Search Results (56)

Ship detection faces significant challenges such as dense arrangements, varying dimensions, and interference from the sea surface background. Existing ship detection methods often fail to accurately identify ships in these complex marine environments. This paper presents OptiShipNet, an efficient network for detecting ships in complex marine environments using optical remote sensing images. First, to effectively capture ship features from complex environments, we designed a DFC-ConvNeXt module as the network’s backbone, where decoupled fully connected (DFC) attention captures long-distance information in both vertical and horizontal directions, thereby enhancing its expressive capabilities. Moreover, a simple, parameter-free attention module (SimAM) is integrated into the network’s neck to enhance focus on ships within challenging backgrounds. To achieve precise ship localization, we employ WIoU loss, enhancing the ship positioning accuracy in complex environments. Acknowledging the lack of suitable datasets for intricate backgrounds, we construct the HRSC-CB dataset, featuring high-resolution optical remote sensing images. This dataset contains 3786 images, each measuring 1000 × 600 pixels. Experiments demonstrate that the proposed model accurately detects ships under complex scenes, achieving an average precision (AP) of 94.1%, a 3.2% improvement over YOLOv5. Furthermore, the model’s frame per second (FPS) rate reaches 80.35, compared to 67.84 for YOLOv5, thus verifying the approach’s effectiveness. Full article

The deformation and damage to seasonal permafrost roadbeds, as seasons shift, stems from the intricate interplay of temperature, moisture, and stress fields. Fundamentally, the frost heave and thaw-induced settlement of soil represent a multi-physics coupling phenomenon, where various physical processes interact and influence each other. In this investigation, a comprehensive co-coupling numerical simulation of both the temperature and moisture fields was successfully executed, utilizing the secondary development module within the finite element software, COMSOL Multiphysics 6.0. This simulation inverted the classical freezing–thawing experiment involving a soil column under constant temperature conditions, yielding simulation results that were in excellent agreement with the experimental outcomes, with an error of no more than 10%. Accordingly, the temperature, ice content, and liquid water content distributions within the seasonal permafrost region were derived. These parameters were then incorporated into the stress field analysis to explore the intricate coupling between the moisture and temperature fields with the displacement field. Subsequently, the frost heave and thaw settlement deformations of the roadbed were calculated, accounting for seasonal variations, thereby gaining insights into their dynamic behavior. The research results show that during the process of freezing and thawing, water migrates from the frozen zone towards the unfrozen zone, with the maximum migration amount reaching 20% of the water content, culminating in its accumulation at the interface separating the two. Following multiple freeze–thaw cycles, this study reveals that the maximum extent of freezing within the roadbed reaches 2.5 m, while the road shoulder experiences a maximum freezing depth of 2 m. A continuous trend of heightened frost heave and thaw settlement deformation of the roadbed is observed in response to temperature fluctuations, leading to the uneven deformation of the road surface. Specifically, the maximum frost heave measured was 51 mm, while the maximum thaw settlement amounted to 13 mm. Full article

The H8 and S1 reservoirs in the lower Shihezi Formation and Shanxi Formation of the central block in the Sulige Gas Field are typical fluvial tight sandstone reservoirs. Due to frequent river channel migrations during deposition, the reservoirs exhibit complex spatial structures with developed intra-sand mudstone interlayers. As the field has entered the middle and late stages of development, the distribution of remaining gas is intricately controlled by these interlayers, necessitating research on their distribution to understand the remaining gas patterns and types for effective extraction enhancement. However, the thinness of interlayers presents a challenge for precise prediction. Addressing this, this study delineates different interlayer types and their origins, applies reservoir architecture theory, and utilizes bounding surfaces characterization, planar and sectional distribution studies, unit scale analysis, horizontal well data, and quantitative characterization methods to investigate the internal reservoir architecture bounding surfaces. The study finely portrays the interlayer distribution, analyzes the control of reservoir architecture bounding surfaces on remaining gas, and establishes a multi-tiered reservoir architecture model in the study area. Numerical simulation of the gas reservoir clarifies the types of remaining gas enrichment. This study also identifies and quantitatively characterizes the 5–3 level architecture bounding surfaces within the sandbody, categorizing the remaining gas into bounding surfaces-controlled, well-network uncontrolled, and single-layer unperforated types, proposing targeted enhancement measures for each type. Based on the findings, four vertical wells and three horizontal wells were deployed, improving the well network density to three wells per square kilometer. The first completed horizontal well encountered an effective drilling rate of 61.7%, marking significant implications for the exploitation and recovery enhancement of similar tight sandstone gas reservoirs. Full article

