Search Results (465)

This paper presents the design of a high-isolation directional coupler for X-band applications, utilizing substrate-integrated waveguide (SIW) technology. The coupler features a simple structure, compact size, and ease of integration with other planar circuits. Typically, the S-parameters of a directional coupler are determined by the dimensions of the SIW and the aperture (or hole) of the coupler. In this study, we introduce additional via lines to modify the SIW and the coupler aperture, aiming to achieve high isolation. First, two via lines are embedded in the center, converging into two central vias that form the coupler’s aperture. The power ratio within the coupler is controlled by adjusting the width of the aperture and the overall width of the SIW. Specifically, the width of the SIW at the aperture position is affected by adding vias on the two outer sides of the SIW. By incorporating these vias, we can effectively manage the power distribution across the four ports while ensuring sufficient isolation among them. The proposed design achieves an insertion loss of 3.3 dB, a coupling factor of 6 dB, and an isolation factor of 28.6 dB at 10 GHz. The experimental results demonstrate that the coupler maintains $S_{41}$ less than −20 dB over a 30% fractional bandwidth, ranging from 8.6 GHz to 11.6 GHz. Full article

This study presents a new multiple-input multiple-output (MIMO) antenna array system designed for sub-6 GHz fifth generation (5G) cellular applications. The design features eight compact trapezoid slot elements with L-shaped CPW (Coplanar Waveguide) feedlines, providing broad bandwidth and radiation/polarization diversity. The antenna elements are compact in size and function within the frequency spectrum spanning from 3.2 to 6 GHz. They have been strategically positioned at the peripheral corners of the smartphone mainboard, resulting in a compact overall footprint of 75 mm × 150 mm FR4. Within this design framework, there are four pairs of antennas, each aligned to offer both horizontal and vertical polarization options. In addition, despite the absence of decoupling structures, the adjacent elements in the array exhibit high isolation. The array demonstrates a good bandwidth of 2800 MHz, essential for 5G applications requiring high data rates and reliable connectivity, high radiation efficiency, and dual-polarized/full-coverage radiation. Furthermore, it achieves low ECC (Envelope Correlation Coefficient) and TARC (Total Active Reflection Coefficient) values, measuring better than 0.005 and −20 dB, respectively. With its compact and planar configuration, quite broad bandwidth, acceptable SAR (Specific Absorption Rate) and excellent radiation characteristics, this suggested MIMO antenna array design shows good promise for integration into 5G hand-portable devices. Furthermore, a compact phased-array millimeter-wave (mmWave) antenna with broad bandwidth is introduced as a proof of concept for higher frequency antenna integration. This design underscores the potential to support future 5G and 6G applications, enabling advanced connectivity in smartphones. Full article

Optical fiber-based acoustic detectors for ultrasound imaging in medical field feature plano-concave Fabry–Perot cavities integrated on fiber tips, realized via dip-coating. This technique imposes constraints on sensor geometry, potentially limiting performance. Lab-on-Fiber technology enables complex three-dimensional structures with precise control over geometric parameters, such as the curvature radius. A careful investigation of the optical and mechanical aspects involved in the sensors’ performances is crucial for determining the design rules of such probes. In this study, we numerically analyzed the impact of curvature on the optical and acoustic properties of a plano-concave cavity using the Finite Element Method. Performance metrics, including sensitivity, bandwidth, and directivity, were compared to planar Fabry–Perot configurations. The results suggest that introducing curvature significantly enhances sensitivity by improving light confinement, especially for cavity thicknesses exceeding half the Rayleigh zone (∼45 μm), reaching an enhancement of 2.5 a L = 60 μm compared to planar designs. The curved structure maintains high spectral quality (FOM) despite 2% fabrication perturbations. A mechanical analysis confirms no disadvantages in acoustic response and bandwidth (∼40 MHz). These findings establish curved plano-concave structures as robust and reliable for high-sensitivity polymeric lab-on-fiber ultrasound detectors, offering improved performance and fabrication tolerance for MHz-scale bandwidth applications. Full article

Light field camera depth estimation is a core technology for high-precision three-dimensional reconstruction and realistic scene reproduction. We propose a depth estimation algorithm that fuses blurry features and planar geometric structure priors, aimed at overcoming the limitations of traditional methods in neighborhood selection and mismatching in weak texture regions. First, by constructing a multi-constraint adaptive neighborhood microimage set, the microimages with the lowest blur degree are selected to calculate matching costs, and sparse feature correspondence relationships are used to propagate depth information. Second, planar prior knowledge is introduced to optimize pixel matching costs in weak texture regions, and weights are dynamically adjusted and pixel matching costs are updated during the iterative propagation process within microimages based on matching window completeness. Then, potential mismatched points are eliminated using epipolar geometric relationships. Finally, experiments were conducted using public and real-world datasets for verification and analysis. Compared with famous depth estimation algorithms, such as Zeller and BLADE, the Our method demonstrates superior performance in quantitative depth estimation metrics, scene reconstruction completeness, object edge clarity, and depth scene coverage, providing richer and more accurate depth information. Full article

