Continuous Control Research Articles

Predefined-time stabilisation of stochastic low-order nonlinear systems with asymmetric output constraint

This paper researches the predefined-time stabilisation problem for a class of stochastic low-order nonlinear systems with asymmetric output constraint whose nonlinearities satisfy high-order and low-order growth conditions. By introducing a novel nonlinear transformation and utilising the adding a power integrator technique, a continuous state feedback controller is designed. The proposed control scheme can guarantee that the output constraint will not be violated almost surely and the trivial solution of the closed-loop system is stochastic predefined-time stable. Finally, two simulation examples are provided to demonstrate the effectiveness of this control method.

A COMPLEX APPROACH TO THE FORMATION OF INTERNATIONAL DEVELOPMENT STRATEGIES OF THE ENTERPRISE

The research focuses on modern academic sources related to theoretical definitions in the field of strategic management of international business processes. A special attention is paid to different approaches for strategy development. The key factors impacting the success of export strategies are determined. In particular, strategies for entering foreign markers are researched based on criteria such as a degree of control over distribution, a level of investment, a predisposition to risks, elasticity, speed of entering a market, and market access. A comparative analysis of main strategies is given, taking into account the above-mentioned factors as well as an evaluation of the strong and weak sides of each approach. In addition, the strategies are analyzed from the perspective of instruments that are used for their implementation, highlighting the necessity of choosing a complex and polyhedral approach for achieving success on international markets. The research outlines the main challenges faced by businesses entering external markets, describing in detail potential obstacles at every step of the process. An emphasis is put not only on the development of strategies but also on the support of a reliable system of continuous monitoring and control. An algorithm for forming a complex approach for realization and control of the implementation of the strategies is suggested. Main principles that ensure successful access to foreign markers are outlined. The main principles for successful strategy implementation are defined, including a detailed market analysis, the use of unique product characteristics, consideration of local market specifics, and adaptability to changes. Adherence to these principles will enhance the enterprise’s competitiveness. Assessment and forecasting methods of external and internal business environments are discussed for effective execution of the chosen strategies. The study provides an overview of qualitative and quantitative methods, including peer review methods, extrapolation methods, and econometric modeling, that allow companies to better adapt their strategies to the dynamic conditions of the global market.

The Effect of Continuous Care Model Based Education on Quality of Life, Sleep Quality, and Fatigue in Patients Undergoing Coronary Artery Bypass Surgery

ABSTRACT Background Postoperative care strategies, such as self-care education and cardiac rehabilitation, are critical in mitigating readmissions and enhancing patient outcomes following Coronary Artery Bypass Surgery. Purpose The purpose of this study was to design and develop a program that leads to acceptance, increased insight, and appropriate action to control the disease and its potential psychological complications. Methods This randomized control trial involved 140 patients scheduled for coronary artery bypass surgery at a rehabilitation clinic in 2023. The intervention followed the Continuous Care Model, encompassing familiarization, sensitization, control, and evaluation phases. Results Post-intervention, the intervention group exhibited a significantly higher mean quality of life score than the control group (p < .001). Furthermore, a notable difference in mean sleep quality scores between the control and intervention groups was observed post-intervention (p = .026). Discussion Patient education based on the Continuous Care Model effectively enhances quality of life sleep and reduces fatigue in patients undergoing coronary artery bypass surgery. Translation to Health Education Practice The study provides empowerment through patient and family education on self-care practices. Implementing of the Continuous Care Model as a non-invasive, cost-effective method can be considered in the patient education unit of hospitals.

