K-Dominance in Multidimensional Data: Theory and Applications

We study the problem of k-dominance in a set of d-dimensional vectors, prove bounds on the number of maxima (skyline vectors), under both worst-case and average-case models, perform experimental evaluation using synthetic and real-world data, and explore an application of k-dominant skyline for extracting a small set of top-ranked vectors in high dimensions where the full skylines can be unmanageably large

CLASH-VLT: Strangulation of cluster galaxies in MACSJ0416.1-2403 as seen from their chemical enrichment

(abridged) We explore the Frontier Fields cluster MACS J0416.1-2403 at z=0.3972 with VIMOS/VLT spectroscopy from the CLASH-VLT survey covering a region which corresponds to almost three virial radii. We measure fluxes of 5 emission lines of 76 cluster members enabling us to unambiguously derive O/H gas metallicities, and also SFRs from Halpha. For intermediate massses we find a similar distribution of cluster and field galaxies in the MZR and mass vs. sSFR diagrams. Bulge-dominated cluster galaxies have on average lower sSFRs and higher O/Hs compared to their disk-dominated counterparts. We use the location of galaxies in the projected velocity vs. position phase-space to separate our cluster sample into a region of objects accreted longer time ago and a region of recently accreted and infalling galaxies. We find a higher fraction of accreted metal-rich galaxies (63%) compared to the fraction of 28% of metal-rich galaxies in the infalling regions. Intermediate mass galaxies falling into the cluster for the first time are found to be in agreement with predictions of the fundamental metallicity relation. In contrast, for already accreted star-forming galaxies of similar masses, we find on average metallicities higher than predicted by the models. This trend is intensified for accreted cluster galaxies of the lowest mass bin, that display metallicities 2-3 times higher than predicted by models with primordial gas inflow. Environmental effects therefore strongly influence gas regulations and control gas metallicities of log(M/Msun)<10.2 (Salpeter IMF) cluster galaxies. We also investigate chemical evolutionary paths of model galaxies with and without inflow of gas showing that strangulation is needed to explain the higher metallicities of accreted cluster galaxies. Our results favor a strangulation scenario in which gas inflow stops for log(M/Msun)<10.2 galaxies when accreted by the cluster.Comment: Version better matched to the published version, including table with observed and derived quantities for the 76 cluster galaxie

