Active Control Research Articles

The effects of cognitive behavioral therapy for insomnia in patients with cardiovascular disease: a systematic review and meta-analysis.

Insomnia affects up to 50% of patients with cardiovascular diseases (CVD) and is associated with poor clinical outcomes. Cognitive behavioral therapy for insomnia (CBT-I) is the recommended first-line treatment for insomnia, but little is known on the effects of CBT-I in patients with established CVD. We aimed to investigate the effects of CBT-I on insomnia symptom severity, sleep parameters, and daytime symptoms in patients with CVD and comorbid insomnia. Medline, Embase, PsycINFO and ClinicalTrials.gov were searched for randomized controlled and open trials up to December 2023. Study selection, data extraction, and risk of bias assessment (Cochrane's risk of bias 2 tool) were independently conducted by co-authors. Data were meta-analyzed using random-effects models. In all, 1275 records with five studies fulfilled the inclusion criteria (n=352 patients). Compared with active control groups, CBT-I significantly reduced insomnia severity post-treatment (standardized mean difference [SMD] = -0.90, 95%CI: -1.43, -0.37, p < .001), sleep onset latency (SOL), anxiety, and fatigue. Moreover, CBT-I significantly improved sleep quality (SMD = -0.77, 95%CI: -1.10, -0.45, p < .001) and sleep efficiency (SMD = 0.68, 95%CI: 0.12-1.25, p < .001). We regarded three RCTs as having low risk of bias, and had some concerns with another. Evidence from our analyses indicated that CBT-I seems to be effective for alleviating insomnia symptoms among CVD patients, largely in line with the results of previous meta-analyses in patients with insomnia. The limited sample size encourages more robust evidence from high-quality, large-scale trials with long-term follow-up. Registry: PROSPERO; Identifier: CRD4202448873; Title: Effects of cognitive behavioral therapy for insomnia in patients with coronary heart disease: A systematic review; URL: https://www.crd.york.ac.uk/PROSPERO/view/CRD42024488739.

Photonic Sintering as an Electrode Structuring Process to Improve Electrocatalytic Activity and Durability in Anion Exchange Membrane Water Electrolysis.

Hydrogen production via water electrolysis is essential for achieving carbon-free energy. However, enhancing the performance of these systems, particularly at the electrode level, remains challenging. Photonic sintering (PS) is proposed as a highly effective post-treatment method for electrodes, highlighting the importance of electrode design and optimization. PS significantly enhances the catalytic activity and durability of spinel-type copper-cobalt oxide-based anodes for the oxygen evolution reaction and Pt@C-based cathodes for the hydrogen evolution reaction, which are attributed to structural and chemical modifications, including active site control, optimized surface chemical bonding, improved catalyst-substrate adhesion, and generation of a reduced surface. PS-treated electrodes maintain well-preserved electrochemical active sites and pore structures, which are crucial for activation polarization and mass transport kinetics. Consequently, an anion exchange membrane water electrolysis cell with PS-treated electrodes achieved 89.57% cell efficiency, 3.91 W cm-2 area-specific power at 1.8 V, and a low degradation rate of 0.049 mV h-1 (at 0.5 A cm-2) and 0.136 mV h-1 (at 1.0 A cm-2) over 500 h. This research overcomes the traditional trade-off between activity and durability, indicating that PS can be widely applied across various energy fields, including electrochemical storage and conversion.

Active control of toroidal dipole and quasibound state in the continuum based on the symmetric and asymmetric hybrid dumbbell aperture arrays

Active control of toroidal dipole and quasibound state in the continuum based on the symmetric and asymmetric hybrid dumbbell aperture arrays

A randomized controlled trial of the effects of dog-assisted versus robot dog-assisted therapy for children with autism or Down syndrome.

