Search Results (665)

This study examines income convergence among EU NUTS-2 regions from 2000 to 2023 using a combination of Phillips-Sul (PS) club convergence methodology, $\beta$-convergence, and spatial econometric models. The results reveal that regional convergence in Europe is heterogeneous and nonlinear: four stable convergence clubs emerge, while overall convergence is rejected. Convergence was faster before 2012 and weakened afterward. A single income threshold and two structural breaks (2005 and 2012) mark shifts in growth dynamics. Spatial models reveal that neighboring regions affect each other’s growth, indicating that regional development in Europe depends on both local conditions and interactions across regions. Full article

Introduction: Stenotrophomonas maltophilia (S. maltophilia) has emerged as an important opportunistic pathogen. It is resistant to most available antibiotics due to its intrinsic resistance, leaving only some antibacterial agents as possible therapeutic options, which is further complicated by acquired mechanisms of antimicrobial resistance. This study aimed to provide a comprehensive genomic characterization of clinical S. maltophilia complex (Smc) isolates, focusing on molecular characterization of its resistance and virulence, since studies tackling this are scarce in Oman. Methods: This study is a prospective cross-sectional study, in which a total of 21 clinical isolates of Smc were collected from different clinical samples and further characterized using Whole Genome Sequencing. Results: Besides S. maltophilia, the isolates included S. hibiscicola, S. pavanii, and S. muris for the first time in Oman. All isolates were found to be susceptible to cefiderocol, levofloxacin, and minocycline. Sequence types (STs) were diverse among the isolates, with more than half of the isolates showing new STs with novel alleles. Additionally, blaOXA-2, sul1, and the recently described aac(6′)-Iap and aph(9)-Ic were detected among the isolates. Moreover, virulence-associated genes (smf-1, pilT, pilQ, gpmA, rmlA, spgM, stmPr1, plcN, clpP, and katE) were highly conserved across all isolates. Mobile genetic elements were detected in most of the isolates (76.20%). Conclusions: The collected isolates showed high ST diversity and showed no specific pattern in terms of antibiotic susceptibility and resistance genes. More studies are needed to establish relationships between the different members of the Smc and the different molecular resistome and virulome. Full article

Cronobacter spp. are opportunistic foodborne pathogens that can cause neonatal meningitis, necrotizing enterocolitis, and sepsis. This study conducted a systematic contamination survey and whole-genome epidemiological analysis of 562 low-water-activity food samples in Hunan Province of China. The results showed an overall Cronobacter spp. detection rate of 41.99% (236/562), with spices exhibiting the highest contamination rate (60.06%), and with high-level contamination samples (>110 MPN/g) concentrated in this category. The 236 isolates comprised 6 species, 120 sequence types, and 39 clonal complexes, with C. sakazakii being the most frequently isolated species (64.83%) and high-risk clones ST4, ST1, ST148, and ST64 prevailing. Multiple virulence genes (TraJ, fur, rcsAB, rpoS) and antimicrobial resistance genes (qnrS1, blaTEM-1, blaCTX-M-55, blaLAP-2, aac(3)-IId, aadA2, tet(A), floR, mcr-9.1, sul2) were detected. Core genome multilocus sequence typing (cgMLST) identified two clustering patterns: Cluster C, whose genetic clustering was consistent with transmission associated with potential common upstream raw materials across different brands and provinces, and Cluster G, whose clustering suggested potential persistent colonization in the production environment across multiple batches of the same brand. This study elucidates the contamination characteristics of Cronobacter spp. in low-water-activity foods from Hunan Province and provides a basis for WGS-based active surveillance and supply chain traceability. Full article

Antibiotic resistance genes (ARGs) are increasingly recognized as a concern in drinking water, yet the factors influencing their persistence from raw to finished water in drinking water treatment plants remain poorly understood. This study investigated the occurrence, removal, and potential factors associated with the persistence of ARGs (sul1, sul2, and tetG) in a full-scale rapid sand filtration drinking water treatment system with intermediate and post-chlorination. ARGs were detected in raw water at a median total concentration of 10⁶ copies/L and remained detectable in finished water at 10⁴ copies/L. Relative ARG abundance increased after treatment despite substantial absolute reductions (2.1–3.6 log). Intermediate chlorination achieved the greatest ARG log reduction value (0.53–2.4 log), likely due to higher chlorine dose and lower pH favoring HOCl formation. By contrast, post-chlorination at higher pH provided limited additional removal, possibly due to predominance of less reactive OCl⁻ and survival of chlorine-tolerant bacteria. Multivariate analyses showed a shift from particle-bound ARGs in raw water to dissolved organic matter (DOM) and fine-particle-associated fractions along the treatment train. These findings suggest that reducing fine particles and DOM, together with optimized disinfection, may help lower ARG-associated risk in finished water. Full article

