Reuse of information for selection of methods and operating conditions for drying of pharmaceutical materials

Drying is a major step in the manufacturing process in pharmaceutical industries, and the selection of dryer and operating conditions are sometimes a bottleneck. In spite of difficulties, the bottlenecks are taken care of with utmost care due to good manufacturing practices (GMP) and industries' image in the global market. The purpose of this work is to research the use of existing knowledge for the selection of dryer and its operating conditions for drying of pharmaceutical materials with the help of methods like case-based reasoning and decision trees to reduce time and expenditure for research. The work consisted of two major parts as follows: Literature survey on the theories of spray dying, case-based reasoning and decision trees; working part includes data acquisition and testing of the models based on existing and upgraded data. Testing resulted in a combination of two models, case-based reasoning and decision trees, leading to more specific results when compared to conventional methods.

Implementing Agile Software Development Methods in a Small Organization

Currently there is a vogue for Agile Software Development methods and many software development organizations have already implemented or they are planning to implement agile methods. Objective of this thesis is to define how agile software development methods are implemented in a small organization. Agile methods covered in this thesis are Scrum and XP. From both methods the key practices are analysed and compared to waterfall method. This thesis also defines implementation strategy and actions how agile methods are implemented in a small organization. In practice organization must prepare well and all needed meters are defined before the implementation starts. In this work three different sample projects are introduced where agile methods were implemented. Experiences from these projects were encouraging although sample set of projects were too small to get trustworthy results.

Use of Statistical Methods in Demand Planning

In a very volatile industry of high technology it is of utmost importance to accurately forecast customers’ demand. However, statistical forecasting of sales, especially in heavily competitive electronics product business, has always been a challenging task due to very high variation in demand and very short product life cycles of products. The purpose of this thesis is to validate if statistical methods can be applied to forecasting sales of short life cycle electronics products and provide a feasible framework for implementing statistical forecasting in the environment of the case company. Two different approaches have been developed for forecasting on short and medium term and long term horizons. Both models are based on decomposition models, but differ in interpretation of the model residuals. For long term horizons residuals are assumed to represent white noise, whereas for short and medium term forecasting horizon residuals are modeled using statistical forecasting methods. Implementation of both approaches is performed in Matlab. Modeling results have shown that different markets exhibit different demand patterns and therefore different analytical approaches are appropriate for modeling demand in these markets. Moreover, the outcomes of modeling imply that statistical forecasting can not be handled separately from judgmental forecasting, but should be perceived only as a basis for judgmental forecasting activities. Based on modeling results recommendations for further deployment of statistical methods in sales forecasting of the case company are developed.

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.

Statistical Methods for Conservation and Alignment Quality in Proteins

Construction of multiple sequence alignments is a fundamental task in Bioinformatics. Multiple sequence alignments are used as a prerequisite in many Bioinformatics methods, and subsequently the quality of such methods can be critically dependent on the quality of the alignment. However, automatic construction of a multiple sequence alignment for a set of remotely related sequences does not always provide biologically relevant alignments.Therefore, there is a need for an objective approach for evaluating the quality of automatically aligned sequences. The profile hidden Markov model is a powerful approach in comparative genomics. In the profile hidden Markov model, the symbol probabilities are estimated at each conserved alignment position. This can increase the dimension of parameter space and cause an overfitting problem. These two research problems are both related to conservation. We have developed statistical measures for quantifying the conservation of multiple sequence alignments. Two types of methods are considered, those identifying conserved residues in an alignment position, and those calculating positional conservation scores. The positional conservation score was exploited in a statistical prediction model for assessing the quality of multiple sequence alignments. The residue conservation score was used as part of the emission probability estimation method proposed for profile hidden Markov models. The results of the predicted alignment quality score highly correlated with the correct alignment quality scores, indicating that our method is reliable for assessing the quality of any multiple sequence alignment. The comparison of the emission probability estimation method with the maximum likelihood method showed that the number of estimated parameters in the model was dramatically decreased, while the same level of accuracy was maintained. To conclude, we have shown that conservation can be successfully used in the statistical model for alignment quality assessment and in the estimation of emission probabilities in the profile hidden Markov models.

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.

