Nonlinear Differential Equation of Macroeconomic Dynamics for Long-Term Forecasting of Economic Development

In this article we derive a general differential equation that describes long-term economic growth in terms of cyclical and trend components. Equation is based on the model of non-linear accelerator of induced investment. A scheme is proposed for obtaining approximate solutions of nonlinear differential equation by splitting solution into the rapidly oscillating business cycles and slowly varying trend using Krylov-Bogoliubov-Mitropolsky averaging. Simplest modes of the economic system are described. Characteristics of the bifurcation point are found and bifurcation phenomenon is interpreted as loss of stability making the economic system available to structural change and accepting innovations. System being in a nonequilibrium state has a dynamics with self-sustained undamped oscillations. The model is verified with economic development of the US during the fifth Kondratieff cycle (1982-2010). Model adequately describes real process of economic growth in both quantitative and qualitative aspects. It is one of major results that the model gives a rough estimation of critical points of system stability loss and falling into a crisis recession. The model is used to forecast the macroeconomic dynamics of the US during the sixth Kondratieff cycle (2018-2050). For this forecast we use fixed production capital functional dependence on a long-term Kondratieff cycle and medium-term Juglar and Kuznets cycles. More accurate estimations of the time of crisis and recession are based on the model of accelerating log-periodic oscillations. The explosive growth of the prices of highly liquid commodities such as gold and oil is taken as real predictors of the global financial crisis. The second wave of crisis is expected to come in June 2011.

Regional Brand and High-quality Development of Fruits in Ethnic Areas of the Yangtze River Economic Belt under the Greater Food Approach

Establishing the Greater Food Approach and promoting the Yangtze River Economic Belt s national major regional development strategy can better support and serve the agricultural power and Chinese-style modernization.This paper introduces the characteristics of fruit industry in 16 autonomous prefectures and 47 autonomous counties under the jurisdiction of the Yangtze River Economic Belt.It studies the intellectual property resources of brand marks from the aspects of geographical indications,collective trademarks,certification trademarks,well-known trademarks in China and national design patents,and analyzes the main problems of brand and high-quality development of fruit industry in these ethnic autonomous areas.Finally,it puts forward some strategies,such as improving the protection of intellectual property rights of geographical indications,using intellectual property rights of brand signs,building modern seed industry upgrading project,drawing lessons from the experience of thousand villages demonstration project,ensuring that large-scale poverty does not occur,and building a diversified food supply system.

The Intersection of Privacy by Design and Behavioral Economics: Nudging Users towards Privacy-Friendly Choices

This paper conducts a comprehensive review of existing research on Privacy by Design (PbD) and behavioral economics, explores the intersection of Privacy by Design (PbD) and behavioral economics, and how designers can leverage “nudges” to encourage users towards privacy-friendly choices. We analyze the limitations of rational choice in the context of privacy decision-making and identify key opportunities for integrating behavioral economics into PbD. We propose a user-centered design framework for integrating behavioral economics into PbD, which includes strategies for simplifying complex choices, making privacy visible, providing feedback and control, and testing and iterating. Our analysis highlights the need for a more nuanced understanding of user behavior and decision-making in the context of privacy, and demonstrates the potential of behavioral economics to inform the design of more effective PbD solutions.

Factors Influencing the Successful Adoption of Human Resource Information System: The Content of Aqaba Special Economic Zone Authority

This study examines the key factors that have impact on the successful adoption of Human Resource Information System (HRIS) within the Aqaba Special Economic Zone Authority (ASEZA)/Jordan. In order to accomplish the purpose of the study four critical factors are inquired. So, four critical factors are inquired: First, TAM Model (Perceived Ease of Use (PEOU) and Perceived Usefulness (PU)). Second, Information Technology Infrastructure (ITI). Third, Top Management Support (TMS). Finally, Individual Experience with Computer (IEC). The research model was applied to collect data from the questionnaires answered by 45 users of HRIS as a source of primary data, based on a convenience sample the response rate was about 91%. In addition, the results were analyzed by utilizing the Statistical Package for Social Software (SPSS). Furthermore, the findings were analyzed;multiple Regression analysis indicated that all research variables have significant relationship on successful adoption of HRIS. The findings indicated IT infrastructures have a positive and significant effect on the successful adoption of HRIS. But there is no significant of PU, PEOU, TMS, and IEC on the successful adoption of HRIS. Finally, the results indicated that no significant statistical differences of demographic characteristics on HRIS adoption. Depending on the research’s findings;the researchers proposed a set of recommendations for better adoption of HRIS in SEZA.

