A Local-Global Attention Fusion Framework With Tensor Decomposition for Medical Diagnosis

Dear Editor,In this letter,a novel hierarchical fusion framework is proposed to address the imperfect data property in complex medical image analysis(MIA)scenes.In particular,by combining the strengths of convolutional neural networks(CNNs)and transformers,the enhanced feature extraction,spatial modeling,and sequential context learning are realized to provide comprehensive insights on the complex data patterns.Integration of information in different level is enabled via a multi-attention fusion mechanism,and the tensor decomposition methods are adopted so that compact and distinctive representation of the underlying and high-dimensional medical image features can be accomplished[1].It is shown from the evaluation results that the proposed framework is competitive and superior as compared with some other advanced algorithms,which effectively handles the imperfect property of inter-class similarity and intra-class differences in diseases,and meanwhile,the model complexity is reduced within an acceptable level,which benefits the deployment in clinic practice.MIA has assumed a pivotal role in numerous critical clinical scenarios,where sophisticated image analysis techniques have proven instrumental in augmenting medical decision-making,facilitating individualized therapeutic interventions,and enhancing patient prognostication[2]−[4].

Observer-Based Adaptive Robust Precision Motion Control of a Multi-Joint Hydraulic Manipulator

Hydraulic manipulators are usually applied in heavy-load and harsh operation tasks.However,when faced with a complex operation,the traditional proportional-integral-derivative(PID)control may not meet requirements for high control performance.Model-based full-state-feedback control is an effective alternative,but the states of a hydraulic manipulator are not always available and reliable in practical applications,particularly the joint angular velocity measurement.Considering that it is not suitable to obtain the velocity signal directly from differentiating of position measurement,the low-pass filtering is commonly used,but it will definitely restrict the closed-loop bandwidth of the whole system.To avoid this problem and realize better control performance,this paper proposes a novel observerbased adaptive robust controller(obARC)for a multi-joint hydraulic manipulator subjected to both parametric uncertainties and the lack of accurate velocity measurement.Specifically,a nonlinear adaptive observer is first designed to handle the lack of velocity measurement with the consideration of parametric uncertainties.Then,the adaptive robust control is developed to compensate for the dynamic uncertainties,and the close-loop system robust stability is theoretically proved under the observation and control errors.Finally,comparative experiments are carried out to show that the designed controller can achieve a performance improvement over the traditional methods,specifically yielding better control accuracy owing to the closed-loop bandwidth breakthrough,which is limited by low-pass filtering in fullstate-feedback control.

基于TCN-GRU的Handle标识解析系统负载均衡算法

数联网技术是解决数据管理困难及数据孤岛等问题的关键。近年来,随着数联网技术的飞速发展,Handle系统作为数联网标识解析领域中最具有代表性的系统得以快速落地。然而,Handle标识注册量和解析请求量的快速增长使得Handle系统缓存/递归解析服务节点的解析请求压力加大,且难以保证标识解析请求的服务质量。针对上述问题,提出一种基于TCN-GRU的缓存/递归解析服务节点的负载均衡算法,旨在优化缓存/递归解析服务节点的标识解析效率。首先,将用户的解析请求合理地分配到缓存/递归解析服务节点的服务器集群当中,以提升服务器集群整体的工作效率和吞吐量;其次,基于Handle系统中节点的层级架构,考虑到循环神经网络中普遍存在的梯度弥散问题,引入TCN时序神经网络,有助于提取服务器集群负载的时序性信息。相较于传统的负载均衡算法,所提算法根据服务器负载状况动态调整负载转发策略,服务器平均响应时间缩短50%左右,吞吐率提高40%左右,请求失败次数大幅减少。

工业互联网Handle标识解析技术在桥梁行业中的创新应用研究

当前,新一轮科技革命和产业变革蓬勃兴起,工业互联网作为第四次工业革命的重要基石,融合人工智能、区块链和大数据、云边协同、数字孪生、边缘计算、5G等新一代信息技术,通过网络、平台、安全3大功能体系构建,实现全要素、全产业链、全价值链的全面连接。Handle标识解析技术作为工业互联网的重要组成部分,也在不断探索在不同场景中的应用。目前,标识解析技术对桥梁建设行业的应用还处于发展探索期,正在不断探索在桥梁全生命周期、供应链管理、上下游对接等方面的应用实践。本文主要描述标识解析技术在打通从桥梁建设到桥梁监测和管养的数据链路方面的应用探索和研究。

