Accurate Basis Research Articles

Spatially controllable fluid hydrogel with in-situ electrospinning PCL/chitosan fiber for treating irregular wounds

Skin injuries sustained during exercise are often irregular in shape and frequently accompanied by infections. Bacteria residing in the crevices of these wounds can lead to persistent infections. Routine wound monitoring, which requires removing the wound dressing to assess recovery, is inconvenient and increases the risk of infection. To address this, we prepared a polyvinyl alcohol/polyhydroxylated fullerenes ((PVA/PHF) hydrogel with good fluidity and photothermal antibacterial properties, which can penetrate into the crevices of irregular wounds. After the hydrogel was applied to the wound, the hydrogel was locally defined by the polycaprolactone/Chitosan (PCL/CS) membrane of in-situ electrospinning, which effectively killed bacteria, and the healing efficiency was increased by 240 % in the wound healing experiment. The PVA/PHF hydrogel exhibits excellent electrical conductivity, making it suitable for real-time monitoring of human body motion as a strain sensor. This capability provides doctors with an accurate basis for wound assessment. At the same time, the hydrogel can achieve self-healing within 1.5 s and withstand up to 2200 % tensile strain, which can be used for large-scale motion monitoring of the human body. This flowable hydrogel, capable of penetrating wound crevices, offers a dual function of both treatment and monitoring.

Development of a predictive model for assessing the risk factors associated with recurrence following surgical treatment of chronic subdural hematoma

BackgroundChronic subdural hematoma (CSDH) is a common disease in neurosurgery. Although many studies have investigated the factors affecting the recurrence of CSDH, no comprehensive prediction model has been established for the risk effect of postoperative recurrence of the disease.ObjectiveThis study aims to collect and analyze the data of CSDH patients treated in our hospital to determine the influence of preoperative, postoperative and treatment factors on the recurrence of CSDH, and to establish a corresponding prediction model to provide neurosurgeons with more accurate basis for identifying high-risk patients and guiding treatment.MethodsA total of 431 patients were collected in this study, including 323 patients who underwent traditional hematoma removal and 108 patients who underwent endoscopic hematoma removal. Relevant preoperative and postoperative data and medical history of patients were collected respectively to study the relevant factors affecting postoperative hematoma recurrence of patients, and to establish a prediction model.ResultsA total of 431 patients were enrolled in this study, 71 of whom had subdural blood recurrence. Possible relevant factors were included in univariate logistic regression, and the results showed that the preoperative GCS score, postoperative residual gas, preoperative CT hematoma thickness, coagulation function, unilateral and bilateral surgery, whether statin was taken after surgery, hematoma site, hematoma density and hematoma volume were all P < 0.2. It is a risk factor for recurrence of chronic subdural hematoma. The obtained data were further included in a multi-factor review. Six factors, including preoperative GCS score, postoperative gas residual, abnormal coagulation function, high-density hematoma, large hematoma volume, and irregular statin use after surgery, were independent risk factors for chronic subdural hematoma recurrence (P < 0.05).ConclusionThis study confirmed that six factors, including preoperative GCS score, postoperative gas residual, abnormal coagulation function, high-density hematoma, large hematoma volume, and irregular statin use, were independent risk factors for recurrence of chronic subdural hematoma. At the same time, long-term use of statins can reduce the recurrence rate of hematoma to a certain extent. In addition, the predictive model in this study could help neurosurgeons accurately identify high-risk CSDH patients.

Improved Gaussian basis sets for norm-conserving 4f-in-core pseudopotentials of trivalent lanthanides (Ln = Ce-Lu).

