To understand the current distribution status of traditional Chinese medicine (TCM) resources in Gangcheng District, Jinan City, Shandong Province, in accordance with the unified requirements of the fourth national survey of TCM resources, the distribution of wild medicinal plant resources, and cultivation of TCM in Gangcheng District were investigated and sorted out through processes including field investigation, internal industry organization, and data analysis. The results showed that there are 180 species of wild resources in Gangcheng District, belonging to 65 families and 151 genera. Among them, the dominant families include Asteraceae, Leguminosae, and Cruciferae, among others. The reserves of wild Phytolacca, Rubia, and Leonurus are relatively large, and 69 species of wild resources are included in the 2020 edition of the Chinese Pharmacopoeia; Cultivar include Salvia miltiorrhiza Bge., Scutellaria baicalensis Georgi, Crataegus pinnatifida Bge., Zanthoxylum bungeanum Maxim., Lonicera japonica Thunb., and Zingiber officinale Roscoe, among which Salvia miltiorrhiza Bge. is a geographical indication resource. This resource survey provides a comprehensive understanding of the types and distribution of wild medicinal plant resources in Gangcheng District, providing a scientific basis for the development and utilization of regional TCM resources and the sustainable development of the TCM industry.

The survey of wild medicinal resources in Weining County, Guizhou Province was conducted using the sample plot and line transect methods, and the diversity and comprehensive value of the resources were analyzed based on the literature. The survey results showed that there are 130 families, 392 genera, and 658 species of wild medicinal plants in Weining County, mainly composed of dominant families such as Compositae, large families such as Polypodiaceae, and medium-sized families such as Pinaceae. It was found that perennial herbaceous plants are the most abundant, with their main medicinal parts being roots and rhizomes, as well as whole grasses. There were 17 families, 21 genera, and 22 species with reserves, including 11 species with high comprehensive value, such as Semiaquilegia adoxoides (DC.) Makino and Tinospora sagittata (Oliv.) Gagnep., indicating that the diversity of wild medicinal plant resources and overall comprehensive value is rich, and the wild medicinal plant resources are mainly cold and flat medicinal materials in Weining County. Targeted development, utilization, and research can be conducted on cold and balanced medicinal plant resources in Weining County, to strengthen the protection of wild medicinal plant resources with high comprehensive value and provide a basis for the sustainable development and utilization of traditional Chinese medicine resources in the county.

Based on the component-antioxidant correlation model, the differences in the content of active components and the antioxidant function of different solvent extracts from artichoke bud were explored. Artichoke bud was extracted with water, 70% methanol, 70% ethanol, and 70% acetone. Total polyphenol and flavonoid contents were compared in the various extracts. The 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) cation scavenging capacity and the total reduction capacity were used to evaluate their antioxidant activity. The correlation between the main active ingredients and antioxidant capacity of different extracts from artichoke bud was comprehensively analyzed. The results showed that the levels of total polyphenols and total flavonoids in 70% ethanol extract were the highest, which were (9.14±0.12) mg/g and (13.46±0.42) mg/g, respectively. The extract with 70% methanol has the strongest antioxidant capacity. The IC₅₀ values of scavenging DPPH and ABTS⁺ were 0.43 mg/mL and 0.10 mg/mL, respectively. Additionally, when the reducing capacity was 0.5, the mass concentration (A_0.5) of the extract was 6.42 mg/mL. The results of correlation analysis showed that the level of total polyphenols and total flavonoids were significantly correlated with the DPPH and ABTS⁺ scavenging capacity (P<0.01). The extract with 70% methanol was rich in polyphenols and flavonoids and possessed the strongest antioxidant capacity, which can provide a certain theoretical basis for further development and utilization of artichoke resources.

