La revista Sciéndo Ingenium es el órgano oficial de publicación científica de la Escuela de Postgrado de la Universidad Nacional de Trujillo, de periodicidad trimestral. Atendiendo a las directrices del CONCYTEC Perú para indizar revistas científicas, desde marzo del 2019 sólo se recibirán y publicarán manuscritos del área de Ingeniería y Tecnología, dejando de esta forma el enfoque multidisciplinario. ISSN: 3084-7788 (En línea) DOI: 10.17268/rev.cyt Título abreviado: Scién. Inge.
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Implementation of an ISO 45001:2018-Based OH&S Management System to Reduce Workplace Accidents in Construction Companies
This research aimed to develop and implement an Occupational Health and Safety Management System (OHSMS) based on ISO 45001:2018, in order to reduce workplace accidents in a construction company. A diagnostic assessment of regulatory compliance and accident history was conducted during 2023, identifying key weaknesses in risk management. Based on this assessment, an OHSMS adapted to the organization's characteristics was developed, implemented, and evaluated using accident and compliance indicators. The results showed an 87.5% reduction in workplace accidents, from eight cases in 2023 to one in 2024. Furthermore, the degree of alignment with the requirements of ISO 45001:2018 increased from 21.6% to 98.9% after the internal audit, demonstrating significant progress in preventative management. These results show that the implemented system directly contributed to reducing occupational risks and consolidating safety-oriented practices. Consequently, it was verified that the implementation of an OSHMS based on this standard significantly strengthens preventive performance in activities specific to the construction sector.
Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0/deed.es
Recent advances in the use of osmotic dehydration of fruits: a bibliometric review
This research aims to conduct a bibliometric analysis of the application of the osmotic dehydration process in fruits. A quantitative approach using bibliometric and scientometric techniques was used, utilizing a collection of 627 articles (2015–2025). Using Bibliometrix (R) and VOSviewer, co-authorship networks, thematic groups, conceptual evolution, and productivity and impact indicators were identified. The results show that dehydration technology is a dynamic line of research where multiple variables converge, such as processing techniques, nutritional and sensory quality, as well as structural characteristics of foods. The studies highlight numerous opportunities for synergy, referring to the application of ultrasound or vacuum during osmosis to improve efficiency without compromising quality.
Ergonomic Model Based on ISO 45001 and ISO 11228 to increase productivity in a Metalworking Company
This study describes the implementation of an ergonomic model based on ISO 45001 and ISO 11228 standards to increase productivity and improve working conditions in a Peruvian metalworking company. A pre-experimental design was used, employing tools such as RULA, REBA, and OWAS to assess working postures and ergonomic risks. After applying the model, a 15.3% increase in efficiency, 16.7% improvement in productivity, and 50% reduction in absenteeism were observed. It is concluded that the systematic application of international standards allows ergonomics to be integrated as a strategic management tool.
Walter Hugo Torres Bustamante Torres Bustamante
Occupational risk management to reduce the accident rate at Frigotech in Peru
The purpose of this analysis was to examine occupational risk management at Frigotech del Perú S.A.C., in order to identify the most vulnerable areas, assess risk exposure, and establish control methodologies that contribute to reducing accidents. The study was framed within a descriptive approach, with a longitudinal, non-experimental design. Tools such as the initial diagnosis, the IPERC matrix, the annual OSH plan, and OSH-related statistics were used. The results showed that the highest level of risk was concentrated in the Operations area. Based on this diagnosis, a SGSST plan was implemented, in accordance with Law No. 29783. As a result, between September 2024 and February 2025, the Accident Rate was reduced from 61% to 28%, the Frequency Rate fell from 61% to 28%, and the Severity Rate fell from 25% to 6%. These results show that effective risk management allows for hazard identification, risk assessment, and the application of appropriate corrective measures, thus contributing to a safe and healthy work environment.
