Introduction: The role of high-sensitive cardiac troponin (hs-cTn) assays has higher analytical precision at lower concentrations to detect myocardial injury. The changes in troponin concentration between two assays c...Introduction: The role of high-sensitive cardiac troponin (hs-cTn) assays has higher analytical precision at lower concentrations to detect myocardial injury. The changes in troponin concentration between two assays conducted within a specified time interval refers to “Delta troponin”. This study aimed to assess the correlation between the complexity of coronary lesions and significant delta high-sensitivity troponin I levels in patients with non-ST elevation myocardial infarction. Methods: This cross-sectional study was conducted in the Department of Cardiology, Ibrahim Cardiac Hospital & Research Institute, Dhaka, Bangladesh from July 2022 to June 2023. A total of 70 patients with significant delta hs-cTnI were included and divided into two groups: Group-A (n = 36) with a delta hs-cTnI rise between >20% to 49%, and Group-B (n = 34) with a delta hs-cTnI rise ≥ 50%. Coronary angiography was performed and the SYNTAX Score was calculated for both groups. Data were collected using SPSS version 25.0. Result: Patients with a high-rise delta cTnI (≥50%) showed a significantly higher proportion of lesions in major coronary arteries LCx and LAD compared to those with a low-rise of cTnI (20% - 49%) (p = 0.007 and 0.004, respectively). The presence of triple vessel diseases was higher in the former group than in the latter (p 22, compared to none in the low-rise group (p Conclusion: A high rise in delta hs-cTnI is linked to higher SYNTAX scores, signifying complex coronary lesions in NSTEMI patients, with a significant linear correlation between them. Patients with a high rise in delta cTnI may exhibit more significant coronary artery lesions and triple vessel diseases compared to those with a low rise in cTnI.展开更多
An infiltration characteristic model was developed by using the modified Kostiakov method for the Agricultural Engineering demonstration field of Bangladesh Agricultural Research Institute (BARI). The constant values ...An infiltration characteristic model was developed by using the modified Kostiakov method for the Agricultural Engineering demonstration field of Bangladesh Agricultural Research Institute (BARI). The constant values a, α, and b of the equation for accumulated infiltration y = atα + b were 9.12, 0.683, and 0.145, respectively. The average value of percentage of error between the actual and calculated values by the model was only 0.134 and showed very good agreement between the model and the field values of accumulated infiltration. This model will be very helpful for making a good irrigation scheduling and best water management.展开更多
Objective: To explore a common B-and T-cell epitope-based vaccine that can elicit an immune response against encephalitis causing genus Henipaviruses, Hendra virus(He V) and Nipah virus(Ni V). Methods: Membrane protei...Objective: To explore a common B-and T-cell epitope-based vaccine that can elicit an immune response against encephalitis causing genus Henipaviruses, Hendra virus(He V) and Nipah virus(Ni V). Methods: Membrane proteins F, G and M of He V and Ni V were retrieved from the protein database and subjected to different bioinformatics tools to predict antigenic B-cell epitopes. Best B-cell epitopes were then analyzed to predict their T-cell antigenic potentiality. Antigenic B-and T-cell epitopes that shared maximum identity with He V and Ni V were selected. Stability of the selected epitopes was predicted. Finally, the selected epitopes were subjected to molecular docking simulation with HLA-DR to confirm their antigenic potentiality in silico. Results: One epitope from G proteins, one from M proteins and none from F proteins were selected based on their antigenic potentiality. The epitope from the G proteins was stable whereas that from M was unstable. The M-epitope was made stable by adding flanking dipeptides. The 15-mer G-epitope(VDPLRVQWRNNSVIS) showed at least 66% identity with all Ni V and He V G protein sequences, while the 15-mer M-epitope(GKLEFRRNNAIAFKG) with the dipeptide flanking residues showed 73% identity with all Ni V and He V M protein sequences available in the database. Molecular docking simulation with most frequent MHC class-II(MHC II) and class-I(MHC I) molecules showed that these epitopes could bind within HLA binding grooves to elicit an immune response. Conclusions: Data in our present study revealed the notion that the epitopes from G and M proteins might be the target for peptide-based subunit vaccine design against He V and Ni V. However, the biochemical analysis is necessary to experimentally validate the interaction of epitopes individually with the MHC molecules through elucidation of immunity induction.展开更多
