Collection of excitation-emission-matrix fluorescence of aerosol-candidate-substances and its application to fluorescence lidar monitoring.

Fluorescence lidars have the potential to identify aerosols, but it seems that the basic data of the fluorescence spectrum of various aerosols appear to be inadequate for practical use in application of fluorescence lidar monitoring. We collected the fluorescence spectrum data of 61 powders with different substances as pseudo-aerosols and organized them as EEM (Excitation-Emission-Matrix) fluorescence data. Our interest was also in the artificial substances that are discarded around our surroundings and become aerosols. Four applications of the EEM fluorescence to fluorescence lidars were discussed; designing fluorescence lidars, reconstructing aerosol fluorescence spectrums measured by fluorescence lidar, searching for new substances for fluorescence lidar measurement, and developing a database of EEM fluorescence for identifying aerosol types measured by fluorescence lidar. All EEM fluorescence data and application software were stored in one USB memory and run in the BIOS (Basic Input/Output System) independent of a computer OS (Operating System) for ease of use. Aerosol identification software worked well in general, but we have also talked a bit about improvements.

A novel telerehabilitation with an educational program for caregivers using telelecture is feasible for fall prevention in elderly people: A case series.

BACKGROUND: The importance of fall prevention rehabilitations has been well recognized. Recently telerehabilitation was developed, however, there have been no reports on telerehabilitation with direct support from specialists for fall prevention among the elderly. We herein reported telerehabilitation by caregivers educated by our novel educational program. METHODS: Caregivers were educated with our educational program using a telelecture system and supported telerehabilitation following instructions from rehabilitation specialists in our university using the telemedicine system every two to four weeks for three months. Caregivers were assessed with our original questionnaire before and after the telelecture. Participants were assessed by the Berg Balance Scale (BBS), Timed Up & Go test (TUG test), Hand-held dynamometer (HHD) and Mini-Mental State Examination (MMSE) before and after telerehabilitation. Wilcoxon's signed-rank test was used for the statistical analyses. A value of P<.05 was considered statistically significant. RESULTS: Nine elderly people were enrolled. The mean age was 84.7 (78-90) years old and the sex ratio was 1:8 (males:females). The average number of telerehabilitation sessions was 4.7. The average score of nineteen caregivers before the lecture was 15.3, while that after the lecture was 18.3. Caregivers' understanding was significantly increased after the telelecture (P<.001). No adverse events occurred during the study period. The median values of the BBSs, TUG test, right and left HHD and MMSE before and after 3 months' telerehabilitation were 43 (95% confidence interval [CI]: 40.10, 49.01) and 49 (95% CI: 41.75, 50.91), 17.89 (95% CI: 15.51, 23.66) and 18.53 (95% CI: 14.56, 25.67), 7.95 (95% CI: 4.38, 10.14) and 11.55 (95% CI: 7.06, 13.55), 9.85 (95% CI: 6.79, 12.59) and 13.20 (95% CI: 7.96, 14.42), and 19 (95% CI: 12.34, 21.66) and 16 (95% CI: 10.81, 21.00), respectively. Although approximately half of the participants showed improvement in the BBS, TUG test, right and left HHD and MMSE, no significant changes were observed (P=.7239, P=.3446, P=.1023, P=.3538 and P=.8253, respectively). CONCLUSIONS: Our telerehabilitation program exhibited significant effects in elderly people and improved the degree of understanding concerning rehabilitation among caregivers in facilities for elderly people.

Dynamics of different bacterial communities are capable of generating sustainable electricity from microbial fuel cells with organic waste.

The relationship between the bacterial communities in anolyte and anode biofilms and the electrochemical properties of microbial fuel cells (MFCs) was investigated when a complex organic waste-decomposing solution was continuously supplied to MFCs as an electron donor. The current density increased gradually and was maintained at approximately 100 to 150 mA m(-2). Polarization curve analyses revealed that the maximum power density was 7.4 W m(-3) with an internal resistance of 110 Ω. Bacterial community structures in the organic waste-decomposing solution and MFCs differed from each other. Clonal analyses targeting 16S rRNA genes indicated that bacterial communities in the biofilms on MFCs developed to specific communities dominated by novel Geobacter. Multidimensional scaling analyses based on DGGE profiles revealed that bacterial communities in the organic waste-decomposing solution fluctuated and had no dynamic equilibrium. Bacterial communities on the anolyte in MFCs had a dynamic equilibrium with fluctuations, while those of the biofilm converged to the Geobacter-dominated structure. These bacterial community dynamics of MFCs differed from those of control-MFCs under open circuit conditions. These results suggested that bacterial communities in the anolyte and biofilm have a gentle symbiotic system through electron flow, which resulted in the advance of current density from complex organic waste.