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Discounted cash flow analysis, including net present value is an established way to value land use and management investments which accounts for the time-value of money. However, it provides a static view and assumes passive commitment to an investment strategy when real world land use and management investment decisions are characterised by uncertainty, irreversibility, change, and adaptation. Real options analysis has been proposed as a better valuation method under uncertainty and where the opportunity exists to delay investment decisions, pending more information. We briefly review the use of discounted cash flow methods in land use and management and discuss their benefits and limitations. We then provide an overview of real options analysis, describe the main analytical methods, and summarize its application to land use investment decisions. Real options analysis is largely underutilized in evaluating land use decisions, despite uncertainty in policy and economic drivers, the irreversibility and sunk costs involved. New simulation methods offer the potential for overcoming current technical challenges to implementation as demonstrated with a real options simulation model used to evaluate an agricultural land use decision in South Australia. We conclude that considering option values in future policy design will provide a more realistic assessment of landholder investment decision making and provide insights for improved policy performance.
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http://dx.doi.org/10.1016/j.jenvman.2015.07.004 | DOI Listing |
Chaos
September 2025
School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
Although many real-world time series are complex, developing methods that can learn from their behavior effectively enough to enable reliable forecasting remains challenging. Recently, several machine-learning approaches have shown promise in addressing this problem. In particular, the echo state network (ESN) architecture, a type of recurrent neural network where neurons are randomly connected and only the read-out layer is trained, has been proposed as suitable for many-step-ahead forecasting tasks.
View Article and Find Full Text PDFAim To analyze the efficacy and cost-effectiveness of various options of antithrombotic therapy in patients with type 2 diabetes mellitus (T2DM) after acute coronary syndrome (ACS), based on the results of a one-year follow-up.Material and methods The article presents features of various antithrombotic therapies in patients with T2DM after ACS from the standpoint of efficacy and cost-effectiveness in real clinical practice based on the materials of the ORACLE II open prospective observational study (2014-2017). The data of 368 patients were divided into three groups based on the selected antithrombotic therapy.
View Article and Find Full Text PDFClin Kidney J
September 2025
Department of Nephrology and Institute of Nephrology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Background: This study aimed to evaluate the efficacy and safety of telitacicept versus mycophenolate mofetil (MMF) in high-risk progressive immunoglobulin A nephropathy (IgAN).
Methods: This retrospective, multicentre cohort study included patients with high-risk progressive IgAN who received telitacicept or MMF therapy, both combined with low-dose steroids. Clinical data were collected from treatment initiation to 12 months.
J Appl Stat
February 2025
Department of Mathematics and Statistics, Loyola University Chicago, Chicago, IL, USA.
When analyzing real data sets, statisticians often face the question that the data are heterogeneous and it may not necessarily be possible to model this heterogeneity directly. One natural option in this case is to use the methods based on finite mixtures. The key question in these techniques often is what is the best number of mixtures or, depending on the focus of the analysis, the best number of sub-populations when the model is otherwise fixed.
View Article and Find Full Text PDFFront Med (Lausanne)
August 2025
Department of Medical Oncology, Kindai University Faculty of Medicine, Osakasayama, Japan.
Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies, with limited treatment options and poor prognosis. Recent advances in cancer genomic analysis enable the identification of actionable gene alterations, opening new opportunities for personalized therapy. Among these, homologous recombination DNA repair (HRR) gene alterations are associated with distinct biological behavior, favorable prognosis, and increased sensitivity to platinum-based chemotherapy.
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