University of Camerino
  • Camerino, The Marches, Italy
Recent publications
The upcoming development in vehicle to grid network (V2G) allows for the flow of energy from battery powered Electric Vehicle (EV) to grid as well as the exchange of information between them. However, during the information exchange, the EV’s confidential information should be transferred from one charging station to another in a secure manner. Furthermore, the anonymity of the EV and charging station should be preserved. Despite the fact that many works on anonymous authentication and privacy preservation exist, there is an increase in computational cost in existing surveys. In this work, the new charging station authenticates the EV using blockchain technology without the involvement of a trusted entity, resulting in a reduction in computational time. Moreover, an efficient revoking mechanism is suggested to block the misbehaving charging station from the V2G network. In addition, security analysis section proves the resistant of our work against several possible well known attacks. Finally, to evaluate the performance of the work, the simulation is performed using CYGWIN platform and the results are proved to be noteworthy.
Blockchain is one of the most disruptive technologies introduced in Bitcoin, which engaged great attention from the industry and academia and determined a rapid growth of other Distributed Ledger Technologies (DLTs). In the complex architecture of a DLT system, a consensus protocol plays a key role by ensuring that all participants agree on the data integrity without any central authority. A wide range of consensus protocols have been designed with different concepts and properties (e.g., lower energy consumption, better scalability, smaller latency, higher throughput, etc.). The key requirements for consensus protocols passing from one blockchain system to another often differ significantly, and there is no one-fit-all protocol. Therefore, selecting the most suitable consensus protocol for a particular DLT system is essential, but at the same time a challenging step, as decision-makers need to make a trade-off between conflicting requirements. This paper introduces a framework for selecting the most suitable consensus protocols depending on the identified criteria, priorities, and other requirements by incorporating Multi-Criteria Decision-Making (MCDM) techniques. We demonstrate its potential by identifying the preferable consensuses for the three most common types of existing blockchain systems and on an actual application for bike renting. Moreover, the collected data and tools are freely available, ensuring full replicability, reusability, and further development.
Forest expansion can make an important contribution to the 2015 Paris Agreement, through offsetting Greenhouse gas (GHG) emissions. EU, UK and Scottish forest policy encourages substantial forest expansion. Unfortunately, policy is still inadequately informed by high resolution data, and often assumes a fairly homogenous landscape, uniformly suitable soil types and idealised ‘average’ tree timber yields, while carbon emissions caused by soil disturbance during planting, and changes in climate are rarely adequately considered. Also, the proportional contribution of afforestation targets to national mitigation needs is often overlooked which could lead to over-reliance on tree planting. We address these shortcomings through an integrated modelling approach which estimates net carbon gain for eleven tree species accounting for the interactions between climate, soil and planting practices. We present detailed spatial results for a case study area (Scotland), showing where forest expansion would be likely to result in overall carbon gains, accounting for the differentiated spatial variability of timber yield classes for each one of the species considered including present and future climate. The results showed that upland ecosystems, whose soils are rich in carbon, were vulnerable to net carbon loss, particularly with intensive ground preparation and planting practices. While the prevalence of mineral soils in the lowlands makes them a safer option for planting in theory, these are also areas which might conflict with agricultural activities. Our findings strongly support the notion that both “the right tree in the right place” and “no trees in the wrong place” are important messages for practitioners. In terms of the total UK and Scottish carbon footprints, the magnitude of the offset obtained in 30 years if afforestation goals were fully reached would likely be around 1% of the UK total business as usual GHG footprint and around 10% of the Scottish footprint. Our results can help to improve the targeting of incentives and investments in forest and woodland expansion, but also reinforce the need to pursue emissions reductions in a variety of ways throughout all sectors.
