Determination of benzoylurea insecticide residues in tomatoes by high-performance liquid chromatography with ultraviolet-diode array and atmospheric pressure chemical ionization-mass spectrometry detection

A simple and sensitive method using high-performance liquid chromatography/ mass spectrometry (LC/MS) was developed and validated for simultaneous determination of 5 benzoylurea insecticides-diflubenzuron, triflumuron, teflubenzuron, lufenuron, and flufenoxuron-in tomatoes. Residues were successfully separated on a C18 column by methanol-water isocratic elution. Detection was carried out by an ultraviolet diode array detector (UV-DAD) coupled with a quadrupole mass spectrometer, using atmospheric pressure chemical ionization (APCI) in negative-ion mode. The main ions were the deprotonated molecules [M-H]- for triflumuron, and the anions formed by elimination of hydrofluoric acid [M-H-HF]- for diflubenzuron and flufenoxuron, and [M-2H-HF] for lufenuron and teflubenzuron. The calibration plots were linear for both detectors over the range 0.05 to 10 microg/mL, and the method presented good quality parameters. The limits of detection for standard solutions were 0.008-0.01 mg/L (equivalent to 0.08-0.1 ng injected) for both detectors, and the limits of quantification (LOQs) were approximately 10 times lower than national maximum residue levels (MRLs). Depending on the compound and the detector, the LOQ values ranged from 0.2 to 0.4 ng injected. The optimum LC-UV-DAD/APCI-MS conditions were applied to the analysis of benzoylureas in tomatoes. The obtained recoveries from fortified tomato samples (50 g), extracted with ethyl acetate and purified by solid-phase extraction on silica sorbent, were 88-100 and 92.9-105% for the UV-DAD and MS detectors, respectively, with precision values (relative standard deviations) of 2.9-11 and 3.7-14%, respectively. The method was applied to 12 tomato samples from local markets, and diflubenzuron and lufenuron were detected in only one sample at concentrations lower than the MRLs. The results indicate that the developed LC/MS method is accurate, precise, and sensitive for quantitative and qualitative analysis at low levels of benzoylureas required by legislation.     

Synthesis of 2D Germanane (GeH): a New,Fast, and Facile Approach

Germanane (GeH), a germanium analogue of graphane, has recently attracted considerable interest because its remarkable combination of properties makes it an extremely suitable candidate to be used as 2D material for field effect devices, photovoltaics, and photocatalysis. Up to now, the synthesis of GeH has been conducted by substituting Ca by H in a β‐CaGe₂ layered Zintl phase through topochemical deintercalation in aqueous HCl. This reaction is generally slow and takes place over 6 to 14 days. The new and facile protocol presented here allows to synthesize GeH at room temperature in a significantly shorter time (a few minutes), which renders this method highly attractive for technological applications. The GeH produced with this method is highly pure and has a band gap (E_g) close to 1.4 eV, a lower value than that reported for germanane synthesized using HCl, which is promising for incorporation of GeH in solar cells.     

Microwave-Assisted Synthesis,Characterization and Modeling of CPO-27-Mg Metal-Organic Framework for Drug Delivery

The coordination polymer CPO-27-Mg was rapidly synthesized under microwave irradiation. This material exhibits a sufficiently high drug loading towards aspirin (~8% wt.) and paracetamol (~14% wt.). The binding of these two molecules with the inner surface of the metal-organic framework was studied employing the Gaussian and Plane Wave approach of the Density Functional Theory. The structure of CPO-27-Mg persists after the adsorption of aspirin or paracetamol and their desorption energies, being quite high, decrease under solvent conditions.     

Evaluating higher education teaching performance using combined analytic hierarchy process and data envelopment analysis

Evaluating higher education teaching performance is complex as it involves consideration of both objective and subjective criteria. The student evaluation of teaching (SET) is used to improve higher education quality. However, the traditional approaches to considering students’ responses to SET questionnaires for improving teaching quality have several shortcomings. This study proposes an integrated approach to higher education teaching evaluation that combines the analytical hierarchy process (AHP) and data envelopment analysis (DEA). The AHP allows consideration of the varying importance of each criterion of teaching performance, while DEA enables the comparison of tutors on teaching as perceived by students with a view to identifying the scope for improvement by each tutor. The proposed teaching evaluation method is illustrated using data from a higher education institution in Greece.     

Diffusion tensor encoding schemes optimized for white matter fibers with selected orientations

A method to produce gradient encoding schemes that minimize the noise of diffusion tensor imaging (DTI) indices for selected fiber orientations has been developed. The accuracy of DTI measurements depends on the gradient encoding scheme used. Most current acquisition schemes contain diffusion directions uniformly distributed in 3D space in order to provide equal noise levels for fibers in any orientation. However, when considering specific fiber bundles such as the corticospinal tract (CST) or parts of fiber bundles, the range of fiber orientations of interest may be limited. We hypothesized that, when studying fiber tracts with a limited range of orientations, measuring diffusion in directions that are uniformly distributed in 3D space may be suboptimal for the noise levels of various DTI indices. Therefore, we first used simulations to determine six diffusion directions that minimize the noise of DTI measurements for selected fiber orientations. The resulting optimized set of directions was then tested on the right CST of a healthy human subject, and its performance was compared with that of conventional acquisition strategies. Both the simulations and the experiments on the human subject demonstrated that the new scheme significantly reduced the standard deviation of DTI indices for tensors with primary eigenvectors within a selected range of orientations.     

