Use of high-resolution geophysical data to characterize heterogeneous aquifers: influence of data integration method on hydrological predictions

The integration of geophysical data into the subsurface characterization problem has been shown in many cases to significantly improve hydrological knowledge by providing information at spatial scales and locations that is unattainable using conventional hydrological measurement techniques. The investigation of exactly how much benefit can be brought by geophysical data in terms of its effect on hydrological predictions, however, has received considerably less attention in the literature. Here, we examine the potential hydrological benefits brought by a recently introduced simulated annealing (SA) conditional stochastic simulation method designed for the assimilation of diverse hydrogeophysical data sets. We consider the specific case of integrating crosshole ground-penetrating radar (GPR) and borehole porosity log data to characterize the porosity distribution in saturated heterogeneous aquifers. In many cases, porosity is linked to hydraulic conductivity and thus to flow and transport behavior. To perform our evaluation, we first generate a number of synthetic porosity fields exhibiting varying degrees of spatial continuity and structural complexity. Next, we simulate the collection of crosshole GPR data between several boreholes in these fields, and the collection of porosity log data at the borehole locations. The inverted GPR data, together with the porosity logs, are then used to reconstruct the porosity field using the SA-based method, along with a number of other more elementary approaches. Assuming that the grid-cell-scale relationship between porosity and hydraulic conductivity is unique and known, the porosity realizations are then used in groundwater flow and contaminant transport simulations to assess the benefits and limitations of the different approaches.

Effects of brood manipulation costs on optimal sex allocation in social hymenoptera.

In eusocial Hymenoptera, queens and workers are in conflict over optimal sex allocation. Sex ratio theory, while generating predictions on the extent of this conflict under a wide range of conditions, has largely neglected the fact that worker control of investment almost certainly requires the manipulation of brood sex ratio. This manipulation is likely to incur costs, for example, if workers eliminate male larvae or rear more females as sexuals rather than workers. In this article, we present a model of sex ratio evolution under worker control that incorporates costs of brood manipulation. We assume cost to be a continuous, increasing function of the magnitude of sex ratio manipulation. We demonstrate that costs counterselect sex ratio biasing, which leads to less female-biased population sex ratios than expected on the basis of relatedness asymmetry. Furthermore, differently shaped cost functions lead to different equilibria of manipulation at the colony level. While linear and accelerating cost functions generate monomorphic equilibria, decelerating costs lead to a process of evolutionary branching and hence split sex ratios.

Reliability and validity of physiological data obtained within a cycle-run transition test in age-group triathletes.

This study examined the validity and reliability of a sequential "Run-Bike-Run" test (RBR) in age-group triathletes. Eight Olympic distance (OD) specialists (age 30.0 ± 2.0 years, mass 75.6 ± 1.6 kg, run VO2max 63.8 ± 1.9 ml· kg(-1)· min(-1), cycle VO2peak 56.7 ± 5.1 ml· kg(-1)· min(-1)) performed four trials over 10 days. Trial 1 (TRVO2max) was an incremental treadmill running test. Trials 2 and 3 (RBR1 and RBR2) involved: 1) a 7-min run at 15 km· h(-1) (R1) plus a 1-min transition to 2) cycling to fatigue (2 W· kg(-1) body mass then 30 W each 3 min); 3) 10-min cycling at 3 W· kg(-1) (Bsubmax); another 1-min transition and 4) a second 7-min run at 15 km· h(-1) (R2). Trial 4 (TT) was a 30-min cycle - 20-min run time trial. No significant differences in absolute oxygen uptake (VO2), heart rate (HR), or blood lactate concentration ([BLA]) were evidenced between RBR1 and RBR2. For all measured physiological variables, the limits of agreement were similar, and the mean differences were physiologically unimportant, between trials. Low levels of test-retest error (i.e. ICC <0.8, CV<10%) were observed for most (logged) measurements. However [BLA] post R1 (ICC 0.87, CV 25.1%), [BLA] post Bsubmax (ICC 0.99, CV 16.31) and [BLA] post R2 (ICC 0.51, CV 22.9%) were least reliable. These error ranges may help coaches detect real changes in training status over time. Moreover, RBR test variables can be used to predict discipline specific and overall TT performance. Cycle VO2peak, cycle peak power output, and the change between R1 and R2 (deltaR1R2) in [BLA] were most highly related to overall TT distance (r = 0.89, p < 0. 01; r = 0.94, p < 0.02; r = 0.86, p < 0.05, respectively). The percentage of TR VO2max at 15 km· h(-1), and deltaR1R2 HR, were also related to run TT distance (r = -0.83 and 0.86, both p < 0.05).

