Solution of a model for the two-channel electronic Mach-Zehnder interferometer

We develop the theory of electronic Mach-Zehnder interferometers built from quantum Hall edge states at Landau level filling factor \nu = 2, which have been investigated in a series of recent experiments and theoretical studies. We show that a detailed treatment of dephasing and non-equlibrium transport is made possible by using bosonization combined with refermionization to study a model in which interactions between electrons are short-range. In particular, this approach allows a non-perturbative treatment of electron tunneling at the quantum point contacts that act as beam-splitters. We find an exact analytic expression at arbitrary tunneling strength for the differential conductance of an interferometer with arms of equal length, and obtain numerically exact results for an interferometer with unequal arms. We compare these results with previous perturbative and approximate ones, and with observations.Comment: 13 pages, 9 figures, final version as publishe

Seasonality in coastal macrobenthic biomass and its implications for estimating secondary production using empirical models

Macrobenthic secondary production is widely used to assess the trophic capacity, health, and functioning of marine and freshwater ecosystems. Annual production estimates are often calculated using empirical models and based on data collected during a single period of the year. Yet, many ecosystems show seasonal variations. Although ignoring seasonality may lead to biased and inaccurate estimates of annual secondary production, it has never been tested at the community level. Using time series of macrobenthic data collected seasonally at three temperate marine coastal soft-bottom sites, we assessed seasonal variations in biomass of macrobenthic invertebrates at both population and community levels. We then investigated how these seasonal variations affect the accuracy of annual benthic production when assessed using an empirical model and data from a single sampling event. Significant and consistent seasonal variations in biomass at the three study sites were highlighted. Macrobenthic biomass was significantly lower in late winter and higher in summer/early fall for 18 of the 30 populations analyzed and for all three communities studied. Seasonality led to inaccurate and often biased estimates of annual secondary production at the community level when based on data from a single sampling event. Bias varied by site and sampling period, but reached similar to 50% if biomass was sampled at its annual minimum or maximum. Since monthly sampling is rarely possible, we suggest that ecologists account for uncertainty in annual production estimates caused by seasonality.Agência financiadora EDF French Ministry of Higher Education, Research and Innovation French Ministry for the Ecological and Inclusive Transition through the Marine Strategy Framework Directive Agreement French Biodiversity Agency (Agence francaise pour la biodiversite) as part of the CAPANOUR projectinfo:eu-repo/semantics/publishedVersio

Effect of the method of preservation on the chemical composition and in vitro fermentation characteristics in two legumes rich in condensed tannins

The objective of the present study was to evaluate the effects of preservation (hay and silage) on the chemical composition and the in vitro fermentation characteristics in comparison with fresh forage in two legumes rich in condensed tannins (CT). Sainfoin (Onobrychis viciifolia) was collected at the late bloom stage and sulla (Hedysarum coronarium) at the early bloom stage. In each forage, a part was immediately freeze-dried, a part was dried at ambient temperature to obtain hay, and another part was ensiled in vacuum-packages for 82 days. An in vitro assay to study the fermentation was carried out with an Ankom system during 72 h. In both forages, the silages had different contents of polyphenols and condensed tannins fractions than fresh forage and hay (P<0.05). Sainfoin hay only had greater content of fibre-bound CT fraction (FBCT) than fresh sainfoin, whereas sulla hay had greater protein-bound CT and FBCT contents than fresh sulla (P<0.05). Sainfoin silage had lower gas and methane production than hay and fresh forage (P < 0.001), whereas fresh sulla had greater gas and methane production, followed by hay and silage, which produced the least (P<0.05). In both legumes, hay had lower in vitro organic matter digestibility (IVOMD) than silage and fresh forage (P<0.001). The method of preservation affected the total production of volatile fatty acids (VFA) only in sulla (P<0.05). Most of the proportions of individual VFA were affected by the method of preservation in both legumes (P<0.001). In conclusion, polyphenols content, total content and fractions of CT were more affected in the silages than in the hays when compared to fresh forages. However, according to gas and methane production and IVOMD, silage may have greater feed nutritive value than hay although further studies on animal performance are warranted before recommendation

Methane Production of Fresh Sainfoin, with or without PEG, and Fresh Alfalfa at Different Stages of Maturity is Similar, but the Fermentation End Products Vary (vol 9, 197, 2019)

The authors wish to make the following correction to their paper [1]. In Table 2, the production of methane in alfalfa at the start-flowering should be 38 mL/g dOM and not 3 mL/g dOM. Table 2. Effect of the substrate (S) and the stage of maturity 1 (SM) on gas and methane production (CH4), potential gas production (A), rate of gas production (c), in vitro organic matter degradability (IVOMD), ammonia (NH3-N), and volatile fatty acids (VFAs). Table The authors would like to apologize for any inconvenience caused

Towards precise recognition of pollen bearing bees by convolutional neural networks

