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Microplastics (MP; 1 µm-5 mm) and microfibers (MF; thin, elongated particles with a high-length-to-width ratio) have become a major global environmental issue due to their ubiquity in the oceans and possess complex physicochemical properties that vary their mobility, bioavailability, and toxicity toward organisms and interactions with their surrounding pollutants. Nonetheless, a reliable methodology that would facilitate and automate the monitoring of MP is still lacking. Intending to select practical and standardized methods and considering the challenges in MPs detection, a new analysis protocol based on optical microscopy for the counting and morphological analysis of the particles has been developed. This method overcomes some issues related to the lack of practicality and standardization of the others currently applied, and does not involve sieving, washing, heating, or density separation and digestion processes. Our method is green and requires a minimum quantity of sediment, i.e., 1.5 g, and shortened timeframes. Future research efforts may need to develop and implement new analytical tools and combinations of technologies to complement respective detection limitations and yield reliable characterization of both MFs and MPs. We tested our protocol to study, for the first time, both marine and land sediment in the Vesuvian area of the Gulf of Naples (Italy)., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Apples are among the most commonly cultivated fruits globally. Approximately 65% of annual apple production is transformed into apple juice concentrate generating a large amount of waste material named apple pomace, which includes seeds, skin, and other components. Disposing of apple by-products directly into the environment constitutes a source of environmental pollution due to its high-water content and easily fermentable nature. Apple pomace is rich in polyphenols that can be utilized as active components in cosmetic, nutraceutical, or pharmaceutical products. The present study aims to describe and compare different physical methods for the extraction of polyphenols from apple pomace. Water was used as the extraction solvent in thermal-stirred extraction (TSE), ultrasound-assisted extraction (UAE), and microwave-assisted extraction (MAE). The best extraction conditions were identified in terms of solid to solvent ratio, temperature, power, and time through a kinetic study. The best extraction parameters were compared environmentally on a pilot scale through a life cycle assessment (LCA). All the results demonstrated the MAE is the best technique to extract polyphenol from apple pomace in terms yield and environmental impact proving that it is possible to transform waste into a sustainable source of bioactive ingredients., (© 2024. The Author(s).)

The study concerned technical feasibility, economic profitability, and carbon footprint (CF) analysis of semi-continuous anaerobic digestion (sAD) of organic fraction of municipal solid waste (OFMSW). The research assessed the pre-treatment effect on sAD by varying organic loading rates (OLR) from 3.38 to 6.75 kgvs/m 3 d. Three sAD configurations were investigated: hydrodynamic-cavitated (HC-OFMSW), enzymatically pre-treated (EN-OFMSW), and non-pre-treated (AD-OFMSW). Principal Component Analysis and Supervised Kohonen's Self-Organizing Maps combined the experimental, economic, and environmental evaluations. The sAD configurations were grouped predominantly according to the OLR however, within each OLR group the configurations were clustered according to the pre-treatments. The finding highlighted that pre-treatments offset inhibition in sAD of OFMSW due to the OLR increase, being economically profitable and CF negative up to 4.50 kgvs/m 3 d for EN-OFMSW and to 5.40 kgvs/m 3 d for HC-OFMSW. Whereas sAD-OFMSW remained economically and environmentally viable only up to 3.87 kgvs/m 3 d. HC-OFMSW reached the highest performance. In detail, for HC-OFMSW the NPV and CF ranged from 17679.30 to 43827.12 euros and from -51.08 to -407.210 kg CO 2 eq/1 MWh daily produced, by decreasing the OLR from 5.40 to 3.87 kgvs/m 3 d. These results are fundamental since pre-treatment is usually expensive due to additional energy or chemical requirements., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The state of the art in violence detection in videos has improved in recent years thanks to deep learning models, but it is still below 90% of average precision in the most complex datasets, which may pose a problem of frequent false alarms in video surveillance environments and may cause security guards to disable the artificial intelligence system. In this study, we propose a new neural network based on Vision Transformer (ViT) and Neural Structured Learning (NSL) with adversarial training. This network, called CrimeNet, outperforms previous works by a large margin and reduces practically to zero the false positives. Our tests on the four most challenging violence-related datasets (binary and multi-class) show the effectiveness of CrimeNet, improving the state of the art from 9.4 to 22.17 percentage points in ROC AUC depending on the dataset. In addition, we present a generalisation study on our model by training and testing it on different datasets. The obtained results show that CrimeNet improves over competing methods with a gain of between 12.39 and 25.22 percentage points, showing remarkable robustness., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Municipal solid waste (MSW) production in the world has increased by 60 % in recent years. Incineration of MSW reduces their volume in conjunction with energy recovery. Incineration produces two residues, namely bottom ash (BA) and fly ash (FA), with high concentration of heavy metals and organic pollutants, especially for FA, making them an environmental concern. Vitrification is a costly, highly safe high temperature treatment, ensuring encapsulation of heavy metals. FA vitrification requires a source of silica to be able to get vitrified. In this study, we have proposed valorizing treated (vitrified) FA through the production of porous glass-ceramics, subsequently to MSWI. The entire process, from incineration to glass-ceramics production, was evaluated for several scenarios by Life Cycle Assessment (LCA) using Sima Pro 9.0. Three main scenarios were analysed; each one considering a different silica source: bottom ash (BA), glass cullet (G) and silica sand (S), and for each scenario, three thermal recovery subscenarios were assumed: no thermal recovery used to heat FA prior to vitrification (N), heating FA prior to vitrification using incineration gases thermal recovery (T) and methane-combustion-aided thermal recovery, which exploits methane combustion to further increase the gases temperature (M). Results proved that vitrification was a technically feasible and environmentally-energetically sustainable technology. The result indicates that the most eco-sustainable scenario was using bottom ashes as a silica source together with methane-combustion-aided recovery: 0.467 kgCO 2,eq , 5.83 × 10 -8 carcinogenic-CTUh and 9.26 MJ required per kg of glass-ceramics produced., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)