Search Results (22,634)

To date, no study has been conducted to investigate the diversity in honeybee populations of Apis mellifera in the Czech Republic. Between 2022 and 2023, worker bees were collected from colonies distributed throughout the Czech Republic in 77 districts, and their genetic differences were examined using 22 microsatellite loci. The samples were obtained from hives (n = 3647) and through the process of capture on flowers (n = 553). Genetic diversity parameters were assessed for both populations in all 77 districts. The findings demonstrated that honeybee populations exhibit moderate genetic diversity, as evidenced by the number of observed alleles, the Shannon index, and heterozygosity values. There was no discrepancy in diversity between hive and flower samples. Diversity characteristics were determined: mean observed heterozygosity 0.55 (hives) and 0.56 (flowers), and fixation index 0.58 for both populations. The average number of alleles per locus was 13.77 and 11.18 from hives and flowers, respectively. The low F_ST and F_IS values (they measured the level of genetic differentiation between populations and the level of inbreeding, respectively) suggest the absence or minimal genetic diversity within and among studied populations. The genetic variation was calculated as 2% and 1% between populations, 8% and 6% between individuals within populations, and 91% and 93% between all individuals in samples from hives and flowers, respectively. Cluster and DAPC (discriminant analysis principal component) analysis classified the bee samples collected from across the country into three and five to six distinguishable groups, respectively. The honeybee population in the Czech Republic displays sufficient diversity and a partial structure. However, there appears to be no correlation between the genetic groups and the geographic regions to which they are assigned. Full article

The development of a single-phase grounding fault arc is influenced by various environmental factors, which can result in the rapid extinction and reignition of the arc. This phenomenon can lead to accidents, such as resonant overvoltage. Current grounding arc models inadequately account for the effects of grounding current, arc length, environmental wind speed, and other variables on the characteristics of the arc. In response to this issue, this article establishes a three-dimensional single-phase grounding arc mathematical model grounded in magnetohydrodynamics. It simulates and analyzes the effects of arc length and environmental wind speed on both arc ignition and extinguishing. Furthermore, an artificial single-phase grounding test platform is constructed within the actual distribution network to validate the accuracy of the simulation model. Research has demonstrated that, under identical operating conditions for both simulation and experimentation, the error range between the simulated arc voltage and the measured data is within 8%. The three-dimensional single-phase grounding arc mathematical model effectively describes the dynamic development process of the grounding arc. At a gap of 12 cm, under windless conditions and with a grounding current of 40.0 A, the temperature of the arc column at the peak of the current reaches 2600 K, while the conductivity decreases to 2.1 × 10⁻⁴ S/m, resulting in the inability of the arc to sustain a burning state. At a gap of 2 cm and a wind speed of 7 m/s, the temperature of the arc column at the peak of the current reaches 2900 K, the conductivity drops to 4.3 × 10⁻³ S/m, leading to the extinction of the arc. Full article

Crape myrtle (Lagerstroemia L.), as a popular ornamental plant, holds significant importance in residents’ daily lives by supporting ecosystem services, enhancing urban aesthetics, and even impacting biological health. There are notable variations among crape myrtle species across different geographical distributions. However, potential differences in residents’ preferences for observing crape myrtle in various regions have not been thoroughly investigated. This study, based on a comprehensive analysis of 700 survey responses from diverse regions in China, sought to determine if discernible patterns exist in residents’ preferences for crape myrtle. The results revealed that residents across different regions exhibited distinct preferences for various ornamental characteristics of crape myrtle. These differences were particularly pronounced in intangible aspects such as cultural expression, ecological value, and economic value. Furthermore, the study demonstrated that the factors driving market demand for ornamental crape myrtle varied substantially across different regional populations. In north China, the flowering period and leaf size were identified as the primary factors influencing market interest. For south China, both the flowering period and flower size were crucial determinants. In central China, the key factors were the flowering period and flower color. The market demand in east China was largely driven by flower size and the flowering period. In northeast China, flower color and planting form played pivotal roles, while in northwest China, spatial ambiance and plant phenotype were significant in shaping preferences. Finally, in southwest China, landscape type and fruit color were the primary factors influencing market demand. These findings provide valuable insights into the relationship between regional preferences and the prevalence of crape myrtle, highlighting the potential factors that shape aesthetic choices in different parts of China. Full article

