First principles studies of a Si tip on Si(100) 2x1 reconstructed surface

We present a systematic study of the interaction between a silicon tip and a reconstructed Si(100)2×1 surface by means of total energy calculations using Density Functional Theory. We perform geometry optimisation to obtain the reconstructed Si surface using the Local Density Approximation and the Generalized Gradient Approximation methods and compare our results with those obtained experimentally. We then study the effects of the tip of a scanning probe of an Atomic Force Microscope (AFM) on the behaviour of atoms on the reconstructed surface when the tip translates at distances close to it. Our results show that at certain positions of the tip relative to the surface and depending on the direction of the scan, the Si dimer on the surface flips, resulting to a local reconstruction of the surface into p(2×2) or c(4×2) configurations. These configurations exhibit energy lower by 0.05 eV/dimer compared to the Si(100)2×1 structure

Assessing the performance of the Asian/Pacific islander identification algorithm to infer Hmong ethnicity from electronic health records in California.

OBJECTIVE:This study assesses the performance of the North American Association of Central Cancer Registries Asian/Pacific Islander Identification Algorithm (NAPIIA) to infer Hmong ethnicity. DESIGN AND SETTING:Analyses of electronic health records (EHRs) from 1 January 2011 to 1 October 2015. The NAPIIA was applied to the EHR data, and self-reported Hmong ethnicity from a questionnaire was used as the gold standard. Sensitivity, specificity, positive (PPV) and negative predictive values (NPVs) were calculated comparing the source data ethnicity inferred by the algorithm with the self-reported ethnicity from the questionnaire. PARTICIPANTS:EHRs indicating Hmong, Chinese, Vietnamese and Korean ethnicity who met the original study inclusion criteria were analysed. RESULTS:The NAPIIA had a sensitivity of 78%, a specificity of 99.9%, a PPV of 96% and an NPV of 99%. The prevalence of Hmong population in the sample was 3.9%. CONCLUSION:The high sensitivity of the NAPIIA indicates its effectiveness in detecting Hmong ethnicity. The applicability of the NAPIIA to a multitude of Asian subgroups can advance Asian health disparity research by enabling researchers to disaggregate Asian data and unmask health challenges of different Asian subgroups

Creating Conflict: Case Studies in the Tension Between native Title Claims and Land Rights Claims

A land rights claim was placed on a particular parcel of land, including a small river. A successful claim will mean that the land is granted to the local Aboriginal land council (LALC). Membership of the LALC is based on an Aboriginal person's residence within the boundary of the LALC, or alternatively, based on that person's association with that area. Traditional connection to the land within the boundaries of the LALC is not required for membership. In this scenario, imagine that the majority of the membership of the LALC consists of Aboriginal people who do not have a traditional association ith the parcel of land

Effect of imputation on gene network reconstruction from single-cell RNA-seq data

Despite the advances in single-cell transcriptomics, the reconstruction of gene regulatory networks remains challenging. Both the large amount of zero counts in experimental data and the lack of a consensus preprocessing pipeline for single-cell RNA sequencing (scRNA-seq) data make it hard to infer networks. Imputation can be applied in order to enhance gene-gene correlations and facilitate downstream analysis. However, it is unclear what consequences imputation methods have on the reconstruction of gene regulatory networks. To study this, we evaluate the differences on the performance and structure of reconstructed networks before and after imputation in single-cell data. We observe an inflation of gene-gene correlations that affects the predicted network structures and may decrease the performance of network reconstruction in general. However, within the modest limits of achievable results, we also make a recommendation as to an advisable combination of algorithms while warning against the indiscriminate use of imputation before network reconstruction in general

Estimating the Statistics of Operational Loss Through the Analyzation of a Time Series

In the world of finance, appropriately understanding risk is key to success or failure because it is a fundamental driver for institutional behavior. Here we focus on risk as it relates to the operations of financial institutions, namely operational risk. Quantifying operational risk begins with data in the form of a time series of realized losses, which can occur for a number of reasons, can vary over different time intervals, and can pose a challenge that is exacerbated by having to account for both frequency and severity of losses. We introduce a stochastic point process model for the frequency distribution that has two important parameters (average frequency and time scale). The advantages of this model are that the parameters, which we systematically vary to demonstrate accuracy, can be fitted with sufficient data but are also intuitive enough to rely on expert judgment when data is insufficient. Furthermore, we address how to estimate the risk of losses on an arbitrary time scale for a specific frequency model where mathematical techniques can be feasibly applied to analytically calculate the mean, variance, and covariances that are accurate compared to more time-consuming Monte Carlo simulations. Additionally, the auto- and vi cross-correlation functions become mathematically tractable, enabling analytic calculations of cumulative loss statistics over larger time horizons that would otherwise be intractable due to temporal correlations of losses for long time windows. Finally, we demonstrate the strengths and shortcomings of our new approach by using combined data from a consortium of institutions, comparing this data to our model and correlation calculations, and showing that different time horizons can lead to a large range of loss statistics that can significantly affect calculations of capital requirements

