Tourism development and economic growth-a nonlinear approach

We use cross sectional data (1995-2005 yearly averages) for 88 countries to investigate the nonlinear relationship between tourism development and economic growth when a threshold variable is used. The degree of tourism specialization (q_i, defined as receipts from international tourism as a percentage of GDP) is used as the threshold variable. The results of the tests for nonlinearity indicate that the 88 countries’ data should be separated into three different groups or regimes to analyze the tourism-growth nexus. The results of the threshold regression show that when the q_i is below 4.0488% (regime 1, 57 countries) or above 4.7337% (regime 3, 23 countries), there exists a significantly positive relationship between tourism growth and economic growth. However, when the q_i is above 4.0488% and below 4.7337% (regime 2, 8 countries), we are unable to find evidence of such a significant relationship. Further in-depth analysis reveals that relatively low ratios of the value added of the service industry to GDP, and the forested area per country area are able to explain why we are unable to find a significant relationship between these two variables in regime 2’s countries.     

Interplay between topology and dynamics in the World Trade Web

We present an empirical analysis of the network formed by the trade relationships between all world countries, or World Trade Web (WTW). Each (directed) link is weighted by the amount of wealth flowing between two countries, and each country is characterized by the value of its Gross Domestic Product (GDP). By analysing a set of year-by-year data covering the time interval 1950–2000, we show that the dynamics of all GDP values and the evolution of the WTW (trade flow and topology) are tightly coupled. The probability that two countries are connected depends on their GDP values, supporting recent theoretical models relating network topology to the presence of a `hidden' variable (or fitness). On the other hand, the topology is shown to determine the GDP values due to the exchange between countries. This leads us to a new framework where the fitness value is a dynamical variable determining, and at the same time depending on, network topology in a continuous feedback.     

Allometric scaling of countries

As huge complex systems consisting of geographic regions, natural resources, people and economic entities, countries follow the allometric scaling law which is ubiquitous in ecological, and urban systems. We systematically investigated the allometric scaling relationships between a large number of macroscopic properties and geographic (area), demographic (population) and economic (GDP, gross domestic production) sizes of countries respectively. We found that most of the economic, trade, energy consumption, communication related properties have significant super-linear (the exponent is larger than 1) or nearly linear allometric scaling relations with the GDP. Meanwhile, the geographic (arable area, natural resources, etc.), demographic (labor force, military age population, etc.) and transportation-related properties (road length, airports) have significant and sub-linear (the exponent is smaller than 1) allometric scaling relations with area. Several differences of power law relations with respect to the population between countries and cities were pointed out. First, population increases sub-linearly with area in countries. Second, the GDP increases linearly in countries but not super-linearly as in cities. Finally, electricity or oil consumption per capita increases with population faster than cities.     

How log-normal is your country? An analysis of the statistical distribution of the exported volumes of products

We have considered the statistical distributions of the volumes of 1131 products exported by 148 countries. We have found that the form of these distributions is not unique but heavily depends on the level of development of the nation, as expressed by macroeconomic indicators like GDP, GDP per capita, total export and a recently introduced measure for countries’ economic complexity called fitness. We have identified three major classes: a) an incomplete log-normal shape, truncated on the left side, for the less developed countries, b) a complete log-normal, with a wider range of volumes, for nations characterized by intermediate economy, and c) a strongly asymmetric shape for countries with a high degree of development. Finally, the log-normality hypothesis has been checked for the distributions of all the 148 countries through different tests, Kolmogorov-Smirnov and Cramér-Von Mises, confirming that it cannot be rejected only for the countries of intermediate economy.     

Adhesive contact: from atomistic model to continuum model

Two types of Lennard-Jones potential are widely used in modeling adhesive contacts. However, the relationships between the parameters of the two types of Lennard-Jones potential are not well defined. This paper employs a self-consistent method to derive the Lennard-Jones surface force law from the interatomic Lennard-Jones potential with emphasis on the relationships between the parameters. The effect of using correct parameters in the adhesion models is demonstrated in single sphere-flat contact via continuum models and an atomistic model. Furthermore, the adhesion hysteresis behaviour is investigated, and the S-shaped force-distance relation is revealed by the atomistic model. It shows that the adhesion hysteresis loop is generated by the jump-to-contact and jump-off-contact, which are illustrated by the S-shaped force-distance curve.     

