The Significance of Generalized Gauge Transformation across Fundamental Interactions

The author of this paper has put forward a unified program of gauge field from the mathematical and physical picture of the principal associated bundles: thinking that our universe may have more fundamental interactions than the four fundamental interactions, and these basic interaction gauge fields are only the projection components to the base manifold, that is our universe, from a unified gauge potential or connection of the principal associated bundle manifold on the base manifold. These components can satisfy the transformation of gauge potential, and can even be transformed from one basic interaction gauge potential to another basic interaction gauge potential, and can be summarized into a unified equation, that is, the generalized gauge Equation (GGE), but the gauge potential or connection on the principal bundle is invariant, corresponding to the invariance of gauge transformation [1]. In this paper, we will continue to discuss this aspect concretely, and specifically construct a spatiotemporal model with the frame bundle as the principal bundle, and the tensor bundle as the associated bundle, so that the four fundamental interactions, especially the electromagnetic interaction and the gravitational interaction, can be reflected in the bottom manifold, that is, the regional distributions in our universe. Furthermore, this paper studies the existence of gauge transformation across basic interactions by establishing a model of gauge transformation of basic interaction field;it is found that the unified expression formula is GGE and the expression relation on the curvature of space-time. Therefore, the author discusses the feasibility of the generalized gauge transformation across the basic electromagnetic interaction and the basic gravitational interaction, and on this basis, specifically determines a method or way to find the generalized gauge transformation, so as to try to realize the last step of the “unification” of the four fundamental interactions in physics, that is, the “unification” of electromagnetism and gravity.

MCIF-Transformer Mask RCNN:Multi-Branch Cross-Scale Interactive Feature Fusion Transformer Model for PET/CT Lung Tumor Instance Segmentation

The precise detection and segmentation of tumor lesions are very important for lung cancer computer-aided diagnosis.However,in PET/CT(Positron Emission Tomography/Computed Tomography)lung images,the lesion shapes are complex,the edges are blurred,and the sample numbers are unbalanced.To solve these problems,this paper proposes a Multi-branch Cross-scale Interactive Feature fusion Transformer model(MCIF-Transformer Mask RCNN)for PET/CT lung tumor instance segmentation,The main innovative works of this paper are as follows:Firstly,the ResNet-Transformer backbone network is used to extract global feature and local feature in lung images.The pixel dependence relationship is established in local and non-local fields to improve the model perception ability.Secondly,the Cross-scale Interactive Feature Enhancement auxiliary network is designed to provide the shallow features to the deep features,and the cross-scale interactive feature enhancement module(CIFEM)is used to enhance the attention ability of the fine-grained features.Thirdly,the Cross-scale Interactive Feature fusion FPN network(CIF-FPN)is constructed to realize bidirectional interactive fusion between deep features and shallow features,and the low-level features are enhanced in deep semantic features.Finally,4 ablation experiments,3 comparison experiments of detection,3 comparison experiments of segmentation and 6 comparison experiments with two-stage and single-stage instance segmentation networks are done on PET/CT lung medical image datasets.The results showed that APdet,APseg,ARdet and ARseg indexes are improved by 5.5%,5.15%,3.11%and 6.79%compared with Mask RCNN(resnet50).Based on the above research,the precise detection and segmentation of the lesion region are realized in this paper.This method has positive significance for the detection of lung tumors.

Backlund transformations, consistent Riccati expansion solvability, and soliton-cnoidal interaction wave solutions of Kadomtsev-Petviashvili equation

The famous Kadomtsev-Petviashvili(KP)equation is a classical equation in soliton theory.A B?cklund transformation between the KP equation and the Schwarzian KP equation is demonstrated by means of the truncated Painlevéexpansion in this paper.One-parameter group transformations and one-parameter subgroup-invariant solutions for the extended KP equation are obtained.The consistent Riccati expansion(CRE)solvability of the KP equation is proved.Some interaction structures between soliton-cnoidal waves are obtained by CRE and several evolution graphs and density graphs are plotted.

基于门控循环单元和Transformer的车辆轨迹预测方法

为增强自动驾驶车辆对动态环境的理解能力及其道路行驶安全性,提出基于门控循环单元(GRU)和Transformer的车辆轨迹预测模型STGTF,使用GRU提取车辆的历史轨迹特征,通过双层多头注意力(MHA)机制提取车辆的时空交互特征,生成预测轨迹。试验结果表明,预测结果的均方根误差(RMSE)平均降低7.3%,STGTF在短期预测和长期预测方面均有不同程度的提升,验证了模型的有效性。

