The rowing technique is a key factor in the overall rowing performance. Nowadays the athletes’ performance is so advanced that even small differences in technique can have an impact on sport competitions. To further improve the athletes’ performance, individualized rowing is necessary. This can be achieved by intelligent measurement technology that provides direct feedback. To address this issue, we developed a novel wireless rowing measurement system (WiRMS) that acquires rowing movement and measures muscle activity using electromyography (EMG). Our measurement system is able to measure several parameters simultaneously: the rowing forces, the pressure distribution on the scull, the oar angles, the seat displacement and the boat acceleration. WiRMS was evaluated in a proof-of-concept study with seven experienced athletes performing a training on water. Evaluation results showed that WiRMS is able to assess the rower’s performance by recording the rower’s movement and force applied to the scull. We found significant correlations (p<0.001) between stroke rate and drive-to-recovery ratio. By incorporating EMG data, a precise temporal assignment of the activated muscles and their contribution to the rowing motion was possible. Furthermore, we were able to show that the rower applies the force to the scull mainly with the index and middle fingers.

Training data for a deep learning (DL) neural network (NN) controller are obtained from the input and output signals of a conventional digital controller that is designed to provide the suitable control signal to a specified plant within a feedback digital control system. It is found that if the DL controller is sufficiently deep (four hidden layers), it can outperform the conventional controller in terms of settling time of the system output transient response to a unit-step reference signal. That is, the DL controller introduces a damping effect. Moreover, it does not need to be retrained to operate with a reference signal of different magnitude, or under system parameter change. Such properties make the DL control more attractive for applications that may undergo parameter variation, like sensor networks.

In Active Flow Control (AFC) applications, to activate the boundary layer the use of pulsating flow has notorious energy advantages versus constant blowing/suction jet injections. For a given AFC application, five parameters, jet location and width, inclination angle, frequency of injection and momentum coefficient need to be tuned. Two main devices are nowadays capable of injecting pulsating flow with the sufficient momentum coefficient to delay the boundary layer separation, these are the Zero Net Mass Flow actuators (ZNMFA) and the Fluidic Oscillators (FO). In the present research, a novel FO configuration is analyzed for the first time at relatively high Reynolds numbers, fluid is considered as incompressible. After obtaining the typical linear correlation between the incoming Reynolds number and the outlet flow oscillating frequency, the effect of outlet width and mixing chamber wedge inclination angle dimensional modifications is addressed, modifications of the outlet width are observed to create large variations on the FO performance. The origin of the self-sustained oscillations is also analyzed in the present manuscript and greatly helps in clarifying the forces acting on the jet inside the mixing chamber. In fact we can conclude saying that the current FO configuration is pressure driven although the mass flow forces appear to be a much more relevant than in previous FO configurations studied.

Improving the acquisition and retention of a new motor skill is of great importance. The present study (i) investigated the effects of difficulty manipulation strategies (gradual difficulty), combined with different modalities of feedback (FB) frequency on performance accuracy and consistency when learning a novel fine motor coordination task, and (ii) examined relationships between novel fine motor task performance and executive function (EF), working memory (WM), and perceived difficulty (PD). Thirty-six, right-handed, novice physical education students volunteered to participate in this study. Participants were divided into three progressive difficulty groups (PDG), 100% visual FB (FB1), 50% FB (FB2), and 33% FB (FB3). Progressive difficulty was increased by the manipulation of the distance to the target; 2 m, 2.37 m, and 3.56 m. Three FB modalities were investigated (i.e.: 100% visual FB (100% FB), 50% reduced feedback condition (50% RFB), and 33% reduced feedback conditions (33% RFB)). Performance assessments were conducted following familiarization, acquisition, and retention learning phases. Two stress-conditions of dart throws were investigated (i.e.: free condition (FC) and time pressure condition (TPC)). After the learning intervention, data showed that, under the free condition, the 100% FB group had a significant improvement in accuracy during all learning phases. Under time pressure condition, for the 50% RFB and the 33% RFB group, the measured variable (accuracy and consistency) showed a significant linear improvement in performance. The association between the percentage of RFB frequencies and the task difficulty (50% group) may be a more appropriate and manageable cognitive load compared to the 33% RFB and the 100% FB group. The present findings could have practical implications for practitioners because, while strategies are clearly necessary for improving learning, the efficacy of the process appears to be essentially based on the characteristics of the learners.

In this paper, the design of a low cost portable ventilator with performance analysis have been done to solve the scarcity of respiratory ventilators for COVID-19 patients. The materials used to build the system are: DC motor, rotating disc and pneumatic piston. The system input is the patient heart beat and the output is volume of air to the patient lung with adjusted breathing rate. This ventilator adjusts the breathing rate to the patient depending on his heart beat rate. The performance analysis of this system have been done using Proportional Integral Derivative (PID) and Full State Feedback H2 controllers. Comparison of the system with the proposed controllers have been done using a step change and a random change of the patient heart beat and a promising result have been analyzed successfully.

The paper aims to study the workflow of the detection center of stealthy attacks on industrial installations that generate increase in energy consumption while avoiding triggering fault detection and damaging the installation. Such long-lasting attacks on industrial facilities make production more expensive and less competitive. We present the concept of the remote detection system of cyberattacks directed at maliciously changing the controlled variable in an industrial process air conditioning system. The monitored signals are gathered at the PLC-controlled installation and sent to the remote detection system, where the discrepancies of signals are analyzed based on the Control Performance Assessment indices. The results of performed tests prove the legitimacy of the adopted approach.

The uncertainty in the secondary path of an Active Noise Control (ANC) headphone affects the waterbed effect and stability of the feedback system. This study focuses on the uncertainty of the secondary path when real users wear headphones, and proposes a new uncertainty constraint based on the measured results of the secondary path transfer function under different wearing conditions of dummy head and limited subjects. This constraint and a cascaded second-order infinite impulse response filter with fixed coefficients are used to formulate a control strategic function, which is optimized by the Improved Grey Wolf Optimizer (IGWO) algorithm to obtain the optimal controller with better noise reduction performance. The proposed method and simulation model are validated based on the experimental test results. The results demonstrate that the safety factor and waterbed suppressing factor contained in the proposed uncertainty constraint ensures more stable noise reduction and effective suppression of the waterbed effect for new subjects without a priori data.

Although instructional feedback plays an essential role in regulating learning and improving performance, few studies have systematically investigated the needs of teachers and students for instructional feedback system or developed designs and experiments, especially at the high school level. To address this research need, the present study investigated the needs of selected students and teachers in a high school in Hubei Province, China, and designed and developed a diagnostic visual feedback system for an experimental study with 125 students from a 10th-grade biology class in the same high school. The results showed that this diagnostic visual feedback report improved student performance (ES=0.37) and that functions such as misconception location, knowledge diagnosis, and knowledge alert were well received by students. These findings have multiple implications for facilitating the design and development of diagnostic visual feedback system.

Students who had been actively engaged in mediated collaborative activities, were asked for their perceptions about the sustainable peer feedback they had received and provided. Their views were then analyzed and categorized in terms of receiver and provider feedback, cognitive feedback and previously acquired feedback to further knowledge about sustainable education processes. A peer supported feedback questionnaire was created and validated, and its categories were correlated. The questionnaire was then aligned with the activities used to foster peer feedback between the pre-service students from the three bachelor’s degrees. The perceptions the students had of the feedback processes were analyzed using defined peer support feedback categories and the results showed a correlation between cognitive feedback and both provider and receiver self-efficacy feedback. In addition, there was a further correlation between both provider and receiver self-efficacy feedback as well as provider and receiver involvement and feedback structure. However, the results also revealed that neither receiver nor provider autonomy support were significant categories for supportive feedback.

This paper presents a thorough review of Electrical Muscle Stimulation (EMS) in the context of Augmented Reality (AR) and Virtual Reality (VR), specifically focusing on its application in providing kinesthetic feedback. Our systematic review of 17 studies reveals the growing interest and potential of EMS in this domain, as evidenced by the growing body of literature and citations. Key elements presented in our review encompass a catalog of the applications developed to date, specifics of the stimulation parameters used, the participant demographics of the studies, and the types of measures used in these research efforts. We discovered that EMS offers a versatile range of applications in AR/VR, from simulating physical interactions like touching virtual walls or objects, to replicating the sensation of weight and impact. Notably, EMS has shown effectiveness in areas such as object handling and musical rhythm learning, indicating its broader potential beyond conventional haptic feedback mechanisms. However, our review also highlights major challenges in the research, such as inconsistent reporting of EMS parameters and a lack of diversity in study participants. These issues underscore the need for improved reporting standards and more inclusive research approaches to ensure wider applicability and reproducibility of results.

This paper proposes a contact force controller for a constrained flexible manipulator in three-dimensional motion. This controller used the conversion formula obtained empirically and experimental results showed the effectiveness of the proposed contact force controller. First, the manipulator was operated with the tip of the second link restrained, then, time response of the root strain, joint angles and contact force were used to derive the relational between the three quantities. The effectiveness of the relational expression was verified by conducting a target contact force tracking experiment by inputting the angle from the relational expression. The contact force control using the strain feedback method was proposed with the strain amount estimated from the target contact force as the target value, and its effectiveness was verified by experiments. From the results obtained, controller using the strain feedback method was designed for the purpose of controlling the contact force at the tip of a flexible manipulator with two links and three degrees of freedom that performs three-dimensional spatial motion, and its effectiveness was shown by comparison with the contact force feedback method.

In this paper, a metal cutting machine position control have been designed and simulated using Matlab/Simulink Toolbox successfully. The open loop response of the system analysis shows that the system needs performance improvement. Static output feedback and full state feedback H₂ controllers have been used to increase the performance of the system. Comparison of the metal cutting machine position using static output feedback and full state feedback H₂ controllers have been done to track a set point position using step and sine wave input signals and a promising results have been analyzed.

It has been known for a long time that many people who stutter are immediately fluent in certain conditions, for instance, when they speak in unison with others, in sync with the clicking of a metronome, or when they hear themselves speak in an altered manner. To understand why stuttering is reduced or even eliminated in such conditions is desirable because it may help understand why stuttering occurs in normal speaking conditions. However, empirical findings in this area appear conflicting and confusing, especially with regard to the role of auditory feedback. The article gives an overview of the variety and diversity of fluency-enhancing conditions and of theories proposed to explain their effect. These theories are evaluated in the light of recent empirical findings. A new hypothesis is proposed, based on findings showing that speech processing is limited without attention to the auditory channel. It is assumed that fluency-enhancing conditions draw the speaker’s attention to the auditory channel and, thereby, improve the processing of auditory feedback and its use in speech control. Implications of this account for a causal theory of stuttering and for the treatment of the disorder are discussed.

Primates have an unparalleled ability to produce a wide range of dexterous movements, each sensitive to context and robust to perturbation. Recent progress in understanding the neural basis of movement generation comes from two largely independent ideas, “Optimal Feedback Control” and “Neural Dynamical Systems”. The optimal control framework was largely inspired by research programs from the ‘80s showing that the brain doesn’t seem to plan a simple desired movement trajectory, but instead produces movements by transforming sensory information into motor output that satisfies an optimality criterion. The more recent idea that the motor cortex acts as a dynamical system came about only as it became possible to analyze large numbers of simultaneously recorded single neurons. These two framings of the motor system have been largely incommensurate, neither able to contribute much to the understanding of the other. In this review, we reconcile these two views into a single model we call “Dynamical Feedback Control”. We propose that the dynamics in the motor cortex emerge from a sensorimotor transformation that couples the motor cortex to sensory input from the periphery, and to contextual inputs from other cortical and subcortical areas. Dynamics in motor cortex can be thought to approximate gains of a feedback controller, and by moving the neural state to different regions of state space, the motor system can rapidly alternate between different controllers. The DFC framework presents a new lens to interpret neural dynamics, and to understand how ensembles of neurons generate flexible and responsive patterns of muscle activity.

