Search Results (48)

To address the issue of jitter and oscillation of guidance command during multi-vehicle cooperative engagement with maneuvering platforms, this paper proposes a novel terminal guidance law with prescribed performance constraints for multiple cooperative vehicles, which explicitly considers both transient and steady-state performance. Firstly, based on the vehicle-target relative kinematics, with time and space as the main constraint indicators, a multi-vehicle cooperative guidance model is established in the inertial coordinate system. Secondly, combined with the sliding mode control theory, cooperative guidance laws are designed for both the line-of-sight (LOS) direction and the LOS normal direction, respectively, and the Lyapunov stability proof is given. Furthermore, to counteract the impact of target maneuvers on guidance performance, a non-homogeneous disturbance observer is designed to estimate target maneuver information that is difficult to obtain directly, which ensures that performance constraints are still satisfied under strong target maneuvering conditions. Simulation results demonstrate that the proposed guidance law enables multiple coordinated vehicles to successfully engage the target under different maneuvering modes, while satisfying the terminal time-space constraints. Compared with conventional sliding mode control methods exhibiting inherent chattering, the proposed approach employs a novel PPC-SMC hybrid structure to quantitatively constrain the transient convergence of cooperative errors. This structure enhances the multi-vehicle cooperative guidance performance by effectively eliminating chattering and oscillations in the guidance commands, thereby significantly improving the system’s transient behavior. Full article

Assessing the energy flux delivered to ecosystem components by wildfires is hard because of technical and safety problems in performing measurements during such events. Here, we present a laboratory and field experimental assessment of a new method of evaluating a wildfire energy flux; our approach is based on the fact that different types of trash deform at different temperatures. We produced deformed trash in a laboratory environment using an iCone calorimeter to deliver a range of heat fluxes over a range of durations. We followed this by placing trash in instrumented prescribed fires. We show that finding melted or heat-altered plastic bottles and aluminium cans in the aftermath of wildfires can provide useful information about the heating that they received during the fire: plastic bottles are a useful indicator for areas that received less than 2 MJ/m² with a maximal temperature of <200 °C, while aluminium cans may be applied to higher-energy sites 100 MJ/m² that experienced a temperature above 600 °C. We provide a semi-quantitative proxy guide as to what different observed deformations may indicate in terms of energy flux and hope that this may allow scientists and forest managers to easily and cheaply assess the energy flux delivered to ecosystems and semi-quantitatively compare different wildfires. Full article

This paper proposes optimal sliding mode fault-tolerant control for multiple robotic manipulators in the presence of external disturbances and actuator faults. First, a quantitative prescribed performance control (QPPC) strategy is constructed, which relaxes the constraints on initial conditions while strictly restricting the trajectory within a preset range. Second, based on QPPC, adaptive gain integral terminal sliding mode control (AGITSMC) is designed to enhance the anti-interference capability of robotic manipulators in complex environments. Third, a critic-only neural network optimal dynamic programming (CNNODP) strategy is proposed to learn the optimal value function and control policy. This strategy fits nonlinearities solely through critic networks and uses residuals and historical samples from reinforcement learning to drive neural network updates, achieving optimal control with lower computational costs. Finally, the boundedness and stability of the system are proven via the Lyapunov stability theorem. Compared with existing sliding mode control methods, the proposed method reduces the maximum position error by up to 25% and the peak control torque by up to 16.5%, effectively improving the dynamic response accuracy and energy efficiency of the system. Full article

The permanent magnet synchronous motor (PMSM) is a critical device that converts kinetic energy into mechanical energy. However, it faces issues such as nonlinearity, time-varying uncertainties, and external disturbances, which may degrade the system control performance. To address these challenges, this paper proposes a prescribed performance model-free adaptive fast integral terminal sliding mode control (PP-MFA-FITSMC) method. This approach replaces conventional techniques such as parameter identification, function approximation, and model reduction, offering advantages such as quantitative constraints on the PMSM tracking error, reduced chattering, strong disturbance rejection, and ease of engineering implementation. The method establishes a compact dynamic linearized data model for the PMSM system. Then, it uses a discrete small-gain extended state observer to estimate the composite disturbances in the PMSM online, effectively compensating for their adverse effects. Meanwhile, an improved prescribed performance function and error transformation function are designed, and a fast integral terminal sliding surface is constructed along with a discrete approach law that adaptively adjusts the switching gain. This ensures finite-time convergence of the control system, forming a model-free, low-complexity, high-performance control approach. Finally, response surface methodology is applied to conduct a sensitivity analysis of the controller’s critical parameters. Finally, controller parameter sensitivity experiments and comparative experiments were conducted. In the parameter sensitivity experiments, the response surface methodology was employed to design the tests, revealing the impact of individual parameters and parameter interactions on system performance. In the comparative experiments, under various operating conditions, the proposed strategy consistently constrained the tracking error within ±0.0028 rad, demonstrating superior robustness compared to other control methods. Full article

