Search

Crop diversity has always been a way to reduce agricultural risk. This study seeks to explore the long-term impact of crop diversity on reducing agricultural income risk in the province of Zanjan. In this study, first the crop diversity was evaluated through the herfindhal index in the timeframe of 1997 to 2018. Next, the income risk was estimated via hodrick-prescott filter. Finally using the Vector Error Correction Model (VECM), the long-term impact of crop diversity on reduced income risk was measured. Given the results of the long-term model it is clear that in the long-run there is a reduction in income fluctuations as crop diversity increases. The result was statistically meaningful by 1%. Meanwhile, based on the results if in the short-run a shock impacts agricultural income fluctuations in the province of Zanjan, in the long-run about 4 cycles are needed to totally balance the impact of the shock out. In other words, the impact of the shock is modified by 25% in each cycle. Thus, it is on the policymakers to first establish supportive policies to diversify cultivation patterns and prevent income shocks. They also need to develop reparative policies such as insurance means in a four-year period to balance the shock once it strikes. [ABSTRACT FROM AUTHOR]

In the financial market, it is important to consider that there is a proportion of customers that have settled their debt in time zero, immediately recovering their ability to pay. In this context, in this paper, we propose a survival analysis methodology that allows the insertion of times equal to zero in scenarios where credit risk is observed. The proposed model addresses the survival analysis model of the zero‐inflated cure rate which incorporates the heterogeneity of three subgroups (individuals having events in the initial time, and individuals not susceptible and susceptible to the event). In our proposal, all available survival data of customers are modeled considering that the number of competitive causes follows a Poisson distribution and the baseline risk function follows a Gompertz distribution. The model parameter estimation is obtained by the maximum likelihood estimation procedure and simulation studies are conducted to evaluate the estimators' performance. The studied methodology will be applied to a credit database provided by a financial institution in Brazil. [ABSTRACT FROM AUTHOR]

Survival models with a frailty term are presented as an extension of Cox's proportional hazard model, in which a random effect is introduced in the hazard function in a multiplicative form with the aim of modeling the unobserved heterogeneity in the population. Candidates for the frailty distribution are assumed to be continuous and non-negative. However, this assumption may not be true in some situations. In this paper, we consider a discretely distributed frailty model that allows units with zero frailty, that is, it can be interpreted as having long-term survivors. We propose a new discrete frailty-induced survival model with a zero-modified power series family, which can be zero-inflated or zero-deflated depending on the parameter value. Parameter estimation was obtained using the maximum likelihood method, and the performance of the proposed models was performed by Monte Carlo simulation studies. Finally, the applicability of the proposed models was illustrated with a real melanoma cancer data set. [ABSTRACT FROM AUTHOR]

• Permeable pavement (PP) hydrologic performance varies widely. • Long-term model needed to understand how design affects the PP water balance. • DRAINMOD, an agricultural drainage model, was tested herein for PP modeling. • Model calibrated to field-collected hydrologic data from four PP systems. • Model effective for long-term modeling of PP hydrology, not single storm events. The hydrologic performance of permeable pavement varies widely due to underlying soil type, drainage configuration, contributing drainage area, surface infiltration rate, and aggregate depth. A long-term hydrologic model is needed to better understand the influence of these design variables on surface runoff, drainage, exfiltration, and evaporation from permeable pavement systems. Most permeable pavement models have not been calibrated with field monitored data, are usually unable to accurately model internal water storage (IWS) zones, and do not account for evaporation from the aggregate profile. Because permeable pavement employs drainage and exfiltration as primary hydrologic mechanisms, it was hypothesized that DRAINMOD, a model shown to accurately simulate bioretention hydrology, could be calibrated to predict the hydrologic response from permeable pavements. Hydrologic data were collected from two permeable pavement applications in North Carolina (Boone and Durham) and two permeable pavement applications in Ohio (Perkins Township and Willoughby Hills) to calibrate and test the model. The specific permeable pavements applications varied widely in aggregate depth, drainage configuration, underlying soil type, and contributing drainage area. Nash-Sutcliffe Efficiencies for drainage ranged from 0.77 to 0.95 during calibration and validation of all sites. Nash-Sutcliffe Efficiencies for exfiltration/evaporation ranged from 0.55 to 0.97 for Boone and Perkins Township, but prediction of exfiltration/evaporation volumes on an event basis was poor for the remaining two sites due to low exfiltration rates (less than 0.20 mm/hr). Despite this, the cumulative volume of exfiltration/evaporation was predicted to within 1–9 % of what was measured during monitoring. Modeled and monitored surface runoff from the Willoughby Hills application (8 % of the water balance) was equivalent. The model predicted the percentage of drainage, surface runoff, and exfiltration/evaporation to within 2 % of what was monitored/estimated at each site, suggesting long-term modeling of permeable pavement hydrology with DRAINMOD is viable. [ABSTRACT FROM AUTHOR]

