8,656 research outputs found
The experience of enchantment in human-computer interaction
Improving user experience is becoming something of a rallying call in human–computer interaction but experience is not a unitary thing. There are varieties of experiences, good and bad, and we need to characterise these varieties if we are to improve user experience. In this paper we argue that enchantment is a useful concept to facilitate closer relationships between people and technology. But enchantment is a complex concept in need of some clarification. So we explore how enchantment has been used in the discussions of technology and examine experiences of film and cell phones to see how enchantment with technology is possible. Based on these cases, we identify the sensibilities that help designers design for enchantment, including the specific sensuousness of a thing, senses of play, paradox and openness, and the potential for transformation. We use these to analyse digital jewellery in order to suggest how it can be made more enchanting. We conclude by relating enchantment to varieties of experience.</p
Diffusion of Point Defects in Two-Dimensional Colloidal Crystals
We report the first study of the dynamics of point defects, mono and
di-vacancies, in a confined 2-D colloidal crystal in real space and time using
digital video microscopy. The defects are introduced by manipulating individual
particles with optical tweezers. The diffusion rates are measured to be
Hz for mono-vacancies and
Hz for di-vacancies. The elementary diffusion
processes are identified and it is found that the diffusion of di-vacancies is
enhanced by a \textit{dislocation dissociation-recombination} mechanism.
Furthermore, the defects do not follow a simple random walk but their hopping
exhibits memory effects, due to the reduced symmetry (compared to the
triangular lattice) of their stable configurations, and the slow relaxation
rates of the lattice modes.Comment: 6 pages (REVTEX), 5 figures (PS
Protecting eyewitness evidence: Examining the efficacy of a self-administered interview tool
Given the crucial role of eyewitness evidence, statements should be obtained as soon as possible after an incident. This is not always achieved due to demands on police resources. Two studies trace the development of a new tool, the Self-Administered Interview (SAI), designed to elicit a comprehensive initial statement. In Study 1, SAI participants reported more correct details than participants who provided a free recall account, and performed at the same level as participants given a Cognitive Interview. In Study 2, participants viewed a simulated crime and half recorded their statement using the SAI. After a delay of 1 week, all participants completed a free recall test. SAI participants recalled more correct details in the delayed recall task than control participants
A Common Variant Associated with Dyslexia Reduces Expression of the KIAA0319 Gene
Numerous genetic association studies have implicated the KIAA0319 gene on human chromosome 6p22 in dyslexia susceptibility. The causative variant(s) remains unknown but may modulate gene expression, given that (1) a dyslexia-associated haplotype has been implicated in the reduced expression of KIAA0319, and (2) the strongest association has been found for the region spanning exon 1 of KIAA0319. Here, we test the hypothesis that variant(s) responsible for reduced KIAA0319 expression resides on the risk haplotype close to the gene's transcription start site. We identified seven single-nucleotide polymorphisms on the risk haplotype immediately upstream of KIAA0319 and determined that three of these are strongly associated with multiple reading-related traits. Using luciferase-expressing constructs containing the KIAA0319 upstream region, we characterized the minimal promoter and additional putative transcriptional regulator regions. This revealed that the minor allele of rs9461045, which shows the strongest association with dyslexia in our sample (max p-value = 0.0001), confers reduced luciferase expression in both neuronal and non-neuronal cell lines. Additionally, we found that the presence of this rs9461045 dyslexia-associated allele creates a nuclear protein-binding site, likely for the transcriptional silencer OCT-1. Knocking down OCT-1 expression in the neuronal cell line SHSY5Y using an siRNA restores KIAA0319 expression from the risk haplotype to nearly that seen from the non-risk haplotype. Our study thus pinpoints a common variant as altering the function of a dyslexia candidate gene and provides an illustrative example of the strategic approach needed to dissect the molecular basis of complex genetic traits
Ward's Hierarchical Clustering Method: Clustering Criterion and Agglomerative Algorithm
The Ward error sum of squares hierarchical clustering method has been very
widely used since its first description by Ward in a 1963 publication. It has
also been generalized in various ways. However there are different
interpretations in the literature and there are different implementations of
the Ward agglomerative algorithm in commonly used software systems, including
differing expressions of the agglomerative criterion. Our survey work and case
studies will be useful for all those involved in developing software for data
analysis using Ward's hierarchical clustering method.Comment: 20 pages, 21 citations, 4 figure
Breast MRI and tumour biology predict axillary lymph node response to neoadjuvant chemotherapy for breast cancer
Background: In patients who have had axillary nodal metastasis diagnosed prior to neoadjuvant chemotherapy for breast cancer, there is little consensus on how to manage the axilla subsequently. The aim of this study was to explore whether a combination of breast magnetic resonance imaging (MRI) assessed response and primary tumour pathology factors could identify a subset of patients that might be spared axillary node clearance.Methods: A retrospective data analysis was performed of patients with core biopsy-proven axillary nodal metastasis prior to commencement of neoadjuvant chemotherapy (NAC) who had subsequent axillary node clearance (ANC) at definitive breast surgery. Breast tumour and axillary response at MRI before, during and on completion of NAC, core biopsy tumour grade, tumour type and immunophenotype were correlated with pathological response in the breast and the number of metastatic nodes in the ANC specimens.Results: Of 87 consecutive patients with MRI at baseline, interim and after neoadjuvant chemotherapy who underwent ANC at time of breast surgery, 33 (38%) had no residual macrometastatic axillary disease, 28 (32%) had 1–2 metastatic nodes and 26 (30%) had more than 2 metastatic nodes. Factors that predicted axillary nodal complete response were MRI complete response in the breast (p < 0.0001), HER2 positivity (p = 0.02) and non-lobular tumour type (p = 0.015).Conclusion: MRI assessment of breast tumour response to NAC and core biopsy factors are predictive of response in axillary nodes, and can be used to guide decision making regarding appropriate axillary surgery
An efficient density-based clustering algorithm using reverse nearest neighbour
Density-based clustering is the task of discovering high-density regions of
entities (clusters) that are separated from each other by contiguous regions of
low-density. DBSCAN is, arguably, the most popular density-based clustering
algorithm. However, its cluster recovery capabilities depend on the combination
of the two parameters. In this paper we present a new density-based clustering
algorithm which uses reverse nearest neighbour (RNN) and has a single
parameter. We also show that it is possible to estimate a good value for this
parameter using a clustering validity index. The RNN queries enable our
algorithm to estimate densities taking more than a single entity into account,
and to recover clusters that are not well-separated or have different
densities. Our experiments on synthetic and real-world data sets show our
proposed algorithm outperforms DBSCAN and its recent variant ISDBSCAN.Comment: Accepted in: Computing Conference 2019 in London, UK.
http://saiconference.com/Computin
On the Schoenberg Transformations in Data Analysis: Theory and Illustrations
The class of Schoenberg transformations, embedding Euclidean distances into
higher dimensional Euclidean spaces, is presented, and derived from theorems on
positive definite and conditionally negative definite matrices. Original
results on the arc lengths, angles and curvature of the transformations are
proposed, and visualized on artificial data sets by classical multidimensional
scaling. A simple distance-based discriminant algorithm illustrates the theory,
intimately connected to the Gaussian kernels of Machine Learning
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