Research with controlled or crossover designs in animal-assisted therapy have largely used control groups receiving no treatment or treatment as usual, which can potentially inflate the effects of these interventions. It is therefore not always clear whether this type of therapy has a positive effect on, for example, the social skills of children with special support needs. To address this, the current study compared children (7-16 years, n = 65) with autism or Down syndrome who received five sessions of dog-assisted therapy (n = 24; 9 female) with an active control group who received five similar sessions of robot dog-assisted therapy (n = 21; 8 female) and a no-treatment control group (n = 20; 8 female). The robot dog was capable of performing autonomous behavior and responding to the child's actions and verbalizations. Using parental questionnaires, we assessed children's social and emotional skills before and after the therapy sessions or waiting period and included a follow-up measurement after 4-6 weeks. On a group level, multilevel analyses showed that children who received dog-assisted therapy improved significantly more in terms of emotional attunement and emotion regulation than children in the two other conditions. No significant differences were found for social confidence, conversational attunement, social cognition, and social motivation. Change from post-test to follow-up was also less apparent. Yet, on a more individual level, when looking at the Reliable Change Index (RCI), most of the highest RCIs (within the 90th percentile) were found in the dog-assisted therapy group. In contrast, most of the lowest RCIs (within the 10th percentile) were found in the robot-assisted group. We discuss the pros and cons of a more individualized approach in this field of study and propose a possible alternative by focusing on interaction dynamics.

Active dual-band terahertz surface plasmonic wave excitation using graphene metasurfaces

The active control of surface plasmonic waves (SPWs) through metasurfaces holds significant potential for advancing on-chip optical components. However, recent research has primarily concentrated on actively modulating the propagation and coupling of SPWs at a single frequency. Here, we propose a dual-band SPW excitation strategy in the terahertz regime using two sets of orthogonally arranged metallic slit arrays based on electromagnetically induced transparency (EIT) coupling, which enables SPW excitations at two separate frequencies under orthogonal polarization incidences. Moreover, by placing graphene ribbons on top of the arrays to adjust the damping of dark mode resonance through capacitive coupling, we numerically demonstrate an active dual-band SPWs coupler with a high modulation depth achieving 86%. Our method is universal and has application prospects in future versatile integrated photonic devices, including data interaction and frequency division multiplexing.

Comparative Study on Active Suspension Controllers with Parameter Adaptive and Static Output Feedback Control

This paper presents a comparative study on active suspension controllers for ride comfort. Two types of active suspension controllers are designed and compared in terms of ride comfort: static output feedback (SOF) and parameter adaptive ones, which have identical controller structure. A quarter-car model is selected as a vehicle model. To date, LQR has been used as an active suspension controller. LQR is hard to implement in real vehicles due to the full-state measurement requirement. To avoid the full-state measurement of LQR, SOF control is selected as a controller structure in this paper. Suspension stroke and its rate are selected as sensor outputs for SOF and parameter active controllers. Two types of SOF controllers are designed. The first is the LQ SOF controller, designed with the state-space model and LQ cost function. The second is SOF controllers, designed by simulation-based optimization (SBOM) for the quarter-car model with nonlinear spring and damper. A parameter adaptive controller is designed with the recursive lease square (RLS) algorithm and its equivalent extended Kalman filter (EKF). For comparison, LQR is designed and used as a baseline. From simulation results, it is shown that the static output feedback and parameter adaptive controllers are equivalent to each other in terms of controller structure and ride comfort and which conditions are needed for better control performance on those controllers.

Effects of combining positive psychological intervention and lifestyle intervention on improving cardiovascular health for at-risk older adults: study protocol of a Chinese multicentric community-based randomised controlled trial (ACCOMPLI-CH)

IntroductionCardiovascular health is influenced by various factors, including not only physiological and behavioural ones but also psychological well-being. However, when developing comprehensive preventive approaches, psychological interventions often receive less attention,...

