Frequent Switching Research Articles

Identifying Predictors of Unfavorable Treatment Outcomes in Tuberculosis Patients

Objectives: In South Korea, there has been a continuous decrease in the incidence of tuberculosis (TB) attributable to a national TB elimination program; however, TB still poses a significant socioeconomic burden. This study aimed to analyze factors associated with successful TB treatment and to identify refractory patient groups with unfavorable outcomes. Methods: We analyzed anonymized data on 89,150 patients with TB provided by the Korea Disease Control and Prevention Agency. Specifically, we collected independent variables, which were categorized as individual, regional, and medical facility factors. Individual factors included age, sex, nationality, TB type, drug-resistant status, category of TB, housing type, underlying disease status, number of referrals, and smoking status. Regional factors referred to the region where the TB case was reported. Medical facility factors included the first visit to a medical facility, categorized by hospital type and the distinction between private–public mix (PPM) and non-PPM depending on the presence or absence of dedicated TB nurses. These factors were analyzed in relation to treatment success to identify refractory patient groups with unfavorable outcomes. Results: Multivariable logistic regression analysis revealed the following significant factors associated with successful TB treatment: sex, nationality, status of drug-resistant TB, category of TB, number of referrals, region of TB registry, underlying diseases, and smoking status. Specifically, compared with their relevant counterparts, male patients had a lower rate of successful treatment (adjusted odds ratio [aOR]: 0.66, reference [Ref.]: women); Korean nationals had a higher rate of treatment success (aOR: 7.20, Ref. foreign residents in Korea); resistant TB was associated with a lower rate of treatment success (aOR: 0.35, Ref.: non-resistant TB status); newly treated patients had a higher rate of treatment success (aOR: 1.75, Ref.: retreatment patient); switching hospitals once (aOR: 1.78), never (aOR: 1.41), or twice (aOR: 1.37) was associated with increased treatment success (Ref.: three or more times); having zero (aOR: 1.45), one (aOR: 1.31), or two (aOR: 1.24) underlying diseases was associated with a higher rate of treatment success (Ref. three or more underlying diseases); and past smokers (aOR: 1.40) and non-smokers (aOR: 1.35) had a higher rate of treatment success (Ref.: current smokers). Conclusions: Our study identified several factors contributing to unfavorable treatment outcomes in tuberculosis patients, including male patients, foreign residents in Korea, drug-resistant TB, retreatment patients, frequent hospital switching, multiple underlying diseases, and current smoking status. These research findings could inform the development of efficient management strategies and policies for improving the treatment success rate among patients with TB.

Analysis of the Creep Mechanism of Low-Alloy Steel in Terms of Plastic Deformation

AbstractAs the proportion of renewable energy sources within the energy grid increases, boiler operations increasingly rely on managing disparities in energy supply. This condition substantially curtails their operational lifespan due to frequent switching cycles. Materials exposed to prolonged stress at high temperatures in harsh environments gradually degrade and eventually fail catastrophically. Thus, understanding processes like creep is essential for accurately evaluating the condition of operational components under new operational standards in power plants. In this regard, this paper introduces an innovative methodological framework for analyzing the creep mechanism, focusing on the plastic deformation of a crucial pipeline segment, specifically an elbow composed of 14MoV6-3 steel, both before and after extensive usage periods (164,000 and 302,000 h). The study explored the development of microstrain from the material's surface employing the electron backscattered diffraction method. This analysis assessed how operational durations influence dislocation structural changes, as examined by synchrotron radiation techniques, across a material depth from 0 to 1.5 mm. Based on these observations, the extent of deformation over time was demonstrated. Furthermore, the evolution of precipitation processes was investigated through transmission electron microscopy. These tests allowed to obtain and compare information on the dislocation structure of the tested steel after service in creep conditions, of small and large volumes of material.