To understand the impact of climate change on water resources, this research investigates long-term rainfall trends and anomalies across Northeastern India (NEI), covering Assam and Meghalaya (A&M); Nagaland, Manipur, Mizoram, and Tripura (NMMT); and Sub-Himalayan West Bengal and Sikkim (SHWB&S) using different statistical tests including innovative trend analysis (ITA). The study scrutinizes 146 years of rainfall statistics, trend analyses, variability, and probability distribution changes to comprehend its implications. Furthermore, the change in the assured rainfall probabilities was also worked out to understand the impact on rainfed agriculture of Northeastern India. Comparative analysis between all India (AI) and NEI reveals that NEI receives nearly double the annual rainfall compared to AI (2051 mm and 1086 mm, respectively). Despite resembling broad rainfall patterns, NEI displays intra-regional variations, underscoring the necessity for region-specific adaptation strategies. Statistical characteristics like the coefficient of skewness (CS) and coefficient of kurtosis indicate skewed rainfall distributions, notably during the winter seasons in NMMT (CS~1.6) and SHWB&S (CS~1.5). Trend analyses reveal declining rainfall trends, especially conspicuous in NEI’s winter (−1.88) and monsoon (−2.9) seasons, where the rate of decrease was higher in the last three decades. The return periods of assured rainfall at 50% and 75% probability levels also increased sharply during the winter and monsoon seasons by over 30% during the recent half, posing challenges for rainfed upland hill farming. Furthermore, this study highlights increasing variability and negative anomalies in monsoon rainfall over NEI, exacerbating decreasing rainfall trends and significantly impacting agricultural productivity. These findings underscore the urgency for adaptive measures tailored to evolving rainfall patterns, ensuring sustainable agricultural practices and efficient water resource management. Full article

Groundwater is essential for ecosystem stability and climate adaptation, with precipitation variations directly affecting groundwater levels (GWLs). Human activities, particularly groundwater exploitation, disrupt the recharge mechanism and the regional water cycle. In this study, we propose a new research framework: On the basis of analyzing the spatiotemporal variability characteristics of precipitation and shallow GWL, we used transfer function analysis (TFA) to quantify the multi-timescale characteristics of precipitation–GWL response under the effects of climate change and human activities. In addition, we evaluated the GWL seasonality and seasonal response while also considering apportionment entropy. We applied this framework to the Lubei Plain (LBP), and the findings indicated the following: (1) Annual precipitation in the LBP decreased from southeast to northwest, with July and August contributing 51.5% of total rainfall; spatial autocorrelation of GWL was high and was influenced by geological conditions and cropland irrigation. (2) The coherence between GWL and precipitation was 0.96 in the high-precipitation areas but was only 0.6 in overexploited areas, and sandy soils enhanced the effective groundwater recharge, with a gain of 1.65 and a lag time of 2.1 months. (3) Over interannual scales, GWL response was driven by precipitation distribution and aquifer characteristics, while shorter timescales (4 months) were significantly affected by human activities, with a longer lag time in overexploited areas, which was nearly 60% longer than areas that were not overexploited. (4) Groundwater exploitation reduced the seasonality of GWL, and irrigation reduced the coherence between GWL and precipitation (0.5), with a gain of approximately 0.5, while a coherence of 0.8 and a gain of 3.5 were observed in the non-irrigation period. This study clarified the multi-timescale characteristics of the precipitation–GWL response, provided a new perspective for regional research on groundwater response issues, and proposed an important basis for the short-term regulation and sustainable development of water resources. Full article

To characterize the naturalized population of burr medic (Medicago polymorpha L.), a valuable pasture legume, in subtropical Queensland, Australia, a collection of 1747 lines from 107 sites in 11 regions was grown, and 26 phenotypic and agronomic attributes were recorded. This data matrix was analyzed by cluster, principal co-ordinates, and discriminant and correlation analyses to examine line relationships based on plant attributes and their association with site characteristics of climate and soil. Among the wide polymorphism of attributes across the collection zone, there were a number of notable phenotypic associations. One of these, with large green leaves, minimally dentate leaf margins, and light purple petioles, was widely distributed. Three others, one with a distinctive magenta leaf mark, dark purple petioles, and an upright habit; one with those same attributes but with a prostrate habit; and one with grey-green leaves, high frost resistance, and the ability to stay green and to produce high pod yields, were associated with climatic and soil characteristics in the north, east, and south of the collection zone, respectively. Days to flowering were longer in lines from saline soils at lower altitude, and plant vigor was greatest in lines from more fertile soils with higher rainfall. A wide variation in time to flower of lines at all collection sites contributes to the adaptation of M. polymorpha in subtropical Queensland and potentially to its persistence with future climate change. Full article

