.

Image processing of false identity documents for forensic intelligence

Forensic intelligence has recently gathered increasing attention as a potential expansion of forensic science that may contribute in a wider policing and security context. Whilst the new avenue is certainly promising, relatively few attempts to incorporate models, methods and techniques into practical projects are reported. This work reports a practical application of a generalised and transversal framework for developing forensic intelligence processes referred to here as the Transversal model adapted from previous work. Visual features present in the images of four datasets of false identity documents were systematically profiled and compared using image processing for the detection of a series of modus operandi (M.O.) actions. The nature of these series and their relation to the notion of common source was evaluated with respect to alternative known information and inferences drawn regarding respective crime systems. 439 documents seized by police and border guard authorities across 10 jurisdictions in Switzerland with known and unknown source level links formed the datasets for this study. Training sets were developed based on both known source level data, and visually supported relationships. Performance was evaluated through the use of intra-variability and inter-variability scores drawn from over 48,000 comparisons. The optimised method exhibited significant sensitivity combined with strong specificity and demonstrates its ability to support forensic intelligence efforts.

Psychosocial Quality-of-Life, Lifestyle and Adiposity: A Longitudinal Study in Pre-schoolers (Ballabeina Study).

PURPOSE: In obesity prevention, understanding psychosocial influences in early life is pivotal. Reviews reported contradictory results and a lack of longitudinal studies focusing on underlying lifestyle factors. This study tested whether psychosocial Quality-Of-Life (QOL) was associated with pre-schoolers' lifestyle and adiposity changes over one school year and whether lifestyle moderated the latter. It was hypothesised that QOL might not impact adiposity in everybody but that this might depend on preceding lifestyle. METHOD: Longitudinal data from 291 Swiss pre-schoolers (initially 3.9-6.3 years) was available. The following measures were used in longitudinal regressions: psychosocial QOL by PedsQL, adiposity (BMI z-score, waist, fat%), diet (food frequency), sedentary time and accelerometer-based activity. RESULTS: Concerning lifestyle, low psychosocial QOL was only related to unfavourable changes in diet (less fruit β = 0.21 and more fat intake β = -0.28) and lower physical activity (β = 0.21). Longitudinal QOL-adiposity relations appeared only after moderation by lifestyle factors (beta-range 0.13-0.67). Low psychosocial QOL was associated with increased adiposity in children with an unhealthy diet intake or high sedentary time. By contrast, low psychosocial QOL was associated with decreasing adiposity in high fruit consumers or more physically active pre-schoolers. CONCLUSION: Results emphasise the need for testing moderation in the QOL-adiposity relation. An unhealthy diet can be a vulnerability factor and high physical activity a protective factor in QOL-related adiposity. Consequently, QOL and lifestyle should be targeted concurrently in multi-factorial obesity prevention. The environment should be an 'activity encouraging, healthy food zone' that minimises opportunities for stress-induced eating. In addition, appropriate stress coping skills should be acquired.

Cost Optimisation of Mobile Advertising Client Data Transfer

Data traffic caused by mobile advertising client software when it is communicating with the network server can be a pain point for many application developers who are considering advertising-funded application distribution, since the cost of the data transfer might scare their users away from using the applications. For the thesis project, a simulation environment was built to mimic the real client-server solution for measuring the data transfer over varying types of connections with different usage scenarios. For optimising data transfer, a few general-purpose compressors and XML-specific compressors were tried for compressing the XML data, and a few protocol optimisations were implemented. For optimising the cost, cache usage was improved and pre-loading was enhanced to use free connections to load the data. The data traffic structure and the various optimisations were analysed, and it was found that the cache usage and pre-loading should be enhanced and that the protocol should be changed, with report aggregation and compression using WBXML or gzip.

One, two, or many mechanisms? The brain's processing of complex words

The heated debate over whether there is only a single mechanism or two mechanisms for morphology has diverted valuable research energy away from the more critical questions about the neural computations involved in the comprehension and production of morphologically complex forms. Cognitive neuroscience data implicate many brain areas. All extant models, whether they rely on a connectionist network or espouse two mechanisms, are too underspecified to explain why more than a few brain areas differ in their activity during the processing of regular and irregular forms. No one doubts that the brain treats regular and irregular words differently, but brain data indicate that a simplistic account will not do. It is time for us to search for the critical factors free from theoretical blinders.

