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Humans, or modern humans (Homo sapiens), are the most common and widespread species of primate. A great ape characterized by their hairlessness, bipedalism, and high intelligence, humans have a large brain and resulting cognitive skills that enable them to thrive in varied environments and develop complex societies and civilizations. Humans are highly social and tend to live in complex social structures composed of many cooperating and competing groups, from families and kinship networks to political states. As such, social interactions between humans have established a wide variety of values, social norms, languages, and rituals, each of which bolsters human society. The desire to understand and influence phenomena has motivated humanity's development of science, technology, philosophy, mythology, religion, and other conceptual frameworks. Although some scientists equate the term "humans" with all members of the genus Homo, in common usage it generally refers to Homo sapiens, the onl

A game-theoretical model of deforestation in human-environment relationships

Antonio Rodrigues

We studied a two-person game regarding deforestation in human–environment relationships. Each landowner manages a single land parcel where the state of land-use is forested, agricultural, or abandoned. The landowner has two strategies available: forest conservation and deforestation. The choice of deforestation provides a high return to the landowner, but it degrades the forest ecosystem services produced on a neighboring land parcel managed by a different landowner. Given spatial interactions between the two landowners, each landowner decides which strategy to choose by comparing the expected discounted utility of each strategy. Expected discounted utility is determined by taking into account the current and future utilities to be received, according to the state transition on the two land parcels. The state transition is described by a Markov chain that incorporates a landowner's choice about whether to deforest and the dynamics of agricultural abandonment and forest regeneration. By considering a stationary distribution of the Markov chain for land-use transitions, we derive explicit conditions for Nash equilibrium. We found that a slow regeneration of forests favors mutual cooperation (forest conservation). As the forest regenerates faster, mutual cooperation transforms to double Nash equilibria (mutual cooperation and mutual defection), and finally mutual defection (deforestation) leads to a unique Nash equilibrium. Two different types of social dilemma emerge in our deforestation game. The stag-hunt dilemma is most likely to occur under an unsustainable resource supply, where forest regenerates extremely slowly but agricultural abandonment happens quite rapidly. In contrast, the prisoner's dilemma is likely under a persistent or circulating supply of resources, where forest regenerates rapidly and agricultural abandonment occurs slowly or rapidly. These results show how humans and the environment mutually shape the dilemma structure in forest management, implying that solutions to dilemmas depend on environmental properties.

2009

Adaptive Task-Space Force Control for Humanoid-to-Human Assistance

Anastasia Bolotnikova

We envision a humanoid robot to serve as a source of additional motion-support forces in assistance for frail persons. In this context, we present a control strategy for a humanoid to adaptively regulate its assistive force contribution. First, we identify a human model torque control for optimal execution of a priori known motion task from sample recordings of this task performed by a healthy individual. We utilize the identified model in the proposed position discrepancy based observer of the human torque contribution, the unknown and unmeasurable variable. We propose an experience-based human contribution model learning strategy that allows to improve the human contribution estimate from trial-to-trial. The target assistive torque contribution is then calculated as the difference between the optimal torque required for the motion task and the estimated human contribution. The target assistive torque is integrated into a multi-robot quadratic programming task-space controller to compute the desired interaction force required for the robot to supply the necessary assistive torque for the human model. We use the non-optimal recordings of the human motion task to emulate human frailty and apply our adaptive force control strategy to demonstrate the results of a humanoid successfully assisting the simulated human model to restore the optimal motion task performance.

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

BIOPHYSICAL CONTROLS ON EVAPOTRANSPIRATION: NUMERICAL MODELS AND EXPERIMENTAL OBSERVATIONS

Federico Croci

Water and food are basics of human life, unfortunately climate changes and water pollution have reduced the amount of water available for human uses. In this context the study of the hydrologic cycle is becoming of growing importance in order to optimize the anthropogenic exploitation of water resource. Evapotranspiration is the term used to describe the part of the water cycle which removes liquid water from an area with vegetation into the atmosphere by the processes of both transpiration and evaporation. Evapotranspiration is an important part of the hydrologic cycle because it represents a considerable percentage of water losses in watersheds. This process is also one of the main consumers of solar energy at the Earth's surface. The estimation of evapotranspiration it is of great importance for agriculture and water resources management, for example, by knowing the rate of water loss from a region, farmers will be better placed to efficiently manage the irrigation strategies. The rate of evapotranspiration at any location on the Earth's surface is controlled by several factors such as energy availability, humidity gradient, wind speed immediately above the surface, water availability, type of vegetation, stomatal resistance and soil characteristics. The problem of estimating evapotranspiration has been widely studied. During the past several decades, different approaches have been proposed and many formulas are available in the literature to fulfill this task. The complexity of the phenomena and its great variability all over the world make difficult to find a universal and robust method for the evapotranspiration prediction and estimation. Evapotranspiration can be obtained by many estimation methods. Some of these methods need many weather parameters as inputs while others need fewer. Factors such as data availability, the intended use, and the time scale required by the problem must be considered when choosing the evapotranspiration calculation technique. The Penman-Monteith equation was derived from the classic Penman equation adding to the terms already considered in the Penman formulation (aerodynamic resistance and energy balance) the canopy resistance. This approach requires many meteorological data, such as maximum and minimum air temperatures, relative humidity, solar radiation, and wind speed. If some of these data are not available, alternative techniques have been developed to overcome this drawback. However, this estimations of meteorological data affect the quality of the result, alternatively, in such cases other simpler methods may be used. The Penman-Monteitu equation is assumed to be the most reliable because is based on physical principles and because it considers all the climatic factors, which affect evapotranspiration.

2013