Large Scale Dynamic Molecular Modelling of Metal Oxide Nanoparticles in Engineering and Biological Fluids

Nanoparticles (NP) offer great merits over controlling thermal, chemical and physical properties when compared to their micro-sized counterparts. The effectiveness of the dispersion of the NP is the key aspect of the applications in nanotechnology. The project studies the characterization and modification of functional NPs aided by the means of large scale molecular thermal dynamic computerized dispersing simulations, in the level of Nanoclusters (NC). Carrying out NP functionality characterisation in fluids can be enhanced, and analysed through computational simulation based on their interactions with fluidic media; in terms of thermo-mechanical, dynamic, physical, chemical and rheological properties. From the engineering perspective, effective characterizations of the nanofluids have also been carried out based on the particles sizes and particle-fluids Brownian motion (BM) theory. The study covered firstly, investigation of the pure CuO NP diffusion in water and hydrocarbon fluids, secondly, examination of the modified CuO NP diffusion in water. In both cases the studies were put under experiments and simulations for data collection and comparison. For simulation the COMPASS forcefield, smoothed particle hydrodynamic potential (SPH) and discrete particle dynamics potential (DPD) were implemented through the system. Excellent prediction of BM, Van der Waals interaction, electrostatic interaction and a number of force-fields in the system were exploited. The experimental results trend demonstrated high coherence with the simulation results. At first the diffusion coefficient was found to be 1.7e-8m2/s in the study of CuO NC in water based fluidic system. Secondly highly concurrent simulation results (i.e. data for viscosity and thermal conductivity) have been computed to experimental coherence. The viscosity trend of MD simulation and experimental results show a high level of convergence for temperatures between 303-323K. The simulated thermal conductivity of the water-CuO nanofluid was between 0.6—0.75W•m−1•K−1, showing a slight increase following a rise in temperature from 303 to 323 K. Moreover, the alkane-CuO nanofluid experimental and simulated work was also carried out, for analysing the thermo-physical quantities. The alkane-CuO nanofluid viscosity was found 0.9—2.7mpas and thermal conductivity is between 0.1—0.4W•m−1•K−1. Finally, the successful modification of the NPs on experimental and simulation platform has been analysed using different characterization variables. Experimental modification data has been quantified by using Fourier Transformation Infrared (FTIR) peak response, from particular ranges of interest i.e. 1667-1609cm-1 and 1668-1557cm-1. These FTIR peaks deduced Carboxylate attachment on the surface of NPs. Later, MD simulation was approached to mimic experimental setup of modification chemistry and similar agglomerations were observed as during experimental conditions. However, this approach has not been presented before; therefore this study has a significant impact on describing the agglomeration of modified NPs on simulation and experimental basis. Henceforth, the methodology established for metal oxide nanoparticle dispersion simulation is a novelty of this work

Mechanism Determination of the Effects of Pancratistatin on Model Mitochondrial Membranes

Apoptosis is programmed cell death that is essential for physiological development and tissue homeostasis. From a biochemical standpoint, this process can be exploited to target and eliminate specific cell types, such as cancer cells. Pancratistatin (PST) is an antiviral alkaloid metabolite that has demonstrated directed apoptotic action on various human cancer cell lines while having minimal/no toxic effect on normal cells. However, PST’s mechanism of action remains uncertain. To better understand how PST induces its anti-cancer action various biophysical techniques were employed. Neutron spin-echo (NSE) spectroscopy was used to examine how PST impacted the bending fluctuations of large unil- amellar vesicles (LUVs) bearing a lipid composition meant to mimic the inner mitochondrial membranes (IMM). The IMM mimic was composed of three lipids: 1-palmitoyl-2-oleoyl-sn- glycero-3-phosphocholine (POPC), 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine (POPE), and tetraoleoyl cardiolipin (TOCL). Small-angle neutron and X-ray scattering (SANS and SAXS) were utilized to determine how PST influences membranes structure. Molecular dynamics (MD) simulations were used to compliment the data gathered from the scattering experiments, while also examining lipid chain order, PST localization and the PST-lipid relationships. The results show that PST has a condensing effect the IMM mimic. This thesis elaborates on the possible implications of this finding with regard to the nature of PST’s interaction with the IMM mimic and proposes a hypothesis for the anti-cancer mechanism of PST

