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Zum dreißigjährigen Bestehen des Kommunalwissenschaftlichen Instituts an der Universität Potsdam vereint dieser Jubiläumsband kurze Aufsätze von ehemaligen und aktuellen Vorstandsmitgliedern, von Ehrenmitgliedern des Vorstands, langjährigen wissenschaftlichen Mitarbeitern des Instituts und aktuellen wissenschaftlichen Kooperationspartnern. Die insgesamt zwölf Beiträge befassen sich mit den Kommunalwissenschaften und der Geschichte des Kommunalwissenschaftlichen Instituts, mit aktuellen kommunalwissenschaftlichen Fragestellungen und wissenschaftlichen Kooperationen des KWI. Der vom KWI-Vorstand herausgegebene Band soll einen breiten Blick auf 30 Jahre Kommunalwissenschaften in Brandenburg und an der Universität Potsdam werfen und einen Ausblick auf zukünftige kommunalwissenschaftliche Forschung geben.
Examining the dissemination of evidence on social media, we analyzed the discourse around eight visible scientists in the context of COVID-19. Using manual (N = 1,406) and automated coding (N = 42,640) on an account-based tracked Twitter/X dataset capturing scientists’ activities and eliciting reactions over six 2-week periods, we found that visible scientists’ tweets included more scientific evidence. However, public reactions contained more anecdotal evidence. Findings indicate that evidence can be a message characteristic leading to greater tweet dissemination. Implications for scientists, including explicitly incorporating scientific evidence in their communication and examining evidence in science communication research, are discussed.
Deep learning has seen widespread application in many domains, mainly for its ability to learn data representations from raw input data. Nevertheless, its success has so far been coupled with the availability of large annotated (labelled) datasets. This is a requirement that is difficult to fulfil in several domains, such as in medical imaging. Annotation costs form a barrier in extending deep learning to clinically-relevant use cases. The labels associated with medical images are scarce, since the generation of expert annotations of multimodal patient data at scale is non-trivial, expensive, and time-consuming. This substantiates the need for algorithms that learn from the increasing amounts of unlabeled data. Self-supervised representation learning algorithms offer a pertinent solution, as they allow solving real-world (downstream) deep learning tasks with fewer annotations. Self-supervised approaches leverage unlabeled samples to acquire generic features about different concepts, enabling annotation-efficient downstream task solving subsequently.
Nevertheless, medical images present multiple unique and inherent challenges for existing self-supervised learning approaches, which we seek to address in this thesis: (i) medical images are multimodal, and their multiple modalities are heterogeneous in nature and imbalanced in quantities, e.g. MRI and CT; (ii) medical scans are multi-dimensional, often in 3D instead of 2D; (iii) disease patterns in medical scans are numerous and their incidence exhibits a long-tail distribution, so it is oftentimes essential to fuse knowledge from different data modalities, e.g. genomics or clinical data, to capture disease traits more comprehensively; (iv) Medical scans usually exhibit more uniform color density distributions, e.g. in dental X-Rays, than natural images. Our proposed self-supervised methods meet these challenges, besides significantly reducing the amounts of required annotations.
We evaluate our self-supervised methods on a wide array of medical imaging applications and tasks. Our experimental results demonstrate the obtained gains in both annotation-efficiency and performance; our proposed methods outperform many approaches from related literature. Additionally, in case of fusion with genetic modalities, our methods also allow for cross-modal interpretability. In this thesis, not only we show that self-supervised learning is capable of mitigating manual annotation costs, but also our proposed solutions demonstrate how to better utilize it in the medical imaging domain. Progress in self-supervised learning has the potential to extend deep learning algorithms application to clinical scenarios.
