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This study selected two sweet potato varieties as research subjects and conducted a field experiment using a two-factor design with two potassium (K) levels (K0 and K1) and five nitrogen (N) levels (N0–N4). The physiological changes in sweet potato leaves under different N and K treatments were measured, and nutrients such as the soluble sugar, protein, and starch content of sweet potato roots were analyzed. The results indicate that the activity of glutamine synthetase (GS) and the soluble protein content in sweet potato leaves increase first and then decrease with increasing N application, while K application can significantly increase the activity of GS and the soluble protein content. The N metabolic capacity of leaves is strongest when the fertilizer ratio is K1N2. The SPAD value of sweet potato leaves increases with increasing N application. The net photosynthetic rate, stomatal conductance, and intercellular CO2 concentration first increase and then decrease with increasing N application. K fertilizer has a significant effect on these parameters. As the N application rate increases, the starch and protein content in the tubers increase, while the soluble sugar content decreases. However, the number of tubers per plant, fresh weight of the tubers, and dry weight of the tubers increase initially and then decrease, while the vine length continuously increases. The application of K fertilizer can significantly increase the number of tubers per plant and stem thickness of sweet potato. In conclusion, the appropriate N–K combined application can promote N metabolism, enhance the photosynthetic capacity of sweet potato, increase yield, and improve quality.

Impaired tumor cell antigen presentation contributes significantly to immune evasion. This study identifies Berbamine hydrochloride (Ber), a compound derived from traditional Chinese medicine, as an effective inhibitor of autophagy that enhances antigen presentation in tumor cells. Ber increases MHC-I-mediated antigen presentation in melanoma cells, improving recognition and elimination by CD8+ T cells. Mutation of Atg4b, which blocks autophagy, also raises MHC-I levels on the cell surface, and further treatment with Ber under these conditions does not increase MHC-I, indicating Ber’s role in blocking autophagy to enhance MHC-I expression. Additionally, Ber treatment leads to the accumulation of autophagosomes, with elevated levels of LC3-II and p62, suggesting a disrupted autophagic flux. Fluorescence staining and co-localization analyses reveal that Ber likely inhibits lysosomal acidification without hindering autophagosome–lysosome fusion. Importantly, Ber treatment suppresses melanoma growth in mice and enhances CD8+ T cell infiltration, supporting its therapeutic potential. Our findings demonstrate that Ber disturbs late-stage autophagic flux through abnormal lysosomal acidification, enhancing MHC-I-mediated antigen presentation and curtailing tumor immune escape.

The development in the fields of clean energy, particularly wind and photovoltaic power, generates a large amount of data streams, and how to mine valuable information from these data to improve the efficiency of power generation has become a hot spot of current research. Traditional classification algorithms cannot cope with dynamically changing data streams, so data stream classification techniques are particularly important. The current data stream classification techniques mainly include decision trees, neural networks, Bayesian networks, and other methods, which have been applied to wind power and photovoltaic power data processing in existing research. However, the data drift problem is gradually highlighted due to the dynamic change in data, which significantly impacts the performance of classification algorithms. This paper reviews the latest research on data stream classification technology in wind power and photovoltaic applications. It provides a detailed introduction to the data drift problem in machine learning, which significantly affects algorithm performance. The discussion covers covariate drift, prior probability drift, and concept drift, analyzing their potential impact on the practical deployment of data stream classification methods in wind and photovoltaic power sectors. Finally, by analyzing examples for addressing data drift in energy-system data stream classification, the article highlights the future prospects of data drift research in this field and suggests areas for improvement. Combined with the systematic knowledge of data stream classification techniques and data drift handling presented, it offers valuable insights for future research.

To comprehensively investigate the physiological characteristics and metabolic processes of the mycelium of Floccularia luteovirens (F. luteovirens), a wild edible fungus unique to the plateau region, we conducted an in-depth analysis of the mycelium enzyme activity and metabolites during different culture periods. The activity of seven enzymes all followed a trend of initially increasing and then decreasing. The intra- and extracellular activity peaks of three hydrolases—amylase, protease, and cellulase—all occurred on the 20th day, except for the extracellular amylase, which peaked on the 15th day. In contrast, the peak activity of laccase occurred on the 10th day. Moreover, three types of oxidoreductases in the mycelium (catalase (CAT), superoxide dismutase (SOD), and 2,3,5-triphenyltetrazolium chloride (TTC)-dehydrogenase (TTC-DH)) also exhibited significant changes in activity. CAT and SOD activity reached their maximum on the 20th day, whereas TTC-DH showed high activity on both the 10th and 20th days. Through a comprehensive assessment of the evolving trends of these physiological parameters, we determined that the optimal cultivation cycle for F. luteovirens liquid spawn is 20 days. An untargeted metabolomic analysis revealed that 3569 metabolites were detected in the F. luteovirens mycelium, including a variety of secondary metabolites and functional components, with terpenoids being particularly abundant, accounting for 148 types. By comparing three different culture stages (10 days, 20 days, and 30 days), 299, 291, and 381 metabolites, respectively, showed different accumulation patterns in the comparison groups of 10d vs. 20d, 20d vs. 30d, and 10d vs. 30d. These differential metabolites were primarily concentrated in carboxylic acids and their derivatives, fatty acyl groups, organic oxygen compounds, and lipid compounds. In addition, there were several amino acids whose abundance continued to grow during culturing. The metabolism of amino acids greatly affects mycelium growth and development. This research delineates the interplay between mycelium growth and metabolism, offering empirical support for a cultivation strategy for liquid F. luteovirens, and an exploration of its metabolites for potential applications.

