On properties of a graph that depend on its distance function

summary:If $G$ is a connected graph with distance function $d$, then by a step in $G$ is meant an ordered triple $(u, x, v)$ of vertices of $G$ such that $d(u, x) = 1$ and $d(u, v) = d(x, v) + 1$. A characterization of the set of all steps in a connected graph was published by the present author in 1997. In Section 1 of this paper, a new and shorter proof of that characterization is presented. A stronger result for a certain type of connected graphs is proved in Section 2

Guides and Shortcuts in Graphs

The geodesic structure of a graphs appears to be a very rich structure. There are many ways to describe this structure, each of which captures only some aspects. Ternary algebras are for this purpose very useful and have a long tradition. We study two instances: signpost systems, and a special case of which, step systems. Signpost systems were already used to characterize graph classes. Here we use these for the study of the geodesic structure of a spanning subgraph F with respect to its host graph G. Such a signpost system is called a guide to (F,G). Our main results are: the characterization of the step system of a cycle, the characterization of guides for spanning trees and hamiltonian cycles

Unterbrechungstolerante Fahrzeugkommunikation im öffentlichen Personennahverkehr

Communication systems play an important role in the efficient operation of public transport networks. Recently, traditional voice-centric real-time communication is complemented and often replaced by data-centric asynchronous machine-to-machine communication. Disruption tolerant networking in combination with license-exempt high bandwidth technologies have the potential to reduce infrastructure investments and operating costs for such applications, because a continuous end-to-end connectivity is no longer required. In this thesis the feasibility of such a system is investigated and confirmed. First, realistic use-cases are introduced and the requirements to the communication system are analyzed. Then the channel characteristics of several WLAN-based technologies are experimentally evaluated in real public transport scenarios. Since the results are promising, the next step is gaining a deeper understanding of the special mobility properties in public transport networks. Therefore, we analyze existing traces as well as our own newly acquired trace. Our trace features additional operator meta-data that is not available for existing traces, and we report on unexpected properties that have not been quantified before. Then the trace is combined with the experimentally obtained channel parameters in order to analyze the characteristics of inter-vehicle contacts. We present the statistical distribution of situation-specific contact events and the impact of radio range on contact capacity. Then results of all steps above are used to propose a routing scheme that is optimized for public transport networks. In the final simulation-based evaluation we show that this router outperforms previously proposed algorithms.Kommunikationssysteme leisten einen wichtigen Beitrag zum effizienten Betrieb des öffentlichen Personennahverkehrs. Seit einigen Jahren wird dabei der Sprechfunk zunehmend durch asynchronen M2M-Datenfunk ergänzt und in vielen Anwendungsgebieten sogar vollständig ersetzt. Die Kombination aus unterbrechungstoleranten Netzwerken und lizenzfreien Drahtlostechnologien birgt ein erhebliches Potential zur Reduzierung von Infrastrukturinvestitionen und Betriebskosten, da für diese Anwendungen eine dauerhafte Ende-zu-Ende Verbindung nicht mehr erforderlich ist. In dieser Arbeit wird die Machbarkeit eines solchen Systems untersucht und belegt. Zunächst werden dazu Anwendungsfälle vorgestellt und deren Anforderungen an das Kommunikationssystem analysiert. Dann werden die Kanalcharakteristika mehrerer WLAN-Technologien im realen ÖPNV-Umfeld experimentell ermittelt und bewertet. Auf Grundlage der erfolgversprechenden Ergebnisse werden im nächsten Schritt die besonderen Mobilitätseigenschaften von ÖPNV-Netzen untersucht. Zu diesen Zweck analysieren wir existierende und eigene, neu aufgezeichnete Bewegungsdaten von ÖPNV-Fahrzeugen. Unsere Daten enthalten dabei zusätzliche Metadaten der Verkehrsbetriebe, die zuvor nicht verfügbar waren, so dass wir unerwartete Effekte beschreiben und erstmals quantifizieren können. Anschließend werden die Bewegungsdaten mit den zuvor experimentell erfassten Kanaleigenschaften kombiniert, um so die Kommunikationskontakte zwischen den Fahrzeugen genauer zu betrachten. Wir stellen die statistische Verteilung der situationsabhängigen Kontaktereignisse vor, sowie den Einfluss der Funkreichweite auf die Kontaktkapazität. Dann werden die Ergebnisse aller vorhergehenden Schritte verwendet, um ein neues, optimiertes Routingverfahren für ÖPNV-Netze vorzuschlagen. In der simulationsbasierten Evaluation belegen wir, dass dieser Router die Leistung bisher bekannter Verfahren übertrifft

