Search Results (861)

Pedestrian trajectory prediction is crucial for autonomous systems navigating human-populated environments. However, existing methods face fundamental challenges including spurious correlations induced by confounding social environments, passive uncertainty modeling that limits prediction diversity, and bias coupling during feature interaction that contaminates trajectory representations. To address these issues, we propose a novel Causal Intervention and Counterfactual Reasoning (CICR) framework that shifts trajectory prediction from associative learning to a causal inference paradigm. Our approach features a hierarchical architecture having three core components: a Multisource Encoder that extracts comprehensive spatio-temporal and social context features; a Causal Intervention Fusion Module that eliminates confounding bias through the front-door criterion and cross-attention mechanisms; and a Counterfactual Reasoning Decoder that proactively generates diverse future trajectories by simulating hypothetical scenarios. Extensive experiments on the ETH/UCY, SDD, and AVD datasets demonstrate superior performance, achieving an average ADE/FDE of 0.17/0.24 on ETH/UCY and 7.13/10.29 on SDD, with particular advantages in long-term prediction and cross-domain generalization. Full article

Effective detection of unexpected events in wide-area surveillance remains a critical challenge in the development of intelligent monitoring systems. Recent advancements in Narrowband Internet of Things (NB-IoT) and 5G technologies provide a robust foundation to address this issue. This study presents an integrated architecture for real-time event detection and response. The system utilizes the Constrained Application Protocol (CoAP) to transmit encapsulated JPEG images from NB-IoT modules to an Internet of Things (IoT) server. Upon receipt, images are decoded, processed, and archived in a centralized database. Subsequently, image data are transmitted to client applications via WebSocket, leveraging the Message Queuing Telemetry Transport (MQTT) protocol. By performing temporal image comparison, the system identifies abnormal events within the monitored area. Once an anomaly is detected, a visual alert is generated and presented through an interactive interface. The test results show that the image recognition accuracy is consistently above 98%. This approach enables intelligent, scalable, and responsive wide-area surveillance reliably, overcoming the constraints of conventional isolated and passive monitoring systems. Full article

Vascular calcification is a complex, regulated process characterized by the pathological deposition of calcium phosphate minerals in the vascular wall, contributing to cardiovascular morbidity and mortality, particularly in patients with chronic kidney disease (CKD), diabetes, and aging. Once thought to be a passive degenerative process, it is now recognized as an active, cell-mediated phenomenon that shares molecular features with bone formation. Beyond traditional risk factors such as hyperphosphatemia and inflammation, disturbances in iron metabolism have recently emerged as modulators of vascular calcification. Iron, a vital trace element involved in numerous cellular functions, exhibits a dual role as both a potential driver and inhibitor of calcification, depending on its dose, distribution, and cellular context. In this review, we summarize in vitro and in vivo studies investigating the impact of iron on the osteochondrogenic differentiation and calcification of vascular smooth muscle cells and valve interstitial cells. We further highlight mechanistic insights that may explain the divergent findings reported in the literature. Finally, we compile clinical evidence linking disturbances in iron metabolism with coronary artery calcification and cardiovascular mortality in CKD patients. Full article

A biomimetic adaptive façade applies natural principles to building design using shading devices that dynamically respond to environmental changes, enhancing daylight, thermal comfort, and energy efficiency. While motorised systems offer precision through sensors and mechanical actuation, they consume energy and are complex. In contrast, passively actuated systems use smart materials that respond to environmental stimuli, offering simpler and more sustainable operation, but often lack responsiveness to dynamic conditions. This study explores a sequential approach by initially developing motorised shading concepts before transitioning to a passive actuation strategy. In the first phase, nine mechanically actuated shading device concepts were designed, inspired by the opening and closing behaviour of plant stomata, and evaluated on structural robustness, actuation efficiency, ease of installation, and visual integration. One concept was selected for further development. In the second phase, a biocomposite made of polylactic acid (PLA) and regenerated cellulose fibres was used for Fused Deposition Modelling (FDM) to fabricate 3D-printed modules with passive, moisture-responsive actuation. The modules underwent environmental testing, demonstrating repeatable shape changes in response to heat and moisture. Moisture application increased the range of motion, and heating led to flap closure as water evaporated. Reinforcement and layering strategies were also explored to optimise movement and minimise unwanted deformation, highlighting the material’s potential for sustainable, responsive façade systems. Full article

