Heel and toe clearance estimation for gait analysis using wireless inertial sensors.

Tripping is considered a major cause of fall in older people. Therefore, foot clearance (i.e., height of the foot above ground during swing phase) could be a key factor to better understand the complex relationship between gait and falls. This paper presents a new method to estimate clearance using a foot-worn and wireless inertial sensor system. The method relies on the computation of foot orientation and trajectory from sensors signal data fusion, combined with the temporal detection of toe-off and heel-strike events. Based on a kinematic model that automatically estimates sensor position relative to the foot, heel and toe trajectories are estimated. 2-D and 3-D models are presented with different solving approaches, and validated against an optical motion capture system on 12 healthy adults performing short walking trials at self-selected, slow, and fast speed. Parameters corresponding to local minimum and maximum of heel and toe clearance were extracted and showed accuracy ± precision of 4.1 ± 2.3 cm for maximal heel clearance and 1.3 ± 0.9 cm for minimal toe clearance compared to the reference. The system is lightweight, wireless, easy to wear and to use, and provide a new and useful tool for routine clinical assessment of gait outside a dedicated laboratory.

A program for the computation of power and determination of sample size in hierarchical experimental designs.

We have devised a program that allows computation of the power of F-test, and hence determination of appropriate sample and subsample sizes, in the context of the one-way hierarchical analysis of variance with fixed effects. The power at a fixed alternative is an increasing function of the sample size and of the subsample size. The program makes it easy to obtain the power of F-test for a range of values of sample and subsample sizes, and therefore the appropriate sizes based on a desired power. The program can be used for the 'ordinary' case of the one-way analysis of variance, as well as for hierarchical analysis of variance with two stages of sampling. Examples are given of the practical use of the program.

The use of heterogeneous chemistry for the characterization of functional groups at the gas/particle interface of soot and TiO(2) nanoparticles

Six gases (N((CH3)3), NH2OH, CF3COOH, HCl, NO2, O3) were selected to probe the surface of seven combustion aerosol (amorphous carbon, flame soot) and three types of TiO2 nanoparticles using heterogeneous, that is gas-surface reactions. The gas uptake to saturation of the probes was measured under molecular flow conditions in a Knudsen flow reactor and expressed as a density of surface functional groups on a particular aerosol, namely acidic (carboxylic) and basic (conjugated oxides such as pyrones, N-heterocycles) sites, carbonyl (R1-C(O)-R2) and oxidizable (olefinic, -OH) groups. The limit of detection was generally well below 1% of a formal monolayer of adsorbed probe gas. With few exceptions most investigated aerosol samples interacted with all probe gases which points to the coexistence of different functional groups on the same aerosol surface such as acidic and basic groups. Generally, the carbonaceous particles displayed significant differences in surface group density: Printex 60 amorphous carbon had the lowest density of surface functional groups throughout, whereas Diesel soot recovered from a Diesel particulate filter had the largest. The presence of basic oxides on carbonaceous aerosol particles was inferred from the ratio of uptakes of CF3COOH and HCl owing to the larger stability of the acetate compared to the chloride counterion in the resulting pyrylium salt. Both soots generated from a rich and a lean hexane diffusion flame had a large density of oxidizable groups similar to amorphous carbon FS 101. TiO2 15 had the lowest density of functional groups among the three studied TiO2 nanoparticles for all probe gases despite the smallest size of its primary particles. The used technique enabled the measurement of the uptake probability of the probe gases on the various supported aerosol samples. The initial uptake probability, g0, of the probe gas onto the supported nanoparticles differed significantly among the various investigated aerosol samples but was roughly correlated with the density of surface groups, as expected. [Authors]

ABCtoolbox: a versatile toolkit for approximate Bayesian computations.

