125 research outputs found

    Quantum entanglement between electronic and vibrational degrees of freedom in molecules

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    We consider the quantum entanglement of the electronic and vibrational degrees of freedom in molecules with a tendency towards double welled potentials using model coupled harmonic diabatic potential-energy surfaces. The von Neumann entropy of the reduced density matrix is used to quantify the electron-vibration entanglement for the lowest two vibronic wavefunctions in such a bipartite system. Significant entanglement is found only in the region in which the ground vibronic state contains a density profile that is bimodal (i.e., contains two separate local minima). However, in this region two distinct types of entanglement are found: (1) entanglement that arises purely from the degeneracy of energy levels in the two potential wells and which is destroyed by slight asymmetry, and (2) entanglement that involves strongly interacting states in each well that is relatively insensitive to asymmetry. These two distinct regions are termed fragile degeneracy-induced entanglement and persistent entanglement, respectively. Six classic molecular systems describable by two diabatic states are considered: ammonia, benzene, semibullvalene, pyridine excited triplet states, the Creutz-Taube ion, and the radical cation of the "special pair" of chlorophylls involved in photosynthesis. These chemically diverse systems are all treated using the same general formalism and the nature of the entanglement that they embody is elucidated

    Ultrafast optical control of entanglement between two quantum dot spins

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    The interaction between two quantum bits enables entanglement, the two-particle correlations that are at the heart of quantum information science. In semiconductor quantum dots much work has focused on demonstrating single spin qubit control using optical techniques. However, optical control of entanglement of two spin qubits remains a major challenge for scaling from a single qubit to a full-fledged quantum information platform. Here, we combine advances in vertically-stacked quantum dots with ultrafast laser techniques to achieve optical control of the entangled state of two electron spins. Each electron is in a separate InAs quantum dot, and the spins interact through tunneling, where the tunneling rate determines how rapidly entangling operations can be performed. The two-qubit gate speeds achieved here are over an order of magnitude faster than in other systems. These results demonstrate the viability and advantages of optically controlled quantum dot spins for multi-qubit systems.Comment: 24 pages, 5 figure

    A multi-targeted approach to suppress tumor-promoting inflammation

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    Cancers harbor significant genetic heterogeneity and patterns of relapse following many therapies are due to evolved resistance to treatment. While efforts have been made to combine targeted therapies, significant levels of toxicity have stymied efforts to effectively treat cancer with multi-drug combinations using currently approved therapeutics. We discuss the relationship between tumor-promoting inflammation and cancer as part of a larger effort to develop a broad-spectrum therapeutic approach aimed at a wide range of targets to address this heterogeneity. Specifically, macrophage migration inhibitory factor, cyclooxygenase-2, transcription factor nuclear factor-ÎșB, tumor necrosis factor alpha, inducible nitric oxide synthase, protein kinase B, and CXC chemokines are reviewed as important antiinflammatory targets while curcumin, resveratrol, epigallocatechin gallate, genistein, lycopene, and anthocyanins are reviewed as low-cost, low toxicity means by which these targets might all be reached simultaneously. Future translational work will need to assess the resulting synergies of rationally designed antiinflammatory mixtures (employing low-toxicity constituents), and then combine this with similar approaches targeting the most important pathways across the range of cancer hallmark phenotypes

    Genome-wide microRNA screening in Nile tilapia reveals pervasive isomiRs’ transcription, sex-biased arm switching and increasing complexity of expression throughout development

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    MicroRNAs (miRNAs) are key regulators of gene expression in multicellular organisms. The elucidation of miRNA function and evolution depends on the identification and characterization of miRNA repertoire of strategic organisms, as the fast-evolving cichlid fishes. Using RNA-seq and comparative genomics we carried out an in-depth report of miRNAs in Nile tilapia (Oreochromis niloticus), an emergent model organism to investigate evo-devo mechanisms. Five hundred known miRNAs and almost one hundred putative novel vertebrate miRNAs have been identified, many of which seem to be teleost-specific, cichlid-specific or tilapia-specific. Abundant miRNA isoforms (isomiRs) were identified with modifications in both 5p and 3p miRNA transcripts. Changes in arm usage (arm switching) of nine miRNAs were detected in early development, adult stage and even between male and female samples. We found an increasing complexity of miRNA expression during ontogenetic development, revealing a remarkable synchronism between the rate of new miRNAs recruitment and morphological changes. Overall, our results enlarge vertebrate miRNA collection and reveal a notable differential ratio of miRNA arms and isoforms influenced by sex and developmental life stage, providing a better picture of the evolutionary and spatiotemporal dynamics of miRNAs