This study characterized eleven grape pomace varieties from São Paulo and Rio Grande do Sul (Brazil) in terms of proximate composition, total phenolic content, and the total and bioaccessible fractions of inorganic elements and phenolic compounds. On a dry basis, ash, protein, lipid, and carbohydrate contents ranged from 1.4–2.9%, 6.4–13.5%, 8.6–14.7%, and 72.1–83.6%, respectively. Total phenolic content ranged from 567 to 1843 mg GAE/100 g. The contents of essential elements (Ca, Fe, Zn, Cu, Mg, Mn, P, Na, and K) and trace elements (Al, Co, As, Se, Mo, Cd, Sb, Ba, Hg, and Pb) showed wide variation among the varieties studied. Regarding bioaccessibility, low values were observed for Fe, Zn, and Ca, while significant percentages were detected for Mg (27–30%), Mn (1–14%), P (16–26%), Cu (5.5–13%), Co (29–72%), Al (2–13%), and Ba (ND-9%), as well as levels of bioaccessible phenolic compounds (7–19%). The grape pomaces evaluated in this study presented variable levels of total phenolic compounds and minerals, although the bioaccessible fractions varied among the analyzed elements and compounds. These findings contribute to the characterization of Brazilian grape pomaces and indicate their potential applicability as value-added agro-industrial by-products in food formulations, while highlighting the importance of considering bioaccessibility when assessing their nutritional relevance. Full article

The beef production chain plays a strategic role in Brazilian and global agri-food systems and faces growing demands for sustainability, transparency, and traceability. Building on official Animal Transit Guide (GTA) records from Mato Grosso do Sul, Brazil, this study examines whether a parsimonious agent-based model (ABM) can generate the main structural signatures of an observed cattle-trade network. The empirical benchmark is a directed and weighted network with 20,827 nodes and 258,120 weighted edges. The ABM represents producers and slaughterhouses as spatial agents connected by trade decisions based on three mechanisms: destination attractiveness, defined as the accumulated pull of a slaughterhouse based on previous simulated throughput; geographic distance, representing spatial friction; and relational memory, representing the tendency to repeat previous commercial ties. Producer choice is formalized through a local utility function that combines attractiveness, distance penalty, and relational memory under capacity, sourcing-radius, and saturation constraints. In the simulated scenarios, the top-five slaughterhouses accounted for 38.49 ± 2.56% of throughput at reduced scale and 14.40 ± 0.65% at intermediate scale, while weighted mean distances were 11.94 ± 0.56 and 9.07 ± 0.39 model units, respectively. The model reproduced, in structural and mechanistic terms, the emergence of dominant hubs, the concentration of flows, and the bounded increase in transaction distance with connectivity around the empirical threshold of kw ≈ 256. Sensitivity analyses indicated that attractiveness increases concentration, distance localizes transactions, and relational memory can stabilize repeated ties when recurrent activation is represented. Rather than reconstructing individual transactions, estimating policy impacts, or identifying a unique parameter vector, the model provides a generative explanation of how local trade rules can produce macro-level network patterns consistent with the observed cattle-trade regime. These findings support future prospective analyses of cattle governance, traceability, and sustainability within the broader context of Livestock 4.0. Full article

