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Introducción: El género Salmonella se destaca por ser un patógeno alimentario causante de Salmonelosis, una enfermedad de distribución cosmopolita, que afecta a todos los grupos poblacionales, tanto en los países desarrollados como en los que están en vía de desarrollo, siendo un problema de salud pública, por tal razón, los biomarcadores moleculares se convierten en una herramienta para su diagnóstico y seguimiento. Objetivo: Describir los marcadores moleculares del género Salmonella y las diferentes técnicas moleculares utilizadas para su detección en la actualidad. Metodología: Se realizó una búsqueda bibliográfica en bases de datos tales como Science direct, PubMed, Proquest y Ovid, utilizando 5 palabras clave, las cuales se combinaron de diferentes maneras para finalmente obtener 50 referencias bibliográficas. Resultados: Se evidencia gran variedad de biomarcadores del género Salmonella, los cuales son detectados por pruebas moleculares, como la técnica de PCR, que permite la detección directa de genes que codifican para los antígenos somáticos O y flagelares H de Salmonella y la determinación de los posibles serovares implicados en las enfermedades transmitidas por alimentos, de una manera rápida y precisa. Cabe resaltar las ventajas de los métodos moleculares frente a la serotipificación en cuanto al costo-beneficio, estandarización óptima, alta sensibilidad, especificidad y rapidez en la obtención de los resultados. Conclusiones: Los biomarcadores moleculares se consideran una herramienta de referencia para la identificación de serovares de Salmonella y su serotipificación, a través de la PCR, con un alto nivel de especificidad y sensibilidad en los resultados, aportando información relevante a nivel epidemiológico

In this work, we present an approach to understand the computational methods and decision-making involved in the identification of emotions in spontaneous speech. The selected task consists of Spanish TV debates, which entail a high level of complexity as well as additional subjectivity in the human perception-based annotation procedure. A simple convolutional neural model is proposed, and its behaviour is analysed to explain its decision-making. The proposed model slightly outperforms commonly used CNN architectures such as VGG16, while being much lighter. Internal layer-by-layer transformations of the input spectrogram are visualised and analysed. Finally, a class model visualisation is proposed as a simple interpretation approach whose usefulness is assessed in the work. The research presented in this paper was conducted as part of the AMIC, AMIC-PdC, BEWORD and MENHIR projects, which received funding from the Spanish Minister of Science under grants TIN2017-85854-C4-3-R, PDC2021-120846-C43 and PID2021-126061OB-C42 and from the European Union’s H2020-MSCA-RISE-2018 Research and Innovation Staff Exchange, under Grant No. 823907. The first author also received a PhD scholarship from the University of the Basque Country UPV/EHU, PIF17/310.

Todos somos responsables de nuestra salud y de la salud de quienes están con nosotros, cuidarnos y cuidar de los demás es la misión, por ello es importante conocer las causas que originan los problemas y las situaciones de riesgo en salud. Actualmente el enfoque en salud es “Una Salud / One Health”, la resistencia a los antimicrobianos es un problema mundial, por ello es importante aprender el uso adecuado de los antimicrobianos en la salud humana, animal y ambiental.

This paper reports on experiments devoted to explore the role of specific attributes of humanoid virtual agents that may influence elderly users’ perception and attitude, determining their acceptance and adoption as assistive devices. In particular, it investigates elderly preference on agents’ gender and the role of the agents’ ability to use voice during the interaction. To this aim two different groups of seniors were involved in the experiments. The first group evaluated talking virtual agents, the second one the same virtual agents, but silenced. The data shows that elderly users, independently from their gender, prefer to interact with female agents, especially when they are able to talk to them, revealing the role played by the voice. Furthermore, it was found a significant effect of the elderly level of experience with technology: when interacting with agents with voice, elderly users with high technological experience were less interested and considered the proposed agents less attractive and appealing, while just the opposite occurred when interacting with silenced agents.

