Future development of gastrointestinal cancer incidence and mortality rates in Switzerland: a tumour registry- and population-based projection up to 2030.

QUESTIONS UNDER STUDY: Since tumour burden consumes substantial healthcare resources, precise cancer incidence estimations are pivotal to define future needs of national healthcare. This study aimed to estimate incidence and mortality rates of oesophageal, gastric, pancreatic, hepatic and colorectal cancers up to 2030 in Switzerland. METHODS: Swiss Statistics provides national incidences and mortality rates of various cancers, and models of future developments of the Swiss population. Cancer incidences and mortality rates from 1985 to 2009 were analysed to estimate trends and to predict incidence and mortality rates up to 2029. Linear regressions and Joinpoint analyses were performed to estimate the future trends of incidences and mortality rates. RESULTS: Crude incidences of oesophageal, pancreas, liver and colorectal cancers have steadily increased since 1985, and will continue to increase. Gastric cancer incidence and mortality rates reveal an ongoing decrease. Pancreatic and liver cancer crude mortality rates will keep increasing, whereas colorectal cancer mortality on the contrary will fall. Mortality from oesophageal cancer will plateau or minimally increase. If we consider European population-standardised incidence rates, oesophageal, pancreatic and colorectal cancer incidences are steady. Gastric cancers are diminishing and liver cancers will follow an increasing trend. Standardised mortality rates show a diminution for all but liver cancer. CONCLUSIONS: The oncological burden of gastrointestinal cancer will significantly increase in Switzerland during the next two decades. The crude mortality rates globally show an ongoing increase except for gastric and colorectal cancers. Enlarged healthcare resources to take care of these complex patient groups properly will be needed.

Development and validation of a visual grading scale for assessing image quality of AP pelvis radiographic images.

OBJECTIVE: The aim of this article was to apply psychometric theory to develop and validate a visual grading scale for assessing the visual perception of digital image quality anteroposterior (AP) pelvis. METHODS: Psychometric theory was used to guide scale development. Seven phantom and seven cadaver images of visually and objectively predetermined quality were used to help assess scale reliability and validity. 151 volunteers scored phantom images, and 184 volunteers scored cadaver images. Factor analysis and Cronbach's alpha were used to assess scale validity and reliability. RESULTS: A 24-item scale was produced. Aggregated mean volunteer scores for each image correlated with the rank order of the visually and objectively predetermined image qualities. Scale items had good interitem correlation (≥0.2) and high factor loadings (≥0.3). Cronbach's alpha (reliability) revealed that the scale has acceptable levels of internal reliability for both phantom and cadaver images (α = 0.8 and 0.9, respectively). Factor analysis suggested that the scale is multidimensional (assessing multiple quality themes). CONCLUSION: This study represents the first full development and validation of a visual image quality scale using psychometric theory. It is likely that this scale will have clinical, training and research applications. ADVANCES IN KNOWLEDGE: This article presents data to create and validate visual grading scales for radiographic examinations. The visual grading scale, for AP pelvis examinations, can act as a validated tool for future research, teaching and clinical evaluations of image quality.

Combining Advanced Forecasting Methods with System Dynamics - the Case of Finnish Seaports

Seaports play an important part in the wellbeing of a nation. Many nations are highly dependent on foreign trade and most trade is done using sea vessels. This study is part of a larger research project, where a simulation model is required in order to create further analyses on Finnish macro logistical networks. The objective of this study is to create a system dynamic simulation model, which gives an accurate forecast for the development of demand of Finnish seaports up to 2030. The emphasis on this study is to show how it is possible to create a detailed harbor demand System Dynamic model with the help of statistical methods. The used forecasting methods were ARIMA (autoregressive integrated moving average) and regression models. The created simulation model gives a forecast with confidence intervals and allows studying different scenarios. The building process was found to be a useful one and the built model can be expanded to be more detailed. Required capacity for other parts of the Finnish logistical system could easily be included in the model.

