Design of a tablet sized human-computer interface and its effect on situation awareness

Emergency Response Teams increasingly use interactive technology to help manage information and communications. The challenge is to maintain a high situation awareness for different interactive devices sizes. This research specifically compared a handheld interactive device in the form of an iPad with a large interactive multi-touch tabletop. A search and rescue inspired simulator was designed to test operator situation awareness for the two sized devices. The results show that operators had better situation awareness on the tabletop device when the operation related to detecting of moving targets, searching target locations, distinguishing target types, and comprehending displayed information.

On the benefits of equicorrelation for portfolio allocation

The importance of modelling correlation has long been recognised in the field of portfolio management, with largedimensional multivariate problems increasingly becoming the focus of research. This paper provides a straightforward and commonsense approach toward investigating a number of models used to generate forecasts of the correlation matrix for large-dimensional problems.We find evidence in favour of assuming equicorrelation across various portfolio sizes, particularly during times of crisis. During periods of market calm, however, the suitability of the constant conditional correlation model cannot be discounted, especially for large portfolios. A portfolio allocation problem is used to compare forecasting methods. The global minimum variance portfolio and Model Confidence Set are used to compare methods, while portfolio weight stability and relative economic value are also considered.

Criteria for interpreting kimberlite as coherent: Insights from the Muskox and Jericho kimberlites (Nunavut, Canada)

The Jurassic Muskox and Jericho kimberlites (Northern Slave Province, Nunavut, Canada) contain a variety of facies exhibiting different geometries, contact relationships, internal organisation, country rock abundance and olivine shapes, although many have similar matrix/groundmass mineralogies and textures. Five facies are examined that either have characteristics consistent with coherent rocks in general (i.e. intrusive and extrusive non-fragmental rocks) or are mineralogically and texturally similar to kimberlite described as coherent (or apparent coherent). Three facies are interpreted as coherent on the basis of: (1) geological setting, (2) apparent-porphyritic texture, (3) sharp contacts with fragmental kimberlite, (4) relative abundance of elongate and unbroken olivine crystals and (5) paucity of country rock xenoliths, while the remaining two facies are interpreted as fragmental on the basis of: (1) the gradational contacts with demonstrably fragmental kimberlite, (2) relative abundance and range of sizes of country rock lithic clasts and (3) numerous broken olivine crystals. Comparisons are made with coherent and apparent-coherent kimberlite from the literature. Our three coherent facies are similar to literature reported coherent kimberlite dykes hosted in country rock (CKd) in terms of internal organisation, low abundance of country rock xenoliths, and apparent-porphyritic texture. Conversely, our two fragmental facies share attributes with previously described pipe-filling coherent and apparent-coherent kimberlite (CKpf) in terms of geometry, internal organisation and abundance of country rock xenoliths. We conclude that CKd and most CKpf, although similar in matrix/groundmass mineralogy and texture, can be distinguished on the basis of internal organisation, country rock lithic clast abundance, texture (e.g. apparent-porphyritic texture) and possibly olivine crystal shapes and suggest that fragmental kimberlite is more common than reported.

Difficulties in distinguishing coherent from fragmental kimberlite: A case study of the Muskox pipe (Northern Slave Province, Nunavut, Canada)

Kimberlite drill core from the Muskox pipe (Northern Slave Province, Nunavut, Canada) highlights the difficulties in distinguishing coherent from fragmental kimberlite and assessing the volcanological implications of the apparent gradational contact between the two facies. Using field log data, petrography, and several methods to quantify crystal and xenolith sizes and abundances, the pipe is divided into two main facies, dark-coloured massive kimberlite (DMK) and light-coloured fragmental kimberlite (LFK). DMK is massive and homogeneous, containing country-rock lithic clasts (~ 10%) and olivine macrocrysts (~ 15%) set in a dark, typically well crystallised, interstitial medium containing abundant microphenocrysts of olivine (~ 15%), opaques and locally monticellite, all of which are enclosed by mostly serpentine. In general, LFK is also massive and structureless, containing ~ 20% country-rock lithic clasts and ~ 12% olivine macrocrysts. These framework components are supported in a matrix of serpentinized olivine microphenocrysts (10%), microlites of clinopyroxene, and phlogopite, all of which are enclosed by serpentine. The contact between DMK and LFK facies is rarely sharp, and more commonly is gradational (from 5 cm to ~ 10 m). The contact divides the pipe roughly in half and is sub-vertical with an irregular shape, locally placing DMK facies both above and below the fragmental rocks. Most features of DMK are consistent with a fragmental origin, particularly the crystal- and xenolith-rich nature (~ 55-65%), but there are some similarities with rocks described as coherent kimberlite in the literature. We discuss possible origins of gradational contacts and consider the significance for understanding the origin of the DMK facies, with an emphasis on the complications of alteration overprinting of primary textures.

