Percorsi mariani in Abruzzo. Memoria storica e prospettiva di valorizzazione

The rediscovery of authentic places expressed by a post-industrial culture is encouraging - among others factors - the revival of the so-called "cultural" routes and their use through slow travels. Amongst these latter ones, religious journeys (in particular Marian paths) play a central role. Although in the Abruzzi there are no sanctuaries of significant extra-regional interest, it is nevertheless a land strongly marked by traces, architectures and routes connected with the figure of Mary. It is actually demonstrated by the numerous cultural buildings which are dedicated to Her and situated along the streets of transhumance. Any systematic evaluation of their presence would nowadays ensure attention upon territory by those enjoying authentic travels. At the same time, it would re-enhance a tangible and intangible heritage which very often threatens to disappear

economic feasibility of methanol synthesis as a method for co2 reduction and energy storage

Abstract In this paper, a thermo-economic analysis concerning a methanol production plant is performed. In particular, this study was developed with the aim of evaluating the opportunity and viability of obtaining methanol from the chemical reaction between recycled CO2, emitted from a fossil-fuel power station, and hydrogen produced by water electrolysis. This solution can represent an interesting carbon dioxide reduction method and methanol as a product can be considered an energy storage means. As a first step, a thermodynamic analysis is performed in order to determine the mass and energy flows of the plant; then, a feasibility analysis concerning a large size methanol production plant is performed taking into account three different economic scenarios (Germany, Italy, and China). In order to evaluate the economic viability, the total investment cost and payback period are calculated in all the scenarios. Different methanol and electrical energy prices are considered, to take into proper account the influence of these parameters on mid-term future scenarios. Moreover, a sensitivity analysis, considering different oxygen selling prices and PEM electrolyzer capital costs, were performed

Promotion of proliferation and metastasis of hepatocellular carcinoma by LncRNA00673 based on the targeted-regulation of notch signaling pathway

we read with great interest the paper by Dr. Chen et al1, recently published in European Review for Medical and Pharmacological Sciences and titled ‘‘Promotion of proliferation and metastasis of hepatocellular carcinoma by LncRNA00673 based on the targeted-regulation of notch signaling pathway’’. Authors concluded that lncRNA00673 is highly expressed and may be a potential target for the treatment of Hepatocellular Carcinoma (HCC). Moreover, according to authors, it can promote the proliferation and metastasis of HCC by the regulation of Notch signaling pathway. We congratulate the authors for their interesting work

L'itinerarium dantesco: geografie per la conoscenza dell'altrove

Dante’s itinerarium: geographies for knowledge of the elsewhere. – The itinerary traveled by Dante to the three reigns of the afterlife and narrated in the Divine Commedia is emblematic of a type of knowledge journey that places physical and metaphysical realities on the same stage and consid-ers the cultural identity of the narrating self and the geographical characteristics of the elsewhere voyaged by the traveler-narrator. This paper aims to offer, from a geographical perspective, an insight into the meaning of travel, considering not only the material geographic reality, but also the perceptual and symbolic dimension that is given to spatiality by persons and communities that identify with a specific culture

Semi-Supervised Active Learning for Semantic Segmentation in Unknown Environments Using Informative Path Planning

Semantic segmentation enables robots to perceive and reason about their environments beyond geometry. Most of such systems build upon deep learning approaches. As autonomous robots are commonly deployed in initially unknown environments, pre-training on static datasets cannot always capture the variety of domains and limits the robot's perception performance during missions. Recently, self-supervised and fully supervised active learning methods emerged to improve a robot's vision. These approaches rely on large in-domain pre-training datasets or require substantial human labelling effort. We propose a planning method for semi-supervised active learning of semantic segmentation that substantially reduces human labelling requirements compared to fully supervised approaches. We leverage an adaptive map-based planner guided towards the frontiers of unexplored space with high model uncertainty collecting training data for human labelling. A key aspect of our approach is to combine the sparse high-quality human labels with pseudo labels automatically extracted from highly certain environment map areas. Experimental results show that our method reaches segmentation performance close to fully supervised approaches with drastically reduced human labelling effort while outperforming self-supervised approaches.Comment: 8 pages, 9 figure