    Hydrogen and Carbon Nanotubes from Pyrolysis-Catalysis of Waste Plastics: A Review

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    More than 27 million tonnes of waste plastics are generated in Europe each year representing a considerable potential resource. There has been extensive research into the production of liquid fuels and aromatic chemicals from pyrolysis-catalysis of waste plastics. However, there is less work on the production of hydrogen from waste plastics via pyrolysis coupled with catalytic steam reforming. In this paper, the different reactor designs used for hydrogen production from waste plastics are considered and the influence of different catalysts and process parameters on the yield of hydrogen from different types of waste plastics are reviewed. Waste plastics have also been investigated as a source of hydrocarbons for the generation of carbon nanotubes via the chemical vapour deposition route. The influences on the yield and quality of carbon nanotubes derived from waste plastics are reviewed in relation to the reactor designs used for production, catalyst type used for carbon nanotube growth and the influence of operational parameters

    Understanding Communication of Sustainability Reporting: Application of Symbolic Convergence Theory (SCT)

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    The purpose of this paper is to investigate the nature of rhetoric and rhetorical strategies that are implicit in the standalone sustainability reporting of the top 24 companies of the Fortune 500 Global. We adopt Bormann’s (Q J Speech 58(4):396–407, 1972) SCT framework to study the rhetorical situation and how corporate sustainability reporting (CSR) messages can be communicated to the audience (public). The SCT concepts in the sustainability reporting’s communication are subject to different types of legitimacy strategies that are used by corporations as a validity and legitimacy claim in the reports. A content analysis has been conducted and structural coding schemes have been developed based on the literature. The schemes are applied to the SCT model which recognizes the symbolic convergent processes of fantasy among communicators in a Society. The study reveals that most of the sample companies communicate fantasy type and rhetorical vision in their corporate sustainability reporting. However, the disclosure or messages are different across locations and other taxonomies of the SCT framework. This study contributes to the current CSR literature about how symbolic or fantasy understandings can be interpreted by the users. It also discusses the persuasion styles that are adopted by the companies for communication purposes. This study is the theoretical extension of the SCT. Researchers may be interested in further investigating other online communication paths, such as human rights reports and director’s reports

    A Universal Power-law Prescription for Variability from Synthetic Images of Black Hole Accretion Flows

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    We present a framework for characterizing the spatiotemporal power spectrum of the variability expected from the horizon-scale emission structure around supermassive black holes, and we apply this framework to a library of general relativistic magnetohydrodynamic (GRMHD) simulations and associated general relativistic ray-traced images relevant for Event Horizon Telescope (EHT) observations of Sgr A*. We find that the variability power spectrum is generically a red-noise process in both the temporal and spatial dimensions, with the peak in power occurring on the longest timescales and largest spatial scales. When both the time-averaged source structure and the spatially integrated light-curve variability are removed, the residual power spectrum exhibits a universal broken power-law behavior. On small spatial frequencies, the residual power spectrum rises as the square of the spatial frequency and is proportional to the variance in the centroid of emission. Beyond some peak in variability power, the residual power spectrum falls as that of the time-averaged source structure, which is similar across simulations; this behavior can be naturally explained if the variability arises from a multiplicative random field that has a steeper high-frequency power-law index than that of the time-averaged source structure. We briefly explore the ability of power spectral variability studies to constrain physical parameters relevant for the GRMHD simulations, which can be scaled to provide predictions for black holes in a range of systems in the optically thin regime. We present specific expectations for the behavior of the M87* and Sgr A* accretion flows as observed by the EHT

    Integrating genetics and epigenetics in breast cancer: biological insights, experimental, computational methods and therapeutic potential

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