Path to Support Development of Production and Operation of Big Grain Production Households——Based on Investigation of Heilongjiang Province

Developing production and operation in scales in the major grain producing areas is the direction of the paper. Seizing the opportunity of modem agriculture comprehensive reform in two plains （Songnen Plain and Sanjiang Plain） of Heilongjiang Province and supporting to build a new type of production and management based on the big grain production householding, which plays demonstration and leading roles, have an important strategic position in improving agricultural comprehensive production capacity and ensuring national food security. In this paper, based on the survey data about the big grain production households production operations and analyses of the obstacles in expansion of production in Heilongjiang Province, specific suggestions in supporting the development of the big grain production household were put forward, such as, increasing agricultural production socialized level; perfecting the service system of land transferring; improving financial policies and farmer-friendly policy measures and perfecting the agriculture socialized service system.

The Value Insistence of the Cultural Production in the Big Data Era

The ultimate value of cultural production should be realizing human's comprehensive and free development,and deconstructing the ultimate value would result in human alienation.In the era of big data,every domain of human's social life,even the mode of thinking,has been transformed significantly.However,when the big data technology entirely penetrates the field of cultural production especially inducts the cultural production depending on the demand forecasting techniques,it would inevitably lead to a worry about value of the cultural production.This paper formulates that the cultural production's essence in the era of big data remains for the purpose of maximizing profit of commercial manipulation based on the modeling analysis of cultural production mechanism in the big data times.If the tendency is not corrected,the two main factors of cultural consumerism prevalence and the instrumental reason dictatorship will gradually deconstruct the ultimate value of cultural production and bring about the alienation of human being.For the sake of avoiding the trend,we should cope with two relationships:one is the people as a means and as a purpose;the other is the instrumental reason and the value rationality,finally giving rise to human's comprehensive and free development rather than human alienation.

Challenges and Access to Production and Distribution of News in the Era of Big Data

With the strategy of media integration,transformation and upgrading of media has become an important issue.In the era of big data,due to the dual impact of data and technology,the media brings both challenges and opportunities.The paper traces the characteristics of the era of big data,focuses on analyzing the challenges and opportunities in the media industry,and analyzes the transformation and upgrading of the media from the dimensions of news production and distribution to better realize the social functions of media in the era of big data.Some strategic suggestions are put forward to improve the propagation effect.

Product Specification Analysis for Modular Product Design Using Big Sales Data

Big data on product sales are an emerging resource for supporting modular product design to meet diversified customers’requirements of product specification combinations.To better facilitate decision-making of modular product design,correlations among specifications and components originated from customers’conscious and subconscious preferences can be investigated by using big data on product sales.This study proposes a framework and the associated methods for supporting modular product design decisions based on correlation analysis of product specifications and components using big sales data.The correlations of the product specifications are determined by analyzing the collected product sales data.By building the relations between the product components and specifications,a matrix for measuring the correlation among product components is formed for component clustering.Six rules for supporting the decision making of modular product design are proposed based on the frequency analysis of the specification values per component cluster.A case study of electric vehicles illustrates the application of the proposed method.

The Path to Reshaping the Structure and Chain System of the Publishing Industry in the Era of Big Data

Today,we are living in the era of“big data”where massive amounts of data are used for quantitative decisions and communication management.With the continuous penetration of big data-based intelligent technology in all fields of human life,the enormous commercial value inherent in the data industry has become a crucial force that drives the aggregation of new industries.For the publishing industry,the introduction of big data and relevant intelligent technologies,such as data intelligence analysis and scenario services,into the structure and value system of the publishing industry,has become an effective path to expanding and reshaping the demand space of publishing products,content decisions,workflow chain,and marketing direction.In the integration and reconstruction of big data,cloud computing,artificial intelligence,and other related technologies,it is expected that a generalized publishing industry pattern dominated by virtual interaction will be formed in the future.

Assessing the Applicability of Multi-Source Precipitation Products over the Chinese Mainland and Its Seven Regions

Satellite-based and reanalysis precipitation products provide valuable information for various applications.However,their performance varies widely across regions due to different data sources and production processes.This paper evaluated the daily performance of four precipitation products(MSWEP,ERA5,PERSIANN,and TRMM)for seven regions of the Chinese mainland,using observations from 2462 ground stations across the country as a benchmark.We used four statistical and four classification indicators to describe their spatial and temporal accuracy,and capability to detect precipitation events while analyzing their applicability.The results show that according to the precipitation char-acteristics and accuracy of different types of precipitation products over the Chinese mainland,MSWEP was the most suitable product over the Chinese mainland,having the lowest root mean square error and mean absolute error,along with the highest coefficient of determination.It was followed by TRMM and ERA5,whereas PERSIANN lagged behind in terms of performance.In terms of different regions,MSWEP still performed well,especially in North China and East China.The accuracy of the four precipitation products was relatively low in the summer months,and they all overestimated in the northwest region.In other months,MSWEP and TRMM were better than PERSIANN and ERA5.The four precipitation products had good detection performance over the Chinese mainland,with probability of detection above 0.5.However,with the increase of precipitation threshold,the detection capability of the four products decreased,and MSWEP and ERA5 had good detection capability for moderate rain.TRMM’s detection capability for heavy rain and rainstorms was better than that of the other three products,and PERSIANN’s detection capability for moderate rain,heavy rain and rainstorms was relatively poor,with a large deviation.

