Statistical assessment of dataset shift and model portability in multi-angle in-track image acquisitions

In this study we propose an evaluation of the angular effects altering the spectral response of the land-cover over multi-angle remote sensing image acquisitions. The shift in the statistical distribution of the pixels observed in an in-track sequence of WorldView-2 images is analyzed by means of a kernel-based measure of distance between probability distributions. Afterwards, the portability of supervised classifiers across the sequence is investigated by looking at the evolution of the classification accuracy with respect to the changing observation angle. In this context, the efficiency of various physically and statistically based preprocessing methods in obtaining angle-invariant data spaces is compared and possible synergies are discussed.

Temporal quantification of MAPK induced expression in single yeast cells.

The quantification of gene expression at the single cell level uncovers novel regulatory mechanisms obscured in measurements performed at the population level. Two methods based on microscopy and flow cytometry are presented to demonstrate how such data can be acquired. The expression of a fluorescent reporter induced upon activation of the high osmolarity glycerol MAPK pathway in yeast is used as an example. The specific advantages of each method are highlighted. Flow cytometry measures a large number of cells (10,000) and provides a direct measure of the dynamics of protein expression independent of the slow maturation kinetics of the fluorescent protein. Imaging of living cells by microscopy is by contrast limited to the measurement of the matured form of the reporter in fewer cells. However, the data sets generated by this technique can be extremely rich thanks to the combinations of multiple reporters and to the spatial and temporal information obtained from individual cells. The combination of these two measurement methods can deliver new insights on the regulation of protein expression by signaling pathways.

Kinetics of atrial repolarization alternans in a free-behaving ovine model.

Kinetics of Atrial Repolarization Alternans. INTRODUCTION: Repolarization alternans (Re-ALT), a beat-to-beat alternation in action potential repolarization, promotes dispersion of repolarization, wavebreaks, and reentry. Recently, Re-ALT has been shown to play an important role in the transition from rapid pacing to atrial fibrillation (AF) in humans. The detailed kinetics of atrial Re-ALT, however, has not been reported so far. We developed a chronic free-behaving ovine pacing model to study the kinetics of atrial Re-ALT as a function of pacing rate. METHODS: Thirteen sheep were chronically implanted with 2 pacemakers for the recording of broadband right atrial unipolar electrograms and delivery of rapid pacing protocols. Beat-to-beat differences in the atrial T-wave apex amplitude as a measure of Re-ALT and activation time were analyzed at incremental pacing rates until the effective refractory period (ERP) defined as stable 2:1 capture. RESULTS: Atrial Re-ALT appeared intermittently but without periodicity, and increased in amplitude as a function of pacing rate until ERP. Intermittent 2:1 atrial capture was observed at pacing cycle lengths 40 ms above ERP, and increased in duration as a function of pacing rate. Episodes of rapid pacing-induced AF were rare, and were preceded by Re-ALT or complex oscillations of atrial repolarization, but without intermittent capture. CONCLUSION: We show in vivo that atrial Re-ALT developed and increased in magnitude with rate until stable 2:1 capture. In rare instances where capture failure did not occur, Re-ALT and complex oscillations of repolarization surged and preceded AF initiation. (J Cardiovasc Electrophysiol, Vol. 23, pp. 1003-1012, September 2012).

