Search Results (184)

Dynamically modeling the flexible characteristics of large-scale jointed composite spacecraft is challenging. In this study, a dynamic modeling method for rigid–flexible composite spacecraft is proposed based on the absolute nodal coordinate formulation (ANCF). First, the spacecraft in the jointed composite is simplified as a rigid body, and the docking mechanisms between spacecraft are approximated using the fully parameterized beam model. Next, regarding the constraints between the beam and the rigid body, the beam’s absolute nodal coordinates are converted into rigid body coordinates. This allows the dynamic equations to be simplified using independent coordinates, reducing the model dimension. Finally, system damping is increased through the mean stress noise reduction method, which suppresses high-frequency components in the dynamic model and further reduces the rigidity of the dynamic equations for the composite body. This modeling method decreases the complexity of the composite body dynamics and avoids the difficulty of solving algebraic–differential equations exhibited by Lagrange multiplier methods, facilitating numerical simulations. The proposed method is applicable to both tree and mesh topologies. MATLAB simulations demonstrate that the proposed dynamic model alleviates the dimensionality disaster caused by conventional algorithms, significantly reducing computation time. The simulation results are consistent with ADAMS. The proposed model exhibits displacement errors less than 1 mm, highlighting its efficiency and accuracy. Full article

To improve the operational efficiency of the Virtual Power Plant (VPP) and the effectiveness and reliability of scheduling boundary characterization, this paper proposes a time-decoupled distributed optimization algorithm. First, based on the Lyapunov optimization theory, time decoupling is implemented within the VPP, transforming long-term optimization problems into single-period optimization problems, thereby reducing optimization complexity and improving operational efficiency. Second, the Alternating Direction Method of Multipliers (ADMM) framework is used to decompose the optimization problem into multiple subproblems, combined with a hybrid strategy to improve the particle swarm optimization algorithm for solving the problem, thus achieving distributed optimization for the VPP. Finally, to facilitate intra-day interaction between the VPP and the distribution network, the remaining controllable capacity of the VPP’s devices is used as the spinning reserve to address renewable energy fluctuations. A dynamic scheduling boundary model is constructed by introducing wind and solar fluctuation factors. Based on time decoupling and algorithm improvement, the scheduling boundaries are solved and updated on a rolling basis. Simulation results show that, firstly, the time decoupling strategy based on Lyapunov optimization has an error of less than 3%, and the solving time is reduced by 86.11% after decoupling, significantly improving solving efficiency and validating the feasibility and effectiveness of the time decoupling strategy. Secondly, the hybrid strategy-improved particle swarm optimization algorithm achieves improvements in convergence speed and accuracy compared to other algorithms. Finally, the VPP scheduling boundary and scheduling cost characterization times are 115 s and 6.7 s, respectively, effectively meeting the timeliness of VPP and distribution network interaction while ensuring the safety and reliability of the scheduling boundaries. Full article

The digital integrated circuit (IC) design industry is continuously evolving. However, the rapid advancements in technology are accompanied by major reliability concerns. Conventional clock-based synchronous designs become exceedingly susceptible to transient errors, caused by radiation rays, power jitters, electromagnetic interferences (EMIs), and/or other noise sources, primarily due to aggressive device and voltage scaling. quasi-delay-insensitive (QDI) asynchronous (clockless) circuits demonstrate inherent robustness against such transient errors, owing to their unique architecture. However, they are not completely immune. This article presents a hardened QDI Sleep Convention Logic (SCL) asynchronous architecture, which can fully recover from radiation-induced single-event effects such as single-event upset (SEU) and single-event latch-up (SEL). Multiple benchmark circuits are designed based on the proposed architecture. The simulation results indicate that the proposed designs offer substantial energy savings per operation, dissipate substantially less power during idle phases, and have lower area footprints in comparison to designs based on an existing resilient Null Convention Logic (NCL) architecture at the cost of increased latency. In addition, a formal verification framework for the proposed architecture is also presented. The performance and scalability of the proposed verification scheme are demonstrated using several multiplier benchmark circuits of varying width. Full article

