Search Results (72,299)

Hand, foot, and mouth disease (HFMD), a common childhood infection caused by enterovirus, poses a serious public health concern in China. We collected and analyzed epidemiological data on 62,133 HFMD cases in Shenyang City, Liaoning Province, from 2013 to 2023. The average annual incidence was 76.12 per 100,000 person-years; 99.45% of cases were mild, while 0.55% were severe. Only one patient died. HFMD infections peaked annually in July. Children in kindergartens and scattered children accounted for 44.6% and 42.2% of cases, respectively. Real-time RT-PCR detection of enteroviruses in 5534 patient samples revealed 3780 positives, of which 25.1% were CVA16-positive. Positives were randomly sampled, yielding 240 VP1 sequences of CVA16. Phylogenetic tree results showed that all VP1 sequences belonged to the B1 sub-genogroup. However, the sub-genogroup prevalence varied over time: from 2013 to 2014 and 2019 to 2021, the predominant sub-genogroup was B1a, while it was B1b from 2015 to 2018. Further phylogenetic analyses showed substantial divergence between B1a branches in CVA16, suggesting possible turnover of the B1a sub-genogroup in CVA16 due to evolution. This study provides epidemiological data on HFMD in Shenyang, and provides a phylogenetic analysis of CVA16, offering a theoretical basis for preventing and controlling HFMD in Shenyang City. Full article

Damaged starch typically arises from mechanical damage caused by the action of the roller mills during the wheat flour milling process. The content of resulting damaged starch in the flour significantly influences its characteristics, emphasizing the importance of understanding and controlling the formation of damaged starch for the production of specialized flours. A detailed passage analysis from three different commercial mills revealed that starch damage control is primarily achievable at front passages of the sizing and reduction system, which generate the majority of the flour release in the mill. Also, it revealed that damaged starch content increases progressively from the initial to the final passages during milling in the break, sizing and reduction system. To investigate the effects of milling parameters on damaged starch, flour yield, and energy consumption, a three-level and three-variable Box–Behnken experimental design with response surface methodology was applied. As independent variables roll gap (0.05–0.35 mm), feed rate (0.15–0.35 kg/cm min), and fast roll speed (400–800 rpm) were employed. The obtained models were utilized to optimize milling conditions for producing flours with special characteristics. Full article

Excessive application of fertilizers in drip-irrigated wheat production can suppress yields, lower nutrient utilization efficiency, and lead to economic and environmental issues such as nitrogen residues in the soil. Based on a recommended fertilizer application (RF) strategy that takes into account target yield and nutrient requirements, this study explores the responses of wheat plant traits, changes in topsoil and subsoil nutrients, fertilizer utilization, and economic benefits under this strategy. From 2022 to 2023, a field experiment was conducted in a typical oasis spring wheat production area at the northern foot of the Tianshan Mountains in Xinjiang. The treatments included no fertilizer control (CK), the farmer’s conventional practice (FP), recommended fertilizer (RF), RF with nitrogen omission (RF-N), phosphorus omission (RF-P), and potassium omission (RF-K). The results showed that compared with FP, the RF reduced 91 kg N ha⁻¹ (30.3%) and 33 kg P₂O₅ ha⁻¹ (24.8%) in 2022, and 69 kg N ha⁻¹ (23.0%) and 2 kg P₂O₅ ha⁻¹ (1.5%) in 2023. The effect in 2023 was better; RF also decreased the NO₃⁻¹-N residue in the 0–100 cm soil layer by 40.1 kg N ha⁻¹ compared with FP, with no significant difference in wheat grain yield (RF: 5382.9 kg ha⁻¹) or economic benefit (RF: USD 1613.1 ha⁻¹). Furthermore, there were no significant differences between RF and FP in pre-anthesis NP transport or post-anthesis NP accumulation; however, RF significantly increased pre-anthesis potassium transport volume (15.8%) and transport rate (12.5%). RF led to a 16.3% increase in nitrogen utilization efficiency (NUE), while there was no significant difference in phosphorus utilization efficiency (PUE) compared with FP. The fertilizer yield effect for RF was evaluated as N > P > K. Correlation analysis indicated that grain yield was significantly positively correlated with pre-anthesis NPK transport and post-anthesis NP accumulation. It was also positively correlated with organic matter, alkali-hydrolyzed nitrogen, and Olsen-P content in both the topsoil (0–20 cm) and subsoil (20–40 cm), but not with available potassium in the soil. Therefore, conducting soil tests and determining fertilizer recommendations based on the proposed RF method at harvest can reduce fertilizer usage and achieve a balance between the conflicting objectives of environmental protection, increased crop yields, nutrient utilization efficiency, and improved economic benefits in oasis agricultural areas facing excessive fertilizer application. Full article

