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The large variation in vertebral shape and calcification observed among elasmobranch species prevents using a single method for enhancing growth bands and reading age. Further, estimating age and growth parameters can be difficult or impractical when samples are incomplete due to the bycatch of a size-selective fishery. Using a single and rapid method, age readings were obtained on the vertebrae of four batoid species, namely 53 individuals of Dasyatis pastinaca, 51 of Raja asterias, 15 of Torpedo marmorata, and 55 specimens of Torpedo torpedo, from the local small-scale trammel net fishery in the coastal waters (5–20 m depth) of the Central Tyrrhenian Sea during 2019–2021. Based on these data, a statistical routine was developed to obtain multiple estimates of age and growth parameters for incomplete samples due to size-selective fishing. The acceptable agreement between and within readers (intra and inter-reader disagreement < 5%) and the rate of increase in vertebral size with body size (differently ranked across species) demonstrated the consistency of the enhancing method. The parameters estimated by the Von Bertalanffy and Gompertz growth models matched the data available in the Mediterranean Sea for the species studied, with D. pastinaca, T. torpedo, and R. asterias showing the lowest (k = 0.05–0.12), intermediate (k = 0.112–0.19), and highest (k = 0.18–0.23) growth rates, respectively, in line with the life history traits of these species. Overall, the method proved effective both in delineating band pairs in vertebrae of different species and in reliably estimating the age and growth parameters of problematic samples due to size-selective fishing. The proposed method supports the collection of comparable demographic data from other areas where similar multi-specific assemblages are bycatch of size-selective fisheries impacting potential nursery areas and other essential habitats for elasmobranchs. [ABSTRACT FROM AUTHOR]

New cosmetic formulations are continuously requested by the market and the ingredients are constantly evolving. Recently the use of antioxidants has gained success and, in this context, analytical methods able to quickly and easily assess the antioxidant activity of cosmetics would make it possible to carry out analyses on new formulations even within the manufacturing process without the need for specialized laboratories and personnel, thus evaluating directly on-site the effectiveness and the shelf life of products. In this work, a chemiluminescent inhibition assay was developed for determining the total antioxidant activity in cosmetic products. The method was based on the luminol/enhancers/hydrogen peroxide/horseradish peroxidase chemiluminescent system, which generates light signals measurable through simple and compact instrumentation. The formation of the chemiluminescent signal is inhibited by the presence of antioxidant substances while it is restored once all the antioxidant molecules have been oxidized. The time of appearance of the light signal is related to the total antioxidant activity. The assay was carried out exploiting an integrated device comprising a microwell plate coupled with an array of amorphous silicon hydrogenated photosensors enclosed in a mini-dark box. The method was optimized in terms of concentrations and volumes of the required reagents and sample pre-treatment. A calibration curve was generated taking as a reference the antioxidant activity of ascorbic acid obtaining a detection limit of 10 µM. The developed method was applied to cosmetic products currently on the market as well as on spiked samples in order to evaluate the performance of the methods in terms of sensitivity, accuracy, and reproducibility. [ABSTRACT FROM AUTHOR]

Wildfires play a crucial role in the transformation of forest ecosystems and exert a significant influence on the global climate over geological timescales. Recent shifts in climate patterns and intensified human–forest interactions have led to an increase in the incidence of wildfires. These fires are characterized by their extensive coverage, higher frequency, and prolonged duration, rendering them increasingly destructive. To mitigate the impact of wildfires on climate change, ecosystems, and biodiversity, it is imperative to conduct systematic monitoring of wildfire progression and evaluate their environmental repercussions on a global scale. Satellite remote sensing is a powerful tool, offering precise and timely data on terrestrial changes, and has been extensively utilized for wildfire identification, tracking, and impact assessment at both local and regional levels. The Canada Centre for Mapping and Earth Observation, in collaboration with the Canadian Forest Service, has developed a comprehensive National Burned Area Composite (NBAC). This composite serves as a benchmark for curating a bi-temporal multi-source satellite image dataset for change detection, compiled from the archives of Sentinel-2, Sentinel-1, and ALOS-2 PALSAR-2. To our knowledge, this dataset is the inaugural large-scale, multi-source, and multi-frequency satellite image dataset with 20 m spatial resolution for wildfire mapping, monitoring, and evaluation. It harbors significant potential for enhancing wildfire management strategies, building upon the profound advancements in deep learning that have contributed to the field of remote sensing. Based on our curated dataset, which encompasses major wildfire events in Canada, we conducted a systematic evaluation of the capability of multi-source satellite earth observation data in identifying wildfire-burned areas using statistical analysis and deep learning. Our analysis compares the difference between burned and unburned areas using post-event observation solely or bi-temporal (pre- and post-event) observations across diverse land cover types. We demonstrate that optical satellite data yield higher separability than C-Band and L-Band Synthetic Aperture Radar (SAR), which exhibit considerable overlap in burned and unburned sample distribution, as evidenced by SAR-based boxplots. With U-Net, we further explore how different input channels influence the detection accuracy. Our findings reveal that deep neural networks enhance SAR's performance in mapping burned areas. Notably, C-Band SAR shows a higher dependency on pre-event data than L-Band SAR for effective detection. A comparative analysis of U-Net and its variants indicates that U-Net works best with single-sensor data, while the late fusion architecture marginally surpasses others in the fusion of optical and SAR data. Accuracy across sensors is highest in closed forests, with sequentially lower performance in open forests, shrubs, and grasslands. Future work will extend the data from both spatial and temporal dimensions to encompass varied vegetation types and climate zones, furthering our understanding of multi-source and multi-frequency satellite remote sensing capabilities in wildfire detection and monitoring. [ABSTRACT FROM AUTHOR]

