An analysis of the interaction mechanism between the social history of medicine research and health communication from the perspective of mass communication

The mass communication model and interactive ritual chain theory,which serve as communication paradigms in the new media era,facilitate and enhance the synergy between the fields of social history of medicine and health communication.This study employs a comprehensive framework based on the five elements of the mass communication model:information source,communication subject,communication object,message content,and post-communication feedback.Additionally,it incorporates the interactive ritual chain theory to examine the evolving dynamics and developmental trajectory of research in the social history of medicine during the new media era.Conclusively,this paper acknowledges the existing interaction gaps in the interaction between health communication and the social history of medicine research while outlining the challenges for fostering collaboration and proposing strategic optimizations for effective integration.

Targeted multi-agent communication algorithm based on state control

As an important mechanism in multi-agent interaction,communication can make agents form complex team relationships rather than constitute a simple set of multiple independent agents.However,the existing communication schemes can bring much timing redundancy and irrelevant messages,which seriously affects their practical application.To solve this problem,this paper proposes a targeted multiagent communication algorithm based on state control(SCTC).The SCTC uses a gating mechanism based on state control to reduce the timing redundancy of communication between agents and determines the interaction relationship between agents and the importance weight of a communication message through a series connection of hard-and self-attention mechanisms,realizing targeted communication message processing.In addition,by minimizing the difference between the fusion message generated from a real communication message of each agent and a fusion message generated from the buffered message,the correctness of the final action choice of the agent is ensured.Our evaluation using a challenging set of Star Craft II benchmarks indicates that the SCTC can significantly improve the learning performance and reduce the communication overhead between agents,thus ensuring better cooperation between agents.

Effects of nursing team communication and collaboration on treatment outcomes in intensive care unit patients with severe pneumonia

BACKGROUND Severe pneumonia is a common severe respiratory infection worldwide,and its treatment is challenging,especially for patients in the intensive care unit(ICU).AIM To explore the effect of communication and collaboration between nursing teams on the treatment outcomes of patients with severe pneumonia in ICU.METHODS We retrospectively analyzed 60 patients with severe pneumonia who were treated at the ICU of the hospital between January 1,2021 and December 31,2023.We compared and analyzed the respiratory mechanical indexes[airway resistance(Raw),mean airway pressure(mPaw),peak pressure(PIP)],blood gas analysis indexes(arterial oxygen saturation,arterial oxygen partial pressure,and oxygenation index),and serum inflammatory factor levels[C-reactive protein(CRP),procalcitonin(PCT),cortisol(COR),and high mobility group protein B1(HMGB1)]of all patients before and after treatment.RESULTS Before treatment,there was no significant difference in respiratory mechanics index and blood gas analysis index between 2 groups(P>0.05).However,after treatment,the respiratory mechanical indexes of patients in both groups were significantly improved,and the improvement of Raw,mPaw,plateau pressure,PIP and other indexes in the combined group after communication and collaboration with the nursing team was significantly better than that in the single care group(P<0.05).The serum CRP and PCT levels of patients were significantly decreased,and the difference was statistically significant compared with that of nursing group alone(P<0.05).The levels of serum COR and HMGB1 before and after treatment were also significantly decreased between the two groups.CONCLUSION The communication and collaboration of the nursing team have a significant positive impact on respiratory mechanics indicators,blood gas analysis indicators and serum inflammatory factor levels in the treatment of severe pneumonia patients in ICU.

Study on DeviceNet communication mechanism and its application in protection measurement and control system

To fit in with the developing requirement of int and communication of protective relays, a protection egrated functions of protection measurement, control measurement and control system based on DeviceNet fieldbus is designed. The communication mechanism of DeviceNet is studied and data trigger modes, communication connection, message types and other key technologies are analyzed. The object modeling and device description of the device are realized too. Results of network test, dynamic simulation and test in the field indicate that this system can accomplish all the communication tasks in real time and can make precise response to every kind of faults of the motor, transformer, line and capacitor. Moreover, this system has higher measurement precision and better control capability.

