Recently, in the commercial and entertainment sectors, we have seen increasing interest in incorporating chatbots into websites and apps, in order to assist customers and clients. In the academic area, chatbots are useful to provide some guidance and information about courses, admission processes and procedures, study programs, and scholarly services. However, these virtual assistants have limited mechanisms to suitably help the teaching and learning process, considering that these mechanisms should be advantageous for all the people involved. In this article, we design a model for developing a chatbot that serves as an extra-school tool to carry out academic and administrative tasks and facilitate communication between middle-school students and academic staff (e.g., teachers, social workers, psychologists, and pedagogues). Our approach is designed to help less tech-savvy people by offering them a familiar environment, using a conversational agent to ease and guide their interactions. The proposed model has been validated by implementing a multi-platform chatbot that provides both textual-based and voice-based communications and uses state-of-the-art technology. The chatbot has been tested with the help of students and teachers from a Mexican middle school, and the evaluation results show that our prototype obtained positive usability and user experience endorsements from such end-users.

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Thermal resistance was determined on a strain of Bacillus couguluns in double concentrated tomato paste (a," = 0.95 at 23"C, pH=4.0, 30.3"Brix, 70.1% moisture and acidity 1.30 g/lOOg citric acid. A microsyringe method was used with an inoculum of 1.3 x lo4 spores/ mL. Values of D,,= 3.5 min and z = 9.5C" were obtained.

Purpose Evaluating consecutive early breast cancer patients, we analyzed both the impact of EndoPredict ® on clinical decisions as well as clinico-pathological factors influencing the decision to perform this gene expression test. Methods Hormone receptor (HR)-positive and human epidermal growth factor receptor 2 (HER2)-negative early breast cancer patients treated between 2011 and 2016 were included in this study to investigate the role of EndoPredict ® (EPclin) in the treatment of early breast cancer. A main study aim was to analyze the changes in therapy recommendations with and without EPclin. In addition, the impact of clinico-pathological parameters for the decision to perform EPclin was examined by Pearson's chi-squared test (χ 2-test) and Fisher's exact test as well as univariate and multivariate logistic regressions. Results In a cohort of 869 consecutive early HR-positive, HER-negative breast cancer patients, EPclin was utilized in 156 (18.0%) patients. EPclin led to changes in therapy recommendations in 33.3% (n = 52), with both therapy escalation in 19.2% (n = 30) and de-escalation in 14.1% (n = 22). The clinico-pathological factors influencing the use of EPclin were age (P < 0.001, odds ratio [OR] 0.498), tumor size (P = 0.011, OR 0.071), nodal status (P = 0.021, OR 1.674), histological grade (P = 0.043, OR 0.432), and Ki-67 (P < 0.001, OR 3.599). Conclusions EPclin led to a change in therapy recommendations in one third of the patients. Clinico-pathological parameters such as younger age, smaller tumor size, positive nodal status, intermediate histological grade and intermediate Ki-67 had a significant influence on the use of EndoPredict ® .

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