Search Results (153)

Water quality monitoring faces increasing challenges due to accelerating industrialization and urbanization, demanding accurate, real-time, and reliable prediction technologies. This study presents a novel ensemble learning framework integrating Gaussian Process Regression, Support Vector Regression, and Random Forest algorithms for high-precision water quality pH prediction. The research utilized a comprehensive spatiotemporal dataset, comprising 11 water quality parameters from 37 monitoring stations across Georgia, USA, spanning 705 days from January 2016 to January 2018. The ensemble model employed a dynamic weight allocation strategy based on cross-validation error performance, assigning optimal weights of 34.27% to Random Forest, 33.26% to Support Vector Regression, and 32.47% to Gaussian Process Regression. The integrated approach achieved superior predictive performance, with a mean absolute error of 0.0062 and coefficient of determination of 0.8533, outperforming individual base learners across multiple evaluation metrics. Statistical significance testing using Wilcoxon signed-rank tests with a Bonferroni correction confirmed that the ensemble significantly outperforms all individual models (p < 0.001). Comparison with state-of-the-art models (LightGBM, XGBoost, TabNet) demonstrated competitive or superior ensemble performance. Comprehensive ablation experiments revealed that Random Forest removal causes the largest performance degradation (+4.43% MAE increase). Feature importance analysis revealed the dissolved oxygen maximum and conductance mean as the most influential predictors, contributing 22.1% and 17.5%, respectively. Cross-validation results demonstrated robust model stability with a mean absolute error of 0.0053 ± 0.0002, while bootstrap confidence intervals confirmed narrow uncertainty bounds of 0.0060 to 0.0066. Spatiotemporal analysis identified station-specific performance variations ranging from 0.0036 to 0.0150 MAE. High-error stations (12, 29, 33) were analyzed to distinguish characteristics, including higher pH variability and potential upstream pollution influences. An integrated software platform was developed featuring intuitive interface, real-time prediction, and comprehensive visualization tools for environmental monitoring applications. Full article

Improving wheat processing quality is a crucial objective in modern wheat breeding. Among various quality parameters, grain protein content (GPC) and wet gluten content (WGC) significantly influence the end-use quality of flour. These traits are controlled by multiple minor effect genes and highly influenced by environmental factors. Identifying stable and major-effect genetic loci and developing breeder-friendly molecular markers are of great significance for breeding high-quality wheat varieties. In this study, we evaluated the GPC and WGC of 310 diverse wheat varieties, mainly from China and Europe, across four environments. Genotyping was performed using the wheat 100K SNP chip, and genome-wide association analysis (GWAS) was employed to identify stable loci with substantial effects. In total, four loci for GPC were identified on chromosomes 1A, 3A, 3B, and 4B, with explained phenotypic variation (PVE) ranging from 6.0 to 8.4%. In addition, three loci for WGC were identified on chromosomes 4B, 5A, and 5D, which explained 7.0–10.0% of the PVE. Among these, three loci coincided with known genes or quantitative trait loci (QTL), whereas QGPC.zaas-3AL, QGPC.zaas-4BL, QWGC.zaas-4BL, and QWGC.zaas-5A were potentially novel. Seven candidate genes were involved in various biological pathways, including growth, development, and signal transduction. Furthermore, five kompetitive allele specific PCR (KASP) markers were developed and validated in a natural population. The newly identified loci and validated KASP markers can be utilized for quality improvement. This research provides valuable germplasm, novel loci, and validated markers for high-quality wheat breeding. Full article

Passive acoustic monitoring (PAM) is an automatic and non-invasive method for long-term monitoring of bird vocal activity. PAM generates a large amount of data, and the automatic recognition of data poses significant challenges. BirdNET is a free-to-use sound algorithm. We evaluated the effectiveness of BirdNET in identifying the vocalizations of Chinese Bamboo Partridge (a Chinese endemic species) and proposed a random forest (RF) method to improve the result based on the detection of BirdNET. The diurnal and seasonal patterns of calling activity were described based on the identification results. The results showed that the recall of BirdNET-Analyzer was 16.6%, the precision of BirdNET-Analyzer-XHS was 50.8%, and the recall and precision of the RF model were 75.2% and 74.4%, respectively. The diurnal vocal activity of the Chinese Bamboo Partridge showed a bimodal pattern, with peaks around sunrise and sunset and low vocal activity during the central hours of the day. The seasonal vocal activity displayed a unimodal pattern, with a peak in vocal activity during April and May. This study used the Chinese Bamboo Partridge as an example and proposes an improved RF model, built on BirdNET recognition results, for species identification, providing a practical approach for recognizing the vocalizations of regional species. Full article

