scholarly journals Geospatial Analysis of the Impact of Flood and Drought Hazards on Crop Land and Its Relationship with Human Migration at the District Level in Uttar Pradesh, India

2021 ◽  
Vol 15 (4) ◽  
pp. 117-127
Author(s):  
Zubairul Islam ◽  
Sudhir Kumar Singh
Keyword(s):  
Hot Spot ◽  
Uttar Pradesh ◽  
Human Migration ◽  
Drought Effect ◽  
Crop Land ◽  
Global Regression ◽  
Cold Spots ◽  
The Impact ◽  
Gwr Model ◽  
The Relationship

The main objective was to explore the connection between flood and drought hazards and their impact on crop land and human migration. The Flood and Drought effect on Cropland Index (FDCI), hot spot analysis and the Global Regression Analysis method was applied for the identification of the relationship between human migration and flood and drought hazards. The spatial pattern and hot and cold spots of FDCI, spatial autocorrelation and Getis-OrdGi* statistic techniques were used respectively. The FDCI was taken as an explanatory variable and human migration was taken as a dependent variable in the environment of the geographically weighted regression (GWR) model which was applied to measure the impact of flood and drought hazards on human migration. FDCI suggests a z-score of 4.9, which shows that the impact of flood and drought frequency on crop land is highly clustered. In the case of the hot spots analysis, out of seventy districts in Uttar Pradesh twenty-one were classified as hot spot and eight were classified as cold spots with a confidence level of 90 to 99%. Hot spot indicate maximum and cold spots show minimum impact of flood and drought hazards on crop land. The impact of flood and drought hazards on human migration show that there are fourteen districts where migration out is far more than predicted while there are ten districts where migration out is far lower.

scholarly journals The Impact of KPNA2 on Prognosis of Colorectal Cancer Patients: A Meta-Analysis

2022 ◽  
Author(s):  
Zhangzhe Yan ◽  
Mingang He ◽  
Haoxin Shi ◽  
Haipeng Wang ◽  
Miao Qin ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Malignant Tumors ◽  
Hot Spot ◽  
Meta Analysis ◽  
Tumor Stage ◽  
Medical Database ◽  
High Level ◽  
Colorectal Cancer Patients ◽  
The Impact ◽  
The Relationship

Abstract Background and purpose: Colorectal cancer (CRC) is one of the most common malignant tumors with the highest mortality globally. At present, there is no exact biomarker to predict the prognosis and clinicopathological monitoring of CRC patients. Recent studies on the relationship of Karyopherin α 2 (KPNA2) expression and the prognosis of CRC has gradually become a hot spot while the results are still controversial. The aim of this study was to analyze and assess the prognostic role of KPNA2 in CRC patients. Methods: PubMed, Web of Science, Medline, EMBASE, CNKI, Wanfang, VIP, and Chinese Medical Database were systematically searched. The cohort study of high-level expression of KNPA2 and low-level expression of KPNA2 in CRC patients was included, the relevant data were extracted and the literature quality was evaluated. At the same time, the relationship between KPNA2 expression level and the overall survival (OS), the clinicopathological stage of CRC patients was studied. Meta-analysis was carried out by Stata MP 17.0 (Stata Corporation, College Station, TX, USA) software. Results: A total of 7 cohort studies involving 1166 patients were included. The analysis results showed that higher KPNA2 expression was significantly associated with higher tumor stage (OR=1.90, 95% CI 1.42–2.54), higher degree of tumor invasion (OR=2.14，95% CI 1.55-2.94), more lymph node metastasis (OR=2.20, 95% CI 1.68-2.88) and more distant metastasis (OR=3.66，95% CI 1.81-7.40). Moreover, higher KPNA2 expression was significantly associated with the shorter OS (HR=2.31, 95%CI 1.46-3.68).Conclusion: KPNA2 overexpression is an unfavorable prognostic factor for CRC patients. It could serve as a prognostic biomarker and as a potential therapeutic target for CRC.

scholarly journals Quantifying the Spatial Association between Land Use Change and Ecosystem Services Value: A Case Study in Xi’an, China

2020 ◽  
Vol 12 (11) ◽  
pp. 4449
Author(s):  
Yajing Shao ◽  
Xuefeng Yuan ◽  
Chaoqun Ma ◽  
Ruifang Ma ◽  
Zhaoxia Ren
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Land Cover ◽  
Spatial Heterogeneity ◽  
Spatial Association ◽  
Lulc Change ◽  
Ecosystem Services Value ◽  
The Impact ◽  
Gwr Model ◽  
The Relationship