A dynamic incentive and reputation mechanism for energy-efficient federated learning in 6G

As 5G becomes commercial,researchers have turned attention toward the Sixth-Generation(6G)network with the vision of connecting intelligence in a green energy-efficient manner.Federated learning triggers an upsurge of green intelligent services such as resources orchestration of communication infrastructures while preserving privacy and increasing communication efficiency.However,designing effective incentives in federated learning is challenging due to the dynamic available clients and the correlation between clients'contributions during the learning process.In this paper,we propose a dynamic incentive and reputation mechanism to improve energy efficiency and training performance of federated learning.The proposed incentive based on the Stackelberg game can timely adjust optimal energy consumption with changes in available clients during federated learning.Meanwhile,clients’contributions in reputation management are formulated based on the cooperative game to capture the correlation between tasks,which satisfies availability,fairness,and additivity.The simulation results show that the proposed scheme can significantly motivate high-performance clients to participate in federated learning and improve the accuracy and energy efficiency of the federated learning model.

Handover Mechanism Based on Underwater Hybrid Software-Defined Modem in Advanced Diver Networks

For the past few decades,the internet of underwater things(IoUT)otained a lot of attention in mobile aquatic applications such as oceanography,diver network monitoring,unmanned underwater exploration,underwater surveillance,location tracking system,etc.Most of the IoUT applications rely on acoustic medium.The current IoUT applications face difficulty in delivering a reliable communication system due to the various technical limitations of IoUT environment such as low data rate,attenuation,limited bandwidth,limited battery,limited memory,connectivity problem,etc.One of the significant applications of IoUT include monitoring underwater diver networks.In order to perform a reliable and energy-efficient communication system in the underwater diver networks,a smart underwater hybrid softwaredefined modem(UHSDM)for the mobile ad-hoc network was developed that is used for selecting the best channel/medium among acoustic,visible light communication(VLC),and infrared(IR)based on the criteria established within the system.However,due to the mobility of underwater divers,the developed UHSDMmeets the challenges such as connectivity errors,frequent link failure,transmission delay caused by re-routing,etc.During emergency,the divers are most at the risk of survival.To deal with diver mobility,connectivity,energy efficiency,and reducing the latency in ADN,a handover mechanism based on pre-built UHSDM is proposed in this paper.This paper focuses on(1)design of UHSDM for ADN(2)propose the channel selection mechanism in UHSDM for selecting the best medium for handover and(3)propose handover protocol inADN.The implementation result shows that the proposed mechanism can be used to find the new route for divers in advance and the latency can be reduced significantly.Additionally,this paper shows the real field experiment of air tests and underwater tests with various distances.This research will contribute much to the profit of researchers in underwater diver networks and underwater networks,for improving the quality of services(QoS)of underwater applications.

Dynamic modelling and engineering simulation of fluid mechanics in water injectors

To study the fluid dynamic response mechanism under the working condition of water injection well borehole,based on the microelement analysis of fluid mechanics and the classical theory of hydrodynamics,a fluid microelement pressure-flow rate relationship model is built to derive and solve the dynamic distribution of fluid pressure and flow rate in the space of well borehole.Combined with the production data of a typical deviated well in China,numerical simulations and analyses are carried out to analyze the dynamic distribution of wellbore pressure at different injection pressures and injection volumes,the delayed and attenuated characteristics of fluid transmission in tube,and the dynamic distribution of wellbore pressure amplitude under the fluctuation of wellhead pressure.The pressure loss along the wellbore has nothing to do with the absolute pressure,and the design of the coding and decoding scheme for wave code communication doesn’t need to consider the absolute pressure during injecting.When the injection pressure is constant,the higher the injection flow rate at the wellhead,the larger the pressure loss along the wellbore.The fluid wave signal delay amplitude mainly depends on the length of the wellbore.The smaller the tubing diameter,the larger the fluid wave signal attenuation amplitude.The higher the target wave code amplitude(differential pressure identification root mean square)generated at the same well depth,the greater the wellhead pressure wave amplitude required to overcome the wellbore pressure loss.

