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Co-N-CDs-based MXene nanocomposites (MXene@PDA/Co-N-CDs) were constructed by decorating Co-N-CDs on polydopamine-functionalized MXene nanosheets. Both Co-N-CDs and MXene nanosheets have peroxidase-like activity; when the two materials are combined to form MXene@PDA/Co-N-CDs nanocomposites, the peroxide-like activity can be further enhanced. MXene@PDA/Co-N-CDs could oxidize the substrate 3,3′5,5′-tetramethylbenziline (TMB) to form ox-TMB, as confirmed by detecting the absorption of the blue products. A highly selective colorimetric biosensor was developed for the determination of glutathione (GSH) in the concentration range of 0.3 to 20 µM with a lower detection limit (LOD) of 0.12 µM, which realized the accurate detection of GSH in human serum and urine samples. Moreover, in the tumor microenvironment, MXene@PDA/Co-N-CDs could catalyze hydrogen peroxide to produce hydroxyl free radicals and produce a photothermal effect under the exposure of NIR-I irradiation. The catalytic activity of MXene@PDA/Co-N-CD nanocomposites was fully achieved for the death of cancer cells through photothermal/photodynamic synergistic therapy. The MXene@PDA/Co-N-CDs nanozyme offers multiple applications in GSH detection and tumor therapy. [ABSTRACT FROM AUTHOR]

Cuelure, an effective lure specifically targeting Tephritid fruit flies, has been widely adopted and applied in the monitoring and control of these pests, providing significant support for agricultural pest management. However, its uncontrollable release speed and duration usually lead to a lot of waste, diminishing its effectiveness and increasing the cost of pest control. In order to solve these problems, we focused on Zeugodacus cucurbitae Coquillett and developed a temperature-sensitive nano-controlled release agent for cuelure. The release rate of this agent can be adjusted by adjusting the ambient temperature. The results show that the temperature-sensitive cuelure nano-controlled release agent demonstrates remarkable temperature-responsive controlled release characteristics. It still exhibits exceptional stability even after being subjected to high-temperature treatment at 60 °C for a week, and the trapping efficiency of this attractant remains between 73% and 75%. This study not only holds immense practical value in monitoring, warning, and managing of fruit fly pests, but it also lays a novel theoretical foundation for the development of insect attractants. [ABSTRACT FROM AUTHOR]

Simple Summary: Exposure to short-term high temperatures of 45 °C can enhance the development and reproduction of Zeugodacus cucurbitae (Coquillett). In this study, the function of the ZcVg3 gene in reproduction was studied by interfering with its expression via the injection of siRNA. The silencing of the ZcVg3 gene could affect the expression of other related genes. It also resulted in a significant reduction in egg production, spawning days, ovarian development and lifespan. The results suggest that the ZcVg3 gene plays a crucial role in pest reproduction under short-term high temperatures. Zeugodacus cucurbitae (Coquillett) is a significant pest affecting fruit and vegetables in tropical and subtropical regions, and its development and reproduction are enhanced after exposure to short-term high-temperature stress at 45 °C. Vitellogenin (Vg) is an essential precursor of yolk protein formation in eggs and plays a vital role in the ovarian development of insects. Interfering with the Z. cucurbitae vitellogenin receptor (ZcVgR) gene in short-term high-temperature conditions decreases the fecundity of female adults, while the transcription level of the ZcVg3 gene increases. To elucidate the reproductive function of the ZcVg3 gene and the synergistic relationship among the ZcVgs genes under short-term high temperatures, this study injected siRNA to interfere with the ZcVg3 gene after subjecting Z. cucurbitae to a 1 h treatment at 45 °C and 25 °C. The expression of the ZcVg3 gene was suppressed, leading to the upregulation of the ZcVg1 and ZcVg2 genes, and the expression of the ZcVgR gene was initially decreased and then increased. Silencing the ZcVg3 gene after a 1 h treatment at 45 °C resulted in a reduction of approximately 84.7% and 75.9% in the fecundity and spawning days of female adults compared to the control. The development rate of their ovaries and the ovarian diameter significantly decreased, and their lifespan was reduced by 71%. The ZcVg3 gene plays a crucial role in the reproduction of Z. cucurbitae in short-term high-temperature conditions. The results of this study provide potential targets for the development of RNAi-based techniques for the control of Z. cucurbitae. [ABSTRACT FROM AUTHOR]