Carcinogenesis is driven by aberrant activation of molecular signaling pathways governing cell proliferation, apoptosis, and differentiation. Among these, the RAS/RAF/MEK/ERK (RAS/MAPK) cascade is one of the most frequently dysregulated oncogenic pathways, driving tumor initiation and progression across diverse cancer types. Although inhibitors of BRAF and MEK have achieved clinical success in selected malignancies, adaptive resistance often undermines therapeutic durability. This has spurred interest in alternative nodes within the pathway. The kinase suppressor of Ras (KSR) is a scaffold protein that organizes RAF, MEK, and ERK into functional complexes, ensuring efficient and sustained signal transmission. Once regarded as a passive structural component, KSR1 is now recognized as an active regulator of pathway dynamics. Emerging evidence indicates that KSR1 overexpression promotes cancer cell proliferation and survival, while genetic or pharmacologic inhibition of KSR1 attenuates RAS/MAPK signaling and suppresses tumor growth in preclinical models. In this review, we provide a comprehensive overview of accessory and scaffold proteins modulating the RAS/MAPK pathway, with a particular focus on KSR1. We highlight its structural and functional properties, summarize preclinical evidence for KSR1-targeted interventions, and discuss its therapeutic potential in cancer, with emphasis on hepatocellular carcinoma (HCC). Full article

Background: Stapes prostheses represent one of the earliest and most widely applied “biomedical actuators” designed to restore hearing in patients with otosclerosis. Unlike conventional actuators, which convert energy into motion, stapes prostheses function as passive or smart micro-actuators, transmitting and modulating acoustic energy through the ossicular chain. Objective: This paper provides a comprehensive analysis of stapes prostheses from an engineering and biomedical perspective, emphasizing design principles, materials science, and recent innovations in smart actuators based on shape-memory alloys combined with surgical applicability. Methods: A narrative review of the evolution of stapes prostheses was consolidated by institutional surgical experience. Comparative evaluation focused on materials (Teflon, Fluoroplastic, Titanium, Nitinol) and design solutions (manual crimping, clip-on, heat-activated prostheses). Special attention was given to endoscopic stapes surgery, which highlights the ergonomic and functional requirements of new device designs. Results: Traditional fluoroplastic and titanium pistons provide reliable sound conduction but require manual crimping, with a higher risk of incus necrosis and displacement. Innovative prostheses, particularly those manufactured from nitinol, act as self-crimping actuators activated by heat, improving coupling precision and reducing surgical trauma. Emerging designs, including bucket-handle and malleus pistons, expand applicability to complex or revision cases. Advances in additive manufacturing and middle ear cement fixation offer opportunities for customized, patient-specific actuators. Conclusions: Stapes prostheses have evolved from simple passive pistons to innovative biomedical actuators exploiting shape-memory and biocompatible materials. Future developments in stapes prosthesis design are closely linked to 3D printing technologies. These developments have the potential to enhance acoustic performance, durability, and patient outcomes, thereby bridging the gap between otologic surgery and biomedical engineering. Full article

