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]

Examination of Heterogeneous Crossing Sequences Between Toner and Rollerball Pen Strokes by Digital Microscopy and 3-D Laser Profilometry

The determination of line crossing sequences between rollerball pens and laser printers presents difficulties that may not be overcome using traditional techniques. This research aimed to study the potential of digital microscopy and 3-D laser profilometry to determine line crossing sequences between a toner and an aqueous ink line. Different paper types, rollerball pens, and writing pressure were tested. Correct opinions of the sequence were given for all case scenarios, using both techniques. When the toner was printed before the ink, a light reflection was observed in all crossing specimens, while this was never observed in the other sequence types. The 3-D laser profilometry, more time-consuming, presented the main advantage of providing quantitative results. The findings confirm the potential of the 3-D laser profilometry and demonstrate the efficiency of digital microscopy as a new technique for determining the sequence of line crossings involving rollerball pen ink and toner. With the mass marketing of laser printers and the popularity of rollerball pens, the determination of line crossing sequences between such instruments is encountered by forensic document examiners. This type of crossing presents difficulties with optical microscopic line crossing techniques involving ballpoint pens or gel pens and toner (1-4). Indeed, the rollerball's aqueous ink penetrates through the toner and is absorbed by the fibers of the paper, leaving the examiner with the impression that the toner is above the ink even when it is not (5). Novotny and Westwood (3) investigated the possibility of determining aqueous ink and toner crossing sequences by microscopic observation of the intersection before and after toner removal. A major disadvantage of their study resides in destruction of the sample by scraping off the toner line to see what was underneath. The aim of this research was to investigate the ways to overcome these difficulties through digital microscopy and three-dimensional (3-D) laser profilometry. The former was used as a technique for the determination of sequences between gel pen and toner printing strokes, but provided less conclusive results than that of an optical stereomicroscope (4). 3-D laser profilometry, which allows one to observe and measure the topography of a surface, has been the subject of a number of recent studies in this area. Berx and De Kinder (6) and Schirripa Spagnolo (7,8) have tested the application of laser profilometry to determine the sequence of intersections of several lines. The results obtained in these studies overcome disadvantages of other methods applied in this area, such as scanning electron microscope or the atomic force microscope. The main advantages of 3-D laser profilometry include the ease of implementation of the technique and its nondestructive nature, which does not require sample preparation (8-10). Moreover, the technique is reproducible and presents a high degree of freedom in the vertical axes (up to 1000 μm). However, when the paper surface presents a given roughness, if the pen impressions alter the paper with a depth similar to the roughness of medium, the results are not always conclusive (8). It becomes difficult in this case to distinguish which characteristics can be imputed to the pen impressions or the quality of the paper surface. This important limitation is assessed by testing different types of paper of variable quality (of different grammage and finishing) and the writing pressure. The authors will therefore assess the limits of 3-D laser profilometry technique and determine whether the method can overcome such constraints. Second, the authors will investigate the use of digital microscopy because it presents a number of advantages: it is efficient, user-friendly, and provides an objective evaluation and interpretation.

Stochastic models and numerical algorithms for a class of regulatory gene networks.

Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

Invasion and eradication of a competitively superior species in heterogeneous landscapes

The effect of heterogeneous environments upon the dynamics of invasion and the eradication or control of invasive species is poorly understood, although it is a major challenge for biodiversity conservation. Here, we first investigate how the probability and time for invasion are affected by spatial heterogeneity. Then, we study the effect of control program strategies (e.g. species specificity, spatial scale of action, detection and eradication efficiency) on the success and time of eradication. We find that heterogeneity increases both the invasion probability and the time to invasion. Heterogeneity also reduces the probability of eradication but does not change the time taken for successful eradication. We confirm that early detection of invasive species reduces the time until eradication, but we also demonstrate that this is true only if the local control action is sufficiently efficient. The criterion of removal efficiency is even more important for an eradication program than simply ensuring control effort when the invasive species is not abundant.

Does the generalist parasitic plant Cuscuta campestris selectively forage in heterogeneous plant communities?