Feedback is a type of formative evaluation linked to student learning and academic achievement. However, it is not known how students perceive this process since there are no instruments to measure attitudes towards feedback. The objective of this work was to develop and validate an attitude scale towards academic feedback through an Exploratory Factor Analysis (EFA), using the principal components method and an internal consistency analysis using Cronbach's Alpha. The sample consisted of 274 students from 2015, 2016, and 2017 cohorts of pedagogy careers from five Chilean universities. The results showed the consolidation of the instrument and its final conformation in four components (Negative experience towards feedback, Effectiveness of feedback, Feedback as an opportunity, and Resistance towards feedback) with a total of 15 items, which allow measuring the students' attitude towards this written formative evaluation.

This systematic literature review explores the impact of social media use (SMU) and practices (SMPs) on team feedback (TF) and performance (TP) in construction project management. The study delves into the intricate dynamics between SMU and SMPs and their influence on communication, collaboration, and stakeholder engagement within construction projects. It investigates how these digital practices reshape the traditional methods of team interaction, feedback mechanisms, and overall team performance in the complex and multifaceted environment of construction sites. The review aims to provide a comprehensive understanding of the role of social media in modern construction project management, highlighting its significance in enhancing team communication, coordination, and performance. This research is crucial for understanding the evolving landscape of construction management, where digital tools and platforms are increasingly integral to successful project outcomes. The findings are expected to offer valuable insights for professionals in the construction industry, helping them leverage social media effectively for improved project management and team collaboration.

A cross-sectional survey was distributed to 1322 members of a 1-on1 personalized strength training studio. 366 respondents (n=134 male and n=232 female), all aged over 20 years reported considerable training experience; 55% of males and 42% of females reporting 5+ years. Data were analyzed and reported descriptively with differences >5% identified based on use of the 5-point likert scale, sample size and nature of the observations. Disparity between males and females were identified; males reported higher perceptions of managing effort, technique, and programming without supervision compared to females. Safety was noted as being more important to females compared to males. Qualitatively, additional themes were raised including analogy of the personal relationship between trainer and trainee being similar to that of medical professionals. This was validated where participants discussed their adaptations from supervised strength training including quality of life in aging, and recovery from medical conditions and injury. Data is discussed in context of a previous body of literature suggesting males falsely report higher confidence in tasks compared to females, particularly in relation to effort, role models, and verbal encouragement. This research proves beneficial for strength training practitioners in enhancing their understanding and expectations of clients, as well as hopefully proving insightful in engaging more people in strength training.

The rhythmical nature of the cardiovascular system constantly generates dynamic mechanical forces. At the center of this system is the heart which must detect these changes and adjust its performance accordingly. Mechano-electric feedback provides a rapid mechanism for detecting even subtle changes in the mechanical environment and transducing these signals into electrical responses which can adjust a variety of cardiac parameters such as heart rate and contractility. However, pathological conditions can disrupt this intricate mechanosensory system and manifest as potentially life-threatening cardiac arrhythmias. Mechanosensitive ion channels are thought to be the main proponents of mechano-electric feedback as they provide a rapid response to mechanical stimulation and can directly affect cardiac electrical activity. Here we demonstrate that the mechanosensitive ion channel Piezo1 is expressed in zebrafish cardiomyocytes. Furthermore, chemically prolonging Piezo1 activation in zebrafish results in cardiac arrhythmias indicating that this ion channel plays an important role in mechano-electric feedback. This also raises the possibility that Piezo1 gain of function mutations could be linked to heritable cardiac arrhythmias such as atrial fibrillation in humans.

This paper introduces a closed-loop control strategy for maintaining consistency of ink temperature in commercial Drop on Demand (DoD) inkjet printing. No additional sensors or additional actuators are installed in the printhead while achieving the consistency in ink temperature. To this end, this paper presents a novel in situ sensing-actuation policy at every individual ink-nozzle, where the jetting mechanism has three distinct roles. It is used for jetting liquid droplet onto the print media based on the print-job. It is used as a softsensor to estimate the real-time liquid temperature of the jetting nozzle. While not jetting liquid, it is used as a heating actuator to minimize the gradient of liquid temperature among jetting nozzles. The soft-sensing based in situ controller is implemented in an experimentally validated digital twin that models the thermo-fluidic processes of the printhead. The digital twin is scalable and flexible to incorporate an arbitrary number of inknozzles, making the control strategy applicable for future designs of the printhead.

Little theoretically-informed research investigates how non-standard eyewitness identification tasks or metacognitive instructions might improve identification accuracy. We used a continuous dual-process model of recognition to explain familiarity-based identification errors and design modified lineup tasks and metacognitive instructions that increased eyewitness recollection and discriminability. In four studies we examined identification performance across lineups (standard simultaneous, elimination, delayed-choice) and instructions (task-related, phenomenological, standard). Participants viewed photos of targets and made identification decisions about a lineup for each target. Instructions about memory phenomenology improved discriminability in delayed-choice lineups, while task-related instructions were ineffective. Metacognitive instructions about how to better evaluate memory quality in modified lineup tasks could improve recollection for greater identification accuracy even when memory is poor. While immediate post-decision confidence is a good predictor of identification accuracy, lineup modifications that improve eyewitness memory use would provide better evidence of suspect guilt or innocence. We discuss implications for lineup theory and design.

In this paper a full state feedback control of a double inverted pendulum on a cart (DIPC) are designed and compared. Modeling is based on Euler-Lagrange equations derived by specifying a Lagrangian, difference between kinetic and potential energy of the DIPC system. A full state feedback control with H infinity and H 2 is addressed. Two approaches are tested: open loop impulse response and a double inverted pendulum on a cart with full state feedback H infinity and H 2 controllers. Simulations reveal superior performance of the double inverted pendulum on a cart with full state feedback H infinity controller.

The significant improvements in Generative Artificial Intelligence (GenAI) observed in recent years present Higher Education with both an opportunity and a significant challenge. Its successful integration will require careful planning and sound pedagogical underpinnings, both in regard to learning and teaching, as well as assessment and feedback. Drawing upon theories from the more-than-human world, as well as concepts such as originality, equality, and sustainability, it is possible to develop a dialogue around GenAI that places the students’ learning journey at the heart of the discussion.

This paper presents an observer-based dynamic output feedback controller design procedure using Linear Matrix Inequality (LMI) optimization for second-order systems with uncertainty and persistent perturbation in the states. Using linear-quadratic criteria, cost functions are minimized in a two-stage procedure to compute optimal state feedback gains, and observer gains are coupled into a dynamic output feedback optimal controller. The LMI set used in the two stages is matrix inversion-free, a key issue for polytope formulation when uncertainty is present. The approach is tested in a mobile inverted pendulum robotic platform, and the effectiveness is verified in this underactuated and undesensed case.

Patients with low back pain often have deficits in trunk stability. For this reason, many patients receive physiotherapy treatment, which represents an enormous socio-economic burden. Training at home could reduce these costs. The prob-lem here is the lack of correction of the exercise execution. This feasibility study therefore investigates the applicability of a vibrotactile-controlled feedback system for trunk stabilization exercises. A sample of 13 healthy adults performed three trunk stabilization exercises. Exercise performance was corrected by physiotherapists using vibrotactile feedback. The NASA TLX questionnaire was used to assess the practicability of the vibrotactile feedback. The Nasa TLX questionnaire show a very low global workload M = 37.96 (SD =11.63). The quality of feedback perception was perceived as good by the subjects, varying between 76.9 % and 92.3 % depending on the body part. 80.8 % rated the feedback as helpful for their training. On the expert side, the results show a high rating of movement quality. The positive evaluations of the physiotherapists and the participants on the use of the vibrotactile feedback system indi-cate that such a system can reduce the trainees fear of independent training and support the users in their training. This could increase training adherence and long-term success.

Feedback control plays a crucial role in improving system accuracy and stability for a variety of scientific and engineering applications. Here, we theoretically and experimentally investigate the implementation of feedback control in microwave photonic (MWP) transversal filter systems based on optical microcomb sources, which offer advantages in achieving highly reconfigurable processing functions without requiring changes to hardware. We propose four different feedback control methods including (1) one-stage spectral power reshaping, (2) one-stage impulse response reshaping, (3) two-stage spectral power reshaping, and (4) two-stage synergic spectral power reshaping and impulse response reshaping. We experimentally implement these feedback control methods and compare their performance. The results show that the feedback control can significantly improve not only the accuracy of comb line shaping as well as temporal signal processing and spectral filtering, but also the system’s long-term stability. Finally, we discuss the current limitations and future prospects for optimizing feedback control in microcomb-based MWP transversal filter systems implemented by both discrete components and integrated chips. Our results provide a comprehensive guide for the implementation of feedback control in microcomb-based MWP filter systems in order to improve their performance for practical applications.

In this paper is shown the dynamic modeling and design of a passivity based controller for the RV-3SB robot. Firstly, the dynamic modeling of the of the Mitsubishi Rv-3SB robot is done by the Euler-Lagrange formulation in order to obtain a decoupled dynamic model considering the actuators orientation besides the position of this analyzed robot. It is important to remark that the dynamic model of the RV-3SB robot is done based in the kinematic model obtention in which is developed by the implementation of screw theory. Then the passivity based controller is obtained by separating the end effector variables and the actuator variables by making an appropriate coordinate transformation. The passivity based controller is obtained by selecting an appropriate storage function and by the Lyapunov theory the passivity based control law is obtained in order to drive the error variaable, which is the difference between the measured end effector position variable and the end effector desired position variable. The passivity based controller makes that the error variable reach the origin in finite time taking into consideration the dissipation properties of the proposed controller in order to stabilizes the desired end effector position. A numerical simulation experiement is performed in order to validate the theoretical results obtained in this research study. It is verified by numerical experimentation that the proposed control strategy is efficient and effective in order to drive the error variable to the origin in comparison with other modified techniques found in the literature. Finally, the appropriate discussion and conclusion of this research study are provided.

Drilling vibrations has been identified as a key performance limiter that prevents successful energy transfer from the surface to the bit. The resultant irregular bit rotation speed causes drilling challenges like poor hole quality and reduction in rate of penetration to name a few. Amongst other vibration suppression techniques, active control of vibrations is widely used and recommended. Active control system utilizes a closed loop feedback control to continuously adapt to downhole vibrations detected at the surface. The system requires regular tuning and upgrades which is done experimentally before field deployment. The paper presents a PID based experimental tuning of horizontal and vertical strings for irregular RPM. In doing so, the paper highlights the need of having horizontal experimental setups for state-of-the-art PID tuning for downhole RPM. The settling time of irregular RPM for horizontal setup is found to be lower than the vertical configuration due to multiple contact points and increased friction coefficient.

Text-to-image tasks have gained significant progress, where vivid images are generated from detailed text descriptions. However, existing studies overlook scenarios where the provided text is sparse, neglect the investigation of human preferences, and fail to acknowledge the diversity of aesthetic opinions. To address those issues, we develop a methodology called personalized short-text-to-image generation through aesthetic assessment and human insights. We develop a Personality Encoder (PE) to extract personal information and establish the Big-Five personality traits-based Image Aesthetic Assessment model (BFIAA) for predicting specific human aesthetic preferences. Utilizing the BFIAA model, we fine-tune the Stable Diffusion model to align it more closely with human preferences. Our experiments demonstrate that our BFIAA model can truly reflect human aesthetic preference and the adapted generation model can generate personalized images more preferred by humans.