Background/Objectives: C-reactive protein (CRP) has been acknowledged to be associated with depression, loneliness, and stress, as well as physical health conditions. The aim of this study was to explore possible associations between CRP semi-quantitative readings and demographic, social, behavioral, and biomedical indices. Methods: Group sampling took place between May and July 2023, and from the 120 non-obese participants initially registered in the study, a random selection of n = 80 was performed for blood sampling in order to measure plasma semi-quantitative CRP (higher levels or ≥10 mg/L and lower or <10) and plasma dopamine. Blood sample collection took place between December 2023 and June 2024. Personal sociability, subjective loneliness, and perceived stress were assessed using relevant scales. Hierarchical multiple logistic regression analysis was also performed. Results: A unit increase in Body Mass Index (BMI) was related to higher odds for greater semi-quantitative CRP levels (OR = 1.26, p = 0.033) while for each unit increase in the Personal Sociability and Connections scale (PeSCs), the odds for higher CRP levels decreased (OR = 0.91, p = 0.025). Lower age (OR = 0.90, p = 0.009) and higher number of prescribed medications per day (OR = 4.21, p = 0.049) also showed significant associations with high semi-quantitative CRP levels. Plasma dopamine and other scale scores used did not show significant associations (p > 0.05), despite some interesting descriptive trends. Conclusions: The presented results suggest that age, BMI, number of prescribed medications per day, sociability, and CRP readings are constellated in everyday consultations. Full article

Depression and anxiety are two common mental health issues that require serious attention, as they have significant impacts on human well-being, with both being emotionally and physically reflected in the increasing number of suicide cases globally. The World Health Organization (WHO) estimated that about 322 million people around the world experienced mental illnesses in 2017, and this number continues to increase. Cortisol is a major stress-controlled hormone that is regulated by the hypothalamic–pituitary–adrenal (HPA) axis. The HPA axis has three main components, including the hypothalamus, pituitary gland, and adrenal gland, where cortisol, the primary stress hormone, is released. It plays crucial roles in responding to stress, energy balance, and the immune system. The cortisol level in the bloodstream usually increases when stress develops. Molecularly imprinted polymers (MIPs) have been highlighted in terms of creating artificial bioreceptors by mimicking the shape of detected biomolecules, making natural bioreceptor molecules no longer required. MIPs can overcome the limitations of chemicals and physical properties reducing over time and the short-time shelf life of natural bioreceptors. MIPs’ benefits are reflected in their ease of use, high sensitivity, high specificity, reusability, durability, and the lack of requirement for complicated sample preparation before use. Moreover, MIPs incur low costs in manufacturing, giving them a favorable budget for the market with simple utilization. MIPs can be formulated by only three key steps, including formation, the polymerization of functional monomers, and the creation of three-dimensional cavities mimicking the shape and size of targeting molecules. MIPs have a high potential as biosensors, especially working as bioanalytics for protein, anti-body, antigen, or bacteria detection. Herein, this research proposes an MIP-based cortisol biosensor in which cortisol is imprinted on methyl methacrylate (MMA) and methacrylic acid (MAA) produced by UV polymerization. This MIP-based biosensor may be an alternative method with which to detect and monitor the levels of hormones in biological samples such as serum, saliva, or urine due to its rapid detection ability, which would be of benefit for diagnosing depression and anxiety and prescribing treatment. In this study, quantitative detection was performed using an electrochemical technique to measure the changes in electrical signals in different concentrations of a cortisol solution ranging from 0.1 to 1000 pg/mL. The MIP-based biosensor, as derived by calculation, achieved its best detection limit of 1.035 pg/mL with a gold electrode. Tests were also performed on molecules with a similar molecular structure, including Medroxyprogesterone acetate and drospirenone, to ensure the sensitivity and accuracy of the sensors, demonstrating a low sensitivity and low linear response. Full article

