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Accurate forecasting of wind speeds is a crucial aspect of providing fine-scale professional meteorological services (such as wind energy generation and transportation operations etc.). This article utilizes CMA-MESO model forecast data and CARAS-SUR_1 km ground truth grid data from January, April, July, and October 2022, employing the random forest algorithm to establish and evaluate a downscaling correction model for near-surface 1 km resolution wind-speed grid forecast in the complex terrain area of northwestern Hebei Province. The results indicate that after downscaling correction, the spatial distribution of grid forecast wind speeds in the entire complex terrain study area becomes more refined, with spatial resolution improving from 3 km to 1 km, reflecting fine-scale terrain effects. The accuracy of the corrected wind speed forecast significantly improves compared to the original model, with forecast errors showing stability in both time and space. The mean bias decreases from 2.25 m/s to 0.02 m/s, and the root mean square error (RMSE) decreases from 3.26 m/s to 0.52 m/s. Forecast errors caused by complex terrain, forecast lead time, and seasonal factors are significantly reduced. In terms of wind speed categories, the correction significantly improves forecasts for wind speeds below 8 m/s, with RMSE decreasing from 2.02 m/s to 0.59 m/s. For wind speeds above 8 m/s, there is also a good correction effect, with RMSE decreasing from 2.20 m/s to 1.65 m/s. Selecting the analysis of the Zhangjiakou strong wind process on 26 April 2022, it was found that the downscaled corrected forecast wind speed is very close to the observed wind speed at the station and the ground truth grid points. The correction effect is particularly significant in areas affected by strong winds, such as the Bashang Plateau and valleys, which has significant reference value. [ABSTRACT FROM AUTHOR]

During civil aviation flights, the aircraft needs to accurately monitor the real-time navigation capability and determine whether the onboard navigation system performance meets the required navigation performance (RNP). The airborne flight management system (FMS) uses actual navigation performance (ANP) to quantitatively calculate the uncertainty of aircraft position estimation, and its evaluation accuracy is highly dependent on the position estimation covariance matrix (PECM) provided by the airborne integrated navigation system. This paper proposed an adaptive PECM estimation method based on variational Bayes (VB) to solve the problem of ANP misevaluation, which is caused by the traditional simple ANP model failing to accurately estimate PECM under unknown time-varying noise. Combined with the 3D ANP model proposed in this paper, the accuracy of ANP evaluation can be significantly improved. This enhancement contributes to ensured navigation integrity and operational safety during civil flight. [ABSTRACT FROM AUTHOR]

The Whirly (WHY) gene family, functioning as transcription factors, plays an essential role in the regulation of plant metabolic responses, which has been demonstrated across multiple species. However, the WHY gene family and its functions in soybean remains unclear. In this paper, we conducted genome-wide screening and identification to characterize the WHY gene family. Seven WHY members were identified and randomly distributed across six chromosomes. The phylogenetic evolutionary tree of WHY genes in soybean and other species was divided into five clades. An in-depth analysis revealed that segmental duplications significantly contributed to the expansion of GmWHYs, and the GmWHY gene members may have experienced evolutionary pressure for purifying selection in soybeans. The analysis of promoter Cis-elements in GmWHYs suggested their potential significance in addressing diverse stress conditions. The expression patterns of GmWHYs exhibited tissue-specific variations throughout the different stages of soybean development. Additionally, six GmWHY genes exhibited different responses to low phosphate stress. These findings will provide a theoretical basis and valuable reference for the future exploration of WHY gene function. [ABSTRACT FROM AUTHOR]

The street spaces in tourist-oriented traditional villages served both the daily lives of villagers and the leisure activities of tourists. However, due to insufficient understanding of the spatial characteristics and under-exploration of spatial genes, these spaces often suffered from homogenization during tourism development. Thus, identifying the characteristics and connotations of such streets, understanding the relationship between tourists' perceptions and built environment elements, and developing optimization strategies for these rural street spaces were urgent issues. Many studies have evaluated street space characteristics from tourists' behavior, but few have focused on rural areas. Especially, research combining new technologies like artificial intelligence to study the psychological perceptions of tourists is still in its infancy. This study used a typical traditional village as a case study and applied the YOLOv5 deep-learning model to build a perception evaluation system based on three dimensions: tourists' aggregation degree, stay time, and facial expressions. The study conducted a multivariate regression analysis on 21 factors across 4 aspects: street scale morphology, environmental facilities, ground-floor interface, and street business types. Results indicated that the functional business type of the scene had the greatest impact on tourists' perception of the street space environment, followed by ground-floor features and environmental facilities. The regression coefficient for business in situ values and spatial perception was 0.47, highlighting it as a key factor influencing characteristic perception. Landscape water systems, flat ground-floor façades, and business diversity also positively affected tourists' perception. This study utilized advanced techniques like the YOLOv5 model, known for its speed and accuracy, to scientifically analyze tourists' behavior and perceptions, serving as feedback and evaluation for the village's built environment. Empirical analysis of Yuanjia Village validated the effectiveness of the multidimensional approach and spatial gene theory. Ultimately, this method identified 12 street characteristic factors significantly affecting tourists' perceptions. The uniqueness of this study lies in its comprehensive approach, combining empirical research, spatial gene theory, and advanced object detection technology, providing new insights for village spatial planning and construction. [ABSTRACT FROM AUTHOR]

Among female oncology patients, cervical cancer stands as the fourth most prevalent malignancy, exerting significant impacts on their health. Over 600,000 women received the diagnosis of cervical cancer in 2020, and the illness claimed over 300,000 lives globally. Curdepsidone A, a derivative of depsidone, was isolated from the secondary metabolites of Curvularia sp. IFB-Z10. In this study, we revised the molecular structure of curdepsidone A and investigated the fundamental mechanism of the anti-tumor activity of curdepsidone A in HeLa cells for the first time. The results demonstrated that curdepsidone A caused G0/G1 phase arrest, triggered apoptosis via a mitochondrial apoptotic pathway, blocked the autophagic flux, suppressed the PI3K/AKT pathway, and increased the accumulation of reactive oxygen species (ROS) in HeLa cells. Furthermore, the PI3K inhibitor (LY294002) promoted apoptosis induced by curdepsidone A, while the PI3K agonist (IGF-1) eliminated such an effect. ROS scavenger (NAC) reduced curdepsidone A-induced cell apoptosis and the suppression of autophagy and the PI3K/AKT pathway. In conclusion, our results revealed that curdepsidone A hindered cell growth by causing cell cycle arrest, and promoted cell apoptosis by inhibiting autophagy and the ROS-mediated PI3K/AKT pathway. This study provides a molecular basis for the development of curdepsidone A as a new chemotherapy drug for cervical cancer. [ABSTRACT FROM AUTHOR]

