Search Results (286)

This paper examines solutions to mathematical models based on functional-differential equations, which have applications in immunology. This new approach allows us to study discontinuous solutions that more accurately depict real-world phenomena. It also enables us to exploit the information contained in the initial function. We discuss immunology models by generalizing existing impulsive delay differential equation models to the proposed form. The new phase space introduced here enables a unified approach to continuous and impulsive solutions that were previously studied, as well as the development of new properties that depend on the initial function. To illustrate our work, we present extensions of current immunological models and demonstrate some applications in fields beyond immunology. This paper focuses on establishing the theoretical basis for modifying models based on delayed differential equations, which are not limited to immunology. It also provides some examples. Full article

In the paper we consider the pulsed disturbances caused in the ionosphere by an extreme G5-level geomagnetic superstorm on 10 May 2024, and by the X1.0 and M-class solar flares on 8 May 2024, which preceded the storm. Particular attention is paid to the short-term delays and the sequence of disturbance appearance in the ionosphere and geomagnetic field during these extreme events. The results of a continuous Doppler sounding of the ionosphere on an inclined radio path with a sampling frequency of 25 Hz were used, as well as the data of a ground-based mid-latitude fluxgate magnetometer LEMI-008, and an induction magnetometer IMS-008, which operated with a sampling frequency of 66.6 Hz. Ionization of the ionosphere by the intense X-ray and extreme ultraviolet radiation of solar flares was accompanied by the equally sudden and similarly timed disturbances in the Doppler frequency shift (DFS) of the ionospheric signal, which had an amplitude of 2.0–5.8 Hz. The largest pulsed burst in DFS was registered 68 s after an X1.0 flare on 8 May 2024 at the time when the change of the X-ray flux was at its maximum. Following onto the effect in the ionosphere, a disturbance in the geomagnetic field appeared with a time delay of 35 s. This disturbance is a secondary one that arose as a consequence of the ionosphere response to the solar flare. It was likely driven by the contribution of ionospheric currents and electric fields, which modified the Earth’s magnetic field. On 10 May 2024, a G5-level geomagnetic superstorm with a sudden commencement triggered an impulsive reaction in the ionosphere. A response in DFS at the calculated reflection altitude of the sounding radio wave of 267.5 km was detected 58 s after the commencement of the storm. The sudden impulsive changes in Doppler frequencies showed a bipolar character, reflecting complex dynamic transformations in the ionosphere at the geomagnetic storm. Consequently, the DFS amplitude initially rose to 5.5 Hz over 86 s, and then its sharp drop to $-3.2$ Hz followed. Using the instruments that operated in a mode with a high temporal resolution allowed us to identify for the first time the impulsive nature of the ionospheric reaction, the time delays, and the sequence of disturbance appearances in the ionosphere and geomagnetic field in response to the X1.0 solar flare on 8 May 2024 as well as to the sudden commencement of the extreme G5-level geomagnetic storm on 10 May 2024. Full article

This paper investigates the synchronization problem of singularly perturbed complex networks with time delays, in which a novel event-triggered delayed impulsive control strategy is developed. To conserve limited communication bandwidth, a dynamic event-triggered mechanism is proposed based on a Lyapunov function construction, while incorporating both delay and singular perturbation parameter $\mathit{\epsilon }$ information to avoid ill conditioning. Unlike conventional triggering approaches, the proposed mechanism only requires the Lyapunov function to decrease at impulsive instants, thereby relaxing the constraint on the energy function. Moreover, an impulse-assisted variable $\mathit{\theta }$ is introduced to adjust the event-triggered threshold according to the intensity of impulsive control, which reduces the triggering frequency while ensuring synchronization. By employing stability theory and the singular perturbation method, a singular perturbation parameter $\mathit{\epsilon }$-dependent Lyapunov function is constructed to derive sufficient synchronization conditions and provide the design of the impulsive gain matrix. Finally, a numerical example is presented to demonstrate the effectiveness of the proposed approach. Full article

