National University Toribio Rodríguez de Mendoza

Non-Technical Losses (NTLs) of electric energy compromise the operational efficiency and sustainability of the electrical system, particularly in the residential sector. This study addresses this problem by developing a predictive model that can estimate energy consumption and detect anomalous patterns. For this purpose, data were collected from the Plataforma Nacional de Datos Abiertos and the Osinergmin website. The study integrates two approaches: ARIMA, which is used to represent time series with well-defined seasonal patterns, and an approach based on XGBoost to represent non-linear behavior in more heterogeneous consumption intervals. The results suggest that ARIMA demonstrated optimal performance in stable cases, with errors close to zero in several cases, where the most representative systems are SR0148 with Mean Absolute Error (MAE) = 0.000124 and Root Mean Square Error (RMSE) = 0.003549, and SE1095 with MAE = 0.000287 and RMSE = 0.004481. XGBoost, on the other hand, reached its maximum performance in the interval "From 1 to 30 kWh", with MAE = 2.81, RMSE = 5.80, and a Coefficient of Determination (R²) of 0.13. This validates the effectiveness of the proposed approach based on the integration of more than one algorithm to identify electric consumption anomalies.

Spontaneous fermentation is a key stage in cocoa processing, during which the main flavor and aroma precursor compounds are formed as a result of microbial activity. This study provides the first integrated characterization of microbial diversity and associated biochemical properties during the spontaneous fermentation of fine-aroma cocoa in the Amazonas region of northern Peru. Using culture-dependent methods combined with DNA barcoding, a dynamic community of bacteria, yeasts, and filamentous fungi was identified, with a total of 79 microbial species detected across 144 h of fermentation. Microbial diversity was highest during the early stages of the process (12–48 h), with Shannon index values ranging from 3.02 to 3.08; it gradually declined as temperature increased from 26 to 55 °C and pH decreased from 4.79 to 3.59. Biochemical characterization based on carbohydrate assimilation, ethanol tolerance, and pectinolytic activity allowed the identification of a select group of native microorganisms with high potential for use as starter cultures. Overall, these results provide a scientific basis for the development of locally adapted starter cultures aimed at improving the efficiency, consistency, and quality of the fermentation process in fine-aroma cocoa and chocolate production.

P. peruviana is a species of agronomic and biotechnological interest; however, the relationship between in vitro regeneration and phenolic compound production remains poorly explored. This study evaluated the combined effects of thidiazuron (TDZ), explant type (cotyledon and hypocotyl), auxin type (naphthaleneacetic acid, NAA, or indole-3-butyric acid, IBA), and auxin concentration on shoot organogenesis, photosynthetic pigment content, and phenolic accumulation. An initial screening identified 4.54 µM TDZ as the optimal concentration for shoot induction. Subsequent experiments showed that morphogenic and physiological responses were strongly dependent on the interaction among explant type, auxin type, and auxin dose. Cotyledon explants consistently exhibited higher shoot regeneration, vigor, biomass accumulation, and photosynthetic pigment content than hypocotyl explants, which showed reduced physiological performance and a higher tendency for callus formation. NAA-based treatments primarily enhanced morphogenic traits, whereas IBA-based treatments were associated with increased photosynthetic pigment content and phenolic accumulation. Multivariate analysis integrating morphogenic, physiological, and biochemical variables identified cotyledon explants cultured with 0.5 µM IBA in the presence of 4.54 µM TDZ as the treatment achieving the most favorable balance between shoot regeneration, physiological stability, and controlled phenolic accumulation. These findings provide a robust basis for optimizing in vitro culture systems of P. peruviana that balance growth, physiological integrity, and secondary metabolism.

Subsistence family farming in Peru is increasingly constrained by ecosystem degradation, climate variability, and limited access to productive services, particularly where environmental exposure is high. This study develops an Agro-productive and Territorial Vulnerability Index (IVAPT) to evaluate environmental, ecosystem, and socioeconomic vulnerability of subsistence agriculture at the district level nationwide. The index integrates district-level agricultural survey data (ENA-2024) with multi-temporal MODIS NDVI series (2000–2024) and comprehensive climatic, topographic, land-cover, and accessibility indicators, processed through multivariate statistics. Three objective weighting schemes (ENTROPY, CRITIC, PCA) construct thematic sub-indices of Environmental Exposure (EnvExp), Ecosystem Condition (EcoCond), and Socioeconomic Capacity (SocioCap). Results show more than half of Peru’s 1552 districts fall within moderate to very high vulnerability, with highest concentration in the Amazon region (Loreto, Ucayali, Madre de Dios), Andean-Amazonian transitions, and highland districts (Huancavelica, Apurímac, Ayacucho, Puno) where biophysical constraints, ecosystem pressure, and socioeconomic isolation converge. Dimensional spatial complementarity EnvExp peaking on coast, EcoCond in Amazon, SocioCap in Andes demonstrates effective vulnerability reduction requires dimension-specific interventions. Despite divergent weighting schemes, spatial patterns remained consistent, validating identified hotspots. IVAPT provides a reproducible framework supporting evidence-based territorial planning and targeted investments in water infrastructure, ecosystem restoration, and climate adaptation.

