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Heimatfabrik Lokalmuseum bietet einen neuen Blick auf lokal verankerte Museen. Anhand von ausgewählten Fallbeispielen, die durch eine quantitative Untersuchung von etwa 370 Museen im Großherzogtum Luxemburg und in der belgischen Region Wallonien ergänzt werden, analysiert die Autorin, welche Identifikationsangebote bäuerliche Alltagsmuseen, Stadtmuseen, Industriemuseen, Kriegsmuseen und Auswanderermuseen ihren Besuchern bieten. Wen schließen die Museumsverantwortlichen durch ihre Erzählweisen ein und wen grenzen sie aus? Wie gehen sie mit sprachlichen, konfessionellen, kulturellen, sexuellen und soziale Minderheiten um?
Das Buch beginnt mit der Klärung der Frage, wie sich das Heimatverständnis in Luxemburg in Luxemburg und im angrenzenden Wallonien im Spannungsfeld zwischen dem klassischen Heimatbegriff des deutschsprachigen Raums und der Inwertsetzung der Landschaft durch die französischen Humangeographen seit der Mitte des 19. Jahrhunderts entwickelt hat. Aus diesem unterschiedlichen Zugang zu dem was als enger Kreis des gesellschaftlichen Zusammenhalts empfunden wird, ergeben sich verschiedene Typen von lokalhistorischen Museen, die die Autorin in historischer Perspektive vorstellt.
Indem sie Dinge des Alltags durch die Aufnahme in ihre Sammlungen zu symbolischen Zeichenträgern einer Gesellschaft erheben sind Museen privilegierte Orte für die Schaffung von Heritage. Mit den Ausstellungen erzeugen die Museumsträger eine subjektiv empfundene gesellschaftliche Einheit, die von manchen Besucher als Heimat angenommen oder abgelehnt wird, andere wiederum gleichgültig lässt. Vor diesem Hintergrund dieser Feststellung beschäftigt sich die Autorin mit dem, was unter lokalem heritage zu verstehen ist und welcher gestalterischen Mittel sich die Verantwortlichen von lokalhistorischen Museen bedienen um ihre Vorstellung von Heimat zu konstruieren. Anhand der Themenbereiche bäuerlicher Alltag, Natur, Ein- und Auswanderung, Krieg sowie Industrie geht das Buch der Frage nach, wie interne und externe Museumsstakeholder das vom Museum vermittelte Heimatbild und damit verbunden auch die nationale Geschichtskultur mitbestimmen.
Das Buch möchte dazu beitragen, den Blick einer interessierten Öffentlichkeit für lokales Kulturerbe zu schulen sowie Historiker auf das Potenzial von lokalhistorischen Museen hinzuweisen. In diesem Sinne ist die Untersuchung auch ein Plädoyer für die Anerkennung der Besonderheit von außerakademischer historischer Aufarbeitung und für die Verstärkung der Zusammenarbeit zwischen universitärer und außeruniversitärer Forschung.
A satellite-based climatology of wind-induced surface temperature anomalies for the Antarctic
(2019)
It is well-known that katabatic winds can be detected as warm signatures in the surface temperature over the slopes of the Antarctic ice sheets. For appropriate synoptic forcing and/or topographic channeling, katabatic surges occur, which result in warm signatures also over adjacent ice shelves. Moderate Resolution Imaging Spectroradiometer (MODIS) ice surface temperature (IST) data are used to detect warm signatures over the Antarctic for the winter periods 2002–2017. In addition, high-resolution (5 km) regional climate model data is used for the years of 2002 to 2016. We present a case study and a climatology of wind-induced IST anomalies for the Ross Ice Shelf and the eastern Weddell Sea. The IST anomaly distributions show maxima around 10–15K for the slopes, but values of more than 25K are also found. Katabatic surges represent a strong climatological signal with a mean warm anomaly of more than 5K on more than 120 days per winter for the Byrd Glacier and the Nimrod Glacier on the Ross Ice Shelf. The mean anomaly for the Brunt Ice Shelf is weaker, and exceeds 5K on about 70 days per winter. Model simulations of the IST are compared to the MODIS IST, and show a very good agreement. The model data show that the near-surface stability is a better measure for the response to the wind than the IST itself.
