Set Of New Indices Research Articles

Composite materials, technologies and manufacturing: current scenario of European Union shipyards

ABSTRACT This paper provides the results and the analysis of a study conducted on the processes and technologies currently used by European Union shipyards, and their potential interest in new advanced composite construction technologies, including Adaptive Moulds, Automated Tape Laying, Automated Fibre Placement, Curved Pultruded Profiles, Additive Manufacturing, Hot Stamping, Modular and Serialised Shipbuilding and Digitisation of Production. A new set of indexes are also introduced with the objective of facilitating the evaluation of the technological level of the shipyard, thereby allowing the understanding of the shipyard's interest in new developments. The analysis of the survey conducted shows that almost the 95% of shipyards either currently use or plan to use composite materials, being the composites made of fibreglass and polyester resin the most used. These composites are mainly manufactured by manual lamination and vacuum infusion techniques. The survey has also shown that there is a high interest in the shipyard digitisation and the use of new technologies in the shipbuilding industry, especially for new construction shipyards. The study shows that despite shipyards want to adopt digitisation in engineering and design processes, implementation of new technologies and concepts is being held back by financial cost and uncertainty regarding outcomes such as improved operational efficiency of vessels. The shipyards that do not use composites are less technologically advanced than those that use them, according to the analysis of the technological indexes. This analysis has also shown that the shipyards with a high technological index have a more varied potential market offer.

Institutions and economic development: new measurements and evidence

We propose a new set of indices to capture the multidimensionality of a country’s institutional setting. Our indices are obtained by employing a dimension reduction approach on the institutional variables provided by the Fraser Institute (2018). We estimate the impact that institutions have on the level and the growth rate of per capita GDP, using a large sample of countries over the period 1980–2015. To identify the causal effect of our institutional indices on a country’s GDP we employ the Generalized Propensity Score method. Institutions matter especially in low- and middle-income countries, and not all institutions are alike for economic development. We also document non-linearities in the causal effects that different institutions have on growth and the presence of threshold effects.

Towards a better ecological understanding of metacommunity stability: A multiscale framework to disentangle population variability and synchrony effects

Abstract Despite great progress in our understanding of the mechanisms governing ecosystem stability in local communities, we still lack knowledge at a larger spatial scale. Studying the stability of metacommunities requires assessing the temporal stability and synchrony of populations across space and organizational levels. Previous attempts to disentangle these effects have provided limited ecological interpretations, and conceptual improvements are needed to identify the underlying ecological processes. We propose an extended framework aiming at disentangling simultaneously the relative effects of population stability and different types of synchronies on metacommunity stability. We adapted previous methods of decomposing stability into a new set of indices associated with clearer ecological hypotheses. Particularly, we provide synchrony indices that are not affected by statistical properties of the metacommunity but focus on species responses to environment, demography and interactions. We applied this framework to a unique dataset describing the sorted biomass of individual plant populations, across 12 communities of a species‐rich meadow, and for 16 years. The communities were sampled in different treatments of fertilization and dominant removal to evaluate the effect of environmental heterogeneity on stability. We found higher stability at a larger spatial scale, mainly due to statistical averaging (portfolio effect). The variability of individual populations was an important determinant of the stability of the whole metacommunity. Consistent with the hypothesis of a common response to environmental conditions, we found that the fluctuations of populations were mostly synchronized (within and between species) at a large spatial scale and tended to destabilize the metacommunity. On the other hand, opposite fluctuations (anti‐synchrony) between populations occurred at the local scale, probably due to local species interactions. Synthesis. Our framework appears as a powerful tool to test how ecological processes occurring simultaneously at different spatial and organizational scales affect the stability of metacommunities. This study advances our ecological understanding of the processes underlying the stability of species‐rich environments.