Processing Rank-Aware Queries in Schema-Based P2P Systems

Effiziente Anfragebearbeitung in Datenintegrationssystemen sowie in P2P-Systemen ist bereits seit einigen Jahren ein Aspekt aktueller Forschung. Konventionelle Datenintegrationssysteme bestehen aus mehreren Datenquellen mit ggf. unterschiedlichen Schemata, sind hierarchisch aufgebaut und besitzen eine zentrale Komponente: den Mediator, der ein globales Schema verwaltet. Anfragen an das System werden auf diesem globalen Schema formuliert und vom Mediator bearbeitet, indem relevante Daten von den Datenquellen transparent für den Benutzer angefragt werden. Aufbauend auf diesen Systemen entstanden schließlich Peer-Daten-Management-Systeme (PDMSs) bzw. schemabasierte P2P-Systeme. An einem PDMS teilnehmende Knoten (Peers) können einerseits als Mediatoren agieren andererseits jedoch ebenso als Datenquellen. Darüber hinaus sind diese Peers autonom und können das Netzwerk jederzeit verlassen bzw. betreten. Die potentiell riesige Datenmenge, die in einem derartigen Netzwerk verfügbar ist, führt zudem in der Regel zu sehr großen Anfrageergebnissen, die nur schwer zu bewältigen sind. Daher ist das Bestimmen einer vollständigen Ergebnismenge in vielen Fällen äußerst aufwändig oder sogar unmöglich. In diesen Fällen bietet sich die Anwendung von Top-N- und Skyline-Operatoren, ggf. in Verbindung mit Approximationstechniken, an, da diese Operatoren lediglich diejenigen Datensätze als Ergebnis ausgeben, die aufgrund nutzerdefinierter Ranking-Funktionen am relevantesten für den Benutzer sind. Da durch die Anwendung dieser Operatoren zumeist nur ein kleiner Teil des Ergebnisses tatsächlich dem Benutzer ausgegeben wird, muss nicht zwangsläufig die vollständige Ergebnismenge berechnet werden sondern nur der Teil, der tatsächlich relevant für das Endergebnis ist. Die Frage ist nun, wie man derartige Anfragen durch die Ausnutzung dieser Erkenntnis effizient in PDMSs bearbeiten kann. Die Beantwortung dieser Frage ist das Hauptanliegen dieser Dissertation. Zur Lösung dieser Problemstellung stellen wir effiziente Anfragebearbeitungsstrategien in PDMSs vor, die die charakteristischen Eigenschaften ranking-basierter Operatoren sowie Approximationstechniken ausnutzen. Peers werden dabei sowohl auf Schema- als auch auf Datenebene hinsichtlich der Relevanz ihrer Daten geprüft und dementsprechend in die Anfragebearbeitung einbezogen oder ausgeschlossen. Durch die Heterogenität der Peers werden Techniken zum Umschreiben einer Anfrage von einem Schema in ein anderes nötig. Da existierende Techniken zum Umschreiben von Anfragen zumeist nur konjunktive Anfragen betrachten, stellen wir eine Erweiterung dieser Techniken vor, die Anfragen mit ranking-basierten Anfrageoperatoren berücksichtigt. Da PDMSs dynamische Systeme sind und teilnehmende Peers jederzeit ihre Daten ändern können, betrachten wir in dieser Dissertation nicht nur wie Routing-Indexe verwendet werden, um die Relevanz eines Peers auf Datenebene zu bestimmen, sondern auch wie sie gepflegt werden können. Schließlich stellen wir SmurfPDMS (SiMUlating enviRonment For Peer Data Management Systems) vor, ein System, welches im Rahmen dieser Dissertation entwickelt wurde und alle vorgestellten Techniken implementiert.In recent years, there has been considerable research with respect to query processing in data integration and P2P systems. Conventional data integration systems consist of multiple sources with possibly different schemas, adhere to a hierarchical structure, and have a central component (mediator) that manages a global schema. Queries are formulated against this global schema and the mediator processes them by retrieving relevant data from the sources transparently to the user. Arising from these systems, eventually Peer Data Management Systems (PDMSs), or schema-based P2P systems respectively, have attracted attention. Peers participating in a PDMS can act both as a mediator and as a data source, are autonomous, and might leave or join the network at will. Due to these reasons peers often hold incomplete or erroneous data sets and mappings. The possibly huge amount of data available in such a network often results in large query result sets that are hard to manage. Due to these reasons, retrieving the complete result set is in most cases difficult or even impossible. Applying rank-aware query operators such as top-N and skyline, possibly in conjunction with approximation techniques, is a remedy to these problems as these operators select only those result records that are most relevant to the user. Being aware that in most cases only a small fraction of the complete result set is actually output to the user, retrieving the complete set before evaluating such operators is obviously inefficient. Therefore, the questions we want to answer in this dissertation are how to compute such queries in PDMSs and how to do that efficiently. We propose strategies for efficient query processing in PDMSs that exploit the characteristics of rank-aware queries and optionally apply approximation techniques. A peer's relevance is determined on two levels: on schema-level and on data-level. According to its relevance a peer is either considered for query processing or not. Because of heterogeneity queries need to be rewritten, enabling cooperation between peers that use different schemas. As existing query rewriting techniques mostly consider conjunctive queries only, we present an extension that allows for rewriting queries involving rank-aware query operators. As PDMSs are dynamic systems and peers might update their local data, this dissertation addresses not only the problem of considering such structures within a query processing strategy but also the problem of keeping them up-to-date. Finally, we provide a system-level evaluation by presenting SmurfPDMS (SiMUlating enviRonment For Peer Data Management Systems) -- a system created in the context of this dissertation implementing all presented techniques