In this thesis, we consider the solution of high-dimensional optimization problems with an underlying low-rank tensor structure. Due to the exponentially increasing computational complexity in the number of dimensions—the so-called curse of dimensionality—they present a considerable computational challenge and become infeasible even for moderate problem sizes.
Multilinear algebra and tensor numerical methods have a wide range of applications in the fields of data science and scientific computing. Due to the typically large problem sizes in practical settings, efficient methods, which exploit low-rank structures, are essential. In this thesis, we consider an application each in both of these fields.
Tensor completion, or imputation of unknown values in partially known multiway data is an important problem, which appears in statistics, mathematical imaging science and data science. Under the assumption of redundancy in the underlying data, this is a well-defined problem and methods of mathematical optimization can be applied to it.
Due to the fact that tensors of fixed rank form a Riemannian submanifold of the ambient high-dimensional tensor space, Riemannian optimization is a natural framework for these problems, which is both mathematically rigorous and computationally efficient.
We present a novel Riemannian trust-region scheme, which compares favourably with the state of the art on selected application cases and outperforms known methods on some test problems.
Optimization problems governed by partial differential equations form an area of scientific computing which has applications in a variety of areas, ranging from physics to financial mathematics. Due to the inherent high dimensionality of optimization problems arising from discretized differential equations, these problems present computational challenges, especially in the case of three or more dimensions. An even more challenging class of optimization problems has operators of integral instead of differential type in the constraint. These operators are nonlocal, and therefore lead to large, dense discrete systems of equations. We present a novel solution method, based on separation of spatial dimensions and provably low-rank approximation of the nonlocal operator. Our approach allows the solution of multidimensional problems with a complexity which is only slightly larger than linear in the univariate grid size; this improves the state of the art for a particular test problem problem by at least two orders of magnitude.
With two-thirds to three-quarters of all companies, family firms are the most common firm type worldwide and employ around 60 percent of all employees, making them of considerable importance for almost all economies. Despite this high practical relevance, academic research took notice of family firms as intriguing research subjects comparatively late. However, the field of family business research has grown eminently over the past two decades and has established itself as a mature research field with a broad thematic scope. In addition to questions relating to corporate governance, family firm succession and the consideration of entrepreneurial families themselves, researchers mainly focused on the impact of family involvement in firms on their financial performance and firm strategy. This dissertation examines the financial performance and capital structure of family firms in various meta-analytical studies. Meta-analysis is a suitable method for summarizing existing empirical findings of a research field as well as identifying relevant moderators of a relationship of interest.
First, the dissertation examines the question whether family firms show better financial performance than non-family firms. A replication and extension of the study by O’Boyle et al. (2012) based on 1,095 primary studies reveals a slightly better performance of family firms compared to non-family firms. Investigating the moderating impact of methodological choices in primary studies, the results show that outperformance holds mainly for large and publicly listed firms and with regard to accounting-based performance measures. Concerning country culture, family firms show better performance in individualistic countries and countries with a low power distance.
Furthermore, this dissertation investigates the sensitivity of family firm performance with regard to business cycle fluctuations. Family firms show a pro-cyclical performance pattern, i.e. their relative financial performance compared to non-family firms is better in economically good times. This effect is particularly pronounced in Anglo-American countries and emerging markets.
In the next step, a meta-analytic structural equation model (MASEM) is used to examine the market valuation of public family firms. In this model, profitability and firm strategic choices are used as mediators. On the one hand, family firm status itself does not have an impact on firms‘ market value. On the other hand, this study finds a positive indirect effect via higher profitability levels and a negative indirect effect via lower R&D intensity. A split consideration of family ownership and management shows that these two effects are mainly driven by family ownership, while family management results in less diversification and internationalization.
Finally, the dissertation examines the capital structure of public family firms. Univariate meta-analyses indicate on average lower leverage ratios in family firms compared to non-family firms. However, there is significant heterogeneity in mean effect sizes across the 45 countries included in the study. The results of a meta-regression reveal that family firms use leverage strategically to secure their controlling position in the firm. While strong creditor protection leads to lower leverage ratios in family firms, strong shareholder protection has the opposite effect.
