Conference Agenda

Este estudio tuvo por objetivo comprender cómo las comunidades locales perciben, usan y priorizan los servicios ecosistémicos derivados del Bofedal Escotacay (Canta, Lima, Perú), así como evaluar la relación de todas estas dimensiones entre sí. De esta manera se aplicaron 86 encuestas estructuradas, las cuales se sistematizaron de acuerdo a la escala de Likert y una escala de jerarquización comparativa, complementándose con un análisis cualitativo riguroso en función de preguntas con formato abierto aplicadas. Los resultados muestran una valoración positiva general (α de Cronbach = 0.825), destacando las dimensiones culturales (media = 3.83), conservación futura (media = 3.71) y bienestar futuro (media = 3.63), mientras que las recreativas obtuvieron menores puntajes. La mayoría de los participantes reportó un uso moderado del bofedal (50.9%), encontrándose asociación significativa entre frecuencia de uso y familiaridad con el ecosistema (χ² = 24.70; p = 0.003). En cuanto a prioridades, la provisión de recursos agrícolas (54.5%) y la conservación de la biodiversidad (12.7%) ocuparon los primeros lugares, seguidas del valor estético y el turístico. Asimismo, se hallaron asociaciones significativas entre la educación, ocupación y las prioridades asignadas (p < 0.05). En conjunto, los hallazgos evidencian que el Bofedal Escotacay es percibido más como un espacio vital para la subsistencia y la identidad cultural que como un sitio recreativo, lo que resalta la necesidad de integrar este tipo de conocimiento en políticas de gestión ambiental local.

Traditional price adjustment mechanisms in public road infrastructure projects exhibit structural constraints that affect contractual financial stability and, consequently, the continuity of critical works serving vulnerable populations. In the Peruvian regulatory framework, rigid application of polynomial formulas and conventional grouping of Unified Construction Price Indices (IUPC) have generated discrepancies between real market fluctuations and recognized contractual adjustments.

This research introduces a resilient contractual architecture model that strategically reorganizes technical index grouping as a financial balance and risk management instrument, incorporating humanitarian engineering principles aimed at territorial sustainability. A quantitative explanatory cross-sectional design was applied to three national road projects executed in 2021 under contracting modality. Monthly adjustments, deductive adjustments, bid variation effects, and an optimized index-grouping configuration were analyzed against executed adjustments.

Findings reveal strong statistical associations between optimized index structuring and improved financial consistency across projects. The evidence suggests that technically restructured adjustment systems reduce contractual distortions and strengthen alignment between physical progress and economic compensation.

The study concludes that price adjustment optimization should be understood not merely as an accounting refinement but as a structural resilience mechanism that safeguards continuity of essential public road infrastructure in territorially vulnerable contexts.

Violence, harassment, and discrimination continue to affect universities worldwide, undermining students’ well-being, academic performance, and trust in institutional protection mechanisms. In Colombia, despite the implementation of awareness programs and reporting protocols, recent studies reveal that more than 71% of students remain unaware of these resources. This critical gap highlights the need for innovative tools that not only facilitate reporting but also ensure timely support and effective case management. This paper introduces UniSegura, a web–mobile platform designed to empower the university community by providing secure, accessible, and user-centered channels for prevention and intervention. The solution integrates a mobile application for students and a web portal for counseling professionals, enabling a continuous flow of information. Among its most innovative features is Alma, a chatbot powered by GPT-4, which guides users through text or voice, identifies potential risk patterns, and directs them to appropriate institutional resources. Pilot testing with 60 students from Universidad del Norte demonstrated high acceptance: 85% considered Alma useful, over 80% expressed satisfaction with the platform, and 85% rated usability, navigation, and functionality between 4 and 5 on a five-point scale. Statistical validation confirmed acceptance levels above 83%. These results position UniSegura not only as a technological innovation but also as a model of social impact engineering, contributing to safer, more inclusive, and empathetic university environments.

In the Peruvian context, landslides represent a persistent threat, especially in the Andean regions where the combination of steep slopes, intense rainfall, and unregulated human activity increases terrain vulnerability. Every year, these events cause severe impacts on infrastructure, communities, and transportation networks, resulting in significant human and economic losses. The Alto Huallaga basin is among the most affected areas due to its geographic conditions and the expansion of extractive activities, which exacerbate landslide risks along critical roads. However, there remains a notable lack of systematized technical information from the government regarding the factors triggering these events. In response, this study proposes a methodology based on multivariable spatial analysis, integrating key variables such as slope, precipitation (CHIRPS), and vegetation cover (NDVI). A JavaScript-based script was implemented on the Google Earth Engine platform to temporally monitor and analyze these variables, enabling a comprehensive assessment of landslide susceptibility. The results provide valuable inputs for civil engineering planning and territorial management in the basin, contributing to a safer and more sustainable approach to geohazard risk reduction.

The Rímac River basin, the main source of water supply for Lima Metropolitan Area, exhibits a complex hydrological response influenced by climatic variability, topography, and soil properties, which complicates the accurate estimation of surface runoff using traditional approaches. In this context, the runoff coefficient (C) represents a key parameter for hydraulic design and hydrological risk assessment. This study aims to estimate the spatial and temporal distribution of the runoff coefficient in the Rímac River basin through the integration of slope, vegetation cover (NDVI), and soil permeability using the Google Earth Engine platform. For this purpose, satellite data from SRTM, MODIS, OpenLandMap, and SoilGrids were processed to generate monthly runoff coefficient maps with homogeneous spatial resolution. The results reveal a marked spatial and seasonal variability of the runoff coefficient, with higher values concentrated in the upper and middle sections of the basin and during wet and transitional periods, highlighting the usefulness of the proposed approach to support preliminary hydrological risk assessment and hydraulic design in basins with limited hydrometric information.

Abstract– Plastic shrinkage cracking is one of the primary early-age deterioration mechanisms in rigid pavements exposed to variable environmental conditions. This study evaluated the effect of incorporating natural fibers from Agave americana L. on reducing surface cracking in full-scale concrete slabs. Four volumetric dosages (0.00%, 0.50%, 0.75%, and 1.00%) were analyzed, measuring average crack width, total crack length, cracked area, and crack frequency. Results demonstrated that the 0.75% dosage achieved complete suppression of measurable cracking, identifying a critical fiber density threshold required to stabilize the early-age tensile stress field. Statistical analysis confirmed a significant structural effect of fiber dosage on cracking behavior. From a humanitarian engineering perspective, agave fiber constitutes a technically efficient, locally available, and economically viable solution to enhance pavement resilience in resource-constrained urban environments.

Personal indebtedness is influenced by multiple socioeconomic, financial, and behavioral factors whose identification is essential for decision-making in financial education and risk management. This study aimed to determine the factors associated with individuals’ decisions to incur debt through the application of a multinomial logistic regression model. A quantitative, explanatory approach was adopted, using data collected through a structured survey administered to a sample of economically active adults. The variables analyzed included sociodemographic characteristics, income level, consumption habits, credit perception, and financial behavior. The results show that income level, employment stability, financial education, and perceived necessity significantly affect the probability of choosing different levels of indebtedness, with statistically significant differences among the analyzed groups. The estimated model demonstrated adequate explanatory capacity and consistent classification of indebtedness profiles. It is concluded that multinomial logistic regression is a robust tool for identifying determinants of indebtedness, providing useful evidence for the design of financial education strategies and policies aimed at preventing over-indebtedness.