Search Results (974)

Wheat viruses are major yield-reducing factors, with mixed infections causing substantial economic losses. Determining field virus populations is crucial for effective management and developing virus-resistant cultivars. This study utilized the high-throughput Oxford Nanopore sequencing technique (ONT) to characterize wheat viral populations in major wheat-growing counties of Kansas from 2019 to 2021. Wheat leaves exhibiting virus-like symptoms were collected, total RNA was extracted, and cDNA libraries were prepared using a PCR-cDNA barcoding kit, then loaded onto ONT MinION flow cells. Sequencing reads aligned with cereal virus references identified eight wheat virus species. Tritimovirus tritici (wheat streak mosaic virus, WSMV), Poacevirus tritici (Triticum mosaic virus TriMV), Bromovirus BMV (brome mosaic virus BMV), as well as Emaravirus tritici, Luteovirus pavhordei, L. sgvhordei, Bymovirus tritici, and Furovirus tritici. Mixed infections involving two to five viruses in a single sample were common, with the most prevalent being WSMV + TriMV at 16.7% and WSMV + TriMV + BMV at 11.9%. Phylogenetic analysis revealed a wide distribution of WSMV isolates, including European and recombinant variants. A phylogenetic analysis of Emaravirus tritici based on RNA 3A and 3B segments and whole-genome characterization of Furovirus tritici were also conducted. These findings advance understanding of genetic variability, phylogenetics, and viral co-infections, supporting the development of sustainable management practices through host genetic resistance. Full article

Reducing energy consumption in buildings is critical to reducing CO₂ emissions and mitigating global warming. Studies have shown that heating and cooling loads account for more than 40% of building energy consumption, and thermochromic glass (TCG) with dynamically adjustable solar transmittance is an excellent way to reduce this load. Although a large number of studies have tested the spectral parameters of TCG in totally transparent and totally turbid states, the impact of dynamic changes in optical properties on the simulation accuracy of building energy consumption has been neglected. In this study, a method is proposed for a hydrogel-type TCG to dynamically test its spectral parameters based on spectrophotometry. The method uses a spectrophotometer and a PID heater to achieve the dynamic optical parameter testing of TCGs at different temperatures. In this paper, the transmission and reflection spectra of the two TCGs at 20~25 °C, 30~35 °C, 40 °C, 45 °C, 50 °C, and 55 °C were obtained, and the regression segmentation functions of visible transmittance and solar transmittance were established. The R² of the function model is 0.99. In addition, the test results show that the thermochromic glass selected in this paper can selectively transmit different wavelengths of light, and its transmission mainly occurs in the visible and near-infrared wavelengths from 320 to 1420 nm, while the transmission rate of other wavelengths is very low. As the temperature increases, the visible, solar, and ultraviolet transmittances decrease at a similar rate. In addition, the higher the temperature acting on the thermochromic (TC) layer, the greater its haze. Full article

Nuclear magnetic resonance (NMR) and high-pressure mercury injection (HPMI) have been widely used as common characterization methods of pore-throat. It is generally believed that there is a power function relationship between transverse relaxation time (T₂) and pore-throat radius (r), but the segmentation process of the pore-throat interval is subjective, which affects the conversion accuracy. In this paper, ordered clustering is used to improve the existing segmentation method of the pore-throat interval, eliminate the subjectivity in the segmentation process, and obtain a more accurate distribution curve of the pore-throat. For the three kinds of cores with ordinary-low permeability (K > 1 mD), ultra-low permeability (0.1 mD < K < 1 mD), and super-low permeability (K < 0.1 mD), the pore-throat distribution curves of the cores were obtained by using the improved T₂ conversion method. Then, the oil and gas two-phase displacement experiment was carried out to investigate the degree of recovery and cumulative gas–oil ratio changes during the displacement process. Finally, the converted T₂ spectrum was used to quantify the utilization of different pore sizes. The improved T₂ conversion method not only has better accuracy but also is not limited by the pore-throat distribution types (such as unimodal, bimodal, and multi-modal, etc.) and is suitable for any core with measured HPMI pore-throat distribution and an NMR T₂ spectrum. Combined with the results of core displacement and the degree of pore-throat utilization, it is found that the potential of miscible flooding to improve the recovery degree is in the order of ordinary-low permeability core (18–22%), ultra-low permeability core (25–29%), and super-low permeability core (8–12%). The utilization degree of immiscible flooding to the <10 nm pore-throat is low (up to 35%), while miscible flooding can effectively use the <3.7 nm pore-throat (up to 73%). The development effect of supercritical CO₂ flooding on K < 0.1 mD reservoirs is not good, the seepage resistance of CO₂ is large, the miscible flooding makes it difficult to improve the recovery degree, and the utilization effect of pore-throat is poor. Full article

