scholarly journals A Coupled Hydrologic-Economic Modeling Framework for Scenario Analysis

2021 ◽  
Vol 3 ◽  
Author(s):  
Maria Amaya ◽  
Ayden Baran ◽  
Carlos Lopez-Morales ◽  
John C. Little
Keyword(s):  
Management Practice ◽  
Nitrogen Concentration ◽  
Economic Modeling ◽  
Agricultural Activity ◽  
Input Output ◽  
Watershed Model ◽  
Modeling Framework ◽  
Hydrological Simulation ◽  
Wide Range ◽  
Modular Framework

To capture the interactions between hydrologic and economic systems necessary for modeling water quality at a sufficient level of spatial detail, we have designed a modular framework that couples an economic model with a watershed model. To represent the economic system, the Rectangular Choice-of-Technology (RCOT) model was used because it represents both the physical and monetary aspects of economic activities and, unlike traditional input-output or general equilibrium models, it can optimize choices among operational technologies in addition to the amount and location of production. For the first implementation of this modeling framework, RCOT is coupled with a watershed model, Hydrological Simulation Program-Fortran (HSPF), which was calibrated to represent Cedar Run Watershed in northern Virginia. This framework was used to analyze eight scenarios related to the expansion of agricultural activity in Fauquier County. The database for RCOT used county-level input-output data representative of the region in 2012. Thus, when crop farming was expanded to fully utilize the farmland available in the watershed, the nitrogen concentration at the outflow of the watershed increased from 0.6 to 4.3 mg/L. However, when RCOT could select between a standard and a more nitrogen-efficient management practice, the outflow nitrogen concentration only increased to 2.6 mg/L because RCOT selected the more resource-efficient practice. Building on this modular framework, future work will involve designing more realistic scenarios that can test policy options and regional planning decisions in a wide range of watersheds.

What Can Demographic–Economic Modeling Tell Us about the Consequences of Regional Decline?

2016 ◽  
Vol 41 (2) ◽  
pp. 256-281 ◽  
Author(s):  
Peter W. J. Batey
Keyword(s):  
Demographic Variables ◽  
Economic Modeling ◽  
Extended Model ◽  
Input Output ◽  
Modeling Framework ◽  
Output Analysis ◽  
East Anglia ◽  
Regional Labor Market ◽  
Regional Labor ◽  
The Impact

The aim of this article is to demonstrate how a particular modeling framework, based on extended input–output analysis, can be used to obtain a clearer understanding of the impact of regional decline of the effects of high, and rising, unemployment; of falling industrial final demand; of welfare payments; and of declining population. The activity–commodity framework used here provides a systematic way of adding demographic variables to the familiar Leontief interindustry model and the extended inverse derived from it provides a rich source of information about the interaction of demographic and economic change, expressed as demographic–economic and economic–demographic multipliers. Drawing on the author’s research in the 1980s and 1990s, this article considers two empirical examples to show the framework’s analytical value: a simple extended model is used to assess the distributional effects of welfare payments in a declining region; and a more elaborate version is linked to a set of regional labor market accounts, summarizing intercensal change in population and employment. This model is used to produce a comprehensive assessment of the effects of population and employment change in two UK regions, one a growing region (East Anglia) and the other a region in decline (Merseyside). In a final section, the benefits and limitations of the extended input–output modeling framework are discussed in comparison with some of the alternative modeling frameworks that are currently available.

scholarly journals Experimental Economics in Agriculture: A Review of Worldwide Research

Agronomy ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1566
Author(s):  
Ernesto Mesa-Vázquez ◽  
Juan F. Velasco-Muñoz ◽  
José A. Aznar-Sánchez ◽  
Belén López-Felices
Keyword(s):  
Environmental Policy ◽  
Literature Review ◽  
Public Goods ◽  
Experimental Economics ◽  
Scientific Production ◽  
Bibliometric Study ◽  
Agricultural Activity ◽  
Global Level ◽  
Policy Makers ◽  
Wide Range

Over the last two decades, experimental economics has been gaining relevance in the research of a wide range of issues related to agriculture. In turn, the agricultural activity provides an excellent field of study within which to validate the use of instruments employed by experimental economics. The aim of this study is to analyze the dynamics of the research on the application of experimental economics in agriculture on a global level. Thus, a literature review has been carried out for the period between the years 2000 and 2020 based on a bibliometric study. The main results show that there has been a growing use of experimental economics methods in the research on agriculture, particularly over the last five years. This evolution is evident in the different indicators analyzed and is reflected in the greater scientific production and number of actors involved. The most relevant topics within the research on experimental economics in agriculture focus on the farmer, the markets, the consumer, environmental policy, and public goods. These results can be useful for policy makers and researchers interested in this line of research.

scholarly journals A modular framework to generate robust biped locomotion: from planning to control