融合Transformer和交互注意力网络的方面级情感分类模型

现有的大多数研究者使用循环神经网络与注意力机制相结合的方法进行方面级情感分类任务。然而,循环神经网络不能并行计算,并且模型在训练过程中会出现截断的反向传播、梯度消失和梯度爆炸等问题,传统的注意力机制可能会给句子中重要情感词分配较低的注意力权重。针对上述问题,该文提出了一种融合Transformer和交互注意力网络的方面级情感分类模型。首先利用BERT(bidirectional encoder representation from Transformers)预训练模型来构造词嵌入向量,然后使用Transformer编码器对输入的句子进行并行编码,接着使用上下文动态掩码和上下文动态权重机制来关注与特定方面词有重要语义关系的局部上下文信息。最后在5个英文数据集和4个中文评论数据集上的实验结果表明,该文所提模型在准确率和F1上均表现最优。

Information perception and feedback mechanism and key techniques of multi-modality human-robot interaction for service robots

With the increasing of the elderly population and the growing hearth care cost, the role of service robots in aiding the disabled and the elderly is becoming important. Many researchers in the world have paid much attention to heaRthcare robots and rehabilitation robots. To get natural and harmonious communication between the user and a service robot, the information perception/feedback ability, and interaction ability for service robots become more important in many key issues.

Exploiting Human Pose and Scene Information for Interaction Detection

Identifying human actions and interactions finds its use in manyareas, such as security, surveillance, assisted living, patient monitoring, rehabilitation,sports, and e-learning. This wide range of applications has attractedmany researchers to this field. Inspired by the existing recognition systems,this paper proposes a new and efficient human-object interaction recognition(HOIR) model which is based on modeling human pose and scene featureinformation. There are different aspects involved in an interaction, includingthe humans, the objects, the various body parts of the human, and the backgroundscene. Themain objectives of this research include critically examiningthe importance of all these elements in determining the interaction, estimatinghuman pose through image foresting transform (IFT), and detecting the performedinteractions based on an optimizedmulti-feature vector. The proposedmethodology has six main phases. The first phase involves preprocessing theimages. During preprocessing stages, the videos are converted into imageframes. Then their contrast is adjusted, and noise is removed. In the secondphase, the human-object pair is detected and extracted from each image frame.The third phase involves the identification of key body parts of the detectedhumans using IFT. The fourth phase relates to three different kinds of featureextraction techniques. Then these features are combined and optimized duringthe fifth phase. The optimized vector is used to classify the interactions in thelast phase. TheMSRDaily Activity 3D dataset has been used to test this modeland to prove its efficiency. The proposed system obtains an average accuracyof 91.7% on this dataset.

Large Scale Fundamental Interactions in the Universe

The author of this paper once attempted to propose a unified framework for gauge fields based on the mathematical and physical picture of the principal fiber bundle: that is, to believe that our universe may have more fundamental interactions than the four, and these fundamental gauge fields are only components on the bottom manifold (i.e. our universe) projected by a unified gauge potential of the principal fiber bundle manifold;these components can satisfy the transformation of gauge potential, or even be transformed from one basic interaction gauge potential to another basic interaction gauge potential, and can be summarized into a unified equation, namely the generalized gauge equation expression, corresponding to gauge transformation invariance;so the invariance of gauge transformation is a necessary condition for unified field theory, and the four (or more) fundamental interaction fields of the universe are unified in a unified gauge field defined by the connection on the principal fiber bundle. In this paper, the author continues to propose a model of large-scale (gravitational) fundamental interactions in the universe based on the mathematical and physical picture of the principal fiber bundle, attempting to explain that dark matter and dark energy are merely reflections of these gravitational fundamental interactions that deviate in intensity from the gravitational fundamental interactions of the solar system at galaxy scales or some cosmic scales which are much larger than the solar system. All these “gravitational” fundamental interactions originate from the unified gauge field of the universe, namely the connection or curvature on the principal fiber bundle. These interactions are their projected representations on the bottom manifold (i.e. our universe) by different cross-sections (gauge transformations). These projection representations of the universe certainly are described by the generalized gauge equation or curvature similarity equation, and under the guidance of curvature gauge transformation factors, oscillate and evolve between the curvatures 1→0→-1→0→1 of the universe.

多级特征交互Transformer的多器官图像分割

多器官医学图像分割有助于医生做出临床诊断.针对CNN提取全局特征能力弱,Transformer提取局部特征能力弱,以及Transformer具有二次方计算复杂度的问题,提出了用于多器官医学图像分割的多级特征交互Transformer模型.所提模型采用CNN提取局部特征,局部特征经Swin Transformer输出全局特征;通过下采样分别产生多级局部和全局特征,每级局部和全局特征经过交互并增强;每级增强后的特征经多级特征融合模块进行交叉融合;再次融合后的特征经过上采样和分割头输出分割掩码.所提模型在Synapse和ACDC数据集上进行实验,平均DSC和平均HD95系数值为80.16%和19.20 mm,均优于LGNet和RFE-UNet等代表性模型.该模型对多器官医学图像分割是有效的.