Reduction and Analysis Methods of Indigo

Throughout history indigo was derived from various plants for example Dyer’s Woad (Isatis tinctoria L.) in Europe. In the 19th century were the synthetic dyes developed and nowadays indigo is mainly synthesized from by-products of fossil fuels. Indigo is a so-called vat dye, which means that it needs to be reduced to its water soluble leucoform before dyeing. Nowadays, most of the industrial reduction is performed chemically by sodium dithionite. However, this is considered environmentally unfavourable because of waste waters contaminating degradation products. Therefore there has been interest to find new possibilities to reduce indigo. Possible alternatives for the application of dithionite as the reducing agent are biologically induced reduction and electrochemical reduction. Glucose and other reducing sugars have recently been suggested as possible environmentally friendly alternatives as reducing agents for sulphur dyes and there have also been interest in using glucose to reduce indigo. In spite of the development of several types of processes, very little is known about the mechanism and kinetics associated with the reduction of indigo. This study aims at investigating the reduction and electrochemical analysis methods of indigo and give insight on the reduction mechanism of indigo. Anthraquinone as well as it’s derivative 1,8-dihydroxyanthraquinone were discovered to act as catalysts for the glucose induced reduction of indigo. Anthraquinone introduces a strong catalytic effect which is explained by invoking a molecular “wedge effect” during co-intercalation of Na+ and anthraquinone into the layered indigo crystal. The study includes also research on the extraction of plant-derived indigo from woad and the examination of the effect of this method to the yield and purity of indigo. The purity has been conventionally studied spectrophotometrically and a new hydrodynamic electrode system is introduced in this study. A vibrating probe is used in following electrochemically the leuco-indigo formation with glucose as a reducing agent.

Improving the effectiveness of supply chain development work – an expert role perspective

This study focuses to the intersection of three sets of activities in a company: expert work, development work and supply chain management, SCM. Experts and expert work represent a set of individuals whose efficiency and impact this study is intended to improve, while development work defines the set of organizational activities to focus on. SCM as an expertise area acts as the platform on which this study is built. The study has two aims. Firstly, it aims to derive a model helping an SCM expert to increase the effectiveness of expert work in development tasks by understanding the encountered organizational situations and processes better, reflecting his/her past and future actions to organizational processes and selecting and adjusting the processes and contents of his/her work accordingly. Secondly, it aims to develop applicable approaches and methods to understand, evaluate and manage the organizational processes and situations in development work. The integrative model on approaches and methods to improve the effectiveness of development processes is split to two aggregate dimensions: technical performance of the developed solution and consumption of resources of the development process. Six potential approaches and methods aiming at helping in the management of organizational dimensions are presented in enclosed publications. The approaches focus on three subtasks of development work: decision making, implementation and change, and knowledge accumulation. The approaches and methods have been tested in case studies representing typical development processes in the area of supply chain management. As a result, four suggestions are presented. Firstly, SCM experts are advised to consider the SCM development work to be consisting of development processes. Secondly, inside these processes they should identify and evaluate the risk of difficult decision-making related to organizational factors. Thirdly, they are prompted for an active role in implementation and change, supporting the implementation through whole process. Finally, the development should be seen in a holistic view, taking into account the stage of knowledge and organizational issues related to it, and adopt a knowledge development strategy.

Development of tender information process by business intelligence in a global company unit

The purpose of this Thesis was to study what is the present situation of Business Intelligence of the company unit. This means how efficiently unit uses possibilities of modern information management systems. The aim was to resolve how operative informa-tion management of unit’s tender process could be improved by modern information technology applications. This makes it possible that tender processes could be faster and more efficiency. At the beginning it was essential to acquaint oneself with written literature of Business Intelligence. Based on Business Intelligence theory is was relatively easy but challenging to search and discern how tender business could be improved by methods of Busi-ness Intelligence. The empirical phase of this study was executed as qualitative research method. This phase includes theme and natural interviews on the company. Problems and challenges of tender process were clarified in a part an empirical phase. Group of challenges were founded when studying information management of company unit. Based on theory and interviews, group of improvements were listed which company could possible do in the future when developing its operative processes.

Offering planning process development: Bridging the Offering Gaps and Consolidating Top Priority Needs in Product Offering

The aim of this Thesis is to study how to manage the front-end of the offering planning process. This includes actual process development and methods to gather and analyze information to achieve the best outcome in customer oriented product offering. Study is carried out in two parts: theoretical part and company related part. Theoretical framework is created introducing different types of approaches to manage product planning processes. Products are seen as platforms and they are broken down to subsystems to show different parts of the development. With the help of the matrix-based approaches product platform related information is gathered and analyzed. In this kind of analysis business/market drivers and cus-tomer/competitor information are connected with product subsystems. This gives possibilities to study product gaps/needs and possible future ideas/scenarios in different customer segments. Company related part consists of offering planning process development in real company environment. Process formation includes documents and tools that guide planning from the information gathering to the prioritization and decision making.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Competence Development and Capacity Building of Sawmill Enterprises in Kenya – A Human Resources Development Approach