This study presents an updated Hybrid Hydrological Forecasting System (HHFS) for streamflow prediction at the Santa Branca outlet, located in the upper Paraíba do Sul River Basin in southeastern Brazil, aiming to support hydropower-oriented water resources management. This paper is explicitly framed as a companion paper which introduced the original HHFS framework and demonstrated the feasibility of combining deterministic and probabilistic machine-learning approaches for monthly streamflow forecasting. Building upon that foundation, the present study develops and validates a substantially enhanced and operationally oriented version of the system. The upgraded HHFS replaces the original BR-DWGD forcing strategy—a Brazilian gridded meteorological dataset useful for research applications but not routinely updated for sustained operations—with ERA5, the fifth-generation global atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), which provides temporally consistent and operationally updated meteorological fields. This transition renders the framework fully operational while preserving the original dual-stage architecture, composed of a deterministic forecasting module (GA₁) and a hydro-adaptive uncertainty module (GA₂). In addition, the study introduces a daily short-term forecasting extension using a single multi-output XGBoost 2.1.1 model to predict streamflow from D+1 to D+10. Predictive uncertainty is quantified using split conformal prediction, a distribution-free uncertainty method that provides valid prediction intervals with empirical coverage guarantees. Coverage represents the proportion of observed values falling within the prediction intervals and is used here as a reliability metric. For the monthly product, the ERA5-based methodology maintained and slightly improved deterministic skill relative to the original BR-DWGD benchmark, with independent-test NSE increasing to 0.798, KGE to 0.878, and RMSE decreasing to 18.778 m³/s. The probabilistic component preserved a high hit rate and similar relative width, although coverage declined modestly to 0.838, indicating slight undercoverage relative to the previous reliability target. For the daily forecasts, predictive skill decreased progressively with lead time, from NSE = 0.881 at D+1 to 0.394 at D+10, accompanied by coherent widening of the uncertainty intervals. Taken together, these results demonstrate that ERA5 is a robust and operationally practical forcing source for the HHFS, preserving monthly forecasting skill while enabling a promising multi-day extension for anticipatory streamflow prediction across multiple temporal scales. Full article

Soil microbiomes play a central role in nutrient cycling and ecosystem stability in forestry ecosystems. Here, we present an exploratory analysis of rhizosphere bacterial communities from eucalyptus plantations in two ecologically distinct Brazilian regions. Using 16S rRNA amplicon sequencing followed by ASV inference and phylogenetic reconstruction, we observed distinct taxonomic composition pattern between samples. Dominant phyla across both samples were Actinomycetota, Pseudomonadota, Acidobacteriota, and Bacillota, with Actinomycetota more abundant in TL (44.0%) than in ES (26.5%), and Acidobacteriota and Verrucomicrobiota more represented in ES. The family Streptomycetaceae and the genus Streptantibioticus were strongly enriched in ES (19.6% and 18.6%, respectively), whereas Solirubrobacteraceae, Pseudonocardiaceae, and Nocardiaceae were preferentially associated with TL. The Eldorado do Sul (ES) sample was characterized by higher observed richness and phylogenetic diversity, whereas Três Lagoas (TL) sample displayed relatively greater community evenness. Beta diversity metrics were consistent with high compositional dissimilarity between samples, with a limited fraction of ASVs forming a shared core microbiome. Despite this taxonomic variation, PICRUSt2-based predictions suggested a broadly conserved set of dominant metabolic pathways across samples. Predicted MetaCyc pathways were largely associated with central carbon metabolism, amino acid biosynthesis, and energy production. At the same time, variation in predicted metabolic profiles was observed between samples. The ES sample showed higher relative representation of pathways related to chitin degradation, purine metabolism, and nitrifier denitrification, whereas the TL sample displayed higher relative representation of pathways associated with alternative TCA variants, glyoxylate metabolism, menaquinol biosynthesis, and aromatic compound degradation. Overall, this exploratory analysis suggests that substantial taxonomic variation may coexist with a relatively conserved predicted functional framework across contrasting eucalyptus plantation systems. These observations should be interpreted as hypothesis-generating and highlight the need for future studies incorporating replicated sampling and direct functional measurements. Full article

This study investigates whether countries converge toward common long-run paths in renewable energy consumption and examines the implications for global fuel transition dynamics. Using a balanced panel of 108 countries over the period 1990–2022, we implement an integrated econometric framework that combines stochastic convergence tests, β- and σ-convergence analysis, the Phillips–Sul club convergence methodology, ordered logit modelling, and heterogeneous panel causality tests. The results reject global stochastic convergence, indicating that countries do not share a common transition trajectory. However, evidence of β- and σ-convergence suggests the presence of partial and bounded catch-up dynamics. The Phillips–Sul approach identifies four distinct convergence regimes, implying multiple steady-state equilibria in global energy systems. Structural analysis shows that income and governance quality increase the probability of belonging to higher-renewable-energy regimes, while carbon intensity constrains upward transitions. Regime-specific causality results further reveal that the drivers of renewable energy dynamics differ across structural contexts. Overall, the findings demonstrate that global energy transitions are characterized by persistent heterogeneity and regime-dependent adjustment processes rather than uniform convergence. This study contributes by integrating convergence analysis with structural modelling and regime-based interpretation, offering a more comprehensive framework for understanding differentiated decarbonization pathways. The results carry important policy implications, highlighting that effective energy transition strategies must be tailored to regime-specific conditions rather than relying on uniform policy approaches. Full article