The environmental/economic dispatch (EED) of power systems addresses the environmental pollution problems caused by power generation at the operational level, offering macroscopic control without requiring additional construction and remediation costs, garnering widespread attention in recent years. This paper undertakes a comprehensive review of existing EED models, categorizing them according to the control of atmospheric pollutants into total air pollutant control (TAPC) and control considering the spatial and temporal diffusion (STD) of atmospheric pollutants. In addition, various methods employed to address the EED problems, as well as the current state of research on multi-area EED models, are presented. Finally, this paper analyzes and summarizes the literature on existing EED models, highlighting the deficiencies of the current work and future research directions. Through these explorations, the authors find that controlling the EED model by considering TAPC is more suitable for general macro planning, whereas the EED model considering the STD of air pollutant emissions enables more precise and effective control. Summarizing such models and techniques is conducive to developing dispatch plans adapted to local conditions, which is significantly beneficial for public welfare and government management, promoting sustainable and environmentally friendly power system dispatch methods. [ABSTRACT FROM AUTHOR]

This paper discusses the dissipative filtering problem for discrete-time nonlinear networked systems with dynamic quantization and data packet dropouts. The Takagi–Sugeno (T–S) fuzzy model is employed to approximate the considered nonlinear plant. Both the measurement and performance outputs are assumed to be quantized by the dynamic quantizers before being transmitted. Moreover, the Bernoulli stochastic variables are utilized to characterize the effects of data packet dropouts on the measurement and performance outputs. The purpose of this paper is to design full- and reduced-order filters, such that the stochastic stability and dissipative filtering performance for the filtering error system can be guaranteed. The collaborative design conditions for the desired filter and the dynamic quantizers are expressed in the form of linear matrix inequalities. Finally, simulation results are used to illustrate the feasibility of the proposed filtering scheme. [ABSTRACT FROM AUTHOR]

Radar reflectivity plays a crucial role in detecting heavy rainfall and is an important tool for meteorological analysis. However, the coverage of a single radar is limited, leading to the use of satellite data as a complementary source. Consequently, how to bridge the gap between radar and satellite data has become a growing research focus. In this paper, we present MAFormer, a novel model for reconstructing radar reflectivity using satellite data within the Transformer framework. MAFormer consists of two modules: the Axial Local Attention Module and the Mixup Global Attention Module, which extract both local saliency and global similarity. Quantitative and qualitative experiments demonstrate the effectiveness of our proposed method. Specifically, the MAFormer model exhibits notable advancements when compared to state-of-the-art deep learning techniques. It demonstrates an improvement ranging from 0.01 to 0.05 in terms of the Heidke skill score, indicating its superior performance. Additionally, MAFormer effectively mitigates false alarm rates by approximately 0.016 to 0.04, which further highlights its enhanced accuracy and reliability. [ABSTRACT FROM AUTHOR]

The integrity of airborne inertial navigation systems (INSs) is the key to ensuring the safe flight of civil aircraft. The airborne attitude and heading reference system (AHRS) is introduced into the construction of a redundant inertial navigation system. As a backup system for an airborne INS, the AHRS exhibits a different device performance. A sequential weighted generalized likelihood ratio test (SWGLT) method, based on a principal component parity vector (PPV), is proposed. The PPV method improves the adaptability of the detection threshold to the inertial sensors' noise and improves the probability of correct detection. At the same time, the multiscale problem of a heterogeneous redundant system error is solved by sequential weighting, and the false alarm rate is reduced. Simulation experiments show that the proposed method can improve fault detection sensitivity, reduce false alarm rates, and ensure the integrity of civil aircraft navigation systems. [ABSTRACT FROM AUTHOR]

Based on the Quick Access Recorder (QAR) data covering over 9000 routes in China, the monthly and intra-day distribution characteristics of aircraft bumpiness at different levels were analyzed, and the relationships between the eddy dissipation rate (EDR) and other aircraft flight status elements during bumpiness occurrence were also analyzed. Afterward, aircraft bumpiness routes were constructed using 19 machine learning models. The analyses show that (1) aircraft bumpiness was mainly concentrated between 0:00 a.m. and 17:00 p.m. Severe aircraft bumpiness occurred more frequently in the early morning in January, especially between 5:00 a.m. and 6:00 a.m., and moderate bumpiness always occurred from 3:00 a.m. to 11:00 a.m. (2) The relationship between the left and right attack angles and aircraft bumpiness on the routes was more symmetrical, with a center at 0 degrees, unlike in the approach area where the hotspots were mainly concentrated in the range of −5 to 0 degrees. In the approach area, the larger the Mach number, the more severe the bumpiness. (3) The performances of the Automatic Relevance Determination Regression (ARD), Partial Least Squares Regression (PLS), Elastic-Net Regression (ENR), Classification and Regression Tree (CART), Passive Aggressive Regression (PAR), Random Forest (RF), Stochastic Gradient Descent Regression (SGD), and Tweedie Regression (TWD) based models were relatively good, while the performances of the Huber Regression (HUB), Least Angle Regression (LAR), Polynomial Regression (PLN), and Ridge Regressor (RR) based models were very poor. The aircraft bumpiness prediction models performed best over the approach area of ZBDT (airport in Datong), ZULS (airport in Lhasa), ZPPP (airport in Kunming), and ZLQY (airport in Qingyang). The model performed best in predicting the ZLLL-ZBDT air route (flight routes for Lanzhou to Datong) with different prediction times. [ABSTRACT FROM AUTHOR]

On 8 January 2022, a seismic event of significant magnitude (Mw 6.7, Ms 6.9) occurred in the northeastern region of the Tibetan Plateau. This earthquake was characterized by left-lateral strike-slip motion, accompanied by a minor reverse movement. The Menyuan earthquake resulted in the formation of two main ruptures and one secondary rupture. These ruptures were marked by a left-lateral step zone that extended over a distance of 1 km between the main ruptures. The length of the rupture zones was approximately 37 km. The surface rupture zone exhibited various features, including left-lateral offset small gullies, riverbeds, wire fences, road subgrades, mole tracks, cracks, and scarps. Through a comprehensive field investigation and precise measurement using unmanned aerial vehicle (UAV) imagery, 111 coseismic horizontal offsets were determined, with the maximum offset recorded at 2.6 ± 0.3 m. The analysis of aftershocks and the findings from the field investigation led to the conclusion that the earthquake was triggered by the Lenglongling fault and the Tuolaishan fault. These faults intersected at a release double-curved structure, commonly referred to as a stepover. During this particular process, the Lenglongling fault was responsible for initiating the coseismic rupture of the Sunan–Qilian fault. It is important to note that the stress applied to the Tuolaishan fault has not been fully relieved, indicating the presence of potential future hazards. [ABSTRACT FROM AUTHOR]

