98 research outputs found
ParetoPrep: Fast computation of Path Skylines Queries
Computing cost optimal paths in network data is a very important task in many
application areas like transportation networks, computer networks or social
graphs. In many cases, the cost of an edge can be described by various cost
criteria. For example, in a road network possible cost criteria are distance,
time, ascent, energy consumption or toll fees. In such a multicriteria network,
a route or path skyline query computes the set of all paths having pareto
optimal costs, i.e. each result path is optimal for different user preferences.
In this paper, we propose a new method for computing route skylines which
significantly decreases processing time and memory consumption. Furthermore,
our method does not rely on any precomputation or indexing method and thus, it
is suitable for dynamically changing edge costs. Our experiments demonstrate
that our method outperforms state of the art approaches and allows highly
efficient path skyline computation without any preprocessing.Comment: 12 pages, 9 figures, technical repor
Query processing in complex modern traffic networks
The transport sector generates about one quarter of all greenhouse gas emissions worldwide. In the European Union (EU), passenger cars and light-duty trucks make up for over half of these traffic-related emissions. It is evident that everyday traffic is a serious environmental threat. At the same time, transport is a key factor for the ambitious EU climate goals; among them, for instance, the reduction of greenhouse gas emissions by 85 to 90 percent in the next 35 years. This thesis investigates complex traffic networks and their requirements from a computer science perspective. Modeling of and query processing in modern traffic networks are pivotal topics. Challenging theoretical problems are examined from different perspectives, novel algorithmic solutions are provided. Practical problems are investigated and solved, for instance, employing qualitative crowdsourced information and sensor data of various sources.
Modern traffic networks are often modeled as graphs, i.e., defined by sets of nodes and edges. In conventional graphs, the edges are assigned numerical weights, for instance, reflecting cost criteria like distance or travel time. In multicriteria networks, the edges reflect multiple, possibly dynamically changing cost criteria. While these networks allow for diverse queries and meaningful insight, query processing usually is significantly more complex. Novel means for computation are required to keep query processing efficient. The crucial task of computing optimal paths is particularly expensive under multiple criteria. The most established set of optimal paths in multicriteria networks is referred to as path skyline (or set of pareto-optimal paths). Until now, computing the path skyline either required extensive precomputation or networks of minor size or complexity. Neither of these demands can be made on modern traffic networks. This thesis presents a novel method which makes on-the-fly computation of path skylines possible, even in dynamic networks with three or more cost criteria. Another problem examined is the exponentially growth of path skylines. The number of elements in a path skyline is potentially exponential in the number of cost criteria and the number of edges between start and target. This often produces less meaningful results, sometimes hindering usability. These drawbacks emphasize the importance of the linear path skyline which is investigated in this thesis. The linear path skyline is based on a different notion of optimality. By the notion of optimality, the linear path skyline is a subset of the conventional path skyline but in general contains less and more diverse elements. Thus, the linear path skyline facilitates interpretation while in general reducing computational effort. This topic is first studied in networks with two cost criteria and subsequently extended to more cost criteria.
These cost criteria are not limited to purely quantitative measures like distance and travel time. This thesis examines the integration of qualitative information into abstractly modeled road networks. It is proposed to mine crowdsourced data for qualitative information and use this information to enrich road network graphs. These enriched networks may in turn be used to produce routing suggestions which reflect an opinion of the crowd. From data processing to knowledge extracting, network enrichment and route computation, the possibilities and challenges of crowdsourced data as a source for information are surveyed. Additionally, this thesis substantiates the practicability of network enrichment in real-world experiments. The description of a demonstration framework which applies some of the presented methods to the use case of tourist route recommendation serves as an example. The methods may also be applied to a novel graph-based routing problem proposed in this thesis. The problem extends the family of Orienteering Problems which find frequent application in tourist routing and other tasks. An approximate solution to this NP-hard problem is presented and evaluated on a large scale, real-world, time-dependent road network.