The Kenyan forestry and sawmilling industry have been subject to a changing environment since 1999 when the industrial forest plantations were closed down. This has lowered raw material supply and it has affected and reduced the sawmill operations and the viability of the sawmill enterprises. The capacity of the 276 registered sawmills is not sufficient to fulfill sawn timber demand in Kenya. This is because of the technological degradation and lack of a qualified labor force, which were caused because of non-existent sawmilling education and further training in Kenya. Lack of competent sawmill workers has led to low raw material recovery, under utilization of resources and loss of employment. The objective of the work was to suggest models, methods and approaches for the competence and capacity development of the Kenyan sawmilling industry, sawmills and their workers. A nationwide field survey, interviews, questionnaire and literature review was used for data collection to find out the sawmills’ competence development areas and to suggest models and methods for their capacity building. The sampling frame included 22 sawmills that represented 72,5% of all the registered sawmills in Kenya. The results confirmed that the sawmills’ technological level was backwards, productivity low, raw material recovery unacceptable and workers’ professional education low. The future challenges will be how to establish the sawmills’ capacity building and workers’ competence development. Sawmilling industry development requires various actions through new development models and approaches. Activities should be started for technological development and workers’ competence development. This requires re-starting of vocational training in sawmilling and the establishment of more effective co-operation between the sawmills and their stakeholder groups. In competence development the Enterprise Competence Management Model of Nurminen (2007) can be used, whereas the best training model and approach would be a practically oriented learning at work model in which the short courses, technical assistance and extension services would be the key functions.

Development and validation of an alternative titration method for the determination of sulfate ion in indinavir sulfate

A simple and rapid precipitation titration method was developed and validated to determine sulfate ion content in indinavir sulfate raw material. 0.1 mol L-1 lead nitrate volumetric solution was used as titrant employing potentiometric endpoint determination using a lead-specific electrode. The United States Pharmacopoeia Forum indicates a potentiometric method for sulfate ion quantitation using 0.1 mol L-1 lead perchlorate as titrant. Both methods were validated concerning linearity, precision and accuracy, yielding good results. The sulfate ion content found by the two validated methods was compared by the statistical t-student test, indicating that there was no statistically significant difference between the methods.

Electrocatalysis and electrocatalysts for low temperature fuel cells: fundamentals, state of the art, research and development

This article deals with electrocatalysis and electrocatalysts for low temperature fuel cells and also with established means and methods in electrocatalyst research, development and characterization. The intention is to inform about the fundamentals, state of the art, research and development of noble metal electrocatalysts for fuel cells operating at low temperatures.

Methods for assessing the sustainability of integrated municipal waste management and

The general striving to bring down the number of municipal landfills and to increase the reuse and recycling of waste-derived materials across the EU supports the debates concerning the feasibility and rationality of waste management systems. Substantial decrease in the volume and mass of landfill-disposed waste flows can be achieved by directing suitable waste fractions to energy recovery. Global fossil energy supplies are becoming more and more valuable and expensive energy sources for the mankind, and efforts to save fossil fuels have been made. Waste-derived fuels offer one potential partial solution to two different problems. First, waste that cannot be feasibly re-used or recycled is utilized in the energy conversion process according to EU’s Waste Hierarchy. Second, fossil fuels can be saved for other purposes than energy, mainly as transport fuels. This thesis presents the principles of assessing the most sustainable system solution for an integrated municipal waste management and energy system. The assessment process includes: · formation of a SISMan (Simple Integrated System Management) model of an integrated system including mass, energy and financial flows, and · formation of a MEFLO (Mass, Energy, Financial, Legislational, Other decisionsupport data) decision matrix according to the selected decision criteria, including essential and optional decision criteria. The methods are described and theoretical examples of the utilization of the methods are presented in the thesis. The assessment process involves the selection of different system alternatives (process alternatives for treatment of different waste fractions) and comparison between the alternatives. The first of the two novelty values of the utilization of the presented methods is the perspective selected for the formation of the SISMan model. Normally waste management and energy systems are operated separately according to the targets and principles set for each system. In the thesis the waste management and energy supply systems are considered as one larger integrated system with one primary target of serving the customers, i.e. citizens, as efficiently as possible in the spirit of sustainable development, including the following requirements: · reasonable overall costs, including waste management costs and energy costs; · minimum environmental burdens caused by the integrated waste management and energy system, taking into account the requirement above; and · social acceptance of the selected waste treatment and energy production methods. The integrated waste management and energy system is described by forming a SISMan model including three different flows of the system: energy, mass and financial flows. By defining the three types of flows for an integrated system, the selected factor results needed in the decision-making process of the selection of waste management treatment processes for different waste fractions can be calculated. The model and its results form a transparent description of the integrated system under discussion. The MEFLO decision matrix has been formed from the results of the SISMan model, combined with additional data, including e.g. environmental restrictions and regional aspects. System alternatives which do not meet the requirements set by legislation can be deleted from the comparisons before any closer numerical considerations. The second novelty value of this thesis is the three-level ranking method for combining the factor results of the MEFLO decision matrix. As a result of the MEFLO decision matrix, a transparent ranking of different system alternatives, including selection of treatment processes for different waste fractions, is achieved. SISMan and MEFLO are methods meant to be utilized in municipal decision-making processes concerning waste management and energy supply as simple, transparent and easyto- understand tools. The methods can be utilized in the assessment of existing systems, and particularly in the planning processes of future regional integrated systems. The principles of SISMan and MEFLO can be utilized also in other environments, where synergies of integrating two (or more) systems can be obtained. The SISMan flow model and the MEFLO decision matrix can be formed with or without any applicable commercial or free-of-charge tool/software. SISMan and MEFLO are not bound to any libraries or data-bases including process information, such as different emission data libraries utilized in life cycle assessments.

