Search Results (49,564)

Time-Weighted Dynamic Time Warping (TWDTW), adapted from speech recognition, is used in agricultural remote sensing to model crop growth, particularly under limited ground sample conditions. However, most related studies rely on full-season or empirically selected features, overlooking the systematic optimization of features at each observation time to improve TWDTW’s performance. This often introduces a large amount of redundant information that is irrelevant to crop discrimination and increases computational complexity. Therefore, this study focused on maize as the target crop and systematically conducted mapping experiments using Sentinel-1/2 images to evaluate the potential of integrating TWDTW with optimally selected multi-source time series features. The optimal multi-source time series features for distinguishing maize from non-maize were determined using a two-step Jeffries Matusita (JM) distance-based global search strategy (i.e., twelve spectral bands, Normalized Difference Vegetation Index, Enhanced Vegetation Index, and the two microwave backscatter coefficients collected during the maize jointing to tasseling stages). Then, based on the full-season and optimal multi-source time series features, we compared TWDTW with two widely used temporal machine learning models in agricultural remote sensing community. The results showed that TWDTW outperformed traditional supervised temporal machine learning models. In particular, compared with TWDTW driven by the full-season optimal multi-source features, TWDTW using the optimal multi-source time series features improved user accuracy by 0.43% and 2.30%, and producer accuracy by 7.51% and 2.99% for the years 2020 and 2021, respectively. Additionally, it reduced computational costs to only 25% of those driven by the full-season scheme. Finally, maize maps of Yangling District from 2020 to 2023 were produced by optimal multi-source time series features-based TWDTW. Their overall accuracies remained consistently above 90% across the four years, and the average relative error between the maize area extracted from remote sensing images and that reported in the statistical yearbook was only 6.61%. This study provided guidance for improving the performance of TWDTW in large-scale crop mapping tasks, which is particularly important under conditions of limited sample availability. Full article

Multi-threshold image segmentation plays an irreplaceable role in extracting discriminative structural information from complex images. It is one of the core technologies for achieving accurate target detection and regional analysis, and its segmentation accuracy directly affects the analysis quality and decision reliability in key fields such as medical imaging, remote sensing interpretation, and industrial inspection. However, most existing image segmentation algorithms suffer from slow convergence speeds and low solution accuracy. Therefore, this paper proposes an Adaptive Cooperative Pelican Optimization Algorithm (ACPOA), an improved version of the Pelican Optimization Algorithm (POA), and applies it to global optimization and multilevel threshold image segmentation tasks. ACPOA integrates three innovative strategies: the elite pool mutation strategy guides the population toward high-quality regions by constructing an elite pool composed of the three individuals with the best fitness, effectively preventing the premature loss of population diversity; the adaptive cooperative mechanism enhances search efficiency in high-dimensional spaces by dynamically allocating subgroups and dimensions and performing specialized updates to achieve division of labor and global information sharing; and the hybrid boundary handling technique adopts a probabilistic hybrid approach to deal with boundary violations, balancing exploitation, exploration, and diversity while retaining more useful search information. Comparative experiments with eight advanced algorithms on the CEC2017 and CEC2022 benchmark test suites validate the superior optimization performance of ACPOA. Moreover, when applied to multilevel threshold image segmentation tasks, ACPOA demonstrates better accuracy, stability, and efficiency in solving practical problems, providing an effective solution for complex optimization challenges. Full article

This paper discusses the use of additional ultrasonic fuel treatment technology to reduce sulfur oxide emissions from marine diesel exhaust gases. The research was conducted on a Bulk Carrier vessel with a deadweight of 64,710 tons with the main engine YMD MAN BW 6S50ME-C9.7 and three auxiliary diesel generators CMP-MAN 5L23/30H. The exhaust gases from all engines were treated for sulfur impurities using a scrubber system. It was stated that the combined use of the exhaust gas scrubber system and ultrasonic fuel treatment technology (compared to scrubber-only exhaust gas cleaning) results in a reduction in carbon dioxide CO₂ and sulfur dioxide SO₂ emissions, along with their ratio SO₂/CO₂. The additional ultrasonic fuel treatment technology has had the most significant effect on sulfur-containing components, leading to a substantial decrease in SO₂ emissions from exhaust gases. For various operating conditions of ship diesel engines, a reduction in CO₂ emissions of 2.9–7.5% and a reduction in SO₂ emissions of 9.3–33.1% were established. This achieved a reduction of 6.3 to 23.7% in the SO₂/CO₂ ratio, a critical parameter for evaluating the performance of the scrubber system in exhaust gas cleaning, as mandated by the provisions of Annex VI of MARPOL. The requirements of the international conventions MARPOL and SOLAS were adhered to during the experiments. Full article