The aim of this study was to investigate the active ingredients and mechanism of action of the anti-inflammatory effect of Mahonia bealei (Fort.) Carr. in Hmong medicine based on network pharmacology and animal experiments. Inflammation models of mice and rats were generated using xylene and carrageenan gum, respectively, and Mahonia bealei (Fort.) Carr. was gavaged (dose of 1.950 mg/kg for mice; 1.350 mg/kg for rats). The active ingredients and their corresponding targets of Mahonia bealei (Fort.) Carr. were obtained using TCMSP, SymMap, SwisstargetPrediction, SEA, and STICH, among other databases, with oral bioavailability ≥30% and drug-likeness ≥0.18. Inflammationrelated targets were obtained through GeneCards, DisGeNET, TTD, DrugBank, OMIM and other databases. The intersection targets of diseases and drugs were determined using Venny 2.1.0, and 10 hub gene were obtained through Cytoscape's MCODE, CytoHubba plug-in and constructed drug-component-target network diagram; Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Ontology (GO) enrichment analysis and molecular docking were performed for the 10 Hub gene. The results of animal experiments showed that Mahonia bealei (Fort.) Carr. could be used to reduce the inflammatory symptoms in mice and rats. The network pharmacological analysis revealed 28 Mahonia bealei (Fort.) Carr. active ingredients, 753 drug action targets, 1 025 inflammatory targets, 225 Mahonia bealei (Fort.) Carr. inflammatory crossover targets and 10 hub genes. The results of GO and KEGG enrichment analysis showed that Mahonia bealei (Fort.) Carr. top ten utilities were predominantly involved in the JAK-STAT signaling pathway, Th17 cell differentiation and some cancer pathways. The molecular docking results demonstrated that 11 active ingredients, including berberine and isoboridine, were successfully docked with 8 targets, including JUN and JAK3. The results of animal experiments showed that Mahonia bealei (Fort.) Carr. has anti-inflammatory effects, and the main ingredients of anti-inflammation include quercetin and berberine, among other compounds, and the mechanism of anti-inflammation may be through the action onIL-2, JAK1 and other targets, involved in JAK-STAT signaling pathway, Th17 cell differentiation, and other pathways of anti-inflammation. The present study initially revealed the material basis and mechanism of action of the anti-inflammatory effect of Mahonia bealei (Fort.) Carr.

This study aimed to investigate the protective effects of the Tibetan medicinal compound Feirepuqing Powder on a zebrafish model in a hypoxic environment and its effect on the hypoxia-inducible factor 1α (Hif1α). Through establishing a zebrafish hypoxic injury model, behavioral and overall lactate changes under hypoxic conditions were investigated. Experiments were conducted using AB zebrafish larvae 72 h after fertilization. In the control group, 100% standard dissolved oxygen (8.4 mg/L) was used, while in the hypoxia group, pure nitrogen (N₂) gas replacement was used to obtain 50% dissolved oxygen (4.2 mg/L) culture water, and the embryos were treated with 50% hypoxic water add different concentrations of Feirepuqing Powder for 24 h. The zebrafish behavioral analyzer was used to record the swimming trajectory for 30 min, and the Zeblab software was used to derive the movement distance and time during the 30 min. Following the experiment, all the zebrafish from both the groups were homogenized and the lactic acid and lactate dehydrogenase (LDH) content in their tissue were determined. The changes in the Hif1α expression level of the zebrafish in each group were analyzed via western blot (WB) analysis, and the expression of Hif1α in the caudal fin of each group of fish was compared using immunohistochemistry. The results revealed that compared with the hypoxic control group, 10 to 30 mg/L Feirepuqing Powder group significantly increased the hypoxia-induced exercise distance and exercise time (p<0.05), and relative to the hypoxia-induced lactic acid increase (p<0.001), the lactic acid content of the 30 mg/L Feirepuqing Powder group significantly reduced. When LDH activity was compared with that of the hypoxic group, LDH activity was significantly reduced in the 30 mg/L Feirepuqing Powder group (p<0.05). The WB results revealed that when compared with the hypoxia group, Feirepuqing Powder inhibited the expression of Hif1α (p<0.05). Finally, the immunohistochemical results showed that 10 mg/L of Feirepuqing Powder reduced the expression of Hif1α. The results of this study show that Feirepuqing Powder exhibits a protective effect on induced exercise injuries in an acute zebrafish hypoxic injury model and that its hypoxia-tolerance mechanism is related to the expression of Hif1α.