The pepper weevil, Anthonomus eugenii Cano, 1894 (Coleoptera: Curculionidae), poses a significant threat to pepper cultivation, causing extensive crop damage and economic losses. While numerous studies have addressed its occurrence, biology, and control methods, less attention has been given to how climate change might alter its distribution. This research utilized the optimized MaxEnt model to project the current and future habitat suitability of the pepper weevil under four distinct climate scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) for the periods spanning the 2030s to 2090s. Optimal model performance was achieved with a regularization multiplier of two and a feature combination of QHP, yielding high predictive accuracy with mean testing AUC values of 0.921. The analysis identified annual mean temperature (Bio1) and precipitation of the coldest quarter (Bio19) as the primary environmental factors influencing the pest’s distribution. Currently, in China, suitable habitats for A. eugenii encompass an area of 273.74 × 10⁴ km² or 28.47% of the nation’s territory, predominantly located in central, eastern, southern, and southwestern regions. Future projections suggest that suitable areas are expected to shrink across various scenarios, barring increases in specific instances like SSP126-2050s, SSP245-2070s, and SSP370-2050s, with shifts towards southwestern regions. This investigation deepens our comprehension of agricultural pest dynamics under climate change and supports the formulation of preemptive management strategies to safeguard agricultural productivity. Full article

Clarifying the migration law of heavy metal pollutants in soil is the key prerequisite for its treatment. Because most heavy metal pollutants possess color-rendering properties, it is theoretically feasible to use synthesized transparent soil to simulate the migration and diffusion of heavy pollutants in soil. In order to assess the feasibility of employing transparent soil for investigating heavy metal migration (singly and multiply) in porous media, the fluctuation rates and concentration distribution of pollutants were measured from both vertical and horizontal perspectives. Simultaneously, the effects of temperature, dry density, and initial concentration on heavy metal migration were investigated simultaneously, while analyzing changes in heavy metal occurrence forms during the migration process. The study shows that transparent soil accurately simulated heavy metal migration with a deviation of less than 10% compared to sandy soil. The migration of Cu(II) in a single heavy metal migration test was greatly affected by three factors. Among them, both Cu(II) and Cr(VI) are similarly affected by the initial concentration, and favorable migration occurs at an initial concentration of 1000 mg/kg. The heat source temperature and initial concentration significantly impact the migration of single Cr(VI) and composite heavy metals. Under the influence of heat source temperature, the increase in heavy metal migration rate is associated with an increase in the proportion of exchangeable (EXC) and carbonate-bound (Carb). Studying the interaction mechanism between these factors is crucial for accurately predicting the transport behavior of heavy metal pollutants in porous media and providing a scientific basis for environmental protection and treatment. Full article

A comparative study on the synergistic effect of the total ionizing dose and neutron single event effect on a SiC MOSFET and Si MOSFET was performed based on the ⁶⁰Co γ source and the high-pressure multiplier 14 MeV neutron source at the China Institute of Atomic Energy. First, a γ-ray total ionizing dose experiment was performed on these two devices, and the differences in the total ionizing dose damage of the SiC and Si MOSFETs were analyzed. Then, neutron single event effect experiments were performed to investigate the effects of different doses on the single event effect for the devices. The results indicate that the unhardened SiC MOSFET has stronger resistance to the total ionizing dose compared with hardened Si MOSFET. During the 14 MeV neutron irradiation experiment, no single event burnout was observed in either device, but single event transients were observed. Even though the hardened Si MOSFETs are capable of suppressing single event transient currents at a higher drain bias, the trapped charge concentration of SiC MOSFETs due to irradiation is smaller than that of Si MOSFETs, which improves their resistance to the total ionizing dose and makes them less affected by the synergistic effect of the total ionizing dose and neutron single event effects. The research results can provide some guidelines for the radiation hardening technology of power devices used in aerospace and nuclear industries. Full article

