Feedback Transmission Research Articles

Investigation of arm stabilization with proprioceptive sensory reflex pathways on a 2-DoF musculoskeletal robot actuated by pneumatic artificial muscles

ABSTRACT The proprioceptive sensory reflex (e.g. stretch reflex) plays an important role in perturbed arm stabilization. Neuroscience studies have widely identified the heteronymous spinal pathways in the human arm, which may contribute to stabilized movement. However, their interactions in living systems pose challenges for specific functional investigations through human experiments. Therefore, this paper concentrates on understanding the effects of two heteronymous pathways, specifically the transmission of monoarticular sensory feedback to innervate biarticular muscles, using the robot. We replicate specific reflex pathways on a 2-DoF musculoskeletal robot equipped with pneumatic artificial muscles. By adjusting the weights of pathways, which resemble human motor control, we evaluate our robot arm performance under the forearm and upper arm disturbances. The outcomes validate their effects on regulating biarticular muscle stimulation, resulting in more stable and coordinated end-effectory trajectories. These reflexive pathways provide insights into the mechanisms underlying human arm perturbations and stabilization. Additionally, the proposed bioinspired system with applicable reflex weights holds great potential in the adaptive response of musculoskeletal robots, guiding robotics researchers in controller design.

Lumbar joint position sense measurement of patients with low back pain.

Lumbar position sense can be assessed by measurement instruments including the goniometer, isokinetic dynamometry, and electronic motion monitoring equipment, which have demonstrated relatively high reliability. This literature provides a comprehensive overview of influencing factors of lumbar position sense measurement, including repositioning method, fatigue degree, and posture during the reposition. It highlights the significant role of muscle proprioception, which contributes to greater accuracy in active reposition compared to passive reposition. The differences in lumbar position sense with different measurement positions may be explained by the presence of mechanoreceptors in the load-bearing structures of the lumbar spine, especially in the facet joint capsules. These mechanoreceptors play a crucial role in providing sensory feedback and proprioceptive information pertaining to the position and movement of the lumbar spine. Individuals with low back pain (LBP) demonstrate alterations in lumbar position sense compared to those without LBP. The auto motor sensory feedback transmission mechanism of patients with non-specific LBP was more unstable than that of healthy people. These findings suggest that lumbar position sense may play a potential role in the development and perpetuation of LBP. At present, the commonly used clinical assessment methods for determining position sense include both active and passive repositioning. However, neither method exhibits high sensitivity and specificity, leading to the poor comparability of relevant studies and posing challenges for clinical application.

Analysis of the Advantages and Disadvantages of Film Short Video Official Account Marketing

Under the background that short video platform has become an important channel of film marketing, opening a short film video official account has become a standard action for film marketing. To find out the advantages and disadvantages of short film video official account marketing is the premise of maximizing marketing effect. Its marketing advantages include autonomy and association of execution, richness and infectivity of information, immediacy and free transmission, precision and participation of objects, feedback and detonation of effects. The disadvantages of its marketing are the duality and interference of noise, the triviality and weak energy of information, and the difficulty to control and predict the effect.

The impact of foreign direct investment, renewable and non-renewable energy consumption, and natural resources on ecological footprint: an Indian perspective

PurposeGlobally, India ranks third in greenhouse gas (GHGs) emissions. Decarbonizing India's economy would necessitate significant changes in how the country generates energy, manufactures things, delivers services and manages natural resources. Recently, scholars from different parts of the world have used various indicators like carbon and methane emissions to investigate potential solutions to the global warming problem that has resulted in climate change. Therefore, this study aims to investigate the impact of foreign direct investment, renewable and non-renewable energy consumption, in addition to economic growth, trade openness, and natural resources on ecological footprint.Design/methodology/approachUsing India's yearly data from 1990 to 2016, this research investigates the impact of direct foreign investment (FDI), trade (TA) and natural resources (NR) on the ecological footprint (EF) within the framework of economic growth (GDP), renewable (RE) and non-renewable (NRE) energy consumption. The Zivot–Andrews unit root approach was used to examine the structural breaks in data series and the presence of stationary. An auto regressive distributive lag model was used to investigate the presence of long-run and short-run dynamic relationships among the variables.FindingsThe empirical findings demonstrate that FDI, RE and GDP have a negative and substantial impact on EF in the long term; in contrast, NRE and TA are significant and positive. The Granger causality test indicates that feedback transmission was observed between NR and EF and TA and EF. One-way causation passed from GDP to FDI and NR; TA to FDI and RE.Originality/valueIndian Government and authorities should push for an eco-friendly manufacturing process and technology adaptation to improve environmental quality.