This study aimed to investigate the effect of copper-induced cell death-related genes on hepatocellular carcinoma (HCC) and to explore active components for treating HCC. The GSE84402 dataset was downloaded from the Gene Expression Omnibus (GEO) database to obtain the differentially expressed genes associated with HCC, and copper-induced cell death-related genes were retrieved from past literature; the commonalities between the two were considered to obtain HCC-related copper-induced cell death genes. The genes in common were further analyzed for differential expression using the UALCAN (University of Alabama at Birmingham Cancer Data Analysis) portal, the correlation between their expression levels and clinical levels was analyzed using the R language, prognostic value was determined using the Kaplan-Meier plotter, their relationship with HCC metastasis was examined using the Human Cancer Metastasis Database (HCMDB), and their pathological relationship with HCC was explored using the Treponema pallidum hemagglutination test. Lastly, compound prediction and molecular docking were performed. The results showed that compared with the normal group, expression levels of the key copper-induced cell death genes SLC31A1 and DBT were downregulated in tumors, and pathological analysis showed that their proteins were increased in HCC tissues. In addition, these genes were significantly correlated with the clinical correlation variables of sex, tumor stage, and lymph node metastasis. Their high expression was correlated with a good HCC prognosis, whereas low expression of SLC31A1 was significantly correlated with the metastasis of HCC to the adrenal glands and lungs. Finally, the active compounds that may bind to SLC31A1 and DBT were screened, of which resveratrol and folic acid exhibited high docking scores. Hence, it could be concluded that copper-induced cell death-related genes SLC31A1 and DBT play an important role in the development of HCC, and this study provides new theories for the diagnosis of HCC and therapeutic drug research.

In this paper, the preparation process of N-propylethylenediamine bonded silica gel (PSA) with controllable bonding amount was optimized; the batch repeatability of PSA preparation was examined; and the pilot scale-up experiment of PSA preparation was conducted. The properties of the PSA were investigated by infrared spectroscopy, elemental analysis, and potentiometric titration. The results showed that N—H stretching vibration peaks appeared at 3 460 cm^-1, asymmetric and symmetric stretching vibration peaks of —CH appeared at 2 960 cm^-1 and 2 860 cm^-1, and deformation vibration absorption peaks of —NH₂ appeared at 708 cm^-1, indicating that N-propylethylenediamine was successfully grafted onto the surface of silica gel.Furthermore, with the increasing proportion of silane reagent in the preparation system, the content of carbon, nitrogen, and hydrogen elements and the ion exchange capacity obtained by potentiometric titration showed an upward trend, indicating that the bonding amount of ethylenediamine-N-propyl functional group gradually increased. Moreover, the prepared PSA packing component was separated from the purification column, and the removal efficiency of ginkgolic acid from the extract of ginkgo biloba leaves using PSA with different bonding amounts was investigated. The results showed that PSA had a strong adsorption capacity for ginkgolic acid and could be used to remove ginkgolic acid from the extract of ginkgo biloba leaves, the maximum sample loading volumes for PSA separation and purification columns 2^#, 3^#, 4^#, and 5^# are 21, 22, 23, 24 mL, respectively. In addition, the removal efficiency was found to increase with the increasing amount of ethylenediamine-N-propyl bonding.

