A silent witness? Medieval urban landscapes and unfolding their mapping histories

This paper offers a critical reflection on the place of maps in writing medieval urban histories. Using findings from recent research on medieval Swansea, the case is made that mapping provides an interpretative space for exploring alternative narratives about past places. To do so the paper draws upon current critical debates on cartography, particularly the idea that mapping is fluid and iterative, to suggest that Swansea's medieval urban origins are open to a range of alternative interpretations. This approach to mapping differs from that often used by historians to map medieval urban landscapes, where historic maps are simply used as ‘sources’, and the landscapes they represent used as ‘witnesses’ to past events, for creating maps, both through digital and analogue media, instead opens up – or unfolds – a landscape's past. The paper uses past attempts to map medieval Swansea to highlight difficulties in interpreting its urban landscape features, and uses multiple mappings of the medieval townscape, resulting from recent research, to question how far any sources about the past really provide a coherent narrative. Instead, multiple mappings of the medieval urban landscape – reflecting different and competing perspectives – are more attuned with how places were perceived and understood during the Middle Ages.

Nonclassicality and criticality in symmetry protected magnetic phases

Quantum and global discord in a spin-1 Heisenberg chain subject to single-ion anisotropy (uniaxial field) are studied using exact diagonalisation and the density matrix renormalisation group (DMRG). We find that these measures of quantum non-classicality are able to detect the quantum phase transitions confining the symmetry protected Haldane phase and show critical scaling with universal exponents. Moreover, in the case of thermal states, we find that quantum discord can increase with increasing temperature.

Privacy-Protected Facial Biometric Verification via Fuzzy Forest Learning

Although visual surveillance has emerged as an effective technolody for public security, privacy has become an issue of great concern in the transmission and distribution of surveillance videos. For example, personal facial images should not be browsed without permission. To cope with this issue, face image scrambling has emerged as a simple solution for privacyrelated applications. Consequently, online facial biometric verification needs to be carried out in the scrambled domain thus bringing a new challenge to face classification. In this paper, we investigate face verification issues in the scrambled domain and propose a novel scheme to handle this challenge. In our proposed method, to make feature extraction from scrambled face images robust, a biased random subspace sampling scheme is applied to construct fuzzy decision trees from randomly selected features, and fuzzy forest decision using fuzzy memberships is then obtained from combining all fuzzy tree decisions. In our experiment, we first estimated the optimal parameters for the construction of the random forest, and then applied the optimized model to the benchmark tests using three publically available face datasets. The experimental results validated that our proposed scheme can robustly cope with the challenging tests in the scrambled domain, and achieved an improved accuracy over all tests, making our method a promising candidate for the emerging privacy-related facial biometric applications.

Religious Nationalism and Christian Zionist Pilgrimages to Holy Landscapes

The mitochondrial and autosomal mutation landscapes of prostate cancer

BACKGROUND: Prostate cancer (PCa) is the most common cancer in men. PCa is strongly age associated; low death rates in surveillance cohorts call into question the widespread use of surgery, which leads to overtreatment and a reduction in quality of life. There is a great need to increase the understanding of tumor characteristics in the context of disease progression.

OBJECTIVE: To perform the first multigenome investigation of PCa through analysis of both autosomal and mitochondrial DNA, and to integrate exome sequencing data, and RNA sequencing and copy-number alteration (CNA) data to investigate how various different tumor characteristics, commonly analyzed separately, are interconnected.

DESIGN, SETTING, AND PARTICIPANTS: Exome sequencing was applied to 64 tumor samples from 55 PCa patients with varying stage and grade. Integrated analysis was performed on a core set of 50 tumors from which exome sequencing, CNA, and RNA sequencing data were available.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Genes, mutated at a significantly higher rate relative to a genomic background, were identified. In addition, mitochondrial and autosomal mutation rates were correlated to CNAs and proliferation, assessed as a cell cycle gene expression signature.