§ 70 Hohe See
(2024)
Im Kontext der zunehmenden Relevanz des Umgangs mit Digitalität im schulischen Unterricht und der daraus resultierenden Popularität von Gaming und Gamification als Lehrmethoden ist das Ziel dieser Arbeit, Game Design als konstruktivistische Herangehensweise an Computerspiele zu untersuchen. Genauer geht es darum, diese Methode hinsichtlich der Tauglichkeit für den Kunstunterricht zu analysieren. Dazu wird darauf eingegangen, inwiefern Game Design als Instruktionsmethode generell Lernen fördert bzw. zur Ausbildung einer Digital Literacy geeignet ist. Der Schwerpunkt liegt darin, Game Design im Hinblick auf die zentralen Kompetenz- und Lerndimensionen des Kunstunterrichts zu beleuchten. Genauer sind damit die künstlerische Produktion und die ästhetische Rezeption als die beiden maßgeblichen künstlerisch-ästhetischen Handlungskompetenzen gemeint sowie die ästhetische Erfahrung als besonderes Lernerlebnis, welches im kunstpädagogischen Diskurs neben den beschriebenen Kompetenzen als höchstes Ziel der Lehre gilt. Ebendiese drei Dimensionen funktionieren hierbei als Analyseebenen der untersuchten Methode. Game Design stellt sich dabei als weitestgehend förderlich für alle drei benannten Bereiche heraus, wobei es in Bezug auf die sinnliche Wahrnehmung im Prozess der ästhetischen Rezeption nur eine ergänzende Funktion annimmt. Es werden nicht alle Bereiche der Gestaltungsfelder der künstlerischen Produktion angesprochen. Ein experimentell-offenes künstlerisches Arbeiten wird ebenso nicht zwangsläufig ermöglicht. Jedoch werden alle anderen Bestandteile dieser Kompetenzdimensionen angesprochen und insbesondere die ästhetische Erfahrung vollumfänglich gefördert. Die digitale Spielentwicklung lässt sich somit aus kunstpädagogischer Perspektive für den Einsatz im Kunstunterricht legitimieren. Mit Ausblick auf STEAM Education und einen projektorientierten Unterricht ist sie sogar zu empfehlen.
The “HPI Future SOC Lab” is a cooperation of the Hasso Plattner Institute (HPI) and industry partners. Its mission is to enable and promote exchange and interaction between the research community and the industry partners.
The HPI Future SOC Lab provides researchers with free of charge access to a complete infrastructure of state of the art hard and software. This infrastructure includes components, which might be too expensive for an ordinary research environment, such as servers with up to 64 cores and 2 TB main memory. The offerings address researchers particularly from but not limited to the areas of computer science and business information systems. Main areas of research include cloud computing, parallelization, and In-Memory technologies.
This technical report presents results of research projects executed in 2019. Selected projects have presented their results on April 9th and November 12th 2019 at the Future SOC Lab Day events.
The wide distribution of location-acquisition technologies means that large volumes of spatio-temporal data are continuously being accumulated. Positioning systems such as GPS enable the tracking of various moving objects' trajectories, which are usually represented by a chronologically ordered sequence of observed locations. The analysis of movement patterns based on detailed positional information creates opportunities for applications that can improve business decisions and processes in a broad spectrum of industries (e.g., transportation, traffic control, or medicine). Due to the large data volumes generated in these applications, the cost-efficient storage of spatio-temporal data is desirable, especially when in-memory database systems are used to achieve interactive performance requirements.
To efficiently utilize the available DRAM capacities, modern database systems support various tuning possibilities to reduce the memory footprint (e.g., data compression) or increase performance (e.g., additional indexes structures). By considering horizontal data partitioning, we can independently apply different tuning options on a fine-grained level. However, the selection of cost and performance-balancing configurations is challenging, due to the vast number of possible setups consisting of mutually dependent individual decisions.
In this thesis, we introduce multiple approaches to improve spatio-temporal data management by automatically optimizing diverse tuning options for the application-specific access patterns and data characteristics. Our contributions are as follows:
(1) We introduce a novel approach to determine fine-grained table configurations for spatio-temporal workloads. Our linear programming (LP) approach jointly optimizes the (i) data compression, (ii) ordering, (iii) indexing, and (iv) tiering. We propose different models which address cost dependencies at different levels of accuracy to compute optimized tuning configurations for a given workload, memory budgets, and data characteristics. To yield maintainable and robust configurations, we further extend our LP-based approach to incorporate reconfiguration costs as well as optimizations for multiple potential workload scenarios.
(2) To optimize the storage layout of timestamps in columnar databases, we present a heuristic approach for the workload-driven combined selection of a data layout and compression scheme. By considering attribute decomposition strategies, we are able to apply application-specific optimizations that reduce the memory footprint and improve performance.