The Pearl River Delta (PRD) is an extremely complex, large-scale estuary system in China. In this study, a long-term process-based morphodynamic model was developed to investigate the characteristics of variations in energy flux and dissipation and their evolution alongside the hydrodynamic and topographic evolution of the PRD since the Holocene transgression maximum. The results show that the evolution of the dynamics and topography of the PRD are largely influenced by the geological and geomorphological structures of the region. Energy flux and dissipation in the inner estuary exhibited a patchy distribution, with areas of high energy flux appearing in deep troughs, near headlands, and in gorges containing bedrock islands, and areas of relatively small energy flux appearing in the flow shadow zones of the islands, tidal fluctuation confluence area, and shoals. Corresponding to the energy flux distribution, sediment accumulation also exhibited a high degree of spatial and temporal variability. The evolution of the coastline of the PRD is not driven from north to south, or from the river outlet to the downstream area. Rather, multiple deposition bodies simultaneously developed in the north and south without overlapping. With the deposition of sediment in the estuary, the isoamplitude lines of tidal waves were gradually extrapolated and the spatial distribution gradually shifted from the northwest to the southwest. This indicates the mutual transformation between the estuarine river and tidal power, and also reflects the development characteristics of the river system. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • EPLANoptTP is a novel long-term perfect foresight model based on EnergyPLAN. • Main novelties are the high time resolution and multi-objectives optimization. • Output: the best timing for capacity expansion to reduce CO 2 emissions and costs. • The EPLANoptTP is applied to the Italian case study and results are presented. • The method highlights the importance of considering cumulated CO 2 emissions. Abstract The planning of an energy system with high penetration of renewables is becoming increasingly important to face environmental and energy security issues. Within bottom-up energy system modelling, two different approaches exist: one optimizes the energy mix of a selected future year, while a second optimizes the transition pathway between the current baseline and a future year. Markal/TIMES and OSeMOSYS are examples of valid modelling tools for both approaches. Due to computational issues, these models usually adopt low time resolutions and follow a time slice approach. The latter approximation is questionable given that renewables are intermittent and storage, stationary and in electric vehicles, is needed. To overcome the accuracy issue, a modelling approach based on a multi-objective evolutionary algorithm and the EnergyPLAN software, which allows for year by year simulations with an hourly time-step, was introduced. The method that includes cost decrease of technologies year by year and decommissioning of old plants is applied to the Italian energy system. The results show the importance of timing in renewables capacity expansion planning. The deepest cumulated CO 2 emission reduction of the energy system operating only on residential photovoltaic, wind power and batteries is 24% while introducing electric mobility lower this value at almost 30%. [ABSTRACT FROM AUTHOR]

Background: Models incorporating long-term outcomes (LTOs) are not available to assess the health economic impact of attention-deficit/hyperactivity disorder (ADHD).Objective: Develop a conceptual modelling framework capable of assessing long-term economic impact of ADHD therapies.Methods: Literature was reviewed; a conceptual structure for the long-term model was outlined with attention to disease characteristics and potential impact of treatment strategies.Results: The proposed model has four layers: i) multi-state short-term framework to differentiate between ADHD treatments; ii) multiple states being merged into three core health states associated with LTOs; iii) series of sub-models in which particular LTOs are depicted; iv) outcomes collected to be either used directly for economic analyses or translated into other relevant measures.Conclusions: This conceptual model provides a framework to assess relationships between short- and long-term outcomes of the disease and its treatment, and to estimate the economic impact of ADHD treatments throughout the course of the disease. [ABSTRACT FROM AUTHOR]

