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2H-molybdenum disulfide (2H-MoS

Climate change is a vital environmental issue that significantly affects rice productivity. Rice paddy fields are one of the greatest anthropogenic sources of methane (CH4) and nitrous oxide (N2O) emissions. To evaluate the combined effects of manure amendment and water management on GHG emissions, grain yield and water productivity per rice yield in a lowland rice field with a sandy clay loam soil in Myanmar, this study was conducted with a split‐plot design. Two water management practices (continuous flooding [CF] and alternate wetting and drying [AWD]) and four levels of cow dung manure (0, 2.5, 5.0 and 7.5 t ha−1) were applied with three replications in the dry (February–May) and wet (July–October) seasons in 2017. In the dry season, significantly higher cumulative methane (CH4) emissions (50.5%) were recorded in CF than in AWD, while cumulative nitrous oxide (N2O) emissions were 70% higher in AWD than in CF, although the difference was not significant. Manure application showed no effect on CH4 and N2O emissions compared with the no‐manure control, irrespective of application level. In the wet season, significantly higher cumulative CH4 emissions (65.2%) were again recorded in CF than in AWD; however, the cumulative N2O emissions were similar between CF and AWD. Methane and N2O emissions in the wet season were 65.8 and 35.8% higher, respectively, than those in the dry season. In both seasons, higher grain yields (1.8% in dry and 7.6% in wet) and higher water productivity (130% in dry and 31% in wet) were recorded in AWD than in CF. Increased grain yields (18.9% in dry and 7.7% in wet) and water productivity (25.5% in dry and 15.8% in wet) were recorded in the manure treatments compared to those in the no‐manure treatment. This study presents quantitative data on how manure amendment and water management affected GHG emissions in a paddy field in Myanmar. © 2020 The Authors. Greenhouse Gases: Science and Technology published by Society of Chemical Industry and John Wiley & Sons, Ltd.

Background: Unmet need for family planning in Myanmar (estimated 15.8% by the UN in 2017) is relatively high compared to other South East Asia countries. Moreover, Social Institutions and Gender Index in Myanmar is very high and cultural norms promote childbearing. Thus, this paper was conducted to examine role of intra-household gendered dominance (IHGD) in unmet need for family planning across Myanmar to set more effective intervention for family planning. Methods: The study utilized secondary data from 2015–2016 MDHS. Total 7,652 married women in reproductive age (MWRA) were included and 16% of them had unmet need for family planning. Binary Logistic Regression Analysis was conducted to examine the association of each explanatory variables with outcomes variables. Results: IHGD factors which are decision on women’s health and women’s attitude towards wife beating are significantly associated with unmet need. Moreover, socio-economic factors which are place of residence and women’s education level have significant impact on unmet need as well. Conclusion: Based on the findings of this study, the government of Myanmar should address dominance of social and cultural gender norms by conducting gender equality awareness campaign and family planning program should target to reach rural and uneducated women.

The inclusion of time based queries in video indexing application is enables by the recognition of time and date stamps in CCTV video. In this paper, we propose the system for reconstructing the path of the object in surveillance cameras based on time and date optical character recognition system. Since there is no boundary in region for time and date, Discrete Cosine Transform DCT method is applied in order to locate the region area. After the region for time and date is located, it is segmented and then features for the symbols of the time and date are extracted. Back propagation neural network is used for recognition of the features and then stores the result in the database. By using the resulted database, the system reconstructs the path for the object based on time. The proposed system will be implemented in MATLAB. Pyae Phyo Thu | Mie Mie Tin | Ei Phyu Win | Cho Thet Mon "Reconstructing the Path of the Object based on Time and Date OCR in Surveillance System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27981.pdf

