Perez Carpio, Jackson Edgardo
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Item type:PublicaciĆ³n, Implementing the SDGs in Higher Education: A Systematic ReviewSustainable development is essential for the well-being of society, as it enabling future generations to meet their own needs. Therefore, it is crucial to work on the 17 Sustainable Development Goals (SDGs) to eradicate poverty, protect the planet and ensure peace and prosperity. Universities must integrate actions related to the SDGs and communicate their results in research that promotes sustainability and sustainable development. A methodology including terms related to academic institutions, such as āuniversi*ā, ācollegeā, āthe 17 goalsā, ā17 SDGsā and āsustainable development goalsā was used to conduct a systematic literature search using the Boolean operators AND and OR to perform a systematic literature search. The resulting search string was: ((universi*) OR (college)) AND ((āthe 17 goalsā) OR (ā17 SDGsā)) AND (āsustainable development goalsā). The goal was to conduct a systematic literature review, that included articles on the implementation of the SDGs from 2015 to 2023, categorized them into three groups. Articles whose titles were not related to the scope of this research were excluded. It was concluded that research on SDG implementation in universities is limited, which can be attributed to the pandemic, lack of demand, and insufficient implementation of international policies regarding SDG compliance. Received: 16 March 2024 / Accepted: 15 August 2024 / Published: 05 September 2024Citas (OpenAlex): 2metric-badges.view 3 - Algunas mĆ©tricas estĆ”n bloqueadas por suconfiguraciĆ³n de consentimiento
Item type:PublicaciĆ³n, Observations of electric fields during two partial solar eclipses at the geomagnetic equator(2025-12-03); ; Urra, BenjamĆn A.Abstract. This study presents the first coordinated observations of atmospheric electric field (AEF) and ionospheric plasma drifts during the partial solar eclipses of 2 July 2019 and 14 October 2023, observed near the magnetic equator in Lima, Peru. AEF was measured using a field mill, while ionospheric drifts were obtained from radar observations at the Jicamarca Radio Observatory and local magnetometers. The two events displayed contrasting electrodynamic responses: in 2019, AEF variations were ambiguous due to meteorological fluctuations, while in 2023, clearer weather conditions revealed distinct decreases in both surface AEF and ionospheric vertical drift near maximum obscuration. These results demonstrate the variable nature of eclipse-time electrodynamics and demonstrate that simultaneous measurements of AEF and ionospheric electric field are crucial for elucidating the mechanisms of vertical coupling between atmospheric layers. Such coordinated observations provide preliminary insight into how solar and terrestrial drivers jointly modulate the near-surface electric environment, contributing to a more comprehensive understanding of atmosphereāionosphere interactions in low-latitude regions.Citas (OpenAlex): 0metric-badges.view 11 - Algunas mĆ©tricas estĆ”n bloqueadas por suconfiguraciĆ³n de consentimiento
Item type:PublicaciĆ³n, Predictive Model with Machine Learning for Environmental Variables and PM2.5 in Huachac, JunĆn, PerĆŗ(2025-03-12); PM2.5 pollution is increasing, causing health problems. The objective of this study was to model the behavior of PM2.5AQI (air quality index) using machine learning (ML) predictive models of linear regression, lasso, ridge, and elastic net. A total of 16,543 records from the Huachac, Junin area in Peru were used with regressors of humidity in % and temperature in Ā°C. The focus of this study is PM2.5AQI and environmental variables. Methods: Exploratory data analysis (EDA) and machine learning predictive models were applied. Results: PM2.5AQI has high values in winter and spring, with averages of 52.6 and 36.9, respectively, and low values in summer, with a maximum value in September (spring) and a minimum in February (summer). The use of regression models produced precise metrics to choose the best model for the prediction of PM2.5AQI. Comparison with other research highlights the robustness of the chosen ML models, underlining the potential of ML in PM2.5AQI. Conclusions: The predictive model found was Ī± = 0.1111111 and a Lambda value Ī» = 0.150025, represented by PM2.5AQI = 83.0846522 ā 10.302222000 (Humidity) ā 0.1268124 (Temperature). The model has an adjusted R2 of 0.1483206 and an RMSE of 25.36203, and it allows decision making in the care of the environment.Citas (OpenAlex): 1metric-badges.view 9 - Algunas mĆ©tricas estĆ”n bloqueadas por suconfiguraciĆ³n de consentimiento
Item type:PublicaciĆ³n, Biodegradation of Low-Density PolyethyleneāLDPE by the Lepidopteran Galleria Mellonella Reusing Beekeeping Waste(2022-09-09); ; Plastic pollution is one of the most serious environmental problems of this century because most plastics are single-use, and once their useful life is over, they become pollutants, since their decomposition takes approximately 100ā400 years. The objective of this research is to evaluate the efficacy of low-density polyethylene (LDPE) biodegradation by G. mellonella in the district of Pangoa, JunĆn, Peru. For the development of the study, the G. mellonella was conditioned in three groups of beekeeping residues (beeswax, balanced diet, and wheat bran); after the conditioning stage, the biodegradation treatment was developed, which consisted of placing the G. mellonella in terrariums with the LDPE, the treatments were carried out at three different times (24, 36, and 48 h). To evaluate the efficacy of biodegradation, two analyses were taken into account: the Raman analysis of the low-density polyethylene samples and the weight reduction of the treated LDPE. The results of the Raman analysis indicated that the best treatment was the one applied with G. mellonella conditioned with beeswax, obtaining a wavelength intensity of 0.45 Ī¼.a., while the weight reduction of the LDPE indicated that the best results were given at 36 h and conditioned with beeswax with a reduction of 236.3 mg. In conclusion, the use of G. mellonella for the biodegradation of low-density polyethylene is effective when it is conditioned with beeswax and the treatment is carried out at 36 h.Citas (OpenAlex): 12metric-badges.view 6