Search Results (4,258)

This paper presents the design and implementation of a real-time visual tracking system for unmanned aerial vehicles (UAVs), based on the DJIPayload Software Development Kit (PSDK), addressing the challenge of balancing high precision with low latency on resource-constrained edge platforms. By utilizing DJI PSDK to abandon the Robot Operating System (ROS) layer and its associated serialization overhead, the proposed Middleware-Free Architecture reduces end-to-end latency by over 60% to approximately 30 ms. To address computational constraints, a Lightweight Asymmetric De-coupled Visual Servoing (ADVS) strategy is proposed. It adopts orthogonal kinematic de-coupling to bypass Jacobian matrix inversion and integrates a non-linear dead-zone mechanism with dynamics-aware gain scheduling to compensate for sensing anisotropy and gravitational nonlinearity. Simultaneously, a Geometry-Aware Fusion strategy is employed to reject visual outliers, while a Finite State Machine (FSM) strictly enforces temporal consistency. Field experiments in various scenarios verify the system’s stability and tracking capability. Specifically, the platform maintains a robust lock on targets at speeds up to 23 m/s across dynamic maneuvers. The successful implementation of this system confirms that high-performance edge tracking does not rely solely on the scaling of visual model complexity but can also be effectively achieved through the architectural minimization of latency combined with the optimization of theoretically grounded robust control strategies. Full article

Phishing remains a persistent cybersecurity threat, exploiting social engineering to bypass traditional defenses. We developed a phishing detection system that integrates baseline supervised learning with Reinforcement Learning through human feedback (RLHF) to improve adaptability against evolving attack strategies. Implemented using the Huawei MindRLHF framework and deployed on Raspberry Pi hardware, the system was evaluated using a dataset of 135,325 email samples consisting of both phishing and legitimate messages. The baseline supervised model achieved 94.3% accuracy, while the RLHF-enhanced model, through 74 iterations, achieved improved adaptability, reaching a 96.8% accuracy with balanced precision and recall. A multi-component reward function was designed to incorporate correct classification, human agreement, confidence matching, and consistency, enabling the model to refine its decision boundaries beyond automated optimization. Real-time monitoring and feedback were facilitated through a hardware-integrated LCD interface. The results confirm enhanced detection accuracy and reduced error rates, demonstrating its viability for deployment. The findings highlight the potential of human-centered RLHF the resilience and scalability of phishing mitigation systems against emerging cyber threats. Full article

Antimicrobial resistance represents one of the most formidable global health crises of the 21st century, driven by the diminishing efficacy of conventional antibiotics due to bacterial adaptation and biofilm formation. In response, antimicrobial nanoformulations have emerged as a transformative therapeutic paradigm, offering multifaceted and innovative mechanisms to combat resistant pathogens. This comprehensive review delineates the broad scope and distinct novelty of nano-enabled antimicrobial strategies, moving beyond the single-target limitations of traditional drugs. We systematically explore the diverse architectural classes of nanoformulations—including metallic, polymeric, and self-assembling nanostructures—and elucidate their unique mechanistic actions. These encompass (1) physical disruption of microbial membranes via electrostatic interactions; (2) catalytic generation of reactive oxygen and nitrogen species to induce an ‘oxidative storm’; (3) intracellular sabotage of essential metabolic pathways; (4) the ‘Trojan horse’ strategy for enhanced drug delivery and bioavailability; (5) efflux pump bypass to counteract a major resistance mechanism; (6) penetration and eradication of resilient biofilms; and (7) disarming pathogens through quorum sensing and virulence inhibition. Furthermore, this review highlights the immunomodulatory potential of nanoformulations; their activity beyond bacteria against fungi, viruses, and parasites; and the critical role of the nano-bio interface defined by surface physicochemistry. We also address the translational pathway, considering challenges in nanotoxicology, scalability, and regulatory approval, alongside the ecological impact and economic horizon of these technologies. This sector is projected to reach USD 5.4 to 8.96 billion by 2033 to 2034, with compound annual growth rates of 11 to 21% across antimicrobial nanomaterials, nanocoatings, and nanomedicine applications. By integrating insights from computational modeling and in silico design, this review underscores how nanoformulations leverage synergistic, multi-target approaches to overcome resistance, enhance therapeutic efficacy, and represent a significant leap forward in the future of infectious disease management. The novelty lies in the holistic and mechanistic synthesis of how nanotechnology is redefining antimicrobial warfare, offering a promising arsenal to avert a post-antibiotic era. Full article