Ocular cystinosis is a disease in which accumulated cystine crystals cause damage to the eyes, necessitating timely treatment and ongoing monitoring of cystine levels. The current treatment involves frequent administration of cysteamine eye drops, which suffer from low bioavailability and can lead to drug toxicity, making it essential to prescribe an appropriate dosage based on the patient’s condition. Additionally, cystine crystal levels are typically assessed subjectively via slit-lamp examination, requiring frequent clinical visits and causing discomfort for the patient. In this study, we propose a theranostic contact lens that simultaneously performs therapy and diagnosis on a single platform utilizing gold nanoparticles (GNPs). The binding interactions between GNPs and cystine were confirmed in solution, and thermodynamic analysis further elucidated the bonding force between the two substances. With a comprehensive understanding of these interactions, we investigated the potential of the theranostic GNP-loaded contact lens (GNP-CL). Upon exposure to various concentrations of cystine, the GNP-CL demonstrated distinct color changes, transitioning from red to blue. This color shift enabled quantitative monitoring of cystine levels. The treatment efficacy was validated by confirming a reduction in cystine concentration following the reaction. This platform has the potential to improve disease management in ocular cystinosis by reducing the reliance on cysteamine and offering an objective self-monitoring tool that does not require specialized equipment. Full article

Achieving formation tracking control of underactuated autonomous underwater vehicles (AUVs) under communication delays presents a significant challenge. To address this challenge, a distributed prescribed performance control protocol based on a real-time state information online predictor (RSIOP) is proposed in this paper. First, we innovatively designed an RSIOP to achieve active compensation for the delayed state information of neighboring AUVs. Next, considering formation performance and safety, a low-complexity and practical nonlinear mapping function was used to implement prescribed performance tracking control for the AUV formation. Additionally, the adverse effects of external disturbance uncertainties and input saturation are also considered. Finally, the simulation tests demonstrated that the proposed formation control protocol can successfully achieve the predetermined formation tracking tasks in the presence of time-varying communication delays and external disturbances, while also enabling real-time changes in formation configuration during the process. Throughout, the protocol maintains input saturation limits, and the actual control inputs remain smooth, with no significant oscillations. Furthermore, comparative simulation tests verified the necessity of the RSIOP developed in this study and quantitatively demonstrated that the proposed control method exhibits superior performance in terms of formation control accuracy, error convergence speed, and transient-state constraints. Full article

This paper proposes a decentralized adaptive event-triggered fault-tolerant cooperative control (ET-FTCC) scheme for multiple unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) with actuator faults and external disturbances under denial-of-service (DoS) attacks. The multiple UAVs and UGVs have a larger search radius, which is important in both the civilian and military domains. The different dynamics between UAVs and UGVs result in unbalanced interactions in the communication topologies, which increases the complexity of cooperative control. DoS attacks are conducted in both sensor and control channels. The dynamic models of UAVs and UGVs are introduced firstly, and the unified heterogeneous multiagent system model with actuator faults is established. The composite observer is designed to obtain the information of state and lumped disturbance, which is used to design the controller. In order to save the limited communication network resources, the event-triggered mechanism is introduced. The transformed error is presented by using the prescribed performance function (PPF). Then, the sliding-mode manifold is presented by combining the event-triggered control scheme to achieve the tracking purpose with actuator faults, external disturbances, and DoS attacks. Based on the Lyapunov function approach, the tracking errors are bounded within the prescribed boundary. Finally, the effectiveness of the proposed method is verified by qualitative analysis and quantitative analysis of the simulation results. This study can enhance the security and reliability of heterogeneous multiagent systems, providing technical support for the safe operation of unmanned systems. This paper mainly solves the FTCC problem of second-order nonlinear heterogeneous multiagent systems, and further research is needed for the FTCC problem of higher-order nonlinear heterogeneous multi-agent systems. In addition, the system may encounter multiple cyber attacks. As one of the future research works, we can extend the results of this paper to high-order nonlinear systems under multiple cyber attacks, which contain DoS attacks and deception attacks, and achieve fault-tolerant cooperative control of heterogeneous multiagent systems. Full article

Quantitative systems pharmacology (QSP) models are rarely applied prospectively for decision-making in clinical practice. We therefore aimed to operationalize a QSP model for potas-sium homeostasis to predict potassium trajectories based on spironolactone administrations. For this purpose, we proposed a general workflow that was applied to electronic health records (EHR) from patients treated in a German tertiary care hospital. The workflow steps included model exploration, local and global sensitivity analyses (SA), identifiability analysis (IA) of model parameters, and specification of their inter-individual variability (IIV). Patient covariates, selected parameters, and IIV then defined prior information for the Bayesian a posteriori prediction of individual potassium trajectories of the following day. Following these steps, the successfully operationalized QSP model was interactively explored via a Shiny app. SA and IA yielded five influential and estimable parameters (extracellular fluid volume, hyperaldosteronism, mineral corticoid receptor abundance, potassium intake, sodium intake) for Bayesian prediction. The operationalized model was validated in nine pilot patients and showed satisfactory performance based on the (absolute) average fold error. This provides proof-of-principle for a Prescribing Monitoring of potassium concentrations in a hospital system, which could suggest preemptive clinical measures and therefore potentially avoid dangerous hyperkalemia or hypokalemia. Full article

