The USD/MMK exchange rate was unchanged at 2,093.7000 on July 1, 2025. Over the past month, the Myanmar Kyat has remained flat, and is unchangedover the last 12 months. Myanmar Kyat - values, historical data, forecasts and news - updated on July of 2025.

Lecture on Youtube: https://youtu.be/Z4cVF1OtcsQ Documentation: https://pypi.org/project/pymannkendall/

Prices for SGDMMK Singapore Dollar Myanmar Kyat including live quotes, historical charts and news. SGDMMK Singapore Dollar Myanmar Kyat was last updated by Trading Economics this July 2 of 2025.

Nilai Tukar Terhadap USD Myanmar dilaporkan sebesar 2,100.000 USD/MMK pada 2023-05. Angka ini tetap dibanding sebelumnya yaitu 2,100.000 USD/MMK untuk 2023-04. Data Nilai Tukar Terhadap USD Myanmar diperbarui bulanan, dengan rata-rata 1,349.118 USD/MMK dari 2012-04 sampai 2023-05, dengan 134 observasi. Data ini mencapai angka tertinggi sebesar 2,100.000 USD/MMK pada 2023-05 dan rekor terendah sebesar 821.615 USD/MMK pada 2012-04. Data Nilai Tukar Terhadap USD Myanmar tetap berstatus aktif di CEIC dan dilaporkan oleh CEIC Data. Data dikategorikan dalam Global Economic Monitor World Trend Plus – Table: Exchange Rate against USD: Period Avg: Monthly.

Myanmars Wechselkurs gegenüber dem USD belief sich im 2023-05 auf 2,100.000 USD/MMK. Dies stellt keine Veränderung im Vergleich zu den vorherigen Zahlen von 2,100.000 USD/MMK für 2023-04 dar. Myanmars Wechselkurs gegenüber dem USD werden monatlich aktualisiert, mit einem Durchschnitt von 1,349.118 USD/MMK von 2012-04 bis 2023-05, mit 134 Beobachtungen. Die Daten erreichten ein Allzeithoch in Höhe von 2,100.000 USD/MMK im 2023-05 und ein Rekordtief in Höhe von 821.615 USD/MMK im 2012-04. Myanmars Wechselkurs gegenüber dem USD Daten behalten den Aktiv-Status in CEIC und werden von CEIC Data gemeldet. Die Daten werden unter World Trend Pluss Global Economic Monitor – Table: Exchange Rate against USD: Period Avg: Monthly kategorisiert.

Results of the Sen’s slope estimator and MKz test for the monthly, seasonal and annual rainfall at the selected stations.

R(lag-1) values for serial correlation test (limits are 0.28 and -0.28).

The Middle East and Africa Orexin Receptor MK 8133 market will be USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 4.7% from 2024 to 2031. The market is foreseen to reach USD xx million by 2031, owing to the growing demand in pediatric and geriatric populations.

Global Dynamic Climate Chambers market size 2025 was XX Million. Dynamic Climate Chambers Industry compound annual growth rate (CAGR) will be XX% from 2025 till 2033.

미얀마의 환율 (USD)은 2023-05에 2,100.000 USD/MMK로 보고 되었습니다. 이는 2023-04에 2,100.000 USD/MMK라는 이전 수치에 비 해큰 차이 없는 기록입니다.미얀마의 환율 (USD) 데이터는 월간 간행물마다 업데이트 되며,134개의 관측으로 2012-04부터 2023-05사이에 평균 1,349.118 USD/MMK입니다. 이 데이터는2023-05에 2,100.000 USD/MMK라는사상 최고치를, 2012-04에 821.615 USD/MMK라는 최저치를 기록했습니다. 미얀마’의 환율 (USD) 데이터는 CEIC에 활성 상태로 남아 있으며CEIC Data에 의해 보고되는 정보입니다. 본 데이터는 World Trend Plus의 Global Economic Monitor - Table: Exchange Rate against USD: Period Avg: Monthly하에 분류 됩니다.

[Keywords] Market include United States Steel (U.S.), ThyssenKrupp AG (Germany), Salzgitter AG (Germany), SSAB AB (Sweden), ArcelorMittal S.A. (Luxembourg)

The M-K trend test for the SPEI.

North America Orexin Receptor MK 8133 market size will be USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 3.2% from 2024 to 2031. North America has emerged as a prominent participant, and its sales revenue is estimated to reach USD XX Million by 2031. This growth is mainly attributed to the region's market, which is driven by the prevalence of comorbid conditions that affect sleep patterns, such as obesity and cardiovascular diseases.

Latin America's Orexin Receptor MK 8133 market will be USD XX million in 2024 and is estimated to grow at a compound annual growth rate (CAGR) of 4.4% from 2024 to 2031. The market is foreseen to reach USD XX million by 2031 because it is driven by pharmaceutical companies that make significant investments in the development of orexin receptor antagonists.

The management of groundwater resources must take into account their variation trends. In this sense, 3 statistical methods were used to identify seasonal and annual groundwater level trends: Mann-Kendall test (MK), Innovative Analysis Method (ITA) and Spearman’s Rho test (SR). Each method was applied for 5 time series (one annual and four seasonal) from 148 hydrological wells from Eastern Romania. The wells were classified in 8 cluster groups based on water depth, using the cluster analysis, covering the full range of depths from under 1.4 to over 15.5 m. Coupling statistical methods (MK and SR test) with one based on graphical analysis (ITA method) offers the possibility of obtaining statistically significant results (between 53% and 69% for spring season, 68% and 96% for autumn season and 68% and 81% from annual values). The decreasing trend of water depth is more obvious for summer and autumn season, for 72%–74% from analyzed wells (based on SR and ITA method) and 68% for annual series (based on MK test). The spatial distribution of seasonal and annual trends highlights that in the northern and central parts of the region, the groundwater depth suffers depletion induced by the effects of prolonged meteorological and hydrological drought manifested in this area in the last decades.

