Angular distribution of carbon ion flux in a nanotube array during the plasma process by the Monte Carlo technique

Angular distribution of microscopic ion fluxes around nanotubes arranged into a dense ordered pattern on the surface of the substrate is studied by means of multiscale numerical simulation. The Monte Carlo technique was used to show that the ion current density is distributed nonuniformly around the carbon nanotubes arranged into a dense rectangular array. The nonuniformity factor of the ion current flux reaches 7 in dense (5× 1018 m-3) plasmas for a nanotube radius of 25 nm, and tends to 1 at plasma densities below 1× 1017 m-3. The results obtained suggest that the local density of carbon adatoms on the nanotube side surface, at areas facing the adjacent nanotubes of the pattern, can be high enough to lead to the additional wall formation and thus cause the single- to multiwall structural transition, and other as yet unexplained nanoscience phenomena.

Computational plasma nanoscience : where plasma physics meets surface science

Multiscale hybrid simulations that bridge the nine-order-of-magnitude spatial gap between the macroscopic plasma nanotools and microscopic surface processes on nanostructured solids are described. Two specific examples of carbon nanotip-like and semiconductor quantum dot nanopatterns are considered. These simulations are instrumental in developing physical principles of nanoscale assembly processes on solid surfaces exposed to low-temperature plasmas.

Ion-assisted functional monolayer coating of nanorod arrays in hydrogen plasmas

Uniformity of postprocessing of large-area, dense nanostructure arrays is currently one of the greatest challenges in nanoscience and nanofabrication. One of the major issues is to achieve a high level of control in specie fluxes to specific surface areas of the nanostructures. As suggested by the numerical experiments in this work, this goal can be achieved by manipulating microscopic ion fluxes by varying the plasma sheath and nanorod array parameters. The dynamics of ion-assisted deposition of functional monolayer coatings onto two-dimensional carbon nanorod arrays in a hydrogen plasma is simulated by using a multiscale hybrid numerical simulation. The numerical results show evidence of a strong correlation between the aspect ratios and nanopattern positioning of the nanorods, plasma sheath width, and densities and distributions of microscopic ion fluxes. When the spacing between the nanorods and/or their aspect ratios are larger, and/or the plasma sheath is wider, the density of microscopic ion current flowing to each of the individual nanorods increases, thus reducing the time required to apply a functional monolayer coating down to 11 s for a 7-μm-wide sheath, and to 5 s for a 50-μm-wide sheath. The computed monolayer coating development time is consistent with previous experimental reports on plasma-assisted functionalization of related carbon nanostructures [B. N. Khare et al., Appl. Phys. Lett. 81, 5237 (2002)]. The results are generic in that they can be applied to a broader range of plasma-based processes and nanostructures, and contribute to the development of deterministic strategies of postprocessing and functionalization of various nanoarrays for nanoelectronic, biomedical, and other emerging applications.

Application of a hybrid Entropy–McKinsey Matrix method in evaluating sustainable urbanization : a China case study

Although urbanization can promote social and economic development, it can also cause various problems. As the key decision makers of urbanization, local governments should be able to evaluate urbanization performance, summarize experiences, and find problems caused by urbanization. This paper introduces a hybrid Entropy–McKinsey Matrix method for evaluating sustainable urbanization. The McKinsey Matrix is commonly referred to as the GE Matrix. The values of a development index (DI) and coordination index (CI) are calculated by employing the Entropy method and are used as a basis for constructing a GE Matrix. The matrix can assist in assessing sustainable urbanization performance by locating the urbanization state point. A case study of the city of Jinan in China demonstrates the process of using the evaluation method. The case study reveals that the method is an effective tool in helping policy makers understand the performance of urban sustainability and therefore formulate suitable strategies for guiding urbanization toward better sustainability.

SWCNT networks on nanoporous silica catalyst support : morphological and connectivity control for nanoelectronic, gas-sensing, and biosensing devices

Effective control of morphology and electrical connectivity of networks of single-walled carbon nanotubes (SWCNTs) by using rough, nanoporous silica supports of Fe catalyst nanoparticles in catalytic chemical vapor deposition is demonstrated experimentally. The very high quality of the nanotubes is evidenced by the G-to-D Raman peak ratios (>50) within the range of the highest known ratios. Transitions from separated nanotubes on smooth SiO2 surface to densely interconnected networks on the nanoporous SiO2 are accompanied by an almost two-order of magnitude increase of the nanotube density. These transitions herald the hardly detectable onset of the nanoscale connectivity and are confirmed by the microanalysis and electrical measurements. The achieved effective nanotube interconnection leads to the dramatic, almost three-orders of magnitude decrease of the SWCNT network resistivity compared to networks of similar density produced by wet chemistry-based assembly of preformed nanotubes. The growth model, supported by multiscale, multiphase modeling of SWCNT nucleation reveals multiple constructive roles of the porous catalyst support in facilitating the catalyst saturation and SWCNT nucleation, consistent with the observed higher density of longer nanotubes. The associated mechanisms are related to the unique surface conditions (roughness, wettability, and reduced catalyst coalescence) on the porous SiO2 and the increased carbon supply through the supporting porous structure. This approach is promising for the direct integration of SWCNT networks into Si-based nanodevice platforms and multiple applications ranging from nanoelectronics and energy conversion to bio- and environmental sensing.