Urbanization is progressing at an unprecedented rate in many places around the world. The Sentinel-1 synthetic aperture radar (SAR) and Sentinel-2 MultiSpectral Instrument (MSI) missions, combined with deep learning, offer new opportunities to accurately monitor urbanization at a global scale. Although the joint use of SAR and optical data has recently been investigated for urban change detection, existing data fusion methods rely heavily on the availability of sufficient training labels. Meanwhile, change detection methods addressing label scarcity are typically designed for single-sensor optical data. To overcome these limitations, we propose a semi-supervised urban change detection method that exploits unlabeled Sentinel-1 SAR and Sentinel-2 MSI data. Using bitemporal SAR and optical image pairs as inputs, the proposed multi-modal Siamese network predicts urban changes and performs built-up area segmentation for both timestamps. Additionally, we introduce a consistency loss, which penalizes inconsistent built-up area segmentation across sensor modalities on unlabeled data, leading to more robust features. To demonstrate the effectiveness of the proposed method, the SpaceNet 7 dataset, comprising multi-temporal building annotations from rapidly urbanizing areas across the globe, was enriched with Sentinel-1 SAR and Sentinel-2 MSI data. Subsequently, network performance was analyzed under label-scarce conditions by training the network on different fractions of the labeled training set. The proposed method achieved an F1 score of 0.555 when using all available training labels, and produced reasonable change detection results (F1 score of 0.491) even with as little as 10% of the labeled training data. In contrast, multi-modal supervised methods and semi-supervised methods using optical data failed to exceed an F1 score of 0.402 under this condition. Code and data are made publicly available. [ABSTRACT FROM AUTHOR]

Hybrid zones occur where genetically distinct populations meet, mate and produce offspring with mixed ancestry. In Plethodontid salamanders, introgressive hybridization is a common phenomenon, where hybrids backcross with parental populations leading to the spread of new alleles into the parental genomes. Whereas many hybrid zones have been reported in American Plethodontid salamanders, only a single hybrid zone has been documented in European plethodontids so far, which is located at the Apuan Alps in the Italian Peninsula. Here, we describe a previously unreported hybrid zone in the Northern Apennines involving all the three Plethodontid salamander species inhabiting the Italian Peninsula. We found 21 new Speleomantes sites of occurrence, from a hitherto unexplored area located at the boundaries between three Speleomantes species ranges. Using mitochondrial (Cytb and ND2 genes) and nuclear markers (two diagnostic SNPs at the NCX1 gene), we revealed a three‐way contact zone where all the three mainland species hybridize: S. strinatii, S. ambrosii and S. italicus. We observed a strong mitonuclear discordance, with mitochondrial markers showing a conspicuous geographic pattern, while diagnostic nuclear SNPs coexisted in both the same populations and individuals, providing evidence of hybridization in many possible combinations. The introgression is asymmetric, with S. italicus mitogenome usually associated with S. a. ambrosii and, to a lesser extent, to S. strinatii nuclear alleles. This finding confirms that Plethodontid are a group of choice to investigate hybridization mechanisms and suggests that behavioural, genetic and ecological components may concur in determining the direction and extent of introgression. [ABSTRACT FROM AUTHOR]

Land Use/Land Cover (LULC) mapping is the first step in monitoring urban sprawl and its environmental, economic and societal impacts. While satellite imagery and vegetation indices are commonly used for LULC mapping, the limited resolution of these images can hamper object recognition for Geographic Object-Based Image Analysis (GEOBIA). In this study, we utilize very high-resolution (VHR) optical imagery with a resolution of 50 cm to improve object recognition for GEOBIA LULC classification. We focused on the city of Nice, France, and identified ten LULC classes using a Random Forest classifier in Google Earth Engine. We investigate the impact of adding Gray-Level Co-Occurrence Matrix (GLCM) texture information and spectral indices with their temporal components, such as maximum value, standard deviation, phase and amplitude from the multi-spectral and multi-temporal Sentinel-2 imagery. This work focuses on identifying which input features result in the highest increase in accuracy. The results show that adding a single VHR image improves the classification accuracy from 62.62% to 67.05%, especially when the spectral indices and temporal analysis are not included. The impact of the GLCM is similar but smaller than the VHR image. Overall, the inclusion of temporal analysis improves the classification accuracy to 74.30%. The blue band of the VHR image had the largest impact on the classification, followed by the amplitude of the green-red vegetation index and the phase of the normalized multi-band drought index. [ABSTRACT FROM AUTHOR]

Lab-on-Chip (LoC) devices for performing real-time PCR are advantageous compared to standard equipment since these systems allow to conduct in-field quick analysis. The development of LoCs, where the components for performing the nucleic acid amplification are all integrated, can be an issue. In this work, we present a LoC-PCR device where thermalization, temperature control and detection elements are all integrated on a single glass substrate named System-on-Glass (SoG) obtained using metal thin-film deposition. By using a microwell plate optically coupled with the SoG, real-time reverse transcriptase PCR of RNA extracted from both a plant and human virus has been carried out in the developed LoC-PCR device. The limit of detection and time of analysis for the detection of the two viruses by using the LoC-PCR were compared with those achieved by standard equipment. The results showed that the two systems can detect the same concentration of RNA; however, the LoC-PCR performs the analysis in half of the time compared to the standard thermocycler, with the advantage of the portability, leading to a point-of-care device for several diagnostic applications. [ABSTRACT FROM AUTHOR]

Floods are one of the most frequent natural disasters worldwide. Although the vulnerability varies from region to region, all countries are susceptible to flooding. Mozambique was hit by several cyclones in the last few decades, and in 2019, after cyclones Idai and Kenneth, the country became the first one in southern Africa to be hit by two cyclones in the same raining season. Aiming to provide the local authorities with tools to yield better responses before and after any disaster event, and to mitigate the impact and support in decision making for sustainable development, it is fundamental to continue investigating reliable methods for disaster management. In this paper, we propose a fully automated method for flood mapping in near real-time utilizing multi-temporal Sentinel-1 Synthetic Aperture Radar (SAR) data acquired in the Beira municipality and Macomia district. The procedure exploits the processing capability of the Google Earth Engine (GEE) platform. We map flooded areas by finding the differences of images acquired before and after the flooding and then use Otsu's thresholding method to automatically extract the flooded area from the difference image. To validate and compute the accuracy of the proposed technique, we compare our results with the Copernicus Emergency Management Service (Copernicus EMS) data available in the study areas. Furthermore, we investigated the use of a Sentinel-2 multi-spectral instrument (MSI) to produce a land cover (LC) map of the study area and estimate the percentage of flooded areas in each LC class. The results show that the combination of Sentinel-1 SAR and Sentinel-2 MSI data is reliable for near real-time flood mapping and damage assessment. We automatically mapped flooded areas with an overall accuracy of about 87–88% and kappa of 0.73–0.75 by directly comparing our prediction and Copernicus EMS maps. The LC classification is validated by randomly collecting over 600 points for each LC, and the overall accuracy is 90–95% with a kappa of 0.80–0.94. [ABSTRACT FROM AUTHOR]