This study investigates the influence of microstructure patterns on the hydrophobic properties of surfaces of 3D-printed objects generated using photopolymer resin. Various arrangements and designs of microstructures on the surface of 3D-printed objects were examined. Leveraging the superior resolution of stereolithography printers (SLA) over fused deposition modeling, intricate microfeature designs were well-implemented. The experiments involved a range of structures on the surface of the 3D-printed objects, including precisely defined arrays of microcylinders, microchannels, and other complex designs generated by parametric equations. The hydrophobicity of the 3D-printed objects was assessed through the water droplet test, revealing a spectrum of results ranging from hydrophobic to weakly hydrophobic, and to hydrophilic surfaces. Light microscopy was employed to characterize the surface morphological properties of the 3D-printed objects, which were then correlated with the measured contact angles. It was discovered that the 3D-printed objects with microstructures formed using parametric functions exhibited patterns with irregularities and fluctuations along all directions or axes, resulting in a higher degree of hydrophobicity compared to structured matrices with pillared arrays. However, some surfaces created with parametric functions resulted in an anisotropic system where the material properties varied along one direction, while the other direction exhibited a flat, planar surface. These anisotropic systems were found to be less hydrophobic according to the water droplet test. Full article

This article introduces an improved deep learning network, GRU-Net, designed to facilitate direct and precise phase unwrapping of wrapped phase measurements in gear tooth surface interferometry. GRU-Net incorporates a Gram matrix within each down-sampling process to compute style loss, thereby capturing essential stripe structure information features. This network exhibits enhanced capability in handling larger and more intricate gear tooth interferograms, particularly in scenarios involving pronounced noise and aliasing, while still yielding favorable outcomes. A comparative evaluation was conducted, contrasting GRU-Net with the Res-UNet network and other conventional methods. The results demonstrate that GRU-Net surpasses the alternative approaches in terms of unwrapping accuracy, noise resilience, and anti-aliasing capabilities, with accuracy improved by at least 24%, exhibiting significantly superior performance. Additionally, in contrast to the Res-UNet network, GRU-Net demonstrates accelerated learning speed and generates more compact models. Full article

Examining the interconnected dynamics of urbanization and climate change is crucial due to their implications for environmental, social, and public health systems. This study provides a comprehensive analysis of these dynamics in the Peshawar Valley, a rapidly urbanizing region in Khyber Pakhtunkhwa, Pakistan, over a 30-year period (1990–2020). A novel methodological framework integrating remote sensing, GIS techniques, and Google Earth Engine (GEE) was developed to analyze land use/land cover (LULC) changes, particularly the expansion of the built-up environment, along with the land surface temperature (LST) and heat index (HI). This framework intricately links these elements, providing a unique perspective on the environmental transformations occurring in the Peshawar Valley. Unlike previous studies that focused on individual aspects, this research offers a holistic understanding of the complex interplay between urbanization, land use changes, temperature dynamics, and heat index variations. Over three decades, urbanization expanded significantly, with built-up areas increasing from 6.35% to 14.13%. The population surged from 5.3 million to 12.6 million, coupled with significant increases in registered vehicles (from 0.171 million to 1.364 million) and operational industries (from 327 to 1155). These transitions influenced air quality and temperature dynamics, as evidenced by a highest mean LST of 30.30 °C and a maximum HI of 55.48 °C, marking a notable increase from 50.54 °C. These changes show strong positive correlations with built-up areas, population size, registered vehicles, and industrial activity. The findings highlight the urgent need for adaptive strategies, public health interventions, and sustainable practices to mitigate the environmental impacts of urbanization and climate change in the Peshawar Valley. Sustainable urban development strategies and climate change mitigation measures are crucial for ensuring a livable and resilient future for the region. This long-term analysis provides a robust foundation for future projections and policy recommendations. Full article

This study investigates the computational fluid dynamics (CFD) modeling of supercritical open channel junction flow using two different turbulence models: k-ω shear stress transport (SST) and k-ω SST scale-adaptive simulation (SAS), in conjunction with Volume of Fluid (VOF) and mixture multiphase models. The efficacy of these models in predicting the intricate free surface fluctuation and free surface elevation in a supercritical junction is evaluated through a comprehensive analysis of time-averaged free surface data obtained from CFD simulations and Light Detection and Ranging (LIDAR) measurements. The dimensionless Reynolds (Re) and Froude (Fr) numbers of the investigated scenario were Fr = 9 and Re = 5.1 × 10⁴ for the main channel, and Fr = 6 and Re = 3.3 × 10⁴ for the side channel. The results of the analysis demonstrated a satisfactory level of agreement with the experimental data. However, certain limitations associated with both CFD and LIDAR were identified. Specifically, the CFD performance was limited by the model’s incapacity to consider small-scale turbulent effects and to model air bubbles smaller than the cell size while the LIDAR measurements were limited by instrument range, inability to provide insight into what is happening below the water surface, and blind spots. Nonetheless, the k-ω SST turbulent model with the VOF multiphase model most closely matched the LIDAR results. Full article