Training needs research applied to the development of a standardised incident investigator training framework

In response to the rail industry lacking a consistently accepted standard of minimal training to perform incident investigations, the Australasian rail industry requested the development of a unified approach to investigator training. This paper details how the findings from a training needs analysis were applied to inform the development of a standardised training package for rail incident investigators. Data from job descriptions, training documents and subject matter experts sourced from 17 Australasian organisations were analysed and refined to yield a draft set of 10 critical competencies. Finally the draft of critical competencies was reviewed by industry experts to verify the accuracy and completeness of the competency list and to consider the most appropriate level of qualification for training development. The competencies identified and the processes described to translate research into an applied training framework in this paper, can be generalised to assist practitioners and researchers in developing industry approved standardised training packages.

Melanopsin expressing intrinsically photosensitive Retinal Ganglion cells in retinal disease

Melanopsin containing intrinsically photosensitive Retinal Ganglion Cells (ipRGCs) are a class of photoreceptors with established roles in non-image forming processes. Their contributions to image forming vision may include the estimation of brightness. Animal models have been central for understanding the physiological mechanisms of ipRGC function and there is evidence of conservation of function across species. ipRGCs can be divided into 5 ganglion cell subtypes that show morphological and functional diversity. Research in humans has established that ipRGCs signal environmental irradiance to entrain the central body clock to the solar day for regulating circadian processes and sleep. In addition, ipRGCs mediate the pupil light reflex (PLR), making the PLR a readily accessible behavioural marker of ipRGC activity. Less is known about ipRGC function in retinal and optic nerve disease, with emerging research providing insight into their function in diabetes, retinitis pigmentosa, glaucoma and hereditary optic neuropathy. We briefly review the anatomical distributions, projections and basic physiological mechanisms of ipRGCs, their proposed and known functions in animals and humans with and without eye disease. We introduce a paradigm for differentiating inner and outer retinal inputs to the pupillary control pathway in retinal disease and apply this paradigm to patients with age-related macular degeneration (AMD). In these cases of patients with AMD, we provide the initial evidence that ipRGC function is altered, and that the dysfunction is more pronounced in advanced disease. Our perspective is that with refined pupillometry paradigms, the pupil light reflex can be extended to AMD assessment as a tool for the measurement of inner and outer retinal dysfunction.

China's "Responsible Protection" concept : re-interpreting the Responsibility to Protect (R2P) and military intervention for humanitarian purposes

This article assesses the extent to which the recently formulated Chinese concept of “Responsible Protection” (RP) offers a valuable contribution to the normative debate over R2P’s third pillar following the controversy over military intervention in Libya. While RP draws heavily on previous proposals such as the original 2001 ICISS report and Brazil’s “Responsibility while Protecting” (RwP), by amalgamating and re-packaging these earlier ideas in a more restrictive form the initiative represents a new and distinctive interpretation of R2P. However, some aspects of RP are framed too narrowly to provide workable guidelines for determining the permissibility of military intervention for civilian protection purposes, and should therefore be clarified and refined. Nevertheless, the Chinese proposal remains significant because it offers important insights into Beijing’s current stance on R2P. More broadly, China’s RP and Brazil’s RwP initiatives illustrate the growing willingness of rising, non-Western powers to assert their own normative preferences on sovereignty, intervention and global governance.

