Fabrication of sub-10 nm gap arrays over large areas for plasmonic sensors

We report a high-throughput method for the fabrication of metallic nanogap arrays with high-accuracy over large areas. This method, based on shadow evaporation and interference lithography, achieves sub-10 nm gap sizes with a high accuracy of 61.5 nm. Controlled fabrication is demonstrated over mm2 areas and for periods of 250 nm. Experiments complemented with numerical simulations indicate that the formation of nanogaps is a robust, self-limiting process that can be applied to wafer-scale substrates. Surface-enhanced Raman scattering (SERS) experiments illustrate the potential for plasmonic sensing with an exceptionally low standard-deviation of the SERS signal below 3% and average enhancement factors exceeding 10 to the power of

Controlling the Fano interference in a plasmonic lattice

We analyze the influence of near-field coupling on the formation of collective plasmon modes in a multilayer metallic nanowire array. It is shown that the spectral interference between super- and subradiant normal modes results in characteristic line shape modifications which are directly controlled by the spacing as well as the alignment of the stacked lattice planes. Moreover, a distinct near-field-induced reversal of particle plasmon hybridization is reported. Our numerical findings are in excellent agreement with experimental results

Electric and magnetic resonances in arrays of coupled gold nanoparticle in-tandem pairs

We present an experimental and theoretical study on the optical properties of arrays of gold nanoparticle in-tandem pairs (nanosandwiches). The well-ordered Au pairs with diameters down to 35 nm and separation distances down to 10 nm were fabricated using extreme ultraviolet (EUV) interference lithography. The strong near-field coupling of the nanoparticles leads to electric and magnetic resonances, which can be well reproduced by Finite- Difference Time- Domain (FDTD) calculations. The influence of the structural parameters, such as nanoparticle diameter and separation distance, on the hybridized modes is investigated. The energy and lifetimes of these modes are studied, providing valuable physical insight for the design of novel plasmonic structures and metamaterials. (C) 2008 Optical Society of America

The CORSMAL benchmark for the prediction of the properties of containers

13 pages, 6 tables, 7 figures, Pre-print submitted to IEEE AccessAuthors' post-print accepted for publication in IEEE Access, see https://doi.org/10.1109/ACCESS.2022.3166906 . 14 pages, 6 tables, 7 figuresThe contactless estimation of the weight of a container and the amount of its content manipulated by a person are key pre-requisites for safe human-to-robot handovers. However, opaqueness and transparencies of the container and the content, and variability of materials, shapes, and sizes, make this estimation difficult. In this paper, we present a range of methods and an open framework to benchmark acoustic and visual perception for the estimation of the capacity of a container, and the type, mass, and amount of its content. The framework includes a dataset, specific tasks and performance measures. We conduct an in-depth comparative analysis of methods that used this framework and audio-only or vision-only baselines designed from related works. Based on this analysis, we can conclude that audio-only and audio-visual classifiers are suitable for the estimation of the type and amount of the content using different types of convolutional neural networks, combined with either recurrent neural networks or a majority voting strategy, whereas computer vision methods are suitable to determine the capacity of the container using regression and geometric approaches. Classifying the content type and level using only audio achieves a weighted average F1-score up to 81% and 97%, respectively. Estimating the container capacity with vision-only approaches and estimating the filling mass with audio-visual multi-stage approaches reach up to 65% weighted average capacity and mass scores. These results show that there is still room for improvement on the design of new methods. These new methods can be ranked and compared on the individual leaderboards provided by our open framework

Paediatric radiation therapy across Europe: A European questionnaire survey supported by the SIOPe, ESTRO, PROS and several national paediatric hematology-oncology societies (NAPHOS)

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Removal of Hepatitis B virus surface HBsAg and core HBcAg antigens using microbial fuel cells producing electricity from human urine