The EASY-NET network program (NET-2016-02364191 - Effectiveness of Audit and Feedback (A&F) strategies to improve health practice and equity in various clinical and organizational set-tings), piloted a new and more structured A&F strategy. This study compared the effectiveness of the new strategy versus the periodic publication of indicators alone in improving the appropri-ateness and timeliness of emergency health interventions in patients with Acute Miocardial In-farction (AMI) and ischemic stroke in the Lazio Region. Efficacy was evaluated according to a prospective quasi-experimental design of pre-post (2021-2022) intervention type with control group. The exposed are hospitals in the Lazio Region where professional teams voluntarily par-ticipated in the intervention. The control group is involved only in the usual reporting activities. Effectiveness analysis was conducted at the patient level. Regional health information systems were used to calculate process and outcome indicators. The effectiveness of the intervention was assessed with Difference In Difference models, comparing pre-post intervention periods between exposures and controls. Estimates were calculated in terms of the difference in percentage points (pp) between absolute risks. Sixteen facilities for the IMA pathway and 13 for the stroke pathway joined the intervention. The intervention reduced the proportion of 30-days readmissions after a hospitalization for ischemic stroke by 0.54 pp in the exposed patients with a significant difference of -3.80 pp (IC95% -6.57; -1.03; 5453 patients, 63.7% cases) in the exposed compared to controls. There were no statistically significant differences attributable to the implemented A&F interven-tion in the other indicators considered. The results show, for the first time in Italy, the impact of A&F interventions in an emergency setting using aggregated data from hospitals involved in the Lazio Region emergency network.

This paper illustrates an experimental activity for the closed-loop position control of an actuator made using shape memory alloy (SMA) wire. A solution with the self-sensing effect was implemented to miniaturize the systems, i.e., without external sensors. A proportional control algorithm was initially used, demonstrating the idea's feasibility: the wire can behave simultaneously as an actuator and sensor. An experimental investigation was subsequently conducted for the optimization of the developed actuator. As for the material, a Flexinol wire, Ni-Ti alloy, with a diameter of 0.150 mm and a length of 200 mm, was used. Preliminarily, a characterization of the SMA wire at constant and variable loads was carried out: the characteristics detected are elongation vs. electric current and elongation vs. electrical resistance. The control system is PC-based with a data acquisition card (DAQ). A drive board has been designed and built to read the wire's electrical resistance and power it by pulse width modulation (PWM). A notable result is that the actuator works with good precision and in dynamic conditions, even when it is called to support a load up to 65% different from that for which the electrical resistance-length correlation has previously been experimentally obtained, on which the control is based. This opens up the possibility of using the actuator in a counteracting configuration with a spring, which makes hardware implementation and control management simple.

Robotic surgery is a rapidly developing and evolving surgical technique. This literature review evaluates the advantages and disadvantages in the context of gallbladder disease comparing robotic Cholecystectomy to the well-established laparoscopic Cholecystectomy. Significant advantages are reduced operative blood loss, hospital stays and post operative pain, alongside increased patient satisfaction and improved visualization and precision compared to the laparoscopic approach. Disadvantages include lack of tactile feedback, significant cost attributed to equipment, training requirements and increased procedural time due to the set-up sequences. The implementation of robotic surgery also poses significant changes for the training of future surgeons. Whilst it can standardize training and increases opportunity for simulation, the concern is the loss of traditional skills. Currently the evidence base remains mixed however the use of robotics in the right setting, with suitably trained operatives and appropriate patients can enable improved outcomes for patients with gallbladder disease. There is a lot of scope for development including the implementation of tactile feedback to aid operative technique and artificial intelligence to aid patient safety. Likely broadening the use and potential benefit of robotic surgery not only for cholecystectomy but many surgical specialties.

Audit&Feedback (A&F) consists of multidimensional quality improvement activities, but its optimal design is still debated. Our study aims to outline how interventions of the Italian EASY-NET research program were designed, to explore whether desirable characteristics of an "ideal" A&F were adopted. A&F design included description of the working group, targeted clinical behaviors, selected indicators, sources, feedback procedures, corrective actions expected. Information was classified into four topics: nature of the desired action, type of data available, feedback display and delivery. Out of 9 projects, 3/9 aimed at changing a focused clinical behavior, 6/9 were generic; all projects identified clinicians as recipients, 8 explicitly considered managers. It was planned to develop an average of 27 indicators from administrative databases, as needed supplemented by ad hoc data collection. Five projects included outcome measures. Comparators derived from scientific literature or from territorial real-life data. Feedback was scheduled every 12, 6 or 3 months, or upon request, delivered as aggregate data (graphs and tables) via web platforms, e-mail, workshops, and individual meetings. In conclusion, at an early stage the projects were mostly “wide focused”, but improvements in A&F design and delivery have been introduced, and projects, still ongoing, will offer interesting insights on A&F effectiveness.

Pose estimation has various applications in analyzing human movement and behavior, including providing feedback to users about their movements so they could adjust and improve their movement skills. To investigate the current research status and possible gaps, we searched Scopus and Web of Science for articles that (1) human `body' pose estimation is used and (2) user movement is assessed and communicated. We used either a bottom-up or top-down approach to analyze 20 articles for methods used to estimate human pose, assess movement, provide feedback to users, as well as methods to evaluate them. Our review found that pose estimation systems typically used CNNs while movement assessment methods varied from mathematical formulas or models, rule-based approaches, to machine learning. Feedback was primarily presented visually in verbal forms and nonverbal forms. The experiments to evaluate each part ranged from the use of public datasets to human participants. We found that while there was an improvement, the majority of pose estimation challenges remain. The effectiveness and factors for choosing movement assessment methods for a new context are still unclear. In the end, we suggest that studies about feedback prioritization and erroneous feedback are needed.

We study the deterministic dynamics of N point particles moving at constant speed in a 2D table made of two polygonal urns connected by an active rectangular channel, which applies a feedback-control on the particles, inverting the horizontal component of their velocities, when their number in the channel exceeds a fixed threshold. Such a bounce--back mechanism is non-dissipative: it preserves volumes in phase space. An additional passive channel closes the billiard table forming a circuit in which a stationary current may flow. Under specific constraints on the geometry and on the initial conditions, the large N limit allows nonequilibrium phase transitions between homogeneous and inhomogeneous phases. The role of ergodicity in making a probabilistic theory applicable is discussed both for rational and irrational urns. The theoretical predictions are compared with the numerical simulation results. Connections with the dynamics of feedback-controlled biological systems are highlighted.

Ultrasound based haptic feedback is a potential technology for human-computer interaction (HCI) with the advantages of low cost, low power consumption and controlled force. In this paper, the phase optimization for multipoint haptic feedback based on ultrasound array is investigated and the corresponding experimental verification is provided. A mathematical model of acoustic pressure is established for the ultrasound array and then a phase optimization model for an ultrasound transducer is constructed. We propose a pseudo-inverse (PINV) algorithm to accurately determine the phase contribution of each transducer in the ultrasound array. By controlling the phase difference of the ultrasound array, the multipoint focusing forces are formed leading to various shapes such as geometries and letters that can be visualized. Because the unconstrained PINV solution results in unequal amplitudes for each transducer, a weighted amplitude iterative optimization is deployed to further optimize the phase solution, by which the uniform amplitude distributions of each transducer are obtained. For the purpose of experimental verifications, a platform of ultrasound haptic feedback consisting of a Field Programmable Gate Array (FPGA), an electrical circuit and an ultrasound transducer array is prototyped. The haptic performances of single point, multiple points and dynamic trajectory were verified by controlling the ultrasound force exerted on the liquid surface. The experimental results demonstrate that the proposed phase optimization model and theoretical results are effective and feasible, and the acoustic pressure distribution is consistent with the simulation results.

Background This paper draws learnings and successes based on field implementation experience spanning four years (2016–2019) of implementing CLTS by Prince of Peace Orphans and Widows Vision, a community-based organization located in Kaberamaido district in eastern Uganda. Methods The study aimed to document, disseminate and inform from an evidence-based point of view how adaptation and collaborative engagements triggers learning from mistakes to inform iterative changes from improvements and success.This is a descriptive paper that used project documents review based on field implementation experience. Existing project reports were synthesised, collated and curated for evidence. Data were drawn from project reports and records to inform narratives in writing. Implementation of the project was executed in homogenous rural communities occupied by people of the same dialect, cultural and social settings. Results We note that success in CLTS implementation can hardly be achieved by merely following prescriptions in handbooks and guidelines but rather by devising innovative community engagement and other participatory and community-driven techniques that foster adaptive management, promote ownership, and buy-in.Having learned from our failures, we used data to inform decisions and transformatively deviated from traditional CLTS implementation and introduced high impact and innovative approaches such as the use of CLTS helpdesks and Situation room, the Pamoja approach, learning labs and iterative feedback loops, innovatively tackling slippage and carefully introducing the follow-up mandona approach. These enhanced experiential learning and ultimately resulted in sustained sanitation behaviour. Conclusions The CLTS approach as outlined in the handbook needs to be flexibly adapted to address contextual needs. Reflective and learning sessions reinforced with routine feedback loops from implementers and beneficiaries yields tremendous results, propagates experiential learning, and ultimately results in a transformative deviation from undesirable to desired sanitation behaviours. These innovative approaches once carefully blended have proved to be sustainable, are adaptable and can work in an even larger scale and in a variety of contexts.

The PI3K/mTOR signalling pathway plays a central role in the governing of cell growth, survival and metabolism. As such, it must integrate and decode information from both external and internal sources to guide efficient decision-making by the cell. To facilitate this, the pathway have evolved an intricate web of complex regulatory mechanisms and elaborate crosstalk with neighbouring signalling pathways, making it a highly non-linear system. Here, we describe the mechanistic biological details that underpin these regulatory mechanisms, covering a multitude of negative and positive feedback loops, feed-forward loops, competing protein interactions, and crosstalk with major signalling pathways. Further, we highlight the non-linear and dynamic network behaviours that arise from these regulations, uncovered through both computational and experimental studies. Given the pivotal role of the PI3K/mTOR network in cellular homeostasis and its frequent dysregulation in pathologies including cancer and diabetes, a coherent and systems-level understanding of the complex regulation and consequential dynamic signalling behaviours within this network is imperative for advancing biology and development of new therapeutic approaches.

As rotary machines have become more complicated, balancing processes have been classified as a vital step in condition monitoring to ensure machines operate both reliably and safely. This is especially important for flexible machines which normally work at rotations speeds above critical limits. Imbalance is a common problem in flexible rotating machinery that can lead to extreme vibration and noise levels. This is one of the major reasons for studying various balancing methods applied to the vibration response of rotating machines. Recently, the relation between acoustic and vibration response during a rotary machine balancing process based on the Four-Run method has been presented for constant speed machines. This method cannot be applied to machines in start-up or shut-off. Hence, by considering the acoustic and vibration responses of a machine between its critical speeds, this research presents a new innovative speed-variant balancing method based on the original Four-Run method, named as "Peak to Peak for Critical Speeds (PPCS)". The proposed method consists of two major types of application: the first is in the Run-up of the machine and the second is in Shut-down. Experimental laboratory results show that the PPCS method can be implemented for speed-variant and flexible rotary machines during run-up or shut-down transient processes based on acoustic and vibration measurements. As a phase-less and a contactless method, the PPCS can be employed as an innovative and readily available method for condition monitoring in the future.

In this paper, a 3 DOF gyrscope position control have been designed and controlled using optimal control theory. An input torque has been given to the first axis and the angular position of the second axis have been analyzed while the third axis are kept free from rotation. The system mathematical model is controllable and observable. Linear Quadratic Integral (LQI) and Linear Quadratic State Feedback Regulator (LQRY) controllers have been used to improve the performance of the system. Comparison of the system with the proposed controllers for tracking a desired step and random angular position have been done using Matlab/Simulink Toolbox and a promising results has been analyzed.

