Search Results (450)

Flexible laryngoscopy (FL) is the standard diagnostic tool for vocal cord paralysis (VCP), but it involves patient discomfort, and its interpretation is subjective and operator-dependent. Dynamic digital radiography (DDR) is a novel imaging technique that acquires high-resolution sequential radiographs at a low radiation dose. While DDR has been widely applied in chest and diaphragmatic imaging, its use for laryngeal motion analysis has been poorly investigated. We present the case of a 50-year-old male referred for Computed Tomography (CT) of the neck and chest for suspected vocal cord paralysis. The referring physician did not specify the side of the suspected paralysis. Due to a language barrier and the absence of prior documentation, a detailed history could not be obtained. To assess vocal cord motion, we performed, for the first time in our Institution, a DDR study of the neck. During phonation maneuvers, DDR demonstrated fixation of the left vocal cord in an adducted paramedian position. CT confirmed this finding and did not highlight any further anomaly. This case demonstrates the feasibility of DDR as a low-cost, low-dose, non-invasive technique for functional evaluation of the larynx and may represent a valuable complementary imaging tool in laryngeal functional assessment. Full article

High-resolution pushbroom satellites routinely acquire multi-tenskilometer-scale strips whose vendors’ rational polynomial coefficients (RPCs) exhibit systematic, direction-dependent biases that accumulate downstream when ground control is sparse. This study presents a physically interpretable stripwise extrapolation framework that predicts along- and across-track RPC correlation coefficients for inaccessible segments from an upstream calibration subset. Terrain-independent RPCs were regenerated and residual image-space errors were modeled with weighted least squares using elapsed time, off-nadir evolution, and morphometric descriptors of the target terrain. Gaussian kernel weights favor calibration scenes with a Jarque–Bera-indexed relief similar to the target. When applied to three KOMPSAT-3A panchromatic strips, the approach preserves native scene geometry while transporting calibrated coefficients downstream, reducing positional errors in two strips to <2.8 pixels (~2.0 m at 0.710 m Ground Sample Distance, GSD). The first strip with a stronger attitude drift retains 4.589 pixel along-track errors, indicating the need for wider predictor coverage under aggressive maneuvers. The results clarify the directional error structure with a near-constant across-track bias and low-frequency along-track drift and show that a compact predictor set can stabilize extrapolation without full-block adjustment or dense tie networks. This provides a GCP-efficient alternative to full-block adjustment and enables accurate georeferencing in controlled environments. Full article

Aim: To investigate the vestibulosympathetic reflex (VSR) in humans by comparing the hemodynamic responses to air-conducted sound stimulus (ACSS) of the vestibular system between healthy individuals and participants with vestibular neuritis (VN). Methods: Twenty-one healthy controls and seven participants with VN were enrolled. Each autonomic test was first conducted without and then with ACSS of the vestibular system. The following autonomic tests were performed: heart rate response to Valsalva maneuver; heart rate response to deep breathing; and heart rate and blood pressure response to a supine position, passive tilt, and active standing. Results: In healthy participants, there was a difference between respiratory sinus arrhythmia values without and with otolithic stimulation (26.63 ± 6.16 vs. 24.67 ± 7.34, p = 0.02). During passive tilt, the average heart rate throughout ACSS was lower than immediately before ACSS (88.63 ± 14.68 vs. 90.96 ± 14.93, p = 0.001). In participants with VN, no such differences were observed. Conclusions: This study demonstrated a significant effect of otolithic stimulation with ACSS on heart rate during passive tilt in healthy participants. These findings suggest that ACSS of the vestibular system could be a valuable method for future research on the VSR. Full article

