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Background: Influenza vaccination is essential for type 2 diabetes mellitus (T2DM) patients due to their higher risks of severe complications and mortality from influenza. This study investigated the willingness of T2DM patients in Chongqing, China, to receive the influenza vaccination during the 2023/2024 season, using behavioral and social drivers (BeSD) tools to improve vaccination uptake in this high-risk group. Methods: A multi-stage sampling method was used to select participants, and face-to-face surveys were conducted in community health centers between March 1 and May 1, 2023. Binary logistic regression was used to analyze the factors influencing vaccination willingness, and standardized scores identified barriers and drivers. Results: Among 1672 T2DM patients, 11.7% had been vaccinated during the 2022/2023 season, and 59.6% were willing to receive the vaccination in the 2023/2024 season. Higher willingness was associated with ethnic minorities (odds ratio [OR], 3.18, 95% confidence interval [CI]: 1.58–6.39), being unemployed individuals (OR 2.69, 95% CI: 1.60–4.52), higher monthly household income per capita (OR 2.72, 95% CI: 1.65–4.50), having diabetes complications (OR 1.76, 95% CI: 1.23–2.51), sufficient vaccine knowledge (OR 1.87, 95% CI: 1.48–2.37), and previous vaccination (OR 7.75, 95% CI: 4.83–12.44). Concerning BeSDs, fear of infecting friends or family members and trust in vaccine efficacy were the predominant drivers, while high vaccine costs were the greatest barrier. Conclusions: Future strategies should focus on improving vaccine knowledge, supporting healthcare workers and peer recommendations, and enhancing vaccination policies. Key interventions such as health education among high-risk groups, such as unemployed individuals, advocacy campaigns, pay-it-forward strategies, and policies for free vaccination could improve coverage in Chongqing.

A field experiment with double cropping rice was carried out to study the foliar application effects of dicarboxylicdimethylammonium chloride (DDAC) on cadmium (Cd) and arsenic (As) accumulation in rice grains. The results showed that the spraying of DDAC could significantly reduce the accumulation of Cd and As in rice grains. The highest reductions in Cd and As content were observed when 1.5 mmol L−1 DDAC was sprayed, with 49.1% and 27.4% reductions in Cd and As content in early rice grains and 56.5% and 28.1% reductions in Cd and As content in late rice grains, respectively. In addition, the content of calcium (Ca) in rice grains increased significantly after DDAC foliar application, which was also conducive to the synthesis of amino acids such as glutamate (Glu), glycine (Gly) and cysteine (Cys) in rice grains. The results indicated that the foliar spraying of DDAC can inhibit the absorption, transport, accumulation and toxicity of Cd and As in rice grains by increasing amino acid synthesis and regulating the absorption and transport of essential elements.

Background: Unhealthy lifestyles among adolescents are reaching alarming levels and have become a major public health problem. This study aimed to assess the relationship between sleep time, physical activity (PA) time, screen time (ST), and nutritional literacy (NL). Methods: This cross-sectional online study involving adolescents aged 10–18 years was conducted in September 2020 in 239 schools in Chongqing, China. NL was measured using the “Nutrition Literacy Scale for middle school students in Chongqing (CM-NLS)”. According to the recommended by the Chinese dietary guidelines (2022), we divided the sleep time of junior high school students into Results: A total of 18,660 adolescents (50.2% males) were included. The proportion of participants that were junior high school students and attended boarding schools was 57.2% and 65.3%, respectively. Compared with senior high school students, junior high school students had a higher level of NL. Whether on workdays or weekends, participants with sleep time ≥ 8/9 h, PA time ≥ 1 h, and ST < 2 h per day had higher levels of NL. On weekdays, participants who met the sleep time ≥ 8 h/9 h (OR = 1.48, 95% CI: 1.36, 1.62) and PA time ≥ 1 h (OR = 1.69, 95% CI: 1.59, 1.81) had higher reporting of NL levels. Conclusions: Sleep time, PA time, and ST were positively correlated with NL among adolescents, especially junior high school students.