Welding is an important process in the production of aluminum reservoirs for motor vehicles. The welding quality affects product performance. However, rapid and accurate detection of weld surface defects remains a huge challenge in the field of industrial automation. To address this problem, we proposed a 3D vision-based aluminum reservoir welding surface defect detection method. First of all, a scanning system based on laser line scanning camera was constructed to acquire the point cloud data of weld seams on the aluminum reservoir surface. Next, a planar correction algorithm was used to adjust the slope of the contour line according to the slope of the contour line in order to minimize the effect of systematic disturbances when acquiring weld data. Then, the surface features of the weld, including curvature and normal vector direction, were extracted to extract holes, craters, and undercut defects. For better extraction of the defect, a double-aligned template matching method was used to ensure comprehensive extraction and measurement of defect areas. Finally, the detected defects were categorized according to their morphology. Experimental results show that the proposed method using 3D laser scanning data can detect and classify typical welding defects with an accuracy of more than 97.1%. Furthermore, different types of defects, including holes, undercuts, and craters, can also be accurately detected with precision 98.9%. Full article

Simultaneous localization and mapping (SLAM) is crucial for autonomous driving, drone navigation, and robot localization, relying on efficient point cloud registration and loop closure detection. Traditional Normal Distributions Transform (NDT) odometry frameworks provide robust solutions but struggle with real-time performance due to the high computational complexity of processing large-scale point clouds. This paper introduces an improved NDT-based LiDAR odometry framework to address these challenges. The proposed method enhances computational efficiency and registration accuracy by introducing a unified feature point cloud framework that integrates planar and edge features, enabling more accurate and efficient inter-frame matching. To further improve loop closure detection, a parallel hybrid approach combining Radius Search and Scan Context is developed, which significantly enhances robustness and accuracy. Additionally, feature-based point cloud registration is seamlessly integrated with full cloud mapping in global optimization, ensuring high-precision pose estimation and detailed environmental reconstruction. Experiments on both public datasets and real-world environments validate the effectiveness of the proposed framework. Compared with traditional NDT, our method achieves trajectory estimation accuracy increases of 35.59% and over 35%, respectively, with and without loop detection. The average registration time is reduced by 66.7%, memory usage is decreased by 23.16%, and CPU usage drops by 19.25%. These results surpass those of existing SLAM systems, such as LOAM. The proposed method demonstrates superior robustness, enabling reliable pose estimation and map construction in dynamic, complex settings. Full article

Linear antenna arrays exhibit radiation patterns that are restricted to a half-space and feature axial radiation, which can be a significant drawback for applications that require omnidirectional coverage. To address this limitation, the synthesis method utilizing the Taguchi approach, originally designed for linear arrays, can be effectively extended to two-dimensional or planar antenna arrays. In the context of a linear array, the synthesis process primarily involves determining the feeding law and/or the spatial distribution of the elements along a single axis. Conversely, for a planar array, the synthesis becomes more complex, as it requires the identification of the complex weighting of the feed and/or the spatial distribution of sources across a two-dimensional plane. This adaptation to planar arrays is facilitated by substituting the direction $\theta$ with the pair of directions $(\theta ,\varphi )$, allowing for a more comprehensive coverage of the angular domain. This article focuses on exploring various configurations of planar arrays, aiming to enhance their performance. The primary objective of these configurations is often to minimize the levels of secondary lobes and/or array lobes while enabling a full sweep of the angular space. Secondary lobes can significantly impede system performance, particularly in multibeam applications, where they restrict the minimum distance for frequency channel reuse. This restriction is critical, as it affects the overall efficiency and effectiveness of communication systems that rely on precise beamforming and frequency allocation. By investigating alternative planar array designs and their synthesis methods, this research seeks to provide solutions that improve coverage, reduce interference from secondary lobes, and ultimately enhance the functionality of antennas in diverse applications, including telecommunications, radar systems, and wireless communication. Full article

