Poverty among households living in slum area of Hlaing Tharyar Township, Yangon City, Myanmar

Background: Slums can be regarded as physical manifestations of urban poverty. Although the world has made dramatic improvement in reducing poverty since 1990, poverty still persists at an unacceptable level. Although current situations highlights the importance of slum areas to be given priority in poverty alleviation, there are limited data on poverty level among people living in urban slums of Myanmar.Methods: A cross-sectional study was conducted among households living in slum areas of Hlaing Tharyar Township, Yangon City, Myanmar during 2016. Multi-staged systematic random sampling and face-to-face interview were applied in selecting the samples and collecting the data, respectively. The new global poverty line (1.9 USD per person per day) was used as a threshold in determining the poverty. Chi-squared test and multivariate logistic regression analysis were utilized in data analysis.Results: Altogether 254 participants were recruited after getting informed consent. The occurrence of poverty among households was 54.3% (95% CI: 48.2%, 60.5%). Head counts of poverty among study population was 58.8%. The education status of household’s head, size of household and the presence of less than 15 years old children in the household were detected as significant determinants of being poor household.Conclusions: Poverty among households living in slum area of Hlaing Tharyar Township, Yangon City was high. Measures to alleviate poverty in urban slums should be intensified. Education level of household’s heads should be improved. Family planning or birth spacing programme should also be strengthened, especially in urban slums.

An overview of chickpea breeding programs in Myanmar

Chickpea is an important legume in Myanmar, not only for local consumption but also for export earnings. Major chickpeaproducing area is the central dry zone which contributes 96% of the chickpea production. Kabuli chickpea is mainly grown for export, while desi chickpea is for local consumption. Eight improved varieties of chickpea (5 desi and 3 kabuli) have been released in Myanmar. The adoption of improved varieties and improved crop production practices has led to remarkable increase in chickpea yields and production

Agency in Transport Service: Implications of Traveller Mode Choice Objective and Latent Attributes Using Random Parameter Logit Model

Abstract: This paper explains how principal-agent theory (PAT) can be used as an analytical tool to understand the traveller-Transport for NSW (TfNSW) relationship and minimise the agency problem in the relationship by examining traveller preferences for mode choices. The paper emphasises latent variables (LVs) and traditional objective attributes (TOAs) together during the choice process within the agency relationship, as a method by which the utility of the principal (traveller) can be maximised and evaluated using a discrete choice experiment, i.e. random parameter logit (RPL) model. The probability of car use is significantly higher than public transport, which indicates that an agency problem exists in the relationship and incorporating traveller preferences in the transport projects may minimise this problem. Citation: Anwar, A.H.M., Tieu, K., Gibson, P., Win, K.T. & Berryman, M.J. (2014). Agency in Transport Service: Implications of Traveller Mode Choice Objective and Latent Attributes Using Ransom Parameter Logit Model. In: Campbell P. and Perez P. (Eds), Proceedings of the International Symposium of Next Generation Infrastructure, 1-4 October 2013, SMART Infrastructure Facility, University of Wollongong, Australia

Association between antimicrobial stewardship programs and antibiotic use globally: a systematic review and meta-analysis

IMPORTANCE: Antimicrobial resistance continues to spread rapidly at a global scale. Little evidence exists on the association of antimicrobial stewardship programs (ASPs) with the consumption of antibiotics across health care and income settings. OBJECTIVE: To synthesize current evidence regarding the association between antimicrobial stewardship programs and the consumption of antibiotics globally. DATA SOURCES: PubMed, Web of Science, and Scopus databases were searched from August 1, 2010, to Aug 1, 2020. Additional studies from the bibliography sections of previous systematic reviews were included. STUDY SELECTION: Original studies of the association of ASPs with antimicrobial consumption across health care and income settings. Animal and environmental studies were excluded. DATA EXTRACTION AND SYNTHESIS: Following the Preferred Reporting Items in Systematic Reviews and Meta-Analyses guideline, the pooled association of targeted ASPs with antimicrobial consumption was measured using multilevel random-effects models. The Effective Public Health Practice Project quality assessment tool was used to assess study quality. MAIN OUTCOMES AND MEASURES: The main outcome measures were proportion of patients receiving an antibiotic prescription and defined daily doses per 100 patient-days. RESULTS: Overall, 52 studies (with 1 794 889 participants) measured the association between ASPs and antimicrobial consumption and were included, with 40 studies conducted in high-income countries and 12 in low- and middle-income countries (LMICs). ASPs were associated with a 10% (95% CI, 4%-15%) reduction in antibiotic prescriptions and a 28% reduction in antibiotic consumption (rate ratio, 0.72; 95% CI, 0.56-0.92). ASPs were also associated with a 21% (95% CI, 5%-36%) reduction in antibiotic consumption in pediatric hospitals and a 28% reduction in World Health Organization watch groups antibiotics (rate ratio, 0.72; 95% CI, 0.56-0.92). CONCLUSIONS AND RELEVANCE: In this systematic review and meta-analysis, ASPs appeared to be effective in reducing antibiotic consumption in both hospital and nonhospital settings. Impact assessment of ASPs in resource-limited settings remains scarce; further research is needed on how to best achieve reductions in antibiotic use in LMICs