This paper investigates the pth moment exponential stability of random impulsive delayed nonlinear systems (RIDNS) with multiple periodic delayed impulses. Moreover, the continuous dynamics are described by random delay differential equations whose random disturbances are driven by second-order moment processes. Using the periodic impulsive intensity (PII), average delay time (ADT), average impulsive delay (AID), as well as the Lyapunov method, we present some pth exponential stability criteria for impulsive random delayed nonlinear systems with multiple delayed impulses. Furthermore, the criterion is unified, which is not only applicable to stable or unstable original systems but also takes into account the coexistence of stabilizing and destabilizing impulses. The periodic structure of impulses and their intensities introduces an intrinsic temporal symmetry, which plays a critical role in determining the stability behavior of the system. This symmetry-based perspective highlights the fundamental impact of regularly recurring impulsive actions on system dynamics. Several illustrated examples are given to verify the effectiveness of our results. Full article

Simulated room impulse responses (RIRs) are important tools for studying architectural acoustics. Many methods exist to generate RIRs, each with unique properties that need to be considered when choosing an RIR synthesis technique. Despite the variation in synthesis techniques, there is a dearth of comparisons between these techniques. To address this, a comprehensive comparison of four major categories of RIR synthesis techniques was conducted: wave-based methods (hybrid FEM and modal analysis), geometrical acoustics methods (the image source method and ray tracing), delay-network reverberators (SDNs), and statistical methods (Sabine-NED). To compare these techniques, RIRs were recorded in a simple shoebox-shaped racquetball court, and we compared the synthesized RIRs against these recordings. We conducted both objective analyses, such as energy decay curves, normalized echo density, and frequency-dependent decay times, and a perceptual assessment of synthesized RIRs, which consisted of a listening assessment with 29 participants that utilized a MUSHRA comparison methodology. Our results reveal distinct advantages and limitations across synthesis categories. For example, the Sabine-NED technique was indistinguishable from the recorded IR, but it does not scale well with increasing geometric complexity. These findings provide valuable insights for selecting appropriate synthesis techniques for applications in architectural acoustics, immersive audio rendering, and virtual reality environments. Full article

The extended operation of high-speed railways has led to an increased incidence of tunnel lining defects, with falling debris posing a significant safety threat. Within tunnels, single-train passage and trains-crossing events constitute the most frequent operational scenarios, both generating extreme aerodynamic environments that alter debris trajectories from free fall. To systematically investigate the aerodynamic differences and underlying mechanisms governing falling debris behavior under these two distinct conditions, a three-dimensional computational fluid dynamics (CFD) model (debris–air–tunnel–train) was developed using an improved delayed detached eddy simulation (IDDES) turbulence model. Comparative analyses focused on the translational and rotational motions as well as the aerodynamic load coefficients of the debris in both single-train and trains-crossing scenarios. The mechanisms driving the changes in debris aerodynamic behavior are elucidated. Findings reveal that under single-train operation, falling debris travels a greater distance compared with trains-crossing conditions. Specifically, at train speeds ranging from 250–350 km/h, the average flight distances of falling debris in the X and Z directions under single-train conditions surpass those under trains crossing conditions by 10.3 and 5.5 times, respectively. At a train speed of 300 km/h, the impulse of C_Fx and C_Fz under single-train conditions is 8.6 and 4.5 times greater than under trains-crossing conditions, consequently leading to the observed reduction in flight distance. Under the conditions of trains crossing, the falling debris is situated between the two trains, and although the wind speed is low, the flow field exhibits instability. This is the primary factor contributing to the reduced flight distance of the falling debris. However, it also leads to more pronounced trajectory deviations and increased speed fluctuations under intersection conditions. The relative velocity (CRV) on the falling debris surface is diminished, resulting in smaller-scale vortex structures that are more numerous. Consequently, the aerodynamic load coefficient is reduced, while the fluctuation range experiences an increase. Full article

