Search Results (156)

This work presents the development of a functional real-time SLAM system designed to enhance the perception capabilities of an Automated Guided Vehicle (AGV) using only a 2D LiDAR sensor. The proposal aims to address recurring gaps in the literature, such as the need for low-complexity solutions that are independent of auxiliary sensors and capable of operating on embedded platforms with limited computational resources. The system integrates scan alignment techniques based on the Iterative Closest Point (ICP) algorithm. Experimental validation in a controlled environment indicated better performance using Gauss–Newton optimization and the point-to-plane metric, achieving pose estimation accuracy of 99.42%, 99.6%, and 99.99% in the position ($x$, $y$) and orientation ($\theta$) components, respectively. Subsequently, the system was adapted for operation with data from the onboard sensor, integrating a lightweight graphical interface for real-time visualization of scans, estimated pose, and the evolving map. Despite the moderate update rate, the system proved effective for robotic applications, enabling coherent localization and progressive environment mapping. The modular architecture developed allows for future extensions such as trajectory planning and control. The proposed solution provides a robust and adaptable foundation for mobile platforms, with potential applications in industrial automation, academic research, and education in mobile robotics. Full article

Thin plates are commonly used in mechanical structures such as ship hulls, offshore platforms, aircraft, automobiles, and bridges. When subjected to in-plane compressive loads, these structures may experience buckling. In some applications, perforations are introduced, altering membrane stress distribution and buckling behavior. This study investigates the elasto-plastic buckling behavior of perforated plates using the Finite Element Method (FEM), Constructal Design (CD), and Exhaustive Search (ES) techniques. Simply supported thin rectangular plates with central elliptical perforations were analyzed under biaxial elasto-plastic buckling. Three shapes of holes were considered—circular, horizontal elliptical, and vertical elliptical—along with sixteen aspect ratios and two different materials. Results showed that higher yield stress leads to higher ultimate stress for perforated plates. Regardless of material, plates exhibited a similar trend: ultimate stress decreased as the aspect ratio dropped from 1.00 to around 0.40 and then increased from 0.35 to 0.25. A similar pattern was observed in the stress components along both horizontal (x) and vertical (y) directions, once the y-component became considerably higher than the x-component for the same range of 0.40 to 0.25. For longer plates, in general, the vertical elliptical hole brings more benefits in structural terms, due to the facility in the distribution of y-components of stress. Full article

Compliant mechanisms are often utilized in precise positioning systems but have not been thoroughly examined in vibration-aided fine CNC machining. This study aims to develop a new 02-DOF flexure stage for vibration-aided fine CNC milling. A hybrid displacement amplifier, featuring a two-lever mechanism, two Scott–Russell mechanisms, and a parallel leading mechanism, was integrated into a symmetric perpendicular series configuration to create an innovative design. The pseudo-rigid body model (PRBM), Lagrangian approach, finite element analysis (FEA), and Firefly optimization algorithm were employed to develop, verify, and optimize the quality response of the new positioner. The PRBM and Lagrangian methods were used to construct an analytical model, while finite element analysis was used to validate the theoretical solution. The primary natural frequency results from theoretical and FEM methods were 318.16 Hz and 308.79 Hz, respectively. The difference between these techniques was 3.04%, demonstrating a reliable modelling strategy. The Firefly optimization approach applied mathematical equations to enhance the key design factors of the mechanism. The prototype was then built, revealing an error of 7.23% between the experimental and simulated frequencies of 331.116 Hz and 308.79 Hz, respectively. The specimen was subsequently mounted on the fabricated optimization positioner, and vibration-assisted fine CNC milling was performed at 100–1000 Hz. At 400 Hz, the specimen achieved ideal surface roughness with a Ra value of 0.187 µm. The developed design is a potential structure that generates non-resonant frequency power for vibration-aided fine CNC milling. Full article