The functions of exosomes targeting astrocytes and astrocyte-derived exosomes targeting other cell types

Astrocytes are the most abundant glial cells in the central nervous system;they participate in crucial biological processes,maintain brain structure,and regulate nervous system function.Exosomes are cell-derived extracellular vesicles containing various bioactive molecules including proteins,peptides,nucleotides,and lipids secreted from their cellular sources.Increasing evidence shows that exosomes participate in a communication network in the nervous system,in which astrocyte-derived exosomes play important roles.In this review,we have summarized the effects of exosomes targeting astrocytes and the astrocyte-derived exosomes targeting other cell types in the central nervous system.We also discuss the potential research directions of the exosome-based communication network in the nervous system.The exosome-based intercellular communication focused on astrocytes is of great significance to the biological and/or pathological processes in different conditions in the brain.New strategies may be developed for the diagnosis and treatment of neurological disorders by focusing on astrocytes as the central cells and utilizing exosomes as communication mediators.

Dynamic Event-Triggered Consensus Control for Input Constrained Multi-Agent Systems With a Designable Minimum Inter-Event Time

This paper investigates the consensus control of multi-agent systems(MASs) with constrained input using the dynamic event-triggered mechanism(ETM).Consider the MASs with small-scale networks where a centralized dynamic ETM with global information of the MASs is first designed.Then,a distributed dynamic ETM which only uses local information is developed for the MASs with large-scale networks.It is shown that the semi-global consensus of the MASs can be achieved by the designed bounded control protocol where the Zeno phenomenon is eliminated by a designable minimum inter-event time.In addition,it is easier to find a trade-off between the convergence rate and the minimum inter-event time by an adjustable parameter.Furthermore,the results are extended to regional consensus of the MASs with the bounded control protocol.Numerical simulations show the effectiveness of the proposed approach.

Impact of Artificial Intelligence on Corporate Leadership

Artificial Intelligence (AI) is transforming organizational dynamics, and revolutionizing corporate leadership practices. This research paper delves into the question of how AI influences corporate leadership, examining both its advantages and disadvantages. Positive impacts of AI are evident in communication, feedback systems, tracking mechanisms, and decision-making processes within organizations. AI-powered communication tools, as exemplified by Slack, facilitate seamless collaboration, transcending geographical barriers. Feedback systems, like Adobe’s Performance Management System, employ AI algorithms to provide personalized development opportunities, enhancing employee growth. AI-based tracking systems optimize resource allocation, as exemplified by studies like “AI-Based Tracking Systems: Enhancing Efficiency and Accountability.” Additionally, AI-powered decision support, demonstrated during the COVID-19 pandemic, showcases the capability to navigate complex challenges and maintain resilience. However, AI adoption poses challenges in human resources, potentially leading to job displacement and necessitating upskilling efforts. Managing AI errors becomes crucial, as illustrated by instances like Amazon’s biased recruiting tool. Data privacy concerns also arise, emphasizing the need for robust security measures. The proposed solution suggests leveraging Local Machine Learning Models (LLMs) to address data privacy issues. Approaches such as federated learning, on-device learning, differential privacy, and homomorphic encryption offer promising strategies. By exploring the evolving dynamics of AI and leadership, this research advocates for responsible AI adoption and proposes LLMs as a potential solution, fostering a balanced integration of AI benefits while mitigating associated risks in corporate settings.

Understanding the mechanism of social tie in the propagation process of social network with communication channel

The propagation of information in online social networks plays a critical role in modern life,and thus has been studied broadly.Researchers have proposed a series of propagation models,generally,which use a single transition probability or consider factors such as content and time to describe the way how a user activates her/his neighbors.However,the research on the mechanism how social ties between users play roles in propagation process is still limited.Specifically,comprehensive summary of factors which affect user’s decision whether to share neighbor’s content was lacked in existing works,so that the existing models failed to clearly describe the process a user be activated by a neighbor.To this end,in this paper,we analyze the close correspondence between social tie in propagation process and communication channel,thus we propose to exploit the communication channel to describe the information propagation process between users,and design a social tie channel(STC)model.The model can naturally incorporate many factors affecting the information propagation through edges such as content topic and user preference,and thus can effectively capture the user behavior and relationship characteristics which indicate the property of a social tie.Extensive experiments conducted on two real-world datasets demonstrate the effectiveness of our model on content sharing prediction between users.

