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The resulting fibre orientation when pressing Sheet Moulding Compound (SMC) is essentially dependent on the position and geometry of the resin mat in the mould. It is desirable to adapt the fibre orientation as best as possible to best withstand the applied load. The relationship between the position and geometry of the resin mat and the deflection of the final part under a specific load can be mapped using a numerical simulation; nevertheless, an optimisation is not feasible based on the simulation in an economically reasonable time frame due to the required computing time. For this reason, a metamodel based on an ensemble of artificial neural networks (ANN) was created on the basis of the simulation data, and an optimisation based on these ANN was set up. However, the investigations show that the minimal deflections found on the basis of the metamodel through optimisation have large deviations compared to the simulation. This leads to the hypothesis that the applied optimisation finds weak points of the metamodel instead of actual minima. From this hypothesis, an extension approach of the data set on which the metamodel is based by the weak points found is derived and implemented. This is done in an iterative process. The results show that the goal of increasing the prediction quality of the optimisation approach is achieved by the developed approach. The root mean square error (RMSE) could be reduced from the original deflection of 25 to 7 mm, which corresponds to a reduction of 72%. It is shown that the presented approach is successful in increasing prediction quality; nevertheless, further measures are needed to reach decent prediction quality. [ABSTRACT FROM AUTHOR]

Seasonal Malaria Chemoprevention consisting of monthly administration of amodiaquine/sulfadoxine-pyrimethamine to children aged 3–59 months during the transmission season could promote SP-resistance. Mutations in dihydrofolate reductase (Pfdhfr) and dihydropteroate synthase (Pfdhps) genes were assessed before and after SMC adoption in Burkina Faso. A total of 769 dried blood spots were selected from studies conducted in Nanoro, Burkina Faso, between 2010 and 2020. Of those, 299 were pre-SMC (2010–2012) and 470 were post-SMC-samples. Pfdhps and Pfdhfr genes were PCR-amplified and sequenced. A systematic review/meta-analysis of published studies conducted in Burkina Faso (2009–2023) was additionally performed. In Nanoro, the prevalence of Pfdhfr triple mutations (CIRNI) rose from 43.6% pre-SMC to 89.4% post-SMC (p < 0.0001). There was no mutation in Pfdhfr 164 and Pfdhps 540; Pfdhps A437G mutation increased from 63.9% (2010–2012) to 84.7% (2020) (p < 0.0001). The VAGKGS haplotype was 2.8% (2020). Pfdhfr/Pfdhps quintuple mutant IRN-436A437G rose from 18.6% (2010–2012) to 58.3% (2020) (p < 0.0001). Meta-analysis results from Burkina Faso showed an increase in mutations at Pfdhfr N51I, C59R, S108N, and Pfdhps A437G after SMC adoption. Post-SMC, the pyrimethamine-resistance marker prevalence increased, while the sulfadoxine-resistance marker prevalence remained stable. Detection of emerging PfdhpsVAGKGS haplotypes in 2020 underscores the importance of continuous SP-resistance monitoring. [ABSTRACT FROM AUTHOR]

The aim of the present article is to design a robust fractional-order (FO) finite-time (FnT) control able to tackle Hölder disturbances of second-order nonlinear systems. First, a novel sliding manifold with Arc-Tangent function is suggested for second nonlinear systems. It has been proven that the system states globally converge to the origin in FnT using the proposed sliding mode variable. To ensure a FnT stability of the sliding variable, a robust control is developed. By using fractional operators, a uniformly continuous control law is designed to tackle Hölder disturbances. Furthermore, the suggested approach is shown to be resistant to matched Hölder disturbances and uncertainties that are continuous but not necessarily differentiable. Moreover, the FnT stability of quadrotors using the proposed control, that is our second result. The quadrotor simulations analysis demonstrates the practicality of the proposed FnT controller in the presence of Hölder disturbances. • A simple nonlinear manifold design is proposed to ensure a finite-time convergence of quadrotors unlike the existing nonlinear sliding variables (Mousavi et al., 2021). • Hölder disturbances are addressed using fractional switching control law in the design of the proposed control scheme. • Compared to existing rejection disturbances (Ju et al., 2022; Labbadi and Cherkaoui, 2020; Razzaghian, 2022; Mousavi et al., 2021), the proposed FOFTC scheme has a faster convergence speed. [ABSTRACT FROM AUTHOR]

DC–DC buck converters have been designed by incorporating different control stages to drive the switches. Among the most commonly used controllers, the sliding mode control (SMC) and proportional-integral-derivative (PID) controller have shown advantages in accomplishing fast slew rate, reducing settling time and mitigating overshoot. The proposed work introduces the implementation of both SMC and PID controllers by using the field-programmable gate array (FPGA) device. The FPGA is chosen to exploit its main advantage for fast verification and prototyping of the controllers. In this manner, a DC–DC buck converter is emulated on an FPGA by applying an explicit multi-step numerical method. The SMC controller is synthesized into the FPGA by using a signum function, and the PID is synthesized by applying the difference quotient method to approximate the derivative action, and the second-order Adams–Bashforth method to approximate the integral action. The FPGA synthesis of the converter and controllers is performed by designing digital blocks using computer arithmetic of 32 and 64 bits, in fixed-point format. The experimental results are shown on an oscilloscope by using a digital-to-analog converter to observe the voltage regulation generated by the SMC and PID controllers on the DC–DC buck converter. [ABSTRACT FROM AUTHOR]

This paper presents an innovative control strategy for robot arm manipulators, utilizing an adaptive sliding mode control with stochastic gradient descent (ASMCSGD). The ASMCSGD controller significant improvements in robustness, chattering elimination, and fast, precise trajectory tracking. Its performance is systematically compared with super twisting algorithm (STA) and conventional sliding mode control (SMC) controllers, all optimized using the grey wolf optimizer (GWO). Simulation results show that the ASMCSGD controller achieves root mean squared errors (RMSE) of 0.12758 for θ 1 and 0.13387 for θ 2 . In comparison, the STA controller yields RMSE values of 0.1953 for θ 1 and 0.1953 for θ 2 , while the SMC controller results in RMSE values of 0.24505 for θ 1 and 0.29112 for θ 2 . Additionally, the ASMCSGD simplifies implementation, eliminates unwanted oscillations, and achieves superior tracking performance. These findings underscore the ASMCSGD's effectiveness in enhancing trajectory tracking and reducing chattering, making it a promising approach for robust control in practical applications of robot arm manipulators. [ABSTRACT FROM AUTHOR]

