Search Results (632)

The pepper weevil Anthonomus eugenii is a devastating pest native to Central America that can cause severe damage to over 35 pepper varieties. Global trade in peppers has significantly increased the risk of its spread and expansion. Moreover, future climate change may add more uncertainty to its distribution, resulting in considerable ecological and economic damage globally. Therefore, we employed an ensemble model combining Random Forests and CLIMEX to predict the potential global distribution of A. eugenii in historical and future climate scenarios. The results indicated that the maximum temperature of the warmest month is an important variable affecting global A. eugenii distribution. Under the historical climate scenario, the potential global distribution of A. eugenii is concentrated in the Midwestern and Southern United States, Central America, the La Plata Plain, parts of the Brazilian Plateau, the Mediterranean and Black Sea coasts, sub-Saharan Africa, Northern and Southern China, Southern India, Indochina Peninsula, and coastal area in Eastern Australia. Under future climate scenarios, suitable areas in the Northern Hemisphere, including North America, Europe, and China, are projected to expand toward higher latitudes. In China, the number of highly suitable areas is expected to increase significantly, mainly in the south and north. Contrastingly, suitable areas in Central America, northern South America, the Brazilian Plateau, India, and the Indochina Peninsula will become less suitable. The total land area suitable for A. eugenii under historical and future low- and high-emission climate scenarios accounted for 73.12, 66.82, and 75.97% of the global land area (except for Antarctica), respectively. The high-suitability areas identified by both models decreased by 19.05 and 35.02% under low- and high-emission scenarios, respectively. Building on these findings, we inferred the future expansion trends of A. eugenii globally. Furthermore, we provide early warning of A. eugenii invasion and a scientific basis for its spread and outbreak, facilitating the development of effective quarantine and control measures. Full article

Integrating artificial intelligence (AI) and cause-related marketing has reshaped corporate social responsibility practices while triggering a conflict between technological instrumental rationality and moral value transmission. Building on the Persuasion Knowledge Model (PKM) and AI aversion literature, this research employs two experiments to reveal that AI disclosure exerts a unique inhibitory effect on consumers’ purchase intentions in cause-related marketing contexts compared to non-cause-related marketing scenarios. Further analysis uncovers a chain mediation pathway through consumer skepticism and advertisement attitudes, explaining the psychological mechanism underlying AI disclosure’s impact on purchase intentions. The study also identifies the moderating role of AI aversion within this chain model. The findings provide a new theoretical perspective for integrating AI disclosure, consumer psychological responses, and marketing effectiveness while exposing the “value-instrumentality” conflict inherent in AI applications for cause-related marketing. This research advances the evolution of the PKM in the digital era and offers practical insights for cause-related marketing enterprises to balance AI technology application with optimized disclosure strategies. Full article

Wild boars (Sus scrofa) and their associated ticks represent important reservoirs and vectors for a variety of zoonotic pathogens, particularly Anaplasma spp. and Babesia spp. The aim of this review is to highlight the diagnostic methods employed throughout the past two decades to detect these pathogens in wild boars and their associated ticks, focusing especially on PCR methods (conventional and real-time), on sample origin (host or vector), and on specific primers. This review compiles data from studies conducted between 2005 and 2024, providing a comparative overview of targeted genes, such as groEL, msp2, and 16S rRNA for Anaplasma, and 18S rRNA for Babesia. Despite the prevalence of molecular diagnostic techniques, serological methods like ELISA have not been applied to wild boar or tick samples in this context. The review also analyzes geographical trends, with a higher research output noted in Central and Eastern Europe, Japan, and the United States. The performance of the methods is discussed based on reproducibility, sensitivity, specificity, pathogen prevalence, and technical variables. By synthesizing these findings, the review identifies methodological gaps and offers a reference framework for improving diagnostic accuracy in wildlife disease surveillance. Full article