基于注意力机制的LSTM时变水声信道深度学习预测

This paper investigates the channel prediction algorithm of the time-varying channels in underwater acoustic(UWA)communication systems using the long short-term memory(LSTM)model with the attention mechanism.AttLstmPreNet is a deep learning model that combines an attention mechanism with LSTM-type models to capture temporal information with different scales from historical UWA channels.The attention mechanism is used to capture sparsity in the time-delay scales and coherence in the gep-time scale under the LSTM framework.The soft attention mechanism is introduced before the LSTM to support the model to focus on the features of input sequences and help improve the learning capacity of the proposed model.The performance of the proposed model is validated using different simulation time-varying UWA channels.Compared with the adaptive channel predictors and the plain LSTM model,the proposed model is better in terms of channel prediction accuracy.

A Systematic Overview of Underwater Wireless Sensor Networks:Applications,Challenge and Research Perspectives

Underwater Wireless Sensor Networks(UWSNs)are becoming increasingly popular in marine applications due to advances in wireless and microelectronics technology.However,UWSNs present challenges in processing,energy,and memory storage due to the use of acoustic waves for communication,which results in long delays,significant power consumption,limited bandwidth,and packet loss.This paper provides a comprehensive review of the latest advancements in UWSNs,including essential services,common platforms,critical elements,and components such as localization algorithms,communication,synchronization,security,mobility,and applications.Despite significant progress,reliable and flexible solutions are needed to meet the evolving requirements of UWSNs.The purpose of this paper is to provide a framework for future research in the field of UWSNs by examining recent advancements,establishing a standard platform and service criteria,using a taxonomy to determine critical elements,and emphasizing important unresolved issues.

城市社区慢性病管理模式及工作机制的实践探索

慢性病已经成为影响居民健康的重大公共卫生问题,社区慢性病管理对控制慢性病流行具有现实意义。本文在现场调查基础上,对社区卫生服务机构开展以团队服务为主导的慢性病管理模式及其相关管理机制进行了初步总结和探讨,为促进我国社区慢性病管理提供政策建议。

论完善健康诊疗机制于少数民族地区精准脱贫的意义——以迪庆藏族自治州德钦县为例

实现少数民族地区精准脱贫是全面建设小康社会过程中的一步重要战略。因历史与现实、自然与人文等客观因素的影响,少数民族地区居民普遍面临着看病难、看病贵的困难,而且一些地方性慢性非传染性疾病常常成为当地居民致贫、返贫的重要因素之一。科学处理好这一问题不但有助于实现精准扶贫脱贫目标,而且还能为实现乡村振兴打下坚实基础。在云南省德钦县所开展的藏族糖尿病视网膜病变防治实践取得了积极成效,探索出一条既能明显降低医疗费用以解决因病致贫、因病返贫问题,又能给予病患及时有效治疗、促进生产发展的精准健康扶贫脱贫方式,即:通过微信网络群建立乡、县、省三级医疗机构协同诊断治疗体系,建立糖尿病视网膜病变诊疗和随访系统,建立糖尿病视网膜病变的眼底图像数据库,对糖尿病患者进行早期干预治疗和定期随访的方法。这样的方法实现了"小病不出乡,中病不出县,大病才到省"的目的,为科学地开展健康扶贫脱贫提供了可资借鉴的经验。