Urea supplements, such as humic acids, could enhance fertilizer nitrogen use effectiveness. Melting is superior to mixing for humate urea application; however, the effects of diverse humate ureas from various coal sources on soil N supply remain unclear. This study compared the properties of two humic acids from different coal sources (HA1, weathered coal; HA2, lignite coal), and their impact on soil mineral N supply and the nitrate–ammonium ratio under flooded and 60% water-filled pore space (WFPS) over a 14-day incubation. Humate ureas stimulated soil mineral N accumulation and balanced the soil nitrate–ammonium ratio at 1:1; however, no significant difference existed between the two humate ureas under 60% WFPS. Humate urea enhanced soil ammonium nitrogen (NH4+-N) retention and delayed nitrate nitrogen (NH4−-N) release, leading to soil mineral N retention, especially in lignite humic acid urea (H2AU) treatments from lignite under flooding. Structural equation modeling (SEM) and linear regression revealed that humic acids elevated soil redox potential (Eh) and electrical conductivity (EC), stimulating soil N mineralization and adjusting the optimal nitrate–ammonium ratio. Humate urea improved soil mineral N supply compared to traditional urea treatments, and humic acids from lignite were more beneficial for crop cultivation from a mineral soil N supply perspective. These findings enhance our understanding of humate urea benefits and aid in optimizing humic acids application for N management.

To investigate the ecological impacts of macroalgae in the framework of shifting global CO2 concentrations, we conducted a study utilizing Ulva fasciata and Sargassum horneri specimens sourced from the Ma’an Archipelago in Zhejiang Province on how ocean acidification (OA) and temperature changes interact to affect the photosynthetic physiological responses of macroalgae. The results of the study showed that OA reduced the tolerance of U. fasciata to bright light at 20 °C, resulting in more pronounced photoinhibition, while 15 °C caused significant inhibition of U. fasciata, reducing its growth and photosynthetic activity, but OA alleviated the inhibition and promoted the growth of the alga to a certain extent. The tolerance of S. horneri to bright light was also reduced at 20 °C; the inhibition was relieved at 15 °C, and the OA further improved the algal growth. The Relative Growth Rate (RGR), photosynthetic pigment content, and the release of the dissolved organic carbon (DOC) of U. fasciata were mainly affected by the change in temperature; the growth of the alga and the synthesis of metabolites were more favored by 20 °C. A similar temperature dependence was observed for S. horneri, with faster growth and high metabolism at 15 °C. Our results suggest that OA reduces the tolerance of macroalgae to high light at suitable growth temperatures; however, at unsuitable growth temperatures, OA effectively mitigates this inhibitory effect and promotes algal growth.

An efficient humanitarian emergency logistics network is vital in responding to earthquake disasters. However, the asymmetric information inherent in the location and distribution stages can complicate the humanitarian emergency logistics network designing process, resulting in an asymmetric optimization problem. This paper addresses a multi-objective humanitarian emergency logistics network design problem during the earthquake response phase. The objective is to reduce societal expenses (e.g., logistical and deprivation costs) and mitigate risk to the logistics network by identifying ideal sites for distribution hubs, optimal emergency material distribution strategies, and precise material loading plans. The proposed model takes into account various constraint types, such as 3D loading limitations for relief materials, interruptions in distribution hubs, distribution centers’ capacity, transport vehicles’ capacity, and specific time windows for demand points. First, a multi-objective mixed-integer programming model is established to solve the problem. Uncertainty is modeled using a scenario-based probability approach. Second, a multi-objective genetic algorithm based on adaptive large neighborhood search (MOGA-ALNS) is designed to further optimize the solutions obtained from the evolutionary process using an adaptive large neighborhood search algorithm. Furthermore, the MOGA-ALNS integrates a simulated annealing process in the neighborhood search stage to inhibit the algorithm from reaching local optimums. Ultimately, the MOGA-ALNS is compared to three additional multi-objective optimization algorithms. The comprehensive analysis and discussion conducted unequivocally validate the competitiveness and efficacy of the proposed approach.

Seaweed farming has made outstanding contributions to food supply and the restoration of the ecological environment despite the limitations in production and ecological effects due to the current intensive farming of single algae species. These limitations can be overcome by selecting suitable algal species based on their physiological characteristics and by constructing a large-scale seaweed rotation model. This study carried out a trial culture in aquaculture sea areas, and performed in situ monitoring of the environmental conditions and physiological characteristics of Saccharina japonica, Hizikia fusiformis, and Gracilariopsis lemaneiformis. Additionally, a comparative analysis of the three macroalgae at different times was conducted to determine their response characteristics to environmental factors. The results showed that: (1) The three macroalgae had varying light tolerance. The effective quantum yield of Hizikia fusiformis and Gracilariopsis lemaneiformis remained unchanged during the changes in light environment, while that of Saccharina japonica first decreased and then recovered. (2) The relative electron transport rates of the three macroalgae were significantly different under different temperature conditions. Hizikia fusiformis and Saccharina japonica exhibited the highest relative electron transport rates (70.45 and 106.75, respectively) in May (20.3 °C). Notably, Gracilariopsis lemaneiformis demonstrated good growth and exhibited the highest relative electron transport rate (93.07) in September (27.5 °C). These findings collectively support the feasibility of establishing a macroalgae rotation model. Based on the combined environmental conditions of the seas in Shandong, Zhejiang, and Fujian, a macroalgae rotation model was proposed. The application of this model in the construction of artificial seaweed farms in marine ranches can provide a stable output of large-scale seaweed production and ecological benefits.

