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  1. Article ; Online: An Overview of Sensors for Long Range Missile Defense.

    Fontana, Simone / Di Lauro, Federica

    Sensors (Basel, Switzerland)

    2022  Volume 22, Issue 24

    Abstract: Given the increasing tensions between world powers, missile defense is a topic that is more relevant than ever. However, information on the subject is often fragmented, confusing and untrustworthy. On the other hand, we believe that an informed overview ... ...

    Abstract Given the increasing tensions between world powers, missile defense is a topic that is more relevant than ever. However, information on the subject is often fragmented, confusing and untrustworthy. On the other hand, we believe that an informed overview of the current status is important for decision makers and citizens alike. A missile is essentially a guided rocket and therefore the term can be used to describe a very wide range of weapon systems. In this paper, we focus on long-range and intercontinental threats, which we believe are more important and problematic to defend against. We provide an overview of the two most common types of sensors, space-based infrared sensors and radars, and highlight their peculiarities and, most importantly, their drawbacks that severely limit their effectiveness.
    Language English
    Publishing date 2022-12-15
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s22249871
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: GTASynth: 3D synthetic data of outdoor non-urban environments

    Curnis, Giovanni / Fontana, Simone / Sorrenti, Domenico G.

    Data in Brief. 2022 June 17,

    2022  

    Abstract: Developing point clouds registration, SLAM or place recognition algorithms requires data with a high quality ground truth (usually composed of a position and orientation). Moreover, many machine learning algorithms require large amounts of data for ... ...

    Abstract Developing point clouds registration, SLAM or place recognition algorithms requires data with a high quality ground truth (usually composed of a position and orientation). Moreover, many machine learning algorithms require large amounts of data for training. However, acquiring this kind of data in non-urban outdoor environments poses several challenges. First of all, off-road robots are usually very expensive. Above all, producing an accurate ground truth is problematic. Even the best sensor available, i.e. RTK GPS, cannot guarantee the required accuracy in every condition. Hence the scarcity of this kind of dataset for point clouds registration or SLAM in off-road conditions. For these reasons, we propose a synthetic dataset generated using Grand Theft Auto V (GTAV), a video game that accurately simulates sensing in outdoor environments. The data production technique is based on DeepGTAV-PreSIL [1]: a simulated LiDAR and a camera are installed on a vehicle which is driven through the GTAV map. Since one of the goals of our work is to produce a large amount of data to train neural networks which will then be used with real data, we have chosen the characteristics of the sensors to accurately simulate real ones. The proposed dataset is composed of 16.207 point clouds and images, divided into five sequences representing different environments, such as fields, woods and mountains. For each pair of point clouds and images we also provide the ground truth pose of the vehicle at the acquisition.
    Keywords cameras ; data collection ; games ; lidar
    Language English
    Dates of publication 2022-0617
    Publishing place Elsevier Inc.
    Document type Article
    Note Pre-press version
    ZDB-ID 2786545-9
    ISSN 2352-3409
    ISSN 2352-3409
    DOI 10.1016/j.dib.2022.108412
    Database NAL-Catalogue (AGRICOLA)

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  3. Article ; Online: GTASynth: 3D synthetic data of outdoor non-urban environments.

    Curnis, Giovanni / Fontana, Simone / Sorrenti, Domenico G

    Data in brief

    2022  Volume 43, Page(s) 108412

    Abstract: Developing point clouds registration, SLAM or place recognition algorithms requires data with a high quality ground truth (usually composed of a position and orientation). Moreover, many machine learning algorithms require large amounts of data for ... ...

