Wireless sensor networks-based solutions for cattle health monitoring : a survey

Wireless Sensor Networks (WSN) are nowadays becoming an active research in different fields. Precise irrigation, agriculture, earthquake, fire monitoring in forests and animal health monitoring are few applications of WSN. Animal health monitoring systems (AHMS) are usually used to monitor physiological parameters such as rumination, heart rate, and body temperature. Traditional methods to monitor animal health such as (traditional surveillance, single observation, and simple tabular and graphic techniques) are not efficient to achieve high performance in the large herds’ management systems. These methods can only provide partial information and introduce a large cost in staffing and physical hardware. Thus, it is of important need to overcome a foresaid draw-back by using alternative low cost, low power consumption sensor nodes, and providing real-time communications at a sensible hardware cost. The objectives of this paper are: reviewing existing WSN solutions for cattle health monitoring models and determining the requirements needed for building an effective WSN model suitable for cattle health monitoring and detect animal diseases. From this review, requirements of the effective WSN-based solution for cattle health monitoring were suggested

Machine Learning approach to repurpose Azacitidine against Covid-19

Background: Since the coronavirus outbreak in 2019, new strains of the virus have evolved, and the Omicron (1.1.529) strain is now prevalent and rapidly spreading globally, prompting scientists to work on developing a novel therapeutic drug that is effective against COVID19. Due to the lag in typical drug development operations, drug repurposing can be chosen as an alternative. We investigated whether Azacitidine, a pyrimidine nucleoside analog of cytidine, which was originally used to treat Acute Leukemia by targeting against the DNA methyltransferase 1 (DNMT1), could be repurposed for the treatment of COVID-19. Methods: To evaluate the efficacy of Azacitidine against COVID-19, we utilized the DrugX pipeline encompassing 14 modules based on network-based, text-mining, and semantic approaches to study various components of the drug repurposing. The SMILES of the Azacitidine was used as the input and the required modules for the study of their chemical properties, gene expression profile, pathways involved in relation to COVID-19, and its interaction with the viral and human proteins were selected for prediction on whether it can be repurposed against COVID-19 or not. Results and conclusion: The CoV-DrugX pipeline concludes the results as 0 or 1, with the exception of the docking modules, which had scores ranging between 0 to 1. Among the 14 modules, 7 modules were scored 1 and 6 modules were scored 0. In addition, we discovered that Azacitidine interacts with DNMT1 and has a binding affinity for Nsp14 viral protein and GAK protein of -7.4 Kcal/mol and -7.3 Kcal/mol, respectively. It also meets the 200 specifications for drug likeliness. Azacitidine was predicted to be involved in host-virus interaction and replication pathways in relation to SARS-CoV-2, as well as having significantly abnormal gene expression during COVID19. Azacitidine was found to have a total SI score of 7.065 and a PI score of 0.507, indicating that it can be considered as a drug target against COVID-19

An assessment of the potential impact of climate change on flood risk in Mumbai

Managing risks from extreme events will be a crucial component of climate change adaptation. In this study, we demonstrate an approach to assess future risks and quantify the benefits of adaptation options at a city-scale, with application to flood risk in Mumbai. In 2005, Mumbai experienced unprecedented flooding, causing direct economic damages estimated at almost two billion USD and 500 fatalities. Our findings suggest that by the 2080s, in a SRES A2 scenario, an 'upper bound' climate scenario could see the likelihood of a 2005-like event more than double. We estimate that total losses (direct plus indirect) associated with a 1-in-100 year event could triple compared with current situation (to $690-$1,890 million USD), due to climate change alone. Continued rapid urbanisation could further increase the risk level. The analysis also demonstrates that adaptation could significantly reduce future losses; for example, estimates suggest that by improving the drainage system in Mumbai, losses associated with a 1-in-100 year flood event today could be reduced by as much as 70%.,We show that assessing the indirect costs of extreme events is an important component of an adaptation assessment, both in ensuring the analysis captures the full economic benefits of adaptation and also identifying options that can help to manage indirect risks of disasters. For example, we show that by extending insurance to 100% penetration, the indirect effects of flooding could be almost halved. We conclude that, while this study explores only the upper-bound climate scenario, the risk-assessment core demonstrated in this study could form an important quantitative tool in developing city-scale adaptation strategies. We provide a discussion of sources of uncertainty and risk-based tools could be linked with decision-making approaches to inform adaptation plans that are robust to climate change