The Journal of Solid Waste Technology and Management, Aug 1, 2006
One of the bottlenecks in implementing waste management policies in Chile is the lack of informat... more One of the bottlenecks in implementing waste management policies in Chile is the lack of information on factors correlating with waste generation. Recognising these factors is essential for implementing policies to reduce waste generation. From over 40 global variables indicating ...
A synaptic protein, Ca(2+)/Calmodulin dependent protein kinase II (CaMKII), has complex state tra... more A synaptic protein, Ca(2+)/Calmodulin dependent protein kinase II (CaMKII), has complex state transitions and facilitates the emergence of long term potentiation (LTP), which is highly correlated to memory formation. Two of the state transitions are critical for LTP: (1) threonine 286 autophosphorylation of CaMKII; and (2) binding to N-methyl-d-aspartate receptor (NMDAR) in the postsynaptic density (PSD) to form CaMKII-NMDAR complex. Both of these state transitions retain the activity of CaMKII when the induction signal disappears which is very important for the long-lasting characteristics of LTP. However, the possible relationships between the state transitions in the emergence of LTP are not well understood. We develop a mathematical model of the formation of CaMKII-NMDAR complex with the full state transitions of CaMKII, including the autophosphorylation, based on ordinary differential equations. In addition, we formulate a probabilistic framework for the binding between CaMKII and NMDAR. The model gives accurate predictions of the behaviours of CaMKII in comparisons to the experimental observations. Using the model, we show that: (1) the formation of CaMKII-NMDAR complex is dependent not only on the binding affinity between CaMKII and NMDAR, but also on the translocation of CaMKII into PSD; and (2) the autophosphorylation is not a requirement for the formation of CaMKII-NMDAR complex, but is important for the rapid formation of CaMKII-NMDAR complex during LTP.
This paper describes a novel computational framework for damage detection and regeneration in an ... more This paper describes a novel computational framework for damage detection and regeneration in an artificial tissue of cells resembling living systems. We represent the tissue as an Auto-Associative Neural Network (AANN) consisting of a single layer of perceptron neurons (cells) with local feedback loops. This allows the system to recognise its state and geometry in a form of collective intelligence. Signalling entropy is used as a global (emergent) property characterising the state of the system. The repair system has two submodels - global sensing and local sensing. Global sensing is used to sense the change in whole system state and detect general damage region based on system entropy change. Then, local sensing is applied with AANN to find the exact damage locations and repair the damage. The results show that the method allows robust and efficient damage detection and accurate regeneration.
There are a large number of computer-based tools available to engineers today ranging from Comput... more There are a large number of computer-based tools available to engineers today ranging from Computer Aided Design (CAD) packages to sophisticated computer models to solve problems. In this article we will discuss the role of computer models in taking various decisions related to complex systems such as watersheds, airports and production plants. Some of die systems we deal with are completely human-made with a high degree of certainty and therefore, the models developed for such systems tend to be associated with a high level of confidence among end-users. But for many systems, we have seen healthy scepticism about computer models of those systems. Before we go any further, let us discuss die nature of model development and see how this scepticism emerges.
The Journal of Solid Waste Technology and Management, Aug 1, 2006
One of the bottlenecks in implementing waste management policies in Chile is the lack of informat... more One of the bottlenecks in implementing waste management policies in Chile is the lack of information on factors correlating with waste generation. Recognising these factors is essential for implementing policies to reduce waste generation. From over 40 global variables indicating ...
A synaptic protein, Ca(2+)/Calmodulin dependent protein kinase II (CaMKII), has complex state tra... more A synaptic protein, Ca(2+)/Calmodulin dependent protein kinase II (CaMKII), has complex state transitions and facilitates the emergence of long term potentiation (LTP), which is highly correlated to memory formation. Two of the state transitions are critical for LTP: (1) threonine 286 autophosphorylation of CaMKII; and (2) binding to N-methyl-d-aspartate receptor (NMDAR) in the postsynaptic density (PSD) to form CaMKII-NMDAR complex. Both of these state transitions retain the activity of CaMKII when the induction signal disappears which is very important for the long-lasting characteristics of LTP. However, the possible relationships between the state transitions in the emergence of LTP are not well understood. We develop a mathematical model of the formation of CaMKII-NMDAR complex with the full state transitions of CaMKII, including the autophosphorylation, based on ordinary differential equations. In addition, we formulate a probabilistic framework for the binding between CaMKII and NMDAR. The model gives accurate predictions of the behaviours of CaMKII in comparisons to the experimental observations. Using the model, we show that: (1) the formation of CaMKII-NMDAR complex is dependent not only on the binding affinity between CaMKII and NMDAR, but also on the translocation of CaMKII into PSD; and (2) the autophosphorylation is not a requirement for the formation of CaMKII-NMDAR complex, but is important for the rapid formation of CaMKII-NMDAR complex during LTP.
This paper describes a novel computational framework for damage detection and regeneration in an ... more This paper describes a novel computational framework for damage detection and regeneration in an artificial tissue of cells resembling living systems. We represent the tissue as an Auto-Associative Neural Network (AANN) consisting of a single layer of perceptron neurons (cells) with local feedback loops. This allows the system to recognise its state and geometry in a form of collective intelligence. Signalling entropy is used as a global (emergent) property characterising the state of the system. The repair system has two submodels - global sensing and local sensing. Global sensing is used to sense the change in whole system state and detect general damage region based on system entropy change. Then, local sensing is applied with AANN to find the exact damage locations and repair the damage. The results show that the method allows robust and efficient damage detection and accurate regeneration.
There are a large number of computer-based tools available to engineers today ranging from Comput... more There are a large number of computer-based tools available to engineers today ranging from Computer Aided Design (CAD) packages to sophisticated computer models to solve problems. In this article we will discuss the role of computer models in taking various decisions related to complex systems such as watersheds, airports and production plants. Some of die systems we deal with are completely human-made with a high degree of certainty and therefore, the models developed for such systems tend to be associated with a high level of confidence among end-users. But for many systems, we have seen healthy scepticism about computer models of those systems. Before we go any further, let us discuss die nature of model development and see how this scepticism emerges.
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