Search Results (43)

The fruiting stage of soybean (Glycine max L.) is critical for determining both its yield and quality, thereby influencing global production. While some studies have provided partial explanations for the occurrence of Fusarium species on soybean seeds and pods, the fungal diversity affecting soybean pods in Sichuan Province, a major soybean cultivation region in Southwestern China, remains inadequately understood. In this study, 182 infected pods were collected from a maize–soybean relay strip intercropping system. A total of 10 distinct pod-infecting fungal genera (132 isolates) were identified, and their pathogenic potential on soybean seeds and pods was evaluated. Using morphological characteristics and DNA barcode markers, we identified 43 Fusarium isolates belonging to 8 species, including F. verticillioides, F. incarnatum, F. equiseti, F. proliferatum, F. fujikuroi, F. oxysporum, F. chlamydosporum, and F. acutatum through the analysis of the translation elongation factor gene (EF1-α) and RNA polymerases II second largest subunit (RPB2) gene. Multi-locus phylogenetic analysis, incorporating the Internal Transcribed Spacer (rDNA ITS), β-tubulin (β-tubulin), Glyceraldehyde 3-phosphate dehydrogenase (GADPH), Chitin Synthase 1 (CHS-1), Actin (ACT), Beta-tubulin II (TUB2), and Calmodulin (CAL) genes distinguished 37 isolates as 6 Colletotrichum species, including C. truncatum, C. karstii, C. cliviicola, C. plurivorum, C. boninense, and C. fructicola. Among these, F. proliferatum and C. fructicola were the most dominant species, representing 20.93% and 21.62% of the isolation frequency, respectively. Pathogenicity assays revealed significant damage from both Fusarium and Colletotrichum isolates on soybean pods and seeds, with varying isolation frequencies. Of these, F. proliferatum, F. acutatum, and F. verticillioides caused the most severe symptoms. Similarly, within Colletotrichum genus, C. fructicola was the most pathogenic, followed by C. truncatum, C. karstii, C. cliviicola, C. plurivorum, and C. boninense. Notably, F. acutatum, C. cliviicola, C. boninense, and C. fructicola were identified for the first time as pathogens of soybean pods under the maize–soybean strip intercropping system in Southwestern China. These findings highlight emerging virulent pathogens responsible for soybean pod decay and provide a valuable foundation for understanding the pathogen population during the later growth stages of soybean. Full article

Soils act as sources or sinks for three major greenhouse gases (CO₂, CH₄, and N₂O). Approximately 20% of global CO₂ emissions are released from soils through the soil respiration process. Soil respiration (soil CO₂ emission) can account for over 85% of ecosystem respiration. The aim of this study was to compare managed and unmanaged stands of pedunculate oak (Quercus robur L.) in order to investigate the impact of forest management on soil CO₂ emissions. We selected one managed and two unmanaged stands. The first stand (S1) represents a managed middle-aged stand, which is the optimal stage of development. The second stand (S2) belongs to the over-mature stage of development in an old-growth oak forest, while the third stand (S3) belongs to the decay stage of development in an old-growth oak forest. The closed chambers method was used for air sampling and the air samples were analyzed using gas chromatography (GC). Multiple regression models that include soil temperature (ST), soil moisture (SM), and their interaction provide a better explanation for variation in soil CO₂ emission (SCDE) (higher R² values) compared to regression models that only involve two variables (ST and SM). The study showed that SCDE in the decay stage of old-growth forest (S3) was significantly lower (p < 0.001) compared to the other two stands (S1 and S2). S3 is characterized by very low canopy cover and intensive natural regeneration, unlike S1 and S2. However, there were no significant differences in SCDE between the managed middle-aged stand (S1) and the over-mature (old-growth) stand (S2). Over a long-term rotation period in pedunculate oak forests, forest management practices that involve the periodic implementation of moderate silvicultural interventions can be deemed acceptable in terms of maintaining the carbon balance in the soil. Full article

