Normality mining: privacy implications of behavioral profiles drawn from GPS enabled mobile phones

There is growing interest in the ways in which the location of a person can be utilized by new applications and services. Recent advances in mobile technologies have meant that the technical capability to record and transmit location data for processing is appearing in off-the-shelf handsets. This opens possibilities to profile people based on the places they visit, people they associate with, or other aspects of their complex routines determined through persistent tracking. It is possible that services offering customized information based on the results of such behavioral profiling could become commonplace. However, it may not be immediately apparent to the user that a wealth of information about them, potentially unrelated to the service, can be revealed. Further issues occur if the user agreed, while subscribing to the service, for data to be passed to third parties where it may be used to their detriment. Here, we report in detail on a short case study tracking four people, in three European member states, persistently for six weeks using mobile handsets. The GPS locations of these people have been mined to reveal places of interest and to create simple profiles. The information drawn from the profiling activity ranges from intuitive through special cases to insightful. In this paper, these results and further extensions to the technology are considered in light of European legislation to assess the privacy implications of this emerging technology.

A combined engineering and statistical model of UK domestic appliance electrical load profiles

The development of a combined engineering and statistical Artificial Neural Network model of UK domestic appliance load profiles is presented. The model uses diary-style appliance use data and a survey questionnaire collected from 51 suburban households and 46 rural households during the summer of 2010 and2011 respectively. It also incorporates measured energy data and is sensitive to socioeconomic, physical dwelling and temperature variables. A prototype model is constructed in MATLAB using a two layer feed forward network with back propagation training which has a 12:10:24 architecture. Model outputs include appliance load profiles which can be applied to the fields of energy planning (microrenewables and smart grids), building simulation tools and energy policy.

Receptor binding profiles of avian influenza virus hemagglutinin subtypes on human cells as a predictor of pandemic potential

The host adaptation of influenza virus is partly dependent on the sialic acid (SA) isoform bound by the viral hemagglutinin (HA). Avian influenza viruses preferentially bind the α-2,3 SA and human influenza viruses the α-2,6 isoform. Each isoform is predominantly associated with different surface epithelial cell types of the human upper airway. Using recombinant HAs and human tracheal airway epithelial cells in vitro and ex vivo, we show that many avian HA subtypes do not adhere to this canonical view of SA specificity. The propensity of avian viruses to adapt to human receptors may thus be more widespread than previously supposed.

An analytical model of mountain wave drag for wind profiles with shear and curvature

An analytical model is developed to predict the surface drag exerted by internal gravity waves on an isolated axisymmetric mountain over which there is a stratified flow with a velocity profile that varies relatively slowly with height. The model is linear with respect to the perturbations induced by the mountain, and solves the Taylor–Goldstein equation with variable coefficients using a Wentzel–Kramers–Brillouin (WKB) approximation, formally valid for high Richardson numbers, Ri. The WKB solution is extended to a higher order than in previous studies, enabling a rigorous treatment of the effects of shear and curvature of the wind profile on the surface drag. In the hydrostatic approximation, closed formulas for the drag are derived for generic wind profiles, where the relative magnitude of the corrections to the leading-order drag (valid for a constant wind profile) does not depend on the detailed shape of the orography. The drag is found to vary proportionally to Ri21, decreasing as Ri decreases for a wind that varies linearly with height, and increasing as Ri decreases for a wind that rotates with height maintaining its magnitude. In these two cases the surface drag is predicted to be aligned with the surface wind. When one of the wind components varies linearly with height and the other is constant, the surface drag is misaligned with the surface wind, especially for relatively small Ri. All these results are shown to be in fairly good agreement with numerical simulations of mesoscale nonhydrostatic models, for high and even moderate values of Ri.

Non-concordance between genetic profiles of olive oil and fruit: a cautionary note to the use of DNA markers for provenance testing.

To investigate the contribution of paternal alleles to the DNA content of olive oil, genetic analyses of olive DNA samples from fruits, leaves, and oil derived from the same tree (cv. Leccino) were carried out. DNA extracted from maternal tissues--leaves and flesh--from different fruits showed identical genetic profiles using a set of DNA markers. Additional simple sequence repeat (SSR) alleles, not found in the maternal samples, were amplified in the embryos (stone), and they were also detected in DNA extracted from the paste obtained by crushing whole fruits and from the oil pressed from this material. These results demonstrate that the DNA profile obtained from olive oil is likely to represent a composite profile of the maternal alleles juxtaposed with alleles contributed by various pollen donors. Therefore, care needs to be taken in the interpretation of DNA profiles obtained from DNA extracted from oil for resolving provenance and authenticity issues.

Graph-based algorithms for comparison and prediction of household-level energy use profiles

We present an efficient graph-based algorithm for quantifying the similarity of household-level energy use profiles, using a notion of similarity that allows for small time–shifts when comparing profiles. Experimental results on a real smart meter data set demonstrate that in cases of practical interest our technique is far faster than the existing method for computing the same similarity measure. Having a fast algorithm for measuring profile similarity improves the efficiency of tasks such as clustering of customers and cross-validation of forecasting methods using historical data. Furthermore, we apply a generalisation of our algorithm to produce substantially better household-level energy use forecasts from historical smart meter data.

Effect of provenance, plant part and processing on extract profiles from cultivated European Rhodiola rosea L. for medicinal use.