Fish4Knowledge: Collecting and Analyzing Massive Coral Reef Fish Video Data

This book gives a start-to-finish overview of the whole Fish4Knowledge project, in 18 short chapters, each describing one aspect of the project. The Fish4Knowledge project explored the possibilities of big video data, in this case from undersea video. Recording and analyzing 90 thousand hours of video from ten camera locations, the project gives a 3 year view of fish abundance in several tropical coral reefs off the coast of Taiwan. The research system built a remote recording network, over 100 Tb of storage, supercomputer processing, video target detection and

Semantic In-Network Complex Event Processing for an Energy Efficient Wireless Sensor Network

Wireless Sensor Networks (WSNs) consist of spatially distributed sensor nodes that perform monitoring tasks in a region and the gateway nodes that provide the acquired sensor data to the end user. With advances in the WSN technology, it has now become possible to have different types of sensor nodes within a region to monitor the environment. This provides the flexibility to monitor the environment in a more extensive manner than before. Sensor nodes are severely constrained devices with very limited battery sources and their resource scarcity remains a challenge. In traditional WSNs, the sensor nodes are used only for capturing data that is analysed later in more powerful gateway nodes. This continuous communication of data between sensor nodes and gateway nodes wastes energy at the sensor nodes, and consequently, the overall network lifetime is greatly reduced. Existing approaches to reduce energy consumption by processing at the sensor node level only work for homogeneous networks. This thesis presents a sensor node architecture for heterogeneous WSNs, called SEPSen, where data is processed locally at the sensor node level to reduce energy consumption. We use ontology fragments at the sensor nodes to enable data exchange between heterogeneous sensor nodes within the WSN. We employ a rule engine based on a pattern matching algorithm for filtering events at the sensor node level. The event routing towards the gateway nodes is performed using a context-aware routing scheme that takes both the energy consumption and the heterogeneity of the sensor nodes into account. As a proof of concept, we present a prototypical implementation of the SEPSen design in a simulation environment. By providing semantic support, in-network data processing capabilities and context-aware routing in SEPSen, the sensor nodes (1) communicate with each other despite their different sensor types, (2) filter events at the their own level to conserve the limited sensor node energy resources and (3) share the nodes' knowledge bases for collaboration between the sensor nodes using node-centric context-awareness in changing conditions. The SEPSen prototype has been evaluated based on a test case for water quality management. The results from the experiments show that the energy saved in SEPSen reaches almost 50% by processing events at the sensor node level and the overall network lifetime is increased by at least a factor of two against the shortest-path-first (Min-Hop) routing approach

Digital Classical Philology

The buzzwords “Information Society” and “Age of Access” suggest that information is now universally accessible without any form of hindrance. Indeed, the German constitution calls for all citizens to have open access to information. Yet in reality, there are multifarious hurdles to information access – whether physical, economic, intellectual, linguistic, political, or technical. Thus, while new methods and practices for making information accessible arise on a daily basis, we are nevertheless confronted by limitations to information access in various domains. This new book series assembles academics and professionals in various fields in order to illuminate the various dimensions of information's inaccessability. While the series discusses principles and techniques for transcending the hurdles to information access, it also addresses necessary boundaries to accessability.This book describes the state of the art of digital philology with a focus on ancient Greek and Latin. It addresses problems such as accessibility of information about Greek and Latin sources, data entry, collection and analysis of Classical texts and describes the fundamental role of libraries in building digital catalogs and developing machine-readable citation systems