Automatic recognition of pollen bearing bees can provide important information both for pollination monitoring and for assessing the health and strength of bee colonies, with the consequent impact on people's lives, due to the role of bees in the pollination of many plant species. In this paper, we analyse some of the Convolutional Neural Networks (CNN) methods for detection of pollen bearing bees in images obtained at hive entrance. In order to show the in uence of colour we preprocessed the dataset images. Studying the results of nine state-of-the-art CNNs, we provide a baseline for pollen bearing bees recognition based in deep learning. For some CNNs the best results were achieved with the original images. However, our experiments showed evidence that DarkNet53 and VGG16 have superior performance against the other CNNs tested, with unsharp masking preprocessed images, achieving accuracy results of 99:1% and 98:6%, respectively.info:eu-repo/semantics/publishedVersio

Carotenoids and liposoluble vitamins in the plasma and tissues of light lambs given different maternal feedings and fattening concentrates

The carotenoids and liposoluble vitamins in the plasma and tissues of the lambs under different maternal feedings and fattening concentrates was studied. During lactation, 21 lambs were housed with their dams, that received a total mixed ration (intensive); 21 ewe–lamb pairs grazed on alfalfa; and 21 pairs grazed on sainfoin. After weaning, half of the lambs in each maternal feeding group received a commercial concentrate (control) and the other half a concentrate with quebracho (Schinopsis balansae), as a source of condensed tannins, until they were slaughtered (23 kg). The analyte concentrations in the plasma of lambs at weaning reflected the content in the feedstuffs. Grazing during suckling more than doubled the contents of lutein in the liver and retinol in the tissues compared to the intensive feeding. The content of a-tocopherol in the tissues was greatest in sainfoin lambs, intermediate in alfalfa lambs, and lowest in the intensive lambs. The quebracho concentrate decreased a-tocopherol (by 41–81%) and ¿-tocopherol (by 65–89%) contents in the lamb tissues. The use of the analytes in the plasma at weaning correctly classified 100% of the lambs into the maternal feeding (intensive vs. grazing (alfalfa + sainfoin)) but has to be improved in the carcass and tissues separately

Relationship-Contingent Self-Esteem As A Moderator Of Borderline Personality Features And Mate Retention

The current study examined the relationship between borderline personality features, relationship-contingent self-esteem, and mate retention behaviors. Participants were recruited through Amazon’s Mechanical Turk. They completed the Personality Inventory for the DSM-5, the Rosenberg Self-Esteem Scale, the Relationship-Contingent Self- Esteem Scale, and the Mate Retention Inventory-Short Form. Participants then received feedback through the modified Future Alone Manipulation, where they were randomly assigned to one of three feedback conditions: positive, negative, or negative control. After the feedback, participants completed the Mate Retention Inventory-Short Form to assess their response to feedback. Contrary to our predictions, borderline personality features (BPF) were not correlated with relationship-contingent self-esteem (RCSE), and RCSE and threat did not moderate the relationship between BPF and mate retention behaviors (MRB). Consistent with our hypotheses, BPF predicted the used of cost-inflicting MRB. Interestingly, RCSE predicted the use of benefit-provisioning MRB. This research is the first to address the relationship between BPF and RCSE and provides insight into individuals differences in relationship behaviors

Estimating fishing effort in small-scale fisheries using high-resolution spatio-temporal tracking data (an implementation framework illustrated with case studies from Portugal)

Marta M. Rufino is funded by a DL57 contract (junior researcher) awarded by IPMA within the project “Real-time monitoring of bivalve dredge fisheries” (MONTEREAL, MAR-01.03.02-FEAMP-0022), funded by the Fisheries Operational Programme (MAR 2020) and co-financed by the European Maritime and Fisheries Fund (EMFF 2014–2020). João Samarão received a research grant (Ref: IPMA-2022-015-BII) awarded by IPMA within the framework of the project PESCAPANHA.Small-scale fisheries (SSF, boats < 12 m) represent 90% of this sector at a worldwide scale and 84% of the EU fleet. Mapping the areas and intensity where the fishing operations occur is essential for spatial planning, safety, fisheries sustainability and biodiversity conservation. The EU is currently regulating position tracking of SSF fishing vessels requiring precision resolved geo-positional data (sec to min resolution). Here we developed a series of procedures aimed at categorizing fishing boats behaviour using high resolution data. Our integrated approach involve novel routines aimed at (i) produce an expert validated data set, (ii) pre-processing of positional data, (iii) establishing minimal required temporal resolution, and (iv) final assessment of an optimized classification model. Objective (iv) was implemented by using statistical and machine learning (ML) routines, using novel combinations of fixed thresholds estimates using regression trees and classification methods based on anti-mode, Gaussian Mixture Models (GMM), Expectation Maximisation (EM) algorithms, Hidden Markov Models (HMM) and Random Forest (RF). Of relevance, the final evaluation framework incorporates both error quantification and fishing effort indicators. We tested the method by running through four SSF fisheries from Portugal recorded every 30 sec, with 183 boat trips validated, and concluded that the more robust time interval for data acquisition in these metiers should bePublisher PDFPeer reviewe