Heavy metal contamination is among the most prominent environmental problems in China, posing serious threats to both ecosystem and human health. Among the diverse heavy metal contaminants, cadmium is the most serious. The whitefly Bemisia tabaci is a cosmopolitan pest capable of causing severe damage to a broad range of agricultural crops, especially vegetables. At present, little is known about the effects of cadmium stress on B. tabaci, including on its bacterial and fungal communities. In the current study, we investigated the effects of cadmium on bacterial and fungal communities in whiteflies. Meta-barcode sequencing of the 16S rRNA gene revealed that the whitefly bacterial community contained 264 operational taxonomic units (OTUs) belonging to 201 known genera and 245 known species. The top five most frequent bacterial genera were Rickettsia, Rhodococcus, Candidatus Portiera, Candidatus Hamiltonella, and Achromobacter. Meta-barcode sequencing of the fungal ITS locus revealed that the whitefly fungal community contained 357 OTUs belonging to 187 known genera and 248 known species. The top five most frequent fungal genera were Wallemia, unclassified_f_Dipodascaceae, Apiotrichum, Penicillium, and unclassified_o_Saccharomycetales. Cadmium exposure reduced the fungal OTU richness but increased the bacterial Shannon and Simpson diversity indices in whiteflies. In addition, upon exposure to cadmium, the microbial community composition in whiteflies changed significantly, with increased prevalence of the bacterial genera Rhodococcus and Exiguobacterium and fungal genus Wallemia. Our results indicate that the whitefly microbiota likely contributed to their adaptation and resistance to cadmium and suggested that whiteflies may contain microbes that could help remediate cadmium contamination in natural environments and agricultural fields. [ABSTRACT FROM AUTHOR]

SUPPRESSOR OF MAX2-LIKE 6, 7, and 8 (SMXL6,7,8) function as repressors and transcription factors of the strigolactone (SL) signaling pathway, playing an important role in the development and stress tolerance in Arabidopsis thaliana. However, the molecular mechanism by which SMXL6,7,8 negatively regulate drought tolerance and ABA response remains largely unexplored. In the present study, the interacting protein and downstream target genes of SMXL6,7,8 were investigated. Our results showed that the substrate receptor for the CUL4-based E3 ligase DDB1-BINDING WD-REPEAT DOMAIN (DWD) HYPERSENSITIVE TO ABA DEFICIENT 1 (ABA1) (DWA1) physically interacted with SMXL6,7,8. The degradation of SMXL6,7,8 proteins were partially dependent on DWA1. Disruption of SMXL6,7,8 resulted in increased drought tolerance and could restore the drought-sensitive phenotype of the dwa1 mutant. In addition, SMXL6,7,8 could directly bind to the promoter of SUCROSE NONFERMENTING 1 (SNF1)-RELATED PROTEIN KINASE 2.3 (SnRK2.3) to repress its transcription. The mutations in SnRK2.2/2.3 significantly suppressed the hypersensitivity of smxl6/7/8 to ABA-mediated inhibition of seed germination. Conclusively, SMXL6,7,8 interact with DWA1 to negatively regulate drought tolerance and target ABA-response genes. These data provide insights into drought tolerance and ABA response in Arabidopsis via the SMXL6,7,8-mediated SL signaling pathway. [ABSTRACT FROM AUTHOR]

The audible noise generated by corona discharge has the N-type characteristic at the initial generation stage, and it is a typical shock wave. This shock wave usually only exists around the corona source with a tiny range, making it difficult to obtain its characteristics through experimental measurements. An electrosound-combined simulation of the corona discharge based on the shock wave theory was conducted, and the development process involving the corona discharge, shock wave, and sound wave was simulated. First, the corona was numerically simulated based on the 2D pin–plate axisymmetric hydrodynamic model. It was found that the plasma was mainly distributed near the axis of the corona field where the electric field changed violently, and the maximum value of the electric field appeared at the head of the discharge channel. Then, the plasma energy was equivalent to the explosive energy, and a plasma explosion shock model was established. It was found that the shock wave pressure had obvious positive and negative pressure zones, and the propagation velocity decays to the sound velocity gradually. Finally, the shock wave pressure derived by the explosion model was used as the acoustic source, and the acoustic wave propagation process was simulated. The simulated sound pressure waveform had the same characteristics as the relevant experimental measurement results, proving that the developed method possessed strong applicability and gave rise to a new angle for the simulation of corona-generated audible noise. [ABSTRACT FROM AUTHOR]

α-Ketoglutarate decarboxylase is a crucial enzyme in the tricarboxylic acid cycle of cyanobacteria, catalyzing the non-oxidative decarboxylation of α-ketoglutarate to produce succinate semialdehyde and CO2. The decarboxylation process is reliant on the cofactor of thiamine diphosphate. However, this enzyme's biochemical and structural properties have not been well characterized. In this work, two α-ketoglutarate decarboxylases encoded by MAE_06010 and MiAbw_01735 genes from Microcystis aeruginosa NIES-843 (MaKGD) and NIES-4325 (MiKGD), respectively, were overexpressed and purified by using an Escherichia coli expression system. It was found that MaKGD exhibited 9.2-fold higher catalytic efficiency than MiKGD, which may be attributed to the absence of glutamate decarboxylase in Microcystis aeruginosa NIES-843. Further biochemical investigation of MaKGD demonstrated that it displayed optimum activity at pH 6.5–7.0 and was most activated by Mg2+. Additionally, MaKGD showed substrate specificity towards α-ketoglutarate. Structural modeling and autodocking results revealed that the active site of MaKGD contained a distinct binding pocket where α-ketoglutarate and thiamine diphosphate interacted with specific amino acid residues via hydrophobic interactions, hydrogen bonds and salt bridges. Furthermore, the mutagenesis study provided strong evidence supporting the importance of certain residues in the catalysis of MaKGD. These findings provide new insights into the structure-function relationships of α-ketoglutarate decarboxylases from cyanobacteria. [ABSTRACT FROM AUTHOR]