BACKGROUND: The estimation of demographic parameters from genetic data often requires the computation of likelihoods. However, the likelihood function is computationally intractable for many realistic evolutionary models, and the use of Bayesian inference has therefore been limited to very simple models. The situation changed recently with the advent of Approximate Bayesian Computation (ABC) algorithms allowing one to obtain parameter posterior distributions based on simulations not requiring likelihood computations. RESULTS: Here we present ABCtoolbox, a series of open source programs to perform Approximate Bayesian Computations (ABC). It implements various ABC algorithms including rejection sampling, MCMC without likelihood, a Particle-based sampler and ABC-GLM. ABCtoolbox is bundled with, but not limited to, a program that allows parameter inference in a population genetics context and the simultaneous use of different types of markers with different ploidy levels. In addition, ABCtoolbox can also interact with most simulation and summary statistics computation programs. The usability of the ABCtoolbox is demonstrated by inferring the evolutionary history of two evolutionary lineages of Microtus arvalis. Using nuclear microsatellites and mitochondrial sequence data in the same estimation procedure enabled us to infer sex-specific population sizes and migration rates and to find that males show smaller population sizes but much higher levels of migration than females. CONCLUSION: ABCtoolbox allows a user to perform all the necessary steps of a full ABC analysis, from parameter sampling from prior distributions, data simulations, computation of summary statistics, estimation of posterior distributions, model choice, validation of the estimation procedure, and visualization of the results.

Particle exposure scenarios for research and production activities involving nanomaterials

Nanomaterials with structures in the nanoscale (1 to 100 nm) often have chemical, physical and bioactive characteristics different from those of larger entities of the same material. This is interesting for industry but raises questions about the health of exposed people. However, little is known so far about the exposure of workers to inhalable airborne nanomaterials. We investigated several activities in research laboratories and industry to learn about relevant exposure scenarios. Work process analyses were combined with measurements of airborne particle mass concentrations and number−size distributions. Background levels in research settings were mostly low, while in industrial production, levels were sometimes elevated, especially in halls near busy roads or in the presence of diesel fork lifts without particle filters. Peak levels were found in an industrial setting dealing with powders (up to 80,000 particles/cm³ and up to 15 mg/m³). Mostly low concentrations were found for activities involving liquid applications. However, centrifugation and lyophilization of nanoparticle containing solutions resulted in very high particle number concentrations (up to 300,000 particles/cm³), whereas no increases were seen for the same activities conducted with nanoparticle−free liquids. No significant increases of particle concentrations were found for processes involving nanoparticles bound to surfaces. Also no increases were observed in laboratories that were visualizing properties and structures of small amounts of nanomaterials. Conclusion: When studying exposure scenarios for airborne nanomaterials, the focus should not only be on processes involving nano−powders, but also on processes involving intensively treated nanoparticle−containing liquids. Acknowledgement: We thank Chantal Imhof, MSc and Guillaume Ferraris, MSc for their contributions.

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.

Fluorescence flow cytometer to determine urine particle reference intervals in doping control samples.

Background: Urine is still the matrix of choice to fight against doping, because it can be collected non-invasively during anti-doping tests. Most of the World Anti-Doping Agency's accredited laboratories have more than 20 years experience in analyzing this biological fluid and the majority of the compounds listed in the 2010 Prohibited List - International Standard are eliminated through the urinary apparatus. Storing and transporting urine samples for doping analyses does not include a specific protocol to prevent microbial and thermal degradation. The use of a rapid and reliable screening method could enable determine reference intervals for urine specimens in doping control samples and evaluate notably the prevalence of microbial contamination known to be responsible for the degradation of chemical substances in urine.Methods: The Sysmex(R) UF-500i is a recent urine flow cytometer analyzer capable of quantifying BACT and other urinary particles such as RBC, WBC, EC, DEBRIS, CAST, PATH. CAST, YLC, SRC as well as measuring urine conductivity. To determine urine anti-doping reference intervals, 501 samples received in our laboratory over a period of two months were submitted to an immediate examination. All samples were collected and then transported at room temperature. Analysis of variance was performed to test the effects of factors such as gender, test type [in-competition, out-of-competition] and delivery time.Results: The data obtained showed that most of the urine samples were highly contaminated with bacteria. The other urine particles were also very different according to the factors.Conclusions: The Sysmex(R) UF-500i was capable of providing a snapshot of urine particles present in the samples at the time of the delivery to the laboratory. These particles, BACT in particular, gave a good idea of the possible microbial degradation which had and/or could have occurred in the sample. This information could be used as the first quality control set up in WADA (World Anti-Doping Agency) accredited laboratories to determine if steroid profiles, endogenous and prohibited substances have possibly been altered. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

Wheat alleles introgress into selfing wild relatives: empirical estimates from approximate Bayesian computation in Aegilops triuncialis.

