Search

Neurocysticercosis (NCC) is caused by the larval stage of Taenia solium. This parasitic disease is endemic in many areas of the world and is emerging in Europe. NCC can affect different brain regions, but simultaneous involvement of the parenchymal, subarachnoid, and ventricular regions is rare. We report the case of a 39-year-old woman from Honduras, resident in Rome for 10 years, who presented to the Emergency Department complaining of headaches, transient hemianopsia, and bilateral papilledema. MRI showed a concomitant parenchymal, subarachnoid, and ventricular involvement in the brain. T. solium IgG antibodies were detected in the blood. The etiological diagnosis of NCC was obtained by identifying T. solium in cerebrospinal fluid using Next Generation Sequencing. Endoscopic neurosurgery with the placement of a ventricular shunt and medical long-term anti-parasitic treatment with a cumulative number of 463 days of albendazole and 80 days of praziquantel were performed. A successful 4-year follow-up is reported. NCC is one of the most common parasitic infections of the human CNS, but it is still a neglected tropical disease and is considered to be an emerging disease in Europe. Its diagnosis and clinical management remain a challenge, especially for European clinicians.

Background: Tourette syndrome is a neurodevelopmental movement disorder involving basal ganglia dysfunction. PDE10A inhibitors modulate signaling in the striatal basal ganglia nuclei and are thus of interest as potential therapeutics in treating Tourette syndrome and other movement disorders. Methods: The preclinical pharmacology and toxicology, human safety and tolerability, and human PET striatal enzyme occupancy data for the PDE10A inhibitor EM-221 are presented. Results: EM-221 inhibited PDE10A with an in vitro IC50 of 9 pM and was >100,000 selective vs. other PDEs and other CNS receptors and enzymes. In rats, at doses of 0.05–0.50 mg/kg, EM-221 reduced hyperlocomotion and the disruption of prepulse inhibition induced by MK-801, attenuated conditioned avoidance, and facilitated novel object recognition, consistent with PDE10A’s inhibition. EM-221 displayed no genotoxicity and was well tolerated up to 300 mg/kg in rats and 100 mg/kg in dogs. In single- and multiple-day ascending dose studies in healthy human volunteers, EM-221 was well tolerated up to 10 mg, with a maximum tolerated dose of 15 mg. PET imaging indicated that a PDE10A enzyme occupancy of up to 92.8% was achieved with a ~24 h half-life. Conclusions: The preclinical and clinical data presented here support the study of EM-221 in phase 2 trials of Tourette syndrome and other movement disorders.

The behind-the-meter technologies integrating “all-in-one” photovoltaic plants, storage systems, and other technological solutions can transform consumers into active prosumages to both reduce their energy costs and provide flexibility to the grid. To exploit those flexibility services, it is necessary to manage the end-users in an aggregated form. End-user aggregation is currently becoming a suitable solution to manage energy flows to obtain environmental, economic, and social benefits. In this scope, the paper presents an algorithm to opportunely manage the energy flows inside this aggregation operating in a Power Cloud framework. The algorithm schedules the energy flows that the end-user storage systems must exchange inside the aggregation to maximize the use of renewable sources, provide grid flexibility services, and simultaneously provide balancing services. The algorithm is organized into three different steps: the day-ahead step, the real-time step, and the balancing one. Some simulation results are illustrated to demonstrate the effectiveness of the proposed algorithm.

Overweight and obesity prevalence has increased worldwide. Apart from conventional approaches, people also resort to botanical supplements for reducing body weight, although several adverse events have been associated with these products. In this context, the present study aimed at evaluating the toxicity of Garcinia cambogia-based products and shedding light on the mechanisms involved. The suspected hepatotoxic reactions related to G. cambogia-containing products collected within the Italian Phytovigilance System (IPS) were examined. Then, an in vitro study was performed to evaluate the possible mechanisms responsible for the liver toxicity, focusing on the modulation of oxidative stress and Nrf2 expression. From March 2002 to March 2022, the IPS collected eight reports of hepatic adverse reactions related to G. cambogia, which exclusively involved women and were mostly severe. The causality assessment was probable in three cases, while it was possible in five. In the in vitro experiments, a low cytotoxicity of G. cambogia was observed. However, its combination with montelukast greatly reduced cell viability, increased the intracellular ROS levels, and affected the cytoplasmic Nrf2 expression, thus suggesting an impairment of the antioxidant and cytoprotective defenses. Overall, our results support the safety concerns about G. cambogia-containing supplements and shed light on the possible mechanisms underpinning its hepatotoxicity.