Recurrence of Drought Events Over Iberia. Part II: Future Changes Using Regional Climate Projections

Seasonal droughts are a common feature of the Iberian (Mediterranean) climate. They can have severe impacts on both natural and human life – especially, when recurring in consecutive years. In this study, we investigate the potential impacts of climate change on recurrent drought events in the Iberian Peninsula (IP). With this aim, we use the new set of indices introduced in Moemken and Pinto (2022): the Recurrent Dry Year Index (RDYI) and the Consecutive Drought Year (CDY) Index. These are applied to a large EURO-CORDEX multi-model ensemble consisting of 25 different global-to-regional model (GCM-RCM) chains that follow the RCP8.5 scenario with 12 km horizontal resolution. A drizzle correction and a simple multiplicative approach are used to bias-adjust the daily precipitation sums. Results reveal a general tendency towards more severe drought conditions in IP under different global warming levels (GWLs). Moreover, recurrent drought events are projected to occur more frequent and last longer. While the ensemble mean responses are only moderate for a GWL of +2°C (compared to the pre-industrial average), recurrent drought conditions are strongly enhanced for the +3°C GWL. The magnitude of projected changes shows some sensitivity on the choice of index and model. Typically, changes are more pronounced for indices based on the effective drought index (EDI) and show a larger spread for the individual GCMs than for the various RCMs. Nevertheless, the climate change signals are robust for most of IP and all indices, with a larger model agreement for the +3°C GWL. We conclude that the Iberian Peninsula is confronted with an increased risk of recurrent drought events in future decades. If global warming should exceed the +3°C threshold, the majority of models projects an almost permanent state of drought – which could result in severe implications for the Iberian population and ecosystems.

Recurrence of Drought Events Over Iberia. Part I: Methodology and Application for Present Climate Conditions

Seasonal drought is a typical feature of the Mediterranean climate that may lead to strong socioeconomic and ecological impacts. We investigate the occurrence and intensity of historical extreme drought events over the Iberian Peninsula (IP) for the past decades, with special focus on recurrent drought events. With this aim, we introduce and apply a new set of indices: The Recurrent Dry Year Index (RDYI) and the Consecutive Drought Year (CDY) Index. Additionally, three drought indices are considered for individual events: A simple Drought Index (DI) based on precipitation deficits and the number of affected grid points, the Effective Drought Index (EDI), and the Standardized Precipitation Index (SPI). Different gridded observational (E-OBS V20e, IBERIA01) and reanalysis datasets (ERA5) are analysed at several spatial resolutions, ranging roughly between 10km and 25km. Results show that extreme droughts are a common feature in the IP, with roughly three individual events per decade. Especially the southern and central parts of IP are exposed to recurrent events. These events typically last two to three years, but may reach a length of six consecutive years. Sensitivity in the number of drought years is found regarding the spatial resolution. Moreover, drought is identified more often with EDI, leading to an enhanced number of recurrent droughts. (Recurrent) Droughts in IP are driven by precipitation deficits in winter (rainiest season) as there is hardly any precipitation during summer over most of IP. Still, deficits in spring and autumn may also be decisive, and some sensitivity is identified regarding the choice of index and the affected region. We conclude that the new indices are suitable for the detection and analysis of recurrent drought events. They are a first step towards a systematic worldwide evaluation of recurrent drought events under present and future climate conditions.

A New Set of Indexes and Thresholds of Preventive Maintenance Decision Making for Airport Runway Composite Pavement

A New Set of Indexes and Thresholds of Preventive Maintenance Decision Making for Airport Runway Composite Pavement

Bias-normal index: A new indicator of dense random packing for thermal polymer/ceramic composites

Thermal composites are widely used in thermal management. Usually, they consist of polymers and fillers. In pursuit of higher thermal conductivity, the fillers are mostly spherical particles for higher packing density. In previous work, the relationship between particle size distribution (PSD) and packing density was studied, especially the parameters such as polydispersity δ and the skewness S are defined to characterize the PSD. However, in our observation, for sieving process, which is very helpful in manipulating PSD and thus tuning thermal conductivity, δ and S are not good enough to explain most of the compositing results. Here, we suggest a new set of indices (bias-normal indices) to evaluate the sieving efficacy. Three kinds of ceramic powders (MgO, Al 2 O 3 , and AlN) and their single- and triple-order composites materials were prepared. The results show that the explanations based on bias-normal ratio index agree well with all the experiments. Thus, this new indicator is competent in guiding the recipe design of the thermal composite materials, and when well-designed recipes are employed, sieving is proven an efficient and simple way to promote the thermal performance, which is of great practical value.

