arXiv subjects

J. R. Nicolás-Carlock

Publications and source records attributed to J. R. Nicolás-Carlock.

7 recordsLinked to original sources

arXiv2025

Prosecution of complex criminal networks: a multilevel ERGMs approach to CICIG's judicial cases

Prosecutors are essential in combating organized crime, making key decisions about prosecution, target selection, and structuring imputation strategies. Despite their importance, the configuration of these strategies remains empirically underexplored. This study engages with that premise by considering the cases investigated by the International Commission Against Impunity in Guatemala (CICIG) and focusing specifically on the role of prosecutors, aiming to uncover how their discretionary decisions translated the CICIG mandate into operational practices intended to achieve systemic deterrence, and to what extent, can we talk about deterrence effectiveness. The research employs a multilevel Exponential Random Graph Model (ERGM) analysis, integrating three networks: the criminal network of actors involved in illegal activities, the legal framework network that represents offenses, and the prosecution network that connects actors to offenses. The model assesses whether the observed network aligns with deterrence-based theoretical assumptions and examines how punishment severity can be effective when it disrupts functional ties that sustain criminal activity -both through long-term sanctions and by increasing the perceived threat of punishment among co-offenders. This approach underscores the need for prosecutorial strategies to evolve beyond a case-by-case model toward a multi-case, multi-offender imputation framework that fully integrates intelligence and data-driven analysis to dismantle criminal networks.

physics.soc-ph↗

arXiv2023

Network efficiency of spatial systems with fractal morphology: a geometric graphs approach

The functional features of spatial networks depend upon a non-trivial relationship between the topological and physical structure. Here, we explore that relationship for spatial networks with radial symmetry and disordered fractal morphology. Under a geometric graphs approach, we quantify the effectiveness of the exchange of information in the system from center to perimeter and over the entire network structure. We mainly consider two paradigmatic models of disordered fractal formation, the Ballistic Aggregation and Diffusion-Limited Aggregation models, and complementary, the Viscek and Hexaflake fractals, and Kagome and Hexagonal lattices. First, we show that complex tree morphologies provide important advantages over regular configurations, such as an invariant structural cost for different fractal dimensions. Furthermore, although these systems are known to be scale-free in space, they have bounded degree distributions for different values of an euclidean connectivity parameter and, therefore, do not represent ordinary scale-free networks. Finally, compared to regular structures, fractal trees are fragile and overall inefficient as expected, however, we show that this efficiency can become similar to that of a robust hexagonal lattice, at a similar cost, by just considering a very short euclidean connectivity beyond first neighbors.

cond-mat.mtrl-sci↗

arXiv2023

Organized crime behavior of shell-company networks in procurement: prevention insights for policy and reform

In recent years, the analysis of economic crime and corruption in procurement has benefited from integrative studies that acknowledge the interconnected nature of the procurement ecosystem. Following this line of research, we present a networks approach for the analysis of shell-companies operations in procurement that makes use of contracting and ownership data under one framework to gain knowledge about the organized crime behavior that emerges in this setting. In this approach, ownership and management data are used to identify connected components in shell-company networks that, together with the contracting data, allows to develop an alternative representation of the traditional buyer-supplier network: the module-component bipartite network, where the modules are groups of buyers and the connected components are groups of suppliers. This is applied to two documented cases of procurement corruption in Mexico characterized by the involvement of large groups of shell-companies in the misappropriation of millions of dollars across many sectors. We quantify the economic impact of single versus connected shell-companies operations. In addition, we incorporate metrics for the diversity of operations and favoritism levels. This paper builds into the quantitative organized crime in the private sector studies and contributes by proposing a networks approach for preventing fraud and understanding the need for legal reforms.

physics.soc-ph↗

arXiv2020

The dynamics of the angular and radial density correlation scaling exponents in fractal to non-fractal morphodynamics