The concept of using special electrical circuit design realize a "cold resistors", that is, an active resistor circuitry with lowered effective noise temperature, was first introduced about 80 years ago. Later on, various kinds of artificial resistors were applied in different research areas, such as gravitational wave detection, photo-amplifiers and quartz oscillators. Their proofs of concepts were experimentally proved. Unfortunately, the complete theory was not found even though several attempts had been published, sometimes with errors. In this paper, we describe a correct and complete circuit theoretical model of a cold resistor system. The results are confirmed by computer simulations. A design tools for this circuit is also shown.

Sensor fusion technology is one of extensive used methods in the field of robot, aerospace and target tracking control. In this paper, the generalized sensor fusion framework, named the closed-loop fusion (CLF) is analyzed and the optimal design principle of filter is proposed in detail. Fusion error optimization problem, which is the core issue of fusion design, is also solved better through the feedback compensation law of CLF framework. Differently from conventional methods, the fusion filter of CLF can be optimally designed and the determination of superposition of fusion information is avoided. To show the validity, simulation and experimental results are to be submitted.

This paper presents a novel 3-degrees-of-freedom (3-DOF) haptic master with rubber bands for self-resetting. The mechanical design avoids coupling between three directions mechanically by using three perpendicular axis intersecting at one point. Bevel gear transmission is adopted to increase the compactness of the overall structure. VR-based interactive system is designed and built by incorporating the proposed haptic master. The proposed haptic device can generate force feedback along 3-degree-of-freedom motion using motors and provide command signals to the avatar in the virtual environment. In order to analyze the performance of the developed device in terms of haptic feedback operation, ergonomics assessments are designed and experimentally implemented. Preliminary studies on the influencing factor including the guidance force, the reset force, the speed of the avatar and the arm the length have been conducted. The results of this paper are of great significance for the design of the haptic master and interactive system.

Empirical findings support the important role played by prosocial behavior and scholastic per-formance in significantly affecting adolescents’ long term psychosocial adjustment. Furthermore, several studies showed the positive impact of academic self-efficacy in affecting adolescents’ social and academic functioning; however, no studies have investigated the effect of other important personality structures, such as students’ feedback sensitivity. The present study aims at investi-gating the effects of adolescents’ feedback sensitivity (reward sensitivity/punishment sensitivity) on their prosocial behavior and scholastic performance also examining the potential indirect effect of academic self-efficacy on the association between reward/punishment sensitivity and prosocial behavior/scholastic performance. Participants were 132 adolescents (53.1% males; Mage = 16.42, SD) from Rome (Italy). Students’ reward/punishment sensitivity, academic self-efficacy, prosocial behavior and scholastic performance were self-reported. A path analyses model showed a positive and significant effect of academic self-efficacy on scholastic performance, a positive significant ef-fect of punishment sensitivity on prosocial behavior, a positive significant effect of reward sensi-tivity on academic self-efficacy and a significant indirect effect of academic self-efficacy on the association between reward sensitivity and scholastic performance. Results of this study are useful in term of practical implications to promote students’ adjustment.

Background We investigated to determine the effectiveness of verbal feedback in learning the round-off back somersault on the balance beam with stable landing. Methods: The research material consisted of female gymnasts (n = 16). They were randomly assigned to one of two groups: FKE group (n = 8) with feedback on key elements, or FAE group (n = 8) with 100% feedback on all errors made in the phase structure of the task. Results: Based on research, it was established that key elements could be identified in the preparatory, main and final phases. Mixed ANOVA showed that significant differences (p < 0.05) were noted due to the teaching method used (Group x Time factor) when performing the gymnastic routine of round-off back somersault with stable landing on the balance beam. Based on the Welch t test for independent data it was revealed that the group with feedback on the key elements obtained significantly higher mean scores from judges at the end of the experiment. Conclusions: The findings of the present study point to a possibility of offering coaches teaching methods that increase the effectiveness of learning complex motor skills and indicate a possibility of applying such solutions in groups of female gymnasts both in training and during competitions.

The proliferation of Unmanned Aerial Vehicle (UAV) networks is increasing, driven by their capacity to deliver automated services tailored to the varied demands of numerous smart city applications. Trust, security, and privacy remain paramount in the public domain. Traditional centralized network designs fall short of ensuring device authentication, data integrity, and privacy within UAV networks’ highly dynamic and adaptable environments. Decentralized reputation systems emerge as a promising solution to enhance the reliability and trustworthiness of data and communications within these networks while safeguarding UAV security. This paper presents an exhaustive survey of trust and reputation systems, exploring existing frameworks and proposed innovations alongside their inherent challenges. It highlights the crucial role of reputation systems in strengthening trust, security, and privacy throughout these networks and discusses various strategies to mitigate existing vulnerabilities. As a useful resource for researchers and practitioners seeking to advance the state of the art in UAV network security, we hope this survey will spark further community discussion and stimulate innovative ideas in this burgeoning field.

Feedback trading theory is one of the most primitive theories about financial market. But for a long time，researches and modelings on this topic are rarely seen. The model in this paper shows the effects of sentiment shocks on asset prices in a market characterized by feedback trading in the long run. We find that，generally，feedback trading will lead to cognitive bias effect and trading inducement effect. Cognitive bias effect increases with the feedback trading parameter ( FTP) . In our model，the abnormal volatility of asset prices is captured by cognitive bias effect，sentiment shock effect and trading inducement effect．

While shoulder injuries represent the musculoskeletal disorders (MSDs) most encountered in physical therapy, there is no consensus on their management. As attempts to provide standardized and personalized treatment, a robot-ic-assisted device combined with EMG biofeedback specifically dedicated to shoulder MSDs has been developed. The aim of this study was to determine the efficacy of an 8-week rehabilitation program (≈3 sessions a week) using a ro-botic-assisted device combined with EMG biofeedback (RA-EMG group) in comparison with a conventional program (CONV group) in patients presenting with shoulder MSDs. This study is a retrospective cohort study including data from 2010 to 2013 on patients initially involved in a physical rehabilitation program in a private clinic of Chicoutimi (Canada) for shoulder MSDs. Shoul-der flexion strength and range of motion were collected before and after the rehabilitation program. Forty-four patients participated in a conventional pro-gram using dumbbell (CONV group) while 72 of them completed a program on robot-assisted device with EMG and visual biofeedback (RA-EMG group), whereby both programs consisted in 2 sets of 20 repetitions at 60% of maximal capacity. Results showed that the RA-EMG had significantly greater benefits than the Conv group for shoulder flexion strength (+103.1% vs 67%, p = 0.016) and range of motion (+14.4% vs 6.1%, p = 0.046). The current retrospective co-hort study showed that a specific and tailored rehabilitation program with constant effort by automatic adjustment of the level of resistance was able to potentiate strength and range of motion shoulder flexion after an 8-week reha-bilitation period in comparison with a conventional approach in patients with shoulder MSDs. This study provides new insight on shoulder MSD rehabilita-tion and future research should be pursued to determine the added potential of this approach for abduction and external rotation with a randomized controlled design.

Based on the two-node Euler-Bernoulli beam, the tower system is discretized by finite element method, and the cubic Hermite polynomial is taken as the shape function of the beam element, and the structural characteristic matrix of the tower system is calculated, and the wind turbine-nacelle-tower multi-degree of freedom is established Finite element numerical model. The aerodynamic load calculation formula for any nacelle attitude angle is deduced. The influence of the vibration feedback of the flexible tower on the aerodynamic load of the wind turbine is studied. The results show that when the rigidity of the tower is large, the impact of tower vibration feedback on the aeroelastic load of the wind turbine is small. For a tower system with greater flexibility, the time-varying feedback of wind-induced vibration will cause greater aeroelastic load changes, especially the overturning moment of the tower top, which will cause a greater impact on the dynamic behavior of the tower in the downwind and crosswind directions. As the flexibility of the tower system increases, the interaction between tower vibration and aerodynamic load is gradually increasing. Taking the impact of the flexible tower on the aeroelastic load of the wind turbine into account, on the one hand, helps to predict the wind more accurately. The aerodynamic load of the wind turbine improves the efficiency of wind energy utilization. On the other hand, it can more accurately analyze the dynamic behavior of the flexible structure of the wind turbine, which is extremely beneficial to the structural optimization design of the wind turbine.

Negative feedback to the back gate of MOS devices available in FD-SOI technologies can be used to improve linearity of operational amplifiers. Two operational amplifiers designed and fabricated in a 22nm FD-SOI technology illustrate this technique, its advantages and limitations.

A number of studies have been conducted to improve the accessibility of images using touchscreen devices for screen reader users. In this study, we conducted a systematic review of 33 papers to get a holistic understanding of existing approaches and to suggest a research road map given identified gaps. As a result, we identified types of images, visual information, input device and feedback modalities that were studied for improving image accessibility using touchscreen devices. Findings also revealed that little has studied how to automate the generation of image-related information, and that screen reader users play important roles during the evaluation but the design process. Then we introduce two of our recent studies on the accessibility of artwork and comics, AccessArt and AccessComics respectively. Based on the identified key challenges, we suggest a research agenda for improving image accessibility for screen reader users.

Noise reduction is the major issue in the loudspeaker for the application of the musical instruments and related areas. In this paper, a noise disturbance control of a loudspeaker with optimal and robust controllers has been done successfully. The noise of the loudspeaker has been analyzed by simply track a reference cone displacement with the actual cone displacement. Static output feedback and H infinity optimal loop shaping controllers have been used to compare the actual and reference cone displacements by using a sine wave and random cone displacement signals and a promising results have been analyzed.

In real financial market, the delayed market feedback and the delayed effect of government macro-control are inevitable. And both the delay of market feedback and the delay of macro-control effect bring about the mathematical difficulties in studying stabilization and synchronization of the hyper-chaotic financial system. However, employing Lyapunov function method, differential mean value theorem, suitable bounded hypotheses and pulse control technology results in the globally asymptotical stabilization and synchronization criteria. It is the first paper to drive the stabilization and synchronization criteria under the assumptions of the double delays. Finally, numerical examples illuminate the effectiveness of the proposed methods.

Computational simulation using mathematical models is a useful method for understanding the complex behavior of a living system. The majority of studies using mathematical models to reveal biological mechanisms uses one of the two main approaches: the bottom-up or the top-down approach. When we aim to analyze a large-scale network, such as a comprehensive knowledge-integrated model of a target phenomenon, for example a whole-cell model, the variation of analyses is limited to particular kind of analysis because of the size and complexity of the model. To analyze a large-scale regulatory network of neural differentiation, we developed a hybrid method that combines both approaches. To construct a mathematical model, we extracted network motifs, subgraph structures that recur more often in a metabolic network or gene regulatory network than in a random network, from a large-scale regulatory network, detected regulatory motifs among them, and combined these motifs. We confirmed that the model reproduced the known dynamics of HES1 and ASCL1 before and after differentiation, including oscillation and equilibrium of their concentrations. The model also reproduced the effects of overexpression and knockdown of the Id2 gene. Our model suggests that the characteristic change in HES1 and ASCL1 expression in the large-scale regulatory network is controlled by a combination of four feedback loops, including a large loop which has not been focused on. The model extracted by our hybrid method has the potential to reveal the critical mechanisms of neural differentiation. The hybrid method is applicable to other biological events.