It is known that the energy transition can be achieved not only with the use of renewable energy sources but also with a new conception and management of the electricity system. Renewable energy communities are then introduced as organizations for maximizing the self-consumption of energy produced from renewable energy sources. To ensure that these energy communities can operate, there is a need for enabling technologies that allow for monitoring, data and algorithms processing as well as the enabling of the same algorithms. There exists a huge confusion in the actual technologies useful to implement the energy communities. This paper first describes and groups the main enabling technologies, analyzing the services that can be offered. The scope is to emphasize the importance of having accurate, efficient and effective technologies that allow the implementation of such communities, underlining how such technologies interact with each other. Using such technologies is important to observing the possible technical and energetic results; indeed, use cases concerning the use of these enabling technologies are proposed and analyzed, showing their operating and their good environmental and energy impact.

Utilities are increasingly interested in integrating energy efficiency and demand response measures as a strategic approach that aims to achieve an increasingly reliable, dynamic, and integrated electric system. The concepts of energy efficiency (EE), demand response (DR), and system reliability (ESR) have been mainly studied from a different perspective, dealing only with the interaction between EE and DR and between EE and ESR. This paper aims to improve knowledge and demonstrate the validity of EE interventions (EEIs) through the use of a tool for evaluating the benefits of energy efficiency measures (EEMs) in the environmental sphere and in terms of DR and ESR. In order to evaluate this interaction, a quantitative method is proposed and validated on real results in an Italian case scenario, taking into account the analysis of smart meters data for residential users located in southern Italy in Calabria. Based on the collected data, an aggregation of users was evaluated with real hourly profiles covering the period from January 2020 to August 2020. These results show how efficient energy use may affect DR resource availability and power systems reliability. In conclusion, the authors justify that a more reliable electric system is ready for new types of EE financing systems based on pay-for-performance contracts.

The recent forecasts regarding the penetration of electric vehicles (EVs) in the transport market and their impact on national electricity distribution grids has presented new challenges in the fields of both of application and research. In this context, vehicle-to-grid (V2G) technology presents itself as an extremely valid solution in terms of application of the “demand side flexibility” paradigm. In this context, the aim of the paper is to analyze from a technical and economical point of view the use of EVs as new flexibility resources to provide network flexibility services in an Italian framework. Within this scope, a methodology for evaluating the flexibility service that a single EV or an EV fleet can offer, and therefore for estimating the EV storage system charge and discharge profile and determining its economic benefit, is proposed. Some numerical results and observations are reported to highlight possible incentive mechanisms for motivating EV end-users to offer flexibility services.

The massive expansion of Distributed Energy Resources and schedulable loads have forced a variation of generation, transmission, and final usage of electricity towards the paradigm of Smart Communities microgrids and of Renewable Energy Communities. In the paper, the use of multiple DC microgrids for residential applications, i.e., the nanogrids, in order to compose and create a renewable energy community, is hypothesized. The DC Bus Signaling distributed control strategy for the power management of each individual nanogrid is applied to satisfy the power flow requests sent from an aggregator. It is important to underline that this is an adaptive control strategy, i.e., it is used when the nanogrid provides a service to the aggregator and when not. In addition, the value of the DC bus voltage of each nanogrid is communicated to the aggregator. In this way, the aggregator is aware of the regulation capacity that each nanogrid can provide and which flexible resources are used to provide this capacity. The effectiveness of the proposed control strategy is demonstrated via numerical experiments. The energy community considered in the paper consists of five nanogrids, interfaced to a common ML-LV substation. The nanogrids, equipped with a photovoltaic plant and a set of lithium-ion batteries, participate in the balancing service depending on its local generation and storage capacity.

To investigate the association of the 2019–2020 influenza vaccine with prognosis of patients positive for SARS-CoV-2A, a large multi-database cohort study was conducted in four Italian regions (i.e., Lazio, Lombardy, Veneto, and Tuscany) and the Reggio Emilia province (Emilia-Romagna). More than 21 million adults were residing in the study area (42% of the population). We included 115,945 COVID-19 cases diagnosed during the first wave of the pandemic (February–May, 2020); 34.6% of these had been vaccinated against influenza. Three outcomes were considered: hospitalization, death, and intensive care unit (ICU) admission/death. The adjusted relative risk (RR) of being hospitalized in the vaccinated group when compared with the non-vaccinated group was 0.87 (95% CI: 0.86–0.88). This reduction in risk was not confirmed for death (RR = 1.04; 95% CI: 1.01–1.06), or for the combined outcome of ICU admission or death. In conclusion, our study, conducted on the vast majority of the population during the first wave of the pandemic in Italy, showed a 13% statistically significant reduction in the risk of hospitalization in some geographical areas and in the younger population. No impact of seasonal influenza vaccination on COVID-19 prognosis in terms of death and death or ICU admission was estimated.

