The Experts below are selected from a list of 5463 Experts worldwide ranked by ideXlab platform

Andrea Parmeggiani - One of the best experts on this subject based on the ideXlab platform.

  • Motor proteins traffic regulation by supply-Demand Balance of resources
    Physical Biology, 2014
    Co-Authors: Luca Ciandrini, Izaak Neri, Jean-charles Walter, Olivier Dauloudet, Andrea Parmeggiani
    Abstract:

    In cells and in vitro assays the number of motor proteins involved in biological transport processes is far from being unlimited. The cytoskeletal binding sites are in contact with the same finite reservoir of motors (either the cytosol or the flow chamber) and hence compete for recruiting the available motors, potentially depleting the reservoir and affecting cytoskeletal transport. In this work we provide a theoretical framework to study, analytically and numerically, how motor density profiles and crowding along cytoskeletal filaments depend on the competition of motors for their binding sites. We propose two models in which finite processive motor proteins actively advance along cytoskeletal filaments and are continuously exchanged with the motor pool. We first look at homogeneous reservoirs and then examine the effects of free motor diffusion in the surrounding medium. We consider as a reference situation recent in vitro experimental setups of kinesin-8 motors binding and moving along microtubule filaments in a flow chamber. We investigate how the crowding of linear motor proteins moving on a filament can be regulated by the Balance between supply (concentration of motor proteins in the flow chamber) and Demand (total number of polymerised tubulin heterodimers). We present analytical results for the density profiles of bound motors, the reservoir depletion, and propose novel phase diagrams that present the formation of jams of motor proteins on the filament as a function of two tuneable experimental parameters: the motor protein concentration and the concentration of tubulins polymerized into cytoskeletal filaments. Extensive numerical simulations corroborate the analytical results for parameters in the experimental range and also address the effects of diffusion of motor proteins in the reservoir.

  • Motor protein traffic regulation by supply–Demand Balance of resources
    Physical Biology, 2014
    Co-Authors: Luca Ciandrini, Izaak Neri, Jean-charles Walter, Olivier Dauloudet, Andrea Parmeggiani
    Abstract:

    In cells and in in vitro assays the number of motor proteins involved in biological transport processes is far from being unlimited. The cytoskeletal binding sites are in contact with the same finite reservoir of motors (either the cytosol or the flow chamber) and hence compete for recruiting the available motors, potentially depleting the reservoir and affecting cytoskeletal transport. In this work we provide a theoretical framework in which to study, analytically and numerically, how motor density profiles and crowding along cytoskeletal filaments depend on the competition of motors for their binding sites. We propose two models in which finite processive motor proteins actively advance along cytoskeletal filaments and are continuously exchanged with the motor pool. We first look at homogeneous reservoirs and then examine the effects of free motor diffusion in the surrounding medium. We consider as a reference situation recent in vitro experimental setups of kinesin-8 motors binding and moving along microtubule filaments in a flow chamber. We investigate how the crowding of linear motor proteins moving on a filament can be regulated by the Balance between supply (concentration of motor proteins in the flow chamber) and Demand (total number of polymerized tubulin heterodimers). We present analytical results for the density profiles of bound motors and the reservoir depletion, and propose novel phase diagrams that present the formation of jams of motor proteins on the filament as a function of two tuneable experimental parameters: the motor protein concentration and the concentration of tubulins polymerized into cytoskeletal filaments. Extensive numerical simulations corroborate the analytical results for parameters in the experimental range and also address the effects of diffusion of motor proteins in the reservoir. We then propose experiments for validating our models and discuss how the 'supply–Demand' effects can regulate motor traffic also in in vivo conditions.

  • motor protein traffic regulation by supply Demand Balance of resources
    Physical Biology, 2014
    Co-Authors: Luca Ciandrini, Izaak Neri, Jean-charles Walter, Olivier Dauloudet, Andrea Parmeggiani
    Abstract:

    In cells and in in vitro assays the number of motor proteins involved in biological transport processes is far from being unlimited. The cytoskeletal binding sites are in contact with the same finite reservoir of motors (either the cytosol or the flow chamber) and hence compete for recruiting the available motors, potentially depleting the reservoir and affecting cytoskeletal transport. In this work we provide a theoretical framework in which to study, analytically and numerically, how motor density profiles and crowding along cytoskeletal filaments depend on the competition of motors for their binding sites. We propose two models in which finite processive motor proteins actively advance along cytoskeletal filaments and are continuously exchanged with the motor pool. We first look at homogeneous reservoirs and then examine the effects of free motor diffusion in the surrounding medium. We consider as a reference situation recent in vitro experimental setups of kinesin-8 motors binding and moving along microtubule filaments in a flow chamber. We investigate how the crowding of linear motor proteins moving on a filament can be regulated by the Balance between supply (concentration of motor proteins in the flow chamber) and Demand (total number of polymerized tubulin heterodimers). We present analytical results for the density profiles of bound motors and the reservoir depletion, and propose novel phase diagrams that present the formation of jams of motor proteins on the filament as a function of two tuneable experimental parameters: the motor protein concentration and the concentration of tubulins polymerized into cytoskeletal filaments. Extensive numerical simulations corroborate the analytical results for parameters in the experimental range and also address the effects of diffusion of motor proteins in the reservoir. We then propose experiments for validating our models and discuss how the 'supply–Demand' effects can regulate motor traffic also in in vivo conditions.

Jun-ichi Imura - One of the best experts on this subject based on the ideXlab platform.

  • optimal scheduling of battery storage systems and thermal power plants for supply Demand Balance
    Control Engineering Practice, 2018
    Co-Authors: Masakazu Koike, Takayuki Ishizaki, Nacim Ramdani, Jun-ichi Imura
    Abstract:

    Abstract This paper focuses on the day-ahead scheduling problem of generating power for thermal power plants and charging/discharging battery energy storage systems based on interval predictions of photovoltaic power. Our previous approach to this problem used the Jacobian of a solution with respect to the variation in Demand. However, this study was limited in the sense that the output capacity constraints of thermal power plants were not taken into account. To overcome this problem, we introduce a virtual thermal plant and apply several properties of an M -matrix. To provide guidelines for the amount of power that should be generated, we determine the exact regulating capacity for each thermal power plant and a storage battery so as to maintain the supply–Demand Balance. The efficiency of the proposed method is verified numerically. We show that a brute-force Monte Carlo method cannot estimate the exact regulating capacity of the thermal power plants when the batteries effectively Balance the supply and Demand. Moreover, it is found that, unless their deterioration cost decreases significantly, storage batteries cannot be effectively utilized.

  • Optimal scheduling of battery storage systems and thermal power plants for supply–Demand Balance
    Control Engineering Practice, 2018
    Co-Authors: Masakazu Koike, Takayuki Ishizaki, Nacim Ramdani, Jun-ichi Imura
    Abstract:

    Abstract This paper focuses on the day-ahead scheduling problem of generating power for thermal power plants and charging/discharging battery energy storage systems based on interval predictions of photovoltaic power. Our previous approach to this problem used the Jacobian of a solution with respect to the variation in Demand. However, this study was limited in the sense that the output capacity constraints of thermal power plants were not taken into account. To overcome this problem, we introduce a virtual thermal plant and apply several properties of an M -matrix. To provide guidelines for the amount of power that should be generated, we determine the exact regulating capacity for each thermal power plant and a storage battery so as to maintain the supply–Demand Balance. The efficiency of the proposed method is verified numerically. We show that a brute-force Monte Carlo method cannot estimate the exact regulating capacity of the thermal power plants when the batteries effectively Balance the supply and Demand. Moreover, it is found that, unless their deterioration cost decreases significantly, storage batteries cannot be effectively utilized.

Xinping Guan - One of the best experts on this subject based on the ideXlab platform.

  • wireless charging lane deployment in urban areas considering traffic light and regional energy supply Demand Balance
    Vehicular Technology Conference, 2019
    Co-Authors: Tian Wang, Bo Yang, Cailian Chen, Xinping Guan
    Abstract:

    In this paper, to optimize the Wireless Charging Lane (WCL) deployment in urban areas, we focus on installation cost reduction while achieving regional Balance of energy supply and Demand, as well as vehicle continuous operability issues. To explore the characteristics of energy Demand, we first analyze the daily trajectory of taxis in different regions and find different fluctuating features of daily energy Demand. Then, we establish the WCL power supply model to obtain the wireless charging supply situation in line with the real urban traffic condition, which is the first work considering the influence of traffic lights on charging situation. To ensure minimum deployment cost and to coordinate the contradiction between regional energy supply-Demand Balance and overall supply-Demand matching, we formulate optimization problems ensuring the charge-energy consumption ratio of vehicles. In addition, we rank the priority of WCL efficiency to reduce the complexity of solution and solve the Mixed Integer NonLinear Programming (MINLP) problem to determine deployment plan. Compared with the baseline, the proposed method has significantly improved the effect.

