Finite-time compensation control with dead-zone estimation for a rehabilitative walker considering internal disturbance forces.

This study discusses a finite-time compensation tracking control method for a rehabilitative training walker. The dynamic model with input dead zone was constructed to describe the walker, and a finite-time disturbance forces observation method was proposed based on the impact mechanism on tracking performance. This approach is novel in that the disturbance forces were observed in reverse through their effects on tracking performance, thus successfully obtaining the disturbance forces of the walker. To ensure the practical finite-time stability of the system, the nonlinear finite-time compensation tracking controller with stochastic configuration networks (SCN) dead-zone estimation was built for the rehabilitative walker. Simulation results and comparative analyses confirmed that the proposed compensation control method effectively restrains dead zone and internal disturbance forces.

Adsorption and Aggregation Behaviors of Oleyl Alcohol-Based Extended Surfactant and Its Mixtures.

An oleyl alcohol-based extended surfactant, sodium oleyl polyethylene oxide-polypropylene oxide sulfate (OE3P3S), was synthesized and identified using FT-IR and 1H NMR. The adsorption and aggregation behaviors of OE3P3S and its mixture with cationic surfactant alkyltrimethylammoniumbromide (ATAB) were investigated under different molar ratios. The static surface tension analysis indicated that the critical micellization concentration (cmc) and the critical surface tension (γcmc) of OE3P3S were 0.72 mmol/L, and 36.16 mN/m, respectively. The cmc and γcmc values of the binary system were much lower than that of the individual component. And the cmc values of OE3P3S/ATAB = 6:4 mixtures decreased with an increase in the chain length of the cationic surfactant in the binary system. It was found from the dynamic surface tension that there was a slower diffusion rate in the binary system compared to the pure surfactant, and the adsorption processes for OE3P3S/ATAB = 6:4 were mixed diffusion-kinetic adsorption mechanisms. With a combination of DLS data and TEM measurements, formations of vesicles in OE3P3S/ATAB = 6:4 solutions appeared to occur at a concentration of 0.05 mmol/L. By studying the formation of liquid crystal structures in an emulsion prepared with OE3P3S as the surfactant, it was found that the oil-in-water emulsion is birefringent with a Maltese cross texture, and the rheological properties revealed its predominant viscoelastic behavior and shear thinning properties.

Dynamic Event-Triggered Safe Control for Nonlinear Game Systems With Asymmetric Input Saturation.

This article focuses on the Pareto optimal issues of nonlinear game systems with asymmetric input saturation under dynamic event-triggered mechanism (DETM). First, the safe control is guaranteed by transforming the system with safety constraints into the one without state constraints utilizing barrier function. The united cost function integrating nonquadratic utility function is constructed to provide the foundation to achieve the Pareto optimal solutions. Then, the adaptive dynamic programming method with concurrent learning is proposed to approximate the Pareto optimal strategies wherein both current and historical data are utilized. To further lessen the consumptions of computation/communication resources, the DETM is integrated into the adaptive algorithm framework which can avoid Zeno phenomena. All the signals of the closed-loop system are proved to be uniformly ultimately bounded. Finally, the simulation results are given to validate the effectiveness of the proposed method from several aspects.

Trajectory Tracking Control of Human Support Robots via Adaptive Sliding-Mode Approach.

In this article, the tracking problem of the adaptive sliding-mode control (SMC) design for human support robots based on a disturbance observer is investigated. First, a finite-time controller using nonsingular fast terminal SMC is proposed. Then, a robust disturbance observer is developed to estimate system uncertainties and disturbances. Simultaneously, to deal with the unknown bounded disturbance observer error, an adaptive control technology is developed. Furthermore, the proposed controller is synthesized to ensure that the tracking errors can be stabilized in finite time. Finally, simulations are performed to demonstrate that human support robots employing the proposed controller can converge to the desired trajectory.

Spectrum of PHEX Mutations and FGF23 Profiles in a Taiwanese Cohort With X-Linked Hypophosphatemia Including 102 Patients.

