Nonlinear inverse dynamic models of gas sensing systems based on chemical sensor arrays for quantitative measurements

Gas sensing systems based on low-cost chemical sensor arrays are gaining interest for the analysis of multicomponent gas mixtures. These sensors show different problems, e.g., nonlinearities and slow time-response, which can be partially solved by digital signal processing. Our approach is based on building a nonlinear inverse dynamic system. Results for different identification techniques, including artificial neural networks and Wiener series, are compared in terms of measurement accuracy.

Petróleo y gas en África: viejas realidades, nuevos escenarios

[cat] En els últims temps es parla molt del nou paper dels hidrocarburs d'Àfrica, fins i tot s'al·ludeix a un oil rush o a un african oil scramble , que inevitablement desembocarà en una confrontació bipolar entre la Xina i els Estats Units, pel control de les reserves de petroli del subsòl del continent africà. Així, el propòsit d'aquest text és, en primer lloc, realitzar una anàlisi descriptiva que ajudi a valorar la hipòtesi d'aquest african oil scramble. A continuación, amb les dades obtingudes, es discutirà sobre la possibilitat de que aquest fenomen desemboqui en un escenari de confrontació xinoamericana. Aquesta especulació ens durà a concloure que hi ha suficients indicis per a argumentar que el joc petrolífer africà podria desenvolupar-se en un escenari marcat per la multilateralitat.

Nonresponse to clozapine and ultrarapid CYP1A2 activity: clinical data and analysis of CYP1A2 gene.

Clozapine (CLO), an atypical antipsychotic, depends mainly on cytochrome P450 1A2 (CYP1A2) for its metabolic clearance. Four patients treated with CLO, who were smokers, were nonresponders and had low plasma levels while receiving usual doses. Their plasma levels to dose ratios of CLO (median; range, 0.34; 0.22 to 0.40 ng x day/mL x mg) were significantly lower than ratios calculated from another study with 29 patients (0.75; 0.22 to 2.83 ng x day/mL x mg; P < 0.01). These patients were confirmed as being CYP1A2 ultrarapid metabolizers by the caffeine phenotyping test (median systemic caffeine plasma clearance; range, 3.85; 3.33 to 4.17 mL/min/kg) when compared with previous studies (0.3 to 3.33 mL/min/kg). The sequencing of the entire CYP1A2 gene from genomic DNA of these patients suggests that the -164C > A mutation (CYP1A2*1F) in intron 1, which confers a high inducibility of CYP1A2 in smokers, is the most likely explanation for their ultrarapid CYP1A2 activity. A marked (2 patients) or a moderate (2 patients) improvement of the clinical state of the patients occurred after the increase of CLO blood levels above the therapeutic threshold by the increase of CLO doses to very high values (ie, up to 1400 mg/d) or by the introduction of fluvoxamine, a potent CYP1A2 inhibitor, at low dosage (50 to 100 mg/d). Due to the high frequency of smokers among patients with schizophrenia and to the high frequency of the -164C > A polymorphism, CYP1A2 genotyping could have important clinical implications for the treatment of patients with CLO.

Greenhouse Gas and Nitrogen Fertilizer Scenarios for U.S. Agriculture and Global Biofuels, June 2011

This analysis uses the 2011 FAPRI-CARD (Food and Agricultural Policy Research Institute–Center for Agricultural and Rural Development) baseline to evaluate the impact of four alternative scenarios on U.S. and world agricultural markets, as well as on world fertilizer use and world agricultural greenhouse gas emissions. A key assumption in the 2011 baseline is that ethanol support policies disappear in 2012. The baseline also assumes that existing biofuel mandates remain in place and are binding. Two of the scenarios are adverse supply shocks, the first being a 10% increase in the price of nitrogen fertilizer in the United States, and the second, a reversion of cropland into forestland. The third scenario examines how lower energy prices would impact world agriculture. The fourth scenario reintroduces biofuel tax credits and duties. Given that the baseline excludes these policies, the fourth scenario is an attempt to understand the impact of these policies under the market conditions that prevail in early 2011. A key to understanding the results of this fourth scenario is that in the absence of tax credits and duties, the mandate drives biofuel use. Therefore, when the tax credits and duties are reintroduced, the impacts are relatively small. In general, the results show that the entire international commodity market system is remarkably robust with respect to policy changes in one country or in one sector. The policy implication is that domestic policy changes implemented by a large agricultural producer like the United States can have fairly significant impacts on the aggregate world commodity markets. A second point that emerges from the results is that the law of unintended consequences is at work in world agriculture. For example, a U.S. nitrogen tax that might presumably be motivated for environmental benefit results in an increase in world greenhouse gas emissions. A similar situation occurs in the afforestation scenario in which crop production shifts from high-yielding land in the United States to low-yielding land and probably native vegetation in the rest of the world, resulting in an unintended increase in global greenhouse gas emissions.

