A hybrid clustering procedure for concentric and chain-like clusters

K-means algorithm is a well known nonhierarchical method for clustering data. The most important limitations of this algorithm are that: (1) it gives final clusters on the basis of the cluster centroids or the seed points chosen initially, and (2) it is appropriate for data sets having fairly isotropic clusters. But this algorithm has the advantage of low computation and storage requirements. On the other hand, hierarchical agglomerative clustering algorithm, which can cluster nonisotropic (chain-like and concentric) clusters, requires high storage and computation requirements. This paper suggests a new method for selecting the initial seed points, so that theK-means algorithm gives the same results for any input data order. This paper also describes a hybrid clustering algorithm, based on the concepts of multilevel theory, which is nonhierarchical at the first level and hierarchical from second level onwards, to cluster data sets having (i) chain-like clusters and (ii) concentric clusters. It is observed that this hybrid clustering algorithm gives the same results as the hierarchical clustering algorithm, with less computation and storage requirements.

Kohti hyvää suometsien hoitoa : harvennusten ja kunnostusojitusten vaikutus ojitusaluemänniköiden puuntuotokseen ja metsänkasvatuksen taloustulokseen

This thesis examines the impacts of silvicultural activities on productivity and financial returns of Scots pine (Pinus sylvestris L.) stands on drained peatlands in Finland. The effects of ditch network maintenance operations (DNM) and thinnings, with different timings and intensities, were studied. Based on stand development simulations, the best regimes for different types of stands according to site type, climatic area, and stand silvicultural status were defined from the viewpoint of both wood production and financial profitability. Certain aspects affecting the management outcomes, such as the timing of the first thinning, were examined using data from thinning experiments. Long-term predictions of the impacts of different management regimes were carried out by simulating the development of well-representative model-stands which were composed from appropriate inventory data sets. The MOTTI stand simulator used to perform the simulations enables the predictions by utilizing specific models for drained peatland stands. In addition to natural stand dynamics, these models describe the effects of silvicultural treatments on the development of a given stand. The mean annual increment of merchantable wood (MAImerch) was used as the measure of wood productivity, and the financial feasibility of the regimes was compared using net present value (NPV) analysis. Silvicultural treatments, when applied to appropriately match stand condition, increased both the productivity and financial returns of stand management. Applying DNM resulted in a small increase in MAImerch. When thinning was introduced along with DNM, their combined effect on wood productivity was considerable. According to current operational practices, DNM is generally combined with thinning. In some cases, e.g., in sites of low productivity, the need for DNM may become apparent prior to the thinning stage. As for profitability, thinnings proved to be crucial. The regimes with heavy and late thinnings were generally more profitable than those with normal thinnings. Further, early thinning (relative to stand volume) lacked appeal when seeking a financially profitable removal from the first thinning. In young stands with an initially poor silvicultural condition, however, applying even a low-yielding first thinning considerably increased the NPV when compared to a regime with no thinning at all. Generally, the regimes resulting in the best profitability included heavier thinnings and fewer DNM and thinning treatments than did the regimes resulting in the best yield results. This study demonstrates considerable potential for profitable wood production-oriented management in pine stands on drained peatlands despite their challenging circumstances and long rotations. The results can be used for defining new and more site-specific silvicultural guidelines for various types of drained, pine-dominated peatland stands within the entire range of boreal conditions.

QTL for nodal root angle in sorghum (Sorghum bicolor L. Moench) co-locate with QTL for traits associated with drought adaptation.

