The noise control of minicar body in white based on acoustic panel participation method

It is very important to predict the acoustic radiation of vehicle body for the control of interior noise. Firstly, the kinetic equations of coupled acoustic-structural finite element method are explained and the numerical analytical methods of noise transfer function and acoustic panel participation are further obtained. Then the coupled acoustic-structural finite element model of body in white and passenger compartment cavity of a minicar is established and verified by modal test. The passive side of engine mounting points are chosen as the excitation points, and driver’s right ear is the output point of sound pressure response. The noise transfer function is calculated and the critical frequency of vehicle interior noise is obtained. The acoustic panel participation analysis of vehicle roof and floor are conducted, and the key acoustic panels are identified. In order to reduce the noise of critical frequency, the measures, pasting damping material and welding beam, are adopted. The results indicate that, compared with the results of structure improvement of modal method, the vehicle interior noise is controlled more effectively by using the acoustic panel participation analytical method

Taming Gradient Variance in Federated Learning with Networked Control Variates

Federated learning, a decentralized approach to machine learning, faces significant challenges such as extensive communication overheads, slow convergence, and unstable improvements. These challenges primarily stem from the gradient variance due to heterogeneous client data distributions. To address this, we introduce a novel Networked Control Variates (FedNCV) framework for Federated Learning. We adopt the REINFORCE Leave-One-Out (RLOO) as a fundamental control variate unit in the FedNCV framework, implemented at both client and server levels. At the client level, the RLOO control variate is employed to optimize local gradient updates, mitigating the variance introduced by data samples. Once relayed to the server, the RLOO-based estimator further provides an unbiased and low-variance aggregated gradient, leading to robust global updates. This dual-side application is formalized as a linear combination of composite control variates. We provide a mathematical expression capturing this integration of double control variates within FedNCV and present three theoretical results with corresponding proofs. This unique dual structure equips FedNCV to address data heterogeneity and scalability issues, thus potentially paving the way for large-scale applications. Moreover, we tested FedNCV on six diverse datasets under a Dirichlet distribution with {\alpha} = 0.1, and benchmarked its performance against six SOTA methods, demonstrating its superiority.Comment: 14 page

HYBRID FINITE-DISCRETE ELEMENT MODELLING OF BLAST-INDUCED EXCAVATION DAMAGED ZONE IN THE TOP-HEADING OF DEEP TUNNELS

A hybrid finite-discrete element method (FEM/DEM) is introduced to model the excavation damage zone induced by blast in a deep tunnel. The key components of the hybrid finite-discrete element method, i.e. transition from continuum to discontinuum through fracture and fragmentation, and detonation-induced gas expansion and flow through fracturing rock, are introduced in detail. The stress and crack initiation and propagation of an uniaxial compression test is then modelled by the proposed method and compared with those well documented in literature to calibrate the hybrid FEM/DEM. The modelled stress-loading displacement curve presents a typical failure process of brittle materials. The calibrated method is then used to model the stress and crack initiation and propagation induced by blast for the last step of excavation in a deep tunnel. A separation contour, which connects the borehole through the radial cracks from each borehole, is observed during the excavation process. The newly formed tunnel wall is produced and the main components of excavation damage zone (EDZ) are obtained. Therefore, the proposed treatment has the capabilities of modelling blast-induced EDZ and rock failure process. It is concluded that the hybrid FEM/DEM is a valuable numerical tool for studying excavation damage zone in terms of crack initiation and propagation and stress distribution

Integration of natural and deep artificial cognitive models in medical images: BERT-based NER and relation extraction for electronic medical records

IntroductionMedical images and signals are important data sources in the medical field, and they contain key information such as patients' physiology, pathology, and genetics. However, due to the complexity and diversity of medical images and signals, resulting in difficulties in medical knowledge acquisition and decision support.MethodsIn order to solve this problem, this paper proposes an end-to-end framework based on BERT for NER and RE tasks in electronic medical records. Our framework first integrates NER and RE tasks into a unified model, adopting an end-to-end processing manner, which removes the limitation and error propagation of multiple independent steps in traditional methods. Second, by pre-training and fine-tuning the BERT model on large-scale electronic medical record data, we enable the model to obtain rich semantic representation capabilities that adapt to the needs of medical fields and tasks. Finally, through multi-task learning, we enable the model to make full use of the correlation and complementarity between NER and RE tasks, and improve the generalization ability and effect of the model on different data sets.Results and discussionWe conduct experimental evaluation on four electronic medical record datasets, and the model significantly out performs other methods on different datasets in the NER task. In the RE task, the EMLB model also achieved advantages on different data sets, especially in the multi-task learning mode, its performance has been significantly improved, and the ETE and MTL modules performed well in terms of comprehensive precision and recall. Our research provides an innovative solution for medical image and signal data

The noise control of minicar body in white based on acoustic panel participation method

It is very important to predict the acoustic radiation of vehicle body for the control of interior noise. Firstly, the kinetic equations of coupled acoustic-structural finite element method are explained and the numerical analytical methods of noise transfer function and acoustic panel participation are further obtained. Then the coupled acoustic-structural finite element model of body in white and passenger compartment cavity of a minicar is established and verified by modal test. The passive side of engine mounting points are chosen as the excitation points, and driver’s right ear is the output point of sound pressure response. The noise transfer function is calculated and the critical frequency of vehicle interior noise is obtained. The acoustic panel participation analysis of vehicle roof and floor are conducted, and the key acoustic panels are identified. In order to reduce the noise of critical frequency, the measures, pasting damping material and welding beam, are adopted. The results indicate that, compared with the results of structure improvement of modal method, the vehicle interior noise is controlled more effectively by using the acoustic panel participation analytical method

