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In the last few years, the use of oral sirolimus has shown promising results in the treatment of some complex vascular anomalies, and recently, it has been used in patients with Sturge‐Weber syndrome (SWS). We present the case of an 11‐year‐old girl with the diagnosis of SWS and hemifacial overgrowth treated with oral sirolimus. Throughout the eight months of follow‐up, improvement of the port‐wine birthmark, intraocular pressure, and neurocognitive development was noted. The mTOR inhibitors may be useful in the treatment of some patients with SWS. [ABSTRACT FROM AUTHOR]

This paper introduces the concept of Choquet-like Copula-based aggregation function (CC-integral) and its application in fuzzy rule-based classification systems. The standard Choquet integral is expanded by distributing the product operation. Then, the product operation is generalized by a copula. Unlike the generalization of the Choquet integral by t-norms using its standard form (i.e., without distributing the product operator), which results in a pre-aggregation function, the CC-integral satisfies all the conditions required for an aggregation function. We build some examples of CC-integrals considering different examples of copulas, including t-norms, overlap functions and copulas that are neither t-norms nor overlap functions. We show that the CC-integral based on the minimum t-norm, when applied in fuzzy rule-based classification systems, obtains a performance that is, with a high level of confidence, better than that which adopts the winning rule (maximum). We concluded that the behavior of CC-integral is similar to the best Choquet-like pre-aggregation function. Consequently, the CC-integrals introduced in this paper can enlarge the scope of the applications by offering new possibilities for defining fuzzy reasoning methods with a similar gain in performance. [ABSTRACT FROM AUTHOR]

A 4-year-old boy was referred for asymptomatic thrombocytopenia for several months associated with abnormal pigmentation and leukoplakia. A germline homozygous missense mutation was identified in I RTEL1 i (regulator of telomere elongation helicase 1) for which variant c.296T>G was detected. Unraveling the pathogenesis of Hoyeraal-Hreidarsson syndrome, a complex telomere biology disorder. [Extracted from the article]

The article present a case study of a 8-year-old boy with prominent venous vessels and hyperlaxity. It mentions on his physical examination, he had a triangular face, long philtrum, thick lips aphthous stomatitis, periodontitis, and a prominent venous circulation on his trunk and extremities; and also mentions with the clinical and laboratory findings, test of the G6PC3 gene was performed on peripheral blood and revealed a homozygous 1-bp deletion in the exon 2.

Exserohilum species are environmental molds that may rarely cause skin and nasal infections, especially in immunocompromised children. We present a 3‐year‐old girl with acute leukemia who presented with a skin infection caused by Exserohilum rostratum. Previously published cases of skin infections by Exserohilum spp. in children are reviewed. [ABSTRACT FROM AUTHOR]

Overlap functions are a class of aggregation functions that measure the overlapping degree between two values. They have been successfully applied as a fuzzy conjunction operation in several problems in which associativity is not required, such as image processing and classification. Interval-valued overlap functions were defined as an extension to express the overlapping of interval-valued data, and they have been usually applied when there is uncertainty regarding the assignment of membership degrees, as in interval-valued fuzzy rule-based classification systems. In this context, the choice of a total order for intervals can be significant, which motivated the recent developments on interval-valued aggregation functions and interval-valued overlap functions that are increasing to a given admissible order, that is, a total order that refines the usual partial order for intervals. Also, width preservation has been considered on these recent works, in an intent to avoid the uncertainty increase and guarantee the information quality, but no deeper study was made regarding the relation between the widths of the input intervals and the output interval, when applying interval-valued functions, or how one can control such uncertainty propagation based on this relation. Thus, in this paper we: (i) introduce and develop the concepts of width-limited interval-valued functions and width limiting functions, presenting a theoretical approach to analyze the relation between the widths of the input and output intervals of bivariate interval-valued functions, with special attention to interval-valued aggregation functions; (ii) introduce the concept of (a , b) -ultramodular aggregation functions, a less restrictive extension of one-dimension convexity for bivariate aggregation functions, which have an important predictable behaviour with respect to the width when extended to the interval-valued context; (iii) define width-limited interval-valued overlap functions, taking into account a function that controls the width of the output interval and a new notion of increasingness with respect to a pair of partial orders (≤ 1 , ≤ 2) ; (iv) present and compare three construction methods for these width-limited interval-valued overlap functions, considering a pair of orders (≤ 1 , ≤ 2) , which may be admissible or not, showcasing the adaptability of our developments. [ABSTRACT FROM AUTHOR]

• We make a revision of recent generalizations of the Choquet integral that appear in the literature. • We show some of the most relevant theoretical features of these extensions. • We also discuss some applications where these extensions have provided good results. In 2013, Barrenechea et al. used the Choquet integral as an aggregation function in the fuzzy reasoning method (FRM) of fuzzy rule-based classification systems. After that, starting from 2016, new aggregation-like functions generalizing the Choquet integral have appeared in the literature, in particular in the works by Lucca et al. Those generalizations of the Choquet integral, namely C T -integrals (by t-norm T), C F -integrals (by a fusion function F satisfying some specific properties), CC -integrals (by a copula C), C F 1 F 2 -integrals (by a pair of fusion functions (F 1 , F 2) under some specific constraints) and their generalization gC F 1 F 2 -integrals, achieved excellent results in classification problems. The works by Lucca et al. showed that the aggregation task in a FRM may be performed by either aggregation, pre-aggregation or just ordered directional monotonic functions satisfying some boundary conditions, that is, it is not necessary to have an aggregation function to obtain competitive results in classification. The aim of this paper is to present and discuss such generalizations of the Choquet integral, offering a general panorama of the state of the art, showing the relations and intersections among such five classes of generalizations. First, we present them from a theoretical point of view. Then, we also summarize some applications found in the literature. [ABSTRACT FROM AUTHOR]

