Control Actions Research Articles

Spatiotemporal evolution of PM2.5 and its components and drivers in China, 2000-2023: effects of air pollution prevention and control actions in China.

This study evaluated the Air Pollution Prevention and Control Action Plan (APPCAP) in China using 2000-2023 data. The average annual PM2.5 concentration dropped from 46.11 ± 16.18µg/m3 to 31.75 ± 14.22µg/m3 (P < 0.05) after APPCAP, with components showing a similar decline. Temporal analysis via Mann-Kendall test indicated a decreasing trend (Z < 0, P < 0.05), seasonally peaking in winter and lowest in summer. Spatially, APPCAP reduced concentration distribution, with key regions improving but areas like Shandong and Henan still facing severe pollution. The main PM2.5 driver shifted from human (e.g., population density) to meteorological (e.g., temperature) factors post-APPCAP, and anthropogenic influence varied across regions. In summary, APPCAP has curbed PM2.5 pollution, yet SO42-, NO3-, and NH4+ remain relatively high, and the increasing human impact in central and southeastern China demands attention in future policies.

Integrating Multiple Control Actions in Advanced Microgrids: an Analogy to Well-Established Inverter Control

This paper proposes multiple control actions applied to centralized advanced microgrids (MGs). The well-established control actions feedback (FB), feedforward (FF), and disturbance decoupling (D) commonly used in current control of distributed energy resources (DERs) are herein extended to advanced MGs. Analytical expressions are derived to show the effect of each control action on the well-established DER current control and then on advanced MG control. Comprehensive comparisons between the feedback and all control action strategies are performed for both DER and MG controls. Simulation and experimental results show a dynamic response improvement in load disturbance rejection when all control actions are considered, as well as a reduction in steady-state error for the grid power flow control. By employing low-bandwidth communication between DERs and central controller, no hardware retrofit is required in comparison to what is needed in other state-of-the-art centralized MG controls.

The life cycle of Schistosoma mansoni and schistosomiasis disease: an educational approach

Schistosoma mansoni, a digenetic trematode, is the causative agent of intestinal schistosomiasis, an infectious parasitic disease that affects approximately 54 million people annually and has a high mortality rate. Disease control involves treatment with the anthelmintic praziquantel, environmental sanitation, access to treated water, and population management of Biomphalaria snails, the intermediate hosts of the parasite. Understanding the life cycle of S. mansoni is an educational challenge due to the complexity of its multiple biological and ecological stages, requiring knowledge in parasitology, molecular biology, ecology, and public health. This difficulty affects students in both basic and higher education. In this context, the creation of illustrative diagrams and educational videos of the parasite’s life cycle proves to be an effective approach. Visual representations facilitate the understanding of the life cycle stages and their relationship to the disease, promoting more accessible theoretical and practical learning. Furthermore, these materials strengthen schistosomiasis control actions, especially in endemic regions, and contribute to the training of public health professionals. This study, therefore, aims to present an illustrative diagram and an educational video that address the different stages of S. mansoni’s life cycle. For the illustrations and graphic element assemblies, digital software and platforms such as Inkscape, Microsoft PowerPoint, Canva, and the GNU Image Manipulation Program were used. It is concluded that the use of graphic design software to create high-quality visual materials contributes to improving education and knowledge dissemination.

Barrier function-based prescribed performance trajectory tracking control of wheelchair upper-limb exoskeleton robot under actuator fault and external disturbance: experimental verification

This paper presents an innovative control strategy for the trajectory tracking of wheelchair upper-limb exoskeleton robots, integrating sliding mode control with a barrier function-based prescribed performance approach to handle actuator faults and external disturbances. The dynamic model of the exoskeleton robot is first extended to account for these uncertainties. The control design is then divided into two phases. In the first phase, the sliding mode control technique is applied to ensure robust trajectory tracking by defining the tracking error between the robot's states and desired trajectories. A sliding surface is constructed based on this error, and to further enhance tracking performance, a prescribed performance control scheme is incorporated, which ensures fast error convergence and improves transient behavior. In the second phase, an advanced barrier function technique is introduced to mitigate the impact of actuator faults and disturbances, enhancing the overall robustness of the system. Stability and tracking accuracy are rigorously verified through Lyapunov theory, ensuring the system's resilience to uncertainties. The combined approach not only guarantees rapid error convergence but also prevents performance degradation due to excessive control action, maintaining system stability. Finally, the effectiveness of the proposed method is demonstrated through extensive simulations and hardware-in-loop experiments, highlighting its practical applicability for real-world exoskeleton systems.

