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Objectives This research first investigated the effect of mesoporous silica nanoparticles (nMS) carrying chlorhexidine and silver (nMS-nAg-Chx) on periodontitis-related biofilms. This study aimed to investigate (1) the antibacterial activity on Porphyromonas gingivalis (P. gingivalis) biofilm; (2) the suppressing effect on virulence of P. gingivalis biofilm; (3) the regulating effect on periodontitis-related multispecies biofilm.Methods Silver nanoparticles (nAg) and chlorhexidine (Chx) were co-loaded into nMS to form nMS-nAg-Chx. Inhibitory zone test and minimum inhibitory concentration (MIC) against P. gingivalis were tested. Growth curves, crystal violet (CV) staining, live/dead staining and scanning electron microscopy (SEM) observation were performed. Biofilm virulence was assessed. The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay and Quantitative Real Time-PCR (qPCR) were performed to validate the activity and composition changes of multispecies biofilm (P. gingivalis, Streptococcus gordonii and Streptococcus sanguinis).Results nMS-nAg-Chx inhibited P. gingivalis biofilm dose-dependently (p

Over the years, the field of landslide disaster research has amassed a wealth of data and specialized knowledge. However, these resources originate from a wide array of sources and often feature complex data structures, highlighting a persistent lack of methods to integrate multi-source, heterogeneous data. Traditional landslide monitoring methods typically focus on singular monitoring targets and data sources, which limits a comprehensive understanding of the complex processes involved in landslides. This paper introduces a landslide monitoring model based on a knowledge graph. This model employs P-Tuning to fine-tune ChatGLM2 for the extraction of triples. Differential InSAR (D-InSAR) is utilized to extract ground deformation data, which is then integrated with the knowledge graph for landslide monitoring and analysis. This study focuses on the co-seismic landslide in Jishishan, Gansu, China. By analyzing the landslide knowledge graph and the spatiotemporal deformation map, the results are as follows: (1) For this event, 106 entities and attributes were constructed, along with two recommended calculation routes. (2) The deformation at the earthquake’s central region reached up to 8.784 cm, with a slightly smaller deformation zone to the northwest peaking at 9.662 cm. Significant unilateral subsidence was observed in the mountain range to the southwest. (3) The area affected by the co-seismic landslide primarily includes farmland and villages, covering an area of 0.3408 square kilometers. (4) Analysis based on the knowledge graph indicates that this landslide was primarily caused by the rapid liquefaction of water-saturated soil layers due to the earthquake, resulting in instability. This study contributes to the analysis of post-disaster losses, attribution, and impacts.

China’s vulnerability to fluvial floods necessitates extensive exposure studies. Previous large-scale regional analyses often relied on a limited set of assessment indicators due to challenges in data acquisition, compounded by the scarcity of corresponding large-scale flood distribution data. The integration of public datasets offers a potential solution to these challenges. In this study, we obtained four key exposure indicators—population, built-up area (BA), road length (RL), and average gross domestic product (GDP)—and conducted an innovative analysis of their correlations both overall and locally. Utilising these indicators, we developed a comprehensive exposure index employing entropy-weighting and k-means clustering methods and assessed fluvial flood exposure across multiple return periods using fluvial flood maps. The datasets used for these indicators, as well as the flood maps, are primarily derived from remote sensing products. Our findings indicate a weak correlation between the various indicators at both global and local scales, underscoring the limitations of using singular indicators for a thorough exposure assessment. Notably, we observed a significant concentration of exposure and river flooding east of the Hu Line, particularly within the eastern coastal region. As flood return periods extended from 10 to 500 years, the extent of areas with flood depths exceeding 1 m expanded markedly, encompassing 2.24% of China’s territory. This expansion heightened flood risks across 15 administrative regions with varying exposure levels, particularly in Jiangsu (JS) and Shanghai (SH). This research provides a robust framework for understanding flood risk dynamics, advocating for resource allocation towards prevention and control in high-exposure, high-flood areas. Our findings establish a solid scientific foundation for effectively mitigating river flood risks in China and promoting sustainable development.

