Output Measurements Research Articles

Leader-following consensus control for nonlinear multiagent systems with unknown time-varying measurement sensitivity and infinite communication delays

This paper investigates the consensus problem for nonlinear multiagent systems (MASs) with unknown time-varying measurement sensitivity and infinite communication delays. Unlike existing works, the output measurement sensitivity is described as time-varying, and an infinite communication delay is considered between the agents. Under this condition, a novel output feedback control algorithm is developed. First, based on the hierarchical technique and Lyapunov-based time-domain method, the high-gain compensator and observer are constructed to tolerate the effect of infinite communication delays and accurately estimate the state of the leader. Subsequently, a new distributed k-filter and output feedback controller are proposed, which not only further relax the traditional Lipschitz conditional conservatism but also greatly simplify the design process. It is proved that the closed-loop system is globally stable and all agents can achieve consensus. Finally, the effectiveness of the proposed method is verified through the simulation of the single-link manipulators.

Measurement of non-invasive cardiac output during cycling exercise in ischemic stroke inpatients: A pilot study.

Cardiac dysfunction accompanies acute ischemic stroke and affects the effective implementation of early rehabilitation interventions. There is a lack of reference hemodynamic data on cardiac function in the subacute phase of ischemic stroke. In this study, we aimed to identify appropriate cardiac parameters for exercise training utilizing a pilot study. We used a transthoracic electrical bioimpedance non-invasive cardiac output measurement (NICOM) device to monitor cardiac function in real time for two groups [i.e., subacute ischemic stroke inpatients group (n= 10) and healthy control group (n= 11)] using a cycling exercise experiment. The parameters of both groups were compared to highlight the cardiac dysfunction in the subacute phase in patients with ischemic stroke. We considered stroke volume index (SVI) and systemic vascular resistance index (SVRi) as the primary outcomes, and there was significant intragroup difference (stroke group: P< 0.001; control group: P< 0.001, using one-way ANOVA) and significant intergroup difference at each individual time segment (P< 0.01, using independent t-test). Among the secondary outcomes, i.e., cardiac index (CI), ejection fraction (EF), end-diastolic volume (EDV), and cardiac contraction index (CTI), we found significant intergroup differences in CI, EF, and CTI scores (P< 0.01, using independent t-test). Significant interaction with respect to time and group were seen only in the SVRi and CI scores (P< 0.01, using two-way ANOVA). There was no significant inter- or intra-group differences in EDV scores. SVRI, SVI, and CI values highlight cardiac dysfunction in stroke patients the most. At the same time, these parameters suggest that cardiac dysfunction in stroke patients may be closely related to the increased peripheral vascular resistance caused by infarction and the limitation of myocardial systolic function.

Rethinking Fluid Responsiveness during Septic Shock: Ameliorate Accuracy of Noninvasive Cardiac Output Measurements through Evaluation of Arterial Biomechanical Properties.

Beat-to-beat estimates of cardiac output from the direct measure of peripheral arterial blood pressure rely on the assumption that changes in the waveform morphology are related to changes in blood flow and vasomotor tone. However, in septic shock patients, profound changes in vascular tone occur that are not uniform across the entire arterial bed. In such cases, cardiac output estimates might be inaccurate, leading to unreliable evaluation of fluid responsiveness. Pulse wave velocity is the gold-standard method for assessing different arterial biomechanical properties. Such methods might be able to guide, personalize and optimize the management of septic patients.

Resilient dynamic output feedback control for leader-following consensus of high-order uncertain multi-agent systems under sensor–actuator attacks

This paper investigates the resilient leader-following consensus problem for a class of high-order multi-agent systems subject to unmatched lower triangular uncertainty dynamics and sensor–actuator attacks. Compared with previous work, the sensor and actuator attacks are modeled to be both time-varying and state-dependent, which makes the resilient consensus control more challenging. To deal with the unmatched uncertainties and sensor–actuator attacks, a new compensator with two online tuned dynamic gains is proposed relying only on the relative output measurements of neighboring agents. Then, using only the local compensation information, a fully distributed output feedback resilient protocol is designed to guarantee the leader-following consensus. Sufficient conditions in terms of matrix inequalities are derived to determine control gains and compensator parameters and simulation studies are presented to demonstrate the proposed theoretical results.