Changes in health, lifestyle, and medication usage significantly impact overall well-being. Aging is associated with an increased need for multiple medications, or polypharmacy. Despite extensive research on how aging and polypharmacy affect the gut microbiome, relatively little is known about their impact on the oral microbiome and how shifts there can contribute to oral and systemic disease. An initial group of 55 saliva donors was formed of individuals with stage 3 periodontal disease and well-characterized for dental decay, both factors that contribute strongly to salivary microbiome identity. Relative levels of saliva bacteria were determined by 16S rRNA amplicon sequencing. Multiple variable analysis was performed to determine taxa associated with polypharmacy after correction for dental decay, tobacco use and gender. A second group, all with stage 3 periodontal disease, over 55 years of age and controlled for caries, served as a validation set. Two differences in taxa were validated as associated with polypharmacy in the elderly group. The tooth surface commensal Corynebacterium durum was lower with polypharmacy, and the dental decay-associated Propionibacterium acidifaciens was elevated. Saliva flow rate differences did not appear to be responsible for the differences seen in these taxa. Additionally, taxa associated with caries level and gender were identified. Polypharmacy associated taxa differences are potentially directly affected by medication usage, or the ailments associated with polypharmacy, and they are strong candidates to contribute to disease in the large group of elderly with poor oral health. Full article

Deep learning has demonstrated significant success in hyperspectral image (HSI) classification by effectively leveraging spatial–spectral feature learning. However, current approaches encounter three challenges: (1) high spectral redundancy and the presence of noisy bands, which impair the extraction of discriminative features; (2) limited spatial receptive fields inherent in convolutional operations; and (3) unidirectional context modeling that inadequately captures bidirectional dependencies in non-causal HSI data. To address these challenges, this paper proposes HG-Mamba, a novel hybrid geometry-aware bidirectional Mamba network for HSI classification. The proposed HG-Mamba synergistically integrates convolutional operations, geometry-aware filtering, and bidirectional state-space models (SSMs) to achieve robust spectral–spatial representation learning. The proposed framework comprises two stages. The first stage, termed spectral compression and discrimination enhancement, employs multi-scale spectral convolutions alongside a spectral bidirectional Mamba (SeBM) module to suppress redundant bands while modeling long-range spectral dependencies. The second stage, designated spatial structure perception and context modeling, incorporates a Gaussian Distance Decay (GDD) mechanism to adaptively reweight spatial neighbors based on geometric distances, coupled with a spatial bidirectional Mamba (SaBM) module for comprehensive global context modeling. The GDD mechanism facilitates boundary-aware feature extraction by prioritizing spatially proximate pixels, while the bidirectional SSMs mitigate unidirectional bias through parallel forward–backward state transitions. Extensiveexperiments on the Indian Pines, Houston2013, and WHU-Hi-LongKou datasets demonstrate the superior performance of HG-Mamba, achieving overall accuracies of 94.91%, 98.41%, and 98.67%, respectively. Full article

Epidemics spread through shipping networks and have dual characteristics as both biological sources of infection and triggers of cascading failures. However, existing resilience models fail to capture this dual and coupled dynamics. To minimize the cascading impacts of epidemics on global shipping networks, this paper proposes an innovative resilience assessment framework that considers the interaction between epidemic transmission and the shipping network cascading failure. First, a weighted shipping network topology is constructed based on route flow characteristics to quantify route frequency, stopping time, and the number of infected people, and the epidemic transmission across ports is modeled with an improved SEIR model, which contains a heterogeneous infectivity function and a dynamic transmission matrix, revealing a dual transmission mechanism inside and outside the ports. Second, a two-stage cascading failure model is developed: a direct failure triggered by infected people exceeding the threshold and an indirect failure triggered by the dynamic redistribution of loads. The load redistribution strategy is optimized to reconcile the residual port capacity and the risk of infection. Finally, a multidimensional resilience assessment framework covering structural destruction resistance, network efficiency, path redundancy, and a cascading failure propagation rate is constructed. Example validation shows that the improved load redistribution strategy reduces the maximum connected subgraph decay rate by 68.2%, reduces the cascading failure rate by 88%, and improves the peak network efficiency by 128.2%. In case of multi-source epidemics, the state of the network collapse can be shortened by 12 days if the following recovery strategy is adopted: initially repair high connectivity hubs (e.g., Port of Shanghai), and then repair high centrality nodes (e.g., Antwerp Port) to achieve a balance between recovery efficiency and network functionality. The research results reduce the risk of systemic disruptions in maritime networks and provide decision-making tools for dynamic port scheduling during pandemics. Full article

