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Vybrané aspekty vývoje úmrtnosti v USA od přelomu tisíciletí / Selected aspects of the mortality development in the USA since the turn of the millenniumVančurová, Mariana January 2021 (has links)
Selected aspects of the mortality development in the USA since the turn of the millennium Abstract The main goal of the thesis was to analyze the development of mortality from selected causes in the USA between the years 1999 and 2019. The selected causes are long-term leading causes of death in the USA. These include cardiovascular diseases, malignant neoplasms, chronic lower respiratory diseases, external causes and cerebrovascular diseases. The current disease covid-19 was included in the selected causes of death, as according to preliminary data, it was the third leading cause of death in the USA in the year 2020. The first part presents the mortality rates in the USA from different perspectives to create the context of the current development of mortality trends and also characterizes the individual causes of death, which are then addressed in the analytical part of the thesis. Furthermore, the healthcare system of the USA is described, as it is one of the factors influencing the mortality rate and also because it differs significantly from the systems known in Europe. The second part presents the development of mortality from selected causes of death, according to sex and individual US states. Methods used in the analytical part of the thesis were the gross mortality rate, direct and indirect...
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Shlukování proteinových sekvencí na základě podobnosti primární struktury / Clustering of Protein Sequences Based on Primary Structure of ProteinsJurásek, Petr January 2009 (has links)
This master's thesis consider clustering of protein sequences based on primary structure of proteins. Studies the protein sequences from they primary structure. Describes methods for similarities in the amino acid sequences of proteins, cluster analysis and clustering algorithms. This thesis presents concept of distance function based on similarity of protein sequences and implements clustering algorithms ANGES, k-means, k-medoids in Python programming language.
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Student Placement: A Multifaceted Methodological ToolkitHille, Kathryn Streeter January 2019 (has links)
No description available.
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Detecting and Measuring Corruption and Inefficiency in Infrastructure Projects Using Machine Learning and Data AnalyticsSeyedali Ghahari (11182092) 19 February 2022 (has links)
Corruption is a social evil that resonates far and deep in societies,
eroding trust in governance, weakening the rule of law, impairing economic
development, and exacerbating poverty, social tension, and inequality. It is
a multidimensional and complex societal malady that occurs in various forms and
contexts. As such, any effort to combat corruption must be accompanied by a
thorough examination of the attributes that might play a key role in
exacerbating or mitigating corrupt environments. This dissertation identifies a number of attributes that
influence corruption, using machine learning techniques, neural network
analysis, and time series causal relationship analysis and aggregated data from
113 countries from 2007 to 2017. The results suggest that improvements in
technological readiness, human development index, and e-governance index have
the most profound impacts on corruption reduction. This dissertation discusses
corruption at each phase of infrastructure systems development and engineering
ethics that serve as a foundation for corruption mitigation. The dissertation then applies novel analytical
efficiency measurement methods to measure infrastructure inefficiencies, and to rank
infrastructure administrative jurisdictions at the state level. An efficiency frontier is
developed using optimization and the highest performing jurisdictions are
identified. The dissertation’s framework could serve as a
starting point for governmental and non-governmental oversight agencies to
study forms and contexts of corruption and inefficiencies, and to propose
influential methods for reducing the instances. Moreover, the framework can help
oversight agencies to promote the overall accountability of infrastructure
agencies by establishing a clearer connection between infrastructure investment
and performance, and by carrying out comparative assessments of infrastructure
performance across the jurisdictions under their oversight or supervision.
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Land-change dynamics and ecosystem services using expert-based assessment and GIS: methodological implications for improving decision-makingMadrigal Martínez, Santiago 02 September 2021 (has links)
Tesis por compendio / [ES] Los servicios ecosistémicos de montaña han adquirido importancia entre los científicos, los administradores y los encargados de formular políticas de todo el mundo; sin embargo, las actividades humanas están amenazando su conservación, en particular los cambios en el uso del suelo debido al aumento de la urbanización, la expansión agrícola y la deforestación. La Puna Altoandina es un ecosistema montañoso representativo que enfrenta estos serios y crecientes desafíos. La Puna Altoandina, cuyos principales socioecosistemas consisten en pastizales naturales, matorrales y zonas agrícolas, puede proporcionar múltiples servicios ecosistémicos influenciados por el tipo de cobertura terrestre y sus dinámicas.