The Role Of The Nmda Receptor In Shaping Cortical Activity During Development

Currently, it is estimated that neuropsychiatric disorders will affect 20-25% of humans in their lifetime. These disorders are a major cause of mortality, suffering, and economic cost to society. Within this broad class, neurodevelopmental disorders (NDDs), including intellectual disability, autism spectrum disorder, and schizophrenia, are estimated to affect 2-5% percent of the world population. Devastatingly, we lack fundamental treatments for NDDs, which have proved some of the most imposing disorders to understand scientifically. The challenge is twofold: first, NDDs affect the most complex aspects of human cognition; second, pathogenesis begins early in neural circuit development, but we lack predictive biomarkers before overt behavioral deficits are apparent. Although we have identified many genes associated with these disorders, how underlying genetic disruptions lead to pathological neural network development and function remains unclear. The overarching framework of this dissertation is that all NPDs are disorders of distributed neural networks, and pathophysiology must be understood at this level to effectively intervene clinically. The cerebral cortex is necessary for complex human capacities, and cortical dysfunction is hypothesized to be central to the pathophysiology of NDDs. NMDA glutamate receptors (NMDARs) are important for the development of local circuit features in the cortex, for normal neurocognitive function, and are strongly implicated in NDDs. However, the role of NMDARs in the development of the large-scale cortical network dynamics that underly higher cognition has not been well examined. Understanding the role of NMDARs at this network level is critical because large-scale “functional connectivity” patterns are thought to be hallmarks of normal cortical function, are hypothesized to be disrupted in NDDs, and may be detectable in humans using non-invasive neuroimaging or electrophysiology. In the studies presented in this dissertation, I (in collaboration and with the support of my colleagues) tested the role of the NMDAR in shaping large-scale cortical network organization using in vivo widefield imaging of whole cortex spontaneous activity in developing mice. I found that NMDAR function in the lineage that includes cortical excitatory neurons and glia, specifically, was critical for the elaboration of normal cortical activity patterns and dynamic network organization. In the first set of experiments, NMDARs were deleted in glutamatergic excitatory neurons (Emx1-cre+/WT/Grin1f/f ; referred to as EX-NMDAR KO mice) or GABAergic inhibitory neurons (Nkx2.1+/WT/Grin1f/f; referred to as IN-NMDAR KO mice). The developing cortex normally exhibits a diverse range of spatio-temporal patterns, reflecting the emergence of functionally associated sub-networks. In EX-NMDAR KO mice, normal patterns of spontaneous activity were severely disrupted and reduced to a nearly one-dimensional dynamic space dominated by large, cortex-wide events. Interestingly, in IN-NMDAR KO mice, the structure and complexity of spontaneous activity was largely normal. In the next set of experiments, I tested the role of extrinsic thalamic neurotransmission on cortical activity during development. Deleting the vesicular glutamate transporter from thalamic neurons while leaving cortical NMDARs intact (Sert-Cre+/−,vglut1−/−,vglut2fl/fl; referred to as TH-VG KO mice) led to a shift in cortical activity patterns towards large domains of activity, reminiscent of patterns observed in EX-NMDAR KO mice. This manipulation also reduced the dimensionality of cortical activity, though not as severally as in EX-NMDAR KO mice. In a final set of experiments, I tested cortical activity in three established mouse models of mono-genetic causes of NDDs in humans: the FMR1-KO mouse based on Fragile X Syndrome, the CNTNAP2-KO mouse, and the TS2-neo mouse based on Timothy Syndrome. In all three of these mouse models, I found that large-scale cortical activity patterns were largely normal, but there was a statistically significant shift towards reduced cortex-wide synchrony and increased dimensionality of spontaneous activity, which may be consistent with the disconnectivity hypothesis of autism. In a final set of experiments, we tested our hypothesis, based on past literature and our results in EX-NMDAR KO and TH-VG KO mice, that the disruptions in cortical activity was predominantly due to the developmental loss of activity-dependent wiring of circuits. To test the developmental versus acute role of NMDAR function in shaping cortical activity, I blocked NMDAR pharmacologically in wild-type mice. I found that acute NMDAR blockade shifted cortical activity to a restricted dynamic space similar to that observed in EX-NMDAR KO mice and more extreme than that observed in TH-VG KO mice. These results strongly reinforce the critical role of NMDAR in shaping cortical activity during development, and suggest that a substantial component of that may be through NMDAR’s role in synaptic transmission and moment to moment cortex-wide circuit function. Overall, these results provide critical insight into the role of NMDARs and the glutamatergic system in cortical network functional organization during development. Specifically, they highlight the essential role of NMDARs in excitatory neurons on the functional connectivity and dynamic repertoire of the cortical network during development. These results make novel contribution to our understanding of how NMDARs may contribute to the pathophysiology of NDDs. Specifically, they contribute powerful new insight into to a critical mechanistic question about the cell-specific role of NMDARs in the pathophysiology of schizophrenia and the mechanisms of NMDAR antagonists, which have transformed psychiatry recently due to their rapid-acting anti-depressant and anti-suicidal properties. Furthermore, they identify a patterns of large-scale network dysfunction that might be detectable in humans using noninvasive functional imaging or electrophysiology