2021 ◽  
Vol 3 (9) ◽  
Author(s):  
Mohammadreza Kasaei ◽  
Ali Ahmadi ◽  
Nuno Lau ◽  
Artur Pereira
Keyword(s):  
Numerical Simulations ◽  
Predictive Control ◽  
Biped Locomotion ◽  
Input Output ◽  
Dynamics Model ◽  
Biped Robots ◽  
The Core ◽  
Simulation Results ◽  
Reference Trajectories ◽  
Modular Framework

AbstractBiped robots are inherently unstable because of their complex kinematics as well as dynamics. Despite many research efforts in developing biped locomotion, the performance of biped locomotion is still far from the expectations. This paper proposes a model-based framework to generate stable biped locomotion. The core of this framework is an abstract dynamics model which is composed of three masses to consider the dynamics of stance leg, torso, and swing leg for minimizing the tracking problems. According to this dynamics model, we propose a modular walking reference trajectories planner which takes into account obstacles to plan all the references. Moreover, this dynamics model is used to formulate the controller as a Model Predictive Control (MPC) scheme which can consider some constraints in the states of the system, inputs, outputs, and also mixed input-output. The performance and the robustness of the proposed framework are validated by performing several numerical simulations using MATLAB. Moreover, the framework is deployed on a simulated torque-controlled humanoid to verify its performance and robustness. The simulation results show that the proposed framework is capable of generating biped locomotion robustly.

scholarly journals EXPRESS: Overcoming the Cold Start Problem of CRM using a Probabilistic Machine Learning Approach

2021 ◽  
pp. 002224372110329
Author(s):  
Nicolas Padilla ◽  
Eva Ascarza
Keyword(s):  
Machine Learning ◽  
Cold Start ◽  
Customer Relationship ◽  
Exponential Families ◽  
Modeling Framework ◽  
Wide Range ◽  
The Moment ◽  
Probabilistic Machine Learning ◽  
Marketing Actions ◽  
Cold Start Problem

The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to identify and leverage differences across customers — a very diffcult task when firms attempt to manage new customers, for whom only the first purchase has been observed. For those customers, the lack of repeated observations poses a structural challenge to inferring unobserved differences across them. This is what we call the “cold start” problem of CRM, whereby companies have difficulties leveraging existing data when they attempt to make inferences about customers at the beginning of their relationship. We propose a solution to the cold start problem by developing a probabilistic machine learning modeling framework that leverages the information collected at the moment of acquisition. The main aspect of the model is that it exibly captures latent dimensions that govern the behaviors observed at acquisition as well as future propensities to buy and to respond to marketing actions using deep exponential families. The model can be integrated with a variety of demand specifications and is exible enough to capture a wide range of heterogeneity structures. We validate our approach in a retail context and empirically demonstrate the model's ability at identifying high-value customers as well as those most sensitive to marketing actions, right after their first purchase.

scholarly journals Soil Nitrogen Dynamics in a Managed Temperate Grassland Under Changed Climatic Conditions

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 931
Author(s):  
Mona Giraud ◽  
Jannis Groh ◽  
Horst H. Gerke ◽  
Nicolas Brüggemann ◽  
Harry Vereecken ◽  
...  
Keyword(s):  
Nitrogen Uptake ◽  
Inorganic Nitrogen ◽  
Nitrogen Concentration ◽  
Nitrogen Dynamics ◽  
Climatic Conditions ◽  
Undisturbed Soil ◽  
Nitrogen Emissions ◽  
Growing Period ◽  
Grassland Type ◽  
Wide Range

Grasslands are one of the most common biomes in the world with a wide range of ecosystem services. Nevertheless, quantitative data on the change in nitrogen dynamics in extensively managed temperate grasslands caused by a shift from energy- to water-limited climatic conditions have not yet been reported. In this study, we experimentally studied this shift by translocating undisturbed soil monoliths from an energy-limited site (Rollesbroich) to a water-limited site (Selhausen). The soil monoliths were contained in weighable lysimeters and monitored for their water and nitrogen balance in the period between 2012 and 2018. At the water-limited site (Selhausen), annual plant nitrogen uptake decreased due to water stress compared to the energy-limited site (Rollesbroich), while nitrogen uptake was higher at the beginning of the growing period. Possibly because of this lower plant uptake, the lysimeters at the water-limited site showed an increased inorganic nitrogen concentration in the soil solution, indicating a higher net mineralization rate. The N2O gas emissions and nitrogen leaching remained low at both sites. Our findings suggest that in the short term, fertilizer should consequently be applied early in the growing period to increase nitrogen uptake and decrease nitrogen losses. Moreover, a shift from energy-limited to water-limited conditions will have a limited effect on gaseous nitrogen emissions and nitrate concentrations in the groundwater in the grassland type of this study because higher nitrogen concentrations are (over-) compensated by lower leaching rates.