In the DC microgrid system, the bidirectional DC/DC converter is one of the most important components; thus, research on its control strategy has attracted widespread attention. Firstly, the single bidirectional DC/DC converter based on a sliding mode (variable structure) control (SMC) strategy exhibits an inherent contradiction between the reaching time and the chattering phenomenon. In order to address this problem, an SMC strategy based on the improved exponential reaching law was designed. This control strategy modifies the constant-speed reaching term and introduces the system state variable to indicate the chattering level, which not only improves the dynamic performance of the bidirectional DC/DC converter but also suppresses the chattering problem. Secondly, the bidirectional DC/DC converter group based on the traditional droop control strategy exhibits an inherent contradiction between load power allocation and bus voltage stabilization. In order to address this problem, an improved droop control strategy that takes the line impedance characteristics into account is proposed. This control strategy modifies the traditional droop control strategy by introducing virtual resistance and uses DC bus voltage information to replace the line impedance value. This ensures the accuracy of power allocation and stability of the DC bus voltage simultaneously. Finally, the stability of each designed strategy is verified individually. The combination of the two control strategies is applied to a group of bidirectional DC/DC converters group to conduct a semi-physical simulation experiment, and the results verify that the proposed control strategies are effective and feasible. [ABSTRACT FROM AUTHOR]

In this paper, a finite time control strategy is investigated to realize motion control for a multi-DOF pneumatic manipulator (MDPM) with vertical downward equilibrium state. Angle deflection is existed for the MDPM at work when gravity compensation has to take into account. To estimate the disturbances on gravity from angle deflection, a nonlinear extended state observer (ESO) is designed for the MDPM. Backstepping super-twisting terminal integral sliding mode control (SMC) is proposed to improve control accuracy and convergence speed. Finite time convergence is shown for the nonlinear ESO and the backstepping super-twisting terminal integral SMC under angle deflection gravity compensation. Experiment results are given to show effectiveness of the finite time control strategy for the MDPM. [ABSTRACT FROM AUTHOR]

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This study reviews numerous control approaches utilized to address various issues encountered by unmanned aerial vehicles (UAVs). Specifically, focusing on the quadrotor system. Due to its versatility and compact size, quadrotors have gained popularity as UAVs in recent decades. Quadrotors face challenges such as ambient disturbances, impediments, non-parametric and parametric perturbations while performing tasks. Consequently, a robust and efficient control system is essential for such a system to ensure the stability and enhance their performance. It should be noted that, in this review, we have examined and analyzed the most recent highly cited papers selected from esteemed journals and magazines renowned for their exceptional quality and reputation.

Abstract Seasonal Malaria Chemoprevention consisting of monthly administration of amodiaquine/sulfadoxine-pyrimethamine to children aged 3–59 months during the transmission season could promote SP-resistance. Mutations in dihydrofolate reductase (Pfdhfr) and dihydropteroate synthase (Pfdhps) genes were assessed before and after SMC adoption in Burkina Faso. A total of 769 dried blood spots were selected from studies conducted in Nanoro, Burkina Faso, between 2010 and 2020. Of those, 299 were pre-SMC (2010–2012) and 470 were post-SMC-samples. Pfdhps and Pfdhfr genes were PCR-amplified and sequenced. A systematic review/meta-analysis of published studies conducted in Burkina Faso (2009–2023) was additionally performed. In Nanoro, the prevalence of Pfdhfr triple mutations (CIRNI) rose from 43.6% pre-SMC to 89.4% post-SMC (p

In this article is used to demonstrate of sliding mode controller (SMC) for a multilevel inverter based distributed static compensator (DSTATCOM)for compensation of current harmonics related power quality issues and dc side capacitor voltage balancing of cascaded H-bridge multilevel inverter (CHBMLI). The nonlinear sliding mode controller is developed for the dc link voltage and current control of CHBMLI based DSTATCOM using feedback linearization method. The use of SMC algorithm for DSTATCOMDC link voltage regulating offers several benefits such as decrease in switching ripple in dc side voltage and the constant DC capacitor voltage during dynamic conditions. The algorithm of SMC is realized on a DSTATCOM based on cascaded H-bridge multilevel inverter feeding three phase loads. The presentation of characteristics of DSTATCOM with the proposed dc link voltage balancing strategy is establish adequate for voltage balancing and elimination of power quality problems like harmonics current. Further, performance of SMC with improved voltage balancing algorithm is compared with PI controller using improved voltage balancing scheme of the DSTATCOM. The performance characteristics are validated with real-time study and SMC with improved voltage balancing scheme exhibits improved transient and steady state response of the DSTATCOM.

This article presents a discrete‐time robust model reference adaptive controller and adaptive sigmoid super‐twisting sliding mode (RMRAC‐ASSTSM) and its stability analysis using Lyapunov stability theory. This control structure is robust to matched and unmatched dynamics. In addition, the chattering phenomenon tends to be suppressed in the steady state due to adaptive super‐twisting sliding mode action using a sigmoid function. The performance of the proposed control structure is corroborated with simulation results, considering a second‐order non‐minimum phase unstable plant, where it can be seen that RMRAC‐ASSTSM regulation errors converge to a finite residual set when the plant presents unmodeled dynamics. A comparison is also presented with a similar RMRAC‐based control structure with an adaptive super‐twisting sliding mode implemented with a sign function. [ABSTRACT FROM AUTHOR]

In recent years, various solutions have been developed to control power electronic converters using devices available on the market that are powerful and easy to use. These solutions, in most cases, offer high performance. However, these have high implementation costs because the required devices are expensive. For this reason, this document presents the implementation of two discrete-time controllers widely used in the literature for a boost converter implemented on a low-cost platform. The objective is to obtain a constant voltage at the converter's output for photovoltaic system applications. The proportional-integral control is implemented as the first case, and the second case is a sliding mode control. In addition, a prior analysis is presented through simulation. Both control algorithms are implemented on the TMS320F28379D microcontroller from Texas Instruments through the same manufacturer's integrated development software based on an optimized C/C++ language compiler. The results of the non-linear algorithm reveal better performance in reducing the time response, the overshoot of the transient state, and the steady-state error. Finally, the significant economic savings associated with the implementation costs of the controllers tested on a low-cost platform differentiate this work from other similar ones. [ABSTRACT FROM AUTHOR]

The purpose of this article is to control the formation of heterogeneous flying robots and to cross obstacles. The robots in question are a quadrotor and two unmanned helicopters. Independent attitude and position of robots and formation flight are controlled by the sliding mode method. Improved Artificial Potential Fields has been used to avoid collision with dynamic and static obstacles. The results of the design of the attitude and position controller showed that the attitude and position of the robots were well stabilized and converged in less than 3 s, which is a favorable time. The results of the formation flight simulation were presented in the form of 4 missions. In the first mission, the quadrotor is considered the leader, and the helicopters are the followers. The flight formation is triangular and the flight path is spiral. The results showed that the followers follow the leader. In the second mission, the robot crosses dynamic and static obstacles and the leader tracks the fixed target. In the third mission, the number of followers increases to 5 and the flight formation is hexagonal. The obstacles in this mission are dynamic and the target is moving. The results showed that in these two missions, the leader tracks the target well and the robots maintain triangular and hexagonal flight formations after crossing the obstacles. The results of simulations of group crossing of obstacles showed that the simulation error is less than 4% according to the expected position of the robots, and show the efficiency of the applied methods. [ABSTRACT FROM AUTHOR]

