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Bread wheat (Triticum aestivum) is a staple food crop worldwide. The genetic dissection of important nutrient traits is essential for the biofortification of wheat to meet the nutritional needs of the world’s growing population. Here, 45,298 single-nucleotide polymorphisms (SNPs) from 55K chip arrays were used to genotype a panel of 768 wheat cultivars, and a total of 154 quantitative trait loci (QTLs) were detected for eight traits under three environments by genome-wide association study (GWAS). Three QTLs (qMn-3B.1, qFe-3B.4, and qSe-3B.1/qFe-3B.6) detected repetedly under different environments or traits were subjected to subsequent analyses based on linkage disequilibrium decay and the P-values of significant SNPs. Significant SNPs in the three QTL regions formed six haplotypes for qMn-3B.1, three haplotypes for qFe-3B.4, and three haplotypes for qSe-3B.1/qFe-3B.6. Phenotypic analysis revealed significant differences among haplotypes. These results indicated that the concentrations of several nutrient elements have been modified during the domestication of landraces to modern wheat. Based on the QTL regions, we identified 15 high-confidence genes, eight of which were stably expressed in different tissues and/or developmental stages. TraesCS3B02G046100 in qMn-3B.1 and TraesCS3B02G199500 in qSe-3B.1/qFe-3B.6 were both inferred to interact with metal ions according to the Gene Ontology (GO) analysis. TraesCS3B02G199000, which belongs to qSe-3B.1/qFe-3B.6, was determined to be a member of the WRKY gene family. Overall, this study provides several reliable QTLs that may significantly affect the concentrations of nutrient elements in wheat grain, and this information will facilitate the breeding of wheat cultivars with improved grain properties.

Abstract Background This study aimed to investigate the impact of nursing interventions on the rehabilitation outcomes of patients after lumbar spine surgery and to provide effective references for future postoperative care for patients undergoing lumbar spine surgery. Methods The study included two groups: a control group receiving routine care and an observation group receiving additional comprehensive nursing care. The comprehensive care encompassed postoperative rehabilitation, pain, psychological, dietary management, and discharge planning. The Visual Analogue Scale (VAS), Oswestry Disability Index (ODI), Short-Form 36 (SF-36) Health Survey, self-rating depression scale (SDS) and self-rating anxiety scale(SAS) were used to assess physiological and psychological recovery. Blood albumin, haemoglobin, neutrophil counts, white blood cell counts, red blood cell counts, inflammatory markers (IL-6, IL-10, and IFN-γ) were measured, and the incidence of postoperative adverse reactions was also recorded. Results Patients in the observation group exhibited significantly improved VAS, ODI, SF-36, SDS and SAS scores assessments post-intervention compared to the control group (P 0.05), suggesting that the comprehensive nursing interventions did not increase the risk of adverse effects. Conclusion Comprehensive nursing interventions have a significant impact on the postoperative recovery outcomes of patients with LSS, alleviating pain, reducing inflammation levels, and improving the overall quality of patient recovery without increasing the patient burden. Therefore, in clinical practice, it is important to focus on comprehensive nursing interventions for patients with LSS to improve their recovery outcomes and quality of life.

Abstract Background Retroperitoneal liposarcoma (RPLS) is known for its propensity for local recurrence and short survival time. We aimed to identify a credible and specific prognostic biomarker for RPLS. Methods Cases from The Cancer Genome Atlas (TCGA) sarcoma dataset were included as the training group. Co-expression modules were constructed using weighted gene co-expression network analysis (WGCNA) to explore associations between modules and survival. Survival analysis of hub genes was performed using the Kaplan–Meier method. In addition, independent external validation was performed on a cohort of 135 Chinese RPLS patients from the REtroperitoneal SArcoma Registry (RESAR) study (NCT03838718). Results A total of 19 co-expression modules were constructed based on the expression levels of 26,497 RNAs in the TCGA cohort. Among these modules, the green module exhibited a positive correlation with overall survival (OS, p = 0.10) and disease-free survival (DFS, p = 0.06). Gene set enrichment analysis showed that the green module was associated with endocytosis and soft-tissue sarcomas. Survival analysis demonstrated that NINJ1, a hub gene within the green module, was positively associated with OS (p = 0.019) in the TCGA cohort. Moreover, in the validation cohort, patients with higher NINJ1 expression levels displayed a higher probability of survival for both OS (p = 0.023) and DFS (p = 0.012). Multivariable Cox analysis further confirmed the independent prognostic significance of NINJ1. Conclusions We here provide a foundation for the establishment of a consensus prognostic biomarker for RPLS, which should not only facilitate medical treatment but also guide the development of novel targeted drugs.

Abstract With the large-scale construction of oil and gas pipelines, the safety issues of long-distance buried pipelines in the service and construction have become increasingly prominent. The complex geological and topographical conditions of the special zone will put forwards extremely high requirements on pipe trench laying backfill materials and construction technology. For example, pipelines are inevitable to cross the active fault, while the trench backfilled with soil has limitations in protecting them from failure under the active fault displacement caused by the earthquake. Therefore, it is necessary to study the pipe–soil interaction mechanism, determine the stress state of the pipeline and propose a new backfilling material that can protect the pipeline from failure. Foam concrete (FC) provides a new choice to backfill the buried pipeline trench due to its high-homogeneity, lightweight, controllable-strength, and self-compacting. To further determine the applicability of the FC, the pipe-FC interaction mechanism is studied. Then, a FE model of the FC-pipeline-soil interaction system is established by Abaqus to quantitatively analyze the applicability of the FC based on the experimental data of the mechanical performance of the FC. It proves that using FC as trench backfill material has a noticeable protective effect on the pipeline under the earthquake-induced displacement of the normal fault. Furthermore, FC has a better protective effect on the pipeline subjected to compressive than tensile. Therefore, the reference for applying FC in trench backfilling of pipelines crossing normal fault is provided.

Abstract In cancer treatment, therapeutic strategies that integrate tumor-specific characteristics (i.e., precision oncology) are widely implemented to provide clinical benefits for cancer patients. Here, through in-depth integration of tumor transcriptome and patients’ prognoses across cancers, we investigated dysregulated and prognosis-associated genes and catalogued such important genes in a cancer type-dependent manner. Utilizing the expression matrices of these genes, we built models to quantitatively evaluate the malignant levels of tumors across cancers, which could add value to the clinical staging system for improved prediction of patients’ survival. Furthermore, we performed a transcriptome-based molecular subtyping on hepatocellular carcinoma, which revealed three subtypes with significantly diversified clinical outcomes, mutation landscapes, immune microenvironment, and dysregulated pathways. As tumor transcriptome was commonly profiled in clinical practice with low experimental complexity and cost, this work proposed easy-to-perform approaches for practical clinical promotion towards better healthcare and precision oncology of cancer patients.

Abstract Background Sleep-disordered breathing (SDB) during childhood is common and includes a range of breathing abnormalities that range from primary snoring (PS) to obstructive sleep apnea syndrome (OSAS).Studies have shown that not only OSAS, but also PS, which is originally considered harmless, could cause cardiovascular, cognitive, behavioral, and psychosocial problems. Many researches are focused on the relation of OSA and serum lipid levels. However, little studies are focused on PS and serum lipid levels in children.We evaluated whether serum lipid (total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C),low-density lipoprotein cholesterol (LDL-C)) concentrations were associated with specific components of SDB, including indices of oxygen reduction index, lowest oxygen saturation, mean oxygen saturation. And we explored whether serum lipid levels were associated with different degree sleep disordered (PS and OSA group) and obese. Methods This was a cross-sectional study. Children who were complained by their guardians with habitual snoring and(or) mouth breathing were collected in the SDB group. Normal children without sleep problem were matched in the control group. Subjects in the SDB group underwent polysomnography. The serum lipid profiles of all the children included TC, TG, HDL-C and LDL-C concentrations were measured by appropriate enzymatic assays. Results A total of 241 with Apnea/Hypopnea Index ≥ 5 (AHI) were assigned to the OSAS group and the remaining 155 with normal AHI were assigned to the PS group. The values of TC, TG, LDL-C and LDL/HDL were significantly higher in the OSAS group than in the PS group, and the values in the PS group were significantly higher than the control group. Multiple regression analysis revealed serum TG only correlated negatively with lowest oxygen saturation. Body mass index-z score has a positive effect on TG in all the 1310 children (P = 0.031) and in SDB 396 children(P = 0.012). The level of serum TG in obese group was significantly higher than that in non-obese group. Conclusions SDB had a very obvious effect on blood lipids, whereas PS without apnea and hypoxia. Obese only affects the aggregation of TG. Trial registration ChiCTR1900026807(2019.10.23).

