Real-time Experiments Research Articles

Understanding Arab social TV viewers’ perceptions of virtual reality acceptance

Social TV has become a part of contemporary functioning and viewing patterns. It enhances the television watching experiences of audiences and introduces new trends that can communicate different viewers. This study examines the social TV experiences of Jordanian young audiences regarding using virtual reality (VR) acceptance to understand their real-time experiences. A cross-sectional study design with randomly selected 354 individuals from Jordan was analysed utilizing the Structural Equation Modelling (SEM) to also examine the strength of every factor regarding VR used for social TV. Results showed four factors were directly linked to watching social TV (experiences, real-time, digital content, face-to-face communication). Therefore, the study also concluded that the prominent role of VR in enhancing social TV experiences regarding factors, e.g., entertainment, communication, and information sharing, its impact is a complex phenomenon, however.

Urokinase-type plasminogen activator blockade ameliorates experimental colitis in mice

Although several angiogenesis-related factors are reportedly involved in the pathogenesis of ulcerative colitis (UC), the mechanisms by which they contribute to disease are unclear. We first examined the expression of angiogenesis-related factors in inflamed colorectal tissue of UC patients using antibody array, and identified the 5 factors with highest expression, which included matrix metalloproteinase-8, urokinase-type plasminogen activator (uPA), angiostatin/plasminogen, hepatocyte growth factor and endoglin. Subsequent real-time PCR experiments using additional colorectal tissues revealed that uPA mRNA levels were significantly higher in inflamed tissues than in non-inflamed tissues, and significantly correlated with the severity of UC. Mirror section immunohistochemistry revealed that uPA was expressed in the neutrophils of inflamed colorectal tissues. We administered dextran sulfate sodium (DSS) in drinking water to uPA knockout (uPA−/−) mice, and found that the disease activity index in uPA-/- mice was marginally lower and the histological score in uPA−/− mice was significantly lower than those in wild-type mice, suggesting the importance of uPA in colitis. When an uPA-selective inhibitor, UK122, was administered to DSS-treated C57BL6J mice, the disease activity index and histological score in those mice were significantly lower compared with control mice. Multiple cytokine/chemokine assay using colorectal tissues from uPA−/− and UK122-treated mice revealed significantly lowered level of RANTES. In conclusion, uPA was highly expressed in neutrophils of the inflamed mucosa of UC patients, and the expression level correlated with the severity of UC. Genetic uPA deletion or pharmacological uPA blockade significantly ameliorated colitis in mice, concomitant with downregulation of RANTES.

Performance Evaluation of an Evacuated Flat-Plate Collector System for Domestic Hot Water Applications

AbstractRapid population growth and increasing energy demand in developing countries are the key drivers behind rising concerns such as energy poverty and environmental degradation. Harnessing solar energy can help the developing countries inch closer to sustainable economic growth. This article presents the performance analysis of a solar water heating system based on an evacuated flat-plate collector (EFPC). EFPCs offer higher optical performance and lower thermal losses in comparison with conventional solar collectors. In this study, a multiparametric analysis provides the guidelines for the design and optimization of a novel low vacuum EFPC system under ambient conditions, for domestic hot water (DHW) applications. A small-scale solar thermal collector system based on a low vacuum (17.5–20 kPa) EFPC of a total area of 4.0 m2 is designed and installed. The system is coupled with a storage tank composed of the helical copper coil configuration inside the tank, which is used as a heat exchanger from a primary loop to a secondary loop. A series of real-time experiments are performed under ambient conditions from December to April. The thermal efficiency of the EFPCs reaches a maximum value of 73.2%, with the glycol–water mixture as a heat transfer fluid at an inlet temperature of 31.2 °C, when the ambient temperature is 15.3 °C, average irradiance is 679.2 Wm−2, and vacuum pressure is 20 kPa. For this duration, the exergy efficiency reaches a peak value of 16%. This EFPC system provides 100 liters of hot water at 57–69 °C per day for DHW consumption when the average ambient temperature is 24 °C. The overall results highlight the potential of EFPCs for hot water applications. Furthermore, an efficiently optimized EFPC system can also be used for space heating during the winter season.

