Search

Leaf stalk-stem angle is an important agronomic trait influencing melon architecture, photosynthetic efficiency, and crop yield. However, the mechanisms governing leaf stalk-stem angle, particularly in melon, are not well understood. In this study, we explored the comparative transcriptome in the expanded architecture line Y164 and the compact plant architecture line Z151 at 30 days after pollination. Phytohormones were measured at the leaf stalk-angle site at the same time in these two lines using liquid chromatography (LC) tandem mass spectrometry (MS) (LC-MS/MS). The phytohormones and transcriptomes were jointly analyzed. Differential hormone profiling revealed that the levels of 1-aminocyclopropane-1-carboxylate (ACC) and 12-oxophytodienoic acid (OPDA) in the large-angled line Y164 were significantly higher than those in the small-angled line Z151. These differences were quantified as 2.1- and 2.8-fold increases, respectively. Conversely, the content of isopentenyl adenosine (IPA) was significantly elevated in Z151, with a 3.8-fold higher concentration relative to Y164. Transcriptome analysis identified a total of 1709 differently expressed genes (DEGs), with a predominant enrichment in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to photosynthesis and plant hormone signal transduction. Similarly, photosynthesis and the hormone metabolic process were predominantly enriched in the biological process of Gene Ontology (GO) terms. Further integration of transcriptome and hormone analyses substantiated the close relationship between melon leaf stalk-stem angle and phytohormones, especially ACC, OPDA and IPA. Selected DEGs from phytohormone signal transduction were validated. Detailed analysis of DEGs highlighted the potential role of genes such as GH3s (LOC103490488, LOC103490483), SUARs (LOC107991561, LOC103497281 and LOC103489067), ARFs (LOC103503893, LOC103493078) and five genes in abscisic acid pathway. In summary, our findings strongly suggest a direct correlation between phytohormones and the leaf stalk-stem angles in melon.

BackgroundIn this study, deep eutectic solvents (DESs) combined with ultrasound-assisted extraction (UAE) were used to extract bioactive compounds from the leaves of Moringa oleifera Lam.MethodsThe FT-IR method was used to analyze the structural characteristics of the DESs, and the extraction efficiencies of the DESs for total phenolic content (TPC) and total flavonoid content (TFC) were evaluated. The stability of the extracts under high temperature and UV radiation was assessed, and their antioxidant activity was investigated after undergoing in vitro simulated digestion.ResultsThe results show that the seven DESs extracted more TPC and TFC than did the 70% ethanol (36.27 ± 1.58 mg GAE/g, 23.09 ± 1.47 mg RT/g), and the extraction process of UAE-DES was optimized by selecting choline chloride: citric acid as the DES solvent, which has the highest extraction of TPC (86.92 ± 1.34 mg GAE/g) and TFC (49.73 ± 0.85 mg RT/g). The stability results indicated that the DES phenolic extracts were less stable when exposed to high temperature and UV radiation, indicating that DES extracts have better bioactivity. Moreover, after in vitro simulated digestion, the DES extract shows a higher DPPH free radical scavenging capacity (12.79 ± 3.88 mmol Trolox/g of DES extracts, 6.99 ± 4.02 mmol Trolox/g of ethanol extracts) and ferric ion reducing antioxidant power (62.61 ± 1.71 mmol Trolox/g of DES extracts, 55.07 ± 1.66 mmol Trolox/g of ethanol extracts) than ethanol extracts.ConclusionThis study confirmed that DESs are a new and environmentally friendly solvent that can be used for the extraction of phenolic compounds.

Abstract Objective The aim of this study was to examine the Coronavirus disease 2019(COVID-19) vaccine policies disparities and effectiveness in Germany, Denmark and Bulgaria, with a view to providing lessons for global vaccination and response to possible outbreak risks. Methods This study analyzed big data through public information on the official websites of the Ministries of Health of the European Union, Germany, Denmark and Bulgaria and the official websites of the World Health Organization. We systematically summarized the COVID-19 vaccine policies of the three countries, and selected the following six indicators for cross-cutting vaccination comparisons: COVID-19 vaccine doses administered per 100 people, COVID-19 vaccination rate, the share of people with fully vaccinated, the share of people only partly vaccinated, cumulative confirmed COVID-19 cases per million, cumulative confirmed COVID-19 deaths per million. Meanwhile, we selected the following four indicators for measuring the effectiveness of COVID-19 vaccine policy implementation: daily cases per million, daily deaths per million, the effective reproduction rate (Rt), the moving-average case fatality rate (CFR). Results Although these three EU countries had the same start time for vaccination, and the COVID-19 vaccine supply was coordinated by the EU, there are still differences in vaccination priorities, vaccination types, and vaccine appointment methods. Compared to Germany and Denmark, Bulgaria had the least efficient vaccination efforts and the worst vaccination coverage, with a vaccination rate of just over 30% as of June 2023, and the maximum daily deaths per million since vaccination began in the country was more than three times that of the other two countries. From the perspective of implementation effect, vaccination has a certain effect on reducing infection rate and death rate, but the spread of new mutant strains obviously aggravates the severity of the epidemic and reduces the effectiveness of the vaccine. Among them, the spread of the Omicron mutant strain had the most serious impact on the three countries, showing an obvious epidemic peak. Conclusions Expanding vaccination coverage has played a positive role in reducing COVID-19 infection and mortality rates and stabilizing Rt. Priority vaccination strategies targeting older people and at-risk groups have been shown to be effective in reducing COVID-19 case severity and mortality in the population. However, the emergence and spread of new variant strains, and the relaxation of epidemic prevention policies, still led to multiple outbreaks peaking. In addition, vaccine hesitancy, mistrust in government and ill-prepared health systems are hampering vaccination efforts. Among the notable ones are divergent types of responses to vaccine safety issue could fuel mistrust and hesitancy around vaccination. At this stage, it is also necessary to continue to include COVID-19 vaccination in priority vaccination plans and promote booster vaccination to prevent severe illness and death. Improving the fairness of vaccine distribution and reducing the degree of vaccine hesitancy are the focus of future vaccination work.