Assessing vines’ vigour is essential for vineyard management and automatization of viticulture machines, including shaking adjustments of berry harvesters during grape harvest or leaf pruning applications. To address these problems, based on a standardized growth class assessment, labeled ground truth data of precisely located grapevines were predicted with specifically selected Machine Learning (ML) classifiers (Random Forest Classifier (RFC), Support Vector Machines (SVM)), utilizing multispectral UAV (Unmanned Aerial Vehicle) sensor data. The input features for ML model training comprise spectral, structural, and texture feature types generated from multispectral orthomosaics (spectral features), Digital Terrain and Surface Models (DTM/DSM- structural features), and Gray-Level Co-occurrence Matrix (GLCM) calculations (texture features). The specific features were selected based on extensive literature research, including especially the fields of precision agri- and viticulture. To integrate only vine canopy-exclusive features into ML classifications, different feature types were extracted and spatially aggregated (zonal statistics), based on a combined pixel- and object-based image-segmentation-technique-created vine row mask around each single grapevine position. The extracted canopy features were progressively grouped into seven input feature groups for model training. Model overall performance metrics were optimized with grid search-based hyperparameter tuning and repeated-k-fold-cross-validation. Finally, ML-based growth class prediction results were extensively discussed and evaluated for overall (accuracy, f1-weighted) and growth class specific- classification metrics (accuracy, user- and producer accuracy). Full article

This study investigates the use of iron ore tailings (IOTs) as recycled aggregates in segmental blocks, focusing on technical performance, CO₂ emissions, and embodied energy using the cradle-to-gate approach. IOTs replaced fine aggregates in concrete at 25%, 50%, and 75% by volume, achieving compressive strengths of 16.23 MPa, 10.02 MPa, and 3.93 MPa, respectively. Raw material production accounted for 98% of CO₂ emissions and 86% of embodied energy. Producing blocks at mining sites offered limited environmental benefits due to longer transport distances. Despite this, the results showed a 6% reduction in CO₂ emissions and a 35% improvement in mechanical–environmental performance (CO₂ emissions weighted by compressive strength) compared to traditional concrete. These findings underscore the potential of IOT-based concrete for segmental block production. Full article

This research proposed the method of using cumulative positive and negative elevation increment indicators based on road segment to identify the slope characteristics of mountain city roads. Furthermore, it proposed the adoption of these indicators, combined with driving dynamics and emission theory, to analyze the correlation mechanism between the road slope and the actual driving fuel consumption and emissions. Three routes with different slope characteristics were selected in the mountain city of Chongqing, and six road driving tests were conducted using a Class N2 heavy-duty diesel vehicle. Finally, a comprehensive and in-depth study on fuel consumption and emission characteristics was carried out. The results show that the cumulative positive and negative elevation increment indicators based on road segment can correctly identify the complex slope characteristics of mountain city roads. Moreover, using the above indicators, the research method based on the theory of driving dynamics and emission successfully revealed the correlation mechanism between the slope of mountain city roads and the fuel consumption and emissions. Overall, the changes in fuel consumption factor and pollutants CO, NO_X, and PN are positively correlated with the change in slope. The increase in slope leads to a rise in load, thereby increasing the required power, fuel consumption, and rich combustion conditions, ultimately leading to an increase in pollutants. It should be noted that driving dynamics also affect fuel consumption and emissions, leading to the specific rate of change between slope and fuel consumption not being consistent and a significant increase in the PN (Particulate Number) on some road sections. In addition, exhaust gas temperature may have a certain impact on emissions. Full article