Preserving historical railway assets presents a complex systems challenge, in which uncertainties in material performance, structural degradation, and regulatory requirements directly impact long-term reliability and operational continuity. Traditional maintenance practices often limit the use of modern materials, introducing inefficiencies, increased lifecycle costs, and higher failure risk due to material ageing and environmental exposure. This study proposes a reliability-informed preservation framework that supports the integration of contemporary materials into historical railway infrastructure while accounting for legal, material, and procedural uncertainties. The framework is validated through two industrial case studies, each reflecting different regulatory and operational constraints. The first case demonstrates the successful substitution of timber with certified PVC cladding on a non-listed signal box, achieving improved durability, reduced maintenance intervals, and enhanced system reliability. The second case explores an unsuccessful attempt to replace decayed timber gables with aluminium, in which late-stage planning misalignment, underestimated risks, and uncertainty in approval outcomes led to a significant cost increase and reduced reliability regarding delivery. By systematically applying and evaluating the framework under real-world conditions, this research contributes to engineering asset management by introducing a structured method for mitigating regulatory and material uncertainties. Full article

This study develops a model to predict and explain short-term fluctuations in the Brazilian local currency interest rate term structure. The model relies on the potential relationship between these movements and key macroeconomic factors. The methodology consists of two stages. First, the Svensson model is applied to fit the daily yield curve data. This involves maximizing the R² statistic in an OLS regression, following the Nelson–Siegel approach. The median decay parameters are then fixed for subsequent estimations. In the second stage, with the daily yield curve estimates in hand, another OLS regression is conducted. This regression incorporates the idea that Svensson’s betas are influenced by macroeconomic variables. Full article

Fatigue damage to asphalt pavements due to continuous loading occurs mainly at the binder–aggregate interface or within the asphalt binder. The mechanical response of asphalt binder under variable stress conditions was comprehensively analyzed by repeated loading tests. The viscoelastic intervals of three asphalt binders (Pen70–80, Pen60–70, and SBS) were determined by stress scanning tests, and two different sizes of stresses were selected for constant stress time scanning inside and outside of the intervals based on the experimental thresholds, to provide a reference for the selection of load combinations for variable stress fatigue tests. Cyclic loading of the samples using DSR focused on the complex shear modulus and phase angle behavior of asphalt binder samples under linear viscoelastic (LVE) and nonlinear viscoelastic (NLVE) stresses. The study reveals that under LVE and NLVE stresses, asphalt binders exhibit different mechanical behaviors, each indicating different aspects of damage accumulation and recovery capabilities. Under LVE stress, asphalt binders demonstrate an initial rapid decay of modulus, followed by a phase of slowed degradation and then a swift decline leading to fatigue failure. This pattern contrasts with the response under NLVE stress, where a more pronounced and quicker degradation is observed in both the initial and final phases, indicating significant initial damage. Analyzing the experimental results, at small stresses within the online viscoelastic interval, the modulus decay of asphalt specimens mainly occurs at the late loading stage, and the phase angle growth also occurs mainly at the late loading stage, while at large stresses, the asphalt specimens produce a large amount of modulus decay at the early loading stage. Furthermore, the study explores the NLVE-LVE loading mode, observing a rapid recovery phase in the early stages of the second phase. This phase is characterized by an increase in modulus accompanied by a decrease in phase angle, indicating an increase in the elasticity of the specimen. However, in the LVE-NLVE mode, a rapid accumulation of damage is observed without a similar recovery phase, highlighting the impact of NLVE stress on inducing irreversible damage. The findings suggest a complex interplay between the type of stress applied and the mechanical response of asphalt binders, with significant implications for understanding the fatigue and recovery behavior of asphalt materials under variable stress conditions. The aim is to investigate the mechanical response and damage evolution law of asphalt binder under repeated loading of variable stress to provide reference for material selection and development of durable pavements. Full article

