Agricultural land development is a pivotal strategy for addressing the global food security crisis.Barren grassland,especially those in mountainous regions,constitutes critical areas where cultivation can substantiall...Agricultural land development is a pivotal strategy for addressing the global food security crisis.Barren grassland,especially those in mountainous regions,constitutes critical areas where cultivation can substantially enhance land resources.This study highlights the necessity for a precise correlation between land development initiatives and constraints in order to optimize efficiency and enhance the effectiveness of such projects,with the core being the seamless integration of land development engineering and techniques to eliminate agricultural constraints.This study employs a systems engineering approach to classify improvement factors into mobile and fixed categories,elucidating the integration methods of constraint factors.Adhering to the Wooden Barrel Principle,these constraints were rigorously analyzed based on soil quality,land topography,water availability,and agricultural infrastructure.An innovative method of engineering type combination is proposed,which effectively explains the correlation between natural factors combination,project type combination,and target factors combination.It provides a convenient way for the selection of barren grassland development projects and lays a foundation for land planning,development project establishment,program selection,engineering design,and budget preparation.Taking Tang County of China as an example,it is divided into 19 factor improvement areas,a quick reference table of engineering types is established,and 14 main types of engineering combinations are obtained,which lays a foundation for the application of theoretical framework in practice.展开更多
A Tibetan art form bridges the past and present and connects cultures around the world.THANGKA,a unique form of Tibetan sacred painting,is gaining prominence globally due to its vibrant colors,exquisite craftsmanship,...A Tibetan art form bridges the past and present and connects cultures around the world.THANGKA,a unique form of Tibetan sacred painting,is gaining prominence globally due to its vibrant colors,exquisite craftsmanship,and profound religious and cultural significance.With the acceleration of globalization,this symbol of Tibetan culture that combines artistic expression with spirituality has become a bridge for cultural exchange between the East and the West.Recently,China Today spoke to Yixi Puncog,art collector and council member of the China Association for Preservation and Development of Tibetan Culture,to learn more about Thangka art,its role in international exchange,and how it is enhancing China’s cultural soft power.展开更多
This article interprets why domestication and those translation techniques as addition, deletion and shift are widely adopted by most translators in modem China and how the target socio-cultural factors at the time co...This article interprets why domestication and those translation techniques as addition, deletion and shift are widely adopted by most translators in modem China and how the target socio-cultural factors at the time constrain the translators＇ selection of strategies in literary translation.展开更多
Genomic selection is more and more popular in animal and plant breeding industries all around the world, as it can be applied early in life without impacting selection candidates. The objective of this study was to br...Genomic selection is more and more popular in animal and plant breeding industries all around the world, as it can be applied early in life without impacting selection candidates. The objective of this study was to bring the advantages of genomic selection to scallop breeding. Two different genomic selection tools Mix P and gsbay were applied on genomic evaluation of simulated data and Zhikong scallop(Chlamys farreri) field data. The data were compared with genomic best linear unbiased prediction(GBLUP) method which has been applied widely. Our results showed that both Mix P and gsbay could accurately estimate single-nucleotide polymorphism(SNP) marker effects, and thereby could be applied for the analysis of genomic estimated breeding values(GEBV). In simulated data from different scenarios, the accuracy of GEBV acquired was ranged from 0.20 to 0.78 by Mix P; it was ranged from 0.21 to 0.67 by gsbay; and it was ranged from 0.21 to 0.61 by GBLUP. Estimations made by Mix P and gsbay were expected to be more reliable than those estimated by GBLUP. Predictions made by gsbay were more robust, while with Mix P the computation is much faster, especially in dealing with large-scale data. These results suggested that both algorithms implemented by Mix P and gsbay are feasible to carry out genomic selection in scallop breeding, and more genotype data will be necessary to produce genomic estimated breeding values with a higher accuracy for the industry.展开更多
The paper firstly analyzes selection factors for market subjects of agricultural industrial development in China. From the political aspect, it is required to take account of features of subjects of agricultural indus...The paper firstly analyzes selection factors for market subjects of agricultural industrial development in China. From the political aspect, it is required to take account of features of subjects of agricultural industrial development at current stage. From economic aspects, we should adheres to the two-tier management system that integrates unified with separate management on the basis of household contract management in the countryside, and cultivate and foster subject enterprises according to features of most important market subjects in market economy. From natural aspects, it is proposed to consider features of agricultural industry and inherent advantages of agricultural resources in China. From social aspects, it is essential to draw on successful experience of developed countries in developing market subjects of agricultural industry.展开更多
The process of globalization requires countries to cultivate talents with global understanding. English classes in primary schools are of fundamental significance in cultivating students' cultural awareness, while...The process of globalization requires countries to cultivate talents with global understanding. English classes in primary schools are of fundamental significance in cultivating students' cultural awareness, while English picture books become suitable teaching materials due to their innate advantages of rich pictures and texts. The selection of picture books suitable for cultivating cultural awareness needs to consider multiple factors: the creator's cultural background, the authenticity of cultural content, avoiding "stereotypes", the presentation of human cultural commonness and individuality, and the diversity of picture books. The themes of picture books include but are not limited to ethnic diversity, gender equality and personality education.展开更多
The development of a national culture represents the quality of the citizens of this country, the cultural connotation of a national spirit. With the development of society, citizens demand more exuberant cultural ser...The development of a national culture represents the quality of the citizens of this country, the cultural connotation of a national spirit. With the development of society, citizens demand more exuberant cultural services. Therefore, strengthening the construction of public cultural service system is imperative, at the same time, the public cultural system construction is the development and prosperity of socialist advanced culture, and building a harmonious society, the government system of public cultural services for the public and cultural life, which also constitutes a multifaceted innovative public cultural service system Building model in the public service, is the focus of the new era of cultural undertakings .展开更多