Linear parameter varying μ synthesis robust control of CDC semi‐active suspension system for nonlinearity and uncertainty

AbstractBecause the continuous damping control (CDC) semi‐active suspension system has complex nonlinear and uncertain characteristics that can significantly affect the performance of the system. And in the controller design process, achieving a balance of multiple performance objectives is often difficult. Therefore, this paper designs a linear parameter varying (LPV) μ synthesis robust controller for the vibration suppression and multi‐objective control of a 7‐degree‐of‐freedom (7‐DOF) vehicle suspension system equipped with CDC dampers. Firstly, the nonlinear force model of the solenoid valve CDC damper is developed based on the actual damping variation. Considering the nonlinear forces of the coil springs, the nonlinear model of the 7‐DOF suspension system is expressed as LPV form. Further, the linear fractional transformation (LFT) method is used to analyze and reconstruct the system model for multiple parameter uncertainties of the suspension. The actuator time delays are also simulated through a frequency domain transfer function, which is considered to be an unmodeled dynamic at the input of the system. Finally, an LPV‐μ synthesis robust controller based on nonlinearity and mixed uncertainty is designed to improve car ride comfort and achieve the best relationship between comfort and handling stability. Simulation and experimental results under random disturbance conditions show that the LPV‐μ synthesis controller has better anti‐jamming performance and controllability compared to the H∞ controller and μ synthesis controller.

Adaptive Integral Sliding Mode Control with Chattering Elimination Considering the Actuator Faults and External Disturbances for Trajectory Tracking of 4Y Octocopter Aircraft

This paper presents a control strategy for a 4Y octocopter aircraft that is influenced by multiple actuator faults and external disturbances. The approach relies on a disturbance observer, adaptive type-2 fuzzy sliding mode control scheme, and type-1 fuzzy inference system. The proposed control approach is distinct from other tactics for controlling unmanned aerial vehicles because it can simultaneously compensate for actuator faults and external disturbances. The suggested control technique incorporates adaptive control parameters in both continuous and discontinuous control components. This enables the production of appropriate control signals to manage actuator faults and parametric uncertainties without relying only on the robust discontinuous control approach of sliding mode control. Additionally, a type-1 fuzzy logic system is used to build a fuzzy hitting control law to eliminate the occurrence of chattering phenomena on the integral sliding mode control. In addition, in order to keep the discontinuous control gain in sliding mode control at a small value, a nonlinear disturbance observer is constructed and integrated to mitigate the influence of external disturbances. Moreover, stability analysis of the proposed control method using Lyapunov theory showcases its potential to uphold system tracking performance and minimize tracking errors under specified conditions. The simulation results demonstrate that the proposed control strategy can significantly reduce the chattering effect and provide accurate trajectory tracking in the presence of actuator faults. Furthermore, the efficacy of the recommended control strategy is shown by comparative simulation results of 4Y octocopter under different failing and uncertain settings.

Barn Owls as a Nature-Based Solution for Pest Control: A Multinational Initiative Around the Mediterranean and Other Regions

Pest rodents cause extensive damage to crops worldwide. Up to 40% of global crop production is lost annually to pests and diseases, with rodents accounting for 15–30% of this loss amounting to billions of dollars each year. The current method of controlling rodent populations involves the extensive use of chemical rodenticides. While effective in the short term, these chemicals pose serious environmental and health risks, leading to secondary poisoning of non-target species and other long-term negative ecological consequences, underscoring the need to adopt more sustainable pest-control measures. Nature-Based Solutions (NbSs), on the other hand, are increasingly recognized for addressing environmental challenges such as climate change, biodiversity loss, and sustainable development, and they include actions that protect, sustainably manage, and restore ecosystems. In this context, Barn Owls (Tyto alba) are highly effective as a natural pest-rodent control agents in agro-ecosystems. The species has a wide distribution and adaptability to various environments, and its diet consists predominantly of small mammals, with rodents making up from 50–60% up to even 90–95% of the diet according to different geographical regions. Each Barn Owl family can consume thousands of rodents annually, creating a high potential to reduce crop damage and infestations. Deploying nest boxes in agricultural areas can significantly increase Barn Owl populations, ensuring continuous and effective rodent control. Limitations of this solution must also be taken into consideration such as predation on rodents and small mammals that are not pests, and possible competition with other nocturnal birds of prey. Ιn the current paper, we aim to introduce the concept of owls as a NbS for pest rodent control and outline the main challenges, pitfalls, advantages, and disadvantages of implementing this solution in a new geographical region, and all the necessary in-between steps (scientific, societal, administrative, educational) that have to be followed for a successful implementation. So far, several countries have successfully implemented Barn Owl nest box schemes, with Israel and Cyprus achieving reduction in the use of pesticides by 45% and 58%, respectively, whereas the project is spreading to other Mediterranean countries (Jordan, Palestine Authority, Greece, Morocco, Spain), in palm plantations in Malaysia and USA, and in the vineyards of Napa Valley in California. The success of Barn Owl nest box programs relies on integrating scientific research, societal needs, supportive policy frameworks, and education. Barn Owl nest box programs are both bottom-up and top-down initiatives, in need of the participation of farmers and local communities to establish and deploy the Barn Owl solution. Continuous research is also necessary to explore systematically Barn owl trophic ecology, foraging and breeding ecology, interactions with agricultural landscape, and land uses in temporal and spatial scales, and challenges such as habitat suitability, availability of nesting sites, and regional ecological conditions must also be addressed.