Predictive analysis and mapping of indoor radon concentrations in Switzerland

It is estimated that around 230 people die each year due to radon (222Rn) exposure in Switzerland. 222Rn occurs mainly in closed environments like buildings and originates primarily from the subjacent ground. Therefore it depends strongly on geology and shows substantial regional variations. Correct identification of these regional variations would lead to substantial reduction of 222Rn exposure of the population based on appropriate construction of new and mitigation of already existing buildings. Prediction of indoor 222Rn concentrations (IRC) and identification of 222Rn prone areas is however difficult since IRC depend on a variety of different variables like building characteristics, meteorology, geology and anthropogenic factors. The present work aims at the development of predictive models and the understanding of IRC in Switzerland, taking into account a maximum of information in order to minimize the prediction uncertainty. The predictive maps will be used as a decision-support tool for 222Rn risk management. The construction of these models is based on different data-driven statistical methods, in combination with geographical information systems (GIS). In a first phase we performed univariate analysis of IRC for different variables, namely the detector type, building category, foundation, year of construction, the average outdoor temperature during measurement, altitude and lithology. All variables showed significant associations to IRC. Buildings constructed after 1900 showed significantly lower IRC compared to earlier constructions. We observed a further drop of IRC after 1970. In addition to that, we found an association of IRC with altitude. With regard to lithology, we observed the lowest IRC in sedimentary rocks (excluding carbonates) and sediments and the highest IRC in the Jura carbonates and igneous rock. The IRC data was systematically analyzed for potential bias due to spatially unbalanced sampling of measurements. In order to facilitate the modeling and the interpretation of the influence of geology on IRC, we developed an algorithm based on k-medoids clustering which permits to define coherent geological classes in terms of IRC. We performed a soil gas 222Rn concentration (SRC) measurement campaign in order to determine the predictive power of SRC with respect to IRC. We found that the use of SRC is limited for IRC prediction. The second part of the project was dedicated to predictive mapping of IRC using models which take into account the multidimensionality of the process of 222Rn entry into buildings. We used kernel regression and ensemble regression tree for this purpose. We could explain up to 33% of the variance of the log transformed IRC all over Switzerland. This is a good performance compared to former attempts of IRC modeling in Switzerland. As predictor variables we considered geographical coordinates, altitude, outdoor temperature, building type, foundation, year of construction and detector type. Ensemble regression trees like random forests allow to determine the role of each IRC predictor in a multidimensional setting. We found spatial information like geology, altitude and coordinates to have stronger influences on IRC than building related variables like foundation type, building type and year of construction. Based on kernel estimation we developed an approach to determine the local probability of IRC to exceed 300 Bq/m3. In addition to that we developed a confidence index in order to provide an estimate of uncertainty of the map. All methods allow an easy creation of tailor-made maps for different building characteristics. Our work is an essential step towards a 222Rn risk assessment which accounts at the same time for different architectural situations as well as geological and geographical conditions. For the communication of 222Rn hazard to the population we recommend to make use of the probability map based on kernel estimation. The communication of 222Rn hazard could for example be implemented via a web interface where the users specify the characteristics and coordinates of their home in order to obtain the probability to be above a given IRC with a corresponding index of confidence. Taking into account the health effects of 222Rn, our results have the potential to substantially improve the estimation of the effective dose from 222Rn delivered to the Swiss population.

Joint inversion of crosshole GPR and seismic traveltime data

Joint inversion of crosshole ground-penetrating radar and seismic data can improve model resolution and fidelity of the resultant individual models. Model coupling obtained by minimizing or penalizing some measure of structural dissimilarity between models appears to be the most versatile approach because only weak assumptions about petrophysical relationships are required. Nevertheless, experimental results and petrophysical arguments suggest that when porosity variations are weak in saturated unconsolidated environments, then radar wave speed is approximately linearly related to seismic wave speed. Under such circumstances, model coupling also can be achieved by incorporating cross-covariances in the model regularization. In two case studies, structural similarity is imposed by penalizing models for which the model cross-gradients are nonzero. A first case study demonstrates improvements in model resolution by comparing the resulting models with borehole information, whereas a second case study uses point-spread functions. Although radar seismic wavespeed crossplots are very similar for the two case studies, the models plot in different portions of the graph, suggesting variances in porosity. Both examples display a close, quasilinear relationship between radar seismic wave speed in unconsolidated environments that is described rather well by the corresponding lower Hashin-Shtrikman (HS) bounds. Combining crossplots of the joint inversion models with HS bounds can constrain porosity and pore structure better than individual inversion results can.

Gait and foot clearance parameters obtained using shoe-worn inertial sensors in a large-population sample of older adults

In order to distinguish dysfunctional gait; clinicians require a measure of reference gait parameters for each population. This study provided normative values for widely used parameters in more than 1400 able-bodied adults over the age of 65. We also measured the foot clearance parameters (i.e., height of the foot above ground during swing phase) that are crucial to understand the complex relationship between gait and falls as well as obstacle negotiation strategies. We used a shoe-worn inertial sensor on each foot and previously validated algorithms to extract the gait parameters during 20 m walking trials in a corridor at a self-selected pace. We investigated the difference of the gait parameters between male and female participants by considering the effect of age and height factors. Besides; we examined the inter-relation of the clearance parameters with the gait speed. The sample size and breadth of gait parameters provided in this study offer a unique reference resource for the researchers.

