Insight into the mechanism of transient trapping in micellar electrokinetic chromatography

Transient trapping is a new mechanism of on-line sample concentration and separation that has recently been presented. It involves the injection of a short length of micellar solution in front of the sample, making it similar to sweeping in partial-filling MEKC. Here, we examine the mechanism of transient trapping by the use of computer simulations and compare it to sweeping in MEKC for the two analytes, sulforhodamine B and 101. The simulation results confirm the mechanism for concentration and separation originally proposed. The mechanism for concentration is similar to sweeping since the analytes are picked and accumulated by the micelles that penetrate the sample zone. The mechanism for separation is however quite unique since the concentrated analytes are trapped for a few seconds on the sample/micelle boundary before they are released as the concentration of micelle is reduced as it undergoes electromigration dispersion and the analytes separate down a micelle gradient. Simulation results suggested that a significant contribution of band broadening arises from the micelle gradient, with shallower gradients resulting in broader peaks. However, this is offset by an increase in selectivity, such that resolution was enhanced even though the peaks are broader. Transient trapping analysis with similar resolution to those obtained by sweeping MEKC could be achieved in 1/10 of the time and 1/4 of the capillary length, which results in a 2-3 times increase in sensitivity.

A satellite-based snow cover climatology (1985–2011) for the European Alps derived from AVHRR data

Seasonal snow cover is of great environmental and socio-economic importance for the European Alps. Therefore a high priority has been assigned to quantifying its temporal and spatial variability. Complementary to land-based monitoring networks, optical satellite observations can be used to derive spatially comprehensive information on snow cover extent. For understanding long-term changes in alpine snow cover extent, the data acquired by the Advanced Very High Resolution Radiometer (AVHRR) sensors mounted onboard the National Oceanic and Atmospheric Association (NOAA) and Meteorological Operational satellite (MetOp) platforms offer a unique source of information. In this paper, we present the first space-borne 1 km snow extent climatology for the Alpine region derived from AVHRR data over the period 1985–2011. The objective of this study is twofold: first, to generate a new set of cloud-free satellite snow products using a specific cloud gap-filling technique and second, to examine the spatiotemporal distribution of snow cover in the European Alps over the last 27 yr from the satellite perspective. For this purpose, snow parameters such as snow onset day, snow cover duration (SCD), melt-out date and the snow cover area percentage (SCA) were employed to analyze spatiotemporal variability of snow cover over the course of three decades. On the regional scale, significant trends were found toward a shorter SCD at lower elevations in the south-east and south-west. However, our results do not show any significant trends in the monthly mean SCA over the last 27 yr. This is in agreement with other research findings and may indicate a deceleration of the decreasing snow trend in the Alpine region. Furthermore, such data may provide spatially and temporally homogeneous snow information for comprehensive use in related research fields (i.e., hydrologic and economic applications) or can serve as a reference for climate models.

Chemistry of igneous rocks from, the Celebes Sea basement

Major and trace elements, mineral chemistry, and Sr-Nd isotope ratios are reported for representative igneous rocks of Ocean Drilling Program Sites 767 and 770. The basaltic basement underlying middle Eocene radiolarianbearing red clays was reached at 786.7 mbsf and about 421 mbsf at Sites 767 and 770, respectively. At Site 770 the basement was drilled for about 106 m. Eight basaltic units were identified on the basis of mineralogical, petrographical, and geochemical data. They mainly consist of pillow lavas and pillow breccias (Units A, B, D, and H), intercalated with massive amygdaloidal lavas (Units Cl and C2) or relatively thin massive flows (Unit E). Two dolerite sills were also recognized (Units F and G). All the rocks studied show the effect of low-temperature seafloor alteration, causing almost total replacement of olivine and glass. Calcite, clays, and Fe-hydroxides are the most abundant secondary phases. Chemical mobilization due to the alteration processes has been evaluated by comparing elements that are widely considered mobile during halmyrolysis (such as low-field strength elements) with those insensitive to seafloor alteration (such as Nb). In general, MgO is removed and P2O5 occasionally enriched during the alteration of pillow lavas. Ti, Cs, Li, Rb, and K, which are the most sensitive indicators of rock/seawater interaction, are generally enriched. The most crystalline samples appear the least affected by chemical changes. Plagioclase and olivine are continuously present as phenocrysts, and clinopyroxene is confined in the groundmass. Textural and mineralogical features as well as crystallization sequences of Site 770 rocks are, in all, analogous to typical mid-ocean-ridge basalts (MORBs). Relatively high content of compatible trace elements, such as Ni and Cr, indicate that these rocks represent nearly primitive or weakly fractionated MORBs. All the studied rocks are geochemically within the spectrum of normal MORB compositional variation. Their Sr/Nd isotopic ratios plot on the mantle array (87Sr/87Sr 0.70324-0.70348 with 143Nd/144Nd 0.51298-0.51291) outside the field of Atlantic and Pacific MORBs. However, Sr and Nd isotopes are typical of both Indian Ocean MORBs and of some back-arc basalts, such as those of Lau Basin. The mantle source of Celebes basement basalts does not show a detectable influence of a subduction-related component. The geochemical and isotopic data so far obtained on the Celebes basement rocks do not allow a clear discrimination between mid-ocean ridge and back-arc settings.