En este contexto, se han explorado las dinámicas entre los usos representativos de la superficie terrestre y su potencial para proporcionar servicios ecosistémicos en la Puna húmeda Altoandina a lo largo del tiempo. Asimismo, se ha completado un análisis espacio-temporal que describe cómo diferentes patrones de 6 dinámicas de cambio del uso del suelo impactan en la provisión de 7 servicios ecosistémicos durante un período de 13 años (de 2000 a 2013), y en el territorio de 25 provincias. Además, con el fin de mejorar la gestión de los servicios ecosistémicos, abordamos los efectos de aplicar dos análisis "clúster" (estáticos y dinámicos) para evaluar los conjuntos de servicios ecosistémicos en cuatro escalas de observación diferentes (dos ámbitos administrativos y dos tamaños de pixel geográfico: 0.25 y 9 km2).
En general, este estudio proporciona un enfoque para facilitar la incorporación de los servicios ecosistémicos a múltiples escalas que permite una interpretación fácil del desarrollo de la región y que puede contribuir a mejorar las acciones para la gestión del uso del suelo y las decisiones de política ambiental. / [CA] Els serveis ecosistèmics muntanya han adquirit importància entre els científics, els administradors i els encarregats de formular polítiques de tot el món; no obstant això, les activitats humanes estan amenaçant la seua conservació, en particular els canvis en l'ús del sòl a causa de l'augment de la urbanització, l'expansió agrícola i la desforestació. La Puna Altoandina és un ecosistema muntanyenc representatiu que enfronta aquests seriosos i creixents desafiaments. La Puna Altoandina que els seus principals soci-ecosistemes consisteixen en pasturatges naturals, matolls i zones agrícoles, pot proporcionar múltiples serveis ecosistèmics influenciats per les diferents categories de cobertura terrestre y els seus dinàmiques.
En aquest context, s'han explorat les dinàmiques entre els usos representatius de la superfície terrestre i el seu potencial per a proporcionar serveis ecosistèmics en la Puna humida Altoandina al llarg del temps. Així mateix, s'ha completat una anàlisi espai-temporal que descriu com diferents patrons de 6 dinàmiques de canvi de l'ús del sòl impacten en la provisió de 7 serveis ecosistèmics durant un període de 13 anys (de 2000 a 2013), i en el territori de 25 províncies. A més, amb la finalitat de millorar la gestió dels serveis ecosistèmics, abordem els efectes d'aplicar dues anàlisis "clúster" (estàtics i dinàmics) per a avaluar els conjunts de serveis ecosistèmics en quatre escales d'observació diferents (dos àmbits administratius i dues grandàries de píxel geogràfic: 0.25 y 9 km2).
En general, aquest estudi proporciona un enfocament per a facilitar la incorporació dels serveis ecosistèmics a múltiples escales que permet una interpretació fàcil del desenvolupament de la regió i que pot contribuir a millorar les accions per la gestió de l'ús del sòl i les decisions de política ambiental. / [EN] Mountain ecosystem services have gained relevance among scientists, managers, and policy-makers worldwide; but, human activities are threatening its conservation, particularly land changes due to increased urbanization, agricultural expansion and deforestation. The high-Andean Puna is a representative mountain ecosystem that is facing these serious and growing challenges. The high-Andean Puna, whose main socialecosystems consist of natural grassland, shrubland and agricultural areas, can provide multiple regulating ecosystem services influenced by the land cover/use type and their dynamics.
In this context, we explored the dynamics between the representative land-cover classes and its potential to provide ecosystem services in the high-Andean moist Puna over time. We completed a spatiotemporal analysis that describes how different patterns of 6 landchange dynamics impact on the supply of 7 ecosystem services over a period of 13 years (from 2000 to 2013), and across 25 provinces. Moreover, in order to improve the management of ecosystem services, we addressed the effects of applying two cluster analyses (static and dynamic) for assessing bundles of ecosystem services across four different scales of observation (two administrative boundaries and two sizes of grids: 0.25 and 9 km2).