The agricultural economy has become an important support of the national economy. Based on a comprehensive understanding of the strategic significance of the rural revitalization, the main factors restricting the deve...The agricultural economy has become an important support of the national economy. Based on a comprehensive understanding of the strategic significance of the rural revitalization, the main factors restricting the development of the rural economy were elaborated. The opportunities for the development of the agricultural economy under the background of the rural revitalization strategy were analyzed, and several suggestions were put forward, in order to effectively promote the sustainable and healthy development of Chinas agricultural economy.展开更多
Different cultural subjects have different cultural and historical background, and thus inevitably bring difference in people's ideological values and behaviors etc,and even shocks. T oday,cross - cultural adaptat...Different cultural subjects have different cultural and historical background, and thus inevitably bring difference in people's ideological values and behaviors etc,and even shocks. T oday,cross - cultural adaptation becomes a common social issue,and arouses general concern of the whole society. Influencing factors of cross - cultural adaptation include cultural distance,personality psychology,thinking pattern,values,social living environment,social support,know ledge & skills,pragmatic transfer etc. Based on making clear the problems,cross - cultural adaptation should be realized from multiple aspects.展开更多
本文基于国际文化经济学期刊Journal of Cultural Economics 2007—2023年所发表的335篇文献,运用Citespace软件进行文献计量与可视化分析,揭示国际文化经济学研究的热点演进与理论特征。研究发现,国际文化经济学聚焦文化市场定价机制...本文基于国际文化经济学期刊Journal of Cultural Economics 2007—2023年所发表的335篇文献,运用Citespace软件进行文献计量与可视化分析,揭示国际文化经济学研究的热点演进与理论特征。研究发现,国际文化经济学聚焦文化市场定价机制、文化消费行为、文化产业创新及文化参与模式等微观实证领域,形成以新古典经济学为基础的研究范式。相比之下,国内文化经济学研究受制度经济学和幸福经济学影响,更侧重宏观层面的文化与经济关系探讨,强调文化政策对经济发展的形塑作用。通过比较分析,本文认为国内文化经济学研究需加强与国际理论界的对话,在实现多元、多尺度研究方法融合基础上,开展面向中国式现代化的文化经济实践,实现理论路径突破。未来研究应聚焦三大方向:一是深化文化与经济互动的制度分析,深化“双效统一”的机制研究;二是探索数字技术驱动的文化经济转型,分析区块链、人工智能等最新技术对文化生产、传播与消费的重构路径;三是立足中国式现代化建设实践,构建文化赋能社会经济发展的内生驱动模式,为全球文化经济发展和治理贡献中国智慧。展开更多
Radiation induced mutagenesis followed by in vitro selection was employed for salt tolerance in popular Indian sugarcane （Saccharum officinarum L.） cv. CoC-671. Embryogenic calli were gamma irradiated and exposed to...Radiation induced mutagenesis followed by in vitro selection was employed for salt tolerance in popular Indian sugarcane （Saccharum officinarum L.） cv. CoC-671. Embryogenic calli were gamma irradiated and exposed to different levels of NaCl （42.8, 85.6, 128.3, 171.1,213.9, 256.7, 299.5, or 342.2 mM）. The relative growth rate （RGR） decreased progressively with increasing salt stress and was the least with a salt stress of 256.7 mM （0.25±0.009）, almost 10 fold lesser than the control. The RGR was significantly lower in 85.6 mM and higher salt stressed calli than the control. The survival percent also decreased, with an increase in NaCl concentration. In case of 10 and 20 Gy irradiated calli, regeneration was observed up to 85.6 mM NaCl selection, medium, whereas, higher treatments （128.3 mM and beyond） exhibited browning initially. However, in the subsequent subcultures, regeneration was obtained in the case of 10 and 20 Gy irradiated calli on 128.3 and 171.1 mM NaCl selections. Higher dose of gamma irradiation （40 Gy） also showed regeneration, but only with 85.6 mM NaCI selection. The unirradiated calli regenerated the highest number of plantlets followed by 10 and 20 Gy irradiated calli on salt selection. A total of 147 plantlets were selected from different salt levels. The salt selected plants are being tested for their field performance.展开更多
The rapid rise of cyberattacks and the gradual failure of traditional defense systems and approaches led to using artificial intelligence(AI)techniques(such as machine learning(ML)and deep learning(DL))to build more e...The rapid rise of cyberattacks and the gradual failure of traditional defense systems and approaches led to using artificial intelligence(AI)techniques(such as machine learning(ML)and deep learning(DL))to build more efficient and reliable intrusion detection systems(IDSs).However,the advent of larger IDS datasets has negatively impacted the performance and computational complexity of AI-based IDSs.Many researchers used data preprocessing techniques such as feature selection and normalization to overcome such issues.While most of these researchers reported the success of these preprocessing techniques on a shallow level,very few studies have been performed on their effects on a wider scale.Furthermore,the performance of an IDS model is subject to not only the utilized preprocessing techniques but also the dataset and the ML/DL algorithm used,which most of the existing studies give little emphasis on.Thus,this study provides an in-depth analysis of feature selection and normalization effects on IDS models built using three IDS datasets:NSL-KDD,UNSW-NB15,and CSE–CIC–IDS2018,and various AI algorithms.A wrapper-based approach,which tends to give superior performance,and min-max normalization methods were used for feature selection and normalization,respectively.Numerous IDS models were implemented using the full and feature-selected copies of the datasets with and without normalization.The models were evaluated using popular evaluation metrics in IDS modeling,intra-and inter-model comparisons were performed between models and with state-of-the-art works.Random forest(RF)models performed better on NSL-KDD and UNSW-NB15 datasets with accuracies of 99.86%and 96.01%,respectively,whereas artificial neural network(ANN)achieved the best accuracy of 95.43%on the CSE–CIC–IDS2018 dataset.The RF models also achieved an excellent performance compared to recent works.The results show that normalization and feature selection positively affect IDS modeling.Furthermore,while feature selection benefits simpler algorithms(such as RF),normalization is more useful for complex algorithms like ANNs and deep neural networks(DNNs),and algorithms such as Naive Bayes are unsuitable for IDS modeling.The study also found that the UNSW-NB15 and CSE–CIC–IDS2018 datasets are more complex and more suitable for building and evaluating modern-day IDS than the NSL-KDD dataset.Our findings suggest that prioritizing robust algorithms like RF,alongside complex models such as ANN and DNN,can significantly enhance IDS performance.These insights provide valuable guidance for managers to develop more effective security measures by focusing on high detection rates and low false alert rates.展开更多