Nodal root angle in sorghum influences vertical and horizontal root distribution in the soil profile and is thus relevant to drought adaptation. In this study, we report for the first time on the mapping of four QTL for nodal root angle (qRA) in sorghum, in addition to three QTL for root dry weight, two for shoot dry weight, and three for plant leaf area. Phenotyping was done at the six leaf stage for a mapping population (n = 141) developed by crossing two inbred sorghum lines with contrasting root angle. Nodal root angle QTL explained 58.2% of the phenotypic variance and were validated across a range of diverse inbred lines. Three of the four nodal root angle QTL showed homology to previously identified root angle QTL in rice and maize, whereas all four QTL co-located with previously identified QTL for stay-green in sorghum. A putative association between nodal root angle QTL and grain yield was identified through single marker analysis on field testing data from a subset of the mapping population grown in hybrid combination with three different tester lines. Furthermore, a putative association between nodal root angle QTL and stay-green was identified using data sets from selected sorghum nested association mapping populations segregating for root angle. The identification of nodal root angle QTL presents new opportunities for improving drought adaptation mechanisms via molecular breeding to manipulate a trait for which selection has previously been very difficult.

Significant evidence of one or more susceptibility loci for endometriosis with near-Mendelian inheritance on chromosome 7p13-15

BACKGROUND: Endometriosis is a common disease with a heritable component. The collaborative International Endogene Study consists of two data sets (Oxford and Australia) comprising 1176 families with multiple affected. The aim was to investigate whether the apparent concentration of cases in a proportion of families could be explained by one or more rare variants with (near-)Mendelian autosomal inheritance. METHODS AND RESULTS: Linkage analyses (aimed at finding chromosomal regions harbouring disease-predisposing genes) were conducted in families with three or more affected (Oxford: n = 52; Australia: n = 196). In the Oxford data set, a non-parametric linkage score (Kong & Cox (K&C) Log of ODds (LOD)) of 3.52 was observed on chromosome 7p (genome-wide significance P = 0.011). A parametric MOD score (equal to maximum LOD maximized over 357 possible inheritance models) of 3.89 was found at 65.72 cM (D7S510) for a dominant model with reduced penetrance. After including the Australian data set, the non-parametric K&C LOD of the combined data set was 1.46 at 57.3 cM; the parametric analysis found an MOD score of 3.30 at D7S484 (empirical significance: P = 0.035) for a recessive model with high penetrance. Critical recombinant analysis narrowed the probable region of linkage down to overlapping 6.4 Mb and 11 Mb intervals containing 48 and 96 genes, respectively. CONCLUSIONS: This is the first report to suggest that there may be one or more high-penetrance susceptibility loci for endometriosis with (near-)Mendelian inheritance.

