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Maize production requires a large amount of nitrogen (N). However, a greater part of the N used gets lost to the environment as reactive forms including nitrous oxide (N2O). N2O emissions and associated soil-related factors were measured in a maize (Zea mays L.) field in the 5th crop after initiation of the experiment in an annual maize-rice sequence. The treatments comprised two levels of crop residues (no residue, NR vs. 30 cm residue, CR) with four levels of N fertilizers (control; farmers' practice, FP; national recommended dose, RD, and 125% of RD, 1.25 RD). Mean and cumulative N2O emissions increased with N rate coupled with either residue level. The CR coupled with 1.25 RD had 10% higher N2O emissions than the same rate as NR. In contrast, yield-scaled N2O emissions were equal in 1.25 RD coupled with either residue level. However, higher N2O emissions in CR than in NR can be offset by the corresponding improvement in soil elemental quality, e.g. soil organic carbon, total N, P, K and S. The N2O emission factor, ranged from 0.99 to 1.34, and was higher in CR coupled with 1.25 RD than in any other combination suggesting that optimization of N rate is one of the best options to reduce N2O emissions. Maize grain yield was higher in RD and 1.25 RD than in the farmers' practice where the former two were similar to each other. Step-wise multiple regression showed that N application rate, soil organic carbon, total N and pH are the dominant factors controlling N2O emissions. Our results suggest that maize production can benefit from residue retention with the current N rate (RD) for better yield, soil quality and N2O mitigation. Highlights: 1. Optimum fertilizer rate coupled with crop residue reduces N2O emissions.2. N2O emission factors in maize are comparable with the IPCC default value.3. Yield-scaled N2O emissions were similar in fields with and without crop residues.4. Maize yield was higher in crop residue coupled with recommended N rate.5. Recommended N with crop residue incorporation increased soil elemental quality. [ABSTRACT FROM AUTHOR]

Background and Aims: Gastrointestinal (GI) symptoms, common in type 2 diabetes (T2D), are typically bothersome, socially embarrassing, and impact negatively on quality of life. They may also contribute to diabetes distress (DD), but this has never been formally evaluated. We aimed to investigate the relationships between GI symptoms, DD and depressive symptoms in a large cohort of individuals with T2D in Bangladesh. Materials and Methods: 1406 unselected T2D individuals (female 58.8%; mean age 51.0 ± 12.5 years) from four diabetes clinics in Bangladesh completed validated questionnaires evaluating GI symptoms (PAGI‐SYM), DD (DDS‐17) and depressive symptoms (PHQ‐9). Results: 31.1% of participants reported GI symptoms (36.2% females, 23.7% males), while 51.1% had elevated DD and 37.8% depressive symptoms. GI symptoms exhibited independent relationships with both DD and depressive symptoms, and their likelihood was higher among those with DD (OR: 3.6 [2.2–5.6] and with depressive symptoms (OR: 5.9 [3.5–9.9]). Conclusions: GI symptoms are independently associated with both DD and depressive symptoms in people with T2D in Bangladesh. [ABSTRACT FROM AUTHOR]

Background: Cholelithiasis is one of the most common surgical problems throughout the world. Earlier, the prevailing treatment of symptomatic Cholelithiasis was an open cholecystectomy which is almost replaced by laparoscopic cholecystectomy. Although occasionaly switch to open cholecystectomy may require during the procedure which is known as conversion in laparoscopic cholecystectomy. Many factors contribute to the conversion which is not a sign of surgeon's failure rather is a sign of surgeon's good surgical judgment Our objectives are to find out the factors which are associated with conversion and thus reduce conversion rate, preoperative preparation and counseling the patient for conversion in laparoscopic cholecystectomy. Methods: This was a hospital based retrospective study, carried out in department of hepatobiliary & pancreatic surgery department, Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka from January 2008 to December 2009. A total no of SO cases were included in our study which were converted to open cholecystectomy. Cases were collected from the hospital medical records which were retrieved and analyzed. Result: A total no of768 laparoscopic cholecystectomies were attempted during the study period. Out of which SO cases were converted to open cholecystectomy. Thus the conversion rate was 6.5%. Among these the reasons for conversion in both genders were dense adhesion in 22 (2.86%), aberrant anatomy in 10 (1.3%), empyema gall bladder in 4 (0.52%), per operative findings of choledocholithiasis in 3 (0.39%), suspicion of common bile duct injury in 3 (0.39%), others causes of conversion included uncontrolled bleeding 3 (0.39%), thick fibrosed gall bladder 2 (0.26%), accidental bowel injury 2 (0.26%), Type-I choledochal cyst 1 (0.13%) cases. Conclusion: various factors are related to conversion in laparoscopic cholecystectomy. But due to improvement of learning curve, good quality operative equipment, now a day's laparoscopic cholecystectomy is safe method of treatment for gall stone diseases with very low conversion rate. [ABSTRACT FROM AUTHOR]

Financial markets are exposed to sharp price volatility, and defaults and errors, which results in high risks for relevant stakeholders. In such markets, success depends upon the quality and quantity of information available to assist the decision‐making. Artificial intelligence (AI), in this regard, can measure or predict systemic and systematic risk in the financial markets. This research study aims to highlight how the risks can be measured and controlled with the support and integration of modern AI and machine learning mechanisms. By performing a review‐based methodology, the study first presents an explanation of the models, which is followed by proposing a new AI‐based model. The model relies on several financial system's inputs, which include portfolio data, trade data, market data, financial reports, market condition, and sector‐wise data. The systemic and systematic risk is then assessed through a number of outputs that the AI algorithm will process, in the form of an interactive dashboard. The article further tests that model and presents benefits and implications. [ABSTRACT FROM AUTHOR]