Polyvinyl chloride (PVC) foam board is prepared by extrusion foaming of PVC with low polymerization degree, and the PVC foam board is prone to curling movement along the force direction of the molecular chain due to environmental changes, resulting in shrinkage and deformation of the board. Heavy calcium carbonate (HCC) was used as raw material, polyvinyl alcohol (PVA) and tannic acid (TA) were used as modifiers to prepare modified HCC. It was combined with PVC to prepare PVC foam sheets. Infrared spectrometer, differential scanning calorimeter, scanning electron microscope, Vicat softening point tester and universal electronic stretching machine were used to characterize the foamed board, and the effect of modifier dosage on the dimensional stability of the foamed board was discussed. The results show that when the TA content is 3% of HCC, the glass transition temperature of PVC foam board is 88.1 ℃, the temperature of Vicat softening point is 75.21 ℃, and the PVC foam board has excellent dimensional stability, and the cell structure is stable and uniform, and has the best tensile strength of 6.17 MPa. Modified HCC particles have good dispersion, strong binding ability with PVC, and high dimensional stability of PVC foam board can replace the use of wood in home decoration boards, which is of great significance to protect the environment.

Silica (mainly comprising nano-SiO₂) is widely used in rubber reinforcement owing to its advantages of easy preparation and environmental protection. However, owing to its structural characteristics, silica has poorer dispersion and reinforcement ability than carbon black. The purpose of this paper is to present a proposal to improve the dispersion of silica in rubber using a silane coupling agent and to study the effect of synergistic reinforcement of modified silica and graphene on natural rubber. The hybrid filler KS-TGE was obtained through a Michael addition reaction between graphene modified by dispersant tannic acid and silica (KS) modified by the silane coupling agent KH570. Subsequently, the KS-TGE/NR composites were prepared by mixing KS-TGE with natural rubber. Test results showed that the modified silica improves the dispersion in rubber and the mechanical properties of natural rubber after blending with the hybrid filler prepared using graphene and natural rubber. Compared with unmodified nano-SiO₂/NR, the tensile strength of the modified composites increased by 36.3% and the elongation at break increased by 79.5%. In addition, KS-TGE/NR can maintain excellent elastic and dynamic mechanical properties.

A lightweight and cooling woven fabric for summer was developed by selecting and combining different cooling fibers. Twelve samples were produced by selecting polyester/mint blended yarn as warp yarn, nylon fiber as weft yarn and plain, and twill and satin as fabric weave to investigate the impact of different weft yarns and fabric structures on the thermal and moisture comfort properties of the fabrics. The results showed that twill and satin fabrics had better thermal and moisture transfer performance; plain weave fabrics provided a good cooling sensation upon contact; cool nylon indeed enhanced the cooling of the fabric, but it showed poor moisture transfer performance in tightly woven structures. Micro-denier nylon had similar thermal and moisture transfer performance to cool-feel nylon but had lower air permeability and cross-sectional nylon had better moisture transfer performance but lower thermal conductivity.

To address the challenges related to distance measurement of an approaching vehicle in fog,we developed an experimental platform to rapid image processing and real-time distance measurement.Firstly,we down-sampled the images through the dark channel algorithm to estimate atmospheric light values. Then, we introduced a tolerance mechanism to deal with the bright regions that do not satisfy the dark channel prior. This tolerance mechanism corrected the estimate with incorrect refractive index of such regions and effectively mitigated the issues of color distortion and low contrast. Secondly, we detected the vertical edges of an approaching vehicle using the edge detection and the improved Hough transform algorithms. Finally, we measured the safe distance from the approaching vehicle using the model. The results shows that the platform developed in this study can effectively measure the distance of the approaching vehiclein fog with a visibility <100 m, and can alert drivers in a timely and effective manner.

An accurate prediction of short-term subway passenger flowscan effectively alleviate traffic congestion and improve the quality of travel services for urban residents. Herein, we propose a multitask learning-based model for the prediction of short-term subway passenger flows, which uses a residual convolutional neural network (NN) and a nested long short-term memory NN to extract the spatio-temporal correlation of traffic patterns, and introduces an attention mechanism to enhance the feature extraction performance of the NNs. Considering the characteristics of subway operations, the model selects train operation features, bus stops around subway stations, and point of interest data as external features to improve the accuracy of the prediction. Based on the historical data of the Beijing Subway, experiments were conducted in multiple time granularity scenarios, such as 10, 30, and 60 min. The results showed that the methodsuccessfully modeled and analyzed the inflow-outflow interaction through multitask learning, improved the prediction performance and generalization ability of the model, and providednovel approaches for the prediction of short-term subway passenger flows.

