Search Results (10,460)

Background and Clinical Significance: Deep thalamic and periventricular lesions are uncommon in adults but can result in significant loss of function because of their convergence on three interdependent processes: thalamocortical state regulation, throughput of periventricular long association systems, and ventricular compartmental compliance. The resulting combination of executive control collapse, retrieval-weighted language fragility, and load-sensitive gait instability may occur early after a lesion forms an atrial/posterior horn interface, and pressure-linked autonomic symptoms may be late to develop. Screening deficits will likely be minimal and therefore underreported. Objective/Aim: To present a thalamic–atrial/posterior horn tumor case with quantified load-sensitive cognitive–language–gait dysfunction and to detail a physiology-guided, sequence-driven decompression approach emphasizing ventricular relaxation and perforator-preserving, interface-limited thalamic resection. Case Presentation: A 56-year-old female patient experienced a 3-month, rapidly progressive decline in her cognitive and language abilities. The clinical progression was not stepwise or punctuated by a single “sentinel” event. She had a moderate level of cognitive impairment consistent with both Broca’s and Wernicke’s aphasias (MoCA: 22/30) and suffered from significant interference effects and increased cost of task-switching. Her ability to generate novel responses and name objects was significantly impaired; however, she was able to repeat words and phrases appropriately. In addition, she exhibited a severe sustained attention signature and a high error rate during dual-task performance, indicating severe gait instability, although her overall global anchors were nearly neutral (GCS 15; FOUR 15/16; NIHSS 2). Nausea and vomiting occurred simultaneously with the cognitive and language decline, suggesting decreased intracranial compliance. MRI revealed a heterogeneous left-sided thalamic tumor extending into the posterior horn of the lateral ventricle. The tumor caused deformation of the lateral ventricle and midline displacement. The patient underwent microsurgical intervention using a physiology-conscious sequence of graded cerebrospinal fluid (CSF) equilibration and primary mechanical removal of the tumor from the ventricular system. Additionally, decompression of the thalamus was performed in a manner that was cognizant of the boundaries formed by the perforating arteries of the thalamus. Early resolution of pressure symptoms was noted postoperatively. Objective measures demonstrated significant improvement in the patient’s executive functioning, language skills, attentional errors, and dual-task performance stability. The patient remained functionally independent at discharge and at subsequent follow-up visits. Surveillance imaging did not demonstrate any evidence of tumor recurrence. Conclusions: The clinical presentation described above is supportive of a model in which the synergy between deep network damage and distortion of the posterior ventricular compartment amplifies network dysfunction. Additionally, the use of quantitative stress-phenotyping makes it possible to identify deep network pathology early in its course. Finally, the physiology-guided decompression approach that was used in this case has the potential to increase functional reserve in patients with pathology that requires millimeter transitions. Full article

Indonesia’s financial system is bank-centric, with banks managing approximately 78% of the nation’s financial assets; therefore, the effectiveness of monetary policy transmission depends on banks’ responsiveness to the central bank’s interest rate policy (the BI Rate). However, a policy-relevant anomaly persists: deposit rate pricing is more strongly anchored to the Deposit Insurance benchmark (IDIC Rate) than to the BI Rate. This study argues that this research is significant because it identifies a “Dual Benchmark System” that traditional single-anchor models fail to address, representing a critical friction in emerging market transmission. This study examines this dual-benchmark paradigm and the associated asymmetric risks using a panel VAR with a Generalized Impulse Response Function (GIRF) on quarterly data for 63 commercial banks from 2010 to 2024. The results indicate that IDIC Rate shocks have a larger and more persistent effect on deposit rates than BI Rate shocks, generating asymmetric transmission risks. This dominance creates a structural “price ceiling” that keeps funding costs high, ultimately raising lending rates for borrowers and distorting deposit growth rates. Furthermore, this analysis reveals that external policy signals are far more influential than internal financial performance. This suggests that under the Basel III framework and prevailing financial regulations, banks prioritize liquidity compliance and safety net protection over internal operational efficiency. Macroeconomic shocks remain weaker than policy shocks and dissipate more quickly. This finding reveals a potential systemic coordination risk, implying an urgent need for tighter policy coordination between the Central Bank and the IDIC to reduce structural frictions, maintain transmission effectiveness, and protect long-term financial stability. Full article

