An inexact hybrid projection-proximal point algorithm for solving generalized mixed variational inequalities

In this paper, we investigate an inexact hybrid projection-proximal method for solving a class of generalized mixed variational inequalities in Hilbert spaces. We construct a general inexact hybrid projection-proximal point algorithm, in which an inexact relaxed proximal point step is followed by a suitable orthogonal projection onto a hyperplane. Under some suitable conditions concerned with the pseudomonotone set-valued mapping T, the nonsmooth convex function f and the step size λ_k, we prove the convergence of the inexact hybrid projection-proximal point algorithm for solving generalized mixed variational inequalities in Hilbert spaces.     

Prevalence and personality correlates of Facebook bullying among university undergraduates

The purpose of the present study was to examine the prevalence of cyber-bullying through Facebook in a sample of 226 Greek university undergraduates, and to explore whether big five personality characteristics, narcissism, as well as attitudes toward Facebook, technological knowledge and skills were predictive of such behavior. Participants completed a self-report questionnaire measuring the above constructs. Results indicated that almost one third of the sample reported Facebook bullying engagement at least once during the past month, with male students reporting more frequent involvement than females. Bullying through Facebook was predicted by low Agreeableness and more time spent on Facebook only for males, whereas for females none of the studied variables predicted engagement in Facebook bullying. Findings are discussed in terms of prevention and intervention strategies.     

Group path covering and distance two labeling of graphs

For a positive integer d, an L(d,1)-labeling f of a graph G is an assignment of integers to the vertices of G such that |f(u)−f(v)|?d if uv∈E(G), and |f(u)−f(v)|?1 if u and u are at distance two. The span of an L(d,1)-labeling f of a graph is the absolute difference between the maximum and minimum integers used by f. The L(d,1)-labeling number of G, denoted by λd,1(G), is the minimum span over all L(d,1)-labelings of G. An L^′(d,1)-labeling of a graph G is an L(d,1)-labeling of G which assigns different labels to different vertices. Denote by the L^′(d,1)-labeling number of G. Georges et al. [Discrete Math. 135 (1994) 103-111] established relationship between the L(2,1)-labeling number of a graph G and the path covering number of Gc, the complement of G. In this paper we first generalize the concept of the path covering of a graph to the t-group path covering. Then we establish the relationship between the L^′(d,1)-labeling number of a graph G and the (d−1)-group path covering number of Gc. Using this result, we prove that and for bipartite graphs G can be computed in polynomial time.     

Necessary optimality conditions for fuzzy variational problems

The main aims of this study are to derive the fuzzy Euler-Lagrange conditions for both fuzzy unconstrained and constrained variational problems based on the concepts of differentiability and integrability of a fuzzy mapping that may be parameterized by the left and right-hand functions of its α-level sets.     

Strong stability of the mono-tubular heat exchanger equation with output feedback

We investigate asymptotic behavior of the C₀-semigroup T(t) associated with the mono-tubular heat exchanger equation with output feedback by a perturbation method. It is shown that T(t) is bounded if a constraint is satisfied by the parameters and the spatial distribution function. Further, applying the Arendt-Batty-Lyubich-Vu theorem, a criterion is established to judge strong stability of T(t).     

Geoadditive expectile regression

Quantile regression has emerged as one of the standard tools for regression analysis that enables a proper assessment of the complete conditional distribution of responses even in the presence of heteroscedastic errors. Quantile regression estimates are obtained by minimising an asymmetrically weighted sum of absolute deviations from the regression line, a decision theoretic formulation of the estimation problem that avoids a full specification of the error term distribution. Recent advances in mean regression have concentrated on making the regression structure more flexible by including nonlinear effects of continuous covariates, random effects or spatial effects. These extensions often rely on penalised least squares or penalised likelihood estimation with quadratic penalties and may therefore be difficult to combine with the linear programming approaches often considered in quantile regression. As a consequence, geoadditive expectile regression based on minimising an asymmetrically weighted sum of squared residuals is introduced. Different estimation procedures are presented including least asymmetrically weighted squares, boosting and restricted expectile regression. The properties of these procedures are investigated in a simulation study and an analysis on rental fees in Munich is provided where the geoadditive specification allows for an analysis of nonlinear effects of the size of flats or the year of construction and the spatial distribution of rents simultaneously.     

