Investigating the relationship between tax revenues and tax ratios : an empirical research for selected OECD countries

Purpose: Effective tax rates can have dual effect in the economic policy of a country by maintaining the state revenues in sustainable levels providing a safe net for the economic development. If taxation struggles the economy, there should be a turning point were the results of high tax rates do not have the expected results on the state revenue. The parabolic relation of Laffer curve is tested on a data set of different OECD countries. Design/Approach/Methodology: Three different functions have been selected to test the Laffer curve starting from the fact that the relation of revenues with taxes should have a parabolic form, with the turning point to be the peak of the parabola. Findings: The findings suggest that there exists a peak point where taxation policy is not providing the expected revenues. Results suggest that this pattern is common in several countries with different taxation regimes. The effective tax rates are different between the countries. Countries are divided into clusters with the same effective tax rates. The relation of the tax revenue and taxation rates is adjusted with the tax moral of the country. Practical Implications: The results are compared with other possible forms of the relation of revenue and taxes with considerable importance.peer-reviewe

International stock markets : a co-integration analysis

This study investigates the degree of co-integration between five major European stock markets and five major non European stock markets. The results show that all five major European stock markets are co-integrated either positively or negatively, while among the five major non European the Canadian, the Japanese and the Singapore are non cointegrated with the others. The results point towards a decreasing number of common stochastic trends influencing the stock markets, i.e. the degree of co-integration between the European stock markets has been increased during the recent decade.peer-reviewe

Knowledge based cloud FE simulation of sheet metal forming processes

The use of Finite Element (FE) simulation software to adequately predict the outcome of sheet metal forming processes is crucial to enhancing the efficiency and lowering the development time of such processes, whilst reducing costs involved in trial-and-error prototyping. Recent focus on the substitution of steel components with aluminum alloy alternatives in the automotive and aerospace sectors has increased the need to simulate the forming behavior of such alloys for ever more complex component geometries. However these alloys, and in particular their high strength variants, exhibit limited formability at room temperature, and high temperature manufacturing technologies have been developed to form them. Consequently, advanced constitutive models are required to reflect the associated temperature and strain rate effects. Simulating such behavior is computationally very expensive using conventional FE simulation techniques. This paper presents a novel Knowledge Based Cloud FE (KBC-FE) simulation technique that combines advanced material and friction models with conventional FE simulations in an efficient manner thus enhancing the capability of commercial simulation software packages. The application of these methods is demonstrated through two example case studies, namely: the prediction of a material's forming limit under hot stamping conditions, and the tool life prediction under multi-cycle loading conditions

Digitally-enhanced lubricant evaluation scheme for hot stamping applications

Digitally-enhanced technologies are set to transform every aspect of manufacturing. Networks of sensors that compute at the edge (streamlining information flow from devices and providing real-time local data analysis), and emerging Cloud Finite Element Analysis technologies yield data at unprecedented scales, both in terms of volume and precision, providing information on complex processes and systems that had previously been impractical. Cloud Finite Element Analysis technologies enable proactive data collection in a supply chain of, for example the metal forming industry, throughout the life cycle of a product or process, which presents revolutionary opportunities for the development and evaluation of digitally-enhanced lubricants, which requires a coherent research agenda involving the merging of tribological knowledge, manufacturing and data science. In the present study, data obtained from a vast number of experimentally verified finite element simulation results is used for a metal forming process to develop a digitally-enhanced lubricant evaluation approach, by precisely representing the tribological boundary conditions at the workpiece/tooling interface, i.e., complex loading conditions of contact pressures, sliding speeds and temperatures. The presented approach combines the implementation of digital characteristics of the target forming process, data-guided lubricant testing and mechanism-based accurate theoretical modelling, enabling the development of data-centric lubricant limit diagrams and intuitive and quantitative evaluation of the lubricant performance

Assessment of lipid uptake and fatty acid metabolism of European eel larvae (Anguilla anguilla) determined by 14C in vivo incubation

