Continuous Control Research Articles

ANÁLISE TEMPORAL DA INCIDÊNCIA DE CASOS NOTIFICADOS DA DOENÇA DE CHAGAS NO BRASIL, NO PERÍODO DE 2010-2019

Chagas disease is caused by Trypanosoma cruzi and remains an important public health concern in Brazil, despite control measures adopted over the last few decades. The objective of this study is to carry out a temporal analysis of the incidence of reported cases of Chagas Disease in Brazil from 2010 to 2019, identifying trends and possible associated factors. Secondary data from the Notifiable Diseases Information System (SINAN) were used to calculate incidence rates by region and year. The statistical analysis included linear regression models to evaluate the temporal variation of notifications. The results indicate an overall reduction in notifications in the country during the period analyzed, with significant regional variations. The North region showed an increase in notifications, suggesting the need for greater surveillance and control strategies. In contrast, the Southeast and South regions maintained a stable downward trend, as a result of continued vector control measures. It is concluded that, although cases of Chagas disease are declining in much of Brazil, the disease still represents a public health challenge in some regions, especially in areas where oral transmission and vector synanthropy are on the rise.

New training simulator for lumbar puncture base on magnetorheological

In response to the difficulties in accurately reproducing the resistance drop generated by puncturing key tissue layers with a needle and the poor experience in existing simulators, based on the continuous controllability and rapid response of magnetorheological fluid under the influence of a magnetic field, this paper proposes a lumbar puncture training simulator(LPTS) that can accurately simulate the puncture feedback force within tissues such as the skin, subcutaneous fat, and supraspinous ligament throughout the entire process. By using a dual rod structure and reasonably arranging the damping channel gap, the influence of mechanical friction and zero-field damping force on the feedback force during tissue progression is minimized. This paper introduces the acquisition and modeling analysis of raw data, and based on this, the design, simulation, and mechanical testing of the simulator are carried out. Finally, a performance testing platform for the simulator is established to evaluate its tracking performance of the expected puncture strength and the reproducibility of the puncture sensation. The results show that the experimental puncture strength deviates from the expected puncture strength by 0.35 N to 0.61 N in the crucial steps of breaking through the supraspinous ligament, interspinous ligament, ligamentum flavum, and dura mater, with a relative error below 10 %.

Enhancing visual reinforcement learning with State–Action Representation

Despite the remarkable progress made in visual reinforcement learning (RL) in recent years, sample inefficiency remains a major challenge. Many existing approaches attempt to address this by extracting better representations from raw images using techniques like data augmentation or introducing some auxiliary tasks. However, these methods overlook the environmental dynamic information embedded in the collected transitions, which can be crucial for efficient control. In this paper, we present STAR: State-Action Representation Learning, a simple yet effective approach for visual continuous control. STAR learns a joint state–action representation by modeling the dynamics of the environment in the latent space. By incorporating the learned joint state–action representation into the critic, STAR enhances the value estimation with latent dynamics information. We theoretically show that the value function can still converge to the optima when involving additional representation inputs. On various challenging visual continuous control tasks from DeepMind Control Suite, STAR achieves significant improvements in sample efficiency compared to strong baseline algorithms.

A predictive fuzzy logic and rule-based control approach for practical real-time operation of urban stormwater storage system

Predictive real-time control (RTC) strategies are usually more effective than reactive strategies for the intelligent management of urban stormwater storage systems. However, it remains a challenge to ensure the practicality of RTC strategies that use accessible, non-idealized predictive information while improving their efficiency for successive rainfall events instead of specific phases. This study developed a predictive fuzzy logic and rule-based control (PFL-RBC) approach to address the continuous control of individual storage systems. This approach incorporates total rainfall depth forecast information with an intra-storm fuzzy logic system to optimize peak flow control and several rule-based strategies for pre-storm water detention, reuse, and release control. Computational experiments were conducted using a storage tank case study to test the proposed approach under various rainfall conditions and storage sizes. The results showed that PFL-RBC outperformed static rule-based control in infrequent design storms and realistic continuous rainfall events, reducing flood peaks and volumes by 55 %∼87 % and 7 %∼20 %, respectively, and significantly increasing water detention time and reuse volume. Meanwhile, PFL-RBC required less predictive information to achieve a 6 %∼15 % advantage in peak flow control compared to optimized model predictive control. More importantly, PFL-RBC was reliable in the face of input uncertainty, with <25 % performance loss for water quantity control when the realistic forecast error ranged from -50 % to +50 %. These findings suggest that the proposed approach has great potential to enhance the efficiency and practicality of stormwater storage operations.

