AUTOMATIZING DEGRADATION MAPPING OF ANCIENT STELAE BY DUAL-BAND IMAGING AND MACHINE LEARNING-BASED CLASSIFICATION

Degradation patterns are the visible consequence of the impacts of environmental factors and biological agents on stone heritage. Accurately documenting them is a key requisite when studying exposed stone antiquities to interpret weathering causes, identify conservation needs, and plan cleaning interventions. However, a significant gap can be identified in practical automatized procedures for mapping patterns on stone antiquities, such as ancient stelae. This work evaluates a workflow that uses visible and near-infrared imaging, combined with machine learning-based digital image segmentation tools, to classify degradation patterns on marble stelae correctly and cost-effectively. For this work, different classification methods are considered. Results are analyzed using error matrixes and reference degradation maps. The application cases include stelae displayed in the courtyard of the Archaeological Museum of Eretria (Euboea, Greece). The proposed methodology aims at being easily adapted to facilitate the conservators’ work

An innovative image processing-based framework for the numerical modelling of cracked masonry structures

A vital aspect when modelling the mechanical behaviour of existing masonry structures is the accuracy in which the geometry of the real structure is transferred in the numerical model. Commonly, the geometry of masonry is captured with traditional techniques (e.g. visual inspection and manual surveying methods), which are labour intensive and error-prone. Over the last ten years, advances in photogrammetry and image processing have started to change the building industry since it is possible to capture rapidly and remotely digital records of objects and features. Although limited work exists in detecting distinct features from masonry structures, up to now there is no automated procedure leading from image-based recording to their numerical modelling. To address this, an innovative framework, based on image-processing, has been developed that automatically extracts geometrical features from masonry structures (i.e. masonry units, mortar, existing cracks and pathologies, etc.) and generate the geometry for their advanced numerical modelling. The proposed watershed-based algorithm initially deconstructs the features of the segmentation, then reconstructs them in the form of shared vertices and edges, and finally converts them to scalable polylines. The polylines extracted are simplified using a contour generalisation procedure. The geometry of the masonry elements is further modified to facilitate the transition to a numerical modelling environment. The proposed framework is tested by comparing the numerical analysis results of an undamaged and a damaged masonry structures, using models generated through manual and the proposed algorithmic approaches. Although the methodology is demonstrated here for use in discrete element modelling, it can be applied to other computational approaches based on the simplified and detailed micro-modelling approach for evaluating the structural behaviour of masonry structures

Study protocol to investigate the effects of testosterone therapy as an adjunct to exercise rehabilitation in hypogonadal males with chronic heart failure

BACKGROUND: Testosterone deficiency is a common occurrence in men with chronic heart failure (CHF) and may underpin features of advanced disease, including reduced skeletal muscle mass and fatigue. It is positively correlated with cardiac output and exercise capacity in patients with CHF, whereas a significant improvement in both these parameters has been observed following testosterone replacement therapy. Testosterone therapy has also been shown to reduce circulating levels of inflammatory markers, (TNF-α, sICAM-1 and sVCAM-1) in patients with established coronary artery disease and testosterone deficiency. This pilot study will assess the feasibility of a combined exercise rehabilitation and adjunctive testosterone therapy intervention for evoking improvements in exercise capacity, circulating inflammatory markers, cardiac and skeletal muscle function, indices of psychological health status and quality of life in hypogonadal males with chronic heart failure. METHODS/DESIGN: Following ethical approval, 36 patients will be randomly allocated to one of two groups: testosterone or placebo therapy during exercise rehabilitation. A combined programme of moderate intensity aerobic exercise and resistance (strength) training will be used. The primary outcome measure is exercise capacity, assessed using an incremental shuttle walk test. Secondary outcome measures include measures of peak oxygen uptake, cardiac function, lower-limb skeletal muscle contractile function and oxygenation during exercise, circulating inflammatory markers, psychological health status and quality of life. DISCUSSION: Exercise rehabilitation can safely increase exercise capacity in stable CHF patients but there is a need for studies which are aimed at evaluating the long-term effects of physical training on functional status, morbidity and mortality. This pilot study will provide valuable preliminary data on the efficacy of testosterone therapy as an adjunct to exercise rehabilitation on a range of functional, physiological and health-related outcomes in this patient population. Preliminary data will be used in the design of a large-scale randomised controlled trial, aimed at informing clinical practice with respect to optimisation of exercise rehabilitation in this patient group