The purpose of our study is to determine the effectiveness of various types of psychocorrection measures: social and psychological training, a method of biological feedback and Sandplay for the indicators of childhood anxiety among younger schoolchildren. The study was conducted in the school of Magadan, North East of Russia (9-10 year old students, n = 43). We used a standardized method of Multidimensional Assessment of Child Anxiety which included 10 scales. The correction methods were used: socio-psychological training (SPT), biofeedback method (BFB), individual and group Sandplay. Students of group I (n = 12) participated only in the SPT. Students of group II (n = 11) participated in the SPT and underwent a course of training in self-regulation using the BFB method. In correction work with the students of group III (n = 20), the SPT, BFB, individual and group Sandplay were used. In group I, after the correction activities, a significant decrease in anxiety was observed in 3 of 10 scales (2, 6, 7; (p <0.05). In group II it was seen in 5 scales (1, 3, 6, 7, 8; p <0.05). In group III, a significant improvements took place in 7 scales (1, 2, 5, 6, 7, 9, 10; p <0.01–p <0.05). The present study has shown the different efficacy of applying the remedial techniques separately and in combination. The use of methods in the complex enhances the impact on the types of the child anxiety.

Although food retailers have embraced organic certified food products as a way to reduce their environmental loading, organic sales only make up a small proportion of total sales worldwide. Most consumers have positive attitudes towards organic food, but attitudes are not reflected in behaviour. This article addresses consumers’ attitude-behaviour gap regarding their purchase organic food and reports on how visualization of personal shopping data may encourage them to buy more organic food. Through the design of the visualization tool, the EcoPanel, and through an empirical study of its use, we provide evidence on the potential of the tool to promote sustainable food shopping practices. Sixty-five users tested the EcoPanel for five months and interviews were made with ten of these. The test users increased their purchase of organic food with 23%. The informants used the EcoPanel to reflect on their shopping behaviour and to increase their organic shopping. We conclude that the visualization of food purchases stimulates critical reflection and the formation of new food shopping practices. This implies that food retailers may increase sales of organic food through using a visualization tool available for their customers. In this way these retailers may decrease their environmental impact.

The feedback collection and analysis has remained an important subject matter since long. The traditional techniques for student feedback analysis are based on questionnaire-based data collection and analysis. However, the student expresses their feedback opinions on online social media sites, which need to be analyzed. This study aims at the development of fuzzy-based sentiment analysis system for analyzing student feedback and satisfaction by assigning proper sentiment score to opinion words and polarity shifters present in the input reviews. Our technique computes the sentiment score of student feedback reviews and then applies fuzzy-logic module to analyze and quantify student’s satisfaction at the fine-grained level. The experimental results reveal that the proposed work has outperformed the baseline studies as well as state-of-the-art machine learning classifiers.

In this paper, we discuss voltage control method for buck converter operating in continuous conduction mode (CCM) using analog feedback system. The aim of this work is to control the output voltage of a buck converter during the variation in load current. This is obtained using analog feedback made with operational amplifier (Opamp). However, the same technique can be applied to other DC-DC converters (e.g boost, buck-boost, cuk converter, etc) in CCM mode, but for the purpose of analysis buck converter is chosen as an example.

Since late December, the underwater Hunga Tonga-Hunga Ha'apai volcano has been erupting for weeks and has seen sporadic activities in a series of pretty big eruptions. On Friday 15th January 2022, an explosion shot a massive cloud of ash high into the atmosphere and generated a tsunami that impacted much of the Pacific Rim, which makes it one of the most energetic explosions of the entire 21st century so far. Thus, the need to determine the significant impact of these generated volcanic aerosols on the environment is a prominent task. This study depicts the modeling of the volcanic ash dispersion from the 2022 Hunga Tonga-Hunga Ha'apai volcanic eruption while investigating the effects of incorporating radiative feedback effects within the inline Weather Research and Forecasting model coupled with chemistry (WRF-Chem). Results for 4-day averaged values have proven that the basic run (No Feedback) produced higher ash concentrations than the one with aerosol radiative feedback effects (Feedback). The simulations highlighted also the significant volcanic ash biases concentrated around the ash cloud. Additionally, our data analysis from meteorological stations and Copernicus TROPOspheric Monitoring Instrument Sentinel-5 Precursor (TROPOMI-S5P) mission indicates that total sulfur dioxide () emissions traveled west. We show also that the huge plume of on January 18 reached Australia, more than 7000 km west of the eruption. With the enormous ash cloud produced, its impact on the environment and global climate change would be considered an excellent exercise for atmospheric dispersion modelers, volcanologists, and the environmental scientists' community.

This study presents a novel kinematic tracking model, designed for a networked exoskeleton system that is asynchronously taught by a remote therapist. On the server side, the therapist’s rehabilitation exercises are quantitatively assessed using a monocular passive vision system. The resultant analytical metrics are then transmitted asynchronously over the network to patients equipped with exoskeletons. On the client side, the exoskeleton utilizes these analytical metrics as reference paths for exercises, complemented by electromyography (EMG) feedback. This work introduces a calibration approach aimed at estimating angular positions by utilizing EMG observations. The calibration model establishes real-time correlations between polynomial reference positions. This calibration mechanism is integrated into simulations of both upper and lower limb exoskeletons. We further explore redundant kinematics, incorporating an EMG observer for linear, time-variant rehabilitation tracking control. Our methodology is validated using vision-based metric data and experimental EMG measurements for various exercises, including shoulder flexion, elbow flexion, and rowing-like movements. This work also includes computer simulations for tracking the control of rehabilitation exercises, demonstrating the adaptability of the system in reliably, robustly, and effectively following desired trajectories.

The Internet of Things (also known as IoT), a revolution, has enhanced the relevance of mobile employees' job efficiency in mobile crowd sensing (MCS). Incentives based on reputation for mobile workers (MW) play an important role in increasing service utilization, motivating mobile employees, and developing confidence in the service. The cell phone is the most exploited entity in mobile crowd-sensing MCS and cloud computing. In the underlying investigation, we observed that they had not evaluated the complexity level of a task, resulting in a strong reputation for executing multiple basic tasks. A person who completes a tough task may have a lower reputation score. Complexity levels of tasks (CLT) were developed for reputation evaluation on a crowd-sensing network, which would be utilized to evaluate the MW reputation. We offered simple and complex levels of challenges to assess reputation scores. Tasks receive incentives based on their reputation. By measuring reputation on (CLT) complexity level of task, this research will help the system to Maintain the reputation of the mobile worker so that entities of the system get the maximum benefit out of it, by hiring well-reputed mobile workers and MW receive an incentive on it. Furthermore, we conduct a comparative analysis between our scheme and various machine learning algorithms to identify the algorithm that best performs in evaluating task complexity. Considering both the simple and complex reputation scores, the comparison suggests that after analyzing the data, it is clear that the CLT (proposed) scheme and the Linear regression scheme not only outperformed the Neural Network scheme in terms of Complex Reputation Scores but also in terms of Simple Reputation Scores. We also apply statistical tests, such as p-tests and t-tests, to determine the significance of the results obtained from different algorithms. Considering MW 308, MW 345, and MW 1045's efforts and abilities, the MCS system may offer incentives and awards to further motivate and consider their continuing contributions. This reputation-based incentivization technique not only encourages strong competition among mobile workers, but also makes sure the delivery of high-quality services inside the MCS system.

In this research, we present a comprehensive methodology to categorize perfumes based on their fragrance profiles and subsequently aid in creating innovative odoriferous molecules using advanced neural networks. Drawing from data on Parfumo and the Good Scents Company webpage (Parfumo, 2008; The Good Scents Company, 2021), the study employs sophisticated web scraping techniques to gather diverse perfume attributes. Following this, a k-means algorithm is applied for perfume clustering, paving the way for recommending similar scents to consumers. The process then bridges customer preferences to molecular design by incorporating their feedback into generating new molecules via graph neural networks (GNNs). Through converting the Simple Molecular Input Line Entry System (SMILES) representation into graph structures, the GNN facilitates the creation of new molecular designs attuned to consumer desires. The proposed approach offers promising avenues for consumers to pinpoint similar perfume choices, incorporating feedback, and for manufacturers to conceptualize new fragrant molecules with a high likelihood of market resonance.

Age-related diseases (ARDs) are the leading cause of death worldwide, and contribute to 90% of mortality in developed countries. Interestingly, the mortality rates of individual ARDs increase exponentially with age. Processes described by the exponential growth function typically involve a branching chain reaction or, more generally, a positive feedback loop. Here I propose that each ARD is mediated by one or several positive feedback loops (vicious cycles). I then identify critical vicious cycles in five major ARDs: atherosclerosis, hypertension, diabetes, Alzheimer’s and Parkinson’s. I also propose that the progression of ARDs can be halted by selectively interrupting the vicious cycles and suggest the most promising targets. An evolutionary perspective is also offered.

The use of haptic devices in rehabilitation of impaired limbs has become rather popular, given the proven effectiveness in promoting recovery. In a standard framework, such devices are used in rehabilitation centers, where patients interact with virtual tasks, presented on a screen. To track their sessions, kinematic/dynamic parameters or performance scores are recorded. However, as Internet access is now available at almost every home, and in order to reduce the hospitalization time of the patient, the idea of doing rehabilitation at home is gaining wide consent. Medical care programs can be synchronized with the home rehabilitation device; patient data can be sent to the central server that could redirect to the therapist laptop (tele-healthcare). The controversial issue is that the recorded data do not actually represent the clinical conditions of the patients according to the medical assessment scales, forcing them to frequently undergo clinical tests at the hospital. To respond to this demand, we propose the use of a bilateral master/slave haptic system that could allow the clinician, who interacts with the master, to assess remotely and in real time the clinical conditions of the patient that uses the home rehabilitation device as the slave. In this paper, we describe a proof of concept to highlight the main issues of such an application, limited to one degree of freedom, and to the measure of the stiffness and range of motion of the hand.

Due to constraints in launch platform and cost, the maneuverability of gliding-guided projectiles is limited, necessitating a rational design of their trajectory schemes. To reduce the sensitivity of trajectory schemes to uncertainties while ensuring compatibility between flight schemes and guidance control systems, and fully exploiting the control capability of the projectile, a closed-loop robust trajectory planning method is proposed. Models of major uncertain factors and states deviation at the control-start point are established. Based on the NIPCE method, the stochastic dynamic model is transformed into a high-dimensional deterministic model with PCE coefficients as state variables, and the uncertainty propagation law is obtained. A PID algorithm is employed to design a tracking guidance law based on position error feedback, and open-loop and closed-loop robust trajectory planning models are established accordingly. The optimal control problem is solved by transforming it into a nonlinear programming problem using the direct shooting method. Simulation results indicate that the NIPCE method can significantly improve the computational efficiency of uncertainty propagation while ensuring accuracy. Open-loop robust planning can effectively mitigate the sensitivity of gliding trajectories to uncertainties but cannot completely eliminate terminal dispersion. Closed-loop robust planning effectively improves control effort consumption on the basis of open-loop planning.

Self-administered pre-participation screening for physical activity (PA) requires an instrument that should be easily used and identify individuals at high risk. The Physical Activity Readiness Questionnaire (PAR-Q+) has been used for many years. Its ease of use and ability to identify those not fit to undergo PA has not been assessed. This study was to determine the rates of the PAR-Q+ in identifying adults who may not be fit for moderate or intense PA and obtain feedback on the use of this tool. A public on-line voluntary survey on the PAR-Q+ was carried out obtaining participants’ bio-characteristics, them completing the PAR-Q+ form and providing feedback. With 1019 participants, about 57.8% engaged in at least 150 minutes of PA weekly. This decreased with increasing number of co-morbidities. Increasing age was associated with more co-morbidities. About 33.1% of the participants using the PARQ+ would have required further medical evaluation. Only 3 of the 7 main PAR-Q+ questions were easily understood. Difficulties were encountered with 39 of the 44 follow-up questions, especially amongst those with co-morbidities. The large number of technical terms was also a source of concern. The PAR-Q+ would need extensive simplification before it may be recommended for use.