Vento Norte (VNOR; Portuguese for North Wind) is a downslope windstorm that develops over modest terrain in the central region of Rio Grande do Sul (RS), southern Brazil. The regional topography is characterized by an abrupt terrain transition with elevation differences of approximately 400–500 m. This atmospheric flow typically occurs during the cold season and is characterized by strong wind gusts, rapid warming, and drying of the planetary boundary layer (PBL). In this study, the performance of different PBL parameterization schemes in the Weather Research and Forecasting (WRF) model is assessed for simulating a VNOR event that occurred between 19 and 20 August 2021 in Santa Maria (SMA), RS. Five high-resolution numerical simulations were conducted using the Yonsei University (YSU), Asymmetric Convective Model version 2 (ACM2), Mellor–Yamada–Nakanishi–Niino level 2.5 (MYNN2.5), Quasi-Normal Scale Elimination (QNSE), and Three-Dimensional Turbulent Kinetic Energy (3DTKE) PBL schemes. Model results were evaluated against observations from a flux tower providing turbulence measurements, twice-daily radiosoundings, and hourly surface meteorological observations. Statistical metrics indicate that the MYNN2.5 scheme provided the most accurate representation of the nighttime stable boundary layer preceding the VNOR, as well as its onset and subsequent evolution. Although this study analyzes a single VNOR event and the results may be case-dependent, the overall performance of the MYNN2.5 scheme suggests that it is a promising option for the operational forecasting of VNOR events. These findings provide new insights into the ability of different PBL schemes to reproduce the mean boundary-layer structure and turbulence characteristics associated with downslope windstorms over modest terrain, contributing to the understanding of these events. Full article

Despite the growing relevance of Agriculture 4.0 technologies for enhancing productivity, decision-making, and sustainability in agri-food systems, their adoption remains uneven in developing-country contexts. This study aims to analyze the perceived severity and co-occurrence structure of barriers to Agriculture 4.0 adoption in the agri-food system of Rio Grande do Sul (RS), Brazil, using an exploratory quantitative design grounded in a barrier co-occurrence perspective rather than a causal or actor-centered network interpretation. An online survey conducted in 2024 with farmers in RS evaluated 25 literature-validated barriers spanning technological, economic, political, social, and environmental dimensions. The analysis combined a Barrier Severity Index (BSI), reliability testing, Principal Component Analysis (PCA), K-means clustering, ANOVA by farm size, and proximity-based co-occurrence networks constructed from highly rated barriers. The results show that economic barriers remain the most severe overall, particularly the lack of affordable solutions, high maintenance costs, and limited infrastructure. At the same time, farm-size-stratified networks reveal distinct association structures: small farms display a more segmented pattern linking affordability and technical access to institutional and capability constraints; medium farms show the most globally integrated co-occurrence structure; and large farms exhibit a dense but more differentiated configuration combining cost, interoperability, skills, and governance-related barriers. These findings are interpreted descriptively, as the networks capture patterns of co-reporting rather than causal interdependence. The study contributes a network-analytic representation of perceived barrier configurations and highlights the need for scale-sensitive policy mixes that address bundles of constraints rather than isolated obstacles. Full article

In southern Brazil, a large proportion of farmers maintain their fields under fallow conditions during the transition period between summer and winter crops. During this interval, mechanical practices such as chiseling or the introduction of cover crop species may contribute to improving soil management and conservation in no-tillage systems. Therefore, this study aimed to investigate the effects of mechanical soil chiseling and production system intensification on soil physical–hydric properties and soybean performance. The experiment was conducted in São José do Ouro, Rio Grande do Sul, Brazil, from September 2023 to April 2025. The experimental design consisted of three factors: soil management (spring 2023 chiseling, autumn 2024 chiseling, and a no-till control), post-maize cover (millet and fallow conditions), and winter cover crops (black oat, white oat, vetch, and radish) grown either as monocultures or in mixtures. A randomized block design with split plots and three replicates was used. The evaluated variables included dry biomass of winter cover crops, soil bulk density, total porosity, microporosity, macroporosity, soil water content at field capacity, soil penetration resistance, plant gas exchange, leaf area index, thousand-grain weight, and soybean grain yield. The results indicated that soil chiseling altered soil physical properties by reducing soil bulk density, penetration resistance, microporosity, and field capacity, while increasing total porosity and macroporosity. Soil chiseling promoted short-term increases in thousand-grain weight and soybean grain yield, with no persistent effects after 20 months. Production system intensification, through the use of cover crops and millet, did not affect grain yield but increased stomatal conductance and soybean leaf area index. Therefore, occasional tillage in high-clay subtropical Oxisols should be strategically applied and associated with long-term conservation agriculture practices to sustain improvements in soil physical quality. Full article