Overall, this study provides an approach to facilitate the incorporation of ES at multiple scales allowing an easy interpretation of the region development that can contribute to land management actions and policy decisions. / Madrigal Martínez, S. (2021). Land-change dynamics and ecosystem services using expert-based assessment and GIS: methodological implications for improving decision-making [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/172369 / Compendio
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Natural and Anthropogenic Sources Controlling Regional Groundwater Geochemistry on the Niagara PeninsulaSmal, Caitlin January 2017 (has links)
Groundwater chemistry on the Niagara Peninsula has been identified as highly mineralized in comparison to groundwaters collected from the same bedrock formations elsewhere in southern Ontario. Three geochemical zones were discerned using hierarchical cluster analysis and other geochemical and isotopic methods. The Escarpment Zone, located along the Niagara and Onondaga Escarpments, is characterized by unconfined aquifer conditions, parameters reflective of surficial contaminants, including road salt, and elevated HCO3, DOC, NO3-, coliform bacteria and tritium. In contrast, in the Salina Zone thick, low-permeability sediments and gypsiferous bedrock results in highly mineralized groundwaters with Ca-SO4 geochemical facies and elevated S2-, Ca2+, Mg2+, K+, Na+, SO42-, Cl-, Br-, Sr2+, NH4+ and CH4. The Guelph Zone contains the lowest electrical conductivity of the three zones and elevated F-. Outliers exist with groundwater geochemistry that differs from the local geochemical zone and the host aquifer. These sites have elevated SO42- (>1000 to 5200 mg/L) with depleted δ34SSO4 (-2.2 to 14.3‰ VCDT) signatures that differs starkly from Devonian and Silurian evaporites (~20 to 32 ‰) in the host formations. This exogenic SO4 was identified in a cross-formational northeast – southwest linear trend crossing three major groundwater flow systems. The lack of down-stream impact in these systems and tritium groundwater ages that are typically only decades old indicate a young, non-geological origin and implicate anthropogenic activities. Additionally, nine samples were identified with elevated methane concentrations and δ13CCH4 signatures within the thermogenic range. As thermogenic methane is not produced within shallow aquifers and would be short-lived in the presence of the ubiquitous sulfate, these samples imply recent upward migration of methane from depth through vertical conduits. Taken together, the evidence supports large-scale upward movement of fluids in the centre of the Niagara geochemical anomaly and more sporadic upward transport of gases over a wider area of the peninsula. The most likely vector is through corroded and leaking casings or boreholes of abandoned (century) gas wells that are common across the peninsula. / Thesis / Master of Science (MSc)
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Unsupervised Anomaly Detection and Root Cause Analysis in HFC Networks : A Clustering ApproachForsare Källman, Povel January 2021 (has links)
Following the significant transition from the traditional production industry to an informationbased economy, the telecommunications industry was faced with an explosion of innovation, resulting in a continuous change in user behaviour. The industry has made efforts to adapt to a more datadriven future, which has given rise to larger and more complex systems. Therefore, troubleshooting systems such as anomaly detection and root cause analysis are essential features for maintaining service quality and facilitating daily operations. This study aims to explore the possibilities, benefits, and drawbacks of implementing cluster analysis for anomaly detection in hybrid fibercoaxial networks. Based on the literature review on unsupervised anomaly detection and an assumption regarding the anomalous behaviour in hybrid fibercoaxial network data, the kmeans, SelfOrganizing Map, and Gaussian Mixture Model were implemented both with and without Principal Component Analysis. Analysis of the results demonstrated an increase in performance for all models when the Principal Component Analysis was applied, with kmeans outperforming both SelfOrganizing Map and Gaussian Mixture Model. On this basis, it is recommended to apply Principal Component Analysis for clusteringbased anomaly detection. Further research is necessary to identify whether cluster analysis is the most appropriate unsupervised anomaly detection approach. / Följt av övergången från den traditionella tillverkningsindustrin till en informationsbaserad ekonomi stod telekommunikationsbranschen inför en explosion av innovation. Detta skifte resulterade i en kontinuerlig förändring av användarbeteende och branschen tvingades genomgå stora ansträngningar för att lyckas anpassa sig till den mer datadrivna framtiden. Större och mer komplexa system utvecklades och således blev felsökningsfunktioner såsom anomalidetektering och rotfelsanalys centrala för att upprätthålla servicekvalitet samt underlätta för den dagliga driftverksamheten. Syftet med studien är att utforska de möjligheterna, för- samt nackdelar med att använda klusteranalys för anomalidetektering inom HFC- nätverk. Baserat på litteraturstudien för oövervakad anomalidetektering samt antaganden för anomalibeteenden inom HFC- data valdes algritmerna k- means, Self- Organizing Map och Gaussian Mixture Model att implementeras, både med och utan Principal Component Analysis. Analys av resultaten påvisade en uppenbar ökning av prestanda för samtliga modeller vid användning av PCA. Vidare överträffade k- means, både Self- Organizing Maps och Gaussian Mixture Model. Utifrån resultatanalysen rekommenderas det således att PCA bör tillämpas vid klusterings- baserad anomalidetektering. Vidare är ytterligare forskning nödvändig för att avgöra huruvida klusteranalys är den mest lämpliga metoden för oövervakad anomalidetektering.
