The Interweaving of Southern Tradition and Postmodern Temper—Time and Place in Richard Ford's Sportswriter

Debate on whether American Southern Literature still exists in the postmodern era poses a hot topic in contemporary literary world. Among the many southern-born writers, Richard Ford publicly denied to be labeled as a southern writer. The author of this paper holds a close study of how time and place, two major traditional southern themes are treated in Richard Ford's Sportswriter, and draws the conclusion that despite the southern staples embedded in the novel, Richard Ford, as a representative of postmodern writers, works for a national or even universal writing by successfully fusing southern tradition and postmodern temper in a crossroad of history.

DIAGNOSTICS OF FATIGUE CRACK IN ULTERIOR PLACES OF LARGER-SCALE OVERLOADED SUPPORTING SHAFT BASED ON TIME SERIES AND NEURAL NETWORKS

To improve the diagnosis accuracy and self-adaptability of fatigue crack in ulterior place of the supporting shaft, time series and neural network are attempted to be applied in research on diag-nosing the fatigue crack’s degree based on analyzing the vibration characteristics of the supporting shaft. By analyzing the characteristic parameter which is easy to be detected from the supporting shaft’s exterior, the time series model parameter which is hypersensitive to the situation of fatigue crack in ulterior place of the supporting shaft is the target input of neural network, and the fatigue crack’s degree value of supporting shaft is the output. The BP network model can be built and net-work can be trained after the structural parameters of network are selected. Furthermore, choosing the other two different group data can test the network. The test result will verify the validity of the BP network model. The result of experiment shows that the method of time series and neural network are effective to diagnose the occurrence and the development of the fatigue crack’s degree in ulterior place of the supporting shaft.

Modeling of Fuel Elements Cycling System in Pebble Bed Reactor Based on Timed Places Control Petri Nets

Pebble bed reactors use cycling scheme of spherical fuel elements relying on fuel elements cycling system (FECS). The structure and control logic of FECS are very complex. Each control link has strict requirements on time and sequence. This increases the difficulties of description and analysis. In this paper, timed places control Petri nets (TPCPN) is applied for the modeling of FECS. On this basis the simulation of two important processes, namely uploading fuel elements into the core for the first time and emptying the core is finished by simulation software Arena. The results show that as TPCPN is able to describe different kinds of logic relationship and has time properties and control properties, it’s very suitable for the modeling and analysis of FECS.

The Big Bang as the Creative Force of the Creation of the Universe

The paper considers the mechanism of the Big Bang energy influence on the creation of space-time fields of four structures of the Universe from the 1st type Ether (the Main Field and three spheres of the Relic). It explains how the Big Bang energy leads to the processes of “melting” in these structures, generating emergent properties that are different from their properties before the Big Bang. The key role of the Big Bang in completing the process of formation of 70% of DE is emphasized. It is shown that the Big Bang preceded the emergence of the furcation point, which chose several directions for the creation of cosmic matter—it was the combined efforts of these directions that created the visible worlds. The principle of dynamic equilibrium is considered the main criterion of the space-time field, in contrast to other physical fields, which is a necessary prerequisite for the quantization of the gravitational field. A spin particle is introduced, capable of emitting special particles—spitons, the characteristics of which are associated with the topology of the Mobius strip and determine the spinor properties of gravitational fields. The mechanism of interaction of particles of the 2nd type of Ether with the fields of space-time is described, allowing the creation of matter first and then the materiality of visible worlds. At the same time, the role of the “matter-negotiator” in the creation process of visible worlds of the Universe is especially highlighted. Since the new properties of gravitational fields go beyond Einstein’s standard theory of gravity, it is proposed to build a new theory of space-time that generalizes it and has a clear geometric interpretation. The proposed theory is based on the action built on a full set of invariants of the Ricci tensor. Within the framework of the Poincaré theory, the classification of furcation points is considered. The processes at the furcation point are described by the Gauss-Laplace curve, for which the principle of conservation of probability density is introduced when considering the transition at the furcation point to four different directions of development.

Time and Place with Premier

Ravi Shankar Narasimhan,executive editor of China Daily's overseas editions,was one of 70-plus foreign experts invited to the Great Hall of the People on January 21 for a symposium and a Chinese New Year dinner with Premier Li Keqiang and senior State leaders.

