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Electroencephalography (EEG) signals frequently contain substantial noise and interference, which can obscure clinically and scientifically relevant features. Traditional denoising approaches, such as linear filtering or wavelet thresholding, often struggle with nonlinear or time-varying artifacts. In response, the present study explores a Generative Adversarial Network (GAN) framework to enhance EEG signal quality, focusing on two variants: a conventional GAN model and a Wasserstein GAN with Gradient Penalty (WGAN-GP). Data were obtained from two distinct EEG datasets: a \"healthy\" set of 64-channel recordings collected during various motor/imagery tasks, and an \"unhealthy\" set of 18-channel recordings from individuals with orthopedic impairments. Both datasets underwent comprehensive preprocessing, including band-pass filtering (8-30 Hz), channel standardization, and artifact trimming. The training stage involved adversarial learning, in which a generator sought to reconstruct clean EEG signals while a discriminator (or critic in the case of WGAN-GP) attempted to distinguish between real and generated signals. The model evaluation was conducted using quantitative metrics such as signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), correlation coefficient, mutual information, and dynamic time warping (DTW) distance. Experimental findings indicate that adversarial learning substantially improves EEG signal fidelity across multiple quantitative metrics. Specifically, WGAN-GP achieved an SNR of up to 14.47 dB (compared to 12.37 dB for the standard GAN) and exhibited greater training stability, as evidenced by consistently lower relative root mean squared error (RRMSE) values. In contrast, the conventional GAN model excelled in preserving finer signal details, reflected in a PSNR of 19.28 dB and a correlation coefficient exceeding 0.90 in several recordings. Both adversarial frameworks outperformed classical wavelet-based thresholding and linear filtering methods, demonstrating superior adaptability to nonlinear distortions and dynamic interference patterns in EEG time-series data. By systematically comparing standard GAN and WGAN-GP architectures, this study highlights a practical trade-off between aggressive noise suppression and high-fidelity signal reconstruction. The demonstrated improvements in signal quality underscore the promise of adversarially trained models for applications ranging from basic neuroscience research to real-time brain-computer interfaces (BCIs) in clinical or consumer-grade settings. The results further suggest that GAN-based frameworks can be easily scaled to next-generation wireless networks and complex electrophysiological datasets, offering robust and dynamic solutions to long-standing challenges in EEG denoising.

Ecoregionalization is the process by which a territory is classified in similar areas according to specific environmental and climatic factors. The climate and the environment strongly influence the presence and distribution of vectors responsible for significant human and animal diseases worldwide. In this paper, we developed a map of the eco-climatic regions of Italy adopting a data-driven spatial clustering approach using recent and detailed spatial data on climatic and environmental factors. We selected seven variables, relevant for a broad set of human and animal vector-borne diseases (VBDs): standard deviation of altitude, mean daytime land surface temperature, mean amplitude and peak timing of the annual cycle of land surface temperature, mean and amplitude of the annual cycle of greenness value, and daily mean amount of rainfall. Principal Component Analysis followed by multivariate geographic clustering using the k-medoids technique were used to group the pixels with similar characteristics into different ecoregions, and at different spatial resolutions (250 m, 1 km and 2 km). We showed that the spatial structure of ecoregions is generally maintained at different spatial resolutions and we compared the resulting ecoregion maps with two datasets related to Bluetongue vectors and West Nile Disease (WND) outbreaks in Italy. The known characteristics of Culicoides imicola habitat were well captured by 2/22 specific ecoregions (at 250 m resolution). Culicoides obsoletus/scoticus occupy all sampled ecoregions, according to its known widespread distribution across the peninsula. WND outbreak locations strongly cluster in 4/22 ecoregions, dominated by human influenced landscape, with intense cultivations and complex irrigation network. This approach could be a supportive tool in case of VBDs, defining pixel-based areas that are conducive environment for VBD spread, indicating where surveillance and prevention measures could be prioritized in Italy. Also, ecoregions suitable to specific VBDs vectors could inform entomological surveillance strategies.

Wastewater treatment plants are highly energy-intensive systems. This research uses Life Cycle Assessment (LCA) to determine the impacts generated during the operation of a wastewater treatment plant. Three different scenarios are analyzed: a baseline scenario that considers a conventional activated sludge treatment technology exploiting data from an existing plant located in central Italy, a second scenario that involves the implementation of MBR technology applied to the baseline scenario, and finally a third scenario that consists of the addition of an anaerobic digester that allows energy recovery from biogas production, followed by a photovoltaic plant capable of supplying the plant energy demand. Global warming potential, eutrophication, and acidification are the environmental categories considered most relevant to emissions. The results showed that the effluent had the highest impact in terms of CO2 equivalent in all three situations due to the presence of N2O. Since emissions from biological processes, transportation, and wastewater are almost similar in all three scenarios, it is preferable to focus on the environmental impacts associated with energy consumption. The third scenario involves careful resource management and the use of treatment technologies that allow for a reduction in the use of nonrenewable energy sources in favor of renewable ones.