Human Activity Recognition (HAR) using wearable sensor data is increasingly important in healthcare, rehabilitation, and smart monitoring. This study systematically compared three dynamic neural network architectures—Finite Impulse Response Neural Network (FIRNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU)—to examine their suitability and specificity for HAR tasks. A controlled experimental setup was applied, training 16,500 models across different delay lengths and hidden neuron counts. The investigation focused on classification accuracy, computational cost, and model interpretability. LSTM achieved the highest classification accuracy (98.76%), followed by GRU (97.33%) and FIRNN (95.74%), with FIRNN offering the lowest computational complexity. To improve model transparency, Layer-wise Relevance Propagation (LRP) was applied to both input and hidden layers. The results showed that gyroscope Y-axis data was consistently the most informative, while accelerometer Y-axis data was the least informative. LRP analysis also revealed that GRU distributed relevance more broadly across hidden units, while FIRNN relied more on a small subset. These findings highlight trade-offs between performance, complexity, and interpretability and provide practical guidance for applying explainable neural wearable sensor-based HAR. Full article

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder with chronic inattention, hyperactivity, and impulsivity and is linked with significant functional impairment. Despite being highly prevalent, diagnosis of ADHD continues to rely on subjective assessment reports of behavior and is often delayed or inaccurate. This review summarizes current advances in biomarkers and neuropsychological tests for the improvement of ADHD diagnosis and treatment. Key biomarkers are neuroimaging methods (e.g., structural and functional MRI), electrophysiological measures (e.g., EEG, ERP), and biochemical measures (e.g., cortisol, vitamin D). Additionally, novel experimental measures, e.g., eye-tracking, pupillometry, and microbiome analysis, hold the promise to be objective and dynamic measures of ADHD symptoms. The review also comments on the impact of the burden of ADHD on quality of life, e.g., emotional well-being, academic achievement, and social functioning. Additionally, differences between individuals, such as age, sex, comorbidities, and the impact of social and family support, are also addressed in relation to ADHD outcomes. In summary, we highlight the potential of these emerging biomarkers and tools to revolutionize ADHD diagnosis and guide personalized treatment strategies. These insights have significant implications for improving patient outcomes. Full article

Vehicle-to-home (V2H) technology enables electric vehicles (EVs) to supply power to residential loads, offering enhanced energy self-sufficiency and backup capabilities. Accurate voltage regulation is essential in such systems, especially under nonlinear and time-varying load conditions. The control method for three-phase four-wire (3P4W) converters plays a vital role in addressing these challenges. In the control configuration of such systems, the non-ideal proportional-resonant (PR) controller stands out due to its ability to reject periodic disturbances. However, the comprehensive study on the discretization of this controller for digital implementation in 3P4W systems has not been available in the literature to date. This paper presents a comparative study of several discretization methods for non-ideal PR controllers. The continuous-time complete transfer function of the integral term of non-ideal PR controllers is discretized using techniques such as Forward Euler, Backward Euler, Tustin, Zero-Order Hold, and Impulse Invariance. Additionally, the discretization methods based on two discrete integrators for the non-ideal PR controller, such as Forward Euler and Backward Euler, Backward Euler and Backward Euler plus computational delay, and Tustin and Tustin, are also evaluated. In the MATLAB/Simulink platform, through evaluating the performance of the non-ideal PR controllers, which are discretized using the above discretization methods, in controlling the output voltage of the 3P4W converter in the V2H application under nonlinear load scenarios, including substantial and sudden changes in load, the discretization method Backward Euler and Backward Euler plus delay is recommended. Full article

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition affecting social interaction, communication, and emotional regulation, often requiring specialized educational approaches. Traditional teaching methods may not meet the needs of children with ASD, while visual and interactive formats tend to be more effective. This study examines the use of a virtual reality (VR) visual novel incorporating social stories to support social–emotional learning in children with Level 1 ASD. The intervention used an interactive, choice-based VR environment simulating everyday social situations. Four primary school students participated in a one-week case study, during which they engaged with the VR prototype. Teachers observed the students and provided feedback through questionnaires and interviews. Results showed high engagement with observable social communication behaviors and emotional responses in one participant but no consistent short-term changes across the group. All teachers expressed positive views, noting the tool’s visual clarity, ease of use, and alignment with ASD learners’ needs. Usability challenges were minimal but included pacing delays and difficulties managing impulsive behavior. Although limited by sample size and short duration, the findings indicate that VR visual novels are a promising and acceptable approach for practicing social–emotional skills in inclusive classrooms. Further research is needed to evaluate long-term effects and enhance adaptability. Full article