Mammalia cysteamine (2-aminoethanethiol) dioxygenase (ADO) controls the stability of the regulator of G protein signaling 4 (RGS4) through the Cys branch of the Arg/N-degron pathway, thereby affecting the response of the body to hypoxia. However, the oxygen-sensing function of ADO remains unknown in teleost fish. Mandarin fish (Siniperca chuatsi) is one of the most important freshwater economic fishes in China. As the scale of the rearing density continues to increase, hypoxia has become an important factor threatening the growth of mandarin fish. Herein, the molecular characterization, the oxygen-sensing enzyme function, and the role in virus infection of ADO from mandarin fish (scADO) were explored. Bioinformation analysis results showed that scADO had all the molecular foundations for achieving thiol dioxygenase function: three histidine residues coordinated with Fe(II), PCO/ADO domain, and a "jelly roll" β-barrel structure. The expression pattern analysis showed that scAdo was highly expressed in the immune-related tissues, liver, and kidneys and responded to hypoxia on the expression level. Protein degradation experiment results revealed that scADO could lead to the degradation of RGS4 protein through the Cys branch of the Arg/N-degron pathway. Furthermore, the expression levels of scADO responded to fish virus infection. scADO could significantly promote the replication of Siniperca chuatsi rhabdovirus, and this was associated with its thiol dioxygenase activity. These findings not only demonstrate scADO as an oxygen-sensing protein in teleost fish, but are also of considerable importance for clarifying the contribution of the mechanism of hypoxia to the outbreaks of fish viruses. [ABSTRACT FROM AUTHOR]

The formation and development of potato tissues and organs is a complex process regulated by a variety of genes and environmental factors. The regulatory mechanisms underlying the growth and development are still unclear. In this work, we aimed to explore the changes in gene expression patterns and genetic characteristics of potato tissues throughout different developmental stages. To achieve this, we used autotetraploid potato JC14 as an experimental subject to analyze the transcriptome of the root, stem, and leaf at the seedling, tuber formation, and tuber expansion stages. The results revealed thousands of differentially expressed genes, predominantly involved in defense response and carbohydrate metabolism according to KEGG pathway enrichment analysis. Weighted gene co-expression network analysis (WGCNA) revealed a total of 12 co-expressed gene modules, with 4 modules showing the highest correlation with potato stem development. By calculating the connectivity of genes within the module, hub genes were identified, and functional annotations were subsequently performed. A total of 40 hub genes from the four modules were identified, and their functions were found to be related to carbohydrate metabolism, defense response, and transcription factors. These findings provide important insights for further understanding of the molecular regulation and genetic mechanisms involved in potato tissue development. [ABSTRACT FROM AUTHOR]

This paper examines two pieces of Ru porcelain glaze excavated from the Qingliangsi kiln site. Compared with the R1 glaze, the R2 glaze was fired at a lower temperature and cooled at a slower rate. The chemical composition, microstructure, and corrosion mechanisms of the two glazes were analyzed by optical microscopy (OM), scanning electron microscopy-energy dispersive X-ray spectroscopy (SEM-EDS), micro-Raman spectroscopy, transmission electron microscopy (TEM), and X-ray diffraction (XRD). The results show that the corrosion morphology of R1 glaze is mainly the dissolution of a three-dimensionally interconnected calcium (Ca)-rich phase around anorthite, and that of R2 glaze is mainly the dissolution of small droplets distributed in rows, including the dissolution of needle-like wollastonite precipitated by droplet aggregation. In addition, the dissolution of the glass phase and wollastonite crystals forms many white corrosion pits, and the physical and chemical interaction between the corroded glaze and the soil results in the deposition of contaminants that alters the color and texture of the glaze. [ABSTRACT FROM AUTHOR]

Simple Summary: Hypoxic stress often occurs in aquaculture environments and is primarily mediated by the hypoxia-inducible factor 1 (HIF-1) signaling pathway. Prolyl hydroxylase domain proteins (PHD) are cellular oxygen-sensing molecules that regulate the stability of HIF-1α. In this study, the characterization of the PHD2 from mandarin fish Siniperca chuatsi (scPHD2) and its roles in the HIF-1 signaling pathway were investigated. This study furthers our understanding of the molecular mechanisms underlying hypoxia adaptation in teleost fish. With increased breeding density, the phenomenon of hypoxia gradually increases in aquaculture. Hypoxia is primarily mediated by the hypoxia-inducible factor 1 (HIF-1) signaling pathway. Prolyl hydroxylase domain proteins (PHD) are cellular oxygen-sensing molecules that regulate the stability of HIF-1α through hydroxylation. In this study, the characterization of the PHD2 from mandarin fish Siniperca chuatsi (scPHD2) and its roles in the HIF-1 signaling pathway were investigated. Bioinformation analysis showed that scPHD2 had the conserved prolyl 4-hydroxylase alpha subunit homolog domains at its C-terminal and was more closely related to other Perciformes PHD2 than other PHD2. Tissue-distribution results revealed that scphd2 gene was expressed in all tissues tested and more highly expressed in blood and liver than in other tested tissues. Dual-luciferase reporter gene and RT-qPCR assays showed that scPHD2 overexpression could significantly inhibit the HIF-1 signaling pathway. Co-immunoprecipitation analysis showed that scPHD2 could interact with scHIF-1α. Protein degradation experiment results suggested that scPHD2 could promote scHIF-1α degradation through the proteasome degradation pathway. This study advances our understanding of how the HIF-1 signaling pathway is regulated by scPHD2 and will help in understanding the molecular mechanisms underlying hypoxia adaptation in teleost fish. [ABSTRACT FROM AUTHOR]

This paper considers a wireless sensor network (WSN) assisted by the unmanned aerial vehicle (UAV) in the Internet of Things (IoT). The UAV departs from the data center to the ground node to collect sensor node data as a relay. Under the constraints of battery energy, the UAV will travel to and from the data center repeatedly and transmit the collected sensor node data. The freshness of the node data received by the data center is measured by the Age of Information (AoI) as a performance metric. A genetic algorithm is used to plan the flight trajectory of the UAV. To ensure the data's integrity and accuracy in a single sensor node, the UAV continuously collects sensor node data when the distance from the sensor node is less than the minimum acquisition distance. Through simulation experiments, we analyzed the influence of changing acquisition distance, the initial battery capacity, acquisition success probability, and transmission power on the peak age of information and the average age of information. [ABSTRACT FROM AUTHOR]