As a sustainable mode of transportation, the electric scooter offers residents a low-carbon, convenient, and fast travel option. However, its battery quality problem also brings safety risks that cannot be ignored. We construct eight different differential game models to investigate quality improvement strategies by battery makers and electric scooter manufacturers at the design and manufacturing stages. Our results show that the government subsidy is a better incentive for manufacturers to invest more in quality in the design and manufacturing steps than the cost-sharing contract. This leads to improvements in the product quality of electric scooters. The indicators of the discrete decision-making model without government subsidies and cost-sharing contracts are relatively low. Second, the quality of the electric scooter is affected by several key factors, including time, quality decay coefficient, and income distribution coefficient. Specifically, the quality of electric scooter products exhibits a positive correlation with time but gradually declines as the quality decay coefficient increases. Third, through specific numerical analyses, we further find that the income distribution coefficient affects the manufacturer’s product quality inputs in the design and manufacturing process, the optimal revenues of upstream and downstream manufacturers, the cost-sharing ratio, and the government subsidy rate to varying degrees. Full article

With increasingly stringent maritime environmental regulations, hybrid fuel cell ships have garnered significant attention due to their advantages in low emissions and high efficiency. However, challenges related to the coordinated control of multi-energy systems and fuel cell degradation remain significant barriers to their practical implementation. This paper proposes an innovative multi-timescale energy management strategy that focuses on optimizing the lifespan decay synergy of fuel cells and lithium batteries. The study designs an attention-based CNN-LSTM hybrid model for power prediction and constructs a two-stage optimization framework: The first stage employs Model Predictive Control (MPC) for long-term power planning to optimize equivalent hydrogen consumption, while the second stage focuses on real-time power allocation considering both power source degradation and system operational efficiency. The simulation results demonstrate that compared to single-layer MPC and the Equivalent Consumption Minimization Strategy (ECMS), the proposed method exhibits significant advantages in reducing single-voyage costs, minimizing differences in power source degradation rates, and alleviating power source stress. The overall performance of this strategy approaches the global optimal solution obtained through Dynamic Programming, comprehensively validating its superiority in simultaneously optimizing system economics and durability. Full article

Background: Coleoptera is the second-most significant insect group associated with decomposing carcasses, yet its role in the decomposition process and postmortem colonization following envenomation is poorly understood. Purpose of the Study: This study aimed to investigate the effects of the venoms from Cerastes cerastes and Naja haje on the decomposition of rabbit carcasses while evaluating the main beetle taxa attracted to these decaying remains. Methods: Three groups of rabbits, each with five individuals, were utilized. The first group was injected with the venom of Cerastes cerastes, the second with Naja haje venom, and the control group received 0.85% physiological saline before euthanasia with CO₂. Results: Four decomposition stages (fresh, bloating, decay, and dry) with durations varying based on venom type and carcass condition were observed. A total of 647 individual beetles of six species (Necrobia rufipes, Attagenus sp., Dermestes frischii, D. maculatus, Bledius sp., and Apentanodes sp.) belonging to four families (Cleridae, Dermestidae, Staphylinidae, and Tenebrionidae) were collected and identified. D. maculatus was the most abundant species. Fewer beetles were attracted to carcasses envenomed with N. haje compared to the other groups. Conclusions: Envenomation by snake venom influences the attraction and succession rate of necrophilous coleopterans to carcasses, which is important for forensic investigations. Full article

Background: First permanent molars (FPM) are highly susceptible to decay before the age of 15. When they are severely affected, the decision between conservation and extraction arises, particularly considering the potential for the second permanent molar (SPM) to replace the FPM. This cohort study aimed to evaluate clinical practices regarding FPM pulp necrosis treatment in children aged eight to twelve in two hospital departments in the Paris region. A second objective was to evaluate the one-year outcomes of the two therapies. Methods: A retrospective analysis was conducted using computerized billing software to identify patients aged eight to twelve who underwent either extraction or root canal treatment (RCT). Data collected included sex, age, arch involved, number of decayed surfaces, presence of Molar Incisor Hypomineralization (MIH), presence of infection, and treatment type. Results: A total of 66 patients were included, representing 61 extracted teeth and 23 RCT. Three main decision criteria were identified: presence of MIH (p < 0.005), extent of decay (p < 0.05), and SPM Nolla’s stage. A total of 48% of the patients were seen at one year. A total of 16 of the 32 extractions and five of the nine RCTs had favorable evolution (p = 1). Conclusions: The question of whether to perform RCT or extraction of necrotic FPM in children aged eight to twelve is difficult to assess. It appears that five criteria need to be considered before the decision: possibility of long-term sealed coronal reconstruction, SPM Nolla’s stage, follow-up possibilities, arch concerned, and presence of third permanent molar. Full article

