Search Results (12,270)

Sclerotinia spp. are globally distributed, devastating plant pathogens with a broad host range, including lettuce, on which they cause lettuce drop disease. To investigate the geographical distribution of lettuce drop incidence and the population structure of Sclerotinia sclerotiorum and S. minor in Serbia, 27 commercial lettuce fields across 12 administrative districts were surveyed. Sclerotinia spp. were confirmed at 10 localities, with S. sclerotiorum occurring more frequently. Co-occurrence of both species within the same field was recorded at only one location. Clear phenotypic and physiological differences were found between Sclerotinia species, as well as among isolates within each species. The two species differed in colony appearance, sclerotia production, virulence, growth rate, oxalic acid production, and tolerance to elevated osmotic pressure. Haplotype analysis of S. minor revealed the existence of 9 haplotypes arranged in a star-shaped network. These findings highlight the importance of considering both inter- and intraspecific variability of Sclerotinia species when evaluating their impact on crops, improving our understanding of Sclerotinia populations in lettuce, and supporting the development of effective management strategies. Full article

Urban expansion and its driving factors are frequently analyzed within administrative regions to inform regional urban planning, yet such analyses often fall short at the natural basin scale (referring to the spatial extent defined by hydrological drainage boundaries) due to the scarcity of statistical data. Geographic and socio-economic spatial data can offer more detailed information across various research scales compared to traditional data (such as administrative statistical data, survey-based data, etc.), providing a potential solution to this limitation. Thus, this study took the Indus Basin as an example to reveal its urban expansion patterns and driving mechanism based on natural–economic–social time-series (2000–2020) spatial data, landscape expansion index, and geographical detector model (GDM). Future urban expansion distribution under different scenarios was also projected using Cellular Automata and Markov model (CA-Markov). The results indicated the following: (1) The Indus River Basin experienced rapid urban expansion during 2000–2020 dominated by edge-expansion, with urban expansion intensity showing a continuous increase. (2) Between 2000 and 2010 as well as 2010 and 2020, the dominant factor influencing urban expansion shifted from altitude to population (Pop), while the strongest interacting factors shifted from fine particulate matter (PM_2.5) and altitude to Gross Domestic Product (GDP) and Pop. (3) Future urban expansion probably occupies substantial mountainous area under the normal scenario, while the expansion region shifts towards the central plains to protect more ecological zones under a sustainable development scenario. Findings in this study would deepen the understanding of urban expansion characteristics of the Indus Basin and benefit its future urban planning. Full article

In modern financial markets, decision-makers increasingly rely on quantitative methods to navigate complex trade-offs among multiple, often conflicting objectives. This paper addresses constrained multi-objective optimization (MOO) with an application to portfolio optimization for minimizing risk and maximizing return. To this end, and to address existing gaps, we propose a novel reinforcement learning (RL)-guided non-dominated sorting genetic algorithm II (NSGA-II) enhanced with gray relational coefficients (GRC), termed RL-NSGA-II-GRC, which combines an RL agent controller and GRC-based selection to improve the convergence and diversity of the Pareto-optimal fronts. The agent adapts key evolutionary parameters online using population-level metrics of hypervolume, feasibility, and diversity, while the GRC-enhanced tournament operator ranks parents via a unified score simultaneously considering dominance rank, crowding distance, and geometric proximity to ideal reference. We evaluate the framework on the Kursawe and CONSTR benchmark problems and on a NASDAQ portfolio optimization application. On the benchmarks, RL-NSGA-II-GRC achieves convergence metric improvements of about 5.8% and 4.4% over the original NSGA-II, while preserving a well-distributed set of non-dominated solutions. In the portfolio application, the method produces a smooth and densely populated efficient frontier that supports the identification of the maximum Sharpe ratio portfolio (with annualized Sharpe ratio = 1.92), as well as utility-optimal portfolios for different risk-aversion levels. The main contributions of this work are three-fold: (1) we propose an RL-NSGA-II-GRC method that integrates an RL agent into the evolutionary framework to adaptively control key parameters using generational feedback; (2) we design a GRC-enhanced binary tournament selection operator that provides a comprehensive performance indicator to efficiently guide the search toward the Pareto-optimal front; (3) we demonstrate, on benchmark MOO problems and a NASDAQ portfolio case study, that the proposed method delivers improved convergence and well-populated efficient frontiers that support actionable investment insights. Full article

