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Carbon nanotubes (CNTs) have attracted interest for optoelectronic applications due to their unique electronic and optoelectronic properties. In particular, multiwall (MW) CNTs film acts as perfect photo‐collector surface with the possibility to tune the absorbance by controlling the film thickness. In this work, we demonstrate two types of hybrid Si‐MWCNTs photodetectors. The MWCNTs are solution‐processed and deposited on n‐silicon substrate covered by two different dielectrics (Si3N4 or SiO2). The MWCNTs/SiO2/n‐Si device is used here as reference, since the SiO2/Si system is the most widely investigated structure in microelectronics. The electrical and optical characteristics of the reference device are compared with the corresponding of our basic MWCNTs/Si3N4/n‐Si device. The MWCNTs are deposited on the substrate with the drop casting technique. Optical performance of the SiO2 device is comparable to the Si3N4 device thus revealing a quite interesting response under UV illumination. The Si3N4 device exhibited a peak equivalent quantum efficiency (EQE) of 57% at 3 μW of source illumination power, thus demonstrating a superior performance as compared to the SiO2 device (EQE of up to 55%, which is also promising for future applications). This performance can be attributed to the great absorption in UV region of CNTs layer. Apart from this technological goal, we also investigated how MWCNTs/Si3N4 or MWCNTs/SiO2 heterojunctions perform using standard electrical characterization techniques and how the presence of the CNTs change the dielectric characteristics of both substrates. [ABSTRACT FROM AUTHOR]

The very shallow marine basin of Puck Lagoon in the southern Baltic Sea, on the Northern coast of Poland, hosts valuable benthic habitats and cultural heritage sites. These include, among others, protected Zostera marina meadows, one of the Baltic's major medieval harbours, a ship graveyard, and likely other submerged features that are yet to be discovered. Prior to this project, no comprehensive high-resolution remote sensing data were available for this area. This article describes the first Digital Elevation Models (DEMs) derived from a combination of airborne bathymetric LiDAR, multibeam echosounder, airborne photogrammetry and satellite imagery. These datasets also include multibeam echosounder backscatter and LiDAR intensity, allowing determination of the character and properties of the seafloor. Combined, these datasets are a vital resource for assessing and understanding seafloor morphology, benthic habitats, cultural heritage, and submerged landscapes. Given the significance of Puck Lagoon's hydrographical, ecological, geological, and archaeological environs, the high-resolution bathymetry, acquired by our project, can provide the foundation for sustainable management and informed decision-making for this area of interest. [ABSTRACT FROM AUTHOR]

The task of colour restoration on datasets acquired in deep waters with simple equipment such as a camera with strobes is not an easy task. This is due to the lack of a lot of information, such as the water environmental conditions, the geometric setup of the strobes and the camera, and in general, the lack of precisely calibrated setups. It is for these reasons that this study proposes a self-adaptive colour calibration method for underwater (UW) images captured in deep waters with a simple camera and strobe setup. The proposed methodology utilises the scene's 3D geometry in the form of Structure from Motion and MultiView Stereo (SfM-MVS)-generated depth maps, the well-lit areas of certain images, and a Feedforward Neural Network (FNN) to predict and restore the actual colours of the scene in a UW image dataset. [ABSTRACT FROM AUTHOR]

This article examines the user experience and cognitive workload in digital storytelling through immersive virtual reality (VR). Specifically, it explores the relationship between various aspects of the user experience and their link to the cognitive workload. The investigation was conducted by means of a large-scale evaluation of an underwater archaeological VR experience that simulated diving into the reconstructions of a submerged ancient site combined with interactive 360° video storytelling. The evaluation included 125 participants from two different geographical locations. Results revealed a strong interdependence between all user experience scales, including presence, immersion, engagement, emotional response, state of flow, subjective judgment, and technological adoption of the VR equipment. Moreover, the sense of presence in VR was strongly related to the reported task performance. The article highlights the importance of understanding the user experience and cognitive workload when creating digital storytelling applications in immersive VR. [ABSTRACT FROM AUTHOR]

