Advances in Sequence Analysis: Theory, Methods, Applications

This book gives a general view of sequence analysis, the statistical study of successions of states or events. It includes innovative contributions on life course studies, transitions into and out of employment, contemporaneous and historical careers, and political trajectories. The approach presented in this book is now central to the life-course perspective and the study of social processes more generally. This volume promotes the dialogue between approaches to sequence analysis that developed separately, within traditions contrasted in space and disciplines. It includes the latest developments in sequential concepts, coding, atypical datasets and time patterns, optimal matching and alternative algorithms, survey optimization, and visualization. Field studies include original sequential material related to parenting in 19th-century Belgium, higher education and work in Finland and Italy, family formation before and after German reunification, French Jews persecuted in occupied France, long-term trends in electoral participation, and regime democratization. Overall the book reassesses the classical uses of sequences and it promotes new ways of collecting, formatting, representing and processing them. The introduction provides basic sequential concepts and tools, as well as a history of the method. Chapters are presented in a way that is both accessible to the beginner and informative to the expert.

Postmortem angiography: review of former and current methods.

OBJECTIVE: Postmortem investigations are becoming more and more sophisticated. CT and MRI are already being used in pathology and forensic medicine. In this context, the impact of postmortem angiography increases because of the rapid evaluation of organ-specific vascular patterns, vascular alteration under pathologic and physiologic conditions, and tissue changes induced by artificial and unnatural causes. CONCLUSION: In this article, the advantages and disadvantages of former and current techniques and contrast agents are reviewed.

Free-living energy expenditure assessed by two different methods in rural Gambian men.

OBJECTIVE: To assess total free-living energy expenditure (EE) in Gambian farmers with two independent methods, and to determine the most realistic free-living EE and physical activity in order to establish energy requirements for rural populations in developing countries. DESIGN: In this cross-sectional study two methods were applied at the same time. SETTING: Three rural villages and Dunn Nutrition Centre Keneba, MRC, The Gambia. SUBJECTS: Eight healthy, male subjects were recruited from three rural Gambian villages in the sub-Sahelian area (age: 25 +/- 4y; weight: 61.2 +/- 10.1 kg; height: 169.5 +/- 6.5 cm, body mass index: 21.2 +/- 2.5 kg/m2). INTERVENTION: We assessed free-living EE with two inconspicuous and independent methods: the first one used doubly labeled water (DLW) (2H2 18O) over a period of 12 days, whereas the second one was based on continuous heart rate (HR) measurements on two to three days using individual regression lines (HR vs EE) established by indirect calorimetry in a respiration chamber. Isotopic dilution of deuterium (2H2O) was also used to assess total body water and hence fat-free mass (FFM). RESULTS: EE assessed by DLW was found to be 3880 +/- 994 kcal/day (16.2 +/- 4.2 MJ/day). Expressed per unit body weight the EE averaged 64.2 +/- 9.3 kcal/kg/d (269 +/- 38 kJ/kg/d). These results were consistent with the EE results assessed by HR: 3847 +/- 605 kcal/d (16.1 +/- 2.5 MJ/d) or 63.4 +/- 8.2 kcal/kg/d (265 +/- 34kJ/kg/d). Physical activity index, expressed as a multiple of basal metabolic rate (BMR), averaged 2.40 +/- 0.41 (DLW) or 2.40 +/- 0.28 (HR). CONCLUSIONS: These findings suggest an extremely high level of physical activity in Gambian men during intense agricultural work (wet season). This contrasts with the relative food shortage, previously reported during the harvesting period. We conclude that the assessment of EE during the agricultural season in non-industrialized countries needs further investigations in order to obtain information on the energy requirement of these populations. For this purpose the use of the DLW and HR methods have been shown to be useful and complementary.

Implementing statistical learning methods through Bayesian networks (Part 2): bayesian evaluations for results of black toner analyses in forensic document examination

This paper presents and discusses the use of Bayesian procedures - introduced through the use of Bayesian networks in Part I of this series of papers - for 'learning' probabilities from data. The discussion will relate to a set of real data on characteristics of black toners commonly used in printing and copying devices. Particular attention is drawn to the incorporation of the proposed procedures as an integral part in probabilistic inference schemes (notably in the form of Bayesian networks) that are intended to address uncertainties related to particular propositions of interest (e.g., whether or not a sample originates from a particular source). The conceptual tenets of the proposed methodologies are presented along with aspects of their practical implementation using currently available Bayesian network software.

Activities of daily living with reverse prostheses: importance of scapular compensation for functional mobility of the shoulder.

HYPOTHESIS: The nonanatomical design of reverse shoulder prostheses induce medial displacement of the center of rotation, impingements and may reduce the mobility of the shoulder. The aim of this study is to test the hypothesis that during activities of daily living functional mobility of the shoulder can be restored by scapular compensation. MATERIAL AND METHODS: A numerical 3-dimensional model was developed to reproduce the movement of the scapula and humerus, during 4 activities of daily living measured experimentally. This hypothesis was tested in 4 configurations of the aequalis reverse prosthesis (standard 36-mm glenosphere, 42-mm glenosphere, lateralized 36-mm glenosphere, lateralized Bony Increased-Offset Reverse Shoulder Arthroplasty [BIO-RSA]), which were implanted in the virtual model. All impingement positions were evaluated, as the required scapular compensation to avoid impingements. RESULTS: With the 36-mm glenosphere, impingements occurred only for rest of hand to back-pocket positions. The 42-mm partly improved the mobility. The 2 lateralized glenospheres were free of impingement. When impingements occurred, the scapular compensation was less than 10°. CONCLUSION: Most reverse prostheses impingements reported in clinical and biomechanical studies can be avoided, either by scapular compensation or by a glenosphere lateralization. After reverse shoulder arthroplasty, a fraction of the mobility of the gleno-humeral is transferred to the scapulo-thoracic joint.