Options for selecting dairy cattle for milk coagulation ability

Lypsylehmien maidon juoksettumiskyvyn jalostuskeinot Väitöskirjassa tutkittiin lypsylehmien maidon juustonvalmistuslaadun parantamista jalostusvalinnan avulla. Tutkimusaihe on tärkeä, sillä yhä suurempi osa maidosta käytetään juustonvalmistukseen. Tutkimuksen kohteena oli maidon juoksettumiskyky, sillä se on yksi keskeisistä juustomäärään vaikuttavista tekijöistä. Maidon juoksettumiskyky vaihteli huomattavasti lehmien, sonnien, karjojen, rotujen ja lypsykauden vaiheiden välillä. Vaikka tankkimaidon juoksettumiskyvyssä olikin suuria eroja karjoittain, karja selitti vain pienen osan juoksettumiskyvyn kokonaisvaihtelusta. Todennäköisesti perinnölliset erot lehmien välillä selittävät suurimman osan karjojen tankkimaitojen juoksettumiskyvyssä havaituista eroista. Hyvä hoito ja ruokinta vähensivät kuitenkin jossain määrin huonosti juoksettuvien tankkimaitojen osuutta karjoissa. Holstein-friisiläiset lehmät olivat juoksettumiskyvyltään ayrshire-rotuisia lehmiä parempia. Huono juoksettuminen ja juoksettumattomuus oli vain vähäinen ongelma holstein-friisiläisillä (10 %), kun taas kolmannes ayrshire-lehmistä tuotti huonosti juoksettuvaa tai juoksettumatonta maitoa. Maitoa sanotaan huonosti juoksettuvaksi silloin, kun juustomassa ei ole riittävän kiinteää leikattavaksi puolen tunnin kuluttua juoksetteen lisäyksestä. Juoksettumattomaksi määriteltävä maito ei saostu lainkaan puolen tunnin aikana ja on siksi erittäin huonoa raaka-ainetta juustomeijereille. Noin 40 % lehmien välisistä eroista maidon juoksettumiskyvyssä selittyi perinnöllisillä tekijöillä. Juoksettumiskykyä voikin sanoa hyvin periytyväksi ominaisuudeksi. Kolme mittauskertaa lehmää kohti riittää varsin hyvin lehmän maidon keskimääräisen juoksettumiskyvyn arvioimiseen. Tällä hetkellä juoksettumiskyvyn suoran jalostamisen ongelmana on kuitenkin automatisoidun, laajamittaiseen käyttöön soveltuvan mittalaitteen puute. Tämän takia väitöskirjassa tutkittiin mahdollisuuksia jalostaa maidon juoksettumiskykyä epäsuorasti, jonkin toisen ominaisuuden kautta. Tällaisen ominaisuuden pitää olla kyllin voimakkaasti perinnöllisesti kytkeytynyt juoksettumiskykyyn, jotta jalostus olisi mahdollista sen avulla. Tutkittavat ominaisuudet olivat sonnien kokonaisjalostusarvossa jo mukana olevat maitotuotos ja utareterveyteen liittyvät ominaisuudet sekä kokonaisjalostusarvoon kuulumattomat maidon valkuais- ja kaseiinipitoisuus sekä maidon pH. Väitöskirjassa tutkittiin myös mahdollisuuksia ns. merkkiavusteiseen valintaan tutkimalla maidon juoksettumattomuuden perinnöllisyyttä ja kartoittamalla siihen liittyvät kromosomialueet. Tutkimuksen tulosten perusteella lehmien utareterveyden jalostaminen parantaa jonkin verran myös maidon juoksettumiskykyä sekä vähentää juoksettumattomuutta ayrshire-rotuisilla lehmillä. Lehmien maitotuotos ja maidon juoksettumiskyky sekä juoksettumattomuus ovat sen sijaan perinnöllisesti toisistaan riippumattomia ominaisuuksia. Myöskin maidon valkuais- ja kaseiinipitoisuuden perinnöllinen yhteys juoksettumiskykyyn oli likimain nolla. Maidon pH:n ja juoksettumiskyvyn välillä oli melko voimakas perinnöllinen yhteys, joten maidon pH:n jalostaminen parantaisi myös maidon juoksettumiskykyä. Todennäköisesti sen jalostaminen ei kuitenkaan vähentäisi juoksettumatonta maitoa tuottavien lehmien määrää. Koska maidon juoksettumattomuus on niin yleinen ongelma suomalaisilla ayrshire-lehmillä, väitöksessä selvitettiin tarkemmin ilmiön taustoja. Kaikissa kolmessa tutkimusaineistoissa noin 10 % ayrshire-lehmistä tuotti juoksettumatonta maitoa. Kahden vuoden kuukausittaisen seurannan aikana osa lehmistä tuotti juoksettumatonta maitoa lähes joka mittauskerralla. Maidon juoksettumattomuus oli yhteydessä lypsykauden vaiheeseen, mutta mikään ympäristötekijöistä ei pystynyt täysin selittämään sitä. Sen sijaan viitteet sen periytyvyydestä vahvistuivat tutkimusten edetessä. Lopuksi tutkimusryhmä onnistui kartoittamaan juoksettumattomuutta aiheuttavat kromosomialueet kromosomeihin 2 ja 18, lähelle DNA-merkkejä BMS1126 ja BMS1355. Tulosten perusteella maidon juoksettumattomuus ei ole yhteydessä maidon juoksettumistapahtumassa keskeisiin kaseiinigeeneihin. Sen sijaan on mahdollista, että juoksettumattomuusongelman aiheuttavat kaseiinigeenien syntetisoinnin jälkeisessä muokkauksessa tapahtuvat virheet. Asia vaatii kuitenkin perusteellista tutkimista. Väitöksen tulosten perusteella maidon juoksettumattomuusgeeniä kantavien eläinten karsiminen jalostuseläinten joukosta olisi tehokkain tapa jalostaa maidon juoksettumiskykyä suomalaisessa lypsykarjapopulaatiossa.

