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Abstract Purpose This study aims to investigate the influence of multifidus muscle fat infiltration on clinical outcomes in lumbar disc herniation (LDH) undergoing percutaneous endoscopic lumbar discectomy (PELD). Methods A retrospective analysis was conducted on 224 patients who underwent lateral PELD, with complete one-year follow-up data. Patients were divided into two groups based on preoperative MRI evaluation of L4 multifidus muscle fat infiltration: a mild group (

Abstract Atrial fibrillation is the most common arrhythmia in adults. The interplay between epicardial adipose tissue and atrial fibrillation has garnered significant scientific interest. Recently, the combined approach of radiofrequency ablation and left atrial appendage occlusion has become a widely adopted strategy for managing non-valvular atrial fibrillation patients at high risk of thrombus formation. This study aims to assess the prognostic significance of epicardial adipose tissue volume in patients undergoing radiofrequency ablation in conjunction with left atrial appendage occlusion. This study results indicate that in patients undergoing the one-stop procedure, which comprises catheter radiofrequency ablation and percutaneous left atrial appendage occlusion, epicardial adipose tissue volume is significantly associated with AF recurrence post-strategy. Higher EATV predicts AF recurrence (HR = 1.17, 95%CI1.047-1.192, P = 0.001) and thromboembolism (P = 0.002) following the one-stop procedure. Epicardial adipose tissue volume serves as a significant predictor of atrial fibrillation recurrence following the one-stop procedure (area under the curve 0.648, 95%CI0.571-0.725, P = 0.002, sensitivity 0.88, specificity 0.50).

Runoff is pivotal in water resource management and ecological conservation. Current research predominantly emphasizes enhancing the precision of machine learning-based runoff predictions, with limited focus on their physical interpretability. This study introduces an innovative two-step hybrid runoff prediction framework tailored for the headwater region of the Yellow River Basin (YRB) to improve prediction accuracy and elucidate the runoff modeling process. The framework integrates machine learning techniques with dual signal decomposition approaches, incorporating diverse hydrometeorological and geographic indicators. Long Short-Term Memory (LSTM) and eXtreme Gradient Boosting (XGBoost) algorithms were employed to predict monthly runoff generation in sub-basins delineated by the Soil and Water Assessment Tool (SWAT), which were subsequently integrated using a Recurrent Neural Network (RNN) for monthly runoff concentration prediction. Results indicate that the proposed models delivered superior prediction performance compared to the SWAT model (R2 = 0.86, NSE = 0.85), with the LSTM-based two-step hybrid model (R2 = 0.90, NSE = 0.90) outperforming the XGBoost-based model (R2 = 0.89, NSE = 0.88). The dual decomposition method, integrating seasonal-trend decomposition based on loess (STL) and successive variational mode decomposition (SVMD), demonstrated exceptional efficacy in addressing the complexities of hydrometeorological time series. Models decomposed by STL-SVMD exhibited the highest average R2 and NSE values, as well as the lowest RMSE and MAE values in sub-basin runoff calculations. The low standard deviations of performance metrics further underscored the stability of these models across all sub-basins. This study demonstrates the efficacy of the proposed two-step hybrid model for simulating physical runoff processes in the headwater region of the YRB, providing valuable insights for regional hydrological cycle research and hydro-ecological security.

Abstract The objective of this work was to investigate the sorption behavior of gases, namely CO2, CH4, and N2, by molecules of coal sampled from Linglu mine under different water inclusion rates. To this end, the adsorption, diffusion, adsorption heat, and potential energy distribution characteristics of the gases in the coal pores at different water inclusion rates were analyzed using molecular dynamics and grand canonical ensemble Monte Carlo methods. The results showed that the adsorption relationship of the coal molecules on CO2, CH4, and N2 exhibited a downtrend followed by an uptrend when the water content was increased from 0 to 3.6%. The adsorption amount of CO2 was approximately twice as much as those of CH4 and N2, indicating that the competitive adsorption advantage of CO2 compared with those of CH4 and N2 was unaffected by the water content. The trend in the average heat of adsorption was generally consistent with the trend in the density of coal molecules under different moisture contents. Under the same conditions, the diffusion coefficient within a coal molecule was negatively related to the water content in the system. The layer spacing of the water molecules (2.875 Å) was greater than the liquid–water layer spacing, indicating the formation of a water molecule layer at this point, which inhibited gas adsorption. This study lays a theoretical foundation for further investigating the microscopic mechanism of coal–water interaction.

