The multistage crystallization of zircon in calc-alkaline granitoids : U-Pb age constraints on the timing of Variscan tectonic activity in SW Iberia

CL imaging and U–Th–Pb data for a population of zircons from two of the Évora Massif granitoids (Ossa-Morena Zone, SW Iberia) show that both calc-alkaline granitoids have zircon populations dominated by grains with cores and rims either showing or not showing differences in Th/U ratio, and having ages in the range ca. 350–335 Ma (Early Carboniferous). Multistage crystallization of zircon is revealed in two main growth stages (ca. 344–342 Ma and ca. 336–335 Ma), well represented by morphologically complex zircons with cores and rims with different ages and different Th/U ratios that can be explained by: (1) crystallization from melts with different compositions (felsic peraluminous to felsic-intermediate metaluminous; 0.001 Th/U ratio < 0.5) and (2) transient temperature fluctuations in a system where anatectic felsic melts periodically underwent injection of more mafic magmas at higher temperatures. The two studied calc-alkaline granitoids do not include inherited zircons (pre-Carboniferous), probably because they were formed at the highest grade of metamorphism (T 837 °C; granulite facies) and/or because they were derived from inheritance-poor felsic and mafic rocks from a previous cycle, as suggested by the internal structures of zircon cores. These Variscan magmatic rocks with crystallization ages estimated at ca. 336–335 Ma are spatially and temporally related to high-temperature metamorphism, anatexis, processes of interaction between crustal- and mantle-derived magmas and intra-orogenic extension that acted in SW Iberia during the Early Carboniferous.

Microfluidic platforms for the characterization of in meso membrane protein crystallization

