Photocatalytic study of two-dimensional ZnO nanopellets in the decomposition of methylene blue

We report several significant photodecomposition rates of methylene blue (MB) obtained before and after the refluxing process of own-synthesized two-dimensional (2D) zinc oxide (ZnO) nanopellets. Each photodecomposition rate of MB was found highly dependent on the weight of photocatalyst. The existing photodecomposition rate has been successfully improved to a factor of 22.0 times through refluxing process in excessive pyridine where the surface capping ligand (oleic acid) is removed from the 2D ZnO nanopellets. On the other hand, the refluxed photocatalyst (0.04 g) in this study was found to exhibit excellent recyclability up to three cycles. Furthermore, X-ray powder diffraction spectrums for the refluxed photocatatalyst, respectively, before and after three cycles of photocatalytic reactions, has generated the same patterns showing that the photocatalyst is stable and feasible to be used as an efficient photocatalyst material. Hence, these 2D ZnO nanopellets would provide a new alternative route as a highly efficient photocatalyst for wastewater treatment

Pilot proof of concept clinical trials of Stochastic Targeted (STAR) glycemic control

ABSTRACT: INTRODUCTION: Tight glycemic control (TGC) has shown benefits but has been difficult to achieve consistently. STAR (Stochastic TARgeted) is a flexible, model-based TGC approach directly accounting for intra- and inter- patient variability with a stochastically derived maximum 5% risk of blood glucose (BG) /=3 days. Written informed consent was obtained for all patients, and approval was granted by the NZ Upper South A Regional Ethics Committee. RESULTS: A total of 402 measurements were taken over 660 hours (~14/day), because nurses showed a preference for 2-hourly measurements. Median [interquartile range, (IQR)] cohort BG was 5.9 mmol/L [5.2-6.8]. Overall, 63.2%, 75.9%, and 89.8% of measurements were in the 4.0-6.5, 4.0-7.0, and 4.0-8.0 mmol/L bands. There were no hypoglycemic events (BG < 2.2 mmol/L), and the minimum BG was 3.5 mmol/L with 4.5% < 4.4 mmol/L. Per patient, the median [IQR] hours of TGC was 92 h [29-113] using 53 [19-62] measurements (median, ~13/day). Median [IQR] results: BG, 5.9 mmol/L [5.8-6.3]; carbohydrate nutrition, 6.8 g/h [5.5-8.7] (~70% goal feed median); insulin, 2.5 U/h [0.1-5.1]. All patients achieved BG < 6.1 mmol/L. These results match or exceed SPRINT and clinical workload is reduced more than 20%. CONCLUSIONS: STAR TGC modulating insulin and nutrition inputs provided very tight control with minimal variability by managing intra- and inter- patient variability. Performance and safety exceed that of SPRINT, which reduced mortality and cost in the Christchurch ICU. The use of glucometers did not appear to impact the quality of TGC. Finally, clinical workload was self-managed and reduced 20% compared with SPRINT

Economic impact of 2015 transboundary haze on Singapore

We quantify and estimate the economic impact of the transboundary haze pollution in 2015 on Singapore following reliable quantitative methods and techniques in cost-benefit analysis. We include in the estimation both tangible and intangible costs associated to haze pollution. Specifically, in the estimation of the tangible costs of haze, the estimation includes (1) adverse impacts of haze on health, (2) loss in tourism, (3) loss in business as an indirect effect from loss of tourist receipts, (4) productivity loss due to restricted activity days and (5) cost of mitigation and adaptation by government agencies and households. For the estimation of the intangible costs, the value is derived from the contingent valuation study of Quah, Chia, and Tsiat-Siong (2018) which was conducted in 2018 to estimate Singapore residents’ willingness to pay for a pro-environment collaboration project that could effectively stop “slash and burn” practices and significantly reduce the annual haze pollution issue. The total cost of the 2015 haze episode on Singapore which lasted for 2 months is estimated at S$1.83 billion, amounting to 0.45$1.46 billion equivalent to 0.36 % of GDP while the total intangible cost stands at S$0.36 billion equivalent to 0.09 % of GDP. The findings have important implications for public policy.Ministry of Education (MOE)The authors gratefully acknowledge financial support from Singapore's Ministry of Education AcRF Tier 1 (RG148/16)

Marriage and fertility patterns in Singapore.

