Learning intrinsic shape representations via spectral mesh convolutions

We introduce spectral-based convolutional operators embedded within Generalized Graph Neural Networks (G-GNNs). These operators enable deep learning on graphs through a learnable, energy-driven evolution process. This approach empowers us to impose specific properties on the graph convolutional kernel directly derived from the corresponding variational formulations. Our model incorporates both parameterized and non- parameterized graph Laplacian-based energies within the generalized graph convolutional layer to address features like smoothness, sharpness, and compact support. By making appropriate choices within our G-GNN framework, we pave the way for designing novel paradigms for 3D shape representation, reconstruction, and processing, while also enabling effective feature embeddings for intrinsic neural fields

Status, sources and contamination levels of organochlorine pesticide residues in urban and agricultural areas: a preliminary review in central–southern Italian soils

Organochlorine pesticides (OCPs) are synthetic chemicals commonly used in agricultural activities to kill pests and are persistent organic pollutants (POPs). They can be detected in different environmental media, but soil is considered an important reservoir due to its retention capacity. Many different types of OCPs exist, which can have different origins and pathways in the environment. It is therefore important to study their distribution and behaviour in the environment, starting to build a picture of the potential human health risk in different contexts. This study aimed at investigating the regional distribution, possible sources and contamination levels of 24 OCP compounds in urban and rural soils from central and southern Italy. One hundred and forty-eight topsoil samples (0–20 cm top layer) from 78 urban and 70 rural areas in 11 administrative regions were collected and analysed by gas chromatography–electron capture detector (GC–ECD). Total OCP residues in soils ranged from nd (no detected) to 1043 ng/g with a mean of 29.91 ng/g and from nd to 1914 ng/g with a mean of 60.16 ng/g in urban and rural area, respectively. Endosulfan was the prevailing OCP in urban areas, followed by DDTs, Drins, Methoxychlor, HCHs, Chlordane-related compounds and HCB. In rural areas, the order of concentrations was Drins > DDTs > Methoxychlor > Endosulfans > HCHs > Chlordanes > HCB. Diagnostic ratios and robust multivariate analyses revealed that DDT in soils could be related to historical application, whilst (illegal) use of technical DDT or dicofol may still occur in some urban areas. HCH residues could be related to both historical use and recent application, whilst there was evidence that modest (yet significant) application of commercial technical HCH may still be happening in urban areas. Drins and Chlordane compounds appeared to be mostly related to historical application, whilst Endosulfan presented a complex mix of results, indicating mainly historical origin in rural areas as well as potential recent applications on urban areas. Contamination levels were quantified by Soil Quality Index (SoQI), identifying high levels in rural areas of Campania and Apulia, possibly due to the intensive nature of some agricultural practices in those regions (e.g., vineyards and olive plantations). The results from this study (which is in progress in the remaining regions of Italy) will provide an invaluable baseline for OCP distribution in Italy and a powerful argument for follow-up studies in contaminated areas. It is also hoped that similar studies will eventually constitute enough evidence to push towards an institutional response for more adequate regulation as well as a full ratification of the Stockholm Convention

Rhus coriaria L. in tradition and innovation like natural dye

: Nowadays, secondary raw materials (SRM) obtained from plant matrices are of great interest for circular economy, suitable for sustainable measures to reduce environmental impact. This work focused on the extraction, characterization and quantification of compounds obtained from leaves and fruits of the Sicilian sumac, Rhus coriaria L. and their application as natural dyes on textile fibres. Extractions were performed with Extractor Naviglio®, maceration and ultrasound assisted methods and food-grade solvents (aqueous and hydroalcoholic) to evaluate the yields for dye compounds. The presence of colouring molecules was evaluated by UV-Vis spectrophotometer, and the extracts selected for colouring were quantified and characterized by LC-MS. The results showed that Extractor Naviglio® achieved the best extraction yield, and the ethanol-water mixture extracts had a higher amount of total phenolic compounds (TPC) and a higher content of total colouring compounds (TCC). These extracts were selected for subsequent applications as dyes for linen, cotton and wool. The chemical profile of selected extracts was rich in compounds such as gallotannin and anthocyanin class. Fibre dyeing was verified by recording CIELAB colouring coordinates. The results suggest that the dyes obtained from R. coriaria can be of great interest for artisanal and industrial processes, in accordance with environmental sustainability

Geogenic versus anthropogenic behaviour and geochemical footprint of Al, Na, K and P in the Campania region (Southern Italy) soils through compositional data analysis and enrichment factor

