Macromolecular engineering via RAFT chemistry : from sequential to modular design

Sequential Design Molecular Weight Range Functional Monomers: Possibilities, Limits, and Challenges Block Copolymers: Combinations, Block Lengths, and Purities Modular Design End-Group Chemistry Ligation Protocols Conclusions

Ambiguity Acceptance Testing : A Comparison of the Ratio Test and Difference Test

Integer ambiguity resolution is an indispensable procedure for all high precision GNSS applications. The correctness of the estimated integer ambiguities is the key to achieving highly reliable positioning, but the solution cannot be validated with classical hypothesis testing methods. The integer aperture estimation theory unifies all existing ambiguity validation tests and provides a new prospective to review existing methods, which enables us to have a better understanding on the ambiguity validation problem. This contribution analyses two simple but efficient ambiguity validation test methods, ratio test and difference test, from three aspects: acceptance region, probability basis and numerical results. The major contribution of this paper can be summarized as: (1) The ratio test acceptance region is overlap of ellipsoids while the difference test acceptance region is overlap of half-spaces. (2) The probability basis of these two popular tests is firstly analyzed. The difference test is an approximation to optimal integer aperture, while the ratio test follows an exponential relationship in probability. (3) The limitations of the two tests are firstly identified. The two tests may under-evaluate the failure risk if the model is not strong enough or the float ambiguities fall in particular region. (4) Extensive numerical results are used to compare the performance of these two tests. The simulation results show the ratio test outperforms the difference test in some models while difference test performs better in other models. Particularly in the medium baseline kinematic model, the difference tests outperforms the ratio test, the superiority is independent on frequency number, observation noise, satellite geometry, while it depends on success rate and failure rate tolerance. Smaller failure rate leads to larger performance discrepancy.

Sequential versus simultaneous viewing of an environment : effects of focal attention to individual object locations on visual spatial learning

We investigated memories of room-sized spatial layouts learned by sequentially or simultaneously viewing objects from a stationary position. In three experiments, sequential viewing (one or two objects at a time) yielded subsequent memory performance that was equivalent or superior to simultaneous viewing of all objects, even though sequential viewing lacked direct access to the entire layout. This finding was replicated by replacing sequential viewing with directed viewing in which all objects were presented simultaneously and participants’ attention was externally focused on each object sequentially, indicating that the advantage of sequential viewing over simultaneous viewing may have originated from focal attention to individual object locations. These results suggest that memory representation of object-to-object relations can be constructed efficiently by encoding each object location separately, when those locations are defined within a single spatial reference system. These findings highlight the importance of considering object presentation procedures when studying spatial learning mechanisms.

Self-organized vertically aligned single-crystal silicon nanostructures with controlled shape and aspect ratio by reactive plasma etching

The formation of vertically aligned single-crystalline silicon nanostructures via "self-organized" maskless etching in Ar+ H 2 plasmas is studied. The shape and aspect ratio can be effectively controlled by the reactive plasma composition. In the optimum parameter space, single-crystalline pyramid-like nanostructures are produced; otherwise, nanocones and nanodots are formed. This generic nanostructure formation approach does not involve any external material deposition. It is based on a concurrent sputtering, etching, hydrogen termination, and atom/radical redeposition and can be applied to other nanomaterials.

Thermodynamical and plasma-driven kinetic growth of high-aspect-ratio nanostructures : effect of hydrogen termination

The results of studies on the growth of high-aspect nanostructures in low-temperature non-equilibrium plasmas of reactive gas mixtures with or without hydrogen are presented. The results suggest that the hydrogen in the reactive plasma strongly affects the length of the nanostructures. This phenomenon is explained in terms of selective hydrogen passivation of the lateral and top surfaces of the surface-supported nanostructures. The theoretical model describes the effect of the atomic hydrogen passivation on the nanostructure shape and predicts the critical hydrogen coverage of the lateral surfaces necessary to achieve the nanostructure growth with the pre-determined shape. Our results demonstrate that the use of a strongly non-equilibrium plasma is very effective in significantly improving the shape control of quasi-one-dimensional single-crystalline nanostructures.