This study presents the design of a controller for a two-degree-of-freedom (2-DOF) helicopter based on sequential invariant manifolds with exponential convergence. The system is decomposed into two subsystems for pitch and yaw angles, and exponentially stable manifolds are constructed for each subsystem. The control law is found based on sequential manifolds and the Analytical Design of Aggregated Regulators (ADAR) method. The controller is designed to increase the system's stability against disturbances while ensuring stability over a finite period of time. The response time of the system can be evaluated in advance through the parameters of the designed manifold. The robustness of the control law for external disturbances was proven using the Lyapunov function in the design process. Finally, the effectiveness of the proposed controller based on the synergetic control theory is demonstrated by numerical simulation results and a comparison with the backstepping controller. [ABSTRACT FROM AUTHOR]

Summary: This paper proposes a novel speed‐current single‐loop speed regulation controller for permanent magnet synchronous motor (PMSM) based on model‐assisted cascaded extended state observer (ESO) and sliding mode control (SMC), aimed at simplifying the control structure, increasing dynamic performance, and improving antidisturbance performance. Firstly, a cascaded ESO based on model information is designed for the second‐order model of single‐loop control of PMSM. This approach allows for quick and accurate estimation of disturbance without increasing bandwidth, while also reducing the burden of ESO with model‐assisted information. Next, with the estimation disturbance feedforward compensation, the composite controller is constructed based on SMC, which effectively eliminates residual disturbance and reduces chatterings. The stability of the closed‐loop system under the proposed controller is proved strictly. Finally, simulations and experiments are conducted to validate the effectiveness and robustness of the proposed method. [ABSTRACT FROM AUTHOR]

Mushroom cultivation is an important branch of the agricultural industry, and global mushrooms production has increased more than sixfold in the last decade. This industry uses large amounts of agricultural, forestry, livestock, and industrial wastes and their by-products. However, it also generates millions of tons of spent mushroom compost (SMC) (approximately 100 million tons per year) which has emerged as a significant issue that hinders the growth of the mushroom business and impacts the environment. Many crop diseases, which cause significant economic losses, are introduced by soil-borne plant pathogens. Spreading spent mushroom compost (SMC) to agricultural soils is a natural way to control plant diseases. Using organic waste material instead of chemicals, which is the most widely used method in agriculture today, is also a more environmentally responsible option. The generated SMC can potentially be used as a soil conditioner, an organic fertilizer, and suitable medium for growing various vegetable crops. The application of SMC has been found to be beneficial in the control of crop diseases by inducing microbiostasis, direct toxicity, or by inducing systemic resistance of the host plant. In the current review, the practical application of SMC in the cultivation of tomato, pepper, lettuce, cucumber, and eggplant was addressed. The application of SMC as a soil amendment showed a significant improvement in soil properties, including soil NPK, organic matter content, and soil beneficial microorganisms. Our review indicated that SMC could be used as a low-cost, alternative growing medium in vegetable production or as a soil amendment to add nutrients and restore soil fertility in agricultural lands. The SMC may be able to replace peat, a non-renewable natural resource, and thereby mitigating the adverse effects of excessive peat extraction in wetlands, bogs, marshes, and peatlands. This review uses unique data on the effective use of SMC in agricultural disease management, reducing the need for chemical pesticides that have adverse effects on both the environment and human health. It also provides a safe method for reusing, recycling, and integrating SMC into a circular economy that reduces its negative environmental effects and carbon footprint impacts. This work also offers a novel application of SMC as a low-cost substitute for peat or other growing media that pose environmental risks. [ABSTRACT FROM AUTHOR]

Currently, artificial intelligence (AI) is emerging as a dominant force in various technologies, owing to its unparalleled efficiency. Among the plethora of AI techniques available, neural networks (NNs) have garnered significant attention due to their adeptness in addressing diverse challenges, particularly for prediction tasks. This study offers a comprehensive review of predominant AI-based approaches to photovoltaic (PV) energy forecasting, with a particular emphasis on artificial neural networks (ANNs). We introduce a revolutionary methodology that amalgamates the predictive capabilities of ANN with the precision control afforded by the minimum-risk problem and sliding mode control (MRP-SMC), thereby revolutionizing the PV panel performance enhancement. Building upon this methodology, our hybrid approach utilizes the ANN as a proficient weather forecaster, accurately predicting the temperature and solar radiation levels impacting the panels. These forecasts serve as guiding principles for the MRP-SMC algorithm, enabling the proactive determination of the Maximum Power Point (MPP). Unlike conventional methods that grapple with weather unpredictability, the MRP-SMC algorithm transforms stochastic optimization challenges into controllable deterministic risk problems. Our method regulates the boost converter's work cycle dynamically. This dynamic adaptation, guided by environmental predictions from ANNs, unlocks the full potential of PV panels, maximizing energy recovery efficiency. To train the model, we utilized a large dataset comprising 60,538 temperature and solar radiation readings from the Department of Systems Engineering and Automation at the Faculty of Engineering in Vitoria (University of the Basque Country). Our approach demonstrates a high regression coefficient (R = 0.99) and low mean square error (MSE = 0.0044), underscoring its exceptional ability to predict real energy values. In essence, this study proposes a potent fusion of artificial intelligence and control mechanisms that unleash the untapped potential of photovoltaic panels. By utilizing forecasts to guide the converter, we are paving the way for a future where solar energy shines brighter than ever. [ABSTRACT FROM AUTHOR]

The quadcopter controller plays a significant role in autonomous vehicle trajectory tracking and has been extensively examined in the literature because it is a highly nonlinear and under-actuated system. This article contributes by methodically comparing PID, BSC, IBSC, SMC, and ISMC control algorithms under standardized conditions. The study involves implementing these algorithms and optimizing their parameters using a hybrid Flower Pollination Algorithm - Genetic Algorithm (FPA-GA). Robust testing scenarios, including mass uncertainty and time-varying disturbances, are employed to assess algorithmic performance. The research centers on trajectory tracking-control approaches for highly maneuverable Unmanned Aerial Vehicles (UAVs) equipped with four heave thrusters, emphasizing controller stability through Lyapunov functions. Theoretical exploration precedes comprehensive numerical simulations, enabling a detailed comparison of the efficacy and resilience of the proposed approaches. Results from exhaustive testing reveal the consistent superiority of the BSC controller, demonstrating notably low Integral of Time-weighted Squared Error (ITSE) values of 0.1253 and 0.5262 from two simulation tests. These findings underscore the practical advantages of the BSC controller in highly dynamic UAV trajectory tracking scenarios. [ABSTRACT FROM AUTHOR]

