Adult Age Differences in Knowledge of Retrieval Processes

We assessed knowledge of retrieval processes in young (25-35 years) and old adults (70-85 years). Both feeling-of-knowing judgments and retrieval monitoring were examined with a set of questions about recent news events. For answers that participants initially failed to recall, they rated their feeling-of-knowing as well as made predictions regarding the likelihood of recalling the answer with the aid of a specified type of retrieval cue (retrieval monitoring). Accuracy was evaluated in the context of later recall or recognition performance. We found age group differences in the accuracy of retrieval monitoring, free recall, and recall aided by phonological cues. Using a separate inventory, we found no evidence for age group differences in participants\u27 knowledge of general retrieval principles

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

Methane Fluxes Into Atmosphere from Fennoskandian Lakes

The experimental data on methane fluxes into the atmosphere from Fennoscandian lakes is analyzed. The contribution made by the lake network of this northern region to the atmospheric methane budget is estimated as 320 +/- 23 KtCH(4) per year. From 16 to 37% of the annual methane emission from Fennoscandian lakes is carried out by methane produced during the ice cover period. The methane fluxe rate from studied lakes is estimated as 2.6 +/- 0.2 gCH(4)m(-2) yr(-1). Among lakes of the region, small lakes (areaPeer reviewe

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

Particle concentration and flux dynamics in the atmospheric boundary layer as the indicator of formation mechanism

We carried out column model simulations to study particle fluxes and deposition and to evaluate different particle formation mechanisms at a boreal forest site in Finland. We show that kinetic nucleation of sulphuric acid cannot be responsible for new particle formation alone as the simulated vertical profile of particle number concentration does not correspond to observations. Instead organic induced nucleation leads to good agreement confirming the relevance of the aerosol formation mechanism including organic compounds emitted by the biosphere. <br><br> The simulation of aerosol concentration within the atmospheric boundary layer during nucleation event days shows a highly dynamical picture, where particle formation is coupled with chemistry and turbulent transport. We have demonstrated the suitability of our turbulent mixing scheme in reproducing the most important characteristics of particle dynamics within the boundary layer. Deposition and particle flux simulations show that deposition affects noticeably only the smallest particles in the lowest part of the atmospheric boundary layer

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

Annual particle flux observations over a heterogeneous urban area

Long-term eddy covariance particle number flux measurements for the diameter range 6 nm to 5 μm were performed at the SMEAR III station over an urban area in Helsinki, Finland. The heterogeneity of the urban measurement location allowed us to study the effect of different land-use classes in different wind directions on the measured fluxes. The particle number fluxes were highest in the direction of a local road on weekdays, with a daytime median flux of 0.8×10<sup>9</sup> m<sup>−2</sup> s<sup>−1</sup>. The particle fluxes showed a clear dependence on traffic rates and on the mixing conditions of the boundary layer. The measurement footprint was estimated by the use of both numerical and analytical models. Using the crosswind integrated form of the footprint function, we estimated the emission factor for the mixed vehicle fleet, yielding a median particle number emission factor per vehicle of 3.0×10<sup>14</sup> # km<sup>−1</sup>. Particle fluxes from the vegetated area were the lowest with daytime median fluxes below 0.2×10<sup>9</sup> m<sup>−2</sup> s<sup>−1</sup>. During weekends and nights, the particle fluxes were low from all land use sectors being in the order of 0.02–0.1×10<sup>9</sup> m<sup>−2</sup> s<sup>−1</sup>. On an annual scale the highest fluxes were measured in winter, when emissions from stationary combustion sources are also highest. Particle number fluxes were compared with the simultaneously measured CO<sub>2</sub> fluxes and similarity in their sources was distinguishable. For CO<sub>2</sub>, the median emission factor of vehicles was estimated to be 370 g km<sup>−1</sup>

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

3D Map Reconstruction of an Orchard using an Angle-Aware Covering Control Strategy

In the last years, unmanned aerial vehicles are becoming a reality in the context of precision agriculture, mainly for monitoring, patrolling and remote sensing tasks, but also for 3D map reconstruction. In this paper, we present an innovative approach where a fleet of unmanned aerial vehicles is exploited to perform remote sensing tasks over an apple orchard for reconstructing a 3D map of the field, formulating the covering control problem to combine the position of a monitoring target and the viewing angle. Moreover, the objective function of the controller is defined by an importance index, which has been computed from a multi-spectral map of the field, obtained by a preliminary flight, using a semantic interpretation scheme based on a convolutional neural network. This objective function is then updated according to the history of the past coverage states, thus allowing the drones to take situation-adaptive actions. The effectiveness of the proposed covering control strategy has been validated through simulations on a Robot Operating System. Copyright (C) 2022 The Authors