Our research explores the marriage and fertility patterns in Singapore; believed to be linked to the total fertility rates and patterns. We can shed light on sub-replacement level fertility rate by understanding marriage rates and making use of timely implementation of public campaigns to raise the low fertility rates

Interface Design and Human Factors Consideration for Model-Based Tight Glycemic Control in Critical Care

Introduction: Tight glycemic control (TGC) has shown benefits but has been difficult to implement. Model-based methods and computerized protocols offer the opportunity to improve TGC quality and compliance. This research presents an interface design to maximize compliance, minimize real and perceived clinical effort, and minimize error based on simple human factors and end user input. Method: The graphical user interface (GUI) design is presented by construction based on a series of simple, short design criteria based on fundamental human factors engineering and includes the use of user feedback and focus groups comprising nursing staff at Christchurch Hospital. The overall design maximizes ease of use and minimizes (unnecessary) interaction and use. It is coupled to a protocol that allows nurse staff to select measurement intervals and thus self-manage workload. Results: The overall GUI design is presented and requires only one data entry point per intervention cycle. The design and main interface are heavily focused on the nurse end users who are the predominant users, while additional detailed and longitudinal data, which are of interest to doctors guiding overall patient care, are available via tabs. This dichotomy of needs and interests based on the end user’s immediate focus and goals shows how interfaces must adapt to offer different information to multiple types of users. Conclusions: The interface is designed to minimize real and perceived clinical effort, and ongoing pilot trials have reported high levels of acceptance. The overall design principles, approach, and testing methods are based on fundamental human factors principles designed to reduce user effort and error and are readily generalizable

Data Entry Errors and Design for Model-Based Tight Glycemic Control in Critical Care

Introduction: Tight glycemic control (TGC) has shown benefits but has been difficult to achieve consistently. Model-based methods and computerized protocols offer the opportunity to improve TGC quality but require human data entry, particularly of blood glucose (BG) values, which can be significantly prone to error. This study presents the design and optimization of data entry methods to minimize error for a computerized and model-based TGC method prior to pilot clinical trials. Method: To minimize data entry error, two tests were carried out to optimize a method with errors less than the 5%-plus reported in other studies. Four initial methods were tested on 40 subjects in random order, and the best two were tested more rigorously on 34 subjects. The tests measured entry speed and accuracy. Errors were reported as corrected and uncorrected errors, with the sum comprising a total error rate. The first set of tests used randomly selected values, while the second set used the same values for all subjects to allow comparisons across users and direct assessment of the magnitude of errors. These research tests were approved by the University of Canterbury Ethics Committee. Results: The final data entry method tested reduced errors to less than 1–2%, a 60–80% reduction from reported values. The magnitude of errors was clinically significant and was typically by 10.0 mmol/liter or an order of magnitude but only for extreme values of BG 15.0–20.0 mmol/liter, both of which could be easily corrected with automated checking of extreme values for safety. Conclusions: The data entry method selected significantly reduced data entry errors in the limited design tests presented, and is in use on a clinical pilot TGC study. The overall approach and testing methods are easily performed and generalizable to other applications and protocols

Using the Johns Hopkins ACG Case-Mix System for population segmentation in a hospital-based adult patient population in Singapore

Objective Population health management involves risk characterisation and patient segmentation. Almost all population segmentation tools require comprehensive health information spanning the full care continuum. We assessed the utility of applying the ACG System as a population risk segmentation tool using only hospital data.Design Retrospective cohort study.Setting Tertiary hospital in central Singapore.Participants 100 000 randomly selected adult patients from 1 January to 31 December 2017.Intervention Hospital encounters, diagnoses codes and medications prescribed to the participants were used as input data to the ACG System.Primary and Secondary Outcome Measures Hospital costs, admission episodes and mortality of these patients in the subsequent year (2018) were used to assess the utility of ACG System outputs such as resource utilisation bands (RUBs) in stratifying patients and identifying high hospital care users.Results Patients placed in higher RUBs had higher prospective (2018) healthcare costs, and were more likely to have healthcare costs in the top five percentile, to have three or more hospital admissions, and to die in the subsequent year. A combination of RUBs and ACG System generated rank probability of high healthcare costs, age and gender that had good discriminatory ability for all three outcomes, with area under the receiver-operator characteristic curve (AUC) values of 0.827, 0.889 and 0.876, respectively. Application of machine learning methods improved AUCs marginally by about 0.02 in predicting the top five percentile of healthcare costs and death in the subsequent year.Conclusion A population stratification and risk prediction tool can be used to appropriately segment populations in a hospital patient population even with incomplete clinical data

Safety and Performance of Stochastic Targeted (STAR) Glycemic Control of Insulin and Nutrition - First Pilot Results

peer reviewe

Nephrinuria associates with multiple renal traits in type 2 diabetes

10.1093/ndt/gfq738Nephrology Dialysis Transplantation2682508-2514NDTR