41 research outputs found
Inter-rater reliability of streetscape audits using online observations: Microscale Audit of Pedestrian Streetscapes (MAPS) global in Japan
This study aimed to evaluate the inter-rater reliability of streetscape audits among online observations using the Microscale Audit of Pedestrian Streetscapes-Global version (MAPS-Global) in Japan.
MAPS-Global observations were conducted on routes with distances ranging from 400 to 725 m from a residence toward a non-residential destination. Google Street View audits were independently conducted by two trained raters on each route. A tiered scoring system was applied to summarize the items at multiple levels of aggregation. Positive and negative valence scores were created based on the expected association with physical activity. Inter-rater reliability analyses were performed using kappa statistics or intraclass correlation coefficients (ICC).
Of the 32 older adults participating in an intervention study in the community-wide physical activity promotion project in Fujisawa City, 19 addresses were used, excluding those with nearby addresses. Results demonstrated “excellent” agreement for most of the summary scores analyzed (kappa or ICC values of 0.75 or higher [80.4 %]), while 6.5 % of items exhibited “good” agreement (ICC = 0.60–0.74). By contrast, only 13.0 % of the scales had ICC values lower than 0.60 (“fair” or “poor” reliability). The results illustrated high reliability for the grand summary scores and composite subscale measures. However, caution should be exercised when interpreting subscale scores for less frequently observed negative attributes and aesthetic/social characteristics. The results presented in this study support the application of online observations using MAPS-Global in urban areas of Japan, which could be implemented to inform decisions related not only to physical activity but also to traffic safety
Analysis of bis(trifluoromethylsulfonyl)imide-doped paramagnetic graphite intercalation compound using F-19 very fast magic angle spinning nuclear magnetic resonance
F atoms bonding to paramagnetic/conductive graphene layers in accepter-type graphite intercalation compounds (GICs) are analyzed using very fast magic angle spinning nuclear magnetic resonance, which is applied for the first time on F-19 nuclei to investigate paramagnetic materials. In the bis(trifluoromethylsulfonyl)imide(TFSI)-doped GIC, C-F bonds between fluorine atoms and graphene layers conform to a weak bonding of F to the graphene sheets. TFSI anions intercalated in the GIC do not show overall molecular motion; even at room temperature only the CF3 groups rotate
Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment
We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70–75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70–80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands.Cancer Research UK, Grant/Award Number: FC001003; Changzhou Science and Technology Bureau, Grant/Award Number: CE20200503; Department of Energy and Climate Change, Grant/Award Numbers: DE-AR001213, DE-SC0020400, DE-SC0021303; H2020 European Institute of Innovation and Technology, Grant/Award Numbers: 675728, 777536, 823830; Institut national de recherche en informatique et en automatique (INRIA), Grant/Award Number: Cordi-S; Lietuvos Mokslo Taryba, Grant/Award Numbers: S-MIP-17-60, S-MIP-21-35; Medical Research Council, Grant/Award Number: FC001003; Japan Society for the Promotion of Science KAKENHI, Grant/Award Number: JP19J00950; Ministerio de Ciencia e Innovación, Grant/Award Number: PID2019-110167RB-I00; Narodowe Centrum Nauki, Grant/Award Numbers: UMO-2017/25/B/ST4/01026, UMO-2017/26/M/ST4/00044, UMO-2017/27/B/ST4/00926; National Institute of General Medical Sciences, Grant/Award Numbers: R21GM127952, R35GM118078, RM1135136, T32GM132024; National Institutes of Health, Grant/Award Numbers: R01GM074255, R01GM078221, R01GM093123, R01GM109980, R01GM133840, R01GN123055, R01HL142301, R35GM124952, R35GM136409; National Natural Science Foundation of China, Grant/Award Number: 81603152; National Science Foundation, Grant/Award Numbers: AF1645512, CCF1943008, CMMI1825941, DBI1759277, DBI1759934, DBI1917263, DBI20036350, IIS1763246, MCB1925643; NWO, Grant/Award Number: TOP-PUNT 718.015.001; Wellcome Trust, Grant/Award Number: FC00100