To study the traffic flow characteristics, the traffic data is analyzed using a complex network method. A box plot-clustering algorithm model is proposed to identify and fill in missing values and outliers in the initial data. The one-dimensional data is reconstructed into network nodes using the phase space reconstruction method. Additionally, the connection threshold is selected to determine the connection relationship of network nodes to convert the traffic sequence data as a complex network and analyze the structure and quantitative indicators of the network. The result shows that the structure of the complex network of traffic data can reflect the traffic flow state of the road section to a certain extent. The research optimizes the data preprocessing method and extends the application of complex networks into traffic data research.

To meet the needs of passengers for connection and evacuation at high-speed rail stations and enhance the role of high-speed rail stations as urban comprehensive transportation hubs, a dynamic route planning model of a high-speed rail feeder bus is established based on mixed demand that includes reservation and real-time demands. Based on the reservation demand, considering the operation cost of a bus company as well as the travel time cost, the route planning model is established before the start of operation. An improved genetic algorithm was designed using niche methods to solve the problem. After the start of operation, real-time demand can be inserted into the established vehicle route with temporary stations. To realize a dynamic route planning scheme, an integer planning model is established to minimize the variable cost of the system. Using the proposed method,30 demand groups were randomly generated and solved in the Beitaipingzhuang street area, Beijing. Results show that the model can generate an optimal dynamic route planning scheme for a high-speed rail feeder bus in two periods to satisfy the mixed demand. Compared with traditional genetic algorithm, niche genetic algorithm can effectively avoid premature and obtain better results, thus confirming the feasibility of the proposed model and the niche genetic algorithm.

This study analyzed the climate change characteristics and causes of foggy days in Qingdao and Jinan using meteorological observation data from 1961 to 2020 in Qingdao and Jinan, as well as sea surface temperature data near Qingdao. Results showed that the average annual foggy days in Qingdao were 50.4 d, 3.1 times more than that in Jinan. The peak fog seasons were substantially different in the two cities; Qingdao experiences more foggy days in spring and summer, accounting for about 78.4% of the whole year, whereas Jinan experiences more foggy days in autumn and winter, accounting for about 70.7% of the whole year. Furthermore, remarkable differences in the annual and seasonal variations of foggy days were observed. Qingdao shows an increasing trend in annual foggy days, i.e., less foggy days in spring and summer, but significantly more in autumn and winter. Alternatively, Jinan exhibits a decreasing trend in annual foggy days, where the number of foggy days is lowest in autumn. Moreover, considerable climate variability and abrupt change in the number of annual foggy days between the two cities were noticed. The climate variability of Qingdao showed an increasing trend and remained at a high level, while Jinan witnessed a decreasing trend; this indicates a higher probability of extreme foggy weather in Qingdao than in Jinan. Qingdao witnessed an increase in the number of foggy days in 1969, while Jinan encountered a decrease in 1995. The increase in the number of foggy days in Qingdao during autumn and winter was closely related to the substantial increase in the sea surface temperature near the city. This increase promoted sea surface evaporation and subsequently increased the atmospheric water vapor content. However, the decrease in foggy days in Jinan during autumn and winter was closely associated with a substantial increase in the minimum temperature and the dew point temperature difference as well as reduced humidity.