The rocket sled, as a ground dynamic test system, combines the characteristics of the wind tunnel test and the flight test. However, some practical factors, such as shock wave interference, ground effect, and high-intensity aerodynamic noise will cause serious interference and even failure of the uniformly distributed sensors during horizontal sliding in a wide speed range. The AGARD HB-2 standard model is employed as the payload to simulate the aerodynamic and aeroacoustic characteristics during the variable acceleration period, aiming to optimize the test sensors layout. It is observed that in the high Mach number flow fields, strong coupling behaviors among complex waves will occur. The peak of wake vortex strength will appear at 1.5 s and gradually diminish over time. In addition, when the vortex between the load and the booster is monitored, its position shifts forward in the subsonic stage, then gradually moves backward and expands in the supersonic stage. Acoustic directivity is pronounced at subsonic and transonic speeds, pointing towards 75° and 135° relative to the sliding speed, respectively. These results can provide technical support for sensor layout and high-precision testing in rocket sled tests.

Vector polygons represent crucial survey data, serving as a cornerstone of national geographic censuses and forming essential data sources for detecting geographical changes. The timely update of these polygons is vital for governmental decision making and various industrial applications. However, the manual intervention required to update existing vector polygons using up-to-date high-resolution remote sensing (RS) images poses significant challenges and incurs substantial costs. To address this, we propose a novel change detection (CD) method for land cover vector polygons leveraging high-resolution RS images and deep learning techniques. Our approach begins by employing the boundary-preserved masking Simple Linear Iterative Clustering (SLIC) algorithm to segment RS images. Subsequently, an adaptive cropping approach automatically generates an initial sample set, followed by denoising using the efficient Visual Transformer and Class-Constrained Density Peak-Based (EViTCC-DP) method, resulting in a refined training set. Finally, an enhanced attention-based multi-scale ConvTransformer network (AMCT-Net) conducts fine-grained scene classification, integrating change rules and post-processing methods to identify changed vector polygons. Notably, our method stands out by employing an unsupervised approach to denoise the sample set, effectively transforming noisy samples into representative ones without requiring manual labeling, thus ensuring high automation. Experimental results on real datasets demonstrate significant improvements in model accuracy, with accuracy and recall rates reaching 92.08% and 91.34%, respectively, for the Nantong dataset, and 93.51% and 92.92%, respectively, for the Guantan dataset. Moreover, our approach shows great potential in updating existing vector data while effectively mitigating the high costs associated with acquiring training samples.

The Winkler foundation modulus is key to evaluating the response of underground structures using the elastic foundation beam model. In this paper, an improved formula of the Winkler foundation modulus for a beam embedded in a full space is proposed to overcome the limitation of inconsistent assumptions in previous studies. To achieve this goal, the bending responses of the beam are obtained using the elastic foundation beam model and three-dimensional elastic continuum model, respectively, wherein a consistent assumption is proposed that tangential interactions at the beam–ground interface are ignored in the two models. In addition, as deformation of the site is an important source of the underground structure response, the beam is applied to standard soil displacement of the free field on the Winkler foundation to improve the accuracy of the Winkler modulus obtained by fitting solutions based on the concentrated force on the beam. The formula for the Winkler foundation is obtained by equating the first zero of the bending moment in the two models. The Winkler foundation modulus is verified by comparing the results with numerical solutions and previous studies.

Generalized Pareto distribution (GPD), an asymmetrical distribution, primarily models exceedances over a high threshold in many applications. Within the peaks-over-threshold (POT) framework, we consider a new GPD parameter estimation method to estimate a common tail risk measure, the value at risk (VaR). The proposed method is more suitable for the POT framework and makes full use of data information. Specifically, our estimation method builds upon the generalized probability weighted moments method and integrates it with the nonlinear weighted least squares method. We use exceedances for the GPD, minimizing the sum of squared differences between the sample and population moments of a function of GPD random variables. At the same time, the proposed estimator uses three iterations and assigns weight to further improving the estimated performance. Under Monte Carlo simulations and with a real heavy-tailed dataset, the simulation results show the advantage of the newly proposed estimator, particularly when VaRs are at high confidence levels. In addition, by simulating other heavy-tailed distributions, our method still exhibits good performance in estimating misjudgment distributions.

Reproduction plays a crucial role in determining the development, fate, and dynamics of bird populations. However, reproductive strategies vary among species and populations. In this study, we investigated the reproductive strategies of the Oriental Magpie Robin (Copsychus saularis) and White-rumped Shama (C. malabarica), which are closely related passerines that reproduce in sympatric areas. We found that although these two species were both cavity nesting, their nest-site selection differed; the Shama preferred nesting close to trees and forests, whereas the Magpie Robin nested close to human residential areas. Furthermore, their egg incubation patterns differed; the Shama increased daily incubation frequency with incubation time, but the Magpie Robin maintained its daily incubation time regardless of changes in incubation frequency. However, the nestling heating patterns of these two species were similar, indicating a critical demand for regulating hatchling body temperature during this crucial stage. The feeding frequencies of male parents were strongly correlated with those of females in both species, suggesting equal contribution and good synchronization between the sexes. Nestling feeding frequency was also correlated with nest cleaning frequency, implying coordination between feeding and defecation by parents and offspring, respectively. This research explored the divergence and convergence of reproductive strategies between these two sympatric species, providing valuable insights into the niche differentiation theory.