Benchmark datasets have become increasingly widespread in the scientific community as a method of comparison, validation, and improvement of theories and techniques thanks to more affordable means for sharing. While this especially holds for test sites and data collected above the water, publicly accessible benchmark activities for geospatial analyses in the underwater environment are not very common. Applying geomatic techniques underwater is challenging and expensive, especially when dealing with deep water and offshore operations. Moreover, benchmarking requires ground truth data for which, in water, several open issues exist concerning geometry and radiometry. Recognizing this scientific and technological challenge, the NAUTILUS (uNder And throUgh waTer datasets for geospatIaL stUdieS) project aims to create guidelines for new multi-sensor/cross-modality benchmark datasets. The project focuses on (i) surveying the actual needs and gaps in through and under-the-water geospatial applications through a questionnaire and interviews, (ii) launching a unique publicly available database collecting already existing datasets scattered across the web and literature, (iii) designing and identifying proper test site(s) and methodologies to deliver to the extended underwater community a brand-new multi-sensor/cross-modality benchmark dataset. The project outputs are available to researchers and practitioners in underwater measurements-related domains, as they can now access a comprehensive tool providing a synthesis of open questions and data already available. In doing so, past research efforts to collect and publish datasets have received additional credit and visibility. [ABSTRACT FROM AUTHOR]

This review paper aims to provide a meta-analysis of the scientific literature for heritage documentation and monitoring using geo-information sensors. The study initially introduces the main types of geomatic sensors that are currently widely used for heritage studies. Although the list provided here is indicative rather than exhaustive, it provides a general overview of the variety of sensors used for different observation scales. The study next focuses on the existing literature, based on published documents. Targeted queries were implemented to the Scopus database to extract the relevant information. Filtering was then applied to the results so as to limit the analysis on the specific thematic sub-domains that is applied for heritage documentation and monitoring. These domains include, among other close-range and underwater photogrammetry, Terrestrial Laser Scanner, Unmanned Aerial Vehicles platforms, and satellite observations. In total, more than 12,000 documents were further elaborated. The overall findings are summarized and presented here, providing further insights into the current status of the domain. [ABSTRACT FROM AUTHOR]

Cloud computing has begun a transformation from using virtual machines to using containers. Containers are attractive because of their "build once, run anywhere" computing model and their minimal performance overhead. Cloud providers leverage the lean nature of containers to run hundreds of them or more on a few cores. Furthermore, containers enable the serverless paradigm, which involves the creation of short-lived processes. In this work, we identify that containerized environments create page translations that are extensively replicated across containers in the TLB and in page tables. The result is high TLB pressure and redundant kernel work during page table management. To remedy this situation, this article proposes BabelFish, a novel architecture to share page translations across containers in the TLB and in page tables. BabelFish reduces the mean and tail latency of containerized workloads, cold-start effects of function execution, and container bring-up time. This work also advocates for the need to provide more hardware support for containerized and serverless environments. [ABSTRACT FROM AUTHOR]

A microarchitectural replay attack is a novel class of attack where an adversary can denoise nearly arbitrary microarchitectural side channels in a single run of the victim. The idea is to cause the victim to repeatedly replay by inducing pipeline flushes. In this article, we design, implement, and demonstrate our ideas in a framework, called MicroScope, that causes repeated pipeline flushes by inducing page faults. Our main result shows that MicroScope can denoise the port contention channel of execution units. Specifically, we show how MicroScope can reliably detect the presence or absence of as few as two divide instructions in a single logical run of the victim program. We also discuss the broader implications of microarchitectural replay attacks. [ABSTRACT FROM AUTHOR]