Multi-scale hybrid numerical simulation of the growth of high-aspect-ratio nanostructures

Recently, a variety high-aspect-ratio nanostructures have been grown and profiled for various applications ranging from field emission transistors to gene/drug delivery devices. However, fabricating and processing arrays of these structures and determining how changing certain physical parameters affects the final outcome is quite challenging. We have developed several modules that can be used to simulate the processes of various physical vapour deposition systems from precursor interaction in the gas phase to gas-surface interactions and surface processes. In this paper, multi-scale hybrid numerical simulations are used to study how low-temperature non-equilibrium plasmas can be employed in the processing of high-aspect-ratio structures such that the resulting nanostructures have properties suitable for their eventual device application. We show that whilst using plasma techniques is beneficial in many nanofabrication processes, it is especially useful in making dense arrays of high-aspect-ratio nanostructures.

Computational fluid dynamics simulation and turbomachinery code validation of a high pressure ratio radial-inflow turbine

The present study explores reproducing the closest geometry of a high pressure ratio single stage radial-inflow turbine applied in the Sundstrans Power Systems T-100 Multipurpose Small Power Unit. The commercial software ANSYS-Vista RTD along with a built in module, BladeGen, is used to conduct a meanline design and create 3D geometry of one flow passage. Carefully examining the proposed design against the geometrical and experimental data, ANSYS-TurboGrid is applied to generate computational mesh. CFD simulations are performed with ANSYS-CFX in which three-dimensional Reynolds-Averaged Navier-Stokes equations are solved subject to appropriate boundary conditions. Results are compared with numerical and experimental data published in the literature in order to generate the exact geometry of the existing turbine and validate the numerical results against the experimental ones.

A speaker rediarization scheme for improving diarization in large two-speaker telephone datasets

In this paper we propose a novel scheme for carrying out speaker diarization in an iterative manner. We aim to show that the information obtained through the first pass of speaker diarization can be reused to refine and improve the original diarization results. We call this technique speaker rediarization and demonstrate the practical application of our rediarization algorithm using a large archive of two-speaker telephone conversation recordings. We use the NIST 2008 SRE summed telephone corpora for evaluating our speaker rediarization system. This corpus contains recurring speaker identities across independent recording sessions that need to be linked across the entire corpus. We show that our speaker rediarization scheme can take advantage of inter-session speaker information, linked in the initial diarization pass, to achieve a 30% relative improvement over the original diarization error rate (DER) after only two iterations of rediarization.

Rescaling clustering trees using impact ratios for robust hierarchical speaker clustering

We present a novel method for improving hierarchical speaker clustering in the tasks of speaker diarization and speaker linking. In hierarchical clustering, a tree can be formed that demonstrates various levels of clustering. We propose a ratio that expresses the impact of each cluster on the formation of this tree and use this to rescale cluster scores. This provides score normalisation based on the impact of each cluster. We use a state-of-the-art speaker diarization and linking system across the SAIVT-BNEWS corpus to show that our proposed impact ratio can provide a relative improvement of 16% in diarization error rate (DER).

A pseudo-marginal sequential Monte Carlo algorithm for random effects models in Bayesian sequential design

A computationally efficient sequential Monte Carlo algorithm is proposed for the sequential design of experiments for the collection of block data described by mixed effects models. The difficulty in applying a sequential Monte Carlo algorithm in such settings is the need to evaluate the observed data likelihood, which is typically intractable for all but linear Gaussian models. To overcome this difficulty, we propose to unbiasedly estimate the likelihood, and perform inference and make decisions based on an exact-approximate algorithm. Two estimates are proposed: using Quasi Monte Carlo methods and using the Laplace approximation with importance sampling. Both of these approaches can be computationally expensive, so we propose exploiting parallel computational architectures to ensure designs can be derived in a timely manner. We also extend our approach to allow for model uncertainty. This research is motivated by important pharmacological studies related to the treatment of critically ill patients.