This study proposes the utilization of particle swarm optimization (PSO) and grey wolf optimization (GWO) algorithms to optimize the gains in sliding mode control (SMC) for a doubly fed induction generator (DFIG) system. The primary aim is to enhance reference tracking, improve overall system performance, and ensure system stability. The controllers' performance is assessed by evaluating tracking performance and stability through the analysis of noise signals in the stator's active and reactive power controllers. The experiments involve 10 search agents in both PSO and GWO algorithms, with a maximum of 100 iterations. Statistical results reveal that the PSO algorithm demonstrates better convergence stability and yields lower fitness function values, particularly in the case of IAE. Simulations demonstrate that SMC tuning with PSO leads to satisfactory dynamics for active and reactive powers, characterized by fast response and no overshoot. Performance metrics, including IAE and ISE indices, are employed to assess the control strategies, consistently showing that the SMC with PSO controller outperforms the SMC with GWO controller in terms of criteria values. The proposed control strategy utilizing PSO optimization effectively enhances reference tracking and overall performance in DFIG systems. [ABSTRACT FROM AUTHOR]

This article proposes a new intelligent trajectory tracking control law for the precise maneuvering of an autonomous vehicle in the presence of parametric uncertainties and external disturbances. The controller design includes a fuzzy sliding mode algorithm for smooth motion control subjected to steering saturation and curvature constraints. Along with the Salp Swarm Optimization technique, explored for optimal selection of surface coefficient in fractional order Proportional-Derivative type P D α sliding manifold. The sliding variable on the surface approaches zero in a finite time. Further, the trajectory tracking control rule offers the stability of closed-loop tracking on the predetermined path and ensures finite time convergence to the sliding surface. In addition, to estimate the hitting gain in online mode, a supervisory fuzzy logic controller system is used. Therefore, it is not necessary to determine upper bounds on uncertainty in the dynamic parameters of autonomous vehicles. Lyapunov theory verifies the global asymptotic stability of the entire closed-loop control strategy. The major control issue is the input constraints arising primarily due to the capability of the steering actuating module, which causes significant deviation or vehicle instability. Consequently, it is desirable to design a robust adaptive stable controller, such as Adaptive Backstepping Control (ABC), even though it requires vehicle model information. Therefore, the proposed model-free intelligent sliding mode technique offers better tracking performance and vehicle stability in adverse conditions. Finally, the efficacy of the proposed control technique was confirmed through a comparative analysis based on numerical simulation using MATLAB/SIMULINK and experimental validation using Quanser's self-driving car module. A quantitative study was conducted to elucidate the superior tracking performance of intelligent control over the traditional SMC and adaptive backstepping control methods. [ABSTRACT FROM AUTHOR]

Wind energy conversion systems (WECS) are emerging as among the most reliable alternative energy sources, requiring innovative control strategies to improve performance and reduce operating costs. The objective of this paper is the implementation of sliding mode control (SMC) for a permanent magnet synchronous generator (PMSG) to optimize the dynamical response and wind turbine system (WTS) stability. The control architecture comprises the PMSG, an AC-DC power converter, and a DC bus link, with a particular focus on extracting the optimum wind turbine power during variable wind speeds. A complete system model was developed and tested in MATLAB for a PMSG of 2 MW subjected to uncertain fluctuations in wind speed. The simulation results confirm that the SMC technique significantly improves speed-tracking accuracy, minimizes current ripple, and improves overall system stability. In addition, the proposed method ensures robust performance under non-linear and uncertain conditions, making it a viable solution for large-scale wind applications. These results highlight the potential of SMC to enhance the accuracy and efficiency of the WECS.

The investigation focuses on the initiation and progression of damage in SMC (Sheet Moulding Compound) composites subjected to tension. These composites consist of a polyester matrix reinforced with randomly oriented short C glass fibers. Damage monitoring is conducted using the acoustic emission technique. To assess the influence of surface density on damage in SMC, three series of composites with surface concentrations of 300 g/m2, 450 g/m2, and 600 g/m2 are tested. Based on stress-strain curves, the main mechanical properties of the different composites are determined. Additionally, the analysis of the collected acoustic emission data enabled us to determine the damage thresholds in the different studied composites. While tensile tests and the acoustic emission technique allowed us to determine important composite parameters, further research is necessary to comprehensively discern the various damage modes.

People living with HIV (PLWH) face a growing burden of chronic diseases, owing to the combinations of aging, environmental triggers, lifestyle choices, and virus-induced chronic inflammation. The rising incidence of pulmonary vascular diseases represents a major concern for PLWH. The study of HIV-associated pulmonary vascular complications ideally requires a strong understanding of pulmonary vascular cell biology and HIV pathogenesis at the molecular level for effective applications in infectious diseases and vascular medicine. Active HIV infection and/or HIV proteins disturb the delicate balance between vascular tone and constriction, which is pivotal for maintaining pulmonary vascular health. One of the defining features of HIV is its high genetic diversity owing to several factors including its high mutation rate, recombination between viral strains, immune selective pressures, or even geographical factors. The intrinsic HIV genetic diversity has several important implications for pathogenic outcomes of infection and the overall battle to combat HIV. Challenges in the field present themselves from two sides of the same coin: those imposed by the virus itself and those stemming from the host. The field may be advanced by further developing in vivo and in vitro models that are well described for both pulmonary vascular diseases and HIV for mechanistic studies. In essence, the study of HIV-associated pulmonary vascular complications requires a multidisciplinary approach, drawing upon insights from both infectious diseases and vascular medicine. In this review article, we discuss the fundamentals of HIV virology and their impact on pulmonary disease, aiming to enhance the understanding of either area or both simultaneously. Bridging the gap between preclinical research findings and clinical practice is essential for improving patient care. Addressing these knowledge gaps requires interdisciplinary collaborations, innovative research approaches, and dedicated efforts to prioritize HIV-related pulmonary complications on the global research agenda.