Hierarchical clustering to measure connectivity in fMRI resting-state data

Low frequency oscillations, which are temporally correlated in functionally related brain regions, characterize the mammalian brain, even when no explicit cognitive tasks are performed. Functional connectivity MR imaging is used to map regions of the resting brain showing synchronous, regional and slow fluctuations in cerebral blood flow and oxygenation. In this study, we use a hierarchical clustering method to detect similarities of low-frequency fluctuations. We describe one measure of correlations in the low frequency range for classification of resting-state fMRI data. Furthermore, we investigate the contribution of motion and hardware instabilities to resting-state correlations and provide a method to reduce artifacts. For all cortical regions studied and clusters obtained, we quantify the degree of contamination of functional connectivity maps by the respiratory and cardiac cycle. Results indicate that patterns of functional connectivity can be obtained with hierarchical clustering that resemble known neuronal connections. The corresponding voxel time series do not show significant correlations in the respiratory or cardiac frequency band.     

An experimental and numerical investigation of the hetero-/homogeneous combustion of fuel-rich hydrogen/air mixtures over platinum

The hetero-/homogeneous combustion of hydrogen/air mixtures over platinum was investigated experimentally and numerically in a channel-flow configuration at fuel-rich equivalence ratios ranging from 2 to 7, pressures up to 5 bar and wall temperatures 760–1200 K. Experiments involved in situ one-dimensional Raman measurements of major gas-phase species concentrations over the catalyst boundary layer and planar laser induced fluorescence (LIF) of the OH radical, while simulations included an elliptic 2-D model with detailed heterogeneous and homogeneous reaction mechanisms. The employed reaction schemes reproduced the measured catalytic reactant consumption, the onset of homogeneous ignition, and the post-ignition flame shapes at all examined conditions. Although below a critical pressure, which depended on temperature, the intrinsic gas-phase kinetics of hydrogen dictated lower reactivity for the fuel-rich stoichiometries when compared to fuel-lean ones, homogeneous ignition was still more favorable for the rich stoichiometries due to the lower molecular transport of the deficient oxygen reactant that resulted in modest catalytic reactant consumption over the gaseous induction zone. Above the critical pressure, the intrinsic gaseous hydrogen kinetics yielded higher reactivity for the rich stoichiometries, which resulted in vigorous gaseous combustion at pressures up to 5 bar, in contrast to lean stoichiometry studies whereby homogeneous combustion was altogether suppressed above 3 bar. Computations at fuel-rich stoichiometries in practical channel geometries indicated that homogeneous combustion was not of concern for reactor thermal management, since the larger than unity Lewis number of the deficient oxygen reactant confined the flames to the core of the channel, away from the solid walls.     

Parallel direct methods for solving the system of linear equations with pipelining on a multicore using OpenMP

Recent developments in high performance computer architecture have a significant effect on all fields of scientific computing. Linear algebra and especially the solution of linear systems of equations lie at the heart of many applications in scientific computing. This paper describes and analyzes three parallel versions of the dense direct methods such as the Gaussian elimination method and the LU form of Gaussian elimination that are used in linear system solving on a multicore using an OpenMP interface. More specifically, we present two naive parallel algorithms based on row block and row cyclic data distribution and we put special emphasis on presenting a third parallel algorithm based on the pipeline technique. Further, we propose an implementation of the pipelining technique in OpenMP. Experimental results on a multicore CPU show that the proposed OpenMP pipeline implementation achieves good overall performance compared to the other two naive parallel methods. Finally, in this work we propose a simple, fast and reasonably analytical model to predict the performance of the direct methods with the pipelining technique.     

Manufacturing performance measurement and target setting: A data envelopment analysis approach

Manufacturing decision makers have to deal with a large number of reports and metrics for evaluating the performance of manufacturing systems. Since the metrics provide different and at times conflicting assessments, it is hard for the manufacturing decision makers to track and improve overall manufacturing system performance. This research presents a data envelopment analysis (DEA) based approach for performance measurement and target setting of manufacturing systems. The approach is applied to two different manufacturing environments. The performance peer groups identified using DEA are utilized to set performance targets and to guide performance improvement efforts. The DEA scores are checked against past process modifications that led to identified performance changes. Limitations of the DEA based approach are presented when considering measures that are influenced by factors outside of the control of the manufacturing decision makers. The potential of a DEA based generic performance measurement approach for manufacturing systems is provided.