scholarly journals The Caucasus Territory Hot-Cold Spots Determination And Description Using 2D Surface Waves Tomography

2021 ◽  
Author(s):  
Seyed Hossein Abrehdari ◽  
Jon K. Karapetyan ◽  
Habib Rahimi ◽  
Eduard Gyodakyan
Keyword(s):  
Wave Velocity ◽  
Hot Spot ◽  
Cold Spot ◽  
Low Velocity ◽  
Linear Inversion ◽  
Edge Zone ◽  
Velocity Anomaly ◽  
Regional Tectonic ◽  
Cold Spots ◽  
Earthquake Data

Abstract In order to identify and describe Hot-Cold spots inside the earth based on increasing and decreasing wave velocity anomalies, this paper attempts to generate the first 2D tomographic maps of Rayleigh surface wave velocity dispersion curves, by using ~1200 local-regional earthquake data and ~30000 vertical (Z) components of earthquake data waveform energy with magnitude M≥4 from 1999 to 2018 in a periods range of 5 to 70 seconds and a grid spacing of 0.2º×0.5º for a depth of ~200 km. To conduct this, a generalized 2D linear inversion procedure developed by Yanovskaya and Ditmar has been applied to construct the first 2D Rayleigh tomography velocity maps in order to understand better the regional tectonic activities in the enigmatic ongoing collision-compressed edge zone of the Eurasian-Arabic plates. In this study, we assumed that low-velocity (slow) region with dark red shade is hot spot and high-velocity (fast) region with dark blue-green-yellow is a cold spot. In short and medium periods were determined the number of 15 and 2 hot spots with a depth of 7 to 108 km, respectively. In long-periods and a depth of ~200 km, most part of the area study has covered by low-velocity anomaly.

scholarly journals The geno-spatio analysis of Mycobacterium tuberculosis complex in hot and cold spots of Guangxi, China

2020 ◽  
Author(s):  
Dingwen Lin ◽  
Zhezhe Cui ◽  
Virasakdi Virasakdi ◽  
Prasit Palittapongarnpim ◽  
Angkana Chaiprasert ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Hot Spots ◽  
Hot Spot ◽  
Cold Spot ◽  
Sequencing Analysis ◽  
Spot Area ◽  
H37rv Strain ◽  
Lineage 2 ◽  
Cold Spots ◽  
Genomic Clusters

Abstract Background At present, there are few studies on polymorphism of Mycobacterium tuberculosis (Mtb) gene and how it affects the TB epidemic. Objective This study aimed to document the differences of polymorphisms between tuberculosis hot and cold spot areas of Guangxi Zhuang Autonomous Region, China. Methods The cold and hot spot areas, each with 3 counties, had been pre-identified by TB incidence for 5 years from the surveillance database. Whole genome sequencing analysis was performed on all sputum Mtb isolates from the detected cases during January and June 2018. Single nucleotide polymorphism (SNP) of each isolate compared to the H37Rv strain were called and used for lineage and sub-lineage identification. Pairwise SNP differences between every pair of isolates were computed. Analyses of Molecular Variance (AMOVA) across counties of the same hot or cold spot area and between the two areas were performed. Results As a whole, 59.8% (57.7% sub-lineage 2.2 and 2.1% sub-lineage 2.1) and 39.8% (17.8% sub-lineage 4.4, 6.5% sub-lineage 4.2 and 15.5% sub-lineage 4.5) of the Mtb strains were Lineage 2 and Lineage 4 respectively. The percentages of sub-lineage 2.2 (Beijing family strains) are significantly higher in hot spots. Through the MDS dimension reduction, the genomic population structure in the three hot spot counties is significantly different from those three cold spot counties (T-test p = 0.05). The median of SNPs distances among Mtb isolates in cold spots was greater than that in hot spots (897 vs 746, Rank-sum test p < 0.001). Three genomic clusters, each with genomic distance ≤ 12 SNPs, were identified with 2, 3 and 4 consanguineous strains. Two clusters were from hot spots and one was from cold spots.Conclusion Narrower genotype diversity in the hot area may indicate higher transmissibility of the Mtb strains in the area compared to those in the cold spot area.

scholarly journals Tomographic image of the crust and uppermost mantle of the Ionian and Aegean regions

1997 ◽  
Vol 40 (1) ◽  
Author(s):  
B. Alessandrini ◽  
L. Beranzoli ◽  
G. Drakatos ◽  
C. Falcone ◽  
G. Karantonis ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Mediterranean Area ◽  
P Wave ◽  
Moho Depth ◽  
Uppermost Mantle ◽  
Low Velocity ◽  
Central Mediterranean ◽  
Data Set ◽  
Velocity Anomaly ◽  
P Wave Velocity