Clusters or networks of economies? A macroeconomy study through Gross Domestic Product

We study correlations between web-downloaded gross domestic product (GDP)'s of rich countries. GDP is used as wealth signatures of the country economical state. We calculate the yearly fluctuations of the GDP. We look for forward and backward correlations between such fluctuations. The correlation measure is based on the Theil index. The system is represented by an evolving weighted network, nodes being the GDP fluctuations (or countries) at different times.In order to extract structures from the network, we focus on filtering the time delayed correlations by removing the least correlated links. This percolation idea-based method reveals the emergence of connections, that are visualized by a branching representation. Note that the network is made of weighted and directed links when taking into account a delay time. Such a measure of collective habits does not readily fit the usual expectations, except if an economy globalization framework is accepted.     

Clusters in weighted macroeconomic networks: the EU case. Introducing the overlapping index of GDP/capita fluctuation correlations

GDP/capita correlations are investigated in various time windows (TW), for the time interval 1990–2005. The target group of countries is the set of 25 EU members, 15 till 2004 plus the 10 countries which joined EU later on. The TW-means of the statistical correlation coefficients are taken as the weights (links) of a fully connected network having the countries as nodes. Thereafter we define and introduce the overlapping index of weighted network nodes. A cluster structure of EU countries is derived from the statistically relevant eigenvalues and eigenvectors of the adjacency matrix. This may be considered to yield some information about the structure, stability and evolution of the EU country clusters in a macroeconomic sense.     

Advantage of populous countries in the trends of innovation efficiency

A flurry of studies indicates that population size has a positive effect on innovation, however, cross-country empirical evidence remains sparse. In this paper, we add to the literature by investigating the relationship between population size and innovation efficiency at the country level through constructing three relative indexes based on the datasets of patent applications and Research and Development (R&D) investment. Different from previous studies based on absolute innovation indicators, the relative indexes can reflect the core innovation efficiency of economies by excluding the impact from the difference of economic development level, with a view putting all economies into a comparable standard framework. For all of the three relative indexes, their long-term trends show significant correlations with population size, and the economy with a larger population usually has better and stable performance on the trends of innovation efficiency. In addition, we find that there is a critical population size, over which the economy would be more likely to have a spontaneous improvement on innovation efficiency. This study provides direct evidence in supporting the population size advantage on the trends of innovation efficiency at the economy level and provides new insight to understand the rapid development of innovation in a few populous countries.     

Interdependence of Sectors of Economic Activities for World Countries from the Reduced Google Matrix Analysis of WTO Data

We apply the recently developed reduced Google matrix algorithm for the analysis of the OECD-WTO World Network of Economic Activities. This approach allows to determine interdependencies and interactions of economy sectors of several countries, including China, Russia and the USA, properly taking into account the influence of all the other world countries and their economic activities. Within this analysis, we also obtain the sensitivity of EU countries’ economies to the petroleum activity sector. We show that this approach takes into account the multiplicity of economical interactions between countries and activity sectors, thus providing a richer analysis compared to the usual export-import analysis.     

A hydrodynamic model for cooperating solidary countries

The goal of international trade theories is to explain the exchange of goods and services between different countries, aiming to benefit from it. Albeit the idea is very simple and known since ancient history, smart policy and business strategies need to be implemented by each subject, resulting in a complex as well as not obvious interplay. In order to understand such a complexity, different theories have been developed since the sixteenth century and today new ideas still continue to enter the game. Among them, the so called classical theories are country-based and range from Absolute and Comparative Advantage theories by A. Smith and D. Ricardo to Factor Proportions theory by E. Heckscher and B. Ohlin. In this work we build a simple hydrodynamic model, able to reproduce the main conclusions of Comparative Advantage theory in its simplest setup, i.e. a two-country world with country A and country B exchanging two goods within a genuine exchange-based economy and a trade flow ruled only by market forces. The model is further generalized by introducing money in order to discuss its role in shaping trade patterns. Advantages and drawbacks of the model are also discussed together with perspectives for its improvement.     

Competitors’ communities and taxonomy of products according to export fluxes

In this paper we use Complex Network Theory to quantitatively characterize and synthetically describe the complexity of trade between nations. In particular, we focus our attention on export fluxes. Starting from the bipartite countries-products network defined by export fluxes, we define two complementary graphs projecting the original network on countries and products respectively. We define, in both cases, a distance matrix amongst countries and products. Specifically, two countries are similar if they export similar products. This relationship can be quantified by building the Minimum Spanning Tree and the Minimum Spanning Forest from the distance matrices for products and countries. Through this simple and scalable method we are also able to carry out a community analysis. It is not gone unnoticed that in this way we can produce an effective categorization for products providing several advantages with respect to traditional classifications of COMTRADE [1]. Finally, the forests of countries allows for the detection of competitors’ community and for the analysis of the evolution of these communities.     