Background: Axillary lymph node (ALN) metastasis is a critical prognostic determinant in breast cancer (BC) that informs surgical management. However, surgically clearing the axilla carries morbidity, so less invasive methods of risk-stratifying patients are needed. ALN fine needle aspiration (FNA) is currently used to detect BC metastases, but these samples also contain immune cells. Methods: Cells obtained via FNA from BC-patient-derived ALNs were analysed using flow cytometry. Results: FNA acquires sufficient leukocytes for comprehensive immunophenotyping of reactive, patient-derived ALNs. All CD4⁺ and CD8⁺ T-cell subsets (naïve, terminal effector, central memory, and effector memory) and rarer (<2%) natural killer (NK) and plasmacytoid dendritic cell (pDC) populations are represented. Importantly, the immune-cell profile of one reactive ALN appears to reflect the immune status of the patient’s axilla. Furthermore, FNA captures immune differences between patients with ≤1 or ≥2 metastatic ALNs. Increased numbers of naïve CD4⁺ T cells, but fewer terminal effector, central memory, and effector memory subpopulations, were obtained from patients with ≥2 metastatic ALNs. Moreover, despite their sparse distribution pattern on whole-section immunohistochemistry (WSI), FNA revealed that CD56⁺ NK cell activation receptors were decreased in patients with ≥2 metastatic ALNs. Finally, FNA captured a decrease in pDCs in patients with ≤1 metastatic ALNs, despite their clustered distribution pattern on WSI. Conclusions: FNA is not only feasible for sampling leukocytes from reactive, patient-derived ALNs, but also identifies immune-cell profiles that reflect axillary tumour burden in BC. Thus, this technique could be used to risk-stratify BC patients in the future. Full article

To address the deficiencies in global search capability and population diversity decline of the black-winged kite algorithm (BKA), this paper proposes an enhanced black-winged kite algorithm integrating opposition-based learning and quasi-Newton strategy (OQBKA). The algorithm introduces a mirror imaging strategy based on convex lens imaging (MOBL) during the migration phase to enhance the population’s spatial distribution and assist individuals in escaping local optima. In later iterations, it incorporates the quasi-Newton method to enhance local optimization precision and convergence performance. Ablation studies on the CEC2017 benchmark set confirm the strong complementarity between the two integrated strategies, with OQBKA achieving an average ranking of 1.34 across all 29 test functions. Comparative experiments on the CEC2022 benchmark suite further verify its superior exploration–exploitation balance and optimization accuracy: under 10- and 20-dimensional settings, OQBKA attains the best average rankings of 2.5 and 2.17 across all 12 test functions, outperforming ten state-of-the-art metaheuristic algorithms. Moreover, evaluations on three constrained engineering design problems, including step-cone pulley optimization, corrugated bulkhead design, and reactor network design, demonstrate the practicality and robustness of the proposed approach in generating feasible solutions under complex constraints. Full article

Investigating the prevalence and molecular genetic characteristics of Anaplasma ovis, Theileria spp., Anaplasma phagocytophilum, and hemotropic Mycoplasma infections in sheep populations across different regions of Gansu Province is of significant importance for the prevention and control of these pathogens. A total of 1523 sheep blood samples were collected from 19 counties (districts) in Gansu Province. Pathogen screening was conducted using PCR-based molecular detection techniques, followed by sequencing and phylogenetic analysis of specific genes (e.g., Msp4, 18S rRNA) from selected positive samples. Blood-borne pathogens infections in Gansu Province were widespread but unevenly distributed geographically. Theileria spp. and Anaplasma ovis were the dominant pathogens, with overall infection rates of approximately 16.7% and 9.6%, respectively. The highest Anaplasma ovis infection rate (82.5%) was observed in the Gannan region, where co-infections were common (24/97). An exceptionally high Theileria spp. infection rate (87.5%) was detected in the Zagana area. No pathogens were detected in Wuwei, Jingyuan, Huining, Jingtai, Qinghuan, or Maqu. Phylogenetic analysis revealed that the Msp4 gene sequences of Anaplasma ovis isolates from Gansu shared 99.48% homology with strains from Europe, Asia, and Africa. Anaplasma phagocytophilum isolates also showed high homology (99.53–99.84%) with multiple global strains. Seasonal data indicated significantly higher Theileria spp. infection rates in spring (23–34%) compared to other seasons (approximately 12%). Gansu Province is an endemic area for multiple blood-borne pathogens, with distinct regional clustering and seasonality in prevalence. The high conservation of pathogen gene sequences suggests genetic stability. This study provides essential epidemiological baseline data and a scientific foundation for targeted prevention and control of blood-borne pathogen diseases in sheep in Gansu Province. Full article