Abstract Objective The present study aims to explore the influencing factors of the scientific fitness literacy of nurses and provide a strategic basis for literacy improvement. Methods A questionnaire on the influencing factors of scientific fitness literacy of nurses was designed by the group conducting the present study; the questionnaire was based on the socioecology model and the questionnaire preparation method. The general data questionnaire and the questionnaire on the influencing factors of scientific fitness literacy of nurses were adopted to investigate nurses in tertiary hospitals in order to analyze and discuss the influencing factors of their scientific fitness literacy. Results (1) The questionnaire on the influencing factors of the scientific fitness literacy of nurses comprised five dimensions and 36 items. The overall item-content validity index was 0.833–1.000, the scale-content validity index was 0.974, and the overall Cronbach’s α coefficient was 0.955; (2) the results of the pairwise Pearson correlation analysis showed that all five dimensions were positively correlated with the scientific fitness literacy of nurses; and (3) the results of the multiple linear regression analysis revealed that five dimensions, as well as the existence of exercise habits in daily life, had a significant impact on the scientific fitness literacy of nurses (P

Abstract We investigate the composite systems consisting of topological orders separated by gapped domain walls. We derive a pair of domain-wall Verlinde formulae, that elucidate the connection between the braiding of interdomain excitations labeled by pairs of anyons in different domains and quasiparticles in the gapped domain wall with their respective fusion rules. Through explicit non-Abelian examples, we showcase the calculation of such braiding and fusion, revealing that the fusion rules for interdomain excitations are generally fractional or irrational. By investigating the correspondence between composite systems and anyon condensation, we unveil the reason for designating these fusion rules as symmetry fractionalized (irrationalized) fusion rules. Our findings hold promise for applications across various fields, such as topological quantum computation, topological field theory, conformal field theory, and parton physics.

Abstract We develop a novel framework for describing quantum fluctuations in field theory, with a focus on cosmological applications. Our method uniquely circumvents the use of operator/Hilbert-space formalism, instead relying on a systematic treatment of classical variables, quantum fluctuations, and an effective Hamiltonian. Our framework not only aligns with standard formalisms in flat and de Sitter spacetimes, which assumes no backreaction, demonstrated through the φ 3-model, but also adeptly handles time-dependent backreaction in more general cases. The uncertainty principle and spatial symmetry emerge as critical tools for selecting initial conditions and understanding effective potentials. We discover that modes inside the Hubble horizon do not necessarily feel an initial Minkowski vacuum, as is commonly assumed. Our findings offer fresh insights into the early universe’s quantum fluctuations and potential explanations to large-scale CMB anomalies.

Abstract Background Epigenetic marks are reprogrammed during sexual reproduction. In flowering plants, DNA methylation is only partially remodeled in the gametes and the zygote. However, the timing and functional significance of the remodeling during plant gametogenesis remain obscure. Results Here we show that DNA methylation remodeling starts after male meiosis in rice, with non-CG methylation, particularly at CHG sites, being first enhanced in the microspore and subsequently decreased in sperm. Functional analysis of rice CHG methyltransferase genes CMT3a and CMT3b indicates that CMT3a functions as the major CHG methyltransferase in rice meiocyte, while CMT3b is responsible for the increase of CHG methylation in microspore. The function of the two histone demethylases JMJ706 and JMJ707 that remove H3K9me2 may contribute to the decreased CHG methylation in sperm. During male gametogenesis CMT3a mainly silences TE and TE-related genes while CMT3b is required for repression of genes encoding factors involved in transcriptional and translational activities. In addition, CMT3b functions to repress zygotic gene expression in egg and participates in establishing the zygotic epigenome upon fertilization. Conclusion Collectively, the results indicate that DNA methylation is dynamically remodeled during male gametogenesis, distinguish the function of CMT3a and CMT3b in sex cells, and underpin the functional significance of DNA methylation remodeling during rice reproduction.

ObjectiveThe distribution of the photon energy spectrum in isocenter plane of the medical linear accelerator and the influence of secondary collimator on the photon energy spectrum are studied. Methods Use the BEAMnrc program to simulate the transmission of the 6 MeV electrons and photons in 5 cm×5 cm,10 cm×10 cm,15 cm×15 cm and 20 cm×20 cm fields in treatment head of the medical linear accelerator, where a phase space file was set up at the isocenter plane to record the particle information passing through this plane. The BEAMdp program is used to analyze the phase space file, in order to obtain the distribution of the photon energy spectrum in isocenter plane and the influence of secondary collimator on the photon energy spectrum. Results By analyzing the photon energy spectrum of a medical linear accelerator with a nominal energy of 6 MV, it is found that the secondary collimator has little effect on the photon energy spectrum; different fields have different photon energy spectrum distributions; the photon energy spectrum in different central regions of the same field have the same normalized distribution. Conclusion In the dose calculation of radiation therapy, the influence of photon energy spectrum should be carefully considered.

SETDB2 is a H3K9 histone methyltransferase required for accurate chromosome segregation. Its H3K9 histone methyltransferase activity was reported to be associated with chromosomes during metaphase. Here, we confirm that SETDB2 is required for mitosis and accurate chromosome segregation. However, these functions are independent of its histone methyltransferase activity. Further analysis showed that SETDB2 can interact with BUBR1, and is required for CDC20 binding to BUBR1 and APC/C complex and CYCLIN B1 degradation. The ability of SETDB2 to regulate the binding of CDC20 to BUBR1 or APC/C complex, and stabilization of CYCLIN B1 are also independent of its histone methyltransferase activity. These results suggest that SETDB2 interacts with BUBR1 to promote binding of CDC20 to BUBR1 and APC3, then degrades CYCLIN B1 to ensure accurate chromosome segregation and mitosis, independently of its histone methyltransferase activity.

Abstract Wild germplasm resources are crucial for gene mining and molecular breeding because of their special trait performance. Haplotype-resolved genome is an ideal solution for fully understanding the biology of subgenomes in highly heterozygous species. Here, we surveyed the genome of a wild walnut tree from Gongliu County, Xinjiang, China, and generated a haplotype-resolved reference genome of 562.99 Mb (contig N50 = 34.10 Mb) for one haplotype (hap1) and 561.07 Mb (contig N50 = 33.91 Mb) for another haplotype (hap2) using PacBio high-fidelity (HiFi) reads and Hi-C technology. Approximately 527.20 Mb (93.64%) of hap1 and 526.40 Mb (93.82%) of hap2 were assigned to 16 pseudochromosomes. A total of 41039 and 39744 protein-coding gene models were predicted for hap1 and hap2, respectively. Moreover, 123 structural variations (SVs) were identified between the two haplotype genomes. Allele-specific expression genes (ASEGs) that respond to cold stress were ultimately identified. These datasets can be used to study subgenome evolution, for functional elite gene mining and to discover the transcriptional basis of specific traits related to environmental adaptation in wild walnut.

Abstract The Xinjiang unearthed brocade as a significant cultural heritage records the historical and cultural information of diverse ethnic groups, and it also influences cultural product development. However, the existing knowledge concerning these brocades is disorganized, fragmented, and incomplete, hindering a comprehensive understanding of their intricate relationships. To address these issues, this study has developed an integrated ontological model for Xinjiang’s unearthed brocades (XJUBontology). By applying Conceptual Reference Model of International Committee for Documentation (CIDOC CRM) ontology and the Remanufactured Process Planning (RPP) approach, this XJUBontology comprises knowledge about both the brocades and their cultural derivatives, and knowledge in these two domains are able to be organized and refined. The implementation of XJUBontology in Protégé and validation via SPARQL queries not only centralize and manage Xinjiang unearthed brocade-related knowledge but also establish vital connections among this fragmented information. The contribution is to help in associating, managing, and sharing knowledge in the domain of Xinjiang unearthed brocades, providing a framework for establishing related data repository, and helping researchers, apparel and accessories designers, museums, and other cultural and tourism institutions to access a more systematic information to assist their works.