Efficiently converting natural capital into economic assets is a critical challenge in urban–rural transformation, yet the interactive mechanism between institutional land reform and physical spatial restructuring remains underexplored. While traditional frameworks emphasize institutional design, this study identifies a “Spatial-First” mechanism where physical reconfiguration serves as a spatial mediator to catalyze property rights breakthroughs. Using an entropy-weighted coupling coordination model, we analyzed policy dynamics in Nanhai District, China, a unique “dual-pilot” zone, from 2020 to 2024. The results indicate a nonlinear leap in the Coupling Coordination Degree (D) from 0.100 to 0.978. We interpret this surge as a policy-driven shock during the intensive pilot phase, where substantive spatial integration (0.719) effectively bypassed high transaction costs inherent in collective tenure, outpacing institutional progress (0.281). However, an Ecological Lag was observed; the disproportionately low weighting of the ecological carrier index (7.09%) suggests that current gains are primarily driven by green industrialization rather than the expansion of absolute ecological stock. This study concludes that while spatial tools can effectively unlock natural capital value in the short term, long-term sustainability necessitates a strategic shift from administrative-led economic efficiency to market-based ecological restoration. Full article

Lymphedema is a chronic, incurable disease affecting patients who undergo high-risk cancer treatments. Advances in microsurgical techniques have paved the way for the development of techniques that can prevent or treat this unrelenting condition. In this article we discuss microsurgical interventions for the prevention and treatment of lymphedema, as well as the role of robotics in lymphatic surgery. Full article

Ultrasound imaging is a crucial tool for guiding radiation therapy, particularly for cancers such as pancreatic cancer, where tumors exhibit respiration-induced motion. While flexible ultrasound transducers offer improved anatomical conformity and reduced compression-induced distortion compared to rigid probes, their variable geometry presents significant challenges for conventional beamforming. In this study, we investigate a deep learning-based beamforming framework that directly predicts delayed RF data from raw RF input, bypassing explicit transducer shape estimation and traditional delay-and-sum computations. Building upon an artificial curvature simulation strategy, we systematically analyze the impact of curvature-induced variation and inherent RF noise on model performance and generalizability. We further introduce frequency-domain analysis to quantify RF-level signal variation that may not be apparent in spatial-domain image comparisons. Our results demonstrate that although noise-augmented training improves prediction consistency, reconstruction performance remains limited under the current prototype noise conditions. These findings highlight the importance of RF data diversity and noise characterization in developing clinically robust deep learning beamformers for flexible transducer-based ultrasound-guided radiation therapy. Full article