Non-parametric kernel estimation for symmetric Hawkes processes. Application to high frequency financial data

We define a numerical method that provides a non-parametric estimation of the kernel shape in symmetric multivariate Hawkes processes. This method relies on second order statistical properties of Hawkes processes that relate the covariance matrix of the process to the kernel matrix. The square root of the correlation function is computed using a minimal phase recovering method. We illustrate our method on some examples and provide an empirical study of the estimation errors. Within this framework, we analyze high frequency financial price data modeled as 1D or 2D Hawkes processes. We find slowly decaying (power-law) kernel shapes suggesting a long memory nature of self-excitation phenomena at the microstructure level of price dynamics.Comment: 6 figure

Chaos and magnetospheric dynamics

International audienceOur intention in this work is to show, by using two different methods, that magnetospheric dynamics reveal low dimensional chaos. In the first method we extend the chaotic analysis for the AE index time series by including singular value decomposition (SVD) analysis in combination with Theiler's test in order to discriminate dynamical chaos from self-affinity or "crinkliness". The estimated fractality of the AE index time series which is obtained belongs to a strange attractor structure with close returns in the reconstructed phase space. In the second method we extend the linear equivalent magnetospheric electric circuit to a nonlinear one, the arithmetic solution of which reveals low dimensional chaotic dynamics. Both methods strongly support the existence of low dimensional magnetospheric chaos

Similar clinical benefits from below‐target and target dose enalapril in patients with heart failure in the SOLVD Treatment trial

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142515/1/ejhf937.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142515/2/ejhf937_am.pd

Co-circulation of Multidrug-resistant Shigella Among Men Who Have Sex With Men in Australia.

BACKGROUND: In urban Australia, the burden of shigellosis is either in returning travelers from shigellosis-endemic regions or in men who have sex with men (MSM). Here, we combine genomic data with comprehensive epidemiological data on sexual exposure and travel to describe the spread of multidrug-resistant Shigella lineages. METHODS: A population-level study of all cultured Shigella isolates in the state of Victoria, Australia, was undertaken from 1 January 2016 through 31 March 2018. Antimicrobial susceptibility testing, whole-genome sequencing, and bioinformatic analyses of 545 Shigella isolates were performed at the Microbiological Diagnostic Unit Public Health Laboratory. Risk factor data on travel and sexual exposure were collected through enhanced surveillance forms or by interviews. RESULTS: Rates of antimicrobial resistance were high, with 17.6% (95/541) and 50.6% (274/541) resistance to ciprofloxacin and azithromycin, respectively. There were strong associations between antimicrobial resistance, phylogeny, and epidemiology. Specifically, 2 major MSM-associated lineages were identified: a Shigellasonnei lineage (n = 159) and a Shigella flexneri 2a lineage (n = 105). Of concern, 147/159 (92.4%) of isolates within the S. sonnei MSM-associated lineage harbored mutations associated with reduced susceptibility to recommended oral antimicrobials: namely, azithromycin, trimethoprim-sulfamethoxazole, and ciprofloxacin. Long-read sequencing demonstrated global dissemination of multidrug-resistant plasmids across Shigella species and lineages, but predominantly associated with MSM isolates. CONCLUSIONS: Our contemporary data highlight the ongoing public health threat posed by resistant Shigella, both in Australia and globally. Urgent multidisciplinary public health measures are required to interrupt transmission and prevent infection