The first-principles quantum chemical computations often scale as Nk (N = basis sets; k = 1-4 for linear scaling, Hartree-Fock or density functional theory methods), which makes the development of accurate pseudopotentials and efficient basis sets necessary ingredients in modeling of heavy elements such as lanthanides and actinides. Recently, we have developed 4f-in-core norm-conserving pseudopotentials and associated basis sets for the trivalent lanthanides [Lu et al., J. Chem. Theory Comput. 19, 82-96 (2023)]. In the present paper, we present a unified approach to optimize high-quality Gaussian basis sets for modeling and simulations of condensed-phase systems. The newly generated basis sets not only capture the low total energy and fairly reasonable condition number of overlap matrix of lanthanide-containing systems, but also exhibit good transferability and reproducibility. These advantages ensure the accuracy of the basis sets while avoiding linear dependency concern of atom-centered basis sets. The performance of the basis sets is further illustrated in lanthanide molecular and condensed-phase systems by using Gaussian-plane wave density functional approach of CP2K. These new basis sets can be of particular interest to model structurally complicated lanthanide molecules, clusters, solutions, and solid systems.

Iterative control decoupling tuning for precision MIMO motion systems: A matrix update method

Control decoupling is the basic control step for precision MIMO (Multi-Input-Multi-Output) motion systems. After decoupling, the MIMO logical controlled plant can be diagonal dominant so that the control design for each DOF (Degree of Freedom) can be separately treated. However, due to the manufacturing tolerances and the assembling errors, the actual CoG (Center of Gravity) and actuator positions are inconsistent with the designed values. The nominal static control decoupling matrix is inaccurate, which significantly deteriorates the decoupling performance. To address the problem, this paper develops a matrix update based iterative control decoupling tuning method. Tuning with feedback control signals to achieve accurate tuning is its first distinct feature. By employing rigid-body model information to construct more accurate basis functions, fast tuning can also be achieved, especially for relatively low control bandwidth occasions. Differing from the feedforward compensation based iterative control decoupling tuning method, the matrix update method improves the dynamics of the logical controlled plant, does not increase the control complexity and is more robust to the inaccuracy of the model information. Experimental results on the short-stroke module of a precision motion stage which is the key subsystem of the lithographic projection lens testing system present significant control decoupling performance improvement (for example the peak value of the Rx-DOF servo error caused by the Z-DOF movement is reduced from 1.29 ×10−5 m to 3.19 ×10−6 m) after just two trials.

Simulation Analysis of Loss of Coolant Accidents Based on CNIFA Program

Abstract The loss of coolant accident in the primary pipeline of a reactor is a typical accident in the safety analysis of nuclear power plants, and it is one of the accidents with a high probability of occurrence. Due to the extremely complex structure of the lower space of the containment vessel, it increases the complexity of fluid flow during a loss of coolant accident. This article is based on the internal water flooding analysis simulation software CNIFA of a nuclear power plant to simulate the water flooding of a rupture in the main pipeline heat pipe section of a power plant, and to conduct a comprehensive water flooding scenario simulation for this working condition. The quantitative information collected during the simulation process, including dynamically displayed water volume, water level, and their changes over time, facilitate emergency response personnel to choose the correct response plan in advance, it can also provide more accurate basis for various specialties in design analysis.

Which Receives More Attention, Online Review Sentiment or Online Review Rating? Spillover Effect Analysis from JD.com.

Studies have found that competitive products' online review ratings (ORRs) have a spillover effect on the focal product's sales. However, the spillover effect of online review sentiment (ORS) as an essential component of online review analysis has yet to be studied. In this study, we analyze online review content from JD.com using the latent Dirichlet allocation to identify the product attribute topics that consumers are most concerned about. We then construct a baseline regression model of ORS and ORRs to explore the effects of online competitive product reviews on focal product sales. Moreover, we examine how the interaction between ORS and critical factors of online reviews affect sales. Our results indicate that the ORS of competitive products has a negative effect on focal product sales, and the effect is greater than the ORS and ORRs of focal products, respectively. In addition, the ORS of competitive products inhibits the sale of focal products as evaluations of product attributes become more positive or online review usefulness increases. We also find that the effect of ORRs of competitive products is not significant, which may be because clothing, as an experiential product, requires consumers to gain more information about specific usage scenarios before making a decision. This study provides a more accurate basis for consumer decision-making and offers retailers a novel approach to developing marketing strategies.