Pushing health data access boundaries - adapting NHS governance for 3 challenges: clinical free-text, safe commercial access and AI development

This presentation will demonstrate expansions to TRE governance frameworks developed to facilitate safe data access in three advanced areas: commercial access, clinical free-text, and innovation with AI/Machine Learning. NHS research governance frameworks - originally set up for clinical trials and expanded into the TRE and secondary data use space – are not an immediate fit for advanced techniques in data science research. Over 2 years, public, expert and user engagement approaches were utilised to support developing frameworks within DataLoch, a Health and Social Care TRE and data access service in South-East Scotland. Surveys, workshops and continuous user and data controller feedback allowed the testing of tools and assessments to adapt traditional NHS governance structures. These frameworks utilise the Five Safes framework to make NHS data controllers supportive of innovative research in the public and health service’s benefit. The presentation will summarise the challenges faced for one TRE and researchers working to support these areas, and the frameworks that are now are being tested within an NHS Scotland Health Board. The development and implementation demonstrates that governance structures can be adapted collaboratively and paves the way for more flexible TRE governance to allow the use of NHS patient data to remain legally and ethically robust while supporting advanced techniques of analysis.

Ecology and Management of Sedges in Direct-seeded Rice: A Review

Sedges, resilient weeds from the Cyperaceae family, pose a significant threat to direct-seeded rice cultivation due to their perennial nature and robust propagules, which endure harsh conditions. Their emergence, growth and seed production during fallow periods contribute significantly to seed banks, making their management challenging compared to other weed types. Water levels in paddy fields dictate weed composition, favouring sedges and grasses under saturated conditions but shifting to grass weeds during cropping seasons, influenced by factors like soil conditions and rainfall. Managing sedges requires a multifaceted approach due to their perennial hydrophilic and pro-alkaline nature with extensive propagules. Sedges possessing strong root system with morphological similarities necessitate continuous weed control throughout the cropping season during the critical period ranging from 15 to 60 days after sowing for wet and dry direct-seeded rice. Effective weed management practices proved crucial for minimizing yield losses caused by infestation of Cyperus difformis, Fimbristylis miliacea and Schoenoplectus juncoides by many researchers. Various methods, including cultural practices like stale seedbeds, physical methods like summer tillage, biological approaches such as integrating poultry and chemical interventions like herbicide application, are utilized for sedge management in rice fields. Higher efficacy of ethoxysulfuron for management of majority of sedge weeds in rice has been reported by many workers. However, relying on a single strategy is insufficient to keep sedge populations below the threshold, necessitating a comprehensive and adaptable approach to weed control in rice cultivation.

Flexible fabrication of core/shell nanoparticles for tailored infrared emissivity on aluminum via femtosecond laser self-deposition.

A metal surface with controllable infrared emissivity has a wide range of applications. However, a flexible and simple fabrication method is needed. Here, a controllable femtosecond laser self-deposition technology was developed to fabricate Al@AlOx core/shell micropillars (MPs) with diverse size distribution on the aluminum surface in a single-step operation under ambient conditions. By establishing a deterministic relationship between pulse-repetition frequency (PRF) and particle size distribution (PSD), we achieved continuous control of the infrared emissivity of the surface by lower PRF, ranging from low (0.31) to high (0.93). Additionally, by using higher PRF, we attained dual-band emissivity control, featuring high emissivity in the range of 10-14 µm and near-continuous change in the range of 2.5-10 µm.