Community-acquired pneumonia in adult patients with special reference to rapid methods for etiological diagnosis

Aikuispotilaan kotisyntyisen keuhkokuumeen etiologinen diagnostiikka mikrobiologisilla pikamenetelmillä Tausta. Keuhkokuume on vakava sairaus, johon sairastuu Suomessa vuosittain n. 60 000 aikuista. Huolimatta siitä, että taudin hoito on kehittynyt, siihen liittyy yhä merkittävä, 6-15%:n kuolleisuus. Alahengitystieinfektion aiheuttajamikrobien tunnistaminen on myös edelleen haasteellista. Tavoitteet. Tämän työn tavoitteena oli tutkia Turun yliopistollisessa keskussairaalassa hoidettujen aikuispotilaiden keuhkokuumeen etiologiaa sekä selvittää uusien mikrobiologisten pikamenetelmi¬en hyödyllisyyttä taudinaiheuttajan toteamisessa. Aineisto. Osatöiden I ja III aineisto koostui 384 Turun yliopistollisen keskussairaalaan infektio-osastolla hoidetusta keuhkokuumepotilaasta. Osatyössä I tutkittiin keuhkokuumeen aiheuttaja¬mikrobeja käyttämällä perinteisten menetelmien lisäksi antigeeniosoitukseen ja PCR-tekniikkaan perustuvia pikamenetelmiä. Osatyö II käsitti 231 potilaasta koostuvan alaryhmän, jossa tutkittiin potilaiden nielun limanäytteestä rinovirusten ja enterovirusten esiintyvyyttä. Osatyössä III potilailta tutkittiin plasman C-reaktiivisen proteiinin (CRP) pitoisuus ensimmäisten viiden sairaalahoitopäi¬vän aikana. Laajoja tilastotieteellisiä analyysejä käyttämällä selvitettiin CRP:n käyttökelpoisuutta sairauden vaikeusasteen arvioinnissa ja komplikaatioiden kehittymisen ennustamisessa. Osatyössä IV 68 keuhkokuumepotilaan sairaalaan tulovaiheessa otetuista näytteistä määritettiin neutrofiilien pintareseptorien ekspressio. Osatyössä V analysoitiin sisätautien vuodeosastoilla vuosina 1996-2000 keuhkokuumepotilaille tehtyjen keuhkohuuhtelunäytteiden laboratoriotutkimustulokset. Tulokset. Keuhkokuumeen aiheuttaja löytyi 209 potilaalta, aiheuttajamikrobeja löydettiin kaikkiaan 230. Näistä aiheuttajista 135 (58.7%) löydettiin antigeenin osoituksella tai PCR-menetelmillä. Suu¬rin osa, 95 (70.4%), todettiin pelkästään kyseisillä pikamenetelmillä. Respiratorinen virus todettiin antigeeniosoituksella 11.1% keuhkokuumepotilaalla. Eniten respiratorisia viruksia löytyi vakavaa keuhkokuumetta sairastavilta potilailta (20.3%). 231 keuhkokuumepotilaan alaryhmässä todettiin PCR-menetelmällä picornavirus 19 (8.2%) potilaalla. Respiratorinen virus löytyi tässä potilasryh¬mässä kaiken kaikkiaan 47 (20%) potilaalta. Näistä 17:llä (36%) löytyi samanaikaisesti bakteerin aiheuttama infektio. CRP-tasot olivat sairaalaan tulovaiheessa merkitsevästi korkeammat vakavaa keuhkokuumetta (PSI-luokat III-V) sairastavilla potilailla kuin lievää keuhkokuumetta (PSI-luokat I-II) sairastavilla potilailla (p <0.001). Yli 100 mg/l oleva CRP-taso neljän päivän kuluttua sairaa¬laan tulosta ennusti keuhkokuumeen komplikaatiota tai huonoa hoitovastetta. Neutrofiilien komple¬menttireseptorin ekspressio oli pneumokokin aiheuttamaa keuhkokuumetta sairastavilla merkitse¬västi korkeampi kuin influenssan aiheuttamaa keuhkokuumetta sairastavilla. BAL-näytteistä vain yhdessä 71:stä (1.3%) todettiin diagnostinen bakteerikasvu kvantitatiivisessa viljelyssä. Uusilla menetelmilläkin keuhkokuumeen aiheuttaja löytyi vain 9.8% BAL-näytteistä. Päätelmät. Uusilla antigeeniosoitus- ja PCR-menetelmillä keuhkokuumeen etiologia voidaan saada selvitettyä nopeasti. Lisäksi näitä menetelmiä käyttämällä taudin aiheuttajamikrobi löytyi huomattavasti suuremmalta osalta potilaista kuin pelkästään tavanomaisia menetelmiä käyttämällä. Pikamenetelmien hyödyllisyys vaihteli taudin vaikeusasteen mukaan. Respiratorinen virus löytyi huomattavan usein keuhkokuumetta sairastavilta potilailta, ja näiden potilaiden taudinkuva oli usein vaikea. Tulovaiheen korkeaa CRP-tasoa voidaan käyttää lisäkeinona arvioitaessa keuhkokuumeen vaikeutta. CRP on erityisen hyödyllinen arvioitaessa hoitovastetta ja riskiä komplikaatioiden ke¬hittymiseen. Neutrofiilien komplementtireseptorin ekspression tutkiminen näyttää lupaavalta pi¬kamenetelmältä erottamaan bakteerien ja virusten aiheuttamat taudit toisistaan. Antimikrobihoitoa saavilla potilailla BAL-tutkimuksen löydökset olivat vähäiset ja vaikuttivat hoitoon vain harvoin.