Background: Enhancer RNAs (eRNAs), a subclass of long non-coding RNAs transcribed from enhancer regions, have emerged as dynamic regulators of gene expression, tumor progression, and therapeutic response. In gliomas, their biological and clinical significance is only recently being elucidated. This systematic review aimed to synthesize current evidence regarding the role of eRNAs in gliomagenesis, chemoresistance, and prognosis. Methods: We conducted a systematic review following PRISMA 2020 guidelines. PubMed/MEDLINE and Scopus databases were searched on September 2025 using a predefined strategy. Eligible studies included clinical or pre-clinical analyses of eRNAs in gliomas, reporting associations with tumorigenicity, survival, or resistance to temozolomide (TMZ). Risk of bias was assessed using ROBINS-I (Version 2), and findings were qualitatively synthesized. Results: From 26 retrieved records, 10 studies were included, encompassing 22 unique eRNAs. Two studies demonstrated that TMZR1-eRNA and LINC02454* modulate TMZ sensitivity by regulating STAT3, SORBS2, and DDR1 pathways. Seven studies evaluated prognostic implications: 12 eRNAs (e.g., AC003092.1, CYP1B1-AS1, CRNDE) were consistently associated with poor survival, while seven (e.g., LINC00844, ENSR00000260547) correlated with favorable outcomes, particularly in low-grade gliomas. One mechanistic study showed that HOXDeRNA directly promotes gliomagenesis by displacing PRC2 repression at key transcription factor promoters and activating oncogenic super-enhancers. Conclusions: eRNAs are not passive transcriptional by-products but active modulators of glioma biology. They influence tumor initiation, therapeutic resistance, and survival outcomes, underscoring their potential as prognostic biomarkers and therapeutic targets. Future research should validate these findings in larger clinical cohorts and explore strategies for eRNA-directed therapies in precision neuro-oncology. Full article

With the rapid proliferation of unmanned aerial vehicles (UAVs) and the associated rise in security concerns, there is a growing demand for robust detection and identification systems capable of operating reliably in complex electromagnetic environments. To address this challenge, this paper proposes a deep learning-based passive UAV detection and identification system leveraging radio frequency (RF) spectrograms. The system employs a high-resolution RF front-end comprising a multi-beam directional antenna and a wideband spectrum analyzer to scan the target airspace and capture UAV signals with enhanced spatial and spectral granularity. A YOLO-based detection module is then used to extract frequency hopping signal (FHS) regions from the spectrogram, which are subsequently classified by a convolutional neural network (CNN) to identify specific UAV models. Extensive measurements are carried out in both line-of-sight (LoS) and non-line-of-sight (NLoS) urban environments. The proposed system achieves over 96% accuracy in both detection and identification under LoS conditions. In NLoS conditions, it improves the identification accuracy by more than 15% compared with conventional full-spectrum CNN-based methods. These results validate the system’s robustness, real-time responsiveness, and strong practical applicability. Full article

In our previous study, we demonstrated that a standardized ethanol extract of Perilla frutescens var. acuta (PE) alleviates memory deficits in an Alzheimer’s disease mouse model by inhibiting amyloid β (Aβ) aggregation and promoting its disaggregation. However, the extent to which PE exerts additional cognitive benefits independent of Aβ pathology remained unclear. Here, we aimed to evaluate the effects of PE on synaptic plasticity and learning and memory functions. Male ICR mice were used, and cognitive impairment was induced by scopolamine administration. PE was orally administered at doses determined from previous studies, and cognitive performance was assessed using the passive avoidance, Y-maze, and Morris water maze tests. In parallel, hippocampal slices were employed to examine the effects of PE on synaptic plasticity. PE (100 and 300 μg/mL) significantly enhanced long-term potentiation (LTP) in a concentration-dependent manner without altering basal synaptic transmission. This facilitation of LTP was blocked by scopolamine (1 μM), a muscarinic acetylcholine receptor (mAChR) antagonist, and IEM-1460 (50 μM), a calcium-permeable α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (CP-AMPAR) inhibitor, indicating the involvement of mAChR and CP-AMPAR pathways. In vivo, PE (100, 250, and 500 mg/kg) treatment improved memory performance across all behavioral tasks and upregulated hippocampal synaptic proteins including GluN2B, PSD-95, and CaMKII. Collectively, these results demonstrate that PE ameliorates scopolamine (1 mg/kg)-induced cognitive impairment by enhancing synaptic plasticity, likely through modulation of mAChR, CP-AMPAR, and NMDA receptor signaling. These findings highlight the therapeutic potential of PE for memory deficits associated with cholinergic dysfunction. Full article