Abstract Background The clinical routine test of HBV-specific T cell reactivity is still limited due to the high polymorphisms of human leukocyte antigens (HLA) in patient cohort and the lack of universal detection kit, thus the clinical implication remains disputed. Methods A broad-spectrum peptide library, which consists of 103 functionally validated CD8+ T-cell epitopes spanning overall HBsAg, HBeAg, HBx and HBpol proteins and fits to the HLA polymorphisms of Chinese and Northeast Asian populations, was grouped into eight peptide pools and was used to establish an ELISpot assay for enumerating the reactive HBV-specific T cells in PBMCs. Totally 294 HBV-infected patients including 203 ones with chronic hepatitis B (CHB), 13 ones in acute resolved stage (R), 52 ones with liver cirrhosis (LC) and 26 ones with hepatocellular carcinoma (HCC) were detected, and 33 CHB patients were longitudinally monitored for 3 times with an interval of 3–5 months. Results The numbers of reactive HBV-specific T cells were significantly correlated with ALT level, HBsAg level, and disease stage (R, CHB, LC and HCC), and R patients displayed the strongest HBV-specific T cell reactivity while CHB patients showed the weakest one. For 203 CHB patients, the numbers of reactive HBV-specific T cells presented a significantly declined trend when the serum viral DNA load, HBsAg, HBeAg or ALT level gradually increased, but only a very low negative correlation coefficient was defined (r = − 0.21, − 0.21, − 0.27, − 0.079, respectively). Different Nucleotide Analogs (NUCs) did not bring difference on HBV-specific T cell reactivity in the same duration of treatment. NUCs/pegIFN-α combination led to much more reactive HBV-specific T cells than NUCs monotherapy. The dynamic numbers of reactive HBV-specific T cells were obviously increasing in most CHB patients undergoing routine treatment, and the longitudinal trend possess a high predictive power for the hepatitis progression 6 or 12 months later. Conclusion The presented method could be developed into an efficient reference method for the clinical evaluation of cellular immunity. The CHB patients presenting low reactivity of HBV-specific T cells have a worse prognosis for hepatitis progression and should be treated using pegIFN-α to improve host T-cell immunity.

Abstract Background To clarify the value of gait analysis and its consistency with traditional scoring scales for the evaluation of knee joint function after total knee arthroplasty (TKA). Methods This study included 25 patients with knee osteoarthritis (KOA) who underwent bilateral TKA, and 25 conditionally matched healthy individuals, categorised into the experimental and control groups, respectively. Patients in the experimental group underwent gait analysis and Western Ontario and McMaster University Osteoarthritis Index (WOMAC) evaluation before and 1 year after TKA. Weight-bearing balance and walking stability were assessed using discrete trends of relevant gait indicators. Pearson’s correlation analysis was performed on the gait and WOMAC score data of the experimental group before and after TKA. Results One year after TKA, patients’ gait indices (except gait cycle) were significantly better than before surgery, but significantly worse than that of the control group (P 80%. The WOMAC scores and gait analysis results were significantly correlated before TKA (P

Abstract Aim To investigate the correlation of angles α and κ with the refractive and biological parameters in children. Methods This case-series study included 438 eyes of 219 children (males/females = 105/114, age: 3–15 years). Ocular biometric parameters, including axial length, corneal radius of curvature (CR), white-to-white distance (WTW), angle κ and angle α, were measured using IOL Master 700; auto-refraction were assessed under cycloplegia. The eyes were assigned to different groups based on CR, WTW, and gender to compare the angles α and κ, and analyze the correlations between the differences of biological parameters on angles α and κ. Results The means of axial length, CR, WTW, angle α, and angle κ were 23.24 ± 1.14 mm, 7.79 ± 0.27 mm, 11.68 ± 0.41 mm, 0.45 ± 0.25 mm, and 0.27 ± 0.22 mm, respectively. Angle α was correlated with CR and WTW (fixed effect coefficient [FEC] = 0.237, p = 0.015; FEC = -0.109, p = 0.003; respectively), and angle κ also correlated with CR and WTW (FEC = 0.271, p = 0.003; FEC = -0.147, p

Objective Incomplete landslide timing information can result in inaccuracies in the temporal relationship between landslides and rainfall, consequently affecting the precision of a critical rainfall threshold model. Methods To address this issue, this study focuses on rainfall-induced landslides in the Wanzhou District of Chongqing from 1995 to 2015. The Henghe Township, lacking historical landslide data, serves as the verification area. We proposed a prediction model for the daily temporal probability of landslide occurrence on a certain day based on long short-term memory (LSTM) and a temporal convolutional network (TCN). This method was used to reconstruct the temporal information of rainfall-induced landslide events by simulating the nonlinear relationship between the duration of landslides and rainfall. After the reconstruction of temporal information, the landslide events were verified and selected and subsequently applied to a reasonable division of the E-D effective rainfall threshold curve to establish the landslide meteorological warning model. Results The results showed that the average temporal probability of rainfall-induced landslides predicted by the proposed method reached 90.33%, which was higher than that of the ANN (71.17%), LSTM (72.75%), and TCN (86.91%) models. Using temporal probabilities exceeding a 90% threshold, 18 data points, including 42 landslides in the verification area, are expanded to 201. Compared with using solely historical landslide events, the meteorological warning model based on expanded temporal information provides a more reasonable warning classification, and the effective warning rate at the severe warning level is increased by 42.86%. Conclusion This method can compensate for the shortage of landslide time information in field investigations and provide data support for early meteorological warning systems for rainfall-induced landslides, thus improving the accuracy of early meteorological warning systems.

This work attempts to provide a new interpretation for the hot corona in active galactic nuclei (AGNs). A thin parabolic magnetic reconnection layer, anchored at the innermost disk and extending along the boundary of the magnetic tower for a few tens of gravitational radii, serves as a hard-X-ray source above the disk. Within this reconnection layer, the tearing instability leads to the formation of a chain of plasmoids, which contain relativistic electrons that generate X-ray radiation through inverse-Compton (IC) scattering of soft photons emitted by the accretion disk. Based on previous theoretical works and numerical simulations, we develop a heuristic framework to parameterize the geometry and magnetization of the reconnection layer, as well as to compute both the power of the IC-scattering radiation and the height of the reconnection layer. Our model allows for a quantitative investigation of the relation between the height of the corona and the X-ray radiation luminosity, which can be directly compared against the observed relation from X-ray reverberation mapping of individual AGNs. The theoretical results are in good agreement with the observations of IRAS 13224-3809, indicating the validation of our model.

Accurately predicting the remaining useful life (RUL) of critical mechanical components is a central challenge in reliability engineering. Stochastic processes, which are capable of modeling uncertainties, are widely used in RUL prediction. However, conventional stochastic process models face two major limitations: (1) the reliance on strict assumptions during model formulation, restricting their applicability to a narrow range of degradation processes, and (2) the inability to account for potential variations in the degradation mechanism during modeling and prediction. To address these issues, we propose a novel mechanism-equivalence-based Tweedie exponential dispersion process (ME-based TEDP) for adaptive degradation modeling and RUL prediction of mechanical components. The proposed model enhances the original Tweedie exponential dispersion process (TEDP) by incorporating degradation mechanism equivalence, effectively capturing the correlation between model parameters. Furthermore, it improves prediction accuracy and interpretability by employing a dynamic testing–modeling–predicting strategy. Application of the ME-based TEDP model to high-speed rail bogie systems demonstrates its effectiveness and superiority over existing approaches. This study advances the theory of degradation modeling and significantly improves the precision of RUL predictions.

The threat power transmission and distribution projects pose to the ecological environment has been widely discussed by researchers. The scarcity of early environmental monitoring and supervision technologies, particularly the lack of effective real-time monitoring mechanisms and feedback systems, has hindered the timely quantitative identification of potential early-stage environmental risks. This study aims to comprehensively review the literature and analyze the research context and shortcomings of the advance warning technologies of power transmission and distribution projects construction period using the integrated space–sky–ground system approach. The key contributions of this research include (1) listing ten environmental risks and categorizing the environmental risks associated with the construction cycle of power transmission and distribution projects; (2) categorizing the monitoring data into one-dimensional, two-dimensional, and three-dimensional frameworks; and (3) constructing the potential environmental risk knowledge system by employing the knowledge graph technology and visualizing it. This review study provides a panoramic view of knowledge in a certain field and reveals the issues that have not been fully explored in the research field of monitoring technologies for potential environmental damage caused by power transmission and transformation projects.