Multiplex ligation-dependent probe amplification (MLPA) for simultaneous detection of DNA from sunflower,poppy, flaxseed,sesame and soy allergenic ingredients in commercial food products

This work describes a multiplex ligation-dependent probe amplification (MLPA) technique for the simultaneous detection of five food allergens: sunflower, poppy, flaxseed, sesame and soy. Species-specific MLPA half-probes were designed to detect the DNA from the targeted species. Ligated probes were amplified by polymerase chain reaction (PCR) and amplicons were detected using capillary electrophoresis. The specificity of the MLPA system was assessed against DNA from more than 50 plant and animal species. The limit of detection (LOD) of the assay was determined to be 10 mg kg⁻¹in a model cookie experimentally spiked with different concentrations of the target species. The applicability of the MLPA was demonstrated through the analysis of 56 different commercial products (breads, pastries, cereals, chocolates, drinks, etc.), evidencing the presence of one or more undeclared allergenic ingredients in some of the tested samples. Real-time PCR assays were also performed to confirm and complement MLPA results. The MLPA technique has proved as a qualified screening tool for determining the presence of low amounts of sunflower, poppy, flaxseed, sesame and soy in processed foods.     

The effects of oxygenation aeration treatment on dissipation behaviors of tricaine mesylate in carp (Cyprinus carpio) muscle and water

Tricaine mesylate (MS-222) is one of the most used anesthetics in fish. It can be absorbed by the human body via food consumption, with related detriments to human health. In this study, a modified quick, easy, cheap, effective, rugged, and safe (QuEChERS) method was developed for the determination of MS-222 in carp muscle and water samples using liquid chromatography-tandem mass spectrometry (LC-MS/MS). For cleanup procedure, multiplug filtration cleanup (m-PFC) method with n-Hexane delipidation was adopted. The extraction solvent, cleanup methods and sorbents were optimized. All method validation parameters were in the acceptable range. The dissipation behavior study was followed by the method development. Firstly, the anesthesia dose and time were optimized in application study. Secondly, carps were revived for different period of time with (experimental group) and without (control group) the oxygenation aeration treatment to compare the dissipation rate of MS-222. After being anesthetized for 6 h at 50 mg/L and 12 h of elimination, the concentrations of MS-222 in crap muscle and water of experimental group was lower than those of control group. After 36 h of elimination under oxygenation aeration, over 90% of MS-222 was dissipated in carp muscle. The results showed that the half-life of MS-222 in carp muscle was 6.2 h. The findings suggested that the commonly-used oxygenation aeration treatment in aquaculture production had potential effects in accelerating the dissipation of MS-222 in carp and water. In this study, three days of withdrawal period was recommended in carps after MS-222 administration under oxygenation aeration.     

Multi-walled carbon nanotubes-based magnetic solid-phase extraction for the determination of zearalenone and its derivatives in maize by ultra-high performance liquid chromatography-tandem mass spectrometry

A simple and rapid magnetic solid-phase extraction (M-SPE) procedure using multi-walled carbon nanotube-magnetic nanoparticles (MWCNT-MNPs) as sorbents was established for purification of zearalenone (ZEA), α-zearalenol (α-ZOL), β-zearalenol (β-ZOL), zearalanone (ZAN), α-zearalanol (α-ZAL) and β-zearalanol (β-ZAL) in maize. The main parameters affecting the clean-up efficiency were thoroughly investigated, and high purification efficiencies for all analytes were obtained. The resulting MWCNT-MNP-ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method was validated for maize samples. The matrix effects were greatly minimized using the M-SPE approach, with signal suppression/enhancement values decreased from 69.9–127.6% to 92.1–103.8%. Consequently, complex matrix-matched calibration curves were not necessary and the calibrations constructed in acetonitrile could be applied for accurate quantification of the targeted mycotoxins in real samples. The average recoveries ranged from 75.8 to 104.1% and the inter- and intra-day precision values expressed as RSDs, were all lower than 14%. Limits of detection and quantification were in the range of 0.03–0.04 and 0.07–0.10 μg/kg, respectively. The analytical performance of the developed method was also successfully evaluated with maize samples, and this method was proved to be a powerful tool for monitoring ZEA and its derivatives in maize.     

Analytical evaluation of different carbon sources and growth stimulators on the biomass and lipid production of Chlorella vulgaris – Implications for biofuels

The key challenges in lipid production from marine microalgae include the selection of appropriate strain, optimization of the culture conditions and enhancement of biolipid yield. This study is aimed at evaluating the optimal harvest time and effect of chlorella growth factor (CGF) extract, carbon sources and phytohormones on the biomass and lipid production in Chlorella vulgaris. CGF, extracted using hot water from Chlorella has been reported to possess various medicinal properties. However, in the present study, for the first time in C. vulgaris, CGF was found as a best growth stimulator by enhancing the biomass level (1.208 kg m⁻³) significantly on day 5. Gibberellin and citrate augmented the biomass by 0.935 kg m⁻³ and 1.025 kg m⁻³. Combination of CGF and phytohormones were more effective than CGF and carbon sources. Analysis of fatty acid methyl esters indicated that the ratio of saturated to unsaturated fatty acids is higher in cytokinin, abscisic acid and CGF, and are also rich in short chain carbon atoms, ideal criteria for biodiesel. Nitrogen starvation favoured synthesis of more unsaturated fatty acids than saturated. This study shows that CGF enhances the biomass and lipid significantly and thus can be used for large scale biomass production.