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.

Comparison of three analytical methods for the determination of quinolones in pig muscle samples

This work presents a comparison between three analytical methods developed for the simultaneous determination of eight quinolones regulated by the European Union (marbofloxacin, ciprofloxacin, danofloxacin, enrofloxacin, difloxacin, sarafloxacin, oxolinic acid and flumequine) in pig muscle, using liquid chromatography with fluorescence detection (LC-FD), liquid chromatography-mass spectrometry (LC-MS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS). The procedures involve an extraction of the quinolones from the tissues, a step for clean-up and preconcentration of the analytes by solid-phase extraction and a subsequent liquid chromatographic analysis. The limits of detection of the methods ranged from 0.1 to 2.1 ng g−1 using LC-FD, from 0.3 to 1.8 using LC-MS and from 0.2 to 0.3 using LC-MS/MS, while inter- and intra-day variability was under 15 % in all cases. Most of those data are notably lower than the maximum residue limits established by the European Union for quinolones in pig tissues. The methods have been applied for the determination of quinolones in six different commercial pig muscle samples purchased in different supermarkets located in the city of Granada (south-east Spain).

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.

New methods for the concentration of viruses from urban sewage using quantitative PCR.

Viruses are among the most important pathogens present in water contaminated with feces or urine and represent a serious risk to human health. Four procedures for concentrating viruses from sewage have been compared in this work, three of which were developed in the present study. Viruses were quantified using PCR techniques. According to statistical analysis and the sensitivity to detect human adenoviruses (HAdV), JC polyomaviruses (JCPyV) and noroviruses genogroup II (NoV GGII): (i) a new procedure (elution and skimmed-milk flocculation procedure (ESMP)) based on the elution of the viruses with glycine-alkaline buffer followed by organic flocculation with skimmed-milk was found to be the most efficient method when compared to (ii) ultrafiltration and glycine-alkaline elution, (iii) a lyophilization-based method and (iv) ultracentrifugation and glycine-alkaline elution. Through the analysis of replicate sewage samples, ESMP showed reproducible results with a coefficient of variation (CV) of 16% for HAdV, 12% for JCPyV and 17% for NoV GGII. Using spiked samples, the viral recoveries were estimated at 30-95% for HAdV, 55-90% for JCPyV and 45-50% for NoV GGII. ESMP was validated in a field study using twelve 24-h composite sewage samples collected in an urban sewage treatment plant in the North of Spain that reported 100% positive samples with mean values of HAdV, JCPyV and NoV GGII similar to those observed in other studies. Although all of the methods compared in this work yield consistently high values of virus detection and recovery in urban sewage, some require expensive laboratory equipment. ESMP is an effective low-cost procedure which allows a large number of samples to be processed simultaneously and is easily standardizable for its performance in a routine laboratory working in water monitoring. Moreover, in the present study, a CV was applied and proposed as a parameter to evaluate and compare the methods for detecting viruses in sewage samples.

New methods for the concentration of viruses from urban sewage using quantitative PCR.

Viruses are among the most important pathogens present in water contaminated with feces or urine and represent a serious risk to human health. Four procedures for concentrating viruses from sewage have been compared in this work, three of which were developed in the present study. Viruses were quantified using PCR techniques. According to statistical analysis and the sensitivity to detect human adenoviruses (HAdV), JC polyomaviruses (JCPyV) and noroviruses genogroup II (NoV GGII): (i) a new procedure (elution and skimmed-milk flocculation procedure (ESMP)) based on the elution of the viruses with glycine-alkaline buffer followed by organic flocculation with skimmed-milk was found to be the most efficient method when compared to (ii) ultrafiltration and glycine-alkaline elution, (iii) a lyophilization-based method and (iv) ultracentrifugation and glycine-alkaline elution. Through the analysis of replicate sewage samples, ESMP showed reproducible results with a coefficient of variation (CV) of 16% for HAdV, 12% for JCPyV and 17% for NoV GGII. Using spiked samples, the viral recoveries were estimated at 30-95% for HAdV, 55-90% for JCPyV and 45-50% for NoV GGII. ESMP was validated in a field study using twelve 24-h composite sewage samples collected in an urban sewage treatment plant in the North of Spain that reported 100% positive samples with mean values of HAdV, JCPyV and NoV GGII similar to those observed in other studies. Although all of the methods compared in this work yield consistently high values of virus detection and recovery in urban sewage, some require expensive laboratory equipment. ESMP is an effective low-cost procedure which allows a large number of samples to be processed simultaneously and is easily standardizable for its performance in a routine laboratory working in water monitoring. Moreover, in the present study, a CV was applied and proposed as a parameter to evaluate and compare the methods for detecting viruses in sewage samples.

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.

Supervised regionalization methods: A survey

This paper reviews almost four decades of contributions on the subject of supervised regionalization methods. These methods aggregate a set of areas into a predefined number of spatially contiguous regions while optimizing certain aggregation criteria. The authors present a taxonomic scheme that classifies a wide range of regionalization methods into eight groups, based on the strategy applied for satisfying the spatial contiguity constraint. The paper concludes by providing a qualitative comparison of these groups in terms of a set of certain characteristics, and by suggesting future lines of research for extending and improving these methods.

Validation and statistical analysis of two high performance liquid chromatography methods for the determination of indinavir sulfate raw material and capsules

Two high performance liquid chromatography (HPLC) methods for the quantitative determination of indinavir sulfate were tested, validated and statistically compared. Assays were carried out using as mobile phases mixtures of dibutylammonium phosphate buffer pH 6.5 and acetonitrile (55:45) at 1 mL/min or citrate buffer pH 5 and acetonitrile (60:40) at 1 mL/min, an octylsilane column (RP-8) and a UV spectrophotometric detector at 260 nm. Both methods showed good sensitivity, linearity, precision and accuracy. The statistical analysis using the t-student test for the determination of indinavir sulfate raw material and capsules indicated no statistically significant difference between the two methods.

Supervised regionalization methods: A survey

This paper reviews almost four decades of contributions on the subject of supervised regionalization methods. These methods aggregate a set of areas into a predefined number of spatially contiguous regions while optimizing certain aggregation criteria. The authors present a taxonomic scheme that classifies a wide range of regionalization methods into eight groups, based on the strategy applied for satisfying the spatial contiguity constraint. The paper concludes by providing a qualitative comparison of these groups in terms of a set of certain characteristics, and by suggesting future lines of research for extending and improving these methods.

Comparing Methods of Evaluating the Spread of Argentine Ants in Natural Habitats: Pitfall Traps vs. Baiting

Two methods of trapping Argentine ants in natural habitats are compared. both methods are used on the boundaries of an invaded area with the goal of assessing the spread of the invasion front. Pitfall surveys take longer to obtain results than bait surveys, but bait surveys are only a “snapshot” of the moment, with less chance of detecting Argentine ant workers. significant differences are found between the methods in terms of the number of traps occupied by Argentine ants, native ants or a combination of both. Differences in the richness of native ant species are found as well, showing that pitfall surveys are necessary to assess such richness. Despite this, no differences in the assessment of spread are found between the methods. bait surveys are an easier and faster method to assess the spread of Argentine ants, spread being one of the most important characteristics of biological invasions