This study evaluates radon exhalation rates and assesses the potential radiological risks of external exposure to primordial radionuclides in building materials employed in the Ica region of Peru, particularly those with high uranium content. The radon exhalation rates are currently measured using a combination of a closed chamber and an active monitor. We proposed a novel method that effectively ensured a hermetic seal for the closed chamber and guaranteed that the efficient maintenance of secular equilibrium. The obtained results ranged from below the detection limit (BDL) to a maximum of 52.3 mBq · kg⁻¹h⁻¹. Gamma spectrometry was employed to measure the concentrations of radionuclides by utilizing a 3′ × 3′ NaI detector. The analysis of cement samples revealed a strong positive correlation between the activity concentration of radium and the radon exhalation rate. The activity concentrations for radionuclides varied, with values ranging from BDL to 60.6 mBq · kg⁻¹h⁻¹ for ²²⁶Ra, BDL to 22.3 mBq · kg⁻¹h⁻¹ for ²³²Th, and BDL to 1074 mBq · kg⁻¹h⁻¹ for ⁴⁰K. These findings contribute valuable insight to decision-making processes in the Peruvian construction industry, particularly regarding material safety and radiological risk management.

Mining generates significant amounts of waste that can represent a source of contamination for areas close to the extraction area, generating a negative impact both on the environment and the health of people. This study aims to evaluate the radiological risk derived from exposure to natural radionuclides contained in tailings from Peruvian gold mines and to establish whether the tailings can be used as raw materials in building materials. The mine tailings come from a mining project in the northern highlands of Peru. Radon exhalation was measured using Rad7 in a closed chamber and activity concentration of ²²⁶Ra, ²³²Th, and ⁴⁰K radioisotopes by gamma spectrometry using NaI 3” × 3” detector. Maximum activity concentrations measured for ²²⁶Ra and ²³²Th were 15.38 Bq kg⁻¹ and 11.9 Bq kg⁻¹, respectively; meanwhile, activity concentration for ⁴⁰K ranged from 182.7 Bq kg⁻¹ to 770.8 Bq kg⁻¹. All activity concentrations were below the worldwide average except for ⁴⁰K. The radon exhalation rate varied from 2.8 to 7.2 mBq kg⁻¹ h⁻¹. The gamma index (I_γ), and radiological parameters, including the Radium equivalent activity (Ra_eq), and the external hazard index (H_ex), being below the recommended levels by UNSCEAR, ensure the safe use of these mines tailing to produce a geopolymer cement.

Radon is the main source of natural radioactivity, and its measurement is considered extremely important in radioprotection, given its relationship with the occurrence of lung cancer. In the last two years, measurements of this radioactive gas were carried out in Lima considering a grid of 5 km${}^2$ and the population density to determine the number of measurements to be carried out. Cellulose nitrate nuclear track detectors exposed in bare mode and diffusion chamber mode were used to estimate ${}^{222}$Rn concentrations. In diffusion chamber mode, non-commercial monitors and commercial monitors were used. The monitoring results are presented for 43 districts of the Lima Province whose population is approximately ten million inhabitants occupying a total area of 2655.15 km${}^2$. Measurements were made obtaining an average concentration of 49 Bq·m${}^{-3}$ using bare detectors and 66 Bq·m${}^{-3}$ using non-commercial diffusion chambers. Average concentrations obtained by both detector exposure modes were below the maximum concentration recommended by the WHO. A radon (${}^{222}$Rn) map was also obtained as a visual representation of the ${}^{222}$Rn levels in the Lima province using inverse distance weighting (IDW) interpolation.

Background: The increasing complexity of global supply chains has intensified the demand for transparency, traceability, security, and sustainability in logistics and operations. Blockchain technology enables decentralized, immutable frameworks that improve data integrity, automate transactions via smart contracts, and integrate seamlessly with the IoT and AI. Methods: This bibliometric review analyzes 559 peer-reviewed publications retrieved from Scopus and Web of Science using a PRISMA-guided protocol. Data were processed with Bibliometrix and Biblioshiny to examine scientific production, contributing institutions, author countries, collaboration patterns, thematic clusters, and keyword evolution. Results: The analysis reveals a 400% increase in publications after 2020, with China, India, and the USA leading in output but with limited international collaboration. Keyword co-occurrence and thematic mapping reveal dominant topics, including smart contracts, food supply chain traceability, and sustainability, as well as emerging themes such as decentralization, privacy, and the circular economy. Conclusions: The field is marked by interdisciplinary growth, yet it remains thematically and geographically fragmented. This review maps the intellectual structure of blockchain-enabled sustainable supply chains, offering insights for policymakers, developers, and industry leaders and outlining future research avenues centered on global cooperation, platform efficiency, and ethical and regulatory dimensions.

Radon anomalies have long been explored as potential geochemical precursors to seismic activity due to their responsiveness to subsurface stress variations. However, before this study, the scientific progression of this research domain had not been systematically examined through a quantitative lens. This study presents a comprehensive bibliometric analysis of 379 articles published between 1977 and 2025 and indexed in Scopus and Web of Science. Utilizing the Bibliometrix R-package and its Biblioshiny interface, the analysis investigates temporal publication trends, leading countries, institutions, international collaboration networks, and thematic evolution. The results reveal a marked increase in research output since 2010, with China, India, and Italy emerging as the most prolific contributors. Thematic mapping indicates a shift from conventional geochemical monitoring toward the integration of artificial intelligence techniques, such as decision trees and neural networks, for anomaly detection and predictive modeling. Notwithstanding this methodological evolution, core research themes remain centered on radon concentration monitoring and the analysis of environmental parameters. Overall, the findings highlight the coexistence of traditional and emerging approaches, emphasizing the importance of standardized methodologies and interdisciplinary collaboration. This bibliometric synthesis provides strategic insights to inform future research and strengthen the role of radon monitoring in seismic early warning systems.

Artificial intelligence is increasingly used to support public safety by predicting events, uncovering patterns, and informing decisions. In Latin America, where crime burdens are high and data systems are heterogeneous, a region-focused synthesis is needed to assess progress, identify gaps, and clarify operational implications. Accordingly, this PRISMA-guided, multilingual (English, Spanish, and Portuguese) bibliometric review synthesizes 146 peer-reviewed journal articles (2010–October 2025) to examine trends, methods, and application domains. Since 2018, publication output accelerated, peaking in 2024–2025. Regionally, Brazil leads within a multi-hub co-authorship network linking Latin American nodes to the United States and Spain; additional hubs include Colombia, Chile, Mexico, Ecuador, and Peru. Methodologically, three motifs dominate: temporal-dependence modeling; ensemble learners with cost-sensitive decision rules; and multimodal integration of remote sensing and computer vision with administrative data. At the application level, four families prevail: utility and fiscal-fraud analytics; environmental offenses with temporal modeling; cyber and platform-based analytics; and sensing, geospatial, and forensic workflows. However, evaluation practices are heterogeneous, with frequent risks of spatial or temporal leakage; moreover, reporting on fairness, accountability, and transparency is limited. In order to support responsible scaling, research directions include interoperable data governance, leakage-controlled and cost-sensitive evaluation, domain adaptation that accounts for spatial dependence, open and auditable benchmarks, and broader regional participation. To our knowledge, this review is one of the first multilingual, region-centered syntheses of artificial intelligence and crime in Latin America, and it establishes a reproducible baseline and an actionable evidence map that enable comparable, leakage-controlled evaluation and inform research, funding, and public safety policy in the region.