Entanglement Distribution in Quantum Metropolitan Optical Networks

The ability to generate entangled photon-pairs over a broad wavelength range opens the door to the simultaneous distribution of entanglement to multiple users of a network using a single source and wavelength-division multiplexing technologies. Here we show the design of a metropolitan optical network made of tree-type access networks where entangled photon-pairs are distributed to any pair of users, independently of their location. The resulting network improves the reach, number of users and capabilities of existing proposals. Moreover, it is made up of typical commercial components and uses the existing infrastructure, which allows for moderate deployment costs. Finally, we develop a channel plan and a network design that allow direct optical communications, quantum and classical, between any pair of users. Therefore, multiple quantum information technologies can make use of this network.

Quantum metropolitan optical network based on wavelength division multiplexing

Quantum Key Distribution (QKD) is maturing quickly. However, the current approaches to its application in optical networks make it an expensive technology. QKD networks deployed to date are designed as a collection of point-to-point, dedicated QKD links where non-neighboring nodes communicate using the trusted repeater paradigm. We propose a novel optical network model in which QKD systems share the communication infrastructure by wavelength multiplexing their quantum and classical signals. The routing is done using optical components within a metropolitan area which allows for a dynamically any-to-any communication scheme. Moreover, it resembles a commercial telecom network, takes advantage of existing infrastructure and utilizes commercial components, allowing for an easy, cost-effective and reliable deployment.

Entanglement distribution in optical networks

The ability to generate entangled photon pairs over a broad wavelength range opens the door to the simultaneous distribution of entanglement to multiple users in a network by using centralized sources and flexible wavelength-division multiplexing schemes. Here, we show the design of a metropolitan optical network consisting of tree-type access networks, whereby entangled photon pairs are distributed to any pair of users, independent of their location. The network is constructed employing commercial off-the-shelf components and uses the existing infrastructure, which allows for moderate deployment costs. We further develop a channel plan and a network-architecture design to provide a direct optical path between any pair of users; thus, allowing classical and one-way quantum communication, as well as entanglement distribution. This allows the simultaneous operation of multiple quantum information technologies. Finally, we present a more flexible backbone architecture that pushes away the load limitations of the original network design by extending its reach, number of users and capabilities.

Multi-dimensional classification of GABAergic interneurons with Bayesian network-modeled label uncertainty

Abstract Interneuron classification is an important and long-debated topic in neuroscience. A recent study provided a data set of digitally reconstructed interneurons classified by 42 leading neuroscientists according to a pragmatic classification scheme composed of five categorical variables, namely, of the interneuron type and four features of axonal morphology. From this data set we now learned a model which can classify interneurons, on the basis of their axonal morphometric parameters, into these five descriptive variables simultaneously. Because of differences in opinion among the neuroscientists, especially regarding neuronal type, for many interneurons we lacked a unique, agreed-upon classification, which we could use to guide model learning. Instead, we guided model learning with a probability distribution over the neuronal type and the axonal features, obtained, for each interneuron, from the neuroscientists’ classification choices. We conveniently encoded such probability distributions with Bayesian networks, calling them label Bayesian networks (LBNs), and developed a method to predict them. This method predicts an LBN by forming a probabilistic consensus among the LBNs of the interneurons most similar to the one being classified. We used 18 axonal morphometric parameters as predictor variables, 13 of which we introduce in this paper as quantitative counterparts to the categorical axonal features. We were able to accurately predict interneuronal LBNs. Furthermore, when extracting crisp (i.e., non-probabilistic) predictions from the predicted LBNs, our method outperformed related work on interneuron classification. Our results indicate that our method is adequate for multi-dimensional classification of interneurons with probabilistic labels. Moreover, the introduced morphometric parameters are good predictors of interneuron type and the four features of axonal morphology and thus may serve as objective counterparts to the subjective, categorical axonal features.

Multi-dimensional classification of GABAergic interneurons with Bayesian network-modeled label uncertainty

Interneuron classification is an important and long-debated topic in neuroscience. A recent study provided a data set of digitally reconstructed interneurons classified by 42 leading neuroscientists according to a pragmatic classification scheme composed of five categorical variables, namely, of the interneuron type and four features of axonal morphology. From this data set we now learned a model which can classify interneurons, on the basis of their axonal morphometric parameters, into these five descriptive variables simultaneously. Because of differences in opinion among the neuroscientists, especially regarding neuronal type, for many interneurons we lacked a unique, agreed-upon classification, which we could use to guide model learning. Instead, we guided model learning with a probability distribution over the neuronal type and the axonal features, obtained, for each interneuron, from the neuroscientists’ classification choices. We conveniently encoded such probability distributions with Bayesian networks, calling them label Bayesian networks (LBNs), and developed a method to predict them. This method predicts an LBN by forming a probabilistic consensus among the LBNs of the interneurons most similar to the one being classified. We used 18 axonal morphometric parameters as predictor variables, 13 of which we introduce in this paper as quantitative counterparts to the categorical axonal features. We were able to accurately predict interneuronal LBNs. Furthermore, when extracting crisp (i.e., non-probabilistic) predictions from the predicted LBNs, our method outperformed related work on interneuron classification. Our results indicate that our method is adequate for multi-dimensional classification of interneurons with probabilistic labels. Moreover, the introduced morphometric parameters are good predictors of interneuron type and the four features of axonal morphology and thus may serve as objective counterparts to the subjective, categorical axonal features.