In this work, we present a multifunctional Lab-on-Chip (LoC) platform based on hydrogenated amorphous silicon sensors suitable for a wide range of application in the fields of biochemical and food quality control analysis. The proposed system includes a LoC fabricated on a 5 cm × 5 cm glass substrate and a set of electronic boards for controlling the LoC functionalities. The presented Lab-on-Chip comprises light and temperature sensors, a thin film resistor acting as a heating source, and an optional thin film interferential filter suitable for fluorescence analysis. The developed electronics allows to control the thin film heater, a light source for fluorescence and absorption measurements, and the photosensors to acquire luminescent signals. All these modules are enclosed in a black metal box ensuring the portability of the whole platform. System performances have been evaluated in terms of sensor optical performances and thermal control achievements. For optical sensors, we have found a minimum number of detectable photons of 8 × 104 s−1·cm−2 at room temperature, 1.6 × 106 s−1·cm−2 in presence of fluorescence excitation source, and 2.4 × 106 s−1·cm−2 at 90 °C. From a thermal management point of view, we have obtained heating and cooling rates both equal to 2.2 °C/s, and a temperature sensor sensitivity of about 3 mV/°C even in presence of light. The achieved performances demonstrate the possibility to simultaneously use all integrated sensors and actuators, making promising the presented platform for a wide range of application fields. [ABSTRACT FROM AUTHOR]

Parasite biodiversity in cetaceans represents a neglected component of the marine ecosystem. This study aimed to investigate the distribution and genetic diversity of anisakid nematodes of the genus Anisakis sampled in cetaceans from the Northeast Atlantic Ocean and the Mediterranean Sea. A total of 478 adults and pre-adults of Anisakis spp. was identified by a multilocus genetic approach (mtDNA cox2, EF1 α − 1 nDNA and nas 10 nDNA gene loci) from 11 cetacean species. A clear pattern of host preference was observed for Anisakis spp. at cetacean family level: A. simplex (s.s.) and A. pegreffii infected mainly delphinids; A. physeteris and A. brevispiculata were present only in physeterids, and A. ziphidarum occurred in ziphiids. The role of cetacean host populations from different waters in shaping the population genetic structure of A. simplex (s.s.), A. pegreffii and A. physeteris was investigated for the first time. Significant genetic sub-structuring was found in A. simplex (s.s.) populations of the Norwegian Sea and the North Sea compared to those of the Iberian Atlantic, as well as in A. pegreffii populations of the Adriatic and the Tyrrhenian Seas compared to those of the Iberian Atlantic waters. Substantial genetic homogeneity was detected in the Mediterranean Sea population of A. physeteris. This study highlights a strong preference by some Anisakis spp. for certain cetacean species or families. Information about anisakid biodiversity in their cetacean definitive hosts, which are apex predators of marine ecosystems, acquires particular importance for conservation measures in the context of global climate change phenomena. [ABSTRACT FROM AUTHOR]

Building change detection is essential for monitoring urbanization, disaster assessment, urban planning and frequently updating the maps. 3D structure information from airborne light detection and ranging (LiDAR) is very effective for detecting urban changes. But the 3D point cloud from airborne LiDAR(ALS) holds an enormous amount of unordered and irregularly sparse information. Handling such data is tricky and consumes large memory for processing. Most of this information is not necessary when we are looking for a particular type of urban change. In this study, we propose an automatic method that reduces the 3D point clouds into a much smaller representation without losing necessary information required for detecting Building changes. The method utilizes the Deep Learning(DL) model U-Net for segmenting the buildings from the background. Produced segmentation maps are then processed further for detecting changes and the results are refined using morphological methods. For the change detection task, we used multi-temporal airborne LiDAR data. The data is acquired over Stockholm in the years 2017 and 2019. The changes in buildings are classified into four types: 'newly built', 'demolished', 'taller' and 'shorter'. The detected changes are visualized in one map for better interpretation. [ABSTRACT FROM AUTHOR]

Urban Heat Islands (UHI) phenomenon is a pressing problem for highly industrialized areas with serious risks for public health. Weather stations guarantee long-term accurate observations of weather parameters, such Air Temperature (AT), but lack appropriate spatial coverage. Numerous studies have argued that satellite Land Surface Temperature (LST) is a relevant parameter for estimating AT maps, exploring both linear regression and Machine Learning algorithms. This study proposes a Neural Network (NN) regression model for estimating the maximum AT from Landsat-8 data. The approach has been tested in a variegated morphological region (Puglia, Italy) using a large stack of data acquired from 2018 to 2020. The algorithm uses the median values of LST and Normalized Difference Vegetation Index (NDVI) computed using different buffer radius around the location of each reference weather station (250 m, 1000 m, and 2000 m) to train the NN model with a K-fold cross-validation strategy. The reference dataset was split into three sets using a stratified sampling approach considering the different station categories: rural, High- and Low-density Urban areas respectively. The algorithm was tested with different learning rates (LR) (0.001 and 0.005). The results show that our NN model accuracy improves with the increase of the buffer radius, minimizing the difference in terms of R^2 between training and evaluation data, with an overall accuracy consistently higher than 0.84. Future research could investigate more input variables in the NN model such as morphology or climate variables and test the algorithm on larger areas. [ABSTRACT FROM AUTHOR]

In this paper we present a device integrating on a single glass substrate a transparent heater and two resistive temperature sensors. Both heater and sensors are constituted by ITO/Au/ITO stacked film, whose thicknesses have been optimized in order to achieve at the same time good electrical conductivity (about 106 S/m) and high transparency degree (higher than 80%) in the visible region of the spectrum. A double-spiral design has been chosen for the heater in order to achieve a uniform temperature distribution on a large area. Indeed, this geometry ensures a temperature variation of ±1.4 °C in a 2.8 cm diameter circle. For the resistive temperature sensors, a distributed meander-shaped geometry ensures temperature sensitivity as high as 0.12 $\text{k}\pmb \Omega / ^{\circ }\text{C}$. The proposed device shows therefore the capability to work as a large-area transparent heater introducing the possibility to perform a precise control of the substrate temperature. [ABSTRACT FROM AUTHOR]

