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[This corrects the article DOI 10.3389/fpsyg.2021.674054.].The aim of this research is to contrast an explanatory model of how the perceived organizational image of a university center (faculty) influences its students' loyalty. The data is obtained from a structured survey of students in Spain, obtaining a sample of 224 valid questionnaires. The methodology used is exploratory and confirmatory factor analysis to validate the measurement scales and the estimation of the model is carried out by applying Structural Equation Modeling (SEM). The results show that organizational image is the key variable to influence students' decision to continue taking new courses at the center, as well as to recommend it to other people. It is observed that the greater students' positive perception of the organizational image is, the greater their satisfaction with the center will be, which results in a higher level of loyalty to the center in which they study. However, their identification levels with the center is not a relevant variable in the process of increasing loyalty.Starting from a pure-image perspective, using machine learning in emotion analysis methods to study artwork is a new cross-cutting approach in the field of literati painting and is an effective supplement to research conducted from the perspectives of aesthetics, philosophy, and history. This study constructed a literati painting emotion dataset. Five classic deep learning models were used to test the dataset and select the most suitable model, which was then improved upon for literati painting emotion analysis based on accuracy and model characteristics. The final training accuracy rate of the improved model was 54.17%. This process visualizes the salient feature areas of the picture in machine vision, analyzes the visualization results, and summarizes the connection law between the picture content of the Chinese literati painting and the emotion expressed by the painter. This study validates the possibility of combining deep learning with Chinese cultural research, provides new ideas for the combination of new technology and traditional Chinese literati painting research, and provides a better understanding of the Chinese cultural spirit and advanced factors.The brain-computer interface (BCI) interprets the physiological information of the human brain in the process of consciousness activity. It builds a direct information transmission channel between the brain and the outside world. As the most common non-invasive BCI modality, electroencephalogram (EEG) plays an important role in the emotion recognition of BCI; however, due to the individual variability and non-stationary of EEG signals, the construction of EEG-based emotion classifiers for different subjects, different sessions, and different devices is an important research direction. Domain adaptation utilizes data or knowledge from more than one domain and focuses on transferring knowledge from the source domain (SD) to the target domain (TD), in which the EEG data may be collected from different subjects, sessions, or devices. In this study, a new domain adaptation sparse representation classifier (DASRC) is proposed to address the cross-domain EEG-based emotion classification. To reduce the differences in domain distribution, the local information preserved criterion is exploited to project the samples from SD and TD into a shared subspace. A common domain-invariant dictionary is learned in the projection subspace so that an inherent connection can be built between SD and TD. In addition, both principal component analysis (PCA) and Fisher criteria are exploited to promote the recognition ability of the learned dictionary. Besides, an optimization method is proposed to alternatively update the subspace and dictionary learning. The comparison of CSFDDL shows the feasibility and competitive performance for cross-subject and cross-dataset EEG-based emotion classification problems.How do people describe the psychological sense of community (PSOC) in the present day ideological climate of globalising neo-liberalism, assuming that people are essentially individualistic, that solidarity, social commitment, and citizenship are not natural dispositions, as we all are the lonely citizen? This issue is addressed by a mixed-methods study using semi-structured interviews with two age groups-young and older people-from two different cultures-India (Mumbai) and Norway (Oslo). This two by two design gives the opportunity to analyse people's meaning systems of PSOC, asking; is there a core meaning system of PSOC shared by people within as well as across cultures? Belongingness and citizenship are continuously formed and negotiated, just at the intersection of two dimensions culture and historical time. The young and older adult informants often live in different "historical times." The meaning systems of PSOC were explored and compared by language analyses of words used by the informants. Text sears. This study points out how community psychology and the applied social sciences can work to strengthen the feelings of connections to other communities, societies, and nations outlining and co-creating transformative multi-level interventions of public policy programmes of inclusion and "we-ness."