This thesis describes a domain of interdependencies emerging in within the projects as well as between them, in situations, when these projects are about to reach the same objective using their shared deliverables or resources. In the IT projects area are such project interdependencies rather identified in majority of all ongoing projects - due to this reason, the theoretical part of this thesis describes relationship of areas of project, program and portfolio management as well as managing projects in the multi-project environment and dependency management. Based on the results of the theoretical part and acquired knowledge, the tools and techniques for managing such project interdependencies are presented in the practical part of this work. The aim of the theoretical part is to introduce the issue of management of interrelated projects and to identify the areas, in which the formation of dependencies and linkages occurs and is followed by the subsequent need of their management - then the practical part is focused on the exploration and presentation of the functionality of available tools and methods that can be used to manage projects interdependencies. When selecting the specific tools and methods, the practical part of this thesis further develops the results theoretical part and extends mapping and assignment of specific tools and methods in different areas of interdependencies and management levels. Due to this systematic approach to the interdependencies topic, which is firstly described on a theoretical level, and then extended with the practically - oriented attitude, the thesis points out where the interdependencies are, who is responsible for managing them and which tools and methods can be used to identify, describe control and work with them. A useful overview of this quite unknown area is provided by this thesis.

In the early 1990s, Robert Kaplan and David Norton introduced and developed a new performance measurement and management system called the balanced scorecard (BSC). Most studies have found that evaluators tend to ignore or are not willing to use nonfinancial measures. This study attempts to examine whether the explicit linkage between the evaluator's BSC and the subordinate's BSC makes the evaluators use nonfinancial measures in performance evaluation. This study used an experimental design where subjects were asked to evaluate two managers' performance under explicit linkage versus nonexplicit linkage conditions. The difference between performance evaluation scores of the two managers under the two linkage conditions captures the influence of explicit linkage between BSCs on performance evaluation. I used regression analyses to test my hypothesis. The results of the regression analyses support my hypothesis. This study attempts to explore one possible reason for evaluators' not using nonfinancial measures much in performance evaluation. It is the first one that studies the influence of the linkage between the BSCs on performance evaluation.

The evolutionary relevance of homeotic alterations for the origin of new taxonomic entities is still a controversial objective in plant sciences. In this context, the discovery of a floral homeotic variant of Capsella bursa-pastoris in natural populations offers the unique opportunity to elucidate the evolutionary significance of homeotic mutants in the wild. Since all petals are transformed into additional stamens, the variant was termed Stamenoid petals (Spe). In this thesis, a combination of ecological and molecular characterisation of the variant was performed, to improve the understanding of evolutionary processes in plant populations. Molecular markers were used to analyze genetic differentiation among known provenances and also within a large sympatric population of wild-type and homeotic mutant. The results clearly suggest a repeated evolution of the novel flower morphology. Furthermore, genetic analyses provided substantial evidence, that the two floral variants are well-defined into flower-type dependent sub-samples within one population. The evaluation of phenotypic traits elucidated that the homeotic variant is not hampered in fitness. In greenhouse and field experiments, a significant ecological differentiation in the onset of flowering was detected among variants. Finally, the novel floral phenotype shows a co-dominant inheritance, and a marker-assisted mapping approach exposed a single locus in a genetic map. In conclusion, the comprehensive study of ecological and molecular aspects indicates that the floral homeotic variant may be treated as an established taxonomic entity and proved the predicted role as model for evolutionary objectives. Since morphological alterations like Spe are discussed as a result of macroevolution, the homeotic variant of C. bursa-pastoris provides the opportunity to survey a (macro)evolutionary novelty in association with continuous micro-evolutionary adaptation

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Due to biodiversity loss being large as well as threatening ecosystem functions necessary for oursociety, the UN and EU have created regulations, strategies, and targets to improve biodiversity.Nationally in Sweden, and locally in Stockholm municipality, actions have also been taken. Oakhabitat is especially interesting for the municipality due to its high biodiversity values. This is whyin this study biodiversity connected to potential oak habitats was analysed by a GIS-basedconnectivity model; through which maps depicting possible movements by a model speciescomplex were created. An interview study was performed to investigate the use of GIS-basedplanning support tools for biodiversity, from the perspectives of professionals. Results suggestthat the methods for making choices regarding friction values need to be more transparent andbetter communicated, or standardised, both alternatives with the goal of facilitating interpretationof maps by physical planners. Also, depending on where in the planning process GIS-basedplanning support tools are used, they can be used in different ways. Early in the process, or evenbefore planning starts, they can act as decision support. After the implementation of a plan, theycan instead be beneficial for follow-up of biodiversity aspects. / Förlust av biologisk mångfald är problematisk och påverkar effektiviteten hos naturligaekosystem. De planetära gränserna för biologisk mångfald har sedan länge överskridits. Mål,lagar, och strategier från FN, EU och nationellt visar att frågor kopplade till biologisk mångfald ärbåde viktiga och aktuella. År 2020 antogs Stockholms stads första Handlingsplan för Biologisk Mångfald, vilken påverkarflertalet lokala åtgärder och mål. Ekar, som är en del av det svenska ädellövsbeståndet, ärprioriterade i Stockholms arbete med biologisk mångfald. I GIS-analyser har vissa skalbaggsarteranvänts som indikatorer för bedömning av naturvärden hos dessa bestånd. I denna studie genomfördes en litteraturstudie och fyra intervjuer för djupare insikt i relationenmellan GIS-baserade verktyg för planeringsstöd för biologisk mångfald, och fysisk planering, iStockholms stad. Ytterligare litteraturstudier genomfördes, inriktade på modellarter för biologiskmångfald i ekhabitat, samt tillvägagångssätt vid skapande av friktionsraster.Konnektivitetsanalyser av potentiella ekhabitat, i studieområdet Skarpnäck i södra Stockholm,genomfördes i ArcGIS och Linkage Mapper. Dessa fokuserade på analysens känslighet vidvariation av utvalda parametrar. Huvudsakliga resultat utgörs av kartor där korridorer och kostviktade avstånd beskrivermöjligheten till rörelse mellan habitat, samt hur dessa kan variera drastiskt av attparametervärden ändras. Den största skillnaden uppstod när större vägar betraktades sombarriärer. Det andra huvudsakliga resultatet består av en sammanställning av de intervjuer somutfördes. Där framgår att tidigt i planeringsprocessen, eller innan planprocessen påbörjas, kanGIS-baserade planeringsverktyg användas som beslutstöd. När planen genomförts kan de iställetvara användbara för uppföljning av konsekvenser för biologisk mångfald. Där dessa delar möts uppstår en diskussion om hur GIS-baserade verktyg kan utgöra ett stöd vidplanering för biologisk mångfald, hur det idag används på flertalet sätt och att användningen bådekan utökas och förbättras. Brister i transparens, och rättfärdigande av val av metod ochfriktionsvärden i konnektivitetsanalyser, ses i ljuset av möjligheten att som icke-professionellinom GIS kunna tolka kartor menade att användas som planeringsstöd.