To achieve the control of foodborne pathogenic bacteria Clostridium perfringens by non-thermal technology, curcumin was used as the photosensitizer to explore its inhibitory mechanism on C. perfringens. The bactericidal effect of different curcumin concentrations on C. perfringens was investigated. The cell morphology after curcumin treatment was investigated through scan electron microscopy. The integrity of the cell membrane was analyzed by confocal laser scanning microscope and leakage of extracellular macromolecules. The oxidative damage of C. perfringens was determined by ROS analysis. The results indicated that curcumin showed a significantly (P

Study region: The Yellow River Basin, situated in northern China. Study focus: Precipitation has shown significant variability over the past century, understanding its evolving trends helps addressing the impacts of climate change on local water resources. The Köppen-Geiger Trend Indicator System was proposed, which divides the study region into various climate zones and calculates indicators for quantifying precipitation trends. New hydrological insights for the region: Annual precipitation exhibits a significant decreasing trend in the Arid, steppe, cold (BSk) and Cold, dry winter, hot/warm summer (Dwa/Dwb) climate zones, while a significant increasing trend occurs in the Cold, dry winter, cold summer (Dwc) and Polar, tundra (ET) climate zones. Middle and lower reaches within the same climate zone exhibit differences in annual precipitation trends, highlighting the important impacts of geographical location. Monthly precipitation shows an increasing trend in winter (December–February) across most climate zones, indicating relatively stable changes in winter precipitation, while other seasons show changes between increasing and decreasing trends. Climate zones with decreasing annual precipitation also show greater variability in monthly precipitation, facing the dual challenges of decreasing water resources and extreme precipitation events.

Deep learning techniques have been widely utilized for image recognition tasks. However, these techniques remain challenging in detecting aquatic plants due to their complex growing environments, long phenological periods, high species similarity, and the fact that they are often obscured by surrounding objects. To overcome these challenges, this study presents a comprehensive dataset of aquatic plant images in complex environments (DS-AP) and proposes a novel method, APNet-YOLOv8s. APNet-YOLOv8s integrates three modules: the Global Receptive Field-Space Pooling Pyramid-Fast (GRF-SPPF), the Shuffle Attention (SA) Mechanism, and the Fast Detection (FD), each designed to tackle specific challenges in aquatic plant detection. The performance of APNet-YOLOv8s was thoroughly evaluated using the DS-AP dataset. The results demonstrate that APNet-YOLOv8s significantly outperforms YOLOv8s, achieving a mean average precision (mAP50) of 75.3 % with a 2.7 % improvement, and a frame per second (FPS) rate of 30.5 with a 50.2 % increase. Moreover, APNet-YOLOv8s accurately and rapidly identifies aquatic plants in Gradient-weighted Class Activation Mapping (Grad-CAM) visualizations and real-world scenarios, highlighting its practical applications in complex environments. Overall, this study advances the application of deep learning in aquatic environments, providing a potential solution for rapid detection in other challenging environments.

Understanding the lagged correlations between regional precipitation and large scale climate indicators (LCI) is crucial for water management and drought risk assessment. Copula functions are commonly used to quantify the relationship between precipitation and these factors. However, existing studies often neglect monsoon inland areas and lack quantification of the lagged correlations of precipitation at the monthly scale. To address these limitations, this study constructed a 3-dimensional vine copula-based model to assess the impact of large scale climatic change on regional precipitation. The analysis focused on the Hengshao Drought Corridor (HDC), the driest region in Hunan Province, China. The results indicate that precipitation in this region is influenced primarily by the Pacific Ocean’s circulation pattern, particularly the Niño1 + 2 and Niño3 indices, with a 2 ∼ 3 month lag. The R-Vine Copula provided the best fit when identifying lagged correlations, but due to its fitting center, it did not perform as well as the C-Vine Copula in generating stochastic simulated precipitation. The study revealed that the HDC receives more precipitation when the Niño1 + 2 and Niño3 are asynchronous, but less precipitation when they are synchronous, making the area more susceptible to drought events. These findings have implications for the HDC and other monsoon inland regions worldwide, providing insights to cope with climate extremes and develop appropriate strategies.

Abstract Topographic Rossby waves (TRWs) dominate the low-frequency variability of deep ocean currents and play a crucial role in energy exchange and material mixing. On the continental slope of the southwestern South China Sea, a deep-water mooring was deployed to observe TRWs for a period of ~ 40 days. The TRWs, with a wavelength of 109 km, account for 41.3% of the subinertial variations. A ray-tracing model was applied to investigate the propagation and energy source. The results showed that the TRWs propagated from the northeast of the mooring location and were most likely caused by the mesoscale eddy disturbances off the Vietnam coast. This study provides a new perspective on examining the impact of mesoscale eddies off Vietnam on abyssal currents.