Comprehensive applicability evaluation of four precipitation products at multiple spatiotemporal scales in Northwest China

Precipitation plays a crucial role in the water cycle of Northwest China.Obtaining accurate precipitation data is crucial for regional water resource management,hydrological forecasting,flood control and drought relief.Currently,the applicability of multi-source precipitation products for long time series in Northwest China has not been thoroughly evaluated.In this study,precipitation data from 183 meteorological stations in Northwest China from 1979 to 2020 were selected to assess the regional applicability of four precipitation products(the fifth generation of European Centre for Medium-Range Weather Forecasts(ECMWF)atmospheric reanalysis of the global climate(ERA5),Global Precipitation Climatology Centre(GPCC),Climatic Research Unit gridded Time Series Version 4.07(CRU TS v4.07,hereafter CRU),and Tropical Rainfall Measuring Mission(TRMM))based on the following statistical indicators:correlation coefficient,root mean square error(RMSE),relative bias(RB),mean absolute error(MAE),probability of detection(POD),false alarm ratio(FAR),and equitable threat score(ETS).The results showed that precipitation in Northwest China was generally high in the east and low in the west,and exhibited an increasing trend from 1979 to 2020.Compared with the station observations,ERA5 showed a larger spatial distribution difference than the other products.The overall overestimation of multi-year average precipitation was approximately 200.00 mm and the degree of overestimation increased with increasing precipitation intensity.The multi-year average precipitation of GPCC and CRU was relatively close to that of station observations.The trend of annual precipitation of TRMM was overestimated in high-altitude regions and the eastern part of Lanzhou with more precipitation.At the monthly scale,GPCC performed well but underestimated precipitation in the Tarim Basin(RB=-4.11%),while ERA5 and TRMM exhibited poor accuracy in high-altitude regions.ERA5 had a large bias(RB≥120.00%)in winter months and a strong dispersion(RMSE≥35.00 mm)in summer months.TRMM showed a relatively low correlation with station observations in winter months(correlation coefficients≤0.70).The capture performance analysis showed that ERA5,GPCC,and TRMM had lower POD and ETS values and higher FAR values in Northwest China as the precipitation intensity increased.ERA5 showed a high capture performance for small precipitation events and a slower decreasing trend of POD as the precipitation intensity increased.GPCC had the lowest FAR values.TRMM was statistically ineffective for predicting the occurrence of daily precipitation events.The findings provide a reference for data users to select appropriate datasets in Northwest China and for data developers to develop new precipitation products in the future.

Big-BALB/c小鼠亚系选育前后的抗体制备效率比较研究

目的比较利用BALB/c和Big-BALB/c(简称B-BALB/c)两种亚系小鼠制备鼠痘及鼠肝炎单克隆抗体的效率,为今后通过杂交瘤进行体内诱导单克隆抗体制备时实验动物的选择提供参考。方法从常规繁育的BALB/c小鼠群体中选择4周龄体重超过正常动物5%(后期选种标准为超过10%)的个体进行选种并单独繁育,经10代选育制备B-BALB/c小鼠亚系。选择10~11周龄、雌雄各半的BALB/c小鼠和B-BALB/c小鼠各40只,分别接种用液体石蜡预处理后的鼠痘单克隆抗体杂交瘤细胞株G23或鼠肝炎单克隆抗体杂交瘤细胞株Y15,然后通过体内诱生法获取含单克隆抗体的小鼠腹水,利用间接ELISA法检验抗体效价,按照品系、性别和接种杂交瘤类型对小鼠进行分组,分析腹水产量、抗体效价和抗体产量以评估两种亚系小鼠的抗体制备效率。结果经10代选育后获得的10周龄雄性和雌性B-BALB/c小鼠体重分别比同周龄BALB/c小鼠增加了22.3%和12.8%。抗体制备过程中,B-BALB/c小鼠的耐受力比BALB/c小鼠更好,能够适应二次腹水采集;与BALB/c小鼠相比,B-BALB/c小鼠腹水产量和抗体效价均显著提高,尤以杂交瘤细胞株G23接种组更明显(均P<0.0001)。接种杂交瘤细胞株G23或Y15后,B-BALB/c小鼠的平均抗体产量(14.99×10^(4)U和33.22×10^(4)U)高于BALB/c小鼠(5.33×10^(4)U和19.31×10^(4)U)(均P<0.01)。接种杂交瘤细胞株G23后,B-BALB/c小鼠的平均单位体重的抗体产量(0.55×10^(4)U/g)高于BALB/c小鼠(0.23×10^(4)U/g)(P<0.0001)。接种杂交瘤细胞株Y15后,雌性B-BALB/c和BALB/c小鼠的单位体重抗体产量高于同亚系的雄性B-BALB/c小鼠(均P<0.01)。结论B-BALB/c小鼠在单克隆抗体体内诱导制备中可作为BALB/c小鼠的替代选择,能够达到减少实验动物使用数量、降低人力成本并提高抗体制备效率的目的。