As the growth of society and the continuous upgrading of people's living standards increase, people's requirements for indoor environment are also increasing. To optimize the ventilation methods inside buildings, a numerical simulation method was used to construct numerical simulations of airflow organization and aerosol diffusion, and based on this model, better ventilation methods were determined. To optimize the determined better ventilation method, a multi-constraint optimization model was constructed using infection probability, thermal comfort, energy utilization coefficient, and velocity non-uniformity coefficient. The ventilation method was optimized through multi-objective constraints. To solve the optimization model, an optimized particle swarm algorithm was studied and designed. The results showed that under the "air rain" flow field, the maximum values of aerosol particles at the human body, bed surface, and outlet were 171, 769, and 19,973, respectively, while the minimum values were 4, 169, and 2197, respectively. The "air rain" flow field is a better ventilation method. The maximum and minimum values of the original non-uniformity coefficient were 0.44 and 0.08, respectively. After optimization by the particle swarm optimization algorithm, the maximum and minimum predicted non-uniformity coefficients were 0.457 and 0.08, respectively. The original value and predicted value are very close. The numerical model and algorithm constructed by the research institute are effective. The algorithm designed by the research institute can provide technical support for multi-objective optimization of indoor ventilation methods. [ABSTRACT FROM AUTHOR]

As the capital of China and a densely populated major city, the characteristics of Beijing's near-surface wind field change significantly with the increase in the density of underlying urban structures. The high randomness of natural wind makes it extremely difficult to develop a universally applicable wind-resistant load design code based on topographic factors and architectural features. This article takes the wind speeds recorded at 15 different height levels within the urban area by the 325 m meteorological tower in Beijing from 1991 to 2020 as the research subject. It quantifies the wind speed trends at different heights and introduces time-varying functions to establish a non-stationary wind speed model based on the optimal model. Additionally, it compares the basic wind speeds and wind pressure height variation coefficients obtained from measurements with the standards. The results show that, during the past 30 years of urbanization, the near-surface wind speed in the Beijing area has shown a decreasing trend. The model incorporating time-varying functions exhibited the best fit and demonstrated good predictive capabilities, with its calculated basic wind speeds being relatively high. The wind pressure height variation coefficient values in Beijing are between Class C and Class D terrains, being closer to Class C at lower altitudes. The conclusion reveals that urbanization has a significant impact on wind speeds, primarily concentrated at lower height levels, and that the basic wind speeds calculated based on standards underestimate the actual conditions when this impact is not considered. Although the average wind speed's wind profile index across the entire time series is mostly greater than the fixed value of 0.3 given by Class D, this represents an overestimated wind profile index for maximum wind speeds. [ABSTRACT FROM AUTHOR]

This study investigated the effects of multidirectional forging (MDF) and aging treatments on the wear properties of ZK61 magnesium alloy. Dry sliding wear tests were performed on homogenized, MDF, and aged samples using a friction wear machine to analyze the surface morphology by scanning electron microscopy (SEM) and white light interferometry, as well as the hardness and tensile mechanical properties. The ZK61 magnesium alloy has higher sliding wear properties after MDF due to higher strength, hardness, and work hardening. Grain refinement affects the wear resistance of the material, but aging increases the hardness and tensile strength and decreases the wear resistance. [ABSTRACT FROM AUTHOR]

In healthcare, wireless body area networks (WBANs) can be used to constantly collect patient body data and assist in real-time medical services for patients from physicians. In such security- and privacy-critical systems, the user authentication mechanism can be fundamentally expected to prevent illegal access and privacy leakage occurrences issued by hacker intrusion. Currently, a significant quantity of new WBAN-oriented authentication protocols have been designed to verify user identity and ensure that body data are accessed only with a session key. However, those newly published protocols still unavoidably affect session key security and user privacy due to the lack of forward secrecy, mutual authentication, user anonymity, etc. To solve this problem, this paper designs a robust user authentication protocol. By checking the integrity of the message sent by the other party, the communication entity verifies the other party's identity validity. Compared with existing protocols, the presented protocol enhances security and privacy while maintaining the efficiency of computation. [ABSTRACT FROM AUTHOR]