Membrane proteins, which reside in the membranes of cells, play a critical role in many important biological processes including cellular signaling, immune response, and material and energy transduction. Because of their key role in maintaining the environment within cells and facilitating intercellular interactions, understanding the function of these proteins is of tremendous medical and biochemical significance. Indeed, the malfunction of membrane proteins has been linked to numerous diseases including diabetes, cirrhosis of the liver, cystic fibrosis, cancer, Alzheimer's disease, hypertension, epilepsy, cataracts, tubulopathy, leukodystrophy, Leigh syndrome, anemia, sensorineural deafness, and hypertrophic cardiomyopathy.1-3 However, the structure of many of these proteins and the changes in their structure that lead to disease-related malfunctions are not well understood. Additionally, at least 60% of the pharmaceuticals currently available are thought to target membrane proteins, despite the fact that their exact mode of operation is not known.4-6 Developing a detailed understanding of the function of a protein is achieved by coupling biochemical experiments with knowledge of the structure of the protein. Currently the most common method for obtaining three-dimensional structure information is X-ray crystallography. However, no a priori methods are currently available to predict crystallization conditions for a given protein.7-14 This limitation is currently overcome by screening a large number of possible combinations of precipitants, buffer, salt, and pH conditions to identify conditions that are conducive to crystal nucleation and growth.7,9,11,15-24 Unfortunately, these screening efforts are often limited by difficulties associated with quantity and purity of available protein samples. While the two most significant bottlenecks for protein structure determination in general are the (i) obtaining sufficient quantities of high quality protein samples and (ii) growing high quality protein crystals that are suitable for X-ray structure determination,7,20,21,23,25-47 membrane proteins present additional challenges. For crystallization it is necessary to extract the membrane proteins from the cellular membrane. However, this process often leads to denaturation. In fact, membrane proteins have proven to be so difficult to crystallize that of the more than 66,000 structures deposited in the Protein Data Bank,48 less than 1% are for membrane proteins, with even fewer present at high resolution (< 2Å)4,6,49 and only a handful are human membrane proteins.49 A variety of strategies including detergent solubilization50-53 and the use of artificial membrane-like environments have been developed to circumvent this challenge.43,53-55 In recent years, the use of a lipidic mesophase as a medium for crystallizing membrane proteins has been demonstrated to increase success for a wide range of membrane proteins, including human receptor proteins.54,56-62 This in meso method for membrane protein crystallization, however, is still by no means routine due to challenges related to sample preparation at sub-microliter volumes and to crystal harvesting and X-ray data collection. This dissertation presents various aspects of the development of a microfluidic platform to enable high throughput in meso membrane protein crystallization at a level beyond the capabilities of current technologies. Microfluidic platforms for protein crystallization and other lab-on-a-chip applications have been well demonstrated.9,63-66 These integrated chips provide fine control over transport phenomena and the ability to perform high throughput analyses via highly integrated fluid networks. However, the development of microfluidic platforms for in meso protein crystallization required the development of strategies to cope with extremely viscous and non-Newtonian fluids. A theoretical treatment of highly viscous fluids in microfluidic devices is presented in Chapter 3, followed by the application of these strategies for the development of a microfluidic mixer capable of preparing a mesophase sample for in meso crystallization at a scale of less than 20 nL in Chapter 4. This approach was validated with the successful on chip in meso crystallization of the membrane protein bacteriorhodopsin. In summary, this is the first report of a microfluidic platform capable of performing in meso crystallization on-chip, representing a 1000x reduction in the scale at which mesophase trials can be prepared. Once protein crystals have formed, they are typically harvested from the droplet they were grown in and mounted for crystallographic analysis. Despite the high throughput automation present in nearly all other aspects of protein structure determination, the harvesting and mounting of crystals is still largely a manual process. Furthermore, during mounting the fragile protein crystals can potentially be damaged, both from physical and environmental shock. To circumvent these challenges an X-ray transparent microfluidic device architecture was developed to couple the benefits of scale, integration, and precise fluid control with the ability to perform in situ X-ray analysis (Chapter 5). This approach was validated successfully by crystallization and subsequent on-chip analysis of the soluble proteins lysozyme, thaumatin, and ribonuclease A and will be extended to microfluidic platforms for in meso membrane protein crystallization. The ability to perform in situ X-ray analysis was shown to provide extremely high quality diffraction data, in part as a result of not being affected by damage due to physical handling of the crystals. As part of the work described in this thesis, a variety of data collection strategies for in situ data analysis were also tested, including merging of small slices of data from a large number of crystals grown on a single chip, to allow for diffraction analysis at biologically relevant temperatures. While such strategies have been applied previously,57,59,61,67 they are potentially challenging when applied via traditional methods due to the need to grow and then mount a large number of crystals with minimal crystal-to-crystal variability. The integrated nature of microfluidic platforms easily enables the generation of a large number of reproducible crystallization trials. This, coupled with in situ analysis capabilities has the potential of being able to acquire high resolution structural data of proteins at biologically relevant conditions for which only small crystals, or crystals which are adversely affected by standard cryocooling techniques, could be obtained (Chapters 5 and 6). While the main focus of protein crystallography is to obtain three-dimensional protein structures, the results of typical experiments provide only a static picture of the protein. The use of polychromatic or Laue X-ray diffraction methods enables the collection of time resolved structural information. These experiments are very sensitive to crystal quality, however, and often suffer from severe radiation damage due to the intense polychromatic X-ray beams. Here, as before, the ability to perform in situ X-ray analysis on many small protein crystals within a microfluidic crystallization platform has the potential to overcome these challenges. An automated method for collecting a "single-shot" of data from a large number of crystals was developed in collaboration with the BioCARS team at the Advanced Photon Source at Argonne National Laboratory (Chapter 6). The work described in this thesis shows that, even more so than for traditional structure determination efforts, the ability to grow and analyze a large number of high quality crystals is critical to enable time resolved structural studies of novel proteins. In addition to enabling X-ray crystallography experiments, the development of X-ray transparent microfluidic platforms also has tremendous potential to answer other scientific questions, such as unraveling the mechanism of in meso crystallization. For instance, the lipidic mesophases utilized during in meso membrane protein crystallization can be characterized by small angle X-ray diffraction analysis. Coupling in situ analysis with microfluidic platforms capable of preparing these difficult mesophase samples at very small volumes has tremendous potential to enable the high throughput analysis of these systems on a scale that is not reasonably achievable using conventional sample preparation strategies (Chapter 7). In collaboration with the LS-CAT team at the Advanced Photon Source, an experimental station for small angle X-ray analysis coupled with the high quality visualization capabilities needed to target specific microfluidic samples on a highly integrated chip is under development. Characterizing the phase behavior of these mesophase systems and the effects of various additives present in crystallization trials is key for developing an understanding of how in meso crystallization occurs. A long term goal of these studies is to enable the rational design of in meso crystallization experiments so as to avoid or limit the need for high throughput screening efforts. In summary, this thesis describes the development of microfluidic platforms for protein crystallization with in situ analysis capabilities. Coupling the ability to perform in situ analysis with the small scale, fine control, and the high throughput nature of microfluidic platforms has tremendous potential to enable a new generation of crystallographic studies and facilitate the structure determination of important biological targets. The development of platforms for in meso membrane protein crystallization is particularly significant because they enable the preparation of highly viscous mixtures at a previously unachievable scale. Work in these areas is ongoing and has tremendous potential to improve not only current the methods of protein crystallization and crystallography, but also to enhance our knowledge of the structure and function of proteins which could have a significant scientific and medical impact on society as a whole. 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Response toolkit to provide an active response against intrusions using Ontology-Based IRS