This paper introduces the theoretical framework for a generalization of C F 1 F 2 -integrals, a family of Choquet-like integrals used successfully in the aggregation process of the fuzzy reasoning mechanisms of fuzzy rule based classification systems. The proposed generalization, called by g C F 1 F 2 -integrals, is based on the so-called pseudo pre-aggregation function pairs (F 1 , F 2) , which are pairs of fusion functions satisfying a minimal set of requirements in order to guarantee that the g C F 1 F 2 -integrals to be either an aggregation function or just an ordered directionally increasing function satisfying the appropriate boundary conditions. We propose a dimension reduction of the input space, in order to deal with repeated elements in the input, avoiding ambiguities in the definition of g C F 1 F 2 -integrals. We study several properties of g C F 1 F 2 -integrals, considering different constraints for the functions F 1 and F 2 , and state under which conditions g C F 1 F 2 -integrals present or not averaging behaviors. Several examples of g C F 1 F 2 -integrals are presented, considering different pseudo pre-aggregation function pairs, defined on, e.g., t-norms, overlap functions, copulas that are neither t-norms nor overlap functions and other functions that are not even pre-aggregation functions. [ABSTRACT FROM AUTHOR]

As a generalization of bivariate overlap functions, which measure the degree of overlapping (intersection for non-crisp sets) of n different classes, in this paper we introduce the concept of general overlap functions. We characterize the class of general overlap functions and include some construction methods by means of different aggregation and bivariate overlap functions. Finally, we apply general overlap functions to define a new matching degree in a classification problem. We deduce that the global behaviour of these functions is slightly better than some other methods in the literature. [ABSTRACT FROM AUTHOR]

In this paper we present a new fuzzy reasoning method in which the Choquet integral is used as aggregation function. In this manner, we can take into account the interaction among the rules of the system. For this reason, we consider several fuzzy measures, since it is a key point on the subsequent success of the Choquet integral, and we apply the new method with the same fuzzy measure for all the classes. However, the relationship among the set of rules of each class can be different and therefore the best fuzzy measure can change depending on the class. Consequently, we propose a learning method by means of a genetic algorithm in which the most suitable fuzzy measure for each class is computed. From the obtained results it is shown that our new proposal allows the performance of the classical fuzzy reasoning methods of the winning rule and additive combination to be enhanced whenever the fuzzy measure is appropriate for the tackled problem. [ABSTRACT FROM AUTHOR]

A divergent approach was used for the synthesis of dendritic structures based on a cyclotriphosphazene core with 12 or 24 hydroxyl groups, by starting from [N3P3(OC6H4OH-4)6] and using an acetal-protected 2,2-di(hydroxymethyl)propionic anhydride as the acylating agent. Hydroxyl groups in these first- and second-generation dendrimers, G1-(OH)12 or G2-(OH)24, were then condensed in turn with mono- or polycatenar pro-mesogenic acids to study their ability to promote self-assembly into liquid crystalline structures. Reactions were monitored by using 31P{1H} and 1H NMR spectroscopy and the chemical structure of the resulting materials was confirmed by using different spectroscopic techniques and mass spectrometry (MALDI-TOF MS). The results were in accordance with monodisperse, fully functionalised cyclotriphosphazene dendrimers. Thermal and liquid crystalline properties were studied by using optical microscopy, differential scanning calorimetry and X-ray diffraction. The dendrimer with 12 4-pentylbiphenyl mesogenic units gives rise to columnar rectangular organisation, whereas the one with 24 pentylbiphenyl units does not exhibit mesomorphic behaviour. In the case of materials that contain polycatenar pro-mesogenic units with two aromatic rings ( A4 vs. A5), the incorporation of a short flexible spacer connected to the periphery of the dendron (acid A5) was needed to achieve mesomorphic organisation. In this case, both dendrimer generations G1 A5 and G2 A5 exhibit a hexagonal columnar mesophase. [ABSTRACT FROM AUTHOR]

The impreciseness of numeric input data can be expressed by intervals. On the other hand, the normalization of numeric data is a usual process in many applications. How do we match the normalization with impreciseness on numeric data? A straightforward answer is that it is enough to apply a correct interval arithmetic, since the normalized exact value will be enclosed in the resulting "normalized" interval. This paper shows that this approach is not enough since the resulting "normalized" interval can be even wider than the input intervals. So, we propose a pair of axioms that must be satisfied by an interval arithmetic in order to be applied in the normalization of intervals. We show how some known interval arithmetics behave with respect to these axioms. The paper ends with a discussion about the current paradigm of interval computations. [ABSTRACT FROM AUTHOR]