Indoor Particulate Matter Transfer in CNC Machining Workshop and The Influence of Ventilation Strategies—A Case Study

Particulate matter in Computer Numerical Control (CNC) machining workshop is harmful to workers’ health. This paper studies particulate matter transfer and the performance of various ventilation strategies in a CNC machining workshop. To obtain the boundary condition of the particle field, instruments were installed to obtain the particle size attenuation characteristics and source strength, respectively. The results show that the 99% cumulative mass concentration of particles is distributed within 1.5 μm, and the release rate of particles from the full enclosure. Next, the indoor flow field and particle field were simulated by numerical simulation with the measured boundary conditions. The working area’s age of air, particle concentration, and ventilation efficiency were compared between four displacement ventilation methods and one mixed ventilation method. The results show that the working area’s mean particle concentration and ventilation efficiency under longitudinal displacement ventilation is better than other methods. At the same time, the mean age of air is slightly worse. In addition, mixed ventilation can obtain lower mean age of air, but the particle concentration is higher in the working area. The bilateral longitudinal ventilation can be improved by placing axial circulation fans with vertical upward outlets in the center of the workshop

EEG-based emotion classification using a deep neural network and sparse autoencoder

Emotion classification based on brain–computer interface (BCI) systems is an appealing research topic. Recently, deep learning has been employed for the emotion classifications of BCI systems and compared to traditional classification methods improved results have been obtained. In this paper, a novel deep neural network is proposed for emotion classification using EEG systems, which combines the Convolutional Neural Network (CNN), Sparse Autoencoder (SAE), and Deep Neural Network (DNN) together. In the proposed network, the features extracted by the CNN are first sent to SAE for encoding and decoding. Then the data with reduced redundancy are used as the input features of a DNN for classification task. The public datasets of DEAP and SEED are used for testing. Experimental results show that the proposed network is more effective than conventional CNN methods on the emotion recognitions. For the DEAP dataset, the highest recognition accuracies of 89.49% and 92.86% are achieved for valence and arousal, respectively. For the SEED dataset, however, the best recognition accuracy reaches 96.77%. By combining the CNN, SAE, and DNN and training them separately, the proposed network is shown as an efficient method with a faster convergence than the conventional CNN

Association between Helicobacter pylori infection and serum uric acid levels in a Chinese community population: a cross-sectional study stratified by renal function

BackgroundThe relationship between Helicobacter pylori (H. pylori) infection and serum uric acid levels remains debated. This study investigates the association between H. pylori infection and serum uric acid levels in a Chinese community, exploring renal function as a potential modifier.MethodsWe conducted a cross-sectional study involving 8,439 adults who underwent health examinations at a hospital in Wuhan from January 2022 to January 2024. H. pylori infection was assessed via the 14C-urea breath test, and serum uric acid levels were measured by the uricase method. Multivariable linear regression models evaluated the associations, and interaction analysis identified potential effect modifiers. Subgroup analyses were stratified by estimated glomerular filtration rate (eGFR).ResultsThe prevalence of H. pylori infection was 21.5% (1,816/8,439). Initial analysis showed higher serum uric acid levels in individuals with H. pylori infection compared to those without (403.76 ± 102.89 vs. 395.87 ± 102.13 μmol/L, p = 0.004). However, after adjusting for age, sex, body mass index, lipid profiles, and hepatorenal function, this association was no longer significant in the overall cohort (β = 1.92, 95% CI: −2.38 to 6.23, p = 0.381). Interaction analysis revealed a significant modification by eGFR (p for interaction = 0.007). Stratified analysis showed an inverse association between H. pylori infection and serum uric acid in individuals with mild renal impairment (eGFR 60–80 mL/min/1.73m2, n = 824; adjusted β = −17.86, 95% CI: −31.28 to −4.44, p = 0.009), while no such association was observed in those with normal renal function (eGFR ≥80 mL/min/1.73m2, n = 7,531; β = 3.92, 95% CI: −0.66 to 8.50, p = 0.094). Sensitivity analyses confirmed the robustness of these findings.ConclusionRenal function modulates the association between H. pylori infection and serum uric acid levels, with an inverse correlation observed in individuals with mild renal impairment. These findings suggest that renal function may influence the impact of H. pylori infection on uric acid metabolism

Antifibrinolytic Role of a Bee Venom Serine Protease Inhibitor That Acts as a Plasmin Inhibitor