Introducción. Las bacterias son organismos que se encuentran en diferentes tipos de ambientes que actúan como reservorios, entre estos, los productos de consumo derivados de los animales. Algunas de estas bacterias son capaces de causar enfermedad a los humanos y, a su vez, han evolucionado generando resistencia a antibióticos, lo cual se ha convertido en un problema de salud pública a nivel mundial. Objetivo. Describir los perfiles de susceptibilidad de grupos bacterianos provenientes de productos cárnicos y derivados, de dos lugares de abasto de Tunja. Materiales y Métodos. Estudio descriptivo de corte transversal. Se realizó muestreo de productos cárnicos en los expendios de carne y derivados, en un periodo de tres meses, en dos lugares de abasto de la ciudad de Tunja, de los cuales se tomaron diferentes cortes de productos cárnicos para su posterior análisis. Resultados. A partir de 160 muestras cárnicas recolectadas de 32 puntos de venta, se aislaron 333 cepas bacterianas, encontrando presencia de bacterias Gram negativas y Gram positivas en un 83.2% y 16.8% respectivamente. Por otra parte, los perfiles de susceptibilidad antimicrobiano para estas bacterias mostraron sensibilidad del 19,2% y 0,9%, respectivamente, a los seis antibióticos utilizados para cada grupo en el estudio. Conclusiones. Se encontró una alta presencia de bacterias procedentes de los aislados de productos cárnicos, que obliga a la mejora de las condiciones de manipulación y expendio de estos productos, dado que, entre los principales riesgos se encuentra la adquisición de cepas resistentes mediante el consumo de alimentos contaminados.

The use of speech as an interaction modality has grown considerably through the integration of Intelligent Personal Assistants (IPAs- e.g. Siri, Google Assistant) into smartphones and voice based devices (e.g. Amazon Echo). Such engineering advances in speech processing present a unique opportunity for enabling users to interact with interface in a truly conversational way. However, we have yet to see current voice-enable interface fully becoming Conversational User Interfaces (CUIs) as afforded by the underlying speech and natural language capabilities. For example, from a conversational / dialogue perspective, there remain significant gaps in using theoretical frameworks to understand user behaviours and choices and how they may applied to specific speech interface interactions. On a design and Human-Computer Interaction level, we don't yet have the proper tools such as validated design guidelines to help us improve the usability of such interfaces. On the speech processing side, variability in speech, language, and conversation still pose problem, and error-recovery strategies often lead to degraded user experience. From a critical perspective, issues of ethics and privacy remain yet to be addressed.

The present investigation aims at assessing elders’ ability to decode facial emotional expressions conveyed by differently aged people in order to confirm (or disconfirm) the appropriateness of the “own age bias” theory, as well as investigate effects of different ages and different emotional categories. The study, involves 44 healthy elders (23 females), aged 65+ (mean age=75.09; SD=±7.9) which were requested to label 76 pictures depicting elders, middle-aged and young women and men displaying the six facial emotional expressions of disgust, anger, fear, sadness, happiness and neutrality. Results show a complex pattern of influences that calls for more deep investigations on the features to be accounted by providing socially and emotionally believable interfaces of effective and efficient algorithms to detect and decode their users’ emotional facial expressions.

The EMPATHIC project develops and validates new interaction paradigms for personalized virtual coaches (VC) to promote healthy and independent aging. To this end, the work presented in this paper is aimed to analyze the interaction between the EMPATHIC-VC and the users. One of the goals of the project is to ensure an end-user driven design, involving senior users from the beginning and during each phase of the project. Thus, the paper focuses on some sessions where the seniors carried out interactions with a Wizard of Oz driven, simulated system. A coaching strategy based on the GROW model was used throughout these sessions so as to guide interactions and engage the elderly with the goals of the project. In this interaction framework, both the human and the system behavior were analyzed. The way the wizard implements the GROW coaching strategy is a key aspect of the system behavior during the interaction. The language used by the virtual agent as well as his or her physical aspect are also important cues that were analyzed. Regarding the user behavior, the vocal communication provides information about the speaker's emotional status, that is closely related to human behavior and which can be extracted from the speech and language analysis. In the same way, the analysis of the facial expression, gazes and gestures can provide information on the non verbal human communication even when the user is not talking. In addition, in order to engage senior users, their preferences and likes had to be considered. To this end, the effect of the VC on the users was gathered by means of direct questionnaires. These analyses have shown a positive and calm behavior of users when interacting with the simulated virtual coach as well as some difficulties of the system to develop the proposed coaching strategy. The research presented in this paper is conducted as part of the project EMPATHIC that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no 769872.

