GIS-based spatial analysis for lightning scenario in Bangladesh.

Bangladesh has witnessed alarmingly rising lightning frequency, particularly during pre-monsoon and monsoon seasons. This has resulted in significant annual death tolls from lightning strikes over the past decade. Recognizing this crisis, the country officially declared lightning casualties a natural disaster in 2016. This study delves deeper into the landscape of lightning fatalities and causalities in Bangladesh. Utilizing secondary data sources, this research introduces a unique approach by integrating Bangladesh Meteorological Department (BMD) data and NASA's Lightning Imaging Sensor (LIS) data from the International Space Station's (ISS) Near-real Time (NRT) mission. This combined dataset allows for a more comprehensive analysis. Furthermore, Geographic Information Systems (GIS) was employed to analyze spatial distributions and generate maps. The Inverse Distance Weighted (IDW) interpolation tool was used to create detailed spatial distribution maps of lightning fatalities, thunderstorm days (TSDs), and lightning flash frequency (LFF) across Bangladesh. The analysis revealed that farmers and fishermen were the most vulnerable populations, with the northeastern regions experiencing the highest impact. Sylhet division emerged as the area with the most fatalities, highlighting the northeastern zone's susceptibility. The study also identified monsoons as the period with the highest occurrences of lightning deaths and injuries. By combining innovative data integration and spatial analysis, this study offers valuable insights into the alarming trend of lightning fatalities in Bangladesh. These findings can inform targeted prevention strategies and interventions to safeguard vulnerable populations and communities.

Net benefit of diagnostic tests for multistate diseases: an indicator variables approach.

A limitation of the common measures of diagnostic test performance, such as sensitivity and specificity, is that they do not consider the relative importance of false negative and false positive test results, which are likely to have different clinical consequences. Therefore, the use of classification or prediction measures alone to compare diagnostic tests or biomarkers can be inconclusive for clinicians. Comparing tests on net benefit can be more conclusive because clinical consequences of misdiagnoses are considered. The literature suggested evaluating the binary diagnostic tests based on net benefit, but did not consider diagnostic tests that classify more than two disease states, e.g., stroke subtype (large-artery atherosclerosis, cardioembolism, small-vessel occlusion, stroke of other determined etiology, stroke of undetermined etiology), skin lesion subtype, breast cancer subtypes (benign, mass, calcification, architectural distortion, etc.), METAVIR liver fibrosis state (F0- F4), histopathological classification of cervical intraepithelial neoplasia (CIN), prostate Gleason grade, brain injury (intracranial hemorrhage, mass effect, midline shift, cranial fracture) . Other diseases have more than two stages, such as Alzheimer's disease (dementia due to Alzheimer's disease, mild cognitive disability (MCI) due to Alzheimer's disease, and preclinical presymptomatics due to Alzheimer's disease). In diseases with more than two states, the benefits and risks may vary between states. This paper extends the net-benefit approach of evaluating binary diagnostic tests to multi-state clinical conditions to rule-in or rule-out a clinical condition based on adverse consequences of work-up delay (due to false negative test result) and unnecessary workup (due to false positive test result). We demonstrate our approach with numerical examples and real data.

The Geriatric Nutritional Risk Index Predicts Postoperative Outcomes in Bladder Cancer: A Propensity Score-Matched Analysis.

PURPOSE: The Geriatric Nutritional Risk Index (GNRI) is a simple screening tool to predict nutrition-related risk of morbidity and mortality in older patients. We assessed whether preoperative GNRI was associated with 30-day complications after radical cystectomy (RC). MATERIALS AND METHODS: Using the American College of Surgeons National Surgical Quality Improvement Program database, we identified patients 65 years or older who underwent RC for the treatment of bladder cancer between 2007 and 2019. Patients were dichotomized into at-risk (GNRI ≤98) or no-risk (GNRI >98) groups. Using propensity score matching, the 2 groups were compared for baseline differences and 30-day outcomes. We evaluated GNRI as an independent predictor of postoperative complications using multivariable logistic regression analysis. RESULTS: We identified 2,926 patients eligible for analysis. After propensity score matching, patients in the at-risk GNRI group had higher rates of any complication (p=0.017), blood transfusion (p=0.002), extended length of stay (p=0.004) and nonhome discharge (p <0.001). Multivariable logistic regression analysis revealed that a decreasing GNRI is an independent prognostic factor for mortality (OR 1.05, 95% CI 1.01-1.08, p=0.009), blood transfusion (OR 1.03, 95% CI 1.02-1.04, p <0.001), pneumonia (OR 1.04, 95% CI 1.01-1.07, p=0.013), extended length of stay (OR 1.03, 95% CI 1.02-1.05, p <0.001) and nonhome discharge (OR 1.04, 95% CI 1.03-1.06, p <0.001). CONCLUSIONS: We demonstrate that nutritional status evaluated by GNRI predicts 30-day complications after RC.

A science framework (SF) for agricultural sustainability.

The significance of Science Framework (SF) to date is receiving more acceptances all over the world to address agricultural sustainability. The professional views, however, advocate that the SF known as Mega Science Framework (MSF) in the transitional economies is not converging effectively in many ways for the agricultural sustainability. Specially, MSF in transitional economies is mostly incapable to identify barriers in agricultural research, inadequate to frame policy gaps with the goal of strategizing the desired sustainability in agricultural technology and innovation, inconsistent in finding to identify the inequities, and incompleteness to rebuild decisions. Therefore, this study critically evaluates the components of MSF in transitional economies and appraises the significance, dispute and illegitimate issue to achieve successful sustainable development. A sound and an effective MSF can be developed when there is an inter-linkage within principal components such as of (a) national priorities, (b) specific research on agricultural sustainability, (c) adequate agricultural research and innovation, and (d) alternative policy alteration. This maiden piece of research which is first its kind has been conducted in order to outline the policy direction to have an effective science framework for agricultural sustainability.