Starting the journey towards manufacturing excellence : MX Start. Innovation report

Manufacturing matters. It matters because of the economic contribution it provides in terms of wealth generation, employment and exports. The manufacturing industry in the United Kingdom can be strengthened. The opportunity for improvement includes closing the productivity gap between other countries, encouraging innovation and developing the skills of the workforce, in order to be globally competitive, drive growth and to help reduce the trade deficit. Critical to exploiting these opportunities, and to the success of the industry, is the adoption of best practice. Existing support for manufacturing improvement can be costly, difficult to access or dependent on input from external experts. This support therefore is not readily accessible to every manufacturing company. There are also a number of quality and performance awards available, however these are predominantly focused on recognising success rather than on how this success can be attained. This research fulfils the gap by providing widely accessible support for manufacturing companies that is focused on helping them to improve. The support provided helps companies to identify and adopt relevant best practices. This research work adapted a product evaluation framework to develop MX Start, a process that supports manufacturing companies to start their improvement journey towards manufacturing excellence. MX Start was developed following a review of the definition of Manufacturing Excellence, a needs assessment of the opportunity, analysis of best practice dissemination strategies, comparative analysis of existing tools and a review of effective self assessment and feedback principles. MX Start provides an easy to use, free of charge, web based system that facilitates manufacturing companies to start their excellence journey. It enables manufacturers to benchmark themselves against best practice in order to gain a greater understanding of what excellence entails, and to enable improvement areas to be identified. This is then supported with a report that helps companies to prioritise the improvement opportunities and provides feedback to then help them make these improvements. The combination of the free of charge, widely accessible, self-directed system that is solely concerned with supporting and encouraging companies to improve, is the basis of the innovation of this work. MX Start has demonstrated impact to the manufacturing industry through a pilot and on-going work with the Manufacturing Advisory Service (MAS). As part of the pilot, over two hundred companies used the process to conduct diagnostic activities to define areas for improvement, and identify where and how they could implement best practices. As a result, MAS in the West Midlands have adopted the tool and supported further developments of this research. This has increased the opportunity for MX Start to help companies progress on their excellence journey and therefore, help support the manufacturing industry to improve. An evaluation of MX Start by companies and manufacturing experts, found that the tool was easy to understand and use, and that it helped companies to identify, and be motivated, to make improvements. The web based system lends itself to further development. In addition to the assessment and report elements of MX Start, the website contains a resource library. The resources contain more information and guidance. The opportunity for the future is to expand this library and build a comprehensive database of support. This would increase the ability of MX Start to support manufacturers to exploit the improvement opportunities to strengthen the competitiveness of the manufacturing industry

Semantic-based framework for the generation of travel demand

Traffic and transportation have a wide-ranging impact on the daily lives of the human population and society. Activity-based travel demand generation models and traffic simulators are tools that have been developed to investigate traffic and transport problems and assist in developing solutions. The closer modelling of human behaviour, the emergence of new technologies and the availability of more detailed datasets is leading to greater modelling complexity. The robustness of conclusions in investigations is supported by comparison of multiple techniques and models yet variations in the platform, data requirements and dataset availability present barriers to their breadth. This thesis investigates the development of a Semantic Web framework for activity-based travel demand generation. It is proposed that the application of a knowledge-based approach and development of an orchestrating framework will enable a loosely coupled modular architecture. This approach will reduce the burden in preparing and accessing datasets through the construction of a platform-independent knowledge-base and facilitate switching between modules and datasets. The principal contributions of this work are the application of a knowledge-based approach to travel demand generation; the development of a Semantic-based framework to control the configuration of the process and the design; and demonstration of the Semantic based framework through the implementation and evaluation of the modular travel demand generation process, including integration with two third-party traffic simulators. The investigation found that the proposed approach can be successfully applied to model and control the travel demand generation process. Multiple configurations were explored, including utilising network communications, and found that this had a noticeable impact on execution duration but also the potential for mitigation through distributed computing. This presents the opportunity for an online infrastructure of datasets and module implementations for travel demand generation that users can select and access through the framework. This infrastructure would remove the need for ad hoc interfaces; data format conversion or platform dependence to facilitate the process of traffic modelling becoming quicker and more robust