For grape canopy pixels captured by an unmanned aerial vehicle (UAV) tilt-mounted RedEdge-M multispectral sensor in a sloped vineyard, an in situ Walthall model can be established with purely image-based methods. This was derived from RedEdge-M directional reflectance and a vineyard 3D surface model generated from the same imagery. The model was used to correct the angular effects in the reflectance images to form normalized difference vegetation index (NDVI)orthomosaics of different view angles. The results showed that the effect could be corrected to a certain scope, but not completely. There are three drawbacks that might restrict a successful angular model construction and correction: (1) the observable micro shadow variation on the canopy enabled by the high resolution; (2) the complexity of vine canopies that causes an inconsistency between reflectance and canopy geometry, including effects such as micro shadows and near-infrared (NIR) additive effects; and (3) the resolution limit of a 3D model to represent the accurate real-world optical geometry. The conclusion is that grape canopies might be too inhomogeneous for the tested method to perform the angular correction in high quality.
In order to discuss potential sustainability issues of expanding silage maize cultivation in Rhineland-Palatinate, spatially explicit monitoring is necessary. Publicly available statistical records are often not a sufficient basis for extensive research, especially on soil health, where risk factors like erosion and compaction depend on variables that are specific to every site, and hard to generalize for larger administrative aggregates. The focus of this study is to apply established classification algorithms to estimate maize abundance for each independent pixel, while at the same time accounting for their spatial relationship. Therefore, two ways to incorporate spatial autocorrelation of neighboring pixels are combined with three different classification models. The performance of each of these modeling approaches is analyzed and discussed. Finally, one prediction approach is applied to the imagery, and the overall predicted acreage is compared to publicly available data. We were able to show that Support Vector Machine (SVM) classification and Random Forests (RF) were able to distinguish maize pixels reliably, with kappa values well above 0.9 in most cases. The Generalized Linear Model (GLM) performed substantially worse. Furthermore, Regression Kriging (RK) as an approach to integrate spatial autocorrelation into the prediction model is not suitable in use cases with millions of sparsely clustered training pixels. Gaussian Blur is able to improve predictions slightly in these cases, but it is possible that this is only because it smoothes out impurities of the reference data. The overall prediction with RF classification combined with Gaussian Blur performed well, with out of bag error rates of 0.5% in 2009 and 1.3% in 2016. Despite the low error rates, there is a discrepancy between the predicted acreage and the official records, which is 20% in 2009 and 27% in 2016.
Abstract: Thermal infrared (TIR) multi-/hyperspectral and sun-induced fluorescence (SIF) approaches together with classic solar-reflective (visible, near-, and shortwave infrared reflectance (VNIR)/SWIR) hyperspectral remote sensing form the latest state-of-the-art techniques for the detection of crop water stress. Each of these three domains requires dedicated sensor technology currently in place for ground and airborne applications and either have satellite concepts under development (e.g., HySPIRI/SBG (Surface Biology and Geology), Sentinel-8, HiTeSEM in the TIR) or are subject to satellite missions recently launched or scheduled within the next years (i.e., EnMAP and PRISMA (PRecursore IperSpettrale della Missione Applicativa, launched on March 2019) in the VNIR/SWIR, Fluorescence Explorer (FLEX) in the SIF). Identification of plant water stress or drought is of utmost importance to guarantee global water and food supply. Therefore, knowledge of crop water status over large farmland areas bears large potential for optimizing agricultural water use. As plant responses to water stress are numerous and complex, their physiological consequences affect the electromagnetic signal in different spectral domains. This review paper summarizes the importance of water stress-related applications and the plant responses to water stress, followed by a concise review of water-stress detection through remote sensing, focusing on TIR without neglecting the comparison to other spectral domains (i.e., VNIR/SWIR and SIF) and multi-sensor approaches. Current and planned sensors at ground, airborne, and satellite level for the TIR as well as a selection of commonly used indices and approaches for water-stress detection using the main multi-/hyperspectral remote sensing imaging techniques are reviewed. Several important challenges are discussed that occur when using spectral emissivity, temperature-based indices, and physically-based approaches for water-stress detection in the TIR spectral domain. Furthermore, challenges with data processing and the perspectives for future satellite missions in the TIR are critically examined. In conclusion, information from multi-/hyperspectral TIR together with those from VNIR/SWIR and SIF sensors within a multi-sensor approach can provide profound insights to actual plant (water) status and the rationale of physiological and biochemical changes. Synergistic sensor use will open new avenues for scientists to study plant functioning and the response to environmental stress in a wide range of ecosystems.