Inter-Purchase Time Prediction Based on Deep Learning

Inter-purchase time is a critical factor for predicting customer churn.Improving the prediction accuracy can exploit consumer’s preference and allow businesses to learn about product or pricing plan weak points,operation issues,as well as customer expectations to proactively reduce reasons for churn.Although remarkable progress has been made,classic statistical models are difficult to capture behavioral characteristics in transaction data because transaction data are dependent and short-,medium-,and long-term data are likely to interfere with each other sequentially.Different from literature,this study proposed a hybrid inter-purchase time prediction model for customers of on-line retailers.Moreover,the analysis of differences in the purchase behavior of customers has been particularly highlighted.The integrated self-organizing map and Recurrent Neural Network technique is proposed to not only address the problem of purchase behavior but also improve the prediction accuracy of inter-purchase time.The permutation importance method was used to identify crucial variables in the prediction model and to interpret customer purchase behavior.The performance of the proposed method is evaluated by comparing the prediction with the results of three competing approaches on the transaction data provided by a leading e-retailer in Taiwan.This study provides a valuable reference for marketing professionals to better understand and develop strategies to attract customers to shorten their inter-purchase times.

Research on Optimization of Component Stock

A set of model is established to optimize BSW Company’s component stock. By analyzing the company’s current part stock condition in terms of the occupation of capitals in the precondition of continuous production, it describes how to control the purchase parameters of import parts. The model describes how to adjust slightly product output sequence and how to control the components’ purchase parameters: purchasing risk time and purchase order quantity. Then simulation is developed to illustrate the model.

The Dance-Ephemeral:With Michel Serres

Short,momentary,temporary,transient,precarious,and labile are adjectives that the current post-pandemic,ecological,climatic,war,political,economic,and social contingencies have accustomed us to employ almost compulsively and indiscriminately by now,and that,beyond everything,are synonyms inter-implicit with and in the ephemerality,which deserves reconsideration in its literalness as epìheméra(for a day),that can take place through a sort of its“double”,not quite mainstream but nonetheless suggestive and perhaps even effective,such as the artistic one of dance.Therefore,it is worth pausing to try and see which streaks/implications of the ephemerality itself the dance-ephemeral conveys and/or produces:the neuralgic concretions that the latter seems to me to involve and permeate,in a perspective of re-cognition/re-discovery/awareness,are time,space and the body,evidently inter-implicated.

自我建构视阈下时间压力对消费者购买意愿的影响

电子商务平台通过限时、限量策略激发消费者购买意愿的现象非常普遍,饥饿营销已发展成现代企业营销的重要手段。时间压力对消费者购买意愿具有很大影响,探究其内在机制有利于构建饥饿营销的解释模型。通过两个实验发现,高强度时间压力会唤起消费者的感知竞争进而提高其购买意愿,而且消费者自我建构类型会调节时间压力对消费者购买意愿的影响,即相较于独立型消费者,依存型自我建构消费者将感知到更强程度的竞争,购买意愿更强烈。从消费者心理角度考察时间压力与消费者购买意愿之间具有密切关系,对现代企业饥饿营销策略的科学运用具有重要的现实意义。

农产品原产地形象对消费者购买意愿的影响研究——电商直播情境下心理距离的调节作用

基于SOR理论及心理距离理论模型,以愉悦和唤醒为中介变量,以心理距离为调节变量,探讨直播情境下农产品原产地形象对消费者购买意愿的影响机制。结果表明:电商直播情境下,农产品原产地形象对消费者的购买意愿具有显著的正向影响;农产品原产地形象显著正向影响消费者的愉悦和唤醒情绪;愉悦和唤醒在农产品原产地形象与购买意愿之间起中介作用;愉悦和唤醒在原产地形象对购买意愿的影响中起链式中介作用;心理距离调节原产地形象与唤醒之间的关系,且心理距离越近,原产地形象对唤醒的影响越强。研究结论丰富了电商直播情境下农产品原产地形象和消费者购买意愿的实证研究,为农产品直播经营决策提供依据。

限时促销中消费者冲动购买意愿的认知机制:基于时间压力和前瞻性情绪的实证研究

购物节频繁举办使得消费者对限时促销活动的感知下降,如何应对“造节”泛滥所导致的营销疲态、重新激发市场活力成为业界亟待解决的难题。随着更多情绪消费形式的涌现和消费者购物行为前置化成为趋势,前瞻性情绪正日益成为影响购买行为的重要因素。因此,探究限时促销期间消费者前瞻性情绪的演化过程具有重要现实意义。基于S-O-R分析框架,构建以时间压力为自变量、前瞻性情绪(预期后悔、预期惊喜)为中介变量、冲动购买意愿为因变量的中介模型,并分析产品类型的调节作用。通过两个实验研究发现,限时促销中时间压力对消费者冲动购买意愿具有显著正向影响;产品类型在时间压力和消费者冲动购买意愿之间发挥调节作用;前瞻性情绪在时间压力—产品类型对消费者冲动购买意愿的交互影响中起中介作用,即面对享乐品时,时间压力对消费者产生的前瞻性情绪具有显著正向影响,进而放大了冲动购买意愿的差异;而面对实用品时,时间压力对前瞻性情绪及冲动购买意愿的影响没有显著差异。本研究拓展了S-O-R理论在限时促销领域的应用,从产品类型层面确定了限时促销活动有效发挥作用的边界条件,深化了对前瞻性情绪驱动冲动购买的理解,并为商家优化限时营销策略提供实践指导。

