Dreissenid colonization during the initial invasion of the quagga mussel in the largest Central European shallow lake,Lake Balaton,Hungary

The colonization progress of the invasive bivalve dreissenids, the formerly dominant Dreissena polymorpha and the recently (2008) introduced Dreissena rostriformis bugensis was studied between 2009 and 2013 in the largest Central European shallow lake, Lake Balaton, Hungary. The density of dreissenid planktonic veligers, new settlers (post-veligers and early juveniles), and the population structure (density, length frequency, relative abundance) of the two species were monitored on experimentally introduced natural stone substrata, on different time scales. Dreissenids started dynamic settling following a sudden veliger bloom. As substratum saturation progressed, competition between species for places was suggested, which, after two years, led to an increased number of large individuals (> 20 mm) and also recruits of D. r. bugensis. By contrast, the population of D. polymorpha was confined to middle size (11–18 mm) individuals of the first settler generation. On local substrata, where the benthic community was already established, the replacement of D. polymorpha by D. r. bugensis took longer, but it happened in a similar way. The invasion speed of D. r. bugensis in Lake Balaton resembled the speed obtained in other European water bodies where D. r. bugensis, similar to Lake Balaton, was introduced much later than D. polymorpha. However, a longer replacement process was found in North America, where both species invaded new habitats at the same time. This suggests that the speed, and probably the success, of D. r. bugensis invasion depends on new surface availability, and whether the two dreissenid species are introduced together or at different times.     

Exploration of the chaotic phenomena induced by fast plastic deformation of metals

We developed a nonlinear mathematical model for chip formation during cutting, comprising four autonomous differential equations and a constitutive equation describing the characteristics of metals. We used a continuation and bifurcation software to find the possible solutions of the differential equations. Certain solutions were determined using numerical simulation and the obtained times series were examined. The seven-dimensional parameter-space of the solutions was partially explored. We found that periodic solutions typically undergo a sequence of period doubling bifurcations as the model parameters are varied. We pointed out during the analysis of the set of equations that chaotic phenomena may also occur besides the formation of continuous chips reflecting a stable equilibrium state and lamellar chips that can be characterised by a periodic solution. Our model was verified by experimental results.     

Deoxynivalenol in wheat,maize, wheat flour and pasta: surveys in Hungary in 2008–2015

Among Fusarium mycotoxins, deoxynivalenol (DON) is the most common contaminant in case of cereals and cereal-based foods in Hungary. In this study, Hungarian wheat (n = 305), maize (n = 108), wheat flour (n = 179) and pasta (n = 226) samples were analysed (N = 818). The samples were collected during 2008–2015 in Hungary. Applied methods of analysis were enzyme-linked immunosorbent assay and liquid-chromatography coupled with a mass spectrometer. Results were compared and evaluated with Hungarian weather data. Among cereal samples, in 2011, wheat was contaminated with DON (overall average ± standard deviation was 2159 ± 2818 µg kg^?1), which was above the maximum limit (ML). In case of wheat flour and pasta, no average values above ML were found during 2008–2015, but higher DON contamination could be observed in 2011 as well (wheat flour: 537 ± 573 µg kg^?1; pasta: 511 ± 175 µg kg^?1).     

Species-specific isotope dilution-based calibration for trace element speciation and its combined uncertainty evaluation: determination of tributyltin in sediment by HPLC-ICPMS

A method is described for the determination of tributyltin (TBT) in NRCC sediment CRM PACS-2 by isotope dilution (ID) analysis using HPLC-ICPMS. Reverse spike ID analysis was performed to determine the accurate concentration of a 117Sn-enriched TBT spike using a well-characterized natural abundance TBT standard. The accuracy of the latter is critical for obtaining reliable results. A unique approach, using hydride generation GC/MS, was developed to quantify the inorganic Sn and dibutyltin impurities in the natural abundance TBT standard. The true natural abundance TBT standard concentration was obtained following correction for these impurities. The total Sn concentration in the natural abundance TBT standard was determined by ID analysis using an enriched inorganic 117Sn following closed vessel mixed-acid digestion. Calibration of the enriched inorganic 117Sn standard was achieved by reverse ID analysis against a natural abundance inorganic tin standard prepared from the high-purity metal. An overall uncertainty associated with the present method was estimated, to which the uncertainties arising from measurement of the natural abundance TBT concentration, from the measurement of the isotope ratio in the spiked sample and in the reverse ID calibration solutions, and from estimation of the extraction efficiency were the main contributors. A concentration of 1.018 +/- 0.054 mg kg(-1) (expanded uncertainty, k = 2) as tin was obtained for TBT in PACS-2 using the present method, in excellent agreement with the certified value of 0.98 +/- 0.13 mg kg(-1) (95% confidence interval). A TBT concentration of 0.97 +/- 0.11 mg kg(-1) (expanded uncertainty, k = 2) as tin in PACS-2 was determined using the standard additions technique. Much smaller expanded uncertainty was obtained with ID, clearly demonstrating its superiority in providing more accurate and precise results over the method of additions. A detection limit (3sigma) of 0.02 mg kg(-1) for TBT, based on a 0.5-g subsample, was obtained.     