Artificial protozoa optimizer (APO), as a newly proposed meta-heuristic algorithm, is inspired by the foraging, dormancy, and reproduction behaviors of protozoa in nature. Compared with traditional optimization algorithms, APO demonstrates strong competitive advantages; nevertheless, it is not without inherent limitations, such as slow convergence and a proclivity towards local optimization. In order to enhance the efficacy of the algorithm, this paper puts forth a multi-strategy fusion artificial protozoa optimizer, referred to as MSAPO. In the initialization stage, MSAPO employs the piecewise chaotic opposition-based learning strategy, which results in a uniform population distribution, circumvents initialization bias, and enhances the global exploration capability of the algorithm. Subsequently, cyclone foraging strategy is implemented during the heterotrophic foraging phase. enabling the algorithm to identify the optimal search direction with greater precision, guided by the globally optimal individuals. This reduces random wandering, significantly accelerating the optimization search and enhancing the ability to jump out of the local optimal solutions. Furthermore, the incorporation of hybrid mutation strategy in the reproduction stage enables the algorithm to adaptively transform the mutation patterns during the iteration process, facilitating a strategic balance between rapid escape from local optima in the initial stages and precise convergence in the subsequent stages. Ultimately, crisscross strategy is incorporated at the conclusion of the algorithm’s iteration. This not only enhances the algorithm’s global search capacity but also augments its capability to circumvent local optima through the integrated application of horizontal and vertical crossover techniques. This paper presents a comparative analysis of MSAPO with other prominent optimization algorithms on the three-dimensional CEC2017 and the highest-dimensional CEC2022 test sets, and the results of numerical experiments show that MSAPO outperforms the compared algorithms, and ranks first in the performance evaluation in a comprehensive way. In addition, in eight real-world engineering design problem experiments, MSAPO almost always achieves the theoretical optimal value, which fully confirms its high efficiency and applicability, thus verifying the great potential of MSAPO in solving complex optimization problems. Full article

Photosynthetic efficiency and dry matter accumulation are essential for achieving high rice yields, yet conventional controlled-release fertilizers often fail to synchronize nitrogen (N) supply with crop demand. In this study, we evaluated a novel double core–shell controlled-release urea (DCSCRU) designed to align with the bimodal N uptake pattern of rice. A two-year field experiment was conducted to compare DCSCRU at three application rates (180, 225, and 270 kg N ha⁻¹) with conventional urea and conventional controlled-release urea (both at 270 kg N ha⁻¹). DCSCRU exhibited a distinct biphasic N release profile, with a rapid initial release peaking at 1.60% d ⁻¹ on day 10 to meet early vegetative demand, followed by a second peak (1.85% d⁻¹ on day 45) supporting reproductive development. Compared with conventional urea, DCSCRU treatments significantly improved photosynthetic efficiency and dry matter accumulation during critical growth stages. The 270 kg N ha⁻¹ DCSCRU treatment achieved a grain yield exceeding 11.50 × 10³ kg ha⁻¹, substantially higher than that of conventional urea. Notably, the 225 kg N ha⁻¹ DCSCRU treatment produced a comparable yield (10.90 × 10³ kg ha⁻¹) to that of the conventional urea treatment (10.83 × 10³ kg ha⁻¹), indicating the potential to reduce N input by 16.7% without compromising yield. The enhanced physiological performance was attributed to improved N availability and optimized canopy function. These findings highlight DCSCRU as a promising strategy for high-yield, resource-efficient, and environmentally sustainable rice production. Full article

This study addresses the problem of pumice deposits in the southern Kyushu region, which can cause landslides during heavy rainfall. To reduce this hazard, it is important to expand pumice applications and promote its use before disaster events occur. Among construction materials, this study explores the possibility of using pumice as a concrete aggregate, considering the global shortage of natural aggregates. Because of the low strength and difficulty of use, pumice must be fired to improve its properties. In our experiment, it was fired at 1000 or 1100 °C, and the performance of the resulting concretes was compared. Concrete incorporating pumice fired at 1100 °C achieved a maximum compressive strength of 54.6 N/mm² with an increase in the amount of cement, whereas concrete with pumice fired at 1000 °C remained within the 20–24 N/mm² range even when the amount of cement was increased. This difference arises because pumice has a lower strength than the cement paste, leading to material failure. Furthermore, freeze–thaw tests showed that concrete made with pumice fired at 1100 °C was resistant to frost damage. These results suggest that pumice fired at 1100 °C has an excellent potential as a sustainable building material. Full article