  • wireless charging lane deployment in urban areas considering traffic light and regional energy supply Demand Balance
    arXiv: Optimization and Control, 2019
    Co-Authors: Tian Wang, Bo Yang, Cailian Chen, Xinping Guan
    Abstract:

    In this paper, to optimize the Wireless Charging Lane (WCL) deployment in urban areas, we focus on installation cost reduction while achieving regional Balance of energy supply and Demand, as well as vehicle continuous operability issues. In order to explore the characteristics of energy Demand in various regions of the city, we first analyze the daily driving trajectory of taxis in different regions and find that the daily energy Demand fluctuates to different degrees in different regions. Then, we establish the WCL power supply model to obtain the wireless charging supply situation in line with the real urban traffic condition, which is the first work considering the influence of traffic lights on charging situation. To ensure minimum deployment cost and to coordinate the contradiction between regional energy supply-Demand Balance and overall supply-Demand matching, we formulate optimization problems ensuring the charge-energy consumption ratio of vehicles. In addition, we rank the priority of WCL efficiency to reduce the complexity of solution and solve the Mixed Integer NonLinear Programming (MINLP) problem to determine deployment plan. Compared with the baseline, the proposed method in this paper has significantly improved the effect.

Luca Ciandrini - One of the best experts on this subject based on the ideXlab platform.

  • Motor proteins traffic regulation by supply-Demand Balance of resources
    Physical Biology, 2014
    Co-Authors: Luca Ciandrini, Izaak Neri, Jean-charles Walter, Olivier Dauloudet, Andrea Parmeggiani
    Abstract:

    In cells and in vitro assays the number of motor proteins involved in biological transport processes is far from being unlimited. The cytoskeletal binding sites are in contact with the same finite reservoir of motors (either the cytosol or the flow chamber) and hence compete for recruiting the available motors, potentially depleting the reservoir and affecting cytoskeletal transport. In this work we provide a theoretical framework to study, analytically and numerically, how motor density profiles and crowding along cytoskeletal filaments depend on the competition of motors for their binding sites. We propose two models in which finite processive motor proteins actively advance along cytoskeletal filaments and are continuously exchanged with the motor pool. We first look at homogeneous reservoirs and then examine the effects of free motor diffusion in the surrounding medium. We consider as a reference situation recent in vitro experimental setups of kinesin-8 motors binding and moving along microtubule filaments in a flow chamber. We investigate how the crowding of linear motor proteins moving on a filament can be regulated by the Balance between supply (concentration of motor proteins in the flow chamber) and Demand (total number of polymerised tubulin heterodimers). We present analytical results for the density profiles of bound motors, the reservoir depletion, and propose novel phase diagrams that present the formation of jams of motor proteins on the filament as a function of two tuneable experimental parameters: the motor protein concentration and the concentration of tubulins polymerized into cytoskeletal filaments. Extensive numerical simulations corroborate the analytical results for parameters in the experimental range and also address the effects of diffusion of motor proteins in the reservoir.

  • Motor protein traffic regulation by supply–Demand Balance of resources
    Physical Biology, 2014
    Co-Authors: Luca Ciandrini, Izaak Neri, Jean-charles Walter, Olivier Dauloudet, Andrea Parmeggiani
    Abstract:

    In cells and in in vitro assays the number of motor proteins involved in biological transport processes is far from being unlimited. The cytoskeletal binding sites are in contact with the same finite reservoir of motors (either the cytosol or the flow chamber) and hence compete for recruiting the available motors, potentially depleting the reservoir and affecting cytoskeletal transport. In this work we provide a theoretical framework in which to study, analytically and numerically, how motor density profiles and crowding along cytoskeletal filaments depend on the competition of motors for their binding sites. We propose two models in which finite processive motor proteins actively advance along cytoskeletal filaments and are continuously exchanged with the motor pool. We first look at homogeneous reservoirs and then examine the effects of free motor diffusion in the surrounding medium. We consider as a reference situation recent in vitro experimental setups of kinesin-8 motors binding and moving along microtubule filaments in a flow chamber. We investigate how the crowding of linear motor proteins moving on a filament can be regulated by the Balance between supply (concentration of motor proteins in the flow chamber) and Demand (total number of polymerized tubulin heterodimers). We present analytical results for the density profiles of bound motors and the reservoir depletion, and propose novel phase diagrams that present the formation of jams of motor proteins on the filament as a function of two tuneable experimental parameters: the motor protein concentration and the concentration of tubulins polymerized into cytoskeletal filaments. Extensive numerical simulations corroborate the analytical results for parameters in the experimental range and also address the effects of diffusion of motor proteins in the reservoir. We then propose experiments for validating our models and discuss how the 'supply–Demand' effects can regulate motor traffic also in in vivo conditions.

