Liquid crystal plasmonic metamaterials

Metamaterials today are often realized as complex structured metasurfaces. Their functionality is based on combination of plasmonic resonances in metallic nanostructures and interferences. Novel concepts of bottom up fabrication using liquid crystal self-organization promise the realization of bulk metamaterials. Only very view such composite self organizing materials based on liquid crystals are demonstrated up to now. In detail we use rod like nematic liquid crystal molecules that are grafted onto gold nanoparticles. Structural analysis is done by X-ray scattering experiments that revealed an arrangement of the nanoparticles in chains similar to the ones found in columnar phases. To aspect are of particular importance: The sufficient size of nanoparticles to achieve efficient plasmon resonance effects and the ligands anchored on the particles that control the self-assembling properties. The combined effect of the ligands birefringence and the anisotropic arrangement of the plasmonic nanoparticles lead to a strong polarization dependence of the metamaterial’s optical properties. These results demonstrate the ability to fabricate a self ordered and tunable metamaterial by chemical engineering of the nanoparticles with liquid crystalline mesogenic ligands. In our contribution, we show experimental evidence of coupling resonances of metallic nanoparticles in an entire self-organizing material. We give details on the pathway to design such structures and to adjust their optical and mechanical properties. Theoretically insight of the electromagnetic properties is provided and the approaches to effective material design will be given

A data set from flash X-ray imaging of carboxysomes

Citation: Hantke, M. F., Hasse, D., Ekeberg, T., John, K., Svenda, M., Loh, D., . . . Maia, F. R. N. C. (2016). A data set from flash X-ray imaging of carboxysomes. Scientific Data, 3. doi:10.1038/sdata.2016.61Ultra-intense femtosecond X-ray pulses from X-ray lasers permit structural studies on single particles and biomolecules without crystals. We present a large data set on inherently heterogeneous, polyhedral carboxysome particles. Carboxysomes are cell organelles that vary in size and facilitate up to 40% of Earth's carbon fixation by cyanobacteria and certain proteobacteria. Variation in size hinders crystallization. Carboxysomes appear icosahedral in the electron microscope. A protein shell encapsulates a large number of Rubisco molecules in paracrystalline arrays inside the organelle. We used carboxysomes with a mean diameter of 115±26 nm from Halothiobacillus neapolitanus. A new aerosol sample-injector allowed us to record 70,000 low-noise diffraction patterns in 12 min. Every diffraction pattern is a unique structure measurement and high-throughput imaging allows sampling the space of structural variability. The different structures can be separated and phased directly from the diffraction data and open a way for accurate, high-throughput studies on structures and structural heterogeneity in biology and elsewhere

Outcome measures in chronic obstructive pulmonary disease (COPD): strengths and limitations

Current methods for assessing clinical outcomes in COPD mainly rely on physiological tests combined with the use of questionnaires. The present review considers commonly used outcome measures such as lung function, health status, exercise capacity and physical activity, dyspnoea, exacerbations, the multi-dimensional BODE score, and mortality. Based on current published data, we provide a concise overview of the principles, strengths and weaknesses, and discuss open questions related to each methodology. Reviewed is the current set of markers for measuring clinically relevant outcomes with particular emphasis on their limitations and opportunities that should be recognized when assessing and interpreting their use in clinical trials of COPD

Robot Learning with Task-Parameterized Generative Models

Task-parameterized models provide a representation of movement/behavior that can adapt to a set of task parameters describing the current situation encountered by the robot, such as location of objects or landmarks in its workspace. This paper gives an overview of the task-parameterized Gaussian mixture model (TP-GMM) introduced in previous publications, and introduces a number of extensions and ongoing challenges required to move the approach toward unconstrained environments. In particular, it discusses its generalization capability and the handling of movements with a high number of degrees of freedom. It then shows that the method is not restricted to movements in task space, but that it can also be exploited to handle constraints in joint space, including priority constraints

Review of the techniques used in motor‐cognitive human‐robot skill transfer

Abstract A conventional robot programming method extensively limits the reusability of skills in the developmental aspect. Engineers programme a robot in a targeted manner for the realisation of predefined skills. The low reusability of general‐purpose robot skills is mainly reflected in inability in novel and complex scenarios. Skill transfer aims to transfer human skills to general‐purpose manipulators or mobile robots to replicate human‐like behaviours. Skill transfer methods that are commonly used at present, such as learning from demonstrated (LfD) or imitation learning, endow the robot with the expert's low‐level motor and high‐level decision‐making ability, so that skills can be reproduced and generalised according to perceived context. The improvement of robot cognition usually relates to an improvement in the autonomous high‐level decision‐making ability. Based on the idea of establishing a generic or specialised robot skill library, robots are expected to autonomously reason about the needs for using skills and plan compound movements according to sensory input. In recent years, in this area, many successful studies have demonstrated their effectiveness. Herein, a detailed review is provided on the transferring techniques of skills, applications, advancements, and limitations, especially in the LfD. Future research directions are also suggested

Omalizumab versus ‘Usual Care’: Results from a Naturalistic Longitudinal Study in Routine Care

Background: It is unclear how far the superior efficacy of omalizumab, established in randomized controlled clinical trials of patients with severe allergic asthma (SAA), translates into routine practice and when compared to matched controls. Methods: New-onset omalizumab-treated (OT) patients with SAA (n = 53) were compared to a matched control group of usual-care (UC) patients (n = 53). Treatment and procedures were naturalistic. Subsequent to a baseline assessment, patients were followed up over at least 6 months with at least two follow-up assessments. Primary clinical outcomes were the number of asthma attacks, persistence of asthma symptoms and degree of control [asthma control test (ACT), Global Initiative for Asthma]. Secondary outcome criteria were quality of life (Euro-Qol 5D) and number of medications. For each outcome we compared within-group effects from baseline to 6-month follow-up as well as between-group effects. Results: OT patients showed significant improvements in number [effect size (ES) = 0.03] and frequency (ES = 0.04) of asthma attacks as well as asthma control (ES = 0.09), whereas controls revealed no significant improvements in these measures. Further improvements in the OT group were found for ‘perceived control always’ (ACT, p = 0.006), no impairment (ACT, p = 0.02), reduction of sickness days (p = 0.002) and number of medications needed (p = 0.001). Conclusions: Substantial beneficial effects of omalizumab, similar to those observed in controlled trials and after marketing studies, were confirmed, particularly with regard to the reduction of asthma attacks, persistence of symptoms, asthma control and reduction of concomitant asthma medications. This study provides a tougher test and generalizable evidence for the effectiveness of omalizumab in routine care

Automated tool for measuring nanotopography of 300 mm wafers at early stages of wafer production

Leading edge lithography processes require silicon wafers of nearly perfect flatness. In order to improve wafer manufacturing processes as well as the wafer quality, already early manufacturing processes like grinding and lapping have to be monitored. Assessment of nanotopography (NT) is an established approach to analyze surface features in a spatial wavelength range of 0.2 to 20 mm on silicon wafers end of line. This paper presents a fully automated measurement tool to measure NT on wafers with low reflectivity and wafer sizes up to 300 mm, based on the FRT MicroProf® MFE series. The system features a newly developed white-light interferometry sensor with a field of view of approximately 85 × 85 mm2. 16 single measurements are stitched to cover the entire surface of a 300 mm wafer. An NT analysis optimized stitching algorithm was developed in order to combine the individual images to a complete wafer map. The stitched map of the non-polished wafer is subsequently high pass filtered and analyzed to quantify NT. Measurement system analysis studies provided repeatability values below 1 nm at a throughput of > 20 wafer/h