Search Results (65)

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

Information diffusion models developed for Twitter, Reddit, and Facebook assume network contagion and competition for shared attention. Telegram operates differently. It is built around channels rather than social graphs, and users receive posts directly from subscribed channels without algorithmic mediation. We analyze over 5000 forwarding cascades from the Pushshift Telegram dataset to examine whether existing diffusion models generalize to this broadcast environment. Our findings reveal fundamental structural differences. Telegram forwarding produces perfect star topologies with zero multi-hop propagation. Every forward connects directly to the original message, creating trees with maximum depth of exactly 1. This contrasts sharply with Twitter retweet chains that routinely reach depths of 5 or more hops. Forwarding delays follow heavy-tailed Weibull or lognormal distributions with median delays measured in days rather than hours. Approximately 15 to 20 percent of cascades exhibit administrative bulk reposting rather than organic user-driven growth. Most strikingly, early-stage competitive overtaking is absent. Six of 30 pairs exhibit crossings, but these occur late (median 79 days) via administrative bursts rather than organic competitive acceleration during peak growth. We develop a delay-driven star diffusion model that treats forwarding as independent draws from a delay distribution. The model achieves median prediction errors below 10 percent for organic cascades. These findings demonstrate that platform architecture fundamentally shapes diffusion dynamics. Comparison with prior studies on Twitter, Weibo, and Reddit reveals that Telegram’s broadcast structure produces categorically different patterns—including perfect star topology and asynchronous delays—requiring platform-specific modeling approaches rather than network-based frameworks developed for other platforms. Full article

This study proposes a novel four-pointed-star-shaped honeycomb structure having zero Poisson’s ratio, designed to overcome the stress concentration inherent in traditional point-to-point connected star-shaped honeycombs.By introducing a horizontal connecting wall at cell junctions, the new configuration achieves a more uniform stress distribution and enhanced structural stability. An analytical model for the in-plane equivalent elastic modulus was derived using homogenization theory and the energy method. The model, along with the structure’s zero Poisson’s ratio characteristic, was validated through finite element simulations and experimental compression tests. The simulations predicted an equivalent elastic modulus of 51.71 MPa (Y-direction) and 74.67 MPa (X-direction), which aligned closely with the experimental measurements of 56.61 MPa and 60.50 MPa, respectively. The experimental Poisson’s ratio was maintained near zero (v = 0.02). Parametric analysis further revealed that the in-plane equivalent elastic modulus decreases with increases in the wall angle, horizontal wall length, and wall thickness. This work demonstrates a successful structural optimization strategy that improves both mechanical performance and manufacturability for zero Poisson’s ratio honeycomb applications. Full article

Understanding the diversity of star formation histories (SFHs) of galaxies is key to reconstructing their evolutionary paths. Traditional models often assume parametric forms such as delayed-$\tau$ or exponentially declining models, which may not reflect the actual variety of formation processes. We aim to assess what types of SFHs are consistent with the observed present-day star formation rates (${\mathrm{SFR}}_0$) and time-averaged star formation rates ($⟨\mathrm{SFR}⟩$) of galaxies in the Local Volume, without assuming any fixed functional form. We construct a non-parametric framework by generating large ensembles of randomized SFHs for each galaxy in the sample. For each SFH, we compute its predicted stellar mass and present-day SFR and retain only those consistent with the observed values within a 20% tolerance. We then infer the statistical distribution of power-law slopes $\eta$ (fitted as $\mathrm{SFR}\left(t\right)\propto {(t-t_{\mathrm{start}})}^{\eta }$) and 50% stellar mass formation times $t_{50}$. Across the full sample of 555 galaxies, we find that ≈70% have flat SFHs ($\left|\eta \right|\le 0.01$), ≈24% are mildly declining ($\eta <-0.01$), and ≈6% are rising ($\eta >0.01$). In the low-mass bin ($M_{★}<3\times {10}^9{M}_{\odot }$), rising SFHs slightly increase (≈7%) but remain a minority as the majority have flat SFHs. Both $\eta$ and $t_{50}$ correlate strongly with the SFR ratio (Spearman $\rho >0.75$, $p\ll {10}^{-16}$), indicating that the shape and timing of star formation are primarily governed by this ratio. The $t_{50}$ distribution shows sharp spikes near 7.74 and 7.86 Gyr, which we attribute to grid discretization combined with filtering, rather than a physical bimodality. Our results confirm that strongly declining SFH templates are disfavored in the Local Volume: most systems are consistent with flat long-term SFHs, with only mild decline or occasional rising. Importantly, this is demonstrated through a fully model-independent, data-driven approach, with per-galaxy uncertainties quantified using the standard error of $\eta$ and $t_{50}$ from the ensemble of accepted SFHs. Full article