Extensive reference set and refined computational protocol for calculations of 57Fe Mössbauer parameters.

Mössbauer spectroscopy is a powerful technique for probing the local electronic structure of iron compounds, because it reports in an element-selective manner on both the oxidation state and coordination environment of the Fe ion. Computational prediction of the two main Mössbauer parameters, isomer shift (δ) and quadrupole splitting (ΔEQ), has long been targeted by quantum chemical studies, and useful protocols based on density functional theory have been proposed. Here we present an extensive curated reference set of Fe compounds that is considerably larger and more diverse than literature precedents. We make a distinction between low-temperature and high-temperature experimental subgroups. This set is employed for optimizing a refined computational protocol utilizing the scalar version of the exact 2-component (X2C) Hamiltonian with the finite nucleus approximation. Attention is devoted to having an accurate and flexible all-electron basis set for Fe. We assess the performance of several DFT methods that cover all representative families and rungs of functionals and find that hybrid functionals with ca. 25-30% exact exchange offer the best accuracy for isomer shifts. The work establishes a refined general protocol of wide applicability that achieves good performance for the prediction of isomer shifts in a wider variety of systems than before, but the limitations of DFT for quadrupole splittings are also highlighted. Finally, comparison of calculated values with high-temperature experimental results shows that the use of an empirical correction factor is required to account for the second-order Doppler shift and to achieve the same quality of correlation as with the low-temperature data.

Spatial–temporal variation and correlation analysis of ecosystem service values and ecological risks in winter city Shenyang, China

Ecosystems in winter cities are complex and fragile, experiencing significant changes due to climate variations and human construction activities. Previous studies on the assessment of overall ecosystem service value (ESV) and ecological risk index (ERI) in winter cities are scarce. In this study, we constructed ESV and ERI measurement models using land use data in 2000, 2010, and 2020 using the improved value per unit area factor method and the landscape pattern index method, respectively, to reveal their spatial and temporal change characteristics. Geographic detectors were used to explore the driving roles of natural and artificial factors on the changes of ESV and ERI. The combination in ESV and ERI can then provide a more quantitative and accurate basis for policy decisions, identify priority areas for urban ecological restoration, and reduce the risk to ecosystems. The results of the study show that the total ESV of Shenyang city decreased from 273.97 × 108 CNY to 270.38 × 108 CNY during 2000–2020. Although the decrease is not large, the ESV changes structurally with the advancement of urbanization. During the 20 years, the construction land with the lowest ecological service function continues to expand, increasing by 354 km2, the grassland decreased by 215.9 km2, and the arable land decreased by 196.6 km2. The ecological service function of the water area is the strongest, with an increase of 51.3 km2 in the water area, ensuring that there is no significant decline in ESV. The size of the ERI is Very high, High, and Medium value zones remained relatively stable, while the size of the Very Low-value zone decreased by 12.78% and the size of the Low-value zone increased by 13.21%. The interaction factors that contributed most to the changes in ESV and ERI were annual evapotranspiration (EVP)/ Normalized Difference Vegetation Index (NDVI) and Annual sunshine hours (SSD)/ Digital Elevation Model (DEM) , respectively. There was a spatial correlation between ESV and ERI. The areas with the highest ESV supply capacity and at the same time facing severe ecological risks to the landscape pattern are distributed in the northeastern hilly lands. This area should be prioritized to develop planning and control measures to prevent further erosion of forest lands and grasslands and reduce ecological risks. These results provide a theoretical basis for ensuring ecological security and sustainable development in winter cities.