Machine learning-based adaptive CSI feedback interval

The channel state information (CSI) is essential for the base station (BS) to schedule user equipments (UEs) and efficiently manage the radio resources. Hence, the BS requests UEs to regularly feed back the CSI. However, frequent CSI reporting causes large signaling overhead. To reduce the feedback overhead, we propose two machine learning-based approaches to adjust the CSI feedback interval. We use a deep neural network and reinforcement learning (RL) to decide whether an UE feeds back the CSI. Simulation results show that the RL-based approach achieves the lowest mean squared error while reducing the number of CSI feedback transmissions.

Moderating effect of institutional policies on energy and technology towards a better environment quality: A two dimensional approach to China's sustainable development

Our study contributes towards identifying the world best practises and possible ways of attaining China's climate and sustainable goals. China is among the fastest growing emerging economies in the world, and its growth cannot be separated from utilization of energy sources which are capable of jeopardizing its climate and sustainable goals. China is ranked 1st in the global carbon emission which has great implications in both its domestic environment sustainable development and global climate change. Considering the position of China in the global economic and environmental performance, it is essential to investigate the possible global best practices to achieve its sustainable development. We utilized China's data of 1996Q1-2018Q4 for this study. Relevant instruments (renewable energy, technology innovation and institution) and methodology (Autoregressive Distributed Lag-ARDL bound and dynamics with granger causality) are adopted to scientifically test both the economic and environment performance of China. Findings from ARDL test established non validity of inverted U-shaped theory of Environmental Kuznets Curve (EKC) for the case of China. Also, inverse relationship is established between all the selected variables (renewable energy, technological innovation and institution) and the CO2. Interestingly, the output from granger causality is in synergy with the output from ARDL short and long run outputs. Feedback transmission was found between the variables (renewable energy, technological innovation and institution) of our choice with both environment (carbon dioxide emissions-CO2) and economic growth (Gross Domestic Product-GDP). The trend of relationship established between the selected variables (renewable energy, technology innovation and institution) points towards China's ability to achieve its climate and sustainable goal by framing its policy around energy sector and enhancement of technology with strong institutions.

Research on Effective Strategies of College Physical Education Interactive Teaching Based on Machine Learning.

To master physical education courses, you must master a complete set of skills and knowledge. Most teachers still adopt traditional teaching forms, teacher centered, which has a negative impact on students. Because learners only passively participate in activities, it reduces students' enthusiasm and focus to master skills. This study is aimed at comparing and contrasting the differences between modern interactive learning and traditional teaching strategies. We collect qualitative and quantitative results about the impact of these studies on students' communication skills and understanding of relevant topics. The form of the noninteractive learning strategies explored in this study is the teaching system. This is a commonly used method and is still used in some institutions. Its limitations have led to the modernization of the education sector, especially in sports. This modernization brings about other forms of physical education, being student centered and more interactive. This form of interaction promotes the connection between teachers and students and promotes the transmission of feedback and the continuous improvement and novelty of activity forms. The interactive approach used in this study is the brainstorming method. Research has found it to generate constructive ideas and ideas. The specific process includes case study and Q & A, which is intuitive and clear, and can enhance the comprehensive understanding of the theme. The modernization of physical education curriculum brings many benefits; some of which will be listed in this paper. This study is aimed at promoting more display of students' personality in modern physical education teaching with clear research conclusions. Let the students in the training interact with teachers and interact with the group, in the interaction to play their own greater initiative, enthusiasm. Let the relationship between students and teachers be more harmonious, and let the students' physical quality get better development.

