Search Results (80)

Precise monitoring of vegetative growth is essential for assessing crop responses to environmental changes. Conventional methods of geometric characterization of plants such as RGB imaging, multispectral sensing, and manual measurements often lack precision or scalability for growth monitoring of rice. LiDAR offers high-resolution, non-destructive 3D canopy characterization, yet applications in rice cultivation across different growth stages remain underexplored, while LiDAR has shown success in other crops such as vineyards. This study addresses that gap by using LiDAR for geometric characterization of rice plants at early, middle, and late growth stages. The objective of this study was to characterize rice plant geometry such as plant height, canopy volume, row distance, and plant spacing using the proximal LiDAR sensing technique at three different growth stages. A commercial LiDAR sensor (model: VPL−16, Velodyne Lidar, San Jose, CA, USA) mounted on a wheeled aluminum frame for data collection, preprocessing, visualization, and geometric feature characterization using a commercial software solution, Python (version 3.11.5), and a custom algorithm. Manual measurements compared with the LiDAR 3D point cloud data measurements, demonstrating high precision in estimating plant geometric characteristics. LiDAR-estimated plant height, canopy volume, row distance, and spacing were 0.5 ± 0.1 m, 0.7 ± 0.05 m³, 0.3 ± 0.00 m, and 0.2 ± 0.001 m at the early stage; 0.93 ± 0.13 m, 1.30 ± 0.12 m³, 0.32 ± 0.01 m, and 0.19 ± 0.01 m at the middle stage; and 0.99 ± 0.06 m, 1.25 ± 0.13 m³, 0.38 ± 0.03 m, and 0.10 ± 0.01 m at the late growth stage. These measurements closely matched manual observations across three stages. RMSE values ranged from 0.01 to 0.06 m and r² values ranged from 0.86 to 0.98 across parameters, confirming the high accuracy and reliability of proximal LiDAR sensing under field conditions. Although precision was achieved across growth stages, complex canopy structures under field conditions posed segmentation challenges. Further advances in point cloud filtering and classification are required to reliably capture such variability. Full article

With the gradual depletion of high-quality iron ore resources, global steel enterprises have shifted their focus to low-grade, high-impurity iron ores. Using low-grade iron ore to produce pellets for blast furnaces is crucial for companies to control production costs and diversify raw material sources. However, producing qualified pellets from limonite and other low-grade iron ores remains highly challenging. This study investigates the mechanism by which basicity affects the consolidation and reduction behavior of high-Al₂O₃ limonite pellets from a thermodynamic perspective. As the binary basicity of the pellets increased from 0.01 under natural conditions to 1.2, the compressive strength of the roasted pellets increased from 1100 N/P to 5200 N/P. The enhancement in basicity led to an increase in the amount of low-melting-point calcium ferrite in the binding phase, which increased the liquid phase in the pellets, thereby strengthening the consolidation. CaO infiltrated into large-sized iron particles and reacted with Al and Si elements, segregating the contiguous large-sized iron particles and encapsulating them with liquid-phase calcium ferrite. Calcium oxide reacts with the Al and Si elements in large hematite particles, segmenting them and forming liquid calcium ferrite that encapsulates the particles. Additionally, this study used thermodynamic analysis to characterize the influence of CaO on aluminum elements in high-aluminum iron ore pellets. Adding CaO boosted the liquid phase’s ability to incorporate aluminum, lessening the inhibition by high-melting-point aluminum elements of hematite recrystallization. During the reduction process, pellets with high basicity exhibited superior reduction performance. Full article

With over 180 million tons produced annually and a global market exceeding 500 billion dollars, beer is one of the most widely consumed beverages in the world, thanks to its broad variety of styles, traditions, ingredients, and brewing techniques. However, behind this widespread popularity lies a potentially impactful production chain, whose environmental impacts remain underexplored, particularly within the craft segment. This research evaluates the sustainability of a hemp-based craft beer produced in the Lazio region (Italy) using an integrated approach that combines life cycle assessment with environmental impact monetization. The results indicate that the main impacts in beer production are related to global warming potential (0.916 kg CO₂ eq/L), terrestrial ecotoxicity (0.404 kg 1.4-DCB eq/L), land use (0.841 m²a crop eq/L), and fossil resource scarcity (0.211 kg oil eq/L), primarily due to malt production and hop transportation. Packaging analysis revealed that including environmental costs, aluminum cans may add an additional environmental cost of €0.80–1.60 per unit, while glass bottles, despite their weight, incur a lower additional cost. For a beer priced at €3.50, this would translate to a real cost of €4.30–5.10, reflecting a 22–45% increase. Improving sustainability in the brewing sector requires strategic actions, such as careful supplier selection and appropriate packaging choices. Overall, sustainability in brewing emerges as a balance between production needs, distribution impacts, and systemic decisions. Full article