Visuelle Suchanfragen auf graphbasierten Datenstrukturen

Die Menge an verfügbaren Daten nimmt stetig zu. Durch standardisierte Datenformate wird die Verknüpfung verschiedener Datenquellen und dadurch auch die Zusammenführung unterschiedlicher Datenelemente je nach Anwendungszweck ermöglicht. Dies führt wiederum zu noch umfassenderen Datenbeständen, in denen die eigentlich gewünschten Informationen teilweise nur schwer gefunden werden können. Handelt es sich bei den Daten um unstrukturierte oder gleichförmige Informationen, so beschränken sich Suchmöglichkeiten auf die Suche nach Übereinstimmungen von Mustern mit Datenelementen oder Teilen davon - beispielsweise Zeichenketten oder regulären Ausdrücken, die mit Teilen von textuellen Datenelementen übereinstimmen. In zunehmendem Maß stehen jedoch auch strukturierte Daten zur Verfügung. Bei diesen wird entweder von Anfang an zwischen unterschiedlichen Facetten pro Datenelement unterschieden, oder es wurden ursprünglich unstrukturierte Daten entsprechend angereichert. Da die einzelnen Facetten auch Verknüpfungen zu anderen Datenelementen darstellen können, entstehen hierbei Graphstrukturen, welche sich für Ansätze der facettierten Suche eignen. Eine Interoperabilität zwischen Datenquellen wird hier unter anderem über die Konzepte und Techniken des Semantic Web erreicht. Zahlreiche Arbeiten haben sich mit der Darstellung der gesamten Datenmengen als Übersicht oder von festgelegten Ausschnitten der Datenmengen im Detail auseinandergesetzt. Jedoch ist das Auffinden bestimmter Daten nach wie vor ein Problem. Die Schwierigkeit liegt dabei darin, die Suchkriterien präzise auszudrücken. Da sich zwischen den einzelnen Kriterien komplexe Zusammenhänge ergeben können, bietet sich auch hier genau wie bei der Übersicht der Datenmengen eine visuelle Darstellung an. Eine Besonderheit dieses Einsatzszenarios für Visualisierungen besteht darin, dass nicht zwangsläufig Daten vorliegen. Statt dessen muss die Visualisierung auch ohne verfügbare Daten die konzeptuelle Idee einer Suchanfrage ausdrücken. Frühere Arbeiten zu diesem Problem befassen sich mit der visuellen Repräsentation von Suchanfragen und Filterausdrücken in Bezug auf relationale Datenbanken und Objektdatenbanken. Viele neuere Arbeiten gehen vermehrt auch auf den Kontext des Semantic Webs ein. Einige dieser Konzepte sind jedoch nicht auf abstrakte Weise klar definiert. Bei komplexeren Anfragen treten zum Teil auch Skalierungsprobleme auf. Zudem wurde bisher kaum betrachtet, wie sich unterschiedliche Konzepte miteinander in Verbindung bringen lassen, um die Vorteile aus unterschiedlichen Anfragevisualisierungen nutzen zu können. Diese Dissertation adressiert die beschriebenen Probleme und stellt sechs Konzepte für die visuelle Darstellung von Suchanfragen vor. Es wird sowohl auf Visualisierungen für allgemeine Einsatzzwecke - also für die Filterung beliebiger strukturierter Informationen -, als auch für spezielle Domänen oder Arten von Informationen eingegangen. Bestehende Ansätze wurden teilweise auf die Gegebenheiten graphbasierter Datenstrukturen angepasst. Ebenso werden neue Ansätze präsentiert, die gezielt auf diese Art von Datenstrukturen ausgelegt sind. Dazu wird jeweils erörtert, inwiefern sich die Anfragevisualisierungen auch ohne Vorhandensein einer zu filternden Datensammlung einsetzen lassen. Zudem wird erklärt, wie bei Vorhandensein einer solchen eine Vorschau auf die Ergebnisse des Filtervorgangs gewährt werden kann. Abschließend werden Verbindungsmöglichkeiten der unterschiedlichen Visualisierungskonzepte präsentiert. Dieser Verbindungsansatz eignet sich dazu, beliebige Anfragevisualisierungen systematisch miteinander zu kombinieren. Mit dem Verbindungskonzept können Benutzer verschiedene Bestandteile einer Anfrage mittels unterschiedlicher Visualisierungskonzepte ausdrücken, um gleichzeitig von den Stärken unterschiedlicher Anfragevisualisierungen zu profitieren. Auf diese Weise können nun Anfragen visuell definiert und dargestellt werden, die sowohl komplexe Bedingungen als auch komplexe Zusammenhänge zwischen den Bedingungen aufweisen, ohne die visuelle Übersicht über einen dieser Aspekte zu verlieren.The total amount of available data is steadily increasing. Standardized data formats allow for connecting different data sources, which can include merging of different data items depending on the use case. This creates even more comprehensive datasets that render finding a particular piece of information difficult. If the data consist of unstructured of homogenous information, searching can only be done by matching patterns with data items or parts thereof - for instance, character strings or regular expressions that match parts of textual data items. However, the availability of structured data is increasing. This kind of data is either stored as distinct facets of each data item from the outset, or originally unstructured data has been enriched to form a structure. As each facet can indicate a link to another data item, the entire dataset forms a graph that is suitable for faceted search conepts. At this point, some interoperability across data sources can be achieved by employing Semantic Web approaches and techniques. Numerous works have attempted to visualize an overview of the entire dataset, or details of a particular excerpt of the dataset. Finding specific data remains a problem, however, as the precise specification of search criteria is difficult. As these criteria can be connected in complex ways, just like the overview of datasets, this issue lends itself to using visual representations. A special trait of this application of visualization is the possible absence of any data. Instead, the visualization must be capable of conveying the conceptual idea of a search query without displaying any data. Former works related to this problem focused on the visual representation of search queries and filter expressions for relational and object-oriented databases. More recent works increasingly address a Semantic Web context. Various of these concepts, however, lack a clear abstract definition. Also, scalability issues appear in the case of complex queries. Furthermore, little attention was paid to how to connect several concepts in order to combine advantages of different query visualizations. This dissertation considers the described problems and presents six concepts for query visualization. Both generic visualizations - that is, for filtering any kind of structured data - and domain-specific or type-specific visualizations are addressed. In part, existing approaches have been adapted to the particularities of graph-based data structures. Likewise, several new approaches specifically designed for this kind of data are presented. For each of these concepts, the necessity of a dataset is discussed. Moreover, options for providing a preview on query results from such a dataset, if available, are considered. Finally, ways for connecting the query visualization concepts are presented. This connection approach is suitable for systematically linking together arbitrary query visualizations. By means of the connection approach, users can express different parts of a query using different visualization concepts, in order to benefit from the advantages of several query visualizations at a time. Like this, queries that include complex criteria as well as complex relations between criteria can now be defined and displayed visually without losing the visual overview of any of these aspects