The enzyme encoded by slr1022 gene from Synechocystis sp. PCC6803 was reported to function as N-acetylornithine aminotransferase, γ-aminobutyric acid aminotransferase, and ornithine aminotransferase, which played important roles in multiple metabolic pathways. Among these functions, N-acetylornithine aminotransferase catalyzes the reversible conversion of N-acetylornithine to N-acetylglutamate-5-semialdehyde with PLP as cofactor, which is a key step in the arginine biosynthesis pathway. However, the investigation of the detailed kinetic characteristics and catalytic mechanism of Slr1022 has not been carried out yet. In this study, the exploration of kinetics of recombinant Slr1022 illustrated that Slr1022 mainly functioned as N-acetylornithine aminotransferase with low substrate specificity to γ-aminobutyric acid and ornithine. Kinetic assay of Slr1022 variants and the model structure of Slr1022 with N-acetylornithine-PLP complex revealed that Lys280 and Asp251 residues were the key amino acids of Slr1022. The respective mutation of the above two residues to Ala resulted in the activity depletion of Slr1022. Meanwhile, Glu223 residue was involved in substrate binding and it served as a switch between the two half reactions. Other residues such as Thr308, Gln254, Tyr39, Arg163, and Arg402 implicated a substrate recognition and catalytic process of the reaction. The results of this study further enriched the understanding of the catalytic kinetics and mechanism of N-acetylornithine aminotransferase, especially from cyanobacteria. [ABSTRACT FROM AUTHOR]

This paper investigates the observer-based non-fragile output feedback tracking control problem for nonlinear networked systems with randomly occurring gain variations. The considered nonlinear networked systems are represented by a Takagi–Sugeno (T–S) fuzzy model. The dynamical quantization methodology is employed to achieve the reasonable and efficacious utilization of the limited communication resources. The objective is to design the observer-based non-fragile output feedback tracking controller, such that the resulting system is mean-square asymptotically stable with the given  H ∞ tracking performance. Based on the descriptor representation strategy combined with the S-procedure, sufficient conditions for the existence of the desired dynamic quantizers and observer-based non-fragile tracking controller are proposed in the form of linear matrix inequalities. Finally, simulation results are provided to show the effectiveness of the proposed design method [ABSTRACT FROM AUTHOR]

Simple Summary: The macrophage CD163 surface glycoprotein is a member of the scavenger receptor cysteine-rich (SRCR) family class B. It has been identified as the receptor for hemoglobin–haptoglobin (Hb-Hp) complexes and erythroblasts, and it is the key trigger in host–pathogen interactions. Previous studies have implicated porcine CD163 in macrophage activation delay upon infection with virulent G. parasuis strains, while its exact roles in sensing G. parasuis infection have not yet been assessed. Here, we investigated the role of CD163 in mediating the adhesion and immune response of G. parasuis using in vitro host–pathogen interaction models. We provide evidence that CD163 plays a minor role, unlike those seen in infections with other pathogens, in mediating G. parasuis infection. The macrophage CD163 surface glycoprotein is a member of the SRCR family class B, which has been identified as the key trigger in host–pathogen interactions, but its specific roles in sensing Glaesserella parasuis (G. parasuis) infection are largely unknown. Here, we investigated porcine CD163 in mediating the adhesion and immune response of G. parasuis using in vitro host–bacteria interaction models. CD163-overexpressing Chinese hamster ovary K1 cells (CHO-K1) showed obvious subcellular localization in the cytoplasm, especially in the cytomembrane. Although detection using scanning electron microscopy (SEM) confirmed the bacterial adhesion, there was no significant difference in the adhesion of G. parasuis to CHO-K1 cells between the presence and absence of CD163. In addition, similar results were observed in 3D4/21 cells. Meanwhile, bindings of G. parasuis to nine synthetic peptides, the bacterial binding motifs within SRCR domains of CD163, were weak based on a solid-phase adhesion assay and agglutination assay. Moreover, CD163 had no effect on the expression of G. parasuis-induced inflammatory cytokines (IL-6, INF-γ, IL-10, IL-4 and TGF-β) in CHO-K1 cells. In conclusion, these findings indicate that porcine CD163 plays a minor role in sensing G. parasuis infection. [ABSTRACT FROM AUTHOR]

Polyetheretherketone (PEEK) is a thermoplastic material widely used in engineering applications due to its good biomechanical properties and high temperature stability. Compared to traditional metal and ceramic dental materials, PEEK dental implants exhibit less stress shielding, thus better matching the mechanical properties of bone. As a promising medical material, PEEK can be used as implant abutments, removable and fixed prostheses, and maxillofacial prostheses. It can be blended with materials such as fibers and ceramics to improve its mechanical strength for better clinical dental applications. Compared to conventional pressed and CAD/CAM milling fabrication, 3D-printed PEEK exhibits excellent flexural and tensile strength and parameters such as printing temperature and speed can affect its mechanical properties. However, the bioinert nature of PEEK can make adhesive bonding difficult. The bond strength can be improved by roughening or introducing functional groups on the PEEK surface by sandblasting, acid etching, plasma treatment, laser treatment, and adhesive systems. This paper provides a comprehensive overview of the research progress on the mechanical properties of PEEK for dental applications in the context of specific applications, composites, and their preparation processes. In addition, the research on the adhesive properties of PEEK over the past few years is highlighted. Thus, this review aims to build a conceptual and practical toolkit for the study of the mechanical and adhesive properties of PEEK materials. More importantly, it provides a rationale and a general new basis for the application of PEEK in the dental field. [ABSTRACT FROM AUTHOR]

Image-based quantified visibility estimation is an important task for both atmospheric science and computer vision. Traditional methods rely largely on meteorological observation or manual camera calibration, which restricts its performance and generality. In this paper, we propose a new end-to-end pipeline for single image-based quantified visibility estimation by an elaborate integration between meteorological physical constraint and deep learning architecture design. Specifically, the proposed Deep Quantified Visibility Estimation Network (abbreviated as DQVENet) consists of three modules, i.e., the Transmission Estimation Module (TEM), the Depth Estimation Module (DEM), and the Extinction coEfficient Estimation Module (E3M). Casting on these modules, the meteorological prior constraint can be combined with deep learning. To validate the performance of DQVENet, this paper also constructs a traffic image dataset (named QVEData) with accurate visibility calibration. Experimental results compared with many state-of-the-art methods on QVEData demonstrate the effectiveness and superiority of DQVENet. [ABSTRACT FROM AUTHOR]