Study on the dynamic characteristics of the head cover-bolts-stay ring of a variable-speed pump-turbine

Abstract The design and operation of variable-speed pump-turbine units is more difficult than that of conventional units due to their adjustable speed, frequent start stop, and forward and reverse operation. Due to the development of variable-speed pump-turbines towards variable-speed, high head, and large capacity, the vibration instability caused by frequent switching between turbine and pump operating conditions is more prominent. The study on the dynamic characteristics of the head cover-bolts-stay ring system is an important guarantee for the long-term safe and stable operation of the units. This article uses the finite element method to conduct modal analysis on the head cover-bolts-stay ring system of a variable-speed pump-turbine. The natural frequency and mode shape are analyzed, and resonance analysis is carried out in combination with the dynamic and static interference characteristics of the variable-speed unit. The research results show that the dynamic and static interference frequency of the unit during the variable-speed process may be close to the natural frequency of the head cover-bolts-stay ring system, which needs to be paid attention to during operation. The results and findings in this article provide theory and practical basis for the research and design of high head, large capacity, and variable-speed pump-turbine units.

Energy-Saving Control Strategy for Ultra-Dense Network Base Stations Based on Multi-Agent Reinforcement Learning

Aiming at the problem of mobile data traffic surge in 5G networks, this paper proposes an effective solution combining massive multiple-input multiple-output techniques with Ultra-Dense Network (UDN) and focuses on solving the resulting challenge of increased energy consumption. A base station control algorithm based on Multi-Agent Proximity Policy Optimization (MAPPO) is designed. In the constructed 5G UDN model, each base station is considered as an agent, and the MAPPO algorithm enables inter-base station collaboration and interference management to optimize the network performance. To reduce the extra power consumption due to frequent sleep mode switching of base stations, a sleep mode switching decision algorithm is proposed. The algorithm reduces unnecessary power consumption by evaluating the network state similarity and intelligently adjusting the agent's action strategy. Simulation results show that the proposed algorithm reduces the power consumption by 24.61% compared to the no-sleep strategy and further reduces the power consumption by 5.36% compared to the traditional MAPPO algorithm under the premise of guaranteeing the quality of service of users.

Neighbors affect vocal behavior of tropical wrens: a multispeaker density-manipulation experiment.

For territorial animals, the behavior of conspecific neighbors sets the social context of communication. Despite numerous investigations of vocalizations related to territory defense and mate attraction, the effect of neighbor density on animal vocal behavior has received little attention, particularly in tropical animals and animals where both sexes produce complex acoustic signals. In this study, we used an innovative multispeaker playback experiment to manipulate the apparent density of neighbors in rufous-and-white wrens, Thryophilus rufalbus, living in Costa Rica's tropical dry forest. In this tropical songbird, both males and females defend year-round territories and sing complex, learned songs for territory defense. We recorded the singing behavior of 24 subjects (12 pairs), and then we used an array of 6 loudspeakers to simulate the presence of 6 new territorial neighbors (3 simulated pairs) outside each subject pair's breeding territory. The stimuli persisted for 3 consecutive days, with both male and female songs broadcast at a natural rate from dawn to dusk. We found that the mean male song rate increased by almost 50% in response to the simulated increase in local density. Females showed less frequent song-type switching rates following the simulated increase in local density, although it was a marginal increase. These findings reveal that male and female songbirds' vocal behavior varies with the local density of territorial neighbors. We conclude that birds are sensitive to acoustic signals of conspecific density arising from sounds beyond their territory boundaries, and that they use this public information to guide their vocal behavior.

Visual Target Interaction Modeling with Multichannel Data Fusion

Facing the demand for accurate, fast, and natural human–computer interaction in the multi-screen control environment, the traditional exchange method of frequent switching control of multi-screen through mouse, keyboard, and other manual methods has problems of low efficiency, weak flexibility, and poor experience. In this paper, we research multi-screen precision control technology based on eye movement to break through the difficulties of precise recognition of human vision under complex environments and poor stability of vision estimation under frequent switching control of multi-screen. This study explores the technology for controlling multiple screens with high precision by tracking eye movements. It overcomes the challenges associated with reliably discerning human visual focus in intricate settings and the instability of visual assessments during rapid transitions between multiple screens. The experimental results of 1143 eye-movement capture tasks are studied, including the accurate recognition technology of human head posture and pupil gaze direction under complex backgrounds, illumination, and different visual field environments, and the theoretical modeling method of multi-screen precise target interaction based on eye-movement is explored. The expression data will be processed using convolutional neural networks, and the dataset will be trained through Python programming and tested on test samples collected by simulated flight crews in the laboratory with an accuracy rate of more than 85%.