In this paper, a new methodology for delineating Hydrological Response Units (HRUs), based on the Curve Number (CN) concept, is presented. Initially, a semi-automatic procedure in a GIS environment is used to produce basin maps of distributed CN values as the product of the three classified layers, soil permeability, land use/land cover characteristics and drainage capacity. The map of CN values is used in the context of model parameterization, in order to identify the essential number and spatial extent of HRUs and, consequently, the number of control variables of the calibration problem. The new approach aims at reducing the subjectivity introduced by the definition of HRUs and providing parsimonious modelling schemes. In particular, the CN-based parameterization (1) allows the user to assign as many parameters as can be supported by the available hydrological information, (2) associates the model parameters with anticipated basin responses, as quantified in terms of CN classes across HRUs, and (3) reduces the effort for model calibration, simultaneously ensuring good predictive capacity. The advantages of the proposed approach are demonstrated in the hydrological simulation of the Nedontas River Basin, Greece, where parameterizations of different complexities are employed in a recently improved version of the HYDROGEIOS model. A modelling experiment with a varying number of HRUs, where the parameter estimation problem was handled through automatic optimization, showed that the parameterization with three HRUs, i.e., equal to the number of flow records, ensured the optimal performance. Similarly, tests with alternative HRU configurations confirmed that the optimal scores, both in calibration and validation, were achieved by the CN-based approach, also resulting in parameters values across the HRUs that were in agreement with their physical interpretation. [ABSTRACT FROM AUTHOR]

There is growing interest for using Spectral Vegetation Indices (SVI) derived by Unmanned Aerial Vehicle (UAV) imagery as a fast and cost-efficient tool for plant phenotyping. The development of such tools is of paramount importance to continue progress through plant breeding, especially in the Mediterranean basin, where climate change is expected to further increase yield uncertainty. In the present study, Normalized Difference Vegetation Index (NDVI), Simple Ratio (SR) and Green Normalized Difference Vegetation Index (GNDVI) derived from UAV imagery were calculated for two consecutive years in a set of twenty durum wheat varieties grown under a water limited and heat stressed environment. Statistically significant differences between genotypes were observed for SVIs. GNDVI explained more variability than NDVI and SR, when recorded at booting. GNDVI was significantly correlated with grain yield when recorded at booting and anthesis during the 1st and 2nd year, respectively, while NDVI was correlated to grain yield when recorded at booting, but only for the 1st year. These results suggest that GNDVI has a better discriminating efficiency and can be a better predictor of yield when recorded at early reproductive stages. The predictive ability of SVIs was affected by plant phenology. Correlations of grain yield with SVIs were stronger as the correlations of SVIs with heading were weaker or not significant. NDVIs recorded at the experimental site were significantly correlated with grain yield of the same set of genotypes grown in other environments. Both positive and negative correlations were observed indicating that the environmental conditions during grain filling can affect the sign of the correlations. These findings highlight the potential use of SVIs derived by UAV imagery for durum wheat phenotyping under low yielding Mediterranean conditions. [ABSTRACT FROM AUTHOR]

We propose a systematic framework for delineating Hydrological Response Units (HRUs), based on a modified Curve Number (CN) approach. The CN-value accounts for three major physiographic characteristics of a river basin, by means of classes of soil permeability, land use/land cover characteristics, and drainage capacity. A semi-automatic procedure in a GIS environment allows producing basin maps of distributed CN-values as the product of the three classified layers. The map of CN-values is used in the context of model parameterization, in order to identify the essential number and spatial extent of HRUs and, consequently, the number of control variables of the calibration problem. The new approach aims at reducing the subjectivity introduced by the definition of HRUs, and simultaneously at providing parsimonious modelling schemes. In particular, the CN-based parameterization (1) allows the user to assign as many parameters as can be supported by the available hydrological information, (2) associates the model parameters with anticipated basin responses, as quantified in terms of CN classes across HRUs, and (3) reduces the effort for model calibration, simultaneously ensuring good predictive capacity. The advantages of the proposed framework are demonstrated in the hydrological simulation of Nedontas river basin, Greece, in which parameterizations of different complexities are employed in a recently improved version of the HYDROGEIOS modelling framework. [ABSTRACT FROM AUTHOR]

