Longitudinal spectra of wind velocity in the atmospheric surface layer perturbed by a small topographic ridge

Turbulence measurements carried out in the near neutral surface layer are presented. The wind velocity components were measured with sonic anemometers at 2 and 10 m height. Three masts are considered, placed about 4 km upwind, on the top and about 6 km downwind of Inexpressible Island, a relief 300 m high and 1 km in cross-section. Spectral features are discussed in detail. Local equilibrium is found in the inertial subrange and in (at least in part of) the intermediate range, characterized by different slopes upwind and downwind (k−1 and k−5/3, respectively) for the components parallel to the terrain

COVID-19: Open-data resources for monitoring, modeling, and forecasting the epidemic

We provide an insight into the open-data resources pertinent to the study of the spread of the Covid-19 pandemic and its control. We identify the variables required to analyze fundamental aspects like seasonal behavior, regional mortality rates, and effectiveness of government measures. Open-data resources, along with data-driven methodologies, provide many opportunities to improve the response of the different administrations to the virus. We describe the present limitations and difficulties encountered in most of the open-data resources. To facilitate the access to the main open-data portals and resources, we identify the most relevant institutions, on a global scale, providing Covid-19 information and/or auxiliary variables (demographics, mobility, etc.). We also describe several open resources to access Covid-19 datasets at a country-wide level (i.e., China, Italy, Spain, France, Germany, US, etc.). To facilitate the rapid response to the study of the seasonal behavior of Covid-19, we enumerate the main open resources in terms of weather and climate variables. We also assess the reusability of some representative open-data sources

Cooperation of unmanned systems for agricultural applications: A theoretical framework

Agriculture 4.0 comprises a set of technologies that combines sensors, information systems, enhanced machinery, and informed management with the objective of optimising production by accounting for variabilities and uncertainties within agricultural systems. Autonomous ground and aerial vehicles can lead to favourable improvements in management by performing in-field tasks in a time-effective way. In particular, greater benefits can be achieved by allowing cooperation and collaborative action among unmanned vehicles, both aerial and ground, to perform in-field operations in precise and time-effective ways. In this work, the preliminary and crucial step of analysing and understanding the technical and methodological challenges concerning the main problems involved is performed. An overview of the agricultural scenarios that can benefit from using collaborative machines and the corresponding cooperative schemes typically adopted in this framework are presented. A collection of kinematic and dynamic models for different categories of autonomous aerial and ground vehicles is provided, which represents a crucial step in understanding the vehicles behaviour when full autonomy is desired. Last, a collection of the state-of-the-art technologies for the autonomous guidance of drones is provided, summarising their peculiar characteristics, and highlighting their advantages and shortcomings with a specific focus on the Agriculture 4.0 framework. A companion paper reports the application of some of these techniques in a complete case study in sloped vineyards, applying the proposed multi-phase collaborative scheme introduced here

Cooperative Agricultural Operations of Aerial and Ground Unmanned Vehicles

Precision agriculture comprises a set of technologies that combines sensors, information systems, enhanced machinery, and informed management to optimize production by accounting for variability and uncertainties within agricultural systems. Autonomous ground and aerial vehicle can lead to favorable improvements in management by performing in-field tasks in a time-effective way. Greater benefits can be achieved by allowing cooperation and collaborative action among Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs). A multi-phase approach is here proposed, where each unmanned vehicle involved has been conceived and will be designed to implement innovative solutions for automated navigation and infield operations within a complex irregular and unstructured scenario as vineyards in sloped terrains