Infrared multi-band small and dim target detection is an important research direction in the fields of modern remote sensing and military surveillance. However, achieving high-precision detection remains challenging due to the small scale, low contrast of small and dim targets, and their susceptibility to complex background interference. This paper innovatively proposes a dual-band infrared small and dim target detection method (MM-IRSTD). In this framework, we integrate a convolutional self-attention mechanism module and a self-distillation mechanism to achieve end-to-end dual-band infrared small and dim target detection. The Conv-Based Self-Attention module consists of a convolutional self-attention mechanism and a multilayer perceptron, effectively extracting and integrating input features, thereby enhancing the performance and expressive capability of the model. Additionally, this module incorporates a dynamic weight mechanism to achieve adaptive feature fusion, significantly reducing computational complexity and enhancing the model’s global perception capability. During model training, we use a spatial and channel similarity self-distillation mechanism to drive model updates, addressing the similarity discrepancy between long-wave and mid-wave image features extracted through deep learning, thus improving the model’s performance and generalization capability. Furthermore, to better learn and detect edge features in images, this paper designs an edge extraction method based on Sobel. Finally, comparative experiments and ablation studies validate the advancement and effectiveness of our proposed method.

Biocontrol agents against rice blast fungus Magnaporthe oryzae have attracted more attention recently. In this study, the antifungal activity of AMEP412 protein against M. oryzae was assessed. AMEP412 induced a visible inhibition zone on M. oryzae coated agar plates, which preliminarily verified its antifungal activity. On complete medium agar plates, the aerial hyphae growth was significantly slowed down by AMEP412 (0.0125–0.05 mg/mL), with inhibition rates ranging from 21.25 to 54.40%. The half maximal effective concentration (EC50 value) was 0.041 mg/mL. On oats medium agar plates, the spore development was also inhibited both in quantity and in pathogenicity. The treatment with AMEP412 (0.0125, 0.025 and 0.05 mg/mL) was associated with a decrease in the spore number by 78.13%, 88.98% and 95.72%, and the lesion area on rice leaves by 38.2%, 58.0% and 63.0%, respectively. Under microscopic observation, the aerial hyphae showed irregular external shape and the spores showed abnormal transverse septum. Fluorescence labeling revealed that AMEP412 localized on the surface of aerial hyphae and the septum of spores, indicating that the membrane integrity and permeability were probably disrupted. The predicted structure model of AMEP412 displayed obvious positive net charge and hydrophobic face, which supported the interaction between AMEP412 and M. oryzae. Finally, the pathogenicity test on rice seedlings showed that AMEP412 (0.05 mg/mL) reduced the lesion area by 90.8%. Our results revealed that AMEP412 had antifungal activity against M. oryzae in vivo and in vitro, and could be developed as an antifungal agent in the control of rice blast.

Abstract Background This study aimed to analyze coronavirus disease 2019 (COVID-19)vaccine policies and effectiveness in Korea, Japan, and Singapore, thereby providing empirical experience for vaccination and response to similar public health emergencies. Methods The study systematically summarized the COVID-19 vaccine policies in Korea, Japan, and Singapore through public information from the Our World in Data website and the official websites of the Ministries of Health in these three countries.Total vaccinations, COVID-19 vaccination rates, rates of fully vaccinated, rates of boostervaccinated, and total confifirmed cases were selected for cross-sectional comparison of COVID-19 vaccination in these three countries. Combining the basic characteristics of these three countries, daily cases per million, daily deaths per million, and the effective reproduction rate were calculated to measure the effectiveness of COVID-19 vaccine policies implementation in each of these three countries Results The countermeasures against the COVID-19 in Korea, Japan, and Singapore, although seemingly different on the surface, have all taken an aggressive approach. There are large similarities in the timing of the start of COVID-19 vaccination, the type of vaccine, how vaccine appointments are made, and whether vaccination are free, and all had high vaccination rates. A systematic comparison of the anti-epidemic practices in the three East Asian countries revealed that all three countries experienced more than one outbreak spike due to the spread of new mutant strains after the start of mass vaccination with COVID-19 vaccination, but that vaccination played a positive role in reducing the number of deaths and stabilizing the effective reproduction rate. Conclusions This study comparatively analyzed the COVID-19 vaccine policies and their effects in South Korea, Japan, and Singapore, and found that there is a common set of logical combinations behind the seemingly different strategies of these three countries. Therefore, in the process of combating COVID-19, countries can learn from the successful experience of combating the epidemic and continue to strengthen the implementation of vaccination programs, as well as adjusting public perceptions to reduce the level of vaccine hesitancy, enhance the motivation for vaccination, and improve the coverage of COVID-19 vaccine based on different cultural factors, which remains the direction for future development.