Performanse višeimpulsno-pozicijske amplitudne modulacije za TH IR-UWB komunikacijske sustave

The multi pulse position amplitude modulation scheme for time-hopping multiple access impulse radio ultrawideband communication systems has been presented in this paper. Multi pulse position amplitude modulation is a hybrid modulation technique, which combines multi pulse position modulation and pulse amplitude modulation. It is shown that multi pulse position amplitude modulation significantly outperforms pulse position modulation with respect to bandwidth efficiency. The multi pulse position amplitude modulation error probability over IEEE 802.15.3a multipath fading channels in multiuser environment is derived. The system analysis shows that the proper selection of modulation parameters can improve the system performance at the cost of hardware complexity (and vice versa).U ovom je radu predstavljena višeimpulsno-pozicijska amplitudna modulacijska shema za impulsne ultraširokopojasne radiokomunikacijske sustave, zasnovana na višekorisničkom pristupu s vremenskim skakanjem. Višeimpulsno-pozicijska amplitudna modulacija je hibridni modulacijski postupak, koji je kombinacija višeimpulsno-pozicijske modulacije i impulsno-amplitudne modulacije. Pokazano je da višeimpulsno-pozicijska amplitudna modulacija značajno nadmašuje impulsno-pozicijsku modulaciju u pogledu pojasne učinkovitosti. Izvedena je vjerojatnost pogreške višeimpulsno-pozicijske amplitudne modulacije u kanalu IEEE 802.15.3a s višestaznim rasprostiranjem i iščezavanjem signala u višekorisničkom okruženju. Analiza sustava pokazuje da odgovaraju ći izbor parametara modulacije može poboljšati performanse sustava uz povećanje složenosti sklopovlja (i obrnuto)

The complete conformal spectrum of a sl(2∣1)sl(2|1) invariant network model and logarithmic corrections

We investigate the low temperature asymptotics and the finite size spectrum of a class of Temperley-Lieb models. As reference system we use the spin-1/2 Heisenberg chain with anisotropy parameter $\Delta$ and twisted boundary conditions. Special emphasis is placed on the study of logarithmic corrections appearing in the case of $\Delta=1/2$ in the bulk susceptibility data and in the low-energy spectrum yielding the conformal dimensions. For the $sl(2|1)$ invariant 3-state representation of the Temperley-Lieb algebra with $\Delta=1/2$ we give the complete set of scaling dimensions which show huge degeneracies.Comment: 18 pages, 5 figure

Risk factor-based screening compared to universal screening for gestational diabetes mellitus in marginalized Burman and Karen populations on the Thailand-Myanmar border: an observational cohort

Background: Gestational diabetes mellitus (GDM) contributes significantly to maternal and neonatal morbidity, but data from marginalized populations remains scarce. This study aims to compare risk-factor-based screening to universal testing for GDM among migrants along the Thailand-Myanmar border. Methods: From the prospective cohort (September 2016, February 2019), 374 healthy pregnant women completed a 75g oral glucose tolerance test (OGTT) at 24-32 weeks gestation. Fasting, one hour and two hour cut-offs were based on Hyperglycaemia and Adverse Pregnancy Outcomes (HAPO trial) criteria and cases were treated. The sensitivity and specificity of risk-factor-based screening criteria was calculated using OGTT as the gold standard. Risk factors included at least one positive finding among 10 criteria, e.g., obesity (body mass index (BMI) >/=27.5kg/m (2)), 1 (st) degree relative with diabetes etc. Adverse maternal and neonatal outcomes were compared by GDM status, and risk factors for GDM were explored. Results: GDM prevalence was 13.4% (50/374) (95% CI: 10.3-17.2). Risk-factors alone correctly identified 74.0% (37/50) OGTT positive cases: sensitivity 74.0% (59.7-85.4) and specificity 27.8% (3.0-33.0). Burman women accounted for 29.1% of the cohort population, but 38.0% of GDM cases. Percentiles for birthweight (p=0.004), head circumference (p=0.005), and weight-length ratio (p=0.010) were higher in newborns of GDM mothers compared with non-GDM, yet 21.7% (75/346) of newborns in the cohort were small-for-gestational age. In Burman women, overweight/obese BMI was associated with a significantly increased adjusted odds ratio 5.03 (95% CI: 1.43-17.64) for GDM compared to normal weight, whereas underweight and overweight/obese in Karen women were both associated with similarly elevated adjusted odds, approximately 2.4-fold (non-significant) for GDM. GDM diagnosis by OGTT was highest prior to peak rainfall. Conclusions: Risk-factor-based screening was not sufficiently sensitive or specific to be useful to diagnose GDM in this setting among a cohort of low-risk pregnant women. A two-step universal screening program has thus been implemented