Bee venom is a rich source of pharmacologically active substances. In this study, we identified a bumblebee (Bombus ignitus) venom Kunitz-type serine protease inhibitor (Bi-KTI) that acts as a plasmin inhibitor. Bi-KTI showed no detectable inhibitory effect on factor Xa, thrombin, or tissue plasminogen activator. In contrast, Bi-KTI strongly inhibited plasmin, indicating that it acts as an antifibrinolytic agent; however, this inhibitory ability was two-fold weaker than that of aprotinin. The fibrin(ogen)olytic activities of B. ignitus venom serine protease (Bi-VSP) and plasmin in the presence of Bi-KTI indicate that Bi-KTI targets plasmin more specifically than Bi-VSP. These findings demonstrate a novel mechanism by which bumblebee venom affects the hemostatic system through the antifibrinolytic activity of Bi-KTI and through Bi-VSP-mediated fibrin(ogen)olytic activities, raising interest in Bi-KTI and Bi-VSP as potential clinical agents

Ship-scale CFD benchmark study of a pre-swirl duct on KVLCC2

Installing an energy saving device such as a pre-swirl duct (PSD) is a major investment for a ship owner and prior to an order a reliable prediction of the energy savings is required. Currently there is no standard for how such a prediction is to be carried out, possible alternatives are both model-scale tests in towing tanks with associated scaling procedures, as well as methods based on computational fluid dynamics (CFD). This paper summarizes a CFD benchmark study comparing industrial state-of-the-art ship-scale CFD predictions of the power reduction through installation of a PSD, where the objective was to both obtain an indication on the reliability in this kind of prediction and to gain insight into how the computational procedure affects the results. It is a blind study, the KVLCC2, which the PSD is mounted on, has never been built and hence there is no ship-scale data available. The 10 participants conducted in total 22 different predictions of the power reduction with respect to a baseline case without PSD. The predicted power reductions are both positive and negative, on average 0.4%, with a standard deviation of 1.6%-units, when not considering two predictions based on model-scale CFD and two outliers associated with large uncertainties in the results. Among the variations present in computational procedure, two were found to significantly influence the predictions. First, a geometrically resolved propeller model applying sliding mesh interfaces is in average predicting a higher power reduction with the PSD compared to simplified propeller models. The second factor with notable influence on the power reduction prediction is the wake field prediction, which, besides numerical configuration, is affected by how hull roughness is considered

Calculation and analysis of electromagnetic-temperature-stress coupling of the stator core of synchronous generator

In order to analyze the loss, temperature rise and the mechanical structural response under the combined magnetic tension and thermal stress of the stator core, the electromagnetic-temperature-stress coupling calculation for the stator core of a synchronous generator is carried out in this paper. Firstly, the core loss and the magnetic pull per unit area are theoretically deduced, followed by an analysis of the core's temperature rise characteristics. On this basis, the mechanical structure response of the core under the coupling excitation of magnetic pull and non-uniform thermal load is obtained. Then, a three-dimensional finite element model of the CS-5 synchronous generator is established. This model calculates the magnetic pull per unit area, loss curve and temperature distribution of the stator core. Furthermore, the deformation, strain and stress of the stator core under the simultaneous action of magnetic tension and thermal load are obtained. The results show that the stator slot temperature is highest when the generator runs stably. The deformation at the groove is largest and the stress at the bottom of the groove is higher. Finally, the temperature rises of the end face, inside slot and outside circle of the stator core are monitored in real-time by thermocouples and a temperature monitor. The measured temperature distribution of the stator core is in good agreement with the finite element simulation results, verifying the effectiveness of the electromagnetic-temperature-stress coupling method. In this paper, the temperature distribution of the stator core and the mechanical structural response distribution of the stator core under magnetic and thermal coupling excitation are obtained, providing a technical reference for the reverse optimization design of the generator structure and the prevention of stator core deformation

In—Line Measurement Of High Temperature Dielectric Constant In The Process Of Sintering

AbstractIn this paper, a resonant cavity method is developed and some experimental results for measuring dielectric constants of ceramic samples (e. g. Al2O3) under different sintering temperatures are reported. The experiments show that this method has higher precision and good prospects of in—line monitoring the high temperature dielectric constant in the process of raising the temperature of the samples. These results provide some scientific experimental basis for physical research of ceramic materials.</jats:p