基于Transformer的蛋白质相互作用预测研究

研究蛋白质相互作用(PPIs)在生物学中具有非常重要的意义,蛋白质相互作用及其相互作用类型的研究对于理解正常和疾病状态下的细胞生物学过程至关重要,从而有助于治疗靶点的识别和新药物的设计。针对传统蛋白质相互作用预测模型预测精度不够高的问题,提出了一种基于Transformer的模型TPPI对蛋白质进行相互作用的预测。五倍交叉验证实验结果表明,该模型在人类蛋白质数据集上预测的准确率为0.944,表现出了较好的预测准确性。

Measurement and Characterization of Microwave Interaction between Integrated Distributed Feedback Laser Diode and Electro-Absorption Modulator

Integrated electro-absorption-modulated distributed feedback laser diodes(EMLs)are attracting much interest in optical communications for the advantages of a compact structure,low power consumption,and high-speed modulation.In integrated EML,the microwave interaction between the distributed feedback laser diode(DFB-LD)and the electro-absorption modulator(EAM)has a nonnegligible influence on the modulation performance,especially at the high-frequency region.In this paper,integrated EML was investigated as a three-port network with two electrical inputs and a single optical output,where the scattering matrix of the integrated device was theoretically deduced and experimentally measured.Based on the theoretical model and the measured data,the microwave equivalent circuit model of the integrated device was established,from which the microwave interaction between DFB-LD and EAM was successfully extracted.The results reveal that the microwave interaction within integrated EML contains both the electrical isolation and optical coupling.The electrical isolation is bidirectional while the optical coupling is directional,which aggravates the microwave interaction in the direction from DFB-LD to EAM.

基于Social Transformer的井下多人轨迹预测方法

目前煤矿井下人员轨迹预测方法中,Transformer与循环神经网络(RNN)、长短期记忆(LSTM)网络相比,在处理数据时不仅计算量小,同时还有效解决了梯度消失导致的长时依赖问题。但当环境中涉及多人同时运动时,Transformer对于场景中所有人员未来轨迹的预测会出现较大偏差。并且目前在井下多人轨迹预测领域尚未出现一种同时采用Transformer并考虑个体之间相互影响的模型。针对上述问题,提出一种基于Social Transformer的井下多人轨迹预测方法。首先对井下每一个人员独立建模,获取人员历史轨迹信息,通过Transformer编码器进行特征提取,接着由全连接层对特征进行表示,然后通过基于图卷积的交互层相互连接,该交互层允许空间上接近的网络彼此共享信息,计算预测对象在受到周围邻居影响时对周围邻居分配的注意力,从而提取其邻居的运动模式,继而更新特征矩阵,最后新的特征矩阵由Transformer解码器进行解码,输出对于未来时刻的人员位置信息预测。实验结果表明,Social Transformer的平均位移误差相较于Transformer降低了45.8%,且与其他主流轨迹预测方法LSTM,S−GAN,Trajectron++和Social−STGCNN相比分别降低了67.1%,35.9%,30.1%和10.9%,有效克服了煤矿井下多人场景中由于人员间互相影响导致预测轨迹失准的问题,提升了预测精度。

基于Swin Transformer和图形推理的结直肠息肉分割方法

针对结直肠息肉图像分割中病灶区域尺度变化大、边缘模糊以及息肉与正常组织对比度低等问题,导致病变区域分割精度低和分割边界存在伪影,提出一种基于Swin Transformer和图形推理的自适应网络.该网络一是利用Swin Transformer编码器逐层提取输入图像的全局上下文信息,弱化背景信息干扰,多尺度分析病变区域的显著性特点.二是提出全局与局部特征交互模块增强网络对复杂病灶的空间感知能力,突出待分割目标的关键位置信息,精准定位目标.三是通过区域引导图推理模块以图循环递推的方式挖掘先验信息之间的高阶显性关系,促进图间信息传递.四是设计面向边缘细节的边缘约束图推理模块,整合边缘细节,改善分割效果,提高分割精度.在CVC-ClinicDB、Kvasir、CVC-ColonDB和ETIS数据集上进行实验,其Dice系数分别为0.939,0.926,0.810和0.788,平均交并比分别为0.889,0.879,0.731和0.710,分割性能优于现有方法.仿真实验结果表明,对于形态结构复杂、对比度低和边缘模糊的结直肠息肉图像均有较高的分割精度.

