120 research outputs found
Assessing natural capital value in the network of Italian marine protected areas: a comparative approach
Marine and coastal natural capital stocks provide a bundle of ecosystem services vital for human well-being. The biophysical and economic assessment of the value of natural capital stocks is much needed for achieving nature conservation goals, while ensuring the sustainable exploitation of marine resources. Marine Protected Areas (MPAs) are increasingly being established worldwide to protect and conserve natural capital stocks from anthropogenic threats. In this study, a biophysical and trophodynamic model based on the emergy accounting method was used to assess the value of natural capital for a set of Italian MPAs. In particular, the assessment focused on four main macro-habitats: 1) sciaphilic hard bottom (SHB), 2) photophilic hard bottom (PHB), 3) soft bottom (SB), and 4) Posidonia oceanica seagrass beds (PSB). The emergy method allowed the assessment of natural capital stocks in terms of direct and indirect solar energy flows invested by nature for their generation. The SHB habitat showed the highest emergy density value in most of the investigated MPAs, confirming the high convergence of input resource flows in the formation of this habitat. When considering extensive indicators, the contribution of the PSB habitat to the total value of natural capital was higher than other habitats in most MPAs. In addition, to facilitate the understanding of the results in socio-economic contexts, the biophysical values of natural capital stocks were converted into monetary units. The total value of natural capital in the investigated MPAs ranged from about 8 to 1163 M€. In conclusion, assessing the value of natural capital can support local managers and policy makers in charge for achieving nature conservation targets while ensuring the sustainable exploitation of natural resources
ILoSA: Interactive Learning of Stiffness and Attractors
Teaching robots how to apply forces according to our preferences is still an
open challenge that has to be tackled from multiple engineering perspectives.
This paper studies how to learn variable impedance policies where both the
Cartesian stiffness and the attractor can be learned from human demonstrations
and corrections with a user-friendly interface. The presented framework, named
ILoSA, uses Gaussian Processes for policy learning, identifying regions of
uncertainty and allowing interactive corrections, stiffness modulation and
active disturbance rejection. The experimental evaluation of the framework is
carried out on a Franka-Emika Panda in three separate cases with unique force
interaction properties: 1) pulling a plug wherein a sudden force discontinuity
occurs upon successful removal of the plug, 2) pushing a box where a sustained
force is required to keep the robot in motion, and 3) wiping a whiteboard in
which the force is applied perpendicular to the direction of movement
The scientific literature on Posidonia oceanica meadows and related ecosystem services
Posidonia oceanica is an endemic seagrass of the Mediterranean Sea. It has recently raised particular interest for its key role in enhancing climate change mitigation. Actually, P. oceanica is one of the most important marine-coastal ecosystems able to sequester and store considerable quantities of carbon, thus being recognized as a “Coastal Blue Carbon System”. However, due to their coastal position, P. oceanica meadows are often subjected to intense human activities that affect their distribution, health and ecological condition, and the capability of generating ecosystem services, including carbon sequestration and storage. Therefore, it is important to identify strategies to protect P. oceanica meadows, also increasing the awareness on the value of the benefits they generate for human well-being. In this context, environmental accounting tools are much needed to assess the biophysical and economic value of the ecosystem services provided by P. oceanicameadows. In this study we explored the scientific literature on P. oceanica, also investigating the relationships between “Posidonia oceanica” and “Ecosystem Services”. The VOSviewer software was used to create maps based on network data of scientific publications using specific keywords to explore the co-occurrence of different terms connected to the considered research topics. Results showed that the most common keywords in scientific publications on P. oceanica were “Biodiversity”, “Environmental monitoring”, and “Conservation”. The analysis on “Posidonia oceanica” and “Ecosystem Services” showed some gaps in terms of standardized approaches for the ecosystem accounting of P. oceanica meadows. Therefore, further efforts are needed to assess the value of ecosystem services generated by P. oceanica through standardized accounting frameworks making visible its contribution to human well-being at different levels of decision-making processes
Interactive Imitation Learning of Bimanual Movement Primitives
Performing bimanual tasks with dual robotic setups can drastically increase
the impact on industrial and daily life applications. However, performing a
bimanual task brings many challenges, like synchronization and coordination of
the single-arm policies. This article proposes the Safe, Interactive Movement
Primitives Learning (SIMPLe) algorithm, to teach and correct single or dual arm
impedance policies directly from human kinesthetic demonstrations. Moreover, it
proposes a novel graph encoding of the policy based on Gaussian Process
Regression (GPR) where the single-arm motion is guaranteed to converge close to
the trajectory and then towards the demonstrated goal. Regulation of the robot
stiffness according to the epistemic uncertainty of the policy allows for
easily reshaping the motion with human feedback and/or adapting to external
perturbations. We tested the SIMPLe algorithm on a real dual-arm setup where
the teacher gave separate single-arm demonstrations and then successfully