This paper presents the improvement of the fuzzy inference model primarily developed for predicting rainfall with data from United States Department of Agriculture (USDA) Soil Climate Analysis Network (SCAN) Station a...This paper presents the improvement of the fuzzy inference model primarily developed for predicting rainfall with data from United States Department of Agriculture (USDA) Soil Climate Analysis Network (SCAN) Station at the Alabama Agricultural and Mechanical University (AAMU) Campus for the year 2004. The primary model was developed with Fuzzy variables selected based on the degree of association of different factors with various combinations causing rainfall. An increase in wind speed (WS) and a decrease in temperature (TP) when compared between the ith and (i-1)th day were found to have a positive relation with rainfall. Results of the model showed better performance after introducing the threshold values of 1) relative humidity (RH) of the ith day;2) humidity increase (HI) when compared between the ith and (i-1)th day;and 3) product (P) of increase in wind speed (WS) and decrease in temperature (TP) when compared between the ith and (i-1)th day. In case of the improved model, errors between actual and calculated amount of rainfall (RF) were 1.20%, 2.19%, and 9.60% when using USDA-SCAN data from AAMU campus for years 2003, 2004 and 2005, respectively. The improved model was tested at William A. Thomas Agricultural Research Station (WTARS) and Bragg farm in Alabama to check the applicability of the model. The errors between the actual and calculated amount of rainfall (RF) were 3.20%, 5.90%, and 1.66% using USDA-SCAN data from WATARS for years 2003, 2004, and 2005, respectively. Similarly, errors were 10.37%, 11.69%, and 25.52% when using SCAN data from Bragg farm for years 2004, 2005, and 2006, respectively. The primary model yielded the value of error equals 12.35% using USDA- SCAN data from AAMU campus for 2004. The present model performance was proven to be better than the primary model.展开更多
The paper presents occurrence of rainfall using principles of fuzzy set theory and principles of reliability analysis. Both the abstract and the rest of the paper are discussed from these two points of view. First, a ...The paper presents occurrence of rainfall using principles of fuzzy set theory and principles of reliability analysis. Both the abstract and the rest of the paper are discussed from these two points of view. First, a fuzzy inference model for predicting rainfall using scan data from the USDA Soil Climate Analysis Network Station at Alabama Agricultural and Mechanical University (AAMU) campus for the year 2004 is presented. The model further reflects how an expert would perceive weather conditions and apply this knowledge before inferring a rainfall. Fuzzy variables were selected based on judging patterns in individual monthly graphs for 2003 and 2004 and the influence of different variables that caused rainfall. A decrease in temperature (TP) and an increase in wind speed (WS) when compared between the ith and (i ? 1)th day were found to have a positive relation with a rainfall (RF) occurrence in most cases. Therefore, TP and WS were used in the antecedent part of the production rules to predict rainfall (RF). Results of the model showed better performance when threshold values for 1) Relative Humidity (RH) of ith day;2) Humidity Increase (HI) between the ith and (i ? 1)th day;and 3) Product (P) of decrease in temperature (TP) and an increase in wind speed (WS) were introduced. The percentage of error was 12.35 when compared the calculated amount of rainfall with actual amount of rainfall. This is followed by prediction of rainfall using principles of reliability analysis. This is done by comparing theoretical probabilities with experimental probabilities for the occurrence of two main events, namely, Relative Humidity (RH) and Humidity Increase (HI) being in between specified threshold values. The experimental values of probability are falling in between μ ? σ and μ + σ for both RH and HI parameters, where μ is the mean value and σ is the standard deviation.展开更多
文摘Introduction: The role of high-sensitive cardiac troponin (hs-cTn) assays has higher analytical precision at lower concentrations to detect myocardial injury. The changes in troponin concentration between two assays conducted within a specified time interval refers to “Delta troponin”. This study aimed to assess the correlation between the complexity of coronary lesions and significant delta high-sensitivity troponin I levels in patients with non-ST elevation myocardial infarction. Methods: This cross-sectional study was conducted in the Department of Cardiology, Ibrahim Cardiac Hospital & Research Institute, Dhaka, Bangladesh from July 2022 to June 2023. A total of 70 patients with significant delta hs-cTnI were included and divided into two groups: Group-A (n = 36) with a delta hs-cTnI rise between >20% to 49%, and Group-B (n = 34) with a delta hs-cTnI rise ≥ 50%. Coronary angiography was performed and the SYNTAX Score was calculated for both groups. Data were collected using SPSS version 25.0. Result: Patients with a high-rise delta cTnI (≥50%) showed a significantly higher proportion of lesions in major coronary arteries LCx and LAD compared to those with a low-rise of cTnI (20% - 49%) (p = 0.007 and 0.004, respectively). The presence of triple vessel diseases was higher in the former group than in the latter (p 22, compared to none in the low-rise group (p Conclusion: A high rise in delta hs-cTnI is linked to higher SYNTAX scores, signifying complex coronary lesions in NSTEMI patients, with a significant linear correlation between them. Patients with a high rise in delta cTnI may exhibit more significant coronary artery lesions and triple vessel diseases compared to those with a low rise in cTnI.
文摘An infiltration characteristic model was developed by using the modified Kostiakov method for the Agricultural Engineering demonstration field of Bangladesh Agricultural Research Institute (BARI). The constant values a, α, and b of the equation for accumulated infiltration y = atα + b were 9.12, 0.683, and 0.145, respectively. The average value of percentage of error between the actual and calculated values by the model was only 0.134 and showed very good agreement between the model and the field values of accumulated infiltration. This model will be very helpful for making a good irrigation scheduling and best water management.
