Article
Engineering, Chemical
Zhefan Yu, Jianping Luo, Han Zhang, Eiji Onchi, Seung-Hee Lee
Summary: This study aimed to investigate the effects of different motion control interfaces on tele-operated crane tasks, finding that using hand-free gestures increases task completion time and overall workload, but does not affect unloading accuracy, heart rate, or mental demand. The expert group performed better in task completion speed and showed positive feedback on the reproducibility of the prototype system.
Article
Environmental Sciences
Christopher J. Smith, Alaa Al Khourdajie, Pu Yang, Doris Folini
Summary: This study uses the DICE model with the FaIR model to analyze climate policy. It finds that including climate uncertainty leads to more refined estimates for the social cost of carbon and provides more certainty about the optimal rate of emissions abatement in different climate scenarios.
ENVIRONMENTAL RESEARCH LETTERS
(2023)
Article
Management
Sanjay Jain, Haipeng (Allan) Chen
Summary: This study investigates the effects of sunk cost bias on consumer decision-making and firm's pricing strategy, demonstrating that it can be beneficial in certain situations by inducing higher effort and improving experienced quality. Additionally, sunk cost bias may improve firm profits, lead to lower prices, and increase welfare.
MANAGEMENT SCIENCE
(2023)
Article
Computer Science, Artificial Intelligence
Qinglai Wei, Tao Li
Summary: This research focuses on optimal control problems (OCPs) with constrained cost for discrete-time nonlinear systems. A novel value iteration with constrained cost (VICC) method is developed to solve the optimal control law with the constrained cost functions. The VICC method is initialized through a value function constructed by a feasible control law. It is proven that the iterative value function is nonincreasing and converges to the solution of the Bellman equation with constrained cost. The feasibility of the iterative control law is proven, and the method to find the initial feasible control law is given. Implementation using neural networks (NNs) is introduced, and the convergence is proven by considering the approximation error. Finally, the property of the present VICC method is shown by two simulation examples.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Environmental Sciences
Richard S. J. Tol
Summary: The social cost of carbon is an essential factor in designing and implementing optimal climate policies, but there are still significant uncertainties since its first publication. This meta-analysis demonstrates an increasing trend in estimates of the social cost of carbon over time, accounting for inflation and emission year. Estimates of the social cost of carbon serve as benchmarks for climate policy targets, but there is great uncertainty regarding their evolution over time. A meta-analysis of published estimates reveals that the social cost of carbon has increased as knowledge about climate change advances. Considering inflation, emission year, and discount rate, a non-stationary distribution is observed through kernel density decomposition. In the past decade, estimates of the social cost of carbon have increased from US$9 per tCO(2) to US$40 per tCO(2) with a high discount rate, and from US$122 per tCO(2) to US$525 per tCO(2) with a low discount rate. This trend is statistically significant when sensitivity analyses are discounted and weighted based on paper quality. Actual carbon prices are generally lower than the estimated value and should therefore be increased.
NATURE CLIMATE CHANGE
(2023)
Article
Public, Environmental & Occupational Health
Nimalan Arinaminpathy, Arindam Nandi, Shibu Vijayan, Nita Jha, Sreenivas A. Nair, Sameer Kumta, Puneet Dewan, Kiran Rade, Bhavin Vadera, Raghuram Rao, Kuldeep S. Sachdeva
Summary: The PPIA initiative to engage with private sector in tuberculosis control in India shows cost-effective ways to reduce TB burden, with different cost-effectiveness outcomes based on local settings such as drug resistance patterns.
Article
Operations Research & Management Science
Xin Chen, Yuanguo Zhu, Bo Li
Summary: Chance theory is utilized to analyze indeterminacy, encompassing both uncertainty and randomness. A method for optimal control of uncertain random continuous-time systems is introduced using chance theory, allowing for the design of dynamic optimization problems. The principle of optimality is presented using the dynamic programming method, accompanied by an optimality equation to solve the proposed problem. Additionally, three special cases of optimal control problems are discussed based on the derived equation. Finally, a numerical example and an optimal cash balance problem are provided to demonstrate the effectiveness of the achieved results.
