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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: M. Silberberg; M.M. Mialon; B. Meunier; I. Veissier;

    International audience; High-energy diets increase the risk of Sub-Acute Ruminal Acidosis (SARA) inruminants. The behaviour of ruminants is modified under SARA however the impact onbehaviour of a high-energy diet and those of SARA per se are often confounded. Weaimed at distinguishing the effects of the diet and of SARA on cow behaviour. We fed28 Holstein cows a low-starch diet (low starch diet, 10.5% starch) or a high-starch diet(high starch diet, 31.5% starch). Control cows (n = 14) received the low starch diet for60 days, Challenge cows (n = 14) received the same diet except for a 2-week periodduring which they received the high starch diet and the 10 preceding days to ensurethe transition between diets. We monitored ruminal pH and activity of cows thanks tosensors, dry matter intake (DMI), and milk yield of each cow on a daily basis. TheSARA status was defined according to the relative decrease in ruminal pH and to pHvariability. High starch diet induced SARA more often than low starch diet (81% dayswhen cows received high starch diet vs. 8% when they received low starch diet. Highstarch diet also decreased milk yield and made cows spending less time eating buteating more quickly (Challenge vs. Control cows during the challenge period: milkyield, 20.0 vs. 18.2 L/d; % time spent eating, 22.5 vs. 27.6; eating rate, 77.1 vs. 69.6 gDMI/min; P (diet x period) 0.50). In conclusion, an increase ineating rate, especially combined with a decrease in milk yield should alert farmers tothe risk of ruminal acidosis.

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    Animal - Open Space
    Article . 2024 . Peer-reviewed
    License: CC BY NC ND
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Animal - Open Spacearrow_drop_down
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      Animal - Open Space
      Article . 2024 . Peer-reviewed
      License: CC BY NC ND
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Gutiérrez Escobar, Norma; Otero Calviño, Beatriz; Rodríguez Luna, Eva; Utrera Iglesias, Gladys Miriam; +2 Authors

    Nowadays, companies collect massive quantities of data to enhance their operations, often at the expense of sharing user sensible information. This data is widely used to train Deep Learning (DL) neural networks to model, classify, or recognize complex data. These activities enable companies to offer an array of services to users, such as precise advertising and optimal location services. This study explores potential solutions for preserving privacy while utilizing DL applications. To address the privacy issue, we develop a privacy-preserving framework specifically designed for fog computing environments. Unlike traditional cloud computing architectures, fog embedded architectures only share a small portion of user data with a nearby fog node, ensuring that the majority of sensitive data remains secure. Within these fog nodes, we incorporate two additional algorithms, namely Generalization and Threshold, to enhance the privacy-preserving capabilities of the framework. The first algorithm, Generalization, introduces a validation dataset within the fog nodes which not only increases the accuracy of the fog-embedded framework but also ensures that user data is preserved. The second algorithm, Threshold, is responsible for protecting user data samples and reducing the amount of information sent to the server. By combining these two algorithms, we are able to provide an additional layer of protection for user privacy while still maintaining the accuracy of the model. We conduct an evaluation to test its effectiveness using two separate datasets. In addition, we analyze them through a Feed Forward Neural Network (FFNN) and compare the results with a traditional centralized architecture to validate the effectiveness of the proposed framework. The results of our evaluation demonstrate that the proposed privacy-preserving framework, when combined with the Generalization and Threshold algorithms, can preserve up to 38.44% of user data. Additionally, we were able to extend the framework to multiple fog nodes without compromising the network’s accuracy, as we only observed a 0.1% decrease in accuracy when using the proposed architecture. This study emphasizes the importance of preserving user information while using DL applications and provides a solution that trains the desired network without violating user privacy, hence preserving their anonymity. Overall, the study highlights the potential of Federated Deep Learning to improve the accuracy and privacy of DL applications in fog computing environments. This work is partially supported by the Spanish Ministry of Science and Innovation, Spain under contracts PID2021-124463OB-IOO and PID2019-107255GB-C22; by the Generalitat de Catalunya, Spain under grant 2021SGR00326; and by the DRAC (IU16-011591), the HORIZON Vitamin-V, Spain(101093062), the HORIZON-AG PHOENI2X, Spain (101070586) and the HORIZON HORSE, Spain (101096342) projects. Peer Reviewed

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    Other literature type . Article . 2024 . Peer-reviewed
    License: CC BY NC ND
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    Engineering Applications of Artificial Intelligence
    Article . 2024 . Peer-reviewed
    License: CC BY NC ND
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ UPCommons. Portal de...arrow_drop_down
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      Other literature type . Article . 2024 . Peer-reviewed
      License: CC BY NC ND
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      Engineering Applications of Artificial Intelligence
      Article . 2024 . Peer-reviewed
      License: CC BY NC ND
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Nikolaos Stathoulopoulos; Anton Koval; George Nikolakopoulos;