Review and Analysis: Evaluation of the Impacts and Consequences of Using Agricultural Herbicides as Military Chemical Weapons in Second Indochina War

The legacy of the human misery caused by the application of the herbicides including Agent Purple and Agent Orange contaminated with unknown amounts of dioxin TCDD and Agent Blue, the arsenic-based herbicide, sprayed over the jungles, rice fields, and hamlets of Vietnam is still haunting us today. Why did this happen? Could it have been prevented? Was it necessary United States military strategy? Was it an intentional decision to inflict this blight on the enemy soldiers and the Vietnamese, Cambodian, and Laotian civilians, to poison their land and cause generations of harm? Alternatively, was it an unpreventable accident in the march of military history? What patterns in the U.S. government’s thought process could be identified as the cause, which led to the decision to use these herbicides as tactical chemical weapons? If the introduction of herbicide (chemical) weapons had not been made, would the outcome of the Vietnam War and the Secret Wars in Laos and Cambodia have been any different? The objective of this treatise is to outline the role of world events and backgrounds and the role of the leaders, U.S. military, CIA, USDA, U.S. State Department, the U.S. President appointed Ambassadors to Vietnam and Laos, chemical companies, and President Diệm’s Republic of Vietnam (RVN) government and military. Their collective advice led to the decision to use herbicides as military and environmental chemical weapons in the Second Indochina War. Were the National interests achieved by U.S. military strategy in the RVN using herbicide weapons worth the long-term environmental and human health consequences in Vietnam, Cambodia, and Laos? Did it impact the outcome of the Second Indochina War?

AI赋能哲学社会科学研究、传播及评价

人工智能正在改变整个人类社会,丰富人们的文化生活,促进科技创新与发展,是各行各业“新质化”的促进剂。人工智能可为哲学社会科学提供高效的研究工具和研究场景,将深刻影响哲学社会科学研究、传播及评价的方方面面。加速人工智能在哲学社会科学研究、传播及评价领域的深入应用,提升哲学社会科学研究效率,促进哲学社会科学的创新与发展,构建自主知识体系,是当下哲学社会科学工作者的重要使命。为推进AI赋能哲学社会科学(AI4SS),2024年9月28日,由西华大学、四川省社会科学学术期刊协会主办,西华大学学术期刊部、四川省社会科学重点研究基地四川学术成果分析与应用研究中心承办的“AI赋能社科研究与评价天府论坛”在西华大学举行。来自南京大学、中国人民大学、四川大学等高校与科研机构的20位专家学者,从不同学科、研究领域出发,就人工智能赋能哲学社会科学研究、传播及评价进行了深入交流。文章为20位专家学者在论坛上所作报告的主要观点。这些报告议题包括AI赋能人文社科研究方法的变革,法学、教育学、经济学、图书情报学、新闻传播等社会学科视域下的人工智能,AI辅助社会科学研究的学术伦理,人工智能在医疗健康、大宗商品价格风险监测、大学生高阶思维能力培养等方面的应用,AI赋能学术期刊出版与传播,AI赋能哲学社会科学评价新模式、新平台、新场景,等等。这些议题共同描绘了一个由AI技术驱动的多学科融合与创新的新时代。

Economic Load Dispatch Based on Efficient Population Utilization Strategy for Particle Swarm Optimization

In this paper, the efficient population utilization strategy for particle swarm optimization (EPUSPSO) is proposed to solve the economic load dispatch (ELD) problem of power system. This algorithm improves the accuracy and the speed of its convergence by changing the number of particles effectively, and improving the velocity equation and position equation. In order to verify the effectiveness of the algorithm, this algorithm is tested in three different ELD cases of power system include IEEE 3-unit case, 13-unit case, and 40-unit case, and the obtained results are compared with those obtained from other algorithms using the same system parameters. The compared results show that the algorithm can find the optimal solution effectively and accurately, and avoid falling into the local optimal problem;meanwhile, faster speed can be ensured in the case.

