TOWARDS REDUCING THE IMPACT OF SOIL MANAGEMENT AND TILLAGE PRACTICES ON THE GLOBAL CLIMATE CHANGE

L'adozione di (agro)ecosistemi sostenibili viene indicata come una efficace strategia in grado sequestrare carbonio (C) nel suolo, mitigando così il cambiamento climatico e migliorando la fertilità. Sebbene il potenziale di sequestro del C della non-lavorazione (NT) sia stato generalmente sovrastimato, esso risulta essere di 0,26 Mg ha-1 anno-1 superiore rispetto al regime arativo. Inoltre, il 76,6% di questo quota è localizzato in frazioni considerabili come relativamente stabili. Il NT aumenta lo sviluppo radicale delle colture erbacee (es. mais, soia, frumento) negli stati superficiali del suolo (0-5 cm). Le correlazioni tra i parametri di densità radicale e le proprietà fisiche del suolo mostrano come lo sviluppo radicale sia un fondamentale indicatore di qualità del suolo in NT. I residui delle cover crops influenzano le emissioni di protossido d’azoto (N2O) in NT: i residui di segale favoriscono l'immobilizzazione dell’azoto (N), aumentandone così l'efficienza d’utilizzo e diminuendo le emissioni, mentre i residui di veccia vellutata aumentano l’N2O come conseguenza della mineralizzazione dell’N. Le emissioni di N2O e la produttività dei prati stabili possono essere positivamente correlate, perché meccanismi diversi rispetto alla regolazione indotta dalla disponibilità di N possono controllare l'N2O: il C potrebbe essere un principale fattore di regolazione per nitrificazione e denitrificazione.Adoption of sustainable (agro)ecosystems has been widely suggested to increase soil organic carbon (C) sequestration, to mitigate climate change and enhance soil fertility. Although its carbon sequestration potential has been generally overestimated, no-till (NT) results in an extra C sequestration of 0.26 ± 0.18 Mg ha-1 yr-1 as compared to conventional tillage and 76.6% of this extra C is located in C pools which could be considered relatively stable. NT increases root development of field crops (i.e. maize, soybean, winter wheat) in the top soil (0-5 cm), while does not in the deeper soil (5-60 cm). Positive correlations between root density and soil physical parameters shows how roots are main drivers of soil physical properties under NT. Cover crop residues may affect nitrous oxide (N2O) emissions under NT: rye residues enhances soil-nitrogen (N) immobilization, thus increasing N use efficiency and decreasing N2O, while hairy vetch residues as cover crop under NT increases N2O as a consequence of soil-N mineralization. N2O emissions and shoot productivity may be positive correlated in grasslands, because other mechanisms than plant-induced regulation of soil N pool may control N2O: C could be a major factor regulating nitrification and denitrification processes

Myoelectric Control Architectures to Drive Upper Limb Exoskeletons

Myoelectric interfaces are sensing devices based on electromyography (EMG) able to read the electrical activity of motoneurons and muscles. These interfaces can be used to infer movement volition and to control assistive devices. Currently, these interfaces are widely used to control robotic prostheses for amputees, but their use could be beneficial even for people suffering from motor disabilities where the peripheral nervous system is intact and the impairment is only due to the muscles, e.g. muscular dystrophy, myopathies, or ageing. In combination with recent robotic orthoses and exoskeletons, myoelectric interfaces could dramatically improve these patients’ quality of life. Unfortunately, despite a wide plethora of methodologies has been proposed so far, a natural, intuitive, and reliable interface able to follow impaired subjects’ volition is still missing. The first contribution of this work is to provide a review of existing approaches. In this work we found that existing EMG-based control interfaces can be viewed as specific cases of a generic myoelectric control architecture composed by three distinct functional modules: a decoder to extract the movement intention from EMG signals, a controller to accomplish the desired motion through an actual command given to the actuators, and an adapter to connect them. The latter is responsible for translating the signal from decoder’s output to controller’s input domain and for modulating the level of provided assistance. We used this concept to analyse the case of study of linear regression decoders and an elbow exoskeleton. This thesis has the scientific objective to determine how these modules affect performance of EMG-driven exoskeletons and wearer’s fatigue. To experimentally test and compare myoelectric interfaces this work proposes: (1) a procedure to automatically tune the decoder module in order to equally compare or to normalize the decoder output among different sessions and subjects; (2) a procedure to automatically tune gravity compensation even for subjects suffering from severe disabilities, allowing them to perform the experimental tests; (3) a methodology to guide the impaired patients through the experimental session; (4) an evaluation procedure and metrics allowing statistically significant and unbiased comparison of different myoelectric interfaces. A further contribution of this work is the design of an experimental test bed composed by an elbow exoskeleton and by a software framework able to collect EMG signals and make them available to the exoskeleton’s actuators with minimal latency. Using this test bed, we were able to test different myoelectric interfaces based on our architecture, with different modules choices and tunings. We used linear regression decoders calibrated to predict the muscular torque, low-level controllers having torque or velocity as reference, and adapters consisting of a properly dimensioned gain or simple dynamic systems, such as an integrator or a mass-damping system. The results we obtained allow to conclude that EMG-based control is a viable technology to assist muscular weakness patients. Moreover, all the components of the myoelectric control architecture – decoder, adapter, controller, and their tuning – significantly affect the task-based performance measures we collect. Further investigations should be devoted to a methodology to automatically tune all the components, not the decoders only, and to the quantitative study of the effect the adapter has on the regulation of the assistance level and of the tradeoff between speed and accuracy

