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Off-grid power systems based on photovoltaic and battery energy storage systems are becoming a solution of great interest for rural electrification. The storage system is one of the most crucial components since inappropriate design can affect reliability and final costs. Therefore, it is necessary to adopt reliable models able to realistically reproduce the working condition of the application. In this paper, different models of lithium-ion battery are considered in the design process of a microgrid. Two modeling approaches (analytical and electrical) are developed based on experimental measurements. The derived models have been integrated in a methodology for the robust design of off-grid electric power systems which has been implemented in a MATLAB-based computational tool named Poli.NRG (POLItecnico di Milano—Network Robust desiGn). The procedure has been applied to a real-life case study to compare the different battery energy storage system models and to show how they impact on the microgrid design.

This paper presents a parametric procedure to size a hybrid system consisting of renewable generation (wind turbines and photovoltaic panels) and Battery Energy Storage Systems (BESS). To cope with the increasing installation of grid-scale BESS, an innovative, fast and flexible procedure for evaluating an efficient size for this asset has been developed. The tool exploits a high-fidelity empirical model to assess stand-alone BESS or hybrid power plants under different service stacking configurations. The economic performance has been evaluated considering the revenue stacking that occurs when participating in up to four distinct energy markets and the degradation of the BESS performances due to both cycle- and calendar-aging. The parametric nature of the tool enables the investigation of a wide range of system parameters, including novel BESS control logic, market prices, and energy production. The presented outcomes detail the techno-economic performances of a hybrid system over a 20-year scenario, proposing a sensitivity analysis of both technical and economic parameters. The case study results highlight the necessity of steering BESS investment towards the coupling of RES and accurate planning of the service stacking. Indeed, the implementation of a storage system in an energy district improves the internal rate of return of the project by up to 10% in the best-case scenario. Moreover, accurate service stacking has shown a boost in revenues by up to 44% with the same degradation.

The use of electrochemical cells is becoming more widespread, especially in the energy industry and battery energy storage systems (BESSs). As we continue to deploy BESSs, it becomes increasingly important for us to understand how these systems age and accurately predict their performance over time. This knowledge is essential for ensuring that the systems operate optimally and can be properly maintained. Since the structure of a BESS is different from a single electrochemical cell, the existing models at the cell level cannot predict and estimate the life of the BESS with suitable accuracy. Furthermore, the test protocols available at the cell level mostly cannot be executed at the BESS level for many reasons. Therefore, in this paper, a review of test protocols for building aging models for BESSs has been performed. After reviewing the protocols for a single electrochemical cell and addressing the differences between BESSs and cells, a review of the works performed on a larger scale has been carried out, and the possible ways for testing the BESS for aging models were investigated.

Less than 15% of rural areas of Cameroon have access to grid electricity. Only 53% of the population has access to grid electricity. Notwithstanding, Cameroon has a huge hydropower potential which could be harnessed. Mini grids, powered by pico and micro hydropower plants, are a relatively new rural electrification strategy in Cameroon. Several of such mini grids have been realized in the mountain regions of the country. Some of these systems have been more successful than others. This paper aims to share the experiences of community-based pico and micro hydropower schemes for rural electrification in Cameroon. The paper provides insight to the challenges that three of such mini grid systems powered by pico and micro hydropower plants had encountered and it attempts to identify issues related to their performances. The study was based on personal experience, field visits, participant observations, interviews and focus group discussions with key members of the beneficiary communities and documentations from the local NGO which implemented the schemes. Key findings of this study relate to the description of the main aspects about: planning of a robust system design, organizational aspects, like social cohesion at all levels of scheme management, community leadership and ownership of the system and involvement of the beneficiaries at all stages of the project cycle. These aspects were particularly addressed within the context of rural communities in Cameroon.

Two decades of investigations have failed to unequivocally clarify the functions and the molecular nature of imidazoline-2 receptors (I2R). However, there is robust pharmacological evidence for the functional modulation of monoamino oxidase (MAO) and other important enzyme activities by I2 site ligands. Some compounds of this class proved to be active experimental tools in preventing both experimental pain and opioid tolerance and dependence. Unfortunately, even though these compounds bind with high potency to central I2 sites, they fail to represent a valid clinical opportunity due to their pharmacokinetic, selectivity or side-effects profile. This paper presents the preclinical profile of a novel I2 ligand (2-phenyl-6-(1H-imidazol-1yl) quinazoline; [CR4056]) that selectively inhibits the activity of human recombinant MAO-A in a concentration-dependent manner. A sub-chronic four day oral treatment of CR4056 increased norepinephrine (NE) tissue levels both in the rat cerebral cortex (63.1% ±4.2%; P < 0.05) and lumbar spinal cord (51.3% ± 6.7%; P < 0.05). In the complete Freund's adjuvant (CFA) rat model of inflammatory pain, CR4056 was found to be orally active (ED50 = 5.8 mg/kg, by mouth [p.o.]). In the acute capsaicin model, CR4056 completely blocked mechanical hyperalgesia in the injured hind paw (ED50 = 4.1 mg/kg, p.o.; ED100 = 17.9 mg/kg, p.o.). This effect was dose-dependently antagonized by the non-selective imidazoline I2/α2 antagonist idazoxan. In rat models of neuropathic pain, oral administration of CR4056 significantly attenuated mechanical hyperalgesia and allodynia. In summary, the present study suggests a novel pharmacological opportunity for inflammatory and/or neuropathic pain treatment based on selective interaction with central imidazoline-2 receptors.

