A Novel Grouping Harmony Search Algorithm for Clustering Problems

The problem of partitioning a data set into disjoint groups or clusters of related items plays a key role in data analytics, in particular when the information retrieval becomes crucial for further data analysis. In this context, clustering approaches aim at obtaining a good parti- tion of the data based on multiple criteria. One of the most challenging aspects of clustering techniques is the inference of the optimal number of clusters. In this regard, a number of clustering methods from the literature assume that the number of clusters is known a priori and sub- sequently assign instances to clusters based on distance, density or any other criterion. This paper proposes to override any prior assumption on the number of clusters or groups in the data at hand by hybridizing the grouping encoding strategy and the Harmony Search (HS) algorithm. The resulting hybrid approach optimally infers the number of clusters by means of the tailored design of the HS operators, which estimates this important structural clustering parameter as an implicit byproduct of the instance-to-cluster mapping performed by the algorithm. Apart from inferring the optimal number of clusters, simulation results ver- ify that the proposed scheme achieves a better performance than other na ̈ıve clustering techniques in synthetic scenarios and widely known data repositories

Detection of non-technical losses in smart meter data based on load curve profiling and time series analysis

The advent and progressive deployment of the so-called Smart Grid has unleashed a profitable portfolio of new possibilities for an efficient management of the low-voltage distribution network supported by the introduction of information and communication technologies to exploit its digitalization. Among all such possibilities this work focuses on the detection of anomalous energy consumption traces: disregarding whether they are due to malfunctioning metering equipment or fraudulent purposes, strong efforts are invested by utilities to detect such outlying events and address them to optimize the power distribution and avoid significant income costs. In this context this manuscript introduce a novel algorithmic approach for the identification of consumption outliers in Smart Grids that relies on concepts from probabilistic data mining and time series analysis. A key ingredient of the proposed technique is its ability to accommodate time irregularities – shifts and warps – in the consumption habits of the user by concentrating on the shape of the consumption rather than on its temporal properties. Simulation results over real data from a Spanish utility are presented and discussed, from where it is concluded that the proposed approach excels at detecting different outlier cases emulated on the aforementioned consumption traces.Ministerio de Energía y Competitividad under the RETOS program (OSIRIS project, grant ref. RTC-2014-1556-3)

Observation of NO(x) Enhancement and Ozone Depletion in the Northern and Southern hemispheres after the October-November 2003 Solar Proton Events

The large solar storms in October-November 2003 produced enormous solar proton events (SPEs) where high energetic particles reached the Earth and penetrated into the middle atmosphere in the polar regions. At this time, the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) was observing the atmosphere in the 6-68 km altitude range. MIPAS observations of NO(x) (NO+NO2) and O3 of the period from 25 October to 14 November 2003 are the first global measurements of NO(x) species, covering both the summer (daylight) and winter (dark) polar regions during an SPE. Very large values of NO(x) in the upper stratosphere of 180 ppbv (parts per billion by volume) have been measured, and a large asymmetry in Northern and Southern polar cap NO(x) enhancements was found. Arctic mean polar cap (>60 deg) NO(x) enhancements of 20 to 70 ppbv between 40 to 60 km lasted for at least two weeks, while the Antarctic mean NO(x) enhancement was between 10 and 35 ppbv and was halved after two weeks. Ozone shows depletion signatures associated with both HO(x) (H+OH+HO2) and NO(x) enhancements but at different time scales. Arctic lower mesospheric (upper stratospheric) ozone is reduced by 50-70% (30-40%) for about two weeks The large solar storms in October-November 2003 produced after the SPEs. A smaller ozone depletion signal was observed in the Antarctic atmosphere. After the locally produced Arctic middle and upper stratospheric as well as mesospheric NO(x) enhancement, large amounts of NO(x) were observed until the end of December. These are explained by downward transport processes

Fiber Optic Sensing System for Temperature and Gas Monitoring in Coal Waste Pile Combustion Environments