Global climate fluctuations pose challenges not only to natural environments but also to the conservation and transmission of human cultural and historical heritage. World Heritage Sites are pivotal regions for studying climate change impacts and devising adaptation strategies, with remote sensing technology showcasing significant utility in monitoring these impacts, especially in the Mediterranean region’s diverse and sensitive climate context. Although existing work has begun to explore the role of remote sensing in monitoring the effects of climate change, detailed analysis of the spatial distribution and temporal trends of landscape stability remains limited. Leveraging remote sensing data and its derived products, this study assessed climate change impacts on the Causses and Cévennes Heritage Site, a typical Mediterranean heritage landscape. Specifically, this study utilized remote sensing data to analyze the trends in various climatic factors from 1985 to 2020. The landscape stability model was developed utilizing land cover information and landscape indicators to explore the landscape stability and its distribution features within the study area. Finally, we adopted the Geographical Detector to quantify the extent to which climatic factors influence the landscape stability’s spatial distribution across different periods. The results demonstrated that (1) the climate showed a warming and drying pattern during the study period, with distinct climate characteristics in different zones. (2) The dominance of woodland decreased (area proportion dropped from 76% to 66.5%); transitions primarily occurred among woodland, cropland, shrubland, and grasslands; landscape fragmentation intensified; and development towards diversification and uniformity was observed. (3) Significant spatiotemporal differences in landscape stability within the heritage site were noted, with an overall downward trend. (4) Precipitation had a high contribution rate in factor detection, with the interactive enhancement effects between temperature and precipitation being the most prominent. The present study delivers a thorough examination of how climate change affects the Causses and Cévennes Heritage Landscape, reveals its vulnerabilities, and offers crucial information for sustainable conservation efforts. Moreover, the results offer guidance for the preservation of similar Mediterranean heritage sites and contribute to the advancement and deepening of global heritage conservation initiatives. Full article

Chalcone synthase (CHS), the first key structural enzyme in the flavonoid biosynthesis pathway, plays a crucial role in regulating plant responses to abiotic stresses and hormone signaling. However, its molecular functions remain largely unknown in Phyllostachys edulis, which is one of the most economically and ecologically important bamboo species and the most widely distributed one in China. This study identified 17 CHS genes in Phyllostachys edulis and classified them into seven subgroups, showing a closer evolutionary relationship to CHS genes from rice. Further analysis of PeCHS genes across nine scaffolds revealed that most expansion occurred through tandem duplications. Collinearity analysis indicated strong evolutionary conservation among CHS genes. Motif and gene structure analyses confirmed high structural similarity, suggesting shared functional characteristics. Additionally, cis-acting element analysis demonstrated that PeCHS genes are involved in hormonal regulation and abiotic stress responses. RNA-Seq expression profiles in different bamboo shoot tissues and heights, under various hormone treatments (gibberellin (GA), naphthaleneacetic acid (NAA), abscisic acid (ABA), and salicylic acid (SA)), as well as salinity and drought stress, revealed diverse response patterns among PeCHS genes, with significant differential expression, particularly under hormone treatments. Notably, PeCHS14 consistently maintained high expression levels, suggesting its key role in stress response mechanisms. qRT-PCR analysis further validated the expression differences in five PeCHS genes under GA and ABA treatments. Subcellular localization analysis demonstrated that PeCHS14 and PeCHS15 proteins are localized in the nucleus. This study provides a foundation for investigating the potential functions of PeCHS genes and identifies candidate genes for future research on the responses of Phyllostachys edulis to abiotic stresses and hormone signaling. Full article

Spatial genes represent the fundamental interplay among the morphological characteristics of historical districts. Identifying and analyzing these morphological elements can enhance our understanding of urban spatial development, uncover spatial meanings, and provide informed recommendations for future development. This study focuses on the Xuzhou Huilongwo historical district, employing geographic information system, Global Mapper, and other digital technologies to determine the area’s microtopographic features. Qualitative methodologies extract the spatial genes of street segments, entry spaces, and node spaces. By summarizing the microtopography’s influence on street and alley characteristics, valuable spatial samples were selected and visually represented for analysis. This included examining the street segment interface, entry space sequences, and the planar morphology of node spaces. The findings reveal that Huilongwo architecture aligns with topographical features, exhibiting a multi-directional distribution. Height differences help establish street boundaries and enhance pathways’ experiential quality. Additionally, topography significantly influences street spaces, leading to undulating sequences in entry spaces. This study provides insights into the preservation and enhancement of streets and alleys within Xuzhou’s historical district. Full article

