Bayesian Conditional Diffusion Models for Versatile Spatiotemporal Turbulence Generation

Turbulent flows have historically presented formidable challenges to predictive computational modeling. Traditional numerical simulations often require vast computational resources, making them infeasible for numerous engineering applications. As an alternative, deep learning-based surrogate models have emerged, offering data-drive solutions. However, these are typically constructed within deterministic settings, leading to shortfall in capturing the innate chaotic and stochastic behaviors of turbulent dynamics. We introduce a novel generative framework grounded in probabilistic diffusion models for versatile generation of spatiotemporal turbulence. Our method unifies both unconditional and conditional sampling strategies within a Bayesian framework, which can accommodate diverse conditioning scenarios, including those with a direct differentiable link between specified conditions and generated unsteady flow outcomes, and scenarios lacking such explicit correlations. A notable feature of our approach is the method proposed for long-span flow sequence generation, which is based on autoregressive gradient-based conditional sampling, eliminating the need for cumbersome retraining processes. We showcase the versatile turbulence generation capability of our framework through a suite of numerical experiments, including: 1) the synthesis of LES simulated instantaneous flow sequences from URANS inputs; 2) holistic generation of inhomogeneous, anisotropic wall-bounded turbulence, whether from given initial conditions, prescribed turbulence statistics, or entirely from scratch; 3) super-resolved generation of high-speed turbulent boundary layer flows from low-resolution data across a range of input resolutions. Collectively, our numerical experiments highlight the merit and transformative potential of the proposed methods, making a significant advance in the field of turbulence generation.Comment: 37 pages, 31 figure

Meta-analysis on the association between the frequency of tooth brushing and diabetes mellitus risk

BACKGROUND AND OBJECTIVE: Epidemiological studies suggested that the frequency of tooth brushing might be associated with the risk of diabetes mellitus (DM), but the results were inconsistent and no systematic review was conducted to focus on this topic. In this meta-analysis, we synthesized available observational epidemiological evidences to identify the association between tooth brushing and DM risk and investigate the potential dose-response relationship of them. METHODS: We searched PubMed and Embase from their inception through December 2017 to identify observational studies examining the association between tooth brushing and the risk of DM. Reference lists from retrieved articles were also reviewed. We quantitatively combined results of the included studies using a random-effects model. Dose-response meta-analysis was conducted to further examine the effect of tooth brushing frequency on DM risk. RESULTS: We identified 20 relevant studies (one cohort study, 14 case-control studies, and five cross-sectional studies) involving161,189 participants and 10,884 patients with DM. Compared with the highest tooth brushing frequency, the lowest level was significantly associated with an increased risk of DM (OR 1.32, 95% CI: 1.19 to 1.47), and there was no significant heterogeneity across the included studies (P = 0.119, I2 = 28.1%). Exclusion of any single study did not materially alter the combined risk estimate. The dose-response analysis indicated that the summary odds of DM for an increment of one time of tooth brushing per day was 1.20 (95% CI: 1.16-1.24). CONCLUSIONS: Integrated epidemiological evidence supports the hypothesis that low frequency of tooth brushing may be a risk factor of DM, and lower frequencies of tooth brushing were significantly associated with higher risk of DM

Reporting quality and statistical analysis of published dose-response meta-analyses was suboptimal: A cross-sectional literature survey

Objective To investigate the characteristics, methodological quality, and reporting of statistical analyses of published dose-response meta-analyses (DRMAs). Study Design and Setting We searched PubMed to identify DRMAs published in 2017. The reporting characteristics and methodological qualities were assessed by the PRISMA (27 items) and AMSTAR (11 items) respectively. We also summarized the reporting of statistical analyses of included DRMAs. Results We identified 93 DRMAs, most of which (59/93) were conducted by Chinese researchers, the main outcome was the incidence of cancers. Of the PRISMA and AMSTAR items, twenty and five were well complied (80% or more) respectively. The compliance rates of several PRISMA checklist items, such as structured summary, objectives, protocol and registration, and funding, were less than 50%. There were no criteria to estimate the doses for the open-ended intervals of exposure or intervention doses. When the restricted cubic splines were used to fit nonlinear dose-response relationships, there were also no criteria to determine the fixed knots. Conclusion The adherence to the methodological items of reporting guidelines and statistical analysis of published DRMAs were suboptimal. Development of reporting guidelines to assist authors in writing and readers in critically appraising the reports of DRMAs is timely