The dynamic distribution of urban population density and the interaction with land use elements involve mutual constraints and guidance. However, in the existing research on the relationship between urban population density and land use, the discussion on the distribution patterns of urban population density typically spans long time periods and uses large spatial units, lacking analysis of the dynamic changes in population density within high granularity land parcels over a day. In studies related to the urban built environment, the complex relationships between different-dimensional land use elements and the dynamic distribution of population density also need further exploration. To address these bottlenecks, this study takes Shanghai’s central urban area as an example. Based on 24 h mobile signaling data on weekdays, weekends, and typical holidays, as well as urban land use data, clustering algorithms are used to summarize patterns of dynamic population density distribution. Pearson correlation analysis is then employed to study the correlation between dynamic population density distribution patterns and different land use elements. The results indicate that various urban land use factors such as locational centrality, functional diversity, transportation accessibility, compactness, and landscape quality have different impacts on the dynamic distribution of population density in spatial units, and the dynamic distribution patterns of population density in different land use types also vary. This research contributes to guiding the optimization of spatial quality and formulating planning and management measures that more effectively match construction intensity with population activity density.

Abstract Objective The study aimed to analyze the efficiency and equity of bed utilization in Please check if the section headings are assigned to appropriate levels.China’s healthcare institutions and to compare and analyze the overall health resource utilization efficiency in recent years and some specific utilization conditions in 2021, to provide empirical experience for the allocation of health care resources in epidemic China. Methods To compare and analyze the overall health resource utilization efficiency of the whole country with that of the East, middle, and West in 2021, and to analyze the bed utilization efficiency of different types of healthcare institutions in China and the bed utilization efficiency of various types of specialist hospitals in the country in 2021 by using the rank-sum ratio method. Results In 2021, the bed utilization rate of China’s health institutions was 69.82%, and the number of bed turnover times was 27.65 times; the bed utilization rate of hospitals was 74.6%, and the number of bed turnover times was 26.08 times. The number of hospital bed turnovers was highest in the western region, lowest in the central region, and close to the national average in the eastern region. The average length of stay for discharged patients was the highest in the central region, the lowest in the eastern region, and the same as the national average in the western region. The analysis of rank-sum ratio method shows that among different types of health institutions’ bed utilization efficiency (r = 0.935, P = 0.000), general hospitals and traditional Chinese medicine hospitals have the best bed utilization rate, and the bed utilization rate of community health service centers (stations) needs to be improved; while among various types of specialized hospitals’ bed utilization efficiency (r = 0.959, P = 0.000), oncology hospitals, thoracic hospitals, and hematology hospitals, children’s hospitals have high bed utilization efficiency; leprosy hospitals, cosmetic hospitals, and stomatology hospitals have low bed utilization efficiency. Health technicians per 1,000 population are highest in the western region, lowest in the central region, and lower in the eastern region than in the western region but slightly higher than the national average. The number of beds in health institutions per 1,000 population is the highest in the central region, the lowest in the eastern region, and slightly lower in the northwest than in the central region but higher than the national average. Conclusion China’s investment in health funding in the field of health care has been on the rise in recent years. However, there still exists the situation of uneven investment in health expenses and inconsistent medical efficiency among regions. And change such a status quo can be further improved in terms of government, capital, human resources, technology, information system, and so on.

ObjectiveThe purpose of this study is to provide experience and evidence support for countries to deal with similar public health emergencies such as COVID-19 by comparing and analyzing the measures taken by six countries in epidemic prevention and control.MethodsThis study extracted public data on COVID-19 from the official website of various countries and used ecological comparative research methods to compare the specific situation of indicators such as daily tests per thousand people, stringency index, and total vaccinations per hundred people in countries.ResultsThe cumulative death toll in China, Germany and Australia was significantly lower than that in the United States, South Africa and Italy. Expanding the scale of testing has helped control the spread of the epidemic to some extent. When the epidemic situation is severe, the stringency index increases, and when the epidemic situation tends to ease, the stringency index decreases. Increased vaccination rates, while helping to build an immune barrier, still need to be used in conjunction with non-drug interventions.ConclusionThe implementation of non-drug interventions and vaccine measures greatly affected the epidemic prevention and control effect. In responding to public health emergencies such as the COVID-19 epidemic, countries should draw on international experience, closely align with their national conditions, follow the laws of epidemiology, actively take non-drug intervention measures, and vigorously promote vaccine research and development and vaccination.