Background/Objectives: Patients with severe hemophilia A on prophylaxis with emicizumab exhibit a mild/moderate bleeding phenotype that requires the use of either recombinant FVIII (rFVIII) or bypassing agents (BPAs) in patients with inhibitors, in the case of breakthrough bleeding or surgery. Since factor IX (FIX) limits the formation of the FIXa–emicizumab–FX complex, exogenously added FIX might enhance complex formation and thrombin generation. This study aimed to compare the procoagulant effects of various FIX concentrates with recombinant activated FVII (rFVIIa), activated prothrombin complex concentrate (aPCC), and rFVIII in SHA patients with and without inhibitors under emicizumab prophylaxis. Methods: Hemostatic changes were monitored using two optimized global coagulation assays: rotational thromboelastometry and calibrated automated thrombin generation. Tubes containing corn trypsin inhibitor (CTI) were used during blood collection to prevent activation. Low concentrations of tissue factor (TF) were used to trigger coagulation in both assays. Results: Ex vivo addition of recombinant FIX concentrates significantly increased the procoagulant activity of emicizumab, achieving levels comparable to therapeutic doses of rFVIIa or rFVIII, and the proportion of active FIXa within the concentrates is a major contributor to their procoagulant function. We assessed the influence of FVIII inhibitors on the hemostatic efficacy of rFIX concentrates and BPAs, finding that rFIX-induced thrombin generation increased in the presence of inhibitors, and no significant differences were observed with BPAs. Conclusions: These findings suggest that FIX concentrates could be an effective alternative to BPAs for emicizumab-treated patients, particularly those with inhibitors. Further studies are needed to confirm their in vivo efficacy and to evaluate thrombotic risk. Full article

Irreversible anterior segment blindness with preserved retinal integrity (e.g., dense corneal opacity) remains a major clinical challenge because effective sight-restoring options are limited. Here, we describe an intraocular micro-light-emitting diode (Micro-LED) epiretinal microdisplay intended to deliver patterned optical stimulation to intact photoreceptors by bypassing opaque anterior optics. The prototype was based on a color-capable VGA microdisplay (640 × 480 pixels) and operated at <30 mW under typical conditions. An ultra-thin flexible cable and a copper-mesh–reinforced polydimethylsiloxane (PDMS) encapsulation provided a compact, conformable intraocular package with high pixel density. We evaluated a monochromatic (green) prototype in a single beagle eye $(n=1)$ using a transscleral implantation approach and performed 7 days of postoperative follow-up with slit-lamp examination and multimodal imaging. Patterned stimulation via the implanted display elicited flash-evoked visual evoked potentials (VEPs) with consistent within-session waveform morphology, providing preliminary neurophysiological surrogate evidence of upstream visual pathway activation under the tested conditions in this single-animal pilot. The short-term postoperative course included transient hypotony and anterior segment inflammation, and implant rotation with associated inferior retinal detachment was observed by day 7, highlighting current biomechanical limitations. Beyond anterior segment opacity, the same intraocular optical interface could be explored as a modular light-delivery platform to pair with emerging retinal therapies (e.g., optogenetics), pending chronic safety and functional validation. This pilot large-animal study therefore provides a translationally relevant testbed while delineating key engineering constraints that must be addressed next. Full article

Photovoltaic (PV) performance in desert environments is significantly hindered by soiling and partial shading. To bridge the gap in empirical data for extreme Saharan conditions, this study presents a novel techno-economic assessment of uniform horizontal shading (UHS) specifically conducted in Mauritania. Controlled outdoor experiments were performed using a 250 W crystalline silicon PV module and a PVPM 2540C I–V curve tracer, applying progressive shading levels from 2.5% to 20%. The novelty of this work lies in the integration of high-resolution experimental I–V/P–V characterization with a localized techno-economic model for five pre-commercial PV plants. It was observed that PV modules are exceptionally sensitive to shading; specifically, a mere 10% shaded area leads to a catastrophic 90% drop in power and current, while the voltage remains remarkably stable. Thermographic analysis further validates the thermal gradients and bypass diode functionality. By quantifying the financial impacts, this research highlights that cumulative economic losses across the five real-world sites reached 87.95%, exceeding 55,000 MRU. These findings provide a strategic framework for optimizing PV systems in arid terrains and offer a robust tool for enhancing the design and operation of large-scale solar applications in desert environments. Full article