BackgroundPaeoniae Radix Rubra (PRR) has been used widely to promote blood circulation and eliminate blood stasis in China clinical practice owing to its extensive pharmacological effects. However, the “quality markers” (Q-markers) of the antioxidant effects remains unknown.ObjectTo explore the Q-markers of antioxidant activity based on multiple strategies, which would provide reference for the quality evaluation of PRR based on specific pharmacodynamic-oriented.MethodsFirstly, the “fingerprint” profiles of 15 batches of PRR were acquired and identified by ultrahigh performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UHPLC-Q-TOF MS/MS) and the common peaks extracted. Meanwhile, the MTT assay was used to evaluate the effect of 15 batches of PRR on H2O2-induced oxidative stress in HT-22 cells. The antioxidant activity of PRR was investigated simultaneously by superoxide dismutase (SOD), glutathione (GSH), and malondialdehyde (MDA) commercial kits. The relationship between common peaks and antioxidant indexes were constructed by grey relational analysis (GRA) and partial least squares-discriminant analysis (PLS-DA) for the identification of preselected Q-markers. Secondly, experimental verification was conducted to investigate the protective effect of the preliminary components on HT-22 cells undergoing oxidative stress. Finally, for the further validation of effectiveness of antioxidant Q-markers, network pharmacology was applied to explore potential targets, and the molecular docking technology was used to value the binding ability of the potential active components of PRR to the antioxidant targets.ResultsThirty-seven common peaks from 15 batches of PRR were identified qualitatively by UHPLC-Q-TOF MS/MS. The MTT assay showed that PRR could reduce the oxidative damage induced by H2O2 upon HT-22 cells according to the index of MDA, SOD and GSH. Eight potential antioxidant components were screened by spectrum-effect correlation analysis: paeoniflorin, galloylpaeoniflorin, albiflorin, 1,2,3,4,6-o-pentagalloylglucose, benzoylpaeoniflorin, pinocembrin, oleanic acid, and isorhamnetin-3-o-nehesperidine. Each of these preliminary components showed significant protections on cellular oxidative stress (P < 0.05). Interleukin-6 (IL-6), protein kinase B (AKT1), and tumor necrosis factor (TNF) were predicted to be the major potential targets of PRR, and the good binding ability were presented between the potential active components of PRR and each target as a whole.ConclusionEight components were identified as the antioxidant Q-markers of PRR based on an integrated multimodal strategy.

Coastal wetlands are important areas with valuable natural resources and diverse biodiversity. Due to the influence of both natural factors and human activities, the landscape of coastal wetlands undergoes significant changes. It is crucial to systematically monitor and analyze the dynamic changes in coastal wetland cover over a long-term time series. In this paper, a long-term time series coastal wetland remote sensing classification process was proposed, which integrated feature selection and sample migration. Utilizing Google Earth Engine (GEE) and Landsat TM/ETM/OLI remote sensing image data, the selected feature set is combined with the sample migration method to generate the training sample set for each target year. The Simple Non-Iterative Clustering-Random Forest (SNIC-RF) model was ultimately employed to accurately map wetland classes in the Liaohe Estuary from 1985 to 2023 and quantitatively evaluate the spatio-temporal pattern change characteristics of wetlands in the study area. The findings indicate that: (1) After feature selection, the accuracy of the model reached 0.88, and the separation of the selected feature set was good. (2) After sample migration, the overall accuracy of sample classification in the target year ranged from 87 to 94%, along with Kappa coefficients of 0.84 to 0.92, thereby ensuring the validity of classification sample migration. (3) SNIC-RF classification results showed better performance of wetland landscape. Compared with RF classification, the overall classification accuracy was increased by 0.69–5.82%, and the Kappa coefficient was increased by 0.0087–0.0751. (4) From 1985 to 2023, there has been a predominant trend of natural wetlands being converted into artificial wetlands. In recent years, this transition has occurred more gently. Finally, this study offers valuable insights into understanding changes and trends in the surface ecological environment of the Liaohe Estuary. The research method can be extended to other types of wetland classification and the comprehensive application of coastal wetland in hydrology, ecology, meteorology, soil, and environment can be further explored on the basis of this research, laying strong groundwork for shaping policies on ecological protection and restoration.

Objective: This study aims to diagnose Rotator Cuff Tears (RCT) and classify the severity of RCT in patients with Osteoporosis (OP) through the analysis of shoulder joint anteroposterior (AP) X-ray-based localized proximal humeral bone mineral density (BMD) measurements and clinical information based on machine learning (ML) models. Methods: A retrospective cohort of 89 patients was analyzed, including 63 with both OP and RCT (OPRCT) and 26 with OP only. The study analyzed a series of shoulder radiographs from April 2021 to April 2023. Grayscale values were measured after plotting ROIs based on AP X-rays of shoulder joint. Five kinds of ML models were developed and compared based on their performance in predicting the occurrence and severity of RCT from ROIs' greyscale values and clinical information (age, gender, advantage side, lumbar BMD, and acromion morphology (AM)). Further analysis using SHAP values illustrated the significant impact of selected features on model predictions. Results: R1-6 had a positive correlation with BMD respectively. The nine variables, including greyscale R1-6, age, BMD, and AM, were used in the prediction models. The RF model was determined to be superior in effectively diagnosing RCT in OP patients, with high AUC scores of 0.998, 0.889, and 0.95 in the training, validation, and testing sets, respectively. SHAP values revealed that the most influential factors on the diagnostic outcomes were the grayscale values of all cancellous bones in ROIs. A column-line graph prediction model based on nine variables was constructed, and DCA curves indicated that RCT prediction in OP patients was favored based on this model. Furthermore, the RF model was also the most superior in predicting the types of RCT within the OPRCT group, with an accuracy of 86.364% and 73.684% in the training and test sets, respectively. SHAP values indicated that the most significant factor affecting the predictive outcomes was the AM, followed by the grayscale values of the greater tubercle, among others. Conclusions: ML models, particularly the RF algorithm, show significant promise in diagnosing RCT occurrence and severity in OP patients using conventional shoulder X-rays based on the nine variables. This method presents a cost-effective, accessible, and non-invasive diagnostic strategy that has the potential to substantially enhance the early detection and management of RCT in OP patient population.

Rheological properties play a crucial role in characterizing 3D printed cement-based materials. To further investigate the mechanism behind rheological evolution, this study employs low-field NMR relaxation time measurement to characterize the microstructure evolution of 3D printed steel slag cementitious material within the first 6 hours. This is combined with rheological parameters to explore the relationship between the mixture's rheological properties and pore microstructure over time. The results demonstrate that relaxation time effectively represents the temporal characteristics of rheological parameters, while pore throat distribution (0–0.1μm) exhibits a positive correlation with plastic viscosity. Low-field NMR relaxation characteristics can effectively describe early properties of 3D printed cementitious materials and provide valuable data support for future exploration of non-destructive testing during early stages.

Environmental pollution has long been a global concern, and the development of fintech has led to radical changes in the financial industry, while finance plays a very important role in environmental governance. We use the number of fintech companies to create a city fintech index, and with the data of 827 listed companies in heavily polluting industries from 2011 to 2020, we study the impact of fintech development on enterprise environmental investment. We find that fintech can significantly increase the environmental investment of heavily polluting enterprises, while increasing the size of enterprise green bonds and improving the green cognition of executives are two important influence mechanisms. Heterogeneity analysis found that the impact of fintech on Southern enterprises and state-owned enterprises is more significant. Further analysis shows that fintech can significantly reduce the carbon emissions of heavily polluting enterprises and increase the number of green invention patents. The results of the study provide a useful reference for the government to promote the implementation of fintech policies and explore new ways to modernize pollution management.