Autonomous UAVs wildlife detection using thermal imaging, predictive navigation and computer vision

There is an increased interest on the use of Unmanned Aerial Vehicles (UAVs) for wildlife and feral animal monitoring around the world. This paper describes a novel system which uses a predictive dynamic application that places the UAV ahead of a user, with a low cost thermal camera, a small onboard computer that identifies heat signatures of a target animal from a predetermined altitude and transmits that target’s GPS coordinates. A map is generated and various data sets and graphs are displayed using a GUI designed for easy use. The paper describes the hardware and software architecture and the probabilistic model for downward facing camera for the detection of an animal. Behavioral dynamics of target movement for the design of a Kalman filter and Markov model based prediction algorithm are used to place the UAV ahead of the user. Geometrical concepts and Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of the user, thus delivering a new way point for autonomous navigation. Results show that the system is capable of autonomously locating animals from a predetermined height and generate a map showing the location of the animals ahead of the user.

Components of productivity growth in Finnish agriculture

The objective was to measure productivity growth and its components in Finnish agriculture, especially in dairy farming. The objective was also to compare different methods and models - both parametric (stochastic frontier analysis) and non-parametric (data envelopment analysis) - in estimating the components of productivity growth and the sensitivity of results with respect to different approaches. The parametric approach was also applied in the investigation of various aspects of heterogeneity. A common feature of the first three of five articles is that they concentrate empirically on technical change, technical efficiency change and the scale effect, mainly on the basis of the decompositions of Malmquist productivity index. The last two articles explore an intermediate route between the Fisher and Malmquist productivity indices and develop a detailed but meaningful decomposition for the Fisher index, including also empirical applications. Distance functions play a central role in the decomposition of Malmquist and Fisher productivity indices. Three panel data sets from 1990s have been applied in the study. The common feature of all data used is that they cover the periods before and after Finnish EU accession. Another common feature is that the analysis mainly concentrates on dairy farms or their roughage production systems. Productivity growth on Finnish dairy farms was relatively slow in the 1990s: approximately one percent per year, independent of the method used. Despite considerable annual variation, productivity growth seems to have accelerated towards the end of the period. There was a slowdown in the mid-1990s at the time of EU accession. No clear immediate effects of EU accession with respect to technical efficiency could be observed. Technical change has been the main contributor to productivity growth on dairy farms. However, average technical efficiency often showed a declining trend, meaning that the deviations from the best practice frontier are increasing over time. This suggests different paths of adjustment at the farm level. However, different methods to some extent provide different results, especially for the sub-components of productivity growth. In most analyses on dairy farms the scale effect on productivity growth was minor. A positive scale effect would be important for improving the competitiveness of Finnish agriculture through increasing farm size. This small effect may also be related to the structure of agriculture and to the allocation of investments to specific groups of farms during the research period. The result may also indicate that the utilization of scale economies faces special constraints in Finnish conditions. However, the analysis of a sample of all types of farms suggested a more considerable scale effect than the analysis on dairy farms.

