A simple and inexpensive "solvent in silicone tube extraction" approach and its evaluation in the gas chromatographic analysis of pesticides in fruits and vegetables

A novel, simple, and inexpensive approach to sorptive extraction, which we call solvent in silicone tube extraction (SiSTEx), was applied to pesticide residue analysis and its effectiveness and efficiency were evaluated. In SiSTEx, which is a form of open tubular sorptive extraction, a piece of silicone tubing (4 cm long, 1.47 mm ID, 1.96 mm OD in this study) is attached to the cap of a 20 mL glass vial that contains the aqueous sample. The tubing is plugged at the end dangling in the sample solution, and MeCN (e.g., 40 microL) added by syringe to the inner tube volume through a septum in the cap. A stir-bar is used to mix the sample for a certain time (e.g., 60 min), which allows chemicals to partition into the tubing where they diffuse across the silicone and partition into the MeCN. The final MeCN extract is then analyzed for the concentrated analytes. In this study, the SiSTEx approach was evaluated for the analysis of organophosphorus (OP) and organochlorine (OC) pesticides in fruits and vegetables using GC/pulsed flame photometric (PFPD) and halogen specific (XSD) detectors for analysis. The produced samples were initially extracted by a rapid MeCN procedure, and 5 mL of the initial extract was diluted four-fold with water to undergo sorptive extraction for 60 min. The final extract was analyzed by GC/PFPD + XSD for 14 OP and 22 OC pesticides. This simple approach was able to detect 26 of the 36 pesticides at 10 ng/g or less original equivalent sample concentration with average reproducibility of 11% RSD. For those 26 pesticides, a 44-fold lower detection limit on average was achieved in matrix extracts using SiSTEx despite the four-fold dilution with water.     

Hydrocarbons and fuels analyses with the supersonic gas chromatography mass spectrometry--the novel concept of isomer abundance analysis

Hydrocarbon analysis with standard GC-MS is confronted by the limited range of volatile compounds amenable for analysis and by the similarity of electron ionization mass spectra for many compounds which show weak or no molecular ions for heavy hydrocarbons. The use of GC-MS with supersonic molecular beams (Supersonic GC-MS) significantly extends the range of heavy hydrocarbons that can be analyzed, and provides trustworthy enhanced molecular ion to all hydrocarbons. In addition, unique isomer mass spectral features are obtained in the ionization of vibrationally cold hydrocarbons. The availability of molecular ions for all hydrocarbons results in the ability to obtain unique chromatographic isomer distribution patterns that can serve as a new method for fuel characterization and identification. Examples of the applicability and use of this novel isomer abundance analysis (IAA) method to diesel fuel, kerosene and oil analyses are shown. It is suggested that in similarity to the "three ions method" for identification purposes, three isomer abundance patterns can serve for fuel characterization. The applications of the Supersonic GC-MS for engine motor oil analysis and transformer oil analysis are also demonstrated and discussed, including the capability to achieve fast 1-2s sampling without separation for oil and fuel fingerprinting. The relatively fast analysis of biodiesel is described, demonstrating the provision of molecular ions to heavy triglycerides. Isomer abundance analysis with the Supersonic GC-MS could find broad range of applications including petrochemicals and fuel analysis, arson analysis, environmental oil/fuel spill analysis, fuel adulteration analysis and motor oil analysis.     

Corrole-based applications

Despite of the many similarities between corroles and porphyrins, the chemistry of the former remained undeveloped for decades because of severe synthetic obstacles. The recent discoveries of facile methodologies for the synthesis of triarylcorroles and the corresponding metal complexes allowed for their utilization in various fields. This survey reveals many examples where corroles were used as the key components in catalysis, sensing of gaseous molecules and medicine-oriented research. The focus in all these cases was on the special features of corroles: stabilization of high valent transition metal ions, unique photophysical properties, large NH acidity, facile synthetic manipulation and distinct catalytic properties. The latter aspect includes several examples of reactions that are not catalyzed by any non-corrole metal complex, such as the iron-based aziridination by Chloramine-T, the clean disproportionation of peroxynitrite, and the very facile N-H activation of amines.     