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Atomic Layer Deposition and High Sensitivity-Low Energy Ion Scattering for the Determination of the Surface Silanol Density on Glass and Unsupervised Exploratory Data Analysis with Summary Statistics and Other MethodsGholian Avval, Tahereh 18 July 2022 (has links)
With the increasing importance of hand-held devices with touch displays, the need for flat panel displays (FPDs) will likely increase in the future. Glass is the most important substrate for FPD manufacturing, where both its bulk and surface properties are critical for its performance. Many properties of the glass used in FPDs are controlled by its surface chemistry. Surface hydroxyls are the most important functional groups on a glass surface, which control processes that occurs on oxide surfaces, including wetting, adhesion, electrostatic charging and discharge, and the rate of contamination. In this dissertation, I present a new approach for determining surface silanol densities on planar surfaces. This methodology consists of tagging surface silanols using atomic layer deposition (ALD) followed by low energy ion scattering (LEIS) analysis of the tags. The LEIS signal is limited to the outermost atomic layer, i.e., LEIS is an extremely surface sensitive technique. Quantification in LEIS is straightforward in the presence of suitable reference materials. An essential part of any LEIS measurement is the preparation and characterization of the sample and appropriate reference materials that best represent the samples. My tag-and-count method was applied to chemically and thermally treated fused silica. In this work, I determined the silanol density of a fully hydroxylated fused silica surface to be 4.67 OH/nm2. This value agrees with the literature value for high surface area silica powder. My methodology should be important in future glass studies. Surface Science Spectra (SSS) is an important, peer-reviewed database of spectra from surfaces. Recently, SSS has been expanding to accept spectra from new surface techniques. I created the first SSS submission form for LEIS spectra (see appendix 5), and used it to create the first SSS LEIS paper (on CaF2 and Au reference materials, see chapter 3). I also show LEIS reference spectra for ZnO, and copper in the appendix 1. The rest of my dissertation focuses on my chemometrics/informatics and data analysis work. For example, I showed the performance and capabilities of a series of summary statistics as new tools for unsupervised exploratory data analysis (EDA) (see chapter 4). Unsupervised EDA is often the first step in understanding complex data sets because it can group, and even classify, samples according to their spectral similarities and differences. Pattern recognition entropy (PRE) and other summary statistics are direct methods for analyzing data - they are not factor-based approaches like principal component analysis (PCA) or multivariate curve resolution (MCR). I show that, in general, PRE outperforms the other summary statistics, especially in image analysis, although I recommend a suite of summary statistics be used in exploring complex data sets. In addition, I introduce the concept of divided spectrum-PRE (DS-PRE) as a new EDA method and use it to analyze multiple data sets. DS-PRE increases the discrimination power of PRE. I have also prepared a guide that discusses the vital aspects and considerations for chemometrics/informatics analyses of XPS data along with specific EDA tools that can be used to probe XPS data sets, including PRE, PCA, MCR, and cluster analysis (see chapter 5). I emphasize the importance of an initial evaluation/plotting of raw data, data preprocessing, returning to the original data after a chemometrics/informatics analysis, and determining the number of abstract factors to keep in an analysis, including reconstructing the data using PCA. In my thesis, I also show the analysis of commercial automotive lubricant oils (ALOs) with various chemometrics techniques (see chapter 6). Using these methods, the ALO samples were readily differentiated according to their American Petroleum Institute (API) classification and base oil types: mineral, semi-synthetic, and synthetic.