Health-related quality of life in the Cambridge City over-75s Cohort (CC75C): development of a dementia-specific scale and descriptive analyses.

BACKGROUND: The assessment of Health Related Quality of Life (HRQL) is important in people with dementia as it could influence their care and support plan. Many studies on dementia do not specifically set out to measure dementia-specific HRQL but do include related items. The aim of this study is to explore the distribution of HRQL by functional and socio-demographic variables in a population-based setting. METHODS: Domains of DEMQOL's conceptual framework were mapped in the Cambridge City over 75's Cohort (CC75C) Study. HRQL was estimated in 110 participants aged 80+ years with a confirmed diagnosis of dementia with mild/moderate severity. Acceptability (missing values and normality of the total score), internal consistency (Cronbach's alpha), convergent, discriminant and known group differences validity (Spearman correlations, Wilcoxon Mann-Whitney and Kruskal-Wallis tests) were assessed. The distribution of HRQL by socio-demographic and functional descriptors was explored. RESULTS: The HRQL score ranged from 0 to 16 and showed an internal consistency Alpha of 0.74. Validity of the instrument was found to be acceptable. Men had higher HRQL than women. Marital status had a greater effect on HRQL for men than it did for women. The HRQL of those with good self-reported health was higher than those with fair/poor self-reported health. HRQL was not associated with dementia severity. CONCLUSIONS: To our knowledge this is the first study to examine the distribution of dementia-specific HRQL in a population sample of the very old. We have mapped an existing conceptual framework of dementia specific HRQL onto an existing study and demonstrated the feasibility of this approach. Findings in this study suggest that whereas there is big emphasis in dementia severity, characteristics such as gender should be taken into account when assessing and implementing programmes to improve HRQL.

The use of mixed methods research in interdisciplinary educational journals

Mixed methods research is becoming increasingly important in several scientific areas. The analysis of prevalence rates is a new line of research that has emerged in mixed methods research, and this methodological approach has only been applied carefully in a handful of journals. The purpose of this article was to analyse the prevalence of mixed methods research in interdisciplinary educational journals. Moreover, the main characteristics of the mixed methods articles identified were examined. This study used a mixed methods approach to analyse these aspects. Specifically, a partially mixed sequential equal status multiple-case study design was applied with a development mixed methods purpose. Three educational journals in different disciplines were reviewed from 2005 to 2010 (Academy of Management Learning and Education, Educational Psychology Review, Journal of the Learning Sciences). The findings show differences among the journals in the prevalence rates and characteristics of the mixed methods studies