The aim of this study was to assess the impact of variations in the 3-hourly geomagnetic activity level during the period of the lowest solar and geomagnetic activity on the psychological state of patients who underwent coronary artery bypass grafting or valve surgery. The study was performed in Kaunas, Lithuania, during 2008–2012. The psychological state of 233 patients was assessed using the Symptom Checklist-90-Revised instrument (SCL-90-R) at 1.5 months, 1 year, and 2 years after the surgery (N = 531). During days of a negative difference between k-index sums at 18:00–00:00 h and 06:00–12:00, all SCL scores were statistically significantly higher. A low k- sum during 18:00–00:00 on the previous day was associated with an increase in anxiety, anger–hostility, phobic anxiety, paranoid ideation, and psychoticism. The combination of these conditions was associated with higher values of the SCL scores. These effects were observed at 1.5 and 12 months after the surgery. During the period lasting from 18:00 on the previous day to 12:00 on the day of the test, variations in k-indices that were not in line with the general trend of changes in the k-index were associated with a poorer psychological state in patients after open-heart surgery. Full article

After vessel preparation, using different strategies such as balloon angioplasty, specialty balloons, atherectomy or intravascular lithotripsy, definitive treatment has emerged as a key feature in endovascular treatment strategies. Based on current guidelines, endovascular treatment is the most common treatment option in patients with claudication. In patients with chronic limb-threatening ischemia (CLTI), on the other hand, the best treatment modality, including bypass surgery and endovascular revascularization, needs to be selected by an interdisciplinary team, focusing on individual anatomic and patient-specific characteristics, on the availability of a vein graft and on cardiovascular and other comorbidities of the patients. With endovascular therapy, currently, a plethora of options are available for the treatment of femoropopliteal lesions, which are increasingly gaining in complexity. Therefore, a practical systematic case-based approach, entailing contemporary treatment options, like drug-coated balloon (DCB) angioplasty tools, self-expanding bare-metal stents (BMSs), drug-eluting stents (DESs), interwoven stents and covered stents, is crucial. Generally, most endovascular operators adhere to the ‘leave nothing behind’ concept, meaning that, after proper lesion preparation, lesions can be treated with DCBs, avoiding the implantation of permanent metallic implants. However, in the case of severe dissections or significant recoil, stent implantation becomes necessary to achieve adequate limb perfusion. The selection between long versus spot stenting and the different stent options depends on the current scientific evidence, guidelines and expert opinion statements. An interdisciplinary expert consensus was recently compiled on how these modalities should be used in specific lesions and patients in the femoropopliteal segment. Herein we present a practical case-based approach, which is based on this algorithm and aims at harmonization of endovascular treatment strategies in daily practice and ultimately at further improvements in limb and patient outcomes. Full article

Adversarial examples, created by adding small distortions to audio, can fool neural network models and cause automatic speech recognition (ASR) systems to produce incorrect outputs. Most current detection methods rely on the recognition capabilities of ASR systems. As a result, they often fail to detect such examples when ASR performance degrades or when facing an evasion attack—referred to in this paper as a “partial adversarial attack”—that is specifically designed to bypass ASR models. In this paper, we identify a distinct noise energy difference between adversarial examples and their original audio. Moreover, this noise energy difference is typically greater than that between adversarial examples and their re-attacked examples. This finding leads us to propose a novel detection method that fundamentally departs from traditional approaches by operating independently of ASR systems. The proposed method employs a detection strategy that involves re-attacking the input audio and identifies adversarial examples by characterizing the noise energy difference before and after re-attack without relying on ASR systems. The experimental results demonstrate that the proposed method detects various state-of-the-art adversarial attacks. Compared with the baselines, the proposed method achieves substantially better detection performance across standard adversarial examples, noisy adversarial examples, and partial adversarial examples. Full article