Article
Mathematics, Interdisciplinary Applications
Xin Chen, Yuanguo Zhu
Summary: This paper applies chance theory to study optimal control for uncertain random singular systems with multiple time-delays, deriving appropriate recurrence equations and discussing two kinds of optimal control problems. It provides the optimal control inputs and respective optimal values through the solvability of the obtained equations. A numerical example demonstrates the effectiveness of the theoretical results.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Mathematics, Interdisciplinary Applications
Xin Chen, Fuzhen Li, Dongmei Yuan, Jian Wang, Yu Shao
Summary: In this paper, we investigate uncertain random discrete-time noncausal systems (URDTNSs) and optimal control problems (OCPs) using chance theory with chance expectation. We convert OCPs subject to URDTNSs into conditional equivalent uncertain random OCPs using an algebraic transformation method. Then, we propose recurrence equations to transform the uncertain random OCPs into solving problems for deterministic difference equations.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Mathematics, Interdisciplinary Applications
Qinyun Lu, Yuanguo Zhu
Summary: This paper focuses on the LQ optimal control problem of fractional-order discrete-time systems based on uncertainty theory. The equivalent integer-order LQ problem is solved using dynamic programming approach, and a numerical example is provided to demonstrate the solution method. The achieved results are also applied to discuss an LQ optimal control problem of a macroeconomic system.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Automation & Control Systems
Shuhua Gao, Changkai Sun, Cheng Xiang, Kairong Qin, Tong Heng Lee
Summary: This study investigates the infinite-horizon optimal control problem for switched Boolean control networks with an average cost criterion and proposes a more efficient approach based on graph theory. By establishing an optimal state transition graph and using a minimum-mean cycle algorithm, the proposed method can quickly find the optimal control law. Experimental results show that this approach outperforms existing methods in terms of computational efficiency.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Adam W. Koenig, Simone D'Amico
Summary: This article introduces a new fast and robust algorithm for providing fuel-optimal impulsive control input sequences to drive a system to a desired state at a specified time. The algorithm reformulates the optimal control problem as a semi-infinite convex program and provides a globally optimal impulsive control input sequences.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2021)
Article
Automation & Control Systems
Jinna Li, Mingwei Yang, Frank L. Lewis
Summary: This paper proposes a self-learning model-free method for optimizing the industrial operation with multi-time scale and strong nonlinearity. By integrating zero-sum game and singular perturbation theories, composite controllers with signal compensation are designed for unknown nonlinear systems with multi-rate operations. The effectiveness of the proposed method is verified through practical and numerical examples.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Public, Environmental & Occupational Health
Lise Jamieson, Leigh F. Johnson, Katleho Matsimela, Linda Alinafe Sande, Marc d'Elbee, Mohammed Majam, Cheryl Johnson, Thato Chidarikire, Karin Hatzold, Fern Terris-Prestholt, Brooke Nichols, Gesine Meyer-Rath
Summary: HIV self-testing has shown significant potential in increasing HIV testing uptake, but different distribution modalities have varied cost-effectiveness and epidemic impact, requiring optimization to improve the long-term health impact of HIVST investment.
Article
Automation & Control Systems
Yuji Ito, Kenji Fujimoto, Yukihiro Tadokoro
Summary: This study designs feedback controllers to address stochastic optimal control problems with generalized cost functions. The target linear systems have time-invariant stochastic parameters and the cost functions involve nonlinear mappings and polynomial forms. Unlike conventional methods, this study overcomes the difficulties caused by time-invariant parameters and handles the generalized cost functions by deriving an explicit relation between the cost function and the linear feedback gain of a controller, which enables optimization via a gradient method. The proposed method ensures convergence and guarantees robust stability, even with stochastic parameters.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Biophysics
Alexander P. Browning, Jesse A. Sharp, Tarunendu Mapder, Christopher M. Baker, Kevin Burrage, Matthew J. Simpson
Summary: Bacteria invest in a slow-growing subpopulation, called persisters, to ensure survival in the face of uncertainty. The study unifies biological population dynamics and financial risk management through optimal control theory, analyzing cellular decision making in volatile environments. The research reveals an emergent cellular hedging strategy that maximizes population growth rate and offers new opportunities for experimental investigation and design.
BIOPHYSICAL JOURNAL
(2021)
Article
Ecology
Anthony R. Rendall, Duncan R. Sutherland, Christopher M. Baker, Ben Raymond, Raylene Cooke, John G. White
Summary: Managing ecosystems in the face of complex species interactions and uncertainty is a major ecological challenge. This study demonstrates the utility of ecosystem models in reducing uncertainty and informing future management, using Phillip Island as a case study. Results suggest that managing prey species may have the most ecosystem-wide benefits, and top-down control of apex predators could lead to unintended consequences.