A full circuit-based quantum algorithm for excited-states in quantum chemistry

Utilizing quantum computer to investigate quantum chemistry is an important research field nowadays. In addition to the ground-state problems that have been widely studied, the determination of excited-states plays a crucial role in the prediction and modeling of chemical reactions and other physical processes. Here, we propose a non-variational full circuit-based quantum algorithm for obtaining the excited-state spectrum of a quantum chemistry Hamiltonian. Compared with previous classical-quantum hybrid variational algorithms, our method eliminates the classical optimization process, reduces the resource cost caused by the interaction between different systems, and achieves faster convergence rate and stronger robustness against noise without barren plateau. The parameter updating for determining the next energy-level is naturally dependent on the energy measurement outputs of the previous energy-level and can be realized by only modifying the state preparation process of ancillary system, introducing little additional resource overhead. Numerical simulations of the algorithm with hydrogen, LiH, H2O and NH3 molecules are presented. Furthermore, we offer an experimental demonstration of the algorithm on a superconducting quantum computing platform, and the results show a good agreement with theoretical expectations. The algorithm can be widely applied to various Hamiltonian spectrum determination problems on the fault-tolerant quantum computers.

Біль і можливості фізіотерапії при імпінджмент-синдромі в плечовому суглобі

Introduction: Shoulder problems are the second most common disease of the musculoskeletal system.&#x0D; Background: The most common cause of these problems is impingement syndrome. The aim of our work was to point out the possibilities of conservative treatment for impingement syndrome. In this work, we tried to draw attention to the deterioration in the quality of life caused by shoulder problems and we wanted to improve the range of motion in the shoulder to flexion, abduction, and reduce pain due to the chosen physiotherapy procedures. Our work has a theoretical part, in which we approach the impingement syndrome, its examination and treatment.&#x0D; Material and methods: In the practical part, we used a clinical study with a questionnaire method to achieve the goal of our work. Th e group consisted of 20 patients with impingement syndrome, in whom we used manual therapy, kinesiotherapy, electrotherapy, and Kinesio taping. Using a questionnaire, we were able to assess how much impingement affects the quality of life.&#x0D; Results: Due to the methods we chose, we managed to improve the range of motion of the arm, where the average value at the initial measurement was 119.25° to flexion and 113° to abduction. In the output measurement, the average value up to flexion was 163.25° and up to abduction 165.75°.&#x0D; Conclusion: We also reduced the overall pain, which averaged 6.90 at baseline and 2.90 at the end. Based on our results we recommend a combination of methods to be used in impingement

Adaptive output observers-based distributed tracking

This paper proposes a novel adaptive output observer method for the distributed output tracking control of heterogeneous systems. Unlike the existing adaptive distributed state observer, an output-based adaptive distributed output observer (OADOO) that only relies on the leader’s output is proposed to estimate the leader’s information. Meanwhile, an input-based triggering mechanism is exploited to avoid continuous interactions between agents, and between the leader and its neighboring agents, respectively. Then, a local controller is developed to achieve the output tracking control. In comparison with the existing results for the similar research problem, our results not only handle the tracking control subject to only relative output measurement, but also considerably lower the data exchange traffic and dimension among agents of the developed OADOO.

Algebraic disturbance estimation for a class of fractional order T-S fuzzy systems with noisy output measurements

This paper concerns with the design of algebraic disturbance estimation method for the fractional order Takagi-Sugeno (T-S) fuzzy systems with noisy output measurements. At first, the overall fractional order fuzzy system model is given for the studied system. By constructing a family of fractional order modulating functions, algebraic integral formulas are derived for the disturbance by using the overall fractional order fuzzy system model. Based on the system’s input and output, these formulas can be algebraically computed in both noise-free and noisy cases. Simulation results are shown to validate the efficiency of the proposed algebraic disturbance estimation method against output measurement noises.

