Minsight: A Fingertip-Sized Vision-Based Tactile Sensor for Robotic Manipulation

Intelligent interaction with the physical world requires perceptual abilities beyond vision and hearing; vibrant tactile sensing is essential for autonomous robots to dexterously manipulate unfamiliar objects or safely contact humans. Therefore, robotic manipulators need high-resolution touch sensors that are compact, robust, inexpensive, and efficient. The soft vision-based haptic sensor presented herein is a miniaturized and optimized version of the previously published sensor Insight. Minsight has the size and shape of a human fingertip and uses machine learning methods to output high-resolution maps of 3D contact force vectors at 60 Hz. Experiments confirm its excellent sensing performance, with a mean absolute force error of 0.07 N and contact location error of 0.6 mm across its surface area. Minsight's utility is shown in two robotic tasks on a 3-DoF manipulator. First, closed-loop force control enables the robot to track the movements of a human finger based only on tactile data. Second, the informative value of the sensor output is shown by detecting whether a hard lump is embedded within a soft elastomer with an accuracy of 98%. These findings indicate that Minsight can give robots the detailed fingertip touch sensing needed for dexterous manipulation and physical human-robot interaction

Adapting land restoration to a changing climate: Embracing the knowns and unknowns

CIFOR Infobrief 249, Center for International Forestry Research, Bogor, doi:10.17528/cifor/007261Land restoration will happen under climate change and different knowledge systems are needed to navigate uncertainties and plan adaptation. • The emergence of novel ecosystems presents a challenge for land restoration; they harbor unknown unknowns. • This brief presents key research linking land restoration and societal adaptation and an example of a practical framework for transformative adaptation. • It also proposes questions that can guide stakeholders in exploring different change narratives for adaptation and restoration planning

Soil termites in a rainforest, a secondary forest and mixed-culture plantation sites in central Amazonia.

Soil termites have been studied in detail in a rain forest, a secondary forest and two agroforestry plantation sites at the Embrapa Amazonia Ocidental, Manaus-AM (Brasil), using soil (0 cm-5 cm) and litter samples taken at random within the study sites, using a soilsampler of 21 cm diameter. As results is presented a list of termite genus diversity, then compare termite biomass and individuals numbers in litter and in soil at the different sites, and discuss possible factors that determine termite distribution in the field

Event selection for dynamical downscaling: a neural network approach for physically-constrained precipitation events

This study presents a new dynamical downscaling strategy for extreme events. It is based on a combination of statistical downscaling of coarsely resolved global model simulations and dynamical downscaling of specific extreme events constrained by the statistical downscaling part. The method is applied to precipitation extremes over the upper Aare catchment, an area in Switzerland which is characterized by complex terrain. The statistical downscaling part consists of an Artificial Neural Network (ANN) framework trained in a reference period. Thereby, dynamically downscaled precipitation over the target area serve as predictands and large-scale variables, received from the global model simulation, as predictors. Applying the ANN to long term global simulations produces a precipitation series that acts as a surrogate of the dynamically downscaled precipitation for a longer climate period, and therefore are used in the selection of events. These events are then dynamically downscaled with a regional climate model to 2 km. The results show that this strategy is suitable to constraint extreme precipitation events, although some limitations remain, e.g., the method has lower efficiency in identifying extreme events in summer and the sensitivity of extreme events to climate change is underestimated

Magnetodielectric detection of magnetic quadrupole order in Ba(TiO)Cu4_4(PO4_4)4_4 with Cu4_4O12_{12} square cupolas

In vortex-like spin arrangements, multiple spins can combine into emergent multipole moments. Such multipole moments have broken space-inversion and time-reversal symmetries, and can therefore exhibit linear magnetoelectric (ME) activity. Three types of such multipole moments are known: toroidal, monopole, and quadrupole moments. So far, however, the ME-activity of these multipole moments has only been established experimentally for the toroidal moment. Here, we propose a magnetic square cupola cluster, in which four corner-sharing square-coordinated metal-ligand fragments form a noncoplanar buckled structure, as a promising structural unit that carries an ME-active multipole moment. We substantiate this idea by observing clear magnetodielectric signals associated with an antiferroic ME-active magnetic quadrupole order in the real material Ba(TiO)Cu$_4$(PO$_4$)$_4$. The present result serves as a useful guide for exploring and designing new ME-active materials based on vortex-like spin arrangements.Comment: 4 figure

Structure and function of soil fauna communities in Amazonian anthropogenic and natural ecosystems.

The aim of our study was to judge the soil biological conditions in the plantations with regard to the aspired sustainability of agricultural and forestry systems

A quantitative model of the role of soil fauna in decomposition as affected by different forested cropping systems in central Amazonia.

The basic idea this study was the improvement of the traditional fallow system with slash burning for land preparation and differs in this respect from attenpts to develop completely new land-use systems, in the Manaus-AM (Brasil)