Optimal antibunching in passive photonic devices based on coupled nonlinear resonators

We propose the use of weakly nonlinear passive materials for prospective applications in integrated quantum photonics. It is shown that strong enhancement of native optical nonlinearities by electromagnetic field confinement in photonic crystal resonators can lead to single-photon generation only exploiting the quantum interference of two coupled modes and the effect of photon blockade under resonant coherent driving. For realistic system parameters in state of the art microcavities, the efficiency of such single-photon source is theoretically characterized by means of the second-order correlation function at zero time delay as the main figure of merit, where major sources of loss and decoherence are taken into account within a standard master equation treatment. These results could stimulate the realization of integrated quantum photonic devices based on non-resonant material media, fully integrable with current semiconductor technology and matching the relevant telecom band operational wavelengths, as an alternative to single-photon nonlinear devices based on cavity-QED with artificial atoms or single atomic-like emitters.Comment: to appear in New J. Physic

Indicators-based spatial SWOT analysis: supporting the strategic planning and management of complex territorial systems

Optimizing the multiple uses of land represents a challenge for today's governments and land managers. In particular, protected area planning should satisfy the demand for multiple land uses, while offering optimal protection of our natural resources. The present research aims at providing park's managers, as well as other stakeholders and decision makers, with a scientifically sound and practical approach to zoning protection levels and supporting the strategic planning phase in nature conservation. This paper thus proposes and tests the development of an indicators-based spatial Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis for a complex territorial system with exceptional multiple values. As a result, key conservation priorities and warning spots are identified to support the subsequent decision-making phase. The innovative value of the research stems not only from the integrated methodological approach based on the combination between spatial analysis, indicators systems and the traditional SWOT analysis, but also from the contextual characteristics and physical extension of the area under investigation. Moreover, the integrated and innovative framework proposed in the paper has also international significance, thanks to the possibility of replicating the research strategy and methodological approach in other contexts

Evidence for pseudogap and phase-coherence gap separation by Andreev reflection experiments in Au/La_{2-x}Sr_{x}CuO_4 point-contact junctions

We present new Au/La_{2-x}Sr_{x}CuO_{4} (LSCO) point-contact conductance measures as a function of voltage and temperature in samples with 0.08 <= x <= 0.2. Andreev reflection features disappear at about the bulk Tc, giving no evidence of gap for T > Tc. The fit of the normalized conductance at any T < Tc supports a (s + d)-wave symmetry of the gap, whose dominant low-T s component follows the Tc(x) curve in contrast with recent angle-resolved photoemission spectroscopy and quasiparticle tunneling data. These results prove the separation between pseudogap and phase-coherence superconducting gap in LSCO at x <= 0.2.Comment: 4 pages, 4 eps figures, 1 table (RevTeX). Labels added to Fig. 1; Fig. 3 resized; references added; short discussion about ballistic contact regime adde

Leukocytapheresis treatment for recurrence Virus C infection in liver transplant recipients

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The zero exemplar distance problem

Given two genomes with duplicate genes, \textsc{Zero Exemplar Distance} is the problem of deciding whether the two genomes can be reduced to the same genome without duplicate genes by deleting all but one copy of each gene in each genome. Blin, Fertin, Sikora, and Vialette recently proved that \textsc{Zero Exemplar Distance} for monochromosomal genomes is NP-hard even if each gene appears at most two times in each genome, thereby settling an important open question on genome rearrangement in the exemplar model. In this paper, we give a very simple alternative proof of this result. We also study the problem \textsc{Zero Exemplar Distance} for multichromosomal genomes without gene order, and prove the analogous result that it is also NP-hard even if each gene appears at most two times in each genome. For the positive direction, we show that both variants of \textsc{Zero Exemplar Distance} admit polynomial-time algorithms if each gene appears exactly once in one genome and at least once in the other genome. In addition, we present a polynomial-time algorithm for the related problem \textsc{Exemplar Longest Common Subsequence} in the special case that each mandatory symbol appears exactly once in one input sequence and at least once in the other input sequence. This answers an open question of Bonizzoni et al. We also show that \textsc{Zero Exemplar Distance} for multichromosomal genomes without gene order is fixed-parameter tractable if the parameter is the maximum number of chromosomes in each genome.Comment: Strengthened and reorganize

A meteorological–hydrological regional ensemble forecast for an early-warning system over small Apennine catchments in Central Italy

Abstract. The weather forecasts for precipitation have considerably improved in recent years thanks to the increase of computational power. This allows for the use of both a higher spatial resolution and the parameterization schemes specifically developed for representing sub-grid scale physical processes at high resolution. However, precipitation estimation is still affected by errors that can impact the response of hydrological models. To the aim of improving the hydrological forecast and the characterization of related uncertainties, a regional-scale meteorological–hydrological ensemble is presented. The uncertainties in the precipitation forecast and how they propagate in the hydrological model are also investigated. A meteorological–hydrological offline coupled ensemble is built to forecast events in a complex-orography terrain where catchments of different sizes are present. The Best Discharge-based Drainage (BDD; both deterministic and probabilistic) index, is defined with the aim of forecasting hydrological-stress conditions and related uncertainty. In this context, the meteorological–hydrological ensemble forecast is implemented and tested for a severe hydrological event which occurred over Central Italy on 15 November 2017, when a flood hit the Abruzzo region with precipitation reaching 200 mm (24 h)−1 and producing damages with a high impact on social and economic activities. The newly developed meteorological–hydrological ensemble is compared with a high-resolution deterministic forecast and with the observations (rain gauges and radar data) over the same area. The receiver operating characteristic (ROC) statistical indicator shows how skilful the ensemble precipitation forecast is with respect to both rain-gauge- and radar-retrieved precipitation. Moreover, both the deterministic and probabilistic configurations of the BDD index are compared with the alert map issued by Civil Protection Department for the event showing a very good agreement. Finally, the meteorological–hydrological ensemble allows for an estimation of both the predictability of the event a few days in advance and the uncertainty of the flood. Although the modelling framework is implemented on the basins of the Abruzzo region, it is portable and applicable to other areas

Modelling and Parameter Identification of Ex-Situ Biological Biogas Upgrading

In this paper, a model of ex-situ biological biogas upgrading process is first developed. Then, parameter sensitivity analysis is performed, in order to determine the most relevant parameters for subsequent parameter identification, based on a linear fractional transformation (LFT) reformulation of the model. Biogas composition and volumetric production have been well predicted by the calibrated model, allowing its adoption as a designing tool for start-up operation of experimental pilot-scale activity

Towards Uncovering Feature Extraction from Temporal Signals in Deep CNN: The ECG Case Study

Despite all the progress made in biomedical field, the Electrocardiogram (ECG) is still one of the most commonly used signal in medical examinations. Over the years, the problem of ECG classification has been approached in many different ways, most of which rely on the extraction of features from the signal in the form of temporal or morphological characteristics. Although feature engineering can led to adequately good results, it mostly relies on human ability and experience in selecting the correct feature set. In the last decade, a growing class of techniques based on Convolutional Neural Network (CNN) has been proposed in opposition to feature engineering. The efficiency and accuracy of CNN-based approaches is indisputable, however their ability in extracting and using temporal features from raw signal is poorly understood. The main objective of this work was to uncover the differences and the relationships between CNN feature maps and human-curated temporal features, towards a deeper understanding of neural-based approaches for ECG. In fact, the proposed study succeeded in finding a similarity between the output stage of the first layers of a deep 1D-CNN with several temporal features, demonstrating that not only that the engineered features effectively works in ECG classification tasks, but also that CNN can improve those features by elaborating them towards an higher level of abstraction