    Localization algorithms that rely on 3D LiDAR scanners often encounter temporary failures due to various factors, such as sensor faults, dust particles, or drifting. These failures can result in a misalignment between the robot’s estimated pose and its actual position in the global map. To address this issue, the process of global re-localization becomes essential, as it involves accurately estimating the robot’s current pose within the given map. In this article, we propose a novel global re-localization framework that addresses the limitations of current algorithms heavily reliant on scan matching and direct point cloud feature extraction. Unlike most methods, our framework eliminates the need for an initial guess and provides multiple top-� candidates for selection, enhancing robustness and flexibility. Furthermore, we introduce an event-based re-localization trigger module, enabling autonomous robotic missions. Focusing on subterranean environments with low features, we leverage range image descriptors derived from 3D LiDAR scans to preserve depth information. Our approach enhances a state-of-the-art data-driven descriptor extraction framework for place recognition and orientation regression by incorporating a junction detection module that utilizes the descriptors for classification purposes. The effectiveness of the proposed approach was evaluated across three distinct real-life subterranean environments. Validerad;2023;Nivå 2;2023-09-22 (joosat);CC BY 4.0 License

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ arXiv.org e-Print Ar...arrow_drop_down
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    https://doi.org/10.48550/arxiv...
    Article . 2022
    License: arXiv Non-Exclusive Distribution
    Data sources: Datacite; Sygma
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    Expert Systems with Applications
    Article . 2024 . Peer-reviewed
    License: CC BY
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ arXiv.org e-Print Ar...arrow_drop_down
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      https://doi.org/10.48550/arxiv...
      Article . 2022
      License: arXiv Non-Exclusive Distribution
      Data sources: Datacite; Sygma
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      Expert Systems with Applications
      Article . 2024 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Osório Nhiuane; Sá Nogueira Lisboa; Meizal Popat; Almeida Sitoe;

    Food insecurity, deforestation, and forest degradation are significant challenges to achieving the Sustainable Development Goals in sub-Saharan Africa. Slash-and-burn cultivation and conventional logging (timber and charcoal production) are two interrelated activities that lead to forest loss and undermine food security. However, the environmental and economic incentives to clear or conserve the forest have yet to be discovered. To address this gap, our study collected costs and benefits data to assess financial profitability and viability related to forest conversion to slash-and-burn cultivation options (e.g., mono-cropping of maize and intercropping between maize, cassava and pigeon peas) and forestry exploitation (logging and charcoal production) practices in smallholders in Zambézia province, central Mozambique. Conventional logging was the highest cost activity (1662 US$ ha−1) compared to charcoal production (278 US$ ha−1) and cropping systems. Estimated total costs for cropping ranged from 302 US$ ha−1 to 508 US$ ha−1. Cropping systems appear more profitable in the first year of investment (30 to 1495 US$ ha−1) than forestry activities. On the other hand, the estimated profits for logging and charcoal production are negative at 15 US$ ha−1 and 782 US$ ha−1, respectively. Regarding viability, cropping systems showed the highest indicators compared to forestry activities. Based on the financial assessment, cropping systems seem attractive land use options with the fastest and highest financial returns and the lowest production costs. As such, it is not easy to prevent them. The long-term implications of increasing deforestation to the detriment of the cropping system can translate into rapid ecosystem degradation that can worsen livelihoods.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Trees, Forests and P...arrow_drop_down
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    Trees, Forests and People
    Article . 2024 . Peer-reviewed
    License: CC BY NC ND
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    DOAJ
    Article . 2024
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Trees, Forests and P...arrow_drop_down
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      Trees, Forests and People
      Article . 2024 . Peer-reviewed
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    Authors: David R. Thompson; Robert O. Green; Christine Bradley; Philip G. Brodrick; +52 Authors