Estimation of cosmological parameters using adaptive importance sampling

We present a Bayesian sampling algorithm called adaptive importance sampling or population Monte Carlo (PMC), whose computational workload is easily parallelizable and thus has the potential to considerably reduce the wall-clock time required for sampling, along with providing other benefits. To assess the performance of the approach for cosmological problems, we use simulated and actual data consisting of CMB anisotropies, supernovae of type Ia, and weak cosmological lensing, and provide a comparison of results to those obtained using state-of-the-art Markov chain Monte Carlo (MCMC). For both types of data sets, we find comparable parameter estimates for PMC and MCMC, with the advantage of a significantly lower wall-clock time for PMC. In the case of WMAP5 data, for example, the wall-clock time scale reduces from days for MCMC to hours using PMC on a cluster of processors. Other benefits of the PMC approach, along with potential difficulties in using the approach, are analyzed and discussed.

Monitoring healing progression and characterizing the mechanical environment in preclinical models for bone tissue engineering

The treatment of large segmental bone defects remains a significant clinical challenge. Due to limitations surrounding the use of bone grafts, tissue-engineered constructs for the repair of large bone defects could offer an alternative. Before translation of any newly developed tissue engineering (TE) approach to the clinic, efficacy of the treatment must be shown in a validated preclinical large animal model. Currently, biomechanical testing, histology, and microcomputed tomography are performed to assess the quality and quantity of the regenerated bone. However, in vivo monitoring of the progression of healing is seldom performed, which could reveal important information regarding time to restoration of mechanical function and acceleration of regeneration. Furthermore, since the mechanical environment is known to influence bone regeneration, and limb loading of the animals can poorly be controlled, characterizing activity and load history could provide the ability to explain variability in the acquired data sets and potentially outliers based on abnormal loading. Many approaches have been devised to monitor the progression of healing and characterize the mechanical environment in fracture healing studies. In this article, we review previous methods and share results of recent work of our group toward developing and implementing a comprehensive biomechanical monitoring system to study bone regeneration in preclinical TE studies.

Remote sensing of boreal land cover: estimation of forest attributes and extent

Remote sensing provides methods to infer land cover information over large geographical areas at a variety of spatial and temporal resolutions. Land cover is input data for a range of environmental models and information on land cover dynamics is required for monitoring the implications of global change. Such data are also essential in support of environmental management and policymaking. Boreal forests are a key component of the global climate and a major sink of carbon. The northern latitudes are expected to experience a disproportionate and rapid warming, which can have a major impact on vegetation at forest limits. This thesis examines the use of optical remote sensing for estimating aboveground biomass, leaf area index (LAI), tree cover and tree height in the boreal forests and tundra taiga transition zone in Finland. The continuous fields of forest attributes are required, for example, to improve the mapping of forest extent. The thesis focus on studying the feasibility of satellite data at multiple spatial resolutions, assessing the potential of multispectral, -angular and -temporal information, and provides regional evaluation for global land cover data. Preprocessed ASTER, MISR and MODIS products are the principal satellite data. The reference data consist of field measurements, forest inventory data and fine resolution land cover maps. Fine resolution studies demonstrate how statistical relationships between biomass and satellite data are relatively strong in single species and low biomass mountain birch forests in comparison to higher biomass coniferous stands. The combination of forest stand data and fine resolution ASTER images provides a method for biomass estimation using medium resolution MODIS data. The multiangular data improve the accuracy of land cover mapping in the sparsely forested tundra taiga transition zone, particularly in mires. Similarly, multitemporal data improve the accuracy of coarse resolution tree cover estimates in comparison to single date data. Furthermore, the peak of the growing season is not necessarily the optimal time for land cover mapping in the northern boreal regions. The evaluated coarse resolution land cover data sets have considerable shortcomings in northernmost Finland and should be used with caution in similar regions. The quantitative reference data and upscaling methods for integrating multiresolution data are required for calibration of statistical models and evaluation of land cover data sets. The preprocessed image products have potential for wider use as they can considerably reduce the time and effort used for data processing.

High-Throughput Prediction of Acacia and Eucalypt Lignin Syringyl/Guaiacyl Content Using FT-Raman Spectroscopy and Partial Least Squares Modeling

High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials.

