Pattern classification with missing values using multitask learning

In many real-life applications it is important to know how to deal with missing data (incomplete feature vectors). The ability of handling missing data has become a fundamental requirement for pattern classification because inappropriate treatment of missing data may cause large errors or false results on classification. A novel effective neural network is proposed to handle missing values in incomplete patterns with Multitask Learning (MTL). In our approach, a MTL neural network learns in parallel the classification task and the different tasks associated to incomplete features. During the MTL process, missing values are estimated or imputed. Missing data imputation is guided and oriented by the classification task, i.e., imputed values are those that contribute to improve the learning. We prove the robustness of this MTL neural network for handling missing values in classification problems from UCI database.This work will stimulate future works in many directions. Some of them are using different error functions (crossentropy error in discrete tasks, and sum-of-squares error in continuous tasks), adding an EM-model to probability density estimation into the proposed MTL scheme, setting the number of neurons in each subnetwork dynamically using constructive learning, an extensive comparison with other imputation methods, to use this procedure in regression problems, and extending the proposed method to different machines, e.g., Support Vector Machines (SVM)

Plant identification via adaptive combination of transversal filters

For least mean-square (LMS) algorithm applications, it is important to improve the speed of convergence vs the residual error trade-off imposed by the selection of a certain value for the step size. In this paper, we propose to use a mixture approach, adaptively combining two independent LMS filters with large and small step sizes to obtain fast convergence with low misadjustment during stationary periods. Some plant identification simulation examples show the effectiveness of our method when compared to previous variable step size approaches. This combination approach can be straightforwardly extended to other kinds of filters, as it is illustrated with a convex combination of recursive least-squares (RLS) filters.Publicad

¿Son los alumnos capaces de atribuir a los microorganismos algunas transformaciones de los alimentos?

In this paper we investigate if primary school students are able to relate microorganisms with food transformations. The subjects of this study were 343 4th. and 7th. grade children from Lugo (Spain) and the instrument used consisted of four multiple choice questions. The results shed light on the difficulties students have at these levels when they try to apply their ideas to interpret biological phenomena. Finally, we discuss some implications for Science teaching and learning

A robust support vector algorithm for nonparametric spectral analysis

A new approach to the nonparametric spectral estimation on the basis of the support vector method (SVM) framework is presented. A reweighted least squared error formulation avoids the computational limitations of quadratic programming. The application to a synthetic example and to a digital communication problem shows the robustness of the SVM spectral analysis algorithm.Publicad

Impact of atmospheric deposition on the metabolism of coastal microbial communities

11 páginas, 3 tablas, 5 figurasThe impact of rain water collected at marine, urban and rural sites on coastal phytoplankton biomass, primary production and community composition as well as the effect on microbial plankton metabolism was studied in 3 microcosm experiments conducted under contrasting spring, autumn and winter conditions. The measured responses were highly variable. Rainwater additions increased chlorophyll a (Chl a) concentration (5–68% difference between rainwater treatments relative to the control) in all experiments and reduced or stimulated primary production (PP) depending on the treatment and the experiment (from −10 to +169% relative to the control). Autotrophic stimulation was highest in spring, probably related to the low initial natural nutrient concentrations. Under winter nutrient replete conditions, rainwater inputs changed the phytoplankton community although this change did not promote increases in primary production. Enhancement of net autotrophy (increase of net oxygen production up to 227%) after rainwater inputs were only found during the period of low nutrient availability. Inputs of dissolved organic nitrogen (DON) explained a large fraction of the variability in the response of PP, Chl a, community respiration (CR) and net community production (NCP). Our results suggest that differences in the initial environmental conditions (i.e. nutrient availability), rainwater composition and the ability of the present autotrophic communities to utilize the new nutrients result in substantial changes in the microbial responses and associated biologically-mediated carbon fluxes. As atmospheric nutrient inputs into coastal oceans are increasing rapidly, our results help to understand the effects of different inputs on the metabolism of distinct microbial communitiesThis research was supported by the Galician Government (Xunta de Galicia) through the grants 07MMA002402PR (IMAN) and PGIDIT06PXIB312222PR (AddEx). S.M-G. and E.E.G-M. were funded by F.P.U. fellowships and E.T. by a Ramón y Cajal contract of the Spanish Ministry of Science and InnovationPeer reviewe

Understanding Primary Care Physician Vaccination Behaviour: A Systematic Review.