Background: Alzheimer's disease (AD) is a common form of dementia, and impaired mitophagy is a hallmark of AD. Mitophagy is mitochondrial-specific autophagy. Ginsenosides from Ginseng involve in autophagy in cancer. Ginsenoside Rg1 (Rg1 hereafter), a single compound of Ginseng, has neuroprotective effects on AD. However, few studies have reported whether Rg1 can ameliorate AD pathology by regulating mitophagy. Methods: Human SH-SY5Y cell and a 5XFAD mouse model were used to investigate the effects of Rg1. Rg1 (1μM) was added to β-amyloid oligomer (AβO)-induced or APPswe-overexpressed cell models for 24 hours. 5XFAD mouse models were intraperitoneally injected with Rg1 (10 mg/kg/d) for 30 days. Expression levels of mitophagy-related markers were analyzed by western blot and immunofluorescent staining. Cognitive function was assessed by Morris water maze. Mitophagic events were observed using transmission electron microscopy, western blot, and immunofluorescent staining from mouse hippocampus. The activation of the PINK1/Parkin pathway was examined using an immunoprecipitation assay. Results: Rg1 could restore mitophagy and ameliorate memory deficits in the AD cellular and/or mouse model through the PINK1-Parkin pathway. Moreover, Rg1 might induce microglial phagocytosis to reduce β-amyloid (Aβ) deposits in the hippocampus of AD mice. Conclusion: Our studies demonstrate the neuroprotective mechanism of ginsenoside Rg1 in AD models. Rg1 induces PINK-Parkin mediated mitophagy and ameliorates memory deficits in 5XFAD mouse models.

Abstract Based on the interrelationship between the built environment and spatial–temporal distribution of population density, this paper proposes a method to predict the spatial–temporal distribution of urban population density using the depth residual network model (ResNet) of neural network. This study used the time-sharing data of mobile phone users provided by the China Mobile Communications Corporation to predict the time–space sequence of the steady-state distribution of population density. Firstly, 40 prediction databases were constructed according to the characteristics of built environment and the spatial–temporal distribution of population density. Thereafter, the depth residual model ResNet was used as the basic framework to construct the behaviour–environment agent model (BEM) for model training and prediction. Finally, the average percentage error index was used to evaluate the prediction results. The results revealed that the accuracy rate of prediction results reached 76.92% in the central urban area of the verification case. The proposed method can be applied to prevent urban public safety incidents and alleviate pandemics. Moreover, this method can be practically applied to enable the construction of a “smart city” for improving the efficient allocation of urban resources and traffic mobility.

Security is paramount in public places such as subways, airports, and train stations, where security screeners use X-ray imaging technology to check passengers’ luggage for potential threats. To streamline this process and make it more efficient, researchers have turned to object detection techniques with the help of deep learning. While some progress has been made, there are few comprehensive literature reviews. This paper provides a comprehensive overview of the standard object detection algorithms and principles in X-ray dangerous goods detection. The article begins by classifying and describing the more popular deep learning object detection techniques in detail and presenting the commonly used publicly available datasets and metrics. And then go on to summarize previous applications of deep learning techniques in X-ray dangerous goods detection, highlighting their successes and limitations. Finally, based on an analysis of the experimental results, it summarizes some of the limitations of deep learning in X-ray baggage detection thus far. It offers insights into the future of this exciting field. With this review, we hope to provide valuable insights and guidance for those seeking to improve public safety through X-ray imaging and deep learning technology.

Objectives The study aims to understand the impact of containment policy and mobility on COVID-19 cases in Chile, Singapore, South Korea and Israel. To provide experience in epidemic prevention and control. Methods Structural equation modeling (SEM) of containment policies, mobility, and COVID-19 cases were used to test and analyze the proposed hypotheses. Results Chile, Israel and Singapore adopted containment strategies, focusing on closure measures. South Korea adopted a mitigation strategy with fewer closure measures, focusing on vaccination and severe case management. There was a significant negative relationship among containment policies, mobility, and COVID-19 cases. Conclusion To control the COVID-19 and slow down the increase of COVID-19 cases, countries can increase the stringency of containment policies when COVID-19 epidemic is more severe. Thus, countries can take measures from the following three aspects: strengthen the risk monitoring, and keep abreast of the COVID-19 risk; adjust closure measures in time and reduce mobility; and strengthen public education on COVID-19 prevention to motivate citizen to consciously adhere to preventive measures.

Rabbit hemorrhagic disease (RHD) is an acute fatal disease caused by the rabbit hemorrhagic disease virus (RHDV). Since the first outbreaks of type 2 RHDV (RHDV2) in April 2020 in China, the persistence of this virus in the rabbit population has caused substantial economic losses in rabbit husbandry. Previous failures in preventing RHDV2 prompted us to further investigate the immune mechanisms underlying the virus’s pathogenicity, particularly concerning the spleen, a vital component of the mononuclear phagocyte system (MPS). For this, a previous RHDV2 isolate, CHN/SC2020, was utilized to challenge naive adult rabbits. Then, the splenic transcriptome was determined by RNA-Seq. This study showed that the infected adult rabbits had 3148 differentially expressed genes (DEGs), which were associated with disease, signal transduction, cellular processes, and cytokine signaling categories. Of these, 100 upregulated DEGs were involved in inflammatory factors such as IL1α, IL-6, and IL-8. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that these DEGs were significantly enriched in the cytokine–cytokine receptor interaction signaling pathway, which may play a vital role in CHN/SC2020 infection. At the same time, proinflammatory cytokines and chemokines were significantly increased in the spleen at the late stages of infection. These findings suggested that RHDV2 (CHN/SC2020) might induce dysregulation of the cytokine network and compromise splenic immunity against viral infection, which expanded our understanding of RHDV2 pathogenicity.