With regards to European waste catalog, automotive shredder residues (ASR) can be classified both as a hazardous or non-hazardous waste according to its hazardous properties (H1–H14). It is thus important to carry out an adequate chemical-physical characterization to identify the presence and concentration of those substances able to give, to this extremely heterogeneous material, the hazardousness character of. The issue of waste characterization, to identify the proper site for appropriate waste disposal, is based, according to the relevant laws, to the use of leaching tests. The analysis of the potential effects of landfilled waste in laboratory, however, run into several difficulties in reproducing phenomena depending both on the characteristics of small, heterogeneous quantity of waste and on the local boundary conditions. These difficulties are much more significant as the waste is heterogeneous at the small scale of the laboratory. This is one of the main problems often leading to scattered results even when starting from the same waste parcel. Present research aimed to overcome the above-mentioned difficulties deriving from waste heterogeneity and was based on a lysimetric simulation. Experimentation with lysimeter has shown it effectiveness in the comparison between leachate from the lysimeter and an ASR landfill leachate, from which similar distribution of metal mass ratios, close values for both BOD 5 and COD, as well as the absence in both the fluids of organochlorinated compounds, emerge.

Two laboratory tests were carried out to verify the suitability of an Italian commercial biochar as an adsorbing material. The chosen contaminant, considered dissolved in groundwater, was As. The circular economic concept demands the use of such waste material. Its use has been studied in recent years on several contaminants. The possibility of using an efficient material at low cost could help the use of low-impact technologies like permeable reactive barriers (PRBs). A numerical model was used to derive the kinetic constant for two of the most used isotherms. The results are aligned with others derived from the literature, but they also indicate that the use of a large amount of biochar does not improve the efficiency of the removal. The particular origin of the biochar, together with its grain size, causes a decrease in contact time required for the adsorption. Furthermore, it is possible that a strong local decrease in the hydraulic conductibility does not allow for a correct dispersion of the flow, thereby limiting its efficiency.

The distribution of Bluetongue virus (BTV) in Europe can be represented by two distinct and interconnected epidemiological systems (episystems), each characterized by different ecological characteristics and vector species. This study investigated the vector competence of Italian populations of Culicoides imicola and Culicoides obsoletus/scoticus to some representative BTV strains after artificial oral infection. The BTV strains were selected according to their ability to spread to one or both episystems and included BTV-4 ITA, responsible of the recent Italian and French BTV-4 outbreaks; the BTV-2 strain which caused the first BTV incursion in Italy, Corsica, and Balearic Islands; BTV-4 MOR, responsible for the epidemic in Morocco; and BTV-8, the strain which spread through Europe between 2006 and 2008. Blood-soaked cotton pledgets and Hemotek membrane feeder using Parafilm® membrane were used to artificially feed midges. For each population/strain, recovery rates (positive/tested heads) were evaluated using serogroup- and serotype-specific RT-PCR. The trial demonstrated that, except for the Abruzzo population of C. obsoletus/C. scoticus, which was refractory to BTV-4 MOR infection, all the investigated Culicoides populations are susceptible to the selected BTV strains and that, if prompt vaccination programs and restriction measures had not been implemented, BTV-2 and BTV-4 MOR could have spread all over Europe.

Zero-valent iron nanoparticle (nZVI) technology has been found to be promising and effective for the remediation of soils or groundwater. However, while nanoparticles are traveling through porous media, they can rapidly aggregate, causing their settling and deposition. When nZVI are injected in the groundwater flow, the behavior (mobility, dispersion, distribution) is unknown in groundwater, causing the use of enormous quantities of them if used at the field scale. In this paper, a laboratory experiment was carried out with groundwater flow in a two-dimensional, laboratory-scale tank to assess the nanoparticle behavior by means of an image analysis procedure. A solution of zero-valent iron nanoparticles, Nanofer 25S particles, were used and glass beads were utilized as porous medium. The laboratory experiment included the use of a digital camera for the acquisition of the images. The image analysis procedure was used to assess the behavior of nZVI plume. A calibration procedure and a mass balance were applied to validate the proposed image analysis procedure, with the hypothesis that nanoparticles would be uniformly distributed in the third dimension of the tank (thickness). The results show that the nanoparticles presented small dispersive effects and the motion was strongly influenced from the higher weight of them with respect to the water. Therefore, the results indicate that nanoparticles have an own motion not strongly influenced by the fluid flow but more determined from the injection phase and gravity. The statistical elaborations show that the nZVI plume did not respond to the classical mechanisms of the dispersion.