European plum (Prunus domestica) orchards in the Kashi region, Xinjiang, China, suffer from fruit brown spot disease. The disease typically appears as red spots on the fruit surface that expand into brown necrotic lesions; affected fruit flesh can shrink, and fruits can harden and drop. We isolate and identify pathogens associated with this disease in this plum from five Kashi counties. Of 210 fungal isolates obtained through standard tissue isolation, Alternaria accounted for 84.8%, with the remainder comprising species of Aspergillus (9.5%), Diplodia (3.3%), and Neoscytalidium (2.4%). Using PCR amplification and sequencing of five loci, pathogens were identified using multi-gene phylogenetic analyses, combined with observations of colony and spore morphology. Multi-locus sequences of Alternaria isolates were highly homologous to those of the Alternaria alternata type strain, and we refer them to an A. alternata species complex. Pathogenicity tests confirm that Alternaria isolates reproduce brown spot symptoms on European plum fruits. By demonstrating that Alternaria is the primary pathogen causing brown spot disease in European plum in Xinjiang, we clarify both the fungal species composition and taxonomic placement of the dominant pathogen associated with this disease. Full article

European plum (Prunus domestica L.) is widely cultivated worldwide, with China producing 6.8 million t annually (55% of the global total output). However, the Kashgar region of Xinjiang, China’s primary production area, has experienced outbreaks of brown spot disease caused by Alternaria alternata (Fr.) Keissl. Outbreaks of this disease severely hinder both domestic and global development of the European plum industry. Because this pathogen has a strong latent infection capability during the early stages of disease development, its early detection is important. We develop two detection methods targeting the ITS sequence of A. alternata: LAMP-Cresol Red chromogenic visible endpoint detection and LAMP-SYBR Green I real-time fluorescent detection. Both methods demonstrate high specificity for A. alternata, enabling stable detection of the pathogen in various plant samples; detection limits reach the femtogram (fg) level, significantly surpassing conventional PCR detection capabilities. Development of these highly efficient and precise early detection methods provides a solid foundation for sustainable development of China as a global hub of the European plum industry, and contributes significantly to global disease prevention, control, and industrial stability for this crop. Full article

Gallic acid (GA) exhibits excellent antioxidant properties but suffers from chemical instability due to its carboxyl group, which limits practical application. To address this, we designed and investigated 14 distinct ester derivatives of GA, which were categorized into two major groups based on their substituents: chain alkyl and hydroxyl-substituted alkyl groups. Systematic evaluation revealed a striking decline in the DPPH radical scavenging activity of alkyl esters with increasing carbon chain length, from 91.9% for GA-C3 to 55.6% for GA-C30. The hydroxyl-functionalized GA esters GA-EG, GA-GL, and GA-PT maintain high antioxidant activity (>90%) while improving applicability through carboxyl substitution. In the oil system, all derivatives significantly prolong the oxidation induction time, with GA-C3 exhibiting the highest performance by extending the induction time by 2.15 h. Hydroxyl-functionalized esters such as GA-EG, GA-GL, and GA-PT also demonstrated significant efficacy, prolonging oxidation induction by 1.92 to 2.03 h. The results suggest how the structure of GA esters affects their antioxidant behavior, providing a direction for designing antioxidants suitable for specific systems. Full article

Stem strength is a key factor influencing lodging resistance in soybeans and other crops. To identify quantitative trait loci (QTLs) associated with stem strength in soybean, we assessed the peak forces required to break a 20 cm stem base segment for each individual within a collection of 2138 plants from eight F₂ and F₃ segregating populations in 2023 and 2024. These populations were derived from four crosses between soybean varieties with contrasting stem strength. Most populations exhibited an approximately normal distribution of stem strength. Using BSA-seq, we identified 17 QTLs associated with stem strength from four populations. Among these, one QTL overlapped with a previously reported locus, while the remaining 16 represented novel loci. Notably, nine loci overlapped with known lodging QTLs, suggesting a genetic relationship between stem strength and lodging. Three QTLs were repeatedly detected in multiple populations, indicating their stability. Further linkage mapping with molecular markers confirmed these three stable QTLs. Among them, qSS10 and qSS19-2 were identified as major QTLs, refined to 1.06 Mb and 1.54 Mb intervals, with phenotypic variation explained (PVE) 23.31–25.15% and 14.21–19.93%, respectively. Within these stable QTL regions, we identified 13 candidate genes and analyzed their sequence variation and expression profiles. Collectively, our findings provide a valuable foundation for future research on stem strength in soybeans and reveal novel genetic loci and candidate genes that may be utilized for the genetic improvement of soybean lodging resistance and yield stability. Full article