(3) We introduce an approach that leverages past trajectory data to improve the dispatch processes of transportation network companies. Based on location probabilities, we developed risk-averse dispatch strategies that reduce critical delays.
(4) Finally, we used the use case of a transportation network company to evaluate our database optimizations on a real-world dataset. We demonstrate that workload-driven fine-grained optimizations allow us to reduce the memory footprint (up to 71% by equal performance) or increase the performance (up to 90% by equal memory size) compared to established rule-based heuristics.
Individually, our contributions provide novel approaches to the current challenges in spatio-temporal data mining and database research. Combining them allows in-memory databases to store and process spatio-temporal data more cost-efficiently.
This thesis presents an attempt to use source code synthesised from Coq formalisations of device drivers for existing (micro)kernel operating systems, with a particular focus on the Linux Kernel.
In the first part, the technical background and related work are described. The focus is here on the possible approaches to synthesising certified software with Coq, namely the extraction to functional languages using the Coq extraction plugin and the extraction to Clight code using the CertiCoq plugin. It is noted that the implementation of CertiCoq is verified, whereas this is not the case for the Coq extraction plugin. Consequently, there is a correctness guarantee for the generated Clight code which does not hold for the code being generated by the Coq extraction plugin. Furthermore, the differences between user space and kernel space software are discussed in relation to Linux device drivers. It is elaborated that it is not possible to generate working Linux kernel module components using the Coq extraction plugin without significant modifications. In contrast, it is possible to produce working user space drivers both with the Coq extraction plugin and CertiCoq. The subsequent parts describe the main contributions of the thesis.
In the second part, it is demonstrated how to extend the Coq extraction plugin to synthesise foreign function calls between the functional language OCaml and the imperative language C. This approach has the potential to improve the type-safety of user space drivers. Furthermore, it is shown that the code being synthesised by CertiCoq cannot be used in kernel space without modifications to the necessary runtime. Consequently, the necessary modifications to the runtimes of CertiCoq and VeriFFI are introduced, resulting in the runtimes becoming compatible components of a Linux kernel module. Furthermore, justifications for the transformations are provided and possible further extensions to both plugins and solutions to failing garbage collection calls in kernel space are discussed.
The third part presents a proof of concept device driver for the Linux Kernel. To achieve this, the event handler of the original PC Speaker driver is partially formalised in Coq. Furthermore, some relevant formal properties of the formalised functionality are discussed. Subsequently, a kernel module is defined, utilising the modified variants of CertiCoq and VeriFFI to compile a working device driver. It is furthermore shown that it is possible to compile the synthesised code with CompCert, thereby extending the guarantee of correctness to the assembly layer. This is followed by a performance evaluation that compares a naive formalisation of the PC speaker functionality with the original PC Speaker driver pointing out the weaknesses in the formalisation and possible improvements. The part closes with a summary of the results, their implications and open questions being raised.
The last part lists all used sources, separated into scientific literature, documentations or reference manuals and artifacts, i.e. source code.
The plant cell wall plays several crucial roles during plant development with its integrity acting as key signalling component for growth regulation during biotic and abiotic stresses. Cellulose microfibrils, the principal load-bearing components is the major component of the primary cell wall, whose synthesis is mediated by microtubule-associated CELLULOSE SYNTHASE (CESA) COMPLEXES (CSC). Previous studies have shown that CSC interacting proteins COMPANION OF CELLULOSE SYNTHASE (CC) facilitate sustained cellulose synthesis during salt stress by promoting repolymerization of cortical microtubules. However, our understanding of cellulose synthesis during salt stress remains incomplete.
In this study, a pull-down of CC1 protein led to the identification of a novel interactor, termed LEA-like. Phylogenetic analysis revealed that LEA-like belongs to the LATE EMBRYOGENESIS ABUNDANT (LEA) protein family, specifically to the LEA_2 subgroup, showing a close relationship with the CC proteins. Roots of the double mutants lea-like and its closest homolog emb3135 exhibited hypersensitivity when grown on cellulose synthesis inhibitors. Further analysis of higher-order mutants of lea-like, emb3135, and cesa6 demonstrated a genetic interaction between them indicating a significant role in cellulose synthesis.
