Averaged Singular Integral Estimation as a Bias Reduction Technique

This paper proposes an averaged version of singular integral estimators, whose bias achieves higher rates of convergence under smoothing assumptions. We derive exact bias bounds, without imposing smoothing assumptions, which are a basis for deriving the rates of convergence under differentiability assumptions.Publicad

Epsilon contaminated priors in testing point null hypothesis: a procedure to determine the prior probability

In this paper the problem of testing a point null hypothesis from the Bayesian perspective and the relation between this and the classical approach is studied. A procedure to determine the mixed prior distribution is introduced and a justification for this construction based on a measure of discrepancy is given. Then, we compare a lower bound for the posterior probability, when the prior is in the class of -contaminated distributions, of the point null hypothesis with the p-value

The Differentiation Syndrome in Patients with Acute Promyelocytic Leukemia: Experience of the Pethema Group and Review of the Literature

Differentiation syndrome (DS), formerly known as retinoic acid syndrome, is the main life-threatening complication of therapy with differentiating agents (all-trans retinoic acid [ATRA] or arsenic trioxide [ATO]) in patients with acute promyelocytic leukemia (APL). The differentiation of leukemic blasts and promyelocytes induced by ATRA and/or ATO may lead to cellular migration, endothelial activation, and release of interleukins and vascular factors responsible of tissue damage. Roughly one quarter of patients with APL undergoing induction therapy will develop the DS, characterized by unexplained fever, acute respiratory distress with interstitial pulmonary infiltrates, and/or a vascular capillary leak syndrome leading to acute renal failure. Although the development of the DS, particularly of the severe form, is still associated with a significant increase in morbidity and mortality during induction, the early administration of high-dose dexamethasone at the onset of the first symptoms seems likely to have dramatically reduced the mortality rate of this complication. In this article, we will review the clinical features, incidence, prognostic factors, management, and outcome of the DS reported in the scientific literature. We will make focus in the experience of the three consecutive Programa Español de Tratamientos en Hematología trials (PETHEMA LPA96, LPA99, and LPA2005), in which more than one thousand patients were treated with ATRA plus idarubicin for induction

Bogdanov-Takens resonance in time-delayed systems

We analyze the oscillatory dynamics of a time-delayed dynamical system subjected to a periodic external forcing. We show that, for certain values of the delay, the response can be greatly enhanced by a very small forcing amplitude. This phenomenon is related to the presence of a Bogdanov- Takens bifurcation and displays some analogies to other resonance phenomena, but also substantial differences.Comment: 14 pages, 8 figure

Global rates of convergence for the bias of singular integral estimators and their shifted versions

This paper provides global rates of convergence for the bias of singular integral estimators of a probability density function under weak conditions, which avoid differentiability. It is also shown that, under smoothing conditions, shifting the singular integral estimators provides a bias reduction technique

On universal unbiasedness of delta estimators

This paper considers delta estimators of a Radon-Nicodym derivative of a probability function with respect to a measure. Sufficient conditions for asymptotic unbiasedness and global rates of convergence, which can be improved by imposing differentiability conditions on the estimated curves, are provided. A bias reduction technique is proposed, and the application of the results to regression estimation is discussed. The sufficient conditions for asymptotic unbiasedness are checked for some broad classes of nonparametric estimators

Long-term management of chronic immune thrombocytopenic purpura in adults

Chronic immune thrombocytopenic purpura (ITP) is generally a more benign disease than previously thought. Currently it is recommended that only those patients with severe and/or symptomatic thrombocytopenia definitely require treatment. Additional factors, such as age, lifestyle, and uremia can also influence the hemorrhagic risk and should be carefully assessed before decision-making on the appropriate management of patients with less severe forms of ITP. The recent introduction of new classes of therapeutic agents such as rituximab and the thrombopoietic growth factors has had a major impact on the management of ITP. Updated treatment guidelines have recently been made available but they are based largely on expert opinion rather than on high-quality clinical trial evidence. This structured review is focused on the management of adults with chronic ITP, including the use of new classes of agents

Application of Machine Learning Methods for Asset Management on Power Distribution Networks

This study aims to study the different kinds of Machine Learning (ML) models and their working principles for asset management in power networks. Also, it investigates the challenges behind asset management and its maintenance activities. In this review article, Machine Learning (ML) models are analyzed to improve the lifespan of the electrical components based on the maintenance management and assessment planning policies. The articles are categorized according to their purpose: 1) classification, 2) machine learning, and 3) artificial intelligence mechanisms. Moreover, the importance of using ML models for proper decision making based on the asset management plan is illustrated in a detailed manner. In addition to this, a comparative analysis between the ML models is performed, identifying the advantages and disadvantages of these techniques. Then, the challenges and managing operations of the asset management strategies are discussed based on the technical and economic factors. The proper functioning, maintenance and controlling operations of the electric components are key challenging and demanding tasks in the power distribution systems. Typically, asset management plays an essential role in determining the quality and profitability of the elements in the power network. Based on this investigation, the most suitable and optimal machine learning technique can be identified and used for future work. Doi: 10.28991/ESJ-2022-06-04-017 Full Text: PD