Nonlinear dynamics of taillight effect in mixed traffic flow driven by competing visual delay and V2X communication

• Adaptive cascaded control applied to grid-forming inverter. • Voltage direct-tracking using a model reference adaptive controller. • Controller validated through extensive tests with wide parameter variations. • Comparison between adaptive and fixed-gain control techniques. • Model-free adaptive control applied to microgrid synchronization. This paper presents a cascaded adaptive control strategy for the inner loop of a grid-forming inverter. The control structure combines an inner proportional regulator for current limiting with an outer Model Reference Adaptive Controller (MRAC) for voltage regulation, tracking references from the primary control layer. The primary control utilizes a droop mechanism with virtual impedance to enhance active and reactive power decoupling. For grid-reconnection scenarios, the secondary control implements an adaptive proportional-integral-derivative (PID) controller in the synchronization loop, effectively compensating for non-deterministic communication delays while maintaining a simple design framework. The control system is validated through hardware-in-the-loop (HIL) simulations, evaluating five critical scenarios: steady-state operation (islanded and grid-connected), reconnection transients, unplanned islanding, and a microgrid fault. A comparative analysis with a fixed-gain controller demonstrates the superior performance of the proposed adaptive approach in managing uncertainties and dynamic grid conditions, with consistent improvements across all scenarios and error reductions of up to 90% in key performance indices.

Event-triggered cooperative control of connected vehicle platoons with distributed unbounded communication delays and unknown external disturbances

This paper proposes a novel adaptive control framework for load frequency regulation (LFC) in modern power systems with renewable energy integration and communication delays. A Single Perceptron Proportional-Integral (SPPI) controller optimized using Harmony Search (HS) is designed for single-area systems, while a cascaded SPPI-PID structure is developed for two-area networks. Unlike conventional fixed-parameter controllers, the proposed approach adapts online to varying operating conditions and disturbances. Simulation studies under step load changes, random load variations, and wind power fluctuations demonstrate superior performance of the proposed controllers. For single-area systems, the SPPI controller achieves overshoot as low as [Formula: see text], settling times between 9 and 21s, and IAE ranging from 0.00176 to 0.312. In two-area systems, the cascaded SPPI-PID controller reduces peak-to-peak deviations to [Formula: see text], with settling times from 3 to 109s and IAE values between 0.00115 and 0.1854. A sensitivity analysis with ± 20% variations in inertia, load damping, and governor speed regulation confirms the robustness of the proposed approach. A frequency-domain robustness analysis using Bode plots further verifies satisfactory stability margins. In addition, a real-time validation has been performed to further confirm the practical applicability and real-world performance of the proposed control framework under realistic operating conditions. These results indicate that the HS-optimized SPPI and cascaded SPPI-PID controllers provide an effective, reliable, and robust solution for frequency regulation in modern interconnected power systems.

Multimorbidity affects most older adults in home health care (HHC), leading to inappropriate polypharmacy and increased risks for adverse outcomes. While deprescribing can mitigate these risks, fragmented communication during hospital-to-home transitions remains a major barrier. This study explored stakeholder perspectives on using telehealth to facilitate deprescribing for older adults with multimorbidity while receiving post-acute HHC. We conducted semi-structured interviews with 44 stakeholders across 12 U.S. states, including 14 HHC patients and 30 clinicians (physicians, nurse practitioners, pharmacists, and HHC nurses). Guided by the socioecological model of deprescribing, interviews explored factors across individual, interpersonal, organizational, and societal levels associated with telehealth use in deprescribing. Analysis followed a phased, iterative approach with independent double-coding and interprofessional team consensus to ensure credibility. Findings categorized telehealth as a promising tool to align medications with the "4Ms" (Medications, Mentation, Mobility, and What Matters) through goal-concordant deprescribing. At the individual level, stakeholders noted that telehealth readiness depended on patient cognition and digital literacy. At the interpersonal level, telehealth facilitated real-time multidisciplinary "virtual huddles" that reduced communication delays but could occasionally overwhelm patients and may be logistically challenging to schedule. Organizational barriers included reimbursement constraints and complex synchronous scheduling. Societal factors include equitable access for rural or low-income populations, populations who may benefit the most from telehealth-enabled deprescribing due to challenges in accessing care. Stakeholders emphasized a hybrid approach which pairs virtual prescriber consultation with in-home support of a clinician to provide context and assist with implementation for patient-centered deprescribing. Telehealth can support goal-concordant deprescribing during post-acute care transitions in HHC. A hybrid model, one that combines remote prescriber consultations with in-home clinician support, is the preferred approach to bridge coordination gaps. To maximize impact, future efforts are needed to improve reimbursement, infrastructure, and scheduling to integrate telehealth into routine deprescribing workflows.

