Reporting of child maltreatment during the SARS-CoV-2 pandemic in New York City from March to May 2020

© 2020 Elsevier Ltd Background: School closures and other public health responses have decreased the extent that children interact with mandated reporters and other professionals trained to detect child maltreatment. Objective: To assess associations between the pandemic public health response and the number of allegations of child abuse or neglect. Methods: This study analyzed monthly data from New York City of the number of child maltreatment allegations, stratified by reporter type (e.g., mandated reporter, education personnel, healthcare personnel), as well as the number of Child Protective Services (CPS) investigations warranting child welfare preventative services. SARIMA models were trained using data from January 2015 to February 2020 to predict expected values for March, April, and May 2020. Observed values were compared against predicted values at an alpha of .05. Results: Substantially fewer allegations of child maltreatment were reported than expected in March (-28.8 %, deviation: 1848, 95 % CI: [1272, 2423]), April (-51.5 %, deviation: 2976, 95 % CI: [2382, 3570]), and May 2020 (-46.0 %, deviation: 2959, 95 % CI: [2347, 3571]). Significant decreases in child maltreatment reporting were also noted for all reporter subtypes examined for March, April, and May 2020. Fewer CPS investigations warranted preventative services than expected in March 2020 (-43.5 %, deviation: 303, 95 % CI: [132, 475]). Conclusions: Precipitous drops in child maltreatment reporting and child welfare interventions coincided with social distancing policies designed to mitigate COVID-19 transmission. In light of these findings, educators and healthcare providers must be especially vigilant when engaging online with children and their families for signs of child abuse and/or neglect

Growing Scale-Free Networks with Tunable Clustering

We extend the standard scale-free network model to include a ``triad formation step''. We analyze the geometric properties of networks generated by this algorithm both analytically and by numerical calculations, and find that our model possesses the same characteristics as the standard scale-free networks like the power-law degree distribution and the small average geodesic length, but with the high-clustering at the same time. In our model, the clustering coefficient is also shown to be tunable simply by changing a control parameter - the average number of triad formation trials per time step.Comment: Accepted for publication in Phys. Rev.

On population abundance and niche structure

Recent published evidence indicates a negative correlation between density of populations and the distance of their environments to a suitably defined ‘niche centroid’. This empirical observation lacks theoretical grounds. We provide a theoretical underpinning for the empirical relationship between population density and position in niche space, and use this framework to understand the circumstances under which the relationship will fail. We propose a metapopulation model for the area of distribution, as a system of ordinary differential equations coupled with a dispersal kernel. We present an analytical approximation to the solution of the system as well as R code to solve the full model numerically. We use this tool to analyze various scenarios and assumptions. General and realistic demographic assumptions imply a good correlation between position in niche space and population abundance. Factors that modify this correlation are: transitory states, a heterogeneous spatial structure of suitability, and Allee effects. We also explain why the raw output of the niche modeling algorithm MaxEnt is not a good predictor of environmental suitability. Our results elucidate the empirical results for spatial patterns of population size in niche terms, and provide a theoretical basis for a structured theory of the niche

Prisoner's Dilemma cellular automata revisited: evolution of cooperation under environmental pressure

We propose an extension of the evolutionary Prisoner's Dilemma cellular automata, introduced by Nowak and May \cite{nm92}, in which the pressure of the environment is taken into account. This is implemented by requiring that individuals need to collect a minimum score $U_{min}$, representing indispensable resources (nutrients, energy, money, etc.) to prosper in this environment. So the agents, instead of evolving just by adopting the behaviour of the most successful neighbour (who got $U^{msn}$), also take into account if $U^{msn}$ is above or below the threshold $U_{min}$. If $U^{msn}<U_{min}$ an individual has a probability of adopting the opposite behaviour from the one used by its most successful neighbour. This modification allows the evolution of cooperation for payoffs for which defection was the rule (as it happens, for example, when the sucker's payoff is much worse than the punishment for mutual defection). We also analyse a more sophisticated version of this model in which the selective rule is supplemented with a "win-stay, lose-shift" criterion. The cluster structure is analyzed and, for this more complex version we found power-law scaling for a restricted region in the parameter space.Comment: 15 pages, 8 figures; added figures and revised tex

Interlayer Registry Determines the Sliding Potential of Layered Metal Dichalcogenides: The case of 2H-MoS2

We provide a simple and intuitive explanation for the interlayer sliding energy landscape of metal dichalcogenides. Based on the recently introduced registry index (RI) concept, we define a purely geometrical parameter which quantifies the degree of interlayer commensurability in the layered phase of molybdenum disulphide (2HMoS2). A direct relation between the sliding energy landscape and the corresponding interlayer registry surface of 2H-MoS2 is discovered thus marking the registry index as a computationally efficient means for studying the tribology of complex nanoscale material interfaces in the wearless friction regime.Comment: 13 pages, 7 figure