Another central aspect of modern traffic networks is the integration of sensor data, often referred to as telematics. Nowadays, manifold sensors provide a plethora of data. Using this data to optimize traffic is and will continue to be a challenging task for research and industry. Some of the applications which qualify for the integration of modern telematics are surveyed in this thesis. For instance, the abstract problem of consumable and reoccurring resources in road networks is studied. An application of this problem is the search for a vacant parking space. Taking statistical and real-time sensor information into account, a stochastic routing algorithm which maximizes the probability of finding a vacant space is proposed. Furthermore, the thesis presents means for the extraction of driving preferences, helping to better understand user behavior in traffic. The theoretical concepts partially find application in a demonstration framework described in this thesis. This framework provides features which were developed for a real-world pilot project on the topics of electric and shared mobility. Actual sensor car data collected in the project, gives insight to the challenges of managing a fleet of electric vehicles.Verkehrsmittel erzeugen rund ein Viertel aller Treibhausgas-Emissionen weltweit. FĂŒr ĂŒber die HĂ€lfte der verkehrsbedingten Emissionen in der EuropĂ€ischen Union (EU) zeichnen PKW und Kleinlaster verantwortlich. Die Tragweite ökologischer Konsequenzen durch alltĂ€glichen Verkehr ist enorm. Zugleich ist ein Umdenken im Bezug auf Verkehr entscheidend, um die ehrgeizigen klimapolitischen Ziele der EU zu erfĂŒllen. Dazu gehört unter anderem, Treibhausgas-Emissionen bis 2050 um 85 bis 90 Prozent zu verringern. Die vorliegende Arbeit widmet sich den komplexen Anforderungen an Verkehr und Verkehrsnetzwerke aus der Sicht der Informatik. Dabei spielen sowohl die Modellierung von als auch die Anfragebearbeitung in modernen Verkehrsnetzwerken eine entscheidende Rolle. Theoretische Fragestellungen werden aus unterschiedlichen Persepektiven beleuchtet, neue Algorithmen werden vorgestellt. Ebenso werden praktische Fragestellungen untersucht und gelöst, etwa durch die Einbindung nutzergenerierten Inhalts oder die Verwendung von Sensordaten aus unterschiedlichen Quellen.
Moderne Verkehrsnetzwerke werden hĂ€ufig als Graphen modelliert, d.h., durch Knoten und Kanten dargestellt. Man unterscheidet zwischen konventionellen Graphen und sogenannten Multiattributs-Graphen. WĂ€hrend die Kanten konventioneller Graphen numerische Gewichte tragen, die statische Kostenkriterien wie Distanz oder Reisezeit modellieren, beschreiben die Kantengewichte in Multiattributs-Graphen mehrere, möglicherweise dynamisch verĂ€nderliche Kostenkriterien. Das erlaubt einerseits vielseitige Anfragen und aussagekrĂ€ftige Erkenntnisse, macht die Anfragebearbeitung jedoch ungleich komplexer und verlangt deshalb nach neuen Berechnungsmethoden. Eine besonders aufwendige Anfrage ist die Berechnung optimaler Pfade, zugleich eine der zentralsten Fragestellungen. Die gĂ€ngigste Menge optimaler Pfade wird als Pfad-Skyline (auch: Menge der pareto-optimalen Pfade) bezeichnet. Die effiziente Berechnung der Pfad-Skyline setzte bisher ĂŒberschaubare Netzwerke oder betrĂ€chtliche Vorberechnungen voraus. Keine der beiden Bedingung kann in modernen Verkehrsnetzwerken erfĂŒllt werden. Diese Arbeit stellt deshalb eine Methode vor, die die Berechnung der Pfad-Skyline erheblich beschleunigt, selbst in dynamischen Netzwerken mit drei oder mehr Kostenkriterien. AuĂerdem wird das Problem des exponentiellen Wachstums der Pfad-Skyline betrachtet. Die Anzahl der Elemente der Pfad-Skyline wĂ€chst im schlechtesten Fall exponentiell in der Anzahl der Kostenkriterien sowie in der Entfernung zwischen Start und Ziel. Dies kann zu unĂŒbersichtlichen und wenig aussagekrĂ€ftigen Resultatmengen fĂŒhren. Diese Nachteile unterstreichen die Bedeutung der linearen Pfad-Skyline, die auch im Rahmen diese Arbeit untersucht wird. Die lineare Pfad-Skyline folgt einer anderen Definition von OptimalitĂ€t. Stets ist die lineare Pfad-Skyline eine Teilmenge der konventionellen Pfad-Skyline, meist enthĂ€lt sie deutlich weniger, unterschiedlichere Resultate. Dadurch lĂ€sst sich die lineare Pfad-Skyline im Allgemeinen schneller berechnen und erleichtert die Interpretation der Resultate. Die Berechnung der linearen Pfad-Skyline wird erst fĂŒr Netzwerke mit zwei Kostenkriterien, anschlieĂend fĂŒr Netzwerke mit beliebig vielen Kostenkriterien untersucht.