Pharmacological treatment of behavioral and psychological symptoms of dementia (BPSD) in nursing homes: development of practice recommendations in a Swiss canton

OBJECTIVES: In 2002, the canton of Fribourg, Switzerland, implemented a coordinated pharmaceutical care service in nursing homes to promote rational drug use. In the context of this service, a project was conducted to develop recommendations for the pharmacological management of behavioral and psychological symptoms of dementia (BPSD) in nursing home residents. DESIGN AND METHODS: Selected evidence-based guidelines and meta-analysis sources related to the management of depression, insomnia, and agitation in dementia patients were systematically searched and evaluated. Evidence and controversies regarding the pharmacological treatment of the most common BPSD symptoms were reviewed, and treatment algorithms were developed. RESULTS: Ten evidence-based guidelines and meta-analyses for BPSD management were identified, with none specifically addressing issues related to nursing home residents. Based on this literature, recommendations were developed for the practice of pharmacological management of depression, sleep disturbances, and agitation in nursing home residents. For depression, SSRIs are considered the first choice if an antidepressant is required. No clear evidence has been found for sleep disturbances; the underlying conditions need to be investigated closely before the introduction of any drug therapy. Many drugs have been investigated for the treatment of agitation, and if necessary, antipsychotics could be used, although they have significant side effects. Several areas of uncertainty were identified, such as the current controversy about typical and atypical antipsychotic use or the appropriateness of cholinesterase inhibitors for controlling agitation. Treatment algorithms were presented to general practitioners, pharmacists, and medical directors of nursing homes in the canton of Fribourg, and will now be implemented progressively, using educational sessions, pharmaceutical counseling, and monitoring. CONCLUSION: Based on existing evidence-based studies, recommendations were developed for the practice of pharmacological management of depression, sleep disturbances, and agitation in nursing home residents. It should be further studied whether these algorithms implemented through pharmaceutical care services will improve psychotropic drug prescriptions and prevent drug-related problems in nursing home residents

Effects of alternative sets of climatic predictors on species distribution models and associated estimates of extinction risk: a test with plants in an arid environment

Aim To evaluate the effects of using distinct alternative sets of climatic predictor variables on the performance, spatial predictions and future projections of species distribution models (SDMs) for rare plants in an arid environment. . Location Atacama and Peruvian Deserts, South America (18º30'S - 31º30'S, 0 - 3 000 m) Methods We modelled the present and future potential distributions of 13 species of Heliotropium sect. Cochranea, a plant group with a centre of diversity in the Atacama Desert. We developed and applied a sequential procedure, starting from climate monthly variables, to derive six alternative sets of climatic predictor variables. We used them to fit models with eight modelling techniques within an ensemble forecasting framework, and derived climate change projections for each of them. We evaluated the effects of using these alternative sets of predictor variables on performance, spatial predictions and projections of SDMs using Generalised Linear Mixed Models (GLMM). Results The use of distinct sets of climatic predictor variables did not have a significant effect on overall metrics of model performance, but had significant effects on present and future spatial predictions. Main conclusion Using different sets of climatic predictors can yield the same model fits but different spatial predictions of current and future species distributions. This represents a new form of uncertainty in model-based estimates of extinction risk that may need to be better acknowledged and quantified in future SDM studies.

Using STD occurence to monitor AIDS prevention : final report of the Working Group on STD Surveillance.

The overall aim of the project has been to assess the extent to which data on the frequency of occurence of STDs [Sexually transmitted diseases] might be useful in the monitoring and evaluation of AIDS prevention programmes. The objectives have been to answer the following questions: (a) Can measures of STD occurence be used as an outcome measure of AIDS/HIV preventive efforts ? In particular: -> which diseases might be useful ? -> in what ways could they be used ? (b) If measures of STD occurence can be used in this way, is existing surveillance data in Western Europe adequate for the purpose ? If not why not ? (c) What do data from existing STD surveillance systems tell us about the success or failure of AIDS prevention to date ? (d) What needs to be done in order taht STD surveillance data in the countries of Western Europe could be used for this purpose ? [Authors, p. 4]