Study on the influence of wood ray morphological characteristics on the tensile strength of wood parallel to grain

The tensile strength of wood parallel to grain is one of the important indicators of wood physical and mechanical properties. Cross-sectional shape possesses a significant effect on the tensile strength parallel to grain, especially for broad-leaved trees with broad wood rays. However the influence of the structural feature of wood rays on the test results, which was commonly ignored. The article focuses on the beech tree with two types of wood rays: broad and narrow, poplar wood with extremely fine wood rays, and dilleniad with extremely rich wood rays. The relationship between the inclination angle and fracture mode of wood rays and the microstructure of wood rays is studied, in order to provide a more accurate scientific basis for determining the tensile strength of wood parallel to grain. The results showed that the inclination angle between the wood ray and the tensile direction has a significant impact on the fracture mode and tensile strength, and the tensile strength parallel to grain without inclination angle is greater than that with inclination angle. Different types of wood rays have a effect on the coefficient of variation of the tensile strength parallel to grain of the specimen. Under the same inclination angle, the Pearson correlation between the wood ray parenchyma ratio and the tensile strength parallel to grain is significantly negative at the 0.01 level (double tailed) or 0.05 level (double tailed). Besides, as the wood ray parenchyma ratio gradually increases, the overall tensile strength of wood parallel to grain shows a downward trend. The fracture surface morphology characteristics of specimens with different fracture modes are different.

The Role of Estrogen across Multiple Disease Mechanisms.

Estrogen is a significant hormone that is involved in a multitude of physiological and pathological processes. In addition to its pivotal role in the reproductive system, estrogen is also implicated in the pathogenesis of a multitude of diseases. Nevertheless, previous research on the role of estrogen in a multitude of diseases, including Alzheimer's disease, depression, cardiovascular disease, diabetes, osteoporosis, gastrointestinal diseases, and estrogen-dependent cancers, has concentrated on a single disease area, resulting in a lack of comprehensive understanding of cross-disease mechanisms. This has brought some challenges to the current treatment methods for these diseases, because estrogen as a potential therapeutic tool has not yet fully developed its potential. Therefore, this review aims to comprehensively explore the mechanism of estrogen in these seven types of diseases. The objective of this study is to describe the relationship between each disease and estrogen, including the ways in which estrogen participates in regulating disease mechanisms, and to outline the efficacy of estrogen in treating these diseases in clinical practice. By studying the role of estrogen in a variety of disease mechanisms, it is hoped that a more accurate theoretical basis and clinical guidance for future treatment strategies will be provided, thus promoting the effective management and treatment of these diseases.

A Visual Representation for Accurate Local Basis Set Construction and Optimization: A Case Study of SrTiO3 with Hybrid DFT Functionals

The linear combination of atomic orbitals (LCAO) method is advantageous for calculating important bulk and surface properties of crystals and defects in/on them. Compared to plane wave calculations and contrary to common assumptions, hybrid density functional theory (DFT) functionals are actually less costly and easier to implement in LCAO codes. However, choosing the proper basis set (BS) for the LCAO calculations representing Guassian-type functions is crucial, as the results depend heavily on its quality. In this study, we introduce a new basis set (BS) visual representation, which helps us (1) analyze the collective behavior of individual atoms’ shell exponents (s, p, and d), (2) better compare different BSs, (3) identify atom-type invariant relationships, and (4) suggest a robust method for building a local all-electron BS (denoted as BS1) from scratch for each atom type. To compare our BS1 with the others existing in the literature, we calculate the basic bulk properties of SrTiO3 (STO) in cubic and tetragonal phases using several hybrid DFT functionals (B3LYP, PBE0, and HSE06). After adjusting the exact Hartree–Fock (HF) exchange of PBEx, HSEx, and the state-of-the-art meta-GGA hybrid r2SCANx functionals, we find the r2SCAN15 and HSE27 for BS1, with the amount of exact HF exchange of 0.15 and 0.27, respectively, perform equally well for reproducing several most relevant STO properties. The proposed robust BS construction scheme has the advantage that all parameters of the obtained BS can be reoptimized for each new material, thus increasing the quality of DFT calculation predictions.