Civil infrastructures, such as tunnels and bridges, are directly related to the overall economic and demographic growth of countries. The aging of these infrastructures increases the probability of catastrophic failures that results in loss of lives and high repair costs; all over the world, these factors drive the need for advanced infrastructure monitoring systems. For these reasons, in the last years, different types of devices and innovative infrastructure monitoring techniques have been investigated to automate the process and overcome the main limitation of standard visual inspections that are used nowadays. This paper presents some preliminary findings of an ongoing research project, named TACK, that combines advanced deep learning techniques and innovative photogrammetric algorithms to develop a monitoring system. Specifically, the project focuses on the development of an automatic procedure for crack detection and measurement using images of tunnels and bridges acquired with a mobile mapping system. In this paper, some preliminary results are shown to investigate the potential of a deep learning algorithm in detecting cracks occurred in concrete material. The model is a CNN (Convolutional Neural Network) based on the U-Net architecture; in this study, we tested the transferability of the model that has been trained on a small available labeled dataset and tested on a large set of images acquired using a customized mobile mapping system. The results have shown that it is possible to effectively detect cracks in unseen imagery and that the primary source of errors is the false positive detection of crack-like objects (i.e., contact wires, cables and tile borders). [ABSTRACT FROM AUTHOR]

This article investigates the stability of hydrogenated amorphous silicon (a-Si:H) p-i-n junctions employed as temperature sensors in lab-on-chip (LoC) applications. The devices have been tested under forward current injection and different temperatures (from room temperature up to 90 °C) in order to reproduce the practical operating conditions. Two sets of devices with different diborane concentrations in the p-doped layer have been investigated as a case study. For both sets, a temperature-drift error of 0.05 °C/h and a sensitivity around 3 mV/°C in the range between 30 °C and 90 °C have been achieved. These results demonstrate the device suitability as a thin-film temperature sensor integrated into LoC systems that implement thermal treatment of the biological samples as, for example, DNA amplification. [ABSTRACT FROM AUTHOR]

Contracaecum rudolphii (s. l.) is a complex of sibling species of anisakid nematodes having the fish-eating birds belonging to the Family Phalacrocoracidae as final hosts. The great cormorant Phalacrocorax carbo sinensis is parasitized by C. rudolphii A and C. rudolphii B. Adults and L4 specimens of C. rudolphii (s. l.) (N = 3282) were collected in cormorants from brackish and freshwater ecosystems of Central Italy. Third-stage larvae of Contracaecum (N = 882) were obtained from the fish species Dicentrarchus labrax, Anguilla anguilla, Aphanius fasciatus, Atherina boyeri, Leuciscus cephalus, Barbus barbus, and Carassius carassius captured in the same geographical areas of cormorants' standings. Contracaecum rudolphii A and C. rudolphii B were identified by a multilocus genetic approach: allozymes, sequences analysis of the mtDNA cox2, and ITS region of rDNA gene loci. Differential distribution of the two parasite species was observed in different aquatic environments. Contracaecum rudolphii B outnumbered C. rudolphii A in wintering cormorants from freshwater ecosystems; the opposite trend was found in cormorants from brackish water. Analogously, C. rudolphii A larvae were more prevalent in brackish water fish, while C. rudolphii B larvae were found infecting only freshwater fish. The findings seem to confirm that C. rudolphii A and C. rudolphii B would have a life-cycle adapted to brackish and freshwater environments, respectively. A differential feeding behavior of wintering cormorants, the ecology of the infected fish species, and abiotic factors related to early stages of the parasites are supposed to maintain the distinctiveness of the two parasite species' life cycles in the two different aquatic ecosystems. [ABSTRACT FROM AUTHOR]

Copyright of Parasite (1252607X) is the property of EDP Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The species of Anisakis constitute one of the most widespread groups of ascaridoid nematodes in the marine ecosystem. Three closely related taxa are recognised in the A. simplex (s. l.) complex, i.e. A. pegreffii , A. simplex (s. s.) and A. berlandi. They are distributed in populations of their intermediate/paratenic (fish and squids) and definitive (cetaceans) hosts. A panel of seven microsatellite loci (Anisl 05784 , Anisl 08059 , Anisl 00875 , Anisl 07132, Anisl 00314, Anisl 10535 and Anisl 00185) , were developed and validated on a total of N = 943 specimens of A. pegreffii and A. simplex (s. s.), collected in fish and cetacean hosts from allopatric areas within the range of distribution of these parasite species. In addition, the locus Anisl 7 , previously detected in those Anisakis spp., was investigated. The parasites were first identified by sequence analysis of the EF1 α -1 nDNA. The panel of the microsatellites loci here developed have allowed to: (i) detect diagnostic microsatellite loci between the two species; (ii) identify specimens of the two species A. pegreffii, A. simplex (s. s.) in a multi-marker nuclear genotyping approach; (iii) discover two sex-linked loci in both Anisakis species and (iv) estimate levels of genetic differentiation at both the inter- and intra-specific level. [ABSTRACT FROM AUTHOR]

DATE (Digital Automatic Terrain Extractor) is a Free and Open Source Software for Geospatial (FOSS4G), which combines photogrammetric and computer vision algorithms in order to automatically generate DSMs from multi-view SAR and optical high resolution satellite imagery, following an iterative and pyramidal workflow in order to refine a coarse DSM used as reference. Consequently, DATE is able to face both the issues of DSM generation and epipolar resampling of satellite imagery. The aim of this work is to evaluate DATE performance, by carrying out a sensitivity analysis based on the dense matching parameters. In particular, DATE implements the Semi-Global Block Matching (SGBM) algorithm, a modified version of Semi-Global Matching method: thus, the sensitivity analysis aims at assessing how SGBM parameters – namely, the difference between maximum and minimum disparity (ndisparities), the minimum disparity value (minimumDisp) and the matched block size (SADWindowSize) – affect the efficiency of the disparity map computation and the final DSM accuracy. The analysis focuses on the case study of Trento and of the Adige Valley, which was chosen due to its geomorphological heterogeneity and complexity, allowing to perform an accuracy evaluation on four tiles, characterized by specific roughness frequencies and morphologies (thus having different effects on disparity variations). Several practical indications on the optimal and critical parameter combinations were retrieved; in addition to this, this work highlighted the most influential parameters both in terms of accuracy (minimumDisp) and computation time (ndisparities), paving the way to further principal component analyses. Finally, the obtained results showed no clear relationship between the area morphology and the solution structure. [ABSTRACT FROM AUTHOR]

