Wealthy people do better? Experimental Evidence on Endogenous Time Preference Heterogeneity and the Effect of Wealth in Renewable Common-Pool Resources Exploitation

Aiming to better characterize the exploitation behavior of renewable common-pool resources, in this paper we explore alternative hypothesis about the valuation of the future by the agents and the possibility of heterogeneous behavior on this regard. To do this, we further analyze the experimental data of an N-person discrete-time deterministic dynamic game of T periods fixed duration. Firstly, we consider the homogeneous case where withdrawers’ rate of time preference is symmetrically determined. Then, we calibrate the best fitting model assuming alternatively, exogenous and endogenous time preference. The exogenous time preference case is the traditional assumption in modeling intertemporal choices, i.e. every period, players discount future values at the same level. In the endogenous case, we statistically model the reduced form of the discount factor as a transformation of a second order polynomial on wealth. Secondly, we further explore the endogenous case looking forward to assess the extent of heterogeneity in the rate of time preference formation process. Dynamic problems resolution gives scope for the implementation of ‘rules of thumb’ as a consequence of its' intrinsic complexity. Then, in order to identify the different decisions rules and to classify appropriators within them, we implement a Bayesian classification algorithm based on Houser et al (2004) work. The application of this econometric procedure has allowed us to identify two types of appropriators: “Quasi Myopic” (QM) appropriators and “Disrupted Farsighted” (DF) appropriators. The algorithm has classified near 85% of the appropriators in our sample as QM, and 5% as DF; the lasting agents could not be identified. We used the fitted empirical model to perform simulations. Some results are: (i) initial wealth increase the average efficiency of exploitation; (ii) when initial wealth is high (low), a more equally (unequally) distribution of wealth between types results in higher efficiency in the exploitation of the resource.

Exploring SnxTi1-xO2 Solid Solutions Grown onto Graphene Oxide (GO) as Selective Toluene Gas Sensors

The major drawback of oxide-based sensors is the lack of selectivity. In this context, SnxTi1- xO2/graphene oxide (GO)-based materials were synthesized via a simple hydrothermal route, varying the titanium content in the tin dioxide matrix. Then, toluene and acetone gas sensing performances of the as-prepared sensors were systematically investigated. Specifically, by using 32:1 SnO2/GO and 32:1 TiO2/GO, a greater selectivity towards acetone analyte, also at room temperature, was obtained even at ppb level. However, solid solutions possessing a higher content of tin relative to titanium (as 32:1 Sn0.55Ti0.45O2/GO) exhibited higher selectivity towards bigger and non-polar molecules (such as toluene) at 350 \ub0C, rather than acetone. A deep experimental investigation of structural (XRPD and Raman), morphological (SEM, TEM, BET surface area and pores volume) and surface (XPS analyses) properties allowed us to give a feasible explanation of the different selectivity. Moreover, by exploiting the UV light, the lowest operating temperature to obtain a significant and reliable signal was 250 \ub0C, keeping the greater selectivity to the toluene analyte. Hence, the feasibility of tuning the chemical selectivity by engineering the relative amount of SnO2 and TiO2 is a promising feature that may guide the future development of miniaturized chemoresistors

Evaluation of phenol detoxification by Brassica napus hairy roots, using Allium cepa test

Introduction: Meristematic mitotic cells of Allium cepa constitute an adequate material for cytotoxicity and genotoxicity evaluation of environmental pollutants, such as phenol, which is a contaminant frequently found in several industrial effluents. Results and discussion: In the present work, Brassica napus hairy roots (HR) were used for phenol removal assays. The toxicity of post-removal solutions (PRS) and phenol solutions was analyzed. These HR removed the contaminant with high efficiency (100-80% for phenol solutions containing 10-250 mg/L, respectively). Phenol solutions treated with B. napus HR showed a significant reduction of general toxicity compared to untreated phenol solutions, since the IC50 values were 318. 39 and 229. 02 mg/L, respectively. Moreover, PRS presented lower cytotoxicity and genotoxicity than that found in phenol solutions untreated. The mitotic index (MI) observed in meristematic cells treated with PRS (100 and 250 mg/L of phenol) showed an increase of 35% and 42%, whereas the chromosome aberrations showed a significant decrease. According to these results, B. napus HR cultures could be used for the treatment of solutions contaminated with phenol, since we observed not only high removal efficiency, but also an important reduction of the general toxicity, cytotoxicity, and genotoxicity.Fil: González, Paola Solange. Universidad Nacional de Río Cuarto; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Maglione, Guillermo A.. Universidad Nacional de Río Cuarto; ArgentinaFil: Giordana, Micaela. Universidad Nacional de Río Cuarto; ArgentinaFil: Paisio, Cintia Elizabeth. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Nacional de Río Cuarto; ArgentinaFil: Talano, Melina Andrea. Universidad Nacional de Río Cuarto; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Agostini, Elizabeth. Universidad Nacional de Río Cuarto; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentin

Uma revisão da literatura Sobre Técnicas de Inteligência Artificial Aplicadas a Redes Inteligentes de Autocura/ A Review of Literature on Artificial Intelligence Techniques Applied to Self-Healing Smart Grids

The development of self-healing in smart grids is an attractive research topic. The application of artificial intelligence (AI) techniques for this purpose has been studied recently, and works published in this area show the effectiveness of AI. This article's purpose is to conduct a literature review of research articles published in recent years between 2014 and 2019, with the main theme related directly to self-healing and AI. Compared to the total number of articles published in smart grids, there is a small number of papers with this specific theme, mostly concentrated in Multi-Agent System (MAS). Performing an attribute agreement analysis, it is possible to look for relations between common characteristics of the articles and the chosen AI technique option. The methodology is applicable for educational and research purposes to facilitate the learning and investigation process.

Network conduciveness with application to the graph-coloring and independent-set optimization transitions

We introduce the notion of a network's conduciveness, a probabilistically interpretable measure of how the network's structure allows it to be conducive to roaming agents, in certain conditions, from one portion of the network to another. We exemplify its use through an application to the two problems in combinatorial optimization that, given an undirected graph, ask that its so-called chromatic and independence numbers be found. Though NP-hard, when solved on sequences of expanding random graphs there appear marked transitions at which optimal solutions can be obtained substantially more easily than right before them. We demonstrate that these phenomena can be understood by resorting to the network that represents the solution space of the problems for each graph and examining its conduciveness between the non-optimal solutions and the optimal ones. At the said transitions, this network becomes strikingly more conducive in the direction of the optimal solutions than it was just before them, while at the same time becoming less conducive in the opposite direction. We believe that, besides becoming useful also in other areas in which network theory has a role to play, network conduciveness may become instrumental in helping clarify further issues related to NP-hardness that remain poorly understood