Institutions and Economic Development: New Measurements and Evidence

We propose a new set of indices to capture the multidimensionality of a country’s institutional quality. Our indices are obtained by employing a dimension reduction approach on the institutional variables provided by the Frazer Institute (2018). We estimate the impact that our measures of institutional quality have on the level and the growth rate of per capita GDP, using a large sample of countries over the period 1980-2015. To identify the causal effect of our measures of institutional quality on a country’s GDP dynamics we employ the Generalized Propensity Score method. Institutions matter especially in low- and middle-income countries, and not all institutions are alike for economic development. For this group of countries, we find: i) a positive correlation between our main institutional index and the GDP growth and ii) that improvement in the reliability and fairness of the legal system leads to a higher long-run per capita GDP level. We also document non-linearities in the causal effects that different institutions have on growth, and the presence of threshold effects.

Evaluating Rainfall Risk Profile of Indian Subcontinent Based on Index Metrics

Floods and droughts represent an embedded monsoon factor impacting the Indian economy. Evaluating monsoon risk based on rainfall index metrics could help design appropriate alternative risk transfer products. This study proposes a new set of rainfall indices that can be used to explore the excess rainfall risk profile of the Indian Subcontinent. The study proposed a new set of indices for evaluating excess rainfall risk profiles which are defined as Excess Rainfall Days (ERDs). The methodology proceeds in a step-wise form: Empirical values of ERDs over 50 years for selected MSDs of India are derived, and then these index values are analyzed for determining the degree of variability and volatility, followed by the examination of the degree of inter-correlation amongst indices of selected Meteorological Sub-divisions. The research is based on the applications of econometric models such as the Augmented Dickey-Fuller (ADF) test followed by the GARCH model. The results revealed that several of the statistical properties of ERD indices support the idea that these indices could be used as building blocks for designing rainfall derivatives similar to HDDs/CDDs underlying temperature derivatives.

Singular value decomposition‐based load indexes for load profiles clustering

Choosing suitable load indexes of load profiles is of vital importance for load profiles clustering, which has wide applications in load forecasting, power grid planning and electricity price designing. To obtain a set of load indexes with rigorous mathematical theory and clear physical meaning, this study proposed a singular value decomposition (SVD) based method to extract indexes. First, empirical rank-l approximation derived from SVD is proposed to extract load indexes. The relationship between singular values and relative approximation error guarantees the indexes retain major characteristics of load profiles, while the invariance of right singular vectors over seasons and sample sizes endows the indexes with good generalisation ability. Then the right singular vectors are discretised to determine definition of indexes and reveal physical meanings of the indexes. Finally, the new set of indexes extracted by the proposed method are applied in indirectly clustering in the case study, which verify the validity of the indexes, the performance of the clustering method and the advantages of the new indexes over the existing load shape indexes.

Determining the dependence structure of multivariate extremes

Summary In multivariate extreme value analysis, the nature of the extremal dependence between variables should be considered when selecting appropriate statistical models. Interest often lies in determining which subsets of variables can take their largest values simultaneously while the others are of smaller order. Our approach to this problem exploits hidden regular variation properties on a collection of nonstandard cones, and provides a new set of indices that reveal aspects of the extremal dependence structure not available through existing measures of dependence. We derive theoretical properties of these indices, demonstrate their utility through a series of examples, and develop methods of inference that also estimate the proportion of extremal mass associated with each cone. We apply the methods to river flows in the U.K., estimating the probabilities of different subsets of sites being large simultaneously.

Global Sensitivity Analysis for Multiple Interpretive Models With Uncertain Parameters

AbstractWe propose a set of new indices to assist global sensitivity analysis in the presence of data allowing for interpretations based on a collection of diverse models whose parameters could be affected by uncertainty. Our global sensitivity analysis metrics enable us to assess the sensitivity of various features (as rendered through statistical moments) of the probability density function of a quantity of interest with respect to imperfect knowledge of (i) the interpretive model employed to characterize the system behavior and (ii) the ensuing model parameters. We exemplify our methodology for the case of heavy metal sorption onto soil, for which we consider three broadly used (equilibrium isotherm) models. Our analyses consider (a) an unconstrained case, i.e., when no data are available to constrain parameter uncertainty and to evaluate the (relative) plausibility of each considered model, and (b) a constrained case, i.e., when the analysis is constrained against experimental observations. Our moment‐based indices are structured according to two key components: (a) a model‐choice contribution, associated with the possibility of analyzing the system of interest by taking advantage of multiple model conceptualizations (or mathematical renderings); and (b) a parameter‐choice contribution, related to the uncertainty in the parameters of a selected model. Our results indicate that a given parameter can be associated with diverse degrees of importance, depending on the considered statistical moment of the target model output. The influence on the latter of parameter and model uncertainty evolves as a function of the available level of information about the modeled system behavior.

