Understanding consumer evaluations of personalised nutrition services in terms of the privacy calculus: a qualitative study

Background: Personalised nutrition (PN) may provide major health benefits to consumers. A potential barrier to the uptake of PN is consumers’ reluctance to disclose sensitive information upon which PN is based. This study adopts the privacy calculus to explore how PN service attributes contribute to consumers’ privacy risk and personalisation benefit perceptions. Methods: Sixteen focus groups (n = 124) were held in 8 EU countries and discussed 9 PN services that differed in terms of personal information, communication channel, service provider, advice justification, scope, frequency, and customer lock-in. Transcripts were content analysed. Results: The personal information that underpinned PN contributed to both privacy risk perception and personalisation benefit perception. Disclosing information face-to-face mitigated the perception of privacy risk and amplified the perception of personalisation benefit. PN provided by a qualified expert and justified by scientific evidence increased participants’ value perception. Enhancing convenience, offering regular face-to face support, and employing customer lock-in strategies were perceived as beneficial. Conclusion: This study suggests that to encourage consumer adoption, PN has to account for face-to-face communication, expert advice providers, support, a lifestyle-change focus, and customised offers. The results provide an initial insight into service attributes that influence consumer adoption of PN.

The role of index trading in price formation in the grains and oilseeds markets

We use both Granger-causality and instrumental variables (IV) methods to examine the impact of index fund positions on price returns for the main US grains and oilseed futures markets. Our analysis supports earlier conclusions that Granger-causal impacts are generally not discernible. However, market microstructure theory suggests trading impacts should be instantaneous. IV-based tests for contemporaneous causality provide stronger evidence of price impact. We find even stronger evidence that changes in index positions can help predict future changes in aggregate commodity price indices. This result suggests that changes in index investment are in part driven by information which predicts commodity price changes over the coming months.

A psychometric analysis of reliability and validity of the index of learning styles (ILS)

Prior literature showed that Felder and Silverman learning styles model (FSLSM) was widely adopted to cater to individual styles of learners whether in traditional or Technology Enhanced Learning (TEL). In order to infer this model, the Index of Learning Styles (ILS) instrument was proposed. This research aims to analyse the soundness of this instrument in an Arabic sample. Data were integrated from different courses and years. A total of 259 engineering students participated voluntarily in the study. The reliability was analysed by applying internal construct reliability, inter-scale correlation, and total item correlation. The construct validity was also considered by running factor analysis. The overall results indicated that the reliability and validity of perception and input dimensions were moderately supported, whereas processing and understanding dimensions showed low internal-construct consistency and their items were weakly loaded in the associated constructs. Generally, the instrument needs further effort to improve its soundness. However, considering the consistency of the produced results of engineering students irrespective of cross-cultural differences, it can be adopted to diagnose learning styles.

Soil quality assessment based on carbon stratification index in different olive grove management practices in Mediterranean areas

In Mediterranean areas, conventional tillage increases soil organic matter losses, reduces soil quality, and contributes to climate change due to increased CO2 emissions. CO2 sequestration rates in soil may be enhanced by appropriate agricultural soil management and increasing soil organic matter content. This study analyzes the stratification ratio (SR) index of soil organic carbon (SOC), nitrogen (N) and C:N ratio under different management practices in an olive grove (OG) in Mediterranean areas (Andalusia, southern Spain). Management practices considered in this study are conventional tillage (CT) and no tillage (NT). In the first case, CT treatments included addition of alperujo (A) and olive leaves (L). A control plot with no addition of olive mill waste was considered (CP). In the second case, NT treatments included addition of chipped pruned branches (NT1) and chipped pruned branches and weeds (NT2). The SRs of SOC increased with depth for all treatments. The SR of SOC was always higher in NT compared to CT treatments, with the highest SR of SOC observed under NT2. The SR of N increased with depth in all cases, ranging between 0.89 (L-SR1) and 39.11 (L-SR3 and L-SR4).The SR of C:N ratio was characterized by low values, ranging from 0.08 (L-SR3) to 1.58 (NT1-SR2) and generally showing higher values in SR1 and SR2 compared to those obtained in SR3 and SR4. This study has evaluated several limitations to the SR index such as the fact that it is descriptive but does not analyze the behavior of the variable over time. In addition, basing the assessment of soil quality on a single variable could lead to an oversimplification of the assessment. Some of these limitations were experienced in the assessment of L, where SR1 of SOC was the lowest of the studied soils. In this case, the higher content in the second depth interval compared to the first was caused by the intrinsic characteristics of this soil's formation process rather than by degradation. Despite the limitations obtained SRs demonstrate that NT with the addition of organic material improves soil quality.