Copyright of Parasite (1252607X) is the property of EDP Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Today, range cameras represent a cheap, intuitive and effective technology for collecting the 3D geometry of objects and environments automatically and practically in real time. Such features can make these sensors a valuable tool for documenting archaeological small finds, especially when not expert users are involved. Therefore, in this work, Scanner and itSeez3D, two of the most promising scanning applications actually available for the Structure Sensor, a range camera specifically designed for mobile devices, were tested in order to evaluate their accuracy in modelling the 3D geometry of two archaeological artefacts, characterized by different shape and dimensions. The 3D models obtained through the two scanning applications were thus compared with the reference ones generated with the more accurate photogrammetric technique. The results demonstrate that both the applications show the same level of geometric accuracy, which amounts generally to very few millimetres, from an overall point of view, and, at the same time, they substantially point out the good quality of the Structure Sensor 3D reconstruction technology. In particular, the itSeez3D application is surely the best solution for the color restitution, even if it requires a payment of $7 to export and thus to use effectively each model generated. On the other side, Scanner is a free application and its geometric accuracy is comparable to that of itSeez3D, but, however, the colours are frequently smoothed and sometimes not fully rendered. [ABSTRACT FROM AUTHOR]

This paper presents the development of a compact optoelectronic device suitable for on-chip detection of fluorescent molecules. In order to obtain a highly integrated device, a long-pass multi-dielectric filter has been integrated with thin-film amorphous silicon photosensors on a single glass substrate. Filter rejects the excitation light, allowing the reduction of the distance between the source and the fluorescent site and avoiding the use of external optical component. The compatibility of the technological processes determined the materials and the temporal sequence of the device fabrication. The developed device has been designed for the fluorescence detection of ruthenium complex based molecules and tested, as a proof of concept, for the detection of double-stranded DNA down to 0.5 ng. Results demonstrate the correct operation of the integrated system in both rejecting the excitation light and in detecting the fluorescent signal, demonstrating the suitability of this optoelectronic platform in practical biomedical applications. [ABSTRACT FROM AUTHOR]

Studies of animal personality have shown consistent between-individual variation in behaviour in many social and non-social contexts, but hunting behaviour has been overlooked. Prey capture sequences, especially in invertebrates, are supposed to be quite invariant. In cuttlefish, the attack includes three components: attention, positioning, and seizure. The previous studies indicated some variability in these components and we quantified it under the hypothesis that it could relate to personality differences. We, therefore, analysed predation sequences of adult cuttlefish to test their association with personality traits in different contexts. Nineteen subjects were first exposed to an “alert” and a “threat” test and then given a live prey, for 10 days. Predation sequences were scored for components of the attack, locomotor and postural elements, body patterns, and number of successful tentacle ejections (i.e. seizure). PCA analysis of predatory patterns identified three dimensions accounting for 53.1%, 15.9%, and 9.6% of the variance and discriminating individuals based on “speed in catching prey”, “duration of attack behaviour”, and “attention to prey”. Predation rate, success rate, and hunting time were significantly correlated with the first, second, and third PCA factors, respectively. Significant correlations between capture patterns and responsiveness in the alert and threat tests were found, highlighting a consistency of prey capture patterns with measures of personality in other contexts. Personality may permeate even those behaviour patterns that appear relatively invariant. [ABSTRACT FROM AUTHOR]

The topic of this research is the identification of an innovative strategy for DSMs generation from optical satellite tri-stereo imagery, exploiting efficient dense matching algorithms from computer vision, without losing a rigorous photogrammetric approach. The main challenge is related to the epipolarity resampling for satellite images, for which it is not straightforward the epipolar geometry achievement, due to their multiple projection centres. The Ground quasi-Epipolar Images (GrEI) are the core of this original strategy for DSMs generation, able to return reliable and accurate solutions. The FOSS4G DATE has been modified since its original implementation, in order to obtain better results in terms of DSMs generated, and a new version has been released. The workflow provides a ground projection for the raw satellite images, exploiting RPFs model and a coarse DSM. In order to bring the ground images in the quasi-epipolar geometry, a preliminary rotation is estimated for both images to align them in the disparity prevailing direction. Then, a refinement of their relative position is performed. These orthorectified images can act as GrEI, and can undergo a dense image matching procedure. Tests have been carried out with Pléiades triplets over Trento (Northern Italy) and very good results are achieved. [ABSTRACT FROM AUTHOR]

Attempts to breed crustacean species of commercial interest to promote the conservation, restoration and enhancement of the stocks are increasing. Optimization of diet for larval growth is a crucial step for successful actions. Here we focus on the caramote prawn (Penaeus kerathurus), a primary target of small-scale fishery because of its high commercial value in the North Mediterranean region and particularly in Italy. Three species of microalgae (Isochrysis galbana, Nannochloropsis oculata, and Chaetoceros calcitrans) with different fatty acid contents were used to feed caramote prawn larvae as monospecific diets. Further, C. calcitrans in combination either with I. galbana or N. oculata were tested as mixed diets. Measurements of developmental performance were taken until the larvae metamorphosed to Mysis 1, while survival rate was estimated at day 10 of benthonic post-larval stage. Larvae fed on mixed diets performed as well or slightly better than those fed on single-C. calcitrans and -N. oculata diets both in terms of development and survival, while larvae fed with I. galbana diet performed worse overall. Diets that performed best (C. calcitrans and I. galbana mix) are known to have a higher proportion of the essential fatty acids eicosapentaenoic acid (EPA, 20:5n-3) and docosahexaenoic acid (DHA, 22:6n-3), respectively. We suggest that mixed-algal diets could improve the performance of larvae by providing a wider availability of fatty acids. [ABSTRACT FROM AUTHOR]

Here, we report on the design, fabrication, and characterization of a prototype of a portable detection system, able to determine if the contamination level of Ochratoxin A (OTA) is below or above the limit imposed by the EU Commission for a specific food. The operating principle of the system is the real-time monitoring of a chromatographic run when an extract of the sample under analysis is spotted on a high-performance thin-layer chromatographic plate. The idea is to induce naturally the fluorescence of the OTA molecules by using an ultraviolet excitation source and to detect the re-emitted light with an array of amorphous silicon photosensors, whose photocurrents will be proportional to the amount of OTA molecules. The system performances have been verified on sample containing pure OTA molecule and OTA extracted from fortified real matrices of wine and beer. The results showed a minimum detectable quantity of OTA of 0.2 ng and repeatability better than 5%. The analysis of the sample is made simultaneously with a reference, which, in the proposed system, corresponds to the amount of OTA equal to the limit for the specific food commodities. Taking into account the extraction efficiency and the minimum acceptable presence of OTA in such food commodities, we infer that the minimum amount of real matrix to be investigated is as low as 5.5 mL. [ABSTRACT FROM AUTHOR]