Hydrogen fuel cells are gaining popularity as a reliable and efficient sustainable energy source. They have found uses in electric vehicles and microgrid applications. A grid-connected microgrid system with a 60 kW proton exchange membrane fuel cell (PEMFC) is proposed. A PEM fuel cell-based generating unit is studied, using a sliding mode controller (SMC) in the control scheme and a nine-switch converter (NSC) for the system integration. The NSC is used to integrate the FC system with the utility grid and controls the system's power flow. This study is focused on the performance evaluation of the proportional-integral-derivative (PID) and SMC controllers. The controllers' gains are tuned using an improved arithmetic optimization method (IAOA). The article also emphasizes improving system performance and stability by incorporating SMC in the control scheme. The suggested system is exposed to different source and load-side disturbances for performance evaluation. Matlab/Simulink is used to model the proposed system and validated by the real-time OPAL-RT 4510.

Purpose: Biological nitrogen (N) fixation (BNF) of understory acacia species presents a potential way for effectively restoring N in forest systems. This study aimed to quantify the impact of acacia species and biochar application rates on BNF and soil mineral N in a suburban native forest of subtropical Australia in the first 4–5 years after prescribed burning. Method: Plant growth values and BNF were measured to assess the impact of biochar rates at 0, 5, and 10 t ha−1 on different acacia species. Soil NH4+-N and NO3−-N along with their N isotope composition (δ15N) were determined to investigate soil–plant interactions in response to acacia species and biochar application. Results: The application of 10 t ha−1 biochar significantly enhanced the growth of acacia species, and concurrently reduced the loss of NO3−-N at soil depths of 0–5 and 5–10 cm. Compared with Acacia disparimma (percentage of N derived from the atmosphere or %Ndfa: 78.2%), A. leiocalyx demonstrated significant higher BNF ability (%Ndfa: 91.3%). Similarly, A. leiocalyx had better growth, in terms of height (269.1 cm versus 179.6 cm), diameter at ground level (2.62 cm versus 1.94 cm), basal area (6.49 cm2 versus 3.43 cm2) and volume (692.2 cm3 versus 258.0 cm3). This was associated with its ability to promote organic matter mineralization, resulting in the accumulation of 15N-depleted NH4+-N. NH4+-N, acting as a substrate, was transformed into NO3−-N through nitrification. From regression analysis, the efficient absorption of NH4+-N by A. leiocalyx significantly mitigated NH4+-N leaching with increasing soil moisture concentration (SMC), resulting in lower δ15N of NH4+-N, which was more negatively related to SMC (R2 = 0.401), compared to that of A. disparimma (R2 = 0.250) at soil depth of 0–5 cm. The production of NO3−-N was reduced, leading to lower NO3−-N concentrations of A. leiocalyx than A. disparimma at soil depth of 0–5 cm (8.06 µg N g−1 versus 9.61 µg N g−1) and that of 5–10 cm (8.24 µg N g−1 versus 9.21 µg N g−1) respectively. Conclusions: As an effective soil amendment, biochar exhibited promise in reducing mineral N loss and stimulating plant growth in long-term applications of exceeding three years. Higher BNF capacity and greater plant growth were observed with A. leiocalyx, compared with those of A. disparimma. The retention and utilisation of mineral N by A. leiocalyx can be considered as strategy to restore forest soils. [ABSTRACT FROM AUTHOR]

An overview of intelligent control techniques for the speed control of a direct current (DC) motor has been described in this study. Using the MATLAB SIMULINK platform, the individually excited DC motor speed control system implemented as a physical model. A mathematical model for both the sliding mode control (SMC) method and PID control, a traditional control methodology that ensures the speed controller has been developed. For comparison's sake, fuzzy logic is constructed using the Mamdani Technique with two inputs to obtain the necessary speed control. In addition, to select the optimal gain, the output signal of The PID controller and SMC were contrasted with fuzzy logic in terms of overshoot peak and stability time period. The outcomes prove the SMC's superiority over the PI controller and fuzzy logic approach. Based on time domain characteristics, this article presents a comparative study between Proportional-Integral-Derivative (PID), a sliding mode control (SMC), and fuzzy logic controller (FLC) controllers. The study concludes the less overshoot peak and fast response through fixed Properties for the DC motor and its mechanical variations due to operating conditions. Based on transient response study, the results show that SMC is superior to fuzzy logic and classical controllers PID. [ABSTRACT FROM AUTHOR]

SMC (Structural maintenance of chromosomes) complexes are key participants in the spatial organization of DNA in all living organisms: in bacteria, archaea and eukaryotes. In bacteria, there are several homologues of SMC complexes that perform seemingly unrelated functions, but function through very similar, highly conserved mechanisms. In recent years, it has been established that SMC complexes are capable of forming loops from DNA (through the so-called loop extrusion), which allows them to be considered as a separate class of DNA translocases. This paper discusses bacterial SMC complexes in comparison with their homologues such as MukBEF, MksBEF, RecN, and Wadjet, as well as with eukaryotic SMC complexes. Their properties, role and functions in the key processes of the bacterial cell are discussed. [ABSTRACT FROM AUTHOR]

Active suspension control technologies have become increasingly significant in improving suspension performance for driving stability and comfort. An RBF-based fractional-order SMC fault-tolerant controller is developed in this research to guarantee ride comfort and handling stability when faced with the partial loss of actuator effectiveness due to failure. To obtain better control performance, fractional-order theory and the RBF algorithm are discussed to solve the jitter vibration problem in SMC, and the RBF is exploited to obtain a more appropriate switching gain. First, a half-nonlinear active suspension model and a fault car model are presented. Then, the design process of the RBF-based fractional-order SMC fault-tolerant controller is described. Next, a simulation is presented to demonstrate the effectiveness of the proposed strategy. According to the simulation, the proposed method can improve performance in the case of a healthy suspension, and the fault-tolerant controller can guarantee the capabilities when actuators go wrong. [ABSTRACT FROM AUTHOR]

Sliding Mode Control (SMC) is a popular nonlinear controller for quadrotor UAVs due to its robustness, fast response, and ability to handle complex dynamics. However, it suffers from chattering, sensitivity to modeling errors, and poor performance in the presence of unmatched uncertainties. In this paper, a novel Neuro-fuzzy adaptive sliding mode control is designed and proposed for the position and attitude control of quadrotor UAVs. The proposed method combines SMC with the learning capabilities of Artificial Neural Networks (ANN) and the decision-making abilities of Fuzzy Logic Control (FLC). Firstly, the quadrotor flight dynamics is derived using Newton’s quaternion formalism. Secondly, conventional SMC is designed, and the system’s stability is validated using Lyapunov stability analysis. Finally, the designed SMC equivalent control part is estimated online by ANN, while its switching control part is estimated by FLC. To verify the controller’s performance, extensive software-in-the-loop simulations have been conducted in various scenarios. The results show that the proposed controller effectively tolerates matched and unmatched uncertainties and has better tracking and disturbance rejection capabilities with minimal control effort compared to fuzzy-based SMC and conventional SMC. Therefore, the suggested controller is very suitable for quadrotor UAV applications that require high tracking precision despite varying operating conditions.