Propuesta de un marco conceptual para el análisis comparativo de las redes de distribución de dos supermercados online = Proposal of a conceptual framework for the comparative analysis of the distribution networks of two online supermarkets

In this article the network configuration for fulfillment and distribution of online orders of two British retailers is analyzed and compared. For this purpose, it is proposed a conceptual framework that consists of the key following aspects: network configuration, transportation management and location of demand. As a result is not obvious to determine the ideal centralization degree in each case. Finally, it is suggested the future development of an analytic tool that helps to choose the most appropriate model.

High-Affinity Binding Of The AP-1 Adaptor Complex to Trans-Golgi Network Membranes Devoid Of Mannose 6-Phosphate Receptors

The GTP-binding protein ADP-ribosylation factor (ARF) initiates clathrin-coat assembly at the trans-Goli network (TGN) by generating high-affinity membrane-binding sites for the AP-1 adaptor complex. Both transmembrane proteins, which are sorted into the assembling coated bud, and novel docking proteins have been suggested to be partners with GTP-bound ARF in generating the AP-1-docking sites. The best characterized, and probably the major transmembrane molecules sorted into the clathrin-coated vesicles that form on the TGN, are the mannose 6-phosphate receptors (MPRs). Here, we have examined the role of the MPRs in the AP-1 recruitment process by comparing fibroblasts derived from embryos of either normal or MPR-negative animals. Despite major alterations to the lysosome compartment in the MPR-deficient cells, the steady-state distribution of AP-1 at the TGN is comparable to that of normal cells. Golgi-enriched membranes prepared from the receptor-negative cells also display an apparently normal capacity to recruit AP-1 in vitro in the presence of ARF and either GTP or GTPγS. The AP-1 adaptor is recruited specifically onto the TGN and not onto the numerous abnormal membrane elements that accumulate within the MPR-negative fibroblasts. AP-1 bound to TGN membranes from either normal or MPR-negative fibroblasts is fully resistant to chemical extraction with 1 M Tris-HCl, pH 7, indicating that the adaptor binds to both membrane types with high affinity. The only difference we do note between the Golgi prepared from the MPR-deficient cells and the normal cells is that AP-1 recruited onto the receptor-lacking membranes in the presence of ARF1·GTP is consistently more resistant to extraction with Tris. Because sensitivity to Tris extraction correlates well with nucleotide hydrolysis, this finding might suggest a possible link between MPR sorting and ARF GAP regulation. We conclude that the MPRs are not essential determinants in the initial steps of AP-1 binding to the TGN but, instead, they may play a regulatory role in clathrin-coated vesicle formation by affecting ARF·GTP hydrolysis.

Apiconuclear Organization of Microtubules Does Not Specify Protein Delivery from the Trans-Golgi Network to Different Membrane Domains in Polarized Epithelial Cells

In nonpolarized epithelial cells, microtubules originate from a broad perinuclear region coincident with the distribution of the Golgi complex and extend outward to the cell periphery (perinuclear [PN] organization). During development of epithelial cell polarity, microtubules reorganize to form long cortical filaments parallel to the lateral membrane, a meshwork of randomly oriented short filaments beneath the apical membrane, and short filaments at the base of the cell; the Golgi becomes localized above the nucleus in the subapical membrane cytoplasm (apiconuclear [AN] organization). The AN-type organization of microtubules is thought to be specialized in polarized epithelial cells to facilitate vesicle trafficking between the trans-Golgi Network (TGN) and the plasma membrane. We describe two clones of MDCK cells, which have different microtubule distributions: clone II/G cells, which gradually reorganize a PN-type distribution of microtubules and the Golgi complex to an AN-type during development of polarity, and clone II/J cells which maintain a PN-type organization. Both cell clones, however, exhibit identical steady-state polarity of apical and basolateral proteins. During development of cell surface polarity, both clones rapidly establish direct targeting pathways for newly synthesized gp80 and gp135/170, and E-cadherin between the TGN and apical and basolateral membrane, respectively; this occurs before development of the AN-type microtubule/Golgi organization in clone II/G cells. Exposure of both clone II/G and II/J cells to low temperature and nocodazole disrupts >99% of microtubules, resulting in: 1) 25–50% decrease in delivery of newly synthesized gp135/170 and E-cadherin to the apical and basolateral membrane, respectively, in both clone II/G and II/J cells, but with little or no missorting to the opposite membrane domain during all stages of polarity development; 2) ∼40% decrease in delivery of newly synthesized gp80 to the apical membrane with significant missorting to the basolateral membrane in newly established cultures of clone II/G and II/J cells; and 3) variable and nonspecific delivery of newly synthesized gp80 to both membrane domains in fully polarized cultures. These results define several classes of proteins that differ in their dependence on intact microtubules for efficient and specific targeting between the Golgi and plasma membrane domains.