Integration of Multivariable Model Predictive Control, Statistical Process Con-trol, and Artificial Neural Networks for the Detection and Management of Structural Changes in Industrial MIMO Processes
This research addresses the detection and monitoring of structural changes in multivariable MIMO industrial processes through an integrated architecture that combines multivariable model predictive control, statistical process control, and artificial neural networks. The objective is to improve operational discrimination among external disturbances, expected operating conditions, and internal structural changes in the process, while preserving adequate closed-loop regulation performance. The methodology is based on controlled and reproducible simulations of a MIMO process under systematically designed scenarios, including step disturbances, activation of operational constraints, and internal parameter drifts. Multivariable model predictive control acts as the regulation mechanism, whereas statistical process control supervises statistical stability through multivariate indicators applied to model residuals. Artificial neural networks are employed as nonlinear reference models for structural consistency assessment, without directly intervening in the control action. The results show that the MPC+ANN+MSPC architecture reduced the post-event alarm occupancy from 0.9834 to 0.1492 in Scenario S5, while maintaining RMSE, MAE, and control effort values comparable to those of the linear MSPC scheme. It is concluded that the proposed integration is a robust and viable tool for advanced supervision of MIMO industrial processes.
Machine Learning as a Pedagogical Tool to Optimize Reading Comprehension in Primary School Students
This study analyzed the impact of machine learning on the reading comprehension of sixth-grade students at a public school in Monsefú in 2024. Three predictive models developed with AutoML, XAI, and DataOps were implemented, aimed at identifying patterns and providing personalized pedagogical support at the literal, inferential, and critical levels. The design was explanatory, with a quantitative approach and a quasi-experimental design. Pretests and posttests were administered to two parallel groups (experimental and control, n=40 each), using validated instruments. In the experimental group, improvements of 24,9% were observed in reading comprehension (62,4% to 87,3%), while in its dimensions, there were improvements of 20,5% at the literal level (from 63,8% to 84,3%), 24% at the inferential level (from 62,1% to 86,1%), and 30,3% at the critical level (from 61,4% to 91,7%). The Wilcoxon and Mann-Whitney U tests showed statistical significance in the three levels evaluated (p < 0,05). Predictive model 03 (test) achieved 100% precision, 100% completeness, and 100% accuracy, determining an R2 of 0,998, which supports that the model correctly explains reading comprehension at all levels. It is concluded that the use of machine learning improves reading comprehension in elementary school students and contributes to data-driven pedagogical decision-making.
Modelado y análisis de temperatura y composición del gas para la evaluación del riesgo de formación de hidratos en gasoductos submarinos
Gas hydrates (HGs), also known as clathrates, represent a critical operational threat in natural gas transportation systems in offshore environments, especially under high-pressure, low-temperature conditions. Therefore, a computational framework is presented to assess the risk of hydrate formation in deep-water gas pipelines under offshore operating conditions in Peru. Three Python models are integrated: (1) a predictive tool based on the Towler and Mokhatab correlation, extended to simulate sensitivity to variations in specific gravity; (2) a thermal gradient model calibrated with local oceanographic data, representing the exponential attenuation of temperature with depth; and (3) a compositional adjustment algorithm that transforms multicomponent gas mixtures from a dry to a wet basis, quantifying the impact of water content on hydrate stability. The models are validated with representative field data from Talara, allowing the identification of thermodynamic instability zones and critical compositional thresholds. The results show that mixtures with higher ethane content shift the formation temperature to higher values ​​and provide technical criteria for risk management in subsea pipelines.
Production Model with ERP for optimum Productivity in SMEs of the Metal Mechanics Sector in Trujillo La Libertad
The objective of this research is to propose a technological solution that contributes to improving the competitiveness of micro and small enterprises in the metal-mechanical sector in the city of Trujillo, through greater integration with the supply chain by means of information and communication technologies. The study focuses on the implementation of an Enterprise Resource Planning (ERP) system as a strategic tool to optimize productivity, strengthen innovation capabilities, improve value chain management, and support business decision-making. The methodology is based on the design and development of an advanced production system, structured through functional ERP modules, as well as on the validation of the source code to ensure its proper operation. As a result, the first stage of the project was completed, corresponding to the design and integration of the system modules, which were implemented and hosted in the Data Center of the Department of Industrial Engineering at the National University of Trujillo. The proposed solution demonstrates a positive impact on productivity, profitability, and strategic management of the MSEs in the analyzed sector.