    EMIT is supported by the National Aeronautics and Space Administration Earth Venture Instrument program, under the Earth Science Division of the Science Mission Directorate. K. Dana Chadwick is supported by the NASA Applied Sciences Program. Carlos P´ erez García- Pando and María Gonçalves Ageitos acknowledge support from the European Research Council (ERC) Consolidator Grant FRAGMENT (grant agreement No. 773051), and the AXA Chair on Sand and Dust Storms at the Barcelona Supercomputing Center funded by the AXA Research Fund. Martina Klose has received funding through the Helmholtz Association’s Initiative and Networking Fund (grant agreement No. VH-NG-1533). We thank Jeffrey Czapla-Myers and the University of Arizona team for their maintenance and operation of the Railroad Valley automated calibration facility. This research was performed at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. We acknowledge the support and assistance of NASA’s International Space Station Program. The USGS authors’ contribution to this published Work was prepared by U.S. federal government employees as part of their official duties and constitutes a “work of the United States government,” and is considered to be in the public domain and therefore domestic copyright does not apply. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Copyright 2024 California Institute of Technology. All rights reserved. US Government Support Acknowledged. The Earth surface Mineral dust source InvesTigation (EMIT) is a remote visible to shortwave infrared (VSWIR) imaging spectrometer that has been operating onboard the International Space Station since July 2022. This article describes EMIT's on-orbit spectroradiometric calibration and validation. Accurate spectroscopy is vital to achieve consistent mapping results with orbital imaging spectrometers. EMIT takes a unique approach to this challenge, with just six optical elements, no shutter, and no onboard calibration systems. Its simple design focuses on uniformity and stability to enable vicarious spectroradiometric calibration. Our experiments demonstrate that this approach is successful, approaching the fidelity of manual field spectroscopy in some cases, and enabling new and more accurate products across diverse Earth science disciplines. EMIT achieves several notable firsts for an instrument of its class. It demonstrates successful on-orbit adjustments of Focal Plane Array (FPA) alignment with sub-micron precision. It offers spectral uniformity better than 98%. Optical artifacts in the measurement channels are at least three orders of magnitude below the primary solar-reflected surface signals. Its noise performance enables percent-level discrimination in the depths of mineral absorption features. In these aspects, EMIT satisfies the stringent performance needs for the next generation of VSWIR imaging spectrometers to observe the Earth's ecosystems, geology, and water resources. Article signat per 56 autors: David R. Thompson, Robert O. Green, Christine Bradley, Philip G. Brodrick, Natalie Mahowald, Eyal Ben Dor, Matthew Bennett, Michael Bernas, Nimrod Carmon, K. Dana Chadwick, Roger N. Clark, Red Willow Coleman, Evan Cox, Ernesto Diaz, Michael L. Eastwood, Regina Eckert, Bethany L. Ehlmann, Paul Ginoux, María Gonçalves Ageitos, Kathleen Grant, Luis Guanter, Daniela Heller Pearlshtien, Mark Helmlinger, Harrison Herzog, Todd Hoefen, Yue Huang, Abigail Keebler, Olga Kalashnikova, Didier Keymeulen, Raymond Kokaly, Martina Klose, Longlei Li, Sarah R. Lundeen, John Meyer, Elizabeth Middleton, Ron L. Miller, Pantazis Mouroulis, Bogdan Oaida, Vincenzo Obiso, Francisco Ochoa, Winston Olson-Duvall, Gregory S. Okin, Thomas H. Painter, Carlos Pérez García-Pando, Randy Pollock, Vincent Realmuto, Lucas Shaw, Peter Sullivan, Gregg Swayze, Erik Thingvold, Andrew K. Thorpe, Suresh Vannan, Catalina Villarreal, Charlene Ung, Daniel W. Wilson, Sander Zandbergen. Objectius de Desenvolupament Sostenible::13 - Acció per al Clima Peer Reviewed

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    Authors: D.M.R. Sampath; J.G. Freitas; J.A. Dias;

    The Drivers-Pressures-State-Impact-Response (DPSIR) framework was employed to understand the land use policies developed to manage coastal sand dunes and their consequences in Oregon, United States of America, during two contrasting periods: from the 19th to the late 20th century and from there to the early 21st century. A combination of historical data and scientific literature was used for this study. Dune destabilization became a socio-economic issue as Euro-Americans settled in Oregon in the 19th century. Ammophila arenaria and Ammophila breviligulata were widely used for stabilization. This led to a paradigm shift regarding dunes, at a time when their management was becoming more complex due to socio-natural factors. As non-native beachgrasses turned invasive causing the loss of biodiversity and habitats, their removal became the focus to restore the active dunes to support the natural processes of the ecosystem. However, the removal of these beachgrasses, particularly, Ammophila arenaria, results in low dune heights, increasing the risk of coastal flooding by reducing their effectiveness as a natural defense against sea-level rise and extreme storm surges. The reason for the contrasting dune management policies in Oregon since the 1930 s is that the management response to environmental impacts due to human drivers creates new drivers, pressures, and corresponding impacts, as shown in the DPSIR analysis. Thus, land use policies for managing coastal dunes in Oregon and other places must balance efforts to restore the native biodiversity while minimizing coastal flooding in a context of accelerating and continuous sea-level rise in the 21st century.