Model Predictive Control (MPC) is widely employed in three-phase two-level voltage source inverters (2L-VSIs) due to its fast dynamic response and straightforward implementation. However, conventional MPC requires the evaluation of all eight candidate voltage vectors (VVs), which increases computational burden and current prediction time, introduces higher common-mode voltage (CMV), and may degrade steady-state performance. To address these limitations, this paper investigates the effect of reducing the number of candidate VVs on CMV suppression, the reduction in current prediction time, and the enhancement of 2L-VSI performance. First, a five-voltage-vectors MPC approach is developed, achieving noticeable CMV suppression compared with the conventional approach. Although this approach achieved CMV suppression, it still incurred a high computational burden. Therefore, it was further developed into a systematic switching approach based on three VVs, in which only three candidate VVs are selected at each sampling instant. The proposed approach achieves two primary objectives: suppressing CMV and reducing the current prediction time by 50%. Experimental validation is conducted to compare the proposed approach with the conventional MPC in terms of CMV, current prediction time, Total Harmonic Distortion (THD), inductance variation sensitivity, dynamic response, and power loss. The results demonstrate that the proposed approach achieves superior steady-state and dynamic performance while significantly reducing the current prediction time and achieving suppression of the CMV at Vdc/2, thereby enhancing the performance of 2L-VSIs. Full article

In this work, we investigate the shadow properties of the Kerr–Newman–Anti-de Sitter black hole coupled to nonlinear electrodynamics. The shadow is constructed by employing the celestial coordinate approach for an observer located at a finite distance, which is required due to the non-asymptotically flat structure of the spacetime. The size, distortion, area, and oblateness of the shadow are analyzed in terms of the black hole parameters, namely, the spin, the effective charge, and the nonlinearity parameter. We show that the nonlinear electrodynamics significantly modifies the photon region and therefore changes the shadow observables, while the rotation mainly controls the deformation of the silhouette. We further confront the theoretical results with the Event Horizon Telescope observations of M87* and Sgr A* in order to constrain the parameter space of the model. The allowed ranges of the effective charge depend sensitively on the nonlinearity parameter, and the combination of both sources leads to tighter and physically more consistent bounds. In addition, we study the energy emission rate derived from the shadow radius and the Hawking temperature and discuss how it is affected by the rotation and the nonlinear electromagnetic field. Our analysis shows that the considered black hole solution provides a consistent extension of the Kerr geometry in a non-asymptotically flat background and that the shadow observables can be used as an efficient tool to test the effects of nonlinear electrodynamics in strong gravity. Full article

Auditory Brain–Computer Interfaces (BCIs) constitute the vital intervention for profound sensorineural hearing loss where the auditory nerve is compromised, yet their clinical efficacy remains restricted by substantial biological bottlenecks and limited spectral resolution. This review critically examines the evolutionary paradigm of auditory restoration, tracing the transition from static physical replacement to dynamic biological symbiosis. We systematically analyze physiological barriers across cochlear, brainstem, and cortical levels, elucidating how rigid interfaces provoke chronic tissue responses and why linear encoding protocols fail in distorted central tonotopy. The article synthesizes emerging methodologies in material science, demonstrating how soft, bio-integrated electronics and biomimetic topologies effectively address mechanical impedance mismatches. Furthermore, the trajectory of neural encoding is evaluated, highlighting the paradigm shift from traditional envelope extraction to deep learning-driven non-linear mapping and adaptive closed-loop neuromodulation. Finally, the potential of high-resolution modulation techniques, including optogenetics and sonogenetics, alongside AI-facilitated intent perception for active listening, is assessed. It is concluded that future neuroprostheses must evolve into symbiotic systems capable of seamlessly integrating with neural plasticity to enable high-fidelity cognitive reconstruction. Full article

