RESULTS: HLC caught more An. balabacensis than any other method (3.6 per night). In contrast, no An. balabacensis were collected in MBT collections, which generally performed poorly for all mosquito taxa. Anopheles vector species including An. balabacensis were sampled in both HENET and MENET collections, but at a mean abundance of less than 1 per night. There was no difference between HENET and MENET in the overall abundance (P = 0.05) or proportion (P = 0.7) of An. balabacensis. The estimated diversity of Anopheles species was marginally higher in electrocuting net than HLC collections, and similar in collections made with humans or monkey hosts.
CONCLUSIONS: Host-baited electrocuting nets had moderate success for sampling known zoonotic malaria vectors. The primary vector An. balabacensis was collected with electrocuting nets baited both with humans and macaques, but at a considerably lower density than the HLC standard. However, electrocuting nets were considerably more successful than monkey-baited traps and representatively characterised anopheline species diversity. Consequently, their use allows inferences about relative mosquito attraction to be meaningfully interpreted while eliminating confounding factors due to trapping method. On this basis, electrocuting net traps should be considered as a useful standardised method for investigating vector contact with humans and wildlife reservoirs.
METHODS: In this article, we propose a new method based on simultaneous EEG-fMRI data and machine learning approach to classify the visual brain activity patterns. We acquired EEG-fMRI data simultaneously on the ten healthy human participants by showing them visual stimuli. Data fusion approach is used to merge EEG and fMRI data. Machine learning classifier is used for the classification purposes.
RESULTS: Results showed that superior classification performance has been achieved with simultaneous EEG-fMRI data as compared to the EEG and fMRI data standalone. This shows that multimodal approach improved the classification accuracy results as compared with other approaches reported in the literature.
CONCLUSIONS: The proposed simultaneous EEG-fMRI approach for classifying the brain activity patterns can be helpful to predict or fully decode the brain activity patterns.
METHODS: We reviewed 22 previous studies that (1) empirically manipulated social support in a stressful situation, (2) measured CVR, and (3) tested a moderator of social support effects on CVR.
RESULTS: Although a majority of studies reported a CVR-mitigating effect of social support resulting in an overall significant combined p-value, we found that there were different effects of social support on CVR when we considered high- and low-engagement contexts. That is, compared to control conditions, social support lowered CVR in more engaging situations but had no significant effect on CVR in less engaging situations.
CONCLUSION: Our results suggest that a dual-effect model of social support effects on CVR may better capture the nature of social support, CVR, and health associations than the buffering hypothesis and emphasize a need to better understand the health implications of physiological reactivity in various contexts. Statement of contribution What is already known on this subject? According to the stress-buffering hypothesis (Cohen & McKay, ), one pathway social support benefits health is through mitigating the physiological arousal caused by stress. However, previous studies that examined the effects of social support on blood pressure and heart rate changes were not consistently supporting the hypothesis. Some studies reported that social support causes elevations in cardiovascular reactivity (CVR) to stress (Anthony & O'Brien, ; Hilmert, Christenfeld, & Kulik, ; Hilmert, Kulik, & Christenfeld, ) and others showed no effect of social support on CVR (Christian & Stoney, ; Craig & Deichert, ; Gallo, Smith, & Kircher, ). What does this study add? When participants were in more engaging conditions, social support decreased CVR relative to no support. When participants were in less engaging conditions, social support did not have a significant effect on CVR. Provide an alternative way to explain the ways social support affects cardiac health.
METHODS: This is a cross-sectional study on 9553 adolescents (aged 12-15 years) from 8 Asian metropolitan cities (Tokyo, Hong Kong, Shanghai, Taipei, Bangkok, Kuala Lumpur, Seoul, and Singapore). Cardiorespiratory fitness was assessed by using a 15-m progressive aerobic capacity endurance run (PACER) test. The time spent on MVPA and watching television was assessed using the International Physical Activity Questionnaire-Short Form.
RESULTS: MVPA was more closely associated with the PACER score than the duration of watching television. Compared with the reference group (i.e. those with the lowest levels of MVPA [