A comparative study of two methods of surgical treatment for painful neuroma.

Painful neuromas may follow traumatic nerve injury. We carried out a double-blind controlled trial in which patients with a painful neuroma of the lower limb (n = 20) were randomly assigned to treatment by resection of the neuroma and translocation of the proximal nerve stump into either muscle tissue or an adjacent subcutaneous vein. Translocation into a vein led to reduced intensity of pain as assessed by visual analogue scale (5.8 (SD 2.7) vs 3.8 (SD 2.4); p < 0.01), and improved sensory, affective and evaluative dimensions of pain as assessed by the McGill pain score (33 (SD 18) vs 14 (SD 12); p < 0.01). This was associated with an increased level of activity (p < 0.01) and improved function (p < 0.01). Transposition of the nerve stump into an adjacent vein should be preferred to relocation into muscle.

Clustering compositional data trajectories

Our essay aims at studying suitable statistical methods for the clustering ofcompositional data in situations where observations are constituted by trajectories ofcompositional data, that is, by sequences of composition measurements along a domain.Observed trajectories are known as “functional data” and several methods have beenproposed for their analysis.In particular, methods for clustering functional data, known as Functional ClusterAnalysis (FCA), have been applied by practitioners and scientists in many fields. To ourknowledge, FCA techniques have not been extended to cope with the problem ofclustering compositional data trajectories. In order to extend FCA techniques to theanalysis of compositional data, FCA clustering techniques have to be adapted by using asuitable compositional algebra.The present work centres on the following question: given a sample of compositionaldata trajectories, how can we formulate a segmentation procedure giving homogeneousclasses? To address this problem we follow the steps described below.First of all we adapt the well-known spline smoothing techniques in order to cope withthe smoothing of compositional data trajectories. In fact, an observed curve can bethought of as the sum of a smooth part plus some noise due to measurement errors.Spline smoothing techniques are used to isolate the smooth part of the trajectory:clustering algorithms are then applied to these smooth curves.The second step consists in building suitable metrics for measuring the dissimilaritybetween trajectories: we propose a metric that accounts for difference in both shape andlevel, and a metric accounting for differences in shape only.A simulation study is performed in order to evaluate the proposed methodologies, usingboth hierarchical and partitional clustering algorithm. The quality of the obtained resultsis assessed by means of several indices

The alcohol purchase task in young men from the general population.

BACKGROUND: The alcohol purchase task (APT), which presents a scenario and asks participants how many drinks they would purchase and consume at different prices, has been used among students and small clinical samples to obtain measures of alcohol demand but not in large, general population samples. METHODS: We administered the APT to a large sample of young men from the general population (Cohort Study on Substance Use Risk Factors). Participants who reported drinking in the past year (n=4790), reported on past 12 months alcohol use, on DSM-5 alcohol use disorder (AUD) criteria and on alcohol related consequences were included. RESULTS: Among the APT's demand parameters, intensity was 8.7 (SD=6.5) indicating that, when drinks are free, participants report a planned consumption of almost 9 drinks. The maximum alcohol expenditure (Omax) was over 35CHF (1CHF=1.1USD) and the demand became elastic (Pmax) at 8.4CHF (SD=5.6). The mean price at which the consumption was suppressed was 15.6CHF (SD=5.4). Exponential equation provided a satisfactory fit to individual responses (mean R(2): 0.8, median: 0.8). Demand intensity was correlated with alcohol use, number of AUD criteria and number of consequences (all r≥0.3, p<0.0001). Omax was correlated with alcohol use (p<0.0001). The elasticity parameter was weakly correlated with alcohol use in the expected direction. CONCLUSION: The APT measures are useful in characterizing demand for alcohol in young men in the general population. Demand may provide a clinically useful index of strength of motivation for alcohol use in general population samples.

Decision Support Methods for Global Optomization

Immobile location-allocation (LA) problems is a type of LA problem that consists in determining the service each facility should offer in order to optimize some criterion (like the global demand), given the positions of the facilities and the customers. Due to the complexity of the problem, i.e. it is a combinatorial problem (where is the number of possible services and the number of facilities) with a non-convex search space with several sub-optimums, traditional methods cannot be applied directly to optimize this problem. Thus we proposed the use of clustering analysis to convert the initial problem into several smaller sub-problems. By this way, we presented and analyzed the suitability of some clustering methods to partition the commented LA problem. Then we explored the use of some metaheuristic techniques such as genetic algorithms, simulated annealing or cuckoo search in order to solve the sub-problems after the clustering analysis

Endometriosis: alternative methods of medical treatment.