Abstract Deep lakes are critical for freshwater storage, yet they are struggling against major ecological issues from climate change and nutrient pollution. A comprehensive understanding of internal feedback mechanisms is crucial for regulating nutrients in these lakes. A five‐year study was conducted on the diatom community and environment in Lake Fuxian, China's largest deep freshwater lake, which is becoming eutrophic. The results indicate a shift in the diatom community from a stable state dominated by a single species to a rapid seasonal fluctuation, and there is a significant increase in diatom biomass. Specifically, stable stratification and low nutrient concentrations are limiting the growth of diatom biomass and maintaining the dominance of Cyclotella. Nutrients in the hypolimnion were replenished in the epilimnion during the extreme cold of winter, triggering a shift in the diatom community. This shift may imply that future climate change will exacerbate the positive feedback of hypoxia‐nutrient release of algal blooms, potentially triggering a regime shift in the ecosystem of the entire lake. This study underscores the fact that climate change alters the internal feedback mechanisms of deep lakes, reducing ecosystem stability, and provides a scientific basis for further clarification of protection measures for deep lakes.

In current urban flood modeling, challenges arise from the inadequate consideration of heterogeneous underlying urban surface characteristics and the complexity of parameter optimization processes. This study integrates multiple machine learning methods to propose an intelligent framework for urban flood modeling that accounts for underlying surface characteristics. It began by coupling a surface runoff model with a pipe network model to form an interpretable flooding model (FM). Subsequently, utilizing the BIC-GMM machine learning method on the sample set of the urban flooding model’s parameters, this study explored the grouping trends of these parameters. The Transformer model was employed to classify different categories of urban land use, which, along with other environmental indices, aided in the construction of an Artificial Neural Network (ANN) model. This model expedites the acquisition of the sensitivity parameters. The study also proposes urban functional zoning rules incorporating “socio-driven-nature-assisted” characteristics of the underlying surface. Finally, the clustering feature thresholds of the sensitive parameters were distributed across various catchment units based on the urban functional area distribution rules. This distribution was used to select multiple observed rainfall-runoff events to determine the optimal parameters of the inundation model, culminating in the construction of the BIC-GMM-Transformer-ANN-flooding model (BGTA-FM). The experimental results indicated that the method based on this intelligent modeling framework reached a mean Nash-Sutcliffe efficiency coefficient (NSE) of 0.8. This performance represents a 0.3 and 0.15 increase in NSE compared to the Transformer-ANN-flooding model and BIC-GMM-flooding model, respectively, and significantly enhances modeling efficiency. This effectively reflects the complex underlying surface environments of the research area. Our work demonstrates the substantial potential of integrating physical knowledge with machine learning in urban flood intelligent modeling and reaffirms the critical role of applying geospatial artificial intelligence (GeoAI) in geo-environmental research and disaster management.

Background To investigate the effects of arsenic trioxide (ATO) on human colorectal cancer cells (HCT116) growth and the role of transient receptor potential melastatin 4 (TRPM4) channel in this process. Methods The viability of HCT116 cells was assessed using the CCK-8 assay. Western blot analysis was employed to examine the protein expression of TRPM4. The apoptosis of HCT116 cells was determined using TUNEL and Flow cytometry. Cell migration was assessed through the cell scratch recovery assay and Transwell cell migration assay. Additionally, Transwell cell invasion assay was performed to determine the invasion ability of HCT116 cells. Results ATO suppressed the viability of HCT116 cells in a dose-dependent manner, accompanied by a decline in cell migration and invasion, and an increase in apoptosis. 9-phenanthroline (9-Ph), a specific inhibitor of TRPM4, abrogated the ATO-induced upregulation of TRPM4 expression. Additionally, blocking TRPM4 reversed the effects of ATO on HCT116 cells proliferation, including restoration of cell viability, migration and invasion, as well as the inhibition of apoptosis. Conclusion ATO inhibits CRC cell growth by inducing TRPM4 expression, our findings indicate that ATO is a promising therapeutic strategy and TRPM4 may be a novel target for the treatment of CRC.

The five axis linkage Computer Numerical Control machine tool for integral impeller can achieve blade machining through side milling, which is of great significance for improving the machining accuracy, production efficiency, and long-term stability of integral impeller blades. This study is based on non-uniform rational B-spline curves and aims to reduce the surface over cutting or under cutting of integral turbine blades. The path planning of non deployable ruled surfaces was analyzed in depth through side milling, and the path planning model of the side milling cutter axis was solved through a fusion algorithm of simulated annealing algorithm and particle swarm optimization algorithm, in order to find the optimal path through iterative process. As the number of iterations increased, the error values of particle swarm optimization algorithm and simulated annealing particle swarm optimization fusion algorithm gradually decreased, with convergence times of about 7 and 6, respectively. The stable error value of the fusion algorithm was 0.253, which is 30.45% lower than that of the particle swarm optimization algorithm. The optimal number of iterations for solving the model using particle swarm optimization algorithm and fusion algorithm was the 7th, with range values of 0.0213 and 0.0165 mm, respectively. The tool axis trajectory surface optimized by the fusion algorithm was closer to the tool axis motion state compared to the initial tool axis trajectory surface. The range of the sum of mean squared deviations for single and global cutting was 0.0011–0.0198 and 0.046–0.0341, but the overall error value was relatively small. This study effectively reduces the envelope error of machining tools and improves machining accuracy, thereby solving the principle error of non expandable ruled surfaces in the motion trajectory of the blade axis of the integral turbine. This provides new research ideas for the intelligent development of Computer Numerical Control machining technology.

Mapping coastal wetlands' spatial distribution and spatiotemporal dynamics is crucial for ecological conservation and restoration efforts. However, the high hydrological dynamics and steep environmental gradients pose challenges for precise mapping. This study developed a new method for mapping coastal wetlands using time-series remote sensing images and a deep learning model. Precise mapping and change analysis were conducted in the Liaohe Estuary Reserve in 2017 and 2022. The results demonstrated the superiority of Temporal Optimize Features (TOFs) in feature importance and classification accuracy. Incorporating TOFs into the ResNet model effectively combined temporal and spatial information, enhancing coastal wetland mapping accuracy. Comparative analysis revealed ecological restoration trends, emphasizing artificial restoration's predominant role in salt marsh vegetation rehabilitation. These findings provide essential technical support for coastal wetland ecosystem monitoring and contribute to the study of sustainability under global climate change.

This investigation aims to elucidate the novel role of Stromal Interaction Molecule 1 (STIM1) in modulating store-operated calcium entry (SOCE) and its subsequent impact on inflammatory cytokine release in T lymphocytes, thereby advancing our understanding of trigeminal neuralgia (TN) pathogenesis. Employing the Gene Expression Omnibus (GEO) database, we extracted microarray data pertinent to TN to identify differentially expressed genes (DEGs). A subsequent comparison with SOCE-related genes from the Genecards database helped pinpoint potential target genes. The STRING database facilitated protein-protein interaction (PPI) analysis to spotlight STIM1 as a gene of interest in TN. Through histological staining, transmission electron microscopy (TEM), and behavioral assessments, we probed STIM1's pathological effects on TN in rat models. Additionally, we examined STIM1's influence on the SOCE pathway in trigeminal ganglion cells using techniques like calcium content measurement, patch clamp electrophysiology, and STIM1- ORAI1 co-localization studies. Changes in the expression of inflammatory markers (TNF-α, IL-1β, IL-6) in T cells were quantified using Western blot (WB) and enzyme-linked immunosorbent assay (ELISA) in vitro, while immunohistochemistry and flow cytometry were applied in vivo to assess these cytokines and T cell count alterations. Our bioinformatic approach highlighted STIM1's significant overexpression in TN patients, underscoring its pivotal role in TN's etiology and progression. Experimental findings from both in vitro and in vivo studies corroborated STIM1's regulatory influence on the SOCE pathway. Furthermore, STIM1 was shown to mediate SOCE-induced inflammatory cytokine release in T lymphocytes, a critical factor in TN development. Supportive evidence from histological, ultrastructural, and behavioral analyses reinforced the link between STIM1-mediated SOCE and T lymphocyte-driven inflammation in TN pathogenesis. This study presents novel evidence that STIM1 is a key regulator of SOCE and inflammatory cytokine release in T lymphocytes, contributing significantly to the pathogenesis of trigeminal neuralgia. Our findings not only deepen the understanding of TN's molecular underpinnings but also potentially open new avenues for targeted therapeutic strategies.