Mature zygotic embryos of three families of loblolly pine ( Pinus taeda L.) were cultured on callus induction medium containing 8?mg·L -1 2,4 dichlorophenoxyacetic acid (2,4 D), 4?mg·L -1 6 b...Mature zygotic embryos of three families of loblolly pine ( Pinus taeda L.) were cultured on callus induction medium containing 8?mg·L -1 2,4 dichlorophenoxyacetic acid (2,4 D), 4?mg·L -1 6 benzyladenine (BA), 4?mg·L -1 kinetin (KT), 500?mg·L -1 casein hydrolysate, and 500?mg·L -1 glutamine for 9 weeks, callus was formed on cotyledons, hypocotyls, and radicles of mature zygotic embryos. Callus was sub cultured on the callus proliferation medium with 1 6?mg·L -1 2,4 dichlorophenoxyacetic acid (2,4 D), 0 8?mg·L -1 6 benzyladenine (BA), 0 8?mg·L -1 kinetin (KT) for 9 weeks. White translucent, glossy, mucilaginous embryogenic callus containing embryogenic suspensor masses (ESM) and immature somatic embryos was obtained, and the highest frequency of explants forming embryogenic callus was 16 9%. Embryogenic suspension cultures were established by culturing embryogenic callus in liquid callus proliferation medium. Liquid cultures containing embryogenic suspension masses and immature somatic embryos were transferred to medium containing abscisic acid (ABA), polyethylene glycols (PEG), or activated charcoal for enhancing the production of cotyledonary somatic embryos. After mature somatic embryos were cultured on medium containing indole butyric acid (IBA), gibberellic acid (GA 3), BA, and activated charcoal and being lowered sucrose concentration for 4～12 weeks, somatic embryos germinated to form regenerated plantlets. Seventy one regenerated plantlets were transferred to a perlits∶peatmoss∶vermiculate (1∶1∶1) soil mixture, and 23 plantlets survived in the field.展开更多
Earth’s internal core and crustal magnetic fields,as measured by geomagnetic satellites like MSS-1(Macao Science Satellite-1)and Swarm,are vital for understanding core dynamics and tectonic evolution.To model these i...Earth’s internal core and crustal magnetic fields,as measured by geomagnetic satellites like MSS-1(Macao Science Satellite-1)and Swarm,are vital for understanding core dynamics and tectonic evolution.To model these internal magnetic fields accurately,data selection based on specific criteria is often employed to minimize the influence of rapidly changing current systems in the ionosphere and magnetosphere.However,the quantitative impact of various data selection criteria on internal geomagnetic field modeling is not well understood.This study aims to address this issue and provide a reference for constructing and applying geomagnetic field models.First,we collect the latest MSS-1 and Swarm satellite magnetic data and summarize widely used data selection criteria in geomagnetic field modeling.Second,we briefly describe the method to co-estimate the core,crustal,and large-scale magnetospheric fields using satellite magnetic data.Finally,we conduct a series of field modeling experiments with different data selection criteria to quantitatively estimate their influence.Our numerical experiments confirm that without selecting data from dark regions and geomagnetically quiet times,the resulting internal field differences at the Earth’s surface can range from tens to hundreds of nanotesla(nT).Additionally,we find that the uncertainties introduced into field models by different data selection criteria are significantly larger than the measurement accuracy of modern geomagnetic satellites.These uncertainties should be considered when utilizing constructed magnetic field models for scientific research and applications.展开更多
The principle of genomic selection(GS) entails estimating breeding values(BVs) by summing all the SNP polygenic effects. The visible/near-infrared spectroscopy(VIS/NIRS) wavelength and abundance values can directly re...The principle of genomic selection(GS) entails estimating breeding values(BVs) by summing all the SNP polygenic effects. The visible/near-infrared spectroscopy(VIS/NIRS) wavelength and abundance values can directly reflect the concentrations of chemical substances, and the measurement of meat traits by VIS/NIRS is similar to the processing of genomic selection data by summing all ‘polygenic effects' associated with spectral feature peaks. Therefore, it is meaningful to investigate the incorporation of VIS/NIRS information into GS models to establish an efficient and low-cost breeding model. In this study, we measured 6 meat quality traits in 359Duroc×Landrace×Yorkshire pigs from Guangxi Zhuang Autonomous Region, China, and genotyped them with high-density SNP chips. According to the completeness of the information for the target population, we proposed 4breeding strategies applied to different scenarios: Ⅰ, only spectral and genotypic data exist for the target population;Ⅱ, only spectral data exist for the target population;Ⅲ, only spectral and genotypic data but with different prediction processes exist for the target population;and Ⅳ, only spectral and phenotypic data exist for the target population.The 4 scenarios were used to evaluate the genomic estimated breeding value(GEBV) accuracy by increasing the VIS/NIR spectral information. In the results of the 5-fold cross-validation, the genetic algorithm showed remarkable potential for preselection of feature wavelengths. The breeding efficiency of Strategies Ⅱ, Ⅲ, and Ⅳ was superior to that of traditional GS for most traits, and the GEBV prediction accuracy was improved by 32.2, 40.8 and 15.5%, respectively on average. Among them, the prediction accuracy of Strategy Ⅱ for fat(%) even improved by 50.7% compared to traditional GS. The GEBV prediction accuracy of Strategy Ⅰ was nearly identical to that of traditional GS, and the fluctuation range was less than 7%. Moreover, the breeding cost of the 4 strategies was lower than that of traditional GS methods, with Strategy Ⅳ being the lowest as it did not require genotyping.Our findings demonstrate that GS methods based on VIS/NIRS data have significant predictive potential and are worthy of further research to provide a valuable reference for the development of effective and affordable breeding strategies.展开更多
Four sequence batch reactors（SBRs） fed by fermented sugar cane wastewater were continuously operated under the aerobic dynamic feeding（ADF） mode with different configurations of sludge retention time（SRT）, carbo...Four sequence batch reactors（SBRs） fed by fermented sugar cane wastewater were continuously operated under the aerobic dynamic feeding（ADF） mode with different configurations of sludge retention time（SRT）, carbon and initial biomass concentrations to enrich polyhydroxyalkanoate（PHA） accumulating mixed microbial cultures（MMCs） from municipal activated sludge.The stability of SBRs was investigated besides the enrichment performance. The microbial community structures of the enriched MMCs were analyzed using terminal restriction fragment length polymorphism（T-RFLP）. The optimum operating conditions for the enrichment process were： SRT of 5 days, carbon concentration of 2.52 g COD/L and initial biomass concentration of3.65 g/L. The best enrichment performance in terms of both operating stability and PHA storage ability of enriched cultures（with the maximum PHA content and PHA storage yield（YPHA/S） of61.26% and 0.68 mg COD/mg COD, respectively） was achieved under this condition. Effects of the SRT, carbon concentration and initial biomass concentration on the PHA accumulating MMCs selection process were discussed respectively. A new model including the segmentation of the enrichment process and the effects of SRT on each phase was proposed.展开更多