synchronized them only using kinesthetic feedback or where the original
bimanual demonstration was locally reshaped to pick a box at a different
height
Treatment of osteolytic solitary painful osseous metastases with radiofrequency ablation or cryoablation: a retrospective study by propensity analysis
The present study aimed to measure the improvement in pain relief and quality of life in patients with osteolytic solitary painful bone metastasis treated by cryoablation (CA) or radiofrequency ablation (RFA). Fifty patients with solitary osteolytic painful bone metastases were retrospectively studied and selected by propensity analysis. Twenty-five patients underwent CA and the remaining twenty-five underwent RFA. Pain relief, in terms of complete response (CR), the number of patients requiring analgesia and the changes in self-rated quality of life (QoL) were measured following the two treatments. Thirty-two percent of patients treated by CA experienced a CR at 12 weeks versus 20% of patients treated by RFA. The rate of CR increased significantly with respect to baseline only in the group treated by CA. In both groups there was a significant change in the partial response with respect to baseline (36% in the CA group vs. 44% in the RFA group). The recurrence rate in the CA and RFA groups was 12% and 8%, respectively. The reduction in narcotic medication requirements with respect to baseline was only significant in the group treated by CA. A significant improvement in self-rated QoL was observed in both groups. The present study seems to suggest that CA only significantly improves the rate of CR and decreases the requirement of narcotic medications. Both CA and RFA led to an improvement in the self-rated QoL of patients after the treatments. However, the results of the present study should be considered as preliminary and to serve as a framework around which future trials may be designed
Treatment of Solitary Painful Osseous Metastases with Radiotherapy, Cryoablation or Combined Therapy: Propensity Matching Analysis in 175 Patients
aim of this study was to identify outcomes in pain relief and quality of life in patients with a solitary painful osseous metastasis treated by radiotherapy, cryoablation or the combination using a propensity score matching study design
A Unifying Variational Framework for Gaussian Process Motion Planning
To control how a robot moves, motion planning algorithms must compute paths
in high-dimensional state spaces while accounting for physical constraints
related to motors and joints, generating smooth and stable motions, avoiding
obstacles, and preventing collisions. A motion planning algorithm must
therefore balance competing demands, and should ideally incorporate uncertainty
to handle noise, model errors, and facilitate deployment in complex
environments. To address these issues, we introduce a framework for robot
motion planning based on variational Gaussian Processes, which unifies and
generalizes various probabilistic-inference-based motion planning algorithms.
Our framework provides a principled and flexible way to incorporate
equality-based, inequality-based, and soft motion-planning constraints during
end-to-end training, is straightforward to implement, and provides both
interval-based and Monte-Carlo-based uncertainty estimates. We conduct
experiments using different environments and robots, comparing against baseline
approaches based on the feasibility of the planned paths, and obstacle
avoidance quality. Results show that our proposed approach yields a good
balance between success rates and path quality
Edwards INSPIRIS RESILIA Valve for Aortic Valve Replacement Achieves Acute Reverse Remodelling of the Left Ventricle and Maintains Excellent Hemodynamic Profile after 1 Year in Young Adults
Objective: Mechanical aortic valve replacement (AVR) is still the recommended valve substitute in young adults, although cultural reasons have popularized bioprostheses also in these patients. Inde..
Oral platelet gel supernatant plus supportive medical treatment versus supportive medical treatment in the management of radiation-induced oral mucositis: a matched explorative active control trial by propensity analysis
OBJECTIVES:: In this active control trial, the rate of radio-induced WHO grade 3/4 oral mucositis and the change in quality of life, assessed by OMWQ-HN, were measured in subjects with head and neck cancer treated by platelet gel supernatant (PGS) and supportive medical treatment versus subjects treated by supportive medical treatment alone. MATERIALS AND METHODS:: Eighty patients with nonmetastatic head and neck cancer underwent curative or adjuvant radiotherapy. All patients underwent supportive medical treatment and/or PGS at the beginning and during radiotherapy. Sixteen patients received PGS in association with supportive medical treatment. To obtain 2 groups virtually randomized for important clinical characteristics subjects were matched, by propensity analysis, with a group of subjects (64 patients) treated with supportive medical treatment alone. RESULTS:: Subjects treated with standard supportive treatment experienced significant higher WHO grade 3/4 toxicity (55%; 35/64) than subjects treated by PGS (13%; 3/16). The reduced toxicity found in PGS group paralleled with the evidence that they developed later symptoms with respect to controls. The Cox proportional hazard model indicated that patients treated with standard supportive medical treatment experienced 2.7-fold increase (hazard ratio=2.7; 95% confidence interval, 1.3-5.7) in the occurrence of WHO grade 3/4 toxicity. PGS group significantly experienced higher quality of life than control groups as measured by OMWQ-HN. A significant decrease in the opioid analgesics usage was found in the PGS group. CONCLUSIONS:: These preliminary data should be interpreted with caution and could serve as a framework around which to design future trials
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