Web-based digital twin online laboratories: Methodologies and implementation

Background: Online laboratories that provide online experimentation are crucial for education and research in all fields of engineering. As a transformative technology, the digital twin can be potentially applied into online laboratories to enable physical-digital twin interactions and enhance user experience. Methods: In this article, web-based digital twin online laboratories are discussed, the methodologies and implementation of which are presented in detail. The digital twin architecture, three-dimensional twin model, web-based digital twin control algorithm design, and real-time physical-twin control are explored to provide a full picture for the design and implementation of digital twin online laboratory systems. To illustrate the effectiveness of the proposed methodologies, a use case with the Networked Control System Laboratory (a previously developed control and automation laboratory) is provided, which details the design and implementation. Results: A four-tier web architecture has been implemented. With the provided web interface, control algorithms can be designed and employed for real-time digital twin experimentation. The experimental results demonstrated that the physical-digital twin fan speed control system can achieve good control and tracking performance with human-in-the-loop interactions. Conclusions: This article presents the methodologies and implementation of digital twin web-based online laboratories. The use case verified the proposed web architecture, digital twin implementation, control architecture, and human-in-the-loop interactions for a digital twin experimentation system, which can potentially be used for the design and implementation of other digital-twin applications in different fields.

Identification and validation of BCL6 and VEGFA as biomarkers and ageing patterns correlating with immune infiltrates in OA progression

Osteoarthritis (OA), the most common type of arthritis, is a complex biological response caused by cartilage wear and synovial inflammation that links biomechanics and inflammation. The progression of OA correlates with a rise in the number of senescent cells in multiple joint tissues. However, the mechanisms by which senescent cells and their involvement with immune infiltration promote OA progression are not fully understood. The gene expression profiles and clinical information of OA and healthy control synovial tissue samples were retrieved from the Gene Expression Omnibus database, and then differential analysis of senescence regulators between OA and normal samples was performed. The random forest (RF) was used to screen candidate senescence regulators to predict the occurrence of OA. The reverse transcription quantitative real-time PCR experiments at tissue’s level was performed to confirm these biomarkers. Moreover, two distinct senescence patterns were identified and systematic correlation between these senescence patterns and immune cell infiltration was analyzed. The senescence score and senescence gene clusters were constructed to quantify senescence patterns together with immune infiltration of individual OA patient. 73 senescence differentially expressed genes were identified between OA patients and normal controls. The RF method was utilized to build an OA risk model based on two senescence related genes: BCL6 and VEGFA. Next, two distinct aging patterns were determined in OA synovial samples. Most patients from senescence cluster A were further classified into gene cluster B and high senescence score group correlated with a non-inflamed phenotype, whereas senescence cluster B were classified into gene cluster A and low senescence score group correlated with an inflamed phenotype. Our study revealed that senescence played an important role in in OA synovial inflammation. Evaluating the senescence patterns of individuals with OA will contribute to enhancing our cognition of immune infiltration characterization, providing novel diagnostic and prognostic biomarkers, and guiding more effective immunotherapy strategies.

Complex Fractional-Order LQIR for Inverted-Pendulum-Type Robotic Mechanisms: Design and Experimental Validation

This article presents a systematic approach to formulate and experimentally validate a novel Complex Fractional Order (CFO) Linear Quadratic Integral Regulator (LQIR) design to enhance the robustness of inverted-pendulum-type robotic mechanisms against bounded exogenous disturbances. The CFO controllers, an enhanced variant of the conventional fractional-order controllers, are realised by assigning pre-calibrated complex numbers to the order of the integral and differential operators in the control law. This arrangement significantly improves the structural flexibility of the control law, and hence, subsequently strengthens its robustness against the parametric uncertainties and nonlinear disturbances encountered by the aforementioned under-actuated system. The proposed control procedure uses the ubiquitous LQIR as the baseline controller that is augmented with CFO differential and integral operators. The fractional complex orders in LQIR are calibrated offline by minimising an objective function that aims at attenuating the position-regulation error while economising the control activity. The effectiveness of the CFO-LQIR is benchmarked against its integer and fractional-order counterparts. The ability of each controller to mitigate the disturbances in inverted-pendulum-type robotic systems is rigorously tested by conducting real-time experiments on Quanser single-link rotary pendulum system. The experimental outcomes validate the superior disturbance rejection capability of the CFO-LQIR by yielding rapid transits and strong damping against disturbances while preserving the control input economy and closed-loop stability of the system.