Thermoelectric Properties of Co4Sb12 Skutterudite Materials with Partial In Filling and Excess In Additions

The properties of Co4Sb12 with various In additions were studied. X-ray diffraction revealed the presence of the pure δ-phase of In0.16Co4Sb12, whereas impurity phases (γ-CoSb2 and InSb) appeared for x = 0.25, 0.40, 0.80, and 1.20. The homogeneity and morphology of the samples were observed by Seebeck microprobe and scanning electron microscopy, respectively. All the quenched ingots from which the studied samples were cut were inhomogeneous in the axial direction. The temperature dependence of the Seebeck coefficient (S), electrical conductivity (σ), and thermal conductivity (κ) was measured from room temperature up to 673 K. The Seebeck coefficient of all In-added Co4Sb12 materials was negative. When the filler concentration increases, the Seebeck coefficient decreases. The samples with In additions above the filling limit (x = 0.22) show an even lower Seebeck coefficient due to the formation of secondary phases: InSb and CoSb2. The temperature variation of the electrical conductivity is semiconductor-like. The thermal conductivity of all the samples decreases with temperature. The central region of the In0.4Co4Sb12 ingot shows the lowest thermal conductivity, probably due to the combined effect of (a) rattling due to maximum filling and (b) the presence of a small amount of fine-dispersed secondary phases at the grain boundaries. Thus, regardless of the non-single-phase morphology, a promising ZT (S 2 σT/κ) value of 0.96 at 673 K has been obtained with an In addition above the filling limit.

When is `partial' adequate? A logic-based proof technique using partial specifications

A technique is presented for ascertaining when a (finite-state) partial process specification is adequate, in the sense of being specified enough, for contexts in which it is to be used. The method relies on the automatic generation of a modal formula from the partial specification; if the remainder of the network satisfies this formula, then any process that meets the specification is guaranteed to ensure correct behavior of the overall system. Using the results, the authors develop compositional proof rules for establishing the correctness of networks of parallel processes and illustrate their use with several examples

A study on the ignition process for the catalytic partial oxidation of methane to synthesis gas by MS-TPSR technique

The ignition processes for the catalytic partial oxidation of methane (POM) to synthesis gas over oxidic nickel catalyst (NiO/Al2O3), reduced nickel catalyst (Ni-0/Al2O3), and Pt-promoted oxidic nickel catalyst (Pt-NiO/Al2O3) were studied by the temperature-programmed surface reaction (TPSR) technique. The complete oxidation of methane usually took place on the NiO catalyst during the CH4/O-2 reaction, even with a pre-reduced nickel catalyst, and Ni-0 is inevitably first oxidized to NiO if the temperature is below the ignition temperature. It is above a certain temperature that Ni-0 is formed again, which leads to the start of the POM. The POM can be initiated at a much lower temperature on a Pt-NiO catalyst because of Pt promotion of the reduction of NiO. The POM in a fluidized bed can be easily initiated due to the addition of Pt.

The effect of radiation technique and bladder filling on the acute toxicity of pelvic radiotherapy for localized high risk prostate cancer

Purpose: The goal of this project was to see if using IMRT to deliver elective pelvic nodal irradiation (EPNI) for prostate cancer reduced acute treatment toxicity.

Methods: Two hundred and thirty patients were enrolled into prospective trials delivering EPNI with a concomitant hypofractionated IMRT boost to the prostate. During accrual, the method of EPNI delivery changed as new literature emerged. Three methods were used (1) 4FB, (2) IMRT with 2 cm CTV margins around the pelvic vessels as suggested by Shih et al. (2005) [7] (IMRT-Shih), and (3) IMRT with nodal volumes suggested by the RTOG (IMRT-RTOG). Initially patients were treated with an empty bladder, with the remainder treated with bladder full.

Results: Patients in the 4FB group had higher rates of grade 2 acute GI toxicities compared to the IMRT-Shih and IMRT-RTOG groups (31.9% vs 20.8% vs 7.2%, p = 0.0009). Patients in the 4FB group had higher rates of grade 3 urinary frequency compared to the two IMRT groups (8.5% vs 0% vs 0%, p = 0.027). However, multivariate analysis suggested the factor that most influenced toxicity was bladder filling followed by IMRT.

Conclusions: Bladder filling appeared to be the dominant factor which predicted for acute toxicity, followed by the use of IMRT.

Reaction of dogs' teeth to root canal filling with mineral trioxide aggregate or a glass ionomer sealer

This study was conducted to observe the reaction of apical tissues of dogs' teeth after root canal filling with gutta-percha and mineral trioxide aggregate (MTA) or a glass ionomer (Ketac-Endo) as a sealer. The root canals were instrumented and filled by the lateral condensation technique with the sealers studied. Animals were killed 6 months later, and the specimens were removed and prepared for histological analysis. Results showed no inflammatory reaction of apical tissue and total closure of the apical foramen of all the teeth sealed with MTA. The teeth sealed with Ketac-Endo showed two cases of partial closure and different degrees of chronic inflammatory reaction. In conclusion, MTA exhibited better biological properties than Ketac-Endo. Copyright © 1999 by The American Association of Endodontists.