Among the renewable power sources, solar power is rapidly becoming popular because it is inexhaustible, clean, and dependable. It has also become more efficient since the power conversion efficiency of photovoltaic solar cells has increased. Following these trends, solar power will become more affordable in years to come and considerable investments are to be expected. Despite the size of solar plants, the sitting procedure is a crucial factor for their efficiency and financial viability. Many aspects influence such a decision: legal, environmental, technical, and financial to name a few. This paper describes a general integrated framework to evaluate land suitability for the optimal placement of photovoltaic solar power plants, which is based on a combination of a geographic information system (GIS), remote sensing techniques, and multi-criteria decision-making methods. An application of the proposed framework for the Limassol district in Cyprus is further illustrated. The combination of a GIS and multi-criteria methods produces an excellent analysis tool that creates an extensive database of spatial and non-spatial data, which will be used to simplify problems as well as solve and promote the use of multiple criteria. A set of environmental, economic, social, and technical constrains, based on recent Cypriot legislation, European's Union policies, and expert advice, identifies the potential sites for solar park installation. The pairwise comparison method in the context of the analytic hierarchy process (AHP) is applied to estimate the criteria weights in order to establish their relative importance in site evaluation. In addition, four different methods to combine information layers and check their sensitivity were used. The first considered all the criteria as being equally important and assigned them equal weight, whereas the others grouped the criteria and graded them according to their objective perceived importance. The overall suitability of the study region for sitting solar parks is appraised through the summation rule. Strict application of the framework depicts 3.0% of the study region scoring a best-suitability index for solar resource exploitation, hence minimizing the risk in a potential investment. However, using different weighting schemes for criteria, suitable areas may reach up to 83% of the study region. The suggested methodological framework applied can be easily utilized by potential investors and renewable energy developers, through a front end web-based application with proper GUI for personalized weighting schemes. [ABSTRACT FROM AUTHOR]

Among the renewable powers sources, solar is rapidly becoming popular being inexhaustible, clean, and dependable. It is also becoming more efficient since the photovoltaic solar cells' power conversion efficiency is rising. Following these trends, solar power will become more affordable in years to come and considerable investments are to be expected. Despite the size of solar plants, the sitting procedure is a crucial factor for their efficiency and financial viability. Many aspects rule such decision; legal, environmental, technical, and financial to name some. This paper describes a general integrated framework to evaluate land suitability for the optimal placement of photovoltaic solar power plants, which is based on a combination of a Geographic Information System (GIS), remote sensing techniques and multi-criteria decision making methods.

An application of the proposed framework for Limassol District in Cyprus is further illustrated. The combination of GIS and multi-criteria methods, consist an excellent analysis tool that creates an extensive database of spatial and non spatial data that will be used to simplify problems, to solve and promote the use of multiple criteria. A set of environmental, economic, social and technical constrains based on recent Cypriot legislation, European's Union policies and experts' advices, identifies the potential sites for solar park installation. The pair-wise comparison method in the context of the analytic hierarchy process (AHP) is applied to estimate the criteria weights in order to establish their relative importance in site evaluation. In addition, four different methods to combine information layers and check their sensitivity were used. The first considered all the criteria as being equally important and assign them equal weight, while the others grouped the criteria and graded them according to their objective perceived importance. The overall suitability of the study region for sitting solar park is appraised through the summation rule. Strict application of the framework depicts 3.0 % of the study region scoring best suitability index for solar resource exploitation, hence minimizing risk of a potential investment. However, using different weighting schemes for criteria, suitable areas may reach up to 83 % of the study region. The suggested methodological framework applied can be easily utilized by potential investors and renewable energy developers, through a front end web based application with proper GUI for personalized weighting schemes. [ABSTRACT FROM AUTHOR]

In the present work diffusion of implanted nitrogen in germanium is studied as a function of implantation energy and post-implantation annealing temperature. Implantations have been performed at a constant dose and energies leading to the amorphization of the substrate. Nitrogen diffusion in Ge is anomalous (not obeying the 2nd Fick's law) towards the substrate surface on which an Al2O3 layer has been deposited before annealing for protection. There is evidence that N diffusion in Ge is interstitial-assisted and takes place in the presence of Ge interstitials gradients between the Al2O3/Ge and the former amorphous/crystalline (a/c) interface of the substrate during annealing. (© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [ABSTRACT FROM AUTHOR]