In covert communications,joint jammer selection and power optimization are important to improve performance.However,existing schemes usually assume a warden with a known location and perfect Channel State Information(...In covert communications,joint jammer selection and power optimization are important to improve performance.However,existing schemes usually assume a warden with a known location and perfect Channel State Information(CSI),which is difficult to achieve in practice.To be more practical,it is important to investigate covert communications against a warden with uncertain locations and imperfect CSI,which makes it difficult for legitimate transceivers to estimate the detection probability of the warden.First,the uncertainty caused by the unknown warden location must be removed,and the Optimal Detection Position(OPTDP)of the warden is derived which can provide the best detection performance(i.e.,the worst case for a covert communication).Then,to further avoid the impractical assumption of perfect CSI,the covert throughput is maximized using only the channel distribution information.Given this OPTDP based worst case for covert communications,the jammer selection,the jamming power,the transmission power,and the transmission rate are jointly optimized to maximize the covert throughput(OPTDP-JP).To solve this coupling problem,a Heuristic algorithm based on Maximum Distance Ratio(H-MAXDR)is proposed to provide a sub-optimal solution.First,according to the analysis of the covert throughput,the node with the maximum distance ratio(i.e.,the ratio of the distances from the jammer to the receiver and that to the warden)is selected as the friendly jammer(MAXDR).Then,the optimal transmission and jamming power can be derived,followed by the optimal transmission rate obtained via the bisection method.In numerical and simulation results,it is shown that although the location of the warden is unknown,by assuming the OPTDP of the warden,the proposed OPTDP-JP can always satisfy the covertness constraint.In addition,with an uncertain warden and imperfect CSI,the covert throughput provided by OPTDP-JP is 80%higher than the existing schemes when the covertness constraint is 0.9,showing the effectiveness of OPTDP-JP.展开更多
Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain c...Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain conditioning factor selection method rather than systematically study this uncertainty issue.Targeted,this study aims to systematically explore the influence rules of various commonly used conditioning factor selection methods on LSP,and on this basis to innovatively propose a principle with universal application for optimal selection of conditioning factors.An'yuan County in southern China is taken as example considering 431 landslides and 29 types of conditioning factors.Five commonly used factor selection methods,namely,the correlation analysis(CA),linear regression(LR),principal component analysis(PCA),rough set(RS)and artificial neural network(ANN),are applied to select the optimal factor combinations from the original 29 conditioning factors.The factor selection results are then used as inputs of four types of common machine learning models to construct 20 types of combined models,such as CA-multilayer perceptron,CA-random forest.Additionally,multifactor-based multilayer perceptron random forest models that selecting conditioning factors based on the proposed principle of“accurate data,rich types,clear significance,feasible operation and avoiding duplication”are constructed for comparisons.Finally,the LSP uncertainties are evaluated by the accuracy,susceptibility index distribution,etc.Results show that:(1)multifactor-based models have generally higher LSP performance and lower uncertainties than those of factors selection-based models;(2)Influence degree of different machine learning on LSP accuracy is greater than that of different factor selection methods.Conclusively,the above commonly used conditioning factor selection methods are not ideal for improving LSP performance and may complicate the LSP processes.In contrast,a satisfied combination of conditioning factors can be constructed according to the proposed principle.展开更多
This article constructs statistical selection procedures for exponential populations that may differ in only the threshold parameters. The scale parameters of the populations are assumed common and known. The independ...This article constructs statistical selection procedures for exponential populations that may differ in only the threshold parameters. The scale parameters of the populations are assumed common and known. The independent samples drawn from the populations are taken to be of the same size. The best population is defined as the one associated with the largest threshold parameter. In case more than one population share the largest threshold, one of these is tagged at random and denoted the best. Two procedures are developed for choosing a subset of the populations having the property that the chosen subset contains the best population with a prescribed probability. One procedure is based on the sample minimum values drawn from the populations, and another is based on the sample means from the populations. An “Indifference Zone” (IZ) selection procedure is also developed based on the sample minimum values. The IZ procedure asserts that the population with the largest test statistic (e.g., the sample minimum) is the best population. With this approach, the sample size is chosen so as to guarantee that the probability of a correct selection is no less than a prescribed probability in the parameter region where the largest threshold is at least a prescribed amount larger than the remaining thresholds. Numerical examples are given, and the computer R-codes for all calculations are given in the Appendices.展开更多
Machine learning(ML)is increasingly applied for medical image processing with appropriate learning paradigms.These applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify sp...Machine learning(ML)is increasingly applied for medical image processing with appropriate learning paradigms.These applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify specific flaws/diseases for diagnosis.The primary concern of ML applications is the precise selection of flexible image features for pattern detection and region classification.Most of the extracted image features are irrelevant and lead to an increase in computation time.Therefore,this article uses an analytical learning paradigm to design a Congruent Feature Selection Method to select the most relevant image features.This process trains the learning paradigm using similarity and correlation-based features over different textural intensities and pixel distributions.The similarity between the pixels over the various distribution patterns with high indexes is recommended for disease diagnosis.Later,the correlation based on intensity and distribution is analyzed to improve the feature selection congruency.Therefore,the more congruent pixels are sorted in the descending order of the selection,which identifies better regions than the distribution.Now,the learning paradigm is trained using intensity and region-based similarity to maximize the chances of selection.Therefore,the probability of feature selection,regardless of the textures and medical image patterns,is improved.This process enhances the performance of ML applications for different medical image processing.The proposed method improves the accuracy,precision,and training rate by 13.19%,10.69%,and 11.06%,respectively,compared to other models for the selected dataset.The mean error and selection time is also reduced by 12.56%and 13.56%,respectively,compared to the same models and dataset.展开更多
基金funded by Science and Technology Project of Hebei Education Department[QN2023085].