Viral diversity and co-evolutionary dynamics across the ant phylogeny.

Knowledge of viral biodiversity within insects, particularly within ants, is extremely limited with only a few environmental viruses from invasive ant species identified to date. This study documents and explores the viral communities in ants. We comprehensively profile the metagenomes of a phylogenetically broad group of 35 ant species with varied ecological traits and report the discovery of 3710 novel and unique ant-associated viral genomes. These previously unknown viruses discovered within this study constitute over 95% of all currently described ant viruses, significantly increasing our knowledge of the ant virosphere. The identified RNA and DNA viruses fill gaps in insect-associated viral phylogenies and uncover evolutionary histories characterized by both frequent host switching and co-divergence. Many ants also host diverse bacterial communities, and we discovered that approximately one-third of these new ant-associated viruses are bacteriophages. Two ecological categories, bacterial abundance in the host and habitat degradation are both correlated with ant viral diversity and help to structure viral communities within ants. These data demonstrate that the ant virosphere is remarkably diverse phylogenetically and genomically and provide a substantial foundation for studies in virus ecology and evolution within eukaryotes. We highlight the importance of studying insect-associated viruses in natural ecosystems in order to more thoroughly and effectively understand host-microbe evolutionary dynamics.

Lightweight multiobject ship tracking algorithm based on trajectory association and improved YOLOv7tiny

In response to various challenges, such as high computational complexity, large parameter counts, and frequent vessel ID switching in ship tracking models, we propose a trajectory association and improved YOLOv7tiny-based vessel tracking algorithm, named the vessel tracking model with YOLOv7tiny-Vessel and StrongSORT-Vessel (VTM-YS). The algorithm consists of two stages: vessel detection and vessel tracking. In the vessel detection stage, we propose a lightweight Fast-PP-LCNet backbone network for efficient feature extraction of ships. Then, a novel Slim Bidirectional Pyramid Aggregation Network (Slim-BiPANet) is constructed to effectively fuse multiscale vessel features. Furthermore, introducing a coordinate attention (CA) module enhances the focus on vessel detection regions. In the vessel tracking stage, we introduce the OSNet reidentification network and the NSA Kalman filter algorithm into the StrongSORT model to reduce the frequency of tracked vessel ID switches. The results indicate that, in terms of vessel detection, the improved YOLOv7tiny achieves a 1.5% increase in mAP50 and a 13.9% reduction in parameters compared to the baseline YOLOv7tiny. For vessel tracking, the StrongSORT model achieves a 3.5% improvement in HOTA, a 7.0% improvement in MOTA, and a 73% reduction in ID switches, meeting the requirements for lightweight design and tracking accuracy.

Dual-layer control strategy based on economic characterization of lifetime state and frequency regulation limit partition of hybrid energy storage

Compared with a single type of energy storage, hybrid energy storage system (HESS) has a better performance in improving the frequency safety of the grid. However, the combination of hybrid energy storage with different resource characteristics and thermal power units will significantly increase the difficulty of coordinated control. In view of the life decay of battery energy storage system (BESS) and the insufficient frequency regulation capability of the system, this paper proposes a dual-layer control strategy based on the economic characterization of hybrid energy storage life state and the frequency regulation limit partition. Real-time state of charge (SOC) is used to establish dynamic equilibrium quotation and energy storage performance characterization as the upper-layer model. Meanwhile, the optimal life evaluation of energy storage is proposed, and the charging and discharging switching model of energy storage is constructed to limit the frequent switching of energy storage and extend its life. The lower-layer model constructs the limit standard of frequency regulation of flywheel energy storage system (FESS), introduces multi-objective constraints, proposes a hybrid energy storage operation scheme suitable for the whole scene, and uses “two rules” as the evaluation index to evaluate the frequency regulation effect of the proposed frequency regulation control model from the regulation rate, accuracy and response time. Finally, taking the actual data of a local thermal power unit as an example, the validity and economy of the frequency regulation effect of the proposed model are verified.

