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The annual assessment of Family Planning (FP) indicators, such as the modern contraceptive prevalence rate (mCPR), is a key component of monitoring and evaluating goals of global FP programs and initiatives. To that end, the Family Planning Estimation Model (FPEM) was developed with the aim of producing survey-informed estimates and projections of mCPR and other key FP indictors over time. With large-scale surveys being carried out on average every 3–5 years, data gaps since the most recent survey often exceed one year. As a result, survey-based estimates for the current year from FPEM are often based on projections that carry a larger uncertainty than data informed estimates. In order to bridge recent data gaps we consider the use of a measure, termed Estimated Modern Use (EMU), which has been derived from routinely collected family planning service statistics. However, EMU data come with known limitations, namely measurement errors which result in biases and additional variation with respect to survey-based estimates of mCPR. Here we present a data model for the incorporation of EMU data into FPEM, which accounts for these limitations. Based on known biases, we assume that only changes in EMU can inform FPEM estimates, while also taking inherent variation into account. The addition of this EMU data model to FPEM allows us to provide a secondary data source for informing and reducing uncertainty in current estimates of mCPR. We present model validations using a survey-only model as a baseline comparison and we illustrate the impact of including the EMU data model in FPEM. Results show that the inclusion of EMU data can change point-estimates of mCPR by up to 6.7 percentage points compared to using surveys only. Observed reductions in uncertainty were modest, with the width of uncertainty intervals being reduced by up to 2.7 percentage points.

The annual assessment of Family Planning (FP) indicators, such as the modern contraceptive prevalence rate (mCPR), is a key component of monitoring and evaluating goals of global FP programs and initiatives. To that end, the Family Planning Estimation Model (FPEM) was developed with the aim of producing survey-informed estimates and projections of mCPR and other key FP indictors over time. With large-scale surveys being carried out on average every 3–5 years, data gaps since the most recent survey often exceed one year. As a result, survey-based estimates for the current year from FPEM are often based on projections that carry a larger uncertainty than data informed estimates. In order to bridge recent data gaps we consider the use of a measure, termed Estimated Modern Use (EMU), which has been derived from routinely collected family planning service statistics. However, EMU data come with known limitations, namely measurement errors which result in biases and additional variation with respect to survey-based estimates of mCPR. Here we present a data model for the incorporation of EMU data into FPEM, which accounts for these limitations. Based on known biases, we assume that only changes in EMU can inform FPEM estimates, while also taking inherent variation into account. The addition of this EMU data model to FPEM allows us to provide a secondary data source for informing and reducing uncertainty in current estimates of mCPR. We present model validations using a survey-only model as a baseline comparison and we illustrate the impact of including the EMU data model in FPEM. Results show that the inclusion of EMU data can change point-estimates of mCPR by up to 6.7 percentage points compared to using surveys only. Observed reductions in uncertainty were modest, with the width of uncertainty intervals being reduced by up to 2.7 percentage points.

Orthodox tea is one of the high-value agriculture commodities having enormous potential of export to international market. Nepal offers suitable climate, soil, and topography for profitable production of the orthodox tea having exceptional flavor, aroma, and taste. The study was designed to analyze the production trend, annual growth rate, export and import, and prospects of the Nepali orthodox tea. Findings showed that production of tea is in increasing trend with an average annual growth rate of 9.55%. Despite possessing ample opportunity in domestic and international markets, yet country only produces little amount of orthodox tea. Further, 90% of the total produced orthodox tea was imported primarily to India which has been one of the factors for not being able to receive optimum premium as compared to other tea exporting countries like China and India. Thus to revitalize tea subsector, it is recommended to focus on improving tea productivity with proper mechanization, establishing tea processing industries, easy and reliable certification, price intervention, market recognition, and enhancing diplomatic relations for easy market accessibility and duty-free trade.