Homogeneous domination-based active shimmy control method for electric vehicle with hub motors considering unknown sensor measurement error and nonlinearity

Vehicles may generate wheel shimmy during motion, affecting driving stability and comfort. The use of hub motors increases the unsprung mass of vehicles, exacerbating this issue. How to actively eliminate wheel shimmy is crucial for the automotive industry. To accurately describe the shimmy phenomenon and eliminate it, a new seven-degree-of-freedom (7DOF) dynamic model that includes the steering system, suspension, and electric wheels is developed. By Lagrange’s theorem, the shimmy dynamics equations are derived, resulting in shimmy control state equations. Compared with other shimmy control state equations, these equations consider unknown sensor measurement errors and nonlinear terms. A homogeneous domination-based observer is constructed, which includes the unknown sensor measurement errors. Then, a homogeneous domination-based output feedback controller is designed for vehicle shimmy control. This controller has strong robustness and fast convergence. Via the Lyapunov method, we prove that the designed controller can stabilize the shimmy system asymptotically. Finally, numerical simulations and co-simulations were conducted. By comparing the response time, convergence speed, and overshoot with the SMC, the homogeneous domination-based controller demonstrates superior control performance under specific conditions.

Variable Step-Size Hybrid Filtered-x Affine Projection Generalized Correntropy Algorithm for Active Noise Control

Active Noise Control (ANC) is frequently utilized to minimize noise in industrial environments. However, the powerful pulses in industrial noise pose challenges to its application. Consequently, ANC systems necessitate a high-performance algorithm as a core component. In this process, the variable step-size strategy is the main approach for enhancing the ANC algorithm’s performance but ensuring robustness while improving performance remains a challenge. To address this problem, we propose a new ANC algorithm with a variable step size. This algorithm is derived from the Affine Projection Generalized Maximum Correntropy (APGMC) method, featuring a hybrid step-size and a new step-size approach achieved by modifying the mean square deviation (MSD). To showcase the practical effectiveness of the proposed algorithm, noisy audio from a real construction site was used for noise reduction control. Results show that the proposed algorithm effectively manages noise across frequency bands, with an improvement of approximately 16% to 19.2% compared to existing similar algorithms.

A novel biomechanical model of the proximal mouse forelimb predicts muscle activity in optimal control simulations of reaching movements.

Mice are key model organisms in neuroscience and motor systems physiology. Fine motor control tasks performed by mice have become widely used in assaying neural and biophysical motor system mechanisms. Although fine motor tasks provide useful insights into behaviors which require complex multi-joint motor control, there is no previously developed physiological biomechanical model of the adult mouse forelimb available for estimating kinematics nor muscle activity or kinetics during behaviors. Here, we developed a musculoskeletal model based on high-resolution imaging of the mouse forelimb that includes muscles spanning the neck, trunk, shoulder, and limbs. Physics-based optimal control simulations of the forelimb model were used to estimate in vivo muscle activity present when constrained to the tracked kinematics during reaching movements. The activity of a subset of muscles was recorded and used to assess the accuracy of the muscle patterning in simulation. We found that the synthesized muscle patterning in the forelimb model had a strong resemblance to empirical muscle patterning, suggesting that our model has utility in providing a realistic set of estimated muscle excitations over time when given a kinematic template. The strength of the similarity between empirical muscle activity and optimal control predictions increases as mice performance improves throughout learning of the reaching task. Our computational tools are available as open-source in the OpenSim physics and modeling platform. Our model can enhance research into limb control across broad research topics and can inform analyses of motor learning, muscle synergies, neural patterning, and behavioral research that would otherwise be inaccessible.

A robust active noise control algorithm using an adjustable arctangent function

Abstract The filtered-x least mean square (FxLMS) algorithm is a classic algorithm in the field of active noise control (ANC). However, its stability is compromised in the presence of impulsive noise, resulting in a poor noise reduction outcome. To address this issue, a normalized step size adjustable filtered-x arctangent least mean square (NAFxatanLMS) algorithm is proposed in this paper, which operates without the need of prior knowledge for threshold estimation. The algorithm employs an adjustable arctangent function as the cost function to perform a nonlinear transformation of the error signal. A compression factor is incorporated into the cost function to control the compression degree of the error signal, and an automated adjustment strategy is proposed to balance convergence speed and robustness of the algorithm. Finally, an improved variable step size strategy is introduced to further enhance the algorithm's performance. Simulation results demonstrate that, compared to other algorithms, the proposed NAFxatanLMS algorithm exhibits superior convergence speed and noise reduction ratio.