Background and Objectives: Atrial secondary mitral regurgitation (A-SMR), also referred to as atrial functional mitral regurgitation, has emerged as a distinct clinical phenotype characterized by left atrial enlargement, mitral annular dilatation, and preserved left ventricular geometry and systolic function. Frequently associated with long-standing atrial fibrillation (AF) and heart failure with preserved ejection fraction (HFpEF), A-SMR challenges the traditional ventricular-centered classification of functional mitral regurgitation (MR) and is increasingly recognized as a clinically relevant condition. Materials and Methods: This narrative review provides an updated and critical overview of current evidence on A-SMR. We summarize available data on pathophysiology, diagnostic imaging, natural history, and therapeutic strategies, with particular emphasis on implications for cardiac surgery and clinical decision-making. Evidence was derived from observational studies, registry analyses, interventional reports, and contemporary guideline documents. Results: A-SMR is primarily driven by atrial remodeling and annular dilatation, with minimal contribution from ventricular distortion or leaflet tethering. Echocardiography and Magnetic Resonance Imaging (MRI) play a central role in diagnosis and phenotypic characterization, allowing differentiation from ventricular functional MR and identification of distinct A-SMR subtypes with potential therapeutic implications. A-SMR is a progressive condition associated with worsening symptoms and adverse clinical outcomes. Rhythm control strategies may reduce MR severity in selected patients by promoting atrial reverse remodeling. Transcatheter edge-to-edge repair (TEER) represents a treatment option for selected high-risk patients, although concerns regarding long-term durability remain in this predominantly annular disease. From a pathophysiological standpoint, surgical mitral valve repair based on annuloplasty directly targets the dominant mechanism of A-SMR and has been associated with favorable outcomes in appropriately selected patients. Conclusions: A-SMR is a distinct and increasingly recognized form of functional MR requiring a mechanism-oriented diagnostic and therapeutic approach. The 2025 ESC/EACTS Guidelines for the management of valvular heart disease have acknowledged A-SMR as a specific clinical phenotype, although dedicated phenotype-specific management recommendations remain limited. Surgical mitral valve repair, particularly when combined with AF ablation, represents a rational treatment strategy in selected patients and may improve long-term outcomes. Full article

The integrity protection of digital signals is an important task in modern applications. We propose DIPS (Data Integrity Protection of Signals), a fragile watermarking algorithm aiming to protect the integrity of sampled signals like images composed of pixels or sampled audio signals that can be divided into block units. The present paper starts with two works that propose fragile watermarking algorithms yielding high-quality watermarked objects, identifies their security vulnerabilities, and finally defines a method that embeds a compressed Message Authentication Code of each block into the LSBs of the block samples. As it modifies 2 bits per block at most, the introduced distortion is extremely low, thus resulting in a very high objective quality ($PSNR$). Experimental results confirming this characteristic are reported on real sampled signals such as speech, images, and ECG signals. Full article

This paper investigates M-PSK symbol detection in Orthogonal Frequency Division Multiplexing (OFDM) systems for wideband Vehicle-to-Vehicle (V2V) communications using lightweight convolutional neural networks. In doubly dispersive channels, Inter-Carrier Interference (ICI) degrades subcarrier orthogonality, rendering conventional equalization ineffective. Current ICI mitigation techniques face a trade-off between Bit-Error Rate (BER) performance and computational complexity, limiting their applicability in dynamic vehicular scenarios. To address this issue, a low-complexity MobileNetV3-based receiver is proposed, incorporating a signal-model-driven preprocessing stage that compensates for Doppler-induced phase distortions responsible for ICI. Simulation results show that the proposed receiver improves BER performance compared to conventional equalizers and recent neural-based schemes in the low-SNR regime (below 15 dB) while maintaining computational complexity close to linear least-squares detection. Full article

Piping systems must cope with the internal pressure of the fluid they carry. They are almost always well-designed for withstanding steady-flow pressures, but allowing for unsteady-flow pressures and for fatigue can be more challenging. Positive and negative gauge pressures induced by waterhammer waves are possibly the most extreme that piping is likely to face during its lifetime. It is widely accepted that this should be addressed by analyses during the design phase, but this is usually done under the assumption that consequential (non-hoop) structural movements do not affect the calculated pressures. However, the calculated pressures are used as input to the structural design. Commonly, attention focusses on static predictions of induced hoop stresses and on the risk of buckling, but attention sometimes has to be paid to dynamic responses. In these cases, the complexity of the structural analysis depends on the assumed degrees of freedom of possible movement, so it is desirable to avoid including unnecessary detail. The title of this paper poses one question that is frequently asked. However, the correct answer is not always obtained, partly because highly misleading answers were published in one early paper, the rebuttals to which were much less widely reported. The current contribution attempts to answer the question for both fixed and movable bends. Attention is paid to pressure transients arriving at bends from remote locations and potentially inducing pipe movement. Then, the opposite effect is considered, namely the generation of pressure transients by structural movements. To avoid distorting the picture by combining this with nominally unrelated causes, strong simplifications are made—e.g., disregarding all forms of energy dissipation. Full article