Cuscuta spp. are holoparasitic plants that can simultaneously parasitise several host plants. It has been suggested that Cuscuta has evolved a foraging strategy based on a positive relationship between preuptake investment and subsequent reward on different host species. Here we establish reliable parasite size measures and show that parasitism on individuals of different host species alters the biomass of C. campestris but that within host species size and age also contributes to the heterogeneous resource landscape. We then performed two additional experiments to test whether C. campestris achieves greater resource acquisition by parasitising two host species rather than one and whether C. campestris forages in communities of hosts offering different rewards (a choice experiment). There was no evidence in either experiment for direct benefits of a mixed host diet. Cuscuta campestris foraged by parasitising the most rewarding hosts the fastest and then investing the most on them. We conclude that our data present strong evidence for foraging in the parasitic plant C. campestris.

CleanEx: a database of heterogeneous gene expression data based on a consistent gene nomenclature.

The main goal of CleanEx is to provide access to public gene expression data via unique gene names. A second objective is to represent heterogeneous expression data produced by different technologies in a way that facilitates joint analysis and cross-data set comparisons. A consistent and up-to-date gene nomenclature is achieved by associating each single experiment with a permanent target identifier consisting of a physical description of the targeted RNA population or the hybridization reagent used. These targets are then mapped at regular intervals to the growing and evolving catalogues of human genes and genes from model organisms. The completely automatic mapping procedure relies partly on external genome information resources such as UniGene and RefSeq. The central part of CleanEx is a weekly built gene index containing cross-references to all public expression data already incorporated into the system. In addition, the expression target database of CleanEx provides gene mapping and quality control information for various types of experimental resource, such as cDNA clones or Affymetrix probe sets. The web-based query interfaces offer access to individual entries via text string searches or quantitative expression criteria. CleanEx is accessible at: http://www.cleanex.isb-sib.ch/.

Fast Approximation of Nonlinearities for improving inversion algorithms of PNL mixtures and Wiener systems

This paper proposes a very fast method for blindly approximating a nonlinear mapping which transforms a sum of random variables. The estimation is surprisingly good even when the basic assumption is not satisfied.We use the method for providing a good initialization for inverting post-nonlinear mixtures and Wiener systems. Experiments show that the algorithm speed is strongly improved and the asymptotic performance is preserved with a very low extra computational cost.

Coherency and sharpness measures by using ICA algorithms. An investigation for Alzheimer’s disease discrimination

In this paper, we present a comprehensive study of different Independent Component Analysis (ICA) algorithms for the calculation of coherency and sharpness of electroencephalogram (EEG) signals, in order to investigate the possibility of early detection of Alzheimer’s disease (AD). We found that ICA algorithms can help in the artifact rejection and noise reduction, improving the discriminative property of features in high frequency bands (specially in high alpha and beta ranges). In addition to different ICA algorithms, the optimum number of selected components is investigated, in order to help decision processes for future works.

Investigation of ICA algorithms for feature extraction of EEG signals in discrimination of Alzheimer disease

In this paper we present a quantitative comparisons of different independent component analysis (ICA) algorithms in order to investigate their potential use in preprocessing (such as noise reduction and feature extraction) the electroencephalogram (EEG) data for early detection of Alzhemier disease (AD) or discrimination between AD (or mild cognitive impairment, MCI) and age-match control subjects.

Syndromic algorithms for detection of gambiense human african trypanosomiasis in South Sudan.

BACKGROUND: Active screening by mobile teams is considered the best method for detecting human African trypanosomiasis (HAT) caused by Trypanosoma brucei gambiense but the current funding context in many post-conflict countries limits this approach. As an alternative, non-specialist health care workers (HCWs) in peripheral health facilities could be trained to identify potential cases who need testing based on their symptoms. We explored the predictive value of syndromic referral algorithms to identify symptomatic cases of HAT among a treatment-seeking population in Nimule, South Sudan. METHODOLOGY/PRINCIPAL FINDINGS: Symptom data from 462 patients (27 cases) presenting for a HAT test via passive screening over a 7 month period were collected to construct and evaluate over 14,000 four item syndromic algorithms considered simple enough to be used by peripheral HCWs. For comparison, algorithms developed in other settings were also tested on our data, and a panel of expert HAT clinicians were asked to make referral decisions based on the symptom dataset. The best performing algorithms consisted of three core symptoms (sleep problems, neurological problems and weight loss), with or without a history of oedema, cervical adenopathy or proximity to livestock. They had a sensitivity of 88.9-92.6%, a negative predictive value of up to 98.8% and a positive predictive value in this context of 8.4-8.7%. In terms of sensitivity, these out-performed more complex algorithms identified in other studies, as well as the expert panel. The best-performing algorithm is predicted to identify about 9/10 treatment-seeking HAT cases, though only 1/10 patients referred would test positive. CONCLUSIONS/SIGNIFICANCE: In the absence of regular active screening, improving referrals of HAT patients through other means is essential. Systematic use of syndromic algorithms by peripheral HCWs has the potential to increase case detection and would increase their participation in HAT programmes. The algorithms proposed here, though promising, should be validated elsewhere.

