Resultados de investigación

Corpus sobre recursos de turismo anotados para su empleo en análisis de sentimiento basado en aspecto., Ministerio de Ciencia e Innovación de España PID2020-115310RB-I00

The identification of behavioral traits that could predict an individual's susceptibility to engage in cocaine addiction is relevant for understanding and preventing this disorder, but investigations of cocaine addicts rarely allow us to determinate whether their behavioral attributes are a cause or a consequence of drug use. To study the behaviors that predict cocaine vulnerability, male C57BL/6J mice were examined in a battery of tests (the elevated plus maze, hole-board, novelty preference in the Y-Maze, episodic-like object recognition and forced swimming) prior to training in a cocaine-conditioned place preference (CPP) paradigm to assess the reinforcing value of the drug. In a second study, the anatomical basis of high and low CPP in the mouse brain was investigated by studying the number of neurons (neuronal nuclei-positive) in two addiction-related limbic regions (the medial prefrontal cortex and the basolateral amygdala) and the number of dopaminergic neurons (tyrosine hydroxylase-positive) in the ventral tegmental area by immunohistochemistry and stereology. Correlational analyses revealed that CPP behavior was successfully predicted by anxiety-like measures in the elevated plus maze (i.e., the more anxious mice showed more preference for the cocaine-paired compartment) but not by the other behaviors analyzed. In addition, increased numbers of neurons were found in the basolateral amygdala of the high CPP mice, a key brain center for anxiety and fear responses. The results support the theory that anxiety is a relevant factor for cocaine vulnerability, and the basolateral amygdala is a potential neurobiological substrate where both anxiety and cocaine vulnerability could overlap., This research was funded by the Spanish Ministry of Economy and Competitiveness and was co-funded by the European Research Development Fund (UE-ERDF) (PSI2013-44901-P to L.J.S.); the Spanish Carlos III Health Institute (ISC-III), the Spanish Ministry of Economy and Competitiveness, UE-ERDF (CP12/03109 to J.S.); the Regional Ministry of Health and Social Welfare of the AndalusianRegional Government (Junta de Andalucía) (PI0228-2013 to F.J.P. and PI0823-2012 to A.S.); Red de Trastornos Adictivos UE-ERDF2012 (RD12/0028/0001) and Plan Nacional sobre Drogas 049/2013to F.R.F.

Resultados de una muestra de 471 estudiantes de educación superior utilizada para la validación de la escala EPIAG-ES.

The aim of this study is to explore a model examining how emotional intelligence (EI), gender, depressive symptoms and suicidal thoughts and behaviours (STB) may interact. The sample included 380 Spanish adolescent bully-victims (61.6% boys; mean age = 14.38 years). The results indicated that EI is a significant negative predictor of decreased STB and that this relation is fully mediated by depressive symptoms. This effect was moderated by gender, such that the mediation is stronger for girls compared to boys. The promotion of EI may be core in the development of prevention programmes for suicide, especially among female bully-victims., Parte del proyecto I+D+i PID2020-117006RB-I00, financiado por MCIN/AEI/10.13039/501100011033, Grupo de investigación Applied Positive Lab CTS-1048G-FEDER, Contrato posdoctoral financiado por el Spanish Ministry of Science, Innovation and Universities (FJC2019-038942-I/ AEI/10.13039/501100011033).

The files contain the mobility traces generated by a group of 19 experimental subjects that emulated a set of predetermined ADL (Activities of Daily Life) and falls. The traces are aimed at evaluating fall detection algorithms. Several video clips describing the performed movements are also included., European FEDER funds, Spanish Ministry of Economy and Competitiveness Award Number, Universidad de Málaga (Spain), Andalucia Tech, TEC2013-42711-R

This database is made up of EEG signals from 6 subjects listening to sentences in different languages and their answers to the questions: have you understood the meaning of the sentence?. The languages chosen are: english, german, italian, korean and spanish. These signals have been captured with the BrainVision actiCHAMP-PLUS system and consist of a total of 64 EEG channels. The BrainVision Recorder software was used to store the signals. The stimulus presentation software used to design the experiment is Eprime 3. For more detailed information on this database, the capture system used and its applications, see [1]. If these data are used for any publication, the following paper must be cited: [1] Isaac Ariza, Ana M. Barbancho, Lorenzo J. Tardón, Isabel Barbancho, Energy-based features and bi-LSTM neural network for EEG-based music and voice classification. Neural Comput & Applic 36, 791–802 (2024). https://doi.org/10.1007/s00521-023-09061-3, Funding for open access publishing: Universidad Málaga/CBUA. This publication is part of Project PID2021-123207NB-I00, funded by MCIN/AEI/10.13039/501100011033/FEDER, UE. This work was partially funded by Junta de Andalucía, Proyectos de I+D+i, in the framework of Plan Andaluz de Investigación, Desarrollo e Innovación (PAIDI 2020), under Project No. PY20_00237. Funding for open access charge: Universidad de Málaga/CBUA. This work was done at Universidad de Málaga, Campus de Excelencia Internacional Andalucia Tech.

