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Slide 1 of 5 Publicación Acceso Abierto
Spatial Dependence and Cluster Persistence in Drinking-Water Quality Risk: Municipal Evidence from the Department of Santander, Colombia, 2007–2020
(Water, 2026-08-25) González-Sánchez, Eduardo José; Pasqualino, Jorgelina Cecilia; Ayala-García, Jhorland; Grupo de Investigación Sistemas Ambientales e Hidráulicos (GISAH)
Drinking-water quality risk in Colombia is monitored through a single municipal indicator, the Water Quality Risk Index (IRCA), yet its spatial structure has not been examined. This
study analyzes the 87 municipalities of the department of Santander between 2007 and 2020 (1202 municipality-year observations from SIVICAP/INS) using exploratory spatial
data analysis. Global Moran’s I is estimated annually and by period, together with local indicators of spatial association (LISA), the Getis-Ord Gi* statistic, and a cluster-persistence
test based on a binomial contrast with false discovery rate correction. Spatial dependencewas positive and significant before 2014 (I = 0.113; p = 0.036) and became undetectable
afterward (I = 0.046; p = 0.183); the share of IRCA variance attributable to spatial structure fell from 5.0% to 1.0%. The change in IRCA showed no detectable spatial clustering
(I = 0.044; p = 0.198), suggesting, though not confirming, that the improvement did not spread through geographic contiguity. Cluster persistence reveals an asymmetry: eight municipalities maintain statistically significant low-risk cluster status after multiple-testing correction, led by Páramo (9 of 14 years) and San Gil (8 of 14), while no high-risk cluster survives that correction. The mean distance among the ten lowest-risk municipalities (≈60 km) remains below the departmental average (82.1 km) in both periods, whereas that among the ten highest-risk municipalities increases from 70.6 to 90.2 km. Finally,2020 shows significant negative autocorrelation (I = −0.114; p = 0.040), coinciding with an increase in municipalities reporting an IRCA of zero (31 of 87, versus 1 in 2018), which suggests a disruption in the surveillance system rather than an actual change in water quality. Water safety consolidates territorially, whereas high risk does not form stable spatial structures.
Slide 2 of 5 Publicación Acceso Abierto
Onset-centered complexity signatures of GOES flare class in Konus-WIND G1–G3 time series
(Advances in Space Research, 2026-08-05) Sierra Porta, David; Perez Navarro, Juan Diego; Petro Ramos, Jesus David; Grupo de Investigación Gravitación y Matemática Aplicada; Semillero de Investigación en Astronomía y Ciencia de Datos
The high-energy emission from solar flares demonstrates highly variable and often complex light curves, whose temporal structure may contain information beyond standard amplitude-based summaries. Using the Konus-WIND solar flare observations, we carried out an investigation into the statistical association between the onset-centered changes in geometric and complexity-based descriptors and GOES flare classes. Our study was based on the data from the background-subtracted count rates from the event catalogue in three energy channels: G1 (20--80~keV), G2 (80--300~keV) and G3 (300--1200~keV). The observation of each event was segmented into pre-onset (``before'') and post-onset (``after'') intervals defined by bin boundaries relative to the trigger time. For each channel and segment we computed five descriptors: Higuchi fractal dimension, normalized permutation entropy, statistical complexity \(C_{JS}\) in the complexity--entropy framework, normalized Lempel--Ziv complexity (median-binarized), and Hjorth complexity. We summarized onset-associated changes by paired differences \(\Delta=\mathrm{after}-\mathrm{before}\) and assessed class dependence using nonparametric hypothesis tests with Benjamini--Hochberg false-discovery-rate control.
In different channels, most descriptors showed non-zero onset-associated shifts, and the magnitude of \(\Delta\) was significantly different for most channel--descriptor combinations across GOES classes. The strongest monotonic class scaling was observed in the G1 channel for Higuchi fractal dimension, permutation entropy, and \(C_{JS}\), while the clearest separation in the G2 channel was provided by normalized Lempel--Ziv and Hjorth complexity, including a marked Hjorth-complexity transition for X-class events. In the G3 channel, onset-related changes remained evident but between-class discrimination was weaker overall, with Higuchi fractal dimension showing near class-invariant $\Delta$. The obtained results provide conservative population-level evidence that multi-channel onset-centered complexity and geometric descriptors are statistically related to flare class, and motivate future work on integrating additional physical covariates and strictly validated classification models.
Slide 3 of 5 Publicación Acceso Abierto
A methodological benchmarking approach for digital maturity models
(Foresight and STI Governance, 2026-05-29) Viloria Núñez, Cesar Augusto; FERNANDEZ MARQUEZ, CARLOS MANUEL; VAZQUEZ HERNANDEZ, FRANCISCO JOSE; Grupo de Investigación Tecnologías Aplicadas y Sistemas de Información (GRITAS)
Digital maturity models are increasingly used by organizations to evaluate their transformation capabilities and define strategic roadmaps. However, despite their popularity, little is known about the consistency and psychometric soundness of the most widely adopted self-assessment instruments. This study has two objectives: (1) to empirically demonstrate that the results obtained from different digital maturity questionnaires vary significantly for the same organization, and (2) to establish an objective benchmarking framework to evaluate the quality of these tools. The analysis focuses on three prominent models: PwC, MinTIC & iNNpulsa, and MIT & Capgemini. Based on a structured case study and survey responses from 90 non-expert participants and 15 digital transformation experts, we assess each instrument using four key criteria: uncertainty, internal consistency, theoretical validity, and suitability for self-assessment. Results reveal statistically significant discrepancies between instruments and highlight the limitations of relying on unvalidated tools for strategic decision-making. The proposed benchmarking framework offers a practical and replicable approach to guide the selection and development of digital maturity instruments, especially in resource-constrained contexts such as small and medium-sized enterprises (SMEs).
