Search

• We study whether distributed ledger technology (DLT) can disintermediate banks. • Early modern economies developed effective peer-to-peer lending based on notaries. • We compare cryptolending and notarial loans: actors, uses, rates, risks, guarantees. • Smart contracts cannot substitute trust intrinsically involved in financial relations. • Cryptolending is a complement rather than an alternative to banks. The application of distributed ledger technology (DLT) in the financial sector has fostered the development of new services that are frequently referred to collectively as 'decentralized finance', or DeFi. In the wake of these recent developments many observers and practitioners regard DLT as a major technological disruption to the financial system, possibly leading to the complete disintermediation of banks and to their substitution with a network of bilateral relations between borrowers and lenders recorded in a common ledger. Recent historiography has shown that a potentially analogous system existed in Ancien Régime societies whereby finance was provided not only by specialized intermediaries, but also by an 'informal' credit network where debtors and creditors entered directly into relationship through notaries. In this paper, we carry out a systematic comparison between cryptolending, an extreme form of DeFi at the technological frontier, and the early system of peer-to-peer lending represented by notarized loans in the early modern period. Our aim is to assess the true novelty of current practices and to understand if, and in what sense, the technological innovation represented by DLT can effectively produce a structural change in the functioning of the financial system. [ABSTRACT FROM AUTHOR]

Hydropower has played an important role in Europe in recent decades, offering a unique combination of safe, low-cost, and clean power generation. Today, it is still one of the largest renewable energy sources (RES), accounting for about 35 % of RES electricity generation. However, grid stability is threatened by the increasing amount of undispatchable RES. Flexibility and dynamics such as energy storage and rapid response are urgently needed to achieve EU policy goals. In such a context, hydropower can play a key role, not only as a provider of regulated renewable energy but also due to its ability to balance a renewable energy system in the short term and the medium/long term by pumped storage technology. All these aspects underline the new role of hydropower, which aims to strengthen grid stability and power supply resilience and to enable higher penetration of volatile RES. In this context, the aim of this paper is to demonstrate the role of hydropower at the European level as well as the needs and opportunities of modernization to fully exploit its potential. In particular, this study provides, the assessment of the today flexibility offered by hydropower to the power system at the European level by leveraging a database of information collected through the participants to the working groups of the COST Action Pen@Hydropower which includes stakeholders in the hydropower sector of 34 European countries. The study confirms the key role of hydropower in future energy scenarios with 30 % of the flexibility demand at all time scales met by hydropower. Furthermore, the paper presents a review of the digitalization solutions and innovative technologies that support the growth of a new generation of sustainable hydropower together with the modernization opportunities for existing hydropower plants. The results of this work have practical implications for stakeholders in the hydropower sector and policymakers as it provides evidence at the European scale of the role of hydropower technology in balancing the power system and the need to have supportive frameworks and adequate markets to fully exploit the European hydropower potential to achieve the energy transition goals. [ABSTRACT FROM AUTHOR]

• An approach for identifying and selecting sustainability indicators for assessing technologies at low TRL. • Three distinct screening tools – a framework, a questionnaire for actor priorities, and a list of indicator selection criteria – are developed and employed to select indicators. • From an initial pool of 382 indicators, the study narrows down to a set of 26 representative indicators deemed essential for assessing the considered system at its early stages. • The new approach outlined in the paper is found to be practical to implement and time- and resource-efficient, when no standard set of indicators exists. In Europe, a decrease in the availability of phosphate rock resources has led to the development of emerging technologies for phosphorus recovery, with the purpose of generating products that can be used as fertilisers. An innovative conceptual system dedicated to the phosphorus recovery from dairy wastewater is considered in the paper. New technologies need to be assessed using relevant sustainability indicators. In this study, we developed an approach for identifying and selecting indicators. Based on searches of literature and expert interviews, three different tools were developed: an indicator screening framework, a questionnaire for finding actor priorities, and a list of indicator selection criteria. The new approach was successfully used to narrow down an initial set of 382 indicators identified in the literature to 26 that were considered representative and practicable for the assessment of the considered system. [Display omitted] [ABSTRACT FROM AUTHOR]