Vesicle-associated Membrane Protein 4 is Implicated in Trans-Golgi Network Vesicle Trafficking

The trans-Golgi network (TGN) plays a pivotal role in directing proteins in the secretory pathway to the appropriate cellular destination. VAMP4, a recently discovered member of the vesicle-associated membrane protein (VAMP) family of trafficking proteins, has been suggested to play a role in mediating TGN trafficking. To better understand the function of VAMP4, we examined its precise subcellular distribution. Indirect immunofluorescence and electron microscopy revealed that the majority of VAMP4 localized to tubular and vesicular membranes of the TGN, which were in part coated with clathrin. In these compartments, VAMP4 was found to colocalize with the putative TGN-trafficking protein syntaxin 6. Additional labeling was also present on clathrin-coated and noncoated vesicles, on endosomes and the medial and trans side of the Golgi complex, as well as on immature secretory granules in PC12 cells. Immunoprecipitation of VAMP4 from rat brain detergent extracts revealed that VAMP4 exists in a complex containing syntaxin 6. Converging lines of evidence implicate a role for VAMP4 in TGN-to-endosome transport.

Fault location in power distribution networks with distributed generation.

This research presents the development and implementation of fault location algorithms in power distribution networks with distributed generation units installed along their feeders. The proposed algorithms are capable of locating the fault based on voltage and current signals recorded by intelligent electronic devices installed at the end of the feeder sections, information to compute the loads connected to these feeders and their electric characteristics, and the operating status of the network. In addition, this work presents the study of analytical models of distributed generation and load technologies that could contribute to the performance of the proposed fault location algorithms. The validation of the algorithms was based on computer simulations using network models implemented in ATP, whereas the algorithms were implemented in MATLAB.

Breaking down complex saproxylic communities: understanding sub-networks structure and implications to network robustness

Saproxylic insect communities inhabiting tree hollow microhabitats correspond with large food webs which simultaneously are constituted by multiple types of plant-animal and animal-animal interactions, according to the use of trophic resources (wood- and insect-dependent sub-networks), or to trophic habits or interaction types (xylophagous, saprophagous, xylomycetophagous, predators and commensals). We quantitatively assessed which properties of specialised networks were present in a complex networks involving different interacting types such as saproxylic community, and how they can be organised in trophic food webs. The architecture, interacting patterns and food web composition were evaluated along sub-networks, analysing their implications to network robustness from random and directed extinction simulations. A structure of large and cohesive modules with weakly connected nodes was observed throughout saproxylic sub-networks, composing the main food webs constituting this community. Insect-dependent sub-networks were more modular than wood-dependent sub-networks. Wood-dependent sub-networks presented higher species degree, connectance, links, linkage density, interaction strength, and were less specialised and more aggregated than insect-dependent sub-networks. These attributes defined high network robustness in wood-dependent sub-networks. Finally, our results emphasise the relevance of modularity, differences among interacting types and interrelations among them in modelling the structure of saproxylic communities and in determining their stability.

Amphibian Hotspots and Conservation Priorities in Eastern Cuba Identified by Species Distribution Modeling

The high rate of amphibian endemism and the severe habitat modification in the Caribbean islands make them an ideal place to test if the current protected areas network might protect this group. In this study, we model distribution and map species richness of the 40 amphibian species from eastern Cuba with the objectives of identify hotspots, detect gaps in species representation in protected areas, and select additional areas to fill these gaps. We used two modeling methods, Maxent and Habitat Suitability Models, to reach a consensus distribution map for each species, then calculate species richness by combining specific models and finally performed gap analyses for species and hotspots. Our results showed that the models were robust enough to predict species distributions and that most of the amphibian hotspots were represented in reserves, but 50 percent of the species were incompletely covered and Eleutherodactylus rivularis was totally uncovered by the protected areas. We identified 1441 additional km2 (9.9% of the study area) that could be added to the current protected areas, allowing the representation of every species and all hotspots. Our results are relevant for the conservation planning in other Caribbean islands, since studies like this could contribute to fill the gaps in the existing protected areas and to design a future network. Both cases would benefit from modeling amphibian species distribution using available data, even if they are incomplete, rather than relying only in the protection of known or suspected hotspots.

