The National University of Saint Anthony the Abad in Cuzco (Spanish: Universidad Nacional de San Antonio Abad del Cusco) (UNSAAC), also known as Saint Anthony University of Cusco or University of Cusco, is a public university in Cusco, Peru and one of the oldest in the country. Its foundation was first proposed on March 1, 1692, at the urging and support of Pope Innocent XII. The document in which Pope Innocent XII sponsored the founding of the university was signed in Madrid, Spain by King Charles II on June 1, 1692, thus becoming Cusco's principal and oldest university. The university was authorized to confer the bachelors, licentiate, masters, and doctorate degrees.UNSAAC consistently ranks among the top ten universities in the country. It currently has 24 faculties with 37 professorial chairs and 29 academic departments..
Tropical montane cloud forests (TMCFs) are globally important ecosystems, acting as large carbon sinks and supporting exceptional biodiversity. However, climate-driven declines in rainfall threaten these forests, but their responses to long-term soil moisture deficit remain poorly understood. We implemented a 5-year throughfall exclusion (TFE) experiment in a Peruvian TMCF, reducing soil moisture by 69.1% across a 0.09 ha plot. We compared the full carbon cycle budget, and surveyed tree physiological traits linked to hydraulics, metabolism and nutrients in the TFE plot and an adjacent, unmodified control (CON) plot. Soil drought reduced gross primary productivity by 4.24 ± 1.97 Mg C ha-1 year-1 but did not change net primary productivity because of an equivalent 3.38 ± 1.42 Mg C ha-1 year-1 decline in autotrophic respiration. Net ecosystem exchange also remained unchanged over 5 years of soil drought. Trees did not change xylem conductivity, hydraulic safety margins or photosynthetic capacity in the TFE, but did have 0.027 ± 0.011 g cm-3 denser wood and 4.58% ± 1.03% higher trunk starch concentrations. These results suggest that trees in TMCF avoid hydraulic failure and carbon starvation under sustained soil moisture drought via metabolic downregulation, resource conservation and non-structural carbohydrate storage. However, reduced uptake of nutrients (nitrogen, phosphorus, calcium) and 90.6% ± 29.8% decline in fruit production may impact future growth and demography. Our findings demonstrate surprising resilience of TMCFs to sustained, severe soil drought but highlight potential impacts on nutrient cycling and reproduction under climate change. Understanding the impacts of soil drought in conjunction with other climatic changes (e.g., fog reduction, temperature increases) is needed to fully assess the resilience of TMCFs to climate change.
Neonatal health requires precise lipid quantification in human milk to ensure proper nutritional development. Traditional manual methods, such as the creamatocrit, are limited by human-induced bias and significant measurement uncertainty. This study presents a low-cost Computer Vision System acting as an automated optical sensing modality for estimate the cream fraction (c) using advanced Machine Learning regression, which is subsequently used to derive fat and energy quantification through established analytical equations. The system is optimized for the Gold-LED spectrum, which enhances the dynamic range to 226 a.u. for robust feature extraction. We evaluated 28 distinct ML regression models across three feature spaces (Gray Scale, RGB, and Combined). The results, based on 6400 samples, demonstrate that the Rational Quadratic GPR model achieved the highest predictive stability with a coefficient of determination of R2=0.867. This computational framework achieved a 57.5% reduction in relative error compared to manual benchmarks. SHAP analysis indicates that the model selectively attributes higher importance to Red channel intensities and Blue contrast gradients, which correspond to the optical scattering characteristics of lipid globules. These findings validate the system as a stable sensing modality for non-invasive quantification. The proposed architecture integrates cost-effective hardware with high-precision analytical modeling, offering a reagent-free and operationally feasible alternative for standardized nutritional assessment in neonatal intensive care units and milk banks.
Climate and atmospheric changes are impacting forest function and structure worldwide, but their effects on tropical forest diversity are unclear. Nowhere is the scientific challenge greater than in the Andes and the Amazon, which together include the world’s most diverse forests. Here, using 406 permanent plots spanning four decades of intact lowland and montane forest dynamics, we test for long-term change in species richness and assess the influence of climate and other variables. We show that, at a continental scale, species richness appears stable, but this masks substantial regional variation. Species richness increased in Northern Andean and Western Amazon plots, yet declined in the Central Andes, Guyana Shield and Central-Eastern Amazon. Overall, warmer, drier and more seasonal forests lost species, while those at higher elevations, in less fragmented areas and with faster rates of tree turnover experienced increases. Region-specific drivers, particularly precipitation seasonality and demographic factors, modulated these trends. The results highlight the diverse ways in which Amazon–Andes forests are changing and underscore the critical need to preserve large-scale ecosystem integrity to maintain local tree diversity. By doing so, Northern Andean forests in particular could serve as an important refuge for species increasingly displaced by climate change. This study examines long-term changes in species richness across tropical forests in the Andes and Amazon. Hotter, drier and more seasonal forests in the eastern and southern Amazon are losing species, while Northern Andean forests are accumulating species, acting as a refuge for climate-displaced species.
Amazon rainforests face intensifying water stress due to increases in vapour pressure deficit and changing hydrological regimes. Embolism resistance (Ψ50) is a critical metric of tree survival under drought conditions, it is defined as a plant's capacity to resist disruption of xylem water flow due to air bubble formation from water stress. However, measurements of Ψ50 are only available for a limited number of Amazon locations and species. Conversely, data on forest taxonomic composition are abundant across Amazonia, and if Ψ50 is conserved phylogenetically, these data could provide a way to scale-up drought resistance patterns. Here we evaluate Ψ50 measurements across non-flooded Amazonian tree taxa and reveal a moderate phylogenetic signal, with phylogenetic conservatism evident at the family-level. Notably, Fabaceae is amongst the most embolism-resistant tree families in Amazonia. Leveraging the phylogenetic signal we use species composition and tree size data from 448 forest plots across Amazonia to produce a macroecological assessment of Amazonian vulnerability to embolism. The resulting estimate spatial pattern reveals that forests in the Brazilian and Guiana Shield regions, where Fabaceae abundance is high, show strong resistance to embolism. In contrast, tree communities in Western Amazonia appear more vulnerable to embolism, suggesting a reduced capacity to withstand future drought conditions.
The production of reproductive structures of entomopathogenic fungi was evaluated using strains isolated from the province of La Convención, Cusco, Peru: Beauveria bassiana (KIT-21), Cordyceps spp. (ALF-01), and two strains of Isaria spp. (IV-09 and PR-02). Four solid substrate formulations based on brown rice were incubated under controlled conditions, with the developmental phase of the reproductive structures occurring under blue LED light at 20 °C and 88% relative humidity. Synnemata and stromata length and fresh biomass were measured as response variables at 30 and 120 days, respectively. Because the data showed deviations from normality and heteroscedasticity, inferential analysis was conducted using a two-way ANOVA with Welch’s correction, complemented by non-parametric tests (Kruskal-Wallis), which revealed significant effects of the substrate and substrate-strain interactions. Comparatively, the reproductive structures of Isaria showed the highest values. In particular, the greatest mean synnemata length was recorded in formulation F3, with PR-02 (26 mm) standing out, followed by F4 (25 mm), while IV-09 showed its best performance in F2 (25.7 mm). Fresh biomass followed a similar trend, with higher values observed for Isaria, especially PR-02 in F3 (1.14 g). Overall, the results indicate that brown rice substrate supplemented according to formulation F3 constitutes a viable and scalable substrate for the production of reproductive structures.
