Complex dynamics in equilibrium asset pricing models with boundedly rational,heterogeneous agents

We study a simple model based upon the Lucas framework where heterogeneous agents behave rationally in a fully intertemporal setting but do not know other investors' personal preferences, wealth or investment portfolios. As a consequence, agents initially do not know the equilibrium asset pricing function and must make guesses, which they update via adaptive learning with constant gain. We demonstrate that even in this simple environment the economy can, depending on parameters, exhibit either stable convergence to equilibrium, or chaotic dynamical behavior of asset prices and trading volume without converging to the rational expectations equilibrium of the Lucas model. This contradicts the assertion that the Lucas model is stable in the face of modest deviations from the strong assumptions required to compute the equilibrium. © 2013 Wiley Periodicals, Inc. Complexity 19: 38–55, 2014     

A new distance measure including the weak preference relation: Application to the multiple criteria aggregation procedure for mixed evaluations

We introduce a new distance measure between two preorders that captures indifference, strict preference, weak preference and incomparability relations. This measure is the first to capture weak preference relations. We illustrate how this distance measure affords decision makers greater modeling power to capture their preferences, or uncertainty and ambiguity around them, by using our proposed distance measure in a multiple criteria aggregation procedure for mixed evaluations.     

Brownian motion with drift on spaces with varying dimension

Many properties of Brownian motion on spaces with varying dimension (BMVD in abbreviation) have been explored in Chen and Lou (2018). In this paper, we study Brownian motion with drift on spaces with varying dimension (BMVD with drift in abbreviation). Such a process can be conveniently defined by a regular Dirichlet form that is not necessarily symmetric. Through the method of Duhamel’s principle, it is established in this paper that the transition density of BMVD with drift has the same type of two-sided Gaussian bounds as that for BMVD (without drift). As a corollary, we derive Green function estimate for BMVD with drift.     

Evaluating impacts of fish stock enhancement and biodiversity conservation actions on the livelihoods of small‐scale fishers on the Beijiang River,China

Inappropriate development and overexploitation have seriously degraded aquatic resources in China. Stakeholders identified three fish stock enhancement and biodiversity conservation scenarios for the Beijiang River: S1, increased fish restocking; S2, no fishing season and habitat conservation; and S3, strict pollution control. Potential impacts of these actions on the livelihoods of fishers were evaluated using applied economic modeling. Baseline costs and benefits came from logbooks from 30 fishers and a survey of 90 households in three villages. The financial net benefit for a household was US$1583 (￥11,160) annually, representing a 142% and 387% return on capital and operating costs, respectively. Larger catches associated with S1 and S2 generated a net benefit of US$1651 and US$1822, respectively. Strict pollution control resulting in higher catches (+20%) and lower operating costs (?20%) would increase the net benefit by 15.9% to US$1835 annually. Pollution control would benefit other resource users and is a prerequisite for ecological restoration. Recommendations for Resource Managers

• Stringent pollution control measures are essential to conserve aquatic biodiversity and enhance the livelihoods of fishers but will require considerable public and private sector investment.
• Enhanced fish stocks in the Beijiang River could benefit poor livelihoods but may not be sufficient to lift households out of poverty, aged fishers require government assistance to diversify their livelihoods, access alternative urban employment, and survive with dignity.
• Adopting the economic modeling approach presented here could enable responsible authorities to simultaneously evaluate fish stock enhancement and biodiversity conservation options.
• Broader application of the approach presented here could help ensure small‐scale inland fisheries are managed sustainably and aquatic ecosystems are restored and protected by 2020, in line with Target 6 of the United Nations’ Convention on Biological Diversity Strategic Plan for Biodiversity.

     

Kinetics Study of the Thermal Decomposition of Post-consumer Poly(Ethylene Terephthalate) in an Argon Atmosphere

The thermal decomposition of post-consumer samples of a carbonated water bottle made of poly(ethylene terephthalate), PC-PET, was examined by linear temperature programing under an argon atmosphere to determine its mass loss kinetics. A simple kinetic model, called the first order pseudo single-component model, was used. The total weight-loss of each sample assumed to be in two periods, with each period corresponding to a one step decomposition of the PC-PET to volatiles. Three methods for determining the kinetic parameters by thermal gravimetric analysis were examined: differential analysis at a constant heating rate (differential), temperatures of a given conversion at a number of heating rates (isoconversional), and the maximum rate at multiple heating rates (peak temperature). The latter two multiple heating rates methods results were comparable to each other but they were not in agreement with the results from the differential method. The results of the differential method were insensitive to the heating rate and consistent with kinetics data reported in the literature for PET.     