The impact of land use and land cover (LULC) change on ecosystem services value (ESV) varies in different spatial locations. Although many studies have focused on quantifying the effect of LULC change on ESV, few have considered the spatial heterogeneity of the relationship between LULC change and ESV. Therefore, this study examines the relationship between ESV and LULC change from a spatial perspective in Xi’an City. We divide the study area into 10,522 grid cells, based on land cover data from 2000 to 2018, and we identify the spatial-temporal dynamics of LULC change. Next, we employ the Benefits Transfer Method (BTM) to evaluate the ESV, and the ESV is corrected by the normalized difference vegetation index (NDVI). A geographically weighted regression (GWR) model and ordinary least squares (OLS) regression model are used to assess the spatial association of LULC change and ESV. The results show that the total ESV loss is 6.57 billion yuan (Chinese yuan), and the loss rate is 12.18%. The distribution of ESV shows an obvious spatial heterogeneity, and the low-value area of ESV expands eastward from the main urban area. More than 50% of total ESV is provided by woodland. From 2000 to 2018, the land use pattern in Xi’an underwent a significant change with the developed land increasing by 64.09%, whereas farmland decreased by 12.49%. Based on the GWR model, the relationship between LULC change and ESV in Xi’an showed a significant negative association and spatial heterogeneity. Our study results provide a new way to effectively identify the relationship between LULC change and ESV, and in turn, to fully understand the ecological trends at the regional scale, laying a foundation for regional sustainable development.

Spatial analysis of COVID-19 for the state of Uttar Pradesh, India

2021 ◽  
pp. 1-15
Author(s):  
Meet Fatewar ◽  
Sandeep Kumar ◽  
Shruti Gautam
Keyword(s):  
Statistical Analysis ◽  
Hot Spot ◽  
Uttar Pradesh ◽  
The State ◽  
Spatial Statistical Analysis ◽  
First Case ◽  
The World ◽  
Analytical Research ◽  
Major Factors ◽  
The Impact

The world is struggling to combat COVID-19 pandemic, which is caused by the SARS-CoV-2 virus. The pandemic has affected millions of people all across the globe since the first case has been reported in the Wuhan city of China in December 2019. India is the second most affected country in the world with more than 8.5 million confirmed cases (as of 10 November 2020) after USA. India is facing an unprecedented crisis due to the pandemic, leading to the Nation’s economy to a near standstill. The share of COVID-19 confirmed cases in six most affected States of India is approximately 60 percent. The analytical research tries to assess the impact of COVID-19 through spatial-statistical analysis for the state of Uttar Pradesh, which is one of the most affected states by COVID-19 in India. The detailed analysis has been carried out at district level. The impact of pandemic is more in regions (or districts), which are either having metropolis or airports along with high population density and growth rate during the last decade. Furthermore, inadequate number of health infrastructure facilities and low number of testing are some of the major factors making the situation worse in India. The spatial-statistical analysis enables to understand the pattern of spreading of disease by identifying the hot-spot areas, perceiving the trend of transmission of disease spatially, and understanding the extent of the pandemic over a period of time.

scholarly journals Spatial Clustering of Dengue Fever Incidence and Its Association with Surrounding Greenness

2018 ◽  
Vol 15 (9) ◽  
pp. 1869 ◽  
Author(s):  
Chi-Chieh Huang ◽  
Tuen Tam ◽  
Yinq-Rong Chern ◽  
Shih-Chun Lung ◽  
Nai-Tzu Chen ◽  
...  
Keyword(s):  
Land Use ◽  
Spatial Autocorrelation ◽  
Dengue Fever ◽  
Vegetation Index ◽  
Green Space ◽  
Hot Spot ◽  
Southern Taiwan ◽  
The Impact ◽  
The Relationship ◽  
Green Land

With more than 58,000 cases reported by the country’s Centers for Disease Control, the dengue outbreaks from 2014 to 2015 seriously impacted the southern part of Taiwan. This study aims to assess the spatial autocorrelation of the dengue fever (DF) outbreak in southern Taiwan in 2014 and 2015, and to further understand the effects of green space (such as forests, farms, grass, and parks) allocation on DF. In this study, two different greenness indexes were used. The first green metric, the normalized difference vegetation index (NDVI), was provided by the long-term NASA MODIS satellite NDVI database, which quantifies and represents the overall vegetation greenness. The latest 2013 land use survey GIS database completed by the National Land Surveying and Mapping Center was obtained to access another green metric, green land use in Taiwan. We first used Spearman’s rho to find out the relationship between DF and green space, and then three spatial autocorrelation methods, including Global Moran’s I, high/low clustering, and Hot Spot were employed to assess the spatial autocorrelation of DF outbreak. In considering the impact of social and environmental factors in DF, we used generalized linear mixed models (GLMM) to further clarify the relationship between different types of green land use and dengue cases. Results of spatial autocorrelation analysis showed a high aggregation of dengue epidemic in southern Taiwan, and the metropolitan areas were the main hotspots. Results of correlation analysis and GLMM showed a positive correlation between parks and dengue fever, and the other five green space metrics and land types revealed a negative association with DF. Our findings may be an important asset for improving surveillance and control interventions for dengue.