Regional HIV-1 epidemics are evolving with distinct patterns in transmission routes, subtype distribution, and molecular transmission cluster (MTCs) characteristics. We analyzed 9500 HIV-1 cases diagnosed over 30 years using phylogenetic and network methods, integrating molecular, epidemiological, demographic, and behavioral data. Subtype A6 remains dominant nationally (80.6%), followed by 63_02A6 (7.9%), subtype B (5.6%), 02_AG_FSU (1.2%), 03_A6B (0.7%), and 14/73_BG (0.6%). Non-A6 infections were more common among males (OR 1.51) and men who have sex with men (OR 7.33). Network analysis identified 421 MTCs, with 256 active clusters. Clustering was more likely among young individuals (OR: 1.31), those not receiving antiretroviral therapy (OR: 2.70), and injecting drug users (OR: 1.28). Non-A6 subtypes showed a higher likelihood of clustering. Phylogenetic analysis revealed that local clusters of the major subtypes originated between the late 1970s (subtype B) and the mid-2000s (63_02A6) with links to populations in Eastern Europe, Central Asia (subtypes A6, 63_02A6, 02_AG_FSU, 03_A6B), and Western Europe and the Americas (subtype B, 14/73_BG). These findings indicate a complex, evolving regional epidemic transitioning from subtype A6 dominance to a more diverse mix of subtypes. The ability of non-A6 subtypes to form active MTCs suggests their establishment in the local population. Full article

The current study aimed to determine the optimum agronomic conditions—specifically sowing date and seeding density—for soybean cultivation in a temperate climate. A field experiment was conducted to evaluate three sowing dates based on soil temperature (S1—9 °C, S2—12 °C, S3—15 °C) and three seeding densities (D1—50, D2—70, D3—90 seeds·m⁻²). A field experiment was conducted in the years 2017–2019 in eastern Poland (Central Europe). Yields were strongly influenced by weather conditions. In 2019, the average yield was 2.61 Mg·ha⁻¹, making it the most favorable year, whereas 2018 was the least favorable, with an average yield of 1.41 Mg·ha⁻¹. Seeding density also affected soybean yields—the highest yield was obtained at the medium density (D2—2.36 Mg∙ha⁻¹). On the other hand, the highest thousand seed weight (159.30 g·m⁻²) was achieved at the lowest density (D1). Plant height and pod length depended on the sowing date. The tallest plants (69.96 cm) and the longest pods (4.55 cm) were obtained with early sowing (S1). The number of seeds per pod ranged from 1.8 to 2.7, with the highest values recorded in 2017, mainly with early sowing (S1) and low density (D1). It is recommended that sowing strategies be flexibly adjusted to the meteorological conditions of a given season. The findings indicate that appropriate selection of sowing parameters can significantly enhance the efficiency and stability of soybean yields under the variable climatic conditions of Poland. Full article

Despite growing academic interest in platform work and the gig economy, most existing research focuses on Western Europe, often neglecting the unique institutional and socioeconomic contexts of Central and Eastern Europe. This study addresses that gap by exploring the working conditions of platform workers in Poland, with particular emphasis on both material and psychosocial dimensions from the workers’ own perspectives. Data were collected from a nationally representative sample of 450 platform workers engaged in both online and location-based tasks, using the computer-assisted web interviewing (CAWI) method. The findings show a high level of perceived autonomy, with 74% of respondents feeling that they are independent in their work. However, autonomy is often limited by external factors, in particular, the availability of work. Workers who treat platform work as a side job are significantly more likely to report a sense of autonomy. In terms of health and safety, only 27% expressed concerns about negative health impacts, and 24% reported poor working conditions. Those who received health and safety information from the platform were more likely to acknowledge potential risks. Interestingly, workers relying on platform work as their primary source of income were more likely to perceive their work as safe, compared to those treating it as supplementary employment. Full article