Thin films of aluminium oxide (Al2O3) and zirconium oxide (ZrO2) were prepared by Atomic Layer Deposition (ALD) on p-type (100) germanium substrates. In the present work a detailed analysis of the films by X-ray photoelectron spectroscopy (XPS) in order to investigate their chemical composition is presented. This study is dedicated to an XPS investigation of the principal core levels (Al, Zr, O) of Al2O3 and ZrO2 thin films. In particular, wide scan spectra, detailed scans for the Zr 3d, Al 2p, O 1s, and C 1s regions and related data for zirconia and alumina films are presented and discussed. The results point out the formation of Al2O3 and ZrO2 films with the presence of OH groups and carbon contamination on the surface. [ABSTRACT FROM AUTHOR]

The topic of underwater (UW) image colour correction and restoration has gained significant scientific interest in the last couple of decades. There are a vast number of disciplines, from marine biology to archaeology, that can and need to utilise the true information of the UW environment. Based on that, a significant number of scientists have contributed to the topic of UW image colour correction and restoration. In this paper, we try to make an unbiased and extensive review of some of the most significant contributions from the last 15 years. After considering the optical properties of water, as well as light propagation and haze that is caused by it, the focus is on the different methods that exist in the literature. The criteria for which most of them were designed, as well as the quality evaluation used to measure their effectiveness, are underlined. [ABSTRACT FROM AUTHOR]

AI, VR and AR have a lot of unexploited potential in the peculiar underwater environment. Photogrammetry-based approaches coupled with virtual and augmented reality (VR/AR) applications are becoming infused in interdisciplinary research in topics such as archeology, biology, industry. The Special Issue "Underwater 3D recording and modelling" is focused on challenges for 3D modeling and ways to overcome them in the underwater environment. [Extracted from the article]

This paper presents a combined subjective and objective evaluation of an application mixing interactive virtual reality (VR) experience with 360° storytelling. The hypothesis that the modern immersive archaeological VR application presenting cultural heritage from a submerged site would sustain high levels of presence, immersion, and general engagement was leveraged in the investigation of the user experience with both the subjective (questionnaires) and the objective (neurophysiological recording of the brain signals using electroencephalography (EEG)) evaluation methods. Participants rated the VR experience positively in the questionnaire scales for presence, immersion, and subjective judgement. High positive rating concerned also the psychological states linked to the experience (engagement, emotions, and the state of flow), and the experience was mostly free from difficulties linked to the accustomization to the VR technology (technology adoption to the head-mounted display and controllers, VR sickness). EEG results are in line with past studies examining brain responses to virtual experiences, while new results in the beta band suggest that EEG is a viable tool for future studies of presence and immersion in VR. [ABSTRACT FROM AUTHOR]

Land cover classification with the focus on chlorophyll-rich vegetation detection plays an important role in urban growth monitoring and planning, autonomous navigation, drone mapping, biodiversity conservation, etc. Conventional approaches usually apply the normalized difference vegetation index (NDVI) for vegetation detection. In this paper, we investigate the performance of deep learning and conventional methods for vegetation detection. Two deep learning methods, DeepLabV3+ and our customized convolutional neural network (CNN) were evaluated with respect to their detection performance when training and testing datasets originated from different geographical sites with different image resolutions. A novel object-based vegetation detection approach, which utilizes NDVI, computer vision, and machine learning (ML) techniques, is also proposed. The vegetation detection methods were applied to high-resolution airborne color images which consist of RGB and near-infrared (NIR) bands. RGB color images alone were also used with the two deep learning methods to examine their detection performances without the NIR band. The detection performances of the deep learning methods with respect to the object-based detection approach are discussed and sample images from the datasets are used for demonstrations. [ABSTRACT FROM AUTHOR]

Although aerial image-based bathymetric mapping can provide, unlike acoustic or LiDAR (Light Detection and Ranging) sensors, both water depth and visual information, water refraction poses significant challenges for accurate depth estimation. In order to tackle this challenge, we propose an image correction methodology, which first exploits recent machine learning procedures that recover depth from image-based dense point clouds and then corrects refraction on the original imaging dataset. This way, the structure from motion (SfM) and multi-view stereo (MVS) processing pipelines are executed on a refraction-free set of aerial datasets, resulting in highly accurate bathymetric maps. Performed experiments and validation were based on datasets acquired during optimal sea state conditions and derived from four different test-sites characterized by excellent sea bottom visibility and textured seabed. Results demonstrated the high potential of our approach, both in terms of bathymetric accuracy, as well as texture and orthoimage quality. [ABSTRACT FROM AUTHOR]

