University of Bath

About: University of Bath is a education organization based out in Bath, Bath and North East Somerset, United Kingdom. It is known for research contribution in the topics: Population & Photonic-crystal fiber. The organization has 15830 authors who have published 39608 publications receiving 1358769 citations. The organization is also known as: Bath University.

The prevalence of suicidal phenomena in adolescents: A systematic review of population-based studies

Abstract: The results of a systematic review of the international literature on the prevalence of suicidal phenomena in adolescents, including the influence of survey method, gender, and ethnicity are reported. The literature was searched using six electronic databases to identify all population-based studies of self-reported suicidal phenomena; 128 studies were included, comprising 513,188 adolescents. The mean proportion of adolescents reporting they had attempted suicide at some point in their lives was 9.7% (95% CI, 8.5-10.9), and 29.9% (95% CI, 26.1-33.8) of adolescents said they had thought about suicide at some point. Females were significantly more likely than males to report most suicidal phenomena. A lower prevalence of some suicidal phenomena was found for Asian populations. The prevalence of suicidal phenomena varied depending on the terminology used and tended to be higher in studies employing anonymous questionnaires than in studies employing non-anonymous methods (questionnaires or interviews), although most of these differences were not statistically significant.

DCT-Based Iris Recognition

Abstract: This paper presents a novel iris coding method based on differences of discrete cosine transform (DCT) coefficients of overlapped angular patches from normalized iris images. The feature extraction capabilities of the DCT are optimized on the two largest publicly available iris image data sets, 2,156 images of 308 eyes from the CASIA database and 2,955 images of 150 eyes from the Bath database. On this data, we achieve 100 percent correct recognition rate (CRR) and perfect receiver-operating characteristic (ROC) curves with no registered false accepts or rejects. Individual feature bit and patch position parameters are optimized for matching through a product-of-sum approach to Hamming distance calculation. For verification, a variable threshold is applied to the distance metric and the false acceptance rate (FAR) and false rejection rate (FRR) are recorded. A new worst-case metric is proposed for predicting practical system performance in the absence of matching failures, and the worst case theoretical equal error rate (EER) is predicted to be as low as 2.59 times 10-1 available data sets

Low‐Rank Scale‐Invariant Tensor Product Smooths for Generalized Additive Mixed Models

Abstract: Summary A general method for constructing low-rank tensor product smooths for use as components of generalized additive models or generalized additive mixed models is presented. A penalized regression approach is adopted in which tensor product smooths of several variables are constructed from smooths of each variable separately, these “marginal” smooths being represented using a low-rank basis with an associated quadratic wiggliness penalty. The smooths offer several advantages: (i) they have one wiggliness penalty per covariate and are hence invariant to linear rescaling of covariates, making them useful when there is no “natural” way to scale covariates relative to each other; (ii) they have a useful tuneable range of smoothness, unlike single-penalty tensor product smooths that are scale invariant; (iii) the relatively low rank of the smooths means that they are computationally efficient; (iv) the penalties on the smooths are easily interpretable in terms of function shape; (v) the smooths can be generated completely automatically from any marginal smoothing bases and associated quadratic penalties, giving the modeler considerable flexibility to choose the basis penalty combination most appropriate to each modeling task; and (vi) the smooths can easily be written as components of a standard linear or generalized linear mixed model, allowing them to be used as components of the rich family of such models implemented in standard software, and to take advantage of the efficient and stable computational methods that have been developed for such models. A small simulation study shows that the methods can compare favorably with recently developed smoothing spline ANOVA methods.

A review of growth mechanism, structure and crystallinity of anodized TiO2 nanotubes

Abstract: This paper reviews the state of the art of anodized titanium dioxide nanotubes (TiO2 NTs), with an emphasis on the growth mechanism leading to their formation and the effect of heat treatment on their structure and properties. The discussion is primarily focused on TiO2 NTs grown in fluoride containing electrolytes, although the mechanism of formation of NTs in fluoride free solutions via Rapid Breakdown Anodization (RBA) is briefly covered. After an initial overview of progress made on the synthesis of anodized TiO2 NTs the review provides an analysis of the factors affecting the anodizing process (fluoride concentration, electrolyte type, applied potential and anodizing time). Details of the current-time transient, the chemistry of the process and the chemical composition of the anodic films are described which provide key information to unveil the nanotube growth mechanism. The main debate is whether NTs growth in fluoride containing solutions occurs via field-assisted plastic flow (i.e. a constant upward displacement of the oxide to form the NTs) combined with field-assisted ejection of the Ti4+ ions (i.e. ions are ejected into the electrolyte without oxide formation) or via field-assisted dissolution (i.e. preferential dissolution at the pore base where the field is stronger) or whether both processes play a role. Whenever anodization takes place in organic solutions the experimental evidence supports the plastic flow model, whereas in aqueous media field-assisted (and chemical) dissolution occur. The mechanism of rib formation on the walls of the NTs is also reviewed, and it clearly emerges that the applied potential and water content in the electrolyte are key factors in determining whether the NTs are ribbed or smooth. There also appears to be a relationship between the presence of ribs and the evolution of oxygen bubbles at the anode. The impact of thermal treatment on the properties of the NTs is also described. A variety of crystalline structures are present in the NTs (i.e. anatase or rutile), depending on the heat treatment temperature and atmosphere and the resulting electrical properties can be varied from dielectric to semi-metallic. A heat treatment temperature limit ranging from 500 to 800 °C exists, depending on preparation history, above which sintering of nanoscale titania particles occurs leading to collapse of the NTs structure. Future work should aim at using annealing not just to influence the resulting crystalline phase, but also for generating defects to be exploited in specific applications (i.e. photocatalysis, water splitting and photovoltaics).