Generating Multimode Entangled Microwaves with a Superconducting Parametric Cavity

In this Letter, we demonstrate the generation of multimode entangled states of propagating microwaves. The entangled states are generated by parametrically pumping a multimode superconducting cavity. By combining different pump frequencies, applied simultaneously to the device, we can produce different entanglement structures in a programable fashion. The Gaussian output states are fully characterized by measuring the full covariance matrices of the modes. The covariance matrices are absolutely calibrated using an in situ microwave calibration source, a shot noise tunnel junction. Applying a variety of entanglement measures, we demonstrate both full inseparability and genuine tripartite entanglement of the states. Our method is easily extensible to more modes.Comment: 5 pages, 1 figures, 1 tabl

Studies of the motion and decay of axion walls bounded by strings

We discuss the appearance at the QCD phase transition, and the subsequent decay, of axion walls bounded by strings in N=1 axion models. We argue on intuitive grounds that the main decay mechanism is into barely relativistic axions. We present numerical simulations of the decay process. In these simulations, the decay happens immediately, in a time scale of order the light travel time, and the average energy of the radiated axions is $\simeq 7 m_a$ for $v_a/m_a \simeq 500$. $$ is found to increase approximately linearly with $\ln(v_a/m_a)$. Extrapolation of this behaviour yields $\sim 60 m_a$ in axion models of interest. We find that the contribution to the cosmological energy density of axions from wall decay is of the same order of magnitude as that from vacuum realignment, with however large uncertainties. The velocity dispersion of axions from wall decay is found to be larger, by a factor $10^3$ or so, than that of axions from vacuum realignment and string decay. We discuss the implications of this for the formation and evolution of axion miniclusters and for the direct detection of axion dark matter on Earth. Finally we discuss the cosmology of axion models with $N>1$ in which the domain wall problem is solved by introducing a small U$_{PQ}$(1) breaking interaction. We find that in this case the walls decay into gravitational waves.Comment: 37 pages, 10 figures, a minor mistake was corrected, several references and comments were adde

Prenatal exposures and exposomics of asthma

This review examines the causal investigation of preclinical development of childhood asthma using exposomic tools. We examine the current state of knowledge regarding early-life exposure to non-biogenic indoor air pollution and the developmental modulation of the immune system. We examine how metabolomics technologies could aid not only in the biomarker identification of a particular asthma phenotype, but also the mechanisms underlying the immunopathologic process. Within such a framework, we propose alternate components of exposomic investigation of asthma in which, the exposome represents a reiterative investigative process of targeted biomarker identification, validation through computational systems biology and physical sampling of environmental medi

Which Factors Can Contribute to the Success of Environmental and Animal Protection Projects in Donation-based Crowdfunding? A Neural Network Model

The crowdfunding industry has developed rapidly in recent years, the existing research shows that crowdfunding can help in many fields such as entrepreneurship, creative products, or donations. Due to global meteorological issues, more and more people are paying attention to the environment and animal protection. However, fundraising in these areas has been the biggest problem, the emergence of donation crowdfunding (DCF) can alleviate this dilemma. Currently, in academia, there is still less research focused on crowdfunding for environmental and animal protection. This paper aims to study the factors influencing the successful financing of environmental and animal protection projects in the DCF. This paper analyses 700 DCF environmental and animal protection projects in China as samples, and creatively introduces financial transparency scoring indicators. Through binary logistic regression, financial transparency was found to be the most critical positive factor affecting project success. At the same time, donors receive NPO-initiated projects well, and the number of donors can also positively impact the results. However, the excessive description of the projects can have the opposite effect. This study also introduced a neural network model, and found that the neural network model can optimize the discriminant accuracy of the traditional binary logistic regression model

A Study on the Optimization of High School Buildings for Evacuation Safety: Classroom Layout and Ramps in Korea

This study used the Pathfinder program to evaluate evacuation safety by assuming evacuation training in high school buildings and changing classroom layout. Analysis of the final evacuation requirements for Scenario 2, which currently has a concentration of classrooms on the third floor of the building, showed that Scenario 2 reduced 29.6 seconds to 173.9 seconds compared to Scenario 1's 203.5 seconds. However, the analysis of Scenario 3, in which 10 classrooms and personnel of three grades were placed equally on the left and right sides of the building, showed that the final evacuation requirements were reduced 3.9 seconds to 170.0 seconds compared to Scenario 2, but there was no significant difference. Scenario 3, which has more the efficiency of school year operation by placing classroom layout on the same floor by grade level than Scenario 2, in which more classrooms and students were placed downstairs. In each scenario, an analysis of the final evacuation requirements showed that the evacuation exit T1 on the left side of the building was 28 seconds or more shorter than T3 on the right side of the building. Therefore, it was analyzed that proper classroom layout and ramp facilities in high school buildings ensure evacuation safet

Graph-based Representation of Syntactic Structures of Natural Languages based on Dependency Relations

Deep Learning approach using probability distribution to natural language processing achieves significant accomplishment. However, natural languages have inherent linguistic structures rather than probabilistic distribution. This paper presents a new graph-based representation of syntactic structures called syntactic knowledge graph based on dependency relations. This paper investigates the valency theory and the markedness principle of natural languages to derive an appropriate set of dependency relations for the syntactic knowledge graph. A new set of dependency relations derived from the markers is proposed. This paper also demonstrates the representation of various linguistic structures to validate the feasibility of syntactic knowledge graphs

Beam Energy and Centrality Dependence of Direct-Photon Emission from Ultrarelativistic Heavy-Ion Collisions.

The PHENIX collaboration presents first measurements of low-momentum (0.41  GeV/c) direct-photon yield dN_{γ}^{dir}/dη is a smooth function of dN_{ch}/dη and can be well described as proportional to (dN_{ch}/dη)^{α} with α≈1.25. This scaling behavior holds for a wide range of beam energies at the Relativistic Heavy Ion Collider and the Large Hadron Collider, for centrality selected samples, as well as for different A+A collision systems. At a given beam energy, the scaling also holds for high p_{T} (>5  GeV/c), but when results from different collision energies are compared, an additional sqrt[s_{NN}]-dependent multiplicative factor is needed to describe the integrated-direct-photon yield

Disposition of Federally Owned Surpluses

PDZ domains are scaffolding modules in protein-protein interactions that mediate numerous physiological functions by interacting canonically with the C-terminus or non-canonically with an internal motif of protein ligands. A conserved carboxylate-binding site in the PDZ domain facilitates binding via backbone hydrogen bonds; however, little is known about the role of these hydrogen bonds due to experimental challenges with backbone mutations. Here we address this interaction by generating semisynthetic PDZ domains containing backbone amide-to-ester mutations and evaluating the importance of individual hydrogen bonds for ligand binding. We observe substantial and differential effects upon amide-to-ester mutation in PDZ2 of postsynaptic density protein 95 and other PDZ domains, suggesting that hydrogen bonding at the carboxylate-binding site contributes to both affinity and selectivity. In particular, the hydrogen-bonding pattern is surprisingly different between the non-canonical and canonical interaction. Our data provide a detailed understanding of the role of hydrogen bonds in protein-protein interactions