Sustainability is becoming increasingly important in the world we live in, because of the rapid global population growth and climate change (drought, extreme temperature fluctuations). People in developing countries need more sustainable protein sources instead of the traditional, less sustainable meat, fish, egg, and dairy products. Alternative sources (plant-based, such as grains (wheat, rice sorghum), seeds (chia, hemp), nuts (almond, walnut), pulses (beans, lentil, pea, lupins), and leaves (duckweed), as well as mycoproteins, microalgae, and insects) can compensate for the increased demand for animal protein. In this context, our attention has been specifically focused on duckweed—which is the third most important aquatic plant after the microalgae Chlorella and Spirulina—to explore its potential for use in a variety of areas, particularly in the food industry. Duckweed has special properties: It is one of the fastest-growing plants in the world (in freshwater), multiplying its mass in two days, so it can cover a water surface quickly even in filtered sunlight (doubling its biomass in 96 hours). During this time, it converts a lot of carbon dioxide into oxygen. It is sustainable, environmentally friendly (without any pesticides), and fast growing; can be grown in indoor vertical farms and aquaculture, so it does not require land; is easy to harvest; and has a good specific protein yield. Duckweed belongs to the family Araceae, subfamily Lemnoideae, and has five genera (Lemna, Spirodela, Wolffia, Wolffiella, Landolita) containing a total of approximately 36–38 recognised species. Duckweed is gaining attention in nutrition and food sciences due to its potential as a sustainable source of protein, vitamins, minerals, and other bioactive compounds. However, there are several gaps in research specifically focused on nutrition and the bioaccessibility of its components. While some studies have analysed the variability in the nutritional composition of different duckweed species, there is a need for comprehensive research on the variability in nutrient contents across species, growth conditions, harvesting times, and geographic locations. There has been limited research on the digestibility, bioaccessibility (the proportion of nutrients that are released from the food matrix during digestion), and bioavailability (the proportion that is absorbed and utilised by the body) of nutrients in duckweed. Furthermore, more studies are needed to understand how food processing (milling, fermentation, cooking, etc.), preparation methods, and digestive physiology affect the nutritional value and bioavailability of the essential bioactive components in duckweed and in food matrices supplemented with duckweed. This could help to optimise the use of duckweed in human diets (e.g., hamburgers or pastas supplemented with duckweed) or animal feed. More research is needed on how to effectively incorporate duckweed into diverse cuisines and dietary patterns. Studies focusing on recipe development, consumer acceptance, palatability, and odour are critical. Addressing these gaps could provide valuable insights into the nutritional potential of duckweed and support its promotion as a sustainable food source, thereby contributing to food security and improved nutrition. In summary, this article covers the general knowledge of duckweed, its important nutritional values, factors that may affect their biological value, and risk factors for the human diet, while looking for technological solutions (covering traditional and novel technologies) that can be used to increase the release of the useful, health-promoting components of duckweed and, thus, their bioavailability. This article, identifying gaps in recent research, could serve as a helpful basis for related research in the future. Duckweed species with good properties could be selected by these research studies and then included in the human diet after they have been tested for food safety. Full article

A detailed theoretical design of an electric resonance-based coupler for dynamic wireless power transfer (DWPT) at the mobile robot level is presented. The scattering matrix of the coupler was derived by transforming and multiplying transmission matrices for each circuit network in a practical equivalent circuit that accounted for loss resistance. This theoretical approach was validated through equivalent circuit models, yielding results consistent with 3D full-wave simulations and showing an error rate of less than 1%. Additionally, a null-power point characteristic, where efficiency sharply decreases when the receiver moves outside the transmitter’s range, was observed. The detailed theoretical design of the practical equivalent circuit for electric resonance-based dynamic WPT couplers is expected to contribute to the design of couplers for various specifications in future applications. Full article