Strategies for Municipal Solid Waste (MSW) management can be sustainable only because of site-specific analyses and choices that take into account not only financial but also environmental costs. Generally, a correct approach should use different scenarios based on the environmental, social, economic and technological conditions of the specific area and on its expected potential. The aim of this paper is to presents an innovative model for the implementation of integrated MSW management approach which can result extremely useful where the MSW systems have to be refined or even designed such in the case of low-income countries. The proposed approach provides the best solid waste (SW) allocation/distribution among the available treatments and disposal options minimizing at the same time the total cost by means of an optimization procedure. The environmental impacts of potential scenarios are simultaneously estimated by means of a tailored Life Cycle Assessment procedure. The LCA tool in the model focus on the specific impacts from a SW management scenario that makes the model more explicit with respect to traditional LCA application. Additional tools allow, through site-specific numerical models, to provide also a preliminary evaluation of local impacts when required (e.g. atmospheric emissions). Such a model can be useful as a supporting tool in decision making for both governmental and non-governmental institutions involved in the planning of more sustainable eco-friendly strategies for MSW management. Graphic Abstract

The aim of the present work was the assessment of the environmental status of marine biota along the Sicilian ionic coast (Italy). Due to its complex habitat requirements, the fish fauna is a crucial indicator of the ecological integrity of aquatic systems at different scales, from micro-habitat to catchment. Besides environmental contaminants, biomarkers of oxidative stress answer to the Water Framework Directive’s challenges for improved detection of the impacts of chemical compounds on aquatic organisms. Highly consumed seafood species (Solea solea, Mullus barbatus, Sardina pilchardus and Scomber scombrus) were taken at the Gulf of Catania (Sicily). Levels of metals/metalloids (As, Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Se, V, Zn) were estimated in muscle tissue as well as oxidative stress parameter such as malondialdehyde (MDA) and protein carbonyl (PC) derivatives in liver. The total metals/metalloids load indicated as Metal Pollution Index (MPI, unitless) were the following: 0.258 in S. pilchardus, 0.203 in S. scombrus, 0.123 in M. barbatus and 0.071 in S. solea. The greatest contribution was given by As (mean range 2.670–9.748 mg/kg wet weight) and Zn (mean range 2.169–4.736 wet weight) levels. Hg, Ni and Zn presented mean levels progressively higher, with increasing trophic position. From a chemical point of view, the analyzed species were healthy for human consumption and the risk to develop chronic systemic and carcinogenic effects was low; nevertheless, it has highlighted an oxidative stress condition.Highly consumed seafood species, caught in the Gulf of Catania, were chosen for metals determination.Malondialdehyde (MDA) and protein carbonyl (PC) derivatives were analysed in liver.From a chemical point of view, the analysed species are healthy for human consumption.Nevertheless, fish species resulted stressed by environmental conditionsMDA and PC are sensitive indicators of low degree of aquatic pollution.

Objective: The objectives of this study were to describe the trajectories of bone mineral density (BMD) and trabecular bone score (TBS) changes throughout pre-menopause (reproductive phase and menopausal transition) and post-menopause (early and late menopause) in women with HIV (WWH) undergoing different antiretroviral therapies (ARTs) and explore the risk factors associated with those changes. Methods: This was an observational longitudinal retrospective study in WWH with a minimum of two DEXA evaluations comprising BMD and TBS measurements, both in the pre-menopausal and post-menopausal periods. Menopause was determined according to the STRAW+10 criteria, comprising four periods: the reproductive period, menopausal transition, and early- and late-menopausal periods. Mixed-effects models were fitted to estimate the trajectories of the two outcomes (BMD and TBS) over time. Annualized lumbar BMD and TBS absolute and percentage changes were calculated in each STRAW+10 time window. A backward elimination procedure was applied to obtain the final model, including the predictors that affected the trajectories of BMD or TBS over time. Results: A total of 202 WWH, all Caucasian, were included. In detail, 1954 BMD and 195 TBS data were analyzed. The median number of DEXA evaluations per woman was 10 (IQR: 7, 12). The median observation periods per patient were 12.0 years (IQR = 8.9–14.4) for BMD and 6.0 years (IQR: 4.3, 7.9) for TBS. The prevalence of osteopenia (63% vs. 76%; p < 0.001) and osteoporosis (16% vs. 36%; p < 0.001) increased significantly between the pre-menopausal and post-menopausal periods. Both BMD (1.03 (±0.14) vs. 0.92 (±0.12) g/cm2; p < 0.001) and TBS (1.41 (IQR: 1.35, 1.45) vs. 1.32 (IQR: 1.28, 1.39); p < 0.001) decreased significantly between the two periods. The trend in BMD decreased across the four STRAW+10 periods, with a slight attenuation only in the late-menopausal period when compared with the other intervals. The TBS slope did not significantly change throughout menopause. The delta mean values of TBS in WWH were lower between the menopausal transition and reproductive period compared with the difference between menopause and menopausal transition. Conclusions: Both BMD and TBS significantly decreased over time. The slope of the change in BMD and TBS significantly decreased in the menopausal transition, suggesting that this period should be considered by clinicians as a key time during which to assess bone health and modifiable risk factors in WWH.