Chatter vibration in machining operations has been identified as one of the major obstacles to improving surface quality and productivity. Therefore, efficiently and accurately predicting stable cutting regions is becoming increasingly important, especially in high-speed milling processes. In this study, on the basis of a predictor–corrector scheme, the following three error correction methods are developed for milling stability analysis: the Correction Hamming–Milne-based method (CHM), the Correction Adams–Milne-based method (CAM) and the Predictor–Corrector Hamming–Adams–Milne-based method (PCHAM). Firstly, we employ the periodic delay differential equations (DDEs), which are usually adopted to describe mathematical models of milling dynamics, and the time period of the coefficient matrix is divided into two unequal subintervals based on an analysis of the vibration modes. Then, the Hamming method and the fourth-order implicit Adams–Moulton method are separately utilized to predict the state term, and the Milne method is adopted to correct the state term. Based on local truncation error, combining the Hamming and Milne methods creates a CHM that can more precisely approximate the state term. Similarly, combining the fourth-order implicit Adams–Moulton method and the Milne method creates a CAM that can more accurately approximate the state term. More importantly, the CHM and the CAM are employed together to acquire the state transition matrix. Thereafter, the effectiveness and applicability of the three error correction methods are verified by comparing them with three existing methods. The results demonstrate that the three error correction methods achieve higher prediction accuracy without sacrificing computational efficiency. Compared with the 2nd SDM, the calculation times of the CHM, CAM and PCHAM are reduced by around 56%, 56% and 58%, respectively. Finally, verification experiments are carried out using a CNC machine (EMV650) to further validate the reliability of the proposed methods, where ten groups of cutting tests illustrate that the stability lobes predicted by the three error correction methods exhibit better agreement with the experimental results. Full article

In recent years, hybrid models that integrate Convolutional Neural Networks (CNNs) with Vision Transformers (ViTs) have achieved significant improvements in hyperspectral image classification (HSIC). Nevertheless, their complex architectures often lead to computational redundancy and inefficient feature fusion, particularly struggling to balance global modeling and local detail extraction in high-dimensional spectral data. To solve these issues, this paper proposes a Spectral-Cube Gated Harmony Network (SCGHN) that achieves efficient spectral–spatial joint feature modeling through a dynamic gating mechanism and hierarchical feature decoupling strategy. There are three primary innovative contributions of this paper as follows: Firstly, we design a Spectral Cooperative Parallel Convolution (SCPC) module that combines dynamic gating in the spectral dimension and spatial deformable convolution. This module adopts a dual-path parallel architecture that adaptively enhances key bands and captures local textures, thereby significantly improving feature discriminability at mixed ground object boundaries. Secondly, we propose a Dual-Gated Fusion (DGF) module that achieves cross-scale contextual complementarity through group convolution and lightweight attention, thereby enhancing hierarchical semantic representations with significantly lower computational complexity. Finally, by means of the coordinated design of 3D convolution and lightweight classification decision blocks, we construct an end-to-end lightweight framework that effectively alleviates the structural redundancy issues of traditional hybrid models. Extensive experiments on three standard hyperspectral datasets reveal that our SCGHN requires fewer parameters and exhibits lower computational complexity as compared with some existing HSIC methods. Full article