Objective This study aimed to investigate the current status and influencing factors of healthy diet knowledge, attitude, and practice (KAP) among middle-aged and older adults aged 45–75 in Southwest China. Methods A questionnaire survey was conducted among 1822 middle-aged and older adults in Southwest China (including Guizhou, Sichuan, Yunnan, and Chongqing) from February to May 2021. Results The average score of healthy diet knowledge was (4.82 ± 2.98), with a passing rate of 7.6%. The mean score of healthy diet attitude was (21.26 ± 4.18), with a passing rate of 69.5%. The average score of healthy diet practice was (13.76 ± 2.84), with a passing rate of 55.5%. The score for healthy diet KAP was (39.85 ± 7.21), with a passing rate of 41.2%. Univariate analysis showed that the scores of healthy diet KAP were significantly different among participants of different ages, genders, ethnicities, residences, education levels, monthly household incomes, and regions, as well as varying according to whether several generations have lived in the same area (p < 0.05). The results of multiple linear regression showed that the healthy diet KAP of participants was influenced by age, gender, residence, education level, monthly household income, and region (p < 0.05). Conclusion The healthy diet KAP of middle-aged and older adults aged 45–75 in Southwest China shows room for improvement. The knowledge regarding healthy diet was relatively low, and certain specific healthy diet practices were not up to the standard. However, there was a positive trend in the attitude towards a healthy diet. Healthy diet education should be promoted for middle-aged and older adults.

The goal of the current study was to explore the potential benefits of Tretinoin (Tre) fatty acid vesicles (Tre-FAV) as a prospective antipsoriatic topical delivery system. This promising system can counteract the drug challenges in terms of its extremely low aqueous solubility, instability, skin irritation, and serious systemic adverse effects. Tre-loaded fatty acid vesicles were successfully developed and entirely characterised. The selected formulation was investigated for in vitro release, ex vivo skin retention and psoriasis efficacy studies. The characterisation results of Tre-FAV showed it has a globular shape with a particle size of 126.37 ± 1.290 nm (0.188 ± 0.019 PDI). The entrapment efficiency and zeta potential were discovered to be 84.26 ± 0.816% and −28.9 ± 1.92 mV, respectively. Encapsulation of the drug in the fatty acid vesicles was also strengthened by differential scanning calorimetric and powder FTIR diffraction studies. In vitro release results showed that Tre-FAV significantly increased skin absorption and retention in comparison to the Tre solution. The topical application of Tre-FAV to a mouse model confirmed that it has superior in vivo antipsoriatic properties in terms of well-demarcated papules, erythema and reduced epidermal thickness in comparison to other treatments. The weight of the spleen and the levels of the cytokines IL-17 and IL-6 decreased after treatment. In conclusion, FAV dramatically increased the water solubility and skin permeability of Tre and its anti-psoriasis activity.

Depression is one of the most common psychological problems in adolescence. Familial and school-related factors are closely related to adolescents’ depression, but their combined effects need further examination. The purpose of this study was to explore the combined effects of risk/protective factors of depression in family and school domains using a sample of Chinese adolescents differing in gender, age group and left-behind status. A total of 2455 Chinese students in primary and secondary school participated in the cross-sectional survey and reported multiple risk/protective factors in family and school environments and depressive symptoms. Association rule mining, a machine learning method, was used in the data analyses to identify the correlation between risk/protective factor combinations and depression. We found that (1) Family cohesion, family conflict, peer support, and teacher support emerged as the strongest factors associated with adolescent depression; (2) The combination of these aforementioned factors further strengthened their association with depression; (3) Female gender, middle school students, and family socioeconomic disadvantages attenuated the protective effects of positive relational factors while exacerbating the deleterious effects of negative relational factors; (4) For individuals at risk, lack of mental health education resources at school intensified the negative impact; (5) The risk and protective factors of depression varied according to gender, age stage and left-behind status. In conclusion, the findings shed light on the identification of high-risk adolescents for depression and underscore the importance of tailored programs targeting specific subgroups based on gender, age, or left-behind status.