Performance-based navigation (PBN) operations based on the required navigation performance (RNP) operations are the trend for civil aviation in the future. In order to further ensure the safety and efficiency of civil aviation operation, RNP will transition from 2D to 3D/4D. Accurately evaluating the actual navigation performance in three-dimensional directions (3D ANP) under civil aircraft RNP operation is important to guarantee the safe flight of civil aircraft. However, the traditional two-dimensional ANP evaluation method mainly focuses on plane navigation performance along the track, lacks the evaluation of the vertical direction. Moreover, the traditional three-dimensional accuracy evaluation method is based on the assumption of three-dimensional independence and uniformity, which can only carry out approximate calculation, and the evaluation result is inaccurate. Therefore, this paper constructs a three-dimensional ellipsoid error probability (EEP) evaluation model for the spatial position uncertainty of the navigation output of the flight management system in three-dimensional directions, and gives the three-dimensional accurate ANP calculation results through iterative numerical integration. The simulation results show that the evaluation method proposed in this paper can accurately evaluate the actual navigation performance of the airborne navigation system in all directions of 3D space, and has higher evaluation accuracy and precision than the traditional ANP evaluation method, which is of great significance to ensure the flight safety of civil aircraft under 3D/4D RNP operation in the future. [ABSTRACT FROM AUTHOR]

A magnitude (Mw) 7.4 Maduo earthquake occurred on 22 May 2021 in the northern Qinghai-Tibet Plateau, with predominantly left-lateral strike-slip faulting and a component of normal faulting within the Bayan Har Block. The co-seismic surface rupture extended in a NWW direction for ~160 km with a complicated geometry along a poorly known young fault: the Jiangcuo Fault. The main surface rupture propagated bilaterally from the epicenter and terminated eastward in horsetail splays. The main rupture can be divided into five segments with two rupture gaps. Field surveys and detailed mapping revealed that the co-seismic surface ruptures were characterized by a series of left-lateral offsets, en echelon tensional cracks and fissures, compressional mole tracks, and widespread sand liquefication. The observed co-seismic left-lateral displacements ranged from 0.2 m to ~2.6 m, while the vertical displacements ranged from 0.1 m to ~1.5 m, much lower than the InSAR inverse slip maximum of 2–6 m. Based on the comprehensive analysis of the causative fault geometry and the tectonic structure of the northern Bayan Har Block, this study suggests that the multiple NWW trending sub-faults, including the Jiangcuo Fault, developed from the East Kunlun fault northeast of the Bayan Har Block could be regarded as the sub-faults of the East Kunlun Fault system, constituting a broad and dispersive northern boundary of the Block, controlling the inner strain distribution and deformation. [ABSTRACT FROM AUTHOR]

Obtaining a full short tandem repeat (STR) profile from a low template DNA (LT-DNA) still presents a challenge for conventional methods due to significant stochastic effects and polymerase slippage. A novel amplification method with a lower cost and higher accuracy is required to improve the DNA amount. Previous studies suggested that DNA polymerases without bypass activity could not perform processive DNA synthesis beyond abasic sites in vitro and our results showed a lack of bypass activity for Phusion, Pfu and KAPA DNA polymerases in this study. Based on this feature, we developed a novel linear amplification method, termed Linear Aamplification for double-stranded DNA using primers with abasic sites near 3′ end (abLAFD), to limit the replication error. The amplification efficiency was evaluated by qPCR analysis with a result of approximately a 130-fold increase in target DNA. In a LT-DNA analysis, the abLAFD method can be employed as a pre-PCR. Similar to nested PCRs, primer sets used for the abLAFD method were designed as external primers suitable for commercial multiplex STR amplification assays. The practical performance of the abLAFD method was evaluated by coupling it to a routine PP21 STR analysis using 50 pg and 25 pg DNA. Compared to reference profiles, all abLAFD profiles showed significantly recovered alleles, increased average peak height and heterozygote balance with a comparable stutter ratio. Altogether, our results support the theory that the abLAFD method is a promising strategy coupled to STR typing for forensic LT-DNA analysis. [ABSTRACT FROM AUTHOR]

Filamentous fungi are abundant resources of bioactive natural products. Here, 151 marine-derived fungi were collected from the north Yellow Sea and identified by an internal transcribed spacer (ITS) sequence. The crude extracts of all strains were evaluated for their antimicrobial activities and analyzed by HPLC fingerprint. Based on these, strain Penicillium oxalicum MEFC104 was selected for further investigation. Two new polyketide–amino acid hybrid compounds with feature structures of tetramic acid, oxopyrrolidine A and B, were isolated. Their planner structures were assigned by HRESIMS and 1D/2D NMR experiments. The absolute configurations were determined by modified Mosher's method, J-based configuration analysis, and ECD calculations. Furthermore, the biosynthetic pathway was identified by bioinformatic analysis and gene-deletion experiments. This study established a link between oxopyrrolidines and the corresponding biosynthesis genes in P. oxalicum. [ABSTRACT FROM AUTHOR]

Strawberry plants and fruits are vulnerable to infections by a broad range of pathogens and pests. However, knowledge about the epidemiology of pathogens causing strawberry diseases is limited. In this study, we analyzed Fusarium commune, a major fungal pathogen causing strawberry root rot, from diseased strawberry root tissues in southcentral China. A total of 354 isolates were obtained from 11 locations that spanned about 700 km from both south to north and east to west. Multilocus genotypes of all isolates were obtained using seven polymorphic simple sequence repeat markers developed in this study. Our analyses revealed significant genetic diversity within each of the 11 local populations of F. commune. STRUCTURE analysis revealed that the optimal number of genetic populations for the 354 strains was two, with most local geographic populations containing isolates in both genetic clusters. Interestingly, many isolates showed allelic ancestry to both genetic clusters, consistent with recent hybridization between the two genetic clusters. In addition, though alleles and genotypes were frequently shared among local populations, statistically significant genetic differentiations were found among the local populations. However, the observed F. commune population genetic distances were not correlated with geographic distances. Together, our analyses suggest that populations of F. commune causing strawberry root rot are likely endemic to southcentral China, with each local population containing shared and unique genetic elements. Though the observed gene flow among geographic regions was relatively low, human activities will likely accelerate pathogen dispersals, resulting in the generation of new genotypes through mating and recombination. [ABSTRACT FROM AUTHOR]