Abstract Background The tea plant (Camellia sinensis (L.) O. Kuntze) is one of the most economically important woody crops. Plastic greenhouse covering cultivation has been widely used in tea areas of northern China. Chlorophyll is not only the crucial pigment for green tea, but also plays an important role in the growth and development of tea plants. Currently, little is known about the effect of plastic greenhouse covering cultivation on chlorophyll in tea leaves. Results To investigate the effect of plastic greenhouse covering cultivation on chlorophyll in tea leaves, color difference values, chlorophyll contents, gene expression, enzyme activities and photosynthetic parameters were analyzed in our study. Sensory evaluation showed the color of appearance, liquor and infused leaves of greenhouse tea was greener than field tea. Color difference analysis for tea liquor revealed that the value of ∆L, ∆b and b/a of greenhouse tea was significantly higher than field tea. Significant increase in chlorophyll content, intracellular CO2, stomatal conductance, transpiration rate, and net photosynthetic rate was observed in greenhouse tea leaves. The gene expression and activities of chlorophyll-metabolism-related enzymes in tea leaves were also activated by greenhouse covering. Conclusion The higher contents of chlorophyll a, chlorophyll b and total chlorophyll in greenhouse tea samples were primarily due to higher gene expression and activities of chlorophyll-metabolism-related enzymes especially, chlorophyll a synthetase (chlG), pheophorbide a oxygenase (PAO) and chlorophyllide a oxygenase (CAO) in tea leaves covered by greenhouse. In general, our results revealed the molecular basis of chlorophyll metabolism in tea leaves caused by plastic greenhouse covering cultivation, which had great significance in production of greenhouse tea.

Abstract Effective watershed management hinges on understanding water sources and pollution origins. In the Hangbu Watershed of Chaohu Lake, China, we analyze pollution source patterns and propose an adaptive strategy. This adaptive strategy is defined as a flexible and dynamic approach that adjusts management practices and policies in response to evolving environmental conditions and emerging data on pollution sources. The analysis includes examining the trends, periodicity, and mutagenicity of pollution sources. The results demonstrated substantial variations in sources, with nitrogen and phosphorus. The adaptive approach enables prioritizing crucial pollution sources, with farmland identified as a significant contributor under varying conditions. Specific pollution sources with growth trends and control robustness have been recognized as vital contributors, even though their contributions to the nitrogen and phosphorus flux at the watershed outlets may not be the most prominent. The results of this study could guide the sustainable management of watersheds.

Designing floods in ungauged watersheds with limited data is a significant challenge in water conservancy projects. To address this, the method of calculating the design flood peak and flood volume using the weighted average method was proposed, which is based on the instantaneous unit hydrograph method and the inference formula method, combined with the characteristics of heavy rainfall floods in ungauged watersheds. The calculation results are analyzed in terms of reasonableness through the distribution pattern of the flood peak modulus under different frequencies of the constructed reservoirs, the relative error analysis, and the HEC-RAS model. Based on the one-day flood process of the adjacent basin, the calculation of deducing the design flood process using the hydrological comparison method was proposed. Taking the “Stormwater Runoff Chart” as the data source, the runoff generation, and concentration model was established with the design flood of Baludi Reservoir in the Gelangram River basin of Menglian, Yunnan Province as the research object. A comparative study of the results of the design floods calculated by different methods was carried out. The results show that the new method can well describe the rainstorm process. The method has better performance in the application to the design flood calculation of ungauged basins due to its consideration of the influence of subsurface conditions. The method not only reduces the construction cost but also improves the safety of the reservoir through a better-fitted design flood calculation.

Abstract The prognostic value of copper homeostasis-related genes in breast cancer (BC) remains largely unexplored. We analyzed copper homeostasis-related gene profiles within The Cancer Genome Atlas Program breast cancer cohorts and performed correlation analysis to explore the relationship between copper homeostasis-related mRNAs (chrmRNA) and lncRNAs. Based on these results, we developed a gene signature-based risk assessment model to predict BC patient outcomes using Cox regression analysis and a nomogram, which was further validated in a cohort of 72 BC patients. Using the gene set enrichment analysis, we identified 139 chrmRNAs and 16 core mRNAs via the Protein–Protein Interaction network. Additionally, our copper homeostasis-related lncRNAs (chrlncRNAs) (PINK1.AS, OIP5.AS1, HID.AS1, and MAPT.AS1) were evaluated as gene signatures of the predictive model. Kaplan–Meier survival analysis revealed that patients with a high-risk gene signature had significantly poorer clinical outcomes. Receiver operating characteristic curves showed that the prognostic value of the chrlncRNAs model reached 0.795 after ten years. Principal component analysis demonstrated the capability of the model to distinguish between low- and high-risk BC patients based on the gene signature. Using the pRRophetic package, we screened out 24 anticancer drugs that exhibited a significant relationship with the predictive model. Notably, we observed higher expression levels of the four chrlncRNAs in tumor tissues than in the adjacent normal tissues. The correlation between our model and the clinical characteristics of patients with BC highlights the potential of chrlncRNAs for predicting tumor progression. This novel gene signature not only predicts the prognosis of patients with BC but also suggests that targeting copper homeostasis may be a viable treatment strategy.

