On the universal TRO of a JC*-triple, ideals and tensor products

In a development from material introduced in recent work, we discuss the interconnections between ternary rings of operators (TROs) and right C*-algebras generated by JC*-triples, deducing that every JC*-triple possesses a largest universally reversible ideal, that the universal TRO commutes with appropriate tensor products and establishing a reversibility criterion for type I JW*-triples.

Multiscale geostatistical analysis of AVHRR, SPOT-VGT, and MODIS global NDVI products

Global NDVI data are routinely derived from the AVHRR, SPOT-VGT, and MODIS/Terra earth observation records for a range of applications from terrestrial vegetation monitoring to climate change modeling. This has led to a substantial interest in the harmonization of multisensor records. Most evaluations of the internal consistency and continuity of global multisensor NDVI products have focused on time-series harmonization in the spectral domain, often neglecting the spatial domain. We fill this void by applying variogram modeling (a) to evaluate the differences in spatial variability between 8-km AVHRR, 1-km SPOT-VGT, and 1-km, 500-m, and 250-m MODIS NDVI products over eight EOS (Earth Observing System) validation sites, and (b) to characterize the decay of spatial variability as a function of pixel size (i.e. data regularization) for spatially aggregated Landsat ETM+ NDVI products and a real multisensor dataset. First, we demonstrate that the conjunctive analysis of two variogram properties – the sill and the mean length scale metric – provides a robust assessment of the differences in spatial variability between multiscale NDVI products that are due to spatial (nominal pixel size, point spread function, and view angle) and non-spatial (sensor calibration, cloud clearing, atmospheric corrections, and length of multi-day compositing period) factors. Next, we show that as the nominal pixel size increases, the decay of spatial information content follows a logarithmic relationship with stronger fit value for the spatially aggregated NDVI products (R2 = 0.9321) than for the native-resolution AVHRR, SPOT-VGT, and MODIS NDVI products (R2 = 0.5064). This relationship serves as a reference for evaluation of the differences in spatial variability and length scales in multiscale datasets at native or aggregated spatial resolutions. The outcomes of this study suggest that multisensor NDVI records cannot be integrated into a long-term data record without proper consideration of all factors affecting their spatial consistency. Hence, we propose an approach for selecting the spatial resolution, at which differences in spatial variability between NDVI products from multiple sensors are minimized. This approach provides practical guidance for the harmonization of long-term multisensor datasets.

Combined use of satellite estimates and rain gauge observations to generate high-quality historical rainfall time series over Ethiopia

Climate data are used in a number of applications including climate risk management and adaptation to climate change. However, the availability of climate data, particularly throughout rural Africa, is very limited. Available weather stations are unevenly distributed and mainly located along main roads in cities and towns. This imposes severe limitations to the availability of climate information and services for the rural community where, arguably, these services are needed most. Weather station data also suffer from gaps in the time series. Satellite proxies, particularly satellite rainfall estimate, have been used as alternatives because of their availability even over remote parts of the world. However, satellite rainfall estimates also suffer from a number of critical shortcomings that include heterogeneous time series, short time period of observation, and poor accuracy particularly at higher temporal and spatial resolutions. An attempt is made here to alleviate these problems by combining station measurements with the complete spatial coverage of satellite rainfall estimates. Rain gauge observations are merged with a locally calibrated version of the TAMSAT satellite rainfall estimates to produce over 30-years (1983-todate) of rainfall estimates over Ethiopia at a spatial resolution of 10 km and a ten-daily time scale. This involves quality control of rain gauge data, generating locally calibrated version of the TAMSAT rainfall estimates, and combining these with rain gauge observations from national station network. The infrared-only satellite rainfall estimates produced using a relatively simple TAMSAT algorithm performed as good as or even better than other satellite rainfall products that use passive microwave inputs and more sophisticated algorithms. There is no substantial difference between the gridded-gauge and combined gauge-satellite products over the test area in Ethiopia having a dense station network; however, the combined product exhibits better quality over parts of the country where stations are sparsely distributed.

Sensory profiles and consumer acceptability of a range of sugar-reduced products on the UK market

Current UK intake of non-milk extrinsic sugars (NMES) is above recommendations. Reducing the sugar content of processed high sugar foods through reformulation is one option for reducing consumption of NMES at a population level. However, reformulation can alter the sensory attributes of food products and influence consumer liking. This study evaluated consumer acceptance of a selection of products that are commercially-available in the UK; these included regular and sugar-reduced baked beans, strawberry jam, milk chocolate, cola and cranberry & raspberry juice. Sweeteners were present in the reformulated chocolate (maltitol), cola (aspartame and acesulfame-K) and juice (sucralose) samples. Healthy, non-smoking consumers (n = 116; 55 men, 61 women, age: 33 ± 9 years; BMI: 25.7 ± 4.6 kg/m2) rated the products for overall liking and on liking of appearance, flavor and texture using a nine-point hedonic scale. There were significant differences between standard and reduced sugar products in consumers’ overall liking and on liking of each modality (appearance, flavor and texture; all P < 0.0001). For overall liking, only the regular beans and cola were significantly more liked than their reformulated counterparts (P < 0.0001). Cluster analysis identified three consumer clusters that were representative of different patterns of consumer liking. For the largest cluster (cluster 3: 45%), there was a significant difference in mean liking scores across all products, except jam. Differences in liking were predominantly driven by sweet taste in 2 out of 3 clusters. The current research has demonstrated that a high proportion of consumers prefer conventional products over sugar-reduced products across a wide range of product types (45%) or across selected products (27%), when tasted unbranded, and so there is room for further optimization of commercial reduced sugar products that were evaluated in the current study. Future work should evaluate strategies to facilitate compliance to dietary recommendations on NMES and free sugars, such as the impact of sugar-reduced food exposure on their acceptance.