Appreciation of cleft lip and palate treatment outcome by professionals and laypeople

The aim of the study was to analyse the aesthetic evaluation of head photographs of treated individuals with clefts by laypeople and professionals and to investigate how certain cephalometric variables could be related to their rating. A set of five standardized head photos (frontal, both laterals, three-quater right and left) of 12 Caucasian patients with treated unilateral cleft lip and palate were presented to 12 adult laypeople, 12 orthodontists, and 12 maxillofacial surgeons. For each set of photos the judges had to answer four questions on a visual analogue scale (VAS). The answers were analysed for intra- and inter-panel level of agreement and correlations of assessments with certain cephalometric parameters were determined. There was a high level of agreement for all assessments of each panel of raters. However, laypeople were less satisfied with lip and nose aesthetics compared to professionals. The three groups were similarly satisfied with the aesthetics of the jaws and the face. The anterior position of the maxilla (SNA) influenced positively professionals' ratings of facial aesthetics. Orthodontists were negatively influenced when the vertical dimension of the face or the distance of the lower lip to E-plane were relatively increased. The latter was the only cephalometric parameter correlated with lower aesthetic scores obtained from laypeople. Professionals report greater satisfaction from the treatment outcome and evaluate cleft consequences with less severity than laypeople. According to cephalometric findings, the relative positions of the lips seem to dominate facial aesthetics' appreciation by laypeople, while specialists appear to focus on different features of the fac

Semantically-Aware Retrieval of Oceanographic Phenomena Annotated on Satellite Images

Scientists in the marine domain process satellite images in order to extract information that can be used for monitoring, understanding, and forecasting of marine phenomena, such as turbidity, algal blooms and oil spills. The growing need for effective retrieval of related information has motivated the adoption of semantically aware strategies on satellite images with different spatiotemporal and spectral characteristics. A big issue of these approaches is the lack of coincidence between the information that can be extracted from the visual data and the interpretation that the same data have for a user in a given situation. In this work, we bridge this semantic gap by connecting the quantitative elements of the Earth Observation satellite images with the qualitative information, modelling this knowledge in a marine phenomena ontology and developing a question answering mechanism based on natural language that enables the retrieval of the most appropriate data for each user’s needs. The main objective of the presented methodology is to realize the content-based search of Earth Observation images related to the marine application domain on an application-specific basis that can answer queries such as “Find oil spills that occurred this year in the Adriatic Sea”

Feasibility study on marine litter detection and reporting in Ghana

Given the urgency of addressing data gaps on marine plastic litter, timely data, effective stakeholder engagement, cross- sector collaboration, and citizen engagement are critical to advancing this feasibility study. The innovative and integrated approach outlined in this report can also support the fulfillment of SDG 14.1.1b (measurement of plastic debris density) as well as informing policy formulation and action plans. The ability to harness the aforementioned innovative data sources, involve members of the public and communities in the process, and communicate findings in accessible formats, empowers people and communities, policymakers, and various stakeholders with the insights necessary for guiding sustainable practices

Marine Litter Windrows: A Strategic Target to Understand and Manage the Ocean Plastic Pollution

Windrow is a long-established term for the aggregations of seafoam, seaweeds, plankton and natural debris that appear on the ocean surface. Here, we define a "litter windrow" as any aggregation of floating litter at the submesoscale domain (<10 km horizontally), regardless of the force inducing the surface convergence, be it wind or other forces such as tides or density-driven currents. The marine litter windrows observed to date usually form stripes from tens up to thousands of meters long, with litter densities often exceeding 10 small items ( 2 cm) per m2 or 1 large item ( 2 cm) per 10 m2. Litter windrows are generally overlooked in research due to their dispersion, small size and ephemeral nature. However, applied research on windrows offers unique possibilities to advance on the knowledge and management of marine litter pollution. Litter windrows are hot spots of interaction with marine life. In addition, since the formation of dense litter windrows requires especially high loads of floating litter in the environment, their detection from space-borne sensors, aerial surveys or other platforms might be used to flag areas and periods of severe pollution. Monitoring and assessing of management plans, identification of pollution sources, or impact prevention are identified as some of the most promising fields of application for the marine litter windrows. In the present Perspective, we develop a conceptual framework and point out the main obstacles, opportunities and methodological approaches to address the study of litter windrows.This study is an outcome of the research project entitled "MappingWindrows as Proxy for Marine Litter Monitoring from Space" (WASP), funded by the European Space Agency (ESA) Contract No. 4000130627/20/NL/GLC, within the Discovery Campaign in Marine Litter. AC had additional support from MIDaS (CTM2016-77106-R, AEI/FEDER/UE), and SA from PRIN 2017-2017WERYZP-EMME project. AI was supported by the Environmental Research and Technology Development Fund (JPMEERF18S20201) of the Ministry of the Environment, Japan, and by SATREPS of Japan International Cooperation Agency and Japan Science and Technology Agency. OB and AR contribution was funded through the EU's LIFE Program (LIFE LEMA project, grant agreement no. LIFE15 ENV/ES/000252). This is contribution number 1016 of AZTI, Marine Research, Basque Research and Technology Alliance (BRTA)

Can we actually monitor the spatial distribution of small pelagic fish based on Sentinel-3 data? An example from the North Aegean Sea (Eastern Mediterranean Sea)