An OCF-IoTivity enabled smart-home optimal indoor environment control system for energy and comfort optimization

The growing energy demand with diminishing energy resources calls for development of optimal indoor control system through accurate energy and occupant comfort modeling in a smart-home. While some major obstacles faced by smart-home IoT network are heterogeneity and disparate IP frameworks resulting in a connectivity and interoperability issues. In this paper we developed a new Open Connectivity Foundation (OCF) based prediction assisted optimal control framework for optimizing energy consumption and maximizing occupant comfort in smart-home. To the best of our knowledge, we are the first to design a scalable, secure, and inter-operable optimal control solution for smart-home IoT networks. The developed framework offloads machine learning models on IoT device for accurate energy and thermal comfort modeling to enable prediction assisted optimization. The system enables edge analytics using deep learning based inference models for proactive response. For optimization standard Firefly algorithm is modified based on inertia weight approach to achieve improved performance. OCF based optimal actuator control test-bed deployment and real-time experimentation is conducted to evaluate the performance of the system. Empirical investigation verified the effectiveness of proposed framework with energy saving scope of 36.82%, 5 s average response time and 3.36 MS Round Trip Time.

A Lyapunov-based robust control for permanent magnet synchronous motor in the modular joint of collaborative robot

AbstractIn order to decrease the influence of system parameters and load on the dynamic performance of permanent magnet synchronous motor (PMSM) in cooperative robot joint modules, a practical model-based robust control method was proposed. It inherits the traditional proportional-integral-derivative (PID) control and robust control based on error and model-based control. We first set up the nominal controller using the dynamics model. In order to limit the influence of uncertainty on dynamic performance, a robust controller is established based on Lyapunov method. The control can be regarded as an improved PID control or a redesigned robust control. Compared with the traditional control method, it is simple to implement and has practical effects. It is proved by theoretical analysis that the controller can guarantee the uniform boundedness and uniform final boundedness of the system. In addition, the prototype of fast controller cSPACE is built on the experiment platform, which averts long-time programming and debugging. It offers immense convenience for practical operation. Finally, numerical simulation and real-time experiment results are presented. Based on cSPACE and a PMSM in the joint module of a practical cooperative robot, the availability of the control design and the achievable control performance are verified.

Interventionist research in management accounting: promoting engagement through face-to-face dialogues

PurposeThis paper explores face-to-face dialogues between practitioners and interventionist researchers in the management accounting (MA) field during real-time interactions for the development of accounting devices. It aims to shed light on whether and how these dialogues can affect the construction of meanings around the devices, thereby influencing the course of interventionist research (IVR) projects.Design/methodology/approachThis study presents a reflective analysis (both in itinere and ex-post) of an IVR project conducted by one of the authors within a healthcare organisation. It draws on a dialogical perspective to delve into the conversations between the author and the organisation's chief executive officer (CEO) during one-to-one meetings for developing a new strategic dashboard.FindingsThe findings show that a lack of alignment between the images invoked by verbal forms and the device representations can hinder accounting IVR projects. Obstacles can be overcome when the researcher, by acting upon verbal forms and device representations that mutually reinforce each other, shapes the practitioner's expectations creating shared meanings around the device. This occurs during face-to-face interactions in which the researcher recognises the trialogue with the practitioner and the device, thereby affecting the practitioner's mode of engagement.Originality/valueThis paper contributes to improving the understanding of how researchers can affect practitioners' conceptualisation of accounting devices through the real-time experience of face-to-face dialogues. In doing so, it sheds light on the potential for IVR in MA to embrace a dialogical perspective. The paper also contributes more broadly to studies on the relationship between verbal and written accounting forms.

Carbogen-Induced Respiratory Acidosis Blocks Experimental Seizures by a Direct and Specific Inhibition of NaV1.2 Channels in the Axon Initial Segment of Pyramidal Neurons.