Collision-Free Trajectory Planning Optimization Algorithms for Two-Arm Cascade Combination System

As a kind of space robot, the two-arm cascade combination system (TACCS) has been applied to perform auxiliary operations at different locations outside space cabins. The motion coupling relation of two arms and complex surrounding obstacles make the collision-free trajectory planning optimization of TACCS more difficult, which has become an urgent problem to be solved. For the above problem, this paper proposed collision-free and time–energy–minimum trajectory planning optimization algorithms, considering the motion coupling of two arms. In this method, the screw-based inverse kinematics (IK) model of TACCS is established to provide the basis for the motion planning in joint space by decoupling the whole IK problem into two IK sub-problems of two arms; the minimum distance calculation model is established based on the hybrid geometric enveloping way and basic distance functions, which can provide the efficient and accurate data basis for the obstacle-avoidance constraint condition of the trajectory optimization. Moreover, the single and bi-layer optimization algorithms are presented by taking motion time and energy consumption as objectives and considering obstacle-avoidance and kinematics constraints. Finally, through example cases, the results indicate that the bi-layer optimization has higher convergence efficiency under the premise of ensuring the optimization effect by separating variables and constraint terms. This work can provide theoretical and methodological support for the efficient and intelligent applications of TACCS in the space arena.

DILA: Dynamic Gaussian Distribution Fitting and Imitation Learning-Based Label Assignment for tiny object detection

With the rapid advancement of deep learning technology, significant achievements have been made in the field of general object detection. However, challenges still remain in the detection of tiny objects. There are two main drawbacks: (1) static prior information makes the localization of tiny objects relatively fixed; (2) Intersection over Union (IoU) is highly sensitive to deviations in tiny objects. To this end, we propose a Dynamic Gaussian Distribution Fitting and Imitation Learning-Based Label Assignment (DILA) strategy for Tiny Object Detection. Specifically, to address the positional deviation of effective receptive fields at different network layers during Gaussian modeling, DILA first designs an Adaptive Dynamic Calculation Strategy (ADCS) to compute estimation factors for the effective receptive field in different feature spaces, dynamically modeling prior information using Gaussian distribution. Then, DILA introduces a new Balance of Gaussian Scaling-aware Metric (BGSM) to measure the similarity between tiny bounding boxes and predefined anchors, instead of using IoU, which is highly sensitive to tiny pixel shifts, for sample assignment, thereby providing a more accurate basis for label assignment. Finally, a Detail Information Imitation Compensation Module (DIM) is presented to improve and compensate for the detailed information of tiny objects that troubles label assignment, achieving balanced learning for tiny objects. The proposed DILA strategy can be seamlessly integrated into various anchor-based detectors. Extensive experiments were conducted on three publicly available datasets for tiny object detection. The results indicate that when DILA is embedded into Faster RCNN, it outperforms other state-of-the-art methods in terms of detection performance for tiny objects, achieving an improvement in average precision of 10.3%, 1.5%, and 4.2% on AI-TOD, SODA-D, and VisDrone2019, respectively. The source codes and results are available at: https://github.com/chnu-cpl/DILA.

The Value of Ultrasound in the Application of Water Enema in Intussusception

Objective: To introduce high-frequency ultrasound diagnostic technology to cooperate with diagnosis and treatment for patients with intussusception, and to observe its clinical application effect. Methods: The study took patients with intussusception as the object of observation, with a total of 52 cases participating, all of which were clinically admitted from December 2022 to December 2023. After enrollment, the patients underwent high-frequency ultrasound detection in sequence, recording the ultrasound imaging characteristics, and referring to the results of surgical or leaky saline enema reset to confirm the diagnosis (the gold standard) to assess the diagnostic efficacy of high-frequency ultrasound technology. Results: Comparing the confirmed diagnostic results of surgery or leaking saline enema restoration, the detection rate of high-frequency ultrasound technology was 98.07% (P > 0.05). Among the 52 patients treated with hydropneumatic enema restoration with the cooperation of high-frequency ultrasound monitoring, 39 patients were successfully reset in the first treatment (75.00%), while 9 patients were successfully reset (17.30%) after multiple treatments (≥ 2 times); the remaining 4 patients were unsuccessful and then converted to surgical treatment, and all of them were successfully treated and cured. Conclusion: For the diagnosis of intussusception, high-frequency color Doppler ultrasound has the advantages of high accuracy and simple operation, which provides a scientific and accurate reference basis for the clinical diagnosis and treatment of patients.

