Unnoticed Fragments of Dante’s \u27Monarchia\u27 with the Commentary Attributed to Cola di Rienzo

This note draws attention to and briefly describes fragments in the Bodleian Library, Oxford, which preserve a previously unknown copy of Dante’s Monarchia with the commentary on that text attributed to Cola di Rienzo. The fragments survive in fifteenth-century bindings from Erfurt but seem to have been written in Central Europe around the middle of the fourteenth century by a combination of Central European and Italian scribes. In their layout, decoration, text, corrections and annotations the fragments provide significant new evidence for the circulation both of the Monarchia and of the commentary. They are also important for the possibility that they originated in the milieu of mid-fourteenth-century Bohemia where Rienzo’s commentary is believed to have been composed

Analysis of Cancer Omics Data In A Semantic Web Framework

Our work concerns the elucidation of the cancer (epi)genome, transcriptome and proteome to better understand the complex interplay between a cancel cell's molecular state and its response to anti-cancer therapy. To study the problem, we have previously focused on data warehousing technologies and statistical data integration. In this paper, we present recent work on extending our analytical capabilities using Semantic Web technology. A key new component presented here is a SPARQL endpoint to our existing data warehouse. This endpoint allows the merging of observed quantitative data with existing data from semantic knowledge sources such as Gene Ontology (GO). We show how such variegated quantitative and functional data can be integrated and accessed in a universal manner using Semantic Web tools. We also demonstrate how Description Lobic (DL) reasoning can be used to infer previously unstated conclusions from existing knowledge bases. As proof of concept, we illustrate the ability of our setup to answer complex queries on resistance of cancer cells to Decitabine, a demethylating agent

Optimized placement of parasitic vibration energy harvesters for autonomous structural health monitoring

Energy harvesting, based on sources including vibration and thermal gradients, has been exploited in recent years to power telemetry, small devices, or to charge batteries or capacitors. Generating the higher levels of power which have thus far been required to run sensor systems such as those needed for structural health monitoring has been more challenging. In addition, harvesters such as those required to capture vibration often require additional elements (e.g. cantilevers) to be added to the structure and harvest over a relatively narrow band of frequencies. In aerospace applications, where weight is at a premium and vibrations occur over a broader range of frequencies, this is non-ideal. With the advent of new, lower power monitoring systems, the potential for energy harvesting to be utilized is significantly increased. This article optimizes the placement of a set of parasitic piezoelectric patches to harvest over the broad band of frequencies found in an aircraft wing and validates the results experimentally. Results are compared with the requirements of a low-power structural health monitoring system, with a closing of the gap between the energy generated and that required being demonstrated

A semantic web framework to integrate cancer omics data with biological knowledge

BACKGROUND: The RDF triple provides a simple linguistic means of describing limitless types of information. Triples can be flexibly combined into a unified data source we call a semantic model. Semantic models open new possibilities for the integration of variegated biological data. We use Semantic Web technology to explicate high throughput clinical data in the context of fundamental biological knowledge. We have extended Corvus, a data warehouse which provides a uniform interface to various forms of Omics data, by providing a SPARQL endpoint. With the querying and reasoning tools made possible by the Semantic Web, we were able to explore quantitative semantic models retrieved from Corvus in the light of systematic biological knowledge. RESULTS: For this paper, we merged semantic models containing genomic, transcriptomic and epigenomic data from melanoma samples with two semantic models of functional data - one containing Gene Ontology (GO) data, the other, regulatory networks constructed from transcription factor binding information. These two semantic models were created in an ad hoc manner but support a common interface for integration with the quantitative semantic models. Such combined semantic models allow us to pose significant translational medicine questions. Here, we study the interplay between a cell's molecular state and its response to anti-cancer therapy by exploring the resistance of cancer cells to Decitabine, a demethylating agent. CONCLUSIONS: We were able to generate a testable hypothesis to explain how Decitabine fights cancer - namely, that it targets apoptosis-related gene promoters predominantly in Decitabine-sensitive cell lines, thus conveying its cytotoxic effect by activating the apoptosis pathway. Our research provides a framework whereby similar hypotheses can be developed easily