This paper aims to describe the Pointing Reconstruction Model (PRM) and the prototype Star Tracker, which will be mounted on LSPE-Strip, a microwave Q- and W-band CMB telescope planned for installation at the \"Observatorio del Teide\" in Tenerife. The PRM integrates information on the instantaneous attitude provided by the telescope control system to determine the actual pointing direction and focal plane orientation of the telescope. It accounts for various non-idealities in the telescope setup, represented by eight configuration angles, which will be calibrated using the Star Tracker. Following the derivation of the PRM formalism and its implementation, we investigate the pointing errors caused by incorrect calibration of these configuration angles to validate the required 1 arcminute maximum systematic pointing error for the LSPE-Strip survey. This paper also describes the main structure and operations of the Star Tracker and presents the results of a campaign of actual sky observations conducted with a prototype. The results demonstrate a Star Tracker RMS accuracy of approximately 3 arcseconds, while systematic errors remain below 10 arcseconds. Based on these results, we analyzed the problem of reconstructing the PRM configuration angles. Two methods for intercalibrating the Star Tracker's pointing direction with respect to the focal plane's pointing direction were examined: (1) observations of planets and (2) observations of a drone carrying both an optical beacon and a radio beacon. In the first case, an intercalibration accuracy between 1/3 arcminute and 1 arcminute is achievable. In the second case, the expected intercalibration accuracy ranges from 0.25 arcminute to 1 arcminute.

The work proposes a novel planning procedure to design the portfolio of Dispersed Generation in a given area in order to exploit optimally the locally available RES. The objective of the work is to provide suitable indications to Policy Makers useful to develop more effective regional energy plans. The developed approach is applied on a real life study case: the electric distribution network supplying the urban area and the neighbourhood of the Italian city of Aosta.

We present the design, manufacturing, and testing of a 37-element array of corrugated feedhorns for Cosmic Microwave Background (CMB) measurements between \\(140\\) and \\(170\\) GHz. The array was designed to be coupled to Kinetic Inductance Detector arrays, either directly (for total power measurements) or through an orthomode transducer (for polarization measurements). We manufactured the array in platelets by chemically etching aluminum plates of \\(0.3\\) mm and \\(0.4\\) mm thickness. The process is fast, low-cost, scalable, and yields high-performance antennas compared to other techniques in the same frequency range. Room temperature electromagnetic measurements show excellent repeatability with an average cross polarization level about \\(-20\\) dB, return loss about \\(-25\\) dB, first sidelobes below \\(-25\\) dB and far sidelobes below \\(-35\\) dB. Our results qualify this process as a valid candidate for state-of-the-art CMB experiments, where large detector arrays with high sensitivity and polarization purity are of paramount importance in the quest for the discovery of CMB polarization \\(B\\)-modes.

Mounting evidence suggests that storage has an impact on extracellular vesicles (EVs) properties. While −80°C storage is a widespread approach, some authors proposed improved storage strategies with conflicting results. Here, we designed a systematic study to assess the impact of −80°C storage and freeze‐thaw cycles on EVs. We tested the differences among eight storage strategies and investigated the possible fusion phenomena occurring during storage. EVs were collected from human plasma and murine microglia culture by size exclusion chromatography and ultracentrifugation, respectively. The analysis included: concentration, size and zeta potential (tunable resistive pulse sensing), contaminant protein assessment; flow cytometry for the analysis of two single fluorescent‐tagged EVs populations (GFP and mCherry), mixed before preservation. We found that −80°C storage reduces EVs concentration and sample purity in a time‐dependent manner. Furthermore, it increases the particle size and size variability and modifies EVs zeta potential, with a shift of EVs in size‐charge plots. None of the tested conditions prevented the observed effects. Freeze‐thaw cycles lead to an EVs reduction after the first cycle and to a cycle‐dependent increase in particle size. With flow cytometry, after storage, we observed a significant population of double‐positive EVs (GFP+‐mCherry+). This observation may suggest the occurrence of fusion phenomena during storage. Our findings show a significant impact of storage on EVs samples in terms of particle loss, purity reduction and fusion phenomena leading to artefactual particles. Depending on downstream analyses and experimental settings, EVs should probably be processed from fresh, non‐archival, samples in majority of cases.

Plants emit biogenic volatile organic compounds (BVOCs), such as isoprene, significantly influencing atmospheric chemistry and climate. BVOC emissions estimated from bottom-up (BU) approaches (derived from numerical simulations) usually exhibit denser and more detailed spatial information compared to those estimated through top-down (TD) approaches (derived from satellite observations). Moreover, numerically simulated emissions are typically easier to obtain, even if they are less reliable than satellite acquisitions, which, being derived from actual measurements, are considered a more trustworthy instrument for performing chemistry and climate investigations. Given the coarseness and relative lack of satellite-derived measurements, fine-grained numerically simulated emissions could be exploited to enhance them. However, simulated (BU) and observed (TD) emissions usually differ regarding value range and spatiotemporal resolution. In this work, we present a novel deep learning (DL)-based approach to increase the spatial resolution of satellite-derived isoprene emissions, investigating the adoption of efficient domain adaptation (DA) techniques to bridge the gap between numerically simulated emissions and satellite-derived emissions, avoiding the need for retraining a specific super-resolution (SR) algorithm on them. For this, we propose a methodology based on the cycle generative adversarial network (CycleGAN) architecture, which has been extensively used for adapting natural images (like digital photographs) of different domains. In our work, we depart from the standard CycleGAN framework, proposing additional loss terms that allow for better DA and emissions’ SR. We extensively demonstrate the proposed method’s effectiveness and robustness in restoring fine-grained patterns of observed isoprene emissions. Moreover, we compare different setups and validate our approach using different emission inventories from both domains. Eventually, we show that the proposed DA strategy paves the way towards robust SR solutions even in the case of spatial resolution mismatch between the training and testing domains and in the case of unknown testing data.