Maintaining optimal pH in hydroponic systems typically requires continuous pH adjustment, increasing both labor and production costs. In regions with alkaline water sources, this challenge is especially critical. Identifying lettuce cultivars tolerant to high pH conditions offers a cost-effective and sustainable alternative to frequent pH buffering. This study evaluated the impact of water pH on growth, water use efficiency (WUE), and nutrient use efficiency (NUE) of lettuce (Lactuca sativa L.) in deep water culture (DWC) hydroponics. A greenhouse experiment was conducted from June to July 2024 using a completely randomized design with four pH treatments: T1 (unbuffered control), T2 (pH 6.3), T3 (pH 7.0), and T4 (pH 8.3). Three lettuce cultivars—Tacitus (L1), Rex (L2), and Rutilai (L3)—were tested, with three replicates per treatment. Results showed that fresh yield was significantly affected by cultivar but not by pH treatment. Rex produced the highest yield, reaching 132 g/plant at pH 7.0, compared to 127 g/plant for Tacitus and 98 g/plant for Rutilai. WUE differed strongly among cultivars, with Rex achieving 68.7 g/L at pH 7.0, which is nearly double that of Rutilai (37.2 g/L). Nitrogen uptake was unaffected by treatment; however, nitrogen NUE differed significantly, with Rutilai recording 12.8 mg N/g fresh weight at pH 8.3, compared to 8.3 mg N/g fresh weight for Rex and 6.7 mg N/g fresh weight for Tacitus. Calcium uptake and NUE were significantly influenced by both pH and cultivar, ranging from 3.2 to 10.7 mg Ca/g fresh weight. These findings suggest that selecting pH-tolerant cultivars plays a more critical role than pH adjustment in determining yield and efficiency in hydroponic lettuce. Choosing pH-tolerant cultivars such as Rex can reduce dependence on chemical buffering, offering a cost-effective strategy for sustainable hydroponic lettuce production in regions with alkaline water sources. Full article

The Geostationary Interferometric Infrared Sounder (GIIRS) on board FengYun-4B (FY-4B), a Chinese second-generation hyperspectral infrared, enables the provision of critical data for forecasting high-impact weather events such as typhoons. To evaluate the reliability of FY-4B/GIIRS data, this study conducted three comparative assimilation trials for both Typhoon Gaemi and Typhoon Doksuri, assimilating observations from the Infrared Atmospheric Sounding Interferometer (IASI), Advanced Microwave Sounding Unit-A (AMSU-A), and FY-4B/GIIRS, respectively. Results demonstrate that the assimilation of GIIRS observations yields more stable forecasts of the wind field at 300 hPa and 500 hPa compared to AMSU-A and IASI, with biases within ±6 m/s relative to NCEP FNL data. However, GIIRS assimilation produces systematic underprediction of vertical velocity, whereas AMSU-A forecasts align more closely with reanalysis. For track forecasts, the GIIRS-assimilated trajectory exhibits closer alignment with observations than AMSU-A and IASI experiments, maintaining biases below 50 km throughout 48 h forecast period of Gaemi. This study provides valuable experience for the application of FY-4B/GIIRS data assimilation. Full article

Background: Heated tobacco products (HTPs) are marketed as reduced-harm alternatives to conventional cigarettes (CCs) and are increasingly used by young adults and occasional smokers. However, their acute nicotine delivery and user experience remain insufficiently studied in occasional smokers without established cigarette or nicotine dependence. Additives such as menthol—known to reduce sensory irritation and facilitate inhalation—may further influence initiation and product appeal, particularly in naïve users. Methods: In a crossover study with three separate study days, n = 15 occasional smokers without established cigarette or nicotine dependence consumed a mentholated HTP (mHTP), a non-mentholated HTP (nmHTP), and a conventional cigarette (CC) under ad libitum conditions during a 30 min observation. We measured plasma nicotine concentrations, smoking topography, cardiovascular parameters, and subjective effects (mCEQ). Results: Nicotine pharmacokinetics (Cmax, AUC) were comparable across products (Cmax 7.8–8.5 ng/mL; AUC 2.3–2.8 ng·min/mL [geometric means]; no significant differences), even though participants had no prior experience with HTPs. Compared to CCs, HTPs were associated with longer puff durations (2.09 s mHTP/2.00 s nmHTP vs. 1.78 s CC), higher puff volumes (mean: 68.06/68.16 vs. 43.76 mL; total: 949.80/897.73 vs. 522.41 mL), and greater flow rates (mean 37.49/38.25 vs. 27.68 mL/s; peak 63.24/63.69 vs. 44.38 mL/s). Subjective effects did not differ significantly between products (mCEQ subscale examples: satisfaction 3.00–3.33/7; reward 2.81–3.31/7; craving reduction 5.07–5.60/7). Cardiovascular parameters such as heart rate or systolic blood pressure showed with no between-product differences (HR p = 0.518; SBP p = 0.109) and no differences in their change over time between products (HR p = 0.807; SBP p = 0.734). No differences were observed between mHTP and nmHTP. Conclusion: HTPs can deliver nicotine and evoke user experiences similar to CCs, even in non-dependent users. The more intensive inhalation behavior observed with HTPs may reflect compensatory use and merits further investigation. Although no menthol-specific effects were observed, methodological constraints may have limited their detectability. Full article