The docking control system of an autonomous underwater vehicle combining intelligent object recognition and deep reinforcement learning

This study develops a visual-based docking system (VDS) for an autonomous underwater vehicle (AUV), significantly enhancing docking performance by integrating intelligent object recognition and deep reinforcement learning (DRL). The system overcomes traditional navigation limitations in complex and unpredictable environments by using a variable information dock (VID) for precise multi-sensor docking recognition in the AUV. Employing image-based visual servoing (IBVS) technology, the VDS efficiently converts 2D visual data into accurate 3D motion control commands. It integrates the YOLO (short for You Only Look Once) algorithm for object recognition and the deep deterministic policy gradient (DDPG) algorithm, improving continuous motion control, docking accuracy, and adaptability. Experimental validation at the National Cheng Kung University towing tank demonstrates that the VDS enhances control stability and operational reliability, reducing the mean absolute error (MAE) in depth control by 42.03% and pitch control by 98.02% compared to the previous method. These results confirm the VDS's reliability and its potential for transforming AUV docking.

Multi-attribute dynamic attenuation learning improved spiking actor network

Deep reinforcement learning (DRL) has shown promising results in solving robotic control and decision tasks, which can learn the high-dimensional state and action information well. Despite their successes, conventional neural-based DRL models are criticized for low energy efficiency, making them laborious to be widely applied in low-power electronics. With more biologically plausible plasticity principles, spiking neural networks (SNNs) are now considered an energy-efficient and robust alternative. The most existing dynamics and learning paradigms for spiking neurons with a common Leaky Integrate-and-Fire (LIF) neuron model often result in relatively low efficiency and poor robustness. To address these limitations, we propose a multi-attribute dynamic attenuation learning improved spiking actor network (MADA-SAN) for reinforcement learning to achieve effective decision-making. The resistance, membrane voltage and membrane current of spiking neurons are updated from a fixed value into dynamic attenuation. By enhancing the temporal relation dependencies in neurons, this model can learn the spatio-temporal relevance of complex continuous information well. Extensive experimental results show MADA-SAN performs better than its counterpart deep actor network on six continuous control tasks from OpenAI gym. Besides, we further validated the proposed MADA-LIF can achieve comparable performance with other state-of-the-art algorithms on MNIST and DVS-gesture recognition tasks.

Development of a control algorithm for a boost converter with the possibility of dynamic correction of control system parameters

RELEVANCE of the study lies in the development of an algorithm for controlling a DC voltage converter capable of providing a high-quality transient process with a wide change in the input parameters of the control object, affecting its nonlinear properties. purpose. THE PURPOSE. To consider methods for the development of continuous and discrete control systems for a step-up DC voltage converter and to obtain an analytical dependence of accounting for the nonlinear properties of the converter that affect the quality of regulation of the output voltage of the voltage stabilizer METHODS. The method of the average geometric root was chosen as a method for calculating the coefficients of the DC voltage converter control system, and the current circuit is adjusted using the technical optimum method, and the voltage circuit using the symmetric optimum method. The obtained analytical solutions of mathematical models and simulation models were compared in the SimInTech software environment. results. RESULTS. The simulation results show that the analytical solution of the mathematical model of the voltage stabilization system has a shorter transition time than the simulation results. This is due to the fact that in the mathematical model according to which the continuous control algorithm was synthesized, the presence of a power input filter, as well as the degree of their precharge, is not taken into account. Because of this, the transition time on simulation models is slower, applied 4 times than in the mathematical model. conclusion. CONCLUSION. When comparing the algorithms with each other, it can be seen that the algorithm obtained by converting a continuous algorithm by the Tusten method has the shortest transition time than all other algorithms. The continuous algorithm and the algorithm obtained by the inverse Euler transformation method have a speed close to each other, and the algorithm obtained by the direct Euler transformation turns out to be the slowest.