BACKGROUND/AIM: X-linked hypophosphatemia (XLH), the most common form of hereditary rickets, results from loss-of-function mutations in the phosphate-regulating PHEX gene. Elevated fibroblast growth factor 23 (FGF23) contributes to hypophosphatemia in XLH. This study aimed to characterize PHEX variants and serum FGF23 profiles in Taiwanese patients with XLH. PATIENTS AND METHODS: We retrospectively reviewed the records of 102 patients clinically suspected of having hypophosphatemic rickets from 2006 to 2022. Serum intact Fibroblast growth factor-23 (iFGF23) levels were measured on clinic visit days. PHEX mutations were identified using Sanger sequencing, and negative cases were analyzed using whole-exome sequencing. RESULTS: The majority (92.1%) of patients exhibited elevated FGF23 compared with normal individuals. Among 102 patients, 44 distinct PHEX mutations were identified. Several mutations recurred in multiple unrelated Taiwanese families. We discovered a high frequency of novel PHEX mutations and identified variants associated with extreme FGF23 elevation and tumorigenesis. CONCLUSION: Our findings revealed the PHEX genotypic variants and FGF23 levels in Taiwanese patients with XLH. These results are crucial given the recent approval of burosumab, a monoclonal FGF23 antibody, for XLH therapy. This study provides key insights into the clinical management of XLH in Taiwan.

Accelerating ion/electron transport by engineering an indium-based heterostructure toward large and reversible lithium storage.

The high activity of the In2O3/In2S3 heterostructure can be activated into homogeneous In2OxS3-x nanodots, thereupon stabilizing the subsequent cycles. The In2O3/In2S3 can offer a high capacity of 1140 mA h g-1 at 0.1 A g-1 after 290 cycles, and even at 1 A g-1, it harvests a reversible capacity of 900 mA h g-1 after 600 cycles.

Improved Event-Triggered Dynamic Output Feedback Control for Networked T-S Fuzzy Systems With Actuator Failure and Deception Attacks.

This article addresses the problem of event-triggered dynamic output feedback controller design for networked Takagi-Sugeno (T-S) fuzzy systems subject to actuator failure and deception attacks. In order to save network resources effectively, two event-triggered schemes (ETSs) are introduced to test whether the measurement output and control input are transmitted under network communication. While the ETS brings advantages, it also leads to a mismatch between the premise variables of the system and the controller. To solve this problem, an asynchronous premise reconstruct method is considered, which relaxes the condition of the previous results that the premises of the plant and the controller are synchronous. Furthermore, two crucial factors, including actuator failure and deception attacks, are taken into consideration simultaneously. Then, the mean square asymptotic stability conditions of the resultant augmented system are derived by utilizing the Lyapunov stability theory. Besides, controller gains and event-triggered parameters are co-designed with the help of linear matrix inequality techniques. Finally, a cart-damper-spring system and a nonlinear mass-spring-damper mechanical system are presented to verify the theoretical analysis.

Automatic Assessments of Parkinsonian Gait with Wearable Sensors for Human Assistive Systems.

The rehabilitation evaluation of Parkinson's disease has always been the research focus of human assistive systems. It is a research hotspot to objectively and accurately evaluate the gait condition of Parkinson's disease patients, thereby adjusting the actuators of the human-machine system and making rehabilitation robots better adapt to the recovery process of patients. The rehabilitation evaluation of Parkinson's disease has always been the research focus of rehabilitation robots. It is a research hotspot to be able to objectively and accurately evaluate the recovery of Parkinson's disease patients, thereby adjusting the driving module of the human-machine collaboration system in real time, so that rehabilitation robots can better adapt to the recovery process of Parkinson's disease. The gait task in the Unified Parkinson's Disease Rating Scale (UPDRS) is a widely accepted standard for assessing the gait impairments of patients with Parkinson's disease (PD). However, the assessments conducted by neurologists are always subjective and inaccurate, and the results are determined by the neurologists' observation and clinical experience. Thus, in this study, we proposed a novel machine learning-based method of automatically assessing the gait task in UPDRS with wearable sensors as a more convenient and objective alternative means for PD gait assessment. In the design, twelve gait features, including three spatial-temporal features and nine kinematic features, were extracted and calculated from two shank-mounted IMUs. A novel nonlinear model is developed for calculating the score of gait task from the gait features. Twenty-five PD patients and twenty-eight healthy subjects were recruited for validating the proposed method. For comparison purpose, three traditional models, which have been used in previous studies, were also tested by the same dataset. In terms of percentages of participants, 84.9%, 73.6%, 73.6%, and 66.0% of the participants were accurately assigned into the true level with the proposed nonlinear model, the support vector machine model, the naive Bayes model, and the linear regression model, respectively, which indicates that the proposed method has a good performance on calculating the score of the UPDRS gait task and conformance with the rating done by neurologists.