The urban–rural relationships in China are experiencing a dual structure period, balancing an urban–rural development period and coordinated urban–rural development period, and urban–rural integrated development has become the current strategy. Urban–rural integrated development has become an important measure to address the unbalanced development between urban and rural areas. Despite proactive explorations by governments at various levels to promote integrated urban–rural development, the anticipated outcomes remain difficult to achieve due to multiple constraints, such as inefficient flow of production factors and unequal provision of basic public services between urban and rural areas. There is an urgent need to re-examine how to advance deeper urban–rural integration from the perspective of collaborative governance. Taking the Yangtze River Delta region as a case study, this research reviews related policy documents, official texts, and development plans regarding urban–rural integrated development, social (urban–rural community) collaborative governance, and urban development at the central and regional levels in recent years. Meanwhile, this study interviews experts in the field of public administration and government officials, and visits the experimental area and demonstration area of integrated development in the Yangtze River Delta region. Through grounded theory method and multi-level coding, concepts, initial categories, main categories are clear, and six core categories in total are identified: policy planning capability, public participation, participation of non-governmental organization, openness of government information, supervision and evaluation, and implementation capacity. This bottom-up construction of the theoretical framework serves as an extension and enrichment of collaborative governance theory. Based on the six core elements identified through the research, the Yangtze River Delta region may implement targeted policy adjustments across these dimensions to enhance the effectiveness of collaborative governance, and it may provide referential insights for urban–rural development practices in other regions. Full article

Ceramic bond grinding wheels were prepared and their performance in grinding Ni-based alloys was evaluated and compared in this study. Ceramic bond grinding wheels with excellent performance were successfully produced by optimizing the preparation process. Ceramic bond grinding wheels and conventional grinding wheels were used to grind Ni-based alloys, and the differences between the two were compared in terms of the surface quality of the workpieces after grinding. The results show that the ceramic bond grinding wheels exhibit significant advantages in improving the grinding surface quality, reducing the generation of grinding heat and extending the service life of the grinding wheels. In addition, the study also compares the differences in grinding force between the two grinding wheels and finds that the ceramic bond grinding wheel can significantly reduce the grinding force under the same processing conditions, thus improving the grinding efficiency and stability. Through systematic analysis, this paper determines the optimal processing parameters of ceramic bond grinding wheels in the process of grinding Ni-based alloys, which provides a theoretical basis and technical support for its application in actual processing. Full article

To fully exploit the acoustic regulation potential of shell-and-tube heat exchangers, this paper proposes a novel heat exchanger design in which the conventional heat exchange tubes are replaced by triply periodic minimal surface structures. The acoustic transmission characteristics of the TPMS-structured heat exchangers were systematically investigated using the finite element method. Four different types of TPMS heat exchanger models—Gyroid, Schwarz P, Split P, and Schwarz D—were constructed, with a focus on analyzing the influence of key parameters such as unit cell type, unit cell size, and volume fraction on their transmission loss characteristics and acoustic transmission capability. It was found that the effects of these parameters on the acoustic transmission characteristics differ significantly between the 100~1600 Hz and 1700~3000 Hz frequency bands. Based on this, the simulation results of the four TPMS heat exchangers were further compared with experimental data from a shell-and-tube heat exchanger. The results show that in a water medium, the sound insulation performance of the Schwarz P type TPMS heat exchanger is comparable to that of the conventional shell-and-tube heat exchanger below 1600 Hz, whereas it improves significantly above 1600 Hz, with an overall transmission loss of up to 78.49 dB. The findings of this study provide valuable theoretical insights for the development of compact underwater heat exchangers with excellent acoustic performance. Full article