Kostenkriterien sind nicht notwendigerweise auf rein quantitative MaĂe wie Distanz oder Reisezeit beschrĂ€nkt. Diese Arbeit widmet sich auch der Integration qualitativer Informationen, mit dem Ziel, intuitivere und greifbarere Routingergebnisse zu erzeugen. Dazu wird die Möglichkeit untersucht, abstrakte StraĂennetzwerke mit qualitativen Informationen anzureichern, wobei die Informationen aus nutzergenerierten Daten geschöpft werden. Solche sogenannten Enriched Networks ermöglichen die Berechnung von Pfaden, die in gewisser Weise das Wissen der Nutzer reflektieren. Von der Datenverarbeitung, ĂŒber die Extraktion von Wissen, bis hin zum Network-Enrichment und der Pfadberechnung, gibt diese Arbeit einen ĂŒberblick zum Thema. Weiterhin wird die PraktikabilitĂ€t dieses Vorgehens mit Experimenten auf Realdaten untermauert. Die Beschreibung eines Demonstrationstools fĂŒr den Anwendungsfall der
Navigation von Touristen dient als anschauliches Beispiel. Die vorgestellten Methoden sind darĂŒber hinaus auch anwendbar auf ein neues, graphentheoretisches Routingproblem, das in dieser Arbeit vorgestellt wird. Es handelt sich dabei um eine zeitabĂ€ngige Erweiterung der Familie der Orienteering Probleme, die hĂ€ufig Anwendung finden, etwa auch im der Bereich der Touristennavigation. Das vorgestellte Problem ist NP-schwer lĂ€sst sich jedoch dank eines hier vorgestellten Algorithmus effizient approximieren. Die Evaluation untermauert die Effizienz des vorgestellten Lösungsansatzes und ist zugleich die erste Auswertung eines zeitabhĂ€ngigen Orienteering Problems auf einem groĂformatigen Netzwerk.
Ein weiterer zentraler Aspekt moderner Verkehrsnetzwerke ist die Integration von Sensordaten, oft unter dem Begriff Telematik zusammengefasst. Heutzutage generiert eine Vielzahl von Sensoren Unmengen an Daten. Diese Daten zur Verkehrsoptimierung einzusetzen ist und bleibt eine wichtige Aufgabe fĂŒr Wissenschaft und Industrie. Einige der Anwendungen, die sich fĂŒr den Einsatz von Telematik anbieten, werden in dieser Arbeit untersucht. So wird etwa das
abstrakte Problem konsumierbarer und wiederkehrender Ressourcen im StraĂennetzwerk untersucht. Ein alltĂ€gliches Beispiel fĂŒr dieses Problem ist die Parkplatzsuche. Der vorgeschlagene Algorithmus, der die Wahrscheinlichkeit maximiert, einen freien Parkplatz zu finden, baut auf die Verwendung statistischer sowie aktueller Sensordaten. Weiterhin werden Methoden zur Ableitung von FahrerprĂ€ferenzen entwickelt. Die theoretischen Fundamente finden zum Teil in einem hier beschriebenen Demonstrationstool Anwendung. Das Tool veranschaulicht Features, die fĂŒr ein Pilotprojekt zu den Themen ElektromobilitĂ€t und Fahrzeugflotten entwickelt wurden. Im Rahmen eines Pilotversuchs wurden Sensordaten von Elektrofahrzeugen erhoben, die Einblick in die Herausforderungen beim Management von Elektrofahrzeugflotten geben
SegmentaciĂłn multiescala del Edema Macular QuĂstico en imĂĄgenes OCT
[Resumen]
De entre todas las diferentes patologĂas oculares existentes, las mĂĄs preocupantes
son las que no provocan ningĂșn signo o sĂntoma en el paciente. En particular, el Edema
Macular QuĂstico (EMQ) no causa ningĂșn sĂntoma hasta una etapa muy avanzada de
la enfermedad y se caracteriza principalmente por la presencia de regiones quĂsticas
(ĂĄreas llenas de lĂquido patolĂłgico) en la regiĂłn macular.