Two in one: a randomized controlled trial on an internet-based intervention (Lenio) for management of both chronic pain and depressive symptoms

The high prevalence of chronic pain and comorbid depression, along with their negative impacts on individuals and society, highlights the need for accessible and effective interventions. This study examined the feasibility, efficacy, and acceptability of Lenio, an Internet-based self-help intervention, combined with the COGITO smartphone application for managing these conditions. The randomized controlled trial involved an intervention group (IG) using Lenio and COGITO, an active control group (ACG) using a transdiagnostic app, and a wait-list control group (WCG) receiving usual treatment. Lenio incorporates cognitive behavioral therapy and third-wave techniques, supported by COGITO’s gamified daily exercises to enhance adherence. Across 263 participants assessed at three intervals over 16 weeks, the IG showed significant improvement in somatic-affective depressive symptoms compared to the WCG post-intervention and both control groups at follow-up. However, the ACG outperformed the IG in managing pain at post-intervention though these effects did not persist until follow-up. The interventions were well-received and feasible, with older participants benefiting more from the Lenio/COGITO combination. Lenio and COGITO could bridge gaps to conventional therapy, potentially easing pain by enhancing psychological well-being and coping strategies. Future studies should investigate tailored interventions for chronic pain and their long-term effectiveness.ProtocolFull trial protocol can be accessed via DOI: 10.1186/s13063-023-07440-8.Clinical trial registrationhttps://drks.de/register/de/trial/DRKS00026722/preview, identifier DRKS-IDDRKS00026722.

Perioperative teriparatide for preventing proximal junctional kyphosis and failure in patients with osteoporosis after adult thoracolumbar spinal deformity surgery: a prospective randomized controlled trial.

This randomized controlled trial is aimed at investigating and comparing the effects of perioperative teriparatide and denosumab as an active control for preventing proximal junctional kyphosis (PJK) and proximal junctional failure (PJF) in patients with osteoporosis after adult spinal deformity (ASD) surgery. A total of 64 patients with osteoporosis, who planned to undergo ASD surgery, were randomly assigned to the teriparatide and denosumab groups. Treatment with teriparatide or denosumab in both groups was conducted from 3months preoperatively to 3months postoperatively based on the standard regimen for each medication. The primary outcome was PJK and PJF incidence within 1year after ASD surgery. The secondary outcomes were patient-reported outcomes (PROs), bone mineral density (BMD), and dual-energy X-ray absorptiometry (DEXA) t-score of the hip. The teriparatide group showed a lower incidence of PJK than the denosumab group (17.2% vs. 33.3%), although this difference was not statistically significant (p = 0.165 in a modified intention-to-treat (mITT) analysis). Furthermore, the teriparatide group exhibited a significantly lower incidence of PJF than the denosumab group (3.4% vs. 22.2%; p = 0.034 in the mITT analysis). As for the secondary outcomes, no significant differences in BMD of the hip were observed between the two groups at the 1-year follow-up. The teriparatide group showed significantly improved postoperative VAS for back pain and EQ-5D score. Perioperative teriparatide treatment of patients with osteoporosis after ASD surgery effectively reduced PJF incidence and postoperative back pain.

The Effectiveness of Reminiscence Interventions on Depression and Depressive Symptoms in Community-dwelling Older Adults without Significant Cognitive Impairment: A Systematic Review.