Knowledge on dietary nutrient requirements of first-feeding European eel larvae (Anguilla anguilla) is very limited. This study provides first ever information on in vivo lipid uptake and fatty acid (FA) metabolism of European pre-leptocephalus eel larvae and advances directions for dietary lipid and FA inclusions. The in vivo capability of eel larvae to incorporate and metabolize unsaturated fatty acids was tested on larvae at different ontogenetic stages (4, 8 and 12 days post hatch, DPH). Larvae were incubated in 10 mL flat-bottom tissue culture plates, with [1-14C]-labelled FA (18:2n-6, ALA; 18:3n-3, LA; 20:4n-6, ARA and 20:5n-3, EPA) directly added to seawater. The capability of the larvae for de-acylation and re-acylation of [1-14C]arachidonic acid (ARA), initially bound to phosphatidylcholine (PC) and phosphatidylethanolamine (PE), was also investigated. In all cases, control incubations without any radiolabelled substrate were performed for further lipid analysis. The results revealed that direct incubation with 14C-labelled FA is a feasible method to investigate in vivo FA and phospholipids metabolism of pre-leptocephalus stages of the European eel. No enzymatic elongation/desaturation activity towards [1-14C]C18 or [1-14C]C20 FA was detected. Consequently, ARA, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) must be considered essential FA and thus provided firstly through female broodstock and later through diet at least during the first-feeding stage. Pre-leptocephalus larvae display a high capacity to remodel dietary phospholipids with a preferential esterification of all FA substrates into PC. The unexpectedly high esterification rate of [1-14C] ARA into PC and PE is supported by the individual FA profiles of the larval phospholipids. The high levels of ARA present in the European eel larvae denotes its physiological relevance for this species. It is therefore essential to consider this FA as particularly important when designing suitable broodstock – or first-feeding diets for this species

Inconsistency of the MLE for the joint distribution of interval censored survival times and continuous marks

This paper considers the nonparametric maximum likelihood estimator (MLE) for the joint distribution function of an interval censored survival time and a continuous mark variable. We provide a new explicit formula for the MLE in this problem. We use this formula and the mark specific cumulative hazard function of Huang and Louis (1998) to obtain the almost sure limit of the MLE. This result leads to necessary and sufficient conditions for consistency of the MLE which imply that the MLE is inconsistent in general. We show that the inconsistency can be repaired by discretizing the marks. Our theoretical results are supported by simulations.Comment: 27 pages, 4 figure

VerdictDB: Universalizing Approximate Query Processing

Despite 25 years of research in academia, approximate query processing (AQP) has had little industrial adoption. One of the major causes of this slow adoption is the reluctance of traditional vendors to make radical changes to their legacy codebases, and the preoccupation of newer vendors (e.g., SQL-on-Hadoop products) with implementing standard features. Additionally, the few AQP engines that are available are each tied to a specific platform and require users to completely abandon their existing databases---an unrealistic expectation given the infancy of the AQP technology. Therefore, we argue that a universal solution is needed: a database-agnostic approximation engine that will widen the reach of this emerging technology across various platforms. Our proposal, called VerdictDB, uses a middleware architecture that requires no changes to the backend database, and thus, can work with all off-the-shelf engines. Operating at the driver-level, VerdictDB intercepts analytical queries issued to the database and rewrites them into another query that, if executed by any standard relational engine, will yield sufficient information for computing an approximate answer. VerdictDB uses the returned result set to compute an approximate answer and error estimates, which are then passed on to the user or application. However, lack of access to the query execution layer introduces significant challenges in terms of generality, correctness, and efficiency. This paper shows how VerdictDB overcomes these challenges and delivers up to 171$\times$ speedup (18.45$\times$ on average) for a variety of existing engines, such as Impala, Spark SQL, and Amazon Redshift, while incurring less than 2.6% relative error. VerdictDB is open-sourced under Apache License.Comment: Extended technical report of the paper that appeared in Proceedings of the 2018 International Conference on Management of Data, pp. 1461-1476. ACM, 201