The Emerging Trends of Renewable Energy Communities’ Development in Italy

Increasing concerns over climate change and energy poverty have triggered the transition toward a decentralized energy system through the widespread adoption of renewable energy technologies. Although this transition was led, over past decades, mainly by major investors and large industrial players, citizens and local authorities are increasingly playing an active role in delivering clean energy investments. In particular, the current European Renewable Energy Directive introduced Renewable Energy Communities (RECs), which allow citizens to collectively organize their participation in the energy market, leading to a more distributed renewable energy system and new forms of sustainable, collaborative, and democratic economies. RECs currently under implementation show differences among European countries due to the different national contexts. A literature review exploring the peculiar Italian regulatory framework on RECs and its recent evolution has been carried out to identify available national and regional financial support mechanisms, barriers, and emerging trends in the diffusion of RECs across the country. The paper reviews and describes three main approaches that emerged in the development of RECs in Italy, discussing their strengths, and limitations. In addition, it provides a brief comparison of the regulatory framework in different European countries, highlighting the distinctive features of the Italian experience. Although the development of RECs in Italy involved a combination of both public and private initiatives, the leading role of local authorities as promoters and aggregators of RECs is evident. This role helps preserve the social impact of RECs but might slow down their implementation due to bureaucratic issues often linked to public procedures and procurement processes, as well as the lack of sufficient expertise within local authorities

Surface doping in T6/ PDI-8CN2 Heterostructures investigated by transport and photoemission measurements

In this paper, we discuss the surface doping in sexithiophene (T6) organic field-effect transistors by PDI-8CN2. We show that an accumulation heterojunction is formed at the interface between the organic semiconductors and that the consequent band bending in T6 caused by PDI-8CN2 deposition can be addressed as the cause of the surface doping in T6 transistors. Several evidences of this phenomenon have been furnished both by electrical transport and photoemission measurements, namely the increase in the conductivity, the shift of the threshold voltage and the shift of the T6 HOMO peak towards higher binding energies.Comment: 5 pages, 5 figure

Hydrogen storage integrated in off-grid power systems: a case study

This paper investigates the feasibility and benefits of integrating hydrogen storage systems into off-grid power systems. As a case study, a stand-alone microgrid located on a small island in southeastern Sardinia (Italy) and already equipped with a photovoltaic (PV) system coupled with batteries is chosen. To evaluate the integration benefits of the two storage systems (hydrogen and batteries) and the optimal sizing of the hydrogen storage section, a parametric analysis with a simulation model implemented in the MATLAB environment has been carried out. Results show that the optimal integration between the two storage systems is found by imposing a share of the batteries (18 kWh, 50% of the overall battery capacity) to exclusively supply the load demand (called battery energy buffer). In these conditions, an almost 100% self-sufficiency of the microgrid can be achieved by a hydrogen generator with the lowest size considered (2.4 kW), a hydrogen storage volume of 10 m3 and a fuel cell, mainly able to completely cover the night loads, of 1.5 kW. This sizing leads to a Levelized Cost of Electricity (LCOE) for the hydrogen section of about 10.5 /kWh

The binding of glucosylceramidase to glucosylceramide is promoted by its activator protein

AbstractA protein activator of glucosylceramidase (EC 3.2.1.45) has been previously identified by us in human placenta [(1985) Biochim. Biophys. Acta 836, 157–166]. In the present paper we report that its function in vitro is to stimulate the binding of the enzyme to its substrate, glucosylceramide. After the purification step which frees the enzyme of most of its activator protein (octyl-Sepharose 4B chromatography), the capacity of glucosylceramidase to bind to the glucosylceramide micelles is dramatically decreased. The addition of the activator protein to the purified enzyme restores this binding

Interactive and Iterative Discovery of Entity Network Subgraphs

Graph mining to extract interesting components has been studied in various guises, e.g., communities, dense subgraphs, cliques. However, most existing works are based on notions of frequency and connectivity and do not capture subjective interestingness from a user's viewpoint. Furthermore, existing approaches to mine graphs are not interactive and cannot incorporate user feedbacks in any natural manner. In this paper, we address these gaps by proposing a graph maximum entropy model to discover surprising connected subgraph patterns from entity graphs. This model is embedded in an interactive visualization framework to enable human-in-the-loop, model-guided data exploration. Using case studies on real datasets, we demonstrate how interactions between users and the maximum entropy model lead to faster and explainable conclusions

Interobserver Agreement of Novel Classification of Central Serous Chorioretinopathy