La TomografĂa de Coherencia Ăptica (OCT) es una tĂ©cnica de diagnĂłstico por
imagen no invasiva que utiliza ondas de luz para tomar imĂĄgenes tridimensionales y
transversales detalladas de los tejidos oculares con resolución micrométrica. OCT es
una herramienta Ăștil y eficaz que es ampliamente utilizada por los oftalmĂłlogos en el
diagnĂłstico y seguimiento del EMQ. Una herramienta capaz de aislar y representar
las distintas estructuras quĂsticas de la retina puede mejorar la calidad y eficacia de
los procesos diagnĂłsticos, permitiendo a los clĂnicos realizar estudios mĂĄs precisos y
tratamientos mĂĄs adecuados de esta relevante patologĂa ocular.
AsĂ, en este proyecto, se propone una novedosa y totalmente automĂĄtica metodologĂa
para la segmentaciĂłn multiescala de los EMQs a partir de imĂĄgenes OCT. En particular,
la metodologĂa propuesta utiliza 3 diferentes y complementarias aproximaciones: (i)
Curvedness y Shape Index, (ii) Central Adaptive Medialness y (iii) la combinaciĂłn
entre ambas aproximaciones.
Para la validaciĂłn del sistema, se han realizado varios experimentos utilizando un
conjunto de imĂĄgenes OCT etiquetadas por un experto clĂnico. Los resultados obtenidos
han demostrado el correcto funcionamiento del sistema para las 3 aproximaciones y,
por tanto, demuestran la solidez del sistema aplicado a la segmentaciĂłn de quistes de
diferentes tamaños y en el apoyo al proceso de toma de decisiones clĂnicas.Traballo fin de grao (UDC.FIC). EnxeñarĂa informĂĄtica. Curso 2019/202
Tratamiento cognitivo conductual de los efectos ocasionados por el alcohol en personas de 20 años de edad.
IdentificĂł el factor desencadenante del sentimiento de culpa generada por el alcoholismo en personas de 20 a 35 años. DefiniĂł el sentimiento de culpa por el alcoholismo. DescribiĂł la sintomatologĂa que presenta el paciente, analizar el factor desencadenante del sentimiento de culpa. Propuso tĂ©cnicas psicolĂłgicas, basadas en terapia cognitivo conductual para el abordaje del sentimiento de culpa generada por el alcoholismo. La investigaciĂłn fue de tipo cualitativa y se realizĂł en el Centro de RehabilitaciĂłn âDesafĂo Juvenilâ ubicada en 9ÂȘ. Calle 12-85 zona 11, del 17 de septiembre del año 2012 al 12 de octubre del año 2012. La poblaciĂłn estuvo integrada por 12 pacientes con problemas de alcoholismo, comprendidos en las edades de 20 a 35 años de edad. Para recolectar datos se utilizaron las tĂ©cnicas siguientes: entrevista semiestructurada, observaciĂłn participativa y testimonios. Se realizĂł el anĂĄlisis de resultados y concluyĂł que, el tratamiento cognitivo conductual se adecua al abordaje de personas que presentan sentimiento de culpa generada por el alcoholismo, permite la toma de conciencia sobre los pensamientos y emociones que presenta el paciente, para que puedan enfrentar la adicciĂłn que tienen, y se minimice la posible recaĂda en el alcohol nuevamente
Modulation of Phosducin-Like Protein 3 (PhLP3) Levels Promotes Cytoskeletal Remodelling in a MAPK and RhoA-Dependent Manner
Background
Phosducin-like protein 3 (PhLP3) forms a ternary complex with the ATP-dependent molecular chaperone CCT and its folding client tubulin. In vitro studies suggest PhLP3 plays an inhibitory role in ?-tubulin folding while conversely in vivo genetic studies suggest PhLP3 is required for the correct folding of ?-tubulin. We have a particular interest in the cytoskeleton, its chaperones and their role in determining cellular phenotypes associated with high level recombinant protein expression from mammalian cell expression systems.