Because EU water quality policy can result in infrastructure creation or adaptation at the local level across member states, compliance cases are worth examining critically from a sustainable spatial planning perspective. In this study, the 2000 EU Water Framework Directive’s (WFD) reach to local implementation efforts in average towns and cities is shown through the case study of nonconforming household wastewater infrastructure in the German state of Rhineland Palatinate. Seeing wastewater as a socio-technical infrastructure, we ask how the WFD implementation can be understood in the context of local infrastructure development, sustainability, and spatial planning concepts. In particular, this study examines what compliance meant for the centralization or decentralization of local wastewater infrastructure systems—and the sustainability implications for cities
from those choices.
Bewertungsprozesse in der Schule als Möglichkeit nutzen, um Schüler*innen bei der realistischen Einschätzung und Weiterentwicklung ihrer Lernprozesse und ihres Lernverhaltens zu unterstützen: Die partizipative Leistungsbewertung bietet verschiedene praxisnahe Ansätze zur Förderung von Lernmotivation, Selbstreflexion und demokratischem Verständnis.
Considérer les processus d’évaluation à l’école comme une possibilité pour soutenir les élèves dans l’évaluation réaliste et le développement de leurs processus et leur comportement d’apprentissage : l’évaluation participative des performances offre différentes possibilités pratiques pour favoriser la motivation d’apprendre, l’autoréflexion et la compréhension démocratique.
Entrepreneurial ventures are associated with economic growth, job creation, and innovation. Most entrepreneurial ventures need external funding to succeed. However, they often find it difficult to access traditional forms of financing, such as bank loans. To overcome this hurdle and to provide entrepreneurial ventures with badly-needed external capital, many types of entrepreneurial finance have emerged over the past decades and continue to emerge today. Inspired by these dynamics, this postdoctoral thesis contains five empirical studies that address novel questions regarding established (e.g., venture capital, business angels) and new types of entrepreneurial finance (i.e., initial coin offerings).
Rückkehrprozesse aus Genderperspektive: remigrierte (Spät-)Aussiedler-Ehepaare in Westsibirien
(2019)
Die Studie untersucht die Rückkehrprozesse von (Spät-)Aussiedler-Ehepaaren aus Deutschland nach Westsibirien. Ein besonderes Augenmerk wird auf die Sichtweisen der Frauen und Männer hinsichtlich ihrer gemachten Erfahrung der Remigration gelegt. Darüber hinaus analysiert die Studie einerseits die Gemeinsamkeiten und Unterschiede beider Geschlechter im Hinblick auf die Rückkehrmotive, die Zufriedenheit mit der Wiederanpassung in Russland sowie die Einstellung hinsichtlich einer erneuten Migration nach Deutschland. Andererseits fokussiert die Arbeit auf die Geschlechterverhältnisse unter den Ehegatten im Prozess der Entscheidungsfindung zur Remigration. Die Studie folgt einem qualitativen methodischen Ansatz und verbindet verschiedene Forschungsrichtungen, genauer (Re)Migrations-, Familien-, (Spät-)AussiedlerInnen- und Geschlechterforschung.
Background: Increasing exposure to engineered inorganic nanoparticles takes actually place in both terrestric and aquatic ecosystems worldwide. Although we already know harmful effects of AgNP on the soil bacterial community, information about the impact of the factors functionalization, concentration, exposure time, and soil texture on the AgNP effect expression are still rare. Hence, in this study, three soils of different grain size were exposed for up to 90 days to bare and functionalized AgNP in concentrations ranging from 0.01 to 1.00 mg/kg soil dry weight. Effects on soil microbial community were quantified by various biological parameters, including 16S rRNA gene, photometric, and fluorescence analyses.