The intermittent nature of photovoltaic (PV) energy, especially under nonlinear and unbalanced loading situations, has made it more difficult to ensure steady operation as it is increasingly integrated into modern power systems. The Power Quality (PQ) issues cause severe degradation of both system performance and device lifetime. A novel Neural Power Quality Network (NeuPQ-Net) controlled Unified Power Quality Conditioner (UPQC) combined with a Quasi Z-Source Lift (QZSL) converter for PV applications is presented in this research as a novel solution for addressing these issues. The QZSL converter, which is controlled by a Maximum Power Point Tracking (MPPT) algorithm based on Perturb and Observe (P&O), increases the PV source voltage to the necessary DC-link level. A Zebra Optimisation Algorithm tuned PI (ZOA-PI) controller continually adjusts PI gains for quick and accurate regulation, ensuring steady DC-link voltage. Unlike conventional Synchronous Reference Frame (SRF) or Decoupled Double Synchronous Reference Frame (DDSRF)-based reference generation, the proposed NeuPQ-Net operates directly in the abc domain, eliminating Phase-Locked Loop (PLL) dependency and reducing computational complexity. Simulation and hardware prototype validations demonstrate that the proposed system achieves significant improvements in PQ indices, including reduced Total Harmonic Distortion (THD), faster response to transients, and enhanced voltage regulation, while complying with IEEE-519 standards. Full article

To mitigate color crosstalk in projected images induced by non-uniform projection surfaces and dynamic ambient lighting, we propose MAPCNet, an adaptive photometric compensation network that enables robust color reproduction across diverse environments. The experimental process begins with a mask-based preprocessing operation on a multi-surface photometric compensation dataset captured under varying ambient light conditions. The algorithm incorporates a multi-attention mechanism and a triple-interaction attention mechanism, and further integrates a hybrid attention module inspired by the Transformer architecture. By integrating channel attention and window-based self-attention, this module improves the network’s adaptability to spatial and illumination changes. Experimental results demonstrate that the photometric compensation achieved by this algorithm meets the visual perception requirements of the human eye. Full article

This study proposes an integrated pixel-level reflectance adjustment (IPRA) method using Sentinel-2 MSI as the reference to address radiometric discrepancies in GF-1/6 WFV imagery, particularly caused by sensor decay and geometric distortions. The proposed IPRA method leverages time-series data and a spatial heterogeneity detection mechanism to effectively mitigate geometric distortions. Furthermore, it incorporates a weighted linear regression (WLR) model to weight pixels based on their temporal decay characteristics. The results demonstrate that IPRA outperforms existing methods (i.e., IRMAD, HM, and TRA) in radiometric consistency, yielding smaller radiometric discrepancies relative to Sentinel-2 MSI. Specifically, NAE decreased by 42.9% (from 0.319 to 0.182), RMSE decreased by 37.3% (from 0.051 to 0.032), PSNR improved from 25.906 dB to 30.195 dB, and the SC value approached the ideal value of 1 (from 1.540 to 1.001). In conclusion, the IPRA method provides a robust solution for normalizing GF-1/6 WFV imagery and thus facilitates its cross-sensor applications. Full article