This paper investigates and analyzes the dynamic response of asphalt pavement under pavement-unevenness excitation based on an orthogonal vector function system and efficient DVP (dual variable and position) method. Firstly, starting from the pavement unevenness of the vehicle excitation source, the pavement-unevenness excitation is established by using the filtered white-noise method, and the random load of the vehicle model is obtained by simulation. Then, based on the basic governing equation of the road-surface problem under the random load, the analytical solution of the road-surface mechanical response is obtained by using the orthogonal vector function system and DVP method. The effects of pavement-unevenness grade, vehicle speed, vehicle load, interlayer contact condition, and transverse isotropy on the mechanical response of the road surface are analyzed via the analytical results. The results show that DVP can effectively solve the dynamic response of pavements under the excitation of pavement unevenness; in addition, it can also be applied to certain situations, such as transverse isotropy of materials and interface conditions. The results show that the pavement unevenness does not affect the average stress and strain of each layer but has a significant effect on the peak value and dispersion degree. An increase in vehicle speed causes a peak in strain and a larger coefficient of variation. Poor bonding between interfaces can lead to increased stress and strain at the bottom of the surface layer.

The vehicle load on a bridge is a critical and dynamic variable. It adversely affects bridges, especially when overloading occurs. Bridges are prone to fatigue damage or collapse. Therefore, identifying the size and type of dynamic vehicle loads on bridges is critical for theoretical studies and practical applications, such as health monitoring, daily maintenance, safety assessment, and traffic planning. The paper proposes a method for identifying the dynamic load parameters based on a convolutional neural network (CNN) and dynamic strain data. The model is implemented in MATLAB. An initial finite-element model of a three-span precast beam bridge is established in the software ABAQUS and modified by combining the modal and experimental data derived from a segmental girder bridge. The dynamic strain response of the bridge under a moving vehicle load is simulated under different working conditions. The results are used as the training data of the CNN to identify the vehicle’s position, speed, and load on the bridge. The high prediction accuracy indicates the proposed model’s suitability for identifying the dynamic load parameters.

In order to study the stiffness degradation of pre-stressed concrete T-beams throughout their entire service life, full-scale destructive tests were conducted on newly constructed T-beams. The test process characterized the relationship between load and deflection at different load levels. Meanwhile, the equivalent stiffness and short-term stiffness of the T-beams at different load levels were calculated based on formulas from the code, and a segmental stiffness back-calculation method for pre-stressed concrete T-beam bridges was proposed based on system identification theory. The results show that, during the destructive test process, the T-beams experienced complete, partial linear, and non-linear stages. By using the equivalent stiffness and short-term stiffness to predict the stiffness changes during the overall failure process of the T-beams, it was found that, when cracks appeared, the stiffness of the T-beams decreased by 31% compared to the initial value, and the stiffness continued to decrease as the cracks extended further. The segmental stiffness system identification back-calculation method more accurately described the destructive test process of each section of the T-beams. This method can help to evaluate the extent of damage in each section of the beams during the overall destructive test process and further assess the overall structural integrity of the beams.

The development of information technology has led to massive, multidimensional, and heterogeneously sourced disaster data. However, there’s currently no universal metadata standard for managing natural disasters. Common pre-training models for information extraction requiring extensive training data show somewhat limited effectiveness, with limited annotated resources. This study establishes a unified natural disaster metadata standard, utilizes self-trained universal information extraction (UIE) models and Python libraries to extract metadata stored in both structured and unstructured forms, and analyzes the results using the Word2vec-Kmeans cluster algorithm. The results show that (1) the self-trained UIE model, with a learning rate of 3 × 10−4 and a batch_size of 32, significantly improves extraction results for various natural disasters by over 50%. Our optimized UIE model outperforms many other extraction methods in terms of precision, recall, and F1 scores. (2) The quality assessments of consistency, completeness, and accuracy for ten tables all exceed 0.80, with variances between the three dimensions being 0.04, 0.03, and 0.05. The overall evaluation of data items of tables also exceeds 0.80, consistent with the results at the table level. The metadata model framework constructed in this study demonstrates high-quality stability. (3) Taking the flood dataset as an example, clustering reveals five main themes with high similarity within clusters, and the differences between clusters are deemed significant relative to the differences within clusters at a significance level of 0.01. Overall, this experiment supports effective sharing of disaster data resources and enhances natural disaster emergency response efficiency.