To prevent damage to human life and health caused by high temperatures and extreme weather and to promote sustainable urban development, it is necessary to optimize the layout of urban development elements to improve the urban wind–heat environment. Taking the high-density urban area of Shanghai as an example, this study used wavelet analysis to investigate the cyclic changes of the average annual temperature of Shanghai from 1950 to 2022 and the average annual wind speed of Shanghai from 2000 to 2020. The correlation between the urban heat environment and the urban development elements was analyzed using geographically weighted regression. The correlation was then examined using BP neural network, and finally, the impacts of different urban spatial patterns on the wind environment were analyzed using CFD numerical simulation. The results show that the average annual temperature of Shanghai city has an overall upward trend, with significant cycles of 44 and 32 years that are shortening over time. The average annual wind speed has a downward trend, with a significant main cycle of 22 years. Greening and water coverage, as well as the floor area ratio, have a significant reducing effect on surface temperature, whereas building density is positively correlated with surface temperature. Building density has a significant reducing effect on wind speed, whereas the effect of floor area ratio is not significant. The effect of building density on wind speed is significantly weakened, whereas the effect of the floor area ratio is not significant. This study provides valuable references for Shanghai and other high-density cities to optimize urban spatial patterns in order to improve the safety and comfort of the urban wind–heat environments. This study is of significant importance and value in promoting sustainable urban development, protecting the health of urban residents, and advancing spatial justice and equal well-being.

Participatory crowdsensing (PCS) is an innovative data sensing paradigm that leverages the sensors carried in mobile devices to collect large-scale environmental information and personal behavioral data with the user’s participation. In PCS, task assignment and path planning pose complex challenges. Previous studies have only focused on the assignment of individual tasks, neglecting or overlooking the associations between tasks. In practice, users often tend to execute similar tasks when choosing assignments. Additionally, users frequently engage in tasks that do not match their abilities, leading to poor task quality or resource wastage. This paper introduces a multi-task assignment and path-planning problem (MTAPP), which defines utility as the ratio of a user’s profit to the time spent on task execution. The optimization goal of MATPP is to maximize the utility of all users in the context of task assignment, allocate a set of task locations to a group of workers, and generate execution paths. To solve the MATPP, this study proposes a grade-matching degree and similarity-based mechanism (GSBM) in which the grade-matching degree determines the user’s income. It also establishes a mathematical model, based on similarity, to investigate the impact of task similarity on user task completion. Finally, an improved ant colony optimization (IACO) algorithm, combining the ant colony and greedy algorithms, is employed to maximize total utility. The simulation results demonstrate its superior performance in terms of task coverage, average task completion rate, user profits, and task assignment rationality compared to other algorithms.

A large-scale physical model experiment was conducted to study the interaction between regular waves and submerged horizontal cylinders, breaking through the bottleneck of a low Reynolds number in a traditional small water tank. The surface pressure distribution and overall force of submerged horizontal cylinders at different submerged depths in waves with different heights and periods under a high Reynolds number were analyzed, and the variation in first- and second-order wave forces with wave height periods was analyzed. Subsequently, the influence of the cylinder on the wave field was analyzed, and the reflection coefficient was obtained through the three-point separation method. According to the analysis of the experimental results, the horizontal and vertical forces acting on the submerged cylinder per linear meter are similar, with the horizontal force slightly greater than the vertical force; at the same time, the submerged cylinder has a certain reflection effect on long-period waves. The summary, analysis, and display of relevant experimental results provide validation support for the current high-precision mathematical model as much as possible.

Due to their versatile and unique properties, tantalum-based thin films have been extensively studied. However, tantalum is susceptible to oxidation due to its higher chemical activity, which is crucial regardless of whether oxidations of Ta are beneficial or detrimental. Therefore, the oxidation of Ta during material processing, especially without conscious means, should be taken seriously. In this study, pure Ta films were fabricated by magnetron sputtering under set procedure parameters. The effects of base pressure and substrate temperature on the degree of oxidation of Ta films were investigated. The results revealed that the magnitude of the base pressure directly affects the oxidation state of the as-deposited Ta films. When preferably avoiding the oxidation of sputtered Ta films, the base pressure should be controlled below 4.4 × 10−4 Pa. The substrate temperature has little effect on the oxidation state of the as-deposited Ta films under a base pressure ranging from about 10−2 Pa to 10−4. We hope that this study can provide some references for controlling the oxidation states of Ta involved in relevant film preparation.

The abnormal regulation and expression of microRNA (miRNA) are closely related to the aging process and the occurrence and development of aging-related diseases. Lethal-7 (let-7) was discovered in Caenorhabditis elegans (C. elegans) and plays an important role in development by regulating cell fate regulators. Accumulating evidence has shown that let-7 is elevated in aging tissues and participates in multiple pathways that regulate the aging process, including affecting tissue stem cell function, body metabolism, and various aging-related diseases (ARDs). Moreover, recent studies have found that let-7 plays an important role in the senescence of B cells, suggesting that let-7 may also participate in the aging process by regulating immune function. Therefore, these studies show the diversity and complexity of let-7 expression and regulatory functions during aging. In this review, we provide a detailed overview of let-7 expression regulation as well as its role in different tissue aging and aging-related diseases, which may provide new ideas for enriching the complex expression regulation mechanism and pathobiological function of let-7 in aging and related diseases and ultimately provide help for the development of new therapeutic strategies.

Bacterial community is a key factor affecting aerobic composting, and understanding bacterial community succession is important to revealing the mechanism of organic matter degradation. In this study, the succession and metabolic characteristics of bacterial communities were explored in 45 days composting of sheep manure and wheat straw by using high-throughput sequencing technology and bioinformatics tools, respectively. Results showed that the alpha diversity of bacterial community significantly decreased in the thermophilic (T2) phase and then recovered gradually in the bio-oxidative (T3) and the maturation (T4) phases. Bacterial communities varied at different stages, but there were 158 genera in common bacterial species. Unclassified_f_Bacillaceae, Oceanobacillus, Bacillus, Pseudogracilibacillus, and Nocardiopsis were identified as keystone bacterial genera. Eleven genera were significantly correlated (p < 0.05), or even extremely significantly correlated (p < 0.001), with the physicochemical factors. Redundancy analysis (RDA) showed that changes of bacterial community diversity correlated with physicochemical factors. The highest relative abundances were amino acid and carbohydrate metabolism among the metabolic groups in the compost. These results will provide theoretical support for further optimizing sheep manure composting conditions and improving the quality of organic fertilizers.