Determination of methionine and selenomethionine in yeast by species-specific isotope dilution GC/MS

A method for the simultaneous determination of methionine (Met) and selenomethionine (SeMet) in yeast using species-specific isotope dilution (ID) gas chromatography/mass spectrometry (GC/MS) is described. Samples were digested by refluxing for 16 h with 4 M methanesulfonic acid. Analytes were derivatized with methyl chloroformate and extracted into chloroform for GC/MS analysis. In addition to use of commercially available 13C-enriched Met and SeMet spikes for species specific ID analysis, a 74Se-enriched SeMet spike was also available for comparison of results. In selective ion monitoring mode, the intensities of ions at m/z 221, 222, 269, 270, and 263 were used to calculate the 221/222, 269/270, and 269/263 ion ratios for quantification of Met and SeMet. Concentrations of 5959 +/- 33 and 3404 +/- 12 microg g(-1) (one standard deviation, n = 6) with relative standard deviations of 0.55 and 0.36% for Met and SeMet, respectively, were obtained using 13C-enriched spikes. A concentration of 3417 +/- 8 microg g(-1) (one standard deviation, n = 6) was obtained using the 74Se-enriched SeMet spike. The concentration of SeMet measured in the yeast is equivalent to 66.43 +/- 0.24% of total Se and 30.31 +/- 0.11% of total Met is in the form of SeMet. Method detection limits (three times the standard deviation) of 3.4 and 1.0 microg g(-1) were estimated for Met and SeMet, respectively, based on a 0.25-g subsample of yeast with 1 mL of extract used for derivatization. A similar concentration of 5930 +/- 29 microg g(-1) (one standard deviation, n = 4) for Met and a lower concentration of 2787 +/- 49 microg g(-1) (one standard deviation, n = 4) for SeMet were obtained for this yeast sample using species-specific ID analysis based on GC/MS with 13C-enriched Met and SeMet spikes when a 2-h open microwave digestion approach using 8 M methanesulfonic acid was used.     

Quantitation of amphetamine,methamphetamine, and their methylenedioxy derivatives in urine by solid-phase microextraction coupled with electrospray ionization-high-field asymmetric waveform ion mobility spectrometry-mass spectrometry

Amphetamine, methamphetamine, and their methylenedioxy derivatives have been identified and measured in a human urine matrix using solid-phase microextraction (SPME) and high-field asymmetric waveform ion mobility spectrometry (FAIMS) in combination with electrospray ionization (ESI) and mass spectrometric detection (MS). Limits of detection in human urine between 200 pg/mL and 7.5 ng/mL have been achieved. The use of a simple extraction method, SPME, combined with the high sensitivity and selectivity of ESI-FAIMS-MS eliminates the need for chromatographic separation and allows for very rapid sample processing.     

Modeling stimulus‐driven attentional selection in dynamic natural scenes

In this paper we have developed a neuromorphic model of bottom‐up (BU) visual attentional selection. The output of a recently developed neuromorphic multi‐channel retina model has represented the input of our model. As a first step, a saliency map has been calculated for each retinal channel which, next, has been integrated into a master saliency map. Model parameters have been optimized based on human eye movement data measured during viewing dynamic natural scenes. We have tested two different strategies for weighting the channel‐specific saliency maps during integration into a master map. In the first case, channel weights have been kept constant throughout the verification measurements, whereas, in the other case, they have been updated on each frame, according to the specific properties of the visual input. Surprisingly, the constant channel weighting strategies have performed better than the continually updated ones. We have measured the model's accuracy by defining the hit ratio (concurrence) between the first few predicted locations (the most salient locations) and the measured fixation locations. Constant weighting methods have achieved ～74% hit ratio on four predictions. For a comparison, the accidental chance for this case has been less than 20%. This pure BU approach has performed surprisingly well on dynamic natural input. Some practical applications have already been made with task‐dependent simplifications. Copyright © 2008 John Wiley & Sons, Ltd.     

Improving object classification robustness in RGB-D using adaptive SVMs

Nowadays object recognition is a fundamental capability for an autonomous robot in interaction with the physical world. Taking advantage of new sensing technologies providing RGB-D data, the object recognition capabilities increase dramatically. Object recognition has been well studied, however, known object classifiers usually feature poor generality and, therefore, limited adaptivity to different application domains. Although some domain adaptation approaches have been presented for RGB data, little work has been done on understanding the effects of applying object classification algorithms using RGB-D for different domains. Addressing this problem, we propose and comprehensively investigate an approach for object recognition in RGB-D data that uses adaptive Support Vector Machines (aSVM) and, in this way, achieves an impressive robustness in cross-domain adaptivity. For evaluation, two datasets from different application domains were used. Moreover, a study of state-of-the-art RGB-D feature extraction techniques and object classification methods was performed to identify which combinations (object representation - classification algorithm) remain less affected in terms of performance while switching between different application domains.