The atomic structure of low-index surfaces of the intermetallic compound InPd

The intermetallic compound InPd (CsCl type of crystal structure with a broad compositional range) is considered as a candidate catalyst for the steam reforming of methanol. Single crystals of this phase have been grown to study the structure of its three low-index surfaces under ultra-high vacuum conditions, using low energy electron diffraction (LEED), X-ray photoemission spectroscopy (XPS), and scanning tunneling microscopy (STM). During surface preparation, preferential sputtering leads to a depletion of In within the top few layers for all three surfaces. The near-surface regions remain slightly Pd-rich until annealing to ∼580 K. A transition occurs between 580 and 660 K where In segregates towards the surface and the near-surface regions become slightly In-rich above ∼660 K. This transition is accompanied by a sharpening of LEED patterns and formation of flat step-terrace morphology, as observed by STM. Several superstructures have been identified for the different surfaces associated with this process. Annealing to higher temperatures (≥750 K) leads to faceting via thermal etching as shown for the (110) surface, with a bulk In composition close to the In-rich limit of the existence domain of the cubic phase. The Pd-rich InPd(111) is found to be consistent with a Pd-terminated bulk truncation model as shown by dynamical LEED analysis while, after annealing at higher temperature, the In-rich InPd(111) is consistent with an In-terminated bulk truncation, in agreement with density functional theory (DFT) calculations of the relative surface energies. More complex surface structures are observed for the (100) surface. Additionally, individual grains of a polycrystalline sample are characterized by micro-spot XPS and LEED as well as low-energy electron microscopy. Results from both individual grains and “global” measurements are interpreted based on comparison to our single crystals findings, DFT calculations and previous literature.

Specific leaf area and leaf area index in developing stands of Fagus sylvatica L. and Picea abies Karst

European beech (Fagus sylvatica L.) and Norway spruce (Picea abies Karst.) are two of the most ecologically and economically important forest tree species in Europe. These two species co-occur in many locations in Europe, leading to direct competition for canopy space. Foliage characteristics of two naturally regenerated pure stands of beech and spruce with fully closed canopies were contrasted to assess the dynamic relationship between foliage adaptability to shading, stand LAI and tree growth. We found that individual leaf size is far more conservative in spruce than in beech. Individual leaf and needle area was larger at the top than at the bottom of the canopy in both species. Inverse relationship was found for specific leaf area (SLA), highest SLA values were found at lowest light availability under the canopy. There was no difference in leaf area index (LAI) between the two stands, however LAI increased from 10.8 to 14.6 m2m-2 between 2009 and 2011. Dominant trees of both species were more efficient in converting foliage mass or area to produce stem biomass, although this relationship changed with age and was species-specific. Overall, we found larger foliage plasticity in beech than in spruce in relation to light conditions, indicating larger capacity to exploit niche openings.

A regionally informed abundance index for supporting integrative analyses across butterfly monitoring schemes

1. The rapid expansion of systematic monitoring schemes necessitates robust methods to reliably assess species' status and trends. Insect monitoring poses a challenge where there are strong seasonal patterns, requiring repeated counts to reliably assess abundance. Butterfly monitoring schemes (BMSs) operate in an increasing number of countries with broadly the same methodology, yet they differ in their observation frequency and in the methods used to compute annual abundance indices. 2. Using simulated and observed data, we performed an extensive comparison of two approaches used to derive abundance indices from count data collected via BMS, under a range of sampling frequencies. Linear interpolation is most commonly used to estimate abundance indices from seasonal count series. A second method, hereafter the regional generalized additive model (GAM), fits a GAM to repeated counts within sites across a climatic region. For the two methods, we estimated bias in abundance indices and the statistical power for detecting trends, given different proportions of missing counts. We also compared the accuracy of trend estimates using systematically degraded observed counts of the Gatekeeper Pyronia tithonus (Linnaeus 1767). 3. The regional GAM method generally outperforms the linear interpolation method. When the proportion of missing counts increased beyond 50%, indices derived via the linear interpolation method showed substantially higher estimation error as well as clear biases, in comparison to the regional GAM method. The regional GAM method also showed higher power to detect trends when the proportion of missing counts was substantial. 4. Synthesis and applications. Monitoring offers invaluable data to support conservation policy and management, but requires robust analysis approaches and guidance for new and expanding schemes. Based on our findings, we recommend the regional generalized additive model approach when conducting integrative analyses across schemes, or when analysing scheme data with reduced sampling efforts. This method enables existing schemes to be expanded or new schemes to be developed with reduced within-year sampling frequency, as well as affording options to adapt protocols to more efficiently assess species status and trends across large geographical scales.