Los sistemas de respuesta activa tienen por objetivo ejecutar una respuesta en contra de una intrusión de forma automática. Sin embargo, ejecutar una respuesta automáticamente no es una tarea trivial ya que el costo de ejecutar una respuesta podría ser más grande que el efecto que cause la intrusión propiamente dicha. También, el sistema debe contar con un amplio conjunto de acciones de respuesta y un algoritmo que seleccione la respuesta óptima. Este artículo propone un toolkit de respuestas que será integrado a un IRS basado en Ontologías para permitir la ejecución automática de la mejor respuesta cuando una intrusión es detectada. Se presenta un conjunto de respuestas basadas en host y basadas en red que pueden ser ejecutadas por el IRS, dicha ejecución es llevada a cabo mediante agentes basados en plugins que han sido distribuidos en la red. Finalmente, se realiza la verificación del sistema propuesto, tomando como caso de uso un ataque de defacement obteniéndose resultados satisfactorios.

An ontology for risk management of digital collections

Maintaining accessibility to and understanding of digital information over time is a complex challenge that often requires contributions and interventions from a variety of individuals and organizations. The processes of preservation planning and evaluation are fundamentally implicit and share similar complexity. Both demand comprehensive knowledge and understanding of every aspect of to-be-preserved content and the contexts within which preservation is undertaken. Consequently, means are required for the identification, documentation and association of those properties of data, representation and management mechanisms that in combination lend value, facilitate interaction and influence the preservation process. These properties may be almost limitless in terms of diversity, but are integral to the establishment of classes of risk exposure, and the planning and deployment of appropriate preservation strategies. We explore several research objectives within the course of this thesis. Our main objective is the conception of an ontology for risk management of digital collections. Incorporated within this are our aims to survey the contexts within which preservation has been undertaken successfully, the development of an appropriate methodology for risk management, the evaluation of existing preservation evaluation approaches and metrics, the structuring of best practice knowledge and lastly the demonstration of a range of tools that utilise our findings. We describe a mixed methodology that uses interview and survey, extensive content analysis, practical case study and iterative software and ontology development. We build on a robust foundation, the development of the Digital Repository Audit Method Based on Risk Assessment. We summarise the extent of the challenge facing the digital preservation community (and by extension users and creators of digital materials from many disciplines and operational contexts) and present the case for a comprehensive and extensible knowledge base of best practice. These challenges are manifested in the scale of data growth, the increasing complexity and the increasing onus on communities with no formal training to offer assurances of data management and sustainability. These collectively imply a challenge that demands an intuitive and adaptable means of evaluating digital preservation efforts. The need for individuals and organisations to validate the legitimacy of their own efforts is particularly prioritised. We introduce our approach, based on risk management. Risk is an expression of the likelihood of a negative outcome, and an expression of the impact of such an occurrence. We describe how risk management may be considered synonymous with preservation activity, a persistent effort to negate the dangers posed to information availability, usability and sustainability. Risk can be characterised according to associated goals, activities, responsibilities and policies in terms of both their manifestation and mitigation. They have the capacity to be deconstructed into their atomic units and responsibility for their resolution delegated appropriately. We continue to describe how the manifestation of risks typically spans an entire organisational environment, and as the focus of our analysis risk safeguards against omissions that may occur when pursuing functional, departmental or role-based assessment. We discuss the importance of relating risk-factors, through the risks themselves or associated system elements. To do so will yield the preservation best-practice knowledge base that is conspicuously lacking within the international digital preservation community. We present as research outcomes an encapsulation of preservation practice (and explicitly defined best practice) as a series of case studies, in turn distilled into atomic, related information elements. We conduct our analyses in the formal evaluation of memory institutions in the UK, US and continental Europe. Furthermore we showcase a series of applications that use the fruits of this research as their intellectual foundation. Finally we document our results in a range of technical reports and conference and journal articles. We present evidence of preservation approaches and infrastructures from a series of case studies conducted in a range of international preservation environments. We then aggregate this into a linked data structure entitled PORRO, an ontology relating preservation repository, object and risk characteristics, intended to support preservation decision making and evaluation. The methodology leading to this ontology is outlined, and lessons are exposed by revisiting legacy studies and exposing the resource and associated applications to evaluation by the digital preservation community.