Real-time, accurate and reliable monitoring of marine environmental information plays a crucial role in marine disaster warning and prediction, disaster prevention and reduction, marine resource development, and ensuring marine safety. In recent years, with the continuous development and upgrading of global navigation satellite systems (GNSS), the detection of atmospheric and marine environmental information based on GNSS navigation signals has become a new method and a hot research topic in the marine environmental monitoring technology. This method has been widely applied to domains such as marine meteorological monitoring and numerical forecasting. This article systematically reviews the current research status of the GNSS technology in marine environmental monitoring, including effective wave height, wind speed, rainfall intensity, water vapor and tide level monitoring. Furthermore, this paper systematically summarizes new technologies and methods and looks forward to provide reference for the future research in related fields.

Hyperuricemia (HUA) is a metabolic disorder caused by the physiologic disorders in purine metabolism, resulting in increased serum uric acid levels, which can lead to gout in severe cases. HUA pathogenesis primarily involves enzyme dysfunction, urate transporter expression dysregulation, glucose and lipid metabolism disorders, and intestinal homeostasis disruption. Numerous studies have reported the effectiveness of natural polyphenols in alleviating hyperuricemia and gout. This article summarizes HUA pathogenesis and the mechanisms of action of polyphenolic compounds in reducing uric acid, to provide a theoretical basis for the research and development of uric acid-lowering drugs.

Ulcerative colitis (UC) is an inflammatory bowel disease characterized by persistent mucosal inflammation.Scutellaria baicalensis (also known as Huangqin), as a common traditional Chinese medicines used in clinical practice, is known for its efficacy at clearing internal heat,eliminating dampness, purging fire,eliminating toxins, stopping bleeding, and calming fetal activity. Its formulations, including Huangqin Decoction, Peony Decoction, and Pueraria, Scutellaria, and Coptis Decoction, are often used to treat damp-heat UC. Studies have shown that S. baicalensis and its active ingredients play an important role in protecting the intestinal mucosa, and have anti-inflammatory and immunomodulatory effects. This study reviews the mechanism of action of S. baicalensisand its active ingredients (baicalin,baicalein,oroxindin, wogonin, Scutellaria baicalensis polysaccharide, etc.) in the treatment of UC in recent years, including the protection and repair of the intestinal mucosal barrier, the active ingredients anti-inflammatory and immunomodulatory properties, effects against antioxidative stress, and regulation of intestinal flora, to provide a reference for targeted clinical treatment of UC and drug development.

Network pharmacology, which is highly consistent with the holistic and systematic perspectives of traditional Chinese medicine (TCM) with its multiple components and targets, has rapidly developed in the modernization of TCM. Experimental verification is one of the key contents of network pharmacology research. The zebrafish model has a complete system of drug metabolism, as well as a complex in vivo environment and target and pathway regulation mechanisms. Experiments that utilize this model have the advantages of low drug dosage, high throughput, and short cycle time. In recent years, the research mode that combines network pharmacology prediction with experimental validation using the zebrafish model has been widely applied to elucidate the effective substances and mechanisms of action of TCM. This study reviews the progress and development trends in the comprehensive application of network pharmacology and zebrafish modeling, aiming to provide a reference for their application in elucidating the modern scientific implications of the efficacy of TCM.

Zebrafish models have been widely used in various fields such as drug screening, pharmacology, and toxicology research. In recent years, with the implementation of regulations such as the standard for the Evaluation of Cosmetic Efficacy Claims, cosmetic efficacy claims have entered into an era of strict supervision, which has led to higher standards for the scientific nature of the efficacy evaluation models and methods. The skin structure of zebrafish is highly similar to that of humans, with zebrafish also having transparent embryos that are easy to observe. Moreover, efficacy evaluation experiments using zebrafish offer advantages such as minimal sample dosage, shortened experimental cycles, and high-throughput capacity. Consequently, zebrafish have become a popular research topic in the field of cosmetic efficacy evaluation. Based on bibliometric methods, this study analyzes the relevant literature on the use of zebrafish to evaluate cosmetic efficacy over the past decade. The study provides an overview of the progress of the application of zebrafish in cosmetic efficacy evaluation, and examines the development dynamics and trends through comprehensive analysis. This is so as to provide a reference for the application of zebrafish models in the cosmetics industry.