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Cerebral venous outflow resistance and interpretation of cervical plethysmography data with respect to the diagnosis of chronic cerebrospinal venous insufficiencyBeggs, Clive B., Shepherd, Simon J., Zamboni, P. January 2014 (has links)
No / PURPOSE: To investigate cerebrospinal fluid (CSF) dynamics in the aqueduct of Sylvius (AoS) in chronic cerebrospinal venous insufficiency (CCSVI)-positive and -negative healthy individuals using cine phase contrast imaging. MATERIALS AND METHODS: Fifty-one healthy individuals (32 CCSVI-negative and 19 age-matched CCSVI-positive subjects) were examined using Doppler sonography (DS). Diagnosis of CCSVI was established if subjects fulfilled >/=2 venous hemodynamic criteria on DS. CSF flow and velocity measures were quantified using a semiautomated method and compared with clinical and routine 3T MRI outcomes. RESULTS: CCSVI was associated with increased CSF pulsatility in the AoS. Net positive CSF flow was 32% greater in the CCSVI-positive group compared with the CCSVI-negative group (P = 0.008). This was accompanied by a 28% increase in the mean aqueductal characteristic signal (ie, the AoS cross-sectional area over the cardiac cycle) in the CCSVI-positive group compared with the CCSVI-negative group (P = 0.021). CONCLUSION: CSF dynamics are altered in CCSVI-positive healthy individuals, as demonstrated by increased pulsatility. This is accompanied by enlargement of the AoS, suggesting that structural changes may be occurring in the brain parenchyma of CCSVI-positive healthy individuals.
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Entstehung von Clustern unter Berücksichtigung der Effekte regionalisierter Innovationspolitik / Emerging Clusters with Particular Emphasis on the Effects of Regionalised Innovation PolicyAnz, Michael 27 May 2010 (has links) (PDF)
Während man sich bislang auf die Gründe für die Entwicklung existierender Cluster konzentrierte, steigt das Interesse an den Prozessen, welche deren Entstehung bewirken. Diese unterscheiden sich jedoch von jenen zusammenhängen, welche ein reifes und dynamisches Cluster kennzeichnen (Bresnahan, Gambardella 2004, S. 842; Henn 2006b). Einige Beispiele haben gezeigt, dass Politik durchaus eine Rolle in der Entwicklung von Clustern spielen kann (z. B. Feldmann et al. 2005, S. 131; Dohse 2000b). Es herrscht jedoch Konsens, dass eine direkte Steuerung und Initiierung von Clustern „wishful thinking“ bleiben muss (Enright 2003, S. 104; Rosenfeld et al. 2006). Indes zeigen sich unternehmerische Akteure im Umfeld von Forschungseinrichtungen bevorteilt, wissenschaftliche Erkenntnisse in neuen Technologiefeldern zu verwerten. In jüngerer Zeit werden deshalb regionalisierte Innovationspolitiken implementiert, welche diesen Prozess unterstützen sollen. Über die Wirkungsweise und die Effekte einer solchen räumlich fokussierten Politik herrscht bislang jedoch noch Unklarheit (Raines 2002b, S. 8; Fromhold-Eisebith, Eisebith 2005, S. 1251; Kiese 03.10.2007). Diese Fragestellungen aufgreifend werden in der vorliegenden Arbeit anhand der Fallbeispiele Dresden und Leipzig die Prozesse der Clusterentstehung im Technologiebereich der Biotechnologie vor dem Hintergrund der Post-Transformationsphase Ostdeutschlands analysiert. Zudem wird die umfangreiche, regionalisierte Innovationspolitik des Freistaates Sachsen hinsichtlich ihres Beitrages bei der Clusterentstehung untersucht. Mit diesem Untersuchungsansatz wird ein Beitrag zur noch jungen Diskussion der Clusterentstehung geleistet sowie Einblick in die Wirkungsmöglichkeiten regionalisierter Innovationspolitik gegeben. Auf der Grundlage der theoretischen Diskussion zu Clustern und regionalisierter Innovationspolitik wird ein Untersuchungsmodell abgeleitet, welches sich an den multidimensionalen Analyserahmen Bathelts anlehnt (Bathelt 2002) und um die