Fish population spatial distribution data provide essential information for fleet monitoring and fishery spatial planning. Modern high resolution ocean color remote sensing sensors with daily temporal coverage can enable consistent monitoring of highly productive areas, giving insight in seasonal and yearly variations. Here is presented the methodology to monitor small pelagic fish spatial distribution by means of 500m resolution satellite data in a geographically and oceanographically complex area. Specifically, anchovy (Engraulis encrasicolus) and sardine (Sardina pilchardus) acoustic biomass data are modeled against environmental proxies obtained from the Sentinel-3 satellite mission. Three modeling techniques (Logistic Regression, Generalized Additive Models, Random Forest) were applied and validated against the in-situ measurements. The accuracy of anchovy presence detection peaked at 76% and for sardine at 78%. Additionally, the spatial distribution of the models’ output highlighted known fishing grounds. For anchovy, biomass modeling highlighted the importance of bathymetry, SST, and the distance from thermal fronts, whereas for sardine, bathymetry, CHL and chlorophyll fronts. The models are applied to a sample dataset to showcase a potential outcome of the proposed methodology and its spatial characteristics. Finally, the results are discussed and compared to other habitat studies and findings in the area

Spatial distribution, abundance and habitat use of the endemic Mediterranean fan mussel Pinna nobilis in Gera Gulf, Lesvos (Greece): comparison of design-based and model-based approaches

An important population of the endemic Mediterranean fan mussel Pinna nobilis thrives in the marine protected area of Gera Gulf (Lesvos island, north-eastern Aegean Sea, Greece), and was assessed for the first time. To estimate the abundance, spatial distribution and habitat use of fan mussels in Gera Gulf, a distance sampling underwater survey was conducted. Detectability was modelled to secure unbiased estimates of population density. Two approaches were applied to analyze survey data, a design-based and a model-based approach using generalized additive models. The first approach was based on stratified random sampling on two strata, an assumed ‘preferable’ zone close to the coastline and an assumed unsuitable habitat, with predominantly muddy sediments, in which low sampling effort was applied. For the needs of the model-based approach, a dedicated cruise was conducted to collect bathymetric data with a single-beam echo-sounder and map the bathymetry of the study area. A very high-resolution image from the Worldview-3 satellite was processed, based on an object-based image analysis, for mapping all main habitat types in the study area. The estimated abundance using the design-based approach was low-biased as the stratum of pre-assumed unsuitable habitat proved to include patches of suitable habitats with high population densities that were missed by sampling. The model-based approach provided an abundance estimate of 213300 individuals (95% confidence interval between 97600-466000 individuals), which renders the fan mussel population of Gera Gulf the largest recorded population in Greece. Population density peaked between 1.5-8 m depth and became practically zero at depths >15 m. A bathymetric segregation of fan mussel size classes was noted, with the density of small individuals peaking in shallow waters, while that of large individuals peaked deeper. The highest population densities were observed in Posidonia oceanica meadows, followed by mixed bottoms (with reefs, rocks and sandy patches), while densities were very low on sandy and zero on muddy sediments. The current assessment provides a baseline for future monitoring of the fan mussel population in Gera Gulf. In view of the current (2017-2018) ongoing mass mortality of the species in the western Mediterranean, continuous monitoring of the main fan mussel populations, such as the one in Gera Gulf, is of utmost importance.  

Bayesian Algorithm Implementation in a Real Time Exposure Assessment Model on Benzene with Calculation of Associated Cancer Risks

The objective of the current study was the development of a reliable modeling platform to calculate in real time the personal exposure and the associated health risk for filling station employees evaluating current environmental parameters (traffic, meteorological and amount of fuel traded) determined by the appropriate sensor network. A set of Artificial Neural Networks (ANNs) was developed to predict benzene exposure pattern for the filling station employees. Furthermore, a Physiology Based Pharmaco-Kinetic (PBPK) risk assessment model was developed in order to calculate the lifetime probability distribution of leukemia to the employees, fed by data obtained by the ANN model. Bayesian algorithm was involved in crucial points of both model sub compartments. The application was evaluated in two filling stations (one urban and one rural). Among several algorithms available for the development of the ANN exposure model, Bayesian regularization provided the best results and seemed to be a promising technique for prediction of the exposure pattern of that occupational population group. On assessing the estimated leukemia risk under the scope of providing a distribution curve based on the exposure levels and the different susceptibility of the population, the Bayesian algorithm was a prerequisite of the Monte Carlo approach, which is integrated in the PBPK-based risk model. In conclusion, the modeling system described herein is capable of exploiting the information collected by the environmental sensors in order to estimate in real time the personal exposure and the resulting health risk for employees of gasoline filling stations

Synergistic exploitation of geoinformation methods for post-earthquake 3D mapping of Vrisa traditional settlement, Lesvos Island, Greece

The aim of this paper is to present the methodology followed and the results obtained by the synergistic exploitation of geo-information methods towards 3D mapping of the impact of the catastrophic earthquake of June 12th 2017 on the traditional settlement of Vrisa on the island of Lesvos, Greece. A campaign took place for collecting: a) more than 150 ground control points using an RTK system, b) more than 20.000 high-resolution terrestrial and aerial images using cameras and Unmanned Aircraft Systems and c) 140 point clouds by a 3D Terrestrial Laser Scanner. The Structure from Motion method has been applied on the high-resolution terrestrial and aerial photographs, for producing accurate and very detailed 3D models of the damaged buildings of the Vrisa settlement. Additionally, two Orthophoto maps and Digital Surface Models have been created, with a spatial resolution of 5cm and 3cm, respectively. The first orthophoto map has been created just one day after the earthquake, while the second one, a month later. In parallel, 3D laser scanning data have been exploited in order to validate the accuracy of the 3D models and the RTK measurements used for the geo-registration of all the above-mentioned datasets. The significant advantages of the proposed methodology are: a) the coverage of large scale areas; b) the production of 3D models having very high spatial resolution and c) the support of post-earthquake management and reconstruction processes of the Vrisa village, since such 3D information can serve all stakeholders, be it national and/or local organizations