Do You Control Your Unconscious Action Impulses?

A crucial aspect of self-control is the voluntary inhibition of impulsive actions. Stimuli can elicit impulses (or preparation) to act not only in the presence but also in the absence of perceptual awareness, but whether people control action impulses elicited by unconscious stimuli remains unclear. This study used a masked prime version of the Go/NoGo/Free task and combined mathematical modeling of behavioral data to investigate whether people control the unconscious action impulses. In the experiment, when the subliminal prime stimulus triggers the unconscious action impulse, participants need to freely decide whether or not to perform the action. The results showed that the no-response rate was higher in Go-prime free-choice trials than in NoGo-prime free-choice trials, and there were marginally larger negative drift rates in the former than in the latter. The results suggest that people are more likely to make inhibitory decisions about unconscious action impulses. This finding provides support for a framework that extends the feedback loop model of intentional inhibition.

Avian pathogenic Escherichia coli and ostriches: a deep dive into pathological and microbiological investigation.

A comprehensive research was conducted to investigate the incidence of avian pathogenic Escherichia coli (APEC) in ostrich farms in Egypt. The study involved seven farms with bird ages ranging from 1 to 12 weeks and capacities of 2,000 to 5,000 birds per farm. 175 tissue specimens were collected from different organs (liver, spleen, heart, lung, kidney, intestine, and meat). Clinical signs of APEC infection included diarrhea, lethargy, depression, and weight loss, with a morbidity rate of 36% and a mortality rate of 7.6%. In the current study, 52.5% of the samples have E coli. The highest prevalence was observed in the liver (10.8%), followed by the spleen and intestine (8% and 9.1%, respectively). The most common serotype identified was O27 (28%), after that O78 (20%) and O44 (12%). Histopathological examination revealed severe lesions in various organs, including the liver, kidney, heart, and intestine. The study concluded the presence of APEC in different organs of ostrich in Egypt especially the liver, spleen, intestine, and breast muscle (meat) with evidence of severe pathological lesions in various organs. The study highlights the significance of APEC as a main cause of morbidity and mortality in ostriches. It underscores the necessity for actual control measures to avoid spreading the disease.

Ideational Shifts and Recurring Complications: A Diplomatic History of Territorial Claims Between India and China in Ladakh

ABSTRACT The concept of territoriality and sovereignty form an important constituent of the modern nation-state. With the establishment of the People's Republic of China (PRC) in 1949, China applied the principle of irredentism to claim territories drawing on evidence it deems as having historicity. This study focuses on the Western Sector of the India–China boundary, specifically Aksai Chin and the vicinity of areas in present-day Ladakh. An examination of some of the key diplomatic communications, cartographic and archival evidence, and other secondary sources on this dispute reveals inconsistencies in claims pertaining to the Line of Actual Control as put forward by both countries. Such a line, as claimed by both sides, was never an unchanging line, as recorded through evidence rooted in cartography, mapping and reports by the British surveyors from the mid-nineteenth to the twentieth century as well as the post-colonial leadership of the two countries – all of which capture the ideational shifts which resulted in the boundary dispute that has only grown over time.