scholarly journals PEMODELAN DEFORESTASI HUTAN LINDUNG DI INDONESIA MENGGUNAKAN MODEL GEOGRAPHICALLY AND TEMPORALLY WEIGHTED REGRESSION (GTWR)

2018 ◽  
Vol 7 (3) ◽  
pp. 314-325
Author(s):  
Thea Zulfa Adiningrumh ◽  
Alan Prahutama ◽  
Rukun Santoso
Keyword(s):  
Regression Model ◽  
Spatial Data ◽  
Information Criterion ◽  
Gaussian Kernel ◽  
Weighted Regression ◽  
Statistical Analysis Method ◽  
Global Regression ◽  
Gwr Model ◽  
Parameter Estimators ◽  
The Relationship

Regression analysis is a statistical analysis method that is used to modeling the relationship between dependent variables and independent variables. In the linear regression model only produced parameter estimators are globally, so it’s often called global regression. While to analyze spatial data can be used Geographically Weighted Regression (GWR) method. Geographically and Temporally Weighted Regression (GTWR) is the development of  GWR model to handle the instability of a data both from the spatial and temporal sides simultaneously. In this GWR modeling the weight function used is a Gaussian  Kernel, which requires the bandwidth value as a distance parameter. Optimum bandwidth can be obtained by minimizing the CV (cross validation) coefficient value. By comparing the R-square, Mean Square Error (MSE) and Akaike Information Criterion (AIC) values in both methods, it is known that modeling the level of deforestation in protected forest areas in Indonesia in 2013 through 2016 uses the GTWR method better than global regression. With the R-square value the GTWR model is 25.1%, the MSE value is 0.7833 and AIC value is 349,6917. While the global regression model has R-square value of 15.8%, MSE value of 0.861 and AIC value of 361,3328. Keywords : GWR, GTWR, Bandwidth, Kernel Gaussian

Accent Policy and Accent Modification Enterprises as Potential Indicators of Intercultural Power Relations: A Call for an Updated Research Agenda

2013 ◽  
Vol 3 (1) ◽  
pp. 22-33 ◽  
Author(s):  
Brynne D. Ovalle ◽  
Rahul Chakraborty
Keyword(s):  
International Relations ◽  
Identity Construction ◽  
Social Theory ◽  
Power Relations ◽  
Linguistic Diversity ◽  
Cultural Organization ◽  
Using Data ◽  
The Individual ◽  
The Impact ◽  
The Relationship

This article has two purposes: (a) to examine the relationship between intercultural power relations and the widespread practice of accent discrimination and (b) to underscore the ramifications of accent discrimination both for the individual and for global society as a whole. First, authors review social theory regarding language and group identity construction, and then go on to integrate more current studies linking accent bias to sociocultural variables. Authors discuss three examples of intercultural accent discrimination in order to illustrate how this link manifests itself in the broader context of international relations (i.e., how accent discrimination is generated in situations of unequal power) and, using a review of current research, assess the consequences of accent discrimination for the individual. Finally, the article highlights the impact that linguistic discrimination is having on linguistic diversity globally, partially using data from the United Nations Educational, Scientific and Cultural Organization (UNESCO) and partially by offering a potential context for interpreting the emergence of practices that seek to reduce or modify speaker accents.

Business: Making Cents of Coding Systems: Billing for Professional Services

2010 ◽  
Vol 20 (1) ◽  
pp. 3-8
Author(s):  
Dee Adams Nikjeh
Keyword(s):  
Professional Services ◽  
Speech Language Pathology ◽  
Coding Systems ◽  
Language Pathology ◽  
Program Funding ◽  
Fee Schedule ◽  
Procedure Codes ◽  
Relationship Of ◽  
The Impact ◽  
The Relationship

Abstract Administrators and supervisors face daily challenges over issues such as program funding, service fees, correct coding procedures, and the ever-changing healthcare regulations. Receiving equitable reimbursement for speech-language pathology and audiology services necessitates an understanding of federal coding and reimbursement systems. This tutorial provides information pertaining to two major healthcare coding systems and explains the relationship of these systems to clinical documentation, the Medicare Physician Fee Schedule and equitable reimbursement. An explanation of coding edits and coding modifiers is provided for use in those occasional atypical situations when the standard use of procedural coding may not be appropriate. Also included in this tutorial is a brief discussion of the impact that the Medicare Improvements for Patients and Providers Act of 2008 (HR 6331 Medicare Improvements for Patients and Providers Act [MIPPA], 2008) has had on the valuation of speech-language pathology procedure codes.