Culinary rhubarb is grown for its large, thick leaf petioles. Red-stalked cultivars and selection are more attractive for the fresh market and processing industry. In vitro cultures are important for rapidly multiplying value genotypes and producing plants free of viruses. This study aimed to develop an in vitro propagation method for six rhubarb selections from the Raspberry (R1, R2, R3), Leader (L1, L2), and Karpow Lipskiego (KL) groups. In addition, the planting material of six rhubarb selections was subjected to phytochemical analysis using the HPLC method to assess the content of bioactive compounds. The cultures were initiated from underground buds on the crowns. The initial growth was obtained for 45 to 75% of initial explants because of bacterial contamination and low bud activity of some genotypes. The type and concentration of cytokinin and its interaction with gibberellin acid (GA₃) were shown to have a significant effect on the cyclic multiplication and commercially interesting rate of all rhubarb genotypes. A high in vitro rooting frequency, 93.7 to 95.8% for rhubarb Raspberry, 94.3 to 100% for rhubarb Leader, and 96.7% KP selections were obtained after two-cycle rooting on a medium containing IBA and NAA. The polyphenolic compounds, such as cyanidin-3-O-rutinoside, rhaponticin, resveratrol, caffeic acid, p-coumaric acid, cinnamic acid, syringic acid, and ferulic acid were detected in selected rhubarb genotypes. The highest content of anthocyanins (2.9 mg·1 g⁻¹ DM) and rhaponticin (107.8 µg·1 g⁻¹ DM) was found in Raspberry selections. On the other hand, Leader selections were characterized by the highest content of resveratrol (0.25 µg·1 g⁻¹ DM) and phenolic acids (1.3 µg·1 g⁻¹ DM). The less attractive for functional food production seems to be KL selection. Full article

The main goal of the paper is to characterize families of $[r,s]$-(upper) superporous subsets of $\mathbb{R}$, which generalize well-known notions of superporosity and strong superporosity of subsets of $\mathbb{R}$. Definitions and properties of $[r,s]$-superporosity are symmetric to definitions and properties of superporosity and strong superporosity. The purpose in all cases is to define small subsets of the line using the notion of porosity. Superporous sets preserve positive porosity, and strongly superporous sets preserve strong porosity; i.e., if E is superporous (correspondingly, E is strongly superporous), then for every $x\in E$ and for every F such that porosity of F at x is greater than 0 (correspondingly, is equal to 1), porosity of $E\cup F$ at x is greater than 0 (correspondingly, is equal to 1). Taking arbitrary positive porosity, instead of 0 or 1, we obtain the symmetric definition as follows: $[r,s]$-superporosity for $0<r\le s<1$ transfers s-porosity to r-porosity; i.e., if E is $[r,s]$-superporous, then for every $x\in E$ and for every F such that porosity of F at x is not less than s, porosity of $E\cup F$ at x is not less than r. Even though the definition and properties of $[r,s]$-superporosity, superporosity and strong superporosity are symmetric and all of them consist of very small sets, the families of these sets are essentially different. In the paper, we focus on relationships between $[r,s]$-superporous sets for different indices $[r,s]$. Furthermore, we compare $[r,s]$-superporosity to superporosity and strong superporosity. We apply the notion of $[r,s]$-superporosity to find multipliers and adders of porouscontinuous functions. Full article

This work presents the design of optimal and multiplierless compensators for Chebyshev sharpened comb decimation filters. The narrowband and wideband compensators are proposed. For the narrowband, the compensator with a magnitude response is proposed in a sinusoidal form, while for the wideband, two compensators with magnitude responses of two sinusoidal functions are introduced. The optimum design is performed using particle swarm optimization (PSO), while the multiplierless design is realized by presenting optimum parameters in a signed-power-of-two (SPT) form. Unlike the methods in the literature, this approach presents flexibility in design, allowing for an exchange between the quality of optimization and the complexity. Comparisons with the compensators from the literature demonstrated that the proposed method provides much better compensation while requiring fewer or slightly increased number of adders. Possible practical applications and potential future research work are also included. Full article