The YOU CALL-WE CALL randomized clinical trial: Impact of a multimodal support intervention after a mild stroke

Background Comparison of a multimodal intervention WE CALL (study initiated phone support/information provision) versus a passive intervention YOU CALL (participant can contact a resource person) in individuals with first mild stroke. Methods and Results This study is a single-blinded randomized clinical trial. Primary outcome includes unplanned use of health services (participant diaries) for adverse events and quality of life (Euroquol-5D, Quality of Life Index). Secondary outcomes include planned use of health services (diaries), mood (Beck Depression Inventory II), and participation (Assessment of Life Habits [LIFE-H]). Blind assessments were done at baseline, 6, and 12 months. A mixed model approach for statistical analysis on an intention-to-treat basis was used where the group factor was intervention type and occasion factor time, with a significance level of 0.01. We enrolled 186 patients (WE=92; YOU=94) with a mean age of 62.5±12.5 years, and 42.5% were women. No significant differences were seen between groups at 6 months for any outcomes with both groups improving from baseline on all measures (effect sizes ranged from 0.25 to 0.7). The only significant change for both groups from 6 months to 1 year (n=139) was in the social domains of the LIFE-H (increment in score, 0.4/9±1.3 [95% confidence interval, 0.1–0.7]; effect size, 0.3). Qualitatively, the WE CALL intervention was perceived as reassuring, increased insight, and problem solving while decreasing anxiety. Only 6 of 94 (6.4%) YOU CALL participants availed themselves of the intervention. Conclusions Although the 2 groups improved equally over time, WE CALL intervention was perceived as helpful, whereas YOU CALL intervention was not used.

The Driver Behaviour Questionnaire as accident predictor: A methodological re-meta-analysis

Problem The Manchester Driver Behaviour Questionnaire (DBQ) is the most commonly used self-report tool in traffic safety research and applied settings. It has been claimed that the violation factor of this instrument predicts accident involvement, which was supported by a previous meta-analysis. However, that analysis did not test for methodological effects, or include contacting researchers to obtain unpublished results. Method The present study re-analysed studies on prediction of accident involvement from DBQ factors, including lapses, and many unpublished effects. Tests of various types of dissemination bias and common method variance were undertaken. Results Outlier analysis showed that some effects were probably not reliable data, but excluding them did not change the results. For correlations between violations and crashes, tendencies for published effects to be larger than unpublished ones and for effects to decrease over time were observed, but were not significant. Also, analysis using the proxy of the mean of accidents in studies indicated that studies where effects for violations are unknown have smaller effect sizes. These differences indicate dissemination bias. Studies using self-reported accidents as dependent variables had much larger effects than those using recorded accident data. Also, zero-order correlations were larger than partial correlations that controlled for exposure. Similarly, violations/accidents effects were strong only when there was also a strong correlation between accidents and exposure. Overall, the true effect is probably very close to zero (r<.07) for violations versus traffic accident involvement, depending upon which systematic tendencies in the data are controlled for. Conclusions: Methodological factors and dissemination bias have inflated the mean effect size of the DBQ in the published literature. Strong evidence of various artefactual effects is apparent. Practical Applications A greater level of care should be taken if the DBQ continues to be used in traffic safety research. Also, validation of self-reports should be more comprehensive in the future, taking into account the possibility of common method variance.

Extending genetic linkage analysis to diffusion tensor images to map single gene effects on brain fiber architecture

We extended genetic linkage analysis - an analysis widely used in quantitative genetics - to 3D images to analyze single gene effects on brain fiber architecture. We collected 4 Tesla diffusion tensor images (DTI) and genotype data from 258 healthy adult twins and their non-twin siblings. After high-dimensional fluid registration, at each voxel we estimated the genetic linkage between the single nucleotide polymorphism (SNP), Val66Met (dbSNP number rs6265), of the BDNF gene (brain-derived neurotrophic factor) with fractional anisotropy (FA) derived from each subject's DTI scan, by fitting structural equation models (SEM) from quantitative genetics. We also examined how image filtering affects the effect sizes for genetic linkage by examining how the overall significance of voxelwise effects varied with respect to full width at half maximum (FWHM) of the Gaussian smoothing applied to the FA images. Raw FA maps with no smoothing yielded the greatest sensitivity to detect gene effects, when corrected for multiple comparisons using the false discovery rate (FDR) procedure. The BDNF polymorphism significantly contributed to the variation in FA in the posterior cingulate gyrus, where it accounted for around 90-95% of the total variance in FA. Our study generated the first maps to visualize the effect of the BDNF gene on brain fiber integrity, suggesting that common genetic variants may strongly determine white matter integrity.