ObjectiveThis study focuses on the preparation and properties of high-performance electromagnetic shielding materials for electronic equipment in marine environments. MethodsThe surface morphology, phase composition, electrical conductivity and ferromagnetic properties of the original ferrosilicochrome powder (FeSiCr) and silver-coated powder (FeSiCr@Ag) are analyzed with a scanning electron microscope, X-ray diffractometer, four probes and vibrating sample magnetometer, and a vector network analyzer is used to test the S parameters of the samples. A salt spray test chamber is used to simulate the corrosion behavior of the coating under marine environment conditions and observe its macro and micro morphology. Meanwhile, an electrochemical workstation is used to monitor the corrosion behavior of the coating in a mass fraction of 3.5% NaCl solution and study its corrosion mechanism. ResultsThe results show that the silver plating layer is compact and complete with the increase of the silver nitrate (AgNO3) addition. After electroless silver plating, the conductivity can reach 586.79 S/cm and the X-band shielding efficiency reaches 80 dB. After 96 h of accelerated corrosion in a humid heat and high salt spray environment, the surface of the resin coating prepared by FeSiCr@Ag shows no corrosion phenomenon. The self-corrosion potential of the coating before and after electroless silver plating is −0.4 V and −0.09 V respectively, indicating that the penetration rate of the corrosive medium into the coating slows down after silver plating, and a good corrosion inhibition effect is achieved.ConclusionsThe modified FeSiCr@Ag material has highly efficient electromagnetic shielding performance and good corrosion resistance properties.

Recently, the number of birds along the 330kV transmission lines in the northwest region has gradually increased. The frequency of birds nesting and excreting on the towers has been steadily rising, with bird droppings increasingly becoming the primary factor causing bird-related tripping faults. A three-dimensional model of the tower cross arm, continuous bird droppings, and insulators was constructed to simulate and analyze the impact characteristics of bird droplet diameter, length, and relative position to insulators on the spatial electric field near the insulators. Experimental corrections were made, and based on simulation and experimental results, a bird-proof baffle was designed. Research results indicate that under conditions of single-ended grounding and suspended droplets of bird droppings, the average electric field strength at the lower end of the bird droppings and the grading ring was extracted to define the protective area against irregular-shaped bird droppings. After experimental validation, a correction coefficient of 1.4 was obtained based on the experimental results. A square protective baffle with a diversion function was designed based on simulation and experimental results. Bird droppings were placed at the baffle’s diversion groove, and the average electric field strength between the lower end of the bird droppings and the grading ring was consistently lower than the breakdown field strength of 2.98 kV/cm. The research results of this paper can serve as a basis for the subsequent designing of physical models of bird-proof baffles and prevention of bird-related flashover faults on V-type insulators.

Here, we report on a bifunctional alginate lyase (Vnalg7) expressed in Pichia pastoris, which can degrade natural Undaria pinnatifida into unsaturated guluronic acid di- and trisaccharide without pretreatment. The enzyme activity of Vnalg7 (3620.00 U/mL-culture) was 15.81-fold higher than that of the original alg (228.90 U/mL-culture), following engineering modification. The degradation rate reached 52.75%, and reducing sugar reached 30.30 mg/mL after combining Vnalg7 (200.00 U/mL-culture) and 14% (w/v) U. pinnatifida for 6 h. Analysis of the action mode indicated that Vnalg7 could degrade many substrates to produce a variety of unsaturated alginate oligosaccharides (AOSs), and the minimal substrate was tetrasaccharide. Site-directed mutagenesis showed that Glu238, Glu241, Glu312, Arg236, His307, Lys414, and Tyr418 are essential catalytic sites, while Glu334, Glu344, and Asp311 play auxiliary roles. Mechanism analysis revealed the enzymatic degradation pattern of Vnalg7, which mainly recognizes and attacks the third glycosidic linkage from the reducing end of oligosaccharide substrate. Our findings provide a novel alginate lyase tool and a sustainable and commercial production strategy for value-added biomolecules using seaweeds.

Abstract Left ventricular regional wall thickness (LVRWT) is an independent predictor of morbidity and mortality in cardiovascular diseases (CVDs). To identify specific genetic influences on individual LVRWT, we established a novel deep learning algorithm to calculate 12 LVRWTs accurately in 42,194 individuals from the UK Biobank with cardiac magnetic resonance (CMR) imaging. Genome-wide association studies of CMR-derived 12 LVRWTs identified 72 significant genetic loci associated with at least one LVRWT phenotype (P

Abstract Genome-wide association studies have identified numerous variants associated with human complex traits, most of which reside in the non-coding regions, but biological mechanisms remain unclear. However, assigning function to the non-coding elements is still challenging. Here we apply Activity-by-Contact (ABC) model to evaluate enhancer-gene regulation effect by integrating multi-omics data and identified 544,849 connections across 20 cancer types. ABC model outperforms previous approaches in linking regulatory variants to target genes. Furthermore, we identify over 30,000 enhancer-gene connections in colorectal cancer (CRC) tissues. By integrating large-scale population cohorts (23,813 cases and 29,973 controls) and multipronged functional assays, we demonstrate an ABC regulatory variant rs4810856 associated with CRC risk (Odds Ratio = 1.11, 95%CI = 1.05–1.16, P = 4.02 × 10−5) by acting as an allele-specific enhancer to distally facilitate PREX1, CSE1L and STAU1 expression, which synergistically activate p-AKT signaling. Our study provides comprehensive regulation maps and illuminates a single variant regulating multiple genes, providing insights into cancer etiology.