Priorities of the Ukraine’s public diplomacy in the early 2020s

The purpose of the Ukraine’s public diplomacy, like those of other countries, is led by a strong objective to reach out to foreign publics to secure its national interests. The article contemplates the public diplomacy of Ukraine such as being at the present stage of its further formation, alongside a focus on the main priorities and basic preferences among the scope of activities considered in the various legislative acts and laws. The number of the documents, on the basis of which the norms of the Ukrainian public diplomacy are stationed, are indicated thoroughly. Regarding the foregoing, the aim is to identify the most important areas of the Ukrainian public diplomacy, involving the press, taking into account trends and events in the world that diverse and expand to the future. All over the text, the author assigns high priority to the role of the mass media in its transmission of the essential feedback about the state and the development of the image of Ukraine according to a public thought abroad. With the help of mass media, Ukraine use various instruments of public communication to establish trust between her and more well-off governments in the West. The author points out the need for close cooperation between diplomats and the press during the actual campaigns that vary and the events within the public diplomacy. This resulted in the issue of a research conclusions made by the author, collecting together the ideas that have been made during the investigation. Among the numerous directions set by the MFA of Ukraine and other government intuitions, the main priorities of the public diplomacy in the early 2020ies can be divided into three categories. They are: improving Ukraine’s image abroad; revealing its individuality in the dynamics of cultural transformations; and creating a positive narratives for a public image of Ukraine for the global audience.

Weighted Online Fountain Codes With Limited Buffer Size and Feedback Transmissions

Online fountain codes (OFC) have attracted much attention for their good intermediate performance, which is important for receivers with low-complexity requirement. However, low-complexity receivers generally have limited buffer size to store coded symbols that have not been fully decoded yet, as well as limited power budget for feedback transmissions. In this paper, we propose improved transmission schemes for online fountain codes to reduce the buffer occupancy and feedback transmissions. Firstly, we analyze the relationship between buffer occupancy and overhead as well as the relationship between recovery rate and overhead for online fountain codes. Motivated by the analysis, we propose the weighted online fountain codes (WOFC) which can adapt to various buffer sizes by adjusting the weight to control the probability that a coded symbol can be fully processed immediately, and analyze its performance. Then we further propose weighted online fountain codes with low feedback (WOFC-LF), which utilize the proposed analysis to estimate the recovery rate, and reduce feedback transmissions. Simulation results verify the effectiveness of the analysis for both OFC and WOFC, and demonstrate the superior performance of WOFC-LF with limited buffer size and feedback transmissions.

Risk transmission between old and new energy markets from a multi-scale perspective: the role of the EU emissions trading system

ABSTRACT The trading market of carbon emission permits is not only an effective tool for tackling climate change, but it also reinforces the connection between carbon and energy markets by risk transmission. This paper investigates the volatility spillover effects and dynamic correlation between fossil energy, clean energy and the European Union carbon markets by applying the asymmetric BEKK- and DCC-GARCH models in a time-frequency framework and designs the portfolio strategies. Empirical results display that fossil energy market has a significantly positive impact on the clean energy market at most scales, but the feedback transmission is relatively weak. Two indirect volatility spillover effects exist between the three markets, which are ‘fossil energy→carbon→clean energy’ and ‘clean energy→carbon→fossil energy’, suggesting that the carbon market plays a vital role in bridging the clean and fossil energy markets. Significant time-varying asymmetric effects are identified between the three markets, and the carbon market is confirmed to offer the least expensive hedge to an investment in oil. Our findings can provide meaningful implications for policymakers to design market mechanism and investors to adjust hedging strategies and diversify their portfolios.

Information Transmission in Delay-Coupled Neuronal Circuits in the Presence of a Relay Population.