Building a Productive Domain-Specific Cloud for Big Data Processing and Analytics Service

Cloud Computing as a disruptive technology, provides a dynamic, elastic and promising computing climate to tackle the challenges of big data processing and analytics. Hadoop and MapReduce are the widely used open source frameworks in Cloud Computing for storing and processing big data in the scalable fashion. Spark is the latest parallel computing engine working together with Hadoop that exceeds MapReduce performance via its in-memory computing and high level programming features. In this paper, we present our design and implementation of a productive, domain-specific big data analytics cloud platform on top of Hadoop and Spark. To increase user’s productivity, we created a variety of data processing templates to simplify the programming efforts. We have conducted experiments for its productivity and performance with a few basic but representative data processing algorithms in the petroleum industry. Geophysicists can use the platform to productively design and implement scalable seismic data processing algorithms without handling the details of data management and the complexity of parallelism. The Cloud platform generates a complete data processing application based on user’s kernel program and simple configurations, allocates resources and executes it in parallel on top of Spark and Hadoop.

Management and instant query of distributed oil and gas production dynamic data

The multidimensional analysis engine data management platform is constructed using big data distributed storage and parallel computing,data warehouse modeling technology,realizing the optimal management and instant query of distributed oil and gas production dynamic big data.The centralized management and quick response of the production data of more than 36×10^4 oil,gas and water wells is realized.Multidimensional analysis subject model of oil,gas and water well production is built to pretreat the relevant data.At the level of China National Petroleum Corporation(CNPC),the rapid analysis and applications such as oil and gas production tracking,early production warning of key oilfields,analysis of low production wells and long shutdown wells,classification of reservoir development laws have been realized,and the processing time has been shortened from 1 d to 5 s.The basic unit of oil and gas production analysis is refined from oilfield to single well,making the production management more detailed.The process can be traced step by step according to CNPC,oil field company,field,block and single well,and the oil and gas production performance of each unit can be mastered in real time.

Public Management Innovation in the Era of Big Data

In the Internet era,computer technology and data analysis technology have been widely applied to people’s work and their daily lives.Big data technology has brought great influence to public management,providing efficient and convenient public services and improving the ability to cope with crises of public opinion[1].However,in the actual public management practice,there are widespread problems such as single practice model and poor data openness.Based on this,the article expounds the relevant contents of big data,introduces the role of big data in public management,and studies the public management innovation in the era of big data.

Theory and practice of urban spatial planning in big data era- Taking Hunan as an example

In recent years, the rapid development of information and communication technologies accelerates the arrival of the big data era. But it still needs to be explored further for what large data brought on the impact of urban planning and how to respond to the implementation and formation of urban planning to the end. We will research from two aspects of the practice study and formation of urban planning in Hunan to discuss based on brief review of research about urban space big data era.

Hadoop + Spark Platform Based on Big Data System Design of Agricultural Product Price Analysis and Prediction by HoltWinters

In the market of agricultural products, the price of agricultural products is affected by production cost, market supply and other factors. In order to obtain the market information of agricultural products, the price fluctuation can be analyzed and predicted. A distributed big data software platform based on Hadoop, Hive and Spark is proposed to analyze and forecast agricultural price data. Firstly, Hadoop, Hive and Spark big data frameworks were built to store the data information of agricultural products crawled into MYSQL. Secondly, the information of agricultural products crawled from MYSQL was exported to a text file, uploaded to HDFS, and mapped to spark SQL database. The data was cleaned and improved by Holt-Winters (three times exponential smoothing method) model to predict the price of agricultural products in the future. The data cleaned by spark SQL was imported and predicted by improved Holt-Winters into MYSQL database. The technologies of pringMVC, Ajax and Echarts were used to visualize the data.