We present a tomographic view of the crust and uppermost mantle beneath the Central Mediterranean area obtained from P-wave arrival times of regional earthquakes selected from the ISC bulletin. The P-wave velocity anomalies are obtained using Thurber's algorithm that jointly relocates earthquakes and computes velocity adjustments with respect to a starting model. A specific algorithm has been applied to achieve a distribution of epicentres as even as possible. A data set of 1009 events and 49072 Pg and Pn phases was selected. We find a low velocity belt in the crust, evident in the map view at 25 km of depth, beneath the Hellenic arc. A low velocity anomaly extends at 40 km of depth under the Aegean back arc basin. High velocities are present at Moho depth beneath the Ionian sea close to the Calabrian and Aegean arcs. The tomographic images suggest a close relationship between P-wave velocity pattern and the subduction systems of the studied area.

scholarly journals The geno-spatio analysis of Mycobacterium tuberculosis complex in hot and cold spots of Guangxi, China

2020 ◽  
Author(s):  
Dingwen Lin ◽  
Zhezhe Cui ◽  
Virasakdi Virasakdi ◽  
Prasit Palittapongarnpim ◽  
Angkana Chaiprasert ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Hot Spots ◽  
Hot Spot ◽  
Cold Spot ◽  
Sequencing Analysis ◽  
Spot Area ◽  
H37rv Strain ◽  
Lineage 2 ◽  
Cold Spots ◽  
Genomic Clusters

Abstract Background At present, there are few studies on polymorphism of Mycobacterium tuberculosis (Mtb) gene and how it affects the TB epidemic. This study aimed to document the differences of polymorphisms between tuberculosis hot and cold spot areas of Guangxi Zhuang Autonomous Region, China. Methods The cold and hot spot areas, each with 3 counties, had been pre-identified by TB incidence for 5 years from the surveillance database. Whole genome sequencing analysis was performed on all sputum Mtb isolates from the detected cases during January and June 2018. Single nucleotide polymorphism (SNP) of each isolate compared to the H37Rv strain were called and used for lineage and sub-lineage identification. Pairwise SNP differences between every pair of isolates were computed. Analyses of Molecular Variance (AMOVA) across counties of the same hot or cold spot area and between the two areas were performed. Results As a whole, 59.8% (57.7% sub-lineage 2.2 and 2.1% sub-lineage 2.1) and 39.8% (17.8% sub-lineage 4.4, 6.5% sub-lineage 4.2 and 15.5% sub-lineage 4.5) of the Mtb strains were Lineage 2 and Lineage 4 respectively. The percentages of sub-lineage 2.2 (Beijing family strains) are significantly higher in hot spots. Through the MDS dimension reduction, the genomic population structure in the three hot spot counties is significantly different from those three cold spot counties (T-test p = 0.05). The median of SNPs distances among Mtb isolates in cold spots was greater than that in hot spots (897 vs 746, Rank-sum test p < 0.001). Three genomic clusters, each with genomic distance ≤ 12 SNPs, were identified with 2, 3 and 4 consanguineous strains. Two clusters were from hot spots and one was from cold spots. Conclusion Narrower genotype diversity in the hot area may indicate higher transmissibility of the Mtb strains in the area compared to those in the cold spot area.

scholarly journals Identifying diabetes management opportunity areas in the USA

2020 ◽  
Vol 8 (1) ◽  
pp. e000293 ◽  
Author(s):  
Michael Topmiller ◽  
Kyle Shaak ◽  
Peter J Mallow ◽  
Autumn M Kieber-Emmons
Keyword(s):  
Hot Spots ◽  
Diabetes Management ◽  
Hot Spot ◽  
The United States ◽  
Cold Spot ◽  
United States Census ◽  
Preventable Hospitalisation ◽  
Cold Spots ◽  
Medicare Spending ◽  
Management Services

