Showing papers by "Faisal Hossain published in 2023"
TL;DR: In this paper , the authors integrated the so-called Forecasting Inundation Extents using Rotated empirical orthogonal function analysis (FIER) framework with an altimetry-based operational Mekong River level forecasting system and built an operational web application, FIER-Mekong, (https://fier-mekong.streamlit.app/) that generates daily skillful forecasted inundation extents and depths in about 3 and 30 seconds, respectively, with up to 18-day lead times.
Abstract: In the Lower Mekong River Basin floodplains, rice cultivation is highly crucial for regional and global food security. However, prolonged flooding can pose damage to rice cultivation and other socio-economic aspects. Yet, there is no rapid operational inundation forecasting system that can help decision-makers proactively mitigate flood damages. Here, we integrated the so-called Forecasting Inundation Extents using Rotated empirical orthogonal function analysis (FIER) framework with an altimetry-based operational Mekong River level forecasting system and built an operational web application, FIER-Mekong, (https://fier-mekong.streamlit.app/) that generates daily skillful forecasted inundation extents (>70% of critical success index) and depths in about 3 and 30 seconds, respectively, with up to 18-day lead times. One of its applications, predicting flood-induced rice economic losses, is also presented. Had FIER-Mekong being adopted, we estimated that the rice damages, up to 87 and 53 million US dollars during the 2020 and 2021 harvest time, respectively, could have been avoided.
2 citations
TL;DR: In this article , a volatile memory-based solution for application analysis is presented in order to record the true working of the application, a time-based memory dumps are collected after interactions with an application, and process-specific artifacts are extracted by examining the kernel task structure of memory.
Abstract: The penetration of malicious applications in the Android market has enhanced the significance of designing malware mitigation systems for Android. Malware detection systems are being developed by examining applications using static and dynamic analysis techniques. The use of code obfuscation has highlighted the importance of dynamic analysis as many static analysis schemes can be evaded by code obfuscation strategies. In order to record the true working of the application, a volatile memory-based solution for application analysis is presented in this study. Time-based memory dumps are collected after interactions with an application. Process-specific artifacts of the application under analysis are extracted by examining the kernel task structure of memory. The features in the kernel task structure belong to nine broad categories based on their semantics. An important contribution of the study is the analysis of the kernel task structure for determining the set of effective categories and features for Android malware categorization. Three of the most important categories and fourteen valuable features are reported. The proposed system categorizes the applications into five classes: adware, banking Trojans, riskware, SMS Trojans, and benign. The proposed system is able to categorize applications with an average F1-score of 0.984, which is the highest score reported so far for multiclass Android malware categorization with a minimum number of kernel task structure-based features.
TL;DR: The Mesopotamian region began experiencing a steady decline in the health of its rivers from the 1980s with a series of unfortunate man-made events ranging from wars to uncoordinated dam development as discussed by the authors .
Abstract: It is not an understatement to say that a thriving and healthy river system for the Mesopotamian region means a thriving economy for all with a productive agriculture and a sustainable manufacturing base that needs reliable water supply and cheap power. When looked at from a 30,000 feet from the ground, the Mesopotamian region began experiencing a steady decline in the health of its rivers from the 1980s with a series of unfortunate man-made events ranging from wars to uncoordinated dam development. While there have been many analyses and historical dissection of the current water situation, one question that we all need to ask now is 'How can we restore the Mesopotamian rivers?'
TL;DR: In this paper , an approach to assess severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and past infection was developed, which is based on cysteamine etching-induced fluorescence quenching of bovine serum albumin-protected gold nanoclusters.
Abstract: An approach to assess severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (and past infection) was developed. For virus detection, the SARS-CoV-2 virus nucleocapsid protein (NP) was targeted. To detect the NP, antibodies were immobilized on magnetic beads to capture the NPs, which were subsequently detected using rabbit anti-SARS-CoV-2 nucleocapsid antibodies and alkaline phosphatase (AP)-conjugated anti-rabbit antibodies. A similar approach was used to assess SARS-CoV-2-neutralizing antibody levels by capturing spike receptor-binding domain (RBD)-specific antibodies utilizing RBD protein-modified magnetic beads and detecting them using AP-conjugated anti-human IgG antibodies. The sensing mechanism for both assays is based on cysteamine etching-induced fluorescence quenching of bovine serum albumin-protected gold nanoclusters where cysteamine is generated in proportion to the amount of either SARS-CoV-2 virus or anti-SARS-CoV-2 receptor-binding domain-specific immunoglobulin antibodies (anti-RBD IgG antibodies). High sensitivity can be achieved in 5 h 15 min for the anti-RBD IgG antibody detection and 6 h 15 min for virus detection, although the assay can be run in "rapid" mode, which takes 1 h 45 min for the anti-RBD IgG antibody detection and 3 h 15 min for the virus. By spiking the anti-RBD IgG antibodies and virus in serum and saliva, we demonstrate that the assay can detect the anti-RBD IgG antibodies with a limit of detection (LOD) of 4.0 and 2.0 ng/mL in serum and saliva, respectively. For the virus, we can achieve an LOD of 8.5 × 105 RNA copies/mL and 8.8 × 105 RNA copies/mL in serum and saliva, respectively. Interestingly, this assay can be easily modified to detect myriad analytes of interest.