Rift Valley fever phlebovirus (RVFV) is a zoonotic mosquito-borne pathogen endemic to sub-Saharan Africa and the Arabian Peninsula which causes Rift Valley fever in ruminant livestock and humans. Co-infection with divergent viral strains can produce reassortment among the L, S, and M segments of the RVFV genome. Reassortment events can produce novel genotypes with altered virulence, transmission dynamics, and/or mosquito host range. This can have severe implications in areas where RVFV is endemic and convolutes our ability to anticipate transmission and circulation in novel geographic regions. Previously, we evaluated the frequency of RVFV reassortment in a susceptible ruminant host and observed low rates of reassortment (0–1.7%). Here, we tested the hypothesis that reassortment occurs predominantly in the mosquito using a highly permissive vector, Culex tarsalis. Cells derived from Cx. tarsalis or adult mosquitoes were co-infected with either two virulent (Kenya-128B-15 and SA01-1322) or a virulent and attenuated (Kenya-128B-15 and MP-12) strain of RVFV. Our results showed approximately 2% of virus genotypes isolated from co-infected Cx. tarsalis-derived cells were reassortant. Co-infected mosquitoes infected via infectious bloodmeal resulted in a higher percentage of reassortant virus (2–60%) isolated from midgut and salivary tissues at 14 days post-infection. The percentage of reassortant genotypes isolated from the midguts of mosquitoes co-infected with Kenya-128B-15 and SA01-1322 was similar to that of mosquitoes co-infected with Kenya-128B-15 and MP-12- strains (60 vs. 47%). However, only 2% of virus isolated from the salivary glands of Kenya-128B-15 and SA01-1322 co-infected mosquitoes represented reassortant genotypes. This was contrasted by 54% reassortment in the salivary glands of mosquitoes co-infected with Kenya-128B-15 and MP-12 strains. Furthermore, we observed preferential inclusion of genomic segments from the three parental strains among the reassorted viruses. Replication curves of select reassorted genotypes were significantly higher in Vero cells but not in Culex—derived cells. These data imply that mosquitoes play a crucial role in the reassortment of RVFV and potentially contribute to driving evolution of the virus. Full article

In this paper, the status quo of manufacturing technology of the wing structures of large and small general aircraft at home and abroad is reported. The existing problems in the manufacturing technology of double-beam, multi-rib composite wing structures are analyzed. The application of adhesive co-curing technology to manufacture eVTOL double-beam, multi-rib integral composite wing box segment structures is proposed. Composite-material wing box segment adhesive co-curing manufacturing technology realizes the high-quality manufacturing of double-beam, multi-rib integral wing box segment structures and the optimal lightweight design of such structures. It can be applied to the manufacture of this type of integral wing box segment structure or the manufacture of other complex integral composite components. Full article

Malaria remains a global health concern, with 249 million cases and 608,000 deaths being reported by the WHO in 2022. Traditional diagnostic methods often struggle with inconsistent stain quality, lighting variations, and limited resources in endemic regions, making manual detection time-intensive and error-prone. This study introduces an automated system for analyzing Romanowsky-stained thick blood smears, focusing on image quality evaluation, leukocyte detection, and malaria parasite classification. Using a dataset of 1000 clinically diagnosed images, we applied feature extraction techniques, including histogram bins and texture analysis with the gray level co-occurrence matrix (GLCM), alongside support vector machines (SVMs), for image quality assessment. Leukocyte detection employed optimal thresholding segmentation utility (OTSU) thresholding, binary masking, and erosion, followed by the connected components algorithm. Parasite detection used high-intensity region selection and adaptive bounding boxes, followed by a custom convolutional neural network (CNN) for candidate identification. A second CNN classified parasites into trophozoites, schizonts, and gametocytes. The system achieved an F1-score of 95% for image quality evaluation, 88.92% for leukocyte detection, and 82.10% for parasite detection. The F1-score—a metric balancing precision (correctly identified positives) and recall (correctly detected instances out of actual positives)—is especially valuable for assessing models on imbalanced datasets. In parasite stage classification, CNN achieved F1-scores of 85% for trophozoites, 88% for schizonts, and 83% for gametocytes. This study introduces a robust and scalable automated system that addresses critical challenges in malaria diagnosis by integrating advanced image quality assessment and deep learning techniques for parasite detection and classification. This system’s adaptability to low-resource settings underscores its potential to improve malaria diagnostics globally. Full article