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    Land Use Policy; ZENODO
    Article . 2024 . Peer-reviewed
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    Data sources: ZENODO; Crossref
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      Land Use Policy; ZENODO
      Article . 2024 . Peer-reviewed
      License: CC BY NC ND
      Data sources: ZENODO; Crossref
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    Authors: Franziska Gaede (b. Wolpert); Cristina Quintas-Soriano; Bill Davison; Tobias Plieninger;

    In a time of multiple global challenges, trees gain more and more attention as an important component of sustainable land use systems, as they can produce food and provide multiple other ecosystem services at the same time. In Germany, traditional orchard meadows (so-called “Streuobstwiesen”) are in decline, although they are well known for their ecological value. In modern agroforestry systems staple perennial food crops seem to be rarely integrated. Here, we propose to use emerging chestnut cultivation for revitalizing traditional orchard meadows, diversifying forests, and integrating perennial staple food crops in modern agroforestry systems. In this study, we interviewed 64 chestnut growers in Germany and aimed to (1) explore characteristics of chestnut stands and management; (2) evaluate the main motivations, aims, and challenges of chestnut growers; (3) identify perceived outcomes of chestnut cultivation and measures for upscaling; and (4) analyze differences between groups of chestnut growers. Our results show that most growers aimed to increase tree numbers and foster the spread of chestnut trees as cultural assets. Sustainable food production was the motivation most often named by the respondents. A guide for cultivation, as well as better funding, were mentioned as the most wanted and easy to implement measures for up-scaling production and consumption. Junior chestnut growers were better connected to other chestnut growers and were more motivated by sustainable food production than senior growers. Pest and diseases as well as legal and funding situations were aspects hampering chestnut cultivation. We suggest that chestnut trees can serve as a valuable element of a diverse tree crop landscape providing staple food crops while supporting ecosystem services.

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    Trees, Forests and People
    Article . 2024 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    DOAJ
    Article . 2024
    Data sources: DOAJ
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      Trees, Forests and People
      Article . 2024 . Peer-reviewed
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  • Authors: Hodel, Leonie; Wegner, Jan Dirk; Sainte Fare Garnot, Vivien; Rocha-Gomes, Francisco; +2 Authors

    Dataset for the regrssion analysis for the manuscript "Deep learning-based cattle counts on satellite imagery offer evidence regarding land use and policy impact in the Brazilian Amazon.".

    ZENODOarrow_drop_down
    ZENODO
    Dataset . 2024
    Data sources: Datacite
    ZENODO
    Dataset . 2024
    Data sources: ZENODO
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      ZENODO
      Dataset . 2024
      Data sources: Datacite
      ZENODO
      Dataset . 2024
      Data sources: ZENODO
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    Authors: Pirotti, Francesco; Kutchartt, Erico; José Ramón Gonzalez Olabarria;

    WORKING VERSION. All layers will be visible in this linked webgis app along with estimated error. <== To Be Updated in new final version, not yet so. The layers available in this dataset are in a WGS84 geographic coordinate reference system (EPSG:4326) where latitude and longitude coordinates at 0.0008983 degrees ground sampling distance per cell, which corresponds to about 1 ha, i.e. ~100 m x ~100 m at the equator, but decreases in area with increasing latitude as the coordinate system is not equal-area, e.g. ~70 m west-est direction at 45° latitude and ~50 m west-est direction at 60° latitude. A_Aspect.tif, A_slope.tif and A__elevation.tif - Earth surface height above sea level and morphology. Prefix was added to group them in Zenodo. biomass.tif - Biomass values at year 2020, Mg/ha. canopyBulkDensity.tif - Amount of canopy biomass per volume of canopy (kg/m3) canopyBaseHeight.tif - Height of canopy start measured from the ground (m) canopyCover.tif - percent of canopy coverage - resampled and updated from the map of Hansen et al. 2005 canopyHeight.tif - Total height of canopy from the ground (m) - resampled from the map of Lang, N., et al. (2023) Fuel Model FuelModelClasses_ScottBurgan.tif - the category of Fuel Model according to Scott&Burgan 2005 FuelModelClasses_Aragonese.tif - the category of Fuel Model according to Aragonese et al. 2023 DOI: 10.5194/essd-15-1287-2023 - values are from 1 to 24, with a Look Up Table for correspondence (values are ordered matching the order in table 1 of the article) . FuelModelClasses_ScottBurgan.clr/qml CLR/QML - style file for QGIS FuelModelClasses_Aragonese.clr/qml CLR/QML - style file for QGIS FuelModelPercent.tif - the percent of fuel model category belonging to that pixel, values range between 50 and 100. Allows to spot pixels with expected mixed fuel categories.