Sequential Approach with Matrix Framework for Various Types of Economic Thermal Power Dispatch Problems

This paper presents a sequential approach with matrix framework for solving various kinds of economic dispatch problems. The objective of the economic dispatch problems of electrical power generation is to schedule the committed generating units output so as to meet the required load demand while satisfying the system equality and inequality constraints. This is a maiden approach developed to obtain the optimal dispatches of generating units for all possible load demands of power system in a single execution. The feasibility of the proposed method is demonstrated by solving economic load dispatch problem, combined economic and emission dispatch problem, multiarea economic dispatch problem and economic dispatch problem with multiple fuel options. The proposed methodology is tested with different scale of power systems. The generating unit operational constraints are also considered. The simulation results obtained by proposed methodology for various economic dispatch problems are compared with previous literatures in terms of solution quality. Numerical simulation results indicate an improvement in total cost saving and hence the superiority of the proposed method is also revealed for economic dispatch problems.

Comparative Analysis of Machine Learning Models for Customer Churn Prediction in the U.S. Banking and Financial Services: Economic Impact and Industry-Specific Insights

Customer churn poses a significant challenge for the banking and finance industry in the United States, directly affecting profitability and market share. This study conducts a comprehensive comparative analysis of machine learning models for customer churn prediction, focusing on the U.S. context. The research evaluates the performance of logistic regression, random forest, and neural networks using industry-specific datasets, considering the economic impact and practical implications of the findings. The exploratory data analysis reveals unique patterns and trends in the U.S. banking and finance industry, such as the age distribution of customers and the prevalence of dormant accounts. The study incorporates macroeconomic factors to capture the potential influence of external conditions on customer churn behavior. The findings highlight the importance of leveraging advanced machine learning techniques and comprehensive customer data to develop effective churn prevention strategies in the U.S. context. By accurately predicting customer churn, financial institutions can proactively identify at-risk customers, implement targeted retention strategies, and optimize resource allocation. The study discusses the limitations and potential future improvements, serving as a roadmap for researchers and practitioners to further advance the field of customer churn prediction in the evolving landscape of the U.S. banking and finance industry.

A Multi-Agent Particle Swarm Optimization for Power System Economic Load Dispatch

A new versatile optimization, the particle swarm optimization based on multi-agent system (MAPSO) is presented. The economic load dispatch (ELD) problem of power system can be solved by the algorithm. By competing and cooperating with the randomly selected neighbors, and adjusting its global searching ability and local exploring ability, this algorithm achieves the goal of high convergence precision and speed. To verify the effectiveness of the proposed algorithm, this algorithm is tested by three different ELD cases, including 3, 13 and 40 units IEEE cases, and the experiment results are compared with those tested by other intelligent algorithms in the same cases. The compared results show that feasible solutions can be reached effectively, local optima can be avoided and faster solution can be applied with the proposed algorithm, the algorithm for ELD problem is versatile and efficient.

9个不同使用类型木薯品系在合浦县的适应性研究

为筛选适宜在合浦县推广的木薯品系,本研究以主栽品种‘南植199’为对照,对9个木薯新品系的生物学特性进行了观察,并测定其农艺性状和经济性状,同时进行相关性分析。结果表明,9个品系分枝角度小、块根长度适中和主茎高度中等以上;‘RC4’的块根产量显著高于对照,其余8个品系与对照差异不显著;‘RC4’等8个品系的淀粉产量高于对照;9个品系的淀粉含量高于对照,其中‘RC3’等5个品系的淀粉含量显著或极显著高于对照;9个木薯品系的直链淀粉含量显著或极显著低于对照‘;RC6’等6个品系的氢氰酸含量低于50 mg/kg。相关性分析结果表明:块根产量与生长中期株高、成熟期株高、块根直径呈极显著正相关,与茎粗呈显著正相关;淀粉含量与生长中期株高、成熟期株高、茎粗呈显著正相关;淀粉产量与生长中期株高、成熟期株高、茎粗、块根直径、块根产量呈极显著正相关,与淀粉含量呈显著正相关。综合来看,这9个木薯新品系的综合表现良好,适合在合浦县进行推广。其中‘,RC3’、‘RC4’和‘RC7’可作为加工型品系;‘RC5’和‘RC10’可作为食用品系;‘RC2’、‘RC6’、‘RC11’和‘RC12’可作为鲜食加工兼用品系;‘RC2’和‘RC5’作为食用品系具有很好的推广前景。