International audienceIt is presented an optical fiber sensing system projected to operate in the demanding conditions associated with coal waste piles in combustion. Distributed temperature measurement and spot gas sensing are requirements for such a system. A field prototype has been installed and is continuously gathering data, which will input a geological model of the coal waste piles in combustion aiming to understand their dynamics and evolution. Results are presented on distributed temperature and ammonia measurement, being noticed any significant methane emission in the short time period considered. Carbon dioxide is also a targeted gas for measurement, with validated results available soon. The assessment of this technology as an effective and reliable tool to address the problem of monitoring coal waste piles in combustion opens the possibility of its widespread application in view of the worldwide presence of coal related fires

Intratumor genetic heterogeneity and clonal evolution to decode endometrial cancer progression

Endometrial cancer; Clonal evolution; MutationCáncer endometrial; Evolución clonal; MutaciónCàncer d'endometri; Evolució clonal; MutacióAnalyzing different tumor regions by next generation sequencing allows the assessment of intratumor genetic heterogeneity (ITGH), a phenomenon that has been studied widely in some tumor types but has been less well explored in endometrial carcinoma (EC). In this study, we sought to characterize the spatial and temporal heterogeneity of 9 different ECs using whole-exome sequencing, and by performing targeted sequencing validation of the 42 primary tumor regions and 30 metastatic samples analyzed. In addition, copy number alterations of serous carcinomas were assessed by comparative genomic hybridization arrays. From the somatic mutations, identified by whole-exome sequencing, 532 were validated by targeted sequencing. Based on these data, the phylogenetic tree reconstructed for each case allowed us to establish the tumors’ evolution and correlate this to tumor progression, prognosis, and the presence of recurrent disease. Moreover, we studied the genetic landscape of an ambiguous EC and the molecular profile obtained was used to guide the selection of a potential personalized therapy for this patient, which was subsequently validated by preclinical testing in patient-derived xenograft models. Overall, our study reveals the impact of analyzing different tumor regions to decipher the ITGH in ECs, which could help make the best treatment decision.We thank all those at the Translational Research Laboratory of the MD Anderson Cancer Center Madrid for their invaluable help with this study. Tissue samples were obtained with the support of the MD Anderson Foundation Biobank (record number B.0000745, ISCIII National Biobank Record), the “Xarxa Catalana de Bancs de Tumors” and “Plataforma de Biobancos” ISCIII (PT13/0010/0014, B.000609). This study has been supported by the Spanish Ministry of Economy and Innovation (PID2019-104644RB-I00 (GMB), the Instituto de Salud Carlos III (ISCIII, CIBERONC, CB16/12/00295 - GMB-, CB16/12/00328 -EC, AGM- and CB16/12/00231 -XMG- [all partly supported by FEDER funds]) and by the AECC Scientific Foundation (FC_AECC PROYE19036MOR -GMB- and Coordinated groups 2018 -XMG, AGM, GMB-). SO is funded by an AECC-postdoctoral grant (2020). JSR-F and BW are funded in part by the Breast Cancer Research Foundation and in part by the NIH/NCI P50 CA247749 01 grant. Research reported in this publication was supported in part by a Cancer Center Support Grant of the NIH/NCI (Grant No. P30CA008748; MSK). We thank the Eurofins Megalab laboratory for helping us to perform the analysis of DNA HPV detection

Effects of coherence on temporal resolution

Measuring small separations between two optical sources, either in space or in time, constitute an important metrological challenge as standard intensity-only measurements fail for vanishing separations. Contrarily, it has been established that appropriate coherent mode projections can appraise arbitrarily small separations with quantum-limited precision. However, the question of whether the optical coherence brings any metrological advantage to mode projections is still a point of debate. Here, we elucidate this problem by experimentally investigating the effect of varying coherence on estimating the temporal separation between two single-photon pulses. We show that, for an accurate interpretation, special attention must be paid to properly normalize the quantum Fisher information to account for the strength of the signal. Our experiment demonstrates that coherent mode projections are optimal for any degree of coherence

HNO3, N2O5 and CIONO2 Enhancements after the October-November 2003 Solar Proton Events