Switching power converters bring a desired output magnitude using semiconductor devices. These switching converters are generally classified as voltage lift and super lift. The conventional lift converters such as buck, boost and buck–boost come under the category of voltage lift technique, in which the output voltage increases in arithmetic progression. The other lift approach that increases the output voltage in the geometric progression is the super-lift method. Nowadays super-lift converters find their role in various applications, because of their high gain and low ripple. The converter taken for analysis is a modified negative output super-lift Luo converter (MNOSLC). Current mode control (CMC) is employed to maintain a stable DC voltage at the load side. This is investigated using different types of controllers such as PI, fuzzy, sliding mode controller (SMC) and fuzzy SMC. The performance of these controllers is compared and it is found that fuzzy SMC results in better line and load regulation. A prototype is developed that validates the simulation results.

DC–DC buck converters have been designed by incorporating different control stages to drive the switches. Among the most commonly used controllers, the sliding mode control (SMC) and proportional-integral-derivative (PID) controller have shown advantages in accomplishing fast slew rate, reducing settling time and mitigating overshoot. The proposed work introduces the implementation of both SMC and PID controllers by using the field-programmable gate array (FPGA) device. The FPGA is chosen to exploit its main advantage for fast verification and prototyping of the controllers. In this manner, a DC–DC buck converter is emulated on an FPGA by applying an explicit multi-step numerical method. The SMC controller is synthesized into the FPGA by using a signum function, and the PID is synthesized by applying the difference quotient method to approximate the derivative action, and the second-order Adams–Bashforth method to approximate the integral action. The FPGA synthesis of the converter and controllers is performed by designing digital blocks using computer arithmetic of 32 and 64 bits, in fixed-point format. The experimental results are shown on an oscilloscope by using a digital-to-analog converter to observe the voltage regulation generated by the SMC and PID controllers on the DC–DC buck converter.

This paper explores the application of sliding mode control (SMC) as a robust security enhancement strategy for unmanned aerial vehicle (UAV) systems. The study proposes integrating advanced SMC techniques with security protocols to develop a dual-purpose system that improves UAV control and fortifies against adversarial actions. The strategy includes dynamic reconfiguration capabilities within the SMC framework, allowing adaptive responses to threats by adjusting control laws and operational parameters. This is complemented by anomaly detection algorithms that monitor deviations in control signals and system states, providing early warnings of potential cyber-intrusions or physical tampering. Additionally, fault-tolerant SMC mechanisms are designed to maintain control and system stability even when parts of the UAV are compromised. The methodology involves simulation and real-world testing to validate the effectiveness of the SMC-based security enhancements. Simulations assess how the UAV handles attack scenarios, such as GPS spoofing and control signal jamming, with SMC adapting in real-time to mitigate these threats. Field tests further confirm the system’s capability to operate under varied conditions, proving the feasibility of SMC for enhancing UAV security. This integration of sliding mode control into UAV security protocols leverages control theory for security purposes, offering a significant advancement in the robust, adaptive control of UAVs in hostile environments.

In response to safety concerns pertaining to multi-UAV formation flights, a novel obstacle avoidance method based on an Improved Adaptive Artificial Potential field (IAAPF) is presented. This approach enhances UAV obstacle avoidance capabilities by utilizing segmented attraction potential fields refined with adaptive factors and augmented with virtual forces for inter-UAV collision avoidance. To further enhance the control and stability of multi-UAV formations, a Sliding Mode Control (SMC) method is integrated into the IAAPF-based obstacle avoidance framework. Renowned for its robustness and ability to handle system uncertainties and disturbances, the SMC method is combined with a feedback control system that utilizes inner and outer loops. The outer loop generates the desired path based on the leader’s state and control commands, while the inner loop tracks these trajectories and adjusts the follower UAVs’ motions. This design ensures that obstacle feedback is accounted for before the desired state information is received, enabling effective obstacle avoidance while maintaining formation integrity. Integrating leader-follower formation control techniques with SMC-based multi-UAV obstacle avoidance strategies ensures the effective convergence of the formation velocity and spacing to predetermined values, meeting the cooperative obstacle avoidance requirements of multi-UAV formations. Simulation results validate the efficacy of the proposed method in reaching otherwise unreachable destinations within obstacle-rich environments, while ensuring robust collision avoidance among UAVs.

In the DC microgrid system, the bidirectional DC/DC converter is one of the most important components; thus, research on its control strategy has attracted widespread attention. Firstly, the single bidirectional DC/DC converter based on a sliding mode (variable structure) control (SMC) strategy exhibits an inherent contradiction between the reaching time and the chattering phenomenon. In order to address this problem, an SMC strategy based on the improved exponential reaching law was designed. This control strategy modifies the constant-speed reaching term and introduces the system state variable to indicate the chattering level, which not only improves the dynamic performance of the bidirectional DC/DC converter but also suppresses the chattering problem. Secondly, the bidirectional DC/DC converter group based on the traditional droop control strategy exhibits an inherent contradiction between load power allocation and bus voltage stabilization. In order to address this problem, an improved droop control strategy that takes the line impedance characteristics into account is proposed. This control strategy modifies the traditional droop control strategy by introducing virtual resistance and uses DC bus voltage information to replace the line impedance value. This ensures the accuracy of power allocation and stability of the DC bus voltage simultaneously. Finally, the stability of each designed strategy is verified individually. The combination of the two control strategies is applied to a group of bidirectional DC/DC converters group to conduct a semi-physical simulation experiment, and the results verify that the proposed control strategies are effective and feasible.

While there is a considerable body of knowledge regarding the molecular and structural biology and biochemistry of archaeal information processing machineries, far less is known about the nature of the substrate for these machineries—the archaeal nucleoid. In this article, we will describe recent advances in our understanding of the three‐dimensional organization of the chromosomes of model organisms in the crenarchaeal phylum. [ABSTRACT FROM AUTHOR]

This paper proposes an improved Wind Turbine Emulator (WTE) structure using Sliding Mode Control (SMC) technique based on the Two-Phase Induction Motor (TPIM) for software simulation laboratory purposes. Since the power electronic converters application with various control strategies in the AC machine drive field facilitates the wind turbine characteristics imitation, an advanced SVM controlled-2ϕ-inverter is adopted. Considering the asymmetry between the TPIM main and auxiliary windings, mathematical equations were studied allowing control of the speed and the torque under different conditions. The 2-phase-inverter is controlled through an appropriate adjustment of four space voltage vectors. In order to enhance the speed and flux regulation loops and to increase the system robustness against the motor parameters variation and the wind sudden fluctuations, the SMC theory, which contains the adaptive rotor flux observer is used here to develop a control law that governs the system to track the reference speed set by the WT mathematical model to obtain the desired output. Several parameters, such as electromagnetic torque, rotor fluxes, stator currents, and rotor speed, were analyzed. Static and dynamic characteristics and the WTE transient and steady-state responses are satisfactorily reproduced by the proposed emulator scheme. [ABSTRACT FROM AUTHOR]