Synchronization between neuronal populations is hypothesized to play a crucial role in the communication between brain networks. The binding of features, or the association of computations occurring in spatially segregated areas, is supposed to take place when a stable synchronization between cortical areas occurs. While a direct cortico-cortical connection typically fails to support this mechanism, the participation of a third area, a relay element, mediating in the communication was proposed to overcome this limitation. Among the different structures that could play the role of coordination during the binding process, the thalamus is the best placed region to carry out this task. In this paper we study how information flows in a canonical motif that mimics a cortico-thalamo-cortical circuit composed by three mutually coupled neuronal populations (also called the V-motif). Through extensive numerical simulations, we found that the amount of information transferred between the oscillating neuronal populations is determined by the delay in their connections and the mismatch in their oscillation frequencies (detuning). While the transmission from a cortical population is mostly restricted to positive detuning, transmission from the relay (thalamic) population to the cortical populations is robust for a broad range of detuning values, including negative values, while permitting feedback communication from the cortex at high frequencies, thus supporting robust bottom up and top down interaction. In this case, a strong feedback transmission between the cortex to thalamus supports the possibility of robust bottom-up and top-down interactions in this motif. Interestingly, adding a cortico-cortical bidirectional connection to the V-motif (C-motif) expands the dynamics of the system with distinct operation modes. While overall transmission efficiency is decreased, new communication channels establish cortico-thalamo-cortical association loops. Switching between operation modes depends on the synaptic strength of the cortico-cortical connections. Our results support a role of the transthalamic V-motif in the binding of spatially segregated cortical computations, and suggest an important regulatory role of the direct cortico-cortical connection.

Model-Based adaptive event-Triggered control of nonlinear continuous-Time systems

This paper presents a model-based adaptive event-triggered control scheme for a class of uncertain single-input and single-output nonlinear continuous-time systems. To this aim, the explicit design of an associated controller is proposed by constructing an adaptive model, exploiting the principle of feedback linearization and using neural networks to approximate an unknown smooth nonlinear function. Then, the stability of the resulting impulsive dynamic system is strictly proved by using the Lyapunov stability theory, and the event-trigger condition is designed to realize that the NN weights and feedback signals are updated only when the condition is violated. In addition, the lower bound of inter-event times is strictly proved to be positive, which effectively avoids Zeno behavior. Compared with the conventional adaptive control based on the time-triggered scheme, feedback transmissions and NN weight updating only occur at necessary instants, such that the waste of communication resources is effectively reduced. Finally, the effectiveness of the developed control algorithm is verified by a simulation example.

Achievable Error Exponents of One-Way and Two-Way AWGN Channels

Achievable error exponents for the one-way with noisy feedback and two-way AWGN channels are derived for the transmission of a finite number of messages M under almost sure (AS) and expected block (EXP) transmit power constraints. In the one-way setting under noisy AWGN feedback, under an AS power constraint, known linear and non-linear passive schemes are modified to incorporate AS constraints in the feedback link as well. In addition, a new active feedback scheme is presented in which the receiver feeds back the most likely pair of codewords, and the transmitter re-transmits which of these two was originally sent. This active feedback scheme outperforms one of the passive feedback schemes for all channel parameters; the linear scheme outperforms the others for low feedback noise variance. Under the EXP constraint, a known achievable error exponent for the transmission of two messages is generalized to any arbitrary but finite number of messages M through the use of simplex codes and erasure decoding. In the two-way AWGN setting, each user has its own message to send in addition to (possibly) aiding in the transmission of feedback for the opposite direction. Two-way error exponent regions are defined and achievable error exponent regions are derived for the first time under both AS and EXP power constraints. For the presented achievability schemes, feedback or interaction leads to error exponent gains in one direction, possibly at the expense of a decrease in the error exponents attained in the other direction. The relationship between M and n supported by our achievable strategies is explored.