In view of various threats of strong electromagnetic environment to ship information equipment under electromagnetic space countermeasures and the requirement of electromagnetic protection, the mechanism of strong electromagnetic environment effect and basic protection principle of ship electronic equipment are prospected. The principle and development of frequency selective surface, energy selective surface and new electromagnetic shielding materials used to reduce the coupling of radiation field to ship electronic system are described; the principle and development of RF front-end protection technology based on gas discharge tube, semiconductor limiter, RF high power limiter technology based PIN diode and electromagnetic pulse protection technology based on plasma for suppressing the strong electromagnetic pulse transmission on the "circuit" are also introduced. This paper analyzes the applicability and advantages of different protection technologies in the design of ship equipment for strong electromagnetic pulse, and forecasts the future development trends of strong electromagnetic environment protection technology for ship equipment, provides support for the design of strong electromagnetic environment protection for ship equipment.

To investigate the effects of different packaging methods on microbial composition of chilled chicken during storage, the microbial diversity was analyzed by Illumina MiSeq high-throughput sequencing. The results showed that the modified atmosphere packaging (MAP), the vacuum packaging (VP) and the nitrogen-filled packaging (N2) could significantly reduce the number of microorganisms and volatile base nitrogen during refrigeration at 4 °C compared with the pallet packed (PP) group. High-throughput sequencing showed that the bacterial species richness of chilled chicken was high in the early stage of storage. The dominant bacteria of chilled chickens in PP group at the later stage of storage were Pseudomonas, Brochothrix, Acinetobacter and Shewanella. It indicated that they could tolerate lower temperatures. Compared with the PP group, the abundance of Pseudomonas and Acinetobacter in MAP group decreased by 14.8% and 9.2%, respectively, while nitrogen-filled packaging reduced the abundance of Acinetobacter and Shewanella. by 9.6% and 7.4%, respectively. The abundance of Acinetobacter and Brochothrix decreased significantly by 8% and 5.6% after vacuum packaging. Different packaging methods could have a greater impact on the flora in chilled chicken meat. All three types of packaging could inhibit the growth of Acinetobacter and MAP had a better inhibitory effect on Pseudomonas, while nitrogen-filled packaging and vacuum packaging had a better inhibitory effect on Shewanella and Brochothrix. This study also provides a theoretical basis for the future packaging methods used in chilled chicken meat.

To investigate the structural characteristics and driving factors of the metazooplankton community in the cascade reservoirs of Feiyun River Basin, monitoring surveys were conducted at 18 sampling sites across different seasons: September 2021 (autumn), January 2022 (winter), May 2022 (spring), and July 2022 (summer). These surveys identified 51 metazooplankton species, with the highest species abundance observed in summer and the lowest in winter. Notably, metazooplankton densities and biomasses peaked in spring, averaging 13.57 ind./l (where ind./l stands for individuals per liter) and 0.362 mg/l, respectively, while the lowest average densities (9.20 ind./l) and biomasses (0.262 mg/l) occurred in summer and winter, respectively. Seasonal variation had a notable influence on the community composition of metazooplankton, with Rotifera predominating in summer and autumn, and Copepoda in winter and spring. Cyclops larva and Nauplius species consistently dominated throughout. Correlation analyses revealed a significant negative association between metazooplankton richness and Pielou evenness indices with phosphate and total phosphorus concentrations, respectively. Redundancy analyses identified chlorophyll a, water temperature, total phosphorus, conductivity, pH, and phosphate as key environmental factors influencing the seasonal distribution of the metazooplankton community. This study provides a preliminary assessment of the seasonal dynamics of metazooplankton communities in the cascade reservoirs of the Feiyun River Basin, offering foundational insights for evaluating the ecological health of the basin waters.

ObjectiveAiming at the deficiency of the existing line impedance stability network (LISN) in the electromagnetic pulse protection capability, a LISN suitable for the pulse current injection (PCI) test of electrical and electronic equipment is proposed. MethodsAiming at the characteristics of high peak value and fast rise of the pulse current in PCI testing, the circuit structure and physical structure of the LISN are improved on the existing basis through PSpice time-domain and frequency-domain simulation combined with engineering design requirements, thereby giving it good nanosecond pulse protection performance and impedance stability at the same time. Pulse current protection performance test and impedance curve test experiments are then designed and carried out.ResultsThe experimental results show that the improved LISN can attenuate the injected pulse current by 60 times, while the error of its impedance curve is less than 5% compared with the Type 5 μH LISN in GJB 151B-2013. ConclusionsThe proposed LISN has good impedance stability and decoupling ability, and can be used in the PCI testing of electrical and electronic equipment in order to protect the power supply and improve the repeatability of testing.