A Grip Strength Estimation Method Using a Novel Flexible Sensor under Different Wrist Angles.

It is a considerable challenge to realize the accurate, continuous detection of handgrip strength due to its complexity and uncertainty. To address this issue, a novel grip strength estimation method oriented toward the multi-wrist angle based on the development of a flexible deformation sensor is proposed. The flexible deformation sensor consists of a foaming sponge, a Hall sensor, an LED, and photoresistors (PRs), which can measure the deformation of muscles with grip strength. When the external deformation squeezes the foaming sponge, its density and light intensity change, which is detected by a light-sensitive resistor. The light-sensitive resistor extended to the internal foaming sponge with illuminance complies with the extrusion of muscle deformation to enable relative muscle deformation measurement. Furthermore, to achieve the speed, accuracy, and continuous detection of grip strength with different wrist angles, a new grip strength-arm muscle model is adopted and a one-dimensional convolutional neural network based on the dynamic window is proposed to recognize wrist joints. Finally, all the experimental results demonstrate that our proposed flexible deformation sensor can accurately detect the muscle deformation of the arm, and the designed muscle model and convolutional neural network can continuously predict hand grip at different wrist angles in real-time.

Design and Realization of Triple dsDNA Nanocomputing Circuits in Microfluidic Chips.

DNA logic gates, nanocomputing circuits, have already implemented basic computations and shown great signal potential for nano logic material application. However, the reaction temperature and computing speed still limit its development. Performing complicated computations requires a more stable component and a better computing platform. We proposed a more stable design of logic gates based on a triple, double-stranded, DNA (T-dsDNA) structure. We demonstrated a half adder and a full adder using these DNA nanocircuits and performed the computations in a microfluidic chip device at room temperature. When the solutions were mixed in the device, we obtained the expected results in real time, which suggested that the T-dsDNA combined microfluidic chip provides a concise strategy for large DNA nanocircuits.

Ovarian steroid cell tumor causing isosexual pseudoprecocious puberty in a young girl: an instructive case and literature review.

BACKGROUND: Steroid cell tumors (SCTs) are very rare sex cord-stromal tumors and account only for less than 0.1% of ovarian neoplasms. SCTs might comprise diverse steroid-secreting cells; hence, the characteristic clinical features were affected by their propensity to secrete a variety of hormones rather than mass effect resulting in compression symptoms and signs. To date, ovarian SCTs have seldom been reported in children, particularly very young children; and pseudoprecocious puberty (PPP) as its unique principal manifestation should be reiterated. CASE PRESENTATION: We reported a 1-year-8-month-old girl presenting with rapid bilateral breast and pubic hair development within a 2-month period. Undetectable levels of LH and FSH along with excessively high estradiol after stimulation with gonadotropin-releasing hormone (GnRH), as well as a heterogeneous mass inside left ovary shown in pelvic sonography indicate isosexual PPP. Her gonadal hormones returned remarkably to the prepubertal range the day after surgery, and histology of the ovary mass demonstrated SCTs containing abundant luteinized stromal cells. CONCLUSION: The case highlighted that SCTs causing isosexual PPP should be taken into consideration in any young children coexistent with rapidly progressive puberty given a remarkable secretion of sex hormones. This article also reviewed thoroughly relevant reported cases to enrich the clinical experience of SCTs in the pediatric group.

Fixed-Time Event-Triggered Output Consensus Tracking of High-Order Multiagent Systems Under Directed Interaction Graphs.

This article investigates the problem of fixed-time event-triggered output consensus tracking for high-order multiagent systems (MASs) under directed interaction graphs. First, a fixed-time event-triggered distributed observer and triggering functions are proposed. Next, fixed-time convergence of the presented distributed observer is proved by the Lyapunov function approach, and an analysis is conducted to show the proposed distributed observer excludes zeno behavior. Then, an event-triggered adaptive dynamic surface fixed-time controller is designed to stabilize the tracking error system. Finally, simulation results are given to show the effectiveness and superiority of the consensus scheme developed. The contribution of this article is to present a novel event-triggered fixed-time distributed observer and a novel fixed-time controller, which can reduce frequency of communication and control update, avoid continuous monitor, exclude zeno behavior, eliminate the effect of mismatched disturbance caused by observation error, and achieve practical fixed-time output consensus tracking of high-order MAS under directed interaction graphs.

