Ground penetrating radar is becoming an established component of the stone conservation researcher's arsenal. There is great potential in this quick and non-destructive technique that provides confirmation of deterioration features, such as voids, whose presence has been suggested using other tools. The past application of this technology has focused upon block scale stone deterioration, with less attention given to the study of features that extend across multiple blocks within the walls. The aim of this paper was to primarily to demonstrate the suitability of GPR for identifying void spaces when run across a rough surfaced wall façade. Additionally, this work aims to aid in the application of GPR for this purpose, by providing a comparison of three commonly used antennas to inform equipment choice during survey design. For this study, three high frequency antennas, 1.2GHz, 1.6GHz and 2.3 GHz, were run along the same perpendicular test lines across multiple blocks within a historical building façade. The resultant reflection profiles demonstrated that GPR can identify the presence of features within the blocks when run across a rough wall section. However, without the use of additional information from secondary data sources it is not possible to confirm the identity of features. The comparison of the three antennas, showed that the 1.6GHz antenna was the least suited for this task, due to the presence of extensive ringing in the resultant reflection profiles. Alternatively, the 1.2GHz antenna is most suitable for investigations deep within the wall and the 2.3GHz better suits highly detailed analysis of features present within the near surface material. The choice of the most appropriate antenna depends upon the nature of the task it will be deployed for.
ObjectivesThe aim of the study was to investigate the spatial and temporal relationships between the prevalence of COVID-19 symptoms in the community-level and area-level social deprivation.DesignSpatial mapping, generalised linear models, using time as a factor and spatial-lag models were used to explore the relationship between self-reported COVID-19 symptom prevalence as recorded through two smartphone symptom tracker apps and a range of socioeconomic factors using a repeated cross-sectional study design.SettingIn the community in Northern Ireland, UK. The analysis period included the earliest stages of non-pharmaceutical interventions and societal restrictions or ‘lockdown’ in 2020.ParticipantsUsers of two smartphone symptom tracker apps recording self-reported health information who recorded their location as Northern Ireland, UK.Primary outcome measuresPopulation standardised self-reported COVID-19 symptoms and correlation between population standardised self-reported COVID-19 symptoms and area-level characteristics from measures of multiple deprivation including employment levels and population housing density, derived as the mean number of residents per household for each census super output area.ResultsHigher self-reported prevalence of COVID-19 symptoms was associated with the most deprived areas (p<0.001) and with those areas with the lowest employment levels (p<0.001). Higher rates of self-reported COVID-19 symptoms within the age groups, 18–24 and 25–34 years were found within the most deprived areas during the earliest stages of non-pharmaceutical interventions and societal restrictions (‘lockdown’).ConclusionsThrough spatial regression of self-reporting COVID-19 smartphone data in the community, this research shows how a lens of social deprivation can deepen our understanding of COVID-19 transmission and prevention. Our findings indicate that social inequality, as measured by area-level deprivation, is associated with disparities in potential COVID-19 infection, with higher prevalence of self-reported COVID-19 symptoms in urban areas associated with area-level social deprivation, housing density and age.
The subjects profiled showed significant cognitive impairment. The MMSE score appears to give much the same information as the CAMCOG score in this general screening of our patient group. The population considered is probably representative of subjects attending similar units in the United Kingdom.
Inspection of the deterioration of both natural outcrops and historical built stone facades reveals that patterns of disruption are not uniform, indicating the influence of material and environmental properties. Sandstones have a spatial variability in weathering response. For this reason, geostatistical techniques have been applied to studies of sandstone properties, mineralogical and structural, that influence susceptibility to decay. For this study, a comparative analysis of permeability data acquired from a 'quarry fresh' stone and a weathered sample is undertaken.The depositional processes that resulted in the formation of sandstone also create structures of spatial variation such as laminations or larger bedding planes within the material. Using geostatistical techniques, the permeability variance observed within 'quarry fresh' blocks of sandstone indicates the subsampling of larger geological structures when cut from the quarry face. Once blocks have been emplaced within a building they will be subjected to the increased stress of the urban environment.These conditions result in exacerbated weathering through processes such as salt and chemical weathering. Weathering can alter material properties such as permeability with the creation of a secondary permeability produced by the opening pores and alteration of pore connectivity. Through the application of geostatistics in the analysis of permeability data observed from the weathered block, variography reveals the presence of smaller scale structures. This suggests that alteration of the sandstone's permeability has led to the creation of new weathering structures within the stone, overwriting the initial sedimentary structures. These weathering related structures will affect both the magnitude and spatial distribution of permeability within the weathered block. The interconnected pathways of permeability, created by past weathering, facilitate the migration of moisture and salts in solution through the substrate. This work has demonstrated that through a geostatistical approach with the application of co-kriging, these potential moisture pathways can be identified and visualised. Highlights (3-5, 85 Characters Each) Structures can be observed within the variance of permeability using geostatistics. Observed variogram structures indicate the block is sampling sedimentary features. Alteration of permeability through weathering overwrites sedimentary structures. Co-Kriging is used to model conduits for moisture movement through a weathered block.
Remote sensing techniques, such as LiDAR and photogrammetry, are used by researchers exploring the spatial distribution of weathering features in historic masonry. These well-established tools provide users with a perspective of the processes affecting the surface of masonry blocks; however, they cannot provide information on the alteration occurring subsurface. Geophysical tools are being explored as a potential approach to observe the variation in material properties beneath masonry block surfaces and to examine the patterns of deterioration across wall sections. Applying such techniques inform the development of conceptual models of weathering at the block to building wall scale. In this study, ground-penetrating radar (GPR) was selected to inspect the subsurface condition of the wall section of an historic church wall, where areas of granular disintegration and flaking can be observed. 3DGPR was selected for this task, as its use of regular grids during data collection make it better suited for detecting features within an area. Three high-frequency antennas, 1.2 Ghz, 1.6 Ghz and 2.3 Ghz, were run across the study area in a series of 80 cm by 80 cm grids. The data were collated within GIS, where observed features were annotated onto a schematic of the wall surface. The 3DGPR outputs identified anomalies within this structure that could not have been as easily interpreted using a 2DGPR transect. However, as 3DGPR relies upon interpolative techniques to estimate the returns between observation transects, the validity of features detected in these locations need to be tested. The results of this application of 3DGPR identified variable weathering response across the wall section, relative to elevation. These observations were used to develop a conceptual model linking these findings to seasonal variation in the capillary rise of groundwater, upward from the base of the church wall. Through these findings it is possible to see how GPR can assist in developing our understanding of the processes threatening heritage buildings.
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