STPA-Based Hazard and Importance Analysis on NPP Safety I&C Systems Focusing on Human–System Interactions

To ensure system safety, conducting required control actions (CAs) in time at the right place is essential. Among the CAs, safety critical ones such as reactor trip signals in a nuclear power plant are preferentially and automatically generated by the instrumentation and control (I&C) system. If necessary, however, they can also be generated manually by human operators. Even for manual CAs, though, the I&C system is still needed to convey relevant feedback to the human operators. It is therefore indispensable to analyze the risk associated with the transmission of feedback to the human operators in terms of the condition of the I&C system. In this context, System-Theoretic Process Analysis (STPA) can provide a framework to link the conditions of the I&C system with the feedback transmission for manual CA generation. Based on STPA, this study proposes a method to analyze I&C system hazards and assess the relative importance of system components in terms of human–system interactions, or more specifically, feedback transmission for manual CA generation. As a feasibility study, the method is applied to an example case requiring reactor trip signal generation in the Advanced Power Reactor 1400 (APR-1400).

Efficient and Reliable Wireless Communications via Multi-Connectivity Using Rateless Codes in Single- and Multi-User Scenarios

Due to the great flexibility and innate simplicity of wireless networks, many applications are now realized with wireless connectivity at their core. Countless novel applications are enabled this way and legacy applications are transferred to mobile networks to reap the same benefits. As the networks evolve, applications are becoming ever more demanding, particularly with respect to high reliability and low latency. A common way to achieve high reliability in wireless communications is adding redundant communication channels by means of multi-connectivity. This comes at the cost of additional radio resources that could have been used by other connections. However, multiple links are not always required to achieve the desired reliability. Thus, we propose to combine multi-connectivity with rateless coding as a strategy for efficient resource usage in reliable wireless communications. The proposed schemes consider an erasure channel, and can therefore be implemented on the application layer, making them suitable for use with different physical layer wireless technologies simultaneously. We start out with a single-user analysis and then extend our discussion to multi-user scenarios. Our approach is compared against standardized packet duplication with our analytical framework and by means of simulation. The results with rateless coding show significant gains with respect to the required resources and feedback transmissions.

Supervisors’ Leadership Styles’ Influence on Foreign Teachers’ Self-Efficacy in a Cross-Cultural Work Setting: A Moderated Mediation Analysis

Leadership style impacts on the manner and frequency of feedback transmission. However, communication challenges between superiors and subordinates originate from cultural differences, which undermine the usefulness of feedback. The study tested leadership style’s effect on self-efficacy through a moderated mediation approach, examined through the lens of the cross-cultural adaptation theory. Path analysis conducted on data from 281 foreign teachers in Chengdu, China, revealed that there is a positive effect of Chinese supervisors’ leadership styles on foreign teacher’s self-efficacy. Leadership style similarly has an influence on the nature of feedback. And the nature of feedback in turn mediates leadership style and self-efficacy. We establish in particular that transactional and transformational leadership styles, through the nature of feedback, influence self-efficacy of foreign teachers. Moreover, the association between the nature of feedback and self-efficacy is moderated by the perceived value of feedback. Employees’ perceptions are also found to be crucial in determining the value of feedback. It is thus imperative for supervisors and managers working with foreigners as subordinates to figure out when and how to provide valuable feedback. We conclude with suggested areas for further research.

Robust control design for teleoperation of multiple mobile manipulators under time delays

SummaryThis article addresses a novel multilateral teleoperation control scheme for single‐master multiple slave systems, which can be extended to n masters and n slaves without the loss of generality, where the master is a m degrees of freedom (DOF) manipulator arm and the slaves are m DOF mobile manipulators. The human operator operates the master robot to remotely control the slaves handling a target object. The master position signal is transmitted to the slave side to generate a desired object trajectory as well as the reference mobile base velocity. An adaptive robust controller is designed for the slaves to follow the desired trajectory from the master, which not only provides the excellent trajectory tracking but also optimize the internal force distribution of the object. A null space controller is designed for the mobile platforms of the mobile manipulators to achieve the velocity consensus while achieving the main task of object transportation. The novel control design uses the transmission of the environmental force feedback over the communication channel by the estimated parameters of the environment, which helps retain the stability of the overall system. The environmental force is predicted on the master side based on the estimated environmental parameters. The proposed control design can simultaneously achieve the objectives of stability, synchronization, and optimal internal force distribution. The simulation results of a single‐master and three slaves teleoperation system validate the efficacy of the proposed control algorithm.