Establishing a 4D-CT lung function related volumetric dose model to reduce radiation pneumonia

In order to study how to use pulmonary functional imaging obtained through 4D-CT fusion for radiotherapy planning, and transform traditional dose volume parameters into functional dose volume parameters, a functional dose volume parameter model that may reduce level 2 and above radiation pneumonia was obtained. 41 pulmonary tumor patients who underwent 4D-CT in our department from 2020 to 2023 were included. MIM Software (MIM 7.0.7; MIM Software Inc., Cleveland, OH, USA) was used to register adjacent phase CT images in the 4D-CT series. The three-dimensional displacement vector of CT pixels was obtained when changing from one respiratory state to another respiratory state, and this three-dimensional vector was quantitatively analyzed. Thus, a color schematic diagram reflecting the degree of changes in lung CT pixels during the breathing process, namely the distribution of ventilation function strength, is obtained. Finally, this diagram is fused with the localization CT image. Select areas with Jacobi > 1.2 as high lung function areas and outline them as fLung. Import the patient's DVH image again, fuse the lung ventilation image with the localization CT image, and obtain the volume of fLung different doses (V60, V55, V50, V45, V40, V35, V30, V25, V20, V15, V10, V5). Analyze the functional dose volume parameters related to the risk of level 2 and above radiation pneumonia using R language and create a predictive model. By using stepwise regression and optimal subset method to screen for independent variables V35, V30, V25, V20, V15, and V10, the prediction formula was obtained as follows: Risk = 0.23656–0.13784 * V35 + 0.37445 * V30-0.38317 * V25 + 0.21341 * V20-0.10209 * V15 + 0.03815 * V10. These six independent variables were analyzed using a column chart, and a calibration curve was drawn using the calibrate function. It was found that the Bias corrected line and the Apparent line were very close to the Ideal line, The consistency between the predicted value and the actual value is very good. By using the ROC function to plot the ROC curve and calculating the area under the curve: 0.8475, 95% CI 0.7237–0.9713, it can also be determined that the accuracy of the model is very high. In addition, we also used Lasso method and random forest method to filter out independent variables with different results, but the calibration curve drawn by the calibration function confirmed poor prediction performance. The function dose volume parameters V35, V30, V25, V20, V15, and V10 obtained through 4D-CT are key factors affecting radiation pneumonia. Establishing a predictive model can provide more accurate lung restriction basis for clinical radiotherapy planning.

Exploring the Relationship Between Atorvastatin and Memory Loss: A Comprehensive Analysis Integrating Real-World Pharmacovigilance and Mendelian Randomization.

