MECHANISMS UNDERLYING CONTROL OF ANTI-MICROBIAL IMMUNITY BY ACETYLCHOLINESTERASE INHIBITION

Inflammation is a crucial defense mechanism that protects the body from the devastating effects of invading pathogens. However, an unrestrained inflammatory reaction may result in systemic manifestations with dire consequences to the host. The extent of activation of the inflammatory response is tightly regulated through immunological and neural pathways. Previously, we demonstrated that cholinergic stimulation confers enhanced protection in experimental animals orally infected with a lethal dose of Salmonella typhymurium. In this study, we investigated the mechanism by which this enhanced protection takes place. We showed that cholinergic stimulation enhanced host survival following oral-route infection, which correlated with significantly reduced bacterial load in target organs, including livers and spleens. Enhanced protection was not due to increased gut motility or rapid bacterial clearance from the GI tract. Moreover, protection against bacterial infection was lost when the animals were infected systemically, suggesting that the acetylcholine-mediated protective effect was mostly confined to the gut mucosal tissue. In vivo imaging demonstrated more localized infection and delay in bacterial dissemination into systemic organs in mice pre-treated with acetylcholinesterase inhibitors. Morphological analysis of the small intestine (ileum) showed that acetylcholinesterase inhibition induced the degranulation of goblet cells and Paneth cells, two specialized secretory cells involved in innate immunity. Our findings demonstrate a crucial pathway between neural and immune systems that acts at the mucosal interface to protect the host against invading pathogens

Investigating IoT Middleware Platforms for Smart Application Development

With the growing number of Internet of Things (IoT) devices, the data generated through these devices is also increasing. By 2030, it is been predicted that the number of IoT devices will exceed the number of human beings on earth. This gives rise to the requirement of middleware platform that can manage IoT devices, intelligently store and process gigantic data generated for building smart applications such as Smart Cities, Smart Healthcare, Smart Industry, and others. At present, market is overwhelming with the number of IoT middleware platforms with specific features. This raises one of the most serious and least discussed challenge for application developer to choose suitable platform for their application development. Across the literature, very little attempt is done in classifying or comparing IoT middleware platforms for the applications. This paper categorizes IoT platforms into four categories namely-publicly traded, open source, developer friendly and end-to-end connectivity. Some of the popular middleware platforms in each category are investigated based on general IoT architecture. Comparison of IoT middleware platforms in each category, based on basic, sensing, communication and application development features is presented. This study can be useful for IoT application developers to select the most appropriate platform according to their application requirement

The Methodologies and Main Challenges of Assessment the Multi-Hazard Interaction and Risk Management Associated with Roads Infrastructures and Dam Safety: A Review

The idea of multi-hazard interactions and risk assessment, particularly in relation to both natural hazards and hazards triggered by anthropogenic processes, has been widely used, especially in recent decades. Numerous areas worldwide, as well as various sectors, face exposure to multiple hazards. These hazards encompass natural phenomena like floods, earthquakes, hurricanes, and more. In comparison, the human-induced or anthropogenic processes associated with infrastructure development, along with other potential human activities such as, land and cover use change, contribute to the overall hazard landscape. Both natural hazards and anthropogenic-induced directly led to infrastructure collapse and loss of functionality with other consequences for human lives, economy, beside the environment impacts. Limited studies have been conducted on the implementation of the comprehensive multi-hazard interaction approach, which is globally or regionally required, along with detailed studies on the interaction between different multi-hazard sources and their interrelationships in short-term or long-term scenarios. The current research aims to review previous literature and studies on the multi-hazard interaction approach, methodologies of visualization and classification, as well as explores the potential of multi-hazard associated with road networks, infrastructures, and dams. The research utilizes simulation various models and tools such as, Geographic Information System (GIS) beside Remote Sensing (Rs) techniques. The current study concludes that using multi-hazard maps, hazard matrix, and fragility curves represents highly valuable and very useful and flexible tools for implementing and visualization hot spot areas exposure by multi-hazard consequences and vulnerability analysis for short and long-term scenarios. In addition, the current review highlighted for development a holistic conceptual framework for multi-hazard and risk assessment associated with hydraulic structures such as dams, road networks and infrastructures with hazard exposure analysis to be used as tools for a decision support system (DSS) in order to develop urban resilience, risk management and hazard mitigations

A New Framework for Distance-based Functional Clustering

We develop a new framework for clustering functional data, based on a distance matrix similar to the approach in clustering multivariate data using spectral clustering. First, we smooth the raw observations using appropriate smoothing techniques with desired smoothness, through a penalized fit. The next step is to create an optimal distance matrix either from the smoothed curves or their available derivatives. The choice of the distance matrix depends on the nature of the data. Finally, we create and implement the spectral clustering algorithm. We applied our newly developed approach, Functional Spectral Clustering (FSC) on sets of simulated and real data. Our proposed method showed better performance than existing methods with respect to accuracy rates

A New Framework for Distance-based Functional Clustering

We develop a new framework for clustering functional data, based on a distance matrix similar to the approach in clustering multivariate data using spectral clustering. First, we smooth the raw observations using appropriate smoothing techniques with desired smoothness, through a penalized fit. The next step is to create an optimal distance matrix either from the smoothed curves or their available derivatives. The choice of the distance matrix depends on the nature of the data. Finally, we create and implement the spectral clustering algorithm. We applied our newly developed approach, Functional Spectral Clustering (FSC) on sets of simulated and real data. Our proposed method showed better performance than existing methods with respect to accuracy rates

The Methodologies and Main Challenges of Assessment the Multi-Hazard Interaction and Risk Management Associated with Roads Infrastructures and Dam Safety: A Review

The idea of multi-hazard interactions and risk assessment, particularly in relation to both natural hazards and hazards triggered by anthropogenic processes, has been widely used, especially in recent decades. Numerous areas worldwide, as well as various sectors, face exposure to multiple hazards. These hazards encompass natural phenomena like floods, earthquakes, hurricanes, and more. In comparison, the human-induced or anthropogenic processes associated with infrastructure development, along with other potential human activities such as, land and cover use change, contribute to the overall hazard landscape. Both natural hazards and anthropogenic-induced directly led to infrastructure collapse and loss of functionality with other consequences for human lives, economy, beside the environment impacts. Limited studies have been conducted on the implementation of the comprehensive multi-hazard interaction approach, which is globally or regionally required, along with detailed studies on the interaction between different multi-hazard sources and their interrelationships in short-term or long-term scenarios. The current research aims to review previous literature and studies on the multi-hazard interaction approach, methodologies of visualization and classification, as well as explores the potential of multi-hazard associated with road networks, infrastructures, and dams. The research utilizes simulation various models and tools such as, Geographic Information System (GIS) beside Remote Sensing (Rs) techniques. The current study concludes that using multi-hazard maps, hazard matrix, and fragility curves represents highly valuable and very useful and flexible tools for implementing and visualization hot spot areas exposure by multi-hazard consequences and vulnerability analysis for short and long-term scenarios. In addition, the current review highlighted for development a holistic conceptual framework for multi-hazard and risk assessment associated with hydraulic structures such as dams, road networks and infrastructures with hazard exposure analysis to be used as tools for a decision support system (DSS) in order to develop urban resilience, risk management and hazard mitigations