This study explored how AI affects the sustainability of competitive advantage in the tourism and hospitality sector, with a particular focus on the mediating roles of digital culture and digital skills in the lens of the Technology Acceptance Model (TAM). Data were collected via a structured questionnaire distributed to a purposive sample of 488 managers and supervisors working in five-star hotels, travel agencies, and DMCs across Saudi Arabia. The findings revealed that AI has a significant direct effect on sustainable competitive advantage and also exerts strong positive effects on both digital culture and digital skills. In turn, both of these internal enablers significantly contribute to sustaining a competitive advantage. Mediation analysis further showed that both digital culture and digital skills partially mediate the relationship between AI and sustainable competitiveness. The study addresses a notable gap in tourism research by providing localized evidence from a market undergoing rapid transformation under Vision 2030, and, taken together, extends TAM to an organizational lens by demonstrating AI’s role in shaping culture and skills that underpin a durable advantage while pointing to actionable priorities—targeting high-value AI use cases, conducting capability audits, institutionalizing continuous learning through visible leadership and role-based upskilling, and embedding culture- and skills-oriented KPIs within AI governance. Full article

Synthetic aperture radar (SAR) ship detection faces significant challenges due to complex marine backgrounds, diverse ship scales and shapes, and the demand for lightweight algorithms. Traditional methods, such as constant false alarm rate and edge detection, often underperform in such scenarios. Although deep learning approaches have advanced detection capabilities, they frequently struggle to balance performance and efficiency. Algorithms of the YOLO series offer real-time detection with high efficiency, but their accuracy in intricate SAR environments remains limited. To address these issues, this paper proposes a lightweight SAR ship detection method based on the YOLOv10 framework, optimized across several key modules. The backbone network introduces a StarNet structure with multi-scale convolutional kernels, dilated convolutions, and an ECA module to enhance feature extraction and reduce computational complexity. The neck network utilizes a lightweight C2fGSConv structure, improving multi-scale feature fusion while reducing computation and parameter count. The detection head employs a dual assignment strategy and depthwise separable convolutions to minimize computational overhead. Furthermore, a hybrid loss function combining classification loss, bounding box regression loss, and focal distribution loss is designed to boost detection accuracy and robustness. Experiments on the SSDD and HRSID datasets demonstrate that the proposed method achieves superior performance, with a parameter count of 1.4 million and 5.4 billion FLOPs, and it achieves higher AP and accuracy compared to existing algorithms under various scenarios and scales. Ablation studies confirm the effectiveness of each module, and the results show that the proposed approach surpasses most current methods in both parameter efficiency and detection accuracy. Full article

We present the results of Doppler Imaging of the Ap star CU Vir in the silicon lines over the 1985–2011 time span, as well as multi-element imaging in the 2009/2011 epoch. The surface distribution of silicon in CU Vir exhibits stability over the approximately 26 years studied: the number, shape, and mutual distribution of the overabundance spots have remained unchanged. The modelling of the light curve based on the surface elemental distribution obtained with DI did not reveal any significant changes in the shape of the light curve that could explain the photometric phase shift observed in CU Vir. Consequently, the phase shifts and changes in the photometric period of CU Vir are caused by the rigid longitudinal drift of the surface-abundance structures. We performed simulations of the Tayler instability of the background magnetic field of CU Vir, and discuss the possibility of explaining the period variations by the drift of surface instability modes. Full article

