Search Results (3,442)

All-inorganic halide perovskites have attracted significant interest in photodetector applications due to their remarkable photoresponse properties. However, the toxicity and instability of lead-based perovskites hinder their commercialization. In this work, we propose cubic Ba₃SbI₃ as a promising, environmentally friendly, lead-free material for next-generation photodetector applications. Ba₃SbI₃ shows good light absorption, low effective masses, and favorable elemental abundance and cost, making it a promising candidate compound for device applications. Its structural, mechanical, electronic, and optical properties were systematically investigated using density functional theory (DFT) with the Perdew–Burke–Ernzerhof (PBE) and hybrid HSE06 functionals. The material was found to be dynamically and mechanically stable, with a direct bandgap of 0.78 eV (PBE) and 1.602 eV (HSE06). Photodetector performance was then simulated in an Al/FTO/In₂S₃/Ba₃SbI₃/Sb₂S₃/Ni configuration using SCAPS-1D. To optimize device efficiency, the width, dopant level, and bulk concentration for each layer of the gadgets were systematically modified, while the effects of interface defects, operating temperature, and series and shunt resistances were also evaluated. The optimized device achieved an open-circuit voltage (Voc) of 1.047 V, short-circuit current density (Jsc) of 31.65 mA/cm², responsivity of 0.605 A W⁻¹, and detectivity of 1.05 × 10¹⁷ Jones. In contrast, in the absence of the Sb₂S₃ layer, the performance was reduced to a Voc of 0.83 V, Jsc of 26.8 mA/cm², responsivity of 0.51 A W⁻¹, and detectivity of 1.5 × 10¹⁵ Jones. These results highlight Ba₃SbI₃ as a promising platform for high-performance, cost-effective, and environmentally benign photodetectors. Full article

Background: Pneumothorax (PTX) requires rapid recognition in emergency and critical care. Lung ultrasound (LUS) offers a fast, radiation-free alternative to computed tomography (CT), but its accuracy is limited by operator dependence. Artificial intelligence (AI) may standardize interpretation and improve performance. Methods: This retrospective single-center study included 46 patients (23 with CT-confirmed PTX and 23 controls). Sixty B-mode and M-mode frames per patient were extracted using a Clarius C3 HD3 wireless device, yielding 2760 images. CT served as the diagnostic reference. Experimental studies were conducted within the framework of three scenarios. Transformer-based models, Vision Transformer (ViT) and DINOv2, were trained and tested under two scenarios: random frame split and patient-level split. Also, Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) classifiers were trained on the feature maps extracted by using Video Vision Transformer (ViViT) for ultrasound video sequences in Scenario 3. Model performance was evaluated using accuracy, sensitivity, specificity, F1-score, and area under the ROC curve (AUC). Results: Both transformers achieved high diagnostic accuracy, with B-mode images outperforming M-mode inputs in the first two scenarios. In Scenario 1, ViT reached 99.1% accuracy, while DINOv2 achieved 97.3%. In Scenario 2, which avoided data leakage, DINOv2 performed best in the B-mode region (90% accuracy, 80% sensitivity, 100% specificity, F1-score 88.9%). ROC analysis confirmed strong discriminative ability, with AUC values of 0.973 for DINOv2 and 0.964 for ViT on B-mode images. Also, both RF and XGBoost classifiers trained on the ViViT feature maps reached 90% accuracy on the video sequences. Conclusions: AI-assisted LUS substantially improves PTX detection, with transformers—particularly DINOv2—achieving near-expert accuracy. Larger multicenter datasets are required for validation and clinical integration. Full article

Neural networks are powerful, high-accuracy systems whose trained parameters represent a valuable intellectual property. Building models that reach top level performance is a complex task and requires substantial investments of time and money so protecting these assets is an increasingly important task. Extensive research has been carried out on Neural Network Watermarking, exploring the possibility of inserting a recognizable marker in a host model either in the form of a concealed bit-string or as a characteristic output, making it possible to confirm network ownership even in the presence of malicious attempts at erasing the embedded marker from the model. The study examines the applicability of Opt-FreeMark, a non-invasive post-training white-box watermarking technique, obtained by modifying and optimizing an already existing state-of-the-art technique for tiny neural networks. Here, “Tiny” refers to models intended for ultra-low-power deployments, such as those running on edge devices like sensors and micro-controllers. Watermark robustness is also demonstrated by simulating common model-modification attacks that try to eliminate it from the model while preserving performance; the results presented in the paper indicate that the watermarking scheme effectively protects the networks against these manipulations. Full article