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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Dataset . 2024
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      Data sources: Datacite
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    Authors: nicolas, olatz; Larrinaga, Felix;

    This dataset contains the information used in the drOp project (Digitally enabled social district renovation processes for age-friendly environments driving social innovation and local economic development. Num.101080025) to build a multidimensional characterization of Ermua and the Santa Ana neighbourhood through relevant indicators, and its visualisation in a Geographic Information System (GIS) by analysing statistical data, as well as other urban and social data available

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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2024
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      Data sources: ZENODO
      ZENODO
      Dataset . 2024
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: M. Silberberg; M.M. Mialon; B. Meunier; I. Veissier;

    International audience; High-energy diets increase the risk of Sub-Acute Ruminal Acidosis (SARA) inruminants. The behaviour of ruminants is modified under SARA however the impact onbehaviour of a high-energy diet and those of SARA per se are often confounded. Weaimed at distinguishing the effects of the diet and of SARA on cow behaviour. We fed28 Holstein cows a low-starch diet (low starch diet, 10.5% starch) or a high-starch diet(high starch diet, 31.5% starch). Control cows (n = 14) received the low starch diet for60 days, Challenge cows (n = 14) received the same diet except for a 2-week periodduring which they received the high starch diet and the 10 preceding days to ensurethe transition between diets. We monitored ruminal pH and activity of cows thanks tosensors, dry matter intake (DMI), and milk yield of each cow on a daily basis. TheSARA status was defined according to the relative decrease in ruminal pH and to pHvariability. High starch diet induced SARA more often than low starch diet (81% dayswhen cows received high starch diet vs. 8% when they received low starch diet. Highstarch diet also decreased milk yield and made cows spending less time eating buteating more quickly (Challenge vs. Control cows during the challenge period: milkyield, 20.0 vs. 18.2 L/d; % time spent eating, 22.5 vs. 27.6; eating rate, 77.1 vs. 69.6 gDMI/min; P (diet x period) 0.50). In conclusion, an increase ineating rate, especially combined with a decrease in milk yield should alert farmers tothe risk of ruminal acidosis.

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    Animal - Open Space
    Article . 2024 . Peer-reviewed
    License: CC BY NC ND
    Data sources: Crossref
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      Animal - Open Space
      Article . 2024 . Peer-reviewed
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    Authors: Gutiérrez Escobar, Norma; Otero Calviño, Beatriz; Rodríguez Luna, Eva; Utrera Iglesias, Gladys Miriam; +2 Authors

    Nowadays, companies collect massive quantities of data to enhance their operations, often at the expense of sharing user sensible information. This data is widely used to train Deep Learning (DL) neural networks to model, classify, or recognize complex data. These activities enable companies to offer an array of services to users, such as precise advertising and optimal location services. This study explores potential solutions for preserving privacy while utilizing DL applications. To address the privacy issue, we develop a privacy-preserving framework specifically designed for fog computing environments. Unlike traditional cloud computing architectures, fog embedded architectures only share a small portion of user data with a nearby fog node, ensuring that the majority of sensitive data remains secure. Within these fog nodes, we incorporate two additional algorithms, namely Generalization and Threshold, to enhance the privacy-preserving capabilities of the framework. The first algorithm, Generalization, introduces a validation dataset within the fog nodes which not only increases the accuracy of the fog-embedded framework but also ensures that user data is preserved. The second algorithm, Threshold, is responsible for protecting user data samples and reducing the amount of information sent to the server. By combining these two algorithms, we are able to provide an additional layer of protection for user privacy while still maintaining the accuracy of the model. We conduct an evaluation to test its effectiveness using two separate datasets. In addition, we analyze them through a Feed Forward Neural Network (FFNN) and compare the results with a traditional centralized architecture to validate the effectiveness of the proposed framework. The results of our evaluation demonstrate that the proposed privacy-preserving framework, when combined with the Generalization and Threshold algorithms, can preserve up to 38.44% of user data. Additionally, we were able to extend the framework to multiple fog nodes without compromising the network’s accuracy, as we only observed a 0.1% decrease in accuracy when using the proposed architecture. This study emphasizes the importance of preserving user information while using DL applications and provides a solution that trains the desired network without violating user privacy, hence preserving their anonymity. Overall, the study highlights the potential of Federated Deep Learning to improve the accuracy and privacy of DL applications in fog computing environments. This work is partially supported by the Spanish Ministry of Science and Innovation, Spain under contracts PID2021-124463OB-IOO and PID2019-107255GB-C22; by the Generalitat de Catalunya, Spain under grant 2021SGR00326; and by the DRAC (IU16-011591), the HORIZON Vitamin-V, Spain(101093062), the HORIZON-AG PHOENI2X, Spain (101070586) and the HORIZON HORSE, Spain (101096342) projects. Peer Reviewed