Physical therapy is often essential for complete recovery after injury. However, a significant population of patients fail to adhere to prescribed exercise regimens. Lack of motivation and inconsistent in-person visits to physical therapy are major contributing factors to suboptimal exercise adherence, slowing the recovery process. With the advancement of virtual reality (VR), researchers have developed remote virtual rehabilitation systems with sensors such as inertial measurement units. A functional garment with an integrated wearable sensor can also be used for real-time sensory feedback in VR-based therapeutic exercise and offers affordable remote rehabilitation to patients. Sensors integrated into wearable garments offer the potential for a quantitative range of motion measurements during VR rehabilitation. In this research, we developed and validated a carbon nanocomposite-coated knit fabric-based sensor worn on a compression sleeve that can be integrated with upper-extremity virtual rehabilitation systems. The sensor was created by coating a commercially available weft knitted fabric consisting of polyester, nylon, and elastane fibers. A thin carbon nanotube composite coating applied to the fibers makes the fabric electrically conductive and functions as a piezoresistive sensor. The nanocomposite sensor, which is soft to the touch and breathable, demonstrated high sensitivity to stretching deformations, with an average gauge factor of ~35 in the warp direction of the fabric sensor. Multiple tests are performed with a Kinarm end point robot to validate the sensor for repeatable response with a change in elbow joint angle. A task was also created in a VR environment and replicated by the Kinarm. The wearable sensor can measure the change in elbow angle with more than 90% accuracy while performing these tasks, and the sensor shows a proportional resistance change with varying joint angles while performing different exercises. The potential use of wearable sensors in at-home virtual therapy/exercise was demonstrated using a Meta Quest 2 VR system with a virtual exercise program to show the potential for at-home measurements. Full article

This study aimed to investigate the resting metabolic rate (RMR) in cross-training practitioners (advanced and novice) using indirect calorimetry (IC) and compare it with predictive equations proposed in the scientific literature. Methods: A cross-sectional and comparative study analyzed 65 volunteers, both sexes, practicing cross-training (CT). Anthropometry and body composition were assessed, and RMR was measured by IC (FitMate PRO^®), bioimpedance (BIA-InBody 570^®), and six predictive equations. Data normality was tested by the Kolgomorov–Smirnov test and expressed as mean ± standard deviation with 95% confidence intervals (CI), chi-square test was performed to verify ergogenic resources, and a Bland–Altman plot (B&A) was made to quantify the agreement between two quantitative measurements. One-way ANOVA was applied to body composition parameters, two-way ANOVA with Bonferroni post hoc was used to compare the RMR between groups, and two-way ANCOVA was used to analyze the adjusted RMR for body and skeletal muscle mass. The effect size was determined using Cohen’s d considering the values adjusted by ANCOVA. If a statistical difference was found, post hoc Bonferroni was applied. The significance level was p < 0.05 for all tests. Results: The main results indicated that men showed a higher RMR than women, and the most discrepant equations were Cunningham, Tinsley (b), and Johnstone compared to IC. Tinsley’s (a) equation indicated greater precision in measuring the RMR in CM overestimated it by only 1.9%, and BIA and the Harris–Benedict in CW overestimated RMR by only 0.1% and 3.4%, respectively. Conclusions: The BIA and Harris–Benedict equation could be used reliably to measure the RMR of females, while Tinsley (a) is the most reliable method to measure the RMR of males when measuring with IC is unavailable. By knowing which RMR equations are closest to the gold standard, these professionals can prescribe a more assertive diet, training, or ergogenic resources. An assertive prescription increases performance and can reduce possible deleterious effects, maximizing physical sports performance. Full article