Modeling,stability and the activity assessment of glutathione reductase from Streptococcus Thermophilus; Insights from the in-silico simulation study

Antioxidant enzymes (AEs) are the main parts of the natural barriers of the body which deactivate the oxidant factors. To discover and understand their structures and function will deserve a deeper investigation. Accordingly, as an AE of probiotic strains, glutathione reductase of Streptococcus thermophilus (GRst), is characterized and modeled by in-silico methods. The investigation indicated the physicochemical properties of the enzyme and estimated its half-life of being more than 10 h. The analysis revealed that the enzyme is composed of 86 strands, 123 helices, and 241 random coils. Homology modeling of the GRst led to the construction of the enzyme’s 3D model that 62% of which is analogous to the glutathione reductase of Escherichia Coli (GRec), and which is qualitatively high in terms of Molpdf, ERRAT, Verify-3D and Ramachandran scores. Moreover, the structural stability of the model was substantiated within 10 and 20 ns at 400 and 300 K, respectively. Interestingly, these data showed that the enzyme is more stable than GRec at 400 K. In other words, the active cavity of the constructed model is characteristic of 38 amino acid residues within 4 Å around the NADPH and GSSG as corresponding ligands of GRst. Noteworthy, herein is the fact that, CYS40 and CYS45 are specified as the active site residues of this enzyme. Furthermore, the interaction assays of the model support its antioxidant capability which is even more than that of GRec.In general, these data provide a new model of AEs being inclusive of high antioxidant capacity and thermostability.     

Neural network modeling of hydrological systems: A review of implementation techniques

This paper presents a review of procedural steps and implementation techniques used in the development of artificial intelligence models, generally referred to as artificial neural networks (ANNs), within the water resources domain. It focusses on identifying different areas wherein ANNs have found application thereby elucidating its advantages and disadvantages as well as various challenges encountered in its use. Results from this review provide useful insights into how the performance of ANNs can be improved and potential areas of application that are yet to be explored in hydrological modeling. Recommendations for Resource Managers

• Development of integrated and hybrid artificial intelligent tools is critical to achieving improved forecasts in hydrological modeling studies.

• Further research into comprehending the internal mechanisms of neural networks is required to obtain a practical meaning of each network component deployed to solve real‐world problems.

• More robust optimization techniques and tools like differential evolution, particle swarm optimization and deep neural nets, are yet to be fully explored in the water resources analysis, and should be given more attention to enhance neural networks aptitude for modeling complex and nonlinear hydrological processes.

     

Kinetic modeling of liquid-phase esterification of acetic acid with n-butanol using heterogeneous poly(o-methylene p-toluene sulfonic acid) as catalyst

Liquid-phase esterification of acetic acid with n-butanol to n-butyl acetate is studied in the presence of a polymeric catalyst, that is, poly(o-methylene p-toluene sulfonic acid). The performance of the proposed catalyst is compared with the other commercially available homogeneous and heterogeneous catalysts in terms of its activity. Experiments are conducted in an isothermal stirred batch reactor to study the effects of speed of agitation, temperature, and catalyst loading on the rate of reaction. A concentration-based pseudo-homogeneous (PH) kinetic model and activity-based kinetic models such as PH, Eley-Rideal (ER), and Langmuir-Hinselwood-Hougen-Watson (LHHW) models are developed. All the models considered in this study resulted in similar percentage deviation close to 4%. Further, kinetic models are validated through additional experiments, and it is observed that the simple concentration-based PH model is able to predict experimental data with least deviation compared to activity-based PH, ER, and LHHW models. The developed kinetic models are also tested using the Fisher-Snedecor test (F-test) and are found to be acceptable. By incorporating both modeling data and validation data, the overall absolute average deviations of different models are found to be concentration-based PH model 4.354%, activity-based PH model 5.006%, ER I model 5.189%, ER II model 5.403%, ER III model 5.437%, and LHHW model 6.104%, illustrating the superiority of the simple concentration-based PH model.     

Charge-Transfer versus Charge-Separated Triplet Excited States of [ReI(dmp)(CO)3(His124)(Trp122)]+ in Water and in Modified Pseudomonas aeruginosa Azurin Protein

A computational investigation of the triplet excited states of a rhenium complex electronically coupled with a tryptophan side chain and bound to an azurin protein is presented. In particular, by using high-level molecular modeling, evidence is provided for how the electronic properties of the excited-state manifolds strongly depend on coupling with the environment. Indeed, only upon explicitly taking into account the protein environment can two stable triplet states of metal-to-ligand charge transfer or charge-separated nature be recovered. In addition, it is also demonstrated how the rhenium complex plus tryptophan system in an aqueous environment experiences too much flexibility, which prevents the two chromophores from being electronically coupled. This occurrence disables the formation of a charge-separated state. The successful strategy requires a multiscale approach of combining molecular dynamics and quantum chemistry. In this context, the strategy used to parameterize the force fields for the electronic triplet states of the metal complex is also presented.