The normalized microwave reflection index (NMRI) is a measure of multipath scattering calculated daily from continuously operating GPS sites. GPS satellites transmit L-band microwave signals, and thus NMRI is sensitive to the amount of water in vegetation, not plant greenness or dry biomass. The sensing footprint is approximately 1000 m ², although reflections from a distance of hundreds of metres are important at some sites. NMRI exhibits clear seasonal variations that are linked to the changes in vegetation water content that accompany plant growth and senescence. In this paper, NMRI and the normalized difference vegetation index (NDVI) are compared for the period 2008–2012. NMRI data are derived from 184 GPS sites in the western USA. NDVI data are from the 250 m, 16-day pixel containing each GPS station. Amplitude of the annual growth cycle and correlation between NMRI and NDVI are estimated, with and without lags. Phenology metrics are calculated from both indices (i.e. the start of the growing season, timing of peak growth, and season length). NMRI and NDVI are correlated at most sites, but the degree of correlation varies regionally. Correlation is lowest in California and coastal regions (R = 0.25), where NDVI increases earlier in the spring than NMRI. It is highest for mountain and prairie sites (R = 0.66 and 0.73, respectively). Allowing for a lag between NMRI and NDVI greatly increases the correlation. The lag that yields the greatest correlation is nearly 30 days for the California sites (R = 0.71 with lag), but only 10 days for mountain and prairie sites (R = 0.78 and 0.85 with lag). There are clear differences in phenology metrics extracted from NMRI and NDVI that are consistent with the correlation-lag analysis. Using NMRI, there is a later start to the season, later peak day of the year, and shorter season length. The greatest differences are in California where NDVI start of the season is nearly 60 days earlier than that calculated from NMRI. These data suggest that green-up precedes increases in vegetation water content, with the duration of offset varying regionally. This study is the first to compare GPS-derived microwave reflectance data with NDVI at multiple sites, and highlights both opportunities and limitations offered by NMRI data.

The molecular structures of four silylbenzenes (benzenes with H₃Si-substituents), viz. silylbenzene, 1,2-, 1,3- and 1,4-disilylbenzene, were studied by electron diffraction in the gas phase and by ab initio calculations. The structures of 1,2- and 1,4-disilylbenzene were also determined by X-ray diffraction experiments on single crystals grown in situ. The results are compared and discussed with the focus on the evaluation of the SARACEN method for the analysis of gas-phase data, and particularly on its ability to deal with small structural distortions. Important experimental structural parameters are the Si-C bond lengths [Å] and the ipso C-C-C angles [deg], which are 1.863(3) / 118.2(2) for gaseous silylbenzene (rα), 1.875(2) / 119.9(2) for gaseous and 1.870(2) / 118.7(av) for solid 1,2-disilylbenzene, 1.871(1) / 119.4(3) for gaseous 1,3-disilylbenzene, 1.870(2) / 119.0(2) for gaseous and 1.866(3) / 117.4(2) for solid 1,4-disilylbenzene. The angle distortions in the benzene ring geometries are analysed and interpreted in terms of an additivity rule of the distortion caused by each of the silyl substituents. This additivity scheme predicts excellently the observed structures of the silylbenzenes and is in best agreement with the structures calculated ab initio. The slight distortion of molecular symmetry in the crystal structures makes a detailed comparison of the solid-state values impossible, but on average they are in good agreement with theory and predictions of the additivity model. The gas-phase values obtained by the SARACEN method show less pronounced distortions of the benzene ring geometries than observed or predicted by the other methods, but the trends of distortion are fully consistent.

The possibility of moisture, as an active substance for lipid oxidation, was determined in linoleic acid model systems containing deuterium oxide (D2O) and deuterium free H2O, by measuring the headspace oxygen content and headspace volatiles. Mixtures of D2O and H2O, at the ratio of 3:0, 2:1, 1:2, and 0:3 (w/w), were added to linoleic acid and oxidised at 60°C. The existence of deuterium in headspace volatiles, was indirectly determined by comparing the amount of fragmented mass to charge ratio (m/z), which was 73.1/72.1 for d1-pentane/pentane, 57.0/56.0 for d1-2-propenal/2-propenal, 101.1/100.1 for d1-hexanal/hexanal, 113.1/112.1 for d1-t-2-heptenal-D/t-2-heptenal, and 153.2/152.2 for d1-2,4-decadieanl/2,4-decadieanl. As the oxidation time increased to 12h, the ratio of 73.1/72.1 (m/z) for pentane and 57.0/56.0 for 2-propenal increased significantly with a concentration dependent manner of deuterium oxide, which implies water was incorporated as a substrate during volatile formation. However, hexanal, t-2-heptenal, and 2,4-decadieanl did not follow the patterns of pentane and 2-propenal, implying that the formation mechanisms of these volatiles may not share the same pathways with pentane and 2-propenal. This study showed that moisture participates for the formation of volatiles and moisture may act as a substrate for lipid oxidation.

Gut methanogenic archaea of monogastric animals are considered to be related to energy metabolism and adipose deposition of the host; however, information on their development in young piglets is limited. Thus, to investigate early methanogenic colonisation in the faeces of Meishan and Yorkshire piglets, faecal samples were collected from piglets at 1, 3, 7, and 14 days after birth and used to analyse the methanogenic community with 16S rRNA gene pyrosequencing. Results showed that the diversity of the methanogenic community in the faeces of neonatal piglets decreased from one to 14 days of age, as the total methanogen populations increased. The age of piglets, but not the breed, significantly affected the diversity of the methanogenic community which was dominated by the genus Methanobrevibacter. From the ages of one to 14 days, the abundance of M. smithii-related operational taxonomic units (OTUs) increased significantly, while the abundances of M. thaueri- and M. millerae-related OTUs decreased significantly. The substitution of M. smithii for M. thaueri/M. millerae was faster in Yorkshire piglets than in Meishan piglets. These results suggest that the early establishment of microbiota in neonatal piglets is accompanied by dramatic changes in the methanogenic community, and that the changes vary among pigs of different genotypes.