Leader-Following Consensus of Linear Multiagent Systems With Aperiodically Sampled Outputs: A Distributed Impulsive-Observer-Based Approach.

This article studies the leader-following consensus problem for a class of linear multiagent systems over a directed graph with aperiodically sampled outputs. First, a novel distributed impulsive-observer-based consensus protocol is designed. This protocol requires only the output measurements at sporadic time instants for the observer and control gain design. Second, by using time-varying Lyapunov function techniques, sufficient conditions for exponential stability of a class of linear impulsive systems are established; subsequently, these stability results are applied for the distributed impulsive observer design. Different from the existing related works, the impulsive observer gain designed in this work is decoupled from the graph properties. As a result, once the impulsive observer gain is designed for one network topology, it can be directly used for other network topologies, as long as the graph properties and the dynamics of local agents satisfy certain conditions. Furthermore, the resilience of the designed protocol is tested under denial of service (DoS) attacks. It is shown that the protocol is robust with respect to low-frequency DoS attacks occurring in the observer communication network. Finally, two examples illustrating the validity and effectiveness of the proposed protocol are included.

Do volatile anaesthetics depress urine output?

Urine output is markedly reduced by isoflurane, but it is unclear whether the decrease is a specific effect of volatile anaesthetics. Therefore, this study compared the diuretic response to crystalloid volume loading during surgical procedures performed with volatile anaesthetics or intravenous anaesthesia. Data from two clinical trials in which patients were randomized between isoflurane and propofol anaesthesia (open thyroid surgery, n = 29) and between sevoflurane and propofol anaesthesia (open hysterectomy; n = 25) were analysed. Urine volume was measured and the diuretic response to volume loading with 1.7-1.8 L of Ringer's solution over 30 min was studied by population volume kinetic analysis. The kinetic method used 631 measurements of plasma dilution based on blood haemoglobin and plasma albumin and 138 measurements of urine output to quantify the diuretic response to volume loading in the four study groups. The urine output after 150 min of thyroid surgery was 132 (77-231) mL in the propofol group and 218 (80-394) mL in the isoflurane group ( P = 0.50; median and interquartile range). The corresponding volumes were 50 (45-65) mL for propofol and 60 (34-71) mL for sevoflurane at 90 min in the hysterectomy patients ( P = 0.81). The kinetic analysis, which corrected for differences in infused volume, body weight, and plasma volume expansion, did not reveal any statistically significant differences in diuretic response to volume loading between the two inhaled anaesthetics and intravenous anaesthesia. Isoflurane and sevoflurane did not affect urine output more strongly than propofol.

Формування логістичної інформаційної системи ефективного управління транспортними і виробничими підприємствами

The article examines the formation of information and the construction of a logistic information system for effective management of transport and production enterprises on this basis. It was found that the functioning of the logistics management system of the enterprise requires high-quality information support, since the management process is a sequence of decision-making acts. The experience of leading foreign enterprises, firms, companies, in terms of design and stages of development, as well as the methodology of implementing model logistics systems on them, is taken into account. The movement of material information flows in the logistics management system at the transport and production enterprise is considered. Seven management functions are identified and their content, types of systems and software products are clarified. Negative and positive points in the activities of enterprises were identified. The adequacy of the formation of information flows at the transport and production enterprise has been clarified. A typical decomposition of the structure of the logistics information system was considered and the building principles (effects) were formed and the main indicators were determined. An organizational structure was built with subsystems: management of order procedures; scientific research and connections; support of logistics solutions; generation of output forms and measures on the dedicated system of operations; the functional structure of the logistics information system is built. The issue of the role and purpose of information in the hierarchy of logistics operations has been clarified. Proposed principles of logistics information organization. The proposed improved structure of the logistics information system at the enterprise and flow chart.