Live-cell imaging revealed that both LEA-like and EMB3135 migrated with the CSC at the plasma membrane along microtubule tracks in control and oryzalin-treated conditions which destabilize microtubules, suggesting a tight interaction. Investigation of fluorescently labeled lines of different domains of the LEA-like protein revealed that the N-terminal cytosolic domain of LEA-like colocalizes with microtubules, suggesting a physical association between the two.
Considering the established role of LEA proteins in abiotic stress tolerance, we performed phenotypic analysis of the mutant under various stresses. Growth of double mutants of lea-like and emb3135 on NaCl containing media resulted in swelling of root cell indicating a putative role in salt stress tolerance. Supportive of this the quadruple mutant, lacking LEA-like, EMB3135, CC1, and CC2 proteins, exhibited a severe root growth defect on NaCl media compared to control conditions. Live-cell imaging revealed that under salt stress, the LEA-like protein forms aggregates in the plasma membrane.
In conclusion, this study has unveiled two novel interactors of the CSC that act with the CC proteins that regulate plant growth in response to salt stress providing new insights into the intricate regulation of cellulose synthesis, particularly under such conditions.
This thesis focuses on the molecular evolution of Macroscelidea, commonly referred to as sengis. Sengis are a mammalian order belonging to the Afrotherians, one of the four major clades of placental mammals. Sengis currently consist of twenty extant species, all of which are endemic to the African continent. They can be separated in two families, the soft-furred sengis (Macroscelididae) and the giant sengis (Rhynchocyonidae). While giant sengis can be exclusively found in forest habitats, the different soft-furred sengi species dwell in a broad range of habitats, from tropical rain-forests to rocky deserts.
Our knowledge on the evolutionary history of sengis is largely incomplete. The high level of superficial morphological resemblance among different sengi species (especially the soft-furred sengis) has for example led to misinterpretations of phylogenetic relationships, based on morphological characters. With the rise of DNA based taxonomic inferences, multiple new genera were defined and new species described. Yet, no full taxon molecular phylogeny exists, hampering the answering of basic taxonomic questions. This lack of knowledge can be to some extent attributed to the limited availability of fresh-tissue samples for DNA extraction. The broad African distribution, partly in political unstable regions and low population densities complicate contemporary sampling approaches. Furthermore, the DNA information available usually covers only short stretches of the mitochondrial genome and thus a single genetic locus with limited informational content.
Developments in DNA extraction and library protocols nowadays offer the opportunity to access DNA from museum specimens, collected over the past centuries and stored in natural history museums throughout the world. Thus, the difficulties in fresh-sample acquisition for molecular biological studies can be overcome by the application of museomics, the research field which emerged from those laboratory developments.
This thesis uses fresh-tissue samples as well as a vast collection museum specimens to investigate multiple aspects about the macroscelidean evolutionary history. Chapter 4 of this thesis focuses on the phylogenetic relationships of all currently known sengi species. By accessing DNA information from museum specimens in combination of fresh tissue samples and publicly available genetic resources it produces the first full taxon molecular phylogeny of sengis. It confirms the monophyly of the genus Elephantulus and discovers multiple deeply divergent lineages within different species, highlighting the need for species specific approaches. The study furthermore focuses on the evolutionary time frame of sengis by evaluating the impact of commonly varied parameters on tree dating. The results of the study show, that the mitochondrial information used in previous studies to temporal calibrate the Macroscelidean phylogeny led to an overestimation of node ages within sengis. Especially soft-furred sengis are thus much younger than previously assumed. The refined knowledge of nodes ages within sengis offer the opportunity to link e.g. speciation events to environmental changes.
Chapter 5 focuses on the genus Petrodromus with its single representative Petrodromus tetradactylus. It again exploits the opportunities of museomics and gathers a comprehensive, multi-locus genetic dataset of P. tetradactylus individuals, distributed across most the known range of this species. It reveals multiple deeply divergent lineages within Petrodromus, whereby some could possibly be associated to previously described sub-species, at least one was formerly unknown. It underscores the necessity for a revision of the genus Petrodromus through the integration of both molecular and morphological evidence. The study, furthermore identifies changing forest distributions through climatic oscillations as main factor shaping the genetic structure of Petrodromus.