The increased frequency of extreme hot weather events in recent years poses a significant threat to the lives and health of urban residents. Consequently, the thermal comfort of urban open areas has garnered growing attention. The ground material in these urban open areas directly impacts the thermal environment, which significantly influences the comfort of crowds. This study aimed to assess the effect of land cover materials in urban center squares on the thermal comfort of people in high-temperature conditions. Eight types of land cover materials were selected from the two urban squares in the central district of Nanjing Xinjiekou. Physiological equivalent temperature (PET) calculations were performed by measuring the surface temperature, the air temperature, the humidity, and other relevant data to evaluate population thermal comfort. The findings indicated that grass provided the highest thermal comfort, with PET scores ranked as follows, from low to high: grass, permeable bricks, granite, concrete, basalt, bluestone, andesite, and asphalt. Additionally, factors such as color, roughness, and shade within the same material also impacted thermal comfort. Subsequently, using the ENVI-met 5.1 software, surface materials exhibiting superior thermal comfort were simulated for replacement, aiming to confirm the experimental results and propose retrofit strategies for improving urban square thermal comfort by optimizing material selection. The outcomes of this study hold significant implications for urban open space design and the overall well-being of city dwellers. The thermal environment in urban centers during high-temperature conditions can be improved by optimizing the choice of land cover materials in urban open areas, thereby enhancing the comfort of the population.

Accurately estimating the breast muscle weight of broilers is important for poultry production. However, existing related methods are plagued by cumbersome processes and limited automation. To address these issues, this study proposed an efficient method for predicting the breast muscle weight of broilers. First, because existing deep learning models struggle to strike a balance between accuracy and memory consumption, this study designed a multistage attention enhancement fusion segmentation network (MAEFNet) to automatically acquire pectoral muscle mask images from X-ray images. MAEFNet employs the pruned MobileNetV3 as the encoder to efficiently capture features and adopts a novel decoder to enhance and fuse the effective features at various stages. Next, the selected shape features were automatically extracted from the mask images. Finally, these features, including live weight, were input to the SVR (Support Vector Regression) model to predict breast muscle weight. MAEFNet achieved the highest intersection over union (96.35%) with the lowest parameter count (1.51 M) compared to the other segmentation models. The SVR model performed best (R2 = 0.8810) compared to the other prediction models in the five-fold cross-validation. The research findings can be applied to broiler production and breeding, reducing measurement costs, and enhancing breeding efficiency.

With the continuous improvement of broiler production performance, the frequent occurrence of leg problems has caused serious economic losses in many factories. In order to more efficiently detect and prevent broiler leg diseases, we propose an auxiliary detection system for broiler leg diseases based on deep learning. The system is divided into two parts. First, a digital radiography (DR) image of a broiler is taken through industrial computed tomography (CT), and then the improved deep-learning network Tibia-YOLO is used to detect the tibia; the detected results are then extracted and measured. Our improved Tibia-YOLO network uses the Content-Aware ReAssembly of Features (CARAFE) upsampling operator to avoid checkerboard artifacts and increase the generalization capabilities. Efficient multi-scale attention (EMA) and parallel network attention (ParNet) were added to the Tibia dataset at multiple scales (COCO2016), and there were improvements when testing on the three VOC2012 datasets. The mean average precision of tibia detection reached 90.8%, and the root mean square error (RMSE) for the tibia length was 3.37 mm.

Abstract Objective This study aims to compare the differences in COVID-19 prevention and control policies adopted by the United Kingdom (UK) during the first wave (31 January 2020 to 6 September 2020) and the second wave (7 September 2020 to 12 April 2021), and analyze the effectiveness of the policies, so as to provide empirical experience for the prevention and control of COVID-19. Methods We systematically summarized the pandemic prevention and control policies of the UK from official websites and government documents, collated the epidemiological data from 31 January 2020 to 12 April 2021, and analyzed the effectiveness of the two waves of pandemic prevention and control policies. Results The main pandemic prevention and control policies adopted by the UK include surveillance and testing measures, border control measures, community and social measures, blockade measures, health care measures, COVID-19 vaccination measure, and relaxed pandemic prevention measures. The new cases per day curve showed only one peak in the first wave and two peaks in the second wave. The number of new cases per million in the second wave was much higher than that in the first wave, and the curve fluctuated less. The difference between mortality per million was small, and the curve fluctuated widely. Conclusion During the first and second waves of COVID-19, the UK implemented three lockdowns and managed to slow the spread of the pandemic. The UK’s experience in mitigating the second wave proves that advancing COVID-19 vaccination needs to be accompanied by ongoing implementation of non-pharmacological interventions to reduce the transmission rate of infection. And a stricter lockdown ensures that the containment effect is maximized during the lockdown period. In addition, these three lockdowns featured distinct mitigation strategies and the UK’s response to COVID-19 is mitigation strategy that reduce new cases in the short term, but with the risk of the pandemic rebound.