The grouting quality of prestressed pipelines directly affects the safety and durability of prestressed reinforced concrete bridge structures, attracting wide attention from the engineering community. Based on the principles of the scattering wave method, this paper designs and manufactures a large-scale model to simulate the actual construction testing environment. Several sets of design defects with significantly distributed spans in the prestressing ducts were pre-set, and the Engineering Geophysical Instrument System–Pipeline Grouting Profile (EGS-PGP) equipment developed was used to detect the grouting quality of the prestressed pipelines under different conditions, obtaining the frequency attenuation values at defect locations. The study shows that stability of the peak frequency throughout the test can indicate compact grouting, while a large fluctuation in the peak frequency range with no regular changes can indicate non-compact grouting; a sudden increase or decrease in peak frequency can effectively indicate the location of grouting defects along the pipeline. The number of sudden changes in frequency can indicate the number of gaps inside the pipeline. The chirp signal, compared to the hammer impact signal, shows greater stability and engineering application value in detecting defects using the scatter wave method. This study provides technical support for the detection of grouting quality in prestressed pipelines based on chirp signals.

Remote sensing precipitation data have the characteristics of wide coverage and revealing spatiotemporal information, but their spatial resolution is low. The accuracy of the data is obviously different in different study areas and hydrometeorological conditions. This study evaluated four precipitation products in the Yellow River basin from 2001 to 2019, constructed the optimal combined product, conducted downscaling with various machine algorithms, and performed corrections using meteorological station precipitation data to analyze the spatiotemporal trends of precipitation. The results showed that (1) GPM and MSWEP had the best four evaluation indicators, with R2 values of 0.93 and 0.90, respectively, and the smallest FSE and RMSE, with a BIAS close to 0. A high-precision mixed precipitation dataset, GPM-MSWEP, was constructed. (2) Among the three methods, the downscaling results of DFNN showed higher accuracy. (3) The results, after correction with GWR, could more effectively enhance the accuracy of the data. (4) Precipitation in the Yellow River Basin showed a decreasing trend in January, September, and December, while it exhibited an increasing trend in other months and seasons, with 2002 and 2016 being points of abrupt change. This study provides a reference for the production of high-precision satellite precipitation products in the Yellow River basin.

The void phenomenon behind the tunnel lining has become the main cause of tunnel disease, easily triggering tunnel lining structure damage, shedding, water seepage, and other diseases that seriously threaten the normal operation of the tunnel. The void area behind the lining seriously reduces the seismic capacity of the tunnel. In this paper, the mechanical parameters of the surrounding rock are calculated by optimizing the inversion of the improved system identification sensitivity analysis method, and the numerical model of the tunnel’s dynamic response is optimized using the improved inversion results to study the repair effect and seismic capacity of the Longmenshan tunnel using polymer grouting to repair the void area behind the lining under the action of a seismic load. The results show that the displacement and stress at the top of the tunnel secondary lining void area are significantly reduced and close to normal after the repair of polymer grouting; however, the stress and displacement at the top of the secondary lining are significantly different under the action of seismic waves at the same peak at different site conditions, which indicates that the dynamic response of this tunnel model has obvious sensitivity to the seismic wave spectrum.