Chapter 6 uses fresh tissue samples to extent the genomic resources of sengis by thirteen new nuclear genomes, of which two were de-novo assembled. An extensive dataset of more than 8000 protein coding one-to-one orthologs allows to further refine and confirm the temporal time frame of sengi evolution found in Chapter 4. This study moreover investigates the role of gene-flow and incomplete lineage sorting (ILS) in sengi evolution. In addition it identifies clade specific genes of possible outstanding evolutionary importance and links them to potential phenotypic traits affected. A closer investigation of olfactory receptor proteins reveals clade specific differences. A comparison of the demographic past of sengis to other small African mammals does not reveal a sengi specific pattern.
Die Zusammenarbeit zwischen Lehr- und anderen Fachkräften stellt in Modellen inklusiver Schul- und Unterrichtsentwicklung sowie Schuleffektivität ein wichtiges Element dar. Wenngleich Kooperation als bedeutsam postuliert wird, so belegen Studien, dass diese bisher überwiegend in autonomieerhaltenden Formen praktiziert wird. Als entwicklungsförderlich gelten jedoch v.a. komplexere Formen der Zusammenarbeit. Vor dem Hintergrund inklusiver Bildung und dem Anspruch einer bestmöglichen individuellen Entwicklung der Schüler*innen stellt die Zusammenarbeit von Lehr- und Fachkräften folglich ein sehr bedeutsames Thema dar. Es ist zu hinterfragen, wie sich die Zusammenarbeit zwischen Lehr- und Fachkräften im Primar- wie Sekundarstufenbereich an inklusiven Schulen gestaltet, welche Faktoren diese beeinflussen und welche Relevanz die unterschiedlichen Formen der Zusammenarbeit im Prozess inklusiver Schulentwicklung einnehmen. Bestehende Forschungsdesiderata aufgrei-fend, fokussiert die vorliegende Dissertation auf die realisierte Zusammenarbeit von Lehr- und Fachkräften im Primar- und Sekundarstufenbereich inklusiver Schulen, am Beispiel des Landes Brandenburg. Neben den realisierten Formen der Zusammenarbeit, stehen insbesondere die Identifikation von Kooperationsmustern von Lehr- und Fachkräften sowie von Schulen, und deren Zusammenhänge mit der Leistungsentwicklung von Schüler*innen im Kern des Forschungsinteresses.
Die vorliegende Dissertation bearbeitet insgesamt sechs Forschungsfragen, welche in drei Teilstudien adressiert werden: Zunächst werden mittels deskriptiver Analysen sowie Mehrebenenmodellierungen die Ausgangslage multiprofessioneller Kooperation (erste Forschungsfrage) sowie deren Rahmenbedingungen (zweite Forschungsfrage) im Primar- wie Sekundarstufenbereich erfasst (Teilstudie 1). Lehr- und Fachkräfte kooperierten überwiegend in autonomieerhaltenden, austauschbasierten Formen. Weiterhin zeigte sich, dass insbesondere die individuelle Offenheit zur Zusammenarbeit sowie die subjektiv wahrgenommene Unterstützung durch die Schulleitung bedeutsame Faktoren für die Realisierung multiprofessioneller Kooperation darstellten. Die Fragestellungen drei und vier befassen sich mit der Identifikation von Mustern im Kooperationsverhalten (Teilstudie 2). Zum einen geht es hierbei um personenbezogene Profile von Lehr- und Fachkräften (dritte Forschungsfrage), zum anderen um schulbezogene Profile (vierte Forschungsfrage), welche mittels des personenzentrierten Ansatzes der latenten Profilanalysen unter Berücksichtigung der Mehrebenenstruktur identifiziert werden. Hinsichtlich des individuellen Kooperationsverhaltens konnten vier Profile eruiert werden, bzgl. des schulspezifischen Kooperationsverhaltens drei. Die Mehrheit der Lehr- und Fachkräfte konnte im „regularly“-Profil verortet werden, d.h. nach eigener Einschätzung kooperierten diese überdurchschnittlich häufig im Austausch miteinander und arbeitsteilig, aber auch regelmäßig kokonstruktiv. Auf Schulebene zeigte sich, dass etwa jede zweite inklusive Schule im Land Brandenburg über eine hoch ausgeprägte Kooperationskultur verfügte. Im Fokus der Teilstudie 3 wird den Fragen nachgegangen, in welchem Zusammenhang die schulspezifischen Kooperationskulturen mit der Leistungsentwicklung von Schüler*innen in der Primar- wie Sekundarstufe steht. Mittels autoregressiver Mehrebenenanalysen wird einerseits der Zusammenhang mit der Leistungsentwicklung aller Schüler*innen (fünfte Forschungsfrage) untersucht, sowie spezifisch auf die Entwicklung von Schüler*innen mit und ohne sonderpädagogischem Förderbedarf (sechste Forschungsfrage) fokussiert. Ein zentrales Ergebnis war hierbei, dass Schüler*innen mit sonderpädagogischem Förderbedarf in der Primar- wie Sekundarstufe in ihrer Leistungsentwicklung am stärksten profitierten, wenn sie an Schulen lernten, an denen sich die Lehr- und Fachkräfte sehr regelmäßig über Lernstände der Schüler*innen austauschten (Austausch), Arbeitspakete für differenzierte Lernangebote erarbeiteten und verteilten (Arbeitsteilung) und darüber hinaus gelegentlich gemeinsam Problemlösungen entwickelten (Kokonstruktion).