The Huanjing-2A/2B (HJ-2A/2B) satellites are China’s next-generation environmental monitoring satellites, equipped with four visible light wide-swath charge-coupled device (CCD) sensors. These sensors enable the acquisition of 16-m multispectral imagery (16m-MSI) with a swath width of 800 km through field-of-view stitching. However, traditional vicarious calibration techniques are limited by their calibration frequency, making them insufficient for continuous monitoring requirements. To address this challenge, the present study proposes a spectral-angle difference correction-based cross-calibration approach, using the Landsat 8/9 Operational Land Imager (OLI) as the reference sensor to calibrate the HJ-2A/2B CCD sensors. This method improves both radiometric accuracy and temporal frequency. The study utilizes cloud-free image pairs of HJ-2A/2B CCD and Landsat 8/9 OLI, acquired simultaneously at the Dunhuang and Golmud calibration sites between 2021 and 2024, in combination with atmospheric parameters from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) dataset and historical ground-measured spectral reflectance data for cross-calibration. The methodology includes spatial matching and resampling of the image pairs, along with the identification of radiometrically stable homogeneous regions. To account for sensor viewing geometry differences, an observation-angle linear correction model is introduced. Spectral band adjustment factors (SBAFs) are also applied to correct for discrepancies in spectral response functions (SRFs) across sensors. Experimental results demonstrate that the cross-calibration coefficients differ by less than 10% compared to vicarious calibration results from the China Centre for Resources Satellite Data and Application (CRESDA). Additionally, using Sentinel-2 MSI as the reference sensor, the cross-calibration coefficients were independently validated through cross-validation. The results indicate that the radiometrically corrected HJ-2A/2B 16m-MSI CCD data, based on these coefficients, exhibit improved radiometric consistency with Sentinel-2 MSI observations. Further analysis shows that the cross-calibration method significantly enhances radiometric consistency across the HJ-2A/2B 16m-MSI CCD sensors, with radiometric response differences between CCD1 and CCD4 maintained below 3%. Error analysis quantifies the impact of atmospheric parameters and surface reflectance on calibration accuracy, with total uncertainty calculated. The proposed spectral-angle correction-based cross-calibration method not only improves calibration accuracy but also offers reliable technical support for long-term radiometric performance monitoring of the HJ-2A/2B 16m-MSI CCD sensors. Full article

Massive machine-type communications (mMTC) in future 6G networks will involve a vast number of devices with sporadic traffic. Grant-free access has emerged as an effective strategy to reduce the access latency and processing overhead by allowing devices to transmit without prior permission, making accurate active user detection and channel estimation (AUDCE) crucial. In this paper, we investigate the joint AUDCE problem in wideband massive access systems. We develop an innovative channel prior model that captures the dual correlation structure of the channel using three state variables: active indication, channel supports, and channel values. By integrating Markov chains with coupled Gaussian distributions, the model effectively describes both the structural and numerical dependencies within the channel. We propose the correlated hybrid message passing (CHMP) algorithm based on Bethe free energy (BFE) minimization, which adaptively updates model parameters without requiring prior knowledge of user sparsity or channel priors. Simulation results show that the CHMP algorithm accurately detects active users and achieves precise channel estimation. Full article

Quantum-dot light-emitting diodes (QLEDs) have emerged as promising candidates for next-generation display technologies owing to their high color purity and external quantum efficiency. Despite rapid advancements in device performance, operational stability and long-term reliability remain critical challenges, particularly for cadmium-free and blue-emitting QLEDs. This review provides a comprehensive overview of the degradation mechanisms of QLEDs, emphasizing the relationship between environmental factors, such as moisture, oxygen, and thermal stress, and excitonic factors, including charge-injection imbalance, Auger recombination, and interface deterioration. We further highlight the role of nondestructive characterization techniques, including impedance spectroscopy, Fourier transform infrared spectroscopy, transient photoluminescence, transient electroluminescence, transient absorption, and electroabsorption spectroscopy, in probing real-time charge dynamics and material degradation. By integrating the insights from these operando analyses, this review offers a detailed perspective on the origins of device degradation and provides guidance for rational design strategies aimed at enhancing the operational stability and commercialization potential of QLEDs. Full article