Ontology-Based Workflow Design for the Coordination of Homecare Interventions

Part 20: Health and Care Networks

Building an Ontology of Product/Service-Systems: Using a Maritime Case Study to Elicit Classifications and Characteristics

Part 4: Transition Towards Product-Service Systems

Crystallization, preliminary X-ray analysis and molecular-replacement solution of haemoglobin-II from the fish matrinxa (Brycon cephalus)

Haemoglobins constitute a set of proteins with interesting structural and functional properties, especially when the two large animal groups reptiles and fishes are focused on. Here, the crystallization and preliminary X-ray analysis of haemoglobin-II from the South American fish matrinxa (Brycon cephalus) is reported. X-ray diffraction data have been collected to 3.0 Angstrom resolution using synchrotron radiation (LNLS). Crystals were determined to belong to space group P2(1) and preliminary structural analysis revealed the presence of two tetramers in the asymmetric unit. The structure was determined using the standard molecular-replacement technique.

Crystallization and preliminary X-ray diffraction analysis of a eumenine mastoparan toxin: a new class of mast-cell degranulating peptide in the wasp venom

Mastoparans are tetradecapeptides found to be the major component of vespid venoms. A mastoparan toxin isolated from the venom of Anterhynchium flavomarginatum micado has been crystallized and X-ray diffraction data collected to 2.7 Angstrom resolution using a synchrotron-radiation source. Crystals were determined to belong to the space group P6(2)22 (P6(4)22). This is the first mastoparan to be crystallized and will provide further insights into the conformational significance of mastoparan toxins with respect to their potency and activity in G-protein regulation.

Ontology forecasting in scientific literature:semantic concepts prediction based on innovation-adoption priors

The ontology engineering research community has focused for many years on supporting the creation, development and evolution of ontologies. Ontology forecasting, which aims at predicting semantic changes in an ontology, represents instead a new challenge. In this paper, we want to give a contribution to this novel endeavour by focusing on the task of forecasting semantic concepts in the research domain. Indeed, ontologies representing scientific disciplines contain only research topics that are already popular enough to be selected by human experts or automatic algorithms. They are thus unfit to support tasks which require the ability of describing and exploring the forefront of research, such as trend detection and horizon scanning. We address this issue by introducing the Semantic Innovation Forecast (SIF) model, which predicts new concepts of an ontology at time t + 1, using only data available at time t. Our approach relies on lexical innovation and adoption information extracted from historical data. We evaluated the SIF model on a very large dataset consisting of over one million scientific papers belonging to the Computer Science domain: the outcomes show that the proposed approach offers a competitive boost in mean average precision-at-ten compared to the baselines when forecasting over 5 years.

Water sorption-induced crystallization, structural relaxations and strength analysis of relaxation times in amorphous lactose/whey protein systems

Water sorption-induced crystallization, α-relaxations and relaxation times of freeze-dried lactose/whey protein isolate (WPI) systems were studied using dynamic dewpoint isotherms (DDI) method and dielectric analysis (DEA), respectively. The fractional water sorption behavior of lactose/WPI mixtures shown at aw ≤ 0.44 and the critical aw for water sorption-related crystallization (aw(cr)) of lactose were strongly affected by protein content based on DDI data. DEA results showed that the α-relaxation temperatures of amorphous lactose at various relaxation times were affected by the presence of water and WPI. The α-relaxation-derived strength parameter (S) of amorphous lactose decreased with aw up to 0.44 aw but the presence of WPI increased S. The linear relationship for aw(cr) and S for lactose/WPI mixtures was also established with R2 > 0.98. Therefore, DDI offers another structural investigation of water sorption-related crystallization as governed by aw(cr), and S may be used to describe real time effects of structural relaxations in noncrystalline multicomponent solids.

Forms, Foundations, and the Ethos of Foremost: Zen Practice, Epistemology, and Ontology in Reflective Knowledge Organization

In reflecting on the practice of knowledge organization, we tacitly or explicitly root our conceptions of work and its value in some epistemic and ontological foundation. Zen Buddhist philosophy offers a unique set of conceptions vis-à-vis organizing, indexing, and describing documents.When we engage in knowledge organization, we are setting our mind to work with an intention. We intend to make some sort of intervention. We then create a form a realization of an abstraction (like classes or terms) [1], we do this from a foundation of some set of beliefs (epistemology, ontology, and ethics), and because we have to make decisions about what to privilege, we need to decide what is foremost in our minds. We must ask what is the most important thing?Form, foundation, and the ethos of foremost require evoke in our reflection on work number of ethical, epistemic, and ontological concerns that ripple throughout our conceptions of space, “good work”, aesthetics, and moral mandate [2,3]. We reflect on this.