With the introduction of the renewable energy communities in the current electrical market environment, it becomes possible to aggregate small generation resources and users’ loads to exchange power within the aggregation and at the same time provide services to the electrical system. The renewable energy community of users equipped with nanogrid technology allows performing an adequate level of flexibility. It may be the solution to coordinate in the best possible way the energy resources in order to increase the community self-consumption and to provide ancillary services to the grid. In this paper, a model for the interaction between the Distribution System Operator (DSO)—Transmission System Operator (TSO) and the energy community based on nanogrids is proposed and an operational example is presented.

At global level nowadays, there is a general movement towards the goal of a ‘zero-emission’ energy systems. It will require a necessary energy transition characterized by a continuous increase of generation facilities from renewable energy sources (RES), from a massive increase in energy efficiency and, contemporary, an increased use of electricity to meet the energy needs traditionally required through the direct use of fossil fuels. In order to provide end-users with a greater knowledge and awareness of their energy consumption and the benefits of distributed use of renewable energy sources, it is fundamental to employ a smart metering progress which can enable an evolved and ‘smart’ management of the production–demand binomial and an active participation in the energy system. The importance of functionalities implemented in a smart meter—for end-user engagement, empowerment, and awareness—is presented in the paper. For instance, we present a simple optimization functionality for photovoltaic (PV) and storage system sizing based on load and production duration curves and historical data collected by the smart meter with fine resolution. The ease of this functionality uses a data history with extremely high resolutions, which are able to measure the power ramps that occur when an appliance or any other load is connected. An example of application of the smart meter functionality and test cases’ analysis are reported to demonstrate the effectiveness of the tool.

Low frequency ultrasounds in air are widely used for real-time applications in short-range communication systems and environmental monitoring, in both structured and unstructured environments. One of the parameters widely evaluated in pulse-echo ultrasonic measurements is the time of flight (TOF), which can be evaluated with an increased accuracy and complexity by using different techniques. Hereafter, a nonstandard cross-correlation method is investigated for TOF estimations. The procedure, based on the use of template signals, was implemented to improve the accuracy of recursive TOF evaluations. Tests have been carried out through a couple of 60 kHz custom-designed polyvinylidene fluoride (PVDF) hemicylindrical ultrasonic transducers. The experimental results were then compared with the standard threshold and cross-correlation techniques for method validation and characterization. An average improvement of 30% and 19%, in terms of standard error (SE), was observed. Moreover, the experimental results evidenced an enhancement in repeatability of about 10% in the use of a recursive positioning system.

The 2018/2001/EU renewable energy directive (RED II) underlined the strategic role of energy communities in the EU transition process towards sustainable and renewable energy. In line with the path traced by RED II, this paper proposes a solution that may help local energy communities in increasing self-consumption. The proposed solution is based on the combination of smart metering and smart charging. A set of smart meters returns the profile of each member of the community with a time resolution of 5 s; the aggregator calculates the community profile and regulates the charging of electric vehicles accordingly. An experimental test is performed on a local community composed of four users, where the first is a consumer with a Nissan Leaf, whereas the remaining three users are prosumers with a photovoltaic generator mounted on the roof of their home. The results of the experimental test show the feasibility of the proposed solution and demonstrate its effectiveness in increasing self-consumption. The paper also calculates the subsidy that the community under investigation would receive if the current Italian incentive policies for renewables were extended to local energy communities; this subsidy is discussed in comparison with the subsidies that the three prosumers individually receive thanks to the net metering mechanism. This paper ends with an economic analysis and calculation of savings on bills when the four users create the local energy community and adopt the proposed combination of smart metering and smart charging.

The development of even more compact, inexpensive, and highly sensitive gas sensors is widespread, even though their performances are still limited and technological improvements are in continuous evolution. Zeolite is a class of material which has received particular attention in different applications due to its interesting adsorption/desorption capabilities. The behavior of a zeolite 4A modified capacitor has been investigated for the adsorption of nitrogen (N2), nitric oxide (NO) and 1,1-Difluoroethane (C2H4F2), which are of interest in the field of chemical, biological, radiological, and nuclear threats. Sample measurements were carried out in different environmental conditions, and the variation of the sensor electric capacitance was investigated. The dielectric properties were influenced by the type and concentration of gas species in the environment. Higher changes in capacitance were shown during the adsorption of dry air (+4.2%) and fluorinated gas (+7.3%), while lower dielectric variations were found upon exposure to N2 (−0.4%) and NO (−0.5%). The proposed approach pointed-out that a simple fabrication process may provide a convenient and affordable fabrication of reusable capacitive gas sensor.