    Abstract Developing point clouds registration, SLAM or place recognition algorithms requires data with a high quality ground truth (usually composed of a position and orientation). Moreover, many machine learning algorithms require large amounts of data for training. However, acquiring this kind of data in non-urban outdoor environments poses several challenges. First of all, off-road robots are usually very expensive. Above all, producing an accurate ground truth is problematic. Even the best sensor available,
    Language English
    Publishing date 2022-06-22
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 2786545-9
    ISSN 2352-3409 ; 2352-3409
    ISSN (online) 2352-3409
    ISSN 2352-3409
    DOI 10.1016/j.dib.2022.108412
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Spatial mismatch between wild bee diversity hotspots and protected areas

    Casanelles‐Abella, Joan / Fontana, Simone / Meier, Eliane / Moretti, Marco / Fournier, Betrand

    Conservation Biology. 2023 Aug., v. 37, no. 4 p.e14082-

    2023  

    Abstract: Wild bees are critical for multiple ecosystem functions but are currently threatened. Understanding the determinants of the spatial distribution of wild bee diversity is a major research gap for their conservation. We modeled wild bee α and β taxonomic ... ...

    Abstract Wild bees are critical for multiple ecosystem functions but are currently threatened. Understanding the determinants of the spatial distribution of wild bee diversity is a major research gap for their conservation. We modeled wild bee α and β taxonomic and functional diversity in Switzerland to uncover countrywide diversity patterns and determine the extent to which they provide complementary information, assess the importance of the different drivers structuring wild bee diversity, identify hotspots of wild bee diversity, and determine the overlap between diversity hotspots and the network of protected areas. We used site‐level occurrence and trait data from 547 wild bee species across 3343 plots and calculated community attributes, including taxonomic diversity metrics, community mean trait values, and functional diversity metrics. We modeled their distribution with predictors describing gradients of climate, resource availability (vegetation), and anthropogenic influence (i.e., land‐use types and beekeeping intensity). Wild bee diversity changed along gradients of climate and resource availability; high‐elevation areas had lower functional and taxonomic α diversity, and xeric areas harbored more diverse bee communities. Functional and taxonomic β diversities diverged from this pattern, with high elevations hosting unique species and trait combinations. The proportion of diversity hotspots included in protected areas depended on the biodiversity facet, but most diversity hotspots occurred in unprotected land. Climate and resource availability gradients drove spatial patterns of wild bee diversity, resulting in lower overall diversity at higher elevations, but simultaneously greater taxonomic and functional uniqueness. This spatial mismatch among distinct biodiversity facets and the degree of overlap with protected areas is a challenge to wild bee conservation, especially in the face of global change, and calls for better integrating unprotected land. The application of spatial predictive models represents a valuable tool to aid the future development of protected areas and achieve wild bee conservation goals.
    Keywords anthropogenic activities ; apiculture ; bees ; climate ; ecosystems ; functional diversity ; global change ; land use ; species diversity ; vegetation ; wildlife management ; Switzerland
    Language English
    Dates of publication 2023-08
    Publishing place John Wiley & Sons, Ltd
    Document type Article ; Online
    Note JOURNAL ARTICLE
    ZDB-ID 58735-7
    ISSN 1523-1739 ; 0888-8892
    ISSN (online) 1523-1739
    ISSN 0888-8892
    DOI 10.1111/cobi.14082
    Database NAL-Catalogue (AGRICOLA)

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  5. Article ; Online: Low resource availability drives feeding niche partitioning between wild bees and honeybees in a European city

    Casanelles‐Abella, Joan / Fontana, Simone / Fournier, Bertrand / Frey, David / Moretti, Marco

    Ecological Applications. 2023 Jan., v. 33, no. 1 p.e2727-

    2023  

    Abstract: Cities are socioecological systems that filter and select species, therefore establishing unique species assemblages and biotic interactions. Urban ecosystems can host richer wild bee communities than highly intensified agricultural areas, specifically ... ...