Proposal to improve the solids and grease recovery process from pumping water at Copeinca Chancay 2022
The central proposal of this was to improve the efficiency of grease traps by incorporating a pressurized system with compressed air to the solids and grease recovery traps, projecting to increase the recovery of total suspended solids from 13,47% in (TSS) and 29,15% fats (ppm) by 60% in both TSS and grease (ppm) The problem is caused by the water being pumped out of the flotation cells, which averages 11794 ppm in total suspended solids, 6225 ppm in grease, and has a pH of 6,44. The high fat content makes treatment difficult in the chemical stage to meet the maximum permissible limits of 700 ppm TSS, 350 ppm fat and pH between 5,0 – 9,0. The design parameter values ​​were calculated as 0,011 ml air/mg solids and 0,017 ml air/mg fat at a recirculation flow rate of 300 m3/h. Using Henry's law and the Setschenow coefficient, the solubility of air in seawater was calculated as 3,67×10−3 mol/L with an air flow rate of 31,8 kg/h.The economic analysis shows that the proposal is profitable, with an IRR of 179%, NPV of $656845,33 and a payback of 0,58 years.
Characterization of water from the Chavimochic Drinking Water Treatment Plant for compliance with Drinking Water Quality Regulation
The aum of this study was to identify contaminants present in the surface water entering the Chavimochic Drinking Water Treatment Plant from the Santa River intake and to evaluate the quality of the drinking water distributed in the province of Trujillo. The research was applied in nature, with a non-experimental and cross-sectional design. Samples were collected at different points during the dry and wet seasons, and physicochemical, inorganic, and microbiological parameters were analyzed using standardized laboratory methods. The results were compared with the Maximum Permissible Limits established by current national regulations. The findings showed that surface water exhibited high levels of turbidity, total coliforms and heavy metals such as arsenic, iron, and manganese, with greater incidence during the wet season. In drinking water, most parameters complied with regulatory standards; however, values close to or exceeding the limits were identified at certain points, requiring greater control of hardness, sulfates, nitrates, arsenic, and total coliforms. It is concluded that, although the treatment process generally ensures the quality of distributed water, factors associated with seasonal variability and system conditions may affect its potability.
Proposal for the Implementation of the Occupational Health and Safety Man-agement System in Compliance with Law 29783 to Prevent Workplace Acci-dents at EMIMSAC, 2024
The management of Occupational Health and Safety (OHS) in Peru used to be limited; there was no preventive culture within companies. Workplace safety focused more on protecting machinery than on protecting workers, and safety largely depended on employees’ experience. Currently Occupational Health and Safety (OHS) has evolved in Peru, adopting a preventive, comprehensive, and participatory approach. With the enactment of Law 29783, the Occupational Health and Safety Law, all companies are required to implement an Occupational Health and Safety Management System (OHSMS), complemented by its regulation, Supreme Decree 005-2012-TR, and further detailed in Ministerial Resolution No. 050-2013-TR, which specifies the mandatory documents and records for its implementation. In the review of the system’s guidelines, the company EMIMSAC obtained a compliance score of 46.7%, receiving a “fair” rating. The PHVA (Plan–Do–Check–Act) method was applied, and two surveys related to accidents and safety were carried out. The company recorded six minor accidents during 2023, showing that the current system is insufficient to protect workers. The absence of an OHSMS exposes the company to potential fines and administrative sanctions by the National Superintendence of Labor Inspection (SUNAFIL). Based on the results obtained, the urgency of proposing the implementation of an OHS management system according to Law 29783 is justified.