The genetic regulation of goose meat quality traits remains relatively unexplored, and the underlying mechanisms are yet to be elucidated. This study aims to employ single nucleotide polymorphism (SNP) genotyping in conjunction with genome-wide association studies (GWAS) to investigate critical candidate regions and genes associated with the pH trait of meat in Sichuan white geese. A cohort of 203 healthy male Sichuan white geese was randomly selected and slaughtered at 70 days of age. Measurements were taken of meat pH, growth parameters, body dimensions, and post-slaughter traits. High-throughput sequencing on the Illumina HiSeq X Ten platform facilitated gene resequencing and SNP evaluation, and GWAS was employed to detect key genes within quantitative trait loci (QTL) intervals. The sequencing of 203 individuals yielded a total of 2601.19 Gb of genomic data, with an average sequencing depth of 10.89×. Through GWAS analysis, a total of 30 SNPs associated with pH were identified. These SNPs were identified on multiple chromosomes, including on chromosome 17 (chr: 23.57–23.68 Mb) and chromosome 13 (chr13: 31.52–31.61 Mb). By annotating these associated SNPs, nine candidate genes (including C19L2, AMFR, POL, RERGL, ZN484, GMDS, WAC) associated with the pH of goose meat were identified. The matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF) genotyping of 10 SNPs centered on these nine candidate genes was confirmed. GO enrichment analysis revealed that genes within 1 Mb of the associated SNPs are significantly enriched in pathways involved in lymphocyte activation, in response to hydrogen peroxide, Salmonella infection, and other metabolic processes. This study explores the gene regulatory pathways influencing pH traits in goose meat and provides molecular markers for enhancing meat quality. These findings are expected to facilitate the advancement of molecular breeding programs in geese. Full article

Rapeseed is an important commercial crop globally, used for both animal fodder and human consumption. Varied insolation duration and intensity are among the main factors affecting the seed yield and quality of Brassica napus (B. napus) worldwide. In this study, the high-oil-content rapeseed cultivar “Qingyou 3” was subjected to a light supplementation trial during both the vegetative growth period and the seed productive stage. Different light intensity conditions were stimulated using light-emitting diodes (LEDs). The main plot factor was land condition, with LED treatment (Treatment) and without LED treatment (Control) under natural conditions. The results showed that the leaf size and thickness, photosynthesis efficiency, and seed oil content of B. napus increased significantly after light supplementation. Then, 18 cDNA libraries were constructed from leaf segments (30 days after transplanting—DAT) and seeds 30 and 40 days after pollination (DPA) for RNA transcriptome sequencing. It was found that genes encoding lipid transfer protein, phenylpropanoid biosynthesis, photosynthesis, and plant hormone signal transduction were enriched in differentially expressed genes (DEGs). The qRT-PCR analysis showed that eight key genes had significant variations, a finding also consistent with the RNA-seq results. The aim of this study was to identify the DEGs and signaling pathways in the leaves and seeds of B. napus during the vegetative and seed productive stages under different light intensities. The results provide insight into how sufficient light plays a critical role in promoting photosynthesis and serves as the foundation for material accumulation and yield formation. Full article

