Search Results (118)

We address the task of point cloud denoising by leveraging a diffusion-based generative framework augmented with adversarial training. While recent diffusion models have demonstrated strong capabilities in learning complex data distributions, their effectiveness in recovering fine geometric details remains limited, especially under severe noise conditions. To mitigate this, we propose the Adversarial Diffusion Bridge Model (ADBM), a novel approach for denoising 3D point cloud data by integrating a diffusion bridge model with adversarial learning. ADBM incorporates a lightweight discriminator that guides the denoising process through adversarial supervision, encouraging sharper and more faithful reconstructions. The denoiser is trained using a denoising diffusion objective based on a Schrödinger Bridge, while the discriminator distinguishes between real, clean point clouds and generated outputs, promoting perceptual realism. Experiments are conducted on the PU-Net and PC-Net datasets, with performance evaluation employing the Chamfer distance and Point-to-Mesh metrics. The qualitative and quantitative results both highlight the effectiveness of adversarial supervision in enhancing local detail reconstruction, making our approach a promising direction for robust point cloud restoration. Full article

Direct Air Capture (DAC) is gaining worldwide attention as a negative emissions strategy critical to meeting climate targets. Among emerging DAC materials, pyrolysis chars (PCs) and gasification chars (GCs) derived from biomass present a promising pathway due to their tunable porosity, surface chemistry, and low-cost feedstocks. This review critically examines the current state of research on the physicochemical properties of PCs and GCs relevant to CO₂ adsorption, including surface area, pore structure, surface functionality and aromaticity. Comparative analyses show that chemical activation, especially with KOH, can significantly improve CO₂ adsorption capacity, with some PCs achieving more than 308 mg/g (100 kPa CO₂, 25 °C). Additionally, nitrogen and sulfur doping further improves the affinity for CO₂ through increased surface basicity. GCs, although inherently more porous, often require additional modification to achieve a similar adsorption capacity. Importantly, the long-term stability and regeneration potential of these chars remain underexplored, but are essential for practical DAC applications and economic viability. The paper identifies critical research gaps related to material design and techno-economic feasibility. Future directions emphasize the need for integrated multiscale research that bridges material science, process optimization, and real-world DAC deployment. A synthesis of findings and a research outlook are provided to support the advancement of carbon-negative technologies using thermochemically derived biomass chars. Full article

We investigate pseudo-complex General Relativity (pcGR)—a coordinate-extended formulation of General Relativity (GR)—within the framework of Hořava-Lifshitz gravity, a regularized theory featuring anisotropic scaling. The pcGR framework bridges GR with modified gravitational theories through the introduction of a minimal length scale. Focusing on Schwarzschild black holes, we derive the Wheeler-deWitt equation, obtaining a quantized description of pcGR. Using perturbative methods and semi-classical approximations, we analyze the solutions of the equations and their physical implications. A key finding is the avoidance of the central singularity due to nonlinear interaction terms in the Hořava-Lifshitz action. Notably, extrinsic curvature (kinetic energy) contributions prove essential for singularity resolution, even in standard GR. Furthermore, the theory offers new perspectives on dark energy, proposing an alternative mechanism for its accumulation. Full article

This study aims to develop an integrated wireless monitoring system named MANTiS-32, which leverages an open-source platform to enable autonomous modular operation, high-speed large-volume data transmission via Wi-Fi, and the integration of multiple complex sensors. The MANTiS-32 system is composed of ESP32-based MANTiS-32 hubs connected to eight MPU-6050 sensors each via RS485. Four MANTiS-32 hubs transmit data to a main PC through an access point (AP), making the system suitable for real-time monitoring of modal information necessary for structural performance evaluation. The fundamental performance of the developed MANTiS-32 system was validated to demonstrate its effectiveness. The evaluation included assessments of acceleration and frequency response measurement performance, wireless communication capabilities, and real-time data acquisition between the MANTiS-32 hub and the eight connected MPU-6050 sensors. To assess the feasibility of using MANTiS-32 for performance monitoring, a flexible model cable-stayed bridge, representing a mid- to long-span bridge, was designed. The system’s ability to perform real-time monitoring of the dynamic characteristics of the bridge model was confirmed. A total of 26 MPU-6050 sensors were distributed across four MANTiS-32 hubs, and real-time data acquisition was successfully achieved through an AP (ipTIME A3004T) without any bottleneck or synchronization issues between the hubs. Vibration data collected from the model bridge were analyzed in real time to extract dynamic characteristics, such as natural frequencies, mode shapes, and damping ratios. The extracted dynamic characteristics showed a measurement error of less than approximately 1.6%, validating the high-precision performance of the MANTiS-32 wireless monitoring system for real-time structural performance evaluation. Full article

