Resultados de investigación

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

This dataset contains scripts and associated data used to deploy, configure, and operate an Open Radio Access Network (O-RAN) environment based on the srsRAN software stack. It includes Python and shell scripts for automating network deployment, managing system components, and executing experiments. The dataset also incorporates tools for parsing network logs and a simulation framework that enables real-time reproduction of previously recorded experiments. This allows controlled and reproducible analysis of network behaviour under consistent conditions

This file makes data available in a public repository from the PlosOne article titled: Cell survival and differentiation with nanocrystalline glass-like carbon using substantia nigra dopaminergic cells derived from transgenic mouse embryos. Rodriguez-Losada, N et al. 2017, 1. Funds from the University of Malaga and Campus de Excelencia Internacional Andalucía Tech (UMA) 2. Junta de Andalucia Government, Spain (PAIDI-CTS156) 3. Spanish Ministry of Science and Innovation through the Ramon y Cajal Fellowship (RG)

La base de datos hace referencia al artículo: Figueirido, B., Palmqvist, P., Pérez-Claros, J. A., & Janis, C. M. (2019). Sixty-six million years along the road of mammalian ecomorphological specialization. Proceedings of the National Academy of Sciences, 116(26), 12698-12703. En ella se establece la clasificación por ecotipos de dieta, locomoción y masa corporal para las especies utilizadas en el artículo. Las categorías ecológicas proceden de NOW database., Ministerio de Ciencia, Innovación y Universidades

La inteligencia emocional (IE) y el afrontamiento resiliente (AR) han mostrado influencias positivas en el compromiso ocupacional (CO). Considerando la falta de estudios en esta línea, el presente trabajo examina el rol del AR como mediador y moderador en la relación entre la IE y el CO en una muestra de 338 docentes noveles (58,9% mujeres; Medad= 26,85, DT= 5,66). Los resultados mostraron que el AR mediaba (B= ,20; IC= ,02, ,37), pero no moderaba esta relación (B= -,01; IC= -,31, ,29). Se discuten las implicaciones para el diseño de acciones de promoción de actitudes laborales positivas en la formación inicial docente., -Junta de Andalucía (UMA18-FEDERJA-147) -Ministerio de Ciencia e Innovación (PID2020-117006RB-I00) -Grupo PAIDI CTS-1048 de la Junta de Andalucía -Universidad de Málaga (contratos postdoctorales) -Ministerio de Ciencia, Innovación y Universidades (FJC2019-038942-I/AEI/10.13039/501100011033)

The present study focuses on the interplay of emotion-regulation ability and perceived workplace social support as predictors of job satisfaction and happiness in a Spanish multi-occupational sample. A total of 494 working adults (39.4% females) took part in this study. Emotion-regulation ability and perceived support from colleagues and supervisors were positively associated. In addition, emotion-regulation ability and perceived support from colleagues and supervisors showed positive associations with job satisfaction and happiness. Furthermore, considering results from moderation analyses, when low levels of perceived workplace social support were reported, the relationship between emotion regulation and both job satisfaction and happiness was stronger than in cases of higher perceived workplace support. In line with previous studies, these findings suggest that training in emotion regulation abilities may take into consideration the potential moderating role of job characteristics such as support from colleagues and supervisors. Finally, theoretical and practical implications of the joint study of these factors in line with the Job Demands-Resources model and the Emotional Intelligence framework are discussed., Proyecto I+D+i del Ministerio de Economía y Competitividad (PSI2012-38813) Ayuda predoctoral del Ministerio de Educación, Cultura y Deporte (FPU16/02238) Plan Propio de Investigación de la Universidad de Málaga (PPIT.UMA.B1.2017/23)

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

Background: Problematic smartphone use (PSU) is a public health issue that is currently rising among adoles- cents. The Compensatory Internet Use Theory (CIUT) poses that difficulties in handling negative life circum- stances could result in PSU. Furthermore, the Interaction of Person-Affect-Cognition-Execution (I-PACE) model suggests that the interaction between core characteristics and affective and cognitive responses could lead to PSU. The present study aimed to clarify the links between psychological distress and PSU by exploring rumi- nation as a mediator and emotional intelligence (EI) as a moderator. Methods: A sample of 1882 adolescents (54% female, 46% male) completed measures of psychological distress, rumination, EI and PSU. The PROCESS macro was used to conduct a moderated mediation analysis. Results: The mediation results showed a significant indirect effect from psychological distress to PSU through rumination. Furthermore, EI was a significant moderator of this effect. Thus, in adolescents with higher EI, the effect of psychological distress on PSU through rumination was not significant. Limitations: Cross-sectional data do not imply causality and further studies should use longitudinal designs. Self- report questionnaires may be susceptible to social desirability bias and future studies including other sources of information may help to minimize such bias. Conclusions: This study contributes to the field of problematic digital technology usage, showing that the link between psychological distress and PSU depends on the EI levels, which might influence PSU indirectly through rumination. Furthermore, empirical evidence for the CIUT and I-PACE models was provided. Lastly, in- terventions aiming at training EI may aid in the prevention of PSU., Universidad de Málaga (PPIT.UMA.A2.2019) Grupo PAIDI Applied Positive Lab CTS-1048 (Junta de Andalucía) Proyecto I+D+i del Ministerio de Ciencia e Innovación de España (PID2020-117006RB-I00) Fondos FEDER/Junta de Andalucía (UMA 18-FEDERJA-147)