RESULTS AND LIMITATIONS: Genes not previously reported to be significantly mutated in PCa, such as cell division cycle 27 homolog (Saccharomyces cerevisiae) (CDC27), myeloid/lymphoid or mixed-lineage leukemia 3 (MLL3), lysine (K)-specific demethylase 6A (KDM6A), and kinesin family member 5A (KIF5A) were identified. The mutation rate in the mitochondrial genome was 55 times higher than that of the autosomes. Multilevel analysis demonstrated a tight correlation between high reactive-oxygen exposure, chromosomal damage, high proliferation, and in parallel, a transition from multiclonal indolent primary PCa to monoclonal aggressive disease. As we only performed targeted sequence analysis; copy-number neutral rearrangements recently described for PCa were not accounted for.

CONCLUSIONS: The mitochondrial genome displays an elevated mutation rate compared to the autosomal chromosomes. By integrated analysis, we demonstrated that different tumor characteristics are interconnected, providing an increased understanding of PCa etiology.

Who Knows What's Going On? Mapping New Security Landscapes in Contemporary Espionage Fiction

This article explores whether or to what extent the contemporary espionage novel is able to map and interrogate transformations in the post-9/11security environment. It asks how well a form or genre of writing, typically handcuffed to the machinations and demands of the Cold War and state sovereignty, is able to adapt to a new security environment characterized by strategies of “risk assessment” and “resilience-building” and by modes or regimes of power not reducible to, or wholly controlled by, the state. In doing so, it thinks about the capacities of this type of fiction for “resisting” the formations of power it wants to make visible and is partly complicit with.

A primer for use of genetic tools in selecting and testing the suitability of set-aside sites protected from deep-sea seafloor massive sulfide mining activities

Seafloor massive sulfide (SMS) mining will likely occur at hydrothermal systems in the near future. Alongside their mineral wealth, SMS deposits also have considerable biological value. Active SMS deposits host endemic hydrothermal vent communities, whilst inactive deposits support communities of deep water corals and other suspension feeders. Mining activities are expected to remove all large organisms and suitable habitat in the immediate area, making vent endemic organisms particularly at risk from habitat loss and localised extinction. As part of environmental management strategies designed to mitigate the effects of mining, areas of seabed need to be protected to preserve biodiversity that is lost at the mine site and to preserve communities that support connectivity among populations of vent animals in the surrounding region. These "set-aside" areas need to be biologically similar to the mine site and be suitably connected, mostly by transport of larvae, to neighbouring sites to ensure exchange of genetic material among remaining populations. Establishing suitable set-asides can be a formidable task for environmental managers, however the application of genetic approaches can aid set-aside identification, suitability assessment and monitoring. There are many genetic tools available, including analysis of mitochondrial DNA (mtDNA) sequences (e.g. COI or other suitable mtDNA genes) and appropriate nuclear DNA markers (e.g. microsatellites, single nucleotide polymorphisms), environmental DNA (eDNA) techniques and microbial metagenomics. When used in concert with traditional biological survey techniques, these tools can help to identify species, assess the genetic connectivity among populations and assess the diversity of communities. How these techniques can be applied to set-aside decision making is discussed and recommendations are made for the genetic characteristics of set-aside sites. A checklist for environmental regulators forms a guide to aid decision making on the suitability of set-aside design and assessment using genetic tools. This non-technical primer document represents the views of participants in the VentBase 2014 workshop.

Assessment of reserve effect in a marine protected area: the case study of the Professor Luiz Saldanha Marine Park (Portugal)

Dissertação de mest., Biologia Marinha (Ecologia e Conservação Marinhas), Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2011

Thesis abstract. Applying species distribution modeling for the conservation of Iberian protected invertebrates

This article outlines the approaches to modeling the distribution of threatened invertebrates using data from atlases, museums and databases. Species Distribution Models (SDMs) are useful for estimating species’ ranges, identifying suitable habitats, and identifying the primary factors affecting species’ distributions. The study tackles the strategies used to obtain SDMs without reliable absence data while exploring their applications for conservation. I examine the conservation status of Copris species and Graellsia isabelae by delimiting their populations and exploring the effectiveness of protected areas. I show that the method of pseudo‐absence selection strongly determines the model obtained, generating different model predictions along the gradient between potential and realized distributions. After assessing the effects of species’ traits and data characteristics on accuracy, I found that species are modeled more accurately when sample sizes are larger, no matter the technique used.