Background: Over the past 100 years, the discovery of antibiotics is regarded as one of the most significant advances in medical research and has saved millions of lives. However, the emergence of antimicrobial-resistant bacteria has significantly reduced the efficacy of antibiotics against infectious disorders. Antimicrobial resistance is mostly caused by antibiotic misuse for conditions that may be treated with self-care. During the COVID-19 pandemic, antibiotic use has been out of control among the general population. Aim: The objective of this study is to investigate the prevalence of antibiotic misuse during the COVID-19 pandemic in Lebanon. Methods: In January 2024, a descriptive cross-sectional study was conducted amongst students registered at the Islamic University of Lebanon. Individuals who have been infected with COVID-19 at least once were eligible for the study and were selected by a non-random snowball sampling technique. Descriptive and quantitative analyses were performed using SPSS 21. Results: Out of the 478 participants who completed the questionnaire, 40.2% (n = 192) received antibiotics during the COVID-19 infection. A physician’s prescription is mentioned by some participants (51%, n = 98), followed by a pharmacist’s (23.4%, n = 45), self-taken (14.5%, n = 28), and others as family or friends (10.9%, n = 21). Moreover, 59.3% (n = 114) of the respondents respected the antibiotic therapy’s rules, and 40.6% (n = 78) discontinued taking the antibiotic when they felt better. Conclusion: Our results showed that participants were likely to show unsatisfactory compliance and to use non-prescribed antibiotics. Campaigns are urgently needed to promote appropriate antibiotic use. Full article

Aims and Objectives: This review aims to analyze the effectiveness of motivational interviewing (MI) in enhancing therapeutic adherence and compliance in adult patients with inflammatory bowel disease (IBD), especially considering the disruptions caused by the COVID-19 pandemic. Background: IBD, which includes conditions such as ulcerative colitis and Crohn’s disease, affects over 10 million people globally. It significantly impacts both physical and psychological well-being, leading to challenges in therapeutic adherence. Only 25–47% of patients with IBD adequately follow prescribed treatments. Design and Methods: An integrative methodology that combines qualitative and quantitative research was utilized, following a 7-step framework. This framework encompasses identifying the research question, devising a search strategy, performing a critical appraisal, summarizing findings, extracting data, conducting an analysis, and drawing conclusions. Results: Poor adherence to therapy among patients with IBD can exacerbate disease progression and result in complications. MI has been identified as a promising approach to improving both adherence and treatment outcomes. Studies, including those predating the COVID-19 pandemic, have demonstrated MI’s effectiveness in enhancing adherence among patients with IBD. Conclusions: MI shows promise in enhancing adherence among adult patients with IBD. Although initial results are promising, additional research is needed to thoroughly understand its effectiveness across various clinical contexts. Relevance to Clinical Practice: The findings underscore the potential of MI as an integral component of IBD treatment strategies, suggesting that its implementation could enhance patient–provider interactions and lead to better overall health outcomes. Full article

Background/Objectives: Heart failure (HF) is a highly prevalent clinical syndrome with serious morbidity and mortality. Furthermore, acute heart failure (AHF) is the main cause of hospital admission in people aged 65 years or more. Sodium-glucose cotransporter type 2 inhibitors (SGLT2is) have been shown to improve the survival and quality of life in patients with HF regardless of left ventricular ejection fraction (LVEF). Our aims were to describe the characteristics of adults with multiple pathologies admitted with acute heart failure as the main diagnosis and of the population treated with SGLT2is, as well as to evaluate if their use was associated with lower readmission and mortality rates. Methods: A prospective study of patients from the PROFUND-IC registry who were admitted with AHF as the main diagnosis was conducted. Clinical and analytical characteristics were analyzed, as well as readmissions and mortality. Descriptive and bivariate analyses of the sample between those taking SGLT2is and those who were not were performed, using the chi-square test for qualitative variables and Welch’s test for quantitative measures, as well as the Fisher and Wilcoxon tests as indicated for nonparametric tests. Kaplan–Meier curves were constructed to analyze the readmission and mortality of patients at 12 months based on SGLT2i treatment. Finally, a propensity score matching was performed, guaranteeing that the observed effect of the drug was not influenced by the differences in the characteristics between the groups. Results: There were 750 patients included: 58% were women, and the mean age was 84 years. Functional class II according to the NYHA scale predominated (54%), and the mean LVEF was 51%. SGLT2 inhibitors were prescribed to only 28% of patients. Most of the patients were men (48.6% vs. 39.8%, p = 0.029), they were younger (82 vs. 84 years, p = 0.002), and their LVEF was lower (48% vs. 52%, p < 0.001). Lower mortality was observed in the group treated with SGLT2is, both during baseline admission (2.4% vs. 6.9%, p = 0.017) and at the 12-month follow-up (6.2% vs. 13%, p = 0.023); as well as a lower readmission rate (23.8% vs. 38.9%, p < 0.001). After the propensity score matching, a decrease in the 12-month readmission rate continued to be observed in the group treated with SGLT2is (p = 0.03). Conclusions: SGLT2is use was associated with lower readmission rates at the 12-month follow-up in older adults with multiple pathologies admitted with acute heart failure. Full article