ObjectiveThe aim of this study was to analyze the effectiveness of prevention and control strategies and put forward further measures according to the epidemiological characteristics of Omicron. It summarized the national response during the Omicron epidemic in four countries: China, Israel, South Africa, and the United States.MethodsThis study summarized prevention and control measures in China, Israel, South Africa, and the United States in their response to the Omicron epidemic, and it also evaluated the effectiveness of these measures.ResultsAfter the Omicron variant emerged, China and Israel adopted containment strategies, using the “dynamic zero” policy and country closure measures. Meanwhile, South Africa and the United States adopted mitigation strategies, which virtually abandoned social interventions and only focused on medical measures and vaccines. From the first day of reported Omicron cases to 28 February 2022, the four countries reported the following cases: China reported 9,670 new confirmed cases and no deaths, with total deaths per million of 3.21; Israel reported 2,293,415 new confirmed cases and 2,016 deaths, with total deaths per million of 1,097.21; South Africa reported 731,384 new confirmed cases and 9,509 deaths, with total deaths per million reaching 1,655.708; the United States reported 3,042,743 new confirmed cases and 1,688,851 deaths, with total deaths per million reaching 2,855.052, which was much higher than the other countries.ConclusionBased on this study, it seems that China and Israel adopted containment strategies, while South Africa and the United States adopted mitigation strategies. A rapid response is a powerful weapon against the Omicron epidemic. Vaccines alone will not get any country out of this crisis, and non-pharmacological measures should be used in addition to them. According to the SPO model, future work should consider the strengthening of emergency management capacity, adhering to public health measures, promoting vaccination, and strengthening patient care and close contact management, which are effective measures in coping with Omicron.

Abstract Background This study aimed to compare the prevention and control strategies adopted by the United States and India in the COVID-19 outbreak and analyze the effectiveness of their strategies, in order to provide empirical experience for the prevention and control of the epidemic. Methods This study extracted official data on COVID-19 from various official websites, summarized the policies in place in the United States and India, and evaluated the effectiveness of their policies. Results The United States has adopted a series of mitigation strategies to control the two waves of epidemic, including strengthening virus detection, calling on the people to wear masks and so on. As of May 30, 2021, although the daily new cases there decreased to some extent, the effect was not ideal. The US’s daily new cases ranked fourth and the cumulative number of confirmed cases ranked first in the world. India has adopted containment strategies in the initial stage of the outbreak, making the epidemic relatively stable. In the later stage, India has turned to adopt mitigation strategies. In addition, many factors including the lack of medical resources and premature relaxation measures led to the rapid deterioration of the epidemic situation. As of May 30, 2021, although the daily new cases in India has a downward trend, it ranked first in the world, and the cumulative number of confirmed cases ranked second. Conclusion There are differences between the epidemic prevention strategies adopted by the United States and India, especially India’s containment strategies which helped it better control the epidemic in the early stage. However, the epidemic in the two countries is still severe. With the advent of virus mutants and the absence of immune barriers, it is meaningful that the two countries continue to take non-pharmacotherapy intervention measures and accelerate vaccination, according to specific national conditions adopt containment strategies that can control the epidemic more quickly when necessary, and pay attention to the risk of epidemic rebound caused by premature relaxation of epidemic prevention policies.

Urban shadow areas, formed by long-term unbalanced and inadequate development during the rapid process of urbanization, are of great significance to a city’s overall development. However, relatively little attention has been paid to identifying and characterizing urban shadow areas. Drawing upon a dataset on urban morphology and cellular signaling, and taking Nanjing as a case study, this paper proposes a method to identify urban shadow areas from the perspective of people flows. The empirical results show that there are 19 urban shadow areas within the downtown areas of Nanjing, 11 of which are distributed in the old downtown areas and the rest are relatively scattered in the periphery. As for morphological characteristics, these urban shadow areas differ from each other in terms of indicators such as building density and development intensity. Moreover, the empirical results show that these urban shadow areas are not isolated but closely connected with other parts of Nanjing. Based on the different spatio-temporal distribution patterns of their connections, the 19 urban shadow areas are divided into four types, and the characteristics of each type have been investigated by analyzing a representative shadow area. It is suggested that policies aiming to eliminate the negative effects of urban shadow areas should consider heterogeneity in their spatial distributions within a city, the temporal distribution of their external connections, and their dominant functions.

The metropolitan fringe area is of great significance to a city’s future growth. However, relatively little attention has been paid to delineating and characterizing the metropolitan fringe area from a spatial morphology perspective, which contributes to the planning and design of metropolitan fringe areas. Therefore, the aim of this study is to develop a morphology–based method to delineate the metropolitan fringe area and investigate the characteristics of its spatial morphology. Drawing upon a large–scale dataset on the spatial morphology of Shanghai, this study finds that the metropolitan fringe area is generally circular in shape and is dominated by residential, industrial, agricultural and forestry land. The metropolitan fringe area accounts for 24.65% of the total area of Shanghai and is mainly located between its outer ring and suburban ring areas. The distributions of spatial characteristics of the metropolitan fringe area suggest that the area has a relatively lower level in terms of building height, building density, and development intensity. Furthermore, the metropolitan fringe area of Shanghai contains five key spatial elements, including residential and industrial clusters, shadow spaces accompanying clusters, corridor lines, green wedges, and surfaces. The interaction of the five spatial elements lays the foundation for the prototype of the spatial structure of the metropolitan fringe area of Shanghai, which is of great significance to understanding the heterogeneity within the metropolitan fringe area in terms of the distribution of spatial morphological characteristics. Such heterogeneity also needs to be considered in the planning and design of the metropolitan fringe area.