Environmental management tools and their contribution to the formalization of small-scale mining operations of the company C.M. Chilia
The purpose of this study was to examine how environmental management tools impact the formalization of small-scale mining, using the case of the company C. M. Chilia. A descriptive approach was adopted, based primarily on the environmental management guidelines for formalization established by Supreme Decree 0004- 2012-MINAM. The research demonstrated that, despite initial challenges in meeting legal requirements, the company was able to implement the elements required by the legislation, investing resources in monitoring, follow-up, and emergency plans during the extraction phases. Using a matrix of significant factors, it was concluded that mining activities produce low-magnitude environmental impacts, although this did not eliminate the need to establish prevention mechanisms. It was recognized that the use of geographic and geomorphological maps of the area, manuals for assessing the impact of mining activity, and strategies for the conscious and responsible management of solid waste promote sustainable and community-friendly economic activities. The investigation concludes by noting that environmental management instruments are fundamental for the formalization of mining and the implementation of practices aligned with environmental conservation. To achieve these instruments, investment was required in each phase of the process, resulting in construction costs totaling S/. 19,200.00. This situation contributed to a closure in accordance with the planning and, above all, in compliance with the provisions of the environmental management instruments.
Development of a mobile application to improve occupational risk management in an Agribusiness
The purpose of this investigation was to design and enforce a mobile operating interface with the Android Studio platform to optimize preventive verification processes for working conditions and improve the coverage of the comprehensive preventive management scheme. Firstly, the fresh blueberry production process was thoroughly characterised, with risks identified in each phase using a 6x6 IPERC matrix. The required sample size was then determined, after which a survey was administered to 255 workers. The results made it possible to specify the system's functional requirements. Based on these results, the application was developed. It consists of seven modules: area; person responsible; finding; corrective action; type of finding (unsafe act or hazardous condition); date; and photographic evidence. Implementing this technological tool generated substantial improvements: findings increased from 429 in 2023 to 780 in 2024 (an 83% increase), while closures increased by 40%. Similarly, there was a 68,42% reduction in accident frequency and a 29% reduction in severity. Finally, Poisson's probabilistic modelling verified that the λ parameter decreased from 2,08 to 0,50, corroborating the innovation's effectiveness in mitigating workplace accidents.
Financial inclusion rate based on solidarity financing of family units of MSEs in Trujillo
At present, microfinance client financing is based on an individual assessment of MSMEs with a low level of individual financial inclusion. Therefore, this research proposes to calculate an indicator of financial inclusion of adults in households with MSMEs in Trujillo. In the methodology, the indicator is calculated in function of the dimensions of use, access and quality of the financial products that attend the MSME segment and according to the human development index (HDI) used by the UNDP. The individual financial inclusion indicator of the households of Trujillo's MSMEs shows a result of 0.317, with 0 being no financial inclusion and 1 being total financial inclusion. And the indicator of financial inclusion based on solidarity financing of family units with MSMEs yields a result of 0.607, concluding that the indicator of financial inclusion of family units with MSMEs in Trujillo allows their financial inclusion much more than individual inclusion. In addition, with a Monte Carlo simulation, the variable with the highest level of sensitivity in the indicator is the amount of credit approved.
Problem Based Learning and Academic Performance in Students of Technological Higher Education
The objective of this research was to demonstrate the impact of applying the Problem-Based Learning (PBL) methodology on the academic performance of students in the Technological Research course of the Technical Nursing program at the Mariano Iberico Rodríguez Technological Institute in Cajamarca, 2018. Based on the theory of action learning and collaboration, the research was conducted with a sample population of 45 students divided into two teams: an experimental team of 25 students and a control team of 20. A mixed quasi-experimental methodology was used, with pre-tests and post-tests. The data was analyzed using the student’s t-test to examine small samples, leading to the following conclusion: the application of PBL to the experimental team improved their academic performance and fostered positive attitudes and skills compared to the control team. The contribution to knowledge lies in demonstrating that the application of PBL contributes to comprehensive training for future professionals.