TL;DR: In this paper , a sensor capable of quantifying both anti-SARS-CoV-2 spike receptor-binding domain (RBD) antibody levels and the severe acute respiratory syndrome coronavirus 2 virus in saliva and serum was developed.
Abstract: A sensor capable of quantifying both anti-SARS-CoV-2 spike receptor-binding domain (RBD) antibody levels and the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus in saliva and serum was developed. This was accomplished by exploiting the enzymatic reaction of maltose and orthophosphate (PO43–) in the presence of maltose phosphorylase to generate an equivalent amount of glucose that was detected using a commercial glucometer test strip and a potentiostat. Important for this approach is the ability to generate PO43– in an amount that is directly related to the concentration of the analytes. RBD-modified magnetic microparticles were used to capture anti-SARS-CoV-2 spike RBD antibodies, while particles modified with anti-SARS-CoV-2 nucleocapsid antibodies were used to capture SARS-CoV-2 nucleocapsid protein from inactivated virus samples. A magnet was used to isolate and purify the magnetic microparticles (with analyte attached), and alkaline phosphatase-conjugated secondary antibodies were bound to the analytes attached to the respective magnetic microparticles. Finally, through enzymatic reactions, specific amounts of PO43– (and subsequently glucose) were generated in proportion to the analyte concentration, which was then quantified using a commercial glucometer test strip. Utilizing glucose test strips makes the sensor relatively inexpensive, with a cost per test of ∼US $7 and ∼US $12 for quantifying anti-SARS-CoV-2 spike RBD antibody and SARS-CoV-2, respectively. Our sensor exhibited a limit of detection of 0.42 ng/mL for anti-SARS-CoV-2 spike RBD antibody, which is sensitive enough to quantify typical concentrations of antibodies in COVID-19-infected or vaccinated individuals (>1 μg/mL). The limit of detection for the SARS-CoV-2 virus is 300 pfu/mL (5.4 × 106 RNA copies/mL), which exceeds the performance recommended by the WHO (500 pfu/mL). In addition, the sensor exhibited good selectivity when challenged with competing analytes and could be used to quantify analytes in saliva and serum matrices with an accuracy of >94% compared to RT-qPCR.
TL;DR: The reservoir assessment tool (RAT) as discussed by the authors is a data-driven software that integrates satellite remote sensing with hydrological models, enabling the estimation of key reservoir parameters such as inflow, outflow, surface area, evaporation and storage.
Abstract: In the modern world, dams and the artificial reservoirs behind them serve the increasing demand for water 13 across diverse needs such as agriculture, energy production, and drinking water. As dams continue to proliferate, 14 monitoring water availability influenced by reservoir operations is now of paramount importance. The Reservoir 15 Assessment Tool (RAT) is a data-driven software that integrates satellite remote sensing with hydrological models, 16 enabling the estimation of key reservoir parameters such as inflow, outflow, surface area, evaporation and storage 17 changes. The earliest rendition of RAT (version 1.0) was set up for 1598 reservoirs around the world with limitations 18 in functional robustness, updating frequency and scalability. Some of these limitations on updating frequency and 19 functional robustness were addressed in version 2.0 that was later made operational for the inter-governmental agency 20 of the Mekong River Commission. Recognizing the need for scalability to mobilize the global water management 21 community to benefit from satellite remote sensing, we hereby introduce RAT version 3.0. This version is optimized 22 for accelerating open collaboration among users for continuous improvement and customization of RAT to enable 23 reservoir management breakthroughs. RAT 3.0 represents a wholesale overhaul from the previous versions to 24 empower the global community of users and developers in the spirit of the open-source movement. RAT 3.0 allows 25 reservoir monitoring advancements and new functional developments that can be freely exchanged and seamlessly 26 integrated for continuous evolution of the software. A centralized web application has also been established to 27 facilitate the storage and dissemination of global reservoir monitoring information along with comprehensive training 28 resources. RAT 3.0 aspires to usher the traditional water management community into the era of satellite remote 29 sensing. The global impact of the software can be expected to increase as uptake spreads, enabling a more sustainable 30 and equitable utilization of our planet's water resources. 31 32