198 research outputs found

    On the Presence and Ubiquity of the Exotic Batophora (J. Agardh) in the Mar Menor Lagoon (SE Spain)

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    We first report the presence of a species of the genus Batophora in the Iberian Peninsula, in the Mar Menor lagoon (Murcia, SE Spain). We detected this macroalga in November 2021. However, according to some observations, it could have been present in the lagoon at least since 2016, being described as a “rare” form of Dasycladus vermicularis. A further survey made during May 2022 confirmed the presence of this species in much of the perimeter of the Mar Menor. Morphologic analyses are not conclusive regarding the species description, but most traits point to Batophora occidentalis or Batophora occidentalis var. largoensis. A consensus sequence from the rbcL barcode gene was compared by the Blastn tool showing its closeness to other Batophora specimens, yet the specific level was unresolved. The recent confirmation of a Batophora species in a littoral lagoon from Formentera (Balearic Islands) with similar morphologic characteristics could indicate that both putative introductions are connected. Further morphologic and genetic analyses are required in order to know the origin and expansion of this genus along the Mediterranean coasts

    Chitosan from Marine Amphipods Inhibits the Wilt Banana Pathogen Fusarium oxysporum f. sp. Cubense Tropical Race 4

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    In this work, we extracted chitosan from marine amphipods associated with aquaculture facilities and tested its use in crop protection. The obtained chitosan was 2.5 ± 0.3% of initial ground amphipod dry weight. The chemical nature of chitosan from amphipod extracts was confirmed via Raman scattering spectroscopy and Fourier transform infrared spectroscopy (FTIR). This chitosan showed an 85.7–84.3% deacetylation degree. Chitosan from biofouling amphipods at 1 mg·mL−1 virtually arrested conidia germination (ca. sixfold reduction from controls) of the banana wilt pathogenic fungus Fusarium oxysporum f. sp cubense Tropical Race 4 (FocTR4). This concentration reduced (ca. twofold) the conidia germination of the biocontrol fungus Pochonia chlamydosporia (Pc123). Chitosan from amphipods at low concentrations (0.01 mg·mL−1) still reduced FocTR4 germination but did not affect Pc123. This is the first time that chitosan is obtained from biofouling amphipods. This new chitosan valorizes aquaculture residues and has potential for biomanaging the diseases of food security crops such as bananas.This project was funded by PID2020-119734RB-I00 (Spanish Ministry of Science and Innovation), EU H2020 MUSA no. 727624, and AIRAM (Biodiversity Foundation, Spanish Ministry for Ecological Transition, and the Demographic Challenge) projects

    Short communication. Phenological growth stages of saffron plant (Crocus sativus L.) according to the BBCH Scale

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    Phenological studies are important for understanding the influence of climate dynamics on vegetative growth, flowering and fruiting on plants and can be used in many scientific subjects, such as Agronomy, Botany and Plant Biology, but also Climatology as a result of the current global interest in climate change monitoring. The purpose of the detailed specific culture descriptions of the principal growth stages in plants is to provide an instrument for standardization of data recording. To date, there was no coding method to describe developmental stages on saffron plant (Crocus sativus L.). Because of the increasing world-wide interest on this crop, a novel growth development code based on the BBCH extended scale is proposed in this paper. Six principal growth stages were set up, starting from sprouting, cataphylls and flowers appearance, plant appearance and development, replacement corms development, plant senescence and corm dormancy. Each principal growth stage is subdivided into secondary growth stages. Descriptive keys with illustrations are included to make effective use of the system

    Using SRAM Based FPGAs for Power-Aware High Performance Wireless Sensor Networks

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    While for years traditional wireless sensor nodes have been based on ultra-low power microcontrollers with sufficient but limited computing power, the complexity and number of tasks of today’s applications are constantly increasing. Increasing the node duty cycle is not feasible in all cases, so in many cases more computing power is required. This extra computing power may be achieved by either more powerful microcontrollers, though more power consumption or, in general, any solution capable of accelerating task execution. At this point, the use of hardware based, and in particular FPGA solutions, might appear as a candidate technology, since though power use is higher compared with lower power devices, execution time is reduced, so energy could be reduced overall. In order to demonstrate this, an innovative WSN node architecture is proposed. This architecture is based on a high performance high capacity state-of-the-art FPGA, which combines the advantages of the intrinsic acceleration provided by the parallelism of hardware devices, the use of partial reconfiguration capabilities, as well as a careful power-aware management system, to show that energy savings for certain higher-end applications can be achieved. Finally, comprehensive tests have been done to validate the platform in terms of performance and power consumption, to proof that better energy efficiency compared to processor based solutions can be achieved, for instance, when encryption is imposed by the application requirements