Extensive gene flow between wheat (Triticum sp.) and several wild relatives of the genus Aegilops has recently been detected despite notoriously high levels of selfing in these species. Here, we assess and model the spread of wheat alleles into natural populations of the barbed goatgrass (Aegilops triuncialis), a wild wheat relative prevailing in the Mediterranean flora. Our sampling, based on an extensive survey of 31 Ae. triuncialis populations collected along a 60 km × 20 km area in southern Spain (Grazalema Mountain chain, Andalousia, totalling 458 specimens), is completed with 33 wheat cultivars representative of the European domesticated pool. All specimens were genotyped with amplified fragment length polymorphism with the aim of estimating wheat admixture levels in Ae. triuncialis populations. This survey first confirmed extensive hybridization and backcrossing of wheat into the wild species. We then used explicit modelling of populations and approximate Bayesian computation to estimate the selfing rate of Ae. triuncialis along with the magnitude, the tempo and the geographical distance over which wheat alleles introgress into Ae. triuncialis populations. These simulations confirmed that extensive introgression of wheat alleles (2.7 × 10(-4) wheat immigrants for each Ae. triuncialis resident, at each generation) into Ae. triuncialis occurs despite a high selfing rate (Fis ≈ 1 and selfing rate = 97%). These results are discussed in the light of risks associated with the release of genetically modified wheat cultivars in Mediterranean agrosystems.

Causal Warrant for Realism about Particle Physics

While scientific realism generally assumes that successful scientific explanations yield information about reality, realists also have to admit that not all information acquired in this way is equally well warranted. Some versions of scientific realism do this by saying that explanatory posits with which we have established some kind of causal contact are better warranted than those that merely appear in theoretical hypotheses. I first explicate this distinction by considering some general criteria that permit us to distinguish causal warrant from theoretical warrant. I then apply these criteria to a specific case from particle physics, claiming that scientific realism has to incorporate the distinction between causal and theoretical warrant if it is to be an adequate stance in the philosophy of particle physics.

Nano-particle vaccination combined with TLR-7 and -9 ligands triggers memory and effector CD8⁺ T-cell responses in melanoma patients.

Optimal vaccine strategies must be identified for improving T-cell vaccination against infectious and malignant diseases. MelQbG10 is a virus-like nano-particle loaded with A-type CpG-oligonucleotides (CpG-ODN) and coupled to peptide(16-35) derived from Melan-A/MART-1. In this phase IIa clinical study, four groups of stage III-IV melanoma patients were vaccinated with MelQbG10, given (i) with IFA (Montanide) s.c.; (ii) with IFA s.c. and topical Imiquimod; (iii) i.d. with topical Imiquimod; or (iv) as intralymph node injection. In total, 16/21 (76%) patients generated ex vivo detectable Melan-A/MART-1-specific T-cell responses. T-cell frequencies were significantly higher when IFA was used as adjuvant, resulting in detectable T-cell responses in all (11/11) patients, with predominant generation of effector-memory-phenotype cells. In turn, Imiquimod induced higher proportions of central-memory-phenotype cells and increased percentages of CD127(+) (IL-7R) T cells. Direct injection of MelQbG10 into lymph nodes resulted in lower T-cell frequencies, associated with lower proportions of memory and effector-phenotype T cells. Swelling of vaccine site draining lymph nodes, and increased glucose uptake at PET/CT was observed in 13/15 (87%) of evaluable patients, reflecting vaccine triggered immune reactions in lymph nodes. We conclude that the simultaneous use of both Imiquimod and CpG-ODN induced combined memory and effector CD8(+) T-cell responses.