    Abstract Cities are socioecological systems that filter and select species, therefore establishing unique species assemblages and biotic interactions. Urban ecosystems can host richer wild bee communities than highly intensified agricultural areas, specifically in resource‐rich urban green spaces such as allotments and family gardens. At the same time, urban beekeeping has boomed in many European cities, raising concerns that the fast addition of a large number of managed bees could deplete the existing floral resources, triggering competition between wild bees and honeybees. Here, we studied the interplay between resource availability and the number of honeybees at local and landscape scales and how this relationship influences wild bee diversity. We collected wild bees and honeybees in a pollination experiment using four standardized plant species with distinct floral morphologies. We performed the experiment in 23 urban gardens in the city of Zurich (Switzerland), distributed along gradients of urban and local management intensity, and measured functional traits related to resource use. At each site, we quantified the feeding niche partitioning (calculated as the average distance in the multidimensional trait space) between the wild bee community and the honeybee population. Using multilevel structural equation models (SEM), we tested direct and indirect effects of resource availability, urban beekeeping, and wild bees on the community feeding niche partitioning. We found an increase in feeding niche partitioning with increasing wild bee species richness. Moreover, feeding niche partitioning tended to increase in experimental sites with lower resource availability at the landscape scale, which had lower abundances of honeybees. However, beekeeping intensity at the local and landscape scales did not directly influence community feeding niche partitioning or wild bee species richness. In addition, wild bee species richness was positively influenced by local resource availability, whereas local honeybee abundance was positively affected by landscape resource availability. Overall, these results suggest that direct competition for resources was not a main driver of the wild bee community. Due to the key role of resource availability in maintaining a diverse bee community, our study encourages cities to monitor floral resources to better manage urban beekeeping and help support urban pollinators.
    Keywords apiculture ; equations ; honey bees ; landscapes ; pollination ; species richness ; Switzerland
    Language English
    Dates of publication 2023-01
    Publishing place John Wiley & Sons, Inc.
    Document type Article ; Online
    Note JOURNAL ARTICLE
    ZDB-ID 1074505-1
    ISSN 1939-5582 ; 1051-0761
    ISSN (online) 1939-5582
    ISSN 1051-0761
    DOI 10.1002/eap.2727
    Database NAL-Catalogue (AGRICOLA)

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  6. Book ; Online: Individual-level trait diversity in photosynthetic organisms and its implications for ecosystem functioning

    Fontana, Simone

    2016  

    Abstract: Dissertation, ETH Zürich, 2016, No. ... ...

    Abstract Dissertation, ETH Zürich, 2016, No. 23953
    Keywords SYSTEMÖKOLOGIE ; ÖKOSYSTEMANALYSE ; ÖKOSYSTEMFORSCHUNG (ÖKOLOGIE) ; POPULATIONSDYNAMIK (ÖKOLOGIE) ; PHYTOPLANKTON (PFLANZENÖKOLOGIE) ; DIVERSITÄT (PFLANZENÖKOLOGIE) ; ÖKOLOGISCHE WECHSELWIRKUNGEN UND BEZIEHUNGEN (ÖKOLOGIE) ; DATENBEHANDLUNG + DATENAUSWERTUNG (EXPERIMENTELLE BIOLOGIE)
    Language English
    Publisher Zürich
    Publishing country ch
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Spatial mismatch between wild bee diversity hotspots and protected areas.

    Casanelles-Abella, Joan / Fontana, Simone / Meier, Eliane / Moretti, Marco / Fournier, Betrand

    Conservation biology : the journal of the Society for Conservation Biology

    2023  Volume 37, Issue 4, Page(s) e14082

    Abstract: Wild bees are critical for multiple ecosystem functions but are currently threatened. Understanding the determinants of the spatial distribution of wild bee diversity is a major research gap for their conservation. We modeled wild bee α and β taxonomic ... ...

