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RISS 인기검색어
- 검색키워드
- 저자 : Saha Arghya (검색결과 2 건)
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Dissociative Experience in Unipolar and Bipolar Depression: Exploring the Great Divide
Seshadri Sekhar Chatterjee,Arghya Pal,Nitu Mallik,Malay Ghosal,Goutam Saha 대한정신약물학회 2018 CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE Vol.16 No.3
Objective: Unipolar and bipolar depression (UD and BD) differ strikingly in respect to neurobiology, course and management, but their apparent clinical similarity often leads to misdiagnosis resulting in chronicity of course and treatment failure. In this study we have tried to assess whether UD and BD can be differentiated on the basis of their dissociative symptoms. Methods: Thrty-six UD patients and 35 BD patients in active episodes, without any psychiatric comorbidity were selected from outpatient department and compared for depressive and dissociative symptoms using Hamilton Depression Rating Scale and Dissociative Experience Scale-II (DES-II). Results: We found that thought the two groups didn’t differ in terms of the socio-demographic or clinical variables, BD group had significantly higher dissociative experience (U=343, p=0.001) than UD and the difference remained significant even after adjusting for the confounding factors. Conclusion: Our study shows that dissociative symptoms are significantly more prevalent in the depressive episodes of bipolar affective disorder as compared to the UD and can be an important tool in differentiating between the two disorders with very similar clinical profile. The difference can be measured using a simple self-report questionnaire like DES-II.
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Sahani Nemai,Goswami Sudipto Kumar,Saha Arghya 대한공간정보학회 2021 Spatial Information Research Vol.29 No.4
The COVID-19 pandemic and related lockdown reduced the pollution level in the major megacities worldwide. The air pollution level of the city directly influences the air temperature and also land surface temperature (LST). In this paper, authors analyzed the impact of lockdown due to COVID-19 pandemic on the pollution level of the city and resulted LST. Single channel algorithm has been used to retrieve LST from Landsat Thematic Mapper satellite data. Pre-lockdown and postlockdown satellite data has been used to show the changes in LST due to lockdown. The air quality index of prelockdown and post-lockdown period of the city estimated based on seven pollutants such as PM2.5, PM10, NO2, NH3, SO2, CO and Ozone. The pollution level of the city and LST significantly decreased after lockdown is enforced. The pollution level of the major portion of the city before lockdown is moderately polluted (95–153 lm) and after lockdown the satisfactory level of pollution level observed (33–45 lm). The mean LST before lockdown is 28.76 C (13 March, 2020) and it decreased down to 26.56 C after lockdown (30 April, 2020). There is a sharp decrease of low value of LST observed (23.6–17.35 C) in the city.
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