Ranking and selection of unsupervised learning marketing segmentation

This research paper has been partially conducted during a three-months visiting period by German Sanchez-Hernandez to the Centre for Computational Intelligence (CCI).NOTICE: this is the author’s version of a work that was accepted for publication in . Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Knowledge-Based Systems, 44, pp. 20–33 http://dx.doi.org/10.1016/j.knosys.2013.01.012This paper addresses the problem of choosing the most appropriate classification from a given set of classifications of a set of patterns. This is a relevant topic on unsupervised systems and clustering analysis because different classifications can in general be obtained from the same data set. The provided methodology is based on five fuzzy criteria which are aggregated using an Ordered Weighted Averaging (OWA) operator. To this end, a novel multi-criteria decision making (MCDM) system is defined, which assesses the degree up to which each criterion is met by all classifications. The corresponding single evaluations are then proposed to be aggregated into a collective one by means of an OWA operator guided by a fuzzy linguistic quantifier, which is used to implement the concept of fuzzy majority in the selection process. This new methodology is applied to a real marketing case based on a business to business (B2B) environment to help marketing experts during the segmentation process. As a result, a segmentation containing three segments consisting of 35, 98 and 127 points of sale respectively is selected to be the most suitable to endorse marketing strategies of the firm. Finally, an analysis of the managerial implications of the proposed methodology solution is provided.This work is supported by the SENSORIAL Research Project (TIN2010-20966- C02-01, 02), funded by the Spanish Ministry of Science and Information Technology

Ultrafast photochemistry produces superbright short-wave infrared dots for low-dose in vivo imaging

12 p.-5 fig.Optical probes operating in the second near-infrared window (NIR-II, 1,000-1,700 nm), where tissues are highly transparent, have expanded the applicability of fluorescence in the biomedical field. NIR-II fluorescence enables deep-tissue imaging with micrometric resolution in animal models, but is limited by the low brightness of NIR-II probes, which prevents imaging at low excitation intensities and fluorophore concentrations. Here, we present a new generation of probes (Ag2S superdots) derived from chemically synthesized Ag2S dots, on which a protective shell is grown by femtosecond laser irradiation. This shell reduces the structural defects, causing an 80-fold enhancement of the quantum yield. PEGylated Ag2S superdots enable deep-tissue in vivo imaging at low excitation intensities (<10 mW cm-2) and doses (<0.5 mg kg-1), emerging as unrivaled contrast agents for NIR-II preclinical bioimaging. These results establish an approach for developing superbright NIR-II contrast agents based on the synergy between chemical synthesis and ultrafast laser processing.Authors thank Dr A. Benayas (CICECO, U. Aveiro, Portugal), Prof G. Lifante and Prof J. García Sole (UAM) for helpful discussions. This work has been founded by Ministerio de Economı́a y Competitividad-MINECO (MAT2017-83111R and MAT2016-75362-C3-1-R) and the Comunidad de Madrid (B2017/BMD-3867 RENIM-CM) co-financed by European Structural and Investment Fund. D.M.-G. thanks UCM-Santander for a predoctoral contract (CT17/17-CT18/17). We thank the staff at the ICTS-National Centre for Electron Microscopy at the UCM for the help in the electron microscopy studies and C.M. at the beamline BL22-CLAESS of the Spanish synchrotron ALBA for his help in the XANES experiments. We also thank J.G.I at the Ultrafast Laser Laboratory at UCM for his help and fruitful discussion. Y.S. acknowledges the support from the China Scholarship Council (CSC File No. 201806870023). Additional funding was provided by the European Commission Horizon 2020 project NanoTBTech, the Fundación para la Investigación Biomédica del Hospital Universitario Ramón y Cajal project IMP18_38 (2018/0265). Ajoy K. Kar and Mark D. Mackenzie acknowledge support from the UK Engineering and Physical Sciences Research Council (Project CHAMP, EP/M015130/1). C. Jacinto thanks the financial support of the Brazilian agencies: CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) through the grants: Projeto Universal Nr. 431736/2018-9 and Scholarship in Research Productivity 1C under the Nr. 304967/20181; FINEP (Financiadora de Estudos e Projetos) through the grants INFRAPESQ-11 and INFRAPESQ-12; FAPEAL (Fundação de Amparo à Pesquisa do Estado de Alagoas) grant Nr. 1209/2016. H. D. A. Santos was supported by a graduate studentship from CNPq and by a sandwich doctoral program (PDSE-CAPES) developed at Universidad Autonoma de Madrid, Spain, Project Nr. 88881/2016-01.Peer reviewe