Slide 4 of 5 Publicación Acceso Abierto
Platform architecture approach for managing traceability, visibility, and risk management in freight transportation
(Universidad Politécnica Salesiana, 2026-05-28) Quiroga-Amaya, Jonathan; Sacoto-Cabrera, Erwin; Tafur-Landazabal, Katiana; Castellanos-Ramirez, Andres; Estrada Gallardo, Jesús Andrés; Viloria Núñez, Cesar Augusto; Grupo de Investigación Tecnologías Aplicadas y Sistemas de Información (GRITAS)
Freight transportation is one of the largest and fastest-growing industries in the world. The movement of goods is a complex process that involves a wide variety of factors, including environmental factors and transportation routes. This paper proposes a comprehensive platform architecture that integrates real-time tracking, data collection, AI-based analytics, risk management, and liability-based decision making. The proposed platform consists of six interconnected components designed to improve traceability, visibility, and risk management in freight transport. The core components of the proposed platform are realtime tracking, geolocation tracking, user interfaces, liability considerations, and telemetry data collection. The model consists of six components that enable dynamic monitoring and management of freight movement throughout the supply chain. The first component is tracking, and the second focuses on the risk assessment algorithm to evaluate the impact of environmental factors on transportation routes. The third component is liability, providing a robust framework for aligning logistics operations with legal, ethical, and safety standards. Finally, the proposed model offers a vision for a more efficient, secure, and compliant logistics industry. This research lays the foundation for the continued evolution of modern freight transportation systems by integrating advanced technologies and addressing the complexities of the field.
Slide 5 of 5 Publicación Acceso Abierto
Co-pyrolysis of plastic-and-biomass waste: current insights into chemical recycling toward fuel generation in Latin America
(ACS Applied Polymer Materials, 2026-08-12) Medina-Guerrero, Astrid; Castilla Caballero, Deyler Rafael; Buelvas Hernández, Ana Margarita; Fajardo Cuadro, Juan Gabriel; Grupo de Investigación Sistemas Ambientales e Hidráulicos (GISAH); Grupo de Investigación Energías Alternativas y Fluidos (EOLITO); Semillero de Investigación en Reacciones y Procesos Fisicoquímicos para Remediación Ambiental
Pyrolysis and catalytic co-pyrolysis are promising technologies to transform plastic and biomass waste into low molecular-weight fuels such as hydrogen or methane in Latin America. They have shown outstanding potential to overcome waste pollution while generating energy and profit. Nevertheless, pyrolysis is underrepresented in projected low-carbon energy scenarios. Consequently, this review aims to identify the current trends in the use of pyrolysis-based processes for the transformation of biomass and plastics into energy and value-added products and its potential introduction in the circular value chain in Latin America. We made a bibliometric analysis to elucidate research trends in the area, resulting in 7 main pillars: production of biofuels, aromatics, and biochar; kinetic and thermo-economic analysis; and the application of artificial intelligence (AI) for predicting gas and bio-oil yields. Furthermore, it was found that scientific publications on catalytic co-pyrolysis in Latin America are scarce. Conversely, the countries dominating the literature in this area China, India, and the United States, contributing, respectively, to the 48%, 14%, and 11% of the global publications in the 2021–2025 period. Results also revealed a substantial increase in scientific production after 2022, reaching a peak of 123 publications in both 2024 and 2025. Despite this, their findings are useful for adapting processes in Latin America. Colombia and Brazil, for example, could benefit from this platform, since pyrolysis of biomass and plastic waste are already being implemented. Additionally, their policies regarding the management of biomass and plastic waste favor the adoption of this technology. Another positive finding is that Brazil and Mexico rank among the top ten countries in the world for plastic production, with 10.78 and 5.9 million metric tons, respectively, giving them high potential for generating energy using this technology. A thermo-kinetic analysis was presented, reflecting the main mathematical models (model-based and model-free methods along with reaction mechanism functions with master plots) used to determine relevant parameters for pyrolytic reactor design and to make decisions by determining the exergoeconomic factor (f). A thermoeconomic case study of co-pyrolysis of empty fruit bunch with high density polyethylene (HDPE) adapted to the Latin American energetic context showed that the energy input required for catalytic co-pyrolysis is 303% greater than that required for pretreatment, demonstrating that catalytic co-pyrolysis is the primary contributor to the overall process energy demand. However, the energetic content of the pyrolysis products exceeds that of the untreated waste by more than 882 kWh/kg, which is attractive for the adoption of technology. Concerning computational tools, Aspen Plus and Computational Fluid Dynamics oriented COMSOL stands out as simulation software in this field. Among the AI tools used are convolutional neural networks, deep neural networks, and lightweight gradient boosting machines to predict product yields, with R2 typically higher than 0.9 in the consulted works. However, real-time industrial applications in pyrolysis still face challenges due to the scarcity, heterogeneity, and poorly standardized data sets. The SWOT analysis applied gave us a broader view of the aspects that still need improvement such as catalyst recovery, reduction of heavy waxes generated during pyrolysis, and the reduction of plastic-and-biomass waste disposing in landfills. The key findings of the work are expected to support research and decision making of the academic/industrial/governmental stakeholders associated with the technology in Latin American countries.