Acyclic Hypergraph Projections

Hypergraphs can be partitioned into two classes: tree (acyclic) hypergraphs and cyclic hypergraphs. This paper analyzes a new class of cyclic hypergraphs called Xrings. HypergraphHis an Xring if the hyperedges ofHcan be circularly ordered so that for every vertex, all hyperedges containing the vertex are consecutive; in addition, the vertices of no hyperedge may be a subset of the vertices of another hyperedge, and no vertex may appear in exactly one hyperedge. LetH₁andH₂be two hypergraphs. A tree projection ofH₁with respect toH₂is an acyclic hypergraphH₃such that the vertices of each hyperedge inH₁appear among the vertices of some hyperedge ofH₃and the vertices of each hyperedge inH₃appear among the vertices of some hyperedge ofH₂. A polynomial time algorithm is presented for deciding, given XringH₁and arbitrary hypergraphH₂, whether there exists a tree projection ofH₂with respect toH₁. It is shown that hypergraphHis an Xring iff a modified adjacency graph ofHis a circular-arc graph. A linear time Xring recognition algorithm, for GYO reduced hypergraphs as inputs, is presented.     

Laser desorption fast gas chromatography–Mass spectrometry in supersonic molecular beams

A novel method for fast analysis is presented. It is based on laser desorption injection followed by fast gas chromatography-mass spectrometry (GC-MS) in supersonic molecular beams. The sample was placed in an open air or purged laser desorption compartment, held at atmospheric pressure and near room temperature conditions. Desorption was performed with a XeCl Excimer pulsed laser with pulse energy of typically 3 mJ on the surface. About 20 pulses at 50 Hz were applied for sample injection, resulting in about 0.4 s injection time and one or a few micrograms sample vapor or small particles. The laser desorbed sample was further thermally vaporized at a heated frit glass filter located at the fast GC inlet. Ultrafast GC separation and quantification was achieved with a 50-cm-long megabore column operated with a high carrier gas flow rate of up to 240 mL/min. The high carrier gas flow rate provided effective and efficient entrainment of the laser desorbed species in the sweeping gas. Following the fast GC separation, the sample was analyzed by mass spectrometry in supersonic molecular beams. Both electron ionization and hyperthermal surface ionization were employed for enhanced selectivity and sensitivity. Typical laser desorption analysis time was under 10 s. The laser desorption fast GC-MS was studied and demonstrated with the following sample/matrices combinations, all without sample preparation or extraction: (a) traces of dioctylphthalate plasticizer oil on stainless steel surface and the efficiency of its cleaning; (b) the detection of methylparathion and aldicarb pesticides on orange leaves; (c) water surface analysis for the presence of methylparathion pesticide; (d) caffeine analysis in regular and decaffeinated coffee powder; (e) paracetamol and codeine drug analysis in pain relieving drug tablets; (f) caffeine trace analysis in raw urine; (g) blood analysis for the presence of 1 ppm lidocaine drug. The features and advantages of the laser desorption fast GC-MS are demonstrated and discussed.     

A von Neumann alternating method for finding common solutions to variational inequalities

By modifying von Neumann’s alternating projections algorithm, we obtain an alternating method for solving the recently introduced Common Solutions to Variational Inequalities Problem (CSVIP). For simplicity, we mainly confine our attention to the two-set CSVIP, which entails finding common solutions to two unrelated variational inequalities in Hilbert space.     

Common Solutions to Variational Inequalities

We study the new variational inequality problem, called the Common Solutions to Variational Inequalities Problem (CSVIP). This problem consists of finding common solutions to a system of unrelated variational inequalities corresponding to set-valued mappings in Hilbert space. We present an iterative procedure for solving this problem and establish its strong convergence. Relations with other problems of solving systems of variational inequalities, both old and new, are discussed as well.