Forty different medicinal plants were investigated for arbuscular mycorrhizal association in the Rajshahi University Campus in Bangladesh. The results indicated that 35 different plants were infected by AM (arbuscular...Forty different medicinal plants were investigated for arbuscular mycorrhizal association in the Rajshahi University Campus in Bangladesh. The results indicated that 35 different plants were infected by AM (arbuscular mycorrhizal) fungi as found by trypan blue staining procedure. The percentage of root colonization by AM fungi varied from 13.3% to 100%. Mangifera indica and Morus indica have maximum percentage of colonization (100%). The intensity of root colonization were abundant in the plants belonging to the families Anacardiaceae, Asclepiadaceae, Moraceae, Leguminosae and Apocynaceae whereas the intensity of colonization of crop roots were moderate and poor belonging to Gramineae and Leguminosae. The presence of greater number of spore in soil was always associated with the incidence of abundant mycelia. In plant roots the formation of spore and mycelia was restricted by low pH. Number of mycorrhizal fungus spores ranged between 35 to100 per 100g air dried soil in different family respective soils. The frequency of mycorrhizal fungus infection showed positive correlation with soil pH, moisture, water holding capacity, texture, total nitrogen, organic carbon, phosphorus, calcium, potassium, and magnesium. Especially phosphorus and nitrogen in the soil greatly influenced the plant root infection by AM fungi.展开更多
The coronavirus disease that outbreak in 2019 has caused various health issues.According to the WHO,the first positive case was detected in Bangladesh on 7th March 2020,but while writing this paper in June 2021,the to...The coronavirus disease that outbreak in 2019 has caused various health issues.According to the WHO,the first positive case was detected in Bangladesh on 7th March 2020,but while writing this paper in June 2021,the total confirmed,recovered,and death cases were 826922,766266 and 13118,respectively.Due to the emergence of COVID-19 in Bangladesh,the country is facing a major public health crisis.Unfortunately,the country does not have a comprehensive health policy to address this issue.This makes it hard to predict how the pandemic will affect the population.Machine learning techniques can help us detect the disease's spread.To predict the trend,parameters,risks,and to take preventive measure in Bangladesh;this work utilized the Recurrent Neural Networks based Deep Learning methodologies like LongShort-Term Memory.Here,we aim to predict the epidemic's progression for a period of more than a year under various scenarios in Bangladesh.We extracted the data for daily confirmed,recovered,and death cases from March 2020 to August 2021.The obtained Root Mean Square Error(RMSE)values of confirmed,recovered,and death cases indicates that our result is more accurate than other contemporary techniques.This study indicates that the LSTM model could be used effectively in predicting contagious diseases.The obtained results could help in explaining the seriousness of the situation,also mayhelp the authorities to take precautionary steps to control the situation.展开更多
The Cuddalore Formation of the Cauvery Basin received siliciclastic detritus from inland areas of the Southern Granulite Terrain(SGT).It represented continental-fluvial sedimentation in the eastern continental margin ...The Cuddalore Formation of the Cauvery Basin received siliciclastic detritus from inland areas of the Southern Granulite Terrain(SGT).It represented continental-fluvial sedimentation in the eastern continental margin of South India during the Miocene.Indian Summer Monsoon was thought to be initiated in the early Miocene and intensified during the middle Miocene causing major climatic shifts in the Indian subcontinent.In the present work,detailed mineralogical and geochemical studies on the siliciclastic Cuddalore Formation have been carried out to understand the provenance and paleoclimatic conditions during the Miocene.The paleocurrent direction,textural immaturity and framework detrital modes of sandstones suggest rapid uplift of basement and sediment source from nearby Madras Block of SGT.Various diagnostic immobile trace element ratios such as Th/Sc,Co/Th,La/Sc,La/Co suggest a tonalite-trondhjemite-granodiorite-charnockite provenance,and somewhat more felsic composition of source area compared to the present upper continental crust(UCC).Rare earth element mixed model suggests that sediments were dominantly(80%)sourced from felsic charnockite,with a minor contribution(20%)from mafic granulites.Higher abundance of advanced-weathering products like kaolinite,very high(>98)chemical index of alteration(CIA)values,severe depletion of mobile elements(Ca,Na,K,Mg,Ba,Rb)in comparison to UCC,significantly higher a Mg,a Ca,a Na,a K,a Sr and a Ba values(higher than the unity),all suggest the extreme chemical weathering in source terrain and/or in the sedimentary basin.Calculations based on CIA show high average surface temperature between 29.3℃and 29.5℃and high mean annual precipitation ranging from 2339 mm/yr to 2467 mm/yr.The geochemical data are consistent with the paleogeographic position of the depositional basin(Cauvery Basin)and suggest the deposition of Cuddalore sediments(the Cuddalore Formation)in a nearequatorial location under a warm climate condition with abundant monsoonal precipitation.展开更多