Due to the influence of atmospheric turbulence, the detector, and background noise, the subaperture image of an extended scene Shack–Hartmann wavefront sensor will have a low signal-to-noise ratio, which will introduce errors to the offset estimation and reduce the accuracy of the slope measurement. To solve this problem, this paper proposes a cross-correlation subaperture image preprocessing method, which uses the generalized Anscombe transform to convert the Gauss–Poisson noise into Gaussian noise and introduces residual feedback on the basis of BM3D to achieve the efficient denoising of subaperture images. The simulation results show that compared with the three commonly used denoising algorithms, the proposed method improves the relative error of the subaperture offset calculation by 51.96% and the corresponding Zernike coefficient of distorted reconstruction wavefront by 85.56%, which realizes the improvement in the detection accuracy on the basis of effectively retaining image details. [ABSTRACT FROM AUTHOR]

Addressing the issue of the simultaneous reconstruction of intensity and phase information in multiscale digital holography, an improved deep-learning model, Mimo-Net, is proposed. For holograms with uneven distribution of useful information, local feature extraction is performed to generate holograms of different scales, branch input training is used to realize multiscale feature learning, and feature information of different receptive fields is obtained. The up-sampling path outputs multiscale intensity and phase information simultaneously through dual channels. The experimental results show that compared to Y-Net, which is a network capable of reconstructing intensity and phase information simultaneously, Mimo-Net can perform intensity and phase reconstruction simultaneously on three different scales of holograms with only one training, improving reconstruction efficiency. The peak signal-to-noise ratio and structural similarity of the Mimo-Net reconstruction for three different scales of intensity and phase information are higher than those of the Y-Net reconstruction, improving the reconstruction performance. [ABSTRACT FROM AUTHOR]

In adaptive optics systems, the precision wavefront sensor determines the closed-loop correction effect. The accuracy of the wavefront sensor is severely reduced when light energy is weak, while the real-time performance of wavefront sensorless adaptive optics systems based on iterative algorithms is poor. The wavefront correction algorithm based on deep learning can directly obtain the aberration or correction voltage from the input image light intensity data with better real-time performance. Nevertheless, manually designing deep-learning models requires a multitude of repeated experiments to adjust many hyperparameters and increase the accuracy of the system. A wavefront sensorless system based on convolutional neural networks with automatic hyperparameter optimization was proposed to address the aforementioned issues, and networks known for their superior performance, such as ResNet and DenseNet, were constructed as constructed groups. The accuracy of the model was improved by over 26%, and there were fewer parameters in the proposed method, which was more accurate and efficient according to numerical simulations and experimental validation. [ABSTRACT FROM AUTHOR]

Modal-free optimization algorithms do not require specific mathematical models, and they, along with their other benefits, have great application potential in adaptive optics. In this study, two different algorithms, the single-dimensional perturbation descent algorithm (SDPD) and the second-order stochastic parallel gradient descent algorithm (2SPGD), are proposed for wavefront sensorless adaptive optics, and a theoretical analysis of the algorithms' convergence rates is presented. The results demonstrate that the single-dimensional perturbation descent algorithm outperforms the stochastic parallel gradient descent (SPGD) and 2SPGD algorithms in terms of convergence speed. Then, a 32-unit deformable mirror is constructed as the wavefront corrector, and the SPGD, single-dimensional perturbation descent, and 2SPSA algorithms are used in an adaptive optics numerical simulation model of the wavefront controller. Similarly, a 39-unit deformable mirror is constructed as the wavefront controller, and the SPGD and single-dimensional perturbation descent algorithms are used in an adaptive optics experimental verification device of the wavefront controller. The outcomes demonstrate that the convergence speed of the algorithm developed in this paper is more than twice as fast as that of the SPGD and 2SPGD algorithms, and the convergence accuracy of the algorithm is 4% better than that of the SPGD algorithm. [ABSTRACT FROM AUTHOR]