Recently, hybrid multi-energy systems consisting of multiple generation, conversion, and storage technologies have been receiving great attention as a promising option to meet the multi-energy demands of residential end-users, by transforming them from passive consumers to active prosumers, who both produce and consume energy. The design problem of such systems is challenging due to the large number of degrees of freedom in the design and operation phases, so the system as a whole must be optimized. Moreover, both economic and low-carbon priorities should be considered in the design problem to foster an effective implementation and deployment. The aim of this paper was to present a methodology for the optimal design of multi-energy nanogrids (MENs) operating in grid-connected and islanded modes. Based on a pre-defined MEN superstructure, a multi-objective linear problem was established to find the types and sizes of the technologies in the MEN, with the aim to reduce the total annual cost and the fossil primary energy input, while satisfying the assigned time-varying user multi-energy demand. With reference to the latter, the thermal behavior of the building was simulated by using the dynamic simulation software TRNSYS. The Pareto frontier was found by minimizing a weighted sum of the total annual cost and fossil primary energy input, and the problem was solved by using branch-and-cut. In the numerical testing, a single-family house of 200 m2 located in Italy was considered as the residential end-user. Results show the effectiveness of the model for providing good balancing solutions for end-users based on economic and energetic priorities. Moreover, it was found that the MEN operating in grid-connected mode showed economic and environmental performances much better than those found for the configuration operating in islanded mode.

The temporal resolution of the demand and generation profiles may have a significant impact on the estimation of self-sufficiency and self-consumption for consumers and prosumers. As an example, measuring the load profile, with a low temporal resolution, may lead to the under-estimation of energy consumption, while measuring solar irradiation with a low temporal resolution may lead to the over-estimation of on-site energy generation. Storage systems may reduce errors due to the lower temporal resolution by 8−10 times or even more, depending on the capacity of the batteries. Besides self-generation and self-consumption, there are other indicators that can be influenced by temporal resolution that deserve to be investigated. This is a detailed study of the influence of temporal resolution and the time averaging on a hybrid photovoltaic-battery system; this study encompasses both economic and technical aspects, from the calculation of savings on the electricity bill to the estimation of the equivalent cycles of battery storage system. To this end, the three-minute load profile of a real case study is used to obtain other three load profiles with temporal resolution equal to 15, 30, and 60 min via data averaging. Therefore, the authors analyze the influence and the impact of temporal resolution and data averaging in terms of: The size of the photovoltaic generator and the capacity of the storage system; the savings in the electricity bill and the balance between costs and savings; the peak values and the average values of power flows during high generation and low generation; the profile of the storage system over the year; the utilization rate of the storage system and the rated power of the electronic converter that regulates the charge and the discharge; the profile of the state of charge of the storage system and the life-time estimation of batteries through the calculation of the equivalent number of cycles.

Smart Community microgrids could help to improve overall energy efficiency reducing transmission and distribution losses and allowing the implementation of optimal load control and resource dispatching. In this context, the authors have proposed the realization of DC smart microgrids. They are considered as a future prospective according to the increase of DC loads and DC output type distribution energy sources such as Photovoltaic and energy storage systems. In this paper, a DC smart microgrid, called Smart User Network, realized in a real-life application as a part of pilot site under the national research project PON04_00146 Smart cities and Communities and Social innovation named “Reti, Edifici, Strade Nuovi Obiettivi Virtuosi per l’Ambiente e l’Energia„ (RES NOVAE), is illustrated. The Smart User Network, is managed by a distributed and decentralized control logic, the DC Bus Signaling, which allows the converters to operate independently of each other according to a decentralized logic. It guarantees the reliability, the continuity and the quality of supply, optimizing the use of energy produced by renewable energy sources, also in stand-alone configuration. The most significant experimental results obtained both in grid-connected and stand-alone configuration are presented and discussed.

Meroterpenes are compounds of mixed biogenesis, isolated from plants, microorganisms and marine invertebrates. We have previously isolated and determined the structure for a series of meroterpenes extracted from the ascidian Aplidium aff. densum. Here, we demonstrate the chemical synthesis of three of them and their derivatives, and evaluate their biological activity on two bacterial strains, on sea urchin eggs, and on cancerous and healthy human cells.

In recent years, the diffusion of electric plants based on renewable non-dispatchable sources has caused large imbalances between the power generation schedule and the actual generation in real time operations, resulting in increased costs for dispatching electric power systems. Although this type of source cannot be programmed, their production can be predicted using soft computing techniques that consider weather forecasts, reducing the imbalance costs paid to the transmission system operator (TSO). The problem is mainly that the forecasting procedures used by the TSO, distribution system operator (DSO) or large producers and they are too expensive, as they use complex algorithms and detailed meteorological data that have to be bought, this can represent an excessive charge for small-scale producers, such as prosumers. In this paper, a cheap photovoltaic (PV) production forecasting method, in terms of reduced computational effort, free-available meteorological data and implementation is discussed, and the economic results regarding the imbalance costs due to the utilization of this method are analyzed. The economic analysis is carried out considering several factors, such as the month, the day type, and the accuracy of the forecasting method. The user can utilize the implemented method to know and reduce the imbalance costs, by adopting particular load management strategies.