Identification of the Emerging Issues in Recycled Fiber Processing

The objectives of this research work “Identification of the Emerging Issues in Recycled Fiber processing” are discovering of emerging research issues and presenting of new approaches to identify promising research themes in recovered paper application and production. The projected approach consists of identifying technological problems often encountered in wastepaper preparation processes and also improving the quality of recovered paper and increasing its proportion in the composition of paper and board. The source of information for the problem retrieval is scientific publications in which waste paper application and production were discussed. The study has exploited several research methods to understand the changes related to utilization of recovered paper. The all assembled data was carefully studied and categorized by applying software called RefViz and CiteSpace. Suggestions were made on the various classes of these problems that need further investigation in order to propose an emerging research trends in recovered paper.

The importance of pre-treatment of spent hydrotreating catalysts on metals recovery

This work describes a three-step pre-treatment route for processing spent commercial NiMo/Al2O3 catalysts. Extraction of soluble coke with n-hexane and/or leaching of foulant elements with oxalic acid were performed before burning insoluble coke under air. Oxidized catalysts were leached with 9 mol L-1 sulfuric acid. Iron was the only foulant element partially leached by oxalic acid. The amount of insoluble matter in sulfuric acid was drastically reduced when iron and/or soluble coke were previously removed. Losses of active phase metals (Ni, Mo) during leaching with oxalic acid were compensated by the increase of their recovery in the sulfuric acid leachate.

Customer knowledge processing in key account management

The ability of the supplier firm to generate and utilise customer-specific knowledge has attracted increasing attention in the academic literature during the last decade. It has been argued the customer knowledge should treated as a strategic asset the same as any other intangible assets. Yet, at the same time it has been shown that the management of customer-specific knowledge is challenging in practice, and that many firms are better at acquiring customer knowledge than at making use of it. This study examines customer knowledge processing in the context of key account management in large industrial firms. This focus was chosen because key accounts are demanding and complex. It is not unusual for a single key account relationship to constitute a complex web of relationships between the supplier and the key account – thus easily leading to the dispersion of customer-specific knowledge in the supplier firm. Although the importance of customer-specific knowledge generation has been widely acknowledged in the literature, surprisingly little attention has been paid to the processes through which firms generate, disseminate and use such knowledge internally for enhancing the relationships with their major, strategically important key account customers. This thesis consists of two parts. The first part comprises a theoretical overview and draws together the main findings of the study, whereas the second part consists of five complementary empirical research papers based on survey data gathered from large industrial firms in Finland. The findings suggest that the management of customer knowledge generated about and form key accounts is a three-dimensional process consisting of acquisition, dissemination and utilization. It could be concluded from the results that customer-specific knowledge is a strategic asset because the supplier’s customer knowledge processing activities have a positive effect on supplier’s key account performance. Moreover, in examining the determinants of each phase separately the study identifies a number of intra-organisational factors that facilitate the process in supplier firms. The main contribution of the thesis lies in linking the concept of customer knowledge processing to the previous literature on key account management. Moreover, given than this literature is mainly conceptual or case-based, a further contribution is to examine its consequences and determinants based on quantitative empirical data.

Financial losses in pork supply chain: a study of the pre-slaughter handling impacts

Brazil is amongst the world’s largest swine producers. However, its competitiveness has been vulnerable due to a lack of cooperation between the supply chain players. This condition makes the financial losses to be evaluated taking into account only an individual node, and most of the time, these damages are imputed by swine breeders. Living weight losses occur between the farm to slaughterhouses, and the main cause of these losses is the pre-slaughter handling, especially during animal transportation. In this research, we analyzed the pre-slaughter handling in a swine farm in Brasilândia, MS, Brazil. Analyzed data were provided by five slaughterhouses (farm clients) from the studied region, in which it was considered living weight losses, carcass bruising, animal injury, and death rate. The results indicated that total financial losses represent 160 thousand dollars per year, when taking into account the supply chain management.

Novel Regression Methods For Spectral Data

Singular Value Decomposition (SVD), Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) are some of the mathematical pre- liminaries that are discussed prior to explaining PLS and PCR models. Both PLS and PCR are applied to real spectral data and their di erences and similarities are discussed in this thesis. The challenge lies in establishing the optimum number of components to be included in either of the models but this has been overcome by using various diagnostic tools suggested in this thesis. Correspondence analysis (CA) and PLS were applied to ecological data. The idea of CA was to correlate the macrophytes species and lakes. The di erences between PLS model for ecological data and PLS for spectral data are noted and explained in this thesis. i