The rapid spread of capitalism in rural areas has facilitated rural land commodification (RLC). While some scholars have studied RLC, few have analyzed its spatial characteristics. Taking Shijiazhuang city as a study area, this paper applies Moran’s I method and spatial regression models to analyze township-scale RLC patterns and driving factors. The study investigates four common pathways of RLC: production-oriented farmland, tourism-oriented farmland, rural homesteads, and construction land commodification which are predominantly found in urban fringe areas. The distribution of RLC demonstrates positive spatial autocorrelation, characterized by spatial aggregation and polarization. Population, economic level, agriculture, and location conditions are identified as key drivers, and their specific mechanisms vary across development pathways. Future efforts should focus on ensuring balanced and coordinated RLC development in accordance with regional conditions and capacity, while also addressing the implications arising from the coexistence of RLC with rural aging and poverty.

OTUD5 (OTU Deubiquitinase 5) is a functional cysteine protease with deubiquitinase activity and is a member of the ovarian tumor protease (OTU) family. OTUD5 is involved in the deubiquitination of many key proteins in various cellular signaling pathways and plays an important role in maintaining normal human development and physiological functions. Its dysfunction can affect physiological processes, such as immunity and DNA damage repair, and it can even lead to tumors, inflammatory diseases and genetic disorders. Therefore, the regulation of OTUD5 activity and expression has become a hot topic of research. A comprehensive understanding of the regulatory mechanisms of OTUD5 and its use as a therapeutic target for diseases is of great value. Herein, we review the physiological processes and molecular mechanisms of OTUD5 regulation, outline the specific regulatory processes of OTUD5 activity and expression, and link OTUD5 to diseases from the perspective of studies on signaling pathways, molecular interactions, DNA damage repair and immune regulation, thus providing a theoretical basis for future studies.

Perovskites with nano-flexible texture structures and excellent catalytic properties have attracted considerable attention for persulfate activation in addressing the organic pollutants in water. In this study, highly crystalline nano-sized LaFeO3 was synthesized by a non-aqueous benzyl alcohol (BA) route. Under optimal conditions, an 83.9% tetracycline (TC) degradation and 54.3% mineralization were achieved at 120 min by using a coupled persulfate/photocatalytic process. Especially compared to LaFeO3-CA (synthesized by a citric acid complexation route), the pseudo-first-order reaction rate constant increased by 1.8 times. We attribute this good degradation performance to the highly specific surface area and small crystallite size of the obtained materials. In this study, we also investigated the effects of some key reaction parameters. Then, the catalyst stability and toxicity tests were also discussed. The surface sulfate radicals were identified as the major reactive species during the oxidation process. This study provided a new insight into nano-constructing a novel perovskite catalyst for the removal of tetracycline in water.

As a member of the TRIM (tripartite motif) protein family, TRIM56 can function as an E3 ubiquitin ligase. In addition, TRIM56 has been shown to possess deubiquitinase activity and the ability to bind RNA. This adds to the complexity of the regulatory mechanism of TRIM56. TRIM56 was initially found to be able to regulate the innate immune response. In recent years, its role in direct antiviral and tumor development has also attracted the interest of researchers, but there is no systematic review on TRIM56. Here, we first summarize the structural features and expression of TRIM56. Then, we review the functions of TRIM56 in TLR and cGAS-STING pathways of innate immune response, the mechanisms and structural specificity of TRIM56 against different types of viruses, and the dual roles of TRIM56 in tumorigenesis. Finally, we discuss the future research directions regarding TRIM56.