Intelligent Vehicle Auxiliary Handling System Based on the Internet of Things Technology

This paper proposes an intelligent vehicle auxiliary handling system based on Internet of Things(IoT)technology,featuring an innovative holding mechanism design that adjusts to the length and width of various vehicles.The system combines precise positioning using satellite tracking technology,intelligent recognition via OpenCV,and the interconnectivity of IoT.This intelligent vehicle auxiliary handling system can independently identify vehicle positions and plan optimal handling paths,eliminating the traditional reliance on manual operation.It offers efficient and accurate handling,setting a new trend in the handling industry.Additionally,the system integrates seamlessly with parking lot management systems,providing real-time updates on vehicle locations and statuses.This allows managers to monitor the parking lot operations clearly and efficiently.This intelligent coordination greatly enhances overall work efficiency and streamlines parking management.Overall,the innovative design of the intelligent vehicle auxiliary handling system represents a significant breakthrough in both function and performance,gaining user favor with its smooth operation.Looking ahead,continued technological advancements and the expansion of application fields will bring even more vitality and intelligence to societal development.

Bronze Vessel with Loop Handles

In 1973, six pieces of bronzeware were unearthed from the No.2 vault in Beidong Village, Liaoning Province. Among them is this four legged vessel with straight loop handles. It is 51.7 cm in height, 40.7 cm in length and 30.7 cm in width. The body of the vessel is patterned with dragon and door-nail designs. The legs are decorated with the faces of wild beasts. Inside the vessel is a 28-character inscription, praising a woman official. The woman, according to experts, was a military leader and was often awarded by the King of Shang. We can see that the slave society of the Shang Dynasty maintained some aspects of the ancient matriarchal society.

基于区块链的Handle标识系统

面对日益剧增的数据量,传统的中心化服务器、数据库的负荷急剧增加乃至难以为继。基于区块链系统的不可篡改和永久存储特性,提出一种基于区块链的Handle标识系统。该系统通过IPFS网络和区块链技术建立了一个去中心化的、不可篡改的、分布式云存储和查询平台,能够将标识对象的信息与Handle标识绑定一同写入到区块链和IPFS网络中,结合AES加密算法保证数据的安全和稳定性。实验表明,该系统能够在保证Handle后缀唯一性的同时,完成标识和存储数据的绑定,实现了数据对象标识的生成和解析。

Construction and application of knowledge graph for grid dispatch fault handling based on pre-trained model

With the construction of new power systems,the power grid has become extremely large,with an increasing proportion of new energy and AC/DC hybrid connections.The dynamic characteristics and fault patterns of the power grid are complex;additionally,power grid control is difficult,operation risks are high,and the task of fault handling is arduous.Traditional power-grid fault handling relies primarily on human experience.The difference in and lack of knowledge reserve of control personnel restrict the accuracy and timeliness of fault handling.Therefore,this mode of operation is no longer suitable for the requirements of new systems.Based on the multi-source heterogeneous data of power grid dispatch,this paper proposes a joint entity–relationship extraction method for power-grid dispatch fault processing based on a pre-trained model,constructs a knowledge graph of power-grid dispatch fault processing and designs,and develops a fault-processing auxiliary decision-making system based on the knowledge graph.It was applied to study a provincial dispatch control center,and it effectively improved the accident processing ability and intelligent level of accident management and control of the power grid.

Digital Object Architecture for IoT Networks

The Internet of Things(IoT)is a recent technology,which implies the union of objects,“things”,into a single worldwide network.This promising paradigm faces many design challenges associated with the dramatic increase in the number of end-devices.Device identification is one of these challenges that becomes complicated with the increase of network devices.Despite this,there is still no universally accepted method of identifying things that would satisfy all requirements of the existing IoT devices and applications.In this regard,one of the most important problems is choosing an identification system for all IoT devices connected to the public communication networks.Many unique soft-ware and hardware solutions are used as a unique global identifier;however,such solutions have many limitations.This article proposes a novel solution,based on the Digital Object Architecture(DOA),that meets the requirements of identifying devices and applications of the IoT.This work analyzes the benefits of using the DOA as an identification platform in modern telecommunication networks.We propose a model of an identification system based on the architecture of digital objects,which differs from the well-known ones.The proposed model ensures an acceptable quality of service(QoS)in the common architecture of the existing public communication networks.A novel interaction architecture is developed by introducing a Middle Handle Register(MHR)between the global register,i.e.,Global Handle Register(GHR),and local register,i.e.,Local Handle Register(LHR).The aspects of the network interaction and the compatibility of IoT end-devices with the integrated DOA identifiers in heterogeneous communication networks are presented.The developed model is simulated for a wide-area network with allocated registers,and the results are introduced and discussed.