    Abstract Wild bees are critical for multiple ecosystem functions but are currently threatened. Understanding the determinants of the spatial distribution of wild bee diversity is a major research gap for their conservation. We modeled wild bee α and β taxonomic and functional diversity in Switzerland to uncover countrywide diversity patterns and determine the extent to which they provide complementary information, assess the importance of the different drivers structuring wild bee diversity, identify hotspots of wild bee diversity, and determine the overlap between diversity hotspots and the network of protected areas. We used site-level occurrence and trait data from 547 wild bee species across 3343 plots and calculated community attributes, including taxonomic diversity metrics, community mean trait values, and functional diversity metrics. We modeled their distribution with predictors describing gradients of climate, resource availability (vegetation), and anthropogenic influence (i.e., land-use types and beekeeping intensity). Wild bee diversity changed along gradients of climate and resource availability; high-elevation areas had lower functional and taxonomic α diversity, and xeric areas harbored more diverse bee communities. Functional and taxonomic β diversities diverged from this pattern, with high elevations hosting unique species and trait combinations. The proportion of diversity hotspots included in protected areas depended on the biodiversity facet, but most diversity hotspots occurred in unprotected land. Climate and resource availability gradients drove spatial patterns of wild bee diversity, resulting in lower overall diversity at higher elevations, but simultaneously greater taxonomic and functional uniqueness. This spatial mismatch among distinct biodiversity facets and the degree of overlap with protected areas is a challenge to wild bee conservation, especially in the face of global change, and calls for better integrating unprotected land. The application of spatial predictive models represents a valuable tool to aid the future development of protected areas and achieve wild bee conservation goals.
    MeSH term(s) Animals ; Bees ; Ecosystem ; Conservation of Natural Resources ; Biodiversity ; Switzerland
    Language English
    Publishing date 2023-05-25
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 58735-7
    ISSN 1523-1739 ; 0888-8892
    ISSN (online) 1523-1739
    ISSN 0888-8892
    DOI 10.1111/cobi.14082
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Measuring individual‐level trait diversity: a critical assessment of methods

    Olusoji, Oluwafemi D. / Barabás, György / Spaak, Jurg W. / Fontana, Simone / Neyens, Thomas / De Laender, Frederik / Aerts, Marc

    Oikos. 2023 Apr., v. 2023, no. 4 p.e09178-

    2023  

    Abstract: Individual‐level trait diversity has been identified as an essential component of trait diversity (TD), influencing community assembly and structure. Traditionally, one employs trait diversity indices to measure facets of individual‐level trait diversity ...

    Abstract Individual‐level trait diversity has been identified as an essential component of trait diversity (TD), influencing community assembly and structure. Traditionally, one employs trait diversity indices to measure facets of individual‐level trait diversity (divergence, richness and evenness). However, the application of species‐level trait diversity indices to individual‐level traits data and their implications have not been adequately studied. Thus, we examined the possible challenges of using four commonly used multi‐trait TD indices: Rao's quadratic entropy (Rao), functional dispersion (FDis), functional evenness (FEve) and functional richness (FRic); two indices primarily developed to measure individual‐level trait diversity: trait evenness distribution (TED‐for evenness) and trait onion peeling (TOP‐for richnness); and a modified version of TED (TEDM‐for evenness). Additionally, we considered an index that integrates both evenness and richness by generalizing ordinary Hill indices for traits (coined HIT). We measured individual‐level trait diversity with these indices using simulated traits data and experimental data from a growth experiment with cyanobacteria. Comparing the observed trends from the indices with the expected trends, we observed that only the trait divergence indices (FDis and Rao) produced the expected trends in the simulation scenarios and experimental data. TED and TEDM are not robust against the number of individuals used, and FEve is not sensitive to some changes in the location of individuals in the trait space. Also, TOP proved to be a discontinuous function dependent on the number of individuals, and FRic did not produce the anticipated trend when changes in the trait space did not affect the edges of the trait space. HIT did produce the anticipated changes, but it was only reliable when many individuals were sampled. In summary, applying these individual‐level trait diversity indices to quantify anything except trait divergence may lead to misinterpretation of the original situation of trait distribution in the trait space if their specific properties are not adequately considered.
    Keywords Cyanobacteria ; community structure ; dispersions ; entropy ; onion peels ; sampling
    Language English
    Dates of publication 2023-04
    Publishing place Blackwell Publishing Ltd
    Document type Article ; Online
    Note JOURNAL ARTICLE
    ZDB-ID 207359-6
    ISSN 0030-1299
    ISSN 0030-1299
    DOI 10.1111/oik.09178
    Database NAL-Catalogue (AGRICOLA)

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  9. Article ; Online: Using leaf traits to explain species co-existence and its consequences for primary productivity across a forest-steppe ecotone

    He, Peng / Fontana, Simone / Ma, Chengcang / Liu, Heyong / Xu, Li / Wang, Pi / Jiang, Yong / Li, Mai-He

    Science of the Total Environment. 2023 Feb., v. 859 p.160139-

    2023  

    Abstract: Trait-based approaches have been widely applied to uncover the mechanisms determining community assembly and biodiversity-ecosystem functioning relationships. However, they have rarely been used in forest-steppe ecotones. These ecosystems are extremely ... ...