The UMAHand Dataset comprises a main directory and three subdirectories: TRACES (containing measurements), VIDEOS (containing video sequences) and SCRIPTS (with two scripts that automate the downloading, unzipping and processing of the dataset). The main directory also includes three descriptive plain text files and an image: • "readme.txt": this file is a brief guide of the dataset which describes the basic characteristics of the database, the testbed or experimental framework used to generate it and the organization of the data file. • "user_characteristics.txt": which contains a line of six numerical (comma-separated) values for each participant describing their personal characteristics in the following order: 1) an abstract user identifier (a number from 01 to 25), 2) a binary value indicating whether the participant is left-handed (0) or right-handed (1), 3) a numerical value indicating gender: male (0), female (1), undefined or undisclosed (2), 4) the weight in kg, and 5) the height in cm and 6) the age in years. • "activity_description.txt": For each activity, this text file incorporates a line with the activity identifier (numbered from 01 to 29) and an alphanumeric string that briefly describes the performed action. • "sensor_orientation.jpg": a JPEG-type image file illustrating the way the sensor is carried and the orientation of the measurement axes. The TRACE subfolder with the data is, in turn, organized into 25 secondary subfolders, one for each participant, named with the word "output" followed by underscore symbol (_) and the corresponding participant identifier (a number from 1 to 25). Each subdirectory contains one CSV (Comma Separated Values) file for each trial (each repetition of any activity) performed by the corresponding volunteer. The filenames with the monitored data follow the following format: "user_XX_activity_YY_trial_ZZ.csv" where XX, YY, and ZZ represent the identifiers of the participant (XX), the activity (YY) and the repetition number (ZZ), respectively. In the files, which do not include any header, each line corresponds to a sample taken by the sensing node. Thus, each line of the CSV files presents a set of the simultaneous measurements captured by the sensors of the Shimmer mote at a certain instant. The values in each line are arranged as follows: •Timestamp, Ax, Ay, Az, Gx, Gy, Gz, Mx, My, Mz, P where: -Timestamp is the time indication of the moment when the following measurements were taken. Time is measured in milliseconds elapsed since the start of the recording. Therefore, the first sample, in the first line of the file, has a zero value while the rest of the timestamps in the file are relative to this first sample. -Ax, Ay, Az are the measurements of the three axes of the triaxial accelerometer (in g units). -Gx, Gy, Gz indicate the components of the angular velocity measured by the triaxial gyroscope (in degrees per second or dps). -Mx, My, Mz represent the 3-axis data in microteslas (µT) captured by the magnetometer. -P is the measurement of pressure in millibars. Besides, the VIDEOS directory includes 29 anonymized video clips that illustrate with the corresponding examples the 29 manual activities carried out by the participants. The video files are encoded in MPEG4 format and named according to the format "Example_Activity_XX.mp4", where XX indicates the identifier of the movement (as described in the activity_description.txt file). Finally, the SCRIPTS subfolder comprises two scripts written in Python and Matlab. These two programs (named Load_traces), which perform the same function, are designed to automate the downloading and processing of the data. Specifically, these scripts perform the following tasks: 1. Download the database from the public repository as a single compressed zip file. 2. Unzip the aforementioned file and create the subfolder structure of the dataset in a specific directory named UMAHand_Dataset. As previously commented, in the subfolder named TRACES, one CSV trace file per each experiment (i.e. per each movement, user, and trial) is created. 3. Read all the CSV files and store their information in a list of dictionaries (Python) or a matrix of structures (Matlab) named datasetTraces. Each element in that list/matrix has two fields: the filename (which identifies the user, the type of performed activity, and the trial number) and a numerical array of 11 columns containing the timestamps and the measurements of the sensors for that experiment (arranged as mentioned above). All experiments and data acquisition were conducted in private home environments. Participants were asked to perform those activities involving sustained or continuous hand movements (e.g. clapping hands) for at least 10 seconds. In the case of brief and punctual movements, which might require less than 10 seconds (e.g. picking up an object from the floor), volunteers were simply asked to execute the action until its conclusion. Thus, a total of 752 samples were collected, with durations ranging from 1.98 to 119.98 seconds., The objective of the UMAHand dataset is to provide a systematic, Internet-accessible benchmarking database for evaluating algorithms for the automatic identification of manual activities. The database was created by monitoring 29 predefined activities involving specific movements of the dominant hand. These activities were performed by 25 participants, each completing a certain number of repetitions. During each movement, participants wore a 'mote' or Shimmer sensor device on their dominant hand's wrist. This sensor, comparable in weight and volume to a wristwatch, was attached with an elastic band according to a predetermined orientation. The Shimmer device contains an Inertial Measurement Unit (IMU) with a triaxial accelerometer, gyroscope, magnetometer, and barometer. These sensors recorded measurements of acceleration, angular velocity, magnetic field, and atmospheric pressure at a constant sampling frequency of 100 Hz during each movement., Spanish Ministry of Science, Innovation, and Universities, NextGenerationEU/PRTR Funds, Universidad de Málaga, Campus de Excelencia Internacional Andalucia Tech, ED2021-130456B-I00, B4-2023-12