The laser-beam powder-bed fusion (PBF-LB) method enables the semi-automatic fabrication of complex three-dimensional structures, making it useful for dental prostheses. However, residual stress during fabrication can cause deformation. Herein, we applied the segmented-scan strategy to three-unit fixed dental prostheses (FDPs) and evaluated its effects on residual stress and fit accuracy compared to conventional methods. Three-unit FDPs consisting of two abutments and a pontic were fabricated using a PBF-LB machine with Co-Cr-Mo powder. In the segmented-scan group, pontics and abutments were scanned separately to shorten the scan vector. Fit accuracy was assessed by measuring the gap between the abutment and the FDPs. Residual stress was measured in the X and Y directions at three points using X-ray diffraction, while CT scans were used to count internal microstructures. The residual stress was lower in the X-direction in the segmented-scan group (24.61–217.17 MPa, respectively) than in the control group (187.70–293.71 MPa, respectively). However, no significant differences in fit accuracy were observed (p < 0.05). The segmented-scan strategy reduced residual stress in the X-direction but did not improve the fit accuracy. Applying this strategy to dental prosthetic devices can shorten the scan vector and reduce residual stress. Full article

In deep brine oil and gas injection–production operations, the combined long-term effects of brine and carbon dioxide on rock mechanical properties are not clear. In order to solve this problem, the influence of long-term salt–CO₂ environment on the mechanical properties of sandstone is discussed. The mechanism of interaction evolution and fracture propagation was studied in detail by NMR, the triaxial compression test and a CT scan. The results show that the triaxial compressive strength and mass of sandstone decrease first and then increase with the prolonging of soaking time. The proportion of micropores first decreased and then increased, while the proportion of medium and large pores first increased and then decreased. The pores obtained by Avizo’s segmentation of the threshold value of CT sections first increased and then decreased, and the fractal dimensions obtained first increased and then decreased. In particular, the calcium ions in the immersion solution increased first and then decreased. The reaction rate was obtained and verified according to the changes in calcium carbonate mass and calcium ion mineralization at different times. The failure mode of the sample gradually changed from /-shaped failure to V-shaped composite failure, then to local /-shaped failure, and finally to X-shaped composite failure. On this basis, the process of sandstone was divided into the dissolution stage, precipitation stage and secondary dissolution stage, and the rock microstructure change model under a salt–CO₂ environment was established. The mechanics, temperature, chemical interaction mechanism and fracture propagation mechanism of sandstone under a salt–CO₂ environment are discussed. Full article

Background: Charcot–Marie–Tooth (CMT) disease is an inherited peripheral neuropathy primarily involving motor and sensory neurons. Mutations in INF2, an actin assembly factor, cause two diseases: peripheral neuropathy CMT-DIE (MIM614455) and/or focal segmental glomerulosclerosis (FSGS). These two phenotypes arise from the progressive degeneration affecting podocytes and Schwann cells. In general, nerve enlargement has been reported in 25% of the demyelinating CMT subtype (CMT1), while little is known about the CMT-DIE caused by INF2 variants. Methods: To characterize the peripheral nerve phenotype of INF2-related CMT, we studied the clinical course, imaging, histology, and germline genetic variants in two unrelated CMT-DIE patients. Results: Patient 1 (INF2 p.Gly73Asp) and patient 2 (p.Val108Asp) first noticed walking difficulties at 10 to 12 years old. Both of them were electrophysiologically diagnosed with demyelinating neuropathy. In patient 2, the sural nerve biopsy revealed an onion bulb formation. Both patients developed nephrotic syndrome almost simultaneously with CMT and progressed into renal failure at the age of 16 to 17 years. Around the age of 30 years, both patients manifested multiple hypertrophy of the trunk, plexus, and root in the cervical, brachial, lumbosacral nerves, and cauda equina. The histology of the cervical mass in patient 2 revealed Schwannoma. Exome analysis showed that patient 2 harbors a germline LZTR1 p.Arg68Gly variant, while patient 1 has no schwannomatosis-related mutations. Conclusions: Peripheral neuropathy caused by INF2 variants may lead to the development of multifocal hypertrophy with age, likely due to the initial demyelination and subsequent Schwann cell proliferation. Schwannoma could co-occur when the tissues attain additional hits in schwannomatosis-related genes (e.g., LZTR1). Full article