Background and Clinical Significance: Benign paroxysmal positional vertigo (BPPV) most commonly involves the posterior semicircular canal (PSC), whereas anterior semicircular canal BPPV (ASC-BPPV) is rare, accounting for only 1–3% of cases. Most ASC-BPPV cases respond well to particle repositioning maneuvers (PRMs), with refractory presentations being exceptional and diagnostically challenging, particularly when differential diagnoses such as apogeotropic posterior semicircular canal BPPV (PSC-BPPV) or central causes must be excluded. Case Presentation: A 43-year-old woman presented with vertigo triggered by head extension and rolling in bed. Initial neurological and otoneurological examinations were unremarkable. During the left Dix–Hallpike maneuver, a vertical down-beating nystagmus with subtle leftward torsion appeared after a 5 s latency and lasted 15 s. The supine head-hanging maneuver provoked a stronger and longer 30 s response, while the right Dix–Hallpike was negative. Despite repeated PRMs, including Yacovino (Deep Head-hanging), reverse Epley, Epley, and modified Semont maneuvers, the patient remained symptomatic over three years. Intermittently, conversion to PSC-BPPV was suspected, and temporary resolution was achieved after left-sided Epley and Semont maneuvers, but recurrence followed. Treatment with a mechanical rotational chair (TRV) initially resolved symptoms, but vertigo recurred several months later following two syncopal episodes with minor trauma. Extensive neurological evaluation, including MRI, CT, EEG, and vascular ultrasound, excluded central causes. Conclusions: This case illustrates the diagnostic and therapeutic difficulties posed by refractory ASC-BPPV, particularly in differentiating it from apogeotropic PSC-BPPV and central etiologies. It underscores the importance of latency, torsional characteristics, and supine head-hanging testing in diagnosis and demonstrates the potential role of mechanical rotational chairs in management. Personalized approaches incorporating anatomical imaging and maneuver adaptation are essential in such complex cases. Full article

This study evaluates the impact of an educational intervention aimed at improving the management of benign paroxysmal positional vertigo (BPPV) in a clinical setting. Interrupted Time Series (ITS) analysis was used to assess changes in the use of key diagnostic maneuvers—Dix–Hallpike and Supine Roll—as well as the treatment maneuver, Canalith Repositioning Maneuvers (CRM), and the use of CT scans. The intervention aimed to promote evidence-based practices and minimize unnecessary imaging. ITS models accounted for confounders such as history of BPPV and dizziness. The results showed significant improvements in the use of the Supine Roll and CRM maneuvers, with both immediate increases and sustained upward trends following the intervention. For the Dix–Hallpike maneuver, an initial increase was observed after the intervention; however, this effect was no longer statistically significant after adjusting for confounders, suggesting that the observed change may have been influenced by shifts in the patient population rather than the intervention itself. A positive long-term trend persisted. No significant reduction in CT scan usage was found. These findings demonstrate the intervention’s effectiveness in enhancing adherence to recommended diagnostic and treatment practices for BPPV. However, they also suggest that reducing unnecessary imaging may require additional strategies beyond provider education. Full article

The increasing use of UAV swarms for collaborative autonomous missions presents significant challenges in coordination, safety, and scalability, especially during dynamic formation reconfigurations. This study introduces the Magnetic Swarm Reconfiguration (MSR) protocol, a fully distributed navigation method that enables UAV swarms to transition smoothly and safely between geometric formations. MSR achieves this by combining two main components: first, it employs the Hungarian algorithm to compute an optimal assignment of UAVs to target positions within the new formation, thereby minimizing trajectory overlap and interference; second, it utilizes virtual magnetic attraction and repulsion forces for real-time navigation, drawing each UAV toward its assigned destination while dynamically repelling nearby agents to avoid collisions. To evaluate the performance of the MSR protocol, six representative formation transitions were simulated across swarm sizes of up to 100 UAVs. Results show that MSR reduces reconfiguration time significantly compared to existing methods, maintains strict safety standards by achieving minimal to zero collisions, and supports fully decentralized and simultaneous maneuvering. The scalability and robustness of the MSR protocol make it suitable for complex, large-scale swarm operations requiring rapid and reliable formation changes. Full article