Improving fluid registration through white matter segmentation in a twin study design

Robust and automatic non-rigid registration depends on many parameters that have not yet been systematically explored. Here we determined how tissue classification influences non-linear fluid registration of brain MRI. Twin data is ideal for studying this question, as volumetric correlations between corresponding brain regions that are under genetic control should be higher in monozygotic twins (MZ) who share 100% of their genes when compared to dizygotic twins (DZ) who share half their genes on average. When these substructure volumes are quantified using tensor-based morphometry, improved registration can be defined based on which method gives higher MZ twin correlations when compared to DZs, as registration errors tend to deplete these correlations. In a study of 92 subjects, higher effect sizes were found in cumulative distribution functions derived from statistical maps when performing tissue classification before fluid registration, versus fluidly registering the raw images. This gives empirical evidence in favor of pre-segmenting images for tensor-based morphometry.

Genetic clustering on the hippocampal surface for genome-wide association studies

Imaging genetics aims to discover how variants in the human genome influence brain measures derived from images. Genome-wide association scans (GWAS) can screen the genome for common differences in our DNA that relate to brain measures. In small samples, GWAS has low power as individual gene effects are weak and one must also correct for multiple comparisons across the genome and the image. Here we extend recent work on genetic clustering of images, to analyze surface-based models of anatomy using GWAS. We performed spherical harmonic analysis of hippocampal surfaces, automatically extracted from brain MRI scans of 1254 subjects. We clustered hippocampal surface regions with common genetic influences by examining genetic correlations (r(g)) between the normalized deformation values at all pairs of surface points. Using genetic correlations to cluster surface measures, we were able to boost effect sizes for genetic associations, compared to clustering with traditional phenotypic correlations using Pearson's r.

Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling

Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.

Comparison of fractional and geodesic anisotropy in diffusion tensor images of 90 monozygotic and dizygotic twins

We used diffusion tensor magnetic resonance imaging (DTI) to reveal the extent of genetic effects on brain fiber microstructure, based on tensor-derived measures, in 22 pairs of monozygotic (MZ) twins and 23 pairs of dizygotic (DZ) twins (90 scans). After Log-Euclidean denoising to remove rank-deficient tensors, DTI volumes were fluidly registered by high-dimensional mapping of co-registered MP-RAGE scans to a geometrically-centered mean neuroanatomical template. After tensor reorientation using the strain of the 3D fluid transformation, we computed two widely used scalar measures of fiber integrity: fractional anisotropy (FA), and geodesic anisotropy (GA), which measures the geodesic distance between tensors in the symmetric positive-definite tensor manifold. Spatial maps of intraclass correlations (r) between MZ and DZ twins were compared to compute maps of Falconer's heritability statistics, i.e. the proportion of population variance explainable by genetic differences among individuals. Cumulative distribution plots (CDF) of effect sizes showed that the manifold measure, GA, comparably the Euclidean measure, FA, in detecting genetic correlations. While maps were relatively noisy, the CDFs showed promise for detecting genetic influences on brain fiber integrity as the current sample expands.

Multivariate variance-components analysis in DTI

Twin studies are a major research direction in imaging genetics, a new field, which combines algorithms from quantitative genetics and neuroimaging to assess genetic effects on the brain. In twin imaging studies, it is common to estimate the intraclass correlation (ICC), which measures the resemblance between twin pairs for a given phenotype. In this paper, we extend the commonly used Pearson correlation to a more appropriate definition, which uses restricted maximum likelihood methods (REML). We computed proportion of phenotypic variance due to additive (A) genetic factors, common (C) and unique (E) environmental factors using a new definition of the variance components in the diffusion tensor-valued signals. We applied our analysis to a dataset of Diffusion Tensor Images (DTI) from 25 identical and 25 fraternal twin pairs. Differences between the REML and Pearson estimators were plotted for different sample sizes, showing that the REML approach avoids severe biases when samples are smaller. Measures of genetic effects were computed for scalar and multivariate diffusion tensor derived measures including the geodesic anisotropy (tGA) and the full diffusion tensors (DT), revealing voxel-wise genetic contributions to brain fiber microstructure.

Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group

The pattern of structural brain alterations associated with major depressive disorder (MDD) remains unresolved. This is in part due to small sample sizes of neuroimaging studies resulting in limited statistical power, disease heterogeneity and the complex interactions between clinical characteristics and brain morphology. To address this, we meta-analyzed three-dimensional brain magnetic resonance imaging data from 1728 MDD patients and 7199 controls from 15 research samples worldwide, to identify subcortical brain volumes that robustly discriminate MDD patients from healthy controls. Relative to controls, patients had significantly lower hippocampal volumes (Cohen’s d=−0.14, % difference=−1.24). This effect was driven by patients with recurrent MDD (Cohen’s d=−0.17, % difference=−1.44), and we detected no differences between first episode patients and controls. Age of onset ⩽21 was associated with a smaller hippocampus (Cohen’s d=−0.20, % difference=−1.85) and a trend toward smaller amygdala (Cohen’s d=−0.11, % difference=−1.23) and larger lateral ventricles (Cohen’s d=0.12, % difference=5.11). Symptom severity at study inclusion was not associated with any regional brain volumes. Sample characteristics such as mean age, proportion of antidepressant users and proportion of remitted patients, and methodological characteristics did not significantly moderate alterations in brain volumes in MDD. Samples with a higher proportion of antipsychotic medication users showed larger caudate volumes in MDD patients compared with controls. This currently largest worldwide effort to identify subcortical brain alterations showed robust smaller hippocampal volumes in MDD patients, moderated by age of onset and first episode versus recurrent episode status.

The role of marketing in today's enterprises

Purpose The purpose of this paper is to explore the role of marketing in today's enterprises and examines the antecedents of the marketing department's influence and its relationship with market orientation and firm performance. Design/methodology/approach Data were collected from the West (i.e. the USA and Europe) and the East (i.e. Asia). Partial least squares (PLS) was used to estimate structural models. Findings The findings support the idea that a strong and influential marketing department contributes positively to firm performance. This finding holds for Western and Asian, and for small/medium and large firms alike. Second, the marketing department's influence in a firm depends more on its responsibilities and resources, and less on internal contingency factors (i.e. a firm's competitive strategy or institutional attributes). Third, a marketing department's influence in the West affects firm performance both directly and indirectly (via market orientation). In contrast, this relationship is fully mediated among Eastern firms. Fourth, low-cost strategies enhance the influence of a firm's marketing department in the East, but not in the West. Research limitations/implications The paper assumes explicitly that a marketing department's influence is an antecedent of its market orientation. While the paper finds support for this link, the paper did not test for dual causality between the constructs. Originality/value Countering the frequent claim in anecdotal and journalistic work that the role of the marketing department diminishes, the findings show that across different geographic regions and firm sizes, strong marketing departments improve firm performance (especially in the marketing-savvy West), and that they should continue to play an important role in firms.

Consistent responses of soil microbial communities to elevated nutrient inputs in grasslands across the globe

Soil microorganisms are critical to ecosystem functioning and the maintenance of soil fertility. However, despite global increases in the inputs of nitrogen (N) and phosphorus (P) to ecosystems due to human activities, we lack a predictive understanding of how microbial communities respond to elevated nutrient inputs across environmental gradients. Here we used high-throughput sequencing of marker genes to elucidate the responses of soil fungal, archaeal, and bacterial communities using an N and P addition experiment replicated at 25 globally distributed grassland sites. We also sequenced metagenomes from a subset of the sites to determine how the functional attributes of bacterial communities change in response to elevated nutrients. Despite strong compositional differences across sites, microbial communities shifted in a consistent manner with N or P additions, and the magnitude of these shifts was related to the magnitude of plant community responses to nutrient inputs. Mycorrhizal fungi and methanogenic archaea decreased in relative abundance with nutrient additions, as did the relative abundances of oligotrophic bacterial taxa. The metagenomic data provided additional evidence for this shift in bacterial life history strategies because nutrient additions decreased the average genome sizes of the bacterial community members and elicited changes in the relative abundances of representative functional genes. Our results suggest that elevated N and P inputs lead to predictable shifts in the taxonomic and functional traits of soil microbial communities, including increases in the relative abundances of faster-growing, copiotrophic bacterial taxa, with these shifts likely to impact belowground ecosystems worldwide.