The pile group-pile cap structure is a key foundation form for deep-water bridges. However, current effective methods for calculating the earthquake-induced hydrodynamic forces on pile caps with arbitrary cross-sections remain insufficient. In this study, the hydrodynamic force is considered as the added mass, and the dynamic equilibrium equations of the isolated pile cap structure (IC model) and the pile group-pile cap structure (PC model) under earthquakes are established, respectively, based on the structural dynamics theory. Correspondingly, the relationships between the hydrodynamic added masses and the fundamental frequencies in the IC model and the PC model are derived, respectively. The fundamental frequencies of the IC model and the PC model are obtained by numerical models built with the ABAQUS (2019) finite element software, and then the added masses on the IC and PC models are calculated accurately. The calculation method proposed in this study avoids the complex fluid–structure interaction problem, which can be applied for the seismic design of deep-water bridge substructures in real practice. Full article

Asynchronous-pouring construction (APC) technology employs a suspended hanging basket directly supported by corrugated steel webs (CSWs) with high shear strength, significantly enhancing construction efficiency. To further elucidate the characteristics of APC and promote its application in prestressed concrete (PC) composite box girder bridges with CSWs, this study analyzes the sustainable development of APC from two aspects, including environmental impact and economic performance. Finite element models of APC and traditional balanced cantilever construction (TBCC) were established for the case bridge with a main span of 105 m. The stress distribution and deflection of the main girder in the cantilever construction state are compared with field measurements, and the variations in stress and deflection in typical sections during construction are analyzed. Additionally, a simplified theoretical method is proposed for calculating stress and deflection in PC composite girder bridges during the cantilever construction stage using APC. Results demonstrate that APC demonstrates significant advantages in reducing economic costs and minimizing long-term environmental impacts. Furthermore, this method ensures acceptable stress and deflection throughout construction. The proposed simplified formula for CSW deflection in the maximum segment agrees well with both measured data and finite element results, providing a valuable reference for deflection calculation in APC applications. Full article

To address the issues of poor thermal performance and high energy consumption in rural dwellings in cold regions of China, this study investigates multi-type energy-efficient retrofitting strategies for rural houses in the Hebei–Tianjin region. By utilizing a two-step cluster analysis method, 458 rural dwellings from 32 villages were classified based on household demographics, architectural features, and energy consumption patterns, identifying three typical categories: pre-1980s adobe dwellings, 1980s–1990s brick–wood structures, and post-1990s brick–concrete houses. Tailored sunspace design strategies were proposed through simulation: low-cost plastic film sunspaces for adobe dwellings (dynamic payback period: 2.8 years; net present value: CNY 2343), 10 mm hollow polycarbonate (PC) panels for brick–wood structures (cost–benefit ratio: 1.72), and high-efficiency broken bridge aluminum Low-e sunspaces for brick–concrete houses (annual natural gas savings: 345.24 m³). Economic analysis confirmed the feasibility of the selected strategies, with positive net present values and cost–benefit ratios exceeding 1. The findings demonstrate that classification-based retrofitting strategies effectively balance energy-saving benefits with economic costs, providing a scientific hierarchical implementation framework for rural residential energy efficiency improvements in cold regions. Full article

The intelligent extraction of highway assets is pivotal for advancing transportation infrastructure and autonomous systems, yet traditional methods relying on manual inspection or 2D imaging struggle with sparse, occluded environments, and class imbalance. This study proposes an enhanced MinkUNet-based framework to address data scarcity, occlusion, and imbalance in highway point cloud segmentation. A large-scale dataset (PEA-PC Dataset) was constructed, covering six key asset categories, addressing the lack of specialized highway datasets. A hybrid conical masking augmentation strategy was designed to simulate natural occlusions and enhance local feature retention, while semi-supervised learning prioritized foreground differentiation. The experimental results showed that the overall mIoU reached 73.8%, with the IoU of bridge railings and emergency obstacles exceeding 95%. The IoU of columnar assets increased from 2.6% to 29.4% through occlusion perception enhancement, demonstrating the effectiveness of this method in improving object recognition accuracy. The framework balances computational efficiency and robustness, offering a scalable solution for sparse highway scenes. However, challenges remain in segmenting vegetation-occluded pole-like assets due to partial data loss. This work highlights the efficacy of tailored augmentation and semi-supervised strategies in refining 3D segmentation, advancing applications in intelligent transportation and digital infrastructure. Full article

