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Manuscript Type: Conceptual. Research Question/Issue: Shareholding structures are sometimes so complex that it can be difficult to know who are the actual owners and controllers of a firm. In particular, in continental Europe and Asia, control tunnelling appears frequently through pyramidal structures. Different methods exist to isolate control from ownership. This paper attempts to better understand these different models and their implications. Research Findings/Results: After describing ownership structure through a graph association, this paper analyzes the voting game at stake in the race for control. It compares existing methods and algorithms to identify the owners and controllers of a firm in a pyramidal structure without cross-ownership. These different methods are then applied to the case of a Belgian retailer, Colruyt. The results are compared and the influence of a control threshold is analyzed. Furthermore, it shows how the ownership structure allows the Colruyt family to maintain control of the firm even if there is dissension within the family. Theoretical Implications: This study clarifies definitions of ownership structures and provides a better understanding of models that analyze ownership structure and their implications. Practical Implications: In practice, these models can help shareholders achieve a majority of voting rights in the general assembly by identifying who are the influential partners. Furthermore, the models provide a means for external parties to determine whether control of a firm is attainable, and if so, how. Established shareholders may also use these models to ascertain the optimal ownership structure that will preserve their control with a minimum level of investment. [ABSTRACT FROM AUTHOR]

This paper discusses the variation between generic soil screening values (SSV) from 17 countries for 11 volatile organic contaminants (VOC). The variation between SSV was one to four orders-of- magnitude (OOM) depending on the SSV and landuse type. What would be the variation if parameter values are harmonized between member states? The effect of harmonization was visualized by firstly reviewing the technical derivation procedure for SSV for 7 SSV from five countries and collecting all parameter values that are involved in the deviation. The parameters were subdivided in scientific (e.g. algorithm plus its parameter values), political (e.g. toxicological reference) or geographical (e.g. building and soil properties) elements. Secondly, new SSV were calculated with progressively harmonized sets of scientific andlor political parameter values, while the geographical parameters varied. Thirdly, the variation between SSV was compared before and after harmonization. Results show that harmonizing algorithms plus other scientific and political parameters are suited for harmonization. The variation decreases to I OOM, after scientific and political parameters were harmonized. Geographical parameters seem to have less impact on the differences between SSV. So, should we harmonize the procedures for deriving SSV between EU member states? The need for discussing harmonization is also raised by the upcoming EU Soil Framework Directive. Clearly common generic SSV across all of Europe are not appropriate, since countries are allowed to include member state specific geographical and cultural elements and also political decision making. By harmonizing scientific andlor political parameters differences between SSV can be made more transparent between member states and it will encourage convergence in procedures among member states to ensure neutral conditions of competition and a coherent soil protection regime throughout Europe. To promote uniformity it is recommended to construct a toolbox for the calculation of human health risk exposure, carried by a European consensus, that includes different model algorithms for which fixed and flexible input parameters are made available. Fixed algorithm parameters are standardized and applied uniformly by all member states, e.g. physico- chemical parameters, while flexible input parameters permits member states to include region or country specific parameter values and policy decisions. [ABSTRACT FROM AUTHOR]

The paper proposes a fully automatic algorithm approach to map burned areas from remote sensing characterized by human interpretable mapping criteria and explainable results. This approach is partially knowledge-driven and partially data-driven. It exploits active fire points to train the fusion function of factors deemed influential in determining the evidence of burned conditions from reflectance values of multispectral Sentinel-2 (S2) data. The fusion function is used to compute a map of seeds (burned pixels) that are adaptively expanded by applying a Region Growing (RG) algorithm to generate the final burned area map. The fusion function is an Ordered Weighted Averaging (OWA) operator, learnt through the application of a machine learning (ML) algorithm from a set of highly reliable fire points. Its semantics are characterized by two measures, the degrees of pessimism/optimism and democracy/monarchy. The former allows the prediction of the results of the fusion as affected by more false positives (commission errors) than false negatives (omission errors) in the case of pessimism, or vice versa; the latter foresees if there are only a few highly influential factors or many low influential ones that determine the result. The prediction on the degree of pessimism/optimism allows the expansion of the seeds to be appropriately tuned by selecting the most suited growing layer for the RG algorithm thus adapting the algorithm to the context. The paper illustrates the application of the automatic method in four study areas in southern Europe to map burned areas for the 2017 fire season. Thematic accuracy at each site was assessed by comparison to reference perimeters to prove the adaptability of the approach to the context; estimated average accuracy metrics are omission error = 0.057, commission error = 0.068, Dice coefficient = 0.94 and relative bias = 0.0046. [ABSTRACT FROM AUTHOR]

As a result of many factors, including the European Union's aim to increase the share of electrical energy from renewable sources, the number of distributed-generation (DG) devices in Europe is significantly increasing. Increasing numbers of DG units may cause problems with power quality (PQ). In this paper, a PQ-management algorithm is presented that reduces or even solves this problem in low-voltage grids. This algorithm will be implemented as one of several software modules in a system for distributed power operation and PQ management in low-voltage grids. PQ management in this context means maintaining PQ within prescribed limits by optimizing the control of generators, storage units, and controllable loads. Significant advantages of the presented approach are that the algorithm is universal and that it adapts its control variables automatically. Therefore, a detailed analysis of the grid in advance is not necessary. Furthermore, local PQ control of distributed resources can work autonomously and continuously without triggering by external signals, which is advantageous in the case of loss of communications. Various simulations to validate the effectiveness and stable operation of the algorithm were performed and results presented that show a marked improvement in PQ. [ABSTRACT FROM AUTHOR]

