47 resultados para optimized process


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This thesis studies human gene expression space using high throughput gene expression data from DNA microarrays. In molecular biology, high throughput techniques allow numerical measurements of expression of tens of thousands of genes simultaneously. In a single study, this data is traditionally obtained from a limited number of sample types with a small number of replicates. For organism-wide analysis, this data has been largely unavailable and the global structure of human transcriptome has remained unknown. This thesis introduces a human transcriptome map of different biological entities and analysis of its general structure. The map is constructed from gene expression data from the two largest public microarray data repositories, GEO and ArrayExpress. The creation of this map contributed to the development of ArrayExpress by identifying and retrofitting the previously unusable and missing data and by improving the access to its data. It also contributed to creation of several new tools for microarray data manipulation and establishment of data exchange between GEO and ArrayExpress. The data integration for the global map required creation of a new large ontology of human cell types, disease states, organism parts and cell lines. The ontology was used in a new text mining and decision tree based method for automatic conversion of human readable free text microarray data annotations into categorised format. The data comparability and minimisation of the systematic measurement errors that are characteristic to each lab- oratory in this large cross-laboratories integrated dataset, was ensured by computation of a range of microarray data quality metrics and exclusion of incomparable data. The structure of a global map of human gene expression was then explored by principal component analysis and hierarchical clustering using heuristics and help from another purpose built sample ontology. A preface and motivation to the construction and analysis of a global map of human gene expression is given by analysis of two microarray datasets of human malignant melanoma. The analysis of these sets incorporate indirect comparison of statistical methods for finding differentially expressed genes and point to the need to study gene expression on a global level.

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In visual object detection and recognition, classifiers have two interesting characteristics: accuracy and speed. Accuracy depends on the complexity of the image features and classifier decision surfaces. Speed depends on the hardware and the computational effort required to use the features and decision surfaces. When attempts to increase accuracy lead to increases in complexity and effort, it is necessary to ask how much are we willing to pay for increased accuracy. For example, if increased computational effort implies quickly diminishing returns in accuracy, then those designing inexpensive surveillance applications cannot aim for maximum accuracy at any cost. It becomes necessary to find trade-offs between accuracy and effort. We study efficient classification of images depicting real-world objects and scenes. Classification is efficient when a classifier can be controlled so that the desired trade-off between accuracy and effort (speed) is achieved and unnecessary computations are avoided on a per input basis. A framework is proposed for understanding and modeling efficient classification of images. Classification is modeled as a tree-like process. In designing the framework, it is important to recognize what is essential and to avoid structures that are narrow in applicability. Earlier frameworks are lacking in this regard. The overall contribution is two-fold. First, the framework is presented, subjected to experiments, and shown to be satisfactory. Second, certain unconventional approaches are experimented with. This allows the separation of the essential from the conventional. To determine if the framework is satisfactory, three categories of questions are identified: trade-off optimization, classifier tree organization, and rules for delegation and confidence modeling. Questions and problems related to each category are addressed and empirical results are presented. For example, related to trade-off optimization, we address the problem of computational bottlenecks that limit the range of trade-offs. We also ask if accuracy versus effort trade-offs can be controlled after training. For another example, regarding classifier tree organization, we first consider the task of organizing a tree in a problem-specific manner. We then ask if problem-specific organization is necessary.

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Composting refers to aerobic degradation of organic material and is one of the main waste treatment methods used in Finland for treating separated organic waste. The composting process allows converting organic waste to a humus-like end product which can be used to increase the organic matter in agricultural soils, in gardening, or in landscaping. Microbes play a key role as degraders during the composting-process, and the microbiology of composting has been studied for decades, but there are still open questions regarding the microbiota in industrial composting processes. It is known that with the traditional, culturing-based methods only a small fraction, below 1%, of the species in a sample is normally detected. In recent years an immense diversity of bacteria, fungi and archaea has been found to occupy many different environments. Therefore the methods of characterising microbes constantly need to be developed further. In this thesis the presence of fungi and bacteria in full-scale and pilot-scale composting processes was characterised with cloning and sequencing. Several clone libraries were constructed and altogether nearly 6000 clones were sequenced. The microbial communities detected in this study were found to differ from the compost microbes observed in previous research with cultivation based methods or with molecular methods from processes of smaller scale, although there were similarities as well. The bacterial diversity was high. Based on the non-parametric coverage estimations, the number of bacterial operational taxonomic units (OTU) in certain stages of composting was over 500. Sequences similar to Lactobacillus and Acetobacteria were frequently detected in the early stages of drum composting. In tunnel stages of composting the bacterial community comprised of Bacillus, Thermoactinomyces, Actinobacteria and Lactobacillus. The fungal diversity was found to be high and phylotypes similar to yeasts were abundantly found in the full-scale drum and tunnel processes. In addition to phylotypes similar to Candida, Pichia and Geotrichum moulds from genus Thermomyces and Penicillium were observed in tunnel stages of composting. Zygomycetes were detected in the pilot-scale composting processes and in the compost piles. In some of the samples there were a few abundant phylotypes present in the clone libraries that masked the rare ones. The rare phylotypes were of interest and a method for collecting them from clone libraries for sequencing was developed. With negative selection of the abundant phylotyps the rare ones were picked from the clone libraries. Thus 41% of the clones in the studied clone libraries were sequenced. Since microbes play a central role in composting and in many other biotechnological processes, rapid methods for characterization of microbial diversity would be of value, both scientifically and commercially. Current methods, however, lack sensitivity and specificity and are therefore under development. Microarrays have been used in microbial ecology for a decade to study the presence or absence of certain microbes of interest in a multiplex manner. The sequence database collected in this thesis was used as basis for probe design and microarray development. The enzyme assisted detection method, ligation-detection-reaction (LDR) based microarray, was adapted for species-level detection of microbes characteristic of each stage of the composting process. With the use of a specially designed control probe it was established that a species specific probe can detect target DNA representing as little as 0.04% of total DNA in a sample. The developed microarray can be used to monitor composting processes or the hygienisation of the compost end product. A large compost microbe sequence dataset was collected and analysed in this thesis. The results provide valuable information on microbial community composition during industrial scale composting processes. The microarray method was developed based on the sequence database collected in this study. The method can be utilised in following the fate of interesting microbes during composting process in an extremely sensitive and specific manner. The platform for the microarray is universal and the method can easily be adapted for studying microbes from environments other than compost.