Ambulatory monitoring of physical activities in patients with Parkinson's disease.

A new ambulatory method of monitoring physical activities in Parkinson's disease (PD) patients is proposed based on a portable data-logger with three body-fixed inertial sensors. A group of ten PD patients treated with subthalamic nucleus deep brain stimulation (STN-DBS) and ten normal control subjects followed a protocol of typical daily activities and the whole period of the measurement was recorded by video. Walking periods were recognized using two sensors on shanks and lying periods were detected using a sensor on trunk. By calculating kinematics features of the trunk movements during the transitions between sitting and standing postures and using a statistical classifier, sit-to-stand (SiSt) and stand-to-sit (StSi) transitions were detected and separated from other body movements. Finally, a fuzzy classifier used this information to detect periods of sitting and standing. The proposed method showed a high sensitivity and specificity for the detection of basic body postures allocations: sitting, standing, lying, and walking periods, both in PD patients and healthy subjects. We found significant differences in parameters related to SiSt and StSi transitions between PD patients and controls and also between PD patients with and without STN-DBS turned on. We concluded that our method provides a simple, accurate, and effective means to objectively quantify physical activities in both normal and PD patients and may prove useful to assess the level of motor functions in the latter.

A hierarchical approach to model parameter optimization for developmental systems.

In the context of Systems Biology, computer simulations of gene regulatory networks provide a powerful tool to validate hypotheses and to explore possible system behaviors. Nevertheless, modeling a system poses some challenges of its own: especially the step of model calibration is often difficult due to insufficient data. For example when considering developmental systems, mostly qualitative data describing the developmental trajectory is available while common calibration techniques rely on high-resolution quantitative data. Focusing on the calibration of differential equation models for developmental systems, this study investigates different approaches to utilize the available data to overcome these difficulties. More specifically, the fact that developmental processes are hierarchically organized is exploited to increase convergence rates of the calibration process as well as to save computation time. Using a gene regulatory network model for stem cell homeostasis in Arabidopsis thaliana the performance of the different investigated approaches is evaluated, documenting considerable gains provided by the proposed hierarchical approach.

Kernel-based methods for change detection in remote sensing images

Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.

Body composition: overview of methods and future directions of research.

A short overview is given on the most important analytical body composition methods. Principles of the methods and advantages and limitations of the methods are discussed also in relation to other fields of research such as energy metabolism. Attention is given to some new developments in body composition research such as chemical multiple-compartment models, computerized tomography or nuclear magnetic resonance imaging (tissue level), and multifrequency bioelectrical impedance. Possible future directions of body composition research in the light of these new developments are discussed.

Direct and indirect root defences of milkweed (Asclepias syriaca): trophic cascades, trade-offs and novel methods for studying subterranean herbivory

P>1. Entomopathogenic nematodes can function as indirect defence for plants that are attacked by root herbivores. By releasing volatile organic compounds (VOCs), plants signal the presence of host insects and thereby attract nematodes.2. Nonetheless, how roots deploy indirect defences, how indirect defences relate to direct defences, and the ecological consequences of root defence allocation for herbivores and plant biomass are essentially unknown.3. We investigate a natural below-ground tritrophic system, involving common milkweed, a specialist root-boring beetle and entomopathogenic nematodes, and asked whether there is a negative genetic correlation between direct defences (root cardenolides) and indirect defences (emission of volatiles in the roots and nematode attraction), and between constitutive and inducible defences.4. Volatiles of roots were analysed using two distinct sampling methods. First, we collected emissions from living Asclepias syriaca roots by dynamic headspace sampling. This method showed that attacked A. syriaca plants emit five times higher levels of volatiles than control plants. Secondly, we used a solid phase micro-extraction (SPME) method to sample the full pool of volatiles in roots for genetic correlations of volatile biosynthesis.5. Field experiments showed that entomopathogenic nematodes prevent the loss of biomass to root herbivory. Additionally, suppression of root herbivores was mediated directly by cardenolides and indirectly by the attraction of nematodes. Genetic families of plants with high cardenolides benefited less from nematodes compared to low-cardenolide families, suggesting that direct and indirect defences may be redundant. Although constitutive and induced root defences traded off within each strategy (for both direct and indirect defence, cardenolides and VOCs, respectively), we found no trade-off between the two strategies.6. Synthesis. Constitutive expression and inducibility of defences may trade off because of resource limitation or because they are redundant. Direct and indirect defences do not trade off, likely because they may not share a limiting resource and because independently they may promote defence across the patchiness of herbivore attack and nematode presence in the field. Indeed, some redundancy in strategies may be necessary to increase effective defence, but for each strategy, an economy of deployment reduces overall costs.