#Gene runner primer design Offline

FSH cells showed a dose-dependent reaction. In the present work, we analysed the action of recombinant human leptin on FSH cells in the pituitary gland of Podarcis siculus female lizards exposed to four different concentrations of the hormone. However, little is known about leptin in lower vertebrates and particularly few studies are available on reptiles.

In mammals, this pleiotropic hormone also plays a key role in controlling gonadotropin secretion by stimulatory hypothalamic and pituitary actions. Leptin is the hormone synthesised by adipocytes, which plays an important role in regulating appetite and metabolism. We also show that the heuristic performs close to the MDP schedule in terms of energy consumption.

#Gene runner primer design Offline

We show that the energy consumption under the MDP schedule converges to the energy of the offline schedule as the size of the time window for measurement collection increases. We compare numerically the performance of the MDP schedule with the heuristic and with an offline, optimal schedule, where the asleep/awake state of the sensors is assumed to be known ahead of time. We also develop a heuristic that schedules the sensors for transmission. Furthermore, we formulate a Markov Decision Process (MDP) to determine a sensor transmission schedule with general time constraints. We also provide an upper bound on the maximum expected distance over which a sensor transmits under this Greedy schedule. We determine a closed-form expression for the expected energy consumption of the sensors when measurements are retrieved according to a Greedy schedule.

Moreover, the sink aims to minimize the energy that the sensors use to transmit their measurements. The sink has to collect a sufficient number of measurements within a fixed time window. A sink, at a random location in the plane, requests measurements from the awake sensors in order to retrieve an estimate of an attribute. They perform energy harvesting and follow an asleep/awake cycle. The sensors are located in the plane according to some random spatial process. We consider the problem of retrieving a reliable estimate of an attribute from a wireless sensor network within a fixed time window and with minimum energy consumption for the sensors.