Along with the global rise in the population of older adults, addressing depression among this population has become a critical public health concern. Reminiscence therapy is one of the interventions shown to be effective in reducing depression and depressive symptoms. To systematically summarize the effectiveness of reminiscence interventions in reducing depression and depressive symptoms in community-dwelling older adults without significant cognitive impairment. The literature search was conducted through four electronic databases: PubMed, CINAHL, PsycINFO, and Scopus for studies published in English. Risks of bias were evaluated using the Cochrane Risk of Bias 2 tool and the Joanna Briggs Institute Quality Appraisal Instrument. The systematic review included 11 studies involving 650 community-dwelling older adults, with mean ages ranging from 65.3 to 78.7. Nine articles found reminiscence therapy effective in alleviating depression and depressive symptoms in community-dwelling older adults without significant cognitive impairment. Structured reminiscence interventions were effective in reducing depression and depressive symptoms in six out of seven studies. Group reminiscence interventions demonstrated significant improvements in depression in 87.5% of studies. Memories triggers, suggested by four included studies, were practical tools to help initiate reminiscence sessions. All included studies were rated as having a low risk of bias. Reminiscence has the potential as a valuable and effective treatment for depression and depressive symptoms in community-dwelling older adults without significant cognitive impairment. Future research should focus on exploring diverse modalities, incorporating active control groups, and having longer follow-up periods to assess sustained benefits.

Tailored Adherence Incentives for Childhood Asthma Medications

Differential adherence to efficacious preventive medications is one potentially modifiable driver of racial disparities in childhood asthma outcomes. To determine the effect of a financial incentive-enhanced intervention on adherence to inhaled asthma preventive medication in a high-risk, predominantly racially minoritized cohort of children with asthma. This was a randomized clinical trial conducted from September 2019 through June 2022 at a large mid-Atlantic pediatric health system in the US. Children were eligible if they were between 5 and 12 years old, prescribed a preventive inhaler for daily use, and had at least 2 asthma exacerbations requiring systemic steroids in the preceding year. Data were analyzed from December 2022 to December 2024. Inhaled medication use was monitored using electronic inhaler sensors over a 7-month period. Families who completed a 1-month run-in interval were randomized to 1 of 3 arms for a 3-month experiment interval: (1) daily text message medication reminders, weekly adherence feedback, and gain-framed, financial incentives of up to $1 per day (full intervention); (2) daily text message medication reminders and weekly adherence feedback (hybrid intervention); or (3) no reminders, feedback, or incentives (active control). Medication adherence monitoring then continued for a 3-month observation interval, where all arms reverted to active control conditions. The primary outcome was adherence to inhaled maintenance medication during the experiment; secondary outcomes included adherence during the observation phase. The study was powered to detect a difference in average monthly adherence between the full intervention and active control condition. Of the 106 children randomized, 99 had at least 1 month of monitoring data (56 male [57%] and 43 female [43%]; mean [SD] age, 8.0 [2.3] years). Most participants (81 [82%]) identified as non-Hispanic Black and demographic and clinical characteristics were similar across study arms. During the experiment interval, participants receiving the full intervention had a 15-percentage point (95% CI, 2-29 percentage points) higher inhaled maintenance medication adherence compared with participants in the active control. There was no evidence of adherence differences in the observation interval. While a financial incentive-enhanced mobile health intervention led to higher inhaled preventive medication adherence as compared with the active control group, there was no evidence for enduring effect after the intervention components ceased, consistent with other studies that include financial incentives to encourage behavior change. ClinicalTrials.gov Identifier: NCT03907410.

Active Fault-Tolerant Control to Prevent Hanger Bending During Configuration Transformation of 3D Cable System in Suspension Bridges

Active Fault-Tolerant Control to Prevent Hanger Bending During Configuration Transformation of 3D Cable System in Suspension Bridges

Synergy-based robotic quadruped leveraging passivity for natural intelligence and behavioural diversity

