Bringing agro-biomass to reality: Keys for new sustainable value chains based on agricultural pruning and plantation removal biomass

The utilization of agro-residues as a source of biomass is an opportunity for supporting the expansion of the bioeconomy in Europe. Among the multiple agro-residues, those produced from vineyards, olive groves and fruit plantation represent a relevant potential for many EU countries. Specifically, the woody biomass residues from Agricultural Pruning and Plantation Removal (APPR in short) is a paradigm of agro-residues being produced year after year, and in most of the cases, not utilized as a resource for added value activities like the production of energy, biochemical or other biocommodities. In this paper, the uP_running project provides a vision to understand the current status of APPR biomass utilization in Europe and gives some recommendations for establishing new value chains based on this fuel. In addition, the document describes how to make the APPR biomass value chains a reality: how the different stages of the value chain and logistics can be carried out, which are the main keys to make the value chain operative, how to ensure that the final user finds an added value in the APPR biomass they receive, and how to preserve the quality and market value

Outpatient treatment of pulmonary embolism

Over the past decade there has been an increasing trend to manage many conditions traditionally treated during a hospital admission as outpatients. Evidence is increasing to support this approach in patients with pulmonary embolism (PE). In this article, we review the current status of outpatient management of confirmed PE and present a pragmatic approach for clinical healthcare settings. © 2020, European Respiratory Society. All rights reserved

FIUSIS, a Biomass Power Plant Fuelled Exclusively by Olive Tree Prunings. A Case Study in the AGROinLOG H2020 Project

AGROinLOG Project aimed at demonstrating the technical, environmental and economic feasibility of Integrated Biomass Logistic Centres (IBLC) for the development of new value chains based on agricultural waste and by-products. Within the Project the Research Centre for Engineering and Agro-Food processing of CREA was in charge to support the birth of a IBLC finalized to the energy valorization of olive tree prunings in the Greek Region of Fthiotida (Central Greece), with particular regard to the mechanical harvesting of pruning. Fiusis plant has been identified as a reference model to follow in the organization of the production chain to set up in Greece. Fiusis is the first biomass power plant in the world to use exclusively olive tree prunings as a fuel source

FIUSIS, a Biomass Power Plant Fuelled Exclusively by Olive Tree Prunings. A Case Study in the AGROinLOG H2020 Project

In the framework of the AGROinLOG H2020 Project, the Research Centre for Engineering and Agro-Food processing of CREA was in charge of supporting the birth of a new olive tree prunings-based energy chain in the Greek Region of Fthiotida (Central Greece), with particular regard to the pruning harvesting phase. Despite the huge areas of olive grow plantations, such bioenergy chains have never taken off anywhere in the Country. On the contrary in Italy the are several practical examples of pruning utilization for energy purposes. Among these, the 1 MWe plant active in Calimera (Lecce), named Fiusis, is the first biomass power plant in the world to use exclusively olive tree prunings as a fuel source. Fiusis has been identified as a reference model to be followed in the organization of the production chain to set up in Greece. This paper reports the key elements that allowed Fiusis to achieve the success highlighting its environmental, economic and social integration with the local territory. The main technical elements of the biomass plant, the supply chain management and the operational parameters of the harvesting machineries are described. Moreover, the first achievements obtained in Greece in transferring the “Fiusis model” are reported

Common Corruptions for Enhancing and Evaluating Robustness in Air-to-Air Visual Object Detection

The main barrier to achieving fully autonomous flights lies in autonomous aircraft navigation. Managing non-cooperative traffic presents the most important challenge in this problem. The most efficient strategy for handling non-cooperative traffic is based on monocular video processing through deep learning models. This letter contributes to the vision-based deep learning aircraft detection and tracking literature by investigating the impact of data corruption arising from environmental and hardware conditions on the effectiveness of these methods. More specifically, we designed 7 types of common corruptions for camera inputs taking into account real-world flight conditions. By applying these corruptions to the Airborne Object Tracking (AOT) dataset we constructed the first robustness benchmark dataset named AOT-C for air-to-air aerial object detection. The corruptions included in this dataset cover a wide range of challenging conditions such as adverse weather and sensor noise. The second main contribution of this letter is to present an extensive experimental evaluation involving 8 diverse object detectors to explore the degradation in the performance under escalating levels of corruptions (domain shifts). Based on the evaluation results, the key observations that emerge are the following: 1) One-stage detectors of the YOLO family demonstrate better robustness, 2) Transformer-based and multi-stage detectors like Faster R-CNN are extremely vulnerable to corruptions, 3) Robustness against corruptions is related to the generalization ability of models. The third main contribution is to present that finetuning on our augmented synthetic data results in improvements in the generalisation ability of the object detector in real-world flight experiments

ERCC6L2 rs591486 polymorphism and risk for amyotrophic lateral sclerosis in Greek population

Background: Α number of genetic variants have been associated with amyotrophic lateral sclerosis (ALS). A recent study supports that rs591486 across the ERCC6L2 gene and exposure to pesticides seem to have a joint effect on the development of Parkinson’s disease, a disease which shares a few common characteristics with ALS. Objective: To detect a possible contribution of rs591486 ERCC6L2 to ALS. Methods: A total of 155 patients with ALS and 155 healthy controls were included in the study and genotyped for rs591486. Using logistic regression analyses (crude and adjusted for age and sex), rs591486 was tested for association with ALS risk. Subgroup analysis based on ALS site of onset was also performed. Cox regression analysis was applied in order for the effect of ERCC6L2 rs591486 on ALS age of onset to be tested. Results: Adjusted analysis showed that ERCC6L2 rs591486 was associated with an increased risk of ALS development, in dominant [odds ratio, OR (95% confidence interval, CI) 2.15 (1.04–4.46), p = 0.037] and over-dominant [OR (95%CI) = 1.91 (1.01–3.60), p = 0.043], modes. Subgroup analysis based on ALS site of onset revealed an association between ERCC6L2 rs591486 and ALS with limb onset. Results for Cox regression analysis indicated that G/A carriers had a lower age of ALS limb onset when compared to G/G carriers. Conclusions: The current study provides preliminary indication for an implication of ERCC6L2 rs591486 in ALS development, as a possible genetic risk factor. These results possibly suggest that oxidative stress may be the main contributor in the pathophysiology of ALS. © 2019, Fondazione Società Italiana di Neurologia