Application of the PMI’s Agile Approach for the validation of a circular economy innovation project
This research examines the application of the agile approach proposed by the Project Management Institute (PMI) in the management of innovation projects. The main objective was to determine whether this approach enables the validation of an innovation project. The study is applied in nature, with an explanatory design and a quantitative focus, utilizing statistical methods to analyze data collected from the population involved in the innovation project. The findings suggest that the implementation of the PMI's agile approach may contribute to project validation by enhancing the acceptance of deliverables through continuous iterations. It is concluded that this approach shows potential effectiveness in validating innovation projects, supporting the alternative hypothesis and providing a foundation for both academic advancement and professional practice in project management. This study differs from previous research, which generally addresses the traditional PMI approach, by examining the application of the PMI agile framework in a context of sustainable innovation developed by a Peruvian microenterprise. This allows for demonstrating its relevance and adaptability in smaller-scale business environments with limited resources. This perspective adds value by analyzing how the PMI agile practices can contribute not only to project validation but also to strengthening sustainability and competitiveness in microenterprises.
Analysis of Open-Ended Questions in Teacher Performance Evaluation Using Text Mining in R and Chat GPT
This study presents a comparative analysis of Text Mining applications in R and the ChatGPT language model for processing open-ended responses in teaching performance evaluations at the National University (UNA) of Costa Rica. Simulated data based on historical student evaluations were used to ensure confidentiality. The analysis in R included techniques such as tokenization, term frequency analysis, word association, and sentiment analysis, while ChatGPT was employed for semantic interpretation, summary generation, and automatic categorization of strengths and areas for improvement. The results show that R provides statistical precision and the ability to explore textual patterns, whereas ChatGPT excels in interpretative flexibility and its potential to automate analytical report generation. The high correlation between both approaches in the detection of emotions and key topics demonstrates the complementarity of their outcomes. It is concluded that integrating text mining tools and language models can optimize qualitative analysis in educational contexts, promoting more objective, efficient, and evidence-based evaluation processes. This combined approach offers a replicable framework to strengthen academic management and foster continuous improvement in university teaching quality.
Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0/deed.es
Plan for the minimization and valoration of hazardous waste generated in vehicle maintenance workshops
This article presents a technical proposal to minimize and recover hazardous waste generated in a vehicle maintenance workshop focused on oil changes for buses and trucks. A descriptive methodology based on direct observation of the processes and documentary analysis was applied, identifying inadequate practices in the management of contaminated oils, filters, rags, and containers. Based on the diagnosis, actions such as source segregation, safe storage, and channeling to authorized managers were implemented. As a result, a 38,0% reduction in hazardous waste generation was achieved, highlighting a 30,0% reduction in used oils and a 23,0% reduction in contaminated filters. Likewise, 100,0% of the collected oils and 65,0% of the metal filters were recovered, representing an overall recovery of 62,0% of the total segregated waste. Overall, the proposal significantly contributed to improving environmental control, reducing operational risks, and strengthening regulatory compliance, positioning itself as a viable and sustainable alternative for hazardous waste management in maintenance workshops.
Study of Thermal Performance of Vaccum-Tube for Solar Water Heaters Adapted for Peruvian Coastal Scenario
The present research aimed to theoretically determine the arrangements of evacuated tubes, considering both tilt angle and inter-tube spacing, that maximize the total annual energy collection for five Peruvian coastal cities. The parameters considered included tube dimensions, azimuthal orientation, tilt angle, and inter-tube spacing. To perform a parametric study of the total solar energy captured by a single evacuated tube, varying the tilt angle for each of the 365 days of the year, the spacing between tubes, and the geographic location of five coastal Peruvian cities, a mathematical model was implemented in Matlab/Octave. The results show that maximum solar energy collection is achieved with tilt angles between 0° and 15° and a relative spacing between tubes equal to twice the outer diameter. Furthermore, it was demonstrated that the optimal operating tilt angles of evacuated tubes depend on the specific city in which they are installed. Unlike commercial systems, tubes arranged at a 15° tilt can capture greater amounts of energy without compromising their thermal conversion through the thermosiphon effect.