In a worldwide context marked by increasing attention to financial literacy as a factor of financial inclusion, Morocco take part of this dynamic, seeking to improve the financial skills of its population. This article does not measure financial literacy directly but aims to explore the structural conditions that enable its diffusion in Morocco, using macroeconomic indicators such as income, employability, and education, along with financial infrastructure. Adopting a mixed methodology, this study combines both qualitative and quantitative analysis of the national context, including an overview of public policies, socioeconomic characteristics, and financial literacy initiatives, with a quantitative analysis based on an Autoregressive Distributed Lag (ARDL) econometric model. Bank branch density is employed as an indirect proxy for financial infrastructure, reflecting access to formal financial services in the absence of time-series literacy data. The results show that gross national income (GNI) per capita, the labor forces, and elementary school enrolment rates influence banking density, though without producing statistically significant effects in the long term. In the short term, only GNI has a temporary but not very robust impact. These results highlight the limitations of macroeconomic indicators alone in explaining financial literacy diffusion and underscore the potential role of structural factors such as digital innovation, governance, or inclusion of youth and female indicators. Full article

Athamanta L. is a small genus of the Apiaceae family, comprising only sixteen species and subspecies, which are distributed in the Canary Islands, Central Europe, and the Mediterranean basin. Background/Objectives: Since the time of Dioscurides, the species of this genus have been reported to have had several ethnopharmacological activities, and some of them are also used currently. Athamanta sicula L., growing in Italy, Tunisia, Algeria, and Morocco, is the only species of this genus present in Sicily. To further explore the phytochemical profile and biological properties of this species, the present study focused on the essential oil (EO) extracted from the aerial parts of wild A. sicula populations collected in central Sicily. Methods: The chemical composition of the EO, obtained by hydrodistillation, was determined by GC–MS analysis. The presence of myristicin was confirmed by isolation and by ¹H-NMR spectroscopic characterization. Results: The EO and its main constituents have been tested for possible antimicrobial properties against several bacterial strains, showing MIC values in the of 15–30 mg/mL range, and the mechanism of action was further investigated, revealing membrane-targeting effects consistent with outer membrane permeabilization. In addition, antibiofilm activity (with up to ~80% inhibition of biofilm formation at sub-MICs), antioxidant potential (demonstrating dose-dependent radical scavenging activity), and biocompatibility with eukaryotic cells were assessed to provide a comprehensive pharmacological profile of A. sicula EO. Specifically, the most abundant constituent was myristicin (62.2%), the principal representative of the phenylpropanoid class (64.4%). Hydrocarbon monoterpenes represented the second class of the EO (27.4%), with β-phellandrene (12.2%) as the main compound. Conclusions: Myristicin emerged as the key contributor to the antimicrobial and antibiofilm activity of the EO. The obtained results highlight the relevance of A. sicula EO as a myristicin-rich essential oil with notable in vitro biological activity. Full article

Understanding the spatial structure of large mammals is critical for conservation planning, especially under increasing habitat fragmentation. This study applies an integrated spatial analysis combining the DBSCAN density-based clustering algorithm and the α-hull method to delineate non-convex geographic ranges of the maned wolf (Chrysocyon brachyurus) across South America. Using 454 occurrence records filtered for ecological reliability, we identified 11 geographically isolated α-populations distributed across five countries and multiple biomes, including the Cerrado, Chaco, and Atlantic Forest. The sensitivity analysis of the α parameter demonstrated that values below 2 failed to generate viable polygons, while α = 2 provided the best balance between geometric detail and ecological plausibility. Our results reveal a highly fragmented distribution, with α-populations varying in area from 43,077 km² to 566,154.7 km² and separated by distances up to 994.755 km. Smaller and peripheral α-populations are likely more vulnerable to stochastic processes, genetic drift, and inbreeding, while larger clusters remain functionally isolated due to anthropogenic barriers. We propose the concept of ‘α-population’ as an operational unit to describe geographically and functionally isolated groups identified through combined spatial clustering and non-convex hull analysis. This approach offers a reproducible and biologically meaningful framework for refining range estimates, identifying conservation units, and guiding targeted management actions. Overall, integrating α-hulls with density-based clustering improves our understanding of the species’ fragmented spatial structure and supports evidence-based conservation strategies aimed at maintaining habitat connectivity and long-term viability of C. brachyurus populations. Full article