    Abstract Trait-based approaches have been widely applied to uncover the mechanisms determining community assembly and biodiversity-ecosystem functioning relationships. However, they have rarely been used in forest-steppe ecotones. These ecosystems are extremely sensitive to disturbances due to their relatively complex ecosystem structures, functionings and processes. In this study, we selected seven sites along a transect from closed canopy forests (CF) to forest-steppe ecotones (FSE) and meadow steppes (MS) in northeast China. Six leaf functional traits (i.e. leaf nitrogen and phosphorus contents, leaf length and thickness, single leaf area and leaf mass per unit area, LMA) as well as the community composition and aboveground biomass at each site were measured. Both functional trait diversity indices (richness, evenness and divergence) and community-weighted mean trait values (CWMs) were calculated to quantify community trait distributions. We found that dominant species in the FSE communities showed acquisitive strategies with highest leaf nitrogen (Mean ± SE: 19.6 ± 0.5 mg g⁻¹) and single leaf area (19.2 ± 1.3 cm²), but the lowest LMA (59.6 ± 1.3 g cm⁻²) values compared to adjacent CF and MS communities. The ecotone communities also exhibited the largest functional trait richness (TOP), evenness (TED) and divergence (FDis) values (0.46, 0.92 and 0.67, respectively). Overall, niche differentiation emerges as the main mechanism influencing the coexistence of plant species in ecotone ecosystems. In addition, CWMs of leaf traits were the most important predictors for estimating variations in aboveground productivity across the transect, suggesting a major influence of dominant species. Our findings suggest that vegetation management practices in forest-steppe ecotones should increasingly focus on community functional trait diversity, and support the establishment and regeneration of plant species with rapid resource acquisition strategies.
    Keywords aboveground biomass ; canopy ; community structure ; dominant species ; ecological differentiation ; ecosystems ; environment ; forest steppe ; leaf area ; leaf length ; leaf mass ; leaves ; meadows ; nitrogen ; phosphorus ; primary productivity ; China ; Biodiversity ; Functional diversity ; Niche theory ; Ecosystem functioning ; Community assembly
    Language English
    Dates of publication 2023-02
    Publishing place Elsevier B.V.
    Document type Article ; Online
    ZDB-ID 121506-1
    ISSN 1879-1026 ; 0048-9697
    ISSN (online) 1879-1026
    ISSN 0048-9697
    DOI 10.1016/j.scitotenv.2022.160139
    Database NAL-Catalogue (AGRICOLA)

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  10. Book ; Online: A Termination Criterion for Probabilistic PointClouds Registration

    Fontana, Simone / Sorrenti, Domenico G.

    2020  

    Abstract: Probabilistic Point Clouds Registration (PPCR) is an algorithm that, in its multi-iteration version, outperformed state of the art algorithms for local point clouds registration. However, its performances have been tested using a fixed high number of ... ...

    Abstract Probabilistic Point Clouds Registration (PPCR) is an algorithm that, in its multi-iteration version, outperformed state of the art algorithms for local point clouds registration. However, its performances have been tested using a fixed high number of iterations. To be of practical usefulness, we think that the algorithm should decide by itself when to stop, to avoid an excessive number of iterations and, therefore, wasting computational time. With this work, we compare different termination criterion on several datasets and prove that the chosen one produce very good results that are comparable to those obtained using a very high number of iterations while saving computational time.
    Keywords Computer Science - Robotics ; Computer Science - Computer Vision and Pattern Recognition
    Publishing date 2020-10-10
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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