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

Search based software engineering: Trends, techniques and applications

© ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is available from the link below.In the past five years there has been a dramatic increase in work on Search-Based Software Engineering (SBSE), an approach to Software Engineering (SE) in which Search-Based Optimization (SBO) algorithms are used to address problems in SE. SBSE has been applied to problems throughout the SE lifecycle, from requirements and project planning to maintenance and reengineering. The approach is attractive because it offers a suite of adaptive automated and semiautomated solutions in situations typified by large complex problem spaces with multiple competing and conflicting objectives. This article provides a review and classification of literature on SBSE. The work identifies research trends and relationships between the techniques applied and the applications to which they have been applied and highlights gaps in the literature and avenues for further research.EPSRC and E

A Multilevel Measurement Model of Social Cohesion

In spite of its currency both in academic research and political rhetoric, there are numerous attempts to define and conceptualize the social cohesion concept but there has been paid little attention to provide a rigorous and empirically tested definition. There are even fewer studies that address social cohesion in a framework of cross-cultural validation of the indicators testing the equivalence of the factorial structure across countries. Finally, as far as we know there is no study that attempt to provide an empirically tested multilevel definition of social cohesion specifying a Multilevel Structural Equation Model. This study aims to cover this gap. First, we provide a theoretical construct of social cohesion taking into account not only its multidimensionality but also its multilevel structure. In the second step, to test the validity of this theoretical construct, we perform a multilevel confirmatory factor analysis in order to verify if the conceptual structure suggested in first step holds. In addition, we test the cross-level structural equivalence and the measurement invariance of the model in order to verify if the same multilevel model of social cohesion holds across the 29 countries analysed. In the final step, we specify a second-order multilevel CFA model in order to identify the existence of a general factor that can be called “social cohesion” operating in society that accounts for the surface phenomena that we observe

Photocatalytic Decomposition of Formic Acid on Mo2C-Containing Catalyst

Soluble components in the peripheral blood from experimental exposure of 14 healthy subjects to filtered air and wood smoke. Samples were collected before (pre), at 24 h and 44 h after exposure, to air and wood smoke. Data are given as medians with interquartile range. (DOCX 62 kb

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

RadPhysBio: A Radiobiological Database for the Prediction of Cell Survival upon Exposure to Ionizing Radiation

: Based on the need for radiobiological databases, in this work, we mined experimental ionizing radiation data of human cells treated with X-rays, γ-rays, carbon ions, protons and α-particles, by manually searching the relevant literature in PubMed from 1980 until 2024. In order to calculate normal and tumor cell survival α and β coefficients of the linear quadratic (LQ) established model, as well as the initial values of the double-strand breaks (DSBs) in DNA, we used WebPlotDigitizer and Python programming language. We also produced complex DNA damage results through the fast Monte Carlo code MCDS in order to complete any missing data. The calculated α/β values are in good agreement with those valued reported in the literature, where α shows a relatively good association with linear energy transfer (LET), but not β. In general, a positive correlation between DSBs and LET was observed as far as the experimental values are concerned. Furthermore, we developed a biophysical prediction model by using machine learning, which showed a good performance for α, while it underscored LET as the most important feature for its prediction. In this study, we designed and developed the novel radiobiological 'RadPhysBio' database for the prediction of irradiated cell survival (α and β coefficients of the LQ model). The incorporation of machine learning and repair models increases the applicability of our results and the spectrum of potential users

Thermal crosstalk rejection for scaling quantum-photonic systems-on-chip with monolithically integrated electronics

We demonstrate integrated feedback control of a C-band microring quantum-correlated photon-pair source fabricated in a monolithic electronics-photonics platform that maintains lock in the presence of nearby on-die thermal disturbances.Agmt dtd 2/28/2020 - Catalyst Foundation; ECCS-1842692 - National Science Foundation; ECCS-2023751 - National Science Foundation; 2021-72489 - The David and Lucile Packard FoundationAccepted manuscrip