Bridging experiments, models and simulations : an integrative approach to validation in computational cardiac electrophysiology

Computational models in physiology often integrate functional and structural information from a large range of spatio-temporal scales from the ionic to the whole organ level. Their sophistication raises both expectations and scepticism concerning how computational methods can improve our understanding of living organisms and also how they can reduce, replace and refine animal experiments. A fundamental requirement to fulfil these expectations and achieve the full potential of computational physiology is a clear understanding of what models represent and how they can be validated. The present study aims at informing strategies for validation by elucidating the complex interrelations between experiments, models and simulations in cardiac electrophysiology. We describe the processes, data and knowledge involved in the construction of whole ventricular multiscale models of cardiac electrophysiology. Our analysis reveals that models, simulations, and experiments are intertwined, in an assemblage that is a system itself, namely the model-simulation-experiment (MSE) system. Validation must therefore take into account the complex interplay between models, simulations and experiments. Key points for developing strategies for validation are: 1) understanding sources of bio-variability is crucial to the comparison between simulation and experimental results; 2) robustness of techniques and tools is a pre-requisite to conducting physiological investigations using the MSE system; 3) definition and adoption of standards facilitates interoperability of experiments, models and simulations; 4) physiological validation must be understood as an iterative process that defines the specific aspects of electrophysiology the MSE system targets, and is driven by advancements in experimental and computational methods and the combination of both.

Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images

Age-related Macular Degeneration (AMD) is one of the major causes of vision loss and blindness in ageing population. Currently, there is no cure for AMD, however early detection and subsequent treatment may prevent the severe vision loss or slow the progression of the disease. AMD can be classified into two types: dry and wet AMDs. The people with macular degeneration are mostly affected by dry AMD. Early symptoms of AMD are formation of drusen and yellow pigmentation. These lesions are identified by manual inspection of fundus images by the ophthalmologists. It is a time consuming, tiresome process, and hence an automated diagnosis of AMD screening tool can aid clinicians in their diagnosis significantly. This study proposes an automated dry AMD detection system using various entropies (Shannon, Kapur, Renyi and Yager), Higher Order Spectra (HOS) bispectra features, Fractional Dimension (FD), and Gabor wavelet features extracted from greyscale fundus images. The features are ranked using t-test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance (CBBD), Receiver Operating Characteristics (ROC) curve-based and Wilcoxon ranking methods in order to select optimum features and classified into normal and AMD classes using Naive Bayes (NB), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The performance of the proposed system is evaluated using private (Kasturba Medical Hospital, Manipal, India), Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) datasets. The proposed system yielded the highest average classification accuracies of 90.19%, 95.07% and 95% with 42, 54 and 38 optimal ranked features using SVM classifier for private, ARIA and STARE datasets respectively. This automated AMD detection system can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.

Decision support system for age-related macular degeneration using discrete wavelet transform

Age-related macular degeneration (AMD) affects the central vision and subsequently may lead to visual loss in people over 60 years of age. There is no permanent cure for AMD, but early detection and successive treatment may improve the visual acuity. AMD is mainly classified into dry and wet type; however, dry AMD is more common in aging population. AMD is characterized by drusen, yellow pigmentation, and neovascularization. These lesions are examined through visual inspection of retinal fundus images by ophthalmologists. It is laborious, time-consuming, and resource-intensive. Hence, in this study, we have proposed an automated AMD detection system using discrete wavelet transform (DWT) and feature ranking strategies. The first four-order statistical moments (mean, variance, skewness, and kurtosis), energy, entropy, and Gini index-based features are extracted from DWT coefficients. We have used five (t test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance, receiver operating characteristics curve-based, and Wilcoxon) feature ranking strategies to identify optimal feature set. A set of supervised classifiers namely support vector machine (SVM), decision tree, k -nearest neighbor ( k -NN), Naive Bayes, and probabilistic neural network were used to evaluate the highest performance measure using minimum number of features in classifying normal and dry AMD classes. The proposed framework obtained an average accuracy of 93.70 %, sensitivity of 91.11 %, and specificity of 96.30 % using KLD ranking and SVM classifier. We have also formulated an AMD Risk Index using selected features to classify the normal and dry AMD classes using one number. The proposed system can be used to assist the clinicians and also for mass AMD screening programs.

On the effect of topology on cellular automata rule spaces

This thesis presents an empirical study of the effects of topology on cellular automata rule spaces. The classical definition of a cellular automaton is restricted to that of a regular lattice, often with periodic boundary conditions. This definition is extended to allow for arbitrary topologies. The dynamics of cellular automata within the triangular tessellation were analysed when transformed to 2-manifolds of topological genus 0, genus 1 and genus 2. Cellular automata dynamics were analysed from a statistical mechanics perspective. The sample sizes required to obtain accurate entropy calculations were determined by an entropy error analysis which observed the error in the computed entropy against increasing sample sizes. Each cellular automata rule space was sampled repeatedly and the selected cellular automata were simulated over many thousands of trials for each topology. This resulted in an entropy distribution for each rule space. The computed entropy distributions are indicative of the cellular automata dynamical class distribution. Through the comparison of these dynamical class distributions using the E-statistic, it was identified that such topological changes cause these distributions to alter. This is a significant result which implies that both global structure and local dynamics play a important role in defining long term behaviour of cellular automata.