Structural and Parametric Synthesis of a Hybrid Repetitive Control System for Uncertain Multi-Mode Plant

Article deals with the problem of constructing a hybrid adaptive-robust repetitive control system for one class of a MIMO plants which operating with structural and parametric uncertainty and constant action of an external disturbances. A procedure for structural and parametric synthesis of a control system is proposed. At the structural synthesis stage with the help of hyperstability criterion the authors are developing a decentralized combined controller. After that using the method of continuous models the authors are built a continuous-discrete control system. The main feature of a control loop structure synthesis stage is to ensure the validity of V. M. Popov’s integral inequality. For this purpose, the authors determining the special estimates that guarantee positivity for nonlinear non-stationary part of the system under consideration. At the system’s parametric synthesis stage the authors are use the environment of engineering and technical calculations "Matlab — Simulink" to perform optimization modeling of the continuous and hybrid repetitive control systems. This action is carried out using one of the functional optimization methods — a genetic algorithm. Authors use the criterion of generalized operation for automatic control systems to form the functionality for assessing the quality of the proposed system. At the simulation stage initially for continuous repetitive system it was searched its controller parameters which ensure the minimum value of the specified functional. Then, with a given discretization step of the control loop elements, the hybrid periodic system was optimized in order to improve the quality of its operation.

Burden of major cancer types in Almaty, Kazakhstan

Globally, cancer is the second leading cause of death, with a growing burden also observed in Kazakhstan. This study evaluates the burden of common cancers in Almaty, Kazakhstan's major city, from 2017 to 2021, utilizing data from the Information System of the Ministry of Health. In Kazakhstan, most common cancers among men include lung, stomach, and prostate cancer, while breast, cervical, and colorectal cancers are predominant among women. Employing measures like disability-adjusted life years (DALYs), we found that selected cancer types accounted for a total DALY burden of 25,016.60 in 2021, with mortality contributing more than disability (95.2% vs. 4.7%) with the ratio of non-fatal to fatal outcomes being 1.4 times higher in women than in men. The share of non-fatal burden (YLD) proportion within DALYs increased for almost all selected cancer types, except stomach and cervical cancer over the observed period in Almaty. Despite the overall increase in cancer burden observed during the time period, a downward trend in specific cancers suggests the efficacy of implemented cancer control strategies. Comparison with global trends highlights the significance of targeted interventions. This analysis underscores the need for continuous comprehensive cancer control strategies in Almaty and Kazakhstan, including vaccination against human papillomavirus, stomach cancer screening programs, and increased cancer awareness initiatives.

Long-term cellular immunity of vaccines for Zaire Ebola Virus Diseases

Recent Ebola outbreaks underscore the importance of continuous prevention and disease control efforts. Authorized vaccines include Merck’s Ervebo (rVSV-ZEBOV) and Johnson & Johnson’s two-dose combination (Ad26.ZEBOV/MVA-BN-Filo). Here, in a five-year follow-up of the PREVAC randomized trial (NCT02876328), we report the results of the immunology ancillary study of the trial. The primary endpoint is to evaluate long-term memory T-cell responses induced by three vaccine regimens: Ad26–MVA, rVSV, and rVSV–booster. Polyfunctional EBOV-specific CD4+ T-cell responses increase after Ad26 priming and are further boosted by MVA, whereas minimal responses are observed in the rVSV groups, declining after one year. In-vitro expansion for eight days show sustained EBOV-specific T-cell responses for up to 60 months post-prime vaccination with both Ad26-MVA and rVSV, with no decline. Cytokine production analysis identify shared biomarkers between the Ad26-MVA and rVSV groups. In secondary endpoint, we observed an elevation of pro-inflammatory cytokines at Day 7 in the rVSV group. Finally, we establish a correlation between EBOV-specific T-cell responses and anti-EBOV IgG responses. Our findings can guide booster vaccination recommendations and help identify populations likely to benefit from revaccination.