ABSTRACT Models based on daily energy balance (or long-term models) have been widely used as a tool in the stand-alone photovoltaic (PV) system sizing, mainly with the purpose of obtaining analytical expressions of the relation between the generator size and the storage capacity of the battery. The system can then be designed to meet the reliability requirements of the specific case. However, such models represent the complex operation of a stand-alone system in an oversimplified way. There is little research so far on the reliability and improvement of such models. Validation and possible modification of a long-term system model requires comparison of the simulated state of charge (SOC) of the battery with that obtained from an experimental system. In this work, experimental data from a 6-month operation of a basic stand-alone PV system have been analysed and compared with modelling results. One obvious improvement that could be applied to the long-term system model is to account for a charging efficiency of the battery, and this possibility is examined in the present work. However, comparison with the modelling results shows that the data cannot be fitted by simply taking into account battery inefficiency. A method to account for system memory effects in the increase of the battery SOC, imposed by the operation of the regulator, is necessary to accurately model the macroscopic diurnal charging/discharging process. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: Previous field studies have shown that the hydrologic performance of bioretention cells varies greatly because of factors such as underlying soil type, physiographic region, drainage configuration, surface storage volume, drainage area to bioretention surface area ratio, and media depth. To more accurately describe bioretention hydrologic response, a long-term hydrologic model that generates a water balance is needed. Some current bioretention models lack the ability to perform long-term simulations and others have never been calibrated from field monitored bioretention cells with underdrains. All peer-reviewed models lack the ability to simultaneously perform both of the following functions: (1) model an internal water storage (IWS) zone drainage configuration and (2) account for soil–water content using the soil–water characteristic curve. DRAINMOD, a widely-accepted agricultural drainage model, was used to simulate the hydrologic response of runoff entering a bioretention cell. The concepts of water movement in bioretention cells are very similar to those of agricultural fields with drainage pipes, so many bioretention design specifications corresponded directly to DRAINMOD inputs. Detailed hydrologic measurements were collected from two bioretention field sites in Nashville and Rocky Mount, North Carolina, to calibrate and test the model. Each field site had two sets of bioretention cells with varying media depths, media types, drainage configurations, underlying soil types, and surface storage volumes. After 12months, one of these characteristics was altered – surface storage volume at Nashville and IWS zone depth at Rocky Mount. At Nashville, during the second year (post-repair period), the Nash–Sutcliffe coefficients for drainage and exfiltration/evapotranspiration (ET) both exceeded 0.8 during the calibration and validation periods. During the first year (pre-repair period), the Nash–Sutcliffe coefficients for drainage, overflow, and exfiltration/ET ranged from 0.6 to 0.9 during both the calibration and validation periods. The bioretention cells at Rocky Mount included an IWS zone. For both the calibration and validation periods, the modeled volume of exfiltration/ET was within 1% and 5% of the estimated volume for the cells with sand (Sand cell) and sandy clay loam (SCL cell) underlying soils, respectively. Nash–Sutcliffe coefficients for the SCL cell during both the calibration and validation periods were 0.92. [Copyright &y& Elsevier]

Because of the influence of human activities, the evolution of the Modaomen Estuary is no longer a purely natural process. We used a long-term morphodynamic model (PRD-LTMM-10) to study the evolution of the estuary from 1977 to 1988. The model incorporated modules for riprap-siltation promotion and waterway dredging. The model can simulate the morphodynamic evolutionary processes occurring in the Modaomen Estuary during the period of interest. We were able to isolate the long-term influences of various human engineering activities and the roles of natural factors in estuarine evolution. The governance projects had the largest effect on the natural development of the estuary, resulting in larger siltation on the west side. Installation of riprap and reclamation of submerged land resulted in scouring of the main Hengzhou Channel causing deep trough out-shift. Severe siltation narrowed the upper end of the Longshiku Deep Trough. [ABSTRACT FROM AUTHOR]

This paper deals with the extremal properties of time series of significant wave height modelled by means of extreme value techniques. The limiting joint generalized extreme value (GEV) distribution for the r largest-order statistic model is used to estimate return values of significant wave height. A method based on filtering the observations to extract the r largest independent values is adopted. A case study of the northern North Sea data set is presented, and the results are compared with those obtained from the Annual Maxima (AM) method. [Copyright &y& Elsevier]

In recent years, researchers have been devoted to illustrating the correlation between bankers' pay contracts and a bank's risk-taking behavior where corporate governance is concerned, especially throughout the past four decades and by using empirical analysis. Despite being a widespread concern, the causality of this relationship is not thoroughly understood. We initiate this research by modeling bankers' multi-stage decisions of option investment and bond investment from the perspective of theoretical analysis, and by analyzing the function image results using data from Wells Fargo & Co. from the ExecuComp, BvD Orbis, and CRSP-COMPUSTAT databases. We aim to deeply explore the mechanism of how compensation influencing on risk. We are the first to find that it has a "risk cap", which is the optimal risk level to maximize the return of decision-making. We are also the first to discover the optimal decision coefficient level to maximize the decision return, during which the internal causes and mechanisms of the impact of bankers' compensation on a bank's default risk are revealed. We also illustrate the influence of the number of periods. We expect our findings to provide advice for establishing policies when designing pay contracts. [ABSTRACT FROM AUTHOR]