The Quest for Well-being in Growth Industries: Contexts, Research Design and Methodological Development

This Working Paper reports the background to the first stage of the ongoing research project, The Quest for Well-being in Growth Industries: A Collaborative Study in Finland and Scotland, conducted under the auspices of the Academy of Finland research programme The Future of Work and Well-being (2008-2011). This collaborative project provides national and transnational data, analysis and outputs. The study is being conducted in the Department of Management and Organisation, Hanken School of Economics, Finland, in collaboration with Glasgow Caledonian University, University of East London, Heriot-Watt University and Reading University, UK. The project examines policies and practices towards the enhancement of work-related well-being in growth industries, and contradictory pressures and tensions posed in this situation. The overall aim is to evaluate the development, implementation and use of work-related well-being policies in four selected growth industries. These sectors – electronics, care, finance and accounting, and tourism – have been selected on the basis of European Union and national forecasts, and demographic and socio-economic trends in employment. In this working paper we outline the background to the research study, the initial research plan, and how the survey of employers has been constructed. The working paper concludes with a brief discussion of general ongoing research issues arising in the project.

Theory and Analysis of Classic Heavy Metal Harmony

This thesis explores melodic and harmonic features of heavy metal, and while doing so, explores various methods of music analysis; their applicability and limitations regarding the study of heavy metal music. The study is built on three general hypotheses according to which 1) acoustic characteristics play a significant role for chord constructing in heavy metal, 2) heavy metal has strong ties and similarities with other Western musical styles, and 3) theories and analytical methods of Western art music may be applied to heavy metal. It seems evident that in heavy metal some chord structures appear far more frequently than others. It is suggested here that the fundamental reason for this is the use of guitar distortion effect. Subsequently, theories as to how and under what principles heavy metal is constructed need to be put under discussion; analytical models regarding the classification of consonance and dissonance and chord categorization are here revised to meet the common practices of this music. It is evident that heavy metal is not an isolated style of music; it is seen here as a cultural fusion of various musical styles. Moreover, it is suggested that the theoretical background to the construction of Western music and its analysis can offer invaluable insights to heavy metal. However, the analytical methods need to be reformed to some extent to meet the characteristics of the music. This reformation includes an accommodation of linear and functional theories that has been found rather rarely in music theory and musicology.

Is a Majority Enough? Psychological Well-being and Its Relation to Academic and Prosocial Motivation, Self-regulation and Achievement at school

This cross-sectional study analyzed psychological well-being at school using the Self-Determination theory as a theoretical frame-work. The study explored basic psychological needs fulfillment (BPNS), academic (SRQ-A), prosocial self-regulation (SRQ-P) and motivation, and their relationship with achievement in general, special and selective education (N=786, 444 boys, 345 girls, mean age 12 yrs 8 mths). Motivation starts behavior which becomes guided by self-regulation. The perceived locus of control (PLOC) affects how self-determined this behavior will be; in other words, to what extent it is autonomously regulated. In order learn and thus to be able to accept external goals, a student has to feel emotionally safe and have sufficient ego-flexibility—all of which builds on satisfied psychological needs. In this study those conditions were explored. In addition to traditional methods Self-organizing maps (SOM), was used in order to cluster the students according to their well-being, self-regulation, motivation and achievement scores. The main impacts of this research were: a presentation of the theory based alternative of studying psychological well-being at school and usage of both the variable and person-oriented approach. In this Finnish sample the results showed that the majority of students felt well, but the well-being varied by group. Overall about for 11–15% the basic needs were deprived depending on the educational group. Age and educational group were the most effective factors; gender was important in relation to prosocial identified behavior. Although the person-oriented SOM-approach, was in a large extent confirming what was no-ticed by using comparison of the variables: the SEN groups had lower levels of basic needs fulfillment and less autonomous self-regulation, interesting deviations of that rule appeared. Some of the SEL- and GEN-group members ended up in the more unfavorable SOM-clusters, and not all SEN-group members belonged to the poorest clusters (although not to the best either). This evidence refines the well-being and self-regulation picture, and may re-direct intervention plans, and turn our focus also on students who might otherwise remain unnoticed. On the other hand, these results imply simultaneously that in special education groups the average is not the whole truth. On the basis of theoretical and empirical considerations an intervention model was sug-gested. The aim of the model was to shift amotivation or external motivation in a more intrinsic direction. According to the theoretical and empirical evidence this can be achieved first by studying the self-concept a student has, and then trying to affect both inner and environmental factors—including a consideration of the basic psychological needs. Keywords: academic self-regulation, prosocial self-regulation, basic psychological needs, moti-vation, achievement

Design and testing of stand-specific bucking instructions for use on modern cut-to-length harvesters