An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo-absence data

1. Few examples of habitat-modelling studies of rare and endangered species exist in the literature, although from a conservation perspective predicting their distribution would prove particularly useful. Paucity of data and lack of valid absences are the probable reasons for this shortcoming. Analytic solutions to accommodate the lack of absence include the ecological niche factor analysis (ENFA) and the use of generalized linear models (GLM) with simulated pseudo-absences. 2. In this study we tested a new approach to generating pseudo-absences, based on a preliminary ENFA habitat suitability (HS) map, for the endangered species Eryngium alpinum. This method of generating pseudo-absences was compared with two others: (i) use of a GLM with pseudo-absences generated totally at random, and (ii) use of an ENFA only. 3. The influence of two different spatial resolutions (i.e. grain) was also assessed for tackling the dilemma of quality (grain) vs. quantity (number of occurrences). Each combination of the three above-mentioned methods with the two grains generated a distinct HS map. 4. Four evaluation measures were used for comparing these HS maps: total deviance explained, best kappa, Gini coefficient and minimal predicted area (MPA). The last is a new evaluation criterion proposed in this study. 5. Results showed that (i) GLM models using ENFA-weighted pseudo-absence provide better results, except for the MPA value, and that (ii) quality (spatial resolution and locational accuracy) of the data appears to be more important than quantity (number of occurrences). Furthermore, the proposed MPA value is suggested as a useful measure of model evaluation when used to complement classical statistical measures. 6. Synthesis and applications. We suggest that the use of ENFA-weighted pseudo-absence is a possible way to enhance the quality of GLM-based potential distribution maps and that data quality (i.e. spatial resolution) prevails over quantity (i.e. number of data). Increased accuracy of potential distribution maps could help to define better suitable areas for species protection and reintroduction.

Evolution of specialization: a phylogenetic study of host range in the red milkweed beetle (Tetraopes tetraophthalmus).

Specialization is common in most lineages of insect herbivores, one of the most diverse groups of organisms on earth. To address how and why specialization is maintained over evolutionary time, we hypothesized that plant defense and other ecological attributes of potential host plants would predict the performance of a specialist root-feeding herbivore (the red milkweed beetle, Tetraopes tetraophthalmus). Using a comparative phylogenetic and functional trait approach, we assessed the determinants of insect host range across 18 species of Asclepias. Larval survivorship decreased with increasing phylogenetic distance from the true host, Asclepias syriaca, suggesting that adaptation to plant traits drives specialization. Among several root traits measured, only cardenolides (toxic defense chemicals) correlated with larval survival, and cardenolides also explained the phylogenetic distance effect in phylogenetically controlled multiple regression analyses. Additionally, milkweed species having a known association with other Tetraopes beetles were better hosts than species lacking Tetraopes herbivores, and milkweeds with specific leaf area values (a trait related to leaf function and habitat affiliation) similar to those of A. syriaca were better hosts than species having divergent values. We thus conclude that phylogenetic distance is an integrated measure of phenotypic and ecological attributes of Asclepias species, especially defensive cardenolides, which can be used to explain specialization and constraints on host shifts over evolutionary time.

Energy gap in the aetiology of body weight gain and obesity: a challenging concept with a complex evaluation and pitfalls.

The concept of energy gap(s) is useful for understanding the consequence of a small daily, weekly, or monthly positive energy balance and the inconspicuous shift in weight gain ultimately leading to overweight and obesity. Energy gap is a dynamic concept: an initial positive energy gap incurred via an increase in energy intake (or a decrease in physical activity) is not constant, may fade out with time if the initial conditions are maintained, and depends on the 'efficiency' with which the readjustment of the energy imbalance gap occurs with time. The metabolic response to an energy imbalance gap and the magnitude of the energy gap(s) can be estimated by at least two methods, i.e. i) assessment by longitudinal overfeeding studies, imposing (by design) an initial positive energy imbalance gap; ii) retrospective assessment based on epidemiological surveys, whereby the accumulated endogenous energy storage per unit of time is calculated from the change in body weight and body composition. In order to illustrate the difficulty of accurately assessing an energy gap we have used, as an illustrative example, a recent epidemiological study which tracked changes in total energy intake (estimated by gross food availability) and body weight over 3 decades in the US, combined with total energy expenditure prediction from body weight using doubly labelled water data. At the population level, the study attempted to assess the cause of the energy gap purported to be entirely due to increased food intake. Based on an estimate of change in energy intake judged to be more reliable (i.e. in the same study population) and together with calculations of simple energetic indices, our analysis suggests that conclusions about the fundamental causes of obesity development in a population (excess intake vs. low physical activity or both) is clouded by a high level of uncertainty.