Using adherence to diabetes management guidelines as a case study, this paper applied a novel geospatial hot-spot and cold-spot methodology to identify priority counties to target interventions. Data for this study were obtained from the Dartmouth Atlas of Healthcare, the United States Census Bureau’s American Community Survey and the University of Wisconsin County Health Rankings. A geospatial approach was used to identify four tiers of priority counties for diabetes preventive and management services: diabetes management cold-spots, clusters of counties with low rates of adherence to diabetes preventive and management services (Tier D); Medicare spending hot-spots, clusters of counties with high rates of spending and were diabetes management cold-spots (Tier C); preventable hospitalisation hot-spots, clusters of counties with high rates of spending and are diabetes management cold-spots (Tier B); and counties that were located in a diabetes management cold-spot cluster, preventable hospitalisation hot-spot cluster and Medicare spending hot-spot cluster (Tier A). The four tiers of priority counties were geographically concentrated in Texas and Oklahoma, the Southeast and central Appalachia. Of these tiers, there were 62 Tier A counties. Rates of preventable hospitalisations and Medicare spending were higher in Tier A counties compared with national averages. These same counties had much lower rates of adherence to diabetes preventive and management services. The novel geospatial mapping approach used in this study may allow practitioners and policy makers to target interventions in areas that have the highest need. Further refinement of this approach is necessary before making policy recommendations.

Global and Local Elastic-Plastic Stress Analysis of Coke Drum Under Thermal-Mechanical Loadings

2011 ◽  
Vol 133 (6) ◽  
Author(s):  
Feng Ju ◽  
John Aumuller ◽  
Zihui Xia ◽  
Pierre Du Plessis
Keyword(s):  
Failure Modes ◽  
Early Stage ◽  
Hot Spot ◽  
Fatigue Cracking ◽  
Plastic Behavior ◽  
Cold Spot ◽  
Operating Cycle ◽  
Elastic Plastic ◽  
Clad Layer ◽  
Cold Spots

Coke drums are critical equipment in the petroleum industry. The failure modes of coke drums include excessive bulging deformation and fatigue cracking. The elastic-plastic behavior of a coke drum, subjected to both thermal and mechanical loadings, is analyzed for a complete cycle of operation. The effects of multiple operational cycles and localized hot/cold spots are also investigated. It is found that yielding of the clad layer starts at the very early stage in an operating cycle and permanent deformation is caused in the first operating cycle. Plastic shakedown occurs in the clad layer under combined operating thermal and mechanical loadings. It is also found that both hot and cold spots will cause bulging of the shell and the cold spot can cause more severe deformation than the hot spot.

scholarly journals Locating Regions of Differential Variability in DNA and Protein Sequences

Genetics ◽  
1999 ◽  
Vol 153 (1) ◽  
pp. 485-495 ◽  
Author(s):  
Hua Tang ◽  
R C Lewontin
Keyword(s):  
Regional Differences ◽  
Hot Spot ◽  
Protein Sequences ◽  
Sequence Length ◽  
Cold Spot ◽  
Sequential Method ◽  
Differential Constraint ◽  
Cold Spots ◽  
Differential Variability ◽  
Adjacent Sequence

Abstract In the comparison of DNA and protein sequences between species or between paralogues or among individuals within a species or population, there is often some indication that different regions of the sequence are divergent or polymorphic to different degrees, indicating differential constraint or diversifying selection operating in different regions of the sequence. The problem is to test statistically whether the observed regional differences in the density of variant sites represent real differences and then to estimate as accurately as possible the location of the differential regions. A method is given for testing and locating regions of differential variation. The method consists of calculating G(xk) = k/n – xk/N, where xk is the position of the kth variant site along the sequence, n is the total number of variant sites, and N is the total sequence length. The estimated region is the longest stretch of adjacent sequence for which G(xk) is monotonically increasing (a hot spot) or decreasing (a cold spot). Critical values of this length for tests of significance are given, a sequential method is developed for locating multiple differential regions, and the power of the method against various alternatives is explored. The method locates the endpoints of hot spots and cold spots of variation with high accuracy.

scholarly journals Issues in the Current Practices of Spatial Cluster Detection and Exploring Alternative Methods

2021 ◽  
Vol 18 (18) ◽  
pp. 9848
Author(s):  
David Wong
Keyword(s):  
Extreme Values ◽  
Hot Spot ◽  
Heuristic Method ◽  
Cluster Detection ◽  
Alternative Methods ◽  
Detection Methods ◽  
Cold Spot ◽  
Spot Detection ◽  
Cold Spots ◽  
Local Moran