Strategies to enhance rice productivity in response to global demand have been the paramount focus of breeders worldwide. Multiple factors, including agronomical traits such as plant architecture and grain formation and physiological traits such as photosynthetic efficiency and NUE (nitrogen use efficiency), as well as factors such as phytohormone perception and homeostasis and transcriptional regulation, indirectly influence rice grain yield. Advances in genetic analysis methodologies and functional genomics, numerous genes, QTLs (Quantitative Trait Loci), and SNPs (Single-Nucleotide Polymorphisms), linked to yield traits, have been identified and analyzed in rice. Genome editing allows for the targeted modification of identified genes to create novel mutations in rice, avoiding the unintended mutations often caused by random mutagenesis. Genome editing technologies, notably the CRISPR/Cas9 system, present a promising tool to generate precise and rapid modifications in the plant genome. Advancements in CRISPR have further enabled researchers to modify a larger number of genes with higher efficiency. This paper reviews recent research on genome editing of yield-related genes in rice, discusses available gene editing tools, and highlights their potential to expedite rice breeding programs. Full article

The mechanical behavior of the metallic components fabricated by additive manufacturing (AM) technologies can be influenced by adjustments in their microstructure or by using specially engineered geometries. Manipulating the topological features of the component, such as incorporating unit cells, enables the production of lighter metamaterials, such as lattice structures. This study investigates the mechanical behavior of lattice structures created from AlSi10Mg, which were produced using the laser beam powder bed fusion (LB-PBF) process. Specifically, their behavior under pure compressive loading has been numerically and experimentally investigated using ten different configurations. Experimental methods and finite element analysis (FEA) were used to investigate the behavior of body-centered cubic (BCC) lattice structures, specifically examining the effects of tapering the struts by varying their diameters at the endpoints ($d_{\mathrm{end}}$) and midpoints ($d_{\mathrm{mid}}$), as well as altering the height of the joint nodes (h). The unit cells were designed with varying parameters in such a way that $d_{\mathrm{end}}$ is changed at three levels, while $d_{\mathrm{mid}}$ and h are changed at two levels. Significant differences in Young’s modulus, yield strength, and ultimate compressive strength between the various specimen configurations were observed both experimentally and numerically. The FEA underestimated the Young’s modulus corresponding to the configurations with thinner struts in comparison to the higher values found experimentally. Conversely, the FEA overestimated the Young’s modulus of those configurations with larger strut diameters with respect to the experimentally determined values. Additionally, the proposed FE method consistently underestimated the yield strength relative to the experimental values, with notable discrepancies in specific configurations. Full article

The waste management sector is crucial for protecting the environment, conserving resources, and promoting sustainable development by ensuring efficient disposal, recycling, and minimizing the harmful impact of waste. This study aims to understand the performance levels (compressive strength), environmental impact, and overall sustainability of three concrete mixes, two of which use recycled materials. The mixes are defined as a conventional mix, mix one, which replaces dune sand for recycled rubber in the mix design, and mix two, which utilizes recycled aggregate as a replacement for fine aggregates. SEM-EDS is used to assess the elemental composition and surface morphology of the materials. The potential leaching of pollutants such as polycyclic aromatic hydrocarbons (PAHs), non-targeted organic compounds, and heavy metals was obtained using GC/MS and ICP-OES. The results showed low concentrations of PAHs in all mixes and a low calculated Potential Ecological Risk Index (PERI), where the conventional mix and mix two had the lowest risk (55 and 33, respectively) compared to mix one, which displayed a higher risk of 125. The results of the heavy metals assessment yielded that mix one was the most contaminated, with 1535 mg/kg of nickel and 1200 mg/kg of zinc, followed by the conventional mix, with 1385 mg/kg of nickel and 135.5 mg/kg of chromium, and finally, mix two was the least contaminated with 378.5 mg/kg of nickel and 142.5 mg/kg of zinc. Overall, the sustainability potential showed that mix two, with the recycled aggregates, was the most sustainable, with a Building Material Sustainability Potential (BMSP) value of 9.25. The study advocates for a shift toward sustainable concrete practices to mitigate environmental impacts while maintaining structural integrity. Full article