Health promotion and tobacco control: a transatlantic perspective between Brazil and Portugal

Health promotion, a concept based on the Ottawa Charter, recognizes that health is influenced by economic, social and environmental factors, as well as individual practices. The fight against smoking is one of the most challenging fronts in this context, given its direct relationship with the global burden of chronic diseases and preventable deaths. The articulation of public policies that involve multiple sectors and civil society has proved fundamental in dealing with this problem. In both Brazil and Portugal, health promotion plays a crucial role in integrating tobacco prevention and control actions, reflecting the guidelines of Canada's Population Health Promotion Model. This Canadian model highlights the intersection between health, public policies and community action, emphasizing the need for healthy environments and structural interventions that shape behaviour. The influence of this paradigm is evident in global policies, including those adopted in Brazil and Portugal. It offers a theoretical framework that guides governments to create evidence-based strategies that are sensitive to cultural and social particularities. In Brazil, the National Health Promotion Policy (Política Nacional de Promoção da Saúde, PNPS) translates these principles into concrete actions, whereas in Portugal, the National Program for the Prevention and Control of Smoking reflects a progressive normative approach, especially in relation to tobacco consumption and electronic devices. Brazil and Portugal have different histories and cultural dynamics, but they share similar challenges in tackling smoking. In Brazil, robust policies have contributed to a significant reduction in the prevalence of adult smokers, from 34.8% in 1989 to 12.6% in 2019(1). These achievements are the result of educational campaigns, tax increases and the creation of smoke-free environments. In Portugal, legislative efforts, such as the Tobacco Law (Law No. 37/2007), have significantly limited smoking in public places and restricted advertising, but the country still faces worrying rates, with 17% of the population identified as smokers in 2019(2). [...]

Spatiotemporal analysis of visceral leishmaniasis in Belo Horizonte, Brazil: a historical perspective (1994-2018).

In the Americas, visceral leishmaniasis (VL) results from the zoonotic transmission of Leishmania infantum. VL has a high occurrence rate in the Metropolitan Region of Belo Horizonte (BH), Minas Gerais, Brazil, and has rapidly spread throughout the municipality since it was first recorded in 1994. This research analysed a historical perspective over 25y of human VL occurrence in BH. An ecological study of reported human VL occurrence from January 1994 to December 2018 in BH was performed. Epidemiological indicators and changes in the spatiotemporal transmission patterns of human VL were analysed throughout the study period. The average annual incidence of human VL was 3.20 cases per 100000 inhabitants over the study period. The case fatality rate ranged from 7% to 21%. The proportion of VL/human immunodeficiency virus coinfection was >20% in the years 2012, 2015 and 2018. Human VL was introduced into BH through the East and Northeast regions, expanding to other areas. The coverage areas of the São Miguel Arcanjo and Cafezal health centres (both in the Centro-Sul region of the city) as well as other areas in the Northeast, Northwest, Pampulha, Venda Nova, North, and East regions of the city presented higher relative risks for human VL occurrence. The study contributes to a better understanding of the disease's epidemiological profile and identifies priority areas for developing control and monitoring actions.

Огляд поширення інвазійних видів рослин на території Українських Карпат

The uncontrolled spread of invasive plants poses a threat to biodiversity by displacing native flora and disrupting established ecotopes. The primary factors contributing to their spread include human activity, the absence of natural enemies and competitors, and the ability to overcome limiting factors. We have analyzed and summarized information related to the spread of invasive plant species in the territory of the Ukrainian Carpathians, the border of which is formed in the northeast along a line connecting the cities of Sudova Vyshnya, Komarne, Mykolaiv, Zhydachiv, Ivano-Frankivsk, Kolomyia, and Chernivtsi, and extends to the west along the state border. As a unique ecoregion, the Carpathians perform ecological functions such as regulating water balance, preventing erosion, and preserving soil resources. Additionally, the Carpathian region is an important tourist and cultural center, and the spread of invasive plants negatively affects the attractiveness of these areas for tourists, as well as traditional forms of economic activity such as forestry and agriculture. The analysis highlighted key research directions related to the issue of invasive flora spread in the Carpathian region, namely: creating lists of invasive plants for specific regions, researching the origin and modes of spread of invasive species, developing methods for control or preventive actions to prevent further spread, and forecasting the future expansion of adventive species. The most dominant families in terms of the number of invasive species in the Ukrainian Carpathians are Asteraceae, the number of species of which is from 18 % to 30 %, Brassicaceae – 8–12 %, and Poaceae – 8–10 %. According to the time of introduction, the ratio of archaeophytes and chenophytes is about 1:2.5 in all regions, except for the analyzed regions of the Ivano-Frankivsk region, where the ratio was either reversed or 1:1. The predominant localities of origin are Mediterranean, North American and Irano-Turanian.