A novel manoeuvering model based on low-aspect-ratio lift theory and Lagrangian mechanics

This paper proposes a physically motivated reappraisal of manoeuvring models for ships and presents a new model developed from first principles by application of low aspect-ratio aerodynamic theory and Lagrangian mechanics. The coefficients of the model are shown to be related to physical processes, and validation is presented using the results from a planar motion mechanism dataset.

Cone Ratios in Myopia and Emmetropia: A Pilot Study

Purpose There is a suggestion that the long wavelength-sensitive (LWS)-to-middle wavelength-sensitive (MWS) cone ratio in the retina is associated with myopia. The aim was to measure the LWS/MWS amplitude modulation ratio, an estimate of the LWS/MWS cone ratio, in young adult emmetropes and myopes. Methods Multifocal visual evoked potentials were measured when the LWS and MWS cone systems were excited separately using the method of silent substitution. The 30 young adult participants (22 to 33 years) included 10 emmetropes (mean [±SD] refraction, +0.3 [±0.4] diopters [D]) and 20 myopes (mean [±SD] refraction, -3.4 [±1.7] D). Results The LWS/MWS amplitude modulation ratios ranged from 0.56 to 1.80 in the central 3- to 13-degree diameter ring and from 0.94 to 1.91 in the peripheral 13- to 30-degree diameter ring. Within the central ring, the mean (±SD) ratios were 1.20 (±0.26) and 1.20 (±0.33) for the emmetropic and the myopic groups, respectively. For the peripheral ring, the mean (±SD) ratios were 1.48 (±0.27) and 1.30 (±0.27), respectively. There were no significant differences in the ratios between the emmetropic and myopic groups for either the central (p = 0.99) or peripheral (p = 0.08) rings. For the latter, more myopic refractive error was associated with lower LWS/MWS amplitude modulation ratio; the refraction explained 16% (p = 0.02) of variation in ratio. Conclusions The relationship between the LWS/MWS amplitude modulation ratios and refraction at 13 to 30 degrees indicates that a large longitudinal study of changes in refraction in persons with known cone ratio is required to determine if a low LWS/MWS cone ratio is associated with myopia development.

A new ambiguity acceptance test threshold determination method with controllable failure rate

The ambiguity acceptance test is an important quality control procedure in high precision GNSS data processing. Although the ambiguity acceptance test methods have been extensively investigated, its threshold determine method is still not well understood. Currently, the threshold is determined with the empirical approach or the fixed failure rate (FF-) approach. The empirical approach is simple but lacking in theoretical basis, while the FF-approach is theoretical rigorous but computationally demanding. Hence, the key of the threshold determination problem is how to efficiently determine the threshold in a reasonable way. In this study, a new threshold determination method named threshold function method is proposed to reduce the complexity of the FF-approach. The threshold function method simplifies the FF-approach by a modeling procedure and an approximation procedure. The modeling procedure uses a rational function model to describe the relationship between the FF-difference test threshold and the integer least-squares (ILS) success rate. The approximation procedure replaces the ILS success rate with the easy-to-calculate integer bootstrapping (IB) success rate. Corresponding modeling error and approximation error are analysed with simulation data to avoid nuisance biases and unrealistic stochastic model impact. The results indicate the proposed method can greatly simplify the FF-approach without introducing significant modeling error. The threshold function method makes the fixed failure rate threshold determination method feasible for real-time applications.

Combining opinions for use in Bayesian networks: A measurement error approach

Bayesian networks (BNs) are graphical probabilistic models used for reasoning under uncertainty. These models are becoming increasing popular in a range of fields including ecology, computational biology, medical diagnosis, and forensics. In most of these cases, the BNs are quantified using information from experts, or from user opinions. An interest therefore lies in the way in which multiple opinions can be represented and used in a BN. This paper proposes the use of a measurement error model to combine opinions for use in the quantification of a BN. The multiple opinions are treated as a realisation of measurement error and the model uses the posterior probabilities ascribed to each node in the BN which are computed from the prior information given by each expert. The proposed model addresses the issues associated with current methods of combining opinions such as the absence of a coherent probability model, the lack of the conditional independence structure of the BN being maintained, and the provision of only a point estimate for the consensus. The proposed model is applied an existing Bayesian Network and performed well when compared to existing methods of combining opinions.