Purpose: This retrospective study aims to evaluate the safety, practicality, and efficacy of the independent retrograde popliteal approach for recanalization superficial femoral artery (SFA) occlusions when the bilateral common femoral artery approach is unavailable, such as after endovascular aneurysm repair or common iliac artery stenting. Methods: This treatment was considered for patients with contralateral iliac artery occlusion, severe iliac tortuosity, or those who had previously undergone endovascular aneurysm repair or common iliac stenting. Patients with SFA lesions extending into the P1–P2 segment of the popliteal artery or with calcification in the P3 segment were excluded. Angioplasty and stenting were conducted via the popliteal artery approach, with hemostasis at the puncture site achieved using an EXOSEAL vascular closure device. Patients were routinely followed up at 3, 6, and 12 months, and annually thereafter. Results: Forty-eight consecutive patients with SFA occlusion who underwent endovascular treatment via the retrograde popliteal artery approach were included in this study. Retrograde puncture of the popliteal artery was successful in all cases. Six-French sheaths were utilized in all procedures. The EXOSEAL vascular closure device was successfully applied in all 48 cases. No instances of pseudoaneurysms, arteriovenous fistulas, major bleeding, or embolic complications were observed. The technical success rate for SFA recanalization was 100 %. All patients experienced clinical improvement. The ankle-brachial index significantly increased from an initial 0.33 ± 0.11 at admission to 0.81 ± 0.19 at discharge (P

Abstract Tumor‐infiltrating CD4+ T cells orchestrate the adaptive immune response through remarkable plasticity, and the expression patterns of exhaustion‐related inhibitory receptors in these cells differ significantly from those of CD8+ T cells. Thus, a better understanding of the molecular basis of CD4+ T cell exhaustion and their responses to immune checkpoint blockade (ICB) is required. Here, we integrated multiomics approaches to define the phenotypic and molecular profiles of exhausted CD4+ T cells in oropharyngeal squamous cell carcinoma (OPSCC). Two distinct immune‐promoting (Module 1) and immunosuppressive (Module 2) functional modules in tumor‐infiltrating CD4+ T cells were identified, and both the immune‐promoting function of Module 1 cells and immunosuppressive function of Module 2 cells were positively associated with their corresponding exhaustion states. Furthermore, the application of ICBs targeting effector CD4+ T cells in Module 1 (αPD‐1) and Treg cells in Module 2 (αCTLA‐4) in mouse models could help reinvigorate the effector function of Module 1‐exhausted CD4+ T cells and reduce the immunosuppressive function of Module 2‐exhausted CD4+ T cells, ultimately promoting OPSCC tumor regression. Taken together, our study provides a crucial cellular basis for the selection of optimal ICB in treating OPSCC.

The rare and endemic largemouth bronze gudgeon (Coreius guichenoti) inhabits the middle and upper reaches of the Yangtze River. It is a typical migratory river fish found in the vicinity of rapids. Over the years, the construction of water conservancy facilities and overfishing by humans have harmed the ecological habitat of this species, resulting in a considerable population decline. Thus, the largemouth bronze gudgeon has emerged as an important conservation objective and artificial stocking target for protecting and restoring the ecological environment in the Yangtze River Basin. Artificial stocking is one of the most effective methods for restoring the population of rare and endangered fish, and it is widely used domestically and abroad. Culturing a healthy and sufficient number of fry is critical to stocking success. In the production of largemouth bronze gudgeon, the formulation of an effective feeding strategy plays an important role. A scientific and reasonable feeding rate and frequency serve as guidelines for improving the production and quality of cultured fry, which directly impact the survival rate, growth performance, and feed consumption of fish. In order to determine the appropriate feeding strategy for improving fry breeding efficiency, an 8-week feeding trial in a 5 × 2 two-factorial design was conducted to investigate the effects of feeding levels (1%, 2%, 3%, 4%, and 5%) and feeding frequency (2 and 3 times/d) on growth, whole-body composition, digestive enzyme activity, and liver structure of juvenile largemouth bronze gudgeons with an initial weight of (4.91±0.11) g. The results were as follows: After 8 weeks of culture, the survival status of largemouth bronze gudgeon in each treatment group was good. Only two fish mortalities were observed, one in each of the two feeding frequency groups at the 5% feeding level. There was no mortality in the other groups. Feeding level, feeding frequency, and the interaction of the two items had significant effects on the weight gain rate (WGR), specific growth rate (SGR), and feed efficiency (FE) of individuals, whereas only the feeding frequency had significant effects on the condition factor (CF) and viscerosomatic index (VSI). WGR and SGR significantly increased with the feeding level. Meanwhile, the FE increased with increasing feeding levels and then stabilized at the 3% feeding level. Fish fed 3 times/d had higher WGR, SGR, and FE than fish fed 2 times/d when feeding levels did not exceed 3%. As feeding frequency increased, the CF and VSI of individuals tended to decrease. Both whole-body moisture content and crude fat content were significantly affected by the feeding level. The increase in feeding level decreased the whole-body moisture content while increasing the whole-body crude fat content. Digestive enzymes in the foregut of individuals were not significantly affected by feeding level, feeding frequency, or their interactions; however, the feeding level had significant effects on hepatic trypsin (TPS) and lipase (LPS) activities. Increasing feeding levels considerably reduced the TPS activity when the feeding levels were higher than 3%, whereas the LPS activity initially increased and then decreased with increasing feeding levels at a feeding frequency of 3 times/d. Hepatic HE staining revealed that the hepatocytes of fish fed 2 times/d continued to increase in size and progressively swelled and vacuolated, exhibiting indications of a fatty liver when the feeding level reached 3% and increased further. Hepatocytes of fish fed 3 times/d were surrounded by a large number of round and ovoid lipid droplets at the 3% and 4% feeding levels, but there were no discernible changes in the structure of the cells. When the feeding level reached 5%, hepatocytes began to enlarge and swell in groups at a feeding frequency of 3 times/d, but to a lesser extent than the groups fed 2 times/d. In conclusion, under the conditions of this experiment, a comprehensive assessment of growth performance, feed utilization efficiency, and hepatic health revealed that feeding juvenile largemouth bronze gudgeons three times daily at a level of 3% body weight was the optimal feeding strategy. The objective of this study was to determine the optimal feeding strategy for the fry culturing process. The findings provide theoretical guidelines for the artificial reproduction of largemouth bronze gudgeon and contribute to the recovery of its native population. Additionally, as a species that inhabits torrential habitats, the largemouth bronze gudgeon possesses distinct digestive and physiological properties. This study lays the foundation and groundwork for future research on the nutritional requirements, feed production, and artificial breeding of these species.

Cereal is an essential source of calories and protein for the global population. Accurately predicting cereal quality before harvest is highly desirable in order to optimise management for farmers, grading harvest and categorised storage for enterprises, future trading prices, and policy planning. The use of remote sensing data with extensive spatial coverage demonstrates some potential in predicting crop quality traits. Many studies have also proposed models and methods for predicting such traits based on multi-platform remote sensing data. In this paper, the key quality traits that are of interest to producers and consumers are introduced. The literature related to grain quality prediction was analyzed in detail, and a review was conducted on remote sensing platforms, commonly used methods, potential gaps, and future trends in crop quality prediction. This review recommends new research directions that go beyond the traditional methods and discusses grain quality retrieval and the associated challenges from the perspective of remote sensing data.

Abstract Identifying high-risk regions and turning points of influenza with a precise spatiotemporal scale may provide effective prevention strategies. In this study, epidemiological characteristics and spatiotemporal clustering analysis at the township level were performed. A descriptive study and a Joinpoint regression analysis were used to explore the epidemiological characteristics and the time trend of influenza. Spatiotemporal autocorrelation and clustering analyses were carried out to explore the spatiotemporal distribution characteristics and aggregation. Furthermore, the hotspot regions were analyzed by spatiotemporal scan analysis. A total of 4025 influenza cases were reported in Yinchuan showing an overall increasing trend. The tendency of influenza in Yinchuan consisted of three stages: increased from 2012 to the first peak in 2019 (32.62/100,000) with a slight decrease in 2016; during 2019 and 2020, the trend was downwards; then it increased sharply again and reached another peak in 2022. The Joinpoint regression analysis found that there were three turning points from January 2012 to December 2022, namely January 2020, April 2020, and February 2022. The children under ten displayed an upward trend and were statistically significant. The trend surface analysis indicated that there was a shifting trend from northern to central and southern. A significant positive spatial auto-correlation was observed at the township level and four high-incidence clusters of influenza were detected. These results suggested that children under 10 years old deserve more attention and the spatiotemporal distribution of high-risk regions of influenza in Yinchuan varies every year at the township level. Thus, more monitoring and resource allocation should be prone to the four high-incidence clusters, which may benefit the public health authorities to carry out the vaccination and health promotion timely.