This study addresses the structure–property relationship within the green concept of wood fibres with cellulose nanofibre functionalised composites (nW-PPr) containing recycled plastic polyolefins, in particular, polypropylene (PP-r). It focuses especially on the challenges posed by nanoscience in relation to wood fibres (WF) and explores possible changes in the thermal properties, crystallinity, morphology, and mechanical properties. In a two-step methodology, wood fibres (50% wt%) were first functionalised with nanocellulose (nC; 1–9 wt%) and then, secondly, processed into composites using an extrusion process. The surface modification of nC improves its compatibility with the polymer matrix, resulting in improved adhesion, mechanical properties, and inherent biodegradability. The effects of the functionalised WF on the recycled polymer composites were investigated systematically and included analyses of the structure, crystallisation, morphology, and surface properties, as well as thermal and mechanical properties. Using a comprehensive range of techniques, including X-ray diffraction (XRD), attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), scanning electron microscopy (SEM), zeta potential measurements, and dynamic mechanical analysis (DMA), this study aims to unravel the intricate interplay of factors affecting the performance and properties of the developed nanocellulose-functionalised wood fibre–polymer composites. The interfacial adhesion of the nW-PPr polymer composites, crystallisation process, and surface properties was improved due to the formation of an H-bond between the nW coupling agent and neat PP-r. In addition, the role of nW (1.0 wt%) as a nucleating agent resulted in increased crystallinity, or, on the other hand, promoted the interfacial interaction with the highest amount (3.0% wt%, 9.0% wt%) of nW in the PP-r preferentially between the nW and neat PP-r, and also postponed the crystallisation temperature. The changes in the isoelectric point of the nW-PPr polymer composites compared to the neat PP-r polymer indicate the acid content of the polymer composite and, consequently, the final surface morphology. Finally, the higher storage modulus of the composites compared to neat r-PP shows a dependence on improved crystallinity, morphology, and adhesion. It was clear that the results of this study contribute to a better understanding of sustainable materials and can drive the development of environmentally friendly composites applied in packaging. Full article

The differential effects of cellular and ultrastructural characteristics on the optical properties of adaxial and abaxial leaf surfaces in the genus Tradescantia highlight the intricate relationships between cellular arrangement and pigment distribution in the plant cells. We examined hyperspectral and chlorophyll a fluorescence (ChlF) kinetics using spectroradiometers and optical and electron microscopy techniques. The leaves were analysed for their spectral properties and cellular makeup. The biochemical compounds were measured and correlated with the biophysical and ultrastructural features. The main findings showed that the top and bottom leaf surfaces had different amounts and patterns of pigments, especially anthocyanins, flavonoids, total phenolics, chlorophyll-carotenoids, and cell and organelle structures, as revealed by the hyperspectral vegetation index (HVI). These differences were further elucidated by the correlation coefficients, which influence the optical signatures of the leaves. Additionally, ChlF kinetics varied between leaf surfaces, correlating with VIS-NIR-SWIR bands through distinct cellular structures and pigment concentrations in the hypodermis cells. We confirmed that the unique optical properties of each leaf surface arise not only from pigmentation but also from complex cellular arrangements and structural adaptations. Some of the factors that affect how leaves reflect light are the arrangement of chloroplasts, thylakoid membranes, vacuoles, and the relative size of the cells themselves. These findings improve our knowledge of the biophysical and biochemical reasons for leaf optical diversity, and indicate possible implications for photosynthetic efficiency and stress adaptation under different environmental conditions in the mesophyll cells of Tradescantia plants. Full article