Abstract Objective To provide experience for formulating prevention and control policies, this study analyzed the effectiveness of the Coronavirus disease 2019(COVID-19) prevention and control policies, and evaluated health equity and epidemic cooperation among BRICS countries. Methods This study summarized the pandemic prevention and control policies in BRICS countries and evaluated the effectiveness of those policies by extracting COVID-19 related data from official websites. Result As of May 4, 2021, responding to COVID-19. China adopted containment strategies. China’s total confirmed cases (102,560) were stable, without a second pandemic peak, and the total deaths per million (3.37) were much lower than others. India and South Africa who adopted intermediate strategies have similar pandemic curves, total confirmed cases in India (20,664,979) surpassed South Africa (1,586,148) as the highest in five countries, but total deaths per million (163.90) lower than South Africa (919.11). Brazil and Russia adopted mitigation strategies. Total confirmed cases in Brazil (14,856,888) and Russia (4,784,497) continued to increase, and Brazil’s total deaths per million (1,936.34) is higher than Russia (751.50) and other countries. Conclusion This study shows BRICS countries implemented different epidemic interventions. Containment strategy is more effective than intermediate strategy and mitigation strategy in limiting the spread of COVID-19. Especially when a strict containment strategy is implemented in an early stage, but premature relaxation of restrictions may lead to rebounding. It is a good choice to combat COVID-19 by improving the inclusiveness of intervention policies, deepening BRICS epidemic cooperation, and increasing health equities.

Although bearings have been used in many rotating machineries, the literatures relative to matched bearings are very scarce. The distributions of contact load and contact angle between bearing parts are the key indicators to reflect the operating condition of bearings, which can directly influence the wear rate and fatigue life of bearings. Owing to the complex and compact structure of matched bearings, it is hard to judge and evaluate what happens inside the matched bearings by experiments. To solve this problem, this paper presents a novel method to determine the distributions of contact load and contact angle of matched bearings under complex working conditions. Firstly, to establish the nonlinear relationship between internal deformations of balls and applied loads, a comprehensive model is proposed by using the coordinate transformation method and the Hertz contact theory. Then, the accuracy of the proposed model is validated by comparing the stiffness values with those reported in the existing reference. Finally, a pair of 7206B bearings is used as a case to introduce the use of the proposed model. The influences of installation type, preload, combined loads on the distributions of contact load and contact angle of matched bearings are detailed analyzed and studied.

In the published publication [...]

Intersections appear where one street crosses another, acting as fundamental nodes embedded in the network of urban public space. Though discussed in configurational and perceptive studies, limited attention has been paid to the morphological aspects of intersections. This study proposes and tested a new approach to modeling the urban intersection form. First, effective cylinder was introduced to define the related space for each intersection based on its scale. Second, a set of morphological indicators were presented to measure the physical properties of the intersection form. Third, the affinity propagation algorithm was used to examine the patterns of intersection form.Using the Old City of Nanjing, China as the study area, 844 intersections were analyzed to test this new method. As a result, we were able to classify the intersections into eight types. This study shows that the intersection can be modelled as a volumetric and integral spatial unit of urban form, which may demand more attention from urban designers and architects in the future for shaping the built environment. The quantitative nature of our method could also open more possibilities for intersection-based studies.

Image classification task is an important branch of computer vision. At present, most of the mainstream CNNs are large in size and take up too much computing resources. The quality-price ratio is not satisfying when the heavy CNNs are used in image classification. So, this work proposes a spatial and channel hybrid attention module (Light-Attention module), an ultra-lightweight but efficient attention module. Given an intermediate feature map, the Light-Attention module will firstly derive the most important attention maps of the channels automatically with global stochastic pooling and Multilayer Perceptron (MLP). Then, the residual structure of Light-Attention module helps to repeatedly introduce global information for secondary screening. For better performance, our pioneering Max module and Mean module to extract key spatial features on the basis of previous operations. In the process of extracting the key attention map, LADNet uses the most labor-saving operation and save a lot of network parameters. The Light-Attention module can be seamlessly integrated into any network, while its parameters and required computing resources are both very small. We verified the excellent performance of the Light-Attention module in extracting key image information through ablation experiments on the Cifar-10, Cifar-100 and ImageNet datasets. For the experiment in Cifar-10, the image classification accuracy achieves 98.7%, achieves 96.5% for the Cifar-100, and for the ImageNet, achieves 83.9%. With the Light-Attention module, LADNet reduces the parameters of convolution neural network to 71% of the original. Compared to the other CNNs used in image classification task, the Light-Attention module uses the least parameters but scores most advanced achievements. The experiments proved that the combination of DRN (Dilated Residual Network) and Light-Attention module achieves superior performance.

Pure organic room-temperature phosphorescence (RTP) materials built upon noncovalent interactions have attracted much attention because of their high efficiency, long lifetime, and stimulus-responsive behavior. However, there are limited reports of noncovalent RTP materials because of the lack of specific design principles and clear mechanisms. Here, we report on a noncovalent material prepared via facile grinding that can emit fluorescence and RTP emission differing from their components’ photoluminescent behavior. Exciplex can be formed during the preparation process to act as the minimum emission unit. We found that H-bonds in the RTP system provide restriction to nonradiative transition but also enhance energy transformation and energy level degeneracy in the system. Moreover, water-stimulated photoluminescent ink is produced from the materials to achieve double-encryption application with good resolution.