The surface quality of high-performance electroformed components, such as the matrix material of the rocket thrust chamber wall, is critical to the overall performance of the devices. However, under high current density and elevated cathode rotation speeds, excessive internal stress often leads to layer detachment, compromising coating adhesion and stability. This study introduces an improved electroforming process termed microbead fusion flexible friction-assisted electroforming (MF³AEF) and examines its effect on the surface roughness of electroformed copper layers. By comparing conventional direct current electroforming (DCEF), abrasive-assisted electroforming (AAEF) with free ceramic beads, and the proposed MF³AEF process, this work investigates the variations in surface quality and roughness under different current densities and cathode rotation speeds. The results indicate that at a current density of 6.8 A/dm² and a cathode rotation speed of 90 rpm, the surface roughness of the MF³AEF-produced layer is reduced to Ra0.24 µm, representing a 98.2% reduction compared to the Ra13.35 µm achieved by DCEF. This demonstrates that MF³AEF significantly enhances surface properties and markedly reduces the surface roughness of electroformed layers. Full article

Objectives: The purpose of this study was to determine whether concomitant tricuspid valve repair (TVr) at the time of left ventricular assist device (LVAD) implantation improves outcomes in patients with ≥moderate tricuspid regurgitation (TR) and to evaluate the prognostic value of preoperative right ventricular (RV) strain. Methods: In a retrospective analysis of 100 LVAD recipients (44 TVr; 56 No-TVr), preoperative (preop) and postoperative (postop) clinical, echocardiographic, and hemodynamic variables, including pulmonary vascular resistance (PVR) and pulmonary artery pulsatility index (PAPI), were analyzed. RV free wall strain (RV-FWS) and RV fractional area change (RV-FAC) were measured by speckle tracking. Early right heart failure (RHF) was modeled with multivariable logistic regression, and 2-year mortality was assessed with Fine–Gray competing risk regression. Preoperative and three-month measurements were compared within each of the 100 patients. Results: Baseline invasive hemodynamics, RV-FWS, and RV-FAC were similar between the TVr and No-TVr groups. TVr at the time of LVAD implantation reduced postoperative TR grade, but it did not improve RV-FWS or RV-FAC at 3 months. The No-TVr patients were more often discharged home and had lower 30-day readmissions. PVR was comparable preoperatively and at 3 months postoperatively. In adjusted analyses, preop PVR, PAPI, and TVr were not independently associated with early RHF, whereas decreased preoperative RV-FWS and lower preop RV-FAC independently predicted higher 2-year mortality. Conclusions: In LVAD recipients with ≥moderate TR, concomitant TVr lowers postoperative TR severity but does not improve early RHF, RV strain-based remodeling, or 2-year mortality. Preoperative RV deformation metrics, rather than preoperative PVR or PAPI, independently predict survival following LVAD implantation with or without TVr. Full article

Patent foramen ovale (PFO) is implicated in cryptogenic stroke and other clinical syndromes, with transcatheter closure demonstrating superiority over medical therapy in selected patients. Most closure devices are composed of nitinol, a nickel–titanium alloy, raising concerns in individuals with nickel hypersensitivity, one of the most prevalent contact allergies worldwide. Although typically manifesting as localized dermatitis, nickel allergy has been associated with systemic reactions after device implantation, including chest pain, palpitations, migraines, dyspnea, and cutaneous eruptions. Recent evidence indicates that nickel-sensitive patients experience a significantly higher incidence of post-procedural device-related symptoms. Nevertheless, severe reactions remain rare, and the benefits of PFO closure generally outweigh the risks. The predictive value of pre-implantation patch testing remains uncertain, and the lack of nickel-free alternatives constrains device selection. Management strategies are empirical, relying on symptomatic treatment with corticosteroids, antihistamines, or device explantation in refractory cases. Future research should focus on elucidating the pathophysiology of nickel-induced hypersensitivity in cardiovascular implants, improving diagnostic algorithms, and developing biocompatible, nickel-free devices. A multidisciplinary approach involving cardiologists, dermatologists, and allergists is essential to optimize outcomes in this complex subset of patients. Full article