The increasing occurrence of pesticides in aquatic environments has raised concern due to their potential impact on human health and ecosystems. In this context, the development of sensitive, reliable, and environmentally sustainable analytical methods is essential for monitoring these contaminants. Therefore, the aim of this study was to develop and validate a miniaturized dispersive solid-phase extraction (DµSPE) method for the determination of current-use multiclass pesticides in water samples using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Initially, a simple and rapid sample preparation procedure was developed, in which different experimental variables were evaluated to obtain suitable extraction efficiency. The validated method has a quantification limit of 0.01 µg L⁻¹ and was applied to the determination of pesticides in surface water from different regions in Rio Grande do Sul State, Brazil. In addition, the environmental sustainability of the method was evaluated using the AGREEprep tool, allowing a quantitative and visual assessment of its compliance with the principles of Green Analytical Chemistry. The results demonstrated that the proposed method provides adequate analytical performance for the determination of 28 compounds in water matrices while offering a simple sample preparation procedure with reduced solvent consumption and waste generation. Full article

The expansion of floriculture into climatic transition regions requires precise tools to mitigate thermo-hydric risks. Gladiolus (Gladiolus × grandiflorus Hort.) is sensitive to temperature extremes, requiring strategic planning of planting schedules and heat stress mitigation. The objective in this study was to evaluate the PhenoGlad model for its ability to simulate developmental stages and heat stress damage in eight gladiolus cultivars across multiple environments and planting dates in the state of Mato Grosso do Sul, Midwest Brazil. Field experiments were conducted in five municipalities during the autumn, winter, and spring growing seasons. Model performance was evaluated by starting the simulation at planting or at emergence, using the statistics root mean square error (RMSE), bias index (BIAS), Willmott’s index of agreement (d), and the correlation coefficient (r). Simulations starting at emergence reduced the error in predicting the timing of developmental stages (from 5.34 to 3.16 days). For leaf development, the model was highly accurate, with an RMSE lower than one leaf for different planting dates, sites, and cultivars. Furthermore, the model accurately predicted extreme heat stress events (daily maximum temperatures > 34 °C associated with low relative humidity), which resulted in severe damage and inhibition of reproductive development in the field. In conclusion, the PhenoGlad model is a robust decision-support system and agricultural engineering tool for production scheduling and climate loss mitigation in tropical floriculture. Full article

During the COVID-19 pandemic carbapenem-resistant Acinetobacter baumannii (CRAB) was found to be the major pathogen associated with ventilator-associated pneumonia in mechanically ventilated patients. This prompted us to analyze the post-pandemic mechanisms of carbapenem resistance, antibiotic resistance trends, and molecular epidemiology of CRAB in Croatia. In total, 94 CRAB isolates from two hospital centers, including outpatient settings, were investigated. Antimicrobial susceptibility testing was performed by broth microdilution. PCR was used to detect genes encoding carbapenemases of group A, B and D and extended-spectrum β-lactamases (ESBL). Randomly selected isolates were subjected to whole resistome analysis by Inter-array CarbaResist Kit and whole-genome sequencing (WGS). Phylogenetic tree and sequence types (STs) were retrieved from WGS. Plasmid incompatibility groups were determined by PCR-based replicon typing (PBRT). All isolates were extensively drug resistant (XDR), showing resistance to ceftazidime, cefepime, piperacillin–tazobactam, imipenem, meropenem, gentamicin, amikacin and ciprofloxacin, and 13% (n = 12) were also resistant to colistin. The Hodge and CIM test exhibited poor sensitivity with only 32 and 30% of isolates being identified as carbapenemase producers, respectively. PCR identified bla_OXA-23 as the dominant carbapenemase gene in both hospitals, found in 71% of the isolates (67/94). In an outpatient setting, bla_OXA-24/40 was dominant. bla_OXA-23 and bla_OXA-72 were the only allelic variants. The Inter-array CarbaResist Kit and whole-genome sequencing (WGS) identified a variety of aminoglycoside (armA, ant(3″)-IIa, aph(3″)-Ib, aph(6)-Id) and sulphonamide resistance (sul1 and sul2) genes. The representative bla_OXA-23-positive isolates belonged to ST2, while bla_OXA-72-positive isolates were allocated to ST492. These data show that there are different populations of XDR A. baumannii between hospital and outpatients. Full article