基于Transformer的多车交互场景车辆轨迹预测

车辆轨迹预测是自动驾驶中的关键技术,对于提高自动驾驶车辆路径规划功能的安全性有重要意义。对变道场景中多辆车的历史车辆轨迹进行建模,基于NGSIM数据集提取场景样本,并构建基于注意力机制的Transformer编码器-解码器模型,通过捕捉轨迹之间的潜在关系,采用递归式方法生成对应的预测轨迹。实验表明,Transformer模型能更好捕捉相邻轨迹之间的时空交互特征,在复杂轨迹预测任务上呈现较优的预测结果。

Effects of Alloying Elements on the Concentration Profile of Equilibrium Phases in Transformation Induced Plasticity Steel

With the two sublattices model, equilibrium compositions of ferrite (α) and austenite (γ) phases, as well as the volume percent of austenite (γ) in different TRIP steels are calculated. Concentration profiles of carbon, manganese, aluminum and silicon in these steels are also estimated under the lattice fixed frame of reference so as to identify if the equilibrium state is obtained. Through the comparison between the profiles after different time diffusion, the distribution of elements in phases is exhibited and the complex effect due to the mutual interaction of the elements on diffusion is discussed.

Protein-protein interaction map is a key gateway into liver regeneration

Recent studies indicate that the process of liver regeneration involves multiple signaling pathways and a variety of genes,cytokines and growth factors. Protein-protein interactions(PPIs)play a role in nearly all events that take place within the cell and PPI maps should be helpful in further understanding the process of liver regeneration.In this review,we discuss recent progress in understanding the PPIs that occur during liver regeneration especially those in the transforming growth factorβsignaling pathways.We believe the use of large-scale PPI maps for integrating the information already known about the liver regeneration is a useful approach in understanding liver regeneration from the standpoint of systems biology.

A SEMI-ANALYTICAL AND SEMI-NUMERICAL METHOD FOR SOLVING 2-D SOUND-STRUCTURE INTERACTION PROBLEMS

Based on the transfer matrix method and the virtual source simulation technique, this paper proposes a novel semi-analytical and semi-numerical method for solving 2-D sound- structure interaction problems under a harmonic excitation.Within any integration segment, as long as its length is small enough,along the circumferential curvilinear coordinate,the non- homogeneous matrix differential equation of an elastic ring of complex geometrical shape can be rewritten in terms of the homogeneous one by the method of extended homogeneous capacity proposed in this paper.For the exterior fluid domain,the multi-circular virtual source simulation technique is adopted.The source density distributed on each virtual circular curve may be ex- panded as the Fourier's series.Combining with the inverse fast Fourier transformation,a higher accuracy and efficiency method for solving 2-D exterior Helmholtz's problems is presented in this paper.In the aspect of solution to the coupling equations,the state vectors of elastic ring induced by the given harmonic excitation and generalized forces of coefficients of the Fourier series can be obtained respectively by using a high precision integration scheme combined with the method of extended homogeneous capacity put forward in this paper.According to the superposition princi- ple and compatibility conditions at the interface between the elastic ring and fluid,the algebraic equation of system can be directly constructed by using the least square approximation.Examples of acoustic radiation from two typical fluid-loaded elastic rings under a harmonic concentrated force are presented.Numerical results show that the method proposed is more efficient than the mixed FE-BE method in common use.

An Improved Robust Model Predictive Control Approach to Systems with Linear Fractional Transformation Perturbations

In this paper, a robust model predictive control approach is proposed for a class of uncertain systems with time-varying, linear fractional transformation perturbations. By adopting a sequence of feedback control laws instead of a single one, the control performance can be improved and the region of attraction can be enlarged compared with the existing model predictive control （MPC） approaches. Moreover, a synthesis approach of MPC is developed to achieve high performance with lower on-line computational burden. The effectiveness of the proposed approach is verified by simulation examples.

Interaction of elementary waves for relativistic Euler equations

In this paper, using the characteristic analysis method, we study the relativistic Euler equations of conservation laws in energy and momentum in special relativity. The interactions of elementary waves for the relativistic Euler equations are shown. The collision of two shocks, two centered rarefaction waves, a shock and a rarefaction wave yield corresponding ransmitted waves. The overtaking of two shocks appears a transmitted shock wave, together with a reflected centered rarefaction wave.

Rational solutions and interaction solutions for(2+1)-dimensional nonlocal Schrodinger equation

A chain of novel higher order rational solutions with some parameters and interaction solutions of a(2+1)-dimensional reverse space–time nonlocal Schrodinger(NLS)equation was derived by a generalized Darboux transformation(DT)which is derived by Taylor expansion and determinants.We obtained a series of higher-order rational solutions by one spectral parameter and we could get the periodic wave solution and three kinds of interaction solutions,singular breather and periodic wave interaction solution,singular breather and traveling wave interaction solution,bimodal breather and periodic wave interaction solution by two spectral parameters.We found a general formula for these solutions in the form of determinants.We also analyzed the complex wave structures of the dynamic behaviors and the effects of special parameters and presented exact solutions for the(2+1)-dimensional reverse space–time nonlocal NLS equation.