Anthropogenic heat is the heat generated by human activities such as industry, construction, transport, and metabolism. Accurate estimates of anthropogenic heat are essential for studying the impacts of human activities on the climate and atmospheric environment. Commonly applied methods for estimating anthropogenic heat include the inventory method, the energy balance equation method, and the building model simulation method. In recent years, the rapid development of computer technology and the availability of massive data have made machine learning a powerful tool for estimating anthropogenic heat fluxes and assessing its effects. Multi-source remote sensing data have also been widely used to obtain more details of the spatial and temporal distribution characteristics of anthropogenic heat. This paper reviews the main approaches for estimating anthropogenic heat emissions. The typical algorithms of the abovementioned three methods are introduced, and their advantages and limitations are also evaluated. Moreover, the recent progress in the application of remote sensing data and machine learning are discussed as well. Based on big data and machine learning techniques, the research on feature engineering and model fusion will bring about major changes in data analysis and modeling of anthropogenic heat. More in-depth research of this issue is recommended to provide important support for curbing global warming, mitigating air pollution, and achieving the national goals of carbon peak and a carbon neutrality strategy. Full article

Background and Objectives: The current study aimed to compare the effectiveness of the Lung Imaging Reporting and Data System (Lung-RADS) Version 2022 and the British Thoracic Society (BTS) guidelines in differentiating lung metastases from de novo primary lung cancer on CT scans in patients without prior cancer diagnosis. Materials and Methods: This retrospective study included 196 patients who underwent chest CT scans between 2015 and 2022 without a known history of cancer but with detected pulmonary nodules. CT images characterized nodules based on size, number, location, margins, attenuation, and growth patterns. Nodules were classified according to Lung-RADS Version 2022 and BTS guidelines. Statistical analyses compared the sensitivity and specificity of Lung-RADS and BTS guidelines in distinguishing metastases from primary lung cancer. Subgroup analyses were conducted based on nodule characteristics. Results: Of the 196 patients, 148 (75.5%) had de novo primary lung cancer, and 48 (24.5%) had lung metastases from occult primary tumors. Lung-RADS Version 2022 demonstrated higher specificity than BTS guidelines (87.2% vs. 72.3%, p < 0.001) while maintaining similar sensitivity (91.7% vs. 93.8%, p = 0.68) in differentiating lung metastases from primary lung cancer. Lung metastases were more likely to present with multiple nodules (81.3% vs. 18.2%, p < 0.001), lower lobe distribution (58.3% vs. 28.4%, p < 0.001), and smooth margins (70.8% vs. 20.3%, p < 0.001), whereas primary lung cancers were associated with solitary nodules, upper lobe location, and spiculated margins. Conclusions: Lung-RADS Version 2022 provides higher specificity than the BTS guidelines in differentiating lung metastases from primary lung cancer on CT scans in patients without prior cancer diagnosis. Recognizing characteristic imaging features can improve diagnostic accuracy and guide appropriate management. Full article

Introduction: Pseudomonas otitidis, known for carrying the bla_POM-1 gene and linked to various diseases, is widely distributed. However, its prevalence in Ghana is unknown, mainly due to misidentification or inadequate research. In this study, for the first time, we characterized P. otitidis from Densu river water in Ghana. Methods: The antimicrobial susceptibility and whole genome characteristics of two strains (Tg_9B and BC12) were determined. The resistance and virulence features were determined using ResFinder and the VFDB database, respectively. Maximum-likelihood phylogeny was conducted based on amino acid sequences of bla_POM-1 and P. otitidis core genomes. Results: The strains carried bla_POM-1 on the chromosome, with only Tg_9B showing intermediate resistance to meropenem. Tg_9B had a unique genetic make-up downstream of bla_POM-1, compared with BC12 and other reference strains. Both strains harbored virulence factors able to induce pathogenicity through immune evasion. The efflux pump genes (adeF, rsmA, and qacG) were present in the genomes of all the strains used in this study. The amino acid sequences of POM-1 in the strains shared a sequence homology with seven other sequences from different countries. Conclusions: This study highlights the emergence of bla_POM-1 harboring P. otitidis in Ghana and affirms the conservation of bla_POM-1 and adeF, rsmA, and qacG in the species. Full article

The growing use of tungsten (W) in industrial applications has made it a critical element in modern production processes. This increasing demand is also contributing to the element’s wider dispersion in the environment, including in soil. In addition to mining areas, it is necessary to evaluate the possible environmental effects of tungsten even in non-contaminated areas. The mobility and bioavailability of W in soil are essentially determined by the sorption processes that regulate its distribution between the liquid and solid phases of the soil. In this study, the effect of different land uses—natural, agricultural, and urban—on the sorption of W in soils of the same geographical area was addressed. The results showed that the maximum sorption can be found in natural soils, with a value of 528 mg/kg, while for agricultural and urban soils, the mean values are 486 and 392 mg/kg, respectively. Anthropic interventions seem to reduce this capacity in agricultural soils by about 8%, probably due to agronomic practices, and by even more, 26%, in urban soils, where the use of different materials can modify the original characteristics of the soils. These results show that variations in some of the main characteristics of soils, such as pH and organic matter content, also derived from different land uses, influence the sorptive properties of the soils. Full article