Prediction of Post-Discharge Bleeding in Elderly Patients with Acute Coronary Syndromes: Insights from the BleeMACS Registry

Background A poor ability of recommended risk scores for predicting in-hospital bleeding has been reported in elderly patients with acute coronary syndromes (ACS). No study assessed the prediction of post-discharge bleeding in the elderly. The new BleeMACS score (Bleeding complications in a Multicenter registry of patients discharged with diagnosis of Acute Coronary Syndrome), was designed to predict post-discharge bleeding in ACS patients. We aimed to assess the predictive ability of the BleeMACS score in elderly patients. Methods We assessed the incidence and characteristics of severe bleeding after discharge in ACS patients aged ≥ 75 years. Bleeding was defined as any intracranial bleeding or bleeding leading to hospitalization and/or red blood transfusion, occurring within the first year after discharge. We assessed the predictive ability of the BleeMACS score according to age by Fine-Gray proportional hazards regression analysis, calculating receiver-operating characteristic (ROC) curves and the area under the ROC curves (AUC). Results The BleeMACS registry included 15,401 patients of whom 3,376/15,401 (21.9%) were aged ≥ 75 years. Elderly patients were more commonly treated with clopidogrel and less often treated with ticagrelor or prasugrel. Of 3,376 elderly patients, 190 (5.6%) experienced post-discharge bleeding. The incidence of bleeding was moderately higher in elderly patients (hazard ratio [HR], 2.31, 95% confidence interval [CI], 1.92-2.77). The predictive ability of the BleeMACS score was moderately lower in elderly patients (AUC, 0.652 vs. 0.691, p = 0.001). Conclusion Elderly patients with ACS had a significantly higher incidence of post-discharge bleeding. Despite a lower predictive ability in older patients, the BleeMACS score exhibited an acceptable performance in these patients

Association of Beta-Blockers with Survival on Patients Presenting with ACS Treated with PCI: A Propensity Score Analysis from the BleeMACS Registry

Purpose: The aim was to evaluate prognostic value of beta-blocker (BB) administration in acute coronary syndromes (ACS) patients in the percutaneous coronary intervention (PCI) era. Methods and Results: The BleeMACS project is a multicenter, observational, retrospective registry enrolling patients with ACS worldwide in 15 hospitals. Patients discharged with BB therapy were compared to those discharged without a BB before and after propensity score with matching. The primary endpoint was all-cause mortality at 1 year. Secondary endpoints included in-hospital reinfarction, in-hospital heart failure, 1-year myocardial infarction, 1-year bleeding and 1-year composite of death and recurrent myocardial infarction. After matching, 2935 patients for each group were enrolled. The primary endpoint of 1-year death was significantly lower in the group on BB therapy (4.5 vs 7%, p < 0.05), while only a trend was noted for recurrent acute myocardial infarction (4.5 vs 4.9%, p = 0.54). These results were consistent for patients older than 80 years of age, for ST-elevation myocardial infarction (STEMI) patients, and for those discharged with complete versus incomplete revascularization, but not for non-STEMI/unstable angina patients. Conclusions: BB therapy was related to 1-year lower risk of all-cause mortality, independently from completeness of revascularization, admission diagnosis, age and ejection fraction. Randomized controlled trials for patients treated with PCI for ACS should be performed

Estimation of Spatial-Temporal Distribution of Grazing Intensity Based on Sheep Trajectory Data

In the arid grasslands of northern China, unreasonable grazing methods can reduce the water content and species numbers of grassland vegetation. This project uses solar-powered GPS collars to obtain track data for sheep grazing. In order to eliminate the trajectory data of the rest area and the drinking area, the kernel density analysis method was used to cluster the trajectory point data. At the same time, the vegetation index of the experimental area, including elevation, slope and aspect data, was obtained through satellite remote sensing images. Therefore, using trajectory data and remote sensing image data to establish a neural network model of grazing intensity of sheep, the accuracy of the model could be high. The results showed that the best input parameters of the model were the combination of vegetation index, sheep weight, duration, moving distance and ambient temperature, where the coefficient of determination R2=0.97, and the mean square error MSE = 0.73. The error of grazing intensity obtained by the model is the smallest, and the spatial-temporal distribution of grazing intensity can reflect the actual situation of grazing intensity in different locations. Monitoring the grazing behavior of sheep in real time and obtaining the spatial-temporal distribution of their grazing intensity can provide a basis for scientific grazing

New Approach for Vibration Suppression through Restrictors on Towering Steel Columns with Supporting Frame