Cooperative Tracking Control of Heterogeneous Mixed-Order Multiagent Systems With Higher-Order Nonlinear Dynamics.

This article investigates a class of finite-time cooperative tracking problems of heterogeneous mixed-order multiagent systems (MASs) with higher-order dynamics. Different from the previous works of heterogeneous MASs, the agents in this study are considered to have different first-, second-, or even higher-order nonlinear dynamics. It means that, according to different tasks and situations, the following agents can have nonidentical orders or different numbers of states to be synchronized, which is more general for the practical cooperative applications. The leader is a higher-order nonautonomous system and contains full state information to be synchronized for all agents with mixed-order dynamics. Accordingly, the spanning tree is defined based on the specific state rather than on the agent to guarantee that each following agent can receive adequate state information. Distributed control protocols are designed for all agents to achieve the ultimate state synchronization to the leader in finite time. The Lyapunov approach is used for the stability analysis and a practical example of mixed-order mechanical MASs verifies the effectiveness and performance of the proposed distributed control protocols.

Hybrid Target Selections by "Hand Gestures + Facial Expression" for a Rehabilitation Robot.

In this study we propose a "hand gesture + face expression" human machine interaction technique, and apply this technique to bedridden rehabilitation robot. "Hand gesture + Facial expression" interactive technology combines the input mode of gesture and facial expression perception. It involves seven basic facial expressions that can be used to determine a target selecting task, while hand gestures are used to control a cursor's location. A controlled experiment was designed and conducted to evaluate the effectiveness of the proposed hybrid technology. A series of target selecting tasks with different target widths and layouts were designed to examine the recognition accuracy of hybrid control gestures. An interactive experiment applied to a rehabilitation robot is designed to verify the feasibility of this interactive technology applied to rehabilitation robots. The experimental results show that the "hand + facial expression" interactive gesture has strong robustness, which can provide a novel guideline for designing applications in VR interfaces, and it can be applied to the rehabilitation robots.

Effects of methylprednisolone and treadmill training on spinal cord injury in experimental rats.

Methylprednisolone (MP) is widely used to treat clinical spinal cord injury (SCI). Treadmill training is also considered an important treatment after SCI to improve motor function in patients, resulting in an evident improvement. Therefore, the present study was designed to evaluate and contrast the effects of MP and treadmill training administered in combination or alone after SCI in adult rats. A rat spinal cord T10 contusion model was induced in Sprague-Dawley rats using an impact device. A total of 40 rats were divided into four groups (n=10 rats/group): the MP, MP + treadmill training, SCI and sham group. At 30 min after injury, MP sodium succinate was injected into the rats of the MP and MP + treadmill training groups. Treadmill training began on the second week post-trauma and was performed for 8 weeks. The results showed that MP therapy combined with treadmill training significantly ameliorated several parameters of hind limb function compared with those by MP treatment alone (all P<0.05). A significantly reduced immunopositive area of Nogo receptor and chondroitin sulfate proteoglycans and reduced relative expression of these mRNAs were found in the MP + treadmill training group (P<0.05) compared with the findings in the MP group. In conclusion, the present study indicated that combined MP and treadmill training treatment improved the recovery of hind limb function in rats with SCI, thus potentially representing a promising strategy to cure SCI.

Stress hyperglycemia as first sign of asymptomatic type 1 diabetes: an instructive case.

BACKGROUND: Stress hyperglycemia (SH) is considered a transient manifestation and routine diagnostic evaluation was thought to be unnecessary due to the lack of definite correlation with diabetes mellitus (DM). Although SH was usually benign and long-term treatment was superfluous, it might be the first sign of insulinopenic status such as type 1 DM (T1DM). CASE PRESENTATION: We reported a boy with acute asthma attack presented incidentally with high blood glucose levels exceeding 300 mg/dL and obvious glycemic variability. A prolonged hyperglycemic duration of more than 48 h was also noticed. To elucidate his unique situation, glucagon test and insulin autoantibody survey were done which showed insulinopenia with positive anti-insulin antibody and glutamic acid decarboxylase antibody despite the absence of overt DM symptoms and signs. CONCLUSIONS: This case highlights that SH might be a prodromal presentation in T1DM children, especially when accompanied simultaneously with extreme hyperglycemia, apparent glucose variability, as well as prolonged hyperglycemic duration.

