Molecular characterization of sweet potato(Ipomoea batatas[L.]Lam)germplasms for desirable traits by using simple sequence repeats markers

Every breeding program that aims to create new and improved cultivars with desired traits mostly relies on information related to genetic diversity.Therefore,molecular characterization of germplasms is important to obtain target cultivars with desirable traits.Sweet potato[Ipomoea batatas(L.)Lam]is widely considered the world’s most important crop,with great diversity in morphological and phenotypic traits.The genetic diversity of 20 sweet potato germplasms originating from Bangladesh,CIP,Philippines,Taiwan,and Malaysia were compared,which was accomplished by genetic diversity analysis by exploring 20 microsatellite DNA markers for germplasm characterization and utilization.This information was effective in differentiating or clustering the sweet potato genotypes.A total of 64 alleles were generated using the 20 primers throughout the 20 germplasm samples,with locus IBS97 having the highest number of alleles(5),whereas locus IbU33 had the fewest alleles(2).The alleles varied in size from 105(IbU31)to 213 base pairs(IBS34).The Polymorphism Information Content(PIC)values for the loci IbL46 and IBS97 varied from 0.445 to 0.730.IBS97 has the highest number of effective alleles(3.704),compared to an average of 2.520.The average Shannon’s diversity index(H)was 1.003,ranging from 0.673 in IbU3 to 1.432 in IBS97.The value of gene flow(Nm)varied between 0.000 and 0.005,with an average of 0.003,whereas genetic differentiation(FST-values)ranged between 0.901 and 1.000.The sweet potato germplasm included in this study had a broad genetic base.SP1 vs.SP9 and SP12 vs.SP18 germplasm pairings had the greatest genetic distance(GD=0.965),while SP1 vs.SP2 germplasm couples had the least genetic diversity(GD=0.093).Twenty genotypes were classified into two groups in the UPGMA dendrogram,with 16 genotypes classified as group“A”and the remaining four genotypes,SP10,SP18,SP19,and SP20,classified as group“B.”According to cluster analysis,the anticipated heterozygosity(gene diversity)of Nei(1973)was 0.591 on average.In summary,SSR markers successfully evaluated the genetic relationships among the sweet potato accessions used and generated a high level of polymorphism.The results of the present study will be useful for the management of germplasm,improvement of the current breeding strategies,and the release of new cultivars as varieties.

Post-Operative Mortality after Ileal Perforation at a Teaching Hospital in Dhaka City

Background: Ileal perforation is a very critical condition. Objectives: The purpose of the present study was to see the post-operative mortality after ileal perforation. Methodology: This prospective cohort study was conducted in the Department of Surgery at Dhaka Medical College Hospital, Dhaka, Bangladesh from September 2000 to December 2002 for period of 2 years and 3 months. All the patients presented with ileal perforation at any age with both sexes were included in this study. Patients were selected consecutively and the patients who showed ileal perforation at laparotomy were included in this study. Preoperative diagnosis was based on detailed history, complete physical examinations supported by plain x-ray abdomen in erect posture including both domes of diaphragm. After immediate resuscitation surgical treatment was undertaken as soon as possible following admission in all cases. The patients were followed up and the mortality profiles were recorded after surgical intervention. Result: Out of 53 patients having postoperative complications 38 patients were survived and 15 patients were expired. So total survivors were 85% and non-survivors 15%. In this study most of the mortality (12%) was attributed to septicemia and mode of death was multiple organ failure. Respiratory complications caused 2% mortality one patient died of ARDS and another elderly patient with preexisting bronchial asthma developed respiratory failure and was unresponsive to treatment. One death was related to faecal fistula followed by severe fluid, electrolyte and acid-base imbalance with peritonitis and gross sepsis. Conclusion: In conclusion, the mortality is significantly high due to septicemia, ARDS and faecal fistula.

Hamiltonian Formulation for Water Wave Equation

This paper concerns the development and application of the Hamiltonian function which is the sum of kinetic energy and potential energy of the system. Two dimensional water wave equations for irrotational, incompressible, inviscid fluid have been constructed in cartesian coordinates and also in cylindrical coordinates. Then Lagrangian function within a certain flow region is expanded under the assumption that the dispersion μ and the nonlinearity ε satisfied . Using Hamilton’s principle for water wave evolution Hamiltonian formulation is derived. It is obvious that the motion of the system is conservative. Then Hamilton’s canonical equation of motion is also derived.

Bayesian Optimized LightGBM model for predicting the fundamental vibrational period of masonry infilled RC frames

The precise prediction of the fundamental vibrational period for reinforced concrete(RC)buildings with infilled walls is essential for structural design,especially earthquake-resistant design.Machine learning models from previous studies,while boasting commendable accuracy in predicting the fundamental period,exhibit vulnerabilities due to lengthy training times and inherent dependence on pre-trained models,especially when engaging with continually evolving data sets.This predicament emphasizes the necessity for a model that adeptly balances predictive accuracy with robust adaptability and swift data training.The latter should include consistent re-training ability as demanded by realtime,continuously updated data sets.This research implements an optimized Light Gradient Boosting Machine(LightGBM)model,highlighting its augmented predictive capabilities,realized through the astute use of Bayesian Optimization for hyperparameter tuning on the FP4026 research data set,and illuminating its adaptability and efficiency in predictive modeling.The results show that the R^(2) score of LightGBM model is 0.9995 and RMSE is 0.0178,while training speed is 23.2 times faster than that offered by XGBoost and 45.5 times faster than for Gradient Boosting.Furthermore,this study introduces a practical application through a streamlit-powered,web-based dashboard,enabling engineers to effortlessly utilize and augment the model,contributing data and ensuring precise fundamental period predictions,effectively bridging scholarly research and practical applications.