In the field of intelligent inspection, high-definition video data collected by quadruped robot dogs face severe transmission and storage constraints. Although existing advanced lossy video coding standards can significantly improve compression efficiency, they inevitably introduce severe compression artifacts in low-bit-rate scenarios. To address this issue, this paper proposes a video decoding quality enhancement network named Video Quality Restoration Network (VQRNet), based on a dual-stream architecture. Specifically, the Local Feature Extraction component incorporates a Progressive Feature Fusion Module (PFFM) with a four-stage progressive structure. By integrating reparameterized convolution and attention mechanisms, PFFM focuses on capturing high-frequency texture details to repair small-scale distortions. Simultaneously, the Multi-Scale Lightweight Spatial Attention Module (MLSA) performs spatial feature recalibration, leveraging multi-scale convolution to adaptively identify and enhance key spatial regions, specifically addressing multi-scale distortion. In the Global Feature Extraction component, the State-Space Attention Module (SSAM) combines State-Space Models (SSMs) with attention mechanisms to capture long-range dependencies and contextual information, for large-scale distortions caused by high-intensity compression. To verify the performance of the proposed algorithm, a dedicated dataset comprising 20 real-world video sequences captured by quadruped robot dogs (partitioned into 15 training and 5 testing sequences) was constructed, and the VTM 23.4 reference software was employed to simulate compression degradation using four quantization parameters (QP 30, 35, 40, and 45). Experimental results demonstrate that VQRNet outperforms state-of-the-art quality enhancement methods in terms of core metrics, including PSNR and SSIM, specifically including MIRNet, NAFNet, TRRHA, and CTNet. In the QP = 30 scenario, VQRNet achieves an average PSNR of 40.33 dB, a significant improvement of 3.32 dB over the VTM 23.4 baseline (37.01 dB), while demonstrating significant advantages in computational complexity and parameter efficiency—requiring only 5.27 G FLOPs and 1.40 M parameters, with an average inference latency of only 11.82 ms per 128 × 128 patch. This work provides robust technical support for the efficient video perception of quadruped robot dogs. Full article

The recent advent of charging infrastructure on an Electric Vehicles (EVs) poses a severe problem with effect on the power grid in terms of harmonic distortion, mostly caused by the nonlinear loads on the electric power produced by charging stations, diode bridge rectifiers, and switching converters. These harmonics continuously negatively influence power quality by increasing system and grid current, voltage total harmonic distortion (THD), power factor, and voltage regulation, and lowering the overall efficiency of the system at high rates that exceed IEEE 519 harmonic standards. This paper develops a thorough design and critical analysis of four topologies of harmonic passive filter, including single-tuned filter (STF), double-tuned filter (DTF), high-pass filter (HPF), and C-type high-pass filter (CHPF), to alleviate harmonics and enhance power quality on grid-tied charging stations of electric vehicles. A generalized structure is modeled and simulated in MATLAB/Simulink R2021a at a charging load of an EV charging load for all the filters under the same conditions and evaluated based on the current THD (ITHD), voltage THD (VTHD), input power factor (PF), voltage regulation (VR), and efficiency (η). The findings show that STF has an ITHD of 8.3%, VTHD of 4.6%, PF of 0.92, VR of 6.2%, and efficiency of 91.3%; DTF has an ITHD of 6.1%, VTHD of 3.9%, PF of 0.95, VR of 5.4%, and 93.5%; HPF has an ITHD of 5.6%, VTHD of 3.5%, 0.96 PF, 5.0% of VR, and 94.2% efficiency. The effectiveness of the proposed CHPH is superior to all other traditional approaches and has the lowest ITHD and VTHD, 3.7% and 2.1%, respectively, the highest PF of 0.987, a better VR of 3.8%, and a higher efficiency of 96.2%. The proposed CHPF shows the high-performance characteristics as reflected in the harmonic reduction, improved voltage stability, power factor, and efficiency. The suggested CHPF complies with IEEE 519 standards and provides better grid compatibility with modern EV charging applications. Full article

Phase-shifting profilometry (PSP) suffers from motion-induced phase-step variations in dynamic scenes. The breakdown of the fixed phase shift assumption results in issues such as ripples, distortions and accuracy decline in PSP systems. To reduce motion-induced phase errors, we propose a wavelet-assisted adaptive extended Kalman filter (WAEKF) to estimate varied pixel-wise phase shift. A wavelet-based strategy is presented to extract an initial spatial carrier frequency at each row from fringe patterns for EKF estimation. A state-space model employing the quadrature phase component and carrier frequency is established in this paper. The unknown phase shifts can be evaluated by using a forward–backward filter. Experiments show that the proposed method can acquire an accurate initial carrier frequency and phase shift map, which effectively reduces 3D reconstruction error and can be extended to N-step PSP systems. Full article