Straw mulching cultivation technology can improve the soil environment of farmland, and it is applied in the dry farming area of Northwestern China. There are few studies on the effect of corn straw mulching on the soil temperature and yield of potato fields in dry land in Northwestern China. In this paper, three treatments, black film ridge (HM), corn straw mulching mechanized no-tillage planting (JG) and no-covering open field flat planting (CK), were set up in the period of 2022 to 2023. A field plot experiment was carried out to determine the soil temperature, growth index, and yield data during the key growth period. The statistical analysis results show that JG and HM significantly increased the potato yield, by 12.27~18.30% and 13.09~18.10%, compared with CK, but there was no significant difference between JG and HM. The yield was significantly positively correlated with tuber weight per plant at the tuber expansion stage, starch accumulation stage, and harvest stage (0.47 *~0.60 **), and significantly negatively correlated with the number of tubers at the harvest stage (−0.54 *). Compared with CK, HM increased the average soil temperature over the whole growth period by 0.27~0.92 °C. In 2022, the increase in the 5 cm soil layer in the tuber expansion period was the largest, reaching 0.83 °C. In 2023, the increase in the 5 cm soil layer in the starch accumulation period was the largest, reaching 3.08 °C. JG reduced the soil temperature over the whole growth period by 0.52 °C, and the 20 cm soil layer in the tuber formation period decreased the most, reaching 1.45 °C, which aggravated the soil temperature change over the whole growth period (the amplitude was 4.13~4.53 °C). The temperature difference between day and night in different growth periods in 2022 was 2.14~5.41 °C, and the soil temperature in some growth periods in 2022 even exceeded that with HM. The results showed that JG could regulate soil temperature and optimize the relationship between tuber weight per plant, tuber number per plant, and biomass allocation during tuber formation, which are beneficial for the improvement of the potato yield in the dry farming area of Northwestern China. Full article

Given the global importance of sweet potatoes as a nutrient-rich staple food, this research aimed to find the optimal cultivation practices to improve both yield and carotenoid content, with a particular focus on enhancing β-carotene content. In this study, the effects of different cultivation methods and plant densities on the agronomic parameters, physiological characteristics and carotenoid content of the ‘Beauregard’ variety were investigated across two consecutive growing seasons. Besides storage root yield, the key physiological parameters, including SPAD and chlorophyll fluorescence (Fv/Fm), were monitored to assess plant health and photosynthetic performance. Carotenoid content, including trans-β-carotene, cis-β-carotene, and ζ-carotene, was quantified using high-performance liquid chromatography (HPLC). Results indicated that the ridge cultivation method, particularly when combined with twin-row planting, consistently produced the highest yields, reaching the maximum of 40.87 t ha⁻¹ in 2020. The flat cultivation method, especially in simple rows, showed the lowest yield. The analysis revealed that plant density had a more pronounced effect on yield and carotenoid content than the ridge or flat cultivation method alone. The maximum β-carotene content was achieved in the simple row (17,500 plants/ha) treatment planted on ridges with 247 µg/g. Significant correlations between both SPAD readings and Fv/Fm and yield were revealed, but no correlations with storage root carotenoid content were found. This suggests that, while these leaf physiological traits can be used to estimate the yield, they are not directly associated with the carotene content of the storage root. The study highlights the ridge cultivation and 35,000 plants/ha method as a stable and high-yielding option for ‘Beauregard’ in terms of improving and balancing the yield and carotenoid content; however, reducing the plant density resulted in elevated carotenoid content with significant yield reductions. The findings contribute to the understanding of how agronomic practices influence the nutritional and physiological traits of sweet potatoes, with implications for improving food security and nutritional outcomes in sweet potato cultivation. Full article