OTU domain-containing protein 3 (OTUD3) knockout mice exhibited loss of nigral dopaminergic neurons and Parkinsonian symptoms. However, the underlying mechanisms are largely unknown. In this study, we observed that the inositol-requiring enzyme 1α (IRE1α)-induced endoplasmic reticulum (ER) stress was involved in this process. We found that the ER thickness and the expression of protein disulphide isomerase (PDI) were increased, and the apoptosis level was elevated in the dopaminergic neurons of OTUD3 knockout mice. These phenomena were ameliorated by ER stress inhibitor tauroursodeoxycholic acid (TUDCA) treatment. The ratio of p-IRE1α/IRE1α, and the expression of X-box binding protein 1-spliced (XBP1s) were remarkably increased after OTUD3 knockdown, which was inhibited by IRE1α inhibitor STF-083010 treatment. Moreover, OTUD3 regulated the ubiquitination level of Fortilin through binding with the OTU domain. OTUD3 knockdown resulted in a decrease in the interaction ability of IRE1α with Fortilin and finally enhanced the activity of IRE1α. Taken together, we revealed that OTUD3 knockout-induced injury of dopaminergic neurons might be caused by activating IRE1α signaling in ER stress. These findings demonstrated that OTUD3 played a critical role in dopaminergic neuron neurodegeneration, which provided new evidence for the multiple and tissue-dependent functions of OTUD3.

Entity and relation linking are the core tasks in knowledge base question answering (KBQA). They connect natural language questions with triples in the knowledge base. In most studies, researchers perform these two tasks independently, which ignores the interplay between the entity and relation linking. To address the above problems, some researchers have proposed a framework for joint entity and relation linking based on feature joint and multi-attention. In this paper, based on their method, we offer a candidate set generation expansion model to improve the coverage of correct candidate words and to ensure that the correct disambiguation objects exist in the candidate list as much as possible. Our framework first uses the initial relation candidate set to obtain the entity nodes in the knowledge graph related to this relation. Second, the filtering rule filters out the less-relevant entity candidates to obtain the expanded entity candidate set. Third, the relation nodes directly connected to the nodes in the expanded entity candidate set are added to the initial relation candidate set. Finally, a ranking algorithm filters out the less-relevant relation candidates to obtain the expanded relation candidate set. An empirical study shows that this model improves the recall and correctness of the entity and relation linking for KBQA. The candidate set expansion method based on entity–relation interaction proposed in this paper is highly portable and scalable. The method in this paper considers the connections between question subgraphs in knowledge graphs and provides new ideas for the candidate set expansion.

A novel virus named SARS-CoV-2 has caused a worldwide pandemic, resulting in a disastrous impact to the public health since 2019. The disease is much more lethal among patients with malignant disease. Vaccination plays an important role in the prevention of infection and subsequent severe COVID-19. However, the efficacy and safety of vaccines for cancer patients needs further investigation. Encouragingly, there have been important findings deduced from research so far. In this review, an overview of the immunogenicity, effectiveness, and safeness of COVID-19 vaccines in patients with cancer to date is to be shown. We also highlight important questions to consider and directions that could be followed in future research.

To explore the effect of exogenous application of chlorinated amino acetic acid on cadmium (Cd) transport characteristics in rice seedlings, X24 and Z35 rice were taken as the research objects to carry out hydroponics experiments, and the changes of Cd content in rice seedlings, rice mineral elements and amino acid content in rice were analyzed. The results showed that exogenous application of 1.2 mmol·L−1 chlorinated amino acetic acid inhibited cadmium in shoots and roots of rice seedlings; Cd content in shoots and roots were reduced by up to 62.19% and 45.61%, respectively. The majority of cadmium was in the cell wall of shoots and roots; this decreased with the increase of the concentration of chlorinated acetic acid. In addition, the Mn content in shoots and Ca content in roots of rice seedlings increased significantly after the application of chlorinated amino acetic acid. The results of amino acid analysis showed that the contents of aspartic acid, glutamic acid and cystine in rice seedlings were increased. These results indicate that exogenous application of chlorinated amino acetic acid is beneficial to the synthesis of aspartic acid, glutamic acid and cysteine in rice seedlings, increases the content of Mn in shoots and Ca in roots of rice seedlings, and significantly alleviates cadmium stress in seedlings. This provides a theoretical basis for the development of an environmentally friendly Cd-lowering foliar fertilizer for rice.