Abstract Background The literature on therapeutic landscapes highlights that the university campus landscape has restorative effects on students. This deserves more scholarly attention since mental health has become an important issue among university students. However, existing empirical studies have revealed mixed evidence with little attention to the heterogeneity across the design and, therefore, the potential therapeutic effects across different landscapes. Method This research examined how 13 landscape sites on a university campus might be differentially related to student well-being. These sites were identified from a variety of sources (campus design documents, photos used in the university’s social media posts, and interviews with a small group of students) to represent a comprehensive list of places that students might visit. The data was collected in a large online survey of a Chinese university (n = 2,528). We asked about students’ use of individual landscape sites and the associated motivations for visits, and measured well-being using a perceived stress scale and overall evaluation of the happiness level. Bivariate analysis was used to explore the zero-order associations between landscape use and well-being. OLS (for stress) and logistic regressions (for happiness) were conducted to further evaluate the associations after controlling the student background variables and potential correlations of uses across different landscapes. Results Among 13 landscape sites, four sites had significant positive associations with either or both measures of well-being after controlling for the student characteristics and use of the other landscape sites. There was also an additive benefit of visiting more landscapes. Compared to those who did not frequently visit any of the sites, well-being had a significant stepwise increase among those who frequently visited one or two and more sites. One site that was significantly related to both measures of well-being only offered distant views of landscapes, but it was right next to the study areas. Conclusions This study demonstrates the heterogeneity of restorative effects across different landscapes on campus. The findings suggest that effective landscape design that aims to promote student well-being should be placed close to stressors (i.e., where they study), and between where they study and live to offer students opportunities to break from the common routines and to relax. The findings hold greater relevance for universities in China and institutions with similar student campus lifestyles, occupancies, and behavior patterns worldwide.

Abstract This study presents a novel method for optimizing parameters in urban flood models, aiming to address the tedious and complex issues associated with parameter optimization. First, a coupled one-dimensional pipe network runoff model and a two-dimensional surface runoff model were integrated to construct an interpretable urban flood model. Next, a principle for dividing urban hydrological response units was introduced, incorporating surface attribute features. The K-means algorithm was used to explore the clustering patterns of the uncertain parameters in the model, and an artificial neural network (ANN) was employed to identify the sensitive parameters. Finally, a genetic algorithm (GA) was used to calibrate the parameter thresholds of the sub-catchment units in different urban land-use zones within the flood model. The results demonstrate that the parameter optimization method based on K-means-ANN-GA achieved an average Nash-Sutcliffe efficiency coefficient (NSE) of 0.81. Compared to the ANN-GA and K-means-deep neural networks (DNN) methods, the proposed method better characterizes the runoff generation and flow processes. This study demonstrates the significant potential of combining machine learning techniques with physical knowledge in parameter optimization research for flood models.

The moving particle simulation (MPS) method is a simulation technique capable of calculating free surface and incompressible flows. As a particle-based method, MPS requires significant computational resources when simulating flow in a large-scale domain with a huge number of particles. Therefore, improving computational speed is a crucial aspect of current research in particle methods. In recent decades, many-core CPUs and GPUs have been widely utilized in scientific simulations to significantly enhance computational efficiency. However, the implementation of MPS on different types of hardware is not a trivial task. In this study, we present an implementation method for the explicit MPS that utilizes the Taichi parallel programming language. When it comes to CPU computing, Taichi’s computational efficiency is comparable to that of OpenMP. Nevertheless, when GPU computing is utilized, the acceleration of Taichi in parallel computing is not as fast as the CUDA implementation. Our developed explicit MPS solver demonstrates significant performance improvements in simulating dam-break flow dynamics.

In order to achieve high quality image transmission, a novel hybrid digital-analog (HDA) wireless transmission method was proposed.Firstly, the image residual layer was constructed by subtracting the downsampled and upsampled images from the original image respectively.Secondly, an adaptive-clustered block-level discrete cosine transform (DCT) algorithm was proposed to efficiently remove the correlation between image pixels in the residual layer.Finally, an image block level-based unequal power allocation strategy for further boosting the quality of received images was proposed.Extensive experiments results demonstrate that the proposed method is significantly superior to existing successful hybrid digital analog image wireless transmission methods in both qualitative evaluation and quantitative measurement.

The incidence of spinal degenerative diseases is increasing yearly, due to the global population aging. Spinal surgery, such as laminectomy, remains the most effective, comprehensive, and widely practiced treatment for spinal degenerative disease. As the lamina is adjacent to the spinal cord, spinal nerve injury is one of the most common complications of freehand laminectomy. In view of the high risk, complexity, and extensive learning curve of laminectomy, the surgical robots can improve the safety of surgical operation and have been gradually applied in orthopedics. However, robotic automated laminectomy was challenging because accurate state recognition and safety control are the prerequisites for robotic control, which lack of mature research. Accurate recognition of the inner cortical bone and precise robotic control are key to ensure that lamina is not pierced, which can prevent spinal nerve injury. Therefore, we took the lead in proposing a bone recognition model based on extreme learning machine (ELM) to recognize bone substance for various lamina milling conditions effectively. Specifically, the proposed model captures the features of milling force in spatial order data to produce richer bone characteristics representations. Also, based on our model, a control strategy was proposed to ensure robots stop timely when the milling instruments contact with the inner cortical bone. We verified the effectiveness of our recognition model and control strategy by in vivo and in vitro experiments and obtained great bone recognition performance. Notably, the recognition accuracy reached 100% under most milling conditions. And the laminectomy conducted by robot-assist automatic was controlled more safely than freehand (P value $2.2110-5$ and $1.7510-5$ ).

Transition metal carbides and nitrides (MXenes) are crystal nanomaterials with a number of surface functional groups such as fluorine, hydroxyl, and oxygen, which can be used as carriers for proteins and drugs. MXenes have excellent biocompatibility, electrical conductivity, surface hydrophilicity, mechanical properties and easy surface modification. However, at present, the stability of most MXenes needs to be improved, and more synthesis methods need to be explored. MXenes are good substrates for nerve cell regeneration and nerve reconstruction, which have broad application prospects in the repair of nervous system injury. Regarding the application of MXenes in neuroscience, mainly at the cellular level, the long-term in vivo biosafety and effects also need to be further explored. This review focuses on the progress of using MXenes in nerve regeneration over the last few years; discussing preparation of MXenes and their biocompatibility with different cells as well as the regulation by MXenes of nerve cell regeneration in two-dimensional and three-dimensional environments in vitro. MXenes have great potential in regulating the proliferation, differentiation, and maturation of nerve cells and in promoting regeneration and recovery after nerve injury. In addition, this review also presents the main challenges during optimization processes, such as the preparation of stable MXenes and long-term in vivo biosafety, and further discusses future directions in neural tissue engineering.

This paper describes the main results from an experimental investigation into the thermal stability of a cold-rolled Al–Y alloy. Tensile tests performed on specimens of the alloy and pure Al in annealed states reveal superior anti-softening properties of the former specimens relative to the latter counterparts. Origins of such thermal stability and underlying recovery and recrystallization kinetics are studied using electron microscopy and high energy X-ray diffraction (HEXRD) techniques. Microscopic observations reveal that recovery and recrystallization begin in the specimens of pure Al at a much lower temperature than in the specimens of Al–Y alloy. Onset of the recovery process in the Al–Y alloy is observed to begin with dislocation rearrangements in the β-Al3Y phases. The onset is followed by more substantial reduction in dislocation density, shrinkage of the β-Al3Y phases, and coarsening of the α-Al grains. The alloy contains stacking faults, which interestingly remain stable during the annealing treatments contributing to the thermal stability. The observed mechanisms are further confirmed by tracking the evolution of peaks under the in-situ synchrotron X-ray diffraction with heating. Onset of recovery was observed at 280 °C in both α-Al and β-Al3Y phases, while substantial shrinkage and spheroidization of β-Al3Y phases and decrease in dislocation density were detected at 400 °C causing loss of the alloy strength. Thermodynamic calculation showed that solubility of Y rapidly increases in α-Al at temperatures above 400 °C explaining the spheroidization and shrinkage of the β-Al3Y phases by diffusion of Y into the Al matrix.