Review on Security Range Perception Methods and Path-Planning Techniques for Substation Mobile Robots

The use of mobile robots in substations improves maintenance efficiency and ensures the personal safety of staff working at substations, which is a trend in the development of technologies. Strong electric and solid magnetic fields around high-voltage equipment in substations may lead to the breakdown and failure of inspection devices. Therefore, safe operation range measurement and coordinated planning are key factors in ensuring the safe operation of substations. This paper first summarizes the current developments that are occurring in the field of fixed and mobile safe operating range sensing methods for substations, such as ultra-wideband technology, the two-way time flight method, and deep learning image processing algorithms. Secondly, this paper introduces path-planning algorithms based on safety range sensing and analyzes the adaptability of global search methods based on a priori information, local planning algorithms, and sensor information in substation scenarios. Finally, in view of the limitations of the existing range awareness and path-planning methods, we investigate the problems that occur in the dynamic changes in equipment safety zones and the frequent switching of operation scenarios in substations. Furthermore, we explore a new type of barrier and its automatic arrangement system to improve the performance of distance control and path planning in substation scenarios.

Event-triggered quasi-time-varying [formula omitted] filtering for switched systems via multiple trigger-dependent Lyapunov functionals

This paper investigates the event-triggered filtering problem for switched systems from the perspective of switched impulsive systems (SISs) by exploiting the characteristics of trigger and impulse behavior. By constructing multiple trigger-dependent Lyapunov functionals (MTDLFs), an event-triggered quasi-time-varying (ET-QTV) H∞ filtering scheme is developed. Since the MTDLFs properly capture the event-induced impulse property of SISs, they release less conservatism. The filtering stability in the scenario of frequent plant switching during an interevent interval is also guaranteed by incorporating the average dwell time switching. The filtering synthesis condition is formulated as a set of QTV matrix inequalities defined over a finite time horizon, based on which a sum of squares-based filter design algorithm is presented further. Additionally, the derivation of a lower bound on interevent intervals is clarified for the event-triggering mechanism (ETM) to exclude the Zeno phenomenon. Finally, the effectiveness and potential practicability of the proposed filtering scheme are validated using a morphing aircraft model.

Adaptive Frame Structure Design for Sensing-Assisted Downlink Communication in the Vehicle-to-Infrastructure Scenario.

Vehicle-to-everything (V2X) is considered a key factor in driving the future development of intelligent transport, which requires high-quality communication and fast sensing of vehicle information in high-speed mobile scenarios. However, high-speed mobility makes the wireless channel change rapidly, which requires frequent channel estimation and channel feedback between a vehicle and the roadside unit (RSU), resulting in an increase in communication overhead. At the same time, the high maneuverability of vehicles leads to frequent switching and misalignment of communication beams, so the RSU must have better beam prediction and tracking capabilities. To address this problem, this paper proposes an adaptive frame structure design scheme for sensing-assisted downlink (DL) communication. The basic idea of the scheme involves analyzing the communication model during the vehicle's movement. This analysis aims to establish a theoretical relationship between the Symbol Error Rate (SER) and the following two key factors: the vehicle's starting position and the distance it travels across. Subsequently, the scheme leverages the vehicle's position data, as detected by the RSU, to calculate the real-time SER for DL communication. The SER threshold is set based on the requirements of DL communication. If the real-time SER is below this threshold, channel estimation becomes unnecessary. This decreases the frequency of channel estimation and frees up time and frequency resources that would otherwise be occupied by channel estimation processes within the frame structure. The design of an adaptive frame structure, as detailed in the above scheme, is presented. Furthermore, the performance of the proposed method is analyzed and compared with that of the traditional communication protocol frame structure and the beam prediction-based frame structure. The simulation results indicate that the communication throughput of the proposed method can be improved by up to 6% compared with the traditional communication protocol frame structure while maintaining SER performance.