文摘Forty different medicinal plants were investigated for arbuscular mycorrhizal association in the Rajshahi University Campus in Bangladesh. The results indicated that 35 different plants were infected by AM (arbuscular mycorrhizal) fungi as found by trypan blue staining procedure. The percentage of root colonization by AM fungi varied from 13.3% to 100%. Mangifera indica and Morus indica have maximum percentage of colonization (100%). The intensity of root colonization were abundant in the plants belonging to the families Anacardiaceae, Asclepiadaceae, Moraceae, Leguminosae and Apocynaceae whereas the intensity of colonization of crop roots were moderate and poor belonging to Gramineae and Leguminosae. The presence of greater number of spore in soil was always associated with the incidence of abundant mycelia. In plant roots the formation of spore and mycelia was restricted by low pH. Number of mycorrhizal fungus spores ranged between 35 to100 per 100g air dried soil in different family respective soils. The frequency of mycorrhizal fungus infection showed positive correlation with soil pH, moisture, water holding capacity, texture, total nitrogen, organic carbon, phosphorus, calcium, potassium, and magnesium. Especially phosphorus and nitrogen in the soil greatly influenced the plant root infection by AM fungi.
文摘The coronavirus disease that outbreak in 2019 has caused various health issues.According to the WHO,the first positive case was detected in Bangladesh on 7th March 2020,but while writing this paper in June 2021,the total confirmed,recovered,and death cases were 826922,766266 and 13118,respectively.Due to the emergence of COVID-19 in Bangladesh,the country is facing a major public health crisis.Unfortunately,the country does not have a comprehensive health policy to address this issue.This makes it hard to predict how the pandemic will affect the population.Machine learning techniques can help us detect the disease's spread.To predict the trend,parameters,risks,and to take preventive measure in Bangladesh;this work utilized the Recurrent Neural Networks based Deep Learning methodologies like LongShort-Term Memory.Here,we aim to predict the epidemic's progression for a period of more than a year under various scenarios in Bangladesh.We extracted the data for daily confirmed,recovered,and death cases from March 2020 to August 2021.The obtained Root Mean Square Error(RMSE)values of confirmed,recovered,and death cases indicates that our result is more accurate than other contemporary techniques.This study indicates that the LSTM model could be used effectively in predicting contagious diseases.The obtained results could help in explaining the seriousness of the situation,also mayhelp the authorities to take precautionary steps to control the situation.
文摘The Cuddalore Formation of the Cauvery Basin received siliciclastic detritus from inland areas of the Southern Granulite Terrain(SGT).It represented continental-fluvial sedimentation in the eastern continental margin of South India during the Miocene.Indian Summer Monsoon was thought to be initiated in the early Miocene and intensified during the middle Miocene causing major climatic shifts in the Indian subcontinent.In the present work,detailed mineralogical and geochemical studies on the siliciclastic Cuddalore Formation have been carried out to understand the provenance and paleoclimatic conditions during the Miocene.The paleocurrent direction,textural immaturity and framework detrital modes of sandstones suggest rapid uplift of basement and sediment source from nearby Madras Block of SGT.Various diagnostic immobile trace element ratios such as Th/Sc,Co/Th,La/Sc,La/Co suggest a tonalite-trondhjemite-granodiorite-charnockite provenance,and somewhat more felsic composition of source area compared to the present upper continental crust(UCC).Rare earth element mixed model suggests that sediments were dominantly(80%)sourced from felsic charnockite,with a minor contribution(20%)from mafic granulites.Higher abundance of advanced-weathering products like kaolinite,very high(>98)chemical index of alteration(CIA)values,severe depletion of mobile elements(Ca,Na,K,Mg,Ba,Rb)in comparison to UCC,significantly higher a Mg,a Ca,a Na,a K,a Sr and a Ba values(higher than the unity),all suggest the extreme chemical weathering in source terrain and/or in the sedimentary basin.Calculations based on CIA show high average surface temperature between 29.3℃and 29.5℃and high mean annual precipitation ranging from 2339 mm/yr to 2467 mm/yr.The geochemical data are consistent with the paleogeographic position of the depositional basin(Cauvery Basin)and suggest the deposition of Cuddalore sediments(the Cuddalore Formation)in a nearequatorial location under a warm climate condition with abundant monsoonal precipitation.
