Learning Grasps in a Synergy-based Framework

In this work, a supervised learning strategy has been applied in conjunction with a control strategy to provide anthropomorphic hand-arm systems with autonomous grasping capabilities. Both learning and control algorithms have been developed in a synergy-basedframework in order to address issues related to high dimension of the configuration space, that typically characterizes robotic hands and arms with humanlike kinematics. An experimental setup has been built to learn hand-arm motion from humans during reaching and grasping tasks. Then, a Neural Network (NN) has been realized to generalize the grasps learned by imitation. Since the NN approximates the relationship between the object characteristics and the grasp configuration of the hand-arm system, a synergy-based control strategy has been applied to overcome planning errors. The reach-to-grasp strategy has been tested on a setup constituted by the KUKA LWR 4+Arm and the SCHUNK 5-Finger Hand

Synergy-based policy improvement with path integrals for anthropomorphic hands

In this work, a synergy-based reinforcement learning algorithm has been developed to confer autonomous grasping capabilities to anthropomorphic hands. In the presence of high degrees of freedom, classical machine learning techniques require a number of iterations that increases with the size of the problem, thus convergence of the solution is not ensured. The use of postural synergies determines dimensionality reduction of the search space and allows recent learning techniques, such as Policy Improvement with Path Integrals, to become easily applicable. A key point is the adoption of a suitable reward function representing the goal of the task and ensuring onestep performance evaluation. Force-closure quality of the grasp in the synergies subspace has been chosen as a cost function for performance evaluation. The experiments conducted on the SCHUNK 5-Finger Hand demonstrate the effectiveness of the algorithm showing skills comparable to human capabilities in learning new grasps and in performing a wide variety from power to high precision grasps of very small objects

Old and new oral anticoagulants : food, herbal medicines and drug interactions

The most commonly prescribed oral anticoagulants worldwide are the vitamin K antagonists (VKAs) such as warfarin. Factors affecting the pharmacokinetics of VKAs are important because deviations from their narrow therapeutic window can result in bleedings due to over-anticoagulation or thrombosis because of under-anticoagulation. In addition to pharmacodynamic interactions (e.g., augmented bleeding risk for concomitant use of NSAIDs), interactions with drugs, foods, herbs, and over-the-counter medications may affect the risk/benefit ratio of VKAs. Direct oral anticoagulants (DOACs) including Factor Xa inhibitors (rivaroxaban, apixaban and edoxaban) and thrombin inhibitor (dabigatran) are poised to replace warfarin. Phase-3 studies and real-world evaluations have established that the safety profile of DOACs is superior to those of VKAs. However, some pharmacokinetic and pharmacodynamic interactions are expected. Herein we present a critical review of VKAs and DOACs with focus on their potential for interactions with drugs, foods, herbs and over-the-counter medications

EQUIVALENZA TERAPEUTICA DEL TIMOLOLO 0.1%-GEL VERSUS TIMOLOLO 0.5% SOLUZIONE NEL RIDURRE LA IOP NEL GLAUCOMA

Lo studio di 12 settimane ha confermato che il timololo 0.10-gel somministrato una volta al giorno è terapeuticamente equivalente al timololo 0.50% applicato due volte al giorno nel ridurre la IOP in pazienti affetti da GAA. Il minore assorbimento plasmatico con il timololo 0.10%-gel rende possibile una minore incidenza di effetti collaterali sistemici