Bayesian statistical analysis of bacterial diversity

Bacteria play an important role in many ecological systems. The molecular characterization of bacteria using either cultivation-dependent or cultivation-independent methods reveals the large scale of bacterial diversity in natural communities, and the vastness of subpopulations within a species or genus. Understanding how bacterial diversity varies across different environments and also within populations should provide insights into many important questions of bacterial evolution and population dynamics. This thesis presents novel statistical methods for analyzing bacterial diversity using widely employed molecular fingerprinting techniques. The first objective of this thesis was to develop Bayesian clustering models to identify bacterial population structures. Bacterial isolates were identified using multilous sequence typing (MLST), and Bayesian clustering models were used to explore the evolutionary relationships among isolates. Our method involves the inference of genetic population structures via an unsupervised clustering framework where the dependence between loci is represented using graphical models. The population dynamics that generate such a population stratification were investigated using a stochastic model, in which homologous recombination between subpopulations can be quantified within a gene flow network. The second part of the thesis focuses on cluster analysis of community compositional data produced by two different cultivation-independent analyses: terminal restriction fragment length polymorphism (T-RFLP) analysis, and fatty acid methyl ester (FAME) analysis. The cluster analysis aims to group bacterial communities that are similar in composition, which is an important step for understanding the overall influences of environmental and ecological perturbations on bacterial diversity. A common feature of T-RFLP and FAME data is zero-inflation, which indicates that the observation of a zero value is much more frequent than would be expected, for example, from a Poisson distribution in the discrete case, or a Gaussian distribution in the continuous case. We provided two strategies for modeling zero-inflation in the clustering framework, which were validated by both synthetic and empirical complex data sets. We show in the thesis that our model that takes into account dependencies between loci in MLST data can produce better clustering results than those methods which assume independent loci. Furthermore, computer algorithms that are efficient in analyzing large scale data were adopted for meeting the increasing computational need. Our method that detects homologous recombination in subpopulations may provide a theoretical criterion for defining bacterial species. The clustering of bacterial community data include T-RFLP and FAME provides an initial effort for discovering the evolutionary dynamics that structure and maintain bacterial diversity in the natural environment.

The Queensland Mango Genomics Initiative

Mango is an important industry for Queensland, Australia, with an annual value exceeding $80 million. The Kensington Pride cultivar, prized by consumers for desirable taste and colour characteristics, commands 60% of the domestic market though this market share has declined in recent years as new varieties, such as Calypso™, get established with consumers. In 2005, the Queensland Government's Department of Agriculture and Fisheries commenced the Mango Genomics Initiative. This project brought together multidisciplinary teams of breeders, pathologists, sensory scientists, flavour chemists and molecular biologists to develop a suite of tools and inter-related data sets to support the accelerated development of new commercial mango varieties. An overview of the Mango Genomics Initiative will be presented here culminating in the generation of a draft Kensington Pride mango genome sequence.

Place Identification : A Comparative Study

Place identification is the methodology of automatically detecting spatial regions or places that are meaningful to a user by analysing her location traces. Following this approach several algorithms have been proposed in the literature. Most of the algorithms perform well on a particular data set with suitable choice of parameter values. However, tuneable parameters make it difficult for an algorithm to generalise to data sets collected from different geographical locations, different periods of time or containing different activities. This thesis compares the generalisation performance of our proposed DPCluster algorithm along with six state-of-the-art place identification algorithms on twelve location data sets collected using Global Positioning System (GPS). Spatial and temporal variations present in the data help us to identify strengths and weaknesses of the place identification algorithms under study. We begin by discussing the notion of a place and its importance in location-aware computing. Next, we discuss different phases of the place identification process found in the literature followed by a thorough description of seven algorithms. After that, we define evaluation metrics and compare generalisation performance of individual place identification algorithms and report the results. The results indicate that the DPCluster algorithm performs superior to all other algorithms in terms of generalisation performance.