[This corrects the article DOI 10.3389/fphys.2021.625044.].Background In attempts to hinder the spread of the Coronavirus disease 2019 (COVID-19), many countries have continued distancing, isolation, and quarantine measures, which has led to limited opportunity of physical activity. This study provides empirical support for a motivational process behind physical activity during the COVID-19 pandemic by testing the influence of psychosocial variables derived from the integrated model of self-determination theory (SDT) and the theory of planned behavior (TPB). Methods A cross-sectional survey was conducted among Korean adults (N = 248). Participants completed the measures of SDT and TPB constructs modified to reflect their participation in physical activity during the COVID-19 pandemic. A sample size of 243 participants was employed, and the integrated model was tested using serial multiple mediation analysis to check the hypothesized relationships. Results Findings indicated that in the COVID-19 context, the satisfaction of basic psychological needs positively predicts the level of self-determined motivations for physical activity, which is partially related to the level of social cognitive beliefs and intentions. The findings also demonstrated that attitude toward physical activity during COVID-19 was a major variable explaining the serial multiple relationships between the SDT and TPB constructs. The potential influence of demographics (gender, age, marital status, and past physical activity) was controlled as a covariate, and no significant effects were identified. Conclusion The current study identified the psychosocial mechanisms of intention of South Koreans' physical activity during the COVID-19 pandemic, which could be used as an empirical basis for the development of interventions to maintain or strengthen physical activity in unprecedented situations.This study aimed to examine the acute physiological effect of shuttle-run-based high-intensity intermittent exercise (HIIE) performed at the same relative speed (i. e., 100% PST-CAR) on sand (SAND) and grass (GRASS) in male junior soccer players. Seven Under-23 Brazilian national league ("Série A") soccer players completed four testing sessions in either SAND or GRASS surface condition. The first two testing sessions consisted of performing a maximal progressive shuttle-run field protocol until volitional exhaustion (Carminatti's test, T-CAR), whereas the third and fourth sessions comprised a HIIE session on each ground surface. The HIIE session consisted of three 5-min bouts [12 s shuttle-run (with a direction change every 6 s)/12 s of passive rest] performed at 100% of T-CAR peak speed (PST-CAR) with 3 min of passive recovery between sets. Measurements of oxygen uptake (VO2), heart rate (HR), blood lactate concentration ([La]), and rating of perceived exertion (RPE) were performed during all conditions. The SAND condition elicited significantly higher %VO2peak (94.58 ± 2.73 vs. 87.45 ± 3.31%, p less then 0.001, d = 2.35), %HRpeak (93.89 ± 2.63 vs. this website 90.31 ± 2.87%, p less then 0.001, d = 1.30), RPE (8.00 ± 0.91 vs. 4.95 ± 1.23 a.u., p less then 0.001, d = 2.82), and [La] (10.76 ± 2.37 vs. 5.48 ± 1.13 mmol/L, p less then 0.010, d = 2.84). This study showed that higher internal workloads are experienced by the players during a single HIIE session performed on a softer surface as SAND, even when the exercise intensity was individualized based on 100%PST-CAR.This systematic review adopts a formal and structured approach to review the intersection of data science and smart tourism destinations in terms of components found in previous research. The study period corresponds to 1995-2021 focusing the analysis mainly on the last years (2015-2021), identifying and characterizing the current trends on this research topic. The review comprises documentary research based on bibliometric and conceptual analysis, using the VOSviewer and SciMAT software to analyze articles from the Web of Science database. There is growing interest in this research topic, with more than 300 articles published annually. Data science technologies on which current smart destinations research is based include big data, smart data, data analytics, social media, cloud computing, the internet of things (IoT), smart card data, geographic information system (GIS) technologies, open data, artificial intelligence, and machine learning. Critical research areas for data science techniques and technologies in smart destinations are public tourism marketing, mobility-accessibility, and sustainability. Data analysis techniques and technologies face unprecedented challenges and opportunities post-coronavirus disease-2019 (COVID-19) to build on the huge amount of data and a new tourism model that is more sustainable, smarter, and safer than those previously implemented.To perceive a second language (L2), non-native speakers not only have to focus on phonological, lexical, and grammatical knowledge, but also need to develop a good mastery of L2 strategic knowledge, including selective attention and language planning. Previous research has found that non-tonal speakers are overtly attentive to segments, while tonal language speakers give more attention to tones. However, it is unclear how different dominant language speakers distribute their attention while processing segments or tones and segments and tones stimuli in non-native speeches. The present study also aims to examine the roles of language dominance play in the designed perceptual tasks. In the current study 20 Cantonese native speakers, 18 Cantonese-dominants, and 18 Urdu-dominants participated in an attention distribution experiment in Cantonese. The results show that the Urdu-dominants retain their L1 attentional strategy in the processing of Cantonese stimuli, classifying the stimuli along segments, while the Cantonese native speakers are more attentive to tones. Moreover, the Cantonese-dominants show a perceptual flexibility as highly proficient and experienced listeners. The results reveal that language dominance plays a vital role in listeners' attention distribution. The research also supports PAM-L2 theory on bilingual. The findings of the current study can be applied to Chinese language learning and teaching and language acquisition studies.