Objective To validate the newly proposed multimodal-imaging-based classification for central serous chorioretinopathy (CSCR). Methods This was a retrospective study performed in a total of 87 eyes of 44 patients with a diagnosis of CSCR. Multimodal images in the form of auto-fluorescence, fundus fluorescein angiography, indocyanine green angiography, and optical coherence tomography (OCT) images, of all the patients, were presented to two masked retina specialists. The masked observers graded each eye into simple or complex; primary, recurrent, resolved; and specific features such as foveal involvement, outer retinal atrophy, and choroidal neovascularization (CNV). Interobserver agreement was assessed using Cohen's kappa. In areas of non-consensus, a detailed discussion was carried out with a third independent grader. Results The mean age of the 44 patients (32 males and 12 females) was 49.2±9.3 years. We found a moderate-strong agreement between the two observers in all subclassifications, that included "simple or complex" (kappa value=0.91, 95% CI 0.82-0.99, p<0.001); "primary/recurrent/resolved" (kappa value=0.88, 95% CI 0.80-0.96, p<0.001) and "foveal involvement" (kappa value=0.89,95%CI 0.8-0.98, p<0.001). However, there was less agreement between the two graders with respect to classification of "outer retinal atrophy" (kappa value=0.72, 95%CI 0.57-0.87, p<0.001) and "presence/absence of CNV" (kappa value=0.75, 95% CI 0.58-0.92, p<0.001). Non-consensus in categorizing "outer retinal atrophy" was seen in eyes with sub-retinal hyper-reflective material (SHRM) and outer nuclear layer (ONL) thinning overlying subretinal fluid, and non-consensus in categorizing "CNV" was seen in eyes with inner choroidal atrophy. Conclusion Our study reports the validity and strong interobserver agreement in several aspects of the multimodal-imaging-based classification. This could support its implementation in clinical practice and pave way for appropriate treatment guidelines

UBEM's archetypes improvement via data-driven occupant-related schedules randomly distributed and their impact assessment

In Urban Building Energy Models (UBEMs), buildings are usually modelled via archetypes describing occupants’ behaviour via fixed schedules. This research (i) creates data-driven schedules for electric use and occupancy from smart meter readings randomly distributed in the model to improve residential archetypes, (ii) assesses the impact of these schedules on UBEMs’ energy results at different temporal resolutions and spatial scales. The novel assessment procedure exploits integrated heat maps based on coefficients of variation of the root means square error (CVRMSE). The outcomes show that differences in energy needs, with randomized schedules, range based on temporal and spatial aggregation. Yearly, for the entire neighbourhood, heating and cooling energy needs, and electric uses are estimated -2%, +1%, and +18% compared to the base case. The outputs show that, when simulations are focused on the entire district, fixed schedules can be enough to describe energy patterns. However, if the simulation is focused on small groups of buildings (e.g., 5 or fewer), randomising the schedules can create variability in the model in terms of electric use and occupancy among buildings characterized by the same archetype. The followed methodology can be exploited also with larger databases and eventually verified with also other types of data

Fast Likelihood-Based Change Point Detection

Change point detection plays a fundamental role in many real-world applications, where the goal is to analyze and monitor the behaviour of a data stream. In this paper, we study change detection in binary streams. To this end, we use a likelihood ratio between two models as a measure for indicating change. The first model is a single bernoulli variable while the second model divides the stored data in two segments, and models each segment with its own bernoulli variable. Finding the optimal split can be done in O(n) time, where n is the number of entries since the last change point. This is too expensive for large n. To combat this we propose an approximation scheme that yields (1 - epsilon) approximation in O(epsilon(-1) log(2) n) time. The speed-up consists of several steps: First we reduce the number of possible candidates by adopting a known result from segmentation problems. We then show that for fixed bernoulli parameters we can find the optimal change point in logarithmic time. Finally, we show how to construct a candidate list of size O(epsilon(-1) log n) formodel parameters. We demonstrate empirically the approximation quality and the running time of our algorithm, showing that we can gain a significant speed-up with a minimal average loss in optimality.Peer reviewe

Doubling the Mechanical Properties of Spider Silk by C60 Supersonic Molecular Beam Epitaxy

Spider silk is one of the most fascinating natural materials, owing to its outstanding mechanical properties. In fact, it is able to combine usually self-excluding properties, like strength and toughness that synthetic fibers fail to replicate. Here, we report a method to further enhance the already excellent mechanical properties of spider's silk, producing nanocomposite fibers where the matrix of spider silk is reinforced with C60 molecules. These are deposited by Supersonic Molecular Beam Epitaxy (SuMBE) and are able to efficiently interact with silk, as evidenced by XPS analysis. As a consequence, upon proper adjustment of the fullerene kinetic energy, the treated fibers show improved strength, Young's modulus and toughness

Is Eriophyes mali Nalepa present in Italy?

In the last few years, blistering symptoms were observed on apple plants in commercial orchards. Blisters are commonly found on apple leaves as well as on small fruits. This symptom is compatible with that described for apple blister mites belonging to the genus Eriophyes (Eriophyidae). To assess the identity of the etiological agent, leaf blisters and buds of symptomatic apple and, as a control, pear plants were examined under the dissection microscope and eriophyoid mites were collected. Specimens were examined using both molecular and morphological approaches. The analysis of sequences confirmed that eriophyoid mites collected from symptomatic apple and pear plants are genetically different. Our analyses highlight a complex scenario inside the genus Eriophyes that is worth to be studied in more detai