中国耕地非农化对经济增长贡献的地区差异分析

现阶段中国耕地非农化对经济增长贡献存在地区差异,掌握差异的主要来源和变化趋势有利于耕地非农化指标的高效调配,促进地区经济增长的协调发展。利用1989～2001年我国东、中、西部建设用地占用耕地面积和国内生产总值的分省数据,测算了以建设用地占用耕地面积和GDP增量为对象的基尼系数、加权变异系数以及泰尔指数等指标,并对泰尔指数进行因素分解得到差异的主要来源和变化趋势。结果表明:三类地区内部省际差异是总体差异的主要来源,其中东部内部差异对总体差异贡献增大、中部减小、西部有先增大后减小趋势。鉴于此,从促进资源的高效利用和保护地区间公平发展环境的角度出发,耕地非农化指标调控的重点在于三类地区各自内部省份之间的调剂。

Effects of Enclosure on Grassland Ecological and Economic Benefits in Northern China

Grasslands in northern China serve the country as both an ecological barrier and a livestock production base.There,installing enclosures has been becoming the major grassland restoration measure adopted by many local governments.However,the effects of restoration on both ecological and production benefits of grassland remain unclear for implemented grassland restoration policies.Therefore,a representative rangeland in northern China,the Maodeng pasture in Inner Mongolia Autonomous Region was selected as the study area,and remote sensing monitoring analyses were carried out to quantify the ecological benefits and economic benefits from 2015 to 2021.The results showed that:1) in terms of ecological benefits,the grassland area with a grassland coverage rate of more than 60% accounts for 32.3% of the regional area,and 86.4% of its grassland grew significantly better than the same period in2015,showing a significant improvement in grassland growth.Using the average amount of carbon per unit area as the ecological benefit evaluation index,it increased by 27.1% to 32.48Tg C/yr from 2015 to 2021.2) In terms of economic benefits,both theoretical grass production and livestock carrying capacity increased from 2015 to 2021.Compared to 2015,the theoretical grass production in 2021 increased by 24.8% to 71 900 t.The livestock carrying capacity reached 52 100 sheep units in 2021,nearly 11 000 sheep units more than that in 2015.During the study period,multiple economic indicators(on a per capita basis of permanent residents) for the pastoral area of Xilinhot City to which the Maodeng pasture belongs,have grown steadily.Per capita total income rose from 29 630 yuan(RMB) in2015 to 62 859 yuan(RMB) in 2021.Relying on grassland resources to develop the pastoral ecology also broadens the potential economic development space.Overall,the establishment of the reserve and the experiment of implanting an enclosure policy have had a significant and positive impact on Maodeng pasture’s development from both an ecological and economic perspective.With the support of scientific evidence,enclosure policy can be extended to more than 110 000 km~2 of grasslands in northern China with similar precipitation and temperature conditions,enhancing the productive and ecological potential of grasslands.The above research results will contribute to the scientific formulation of grassland pasture quality improvement plans in northern China.

Escaping Dependency and Trade War:China and the US

Marxist political economy provides a perspective for grasping the root cause of the China-US trade war.The international relations of production,which stem from the international division of labor,shape the distribution of international economic interests and the political status of countries.Traditionally,developing countries have been subjected to the“periphery”in the international division of labor.In the new global value chain,developing countries have remained in a subordinate position characterized by“technological-market”dependence.To achieve the goal of building a strong modern nation,China must escape the“technological-market”dependence.Yet China’s efforts and achievements in escaping dependent development are deemed as a threat to US vested interests in the international markets.To preserve the economic foundation of its hegemony,the US has resorted to a trade war to contain China’s development.