The noise control of minicar body in white based on acoustic panel participation method

It is very important to predict the acoustic radiation of vehicle body for the control of interior noise. Firstly, the kinetic equations of coupled acoustic-structural finite element method are explained and the numerical analytical methods of noise transfer function and acoustic panel participation are further obtained. Then the coupled acoustic-structural finite element model of body in white and passenger compartment cavity of a minicar is established and verified by modal test. The passive side of engine mounting points are chosen as the excitation points, and driver’s right ear is the output point of sound pressure response. The noise transfer function is calculated and the critical frequency of vehicle interior noise is obtained. The acoustic panel participation analysis of vehicle roof and floor are conducted, and the key acoustic panels are identified. In order to reduce the noise of critical frequency, the measures, pasting damping material and welding beam, are adopted. The results indicate that, compared with the results of structure improvement of modal method, the vehicle interior noise is controlled more effectively by using the acoustic panel participation analytical method

Maternal body fluid lncRNAs serve as biomarkers to diagnose ventricular septal defect: from amniotic fluid to plasma

Background: Maternal body fluids contain abundant cell-free fetal RNAs which have the potential to serve as indicators of fetal development and pathophysiological conditions. In this context, this study aimed to explore the potential diagnostic value of maternal circulating long non-coding RNAs (lncRNAs) in ventricular septal defect (VSD).Methods: The potential of lncRNAs as non-invasive prenatal biomarkers for VSD was evaluated using quantitative polymerase chain reaction (qPCR) and receiver operating characteristic (ROC) curve analysis. The biological processes and regulatory network of these lncRNAs were elucidated through bioinformatics analysis.Results: Three lncRNAs (LINC00598, LINC01551, and GATA3-AS1) were found to be consistent in both maternal plasma and amniotic fluid. These lncRNAs exhibited strong diagnostic performance for VSD, with AUC values of 0.852, 0.957, and 0.864, respectively. The bioinformatics analysis revealed the involvement of these lncRNAs in heart morphogenesis, actin cytoskeleton organization, cell cycle regulation, and protein binding through a competitive endogenous RNA (ceRNA) network at the post-transcriptional level.Conclusion: The cell-free lncRNAs present in the amniotic fluid have the potential to be released into the maternal circulation, making them promising candidates for investigating epigenetic regulation in VSD

Overexpression of RrGGP2 and RrDHAR increases ascorbic acid content in tomato

Ascorbic acid (AsA) is the most abundant antioxidant in plants and is an important nutritional index for agricultural products. Some plants, such as Rosa roxburghii Tratt., contain exceptionally high levels of AsA, but are relatively unpalatable. In view of its role in human health, as well as plant growth and development, we examined the effects of two important AsA regulatory genes from R. roxburghii in tomato, with the aim of producing a crop of higher nutritional quality. RrGGP2 and RrDHAR were cloned from R. roxburghii fruit. The overexpression vectors were made using 35S promoters and mediated by Agrobacterium tumefaciens to obtain the overexpression lines. A PCR and qRT-PCR verified that the two genes had been inserted and overexpressed in the tomato leaves and fruits. The results showed that the overexpression of RrGGP2 increased tomato leaf and fruit AsA content by 108.5% and 294.3%, respectively, while the overexpression of RrDHAR increased tomato leaf and fruit AsA content by 183.9% and 179.9%. The overexpression of RrGGP2 and RrDHAR further changed the expression of genes related to AsA metabolism, and the upregulation of one such gene, SlGGP, may have contributed greatly to the increase in AsA. Results here indicate that RrGGP2 contributes more towards fruit AsA accumulation in tomato than RrDHAR

Gene expression profiling in Rosa roxburghii fruit and overexpressing RrGGP2 in tobacco and tomato indicates the key control point of AsA biosynthesis

Rosa roxburghii Tratt. is an important commercial horticultural crop endemic to China, which is recognized for its extremely high content of L-ascorbic acid (AsA). To understand the mechanisms underlying AsA overproduction in fruit of R. roxburghii, content levels, accumulation rate, and the expression of genes putatively in the biosynthesis of AsA during fruit development have been characterized. The content of AsA increased with fruit weight during development, and AsA accumulation rate was found to be highest between 60 and 90 days after anthesis (DAA), with approximately 60% of the total amount being accumulated during this period. In vitro incubating analysis of 70DAA fruit flesh tissues confirmed that AsA was synthesized mainly via the L-galactose pathway although L-Gulono-1, 4-lactone was also an effective precursor elevating AsA biosynthesis. Furthermore, in transcript level, AsA content was significantly associated with GDP-L-galactose phosphorylase (RrGGP2) gene expression. Virus-induced RrGGP2 silencing reduced the AsA content in R. roxburghii fruit by 28.9%. Overexpressing RrGGP2 increased AsA content by 8-12-fold in tobacco leaves and 2.33-3.11-fold in tomato fruit, respectively, and it showed enhanced resistance to oxidative stress caused by paraquat in transformed tobacco. These results further justified the importance of RrGGP2 as a major control step to AsA biosynthesis in R. roxburghii fruit