  • motor protein traffic regulation by supply Demand Balance of resources
    Physical Biology, 2014
    Co-Authors: Luca Ciandrini, Izaak Neri, Jean-charles Walter, Olivier Dauloudet, Andrea Parmeggiani
    Abstract:

    In cells and in in vitro assays the number of motor proteins involved in biological transport processes is far from being unlimited. The cytoskeletal binding sites are in contact with the same finite reservoir of motors (either the cytosol or the flow chamber) and hence compete for recruiting the available motors, potentially depleting the reservoir and affecting cytoskeletal transport. In this work we provide a theoretical framework in which to study, analytically and numerically, how motor density profiles and crowding along cytoskeletal filaments depend on the competition of motors for their binding sites. We propose two models in which finite processive motor proteins actively advance along cytoskeletal filaments and are continuously exchanged with the motor pool. We first look at homogeneous reservoirs and then examine the effects of free motor diffusion in the surrounding medium. We consider as a reference situation recent in vitro experimental setups of kinesin-8 motors binding and moving along microtubule filaments in a flow chamber. We investigate how the crowding of linear motor proteins moving on a filament can be regulated by the Balance between supply (concentration of motor proteins in the flow chamber) and Demand (total number of polymerized tubulin heterodimers). We present analytical results for the density profiles of bound motors and the reservoir depletion, and propose novel phase diagrams that present the formation of jams of motor proteins on the filament as a function of two tuneable experimental parameters: the motor protein concentration and the concentration of tubulins polymerized into cytoskeletal filaments. Extensive numerical simulations corroborate the analytical results for parameters in the experimental range and also address the effects of diffusion of motor proteins in the reservoir. We then propose experiments for validating our models and discuss how the 'supply–Demand' effects can regulate motor traffic also in in vivo conditions.

Masakazu Koike - One of the best experts on this subject based on the ideXlab platform.

  • optimal scheduling of battery storage systems and thermal power plants for supply Demand Balance
    Control Engineering Practice, 2018
    Co-Authors: Masakazu Koike, Takayuki Ishizaki, Nacim Ramdani, Jun-ichi Imura
    Abstract:

    Abstract This paper focuses on the day-ahead scheduling problem of generating power for thermal power plants and charging/discharging battery energy storage systems based on interval predictions of photovoltaic power. Our previous approach to this problem used the Jacobian of a solution with respect to the variation in Demand. However, this study was limited in the sense that the output capacity constraints of thermal power plants were not taken into account. To overcome this problem, we introduce a virtual thermal plant and apply several properties of an M -matrix. To provide guidelines for the amount of power that should be generated, we determine the exact regulating capacity for each thermal power plant and a storage battery so as to maintain the supply–Demand Balance. The efficiency of the proposed method is verified numerically. We show that a brute-force Monte Carlo method cannot estimate the exact regulating capacity of the thermal power plants when the batteries effectively Balance the supply and Demand. Moreover, it is found that, unless their deterioration cost decreases significantly, storage batteries cannot be effectively utilized.

  • Optimal scheduling of battery storage systems and thermal power plants for supply–Demand Balance
    Control Engineering Practice, 2018
    Co-Authors: Masakazu Koike, Takayuki Ishizaki, Nacim Ramdani, Jun-ichi Imura
    Abstract:

    Abstract This paper focuses on the day-ahead scheduling problem of generating power for thermal power plants and charging/discharging battery energy storage systems based on interval predictions of photovoltaic power. Our previous approach to this problem used the Jacobian of a solution with respect to the variation in Demand. However, this study was limited in the sense that the output capacity constraints of thermal power plants were not taken into account. To overcome this problem, we introduce a virtual thermal plant and apply several properties of an M -matrix. To provide guidelines for the amount of power that should be generated, we determine the exact regulating capacity for each thermal power plant and a storage battery so as to maintain the supply–Demand Balance. The efficiency of the proposed method is verified numerically. We show that a brute-force Monte Carlo method cannot estimate the exact regulating capacity of the thermal power plants when the batteries effectively Balance the supply and Demand. Moreover, it is found that, unless their deterioration cost decreases significantly, storage batteries cannot be effectively utilized.