To address the sideslip phenomenon caused by the lack of lateral constraints in path following of underactuated hovercraft, this paper proposes a path following control algorithm. The algorithm adopts a method of controlling two control points on the underactuated hovercraft, in which the first control point ensures position tracking accuracy while the second point decreases the sideslip angle. To further decrease the sideslip effects during turning maneuvers, a speed regulator based on path curvature radius is designed to adjust the desired speed by balancing centrifugal force and lateral dynamic constraints. Simulation results show that the sideslip angle can be reduced while the position error exponentially converges to zero. Full article

Automated Valet Parking (AVP) systems require high-precision positioning, especially in indoor environments where Global Positioning System (GPS) is unavailable. Existing methods, which use markers installed on parking lot walls or ceilings, often encounter difficulties due to marker detection failures caused by complex parking behaviors, such as infrastructure constraints or perpendicular parking. This study proposes an optimized indoor positioning system for AVP using fiducial markers recognized by front and rear vehicle cameras. To enhance accuracy and robustness, an Extended Kalman Filter (EKF) fuses vehicle kinematic data with marker pose information. Critically, to address the issue of marker occlusion by the front camera during reverse parking, a novel camera switching algorithm employing a hysteresis pattern based on vehicle position, heading, and motion direction is introduced. This ensures continuous marker visibility and stable positioning during parking maneuvers. The system’s effectiveness was validated through simulations and extensive real-vehicle experiments in a real parking space. Results demonstrate that the EKF significantly reduces positioning errors compared to kinematic prediction alone, particularly during curved driving. Furthermore, the proposed camera switching algorithm successfully overcomes the limitations of a front-only camera system, significantly improving positioning accuracy (e.g., reducing RMS error by up to 25.0% in X and 17.6% in Y during parking) and eliminating instability observed with simpler switching logic. This research contributes a cost-effective and reliable positioning solution, advancing the feasibility of AVP systems in challenging indoor environments. Full article

Background/Objectives: Dizziness is a frequent medical complaint with neurological, otolaryngological, and psychological origins. Imaging studies such as CT (Computer Tomography), cervical X-rays, and ultrasound aid diagnosis, while MRI (Magnetic Resonance Imaging) is crucial for detecting brain abnormalities. Our purpose is to identify structural brain changes associated with vertigo, assess pre-MRI diagnostic approaches, and evaluate treatment strategies. Methods: A case-control study of 232 vertigo patients and 232 controls analyzed MRI findings, pre-MRI examinations, symptoms, and treatments. Statistical comparisons were performed using chi-square and t-tests (p < 0.05). Results: White matter lesions, lacunar infarcts, Circle of Willis variations, and sinusitis were significantly more frequent in vertigo patients (p < 0.05). Pre-MRI diagnostics frequently identified atherosclerosis (ultrasound) and spondylosis (X-ray). Common symptoms included headache, imbalance, and visual disturbances. The most frequent post-MRI diagnosis was Benign Paroxysmal Positional Vertigo (BPPV). Treatments included lifestyle modifications, physical therapy (e.g., Epley maneuver), and pharmacological therapies such as betahistine. Conclusions: MRI revealed structural brain changes linked to vertigo. Pre-MRI assessments are essential for ruling out vascular and musculoskeletal causes. A multidisciplinary treatment approach is recommended. Trial Registration: This study was registered in ClinicalTrials.gov with the trial registration number NCT06848712 on 22 February 2025. Full article

This study addresses the nonlinear estimation problem in the strapdown inertial navigation system (SINS) and Doppler velocity log (DVL) integrated navigation by proposing an improved filtering algorithm based on $S{E}_2(3)$ Lie group state representation. A dynamic model satisfying the group affine condition is established to systematically construct both left-invariant and right-invariant error state spaces, upon which two nonlinear filtering approaches are developed. Although the fast unscented transformation method is not novel by itself, its first integration with the $S{E}_2(3)$ Lie group model for SINS/DVL integrated navigation represents a significant advancement. Experimental results demonstrate that under large misalignment angles, the proposed method achieves slightly lower attitude errors compared to linear approaches, while also reducing position estimation errors during dynamic maneuvers. The 12,000 s endurance test confirms the algorithm’s stable long-term performance. Compared with conventional unscented Kalman filter methods, the proposed approach not only reduces computation time by 90% but also achieves real-time processing capability on embedded platforms through optimized sampling strategies and hierarchical state propagation mechanisms. These innovations provide an underwater navigation solution that combines theoretical rigor with engineering practicality, effectively overcoming the computational efficiency and dynamic adaptability limitations of traditional nonlinear filtering methods. Full article