A critical aspect in the design of power electronics packages is the prediction of their mechanical response under severe thermomechanical loads and the consequent structural damage. For this purpose, finite element (FE) simulations are used to estimate the mechanical performance and reliability under operational conditions, typically alternate high voltages/currents resulting in thermal gradients. When simulations are performed, it is common practice to consider the as-received package to be in a stress-free state. Namely, residual stresses and plastic deformation induced by the manufacturing processes are neglected. In this study, an advanced FE modeling approach is proposed to assess the structural consequences of the encapsulating resin curing, typical in the production of silicon carbide (SiC)-based power electronics modules for electric vehicles. This work offers a general modeling framework that can be further employed to simulate the effects of thermal gradients induced by the production process on the effective shape and residual stresses of the as-received package for other manufacturing stages, such as metal brazing, soldering processes joining copper and SiC, and, to lower extents, the application of polyimide on top of passivation layers. The obtained results have been indirectly validated with experimental data from literature. Full article

A contactless passive magnetoelastic sensing setup, recently proposed for detecting pest/substance accumulation in confined spaces (labs, museum reserves), is optimized for enhanced low-frequency performance. The setup uses a short flexible polymer slab, clamped at one end. There, a short Metglas^® 2826MB magnetoelastic ribbon is fixed upon the slab’s surface. The opposite end receives excitation by a remotely controlled module of ultra-low amplitude vibration. When vibrating (with the slab), the ribbon generates magnetic flux, which depends on (and reflects) the slab’s dynamics. This changes when loads accumulate on its surface. The flux induces voltage in a contactless manner in a low-cost pick-up coil suspended above the ribbon. Voltage monitoring allows for evaluation of the vibrating slab’s real-time dynamics and, consequently, the detection of load-induced changes. This work innovates by introducing a low-cost passive circuit for real-time voltage processing, thus achieving an accurate representation of the low-frequency dynamics of the magnetic flux. Furthermore, it introduces an algorithm, which statistically detects load-induced changes using the voltage’s low-frequency power characteristics. Both additions enable load detection at relatively low frequencies, thus addressing a principal issue of passive contactless sensing setups. Extensive testing at different occasions demonstrates promising load detection performance under various conditions, especially given its cost-efficient hardware and operation. Full article

Accurate assessment of sleep architecture is critical for diagnosing and managing sleep disorders, which significantly impact global health and well-being. While polysomnography (PSG) remains the clinical gold standard, its inherent intrusiveness, high cost, and logistical complexity limit its utility for routine or home-based monitoring. Recent advances highlight that subtle variations in respiratory dynamics, such as respiratory rate and cycle regularity, exhibit meaningful correlations with distinct sleep stages and could serve as valuable non-invasive biomarkers. In this work, we propose a framework for estimating sleep stage distribution—specifically Wake, Light (N1+N2), Deep (N3), and REM—based on respiratory audio captured over a single sleep episode. The framework comprises three principal components: (1) a segmentation module that identifies distinct respiratory cycles in respiratory sounds using a fine-tuned Transformer-based architecture; (2) a feature extraction module that derives a suite of statistical, spectral, and distributional descriptors from these segmented respiratory patterns; and (3) stage-specific regression models that predict the proportion of time spent in each sleep stage. Experiments on the public PSG-Audio dataset (287 subjects; mean 5.3 h per subject), using subject-wise cross-validation, demonstrate the efficacy of the proposed approach. The segmentation model achieved lower RMSE and MAE in predicting respiratory rate and cycle duration, outperforming classical signal-processing baselines. For sleep stage proportion prediction, the proposed method yielded favorable RMSE and MAE across all stages, with the TabPFN model consistently delivering the best results. By quantifying interpretable respiratory features and intentionally avoiding black-box end-to-end modeling, our system may support transparent, contact-free sleep monitoring using passive audio. Full article