Fractal/non-fractal morphological transitions allow for the systematic study of the physics behind fractal morphogenesis in nature. In these systems, the fractal dimension is considered a non-thermal order parameter, commonly and equivalently computed from the scaling of the two-point radial- or angular-density correlations. However, these two quantities lead to discrepancies during the analysis of basic systems, such as in the diffusion-limited aggregation fractal. Hence, the corresponding clarification regarding the limits of the radial/angular scaling equivalence is needed. In this work, considering three fundamental fractal/non-fractal transitions in two dimensions, we show that the unavoidable emergence of growth anisotropies is responsible for the breaking-down of the radial/angular equivalence. Specifically, we show that the angular scaling behaves as a critical power-law, whereas the radial scaling as an exponential that, under the fractal dimension interpretation, resemble first- and second-order transitions, respectively. Remarkably, these and previous results can be unified under a single fractal dimensionality equation.

nlin.PS↗

arXiv2018

The fractal dimensions of Laplacian growth: an analytical approach based on a universal dimensionality function

Laplacian growth, associated to the diffusion-limited aggregation (DLA) model or the more general dielectric-breakdown model (DBM), is a fundamental out-of-equilibrium process that generates structures with characteristic fractal/non-fractal morphologies. However, despite of diverse numerical and theoretical attempts, a data-consistent description of the fractal dimensions of the mass-distributions of these structures has been missing. Here, an analytical description to the fractal dimensions of the DBM and DLA is provided by means of a recently introduced general dimensionality equation for the scaling of clusters undergoing a continuous morphological transition. Particularly, this equation relies on an effective information-function dependent on the Euclidean dimension of the embedding-space and the control parameter of the system. Numerical and theoretical approaches are used in order to determine this information-function for both DLA and DBM. In the latter, a connection to the Rényi entropies and generalized dimensions of the cluster is made, showing that DLA could be considered as the point of maximum information-entropy production along the DBM transition. These findings are in good agreement with previous theoretical and numerical results (two- and three-dimensional DBM, and high-dimensional DLA). Notably, the DBM dimensions can be conformed to a universal description independently of the initial cluster-configuration and the embedding-space.

cond-mat.stat-mech↗

arXiv2016

Universality of fractal to non-fractal morphological transitions in stochastic growth processes

Stochastic growth processes give rise to diverse intricate structures everywhere and across all scales in nature. Despite the seemingly unrelated complex phenomena at their origin, the Laplacian growth theory has succeeded in unifying their treatment under one framework, nonetheless, important aspects regarding fractal to non-fractal morphological transitions, coming from the competition between screening and anisotropy-driven forces, still lacks a comprehensive description. Here we provide such unified description, encompassing all the known characteristics for these transitions, as well as new universal ones, through the statistical mix of basic models of particle-aggregation and the introduction of a phenomenological physically meaningful dimensionality function, that characterizes the fractality of a symmetry-breaking process induced by a generalized anisotropy-driven force. We also show that the generalized Laplacian growth (dielectric breakdown) model belongs to this class. Moreover, our results provide important insights on the dynamical origins of mono/multi-fractality in pattern formation, that generally occur in far-from-equilibrium processes.

cond-mat.stat-mech↗

arXiv2015

Fractality à la carte: a general particle-cluster aggregation model

Aggregation phenomena are ubiquitous in nature, encompassing out-of-equilibrium processes of fractal pattern formation, important in many areas of science and technology. Despite their simplicity, foundational models such as diffusion-limited aggregation (DLA) or ballistic aggregation (BA), have contributed to reveal the most basic mechanisms that give origin to fractal structures. Hitherto, it has been commonly accepted that, in the absence of long-range particle-cluster interactions, the trajectories of aggregating particles, carrying the entropic information of the growing medium, are the main elements of the aggregation dynamics that determine the fractality and morphology of the aggregates. However, when interactions are not negligible, fractality is enhanced or emerges from the screening effects generated by the aggregated particles, a fact that has led to believe that the main contribution to fractality and morphology is of an energetic character only, turning the entropic one of no special significance, to be considered just as an intrinsic stochastic element. Here we show that, even when long-range attractive interactions are considered, not only screening effects but also, in a very significant manner, particle trajectories themselves are the two fundamental ingredients that give rise to the fractality in aggregates. We found that, while the local morphology of the aggregates is determined by the interactions, their global aspect will exclusively depend on the particle trajectories. Thus, by considering an effective aggregation range, we obtain a wide and versatile generalization of the DLA and BA models. Furthermore, for the first time, we show how to generate a vast richness of natural-looking branching clusters with any prescribed fractal dimension, very precisely controlled.

cond-mat.stat-mech↗