The essential oils (EOs) produced by a number of Apiaceae species are well known for their insecticidal efficacy against a wide spectrum of insects, including vectors, stored product and agricultural pests. In the real world, rawly formulated EOs are scarcely effective due to their low chemical stability, limited persistence into the environment, and poor hydrophilicity. Therefore, for practical applications they need to be encapsulated using nanocarriers. In the present study, we evaluated two novel EO-based nanoemulsions (NEs), derived from Pimpinella anisum and Trachyspermun ammi, two plants with documented insecticidal effectiveness, for the management of stored product insects causing economic damages, including Tribolium castaneum, Tribolium confusum, Tenebrio molitor, Trogoderma granarium adults or larvae, and Acarus siro adults or nymphs. The NEs were prepared by a high-pressure homogenization procedure and determined according to the distribution of particle size through dynamic light scattering. Pimpinella anisum EO resulted mainly dominated by the phenylpropanoid (E)-anethole and other minor compounds, while T. ammi EO was mainly composed of thymol, p-cymene, and γ-terpinene and other minor constituents. Each EO-based NE was tested at two concentrations (500 and 1000 ppm) on stored wheat. We evaluated mortality values of the arthropod pests after 4h, 8h, and 16h, and daily from 1–7 days. Complete mortality was achieved for T. castaneum larvae on wheat sprayed with 1000 ppm of 4% (w/w) P. anisum EO-based NE after 6 days of exposure. Similarly, the 8% (w/w) T. ammi EO-based NE killed 100.0% of the tested T. confusum larvae after 7 days to 1000 ppm. When A. siro adults was exposed to 1000 ppm of the 8% (w/w) T. ammi EO-based NE, 89.4% of the tested individuals were killed after 7 days. Binary EO-based NE combination toxicity tests were also carried out. Almost all T. molitor adults (97.8%) died after 7 days to 1000 ppm of 3% (w/w) T. ammi + 3% (w/w) P. anisum EO-based NE. The 3% (w/w) T. ammi + 3% (w/w) P. anisum EO-based NE killed 98.6% of T. granarium adults after 7 days at 1000 ppm. Overall, the tested Apiaceae EO-based NEs exhibited relevant pesticidal efficacy under short exposure intervals, therefore they could be taken into account as auxiliary management tools towards the sustainable protection of durable commodities in storages.
We report on lasing from a new organic mixture, in which a high resolution one dimensional reflection hologram is recorded via blue laser light irradiation at λ = 457.9 nm. The mixture is made by a photo-sensitized acrylate (di-pentaerythrithol-penta/hexa-acrylate) blended with halo-alkanes (1-bromo-hexane and 1-bromo-butane).The halo-alkanes mixture is selected on the basis of its ability to originate phase-separation from the acrylate during the photo-polymerization process and for its relatively low refractive index value. This last property allows the achievement of a good dielectric contrast between polymer-rich and haloalkane-rich layers constituting a one dimensional grating. The recorded structures show a narrow reflection peak and a 40% value diffraction efficiency. The addition of a small percentage (10⁻³ M) of a fluorescent molecule (9-[2-(Ethoxycarbonyl)phenyl]-N-ethyl-6-(ethylamino)-2,7-dimethyl-3H-xanthen-3-iminium chloride) allows lasing when the structure is optically pumped with a pulsed laser. The reflected grating peak (λr = 563 nm) is indeeed tuned to fall inside the emission band of the fluorescent molecule. The periodic grating selects and amplifies only a very narrow band of frequencies which represent our laser radiation.
Advection–diffusion–reaction equations are largely exploited in applied science, for their ability to describe real-life phenomena where mass transport and diffusion, as well as chemical reactions, occur. Here, these models are used to describe the percolation phenomena arising in espresso coffee extraction. The resulting initial/boundary value problem is solved using the Crank–Nicolson scheme and a nested fixed-point iteration. Mass conservation and positivity of the solution are guaranteed. The reliability of the model together with the proposed solving strategy is assessed experimentally, by comparing the efficiency of real and simulated extractions conducted under different physico-chemical conditions.
Insulin resistance (IR) is a risk factor for metabolic disorders and neurodegeneration. Peroxisome proliferator‐activated receptor (PPAR) agonists have been proven to mitigate the neuronal pathology associated with IR. However, the synergetic efficacy of these agonists is yet to be fully described. Hence, we aimed to investigate the efficacy of PPARα/γ agonists (fenofibrate and pioglitazone) on a high‐fat diet (HFD) and streptozotocin (STZ)‐induced hippocampal neurodegeneration. Male Wistar rats (200 ± 25 mg/body weight [BW]) were divided into five groups. The experimental groups were fed on an HFD for 12 weeks coupled with 5 days of an STZ injection (30 mg/kg/BW, i.p) to induce IR. Fenofibrate (FEN; 100 mg/kg/BW, orally), pioglitazone (PIO; 20 mg/kg/BW, orally), and their combination were administered for 2 weeks postinduction. Behavioral tests were conducted, and blood was collected to determine insulin sensitivity after treatment. Animals were killed for assessment of oxidative stress, cellular morphology characterization, and astrocytic evaluation. HFD/STZ‐induced IR increased malondialdehyde (MDA) levels and decreased glutathione (GSH) levels. Evidence of cellular alterations and overexpression of astrocytic protein was observed in the hippocampus. By contrast, monotherapy of FEN and PIO increased the GSH level (p < 0.05), decreased the MDA level (p < 0.05), and improved cellular morphology and astrocytic expression. Furthermore, the combined treatment led to improved therapeutic activities compared to monotherapies. In conclusion, FEN and PIO exerted a therapeutic synergistic effect on HFD/STZ‐induced IR in the hippocampus. Induction of symptoms of insulin insensitivity with the concomitant administration of streptozotocin (STZ) and a high‐fat diet (HFD) increased the fasting glucose level. This alters the neural activities and morphology of the hippocampus via negative activation of Peroxisome proliferator‐activated receptor (PPARs)‐regulated signaling pathways needed for synaptic plasticity and neuronal survival. However, the use of fenofibrate and pioglitazone (PPARs agonists) results in competition for similar active sites and leads to modulation of the respective signaling pathways altered by insulin insensitivity to mitigate alterations of the hippocampus and improve its functionality and neuronal survival.