This study addresses the dynamic response control of deep-water jacket offshore platforms under typhoon and misaligned wave loads by proposing a Tuned Mass Damper (TMD)-based vibration suppression strategy. Typhoon loading is predicted using the Weather Research and Forecasting (WRF) model to simulate maximum wind speed and direction, a customized exponential wind profile fitted to WRF results, and a spectral model calibrated with field-measured data. Correspondingly, typhoon wave loading is calculated using stochastic wave theory with the Joint North Sea Wave Project (JONSWAP) spectrum. A rigorous Finite Element Model (FEM) incorporating soil–structure interaction (SSI) and water-pile interaction is implemented in the Opensees platform. The SSI is modeled using nonlinear Beam on Nonlinear Winkler Foundation (BNWF) elements (PySimple1, TzSimple1, QzSimple1). Numerical simulations demonstrate that the TMD effectively mitigates dynamic platform responses under aligned typhoon and wave conditions. Specifically, the maximum deck acceleration in the X-direction is reduced by 26.19% and 31.58% under these aligned loads, with a 17.7% peak attenuation in base shear. For misaligned conditions, the TMD exhibits pronounced control over displacements in both X- and Y-directions, achieving reductions of up to 29.4%. Sensitivity studies indicated that the TMD’s effectiveness is more significantly impacted by stiffness detuning than mass detuning. It should be emphasized that the effectiveness verification of linear TMD is limited to the load levels within the design limits; for the load conditions that trigger extreme structural nonlinearity, its performance remains to be studied. This research provides theoretical and practical references for multi-directional coupled vibration control of deep-water jacket platforms in extreme marine environments. Full article

This paper presents the design of an airborne DMD-based dual-path multi-target imaging spectrometer that is capable of achieving instantaneous imaging over a two-dimensional large field of view and the simultaneous spectral analysis of thousands of targets. It also offers advantages such as high spatial resolution, high spectral resolution, high timeliness, and low platform requirements. However, its working mechanism inherently causes misalignment errors in the dual-path images that it obtains due to exposure time differences. To address this issue, we propose a dual-path exposure time difference compensation method based on a velocity vector field model, enabling dynamic and precise matching of the dual paths. For target image points that move beyond the field of view, we propose an attitude compensation method based on optimal angular velocity coordination. Monte Carlo simulation results show that the maximum root mean square error of the compensation method across the entire field of view is 0.9792 pixels in the x-direction and 0.7130 pixels in the y-direction. Experimental results demonstrate the effectiveness of the method, which meets the requirements for practical applications and provides a reliable foundation for the real-world implementation of dual-path multi-target imaging spectrometers. Full article

Ammonia (NH₃) is a promising carbon-free marine fuel that is aligned with the International Maritime Organization’s (IMO) decarbonization targets. However, its high toxicity and flammability pose serious explosion hazards, particularly in confined fuel preparation spaces. This study investigates the influence of the ignition source location on the explosion characteristics of ammonia within an ammonia fuel preparation room using computational fluid dynamics (CFD) simulations via the FLACS platform. Nineteen ignition scenarios are established along the X-, Y-, and Z-axes. Key parameters, such as the maximum overpressure, pressure rise rate, reduction rate of flammable gas, ignition detection time, and spatial–temporal distributions of temperature and combustion products, are evaluated. The results show that the ignition location plays a critical role in the explosion dynamics. Ceiling-level ignition (Case 19) produced the highest overpressure (4.27 bar) and fastest pressure rise rate (2.20 bar/s), indicating the most hazardous condition. In contrast, the forward wall ignition (Case 13) resulted in the lowest overpressure (3.24 bar) and limited flame propagation. These findings provide essential insights into the risk assessment and safety design of ammonia-fueled marine systems. Full article