This paper presents the development of a lab-on-chip, based on thin-film sensors, suitable for DNA treatments. In particular, the system performs on-chip DNA amplification and separation of double-strand DNA into single-strand DNA, combining a polydimethylsiloxane microfluidic network, thin-film electronic devices, and surface chemistry. Both the analytical procedures rely on the integration on the same glass substrate of thin-film metal heaters and amorphous silicon temperature sensors to achieve a uniform temperature distribution (within ±1 °C) in the heated area and a precise temperature control (within ±0.5 °C). The DNA separation also counts on the binding between biotinylated dsDNA and a layer of streptavidin immobilized into a microfluidic channel through polymer-brushes-based layer. This approach results in a fast and low reagents consumption system. The tested DNA treatments can be applied for carrying out the on-chip systematic evolution of ligands by exponential enrichment process, a chemistry technique for the selection of aptamers. [ABSTRACT FROM AUTHOR]

Earthquakes cannot be predicted with precision, but algorithms exist for intermediate-term middle-range prediction of main shocks above a pre-assigned threshold, based on seismicity patterns. Few years ago, a first attempt was made in the framework of project SISMA, funded by Italian Space Agency, to jointly use seismological tools, like CN algorithm and scenario earthquakes, and geodetic methods and techniques, like GPS and SAR monitoring, to effectively constrain priority areas where to concentrate prevention and seismic risk mitigation. We present a further development of integration of seismological and geodetic information, clearly showing the contribution of geodesy to the understanding and prediction of earthquakes. As a relevant application, the seismic crisis that started in Central Italy in August 2016 with the Amatrice earthquake and still going on is considered in a retrospective analysis of both GPS and SAR data. Differently from the much more common approach, here, GPS data are not used to estimate the standard 2D velocity and strain field in the area, but to reconstruct the velocity and strain pattern along transects, which are properly oriented according to the a priori information about the known tectonic setting. SAR data related to the Amatrice earthquake coseismic displacements are here used as independent check of the GPS results. Overall, the analysis of the available geodetic data indicates that it is possible to highlight the velocity variation and the related strain accumulation in the area of Amatrice event, within the area alarmed by CN since November 1st, 2012. The considered counter examples, across CN alarmed and not-alarmed areas, do not show any spatial acceleration localized trend, comparable to the one well defined along the Amatrice transect. Therefore, we show that the combined analysis of the results of intermediate-term middle-range earthquake prediction algorithms, like CN, with those from the processing of adequately dense and permanent GNSS network data, possibly complemented by a continuous InSAR tracking, may allow the routine highlight in advance of the strain accumulation. Thus, it is possible to significantly reduce the size of the CN alarmed areas. [ABSTRACT FROM AUTHOR]

In the last few decades, there has been a growing interest in studying non-contact methods for full-field displacement and strain measurement. Among such techniques, Digital Image Correlation (DIC) has received particular attention, thanks to its ability to provide these information by comparing digital images of a sample surface before and after deformation. The method is now commonly adopted in the field of civil, mechanical and aerospace engineering and different companies and some research groups implemented 2D and 3D DIC software. In this work a review on DIC software status is given at first. Moreover, a free and open source 2D DIC software is presented, named py2DIC and developed in Python at the Geodesy and Geomatics Division of DICEA of the University of Rome "La Sapienza"; its potentialities were evaluated by processing the images captured during tensile tests performed in the Structural Engineering Lab of the University of Rome "La Sapienza" and comparing them to those obtained using the commercial software Vic- 2D developed by Correlated Solutions Inc, USA. The agreement of these results at one hundredth of millimetre level demonstrate the possibility to use this open source software as a valuable 2D DIC tool to measure full-field displacements on the investigated sample surface. [ABSTRACT FROM AUTHOR]

The aim of this work is to exploit the large-scale analysis capabilities of the innovative Google Earth Engine platform in order to investigate the temporal variations of the Urban Heat Island phenomenon as a whole. A intuitive methodology implementing a largescale correlation analysis between the Land Surface Temperature and Land Cover alterations was thus developed. The results obtained for the Phoenix MA are promising and show how the urbanization heavily affects the magnitude of the UHI effects with significant increases in LST. The proposed methodology is therefore able to efficiently monitor the UHI phenomenon. [ABSTRACT FROM AUTHOR]

The glaciers are a natural global resource and one of the principal climate change indicator at global and local scale, being influenced by temperature and snow precipitation changes. Among the parameters used for glacier monitoring, the surface velocity is a key element, since it is connected to glaciers changes (mass balance, hydro balance, glaciers stability, landscape erosion). The leading idea of this work is to continuously retrieve glaciers surface velocity using free ESA Sentinel-1 SAR imagery and exploiting the potentialities of the Google Earth Engine (GEE) platform. GEE has been recently released by Google as a platform for petabyte-scale scientific analysis and visualization of geospatial datasets. The algorithm of SAR off-set tracking developed at the Geodesy and Geomatics Division of the University of Rome La Sapienza has been integrated in a cloud based platform that automatically processes large stacks of Sentinel-1 data to retrieve glacier surface velocity field time series. We processed about 600 Sentinel-1 image pairs to obtain a continuous time series of velocity field measurements over 3 years from January 2015 to January 2018 for two wide glaciers located in the Northern Patagonian Ice Field (NPIF), the San Rafael and the San Quintin glaciers. Several results related to these relevant glaciers also validated with respect already available and renown software (i.e. ESA SNAP, CIAS) and with respect optical sensor measurements (i.e. LANDSAT8), highlight the potential of the Big Data analysis to automatically monitor glacier surface velocity fields at global scale, exploiting the synergy between GEE and Sentinel-1 imagery. [ABSTRACT FROM AUTHOR]

Objective: Species of the Baetis rhodani group are among the most widespread mayflies of the Palearctic region. However, frequent occurrence of morphologically cryptic species complicates the identification of sympatric species. Here, we proposed and tested a method for the fast, accurate, and cost-effective assignment of a large number of individuals to their putative species, based on high resolution melting profiles of a standard mitochondrial gene fragment. We tested this method using a system of three recently identified cryptic species inhabiting the Tyrrhenian Islands (western Mediterranean basin). Results: Highly species-specific high resolution melting profiles were obtained, allowing the unequivocal attribution of each individual to the respective species. This assay provides a convenient and easily customizable alternative to traditional barcoding approaches, provided that the mayfly taxa occurring within the geographic area of interest have been previously identified and their high resolution melting profiles assessed. [ABSTRACT FROM AUTHOR]