Study on phase selection control characteristics of fast vacuum circuit breakers suitable for new power systems

Abstract With a high proportion of new energy access to the power system, the user side of the randomness and volatility of distributed photovoltaic large-capacity access to the 10 kV medium-voltage distribution grid operation results in more frequent fluctuations in the system voltage and more frequent switching of reactive compensation of the shunt capacitor bank on the 10 kV side of the conventional substation. Conventional reactive compensation switching circuit breakers adopt a spring mechanism whose mechanical stability is insufficient and the selection of the relevant fit capacitor bank accuracy is not enough. The 12 kV fast vacuum circuit breaker of small mechanical dispersion for selection related to the combination was proposed. First of all, based on the neutral grounded and ungrounded system of the capacitor bank, the strategy of capacitor bank phase selection closing was developed. For the action characteristics of the phase selection of the 12 kV fast vacuum circuit breaker, the variation laws of mechanical dispersion and the influence factors such as ambient temperature, capacitance voltage, capacitance degradation, mechanical wear, and conductive rod deformation were obtained by simulation and experiment. The results showed that the ambient temperature and capacitance voltage had a great influence on the switching time of the fast circuit breaker, while other factors had a small influence. Again, the pre-breakdown characteristics of the 12 kV fast vacuum circuit breaker were obtained by experiments. The results showed that the influence of contact opening distance and pre-breakdown voltage was a linear relationship, and the pre-breakdown slope was 30 kV/mm. According to the pre-breakdown closing characteristic curve, the pre-breakdown time of the fast circuit breaker was 0.45 ms at most. The feedforward compensation mechanism based on a neural network was proposed to compensate for the action characteristics of the fast circuit breaker and aimed to improve the phase selection accuracy. Finally, two rounds of capacitive current switching tests of 12 kV fast vacuum circuit breakers with C2 level were carried out in a third-party test station. The accuracy of phase closing is within the ±0.5 ms closing window, effectively preventing the occurrence of closing inrush current.

Online learning MPC for switched systems with performance dependent mixed switching law

This paper explores online learning model predictive control (MPC) for switched systems with stable terminal constraints. In order to reduce the computational burden, we decompose the infinite horizon MPC into n finite horizons, and adopt adaptive dynamic programming (ADP) to assist MPC in online solving the optimal control problem in each finite horizon. Further, we use a set of stable terminal constraints to ensure both the convergence of online learning MPC in each finite horizon and the connection of adjacent finite horizons. In addition, in order to ensure the uniform ultimate boundedness (UUB) of the triggered switched systems, on the one hand, a novel performance dependent mixed switching law (PD-MSL) is proposed to both avoid frequent switching and take advantage of performance dependent decision-making; on the other hand, an analytical framework of the coupling between mode switching and event-triggering is proposed. Finally, the validity of the presented approach is demonstrated through simulations.

Switching of monoclonal antibodies against the calcitonin gene-related peptide or its receptor in migraine. Results from a Spanish Cohort

BackgroundSwitching between calcitonin gene-related peptide (CGRP) and monoclonal antibodies (mAbs) may be a beneficial strategy after discontinuation. The aim of this study was to evaluate switching outcomes of effectiveness/tolerability. MethodsRetrospective multicentric study of migraine patients who switched to another CGRP–mAb due to lack of tolerability or effectiveness (defined as <30% reduction of monthly headache days [MHD]). Assessment was performed before and 3 months after switch. The main outcome was the response rate of MHD. Secondary outcomes included other effectiveness/tolerability measures. Results90patients were included: 75(83.3%) women, 72(80%) chronic, and 18(20%) episodic migraine. Mean age was 45.9±11 years and mean duration of migraine was 29.2±12.4 years. Mean time under first mAb prior to switch was 10.4±4.9 months. Most frequent switches were erenumab-galcanezumab 38 (42.2%) and erenumab–fremanezumab 21 (23.3%). Lack of effectiveness (50/90, 55.6%) or tolerability (40/90, 44.4%) provoked switching. Most common adverse events (AEs) leading to discontinuation were constipation and flu-like syndrome in 16 (40%) patients each. Response rate (RR) of MHD 30%–50% occurred in 10 patients (11.1%), ≥50% in 32 (35.6%) and <30% in 48 (53.3%) patients. Significant reduction was proved after switch in MHD (20 [IQR:15–29] vs 13 [IQR:7–23]; p<.001) and monthly migraine days (15 [IQR:12–20] vs 10 [IQR:7–16]; p<.001). After switching, 38 (42.2%) experienced AEs, but tolerability improved in 50% of patients who discontinued due to lack of tolerability. RR compared between switches to different CGRP-mAb classes showed no differences. ConclusionSwitching may become an individualized strategy in migraine refractory patients who discontinue CGRP–mAbs due to lack of effectiveness/tolerability. In this study, supportive data are provided to the growing evidence of switch and future needs are highlighted.