Areas of normal pulmonary parenchyma on HRCT exhibit increased FDG PET signal in IPF patients

Purpose: Patients with idiopathic pulmonary fibrosis (IPF) show increased PET signal at sites of morphological abnormality on high-resolution computed tomography (HRCT). The purpose of this investigation was to investigate the PET signal at sites of normal-appearing lung on HRCT in IPF. Methods: Consecutive IPF patients (22 men, 3 women) were prospectively recruited. The patients underwent 18F-FDG PET/HRCT. The pulmonary imaging findings in the IPF patients were compared to the findings in a control population. Pulmonary uptake of 18F-FDG (mean SUV) was quantified at sites of morphologically normal parenchyma on HRCT. SUVs were also corrected for tissue fraction (TF). The mean SUV in IPF patients was compared with that in 25 controls (patients with lymphoma in remission or suspected paraneoplastic syndrome with normal PET/CT appearances). Results: The pulmonary SUV (mean ± SD) uncorrected for TF in the controls was 0.48 ± 0.14 and 0.78 ± 0.24 taken from normal lung regions in IPF patients (p < 0.001). The TF-corrected mean SUV in the controls was 2.24 ± 0.29 and 3.24 ± 0.84 in IPF patients (p < 0.001). Conclusion: IPF patients have increased pulmonary uptake of 18F-FDG on PET in areas of lung with a normal morphological appearance on HRCT. This may have implications for determining disease mechanisms and treatment monitoring. © 2013 The Author(s)

Characterizing and mapping cropping patterns in a complex agro-ecosystem: An iterative participatory mapping procedure using machine learning algorithms and MODIS vegetation indices

Accurate and up-to-date spatial agricultural information is essential for applications including agro-environmental assessment, crop management, and appropriate targeting of agricultural technologies. There is growing research interest in spatial analysis of agricultural ecosystems applying satellite remote sensing technologies. However, usability of information generated from many of remotely sensed data is often constrained by accuracy problems. This is of particular concern in mapping complex agro-ecosystems in countries where small farm holdings are dominated by diverse crop types. This study is a contribution to the ongoing efforts towards overcoming accuracy challenges faced in remote sensing of agricultural ecosystems. We applied time-series analysis of vegetation indices (Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI)) derived from the Moderate Resolution Imaging Spectrometer (MODIS) sensor to detect seasonal patterns of irrigated and rainfed cropping patterns in five townships in the Central Dry Zone of Myanmar, which is an important agricultural region of the country has been poorly mapped with respect to cropping practices. To improve mapping accuracy and map legend completeness, we implemented a combination of (i) an iterative participatory approach to field data collection and classification, (ii) the identification of appropriate size and types of predictor variables (VIs), and (iii) evaluation of the suitability of three Machine Learning algorithms: Support Vector Machine (SVM), Random Forest (RF), and C5.0 algorithms under varying training sample sizes. Through these procedures, we were able to progressively improve accuracy and achieve maximum overall accuracy of 95% When a small sized training dataset was used, accuracy achieved by RF was significantly higher compared to SVM and C5.0 (P < 0.01), but as sample size increased, accuracy differences among the three machine learning algorithms diminished. Accuracy achieved by use of NDVI was consistently better than that of EVI (P < 0.01). The maximum overall accuracy was achieved using RF and 8-days NDVI composites for three years of remote sensing data. In conclusion, our findings highlight the important role of participatory classification, especially in areas where cropping systems are highly diverse and differ over space and time. We also show that the choice of classifiers and size of predictor variables are essential and complementary to the participatory mapping approach in achieving desired accuracy of cropping pattern mapping in areas where other sources of spatial information are scarce