文摘Agricultural land development is a pivotal strategy for addressing the global food security crisis.Barren grassland,especially those in mountainous regions,constitutes critical areas where cultivation can substantially enhance land resources.This study highlights the necessity for a precise correlation between land development initiatives and constraints in order to optimize efficiency and enhance the effectiveness of such projects,with the core being the seamless integration of land development engineering and techniques to eliminate agricultural constraints.This study employs a systems engineering approach to classify improvement factors into mobile and fixed categories,elucidating the integration methods of constraint factors.Adhering to the Wooden Barrel Principle,these constraints were rigorously analyzed based on soil quality,land topography,water availability,and agricultural infrastructure.An innovative method of engineering type combination is proposed,which effectively explains the correlation between natural factors combination,project type combination,and target factors combination.It provides a convenient way for the selection of barren grassland development projects and lays a foundation for land planning,development project establishment,program selection,engineering design,and budget preparation.Taking Tang County of China as an example,it is divided into 19 factor improvement areas,a quick reference table of engineering types is established,and 14 main types of engineering combinations are obtained,which lays a foundation for the application of theoretical framework in practice.
文摘A Tibetan art form bridges the past and present and connects cultures around the world.THANGKA,a unique form of Tibetan sacred painting,is gaining prominence globally due to its vibrant colors,exquisite craftsmanship,and profound religious and cultural significance.With the acceleration of globalization,this symbol of Tibetan culture that combines artistic expression with spirituality has become a bridge for cultural exchange between the East and the West.Recently,China Today spoke to Yixi Puncog,art collector and council member of the China Association for Preservation and Development of Tibetan Culture,to learn more about Thangka art,its role in international exchange,and how it is enhancing China’s cultural soft power.
文摘This article interprets why domestication and those translation techniques as addition, deletion and shift are widely adopted by most translators in modem China and how the target socio-cultural factors at the time constrain the translators＇ selection of strategies in literary translation.
基金supported by the National High-Tech R&D Program (863 Program No. 2012AA10A405)the earmarked fund for Modern Agro-industry Technology Research Systemthe National Natural Science Foundation of China (No. 31302182)
文摘Genomic selection is more and more popular in animal and plant breeding industries all around the world, as it can be applied early in life without impacting selection candidates. The objective of this study was to bring the advantages of genomic selection to scallop breeding. Two different genomic selection tools Mix P and gsbay were applied on genomic evaluation of simulated data and Zhikong scallop(Chlamys farreri) field data. The data were compared with genomic best linear unbiased prediction(GBLUP) method which has been applied widely. Our results showed that both Mix P and gsbay could accurately estimate single-nucleotide polymorphism(SNP) marker effects, and thereby could be applied for the analysis of genomic estimated breeding values(GEBV). In simulated data from different scenarios, the accuracy of GEBV acquired was ranged from 0.20 to 0.78 by Mix P; it was ranged from 0.21 to 0.67 by gsbay; and it was ranged from 0.21 to 0.61 by GBLUP. Estimations made by Mix P and gsbay were expected to be more reliable than those estimated by GBLUP. Predictions made by gsbay were more robust, while with Mix P the computation is much faster, especially in dealing with large-scale data. These results suggested that both algorithms implemented by Mix P and gsbay are feasible to carry out genomic selection in scallop breeding, and more genotype data will be necessary to produce genomic estimated breeding values with a higher accuracy for the industry.
基金Supported by Research on Development Strategy,Thought,Model,Approach and Policy of Modern Circular Agriculture in Jiangsu Province(2010ZDAXM016)Philosophical and Social Science Research Project in Colleges and Universities of Jiangsu Province (2011SJD630029)
文摘The paper firstly analyzes selection factors for market subjects of agricultural industrial development in China. From the political aspect, it is required to take account of features of subjects of agricultural industrial development at current stage. From economic aspects, we should adheres to the two-tier management system that integrates unified with separate management on the basis of household contract management in the countryside, and cultivate and foster subject enterprises according to features of most important market subjects in market economy. From natural aspects, it is proposed to consider features of agricultural industry and inherent advantages of agricultural resources in China. From social aspects, it is essential to draw on successful experience of developed countries in developing market subjects of agricultural industry.
文摘The process of globalization requires countries to cultivate talents with global understanding. English classes in primary schools are of fundamental significance in cultivating students' cultural awareness, while English picture books become suitable teaching materials due to their innate advantages of rich pictures and texts. The selection of picture books suitable for cultivating cultural awareness needs to consider multiple factors: the creator's cultural background, the authenticity of cultural content, avoiding "stereotypes", the presentation of human cultural commonness and individuality, and the diversity of picture books. The themes of picture books include but are not limited to ethnic diversity, gender equality and personality education.
文摘The development of a national culture represents the quality of the citizens of this country, the cultural connotation of a national spirit. With the development of society, citizens demand more exuberant cultural services. Therefore, strengthening the construction of public cultural service system is imperative, at the same time, the public cultural system construction is the development and prosperity of socialist advanced culture, and building a harmonious society, the government system of public cultural services for the public and cultural life, which also constitutes a multifaceted innovative public cultural service system Building model in the public service, is the focus of the new era of cultural undertakings .