Small size construction and demolition waste (CDW) is rarely reused and consequently causes environmental problems. CDW can increase aeration porosity of soil due to the big surface area and water absorption. In order to investigate the feasibility and function of CDW as a component of container substrate, we mixed four small sizes CDW (<10 mm) of 0–3, 3–6, 6–8, and 0–10 mm with clay soil according to the mass ratios of 20%, 35%, and 50% to plant one-year old Duranta repens cuttings, clay soil (CS) and pure CDW (CW) as the controls. Cluster analysis and principal component analysis (PCA) were performed to screen the most suitable particle size and proportion of CDW for plant growth and physiological function. The substrate containing 50% 3–6 mm CDW (S6) had the higher aeration porosity, lower water loss, better water retention and permeability, and therefore higher PCA score. The total branch length of plants in the S6 was increased by 18% and 71%, leaf area by 116% and 444%, and net photosynthetic rate by 10% and 59% compared to CS and CW, respectively. The suitable CDW has potential to improve substrate properties and can effectively improve plant growth. Meanwhile, the reuse of CDW can partially alleviate the problem of construction waste disposal and environmental pollution, and provide reference for the research on the combination of CDW and landscaping. [ABSTRACT FROM AUTHOR]

The harm of agricultural pests presents a remarkable effect on the quality and safety of edible farm products and the monitoring and identification of agricultural pests based on the Internet of Things (IoT) produce a large amount of data to be transmitted. To achieve efficient and real-time transmission of the sensors' data for pest monitoring, this paper selects 235 geographic coordinates of agricultural pest monitoring points and uses genetic algorithm (GA), particle swarm optimization (PSO), and simulated annealing (SA) to optimize the data transmission paths of sensors. The three intelligent algorithms are simulated by MATLAB software. The results show that the optimized path based on PSO can make the shortest time used for transmitting data, and its corresponding minimum time is 4.868012 s. This study can provide a reference for improving the transmission efficiency of agricultural pest monitoring data, provide a guarantee for developing real-time and effective pest control strategies, and further reduce the threat of pest damage to the safety of farm products. [ABSTRACT FROM AUTHOR]

Conflict in cost sharing is normal in complex water distribution system projects, such as the inter-basin water diversion project (IWDP). China's South to North Water Diversion Project (SNWDP) is the largest IWDP in the world, with a complex relationship between upstream and downstream users of the water supply. Therefore, it is necessary to propose an applicable and unsophisticated cost-sharing method to deal with the complex relationship between upstream and downstream users. This paper proposes an improved cost-sharing method based on the continuity equation of water quantity and the balance equation of the project cost between upstream and downstream users. The fairness of sharing the joint cost between parties involved in the eastern route of SNWDP (ER-SNWDP) obtained using the proposed improved cost-sharing method is investigated by comparing its results with the existing cost-sharing method. The results demonstrate that the proposed method can overcome the non-convergence issue of the existing sharing formula and reduce the differences between upstream and downstream users' sharing costs. The improved method provides a cost-sharing strategy that is more easily accepted by both the upstream and downstream users than the existing estimation approach. Therefore, the proposed pricing approach can provide technical guidance for decision makers in the effective operation of large-scale IWDPs in areas with quasi water markets. [ABSTRACT FROM AUTHOR]

Electroencephalography (EEG) is recorded by electrodes from different areas of the brain and is commonly used to measure neuronal activity. EEG-based methods have been widely used for emotion recognition recently. However, most current methods for EEG-based emotion recognition do not fully exploit the relationship of EEG channels, which affects the precision of emotion recognition. To address the issue, in this paper, we propose a novel method for EEG-based emotion recognition called CR-GCN: Channel-Relationships-based Graph Convolutional Network. Specifically, topological structure of EEG channels is distance-based and tends to capture local relationships, and brain functional connectivity tends to capture global relationships among EEG channels. Therefore, in this paper, we construct EEG channel relationships using an adjacency matrix in graph convolutional network where the adjacency matrix captures both local and global relationships among different EEG channels. Extensive experiments demonstrate that CR-GCN method significantly outperforms the state-of-the-art methods. In subject-dependent experiments, the average classification accuracies of 94.69% and 93.95% are achieved for valence and arousal. In subject-independent experiments, the average classification accuracies of 94.78% and 93.46% are obtained for valence and arousal. [ABSTRACT FROM AUTHOR]