Development and validation of the ankle fracture outcome of rehabilitation measure (A-FORM)

Study Design Delphi panel and cohort study. Objective To develop and refine a condition-specific, patient-reported outcome measure, the Ankle Fracture Outcome of Rehabilitation Measure (A-FORM), and to examine its psychometric properties, including factor structure, reliability, and validity, by assessing item fit with the Rasch model. Background To our knowledge, there is no patient-reported outcome measure specific to ankle fracture with a robust content foundation. Methods A 2-stage research design was implemented. First, a Delphi panel that included patients and health professionals developed the items and refined the item wording. Second, a cohort study (n = 45) with 2 assessment points was conducted to permit preliminary maximum-likelihood exploratory factor analysis and Rasch analysis. Results The Delphi panel reached consensus on 53 potential items that were carried forward to the cohort phase. From the 2 time points, 81 questionnaires were completed and analyzed; 38 potential items were eliminated on account of greater than 10% missing data, factor loadings, and uniqueness. The 15 unidimensional items retained in the scale demonstrated appropriate person and item reliability after (and before) removal of 1 item (anxious about footwear) that had a higher-than-ideal outfit statistic (1.75). The “anxious about footwear” item was retained in the instrument, but only the 14 items with acceptable infit and outfit statistics (range, 0.5–1.5) were included in the summary score. Conclusion This investigation developed and refined the A-FORM (Version 1.0). The A-FORM items demonstrated favorable psychometric properties and are suitable for conversion to a single summary score. Further studies utilizing the A-FORM instrument are warranted. J Orthop Sports Phys Ther 2014;44(7):488–499. Epub 22 May 2014. doi:10.2519/jospt.2014.4980

Detection of rain in acoustic recordings of the environment

Environmental monitoring has become increasingly important due to the significant impact of human activities and climate change on biodiversity. Environmental sound sources such as rain and insect vocalizations are a rich and underexploited source of information in environmental audio recordings. This paper is concerned with the classification of rain within acoustic sensor re-cordings. We present the novel application of a set of features for classifying environmental acoustics: acoustic entropy, the acoustic complexity index, spectral cover, and background noise. In order to improve the performance of the rain classification system we automatically classify segments of environmental recordings into the classes of heavy rain or non-rain. A decision tree classifier is experientially compared with other classifiers. The experimental results show that our system is effective in classifying segments of environmental audio recordings with an accuracy of 93% for the binary classification of heavy rain/non-rain.

Carcinogenicity and genotoxicity of ethylene oxide : new aspects and recent advances

Long-term inhalation studies in rodents have presented unequivocal evidence of experimental carcinogenicity of ethylene oxide, based on the formation of malignant tumors at multiple sites. However, despite a considerable body of epidemiological data only limited evidence has been obtained of its carcinogenicity in humans. Ethylene oxide is not only an important exogenous toxicant, but it is also formed from ethylene as a biological precursor. Ethylene is a normal body constituent; its endogenous formation is evidenced by exhalation in rats and in humans. Consequently, ethylene oxide must also be regarded as a physiological compound. The most abundant DNA adduct of ethylene oxide is 7-(2-hydroxyethyl)guanine (HOEtG). Open questions are the nature and role of tissue-specific factors in ethylene oxide carcinogenesis and the physiological and quantitative role of DNA repair mechanisms. The detection of remarkable individual differences in the susceptibility of humans has promoted research into genetic factors that influence the metabolism of ethylene oxide. With this background it appears that current PBPK models for trans-species extrapolation of ethylene oxide toxicity need to be refined further. For a cancer risk assessment at low levels of DNA damage, exposure-related adducts must be discussed in relation to background DNA damage as well as to inter- and intraindividual variability. In rats, subacute ethylene oxide exposures on the order of 1 ppm (1.83 mg/m3) cause DNA adduct levels (HOEtG) of the same magnitude as produced by endogenous ethylene oxide. Based on very recent studies the endogenous background levels of HOEtG in DNA of humans are comparable to those that are produced in rodents by repetitive exogenous ethylene oxide exposures of about 10 ppm (18.3 mg/m3). Experimentally, ethylene oxide has revealed only weak mutagenic effects in vivo, which are confined to higher doses. It has been concluded that long-term human occupational exposure to low airborne concentrations to ethylene oxide, at or below current occupational exposure limits of 1 ppm (1.83 mg/m3), would not produce unacceptable increased genotoxic risks. However, critical questions remain that need further discussions relating to the coherence of animal and human data of experimental data in vitro vs. in vivo and to species-specific dynamics of DNA lesions.