Endometriosis is an inflammatory estrogen-dependent disease defined by the presence of endometrial glands and stroma at extrauterine sites. The main purpose of endometriosis management is alleviating pain associated to the disease. This can be achieved surgically or medically, although in most women a combination of both treatments is required. Long-term medical treatment is usually needed in most women. Unfortunately, in most cases, pain symptoms recur between 6 months and 12 months once treatment is stopped. The authors conducted a literature search for English original articles, related to new medical treatments of endometriosis in humans, including articles published in PubMed, Medline, and the Cochrane Library. Keywords included "endometriosis" matched with "medical treatment", "new treatment", "GnRH antagonists", "Aromatase inhibitors", "selective progesterone receptor modulators", "anti-TNF α", and "anti-angiogenic factors". Hormonal treatments currently available are effective in the relief of pain associated to endometriosis. Among new hormonal drugs, association to aromatase inhibitors could be effective in the treatment of women who do not respond to conventional therapies. GnRH antagonists are expected to be as effective as GnRH agonists, but with easier administration (oral). There is a need to find effective treatments that do not block the ovarian function. For this purpose, antiangiogenic factors could be important components of endometriosis therapy in the future. Upcoming researches and controlled clinical trials should focus on these drugs.

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.

Anastomotic longitudinal stress due to modification of arterial longitudinal properties after anastomosis.

BACKGROUND: In our hands, in vivo segmental vessel length changes up to 5% because of blood pressure: increasing in arterial pressure is associated to decrease in segmental vessel length. METHODS AND MATERIAL: Using two piezoelectric crystals sutured on vessel wall and a high fidelity pressure probe, we recorded artery length variations as function of blood pressure, before and after an end-to-end anastomosis on four pigs carotid arteries. RESULTS: Mean arterial pressure before anastomosis = 73 mmHg (+/- 12); mean arterial pressure after anastomosis = 91 mmHg (+/- 14); mean crystals displacement before anastomosis during systole = -0.21 mm; mean crystals displacement after anastomosis during systole = +0.24 mm; mean distance between crystals before anastomosis = 12.3 mm (+/- 0.8) and after anastomosis = 11.2 mm (+/- 0.5). CONCLUSIONS: In the acute phase following an end-to-end anastomosis, an increase in blood pressure causes increasing in vessel length, with an exponential correlation. The anastomosis is constantly subjected to a longitudinal traction whose magnitude depends on blood pressure.

Portafolio selection with skewness: a comparison of methods and a generalized two fund separation result

This contribution compares existing and newly developed techniques for geometrically representing mean-variances-kewness portfolio frontiers based on the rather widely adapted methodology of polynomial goal programming (PGP) on the one hand and the more recent approach based on the shortage function on the other hand. Moreover, we explain the working of these different methodologies in detail and provide graphical illustrations. Inspired by these illustrations, we prove a generalization of the well-known two fund separation theorem from traditionalmean-variance portfolio theory.

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.

Evaluation of four whole-plant inoculation methods to analyze the pathogenicity of Erwinia amylovora under quarantine conditions

Four methods were tested to assess the fire-blight disease response on grafted pear plants. The leaves of the plants were inoculated with Erwinia amylovora suspensions by pricking with clamps, cutting with scissors, local infiltration, and painting a bacterial suspension onto the leaves with a paintbrush. The effects of the inoculation methods were studied in dose-time-response experiments carried out in climate chambers under quarantine conditions. A modified Gompertz model was used to analyze the disease-time relatiobbnships and provided information on the rate of infection progression (rg) and time delay to the start of symptoms (t0). The disease-pathogen-dose relationships were analyzed according to a hyperbolic saturation model in which the median effective dose (ED50) of the pathogen and maximum disease level (ymax) were determined. Localized infiltration into the leaf mesophile resulted in the early (short t0) but slow (low rg) development of infection whereas in leaves pricked with clamps disease symptoms developed late (long t0) but rapidly (high rg). Paintbrush inoculation of the plants resulted in an incubation period of medium length, a moderate rate of infection progression, and low ymax values. In leaves inoculated with scissors, fire-blight symptoms developed early (short t0) and rapidly (high rg), and with the lowest ED50 and the highest ymax

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.

A comparative analysis of two methods for the calculation of electric-field-induced perturbations to molecular vibration

Two common methods of accounting for electric-field-induced perturbations to molecular vibration are analyzed and compared. The first method is based on a perturbation-theoretic treatment and the second on a finite-field treatment. The relationship between the two, which is not immediately apparent, is made by developing an algebraic formalism for the latter. Some of the higher-order terms in this development are documented here for the first time. As well as considering vibrational dipole polarizabilities and hyperpolarizabilities, we also make mention of the vibrational Stark effec