2014

BACKGROUND: Self-reported and objectively-determined neighborhood built characteristics are associated with physical activity, yet little is known about their combined influence on walking. This study: 1) compared self-reported measures of the neighborhood built environment between objectively-determined low, medium, and high walkable neighborhoods; 2) estimated the relative associations between self-reported and objectively-determined neighborhood characteristics and walking and; 3) examined the extent to which the objectively-determined built environment moderates the association between self-reported measures of the neighborhood built environment and walking. METHODS: A random cross-section of 1875 Canadian adults completed a telephone-interview and postal questionnaire capturing neighborhood walkability, neighborhood-based walking, socio-demographic characteristics, walking attitudes, and residential self-selection. Walkability of each respondent’s neighborhood was objectively-determined (low [LW], medium [MW], and high walkable [HW]). Covariate-adjusted regression models estimated the associations between weekly participation and duration in transportation and recreational walking and self-reported and objectively-determined walkability. RESULTS: Compared with objectively-determined LW neighborhoods, respondents in HW neighborhoods positively perceived access to services, street connectivity, pedestrian infrastructure, and utilitarian and recreation destination mix, but negatively perceived motor vehicle traffic and crime related safety. Compared with residents of objectively-determined LW neighborhoods, residents of HW neighborhoods were more likely (p < .05) to participate in (odds ratio [OR] = 3.06), and spend more time, per week (193 min/wk) transportation walking. Perceived access to services, street connectivity, motor vehicle safety, and mix of recreational destinations were also significantly associated with transportation walking. With regard to interactions, HW x utilitarian destination mix was positively associated with participation, HW x physical barriers and MW x pedestrian infrastructure were positively associated with minutes, and HW x safety from crime was negatively associated with minutes, of transportation walking. Neither neighborhood type nor its interactions with perceived measures of walkability were associated with recreational walking, although perceived aesthetics was associated with participation (OR = 1.18, p < .05). CONCLUSIONS: Objectively-determined and self-reported built characteristics are associated with neighborhood-based transportation walking. The objectively-determined built environment might moderate associations between perceptions of walkability and neighborhood-based transportation walking. Interventions that target perceptions in addition to modifications to the neighborhood built environment could result in increases in physical activity among adults.

We evaluated genetic diversity and structure of Echinococcus granulosus by analyzing the complete mitochondrial NADH dehydrogenase subunit 2 (ND2) gene in 51 isolates of E. granulosus sensu stricto metacestodes collected at three locations in this region. We detected 19 haplotypes, which formed a distinct clade with the standard sheep strain (G1). Hence, all 51 isolates were identified as E. granulosus sensu stricto (G1–G3). Genetic relationships among haplotypes were not associated with geographical divisions, and fixation indices (Fst) among sampling localities were low. Hence, regional populations of E. granulosus in the southwest China are not differentiated, as gene flow among them remains high. This information is important for formulating unified region-wide prevention and control measures. We found large negative Fu’s Fs and Tajima’s D values and a unimodal mismatch distribution, indicating that the population has undergone a demographic expansion. We observed high genetic diversity among the E. granulosus s. s. isolates, indicating that the parasite population in this important bioregion is genetically robust and likely to survive and spread. The data from this study will prove valuable for future studies focusing on improving diagnosis and prevention methods and developing robust control strategies.

PURPOSE: Hydrosedimentological modeling is a tool that can be used to understand better important processes occurring at the catchment scale, such as runoff and sediment yield. The aim of this study was to use the Limburg Soil Erosion Model (LISEM) to describe the runoff and sediment yield during rainfall–runoff events in a small rural catchment in southern Brazil. MATERIALS AND METHODS: The study was conducted in the Lajeado Ferreira Creek catchment (drainage area of 1.19 km²) where intense land use has caused a negative impact on water resources. Thirteen rainfall–runoff events that occurred in 2010 and 2011, including high-magnitude events, were used to model hydrosedimentological processes. RESULTS AND DISCUSSION: RESULTS: from the calibration and validation stages indicate that the model had a good performance when representing the hydrograph, including events with greater complexity. The use of a second soil layer in the model increased its efficiency, which is in accordance with the importance of subsurface flow in this catchment and its sensitivity to the physical properties of the soil, which are essential for controlling hydrosedimentological processes at the catchment scale. The simulation of sediment yield was overestimated by the model, constrained by the lack of sensitivity of the model to soil cohesion and the stability of soil aggregates. During the model calibration stage, these parameters had values different from those measured in the field. CONCLUSIONS: The LISEM model performed well in representing runoff for events of different magnitudes. The discretization of the physical–hydrologic properties in the soil profile enabled the evaluation of the effect of subsurface impediment layers on water infiltration and runoff. The simulation was less accurate for suspended sediment concentration than for runoff. This indicates the need for further studies to either identify other factors controlling erosion and sediment yield that have not been identified by the model, or identify if the representation of the physical parameters is inadequate, especially the values of soil cohesion and aggregate stability.