This work explores the application of Hidden Markov Models (HMMs) for the classification and reconstruction of corrosion mechanisms in the aerospace-grade aluminum alloy AA2055 from the signals obtained by electrochemical noise (EN) analysis. Using the PELT algorithm to segment the signal based on relevant changepoints, distinct corrosion states within the segments are isolated and identified, including general, localized, and mixed corrosion based on statistical signal features, which are used to create the probabilistic structure of HMMs through the initiation, transition, and emission matrices. This study utilized a dataset composed of five electrolyte groups, each containing ten EN signals with 1024 data points per signal, totaling 51,200 data points. The model demonstrates that even with variability in signal quality, meaningful reconstruction is achievable, especially when datasets include distinct transient behavior. Full article

The polygalacturonase (PG) gene family plays a crucial role in plant cell wall metabolism and participates in various biological processes, such as fruit ripening, pod dehiscence, and pollen tube growth. However, the members of the PG gene family in Vicia sativa remain largely unexplored. We identified and analyzed the PG gene family members in V. sativa to investigate their gene expansion, functional evolution, and potential associations with agronomic traits. A total of 83 V. sativa PG genes (VsPGs) were identified, 51 of which retained all four characteristic PG domains (I–IV). We classified the VsPGs into seven subgroups (A–G) based on the results of phylogenetic analysis, and collinearity analysis suggested that segmental duplication was the primary driver of family expansion. The VsPG promoters were enriched with elements responsive to abscisic acid, low temperatures, and aluminum stress. Transcriptomic and qPCR analyses revealed tissue-specific and stress-responsive expression patterns of the VsPGs. Notably, VsPG48 and VsPG60 were highly expressed in the ventral sutures of pod-dehiscent varieties, whereas VsPG2 and VsPG41, among others, were co-upregulated under cold and aluminum stress. This study provides a foundation for further exploration of the biological functions of VsPGs. Full article

Ultrasonic signal processing methodologies use many signal parameters to be investigated, one of which is time-of-flight (ToF). There are many and various methods used to determine ToF, such as threshold detection, peak-based methods, cross-correlation, zero-crossing tracking algorithms, etc. The application of most of these methods becomes problematic when the background noise becomes high and the signal amplitude, frequency, or propagation velocity changes. In order to partially solve these problems, this paper proposes a new and simple method to determine the time-of-flight and center frequency of signals based on the use of zero-crossing times of filtered signals to calculate these parameters. Taking advantage of the idea that these zero-crossing times are concentrated around the maximum of the signal envelope, they were used as the time-of-flight of the signal. Together with the ToF, the center frequency of the signal was also determined. The proposed method was adapted to the processing of experimental signals obtained during various ultrasound investigations. By processing S₀ mode signals propagating in the sheet molding compound plate, the propagation velocity of this mode was calculated. Its value was compared with the value obtained by the 2D FFT method. The obtained results differed by 0.9%. Using simulated signals propagating in 1 mm-thick aluminum, the phase and group velocity segments of the A₀ mode were calculated. Their values differed by 0.7% from the theoretically calculated values of the dispersion curves by the SAFE method. Full article

This study presents a two-segment continuum robot with piecewise stiffness, designed to enhance the precision, adaptability, and safety of tracheal intubation procedures. The robot employs a continuum manipulator (CM) as its end-effector, featuring a proximal segment (PS) with an aluminum alloy interlocking joint, which provides high axial stiffness for stable insertion, and a distal segment (DS) with a micro-nano resin-based notched structure, offering increased flexibility and compliance to navigate complex anatomical structures such as the epiglottis and vocal cords, thereby reducing airway trauma. To describe the motion behavior of the robot, a piecewise variable curvature kinematic model is developed, capturing the deformation characteristics of each segment under actuation. Furthermore, a piecewise stiffness analysis is conducted to determine the axial and bending stiffness of each segment, ensuring an appropriate balance between stability and flexibility. To enhance control precision, an active tendon-driven decoupling control strategy is introduced, effectively minimizing the interaction forces between flexible segments and improving end-effector maneuverability. The results demonstrate that the proposed design significantly improves the adaptability of the tracheal intubation robot, ensuring controlled insertion while reducing the risk of excessive force on the airway walls. This study provides theoretical and technical insights into the mechanical design and control strategies of continuum robots, contributing to the safety and efficiency of tracheal intubation. Full article