This article addresses the formation control of under-actuated multiple autonomous surface vehicles (MASVs) with input quantization under communication delay conditions, which is influenced by external marine disturbances and internal model uncertainties. A two-level distributed guidance and quantization control architecture based on the Nussbaum function is proposed. At the communication level, a time-delay distributed event-triggered extended state observer (ESO) is introduced to estimate the state of the single virtual leader, thereby further conserving communication resources. At the control level, the distributed formation guidance laws based on ESO are proposed in the kinematic subsystem, enabling effective tracking of the ideal trajectory while estimating the states of neighboring agents and unknown ocean disturbances. In the dynamics subsystem, a fuzzy logic system is used to estimate the uncertain terms within the model, and a linear model is introduced to handle the input quantization process. Additionally, the fuzzy adaptive quantization tracking control laws based on the Nussbaum function are proposed to achieve accurate tracking of the guidance signals and reduce actuator execution frequency, which makes the proposed scheme more applicable to practical marine engineering scenarios. The stability of the designed control structure is proven based on stability theory, and all signals within the closed-loop control system are uniformly ultimately bounded. Simulation experiments validate the rationality and effectiveness of the proposed method.

In modern-day, real-time challenges are increasing in Load frequency control (LFC). This work presents a novel reduced-order generalized active disturbance rejection control (RGADRC) strategy. The generalized structure of ADRC incorporates detailed plant information in the design. The proposed work incorporates an innovative hyperbolic non-linear error function in a reduced-order extended state observer (RESO). This refinement in observer gain due to non-linear gain variation improves the time domain specification of the response, specifically in terms of overshoot, settling time, and error indices. The proposed approach is simulated for various delayed single area non-reheat and reheat systems, including non-linearities like Generation rate constraint (GRC) and Governor dead band (GDB). Further, the proposed strategy is extended for two-area PV-thermal hybrid systems with non-linearity, and a practical IEEE 39 Bus New England system, which is a widely used benchmark system in power system studies. The robustness of this method is analyzed under the condition of + 50 % parametric uncertainty in gain and time constant simultaneously. This design technique effectively manages non-linearities, constant, and varying time delays, and assesses cyber-attack vulnerabilities. Further, the real-time challenges in the IEEE system are studied for multistep load variations with communication delay.

This article proposes a resilient control framework for securing cyber-physical systems, specifically addressing large-scale interconnected systems operating over constrained networks subject to communication delays and deception attacks. A dynamic event-triggered mechanism (DETM) is proposed to reduce network traffic while preserving control performance. Using the Lyapunov–Krasovskii approach, sufficient conditions guaranteeing mean-square stability with an H ∞ performance level are derived, and a decentralised dynamic output-feedback (DOF) controller is designed. To solve the resulting bilinear matrix inequalities (BMIs) and avoid conservative transformations, a homotopy-based iterative algorithm for the co-design of the controller and DETM parameters is employed. The new control scheme is validated through extensive Monte Carlo simulations on a multi-area power system, demonstrating the efficacy of the approach in maintaining system stability and performance under various attack scenarios, thereby making a significant contribution to the security of complex systems in networked environments.

Vehicle platooning in urban traffic is employed for enhancing efficacy by minimizing the fuel consumption and improving road safety. Nevertheless, the dynamic and uncertain nature of urban traffic creates various challenges for successful platooning. The major intent of this research is to present a Tangent Secretary Bird Optimization Algorithm (TSBOA) for vehicle platooning in urban traffic scenarios. Here, various multi-agent constraints, namely spacing, velocity range, communication delay, and speed, are included to establish which vehicle platooning effectively increases the throughput at intersections. Here, the Model Predictive Control (MPC) is established by utilizing the TSBOA method, where this model relies on vehicle connectivity through Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2 V) communication. Further, the TSBOA method is developed by integrating two optimization methods, such as Tangent Search Algorithm (TSA) and Secretary Bird Optimization Algorithm (SBOA). Furthermore, the distance, position, spacing error, and velocity error attained by TSBOA are 1.1068, 958.05, 0.0002, and 0.0015 m/s.