In this paper, a new analytical method to achieve the maximum signal-to-noise ratio (SNR) of a micro search coil magnetometer (µSCM) is presented. A planar spiral inductor was utilized to miniaturize conventional bulky search coil magnetometers. First, dimensional analysis was applied to identify three dimensionless parameters for the µSCM’s key performance indices (sensitivity (Se), noise, and SNR). The effect of the parameters on the µSCM’s performance was carefully investigated, and a novel 4D nomogram was developed. Furthermore, an SNR analysis considering noise sources of a low-noise amplifier was performed. By combining the results from the nomogram and the effect of the noise sources from the amplifier circuit, optimum values for the dimensionless parameters were calculated. According to the calculation results, the dominant noise source varied with an increase in the track width ratio to the outer diameter. Seven different samples were fabricated by a single-mask lithography process. The sensitivity of 1612 mV/mT was demonstrated at a 50 Hz input magnetic field, which was better than the previous µSCM (Se = 6.5 mV/mT) by more than 2 orders of magnitude. Finally, one of the fabricated µSCMs was employed to measure the online power consumption of a personal computer while different types of software were running.

This paper presents a method for use in estimating the state of charge (SOC) of lithium-ion batteries which is based on an electrochemical impedance equivalent circuit model with a controlled source. Considering that the open-circuit voltage of a battery varies with the SOC, an equivalent circuit model with a controlled source is proposed which the voltage source and current source interact with each other. On this basis, the radial basis function (RBF) neural network is adopted to estimate the uncertainty in the battery model online, and a non-linear observer based on the radial basis function of the RBF neural network is designed to estimate the SOC of batteries. It is proved that the SOC estimation error is ultimately bounded by Lyapunov stability analysis, and the error bound can be arbitrarily small. The high accuracy and validity of the non-linear observer based on the RBF neural network in SOC estimation are verified with experimental simulation results. The SOC estimation results of the extended Kalman filter (EKF) are compared with the proposed method. It improves convergence speed and accuracy.

Air pollution is a major global problem, closely related to economic and social development and ecological environment construction. Air pollution data for most regions of China have a close correlation with time and seasons and are affected by multidimensional factors such as meteorology and air quality. In contrast with classical peaks-over-threshold modeling approaches, we use a deep learning technique and three new dynamic conditional generalized Pareto distribution (DCP) models with weather and air quality factors for fitting the time-dependence of the air pollutant concentration and make statistical inferences about their application in air quality analysis. Specifically, in the proposed three DCP models, a dynamic autoregressive exponential function mechanism is applied for the time-varying scale parameter and tail index of the conditional generalized Pareto distribution, and a sufficiently high threshold is chosen using two threshold selection procedures. The probabilistic properties of the DCP model and the statistical properties of the maximum likelihood estimation (MLE) are investigated, simulating and showing the stability and sensitivity of the MLE estimations. The three proposed models are applied to fit the PM2.5 time series in Beijing from 2015 to 2021. Real data are used to illustrate the advantages of the DCP, especially compared to the estimation volatility of GARCH and AIC or BIC criteria. The DCP model involving both the mixed weather and air quality factors performs better than the other two models with weather factors or air quality factors alone. Finally, a prediction model based on long short-term memory (LSTM) is used to predict PM2.5 concentration, achieving ideal results.

SNAREs (soluble N-ethylmaleimide-sensitive factor attachment protein receptors) are central components that drive membrane fusion events during exocytosis and endocytosis and play important roles in different biological processes of plants. In this study, we identified 237 genes encoding SNARE family proteins in B. napus in silico at the whole-genome level. Phylogenetic analysis showed that BnaSNAREs could be classified into five groups (Q (a-, b-, c-, bc-) and R) like other plant SNAREs and clustered into twenty-five subclades. The gene structure and protein domain of each subclade were found to be highly conserved. In many subclades, BnaSNAREs are significantly expanded compared with the orthologous genes in Arabidopsis thaliana. BnaSNARE genes are expressed differentially in the leaves and roots of B. napus. RNA-seq data and RT-qPCR proved that some of the BnaSNAREs are involved in the plant response to S. sclerotiorum infection as well as treatments with toxin oxalic acid (OA) (a virulence factor often secreted by S. sclerotiorum) or abscisic acid (ABA), methyl jasmonate (MeJA), and salicylic acid (SA), which individually promote resistance to S. sclerotiorum. Moreover, the interacted proteins of BnaSNAREs contain some defense response-related proteins, which increases the evidence that BnaSNAREs are involved in plant immunity. We also found the co-expression of BnaSYP121/2s, BnaSNAPs, and BnaVAMP722/3s in B. napus due to S. sclerotiorum infection as well as the probable interaction among them.

To guarantee information security in communication, quantum identity authentication plays a key role in politics, economy, finance, daily life and other fields. In this paper, a new quantum multiparty simultaneous identity authentication protocol with Greenberger–Home–Zeilinger (GHZ) state is presented. In this protocol, the authenticator and the certified parties are the participants with quantum ability, whereas the third party is a classical participant. Here, the third-party is honest and the other two parties may be dishonest. With the help of a classical third-party, a quantum authenticator and the multiple certified parties can implement two-way identity authentication at the same time. It reduces the quantum burden of participants and lowers down the trustworthiness, which makes the protocol be feasible in practice. Through further security analysis, the protocol can effectively prevent an illegal dishonest participant from obtaining a legitimate identity. It shows that the protocol is against impersonation attack, intercept-measure-resend attack and entangle-measure attack, etc. In all, the paper provides positive efforts for the subsequent security identity authentication in quantum network.