With the growth of data in the real world, datasets often encounter the problem of long-tailed distribution of class sample sizes. In long-tailed image recognition, existing solutions usually adopt a class rebalancing strategy, such as reweighting based on the effective sample size of each class, which leans towards common classes in terms of higher accuracy. However, increasing the accuracy of rare classes while maintaining the accuracy of common classes is the key to solving the problem of long-tailed image recognition. This research explores a direction that balances the accuracy of both common and rare classes simultaneously. Firstly, a two-stage training is adopted, motivated by the use of transfer learning to balance features of common and rare classes. Secondly, a balanced weight function called Balanced Focal Softmax (BFS) loss is proposed, which combines balanced softmax loss focusing on common classes with balanced focal loss focusing on rare classes to achieve dual balance in long-tailed image recognition. Subsequently, a Balanced Weight Learning Mechanism (BWLM) to further utilize the feature of weight decay is proposed, where the weight decay as the weight balancing technique for the BFS loss tends to make the model learn smaller balanced weights by punishing the larger weights. Through extensive experiments on five long-tailed image datasets, it proves that transferring the weights from the first stage to the second stage can alleviate the bias of the naive models toward common classes. The proposed BWLM not only balances the weights of common and rare classes, but also greatly improves the accuracy of long-tailed image recognition and outperforms many state-of-the-art algorithms. Full article

This paper studies the decay law of low-temperature crack resistance performance of rubber powder basalt fiber composite-modified porous asphalt concrete (CM-PAC) under medium- and high-temperature water erosion. Firstly, the prepared Marshall specimens were subjected to water erosion treatment at different temperatures of 20 °C, 40 °C, and 60 °C for 0–15 days. Then, the processed specimens were subjected to low-temperature splitting tests, and acoustic emission data during the splitting test process were collected using an acoustic emission device. It can be seen that the low-temperature splitting strength and low-temperature splitting stiffness modulus of CM-PAC gradually decrease with the increase in water erosion time. The maximum reduction rates of the two compared to the control group reached 72.63% and 91.60%, respectively. The low-temperature splitting failure strain gradually increases. Under the same erosion time, the higher the temperature of water, the more significant the amplitude of changes in the above parameters. In addition, it is shown that as the water erosion time increases, the first stage of loading on the specimen gradually shortens, and the second and third stages gradually advance. As the water temperature increases and the water erosion time prolongs, the acoustic emission energy released by the CM-PAC specimen during the splitting process slightly decreases. The application of acoustic emission technology in the splitting process can clarify the changes in the failure pattern of CM-PAC specimens during the entire loading stage, which can better reveal the impact of medium- to high-temperature water on the performance degradation of CM-PAC. Full article

The deviation of conventional fungal niches is an important factor in the implications of hidden fungal diversity and global fungal numbers. The Xylariomycetidae (Sordariomycetes, Ascomycota), which is also referred to as xylarialean taxa, has a wide range of species that demonstrate a high degree of variation in their stromatic characteristics, showing either conspicuous or inconspicuous forms. In this study, samples were collected while focusing on temporal and spatial parameters and substrate characteristics. Based on internal transcribed spacer (ITS), 28S large subunit rDNA (LSU), RNA polymerase II second largest subunit (RPB2), and β-tubulin (TUB2) multigene phylogeny and morphology, five new species are introduced as Muscodor brunneascosporus, M. lamphunensis (Xylariaceae), Nigropunctata hydei, N. saccata (Incertae sedis), and Xenoanthostomella parvispora (Gyrotrichaceae). Plant substrates in the early stages of decay and attached to the host were feasible sample niches, with an emphasis on the collection of inconspicuous, hidden xylarialean species. The appearance of inconspicuous saprobic xylarialean forms during the rainy season may be linked to the change in nutritional mode, from endophytic mode during the dry season to saprobic in the wet. Therefore, it would be fascinating to concentrate future research on how seasonal fluctuations affect nutritional mode shifts, especially in northern Thailand, which would provide the optimal spatial characteristics. In order to establish a comprehensive linkage between endophytic and saprobic modes, it is imperative to have a substantial representation of endophytic isolate sequences resembling inconspicuous xylariaceous fungi within publicly accessible databases. Full article