Simulation Modelling and Techno-Economics of Supercritical Carbon Dioxide Recompression Closed Brayton Cycle

In recent years, there has been global interest in meeting targets relating to energy affordability and security while taking into account greenhouse gas emissions. This has heightened major interest in potential investigations into the use of supercritical carbon dioxide (sCO2) power cycles. Climate change mitigation is the ultimate driver for this increased interest;other relevant issues include the potential for high cycle efficiency and a circular economy. In this study, a 25 MWe recompression closed Brayton cycle (RCBC) has been assessed, and sCO2 has been proposed as the working fluid for the power plant. The methodology used in this research work comprises thermodynamic and techno-economic analysis for the prospective commercialization of this sCO2 power cycle. An evaluated estimation of capital expenditure, operational expenditure, and cost of electricity has been considered in this study. The ASPEN Plus simulation results have been compared with theoretical and mathematical calculations to assess the performance of the compressors, turbine, and heat exchangers. The results thus reveal that the cycle efficiency for this prospective sCO2 recompression closed Brayton cycle increases (39% - 53.6%) as the temperature progressively increases from 550˚C to 900˚C. Data from the Aspen simulation model was used to aid the cost function calculations to estimate the total capital investment cost of the plant. Also, the techno-economic results have shown less cost for purchasing equipment due to fewer components being required for the cycle configuration as compared to the conventional steam power plant.

Economic Benefit Estimating of Polydimensional Efficiency Measurement Model Implementation

This paper is a revised and expanded version of a paper entitled “The static and dynamic criteria of building an investment asset portfolio” presented at International Conference on Applied Economics (ICOAE, 2014), Chania, 3-5 July 2014 and published at Procedia Economics and Finance, Volume 14, Pages 575-584 (2014) [1]. At the previous research, it showed the significance to go beyond the scope of selecting one or another metric of static efficiency. And the attention was paid to the dynamic efficiency criteria. The ICOAE 2015 research gives brief results of that work, which is only one of applied areas of polydimensional efficiency measurement model (PEMM). Research work on PEMM conceptual and methodical elaboration has been started in the author’s dissertation study [2] and continued in the practical activity and materialized in Innovative LLC (limited liability company) creating project. The research is concentrating on the real economic benefit of 3D PEMM (thee criterial PEMM version) implementation. In the first part of ICOAE 2015 empirical study, the dynamic component of 3D PEMM on the industrial level was tested. Next, the company economic profit changes and dynamic-market 3D PEMM components correlation was estimated. Finally, the economic benefit of 3D PEMM functional operationalization in the framework of management systems development was calculated.

Socio-economic vulnerability level in the Jeneberang watershed in Gowa Regency,South Sulawesi Province,Indonesia

Jeneberang watershed is vital,particularly for people living in Gowa Regency(South Sulawesi Province,Indonesia),who benefit from its many advantages.Landslides and floods occur every year in the Jeneberang watershed,so it is imperative to understand the socio-economic vulnerability of this region.This research aims to identify the vulnerability level of the Jeneberang watershed so that the government can prioritize areas with high vulnerability level and formulate effective strategies to reduce these the vulnerability.Specifically,this study was conducted in 12 districts located in the Jeneberang watershed.The primary data were collected from questionnaires completed by community members,community leaders,and various stakeholders,and the secondary data were from the Landsat satellite imagery in 2020,the Badan Push Statistic of Gowa Regency,and some governmental agencies.The socio-economic vulnerability variables were determined using the Multiple Criteria Decision Analysis(MCDA)method,and each variable was weighted and analyzed using the Geographical Information System(GIS).The study reveals that the levels of socio-economic vulnerability are affected by variables such as population density,vulnerable groups(disabled people,elderly people,and young people),road network and settlement,percentage of poor people,and productive land area in the Jeneberang watershed.Moreover,all of the 12 districts in the Jeneberang watershed are included in the medium vulnerability level,with the mean percentage of socio-economic vulnerability around 50.92%.The socio-economic vulnerability of Bajeng,Pallangga,and Somba Opu districts is categorized at high level,the socio-economic vulnerability of Bungaya,Parangloe,and Tombolo Pao districts is classified as medium level,and the remaining 6 districts(Barombong,Bontolempangan,Bontomarannu,Manuju,Parigi,and Tinggimoncong)are ranked as low socio-economic vulnerability.This study can help policy-makers to formulate strategy that contributes to the protection of biodiversity and sustainable development of the Jeneberang watershed,while improving disaster resilience and preparedness of the watershed.