Hierarchical characterization of complex networks

While the majority of approaches to the characterization of complex networks has relied on measurements considering only the immediate neighborhood of each network node, valuable information about the network topological properties can be obtained by considering further neighborhoods. The current work discusses on how the concepts of hierarchical node degree and hierarchical clustering coefficient (introduced in cond-mat/0408076), complemented by new hierarchical measurements, can be used in order to obtain a powerful set of topological features of complex networks. The interpretation of such measurements is discussed, including an analytical study of the hierarchical node degree for random networks, and the potential of the suggested measurements for the characterization of complex networks is illustrated with respect to simulations of random, scale-free and regular network models as well as real data (airports, proteins and word associations). The enhanced characterization of the connectivity provided by the set of hierarchical measurements also allows the use of agglomerative clustering methods in order to obtain taxonomies of relationships between nodes in a network, a possibility which is also illustrated in the current article.Comment: 19 pages, 23 figure

Tribological performance of novel Nickel-based composite coatings with lubricant particles

Abstract The present study is focused on the evaluation of the tribological performance of novel Ni/hBN and Ni/WS2 composite coatings electrodeposited from an additive-free Watts bath with the assistance of ultrasound. Lubricated and non-lubricated scratch tests were performed on both novel composite coatings and on standard Ni deposits used as a benchmark coating to have an initial idea of the effect of the presence of particles within the Ni matrix. Under lubricated conditions, the performance of the Ni/hBN composite coating was very similar to the benchmark Ni coating, whereas the Ni/WS2 behaved quite differently, as the latter did not only show a lower coefficient of friction, but also prevented the occurrence of stick-slip motion that was clearly observed in the other coatings. Under non-lubricated conditions, whereas the tribological performance of the Ni/hBN composite coating was again very similar to that of the benchmark Ni coating, the Ni/WS2 composite coatings again showed a remarkable enhancement, as the incorporation of the WS2 particles into the Ni coating not only resulted in a lower coefficient of friction, but also in the prevention of coating failure

The UN in the lab

We consider two alternatives to inaction for governments combating terrorism, which we term Defense and Prevention. Defense consists of investing in resources that reduce the impact of an attack, and generates a negative externality to other governments, making their countries a more attractive objective for terrorists. In contrast, Prevention, which consists of investing in resources that reduce the ability of the terrorist organization to mount an attack, creates a positive externality by reducing the overall threat of terrorism for all. This interaction is captured using a simple 3×3 “Nested Prisoner’s Dilemma” game, with a single Nash equilibrium where both countries choose Defense. Due to the structure of this interaction, countries can benefit from coordination of policy choices, and international institutions (such as the UN) can be utilized to facilitate coordination by implementing agreements to share the burden of Prevention. We introduce an institution that implements a burden-sharing policy for Prevention, and investigate experimentally whether subjects coordinate on a cooperative strategy more frequently under different levels of cost sharing. In all treatments, burden sharing leaves the Prisoner’s Dilemma structure and Nash equilibrium of the game unchanged. We compare three levels of burden sharing to a baseline in a between-subjects design, and find that burden sharing generates a non-linear effect on the choice of the efficient Prevention strategy and overall performance. Only an institution supporting a high level of mandatory burden sharing generates a significant improvement in the use of the Prevention strategy

Cooperation and Self-Regulation in a Model of Agents Playing Different Games

A simple model for cooperation between "selfish" agents, which play an extended version of the Prisoner's Dilemma(PD) game, in which they use arbitrary payoffs, is presented and studied. A continuous variable, representing the probability of cooperation, $p_k(t) \in$ [0,1], is assigned to each agent $k$ at time $t$. At each time step $t$ a pair of agents, chosen at random, interact by playing the game. The players update their $p_k(t)$ using a criteria based on the comparison of their utilities with the simplest estimate for expected income. The agents have no memory and use strategies not based on direct reciprocity nor 'tags'. Depending on the payoff matrix, the systems self-organizes - after a transient - into stationary states characterized by their average probability of cooperation $\bar{p}_{eq}$ and average equilibrium per-capita-income $\bar{p}_{eq},\bar{U}_\infty$. It turns out that the model exhibit some results that contradict the intuition. In particular, some games which - {\it a priory}- seems to favor defection most, may produce a relatively high degree of cooperation. Conversely, other games, which one would bet that lead to maximum cooperation, indeed are not the optimal for producing cooperation.Comment: 11 pages, 3 figures, keybords: Complex adaptive systems, Agent-based models, Social system