Compared with traditional manual inspection, inspection robots can not only meet the all-weather, real-time, and accurate inspection needs of substation inspection, they also reduce the work intensity of operation and maintenance personnel and decrease the probability of safety accidents. For the urgent demand of substation inspection robot intelligence enhancement, an environment understanding algorithm is proposed in this paper, which is an improved DeepLab V3+ neural network. The improved neural network replaces the original dilate rate combination in the ASPP (atrous spatial pyramid pooling) module with a new dilate rate combination with better segmentation accuracy of object edges and adds a CBAM (convolutional block attention module) in the two up-samplings, respectively. In order to be transplanted to the embedded platform with limited computing resources, the improved neural network is compressed. Multiple sets of comparative experiments on the standard dataset PASCAL VOC 2012 and the substation dataset have been made. Experimental results show that, compared with the DeepLab V3+, the improved DeepLab V3+ has a mean intersection-over-union (mIoU) of eight categories of 57.65% on the substation dataset, with an improvement of 6.39%, and the model size of 13.9 M, with a decrease of 147.1 M.

The rapid acquisition of deposit volume information and dynamic modeling, as well as the visualization of disaster scenes, have great significance for the sharing of landslide information and the management of emergency rescue. However, existing methods have shortcomings, such as a long and costly deposit volume acquisition cycle, lack of knowledge and guidance, complex operations for scene modeling expression, and low scene rendering efficiency. Therefore, this paper focuses on the study of a three-dimensional visualization and optimization method for landslide disaster scenes guided by knowledge, and discusses key technologies such as the rapid acquisition of landslide deposit volume information based on three-dimensional reconstruction, the knowledge-guided dynamic modeling visualization of disaster scenes, and scene optimization considering visual significance. The prototype systems are developed and used in a case experiment and analysis. The experimental results show that the proposed method can quickly obtain the deposit volume, and the results are equivalent to ContextCapture, Metashape, and Pix4Dmapper software. The method realizes the dynamic visualization of the whole disaster process, provides rich information, achieves high readability, and improves the efficiency of scene rendering, with a stable average rendering frame rate of more than 80 frames/second.

Landslide monitoring plays an important role in predicting, forecasting and preventing landslides. Quantitative explorations at the subject level and fine-scale knowledge in landslide monitoring research can be used to provide information and references for landslide monitoring status analysis and disaster management. In the context of the large amount of network information, it is difficult to clearly determine and display the domain topic hierarchy and knowledge structure. This paper proposes a landslide monitoring knowledge discovery method that combines K-core decomposition and Louvain algorithms. In this method, author keywords are used as nodes to construct a weighted co-occurrence network, and a pruning standard value is defined as K. The K-core approach is used to decompose the network into subgraphs. Combined with the unsupervised Louvain algorithm, subgraphs are divided into different topic communities by setting a modularity change threshold, which is used to establish a topic hierarchy and identify fine-scale knowledge related to landslide monitoring. Based on the Web of Science, a comparative experiment involving the above method and a high-frequency keyword subgraph method for landslide monitoring knowledge discovery is performed. The results show that the run time of the proposed method is significantly less than that of the traditional method.