区域夜间经济发展的理论逻辑与提升路径:以成渝地区双城经济圈为例

本文构建了包括供给需求逻辑、政市关系逻辑、空间布局逻辑、竞合优势逻辑在内的区域夜间经济理论分析框架。据此分析,成渝双城经济圈夜间经济市场需求旺盛、供给亮点纷呈,多地高度重视、政策密集出台,初步形成双城引领、多点开花的空间格局,具有一定的竞合优势,但也存在业态供给亟待丰富创新、政府作用未充分发挥,空间布局缺乏系统规划,竞合优势有待增强等问题。成渝双城经济圈夜间经济能级提升可从四个层面着手:完善市场体系,进一步形成供需适配的市场供给格局;优化营商环境,展现更加积极的政府作为;优化空间布局,推动形成经济圈夜间经济新地理;立足资源禀赋,塑造区域夜间经济竞合新优势。

电子服务场景如何唤起旅游电商直播观众的购买意愿——基于场所依恋的链式中介模型

在互联网时代,直播已成为旅游产品营销的重要渠道之一。然而,尚未有研究审视过娱乐氛围和名人光环在旅游电商直播中对观众购买意愿影响的场景效应。文章基于刺激-机体-反应分析框架和场所依恋理论,构建了一个以电商直播娱乐氛围和名人光环为自变量、以场所依赖和场所认同为中介变量、以观众购买意愿为因变量的链式中介模型,并基于688份问卷数据进行了实证检验。文章使用了PLS-SEM和Bootstrapping等分析方法,研究发现:1)娱乐氛围场景和名人光环场景均能正向影响场所依赖和场所认同;2)旅游电商直播场所依赖能正向影响场所认同,且场所依赖和场所认同均能正向影响购买意愿;3)场所依赖在服务场景和购买意愿关系中的简单中介效应显著,但场所认同只能简单中介名人光环和购买意愿之间的关系,在娱乐氛围和购买意愿之间简单中介效应较弱;4)场所依赖和场所认同在服务场景对购买意愿的间接影响中起链式中介作用。文章基于旅游电商直播场景,对娱乐氛围景观和名人光环景观的场所依恋机制及其对观众购买意愿的影响进行了实证,为电子服务场景的场所依恋效应提供了新的认知,并为电商直播场所认同和观众购买意愿的激发提供了有益的管理启示。

基于Petri网和改进遗传算法的多资源调度问题

针对混流装配线工序加工资源需求多样、工艺复杂、装配工期长等问题,采用Petri网和改进遗传算法对该问题进行优化求解。建立混流装配线赋时库所Petri网(timed place Petri net, TPPN)调度模型,基于模型激发序列,采用基于工序的编码方式进行染色体编码;采用精英保留策略选择优异个体,改进遗传算法的交叉、变异操作,用改进后的遗传算法求解混流装配线调度问题。通过对比案例及实例数据计算结果验证了方案的有效性。

考虑不确定性的周期性资源购买机制及多时间尺度调峰调度策略

合理的资源购买和有效的调度策略是充分利用需求响应资源向系统提供辅助服务的关键。该文针对电力系统运行中最常出现、影响也较大的辅助服务事件之一--调峰的需求响应资源周期性购买问题和日内调度问题进行研究。首先,对广大调峰事件的调峰需求特征进行聚类,利用概率描述调度中心不同的决策行为,建立周期内调节资源购买的不确定性模型并获取最优调节资源购买量。其次,针对日内调度,结合负荷预测,建立基于滚动优化的多时间尺度能量和功率协调调度策略。大时间尺度上以调度中心调峰经济性最优为目标对调节能量进行分配,小时间尺度上以调峰效果最优为目标对调节功率进行分配。仿真结果表明,所提周期性资源购买决策机制能够有效提升周期内调度中心的平均收益;而日内多时间尺度协调的调峰策略则能够充分利用已购资源,实现调度中心调峰经济性和调峰效果的双赢。