The severe ozone depletion over the Southern polar region, known as the “ozone hole,” is a stark example of global ozone depletion caused by human-made chemicals. This has implications for climate change and increased harmful surface solar UV. Several Chemistry–Climate models (CCMs) tend to underestimate total column ozone (TCO) against satellite measurements over the Southern polar region. This underestimation can reach up to 50% in monthly mean zonally averaged biases during cold seasons. The most significant discrepancies were found in the CCM SOlar Climate Ozone Links version 3 (SOCOLv3). We use SOCOLv3 to study the sensitivity of Antarctic TCO to three key factors: (1) stratospheric heterogeneous reaction efficiency, (2) meridional flux intensity into polar regions from sub-grid scale mixing, and (3) photodissociation rate calculation accuracy. We compared the model results with satellite data from Infrared Fourier Spectrometer-2 (IKFS-2), Microwave Limb Sounder (MLS), and Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). The most effective processes for improving polar ozone simulation are photolysis and horizontal mixing. Increasing horizontal mixing improves the simulated TCO seasonal cycle but negatively impacts CH₄ and N₂O distributions. Using the Cloud-J v.8.0 photolysis module has improved photolysis rate calculations and the seasonal ozone cycle representation over the Southern polar region. This paper outlines how different processes impact chemistry–climate model performance in the southern polar stratosphere, with potential implications for future advancements. Full article

At a particular frequency, most materials and objects of interest exhibit a polarization signature, or Mueller matrix, of limited dimensionality, with many matrix elements either negligibly small or redundant due to symmetry. Robust design of a polarization sensor for a particular material or object of interest, or for an application with a limited set of materials or objects, will adapt to the signature subspace, as well as the available modulators, in order to avoid unnecessary measurements and hardware and their associated budgets, errors, and artifacts. At the same time, measured polarization features should be expressed in the Stokes–Mueller basis to allow use of known phenomenology for data interpretation and processing as well as instrument calibration and troubleshooting. This approach to partial Mueller-matrix polarimeter (pMMP) design begins by defining a vector space of reduced Mueller matrices and an instrument vector representing the polarization modulators and other components of the sensor. The reduced-Mueller vector space is proven to be identical to ${\mathbb{R}}^{15}$ and to provide a completely linear description constrained to the Mueller cone. The reduced irradiance, the inner product of the reduced instrument and target vectors, is then applied to construct classifiers and tune modulator parameters, for instance to maximize representation of a specific target in a fixed number of measured channels. This design method eliminates the use of pseudo-inverses and reveals the optimal channel compositions to capture a particular signature feature, or a limited set of features, under given hardware constraints. Examples are given for common optical division-of-amplitude (DoA) 2-channel passive and serial/DoT-DoA 4-channel active polarimeters with rotating crystal modulators for classification of targets with diattenuation and depolarization characteristics. Full article

Bone metastases continue to be a major cause of morbidity and mortality in patients with advanced cancers, driven by the dynamic remodeling of the bone marrow niche. Traditionally viewed as passive space-fillers, bone marrow adipocytes (BMAs) are now recognized as active regulators of tumor growth, therapeutic resistance, and skeletal pathology. BMAs comprise a significant portion of the adult marrow space, particularly in aging and obesity, and facilitate metastatic colonization through various mechanisms. These include metabolic coupling, where adipocyte-derived fatty acids fuel tumor oxidative phosphorylation; the secretion of adipokines such as leptin and IL-6, which promote epithelial-to-mesenchymal transition, invasion, and immune evasion; regulation of osteoclastogenesis via RANKL expression; and the release of extracellular vesicles that reprogram cancer cell metabolism. Clinical and experimental studies show that BMA expansion correlates with increased tumor burden and poorer outcomes in breast, prostate, lung cancers, and multiple myeloma. Additionally, BMAs actively promote therapeutic resistance through metabolic rewiring and drug sequestration. Experimental models, ranging from in vitro co-cultures to in vivo patient-derived xenografts, demonstrate the complex roles of BMAs and also reveal important translational gaps. Despite promising preclinical approaches such as metabolic inhibitors, PPARγ modulation, adipokine blockade, and lifestyle changes, no therapies directly targeting BMAs have yet reached clinical practice. This review compiles current evidence on the biology of BMAs, their tumor-promoting interactions, and potential therapeutic strategies, while also highlighting unresolved questions about BMA heterogeneity, lipid flux, and immunometabolic crosstalk. By revealing how bone marrow adipocytes actively shape the metastatic niche through metabolic, endocrine, and immunological pathways, this review highlights their potential as novel biomarkers and therapeutic targets for improving the management of bone metastases. Full article