The metal oxide heterostructures market is exponentially growing, adhering to the trend of achieving fabrication versatility on a vast range of nonconventional electromagnetic and optical properties. A high degree of substrate tolerance and solution‐phase growth potential promise low‐cost flexible electronics and silicon‐based process compatibility. A molecule‐based complex oxide nanostructured stack integrated in an electro‐optically operable nonvolatile two‐terminal capacitive memory element is proposed. The cell demonstrates a remarkably high > 7 V memory window and write–read times down to 10 ns, promising for reliable high‐speed storage. Molecular orbital occupancy through broadband optical stimulus enables simultaneous phononic addressing and boosts the written information amount by up to 37%, achieving 10+ years storage duration. The resulting nonvolatile memories are the first‐documented complementary metal oxide semiconductor (CMOS)‐compatible long‐term‐retention molecular capacitive cell of its kind, implementing inherent structure‐emerging heat management. Great potential emerges for numerous energy‐inspired innovations, enabling functional oxide–molecular hybrids exploitation as high‐end nonvolatile memory products. [ABSTRACT FROM AUTHOR]

The determination of accurate bathymetric information is a key element for near offshore activities; hydrological studies, such as coastal engineering applications, sedimentary processes, hydrographic surveying, archaeological mapping and biological research. Through structure from motion (SfM) and multi-view-stereo (MVS) techniques, aerial imagery can provide a low-cost alternative compared to bathymetric LiDAR (Light Detection and Ranging) surveys, as it offers additional important visual information and higher spatial resolution. Nevertheless, water refraction poses significant challenges on depth determination. Till now, this problem has been addressed through customized image-based refraction correction algorithms or by modifying the collinearity equation. In this article, in order to overcome the water refraction errors in a massive and accurate way, we employ machine learning tools, which are able to learn the systematic underestimation of the estimated depths. In particular, an SVR (support vector regression) model was developed, based on known depth observations from bathymetric LiDAR surveys, which is able to accurately recover bathymetry from point clouds derived from SfM-MVS procedures. Experimental results and validation were based on datasets derived from different test-sites, and demonstrated the high potential of our approach. Moreover, we exploited the fusion of LiDAR and image-based point clouds towards addressing challenges of both modalities in problematic areas. [ABSTRACT FROM AUTHOR]

Augmented reality can be deployed in various application domains, such as enhancing human vision, manufacturing, medicine, military, entertainment, and archeology. One of the least explored areas is the underwater environment. The main benefit of augmented reality in these environments is that it can help divers navigate to points of interest or present interesting information about archaeological and touristic sites (e.g., ruins of buildings, shipwrecks). However, the harsh sea environment affects computer vision algorithms and complicates the detection of objects, which is essential for augmented reality. This paper presents a new algorithm for the detection of fiducial markers that is tailored to underwater environments. It also proposes a method that generates synthetic images with such markers in these environments. This new detector is compared with existing solutions using synthetic images and images taken in the real world, showing that it performs better than other detectors: it finds more markers than faster algorithms and runs faster than robust algorithms that detect the same amount of markers. [ABSTRACT FROM AUTHOR]

Photogrammetry using structure from motion (SfM) techniques has evolved into a powerful tool for a variety of applications. Nevertheless, limits are imposed when two-media photogrammetry is needed, in cases such as submerged archaeological site documentation. Water refraction poses a clear limit on photogrammetric applications, especially when traditional methods and standardized pipelines are followed. This work tries to estimate the error introduced to depth measurements when no refraction correction model is used and proposes an easy to implement methodology in a modern photogrammetric workflow dominated by SfM and multi-view stereo (MVS) techniques. To be easily implemented within current software and workflow, this refraction correction approach is applied at the photo level. Results over two test sites in Cyprus against reference data suggest that despite the assumptions and approximations made the proposed algorithm can reduce the effect of refraction to two times the ground pixel size, regardless of the depth. [ABSTRACT FROM AUTHOR]