Vehicular communication is crucial for the future of intelligent transportation systems. However, providing continuous high-data-rate connectivity for vehicles in hard-to-reach areas, such as highways, rural regions, and disaster zones, is challenging, as deploying ground base stations (BSs) is either infeasible or too costly. In this paper, multiple unmanned aerial vehicles (UAVs) using millimeter-wave (mmWave) bands are proposed to deliver high-data-rate and secure communication links to vehicles. This is due to UAVs’ ability to fly, hover, and maneuver, and to mmWave properties of high data rate and security, enabled by beamforming capabilities. In this scenario, the vehicle should autonomously select the optimal UAV to maximize its achievable data rate and ensure long coverage periods so as to reduce the frequency of UAV handovers, while considering the UAVs’ battery lives. However, predicting UAVs’ coverage periods and optimizing mmWave beam directions are challenging, since no prior information is available about UAVs’ positions, speeds, or altitudes. To overcome this, out-of-band communication using orthogonal time-frequency space (OTFS) modulation is employed to enable the vehicle to estimate UAVs’ speeds and positions by assessing channel state information (CSI) in the Delay-Doppler (DD) domain. This information is used to predict maximum coverage periods and optimize mmWave beamforming, allowing for the best UAV selection. Compared to other benchmarks, the proposed scheme shows significant performance in various scenarios. Full article

This study investigates how local governance actors in northern Taiwan navigate agricultural irrigation coordination under intensifying climate-induced water stress. Although conventional water governance models prioritize structural alignment and centralized integration, they frequently prove to be inadequate under conditions marked by institutional ambiguity and semantic volatility. Focusing on the transitional phase between early drought signaling and the formal implementation of water rationing, this research adopts Situational Grounded Theory (SGT) to examine how actors discursively interpret, negotiate, and adapt to evolving hydrological and institutional constraints. Based on unstructured interviews with irrigation officials, farmers, and public administrators, this study traces how expressions such as “under review” and “adjusting regionally” function as semantic instruments for deferral, alignment, and legitimacy building. These phrases are not merely rhetorical fillers; rather, they operate as situated mechanisms through which actors reposition their roles and recalibrate the meanings of governance. Through iterative coding, semantic clustering, and reflexive mapping grounded in SGT, this study develops the LAWFGS (Local Adaptive Water Governance under Flexible Governance Settings) framework. This tri-axial interpretive framework comprises three interrelated dimensions: (1) governance contexts, which captures the hydrological and institutional phase; (2) actor strategy roles, which reflect how actors adopt and shift their discursive positions; and (3) interpretive flexibility, which denotes the degree of semantic maneuvering exercised in response to governance tensions. The LAWFGS framework offers a situated analytical perspective for understanding how coordination is maintained through meaning-making practices under environmental pressure. The framework emphasizes the relational dynamics through which governance unfolds across shifting and often uncertain contexts. Full article