Analysis of the generation mechanism of the S-shaped J—V curves of MoS2/Si-based solar cells

Amorphous-microcrystalline MoS$_{2}$ thin films are fabricated using the sol-gel method to produce MoS$_{2}$/Si-based solar cells. The generation mechanisms of the S-shaped current density-voltage ($J$-$V$) curves of the solar cells are analyzed. To improve the performance of the solar cells and address the problem of the S-shaped $J$-$V$ curve, a MoS$_{2}$ film and a p$^+$ layer are introduced into the front and back interfaces of the solar cell, respectively, which leads to the formation of a p-n junction between the p-Si and the MoS$_{2}$ film as well as ohmic contacts between the MoS$_{2}$ film and the ITO, improving the S-shaped $J$-$V$ curve. As a result of the high doping characteristics and the high work function of the p$^+$ layer, a high-low junction is formed between the p$^+$ and p layers along with ohmic contacts between the p$^+$ layer and the Ag electrode. Consequently, the S-shaped $J$-$V$ curve is eliminated, and a significantly higher current density is achieved at a high voltage. The device exhibits ideal p-n junction rectification characteristics and achieves a high power-conversion efficiency (CE) of 7.55%. The findings of this study may improve the application of MoS$_{2}$ thin films in silicon-based solar cells, which are expected to be widely used in various silicon-based electronic and optical devices.     

COVID-19’s Impact on International Trade

We analyze how the COVID-19 pandemic affected the trade of products between countries. With this aim, using the United Nations Comtrade database, we perform a Google matrix analysis of the multiproduct World Trade Network (WTN) for the years 2018–2020, comprising the emergence of the COVID-19 as a global pandemic. The applied algorithms—PageRank, CheiRank and the reduced Google matrix—take into account the multiplicity of the WTN links, providing new insights into international trade compared to the usual import–export analysis. These complex networks analysis algorithms establish new rankings and trade balances of countries and products considering all countries on equal grounds, independent of their wealth, and every product on the basis of its relative exchanged volumes. In comparison with the pre-COVID-19 period, significant changes in these metrics occurred for the year 2020, highlighting a major rewiring of the international trade flows induced by the COVID-19 pandemic crisis. We define a new PageRank–CheiRank product trade balance, either export or import-oriented, which is significantly perturbed by the pandemic.     

基于对数二阶微分极小峰值时间的测厚方法研究

本文提出了一种反射式脉冲红外热波技术中采用对数温度-对数时间二 阶微分极小峰值时间作为特征时间进行缺陷深度定量测量的方法. 首先, 介绍了反射式脉冲红外热波技术的基本原理, 在半无限厚平板解的基础上得到了对数温度-对数时间二阶微分极小峰值时间与缺陷深度平方的关系式. 其次, 利用不锈钢和铝材料制作平底洞试件并得到红外热图序列, 提取对数二阶微分极小峰值时间. 该特征时间与缺陷深度平方实验结果显示其具有很好线性关系, 该线性关系可用于实际缺陷深度定量测量, 并讨论了与应用广泛的对数二阶微分极大峰值法相比的优缺点. 关键词： 红外热波 定量测量 缺陷深度 极小峰值     

The relationships between electricity consumption and GDP in Asian countries,using hierarchical structure methods

This study uses hierarchical structure methods (minimal spanning tree (MST) and hierarchical tree (HT)) to examine the relationship between energy consumption and economic growth in a sample of 30 Asian countries covering the period 1971–2008. These countries are categorized into four panels based on the World Bank income classification, namely high, upper middle, lower middle, and low income. In particular, we use the data of electricity consumption and real gross domestic product (GDP) per capita to detect the topological properties of the countries. We show a relationship between electricity consumption and economic growth by using the MST and HT. We also use the bootstrap technique to investigate a value of the statistical reliability to the links of the MST. Finally, we use a clustering linkage procedure in order to observe the cluster structure. The results of the structural topologies of these trees are as follows: (i) we identified different clusters of countries according to their geographical location and economic growth, (ii) we found a strong relationship between energy consumption and economic growth for all income groups considered in this study and (iii) the results are in good agreement with the causal relationship between electricity consumption and economic growth.     