(1) Purpose: This study aimed to analyze coronavirus disease 2019 (COVID-19) vaccine policies and their effectiveness in Italy, India, and South Africa to provide empirical experience for vaccination and COVID-19 pandemic control. (2) Methods: The study systematically summarized the COVID-19 vaccine policies in Italy, India, and South Africa through public information available on the official websites of the World Health Organization and the ministries of health in these three countries. Total vaccinations, COVID-19 vaccination rates, rates of fully vaccinated, rates of booster-vaccinated, and total confirmed cases were selected for cross-sectional comparison of COVID-19 vaccination in these three countries. Daily cases per million, daily deaths per million, and the effective reproduction rate were calculated to measure the effectiveness of COVID-19 vaccine policies implementation in each of these three countries. (3) Results: Italy, India, and South Africa differ in the start date of COVID-19 vaccination, vaccine types, vaccine appointments, and whether vaccinations are free. The COVID-19 vaccination rates in these three countries varied widely, with Italy having the highest and South Africa the lowest. COVID-19 vaccination has had a positive effect on reducing daily deaths and stabilizing the effective reproduction rate. The three countries had experienced more than one outbreak spike due to the spread of new mutated strains since the start of COVID-19 vaccination. (4) Conclusions: This study concluded that responding to the COVID-19 pandemic requires active promotion of basic and booster vaccinations to comprehensively build up the population immune barrier. Promoting equitable distribution of COVID-19 vaccine internationally and solidarity and cooperation among countries maximizes global common interests. By combining vaccination with non-pharmaceutical interventions, the pandemic can be prevented and controlled comprehensively and systematically in three aspects: detection of the source of infection, reduction of transmission routes, and protection of susceptible populations.

The mechanism of the formation of the hydrophobic agglomerate in fine scheelite flotation was studied using zeta potential measurement, contact angle measurement, optical microscope measurement, and atomic force microscopy (AFM) colloid probe technology. Zeta potential measurement results confirmed the adsorption of sodium oleate on scheelite, fluorite, and calcite surface and surface potential difference at different pH values of ultrapure water. Contact angle measurement results confirmed the surface of nature scheelite, fluorite, and calcite was hydrophilic, and the surface after thread by sodium oleate solution was hydrophobic. The optical microscope measurement results confirmed the agglomerates could really form in ultrapure water of pH 8 or 10 and in 1 mM sodium oleate solution of pH 10. The agglomerations were empty and not tight in ultrapure water. On the contrary, the hydrophobic agglomerations were larger and denser after treated with sodium oleate solution than that of in ultrapure water. According to the AFM experiment results, the interaction forces on hydrophilic scheelite-scheelite and scheelite-fluorite were repulsive at pH 5.6 and attractive at pH 8 or 10. However, the interaction forces on hydrophilic scheelite-calcite were attractive at pH 5.6, 8 or 10. The interaction forces on hydrophobic scheelite-scheelite, scheelite-fluorite, and scheelite-calcite were attractive strongly due to the existence of hydrophobic force. The measurement results of the interaction forces were in good agreement with the changes of zeta potential and contact angle at different conditions. The combined results could be beneficial to understand the interaction force in fine scheelite flotation.

Based on threshold analysis theory, spatial limiting factors such as mountains, rivers, and roads not only affect the way in which cities spread out, but also play a vital role in shaping the flattened forms of their central districts. This study, based on field investigations of 21 central districts in 13 Asian megacities, seeks out limiting factors that determine the boundaries of urban central districts by quantifying the spatial boundary and distance of the limiting factors. The results suggest a strong correlation between the spatial limiting factors and the urban central district′s form. The limiting elements constrain the size of buildings and population density based on floor area ratio, building density, and development boundaries. Reduction in population and the inconvenience of traffic have decreased urban vitality, leading to delays in the extension of cites′ central districts. It is necessary to fully consider the role of the city′s internal limiting elements in order to reasonably plan the construction of an urban central district.

Urban energy simulation can provide valuable information to urban planning, urban energy management, and urban emission reduction. Therefore, urban energy simulation has become an active research discipline. Various urban energy simulation methods and techniques have been developed and applied to cities on different scales. A review is conducted to categorize these methods and techniques and to analyze their pros and cons. Several representative methods and techniques are compared for their data inputs, suitable scales, accuracy, and computing speeds. Hangzhou South Railway Station area, which contains 522 buildings, is used as the case to evaluate the effectiveness and challenges of different urban energy simulation methods.

Some studies have confirmed the association between urban public services and population density; however, other studies using census data, for example, have arrived at the opposite conclusion. Mobile signaling data provide new technological tools to investigate the subject. Based on the data of 20 million 2G mobile phone users in downtown Shanghai and the land use data of urban public service facilities, this study explores the spatiotemporal correlation between population density and public service facilities’ locations in downtown Shanghai and its variation laws. The correlation between individual population density at day vs. night and urban public service facilities distribution was also examined from a dynamic perspective. The results show a correlation between service facilities’ locations and urban population density at different times of the day. As a result, the average population density observed over a long period of time (day-time periodicity or longer) with census data or remote sensing data does not directly correlation with the distribution of public service facilities despite its correlation with public service facilities distribution. Among them, there is a significant spatial correlation between public service facilities and daytime population density and a significant spatial correlation between non-public service facilities and night-time population density. The spatial and temporal changes in the relationship between urban population density and service facilities is due to changing crowd behavior; however, the density of specific types of behavior is the real factor that affects the layout of urban public service facilities. The results show that mobile signaling data and land use data of service facilities are of great value for studying the spatiotemporal correlations between urban population density and service facilities.