This study addresses three important issues in tree bucking optimization in the context of cut-to-length harvesting. (1) Would the fit between the log demand and log output distributions be better if the price and/or demand matrices controlling the bucking decisions on modern cut-to-length harvesters were adjusted to the unique conditions of each individual stand? (2) In what ways can we generate stand and product specific price and demand matrices? (3) What alternatives do we have to measure the fit between the log demand and log output distributions, and what would be an ideal goodness-of-fit measure? Three iterative search systems were developed for seeking stand-specific price and demand matrix sets: (1) A fuzzy logic control system for calibrating the price matrix of one log product for one stand at a time (the stand-level one-product approach); (2) a genetic algorithm system for adjusting the price matrices of one log product in parallel for several stands (the forest-level one-product approach); and (3) a genetic algorithm system for dividing the overall demand matrix of each of the several log products into stand-specific sub-demands simultaneously for several stands and products (the forest-level multi-product approach). The stem material used for testing the performance of the stand-specific price and demand matrices against that of the reference matrices was comprised of 9 155 Norway spruce (Picea abies (L.) Karst.) sawlog stems gathered by harvesters from 15 mature spruce-dominated stands in southern Finland. The reference price and demand matrices were either direct copies or slightly modified versions of those used by two Finnish sawmilling companies. Two types of stand-specific bucking matrices were compiled for each log product. One was from the harvester-collected stem profiles and the other was from the pre-harvest inventory data. Four goodness-of-fit measures were analyzed for their appropriateness in determining the similarity between the log demand and log output distributions: (1) the apportionment degree (index), (2) the chi-square statistic, (3) Laspeyres quantity index, and (4) the price-weighted apportionment degree. The study confirmed that any improvement in the fit between the log demand and log output distributions can only be realized at the expense of log volumes produced. Stand-level pre-control of price matrices was found to be advantageous, provided the control is done with perfect stem data. Forest-level pre-control of price matrices resulted in no improvement in the cumulative apportionment degree. Cutting stands under the control of stand-specific demand matrices yielded a better total fit between the demand and output matrices at the forest level than was obtained by cutting each stand with non-stand-specific reference matrices. The theoretical and experimental analyses suggest that none of the three alternative goodness-of-fit measures clearly outperforms the traditional apportionment degree measure. Keywords: harvesting, tree bucking optimization, simulation, fuzzy control, genetic algorithms, goodness-of-fit

Computational Methods for Reconstruction and Analysis of Genome-Scale Metabolic Networks

Metabolism is the cellular subsystem responsible for generation of energy from nutrients and production of building blocks for larger macromolecules. Computational and statistical modeling of metabolism is vital to many disciplines including bioengineering, the study of diseases, drug target identification, and understanding the evolution of metabolism. In this thesis, we propose efficient computational methods for metabolic modeling. The techniques presented are targeted particularly at the analysis of large metabolic models encompassing the whole metabolism of one or several organisms. We concentrate on three major themes of metabolic modeling: metabolic pathway analysis, metabolic reconstruction and the study of evolution of metabolism. In the first part of this thesis, we study metabolic pathway analysis. We propose a novel modeling framework called gapless modeling to study biochemically viable metabolic networks and pathways. In addition, we investigate the utilization of atom-level information on metabolism to improve the quality of pathway analyses. We describe efficient algorithms for discovering both gapless and atom-level metabolic pathways, and conduct experiments with large-scale metabolic networks. The presented gapless approach offers a compromise in terms of complexity and feasibility between the previous graph-theoretic and stoichiometric approaches to metabolic modeling. Gapless pathway analysis shows that microbial metabolic networks are not as robust to random damage as suggested by previous studies. Furthermore the amino acid biosynthesis pathways of the fungal species Trichoderma reesei discovered from atom-level data are shown to closely correspond to those of Saccharomyces cerevisiae. In the second part, we propose computational methods for metabolic reconstruction in the gapless modeling framework. We study the task of reconstructing a metabolic network that does not suffer from connectivity problems. Such problems often limit the usability of reconstructed models, and typically require a significant amount of manual postprocessing. We formulate gapless metabolic reconstruction as an optimization problem and propose an efficient divide-and-conquer strategy to solve it with real-world instances. We also describe computational techniques for solving problems stemming from ambiguities in metabolite naming. These techniques have been implemented in a web-based sofware ReMatch intended for reconstruction of models for 13C metabolic flux analysis. In the third part, we extend our scope from single to multiple metabolic networks and propose an algorithm for inferring gapless metabolic networks of ancestral species from phylogenetic data. Experimenting with 16 fungal species, we show that the method is able to generate results that are easily interpretable and that provide hypotheses about the evolution of metabolism.

Construction of a global map of human gene expression : the process, tools and analysis

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.