Study of the effectiveness of crystal growth modifiers in the prevention of damage due to crystallization of sodium carbonates in stone artworks

The disintegration of stone materials used in sculpture and architecture due to the crystallization of salts is capable of irreparably damaging artistic objects and historic buildings. A number of phosphonates and carboxylates were tested here as potential crystallization modifiers for sodium carbonate crystallization. Precipitated phases during crystallization induced either by cooling or by evaporation tests were nahcolite (NaHCO3), natron (Na2CO3∙10H2O) and thermonatrite (Na2CO3∙H2O), identified using X-ray diffraction. By using the thermodynamic code PHREEQC and the calculation of the nucleation rate it was demonstrated that nahcolite had to be first phase formed during both tests. The formation of the other phases depended on the experimental conditions under which the two tests were conducted. Nahcolite nucleation is strongly inhibited in the presence of sodium citrate tribasic dihydrate (CA), polyacrylic acid 2100MW (PA) and etidronic acid (HEDP), when the additives are dosed at appropriate concentrations and the pH range of the resulting solution is about 8. Electrostatic attraction generated between the deprotonated organic additives and the cations present in solution appears to be the principal mechanism of additive-nahcolite interaction. Salt weathering tests, in addition to mercury intrusion porosimetry tests allowed to quantify the damage induced by such salts. FESEM observation of both salts grown on calcite single crystals and in limestone blocks subjected to salt crystallization tests allowed to identify the effect of these additives on crystal growth and development. The results show that PA seems to be the best inhibitor, while CA and HEDP, which show similar behaviors, are slightly less effective. The use of such effective crystallization inhibitors may lead to more efficient preventive conservation of ornamental stone affected by crystallization damage due to formation of sodium carbonate crystals.

Empirical ontology design patterns

Knowledge graphs (KGs) and ontologies have been widely adopted for modelling numerous domains. However, understanding the content of an ontology/KG is far from straightforward: existing methods partially address this issue. This thesis is based on the assumption that identifying the Ontology Design Patterns (ODPs) in an ontology or a KG contributes to address this problem. Most times, the reused ODPs are not explicitly annotated, or their reuse is unintentional. Therefore, there is a challenge to automatically identify ODPs in existing ontologies and KGs, which is the main focus of this research work. This thesis analyses the role of ODPs in ontology engineering, through experiences in actual ontology projects, placing this analysis in the context of existing ontology reuse approaches. Moreover, this thesis introduces a novel method for extracting empirical ODPs (EODPs) from ontologies, and a novel method for extracting EODPs from knowledge graphs, whose schemas are implicit. The first method groups the extracted EODPs in clusters: conceptual components. Each conceptual component represents a modelling problem, e.g. representing collections. As EODPs are fragments possibly extracted from different ontologies, some of them will fall in the same cluster, meaning that they are implemented solutions to the same modelling problem. EODPs and conceptual components enable the empirical observation and comparison of modelling solutions to common modelling problems in different ontologies. The second method extracts EODPs from a KG as sets of probabilistic axioms/constraints involving the ontological entities instantiated. These EODPs may support KG inspection and comparison, providing insights on how certain entities are described in a KG. An additional contribution of this thesis is an ontology for annotating ODPs in ontologies and KGs.

Supporting requirement elicitation and ontology testing in knowledge graph engineering

Knowledge graphs and ontologies are closely related concepts in the field of knowledge representation. In recent years, knowledge graphs have gained increasing popularity and are serving as essential components in many knowledge engineering projects that view them as crucial to their success. The conceptual foundation of the knowledge graph is provided by ontologies. Ontology modeling is an iterative engineering process that consists of steps such as the elicitation and formalization of requirements, the development, testing, refactoring, and release of the ontology. The testing of the ontology is a crucial and occasionally overlooked step of the process due to the lack of integrated tools to support it. As a result of this gap in the state-of-the-art, the testing of the ontology is completed manually, which requires a considerable amount of time and effort from the ontology engineers. The lack of tool support is noticed in the requirement elicitation process as well. In this aspect, the rise in the adoption and accessibility of knowledge graphs allows for the development and use of automated tools to assist with the elicitation of requirements from such a complementary source of data. Therefore, this doctoral research is focused on developing methods and tools that support the requirement elicitation and testing steps of an ontology engineering process. To support the testing of the ontology, we have developed XDTesting, a web application that is integrated with the GitHub platform that serves as an ontology testing manager. Concurrently, to support the elicitation and documentation of competency questions, we have defined and implemented RevOnt, a method to extract competency questions from knowledge graphs. Both methods are evaluated through their implementation and the results are promising.