Electroencephalography is a widely used method for emotion recognition. However, it requires specialized equipment, leading to high costs. Additionally, attaching devices to the body during such procedures may cause physical and psychological stress to participants. These issues are addressed in this study by focusing on physiological signals that are noninvasive and contact-free, and a generalized method for estimating emotions is developed. Specifically, the facial skin temperature and eye-opening degree of participants captured via infrared thermography and visible cameras are utilized, and emotional states are estimated while Japanese older adults view digital content. Emotional responses while viewing digital content are often subtle and dynamic. Additionally, various emotions occur during such situations, both positive and negative. Fluctuations in facial skin temperature and eye-opening degree reflect activities in the autonomic nervous system. In particular, expressing emotions through facial expressions is difficult for older adults; as such, emotional estimation using such ecological information is required. Our study results demonstrated that focusing on skin temperature changes and eye movements during emotional arousal and non-arousal using bidirectional long short-term memory yields an F1 score of 92.21%. The findings of this study can enhance emotion recognition in digital content, improving user experience and the evaluation of digital content. Full article

The widespread adoption of mobile devices has made secure and user-friendly biometric authentication critical. However, widely used modalities such as fingerprint and facial recognition show limited robustness under uncontrolled illumination and on heterogeneous devices. In contrast, palmprint recognition offers strong potential because of its rich textural patterns and high discriminative power. This study addresses the limitations of laboratory-based datasets that fail to capture real-world challenges. We introduce MPW-180, a novel dataset comprising videos of 180 participants recorded on their own smartphones in everyday environments. By systematically incorporating diverse illumination conditions (with and without flash) and natural free-hand movements, MPW-180 is the first dataset to adopt a bring-your-own-device paradigm, providing a realistic benchmark for evaluating generalization in mobile biometric models. In addition, we propose PalmWildNet, an SE-block-enhanced deep learning architecture trained with Triplet Loss and a cross-illumination sampling strategy. The experimental results show that conventional methods suffer over 50% performance degradation under cross-illumination conditions. In contrast, our method reduces the Equal Error Rate to 1–2% while maintaining an accuracy above 97%. These findings demonstrate that the proposed framework not only tolerates illumination variability but also learns robust illumination-invariant representations, making it well-suited for mobile biometric authentication. Full article

Background and Clinical Significance: Tandem pathology at the dominant-hemisphere middle cerebral artery (MCA)—combining a wide-neck bifurcation aneurysm that shares the neck with both M2 origins and a short dorsal M1 fusiform dilation embedded in the lenticulostriate belt—compresses the therapeutic margin and complicates device-first pathways. We aimed to describe an anatomy-led, microscope-only sequence designed to secure an immediate branch-definitive result at the fork and to remodel dorsal M1 without perforator compromise, and to place these decisions within a pragmatic perioperative framework. Case Presentation: A 37-year-old right-handed man with reproducible, load-sensitive cortical association and capsulostriate signs underwent high-fidelity digital subtraction angiography (DSA) with 3D rotational reconstructions. Through a left pterional approach, vein-respecting Sylvian dissection achieved gravity relaxation. Reconstruction proceeded in sequence: a fenestrated straight clip across the bifurcation neck with the superior M2 encircled to preserve both M2 ostia, followed by a short longitudinal clip parallel to M1 to reshape the fusiform segment while keeping each lenticulostriate mouth visible and free. Temporary occlusion windows were brief (bifurcation 2 min 30 s; M1 < 2 min). No neuronavigation, intraoperative fluorescence, micro-Doppler, or intraoperative angiography was used. No perioperative antiplatelets or systemic anticoagulation were administered and venous thromboembolism prophylaxis followed institutional practice. The bifurcation dome collapsed immediately with round, mobile M2 orifices, and dorsal M1 regained near-cylindrical geometry with patent perforator ostia under direct inspection. Emergence was neurologically intact, headaches abated, and preoperative micro-asymmetries resolved without new deficits. The early course was uncomplicated. Non-contrast CT at three months showed structurally preserved dominant-hemisphere parenchyma without infarction or hemorrhage. Lumen confirmation was scheduled at 12 months. Conclusions: In dominant-hemisphere tandem MCA disease, staged, perforator-sparing clip reconstruction can restore physiologic branch and perforator behavior while avoiding prolonged antiplatelet exposure and device-related branch uncertainty. A future-facing pathway pairs subtle clinical latency metrics with high-fidelity angiography, reports outcomes in branch- and perforator-centric terms, and, where available, incorporates patient-specific hemodynamic simulation and noninvasive lumen surveillance to guide timing, technique, and follow-up. Full article