In recent years, LiDAR Odometry (LO) and LiDAR Inertial Odometry (LIO) algorithms for robot localization have considerably improved, with significant advancements demonstrated in various benchmarks. However, their performance in agricultural environments remains underexplored. This study addresses this gap by evaluating five state-of-the-art LO and LIO algorithms—LeGO-LOAM, DLO, DLIO, FAST-LIO2, and Point-LIO—in a blueberry farm setting. Using an Ouster OS1-32 LiDAR mounted on a four-wheeled mobile robot, the algorithms were evaluated using the translational error metric across four distinct sequences. DLIO showed the highest accuracy across all sequences, with a minimal error of 0.126 m over a 230 m path, while FAST-LIO2 achieved its lowest translational error of 0.606 m on a U-shaped path. LeGO-LOAM, however, struggled due to the environment’s lack of linear and planar features. The results underscore the effectiveness and potential limitations of these algorithms in agricultural environments, offering insights into future improvements and adaptations. Full article

In order to resolve Borodin’s Conjecture, DP-coloring was introduced in 2017 to extend the concept of list coloring. In previous works, it is proved that every planar graph without 7-cycles and butterflies is DP-4-colorable. And any planar graph that does not have 5-cycle adjacent to 6-cycle is DP-4-colorable. The existing research mainly focus on the forbidden adjacent cycles that guarantee the DP-4-colorability for planar graph. In this paper, we demonstrate that any planar graph G that excludes 7-cycles adjacent to k-cycles (for each $k=4,5$), and does not feature a Near-bow-tie as an induced subgraph, is DP-4-colorable. This result extends the findings of the previous works mentioned above. Full article

Spatial genes represent the fundamental interplay among the morphological characteristics of historical districts. Identifying and analyzing these morphological elements can enhance our understanding of urban spatial development, uncover spatial meanings, and provide informed recommendations for future development. This study focuses on the Xuzhou Huilongwo historical district, employing geographic information system, Global Mapper, and other digital technologies to determine the area’s microtopographic features. Qualitative methodologies extract the spatial genes of street segments, entry spaces, and node spaces. By summarizing the microtopography’s influence on street and alley characteristics, valuable spatial samples were selected and visually represented for analysis. This included examining the street segment interface, entry space sequences, and the planar morphology of node spaces. The findings reveal that Huilongwo architecture aligns with topographical features, exhibiting a multi-directional distribution. Height differences help establish street boundaries and enhance pathways’ experiential quality. Additionally, topography significantly influences street spaces, leading to undulating sequences in entry spaces. This study provides insights into the preservation and enhancement of streets and alleys within Xuzhou’s historical district. Full article

To enhance the performance of combustors in micro thermophotovoltaic systems, this study employs numerical simulations to investigate a planar microscale combustor featuring a counter-flow flame configuration. The analysis begins with an evaluation of the effects of (1) equivalence ratio Φ and (2) inlet flow rate V_i on key thermal and combustion parameters, including the average temperature of the combustor main wall (${\overline{T}}_w$), wall temperature non-uniformity (${\overline{R}}_{Tw}$) and radiation efficiency (${\eta }_r$). The findings indicate that increasing Φ causes these parameters to initially increase and subsequently decrease. Similarly, increasing the inlet flow rate leads to a monotonic decline in ${\eta }_r$, while the ${\overline{T}}_w$ and ${\overline{R}}_{Tw}$ exhibit a rise-then-fall trend. A comparative study between the proposed combustor and a conventional planar combustor reveals that, under identical inlet flow rate and equivalence ratio conditions, the use of the counterflow flame configuration can increase the ${\overline{T}}_w$ while reducing the ${\overline{R}}_{Tw}$. The Nusselt number analysis shows that the counter-flow flame configuration micro-combustor achieves a larger area with positive Nusselt numbers and higher average Nusselt numbers, which highlights improved heat transfer from the fluid to the solid. Furthermore, the comparison of blow-off limits shows that the combustor with counter-flow flame configuration exhibits superior flame stability and a broader flammability range. Overall, this study provides a preliminary investigation into the use of counter-flow flame configurations in microscale combustors. Full article