Mediterranean diet adherence has been decreasing during the last few decades, and non-appropriate snacking habits have also been identified among Mediterranean children and adolescents. To co-create new snacks and to explore children’s interests and preferences, a multi-method approach was used in the present study, including some qualitative and quantitative research phases. Conducted in collaboration with schools in Lebanon, Egypt, Portugal, Italy, and Spain, different snack prototypes were designed and tested in a Mediterranean cross-cultural context. The results showed significant differences among countries in snacking preferences and general food-related attitudes. Italian children exhibited higher levels of neophobia, resulting in lower acceptance of all proposed snacks. Some sensory and contextual insights were collected, such as Egyptian children favoring sweet and crunchy textures and “At school”, “With my friends”, and “As a morning/afternoon snack” being identified as linked to snack acceptance in some countries. The present study underscores the value of co-creation processes involving children to address non-recommended dietary patterns, highlighting the critical role of sensory properties, cultural differences, and contextual factors in designing healthy snacks that meet the Mediterranean diet’s principles but are highly appreciated by the young segment of the population. Full article

Bombyx mori bidensovirus (BmBDV), a significant pathogen in the sericulture industry, holds a unique taxonomic position due to its distinct segmented single-stranded DNA (ssDNA) genome and the presence of a self-encoding DNA polymerase. However, the functions of viral non-structural proteins, such as NS2, remain unknown. This protein is hypothesized to play a role in viral replication and pathogenesis. To investigate its structure and function, we employed phylogenetic analysis, subcellular localization, mutational analysis, and a dual-luciferase reporter system to characterize the nuclear localization signal (NLS) within NS2 and its effect on viral promoter activity. Additionally, co-immunoprecipitation and mass spectrometry were utilized to identify host proteins interacting with NS2. We identified a functional bipartite NLS in NS2, validated the combination pattern of key amino acids, and demonstrated its role in regulating viral promoter activity. Furthermore, we identified potential NLSs in NS2 homologs in other invertebrate ssDNA viruses based on sequence analysis. We also revealed interactions between NS2 and host nuclear transport proteins, suggesting that it plays a role in nuclear transport and viral replication. This research underscores the importance of NS2’s NLS in BmBDV’s life cycle and its potential conservation across invertebrate ssDNA viruses, providing insights into virus–host interactions and avenues for antiviral strategy development. Full article

Since private cars and vans accounted for more than 25% of global oil consumption and about 10% of energy-related CO₂ emissions in 2022, increasing the share of electric vehicle (EV) ownership is considered an important solution for reducing CO₂ emissions. At the same time, reducing emissions entails certain economic losses for those countries whose exports are largely covered by the oil trade. The explosive growth of the EV segment over the past 15 years has given rise to overly optimistic forecasts for global EV penetration by 2050. One of the major obstacles to such a development scenario is the limited availability of resources, especially critical materials. This paper proposes a mathematical model to predict the global EV fleet based on the limited availability of critical materials such as lithium, one of the key elements for battery production. The proposed model has three distinctive features. First, it shows that the classical logistic function, due to the specificity of its structure, cannot correctly describe market saturation in the case of using resources with limited serves. Second, even the use of a special multiplier that describes the market saturation process taking into account the depletion (finiteness) of the used resource does not obtain satisfactory economic results because of the “high speed” depletion of this resource. Third, the analytical solution of the final model indicates the point in time at which changes in saturation rate occur. The latter situation allows us to determine the tracking of market saturation, which is more similar to the process that is actually occurring. We believe that this model can also be validated to estimate the production of wind turbines that use rare earth elements such as neodymium and dysprosium (for the production of powerful and permanent magnets for wind turbines). These results also suggest the need for oil-exporting countries to technologically diversify their economies to minimize losses in the transition to a low-carbon economy. Full article