Local Moran and local G-statistic are commonly used to identify high-value (hot spot) and low-value (cold spot) spatial clusters for various purposes. However, these popular tools are based on the concept of spatial autocorrelation or association (SA), but do not explicitly consider if values are high or low enough to deserve attention. Resultant clusters may not include areas with extreme values that practitioners often want to identify when using these tools. Additionally, these tools are based on statistics that assume observed values or estimates are highly accurate with error levels that can be ignored or are spatially uniform. In this article, problems associated with these popular SA-based cluster detection tools were illustrated. Alternative hot spot-cold spot detection methods considering estimate error were explored. The class separability classification method was demonstrated to produce useful results. A heuristic hot spot-cold spot identification method was also proposed. Based on user-determined threshold values, areas with estimates exceeding the thresholds were treated as seeds. These seeds and neighboring areas with estimates that were not statistically different from those in the seeds at a given confidence level constituted the hot spots and cold spots. Results from the heuristic method were intuitively meaningful and practically valuable.

scholarly journals The geno-spatio analysis of Mycobacterium tuberculosis complex in hot and cold spots of Guangxi, China

2020 ◽  
Author(s):  
Dingwen Lin ◽  
Zhezhe Cui ◽  
Virasakdi Virasakdi ◽  
Prasit Palittapongarnpim ◽  
Angkana Chaiprasert ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Hot Spots ◽  
Hot Spot ◽  
Cold Spot ◽  
Sequencing Analysis ◽  
Spot Area ◽  
H37rv Strain ◽  
Lineage 2 ◽  
Cold Spots ◽  
Genomic Clusters

Abstract Background At present, there are few studies on polymorphism of Mycobacterium tuberculosis (Mtb) gene and how it affects the TB epidemic. This study aimed to document the differences of polymorphisms between tuberculosis hot and cold spot areas of Guangxi Zhuang Autonomous Region, China. Methods The cold and hot spot areas, each with 3 counties, had been pre-identified by TB incidence for 5 years from the surveillance database. Whole genome sequencing analysis was performed on all sputum Mtb isolates from the detected cases during January and June 2018. Single nucleotide polymorphism (SNP) of each isolate compared to the H37Rv strain were called and used for lineage and sub-lineage identification. Pairwise SNP differences between every pair of isolates were computed. Analyses of Molecular Variance (AMOVA) across counties of the same hot or cold spot area and between the two areas were performed. Results As a whole, 59.8% (57.7% sub-lineage 2.2 and 2.1% sub-lineage 2.1) and 39.8% (17.8% sub-lineage 4.4, 6.5% sub-lineage 4.2 and 15.5% sub-lineage 4.5) of the Mtb strains were Lineage 2 and Lineage 4 respectively. The percentages of sub-lineage 2.2 (Beijing family strains) are significantly higher in hot spots. Through the MDS dimension reduction, the genomic population structure in the three hot spot counties is significantly different from those three cold spot counties (T-test p = 0.05). The median of SNPs distances among Mtb isolates in cold spots was greater than that in hot spots (897 vs 746, Rank-sum test p < 0.001). Three genomic clusters, each with genomic distance ≤ 12 SNPs, were identified with 2, 3 and 4 consanguineous strains. Two clusters were from hot spots and one was from cold spots. Conclusion Narrower genotype diversity in the hot area may indicate higher transmissibility of the Mtb strains in the area compared to those in the cold spot area.

scholarly journals Variations of the crustal thickness in Nepal Himalayas based on tomographic inversion of regional earthquake data

2014 ◽  
Vol 6 (2) ◽  
pp. 2867-2883
Author(s):  
I. Koulakov ◽  
G. Maksotova ◽  
S. Mukhopadhyay ◽  
J. Raoof ◽  
J. R. Kayal ◽  
...  
Keyword(s):  
Gravity Anomalies ◽  
Crustal Thickness ◽  
Crustal Thickening ◽  
Moho Depth ◽  
Low Velocity ◽  
Tomographic Inversion ◽  
Velocity Anomaly ◽  
Free Air Gravity ◽  
Regional Earthquake ◽  
Earthquake Data

Abstract. We estimate variations of the crustal thickness beneath the Nepal Himalayas based on tomographic inversion of regional earthquake data. We have obtained a low-velocity anomaly in the upper part of the model down to depths of 40 to 80 km and proposed that the lower limit of this anomaly represents variations of the Moho depth. This statement was supported by results of synthetic modeling. The obtained variations of crustal thickness match fairly well with the free-air gravity anomalies: thinner crust patterns correspond to lower gravity values and vice versa. There is also some correlation with magnetic field: higher magnetic values correspond to the major areas of thicker crust. We propose that elevated magnetic values can be associated with more rigid segments of the incoming Indian crust which cause more compression in the thrust zone and leads to stronger crustal thickening.

Sign in / Sign up

Export Citation Format

Share Document