Fluid sloshing within containers subjected to external motion is a crucial yet intricate phenomenon with implications across various industries. This study investigates sloshing in a rectangular liquid tank through a series of experiments examining pitch excitations with diverse excitation frequencies and amplitudes across different liquid carrying rates. By analyzing pressure data and imagery of the free liquid surface, statistical trends in peak pressure at measurement points within the tank are identified, revealing the nonlinear behavior of the fluid. Spectral analysis generates power spectrum curves that delineate frequency components and energy distribution within the sloshing dynamics. Key findings include the identification of resonance-induced violent sloshing at a 20% liquid-carrying rate and a resonant frequency shift at a 70% liquid-carrying rate due to nonlinearity, displaying a “soft spring” characteristic in the frequency response. The free liquid surface exhibits four distinct waveforms depending on frequency. Notably, at a 70% liquid-carrying rate and resonant frequency excitation, three-dimensional vortex waves emerge, highlighting a complex three-dimensional effect within the tank. The power spectrum shows that the dominant response frequency aligns with the excitation frequency and its multiples. This investigation enhances our understanding of the intricate nature of sloshing in various liquid-carrying conditions, offering insights valuable for diverse industrial applications. Full article

Porous carbon fibers play a pivotal role in electrochemistry due to their unique structural and textural properties, offering a promising avenue for diverse applications ranging from energy storage to electrocatalysis. In this study, we investigate the intricate relationship between the electrochemical responses of porous carbon fibers synthesized using the Design of Experiments protocol and their textural properties, aiming to elucidate key insights for material design and optimization. Through comprehensive correlation analyses, we uncover notable associations between oxygen reduction reaction mass activities and capacitances measured at different polarization rates, highlighting the significance of pore accessibility in dictating electrochemical performance. While direct correlations with specific surface area and total pore volume for mass activities were not observed, our findings reveal significant trends regarding capacitance retention. Specifically, materials with an elevated specific surface area and total pore volume demonstrate enhanced capacitance retention, particularly under varying charging and discharging rates. These results underscore the importance of optimizing specific surface area and pore volume to maximize capacitive performance across diverse operating conditions. Our study provides valuable guidance for developing porous carbon fibers tailored for superior electrochemical performance in various applications. Full article

In this study, an inverse conjugate heat transfer problem is examined to estimate temporally and spatially the dependent unknown surface heat flux using thermography techniques with a thermal camera in a three-dimensional domain. Thermography techniques encompass a broad set of methods and procedures used for capturing and analyzing thermal data, while thermal cameras are specific tools used within those techniques to capture thermal images. In the present study, the interface conditions of the plate and air domains are obtained using perfect thermal contact conditions, and therefore we define the problem studied as an inverse conjugate heat transfer problem. Achieving the simultaneous solution of the continuity, Navier–Stokes, and energy equations within the air domain, alongside the heat conduction equation in the plate domain, presents a more intricate challenge compared to conventional inverse heat conduction problems. The validity of our inverse solutions was verified through numerical simulations, considering various inlet air velocities and plate thicknesses. Notably, it was found that due to the singularity of the gradient of the cost function at the final time point, the estimated results near the final time must be discarded, and exact measurements consistently produce accurate boundary heat fluxes under thin-plate conditions, with air velocity exhibiting no significant impact on the estimates. Additionally, an analysis of measurement errors and their influence on the inverse solutions was conducted. The numerical results conclusively demonstrated that the maximum error when estimating heat flux consistently remained below 3% and higher measurement noise resulted in the accuracy of the heat flux estimation decreasing. This underscores the inherent challenges associated with inverse problems and highlights the importance of obtaining accurate measurement data in the problem domain. Full article

This study delves into the analysis of a vineyard in Carinthia, Austria, focusing on the automated derivation of ecosystem structures of individual vine parameters, including vine heights, leaf area index (LAI), leaf surface area (LSA), and the geographic positioning of single plants. For the derivation of these parameters, intricate segmentation processes and nuanced UAS-based data acquisition techniques are necessary. The detection of single vines was based on 3D point cloud data, generated at a phenological stage in which the plants were in the absence of foliage. The mean distance from derived vine locations to reference measurements taken with a GNSS device was 10.7 cm, with a root mean square error (RMSE) of 1.07. Vine height derivation from a normalized digital surface model (nDSM) using photogrammetric data showcased a strong correlation (R² = 0.83) with real-world measurements. Vines underwent automated classification through an object-based image analysis (OBIA) framework. This process enabled the computation of ecosystem structures at the individual plant level post-segmentation. Consequently, it delivered comprehensive canopy characteristics rapidly, surpassing the speed of manual measurements. With the use of uncrewed aerial systems (UAS) equipped with optical sensors, dense 3D point clouds were computed for the derivation of canopy-related ecosystem structures of vines. While LAI and LSA computations await validation, they underscore the technical feasibility of obtaining precise geometric and morphological datasets from UAS-collected data paired with 3D point cloud analysis and object-based image analysis. Full article