© 2019, The Author(s). Microbial electrochemical technology is emerging as an alternative way of treating waste and converting this directly to electricity. Intensive research on these systems is ongoing but it currently lacks the evaluation of possible environmental transmission of enteric viruses originating from the waste stream. In this study, for the first time we investigated this aspect by assessing the removal efficiency of hepatitis B core and surface antigens in cascades of continuous flow microbial fuel cells. The log-reduction (LR) of surface antigen (HBsAg) reached a maximum value of 1.86 ± 0.20 (98.6% reduction), which was similar to the open circuit control and degraded regardless of the recorded current. Core antigen (HBcAg) was much more resistant to treatment and the maximal LR was equal to 0.229 ± 0.028 (41.0% reduction). The highest LR rate observed for HBsAg was 4.66 ± 0.19 h−1 and for HBcAg 0.10 ± 0.01 h−1. Regression analysis revealed correlation between hydraulic retention time, power and redox potential on inactivation efficiency, also indicating electroactive behaviour of biofilm in open circuit control through the snorkel-effect. The results indicate that microbial electrochemical technologies may be successfully applied to reduce the risk of environmental transmission of hepatitis B virus but also open up the possibility of testing other viruses for wider implementation

Cultural Aspects of Attachment Anxiety, Avoidance, and Life Satisfaction: Comparing the US and Turkey

Attachment insecurity can interfere with the experience, expression, and benefits of positive emotions, including happiness and life satisfaction (LS). However, both the pattern and effects of insecure attachment orientations on LS vary across cultures. Considering that attachment anxiety is higher in collectivist cultures and attachment avoidance is relatively high in individualistic cultures, the present chapter elaborates on the idea that anxious and avoidant attachment would have varying effects on LS in individualistic and collectivistic cultural contexts. Study 1 (N = 2456) involved a community sample of married couples in Turkey and demonstrated that attachment avoidance was a stronger predictor of LS than attachment anxiety in Turkish collectivist context. Study 2 tested the hypothesis that the roles of attachment anxiety and avoidance in predicting LS would vary between collectivistic and individualistic cultures. Mothers’ adult attachment dimensions and LS in Turkey (N = 89) and the United States (N = 91) were measured. As expected, results indicated that LS was predicted only by attachment avoidance in Turkey and by attachment anxiety in the United States. These findings are in line with the cultural fit hypothesis, suggesting that culturally incongruent attachment orientations have a stronger negative impact on individuals’ LS

Active learning and optimal climate policy

This paper develops a climate-economy model with uncertainty, irreversibility, and active learning. Whereas previous papers assume learning from one observation per period, or experiment with control variables to gain additional information, this paper considers active learning from investment in monitoring, specifically in improved observations of the global mean temperature. We find that the decision maker invests a significant amount of money in climate research, far more than the current level, in order to increase the rate of learning about climate change. This helps the decision maker make improved decisions. The level of uncertainty decreases more rapidly in the active learning model than in the passive learning model with only temperature observations. As the uncertainty about climate change is smaller, active learning reduces the optimal carbon tax. The greater the risk, the larger is the effect of learning. The method proposed here is applicable to any dynamic control problem where the quality of monitoring is a choice variable, for instance, the precision at which we observe GDP, unemployment, or the quality of education

Predictors of enhancing human physical attractiveness: Data from 93 countries

People across the world and throughout history have gone to great lengths to enhance their physical appearance. Evolutionary psychologists and ethologists have largely attempted to explain this phenomenon via mating preferences and strategies. Here, we test one of the most popular evolutionary hypotheses for beauty-enhancing behaviors, drawn from mating market and parasite stress perspectives, in a large cross-cultural sample. We also test hypotheses drawn from other influential and non-mutually exclusive theoretical frameworks, from biosocial role theory to a cultural media perspective. Survey data from 93,158 human participants across 93 countries provide evidence that behaviors such as applying makeup or using other cosmetics, hair grooming, clothing style, caring for body hygiene, and exercising or following a specific diet for the specific purpose of improving ones physical attractiveness, are universal. Indeed, 99% of participants reported spending >10 min a day performing beauty-enhancing behaviors. The results largely support evolutionary hypotheses: more time was spent enhancing beauty by women (almost 4 h a day, on average) than by men (3.6 h a day), by the youngest participants (and contrary to predictions, also the oldest), by those with a relatively more severe history of infectious diseases, and by participants currently dating compared to those in established relationships. The strongest predictor of attractiveness-enhancing behaviors was social media usage. Other predictors, in order of effect size, included adhering to traditional gender roles, residing in countries with less gender equality, considering oneself as highly attractive or, conversely, highly unattractive, TV watching time, higher socioeconomic status, right-wing political beliefs, a lower level of education, and personal individualistic attitudes. This study provides novel insight into universal beauty-enhancing behaviors by unifying evolutionary theory with several other complementary perspectives