Ising model on the Apollonian network with node dependent interactions

This work considers an Ising model on the Apollonian network, where the exchange constant $J_{i,j}\sim1/(k_ik_j)^\mu$ between two neighboring spins $(i,j)$ is a function of the degree $k$ of both spins. Using the exact geometrical construction rule for the network, the thermodynamical and magnetic properties are evaluated by iterating a system of discrete maps that allows for very precise results in the thermodynamic limit. The results can be compared to the predictions of a general framework for spins models on scale-free networks, where the node distribution $P(k)\sim k^{-\gamma}$, with node dependent interacting constants. We observe that, by increasing $\mu$, the critical behavior of the model changes, from a phase transition at $T=\infty$ for a uniform system $(\mu=0)$, to a T=0 phase transition when $\mu=1$: in the thermodynamic limit, the system shows no exactly critical behavior at a finite temperature. The magnetization and magnetic susceptibility are found to present non-critical scaling properties.Comment: 6 figures, 12 figure file

Negative intrusive thoughts and dissociation as risk factors for self-harm.

Relationships between self-harm and vulnerability factors were studied in a general population of 432 participants, of whom 30% reported some experience of self-harm. This group scored higher on dissociation and childhood trauma, had lower self-worth, and reported more negative intrusive thoughts. Among the non-harming group, 10% scored similarly to the self-harmers on the dissociation and self-worth scales, and engaged in potentially maladaptive behaviors that are not defined as indicating clinical self-harm, but experienced fewer negative intrusive thoughts. This group may be at risk of future self-harm if they begin to experience negative intrusive thoughts. If negative intrusive thoughts are playing a causal role, then therapeutic approaches tackling them may help those who are currently self-harming

Inattentive professional forecasters

We use the ECB Survey of Professional Forecasters to characterize the dynamics of expectations at the micro level. We find that forecasters (i) have predictable forecast errors; (ii) disagree; (iii) fail to systematically update their forecasts in the wake of new information; (iv) disagree even when updating; and (v) differ in their frequency of updating and forecast performances. We argue that these micro data facts are qualitatively in line with recent models in which expectations are formed by inattentive agents. However building and estimating an expectation model that features two types of inattention, namely sticky information à la Mankiw-Reis and noisy information à la Sims, we cannot quantitatively generate the error and disagreement that are observed in the SPF data. The rejection is mainly due to the fact that professionals relatively agree on very sluggish forecasts.imperfect information, inattention, forecast errors, disagreement, business cycle.

Computer simulation of fatigue under diametrical compression

We study the fatigue fracture of disordered materials by means of computer simulations of a discrete element model. We extend a two-dimensional fracture model to capture the microscopic mechanisms relevant for fatigue, and we simulate the diametric compression of a disc shape specimen under a constant external force. The model allows to follow the development of the fracture process on the macro- and micro-level varying the relative influence of the mechanisms of damage accumulation over the load history and healing of microcracks. As a specific example we consider recent experimental results on the fatigue fracture of asphalt. Our numerical simulations show that for intermediate applied loads the lifetime of the specimen presents a power law behavior. Under the effect of healing, more prominent for small loads compared to the tensile strength of the material, the lifetime of the sample increases and a fatigue limit emerges below which no macroscopic failure occurs. The numerical results are in a good qualitative agreement with the experimental findings.Comment: 7 pages, 8 figures, RevTex forma

Family and parenting characteristics associated with marijuana use by Chilean adolescents

OBJECTIVE: Family involvement and several characteristics of parenting have been suggested to be protective factors for adolescent substance use. Some parenting behaviors may have stronger relationships with adolescent behavior while others may have associations with undesirable behavior among youth. Although it is generally acknowledged that families play an important role in the lives of Chilean adolescents, scant research exists on how different family and parenting factors may be associated with marijuana use and related problems in this population which has one of the highest rates of drug use in Latin America. METHODS: Using logistic regression and negative binomial regression, we examined whether a large number of family and parenting variables were associated with the possibility of Chilean adolescents ever using marijuana, and with marijuana-related problems. Analyses controlled for a number of demographic and peer-related variables. RESULTS: Controlling for other parenting and family variables, adolescent reports of parental marijuana use showed a significant and positive association with adolescent marijuana use. The multivariate models also revealed that harsh parenting by fathers was the only family variable associated with the number of marijuana-related problems youth experienced. CONCLUSION: Of all the family and parenting variables studied, perceptions of parental use of marijuana and harsh parenting by fathers were predictors for marijuana use, and the experience of marijuana-related problems. Prevention interventions need to continue emphasizing the critical socializing role that parental behavior plays in their children's development and potential use of marijuana.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3109755/https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3109755/Accepted manuscrip

Large cities are less green

We study how urban quality evolves as a result of carbon dioxide emissions as urban agglomerations grow. We employ a bottom-up approach combining two unprecedented microscopic data on population and carbon dioxide emissions in the continental US. We first aggregate settlements that are close to each other into cities using the City Clustering Algorithm (CCA) defining cities beyond the administrative boundaries. Then, we use data on $\rm{CO}_2$ emissions at a fine geographic scale to determine the total emissions of each city. We find a superlinear scaling behavior, expressed by a power-law, between $\rm{CO}_2$ emissions and city population with average allometric exponent $\beta = 1.46$ across all cities in the US. This result suggests that the high productivity of large cities is done at the expense of a proportionally larger amount of emissions compared to small cities. Furthermore, our results are substantially different from those obtained by the standard administrative definition of cities, i.e. Metropolitan Statistical Area (MSA). Specifically, MSAs display isometric scaling emissions and we argue that this discrepancy is due to the overestimation of MSA areas. The results suggest that allometric studies based on administrative boundaries to define cities may suffer from endogeneity bias

Modeling river delta formation

A new model to simulate the time evolution of river delta formation process is presented. It is based on the continuity equation for water and sediment flow and a phenomenological sedimentation/ erosion law. Different delta types are reproduced using different parameters and erosion rules. The structures of the calculated patterns are analyzed in space and time and compared with real data patterns. Furthermore our model is capable to simulate the rich dynamics related to the switching of the mouth of the river delta. The simulation results are then compared with geological records for the Mississippi river