Transparent conducting oxides for active hybrid metamaterial devices

We present here a study of the combined nonlinear response of plasmonic antenna—transparent conducting oxide hybrids for activation of metamaterial devices. Nanoantenna layers consisting of randomly positioned gold nanodisk dimers are fabricated using hole-mask lithography. The nanoantenna layers are covered with a 20 nm thin layer of transparent conducting oxide (TCO). We investigate the response of atomic layer deposited aluminum-doped zinc oxide (AZO) next to indium–tin oxide (ITO) produced using sputter coating. We show that our results are in agreement with the hypothesis of fast electron-mediated cooling, facilitated by the Ohmic interface between the gold nanodisks and the TCO substrate, which appears a universal mechanism for providing a new hybrid functionality to active metamaterial device

Spatial Modulation Microscopy for Real-Time Imaging of Plasmonic Nanoparticles and Cells

Spatial modulation microscopy is a technique originally developed for quantitative spectroscopy of individual nano-objects. Here, a parallel implementation of the spatial modulation microscopy technique is demonstrated based on a line detector capable of demodulation at kHz frequencies. The capabilities of the imaging system are shown using an array of plasmonic nanoantennas and dendritic cells incubated with gold nanoparticles.Comment: 3 pages, 4 figure

Immune factors preceding diagnosis of glioma: a Prostate Lung Colorectal Ovarian Cancer Screening Trial nested case-control study.

BackgroundEpidemiological studies of adult glioma have identified genetic and environmental risk factors, but much remains unclear. The aim of the current study was to evaluate anthropometric, disease-related, and prediagnostic immune-related factors for relationship with glioma risk.MethodsWe conducted a nested case-control study among the intervention arm of the Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) Screening Trial. One hundred and twenty-four glioma cases were identified and each matched to four controls. Baseline characteristics were collected at enrollment and were evaluated for association with glioma status. Serum specimens were collected at yearly intervals and were analyzed for immune-related factors including TGF-β1, TNF-α, total IgE, and allergen-specific IgE. Immune factors were evaluated at baseline in a multivariate conditional logistic regression model, along with one additional model that incorporated the latest available measurement.ResultsA family history of glioma among first-degree relatives was associated with increased glioma risk (OR = 4.41, P = .002). In multivariate modeling of immune factors at baseline, increased respiratory allergen-specific IgE was inversely associated with glioma risk (OR for allergen-specific IgE > 0.35 PAU/L: 0.59, P = .03). A logistic regression model that incorporated the latest available measurements found a similar association for allergen-specific IgE (P = .005) and showed that elevated TGF-β1 was associated with increased glioma risk (P-value for trend <.0001).ConclusionThe results from this prospective prediagnostic study suggest that several immune-related factors are associated with glioma risk. The association observed for TGF-β1 when sampling closer to the time of diagnosis may reflect the nascent brain tumor's feedback on immune function

Static and Dynamic Vector Semantics for Lambda Calculus Models of Natural Language

To appear in Journal of Language Modelling. Short versions presented in DSALT 2016, SaLMoM 2016, LACL 2016. A version presented in AC 2017To appear in Journal of Language Modelling. Short versions presented in DSALT 2016, SaLMoM 2016, LACL 2016. A version presented in AC 2017To appear in Journal of Language Modelling. Short versions presented in DSALT 2016, SaLMoM 2016, LACL 2016. A version presented in AC 2017Vector models of language are based on the contextual aspects of language, the distributions of words and how they co-occur in text. Truth conditional models focus on the logical aspects of language, compositional properties of words and how they compose to form sentences. In the truth conditional approach, the denotation of a sentence determines its truth conditions, which can be taken to be a truth value, a set of possible worlds, a context change potential, or similar. In the vector models, the degree of co-occurrence of words in context determines how similar the meanings of words are. In this paper, we put these two models together and develop a vector semantics for language based on the simply typed lambda calculus models of natural language. We provide two types of vector semantics: a static one that uses techniques familiar from the truth conditional tradition and a dynamic one based on a form of dynamic interpretation inspired by Heim's context change potentials. We show how the dynamic model can be applied to entailment between a corpus and a sentence and we provide examples

Concentrating or scattering management in agricultural landscapes:Examining the effectiveness and efficiency of conservation measures