The “cocktail party problem”, the challenge of isolating individual speech signals from a noisy mixture, has traditionally been addressed using statistical methods. However, deep neural networks (DNNs), with their ability to learn complex patterns, have emerged as superior solutions. DNNs excel at capturing intricate relationships between mixed audio signals and their respective speech sources, enabling them to effectively separate overlapping speech signals in challenging acoustic environments. Recent advances in speech separation systems have drawn inspiration from the brain’s hierarchical sensory information processing, incorporating top-down attention mechanisms. The top-down attention network (TDANet) employs an encoder–decoder architecture with top-down attention to enhance feature modulation and separation performance. By leveraging attention signals from multi-scale input features, TDANet effectively modifies features across different scales using a global attention (GA) module in the encoder–decoder design. Local attention (LA) layers then convert these modulated signals into high-resolution auditory characteristics. In this study, we propose two key modifications to TDANet. First, we substitute the fully trainable convolutional encoder with a deterministic hand-crafted multi-phase gammatone filterbank (MP-GTF), which mimics human hearing. Experimental results demonstrated that this substitution yielded comparable or even slightly superior performance to the original TDANet with a trainable encoder. Second, we replace the single multi-head self-attention (MHSA) layer in the global attention module with a transformer encoder block consisting of multiple MHSA layers. To optimize GPU memory utilization, we introduce a parameter sharing mechanism, dubbed “Reverse Cycle”, across layers in the transformer-based encoder. Our experimental findings indicated that these proposed modifications enabled TDANet to achieve competitive separation performance, rivaling state-of-the-art techniques, while maintaining superior computational efficiency. Full article

The impact of fluoride-based coatings on the microstructure and mechanical integrity of extruded Mg-1.0Zn-0.3Zr-1.0Y-2.0Sn alloys was assessed utilizing optical microscopy (OM), scanning electron microscopy (SEM), X-ray diffraction (XRD), immersion testing, electrochemical analysis, and tensile testing. It was observed that the magnesium alloys could be immersed in hydrofluoric acid (HF) for varying durations to achieve coatings of distinct thicknesses, with the coating thickness stabilizing at approximately 8 μm after a 48 h immersion period. The application of the fluoride coating significantly enhanced the corrosion resistance of the alloys, with a corrosion rate (CR_H) of 0.13 ± 0.012 mm/y. Upon a 20-day immersion in simulated body fluid (SBF), the degradation rates of the yield strength (YS), tensile strength (UTS), and elongation (EL) for the cast alloys were recorded as 62%, 59%, and 64%, respectively. For the extruded alloys, these rates escalated to 77%, 76%, and 95%. In contrast, the fluorine-coated alloys exhibited significantly lower degradation rates of 28%, 23%, and 39% after a 25-day immersion in SBF. Upon extrusion, the specimens exhibit a diminished corrosion resistance and a more substantial decline in mechanical properties compared to their as-cast state. Upon the application of the coating, there is a discernible reduction in the rate of mechanical property degradation observed in the specimens. This indicates that the fluorinated coating can mitigate the corrosion rate and enhance the corrosion resistance of magnesium alloys. Full article

Mitigating the irreversible consequences of climate change necessitates the application of sustainable energy resources. Hereby, we investigated the biological anaerobic fermentation of Azolla filiculoides biomass for biohydrogen production as a clean renewable energy source. Azolla filiculoides is a widely growing aquatic plant in polluted freshwater streams. However, the high non-biodegradable organic matter content in Azolla filiculoides biomass remains challenging in efficiently producing renewable energy, especially when it is being used as the sole donor substrate. In order to overcome this challenge, different pretreatment scenarios (namely, alkali, autoclaving, and ultrasonication) have been employed for enhancing the hydrolysis of Azolla filiculoides biomass to maximize the anaerobic fermentation and, consequently, the biohydrogen production potential. The biohydrogen production potential was 250.5, 398, 414.5, and 439.5 mL-H₂, giving a hydrogen yield of 60.1, 89.6, 92.9, and 107.9 mL-H₂/g-VS, respectively. Gompertz kinetics were applied to estimate the growth parameters of the process, which revealed a good fit with R² ranging from 0.96 to 0.98. The produced digestate was valorized for biochar production, a material that could be applied for water treatment purposes. The produced biochar was characterized using different physical analyses, including FTIR, SEM, EDX, and TEM. The physicochemical characterizations of biochar demonstrate a successful formation of biochar with a highly porous structure and a rough surface, as evidenced by the emergence of significant functional groups (e.g., O-H, C-H, C=C, and C=O) existing on the surface of the biochar. In conclusion, this study harnesses a sustainable approach for the treatment of organic waste streams, which represents a circular economy model by transforming waste materials into valuable products and reducing the reliance on non-renewable resources. Full article