The power system frequency is an important indicator that reflects the power system’s operating status. Through real-time detection or prediction, it can effectively ensure stable power system operation. To provide a theoretical basis for the steady-state recovery of thepower system after major disturbances, a deep belief neural network model for predicting the power system’s frequency response mode after major disturbances has been proposed. This model combines deep belief networks with deep neural networks. The feature extraction and learning abilities of deep belief networks were utilized to complete model training and learning. Deep neural networks were utilized to complete data classification and prediction. The load sudden variable is larger, the system frequency fluctuation is greater, the inertia time constant increases less, and the system frequency fluctuation is greater. In simulation testing with a training sample size of 2100 and a testing sample size of 900, the deep belief neural network took 3320 seconds, while the deep neural network took 11523 seconds. The prediction results’ absolute error amplitude of this deep belief neural network is 0.025Hz. It meets the practical needs of frequency response mode prediction in power systems after major disturbances. The study analyzed the impact of load sudden changes and inertia time constants on system frequency, and successfully designed a frequency response mode prediction model for power systems after major disturbances.

The highly infectious Delta variant strain of SARS-CoV-2 remains globally dominant and undermines COVID-19 vaccines. Rapid detection of the Delta variant is crucial for the identification and quarantine of infected individuals. In this study, our aim was to design and validate a genotyping RT-LAMP method to detect Delta variants specifically. R203M in the N gene of SARS-CoV-2 was chosen as the Delta variant-specific mutation for genotyping. To target the R203M-harboring region and the conserved sequence of the N gene, two sets of primers were designed, and a Cq (quantification cycle) ratio-based RT-LAMP for SARS-CoV-2 and R203M detection was developed by analyzing the significant discrepancy in amplification efficiency of the two sets of primers. We validated the RT-LAMP method on 498 clinical specimens in parallel with RT-qPCR, and 84 Delta variants from 198 positive samples were determined by sequencing. Compared with traditional RT-qPCR analyses, RT-LAMP appears to be 100% accurate in detecting SARS-CoV-2 clinical samples. RT-LAMP has a good ability to distinguish between Delta and non-Delta variants under a Cq ratio threshold of 1.80. Furthermore, the AUC (area under the curve) of this method was 1.00; the sensitivity, specificity and accuracy were all 100%. In summary, we have proposed a rapid, accurate and cost-effective RT-LAMP method to detect SARS-CoV-2 and Delta variants, which may facilitate the surveillance of COVID-19.

The water resources in Lianshui Basin is facing a prominent contradiction between production and ecology, as well as fierce competition among various regions. However, existing researches on spatial equilibrium typically tend to address only one of the dimensions among water resources system and other systems or among different regions, which can not meet the requirements for optimal allocation of water resources aiming for spatial equilibrium under the high-quality development strategy. The definition and quantitative evaluation method of spatial equilibrium remain unclear. In order to respond to the policy of spatial equilibrium and overcome the dilemma of water resources development and utilization under the new normal, the connotation of spatial equilibrium at two levels of system and region was presented, a quantitative dynamic evaluation method for the spatial equilibrium degree in system-region two stages was proposed in this study. A comprehensive evaluation indicators system was built for the water resources composite system composed of three subsystems: water resources, social economy and ecological environment, and a dynamic quantization model of coupling coordination degree based on the comprehensive evaluation indices of three subsystems was established, the temporal and spatial dynamic evolution process of the coupling coordination degree of water resources composite system was analyzed. At the same time, Theil index was used to research the dynamic evolution characteristics of the regional difference in coupling coordination degree in Lianshui Basin. This paper also identified the main source of difference based on the decomposition of Theil index, and the degree and trend of spatial equilibrium of water resources in Lianshui Basin were comprehensively analyzed. The results showed that the coupling coordination degree of the composite system of each district in Lianshui Basin was continuously improving, but there was no significant trend in the difference of coupling coordination degree among regions, which means the degree of spatial equilibrium in the “system stage” has notably improved, but the degree of spatial equilibrium in the “region stage” had no significant and stable increase. In addition, the difference within the region was always the main reason for the deficiency of spatial equilibrium.