Cities and fringes are often characterised by neglected heritages that affect the perceived quality of life in the territories, especially when it comes to industrial sites. Some studies suggest that their regeneration with social innovation fosters a greater feeling of belonging to the place, creates new socio-cultural activities and new jobs, and increases ground rent. Does this create territorial innovation? What are the impacts of S.I. and T.I. generated by regeneration? This paper aims to assess the average social and territorial innovation impacts of industrial heritage regeneration in cities and fringes and to test the hypothesis of a correlation between them. A mixed methods approach has been adopted with semi-structured telephonic interviews, data analysis, and comparison. 100 examples of industrial heritage regeneration in Europe, equally located in cities and fringes, were analysed. This research offers a novel theoretical contribution to the international literature, corroborating that social innovation plays a vital role in the territorial innovation of cities and fringes. The results show that the greater the social innovation, the higher the level of territorial innovation. Furthermore, this study confirms that innovation depends on location, new uses and regeneration model. These results contribute to the body of knowledge and open new research opportunities in theories and practice for territorial innovation and industrial heritage urban regeneration with social innovation. [Display omitted] • Industrial heritage regeneration with social innovation is a driver for territorial innovation. • Three models of industrial heritage regeneration are identified. • Social innovation and territorial innovation are correlated. • The average impact of social and territorial innovation is higher in ecosystemic models. • The average impact of social and territorial innovation is slightly higher in cities than in fringes. [ABSTRACT FROM AUTHOR]

Recently, smart agriculture has become an essential part of modern agriculture approaches from tillage, via plant seeding and grow support to their collection. With modern technologies, farmers can use substances like pesticides, herbicides, or fertilizers at precise dosages or to identify places on a field with specific production rates. The main objective of this study is to introduce a novel and a unique aerial image dataset of various fields acquired by UAV containing crops/weeds in the early phenophases captured in two different resolutions (2 mm and 7 mm per pixel). Secondly, the best super-resolution technique for high-resolution images, substitution with lower resolution is explored. For data acquisition, we employed DJI Matrice 600 equipped with a full-frame Sony Alpha A7R IV285 image sensor. Data were captured at flight heights of 26 and 95 m from 4 different fields in Central Europe. In addition, we proposed a methodology focused on the selection of an appropriate super-resolution method to enhance low-resolution aerial images to obtain better accuracy of crop/weed detection. As a baseline crop/weed detector for super-resolution effect evaluation, YOLOv5 architecture was used. Next, we explored the performance of several super-resolution models (U-Net++, ESRGAN, SwinIR), and fine-tuned the best-performed one. We present the new dataset named SPAGRI-AI: a novel unique dataset of aerial images for super-resolution experiments in smart precision agriculture. The dataset contains 27,638 aerial images (1024 × 1024 px) and additionally, it contains a subset of 2014 labeled images with 45,548 bounding boxes of 12 classes. The main purpose of the SPAGRI-AI is to provide the scientific community with real-world data to test new methods for super-resolution (SR) and crop/weed detection. During the evaluation of selected super-resolution models, the YOLOv5 model trained on high-resolution images resulted in corn mAP@0.5 of 94.48%. The YOLOv5 model trained on low-resolution images resulted in corn mAP@0.5 of only 51.43%. Nevertheless, if the low-resolution images were pre-processed using the SwinIR super-resolution method, corn mAP@0.5 of 62.36% was achieved. To the best of our knowledge, it is one of the largest datasets available to the paper's publication date. Overall, the SPAGRI-AI dataset and the findings from our experiments contribute to the advancement of super-resolution techniques and crop/weed detection methods in the field of smart agriculture. By utilizing real-world data and optimizing image enhancement approaches, we paved the way for further developments in precision farming practices and applying emerging technologies in agriculture. [Display omitted] • Dataset consists of 27,638 aerial images captured at two different flight heights (26 and 95 m). • Dataset contains a subset of 2014 labeled images with 45,548 bounding boxes across 12 distinct classes. • Baseline model trained on higher resolution data (127 PPI) achieved up to 95% of mAP@0.5 for corn detection. • Model employing super-resolution method on lower resolution data (36 PPI) improved detection performance by 11%. [ABSTRACT FROM AUTHOR]