Metformin, a drug widely used in type 2 diabetes (T2D), has been shown to protect human β-cells exposed to gluco- and/or lipotoxic conditions and those in islets from T2D donors. We assessed whether metformin could relieve the human β-cell stress induced by pro-inflammatory cytokines (which mediate β-cells damage in type 1 diabetes, T1D) and investigated the underlying mechanisms using shotgun proteomics. Human islets were exposed to 50 U/mL interleukin-1β plus 1000 U/mL interferon-γ for 48 h, with or without 2.4 µg/mL metformin. Glucose-stimulated insulin secretion (GSIS) and caspase 3/7 activity were studied, and a shotgun label free proteomics analysis was performed. Metformin prevented the reduction of GSIS and the activation of caspase 3/7 induced by cytokines. Proteomics analysis identified more than 3000 proteins in human islets. Cytokines alone altered the expression of 244 proteins (145 up- and 99 down-regulated), while, in the presence of metformin, cytokine-exposure modified the expression of 231 proteins (128 up- and 103 downregulated). Among the proteins inversely regulated in the two conditions, we found proteins involved in vesicle motility, defense against oxidative stress (including peroxiredoxins), metabolism, protein synthesis, glycolysis and its regulation, and cytoskeletal proteins. Metformin inhibited pathways linked to inflammation, immune reactions, mammalian target of rapamycin (mTOR) signaling, and cell senescence. Some of the changes were confirmed by Western blot. Therefore, metformin prevented part of the deleterious actions of pro-inflammatory cytokines in human β-cells, which was accompanied by islet proteome modifications. This suggests that metformin, besides use in T2D, might be considered for β-cell protection in other types of diabetes, possibly including early T1D.
Currently, Android apps are easily targeted by malicious network traffic because of their constant network access. These threats have the potential to steal vital information and disrupt the commerce, social system, and banking markets. In this paper, we present a malware detection system based on word2vec-based transfer learning and multi-model image representation. The proposed method combines the textual and texture features of network traffic to leverage the advantages of both types. Initially, the transfer learning method is used to extract trained vocab from network traffic. Then, the malware-to-image algorithm visualizes network bytes for visual analysis of data traffic. Next, the texture features are extracted from malware images using a combination of scale-invariant feature transforms (SIFTs) and oriented fast and rotated brief transforms (ORBs). Moreover, a convolutional neural network (CNN) is designed to extract deep features from a set of trained vocab and texture features. Finally, an ensemble model is designed to classify and detect malware based on the combination of textual and texture features. The proposed method is tested using two standard datasets, CIC-AAGM2017 and CICMalDroid 2020, which comprise a total of 10.2K malware and 3.2K benign samples. Furthermore, an explainable AI experiment is performed to interpret the proposed approach.
The relevance of IoT-based solutions in everyday life is continuously increasing. The capability to sense the world, activate computation based on data gathered by sensors, and possibly produce reactions on the world itself results in an almost never-ending identification of novel IoT solutions and application scenarios. Nonetheless, IoT’s intrinsic nature, which includes a high degree of variability in used devices, data formats, resources, and communication protocols, complicates the design, development, reuse and customisation of IoT-based software systems. In addition, customers require personalised solutions strongly based on their specific requirements. Reducing the complexity of building customised solutions and increasing the reusability of developed artefacts are among the topmost challenges for enterprises and IoT application developers. Upon these challenges, we propose a model-driven approach organising the modelling and development of IoT applications in different steps, handling the complexity in representing the IoT domain variability, and empowering the reusability of design decisions and artefacts to simplify the derivation of customised IoT applications. Our proposal is named FloWare. It follows the typical path of an MDE solution, providing modelling support through feature models to fully represent and handle the possible variability of devices in a specific IoT application domain. Once a specific configuration has been selected, this will be complemented with specific information about the deployment context to automatically derive fragments of the IoT applications, that will be successively combined by the developer within a low-code development environment. The approach is fully supported by a toolchain that has been released for public use.