Мониторинг обрабатывающей промышленности: оценка устойчивого развития

The article presents and tests a methodology for assessing the sustainable development of the Russian manufacturing industry, based on publicly available annual data from the Federal State Statistics Service (Rosstat) and the Ministry of Natural Resources and Environment of the Russian Federation over the period 2010-2022. To assess the sustainability of the industry, 32 indicators from three main areas - economic (13), social (10), and environmental (9) - were used. These indicators include measures of output, investment, fixed assets, innovation, efficiency of resource use, profitability, organization of employment, labor protection, occupational safety and health, wages, environmental investments, waste management, atmospheric and water pollution, and energy consumption. All indicators were standardized and subjected to logical checks to ensure that an increase in their values corresponded to an improvement in the relevant aspect of the industry. This allowed for a comprehensive assessment of the sustainability of Russian manufacturing. Estimates using the proposed methodology demonstrate the degree of change in indicators over time and do not necessitate the presence of normative values, which may be controversial. The findings indicate an increase in the overall indicator of sustainable development for the analyzed period of 17.9%. Approximately half of this increase is due to improvements in the environmental sector, which rose by 28%. The economic and social components contributed approximately a quarter each to the improvement in the composite measure of sustainable development in the manufacturing industry, rising by 13.4% and 13% respectively over the review period. Problem areas have also been identified where improvement is minimal or the situation is worsening: the situation with fixed assets, innovation, waste management and employment.

Ambitions and realities: Are Global Fund investments designed to achieve resilient and sustainable systems for health? Findings from the Global Fund Prospective Country Evaluation.

Strengthening resilient and sustainable systems for health (RSSH) is central to the Global Fund's strategy, however questions persist about the Global Fund's role in the health systems strengthening space, and the extent to which investments are designed to achieve strengthening objectives, or just fill in gaps in the system. This paper reports on findings from the Prospective Country Evaluations (PCE), a multi-country multi-year evaluation of Global Fund support. We adapted a framework from Chee et al. (2013) to assess whether Global Fund investments were designed to strengthen or support the health system. Per this framework, 'systems support' refers to improvements in health systems functioning primarily driven by increases in inputs, whereas 'systems strengthening' refers to activities that drive changes in how the health system operates (often related to policies, regulations, governance structures, behavior change, and resource optimization). In the 2017 and 2019 funding cycles, we found that despite calls from the Global Fund to invest more strategically to strengthen health systems, a high proportion of RSSH funding was directed toward activities that support the health system. Factors underlying this pattern include limitations imposed by the three-year grant cycle, a lack of clear guidance on how to design strengthening investments, a persistent need for funding to address input gaps, and minimal feedback during the funding request process related to RSSH design. For the Global Fund, and indeed other global health initiatives, to contribute to sustained strengthening of health systems, is likely to require enhanced guidance and technical assistance, as well as improved measurement of outputs and outcomes.

Comparison of 2D thermal diffusion approximations with experimental data

The European Space agency is highly interested in a full atmospheric reentry from low Earth orbit conditions using an automatic lifting body. In this respect, a numerical method is performed to estimate the heat transfer conditions at the rear surface of a stainless steel material through solving the heat equation. The proposed models should be easily invertible in order to reconstruct the heat flux. The present study presents the analytical modeling of a 2D thermal diffusion which will be compared to different approximations: Taylor approximation, Padé approximation and finite difference method. A benchmark is developed and the temperature output measurements are compared with the proposed approximations.

The Impact of Dermal Characteristics on Low‐Level Laser Power Measurement in Postmortem Zoological Species

