Research on the Prediction of Rigid Frame-Continuous Girder Bridge Deflection Using BP and RBF Neural Networks

To solve the problem of excessive deflection in the post-operation process of a rigid frame-continuous girder bridge and provide a basis for the setting of its initial camber, this paper, based on the results of finite element analysis, uses three methods to predict and verify the deflection of a rigid frame-continuous girder bridge. The results show that the average deflection method can be used to fit the average deflection value for a relatively long period of time and predict the average deflection value for the next longer period of time. Both the back-propagation (BP) neural network model and the radial basis function (RBF) neural network model can predict deflection well, but the RBF neural network model has higher prediction accuracy, with a mean absolute error (MAE) of 2.55 cmm and a relative error not exceeding 1%. The prediction model established by the RBF neural network has higher stability, better generalization ability, and better overall prediction performance. The established model has some reference significance for similar engineering projects and can achieve the optimization of structural parameters

A Comparative Study of Sino-U.S. Business Negotiation Strategy From the Perspective of Cultural Dimensions Theory

Business negotiation serves as an important activity in Sino-U.S. trade where Chinese companies pay much attention to the relations with their American counterparts. Due to the salient differences in cultures and ways of doing business, negotiating conflicts occur frequently, which impedes the smooth advance of business activities. This comparative research aims to analyze differences in Sino-U.S. business negotiation from an intercultural perspective, providing advice for Chinese negotiators in an attempt to reduce misunderstandings and disputes. The author has collected information about the definition of international negotiation as well as the current state of intercultural research and summarized previous related studies. This study employs Hofstede’s cultural dimensions theory and conducts case analysis in ways that apply the theory into practical negotiation situation.The findings show that Chinese negotiators value long-term business partnership; in addition, they often consult their superiors when the expected conditions change; in terms of communication model, Chinese negotiators prefer indirect speech and constantly use euphemism; a general framework on the contract is more important than specific details for them. American negotiators give priority to the realization of business goals; negotiators represent the company to make decisions and are responsible for the negotiation results; Americans often point out issues face to face and specify concrete solutions to problems; compared with Chinese negotiators, they prefer to reach a consensus on detailed matters and stress less on general tenets. This study illustrates features of Sino-U.S. negotiation in an attempt to provide guidance for future related studies. The author also tries to summarize some pragmatic strategies for Chinese negotiators so as to facilitate the negotiation

The Relationship between Estimated Glomerular Filtration Rate and Diabetic Retinopathy

Diabetic retinopathy (DR) is the leading cause of visual impairment and blindness in working-aged people. Several studies have suggested that glomerular filtration rate (GFR) was correlated with DR. This is a hospital-based study and the aim of it was to examine the relationship between the GFR and DR in patients with type 2 diabetes mellitus (T2DM). We used CKD-EPI equation to estimate GFR and SPSS 19.0 and EmpowerStats software to assess their relationship. Among the 1613 participants (aged 54.75 ± 12.19 years), 550 (34.1%) patients suffered from DR. The multivariate analysis revealed that the risk factors for DR include age (P<0.001, OR = 0.940), duration of diabetes (P<0.001, OR = 1.163), hemoglobin A1c (P=0.007, OR = 1.224), systolic blood pressure (P<0.001, OR = 1.032), diastolic blood pressure (P=0.007, OR = 0.953), high density lipoprotein cholesterol (P=0.024, OR = 3.884), and eGFR (P=0.010, OR = 0.973). Through stratified analysis and saturation effect analysis, our data suggests that eGFR of 99.4 mL/min or lower might imply the early stage of DR in diabetic patients. Thus, the evaluation of eGFR has clinical significance for the early diagnosis of DR

Sound Velocity Profile (SVP) inversion through correcting the terrain distortion

In this paper, mode vectors are obtained via the Empirical Orthogonal Function (EOF) based on real Sound Velocity Profiles (SVP) measurements. Through correcting the terrain distortion, reconstructed coefficients of SVPs are determined by Genetic Algorithm (GA) and then the inversion result of the SVP is obtained. The conclusions show that the terrain distortion caused by sound velocity errors can be effectively corrected by the inversion result of the SVP. Using this process, the accuracy and processing efficiency of multi-beam bathymetry data can be significantly improved.En este artículo, se obtienen los vectores de forma a través de la Función Empírica Ortogonal (EOF) basada en mediciones reales de los Perfiles de la Velocidad del Sonido (SVP). Mediante la corrección de la distorsión del terreno, los coeficientes reconstruidos de los SVPs son determinados por el Algoritmo Genético (AG) y posteriormente se obtiene el resultado de la inversión del SVP. Las conclusiones muestran que la distorsión del terreno causada por errores de velocidad del sonido puede corregirse eficazmente mediante el resultado de la inversión del SVP. Utilizando este proceso, la exactitud y la eficiencia del procesado de los datos de batimetría multihaz pueden mejorarse significativamente.Cet article décrit la décomposition en vecteurs propres via les fonctions empiriques orthogonales (EOF) des mesures des profils de vitesse du son (SVP). La correction des distorsions de terrain permet de déterminer des coefficients reconstruits des SVP à l’aide d’un algorithme génétique (AG), puis le résultat de l’inversion du SVP est obtenu. Les conclusions montrent que les distorsions de terrain causées par les erreurs de vitesse du son peuvent être effectivement corrigées par le résultat de l’inversion du SVP. A l’aide de ce processus, la précision et l’efficacité du traitement des données bathymétriques multifaisceaux peuvent être améliorées de façon importante