NEW INDUSTRIAL BUSINESS MODELS: FROM LINEAR TO CIRCULAR ECONOMY APPROACH

In the growth of the Industry 4.0 transformation the economy has become to changed. Thus, not just the economy regulations are fostered but a new business approach has been arisen: the circular / regenerative economy approach. The EC already reacted as it introduced not just updated Sustainable development indices but a new set of indices: circular economy indices. According to this change of the economic model, the business organizations are fostered to change their business models, especially for the industry. Thus, not just the new regulations have to be introduced to the industrial business model but the total change of the added value of the business as introduction of green technologies or innovations for non-waste production value chains. Aim of the paper: to identify and to analyze the requirements to the business that foster them to change their linear business model to circular one. Methods: descriptive analysis of the Bulgarian economy according to circular economy indices; comparative analyses for identification of main differences between linear and circular economies; induction and deduction of the elements of business models. Results: analysis of the indices of circularity of the Bulgarian economy; analysis of requirements for transition from linear to circular economy; identifying requirements to the business model of a circular economy; systematizing rules / guidelines for transforming the business model of a linear economy into the business model of a circular economy. Conclusions: The indicators of the circular economy can be considered as a part of the harmonization process in the EU. Avoiding from the responsibilities of the circular economy approach by Bulgarian industry leads to moving away from the EU economies. This requires relevant national policies, measures and instruments to promote the transformation of the business model to circular one. The paper aims to present the need of industrial business model change as to analyze the starting position of the Bulgarian industry. Thus, the structure of the paper is following: 1. Introduction to Circular economy indices. 2. Definition of Circular economy approach. 3. Analysis of the Circular economy indices change for Bulgaria. 4. Introduction to business model change from linear to circular one. Conclusions.

Populism, Ethnic Nationalism and Xenophobia

In this paper, we study a set of new indices, which are based on the answers of citizens to certain batteries of items included in a CSES module 5 pilot study conducted in Greece after the parliamentary election of September 2015. The first index is used to capture attitudes of citizens towards the political elites and is related to the increasing number of recent publications focusing on the study of populist attitudes. Likewise, the second index is based on items related to a demand for more power to the poor people. Another index developed here is built to measure attitudes towards out-groups. The use of this index is motivated by the increasing power of radical right-wing anti-immigrant parties, especially in Europe and due, to a certain extent, to the recent immigrant crisis. In addition to the aforementioned indices, we also identify the characteristics respondents think to be the most important for someone to be considered as a Real Greek, i.e. we present what are the most important lines that according to Greek citizens separate the in-group from the out-groups.

A new segregation index for solid multicomponent mixtures

Several indices can be found in the literature in order to quantify the mixing degree of two component mixtures in fluidized beds, but none of them is actually capable of describing how a specific component of the mixture is distributed. Many of these indices may be influenced by the experimental procedure used for evaluating the mixture, such as the number of vacuumed layers, or equivalently the layer thickness, since the solids distribution is generally measured in layers (or at most in cells) and not in a continuous way along the bed. In the present work, a novel set of indices for studying segregation is proposed: the Three Thirds Segregation Indices Set, is developed allowing the characterization of not only the segregation level, but also the segregation pattern of a specific component of interest. The set is also compared, tested and validated with other existing indices (M index by Rowe et al. (1972) and “s” index by Goldscmidt et al. (2003)), and experimentally verified. As a result of these tests, it is found that M and “s” indices do not allow the comparison of experiments performed with different numbers of layers, and they do not distinguish different segregation profiles leading to some mistakes when in the proximity to the extreme cases (Full Central or Full Bottom segregation). On the opposite, the new set of indices turns out to be independent on the number of layers, and to minimize experimental errors or the discrepancies caused by applying different experimental procedures.