ABSTRACT Agricultural extension services play a critical role in improving farm productivity and ensuring sustainable rural livelihoods, yet their effectiveness is often limited by persistent resource constraints. This study investigates how such constraints influence the effectiveness of extension services in Juaben Municipality, Ghana. A qualitative descriptive exploratory design was employed, involving 14 smallholder farmers, two focus group discussions, and one key informant interview with an extension officer. Thematic analysis revealed that although farmers regard extension advice as valuable, its impact is weakened by delays in delivery and ineffective communication. Extension officers are perceived as committed, but their work is hindered.

Advances in high-throughput neural recording technologies enable simultaneous measurement of activity across multiple brain regions in behaving animals, producing datasets of unprecedented scale and richness. Interpreting these data remains challenging due to the bidirectional and temporally offset nature of inter-regional communication, where feedforward and feedback signals are superimposed within neural populations. We introduce BiXformer, a bidirectional cross-attention transformer that disentangles these interactions by decomposing inter-regional communication into causal and acausal streams using directionally masked attention. By enforcing temporal constraints within attention heads, BiXformer recovers low-dimensional, directed latent dynamics and estimates communication delays without relying on linearity or stationarity assumptions. We validate the model on synthetic datasets with known ground-truth delays, demonstrating accurate recovery of both latent structure and inter-regional timing. Applied to simultaneous neural-behavioral recordings and multi-region neural recordings during a movement task, BiXformer reveals interpretable, temporally structured components consistent with the coexistence of sensory feedback and motor-related signals. These results establish BiXformer as a flexible framework for uncovering dynamic, directed communication in complex neural circuits.

Natural and man-made disasters such as floods, fires, earthquakes, gas leakages, landslides, and industrial acci- dents cause severe damage to human life, infrastructure, and the environment. Traditional disaster management systems mainly depend on manual monitoring and delayed communication mechanisms, which often create challenges in disaster preparedness, emergency response efficiency, and public safety. Due to the increasing occurrence of disasters and the rapid advancement of smart technologies, there is a growing need for intelligent systems capable of monitoring environmental conditions and generating emergency alerts in real time. Recent advancements in Internet of Things (IoT), Artificial Intelligence (AI), cloud computing, and wireless communication technologies have enabled the development of smart disaster monitoring systems. Modern IoTbased disaster management platforms allow continuous monitoring of environmental con- ditions using smart sensors and real-time communication sys- tems. These technologies improve disaster detection accuracy, reduce emergency response delays, and enhance rescue coordi- nation efficiency. However, many existing disaster management systems mainly focus on basic monitoring functionalities and lack advanced capabilities such as AI-based predictive analysis, centralized cloud monitoring, GPSbased emergency tracking, and scalable IoT infrastructures. The proposed AI-Enabled Smart Disaster Management System using IoT Devices is designed as a centralized environmental monitoring and emergency response platform that integrates IoT sensors, Artificial Intelligence, cloud communication technologies, GPS tracking, and automated emergency alert mechanismsinto a single system. The system uses smart sensors such as temperature sensors, smoke sensors, gas sensors, vibration sensors, and water level sensors for continuously monitoring environmental conditions. IoT devices such as ESP32 and Raspberry Pi process sensor data and communicate with cloud servers through wireless communication technologies.c Whenever dangerous environmental conditions exceed pre- defined safety thresholds, the system automatically generates emergency alerts through SMS notifications, email services, mobile applications, and GPSbased location sharing systems. The proposed system provides a secure, scalable, reliable, and cost-effective solution for improving disaster preparedness, public safety, emergency response coordination, and smart city disaster management operations