Meiosis is the process of producing haploid gametes through a series of complex chromosomal events and the coordinated action of various proteins. The mitochondrial protease complex (ClpXP), which consists of caseinolytic mitochondrial matrix peptidase X (ClpX) and caseinolytic protease P (ClpP) and mediates the degradation of misfolded, damaged, and oxidized proteins, is essential for maintaining mitochondrial homeostasis. ClpXP has been implicated in meiosis regulation, but its precise role is currently unknown. In this study, we engineered an inducible male germ cell-specific knockout caseinolytic mitochondrial matrix peptidase X (ClpxcKO) mouse model to investigate the function of ClpX in meiosis. We found that disrupting Clpx in male mice induced germ cell apoptosis and led to an absence of sperm in the epididymis. Specifically, it caused asynapsis of homologous chromosomes and impaired meiotic recombination, resulting in meiotic arrest in the zygotene-to-pachytene transition phase. The loss of ClpX compromised the double-strand break (DSB) repair machinery by markedly reducing the recruitment of DNA repair protein RAD51 homolog 1 (RAD51) to DSB sites. This dysfunction may be due to an insufficient supply of energy from the aberrant mitochondria in ClpxcKO spermatocytes, as discerned by electron microscopy. Furthermore, ubiquitination signals on chromosomes and the expression of oxidative phosphorylation subunits were both significantly attenuated in ClpxcKO spermatocytes. Taken together, we propose that ClpX is essential for maintaining mitochondrial protein homeostasis and ensuring homologous chromosome pairing, synapsis, and recombination in spermatocytes during meiotic prophase I.

Because of the challenges associated with the difficulty of accurately labeling the remote sensing (RS) scene images and the need to identify new scene classes, few-shot learning has shown significant advantages in addressing the remote sensing scene classification (RSSC) tasks, leading to a growing interest. However, due to the scale variations of targets and irrelevant complex background in scene images, the current few-shot methods exist the following problems: the problem of the extraction capability of feature extractor in the few-shot mechanism; the problem of the separability of few-shot RS scene images classifier. To solve the above problems, an approach, called few-shot RSSC via subspace based on multiscale feature learning is introduced in this work. We first design a multiscale feature learning technique to address scale variations of the targets in the scene images. Concretely, different branches are utilized to learn scene features at various scales. The self-attention mechanism is embedded in each branch to incorporate the understanding of the global information in the different scale features. After that, a multiscale feature fusion operation, incorporating channel attention, will be devised to effectively merge the different scale features, so as to obtain a more precise feature representation of RS scene images. Furthermore, the subspace is utilized to capture the shared characteristics of each category, to reduce the impact of the complex irrelevant backgrounds in the scene images. The results of our experiments conducted on the public available RS scene datasets demonstrate the strong competitiveness of our approach.

The electrolytic capacitor-less variable frequency drive scheme using film capacitors to replace electrolytic capacitors has been partially applied in the field of washing machines and air conditioners driven by permanent magnet synchronous motors, due to its advantages of good reliability and low cost. However, recently, with the development and application of synchronous reluctance motors to replace permanent magnet synchronous motors, the existing methods have problems such as id = 0 control unsuitable for synchronous reluctance motors, low power factor on the input side, and poor motor running performance and other problems. Therefore, firstly, this paper takes the variable frequency drive system for the synchronous reluctance motors as the research object, analyses the influence of the value of the bus capacitance on the performance of the variable frequency drive system, and provides a theoretical basis for the selection of bus capacitance. Secondly, a current control strategy based on power balance and compensation is proposed, which includes current feeding based on power balance, input voltage phase detection based on a phase-locked loop, and output voltage vector regulation based on power compensation. To verify the correctness of the proposed method, a platform was built and tested, and the experimental results show that the electrolytic capacitor-less variable frequency drive system for synchronous reluctance motors using the method proposed in this paper not only improves the power factor at the input side of the drive system but also reduces the fluctuation of the motor speed and torque, which in turn improves the operating performance of the motor.

Unconventional resources like shale gas has been the focus of intense research and development for two decades. Apart from intrinsic geologic factors that control the gas shale productivity (e.g. organic matter content, bedding planes, natural fractures, porosity and stress regime among others), external factors like wellbore orientation and stimulation design play a role. In this study, we present a series of true triaxial hydraulic fracturing experiments conducted on Lushan shale to investigate the interplay of internal factors (bedding, natural fractures and in situ stress) and external factors (wellbore orientation) on the growth process of fracture networks in cubic specimens of 200 mm in length. We observe relatively low breakdown pressure and fracture propagation pressure as the wellbore orientation and/or the maximum in situ stress is subparallel to the shale bedding plane. The wellbore orientation has a more prominent effect on the breakdown pressure, but its effect is tapered with increasing angle of bedding inclination. The shale breakdown is followed by an abrupt response in sample displacement, which reflects the stimulated fracture volume. Based on fluid tracer analysis, the morphology of hydraulic fractures (HF) is divided into four categories. Among the categories, activation of bedding planes (bedding failure, BF) and natural fractures (NF) significantly increase bifurcation and fractured areas. Under the same stress regime, a horizontal wellbore is more favorable to enhance the complexity of hydraulic fracture networks. This is attributed to the relatively large surface area in contact with the bedding plane for the horizontal borehole compared to the case with a vertical wellbore. These findings provide important references for hydraulic fracturing design in shale reservoirs.

Abstract Background The characteristics of otological symptoms in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are lacking. Almost no research has been conducted to explore the emergence of otological symptoms after coronavirus disease 2019 infection. The aims of this study were to investigate the prevalence and specific clinical characteristics of and risk factors for otological symptoms among patients with SARS-CoV-2 infection. Methods We included two groups to investigate the prevalence and clinical characteristics of otological symptoms among patients with SARS-CoV-2 infection. The first sample (S1) was drawn retrospectively from four communities via questionnaires, and the second sample (S2) from an outpatient clinic. Results A total of 189 participants were included in S1 (124 women [65.6%]; mean [standard deviation (SD)] age, 33.66 [13.56] years), and 47 in S2 (25 women [53.2%]; mean [SD] age, 45.28 [14.64] years). The most prevalent otological symptoms in S1 were dizziness (15.9%), tinnitus (7.9%), aural fullness (6.9%), otalgia (5.3%), hearing loss (1.6%), and otopyorrhoea (1.1%). Moreover, for each additional typical symptom of SARS-CoV-2 infection, the risk (odds ratio) of otological symptoms increased by 1.33 (95% confidence interval: 1.10–1.61, p = 0.003). The prevalence of aural fullness was higher in the unvaccinated group than that in the group receiving two or three vaccinations (p = 0.018). Conclusions Various otological symptoms may occur in patients with SARS-CoV-2 infection. The number of typical symptoms of SARS-CoV-2 infection is positively associated with the probability of otological symptoms. However, vaccination may reduce the probability of certain otological symptoms.

Antibiotic contamination in water has received significant attention in recent years for the reason that the residuals of antibiotics can promote the progression of antibiotic-resistant bacteria (ARB) and antibiotic-resistant genes (ARGs). It is difficult to treat antibiotics using conventional biological treatment methods. In order to investigate an efficient new method of treating antibiotics in water, in this study, microwave (MW) was employed in revitalizing peroxymonosulfate (PMS) to treat typical antibiotic tetracycline (TC). The Box–Behnken design (BBD) was applied to organize the experimental schemes. The response surface methodology (RSM) optimization was run to derive the best experimental conditions and validated using actual data. Moreover, the main mechanisms of PMS activation via MW were resolved. The results demonstrated that the relationship between TC removal rate and influencing factors was consistent with a quadratic model, where the P-value was less than 0.05, and the model was considered significant. The optimal condition resulting from the model optimization were power = 800 W, [PMS] = 0.4 mM, and pH = 6.0. Under such conditions, the actual removal of TC was 99.3%, very close to the predicted value of 99%. The quenching experiment confirmed that SO4•− and •OH were jointly responsible for TC removal. HIGHLIGHTS MW/PMS was employed to treat tetracycline.; BBD was applied to design the experimental protocol.; The equation between TC removal and influences was established.; RSM was used to predict optimal conditions.; TC was co-oxidized by SO4•− and •OH to CO2 and H2O.;