Recent advances in Artificial Intelligence (AI)-driven wireless communication are driving the adoption of Sixth Generation (6G) technologies in crucial environments such as hospitals. Visible Light Communication (VLC) leverages existing lighting infrastructure to deliver high data rates while mitigating electromagnetic interference (EMI); however, patient movement induces fluctuating signal strength and dynamic channel conditions. In this paper, we present a novel integration of site-specific ray tracing and machine learning (ML) for VLC-enabled Medical Body Sensor Networks (MBSNs) channel modeling in distinct hospital settings. First, we introduce a Q-learning-based adaptive modulation scheme that meets target symbol error rates (SERs) in real time without prior environmental information. Second, we develop a Long Short-Term Memory (LSTM)-based estimator for path loss and Root Mean Square (RMS) delay spread under dynamic hospital conditions. To our knowledge, this is the first study combining ray-traced channel impulse response modeling (CIR) with ML techniques in hospital scenarios. The simulation results demonstrate that the Q-learning method consistently achieves SERs with a spectral efficiency (SE) lower than optimal near the threshold. Furthermore, LSTM estimation shows that D1 has the highest Root Mean Square Error (RMSE) for path loss (1.6797 dB) and RMS delay spread (1.0567 ns) in the Intensive Care Unit (ICU) ward, whereas D3 exhibits the highest RMSE for path loss (1.0652 dB) and RMS delay spread (0.7657 ns) in the Family-Type Patient Rooms (FTPRs) scenario, demonstrating high estimation accuracy under realistic conditions. Full article

Vestibular atelectasis (VA) is a rare clinical entity characterized by a collapse of the endolymphatic space resulting in vestibular loss with the possible onset of positional and/or sound/pressure-induced vertigo. It could be idiopathic or secondary to other inner-ear diseases including Meniere’s disease (MD). A collapse of the membranous labyrinth involving the semicircular canals (SCs) and the utricle represents its distinctive histopathological feature. While specific radiological patterns consistent with VA have been described on contrast-enhanced MRI with delayed acquisitions, an impairment of the blood–labyrinthine barrier (BLB) could be detected in several disorders leading to vestibular loss. We conducted a narrative review of the literature on VA focusing on the putative pathomechanisms accounting for positional and sound/pressure-induced nystagmus despite unilateral vestibular loss (UVL) in this condition, providing two novel cases of VA. Both patients presented with a clinical picture consistent with unilateral MD that rapidly turned into progressive UVL and positional and/or sound/pressure-induced vertigo. In both cases, the posterior SC was initially impaired at the video-head impulse test (vHIT) and both cervical and ocular VEMPs were initially reduced. Progressively, they developed unsteadiness with paretic spontaneous nystagmus, an impairment also for the lateral and anterior SCs, caloric hypo/areflexia and VEMPs areflexia. They both exhibited ipsilesional nystagmus to sound/pressure stimuli and in one case a persistent geotropic direction-changing positional nystagmus consistent with a “light cupula” mechanism involving the lateral SC of the affected side. A collapse of the membranous labyrinthine walls resulting in contact between the vestibular sensors and the stapes footplate could explain the onset of nystagmus to loud sounds and/or pressure changes despite no responses to high- and low-frequency inputs as detected by caloric irrigations, vHIT and VEMPs. On the other hand, the onset of positional nystagmus despite UVL could be explained with the theory of the “floating labyrinth”. Both patients received contrast-enhanced brain MRI with delayed acquisition exhibiting increased contrast uptake in the pars superior of the labyrinth, suggesting an impairment of the BLB likely resulting in secondary VA. A small intralabyrinthine schwannoma was detected in one case. VA should always be considered in case of positional and/or sound/pressure-induced vertigo despite UVL. Full article