With the continuous growth of the global population, cities worldwide face the challenge of limited surface land area, making the utilization of underground space increasingly important. The structural stability of underground tunnels is a critical component of underground space safety, influenced by the distribution of the surrounding composite strata and hydrogeological environment. To better analyze the structural stability of underground tunnels, this study proposes a method for estimating the distribution of composite strata that considers the surrounding hydrogeological conditions. The method uses a hydrogeological analysis of the tunnel area to determine the spatial estimation range and unit scale to meet the actual project requirements and then uses the geostatistical kriging method to obtain a distance-weighted interpolation algorithm for the impact area. First, the spatial data are used to obtain the statistical characteristics. Second, the statistical data are interpolated, multifractal theory is used to compensate for the kriging method of sliding weighted average defects, and the local singularity of the regionalized variables is measured. Finally, the mean results of 100 simulations are compared with the empirical results for the tunnel. The interpolation results reveal that this method can be used to quickly obtain good interpolation results. Full article

Verticillium wilt (VW) of cotton caused by the soilborne pathogen Verticillium dahliae is a major disease across cotton production worldwide. The disease can result in yield reductions up to 80% on some occasions. V. dahliae is an asexual fungus and belongs to a relatively small Verticillium genus in the Ascomycota, though both of the mating type idiomorphs are present within some populations. The diversity of V. dahliae is widely associated with vegetative compatibility groups (VCGs), of which six different VCGs are recognised. Of these, isolates belonging to VCGs 1, 2, and 4 are globally distributed and associated with a broad host range, including cotton. Approximately 400 plant species have been recorded as hosts of V. dahliae. The pathogenicity and virulence of V. dahliae in many cases are correlated with VCG designations and hosts of origin. Disease management of VW of cotton still relies on accurate, rapid detection and quantification of V. dahliae using both conventional and molecular approaches. The use of resistant cultivars is the most effective and economical control strategy; however, no cultivars confer complete resistance to the disease. Control strategies including cultural, biological, chemical, and induced-resistance approaches have indicated certain degrees of success in minimising disease damage and diminishing the build-up of pathogen inoculum. In this review, we discuss insights into the VW disease of cotton, and the associated pathogen and current control approaches, as well as future research perspectives. Full article

Purpose: Aeromonas species are emerging pathogens associated with a range of human infections, particularly gastroenteritis in the paediatric population. However, data on their molecular characteristics in Latvia and the wider Baltic region remain limited. This study aimed to describe the distribution and genetic diversity of Aeromonas isolates from paediatric patients in Latvia using multilocus sequence typing (MLST). Methods: Stool samples were collected from children aged 0–18 years who presented with gastroenteritis at the Children’s Clinical University Hospital between 2020 and 2021. A subset of 30 non-duplicate Aeromonas isolates was randomly selected for molecular characterisation and analysed by MLST. Sequence type data were deposited in the PubMLST.org database. Results: MLST analysis revealed substantial genetic diversity, with 25 novel sequence types (STs) being identified and three isolates matching previously reported STs. Two novel STs were detected in duplicate, with an epidemiological link being confirmed in one case. The local distribution of Aeromonas species and STs differed from global PubMLST datasets, suggesting a distinct local population of Aeromonas strains in Latvian paediatric patients. Conclusions: This study provides the first MLST-based description of paediatric Aeromonas isolates in Latvia and establishes a regional baseline for future comparative and epidemiological research. Although limited by a small sample size, the findings contribute to the molecular characterisation of Aeromonas spp. in the Baltic region and support the value of continued surveillance rather than direct public-health inference at this stage. Full article