It is unavoidable that the characteristics of the robot system alter inexactly or cannot be correctly determined during movement and are impacted by external disturbances. There are many adaptive control methods, such as sliding control or neural control, to improve the quality of trajectory tracking for robot motion systems. Still, those methods require a large amount of computation related to solving the problem of constrained nonlinear optimization problem. The article presents some techniques for determining an intelligent controller's online learning function parameters, including two circuits: the inner circuit is a state feedback linearized controller, and the outer course is an Interactive learning controller and does not use the robot's mathematical mode with function parameters online optimal learning and intelligent online learning closely following the joint model to stabilize the robot system. Finally, the 2-DOF planar robot simulation is performed on Matlab software R2022b. The findings indicate that outstanding tracking performance is achievable.

Background: Alzheimer's disease causes great changes, with the prefrontal cortex be-ing frequently damaged zones, affecting physical and cognitive behavioural and compromising autonomy and quality of life. Objective: To evaluate the effectiveness of feedback-based tech-nology on the improvement of physical-cognitive capacities in Alzheimer. Methods: Forty pa-tients with Alzheimer were recruited from the Santa Elena Alzheimer's Association, Seville, of which 15 ended up being pilot participants, divided randomly into controls (8) and experi-mental (7). They were evaluated with: Cognitive Mini-Examination Scale, Oddball Test and At-tention Network, Berg Scale, Tinetti, Timed up and Go and Geriatric Deterioration Scale. The experimental group was treated with feedback-based technology under the supervision of physiotherapists, during 16 thirty-minute sessions, twice a week. The control group performed their usual care. Result: A significant improvement was observed in the experimental group (Cognitive Mini-Examination and Tinetti). In the group of control, a worsening of physical and motor skills was evidenced because of the degenerative disease. Discussion/Conclusion: This treatment could be a strategy to keep the patient in early stages for longer, and improve quali-ty of life delaying dependency. It creates intergenerational bonds and use at home to promote treatment adherence.

Chaotic systems are systems whose results are sensitive to the initial conditions. Chaotic systems generally have nonlinearities that can be difficult to model. One example of a chaotic system with nonlinearities is the Lorenz system. The Lorenz system can be used to model weather, wind disturbances, and electronic circuit design, among other applications. In this manuscript, the Lorenz system is modeled and various control methods are applied in an effort to dictate the system’s state and rate trajectories. The combination of the linear feedback and nonlinear feedforward controllers can show over an 80% improvement in state trajectory errors when compared to the baseline run. However, the improved state trajectory performance comes at a cost of as much as 1800% error in the rate trajectories.

Classical and optimal control architectures for motion mechanics with fusion of noisy sensors use different algorithms and calculations to perform and control any number of physical demands, to varying degrees of accuracy, precision, and cost. Their performances are tested for the purpose of comparison through the means of a Monte Carlo simulation that simulates how different parameters might vary under noise, representing real-world imperfect sensors. We find that improvements in one figure of merit often come at a cost in the performance in the others, especially depending on the presence of noise in the system sensors. If sensor noise is negligible, open-loop optimal control performs the best. However, in the overpowering presence of sensor noise, using a control law inversion patching filter performs as the best replacement, but has significant computational strain.

This study aims to explore the effect of real-time visual feedback (VF) information of the pres-sure of center (COP) provided by intelligent insoles on balance training in a one leg stance (OLS) and tandem stance (TS) posture. Thirty healthy female college students were randomly assigned to the visual feedback balance training group (VFT), non-visual feedback balance training group (NVFT), and control group (CG). The balance training includes: OLS, tandem Stance (dominant leg behind, TSDL), tandem stance (non-dominant leg behind, TSNDL). The training lasted 4 weeks, the training lasts 30 minutes at an interval of 1 days. There was a sig-nificant difference in the interaction effect between Groups*Times of the COP parameters (p<0.05) for OLS. There was no significant difference in the interaction effect between Groups*Times of the COP parameters (p>0.05) for TS. The main effect of the COP parameters was a significant difference in Times (p<0.05). The COP displacement, velocity, radius, and area in VFT significantly decreased after training (p < 0.05). Therefore, the visual feedback technology of intelligent auxiliary equipment during balance training can enhance the benefit of training. The use of smart wearable devices in OLS balance training may improve the visual and physical balance integration ability.

Research on bidirectional human-machine interfaces will enable the smooth interaction with robotic platforms in contexts ranging from industry to tele-medicine and rescue. This paper introduces a bidirectional communication system to achieve multisensory telepresence during the gestural control of an industrial robotic arm. We complement the gesture-based control by means of a tactile-feedback strategy grounding on a spiking artificial neuron model. Force and motion from the robot are converted in neuromorphic haptic stimuli delivered on the user’s hand through a vibro-tactile glove. Untrained personnel participated in an experimental task benchmarking a pick-and-place operation. The robot end-effector was used to sequentially press six buttons, illuminated according to a random sequence, and comparing the tasks executed without and with tactile feedback. The results demonstrated the reliability of the hand tracking strategy developed for controlling the robotic arm, and the effectiveness of a neuronal spiking model for encoding hand displacement and exerted forces in order to promote a fluid embodiment of the haptic interface and control strategy. The main contribution of this paper is in presenting a robotic arm under gesture-based remote control with multisensory telepresence, demonstrating for the first time that a spiking haptic interface can be used to effectively deliver on the skin surface a sequence of stimuli emulating the neural code of the mechanoreceptors beneath.

Owing to the large ratio of consumption in the building sector, energy saving strategies are required. Energy feedback is an energy-saving strategy that consumers to change their energy-consumption behaviors. The strategy has been principally focused on providing energy-consumption information. However, realization of energy savings using only consumption information remains limited. In this paper, a building-energy three-dimensional (3D) visualization solution is thus proposed. This solution includes the process of diagnosing a building and providing prediction of energy requirements if a building improvement is undertaken. Accurate diagnostic information is provided by real-time measurement data from sensors and building models using a close-range photogrammetry (CRP) method without depending on blueprints. The information is provided by employing visualization effects to increase the energy-feedback efficiency. The proposed strategy is implemented on two testbeds, and building diagnostics are performed accordingly. For the first testbed, the predicted energy improvement amount resulting from the facility upgrade is provided. The second testbed is provided with a 3D visualization of the energy information. The aim is to determine if the building manager will replace the facility after our recommendation is given to improve the building energy efficiency driven from the energy information. Unlike existing systems, which provide only ambiguous data that lack quantitative information, this study is meaningful because it provides energy information with the aid of visualization effects before and after building improvements.

Mechanical properties of cardiomyocytes from different transmural regions are heterogeneous in the left ventricular wall. The cardiomyocyte mechanical environment affects this heterogeneity because of mechano-electric feedback mechanisms. In the present study, we investigated the effects of load upon transmural differences in contraction of subendocardial (ENDO) and subepicardial (EPI) single cells isolated from the murine left ventricle. Various loads were applied to the cells using carbon fiber techniques for single myocytes. To simulate experimentally obtained results and to predict mechanisms underlying the cellular response to change in load, our mathematical models of the ENDO and EPI cells were used. Extent of the transmural gradient in the time course of contractions was independent of the loading conditions where unloaded and heavy loaded (isometric) contractions were examined, but the regional gradient of the relaxation time characteristics tended to decrease when the load decreased. Under auxotonic contractions, time to peak contraction (T_max) was significantly longer in ENDO cells than in EPI cells at low preload. An increase in preload (axial stretch) prolonged T_max in both cell types; however, the prolongation was greater in EPI cells, resulting in a decrease in transmural gradient in T_max at high preload. The [Ca²⁺]_i transient decay time constant was consistent with the greater preload dependency in T_max of EPI cells. Our modified mathematical models reproduced experimental results, suggesting that differences in cooperativity of cross bridges and calcium troponin C complex interactions between the ENDO and EPI cardiomyocytes may contribute to the different cellular responses to stretch, which may provide a decrease in transmural dispersion of cellular shortening in the intact heart.

Myocardial heterogeneity is an attribute of the normal heart. We have developed integrative models of cardiomyocytes from the subendocardial (ENDO) and subepicardial (EPI) ventricular regions that take into account experimental data on specific features of intracellular electromechanical coupling in the guinea pig heart. The models adequately simulate experimental data on the action potential and contraction of the ENDO and EPI cells. The modeling results predict that heterogeneity in the parameters of calcium handling and myofilament mechanics in isolated ENDO and EPI cardiomyocytes via cooperative mechanisms of mechano-calcium-electric feedback are essential to produce the differences in Ca²⁺ transients and contraction profiles and may further enhance transmural differences in the electrical properties between the cells. Simulation results predict that ENDO cells have greater sensitivity to changes in afterload than EPI cells. These data are important for understanding the behavior of cardiomyocytes in the intact heart.

Controlling an object that is extremely prone to oscillations is a complex and highly relevant task. The tendency to oscillate arises due to the presence of an oscillatory element and a delay element, and control is often complicated by the presence of an integrator in the object. For such objects, a very effective method of numerical optimization of the controller is not effective enough without choosing the most efficient structure, more efficient than the PID controller and even than the PIDD controller. The method of using the Smith predictor, which is switched on parallel to the plant, allows solving a similar problem, but the resulting quality of control remains not good enough, since a large overshoot remains in the system. The article recommends, after using the Smith predictor, to additionally use an external control loop, the sequential controller of which should also be designed using the numerical optimization method. But the Smith predictor is not the best solution either. The article recommends the use of pseudo-local feedback. Such a connection provides more opportunities, since its structure and parameters can be optimized, while the Smith predictor in its parameters is completely determined by the object model and its modification is not allowed. The article shows that even the best sequential controller in the case of using the Smith predictor on a test example still cannot provide the required quality of control; in such a system, significant overshoot remains, more than 10%. The proposed method allows reducing overshoot to less than 0.5%. It is shown that the resulting system is robust, since the quality of control remains within specified limits even when the gain changes by 30% in both directions.

Visual thinking leverages spatial mechanisms in animals for navigation and reasoning. Therefore, given the challenge of abstract mathematics and logic, spatial reasoning-based teaching strategies can be highly effective. Our previous research verified that innovative box and ball coloring activities help teach elementary school students complex notions like quantifiers, logical connectors, and dynamic systems. However, given the richness of the activities, correction is slow, error-prone, and demands high attention and cognitive load from the teacher. Moreover, feedback to the teacher should be immediate. Thus, we propose to provide the teacher with real-time help with LLMs. We explored various prompting techniques with and without context Zero shot, Few shot, Chain of Thought, Visualization of Thought, Self Consistency, logicLM and Emotional to test GPT-4o’s visual, logical, and correction capabilities. We obtained that Visualization of Thought and Self Consistency techniques enabled GPT-4o to correctly evaluate 90% of logical-spatial problems that we tested. Additionally, we propose a novel prompt combining some of these techniques that achieved 100% accuracy on a testing sample, excelling in spatial problems and enhancing logical reasoning.