Switching power converters bring a desired output magnitude using semiconductor devices. These switching converters are generally classified as voltage lift and super lift. The conventional lift converters such as buck, boost and buck–boost come under the category of voltage lift technique, in which the output voltage increases in arithmetic progression. The other lift approach that increases the output voltage in the geometric progression is the super-lift method. Nowadays super-lift converters find their role in various applications, because of their high gain and low ripple. The converter taken for analysis is a modified negative output super-lift Luo converter (MNOSLC). Current mode control (CMC) is employed to maintain a stable DC voltage at the load side. This is investigated using different types of controllers such as PI, fuzzy, sliding mode controller (SMC) and fuzzy SMC. The performance of these controllers is compared and it is found that fuzzy SMC results in better line and load regulation. A prototype is developed that validates the simulation results. [ABSTRACT FROM AUTHOR]

Background Owing to the increased cases of malaria in older children, the World Health Organization has recently recommended extending seasonal malaria chemoprevention (SMC) to children >5 years of age and using other effective drugs for malaria. In this study, we report the safety and efficacy of dihydroartemisinin-piperaquine (DHA-PQ) for SMC in school-aged children in Mali. Method This randomized, controlled trial included 345 participants aged 6–15 years randomized to receive DHA-PQ, sulfadoxine-pyrimethamine plus amodiaquine (SP-AQ), or no chemoprevention (albendazole) at a 1:1:1 ratio. Four rounds of SMC were conducted from September to December 2021. The participants were assessed 7 days after each round for safety and efficacy of the interventions. Results Abdominal pain (11.8% vs 29.2%), headache (11.2% vs 19.2%), and vomiting (5.7% vs 15.2%) were frequently reported in the DHA-PQ and SP-AQ arms. On Day 120 of follow up, the incidence of clinical malaria was 0.01 episodes/person-month in the DHA-PQ and SP-AQ arms and 0.17 episodes/person-month in the control arm (P <.0001). Gametocytes were detected in 37 participants in all arms. Conclusions Children in DHA-PQ arm reported less adverse events compared to the SP-AQ arm. Both drugs were effective against clinical malaria and infection. [ABSTRACT FROM AUTHOR]

In this paper, the authors present a new method to synthesize an adaptive sliding controller for Twin Rotor MIMO System (TRMS) based on Synergetic Control Theory (SCT). This system represents a prototype of a helicopter with two degrees of freedom and is widely used in automatic control laboratories. The complexity of the control problem is due to the nonlinear cross-coupling between the main and tail rotors. Uncertainty in system parameters further increases the complexity of the control problem. In Synergetic Control Theory, manifolds are designed for each channel. The control law is found based on sequential manifolds and the Analytical Design of Aggregated Regulators (ADAR) method. The adaptive law when the parameters are uncertain is given based on the analysis of system stability thanks to the Lyapunov function of the first manifold. Finally, the effectiveness of the proposed controller is demonstrated by numerical simulation results and comparison with conventional Sliding Mode Control (SMC). [ABSTRACT FROM AUTHOR]

Aims: We sought to identify and optimise a universally available histological marker for pericytes in the human brain. Such a marker could be a useful tool for researchers. Further, identifying a gene expressed relatively specifically in human pericytes could provide new insights into the biological functions of this fascinating cell type. Methods: We analysed single‐cell RNA expression profiles derived from different human and mouse brain regions using a high‐throughput and low‐cost single‐cell transcriptome sequencing method called EasySci. Through this analysis, we were able to identify specific gene markers for pericytes, some of which had not been previously characterised. We then used commercially (and therefore universally) available antibodies to immunolabel the pericyte‐specific gene products in formalin‐fixed paraffin‐embedded (FFPE) human brains and also performed immunoblots to determine whether appropriately sized proteins were recognised. Results: In the EasySci data sets, highly pericyte‐enriched expression was notable for SLC6A12 and SLC19A1. Antibodies against these proteins recognised bands of approximately the correct size in immunoblots of human brain extracts. Following optimisation of the immunohistochemical technique, staining for both antibodies was strongly positive in small blood vessels and was far more effective than a PDGFRB antibody at staining pericyte‐like cells in FFPE human brain sections. In an exploratory sample of other human organs (kidney, lung, liver, muscle), immunohistochemistry did not show the same pericyte‐like pattern of staining. Conclusions: The SLC6A12 antibody was well suited for labelling pericytes in human FFPE brain sections, based on the combined results of single‐cell RNA‐seq analyses, immunoblots and immunohistochemical studies. [ABSTRACT FROM AUTHOR]

Abstract Background Seasonal malaria chemoprevention (SMC) using sulfadoxine-pyrimethamine plus amodiaquine (SP-AQ), is a community-based malaria preventive strategy commonly used in the Sahel region of sub-Saharan Africa. However, to date it has not been implemented in East Africa due to high SP resistance levels. This paper is a report on the implementation of SMC outside of the Sahel in an environment with a high level of presumed SP-resistance: five cycles of SMC using SPAQ were administered to children 3–59 months during a period of high malaria transmission (July–December 2019) in 21 villages in South Sudan. Methods A population-based SMC coverage survey was combined with a longitudinal time series analysis of health facility and community health data measured after each SMC cycle. SMC campaign effectiveness was assessed by Poisson model. SPAQ molecular resistance markers were additionally analysed from dried blood spots from malaria confirmed patients. Results Incidence of uncomplicated malaria was reduced from 6.6 per 100 to an average of 3.2 per 100 after SMC administration (mean reduction: 53%) and incidence of severe malaria showed a reduction from 21 per 10,000 before SMC campaign to a mean of 3.3 per 10,000 after each cycle (mean reduction: 84%) in the target group when compared to before the SMC campaign. The most prevalent molecular haplotype associated with SP resistance was the IRNGE haplotype (quintuple mutant, with 51I/59R/108N mutation in pfdhfr + 437G/540E in pfdhps). In contrast, there was a low frequency of AQ resistance markers and haplotypes resistant to both drugs combined (

Grid frequency regulation is essential for a reliable power grid. Whilst in distributed energy sources, (DERs) power fluctuations arise from the imbalance of frequency. There are multiple conventional and recent advanced frequency regulation techniques to dissolve this issue. The existing techniques using conventional controllers in microgrid control are well suited for voltage regulation, but the frequency cannot be adequately controlled using conventional and linear controllers. Most of the advanced control methods use algorithms to manage the grid frequency stability. This review comprehensively discusses the advanced control techniques for frequency regulation in micro-grids namely model predictive control, adaptive control, sliding mode control, h-infinity control, back-stepping control, (Disturbance estimation technique) kalman state estimator-based strategies, and intelligent control methods. Each control method is briefly explained along with recent advancements and corresponding governing equations. At glace, these control techniques are comparatively studied by elaborating future requirements.