Background: Vaccine hesitancy decreases adult vaccination coverage and has been recognized by WHO as a major health threat. Primary care physicians (PCP) play a key role in vaccination by giving vaccine counselling to their patients. The aim of this systematic review is to identify the knowledge, beliefs, attitudes and barriers (KBAB) associated with own vaccination and patient recommendation in primary care physicians. Methods: MEDLINE/PubMed, EMBASE and Cochrane Library databases were used to search and identify relevant studies based on their title and abstract. In the next step, the full text of each previously selected article was read for eligibility. Articles were selected by two independent reviewers and data extraction was performed using tables. The following information was extracted: methodological characteristics, demographic factors, professional characteristics, and intrinsic or extrinsic factors influencing vaccination or recommendation. Results: Our search yielded 41 eligible papers, data-sources, previous practices, belief in the effectiveness or safety of the vaccine, perceived risk, and trust in health authorities were all shown to be related to own vaccination and patient recommendation. Conclusion: Internet is the main source of information for PCP related to vaccine hesitancy. It is therefore essential to increase the presence and access to pro-vaccination content in this area. In addition, involving PCP in the establishment of vaccination recommendations could improve their credibility in the institutions. On the other hand, training in communication skills and establishing reminder systems could reflect higher vaccination coverage among their patients

Some new results in sampling deterministic signals

Whittaker's (or Shannon 's) Sampling Theorem is a well-known interpolation formula that has been extended in many directions. In this paper, we introduce two new formulations: -The first follows Papoulis' Generalized Sampling Expansion for reconstructing a signal from regular samples of N(linear, time-invariant) functionals of it, taking the samples at 1/N the Nyquist rate; but generalizing it for including linear T- periodically time-varying systems. This way is in close relation with works that extend sampling in other directions. -The second generalizes Linden's proof of Kohlenberg's sampling for a bandpass signal, in order to maintain the minimum sampling rate (in the average) and to obtain a separate interpolation of the in-phase and quadrature components of the signal. This follows Grace- Pitt-Brown's theory of bandpass sampling.Peer ReviewedPostprint (published version

Understanding primary care physician vaccination behaviour: a systematic review

Background: Vaccine hesitancy decreases adult vaccination coverage and has been recognized by WHO as a major health threat. Primary care physicians (PCP) play a key role in vaccination by giving vaccine counselling to their patients. The aim of this systematic review is to identify the knowledge, beliefs, attitudes and barriers (KBAB) associated with own vaccination and patient recommendation in primary care physicians. Methods: MEDLINE/PubMed, EMBASE and Cochrane Library databases were used to search and identify relevant studies based on their title and abstract. In the next step, the full text of each previously selected article was read for eligibility. Articles were selected by two independent reviewers and data extraction was performed using tables. The following information was extracted: methodological characteristics, demographic factors, professional characteristics, and intrinsic or extrinsic factors influencing vaccination or recommendation. Results: Our search yielded 41 eligible papers, data-sources, previous practices, belief in the effectiveness or safety of the vaccine, perceived risk, and trust in health authorities were all shown to be related to own vaccination and patient recommendation. Conclusion: Internet is the main source of information for PCP related to vaccine hesitancy. It is therefore essential to increase the presence and access to pro-vaccination content in this area. In addition, involving PCP in the establishment of vaccination recommendations could improve their credibility in the institutions. On the other hand, training in communication skills and establishing reminder systems could reflect higher vaccination coverage among their patientsS

Factors associated with underreporting of adverse drug reactions by health care professionals: a systematic review update

Introduction Underreporting is a major limitation of the voluntary reporting system of adverse drug reactions (ADRs). A 2009 systematic review showed the knowledge and attitudes of health professionals were strongly related with underreporting of ADRs. Objective Our aim was to update our previous systematic review to determine factors (sociodemographic, knowledge and attitudes) associated with the underreporting of ADRs by healthcare professionals. Methods We searched the MEDLINE and EMBASE databases for studies published between 2007 and 2021 that met the following inclusion criteria: (1) published in English, French, Portuguese or Spanish; (2) involving health professionals; and (3) the goal was to evaluate factors associated with underreporting of ADRs through spontaneous reporting. Results Overall, 65 papers were included. While health professional sociodemographic characteristics did not influence underreporting, knowledge and attitudes continue to show a significant effect: (1) ignorance (only serious ADRs need to be reported) in 86.2%; (2) lethargy (procrastination, lack of interest, and other excuses) in 84.6%; (3) complacency (the belief that only well tolerated drugs are allowed on the market) in 46.2%; (4) diffidence (fear of appearing ridiculous for reporting merely suspected ADRs) in 44.6%; and (5) insecurity (it is nearly impossible to determine whether or not a drug is responsible for a specific adverse reaction) in 33.8%, and the absence of feedback in 9.2%. In this review, the non-obligation to reporting and confidentiality emerge as new reasons for underreporting. Conclusions Attitudes regarding the reporting of adverse reactions continue to be the main determinants of underreporting. Even though these are potentially modifiable factors through educational interventions, minimal changes have been observed since 2009Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This study has been funded in part by the Instituto de Salud Carlos III (ISCIII) through the project PI19/01006, cofinanced by FEDER, European UnionS

Management de recursos humanos y sistemas de información

Ponencia premiada en el Seminario que sobre el tema "Management de Recursos Humanos y Sistemas de Información" se ha organizado por el Instituto de Dirección y Organización de Empresas de la Universidad de Alcalá de Henares y de la empresa SAP, el día 2 de octubre de 1990