Analysis of load status and management strategies of main caregivers of patients with malignant tumors of digestive tract

Caregiver load refers to the subjective and objective negative impact of caregivers in the care of patients,and excessive load will have a serious impact on patients and caregivers themselves and can reduce their quality of life.For the main caregivers,it not only needs to care for the patients in life and daily life,but also needs to pay the cost of treatment for the patients,coupled with the need to carry out their own original work,life,etc.excessive life pressure,economic pressure,work pressure,emotional pressure,etc.lead to heavy load of the main caregivers,which can easily cause caregivers to have different degrees of psychological problems,which will cause serious adverse effects on the caregivers themselves and cancer patients,not conducive to the construction of a harmonious family and society.This article analyzes the current situation of primary caregiver burden in patients with gastrointestinal malignant tumors,analyzes its influencing factors,and specifies specific treatment strategies.It is hoped to provide scientific guidance for later related research and application.

Online Fault Detection Configuration on Equipment Side of a Variable-Air-Volume Air Handling Unit

With the development of the technology of the Internet of Things,more and more operational data can be collected from air conditioning systems.Unfortunately,the most of existing air conditioning controllers mainly provide controlling functions more than storing,processing or computing the measured data.This study develops an online fault detection configuration on the equipment side of air conditioning systems to realize these functions.Modbus communication is served to collect real-time operational data.The calculating programs are embedded to identify whether the measured signals exceed their limits or not,and to detect if sensor reading is frozen and other faults in relation to the operational performance are generated or not.The online fault detection configuration is tested on an actual variable-air-volume(VAV)air handling unit(AHU).The results show that the time ratio of fault detection exceeds 95.00%,which means that the configuration exhibits an acceptable fault detection effect.

Special Topic on Reinforcement Learning and Intelligent Decision

Over the past few years,deep reinforcement learning(RL)has made remarkable progress in a range of applications,including Go games,vision-based control,and generative dialogue systems.Via error-and-trial mechanisms,deep RL enables data-driven optimization and sequential decision-making in uncertain environments.Compared to traditional programming or heuristic optimization methods,deep RL can elegantly balance exploration and exploitation and handle environmental uncertainties.As a result,this learning paradigm has attracted increasing attention from both academia and industry and is paving a new path for largescale complex decision-making applications.

Failure rate,return-to-sports and magnetic resonance imaging after meniscal repair:119 patients with 7 years mean follow up

BACKGROUND One of the most important factors to consider in relation to meniscal repair is the high failure rate reported in the existing literature.AIM To evaluate failure rates,return to sports(RTS)rate,clinical outcomes and magnetic resonance image(MRI)evaluation after meniscus suture repair for longitudinal tears at a minimum 2-year-follow-up.METHODS We conducted a retrospective review of meniscal repairs between January 2004 and December 2018.All patients treated for longitudinal tears associated or not with an anterior cruciate ligament reconstruction(ACL-R)were included.Meniscal ramp lesions,radial and root tears,associated with multiligament injuries,tibial fracture and meniscal allograft transplants were excluded.Surgical details and failure rate,defined as symptomatic patients who underwent a revision surgery,were analyzed.As isolated bucket handle tears(BHTs)were usually associated with higher failure rates,we compared BHTs and not BHTs associated or not with an ACL-R.Since 2014,the inside-out technique using cannulas and suture needles with 2-0 Tycron began to predominate.In addition,the number of stitches per repair was increased.In view of differences in surgical technique,we compared two different cohorts:before and after 2014.We recorded the RTS according to the level achieved and the time to RTS.Lysholm and IKDC scores were recorded.Patients were studied with x-rays and MRI as standard postoperative control.RESULTS One hundred and nineteen patients were included with a mean follow up of 7 years(SD:4.08).Overall failure rate was 20.3%at a mean 20.1 mo.No statistically significant differences were found when comparing failure for medial and lateral meniscal repair(22.7%and 15.3%,P=0.36),BHTs and not BHTs(26%and 17.6%,P=0.27),isolated or associated with an ACL-R(22.9%and 18%,P=0.47),or when comparing only BHTs associated with an ACL-R(23%and 27.7%,P=0.9)or not.When comparing cohorts before and after 2014,we found a significant decrease in the overall failure rate from 26%to 11%(P<0.03).Isolated lesions presented a decrease from 28%to 6.6%(P=0.02),BHTs from 34%to 8%(P=0.09)and those associated with an ACL-R from 25%to 10%(P=0.09).Mean RTS time was 6.5 mo in isolated lesions and 8.64 mo when associated with an ACL-R.Overall,56%of patients returned to the same sport activity level.Mean pre and postoperative Lysholm scores were 64 and 85(P=0.02),and IKDC 58 and 70(P=0.03).Out of 84 asymptomatic patients evaluated with MRI,39%were classified as“not healed”and 61%as“healed”.CONCLUSION Even though the overall failure rate of our series was 20.3%,we found a statistically significant decrease from 26%to 11%,not only for isolated lesions,but also for BHT’s and those associated with an ACL-R when comparing our series in two different cohorts,most probably due to improvements in surgical technique.