The component-level performance of materials is fundamentally determined by the underlying microstructural features. Therefore, designing high-performance materials using multi-scale models plays a significant role to improve the predictability, reliability, proper functioning, and longevity of components for a wide range of applications in the fields of aerospace, electronics, energy, and structural engineering. This thesis aims to develop new methodologies to design microstructures under inherent material uncertainty by incorporating machine learning techniques. To achieve this objective, the study addresses gradient-based and machine learning-driven design optimization methods to enhance homogenized linear and non-linear properties of polycrystalline microstructures. However, variations arising from the thermo-mechanical processing of materials affect microstructural features and properties by propagating over multiple length scales. To quantify this inherent microstructural uncertainty, this study introduces a linear programming-based analytical method. When this analytical uncertainty quantification formulation is not applicable (e.g., uncertainty propagation on non-linear properties), a machine learning-based inverse design approach is presented to quantify the microstructural uncertainty. Example design problems are discussed for different polycrystalline systems (e.g., Titanium, Aluminium, and Galfenol). Though conventional machine learning performs well when used for designing microstructures or modeling material properties, its predictions may still fail to satisfy design constraints associated with the physics of the system. Therefore, the physics-informed neural network (PINN) is developed to incorporate problem physics in the machine learning formulation. In this study, a PINN model is built and integrated into materials design to study the deformation processes of Copper and a Titanium-Aluminum alloy. / Doctor of Philosophy / Microstructure-sensitive design is a high-throughput computational approach for materials design, where material performance is improved through the control and design of microstructures. It enhances component performance and, subsequently, the overall system's performance at the application level. This thesis aims to design microstructures for polycrystalline materials such as Galfenol, Titanium-Aluminum alloys, and Copper to obtain desired mechanical properties for certain applications. The advantage of the microstructure-sensitive design approach is that multiple microstructures can be suggested, which provide a similar value of the design parameters. Therefore, manufacturers can follow any of these microstructure designs to fabricate the materials with the desired properties. Moreover, the microstructure uncertainty arising from the variations in thermo-mechanical processing and measurement of the experimental data is quantified. It is necessary to address the resultant randomness of the microstructure because it can alter the expected mechanical properties. To check the manufacturability of proposed microstructure designs, a physics-informed machine learning model is developed to build a relation between the process, microstructure, and material properties. This model can be used to solve the process design problem to identify the processing parameters to achieve a given/desired microstructure.

Background: The impact children with complex healthcare needs have on the healthcare system is significant and requires a multidisciplinary response. Congenital anomaly (CA) is a group of conditions requiring complex and variable input from primary and secondary healthcare. This thesis explores the literature on health system preparedness for children with complex healthcare needs and quantitatively describes healthcare use for a population of children with CA, an exemplar for children with complex healthcare needs. Methods: Routine health data from primary care was explored to identify children with CA and linked to secondary care data, outpatient records, and questionnaire data from a multi-ethnic prospective birth cohort over a five-year period. Rates of CA were calculated and healthcare use for children with and without CA was analysed. Results: Out of a birth cohort of 13,857 children, 860 had a CA. Using primary care data for children aged 0 to 5 years, the number of children with CA was found to be 620.6 per 10,000 live births, above the national rate of 226.5 per 10,000 live births. Healthcare use was higher for children with CA than those without CA. Demand for use of hospital services for children with CA was higher (Incident rate ratio (IRR) 4.38, 95% confidence interval (CI) 3.90 to 4.92) than demand for primary care services (IRR, 1.27, 95% CI 1.20 to 1.35). Conclusion: These results suggest that using primary care data as a source of CA case ascertainment reveals more children with CA than previously thought. These results have significant implications for commissioning healthcare services for children with complex healthcare needs.

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