Background: The critical power model (CPM) is used extensively in sports to characterize fitness by estimating anaerobic work capacity (W’) and critical power (CP). Traditionally, estimates of CP and W’ require repeated, time-consuming tests. Alternatively, a 3 min all-out test yields good estimates of W’ and CP. However, adoption of the 3 min protocol for regular fitness monitoring is deterred by the mentally/physically strenuous nature of the test. Objective: We propose to examine an alternative single-session testing protocol that can accurately estimate critical power model parameters. Methods: Twenty-eight healthy competitive athletes (cyclists or triathletes) (mean ± SD: age: 38.5 ± 10.4 years, height: 177.9 ± 8.6 cm, mass: 73.4 ± 9.9 kg) participated in 5 sessions on a Lode cycle ergometer in isokinetic mode within a 2-week period. A 3 min all-out test (3MT) was conducted on the first visit to determine CPM parameters from which power outputs for 4 subsequent constant-power plus all-out tests (CPT) were selected to result in exhaustion in 1–10 min. The subjects were to maintain the prescribed power output as consistently as possible at their preferred race cadence. Once the power output could no longer be maintained for more than 10 s, the subjects were instructed to produce an all-out effort. Tests were terminated after power output fell to an asymptote which was sustained for 2 min. Results: The CPM parameters for all of the CPT durations were compared to the traditional CP protocol (significant parameter differences were identified for all CPT durations) and the 3MT (only CPT durations > 3 min were different [3–6 min test, p < 0.01; >6 min test, p < 0.01]). CPT does not estimate traditional CP and W’ parameters well. However, the CPT with a duration < 3 min accurately estimates both parameters of a 3MT. Conclusion: Therefore, CPT has the capacity to serve as an alternative tool to assess CP parameters. Full article

The rapid reconstruction of the internal flow field within pressure vessel equipment based on features from limited detection points was of significant value for online monitoring and the construction of a digital twin. This paper proposed a surrogate model that combined Proper Orthogonal Decomposition (POD) with deep learning to capture the dynamic mapping relationship between sensor monitoring point information and the global flow field state during equipment operation, enabling rapid reconstruction of the temperature field and velocity field. Using POD, the order of the tested temperature field was reduced by 99.75%, and the order of the velocity field was reduced by 99.13%, effectively decreasing the dimensionality of the flow field. Our analysis revealed that the first modal coefficient of the temperature field snapshot data, after modal decomposition, had a higher energy proportion compared to that of the velocity field snapshot data, along with a more pronounced marginal effect. This indicates that more modes need to be retained for the velocity field to achieve a higher total energy proportion. By constructing a CSSA-BP model to represent the mapping relationship between the modal coefficients of the temperature and velocity fields and the data collected from the detection points, a comparison was made with the BP method in reconstructing the temperature field of a shell-and-tube heat exchanger. The CSSA-BP method yielded a maximum mean squared error (MSE) of 9.84 for the reconstructed temperature field, with a maximum mean absolute error (MAE) of 1.85. For the velocity field, the maximum MSE was 0.0135 and the maximum MAE was 0.0728. The global maximum errors for the reconstructed temperature field were 4.85%, 3.65%, and 4.29%, respectively. The global maximum errors for the reconstructed velocity field were 17.72%, 11.30%, and 16.79%, indicating that the model established in this study has high accuracy. Conventional CFD simulation methods require several hours, whereas the reconstruction model proposed here can rapidly reconstruct the flow field within 1 min after training is completed, significantly reducing reconstruction time. This work provides a new method for quickly obtaining the internal flow field state of pressure vessel equipment under limited detection points, offering a reference for online monitoring and the development of digital twins for pressure vessel equipment. Full article