Global phylogenomic analysis of nonencapsulated Streptococcus pneumoniae reveals a deep-branching classic lineage that is distinct from multiple sporadic lineages.

The surrounding capsule of Streptococcus pneumoniae has been identified as a major virulence factor and is targeted by pneumococcal conjugate vaccines (PCV). However, nonencapsulated S. pneumoniae (non-Ec-Sp) have also been isolated globally, mainly in carriage studies. It is unknown if non-Ec-Sp evolve sporadically, if they have high antibiotic nonsusceptiblity rates and a unique, specific gene content. Here, whole-genome sequencing of 131 non-Ec-Sp isolates sourced from 17 different locations around the world was performed. Results revealed a deep-branching classic lineage that is distinct from multiple sporadic lineages. The sporadic lineages clustered with a previously sequenced, global collection of encapsulated S. pneumoniae (Ec-Sp) isolates while the classic lineage is comprised mainly of the frequently identified multilocus sequences types (STs) ST344 (n = 39) and ST448 (n = 40). All ST344 and nine ST448 isolates had high nonsusceptiblity rates to β-lactams and other antimicrobials. Analysis of the accessory genome reveals that the classic non-Ec-Sp contained an increased number of mobile elements, than Ec-Sp and sporadic non-Ec-Sp. Performing adherence assays to human epithelial cells for selected classic and sporadic non-Ec-Sp revealed that the presence of a integrative conjugative element (ICE) results in increased adherence to human epithelial cells (P = 0.005). In contrast, sporadic non-Ec-Sp lacking the ICE had greater growth in vitro possibly resulting in improved fitness. In conclusion, non-Ec-Sp isolates from the classic lineage have evolved separately. They have spread globally, are well adapted to nasopharyngeal carriage and are able to coexist with Ec-Sp. Due to continued use of PCV, non-Ec-Sp may become more prevalent.

Petróleo y gas en África: viejas realidades, nuevos escenarios

[cat] En els últims temps es parla molt del nou paper dels hidrocarburs d'Àfrica, fins i tot s'al·ludeix a un oil rush o a un african oil scramble , que inevitablement desembocarà en una confrontació bipolar entre la Xina i els Estats Units, pel control de les reserves de petroli del subsòl del continent africà. Així, el propòsit d'aquest text és, en primer lloc, realitzar una anàlisi descriptiva que ajudi a valorar la hipòtesi d'aquest african oil scramble. A continuación, amb les dades obtingudes, es discutirà sobre la possibilitat de que aquest fenomen desemboqui en un escenari de confrontació xinoamericana. Aquesta especulació ens durà a concloure que hi ha suficients indicis per a argumentar que el joc petrolífer africà podria desenvolupar-se en un escenari marcat per la multilateralitat.

Analysis and spatial modeling of the indoor radon Swiss data

The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.

A novel method for quantification of sulfolane (a metabolite of busulfan) in plasma by gas chromatography-tandem mass spectrometry.

The role of busulfan (Bu) metabolites in the adverse events seen during hematopoietic stem cell transplantation and in drug interactions is not explored. Lack of availability of established analytical methods limits our understanding in this area. The present work describes a novel gas chromatography-tandem mass spectrometric assay for the analysis of sulfolane (Su) in plasma of patients receiving high-dose Bu. Su and Bu were extracted from a single 100 μL plasma sample by liquid-liquid extraction. Bu was separately derivatized with 2,3,5,6-tetrafluorothiophenolfluorinated agent. Mass spectrometric detection of the analytes was performed in the selected reaction monitoring mode on a triple quadrupole instrument after electronic impact ionization. Bu and Su were analyzed with separate chromatographic programs, lasting 5 min each. The assay for Su was found to be linear in the concentration range of 20-400 ng/mL. The method has satisfactory sensitivity (lower limit of quantification, 20 ng/mL) and precision (relative standard deviation less than 15 %) for all the concentrations tested with a good trueness (100 ± 5 %). This method was applied to measure Su from pediatric patients with samples collected 4 h after dose 1 (n = 46), before dose 7 (n = 56), and after dose 9 (n = 54) infusions of Bu. Su (mean ± SD) was detectable in plasma of patients 4 h after dose 1, and higher levels were observed after dose 9 (249.9 ± 123.4 ng/mL). This method may be used in clinical studies investigating the role of Su on adverse events and drug interactions associated with Bu therapy.