Abstract Background We sought to determine (1) whether the addition of prophylactic oral mosapride to a protocol including dexamethasone and ondansetron further reduces postoperative nausea and vomiting (PONV) compared with ondansetron alone or the combination of both; (2) whether preemptive application of oral mosapride provides additional clinical benefits for bowel function and appetite, thus improving functional recovery. Methods We randomized 240 patients undergoing total hip and knee arthroplasty to receive placebo (Control, n = 80), dexamethasone (10 mg) before anesthesia induction (Dexa, n = 82), or dexamethasone (10 mg) before anesthesia induction as well as oral mosapride (5 mg) before and after surgery (Mosa+Dexa, n = 78). Patients were assessed at 0–6, 6–12, 12–24, and 24–48 h postoperatively. Primary outcomes were incidence and severity of PONV as well as complete response. Secondary outcomes were appetite, time until first defecation and ambulation, patient satisfaction score, and length of hospital stay. Results Mosa+Dexa patients showed significantly lower incidence of nausea at 6–12 h (3.8%) and over the entire evaluation period (6.4%), as well as a higher rate of complete response (89.7%) than other patients. Mosa+Dexa patients required less time to achieve first defecation and ambulation, they were hospitalized for shorter time, and they were more satisfied with clinical care. Conclusion Addition of oral mosapride further reduced incidence of PONV, especially postoperative nausea, during 6–12 h postoperatively. Moreover, preemptive application of oral mosapride can further improve appetite, bowel function, ambulation and length of hospital stay. Trial registration The study protocol was registered at the Chinese Clinical Trial Registry ( ChiCTR1800015896 ), prospectively registered on 27/04/2018.

Emulsified asphalt is widely used as a prime coat in road engineering, especially in pavements with cement-stabilized semi-rigid bases. The objective of this paper is to develop a new emulsified asphalt with high permeability and pulling-off strength. A new type of high-permeability emulsified asphalt was prepared by using 55.2% diluted asphalt (44.16% matrix asphalt + 11.04% diluent) + 40% emulsion (2% emulsifier + 0.5% stabilizer + 1% osmotic agent + 1% op-10 + 35.5% water) + 4.8% aromatic oil. The storage stability was verified to be better, and the penetrating rate and depth were increased largely compared to the traditional products. To improve pulling-off strength, the high-permeability emulsified asphalt was further modified by mixing with 20% water-based epoxy resin and a curing agent. The penetration, pull-off, and shear strength tests were also conducted. It can be found that the permeability, adhesive, and water-resisting properties of the modified high-permeability emulsified asphalt can be further improved to a certain degree.

As a sustainable development requirement, rational utilization of solid waste has been paid more and more attention, such as acetylene sludge (AS), fly ash (FA), coal gangue, and construction waste used in civil engineering. The comprehensive utilization of the solid waste has already been developed for road engineering recently. This study focuses on the properties of base or subbase that are made of coal gangue and construction waste stabilized by AS and FA. The base or subbase material with various volumetric ratios of AS:FA:stacked coal gangue (SCG), AS:FA:air-washed coal gangue (ACG), AS:FA:recycled brick, and concrete debris (RBCD) were designed. In addition, their properties were tested, including unconfined compressive strength (UCS), indirect tensile strength (ITS), and compressive resilient modulus. The results showed that the UCS and ITS of the SCG stabilized by AS–FA are higher than that of the ACG stabilized by AS–FA. However, there was no significant correlation between UCS, ITS, compressive resilient modulus, and binder content of the AS/FA-stabilized RBCD. Even though the properties of the solid waste mixture were not stable enough, it could be potentially used in the base or subbase of the pavements.

Wood easily acquires a large amount of moisture when it is exposed to high-humidity conditions. The high moisture content influences the service life of wood. Thus, there is a need for an accurate, rapid, nondestructive, and simple measurement technique for wood’s moisture content. This investigation proposes a method to measure the moisture content of wood by the wood volumetric heat capacity using a transient hot wire (THW) technique. The moisture content was inferred from the change of the volumetric heat capacity before and after the wood acquired moisture; the volumetric heat capacity is the ratio of the thermal conductivity to the thermal diffusivity. The results were validated by the gravimetric method, displaying good agreement, with discrepancies within 4%.