Wireless medical sensor networks (WMSNs) enable continuous patient monitoring by transmitting sensitive physiological data over open wireless links. Given the resource-constrained nature and large-scale deployment of such networks, authentication mechanisms must be both lightweight and privacy-preserving. Moreover, due to the frequent turnover of patients and devices in hospital environments, timely member revocation is crucial to prevent discharged or compromised entities from injecting forged reports that could mislead medical diagnosis. Although existing pairing-free certificateless aggregate authentication schemes are efficient, they often suffer from critical security and privacy vulnerabilities. Recently, an efficient certificateless authentication scheme with revocation has been proposed. However, our analysis reveals that the scheme presents the following security vulnerabilities: (i) member witnesses can be recovered from public information, (ii) revocation checks can be bypassed via identity grafting attack, and (iii) user identities can be linked due to the long-term use of static pseudonyms. To address these issues, we propose a security-enhanced certificateless aggregate authentication protocol with revocation for WMSNs. Our design enforces strong identity–membership binding to resist grafting attacks, employs a non-interactive zero-knowledge membership proof to preserve witness secrecy, and adopts dynamic pseudonym rotation to achieve unlinkability. We provide formal security proofs and comprehensive performance comparisons. The results indicate that, at the same security level, our protocol achieves more efficient signature verification while maintaining communication overhead comparable to existing schemes. In addition, the overhead introduced by our revocation mechanism remains constant, making it well suited for large-scale WMSNs deployments with frequent membership changes. Full article

Multiview video coding grows exponentially with the number of views, and VVC-based systems face particularly severe computational burdens from exhaustive inter-view prediction searches. We propose VVC-MV-CM, a complexity-managed multiview extension of VVC that combines rule-based pre-screening with CNN-based adaptive inter-view prediction bypassing within a two-stage decision engine. Performance trends are observed across 19 test sequences covering planar, arc, and spherical camera configurations under all-view and selected-view encoding modes. For planar all-view configurations, VVC-MV-CM-A achieves −52.7% BD-rate relative to MIV-A with 68% encoding time reduction. Arc arrangements yield competitive performance at −1.26% (all-view) and approximately −1% (selected-view) BD-rate. Spherical configurations demonstrate −19.8% (all-view) and −15.0% (selected-view) BD-rate gains, driven by multi-reference redundancy and temporal prediction prioritization. View density analysis reveals a 4.8 percentage-point compression difference between all-view and selected-view configurations, corresponding to approximately 2.4% efficiency gain per doubling of camera count. The proposed codec achieves 1.17–1.46× encoding time relative to MIV anchors with 18–36% decoding speedup, establishing configuration-adaptive prediction as an effective and deployable approach to multiview video coding across a wide range of geometric complexities and view-sampling densities. Full article

Rotary kiln-based activated carbon production combines high-temperature operation with flammable/reducing gases, carbonaceous dust, and downstream off-gas treatment and acid/base washing, creating complex escalation pathways. This study prioritizes safety improvements by applying classical failure modes and effects analysis (FMEA) and a transparent Fuzzy-FMEA framework to 18 representative failure modes (six each for kiln/activation, acid/base handling, and atmosphere/control). Five experts evaluated Severity, Occurrence, and Detection on a 10-point scale. The fuzzy model used triangular membership functions (L/M/H), a monotonic 27-rule base, Mamdani max–min inference, and centroid defuzzification to compute a continuous fuzzy risk priority number (FRPN, 0–10). Classical FMEA identified dust explosion (RPN = 405), temperature control failure (RPN = 378), and off-gas leakage (RPN = 324) as the highest-ranked risks. Fuzzy-FMEA preserved the top-risk group while more strongly highlighting barrier-related risks, placing off-gas leakage, instrumentation/interlock failure, and electrostatic ignition control alongside dust explosion (FRPN 9.221–9.332). The rankings were strongly correlated (Spearman ρ = 0.871; Kendall τ = 0.752), yet mid-risk items were rearranged (mean |Δrank| = 2.06; max = 5), improving discrimination within tied RPN clusters. The five highest-priority scenarios were reconstructed into actionable engineering packages, including dust and ignition control, off-gas integrity linked to shutdown logic, interlock proof testing and bypass management, and independent protection layers for kiln temperature control. Full article