Atherosclerosis (AS) is recognized as the original cause of most cardiovascular and cerebrovascular diseases. The dual-protein (DP) nutrition that consists of soy protein and whey protein is reported to be associated with a reduction in AS; however, the relationship between DP and AS remains ambiguous. Therefore, this study aimed to verify the effect of DP on AS and explore the optimal DP intake to improve AS. ApoE−/− mice were administrated with low- (LDP), middle- (MDP), and high-dose (HDP) DP. The MDP group exhibited significant improvements in AS. In terms of lipid metabolism, the levels of plasma total triglyceride and LDL-C and the mRNA expression levels of Cyp7a1 and PCSK9 were markedly tuned in the MDP group. In addition, the MDP treatment group had a substantially lower inflammatory response and better intestinal barrier function than LDP and HDP groups. The species richness demonstrated by the Chao1 index was distinctly increased in the MDP group, and the relative abundance of intestinal-permeability-protective microbes Blautia and Akkermansia was significantly elevated. In summary, an adequate intake of DP was able to counteract atherosclerosis development in ApoE−/− mice, and this study provides a scientific theoretical basis for the application of DP in the food and pharmaceutical fields.

The dynamic voltage is a unique phenomenon of superconducting materials. It arises when the superconductor is carrying a DC transport current and spontaneously in subject to an AC magnetic field. This study excavates the aspects that previous studies have not comprehensively investigated: the dynamic voltage in a DC-carrying superconducting tape exposed to different oscillating AC magnetic fields. First, the fundamental physics of dynamic voltage/flux of superconductors is reviewed and further analysed in detail. We used the superconducting modelling method using the H-formulation merged into the finite-element method (FEM) software, to re-produce the typical dynamic voltage behaviour of a superconducting tape. The modelling was verified by both the analytical and experimental results, in order to precisely prove the reliability of the modelling. Afterwards, the modelling was performed for a DC-carrying superconducting tape under four different oscillating magnetic fields (sine, triangle, sawtooth and square), and their corresponding dynamic voltages and energy losses were analysed and compared. Results show the sinusoidal magnetic field can lead to the optimal combination of reasonable dynamic voltage but relatively lower loss, which is suitable for those superconducting applications requiring dynamic voltage as the energy source, e.g., flux pumps. This article presents novel investigation and analysis of the dynamic voltage in superconducting materials, and both the methodology and results can provide useful information for the future design/analysis of superconducting applications with DC transport currents and AC magnetic fields.

Heat stress (HS) is one of the most serious factors to negatively affect the lactation performance of dairy cows. Bovine mammary epithelial cells are important for lactation. It was demonstrated that HS decreases the lactation performance of dairy cows, partly through altering gene expression within bovine mammary epithelial tissue. However, the cellular metabolism mechanisms under HS remains largely unknown. The objective of this study was to determine whether HS induced changes in intracellular metabolites and gene transcription related to amino acid metabolism, amino acid transportation and the mTOR signaling pathway. Immortalized bovine mammary epithelial cell lines (MAC-T cells, n = 5 replicates/treatment) were incubated for 12 h at 37 °C (Control group) and 42 °C (HS group). Relative to the control group, HS led to a greater mRNA expression of heat shock protein genes HSF1, HSPB8, HSPA5, HSP90AB1 and HSPA1A. Compared with the control group, metabolomics using liquid chromatography tandem–mass spectrometry identified 417 differential metabolites with p < 0.05 and a variable importance in projection (VIP) score >1.0 in the HS group. HS resulted in significant changes to the intracellular amino acid metabolism of glutathione, phenylalanine, tyrosine, tryptophan, valine, leucine, isoleucine, arginine, proline, cysteine, methionine, alanine, aspartate and glutamate. HS led to a greater mRNA expression of the amino acid transporter genes SLC43A1, SLC38A9, SLC36A1, and SLC3A2 but a lower mRNA expression of SLC7A5 and SLC38A2. Additionally, HS influenced the expression of genes associated with the mTOR signaling pathway and significantly upregulated the mRNA expression of mTOR, AKT, RHEB, eIF4E and eEF2K but decreased the mRNA expression of TSC1, TSC2 and eEF2 relative to the control group. Compared with the control group, HS also led to greater mRNA expression of the CSN1S2 gene. Overall, our study indicates that bovine mammary epithelial cells may have the ability to resist HS damage and continue milk protein synthesis partly through enhanced intracellular amino acid absorption and metabolism and by activating the mTOR signaling pathway during HS.