Members of the class Opitutae are widely distributed in various environments such as rice paddy soil, freshwater lakes, seawater, marine sediment, and invertebrate digestive tracts. The class currently consists of two orders, Opitutales and Puniceicoccales, represented by the families Opitutaceae and Puniceicoccaceae, respectively, which are primarily delineated on the basis of 16S rRNA gene sequences and limited phenotypic characterizations of a few type strains. The scarcity of 16S rRNA gene and genome sequences generated from the type strains of the class Opitutae constrained our understanding of the ecological distribution and adequate resolution of its taxonomy. Here, an Opitutae strain designated WMMB3T, isolated from a mangrove sediment, was subjected to taxonomic characterization. The 16S rRNA gene of strain WMMB3T shared high sequence similarities with Coraliomargarita akajimensis DSM 45221T and C. sinensis WN38T of 96.1 and 95.9%, respectively. Phylogenetic analysis suggested that strain WMMB3T formed a monophyletic branch affiliated to the genus Coraliomargarita. The average nucleotide identity (ANI) values, digital DNA–DNA hybridization (dDDH) values and average amino acid identity (AAI) values of strain WMMB3T compared between Coraliomargarita members were 71.8–72.5, 20.7, and 68.2–68.7%, respectively, indicating that strain WMMB3T represented a novel species of Coraliomargarita. The genome of strain WMMB3T was 4.5 Mbp with a DNA G + C content of 56.0%. The respiratory quinone was menaquinone-7. The major fatty acids were iso-C14:0, and C18:1ω9c. Based on genomic, phenotypic, and chemotaxonomic characterizations, strain WMMB3T represents a novel species, and Coraliomargarita parva sp. nov. is proposed. Additionally, the phylogenomic analysis of more than 500 genomes of the class Opitutae, encompassing a majority of uncultivated bacteria and a few type strains, was performed using the Genome Taxonomic Database toolkit (GTDB-Tk) to present adequate resolution of the taxonomy. Combined with 16S rRNA gene sequence phylogeny and genomic relatedness, five novel families retrieved mainly from marine habitats were proposed: Coraliomargaritaceae fam. nov., Pelagicoccaceae fam. nov., Cerasicoccaeae fam. nov., Oceanipulchritudinaceae fam. nov., and Alterococcaeae fam. nov. AAI values of 58–60% could be considered as the boundary to delineate families of the class Opitutae. This study provided a new taxonomic framework of the class Opitutae based on the genomic data.

Most current water allocation strategies fail to address the unbalanced development among multiple systems. How to optimize the coordination development relationships among the social, economic and environmental systems has always been the focus. To bridge this gap, a water optimal allocation model for coordinated development was innovatively constructed and applied to the main stream of the Xiangjiang River Basin, China. The results showed the following. (i) From 2025 to 2030, the water deficit ratio of the study area will increase from 3.21 to 5.50% when P = 50% and from 4.59 to 6.85% when P = 75%. The existing water supply capacity will not be able to meet the increasing water demand. (ii) Agricultural and industrial water will account for a large proportion of the total water consumption. Due to the transformation of industrial structure, measures should be formulated to bring the best benefits. (iii) Restricted by different systems, the coordinated development in each city will present spatial and temporal differences. (iv) The proposed model was proved to overcome the backwards of uncoordinated development and achieve a balance of the regional social, economic and environmental benefits. Also, some recommendations and limitations were discussed. This study provides an effective basis for enhancing regional sustainable water resources planning and management. HIGHLIGHTS A new water optimal allocation model for coordinated development (WOAM-CD) is designed in this study.; The WOAM-CD can effectively deal with the uncoordinated development among the regional social-economic-environmental systems.; According to the regional water endowment and industrial characteristics, the WOAM-CD can draw up corresponding water allocation schemes to balance the social, economic and environmental benefits.;

The impacts of climate change and human activity, combined with streamflow reduction in the Yellow River Basin, have presented significant challenges to water resource management strategies. Here, the trends and change points of streamflow were determined for the period 1956–2017 via five statistical methods. A runoff-sensitive coefficients method (the Budyko hypothesis) and a conceptual rainfall–runoff model (the TUW model) were applied to assess the streamflow variation. The following conclusions were ascertained: (1) 1989, 1986, and 1990 were the change points for streamflow in the upstream Tang-Nai-Hai and Lan-Zhou stations and the downstream Hua-Yuan-Kou hydrological station; (2) the streamflow showed statistically significant decreasing trends with spatiotemporal variations in the Yellow River Basin; (3) the relationship between runoff and precipitation showed a downward trend over time; (4) comparisons of the Budyko and TUW models show that human activity is responsible for more than 65% of streamflow reduction, while climate change contributes to less than 35% of the reduction. Therefore, human activity is the main reason for streamflow reduction in the Yellow River Basin. This finding is of critical importance for water resources management under changing environment.

The accuracy of rotor position estimation determines the performance of the sensorless control system of a permanent magnet synchronous motor. In order to realize the accurate control of rotor position and speed, it is necessary to identify the motor parameters. Modeling and simulation of the state estimation are investigated for a permanent magnet synchronous motor with parameter identification based on the unscented Kalman filter (UKF) in this article. Based on the mathematical model of the motor, the unscented Kalman filter is used to identify the rotor flux and quadrature axis inductance simultaneously, and the identified parameters are used to update the motor model in the sensorless vector control algorithm. The simulation results show that the unscented Kalman filter can converge to the real value in a short time with small errors. It can follow the changes of motor parameters well and achieve high-precision speed and position estimation.