Ubiquitous User Modeling

More and more interactions take place between humans and mobile or connected IT-systems in daily life. This offers a great opportunity, especially to user modeling, to reach better adaptation with ongoing evaluation of user behavior. This work develops a complete framework to realize the newly defined concept of ubiquitous user modeling. The developed tools cover methods for the uniform exchange and the semantic integration of partial user models. They also account for the extended needs for privacy and the right of every human for introspection and control of their collected data. The SITUATIONALSTATEMENTS and the exchange language USERML have been developed on the syntactical level, while the general user model ontology GUMO and the UBISWORLD ontology have been developed on the semantical level. A multilevel conflict resolution method, which handles the problem of contradictory statements, has been implemented together with a web-based user model service, such that the road capability and the scalability can be proven with this approach.Immer häufiger auftretende Interaktionen im täglichen Leben zwischen Menschen und vernetzten oder mobilen IT-Systemen bieten insbesondere für die Benutzermodellierung eine große Chance, durch ständige Evaluation des Benutzerverhaltens verbesserte Adaptionsleistungen zu erzielen. Die vorliegende Arbeit entwickelt ein komplettes Rahmensystem, um dieses neu definierte Konzept der ubiquitären Benutzermodellierung zu realisieren. Die erarbeiteten Werkzeuge umfassen Methoden zum einheitlichen Austausch und zur semantischen Integration von partiellen Benutzermodellen. Sie berücksichtigen aber auch die erhöhten Anforderungen an die Privatsphäre, sowie das Recht der Menschen auf Introspektion und Kontrolle über die erhobenen Daten. Auf syntaktischer Ebene werden die situationsbeschreibenden Aussagen sowie die Austauschsprache UserML entworfen. Auf semantischer Ebene werden die allgemeine Benutzermodell-Ontologie GUMO und die UBISWELT-Ontologie entwickelt. Ein mehrstufiger Konfliktlösungsmechanismus, der das Problem sich widersprechender Aussagen bearbeitet, wird zusammen mit einem webbasierten Benutzermodell-Service implementiert, sodass die Praxistauglichkeit und die Skalierbarkeit dieses Ansatzes an mehreren Beispielen gezeigt werden kann

EG-ICE 2021 Workshop on Intelligent Computing in Engineering

The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

Affordances and limitations of algorithmic criticism

Humanities scholars currently have access to unprecedented quantities of machine-readable texts, and, at the same time, the tools and the methods with which we can analyse and visualise these texts are becoming more and more sophisticated. As has been shown in numerous studies, many of the new technical possibilities that emerge from fields such as text mining and natural language processing can have useful applications within literary research. Computational methods can help literary scholars to discover interesting trends and correlations within massive text collections, and they can enable a thoroughly systematic examination of the stylistic properties of literary works. While such computer-assisted forms of reading have proven invaluable for research in the field of literary history, relatively few studies have applied these technologies to expand or to transform the ways in which we can interpret literary texts. Based on a comparative analysis of digital scholarship and traditional scholarship, this thesis critically examines the possibilities and the limitations of a computer-based literary criticism. It argues that quantitative analyses of data about literary techniques can often reveal surprising qualities of works of literature, which can, in turn, lead to new interpretative readings