Atorvastatin is a drug widely used to prevent cardiovascular and cerebrovascular diseases. Current observational studies suggest that atorvastatin may be associated with cognitive dysfunction (especially memory loss). However, some studies have suggested that dyslipidemia may be an important factor in cognitive dysfunction. The purpose of this study was to perform a pharmacovigilance analysis using real-world data from the US Food and Drug Administration's Adverse Event Reporting System (FAERS) to assess whether memory loss is an adverse effect of atorvastatin and to further clarify its causality through Mendelian randomization (MR). We extracted real-world data from the FAERS database (Quarter 1 2004 to Quarter 1 2023). Disproportionality analysis methods and measures of association such as the reporting odds ratio (OR), proportional reporting ratio, Bayesian confidence interval progressive neural network, and polynomial Gamma Poisson distribution reduction were used to assess whether memory loss was an adverse effect of atorvastatin. In addition, we used MR to evaluate causality in depth. In the pharmacovigilance analysis of atorvastatin, we extracted four datasets of clinical symptoms associated with memory loss from the FAERS database [Amnesia (n = 1196), Memory impairment (n = 840), Transient global amnesia (n = 38), and Retrograde amnesia (n = 9)]. The reporting OR, proportional reporting ratio, Bayesian confidence interval progressive neural network, and Gamma Poisson distribution reduction all showed positive results for amnesia, transient global amnesia, and retrograde amnesia, while the reporting OR and Bayesian confidence interval progressive neural network also showed positive results for memory disorders. Thus, memory loss was a frequent side effect of atorvastatin. The MR analyses were used to further evaluate the association between statins and memory loss. The results of the MR analysis (statins and memory loss) are as follows: Ivw (mre) (β = 0.11 [OR = 1.11], P = 0.01 < 0.05) and the OR and β directions of MR-Egger and weighted mode were the same. The results of the MR analysis (statins and mitochondrial DNA copy number) are as follows: Ivw(mre) (β = -0.03 [OR = 0.96], P < 0.01) and the OR and β direction of MR-Egger and weighted mode are the same. The results of the MR analysis (DNA copy number and memory loss) are as follows: Ivw(β = - 0.06 [OR = 0.94], P = 0.04 < 0.05) and the OR and β direction of MR-Egger and weighted mode were the same. The pleiotropy test did not find horizontal diversity in our results. This study suggests that memory loss is a notable adverse event associated with atorvastatin and provides evidence indicating a potential causal relationship between atorvastatin and memory loss. We also found that statins may further affect memory by affecting mitochondrial function. Therefore, in the clinical use of atorvastatin, it is important to carefully monitor the changes in cognitive function of patients. Second, a pharmacovigilance analysis combined with MR was used in this study to provide a new approach for the study of adverse drug reactions. This comprehensive analysis method helps to evaluate the safety of drugs and the risk of adverse reactions more comprehensively and provides doctors with a more accurate clinical decision-making basis.

Age-related morphological change in bony segment and cartilage segment of Eustachian tube.

Eustachian tube dysfunction (ETD) is the predominant cause of otitis media with effusion in children and adults. Balloon dilatation of the Eustachian tube (BDET) provides a new method for restoring the ventilatory function of Eustachian tube (ET). However, the differences in age-related morphological changes in the dimensions and positions of ET in children and adults are unclear. This study aimed to examine age-related morphological changes in bony and cartilage segments of the ET in a three-dimensional space in normal population. A total of 71 randomly selected computed tomography (CT) images of the temporal bones of 46 people were retrospectively studied in four age groups: A (0-3 years old); B (4-8 years old), C (9-18 years old), and D (19-65 years old). Space analytic geometry was assessed to calculate the dimensions and positions of ET. The bony segment of ET lengthened from infancy to adulthood with age in groups A, B and C (r = 0.562**/0.000). The cartilage segment of ET mostly extended with age from infancy to 8 years old in children (r = 0.633**/0.000), but with bending close to the sagittal plane and away from the horizontal plane with age in groups A, B and C (P < .05), and with a constant angle to the coronal plane among the four groups (P > .05). The bony and cartilaginous segments of ET exhibit distinct morphological changes in space with age. The bony segment of ET extends in a constant position from infancy to adulthood. In contrast, the cartilaginous segment of the ET indicates multidimensional positional changes until adulthood, in addition to the elongation from infancy to children. This may provide an accurate morphological basis for comparing the differences in ETD pathogenesis and surgical treatment between children and adults.