    Improving uncertainty estimations for mammogram classification using semi-supervised learning

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    The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Computer aided diagnosis for mammogram images have seen positive results through the usage of deep learning architectures. However, limited sample sizes for the target datasets might prevent the usage of a deep learning model under real world scenarios. The usage of unlabeled data to improve the accuracy of the model can be an approach to tackle the lack of target data. Moreover, important model attributes for the medical domain as model uncertainty might be improved through the usage of unlabeled data. Therefore, in this work we explore the impact of using unlabeled data through the implementation of a recent approach known as MixMatch, for mammogram images. We evaluate the improvement on accuracy and uncertainty of the model using popular and simple approaches to estimate uncertainty. For this aim, we propose the usage of the uncertainty balanced accuracy metric

    Martian Atmospheric Aerosols Composition and Distribution Retrievals During the First Martian Year of NOMAD/TGO Solar Occultation Measurements: 2. Extended Results, End of MY 34 and First Half of MY 35

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    This is the second part of Stolzenbach et al. (2023, https://doi.org/10.1029/2022JE007276), named hereafter Paper I, extends the period to the end of MY 34 and the first half of MY 35. This encompasses the end phase of the MY 34 Global Dust Storm (GDS), the MY 34 C-Storm, the Aphelion Cloud Belt (ACB) season of MY 35, and an unusual early dust event of MY 35 from LS_S 30° to LS_S 55°. The end of MY 34 overall aerosol size distribution shows the same parameters for dust and water ice to what was seen during the MY 34 GDS. Interestingly, the layered water ice vertical structure of MY 34 GDS disappears. The MY 34 C-Storm maintains condition like the MY 34 GDS. A high latitude layer of bigger water ice particles, close to 1 μm, is seen from 50 to 60 km. This layered structure is linked to an enhanced meridional transport characteristic of high intensity dust event which put the MY 34 C-Storm as particularly intense compared to non-GDS years C-Storms as previously suggested by Holmes et al. (2021, https://doi.org/10.1016/j.epsl.2021.117109). Surprisingly, MY 35 began with an unusually large dust event (Kass et al., 2020, https://ui.adsabs.harvard.edu/abs/2020AGUFMP039…01K) found in the Northern hemisphere during LS_S 35° to LS_S 50°. During this dust event, the altitude of aerosol first detection is roughly equal to 20 km. This is close to the values encountered during the MY 34 GDS, its decay phase and the C-Storm of the same year. Nonetheless, no vertical layered structure was observed

    Martian Atmospheric Aerosols Composition and Distribution Retrievals During the First Martian Year of NOMAD/TGO Solar Occultation Measurements: 1. Methodology and Application to the MY 34 Global Dust Storm

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    Since the beginning of the Trace Gas Orbiter (TGO) science operations in April 2018, its instrument “Nadir and Occultation for MArs Discovery” (NOMAD) supplies detailed observations of the IR spectrums of the Martian atmosphere. We developed a procedure that allows us to evaluate the composition and distribution\u27s parameters of the atmospheric Martian aerosols. We use a retrieval program (RCP) in conjunction with a radiative forward model (KOPRA) to evaluate the vertical profile of aerosol extinction from NOMAD measurements. We then apply a model/data fitting strategy of the aerosol extinction. In this first article, we describe the method used to evaluate the parameters representing the Martian aerosol composition and size distribution. MY 34 GDS showed a peak intensity from LS_S 190° to 210°. During this period, the aerosol content rises multiple scale height, reaching altitudes up to 100 km. The lowermost altitude of aerosol\u27s detection during NOMAD observation rises up to 30 km. Dust aerosols reff_{eff} were observed to be close to 1 μm and its νeff_{eff} lower than 0.2. Water ice aerosols reff_{eff} were observed to be submicron with a νeff_{eff} lower than 0.2. The vertical aerosol structure can be divided in two parts. The lower layers are represented by higher reff_{eff} than the upper layers. The change between the lower and upper layers is very steep, taking only few kilometers. The decaying phase of the GDS, LS 210°–260°, shows a decrease in altitude of the aerosol content but no meaningful difference in the observed aerosol\u27s size distribution parameters
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