Topological insight into the non-Arrhenius mode hopping of semiconductor ring lasers

We investigate both theoretically and experimentally the stochastic switching between two counter-propagating lasing modes of a semiconductor ring laser. Experimentally, the residence time distribution cannot be described by a simple one parameter Arrhenius exponential law and reveals the presence of two different mode-hop scenarios with distinct time scales. In order to elucidate the origin of these two time scales, we propose a topological approach based on a two-dimensional dynamical system.Comment: 4 pages, 3 figure

Experimental evidence of localized oscillations in the photosensitive chlorine dioxide-iodine-malonic acid reaction

The interaction between Hopf and Turing modes has been the subject of active research in recent years. We present here experimental evidence of the existence of mixed Turing-Hopf modes in a two-dimensional system. Using the photosensitive chlorine dioxide-iodine-malonic acid reaction (CDIMA) and external constant background illumination as a control parameter, standing spots oscillating in amplitude and with hexagonal ordering were observed. Numerical simulations in the Lengyel-Epstein model for the CDIMA reaction confirmed the results

Inflation persistence in structural macroeconomic models (RG10)

This paper analyses the response of inflation in the euro area to five macroeconomic shocks through the use of results derived from Eurosystem large-scale macroeconomic models. The main finding is that only a fiscal shock, and to a lesser extent a TFP shock, generate marked inflation persistence. In contrast, an indirect tax and an oil price shock appear much less persistent and a social security shock generates less inflation persistence in the majority of the countries (although some weak persistence was observed at the euro area level). The paper also considers evidence on the sources of persistence, which indicates that it is crucially affected by the responsiveness of wages to employment, by the sluggishness in the adjustments of the demand components, and by the speed of adjustment of employment to output and wage changes. JEL Classification: C53, E31, E52impulse response function, Inflation persistence, large-scale macroeconomic models

Correlator of heavy-quark currents at small q^2 in the large-beta_0 limit

The correlator of vector heavy-quark currents at small q^2 is considered in the large-beta_0 limit. The leading IR renormalon ambiguity of the sum of the perturbative series is canceled by the UV renormalon ambiguity of the gluon condensate. Asymptotic behaviour of the perturbative series is obtained in a model-independent way, up to a single unknown normalization factor. Gluon-virtuality distribution functions for the perturbative correction are calculated.Comment: 8 pages, 3 figure

Microfossils of the Yangtzeplacognathus crassus zone in the middle darriwilian of the argentine precordillera

The San Juan Formation of the Eastern and Central Precordillera is composed mainly of fossiliferous limestone and marly limestone. The conodont biostratigraphy of the very top of this unit has been studied on several localities such as: Don Braulio, La Pola, Cecilia and Del Aluvión creeks, recording the Y. crassus Zone for this levels (Mestre, 2010; Mestre, 2013, Heredia and Mestre, 2013). The microfossils associated to this conodont biozone are represented by spicules, foraminifers and protoconchs, which are reported and figured in this work.Fil: Mestre Garcia, Ana Isabel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico San Juan. Centro de Investigaciones de la Geosfera y Biosfera; ArgentinaFil: Beresi, Matilde Sylvia. Consejo Nacional de Investigaciones Científicas y Técnicas. Científico Tecnológico Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; ArgentinaFil: Heredia, Susana Emma. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico San Juan. Centro de Investigaciones de la Geosfera y Biosfera; ArgentinaFil: Nestell, G.. University Of Texas; Estados Unido

Multi-class determination of undesirables in aquaculture samples by gas chromatography/tandem mass spectrometry with atmospheric pressure chemical ionization: A novel approach for polycyclic aromatic hydrocarbons

In this work, a method for the analysis of 24 PAHs in 19 different matrices, including fish tissues, feeds and feed ingredients, has been developed using gas chromatography coupled to triple quadrupole tandem mass spectrometry with atmospheric pressure chemical ionization source (GC-APCI-MS/MS). The method is based on a modification of the unbuffered QuEChERS method, using freezing as an additional clean-up step and applying a 20-fold dilution factor to the final extract. The procedure was also tested for 15 pesticides and 7 polychlorinated biphenyl (PCB) congeners in order to widen the scope of the method. The excellent sensitivity and selectivity provided by GC-APCI-MS/MS allowed the dilution of the sample extracts and quantification using calibration with standards in solvent for all the 19 matrices tested. The developed method was evaluated at 2, 5 and 50 ng·g-1 spiking levels. LOQs were 2 ng·g-1 for most compounds, and LODs ranged from 0.5 to 2 ng·g-1. Analysis of real-world samples revealed the presence of naphthalene, fluorene, phenanthrene, fluoranthene and pyrene at concentration levels ranging from 4.8 to 187 ng·g-1. No PCBs, DDTs and pesticides were found in fillets from salmon and sea bream

Exploiting graphlet decomposition to explain the structure of complex networks: the GHuST framework