部分国家慢性病防控机制的经验和启示

慢性病已经成为威胁人类健康的主要危险因素之一,慢性病的预防和控制意义重大。而我国的慢性病防控机制尚未成熟,这在很大程度上制约了我国慢性病防控事业的发展。本文对美国、德国、芬兰、新加坡四个发达国家慢性病防控工作的机制进行分析,并总结出三点经验:相互协调的防控机构、具有法律效力的防控政策、处在防控前线的社区卫生机构,进而对完善我国慢性病防控机制的构建提出了制定有力的防控政策、加强防控机构之间的配合以及健全以基层医疗卫生机构为基础的防控体系等建议。

牛分枝杆菌引起人结核病的概况和控制

牛分枝杆菌是牛结核病的病原体,也可引起人畜共患结核病。虽然由牛分枝杆菌感染引起的人结核病患者例数明显少于由结核分枝杆菌感染引起者,但由于诊断技术的局限性,现有的牛分枝杆菌感染人的流行病学数据并不能准确反映牛分枝杆菌引起的人畜共患结核病的实际流行情况。作者就牛分枝杆菌造成的人畜共患结核病负担、牛分枝杆菌的致病机制、人畜共患结核病对公共卫生的影响,以及控制措施等方面内容进行综述。

Encoding-Decoding-Based Control and Filtering of Networked Systems： Insights, Developments and Opportunities

In order to make the information transmission more efficient and reliable in a digital communication channel with limited capacity, various encoding-decoding techniques have been proposed and widely applied in many branches of the signal processing including digital communications, data compression,information encryption, etc. Recently, due to its promising application potentials in the networked systems(NSs), the analysis and synthesis issues of the NSs under various encoding-decoding schemes have stirred some research attention. However, because of the network-enhanced complexity caused by the limited network resources, it poses new challenges to the design of suitable encoding-decoding procedures to meet certain control or filtering performance for the NSs. In this survey paper, our aim is to present a comprehensive review of the encoding-decodingbased control and filtering problems for different types of NSs.First, some basic introduction with respect to the coding-decoding mechanism is presented in terms of its engineering insights,specific properties and theoretical formulations. Then, the recent representative research progress in the design of the encodingdecoding protocols for various control and filtering problems is discussed. Some possible further research topics are finally outlined for the encoding-decoding-based NSs.

Analysis of wave propagation on human body based on stratified media model

Human body communication(HBC) is a promising near-field communication(NFC) method emerging in recent years. But existing theoretical models of HBC are too simple to simulate the wave propagation on human body. In this work, in order to clarify the propagation mechanism of electromagnetic wave on human body, a surface waveguide HBC theoretical model based on stratified media cylinder is presented. A numerical model analyzed by finite element method(FEM) is used for comparing and validating the theoretical model. Finally, results of theoretical and numerical models from 80 MHz to 200 MHz agree fairly well, which means that theoretical model can characterize accurate propagation mechanism of HBC signal. Meanwhile, attenuation constants derived from two kinds of models are within the range from 1.64 to 3.37, so that HBC signal can propagate effectively on human body. The propagation mechanism derived from the theoretical model is useful to provide design information for the transmitter and the modeling of the propagation channel in HBC.

Spatio-temporal Fragmentation of Leisure Activities in Information Era： Empirical Evidence from Nanjing, China

Activity fragmentation provides a new approach for understanding the transformation of urban space and function in the information era. Numerous theoretical and empirical studies have been conducted on activity fragmentation, but few studies have focused on the fragmentation of leisure activities. This study was intended to extend the extant literature by: 1) analysing the spatio-temporal fragmentation of physical and virtual leisure activities by using a dataset collected in Nanjing, China, and 2) evaluating the reasons of leisure activity fragmentation, as well as the potential spatial effect of activity fragmentation. The results indicated that virtual leisure activities are more fragmented than physical leisure activities, but the fragmentation of physical and virtual leisure activities varies on weekday and weekend, as well as in various locations and urban districts. In addition, the results suggested that sociodemographic factors and information and communication technology(ICT) variables distinctly affect the fragmentation of leisure activities. Meanwhile, the fragmentation of virtual leisure activities may enhance the transformation of traditional urban space by reallocating leisure activity times and locations.