Temporal-spatial evolution and formation mechanism of energy consumption carbon footprint at county scale in the Yellow River Basin

The development and implementation of county carbon control action plans in the Yellow River Basin (YRB) are crucial for realizing the “dual carbon” goals and modernizing national governance. Utilizing remote sensing data from 2001 to 2020, this study constructs a light-carbon conversion model and a carbon footprint model to simulate the carbon footprint of county energy consumption in the YRB. Employing spatial autocorrelation and spatial Durbin models, the study examines the temporal-spatial evolution characteristics and spatial effect mechanism. The results show that: (1) The county carbon footprint increased year by year. The distribution of the high carbon footprint is consistent with that of energy-intensive areas. The carbon cycle system is significantly unbalanced, and the counties with carbon deficit spread inland. (2) The carbon footprint exhibits significant spatial dependence, and the high carbon spillover effect is significant. Regional joint prevention and control strategy is essential to control the carbon footprint. Otherwise, the inter-regional carbon leakage effect may occur. (3) The current stage of economic development and industrial structure upgrading is not conducive to low-carbon development. Because of the energy rebound effect, technology development has not played the expected emission reduction effect. Nevertheless, the technology level and residents’ living standard are critical factors in reducing the carbon footprint. Government intervention, urbanization, human capital, and agricultural energy inputs increase the carbon footprint.

Driving Trajectories of Multistable Systems to Desirable Modes with Parametric Excitations

In this work, switching of vibrations between different modes of a class of multistable systems with parametric excitations is studied. An intermittent control method without altering the underlying dynamics of the system or its coexisting attractors is proposed. When an orbit meets a proximity constraint with the desired orbit, the control action is applied intermittently in the time domain. This control input is operated by perturbing one of the attractors with an impulsive force, thereby switching the system response to the other attractor. The stability of the method is analyzed theoretically, and its effectiveness is verified by numerical results. Additionally, the influences of neighborhood boundary on the amplitude and duration of control inputs in unconstrained and constrained intermittent control methods are also analyzed.

Heterogeneous zonal impacts of climate change on a wide hyperendemic area of human and animal fascioliasis assessed within a One Health action for prevention and control.

The Northern Bolivian Altiplano is the fascioliasis endemic area where the highest prevalences and intensities in humans have been recorded. In this hyperendemic area of human fascioliasis, the disease is caused only by Fasciola hepatica and transmitted by Galba truncatula, the sole lymnaeid species present in the area. When analysing the link between global warning and the recently reported geographical spread of lymnaeid populations to out-border localities, a marked heterogeneous climatic change was found throughout the endemic area. The aim of the present study was to analyse the physiographical heterogeneity of the fascioliasis hyperendemic area in the Northern Bolivian Altiplano, in order to assess its repercussions in the implementation of a One Health action. We applied multivariate linear mixed models to analyse the influence of a number of physiographical features on the long-term variation of climate and of the risk of transmission. Despite its apparent physiographic homogeneity, the findings of this study revealed markedly heterogeneous climate characteristics throughout the endemic area. This irregular pattern is influenced by physiographical features such as altitude, inner hills, closeness to Lake Titicaca, and El Niño-Southern Oscillation. This is the broadest study ever performed in a human fascioliasis endemic area about the influence of physiography on climate. It highlights the importance of considering physiographical features, an aspect usually not considered in studies dealing with the influences of climate and climate change on human and animal fascioliasis. Moreover, it shows that an endemic area may climatically evolve differently in its various inner zones and emphasizes the need for continuous monitoring to assess whether control measures should be modified accordingly.