Spilostethus pandurus is a phytophagous insect widely distributed across Asia, Europe, and Africa, yet its genetic variation remains poorly understood. This study presents the first comprehensive analysis of the genetic diversity and structure of S. pandurus in Thailand using mitochondrial cytochrome c oxidase subunit 1 (CO1) sequences from 202 individuals across 27 localities. A total of 58 haplotypes were identified, with high haplotype and nucleotide diversity observed, suggesting substantial genetic variation. The haplotype network revealed a star-like topology, indicating recent population expansion or ongoing gene flow. Neutrality tests and mismatch distribution analyses showed no strong signal of recent demographic expansion. Phylogenetic analysis confirmed that all Thai specimens clustered within a well-supported S. pandurus clade along with sequences from India, Namibia, and Europe. Analysis of Molecular Variance (AMOVA) revealed significant genetic differentiation among four continental groups, indicating that geographic isolation and restricted gene flow have shaped genetic divergence at a broad biogeographic scale. Further research using highly polymorphic nuclear markers is recommended to better resolve the population structure and evolutionary history of S. pandurus in Thailand and beyond. Full article

Hypereutectic Al-Si alloys containing primary Si exhibit unique material properties that make them suitable for various industrial applications. Understanding the characteristics of primary Si is crucial for predicting the effect of solidification conditions on the microstructure of these alloys. This paper presents a comprehensive characterisation study of primary Si in hypereutectic alloys. This study provides a detailed analysis of the size, distribution, and morphology of primary Si, providing valuable insights into the alloy structure, mechanical properties, and even the performance of the production process. The effect of forced melt flow by a rotating magnetic field (RMF) and solid/liquid front velocity on the size and morphology of primary Si in a hypereutectic Al-18 wt.% Si alloy was investigated. The purpose of using the RMF technique during the solidification process of Al-Si alloys is to enhance the alloy’s microstructure by inducing electromagnetic stirring. The hypereutectic samples were solidified at five different front velocities (0.02, 0.04, 0.08, 0.2, and 0.4 mm/s), under an average temperature gradient (G) of 8 K/mm, in a crystalliser equipped with an RMF inductor. Each sample was divided into two parts: the first solidified without stirring, while the second underwent electromagnetic stirring using RMF at an induction (B) of 7.2 mT. The results revealed that increasing the front velocity during solidification refined the primary Si in stirred and non-stirred parts. In non-stirred parts, it decreased dendritic forms and increased star-like Si, while polyhedral shapes remained nearly constant. Stirred parts showed stable Si morphology across velocities. Higher velocities also promoted equiaxed over elongated Si forms in both parts. Full article

The choice of constellations largely affects the performance of both wireless and optical communications. To address increasing capacity requirements, constellation shaping, especially for high-order modulations, is imperative in high-speed coherent communication systems. This paper, thus, proposes novel mutual information neural estimation (MINE)-based geometric, probabilistic, and joint constellation shaping schemes, i.e., the MINE-GCS, MINE-PCS, and MINE-JCS, to maximize mutual information (MI) via emerging deep learning (DL) techniques. Innovatively, we first introduce the MINE module to effectively estimate and maximize MI through backpropagation, without clear knowledge of the channel state information. Then, we train encoder and probability generator networks with different signal-to-noise ratios to optimize the distribution locations and probabilities of the points, respectively. Note that MINE transforms the precise MI calculation problem into a parameter optimization problem. Our MINE-based schemes only optimize the transmitter end, and avoid the computational and structural complexity in traditional shaping. All the designs were verified through simulations as having superior performance for MI, among which the MINE-JCS undoubtedly performed the best for additive white Gaussian noise, compared to the unshaped QAMs and even the end-to-end training and other DL-based joint shaping schemes. For example, the low-order 8-ary MINE-GCS could achieve an MI gain of about 0.1 bits/symbol compared to the unshaped Star-8QAM. It is worth emphasizing that our proposed schemes achieve a balance between implementation complexity and MI performance, and they are expected to be applied in various practical scenarios with different noise and fading levels in the future. Full article