Modeling framework for IoT integration of building automation systems

2017 ◽  
Vol 65 (9) ◽  
Author(s):  
Daniel Schachinger ◽  
Andreas Fernbach ◽  
Wolfgang Kastner
Keyword(s):  
Web Services ◽  
Web Service ◽  
Building Automation ◽  
Modeling Framework ◽  
Seamless Integration ◽  
Automation Systems ◽  
Wide Range ◽  
Machine To Machine Communication ◽  
Machine Communication ◽  
The Internet Of Things

AbstractAdvancements within the Internet of Things are leading to a pervasive integration of different domains including also building automation systems. As a result, device functionality becomes available to a wide range of applications and users outside of the building automation domain. In this context, Web services are identified as suitable solution for machine-to-machine communication. However, a major requirement to provide necessary interoperability is the consideration of underlying semantics. Thus, this work presents a universal framework for tag-based semantic modeling and seamless integration of building automation systems via Web service-based technologies. Using the example of the KNX Web services specification, the applicability of this approach is pointed out.

scholarly journals Size-Resolved Evaluation of Simulated Deep Tropical Convection

2018 ◽  
Vol 146 (7) ◽  
pp. 2161-2182 ◽  
Author(s):  
Fabian Senf ◽  
Daniel Klocke ◽  
Matthias Brueck
Keyword(s):  
Deep Convection ◽  
Winter Season ◽  
Power Laws ◽  
Moist Convection ◽  
Modeling Framework ◽  
Western Atlantic ◽  
Spatial Coupling ◽  
Wide Range ◽  
Realistic Representation ◽  
Deep Moist Convection

Abstract Deep moist convection is an inherently multiscale phenomenon with organization processes coupling convective elements to larger-scale structures. A realistic representation of the tropical dynamics demands a simulation framework that is capable of representing physical processes across a wide range of scales. Therefore, storm-resolving numerical simulations at 2.4 km have been performed covering the tropical Atlantic and neighboring parts for 2 months. The simulated cloud fields are combined with infrared geostationary satellite observations, and their realism is assessed with the help of object-based evaluation methods. It is shown that the simulations are able to develop a well-defined intertropical convergence zone. However, marine convective activity measured by the cold cloud coverage is considerably underestimated, especially for the winter season and the western Atlantic. The spatial coupling across the resolved scales leads to simulated cloud number size distributions that follow power laws similar to the observations, with slopes steeper in winter than summer and slopes steeper over ocean than over land. The simulated slopes are, however, too steep, indicating too many small and too few large tropical cloud cells. It is also discussed that the number of larger cells is less influenced by multiday variability of environmental conditions. Despite the identified deficits, the analyzed simulations highlight the great potential of this modeling framework for process-based studies of tropical deep convection.

Possible Effects of Depolarizing GABAA Conductance on the Neuronal Input–Output Relationship: A Modeling Study

2005 ◽  
Vol 93 (6) ◽  
pp. 3504-3523 ◽  
Author(s):  
Kenji Morita ◽  
Kunichika Tsumoto ◽  
Kazuyuki Aihara
Keyword(s):  
Firing Rate ◽  
Cortical Neurons ◽  
Reversal Potential ◽  
Pyramidal Cells ◽  
Resting Potential ◽  
Input Output ◽  
Wide Range ◽  
The Relationship

Recent in vitro experiments revealed that the GABAA reversal potential is about 10 mV higher than the resting potential in mature mammalian neocortical pyramidal cells; thus GABAergic inputs could have facilitatory, rather than inhibitory, effects on action potential generation under certain conditions. However, how the relationship between excitatory input conductances and the output firing rate is modulated by such depolarizing GABAergic inputs under in vivo circumstances has not yet been understood. We examine herewith the input–output relationship in a simple conductance-based model of cortical neurons with the depolarized GABAA reversal potential, and show that a tonic depolarizing GABAergic conductance up to a certain amount does not change the relationship between a tonic glutamatergic driving conductance and the output firing rate, whereas a higher GABAergic conductance prevents spike generation. When the tonic glutamatergic and GABAergic conductances are replaced by in vivo–like highly fluctuating inputs, on the other hand, the effect of depolarizing GABAergic inputs on the input–output relationship critically depends on the degree of coincidence between glutamatergic input events and GABAergic ones. Although a wide range of depolarizing GABAergic inputs hardly changes the firing rate of a neuron driven by noncoincident glutamatergic inputs, a certain range of these inputs considerably decreases the firing rate if a large number of driving glutamatergic inputs are coincident with them. These results raise the possibility that the depolarized GABAA reversal potential is not a paradoxical mystery, but is instead a sophisticated device for discriminative firing rate modulation.

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