Sixth-generation (6G) networks are likely to support advanced Internet of Vehicles (IoV) applications that have rigid latency, reliability, and computation demands. Nevertheless, efficient task offloading is a challenging problem because vehicle environments are characterized by mobility, changing channels, varying task requirements, constrained edge resources, and growing energy demands. To address these issues, this study presents an Optimized Multi-Tier Task Offloading Strategy (OMTOS) for sustainable IoV systems. The proposed framework comprises a four-tier computing architecture comprising vehicles, roadside units (RSUs), mobile edge computing (MEC) servers, and cloud infrastructure. The generalized latency-energy optimization problem is formulated to allocate tasks across these levels, accounting for task due dates, resource capacity, communication delay, computation delay, and energy consumption. To address dynamic offloading, OMTOS employs a centralized training and decentralized execution (CTDE) based multi-agent Soft Actor-Critic (SAC) method, where the vehicle agents can make decentralized offloading decisions with centralized critics guiding the coordinated learning process during training. It is tested against rule-based and heuristic as well as deep reinforcement learning and various multi-agent reinforcement learning baselines, including LE, EO, RO, GO, DQN, DDPG, SAC, MADDPG, and MAPPO. The aforementioned results reveal that OMTOS achieves low average delay, low energy consumption, a high task success rate, and high convergence compared to the competing methods. Sensitivity analysis also indicates that the latency and energy weightings can be changed to suit various IoV service requirements, including delay-critical safety services, and energy-conscious delay-tolerant services. These results show that OMTOS offers an adaptive and sustainable task-offloading tool in 6G-enabled IoV environments.

Background48,XXYY syndrome is a rare sex chromosome aneuploidy (SCA) characterized by neurodevelopmental deficits and medical comorbidities. The limited information available in the literature is almost exclusively limited to postnatally diagnosed cases. This study aims to describe the early medical and developmental features of prenatally identified 48,XXYY infants, with comparisons to 47,XYY, 47,XXY cohorts, and typical populations, as well as previously reported postnatally diagnosed 48,XXYY cases.MethodsThe eXtraordinarY Babies Study prospectively follows children prenatally identified to be at high risk for SCA with annual medical and neurodevelopmental evaluations. Data presented herein include the prevalence of medical conditions, developmental milestones, developmental and adaptive functioning assessment scores, and therapy utilization in participants confirmed to have 48,XXYY. Comparisons were made between this cohort and the typical population, infants with 47,XYY and 47,XXY also enrolled in the eXtraordinarY Babies Study, and a 2008 cohort of individuals postnatally identified 48,XXYY.ResultsInfants with 48,XXYY exhibited a range of early medical features, including high rates of feeding and GI disorders (breastfeeding difficulties, gastroesophageal reflux, and eosinophilic esophagitis), allergic disorders (food allergies and environmental allergies), and hypotonia. Developmental and adaptive functioning scores indicated delays in motor, communication, and social domains, with nearly all infants receiving speech therapy, physical and/or occupational therapy. Comparisons with the 47,XYY and 47,XXY cohorts revealed more medical and developmental challenges in the 48,XXYY group, however there was variability and some overlap with both the general population and sex chromosome trisomy conditions. Additionally, comparison to the 2008 postnatally identified 48,XXYY cohort indicated that while prenatal diagnosis allowed for earlier intervention, developmental outcomes in the first years of life were similar between the two groups.Conclusions48,XXYY diagnosed prenatally facilitates early monitoring, anticipatory guidance, and proactive referrals for medical evaluations and intervention, given developmental delays and medical challenges are more common in infancy and early childhood compared to the general population and trisomy SCAs. These findings provide valuable insights for genetic counselors and healthcare providers, emphasizing the spectrum of medical and developmental findings and importance of early and proactive care to support individual outcomes. Prospective study of this prenatally identified cohort will provide important natural history and phenotypic variability in XXYY, as well as identification of predictors of health and developmental outcomes.

