The National University of Trujillo (Spanish: Universidad Nacional de Trujillo) (UNT) is a major public university located in Trujillo, Peru, capital of the department of La Libertad. The university was founded by Simón Bolívar and José Faustino Sánchez Carrión, who met in Huamachuco; they signed the decree of foundation on May 10, 1824, before Peru's independence from Spain. National University of Trujillo, was the first republican university founded in Peru.UNT has approximately 16,000 students in 13 academic faculties, making it one of the largest universities in the country. The current rector is Dr. Carlos Vásquez Boyer.The UNT is ranked as one of the best universities in Peru.
The progressive degradation of water quality in Lake Titicaca, driven primarily by untreated wastewater discharges, diffuse agricultural runoff, and urban expansion, poses increasing risks to ecosystem integrity and public health. This study presents a hybrid framework integrating multi-campaign in situ monitoring (2011–2024), descriptive spatial mapping via Inverse Distance Weighting (IDW), and machine-learning regression to model two policy-relevant indicators: chlorophyll-a (Chl-a) and dissolved oxygen (DO). Four algorithms were benchmarked under grouped tenfold cross-validation to reduce spatial leakage: Random Forest, XGBoost, LightGBM, and an artificial neural network (MLP). XGBoost achieved the best out-of-fold performance for both targets, reaching mean R2 = 0.92 for Chl-a (testing MAPE = 10.89
The future exploitation of non-metallic minerals in La Libertad faces a central economic dilemma: extraction today generates immediate rents but reduces the available stock and constrains regional competitiveness in key inputs for construction, energy, and processing industries. This study aims to estimate and compare the intertemporal economic performance of clay, anthracite coal, and salt (halite) under finite reserves, explicitly incorporating the trade-off between profitability and resource depletion. A non-renewable resource model based on Hotelling’s rule is applied, operationalized through net price, discount rate ( r ), parametric price trajectories, and three marginal cost scenarios, together with physical stock constraints and an operational cap. Outcomes are evaluated under a fixed 15-year horizon (2025–2039) and under an endogenous horizon extending until depletion or economic infeasibility. Results indicate that coal dominates in value under the fixed horizon but is highly cost-sensitive (NPV ranging from USD 121.1 to 42.5 million), while clay exhibits greater stability (NPV USD 7.74–6.48 million), and salt proves fragile due to a short operational window (3 years; NPV up to USD 0.089 million). Under the endogenous path, clay sustains long-term value (depletion in 2083; NPV USD 568.4 million), coal concentrates rents in the short to medium term (2036; USD 213.3 million), and salt is rapidly depleted (2027; USD 5.52 million). The study concludes that regional management and policy should differentiate instruments and priorities by mineral, emphasizing cost efficiency for cost-sensitive resources, cautious valuation for short-horizon fragile resources, and long-term planning for structurally strategic resources.
The neutrophil-to-lymphocyte ratio (NLR) is an accessible biomarker of systemic inflammation with potential prognostic utility in cerebrovascular disease (CVD). Its relationship with prolonged hospitalization in stroke remains insufficiently explored in Peruvian populations. To evaluate whether the NLR at admission is associated with prolonged hospital stay (≥ 9 days) in patients with ischemic and hemorrhagic CVD treated at Hospital de Emergencias José Casimiro Ulloa (2022–2024) A retrospective observational study was performed including 227 adults with confirmed CVD. Clinical, demographic, and laboratory data were retrieved from medical records. Optimal NLR cut-offs were determined using RO1C curve analysis. Logistic regression models—stratified by stroke subtype—assessed associations between NLR and prolonged hospitalization, adjusting for relevant clinical variables and collinearity. Among 227 patients, 61.7
This systematic literature review examines the rapid growth of research on the use of drones applied to smart agriculture, a key field for the digital and sustainable transformation of the agricultural sector. The study aimed to synthesize the current state of knowledge regarding the application of drones in smart agriculture by applying the Kitchenham protocol (SLR), complemented with Petersen’s systematic mapping (SMS). A search was conducted in high-impact academic databases (Scopus, IEEE Xplore, Taylor & Francis Online, Google Scholar, and ProQuest), covering the period 2019–2025 (July). After applying the inclusion, exclusion, and quality criteria, 73 relevant studies were analyzed. The results reveal that 90% of the publications appear in Q1 journals, with China and the United States leading scientific production. The thematic analysis identified “UAS Phenotyping” as the main driving theme in the literature, while “precision agriculture,” “machine learning,” and “remote sensing” were the most recurrent and highly interconnected keywords. An exponential increase in publications was observed between 2022 and 2024. The review confirms the consolidation of drones as a central tool in digital agriculture, with significant advances in yield estimation, pest detection, and 3D modeling, although challenges remain in standardization, model generalization, and technological equity. It is recommended to promote open access repositories and interdisciplinary studies that integrate socioeconomic and environmental dimensions to strengthen the sustainable adoption of drone technologies in agriculture.
In this work, we investigate late-time interacting cosmologies within the framework of generalized Rastall gravity, where the interaction arises naturally from the non-conservation of the energy-momentum tensor. We formulate the background evolution of the dark sector as an autonomous dynamical system, defining interaction terms Q1=αf˙ and Q2=−f˙(1+α), with α a constant parameter and f a time-dependent function. Three interaction scenarios are studied: f∝ρm, f∝ρde, and f∝ρm+ρde, assuming a constant dark-energy equation-of-state parameter wde. For each scenario, we derive the closed dynamical system in terms of the density parameters (Ωde, Ωm), identify its fixed points, and analyze their stability across the parameter space. In this context, the phase space exhibits standard cosmological dynamics: an unstable radiation point, a transient matter saddle, and a stable late-time attractor with accelerated expansion. In addition, we perform a joint likelihood analysis using Cosmic Chronometers, PantheonPlus, and DESI data to obtain marginalized parameter estimates at the 68% and 95% confidence levels, constraining the parameter space in each interaction model.