Geochemical studies that focus on environmental applications tend to approach the chemical elements as individual entities and may therefore offer only partial and sometimes biased interpretations of their distributions and behaviour. A potential alternative approach is to consider a compositional data analysis, where every element is part of a whole. In this study, an integrated methodology, which included compositional data analysis, multifractal data transformations and interpolation, as well as enrichment factor analysis, was applied to a geochemical dataset for the Campania region, in the south of Italy, focusing in particular on the behaviour, footprints and sources of a smaller pool of elements: Al, Na, K and P. The initial dataset included 3669 topsoil samples, collected at an average sampling density of 1 site per 2.3 km2, and analyzed (after an aqua regia extraction) by a combination of ICP-AES and ICP-MS for 53 elements. Frequency based methods (Clr biplot, Enrichment Factor computation) and frequency spatial-method (fractal and multifractal plots) allowed identifying the relationships between the elements and their possible source patterns in Campania soils in relation to a natural occurring concentrations in geogenic material (rocks, soils and sediments) or human input. Results showed how the interpretation of concentration and behaviour of Al, Na, K and P was enhanced thanks to the application of data log-ratio transformation in univariate and multivariate analysis compared to the use of raw or log-normal data. Multivariate analyses with compositional biplot allowed the identification of four element associations and their potential association with the underling geology and/or human activities. When focusing on the smaller pool of elements (Al, P, K and Na), these relationships with the unique geology of the region, were largely confirmed by multifractal interpolated maps. However, when the local background was used for the calculation of the enrichment factor, the resulting interpolated maps allowed to identify smaller areas where the greater concentrations of P could not be possibly associated to a mineralisation (e.g., ultrapotassic rocks) but were more likely to be associated to anthropogenic input such as agriculture activities with potentially extensive use of phosphate fertilizers. The integrated approach of this study allowed a more robust qualitative and quantitative evaluation of elemental concentration, providing in particular new and vital information on the distribution and patterns of P in soils of the Campania region, but also a viable, more robust, methodological approach to regional environmental geochemistry studies

Multi-omic characterisation as a tool to improve knowledge, valorisation and conservation of wild fruit genetic resources: the case of Arbutus unedo L

The valorisation and conservation of plant genetic resources (PGRs) and wild fruit PGRs are critical to ensure the maintenance of genetic and cultural heritage and to promote new perspectives on resource use. New strategies to characterize PGRs are needed, and the omics approach can provide information that is still largely unknown. The Strawberry tree (Arbutus unedo L.) is an underutilized, drought and fire-resistant species distributed in the Mediterranean area and its berries have large ethnobotanical use. Although their phenolic profile and antioxidant capacity are known, they are not well characterised, particularly from a proteomic perspective. The aim of this work is the characterisation of two ecotypes of A. unedo (Campania and Sicily) from a molecular viewpoint to valorise and encourage the preservation of this wild fruit. Samples were collected from two different geographical areas to assess whether different geographical conditions could influence the characteristics of leaves and fruits at the three stages of ripening (green, veraison, red). Proteomic analysis identified 904 proteins, of which 122 showed significance along the ripening. Some of these differentially abundant proteins, such as chalcone synthase, show a marked increase during ripening. The protein functional classes with the highest representation are involved in protein and amino acid metabolism, glycolysis and in secondary metabolism. From a proteomic perspective, there are no differences between the fruits from the two regions compared by the ripening stage. However, the pedoclimatic metabolic imprinting allowed the observation of good diversity in the metabolomic profiles between the two ecotypes, especially for anthocyanins, 4 times more abundant in the Sicilian veraisoned fruit than in the Campania one, and catechins, with double the abundance in the Campania ecotype compared to the Sicilian ecotype in the green phase, but more abundant (3x) in the Sicilian veraisoned fruit. Phenolic compounds show a 20% greater abundance in the Campania green arbutus fruit than in the Sicilian one, values that then equalise as ripening progresses. Multi-omic characterisation enhanced the knowledge on a wild fruit plant species which shows specific adaptations and responses to the environment to be considered when addressing the issue of local agrobiodiversity

Source patterns and contamination level of polycyclic aromatic hydrocarbons (PAHs) in urban and rural areas of Southern Italian soils