Laying hens in the late laying period often experience reduced productivity and declining egg and meat quality, which limits breeding efficiency and resource utilization. This study aimed to evaluate the effects of multi-component Botanical Crude Extracts (BCEs) on egg and meat quality, metabolic health, and gut microbiota in aged laying hens. A total of 4320 hens were supplemented with 0.3% BCEs for 100 days, with evaluations at 60 and 100 days. BCE supplementation significantly enhanced egg flavor by promoting aromatic and fat-soluble volatiles and reducing odorous compounds (p < 0.05). BCEs improved yolk nutrition by enriching n-3 polyunsaturated fatty acids, especially docosahexaenoic acid (DHA), and optimizing the n-6/n-3 ratio (p < 0.05). A moderate reduction in amino acids was observed, which may reduce bitterness and ammonia burden (0.05 ≤ p < 0.10, trend). In muscle, BCEs improved protein–fat distribution, increased intramuscular fat, and enhanced flavor-related metabolites, significantly improving meat quality of culled hens (p < 0.05). BCEs also reshaped gut microbiota, reducing harmful taxa and promoting short-chain fatty acid and aromatic metabolite biosynthesis (p < 0.05). Serum metabolomics revealed modulation of AMPK, calcium, and cholesterol pathways, improving antioxidant capacity and lipid regulation (p < 0.05). Correlation analyses linked beneficial bacteria and metabolites with yolk DHA levels and flavor (p < 0.05). Overall, BCEs enhanced egg and meat quality and physiological health, providing guidance for functional feed strategies in aged laying hens. Full article

Background/Objectives: Alcohol consumption can increase the risk of dyslipidemia, thereby elevating the risk of cardiovascular diseases. However, the relationship between alcohol consumption patterns and dyslipidemia remains controversial. Based on large-scale cross-sectional data from the Chinese population, this study aims to investigate the correlations between various alcohol consumption behaviors and dyslipidemia among adult residents in China. Methods: Our analysis utilized data from the 2015–2017 China Nutrition and Health Surveillance project, which provides a large, nationally representative sample (N = 52,471). We employed a binary logistic regression model specifically designed for complex sampling frameworks. This model was utilized to assess the relationship between various alcohol consumption behaviors (including daily alcohol intake levels and drinking frequency) and the incidence of hypercholesterolemia, hypertriglyceridemia, low levels of high-density lipoprotein cholesterol (low HDL-C), and elevated levels of low-density lipoprotein cholesterol (high LDL-C). Drinking behaviors were classified into three distinct categories for analysis: China classification (never, moderate, excessive), WHO classification (never, low-risk, medium-risk, high-risk), and drinking frequency (never, <1, 1–3, 4–6, ≥7 times/week). Results: Compared with never drinkers, the risk of hypercholesterolemia was significantly higher in men who were excessive drinkers (aOR = 1.39, 95%CI: 1.24–1.57), medium-risk drinkers (aOR = 1.24, 95%CI 1.01–1.53), high-risk drinkers (aOR = 1.67, 95%CI: 1.4–1.95), and those who drank more than once a week (aOR range: 1.27–1.65), and there was no such association in women (p > 0.05). Compared with never drinkers, the risk of hypertriglyceridemia was higher in male drinkers with excessive drinking (aOR = 1.35, 95%CI: 1.24–1.47), medium-risk drinking (aOR = 1.29, 95%: 1.11–1.50), high-risk drinking (aOR = 1.52, 95%CI: 1.3–1.71), and a drinking frequency more than 1 time/week (aOR range: 1.22–1.38), while in women, it was moderate drinking (aOR = 0.85, 95%CI 0.77–0.94), low-risk drinking (aOR = 0.86, 95%CI 0.78–0.94), and a drinking frequency of more than once a week (aOR = 0.74, 95%CI 0.63–0.87) that reduced the occurrence of hypertriglyceridemia. Compared with non-drinkers, men with any drinking status had a lower risk of low HDL-C (aOR range: 0.38–0.90) and a similar association was also observed in women (aOR range: 0.26–0.84). Compared with never drinkers, male excessive drinkers (aOR = 0.86, 95%CI: 0.77–0.97), medium-risk drinkers (aOR = 0.80, 95%CI:0.65–0.99), high-risk drinkers (aOR = 0.83, 95%CI: 0.70–0.97), and those with a drinking frequency of 1–3 times/week (aOR = 0.89, 95%: 0.79–0.99) had a lower risk of high LDL-C, and there was no such association in women (p > 0.05). Conclusions: Significant gender differences were observed in the effects of alcohol consumption on lipid profiles. Men who were excessive drinkers, medium-risk drinkers, high-risk drinkers, and those who drank more than once a week had a higher risk of hypercholesterolemia and hypertriglyceridemia, but a lower risk of low HDL-C and high LDL-C. In women, moderate drinking was associated with a reduced risk of hypertriglyceridemia. Any alcohol consumption and drinking frequency more than 1 time/week were associated with a lower risk of low HDL-C in women. No significant association was found between alcohol consumption and hypercholesterolemia or high LDL-C in women. Full article