ResumenIntroducción: La resistencia antimicrobiana es un grave problema de salud pública que se encuentra en aumento. Entre los factores más importantes relacionados con la diseminación de bacterias multirresistentes está el uso inapropiado de antibióticos y la aplicación insuficiente de las medidas de prevención y control. Adicionalmente, las bacterias tienen la capacidad de mutar o generar mecanismos de transferencia de genes de resistencia mediante plásmidos, transposones e integrones. Materiales y métodos: Se hizo una revisión crítica de la literatura sobre los principales genes de resistencia Gram negativos y su impacto en la salud pública. Fueron utilizadas las bases de datos de Medline, Embase, Lilacs, ScienceDirect, Scopus, SciELO, the Cochrane Library y Lilacs. Resultados: Se presenta una revisión de literatura que describe y analiza los principales genes de resistencia a antibióticos presentes en bacilos gram negativos, su origen, evolución y diseminación a microorganismos mediante la transferencia horizontal de genes; justificando la importancia de realizar una vigilancia epidemiológica del tránsito de clones con diferentes perfiles de resistencia y principales enzimas. Conclusiones: El seguimiento de la resistencia antimicrobiana desde el punto de vista de la epidemiología molecular forma parte transcendental de la vigilancia antibiótica como lo recomienda la Organización Mundial de la Salud; pues representa el futuro del monitoreo de la resistencia.AbstractIntroduction: Antimicrobial resistance is a serious public health problem that is increasing. Among the most important factors related to the spread of multi-resistant bacteria are the inappropriate use of antibiotics and the insufficient implementation of prevention and control measures. Additionally, bacteria have the ability to mutate or create mechanisms for transfer of resistance genes via plasmids, transposons and integrons. Materials and methods: A critical review of the literature on major resistance genes in Gram negative bacteria and its impact on public health was conducted. Data have been collected from Medline, Embase, Lilacs, ScienceDirect, Scopus, SciELO, the Cochrane Library and Lilacs. Results: A review of literature that describes and analyzes the main antibiotic resistance genes present in gram-negative bacilli is presented, as well as their origin, evolution, and subsequent spread to hundreds of species of microorganisms by Horizontal gene transfer which justifies the importance of conducting an epidemiological surveillance on transit of clones with different resistance profiles and major enzymes. Conclusions: The control of antimicrobial resistance from the point of view of molecular epidemiology is part of the antibiotic surveillance control as recommended by the World Health Organization; as it represents the future of the surveillance of resistance.

The research leading to the results in this paper has been conducted in the project EMPATHIC (Grant N: 769872) that received funding from the European Union’s Horizon2020 research and innovation programme.Additionally, this work has been partially funded by the Spanish Minister of Science under grants TIN2014-54288-C4-4-R and TIN2017-85854-C4-3-R, by the Basque Government under grant PRE_2017_1_0357,andby the University of the Basque Country UPV/EHU under grantPIF17/310.

The presented study investigated the preferences of seniors towards artificial avatars showing personality both from a pragmatic and a hedonic point of view. Also, preferences for technological devices were considered. The involved participants were 45 adults (20 female) aged 65+ years in good health. They were asked to watch video clips of 4 agents (two males and two females) showing different personality traits (i.e. angry, depressed, joyful, and practical), and subsequently had to complete a questionnaire. Subjects were not informed about an avatar’s personality and not openly interviewed regarding this subject. Rather, the administered questionnaire was devoted to test their perception of agents and whether such complies with the intended characteristics. Results show that subjects prefer female agents with a positive personality (joyful and practical) on both pragmatic and hedonic dimensions of the interactive system.

Home is associated with well-being especially during aging, reinforcing aspects such as control and security perception. In that sense more than 80% of the Spanish elderly population prefers to get support at home than outside. Moreover, home-based solutions preserve the dignity of and tend to be less costly. The goal of this workshop is, through a participative process, obtain a map of factors and opportunities for the absorption of ICT technology by remote care services. The specific goal is to evaluate how virtual agents and related tools can provide support and home-based solution for elderly people suffering cognitive impairment. We believe that such innovations can extend the autonomy of the patients and their life at home. This workshop is targeted at remote services providers or related agents such as social agents, formal or informal caregivers, patient associations etc. We aim to identify new opportunities for virtual agents, based on the technology developed within the Empathic EU project. Identification process will be achieved by confronting a PUSH approach, based on technology capabilities, against a PULL approach, based on market needs and end user’s real service acceptance. The workshop will have 2 separated parts. The first part (30 min), is designed to create meaningful stimulus for the attendees through two invited experts. The considered experts are coming from “Centro de Referencia Estatal de atencion a personas con enfermedad de Azheimer y otras demencias de Salamanca (IMSERSO)” and “Fundacion mas que ideas”. Both experts will provide real examples of ICT solutions for people suffering different types of cognitive impairment and dementia. After the expert’s intervention, we will split the participants in different groups. Each group will have a set of so called “modules capacities”. Each module capacity is a minimal integrated technological solution that can provide added-value. The focus of this second phase is to respond to the question: “Could any of those capacity provide benefit in the daily life of a patient or caregiver?”. The living lab H-ENEA will provide support on the design and the implementation of the workshop in order to ensure the proper interaction and dynamics among participants. Basically, the working groups from the experts’ interventions, the list of “module capacities” and the scenarios provided (showing different value chain of services) will identify from its own perspective: - Factors that have allowed to integrate technology (20 min) - Potential use of the “module capacities” (20 min) Finally, through the group coordinators, the main conclusions will be presented and shared among all the participants (20 min).