Association of FokI, TaqI, BsmI and ApaI polymorphisms with diabetic retinopathy: a pooled analysis of case-control studies

Background: To assess synthetically the association between polymorphisms in the vitamin D receptor (VDR) gene (FokI, BsmI, ApaI, and TaqI) and diabetic retinopathy (DR).Methods: Pubmed, Embase, ISI Web of Science, Google-scholar and CBMDisc, CNKI and Chongqing VIP databases were searched. A meta-analysis was performed.Results: Six studies with 636 cases and 1,035 controls were included in this meta-analysis. The outcomes showed that the FokI polymorphism (F allele) of VDR gene had no statistical protective relationship with DR in overall studies. Interestingly, stratification analysis showed that the FokI polymorphism (Fallele) was significantly associated with decreased DR risk in the Chinese population, among included studies without publication bias, during a comparison analysis between normal subjects and DR patients, and among articles published after 2010. However, the TaqI, BsmI and ApaI polymorphisms of VDR gene had no significant association with the risk of DR.Conclusion: This meta-analysis of case-control studies revealed that the VDR-FokI polymorphism (F allele) decreased the risk of DR in Chinese people, among included studies without publication bias, during a comparison analysis between normal subjects and DR patients, and among articles published after 2010. Further rigorous and prospective studies with large sample size are needed to confirm our findings.Keywords: Diabetic retinopathy; polymorphism; Vitamin D receptor

Does Scale-Free Syntactic Network Emerge in Second Language Learning?

Language is a complex system during whose operation many properties may emerge spontaneously. Using complex network approach, existing studies have found that, in first language (L1) acquisition, syntactic complex network featuring the scale-free and the small-world properties, will emerge at the age of 24 months. For foreign language (L2) learning, however, researchers have not reached a consensus on whether syntactic network with these two properties will emerge. Therefore, this study adopts complex network approach in L2 learning study, attempting to answer this question. In this study, nine networks are constructed on the basis of English compositions by Chinese students. Properties of these networks reveal that the syntactic network featuring these two properties, instead of emerging suddenly at a certain point, has existed at the very beginning of the L2 learning of Chinese students, and persists throughout the entire process of L2 learning, which is different from what has been found in L1 acquisition. The reason is probably that the already established L1 syntactic system provides foundation for L2 syntactic learning, and L2 learners tend to use the entrenched L1 syntactic network to generate L2 syntactic structures. L2 syntactic learning thus is not characterized by a sudden emergence of syntactic system, but a gradual approximation to the target language, with its own unique properties. For the first time, this study provides a tentative answer to L2 syntactic emergence from the perspective of complex network, and provides a macroscopic description of L2 syntactic developmental trajectory

SUBP: Soft Uniform Block Pruning for 1xN Sparse CNNs Multithreading Acceleration

The study of sparsity in Convolutional Neural Networks (CNNs) has become widespread to compress and accelerate models in environments with limited resources. By constraining N consecutive weights along the output channel to be group-wise non-zero, the recent network with 1$\times$N sparsity has received tremendous popularity for its three outstanding advantages: 1) A large amount of storage space saving by a \emph{Block Sparse Row} matrix. 2) Excellent performance at a high sparsity. 3) Significant speedups on CPUs with Advanced Vector Extensions. Recent work requires selecting and fine-tuning 1$\times$N sparse weights based on dense pre-trained weights, leading to the problems such as expensive training cost and memory access, sub-optimal model quality, as well as unbalanced workload across threads (different sparsity across output channels). To overcome them, this paper proposes a novel \emph{\textbf{S}oft \textbf{U}niform \textbf{B}lock \textbf{P}runing} (SUBP) approach to train a uniform 1$\times$N sparse structured network from scratch. Specifically, our approach tends to repeatedly allow pruned blocks to regrow to the network based on block angular redundancy and importance sampling in a uniform manner throughout the training process. It not only makes the model less dependent on pre-training, reduces the model redundancy and the risk of pruning the important blocks permanently but also achieves balanced workload. Empirically, on ImageNet, comprehensive experiments across various CNN architectures show that our SUBP consistently outperforms existing 1$\times$N and structured sparsity methods based on pre-trained models or training from scratch. Source codes and models are available at \url{https://github.com/JingyangXiang/SUBP}.Comment: 14 pages, 4 figures, Accepted by 37th Conference on Neural Information Processing Systems (NeurIPS 2023