Growth of nanostructures by cluster deposition : a review

This paper presents a comprehensive analysis of simple models useful to analyze the growth of nanostructures obtained by cluster deposition. After detailing the potential interest of nanostructures, I extensively study the first stages of growth (the submonolayer regime) by kinetic Monte-Carlo simulations. These simulations are performed in a wide variety of experimental situations : complete condensation, growth with reevaporation, nucleation on defects, total or null cluster-cluster coalescence... The main scope of the paper is to help experimentalists analyzing their data to deduce which of those processes are important and to quantify them. A software including all these simulation programs is available at no cost on request to the author. I carefully discuss experiments of growth from cluster beams and show how the mobility of the clusters on the surface can be measured : surprisingly high values are found. An important issue for future technological applications of cluster deposition is the relation between the size of the incident clusters and the size of the islands obtained on the substrate. An approximate formula which gives the ratio of the two sizes as a function of the melting temperature of the material deposited is given. Finally, I study the atomic mechanisms which can explain the diffusion of the clusters on a substrate and the result of their mutual interaction (simple juxtaposition, partial or total coalescence...)Comment: To be published Rev Mod Phys, Oct 99, RevTeX, 37 figure

The Influence of Manga on the Graphic Novel

This material has been published in The Cambridge History of the Graphic Novel edited by Jan Baetens, Hugo Frey, Stephen E. Tabachnick. This version is free to view and download for personal use only. Not for re-distribution, re-sale or use in derivative works. © Cambridge University PressProviding a range of cogent examples, this chapter describes the influences of the Manga genre of comics strip on the Graphic Novel genre, over the last 35 years, considering the functions of domestication, foreignisation and transmedia on readers, markets and forms

Defining an ageing-related pathology, disease or syndrome: International Consensus Statement

Around the world, individuals are living longer, but an increased average lifespan does not always equate to an increased health span. With advancing age, the increased prevalence of ageing-related diseases can have a significant impact on health status, functional capacity and quality of life. It is therefore vital to develop comprehensive classification and staging systems for ageing-related pathologies, diseases and syndromes. This will allow societies to better identify, quantify, understand and meet the healthcare, workforce, well-being and socioeconomic needs of ageing populations, whilst supporting the development and utilisation of interventions to prevent or to slow, halt or reverse the progression of ageing-related pathologies. The foundation for developing such classification and staging systems is to define the scope of what constitutes an ageing-related pathology, disease or syndrome. To this end, a consensus meeting was hosted by the International Consortium to Classify Ageing-Related Pathologies (ICCARP), on February 19, 2024, in Cardiff, UK, and was attended by 150 recognised experts. Discussions and voting were centred on provisional criteria that had been distributed prior to the meeting. The participants debated and voted on these. Each criterion required a consensus agreement of ≥ 70% for approval. The accepted criteria for an ageing-related pathology, disease or syndrome were (1) develops and/or progresses with increasing chronological age; (2) should be associated with, or contribute to, functional decline or an increased susceptibility to functional decline and (3) evidenced by studies in humans. Criteria for an ageing-related pathology, disease or syndrome have been agreed by an international consortium of subject experts. These criteria will now be used by the ICCARP for the classification and ultimately staging of ageing-related pathologies, diseases and syndromes

AudioGene: Predicting Hearing Loss Genotypes from Phenotypes to Guide Genetic Screening

Item does not contain fulltextAutosomal dominant nonsyndromic hearing loss (ADNSHL) is a common and often progressive sensory deficit. ADNSHL displays a high degree of genetic heterogeneity and varying rates of progression. Accurate, comprehensive, and cost-effective genetic testing facilitates genetic counseling and provides valuable prognostic information to affected individuals. In this article, we describe the algorithm underlying AudioGene, a software system employing machine-learning techniques that utilizes phenotypic information derived from audiograms to predict the genetic cause of hearing loss in persons segregating ADNSHL. Our data show that AudioGene has an accuracy of 68% in predicting the causative gene within its top three predictions, as compared with 44% for a majority classifier. We also show that AudioGene remains effective for audiograms with high levels of clinical measurement noise. We identify audiometric outliers for each genetic locus and hypothesize that outliers may reflect modifying genetic effects. As personalized genomic medicine becomes more common, AudioGene will be increasingly useful as a phenotypic filter to assess pathogenicity of variants identified by massively parallel sequencing