Anchor of Stability and Source of Prosperity:International Situation and Chinese Diplomacy 2022

The international situation continued to change in a complex way in 2022,with accelerating evolution of profound changes unseen in a century.Guided byXiJinpingThoughtonDiplomacy,China calmly met perplexing and profound changes in the international situation,appropriately handled new difficulties and new challenges coming its way,and creatively advanced major-country diplomacy with Chinese characteristics.

CHINA-LAOS RAILWAY:BEACON OF BRI COOPERATION

Since its launch in December 2021,the China-Laos Railway has been benefiting the peoples of both China and Laos and generating great momentum for regional economic trade and development.Over the past year,the railway has handled 8.5 million passenger trips and transported 1.12 million tons of cargo.Furthermore,the varieties of the transported goods have diversified to over 1,200 from barely a dozen,an encouraging achievement of the cooperation project between the two countries.

Automatic Driving Material Handling Vehicle Station Location and Scheduling Mathematical Modeling and Analysis

Traditional material handling vehicles often use internal combustion engines as their power source, which results in exhaust emissions that pollute the environment. In contrast, automated material handling vehicles have the advantages of zero emissions, low noise, and low vibration, thus avoiding exhaust pollution and providing a more comfortable working environment for operators. In order to achieve the goals of “peaking carbon emissions by 2030 and achieving carbon neutrality by 2060”, the use of environmentally friendly autonomous material handling vehicles for material transportation is an inevitable trend. To maximize the amount of transported materials, consider peak-to-valley electricity pricing, battery pack procurement, and the construction of charging and swapping stations while achieving “minimum daily transportation volume” and “lowest investment and operational cost over a 3-year settlement period” with the shortest overall travel distance for all material handling vehicles, this paper examines two different scenarios and establishes goal programming models. The appropriate locations for material handling vehicle swapping stations and vehicle battery pack scheduling schemes are then developed using the NSGA-II algorithm and ant colony optimization algorithm. The results show that, while ensuring a daily transportation volume of no less than 300 vehicles, the lowest investment and operational cost over a 3-year settlement period is approximately 24.1 million Yuan. The material handling vehicles follow the shortest path of 119.2653 km passing through the designated retrieval points and have two shortest routes. Furthermore, the advantages and disadvantages of the proposed models are analyzed, followed by an evaluation, deepening, and potential extension of the models. Finally, future research directions in this field are suggested.

如何管理你的钱

1 Although money cannot buy you happi⁃ness,it can bring a sense of security if you manage your money right.Without a handle on money management,you may always feel like your life is one step away from a financial cliff.The following money management tips can help.2 Set up right bank accounts.

Maximizing the Efficiency of Automation Solutions with Automation 360: Approaches for Developing Subtasks and Retry Framework

I present a solution that explores the use of A360 subtasks as a comparable concept to functions in programming. By leveraging subtasks as reusable and maintainable functions, users can efficiently develop customized high-quality automation solutions. Additionally, the paper introduces the retry framework, which allows for the automatic retrying of subtasks in the event of system or unknown exceptions. This framework enhances efficiency and reduces the manual effort required to retrigger bots. The A360 Subtask and Retry Framework templates provide valuable assistance to both professional and citizen developers, improving code quality, maintainability, and the overall efficiency and resiliency of automation solutions.