Explaining Fiscal Balances with a Simultaneous Equation Model of Revenue and Expenditure : A Case Study of Swiss Cantons Using Panel Data

Empirical literature on the analysis of the efficiency of measures for reducing persistent government deficits has mainly focused on the direct explanation of deficit. By contrast, this paper aims at modeling government revenue and expenditure within a simultaneous framework and deriving the fiscal balance (surplus or deficit) equation as the difference between the two variables. This setting enables one to not only judge how relevant the explanatory variables are in explaining the fiscal balance but also understand their impact on revenue and/or expenditure. Our empirical results, obtained by using a panel data set on Swiss Cantons for the period 1980-2002, confirm the relevance of the approach followed here, by providing unambiguous evidence of a simultaneous relationship between revenue and expenditure. They also reveal strong dynamic components in revenue, expenditure, and fiscal balance. Among the significant determinants of public fiscal balance we not only find the usual business cycle elements, but also and more importantly institutional factors such as the number of administrative units, and the ease with which people can resort to political (direct democracy) instruments, such as public initiatives and referendum.

Phylogeny and circumscription of Sapindaceae revisited: molecular sequence data, morphology and biogeography support recognition of a new family, Xanthoceraceae

Background and aims Recent studies have adopted a broad definition of Sapindaceae that includes taxa traditionally placed in Aceraceae and Hippocastanaceae, achieving monophyly but yielding a family difficult to characterize and for which no obvious morphological synapomorphy exists. This expanded circumscription was necessitated by the finding that the monotypic, temperate Asian genus Xanthoceras, historically placed in Sapindaceae tribe Harpullieae, is basal within the group. Here we seek to clarify the relationships of Xanthoceras based on phylogenetic analyses using a dataset encompassing nearly 3/4 of sapindaceous genera, comparing the results with information from morphology and biogeography, in particular with respect to the other taxa placed in Harpullieae. We then re-examine the appropriateness of maintaining the current broad, morphologically heterogeneous definition of Sapindaceae and explore the advantages of an alternative family circumscription. Methods Using 243 samples representing 104 of the 142 currently recognized genera of Sapindaceae s. lat. (including all in Harpullieae), sequence data were analyzed for nuclear (ITS) and plastid (matK, rpoB, trnD-trnT, trnK-matK, trnL-trnF and trnS-trnG) markers, adopting the methodology of a recent family-wide study, performing single-gene and total evidence analyses based on maximum likelihood (ML) and maximum parsimony (MP) criteria, and applying heuristic searches developed for large datasets, viz, a new strategy implemented in RAxML (for ML) and the parsimony ratchet (for MP). Bootstrap analyses were performed for each method to test for congruence between markers. Key results Our findings support earlier suggestions that Harpullieae are polyphyletic: Xanthoceras is confirmed as sister to all other sampled taxa of Sapindaceae s. lat.; the remaining members belong to three other clades within Sapindaceae s. lat., two of which correspond respectively to the groups traditionally treated as Aceraceae and Hippocastanaceae, together forming a clade sister to the largely tropical Sapindaceae s. str., which is monophyletic and morphologically coherent provided Xanthoceras is excluded. Conclusion To overcome the difficulties of a broadly circumscribed Sapindaceae, we resurrect the historically recognized temperate families Aceraceae and Hippocastanaceae, and describe a new family, Xanthoceraceae, thus adopting a monophyletic and easily characterized circumscription of Sapindaceae nearly identical to that used for over a century.

Universal features of personality traits from the observer's perspective: Data from 50 cultures

To test hypotheses about the universality of personality traits, college students in 50 cultures identified an adult or college-aged man or woman whom they knew well and rated the 11,985 targets using the 3rd-person version of the Revised NEO Personality Inventory. Factor analyses within cultures showed that the normative American self-report structure was clearly replicated in most cultures and was recognizable in all. Sex differences replicated earlier self-report results, with the most pronounced differences in Western cultures. Cross-sectional age differences for 3 factors followed the pattern identified in self-reports, with moderate rates of change during college age and slower changes after age 40. With a few exceptions, these data support the hypothesis that features of personality traits are common to all human groups.

Structural components in functional data

Analyzing functional data often leads to finding common factors, for which functional principal component analysis proves to be a useful tool to summarize and characterize the random variation in a function space. The representation in terms of eigenfunctions is optimal in the sense of L-2 approximation. However, the eigenfunctions are not always directed towards an interesting and interpretable direction in the context of functional data and thus could obscure the underlying structure. To overcome such difficulty, an alternative to functional principal component analysis is proposed that produces directed components which may be more informative and easier to interpret. These structural components are similar to principal components, but are adapted to situations in which the domain of the function may be decomposed into disjoint intervals such that there is effectively independence between intervals and positive correlation within intervals. The approach is demonstrated with synthetic examples as well as real data. Properties for special cases are also studied.

Histology-driven data mining of lipid signatures from multiple imaging mass spectrometry analyses: application to human colorectal cancer liver metastasis biopsies.