At the end of 2019, an outbreak of the novel coronavirus (COVID-19) made a profound impact on the country’s production and people’s daily lives. Up until now, COVID-19 has not been fully controlled all over the world. Based on the clinical research progress of infectious diseases, combined with epidemiological theories and possible disease control measures, this paper establishes a Susceptible Infected Recovered (SIR) model that meets the characteristics of the transmission of the new coronavirus, using the least square estimation (LSE) method to estimate the model parameters. The simulation results show that quarantine and containment measures as well as vaccine and drug development measures can control the spread of the epidemic effectively. As can be seen from the prediction results of the model, the simulation results of the epidemic development of the whole country and Nanjing are in agreement with the real situation of the epidemic, and the number of confirmed cases is close to the real value. At the same time, the model’s prediction of the prevention effect and control measures have shed new light on epidemic prevention and control.

Quantum dual-signature means that two signed quantum messages are combined and expected to be sent to two different recipients. A quantum signature requires the cooperation of two verifiers to complete the whole verification process. As an important quantum signature aspect, the trusted third party is introduced to the current protocols, which affects the practicability of the quantum signature protocols. In this paper, we propose a quantum dual-signature protocol without arbitrator and entanglement for the first time. In the proposed protocol, two independent verifiers are introduced, here they may be dishonest but not collaborate. Furthermore, strongly nonlocal orthogonal product states are used to preserve the protocol security, i.e., no one can deny or forge a valid signature, even though some of them conspired. Compared with existing quantum signature protocols, this protocol does not require a trusted third party and entanglement resources.

For utilizing the largest source of marine proteins, Antarctic krill (Euphausia superba) proteins were defatted and hydrolyzed separately using pepsin, alcalase, papain, trypsin, and netrase, and alcalase hydrolysate (EPAH) showed the highest DPPH radical (DPPH·) and hydroxyl radical (HO·) scavenging activity among five hydrolysates. Using ultrafiltration and chromatography methods, fifteen antioxidant peptides were purified from EPAH and identified as Asn-Gln-Met (NQM), Trp-Phe-Pro-Met (WFPM), Gln-Asn-Pro-Thr (QNPT), Tyr-Met-Asn-Phe (YMNF), Ser-Gly-Pro-Ala (SGPA), Ser-Leu-Pro-Tyr (SLPY), Gln-Tyr-Pro-Pro-Met-Gln-Tyr (QYPPMQY), Glu-Tyr-Glu-Ala (EYEA), Asn-Trp-Asp-Asp-Met-Arg-Ile-Val-Ala-Val (NWDDMRIVAV), Trp-Asp-Asp-Met-Glu-Arg-Leu-Val-Met-Ile (WDDMERLVMI), Asn-Trp-Asp-Asp-Met-Glu-Pro-Ser-Phe (NWD-DMEPSF), Asn-Gly-Pro-Asp-Pro-Arg-Pro-Ser-Gln-Gln (NGPDPRPSQQ), Ala-Phe-Leu-Trp-Asn (AFLWA), Asn-Val-Pro-Asp-Met (NVPDM), and Thr-Phe-Pro-Ile-Tyr-Asp-Tyr-Pro-Gln (TFPIYDPQ), respectively, using a protein sequencer and ESI/MS. Among fifteen antioxidant peptides, SLPY, QYPPMQY and EYEA showed the highest scavenging activities on DPPH· (EC50 values of 1.18 ± 0.036, 1.547 ± 0.150, and 1.372 ± 0.274 mg/mL, respectively), HO· (EC50 values of 0.826 ± 0.027, 1.022 ± 0.058, and 0.946 ± 0.011 mg/mL, respectively), and superoxide anion radical (EC50 values of 0.789 ± 0.079, 0.913 ± 0.007, and 0.793 ± 0.056 mg/mL, respectively). Moreover, SLPY, QYPPMQY and EYEA showed strong reducing power, protective capability against H2O2-damaged plasmid DNA, and lipid peroxidation inhibition ability. Furthermore, SLPY, QYPPMQY, and EYEA had high stability under temperatures lower than 80 °C, pH values ranged from 6–8, and simulated GI digestion for 180 min. The results showed that fifteen antioxidant peptides from alcalase hydrolysate of Antarctic krill proteins, especially SLPY, QYPPMQY and EYEA, might serve as effective antioxidant agents applied in food and health products.

To study the effect of weld and defects on the corrosion behavior of nickel aluminum bronze (UNS C95810) in 3.5% NaCl solution, the weight loss, X-ray diffraction, optical microscope, scanning electron microscope and electrochemical test of the specimen with weld and defects were investigated. The results show that the presence of weld and defects increases the corrosion rate of bronze. Weld does not change the structure of the corrosion product film, but defects induce a lack of the protective outermost corrosion product in bronze. Weld makes the corrosion product film in the early stage more porous. Defects always produce an increase in the dissolution rate of the bronze.