Mobile Subscription Acquisition and Retention Costs - An Actvity-Based Model

The objective of this master’s thesis was to develop a model for mobile subscription acquisition cost, SAC, and mobile subscription retention cost, SRC, by applying activity-based cost accounting principles. The thesis was conducted as a case study for a telecommunication company operating on the Finnish telecommunication market. In addition to activity-based cost accounting there were other theories studied and applied in order to establish a theory framework for this thesis. The concepts of acquisition and retention were explored in a broader context with the concepts of customer satisfaction, loyalty and profitability and eventually customer relationship management to understand the background and meaning of the theme of this thesis. The utilization of SAC and SRC information is discussed through the theories of decision making and activity-based management. Also, the present state and future needs of SAC and SRC information usage at the case company as well as the functions of the company were examined by interviewing some members of the company personnel. With the help of these theories and methods it was aimed at finding out both the theory-based and practical factors which affect the structure of the model. During the thesis study it was confirmed that the existing SAC and SRC model of the case company should be used as the basis in developing the activity-based model. As a result the indirect costs of the old model were transformed into activities and the direct costs were continued to be allocated directly to acquisition of new subscriptions and retention of old subscriptions. The refined model will enable managing the subscription acquisition, retention and the related costs better through the activity information. During the interviews it was found out that the SAC and SRC information is also used in performance measurement and operational and strategic planning. SAC and SRC are not fully absorbed costs and it was concluded that the model serves best as a source of indicative cost information. This thesis does not include calculating costs. Instead, the refined model together with both the theory-based and interview findings concerning the utilization of the information produced by the model will serve as a framework for the possible future development aiming at completing the model.

Methods to test gas tightness of packages

One of the primary goals for food packages is to protect food against harmful environment, especially oxygen and moisture. The gas transmission rate is the total gas transport through the package, both by permeation through the package material and by leakage through pinholes and cracks. The shelf life of a product can be extended, if the food is stored in a gas tight package. Thus there is a need to test gas tightness of packages. There are several tightness testing methods, and they can be broadly divided into destructive and nondestructive methods. One of the most sensitive methods to detect leaks is by using a non destructive tracer gas technique. Carbon dioxide, helium and hydrogen are the most commonly used tracer gases. Hydrogen is the lightest and the smallest of all gases, which allows it to escape rapidly from the leak areas. The low background concentration of H2 in air (0.5 ppm) enables sensitive leak detection. With a hydrogen leak detector it is also possible to locate leaks. That is not possible with many other tightness testing methods. The experimental work has been focused on investigating the factors which affect the measurement results with the H2leak detector. Also reasons for false results were searched to avoid them in upcoming measurements. From the results of these experiments, the appropriate measurement practice was created in order to have correct and repeatable results. The most important thing for good measurement results is to keep the probe of the detector tightly against the leak. Because of its high diffusion rate, the HZ concentration decreases quickly if holding the probe further away from the leak area and thus the measured H2 leaks would be incorrect and small leaks could be undetected. In the experimental part hydrogen, oxygen and water vapour transmissions through laser beam reference holes (diameters 1 100 μm) were also measured and compared. With the H2 leak detector it was possible to detect even a leakage through 1 μm (diameter) within a few seconds. Water vapour did not penetrate even the largest reference hole (100 μm), even at tropical conditions (38 °C, 90 % RH), whereas some O2 transmission occurred through the reference holes larger than 5 μm. Thus water vapour transmission does not have a significant effect on food deterioration, if the diameter of the leak is less than 100 μm, but small leaks (5 100 μm) are more harmful for the food products, which are sensitive to oxidation.

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.

Food Safety Testing: Rapid Molecular Methods for Chemical and Biological Hazards

The central goal of food safety policy in the European Union (EU) is to protect consumer health by guaranteeing a high level of food safety throughout the food chain. This goal can in part be achieved by testing foodstuffs for the presence of various chemical and biological hazards. The aim of this study was to facilitate food safety testing by providing rapid and user-friendly methods for the detection of particular food-related hazards. Heterogeneous competitive time-resolved fluoroimmunoassays were developed for the detection of selected veterinary residues, that is coccidiostat residues, in eggs and chicken liver. After a simplified sample preparation procedure, the immunoassays were performed either in manual format with dissociation-enhanced measurement or in automated format with pre-dried assay reagents and surface measurement. Although the assays were primarily designed for screening purposes providing only qualitative results, they could also be used in a quantitative mode. All the developed assays had good performance characteristics enabling reliable screening of samples at concentration levels required by the authorities. A novel polymerase chain reaction (PCR)-based assay system was developed for the detection of Salmonella spp. in food. The sample preparation included a short non-selective pre-enrichment step, after which the target cells were collected with immunomagnetic beads and applied to PCR reaction vessels containing all the reagents required for the assay in dry form. The homogeneous PCR assay was performed with a novel instrument platform, GenomEra^™, and the qualitative assay results were automatically interpreted based on end-point time-resolved fluorescence measurements and cut-off values. The assay was validated using various food matrices spiked with sub-lethally injured Salmonella cells at levels of 1-10 colony forming units (CFU)/25 g of food. The main advantage of the system was the exceptionally short time to result; the entire process starting from the pre-enrichment and ending with the PCR result could be completed in eight hours. In conclusion, molecular methods using state-of-the-art assay techniques were developed for food safety testing. The combination of time-resolved fluorescence detection and ready-to-use reagents enabled sensitive assays easily amenable to automation. Consequently, together with the simplified sample preparation, these methods could prove to be applicable in routine testing.