Probabilistic evidential assessment of gunshot residue particle evidence (Part I): likelihood ratio calculation and case pre-assessment using Bayesian networks

Well developed experimental procedures currently exist for retrieving and analyzing particle evidence from hands of individuals suspected of being associated with the discharge of a firearm. Although analytical approaches (e.g. automated Scanning Electron Microscopy with Energy Dispersive X-ray (SEM-EDS) microanalysis) allow the determination of the presence of elements typically found in gunshot residue (GSR) particles, such analyses provide no information about a given particle's actual source. Possible origins for which scientists may need to account for are a primary exposure to the discharge of a firearm or a secondary transfer due to a contaminated environment. In order to approach such sources of uncertainty in the context of evidential assessment, this paper studies the construction and practical implementation of graphical probability models (i.e. Bayesian networks). These can assist forensic scientists in making the issue tractable within a probabilistic perspective. The proposed models focus on likelihood ratio calculations at various levels of detail as well as case pre-assessment.

Dissociation between components of spatial memory in rats after recovery from the effects of retrohippocampal lesions

A series of 4 experiments examined the performance of rats with retrohippocampal lesions on a spatial water-maze task. The animals were trained to find and escape onto a hidden platform after swimming in a large pool of opaque water. The platform was invisible and could not be located using olfactory cues. Successful escape performance required the rats to develop strategies of approaching the correct location with reference solely to distal extramaze cues. The lesions encompassed the entire rostro-caudal extent of the lateral and medial entorhinal cortex, and included parts of the pre- and para-subiculum, angular bundle and subiculum. Groups ECR 1 and 2 sustained only partial damage of the subiculum, while Group ECR+S sustained extensive damage. These groups were compared with sham-lesion and unoperated control groups. In Expt 1A, a profound deficit in spatial localisation was found in groups ECR 1 and ECR+S, the rats receiving all training postoperatively. In Expt 1B, these two groups showed hyperactivity in an open-field. In Expt 2, extensive preoperative training caused a transitory saving in performance of the spatial task by group ECR 2, but comparisons with the groups of Expt 1A revealed no sustained improvement, except on one measure of performance in a post-training transfer test. All rats were then given (Expt 3) training on a cueing procedure using a visible platform. The spatial deficit disappeared but, on returning to the normal hidden platform procedure, it reappeared. Nevertheless, a final transfer test, during which the platform was removed from the apparatus, revealed a dissociation between two independent measures of performance: the rats with ECR lesions failed to search for the hidden platform but repeatedly crossed its correct location accurately during traverses of the entire pool. This partial recovery of performance was not (Expt 4) associated with any ability to discriminate between two locations in the pool. The apparently selective recovery of aspects of spatial memory is discussed in relation to O'Keefe and Nadel's (1978) spatial mapping theory of hippocampal function. We propose a modification of the theory in terms of a dissociation between procedural and declarative subcomponents of spatial memory. The declarative component is a flexible access system in which information is stored in a form independent of action. It is permanently lost after the lesion. The procedural component is "unmasked" by the retrohippocampal lesion giving rise to the partial recovery of spatial localisation performance.

Ego identity in adolescence: preliminary validation of a French short-form of the EIPQ

Following the seminal work on personal identity of Erikson, Marcia's identity status model has been one of the most enduring paradigms. The Ego Identity Process Questionnaire (EIPQ; Balistreri, Busch-Rossnagel, & Geissinger, 1995) is a widely used measure of identity status. The purpose of this study was to evaluate the factor structure and the reliability of a French version of the EIPQ. The hypothesized structures were not confirmed. In light of the failed attempts to validate the original version, an alternative short-form version of the EIPQ (EIPQ-SF), maintaining the integrity of the original model, was developed in one sample and cross-validated in another sample. Additionally, theoretically consistent associations between the EIPQ-SF dimensions and self-esteem confirmed convergent validity. Globally, the results indicated that the French short-version of the EIPQ might be a useful instrument for the assessment of the identity statuses in adolescence and emerging adulthood.