Numerical analysis of second harmonic generation in soft glass equiangular spiral photonic crystal fibers

In this paper, the accurate and numerically efficient finite element (FE)-based beam propagation method (BPM) has been employed to investigate second harmonic generation (SHG) in highly nonlinear soft glass (SF57) equiangular spiral photonic crystal fibers (ES-PCFs) for the first time. It is shown here that the SHG output power in highly nonlinear SF57 soft glass PCF exploiting the ES design is significantly higher compared with that of silica PCF with hexagonal air-hole arrangements. The effects of fabrication tolerances on the coherence length and the modal properties of ES-PCF are also illustrated. Moreover, phase matching between the fundamental and the second harmonic modes is discussed through the use of the quasi-phase matching technique. Furthermore, the ultralow bending loss in the SF57 ES-PCF design has been successfully analyzed

Rigorous Full-Vectorial Beam Propagation Analysis of Second-Harmonic Generation in Zinc Oxide Waveguides

In this paper, a rigorous full-vectorial finite-element (FE)-based beam propagation method (BPM) has been implemented to study second-harmonic generation (SHG) in planar zinc oxide (ZnO) waveguides for the first time. It is shown here that the SHG output power is significantly improved when the waveguide structure is optimized. Furthermore, phase matching between the fundamental and second-harmonic modes, through the use of the quasi-phase matching technique, is discussed

In-silico dynamic analysis of cytotoxic drug administration to solid tumours: Effect of binding affinity and vessel permeability

The delivery of blood-borne therapeutic agents to solid tumours depends on a broad range of biophysical factors. We present a novel multiscale, multiphysics, in-silico modelling framework that encompasses dynamic tumour growth, angiogenesis and drug delivery, and use this model to simulate the intravenous delivery of cytotoxic drugs. The model accounts for chemo-, hapto- and mechanotactic vessel sprouting, extracellular matrix remodelling, mechano-sensitive vascular remodelling and collapse, intra- and extravascular drug transport, and tumour regression as an effect of a cytotoxic cancer drug. The modelling framework is flexible, allowing the drug properties to be specified, which provides realistic predictions of in-vivo vascular development and structure at different tumour stages. The model also enables the effects of neoadjuvant vascular normalisation to be implicitly tested by decreasing vessel wall pore size. We use the model to test the interplay between time of treatment, drug affinity rate and the size of the vessels endothelium pores on the delivery and subsequent tumour regression and vessel remodelling. Model predictions confirm that small-molecule drug delivery is dominated by diffusive transport and further predict that the time of treatment is important for low affinity but not high affinity cytotoxic drugs, the size of the vessel wall pores plays an important role in the effect of low affinity but not high affinity drugs, that high affinity cytotoxic drugs remodel the tumour vasculature providing a large window for the normalisation of the vascular architecture, and that the combination of large pores and high affinity enhances cytotoxic drug delivery efficiency. These results have implications for treatment planning and methods to enhance drug delivery, and highlight the importance of in-silico modelling in investigating the optimisation of cancer therapy on a personalised setting

Towards a Steady State Economy in Sri Lanka

In general, it is desired that Sri Lankan economy shows growth. A growing economy brings waste production which leads environmental pollutions such as air pollution water pollution etc. At present, increasing population in Sri Lanka requires more natural resources to meet the market demand. The ultimate result is an imbalance in the biological cycles, and an irreversible change in both economic process and environment.An irreversible economic process increases entropy. Ultimately, the entropy will reach its maximum value. Then everything will become standstill since there would not exist more energy to continue the economic process. As a solution, the concept of a steady state economy is structured.Sri Lankan economy was assessed within steady state economics to evaluate the present economic situation of Sri Lanka. A statistical analysis was carried out on Gross Domestic Product (GDP), population, energy use, CO2 emission through time series analysis and regression analysis,to identify the extent to which Sri Lankan economy has deviated from a steady state economy. Regression analysis indicates a strong relationship between GDP and CO2 emission. Total population size in Sri Lanka is increased from 9.9 million in 1960 to 20.48 million in 2013. CO2 emission per capita is increased from 0.25 metric tons in 1960 to 0.65 metric tons in 2010. CO2 emission is increased from 2259 kiloton in 1960 to 12831 kiloton in 2010.Rapid growth rates, CO2 emissions, population growth rates reveal that Sri Lankan economy is far apart from the concept of steady state.Transition to a steady state economy would require the implementation of new policies to restrict the utilization of nonrenewable resources. On the other hand it is mandatory to have legal regulations encouraging renewable resource use, energy efficiency, and reuse and recycling

Seiches around the Shetland Islands

Sea level records have been obtained from a dozen tide gauges deployed around the Shetland Islands, and the high-frequency components of each record have been analysed to determine how the amplitudes and periods of seiches vary from place to place. We have found that seiches occur almost everywhere, although with different periods at different locations, and sometimes with amplitudes exceeding several decimetres. Spectral analysis shows that two or more modes of seiching are present at some sites. The study attempts to explain, with the help of a numerical model, why seiches with particular periods are observed at each location, and what forcings are responsible for them. In particular, we have revisited an earlier study of seiches on the east coast of Shetland by Cartwright and Young (Proc R Soc Lond A 338:111–128, 1974) and find no evidence to support the theory that they proposed for their generation. In addition, we have investigated how often and why the largest seiche events occur at Lerwick (with trough-to-crest wave heights of about 1 m), taking advantage of its long sea level record. Seiches (and other types of high-frequency sea level variability) are often ignored in studies of sea level changes and their coastal impacts. And yet they can be large enough to contribute significantly to the extreme sea levels that have major impacts on the coast. Therefore, our Shetland research serves as a case study of the need to have a fuller understanding of the climatology of seiches for the whole world coastline