This research presents a novel square-shaped photonic crystal fiber (PCF)-based surface plasmon resonance (SPR) sensor, designed using the external metal deposition (EMD) technique, for highly sensitive refractive index (RI) sensing applications. The proposed sensor operates effectively over an RI range of 1.33 to 1.37 and supports both x- polarized and y-polarized modes. It achieves a wavelength sensitivity of 15,800 nm/RIU and 14,300 nm/RIU, and amplitude sensitivities of 11,584 RIU⁻¹ and 11,007 RIU⁻¹, respectively, for the x-pol. and y-pol. The sensor also reports a resolution in the order of 10⁻⁶ RIU and a strong linearity of R² ≈ 0.97 for both polarization modes, indicating its potential for precision detection in complex sensing environments. Beyond the sensor’s structural and performance innovations, this work also explores the future integration of artificial intelligence (AI) into PCF-SPR sensor design. AI techniques such as machine learning and deep learning offer new pathways for sensor calibration, material optimization, and real-time adaptability, significantly enhancing sensor performance and reliability. The convergence of AI with photonic sensing not only opens doors to smart, self-calibrating platforms but also establishes a foundation for next-generation sensors capable of operating in dynamic and remote applications. Full article

Friction–inertia piezoelectric actuators can perform long-range positioning with nanometer resolution. However, friction and inertia are not easy to control and can influence the actuator’s performance. The present study proposes a friction–inertia-type piezoelectric XY positioning platform with a simple structure, which uses magnets to provide stable normal force and friction. Sliders and rails were used to provide long travel ranges of 80 mm and 70 mm in the X and Y directions, respectively. Compact optical encoders were installed on the platform to enhance the positioning accuracy. With a three-phase positioning strategy involving both stepping and closed-loop methods, the system achieved a positioning accuracy of 3 µm (0.03%) and a repeatability of 325 nm (0.0033%) over a 10 mm long travel range. The positioning resolution was 4.7 nm, which was primarily limited by optical encoder noise under the closed-loop control mode. An astigmatic optical profilometer was used for the wide-range and high-resolution surface imaging of the XY positioning platform. Full article

Background: Previous evidence demonstrated DNA methylation changes in response to stress in plants, showing rapid changes within a limited time frame. Exposure to self-DNA inhibits seedling root elongation, and it was shown that it causes changes in CG DNA methylation in Lactuca sativa. We assessed cytosine methylation changes and associated gene expression patterns in roots of Arabidopsis thaliana Col-0 seedlings exposed to self-DNA for 6 and 24 h. Methods: We used whole genome bisulfite sequencing (WGBS) and RNA-seq analyses to assess genomic cytosine methylation and corresponding gene expression, respectively, on DNA and RNA extracted with commercial kits from roots exposed to self-DNA by an original setup. Fifteen hundred roots replicates, including the control in distilled water, were collected after exposure. Sequencing was performed on a NovaSeq 6000 platform and Ultralow Methyl-Seq System for RNA and DNA WGBS, respectively. Results: Gene expression in roots exposed to self-DNA differed from that of untreated controls, with a total of 305 genes differentially expressed and 87 ontologies enriched in at least one treatment vs. control comparison, and particularly after 24 h of exposure. DNA methylation, particularly in CHG and CHH contexts, was also different, with hyper- and hypomethylation prevailing in treatments vs. controls at 6 h and 24 h, respectively. Differentially expressed genes (DEGs) analysis, Gene Ontology (GO) enrichment analysis, and differentially methylated regions (DMRs) analysis, provided an integrated understanding of the changes associated with self-DNA exposure. Our results suggest differential gene expression associated with DNA methylation in response to self-DNA exposure in A. thaliana roots, enhanced after prolonged exposure. Conclusions: Main functional indications of association between DNA methylation and gene expression involved hypomethylation and downregulation of genes related to nucleotide/nucleoside metabolism (ATP synthase subunit) and cell wall structure (XyG synthase), consistent with previous observations from metabolomics and physiological studies. Further confirmation of these findings will contribute to improving our understanding of the plant molecular response to self-DNA and its implications in stress responses. Full article