Acoustic fingerprints can be used for device-to-device authentication due to manufacturing-induced variations in microphones and speakers. However, previous works have focused mostly on recognizing single devices from a set of multiple devices, which may not be sufficiently realistic since in practice, a single device has to be recognized from a very large pool of devices that are not available for training machine learning classifiers. Therefore, in this work, we focus on one-class classification algorithms, namely one-class Support Vector Machine and the local outlier factor. As such, learning the fingerprint of a single device is sufficient to recognize the legitimate device and reject all other attempts to impersonate it. The proposed application can also rely on cloud-based deployment to free the smartphone from intensive computational tasks or data storage. For the experimental part, we rely both on smartphones and an automotive-grade Android headunit, exploring in-vehicle environments as the main area of application. We create a dataset consisting of more than 5000 measurements and achieve a recognition rate ranging from 50% to 100% for different devices under various environmental conditions such as distance, altitude, and component aging. These conditions also serve as our limitations, however, we propose different solutions for overcoming them, which are part of our threat model. Full article

Background: Bioelectrical Impedance Vector Analysis (BIVA) is a qualitative method that standardizes resistance and reactance relative to stature (R/H and Xc/H) and plots them as vectors on an R-Xc graph. This equation-free approach assesses body composition, allowing for the evaluation of hydration status and cellular integrity through tolerance ellipses. This study aimed to systematically map BIVA reference ellipses across general, pediatric, pathological, and athletic populations. Methods: A scoping review was conducted according to PRISMA-ScR guidelines. Five databases were searched. Extracted data included (a) sample characteristics (sample size, age, sex, BMI, country, ethnicity), (b) population type, (c) analyzer specifications, and (d) R/H and Xc/H means, standard deviations, and correlation values. Results: A total of 53 studies published between 1994 and July 2025 were included. From these, 508 tolerance ellipses were identified: 281 for the general population (18–92 years), 133 for children/adolescents (0–18 years), 49 for athletes, and 45 for pathological groups. Studies were primarily conducted in Europe and the Americas, using 11 analyzers with variations in measurement protocols, including body side, posture, and electrode placement. Conclusions: This scoping review categorizes the existing BIVA tolerance ellipses by population type, sex, age, BMI, device used, and measurement protocol. The structured presentation is intended to guide researchers, clinicians, nutritionists, and sports professionals in selecting appropriate reference ellipses tailored to specific populations and contexts. Full article

Based on first-principles calculations and linear-response time-dependent density functional theory within the random phase approximation (LR-TDDFT-RPA), this work systematically investigates the modulation of Dirac plasmons in germanene via carrier doping, biaxial strain, and substrate effects. The results demonstrate that carrier doping induces highly tunable Dirac plasmons whose excitation energy follows the ω ∝ n^1/4 scaling relation, leading to a sublinear increase with doping concentration. Furthermore, biaxial strain effectively modulates the Fermi velocity, and the established ω ∝ √V_F relationship directly explains the observed linear tuning of plasmon energy with strain. More importantly, the combined modulation of carrier density and strain enables a significantly broader plasmon energy range (0.16–0.61 eV) than achievable through individual parameter control. When supported on hBN substrates, germanene maintains the characteristic √q plasmon dispersion despite band hybridization and a redshift in energy, a behavior well explained by the 2D free electron gas model. This study provides important theoretical insights into the multi-parameter control of Dirac plasmons and supports the design of germanene-based tunable nanophotonic devices. Full article