Synthesis and characterization of a thermosensitive solid amine biomass adsorbent for carbon dioxide adsorption.

A thermosensitive solid amine fiber SF-AM-co-NIPAM-HBP-NH2 was synthesized by grafting temperature-sensitive monomer N-isopropyl acrylamide (NIPAM) as well as acrylamide (AM) onto the surface of substrate sisal fiber, and further aminating with hyperbranched amine. FTIR, 13C NMR, SEM, EA and TGA were used to confirm the structure and chemical properties of the grafted fibers. Swelling ratio and CO2 adsorption-desorption experiment were investigated to verify the thermo-sensitivity of the grafted fibers and their CO2 adsorption-desorption behavior. Compared with conventional solid amine adsorbents regenerated around 140 °C, SF-AM-co-NIPAM-HBP-NH2 (1:1) with NIPAM could be regenerated at a much lower temperature of 60 °C, while still maintain a high CO2 adsorption capacity (2.61 mmol/g), comparable to that of SF-AM-HBP-NH2 (2.73 mmol/g) before NIPAM introduction. Its excellent regeneration property and the effect of energy consumption reduction make it possible to be used for CO2 adsorption in industrial process.

Adaptive Neural Control for a Class of Nonlinear Multiagent Systems.

This article studies the adaptive neural controller design for a class of uncertain multiagent systems described by ordinary differential equations (ODEs) and beams. Three kinds of agent models are considered in this study, i.e., beams, nonlinear ODEs, and coupled ODE and beams. Both beams and ODEs contain completely unknown nonlinearities. Moreover, the control signals are assumed to suffer from a class of generalized backlash nonlinearities. First, neural networks (NNs) are adopted to approximate the completely unknown nonlinearities. New barrier Lyapunov functions are constructed to guarantee the compact set conditions of the NNs. Second, new adaptive neural proportional integral (PI)-type controllers are proposed for the networked ODEs and beams. The parameters of the PI controllers are adaptively tuned by NNs, which can make the system output remain in a prescribed time-varying constraint. Two illustrative examples are presented to demonstrate the advantages of the obtained results.

Proteasome Inhibitors Interrupt the Activation of Non-Canonical NF-κB Signaling Pathway and Induce Cell Apoptosis in Cytarabine-Resistant HL60 Cells.

Over half of older patients with acute myeloid leukemia (AML) do not respond to cytotoxic chemotherapy, and most responders relapse because of drug resistance. Cytarabine is the main drug used for the treatment of AML. Intensive treatment with high-dose cytarabine can increase the overall survival rate and reduce the relapse rate, but it also increases the likelihood of drug-related side effects. To optimize cytarabine treatment, understanding the mechanism underlying cytarabine resistance in leukemia is necessary. In this study, the gene expression profiles of parental HL60 cells and cytarabine-resistant HL60 (R-HL60) cells were compared through gene expression arrays. Then, the differential gene expression between parental HL60 and R-HL60 cells was measured using KEGG software. The expression of numerous genes associated with the nuclear factor κB (NF-κB) signaling pathway changed during the development of cytarabine resistance. Proteasome inhibitors inhibited the activity of non-canonical NF-κB signaling pathway and induced the apoptosis of R-HL60 cells. The study results support the application and possible mechanism of proteasome inhibitors in patients with relapsed or refractory leukemia.

Neural Networks-Based Distributed Adaptive Control of Nonlinear Multiagent Systems.

The cooperative control problem of nonlinear multiagent systems is studied in this paper. The followers in the communication network are subject to unmodeled dynamics. A fully distributed neural-networks-based adaptive control strategy is designed to guarantee that all the followers are asymptotically synchronized to the leader, and the synchronization errors are within a prescribed level, where some global information, such as minimum and maximum singular value of graph adjacency matrix, is not necessarily to be known. Based on the Lyapunov stability theory and algebraic graph theory, the stability analysis of the resulting closed-loop system is provided. Finally, an numerical example illustrates the effectiveness and potential of the proposed new design techniques.