Selective and sensitive molecularly imprinted polymer-based electrochemical sensor for detection of deltamethrin

Electrochemical sensors have a broad range of industrial applications due to their sensitivity, speed, and cost-effectiveness. These sensors enable the continuous monitoring and control of critical parameters in various industrial processes. For instance, they are essential in food safety, environmental monitoring, biomedical applications, and pharmaceutical production. In the food industry, electrochemical sensors facilitate the rapid and reliable detection of contaminants and pathogens in food products, thus enhancing product quality and consumer safety. An electrochemical sensor was developed with the molecularly imprinted polymer (MIP) technique to detect deltamethrin with high sensitivity and selectivity. The sensor was fabricated by electrodeposition of Co3O4 on indium tin oxide (ITO), followed by electropolymerization of o-phenylenediamine with deltamethrin as a template molecule. The template molecules were then removed from the modified electrode by a methanol. The MIP-based electrochemical sensor exhibited high sensitivity and selectivity towards deltamethrin. Under the optimized conditions, the LOD values for the MIP/Co3O4/ITO electrode in the first and second linear regressions were 1.53 nM for linear range of 2.82 nM to 56.5 nM and 0.34 μM for linear range of 0.25 μM to 3.98 μM. Moreover, the LOD values for the NIP/Co3O4/ITO electrode in the first and second regressions were 2.43 nM for the linear range of 3.91 nM to 65.0 nM and 726.0 nM for the linear range of 0.023 μM to 4.5 μM. The developed electrochromic pesticide sensor, being an electrochemical-based molecularly imprinted polymer (MIP) sensor incorporating electrochromic materials, enables both target-specific pesticide detection and visual pesticide identification based on color changes dependent on pesticide concentration. Consequently, this system is more advantageous compared to electrochemical-based MIP sensors, as it provides both qualitative and quantitative determinations. The qualitative assessment aims to enhance the ease of use of the sensor, thereby increasing the potential for it to become a commercially viable product by reducing the need for instrumental devices.

Optimal Joint Design on Continuous Trajectory and Power Control for UAV-Assisted Energy Constrained Communications

Optimal Joint Design on Continuous Trajectory and Power Control for UAV-Assisted Energy Constrained Communications

The Use of Bio-control Agents in Mulberry Pest Management: Successful Techniques and Important Issues

Since bio-control agents target specific pests without affecting the usefulness insects or/and damaging the soil and water resources, it plays a role in conservation of ecological balance in the environment. A variety of insect and non-insect pests, as well as hosts of parasites (fungi, insect, and mite parasites), occur in silkworm sericulture. This method does not in any way influence the sustainability of environment through pest control as required by sustainable agriculture. Since bio-control agents are known to be harmless to human beings and other organisms that may be of equal importance in the ecosystem such as pollinators, wildlife etc., they also have safety advantages. This is a big step forward to eradicating pests as compared to the chemical pesticides which have been known to affect the human lives and other wildlife. In the meantime, the bio-control agents may be cost effective in the long run. Because bio-control agents could offer continuous control of pests with minimal extra cost, it is possible, even when the outlay of obtaining and developing such organisms is more expensive than straightforward chemical applications. Further, the use of bio-control agents may reduce the reliance on traditional chemical pesticides and hence cost outlay and pest control costs and also reduce the probabilities of pesticide resistance. In the farming of mulberry, bio control agents are one the most important components of integrated pest management and have proved be an effective substitute to chemical control. Bio-control agents offer long-term pest suppression in comparison to chemical control methods, whose impacts tend to weaken after several generations of treatment. The continuous use of chemicals may result in pest resistance to the pesticides used. Spraying synthetic pesticides leads to the formation of pesticide residues on mulberry foliage, which affects food products and environmental health.

Actor-Critic With Synthesis Loss for Solving Approximation Biases.