Groundwater contamination by nitrates (NO₃⁻) and nitrites (NO₂⁻) is an urgent problem in rural areas of Eastern Europe, with profound public health and sustainability implications. This paper presents an integrated assessment of groundwater vulnerability and water quality in rural wells in the Ceanu Mare commune, Cluj County, Romania—a representative area of the Northern Transylvania Basin, characterized by diverse geological structures, intensive agricultural activities, and incomplete public water infrastructure. This study combines detailed hydrochemical analyses, household-level studies, and geological context to identify and quantify key factors influencing nitrate and microbial contamination in rural wells, providing a comprehensive perspective on water quality challenges in the central part of Romania. This study adopts a multidisciplinary approach, integrating detailed geotechnical investigations conducted through four strategically located boreholes. These are complemented by extensive hydrogeological and lithological characterization, as well as rigorous chemical and microbiological analyses of nearby wells. The results reveal persistently elevated concentrations of NO₃⁻ and NO₂⁻, commonly associated with inadequate livestock waste management and the proximity of manure storage areas. Microbiological contamination was also frequent. In this study, the NO₃⁻ levels in well water ranged from 39.7 to 48 mg/L, reaching up to 96% of the EU/WHO threshold (50 mg/L), while the NO₂⁻ concentrations varied from 0.50 to 0.69 mg/L, exceeding the legal limit (0.5 mg/L) in 87% of the sampled wells. Ammonium (NH₄⁺) was detected (0.25–0.34 mg/L) in all the wells, below the maximum allowed limit (0.5 mg/L) but indicative of ongoing organic pollution. All the well water samples were non-compliant for microbiological parameters, with E. coli detected in 100% of cases (5–13 CFU/100 mL). The regional clay–marl substrate offers only limited natural protection against pollutant infiltration, primarily due to lithological heterogeneity and discontinuities observed within the clay–marl layers in the study area. This research delivers a replicable model for rural groundwater assessment and addresses a critical gap in regional and European water safety studies. It also provides actionable recommendations for sustainable groundwater management, infrastructure development, and community risk reduction in line with EU water directives. Full article

The agriculture sector is increasingly challenged to maintain productivity and sustainability amidst environmental, marketplace, and geopolitical pressures. While precision agriculture enhances physical production, the financial resilience of agricultural firms has been understudied. In this study, machine learning (ML) methods, including logistic regression (LR), decision trees (DTs), and artificial neural networks (ANNs), are employed to predict the bankruptcy risk for Central and Eastern European (CEE) farming firms. All models consistently showed high performance, with AUC values exceeding 0.95. DTs had the highest overall accuracy (95.72%) and F1 score (0.9768), LR had the highest recall (0.9923), and ANNs had the highest discrimination power (AUC = 0.960). Visegrad, Balkan, Baltic, and Eastern Europe subregional models featured economic and structural heterogeneity, reflecting the need for local financial risk surveillance. The results support the development of AI-based early warning systems for agricultural finance, enabling smarter decision-making, regional adaptation, and enhanced sustainability in the sector. Full article

Rye (Secale cereale L.) is one of the most important cereals cultivated in Central and Eastern Europe, valued for its high resistance to environmental stress and high levels of bioactive compounds, such as dietary fiber (DF) and alkylresorcinols (ARR). The aim of the study was to evaluate the content and variability of DF fractions and ARR in rye grain of hybrid and population cultivars. The research was conducted on grain from four rye cultivars cultivated in five locations over three consecutive growing seasons. The content of DF, its fractions, and ARR, was determined using enzymatic–gravimetric and colorimetric methods. The results showed significant variability in all analyzed traits, with environmental conditions and G×E interaction having the greatest impact on their content. Hybrid cultivars were characterized by a higher and more stable content of bioactive compounds. Notable average values for hybrids vs. populations included DF: 153.9 vs. 151.7 g kg⁻¹, NSP: 129.4 vs. 127.7 g kg⁻¹, lignin: 24.5 vs. 24.0 g kg⁻¹, β-glucan: 21.7 vs. 20.6 g kg⁻¹, and ARR: 1015 vs. 987 g kg⁻¹. The KWS Serafino cultivar characterized by the highest and most stable content of bioactive compounds. Selecting genotypes with stable chemical profiles regardless of environmental conditions is crucial for developing nutritionally valuable rye-based products. Full article