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    Other literature type . Article . 2024 . Peer-reviewed
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    Engineering Applications of Artificial Intelligence
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      Engineering Applications of Artificial Intelligence
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    Authors: Nikolaos Stathoulopoulos; Anton Koval; George Nikolakopoulos;

    Localization algorithms that rely on 3D LiDAR scanners often encounter temporary failures due to various factors, such as sensor faults, dust particles, or drifting. These failures can result in a misalignment between the robot’s estimated pose and its actual position in the global map. To address this issue, the process of global re-localization becomes essential, as it involves accurately estimating the robot’s current pose within the given map. In this article, we propose a novel global re-localization framework that addresses the limitations of current algorithms heavily reliant on scan matching and direct point cloud feature extraction. Unlike most methods, our framework eliminates the need for an initial guess and provides multiple top-� candidates for selection, enhancing robustness and flexibility. Furthermore, we introduce an event-based re-localization trigger module, enabling autonomous robotic missions. Focusing on subterranean environments with low features, we leverage range image descriptors derived from 3D LiDAR scans to preserve depth information. Our approach enhances a state-of-the-art data-driven descriptor extraction framework for place recognition and orientation regression by incorporating a junction detection module that utilizes the descriptors for classification purposes. The effectiveness of the proposed approach was evaluated across three distinct real-life subterranean environments. Validerad;2023;Nivå 2;2023-09-22 (joosat);CC BY 4.0 License

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    https://doi.org/10.48550/arxiv...
    Article . 2022
    License: arXiv Non-Exclusive Distribution
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    Expert Systems with Applications
    Article . 2024 . Peer-reviewed
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      https://doi.org/10.48550/arxiv...
      Article . 2022
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      Expert Systems with Applications
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    Authors: Osório Nhiuane; Sá Nogueira Lisboa; Meizal Popat; Almeida Sitoe;

    Food insecurity, deforestation, and forest degradation are significant challenges to achieving the Sustainable Development Goals in sub-Saharan Africa. Slash-and-burn cultivation and conventional logging (timber and charcoal production) are two interrelated activities that lead to forest loss and undermine food security. However, the environmental and economic incentives to clear or conserve the forest have yet to be discovered. To address this gap, our study collected costs and benefits data to assess financial profitability and viability related to forest conversion to slash-and-burn cultivation options (e.g., mono-cropping of maize and intercropping between maize, cassava and pigeon peas) and forestry exploitation (logging and charcoal production) practices in smallholders in Zambézia province, central Mozambique. Conventional logging was the highest cost activity (1662 US$ ha−1) compared to charcoal production (278 US$ ha−1) and cropping systems. Estimated total costs for cropping ranged from 302 US$ ha−1 to 508 US$ ha−1. Cropping systems appear more profitable in the first year of investment (30 to 1495 US$ ha−1) than forestry activities. On the other hand, the estimated profits for logging and charcoal production are negative at 15 US$ ha−1 and 782 US$ ha−1, respectively. Regarding viability, cropping systems showed the highest indicators compared to forestry activities. Based on the financial assessment, cropping systems seem attractive land use options with the fastest and highest financial returns and the lowest production costs. As such, it is not easy to prevent them. The long-term implications of increasing deforestation to the detriment of the cropping system can translate into rapid ecosystem degradation that can worsen livelihoods.

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    Trees, Forests and People
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      Trees, Forests and People
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: David R. Thompson; Robert O. Green; Christine Bradley; Philip G. Brodrick; +52 Authors