Alzheimer’s disease (AD) is a fatal neurodegenerative disorder associated with severe dementia, progressive cognitive decline, and irreversible memory loss. Although its etiopathogenesis is still unclear, the aggregation of amyloid-β (Aβ) peptides into supramolecular structures and their accumulation in the central nervous system play a critical role in the onset and progression of the disease. On such a premise, the inhibition of the early stages of Aβ aggregation is a potential prevention strategy for the treatment of AD. Since several natural occurring compounds, as well as metal-based molecules, showed promising inhibitory activities toward Aβ aggregation, we herein characterized the interaction of an organoruthenium derivative of curcumin with Aβ(1–40) and Aβ(1–42) peptides, and we evaluated its ability to inhibit the oligomerization/fibrillogenesis processes by combining in silico and in vitro methods. In general, besides being less toxic to neuronal cells, the derivative preserved the amyloid binding ability of the parent compound in terms of equilibrium dissociation constants but (most notably) was more effective both in retarding the formation and limiting the size of amyloid aggregates by virtue of a higher hindering effect on the amyloid–amyloid elongation surface. Additionally, the complex protected neuronal cells from amyloid toxicity.
Digitization of health records is still struggling to take hold in the Italian healthcare context, where medical records are still largely kept manually on paper. Besides being anachronistic, this practice is particularly critical if applied to the drug chart. Poor handwriting and transcription errors can generate medication errors and thus represent a potential source of adverse events. In the present study, we attempt to test the hypothesis that the application of a computerized medical record model may represent a useful tool for managing clinical risk and medical expenditure. We shall do so through the analysis of the preliminary results of the application of such a model in two private hospitals in Northern Italy. The results, although preliminary, are encouraging. Among the benefits of digitizing drug records, we recorded a greater accuracy and adequacy of prescriptions, a reduction in the overall workload for nurses (no longer required to manually transcribe the list of drugs from one chart to another), as well as an optimization of the management of drug stocks by hospital pharmacies. The results in terms of clinical risk reduction will be monitored through a prospective cohort study that will take place in the coming months.
Tajogaite cone in the Cumbre Vieja ridge (La Palma, Canary Islands) erupted between 19 September and 13 December 2021. The tephra and lava sourced from the newly formed fissure rapidly built a pyroclastic cone. During the early days of eruption and after several small-scale landslides, the west flank of the edifice partially collapsed on 25 September, breaching the cone and emplacing a prominent raft-bearing lava flow. Our research combines direct observations, digital elevation models, thermal and visible imaging, and textural and compositional investigation of the explosive products to describe and characterize the edifice growth and collapse. The cone built over a steep slope (26°) and its failure occurred after an intense phase of lava fountaining (up to 30 m3 s-1) that produced rapid pyroclastic accumulation. We suggest that an increased magma supply, to an ascent rate of 0.30 m s-1, led to the rapid growth of the cone (at 2.4 x 106 m3 day-1). Simultaneously, the SW lava flow reactivated and formed a lava ‘seep’ that undercut the flank of the cone, triggering a lateral collapse via rotational rockslide that moved at minimum speeds of 34-70 m h-1. The lateral collapse formed a ~200 m wide scar, involving 5.5 x 106 m3 of material, and covered 1.17 km2 with decametric edifice portions and raft-bearing lava. The collapse produced a modest change in the vent geometry, but did not affect eruptive activity long term. A short pause in the eruption after the collapse may have been favored by rapid emptying of the shallower magma system, reducing ascent rates and increasing crystallization times. These results reveal the complex chain of events related to the growth and destruction of newly formed volcanic cones and highlight hazards when situated close to inhabited areas.
The p62 protein, also called sequestosome 1 (SQSTM1), is a ubiquitin-binding scaffold protein. In human oncology, although the interest in the function of this protein is recent, the knowledge is now numerous but its role in tumorigenesis is not yet clear. This preliminary study aims to evaluate the immunohistochemical expression of p62 in 38 cases of feline mammary carcinoma with different grades of differentiation and in 12 non-neoplastic mammary gland tissues, to assess the expression level and a possible correlation with malignancy. The expression of p62 was statistically higher in carcinoma compared to non-neoplastic mammary glands: 28 feline mammary carcinomas (73.7%) had a high p62 expression score, three (7.9%) had a moderate expression, while 7 cases (18.4 %) had a low expression. The grade of differentiation of the carcinoma was not correlated with the p62 expression. Even if new knowledge came out about the role and expression of p62 in veterinary oncology, this study represents the first approach in feline oncology. Our results, although preliminary, are similar to the results of breast cancer therefore, also in the cat, p62 could be considered a possible oncotarget.