Partial lateral corpectomy associated with pediculectomy to treat extradural chondroma in a dog: technique description

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Effectiveness of gutta-percha and Resilon in filling lateral root canals using thermomechanical technique

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A clustering technique for partial discharge and noise sources identification in power cables by means of waveform parameters

On-line partial discharge (PD) measurements have become a common technique for assessing the insulation condition of installed high voltage (HV) insulated cables. When on-line tests are performed in noisy environments, or when more than one source of pulse-shaped signals are present in a cable system, it is difficult to perform accurate diagnoses. In these cases, an adequate selection of the non-conventional measuring technique and the implementation of effective signal processing tools are essential for a correct evaluation of the insulation degradation. Once a specific noise rejection filter is applied, many signals can be identified as potential PD pulses, therefore, a classification tool to discriminate the PD sources involved is required. This paper proposes an efficient method for the classification of PD signals and pulse-type noise interferences measured in power cables with HFCT sensors. By using a signal feature generation algorithm, representative parameters associated to the waveform of each pulse acquired are calculated so that they can be separated in different clusters. The efficiency of the clustering technique proposed is demonstrated through an example with three different PD sources and several pulse-shaped interferences measured simultaneously in a cable system with a high frequency current transformer (HFCT).

Toward prediction of class II mouse major histocompatibility complex peptide binding affinity:in silico bioinformatic evaluation using partial least squares, a robust multivariate statistical technique

The accurate identification of T-cell epitopes remains a principal goal of bioinformatics within immunology. As the immunogenicity of peptide epitopes is dependent on their binding to major histocompatibility complex (MHC) molecules, the prediction of binding affinity is a prerequisite to the reliable prediction of epitopes. The iterative self-consistent (ISC) partial-least-squares (PLS)-based additive method is a recently developed bioinformatic approach for predicting class II peptide−MHC binding affinity. The ISC−PLS method overcomes many of the conceptual difficulties inherent in the prediction of class II peptide−MHC affinity, such as the binding of a mixed population of peptide lengths due to the open-ended class II binding site. The method has applications in both the accurate prediction of class II epitopes and the manipulation of affinity for heteroclitic and competitor peptides. The method is applied here to six class II mouse alleles (I-Ab, I-Ad, I-Ak, I-As, I-Ed, and I-Ek) and included peptides up to 25 amino acids in length. A series of regression equations highlighting the quantitative contributions of individual amino acids at each peptide position was established. The initial model for each allele exhibited only moderate predictivity. Once the set of selected peptide subsequences had converged, the final models exhibited a satisfactory predictive power. Convergence was reached between the 4th and 17th iterations, and the leave-one-out cross-validation statistical terms - q2, SEP, and NC - ranged between 0.732 and 0.925, 0.418 and 0.816, and 1 and 6, respectively. The non-cross-validated statistical terms r2 and SEE ranged between 0.98 and 0.995 and 0.089 and 0.180, respectively. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made freely available online (http://www.jenner.ac.uk/MHCPred).

Improving the performance of model-order selection criteria by partial-model selection search

The traditional searching method for model-order selection in linear regression is a nested full-parameters-set searching procedure over the desired orders, which we call full-model order selection. On the other hand, a method for model-selection searches for the best sub-model within each order. In this paper, we propose using the model-selection searching method for model-order selection, which we call partial-model order selection. We show by simulations that the proposed searching method gives better accuracies than the traditional one, especially for low signal-to-noise ratios over a wide range of model-order selection criteria (both information theoretic based and bootstrap-based). Also, we show that for some models the performance of the bootstrap-based criterion improves significantly by using the proposed partial-model selection searching method. Index Terms— Model order estimation, model selection, information theoretic criteria, bootstrap 1. INTRODUCTION Several model-order selection criteria can be applied to find the optimal order. Some of the more commonly used information theoretic-based procedures include Akaike’s information criterion (AIC) [1], corrected Akaike (AICc) [2], minimum description length (MDL) [3], normalized maximum likelihood (NML) [4], Hannan-Quinn criterion (HQC) [5], conditional model-order estimation (CME) [6], and the efficient detection criterion (EDC) [7]. From a practical point of view, it is difficult to decide which model order selection criterion to use. Many of them perform reasonably well when the signal-to-noise ratio (SNR) is high. The discrepancies in their performance, however, become more evident when the SNR is low. In those situations, the performance of the given technique is not only determined by the model structure (say a polynomial trend versus a Fourier series) but, more importantly, by the relative values of the parameters within the model. This makes the comparison between the model-order selection algorithms difficult as within the same model with a given order one could find an example for which one of the methods performs favourably well or fails [6, 8]. Our aim is to improve the performance of the model order selection criteria in cases where the SNR is low by considering a model-selection searching procedure that takes into account not only the full-model order search but also a partial model order search within the given model order. Understandably, the improvement in the performance of the model order estimation is at the expense of additional computational complexity.