We suggest that as people move to construe robots as social agents, interact with them, and treat them as capable of social ties, they might develop (close) relationships with them. We then ask what kind of relationships can people form with bots, what functions can bots fulfill, and what are the societal and moral implications of such relationships.

The growth in wirelessly enabled sensor network technologies has enabled the low cost deployment of sensor platforms with applications in a range of sectors and communities. In the agricultural domain such sensors have been the foundation for the creation of decision support tools that enhance farm operational efficiency. This Research Reflection illustrates how these advances are assisting dairy farmers to optimise performance and illustrates where emerging sensor technology can offer additional benefits. One of the early applications for sensor technology at an individual animal level was the accurate identification of cattle entering into heat (oestrus) to increase the rate of successful pregnancies and thus optimise milk yield per animal. This was achieved through the use of activity monitoring collars and leg tags. Additional information relating to the behaviour of the cattle, namely the time spent eating and ruminating, was subsequently derived from collars giving further insights of economic value into the wellbeing of the animal, thus an enhanced range of welfare related services have been provisioned. The integration of the information from neck-mounted collars with the compositional analysis data of milk measured at a robotic milking station facilitates the early diagnosis of specific illnesses such as mastitis. The combination of different data streams also serves to eliminate the generation of false alarms, improving the decision making capability. The principle of integrating more data streams from deployed on-farm systems, for example, with feed composition data measured at the point of delivery using instrumented feeding wagons, supports the optimisation of feeding strategies and identification of the most productive animals. Optimised feeding strategies reduce operational costs and minimise waste whilst ensuring high welfare standards. These IoT-inspired solutions, made possible through Internet-enabled cloud data exchange, have the potential to make a major impact within farming practices. This paper gives illustrative examples and considers where new sensor technology from the automotive industry may also have a role.

We present the results of two 2.3 μm near-infrared (NIR) radial velocity (RV) surveys to detect exoplanets around 36 nearby and young M dwarfs. We use the CSHELL spectrograph (R ~ 46,000) at the NASA InfraRed Telescope Facility (IRTF), combined with an isotopic methane absorption gas cell for common optical path relative wavelength calibration. We have developed a sophisticated RV forward modeling code that accounts for fringing and other instrumental artifacts present in the spectra. With a spectral grasp of only 5 nm, we are able to reach long-term radial velocity dispersions of ~20–30 m s−1 on our survey targets.

Knowing what information, and from which sensory cues, is available to an animal regarding its position and direction of movement is vital for unravelling the mechanisms underlying animal navigation. Although considerable progress has been made with traditional field and laboratory techniques, these approaches generally do not provide direct control over the animal's motivation to display its sensory abilities. In contrast, psychologists have for many decades used conditioning as a reliable tool to study sensory perception as well as the mechanisms underlying learning. There has been growing interest in the use of conditioning techniques to investigate responses to stimuli that might be used in guiding movement over long distances. This review seeks to facilitate that development by providing a general introduction to conditioning and the considerations involved in designing robust conditioning experiments together with a perspective for its future use in studying sensory systems in migratory and homing species.

Maternal nutrition during pregnancy has a significant influence in establishing patterns of metabolism and postnatal behaviours in offspring, and therefore shapes their risk of developing disorders in later life. Although it is well established that a mismatch between food consumption and energy expenditure leads to obesity and metabolic dysregulation, little research has investigated the biological origin of such behaviour. We conducted the present experiments to investigate effects of early-life nutrition on preference between wheel running and lever pressing for food during adult life. To address this issue we employed a well-established experimental approach in the rat which has shown that offspring of mothers undernourished during pregnancy develop obesity and metabolic disorders when kept under standard laboratory conditions. Using this experimental approach, two studies were conducted where offspring of ad libitum-fed dams and dams undernourished throughout pregnancy were given the choice between wheel running and pressing a response lever for food. Across subsequent conditions, the rate at which the response lever provided food was varied from 0·22 to 6·0 (study 1) and 0·19 to 3·0 (study 2) pellets per min. Compared with the control group, offspring from dams undernourished during pregnancy showed a consistently greater preference for running over lever pressing for food throughout both experiments of the study. The results of the present study provide experimental evidence that a mother's nutrition during pregnancy can result in a long-term shift in her offspring's lifestyle choices that are relevant to obesity prevention. Such a shift, if endorsed, will have substantial and wide-ranging health consequences throughout the lifespan.