This study explores the public library service evaluation domain through user-generated content on Google Maps, highlighting digital feedback's significant yet underexplored potential in understanding public library patronage across Taiwan's six major cities. Utilizing a mixed-methods research design, this study integrates Google Maps review content analysis with Social Network Analysis to delineate public perceptions and identify areas for service enhancement in public libraries. It innovatively leverages personal experiences extracted from over 60,000 Google Maps reviews to evaluate public library services in cities such as Taipei, New Taipei, Taoyuan, Taichung, Tainan, and Kaohsiung. The research taps into the National Library of Taiwan's National Library Statistics System to provide a robust analysis of library performance and user satisfaction, offering a novel perspective by emphasizing user-centric feedback from Google Maps as a primary data source. This approach provides quantitative data on library usage and geographic distribution and enriches our understanding of the qualitative experiences of library users. In analyzing the keywords from Google Maps reviews of public libraries, we categorize and interpret these under the three core LibQUAL+ dimensions—Affect of Service, Information Control, and Library as Place. The findings expose variances in perceived service quality among the cities, with Kaohsiung and Taichung receiving the highest accolades for service satisfaction. Simultaneously, the study identifies potential areas for improvement, particularly in cities with lower satisfaction ratings like Taipei. This personalized feedback illustrates the intimate relationship between public libraries and their communities, offering invaluable insights for policymakers and library management to enhance service delivery and user experience.

The introduction of ChatGPT in academia has raised significant concerns, particularly regarding issues like plagiarism and the ethical use of generative text for academic purposes. Existing literature has predominantly focused on ChatGPT adoption, leaving a notable gap in addressing the strategies users employ to mitigate these emerging challenges. To bridge this gap, this research utilizes the Uncertainty Reduction Theory (URT) to formulate user strategies for reducing uncertainty. These strategies include both interactive and passive approaches. Concurrently, the study identifies key sources of uncertainty, which include concerns related to transparency, information accuracy, and privacy. Additionally, it introduces the concepts of seeking clarification and consulting peer feedback as mediating roles to facilitate reduced uncertainty. We tested these hypotheses with a sample of Indonesian users (N = 566) using structural equation modeling via Smart-PLS 4.0 software. The results confirm that interactive Uncertainty Reduction Strategies (URS) are more effective in reducing uncertainty when using ChatGPT compared to passive URS. Transparency concerns, information accuracy, and privacy concerns are identified as factors that increase the level of uncertainty. In contrast, consulting peer feedback is the most effective strategy for reducing uncertainty compared to seeking clarification at the individual-system level. Insights from the mediating effects confirm that consulting peer feedback significantly mediates uncertainty sources to reduce uncertainty. The study discusses various strategies for the ethical use of ChatGPT by users in the educational context and contributes significantly to theoretical development.

An event-based dynamic output feedback control (DOFC) strategy for unmanned marine vehicle (UMV) systems is concerned. The whole UMV systems are composed of an UMV closed-loop system, a land-based control unit and the communication network. To increase the effectiveness of data transmission in the network channel and better enable the control unit against attack, an adaptive event-triggered mechanism (AETM) is applied. Moreover, a quantizer is installed between the sampler and the control unit. The quantizer further reduces the communication burden. The occurrence of aperiodic denial-of-service (DoS) attack is considered in the channel from the control unit to the UMV system. Sufficient criterion for ensuring global exponential stability of system with an expected H∞ disturbance attenuation index is obtained. Co-design of the dynamic output feedback controller and the AETM is derived. The effectiveness of the proposed approach is verified in the given illustrative simulation. The simulation results indicate that the reduction percentages of yaw angle amplitudes and yaw velocity accumulative error of the UMV system with the control strategy proposed in this paper are 43.2%and 45.9%, respectively, which are 0.3% and 5.8% improvement in both metrics compared to the previously published work.

This paper proposes an optimal trading algorithm based on a novel application of the conventional Control Engineering (CE). We consider a fundamental CE concept, namely, the feedback control and apply it to the Algorithmic Trading (AT). The concrete feedback control strategy is designed in a form of the celebrated Proportional-Integral-Derivative (PID) model. The highly fluctuating nature of the modern financial markets has led to the adoption of a model-free realisation of the generic PID framework. The control theoretical methodology we propose is combined with the advanced statistics for the historical market data. We obtain a specific log-normal probability distribution function (pdf) associated with the specific quantities associated with the available stock data. The empirical log-normal pdf mentioned above makes it possible the necessary PID gains optimization. For this aim, we apply the data-driven optimization approaches and consider the corresponding Monte Carlo solution procedure. The optimized PID trading algorithm we propose is also studied in the Fourier analysis framework. This equivalent frequency domain representation involves a new concept in the financial engineering, namely, the "stock market energy" concept. For the evaluation, we implement the proposed PID optimal trading algorithm and develop a Python based prototype software. We finally apply the corresponding prototype software to a dataset from the Binance BTC / USDT stock market. The experimental result illustrates the implementability of the proposed optimal PID trading scheme and also shows the effectiveness of the proposed CE methods in the modern AT.

Patients often need the use of their arms to assist with functional activities, but after bone disruption, pushing is frequently limited to less than 4.5 kg. No method exists to measure arm weight bearing objectively in clinical settings. This project aimed to design, construct, and test a walker for patients who need to limit arm force to prevent excessive bone stress during post-fracture (iatrogenic or traumatic) ossification. First, a qualitative study was conducted to obtain critiques of a Clinical Force Measuring (CFM) walker prototype from rehabilitation professionals. Key statements and phrases were coded that allowed “themes” to emerge from transcribed interviews, which guided device revisions. Next, a second CFM Walker prototype was designed based on the qualitative data and device criteria/constraints and finally tested. The result was fabrication of a new lightweight, streamlined, and cost-effective prototype walker with a simple visual display and auditory cue with upper limit alarms. Key features included attachments for medical equipment and thin film force-sensing resistors integrated into the walker handles that progressively activated 3 LEDs and a buzzer when arm force exceeded programmed thresholds. The innovative CFM Walker will help patients with restricted arm weight bearing, especially elderly adults, recover safer and faster in the future.

In response to droughts, various media campaigns and water saving instructions are released, often however, with only temporary water conservation effects. A promising development is this regard are Digital Water Meters (DWM) that provide near real-time water-use feedback. Despite extensive DWM experience in some water-stressed regions, a profound understanding of the initial attitude towards DWM and message tailoring opportunities are rarely empirically explored. Therefore, we aim to obtain insights into the attitude towards the introduction of DWM and explore opportunities for message tailoring, a topic of extra relevance as we may be on the threshold of a large-scale implementation in many world regions. Messages tailored to (i) normative beliefs and attitudes on drinking water, (ii) water-use activity and (iii) phase of decision-making, seem particularly compatible with DWM. Through a survey (n=1037) in the Netherlands, we observe that 93% of respondents have no objections utility investments in DWM and that 78% would accept a free DWM because of improved leakage detection, lower costs and environmental considerations. Finally, instead of sociodemographic factors, we observed that an attitude-based customer segmentation approach proved an especially useful predictor of respondent’s motivation to endorse DWM and forms a promising basis for water conservation message-tailoring strategies.

In this paper, the stability control of the inverted pendulum on a cart with a disturbance forces has been done using observer based and full state feedback H2 controllers. The Lagrangian equation has been used to model the system equation of motions and linearized the system to the unstable upward position. Comparison of the system stability has been simulated by comparing the proposed controllers using Matlab/Scripts and a promising results has been analyzed successfully.

In this paper we present an application of the dynamic tracking games framework to a monetary union. We use a small stylized nonlinear three-country macroeconomic model of a monetary union to analyse the interactions between fiscal (governments) and monetary (common central bank) policy makers, assuming different objective functions of these decision makers. Using the OPTGAME algorithm we calculate solutions for several games: a noncooperative solution where each government and the central bank play against each other (a feedback Nash Equilibrium solution), a fully cooperative solution with all players following a joint course of action (a Pareto optimal solution), and three solutions where various coalitions (subsets of the players) play against coalitions of the other players in a noncooperative way. It turns out that the fully cooperative solution yields the best results, the noncooperative solution fares worst, and the coalition games lie in between, with a broad coalition of the fiscally more responsible countries and the central bank against the less thrifty country coming closest to the Pareto optimum.

This paper investigates the leader-following H∞ consensus of fractional-order multi-agent systems (FOMASs) under input saturation via the output feedback. Based on the bounded real lemma for FOSs, the sufficient conditions of H∞ consensus for FOMASs are provided in α∈0,1 and 1,2, respectively. Furthermore, the iterative linear matrix inequalities (ILMIs) approaches are applied for solving quadratic matrix inequalities (QMIs). The ILMI algorithms show a method to derive initial values and transform QMIs into LMIs. Mathematical tools are employed to transform the input saturation issue into optimal solution of LMIs for estimating stable regions. The ILMI algorithms avoid the conditional constraints on matrix variables during the LMIs construction and reduce conservatism. The approach does not disassemble the entire MASs by transformations to the Laplacian matrix, instead adopting a holistic analytical perspective to obtain gain matrices. In the end, numerical examples are conducted to validate the efficiency of the approach.

In the DC distribution networks, DC bus voltage is maintained by the grid-connected converter, the controllability and reliability of the grid-connected converter significantly affects the bus voltage characteristic. To address the problem of limited stability and frequent oscillations, this paper proposes a state feedback control method for the AC/DC converter. Conventional AC/DC converter adopts the voltage-current double-closed-loop control structure with the proportional integral (PI) controllers, which is the equivalent of the typical type II control system, but the typical type II control system cannot fully settle the stability and immunity problems. In contrast, the state feedback control strategy not only achieves the control objectives of the traditional double-closed-loop control, but also reduce the AC/DC converter system model to a typical I-type system, which improves the stability, thus enhances the oscillation suppression capability of the bus voltage. By selecting multiple state variables and designing the converter pole configuration range, the proposed single-loop state feedback control method manages to optimize both the dynamic and steady-state performances of the grid-connected AC/DC converter. Finally, the effectiveness of the proposed single-loop state feedback control strategy has been verified by both the simulation and experiment results.

Although flow mixing and cooling can be greatly enhanced when considering the use of Fluidic Oscillators (FO), they are more commonly employed in Active Flow Control (AFC) applications where the injected pulsating flow interacts with the boundary layer in order to usually delay its separation. In fact, prior to any FO implementation in a given application, it is essential to study the range of frequencies and amplitudes it can generate as a function of the incoming mass flow and its dimensions. This point is what is being enlightened in the present manuscript for a rather novel FO configuration. We are numerically studding a standard FO configuration in three dimensions 3D and also using a two dimensional 2D approach. After comparing the 3D and the 2D results and analyzing the main differences, we modified some of the internal dimensions of the FO in order to evaluate the variation of its dynamic performance. The present results clarify which internal dimensional modifications are more effective in generating larger output frequencies and velocity field variations. Care is taken to analyze the origin of the self sustained oscillations. In fact, the present research needs to be seen as the continuation of a former one recently published , where the effect of several Reynolds numbers as well as some different internal dimensions was considered.

This paper focuses on distributed generation (DG) controller of a PV based Micro Grid. An independent DG controller (IDGC) is designed for PV applications to improve maximum power point tracking (MPPT) in Micro Grid (MG). Extreme learning machine (ELM) based MPPT method exactly estimate the reference input of converter control. They are voltage and current at MPP. Feedback controls employ linear PI schemes or nonlinear, intricate techniques. Here the converter controller, IDGC is improved by measuring directly converter outputs like duty cycle. PWM index in a single DG PV-based MG. It introduces a fast learning Extreme Learning Machine (ELM) using Moore-Penrose pseudo-inverse and an online-sequential ridge re method for robust CR estimation. The approach ensures the stability of the microgrid during PV uncertainties. Internal DG control approach (IDGC) improves the strength of the Micro Grid during, three-phase faults at load bus, partial shading, irradiance change, islanding operation and load change. The model is designed and simulated in MATLAB/SIMULINK platform and some of the results are validated in hardware in simulation (HIL) platform.

In this paper, the existence of optimal solutions for problems governed by differential equations involving feedback controls is established, when the problem must account for a Volterra-type distributed delay and is subject to the action of impulsive external forces. The problem is reformulated within the class of impulsive semilinear integro-differential inclusions in Banach spaces and is studied using topological methods and multivalued analysis. The paper concludes with an application to a population dynamics model.