Angioprotein-like 3 and atheroma progression in statin-treated type 2 diabetic patients with coronary artery disease: the pre-specified analysis from the OPTIMAL randomized controlled trial

Abstract Introduction Despite guideline-recommended control of LDL-C with a statin, type 2 diabetic patients more likely cause cardiovascular events. This indicates the need to identify additional therapeutic targets in those patients. Angioprotein-like 3 (ANGPTL3) is an inhibitor of lipoprotein and endothelial lipase, which increases the levels of LDL-C and other atherogenic lipoproteins. These properties suggest ANGPTL3 as a potential driver associated with diabetic atherosclerosis. The OPTIMAL randomized controlled trial (jRCT1052180152) compared the efficacy of continuous glucose monitoring-guided versus HbA1c-guided glycemic control on coronary atherosclerosis in statin-treated type 2 diabetic patients by using serial intravascular ultrasound (IVUS) imaging. This pre-specified analysis of the OPTIMAL study was designed to evaluate whether ANGPTL3 affects progression of coronary atheroma in statin-treated type 2 diabetic patients. Purpose To elucidate the association of serial change in ANGPTL3 with the degree of atheroma progression in statin-treated type 2 diabetic patients. Methods 59 patients (59 lesions) with serial ANGPTL3 levels at baseline and week 48 were included into the current analysis. Clinical demographics and IVUS-derived measure were compared in patients with and without any increase in ANGPTL3. Results All of study subjects received a statin, and over 60% of them were treated with high-intensity statin. Under these lipid-lowering therapies, any increase in ANGPTL3 levels at week 48 was observed in 52.5% of study participants. Patients with any increase in ANGPTL3 were more likely to have a history of hypertension (90.0% vs. 64.3%, p=0.02), whereas there was no significant difference in on-treatment LDL-C levels between the two groups (1.8 ± 0.4 vs. 1.6 ± 0.6 mmol/L, p=0.25) (Table). On IVUS imaging analysis, baseline percent atheroma volume (PAV) did not differ in those with and without any increase in ANGPTL3. However, patients with any increase in ANGPTL3 presented a greater progression of PAV (0.08 ± 0.28 vs. -0.74 ± 0.29, p=0.04). There was a trend toward a lower frequency of PAV regression in those exhibiting any increase in ANGPTL3 (48.4% vs. 57.1%), but this comparison did not meet statistical significance (p=0.50) (Figure). Multivariate analysis adjusting clinical characteristics demonstrated that any increase in ANGPTL3 level was not independently associated with PAV progression (β=0.16, 95%CI=-0.01 – 0.18, p=0.27). Conclusion Over 50% of statin-treated type 2 diabetic patients with coronary atherosclerosis showed any increase in ANGPTL3 levels at week 48. Serial IVUS imaging revealed that patients with any increase in ANGPTL3 more likely presented a greater atheroma progression. However, this relationship did not exist after adjusting clinical characteristics. Our findings suggest that ANGPTL3 may not be a pivotal driver associated with atheroma progression in statin-treated type 2 diabetic patients.