Habitat choice is defined as a nonrandom distribution of genotypes in different microhabitats. Therefore, it could exert a great impact on the genetic variance of natural populations by promoting genetic divergence, local adaptation, and may even lead to sympatric speciation. Despite this potential role in micro- and macro-evolutionary processes, there is little empirical evidence that the various genotypes within a population may differ in habitat choice-related behaviors. Here, we tested whether habitat choice may have contributed to genetic divergence within a local population of the Mediterranean killifish Aphanius fasciatus, which emerged between groups inhabiting microhabitats with different oxygen concentrations during previous field studies. In a first experiment, we studied the distribution of individuals in conditions of hypoxia and normoxia to test whether they had a different ability to shy away from a hypoxic environment; in a second experiment, we analyzed the individual behavior of fish separately in the two conditions, to verify whether they showed peculiar behavioral responses linked to a possible differential distribution. We then analyzed the six allozyme loci, whose allelic and genotypic frequencies were significantly divergent in the previous studies. In the first test, we found that the distribution of the two homozygote genotypes of the glucose-6-phosphate isomerase-1 locus ( GPI-1) was significantly different between the hypoxic and the normoxic conditions. During the second test, all individuals were more active in hypoxic conditions, but the two GPI-1 homozygotes showed a significant difference in time spent performing surface breathing, which was consistent with their distribution observed in the first experiment. These results provide evidence that individual behavioral traits, related to genetic features, may lead to a nonrandom distribution of genotypes in heterogeneous although contiguous microhabitats and, consequently, that habitat choice can play a significant role in driving the micro-evolutionary dynamics of this species. [ABSTRACT FROM AUTHOR]

A lab-on-chip system, integrating an all-glass microfluidics and on-chip optical detection, was developed and tested. The microfluidic network is etched in a glass substrate, which is then sealed with a glass cover by direct bonding. Thin film amorphous silicon photosensors have been fabricated on the sealed microfluidic substrate preventing the contamination of the micro-channels. The microfluidic network is then made accessible by opening inlets and outlets just prior to the use, ensuring the sterility of the device. The entire fabrication process relies on conventional photolithographic microfabrication techniques and is suitable for low-cost mass production of the device. The lab-on-chip system has been tested by implementing a chemiluminescent biochemical reaction. The inner channel walls of the microfluidic network are chemically functionalized with a layer of polymer brushes and horseradish peroxidase is immobilized into the coated channel. The results demonstrate the successful on-chip detection of hydrogen peroxide down to 18μM by using luminol and 4-iodophenol as enhancer agent. [ABSTRACT FROM AUTHOR]

Nowadays, the increasing availability of low-cost sensors, Free and Open Source Software and High Performance Computing infrastructures allows Geomatics to widen its application scope, by stimulating new challenging investigations related to the modeling of the observations provided by these new tools. In this review, some methodologies and applications, developed at the Geodesy and Geomatics Division (DICEA) of University of Rome "La Sapienza", are shortly presented. Directly related to the mentioned software and hardware new availability, they are already ready for industrial applications and hopefully can broaden the interaction between Geomatics and other scientific and technological disciplines. [ABSTRACT FROM AUTHOR]

Background: Anisakiasis is a fish-borne zoonosis caused by Anisakis spp. larvae. One challenging issue in the diagnosis of anisakiasis is the molecular detection of the etiological agent even at very low quantity, such as in gastric or intestinal biopsy and granulomas. Aims of this study were: 1) to identify three new cases of invasive anisakiasis, by a species-specific Real-time PCR probe assay; 2) to detect immune response of the patients against the pathogen.Methods: Parasite DNA was extracted from parasites removed in the three patients. The identification of larvae removed at gastric and intestinal level from two patients was first obtained by sequence analysis of mtDNA cox2 and EF1 α-1 of nDNA genes. This was not possible in the third patient, because of the very low DNA quantity obtained from a single one histological section of a surgically removed granuloma. Real-time PCR species-specific hydrolysis probe system, based on mtDNA cox2 gene, was performed on parasites tissue of the three cases. IgE, IgG4 and IgG immune response against antigens A. pegreffii by Immunoblotting assay was also studied.Results: According to the mtDNA cox2 and the EF1 α - 1 nDNA sequence analysis, the larvae from stomach and intestine of two patients were assigned to A. pegreffii. The Real-time PCR primers/probe system, showed a fluorescent signal at 510 nm for A. pegreffii, in all the three cases. In Immunoblotting assay, patient CC1 showed IgE, IgG4 reactivity against Ani s 13-like and Ani s 7-like; patient CC2 revealed only IgG reactivity against Ani s 13-like and Ani s 7-like; while, the third patient showed IgE and IgG reactivity against Ani s 13-like, Ani s 7-like and Ani s 1-like.Conclusion: The Real-time PCR assay, a more sensitive method than direct DNA sequencing for the accurate and rapid identification of etiological agent of human anisakiasis, was successfully assessed for the first time. The study also highlights the importance to use both molecular and immunological tools in the diagnosis of human anisakiasis, in order to increase our knowledge about the pathological findings and immune response related to the infection by zoonotic species of the genus Anisakis. [ABSTRACT FROM AUTHOR]

Recently, there has been a growing interest in studying non-contact techniques for strain and displacement measurement. Within photogrammetry, Digital Image Correlation (DIC) has received particular attention thanks to the recent advances in the field of lowcost, high resolution digital cameras, computer power and memory storage. DIC is indeed an optical technique able to measure full field displacements and strain by comparing digital images of the surface of a material sample at different stages of deformation and thus can play a major role in structural monitoring applications. For all these reasons, a free and open source 2D DIC software, named py2DIC, was developed at the Geodesy and Geomatics Division of DICEA, University of Rome "La Sapienza". Completely written in python, the software is based on the template matching method and computes the displacement and strain fields. The potentialities of Py2DIC were evaluated by processing the images captured during a tensile test performed in the Lab of Structural Engineering, where three different Glass Fiber Reinforced Polymer samples were subjected to a controlled tension by means of a universal testing machine. The results, compared with the values independently measured by several strain gauges fixed on the samples, demonstrate the possibility to successfully characterize the deformation mechanism of the investigated material. Py2DIC is indeed able to highlight displacements at few microns level, in reasonable agreement with the reference, both in terms of displacements (again, at few microns in the average) and Poisson's module. [ABSTRACT FROM AUTHOR]