Analyzing economic feasibility for investing in nursing care: Evidence from panel data analysis in 35 OECD countries

Objective:To analyze economic feasibility for investing in nursing care.Method:The number of practicing nurses'density per 1000 population as a proxy for nursing staff and Gross Domestic Product(GDP)per capita(current US$)were collected in 35 member countries of Organization for Economic Co-operation and Development(OECD)over 2000-2016 period.The statistical technique of panel data analysis including unit root test,cointegration analysis,Granger causality test,dynamic long-run model analysis and error correction model were applied to measure economic impact of nursing-related services.Results:There was a committed bilateral relationship between nurse-staffing level and GDP with longrun magnitudes of 1.39 and 0A1 for GDP-lead-nurse and nurse-lead-GDP directions in OECD countries,respectively.Moreover,the highest long-run magnitudes of the effect nursing staff has on increasing GDP per capita were calculated in Finland(2.07),Sweden(1.92),Estonia(1.68),Poland(1.52),Czech Republic(1.48),Norway(1.47)and Canada(1.24).Conclusion:Our findings verify that although the dependency of nursing characteristics to GDP per capita is higher than the reliance of GDP to number of nurses'density per 1000 population,investing in nursing care is economically feasible in OECD countries i.e.nursing is not only a financial burden(or cost)on health care systems,but also an economic stimulus in OECD countries.Hence,we alert governments and policy makers about the risk of underestimating the economic impacts of nurses on economic systems of OECD countries.

ADMM-based Distributed Algorithm for Economic Dispatch in Power Systems With Both Packet Drops and Communication Delays

By virtue of alternating direction method of multipliers(ADMM), Newton-Raphson method, ratio consensus approach and running sum method, two distributed iterative strategies are presented in this paper to address the economic dispatch problem(EDP) in power systems. Different from most of the existing distributed ED approaches which neglect the effects of packet drops or/and time delays, this paper takes into account both packet drops and time delays which frequently occur in communication networks. Moreover, directed and possibly unbalanced graphs are considered in our algorithms, over which many distributed approaches fail to converge. Furthermore, the proposed schemes can address the EDP with local constraints of generators and nonquadratic convex cost functions, not just quadratic ones required in some existing ED approaches. Both theoretical analyses and simulation studies are provided to demonstrate the effectiveness of the proposed schemes.

Lithofacies modeling by multipoint statistics and economic evaluation by NPV volume for the early Cretaceous Wabiskaw Member in Athabasca oilsands area, Canada

The static modeling and dynamic simulation are essential and critical processes in petroleum exploration and development. In this study, lithofacies models for Wabiskaw Member in Athabasca, Canada are generated by multipoint statistics(MPS) and then compared with the models built by sequential indicator simulation(SIS). Three training images(Tls) are selected from modern depositional environments;the Orinoco River Delta estuary, Cobequid bay-Salmon River estuary, and Danube River delta environment. In order to validate lithofacies models, average and variance of similarity in lithofacies are calculated through random and zonal blind-well tests.In random six-blind-well test, similarity average of MPS models is higher than that of SIS model. The Salmon MPS model closely resembles facies pattern of Wabiskaw Member in subsurface. Zonal blind-well tests show that successful lithofacies modeling for transitional depositional setting requires additional or proper zonation information on horizontal variation, vertical proportion, and secondary data.As Wabiskaw Member is frontier oilsands lease, it is impossible to evaluate the economics from production data or dynamic simulation. In this study, a dynamic steam assisted gravity drainage(SAGD)performance indicator(SPIDER) on the basis of reservoir characteristics is calculated to build 3 D reservoir model for the evaluation of the SAGD feasibility in Wabiskaw Member. SPIDER depends on reservoir properties, economic limit of steam-oil ratio, and bitumen price. Reservoir properties like porosity,permeability, and water saturation are measured from 13 cores and calculated from 201 well-logs. Three dimensional volumes of reservoir properties are constructed mostly based on relationships among properties. Finally, net present value(NPV) volume can be built by equation relating NPV and SPIDER. The economic area exceeding criterion of US$ 10,000 is identified, and the ranges of reservoir properties are estimated. NPV-volume-generation workflow from reservoir parameter to static model provides costand time-effective method to evaluate the oilsands SAGD project.