Stress Measurement on TiN/TaN Multilayers coated by Magnetron Sputtering with Bias on Silicon Substrate (100)
In the present study, the stress behavior in TiN/TaN multilayer films, coated on 0.3 mm thick silicon (100) wafers using the reactive Magnetron Sputtering technique, was investigated. The main objective was to analyze the influence of the substrate bias and the number of bilayers on the residual stress of the thin films, while maintaining a constant total thickness. The coatings were produced in an Ar/N2 atmosphere, with a substrate temperature of 400 °C and bias of -50 V and -250 V. The nanocrystalline structure and morphology of the multilayers were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM), respectively. The stress was determined by measuring the substrate curvature via laser deflection, using the Stoney formula. A transition in the stress behavior from tensile to compressive was observed as the bias voltage was increased from -50 V to -250 V. Specifically, for a bias of -50 V, the stress was tensile, and its absolute value increased slightly with the number of bilayers. In contrast, for a bias of -250 V, the residual stress was compressive, and its absolute magnitude tended to decrease when going from 2 to 4 bilayers, subsequently stabilizing for a higher number of bilayers. These findings demonstrate the possibility of modulating the stress state in TiN/TaN multilayer systems by controlling the bias, which is crucial for optimizing the adhesion and mechanical performance of protective coatings and other surface engineering applications.
Influence of the content and particle size of rice husk ash on the water susceptibility of asphalt mixtures
This study investigates how rice husk ash (RHA) content and particle size influence the water susceptibility of asphalt mixes. A two-factor experiment was conducted, varying RHA proportions (2.5%, 5.0%, and 7.5%) and particle sizes (149, 74, and 53 µm). The RHA, sourced from agro-industrial wastes in Trujillo, Peru, was previously analyzed by, scanning electron microscopy (SEM) showed irregular, porous, and angular particles, typical of ashes produced at moderate temperatures, which enhance binder interaction and internal friction. The ash analysis also identified crystalline phases like cristobalite and quartz, suggesting chemical reactivity. Coarse and fine aggregates met Peruvian standards for durability and wear resistance. The optimal asphalt cement content was 4.39%, balancing cohesion, stability, and air voids. The experimental results indicate that adding 5.0% RHA, especially with particle sizes smaller than 53 µm, significantly improves the mixture's resistance to moisture damage. This not only enhances the longevity of pavements but also promotes sustainability by incorporating waste materials into road construction. The incorporation of RHA not only improves the technical performance of asphalt mixtures, but also represents an environmentally beneficial strategy by reusing an abundant agricultural waste, reducing the environmental impact and promoting a circular economy.
Assessment of cement-based boards reinforced with fibers extracted from Andean Ichu grass
The continuous growing of the construction industry it is challenging to find the right choice for raw materials especially fibers for cement-based composites. In this study, raw Ichu fibers were evaluated to be used as reinforcement of cement matrices; mercerization treatment of the original fibers followed by the shear defibrillation technique were used to obtain the pulp; afterward, slurry-dewatering with the final pressing process technique were used to manufacture the composites boards. Results show that Ichu fibers required low aggressive mercerization treatment; furthermore, with mechanical shear defibrillation more than 80% of the defibrillated fiber present an aspect ratio over 80. The manufactured fiber cement composites board present a modulus of rupture over 8 MPa; moreover, with outdoor and indoor aging, samples modulus of rupture increases, reaching around 13.5 MPa for the outdoor aging; furthermore, progressive embrittlement was observed with impact over aging time. Finally, based on the mechanical properties of the boards, results suggest that with 9%wt of the Ichu pulp fibers as reinforcement, boards shown a bests characteristic.