    EMIT is supported by the National Aeronautics and Space Administration Earth Venture Instrument program, under the Earth Science Division of the Science Mission Directorate. K. Dana Chadwick is supported by the NASA Applied Sciences Program. Carlos P´ erez García- Pando and María Gonçalves Ageitos acknowledge support from the European Research Council (ERC) Consolidator Grant FRAGMENT (grant agreement No. 773051), and the AXA Chair on Sand and Dust Storms at the Barcelona Supercomputing Center funded by the AXA Research Fund. Martina Klose has received funding through the Helmholtz Association’s Initiative and Networking Fund (grant agreement No. VH-NG-1533). We thank Jeffrey Czapla-Myers and the University of Arizona team for their maintenance and operation of the Railroad Valley automated calibration facility. This research was performed at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. We acknowledge the support and assistance of NASA’s International Space Station Program. The USGS authors’ contribution to this published Work was prepared by U.S. federal government employees as part of their official duties and constitutes a “work of the United States government,” and is considered to be in the public domain and therefore domestic copyright does not apply. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Copyright 2024 California Institute of Technology. All rights reserved. US Government Support Acknowledged. The Earth surface Mineral dust source InvesTigation (EMIT) is a remote visible to shortwave infrared (VSWIR) imaging spectrometer that has been operating onboard the International Space Station since July 2022. This article describes EMIT's on-orbit spectroradiometric calibration and validation. Accurate spectroscopy is vital to achieve consistent mapping results with orbital imaging spectrometers. EMIT takes a unique approach to this challenge, with just six optical elements, no shutter, and no onboard calibration systems. Its simple design focuses on uniformity and stability to enable vicarious spectroradiometric calibration. Our experiments demonstrate that this approach is successful, approaching the fidelity of manual field spectroscopy in some cases, and enabling new and more accurate products across diverse Earth science disciplines. EMIT achieves several notable firsts for an instrument of its class. It demonstrates successful on-orbit adjustments of Focal Plane Array (FPA) alignment with sub-micron precision. It offers spectral uniformity better than 98%. Optical artifacts in the measurement channels are at least three orders of magnitude below the primary solar-reflected surface signals. Its noise performance enables percent-level discrimination in the depths of mineral absorption features. In these aspects, EMIT satisfies the stringent performance needs for the next generation of VSWIR imaging spectrometers to observe the Earth's ecosystems, geology, and water resources. Article signat per 56 autors: David R. Thompson, Robert O. Green, Christine Bradley, Philip G. Brodrick, Natalie Mahowald, Eyal Ben Dor, Matthew Bennett, Michael Bernas, Nimrod Carmon, K. Dana Chadwick, Roger N. Clark, Red Willow Coleman, Evan Cox, Ernesto Diaz, Michael L. Eastwood, Regina Eckert, Bethany L. Ehlmann, Paul Ginoux, María Gonçalves Ageitos, Kathleen Grant, Luis Guanter, Daniela Heller Pearlshtien, Mark Helmlinger, Harrison Herzog, Todd Hoefen, Yue Huang, Abigail Keebler, Olga Kalashnikova, Didier Keymeulen, Raymond Kokaly, Martina Klose, Longlei Li, Sarah R. Lundeen, John Meyer, Elizabeth Middleton, Ron L. Miller, Pantazis Mouroulis, Bogdan Oaida, Vincenzo Obiso, Francisco Ochoa, Winston Olson-Duvall, Gregory S. Okin, Thomas H. Painter, Carlos Pérez García-Pando, Randy Pollock, Vincent Realmuto, Lucas Shaw, Peter Sullivan, Gregg Swayze, Erik Thingvold, Andrew K. Thorpe, Suresh Vannan, Catalina Villarreal, Charlene Ung, Daniel W. Wilson, Sander Zandbergen. Objectius de Desenvolupament Sostenible::13 - Acció per al Clima Peer Reviewed

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    Authors: D.M.R. Sampath; J.G. Freitas; J.A. Dias;

    The Drivers-Pressures-State-Impact-Response (DPSIR) framework was employed to understand the land use policies developed to manage coastal sand dunes and their consequences in Oregon, United States of America, during two contrasting periods: from the 19th to the late 20th century and from there to the early 21st century. A combination of historical data and scientific literature was used for this study. Dune destabilization became a socio-economic issue as Euro-Americans settled in Oregon in the 19th century. Ammophila arenaria and Ammophila breviligulata were widely used for stabilization. This led to a paradigm shift regarding dunes, at a time when their management was becoming more complex due to socio-natural factors. As non-native beachgrasses turned invasive causing the loss of biodiversity and habitats, their removal became the focus to restore the active dunes to support the natural processes of the ecosystem. However, the removal of these beachgrasses, particularly, Ammophila arenaria, results in low dune heights, increasing the risk of coastal flooding by reducing their effectiveness as a natural defense against sea-level rise and extreme storm surges. The reason for the contrasting dune management policies in Oregon since the 1930 s is that the management response to environmental impacts due to human drivers creates new drivers, pressures, and corresponding impacts, as shown in the DPSIR analysis. Thus, land use policies for managing coastal dunes in Oregon and other places must balance efforts to restore the native biodiversity while minimizing coastal flooding in a context of accelerating and continuous sea-level rise in the 21st century.