Diastereomeric Drug Glucuronides: Enzymatic Glucuronidation and Analysis by Capillary Electrophoresis and Liquid Chromatography-Mass Spectrometry

Foreign compounds, such as drugs are metabolised in the body in numerous reactions. Metabolic reactions are divided into phase I (functionalisation) and phase II (conjugation) reactions. Uridine diphosphoglucuronosyltransferase enzymes (UGTs) are important catalysts of phase II metabolic system. They catalyse the transfer of glucuronic acid to small lipophilic molecules and convert them to hydrophilic and polar glucuronides that are readily excreted from the body. Liver is the main site of drug metabolism. Many drugs are racemic mixtures of two enantiomers. Glucuronidation of a racemic compound yields a pair of diastereomeric glucuronides. Stereoisomers are interesting substrates in glucuronidation studies since some UGTs display stereoselectivity. Diastereomeric glucuronides of O-desmethyltramadol (M1) and entacapone were selected as model compounds in this work. The investigations of the thesis deal with enzymatic glucuronidation and the development of analytical methods for drug metabolites, particularly diastereomeric glucuronides. The glucuronides were analysed from complex biological matrices, such as urine or from in vitro incubation matrices. Various pretreatment techniques were needed to purify, concentrate and isolate the analytes of interest. Analyses were carried out by liquid chromatography (LC) with ultraviolet (UV) or mass spectrometric (MS) detection or with capillary electromigration techniques. Commercial glucuronide standards were not available for the studies. Enzyme-assisted synthesis with rat liver microsomes was therefore used to produce M1 glucuronides as reference compounds. The glucuronides were isolated by LC/UV and ultra performance liquid chromatography (UPLC)/MS, while tandem mass spectrometry (MS/MS) and nuclear magnetic resonance (NMR) spectroscopy were employed in structural characterisation. The glucuronides were identified as phenolic O-glucuronides of M1. To identify the active UGT enzymes in (±)-M1 glucuronidation recombinant human UGTs and human tissue microsomes were incubated with (±)-M1. The study revealed that several UGTs can catalyse (±)-M1 glucuronidation. Glucuronidation in human liver microsomes like in rat liver microsomes is stereoselective. The results of the studies showed that UGT2B7, most probably, is the main UGT responsible for (±)-M1 glucuronidation in human liver. Large variation in stereoselectivity of UGTs toward (±)-M1 enantiomers was observed. Formation of M1 glucuronides was monitored with a fast and selective UPLC/MS method. Capillary electromigration techniques are known for their high resolution power. A method that relied on capillary electrophoresis (CE) with UV detection was developed for the separation of tramadol and its free and glucuronidated metabolites. The suitability of the method to identify tramadol metabolites in an authentic urine samples was tested. Unaltered tramadol and four of its main metabolites were detected in the electropherogram. A micellar electrokinetic chromatography (MEKC) /UV method was developed for the separation of the glucuronides of entacapone in human urine. The validated method was tested in the analysis of urine samples of patients. The glucuronides of entacapone could be quantified after oral entacapone dosing.

Categorical Meteorological Products: Evaluation and Analysis

In meteorology, observations and forecasts of a wide range of phenomena for example, snow, clouds, hail, fog, and tornados can be categorical, that is, they can only have discrete values (e.g., "snow" and "no snow"). Concentrating on satellite-based snow and cloud analyses, this thesis explores methods that have been developed for evaluation of categorical products and analyses. Different algorithms for satellite products generate different results; sometimes the differences are subtle, sometimes all too visible. In addition to differences between algorithms, the satellite products are influenced by physical processes and conditions, such as diurnal and seasonal variation in solar radiation, topography, and land use. The analysis of satellite-based snow cover analyses from NOAA, NASA, and EUMETSAT, and snow analyses for numerical weather prediction models from FMI and ECMWF was complicated by the fact that we did not have the true knowledge of snow extent, and we were forced simply to measure the agreement between different products. The Sammon mapping, a multidimensional scaling method, was then used to visualize the differences between different products. The trustworthiness of the results for cloud analyses [EUMETSAT Meteorological Products Extraction Facility cloud mask (MPEF), together with the Nowcasting Satellite Application Facility (SAFNWC) cloud masks provided by Météo-France (SAFNWC/MSG) and the Swedish Meteorological and Hydrological Institute (SAFNWC/PPS)] compared with ceilometers of the Helsinki Testbed was estimated by constructing confidence intervals (CIs). Bootstrapping, a statistical resampling method, was used to construct CIs, especially in the presence of spatial and temporal correlation. The reference data for validation are constantly in short supply. In general, the needs of a particular project drive the requirements for evaluation, for example, for the accuracy and the timeliness of the particular data and methods. In this vein, we discuss tentatively how data provided by general public, e.g., photos shared on the Internet photo-sharing service Flickr, can be used as a new source for validation. Results show that they are of reasonable quality and their use for case studies can be warmly recommended. Last, the use of cluster analysis on meteorological in-situ measurements was explored. The Autoclass algorithm was used to construct compact representations of synoptic conditions of fog at Finnish airports.