Space debris is an increasingly severe problem in the space industry. According to projections, the number of satellites will increase from the current 10,000 to 100,000 by 2030, specially in LEO orbits. This significant rise in the number of satellites threatens space sustainability, forcing satellites to perform more maneuvers to avoid impacts or leading to the production of more and more space debris due to collisions (Kessler Syndrome). Consequently, substantial efforts have been made to detect and track space debris, leading to the development of the current catalogs. However, with existing technology, detecting and tracking small debris remains challenging. In order to improve the current system, several proposals of Space-Based Situational Awareness (SBSA) have been made. These proposals involve satellites equipped with telescopes to detect space debris and determine their orbits. Unlike prior works, focused primarily on detection rates, this research aims to quantify their accuracy in orbit determination as a function of observation duration, the number of observers, and sensor precision. The Unscented Kalman Filter (UKF) is employed as the core estimation algorithm, leveraging both simulated single-case analyses and Monte Carlo simulations to evaluate system performance under various configurations and uncertainties. The results indicate that a constellation of at least three observers with high-precision instruments and sub-kilometer positioning accuracy can reliably estimate debris orbits within an observation period of 4–7 min, with the mean error in position and velocity obtained being 2.2–3 km and 3–4 m/s, respectively. These findings offer critical insights for designing future SBSA constellations and optimizing their operational parameters to address the growing challenge of orbital debris. Full article

Background/Objectives: To evaluate the safety and feasibility of continuous positive airway pressure (CPAP) in patients with acute myocardial infarction (AMI) and acute decompensated heart failure (ADHF) during percutaneous coronary intervention (PCI). Non-invasive ventilation (NIV) is an established treatment for ADHF. Methods: All consecutive patients admitted to Santa Croce Hospital of Cuneo, receiving CPAP for ADHF in the cath lab during PCI for AMI, were included in a case series. Results: Between December 2018 and March 2021, 25 pts were included (median age 78 yrs, 48% female), with 64% of patients presenting with ST-elevation AMI and 17 (69%) in cardiogenic shock. At admission median left ventricular ejection fraction was 35 (20–60)% and eight (32%) patients had severe mitral regurgitation. Median PaO₂/FiO₂ was 183 (141–261) mmHg/%, lactate level 2.4 (1.3–3.8) mmol/L, and NTproBNP 7882 (3139–35,000) ng/L. CPAP was positioned and managed by nurses in all cases. Median FiO₂ was 50 (35–100)% and median positive end-expiratory pressure was 7.5 (5–12) cmH₂O. CPAP was generally well tolerated in 22 (88%) patients. One patient suffered cardiac arrest that led to CPAP interruption due to resuscitation maneuvers. No patient required orotracheal intubation in the cath lab. The post-procedural PaO₂/FiO₂ ratio substantially improved to 230 (175–356) mmHg/% (p = 0.007) and lactate decreased to 1.5 (1.0–1) mmol/L (p = 0.002). One patient died during hospital stay due to underlying disease, unrelated to the study procedure. Conclusions: CPAP during PCI in patients with AMI and ADHF seems feasible, safe, and well tolerated. Larger studies are warranted to confirm these results. Full article

This paper introduces a robust and efficient Localized Spline-based Path-Planning (LSPP) algorithm designed to enhance autonomous vehicle navigation on highways. The LSPP approach prioritizes smooth maneuvering, obstacle avoidance, passenger comfort, and adherence to road constraints, including lane boundaries, through optimized trajectory generation using quintic spline functions and a dynamic speed profile. Leveraging real-time data from the vehicle’s sensor fusion module, the LSPP algorithm accurately interprets the positions of surrounding vehicles and obstacles, creating a safe, dynamically feasible path that is relayed to the Model Predictive Control (MPC) track-following module for precise execution. The theoretical distinction of LSPP lies in its modular integration of: (1) a finite state machine (FSM)-based decision-making layer that selects maneuver-specific goal states (e.g., keep lane, change lane left/right); (2) quintic spline optimization to generate smooth, jerk-minimized, and kinematically consistent trajectories; (3) a multi-objective cost evaluation framework that ranks competing paths according to safety, comfort, and efficiency; and (4) a closed-loop MPC controller to ensure real-time trajectory execution with robustness. Extensive simulations conducted in diverse highway scenarios and traffic conditions demonstrate LSPP’s effectiveness in delivering smooth, safe, and computationally efficient trajectories. Results show consistent improvements in lane-keeping accuracy, collision avoidance, enhanced materials wear performance, and planning responsiveness compared to traditional path-planning methods. These findings confirm LSPP’s potential as a practical and high-performance solution for autonomous highway driving. Full article