ECOLOGICAL APPLICATIONS
(2021)
Article
Biodiversity Conservation
Dana M. Bergstrom, Barbara C. Wienecke, John van den Hoff, Lesley Hughes, David B. Lindenmayer, Tracy D. Ainsworth, Christopher M. Baker, Lucie Bland, David M. J. S. Bowman, Shaun T. Brooks, Josep G. Canadell, Andrew J. Constable, Katherine A. Dafforn, Michael H. Depledge, Catherine R. Dickson, Norman C. Duke, Kate J. Helmstedt, Andres Holz, Craig R. Johnson, Melodie A. McGeoch, Jessica Melbourne-Thomas, Rachel Morgain, Emily Nicholson, Suzanne M. Prober, Ben Raymond, Euan G. Ritchie, Sharon A. Robinson, Katinka X. Ruthrof, Samantha A. Setterfield, Carla M. Sgro, Jonathan S. Stark, Toby Travers, Rowan Trebilco, Delphi F. L. Ward, Glenda M. Wardle, Kristen J. Williams, Phillip J. Zylstra, Justine D. Shaw
Summary: This study examines the current state and recent trajectories of ecosystem collapse globally, highlighting the pressures from global climate change and human impacts as key drivers. The manifestation of widespread ecosystem collapse serves as a stark warning of the necessity for action to alleviate further degradation. A three-step assessment and management framework is proposed to aid in strategic and effective mitigation to secure our future.
GLOBAL CHANGE BIOLOGY
(2021)
Article
Mathematics
Danielle Burton, Suzanne Lenhart, Christina J. Edholm, Benjamin Levy, Michael L. Washington, Bradford R. Greening, K. A. Jane White, Edward Lungu, Obias Chimbola, Moatlhodi Kgosimore, Faraimunashe Chirove, Marilyn Ronoh, M. Helen Machingauta
Summary: Contact tracing plays a vital role in controlling and ending Ebola virus outbreaks, and modeling this process can help improve tracking efforts and highlight its importance. Results indicate that implementing a larger scale contact tracing program could reduce the death toll of outbreaks.
Article
Biology
Tricia Phillips, Suzanne Lenhart, W. Christopher Strickland
Summary: Opioid addiction, particularly involving heroin and fentanyl, has become a major issue in Tennessee, surpassing prescription drug addiction. Model projections suggest that heroin and fentanyl-related addictions and overdoses will continue to rise in the coming years, while addiction to prescription drugs continues to decline. Management strategy analysis indicates that focusing on treatment availability, monitoring recovered individuals, and efforts to decrease opioid overdose fatalities will be crucial in addressing this epidemic.
BULLETIN OF MATHEMATICAL BIOLOGY
(2021)
Article
Ecology
Christopher M. Baker, Patricia T. Campbell, Iadine Chades, Angela J. Dean, Susan M. Hester, Matthew H. Holden, James M. McCaw, Jodie McVernon, Robert Moss, Freya M. Shearer, Hugh P. Possingham
Summary: Scientific knowledge and advances play a crucial role in modern society, but there is a perpetual challenge in translating scientific insight into policy. Decision science provides a solution by framing scientific questions in a way that benefits policy development, allowing scientists to contribute more effectively to important societal problems.
FRONTIERS IN ECOLOGY AND EVOLUTION
(2022)
Article
Biodiversity Conservation
Michaela Plein, Katherine R. O'Brien, Matthew H. Holden, Matthew P. Adams, Christopher M. Baker, Nigel G. Bean, Scott A. Sisson, Michael Bode, Kerrie L. Mengersen, Eve McDonald-Madden
Summary: Data-hungry and complex ecosystem models are not practical in systems with insufficient data. Instead, we propose a minimum realistic model to guide decision making. We used biophysical constraints and observable parameters to determine the combined abundances of cats and rats that could threaten the tropicbird population. Our approach is especially useful in the absence of knowledge of predator-predator interactions for on-the-ground predator control.