Recycling of Wastes Deriving from the Production of Epoxy-Carbon Fiber Composites in the Production of Polymer Composites

The formulation of composites reinforced with shredded epoxy-carbon fibers wastes is investigated. Poly (buthylene terephthalate) PBT was selected as the matrix for the composites. In order to increase the interaction between the epoxy resin still coating the carbon fibers and the PBT matrix, polycarbonate (PC) was added either to the matrix formulation or as a waste coating. The flexural strength, impact strength, and dynamic-mechanical analysis of the new composites was investigated, as well as their microstructure by scanning electron microscopy. Experimental results show that the recycled fibers can be dispersed in both pure PBT and in its blend, enhancing the mechanical properties of the composites. An increase in the investigated properties is found specifically in the elastic modulus below 50 degrees C and in the impact strength. The extent of the increase depends on the obtained microstructure

automatic process modeling with time delay neural network based on low level data

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A modified energy‐based fatigue parameter for short fiber reinforced polymers: Performance analysis with varying thicknesses, load ratios, and fiber orientations

The durability of Short Fibre Reinforced Polymers (SFRPs) is affected by several variables. Accurate unifying fatigue parameters are thus essential for an efficient characterization campaign. This research investigated the fatigue behaviour of a Polyphtalamide PA6T/6I reinforced with 50% of glass fibres. Two thicknesses (1.6 mm and 3 mm), two orientations from the injection moulding direction (0° and 90°) and three load rations (-0.5, 0.1, 0.5) were investigated. A new fatigue parameter, called Alternating Energy Density (AED), was presented; its ability to correlate the fatigue tests results was compared to other known fatigue parameters – cyclic mean strain rate and cyclic creep energy density. All the fatigue parameters were found to be independent of specimen thickness. Furthermore, the prediction of the fatigue lifetime based on AED showed greater accuracy with respect to the other known investigated methods. AED could thus be used for accurate and efficient lifetime prediction of SFRPs

Effects of short‐loop material recycling on mechanical properties of parts by Arburg Plastic Freeforming

Arburg Plastic Freeforming allows for transforming granulated thermoplastics with variable shapes and sizes. This opens marvellous opportunities for in-place recycling of process waste and auxiliary structures. The present study investigates for the first time the effects of recycled material on the mechanical properties of manufactured parts. To this end, the mechanical, thermomechanical and rheological properties of parts produced with different contents of recycled material are investigated. Findings demonstrate that a balanced mixture of primary and secondary material determines a drop in mechanical performances due to a less accurate deposition. A higher percentage of recycled material determines a sharp decrease in viscosity, leading to a more homogeneous layer and tensile properties similar to those of the virgin polymer. The drop in viscosity also affects the accuracy of deposition, determining a worse definition of sharp edges

Dynamic Movement Primitives: Volumetric Obstacle Avoidance Using Dynamic Potential Functions

Obstacle avoidance for DMPs is still a challenging problem. In our previous work, we proposed a framework for obstacle avoidance based on superquadric potential functions to represent volumes. In this work, we extend our previous work to include the velocity of the trajectory in the definition of the potential. Our formulations guarantee smoother behavior with respect to state-of-the-art point-like methods. Moreover, our new formulation allows to obtain a smoother behavior in proximity of the obstacle than when using a static (i.e. velocity independent) potential. We validate our framework for obstacle avoidance in a simulated multi-robot scenario and with different real robots: a pick-and-place task for an industrial manipulator and a surgical robot to show scalability; and navigation with a mobile robot in dynamic environment.Comment: Preprint for Journal of Intelligent and Robotic System

Temporal prediction of multiple sclerosis evolution from patient-centered outcomes

Multiple Sclerosis is a degenerative condition of the central nervous system that affects nearly 2.5 million of individuals in terms of their physical, cognitive, psychological and social capabilities. Despite the high variability of its clinical presentation, relapsing and progressive multiple sclerosis are considered the two main disease types, with the former possibly evolving into the latter. Recently, the attention of the medical community toward the use of patient-centered outcomes in multiple sclerosis has significantly increased. Such patient-friendly measures are devoted to the assessment of the impact of the disease on several domains of the patient life. In this work, we investigate on use of patient-centered outcomes to predict the evolution of the disease and to assess its impact on patients\u201a\uc4\uf4 lives. To this aim, we build a novel temporal model based on gradient boosting classification and multiple-output elastic-net regression. The model provides clinically interpretable results along with accurate predictions of the disease course evolution

Autonomous task planning and situation awareness in robotic surgery

The use of robots in minimally invasive surgery has improved the quality of standard surgical procedures. So far, only the automation of simple surgical actions has been investigated by researchers, while the execution of structured tasks requiring reasoning on the environment and the choice among multiple actions is still managed by human surgeons. In this paper, we propose a framework to implement surgical task automation. The framework consists of a task-level reasoning module based on answer set programming, a low-level motion planning module based on dynamic movement primitives, and a situation awareness module. The logic-based reasoning module generates explainable plans and is able to recover from failure conditions, which are identified and explained by the situation awareness module interfacing to a human supervisor, for enhanced safety. Dynamic Movement Primitives allow to replicate the dexterity of surgeons and to adapt to obstacles and changes in the environment. The framework is validated on different versions of the standard surgical training peg-and-ring task.Comment: Submitted to IROS 2020 conferenc