Recent studies have focused on how spinning black holes (BHs) within a binary system containing a strongly magnetized neutron star, then immersed in external magnetic fields, can acquire charge through mechanisms like the Wald process and how this charge could power pulsar-like electromagnetic radiation. Those objects called “Black hole pulsar” mimic the behaviour of a traditional pulsar, and they can generate electromagnetic fields, such as magnetic dipoles. Charged particles within an accretion disk around the black hole would then be influenced not only by the gravitational forces but also by electromagnetic forces, leading to different geometries and dynamics. In this context, we focus here on the interplay of the magnetic dipole and the accretion disk. We construct the equilibrium structures of non-conducting charged perfect fluids orbiting Kerr black holes under the influence of a dipole magnetic field aligned with the rotation axis of the BH. The dynamics of the accretion disk in such a system are shaped by a complex interplay between the non-uniform, non-Keplerian angular momentum distribution, the black hole’s induced magnetic dipole, and the fluid’s charge. We show how these factors jointly influence key properties of the disk, such as its geometry, aspect ratio, size, and rest mass density. Full article

Spatial distribution is a critical factor influencing the success or failure of hotel management. This study examines the spatial distribution patterns of foreign star-rated hotels in China from 2000 to 2015 based on 27 typical city cases, using global and local spatial autocorrelation methods within GIS spatial analysis. The research explores the evolution of these patterns, analyzes key characteristics, and combines these insights with a stepwise regression method. Pearson correlation analysis is used to identify factors that influence the evolution of the spatial pattern. This study reveals that, first, the Z-value of global spatial autocorrelation of foreign star-rated hotels in China decreases from 2.38 to 1.63, indicating that the spatial distribution of foreign star-rated hotels in China has shifted from imbalanced to balanced, transitioning from economically developed regions such as areas with overseas Chinese populations, provincial capitals, and municipalities directly under central government control, toward tourist cities. Second, star-rated hotels hold a critical position within the spatial pattern, highlighting their central role in shaping the hospitality landscape. Third, the spatial distribution of foreign star-rated hotels is primarily influenced by the number of inbound tourists, followed by the presence of scenic spots rated 4A and above. The influence of other factors is found to be less significant. Fourth, the correlation coefficient between tourism demand and foreign star-rated hotels increased by 0.004, whereas the correlation coefficient between tourism supply and foreign star-rated hotels decreased by 0.036, indicating that market factors are playing an increasingly important role in shaping the evolution of foreign star-rated hotels in China, reflecting broader market dynamics. This study provides practical guidance for local Chinese hotels facing competition from foreign-funded establishments and offers theoretical insight into the strategic implementation of transnational operations. It points out the expansion direction of local Chinese hotels across different developmental stages. Full article