A clathrin-dependent pathway leads to KRas signaling on late endosomes en route to lysosomes

Ras proteins are small guanosine triphosphatases involved in the regulation of important cellular functions such as proliferation, differentiation, and apoptosis. Understanding the intracellular trafficking of Ras proteins is crucial to identify novel Ras signaling platforms. In this study, we report that epidermal growth factor triggers Kirsten Ras (KRas) translocation onto endosomal membranes (independently of calmodulin and protein kinase C phosphorylation) through a clathrin-dependent pathway. From early endosomes, KRas but not Harvey Ras or neuroblastoma Ras is sorted and transported to late endosomes (LEs) and lysosomes. Using yellow fluorescent protein–Raf1 and the Raichu-KRas probe, we identified for the first time in vivo–active KRas on Rab7 LEs, eliciting a signal output through Raf1. On these LEs, we also identified the p14–MP1 scaffolding complex and activated extracellular signal-regulated kinase 1/2. Abrogation of lysosomal function leads to a sustained late endosomal mitogen-activated protein kinase signal output. Altogether, this study reveals novel aspects about KRas intracellular trafficking and signaling, shedding new light on the mechanisms controlling Ras regulation in the cell

Crystal structures of taxane-tubulin complexes: Implications for the mechanism of microtubule stabilization by Taxol

30 p.-9 fig.-1 tab.Paclitaxel (Taxol®) is a first-line chemotherapeutic drug that promotes the curved-to-straight conformational transition of tubulin, an activation step that is necessary for microtubule formation. Crystallization of Taxol bound to tubulin has been long elusive. We found that baccatin III, the core structure of paclitaxel which lacks the C13 side chain, readily co-crystallizes with curved tubulin. Tailor-made taxanes with alternative side chains also co-crystallized, allowing us to investigate their binding modes. Interestingly, these Taxol derived compounds lost their microtubule stabilizing activity and cytotoxicity but kept their full microtubule binding affinity, and all induced lattice expansion upon binding. Additional nuclear magnetic resonance studies propose that Taxol binds to a small fraction of straight tubulin present in solution. Our results suggest a mode of action of Taxol, where the core structure is responsible for the interacting energy while the bulky hydrophobic C13 side chain enables binding selectively to straight tubulin and promotes stabilization.N

Convenio Marco con la Consejería de Enseñanza del Gobierno de la Generalitat de Catalunya, España.

El presente acuerdo tiene como objetivo desarrollar programas de estudios conjuntos, intercambio y cooperación en el campo de la docencia, formación de estudiantes e investigació

Multimodal Diaries

Time management is an important aspect of a successful professional life. In order to have a better understanding of where our time goes, we propose a system that summarizes the user’s daily activity (e.g. sleeping, walking, working on the computer, talking, ...) using all-day multimodal data recordings. Two main novelties are proposed: • A system that combines both physical and contextual awareness hardware and software. It records synchronized audio, video, body sensors, GPS and computer monitoring data. • A semi-supervised temporal clustering (SSTC) algorithm that accurately and efficiently groups large amounts of multimodal data into different activities. The effectiveness and accuracy of our SSTC is demonstrated in synthetic and real examples of activity segmentation from multimodal data gathered over long periods of time

Platform for Analysis and Labeling of Medical Time Series

Reliable and diverse labeled reference data are essential for the development of high-quality processing algorithms for medical signals, such as electrocardiogram (ECG) and photoplethysmogram (PPG). Here, we present the Platform for Analysis and Labeling of Medical time Series (PALMS) designed in Python. Its graphical user interface (GUI) facilitates three main types of manual annotations&mdash;(1) fiducials, e.g., R-peaks of ECG; (2) events with an adjustable duration, e.g., arrhythmic episodes; and (3) signal quality, e.g., data parts corrupted by motion artifacts. All annotations can be attributed to the same signal simultaneously in an ergonomic and user-friendly manner. Configuration for different data and annotation types is straightforward and flexible in order to use a wide range of data sources and to address many different use cases. Above all, configuration of PALMS allows plugging-in existing algorithms to display outcomes of automated processing, such as automatic R-peak detection, and to manually correct them where needed. This enables fast annotation and can be used to further improve algorithms. The GUI is currently complemented by ECG and PPG algorithms that detect characteristic points with high accuracy. The ECG algorithm reached 99% on the MIT/BIH arrhythmia database. The PPG algorithm was validated on two public databases with an F1-score above 98%. The GUI and optional algorithms result in an advanced software tool that allows the creation of diverse reference sets for existing datasets