Die Ergebnisse werden vor dem Hintergrund der postulierten Relevanz multiprofessioneller Kooperation für inklusive Schul- und Unterrichtsentwicklungsprozesse eingeordnet und diskutiert. Weiterhin werden verschiedene praktische Implikationen für die Unterstützung multiprofessioneller Zusammenarbeit im Primar- und Sekundarstufenbereich abgeleitet.
The Jewish population of early modern Italy was characterised by its inner diversity, which found its expression in the coexistence of various linguistic, cultural and liturgical traditions, as well as social and economic patterns. The contributions in this volume aim to explore crucial questions concerning the self-perception and identity of early modern Italian Jews from new perspectives and angles.
ADHS bei Jugendlichen
(2024)
ADHS galt lange als eine Störung des Kindesalters. Aber bis zu 80 % der Patient:innen sind auch noch als Jugendliche betroffen. Gerade sie brauchen Hilfe bei ihren Problemen!
In der Schule müssen sie öfter die Klasse wiederholen, im sozialen und emotionalen Bereich gibt es Konflikte mit Gleichaltrigen und Eltern. Unbehandelt drohen psychische Störungen, Drogenmissbrauch oder delinquentes Verhalten.
Das vorliegende Lerntraining ist das erste multimodale Behandlungskonzept für Jugendliche im Alter von 12 bis 17 Jahren. Es werden konkrete Probleme und Aufgaben aus Schule und Umwelt behandelt, um daran allgemeine Strategien herzuleiten. Eltern und Lehrer werden intensiv in die Behandlung mit einbezogen.
In Time and the Other Johannes Fabian analysed how modern conceptions of time were “not only secularized and naturalized but also thoroughly spatialized.” According to Fabian, this was particularly visible in modern anthropology which “promoted a scheme in terms of which not only past cultures but all living societies were irrevocably placed on a temporal slope, a stream of Time – some upstream, others downstream.”3 Anthropologists attributed otherness to a distant past which was traditionally associated with cultural retardation, i.e. a lower degree of development, progress, and civilization. Cultural difference was expressed in terms of temporal distance while temporal distance was attributed to spatial remoteness. The result was a phenomenon that Fabian coined “the denial of coevalness” which pointed towards “a persistent and systematic tendency to place the referent(s) of anthropology in a Time other than the present of the producer of anthropological discourse.
Das historische Erzählen ist im 19. Jahrhundert eine der prominentesten narrativen Formen. Aber es ist immer auch zukunftsaffin. In diesem Band wird diese Kehrseite der Vergangenheitsorientierung in historischer und systematischer Perspektive entlang folgender Leitfragen untersucht: Wie können Zukunftsreflexionen in Genres analytisch und konzeptionell gefasst werden, die nicht programmatisch dem Zukunftssujet verpflichtet sind? Wie ist das Wissen um Zukunft organisiert und ästhetisch strukturiert? Wie verhält sich eine solche implizite ästhetische Problematisierung von Zukunft gegenüber expliziten Zukunftsmodellen der entstehenden Science Fiction?
Prognose, Planung, Sicherung
(2024)