Discrepancies in breast cancer screening and hypothesis of artificial intelligence support

Abstract In Italy,the National Breast Screening Programme offers mammography as the 1st level examination, blindly assessed by two radiologists.In the context of continuous quality control,discrepancies in the assessment of mammograms between the 1st and 2nd reader have been studied,focusing on the most significant ones.The aims of the present study are:to evaluate the outcome of women sent to the 2nd level of review;to evaluate the possibility of using artificial intelligence (AI) software to assist radiologists in case of discrepancies. In the Local Health Authority Roma2,radiologists use a standardised classification that rates radiographs on a five-level scale from R1 to R5:R1=no abnormalities,R2=benign findings,R3=equivocal findings,R4=suspected cancer,R5=strongly suspected cancer.Data were extracted from the mammograms performed in 2023 that showed discrepancies (R1/R2 vs. R4/R5).2nd level mammography≥R4 and 2nd level histology≥B4 were considered positive. For the second aim,”IA Lunit INSIGHT” software was used to create specific target groups using the following cut-offs:G1&amp;lt;10%, G2 11-29%; G3 30-59%; G4 60-85%; G5 86-100%(groups ≥G3 were considered positive). Of the 36,339 mammograms,524(1.5%) were discordant:347(66.2%) were considered suspicious by the second radiologist.49(9.4%) were confirmed positive by Level II mammography and 23(4.4%) reported histology≥B4. The AI red a random sample of 247 mammograms and classified 34 women as positive (1 G5, 6 G4, 9 G3), of whom 11 (4.5%) were confirmed positive by Level II mammography and 6 (2.4%) were histologically positive. Of the negative women, 2 had histology≥B4. Discrepancies may be one of the factors leading to inappropriate referral to second level investigation. In such cases, the use of AI may improve the appropriateness of further investigation, although this hypothesis needs to be tested in larger numbers, with additional comparisons with experienced radiologists and consideration of retraining. Key messages • Continuous monitoring in cancer screening programs are vital to assure a sustainability of the process. • Artificial Intelligence software are promising in aiding health care professionals in case of discrepancies.

DEVICE FOR SYNCHRONIZATION ELECTRON ACCELERATOR

A device designed for continuous management and control of the parameters of elements and nodes of an electronic accelerator has been developed. The created device makes it possible to control the modes of the accelerator taking into account the state of electrical blockages and counting the necessary time exposures.

Simulation-based evaluation of advanced threat detection and response in financial industry networks using zero trust and blockchain technology

The financial sector is increasingly facing advanced cyber threats, necessitating a shift from traditional security measures to more dynamic frameworks. This study presents a novel integration of Zero Trust architecture with hybrid access control system and blockchain technology to enhance security in financial institutions. Zero Trust enforces continuous authentication and dynamic access controls, while blockchain secures digital identities and transaction logs through its immutable ledger, ensuring data integrity and non-repudiation. The proposed framework, evaluated using OMNeT++ simulations enhanced by Ethereum-Ganache, shows improved detection accuracy, reduced false positives, and increased resistance to insider threats and other attacks. It also strengthens compliance with regulatory requirements through robust audit trails, providing enhanced protection for sensitive financial data.

Full-space trifunctional metasurface with independent amplitude/phase control and its application to asymmetric spatial power divider

ABSTRACT In this paper, a dual-frequency trifunctional metasurface (MS) consisting of three metal layers printed on two substrate layers is proposed. The low-frequency transmitted wave is regulated through a C-shaped slot etched in middle layer and C-shaped patches in top/bottom metal layers. High-frequency reflected waves can be regulate by the C-shaped slot etched in ring patch in top/bottom layers. Also, in top/bottom layers, C-shaped patches and slots operate in electric and magnetic resonant modes that the interference between transmitted and reflected waves is suppressed. This MS integrates three independent working modes, that is to say, it can reflect x-polarized waves propagating along +z/-z direction at high frequency and transmit x-polarized low-frequency waves from -z direction. Meanwhile, 360° phase coverage and continuous amplitude control from 0 to 1 can be independently achieved in three working modes. Based on this MS, an asymmetric spatial power divider is designed and measured. The measured results are consistent with the designed goals.