文摘The agricultural economy has become an important support of the national economy. Based on a comprehensive understanding of the strategic significance of the rural revitalization, the main factors restricting the development of the rural economy were elaborated. The opportunities for the development of the agricultural economy under the background of the rural revitalization strategy were analyzed, and several suggestions were put forward, in order to effectively promote the sustainable and healthy development of Chinas agricultural economy.
文摘Different cultural subjects have different cultural and historical background, and thus inevitably bring difference in people's ideological values and behaviors etc,and even shocks. T oday,cross - cultural adaptation becomes a common social issue,and arouses general concern of the whole society. Influencing factors of cross - cultural adaptation include cultural distance,personality psychology,thinking pattern,values,social living environment,social support,know ledge & skills,pragmatic transfer etc. Based on making clear the problems,cross - cultural adaptation should be realized from multiple aspects.
文摘本文基于国际文化经济学期刊Journal of Cultural Economics 2007—2023年所发表的335篇文献,运用Citespace软件进行文献计量与可视化分析,揭示国际文化经济学研究的热点演进与理论特征。研究发现,国际文化经济学聚焦文化市场定价机制、文化消费行为、文化产业创新及文化参与模式等微观实证领域,形成以新古典经济学为基础的研究范式。相比之下,国内文化经济学研究受制度经济学和幸福经济学影响,更侧重宏观层面的文化与经济关系探讨,强调文化政策对经济发展的形塑作用。通过比较分析,本文认为国内文化经济学研究需加强与国际理论界的对话,在实现多元、多尺度研究方法融合基础上,开展面向中国式现代化的文化经济实践,实现理论路径突破。未来研究应聚焦三大方向:一是深化文化与经济互动的制度分析,深化“双效统一”的机制研究;二是探索数字技术驱动的文化经济转型,分析区块链、人工智能等最新技术对文化生产、传播与消费的重构路径;三是立足中国式现代化建设实践,构建文化赋能社会经济发展的内生驱动模式,为全球文化经济发展和治理贡献中国智慧。
基金ASPEE Agricultural Research and Development Foundation,Malad,Mumbai,India,for research fellowship during the PG course
文摘Radiation induced mutagenesis followed by in vitro selection was employed for salt tolerance in popular Indian sugarcane （Saccharum officinarum L.） cv. CoC-671. Embryogenic calli were gamma irradiated and exposed to different levels of NaCl （42.8, 85.6, 128.3, 171.1,213.9, 256.7, 299.5, or 342.2 mM）. The relative growth rate （RGR） decreased progressively with increasing salt stress and was the least with a salt stress of 256.7 mM （0.25±0.009）, almost 10 fold lesser than the control. The RGR was significantly lower in 85.6 mM and higher salt stressed calli than the control. The survival percent also decreased, with an increase in NaCl concentration. In case of 10 and 20 Gy irradiated calli, regeneration was observed up to 85.6 mM NaCl selection, medium, whereas, higher treatments （128.3 mM and beyond） exhibited browning initially. However, in the subsequent subcultures, regeneration was obtained in the case of 10 and 20 Gy irradiated calli on 128.3 and 171.1 mM NaCl selections. Higher dose of gamma irradiation （40 Gy） also showed regeneration, but only with 85.6 mM NaCI selection. The unirradiated calli regenerated the highest number of plantlets followed by 10 and 20 Gy irradiated calli on salt selection. A total of 147 plantlets were selected from different salt levels. The salt selected plants are being tested for their field performance.
文摘The rapid rise of cyberattacks and the gradual failure of traditional defense systems and approaches led to using artificial intelligence(AI)techniques(such as machine learning(ML)and deep learning(DL))to build more efficient and reliable intrusion detection systems(IDSs).However,the advent of larger IDS datasets has negatively impacted the performance and computational complexity of AI-based IDSs.Many researchers used data preprocessing techniques such as feature selection and normalization to overcome such issues.While most of these researchers reported the success of these preprocessing techniques on a shallow level,very few studies have been performed on their effects on a wider scale.Furthermore,the performance of an IDS model is subject to not only the utilized preprocessing techniques but also the dataset and the ML/DL algorithm used,which most of the existing studies give little emphasis on.Thus,this study provides an in-depth analysis of feature selection and normalization effects on IDS models built using three IDS datasets:NSL-KDD,UNSW-NB15,and CSE–CIC–IDS2018,and various AI algorithms.A wrapper-based approach,which tends to give superior performance,and min-max normalization methods were used for feature selection and normalization,respectively.Numerous IDS models were implemented using the full and feature-selected copies of the datasets with and without normalization.The models were evaluated using popular evaluation metrics in IDS modeling,intra-and inter-model comparisons were performed between models and with state-of-the-art works.Random forest(RF)models performed better on NSL-KDD and UNSW-NB15 datasets with accuracies of 99.86%and 96.01%,respectively,whereas artificial neural network(ANN)achieved the best accuracy of 95.43%on the CSE–CIC–IDS2018 dataset.The RF models also achieved an excellent performance compared to recent works.The results show that normalization and feature selection positively affect IDS modeling.Furthermore,while feature selection benefits simpler algorithms(such as RF),normalization is more useful for complex algorithms like ANNs and deep neural networks(DNNs),and algorithms such as Naive Bayes are unsuitable for IDS modeling.The study also found that the UNSW-NB15 and CSE–CIC–IDS2018 datasets are more complex and more suitable for building and evaluating modern-day IDS than the NSL-KDD dataset.Our findings suggest that prioritizing robust algorithms like RF,alongside complex models such as ANN and DNN,can significantly enhance IDS performance.These insights provide valuable guidance for managers to develop more effective security measures by focusing on high detection rates and low false alert rates.