Approximation biases of value functions are considered a key problem in reinforcement learning (RL). In particular, existing RL algorithms are hindered by overestimation and underestimation biases, i.e., value mismatching between RL's actual returns and action-value approximations limits the performance of RL algorithms. In this article, we first develop a new synthesis loss function for RL's action-value estimation integrating a regularization term and a modified "clipped double Q-learning" structure for solving overestimation and underestimation biases. To minimize the differences between action-value estimations and actual returns in RL, we develop a new discrepancy function to determine the type and magnitude of approximation biases. Then, two coefficients embedded in the synthesis loss are automatically tuned by minimizing the discrepancy function during training to minimize approximation biases. We further design a new actor-critic (AC) algorithm, named AC with synthesis loss (ACSL), by integrating the synthesis loss function and an error-controlled mechanism. Experimental results on continuous control tasks illustrate that the proposed ACSL algorithm outperforms other cutting-edge RL methods in many tasks and that the proposed synthesis loss function is easily implemented into other algorithms and significantly reduces approximation biases while improving performance. The proposed method can successfully handle many complex continuous control tasks and can greatly outperform other state-of-the-art algorithms on most tasks.

TAG: Teacher-Advice Mechanism With Gaussian Process for Reinforcement Learning.

Reinforcement learning (RL) still suffers from the problem of sample inefficiency and struggles with the exploration issue, particularly in situations with long-delayed rewards, sparse rewards, and deep local optimum. Recently, learning from demonstration (LfD) paradigm was proposed to tackle this problem. However, these methods usually require a large number of demonstrations. In this study, we present a sample efficient teacher-advice mechanism with Gaussian process (TAG) by leveraging a few expert demonstrations. In TAG, a teacher model is built to provide both an advice action and its associated confidence value. Then, a guided policy is formulated to guide the agent in the exploration phase via the defined criteria. Through the TAG mechanism, the agent is capable of exploring the environment more intentionally. Moreover, with the confidence value, the guided policy can guide the agent precisely. Also, due to the strong generalization ability of Gaussian process, the teacher model can utilize the demonstrations more effectively. Therefore, substantial improvement in performance and sample efficiency can be attained. Considerable experiments on sparse reward environments demonstrate that the TAG mechanism can help typical RL algorithms achieve significant performance gains. In addition, the TAG mechanism with soft actor-critic algorithm (TAG-SAC) attains the state-of-the-art performance over other LfD counterparts on several delayed reward and complicated continuous control environments.

Persistent low job control and subsequent major depression: A prospective cohort study of Australian working males

Workers' perception of control over work is a key construct in the relationship between the psychosocial work environment and health. While exposure to low job control has been prospectively linked to poor mental health including depression and anxiety, there is less research examining the impact of prolonged exposure to low job control on mental health. Data from 5054 employed men from 2013 to 2021 in the Australian Longitudinal Study on Male Health was used to examine persistent and intermittent low job control and subsequent major depression symptoms. Persistent low job control was based on consecutive self-reports of low job control over waves 1 and 2. Combinations of low and high job control were classified as intermittent exposure and continuous high job control exposure over both waves was classified as persistent high job control. Major depression symptoms, derived from the Patient Health Questionnaire-9, was measured in wave 3. Generalised linear models and augmented inverse probability weighting were undertaken. There was a strong stepwise relationship between low job control and major depression. Compared to persistent high job control, intermittent low job control was associated with an increased risk of subsequent major depression symptoms by 32% (RR 1.32, 95% CI 0.82, 2.15); and persistent low job control by 103% (RR 2.03, 95% CI 1.21, 3.41). Compared to men exposed to persistent high job control, the average treatment effect for persistent low job control was 0.036 (95%CI 0.014, 0.058) and intermittent low job control 0.019 (95%CI 0.006, 0.032) equating to a risk ratio of 2.46 (95%CI 1.43, 3.50) and 1.79 (95% CI 1.14, 2.45) respectively. This study's findings have implications for public health and occupational policies, as they underscore the importance of reducing prolonged exposure to low job control to protect against the risk of major depression in the working population.