3D noise power spectrum applied on clinical mdct scanners: effects of reconstruction algorithms and reconstruction filters

The noise power spectrum (NPS) is the reference metric for understanding the noise content in computed tomography (CT) images. To evaluate the noise properties of clinical multidetector (MDCT) scanners, local 2D and 3D NPSs were computed for different acquisition reconstruction parameters.A 64- and a 128-MDCT scanners were employed. Measurements were performed on a water phantom in axial and helical acquisition modes. CT dose index was identical for both installations. Influence of parameters such as the pitch, the reconstruction filter (soft, standard and bone) and the reconstruction algorithm (filtered-back projection (FBP), adaptive statistical iterative reconstruction (ASIR)) were investigated. Images were also reconstructed in the coronal plane using a reformat process. Then 2D and 3D NPS methods were computed.In axial acquisition mode, the 2D axial NPS showed an important magnitude variation as a function of the z-direction when measured at the phantom center. In helical mode, a directional dependency with lobular shape was observed while the magnitude of the NPS was kept constant. Important effects of the reconstruction filter, pitch and reconstruction algorithm were observed on 3D NPS results for both MDCTs. With ASIR, a reduction of the NPS magnitude and a shift of the NPS peak to the low frequency range were visible. 2D coronal NPS obtained from the reformat images was impacted by the interpolation when compared to 2D coronal NPS obtained from 3D measurements.The noise properties of volume measured in last generation MDCTs was studied using local 3D NPS metric. However, impact of the non-stationarity noise effect may need further investigations.

quantiNemo: an individual-based program to simulate quantitative traits with explicit genetic architecture in a dynamic metapopulation.

quantiNemo is an individual-based, genetically explicit stochastic simulation program. It was developed to investigate the effects of selection, mutation, recombination and drift on quantitative traits with varying architectures in structured populations connected by migration and located in a heterogeneous habitat. quantiNemo is highly flexible at various levels: population, selection, trait(s) architecture, genetic map for QTL and/or markers, environment, demography, mating system, etc. quantiNemo is coded in C++ using an object-oriented approach and runs on any computer platform. Availability: Executables for several platforms, user's manual, and source code are freely available under the GNU General Public License at http://www2.unil.ch/popgen/softwares/quantinemo.

Update on the non-prewhitening model observer in computed tomography for the assessment of the adaptive statistical and model-based iterative reconstruction algorithms.

The state of the art to describe image quality in medical imaging is to assess the performance of an observer conducting a task of clinical interest. This can be done by using a model observer leading to a figure of merit such as the signal-to-noise ratio (SNR). Using the non-prewhitening (NPW) model observer, we objectively characterised the evolution of its figure of merit in various acquisition conditions. The NPW model observer usually requires the use of the modulation transfer function (MTF) as well as noise power spectra. However, although the computation of the MTF poses no problem when dealing with the traditional filtered back-projection (FBP) algorithm, this is not the case when using iterative reconstruction (IR) algorithms, such as adaptive statistical iterative reconstruction (ASIR) or model-based iterative reconstruction (MBIR). Given that the target transfer function (TTF) had already shown it could accurately express the system resolution even with non-linear algorithms, we decided to tune the NPW model observer, replacing the standard MTF by the TTF. It was estimated using a custom-made phantom containing cylindrical inserts surrounded by water. The contrast differences between the inserts and water were plotted for each acquisition condition. Then, mathematical transformations were performed leading to the TTF. As expected, the first results showed a dependency of the image contrast and noise levels on the TTF for both ASIR and MBIR. Moreover, FBP also proved to be dependent of the contrast and noise when using the lung kernel. Those results were then introduced in the NPW model observer. We observed an enhancement of SNR every time we switched from FBP to ASIR to MBIR. IR algorithms greatly improve image quality, especially in low-dose conditions. Based on our results, the use of MBIR could lead to further dose reduction in several clinical applications.