CONSERVATION BIOLOGY
(2022)
Article
Mathematics, Applied
Ibrahim Halil Aslan, Mahir Demir, Michael Morgan Wise, Suzanne Lenhart
Summary: This study analyzes the dynamics of local outbreaks of COVID-19 using a system of ordinary differential equations (ODEs). Based on data from Hubei, China, the trajectory of the outbreak is predicted, and the effects of social distancing on the outbreak dynamics are observed. The model is then applied to analyze the outbreak in Turkey, providing forecasts for the peak and daily number of cases and deaths.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2022)
Article
Biochemical Research Methods
Wenrui Hao, Suzanne Lenhart, Jeffrey R. Petrella
Summary: With the recent FDA approval of the first disease-modifying drug for Alzheimer's Disease, personalized medicine becomes increasingly important in managing and counseling AD patients. This paper develops a mathematical model, based on AD biomarkers, to provide a personalized optimal treatment plan for individuals.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Article
Multidisciplinary Sciences
Gloria M. Monsalve-Bravo, Brodie A. J. Lawson, Christopher Drovandi, Kevin Burrage, Kevin S. Brown, Christopher M. Baker, Sarah A. Vollert, Kerrie Mengersen, Eve McDonald-Madden, Matthew P. Adams
Summary: This work introduces a comprehensive approach to assess the sensitivity of model outputs to changes in parameter values, constrained by the combination of prior beliefs and data. It identifies stiff parameter combinations affecting the model-data fit, and reveals which of these combinations are primarily influenced by the data or the priors. The technique is beneficial in contexts where data is limited compared to the number of model parameters, and has applications in biochemistry, ecology, and cardiac electrophysiology. It also helps uncover controlling mechanisms and guide parameter prioritization for improved parameter inference.
Article
Biochemical Research Methods
Brenda Lyn A. Gavina, V. Aurelio A. de los Reyes, Mette Olufsen, Suzanne Lenhart, Johnny Ottesen
Summary: Anovulation can be achieved by using exogenous hormones, but high doses are associated with adverse effects. This study utilizes optimal control theory on a modified menstrual cycle model to determine the minimum total exogenous estrogen/progesterone dose, and timing of administration to induce anovulation. Results show significant reduction in dosage with combination therapy and the most effective timing for estrogen contraception is the mid follicular phase.
PLOS COMPUTATIONAL BIOLOGY
(2023)
Article
Biodiversity Conservation
Charles Sims, Paul R. Armsworth, Julie Blackwood, Ben Fitzpatrick, David M. Kling, Suzanne Lenhart, Michael Neubert, Monica Papes, James Sanchirico, Katriona Shea, Michael Springborn
Summary: Managing social-ecological systems requires balancing local heterogeneity and accommodating the extent of the system. Ecological federalism proposes a research agenda that combines environmental law, economics, ecology, and biology to determine the appropriate division of management responsibilities between federal and state governments.
Article
Ecology
Spencer Catron, Sarah Roth, Francesca Zumpano, Jason Bintz, James A. Fordyce, Suzanne Lenhart, Debra L. Miller, Jeanette Wyneken
Summary: Loggerhead sea turtles (Caretta caretta), a threatened species, predominantly nest in Florida and contribute to a significant portion of the Atlantic Ocean loggerhead population. However, the ecological mechanisms underlying their population dynamics remain understudied. This study examines the relationship between air temperature and emergence success across multiple nesting seasons, providing insights into the potential impact of climate change on loggerhead populations.
ECOLOGICAL MODELLING
(2023)
Article
Mathematical & Computational Biology
Isobel R. Abell, James M. McCaw, Christopher M. Baker
Summary: This paper develops a conceptual mathematical model to simulate strategies for pre-epidemic vaccination. By comparing the outcomes of optimal and suboptimal vaccination strategies, we conclude that efficient allocation of resources is just as crucial to the success of a vaccination strategy as the vaccine effectiveness and/or amount of vaccines available.
INFECTIOUS DISEASE MODELLING
(2023)
Article
Mathematical & Computational Biology
Lee Spence, David E. Anderson, Ibrahim Halil Aslan, Mahir Demir, Chika C. Okafor, Marcy Souza, Suzanne Lenhart
Summary: With the onset of the COVID-19 pandemic, the University of Tennessee College of Veterinary Medicine (UTCVM) adapted its services to curb the virus spread while ensuring essential veterinary care. They developed a mathematical model to forecast the impact of increased contact within the hospital on COVID-19 infections. The model used data from surrounding areas and UTCVM personnel to estimate key transmission rates. Simulations indicated a rise in COVID-19 cases among staff with an influx of clients and veterinary personnel. The study emphasized the importance of understanding reopening scenarios in veterinary teaching hospitals.
INFECTIOUS DISEASE MODELLING
(2023)