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Cytomegalovirus (CMV) is a major cause of morbidity, costs and even mortality in organ transplant recipients. CMV may also enhance the development of chronic allograft nephropathy (CAN), which is the most important cause of graft loss after kidney transplantation. The evidence for the role of CMV in chronic allograft nephropathy is somewhat limited, and controversial results have also been reported. The aim of this study was to investigate the role of CMV in the pathogenesis of CAN. Material for the purpose of this study was available from altogether 70 kidney transplant recipients who received a kidney transplant between the years 1992-2000. CMV infection was diagnosed with pp65 antigenemia test or by viral culture from blood, urine, or both. CMV proteins were demonstrated in the kidney allograft biopsies by immunohistochemisrty and CMV-DNA by in situ hybridization. Cytokines, adhesion molecules, and growth factors were demonstrated from allograft biopsies by immunohistochemistry, and from urinary samples by ELISA-methods. CMV proteins were detectable in the 6-month protocol biopsies from 18/41 recipients with evidence of CMV infection. In the histopathological analysis of the 6-month protocol biopsies, presence of CMV in the allograft together with a previous history of acute rejection episodes was associated with increased arteriosclerotic changes in small arterioles. In urinary samples collected during CMV infection, excretion of TGF-β was significantly increased. In recipients with increased urinary excretion of TGF-β, increased interstitial fibrosis was recorded in the 6- month protocol biopsies. In biopsies taken after an active CMV infection, CMV persisted in the kidney allograft in 17/48 recipients, as CMV DNA or antigens were detected in the biopsies more than 2 months after the last positive finding in blood or urine. This persistence was associated with increased expression of TGF-β, PDGF, and ICAM-1 and with increased vascular changes in the allografts. Graft survival and graft function one and two years after transplantation were reduced in recipients with persistent intragraft CMV. Persistent intragraft CMV infection was also a risk factor for reduced graft survival in Cox regression analysis, and an independent risk factor for poor graft function one and two years after transplantation in logistic regression analysis. In conclusion, these results show that persistent intragraft CMV infection is detrimental to kidney allografts, causing increased expression of growth factors and increased vascular changes, leading to reduced graft function and survival. Effective prevention, diagnosis and treatment of CMV infections may a major factor in improving the long term survival of kidney allograft.

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Thin films are the basis of much of recent technological advance, ranging from coatings with mechanical or optical benefits to platforms for nanoscale electronics. In the latter, semiconductors have been the norm ever since silicon became the main construction material for a multitude of electronical components. The array of characteristics of silicon-based systems can be widened by manipulating the structure of the thin films at the nanoscale - for instance, by making them porous. The different characteristics of different films can then to some extent be combined by simple superposition. Thin films can be manufactured using many different methods. One emerging field is cluster beam deposition, where aggregates of hundreds or thousands of atoms are deposited one by one to form a layer, the characteristics of which depend on the parameters of deposition. One critical parameter is deposition energy, which dictates how porous, if at all, the layer becomes. Other parameters, such as sputtering rate and aggregation conditions, have an effect on the size and consistency of the individual clusters. Understanding nanoscale processes, which cannot be observed experimentally, is fundamental to optimizing experimental techniques and inventing new possibilities for advances at this scale. Atomistic computer simulations offer a window to the world of nanometers and nanoseconds in a way unparalleled by the most accurate of microscopes. Transmission electron microscope image simulations can then bridge this gap by providing a tangible link between the simulated and the experimental. In this thesis, the entire process of cluster beam deposition is explored using molecular dynamics and image simulations. The process begins with the formation of the clusters, which is investigated for Si/Ge in an Ar atmosphere. The structure of the clusters is optimized to bring it as close to the experimental ideal as possible. Then, clusters are deposited, one by one, onto a substrate, until a sufficiently thick layer has been produced. Finally, the concept is expanded by further deposition with different parameters, resulting in multiple superimposed layers of different porosities. This work demonstrates how the aggregation of clusters is not entirely understood within the scope of the approximations used in the simulations; yet, it is also shown how the continued deposition of clusters with a varying deposition energy can lead to a novel kind of nanostructured thin film: a multielemental porous multilayer. According to theory, these new structures have characteristics that can be tailored for a variety of applications, with precision heretofore unseen in conventional multilayer manufacture.