Polycyclic aromatic hydrocarbons (PAHs) are a group of persistent organic pollutants (POPs). They have been identified as a type of carcinogenic substance and are relatively widespread in environment media such as air, water and soils, constituting a significant hazard for human health. In many parts of the world, PAHs are still found in high concentrations despite improved legislation and monitoring, and it is therefore vital defining their profiles, and assessing their potential sources. This study focused on a large region of the South of Italy, where concentration levels, profiles, possible sources and toxicity equivalent quantity (TEQ) level of sixteen PAHs were investigated. The survey included soils from five large regions of the south of Italy: 80 soil samples (0–20 cm top layer) from urban and rural locations were collected and analysed by Gas chromatography-mass spectrometry (GC-MS). Total PAHs and individual molecular compounds from the US Environmental Protection Agency (EPA) priority pollutants list were identified and measured. Results showed that 16PAHs varied significantly in urban and rural areas, and different regions presented discordant characteristics. Urban areas presented concentrations ranging from 7.62 to 755 ng/g (mean = 84.85 ng/g), whilst rural areas presented ranges from 1.87 to 11, 353 ng/g (mean = 333 ng/g). Large urban areas, such as Rome, Naples and Palermo, exhibited high PAHs total concentration, but high values were also found in rural areas of Campania region. Different PAHs molecular ratios were used as diagnostic fingerprinting for source identification: L WMPAHs/HWMPAHs, Fluo/(Fluo +Pyr), BaA/(BaA +Chr), Ant/(Ant +Phe), and IcdP/(IcdP +BghiP). These ratios indicated that PAHs sources in the study area were mainly of pyrogenic origin, i.e. mostly related to biomass combustion and vehicular emission. On the other hand, values in Sicilian soils seemed to indicate a petrogenic origin, possibly linked to emissions from crude oil combustion and refineries present in the region. Finally, results allowed to calculate the Toxicity equivalent Quantity (TEQ BAP) levels for the various locations sampled, highlighting that the highest values were found in the Campania region, with 661 ng g-1 and 54.20 ng g-1, in rural and urban areas, respectively. These findings, which could be linked to the presence of a large solid waste incinerator plant, but also to well-documented illegal waste disposal and burning, suggest that exposure to PAH may be posing an increased risk to human health in some of the studied areas

The remediation potential for PAHs of Verbascum sinuatum L. combined with an enhanced rhizosphere landscape: A full-scale mesocosm experiment

A full-scale mesocosm study was conducted to depict how integrated biological systems interact to adapt to contaminant stress and improve remediation of polycyclic aromatic hydrocarbons (PAHs)contaminated soils. The combination of Verbascum sinuatum L. and microbial consortium (fungi and bacteria) was employed along with three differently contaminated soils. After 240 days the highest PAHs removal (up to 68 %) and 6-rings compounds decrease was found in soil with lower pollution and cation exchange capacity. V. sinuatum showed a significant adaptability over time in terms of redox biology. Soil enzyme activities and microscopic evidences proved a rising plant-microorganisms association and a successful mycorrhization, arising from the inoculation of our consortia. In addition, an enhanced richness of PAHs degrading genes was achieved. Microbial co-metabolism, helped by the establishment of complex relationships with hosting plant, demonstrated to be suitable for the degradation of high molecular weight PAHs and represents a biotechnology with great prospects

Coupling compositional data analysis (CoDA) with hierarchical cluster analysis (HCA) for preliminary understanding of the dynamics of a complex water distribution system: The Naples (South Italy) case study

Providing safe tap water has been a global concern. Water scarcity, the ever-increasing water demand, temporal variation of water consumption, aging urban water infrastructure and anthropogenic pressure on the water resources are the greatest challenges in effective water supply. In the present article, the waters exploited to be introduced in a water distribution system (i.e. input water) and tap waters are collected for determination of metal(loid)s, ions and physicochemical parameters. Seasonal variation is observed in the chemistry of the input waters. Further, the annual total dissolved solids (TDS) of the tap waters range from 200 to 1000 mg l-1 which stresses the importance of interconnections between urban water reservoirs for mixing different water types and adjusting water quality. It is complicated in populated cities like Naples with an old water distribution network, which also challenges setting up hydraulic and water quality models. The preliminary data visualization indicates the different chemical characteristics of some samples that are supposed to receive water from the same source. This might explain the difficulties in understanding the network layout in Naples. Thus, the compositional nature of chemical data was considered in hierarchical cluster analysis (HCA) to seasonally study water transfer between urban water reservoirs and define the source of tap water in each city area. The proposed method can preliminarily divide the pipe network into unique clusters and provide an overview of the relationships between different components when representative models cannot be set up due to limited information about network characteristics. Hence, advanced water distribution simulation and management is encouraged. This journal i

Atlante geochimico–ambientale dei suoli della Campania

L’Atlante illustra i risultati ottenuti dalle indagini sui suoli superficiali della Campania. Su un’area di 13.595 Km2 sono stati raccolti 3.535 campioni di suolo e analizzati con una metodologia che combina l’ICP–MS (Spettrometria di massa al plasma accoppiato induttivamente) e l’ICP–ES (Spettrometria a emissione al plasma accoppiato induttivamente). Per ogni elemento chimico sono riportate le proprietà, le applicazioni, gli effetti sulla salute, nonché la distribuzione geochimica in Campania. Le carte geochimico–ambientali che compongono il volume rappresentano una “fotografia” risalente al momento del campionamento e potranno essere utilizzate in futuro come riferimento per la valutazione dell’impatto ambientale delle attività antropiche presenti sul territorio. Sono anche uno strumento di notevole valenza ambientale, soprattutto per quanto concerne la valutazione dei tenori di fondo (background) dei vari elementi chimici esaminati