This study investigates the impact of real-time emotional feedback on the quality of teamwork conducted over videoconferencing. We developed a framework that provides real-time feedback through a virtual mirror based on facial and voice emotion recognition. In an experiment with 28 teams (84 participants), teams collaborated over Zoom to set up a virtual Mars station using custom simulation software. Participants were divided into 14 experimental teams which were shown the virtual mirror, and 14 control teams without it. Team performance was measured by the improvement in the Mars simulation output quality. Our analysis using correlation, multilevel regression, and machine learning revealed that fewer interruptions but an increasing number over time correlated with higher performance. Higher vocal arousal and happiness also enhanced performance. We confirmed that female presence in teams boosts performance. SHAP values indicated that high variability in happiness, head movement, and positive facial valence—an “emotional rollercoaster”—positively predicted team performance. The experimental group outperformed the control group, suggesting that virtual mirroring improves virtual teamwork and that interrupting each other more, while speaking less, leads to better results.

Using the potent tools of information geometry (IG), the current research analyses the information geometrics of the five-dimensional HTBFC Manifold. By enabling a unique revolutionary analysis for the performance of Human-Trust Based Feedback Control (HTBFC), the integration of information geometry into HTBFC facilitates the relativistic analysis of the five-dimensional HTBFC manifold. Both the two- and three-dimensional manifold subcases are investigated. This work provides a ground-breaking approach to IG unification of Human- Machine Interactions (HMIs). Some potential applications of HTBFC to robotics are presented.Conclusions are provided, along with some emerging open problems and recommendations for future research.

Generating localized haptic feedback on touch displays has been a challenge in recent years. In this study, we introduce a haptic interface using transparent thin-film PVDF actuators to address this issue. The transparency feature allows for mounting the actuators at any location beneath the display, enabling localized haptic feedback as the generated vibration is primarily evident on the mounting area. Two different configurations are designed, simulated and prepared to explore the effectiveness of the proposed approach. The first configuration is used to characterize the haptic interface. Modal and forced-vibration analysis are performed to identify important design characteristics based on human factor considerations. Subsequent 2AFC psychophysics experiments validate the characteristics. In the second configuration, eight actuators are attached to the touch surface in a 2x4 matrix formation and excited at different voltage amplitudes. Human experiments are conducted based on the results from corresponding forced-vibration analysis. The results show that subjects demonstrate an accuracy of 96% in identifying locations with haptic feedback when the actuators are excited with 232 Vpp. Overall, our study demonstrates the effectiveness of the haptic interface equipped with PVDF-type actuators in achieving localized haptic feedback on touch displays.

A block-diagonal fuzzy neural network for short-term load forecasting is proposed. DBD-FELF consists of fuzzy rules with consequent parts that are neural networks with internal recurrence. These networks have a hidden layer which consists of pairs of neurons with feedback connections between them. The overall fuzzy model partitions the input space in partially overlapping fuzzy regions, where the recurrent neural networks of the respective rules operate. The partition of the input space and determination of the fuzzy rule base is performed by use of Fuzzy C-Means clustering algorithm and the RENNCOM constrained optimization method is applied for consequent parameter tuning. The electric load time-series of the Greek power system is examined, and hourly-based forecasting for the whole year is performed. The performance of DBD-FELF is tested via extensive experimental analysis and the results are promising, since an average percentage error of 1.18% is attained, along with an average yearly absolute error of 76.2 MW. Moreover, DBD-FELF is compared with Deep Learning, fuzzy and neurofuzzy rivals, such that its particular attributes are highlighted.

This research work presents the nonlinear control framework to estimate and reject the mismatched lumped disturbances acting on the nonlinear uncertain system. It is an unfortunate fact that the conventional Extended State Observer (ESO) is not capable to estimate the mismatched lumped disturbance and its derivative simultaneously for the systems. Also, the basic ESO is only suitable for systems with Integral Chain Form (ICF) structure. Similarly, the conventional Feedback Linearizing Control (FLC) approach is not robust for stabilizing the systems in the presence of disturbances and uncertainties. Hence, the nonlinear control framework is proposed to overcome the above issues which are composed of, (a) Dual Extended State Observer (DESO), and (b) DESO based FLC. The DESO provides information on the unmeasured state, mismatched disturbance, and its derivative. While the DESO-FLC utilizes the information from DESO to counter the effect of such disturbances and to stabilize the nonlinear systems around the reference point. The detailed closed-loop analysis is presented for the proposed control framework in the presence of lumped disturbances. The performance robustness of the presented design has been validated for the third order, nonlinear, unstable, and disturbed Magnetic Levitation System (MLS). The results of the DESO-FLC approach are compared with the most popular Linear Quadratic Regulator (LQR) and nonlinear FLC approaches based on the integral error criterion and the average electrical energy consumption.

The study reports about a case of a lung cancer patient with increasing difficulties in falling asleep and frequent periods of wakefulness. Severe dyspnea related to pneumonitis caused as a side effect of immunotherapy worsened the situation. Eventually, fear of falling asleep developed, including panic attacks and anxiety of choking, which was shown to lead to nights of complete wakefulness. The patient did not only sleep poorly; he did not sleep at all at night for several days, as evidenced by the notes he made during the night. Polygraphy showed no evidence of sleep-disordered breathing, but frequent periods of wakefulness and reduced basal saturation around 90% during sleep due to lung changes such as extensive functional failure of the left upper lobe with position-dependent shunts. The authors hypothesized that the symptoms described were causally related to a drop in oxygen saturation in the patient's blood. Therefore, they pursued the goal of finding a measurement technique that is as inexpensive as possible and that the patient can operate without outside assistance and great effort. So the patient started using a low-cost wearable device that allows simultaneous measurements of blood oxygen content, pulse rate and movement intensity. It consists of a finger ring with pulse oximetry sensor and a wristband with the control unit containing a vibration motor. The described device reliably warned of disturbances in oxygen concentration in the blood during the night with its vibration alarm. By use of that device during the whole night at home, the events of reduced oxygen saturation and the anxiety symptoms were reduced. Sleep disturbances with sudden awakenings did not occur when using the device. The patient benefited from the security gained in this way and slept much more peacefully, and he could spend nights without waking up again. In conclusion, wearable oximeters with vibration alarm can be recommended for patients’ home care in lung cancer patients.

This work presents an alternative to harnessing wind energy with an Electromagnetic Frequency Regulator (EFR) coupled to a hydrostatic transmission and associated with a horizontal axis wind turbine, a bidirectional frequency inverter and a secondary energy source, in a hybridized system. The hydrostatic transmision is composed by a fixed displacement axial piston pump and a variable displacement, swash plate, axial piston motor. Feedback linearization was used as a technique to control the motor geometric displacement, and a prediction algorithm for the steady state rotations of the armature and the electromagnetic field has been developed. A 5\,kW project was simulated on a Scilab platform, with combinations of constant or variable load, and constant or variable wind speed. The results indicated that the system was able to supply the generator load, adapting to fluctuations in wind speed. The possibility of storing wind energy through the inverter has also been proven. The system can accumulate energy in batteries during the fastest wind regimes, to use it when the turbine power is lower than the load.

The current work addresses the control of two-input two-output (TITO) Wood and Berry model of a binary distillation column. The controller design problem is formulated in terms of multivariable H_∞ control synthesis. The controller structure takes the form of simplest static output feedback (SOF) control. The controller synthesis is performed using a hybrid approach of blending linear matrix inequalities (LMI) and genetic algorithm (GA). The performance of the static output feedback controller is compared with three other controllers designed for Wood and Berry model available in the literature. The first simulation study is performed for the case of tracking a unit step command in the presence of a step change in output disturbance. A second simulation study is performed for rejecting a change in sinusoidal output disturbance.

The design of a mixed-mode proportional-integral-derivative (PID) controller circuit using current-feedback operational amplifiers (CFOAs) as active components is proposed. With the same circuit topology, the proposed configuration of three CFOAs, four resistors, and two capacitors is capable of performing the PID controller in all four operation modes: namely voltage mode, trans-admittance mode, current mode, and trans-impedance mode. Numerous mathematical analyses are conducted to determine the controller performance under ideal and non-ideal conditions. Additionally, the mixed-mode second-order lowpass filter is suggested, and also used to examine the workability of the proposed mixed-mode PID controller in a feedback control structure. The proposed PID controller is implemented with the commercially available IC-type CFOA AD844, and the simulation results are presented to illustrate the functionality of the controller and its closed-loop control system.

This study proposed to use wearable EEG to study the impact of vipassana mindfulness practice on beginner's physiological and neurological responses. Mindfulness meditation has been shown to have numerous benefits, including stress reduction, improved attention and cognitive function, and enhanced emotional regulation. The roots of mindfulness meditation in Buddhism emphasize cultivating present-moment awareness and insight. However, the neural mechanisms together with physiological mechanism and their interaction underlying these benefits remain poorly understood. Method: One middle age man (50 years old) participated in this longitudinal study using wearable EEG to investigate the neurophysiological change during a one-month consecutive vipassana mindfulness practice. Both EEG and heart rate responses were recorded each time, before (5 minutes), during (20 minutes), and after (5 minutes) meditation sessions. The EEG and HR data were analyzed by Matlab and EEGlab to examine changes in brainwave activity and heart rate. Results: alpha peak frequency (APF) is significantly lower after mindfulness meditation, as shown by comparison of APF before mindfulness (pre-5) and during mindfulness practice (med-20), and comparison between APF of pre-5 and after mindfulness practice (post-5). The same is with the beta peak power. While for theta peak frequency, it is significant lower during mindfulness meditation (med-20), when comparing to either pre-5 or post-5. See figure 1a. However, peak power index is not so sensitive, and it is more obvious in theta wave band. That is, the theta power peak is significantly lower after meditation, as can be observed in comparison between pre-5 and med-20, also between pre-5 and med-20. See figure 1b. STATE Heart-mean (bpm) Heart-std(bmp) pre-5 69.88 3.88 med-20 68.36 2.81 post-5 69.55 4.13 t-value test (pre-med) 0.0694 0.0003 t-value test (pre-post) 0.7934 0.3656 t-value test (post-med) 0.3193 0.0001 Table 1. The difference of Heart rate (mean and SD) in before (pre-5), during (med-20) and after (post-5)mindfulness meditation. We find significant change in standard deviation (SD) of heart rate between meditation and non-meditation mental states, as shown in table 1. The study provides insights into the underlying neurophysiological mechanisms of mindfulness meditation using wearable EEG devices. It demonstrates that in term of EEG measurement, spectrum frequency can be more sensitive than spectrum power; also heart rate variability as measured by SD is more sensitive to mean of HR. The proposed study contributes to the literature by using wearable EEG devices to collect data in a more accessible and convenient manner.

The complexity of objects and control systems increases the requirements for mathematical models. The structural identifiability (SI) assessment of nonlinear systems is one of the identification problems. Until now, this problem solves by parametric methods using various approximation methods. This approach is not always effective under uncertainty. We apply an approach to SI estimation based on the analysis of virtual structures. The requirements form for the system input based on the expansion of the excitation constancy property and S-synchronizability. The approach generalization to structural identifiability used in the analysis of systems with symmetric nonlinearity is given. homothety and identifiability conditions for systems with non-symmetric nonlinearities (SNN) obtained. The detectability and recoverability proofed for virtual frameworks (VF) guaranteed the SI estimation under uncertainty. The conditions under which the non-symmetric nonlinearity is hypothetical symmetric nonlinearity obtained. SI estimation examples considered for closed nonlinear systems under uncertainty.