文摘Objective: To explore a common B-and T-cell epitope-based vaccine that can elicit an immune response against encephalitis causing genus Henipaviruses, Hendra virus(He V) and Nipah virus(Ni V). Methods: Membrane proteins F, G and M of He V and Ni V were retrieved from the protein database and subjected to different bioinformatics tools to predict antigenic B-cell epitopes. Best B-cell epitopes were then analyzed to predict their T-cell antigenic potentiality. Antigenic B-and T-cell epitopes that shared maximum identity with He V and Ni V were selected. Stability of the selected epitopes was predicted. Finally, the selected epitopes were subjected to molecular docking simulation with HLA-DR to confirm their antigenic potentiality in silico. Results: One epitope from G proteins, one from M proteins and none from F proteins were selected based on their antigenic potentiality. The epitope from the G proteins was stable whereas that from M was unstable. The M-epitope was made stable by adding flanking dipeptides. The 15-mer G-epitope(VDPLRVQWRNNSVIS) showed at least 66% identity with all Ni V and He V G protein sequences, while the 15-mer M-epitope(GKLEFRRNNAIAFKG) with the dipeptide flanking residues showed 73% identity with all Ni V and He V M protein sequences available in the database. Molecular docking simulation with most frequent MHC class-II(MHC II) and class-I(MHC I) molecules showed that these epitopes could bind within HLA binding grooves to elicit an immune response. Conclusions: Data in our present study revealed the notion that the epitopes from G and M proteins might be the target for peptide-based subunit vaccine design against He V and Ni V. However, the biochemical analysis is necessary to experimentally validate the interaction of epitopes individually with the MHC molecules through elucidation of immunity induction.
文摘This paper presents the improvement of the fuzzy inference model primarily developed for predicting rainfall with data from United States Department of Agriculture (USDA) Soil Climate Analysis Network (SCAN) Station at the Alabama Agricultural and Mechanical University (AAMU) Campus for the year 2004. The primary model was developed with Fuzzy variables selected based on the degree of association of different factors with various combinations causing rainfall. An increase in wind speed (WS) and a decrease in temperature (TP) when compared between the ith and (i-1)th day were found to have a positive relation with rainfall. Results of the model showed better performance after introducing the threshold values of 1) relative humidity (RH) of the ith day;2) humidity increase (HI) when compared between the ith and (i-1)th day;and 3) product (P) of increase in wind speed (WS) and decrease in temperature (TP) when compared between the ith and (i-1)th day. In case of the improved model, errors between actual and calculated amount of rainfall (RF) were 1.20%, 2.19%, and 9.60% when using USDA-SCAN data from AAMU campus for years 2003, 2004 and 2005, respectively. The improved model was tested at William A. Thomas Agricultural Research Station (WTARS) and Bragg farm in Alabama to check the applicability of the model. The errors between the actual and calculated amount of rainfall (RF) were 3.20%, 5.90%, and 1.66% using USDA-SCAN data from WATARS for years 2003, 2004, and 2005, respectively. Similarly, errors were 10.37%, 11.69%, and 25.52% when using SCAN data from Bragg farm for years 2004, 2005, and 2006, respectively. The primary model yielded the value of error equals 12.35% using USDA- SCAN data from AAMU campus for 2004. The present model performance was proven to be better than the primary model.
文摘The paper presents occurrence of rainfall using principles of fuzzy set theory and principles of reliability analysis. Both the abstract and the rest of the paper are discussed from these two points of view. First, a fuzzy inference model for predicting rainfall using scan data from the USDA Soil Climate Analysis Network Station at Alabama Agricultural and Mechanical University (AAMU) campus for the year 2004 is presented. The model further reflects how an expert would perceive weather conditions and apply this knowledge before inferring a rainfall. Fuzzy variables were selected based on judging patterns in individual monthly graphs for 2003 and 2004 and the influence of different variables that caused rainfall. A decrease in temperature (TP) and an increase in wind speed (WS) when compared between the ith and (i ? 1)th day were found to have a positive relation with a rainfall (RF) occurrence in most cases. Therefore, TP and WS were used in the antecedent part of the production rules to predict rainfall (RF). Results of the model showed better performance when threshold values for 1) Relative Humidity (RH) of ith day;2) Humidity Increase (HI) between the ith and (i ? 1)th day;and 3) Product (P) of decrease in temperature (TP) and an increase in wind speed (WS) were introduced. The percentage of error was 12.35 when compared the calculated amount of rainfall with actual amount of rainfall. This is followed by prediction of rainfall using principles of reliability analysis. This is done by comparing theoretical probabilities with experimental probabilities for the occurrence of two main events, namely, Relative Humidity (RH) and Humidity Increase (HI) being in between specified threshold values. The experimental values of probability are falling in between μ ? σ and μ + σ for both RH and HI parameters, where μ is the mean value and σ is the standard deviation.