Roots play essential roles in the acquisition of water and minerals from soils in higher plants. However, water or nutrient limitation can alter plant root morphology. To clarify the spatial distribution characteristics of essential nutrients in citrus roots and the influence mechanism of micronutrient deficiency on citrus root morphology and architecture, especially the effects on lateral root (LR) growth and development, two commonly used citrus rootstocks, trifoliate orange (Poncirus trifoliata L. Raf., Ptr) and red tangerine (Citrus reticulata Blanco, Cre), were employed here. The analysis of the mineral nutrient distribution characteristics in different root parts showed that, except for the P concentrations in Ptr, the last two LR levels (second and third LRs) had the highest macronutrient concentrations. All micronutrient concentrations in the second and third LRs of Ptr were higher than those of Cre, except for the Zn concentration in the second LR, which indicates that Ptr requires more micronutrients to maintain normal root system growth and development. Principal component analysis (PCA) showed that B and P were very close in terms of spatial distribution and that Mo, Mn, Cu, and Fe contributed significantly to PC1, while B, Cu, Mo, and Zn contributed significantly to PC2 in both rootstocks. These results suggest that micronutrients are major factors in citrus root growth and development. The analysis of root morphology under micronutrient deficiency showed that root growth was more significantly inhibited in Ptr and Cre under Fe deficiency (FeD) than under other micronutrient deficiencies, while Cre roots exhibited better performance than Ptr roots. From the perspective of micronutrient deficiency, FeD and B deficiency (BD) inhibited all root morphological traits in Ptr and Cre except the average root diameter, while Mn deficiency (MnD) and Zn deficiency (ZnD) had lesser impacts, as well as the morphology of the stem. The mineral nutrient concentrations in Ptr and Cre seedlings under micronutrient deficiency revealed that single micronutrient deficiencies affected both their own concentrations and the concentrations of other mineral nutrients, whether in the roots or in stems and leaves. Dynamic analysis of LR development revealed that there were no significant decreases in either the first or second LR number in Ptr seedlings under BD and ZnD stress. Moreover, the growth rates of first and second LRs in Ptr and Cre did not significantly decrease compared with the control under short-term (10 days) BD stress. Altogether, these results indicate that micronutrients play essential roles in citrus root growth and development. Moreover, citrus alters its root morphology and biological traits as a nutrient acquisition strategy to maintain maximal micronutrient acquisition and growth. The present work on the spatial distribution characteristics and micronutrient deficiency of citrus roots provides a theoretical basis for effective micronutrient fertilization and the diagnosis of micronutrient deficiency in citrus. Full article

Cropland resilience is the ability of cropland systems to adapt and rebound from multiple stresses and disturbances. Cropland resilience is vital for ensuring national food security, promoting sustainable agricultural development, and adapting to global climate change. This study measures cropland resilience in China using the entropy method within the PSR framework. Additionally, it employs quantitative analysis methods, including kernel density estimation, the standard deviation ellipse, the Theil Index, and the geographical detector, to systematically examine the spatiotemporal dynamics of cropland resilience and its driving factors in China. The findings reveal the evolving trends of cropland resilience over time and space, highlighting regional differences and the spatial distribution of resilience. The study found the following: (1) The overall cropland resilience in China shows an upward trend, but there is uneven development among regions, particularly in the relatively lagging western areas. (2) There is a notable spatial imbalance in cropland resilience, primarily driven by intra-regional differences. (3) Stability of Grain Production; Total Grain Production; Fiscal Expenditure on Agriculture, Forestry, and Water; Soil–Water Harmony; and the Cropland Disaster Resistance Index are identified as key driving factors, with the influence of the Cropland Disaster Resistance Index notably increasing over time. (4) The study highlights the critical role of synergistic effects among these factors in enhancing cropland resilience, noting a significant strengthening of these synergies over time. The research results offer a fresh perspective on the role of cropland resilience in dynamic environments. They enhance our understanding of the spatiotemporal characteristics of cropland resilience, reveal its underlying dynamic processes, and provide a scientific basis for policymaking aimed at promoting the sustainable use and management of cropland. Full article