The homogenized micro-crack crushing technology for concrete pavement maintenance has received increased attention in China. To study the fracture mechanism of the homogenized micro-crack crushing technology, a low-velocity impact test system is developed and experiments using concrete slabs of different thicknesses are conducted with different drop heights and hammer weights. Furthermore, the fracture of concrete slabs under impact loading is simulated using the continuous-discontinuous element method. Finally, the fracture mechanism is investigated in a case study. It is concluded that a cylindrical compression–shear fracture surface appears under the impact head while the fractured blocks are still interlocked with each other. The main cracks in the concrete slabs are initiated and propagate parallel to the longer side of the impact head, whereas branch cracks develop perpendicular to the main cracks. These cracks radiate from the center of the impact head. The cracks inside the concrete develop upward from the bottom of the slabs. Because fractured blocks divided by micro-cracks can interlock with themselves and the crack distributions tend to be uniform, it is beneficial for portland cement concrete pavement rehabilitation to be overlaid by a hot-mix asphalt mixture.

The effect of low pressure saturated vapor pre-steaming on restrained shrinkage strain, mechano-sorptive creep and the distribution of moisture content was investigated during conventional drying of wood discs. Mechano-sorptive creep was furthermore modelled by artificial neural network theory with five inputs, i.e., pre-steaming and drying temperatures, wood moisture content, relative humidity and distance from the pith. Results revealed that, pre-steaming partly reduced the variation of moisture content distribution along radial direction, increased restrained shrinkage strain in heartwood and decreased in sapwood and slightly decreased the mechano-sorptive creep. The neural network model provided reasonable prediction results, namely, the coefficient of determination for training, validation and test sets greater than 0.95.

The mass and heat transfer mechanisms during radio frequency/vacuum (RF/V) drying of square-edged timber were analyzed and discussed in detail. Based on the mass and heat transfer theory of porous materials, a one-dimensional mathematical model was developed from conservation equations. Compared with conventional models, it has the following advantages: (1) Each independent variable has a separate governing equation and is solved independently by converting the partial differential equation into a difference equation with the finite volume method; and (2) The calculated data from different parts of the wood specimen are displayed in the evolution curves because the specimen is divided into several units along fiber direction. Therefore, the change law of the parameters can be better described. The software Matlab, which has the advantages of fast calculation speed and high precision, was used for programming and calculations. In addition, the square-edged timber Sugi specimen was dried in a laboratory RF/V dryer, and the total average moisture content (MC) and local temperature were monitored as a function of time. By analyzing the calculated and experimental results, it can be concluded that most of the important phenomena observed during RF/V drying can be adequately described by this model.

Collapse is considered one of the most severe defects that can occur during the drying of eucalyptus, resulting in drying degradation. Liquid tension is one of the reasons for the collapse. Some transient-collapse cells can be recovered upon the disappearance of liquid tension, when moisture content is reduced during the drying process. How to control collapse and help its recovery are key factors of drying technology. This supports the introduction of a kind of sequential drying technology to the drying process. Thus, several intermittent drying procedures were used in this study. Measurements of shrinkage and collapse were made on Eucalyptus urophylla under continuous drying as well as several kinds of intermittent drying. Key factors of the intermittent drying schedule, observed for their effect on collapse recovery, were the length of the drying periods and temperature during the intermittent periods. The microstructure of collapse under different drying schedules was examined at the cellular level using scanning electron microscopy (SEM). This confirmed that intermittent drying conditions can help collapsed cells recover more thoroughly than continuous drying conditions.