The demand for plant material of Rhodiola rosea L. (Crassulaceae) for medicinal use has increased recently, amid concerns about its quality and sustainability. We have analysed the content of phenylpropanoids (total rosavins) and salidroside in liquid extracts from 3-year old cultivated plants of European origin, and mapped the influence of plant part (rhizome versus root), genotype, drying, cutting, and extraction solvent to chemical composition. Rhizomes contained 1.5-4 times more salidroside (0.3-0.4% dry wt) and total rosavins (1.2-3.0%) than roots. The qualitative decisive phenylpropanoid content in the extracts was most influenced by plant part, solvent, and genotype, while drying temperature and cutting conditions were of less importance. We have shown that R. rosea from different boreal European provenances can be grown under temperate conditions and identified factors to obtain consistent high quality extracts provided that authentic germplasm is used and distinguished between rhizome, roots and their mixtures.

Observations of wind speed profiles over Greater London, UK, using a Doppler lidar

To calculate the potential wind loading on a tall building in an urban area, an accurate representation of the wind speed profile is required. However, due to a lack of observations, wind engineers typically estimate the characteristics of the urban boundary layer by translating the measurements from a nearby reference rural site. This study presents wind speed profile data obtained from a Doppler lidar in central London, UK, during an 8 month observation period. Used in conjunction with wind speed data measured at a nearby airport, the data have been used to assess the accuracy of the predictions made by the wind engineering tools currently available. When applied to multiple changes in surface roughness identified from morphological parameters, the non-equilibrium wind speed profile model developed by Deaves (1981) provides a good representation of the urban wind speed profile. For heights below 500 m, the predicted wind speed remains within the 95% confidence interval of the measured data. However, when the surface roughness is estimated using land use as a proxy, the model tends to overestimate the wind speed, particularly for very high wind speed periods. These results highlight the importance of a detailed assessment of the nature of the surface when estimating the wind speed above an urban surface.

Black carbon vertical profiles strongly affect its radiative forcing uncertainty

The impact of black carbon (BC) aerosols on the global radiation balance is not well constrained. Here twelve global aerosol models are used to show that at least 20% of the present uncertainty in modeled BC direct radiative forcing (RF) is due to diversity in the simulated vertical profile of BC mass. Results are from phases 1 and 2 of the global aerosol model intercomparison project (AeroCom). Additionally, a significant fraction of the variability is shown to come from high altitudes, as, globally, more than 40% of the total BC RF is exerted above 5 km. BC emission regions and areas with transported BC are found to have differing characteristics. These insights into the importance of the vertical profile of BC lead us to suggest that observational studies are needed to better characterize the global distribution of BC, including in the upper troposphere.

Impact of geographical region on urinary metabolomic and plasma fatty acid profiles in subjects with the metabolic syndrome across Europe: the LIPGENE study

The application of metabolomics in multi-centre studies is increasing. The aim of the present study was to assess the effects of geographical location on the metabolic profiles of individuals with the metabolic syndrome. Blood and urine samples were collected from 219 adults from seven European centres participating in the LIPGENE project (Diet, genomics and the metabolic syndrome: an integrated nutrition, agro-food, social and economic analysis). Nutrient intakes, BMI, waist:hip ratio, blood pressure, and plasma glucose, insulin and blood lipid levels were assessed. Plasma fatty acid levels and urine were assessed using a metabolomic technique. The separation of three European geographical groups (NW, northwest; NE, northeast; SW, southwest) was identified using partial least-squares discriminant analysis models for urine (R 2 X: 0•33, Q 2: 0•39) and plasma fatty acid (R 2 X: 0•32, Q 2: 0•60) data. The NW group was characterised by higher levels of urinary hippurate and N-methylnicotinate. The NE group was characterised by higher levels of urinary creatine and citrate and plasma EPA (20 : 5 n-3). The SW group was characterised by higher levels of urinary trimethylamine oxide and lower levels of plasma EPA. The indicators of metabolic health appeared to be consistent across the groups. The SW group had higher intakes of total fat and MUFA compared with both the NW and NE groups (P≤ 0•001). The NE group had higher intakes of fibre and n-3 and n-6 fatty acids compared with both the NW and SW groups (all P< 0•001). It is likely that differences in dietary intakes contributed to the separation of the three groups. Evaluation of geographical factors including diet should be considered in the interpretation of metabolomic data from multi-centre studies.

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.

Predicting fatty acid profiles in blood based on food intake and the FADS1 rs174546 SNP

SCOPE: A high intake of n-3 PUFA provides health benefits via changes in the n-6/n-3 ratio in blood. In addition to such dietary PUFAs, variants in the fatty acid desaturase 1 (FADS1) gene are also associated with altered PUFA profiles. METHODS AND RESULTS: We used mathematical modelling to predict levels of PUFA in whole blood, based on MHT and bolasso selected food items, anthropometric and lifestyle factors, and the rs174546 genotypes in FADS1 from 1,607 participants (Food4Me Study). The models were developed using data from the first reported time point (training set) and their predictive power was evaluated using data from the last reported time point (test set). Amongst other food items, fish, pizza, chicken and cereals were identified as being associated with the PUFA profiles. Using these food items and the rs174546 genotypes as predictors, models explained 26% to 43% of the variability in PUFA concentrations in the training set and 22% to 33% in the test set. CONCLUSIONS: Selecting food items using MHT is a valuable contribution to determine predictors, as our models' predictive power is higher compared to analogue studies. As unique feature, we additionally confirmed our models' power based on a test set.