In large-scale, multi-national research projects on agricultural cropping systems such as SoilCare (Horizon 2020), ensuring consistency, comparability, and timely reporting of the (meta)data of the agricultural experiments across diverse partners has been a persistent challenge. To address these concerns, the SoilCare project developed a comprehensive data management system centered around a standardized template for the collection, organization, and sharing of experimental data and metadata from cropping systems. This template, designed to support harmonized sharing, analysis, and documentation through a common structure and terminology, meets the interdisciplinary requirements of modern agricultural research. Experimental data and metadata were structured into five core pools: 1. basic information, 2. field information, 3. experimental setup, 4. agricultural management data and 5. measured data/results. The Excel-based template was carefully structured to support integration into a relational database, enabling robust monitoring, analysis, and traceability of experimental processes and outcomes. The database schema and template, together with the (meta)data collected using this system during the SoilCare projects, were made openly available via Zenodo. The standardized approach ultimately enabled unified analyses and harmonized reporting across all experimental sites, demonstrating the system’s effectiveness in facilitating collaborative agricultural research at scale. Full article

Infrared small target detection (IRSTD) remains a critical yet challenging task due to the inherent low signal-to-noise ratio, weak target features, and complex backgrounds prevalent in infrared images. Existing methods often struggle to effectively capture the subtle edge features of targets and suppress background clutter simultaneously. To address these limitations, this study proposed a novel Multi-directional Learnable Edge-assisted Dense Nested Attention Network (MLEDNet). Firstly, we propose a multi-directional learnable edge extraction module (MLEEM), which is designed to capture rich directional edge information. The extracted multi-directional edge features are hierarchically integrated into the dense nested attention module (DNAM) to significantly enhance the model’s capability in discerning the crucial edge features of infrared small targets. Then, we design a feature fusion module guided by residual channel spatial attention (ResCSAM-FFM). This module leverages spatio-channel contextual cues to intelligently fuse features across different levels output by the DNAM, effectively enhancing target representation while robustly suppressing complex background interferences. By combining the MLEEM and the ResCSAM-FFM within a dense nested attention framework, we present a new model named MLEDNet. Extensive experiments conducted on benchmark datasets NUDT-SIRST and NUAA-SIRST demonstrate that the proposed MLEDNet achieves superior performance compared to state-of-the-art methods. Full article

The influence of polar ice-covered environments on the corrosion-related static electric field (CRSE) of underwater vehicles is critical for understanding and applying the characteristics of underwater electric fields in polar regions. This study utilizes a combined methodology involving COMSOL Multiphysics 6.1 simulations and laboratory-simulated experiments to systematically investigate the distribution characteristics of underwater vehicle electric fields under ice-covered conditions. By comparing the electric field distributions in scenarios with and without ice coverage, this study clarifies the effect of ice presence on the behavior of underwater electric fields. The simulation results demonstrate that the existence of ice layers enhances both the electric potential and field strength, with the degree of influence depending on the ice layer conductivity, thickness, and proximity of the measurement points to the ice layer. The accumulation of error analysis and laboratory experiments corroborates the reliability of the simulation results, demonstrating that ice layers enhance electric field signals by modifying the conductive properties of the surrounding medium, whereas the overall spatial distribution characteristics remain largely consistent. These findings offer a theoretical and technical basis for the optimization of stealth strategies in polar underwater vehicles and contribute to the advancement of electric field detection technologies. Full article

Many trauma-focused psychotherapies for posttraumatic stress disorder (PTSD) focus on the most distressing trauma. However, military personnel are often exposed to multiple traumatic experiences. This study aimed to evaluate and categorize the top three traumatic experiences identified by United States (U.S.) military service members seeking treatment for PTSD and compare frequency of trauma types by demographic/military characteristics. Active duty service members and veterans (N = 110) with PTSD identified and ranked their top three most distressing experiences. Behavioral health professionals classified experiences according to one categorical and four dichotomous classification schemes. The categorical scheme included life threat to self, life threat to others, aftermath of violence, traumatic loss, moral injury by self, and moral injury by others. The Life Threat to Self classification represented the largest portion of categorical experiences (43%). Most experiences were dichotomously classified as military-related (86%), combat-related (70%), non-sexual (91%), and trainability (versus futility; 71%). Women were more likely to report sexual traumatic experiences and less likely to report military- and combat-related experiences. Military occupational specialty, number of deployments, time in military, active duty status, and marital status were also associated with different classification rates. There was noteworthy variability in types of experience across top three traumas, especially among certain subpopulations. Full article