von Henn diskutierten Entstehungsdimensionen Ansiedlung, Lernen und Gründung erweitert (Henn 2006b). Schwerpunkt der empirischen Analyse ist ein Mix aus leitfadengestützten Interviews und quantitativer Analyse sozialer Netzwerke. Bei der Analyse zeigt sich, dass „klassische“ Erklärungsmuster zur Clusterentstehung teilweise auf Prozesse hinweisen, die sich so nicht feststellen lassen. Als wesentlich erweisen sich vor allem Gründungs- und Ansiedlungsprozesse. Zu ihrer Erklärung kann jedoch kaum auf einfache Standortfaktoren zurückgegriffen werden, vielmehr müssen Forschernetzwerke zur Erklärung herangezogen werden. Bei der Analyse der Effekte der regionalisierten Innovationspolitik zeigt sich, dass die Wirksamkeit maßgeblich von der Gestaltbarkeit und Anpassung der Politik an sich ändernde Governancebedingungen abhängt. Dies betrifft sowohl das regionale technologische Umfeld als auch die Region im Allgemeinen. Daneben 243 ist die Unterstützung der Erzeugung materieller Vorraussetzungen u. a. für den Erfolg von Ausgründungen, Ansiedlungen sowie von unternehmerischen Lernprozessen relevant. Diese müssen jedoch in flexible Strukturen eingebettet werden, die es zu entwickeln gilt. Dafür werden am Ende der Arbeit Handlungsempfehlungen aufgezeigt. / While focussing on the development of existing clusters there is a growing interest in those processes which lead to the emergence of clusters. Those differ from these ones which are typical for a ripe cluster (Bresnahan, Gambardella 2004, p. 842; Henn 2006).
Several cases show that policy has an impact on the development of a cluster (z.B. Feldmann et al. 2005, p. 131; Dohse 2000). Though there is a consensus that wishing to stear or initiate a cluster is „wishful thinking“ (Enright 2003, p. 104; Rosenfeld et al. 2006).
Entrepreneurs in the surrounding of research institutions are in an advantage commercialising knowledge in new technology fields. This is why regionalised innovation policies are implemented recently, which aim to support this process. The effects and mechanisms of such a spatially focused policy have yet to be clarified (Raines 2002, p. 8; Fromhold-Eisebith, Eisebith 2005, p. 1251; Kiese 3. Oktober 2007).
Taking up this question in this thesis the process of emerging clusers is analysed in the field of biotechnology for the cases of Dresden and Leipzig under conditions of post-transformation in Eastern Germany. Further the influence of the complex, regionalised innovation policy of the Free State of Saxony is studied concerning the emgergence of clusters. The aim is to contribute to the discussion on emerging clusters as well as to point out the impact regionalised innovation policy can have.
A research model is deduced from theoretical discussion on clusters and regionalised innovation policy. It refers to the multidimensional model of Bathelt (Bathelt 2002) and the relevant dimensions for the emergence process, settlements, learning and founding (Henn 2006). To implement this model among others a mix of semi-structured interviews and social network analysis is used.
The analysis shows that “classical” explanations for emerging clusters can not be verified. Founding and settling processes of enterprises seem to be most important. A simple location factor based explanation does not give satisfying answers. Explanations have to take researcher-entrepreneurial networks into account.
The analysis shows that the impact of regionalised innovation policy depends on a continual development and evolution of policy in accordance with a changing governance structure in the regional technological surrounding as in the overall region. Monetary support proves to be favourably for spin offs and settlements as well as for entrepreneurial learning processes. Those have to be embedded in flexible and developing governance structures.
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