文摘Mature zygotic embryos of three families of loblolly pine ( Pinus taeda L.) were cultured on callus induction medium containing 8?mg·L -1 2,4 dichlorophenoxyacetic acid (2,4 D), 4?mg·L -1 6 benzyladenine (BA), 4?mg·L -1 kinetin (KT), 500?mg·L -1 casein hydrolysate, and 500?mg·L -1 glutamine for 9 weeks, callus was formed on cotyledons, hypocotyls, and radicles of mature zygotic embryos. Callus was sub cultured on the callus proliferation medium with 1 6?mg·L -1 2,4 dichlorophenoxyacetic acid (2,4 D), 0 8?mg·L -1 6 benzyladenine (BA), 0 8?mg·L -1 kinetin (KT) for 9 weeks. White translucent, glossy, mucilaginous embryogenic callus containing embryogenic suspensor masses (ESM) and immature somatic embryos was obtained, and the highest frequency of explants forming embryogenic callus was 16 9%. Embryogenic suspension cultures were established by culturing embryogenic callus in liquid callus proliferation medium. Liquid cultures containing embryogenic suspension masses and immature somatic embryos were transferred to medium containing abscisic acid (ABA), polyethylene glycols (PEG), or activated charcoal for enhancing the production of cotyledonary somatic embryos. After mature somatic embryos were cultured on medium containing indole butyric acid (IBA), gibberellic acid (GA 3), BA, and activated charcoal and being lowered sucrose concentration for 4～12 weeks, somatic embryos germinated to form regenerated plantlets. Seventy one regenerated plantlets were transferred to a perlits∶peatmoss∶vermiculate (1∶1∶1) soil mixture, and 23 plantlets survived in the field.
基金supported by the National Natural Science Foundation of China(42250101)the Macao Foundation。
文摘Earth’s internal core and crustal magnetic fields,as measured by geomagnetic satellites like MSS-1(Macao Science Satellite-1)and Swarm,are vital for understanding core dynamics and tectonic evolution.To model these internal magnetic fields accurately,data selection based on specific criteria is often employed to minimize the influence of rapidly changing current systems in the ionosphere and magnetosphere.However,the quantitative impact of various data selection criteria on internal geomagnetic field modeling is not well understood.This study aims to address this issue and provide a reference for constructing and applying geomagnetic field models.First,we collect the latest MSS-1 and Swarm satellite magnetic data and summarize widely used data selection criteria in geomagnetic field modeling.Second,we briefly describe the method to co-estimate the core,crustal,and large-scale magnetospheric fields using satellite magnetic data.Finally,we conduct a series of field modeling experiments with different data selection criteria to quantitatively estimate their influence.Our numerical experiments confirm that without selecting data from dark regions and geomagnetically quiet times,the resulting internal field differences at the Earth’s surface can range from tens to hundreds of nanotesla(nT).Additionally,we find that the uncertainties introduced into field models by different data selection criteria are significantly larger than the measurement accuracy of modern geomagnetic satellites.These uncertainties should be considered when utilizing constructed magnetic field models for scientific research and applications.
基金supported by the National Natural Science Foundation of China(32160782 and 32060737).
文摘The principle of genomic selection(GS) entails estimating breeding values(BVs) by summing all the SNP polygenic effects. The visible/near-infrared spectroscopy(VIS/NIRS) wavelength and abundance values can directly reflect the concentrations of chemical substances, and the measurement of meat traits by VIS/NIRS is similar to the processing of genomic selection data by summing all ‘polygenic effects' associated with spectral feature peaks. Therefore, it is meaningful to investigate the incorporation of VIS/NIRS information into GS models to establish an efficient and low-cost breeding model. In this study, we measured 6 meat quality traits in 359Duroc×Landrace×Yorkshire pigs from Guangxi Zhuang Autonomous Region, China, and genotyped them with high-density SNP chips. According to the completeness of the information for the target population, we proposed 4breeding strategies applied to different scenarios: Ⅰ, only spectral and genotypic data exist for the target population;Ⅱ, only spectral data exist for the target population;Ⅲ, only spectral and genotypic data but with different prediction processes exist for the target population;and Ⅳ, only spectral and phenotypic data exist for the target population.The 4 scenarios were used to evaluate the genomic estimated breeding value(GEBV) accuracy by increasing the VIS/NIR spectral information. In the results of the 5-fold cross-validation, the genetic algorithm showed remarkable potential for preselection of feature wavelengths. The breeding efficiency of Strategies Ⅱ, Ⅲ, and Ⅳ was superior to that of traditional GS for most traits, and the GEBV prediction accuracy was improved by 32.2, 40.8 and 15.5%, respectively on average. Among them, the prediction accuracy of Strategy Ⅱ for fat(%) even improved by 50.7% compared to traditional GS. The GEBV prediction accuracy of Strategy Ⅰ was nearly identical to that of traditional GS, and the fluctuation range was less than 7%. Moreover, the breeding cost of the 4 strategies was lower than that of traditional GS methods, with Strategy Ⅳ being the lowest as it did not require genotyping.Our findings demonstrate that GS methods based on VIS/NIRS data have significant predictive potential and are worthy of further research to provide a valuable reference for the development of effective and affordable breeding strategies.
基金supported by the National Natural Science Foundation of China(No.51378142)the Program for New Century Excellent Talents in University(No.NCET-12-0156)+1 种基金the Open Project of the State Key Laboratory of Urban Water ResourceEnvironment(Harbin institute of Technology)(No.2015DX10)
文摘Four sequence batch reactors（SBRs） fed by fermented sugar cane wastewater were continuously operated under the aerobic dynamic feeding（ADF） mode with different configurations of sludge retention time（SRT）, carbon and initial biomass concentrations to enrich polyhydroxyalkanoate（PHA） accumulating mixed microbial cultures（MMCs） from municipal activated sludge.The stability of SBRs was investigated besides the enrichment performance. The microbial community structures of the enriched MMCs were analyzed using terminal restriction fragment length polymorphism（T-RFLP）. The optimum operating conditions for the enrichment process were： SRT of 5 days, carbon concentration of 2.52 g COD/L and initial biomass concentration of3.65 g/L. The best enrichment performance in terms of both operating stability and PHA storage ability of enriched cultures（with the maximum PHA content and PHA storage yield（YPHA/S） of61.26% and 0.68 mg COD/mg COD, respectively） was achieved under this condition. Effects of the SRT, carbon concentration and initial biomass concentration on the PHA accumulating MMCs selection process were discussed respectively. A new model including the segmentation of the enrichment process and the effects of SRT on each phase was proposed.