High-resolution remote sensing images contain abundant building information and provide an important data source for extracting buildings, which is of great significance to farmland preservation. However, the types of ground features in farmland are complex, the buildings are scattered and may be obscured by clouds or vegetation, leading to problems such as a low extraction accuracy in the existing methods. In response to the above problems, this paper proposes a method of attention-enhanced U-Net for building extraction from farmland, based on Google and WorldView-2 remote sensing images. First, a Resnet unit is adopted as the infrastructure of the U-Net network encoding part, then the spatial and channel attention mechanism module is introduced between the Resnet unit and the maximum pool and the multi-scale fusion module is added to improve the U-Net network. Second, the buildings found on WorldView-2 and Google images are extracted through farmland boundary constraints. Third, boundary optimization and fusion processing are carried out for the building extraction results on the WorldView-2 and Google images. Fourth, a case experiment is performed. The method in this paper is compared with semantic segmentation models, such as FCN8, U-Net, Attention_UNet, and DeepLabv3+. The experimental results indicate that this method attains a higher accuracy and better effect in terms of building extraction within farmland; the accuracy is 97.47%, the F1 score is 85.61%, the recall rate (Recall) is 93.02%, and the intersection of union (IoU) value is 74.85%. Hence, buildings within farming areas can be effectively extracted, which is conducive to the preservation of farmland.

Quartz glass is a typical optical material. In this research, colloidal silica (SiO2) and colloidal cerium oxide (CeO2) are used as abrasive grains to polish quartz glass in the shear thickening polishing (STP) process. The STP method employs the shear-thickening mechanism of non-Newtonian power-law fluid to achieve high-efficiency and high-quality polishing. The different performance in material removal and surface roughness between SiO2 and CeO2 slurries was analyzed. The influence of the main factors including polishing speed, abrasive concentration, and pH value on the MRR, workpiece surface roughness, and the surface topography was discussed. Two different slurries can both achieve fine quartz surface in shear thickening polishing with the polishing speed 100 rpm, and pH value 8. The quartz glass surface roughness Ra decreases from 120 ± 10 to 2.3 nm in 14 minutes’ polishing with 8 wt% 80 nm SiO2 slurry, and the MRR reaches 121.6 nm/min. The quartz glass surface roughness Ra decreases from 120 ± 10 to 2.1 nm in 12 minutes polishing by 6 wt% 100 nm CeO2 slurry and the MRR reaches 126.2 nm/min.

Multi-rotor unmanned aerial vehicles (UAVs) for plant protection are widely used in China’s agricultural production. However, spray droplets often drift and distribute nonuniformly, thereby harming its utilization and the environment. A variable spray system is designed, discussed, and verified to solve this problem. The distribution characteristics of droplet deposition under different spray states (flight state, environment state, nozzle state) are obtained through computational fluid dynamics simulation. In the verification experiment, the wind velocity error of most sample points is less than 1 m/s, and the deposition ratio error is less than 10%, indicating that the simulation is reliable. A simulation data set is used to train support vector regression and back propagation neural network with multiple parameters. An optimal regression model with the root mean square error of 6.5% is selected. The UAV offset and nozzle flow of the variable spray system can be obtained in accordance with the current spray state by multi-sensor fusion and the predicted deposition distribution characteristics. The farmland experiment shows that the deposition volume error between the prediction and experiment is within 30%, thereby proving the effectiveness of the system. This article provides a reference for the improvement of UAV intelligent spray system.

Evacuation simulations in virtual indoor fire scenes hold great significance for public safety. However, existing evacuation simulation methods are inefficient and provide poor visualized when applied to virtual reality (VR) simulations. Additionally, the influences of the interaction of evacuation processes on the choice of multiple exits have not been fully considered. In the paper, we propose a VR simulation method for crowd evacuation in a multiexit indoor fire environment. An indoor 3D scene model and character model, for studying the environmental factors that affect the multiexit selection of personnel during the fire process, are combined with environmental factors to enhance the evacuation route planning algorithm to improve the efficiency of the VR simulation of evacuation in the scene. In addition, a prototype system that supports multiple experience modes is proposed, and case experiment analyses are performed. The results show that the method described in this paper can effectively support the real-time simulation of indoor fire evacuations in virtual scenes, providing both reliable simulation results and good visualization effects.