Analyse de la distribution d'Escherichia coli, utilisée comme un marqueur microbiologique, dans un réseau de production porcin

La présence d’Escherichia coli pathogènes en élevages porcins entraine des retards de croissance et la mortalité. La transmission des E. coli pathogènes entre les élevages et l'abattoir d’un même réseau de production n'est pas bien décrite. La détection des gènes de virulence des E. coli pathogènes pourrait permettre d’identifier un marqueur de contamination dans le réseau. L’objectif de cette étude a été d’identifier un marqueur de contamination E. coli dans un réseau de production porcine défini afin de décrire certains modes de transmission des E. coli pathogènes. Pour ce faire, une région géographique comprenant 10 fermes d’engraissement, un abattoir et un réseau de transport a été sélectionnée. Trois lots de production consécutifs par ferme ont été suivis pendant 12 mois. Des échantillons environnementaux ont été prélevés à l’intérieur et à l’extérieur des fermes (3 visites d’élevage), dans la cour de l’abattoir (2 visites lors de sorties de lot) et sur le camion de transport. La détection des gènes de virulence (eltB, estA, estB, faeG, stxA, stx2A, eae, cnf, papC, iucD, tsh, fedA) dans les échantillons a été réalisée par PCR multiplexe conventionnelle. La distribution temporelle et spatiale des gènes de virulence a permis d’identifier le marqueur de contamination ETEC/F4 défini par la détection d’au moins un gène d’entérotoxine ETEC (estB, estA et eltB) en combinaison avec le gène de l’adhésine fimbriaire (faeG). La distribution des échantillons positifs ETEC/F4 qualifie la cour de l’abattoir comme un réservoir de contamination fréquenté par les transporteurs, vecteurs de contamination entre les élevages. Ceci suggère le lien microbiologique entre l’élevage, les transporteurs et l’abattoir jouant chacun un rôle dans la dissémination des microorganismes pathogènes et potentiellement zoonotiques en production porcine.

Trends in diabetes incidence from 1992 to 2015 and projections for 2024: A Portuguese General Practitioner’s Network study

Background: Diabetes is known as a major cause of morbidity and mortality worldwide. Portugal is known as the European country with the highest prevalence of this disease. While diabetes prevalence data is updated annually in Portugal, the General Practitioner’s (GP) Sentinel Network represents the only data source on diabetes incidence. This study describes the trends in Diabetes incidence, between 1992 and 2015, and estimate projections for the future incidence rates in Portugal until 2024. Methods: An ecological time-series study was conducted using data from GP Sentinel Network between 1992 and 2015. Family doctors reported all new cases of Diabetes in their patients’ lists. Annual trends were estimated through Poisson regression models as well as the future incidence rates (until 2024), sex and age group stratified. Incidence rate projections were adjusted to the distribution of the resident Portuguese population given Statistics Portugal projections. Results: The average increase in Diabetes incidence rate was in total 4.29% (CI95% 3.80–4.80) per year under study. Until 1998–2000, the annual incidence rate was higher in women, and from 1998–2000 to 2013–2015 turn out to be higher in men. The incidence rate projected for 2022–2024 was 972.77/105 inhabitants in total, and 846.74/105 and 1114.42/105, respectively, in women and men. Conclusions: This is the first study in Portugal to estimate diabetes incidence rate projections. The disturbing reported projections seem realistic if things continue as in the past. Actually, effective public health policies will need to be undertaken to minimize this alarming future scenario.

Near Real-Time Detection Of Pipe Bursts in Water Distribution Systems

The research work presented in the thesis describes a new methodology for the automated near real-time detection of pipe bursts in Water Distribution Systems (WDSs). The methodology analyses the pressure/flow data gathered by means of SCADA systems in order to extract useful informations that go beyond the simple and usual monitoring type activities and/or regulatory reporting , enabling the water company to proactively manage the WDSs sections. The work has an interdisciplinary nature covering AI techniques and WDSs management processes such as data collection, manipulation and analysis for event detection. Indeed, the methodology makes use of (i) Artificial Neural Network (ANN) for the short-term forecasting of future pressure/flow signal values and (ii) Rule-based Model for bursts detection at sensor and district level. The results of applying the new methodology to a District Metered Area in Emilia- Romagna’s region, Italy have also been reported in the thesis. The results gathered illustrate how the methodology is capable to detect the aforementioned failure events in fast and reliable manner. The methodology guarantees the water companies to save water, energy, money and therefore enhance them to achieve higher levels of operational efficiency, a compliance with the current regulations and, last but not least, an improvement of customer service.