Assessment of cognitive dysfunction and its influencing factors after acute ischemic stroke

Objective In order to provide a more accurate and effective basis for clinical diagnosis and treatment, patients with cognitive dysfunction after acute ischemic stroke (AIS) were evaluated and their influencing factors were analyzed. Methods A rigorous and systematic logistic regression analysis was conducted to comprehensively investigate the various influencing factors that contribute to cognitive dysfunction. Results Among them, the sex granulocyte/lymphocyte ratio (NLR), low-density lipoprotein cholesterol (LDL-C) level, and C-reactive protein (CRP) were also higher than those in the control group (p < 0.05). The scores of memory, orientation, visual and spatial function, abstract thinking and language in the control group were higher than those in the experimental group (p < 0.05). The results of multivariate logistic regression analysis showed that history of diabetes mellitus, high NLR, high LDL-C, high CRP, smoking and temporal lobe infarction were risk factors for cognitive dysfunction after AIS, while elevated BMI and love of exercise were protective factors for cognitive dysfunction after AIS. Conclusion Patients with cognitive dysfunction had the highest incidence of temporal lobe infarction, and they scored lower than the control group on memory, orientation, visual and spatial function, abstract thinking, and language function. Multivariate logistic regression analysis showed that a history of diabetes mellitus, high NLR, high LDL-C, high CRP, smoking, and temporal lobe infarction were independent risk factors for cognitive dysfunction after acute ischemic stroke, while elevated BMI and a love of exercise were protective factors for cognitive dysfunction after acute ischemic stroke.

Study on time range of definite integral in derivation process of chloride ion diffusion theoretical model of concrete

In the study of the durability of concrete structures, the chloride ion diffusion coefficient (Dt) is a key parameter that directly affects the prediction of concrete's service life. This study aims to explore the relationship between the chloride ion diffusion coefficient in concrete and the "curing age (tref)" and "exposure time (t)." By conducting long-term curing and seawater exposure experiments on three different mixes of high-performance concrete samples, we collected experimental data with a curing age of 3 years and a seawater exposure time of 4.5 years. Through in-depth analysis of these data, we found that there is a significant power function relationship between the chloride ion diffusion coefficient and exposure time, while the relationship with curing age is not significant. This finding suggests that in the derivation of the concrete chloride ion diffusion theory model, the time range of the definite integral of Dt should be from 0 to t, rather than from tref to tref+t. Furthermore, we have validated the concrete life prediction model using actual data from the Swedish Marine Exposure Station, further confirming the accuracy and reliability of our research results. This study provides a more scientific and accurate theoretical basis for the durability assessment and service life prediction of concrete structures.

Study on the thermal behaviour of spontaneous combustion of open-pit minerals

To study thermal behaviour during spontaneous combustion of an open-pit coal mine, mixed slag (coal, oil shale, and coal gangue) was taken as the research object. Laser thermal conductivity analyser and differential scanning calorimetry were used to test thermophysical parameters and heat release characteristics of the minerals. The parameters can be employed to calculate the apparent activation energy using the Arrhenius equation and evaluate the thermal behaviour of open-pit mixed slag. The results indicate that thermophysical parameters have stage characteristics. Thermal diffusivity and thermal conductivity of minerals, especially mixed slag, have a strong correlation with temperature. Heat flow of minerals exhibits five characteristic stages, and heat flow of the samples is consistent with the change in heating rate. During the heating process, thermal diffusivity and heat flow of the mixed slag are between those of a single mineral. Except for the mixed slag at 15 and 20 °C/min, the initial exothermic temperature of the other samples is mainly concentrated at 50–80 °C. Thermal energy release of the sample is mainly concentrated in the accelerated exothermic stage and rapid exothermic stage. Thermal energy release of mixed slag in rapid exothermic stage is always greater than that in accelerated exothermic stage, and the proportion of thermal energy release in these two stages exceeds 98 %. The apparent activation energy during the accelerated exothermic stage is lower, making it easier to release heat, and rapid exothermic stage is relatively high, which can readily lead to heat accumulation. Thermal analysis reveals that the thermal behaviour of mixed slag is significantly different from that of a single mineral. Its unique exothermic characteristics can provide a more accurate theoretical basis for the prevention and control of environmental pollution caused by slag spontaneous combustion.