From Proximity to Utility: A Voronoi Partition of Pareto Optima

We present an extension of Voronoi diagrams where when considering which site a client is going to use, in addition to the site distances, other site attributes are also considered (for example, prices or weights). A cell in this diagram is then the locus of all clients that consider the same set of sites to be relevant. In particular, the precise site a client might use from this candidate set depends on parameters that might change between usages, and the candidate set lists all of the relevant sites. The resulting diagram is significantly more expressive than Voronoi diagrams, but naturally has the drawback that its complexity, even in the plane, might be quite high. Nevertheless, we show that if the attributes of the sites are drawn from the same distribution (note that the locations are fixed), then the expected complexity of the candidate diagram is near linear. To this end, we derive several new technical results, which are of independent interest. In particular, we provide a high-probability, asymptotically optimal bound on the number of Pareto optima points in a point set uniformly sampled from the $d$-dimensional hypercube. To do so we revisit the classical backward analysis technique, both simplifying and improving relevant results in order to achieve the high-probability bounds

Magnitude of urban heat islands largely explained by climate and population

Urban heat islands (UHIs) exacerbate the risk of heat-related mortality associated with global climate change. The intensity of UHIs varies with population size and mean annual precipitation, but a unifying explanation for this variation is lacking, and there are no geographically targeted guidelines for heat mitigation. Here we analyse summertime differences between urban and rural surface temperatures (ΔTs) worldwide and find a nonlinear increase in ΔTs with precipitation that is controlled by water or energy limitations on evapotranspiration and that modulates the scaling of ΔTs with city size. We introduce a coarse-grained model that links population, background climate, and UHI intensity, and show that urban–rural differences in evapotranspiration and convection efficiency are the main determinants of warming. The direct implication of these nonlinearities is that mitigation strategies aimed at increasing green cover and albedo are more efficient in dry regions, whereas the challenge of cooling tropical cities will require innovative solutions

An Architectural Perspective on Structured Sacred Space—Recent Evidence from Iron Age Ireland

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Stellar Feedback and Resolved Stellar IFU Spectroscopy in the nearby Spiral Galaxy NGC 300

We present MUSE Integral Field Unit (IFU) observations of five individual HII regions in two giant (> 100 pc in radius) star-forming complexes in the low-metallicity (Z~0.33 Z) nearby (D ~ 2 Mpc) dwarf spiral galaxy NGC 300. We combine the IFU data with high spatial resolution HST photometry to demonstrate the extraction of stellar spectra and the classification of individual stars from ground-based data at the distance of 2 Mpc. For the two star-forming complexes, in which no O-type stars had previously been identified, we find a total of 13 newly identified O-type stars in the mass range 15-50 M, as well as 4 Wolf-Rayet stars. We use the derived massive stellar content to analyze the impact of stellar feedback on the HII regions. As already found for HII regions in the Magellanic Clouds, the dynamics of the analyzed NGC 300 HII regions are dominated by a combination of the pressure of the ionized gas and stellar winds. By comparing the derived ionized gas mass loading factors to the total gas mass loading factor across the NGC 300 disk, we find that the latter is an order of magnitude higher, either indicating very early evolutionary stages for these HII regions, or being a direct result of the multi-phase nature of feedback-driven bubbles. Moreover, we analyze the relation between the star formation rate and the pressure of the ionized gas as derived from small (<100 pc) scales, as both quantities are systematically overestimated when derived on galactic scales. With the wealth of ongoing and upcoming IFU instruments and programs, this study serves as a pathfinder for the systematic investigation of resolved stellar feedback in nearby galaxies, and it delivers the necessary analysis tools to enable massive stellar content and feedback studies sampling an unprecedented range of HII region properties across entire galaxies in the nearby Universe