Industrial exhausted heat can be used as the heat source of central heating for higher energy efficiency. To recover more industrial exhausted heat, a new low-temperature central heating system integrated with industrial exhausted heat using distributed electric compression heat pumps is put forward and analyzed from the aspect of thermodynamics and economics. The roles played by the distributed electric compression heat pumps in improving both thermal performance and financial benefit of the central heating system integrated with industrial exhausted heat are greater than those by the centralized electric compression heat pumps. The proposed low-temperature central heating system has higher energy efficiency, better financial benefit, and longer economical distance of transmitting exhausted heat, and thus, its configuration is optimal. For the proposed low-temperature central heating system, the annual coefficient of performance, annual product exergy efficiency, heating cost, and payback period are about 22.2, 59.4%, 42.83 ¥/GJ, and 6.2 years, respectively, when the distance of transmitting exhausted heat and the price of exhausted heat are 15 km and 15 ¥/GJ, respectively. The economical distance of transmitting exhausted heat of the proposed low-temperature central heating system could approach 25.1 km.

The construction of a virtual debris flow disaster environment is of great significance in debris flow disaster prevention, risk assessment, accurate simulation, and disaster emergency response. However, existing research on virtual disaster environments mainly focus on the specific visualization task requirements of single-type users, and the multilevel visualization task requirements of multitype users are generally not met. In this paper, an adaptive construction method for virtual debris flow disaster environments driven by multilevel visualization task is proposed based on the characteristics of users with different professional knowledge backgrounds and requirements in disaster emergency response scenarios. The on-demand construction of virtual debris flow disaster environments and the corresponding diverse organization and dynamic scheduling technologies are discussed in detail. Finally, the Qipan Gully debris flow disaster is selected for experimental analysis, and a prototype system is developed. The experimental results show that the proposed method can adaptively construct virtual debris flow disaster environments according to the multilevel visualization task requirements of multitype users in debris flow disaster emergency response scenarios. This approach can provide efficient rendering of disaster scenes and appropriate disaster information to multitype users who are involved in debris flow disaster emergency response scenarios.

Scientific and appropriate visualizations increase the effectiveness and readability of disaster information. However, existing fusion visualization methods for disaster scenes have some deficiencies, such as the low efficiency of scene visualization and difficulties with disaster information recognition and sharing. In this paper, a fusion visualization method for disaster information, based on self-explanatory symbols and photorealistic scene cooperation, was proposed. The self-explanatory symbol and photorealistic scene cooperation method, the construction of spatial semantic rules, and fusion visualization with spatial semantic constraints were discussed in detail. Finally, a debris flow disaster was selected for experimental analysis. The experimental results show that the proposed method can effectively realize the fusion visualization of disaster information, effectively express disaster information, maintain high-efficiency visualization, and provide decision-making information support to users involved in the disaster process.

In this study, ternary Cu2SnS3 (CTS) nanostructure materials with high crystallinity were successfully prepared via a facile solvothermal method, which was followed by high-temperature treatment. The morphology of the as-synthesized samples is uniform flower-like spheres, with these spheres consisting of hierarchical nanosheets and possessing network features. Sodium storage measurements demonstrate that the annealed CTS electrodes have high initial reversible capacity (447.7 mAh·g−1 at a current density of 100 mA·g−1), good capacity retention (200.6 mAh·g−1 after 50 cycles at a current density of 100 mA·g−1) and considerable rate capability because of their high crystallinity and unique morphology. Such good performances indicate that the high crystallinity CTS is a promising anode material for sodium ion batteries.