(2,2′-Bipyrid­yl)bis­[N,N-bis­(2-hydroxy­ethyl)dithio­carbamato-κ2 S,S′]cadmium(II)

The title compound, [Cd(C5H10NO2S2)2(C10H8N2)], features a trigonal-prismatic coordination geometry for the CdII ion, based on an N2S4 donor set defined by two chelating dithio­carbamate ligands and a 2,2′-bipyridyl ligand. In the crystal, extensive O—H⋯O hydrogen bonding results in the formation of 12-membered {⋯HO}6 synthons and one-dimensional supra­molecular chains with further O—H⋯S inter­actions providing additional stability to the linear chain with base vector [01]

Influence of Forest Therapy on Cardiovascular Relaxation in Young Adults

Background. Despite increasing attention toward forest therapy as an alternative medicine, very little evidence continues to be available on its therapeutic effects. Therefore, this study was focused on elucidating the health benefits of forest walking on cardiovascular reactivity. Methods. Within-group comparisons were used to examine the cardiovascular responses to walking in forest and urban environments. Forty-eight young adult males participated in the two-day field research. Changes in heart rate variability, heart rate, and blood pressure were measured to understand cardiovascular reactivity. Four different questionnaires were used to investigate the changes in psychological states after walking activities. Results. Forest walking significantly increased the values of ln(HF) and significantly decreased the values of ln(LF/HF) compared with the urban walking. Heart rate during forest walking was significantly lower than that in the control. Questionnaire results showed that negative mood states and anxiety levels decreased significantly by forest walking compared with urban walking. Conclusion. Walking in the forest environment may promote cardiovascular relaxation by facilitating the parasympathetic nervous system and by suppressing the sympathetic nervous system. In addition, forest therapy may be effective for reducing negative psychological symptoms

Meta-analysis of genome-wide association studies in East Asian-ancestry populations identifies four new loci for body mass index

Recent genetic association studies have identified 55 genetic loci associated with obesity or body mass index (BMI). The vast majority, 51 loci, however, were identified in European-ancestry populations. We conducted a meta-analysis of associations between BMI and ∼2.5 million genotyped or imputed single nucleotide polymorphisms among 86 757 individuals of Asian ancestry, followed by in silico and de novo replication among 7488–47 352 additional Asian-ancestry individuals. We identified four novel BMI-associated loci near the KCNQ1 (rs2237892, P = 9.29 × 10−13), ALDH2/MYL2 (rs671, P = 3.40 × 10−11; rs12229654, P = 4.56 × 10−9), ITIH4 (rs2535633, P = 1.77 × 10−10) and NT5C2 (rs11191580, P = 3.83 × 10−8) genes. The association of BMI with rs2237892, rs671 and rs12229654 was significantly stronger among men than among women. Of the 51 BMI-associated loci initially identified in European-ancestry populations, we confirmed eight loci at the genome-wide significance level (P < 5.0 × 10−8) and an additional 14 at P < 1.0 × 10−3 with the same direction of effect as reported previously. Findings from this analysis expand our knowledge of the genetic basis of obesity

Korean language teachers’ vulnerability over English competency in Korean-only classrooms

Abstract The recent trend of the internationalization of higher education has increased the significance of English as a medium of instruction and communication on campus in non-English speaking countries. Within this context, this study explores emotional vulnerability of teachers of Korean as a second language (KSL) over their foreign language competency, particularly English. Analysis of interviews of twelve KSL teachers demonstrates these teachers’ divergent ways of interpreting and implementing Korean-only instruction, a prevalent norm within the language program, according to their perceived foreign language competency and relevant emotional vulnerability. KSL teachers with proficiency in other foreign language(s) tended to challenge the monolingual norm by utilizing their bilingual skills and experiences as resources for their teaching. Monolingual KSL teachers interpreted Korean-only narrowly and supported a monolingual immersion approach as a way to secure their teacher authority. Regardless of their attitudes towards the Korean-only instruction, however, most teachers experienced various levels of anxiety concerning their perceived lack of adequate English proficiency in the KSL classroom. The results suggest how second language teachers struggle to maintain legitimacy and authority against the hegemony of English in non-English second language contexts, providing implications for the language teacher education

Social Big-Data Analysis of Particulate Matter, Health, and Society

The study collected particulate matter (PM)-related documents in Korea and classified main keywords related to particulate matter, health, and social problems using text and opinion mining. The study attempted to present a prediction model for important causes related to particulate matter by using social big-data analysis. Topics related to particulate matter were collected from online (online news sites, blogs, caf&eacute;s, social network services, and bulletin boards) from 1 January 2015, to 31 May 2016, and 226,977 text documents were included in the analysis. The present study applied machine-learning analysis technique to forecast the risk of particulate matter. Emotions related to particulate matter were found to be 65.4% negative, 7.7% neutral, and 27.0% positive. Intelligent services that can detect early and prevent unknown crisis situations of particulate matter may be possible if risk factors of particulate matter are predicted through the linkage of the machine-learning prediction model

Application of Social Big Data to Identify Trends of School Bullying Forms in South Korea

As the contemporary phenomenon of school bullying has become more widespread, diverse, and frequent among adolescents in Korea, social big data may offer a new methodological paradigm for understanding the trends of school bullying in the digital era. This study identified Term Frequency-Inverse Document Frequency (TF-IDF) and Future Signals of 177 school bullying forms to understand the current and future bullying experiences of adolescents from 436,508 web documents collected between 1 January 2013, and 31 December 2017. In social big data, sexual bullying rapidly increased, and physical and cyber bullying had high frequency with a high rate of growth. School bullying forms, such as “group assault” and “sexual harassment”, appeared as Weak Signals, and “cyber bullying” was a Strong Signal. Findings considering five school bullying forms (verbal, physical, relational, sexual, and cyber bullying) are valuable for developing insights into the burgeoning phenomenon of school bullying

The Politics of Emotions in ELT: Structure of Feeling and Anxiety of Korean English Teachers

10.1080/1358684X.2019.1590145Changing English263252-26

Social big data analysis of future signals for bullying in South Korea: Application of general strain theory

The utilization of traditional social survey data to address today&apos;s bullying problems presents some limitations. In response, a new method to investigate and subsequently intervene is warranted. Therefore, this study analyzed big data generated by social media to identify Future Signals of bullying. This approach may contribute to effectively clarifying the problem and suggesting targeted interventions to address the bullying phenomenon in South Korea. For social big data analysis, 350,314 web documents were collected per hour each day from January 1, 2013 to June 30, 2017, from 279 subject channels based on an ontology of bullying-related topics. Term frequency, document frequency, degree of visibility, and degree of diffusion were computed to identify Future Signals. A substantial overlap of findings between studies based on social big data and traditional survey results was observed for family (e.g., parental divorce, domestic violence, child abuse), peer (e.g., transfer, friend violence), economic (e.g., economic problem), and school/academic (e.g., academic record, school control, academic stress) strain domains, whereas strains concerning the media (e. g., movie, celebrity) and cultural (e.g., materialism, hell Korea) domains seemed to be more salient in social big data. Weak Signal topics in social big data representing media and cultural strain domains (e.g., Youtube, class society, bullying culture) related to the bullying phenomenon appear to be emerging in significance. These topics and their respective strain domains represent potentially important new areas that warrant further investigation by practitioners and policymakers. These findings may allow the early detection of crucial information by providing data to support better informed insight and intervention related to the complex problem of bullying in South Korea.N