Results: Multivariate data analysis revealed significant effects of AgNP exposure for all factors and factor combinations investigated. Analysis of individual factors (silver species, concentration, exposure time, soil texture) in the unifactorial ANOVA explained the largest part of the variance compared to the error variance. In depth analysis of factor combinations revealed even better explanation of variance. For the biological parameters assessed in this study, the matching of soil texture and silver species, and the matching of soil texture and exposure time were the two most relevant factor combinations. The factor AgNP concentration contributed to a lower extent to the effect expression compared to silver species, exposure time and physico–chemical composition of soil.
Conclusions: The factors functionalization, concentration, exposure time, and soil texture significantly impacted the effect expression of AgNP on the soil microbial community. Especially long-term exposure scenarios are strongly needed for the reliable environmental impact assessment of AgNP exposure in various soil types.
Auch in Sekundarschulen bietet der Klassenrat den Schüler*innen Raum, um ihre Anliegen zu artikulieren und in einem demokratischen Prozess Verbesserungspotenziale für die Klasse und Schule auszuloten. Die vorliegenden Materialien helfen dabei, die Sitzungen eigenverantwortlich vorzubereiten und durchzuführen.
Dans les écoles secondaires, le conseil de coopération offre aussi aux élèves un espace pour exprimer leurs demandes et explorer, dans un processus démocratique, les potentiels d’amélioration pour la classe et l’école. Les supports ci-dessous vous aideront à préparer et à mener les réunions de manière autonome.
Faut-il interdire les emballages en plastique ? Quels arguments s’opposent au droit de vote à partir de 14 ans ? Quelles sont les conséquences du Brexit sur l’Europe ? – Ce type de questions a toute sa place en conseil de coopération, car leur discussion offre des possibilités d’apprentissage des processus démocratiques.
Sollten Plastikverpackungen verboten werden? Was spricht gegen eine Wahlberechtigung ab 14 Jahren? Wie sollte die EU mit möglichen Auswirkungen des Brexits umgehen? – Auch solche Fragen haben im Klassenrat ihre Berechtigung, denn ihre Diskussion bietet besondere Chancen für demokratische Lernprozesse.
Der Photograph Willi Huttig
(2019)
Mit diesem Territorial Science Echo werden wesentliche Facetten von Governance beleuchtet, die sich für die künftige Entwicklung der Großregion als relevant erweisen können. Es wird insbesondere dargestellt, wie thematische Kooperationen und Konflikte zur der Etablierung von Governance Strukturen beitragen. Das Paper setzt sich mit den Themen Governance im Allgemeinen, Partizipation und Wohnen sowie den Außenbeziehungen der Großregion auseinander, formuliert wesentliche Herausforderungen und Empfehlungen, und ist somit als Anregung im fachlichen Diskurs um die weitere Gestaltung des Raumentwicklungskonzeptes der Großregion zu verstehen.
This doctoral thesis includes five studies that deal with the topics work, well-being, and family formation, as well as their interaction. The studies aim to find answers to the following questions: Do workers’ personality traits determine whether they sort into jobs with performance appraisals? Does job insecurity result in lower quality and quantity of sleep? Do public smoking bans affect subjective well-being by changing individuals’ use of leisure time? Can risk preferences help to explain non-traditional family forms? And finally, are differences in out-of-partnership birth rates between East and West Germany driven by cultural characteristics that have evolved in the two separate politico-economic systems? To answer these questions, the following chapters use basic economic subjects such as working conditions, income, and time use, but also employ a range of sociological and psychological concepts such as personality traits and satisfaction measures. Furthermore, all five studies use data from the German Socio-Economic Panel (SOEP), a representative longitudinal panel of private households in Germany, and apply state-of-the-art microeconometric methods. The findings of this doctoral thesis are important for individuals, employers, and policymakers. Workers and employers benefit from knowing the determinants of occupational sorting, as vacancies can be filled more accurately. Moreover, knowing which job-related problems lead to lower well-being and potentially higher sickness absence likely increases efficiency in the workplace. The research on smoking bans and family formation in chapters 4, 5, and 6 is particularly interesting for policymakers. The results on the effects of smoking bans on subjective well-being presented in chapter 4 suggest that the impacts of tobacco control policies could be weighed more carefully. Additionally, understanding why women are willing to take the risks associated with single motherhood can help to improve policies targeting single mothers.