some perceptions on the portuguese legacy in Sri Lanka

Remembered histories and forgotten societie

Covariate-Adjusted Constrained Bayes Predictions of Random Intercepts and Slopes. Sujit Ghosh is a

Constrained Bayes methodology represents an alternative to the posterior mean (empirical Bayes) method commonly used to produce random effect predictions under mixed linear models. The general constrained Bayes methodology of Ghosh (1992) is compared to a direct implementation of constraints, and it is suggested that the former approach could feasibly be incorporated into commercial mixed model software. Simulation studies and a real-data example illustrate the main points and support the conclusions

Using student self-assessment to steer feedback

BACKGROUND Students might better engage with feedback if they are responsible for steering the feedback process. However, this requires them to first accurately assess the quality of their work. AIMS To determine whether providing students with a structured self-assessment method prior to submission influences their confidence with this process. DESCRIPTION OF INTERVENTION Students were asked to complete a brief self-assessment of one of their laboratory reports, which markers then used to guide their feedback to each student. DESIGN AND METHODS Participants were undergraduate students undertaking a second-year pharmacology unit in semester 2, 2018 (n=117/265 enrolled). Students were invited to complete an anonymous survey asking them about their perceptions of self-assessment. RESULTS 55% of respondents indicated that they found feedback useful following self-assessment. Of these respondents, 54% indicated that being able to first specify areas of difficulty was the reason why. However, 34% of all respondents indicated that they still lacked confidence in accurately evaluating their work. CONCLUSIONS Students’ lack of confidence in their ability to self-evaluate suggests that perhaps they are not given sufficient opportunity to practice this skill. Although our current model could be extended into any setting, the value of self-evaluation first needs to be understood by students in order to promote their full engagement with this process

UAV Remote Sensing for delineation of Urban Vegetation using Object Based Image Analysis

Remote sensing technology has rapidly advanced during the last few decades and the number of remote sensing platforms has increased. The development of Unmanned Aerial Vehicles (UAV) image acquisition systems has radically changed the aerial Photogrammetric mapping due to its low cost, high spatial resolution and high accuracy and provide a great potential for vegetation mapping in urban areas. Urban environment planning becomes a challenging task for urban planners due to fast urbanization processes and growth of population. Urban land use is a crucial information for planning authorities and there is a growing demand for urban land cover maps for decision-making procedures in urban planning. In this article, we demonstrate a rule sets knowledge-based classification method, in object oriented classification which is a fully automated and highly accurate engineering approach for demarcation of urban vegetation with the use of eCognition software. DJI Phantom 4, consumer grade drone was used to acquire high resolution aerial photos as an input dataset in the study. In this study, vegetation mapping was done using the textural and contextual information acquired from the RGB image (Orthophoto) without using any Near Infrared (NIR) information and a Digital Surface Model (DSM) which was developed using Pix4D software, used as an ancillary data in the classification process in order to obtain the elevation information. The extraction of tree canopy and the buildings in a coastal urban environment has used to illustrate the analysis. The DSM was validated using ground control points observed by field measurements. The resultant urban vegetation map was validated with the digitized land use layer and an overall accuracy of 90.15% was obtained. This study indicates that low cost drones compared to the survey grade drones, also can provide high accurate and high resolution products suitable for many urban local area planning studies.Keywords: Photogrammetry, Object oriented classification, DSM, Orthophoto, Urban plannin

Sample size and robust marginal methods for cluster-randomized trials with censored event times

This is the peer reviewed version of the following article: Zhong Yujie, and Cook Richard J. (2015), Sample size and robust marginal methods for cluster-randomized trials with censored event times, Statist. Med., 34, pages 901–923. doi: 10.1002/sim.6395, which has been published in final form at http://dx.doi.org/10.1002/sim.6395. This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.In cluster-randomized trials, intervention effects are often formulated by specifying marginal models, fitting them under a working independence assumption, and using robust variance estimates to address the association in the responses within clusters. We develop sample size criteria within this framework, with analyses based on semiparametric Cox regression models fitted with event times subject to right censoring. At the design stage, copula models are specified to enable derivation of the asymptotic variance of estimators from a marginal Cox regression model and to compute the number of clusters necessary to satisfy power requirements. Simulation studies demonstrate the validity of the sample size formula in finite samples for a range of cluster sizes, censoring rates and degrees of within-cluster association among event times. The power and relative efficiency implications of copula misspecification is studied, as well as the effect of within-cluster dependence in the censoring times. Sample size criteria and other design issues are also addressed for the setting where the event status is only ascertained at periodic assessments and times are interval censored.Natural Sciences and Engineering Research Council of Canada (RGPIN 155849); Canadian Institutes for Health Research (FRN 13887); Canada Research Chair (Tier 1) – CIHR funded (950-226626

Novel Acumens into Biodegradation: Impact of Nanomaterials and Their Contribution

Biodegradation is the most viable alternative for numerous health and environmental issues associated with non-biodegradable materials. In recent years, there has been considerable interest in biodegradable nanomaterials due to their relative abundance, environmental benignity, low cost, easy use, and tunable properties. This chapter covers an overview of biodegradation, factors and challenges associated with biodegradation processes, involvement of nanotechnology and nanomaterials in biodegradation, and biodegradable nanomaterials. Furthermore, current chapter extensively discusses the most recent applications of biodegradable nanomaterials that have recently been explored in the areas of food packaging, energy, environmental remediation, and nanomedicine. Overall, this chapter provides a synopsis of how the involvement of nanotechnology would benefit the process of biodegradation

Fabrication of 6-gingerol, doxorubicin and alginate hydroxyapatite into a bio-compatible formulation: enhanced anti-proliferative effect on breast and liver cancer cells

Ample attention has been devoted to the construction of anti-cancer drug delivery systems with increased stability, and controlled and targeted delivery, minimizing toxic effects. In this study we have designed a magnetically attractive hydroxyapatite (m-HAP) based alginate polymer bound nanocarrier to perform targeted, controlled and pH sensitive drug release of 6-gingerol, doxorubicin, and their combination, preferably at low pH environments (pH 5.3). They have exhibited higher encapsulation efficiency which is in the range of 97.4–98.9% for both 6-gingerol and doxorubicin molecules whereas the co-loading has accounted for a value of 81.87 ± 0.32%. Cell proliferation assays, fluorescence imaging and flow cytometric analysis, demonstrated the remarkable time and dose responsive anti-proliferative effect of drug loaded nanoparticles on MCF-7 cells and HEpG2 cells compared with their neat counter parts. Also, these systems have exhibited significantly reduced toxic effects on non-targeted, non-cancerous cells in contrast to the excellent ability to selectively kill cancerous cells. This study has suggested that this HAP based system is a versatile carrier capable of loading various drug molecules, ultimately producing a profound anti-proliferative effect