Introduction: Smoking is a known risk factor for cardiovascular diseases, but its specific relationship with blood pressure remains a topic of debate. Recent studies suggest that different aspects of smoking behavior, such as intensity and duration, may have distinct effects on blood pressure. Objective: To evaluate the association between different measures of smoking behavior and blood pressure in the Peruvian population. Methodology: A cross-sectional analysis was conducted using data from the Peruvian Demographic and Family Health Survey (DHS) from 2018 to 2023. Multiple aspects of smoking were assessed, including current smoking status, intensity, duration, and the global tobacco index. Multiple linear regression models were used to examine the association between these measures and systolic (SBP) and diastolic (DBP) blood pressure, adjusting for sociodemographic and health variables. Results: A significant association was found between smoking intensity and elevated blood pressure. Smokers of 20 or more cigarettes per day showed an increase of 6.82 mmHg in SBP (95% CI: 2.90, 10.75) and 5.07 mmHg in DBP (95% CI: 2.44, 7.70) compared to non-smokers. The global tobacco index and smoking duration showed weaker and more variable associations with blood pressure. Conclusions: Smoking intensity, rather than other measures of smoking behavior, is more strongly associated with blood pressure levels. These findings highlight the importance of considering smoking intensity in cardiovascular risk assessment and suggest that prevention strategies should focus not only on cessation but also on reducing smoking intensity.

Abstract Chacha XR is an interactive project developed between 2021 and 2023 that explores contemporary forms of documentation and digital dissemination of cultural heritage in the context of Chachapoya archaeology. Through a web portal and a multiplatform app, users can explore seven pre-Columbian archaeological sites located in the northeastern Andes of Peru. Most of these are necropolises perched on inaccessible vertical cliffs in remote locations. The project leverages extended reality (XR) technologies to generate an immersive experience by integrating photogrammetric models, 360° panoramas, gigapixel imagery, 360° video, and spatial audio. This digital reconstruction enhances accessibility to fragile and geographically remote heritage sites, fostering both public engagement and academic research. Chacha XR builds upon over a decade of speleological and archaeological research, incorporating non-invasive documentation methods to preserve site integrity. The resulting hypermedia system provides an educational tool for researchers, students, and the general public, promoting cultural heritage awareness while addressing accessibility challenges. By bridging archaeological documentation and immersive media, Chacha XR contributes to heritage conservation, digital museology, and public archaeology, offering a replicable model for similar projects worldwide.

Spatial monitoring of olive systems in arid regions is essential for understanding agricultural expansion, water pressure, and productive sustainability. This study aimed to map coverage and estimate olive plantation density (Olea europaea L.) in the Atacama Desert, Tacna (Peru) through the integration of UAV-satellite multispectral images and machine learning algorithms (CART, Random Forest, and Gradient Tree Boosting). Forty-eight optical, radar, and topographic covariates were analyzed. Fifteen were selected for coverage classification and 16 for plantation density, using Pearson’s correlation (|r| > 0.75). The classification maps reported an area of 23,059.87 ha (38.21%) of olive groves, followed by 5352.10 ha (8.87%) of oregano cultivation and 725.74 ha (1.20%) of orange cultivation, with respect to the total study area, with overall accuracy (OA) of 86.6% and a Kappa coefficient of 0.81. Meanwhile, the RF and GTB regression models showed R2 ≈ 0.89 and RPD > 2.8, demonstrating excellent predictive performance for estimating tree density (between 1 and 8 trees per 100 m2). Furthermore, the highest concentration of olive trees was found in the central and southern zones of the study area, associated with favorable soil and microclimatic conditions. This work constitutes the first comprehensive approach for olive mapping in southern Peru using UAV–satellite fusion, demonstrating the capability of ensemble models to improve agricultural mapping accuracy and support water and productive management in arid ecosystems.