Gas-chromatography mass-spectrometry determination of phthalic acid in human urine as a biomarker of folpet exposure.

Agricultural workers are exposed to folpet, but biomonitoring data are limited. Phthalimide (PI), phthalamic acid (PAA), and phthalic acid (PA) are the ring metabolites of this fungicide according to animal studies, but they have not yet been measured in human urine as metabolites of folpet, only PA as a metabolite of phthalates. The objective of this study was thus to develop a reliable gas chromatography-tandem mass spectrometry (GC-MS) method to quantify the sum of PI, PAA, and PA ring-metabolites of folpet in human urine. Briefly, the method consisted of adding p-methylhippuric acid as an internal standard, performing an acid hydrolysis at 100 °C to convert ring-metabolites into PA, purifying samples by ethyl acetate extraction, and derivatizing with N,O-bis(trimethylsilyl)trifluoro acetamide prior to GC-MS analysis. The method had a detection limit of 60.2 nmol/L (10 ng/mL); it was found to be accurate (mean recovery, 97%), precise (inter- and intra-day percentage relative standard deviations <13%), and with a good linearity (R (2) > 0.98). Validation was conducted using unexposed peoples urine spiked at concentrations ranging from 4.0 to 16.1 μmol/L, along with urine samples of volunteers dosed with folpet, and of exposed workers. The method proved to be (1) suitable and accurate to determine the kinetic profile of PA equivalents in the urine of volunteers orally and dermally administered folpet and (2) relevant for the biomonitoring of exposure in workers.

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.

Optimization of HS-SPME/GC-MS analysis and its use in the profiling of illicit ecstasy tablets (Part 1)

A headspace solid-phase microextraction procedure (HS-SPME) was developed for the profiling of traces present in 3,4-methylenedioxymethylampethamine (MDMA). Traces were first extracted using HS-SPME and then analyzed by gas chromatography-mass spectroscopy (GC-MS). The HS-SPME conditions were optimized using varying conditions. Optimal results were obtained when 40 mg of crushed MDMA sample was heated at 80 °C for 15 min, followed by extraction at 80 °C for 15 min with a polydimethylsiloxane/divinylbenzene coated fibre. A total of 31 compounds were identified as traces related to MDMA synthesis, namely precursors, intermediates or by-products. In addition some fatty acids used as tabletting materials and caffeine used as adulterant, were also detected. The use of a restricted set of 10 target compounds was also proposed for developing a screening tool for clustering samples having close profile. 114 seizures were analyzed using an SPME auto-sampler (MultiPurpose Samples MPS2), purchased from Gerstel GMBH & Co. (Germany), and coupled to GC-MS. The data was handled using various pre-treatment methods, followed by the study of similarities between sample pairs based on the Pearson correlation. The results show that HS-SPME, coupled with the suitable statistical method is a powerful tool for distinguishing specimens coming from the same seizure and specimens coming from different seizures. This information can be used by law enforcement personnel to visualize the ecstasy distribution network as well as the clandestine tablet manufacturing.

Development and validation of a gas chromatography-negative chemical ionization tandem mass spectrometry method for the determination of ethyl glucuronide in hair and its application to forensic toxicology.