The study is focused on impact of manure application, rice varieties and water management on greenhouse gas (GHG) emissions from paddy rice soil in pot experiment. The objectives of this study were a) to assess the effect of different types of manure amendments and rice varieties on greenhouse gas emissions and b) to determine the optimum manure application rate to increase rice yield while mitigating GHG emissions under alternate wetting and drying irrigation in paddy rice production. The first pot experiment was conducted at the Department of Agronomy, Yezin Agricultural University, Myanmar, in the wet season from June to October 2016. Two different organic manures (compost and cow dung) and control (no manure), and two rice varieties; Manawthukha (135 days) and IR-50 (115 days), were tested. The results showed that cumulative CH4 emission from Manawthukha (1.084 g CH4 kg-1 soil) was significantly higher than that from IR-50 (0.683 g CH4 kg-1 soil) (P2O kg-1 soil) than for Manawthukha (2.585 mg N2O kg-1 soil). However, IR-50 showed less global warming potential (GWP) than Manawthukha (P4 and N2O emissions were observed in the cow dung manure treatment (0.808 g CH4 kg-1 soil, 2.135 mg N2O kg-1 soil) compared to those of the control and compost. To determine the effect of water management and organic manures on greenhouse gas emissions, second pot experiments were conducted in Madaya township during the dry and wet seasons from February to October 2017. Two water management practices {continuous flooding (CF) and alternate wetting and drying (AWD)} and four cow dung manure rates {(1) 0 (2) 2.5 t ha-1 (3) 5 t ha-1 (4) 7.5 t ha-1} were tested. The different cow dung manure rates did not significantly affect grain yield or greenhouse gas emissions in this experiment. Across the manure treatments, AWD irrigation significantly reduced CH4 emissions by 70% during the dry season and 66% during the wet season. Although a relative increase in N2O emissions under AWD was observed in both rice seasons, the global warming potential was significantly reduced in AWD compared to CF in both seasons (P4. Therefore, AWD is the effective mitigation practice for reducing GWP without compromising rice yield while manure amendment had no significant effect on GHG emission from paddy rice field. Besides, AWD saved water about 10% in dry season and 19% in wet season.

The development of high-performance electrochemical energy storage device is important for addressing energy shortage issues. As one of the next-generation energy storage devices, supercapacitor (SCs) material and their composite designs have gained increased attention in recent years. Herein, the CNT@MoS2/PDDA/PMo12 nanocomposite, was assembled via PDDA-assisted (PDDA is poly(dimethyldiallylammonium chloride)) synthesis strategy. The positively charged polyelectrolyte can interact with two negatively charged components, phosphomolybdic acid (PMo12) and CNT@MoS2 (CNT referred to multi-walled carbon nanotubes, and MoS2 referred to molybdenum disulfide) through electrostatic interaction. PMo12 has uniformly attracted on the surface of the ultrathin MoS2 nanosheets-modified CNT, which endowed the nanocomposite with a fast electron transport efficiency, enrich charge storage and multi-electron transfer capabilities. As a symmetric supercapacitor system, this composite exhibited a high rate specific capacitance of 110 F g−1 at 0.5 A g−1 and an energy density of 15.27 W h kg−1 at a power density of 152 W kg−1. Moreover, an excellent cycle performance with 89% specific capacitance after 10000 charge-discharge cycles was obtained.

Modern technologies are being used in agriculture such as quality control and classification of grains that are very important for more productive and sustainable production. Classification of the similar small rice grains can be also made with the help of image processing techniques. This paper studies different characteristics of Myanmar rice grains and their varieties. The classification of various varieties of rice grains is made by using image processing techniques and algorithms. Five types of rice grains in Myanmar such as Paw San Hmwe, Lone Thwe Hmwe, Ayeyarmin, Kauk-Nyinn-Thwe and Kauk-Nyinn-Pu are considered for present study in classifying the rice seeds and quality. Firstly, each grain image is preprocessed to enhance the grain image and then segmented by using the edge detection methods such as threshold method. Five morphological features are extracted from each grain image. This system emphasizes on the development a computer vision-based system that is combined with proper heuristic algorithms for automatic classification of Myanmar’s rice grain samples. This research is very significant in Myanmar because Myanmar is great producer of different qualities of rice grains and therefore the study and basic implementation would greatly help the researchers, agriculturist and other stakeholders of agricultural growth.