Brain pH is a critical factor for determining neuronal activity, with alkalosis increasing and acidosis reducing excitability. Acid shifts in brain pH through the breathing of carbogen (5% CO2/95% O2) reduces seizure susceptibility in animal models and patients. The molecular mechanisms underlying this seizure protection remain to be fully elucidated. Here, we demonstrate that male and female mice exposed to carbogen are fully protected from thermogenic-triggered seizures. Whole-cell patch-clamp recordings revealed that acid shifts in extracellular pH (pHo) significantly reduce action potential firing in CA1 pyramidal neurons but did not alter firing in hippocampal inhibitory interneurons. In real-time dynamic clamp experiments, acidification reduced simulated action potential firing generated in hybrid model neurons expressing the excitatory neuron predominant NaV1.2 channel. Conversely, acidification had no effect on action potential firing in hybrid model neurons expressing the interneuron predominant NaV1.1 channel. Furthermore, knockdown of Scn2a mRNA in vivo using antisense oligonucleotides reduced the protective effects of carbogen on seizure susceptibility. Both carbogen-mediated seizure protection and the reduction in CA1 pyramidal neuron action potential firing by low pHo were maintained in an Asic1a knock-out mouse ruling out this acid-sensing channel as the underlying molecular target. These data indicate that the acid-mediated reduction in excitatory neuron firing is mediated, at least in part, through the inhibition of NaV1.2 channels, whereas inhibitory neuron firing is unaffected. This reduction in pyramidal neuron excitability is the likely basis of seizure suppression caused by carbogen-mediated acidification.SIGNIFICANCE STATEMENT Brain pH has long been known to modulate neuronal excitability. Here, we confirm that brain acidification reduces seizure susceptibility in a mouse model of thermogenic seizures. Extracellular acidification reduced excitatory pyramidal neuron firing while having no effect on interneuron firing. Acidification also reduced dynamic clamp firing in cells expressing the NaV1.2 channel but not in cells expressing NaV1.1 channels. In vivo knockdown of Scn2a mRNA reduced seizure protection of acidification. In contrast, acid-mediated seizure protection was maintained in the Asic1a knock-out mouse. These data suggest NaV1.2 channel as an important target for acid-mediated seizure protection. Our results have implications on how natural variations in pH can modulate neuronal excitability and highlight potential antiseizure drug development strategies based on the NaV1.2 channel.

Carrier recovery for satellite-to-ground coherent laser communication systems using double feedback loop and Viterbi–Viterbi feedforward cascade structure

High dynamic and wide range frequency offset in satellite-to-ground coherent optical communication system caused by Doppler frequency shift, transceiver laser frequency offset and laser frequency stabilization technology based on perturbation is one of the important differences compared with terrestrial fiber-optic coherent transmission. The design of a reliable frequency offset acquisition and fine carrier tracking algorithm is critical to ground optical stations. Two-stage feedback loop and Viterbi–Viterbi (V–V) feedforward cascaded carrier recovery algorithm is presented in this work. Pre-decision-based angle differential estimator (PADE) is adopted as the residual frequency offset (RFO) estimator in the first stage to estimate the high dynamic and wide range of frequency offset. Then V–V based RFO estimator in the second stage is employed to accurately compensate the residual frequency. V–V algorithm is used to compensate phase offset, which share the same logic resource with V–V based RFO estimator. A real-time 10-Gbps data rate PM-QPSK experiment based on FPGA is performed to evaluate the algorithm performance. The proposed cascaded algorithm exhibits excellent performance in terms of dynamic tracking speed and normalized mean-square-error (MSE) of the FOE.

Real-Time Model Predictive Control for Battery-Supercapacitor Hybrid Energy Storage Systems Using Linear Parameter-Varying Models

This article proposes a new model predictive control (MPC) strategy for the energy management of a battery-supercapacitor (SC) hybrid energy storage system (HESS) for electric vehicle (EV) applications. First, linear parameter-varying (LPV) models of the HESS are developed, which account for battery parameter variations along its state of charge (SOC). Compared with the conventional linear time invariant (LTI) models reported in the literature, the LPV models of the HESS offer higher modeling and prediction accuracy. Based on the LPV prediction model, a real-time LPV-MPC strategy is then proposed to optimally allocate the load current of the HESS between battery and SC to achieve three goals: minimizing the power loss of the HESS, mitigating the battery degradation, and regulating the SOC of the SC. The optimization problem of the LPV-MPC strategy is transformed into a quadratic programming problem, which can be efficiently solved in real time. Simulation studies verify the superiority of the proposed LPV-MPC strategy over the existing energy management strategies in reducing the energy losses and battery degradation of the HESS. Finally, a real-time experiment is carried out to further validate the proposed LPV-MPC strategy for EV applications.