大数据牵引背景下的服装设计开发模式

在大数据牵引背景下,随着数据量呈爆炸式增长和大数据应用的不断深化,大数据资源以数据要素的形式牵引着传统服装设计模式的改变。通过对服装设计相关的大数据进行分类甄别,探讨大数据在多方面赋能服装设计协同价值创造,多维度比较传统服装设计开发与以大数据牵引的服装设计开发模式,以大数据赋能服装精准设计,构建基于大数据引导下的服装设计框架;将该框架应用于MZ品牌的开发案例中,从商品企划、设计开发和预售下单3个方面论述大数据在服装设计开发中的实践应用。大数据时代设计模式的演变将更加聚焦于设计师与海量数据之间的相互作用,应用大数据牵引服装设计开发模式的迭代,可实现更高精准度和更快反应能力的服装设计开发。

大数据背景下全科医学信息课程改革的必要性及策略

大数据在医疗领域快速发展,无论从世界医疗科技趋势、国家政策方针,还是市场效益、工作效率上来看,大数据对全科医学是非常重要的。基于大数据技术的人工智能在全科领域应用广泛,如学生的校园管理、全科医疗服务、全科医生的规范化培训及继续教育等。同时医疗大数据又涉及到国家安全及个人隐私等道德法律问题。目前全科医学本科的信息课程缺乏大数据的内容,没有跟上医学信息发展形势。分析大数据背景下全科医学信息课程改革的背景、作用与意义,并分析全科医学信息的教育现状、发展及趋势,对课程改革的策略进行探讨,从而提供对全科医学信息课程改革具有帮助的意见和建议。

大数据驱动的企业与用户互动创新:理论框架与前沿课题

大数据驱动的企业与用户互动创新已成为企业洞察市场和用户动态、提升创新敏捷性和适应性的重要模式,其关键因素和作用机制日益成为创新、营销和信息系统等领域的热点议题。结合系统性综述设计和关键词共现分析,梳理大数据情境下企业与用户互动创新的研究洞见。针对情境和工具如何影响领先用户与普通用户关系及二者的相互作用机制两个研究缺口,提出大数据驱动的企业与用户互动创新“条件—路径—绩效”理论框架。依据该理论框架,结合文献和案例证据,重点阐述在什么情境和工具条件下企业与领先用户、普通用户以何种互动创新路径影响创新产品和大数据合作资产,由此形成理论创新。分析结果表明,互动创新路径选择本质是在异质性情境和工具条件下,企业在创新新颖性—泛用性以及数据分析成本—收益之间的动态权衡;两类创新路径的动态变化由互动创新工具成熟度、创新主导权的变更所触发。最后,进一步提炼出大数据驱动的企业与用户互动创新理论研究的三类前沿课题,并讨论其理论和实践意义。

农业新质生产力:理论内涵、现实基础及提升路径

新质生产力是实现高质量发展的根本动力。农业新质生产力既具有新质生产力一般特征,又兼具不平衡性、开发与保护的二重性、资源禀赋的先决性及创新主体多元性等特殊性。我国农业新质生产力发展具有一定基础,但要素错配、生产关系失调、人力资本不足、资源环境约束、观念冲突束缚等因素对提升农业全要素生产率形成挑战。加快农业绿色转型、全面深化农村改革、畅通国内国外两个市场、坚持技术研发与应用并重、构建新型农业经营体系、完善新质人才培养环节,有助于激发农业新质生产力潜能。

大数据时代的农业发展:国际前沿与中国实践

随着信息革命、数据革命的到来,农业生产已经发生了翻天覆地的变化。在新时代,传统农业逐步遇到瓶颈,亟待向着精准农业、智慧农业等新型数字农业发展模式转型。21世纪以来,世界多国探索了农业大数据的十余个领域,发展了一系列数据收集、存储、分析的技术和方法,并取得了显著的应用成效。中国面临着人口多、耕地少等一系列问题,应紧跟技术进步,结合中国国情和农业特征,加快发展农业新质生产力,在农业大数据的基础研究、行业标准、基础设施、供应链管理、金融保险等方面着力,促进农业高质量发展,加快建设农业强国,促进农业农村现代化。

新时代背景下新质生产力的理论及实践

新质生产力是2023年9月习近平总书记在黑龙江考察时提出的全新理念,总书记强调要“整合科技创新资源,引领发展战略性新兴产业和未来产业,加快形成新质生产力”。新质生产力是科技创新在其中发挥主导作用的生产力,包含一切能够促进新兴产业和未来产业高质量发展的生产要素及形态。这是在传统生产力形式不足以支持我国新时代产业爬坡、转型升级与高质量发展现实需求背景下提出的全新理念,是我国构建“双循环”新发展格局和实现第二个百年奋斗目标的科学指引。新质生产力是一种改造社会生产方式,具有引领新兴产业及未来产业发展、提供经济增长新动能、提高生产效率、推动产业升级、创造就业机会、促进绿色低碳发展等多个维度的重要作用。培育新质生产力,应当围绕加强技术创新、聚焦人力资本积累、改善创业环境、促进国际合作等多个方面综合发力。