The characterization of topology is crucial in understanding network evolution and behavior. This paper presents an innovative approach, the GHuST framework to describe complex-network topology from graphlet decomposition. This new framework exploits the local information provided by graphlets to give a global explanation of network topology. The GHuST framework is comprised of 12 metrics that analyze how 2- and 3-node graphlets shape the structure of networks. The main strengths of the GHuST framework are enhanced topological description, size independence, and computational simplicity. It allows for straight comparison among different networks disregarding their size. It also reduces the complexity of graphlet counting, since it does not use 4- and 5-node graphlets. The application of the novel framework to a large set of networks shows that it can classify networks of distinct nature based on their topological properties. To ease network classification and enhance the graphical representation of them, we reduce the 12 dimensions to their main principal components. Furthermore, the 12 dimensions are easily interpretable. This enables the connection between complex-network analyses and diverse real applications

Screening of Pesticides and Polycyclic Aromatic Hydrocarbons in Feeds and Fish Tissues by Gas Chromatography Coupled to High-Resolution Mass Spectrometry Using Atmospheric Pressure Chemical Ionization

This paper reports a wide-scope screening for detection and identification of pesticides and polycyclic aromatic hydrocarbons (PAHs) in feeds and fish tissues. QuEChERS sample treatment was applied, using freezing as an additional cleanup. Analysis was carried out by gas chromatography coupled to hybrid quadrupole time-of-flight mass spectrometry with atmospheric pressure chemical ionization (GC-(APCI) QTOF MS). The qualitative validation was performed for over 133 representative pesticides and 24 PAHs at 0.01 and 0.05 mg/kg. Subsequent application of the screening method to aquaculture samples made it possible to detect several compounds from the target list, such as chlorpyrifos-methyl, pirimiphos-methyl, and ethoxyquin, among others. Light PAHs (≤4 rings) were found in both animal and vegetable samples. The reliable identification of the compounds was supported by accurate mass measurements and the presence of at least two representative m/z ions in the spectrum together with the retention time of the peak, in agreement with the reference standard. Additionally, the search was widened to include other pesticides for which standards were not available, thanks to the expected presence of the protonated molecule and/or molecular ion in the APCI spectra. This could allow the detection and tentative identification of other pesticides different from those included in the validated target list

Scintillating double beta decay bolometers

We present the results obtained in the development of scintillating Double Beta Decay bolometers. Several Mo and Cd based crystals were tested with the bolometric technique. The scintillation light was measured through a second independent bolometer. A 140 g CdWO_4 crystal was run in a 417 h live time measurement. Thanks to the scintillation light, the alpha background is easily discriminated resulting in zero counts above the 2615 keV gamma line of Thallium 208. These results, combined with an extremely easy light detector operation, represent the first tangible proof demonstrating the feasibility of this kind of technique.Comment: 15 pages, 8 figure

Deep learning-based segmentation of multiple species of weeds and corn crop using synthetic and real image datasets

Weeds compete with productive crops for soil, nutrients and sunlight and are therefore a major contributor to crop yield loss, which is why safer and more effective herbicide products are continually being developed. Digital evaluation tools to automate and homogenize field measurements are of vital importance to accelerate their development. However, the development of these tools requires the generation of semantic segmentation datasets, which is a complex, time-consuming and not easily affordable task. In this paper, we present a deep learning segmentation model that is able to distinguish between different plant species at the pixel level. First, we have generated three extensive datasets targeting one crop species (Zea mays), three grass species (Setaria verticillata, Digitaria sanguinalis, Echinochloa crus-galli) and three broadleaf species (Abutilon theophrasti, Chenopodium albums, Amaranthus retroflexus). The first dataset consists of real field images that were manually annotated. The second dataset is composed of images of plots where only one species is present at a time and the third type of dataset was synthetically generated from images of individual plants mimicking the distribution of real field images. Second, we have proposed a semantic segmentation architecture by extending a PSPNet architecture with an auxiliary classification loss to aid model convergence. Our results show that the network performance increases when supplementing the real field image dataset with the other types of datasets without increasing the manual annotation effort. More specifically, the use of the real field dataset obtains a Dice-Søensen Coefficient (DSC) score of 25.32. This performance increases when this dataset is combined with the single-species class dataset (DSC=47.97) or the synthetic dataset (DSC=45.20). As for the proposed model, the ablation method shows that by removing the proposed auxiliary classification loss, the segmentation performance decreases (DSC=45.96) compared to the proposed architecture method (DSC=47.97). The proposed method shows better performance than the current state of the art. In addition, the use of proposed single-species or synthetic datasets can double the performance of the algorithm than when using real datasets without additional manual annotation effort.We would like to thank BASF technicians Rainer Oberst, Gerd Kraemer, Hikal Gad, Javier Romero and Juan Manuel Contreras, as well as Amaia Ortiz-Barredo from Neiker for their support in the design of the experiments and the generation of the data sets used in this work. This was partially supported by the Basque Government through ELKARTEK project BASQNET(ref K-2021/00014)