Photobiomodulation therapy, also termed as low‐level laser therapy, is commonly used as an adjunctive therapy for various medical conditions in veterinary practice. The ACTIVet PRO low‐level laser has been used for treatment of various nondomestic species, yet the effects of dermal attributes such as pigment, feathers, or scales have not been evaluated. The effects of low‐level laser therapy with the ACTIVet PRO have been investigated in laboratory animals, including a study in rats that evaluated the passage of laser light through the skin in postmortem samples. The objective of this study was to measure the power of a low‐level laser (ACTIVet PRO) after penetration through dermal tissue (∼1 mm thickness) in a variety of postmortem animal tissue. This study sought to determine the impact of fur, feathers, scales, and different pigments on the ability of the laser to penetrate. Frozen and thawed skin tissue samples from various species were placed inside a light restricted laser box and exposed to a preprogrammed laser level from a Multi Radiance ACTIVet PRO photobiomodulation (PBM) device, with a power meter to measure the light penetration through the tissue samples. Light penetration measurements via power output measurements (mW) were recorded at 7 time points (range, 1–150 sec). A Friedman test was performed to evaluate the difference of the mean tissue penetration by each species at each time point. Lighter colored specimens had higher power readings than darker colored or pigmented samples, and feathers appeared to inhibit the laser, showing minimal to no power readings on bird skin covered in covert and down feathers. There was statistically significant mean tissue penetration for all time points between the rabbit and green sea turtle (p = 0.0046), the red‐tailed hawk and green iguana (p = 0.0046), and the red‐tailed hawk and green sea turtle (p = 0.000034). Overall findings found that certain skin coverings, such as feathers, appear to inhibit passage of laser light through tissue to the photo meter. Darker pigmented areas of tissue appeared to absorb the laser light, which also did not allow light passage through the tissue to the photo meter. All of this illustrates that there are differences in tissue penetration between different animal species, at least in postmortem tissues. This could necessitate adjustment of machine settings for therapeutic effect in different species, though further studies would be warranted to determine the extent to which this would be necessary. Additional studies evaluating biologically active tissues would be needed as a next step, as photobiomodulation has an effect at the cellular level and the exact amount of medical benefit is not measurable in skin samples that are separate from a living organism.

Range and light output measurements of trajectory images in a GAGG plate with different alpha particle energies

An imaging method that utilizes a scintillator plate combined with a magnifying unit and a cooled electron multiplying charge-coupled device (EM-CCD) camera shows promise for obtaining high-resolution trajectory images. However, it is not yet clear whether the ranges of the trajectory images change with the energy of the alpha particles. Additionally, it remains unclear whether the intensity of the trajectory images is affected by the energy of the alpha particles. To address these questions in our trajectory imaging research, we conducted experiments to capture trajectory images of alpha particles with varying energy levels. To generate alpha particles with different energies, we modulated the energy using an americium-241 (Am-241) source covered with varying numbers of Mylar films. With this alpha source and imaging system, we successfully captured trajectory images with different alpha particle energies and were able to assess the ranges and intensities of these trajectories at various energy levels. The estimated ranges from the measured images with different alpha particle energies closely matched the results obtained through simulations. However, it's worth noting that the light output, as evaluated for the measured trajectory images, was slightly lower than the simulated results at lower energy levels probably due to the non-proportionality of the GAGG plate with respect to alpha particle energies.

Entropy-metric estimation of the small data models with stochastic parameters

The formalization of dependencies between datasets, taking into account specific hypotheses about data properties, is a constantly relevant task, which is especially acute when it comes to small data. The aim of the study is to formalize the procedure for calculating optimal estimates of probability density functions of parameters of linear and nonlinear dynamic and static small data models, created taking into account specific hypotheses regarding the properties of the studied object. The research methodology includes probability theory and mathematical statistics, information theory, evaluation theory, and stochastic mathematical programming methods. The mathematical apparatus presented in the article is based on the principle of maximization of information entropy on sets determined as a result of a small number of censored measurements of “input" and “output" entities in the presence of noise. These data structures became the basis for the formalization of linear and nonlinear dynamic and static models of small data with stochastic parameters, which include both controlled and noise-oriented input and output measurement entities. For all variants of the above-mentioned small data models, the tasks of determining the optimal estimates of the probability density functions of the parameters were carried out. Formulated optimization problems are reduced to the forms canonical for the stochastic linear programming problem with probabilistic constraints.

Investigation of geometry-dependent sensing characteristics of microfluidic for single-cell 3D localization.