Along with the long preparation cycle time and high cost of conventional preparation methods, the inherent high thermal conductivity of TiCoSb Half-Heusler alloy limited its commercial application. Herein, Ti_1-xNb_xCoSb Half-Heusler alloys with low thermal conductivity were successfully prepared by microwave synthesis combined with rapid hot-pressing sintering, which substantially shortened the preparation cycle and increased the density of TiCoSb Half-Heusler alloys. Furthermore, we studied the effects of Nb substitution at Ti sites on the phase composition, composition distribution, and thermoelectric transport properties of Ti_1-xNb_x CoSb Half-Heusler thermoelectric materials. Additionally, the figure of merit(ZT) of Ti_1-xNb_x CoSb samples were considerably optimized under the combined effects of increasing power factor and decreasing lattice thermal conductivity. The results showed that the Ti_0.93Nb_0.07CoSb sample had a maximum ZT of 0.1 at 725 K, which was two orders of magnitude higher than that of the TiCoSb sample prepared by the same process.

In this paper, graphene prepared by liquid-phase stripping assisted by tannic acid achieved better dispersion than ordinary graphene. The new graphene can meet the requirements of low cost, high output, and environmental protection. Graphene-SiO₂ hybrid materials were obtained by reacting SiO₂ treated with silane coupling agent (KH550) modification and graphene modified with tannic acid to form strong hybridization bonds, and the success of obtaining graphene-SiO₂ hybrid materials was confirmed by infrared spectroscopy. Furthermore, the mechanical properties of graphene-SiO₂ hybrid material in styrene-butadiene/polybutadiene composites were studied. In addition, the mechanical properties and the electrical and thermal conductivity of the blend of conductive carbon black and graphene-SiO₂ hybrid material in styrene-butadiene/polybutadiene composite were investigated. The results show that: at the addition of 1 part per hundred(phr) of graphene-SiO₂ hybrid material, the butadiene/cis rubber composites obtained relatively good wear resistance, if the loading is more than 1 phr, the graphene fillers will easily reaggregate with each other, resulting in an increase in wear volume compared with the blank control group. Moreover, when 8 phrs of self-made graphene were added, the conductivity increased by 1 000 times, and the antistatic properties of rubber composites were considerably improved.

The most critical step in a line-structured light three-dimensional scan modeling system is to extract the centerline of the light stripe, but the interference of various environmental factors makes this extraction difficult. Several problems exists in a line-structured light streak image issues such as light spot interference, uneven distribution of light intensity, large differences in the width of the light bars, and complex background. This paper proposed a solution to overcome these problems. First, the structured light image is binarized using the Otsu method. Then, the improved density-based spatial clustering of applications with nose (DBSCAN) algorithm is used to retain the core points and remove the boundary and noise points. Finally, the core points are used as inputs to construct the graph data structure, and the shortest path search algorithm that fits the line-structured light streak image is used to obtain the center-line of the light streak. The experimental results show that the algorithm of this paper runs within 150 ms and the error is within 0.2 pixels. Moreover, this algorithm is applicable to various complex environments, meeting the requirements of real-time calculations, accuracy, and stability.

With the development of science and technology, the systematization, networking and intelligentization of the social technology system gradually deepen, forming the complexity of the system. The failures of these complex systems, such as traffic jams, rumor spreading, and financial collapse, can be regarded as a kind of "1+1<2" negative emergence of system capability, which is difficult to understand directly through the reduction analysis of system components. It challenges the classical reliability theory. Research on the complex systems reliability mainly focuses on failures laws, which includes two perspectives. One is the study of system vulnerability considering failure propagation. The other is the study of system adaptability considering failure recovery. System vulnerability studies focus on exploring the internal mechanism of system collapse, namely the failure propagation mechanism. System adaptability studies focus on the capacity to adapt and recover, including the system failure recovery mechanism. Based on this, the article introduces relevant research on reliability method.