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    Land Use Policy; ZENODO
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      Land Use Policy; ZENODO
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    Authors: Franziska Gaede (b. Wolpert); Cristina Quintas-Soriano; Bill Davison; Tobias Plieninger;

    In a time of multiple global challenges, trees gain more and more attention as an important component of sustainable land use systems, as they can produce food and provide multiple other ecosystem services at the same time. In Germany, traditional orchard meadows (so-called “Streuobstwiesen”) are in decline, although they are well known for their ecological value. In modern agroforestry systems staple perennial food crops seem to be rarely integrated. Here, we propose to use emerging chestnut cultivation for revitalizing traditional orchard meadows, diversifying forests, and integrating perennial staple food crops in modern agroforestry systems. In this study, we interviewed 64 chestnut growers in Germany and aimed to (1) explore characteristics of chestnut stands and management; (2) evaluate the main motivations, aims, and challenges of chestnut growers; (3) identify perceived outcomes of chestnut cultivation and measures for upscaling; and (4) analyze differences between groups of chestnut growers. Our results show that most growers aimed to increase tree numbers and foster the spread of chestnut trees as cultural assets. Sustainable food production was the motivation most often named by the respondents. A guide for cultivation, as well as better funding, were mentioned as the most wanted and easy to implement measures for up-scaling production and consumption. Junior chestnut growers were better connected to other chestnut growers and were more motivated by sustainable food production than senior growers. Pest and diseases as well as legal and funding situations were aspects hampering chestnut cultivation. We suggest that chestnut trees can serve as a valuable element of a diverse tree crop landscape providing staple food crops while supporting ecosystem services.

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    Trees, Forests and People
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  • Authors: Hodel, Leonie; Wegner, Jan Dirk; Sainte Fare Garnot, Vivien; Rocha-Gomes, Francisco; +2 Authors

    Dataset for the regrssion analysis for the manuscript "Deep learning-based cattle counts on satellite imagery offer evidence regarding land use and policy impact in the Brazilian Amazon.".

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      ZENODO
      Dataset . 2024
      Data sources: Datacite
      ZENODO
      Dataset . 2024
      Data sources: ZENODO
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    Authors: Pirotti, Francesco; Kutchartt, Erico; José Ramón Gonzalez Olabarria;

    WORKING VERSION. All layers will be visible in this linked webgis app along with estimated error. <== To Be Updated in new final version, not yet so. The layers available in this dataset are in a WGS84 geographic coordinate reference system (EPSG:4326) where latitude and longitude coordinates at 0.0008983 degrees ground sampling distance per cell, which corresponds to about 1 ha, i.e. ~100 m x ~100 m at the equator, but decreases in area with increasing latitude as the coordinate system is not equal-area, e.g. ~70 m west-est direction at 45° latitude and ~50 m west-est direction at 60° latitude. A_Aspect.tif, A_slope.tif and A__elevation.tif - Earth surface height above sea level and morphology. Prefix was added to group them in Zenodo. biomass.tif - Biomass values at year 2020, Mg/ha. canopyBulkDensity.tif - Amount of canopy biomass per volume of canopy (kg/m3) canopyBaseHeight.tif - Height of canopy start measured from the ground (m) canopyCover.tif - percent of canopy coverage - resampled and updated from the map of Hansen et al. 2005 canopyHeight.tif - Total height of canopy from the ground (m) - resampled from the map of Lang, N., et al. (2023) Fuel Model FuelModelClasses_ScottBurgan.tif - the category of Fuel Model according to Scott&Burgan 2005 FuelModelClasses_Aragonese.tif - the category of Fuel Model according to Aragonese et al. 2023 DOI: 10.5194/essd-15-1287-2023 - values are from 1 to 24, with a Look Up Table for correspondence (values are ordered matching the order in table 1 of the article) . FuelModelClasses_ScottBurgan.clr/qml CLR/QML - style file for QGIS FuelModelClasses_Aragonese.clr/qml CLR/QML - style file for QGIS FuelModelPercent.tif - the percent of fuel model category belonging to that pixel, values range between 50 and 100. Allows to spot pixels with expected mixed fuel categories.

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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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    Authors: nicolas, olatz; Larrinaga, Felix;

    This dataset contains the information used in the drOp project (Digitally enabled social district renovation processes for age-friendly environments driving social innovation and local economic development. Num.101080025) to build a multidimensional characterization of Ermua and the Santa Ana neighbourhood through relevant indicators, and its visualisation in a Geographic Information System (GIS) by analysing statistical data, as well as other urban and social data available

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    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2024
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Dataset . 2024
      License: CC BY
      Data sources: Datacite
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