A novel microstructurally controlled graded micro-porous material was developed and experimentally validated for noise reduction through a normal incidence impedance test. Extensive parametric studies were conducted to understand the influence of test specimen size, particle size, porosity, pore size, and its distribution on acoustic absorption and transmission loss. Based on previous research, this study evaluates the application of graded microporous material as an acoustic liner technology for aircraft turbomachine engines. The liner was fabricated in eight 45° segments, assembled in an aluminum test rig, and tested on NASA Glenn Research Center’s Advanced Noise Control Fan (ANCF) low-speed test bed for tonal and broadband noise. The study demonstrates that microstructurally controlled graded microporous material is very effective in dissipating sound energy with reductions in tonal sound pressure level (SPL) of 2 to 13 dB at blade passing frequencies and reductions in broadband SPL of about 2 to 3 dB for the shaft order greater than 40. While the proposed two-layer graded liner model successfully validated the concept, additional design optimization is needed to enhance performance further. This work highlights the potential of graded microporous material as next-generation acoustic liners, offering lightweight, efficient, and scalable aircraft engine noise reduction solutions. Full article

In laser-directed energy deposition (LDED) additive manufacturing, stress-induced deformation and cracking often occur unexpectedly, and, once initiated, they are difficult to remedy. To address this issue, we previously proposed the Dynamic Counter Method (DCM), which monitors internal stress based on deposition layer shrinkage, enabling real-time stress monitoring without damaging the component. To validate this method, we used AlSi10Mg material, which has a low melting point and high reflectivity, and developed a high-precision segmentation network based on DeeplabV3+ to test its ability to measure shrinkage in high-exposure images. Using a real-time reconstruction model, stress calculations were performed with DCM and thermal–mechanical coupling simulations, and the results were validated through XRD residual stress testing to confirm DCM’s accuracy in calculating internal stress in aluminum alloys. The results show that the DeeplabV3+ segmentation network accurately extracted deposition-layer contours and shrinkage information. Furthermore, DCM and thermal–mechanical coupling simulations showed good consistency in residual stress distribution, with all results falling within the experimental error range. In terms of stress evolution trends, DCM was also effective in predicting stress variations. Based on these findings, two loading strategies were proposed, and, for the first time, DCM’s application in online stress monitoring of large LDED components was validated, offering potential solutions for stress monitoring in large-scale assemblies. Full article

This research explores the dynamic characteristics of composite nano-beams with a hybrid cellular structure (HCS) core, composed of two segments with distinct unit cell configurations, and face sheets reinforced with carbon nanotube (CNT) composites. By considering three-layered sandwich beams with aluminum cores of varying unit cell angles, the study explores a broad spectrum of achievable Poisson’s ratios. The top and bottom face sheets incorporate CNTs, distributed either uniformly or in a functionally graded manner. The governing equations are derived using Eringen’s nonlocal elasticity framework and the modified theory of shear deformation, with solutions obtained via the Galerkin method. A detailed parametric analysis is conducted to evaluate the effects of CNT content, arrangement configurations, hybrid core cellular angles, nonlocal parameters, and slenderness ratio (L/h) on the dimensionless natural frequencies of sandwich nanobeams with hybrid cellular cores. A key contribution of this study is the presentation of natural frequencies for nanobeams with hybrid cellular cores and composite face sheets reinforced with functionally graded CNTs, derived from advanced theoretical formulations. These findings offer new insights into design optimization and highlight the potential applications of hybrid cellular sandwich nanobeams in cutting-edge engineering systems. Full article

Peanut faces yield constraints due to aluminum (Al) toxicity in acidic soils. The multidrug and toxic compound extrusion (MATE) family is known for extruding organic compounds and transporting plant hormones and secondary metabolites. However, the MATE transporter family has not yet been reported in peanuts under the Al stress condition. In this genome-wide study, we identified 111 genes encoding MATE proteins from the cultivated peanut genome via structural analysis, designated as AhMATE1–AhMATE111. Encoded proteins ranged from 258 to 582 aa residues. Based on their phylogenetic relationship and gene structure, they were classified into six distinct groups. Genes were distributed unevenly on twenty peanut chromosomes. Chr-05 exhibited the higher density of 12%, while chr-02 and chr-11 have the lowest 1% of these loci. Peanut MATE genes underwent a periodic strong to moderate purifying selection pressure during evolution, exhibiting both tandem and segmental duplication events. Segmental duplication accounted for 82% of the events, whereas tandem duplication represented 18%, with both events predominantly driving their moderate expansion. Further investigation of seven AhMATE genes expression profiles in peanut root tips resulted in distinct transcriptional responses at 4, 8, 12, and 24 h post-Al treatment. Notably, AhMATE genes exhibited greater transcriptional changes in the Al-tolerant cultivar 99-1507 compared to the Al-sensitive cultivar ZH2 (Zhonghua No.2). Our findings provide the first comprehensive genome-wide analysis of the MATE family in cultivated peanuts, highlighting their potential roles in response to Al stress. Full article