Adaptive Generator Tripping Scheme based on Deep Learning as Real Time Control Action for Transient Stability

Transient stability has typically received attention in the literature, focusing on its assessment and control under limited operational scenarios and contingencies. This often results in persistent transient stability issues, leaving the system vulnerable to imminent collapses. In this regard, this work aims to develop an adaptable tripping scheme based on the power system dynamics following a major disturbance to prevent grid blackouts due to transient stability loss. The proposed methodology takes advantage of data analysis tools based on deep learning and Phasor Measurement Units (PMUs) technologies. In this approach, the methodology involves generating a database of both operational scenarios and n-1 contingencies, labeling critical generators to be tripped to mitigate transient instability, and training a hybrid deep neural network RCNN (recurrent convolutional neural network) that constitutes the core of the tripping scheme. Following the application of the methodology in a controlled simulation environment, the RCNN model demonstrated strong performance, as it not only mitigated transient instability through minimal tripping of generation plants with an effectiveness of 92.4% but also showed potential for real-time application, as the control action accounts for latencies inherent in real-time operation.

Utilizing Raspberry-Pi 3 to Implement Fuzzy Logic Controller Optimized by Genetic Algorithm

The development of Fuzzy Logic Controllers (FLC) with low error rates and cost effectiveness has been the subject of numerous studies. This paper study goals to the investigation and then implementation an FLC using the readily accessible and reasonably priced Raspberry Pi technology. The FLC used in this work has two inputs, one output, and five Membership Functions (MFs) for each input and output. The FLC goes through two processes, tweaking the MF parameters and tuning input/ output Scaling Factors. The tuning technique makes use of the Genetic Algorithm (GA). The whole set of the FLC probabilities is taken into account as the tuned FLC controller, and then transformed into a lookup table. The Center of Gravity (COG) approach is used to determine the output for the tuned FLC controller. The resulting table is converted into values of digital binary using a specific type of encoder, and then extraction of the set of Boolean functions to apply this tuned circuit. Finally, the Python 3 programming language is used to define the resultant Boolean functions on the Raspberry Pi platform, and then a decoder extracted the appropriate control action from the output. The Benefit of this method is the use of a digital numbering system to define the FLC, which is implemented on Raspberry Pi technology and allows for fuzzified high processing speed output per second. The controller speed has not been unaffected by the quantity for these fuzzy rules.

Hierarchical production control and distribution planning under retail uncertainty with reinforcement learning

Effective coordination between production control and distribution planning is critical in supply chain management. However, existing research mainly focuses on responding to stochastic demand, while the impact of uncertain retail capabilities is often overlooked. This study proposes a hierarchical framework that integrates and coordinates production control and distribution planning while explicitly addressing the uncertainty of retail capabilities. Specifically, we develop a reinforcement learning (RL) algorithm that learns stochastic retail capabilities under adaptive production control (upper level) and distribution planning (lower level). This retail information is then fed into the hierarchical control framework, which enhances the performance of both control layers to maximise system profit while considering opportunity costs and holding costs. Moreover, we incorporate a novel holding function based on the exponential penalty term into the reward function to effectively enforce the side constraint of inventory capacity. This approach enables the RL algorithm to derive feasible production policies and thereby enhance the training process. We evaluate the proposed hierarchical controller through a case study utilising real-world transaction data from the steel manufacturing industry. The results demonstrate that the accurate identification of retail capabilities can facilitate inventory management under stochastic market conditions. Furthermore, the hierarchical framework can improve overall profits by coordinating production control actions under different retail strategies.