The supply and demand levels of urban health resources directly impact residents’ quality of life and health. This study employs the Multi-Mode Three-Step Floating Catchment Area (MM3SFCA) method to assess the supply and demand levels of health resources in the main urban area of Harbin under different transportation modes. To address the gap in previous studies that did not consider the impact of the spatial distribution of health resources at varying distances on residents, K-means clustering analysis was applied. The results indicate a significant imbalance between supply and demand for health resources in Harbin’s main urban area. Specifically, approximately 86% of the population met the supply-and-demand standards for health care facilities. However, only 29% and 41% of the population met the supply and demand standards for physical activity facilities and leisure wellness facilities, respectively. From a transportation perspective, the findings reveal that in areas with balanced or abundant supply and demand, residents primarily rely on driving and public transportation. This suggests that health resources are still concentrated in areas far from residential zones, thereby affecting accessibility to resources for some residents. Full article

Background/Objectives: Healthy ageing, focused on maintaining daily autonomy and cognitive function despite chronic comorbidities, poses a challenge for public health systems, especially for those aged ≥80, given the expected increase in this population. Promoting a healthy lifestyle in this group is essential to achieving this goal, with primary care services playing a key role in this effort. Therefore, our objective was to profile the participants based on these characteristics. Methods: The study included 222 non-institutionalized, dementia-free individuals (mean age 84.58 ± 3.72 years, 56.3% women) recruited from a primary healthcare service. Data were collected from medical records and interviews, including the cognitive Pfeiffer test, the functional Barthel index (BI), and ad hoc questionnaires (for lifestyle variables). Latent profiling analysis (LPA) was used to classify the participants. Results: The participants reported social support (97.7%), low-risk alcohol consumption (94.6%), adherence to the Mediterranean diet (85.1%), physical activity (74.8%), and never smoking (72.5%). Hypertension (86.5%), cataracts (74.3%), and osteoarticular diseases (68.5%) were the most frequent chronic conditions. Women showed a significantly different distribution of certain variables and a higher number of comorbidities (6.34 ± 2.38) than men (5.58 ± 2.44) (p = 0.019). After LPA, we found that 38.29% of individuals met characteristics compatible with healthy ageing, predominantly male (60%); the association of a high probability of cognitive impairment with a high degree (severe or total), exhibited by the profiles likely >85% women (18.5% of individuals); physical activity, smoking, osteoporosis, anxiety, COPD, chronic kidney disease (CKD), and creatinine blood levels exhibited statistical differences between profiles; and the probability of dependence severity was associated with an increase in age, although cognitive status conservation was associated being male. Conclusions: The studied +80 group seems to follow a healthy lifestyle, as self-reported. Women fare worse than men in resilient ageing. While common factors related to dysfunctionality did not differentiate between profiles, CKD, an increasingly common age-related condition, did. Full article

Background/Objectives: Cyclosporine A (CsA) is a key immunosuppressant in post-transplantation therapy protocol characterized by large interindividual and intraindividual pharmacokinetic (PK) variability and a narrow therapeutic range necessitating therapeutic drug monitoring (TDM) to prevent graft rejection and minimize side effects. TDM data can be used for developing PK models with the objective of identification and quantification of variability factors that contribute to the differences in CsA concentrations. Methods: Retrospectively collected data from medical records of 58 patients (children and young adults) regarding CsA blood concentrations, concomitant medications, and laboratory findings of significance were used for the population PK model development in NONMEM^® (version 7.5) with first-order conditional estimation method with interaction (FOCE-I). Simulation of the concentrations and area under the curve (AUC) was performed in the web application e-campsis^®. RStudio (version 4.5.0) was used for the purpose of descriptive statistics analysis and graphs plotting. Results: A one-compartment model with first-order absorption and elimination best described the data. Value of clearance (CL/F) was estimated to be 15 L/h, and volume of distribution (V/F) was 71.1 L for a typical patient weighing 40 kg. Interindividual variability (IIV) on CL/F and V/F was 34.91% and 43.05%, respectively. Interoccasional variability (IOV) was 12.25%. Body weight (WT) was introduced allometrically on CL/F and V/F, with the estimated exponent of 0.89 for CL/F and 1 (fixed) for V/F. According to the final model, CL/F decreases with increasing haemoglobin (HGB) value. A difference of almost 22.5% in CL/F was observed among patients’ HGB values reported in the study. Conclusions: Our findings indicate that HGB levels significantly influence CsA PK, particularly minimum concentration (C_min), highlighting the importance of regular HGB levels monitoring together with CsA levels. Full article