A novel thermal conductivity prediction model was developed to address the complex influence of pore structure in porous materials. This model incorporates pore size (d) and a pore distribution parameter (t) to calculate the material’s thermal conductivity. To validate the model’s accuracy, geopolymer foamed concrete (GFC) samples with varying pore structures were fabricated. These utilized ground granulated blast furnace slag (GGBS) as the precursor, a mixed solution of sodium hydroxide (NaOH) and sodium silicate as the alkaline activator, and sodium stearate (NaSt), hydroxypropyl methylcellulose (HPMC), and sodium carboxymethyl cellulose (CMC-Na) as foam stabilizers. Conventional pore size characterization techniques exhibit limitations; consequently, this research implements a high-fidelity machine vision-driven image analysis methodology. Pore size measurement is achieved through a combined technical approach involving equivalent diameter modeling and morphological optimization. The feasibility of the proposed theory is validated by our experimental data and data from previous literature, with the error between experimental and theoretical values maintained within 5%. The value of t increases with increasing porosity and increasing disorder in pore distribution. Based on the experimental data obtained in this study and the research data from previous scholars’ studies, the t value for porous materials can be categorized according to porosity: when porosity is approximately 30%, t ≈ 0.9; when porosity is 55~65%, t ranges from 1.2 to 1.3; and when porosity is approximately 80%, t ranges from 1.9 to 2.2. Full article

Background: Forsythia suspensa (Thunb.) Vahl is a perennial deciduous shrub of the Oleaceae family. Its dried mature fruits are used as medicine and hold an important position in traditional Chinese medicine. Tyrosine decarboxylase (TyDC) is a key enzyme involved in the synthesis of dopamine in Forsythia suspensa. At the same time, it also affects the growth and development of this species under biotic stress. Methods: This study examined the expression and function of FsTyDC1 under drought and salt stress. The TyDC gene identified in F. suspensa, termed FsTyDC1, has an open reading frame (ORF) of 1518 bp. Results: qRT-PCR and subcellular localization analyses indicated that FsTyDC1 is highly expressed in F. suspensa fruit and its protein is located in the cytoplasm. The gene was silenced using a pTRV2-FsPDS/FsTyDC1 vector with virus-induced gene silencing. Following exposure to drought and salt stress, the leaves of FsTyDC1-silenced plants exhibited increased curling and wilting. Conclusions: The results indicate that FsTyDC1 responds to both salt and drought stress, which provides a foundation for further investigation into the function of FsTyDC1. Full article

Extreme drought events may become more frequent with climate change. Understanding the impact of extreme drought on grassland ecosystems is therefore crucial for the long-term sustainability of ecosystems. Here, we identified extreme drought events in the Inner Mongolia grasslands of China using long-term standardized precipitation evapotranspiration index (SPEI) data and evaluated drought resistance of the vegetation under extreme drought based on net primary production (NPP). The impact of consecutive extreme drought events and multiple discontinuous one-year extreme drought events on grasslands were further analyzed to investigate the response strategies of different grassland types to different drought conditions. We found that the frequency and area of extreme drought in 2000–2011 were significantly higher than those in 2012–2020, and the Xilingol League region showed the highest frequency of extreme drought events. Under extreme drought, vegetation resistance was positively correlated, where annual precipitation > 300 mm. The mean resistance of different grassland types followed the order: upland meadow (UM) > lowland meadow (LM) > temperate meadow steppe (TMS) > temperate desert (TD) > temperate steppe (TS) > temperate steppe desert (TSD) > temperate desert steppe (TDS). In the analysis of two cases of consecutive two-year extreme drought, all grassland types except TSD and TD showed obvious decreased resistance in the final drought year, with the highest reduction (0.16) in LM during 2010–2011, implying the widespread and significant inhibition of grassland growth by continuous drought. However, under the multiple discontinuous extreme drought events, the resistance of all grassland types showed a fluctuating but an overall increasing trend, suggesting the adaptability of grassland to drought. The results emphasize that management departments should pay more attention to regions with low resistance and enhance the stability of grassland production by increasing the proportion of drought-resistant plants in reaction to future extreme drought scenarios. Full article