In multi-load wireless power transfer (WPT) systems, when multiple loads simultaneously charge using the same transmitter, the unpredictable spatial positions of the loads and the presence of cross-coupling make it challenging to achieve complete system decoupling, thereby limiting the effective power reception area. To address this issue, this paper investigates a one-to-multiple WPT system based on a single-transistor P^#-type LCC-S compensation network. Air-core coils are employed at the receiving end to mitigate cross-coupling, and the effective power reception area is analyzed. First, the operating principle of the system is examined and the parameter configuration conditions for the resonant circuit are derived. Then, MATLAB/Simulink R2022b is used to establish simulation circuit models for both single-transmitter single-receiver and single-transmitter dual-receiver WPT systems. The results indicate that for an effective output power of 5 W, the mutual inductance ranges are (3.5, 6) μH and (3, 6.5) μH, respectively. Next, finite element simulations are conducted to analyze the mutual inductance variations caused by spatial misalignment of the coils. For the single-transmitter single-receiver system, when the transmission distance is 5–12.5 mm, the effective power reception area corresponds to an X- and Y-axis misalignment of ±15 mm, while at a transmission distance of 10 mm, the effective reception area is ±10 mm along both axes. In the single-transmitter dual-receiver system, for a transmission distance of 5–14 mm, the maximum reception area is ±15 mm along the X-axis and ±10 mm along the Y-axis. Finally, an experimental platform is built to verify that multiple loads at different positions can achieve effective power reception for charging. Full article

In this paper, an analysis and monitoring algorithm is proposed for mold health evaluation using vibration data. Two inertial measurement units (IMUs) and an embedded system are first used to acquire vibration data from a powder metallurgy molding machine. These data are collected on an Internet of Things (IoT) platform using the Message Queueing Telemetry Transport (MQTT) protocol. For data analysis, the vibration signal on the Z axis is segmented to label the contact section of the upper and middle molds, and the corresponding vibration data of the stamping friction on the X, Y, and Z axes are extracted. Using only historical vibration data from normal stamping, a Bidirectional Long Short-Term Memory (Bi-LSTM) model with an attention mechanism is trained to predict normal stamping vibrations several minutes in advance. By comparing the predicted stamping vibrations with the observed data at the current time, the mean square errors (MSEs) are calculated to evaluate the health status of the mold. Several ablation experiments were conducted to assess the performance of the trained model. The average MSE values for normal samples and abnormal samples were smaller than 0.5 and larger than 1.0, respectively. The experimental results confirm that the trained prediction model and evaluation indicators can effectively notify operators in advance. An early warning system using vibration data for mold damage was successfully implemented, enhancing predictive maintenance. Full article

Cannabis sativa L. is a globally cultivated plant with significant industrial, nutritional, and medicinal value. Its genome, comprising nine autosomes and sex chromosomes (X and Y), has been extensively studied, particularly in the context of precise breeding for specific enduses. Recent advances have facilitated genome-wide analyses through platforms like the NCBI Comparative Genome Viewer (CGV) and CannabisGDB, among others, enabling comparative studies across multiple Cannabis genotypes. Despite the abundance of genomic data, a particular group of transposable elements, known as miniature inverted-repeat transposable elements (MITEs), remains underexplored in Cannabis. These elements are non-autonomous class II DNA transposons characterized by high copy numbers and insertion preference in non-coding regions, potentially affecting gene expression. In the present study, we report the sequence annotation of MITEs in wild-type and domesticated Cannabis genomes obtained using the MITE Tracker software. We also develop a simple and innovative protocol to identify genome-specific MITE families, offering valuable tools for future research on marker development focused on important genetic variation for breeding in Cannabis sativa. Full article