Plant mediated methane efflux from a boreal peatland complex

Purpose Aerenchymous plants are an important control for methane efflux from peatlands to the atmosphere, providing a bypass from the anoxic peat and avoiding oxidation in the oxic peat. We aimed to quantify the drivers of aerenchymous peatland species methane transport and the importance of this process for ecosystem-scale methane efflux. Methods We measured seasonal and interspecies variation in methane transport rate per gram of plant dry mass at a boreal fen and bog, which were upscaled to ecosystem-scale plant methane transport. Results Methane transport rate was better explained by plant species, leaf greenness and area than by environmental variables. Leaves appeared to transport methane even after senescence. Contrary to our expectations, both methane transport rate and the proportion of plant transport were lower in the fen (with greater sedge cover) than in the bog site. At the fen and bog, average methane transport rate was 0.7 and 1.8 mg g(-1) d(-1), and the proportion of seasonally variable plant transport was 7-41% and 6-90%, respectively. Species-specific differences in methane transport rate were observed at the ecosystem-scale: Scheuchzeria palustris, which accounted for 16% of the aerenchymous leaf area in the fen and displayed the greatest methane transport rate, was responsible for 45% of the ecosystem-scale plant transport. Conclusion Our study showed that plant species influence the magnitude of ecosystem-scale methane emissions through their properties of methane transport. The identification and quantification of these properties could be the pivotal next step in predicting plant methane transport in peatlands.Peer reviewe

An algorithm based on OmniView technology to reconstruct sagittal and coronal planes of the fetal brain from volume datasets acquired by three-dimensional ultrasound

To describe a novel algorithm, based on the new display technology 'OmniView', developed to visualize diagnostic sagittal and coronal planes of the fetal brain from volumes obtained by three-dimensional (3D) ultrasonography

Intuitive geometry and visuospatial working memory in children showing symptoms of nonverbal learning disabilities.

Visuospatial working memory (VSWM) and intuitive geometry were examined in two groups aged 11-13, one with children displaying symptoms of nonverbal learning disability (NLD; n = 16), and the other, a control group without learning disabilities (n = 16). The two groups were matched for general verbal abilities, age, gender, and socioeconomic level. The children were presented with simple storage and complex-span tasks involving VSWM and with the intuitive geometry task devised by Dehaene, Izard, Pica, and Spelke (2006 ). Results revealed that the two groups differed in the intuitive geometry task. Differences were particularly evident in Euclidean geometry and in geometrical transformations. Moreover, the performance of NLD children was worse than controls to a larger extent in complex-span than in simple storage tasks, and VSWM differences were able to account for group differences in geometry. Finally, a discriminant function analysis confirmed the crucial role of complex-span tasks involving VSWM in distinguishing between the two groups. Results are discussed with reference to the relationship between VSWM and mathematics difficulties in nonverbal learning disabilities

Canopy uptake dominates nighttime carbonyl sulfide fluxes in a boreal forest

Nighttime vegetative uptake of carbonyl sulfide (COS) can exist due to the incomplete closure of stomata and the light independence of the enzyme carbonic anhydrase, which complicates the use of COS as a tracer for gross primary productivity (GPP). In this study we derived nighttime COS fluxes in a boreal forest (the SMEAR II station in Hyytiälä, Finland; 61°51′ N, 24°17′ E; 181 m a.s.l.) from June to November 2015 using two different methods: eddy-covariance (EC) measurements (FCOS-EC) and the radon-tracer method (FCOS-Rn). The total nighttime COS fluxes averaged over the whole measurement period were −6.8 ± 2.2 and −7.9 ± 3.8 pmol m−2 s−1 for FCOS-Rn and FCOS-EC, respectively, which is 33–38 % of the average daytime fluxes and 21 % of the total daily COS uptake. The correlation of 222Rn (of which the source is the soil) with COS (average R2  =  0.58) was lower than with CO2 (0.70), suggesting that the main sink of COS is not located at the ground. These observations are supported by soil chamber measurements that show that soil contributes to only 34–40 % of the total nighttime COS uptake. We found a decrease in COS uptake with decreasing nighttime stomatal conductance and increasing vapor-pressure deficit and air temperature, driven by stomatal closure in response to a warm and dry period in August. We also discuss the effect that canopy layer mixing can have on the radon-tracer method and the sensitivity of (FCOS-EC) to atmospheric turbulence. Our results suggest that the nighttime uptake of COS is mainly driven by the tree foliage and is significant in a boreal forest, such that it needs to be taken into account when using COS as a tracer for GPP