This paper estimates the readiness of the accession countries of Central and Eastern Europe for EMU or unilateral euroization using a fuzzy clustering algorithm. The variables to which the algorithm is applied are suggested alternately by the criteria in the Maastricht Treaty (nominal convergence) and by Optimum Currency Area theory (real convergence). The algorithm reveals that Estonia and Slovenia are the leaders in both nominal and real convergence, whereas the other countries from the 1998 accession wave have achieved substantial results only in real convergence. Moreover, Poland is excluded from the leading group in the most recent years due to its worsened economic performance. Copyright © 2003 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The recruitment of athletes with limited resources is a global problem in professional sports. In US Major League Baseball, the experience of the Oakland Athletics' general manager in the last decade turned his "Moneyball" model into a synonym of quantitative analysis in the transfer market of baseball players. His strategy focused on hiring players with outstanding technical skills but relatively low market value. This study adapted this model to the framework of a multiple criteria decision aid (MCDA), by selecting undervalued players who have complementary abilities. The novelty here refers to the joint use of four algorithms explored by the composition of probabilistic preferences (CPP) (i.e., ranking, classification, dynamic evaluation and regularity analysis) and their application to soccer player performance evaluation. The new model analysed the recent transfer of a left-back soccer player to Europe. The results indicated 12 opportunities for better investment, among 32 left and right-back players considered. Two years later, the value of the same player was considerably lower. He played only five matches in the 2018–2019 season, without scoring or providing any assists. On the other hand, the players better classified by the CPP-MB model presented higher performances and market values. [ABSTRACT FROM AUTHOR]

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Objective: The long-term predictive value of the new proposed algorithm in the updated 2016 guidelines of the European Association of Cardiovascular Imaging to assess diastolic dysfunction (DD) in patients with heart failure with preserved ejection fraction (HFpEF) has not been validated.Methods: The analysis included 451 patients who were diagnosed with HFpEF as confirmed via echocardiography. The endpoints were mortality and hospitalization for HF. The Kaplan-Meier curves and Cox regression models were generated to determine the risk of all-cause mortality based on the 2016 and 2009 DD grading algorithm, respectively. We evaluated the net reclassification index of outcomes on the basis of 2009 DD grade after abiding by the 2016 recommendations.Results: After a follow-up of 2976 days, 119 patients (26.4%) died. According to the 2016 DD grading, grade III DD was associated with a significantly higher risk of mortality (hazard ratio [HR], 2.209; 95% CI 1.144-4.266) and HF hospitalization (HR, 2.047; 95% CI 1.348-3.870), as compared with grade I DD. Grade II DD was also associated with a higher risk of mortality (HR, 1.538; 95% CI 1.313-1.924). However, only grade III DD was independently associated with worse mortality based on 2009 DD grading. The net reclassification index for mortality increased significantly after grading by 2016 algorithm (10.6%, p < 0.001).Conclusions: The 2016 DD grading algorithm showed improved prognostic value of long-term mortality in patients with HFpEF. Based on the findings of the study, the appropriate grading of DD is important in the prognostication of patients with HFpEF.Key Points: • The application of the 2016 European Association of Cardiovascular Imaging recommendations diastolic dysfunction (DD) grading algorithm improves the predictive value for mortality. • Our analysis suggests DD grades II and III based on 2016 guidelines is associated with poor outcomes as compared with grade I. The echocardiographic indices of the new algorithm should be obtained and applied to effectively evaluate DD. [ABSTRACT FROM AUTHOR]

Breakthrough pain is common in patients with cancer and is a significant cause of morbidity in this group of patients. Breakthrough pain is a heterogeneous condition, and so its management needs to be individualised. This paper describes the management of breakthrough pain and, specifically, the recently published guidelines of the European Oncology Nursing Society. [ABSTRACT FROM AUTHOR]

Three algorithm intercomparison experiments have recently been conducted as part of the Global Precipitation Climatology Project with the goal of (a) assessing the skill of current satellite rainfall algorithms, (b) understanding the differences between them, and (c) moving toward improved algorithms. The results of these experiments are summarized and intercompared in this paper. It was found that the skill of satellite rainfall algorithms depends on the regime being analyzed, with algorithms producing very good results in the tropical western Pacific and over Japan and its surrounding waters during summer, but relatively poor rainfall estimates over western Europe during late winter. Monthly rainfall was estimated most accurately by algorithms using geostationary infrared data, but algorithms using polar data [Advanced Very High Resolution Radiometer and Special Sensor Microwave/Imager (SSM/I)] were also able to produce good monthly rainfall estimates when data from two satellites were available. In most eases, SSM/I algorithms showed significantly greater skill than IR-based algorithms in estimating instantaneous rain rates. [ABSTRACT FROM AUTHOR]