Active sulphide mine tailings impoundments as sources of contaminated drainage: controlling factors, methods of characterisation and geochemical constraints for mitigation

Low quality mine drainage from tailings facilities persists as one of the most significant global environmental concerns related to sulphide mining. Due to the large variation in geological and environmental conditions at mine sites, universal approaches to the management of mine drainage are not always applicable. Instead, site-specific knowledge of the geochemical behaviour of waste materials is required for the design and closure of the facilities. In this thesis, tailings-derived water contamination and factors causing the pollution were investigated in two coeval active sulphide mine sites in Finland: the Hitura Ni mine and the Luikonlahti Cu-Zn-Co-Ni mine and talc processing plant. A hydrogeochemical study was performed to characterise the tailingsderived water pollution at Hitura. Geochemical changes in the Hitura tailings were evaluated with a detailed mineralogical and geochemical investigation (solid-phase speciation, acid mine drainage potential, pore water chemistry) and using a spatial assessment to identify the mechanisms of water contamination. A similar spatial investigation, applying selective extractions, was carried out in the Luikonlahti tailings area for comparative purposes (Hitura low-sulphide tailings vs. Luikonlahti sulphide-rich tailings). At both sites, hydrogeochemistry of tailings seepage waters was further characterised to examine the net results of the processes observed within the impoundments and to identify constraints for water treatment. At Luikonlahti, annual and seasonal variation in effluent quality was evaluated based on a four-year monitoring period. Observations pertinent to future assessment and mine drainage prevention from existing and future tailings facilities were presented based on the results. A combination of hydrogeochemical approaches provided a means to delineate the tailings-derived neutral mine drainage at Hitura. Tailings effluents with elevated Ni, SO₄ ^2- and Fe content had dispersed to the surrounding aquifer through a levelled-out esker and underneath the seepage collection ditches. In future mines, this could be avoided with additional basal liners in tailings impoundments where the permeability of the underlying Quaternary deposits is inadequate, and with sufficiently deep ditches. Based on the studies, extensive sulphide oxidation with subsequent metal release may already initiate during active tailings disposal. The intensity and onset of oxidation depended on e.g. the Fe sulphide content of the tailings, water saturation level, and time of exposure of fresh sulphide grains. Continuous disposal decreased sulphide weathering in the surface of low-sulphide tailings, but oxidation initiated if they were left uncovered after disposal ceased. In the sulphide-rich tailings, delayed burial of the unsaturated tailings had resulted in thick oxidized layers, despite the continuous operation. Sulphide weathering and contaminant release occurred also in the border zones. Based on the results, the prevention of sulphide oxidation should already be considered in the planning of tailings disposal, taking into account the border zones. Moreover, even lowsulphide tailings should be covered without delay after active disposal ceases. The quality of tailings effluents showed wide variation within a single impoundment and between the two different types of tailings facilities assessed. The affecting factors included source materials, the intensity of weathering of tailings and embankment materials along the seepage flow path, inputs from the process waters, the water retention time in tailings, and climatic seasonality. In addition, modifications to the tailings impoundment may markedly change the effluent quality. The wide variation in the tailings effluent quality poses challenges for treatment design. The final decision on water management requires quantification of the spatial and seasonal fluctuation at the site, taking into account changes resulting from the eventual closure of the impoundment. Overall, comprehensive hydrogeochemical mapping was deemed essential in the identification of critical contaminants and their sources at mine sites. Mineralogical analysis, selective extractions, and pore water analysis were a good combination of methods for studying the weathering of tailings and in evaluating metal mobility from the facilities. Selective extractions with visual observations and pH measurements of tailings solids were, nevertheless, adequate in describing the spatial distribution of sulphide oxidation in tailings impoundments. Seepage water chemistry provided additional data on geochemical processes in tailings and was necessary for defining constraints for water treatment.

Assembly Methods of Permanent Magnets for Synchronous Generators

This thesis examines and explains the procedure used to redesign the attachment of permanent magnets to the surface of the rotor of a synchronous generator. The methodology followed to go from the actual assembly to converge to the final purposed innovation was based on the systematic approach design. This meant that first a series of steps had to be predefined as a frame of reference later to be used to compare and select proposals, and finally to obtain the innovation that was sought. Firstly, a series of patents was used as the background for the upcoming ideas. To this end, several different patented assemblies had been found and categorized according the main element onto which this thesis if focused, meaning the attachment element or method. After establishing the technological frame of reference, a brainstorm was performed to obtain as many ideas as possible. Then these ideas were classified, regardless of their degree of complexity or usability, since at this time the quantity of the ideas was the important issue. Subsequently, they were compared and evaluated from different points of view. The comparison and evaluation in this case was based on the use of a requirement list, which established the main needs that the design had to fulfill. Then the selection could be done by grading each idea in accordance with these requirements. In this way, one was able to obtain the idea or ideas that best fulfilled these requirements. Once all of the ideas were compared and evaluated, the best or most suitable idea or ideas were separated. Finally, the selected idea or ideas was/were analyzed in extension and a number of improvements were made. Consequently, a final idea was refined and made more suitable at its performance, manufacture, and life cycle assessment. Therefore, in the end, the design process gave a solution to the problem pointed out at the beginning.

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.