Performance of capacitive deionizing membrane distillation (CDIMD) process for the organic sewage treatment and how operating parameters can affect it

To solve the fouling issue of traditional membrane distillation (MD) technique, a newly-designed hybrid purification system integrating capacitive deionization (CDI) with MD technology was established for the organic sewage treatment in this study, namely capacitive deionizing membrane distillation (CDIMD) technology. Complexes formation via cross-linking among protein, divalent cations, and polysaccharide, an archcriminal inducing MD fouling, was remarkably alleviated in the CDIMD system considering that negatively-charged organics were clearly divided away from those divalent cations in an electric field circumstance. The CDIMD performance was deeply explored in this study focusing on the impact mechanisms of core operational parameters. An appropriate increment of feed temperature (60–65 °C) and feed flow velocity (15.72–17.82 mm/s) contributed to the anti-fouling performance of CDIMD. Considering the side reactions at voltage >1.2 v, setting working voltage at around 1.2 v seemed to be optimal for CDIMD operation. With an overall consideration of pure water production and anti-fouling performance, a properly thicker CNTs layer (40–60 μm) efficiently enhanced the fouling mitigation of CDIMD. A frequent switching of electric field direction (9/1 min) facilitated the timely regeneration of electrode and composite membranes, accordingly promoting a reliable purification of organic wastewater by CDIMD technique.

The interactive effect of geopolitical risk and natural resource rent on political instability: Evidence from Ghana

AbstractBackgroundAccording to economists, political instability is regarded as a serious malaise harmful to economic development, which results in frequent switches of policies, creating instability to impede economic performance. The widespread political instability in many developing countries, along with its harmful effects on social welfare and economic performance, has heightened the interest of policymakers and economists in understanding the factors that contribute to political instability to inform better policy formulation. It is therefore imperative to examine the interactive effect of geopolitical risk and natural resource rent on political instability to provide strong empirical grounds for policy implementation.ObjectivesThis study employs a long time series dating from the period of 1824–2020 to examine how natural resource rent and geopolitical risk influence political instability in Ghana. First, we examine long‐run effects using linear methods. Second, we employ nonparametric methods to investigate the nonlinear link between natural resource rent and political instability as well as between geopolitical risk and political instability.MethodsThe study applied linear methods and nonparametric methods to historical time series data dating from the period of 1824–2020.ResultsThe results from the linear methods show that the interaction of natural resource rent and geopolitical risk exerts a positive and larger impact on political instability compared to their separate effects. The results from the nonparametric methods show a weak nonlinear link between these variables (i.e., natural resource rent, geopolitical risk, and political instability), although consistent with the linear long‐run results, the links are positive.ConclusionOverall, the results demonstrate that the observed positive relationship between natural resource rent and political instability is not just a recent phenomenon but holds for over more than 100 years in Ghana. Therefore, to attain a stable political environment, both long‐ and short‐term policies on political stability should be formulated.

Drug survival and risk factors for ADHD medication discontinuation in adults: A Danish Nationwide Registry-based cohort study.