Estimating the correlation between operational risk loss categories over different time horizons

Operational risk is challenging to quantify because of the broad range of categories (fraud, technological issues, natural disasters) and the heavy-tailed nature of realized losses. Operational risk modeling requires quantifying how these broad loss categories are related. We focus on the issue of loss frequencies having different time scales (e.g., daily, yearly, monthly basis), specifically on estimating the statistics of losses on arbitrary time horizons. We present a frequency model where mathematical techniques can be feasibly applied to analytically calculate the mean, variance, and co-variances that are accurate compared to more time-consuming Monte Carlo simulations. We show that the analytic calculations of cumulative loss statistics in an arbitrary time window are feasible here and would otherwise be intractable due to temporal correlations. Our work has potential value because these statistics are crucial for approximating correlations of losses via copulas. We systematically vary all model parameters to demonstrate the accuracy of our methods for calculating all first and second order statistics of aggregate loss distributions. Finally, using combined data from a consortium of institutions, we show that different time horizons can lead to a large range of loss statistics that can significantly affect calculations of capital requirements.Comment: 27 pages, 11 figures, 6 table

Exposure to hazardous volatile organic compounds, PM 10 and CO while walking along streets in urban Guangzhou, China

Toxic air pollutants in street canyons are important issues concerning public health especially in some large Asian cities like Guangzhou. In 1998 <18% of Guangzhou citizens used public transportation modes, with a majority commuting on foot (42%) or by bicycle (22%). Of the pedestrians, 57% were either senior citizens or students. In the present study, we measured toxic air pollutants while walking along urban streets in Guangzhou to evaluate pedestrian exposure. Volatile organic compounds (VOCs) were collected with sorbent tubes, and PM 10 and CO were measured simultaneously with portable analyzers. Our results showed that pedestrian exposure to PM 10 (with an average of 303 μg m -3 for all samples) and some toxic VOCs (for example, benzene) was relatively high. Monocyclic aromatic hydrocarbons were found to be the most abundant VOCs, and 71% of the samples had benzene levels higher than 30 μg m -3. Benzene, PM 10 and CO in walk-only streets were significantly lower (p<0.05) than in traffic streets, and the differences in exposure levels between new urban streets and old urban streets were highly significant (p<0.01). Pedestrian exposure to toxic VOCs and PM 10 was higher than those reported in other public transportation modes (bus and subway). The good correlations between BTEX, PM 10 and CO in the streets indicated that automotive emission might be their major source. Our study also showed that the risk to pedestrians due to air pollution was misinterpreted by the reported air quality index based on measurement of SO 2, NO x and PM 10 in the government monitoring stations. An urban roadside monitoring station might be needed by air quality monitoring networks in large Asian cities like Guangzhou, in order to survey exposure to air toxics in urban roadside microenvironments. © 2004 Elsevier Ltd. All rights reserved

Kepemimpinan Instruksional Kepala Sekolah Dan Iklim Sekolah Terhadap Kinerja Mengajar Guru

This research is to describe the influence of principals\u27 instructional leadership and school climate on teacher performance of secondary schools in the north of Bandung. The study used correlation statistical analysis based on the interpretation of the Pearson Correlation which provides the direction and significance. The Principal Instructional Management Rating Scale (PIMRS) by Hillinger & Murphy, 1985), Organizational Climate Index (OCI) by Hoy, (2003), dan Teacher Performance Criteria Questionnaires (TPCQ) modified by Cheffers & Sullivan (2010); Cheffers & Keilty (1981), Cheffers (1972) are used as the data collection instrument through survey questionnaires. This study with population of 30 schools and 85 teachers as respondents found that the instructional leadership of school principals and school climate significantly and positively influence on teacher performance, yet as the commendation; in order to improve the quality of education, Teacher performance needs to be improved is to use constructively and critically criticism and avoid using harsh criticism