Image-Guided Breast Conserving Surgery

Background: Breast-conserving surgery (BCS) has gained wide acceptance as the treatment of choice for early-stage breast cancer. One of the primary goals of BCS is to obtain tumor-free resection margins. In practice, the excision of a palpable breast carcinoma is guided by preoperative diagnostic images and the intraoperative tactile skills of the surgeon. The somewhat ‘blind’ approach of using palpation-guided surgery is known to be highly inaccurate, with studies worldwide reporting positive resection margins in up to 41% of patients. In recent years, ultrasonography has emerged as an effective guidance tool during surgery and ultrasound-guided surgery has been introduced into breast cancer surgery as a method of excising nonpalpable breast cancer. Objective: The aim of this study is comparing ultrasound-guided vs palpation-guided conservative breast surgery in obtaining tumor-free resection margins. Methods: This study was a prospective randomized controlled clinical trial where patients with early breast cancer (T1-T2) and eligible for breast conserving surgery are randomly assigned (1:1) into two arms. Arm A: included the patients who will undergo ultrasound-guided breast conserving surgery. Arm B: included the patients who will undergo the conventional palpation-guided breast conserving surgery. Results: Overall, 142 patients undergoing breast conserving surgery were enrolled: 71 were allocated to the Ultrasound-guided (US) group (Arm A) and 71 to the Palpation-guided (PG) group (Arm B). Patient and tumor characteristics were comparable between the two groups. Age, Body mass index, tumor laterality, tumor location and tumor stage were comparable in both groups and statistically insignificant. Despite that the final tumor size was comparable between both groups, IOUS significantly reduced the main specimen volume and the least negative margin width (p&lt;0.001). The median operative time was significantly longer in the US group bey around 27 min than in the PG group and this was statistically significant in favor of the PG surgery (p&lt;0.001). The involved resection margin rate was significantly higher in the PG group and thus the need for reoperation (p&lt;0.001). Conclusion: IOUS is the only method allowing a true real-time visualization and continuous control of resection margins during all phases of BCS. In our single-institution study, IOUS demonstrated clear superiority over palpation-guided surgery in both oncological and surgical outcomes except for the operative time (smaller excision volume yet, with optimum resection margins). IOUs provides much better tumor localization in small breasts with dense fibroadenosis. Since all the other available localization techniques (including palpation) limit the surgeon’s visual guidance during BCS, IOUS could be regarded as one of the most significant modern technological innovations in the field of breast cancer surgery, restoring sight to the breast surgeon. Our findings strongly suggests that the integration of IOUS in breast conserving surgery could be regarded as a highly beneficial surgical approach.

Fixed-time second-order sliding mode output feedback trajectory tracking control for an autonomous surface vehicle with model uncertainties and prescribed performance

This paper investigates the fixed-time trajectory tracking control problem of autonomous surface vehicle system with asymmetric performance constraints. The external disturbances, model uncertainties and the difficulty of velocity measurement are all taken into account in the controller design. Asymmetric performance constraints are firstly studied to improve the transient and steady-state performance of the tracking error system. Next, a fixed-time extended state observer is developed to estimate the unknown velocity and external disturbances. Both the fixed-time first-order and the second-order PID-type sliding surfaces are designed. Further, two continuous output feedback controllers are built to achieve high control accuracy and low energy consumption and to achieve fixed-time stability of the closed-loop system. Finally, abundant simulations for CyberShip II demonstrate the effectiveness of the proposed algorithms.

Hyperparameter Control Using Fuzzy Logic: Evolving Policies for Adaptive Fuzzy Particle Swarm Optimization Algorithm.

Heuristic optimization methods such as Particle Swarm Optimization depend on their parameters to achieve optimal performance on a given class of problems. Some modifications of heuristic algorithms aim at adapting those parameters during the optimization process. We present a novel approach to design such adaptation strategies using continuous fuzzy feedback control. Fuzzy feedback provides a simple interface where probes are sampled in the optimization process and parameters are fed back to the optimizer. The probes are turned into parameters by a fuzzy process optimized beforehand to maximize performance on a training benchmark. Utilizing this framework, we systematically established 127 different Fuzzy Particle Swarm Optimization algorithms featuring a maximum of 7 parameters under fuzzy control. These newly devised algorithms exhibit superior performance compared to both traditional PSO and some of its best parameter control variants. The performance is reported in the single-objective bound-constrained numerical optimization competition of CEC 2020. Additionally, two specific controls, highlighted for their efficacy and dependability, demonstrated commendable performance in real-world scenarios from CEC 2011.