This study examines the complex interactions among soil moisture, evaporation, extreme weather events, and lightning, and their influence on fire activity across the extratropical and Pan-Arctic regions. Leveraging reanalysis and remote-sensing datasets from 2000 to 2020, we applied cross-correlation analysis, a modified Mann–Kendall trend test, and assessments of interannual variability to key variables including soil moisture, fire frequency and risk, evaporation, and lightning. Results indicate a significant increase in dry days (up to 40%) and heatwave events across Central Eurasia and Siberia (up to 50%) and Alaska (25%), when compared to the 1980–2000 baseline. Upward trends have been detected in evaporation across most of North America, consistent with soil moisture trends, while much of Eurasia exhibits declining soil moisture. Fire danger shows a strong positive correlation with evaporation north of 60° N (r ≈ 0.7, p ≤ 0.005), but a negative correlation in regions south of this latitude. These findings suggest that in mid-latitude ecosystems, fire activity is not solely driven by water stress or atmospheric dryness, highlighting the importance of region-specific surface–atmosphere interactions in shaping fire regimes. In North America, most fires occur in temperate grasslands, savannas, and shrublands (47%), whereas in Eurasia, approximately 55% of fires are concentrated in forests/taiga and temperate open biomes. The analysis also highlights that lightning-related fires are more prevalent in Eastern Europe and Southeastern Asia. In contrast, Western North America exhibits high fire incidence in temperate conifer forests despite relatively low lightning activity, indicating a dominant role of anthropogenic ignition. These findings underscore the importance of understanding land–atmosphere interactions in assessing fire risk. Integrating surface conditions, climate extremes, and ignition sources into fire prediction models is crucial for developing more effective wildfire prevention and management strategies. Full article

Background: The increasing complexity of global supply chains and environmental expectations has highlighted the strategic importance of digital transformation in the transport, forwarding, and logistics (TFL) sector. Despite a growing portfolio of available tools, adoption rates—particularly among small and medium-sized enterprises (SMEs) in Central and Eastern Europe—remain low. This study investigates the barriers and motivations related to the implementation of digital planning tools supporting intermodal transport planning. Methods: A structured online survey was conducted among 80 Polish TFL enterprises, targeting decision-makers responsible for operational and digital strategies. The questionnaire included 17 closed and semi-open questions grouped into three thematic sections: tool usage, implementation barriers, and digital readiness. Results: The findings indicate that only 20% of respondents use dedicated route planning tools, and merely 10% report satisfaction with their performance. Key barriers include lack of awareness, organizational inertia, and the prioritization of other initiatives, with financial cost cited less frequently. While environmental sustainability is declared as a priority by most enterprises, digital support for emission tracking is limited. The results highlight the need for targeted education, integration support, and differentiated platform functionalities for SMEs and larger firms. Conclusions: This study offers evidence-based recommendations for developers, policymakers, and logistics managers aiming to accelerate digital adoption in the intermodal logistics landscape. Full article

Equine piroplasmosis (EP) is an endemic parasitic disease in southern European countries, such as Spain. Andalusia, the most southwestern region of Europe, is the community with the highest number of registered horses and farms in Spain and one of the main international exporters of Andalusian (Spanish Purebred) horses worldwide. Considering the current expansion of this disease and the possible effect of climate change on its prevalence, studying the EP prevalence in this region is compelling. Molecular (PCR) and serological methods (cELISA and IFAT) were used to study the true and apparent prevalences during a period of three consecutive years, evaluating the effects of age, sex, season, year of testing, and province. Results showed different EP prevalences between western and eastern provinces, as well as among seasons. Moreover, a positive association was observed between age and T. equi seropositivity, without any effect of sex. Our findings demonstrate that Andalusia is an EP endemic region, but prevalences were lower compared to central and northern Spanish regions. Moreover, EP prevalence has not increased in Andalusia in recent years despite climate changes. Full article