Mediation of foreign direct investment and agriculture towards ecological footprint: a shift from single perspective to a more inclusive perspective for India.

According to the Carbon Brief Profile report by Timperley (2019), India has been identified as the world's 3rd largest emitter of greenhouse gases (GHGs) after China and the USA. Following the Paris Agreement and India's pledge as among the stakeholders at the global climate talks and how fast India ratified the Paris Agreement within a year on the 2nd of October 2016, it is essential to investigate the country's (India) commitment in reducing its emission towards enhancing a positive environmental performance. Both structural breaks, linear autoregressive distributed lag (ARDL) and nonlinear autoregressive distributed lag (NARDL), were selected simultaneously for this study, but at a later stage, after being bound to cointegration estimation, the NARDL was dropped because of its inability to sustain the claim of cointegration in the analysis. The rest of the analyses were based on liner ARDL model (short-run and long-run) with diagnostic tests, Granger causality estimation. Ecological Footprint (EFP) was chosen as an indicator to environment because of its richness in measuring the environmental performance. The linear (ARDL) output affirms a positive and significant link among ecological footprint and agriculture, energy use, and population with a negative link between ecological footprint (EFP) and foreign direct investment (FDI). The Granger causality test indicates a one-way transmission passing from agriculture, foreign direct investment, energy use, and population to ecological footprint. Also, a one-way transmission was found passing to economic growth (GDP) from foreign direct investment (FDI) and feedback transmission was found between FDI and energy use. This finding has an implication to both economic and environmental performances; hence, the policy framework should be targeting the enhancement of economy via the foreign direct investment and agriculture with a focus on energy use and environmental performance.

Spatio-Temporal Representation With Deep Neural Recurrent Network in MIMO CSI Feedback

In multiple-input multiple-output (MIMO) systems, it is crucial of utilizing the available channel state information (CSI) at the transmitter for precoding to improve the performance of frequency division duplex (FDD) networks. One of the mainchallenges is to compress a large amount of CSI in CSI feedback transmission in massive MIMO systems. In this paper, we propose a deep learning (DL)-based approach that uses a deep recurrent neural network (RNN) to learn temporal correlation and adopts depthwise separable convolution to shrink the model. The feature extraction module is also elaborately devised by studyingdecoupled spatio-temporal feature representations in different structures. Experimental results demonstrate that the proposed approach outperforms existing DL-based methods in terms of recovery quality and accuracy, which can also achieve remarkable robustness at low compression ratio (CR).

Enabling Remote Human-to-Machine Applications With AI-Enhanced Servers Over Access Networks

The recent research trends for achieving ultra-reliable and low-latency communication networks are largely driven by smart manufacturing and industrial Internet-of-Things applications. Such applications are being realized through Tactile Internet that allows users to control remote things and involve the bidirectional transmission of video, audio, and haptic data. However, the end-to-end propagation latency presents a stubborn bottleneck, which can be alleviated by using various artificial intelligence-based application layer and network layer prediction algorithms, e.g., forecasting and preempting haptic feedback transmission. In this paper, we study the experimental data on traffic characteristics of control signals and haptic feedback samples obtained through virtual reality-based human-to-machine teleoperation. Moreover, we propose the installation of edge-intelligence servers between master and slave devices to implement the preemption of haptic feedback from control signals. Harnessing virtual reality-based teleoperation experiments, we further propose a two-stage artificial intelligence-based module for forecasting haptic feedback samples. The first-stage unit is a supervised binary classifier that detects if haptic sample forecasting is necessary and the second-stage unit is a reinforcement learning unit that ensures haptic feedback samples are forecasted accurately when different types of material are present. Furthermore, by evaluating analytical expressions, we show the feasibility of deploying remote human-to-machine teleoperation over fiber backhaul by using our proposed artificial intelligence-based module, even under heavy traffic intensity.