Online learning of dialogue managers is a desirable but often costly property to obtain. Probabilistic Finite State Bi-Automata (PFSBA) have shown to provide a flexible and adaptive framework to achieve this goal. In this paper, an Attributed PFSBA (A-PSFBA) is implemented and experimentally compared with previous non-attributed PFSBA proposals. Then, a simple yet effective online learning algorithm that adapts the probabilistic structure of the Bi-Automata on the run is presented and evaluated. To this end, the User Model is also represented by an A-PFSBA and the impact of different user behaviors is tested. The proposed approaches are evaluated on the Let’s Go corpus, showing significant improvements on the dialogue success rates reported in previous works.

A frequent difficulty faced by developers of Dialog Systems is the absence of a corpus of conversations to model the dialog statistically. Even when such a corpus is available, neither an agenda nor a statistically-based dialog control logic are options if the domain knowledge is broad. This article presents a module that automatically generates system-turn utterances to guide the user through the dialog. These system-turns are not established beforehand, and vary with each dialog. In particular, the task defined in this paper is the automation of a call-routing service. The proposed module is used when the user has not given enough information to route the call with high confidence. Doing so, and using the generated system-turns, the obtained information is improved through the dialog. The article focuses on the development and operation of this module, which is valid for agenda-based and statistical approaches, being applicable in both types of corpora.

The detection of secondary emotions, like sarcasm, in online dialogues is a difficult task that has rarely been treated in the literature. In this work (This work has been partially supported by the Spanish Ministry of Science under grant TIN2011-28169-C05-04, and by the Basque Government under grant IT685-13.), we tackle this problem as an affective pattern recognition problem. Specifically, we consider different kind of information sources (statistical and semantic) and propose alternative ways of combining them. We also provide a comparison of a Support Vector Machine (SVM) classification method with a simpler Naive Bayes parametric classifier. The experimental results show that combining statistical and semantic feature sets comparable performances can be achieved with Naive Bayes and SVM classifiers.

The goal of this paper is to describe a multimodal dialogue system based project developed under EDECA ??Narchitecture for Softec-Iberma ??tica company. The demonstration takes 10 min. aprox.

In this paper we undertake the use of phonological features applied to speech recognition in Spanish language. We investigate two different ways to integrate these phonological features into an HMM based speech recognition system. We also propose a method to integrate these features using an architecture that uses independent feature streams. In the experimental results we find that higher recognition accuracies and less computational cost can be obtained.

Interactive and multimodal interfaces have been proved of help in human-machine interactive systems such as dialogue systems. Facial animation, specifically lips motion, helps to make speech comprehensible and dialogue turns intuitive. The dialogue system under consideration consists of a stand that allows to get current and past news published on the Internet by several newspapers and sites, and also to get information about the weather, initially of Spanish cities, although it can be easily extended to other cities around the world. The final goal is to provide with valuable information and entertainment to people queuing or just passing around. The system aims, as well, at disabled people thanks to the different multi-modal input/outputs taken into consideration. In this work are described the diferent modules that are part of the dialogue system. These modules where developed under EDECAN architecture specifications.

Stochastic finite-state transducers constitute a type of word-based models that allow an easy integration with acoustic model for speech translation. The aim of this work is to develop a novel approach to phrase-based statistical finite-state transducers. In this work, we explore the use of linguistically motivated phrases to build phrase-based models. The proposed phrase-based transducer has been tested and compared to a word-based equivalent machine, yielding promising results in the reported preliminary text and speech translation experiments.