This paper explores the under-researched phenomenon of queer migration in Croatia, Lithuania, and Poland—three post-communist, Catholic-majority countries. Drawing on existing studies in the literature and empirical data, it examines how prevailing social conservatism—shaped by the influence of Catholicism and the distinct developmental trajectories of these countries—is reflected in research on queer migration. Although limited, the current body of knowledge confirms that concerns over LGBTQIA+ rights are a factor motivating emigration. The three examples illustrate how queer migration must be analyzed within the complex interplay between Europeanization and liberalization, and the backlash against these processes. This backlash, prominently supported by the Catholic Church, includes resistance to gender equality and LGBTQIA+ rights. By critically engaging with existing research, the paper underscores the need for future studies—particularly those investigating the gap between legal protections and prevailing social attitudes toward LGBTQIA+ individuals, the relationship between human rights backlashes and queer migration, the intersections between spatial context and personal biographies, and the connection between the queer migration and recent immigration waves in these countries. Full article

Heracleum sosnowskyi Manden. (Sosnowsky’s hogweed), originally introduced to Central and Eastern Europe as a fodder crop, has become a highly invasive species due to its ecological adaptability, high reproductive capacity, and efficient seed dispersal. Despite its negative impact on native flora and its health risks to humans and animals, the species also represents a valuable source of biologically active compounds. In this study, we demonstrate that the leaves of H. sosnowskyi contain substantial amounts of furanocoumarins—phototoxic compounds with notable therapeutic potential, particularly as natural photosensitizers in anticancer therapies. To extract furanocoumarins from H. sosnowskyi, microwave-assisted extraction (MAE) was employed, with optimization of key parameters including extraction solvent (hexane), temperature (70 °C), extraction time (10 min), and solvent-to-solid ratio (20:1). Four major compounds—angelicin (2.3 mg/g), psoralen (0.15 mg/g), methoxsalen (0.76 mg/g), and bergapten (3.14 mg/g)—were identified and quantified using gas chromatography–mass spectrometry and gas chromatography with flame ionization detection. To purify the extract and selectively isolate the target compounds, a solid-phase extraction method was developed using a Strata Eco-Screen sorbent and stepwise elution with a hexane–acetone mixture. As a result, pure angelicin, pure methoxsalen, and various mixtures of the furanocoumarins were obtained. These findings highlight the potential of H. sosnowskyi as a sustainable source of furanocoumarins for pharmaceutical applications. Full article

Questionnaire data plays a key role in social research, especially when evaluating public attitudes using Likert-type scales. Yet, traditional analyses often merge some ordinal categories and exclude responses such as Don’t Know, No Answer, or Refused—risking the loss of valuable information. This study introduces BS-TOSIE (Belief Structure-Based TOPSIS for Survey Item Evaluation), a novel method that preserves and integrates all response types, including ambiguous ones. By combining the Belief Structure framework with the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method, BS-TOSIE offers a structured approach to ranking and evaluating individual survey items measured on an ordinal scale, even in the presence of missing or incomplete data. Response distributions are transformed into a belief structure vector, enabling comparison against ideal and anti-ideal benchmarks. We demonstrate this approach using data from the Quality of Life in European Cities survey to assess perceptions of local governance in European cities. This study analyzes changes in citizen satisfaction with local public administration across five key dimensions—timeliness, procedural clarity, fairness of fees, digital accessibility, and perceived corruption—in 83 European cities between 2019 and 2023. The findings reveal persistent regional disparities, with Northern and Western European cities consistently outperforming those in Southern and Eastern Europe, although some cities in Central Europe show signs of improvement. Zurich consistently received high satisfaction scores, while other cities, such as Rome and Palermo, showed lower scores. Unlike traditional methods, our approach preserves the full spectrum of responses, yielding more nuanced and interpretable insights. The results show that BS-TOSIE enhances both the clarity and depth of survey analysis, making a methodological contribution to the evaluation of ordinal data and offering empirical insights into public perceptions of local city administration. Full article