Finite-Time Path-Following Control of Underactuated AUVs with Actuator Limits Using Disturbance Observer-Based Backstepping Control

This paper presents a three-dimensional (3D) robust adaptive finite-time path-following controller for underactuated Autonomous Underwater Vehicles (AUVs), addressing model uncertainties, external disturbances, and actuator magnitude and rate saturations. A path-following error system is built in a path frame using the virtual guidance method. The proposed cascaded closed-loop control scheme can be described in two separate steps: (1) A kinematic law based on a finite-time backstepping control (FTBSC) is introduced to transform the 3D path-following position errors into the command velocities; (2) The actual control inputs are designed in the dynamic controller using an adaptive fixed-time disturbance observer (AFTDO)-based FTBSC to stabilize the velocity tracking errors. Moreover, the adverse effects of magnitude and rate saturations are reduced by an auxiliary compensation system. A Lyapunov-based stability analysis proves that the path-following errors converge to an arbitrarily small region around zero within a finite time. Comparative simulations illustrate the effectiveness and robustness of the proposed controller.

A Multivariate Machine Learning Approach for the Prediction of Wind Turbine Blade Structural Dynamics

Wind turbine blade structural dynamics are crucial in the turbine structural design phase. Blade deflections and loads can affect the weight of the rotor as well as the power performance of a wind turbine if the deflections are extremely high. Predictions of the turbine’s blade deflections and loads can lead to informative decisions on optimizing the design of the blade. In this work, a multivariate machine learning (ML) approach is used to predict the blade’s dynamics based on the wind flow conditions and control actions of the turbine. Three different datasets were generated using the OpenFAST software tool for three different wind turbulence classes. Various ML algorithms were trained to predict the blade deflections at the tip and blade loads at the root in the edgewise and flapwise directions. The ML models were tested for generalization of the model to different flow conditions. A model is trained for one dataset with one of the turbulence classes and then used to predict the outputs of the other two datasets. The random forest ML algorithm gave the best accuracy for predicting the outputs for the dataset it was trained for, as well as the other two datasets. The accuracy of predictions was found to be higher in the edgewise direction for both load and deflection outputs. In the flapwise direction, the model could predict the outputs of the data it was trained for with an accuracy of around 99% and for the other two datasets with an accuracy of over 75%. While in the edgewise direction, the model trained on only one dataset gave a prediction accuracy above 95% for all three datasets.

Near-Field Aeroacoustics of Spanwise Forcing on a Transonic Wing: A DNS Study

The transonic airflow around a supercritical wing with a shock wave is described via direct numerical simulations. Flow control for turbulent drag reduction is applied via streamwise traveling waves of spanwise velocity applied on a finite portion of the suction side. The near-field modifications caused by the forcing are studied via the analysis of the wake profile downstream of the trailing edge. Moreover, for the first time, the effects of spanwise forcing on aeroacoustic noise are considered to establish whether active flow control for drag reduction could possibly increase noise. By extracting the acoustic signals on a circumference placed in the near-field around the wing and by studying them in terms of sound intensity and frequency content, it is found that noise intensity is not significantly increased by spanwise forcing and that frequency content is only minimally altered. Furthermore, if the angle of attack is reduced to take into account the increased lift and the reduced drag made possible by the control action, changes in the noise characteristics become negligible.

Electromagnetically induced transparency and second-order sideband Effects in a Laguerre-Gaussian cavity optorotational system with Kerr medium

Abstract In this paper, we investigate the phenomena of electromagnetically induced transparency (EIT) and the generation of second-order sideband in a Laguerre-Gaussian (LG) cavity optorotational sys tem with a Kerr nonlinear medium. Using the perturbation method, we analyze the first- and second order sideband generations in the output field from the system under the actions of a strong control&amp;#xD;field and a weak probe field. Numerical simulations show that the Kerr nonlinearity can lead to the occurrence of the asymmetric line shape in the transmission of the probe field and the efficiency of second-order sideband generation, and the Kerr nonlinearity can enhance the efficiency of the second order sideband generation. Comparing with traditional scheme for generating the second-order sideband, our spectral shape of the second-order sideband is amplified and becomes asymmetric, which has potential applications in precision measurement, high-sensitivity devices, and frequency conversion.