Exploiting satellite-based rainfall for weather index insurance: the challenges of spatial and temporal aggregation

Lack of access to insurance exacerbates the impact of climate variability on smallholder famers in Africa. Unlike traditional insurance, which compensates proven agricultural losses, weather index insurance (WII) pays out in the event that a weather index is breached. In principle, WII could be provided to farmers throughout Africa. There are two data-related hurdles to this. First, most farmers do not live close enough to a rain gauge with sufficiently long record of observations. Second, mismatches between weather indices and yield may expose farmers to uncompensated losses, and insurers to unfair payouts – a phenomenon known as basis risk. In essence, basis risk results from complexities in the progression from meteorological drought (rainfall deficit) to agricultural drought (low soil moisture). In this study, we use a land-surface model to describe the transition from meteorological to agricultural drought. We demonstrate that spatial and temporal aggregation of rainfall results in a clearer link with soil moisture, and hence a reduction in basis risk. We then use an advanced statistical method to show how optimal aggregation of satellite-based rainfall estimates can reduce basis risk, enabling remotely sensed data to be utilized robustly for WII.

Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19·2 million participants

Background Underweight and severe and morbid obesity are associated with highly elevated risks of adverse health outcomes. We estimated trends in mean body-mass index (BMI), which characterises its population distribution, and in the prevalences of a complete set of BMI categories for adults in all countries. Methods We analysed, with use of a consistent protocol, population-based studies that had measured height and weight in adults aged 18 years and older. We applied a Bayesian hierarchical model to these data to estimate trends from 1975 to 2014 in mean BMI and in the prevalences of BMI categories (<18·5 kg/m2 [underweight], 18·5 kg/m2 to <20 kg/m2, 20 kg/m2 to <25 kg/m2, 25 kg/m2 to <30 kg/m2, 30 kg/m2 to <35 kg/m2, 35 kg/m2 to <40 kg/m2, ≥40 kg/m2 [morbid obesity]), by sex in 200 countries and territories, organised in 21 regions. We calculated the posterior probability of meeting the target of halting by 2025 the rise in obesity at its 2010 levels, if post-2000 trends continue. Findings We used 1698 population-based data sources, with more than 19·2 million adult participants (9·9 million men and 9·3 million women) in 186 of 200 countries for which estimates were made. Global age-standardised mean BMI increased from 21·7 kg/m2 (95% credible interval 21·3–22·1) in 1975 to 24·2 kg/m2 (24·0–24·4) in 2014 in men, and from 22·1 kg/m2 (21·7–22·5) in 1975 to 24·4 kg/m2 (24·2–24·6) in 2014 in women. Regional mean BMIs in 2014 for men ranged from 21·4 kg/m2 in central Africa and south Asia to 29·2 kg/m2 (28·6–29·8) in Polynesia and Micronesia; for women the range was from 21·8 kg/m2 (21·4–22·3) in south Asia to 32·2 kg/m2 (31·5–32·8) in Polynesia and Micronesia. Over these four decades, age-standardised global prevalence of underweight decreased from 13·8% (10·5–17·4) to 8·8% (7·4–10·3) in men and from 14·6% (11·6–17·9) to 9·7% (8·3–11·1) in women. South Asia had the highest prevalence of underweight in 2014, 23·4% (17·8–29·2) in men and 24·0% (18·9–29·3) in women. Age-standardised prevalence of obesity increased from 3·2% (2·4–4·1) in 1975 to 10·8% (9·7–12·0) in 2014 in men, and from 6·4% (5·1–7·8) to 14·9% (13·6–16·1) in women. 2·3% (2·0–2·7) of the world's men and 5·0% (4·4–5·6) of women were severely obese (ie, have BMI ≥35 kg/m2). Globally, prevalence of morbid obesity was 0·64% (0·46–0·86) in men and 1·6% (1·3–1·9) in women. Interpretation If post-2000 trends continue, the probability of meeting the global obesity target is virtually zero. Rather, if these trends continue, by 2025, global obesity prevalence will reach 18% in men and surpass 21% in women; severe obesity will surpass 6% in men and 9% in women. Nonetheless, underweight remains prevalent in the world's poorest regions, especially in south Asia.

The use of remotely sensed rainfall for managing drought risk: a case study of weather index insurance in Zambia

Remotely sensed rainfall is increasingly being used to manage climate-related risk in gauge sparse regions. Applications based on such data must make maximal use of the skill of the methodology in order to avoid doing harm by providing misleading information. This is especially challenging in regions, such as Africa, which lack gauge data for validation. In this study, we show how calibrated ensembles of equally likely rainfall can be used to infer uncertainty in remotely sensed rainfall estimates, and subsequently in assessment of drought. We illustrate the methodology through a case study of weather index insurance (WII) in Zambia. Unlike traditional insurance, which compensates proven agricultural losses, WII pays out in the event that a weather index is breached. As remotely sensed rainfall is used to extend WII schemes to large numbers of farmers, it is crucial to ensure that the indices being insured are skillful representations of local environmental conditions. In our study we drive a land surface model with rainfall ensembles, in order to demonstrate how aggregation of rainfall estimates in space and time results in a clearer link with soil moisture, and hence a truer representation of agricultural drought. Although our study focuses on agricultural insurance, the methodological principles for application design are widely applicable in Africa and elsewhere.