With the increasing global emphasis on sustainable energy, wave energy has gained recognition as a significant renewable marine resource, drawing substantial research attention. However, the efficient conversion of low-frequency, random, and low-energy wave motion into electrical power remains a considerable challenge. In this study, an advanced hybrid generator design is introduced which enhances wave energy harvesting by optimizing wave–body coupling characteristics and incorporating both a triboelectric nanogenerator (TENG) and an electromagnetic generator (EMG) within the shell. The optimized asymmetric trapezoidal shell (ATS) improves output frequency and energy harvesting efficiency in marine environments. Experimental findings under simulated water wave excitation indicate that the accelerations in the x, y, and z directions for the ATS are 1.9 m·s⁻², 0.5 m·s⁻², and 1.4 m·s⁻², respectively, representing 1.2, 5.5, and 2.3 times those observed in the cubic shell. Under real ocean conditions, a single TENG unit embedded in the ATS achieves a maximum transferred charge of 1.54 μC, a short-circuit current of 103 μA, and an open-circuit voltage of 363 V, surpassing the cubic shell by factors of 1.21, 1.24, and 2.13, respectively. These performance metrics closely align with those obtained under six-degree-of-freedom platform oscillation (0.4 Hz, swing angle range of ±6°), exceeding the results observed in laboratory-simulated waves. Notably, the most probable output frequency of the ATS along the x-axis reaches 0.94 Hz in ocean trials, which is 1.94 times the significant wave frequency of ambient sea waves. The integrated hybrid generator efficiently captures low-quality wave energy to power water quality sensors in marine environments. This study highlights the potential of combining synergistic geometric shell design and generator integration to achieve high-performance wave energy harvesting through improved wave–body coupling. Full article

Shelling Camellia oleifera fruit (COF) is a fundamental step in its oil extraction and further processing. Mechanical shelling mainly relies on cracking through collision. Determining the collision mechanics and structural damage to COF during shelling under specific conditions is crucial for the design of the shelling equipment. In this study, a self-established COF collision mechanical–structural cracking damage test platform was built, with observation in situ using a high-speed macro camera. The main influencing factors on the impact force and structural damage during shelling were analyzed in depth, including the collision material, position, drying temperature, and impact angle. The experimental test results show that the COF collision cracking behavior can be divided into two stages—initial contact to maximum deformation, cracking, and propagation—matching with the mechanical–structural testing. Collision along the y-axis obviously causes more damage than that along the x-axis. Cracking of the COF occurs when the impact speed exceeds 3.27 m/s. The collision materials 304 stainless steel and 7075 aluminum alloy significantly facilitate cracking, while fresh fruit and polyurethane as collision materials cause no obvious damage. The drying temperature reduces the shell-breaking force for COF, with a drying temperature of 110° leading to the best shell-breaking. This research identifies key factors influencing the cracking behavior in COF shelling, such as the material selection, impact speed, and drying temperature. Optimizing these parameters can enhance shelling efficiency, reduce equipment wear, and increase throughput. This tailored approach supports scalable, cost-effective, and high-quality COF oil production with minimized waste and energy use. Full article

This paper addresses the challenge of misalignment in cantilever-based mechanical interlocking structures used for the heterogeneous integration of integrated circuits (ICs). As IC applications expand into flexible and multi-functional platforms, precise alignment becomes critical to maintaining optimal mechanical and electrical performance. We investigate the effects of X and Y misalignment on snap-through forces in cantilever arrays, focusing on their impact on mechanical integrity. The experimental results demonstrate that for X-axis misalignments below 15%, the increase in the required snap-through force is less than 5%. In contrast, Y-axis misalignment shows an even more negligible impact, with less than a 5% reduction in force for up to 20% misalignment. Additionally, through polynomial fits of the model across a range of cantilever angles, this study provides a design template for future exploration of cantilever interactions using nonlinear mechanics while minimizing computational load. These findings offer valuable insights for optimizing misalignment tolerance and improving the design of interlocking structures for IC integration, contributing to the development of robust systems for next-generation IC devices. Full article