Growth and Pollution Convergence: Theory and Evidence

Stabilizing pollution levels in the long run is a pre-requisite for sustainable growth. We develop a neoclassical growth model with endogenous emission reduction predicting that, along optimal sustainable paths, pollution growth rates are (i) positively related to output growth (scale effect) and (ii) negatively related to emission levels (defensive effect). This dynamic law reduces to a convergence equation that is empirically tested for two major and regulated air pollutants - sulfur oxides and nitrogen oxides - with a panel of 25 European countries spanning the years 1980-2005. Traditional parametric models are rejected by the data. More flexible regression techniques confirm the existence of both the scale and the defensive effect, supporting the model predictions.Air pollution, convergence, economic growth, nonparametric regressions

Corrosion behavior of dental implants immersed into human saliva: Preliminary results of an in vitro study

Over the years, dif- ferent implant surfaces have been used to try to maximize bone to implant contact. The aim of this study was to compare levels of metallic ions and particles dissolution collected from two dif- ferent dental implants surfaces immersed into human saliva. PATIENTS AND METHODS: A total of 60 den- tal implants were tested. Group A: sanded with aluminium oxide medium grade particles and ac- id-etched; Group B: micro-sanded with calcium phosphate powders and acid-etched. Forty im- plants were immersed in 20 ml of human saliva, twenty, as a control, in sterile saline solution. ICP-MS was performed to detect any metallic ions released from dental implants at T0, on day 1 (T1), on day 3 (T2), after one week (T3), on day 14 (T4), after 3 months (T5) and after 6 months (T6). RESULTS: Dissolution of metallic particles of titanium and nickel, absent in human saliva (T0), were found after one week (T3) for Group B and after 3 months (T5) for Group A. Vanadium was already detected in small concentrations in either group after 1 day, with an exponential growth for Group B. CONCLUSIONS: Preliminary results reported signi cant values of Ti, Ni and V released by Group B, showing for the rst time statistically signi cant values of vanadium

Modelling diffusion of innovations in a social network

A new simple model of diffusion of innovations in a social network with upgrading costs is introduced. Agents are characterized by a single real variable, their technological level. According to local information agents decide whether to upgrade their level or not balancing their possible benefit with the upgrading cost. A critical point where technological avalanches display a power-law behavior is also found. This critical point is characterized by a macroscopic observable that turns out to optimize technological growth in the stationary state. Analytical results supporting our findings are found for the globally coupled case.Comment: 4 pages, 5 figures. Final version accepted in PR

Extremism propagation in social networks with hubs

One aspect of opinion change that has been of academic interest is the impact of people with extreme opinions (extremists) on opinion dynamics. An agent-based model has been used to study the role of small-world social network topologies on general opinion change in the presence of extremists. It has been found that opinion convergence to a single extreme occurs only when the average number of network connections for each individual is extremely high. Here, we extend the model to examine the effect of positively skewed degree distributions, in addition to small-world structures, on the types of opinion convergence that occur in the presence of extremists. We also examine what happens when extremist opinions are located on the well-connected nodes (hubs) created by the positively skewed distribution. We find that a positively skewed network topology encourages opinion convergence on a single extreme under a wider range of conditions than topologies whose degree distributions were not skewed. The importance of social position for social influence is highlighted by the result that, when positive extremists are placed on hubs, all population convergence is to the positive extreme even when there are twice as many negative extremists. Thus, our results have shown the importance of considering a positively skewed degree distribution, and in particular network hubs and social position, when examining extremist transmission

Optimization of Robustness of Complex Networks

Networks with a given degree distribution may be very resilient to one type of failure or attack but not to another. The goal of this work is to determine network design guidelines which maximize the robustness of networks to both random failure and intentional attack while keeping the cost of the network (which we take to be the average number of links per node) constant. We find optimal parameters for: (i) scale free networks having degree distributions with a single power-law regime, (ii) networks having degree distributions with two power-law regimes, and (iii) networks described by degree distributions containing two peaks. Of these various kinds of distributions we find that the optimal network design is one in which all but one of the nodes have the same degree, $k_1$ (close to the average number of links per node), and one node is of very large degree, $k_2 \sim N^{2/3}$, where $N$ is the number of nodes in the network.Comment: Accepted for publication in European Physical Journal