Impact of proprioceptive cervical dizziness in chronic neck pain syndromes on gait and stance during active head-turn challenges.

An earlier observational study described selected patients with acute neck pain syndrome, who experienced short bursts of cervical vertigo elicited by rapid head movements. The current study on a larger cohort of 20 patients with chronic or frequently recurring neck pain syndrome and age-matched controls focused on two major questions: (1) Can head movements in subjects with exacerbations of neck pain and restrictions of neck mobility also elicit bursts of vertigo? (2) What is the impact on postural balance measured by analysis of body sway and locomotion? A detailed questionnaire was applied, posture and gait were evaluated by use of instrumented posturography-and gait analysis with and without slow or rapid horizontal head rotations in the yaw plane with and without sight/visual input. All patients reported some or frequent episodes of dizziness in the range of seconds only elicited by rapid, not by slow head movements. Postural sway in patients was unremarkable in undisturbed conditions without head movements, but specifically increased by rapid but not slow head turns. The latter is best explained by the lack of continuous control of velocity and amplitude of saccadic head movements. Gait analysis revealed a slowed and cautious gait pattern already at undisturbed condition that was even exaggerated during rapid head turns. These observations demonstrate that chronic or recurrent neck pain is associated with episodic experiences of dizziness and above results in both chronic and episodic alterations of stance and gait that resemble those described for patients with phobic postural vertigo/persistent postural perceptual dizziness, a functional gait disorder.

Mixed‐Integer Optimal Control via Reinforcement Learning: A Case Study on Hybrid Electric Vehicle Energy Management

ABSTRACTMany optimal control problems require the simultaneous output of discrete and continuous control variables. These problems are typically formulated as mixed‐integer optimal control (MIOC) problems, which are challenging to solve due to the complexity of the solution space. Numerical methods such as branch‐and‐bound are computationally expensive and undesirable for real‐time control. This article proposes a novel hybrid‐action reinforcement learning (HARL) algorithm, twin delayed deep deterministic actor‐Q (TD3AQ), for MIOC problems. TD3AQ leverages actor‐critic and Q‐learning methods to manage discrete and continuous action spaces simultaneously. The proposed algorithm is evaluated on a plug‐in hybrid electric vehicle (PHEV) energy management problem, where real‐time control of the discrete variables, clutch engagement/disengagement and gear shift, and continuous variable, engine torque, is essential to maximize fuel economy while satisfying driving constraints. Simulation results show that TD3AQ achieves near‐optimal control, with only a 4.69% difference from dynamic programming (DP), and outperforms baseline reinforcement learning algorithms for hybrid action spaces. The sub‐millisecond execution time indicates potential applicability in other time‐critical scenarios, such as autonomous driving or robotic control.

ESTUDO EPIDEMIOLÓGICO DE CASOS NOTIFICADOS POR CHIKUNGUNYA ENTRE OS ANOS DE 2019 A 2023 EM UM MUNICÍPIO DO TOCANTINS

INTRODUCTION: The Chikungunya virus is transmitted by Aedes aegypti and Aedes albopictus, causing fever and joint pain, with potential serious complications. This study aimed to analyze the incidence and epidemiological profile of Chikungunya cases in Porto Nacional, Tocantins, between 2019 and 2023. METHODOLOGY: A quantitative approach was used, based on retrospective data found in the Notifiable Diseases Information System (SINAN). The variables tested included sex, age group, education and disease progression. The incidence calculation was carried out based on population estimates provided by IBGE. RESULTS: The results indicated a significant increase in cases in 2022, representing 58% of the total, followed by a drop in 2023. The majority of cases affected women (65%) and people between 20 and 39 years old. Laboratory classification was the main diagnostic method, responsible for 60% of confirmed cases. DISCUSSION: The discussion of the results highlights the need for more effective public policies to control the spread of the virus, especially in vulnerable regions. FINAL CONSIDERATIONS: Therefore, although there was a reduction in cases in 2023, it is crucial to maintain continuous epidemiological surveillance and vector control actions to prevent future outbreaks and mitigate the impacts of Chikungunya on the population.