Background/Objectives: Early integration of palliative care (PC) improves outcomes for patients with life-limiting diseases (LLDs). This study evaluated the effectiveness of the Palliative Care and Rapid Emergency Screening (P-CaRES) tool—originally developed for emergency settings—in identifying unmet PC needs among patients admitted to internal medicine wards. Methods: In this retrospective study, the P-CaRES tool was applied to medical records of patients with LLDs. Demographic and clinical data were extracted from charts. Logistic regression identified predictors of PC receipt; survival was analyzed using Kaplan–Meier estimates and log-rank tests. Results: Among 2509 patients screened, 631 (23.9%) had at least one LLD. Of these, 451 (71.5%) were identified as having PC needs. However, only 132 (20.9%) received PC services—126 with documented need and 6 without. Advanced cancer (OR = 6.46, p < 0.001), a positive response to the surprise question (OR = 4.88, p = 0.008), and frequent hospitalizations (OR = 2.24, p < 0.001) predicted PC receipt. Median survival declined with increasing disease burden (10 vs. 372 days for patients with ≥3 vs. 1 LLD), unmet PC needs (85 vs. 1383 days), and a “yes” response to the surprise question (79 vs. 1598 days) (all p < 0.001). Conclusions: The P-CaRES tool effectively identified PC needs in patients with LLDs, including those with cancer. Clinical indicators such as frequent hospital admissions, a positive response to the surprise question, and multimorbidity predicted both the need for PC and shorter survival. Nonetheless, substantial gaps existed between identified needs and PC delivery—especially for non-cancer patients. Structured screening and timely referrals may bridge this gap and improve care for seriously ill individuals. Full article

Pancreatic cancer remains one of the most aggressive malignancies globally, with a 5-year survival rate of less than 13%. This poor prognosis stems from late-stage diagnosis and intrinsic resistance to conventional therapies, including chemotherapy and radiotherapy. A hallmark of PC is oncogene-driven metabolic reprogramming—notably mediated by mutations in KRAS and other key pathways—which fuels tumor progression and undermines the efficacy of neoadjuvant treatments. Consequently, there is a pressing demand for non-invasive techniques capable of mapping metabolic alterations at both the tumor microenvironmental and systemic levels. This review will discuss molecular imaging techniques that identify metabolic changes within the tumor microenvironment. By bridging preclinical insights with clinical applications, we highlight how these innovations promise to revolutionize PC diagnosis, treatment stratification, and therapeutic monitoring, ultimately paving the way for precision oncology. Full article

This study developed a vinyl acetate-ethylene rapid repair mortar (VAE-RRM) by using a binary blended cementitious system (ordinary Portland cement and sulfoaluminate cement) and vinyl acetate-ethylene (VAE) redispersible polymer powder. The effects of the polymer-to-cement ratio (P/C: 0~2.0%) on setting time, mechanical properties, interfacial bonding, and microstructure were systematically investigated. The results reveal that VAE delayed cement hydration via physical encapsulation and chemical chelation, extending the initial setting time to 182 min at P/C = 2.0%. At the optimal P/C = 0.9%, a synergistic organic–inorganic network enhanced flexural strength (14.62 MPa at 28 d, 34.0% increase) and interfacial bonding (2.74 MPa after interface treatment), though compressive strength decreased to 65.7 MPa due to hydration inhibition. Excessive VAE (P/C ≥ 1.5%) suppressed AFt/C-S-H growth, increasing harmful pores (>1 μm) and degrading performance. Microstructural analysis via scanning electron microscopy (SEM) and mercury intrusion porosimetry (MIP) demonstrates that VAE films bridged hydration products, filled interfacial transition zones (ITZ), and refined pore structures, reducing the most probable pore size from 62.8 nm (reference) to 23.5 nm. VAE-RRM 3 (P/C = 0.9%) exhibited rapid hardening (initial setting time: 75 min), high substrate recovery (83.3%), and low porosity (<10%), offering an efficient solution for urban infrastructure repair. This work elucidates the dual mechanisms of pore refinement and interface reinforcement driven by VAE, providing theoretical guidance for designing high-performance repair materials. Full article