Background: Problematic Internet Use (PIU) has become a significant concern among adolescents. While previous studies have examined individual predictors of PIU, the role of teachers' emotionally intelligent behaviors (TEIB) in mitigating PIU remains unexplored. Objective: This research aims to examine the underlying mechanisms in the link between TEIB and PIU through a serial mediation model involving teacher-student relationships (TSR) and stress in two independent studies. Methods: Two studies with Spanish adolescents were conducted: a cross-sectional study (N = 1,966) and a 9-month prospective study (N = 517). TEIB, TSR, stress symptoms (Study 1), perceived stress (Study 2), and PIU were assessed. Results: In both studies, TEIB was positively associated with TSR and negatively associated with stress and PIU. The serial mediation path was significant: TEIB predicted higher TSR, which in turn was linked to lower stress levels, thereby reducing PIU. In Study 1, both simple and serial mediation effects were significant, whereas in Study 2, only the serial mediation effect was supported. Conclusion: These findings highlight the importance of teachers' emotionally intelligent behaviors in reducing students’ PIU. Schools should consider implementing emotional skills training programs for teachers to foster supportive teacher-student relationships and promote healthier online behaviors among adolescents. Finally, school-based recommendations for teachers to prevent adolescents from PIU are suggested in the light of our findings., This work was part of the R+D+i project PID2020-117006RB-I00, funded by MCIN/AEI/10.13039/501100011033/ and Group CTS-1048G-FEDER (Junta de Andalucía). The first author was supported by Spanish Ministry of Universities (FPU21/02323).

El objetivo del estudio es desarrollar, implementar, y analizar la efectividad de una intervención psicoeducativa basada en la práctica del mindfulness para prevenir la obesidad infantil y mejorar los hábitos alimenticios. Para ello se llevó un estudio durante más de 6 meses en el que participaron 207 menores entre 7 y 11 años, con un diseño pre-post con seguimiento y grupo control. Se implementó el Mindful Eating Programme for Childhood Obesity Prevention (MEPCOP), con el objetivo de mejorar los hábitos alimenticios de los menores. El programa estaba compuesto de ocho sesiones de una hora, que se llevaban a cabo en el aula de diferentes escuelas de educación primaria. Se realizaron diferentes análisis de varianza (ANOVA) de medidas parcialmente repetidas con un factor intersujeto (el tratamiento: grupo control y grupo experimental) y un factor intrasujeto (el momento de intervención: pre, post, y seguimiento). Como variables dependientes se incluyeron la adherencia a la dieta mediterránea, las habilidades de mindfulness, y la alimentación consciente (cata consciente y alimentación inconsciente). Los resultados mostraron que tras la intervención mejoraron la adherencia a la dieta mediterránea, las habilidades de mindfulness, y que hubo un decremento de la alimentación inconsciente (mejora de alimentación consciente). Los resultados indican que el MEPCOP es efectivo para mejorar los hábitos alimenticios de los menores. A pesar de ello, se deben realizar más estudios para confirmar y apoyar la generalización de estos resultados., Departamento de Psicología Evolutiva y de la Educación. Universidad de Málaga

Measurements, ages and references of the specimens analyzed., Junta de Andalucía, Universidad de Málaga