A Converse Lyapunov-Type Theorem for Control Systems with Regulated Cost

Given a nonlinear control system, a target set, a nonnegative integral cost, and a continuous function W, we say that the system is globally asymptotically controllable to the target withW-regulated cost, whenever, starting from any point z, among the strategies that achieve classical asymptotic controllability we can select one that also keeps the cost less than W(z). In this paper, assuming mild regularity hypotheses on the data, we prove that a necessary and sufficient condition for global asymptotic controllability with regulated cost is the existence of a special, continuous Control Lyapunov Function, called a Minimum Restraint Function. The main novelty is the necessity implication, obtained here for the first time. Nevertheless, the sufficiency condition extends previous results based on semiconcavity of the Minimum Restraint Function, while we require mere continuity.

Організаційно-економічний механізм управління ризиками підприємства в умовах цифровізації

The article examines the current challenges and risks faced by Ukrainian enterprises in the context of digitalization and external environmental uncertainty. The article aims to substantiate the organizational and economic mechanism for managing enterprise risks in the conditions of digitalization. This study highlights risks related to cybersecurity, technological changes, the impact of military actions, market competition, and more. The research justifies the need to create an effective risk management mechanism to ensure enterprises’ sustainable development and adaptation to the challenges of the modern economy and digitalization. An analysis of contemporary approaches to defining the concepts of “risk” and “risk management,” presented in domestic and foreign sources, has revealed the key elements of risk management mechanisms. It was found that the concept of “risk” is characterized by critical aspects such as probability, negative consequences in the form of losses, potential positive outcomes, and benefits. In contrast, risk management should be viewed as preventing unforeseen events in the company’s operations, ensuring continuous control, and mitigating consequences when they occur. It is substantiated that the risk management process is continuous and systematic and includes monitoring and assessing risks at all levels of enterprise activity. The study presents an organizational and economic mechanism for risk management in enterprises under digitalization conditions, which, unlike existing models, considers the digitalization of economic processes in the enterprise, covers critical components such as personnel, legal, informational and digital, analytical, organizational, financial, and investment support, and is multi-component, systematic, and governed by its principles. The mechanism’s practical value lies in the effective interaction of its elements, which allows enterprises to identify and minimize risks promptly, maintain stability, and promote sustainable development. The research revealed the importance of integrating digital tools into the risk management process, which enhances decision-making efficiency and minimizes negative consequences. Keywords: risk, risk management, organizational and economic mechanism of risk management, risk management, digitalization of the economy, cyber risks.

Research on Auxiliary Effect of Lorentz Force for On-orbit Servicing of Spacecraft

Background: On-orbit servicing of spacecraft is mainly aimed at repairing failed spacecraft, maintaining and upgrading normally operating spacecraft to extend their life in order to reduce the increase of space debris and maintain the space environment. Objective: In performing on-orbit servicing, the spacecraft typically requires continuous control force to hover for a long period of time in order to maintain a relatively stationary state towards the target. Methods: Considering the limited amount of fuel carried, the Lorentz force is introduced into onorbit servicing to assist spacecraft in hovering. In order to demonstrate the feasibility of using Lorentz force as spacecraft thrust, many related patents have been provided. Results: Firstly, the velocity of the spacecraft's orbital motion and the variation of the geomagnetic field were given, and the specific expression of the Lorentz force in the relative dynamics model of the spacecraft was deduced. When studying the auxiliary effect of Lorentz force, a critical angle was defined. The relation between the critical angle and the Lorentz force on the auxiliary effect of spacecraft hovering was analyzed through numerical examples. Conclusion: Furthermore, based on the influence of the charge-to-mass ratio on the critical angle, the variation law of the Lorentz force-assisted spacecraft hovering area with different charge-tomass ratios was derived.

Stochastic maximum principle for optimal continuous and impulse controls of infinite horizon delay system

This paper is concerned with a continuous and impulse hybrid stochastic optimal control problem for a delay system in infinite horizon. The unique solvability and related estimates of solutions for multidimensional infinite horizon advanced backward stochastic differential equations (ABSDEs, for short) are established. When the control domain is convex, a maximum principle as a necessary condition for optimal controls is obtained through the variational method and dual analysis. With the help of additional convexity, a verification theorem as a sufficient condition for optimal controls is also obtained.