An evolutionary model of industry dynamics and firms' institutional behavior with job search, bargaining and matching

This paper proposes an evolutionary model that captures the main dynamics of a world where heterogeneous firms and workers interact and co-evolve. Within a micro-meso perspective, the model focuses on the influence of firms' "institutional settings" on industry dynamics, formalizing these settings as firms' labor choices. Benefiting from insights offered by mainstream labor economics, we introduce the dynamic processes of job search, bargaining and matching in an evolutionary framework. The results of a computer simulation model show that in a stable environment there is an initial clear improvement in the average fitness of the population of incumbent firms, which then evolves around an evolutionary stationary threshold. The consideration of endogenous matching and bargaining processes in the labor market results in important frictions. Furthermore, the simulation results show an increasing wage inequality between the two types of workers considered in the model. We also consider the effect of both positive and negative demand shocks. The turbulence in the industry increases (decreases) after the negative (positive) demand shock. As expected, the negative demand shock causes a decrease in the number of vacancies and, consequently, the unemployment rates increase considerably. Following the positive demand shock, on the other hand, the firms slightly increase the number of vacancies, so the behavior in terms of unemployment rates is better than in the model without shocks.evolutionary, firm behavior, job search, bargaining and matching, microfoundations, industrial dynamics

Long-term manipulation of soil moisture availability alters ecosystem processes in eastern Amazonian forest regrowth, Brazil.

Resumo: 277

Compulsory treatments in eating disorders: a systematic review and meta-analysis

Introduction: The aims of this systematic review and meta-analysis are to provide a summary of the current literature concerning compulsory treatments in patients with eating disorders (ED) and to understand whether compulsorily and involuntarily treated patients differ in terms of baseline characteristics and treatment outcomes. Methods: Relevant articles were identified following the PRISMA guidelines by searching the following terms: “treatment refusal”, “forced feeding”, “compulsory/coercive/involuntary/forced treatment/admission”, “eating disorders”, “feeding and eating disorders”, “anorexia nervosa”, “bulimia nervosa”. Research was restricted to articles concerning humans and published between 1975 and 2020 in English. Results: Out of 905 articles retrieved, nine were included for the analyses allowing the comparisons between 242 compulsorily and 738 voluntarily treated patients. Mean body mass index (BMI) was slightly lower in patients compelled to treatments. Mean illness duration, BMI at discharge and BMI variation showed no significant differences between the two groups. Average length of hospitalization was 3 weeks longer among compulsory-treated patients, but this did not result in a higher increase in BMI. No significant risk difference on mortality was estimated (three studies). Conclusions: Compulsory treatments are usually intended for patients having worse baseline conditions than voluntary ones. Those patients are unlikely to engage in treatments without being compelled but, after the treatments, albeit with longer hospitalisations, they do achieve similar outcomes. Therefore, we can conclude that forcing patients to treatment is a conceivable option. Level of evidence: Level I, systematic review and meta-analysis

A Fuzzy Inference System for the Assessment of Indoor Air Quality in an Operating Room to Prevent Surgical Site Infection

Indoor air quality in hospital operating rooms is of great concern for the prevention of surgical site infections (SSI). A wide range of relevant medical and engineering literature has shown that the reduction in air contamination can be achieved by introducing a more efficient set of controls of HVAC systems and exploiting alarms and monitoring systems that allow having a clear report of the internal air status level. In this paper, an operating room air quality monitoring system based on a fuzzy decision support system has been proposed in order to help hospital staff responsible to guarantee a safe environment. The goal of the work is to reduce the airborne contamination in order to optimize the surgical environment, thus preventing the occurrence of SSI and reducing the related mortality rate. The advantage of FIS is that the evaluation of the air quality is based on easy-to-find input data established on the best combination of parameters and level of alert. Compared to other literature works, the proposed approach based on the FIS has been designed to take into account also the movement of clinicians in the operating room in order to monitor unauthorized paths. The test of the proposed strategy has been executed by exploiting data collected by ad-hoc sensors placed inside a real operating block during the experimental activities of the “Bacterial Infections Post Surgery” Project (BIPS). Results show that the system is capable to return risk values with extreme precision