Attention deficit hyperactivity disorder (ADHD) medication has proven effective for treating ADHD in adults, nonetheless previous studies have shown high rates of medication discontinuation. To assess drug survival and identify risk factors associated with discontinuation of ADHD medication. A nationwide registry-based cohort study in Danish adults who redeemed a prescription for ADHD medication for the first time between 2010 and 2015. All patients were followed for 5 years from the first redeemed prescription. Discontinuation was defined as a gap of 12 months between redemptions. Logistic regression analysis with odds ratio (OR) and Kaplan Meier analysis were used to examine risk factors (sex, age, socioeconomic status, substance use disorders, and comorbidities) associated with discontinuation. Twenty three thousand nine-hundred and sixteen patients with ADHD were identified. The 5-year overall drug survival was 29% in women vs. 23.5% in men. The risk of medication discontinuation was significantly higher in men compared to women, OR 1.26 (95% CI 1.19-1.34, p < 0.001). Adults aged 31-50 years had a significantly decreased risk of medication discontinuation compared to adults aged 18-30 years, OR 0.57 (95% CI 0.53-0.61, p < 0.001). Switching ADHD medication two times or three times or more significantly decreased the risk of discontinuation; OR 0.53 (95% CI 0.49-0.56, p < 0.001) and OR 0.26 (95% CI 0.23-0.30, p < 0.001), respectively. Substance use disorders and certain comorbidities were associated with medication discontinuation. Eating disorders, OR 0.71 (95% CI 0.64-0.78, p < 0.001), intellectual disabilities, OR 0.65 (95% CI 0.59-0.73, p < 0.001) and sleep disorders, OR 0.42 (95% CI 0.37-0.49, p < 0.001) were associated with continuation of ADHD medication. The 5-year overall drug survival was longer in women compared to men. Women with ADHD; adults aged 31-50; and patients with comorbid eating disorder; intellectual disability; sleep disorder and medication switching were individually associated with continuation of ADHD medication. Various factors were associated with medication discontinuation. Discontinuation should be acknowledged as a common phenomenon in patients with ADHD and calls for increased attention from the treatment responsible prescriber or team. Moreover, our findings suggest that timely, frequent medication switching, or temporary regimens may indeed represent optimal management strategies for a significant proportion of the ADHD population.

Online parameter identification based predictive pressure control for train electro-pneumatic braking systems with thermal effect

The electro-pneumatic braking system with ON/OFF solenoid valves has been widely used in trains due to its advantages and superiority. The undesirable impact of the thermal effect on the electro-pneumatic braking system leads to frequent valve switching, degradation of the pressure tracking performance and sometimes instability. This article presents an adaptive model predictive control approach to solve the pressure control problem under temperature uncertainty based on a switched unscented Kalman filter. First, a nonlinear switched dynamical model with the uncertain temperature parameter is derived for the electro-pneumatic braking system by comprehensively integrating its nonlinear, discontinuous dynamics and thermal effect. Using a switched unscented Kalman filter on the presented model of the system, the temperature parameter is accurately estimated to improve the model’s accuracy. Based on the corrected system model and the designed adaptive model predictive control method, the pressure tracking performance and the valves’ switchings of the electro-pneumatic braking system are improved, and the stability is guaranteed. The simulations and the experiments conducted for a braking system prototype confirm the performance validity of the proposed method.

A stable satellite routing algorithm based on a-star algorithm in dynamic networks

Abstract This paper focuses on solving the routing optimization problem under the dynamic topology of the satellite communication network. With the rapid development of low-earth-orbit (LEO) satellite network communication technology, the dynamically changing topology of satellite networks has brought about frequent link switching and triggered a large number of routing updates. This paper proposes an improved routing algorithm named the Stable A-Star Routing (SASR) algorithm. The SASR algorithm is based on the A-star algorithm and aims to reduce path-switching frequency and enhance path stability by optimizing the path selection strategy. Through detailed simulation experiments and performance evaluation, we verified the performance advantages of the SASR algorithm in terms of the number of path switches, the number of path hops, the route convergence time, and the occurrences of congestion in business under different business volumes, and conducted comparative studies with classic algorithms. The results show that the SASR algorithm offers obvious advantages in key performance indicators. Compared with the Dijkstra algorithm and the A-star algorithm, the average number of path switches can be reduced by 22% and 10%, respectively. It shows more prominent advantages under a larger business volume, providing an efficient and reliable solution for routing optimization under the dynamic topology of satellite communication networks.