Background/Objectives: Idiopathic immune-mediated uveitis (IIMU) is an intraocular inflammatory condition affecting the uveal tract and adjacent ocular structures, potentially leading to systemic involvement. Audiovestibular symptoms, such as sensorineural hearing loss (SNHL) and balance disturbances, are often underdiagnosed in these patients. The potential correlation between IIMU and audiovestibular dysfunction remains insufficiently studied. This study aimed to estimate the prevalence and describe the clinical characteristics of audiovestibular manifestations in patients with IIMU. Methods: We conducted a cross-sectional observational study of 34 patients with a confirmed diagnosis of IIMU at a tertiary academic center. All participants underwent a standardized neurootological assessment, including pure-tone audiometry, video head impulse testing (vHIT), and cervical vestibular-evoked myogenic potentials (cVEMP). Demographic and clinical data were also collected. Results: Audiovestibular dysfunction was identified in 41.18% of patients, with bilateral SNHL (B-SNHL) being the most common finding. Patients with B-SNHL had a significantly later age of uveitis onset (52.3 ± 14.4 vs. 35.9 ± 13.9 years, p = 0.003) and a higher incidence of ocular complications (83.3% vs. 59.1%, p = 0.252). Furthermore, worsening ophthalmologic activity was observed in 25% of patients with B-SNHL, compared to 0% in those without B-SNHL (p = 0.037). Vestibular dysfunction was also associated with delayed onset of uveitis (51.0 ± 17.4 vs. 36.0 ± 12.2 years, p = 0.006) and a non-significantly higher complication rate (76.9% vs. 61.9%, p = 0.465). Conclusions: Audiovestibular dysfunction is a frequent finding in patients with IIMU and is associated with delayed uveitis onset and greater ocular morbidity. These results support the inclusion of systematic audiovestibular screening in clinical evaluations of IIMU patients and suggest that earlier detection may inform prognosis and guide multidisciplinary management strategies. Full article

A critical requirement for rehabilitation robots is achieving high transparency in user interaction to minimize interference when assistance is unnecessary. Cable-driven systems are a compelling alternative to rigid-link robots due to their lighter weight and reduced inertia, enhancing transparency. However, controlling cable tension forces remains a significant challenge, as these forces directly affect the interaction between the user and the robot. Effective strategies must maintain low tension during non-assistive phases while preventing slackness. This paper introduces PACE-R (Passive Active CablE Robot), a novel lightweight actuation system for cable-driven rehabilitation devices. The PACE-R module utilizes remote actuation and an open-loop, discrete state control, where the cable is coupled to the motor only during active intervention. When not assisting, the cable is passively decoupled from the motor, and a low-stiffness spring maintains minimal tension, enabling high transparency. Benchtop tests showed that the module consistently produced force impulses proportional to motor input with delays not exceeding 15 ms. In the treadmill push-off assistance demonstration, PACE-R contributed about 20% to total ankle moment and power. Transparency analysis revealed negligible interference, with only 1% and 0.5% contributions to peak total ankle moment and power, respectively. Full article

The amplitude panning method is a prevalent technique for controlling sound image directions in stereophonic and multichannel surround systems. However, conventional methods typically achieve accurate localization only with standardized loudspeaker configurations, limiting their applicability in diverse scenarios. This paper presents an adaptive binaural cue-based amplitude panning algorithm based on binaural cues tailored for accurate azimuthal sound image localization in irregular loudspeaker configurations. Our two-stage approach first employs inverse filtering to equalize loudspeaker magnitude responses. Subsequently, gains and inter-loudspeaker time delay are optimized based on interaural time difference and interaural cross-correlation values, derived from the measured binaural room impulse responses using a dummy head. Objective and subjective evaluations on a stereo system demonstrate that the proposed method significantly improves azimuth localization accuracy compared to existing techniques. Full article