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The ProFacil model is a generic process model defined as a framework model showing the links between the facilities management process and the building end user’s business process. The purpose of using the model is to support more detailed process modelling. The model has been developed using the IDEF0 modelling method. The ProFacil model describes business activities from the generalized point of view as management-, support-, and core processes and their relations. The model defines basic activities in the provision of a facility. Examples of these activities are “operate facilities”, “provide new facilities”, “provide re-build facilities”, “provide maintained facilities” and “perform dispose of facilities”. These are all generic activities providing a basis for a further specialisation of company specific FM activities and their tasks. A facilitator can establish a specialized process model using the ProFacil model and interacting with company experts to describe their company’s specific processes. These modelling seminars or interviews will be done in an informal way, supported by the high-level process model as a common reference.

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A model of the information and material activities that comprise the overall construction process is presented, using the SADT activity modelling methodology. The basic model is further refined into a number of generic information handling activities such as creation of new information, information search and retrieval, information distribution and person-to-person communication. The viewpoint could be described as information logistics. This model is then combined with a more traditional building process model, consisting of phases such as design and construction. The resulting two-dimensional matrix can be used for positioning different types of generic IT-tools or construction specific applications. The model can thus provide a starting point for a discussion of the application of information and communication technology in construction and for measurements of the impacts of IT on the overall process and its related costs.

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The industry foundation classes (IFC) file format is one of the most complex and ambitious IT standardization projects currently being undertaken in any industry, focusing on the development of an open and neutral standard for exchanging building model data. Scientific literature related to the IFC standard has dominantly been technical so far; research looking at the IFC standard from an industry standardization per- spective could offer valuable new knowledge for both theory and practice. This paper proposes the use of IT standardization and IT adoption theories, supported by studies done within construction IT, to lay a theoretical foundation for further empirical analysis of the standardization process of the IFC file format.

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There has been a demand for uniform CAD standards in the construction industry ever since the large-scale introduction of computer aided design systems in the late 1980s. While some standards have been widely adopted without much formal effort, other standards have failed to gain support even though considerable resources have been allocated for the purpose. Establishing a standard concerning building information modeling has been one particularly active area of industry development and scientific interest within recent years. In this paper, four different standards are discussed as cases: the IGES and DXF/DWG standards for representing the graphics in 2D drawings, the ISO 13567 standard for the structuring of building information on layers, and the IFC standard for building product models. Based on a literature study combined with two qualitative interview studies with domain experts, a process model is proposed to describe and interpret the contrasting histories of past CAD standardisation processes.

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The driving force behind this study is the gap between the reality of the firms engaged in project business and the available studies covering project management and business process development. Previous studies show that project-based organizations were ‘immature’ in terms of the project-management ‘maturity model’, as few firms were found to be optimizing processes. Even within those, very little attention was paid to combine inter-organizational and intra-organizational perspectives. In this study an effort is made to elaborate some thoughts and views on project management, which interrelate firms’ external and internal activities. In line with the integration, the dissertation uses an approach to the management of project-business interdependencies in the networks of actors, activities and resources. Firstly, the study develops an understanding for inter-organizational perspectives by exploring the complementarities of process activities in the basic development of project business. It presents a framework that is elaborated on the basis of the reciprocal interactions of activities within and outside the organization—thus providing a coherent basis for continuous business-process improvement. In addition, the study presents new tools that can be used to develop project-business processes in each of its functional areas. The research demonstrates how project-business activities can be optimized using the right resources at the right time with the right actors and the right actions. The selected five articles included in this dissertation explain the basic framework for the development of project business. Each paper covers various aspects of inter-organizational and intra-organizational perspectives for project management. The study develops a valuable and procedural model for business-process improvement using the Delphi method that can be used not only in academia but also as a guide for practitioners that takes them through a series of well-defined steps when making informed, consistent and efficient changes to their business processes.

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This study contributes to our knowledge of how information contained in financial statements is interpreted and priced by the stock market in two aspects. First, the empirical findings indicate that investors interpret some of the information contained in new financial statements in the context of the information of prior financial statements. Second, two central hypotheses offered in earlier literature to explain the significant connection between publicly available financial statement information and future abnormal returns, that the signals proxy for risk and that the information is priced with a delay, are evaluated utilizing a new methodology. It is found that the mentioned significant connection for some financial statement signals can be explained by that the signals proxy for risk and for other financial statement signals by that the information contained in the signals is priced with a delay.