This dissertation is based on a novel experimental discovery of what we have labeled as a “ghost frequency comb (GFC),” observed from the measurements of nonlocal correlations with a laser beam. Unlike a conventional frequency comb, the laser beam used in this work does not consist of a pulse train—instead it is in a continuous-wave (cw) operation. In addition, the laser beam is in a multi-longitudinal-mode coherent state, far from a thermal state. The intensity fluctuations of the laser beam are found to be correlated within periodically spaced, precise, narrow time windows, giving periodic sharp correlation peaks. However, as long as the relative delay of the correlation falls into the region between these peaks, the intensity fluctuations of the laser beam remain uncorrelated. These experimental observations lead one to speculate whether there is a light source with such a peculiar statistical behavior, and beg two important questions: (1) How could a cw laser beam, approximated to be in coherent state, produce nontrivial intensity correlations like thermal state? (2) How could a cw laser generate a frequency comb? It is not surprising that a mode-locked laser can generate a train of sharp pulses as frequency comb, but the observation of a frequency comb from a cw laser beam would be unexpected. This dissertation provides a conclusive answer to these fundamentally interesting questions: the GFC is the result of two-photon interference—a pair of distinguishable groups of indistinguishable photons interfering with the pair itself. It is the nonlocal two-photon beats that produce the comb-like intensity fluctuation correlation. Besides its fundamental importance, this dissertation also explores useful applications of the GFC in precision spectroscopy. Nontrivial correlations of light have been a subject of debate since the development of intensity interferometry by Hanbury Brown and Twiss (HBT) in the 1950s. Conventional theory suggests that the HBT correlation of distant stars is the intrinsic statistical property of thermal state. Questions such as “Are the photons ‘bunched’ or ‘anti-bunched’ at the light source?” have been raised for decades. This dissertation also attempts to address this fundamental issue surrounding the origin of second-order correlation. In addition to the work with multi-cavity-mode cw laser beam mentioned above, a study of the second-order correlation of a multi-color or multi-frequency thermal light source in interferometric settings is reported. It is concluded that, like the GFC, the second-order correlation in multi-frequency thermal light also results from two-photon beats. Thus, this dissertation provides solid experimental evidence and theoretical analysis for exploring the nonlocal quantum interference as the origin of nontrivial correlations of light in general. The findings presented here should further corroborate the view that the two-photon correlation picture provides an accurate result in second-order coherence measurements.

We report a proof-of-principle experimental demonstration of a turbulence-resistant quantum Lidar system. As a key technology for sensing and ranging, Lidar has drawn considerable attention for a study from quantum perspective, in search of proven advantages complementary to the capabilities of conventional Lidar technologies. Environmental factors such as strong atmospheric turbulence can have detrimental effects on the performance of these systems. We demonstrate the possibility of turbulence-resistant operation of a quantum Lidar system via two-photon interference of entangled photon pairs. Additionally, the reported quantum Lidar also demonstrates the expected noise resistance. This study suggests a potential high precision timing-positioning technology operable under turbulence and noise.

Some 40,000 people poured into Kathmandu, capital of Nepal, Friday in the latest protest of...

About 100 Mt.

The primary objective of National NCD monitoring survey (NNMS) was to generate national-level estimates of key NCD indicators identified in the national NCD monitoring framework. This paper describes survey study protocol and prevalence of risk factors among adults (18-69 years). NNMS was a national level cross-sectional survey conducted during 2017-18. The estimated sample size was 12,000 households from 600 primary sampling units. One adult (18-69 years) per household was selected using the World Health Organization-KISH grid. The study tools were adapted from WHO-STEPwise approach to NCD risk factor surveillance, IDSP-NCD risk factor survey and WHO-Global adult tobacco survey. Total of 8/10 indicators of adult NCD risk factors according to national NCD disease monitoring framework was studied. This survey for the first time estimated dietary intake of salt intake of population at a national level from spot urine samples. Total of 11139 households and 10659 adults completed the survey. Prevalence of tobacco and alcohol use was 32.8% (95% CI: 30.8-35.0) and 15.9% (95% CI: 14.2-17.7) respectively. More than one-third adults were physically inactive [41.3% (95% CI: 39.4-43.3)], majority [98.4% (95% CI: 97.8-98.8)] consumed less than 5 servings of fruits and / or vegetables per day and mean salt intake was 8 g/day (95% CI: 7.8-8.2). Proportion with raised blood pressure and raised blood glucose were 28.5% (95% CI: 27.0-30.1) and 9.3% (95% CI: 8.3-10.5) respectively. 12.8% (95% CI: 11.2-14.5) of adults (40-69 years) had ten-year CVD risk of ≥30% or with existing CVD. NNMS was the first comprehensive national survey providing relevant data to assess India's progress towards targets in National NCD monitoring framework and NCD Action Plan. Established methodology and findings from survey would contribute to plan future state-based surveys and also frame policies for prevention and control of NCDs.