The impregnation of poplar wood (Populus adenopoda Maxim) with 1,3-dimethylol-4,5-dihydroxyethyleneurea and maltodextrin and the effects of ZnCl2 and curing at 103 °C and 120 °C on the fixation rate and the leaching resistance of modified samples were investigated (103 °C curing, ZnCl2 + 103 °C curing, 120 °C curing, and ZnCl2 + 120 °C curing are denoted as 103, ZC-103, 120, and ZC-120, respectively), with the aim of improving the modification effect. The results showed that ZC-103 had the highest fixation rate, and its weight leaching ratio was higher than that of 120. Fourier-transform infrared spectroscopy showed that ZnCl2 did not affect the functional groups of the modified chemicals. The flexural strength and modulus and the compressive strength perpendicular to the grain were highest for ZC-103. In summary, ZC-103 exhibited the highest fixation rate, indicating that the hardener ZnCl2 bridged and increased the interfacial properties between the chemicals and cell walls and therefore increased the potential for macromolecule polycondensation between the chemicals and cell wall materials. This research paves the way for improving the fixation rate of impregnated wood and provides new insights into practical applications.

The drying characteristics of poplar wood (Populus adenopoda Maxim) under three treatments were investigated with the aim of improving the drying quality of the impregnated wood. Untreated materials, impregnated materials with 10% initial moisture content (MC), and impregnated materials with 20% initial MC—denoted as T1, T2, and T3, respectively—were examined during conventional drying. Relative to that of T1, the average drying rate of T2 was reduced by 46%, and that of T3 was reduced by 37%. The anti-swelling efficiency of T2 sharply increased, whereas that of T3 only slightly increased in width and thickness. The drying defects of T2 were markedly less than those of T1 and T3, attributed to the reduced residual stress and fixation of the modifier. Scanning electron microscopy indicated that large amounts of modifiers were deposited inside the cell cavity of T2, whereas small amounts of modifiers were deposited in the cell cavity of T3. The impregnation treatment generally reduced the average drying rate and MC uniformity and delayed the decrease in residual stress; however, it reduced the number of defects in the wood and considerably improved the dimensional stability of the wood. Meanwhile, impregnation treatment with increased initial MC could potentially lead to more drying defects and increase production cost.

Drying stress is the main cause for the generation of drying cracks in wood disks during drying, which limits the processing and utilization of this valuable material. For this study, white birch disks with one trunk and a thickness of 30 mm were dried under three different drying conditions: 1) a very slow drying process preventing the generation of a radial moisture content (MC) gradient, 2) a drying process with slowly increasing temperature leading to a radial MC gradient, with a higher MC in the heartwood, and 3) the same heat drying process but the wood disks were partly covered with a thin plastic film prior to the drying process leading to a reversed radial MC gradient, i.e., a higher MC in the sapwood. For each drying condition, the tangential elastic strain in the wood disks was investigated for a mean MC of 26%, 18% and 10%, respectively, as a function of the radial distance from the pith in order to predict the drying stress. Furthermore, the stress characteristics and stress reversal mechanisms in wood disks are discussed in this paper with the help of stress analysis sketches.

This paper deals with the moisture diffusion coefficient of Dahurian Larch (Larix gmelinii Rupr.) by use of the Finite Difference Method (FDM). To obtain moisture distributions the dimensional boards of Dahurian Larch were dried, from which test samples were cut and sliced evenly into 9 pieces in different drying periods, so that moisture distributions at different locations and times across the thickness of Dahurian Larch were obtained with a weighing method. With these experimental data, FDM was used to solve Fick’s one-dimensional unsteady-state diffusion equation, and the moisture diffusion coefficient across the thickness at specified time was obtained. Results indicated that the moisture diffusion coefficient decreased from the surface to the center of the Dahurian Larch wood, and it decreased with decreasing moisture content at constant wood temperature; as the wood temperature increased, the moisture diffusion coefficient increased, and the effect of the wood temperature on the moisture diffusion coefficient was more significant than that of moisture content. Moisture diffusion coefficients were different for the two experiments due to differing diffusivity of the specimens.