Few studies have comprehensively examined, within the same population, the roles of both prenatal and postnatal factors in the association between family socioeconomic status (SES) and early infant neurodevelopment. Four thousand seven hundred ninety-one singleton live births from November 1, 2017, to December 31, 2022, were included. Family SES was classified as low or high using latent class analysis of family income, parental education, and occupation. Prenatal maternal psychological status, pregnancy complications, and birth outcomes were classified as favorable or unfavorable. Health-related parenting practices was scored based on breastfeeding duration (≥ 6 months), sleep duration (12-16h/day), outdoor activity (≥ 0.5h/day), and screen time (none), with each factor scored as 0 or 1 (higher scores indicating healthier parenting practices). Infant neurodevelopment at 1 year was assessed using Bayley Scales of Infant and Toddler Development, Third Edition (Bayley-III) screening test, across five domains: cognition, receptive communication, expressive communication, fine motor, and gross motor. Each domain was categorized as either competent or 'emerging or at risk'. Low family SES was associated with a higher risk of being classified as 'emerging or at risk' in receptive communication after adjusting for covariates (risk ratio [RR], 1.42; 95% confidence interval [CI], 1.24-1.62; P<.001), with health-related parenting practices partially mediating this association (mediated proportion, 6.3% (0.9% to 14.1%)).In infants from high-SES families, 0-2 health-related parenting practices scores exerted a more pronounced effect, accounting for nearly one-third of cases (attributable risk percentage, 30.97%). Joint analysis showed infants from low-SES families with 0-2 health-related parenting practices scores had the highest risk compared with infants from high-SES families with 3-4 health-related parenting practices scores (RR, 1.73; 95%CI, 1.41-2.12; P<.001). Health-related parenting practices partially mediated the relationship between family SES and early infant neurodevelopment, suggesting that while improving health-related parenting practices may reduce disparities, additional strategies are required to address the elevated risk of receptive communication delays among infants from low-SES families. Additionally, unhealthy parenting practices were associated with a higher risk of neurodevelopmental delay even in high-SES families, underscoring the universal importance of early parenting interventions.

This paper investigates the relay cooperative tracking problem of networked nonlinear multi-agent systems under network delays, and introduces an event-triggered control strategy to reduce communication transmission. When the target crosses the monitoring area, the nearby agents will capture its distance from the target. The purpose of this study is to track targets traversing the monitoring area using a relay cooperative tracking strategy. To achieve more efficient target tracking by the agent, this paper designs a dynamic event-triggered mechanism on own error of the agent rather than errors between agents. This mechanism reduces the communication transmission between agents, thereby avoiding the impact of network delay in agent communication. The results show that the proposed relay event-triggered control strategy effectively enhances the tracking performance of the pursuing agents with respect to the target and significantly reduces the communication burden on the network. Additionally, the strategy incorporates a delay compensation mechanism to mitigate the effects of communication delays. Finally, the effectiveness of the proposed method is validated through simulation experiments.

Bloodstream infections are associated with substantial morbidity and mortality. Rapid diagnostic tests (RDTs) have been shown to improve clinical outcomes when combined with antimicrobial stewardship (AMS) programmes. The lack of systematic reporting of rapid antimicrobial susceptibility testing (AST) can cause delays in communication to prescribers and in targeted antimicrobial treatment. To evaluate the impact of a structured intervention in integrating systematic RAST and AMR detection within an existing AMS programme. The main outcomes were time to report (from Gram to AST report) (TTR), time from Gram to AMS recommendation (TAMS) and time to change antimicrobial prescription (TCAP) following this recommendation. We performed a contemporaneous comparative study evaluating episodes of bacteraemia managed with rapid AST (RAST) and/or antimicrobial resistance mechanisms (AMR) detection integrated into AMS workflows versus episodes managed without RAST/AMR during the same implementation period. Episodes managed with RAST/AMR had significantly shorter TTR, TAMS and TCAP compared with episodes without RAST/AMR (median absolute reduction in hours of 31, 37 and 24, respectively). There was no significant reduction in duration of antimicrobial therapy, hospital length of stay (LOS) or mortality in the RAST/AMR group. Compliance with AMS recommendations was high (90%). As reported previously, RAST or AMR detection in combination with AMS was an effective strategy for targeting antimicrobial therapy. This intervention demonstrates that structured implementation of RAST/AMR detection, when embedded within the AMS workflow, can substantially shorten time to targeted therapy even in settings with pre-existing AMS infrastructure.

Byzantine-resilient distributed consensus for autonomous satellite constellation via optical inter-satellite links

Mitigating delay and poor transparency in ground vehicle teleoperation based on the predicted trajectory guidance control framework.

This article analyzes the effects of communication delays on the stability of sampled data systems. In order to derive less conservative stability conditions for the system under consideration, certain zero equalities are typically introduced. These zero equalities are crucial for minimising conservativeness by establishing the link between communication delay and sampling time. However, the application of these zero equations can become problematic when the time delay exceeds the sampling period. To resolve this issue, the paper utilises a delay-decomposing approach, which validates the introduction of the zero equations. Leveraging this segmentation method, a new Lyapunov-Krasovskii functional has been developed, and these zero equations are used to establish an improved stability criterion. Numerical examples demonstrate the effectiveness and benefits of the proposed criterion.