With the development of network science and the emergence of complex systems theory, scholars have embarked on in-depth research on the structural and dynamic properties of complex networks. Among the dynamic properties of complex networks, cascading failures, as one of the most important research areas, describe a situation where a fault or error in a system or process leads to the failures of other related components or links. Various models and recovery strategies have been proposed for cascading failures in complex networks. This study analyzes the mechanisms of cascading failures, provides a comprehensive summary on the development of domestic and international cascading failure in complex networks, outlines the recovery strategies for addressing cascading failures, and highlights the existing issues and shortcomings in current research, providing valuable insights for future studies.

A functional relationship was constructed between the probability of inhaling viruses and social distance to characterize the viral transmission of subway passengers at the microscopic level. Formulas for calculating the increase and decrease of viral load were constructed based on establishing the viral load evolution equation. Normalized parameters were used within this equation to describe the effect of pandemic prevention measures. The viral load of each passenger was programmed through the Anylogic software’s secondary development interface to characterize the viral load change at the pre- and post-infection phases. In the initial simulation settings, 10% of the passengers were infected with the virus, including ordinary carriers and supercarriers. The evolution of the virus under different passenger number conditions within subway carriages was simulated, which was categorized into with-control and without-control scenarios. The simulation results showed the following: as the number of passengers increases, the passenger density increases, the virus transmission increases, and the individual viral load increases rapidly. Isolating passengers with a viral load greater than a threshold of 1 000 and prohibiting them from taking the subway can reduce the viral load of all passengers by an order of magnitude.

Frequent delays of flights at large international airports can affect their smooth operation, hence, the airport apron allocation problem needs to be robustly optimized. In this study, we proposed two integer linear-programing models for solving this problem and used two algorithms for performance comparison: the hill-climbing and large-neighborhood search (LNS) metaheuristic algorithms. In addition, we used the Monte Carlo method to evaluate the effectiveness of different objective functions in dealing with flight conflicts. The final test results show that the LNS algorithm not only improves the robustness of the gate allocation scheme for large airports but also excels in speed and quality, especially, when the square of idle time is used as the objective function.

Nitrogen fertilizers provide the nitrogen necessary for crop growth in modern agricultural production, but their excessive use in the long term leads to waste of resources, economic losses and profound negative environmental impacts. Microorganisms play a critical role in the nitrogen cycle; therefore, there is a significant need for further research in this field. Here, we summarize our findings on the mechanisms and processes by which microorganisms drive the soil nitrogen cycle, including nitrogen fixation, nitrification, denitrification, ammonification, and nitrogen assimilation/dissimilation. We further summarize microbial technologies and strategies for mitigating agricultural nitrogen loss and improving agricultural sustainability, such as nitrogen fixation, greenhouse gas emission reduction, nitrogen bioretention, and ammonia volatilization. These strategies illustrate the potential of microorganisms in reducing the dependence on nitrogen fertilizers and increasing crop yields, while also highlighting the challenges of research and effective field application of these technologies.

In this study, the hot water extraction method was utilized to extract polysaccharides from persimmon peel, and the persimmon peel polysaccharides were combined with trivalent chromium ions to prepare persimmon peel polysaccharide chromium. Considering the adsorption rate of chromium as the index, the adsorption process of persimmon peel polysaccharide chromium was optimized using single factor and response surface methodology. The results showed that the optimal preparation process of persimmon peel polysaccharide chromium consisted of the following steps, such as the mass ratio of persimmon peel polysaccharides to chromium chloride was set at 6.7∶1; the reaction time was 150 min; the temperature was set at 82 ℃; and the pH of the adsorption liquid was fixed at 5. Under these conditions, the maximum adsorption rate reached 92.81%. Therefore, this study has shown that persimmon peel polysaccharides can efficiently bind trivalent chromium ions, which can further provide technical support for the development of green pollution-free heavy-adsorption chromium adsorbents or animal nutritional supplements.