Imaging mass spectrometry (IMS) represents an innovative tool in the cancer research pipeline, which is increasingly being used in clinical and pharmaceutical applications. The unique properties of the technique, especially the amount of data generated, make the handling of data from multiple IMS acquisitions challenging. This work presents a histology-driven IMS approach aiming to identify discriminant lipid signatures from the simultaneous mining of IMS data sets from multiple samples. The feasibility of the developed workflow is evaluated on a set of three human colorectal cancer liver metastasis (CRCLM) tissue sections. Lipid IMS on tissue sections was performed using MALDI-TOF/TOF MS in both negative and positive ionization modes after 1,5-diaminonaphthalene matrix deposition by sublimation. The combination of both positive and negative acquisition results was performed during data mining to simplify the process and interrogate a larger lipidome into a single analysis. To reduce the complexity of the IMS data sets, a sub data set was generated by randomly selecting a fixed number of spectra from a histologically defined region of interest, resulting in a 10-fold data reduction. Principal component analysis confirmed that the molecular selectivity of the regions of interest is maintained after data reduction. Partial least-squares and heat map analyses demonstrated a selective signature of the CRCLM, revealing lipids that are significantly up- and down-regulated in the tumor region. This comprehensive approach is thus of interest for defining disease signatures directly from IMS data sets by the use of combinatory data mining, opening novel routes of investigation for addressing the demands of the clinical setting.

The prognostic value of health-related quality-of-life data in predicting survival in glioblastoma cancer patients: results from an international randomised phase III EORTC Brain Tumour and Radiation Oncology Groups, and NCIC Clinical Trials Group study.

This is one of the few studies that have explored the value of baseline symptoms and health-related quality of life (HRQOL) in predicting survival in brain cancer patients. Baseline HRQOL scores (from the EORTC QLQ-C30 and the Brain Cancer Module (BN 20)) were examined in 490 newly diagnosed glioblastoma cancer patients for the relationship with overall survival by using Cox proportional hazards regression models. Refined techniques as the bootstrap re-sampling procedure and the computation of C-indexes and R(2)-coefficients were used to try and validate the model. Classical analysis controlled for major clinical prognostic factors selected cognitive functioning (P=0.0001), global health status (P=0.0055) and social functioning (P<0.0001) as statistically significant prognostic factors of survival. However, several issues question the validity of these findings. C-indexes and R(2)-coefficients, which are measures of the predictive ability of the models, did not exhibit major improvements when adding selected or all HRQOL scores to clinical factors. While classical techniques lead to positive results, more refined analyses suggest that baseline HRQOL scores add relatively little to clinical factors to predict survival. These results may have implications for future use of HRQOL as a prognostic factor in cancer patients.

Imputation in data fusion of heterogeneous data sets a model-based numerical experiment

Given the very large amount of data obtained everyday through population surveys, much of the new research again could use this information instead of collecting new samples. Unfortunately, relevant data are often disseminated into different files obtained through different sampling designs. Data fusion is a set of methods used to combine information from different sources into a single dataset. In this article, we are interested in a specific problem: the fusion of two data files, one of which being quite small. We propose a model-based procedure combining a logistic regression with an Expectation-Maximization algorithm. Results show that despite the lack of data, this procedure can perform better than standard matching procedures.

Lifelong dynamics of human CD4+CD25+ regulatory T cells: insights from in vivo data and mathematical modeling.

Despite their limited proliferation capacity, regulatory T cells (T(regs)) constitute a population maintained over the entire lifetime of a human organism. The means by which T(regs) sustain a stable pool in vivo are controversial. Using a mathematical model, we address this issue by evaluating several biological scenarios of the origins and the proliferation capacity of two subsets of T(regs): precursor CD4(+)CD25(+)CD45RO(-) and mature CD4(+)CD25(+)CD45RO(+) cells. The lifelong dynamics of T(regs) are described by a set of ordinary differential equations, driven by a stochastic process representing the major immune reactions involving these cells. The model dynamics are validated using data from human donors of different ages. Analysis of the data led to the identification of two properties of the dynamics: (1) the equilibrium in the CD4(+)CD25(+)FoxP3(+)T(regs) population is maintained over both precursor and mature T(regs) pools together, and (2) the ratio between precursor and mature T(regs) is inverted in the early years of adulthood. Then, using the model, we identified three biologically relevant scenarios that have the above properties: (1) the unique source of mature T(regs) is the antigen-driven differentiation of precursors that acquire the mature profile in the periphery and the proliferation of T(regs) is essential for the development and the maintenance of the pool; there exist other sources of mature T(regs), such as (2) a homeostatic density-dependent regulation or (3) thymus- or effector-derived T(regs), and in both cases, antigen-induced proliferation is not necessary for the development of a stable pool of T(regs). This is the first time that a mathematical model built to describe the in vivo dynamics of regulatory T cells is validated using human data. The application of this model provides an invaluable tool in estimating the amount of regulatory T cells as a function of time in the blood of patients that received a solid organ transplant or are suffering from an autoimmune disease.