This groundbreaking research delves into the intricate molecular interactions between MXene and trihalomethanes (THs) through a comprehensive theoretical study employing density-functional theory (DFT). Trihalomethanes are common carcinogenic chlorination byproducts found in water sanitation systems. This study focuses on a pristine MXene [M_n+1·X_n] monolayer and its various terminal [T_x] functional groups [M_n+1·X_nT_x], strategically placed on the surface for enhanced performance. Our investigation involves a detailed analysis of the adsorption energies of THs on different MXene types, with the MXene-Cl layer emerging as the most compatible variant. This specific MXene-Cl layer exhibits remarkable properties, including a total dipole moment (TDM) of 12.443 Debye and a bandgap of 0.570 eV, achieved through meticulous geometry optimization and computational techniques. Notably, THs such as trichloromethane (CHCl₃), bromide-chloromethane (CHBrCl₂), and dibromochloromethane (CHBr₂Cl) demonstrate the highest TDM values, indicating substantial changes in electronic and optical parameters, with TDM values of 16.363, 15.998, and 16.017 Debye, respectively. These findings highlight the potential of the MXene-Cl layer as an effective adsorbent and detector for CHF₃, CHClF₂, CHCl₃, CHBrCl₂, and CHBr₂Cl. Additionally, we observe a proportional increase in the TDM and bandgap energy, indicative of conductivity, for various termination atom combinations, such as Mxene-O-OH, Mxene-O-F, Mxene-O-Cl, Mxene-OH-F, Mxene-F-Cl, and Mxene-OH-Cl, with bandgap energies measured at 0.734, 0.940, 1.120, 0.835, and 0.927 eV, respectively. Utilizing DFT, we elucidate the adsorption energies of THs on different MXene surfaces. Our results conclusively demonstrate the significant influence of the termination atom nature and quantity on MXene’s primitive TDM value. This research contributes to our understanding of MXene–THs interactions, offering promising avenues for the development of efficient adsorbents and detectors for THs. Ultimately, these advancements hold the potential to revolutionize water sanitation practices and enhance environmental safety. Full article

The fouling of separation membranes has consistently been a primary factor contributing to the decline in membrane performance. Enhancing the surface hydrophilicity of the membrane proves to be an effective strategy in mitigating membrane fouling in water treatment processes. Zwitterionic polymers (containing an equimolar number of homogeneously distributed anionic and cationic groups on the polymer chains) have been used extensively as one of the best antifouling materials for surface modification. The conventional application of zwitterionic compounds as surface modifiers is intricate and inefficient, adding complexity and length to the membrane preparation process, particularly on an industrial scale. To overcome these limitations, zwitterionic polymer, directly used as a main material, is an effective method. In this work, a novel zwitterionic polymer (TB)—zwitterionic Tröger’s base (ZTB)—was synthesized by quaternizing Tröger’s base (TB) with 1,3-propane sultone. The obtained ZTB is blended with TB to fabricate microfiltration (MF) membranes via the vapor-induced phase separation (VIPS) process, offering a strategic solution for separating emulsified oily wastewater. Atomic force microscopy (AFM), scanning electron microscopy (SEM), water contact angle, and zeta potential measurements were employed to characterize the surface of ZTB/TB blended membranes, assessing surface morphology, charge, and hydrophilic/hydrophobic properties. The impact of varying ZTB levels on membrane surface morphology, hydrophilicity, water flux, and rejection were investigated. The results showed that an increase in ZTB content improved hydrophilicity and surface roughness, consequently enhancing water permeability. Due to the attraction of water vapor, the enrichment of zwitterionic segments was enriched, and a stable hydration layer was formed on the membrane surface. The hydration layer formed by zwitterions endowed the membrane with good antifouling properties. The proposed mechanism elucidates the membrane’s proficiency in demulsification and the reduction in irreversible fouling through the synergistic regulation of surface charge and hydrophilicity, facilitated by electrostatic repulsion and the formation of a hydration layer. The ZTB/TB blended membranes demonstrated superior efficiency in oil–water separation, achieving a maximum flux of 1897.63 LMH bar⁻¹ and an oil rejection rate as high as 99% in the oil–water emulsion separation process. This study reveals the migration behavior of the zwitterionic polymer in the membrane during the VIPS process. It enhances our comprehension of the antifouling mechanism of zwitterionic membranes and provides guidance for designing novel materials for antifouling membranes. Full article