SUMMARY Ig E sensitization to Anisakis pegreffii in Italian subjects suffering from gastro-allergic anisakiasis ( GAA) (N=5), or showing chronic urticaria ( CU+) after fish consumption (N=100), was investigated. A control group (N=5) was also included. Ig E response was analysed by immunoblotting ( WB) assay, using both excretory/secretory products ( ESPs) and crude extract ( CE) of A. pegreffii larvae. The results were compared with those achieved by the conventional immunological method for Anisakis allergy (ie, immuno CAP). Among the 110 subjects, 28 showed IgE positivity with both WB and iCAP methods; 13 proved IgE reactivity, in WB assay, to ESP antigens of A. pegreffii, here provisionally indicated as Ani s 1 -like, Ani s 7 -like, Ani s 13 -like; only 15 sera have shown IgE- WB reaction to Ani s 7 -like and Ani s 13 -like. iCAP and WB exhibited a high concordance value (κ=1.00) when iCAP value was <0.35 (negative result) and >50.0 (positive result). In the sera samples recorded as positive to Anisakis allergy, Ani s 1 -like was responsible for 46.4% of the sensitivity, while Ani s 7 -like and Ani s 13 -like for 100%. They could be considered as major antigens in the diagnosis of allergic anisakiasis caused by A. pegreffii. [ABSTRACT FROM AUTHOR]

Environmental stress can promote evolutionary forces and genetic divergence, but at which microgeographic scale divergence may arise, even in the presence of gene flow, remains poorly known. We studied the effects of eutrophication in a saltwork over a period of 6 years on the gene pool of a local population of the Mediterranean killifishAphanius fasciatus, a species resistant to extreme conditions. We hypothesised that during eutrophication, the environmental stress may have acted differently along a gradient of salinity and oxygen concentration in promoting evolutionary forces, generating divergence over a small spatial scale (2 km), despite gene flow. We analysed 24 allozymes in three temporal samples each composed of four spatial sub-samples, collected along the gradient, during eutrophication (2003 and 2005) and after a recovery project (2008). The results suggest that eutrophication promoted natural selection, originating a genetic cline on one locus (adenosine deaminase) significantly linked to salinity and oxygen concentration. Together with selection, both genetic drift and gene flow contributed to shaping the genetic structure under stress by further promoting the genetic heterogeneity and giving rise to deficits of heterozygotes as a secondary effect of the divergence. Environmental stress thus increased diversification, with the effects of selection and drift prevailing on gene flow. When environmental stress was relaxed (2008), allele and genotype frequencies became homogeneous, likely because under less extreme conditions the gene flow prevailed. These results improve our understanding of microgeographic divergence, and highlight the role of environmental stress in moulding microevolutionary dynamics and genetic patterns of animal populations. [ABSTRACT FROM AUTHOR]

This review provides an inventory of the biodiversity of the anisakid species identified so far from fish and marine mammals of the NE Atlantic Ocean. The paper reviews and discusses various taxonomical and epidemiological aspects related to biodiversity assessment, with emphasis on: (1) taxa recognized as 'biological species' based on molecular/genetic markers; (2) current molecular/genetic approaches to identify the species at different developmental stages; (3) ecological data related to the actual geographical distribution and definitive host preferences of the species; (4) their distribution in various, commercially important fish species in northern European waters; (5) their possible occurrence in farmed fish; and, finally, (6) an update of their zoonotic potential as causative agents of anisakidosis in humans. [ABSTRACT FROM AUTHOR]

The ISPRS Working Group 4 Commission I on "Geometric and Radiometric Modelling of Optical Spaceborne Sensors", provides a benchmark dataset with several stereo data sets from space borne stereo sensors. In this work, the Worldview-1 and Cartosat-1 datasets are used, in order to test the Free and Open Source Software for Geospatial (FOSS4G) Digital Automatic Terrain Extractor (DATE), developed at Geodesy and Geomatics Division, University of Rome "La Sapienza", able to generate Digital Surface Models starting from optical and SAR satellite images. The accuracy in terms of NMAD ranges from 1 to 3 m for Wordview-1, and from 4 to 6 m for Cartosat-1. The results obtained show a general better 3D reconstruction for Worldview-1 DSMs with respect to Cartosat-1, and a different completeness level for the three analysed tiles, characterized by different slopes and land cover. [ABSTRACT FROM AUTHOR]

The high-performance cloud-computing platform Google Earth Engine has been developed for global-scale analysis based on the Earth observation data. In particular, in this work, the geometric accuracy of the two most used nearly-global free DSMs (SRTM and ASTER) has been evaluated on the territories of four American States (Colorado, Michigan, Nevada, Utah) and one Italian Region (Trentino Alto-Adige, Northern Italy) exploiting the potentiality of this platform. These are large areas characterized by different terrain morphology, land covers and slopes. The assessment has been performed using two different reference DSMs: the USGS National Elevation Dataset (NED) and a LiDAR acquisition. The DSMs accuracy has been evaluated through computation of standard statistic parameters, both at global scale (considering the whole State/Region) and in function of the terrain morphology using several slope classes. The geometric accuracy in terms of Standard deviation and NMAD, for SRTM range from 2-3 meters in the first slope class to about 45 meters in the last one, whereas for ASTER, the values range from 5-6 to 30 meters. In general, the performed analysis shows a better accuracy for the SRTM in the flat areas whereas the ASTER GDEM is more reliable in the steep areas, where the slopes increase. These preliminary results highlight the GEE potentialities to perform DSM assessment on a global scale. [ABSTRACT FROM AUTHOR]

The production of reliable documentation of small finds is a crucial process during archaeological excavations. Range cameras can be a valid alternative to traditional illustration methods: they are veritable 3D scanners able to easily collect the 3D geometry (shape and dimensions in metric units) of an object/scene practically in real-time. This work investigates precisely the potentialities of a promising low-cost range camera, the Structure Sensor™ by Occipital, for rapid modelling archaeological objects. The accuracy assessment was thus performed by comparing the 3D model of a Cipriot-Phoenician globular jug captured by this device with the 3D model of the same object obtained through photogrammetry. In general, the performed analysis shows that Structure Sensor is capable to acquire the 3D geometry of a small object with an accuracy comparable at millimeter level to that obtainable with the photogrammetric method, even though the finer details are not always correctly modelled. The texture reconstruction is instead less accurate. In the end, it can be concluded that the range camera used for this work, due to its low-cost and flexibility, is a suitable tool for the rapid documentation of archaeological small finds, especially when not expert users are involved. [ABSTRACT FROM AUTHOR]