The large solar storm in October-November 2003 produced enormous amounts of high-energy protons which reached the Earth and penetrated into the middle atmosphere in the polar regions. At this time, the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on board the Environmental Satellite (ENVISAT) was observing the atmosphere in the 6-68 km altitude range. MIPAS observed significant enhancements of the NO(y) components HNO3, N2O5 and CIONO2 in the Northern polar stratosphere after the intense solar proton events. Two distinct HNO3 enhancements were observed. An instantaneous increase of 1-2 ppbv was observed immediately after the SPEs and is attributed to gas-phase chemistry: NO2 + OH + M yields HNO3 + M, accelerated by SPE-produced excess OH. A very large second increase of 1- 5 ppbv started around 10 November and lasted until the end of December. It is attributed to NO(x) (NO+NO2) produced in the mesosphere during the major SPEs in late October/early November and then transported downwards during November and December, partially converted to N2O5 in the upper stratosphere, which finally formed HNO3 via ion cluster reactions. N2O5 was observed to increase by 0.1-0.4 ppbv 1-3 days after the major SPEs and reached down to 30 km altitude. A second, more pronounced N2O5 enhancement of up to 1.2 ppbv at 40 km appeared about 12-13 days after the major SPEs. With a delay of 1-2 days after the major SPEs CIONO2 increased by up to 0.4 ppbv (40%) at 32 km altitude. NO(y) enhancements in the Southern hemisphere were generally less pronounced

Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI

In the last few years, Artificial Intelligence (AI) has achieved a notable momentum that, if harnessed appropriately, may deliver the best of expectations over many application sectors across the field. For this to occur shortly in Machine Learning, the entire community stands in front of the barrier of explainability, an inherent problem of the latest techniques brought by sub-symbolism (e.g. ensembles or Deep Neural Networks) that were not present in the last hype of AI (namely, expert systems and rule based models). Paradigms underlying this problem fall within the so-called eXplainable AI (XAI) field, which is widely acknowledged as a crucial feature for the practical deployment of AI models. The overview presented in this article examines the existing literature and contributions already done in the field of XAI, including a prospect toward what is yet to be reached. For this purpose we summarize previous efforts made to define explainability in Machine Learning, establishing a novel definition of explainable Machine Learning that covers such prior conceptual propositions with a major focus on the audience for which the explainability is sought. Departing from this definition, we propose and discuss about a taxonomy of recent contributions related to the explainability of different Machine Learning models, including those aimed at explaining Deep Learning methods for which a second dedicated taxonomy is built and examined in detail. This critical literature analysis serves as the motivating background for a series of challenges faced by XAI, such as the interesting crossroads of data fusion and explainability. Our prospects lead toward the concept of Responsible Artificial Intelligence, namely, a methodology for the large-scale implementation of AI methods in real organizations with fairness, model explainability and accountability at its core. Our ultimate goal is to provide newcomers to the field of XAI with a thorough taxonomy that can serve as reference material in order to stimulate future research advances, but also to encourage experts and professionals from other disciplines to embrace the benefits of AI in their activity sectors, without any prior bias for its lack of interpretability

A Study of the Near-Ultraviolet Spectrum of Vega

UV, optical, and near-IR spectra of Vega have been combined to test our understanding of stellar atmospheric opacities, and to examine the possibility of constraining chemical abundances from low-resolution UV fluxes. We have carried out a detailed analysis assuming Local Thermodynamic Equilibrium (LTE) to identify the most important contributors to the UV continuous opacity: H, H$^{-}$, C I, and Si II. Our analysis also assumes that Vega is spherically symmetric and its atmosphere is well described with the plane parallel approximation. Comparing observations and computed fluxes we have been able to discriminate between two different flux scales that have been proposed, the IUE-INES and the HST scales, favoring the latter. The effective temperature and angular diameter derived from the analysis of observed optical and near-UV spectra are in very good agreement with previous determinations based on different techniques. The silicon abundance is poorly constrained by the UV observations of the continuum and strong lines, but the situation is more favorable for carbon and the abundances inferred from the UV continuum and optical absorption lines are in good agreement. Some spectral intervals in the UV spectrum of Vega that the calculations do not reproduce well are likely affected by deviations from LTE, but we conclude that our understanding of UV atmospheric opacities is fairly complete for early A-type stars.Comment: 13 pages, 9 figures, to be published in Ap