Quantitative analysis of the reallocation and linkages of virtual water in the economic sector was important for the integrated water resources management in inland arid regions. Taking the northern Tianshan Mountains (NTM) as an example, we applied the environmental input-output model to design the accounting framework for the reallocation of blue and green virtual water (VW) in the economic sector and analyzed the correlation effect of VW reallocation among various sectors by backward and forward linkages in economic analysis. The results showed that the direct blue and green water consumption of primary industry respectively accounted for 99.2% and 100% of the total water consumption in NTM. Planting sector had the largest amount of VW outflow among all sectors. Animal husbandry, forestry and construction had a large pulling effect on VW outflow of planting sector, while planting sector and animal husbandry were the main sectors for VW export of blue and green water. We suggest that the government can increase the import of blue-green VW for agricultural raw materials through VW trade and develop industries such as service and electricity that have less pulling effect on the primary industry VW, so as to improve the economic added value of VW in the primary industry and reduce the loss of VW in primary industry production and trade flows in future water management.

To solve the problems of the decreased reliability and safety of battery pack due to the inconsistency between batteries after single batteries are grouped is of great significance to find an appropriate sorting method of single batteries. This study systematically reviews the available literature on battery sorting applications for battery researchers and users. These methods can be roughly divided into three types: direct measurement, sorting based on the model, and sorting based on the material chemistry of batteries. Among them, direct measurement is about the direct measurement of the state parameters of batteries using some professional instruments or testing tools to sort and group batteries with similar or close parameters. Sorting based on the model classifies batteries into groups by establishing a battery equivalent model and carrying out model identification and parameter estimation with machine learning or artificial intelligence algorithm. Sorting based on the material chemistry of batteries is to explore some characteristics related to the chemical mechanism inside the battery. On the basis of reading extensive literature, the methods for classification of battery are provided with an in-depth explanation, and each corresponding strengths and weaknesses of these methods are analyzed. Finally, the future developments of advanced sorting algorithms and batteries prospect.

The filter press is one of the most important devices in purified terephthalic acid (PTA) refinement, and it is of great significance to ensure the fatigue strength of the structure in operation. In this study, the fatigue life prediction of the shell structure of the PTA filter press was investigated through numerical and experimental methods. Firstly, the accurate stress at the critical area of the stiffener was obtained based on the thermomechanical model and submodel approach proposed. Subsequently, the fatigue life was evaluated by the fatigue strength reduction method and hot spot stress method. Finally, the shell structure is optimized by increasing the size of the axial stiffener and continuous hoop stiffener. The results unveil that both thermal load and outer structure constraints have little effect on the radial displacement and stress amplitude of the shell structure. Through modifying the fatigue design curve of the fatigue strength reduction method, the shell structure of the PTA filter press has 42.0% and 0.3% failure probabilities in the previous and present cyclic pressure conditions. Furthermore, the hoop stiffener plays an important role in reducing radial displacement and stress amplitude, among which three hoop stiffeners exhibit the most satisfactory optimization.

This study investigates the spatial expansion process, the de facto land use change, and their endogenous driving forces in the village of Fengzhuang since the 1990s. Fengzhuang is a specialized village in Hebei, North China, in which above 80% of rural residents are engaged in the manufacturing of mahogany furniture. Land use data were extracted from a participatory rural appraisal (PRA) survey conducted in 2014–2015. The results suggest that the land in Fengzhuang has been expanding rapidly under the influence of the informal furniture industry. The villagers transform their residential areas into family workshops and factories for the production of furniture. Most rural areas officially marked as residential are, in effect, used for industrial production, resulting in the informality of land use and circulation. The in-depth survey also reveals that the informality of the furniture industry, the bottom-up process of land development, and the evolution of government regulation are the major reasons leading to the de facto change of land use in Fengzhuang. This study offers a microscopic perspective of land use change, which helps to explore the formation and change of rural land use and actual functions, as well as the mechanisms behind them. These findings are expected to provide some implications for improving rural development strategies, rural planning, and governance in China’s specialized villages such as Fengzhuang.

To study the effect of cast defects on the corrosion behavior and mechanism of the UNS C95810 alloy in seawater, an investigation was conducted by weight loss determination, scanning electron microscopy (SEM), confocal laser scanning microscopy (CLSM), X-ray diffraction (XRD) and electrochemical testing of the specimen with and without cast defects on the surface. The results show that the corrosion rate of the alloy with cast defects is higher than that of the alloy without cast defects, but the defects do not change the composition of the resulting corrosion products. The defects increase the complexity of the alloy microstructure and the tendency toward galvanic corrosion, which reduce the corrosion potential from −3.83 to −86.31 mV and increase the corrosion current density from 0.228 to 0.23 μA⋅cm−2.

Bioactive peptides from fish collagens with antioxidant properties have become a topic of great interest for health, food, and processing/preservation industries. To explore the high-value utilized way of scales produced during the fish processing, collagen hydrolysates of redlip croaker (Pseudosciaena polyactis) scales were prepared using six different proteases, and the hydrolysate (RSCH) prepared using neutrase showed the highest degree of hydrolysis (21.36 ± 1.18%) and 2,2-diphenyl-1-picrylhydrazyl (DPPH·) radical scavenging activity (30.97 ± 1.56%) among the six hydrolysates. Subsequently, six antioxidant peptides were purified from RSCH using membrane ultrafiltration and serial chromatography, and their amino acid sequences were identified as DGPEGR, GPEGPMGLE, EGPFGPEG, YGPDGPTG, GFIGPTE, and IGPLGA with molecular masses of 629.61, 885.95, 788.96, 762.75, 733.80, and 526.61 Da, respectively. Among six collagen peptides, GPEGPMGLE, EGPFGPEG, and GFIGPTE exhibited the strongest scavenging activities on DPPH· radical (EC50 0.59, 0.37, and 0.45 mg/mL), hydroxyl radical (EC50 0.45, 0.33, and 0.32 mg/mL), and superoxide anion radical (EC50 0.62, 0.47, and 0.74 mg/mL). GPEGPMGLE, EGPFGPEG, and GFIGPTE showed high inhibiting ability on lipid peroxidation in a linoleic acid model system and protective activities on oxidation-damaged DNA. More importantly, GPEGPMGLE, EGPFGPEG, and GFIGPTE could protect HepG2 cells from H2O2-induced oxidative damage through decreasing the levels of reactive oxygen species (ROS) and MDA and activating intracellular antioxidant enzymes of superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH-Px). These results suggested that six collagen peptides (RCP1−RCP6), especially GPEGPMGLE, EGPFGPEG, and GFIGPTE, might serve as potential antioxidants applied in nutraceutical and pharmaceutical products.