A versatile biaxial stretching device for in situ synchrotron radiation small- and wide-angle x-ray scattering measurements of polymer films.

A biaxial stretching device is designed and developed for the real-time structural measurements of polymer films. This device adopts a vertical layout to perform real-time x-ray scattering measurements. It has a maximum stretching ratio of 8 × 8 in two perpendicular directions. Its maximum experimental temperature and stretching rate are 250 °C and 100 mm/s, respectively. The control accuracies of the experimental temperature and stretching rate are ±1 °C and 0.01mm, respectively. All the parameters related to film biaxial processing, such as stretching speed, stretching ratio, and temperature, can be independently set. The device feasibility is demonstrated via a real-time experiment in a synchrotron radiation beamline. Wide-angle x-ray diffraction, small-angle x-ray scattering, and stress-strain data can be simultaneously obtained during various stretching modes. The proposed device fills the gap between the synchrotron radiation x-ray scattering technique and the biaxial stretching processing of polymer films. This device will play an important role in improving the understanding of the physics behind biaxial polymer processing.

LAS-SG: An Elliptic Curve-Based Lightweight Authentication Scheme for Smart Grid Environments

The communication among smart meters (SMs) and neighborhood area network (NAN) gateways is a fundamental requisite for managing the energy consumption at the consumer site. The bidirectional communication among SMs and NANs over the insecure public channel is vulnerable to impersonation, SM traceability, and SM physical capturing attacks. Many existing schemes’ insecurities and/or inefficiencies call for an efficient and secure authentication scheme for smart grid infrastructure. In this article, we present a privacy preserving and lightweight authentication scheme for smart grid (LAS-SG) using elliptic curve cryptography. The proposed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LAS-SG</i> is proved as secure under the standard model. Moreover, the efficiency of the LAS-SG is extracted through a real-time experiment, which attests that proposed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LAS-SG</i> completes a round of authentication in 20.331 ms by exchanging only two messages and 192 B. Due to the adequate efficiency and ample security, the proposed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LAS-SG</i> is more appropriate for SG environments.

Development of an Interactive Mobile Robot for Playful Learning and Language Teaching

This paper presents a mobile robot for development of interactive games and language learning purposes based on the Kinect v2. The game uses interface seeks to take advantage of human computer interaction in a playful way through gesture recognition. This work combines robotics and games, games and language learning, and some recent developments about robotics and language learning. The hardware used to build the mobile robot is described as well as the ludic game for language teaching by an interface human-robot. Performance of the platform is assessed by means of real-time experiments by students using a non-linear control based on a trajectory tracking during various practices. The experiment proves the platform potential for supporting ludic game and tested successfully and then discuss the results and mention future perspectives.

Real-time transponder architecture for hitless transmission baud rate switching in association with an auto-negotiation protocol

We propose a novel digital signal processing architecture for a coherent receiver that allows instantaneous and hitless variable baud rate transmission for integer sub-division values. This solution allows the receiver to self-adapt a new baud rate without processing modification, re-initialization, or any knowledge of the transmission speed modification. As for implantation concern, this architecture requires negligible extra logic compared to the standard one. Its development and operation developed on a simulation basis are presented; then its dynamic behavior and performance are demonstrated in a real-time experiment attesting a zero-bit loss. We also show how an in-line auto-negotiation protocol between a transmitter and a receiver minimizing the mediation through the control plane can leverage this instantaneous baud rate variation.

A hardware system for real-time decoding of in vivo calcium imaging data.

