Spread of Mycobacterium tuberculosis lineage 4 in South China influenced by Maritime Silk Road and “Huguang Filling Sichuan” population migration

Background Lineage 4 of Mycobacterium tuberculosis complex (MTBC), mainly epidemic in Europe and Americas, presents in high proportions in South China and is believed to enter China around the 13th century, when the important human migratory events of the Maritime Silk Road and “Huguang Filling Sichuan” population migration happened in China. This study was to explain the coincidence of these two events with lineage 4’s high proportion in South China. Methods Based on the spatial interpolation analysis of the genotyping data of 25,575 MTBC isolates, the distribution of lineage 4 was compared with that of targeted surname populations and the Maritime Silk Road’s main ports. Results The results showed that lineage 4 distribution in China could be mapped to the regions affected by “Huguang Filling Sichuan” population migration; while the distribution of lineage 4’s two sub-lineages in Asia, Europe, Africa and Oceania could be best explained by the Maritime Silk Road. Conclusion Our results suggest that these two events might pose a crucial shared influence, leading to the greater incidence of lineage 4 in South China. And this may contribute to our better understanding of the prevailing tuberculosis landscape in China and facilitate the epidemiological investigations and tracking of emerging MTBC clones.

Geostatistical analysis of static level evolution between 1995-2005 and 2007-2017 in San Luis Potosí Aquifer, México

Knowing the piezometric levels evolution of an aquifer is essential for planning the use of water resources in the cities of central México, such as San Luis Potosí, whose population depends almost entirely on groundwater. Applying geostatistical methods from georeferenced data can reliably provide information on the spatial variability of valley piezometry. The objective of this study is to evaluate the evolution of the static levels of the aquifer in San Luis Potosí Valley, through an interpolation analysis by the kriging method. For both periods, the experimental variogram was adjusted to the Gaussian model and the method with the best results was ordinary kriging. From this analysis it was obtained that the decay of the static levels is more critical in the central zone of the valley, while the zones of the northwest and towards the south, the aquifer levels have shown an important recovery; the important values for the decrease in static levels coincide with the areas where the population density is greater.

Calculation of winter average ten-day minimum flows of rivers of the Lake Sevan Basin and analysis of its time variability

Studying decadal minimum costs, especially in the context of expected climate change, is relevant and urgent. Both on the rivers of the study area and the whole republic, minimum water discharge is observed during periods of summer- autumn and winter low water. In both cases, the power of the rivers is mostly underground. However, summer-autumn rains can often disrupt the river’s feeding patterns and cause flooding. The paper calculated the winter average ten-day minimum costs for posts that have a long series of observations on rivers flowing into Lake Sevan. In a number of longterm observations, the dynamics of changes in the winter average ten-day minimum costs of rivers flowing into the basin and the patterns of their spatial distribution have been estimated. As a source material daily data from actual observations at 12 hydrological posts in the study area of the Service of the Hydrometeorology and Active Influence on Atmospheric Phenomena, Ministry of Emergency Situations of the Republic of Armenia, are used. All observed hydrological posts have a number of observations 40 years or more. The methods used in the work are: mathematical-statistical, extrapolation, interpolation, analysis, analogue and correlation. It turned out that most rivers in the Lake Sevan Basin have a tendency to increase in winter average ten-day minimum costs.

Estimation of sea ice parameters from sea ice model with assimilated ice concentration and SST

A multi-category numerical sea ice model CICE was used along with data assimilation to derive sea ice parameters in the region of Baffin Bay and Labrador Sea. The assimilation of ice concentration was performed using the data derived from the Advanced Microwave Scanning Radiometer (AMSR-E and AMSR2). The model uses a mixed-layer slab ocean parameterization to compute the sea surface temperature (SST) and thereby to compute the freezing and melting potential of ice. The data from Advanced Very High Resolution Radiometer (AVHRR-only optimum interpolation analysis) were used to assimilate SST. The modelled ice parameters including concentration, ice thickness, freeboard and keel depth were compared with parameters estimated from remote-sensing data. The ice thickness estimated from the model was compared with the measurements derived from Soil Moisture Ocean Salinity – Microwave Imaging Radiometer using Aperture Synthesis (SMOS–MIRAS). The model freeboard estimates were compared with the freeboard measurements derived from CryoSat2. The ice concentration, thickness and freeboard estimates from the model assimilated with both ice concentration and SST were found to be within the uncertainty in the observation except during March. The model-estimated draft was compared with the measurements from an upward-looking sonar (ULS) deployed in the Labrador Sea (near Makkovik Bank). The difference between modelled draft and ULS measurements estimated from the model was found to be within 10 cm. The keel depth measurements from the ULS instruments were compared to the estimates from the model to retrieve a relationship between the ridge height and keel depth.

GIS-Based Rainfall Estimator Evaluation and Interpolation Analysis Using ArcGIS

We have been always trying to predict the weather to minimize risk, produce strategy, and other decision making situation. To achieve this, monitoring method need to be used to gather data. Rainfall monitoring is one of the area that widely used and one of the mostly used method is satellite-based rainfall monitoring. However, there are limitation to apply to the Satellite Rainfall (SR) estimation specifically on its accuracy and lack of certainty. Thus, study that directed to measure the inaccuracies of SR measurements is needed by using data of distribution of Actual Rainfall (AR). The SR data is taken from the National Oceanic and Atmospheric Administration (NOAA)’s Hydro—Estimator while the AR data was from the National Institute of Water and Atmospheric Research (NIWA). Through the statistics and interpolation analysis using ArcGIS, the study shows a prominent result of SR estimation accuracy in the sample area and thus may opens up more similar implementation as well as stands as a good benchmark for future improvement of the method. This study also shows how interpolation method through a GIS software could provide a significant result on a geographical related studies. Keywords : GIS, Geospatial Analysis, Interpolation Analysis, Arcgis