Semantic Web-Based Integration of Cancer Pathways and Allele Frequency Data

We demonstrate the use of Semantic Web technology to integrate the ALFRED allele frequency database and the Starpath pathway resource. The linking of population-specific genotype data with cancer-related pathway data is potentially useful given the growing interest in personalized medicine and the exploitation of pathway knowledge for cancer drug discovery. We model our data using the Web Ontology Language (OWL), drawing upon ideas from existing standard formats BioPAX for pathway data and PML for allele frequency data. We store our data within an Oracle database, using Oracle Semantic Technologies. We then query the data using Oracle’s rule-based inference engine and SPARQL-like RDF query language. The ability to perform queries across the domains of population genetics and pathways offers the potential to answer a number of cancer-related research questions. Among the possibilities is the ability to identify genetic variants which are associated with cancer pathways and whose frequency varies significantly between ethnic groups. This sort of information could be useful for designing clinical studies and for providing background data in personalized medicine. It could also assist with the interpretation of genetic analysis results such as those from genome-wide association studies

PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis

BACKGROUND: To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. RESULTS: We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. CONCLUSION: PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s)

Acoustic emission source location in complex structures using full automatic delta T mapping technique

An easy to use, fast to apply, cost-effective, and very accurate non-destructive testing (NDT) technique for damage localisation in complex structures is key for the uptake of structural health monitoring systems (SHM). Acoustic emission (AE) is a viable technique that can be used for SHM and one of the most attractive features is the ability to locate AE sources. The time of arrival (TOA) technique is traditionally used to locate AE sources, and relies on the assumption of constant wave speed within the material and uninterrupted propagation path between the source and the sensor. In complex structural geometries and complex materials such as composites, this assumption is no longer valid. Delta T mapping was developed in Cardiff in order to overcome these limitations; this technique uses artificial sources on an area of interest to create training maps. These are used to locate subsequent AE sources. However operator expertise is required to select the best data from the training maps and to choose the correct parameter to locate the sources, which can be a time consuming process. This paper presents a new and improved fully automatic delta T mapping technique where a clustering algorithm is used to automatically identify and select the highly correlated events at each grid point whilst the “Minimum Difference” approach is used to determine the source location. This removes the requirement for operator expertise, saving time and preventing human errors. A thorough assessment is conducted to evaluate the performance and the robustness of the new technique. In the initial test, the results showed excellent reduction in running time as well as improved accuracy of locating AE sources, as a result of the automatic selection of the training data. Furthermore, because the process is performed automatically, this is now a very simple and reliable technique due to the prevention of the potential source of error related to manual manipulation

The cuticle modulates ultraviolet reflectance of avian eggshells

ABSTRACT Avian eggshells are variedly coloured, yet only two pigments, biliverdin and protoporphyrin IX, are known to contribute to the dramatic diversity of their colours. By contrast, the contributions of structural or other chemical components of the eggshell are poorly understood. For example, unpigmented eggshells, which appear white to the human eye, vary in their ultraviolet (UV) reflectance, which may be detectable by birds. We investigated the proximate mechanisms for the variation in UV-reflectance of unpigmented bird eggshells using spectrophotometry, electron microscopy, chemical analyses, and experimental manipulations. We specifically tested how UV-reflectance is affected by the eggshell cuticle, the outermost layer of most avian eggshells. The chemical dissolution of the outer eggshell layers, including the cuticle, increased UV-reflectance for only eggshells that contained a cuticle. Our findings demonstrate that the outer eggshell layers, including the cuticle, absorb UV-light, probably because they contain higher levels of organic components and other chemicals, such as calcium phosphates, compared to the predominantly calcite-based eggshell matrix. These data highlight the need to examine factors other than the known pigments in studies of avian eggshell colour

Characterisation of fatigue damage in composites using an Acoustic Emission Parameter Correction Technique

In industrial applications of composite materials, accurate characterisation of damage is vital. Acoustic Emission (AE) can be utilised to achieve this, however, in large-scale complex geometry components, traditional AE approaches have limitations. In this study a large carbon fibre specimen was used to generate different damage mechanisms under fatigue loading. The Delta T Mapping technique was used to locate damage and signal features were corrected using the Parameter Correction Technique (PCT). A comparison between results obtained using traditional signal features and those obtained using PCT is given. The results are validated using C-scanning and computed tomography. Matrix cracking and delamination were successfully identified using the PCT approach and improved location accuracy was achieved