Challenges to the integration of circular economy into the strategic management of the agricultural sector: A systematic review
The circular economy is emerging as a key strategy for achieving sustainability in the agricultural sector, given its dependence on natural resources and its environmental impact. This study aims to systematically analyze the scientific literature on the incorporation of circular economy into agricultural sector management, using the strategic direction approach as an analytical framework. The PRISMA protocol was used for the systematic review of 35 scientific papers selected from international databases. Bibliometric and thematic analysis was conducted using R Studio, which allowed for the identification of trends, co-occurrence networks, and research gaps. The results show a progressive growth in publications related to the circular economy in agricultural companies, with a predominance of studies focused on environmental and internal process perspectives, while financial and organizational learning dimensions are less addressed. It is concluded that implementing CE in the agricultural sector requires a comprehensive strategic approach that articulates sustainability and organizational performance indicators, such as investment in R&D for green technologies and innovation in patents. This study contributes a useful conceptual framework for researchers, policymakers, and agroindustrial managers
Fine-tuning a Long Language Model for Curriculum Vitae Classification
Este trabajo tuvo por principal objetivo clasificar curriculums vitae respecto al área de profesión, tarea importante en la gestión de recursos humanos y captación de personal. Esta investigación busca explorar las capacidades de clasificación de los Modelos de Lenguaje Largo (MLL) realizando un análisis comparativo versus métodos tradicionales de Machine Learning. Para lograr tal objetivo se empleó la técnica de fine-tuning al Modelo de Lenguaje Largo pre-entrenado por Google en el idioma inglés llamado BERT BASE UNCASED empleando un dataset de más de 3 mil currículums vitae de 25 áreas de profesión y 3 épocas de entrenamiento contra los modelos tradicionales Random Forest, SVM, Logistic Regression y Naive Bayes Multinomial. La metodología está compuesta por 7 etapas esenciales para adaptar un modelo pre-entrenado en una tarea específica asegurando su óptimo performance. La investigación proporciona un análisis comparativo enfocándose en las métricas Exactitud, F1-score, Precisión y Recall. Los resultados más importantes obtenidos fueron 83,0% de Exactitud y 82,3% de Precisión para el modelo base de Google y 82,8% de F1-score y 86,2% de Recall para Naive Bayes Multinomial revelando que el modelo base de Google tiene un buen desempeño prediciendo la clasificación de currículum vitae mientras que Naive Bayes Multinomial es mejor para detectar la mayoría de casos positivos. Esta investigación no solo contribuye mostrando el desempeño de los MLL para la tarea de clasificación en contraste con sus pares de Machine Learning tradicional, sino que adicionalmente ofrece un enfoque innovador para las prácticas de gestión de recursos humanos y captación de personal.
Heat Stress Assessment in a chemical factory for the food industry
In the emulsifier area of a food supply company, high temperatures and humidity generate thermal stress conditions that affect workers' health and reduce their productivity. The lack of adequate environmental control exacerbates this situation, impacting operational efficiency. This research aims to evaluate the level of thermal stress at two levels in the emulsifiers area of a factory that manufactures chemical inputs for food, located in the district of Chorrillos, in the city of Lima, Peru. The WBGT index method is used, taking as a reference Standard RM No. 375-2008-TR, which also analyzes the metabolic consumption of workers. This study was conducted in the summer of 2024, using Criffer Protemp 4 and Inlite ITEMP thermal load monitors to determine environmental variables. The results obtained showed that the heat stress indices evaluated at workstations ET-01 and ET-02 were 34.9 and 35.6, exceeding the permitted limit values of 30.5 and 28.5, respectively. This situation represents a considerable risk to occupational health and creates a suboptimal work environment for the physical and mental performance of workers. In addition, operators showed a decrease in their work pace, as well as a higher frequency of unscheduled breaks and signs of fatigue at the end of the shift, affecting productivity in the area. Thermal load levels exceed the recommended thresholds for moderate work, indicating an urgent need to implement corrective measures, such as mechanical ventilation, controlled thermal breaks, or staff rotation. Overall, the results of thermal stress have a significant negative impact on the operational productivity of the area evaluated.
Impact of PM2,5 Particulate Matter on Air Quality Due to the Burning of Saccharum officinarum in Laredo, Trujillo-Peru
This study analyzes the impact of PM2.5 particulate matter generated by the burning of Saccharum officinarum hectares in Laredo between 2017 and 2022. Meteorological data were obtained using the WRF model with a 1 km resolution, covering Trujillo and the Pacific Ocean. The WRF results were validated through comparison with observed data, showing high correlation and predictive capability. The dispersion of PM2.5 was simulated using the Calpuff model from the Environmental Protection Agency (EPA), validated with data from controlled burns and various burning scenarios. The analyses showed maximum PM2.5 concentrations in areas near emission sources, exceeding Environmental Quality Standards (EQS). This was particularly evident between June and November due to south-southeast winds and subsidence inversion conditions. In 2021, critical days exhibited calm wind conditions. Regarding emissions, the burning of 3 hectares generated a moderate air quality index for 60.47% of the receptors. In contrast, the burning of 6 and 9 hectares reached the caution threshold, affecting 32.56% and 43.41% of the receptors, respectively.