Spirituality of Finnish peacekeepers

The previous academic research on Finnish peacekeeping has clarified the operative and historical aspects of Finnish peacekeeping lacking the view of an individual who does the actual peacekeeping work. This research is based on the underlying theoretical assumption of human beings possessing different kinds of talents and intelligences creating a holistic entity. In this broad perspective spirituality was explored as an umbrella concept, as a holistic ability or talent, that can be explored as the deepest aspect of defining what it means to be human. The theoretical framework incorporated the concept of an intelligence, which is defined in Gardner's theory of multiple intelligences as the ability to solve problems, or to create products, that are valued within one or more cultural settings (Gardner, 1993, x). The viability of this theory was studied in the sample of Finnish peacekeepers. Spirituality in the theoretical and conceptual horizon was viewed as an extension of Gardner's theory of intelligences as one potential Gardnerian intelligence candidate. In addition to Gardner's theory, spirituality was explored as sensitivity which includes capacities such as sensing awareness, sensing mystery and sensing value (Hay, 1998). Also the practical aspects of spirituality were taken in account as shown in our everyday lives giving us the direction and influencing our social responsibilities and concerns (Bradford, 1995). Spirituality was explored also involving the element of the peacekeepers' community, the element of personal moral orientations and in the domain of religion and coping. The purpose of this research aimed in two dimensions. First, the aim was to outline the intelligence profile and the spiritual sensitivity profile of peacekeepers. Second, the aim was to understand qualitatively the nature of peacekeepers' spirituality The research interests were studied with different kinds of peacekeepers. Applying the mixed methods approach the research was conducted in two phases: first the former SFOR peacekeepers (N=6) were interviewed and the data was analysed. Inspired by the primary findings of these interviews, the data for the case-study of one peacekeeper was collected in co-operation with one former SFOR peacekeeper (N=1). In the second phase the data was collected from KFOR peacekeepers through the quantitative MI-Survey and the spiritual sensitivity survey (N=195). The quantitative method was used to outline the intelligence profile and the spiritual sensitivity profile of peacekeepers (N=195). In the mixed methods approach this method highlighted the general overview of intelligence traits and spiritual sensitivity of peacekeepers. In the mixed methods approach the qualitative method including interviews (N=6) and a case-study of one peacekeeper (N=1) increased subjective, qualitative information of spirituality of peacekeepers. The intelligence profile of peacekeepers highlighted the bodily-kinesthetic and interpersonal dimensions as the practical and social aspects of peacekeepers. Strong inter-item dependencies in the intrapersonal intelligence profile meant that peacekeepers possess a self-reflection and self-knowledge component and they reflect on deep psychological and philosophical issues. Regarding the spiritual sensitivity, peacekeepers found awareness-sensing, mystery-sensing, value-sensing and community-sensing important. The community-sensing emphasised a strong will to advance peace and to help people who are in need: things that are close to the heart of the peacekeepers. These results depicted practicality, being socially capable, and reflecting one's inner world as essential to peacekeepers. Moreover, spirituality as peacekeepers' moral endeavour became clearer because the sub-model of their community-sensing described morally charged destinations: advancing peace and helping people in need. In the qualitative findings peacekeepers articulated justice orientation and rule-following characterising the nature of peacekeepers' moral attitude and moral call (Kohlberg, 1969). An ethic of care (Gilligan, 1982) describes mainly female moral orientation, but the findings revealed that an ethic of care is also an important agent supporting strongly male peacekeepers in their aim to carry out qualitatively good peacekeeping work. The moral endeavour was voiced, when the role of religion in coping meant the assessment of the a way of life, a way of conduct, a way of being truthful to one's own values in confusing surroundings. The practical level of spiritual and religious contemplation was voiced as morally charged inner motivation to fulfil one's duties and at the same time to cope with various peacekeeping challenges. The results of different data sets were combined and interpreted as the moral endeavour, which characterises peacekeepers' spirituality. As the combining result, the perspective of peacekeepers' spirituality is considered moral or at least morally charged.