Ethyl glucuronide (EtG) is a minor and direct metabolite of ethanol. EtG is incorporated into the growing hair allowing retrospective investigation of chronic alcohol abuse. In this study, we report the development and the validation of a method using gas chromatography-negative chemical ionization tandem mass spectrometry (GC-NCI-MS/MS) for the quantification of EtG in hair. EtG was extracted from about 30 mg of hair by aqueous incubation and purified by solid-phase extraction (SPE) using mixed mode extraction cartridges followed by derivation with perfluoropentanoic anhydride (PFPA). The analysis was performed in the selected reaction monitoring (SRM) mode using the transitions m/z 347-->163 (for the quantification) and m/z 347-->119 (for the identification) for EtG, and m/z 352-->163 for EtG-d(5) used as internal standard. For validation, we prepared quality controls (QC) using hair samples taken post mortem from 2 subjects with a known history of alcoholism. These samples were confirmed by a proficiency test with 7 participating laboratories. The assay linearity of EtG was confirmed over the range from 8.4 to 259.4 pg/mg hair, with a coefficient of determination (r(2)) above 0.999. The limit of detection (LOD) was estimated with 3.0 pg/mg. The lower limit of quantification (LLOQ) of the method was fixed at 8.4 pg/mg. Repeatability and intermediate precision (relative standard deviation, RSD%), tested at 4 QC levels, were less than 13.2%. The analytical method was applied to several hair samples obtained from autopsy cases with a history of alcoholism and/or lesions caused by alcohol. EtG concentrations in hair ranged from 60 to 820 pg/mg hair.

Accuracy profile validation of a new analytical method for propane measurement using headspace-gas chromatography-mass spectrometry

Propane can be responsible for several types of lethal intoxication and explosions. Quantifying it would be very helpful to determine in some cases the cause of death. Some gas chromatography-mass spectrometry (GC-MS) methods of propane measurements do already exist. The main drawback of these GC-MS methods described in the literature is the absence of a specific propane internal standard necessary for accurate quantitative analysis. The main outcome of the following study was to provide an innovative Headspace-GC-MS method (HS-GC-MS) applicable to the routine determination of propane concentration in forensic toxicology laboratories. To date, no stable isotope of propane is commercially available. The development of an in situ generation of standards is thus presented. An internal-labeled standard gas (C3DH7) is generated in situ by the stoichiometric formation of propane by the reaction of deuterated water (D2O) with Grignard reagent propylmagnesium chloride (C3H7MgCl). The method aims to use this internal standard to quantify propane concentrations and, therefore, to obtain precise measurements. Consequently, a complete validation with an accuracy profile according to two different guidelines, the French Society of Pharmaceutical Sciences and Techniques (SFSTP) and the Gesellschaft für toxikologische und Forensische Chemie (GTFCh), is presented.

Identification of Wax Esters in Latent Print Residues by Gas Chromatography-Mass Spectromertry and Their Potential Use as Aging Parameters

Recent studies show that the composition of fingerprint residue varies significantly from the same donor as well as between donors. This variability is a major drawback in latent print dating issues. This study aimed, therefore, at the definition of a parameter that is less variable from print to print, using a ratio of peak area of a target compound degrading over time divided by the summed area of peaks of more stable compounds also found in latent print residues.Gas chromatography-mass spectrometry (GC/MS) analysis of the initial lipid composition of latent prints identifies four main classes of compounds that can be used in the definition of an aging parameter: fatty acids, sterols, sterol precursors, and wax esters (WEs). Although the entities composing the first three groups are quite well known, those composing WEs are poorly reported. Therefore, the first step of the present work was to identify WE compounds present in latent print residues deposited by different donors. Of 29 WEs recorded in the chromatograms, seven were observed in the majority of samples.The identified WE compounds were subsequently used in the definition of ratios in combination with squalene and cholesterol to reduce the variability of the initial composition between latent print residues from different persons and more particularly from the same person. Finally, the influence of a latent print enhancement process on the initial composition was studied by analyzing traces after treatment with magnetic powder, 1,2-indanedione, and cyanoacrylate.

Performance Analysis of Two Quantum Reaction Dynamics Codes: Time-Dependent and Time-Independent Strategies

The computer simulation of reaction dynamics has nowadays reached a remarkable degree of accuracy. Triatomic elementary reactions are rigorously studied with great detail on a straightforward basis using a considerable variety of Quantum Dynamics computational tools available to the scientific community. In our contribution we compare the performance of two quantum scattering codes in the computation of reaction cross sections of a triatomic benchmark reaction such as the gas phase reaction Ne + H2+ %12. NeH++ H. The computational codes are selected as representative of time-dependent (Real Wave Packet [ ]) and time-independent (ABC [ ]) methodologies. The main conclusion to be drawn from our study is that both strategies are, to a great extent, not competing but rather complementary. While time-dependent calculations advantages with respect to the energy range that can be covered in a single simulation, time-independent approaches offer much more detailed information from each single energy calculation. Further details such as the calculation of reactivity at very low collision energies or the computational effort related to account for the Coriolis couplings are analyzed in this paper.