Towering steel column with supporting frame is a typical equipment in chemical process engineering. Here, displacement restrictors are proposed to restrict the displacement of the towering and slender equipment while making the column to be structurally nonlinear and statically indeterminate. This study investigated on along-wind and cross-wind vibration characteristics of such equipment with the restrictors experimentally and numerically. A field test is carried out to measure the natural frequency and damping ratio of the 42.5-meter-high equipment vibrating in the wind, which is the prototype of the experimental model. A noncontact excitation system was applied on the experimental model to simulate the wind loads. The displacements and strains of the experimental model are collected under different frame types by changing the heights of displacement restrictors. The numerical simulation and experimental results showed that the height of displacement restrictors has a great influence on the vibration intensity of the equipment. An optimum location, recommended as about 40% of the height, could decrease the vibration intensity and enhance the safety of the equipment. Based on the results, a simplified formula in which the natural frequency and the damping ratio dominate the dynamic behavior of along-wind and cross-wind vibration, respectively, is derived from multi-degrees-of-freedom system. It could be furtherly utilized to predict the amplitude ratio of two structures and select a better design featuring an efficient vibration suppression performance. This work presents an important design guide to the frame-supporting towering process equipment and is of great significance to an economical and safety design

3D Printed Cascaded Cavity-Backed Millimeter-Wave Filtering Antenna

Publisher Copyright: © 2024 18th European Conference on Antennas and Propagation, EuCAP 2024. All Rights Reserved.In this manuscript, a cascaded filtering antenna structure is proposed. To realize this concept, we leverage the cavity-backed slot antenna as a foundation and take advantage of cutoff frequencies of waveguides to achieve it in the millimeter-wave (mmW) bands. The working principle and parameter analyses are introduced. Subsequently, we present the fabrication process and measurement results, which are then compared with simulation results. The obtained results demonstrate acceptable performance in terms of reflection coefficients and radiation patterns. Furthermore, by comparing our proposed antenna with published works, we highlight its advantages in terms of out-of-band rejection and similar beam width in E-plane and H-plane.Peer reviewe

Estimation of Spatial-Temporal Distribution of Grazing Intensity Based on Sheep Trajectory Data

In the arid grasslands of northern China, unreasonable grazing methods can reduce the water content and species numbers of grassland vegetation. This project uses solar-powered GPS collars to obtain track data for sheep grazing. In order to eliminate the trajectory data of the rest area and the drinking area, the kernel density analysis method was used to cluster the trajectory point data. At the same time, the vegetation index of the experimental area, including elevation, slope and aspect data, was obtained through satellite remote sensing images. Therefore, using trajectory data and remote sensing image data to establish a neural network model of grazing intensity of sheep, the accuracy of the model could be high. The results showed that the best input parameters of the model were the combination of vegetation index, sheep weight, duration, moving distance and ambient temperature, where the coefficient of determination R2=0.97, and the mean square error MSE = 0.73. The error of grazing intensity obtained by the model is the smallest, and the spatial-temporal distribution of grazing intensity can reflect the actual situation of grazing intensity in different locations. Monitoring the grazing behavior of sheep in real time and obtaining the spatial-temporal distribution of their grazing intensity can provide a basis for scientific grazing

Hydrodynamic Performance Study of a Reciprocating Plate Column Dirven by Electro-permanent Magnet Technology

The reciprocating plate column is a kind of column with the plates driven by a geared motor, and it has advantages in regard to efficiency compared to traditional columns in the extraction process, however, it comes with an increase in energy consumption. A new type of reciprocating plate column driven by electro-permanent magnet technology (EPM) is proposed in this paper to obtain a better performance with lower energy consumption. The feasibility and performance of the proposed column is studied by numerical simulation and experiments with a kerosene–water system. The electro-permanent magnet chuck could provide a maximum amplitude of 12 mm in this study. Kerosene was used as the dispersed phase, and deionized water was used as the continuous phase, in a laboratory-scale 35 mm diameter reciprocating plate column driven by EPM. Hydrodynamic performance experiments were carried out with different flowrates of both phases and reciprocating frequencies. The experimental results show that the electro-permanent magnet chuck, which serves as the driving device of the reciprocating plate column, plays the role of adding energy and increasing the droplet breakage. In addition, the energy consumption of the reciprocating plate column with traditional geared motor and electro-permanent magnet chuck is calculated respectively. Compared with the traditional geared motor, the energy saving of the electro-permanent magnet chuck is as high as 98.55%