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The aim of this research is to highlight the various factors relating to the water conflict among the riparian countries in the Ganges basin and to examine the potential benefits of integrated water development. Lack of cooperation between the nations involved who promote a nationalistic approach for the management of the basin have made integrated development difficult. This paper examines the issues related to the utilization of the Ganges water resources, regional water-based development potentials and views of riparian countries on integrated Ganges basin management. It identifies four types of prospective benefit from integrated Ganges basin management: benefits to the river; benefits from the river; reducing costs because of the river; and benefits beyond the river. Finally, it recommends guidelines to overcome the constraints to integrated Ganges management and, hence, achieve overall regional development. This paper stresses the need to develop an integrated water management approach intended to foster regional development and overcome the prospect of severe water conflict along the Ganges basin. [ABSTRACT FROM AUTHOR]

• A compartmental mathematical model has been proposed in this paper incorporating all possible non-pharmaceutical intervention policies. • Short-term projection results have been illustrated for Bangladesh and India. • All necessary graphical simulations have been performed with the help of Caputo–Fabrizio fractional derivatives. • Optimal control problem for fractional system has been designed and the existence of unique solution has also been showed by using Picard–Lindelof technique. When the entire world is eagerly waiting for a safe, effective and widely available COVID-19 vaccine, unprecedented spikes of new cases are evident in numerous countries. To gain a deeper understanding about the future dynamics of COVID-19, a compartmental mathematical model has been proposed in this paper incorporating all possible non-pharmaceutical intervention strategies. Model parameters have been calibrated using sophisticated trust-region-reflective algorithm and short-term projection results have been illustrated for Bangladesh and India. Control reproduction numbers (R c) have been calculated in order to get insights about the current epidemic scenario in the above-mentioned countries. Forecasting results depict that the aforesaid countries are having downward trends in daily COVID-19 cases. Nevertheless, as the pandemic is not over in any country, it is highly recommended to use efficacious face coverings and maintain strict physical distancing in public gatherings. All necessary graphical simulations have been performed with the help of Caputo–Fabrizio fractional derivatives. In addition, optimal control strategies for fractional system have been designed and the existence of unique solution has also been showed using Picard–Lindelof technique. Finally, unconditional stability of the fractional numerical technique has been proved. [ABSTRACT FROM AUTHOR]

Climate change is one of the drivers of change in the Ganges River Basin, together with population growth, economic development and water management practices. These changing circumstances have a significant impact on key social and economic sectors of the basin, largely through changes in water quantity, quality and timing of availability. This paper evaluates the impact of water on changing circumstances in three sectors of the Ganges Basin - agriculture, ecosystems and energy. Given the inherent interconnectedness of these core sectors and the cross-cutting impact of changing circumstances on water resources, we argue that adaptation should not be viewed as a separate initiative, but rather as a goal and perspective incorporated into every level of planning and decision making. Adaptation to changing circumstances will need to be closely linked to water resource management and will require significant collaboration across the sectors. [ABSTRACT FROM AUTHOR]

The world is suffering from an existential global health crisis known as the COVID-19 pandemic. Countries like India, Bangladesh, and other developing countries are still having a slow pace in the detection of COVID-19 cases. Therefore, there is an urgent need for fast detection with clear visualization of infection is required using which a suspected patient of COVID-19 could be saved. In the recent technological advancements, the fusion of deep learning classifiers and medical images provides more promising results corresponding to traditional RT-PCR testing while making detection and predictions about COVID-19 cases with increased accuracy. In this paper, we have proposed a deep transfer learning algorithm that accelerates the detection of COVID-19 cases by using X-ray and CT-Scan images of the chest. It is because, in COVID-19, initial screening of chest X-ray (CXR) may provide significant information in the detection of suspected COVID-19 cases. We have considered three datasets known as 1) COVID-chest X-ray, 2) SARS-COV-2 CT-scan, and 3) Chest X-Ray Images (Pneumonia). In the obtained results, the proposed deep learning model can detect the COVID-19 positive cases in ≤ 2 seconds which is faster than RT-PCR tests currently being used for detection of COVID-19 cases. We have also established a relationship between COVID-19 patients along with the Pneumonia patients which explores the pattern between Pneumonia and COVID-19 radiology images. In all the experiments, we have used the Grad-CAM based color visualization approach in order to clearly interpretate the detection of radiology images and taking further course of action. [ABSTRACT FROM AUTHOR]