Aiming at the specific target search and controllable angle guidance of unmanned surface ships in uncertain waters, this paper explores the target detection method based on YOLO and the guidance control method based on side angle constraint. On the basis of analyzing the uncertain conditions such as sea fog, the paper designs the correlation filter with improved YOLOv5 algorithm to extract the target features, combines depth information to realize the detection and positioning of water surface targets, sliding mode variable structure guidance control to achieve the high maneuverability target side angle constraint guidance. TCP/IP combined with ROS is used to create a corner constrained terminal guidance system for information processing. Two-dimensional simulation experiment is completed with Autolabor platform, and the result of target guidance error is 1.54%, which proves the effectiveness of the method proposed.

Day by day, the power electronics (PE) application is increasing in hybrid electric vehicles (EV). The power interfacing between the DC link drive and battery is the main issue of EVs. The best choice for this application is the bidirectional flyback converter (BFC). This can be used in a different interface, like load from the grid to the battery, external Genset to the battery, and battery to the load. In this work, a Multiphase BFC Topology is developed for Hybrid EVs. It includes the design of the Sliding mode controller (SMC), which offers superior performance to the existing controller. Due to its separated nature and smaller machinery, it is most favoured in high-voltage applications. The suggested work is executed in MATLAB/Simulink environment. The proposed method is compared with the current controllers like GA-PID, Fuzzy logic controller (FLC). From the experimental outcomes, it is observed that the proposed SMC technique gives better converter performance.

In recent years, various solutions have been developed to control power electronic converters using devices available on the market that are powerful and easy to use. These solutions, in most cases, offer high performance. However, these have high implementation costs because the required devices are expensive. For this reason, this document presents the implementation of two discrete-time controllers widely used in the literature for a boost converter implemented on a low-cost platform. The objective is to obtain a constant voltage at the converter’s output for photovoltaic system applications. The proportional-integral control is implemented as the first case, and the second case is a sliding mode control. In addition, a prior analysis is presented through simulation. Both control algorithms are implemented on the TMS320F28379D microcontroller from Texas Instruments through the same manufacturer’s integrated development software based on an optimized C/C++ language compiler. The results of the non-linear algorithm reveal better performance in reducing the time response, the overshoot of the transient state, and the steady-state error. Finally, the significant economic savings associated with the implementation costs of the controllers tested on a low-cost platform differentiate this work from other similar ones.

Currently, artificial intelligence (AI) is emerging as a dominant force in various technologies, owing to its unparalleled efficiency. Among the plethora of AI techniques available, neural networks (NNs) have garnered significant attention due to their adeptness in addressing diverse challenges, particularly for prediction tasks. This study offers a comprehensive review of predominant AI-based approaches to photovoltaic (PV) energy forecasting, with a particular emphasis on artificial neural networks (ANNs). We introduce a revolutionary methodology that amalgamates the predictive capabilities of ANN with the precision control afforded by the minimum-risk problem and sliding mode control (MRP-SMC), thereby revolutionizing the PV panel performance enhancement. Building upon this methodology, our hybrid approach utilizes the ANN as a proficient weather forecaster, accurately predicting the temperature and solar radiation levels impacting the panels. These forecasts serve as guiding principles for the MRP-SMC algorithm, enabling the proactive determination of the Maximum Power Point (MPP). Unlike conventional methods that grapple with weather unpredictability, the MRP-SMC algorithm transforms stochastic optimization challenges into controllable deterministic risk problems. Our method regulates the boost converter’s work cycle dynamically. This dynamic adaptation, guided by environmental predictions from ANNs, unlocks the full potential of PV panels, maximizing energy recovery efficiency. To train the model, we utilized a large dataset comprising 60,538 temperature and solar radiation readings from the Department of Systems Engineering and Automation at the Faculty of Engineering in Vitoria (University of the Basque Country). Our approach demonstrates a high regression coefficient (R = 0.99) and low mean square error (MSE = 0.0044), underscoring its exceptional ability to predict real energy values. In essence, this study proposes a potent fusion of artificial intelligence and control mechanisms that unleash the untapped potential of photovoltaic panels. By utilizing forecasts to guide the converter, we are paving the way for a future where solar energy shines brighter than ever.

Two main domains have been followed; joint space control and operational (task) space control for robot manipulators. Task space control is simpler than joint space control as it avoids tackling the robot inverse kinematics which is very complex and challenging. However, in order to design robust and accurate controllers in operational space, both kinematics and dynamics uncertainties must be considered. Additionally, singularities that may occur while mapping between joint space and task space should be addressed. To tackle these issues, a new adaptive task space control approach is developed in this paper. The developed approach is able to overcome uncertainties and mitigate the chattering that commonly occur during the control process. The introduced control system has been proven to be globally stable using a designed Lyapunov function. The simulation results show that the suggested model is able to control the robot manipulators efficiently even in the existence of external disturbances.

Background The World Health Organization (WHO) recommends seasonal malaria chemoprevention (SMC) with sulfadoxine-pyrimethamine and amodiaquine (SPAQ) for children aged 3 to 59 months, living in areas where malaria transmission is highly seasonal. However, due to widespread prevalence of resistance markers, SMC has not been implemented at scale in East and Southern Africa. An initial study in Uganda showed that SMC with SPAQ was feasible, acceptable, and protective against malaria in eligible children in Karamoja region. Nonetheless, exploration of alternative regimens is warranted since parasite resistance threats persist. Objective The study aims to test the effectiveness of SMC with Dihydroartemisinin-piperaquine (DP) or SPAQ (DP-SMC & SPAQ-SMC), chemoprevention efficacy as well as the safety and tolerability of DP compared to that of SPAQ among 3-59 months old children in Karamoja region, an area of Uganda where malaria transmission is highly seasonal. Methods A Type II hybrid effectiveness-implementation study design consisting of four components: 1) a cluster randomized controlled trial (cRCT) using passive surveillance to establish confirmed malaria cases in children using both SPAQ and DP; 2a) a prospective cohort study to determine the chemoprevention efficacy of SPAQ and DP (if SPAQ or DP clears sub-patent infection and provides 28 days of protection from new infection) and whether drug concentrations and/or resistance influence the ability to clear and prevent infection; 2b) a sub study examining pharmacokinetics of DP in children between 3 to