A key issue in conservation is where and how much management should be implemented to obtain optimal biodiversity benefits. Cost-effective conservation requires knowledge on whether biodiversity benefits are higher when management is concentrated in a few core areas or scattered across the landscape, and how these effects vary between species. To address these questions, we examined species-specific behavioural responses of over-wintering farmland birds to enhanced seed availability. In a two-year experiment we first examined the relationship between landscape-scale seed availability and farmland bird density. Then we investigated the relative resource delivery (difference in bird densities between landscapes with and without additional management) and the efficiency (number of individuals supported per unit management) of conservation actions, both at the landscape-scale (ca 100 ha) and at the scale of the conservation measures (3.6 ha). The conservation actions were targeted towards ten seed-eating farmland bird species, but we also considered the responses of seven non-targeted and more generalist seed-eating species, seven species that are less dependent on seeds and three species of birds of prey. We found a positive relationship between bird density and landscape-scale seed availability for eleven species and, for four of these species, the slope of this relationship changed before and after a threshold seed density. For two seed-eating specialists, the number of individuals using conservation patches declined with landscape-scale seed availability. In addition, we found that the relative resource delivery declined with landscape scale seed availability for three seed-eating specialists and was independent of landscape-scale seed availability in four other species. Our results suggest that farmland specialists may benefit most from winter food additions if conservation actions result in high landscape-scale seed availability. This may be achieved by concentrating conservation measures or by establishing measures in areas with high baseline seed availability. By contrast, species that can utilize a wider range of habitats and resources may benefit more from scattering measures across larger areas. Therefore, optimal management for the full range of farmland birds in wintertime may require a combination of core areas with concentrated management and more widely distributed smaller patches of conservation measures.</p

Giant optical birefringence of semiconductor nanowire metamaterials

Semiconductor nanowires exhibit large polarization anisotropy for the absorption and emission of light, making them ideal building blocks for novel photonic metamaterials. Here, we demonstrate that a high density of aligned nanowires exhibits giant optical birefringence, a collective phenomenon observable uniquely for collections of wires. The nanowire material was grown on gallium phosphide (GaP) (111) in the form of vertically standing GaP nanowires. We obtain the largest optical birefringence to date, with a difference between the in-plane and out-of-plane refractive indices of 0.80 and a relative birefringence of 43%. These values exceed by a factor of 75 the natural birefringence of quartz and a by more than a factor of two the highest values reported so far in other artificial materials. By exploiting the specific crystallographic growth directions of the nanowires on the substrate, we further demonstrate full control over the orientation of the optical birefringence effect in the metamaterial.Comment: 10 pages, 4 figure

A Paraconsistent Higher Order Logic

Classical logic predicts that everything (thus nothing useful at all) follows from inconsistency. A paraconsistent logic is a logic where an inconsistency does not lead to such an explosion, and since in practice consistency is difficult to achieve there are many potential applications of paraconsistent logics in knowledge-based systems, logical semantics of natural language, etc. Higher order logics have the advantages of being expressive and with several automated theorem provers available. Also the type system can be helpful. We present a concise description of a paraconsistent higher order logic with countable infinite indeterminacy, where each basic formula can get its own indeterminate truth value (or as we prefer: truth code). The meaning of the logical operators is new and rather different from traditional many-valued logics as well as from logics based on bilattices. The adequacy of the logic is examined by a case study in the domain of medicine. Thus we try to build a bridge between the HOL and MVL communities. A sequent calculus is proposed based on recent work by Muskens.Comment: Originally in the proceedings of PCL 2002, editors Hendrik Decker, Joergen Villadsen, Toshiharu Waragai (http://floc02.diku.dk/PCL/). Correcte

Utilization of LSTM neural network for water production forecasting of a stepped solar still with a corrugated absorber plate

This study introduces a long short-term memory (LSTM) neural network model to forecast the freshwater yield of a stepped solar still and a conventional one. The stepped solar still was equiped by a copper corrugated absorber plate. The thermal performance of the stepped solar still is compared with that of conventional single slope solar still. The heat transfer coefficients of convection, evaporation, and radiation process have been evaluated. The exergy and energy efficiencies of both solar stills have been also evaluated. The yield of the stepped solar still is enhanced by about 128 % compared with that of conventional solar still. Then, the proposed LSTM neural network method is utilized to forecast the hourly yield of the investigated solar stills. Field experimental data was used to train and test the developed model. The freshwater yield was used in a time series form to train the proposed model. The forecasting accuracy of the proposed model was compared with those obtained by conventional autoregressive integrated moving average (ARIMA) and was evaluated using different statistical assessment measures. The coefficient of determination of the forecasted results has a high value of 0.97 and 0.99 for the conventional and the stepped solar still, respectively