Characteristics of in-situ meteorological stations.

Climate variability is one of the major factors affecting the supply of ecosystem services and the well-being of people who rely on them. Despite the substantial effects of climate variability on ecosystem goods and services, empirical researches on these effects are generally lacking. Thus, this study examines the spatiotemporal impacts of climate variability on selected ecosystem services in Maze National Park and its surroundings, in southwestern Ethiopia. We conducted climate trend and variability analysis by using the Mann-Kendall (MK) trend test, Sen’s slope estimator, and innovative trend analysis (ITA). Relationships among ecosystem services and climate variables were evaluated using Pearson’s correlation coefficient (r), while partial correlation was used to evaluate the relationship among key ecosystem services and potential evapotranspiration (PET). The MK tests show a decreasing trend for both mean annual and main rainy season rainfall, with Sen’s slope (β) = -0.721 and β = -0.1.23, respectively. Whereas, the ITA method depicted a significant increase in the second rainy season rainfall (Slope(s) = 1.487), and the mean annual (s = 0.042), maximum (s = 0.024), and minimum (s = 0.060) temperature. Spatial correlations revealed significant positive relationships between ecosystem services and the mean annual rainfall and Normalized Difference Vegetation Index (NDVI), while negative correlations with the mean annual temperature. Additionally, temporal correlations highlighted positive relationships among key ecosystem services and the main rainy season rainfall. The maximum and minimum temperatures and ecosystem services were negatively correlated; whereas, there was strong negative correlations between annual (r = -0.929), main rainy season (r = -0.990), and second rainy season (r = -0.814) PET and food production. Thus, understanding the spatiotemporal variability of climate and the resulting impacts on ecosystem services helps decision-makers design ecosystem conservation and restoration strategies to increase the potential of the ecosystems to adapt to and mitigate the impacts of climate variability.

Climate variability is one of the major factors affecting the supply of ecosystem services and the well-being of people who rely on them. Despite the substantial effects of climate variability on ecosystem goods and services, empirical researches on these effects are generally lacking. Thus, this study examines the spatiotemporal impacts of climate variability on selected ecosystem services in Maze National Park and its surroundings, in southwestern Ethiopia. We conducted climate trend and variability analysis by using the Mann-Kendall (MK) trend test, Sen’s slope estimator, and innovative trend analysis (ITA). Relationships among ecosystem services and climate variables were evaluated using Pearson’s correlation coefficient (r), while partial correlation was used to evaluate the relationship among key ecosystem services and potential evapotranspiration (PET). The MK tests show a decreasing trend for both mean annual and main rainy season rainfall, with Sen’s slope (β) = -0.721 and β = -0.1.23, respectively. Whereas, the ITA method depicted a significant increase in the second rainy season rainfall (Slope(s) = 1.487), and the mean annual (s = 0.042), maximum (s = 0.024), and minimum (s = 0.060) temperature. Spatial correlations revealed significant positive relationships between ecosystem services and the mean annual rainfall and Normalized Difference Vegetation Index (NDVI), while negative correlations with the mean annual temperature. Additionally, temporal correlations highlighted positive relationships among key ecosystem services and the main rainy season rainfall. The maximum and minimum temperatures and ecosystem services were negatively correlated; whereas, there was strong negative correlations between annual (r = -0.929), main rainy season (r = -0.990), and second rainy season (r = -0.814) PET and food production. Thus, understanding the spatiotemporal variability of climate and the resulting impacts on ecosystem services helps decision-makers design ecosystem conservation and restoration strategies to increase the potential of the ecosystems to adapt to and mitigate the impacts of climate variability.

Descriptive statistics, variability and MK trend test of monthly temperature (1985–2020).

Climate variability is one of the major factors affecting the supply of ecosystem services and the well-being of people who rely on them. Despite the substantial effects of climate variability on ecosystem goods and services, empirical researches on these effects are generally lacking. Thus, this study examines the spatiotemporal impacts of climate variability on selected ecosystem services in Maze National Park and its surroundings, in southwestern Ethiopia. We conducted climate trend and variability analysis by using the Mann-Kendall (MK) trend test, Sen’s slope estimator, and innovative trend analysis (ITA). Relationships among ecosystem services and climate variables were evaluated using Pearson’s correlation coefficient (r), while partial correlation was used to evaluate the relationship among key ecosystem services and potential evapotranspiration (PET). The MK tests show a decreasing trend for both mean annual and main rainy season rainfall, with Sen’s slope (β) = -0.721 and β = -0.1.23, respectively. Whereas, the ITA method depicted a significant increase in the second rainy season rainfall (Slope(s) = 1.487), and the mean annual (s = 0.042), maximum (s = 0.024), and minimum (s = 0.060) temperature. Spatial correlations revealed significant positive relationships between ecosystem services and the mean annual rainfall and Normalized Difference Vegetation Index (NDVI), while negative correlations with the mean annual temperature. Additionally, temporal correlations highlighted positive relationships among key ecosystem services and the main rainy season rainfall. The maximum and minimum temperatures and ecosystem services were negatively correlated; whereas, there was strong negative correlations between annual (r = -0.929), main rainy season (r = -0.990), and second rainy season (r = -0.814) PET and food production. Thus, understanding the spatiotemporal variability of climate and the resulting impacts on ecosystem services helps decision-makers design ecosystem conservation and restoration strategies to increase the potential of the ecosystems to adapt to and mitigate the impacts of climate variability.