In order to reduce the chattering caused by the discontinuity of the control function in the traditional sliding mode observer (SMO), this article proposes a sliding mode observer with phase-locked loop (PLL) to estimate the speed and position of the rotor. The back electromotive force (EMF) of a permanent magnet synchronous motor (PMSM) in a static coordinate system is accurately estimated by SMO, and then, PLL is constructed to combine the observed rotor position angle and back EMF to compensate the phase lag in angle estimation so as to obtain a more accurate speed. It solves the problems of poor robustness and complex algorithms in the traditional SMO prediction algorithm. The simulation results show that the SMO with PLL can effectively reduce the system chattering and effectively improve the accuracy of rotor speed and position estimation.

The effects of modified atmosphere packaging (MAP) on the growth and spoilage characteristics of Pseudomonas lundensis LD1 and Shewanella putrefaciens SP1 in chilled chicken at 0–10 °C were studied. MAP inhibited microbial growth, TVB-N synthesis, and lipid oxidation. The inhibitory effect of MAP became more significant as the temperature decreased. The kinetic models to describe the growth of P. lundensis LD1 and S. putrefaciens SP1 at 0–10 °C were also established to fit the primary model Gompertz and the secondary model Ratkowsky. The models had a high degree of fit to describe the growth of dominant spoilage bacteria in chilled chicken. The observed numbers of P. lundensis LD1 and S. putrefaciens SP1 at 2 °C were compared with the predicted numbers, and the accuracy factor and bias factor ranged from 0.93 to 1.14. These results indicated that the two models could help predict the growth of P. lundensis and S. putrefaciens in chilled chicken at 0–10 °C. The analyzed models provide fast and cost-effective alternatives to replace traditional culturing methods to assess the influence of temperature and MAP on the shelf life of meat.

The conventional grey water footprint (GWF) cannot deal with the uncertainties induced by the background information. To solve this problem, this study develops a stochastic GWF model based on probability theory and the maximum entropy principle. The stochastic GWF model further introduces the expectation calculation and water pollution risk (WPR) identification into assessment, which are used to comprehensively evaluate the GWF and quantify the potential water shortage risk induced by pollution, respectively. To verify its effectiveness, the stochastic GWF is applied to the evaluation of chemical oxygen demand (COD) in Ningxia province, China. Results show the following: (i) compared with the conventional GWF, the stochastic GWF significant is in advantage in terms of grade identification, pollution ranking, and risk recognizing. (ii) From 2011 to 2017, the GWF expectations of COD in Ningxia provinces are 7.52, 7.32, 7.15, 6.92, 3.95, and 3.36 billion m3, and the WPRs are 0.51, 0.10, 0.13, 0.06, 0.00, and 0.00, respectively. (iii) The WPRs are determined not only by the pollution load but also by climate change and the hydrological rhythm. (iv) Only using the mathematical expectation of the background parameter for evaluation may ignore the environmental risk in the water area with high background values, making the evaluation over-optimistic.

Selective maintenance is widely used as a reliability-centered maintenance strategy due to the limited maintenance resources. However, existing selective maintenance studies only consider basic reliability, which cannot systematically describe the operating mechanism of a multistate system, thereby resulting in the inability to obtain an optimal maintenance strategy. Moreover, intelligent manufacturing systems are highly representative of typical multistate industrial systems. In this study, a mission reliability-oriented selective maintenance optimization model for intelligent manufacturing systems that considers the uncertain maintenance effect was proposed. First, a new connotation and modeling method for mission reliability based on multistate system theory was presented to comprehensively characterize the operating mechanism of intelligent manufacturing systems. Second, a quantitative model between maintenance resources and quality based on real-time data was established to reflect the uncertain characteristics caused by repairmen and tools. Third, a selective maintenance decision model of a multistate manufacturing system was developed under the constraints of maintenance cost and time. This constraint combination optimization problem was solved using the particle swarm optimization algorithm. Finally, a case study of selective maintenance optimization for a cylinder head manufacturing system was presented to verify the proposed method.

Abnormal development of central nervous system (CNS) caused by neural tube defects (NTDs) is not only remained the major contributor in the prevalence of stillbirths and neonatal deaths, but also represents a significant cause of lifelong physical disability in the surviving infants. Ethionine is a non-proteinogenic amino acid and antagonist of methionine. Methionine cycle is essential for the elimination of reactive oxygen species (ROS), while lysosomes are involved in the initiation of autophagy. However, its role in ethionine-induced cell death in neural tube defects, still need to be explored. In this study, we investigated the effect of ethionine on NTDs as well as the underlying mechanism involved in this process. Following the establishment of NTDs model using ethionine-induced C57BL/6 mice, ethionine was intraperitoneally injected at a dose of 500 mg/kg in E7.5. Our study revealed that ethionine has induced mitochondrial apoptosis in NTDs by reducing mitochondrial autophagy both in vivo and in vitro. These results provided a possible molecular mechanism for redox regulation of autophagic process.