The Need to Belong and the Relationship Between Loneliness and Health

2014 ◽  
Vol 22 (4) ◽  
pp. 194-201 ◽  
Author(s):  
Freda-Marie Hartung ◽  
Britta Renner
Keyword(s):  
Individual Differences ◽  
Social Isolation ◽  
Social Situation ◽  
First Year ◽  
Health State ◽  
Need To Belong ◽  
First Year University ◽  
Perceived Social Isolation ◽  
The Impact ◽  
The Relationship

Humans are social animals; consequently, a lack of social ties affects individuals’ health negatively. However, the desire to belong differs between individuals, raising the question of whether individual differences in the need to belong moderate the impact of perceived social isolation on health. In the present study, 77 first-year university students rated their loneliness and health every 6 weeks for 18 weeks. Individual differences in the need to belong were found to moderate the relationship between loneliness and current health state. Specifically, lonely students with a high need to belong reported more days of illness than those with a low need to belong. In contrast, the strength of the need to belong had no effect on students who did not feel lonely. Thus, people who have a strong need to belong appear to suffer from loneliness and become ill more often, whereas people with a weak need to belong appear to stand loneliness better and are comparatively healthy. The study implies that social isolation does not impact all individuals identically; instead, the fit between the social situation and an individual’s need appears to be crucial for an individual’s functioning.

Investigating the Relationship Between Self-Esteem and Stigma Among Young Adults With History of Suicide Attempts

Crisis ◽  
2016 ◽  
Vol 37 (4) ◽  
pp. 265-270 ◽  
Author(s):  
Meshan Lehmann ◽  
Matthew R. Hilimire ◽  
Lawrence H. Yang ◽  
Bruce G. Link ◽  
Jordan E. DeVylder
Keyword(s):  
Young Adults ◽  
Suicide Attempts ◽  
Self Esteem ◽  
High Risk Population ◽  
High Functioning ◽  
People With Mental Illness ◽  
History Of ◽  
The Individual ◽  
The Impact ◽  
The Relationship

Abstract. Background: Self-esteem is a major contributor to risk for repeated suicide attempts. Prior research has shown that awareness of stigma is associated with reduced self-esteem among people with mental illness. No prior studies have examined the association between self-esteem and stereotype awareness among individuals with past suicide attempts. Aims: To understand the relationship between stereotype awareness and self-esteem among young adults who have and have not attempted suicide. Method: Computerized surveys were administered to college students (N = 637). Linear regression analyses were used to test associations between self-esteem and stereotype awareness, attempt history, and their interaction. Results: There was a significant stereotype awareness by attempt interaction (β = –.74, p = .006) in the regression analysis. The interaction was explained by a stronger negative association between stereotype awareness and self-esteem among individuals with past suicide attempts (β = –.50, p = .013) compared with those without attempts (β = –.09, p = .037). Conclusion: Stigma is associated with lower self-esteem within this high-functioning sample of young adults with histories of suicide attempts. Alleviating the impact of stigma at the individual (clinical) or community (public health) levels may improve self-esteem among this high-risk population, which could potentially influence subsequent suicide risk.

Assessing the Impact of Suicide Exclusion Periods on Life Insurance

Crisis ◽  
2010 ◽  
Vol 31 (4) ◽  
pp. 217-223 ◽  
Author(s):  
Paul Yip ◽  
David Pitt ◽  
Yan Wang ◽  
Xueyuan Wu ◽  
Ray Watson ◽  
...  
Keyword(s):  
Life Insurance ◽  
Accidental Death ◽  
Insurance Policy ◽  
Death Rates ◽  
Insurance Policies ◽  
Suicidal Death ◽  
Insured Individual ◽  
The Impact ◽  
Insurance Data ◽  
The Relationship

Background: We study the impact of suicide-exclusion periods, common in life insurance policies in Australia, on suicide and accidental death rates for life-insured individuals. If a life-insured individual dies by suicide during the period of suicide exclusion, commonly 13 months, the sum insured is not paid. Aims: We examine whether a suicide-exclusion period affects the timing of suicides. We also analyze whether accidental deaths are more prevalent during the suicide-exclusion period as life-insured individuals disguise their death by suicide. We assess the relationship between the insured sum and suicidal death rates. Methods: Crude and age-standardized rates of suicide, accidental death, and overall death, split by duration since the insured first bought their insurance policy, were computed. Results: There were significantly fewer suicides and no significant spike in the number of accidental deaths in the exclusion period for Australian life insurance data. More suicides, however, were detected for the first 2 years after the exclusion period. Higher insured sums are associated with higher rates of suicide. Conclusions: Adverse selection in Australian life insurance is exacerbated by including a suicide-exclusion period. Extension of the suicide-exclusion period to 3 years may prevent some “insurance-induced” suicides – a rationale for this conclusion is given.

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