Zeugodacus cucurbitae is an important pest of fruit and vegetable crops in tropical and subtropical regions, and high-temperature stress can have different effects on the development and reproduction of successive generations of Z. cucurbitae. To clarify the multigenerational effects of short-time high temperature on the development and reproduction of Z. cucurbitae, the newly emerged adults of the contemporary (F1 generation) and the next generation (F2 generation) were exposed to short-term high temperatures of 25 °C, 33 °C, 37 °C, 41 °C, and 45 °C for 1 h, and the multigenerational (F1, F2, and F3 generation) effects of these temperatures on the development and reproduction of Z. cucurbitae were evaluated. The results showed that (1) when the F1 was exposed to short-term high temperature, the egg production and lifespan of the F1 decreased continuously with the increasing temperature, except for the 45 °C treatment for 1 h, which stimulated egg production. Only the 41 °C group had significantly higher egg production and lifespan than the control group in the F3. (2) In the F1 and F2 that were exposed to short-term high temperature, the F1 and F3 were consistent with the results of F1 that were exposed to short-term high temperature. In conclusion, the effects of high-temperature intensity and frequency on multiple generations of Z. cucurbitae were different. The results of this study can elucidate the effects of short-term high-temperature stress on the growth, development, and reproduction of Z. cucurbitae in different generations, and provide a reference basis for the integrated control of Z. cucurbitae. [ABSTRACT FROM AUTHOR]

Cyromazine is an insect growth regulator insecticide with high selectivity and is widely used in the production and cultivation of fruits and vegetables. In recent years, incidents of excessive cyromazine residues in food have occurred frequently, and it is urgent to establish an accurate, fast, and convenient method for the detection of cyromazine residues to ensure the safety of edible agricultural products. To achieve rapid detection of cyromazine residues, we prepared a molecularly imprinted electrochemical sensor for the detection of cyromazine residues in agricultural products. Samples of tomato (Lycopersicon esculentum Miller), cowpea (Vigna unguiculata), and water were tested for the recovery rate of cyromazine. The results showed that the concentration of cyromazine showed a good linear relationship with the peak response current of the sensor developed in this study. The lower limit of detection for cyromazine was 0.5 µmol/L, and the sensor also had good reproducibility and interference resistance. This paper can be used as a basis for the study of methods for the detection of cyromazine residues in edible agricultural products. [ABSTRACT FROM AUTHOR]

In this study, a Mg-9Gd-4Y-2Zn-0.5Zr (wt.%) alloy was subjected, after solution treatment, to hot compression deformation at different temperatures (350 °C, 400 °C and 450 °C) and different strain rates (0.001 s−1, 0.01 s−1, 0.1 s−1 and 0.5 s−1) on a Gleeble-3800 thermal simulator. The evolution of the stress–strain curves under different conditions was compared. The changes in microstructure caused by the different deformation parameters and the change law of the long-period stacking-ordered (LPSO) phase during compression were observed and analyzed by optical microscope (OM) and scanning electron microscope (SEM). The results show that with the increase in the deformation temperature and the decrease in the strain rate, the degree of dynamic recrystallization (DRX) gradually increased, and the morphology of the phase also changed through, for example, twist fracture. The continuous dynamic recrystallization (CDRX) and discontinuous dynamic recrystallization (DDRX) mechanisms activated during the thermal deformation process can effectively refine the grains and weaken the texture in the alloy. [ABSTRACT FROM AUTHOR]

Electric carsharing (ECS) is a potential option to address the problem of unsustainability in the transportation sector. The business-to-consumer model of ECS, which is one of several different electric carsharing models, has gained much popularity in recent years. Generating sufficient revenue to cover costs is a critical factor for ECS companies to maintain healthy development. This study makes an economic analysis, on the basis of life-cycle cost and monetary revenue associated with the operation of ECS, of two Chinese ECS companies: EVCARD and LCCS. Based on data gathered by field investigation, this study aims to determine the break-even moment for each company's main vehicle models by means of the net present value method. The results show that EVCARD achieved an earlier break-even moment than LCCS. The break-even moment of Chery eQ of EVCARD was the shortest of all the vehicle models, at only 181.3 min. Moreover, a sensitivity analysis was conducted to portray how different cost-related and revenue-related factors influence the break-even moment. Our findings indicate that a wide difference exists in terms of the influence of different factors on the break-even moment. Among these, the manufacturer's suggested retail price is the most influential variable, followed by the unit rental price. The reaction of the break-even moment to the market price of a charging pile and the non-rental revenue per vehicle—especially the latter—was found to be negligible in the sensitivity analysis. [ABSTRACT FROM AUTHOR]