Abstract Quadrupedal animals show remarkable capabilities in traversing diverse terrains and display a range of behaviours and gait patterns. Achieving similar performance by exploiting the natural dynamics of the system is a key goal for robotics researchers. Here we show a bioinspired approach to the design of quadrupeds that seeks to exploit the body and the passive properties of the robot while maintaining active controllability on the system through minimal actuation. Utilizing an end-to-end computational design pipeline, neuromechanical couplings recorded in biological quadrupeds are translated into motor synergies, allowing minimal actuation to control the full structure via multijoint compliant mechanical couplings. Using this approach, we develop PAWS, a passive automata with synergies. By leveraging the principles of motor synergies, the design incorporates variable stiffness, anatomical insights and self-organization to simplify control while maximizing its capabilities. The resulting synergy-based quadruped requires only four actuators and exhibits emergent, animal-like dynamical responses, including passive robustness to environmental perturbations and a wide range of actuated behaviours. The finding contributes to the development of machine physical intelligence and provides robots with more efficient and natural-looking robotic locomotion by combining synergistic actuation, compliant body properties and embodied compensatory strategies.

Activity and control of methanol metabolism in the seawaters across the estuary–coast–shelf continuum

AbstractMethanol metabolism is important in marine carbon cycling, while the control of metabolic mode and activity remains poorly constrained, particularly in coastal waters. Here, we investigated the biogeochemical cycling of methanol across the estuary–coast–shelf continuum of the East China Sea. Methanol concentrations varied from &lt; 12.3 to 617.3 nmol L−1, decreasing from coast to shelf. The total uptake rates of methanol in the estuary (143.4 ± 29.6 nmol L−1 d−1) and coast (92.3 ± 86.9 nmol L−1 d−1) were much higher than those in the shelf (20.4 ± 33.8 nmol L−1 d−1). While methanol was primarily used as an energy source in the coast and shelf (oxidation/total uptake: &gt; 72.2%), much more methanol was channeled to the biomass (assimilation/total uptake: 31.9–49.7%) in the estuarine waters. As supported by incubation experiments with the addition of nutrients and other C1 compounds, enhanced methanol assimilation suggests the use of methanol as a supplementary source of carbon, while reduced methanol oxidation indicated the competitive utilization of other C1 compounds as an energy source. The estuary and coastal waters acted as net sources of methanol to the atmosphere, while ventilation accounted for &lt; 5.7% of total loss, suggesting that microbial consumption was the dominant pathway of methanol removal. In the shelf, atmospheric deposition replenished surface methanol pools and contributed up to 17.5% ± 16.9% of microbial consumption. These results provided insights into the control of methanol metabolism and assessed the relative importance of different methanol sources and sinks along the estuary–coast–shelf continuum.

Nonlinear Robust Control of Turbofan Engine Based on Improved Active Disturbance Rejection Control with Cascade Observer

Nonlinear Robust Control of Turbofan Engine Based on Improved Active Disturbance Rejection Control with Cascade Observer

Active-Controlled Trial Design for HIV Prevention Trials With a Counterfactual Placebo.

In the quest for enhanced HIV prevention methods, the advent of antiretroviral drugs as pre-exposure prophylaxis (PrEP) has marked a significant stride forward. However, the ethical challenges in conducting placebo-controlled trials for new PrEP agents against a backdrop of highly effective existing PrEP options necessitate innovative approaches. This manuscript delves into the design and implementation of active-controlled trials that incorporate a counterfactual placebo estimate-a theoretical estimate of what HIV incidence would have been without effective prevention. We introduce a novel statistical framework for regulatory approval of new PrEP agents, predicated on the assumption of an available and consistent counterfactual placebo estimate. Our approach aims to assess the absolute efficacy (i.e., against placebo) of the new PrEP agent relative to the absolute efficacy of the active control. We propose a two-step procedure for hypothesis testing and further develop an approach that addresses potential biases inherent in non-randomized comparisons to counterfactual placebos. By exploring different scenarios with moderately and highly effective active controls and counterfactual placebo estimates from various sources, we demonstrate how our design can significantly reduce sample sizes compared to traditional non-inferiority trials and offer a robust framework for evaluating new PrEP agents. This work contributes to the methodological repertoire for HIV prevention trials and underscores the importance of adaptability in the face of ethical and practical challenges.