Competitive Pattern of Foreign Direct Investment in India

Globalization can be summarized as opening-up of markets, leading to transfer of capital, technology and people. However, another important dimension of globalization is multilateralism. The international economic reforms encourage multilateralism leads allocative efficiency. Multilateralism implies importing capital from a variety of sources as may be most efficient. Indias FDI policy is in alignment with global FDI. In 1991, India had receiving FDI from 86 investing countries, which reached to 137 investing countries in 2013. This indicates global attractiveness and preferred investment destination. The paper examines FDI investing pattern of source countries in India. The period of study is 1991-2013. The paper applies a set of new indices like Index of Rank Dominance (IRD) and Bodenhorns measure of Mobility and Turnover. The most dominant country is USA. The RIRD (Relative Index of Rank Dominance) are top heavy. The first five countries are investing more than 60 percent FDI in India. Asian Tiger countries invested around 11 percent and BRICS countries have insignificant FDI in India. The competitive pattern of FDI has been declined among three different grouping countries. The global FDI in India has been declined 8 percent per annum in spite of favoured investment destination.

Indo-China monsoon indices.

Myanmar and Thailand often experience severe droughts and floods that cause irreparable damage to the socio-economy condition of both countries. In this study, the Southeastern Asian Summer Monsoon variation is found to be the main element of interannual precipitation variation of the region, more than the El Niño/Southern Oscillation (ENSO). The ENSO influence is evident only during the boreal spring season. Although the monsoon is the major factor, the existing Indian Monsoon Index (IMI) and Western North Pacific Monsoon Index (WNPMI) do not correlate well with the precipitation variation in the study regions of Southern Myanmar and Thailand. Therefore, a new set of indices is developed based on the regional monsoon variations and presented here for the first time. Precipitation variations in Southern Myanmar and Thailand differ as well as the elements affecting the precipitation variations in different seasons. So, separate indices are proposed for each season for Southern Myanmar and Thailand. Four new monsoon indices based on wind anomalies are formulated and are named as the Indochina Monsoon Indices. These new indices correlate better with the precipitation variations of the study region as compared to the existing IMI and WNPMI.

Global Inward Foreign Direct Investment: Trends and Concentration Patterns

With globalisation, there has been a phenomenal rise in Foreign Direct Investment (FDI). This has led to an international relocation of production and consequent generation of income and employment. This, in turn, has led to international specialisation of production and is likely to maximize global welfare. This could happen only if the concentration of FDI is low or FDI is well distributed. We use a set of new indices and Herfindahl index of concentration to examine concentration of inward FDI in terms of flow and stock during 1990-2009. The results clearly indicate that there is a low concentration in distribution of FDI in terms of inflow and stock. The low concentration ratio implies that the share of developing countries is increasing. It implies that the distribution of FDI has been moving towards uniform distribution of productive resources across countries, which is the basic purpose of globalisation and competition.

Redefining the Economic Power of Nations

The paper challenges the current common rankings of economies when measured over the GDP, and introduces a set of new Indices based on the factors GDP, Gini Coefficient and Inflation. This Social factors relativized GDP cuts out that part of the GDP, which is structurally long term frozen up by social transfers. Furthermore, the paper introduces an economic model that implements the future aspect into the GDP over the factors of change in capital expenditures and change in private investments. The first part of the pa-per explains the κ_Index models, the factors that were applied, as well as the reasons for the choice. The second part of the paper shows variations of the κ_Index including a few ideal-typical examples. The final part asks some critical questions and concludes the pa-per. Basic social factors relativized GDP: κ _Index = GDP – GDP x Gini is (1 – GINI) x GDP Inflation indexed Version: κ _Index_Infl. = (1 – Gini – Inflation) x GDP Future aspect of GDP With Private Investment variable: κp = (B + B × ΔP) – (B × G) With Private Investment variable and inflation: κip = (B + B × ΔP) - [(B × G)+(B × In)] Productivity Index: κ_PROD = κ_Index / Labor Force = κ_PROD Inflation indexed Productivity Index: κ_PROD_Infl. = κ_Index_Infl. / Labor Force Debt-to- κ _Index κ _Debt = National debt / κ_Index Debt-to- κ _Index_Inflation κ _Debt_Infl. = National debt / κ_Index_Infl.

A network approach based on cliques

The characterization of complex networks is a procedure that is currently found in several research studies. Nevertheless, few studies present a discussion on networks in which the basic element is a clique. In this paper, we propose an approach based on a network of cliques. This approach consists not only of a set of new indices to capture the properties of a network of cliques but also of a method to characterize complex networks of cliques (i.e., some of the parameters are proposed to characterize the small-world phenomenon in networks of cliques). The results obtained are consistent with results from classical methods used to characterize complex networks.