Flow cytometry-based measurement techniques have been widely used for single-cell characterizations, such as impedance, size, and dielectric properties. However, in the measurement process, the reliability of the output measurement signal directly affects the ability of the microsystem to judge the characteristics of single cells. Here, we designed a multiple nonparallel electrode structure for single-cell 3D localization. The performance of the structures was studied by analyzing the changes in electric field strength and the output differential current. The effects of microchannel height, sensing electrode distance, electrode inclination angle, and electrode width on output signals are investigated by analyzing the current change and electric field strength of single cells passing from the center of the microchannel. The numerical simulation results indicate that, when the microchannel height is 20 µm, the distance of the sensing electrodes is 100 µm, the inclination angle is 30°, the electrode width is 20 µm, and the optimal signal quality can be obtained. Reducing the height of the flow channel and shortening the sensing electrode spacing can significantly improve the signal amplitude. When the channel height is 20 µm, the signal intensity increases by 80% than that of 30 µm. The signal intensity of induced current with the sensing electrode spacing of 100 µm is 42% higher than that with the spacing of 120 µm. We analyzed the presence of multiple independent cells and adherent cells in the detection area and demonstrated through simulation that the signal changes caused by multi-cells can be superimposed by multiple single-cell signals. The induced current signal intensity of the same volume of cells with an ellipticity of 1 is 49% lower than that of cells with an ellipticity of 4. Based on the numerical investigation, we expect that the optimal geometry structure design will aid in the development of better performance signal cell impedance cytometry microsystems.

HcHCR: High-Throughput Single-Cell Imaging of RNA in Human Primary Immune Cells.

Functional genomics and chemical screens can identify and characterize novel cellular factors regulating signaling networks and chemical tools to modulate their function for the treatment of disease. Screening methods have relied primarily on immortalized and/or transformed cancer cell lines, which can limit the generalization of results to more physiologically relevant systems. Most have also relied on immunofluorescence, or on stably expressed recombinant fluorescent proteins, to detect specific protein markers using high-content imaging readouts. In comparison, high-throughput methods to visualize and measure RNA species have been less explored. To address this, we have adapted an isothermal signal amplification chemistry for RNA FISH known as hybridization chain reaction (HCR) to an automated, high-content imaging assay format. We present a detailed protocol for this technique, which we have named high-content HCR (hcHCR). The protocol focuses on the measurement of changes in mRNA abundance at the single-cell level in human primary cells, but it can be applied to a variety of primary cell types and perturbing agents. We anticipate that hcHCR will be most suitable for low- to medium-throughput screening experiments in which changes in transcript abundance are the desired output measure.

A mathematical model for simulation of cardiovascular, renal, and hormonal responses to burn injury and resuscitation.

Treating extensive burn injury requires an individually tailored resuscitation protocol that includes hourly-titrated intravenous fluid infusion to avert both hypovolemic shock and edema. Due to the complexity of burn pathophysiology and significant variability in treatment protocols, there is an ongoing effort to optimize burn resuscitation. The goal of this work is to contribute to this effort by developing a mathematical model of burn pathophysiology and resuscitation for in silico testing of burn resuscitation protocols and decision-support systems. In our previous work, we developed and validated a mathematical model consisting of volume kinetics, burn-induced perturbations, and kidney function. In this work, we expanded our previous mathematical model to incorporate novel mathematical models of cardiovascular system and hormonal system (renin-angiotensin-aldosterone (RAAS) system and antidiuretic hormone) which affect blood volume and pressure regulation. We also developed a detailed mathematical model of kidney function to regulate blood volume, pressure, and sodium levels, including components for glomerular filtration rate, reabsorption rates in nephron tubules, Tubuglomerular feedback, and myogenic mechanisms. We trained and validated the expanded mathematical model using experimental data from 15 pigs and 9 sheep with extensive burns to quantitatively evaluate its prediction accuracy for hematocrit, cardiac output, mean arterial pressure, central venous pressure, serum sodium levels, and urinary output. We then trained and tested the mathematical model using a clinical dataset of 233 human burn patients with demographic data and urinary output measurements. The mathematical model could predict all tested variables very well, while internal variables and estimated parameters were consistent with the literature. To the best of our knowledge, this is the first mathematical model of burn injury and resuscitation which is extensively validated to replicate actual burn patients. Hence, this in silico platform may complement large animal pre-clinical testing of burn resuscitation protocols. Beyond its primary purpose, the mathematical model can be used as a training tool for healthcare providers delivering insight into the pathophysiology of burn shock, and offering novel mathematical models of human physiology which can be independently used for other purposes and contexts.