Aalto University

About: Aalto University is a education organization based out in Espoo, Finland. It is known for research contribution in the topics: Computer science & Context (language use). The organization has 9969 authors who have published 32648 publications receiving 829626 citations. The organization is also known as: TKK & Aalto-korkeakoulu.

Review of Recent Progress of Plasmonic Materials and Nano-Structures for Surface-Enhanced Raman Scattering.

Abstract: Surface-enhanced Raman scattering (SERS) has demonstrated single-molecule sensitivity and is becoming intensively investigated due to its significant potential in chemical and biomedical applications. SERS sensing is highly dependent on the substrate, where excitation of the localized surface plasmons (LSPs) enhances the Raman scattering signals of proximate analyte molecules. This paper reviews research progress of SERS substrates based on both plasmonic materials and nano-photonic structures. We first discuss basic plasmonic materials, such as metallic nanoparticles and nano-rods prepared by conventional bottom-up chemical synthesis processes. Then, we review rationally-designed plasmonic nano-structures created by top-down approaches or fine-controlled synthesis with high-density hot-spots to provide large SERS enhancement factors (EFs). Finally, we discuss the research progress of hybrid SERS substrates through the integration of plasmonic nano-structures with other nano-photonic devices, such as photonic crystals, bio-enabled nanomaterials, guided-wave systems, micro-fluidics and graphene.

Fuel retention studies with the ITER-Like Wall in JET

Abstract: JET underwent a transformation from a full carbon-dominated tokamak to a fully metallic device with beryllium in the main chamber and a tungsten divertor. This material combination is foreseen for the activated phase of ITER. The ITER-Like Wall (ILW) experiment at JET shall demonstrate the plasma compatibility with metallic walls and the reduction in fuel retention. We report on a set of experiments (Ip = 2.0 MA, Bt = 2.0–2.4 T, δ = 0.2–0.4) in different confinement and plasma conditions with global gas balance analysis demonstrating a strong reduction in the long-term retention rate by more than a factor of 10 with respect to carbon-wall reference discharges. All experiments are executed in a series of identical plasma discharges in order to achieve maximum plasma duration until the analysis limit of the active gas handling system is reached. The composition analysis shows high purity of the recovered gas, typically 99% D. For typical L-mode discharges (Paux = 0.5 MW), type III (Paux = 5.0 MW) and type-I ELMy H-mode plasmas (Paux = 12.0 MW) a drop of the deuterium retention rate normalized to the operational time in divertor configuration is measured from 1.27 × 1021, 1.37 × 1021 and 1.97 × 1021 D s−1 down to 4.8 × 1019, 7.2 × 1019 and 16 × 1019 D s−1, respectively. The dynamic retention increases in the limiter phase in comparison with carbon-fibre composite, but also the outgassing after the discharge has risen in the same manner and overcompensates this transient retention. Overall an upper limit of the long-term retention rate of 1.5 × 1020 D s−1 is obtained with the ILW. The observed reduction by one order of magnitude confirms the expected predictions concerning the plasma-facing material change in ITER and is in line with identification of fuel co-deposition with Be as the main mechanism for the residual long-term retention. The reduction widens the operational space without active cleaning in the DT phase in comparison with a full carbon device.

How Much Does Expertise Reduce Behavioral Biases? The Case of Anchoring Effects in Stock Return Estimates

Abstract: We use data from surveys involving 300 Scandinavian financial market professionals and 213 university students to conduct three controlled experiments in which we manipulate the background information given to subjects. We find a very large anchoring effect in the students' long-term stock return expectations, that is, their estimates are influenced by an initial starting value. Professionals show a much smaller anchoring effect, but it nevertheless remains statistically and economically significant, even when we restrict the sample to more experienced professionals. We also find that the professionals are not conscious of the impact of historical returns on their expectations.

Design of emerging digital services: a taxonomy

Abstract: There has been a gigantic shift from a product based economy to one based on services, specifically digital services. From every indication it is likely to be more than a passing fad and the changes these emerging digital services represent will continue to transform commerce and have yet to reach market saturation. Digital services are being designed for and offered to users, yet very little is known about the design process that goes behind these developments. Is there a science behind designing digital services? By examining 12 leading digital services, we have developed a design taxonomy to be able to classify and contrast digital services. What emerged in the taxonomy were two broad dimensions; a set of fundamental design objectives and a set of fundamental service provider objectives. This paper concludes with an application of the proposed taxonomy to three leading digital services. We hope that the proposed taxonomy will be useful in understanding the science behind the design of digital services.

Data Envelopment Analysis as Nonparametric Least Squares Regression

Abstract: Data Envelopment Analysis (DEA), a nonparametric mathematical programming approach to productive efficiency analysis, envelops all observed data. In this paper we show that DEA can be interpreted as nonparametric least squares regression subject to shape constraints on frontier and sign constraints on residuals, and that classic parametric programming model is a constrained special case of DEA. Applying these insights, we present a nonparametric variant of the corrected ordinary least squares (COLS) method. We show that this new method, which we term corrected concave nonparametric least squares (C2NLS) is consistent and asymptotically unbiased. The linkages established in this paper contribute to further integration of the econometric and linear programming approaches.