基金supported by the CAS Project for Young Scientists in Basic Research under Grant YSBR-035Jiangsu Provincial Key Research and Development Program under Grant BE2021013-2.
文摘In covert communications,joint jammer selection and power optimization are important to improve performance.However,existing schemes usually assume a warden with a known location and perfect Channel State Information(CSI),which is difficult to achieve in practice.To be more practical,it is important to investigate covert communications against a warden with uncertain locations and imperfect CSI,which makes it difficult for legitimate transceivers to estimate the detection probability of the warden.First,the uncertainty caused by the unknown warden location must be removed,and the Optimal Detection Position(OPTDP)of the warden is derived which can provide the best detection performance(i.e.,the worst case for a covert communication).Then,to further avoid the impractical assumption of perfect CSI,the covert throughput is maximized using only the channel distribution information.Given this OPTDP based worst case for covert communications,the jammer selection,the jamming power,the transmission power,and the transmission rate are jointly optimized to maximize the covert throughput(OPTDP-JP).To solve this coupling problem,a Heuristic algorithm based on Maximum Distance Ratio(H-MAXDR)is proposed to provide a sub-optimal solution.First,according to the analysis of the covert throughput,the node with the maximum distance ratio(i.e.,the ratio of the distances from the jammer to the receiver and that to the warden)is selected as the friendly jammer(MAXDR).Then,the optimal transmission and jamming power can be derived,followed by the optimal transmission rate obtained via the bisection method.In numerical and simulation results,it is shown that although the location of the warden is unknown,by assuming the OPTDP of the warden,the proposed OPTDP-JP can always satisfy the covertness constraint.In addition,with an uncertain warden and imperfect CSI,the covert throughput provided by OPTDP-JP is 80%higher than the existing schemes when the covertness constraint is 0.9,showing the effectiveness of OPTDP-JP.
基金funded by the Natural Science Foundation of China(Grant Nos.42377164 and 41972280)the Badong National Observation and Research Station of Geohazards(Grant No.BNORSG-202305).
文摘Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain conditioning factor selection method rather than systematically study this uncertainty issue.Targeted,this study aims to systematically explore the influence rules of various commonly used conditioning factor selection methods on LSP,and on this basis to innovatively propose a principle with universal application for optimal selection of conditioning factors.An'yuan County in southern China is taken as example considering 431 landslides and 29 types of conditioning factors.Five commonly used factor selection methods,namely,the correlation analysis(CA),linear regression(LR),principal component analysis(PCA),rough set(RS)and artificial neural network(ANN),are applied to select the optimal factor combinations from the original 29 conditioning factors.The factor selection results are then used as inputs of four types of common machine learning models to construct 20 types of combined models,such as CA-multilayer perceptron,CA-random forest.Additionally,multifactor-based multilayer perceptron random forest models that selecting conditioning factors based on the proposed principle of“accurate data,rich types,clear significance,feasible operation and avoiding duplication”are constructed for comparisons.Finally,the LSP uncertainties are evaluated by the accuracy,susceptibility index distribution,etc.Results show that:(1)multifactor-based models have generally higher LSP performance and lower uncertainties than those of factors selection-based models;(2)Influence degree of different machine learning on LSP accuracy is greater than that of different factor selection methods.Conclusively,the above commonly used conditioning factor selection methods are not ideal for improving LSP performance and may complicate the LSP processes.In contrast,a satisfied combination of conditioning factors can be constructed according to the proposed principle.
文摘This article constructs statistical selection procedures for exponential populations that may differ in only the threshold parameters. The scale parameters of the populations are assumed common and known. The independent samples drawn from the populations are taken to be of the same size. The best population is defined as the one associated with the largest threshold parameter. In case more than one population share the largest threshold, one of these is tagged at random and denoted the best. Two procedures are developed for choosing a subset of the populations having the property that the chosen subset contains the best population with a prescribed probability. One procedure is based on the sample minimum values drawn from the populations, and another is based on the sample means from the populations. An “Indifference Zone” (IZ) selection procedure is also developed based on the sample minimum values. The IZ procedure asserts that the population with the largest test statistic (e.g., the sample minimum) is the best population. With this approach, the sample size is chosen so as to guarantee that the probability of a correct selection is no less than a prescribed probability in the parameter region where the largest threshold is at least a prescribed amount larger than the remaining thresholds. Numerical examples are given, and the computer R-codes for all calculations are given in the Appendices.
基金the Deanship of Scientifc Research at King Khalid University for funding this work through large group Research Project under grant number RGP2/421/45supported via funding from Prince Sattam bin Abdulaziz University project number(PSAU/2024/R/1446)+1 种基金supported by theResearchers Supporting Project Number(UM-DSR-IG-2023-07)Almaarefa University,Riyadh,Saudi Arabia.supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(No.2021R1F1A1055408).
文摘Machine learning(ML)is increasingly applied for medical image processing with appropriate learning paradigms.These applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify specific flaws/diseases for diagnosis.The primary concern of ML applications is the precise selection of flexible image features for pattern detection and region classification.Most of the extracted image features are irrelevant and lead to an increase in computation time.Therefore,this article uses an analytical learning paradigm to design a Congruent Feature Selection Method to select the most relevant image features.This process trains the learning paradigm using similarity and correlation-based features over different textural intensities and pixel distributions.The similarity between the pixels over the various distribution patterns with high indexes is recommended for disease diagnosis.Later,the correlation based on intensity and distribution is analyzed to improve the feature selection congruency.Therefore,the more congruent pixels are sorted in the descending order of the selection,which identifies better regions than the distribution.Now,the learning paradigm is trained using intensity and region-based similarity to maximize the chances of selection.Therefore,the probability of feature selection,regardless of the textures and medical image patterns,is improved.This process enhances the performance of ML applications for different medical image processing.The proposed method improves the accuracy,precision,and training rate by 13.19%,10.69%,and 11.06%,respectively,compared to other models for the selected dataset.The mean error and selection time is also reduced by 12.56%and 13.56%,respectively,compared to the same models and dataset.