This paper addresses a comprehensive and further insight into the sensitivity of material removal and the surface defect formation mechanism to scratch depth during single-grit scratch tests of 50 vol% SiCp/Al composites. The three-dimensional (3D) finite element model with more realistic 3D micro-structure, particle-matrix interfacial behaviors, particle-particle contact behaviors, particle-matrix contact behaviors and a Johnson-Holmquist-Beissel (JHB) model of SiC was developed. The scratch simulation conducted at scratch velocity 10 mm/min and loading rate 40 N/min revealed that the scratch depth plays a crucial role in material removal and the surface forming process. Brittle fracturing of SiC particles and surface defects become more deteriorative under a large scratch depth ranging from 0.0385 to 0.0764 μm. The above phenomenon can be attributed to the influence of scratch depth on SiC particles’ transport; the increase in the amount of SiC particle transport resulting from an increase of scratch depth raises the occurrence of particle-particle collision which provides hard support and shock for the scratched particles; therefore, brittle fracturing gradually becomes the major removal mode of SiC particles as the scratch depth increases. On the deteriorative surface, various defects are observed; i.e., lateral cracks, interfacial debonding, cavies filled with residually broken particles, etc. The von Mises stress distribution shows that SiC particles bear vast majority of load, and thus present greater stress than the surrounding Al matrix. For example: their ratio of 3 to 30 under the scratch depth of 0.011 mm. Namely, SiC particles impede stress diffusion within the Al matrix. Finally, the SEM images of the scratched surface obtained from the single-grit scratch experiments verify the numerical analysis’s results.

Identifying the main sources of conflict and understanding the relationships between protected areas and local communities are critical to conflict resolution related to protected area management. We surveyed and assessed the perceptions of local people related to forest values of the Bulong Nature Reserve (BNR), Yunnan, China, and their attitudes toward forest management of the recently-established nature reserve. Factors influencing the differences in perceptions and attitudes were investigated. Our results indicated local residents preferred the economic value of forests, and they perceived more forest values after reserve establishment than before, especially for ecological services. Interviewees believed the value of the forests have increased, and predicted that the forest will have increased importance to their livelihoods and health in the future. Nonetheless, the majority of interviewees were dissatisfied with current reserve management. Variation in these perceptions and attitudes were related to several social variables: age, gender, education, and distance from the reserve. Embedding the findings of the present study, specifically the perceptions and attitudes of local people, into management guidelines for mitigation of potential conflicts is proposed and should help managers to achieve biodiversity-related goals. This study offers new insights related to the identification of the underlying sources of conflict in forest management and provides a better understanding of the relationship between local people and protected areas. The study also contributes to the literature on forest values of indigenous populations by examining those of remote, rural populations in China.

This paper proposes a new ultracompact planar positioner driven by unbalanced frictional forces. The prototype of the designed positioner is 17 mm × 17 mm × 9 mm in size, and is simply constructed using lead zirconate titanate piezoelectric elements, neodymium magnetic feet, and junction pieces. Alternating static and kinetic frictional forces are utilized to control the motion of the positioner. The working principle is illustrated, and the performance of the positioner is evaluated under atmospheric and vacuum conditions. Under atmospheric conditions, the positioner had a minimum step size of approximately 17 nm at 55 V, a maximum step size of approximately 1.6 μm, and a moving speed of approximately 4 μm/s at 138 V. However, the step size significantly decreased in vacuum. The step size can be controlled by adjusting the frictional forces on the magnetic feet. In addition, the positioner showed instability caused by the wear of the stainless plate. This problem was resolved by using a borosilicate glass that was fixed on the stainless plate, and the position accuracy was obviously improved.

The search to date for accurate protein biomarkers in acute ischemic stroke has taken into consideration the stage and/or the size of infarction, but has not accounted for the site of stroke. In the present study, multiple reaction monitoring using labeled reference peptide (LRP) following laser capture microdissection (LCM) is used to identify site-specific protein biomarker candidates. In middle cerebral artery occlusion (MCAO) rat models, both intact and infarcted brain tissue was collected by LCM, followed by on-film digestion and semi-quantification using triple-quadrupole mass spectrometry. Thirty-four unique peptides were detected for the verification of 12 proteins in both tissue homogenates and LCM-captured samples. Six insoluble proteins, including neurofilament light polypeptide (NEFL), alpha-internexin (INA), microtubule-associated protein 2 (MAP2), myelin basic protein (MBP), myelin proteolipid protein (PLP) and 2′,3′-cyclic-nucleotide 3′-phosphodiesterase (CNP), were found to be site-specific. Soluble proteins, such as neuron-specific enolase (NSE) and ubiquitin carboxyl-terminal hydrolase isozyme L1 (UCHL1), and some insoluble proteins, including neurofilament heavy polypeptide (NEFH), glial fibrillary acidic protein (GFAP), microtubule-associated protein tau (MAPT) and tubulin β-3 chain (TUBB3), were found to be evenly distributed in the brain. Therefore, we conclude that some insoluble protein biomarkers for stroke are site-specific, and would make excellent candidates for the design and analysis of relevant clinical studies in the future.