The stellar initial mass function (IMF) represents a fundamental quantity in astrophysics and cosmology describing the mass distribution of stars from low mass all the way up to massive and very massive stars. It is intimately linked to a wide variety of topics, including stellar and binary evolution, galaxy evolution, chemical enrichment, and cosmological reionization. Nonetheless, the IMF still remains highly uncertain. In this work, we aim to determine the IMF with a novel approach based on the observed rates of transients of stellar origin. We parametrize the IMF with a simple but flexible Larson shape, and insert it into a parametric model for the cosmic UV luminosity density, local stellar mass density, type Ia supernova (SN Ia), core-collapse supernova (CCSN), and long gamma-ray burst (LGRB) rates as a function of redshift. We constrain our free parameters by matching the model predictions to a set of empirical determinations for the corresponding quantities via a Bayesian Markov Chain Monte Carlo method. Remarkably, we are able to provide an independent IMF determination with a characteristic mass $m_c=0.{10}_{-0.08}^{+0.24}{\mathrm{M}}_{\odot }$ and high-mass slope $\xi =-2.{53}_{-0.27}^{+0.24}$ that are in accordance with the widely used IMF parameterizations (e.g., Salpeter, Kroupa, Chabrier). Moreover, the adoption of an up-to-date recipe for the cosmic metallicity evolution allows us to constrain the maximum metallicity of LGRB progenitors to $Z_{max}=0.{12}_{-0.05}^{+0.29}{\mathrm{Z}}_{\odot }$. We also find which progenitor fraction actually leads to SN Ia or LGRB emission (e.g., due to binary interaction or jet-launching conditions), put constraints on the CCSN and LGRB progenitor mass ranges, and test the IMF universality. These results show the potential of this kind of approach for studying the IMF, its putative evolution with the galactic environment and cosmic history, and the properties of SN Ia, CCSN, and LGRB progenitors, especially considering the wealth of data incoming in the future. Full article

The mitochondrial cytochrome c oxidase subunit I (COI) genes of six endangered goose breeds (Xupu, Yangjiang, Yan, Wuzong, Baizi, and Lingxian) were sequenced and compared to assess the genetic diversity of endangered goose breeds. By constructing phylogenetic trees and evolutionary maps of genetic relationships, the affinities and degrees of genetic variations among the six different breeds were revealed. A total of 92 polymorphic sites were detected in the 741 bp sequence of the mtDNA COI gene after shear correction, and the GC content of the processed sequence (51.11%) was higher than that of the AT content (48.89%). The polymorphic loci within the populations of five of the six breeds (Xupu, Yangjiang, Yan, Baizi, and Lingxian) were more than 10, the haplotype diversity > 0.5, and the nucleotide diversity (Pi) > 0.005, with the Baizi geese being the exception. A total of 35 haplotypes were detected based on nucleotide variation among sequences, and the goose breed haplotypes showed a central star-shaped dispersion; the FST values were −0.03781 to 0.02645, The greatest genetic differentiation (FST = 0.02645) was observed in Yan and Wuzong breeds. The most frequent genetic exchange (Nm > 15.00) was between the Wuzong and Yangjiang geese. An analysis of molecular variance showed that the population genetic variation mainly came from within the population; the base mismatch differential distribution analysis of the goose breeds and the Tajima’s D and Fu’s Fs neutral detection of the historical occurrence dynamics of their populations were negative (p > 0.10). The distribution curve of the base mismatches showed a multimodal peak, which indicated that the population tended to be stabilised. These results provide important genetic information for the conservation and management of endangered goose breeds and a scientific basis for the development of effective conservation strategies. Full article

Barred galaxies constitute about two-thirds of observed disc galaxies. Bars affect not only the mass distribution of gas and stars but also that of the dark matter. An elongation of the inner dark matter halo is known as the halo bar. We aim to characterize the structure of the halo bars, with the goal of correlating them with the properties of the stellar bars. We use a suite of simulated galaxies with various bar strengths, including gas and star formation. We quantify the strengths, shapes, and densities of these simulated stellar bars. We carry out numerical experiments with frozen and analytic potentials in order to understand the role played by a live responsive stellar bar. We find that the halo bar generally follows the trends of the disc bar. The strengths of the halo and stellar bars are tightly correlated. Stronger bars induce a slight increase in dark matter density within the inner halo. Numerical experiments show that a non-responsive frozen stellar bar would be capable of inducing a dark matter bar, but it would be weaker than the live case by a factor of roughly two. Full article