This paper presents advancements in structural health monitoring (SHM) techniques, with a particular focus on wave-screening methods for assessing prestress loss in a large-scale prestressed concrete (PC) bridge model under outdoor conditions. The wave-screening process utilizes low-frequency wave propagation obtained from seismic interferometry of structural free vibrations and high-frequency wave propagation obtained through ultrasonic transducers embedded in the structure. An adjustable post-tensioning system was employed in a series of experiments to simulate prestress loss. By comparing bridge vibrations under varying post-tensioning forces, the study investigated prestress loss and examined temperature-related effects using the coda wave interferometry (CWI) method. Local structural alterations were analyzed through wave velocity variations, demonstrating sensitivity to bridge temperature changes. The findings indicate that wave-based methods are more effective than traditional modal analysis for damage detection, highlighting the dual impacts of prestress loss and temperature, as well as damage localization. This study underscores the need for long-term measurements to account for temperature fluctuations when analyzing vibration measurements to investigate changes in prestressing force in PC structures. Full article

To investigate the dynamic characteristics of a PC beam–steel box arch composite bridge when the number of loading lanes for autonomous vehicles changes, the vehicle–bridge coupling motion equation was derived and solved iteratively via the Newmark-β method. Joint simulation software based on ANSYS 17.0 and Easy Language was developed to analyze vehicle–bridge coupling and driving comfort. The results showed that the dynamic response is the largest under single-lane conditions, with suspected vehicle–bridge resonance. For multilane conditions, eccentricity is the main factor when the vehicle weight is low, whereas the vehicle weight dominates when it is large. The dynamic response is positively correlated with eccentricity and vehicle weight. With respect to the dynamic amplification factor (DAF), single-lane conditions yield high DAF values for the main beam, main arch, and boom, whereas the main pier has a greater DAF under multilane conditions. Driving comfort is best under single-lane conditions, followed by dual-lane conditions, and worst under three-lane conditions. Speed is the primary influencer of comfort under single-lane conditions, with comfort reduced at higher speeds. Under multilane conditions, both speed and eccentricity affect comfort, with speed being the dominant factor. The calculated impact coefficient significantly exceeds the standard values, suggesting that separate impact coefficients should be set for each load-bearing component. These findings, combined with driving comfort analysis, provide valuable references for the setting of speed limits and the design and maintenance of such bridges under autonomous vehicle loads. Full article

Cooperative Intelligent Transportation Systems (C-ITSs) are emerging as transformative technologies, paving the way for safe and fully automated driving solutions. As the demand for autonomous vehicles accelerates, the development of advanced Radio Access Technologies capable of delivering reliable, low-latency vehicular communications has become paramount. Standardized approaches for Vehicular-to-Everything (V2X) communication often fall short in addressing the dynamic and diverse requirements of multi-service, multi-priority systems. Conventional vehicular networks employ static parameters such as Access Category (AC) in IEEE 802.11p-based ITS-G5 and Resource Reservation Interval (RRI) in C-V2X PC5 for prioritizing different V2X services. This static parameter assignment performs unsatisfactorily in dynamic and diverse requirements. To bridge this gap, we propose intelligent Multi-Attribute Decision-Making algorithms for adaptive AC selection in ITS-G5 and RRI adjustment in C-V2X PC5, tailored to the varying priorities of active V2X services. These adaptations are integrated with a priority-aware rate-control mechanism to enhance congestion management. Through extensive simulations conducted using NS3, our proposed strategies demonstrate superior performance compared to standardized methods, achieving improvements in one-way end-to-end latency, Packet Reception Ratio (PRR) and overall communication reliability. Full article

Prestressed concrete (PC) continuous beam bridges are widely used in transportation infrastructure. However, their construction involves substantial material consumption, raising sustainability concerns amid increasing environmental pressures. This study aims to address the urgent need for resource-efficient bridge design by developing a comprehensive optimization framework that minimizes material usage while ensuring structural safety, durability, and compliance with engineering standards. The proposed methodology integrates a Genetic Algorithm (GA) with a Backpropagation (BP) neural network to optimize both the cross-sectional geometry and the overall alignment of PC continuous beam bridges. The GA is utilized to identify optimal cross-sectional parameters within regulatory constraints, while the BP neural network, trained on extensive design data, refines the bridge bottom height profile to enhance structural performance. The integrated GA-BP framework is validated through a case study of a continuous beam bridge, demonstrating a 94% improvement in design efficiency, a 14% reduction in concrete consumption, and a 34% reduction in prestressed steel usage during the preliminary design stage. These results highlight the framework’s significant potential in advancing sustainable and intelligent bridge design, offering a novel approach to combining artificial intelligence with structural optimization for practical engineering applications. Full article