Recent studies have identified microneedle (MN) arrays as promising alternatives for transdermal drug delivery. This study investigated the properties of novel staggered MN arrays design featuring two distinct heights of MNs. The staggered MN arrays were precisely fabricated via PμSL light-cured 3D printing technology. The arrays were systematically evaluated for their morphology, fracture force, skin penetration ability, penetration mechanism, and drug delivery capability. The results demonstrated that the staggered MN arrays punctured the skin incrementally, leveraging the benefits of skin deformation during the puncture process. This approach effectively reduced the puncture force needed, achieving a maximum reduction of approximately 80.27% due to variations in the staggered height. Additionally, the staggered design facilitated skin penetration, as confirmed by the results of the rat skin hematoxylin-eosin (H&E) staining experiments. Compared with 3D-printed planar structures and highly uniform MN arrays, the staggered design exhibited enhanced hydrophilicity, as evidenced by a reduction in the contact angle from approximately 93° to 70°. Simulated drug release images of both coated and hollow staggered MNs illustrated the release and delivery capabilities of these structures across various skin layers, and the staggered design expanded the effective area of the MN arrays within the vertical dimension of the skin layers. This study offers both experimental and theoretical foundations for developing MN arrays with three–dimensional structural distributions, thereby facilitating advancements in MN array technology. Full article

This study investigates novel optical solitons within the intriguing (4+1)-dimensional Korteweg–de Vries–Calogero–Bogoyavlenskii–Schiff (KdV-CBS) equation, which integrates features from both the Korteweg–de Vries and the Calogero–Bogoyavlenskii–Schiff equations. Firstly, all possible symmetry generators are found by applying Lie symmetry analysis. By using these generators, the given model is converted into an ordinary differential equation. An adaptive approach, the generalized exp(-$\mathfrak{S}$($\chi$)) expansion technique has been utilized to uncover closed-form solitary wave solutions. The findings reveal a range of soliton types, including exponential, rational, hyperbolic, and trigonometric functions, represented as bright, singular, rational, periodic, and new solitary waves. These results are illustrated numerically and accompanied by insightful physical interpretations, enriching the comprehension of the complex dynamics modeled by these equations. Our approach’s novelty lies in applying a new methodology to this problem, yielding a variety of novel optical soliton solutions. Additionally, we employ bifurcation and chaos techniques for a qualitative analysis of the model, extracting a planar system from the original equation and mapping all possible phase portraits. A thorough sensitivity analysis of the governing equation is also presented. These results highlight the effectiveness of our methodology in tackling nonlinear problems in both mathematics and engineering, surpassing previous research efforts. Full article

Background: The accurate and early distinction of glioblastomas (GBMs) from single brain metastases (BMs) provides a window of opportunity for reframing treatment strategies enabling optimal and timely therapeutic interventions. We sought to leverage physiologically sensitive parameters derived from diffusion tensor imaging (DTI) and dynamic susceptibility contrast (DSC)–perfusion-weighted imaging (PWI) along with machine learning-based methods to distinguish GBMs from single BMs. Methods: Patients with histopathology-confirmed GBMs (n = 62) and BMs (n = 26) and exhibiting contrast-enhancing regions (CERs) underwent 3T anatomical imaging, DTI and DSC-PWI prior to treatment. Median values of mean diffusivity (MD), fractional anisotropy, linear, planar and spheric anisotropic coefficients, and relative cerebral blood volume (rCBV) and maximum rCBV values were measured from CERs and immediate peritumor regions. Data normalization and scaling were performed. In the next step, most relevant features were extracted (non-interacting features), which were subsequently used to generate a set of new, innovative, high-order features (interacting features) using a feature engineering method. Finally, 10 machine learning classifiers were employed in distinguishing GBMs and BMs. Cross-validation and receiver operating characteristic (ROC) curve analyses were performed to determine the diagnostic performance. Results: A random forest classifier with ANOVA F-value feature selection algorithm using both interacting and non-interacting features provided the best diagnostic performance in distinguishing GBMs from BMs with an area under the ROC curve of 92.67%, a classification accuracy of 87.8%, a sensitivity of 73.64% and a specificity of 97.5%. Conclusions: A machine learning based approach involving the combined use of interacting and non-interacting physiological MRI parameters shows promise to differentiate between GBMs and BMs with high accuracy. Full article

The nucleus-independent chemical shift (NICS) criterion plays a significant role in evaluating (anti-)aromaticity. While being readily accessible even for non-computational chemists, adding ghost atoms for multi-points NICS evaluations poses a significant challenge. In this article, I introduce py.Aroma 4, a freely available and open-source Python package designed specifically for analyzing (anti-)aromaticity. Through its user-friendly graphical interface, py.Aroma simplifies and enhances aromaticity analyses by offering key features such as HOMA/HOMER index computation, Gaussian-type input file generation for diverse NICS calculations and corresponding output processing, NMR spectra plotting, and computational supporting information (SI) generation for scientific manuscripts. Additionally, NICS_⊥ is suggested for evaluating (anti-)aromaticity for non-planar or tilted rings. Pre-compiled executables for macOS and Windows are freely available online. Facilitate accessibility for users lacking programming experience or time constraints. Full article