In the domain of new energy vehicles, the control of welding deformation in aluminum alloy battery systems poses substantial challenges. The existing methodologies for diminishing welding deformation, such as laser segmented skip welding, alteration of welding path sequences, numerical simulation prediction, and post-weld heat treatment, still possess room for further optimization when applied to intricate welding structures. In this research, a novel adjustable-ring-mode laser in conjunction with the oscillation welding technique was employed to explore the impacts of fiber core diameter, laser light field brightness distribution, and process parameters on weld formation. The regulation of welding deformation was achieved through optimizing the welding process and adjusting the welding path. The results indicate that when the fiber core diameter is 50/150 µm and the light field brightness distribution is H, the weld size exhibits the highest stability. Under the conditions of process parameters p = 5300 W, v = 5.4 m/min, A = 1.6 mm, f = 120 Hz, and θ = 40°, and with the spot position located at the bottom of the side of the upper substrate, the optimal weld formation is obtained. After optimizing the welding path, the maximum Z-direction deformation of the weld is 1.403 mm, representing a reduction of 1.702 mm compared to the previous value. This work is capable of providing novel theoretical guidance and technical insights for the control of welding deformation in thin aluminum alloy plates. Full article

A thermal neutron-absorbing metal matrix composite (MMC) comprised of Al₃Hf particles in an aluminum matrix was developed to filter out thermal neutrons and create a fast flux environment for material testing in a mixed-spectrum nuclear reactor. Intermetallic Al₃Hf particles capture thermal neutrons and are embedded in a highly conductive aluminum matrix that provides conductive cooling of the heat generated due to thermal neutron capture by the hafnium. These Al₃Hf-Al MMCs were fabricated using powder metallurgy via hot pressing. The specimens were neutron-irradiated to between 1.12 and 5.38 dpa and temperatures ranging from 286 °C to 400 °C. The post-irradiation examination included microstructure characterization using transmission electron microscopy (TEM) and energy-dispersive X-ray spectroscopy. This study reports the microstructural observations of four irradiated samples and one unirradiated control sample. All the samples showed the presence of oxide at the particle–matrix interface. The irradiated specimens revealed needle-like structures that extended from the surface of the Al₃Hf particles into the Al matrix. An automated segmentation tool was implemented based on a YOLO11 computer vision-based approach to identify dislocation lines and loops in TEM images of the irradiated Al-Al₃Hf MMCs. This work provides insight into the microstructural stability of Al₃Hf-Al MMCs under irradiation, supporting their consideration as a novel neutron absorber that enables advanced spectral tailoring. Full article

To solve the problem of low segmentation model accuracy due to the complex shape of carbon slag in the aluminum electrolysis fire-eye image and the blurring of the boundary between the slag and the surrounding electrolyte, this paper proposes a segmentation model of the fire-eye image based on an improved U-Net. The model reduces the depth of the traditional U-Net to four layers and uses the multiscale dilated convolution module (MDCM) in the down-sampling stage. Second, the Convolutional Block Attention Module (CBAM) is embedded in the skip connection part of the network to improve the ability of the model to extract contextual features from images of multiple scales, enhance the guidance of high-level features to low-level features, and make the model pay more attention to the critical regions. To alleviate the negative impact of the imbalance of positive and negative examples in the dataset, the weighted binary cross-entropy loss and the Dice loss are used to replace the traditional cross-entropy loss. The experimental results show that the segmentation accuracy of the improved model on the fire-eye dataset reaches 88.03%, which is 5.61 percentage points higher than U-Net. Full article

The initial investigation evaluates the feasibility of ultra high performance concrete (UHPC) as a material for reusable molds in aluminum casting. Two specific UHPC formulations were investigated: one based on ordinary Portland cement (OPC) and another utilizing alkali-activated materials (AAM). The study focused on investigating the surface through roughness measurements and the thermal durability through repeated casting cycles. The thermal stability of the molds was investigated by thermogravimetric analysis, mercury intrusion porosimetry, crack segmentation, optical microscopy, and electron microscopy. Results indicate that molds fabricated from AAM-UHPC exhibit relatively better performance in terms of maintaining structural integrity and surface quality over repeated uses. AAM-UHPC molds were able to withstand up to ten casting cycles with acceptable surface degradation and no significant failure, while OPC-UHPC molds exhibited a faster degradation under similar conditions. Microstructural changes and the interaction of UHPC materials with molten aluminum were investigated, highlighting the low adhesion and defect formation. Additionally, the molds demonstrated sound casting quality, with a grain size comparable to that achieved using traditional steel molds (~ 90 µm), underscoring the potential of UHPC materials for enhancing casting quality and efficiency. The study concludes that UHPC, particularly with alkali-activated formulations, shows promise for low-pressure casting environments. Full article