Statistical properties of stock market indices of different economies

Daily changes in the logarithm of stock market index from 1997 to 2004 are analyzed for countries from three subgroups of economies classified by the International Monetary Fund (IMF): developing Asian countries, newly industrialized Asian economies and major advanced economies. For all markets, the daily changes are well fitted by a non-Gaussian stable probability density. The time evolution of the standard deviation of the daily changes for each market obeys a power law. However, the developing Asian countries have the smallest stable density characteristic parameters α and the largest exponents b of the power law, except China's SSEC and India's SENSEX. The values of α and b for these two markets are closer to those of the newly industrialized Asian economies; in particular, those for China's SSEC are close to those for Hong Kong's HSI. The values of α and b for the newly industrialized Asian economies are in between those for the developing Asian countries and major advanced economies, consistent with the results for generalized Hurst exponent [Physica A 324 (2003) 183]. The daily changes for the developing Asian countries and newly industrialized Asian economies have a weak long-range correlation, whereas the daily changes for the major advanced economies have a weak long-range anti-correlation.     

Asymmetric Relatedness from Partial Correlation

Relatedness is a key concept in economic complexity, since the assessment of the similarity between industrial sectors enables policymakers to design optimal development strategies. However, among the different ways to quantify relatedness, a measure that takes explicitly into account the time correlation structure of exports is still lacking. In this paper, we introduce an asymmetric definition of relatedness by using statistically significant partial correlations between the exports of economic sectors and we apply it to a recently introduced database that integrates the export of physical goods with the export of services. Our asymmetric relatedness is obtained by generalising a recently introduced correlation-filtering algorithm, the partial correlation planar graph, in order to allow its application on multi-sample and multi-variate datasets, and in particular, bipartite temporal networks. The result is a network of economic activities whose links represent the respective influence in terms of temporal correlations; we also compute the statistical confidence of the edges in the network via an adapted bootstrapping procedure. We find that the underlying influence structure of the system leads to the formation of intuitively-related clusters of economic sectors in the network, and to a relatively strong assortative mixing of sectors according to their complexity. Moreover, hub nodes tend to form more robust connections than those in the periphery.     

Power law for the duration of recession and prosperity in Latin American countries

Ormerod and Mounfield [P. Ormerod, C. Mounfield, Power law distribution of duration and magnitude of recessions in capitalist economies: Breakdown of scaling, Physica A 293 (2001) 573] and Ausloos et al. [M. Ausloos, J. Mikiewicz, M. Sanglier, The durations of recession and prosperity: Does their distribution follow a power or an exponential law? Physica A 339 (2004) 548] have independently analyzed the duration of recessions for developed countries through the evolution of the GDP in different time windows. It was found that there is a power law governing the duration distribution. We have analyzed data collected from 19 Latin American countries in order to observe whether such results are valid or not for developing countries. The case of prosperity years is also discussed. We observe that the power law of recession time intervals, see Ref. [1], is valid for Latin American countries as well. Thus an interesting point is discovered: the same scaling time is found in the case of recessions for the three data sets (ca. 1 year), and this could represent a universal feature. Other time scale parameters differ significantly from each other.     

3D combinational curves for accuracy and performance analysis of positive biometrics identification

The receiver operating characteristic (ROC) curve has been widely used as an evaluation criterion to measure the accuracy of biometrics system. Unfortunately, such an ROC curve provides no indication of the optimum threshold and cost function. In this paper, two kinds of 3D combinational curves are proposed: the 3D combinational accuracy curve and the 3D combinational performance curve. The 3D combinational accuracy curve gives a balanced view of the relationships among FAR (false alarm rate), FRR (false rejection rate), threshold t, and Cost. Six 2D curves can be derived from the 3D combinational accuracy curve: the conventional 2D ROC curve, 2D curve of (FRR, t), 2D curve of (FAR, t), 2D curve of (FRR, Cost), 2D curve of (FAR, Cost), and 2D curve of (t, Cost). The 3D combinational performance curve can be derived from the 3D combinational accuracy curve which can give a balanced view among Security, Convenience, threshold t, and Cost. The advantages of using the proposed 3D combinational curves are demonstrated by iris recognition systems where the experimental results show that the proposed 3D combinational curves can provide more comprehensive information of the system accuracy and performance.