Temporal Progression Patterns of Brain Atrophy in Corticobasal Syndrome and Progressive Supranuclear Palsy Revealed by Subtype and Stage Inference (SuStaIn)

Differentiating corticobasal degeneration presenting with corticobasal syndrome (CBD-CBS) from progressive supranuclear palsy with Richardson's syndrome (PSP-RS), particularly in early stages, is often challenging because the neurodegenerative conditions closely overlap in terms of clinical presentation and pathology. Although volumetry using brain magnetic resonance imaging (MRI) has been studied in patients with CBS and PSP-RS, studies assessing the progression of brain atrophy are limited. Therefore, we aimed to reveal the difference in the temporal progression patterns of brain atrophy between patients with CBS and those with PSP-RS purely based on cross-sectional data using Subtype and Stage Inference (SuStaIn)—a novel, unsupervised machine learning technique that integrates clustering and disease progression modeling. We applied SuStaIn to the cross-sectional regional brain volumes of 25 patients with CBS, 39 patients with typical PSP-RS, and 50 healthy controls to estimate the two disease subtypes and trajectories of CBS and PSP-RS, which have distinct atrophy patterns. The progression model and classification accuracy of CBS and PSP-RS were compared with those of previous studies to evaluate the performance of SuStaIn. SuStaIn identified distinct temporal progression patterns of brain atrophy for CBS and PSP-RS, which were largely consistent with previous evidence, with high reproducibility (99.7%) under cross-validation. We classified these diseases with high accuracy (0.875) and sensitivity (0.680 and 1.000, respectively) based on cross-sectional structural brain MRI data; the accuracy was higher than that reported in previous studies. Moreover, SuStaIn stage correctly reflected disease severity without the label of disease stage, such as disease duration. Furthermore, SuStaIn also showed the genialized performance of differentiation and reflection for CBS and PSP-RS. Thus, SuStaIn has potential for improving our understanding of disease mechanisms, accurately stratifying patients, and providing prognoses for patients with CBS and PSP-RS

Dual action antifungal small molecule modulates multidrug efflux and TOR signaling.

There is an urgent need for new strategies to treat invasive fungal infections, which are a leading cause of human mortality. Here, we establish two activities of the natural product beauvericin, which potentiates the activity of the most widely deployed class of antifungal against the leading human fungal pathogens, blocks the emergence of drug resistance, and renders antifungal-resistant pathogens responsive to treatment in mammalian infection models. Harnessing genome sequencing of beauvericin-resistant mutants, affinity purification of a biotinylated beauvericin analog, and biochemical and genetic assays reveals that beauvericin blocks multidrug efflux and inhibits the global regulator TORC1 kinase, thereby activating the protein kinase CK2 and inhibiting the molecular chaperone Hsp90. Substitutions in the multidrug transporter Pdr5 that enable beauvericin efflux impair antifungal efflux, thereby impeding resistance to the drug combination. Thus, dual targeting of multidrug efflux and TOR signaling provides a powerful, broadly effective therapeutic strategy for treating fungal infectious disease that evades resistance

Gene content evolution in the arthropods

Arthropods comprise the largest and most diverse phylum on Earth and play vital roles in nearly every ecosystem. Their diversity stems in part from variations on a conserved body plan, resulting from and recorded in adaptive changes in the genome. Dissection of the genomic record of sequence change enables broad questions regarding genome evolution to be addressed, even across hyper-diverse taxa within arthropods. Using 76 whole genome sequences representing 21 orders spanning more than 500 million years of arthropod evolution, we document changes in gene and protein domain content and provide temporal and phylogenetic context for interpreting these innovations. We identify many novel gene families that arose early in the evolution of arthropods and during the diversification of insects into modern orders. We reveal unexpected variation in patterns of DNA methylation across arthropods and examples of gene family and protein domain evolution coincident with the appearance of notable phenotypic and physiological adaptations such as flight, metamorphosis, sociality, and chemoperception. These analyses demonstrate how large-scale comparative genomics can provide broad new insights into the genotype to phenotype map and generate testable hypotheses about the evolution of animal diversity

Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of sqrt(s) = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.Comment: 24 pages plus author list (36 pages total), 23 figures, 1 table, submitted to European Physical Journal

Measurement of χ c1 and χ c2 production with s√ = 7 TeV pp collisions at ATLAS

The prompt and non-prompt production cross-sections for the χ c1 and χ c2 charmonium states are measured in pp collisions at s√ = 7 TeV with the ATLAS detector at the LHC using 4.5 fb−1 of integrated luminosity. The χ c states are reconstructed through the radiative decay χ c → J/ψγ (with J/ψ → μ + μ −) where photons are reconstructed from γ → e + e − conversions. The production rate of the χ c2 state relative to the χ c1 state is measured for prompt and non-prompt χ c as a function of J/ψ transverse momentum. The prompt χ c cross-sections are combined with existing measurements of prompt J/ψ production to derive the fraction of prompt J/ψ produced in feed-down from χ c decays. The fractions of χ c1 and χ c2 produced in b-hadron decays are also measured