Epifluorescence miniature microscopes ('miniscopes') are widely used for in vivo calcium imaging of neural population activity. Imaging data are typically collected during a behavioral task and stored for later offline analysis, but emerging techniques for online imaging can support novel closed-loop experiments in which neural population activity is decoded in real time to trigger neurostimulation or sensory feedback. To achieve short feedback latencies, online imaging systems must be optimally designed to maximize computational speed and efficiency while minimizing errors in population decoding. Here we introduce DeCalciOn, an open-source device for real-time imaging and population decoding of in vivo calcium signals that is hardware compatible with all miniscopes that use the UCLA Data Acquisition (DAQ) interface. DeCalciOn performs online motion stabilization, neural enhancement, calcium trace extraction, and decoding of up to 1024 traces per frame at latencies of <50 ms after fluorescence photons arrive at the miniscope image sensor. We show that DeCalciOn can accurately decode the position of rats (n = 12) running on a linear track from calcium fluorescence in the hippocampal CA1 layer, and can categorically classify behaviors performed by rats (n = 2) during an instrumental task from calcium fluorescence in orbitofrontal cortex. DeCalciOn achieves high decoding accuracy at short latencies using innovations such as field-programmable gate array hardware for real-time image processing and contour-free methods to efficiently extract calcium traces from sensor images. In summary, our system offers an affordable plug-and-play solution for real-time calcium imaging experiments in behaving animals.

Near-optimal sliding mode control for multi-robot consensus under dynamic events

We propose a continuous-time design for finite-time consensus control for multi-robot system using event-based near-optimal sliding mode control. The system has a leader–follower framework prone to external bounded disturbance. The proposed design comprises of three parts: (i) formulation of control-affine dynamics, (ii) design a triggering condition for control updates that guarantee stability and consensus in the system, and (iii) design a near-optimal sliding mode control using neural-network based approximate dynamic programming. We derive a bound on inter-event time that guarantees admissibility of updated control input values. We finally validate the efficacy of proposed design through real-time experiments using three Pioneer P3-DX mobile robots (leader and two followers) and comparative analyses with other state-of-the-art approaches. The control updates of follower-1 and follower-2 robots are approximately and , respectively, that reduce the computational burden in multi-robot framework.

Fractional order internal model control of non‐minimum phase and time‐delayed plants

AbstractSeveral applications on fractional order (FO) control have gained considerable significance in the recent years, which led to the evolution of novel tuning strategies of the generalized order FO controllers. Some of the methods in available literatures are based on constrained minimization optimization techniques or analytical method defined only for specific plants. They are valid only for some special model cases. On the contrary, in this technical note, a generalized non‐integer order internal model control (IMC) framework is realized for any order non‐minimum phase (NMP) plants with right half plane (RHP) zero as well as time delayed plants having any finite relative order. Its parameters are graphically interpreted satisfying the frequency domain design stipulations for single input and single output (SISO) higher order linear time invariant (LTI) plants. The performance of the same on a bioreactor fermentation process for its temperature control is found to have outperformed in contrast to its integer order (IO)‐IMC. It is therefore inferred here that this new approach pledges to impart unique solution of the controller parameters, formulating a highly efficient tool outperforming the existing paradigms. Simulation and real time experimentation are presented to validate the method put forward providing satisfactory performance in reference tracking, disturbance rejection, and robustness to various plant parameter perturbations.

Dependency of the source term estimation method for radionuclides released into the atmosphere on the available environmental monitoring data and its applicability to real-time source term estimation

ABSTRACT It is essential to establish a method for reconstructing the source term and spatiotemporal distribution of radionuclides released into the atmosphere due to a nuclear accident for emergency countermeasures. We examined the dependency of a source term estimation method based on Bayesian inference using atmospheric dispersion simulation and environmental monitoring data on the availability of various monitoring data. Additionally, we examined the applicability of this method to a real-time estimation conducted immediately after an accident. A sensitivity analysis of the estimated source term during the Fukushima Daiichi Nuclear Power Station (FDNPS) accident for combinations of various monitoring data indicated that using monitoring data with a high temporal and spatial resolution and the concurrent use of air concentration and surface deposition data is effective for accurate estimation. A real-time source term estimation experiment assuming the situation of monitoring data acquisition during the FDNPS accident revealed that this method could provide the necessary source term for grasping the overview of surface contamination in the early phase and evaluating the approximate accident scale. If the immediate online acquisition of monitoring data and regular operation of an atmospheric dispersion simulation are established, this method can provide the source term in near-real time.