Recent studies have shown that by using channel-correlation and cosparsity in a centralized framework, the accuracy of reconstructing multichannel EEG signals can be improved. A single-channel electroencephalogram (EEG) signal is intrinsically non-sparse in both the converted and raw time domains, which presents a number of important issues. However, this is ignored by contemporary compressive sensing (CS) algorithms, resulting in less recovery quality than is ideal. To address these constraints, we provide a novel CS method that takes advantage of Nonlocal Low-Rank and Cosparse priors (NLRC). By utilizing low-rank approximations and block operations, our method aims to improve the CS recovery process and take advantage of channel correlations. The Alternating Direction Method of Multipliers (ADMM) are also used to efficiently solve the resulting non-convex optimization problem. The outcomes of the experiments unequivocally demonstrate that by using NLRC, the quality of signal reconstruction is significantly enhanced. Full article

A multi-level 2D Discrete wavelet transform (DWT) architecture for JPEG2000 is proposed, enhancing speed through parallel processing multiple tile blocks. Based on the lifting scheme, folded architecture and unfolded architecture achieving critical path delay with only one multiplier are designed to increase throughput rate. Connecting the folded and unfolded architecture through a pipeline architecture ensures uniform throughput rates across all DWT levels within a singular clock domain. Computational resource consumption is reduced by adjusting the timing to allow one folded architecture to process three tile blocks of three to five levels of DWT, and a transposing module requiring merely six registers is devised to decrease storage resource consumption. The quantization module, crucial for code-word control in JPEG2000, is integrated into the scaling module with minimal additional resource expenditure. Compared to the existing architecture, the analysis demonstrates that the proposed architecture exhibits enhanced hardware efficiency, with a reduction in transistor-delay-product (TDP) of no less than 14.69%. Synthesis results further reveal an area reduction of at least 26.64%, and a decrease in area-delay-product (ADP) by a minimum of 29.89%. Results from FPGA implementation indicate a significant decrease in resource utilization. Full article

The maritime industry is under increasing pressure to reduce CO₂ emissions, with the International Maritime Organization (IMO) setting a target to reduce greenhouse gas emissions, including emissions from the port sector, by 40% by 2030. However, accurate and reliable methods for estimating CO₂ emissions at container ports, which are significant contributors to maritime emissions, are still lacking. This study aims to address this by evaluating a novel method for estimating CO₂ emissions at container ports. The proposed method utilizes the cargo handling equipment movement theory, quantifying both vertical and horizontal movements based on the amount of container handling equipment at the port. The emissions for each piece of equipment are estimated by multiplying the movement quantity by the respective emission factor. To validate the model, a robustness test compares the estimated CO₂ emissions with actual energy consumption data from the port. A case study was conducted at a container port with an annual capacity of over 500,000 TEUs and a parallel layout type. The estimated CO₂ emissions were approximately 8183 tons per year, with container cranes contributing 56%, rubber-tire gantry cranes contributing 27%, terminal trucks contributing 14%, and reach stackers contributing 3%. The method demonstrated accuracy, with a deviation of less than 1%. This method offers a fast and reliable approach for estimating baseline CO₂ emissions at container ports, providing valuable insights for port authorities and policymakers to develop more effective emission-reduction strategies. Full article

Plant pathogenic Pseudomonas species cause a variety of diseases in plants. Each Pseudomonas species employs different virulence factors and strategies for successful infection. Moreover, even the same bacterial pathogens can differentially utilize virulence factors against various host plants. However, there has been relatively less emphasis on comparing the infection strategies of a single bacterial pathogen on different hosts and different bacterial pathogens on a single host. Here, we investigated plant–pathogen interactions using two Pseudomonas species, Pseudomonas cannabina pv. alisalensis (Pcal) KB211 and Pseudomonas syringae pv. tomato (Pst) DC3000, and their host plants, cabbage and tomato. Our findings reveal distinct behaviors and virulence patterns across different host plants. Pcal multiplies to greater levels in cabbage compared to tomato, suggesting that Pcal is more adaptive in cabbage than tomato. Conversely, Pst showed robust multiplication in tomato even at lesser inoculum levels, indicating its aggressiveness in the apoplastic space. Gene expression analyses indicate that these pathogens utilize distinct virulence-related gene expression profiles depending on the host plant. These insights highlight the importance of revealing the spatiotemporal regulation mechanisms of virulence factors. Full article