B Specifically, in the two pictures in Figure 2C, showing the results of the adhesion study using a Scanning Electron Microscope (SEM), the same original SEM picture was inadvertently used. b The corrected B Figure 2 b appears below. Figure Graph: Figure 2 The adhesion of G. parasuis to CHO-K1 cells with or without CD163 expression. (C) SEM micrograph showing the attachment of G. parasuis to the surface of CHO-K1 cells or CHO-K1CD163' cells after incubation for 6 h. [Extracted from the article]

In this paper, six-layer AlN/Al gradient composites were prepared by a spark plasma sintering process to study the influences of sintering temperature and holding time on the microstructure and mechanical properties. The well-bonded interface enables the composite to exhibit excellent thermal and mechanical properties. The hardness and thermal expansion properties of the composite exhibit a gradient property. The hardness increased with the volume fraction of AlN while the CTE decreased as the volume fraction of AlN. The thermal expansion reaches the lowest value of 13–14 ppm/K, and the hardness reaches the maximum value of 1.25 GPa, when the target volume fraction of AlN is 45%. The simulation results show that this gradient material can effectively reduce the thermal stress caused by the mismatch of the thermal expansion coefficient as a transmitter and receiver (T/R) module. This paper attempts to provide experimental support for the preparation of gradient Al matrix composites. [ABSTRACT FROM AUTHOR]

Fiber crops are an important group of economic plants. Traditionally cultivated for fiber, fiber crops have also become sources of other materials such as food, animal feed, cosmetics and medicine. Asia and America are the two main production areas of fiber crops in the world. However, oomycete diseases have become an important factor limiting their yield and quality, causing devastating consequences for the production of fiber crops in many regions. To effectively control oomycete pathogens and reduce their negative impacts on these crops, it is very important to have fast and accurate detection systems, especially in the early stages of infection. With the rapid development of molecular biology, the diagnosis of plant pathogens has progressed from relying on traditional morphological features to the increasing use of molecular methods. The objective of this paper was to review the current status of research on molecular diagnosis of oomycete pathogens on fiber crops. Our search of PubMed identified nearly 30 species or subspecies of oomycetes on fiber crops, among which the top three species were Phytophthora boehmeriae, Phytophthora nicotianae and Pythium ultimum. The gene regions that have been used for molecular identifications of these pathogens include the internal transcribed spacer (ITS) regions of the nuclear ribosomal RNA gene cluster, and genes coding for translation elongation factor 1α (EF-1α) and mitochondrial cytochrome c oxidase subunits I and II (Cox 1, Cox 2), etc. We summarize the molecular assays that have been used to identify these pathogens and discuss potential areas of future development for fast, specific, and accurate diagnosis of oomycetes on fiber crops. [ABSTRACT FROM AUTHOR]

The hemp flea beetle Psylliodes attenuata (Coleoptera: Chrysomelidae: Psylliodes) is a common pest of Cannabis sativa, including cultivars of both industrial hemp and medicinal marijuana. Both the larval and adult stages of this beetle can cause significant damages to C. sativa, resulting in substantial crop losses. At present, little is known about the populations of this pest, including its genetic diversity. In this study, we obtained 281 P. attenuata samples from nine field sites representing broad industrial hemp productions in China and analyzed their DNA sequences at the mitochondrial COI gene, the insect DNA barcode. Our analyses revealed a total of 48 haplotypes, with 28 being found only in one specimen each while the remaining 20 were shared by two or more specimens each. Of the 20 shared haplotypes, eight were shared among local populations often from far away locations, consistent with recent long-distance dispersals. However, the observed putative long-distance dispersals have not obscured the significant genetic differentiations among the regional populations from northeastern, eastern, central and southwestern China. Interestingly, haplotype network analyses suggest evidence for potential mitochondrial recombination in natural populations of this species. We briefly discuss the implications of our results on its evolution, center of diversity, route of spread, and pest management strategies in hemp fields. [ABSTRACT FROM AUTHOR]

Pectinases have many applications in the industry of food, paper, and textiles, therefore finding novel polygalacturonases is required. Multiple sequence alignment and phylogenetic analysis of AnEPG (an endo-α-1,4-polygalacturonase from Aspergillus nidulans) and other GH 28 endo-polygalacturonases suggested that AnEPG is different from others. AnEPG overexpressed in Pichia pastoris was characterized. AnEPG showed the highest activity at pH 4.0, and exhibited moderate activity over a narrow pH range (pH 2.0–5.0) and superior stability in a wide pH range (pH 2.0–12.0). It displayed the highest activity at 60 °C, and retained >42.2% of maximum activity between 20 and 80 °C. It was stable below 40 °C and lost activity very quickly above 50 °C. Its apparent kinetic parameters against PGA (polygalacturonic acid) were determined, with the Km and kcat values of 8.3 mg/mL and 5640 μmol/min/mg, respectively. Ba2+ and Ni2+ enhanced activity by 12.2% and 9.4%, respectively, while Ca2+, Cu2+, and Mn2+ inhibited activity by 14.8%, 12.8%, and 10.2% separately. Analysis of hydrolysis products by AnEPG proved that AnEPG belongs to an endo-polygalacturonase. Modelled structure of AnEPG by I-TASSER showed structural characteristics of endo-polygalacturonases. This pectinase has great potential to be used in food industry and as feed additives. [ABSTRACT FROM AUTHOR]

Bast fibers and products derived from them are undergoing a resurgence in demand in the global market. However, fungal diseases have become an important factor limiting their yield and quality, causing devastating consequences for the production of bast fiber crops in many parts of the world. Thus, there is a high demand for effective control and prevention strategies against fungal pathogens. Having rapid, specific, sensitive, and cost-effective tests that can be used for early and accurate diagnosis of disease agents is an essential step of such strategies. The objective of this study was to review the current status of research on molecular diagnosis of fungal pathogens on bast fiber crops. Our search of PubMed identified nearly 20 genera of fungal pathogens on bast fiber crops, among which the five most common genera were Colletotrichum, Pythium, Verticillium, Fusarium, and Golovinomyces. The gene regions that have been used for molecular identifications of these fungi include internal transcribed spacer (ITS), translation elongation factor 1-α (EF-1α), ß-tubulin, calmodulin (CAL), histone subunit 3 (H3), glyceraldehydes-3-phosphate dehydrogenase (GAPDH), etc. We summarize the molecular assays that have been used to identify these fungi and discuss potential areas of future development for fast, specific, and accurate diagnosis of fungal pathogens on bast fiber crops. [ABSTRACT FROM AUTHOR]