Patagonia is a geographical area characterized by a wide plant biodiversity. Several native plant species are traditionally used in medicine by the local population and demonstrated to be sources of biologically active compounds. Due to the massive need for green and sustainable pesticides, this study was conducted to evaluate the insecticidal activity of essential oils (EOs) from understudied plants growing in this propitious area. Ciprés (Pilgerodendron uviferum), tepa (Laureliopsis philippiana), canelo (Drimys winteri), and paramela (Adesmia boronioides) EOs were extracted through steam distillation, and their compositions were analyzed through GC–MS analysis. EO contact toxicity against Musca domestica L., Spodoptera littoralis (Boisd.), and Culex quinquefasciatus Say was then evaluated. As a general trend, EOs performed better on housefly males over females. Ciprés EO showed the highest insecticidal efficacy. The LD50(90) values were 68.6 (183.7) and 11.3 (75.1) µg adult−1 on housefly females and males, respectively. All EOs were effective against S. littoralis larvae; LD50 values were 33.2–66.7 µg larva−1, and tepa EO was the most effective in terms of LD90 (i.e., <100 µg larva−1). Canelo, tepa, and paramela EOs were highly effective on C. quinquefasciatus larvae, with LC50 values < 100 µL L−1. Again, tepa EO achieved LD90 < 100 µL L−1. This EO was characterized by safrole (43.1%), linalool (27.9%), and methyl eugenol (6.9%) as major constituents. Overall, Patagonian native plant EOs can represent a valid resource for local stakeholders, to develop effective insecticides for pest and vector management, pending a proper focus on their formulation and nontarget effects.
Concerning the increasing level of ultraviolet (UV) radiation in many parts of the world, researching plant establishment under UV exposure is an essential subject. This experiment was aimed at exploring the effects of UV-B on the germination rate, seedling length, radix and stem's length, seedling's fresh/dry weight, and germination indices of Scrophularia striata seeds (Scrophulariaceae), a native medicinal plant from Iran. Treatments included UV-B exposure times (0/control, 15, 30, and 45 min) on two different ecotypes of S. striata including Lizan (LE) and Pahleh (PE). The UV-B radiation treatment for 45 min significantly enhanced the final germination percentage (FGP) of PE seeds. Maximum TSG (time spread of germination) was achieved under 45 min UV exposure (3.67 Day) in PE, while in LE, increasing radiation caused a significant reduction in TSG. Regarding principle component analysis, PE showed better germination indices under UV-B radiation. The seedling length of S. striata was remarkably changed by UV-B treatment; in this case, enhanced seedling length was observed in LE than PE. The UV-B exposure can have promotive effects on many important germination indices in seeds and some seedling growth parameters in S. striata ecotypes, and this effect could be related to the ecotype differences and ecotype-specific responses.
This paper presents the results of a study on the dynamic and seismic response of the support structures of three reference Offshore Wind Turbines (OWT) of increasing rated power, founded to the seabed through monopile foundations. Thus, the structural behaviour of the NREL 5 MW, IEA Wind 10 MW and IEA Wind 15 MW reference OWTs under seismic input is analysed. To do so, a model based on the aero-hydro-servo-elastic OpenFAST open-software code, modified to include dynamic Soil–Structure Interaction (SSI) and input ground motion, is employed. Dynamic SSI phenomena are incorporated through lumped parameter models fitted to the impedances computed using an advanced boundary elements–finite elements model of the soil–foundation system in which the monopile is discretized as a steel pipe buried in the unbounded seabed. The fore–aft and side-to-side responses of the systems are computed under power production, parked and emergency shutdown operating conditions considering different earthquakes and arrival times. It is found that even low and moderate intensity earthquakes can produce significant increases in the structural demands of large OWTs. There exists a clear tendency for SSI to be beneficial when the size of the OWT increases.
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1,634 members
Michele Bellesi
  • School of Bioscience and Veterinary Medicine
Stefania Pucciarelli
  • Scuola di Bioscienze e Medicina Veterinaria
Rita Giovannetti
  • School of Science and Technology Section Chemistry
Seyed Khosrow Tayebati
  • EX Dipartimento di Medicina Sperimentale e Sanità Pubblica
Piazza dei Costanti, 62032, Camerino, The Marches, Italy