Effect of ZnO nanoparticles on the sensitivity of cholesterol detection by cyclic voltammetry
In this work, the cyclic voltammetric response of the enzymatic carbon biosensor with ZnO nanoparticles (ZnO NPs) synthesized by the sol-gel route is reported, to determine the sensitivity of cholesterol detection. ZnO NPs with a wurtzite-type hexagonal structure with a hydrodynamic diameter of 11.5 nm were obtained, presenting absorbance in the UV region at 347 nm due to the formation of the exciton and with a band gap of 3.57 eV. The enzymatic carbon biosensor with ZnO NPs: COX / ZnO NPs / C, detected an increase in peak response current with increasing cholesterol concentration as well as an increase in Faradaic peak current with increasing cholesterol concentration due to the electronic transfer in the redox reaction that occurs at the biosensor-solution interface towards the electrode through its mediator, showing direct linearity between both variables from 25 mg/dL to 180 mg/dL, which was not detected without ZnO nanoparticles. The sensitivity of the biosensor was determined, obtaining a high value of 30.8 μAmM-1cm-2. ZnO nanoparticles improve the cholesterol detection sensitivity of the carbon biosensor since it immobilizes the enzymes by physical adsorption for a better interaction with cholesterol, improving the electronic transfer with the applied potential.
Management of hazardous waste from mining to mitigate adverse environmental impact in the La Libertad Region
This study proposes a management model aimed at reducing the environmental impact caused by hazardous waste generated by mining activities in the La Libertad region. The approach used is both descriptive and analytical, based on a detailed analysis of the available literature. An inventory of mining companies was compiled, and the types of waste generated were characterized, ranging from sterile to industrial waste. Using a cause-and-effect matrix, environmental impacts were assessed, resulting in a Hazardous Waste Management Plan that includes strategies for waste minimization, treatment, and final disposal, validated by experts. Although companies operate within a formal framework, improper waste management remains a challenge. It is concluded that it is crucial to implement minimization alternatives from the source of waste generation to protect the natural environment and nearby communities. The effective implementation of the proposed management model will contribute to the evaluation of hazardous waste and foster greater environmental responsibility in the mining sector, ensuring the preservation of ecosystems and safeguarding the health of surrounding communities.
Environmental impacts generated by artisanal coal mining in Sanagorán, Huamachuco
The research aims to assess the environmental impacts resulting from coal extraction in artisanal mines located in Agopampa and Huacchac, within Sanagorán, Huamachuco. To achieve this, technical visits and field consultations were conducted with miners and local inhabitants. A methodology based on direct observation and data collection was applied, identifying environmental impacts on the abiotic components (water, soil, and air) and the biotic component (tree deforestation). The evaluation was based on environmental impact intensity criteria: high, medium, and low. A total of 21 environmental impacts were identified, with 40% classified as high intensity, 40% as medium intensity, and 20% as low intensity. One of the most alarming findings was the daily average consumption of 5424 kg of wood in the mines. Additionally, the increase in coal prices led to two main effects: a rise in solid waste production, heightening ecological concerns, and the commercialization of sterile materials, reducing their contaminating impact on the soil. In conclusion, the manual extraction of coal in the area has severe consequences for the ecosystem and public health, while also serving as a crucial economic source for many mining families.
Machine Learning applied to mining exploration using confusion matrix
The objective of this study was to determine how to spatially validate geological datasets obtained from the Huancayo region in Peru, as well as to identify the most common methods for evaluating the performance of classification models. The methodology employed involved the use of machine learning algorithms applied to a confusion matrix, with results represented through a ROC curve. The findings indicated that the accuracy parameter reached a maximum percentage of 65.4%, precision was 80.4%, recall was 96.2%, and the F1-score achieved a value of 96.1%. It is concluded that when using classification models, it is essential to consider additional metrics beyond accuracy to obtain a more reliable estimation.