基于智能算法的代理购电业务电量预测与评价体系研究

我国电力市场目前仍处于改革中,电力企业代理购电预测的准确与否,在市场资源配置中起着决定性作用。为保证代理购电机制平稳发展,需明确电力企业市场化购电规模。目前代理购电电量主要是根据代理购电工商业用户用电量及典型负荷曲线进行预测,缺乏完整的体系,难以精确预测,导致缺少合理的规划。文章提出一套相似日月度预测算法与混合时序月度预测算法相结合的智能算法,用于代理购电业务电量预测与评价,围绕江苏省2022年用电情况进行预测,从5个维度对预测结果进行评价,帮助电力企业精准预判整体售电量规模,合理规划购电计划。

中国近代棉业期刊整理与研究

通过对中国近代棉业期刊统计来源进行检索整理,获得统计数据并进行分析,包括期刊的创刊时间与数量分布、出版机构分布、出版地分布,整理了中国近代重要的棉业期刊,并探讨其特色与作用。统计得到中国近代棉业期刊74种,创刊数量呈曲折发展态势,出版机构有官方机构、行业组织、学校、企业、学术团体和期刊社,出版地有上海、江苏等15个地区。研究认为,中国近代棉业期刊具有出版数量后来居上、出版内容涵盖棉业的各个方面、多种机构合力形成棉业期刊的出版力量、全国性棉业期刊的出版区域以上海和江苏居多、地区性棉业期刊的出版区域分布广泛等特点,为中国近代棉业发展作出了积极贡献。整理和研究为中国近代农业史、纺织史、出版史研究提供了素材。

反事实思维视角下限时促销对旅游直播消费者即时购买意愿的影响机制研究

限时促销作为一种条件促销模式,已成为提升旅游直播营销效果的重要手段,但已有研究较少关注旅游直播领域的限时促销。为弥补现有研究不足,探究旅游直播中限时促销对消费者即时购买决策的影响机制,本文以目标导向行为理论为基础,从反事实思维视角,通过两项情景实验对此进行了剖析,研究发现:(1)旅游直播限时促销能够直接激发消费者的即时购买意愿,其中限时折扣形式比限时赠品效果更好;(2)当消费者具有较强的上行反事实思维时,旅游直播限时促销能够诱发消费者的预期作为后悔,从而降低即时购买意愿;(3)当消费者具有较强的下行反事实思维时,旅游直播限时促销能够诱发消费者的预期不作为后悔,从而提升即时购买意愿。研究结果揭示了旅游直播限时促销所具有的双面性,丰富了旅游直播营销的相关研究,可为旅游企业合理采取网络促销措施提供启示。

考虑满意度的团购两级混合冷链低碳路径优化

考虑当前社区团购生鲜品冷链运输过程中,因品质衰减导致顾客满意度降低,同时需求井喷造成运力不足的问题,提出一种基于众包模式的两级冷链协同优化配送策略,即由企业冷藏车完成城市仓至中转仓的一级冷链运输,由众包冷藏车完成由中转仓至团长的二级冷链运输,并以包含服务延迟成本、碳排放成本和固定成本的总成本最小,及团长对产品品质满意度最大为优化目标,建立一个带有众包的两级开闭混合冷链低碳路径规划模型。针对模型特点,构造了一种改进的自适应大领域搜索算法(improved adaptive large neighborhood search,IALNS),设计了新的破坏-修复解的策略,并在算子选择阶段加入模拟退火算法(simulated annealing,SA)的思想,以加快收敛速度,提高算法全局搜索能力。通过分别与自适应大领域算法(adaptive large neighborhood search,ALNS)、模拟退火算法、遗传算法(genetic algorithm,GA)、粒子群优化算法(particle swarm optimization,PSO)的算例优化结果对比,证明该算法的有效性。该策略兼顾企业利润和客户需求,对比在不同配送模式下的实验结果,验证了该模型在解决社区团购生鲜品冷链物流问题上有积极意义。

上海城市绿地更新中花园的设计与实践

在城市快速发展的今天,城市与居民对城市绿地的功能需求发生着较大的变化,人们越来越重视人与自然的交流和共处。城市绿地更新从只满足基本的生态功能向公园的共享和花园的生活演变。而花园作为城市绿地的一种表达方式与场所空间,在城市绿地更新中扮演着由量到质的重要角色。从分析花园的概念特征、发展及在上海城市绿地中扮演的角色出发,建立起以场所属性为主导的花园设计理念,进而以此理念在上海城市绿地更新实践中进行探索,为建设花园人居城市、改善城市公共环境、打造宜居城市提供理论和实践基础。