Wax deposition during crude oil transmission can cause a series of negative effects and lead to problems associated with pipeline safety. A considerable number of previous works have investigated the wax deposition mechanism, inhibition technology, and remediation methods. However, studies on the shearing mechanism of wax deposition have focused largely on the characterization of this phenomena. The role of the shearing mechanism on wax deposition has not been completely clarified. This mechanism can be divided into the shearing dispersion effect caused by radial migration of wax particles and the shearing stripping effect caused by hydrodynamic scouring. From the perspective of energy analysis, a novel wax deposition model was proposed that considered the flow parameters of waxy crude oil in pipelines instead of its rheological parameters. Considering the two effects of shearing dispersion and shearing stripping coexist, with either one of them being the dominant mechanism, a shearing dispersion flux model and a shearing stripping model were established. Furthermore, a quantitative method to distinguish between the roles of shearing dispersion and shearing stripping in wax deposition was developed. The results indicated that the shearing mechanism can contribute an average of approximately 10% and a maximum of nearly 30% to the wax deposition process. With an increase in the oil flow rate, the effect of the shearing mechanism on wax deposition is enhanced, and its contribution was demonstrated to be negative; shear stripping was observed to be the dominant mechanism. A critical flow rate was observed when the dominant effect changes. When the oil flow rate is lower than the critical flow rate, the shearing dispersion effect is the dominant effect; its contribution rate increases with an increase in the oil flow temperature. When the oil flow rate is higher than the critical flow rate, the shearing stripping effect is the dominant effect; its contribution rate increases with an increase in the oil flow temperature. This understanding can be used to design operational parameters of the actual crude oil pipelines and address the potential flow assurance problems. The results of this study are of great significance for understanding the wax deposition theory of crude oil and accelerating the development of petroleum industry pipelines. [ABSTRACT FROM AUTHOR]

In this paper, a drag model-aided fault-tolerant state estimation method is presented for quadrotors. Firstly, the drag model accuracy was improved by modeling an angular rate related item and an angular acceleration related item, which are related with flight maneuver. Then the drag model, light detection and ranging (LIDAR), and inertial measurement unit (IMU) were fused based on the Federal Kalman filter frame. In the filter, the LIDAR estimation fault was detected and isolated, and the disturbance to the drag model was estimated and compensated. Some experiments were carried out, showing that the velocity and position estimation were improved compared with the traditional LIDAR/IMU fusion scheme. [ABSTRACT FROM AUTHOR]

In the context of large-scale wind power integration and rapid development of electric vehicles (EVs), a joint operation pattern was proposed to use a centralized charging station (CCS) to address high uncertainties incurred by wind power integration. This would directly remove the significant indeterminacy of wind power. Because the CCS is adjacent to a wind power gathering station, it could work jointly with wind farms to operate in power system as an independent enterprise. By combining the actual operational characteristics of the wind farm and the CCS, a multidimensional operating index evaluation system was created for the joint system. Based on the wind farm's known capacity, a multi-target capacity planning model was established for CCS to maximize the probability of realizing diverse indices of the system based on dependent-chance goal programming. In this model, planning and dispatching are combined to improve the feasibility of results in the operational stage. This approach takes the effects of randomness into account for wind power and battery swapping. The model was solved through combining Monte Carlo simulation and a genetic algorithm (GA) based on segmented encoding. As shown in the simulation results, the proposed model could comprehensively include factors such as initial investment, wind power price, battery life, etc., to optimize CCS capacity and to ultimately improve the operating indices of the joint system. [ABSTRACT FROM AUTHOR]

Phytocystatins play multiple roles in plant growth, development and resistance to pests and other environmental stresses. A ramie ( Boehmeria nivea L.) phytocystatin gene, designated as BnCPI , was isolated from a ramie cDNA library and its full-length cDNA was obtained by rapid amplification of cDNA ends (RACE). The full-length cDNA sequence (691 bp) consisted of a 303 bp open reading frame (ORF) encoding a protein of 100 amino acids with deduced molecular mass of 11.06 kDa and a theoretical isoelectric point (pI) of 6.0. The alignment of genome DNA (accession no. MF153097) and cDNA sequences of BnCPI showed that an intron (~104 bp) exists in the coding region. The BnCPI protein contains most of the highly conserved blocks including Gly⁵-Gly⁶ at the N-terminal, the reactive site motif QxVxG (Q 49 V 50 V 51 S 52 G 53 ), the L 79 -W 80 block and the [LVI]-[AGT]-[RKE]-[FY]-[AS]-[VI]-x-[EDQV]-[HYFQ]-N (L 22 G 23 R 24 F 25 A 26 V 27 D 28 D 29 H 30 N 31 ) block that is common among plant cystatins. BLAST analysis indicated that BnCPI is similar to cystatins from Glycine max (77%), Glycine soja (76%), Hevea brasiliensis (75%) and Ricinus communis (75%). The BnCPI was subcloned into expression vector pSmart-I and then overexpressed in Escherichia coli BL21 (DE3) as a His-tagged recombinant protein. The purified reBnCPI has a molecular mass of 11.4 kDa determined by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). Purified reBnCPI can efficiently inhibit the protease activity of papain and ficin toward BANA ( N α-benzoyl-L-arginine-2-naphthyamide), as well as the mycelium growth of some important plant pathogenic fungi. The data further contribute to our understanding of the molecular functions of BnCPI.

Medical staff in the department of obstetrics and gynecology are a group of professionals reportedly at high risk of work-related musculoskeletal disorders (WMSD), however, little is known about the current status of this problem in China. The aim of this study was to investigate prevalence and risk factors of work-related musculoskeletal disorders among this population in China. A self-developed questionnaire was distributed to 1017 obstetrics and gynecology practitioners to collect information on musculoskeletal symptoms and relevant factors. Prevalence and severity of work-related musculoskeletal disorders in different parts of the body were calculated and the relationship between personal and ergonomic factors and work-related musculoskeletal disorders was analyzed using Chi-square test and unconditional logistic regression models. The results indicated a high prevalence of 85.5% among the subjects, with the shoulder ( n = 575, 62.0%), neck ( n = 560, 60.3%) and lower back ( n = 504, 54.3%) being the three most affected regions. Individual, postural, work-environmental as well as psychosocial factors were recognized to be associated with WMSDs in different body parts. Therefore, attention must be given to the problem of musculoskeletal disorders among Chinese obstetrics and gynecology staff. It is recommended to develop good life habits, improve work environment, adjust work organization as well as train on proper postures in their daily operation., Competing Interests: The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.