Methodology/Principal Findings
As studies into PhLP3 function have been largely carried out in non mammalian systems, we examined the effect of human PhLP3 over-expression and siRNA silencing using a single murine siRNA on both tubulin and actin systems in mammalian Chinese hamster ovary (CHO) cell lines. We show that over-expression of PhLP3 promotes an imbalance of ? and ? tubulin subunits, microtubule disassembly and cell death. In contrast, ?-actin levels are not obviously perturbed. On-the-other-hand, RNA silencing of PhLP3 increases RhoA-dependent actin filament formation and focal adhesion formation and promotes a dramatic elongated fibroblast-like change in morphology. This was accompanied by an increase in phosphorylated MAPK which has been associated with promoting focal adhesion assembly and maturation. Transient overexpression of PhLP3 in knockdown experiments rescues cells from the morphological change observed during PhLP3 silencing but mitosis is perturbed, probably reflecting a tipping back of the balance of PhLP3 levels towards the overexpression state.
Conclusions
Our results support the hypothesis that PhLP3 is important for the maintenance of ?-tubulin levels in mammalian cells but also that its modulation can promote actin-based cytoskeletal remodelling by a mechanism linked with MAPK phosphorylation and RhoA-dependent changes. PhLP3 levels in mammalian cells are thus finely poised and represents a novel target for engineering industrially relevant cell lines to evolve lines more suited to suspension or adherent cell growth
Dss1 is a 26S proteasome ubiquitin receptor
The ubiquitin-proteasome system is the major pathway for protein degradation in eukaryotic cells. Proteins to be degraded are conjugated to ubiquitin chains that act as recognition signals for the 26S proteasome. The proteasome subunits Rpn10 and Rpn13 are known to bind ubiquitin, but genetic and biochemical data suggest the existence of at least one other substrate receptor. Here, we show that the phylogenetically conserved proteasome subunit Dss1 (Sem1) binds ubiquitin chains linked by K63 and K48. Atomic resolution data show that Dss1 is disordered and binds ubiquitin by binding sites characterized by acidic and hydrophobic residues. The complementary binding region in ubiquitin is composed of a hydrophobic patch formed by I13, I44, and L69 flanked by two basic regions. Mutations in the ubiquitin-binding site of Dss1 cause growth defects and accumulation of ubiquitylated proteins
Experimental determination of codon usage?dependent selective pressure on high copy?number genes in Saccharomyces cerevisiae
One of the central hypotheses in the theory of codon usage evolution is that in highly expressed genes particular codon usage patterns arise because they facilitate efficient gene expression and are thus selected for in evolution. Here we use plasmid copy number assays and growth rate measurements to explore details of the relationship between codon usage, gene expression level, and selective pressure in Saccharomyces cerevisiae. We find that when high expression levels are required optimal codon usage is beneficial and provides a fitness advantage, consistent with evolutionary theory. However, when high expression levels are not required, optimal codon usage is surprisingly and strongly selected against. We show that this selection acts at the level of protein synthesis, and we exclude a number of molecular mechanisms as the source for this negative selective pressure including nutrient and ribosome limitations and proteotoxicity effects. These findings inform our understanding of the evolution of codon usage bias, as well as the design of recombinant protein expression systems
Localization of Fe?S Biosynthesis Machinery in Cryptosporidium parvum Mitosome
Cryptosporidium is a protozoan, apicomplexan, parasite that poses significant risk to humans and animals, as a common cause of potentially fatal diarrhea in immunodeficient hosts. The parasites have evolved a number of unique biological features that allow them to thrive in a highly specialized parasitic lifestyle. For example, the genome of Cryptosporidium parvum is highly reduced, encoding only 3,805 proteins, which is also reflected in its reduced cellular and organellar content and functions. As such, its remnant mitochondrion, dubbed a mitosome, is one of the smallest mitochondria yet found. While numerous studies have attempted to discover the function(s) of the C. parvum mitosome, most of them have been focused on in silico predictions. Here, we have localized components of a biochemical pathway in the C. parvum mitosome, in our investigations into the functions of this peculiar mitochondrial organelle. We have shown that three proteins involved in the mitochondrial iron-sulfur cluster biosynthetic pathway are localized in the organelle, and one of them can functionally replace its yeast homolog. Thus, it seems that the C. parvum mitosome is involved in iron-sulfur cluster biosynthesis, supporting the organellar and cytosolic apoproteins. These results spearhead further research on elucidating the functions of the mitosome and broaden our understanding in the minimalistic adaptations of these organelles
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