Fundamentos de la biopsia del ganglio centinela en el cáncer de mama

La linfadenectomía axilar es el método clásico para informarnos del estado de los ganglios axilares en el cáncer de mama. Sin embargo, al incorporarse el screenning mamográfico, los tumores diagnosticados en la actualidad son de tamaño reducido. Por lo tanto, el porcentaje de pacientes en las cuales esperamos que exista afectación axilar es muy bajo en la actualidad. La linfadenectomía axilar no está exenta de morbilidad; afecta al 80% de las pacientes sometidas a resección axilar niveles I y II. En el caso de que exista enfermedad a nivel axilar, esta morbilidad es aceptable y se compensa por el beneficio que la paciente obtiene al reducirse la masa tumoral; no obstante, en los casos en los que no existe afectación de los ganglios axilares esta morbilidad es inaceptable. La biopsia del ganglio centinela permite la resección y estudio de un único ganglio axilar con un mínimo porcentaje de falsos negativos, y una morbilidad prácticamente inexistente. El estudio sobre el ganglio centinela es más exacto y meticuloso, constituyendo en la actualidad la técnica quirúrgica de elección en pacientes con tumores menores de 3 cm y sin afectación axilar clínica.Axillary lymph node dissection is the gold standard for detecting axillary disease in breast cancer. Node status remains the most important prognostic factor, and is an important information to make decisions over further treatment. However, both the morbidity associated to this technique, and the fact that, due to mammografic screening, most of the cancer cases nowadays are early cancers that have no axillary metastases, have encouraged investigations towards new surgical approaches. Sentinel node biopsy has been recognized to detect any axillary disease with minimal morbidity and false-negative rates. This technique is routinely indicated for tumors below 3 cm in size, without clinical axillary disease

Normal subgroups and class sizes of elements of prime power order

[EN] If G is a finite group and N is a normal subgroup of G with two C-conjugacy class sizes of elements of prime power order, then we show that N is nilpotent.We would like to thank the referee for some simplifications in the original proofs. This research was supported by the Spanish Government, Proyecto MTM2010-19938-C03-02, and by the Valencian Government, Proyecto PROMETEO/2011/30. The first author was also supported by grant Fundacio Caixa-Castello P11B2010-47.Beltrán, A.; Felipe Román, MJ. (2012). Normal subgroups and class sizes of elements of prime power order. Proceedings of the American Mathematical Society. 140(12):4105-4109. https://doi.org/10.1090/S0002-9939-2012-11276-6S410541091401

LMDI decomposition analysis of energy efficiency in Andalusia (Spain) during 2003-2011

The aim of this paper is to analyse the changes in final energy consumption in Andalusia through logarithmic mean Divisia index (LMDI) decomposition analysis during the period 2003–2012. The results lead us to conclude that a reduction of final energy (FE) consumption of 1 % took place as a result of a diminishing in structural effect by 11 % and an increase in the activity effect and intensity effect by 7.4 and 3.5 %, respectively. Chain-linked LMDI decomposition shows the existence of two sub-periods, with a turning point in 2008. The first period, coinciding to a great extent with the Andalusian Energy Plan 2003–2006 (PLEAN), showed an increase in final energy consumption, mostly due to the activity effect but also to the intensity effect. The second period, coinciding with the implementation of the Andalusian Sustainable Energy Plan 2007–2013 (PASENER), shows a reduction in the activity, structure and intensity effects. The results allow us to conclude that many of the energy efficiency measures, implemented through the PASENER, are related to sectors that experienced a decline in energy consumption due to the intensity effect, such as transport, primary and service sectors. Additionally, although they were included in PASENER, more policy attention should be given to the energy transformation, residential and industrial sectors which increased the demand for energy due to the intensity effect during this period. Finally, the energy-saving behaviour of economic agents due to the economic downturn should also be considered as an explanation for the diminishing in energy consumption during this sub-period.Junta de Andalucía SEJ 132Ministerio de Economía y Competitividad ECO2014-56399-RMinisterio de Educación (Chile) 115002

Is residential energy consumption a key driver of final energy consumption changes in Andalucia?

The economic expansion period during 2000-2008 was accompanied by an important increase of energy consumption in Andalusia. The desire of decoupling between both of them, has led us to carry out a structural decomposition analysis (SDA) based on the Andalusia input-output tables. Additionally, this decomposition has been supplemented by a Logarithmic Mean Divisia Index (LMDI) analysis of the energy consumption changes during a longer period 2000-2013. Therefore, the novelty of this paper is found in the following aspects: i) the structural decomposition of the final energy consumption changes is applied on the largest disaggregation of sectors made until now for the Andalusian economy (73 productive sectors) during the period 2000-2008; ii) the LMDI analysis provide results for a longer period (2000-2013) and allows us to compare the two decomposition approaches; iii) both decompositions analyse the residential and productive energy consumption changes, iv) the analysis provides a better understanding of the energy sources that are behind the driving forces; and v) based on the above results, some energy policy recommendations are provided

Measuring Software Process: A Systematic Mapping Study

Context: Measurement is essential to reach predictable performance and high capability processes. It provides support for better understanding, evaluation, management, and control of the development process and project, as well as the resulting product. It also enables organizations to improve and predict its process’s performance, which places organizations in better positions to make appropriate decisions. Objective: This study aims to understand the measurement of the software development process, to identify studies, create a classification scheme based on the identified studies, and then to map such studies into the scheme to answer the research questions. Method: Systematic mapping is the selected research methodology for this study. Results: A total of 462 studies are included and classified into four topics with respect to their focus and into three groups based on the publishing date. Five abstractions and 64 attributes were identified, 25 methods/models and 17 contexts were distinguished. Conclusion: capability and performance were the most measured process attributes, while effort and performance were the most measured project attributes. Goal Question Metric and Capability Maturity Model Integration were the main methods and models used in the studies, whereas agile/lean development and small/medium-size enterprise were the most frequently identified research contexts.Ministerio de Economía y Competitividad TIN2013-46928-C3-3-RMinisterio de Economía y Competitividad TIN2016-76956-C3-2- RMinisterio de Economía y Competitividad TIN2015-71938-RED

Modelling long term trend and local spatial correlation: a mixed penalized spline and spatial econometrics approach

In this work we propose the combination of P-splines with traditional spatial econometric models in such a way that it allows for their representation as a mixed model. The advantages of combining these models include: (i) dealing with complex non-linear and non-separable trends, (ii) estimating short-range spatial correlation together with the large-scale spatial trend, (iii) decomposing the systematic spatial variation into those two components and (iv) estimating the smoothing parameters included in the penalized splines together with the other parameters of the model. The performance of the proposed spatial non-parametric models is checked by both simulation and a empirical study. More specifically, we simulate 3,600 datasets generated by those models (with both linear and non-linear-non-separable global spatial trends). As for the empirical case, we use the well-known Lucas county data on housing prices. Our results indicate that the proposed models have a better performance than the traditional spatial strategies, specially in the presence of nonlinear tren