Introduction: Vicarious violence is a form of gender-based violence that affects women and children throughout the world, including Ecuador. Despite its seriousness, this form of violence is not always recognized or typified in Ecuadorian criminal legislation. Objective: The main objective of this study is to analyze the need to typify vicarious violence in the Ecuadorian Organic Integral Penal Code in order to provide legal protection to victims of this type of violence. Methodology: Documentary analysis, literature review, case studies and semi-structured interviews with experts in criminal law, gender and gender violence in Ecuador were used. Comparative analysis of legislation, systematic literature review and content analysis of cases of vicarious violence were carried out. Results: The research revealed that vicarious violence is a serious form of gender violence that affects women and children in Ecuador, with devastating consequences on their physical, psychological and emotional integrity. The importance of promoting public awareness and sensitization campaigns on this phenomenon was identified. Conclusion: The inclusion of vicarious violence in Ecuadorian legislation is crucial to guarantee the protection of victims and promote a culture of respect and gender equity in society. It is recommended that early detection strategies, specialized training and inter-institutional coordination be implemented to effectively address this problem.  

The present investigation is based on the factors associated with occupational risk in the city of Cuenca - Ecuador with in a company with operational personnel. Through applied research, it is proposed to determine which metabolic diseases are correlated with occupational risk. The study is quantitative and relies on the theoretical construct where obesity, dyslipidemia and high blood pressure are associated with occupational risk. 64 people from the operational area of ​​the “Indurama” company were investigated. The results reveal that there is a positive correlation between dyslipidemias with 0.351**, the tests being statistically significant at a level less than the p - value of 0.05, while the obesity variables with 0.031 and arterial hypertension with 0.029 did not pass the statistical test. . It is concluded that preventive health programs must be aimed at treating dyslipidemia, if the occupational risk indicator is to be reduced in the specific context of the study.

Introduction.  The placement of block masonry emerges as a critical phase in the construction process, where efficiency and accuracy directly influence the duration and quality of the project. This activity, although seemingly simple, carries an inherent complexity that often results in significant delays in the execution of the work. The need to understand and address the factors contributing to these delays is evident, as their impact is not only reflected in terms of schedule and budget, but also in client satisfaction. Objective.  To propose a mathematical model to calculate the labor performance in the placement of masonry with blocks in Cañaribamba Parish, Cuenca, Ecuador. Methodology.  The methodological design adopted follows a relational and descriptive orientation, involving the collection of data from nine construction sites by means of an observation sheet that covers both external and internal factors. Using these data, a linear regression analysis was carried out using a statistical program. Results.  The results highlight that, individually, none of the factors analyzed significantly influences job performance; however, the combination of these factors allows predicting performance with an accuracy of 93.3%. Conclusion.  It is concluded that linear regression emerges as a robust tool to anticipate the performance of work crews in the Cañaribamba Parish, considering the complexity of both internal and external factors in the works.

Introduction. The prediction of labor performance in the masonry plastering activity is crucial to ensure efficient planning in the construction industry. Accurate prediction of this activity is vital to avoid delays, control costs and meet contractual deadlines, which highlights the importance of this study in the optimization of construction processes. Objective.  The purpose of this research is to present a mathematical model to anticipate labor performance in the activity of masonry plastering with mortar, using a linear regression technique. Methodology. A relational-descriptive methodological design was adopted, which began with a literature review to identify the factors that influence workers' performance. Subsequently, a data collection instrument was designed and applied to a sample of seven construction sites registered in the database of the GAD municipal de Cuenca, located in the mortar plastering phase in the parish of Yanuncai. The data collected were analyzed using a statistical program, which allowed the development of a mathematical model to predict the performance of workers according to the factors studied. Results.  The results revealed that the model developed can effectively predict the performance of the workers considering both external and internal factors of the construction site. It was found that, for the masonry plastering activity, only certain factors, such as time, temperature, soil type, roof characteristics, level of difficulty, associated risks, work methods and worker skill, can predict this performance using linear regression. Conclusion.  In conclusion, it is evident that theoretical performance is not effective in predicting actual labor performance, and the effectiveness of linear regression in improving the planning capacity of construction sector managers in the city of Cuenca is highlighted.

Introduction.  Ceiling installation is an essential task in construction, whose performance is key to efficient project planning and execution. However, current approaches to predicting performance in this activity are often simplistic in that they assume linearity in results, without considering the inherent variability in worker performance. Objective. The main objective of this study is the creation of an efficient mathematical model to project labor performance in ceiling installation projects in the city of Cuenca, particularly in the San Sebastian parish. Methodology. A relational-descriptive methodology with a quantitative approach was implemented. It began with an exhaustive review of the literature to identify possible factors that could influence labor performance. With this information, an observation form was designed and applied to 45 workers at six different construction sites within the study area. The data collected were analyzed using statistical software to establish a mathematical model to predict the performance of the workers based on the factors identified. Subsequently, these values were compared with the actual and theoretical performance obtained. Results. One of the most outstanding findings was the notable difference between the actual performance of the workers and the theoretical performance, indicating that performance does not follow a linear trend over time and varies according to various factors such as climatic conditions, equipment used, supervision and individual worker characteristics. Conclusion.  The mathematical model developed in this research proved to be effective in predicting worker performance based on the factors analyzed.

Introduction. Given the recurrent flooding during the rainy season, this study focuses on modeling the flood risk in the areas adjacent to the Burgay river, located in the urban area of Biblián canton in the province of Cañar, Ecuador. Objective. Identify the risk of flooding caused by the flooding of the Burgay river in the Biblián canton through the application of the hydrological-hydraulic method to evaluate the threat, the use of a GIS and the zoning of elements exposed to flooding to establish strategies for risk reduction. Methodology. A descriptive-correlational methodology is used to detail the phenomenon and evaluate the interrelationships between variables relevant to this risk. Results. The results highlight a significant distribution of areas exposed to different levels of flood hazards in the vicinity of the Burgay River. Considerable extensions with worrying levels of risk are identified, mainly areas of high and medium threat, covering a considerable percentage of the evaluated territory. Fundamental aspects of the infrastructure, such as buildings, the drinking water network, the sewage system and urban roads, show a notable exposure to these risk levels, especially in the high and medium hazard categories. Conclusion. The main conclusion highlights the urgency of implementing preventive measures and risk management strategies in these vulnerable and exposed areas. These actions become imperative to mitigate the possible impacts of future floods, preserving the functionality of critical infrastructure and guaranteeing the safety of the community in the Biblián canton of the province of Cañar, Ecuador. General area of study: Engineering. Specific Area of Study: Sustainable Construction

Introduction: This study addresses the construction of a conceptual framework of feminicidal suicide by induction or aiding and abetting, supported by doctrinaires who have validated this terminology since decades ago. In addition, an analysis is made of the international legal frameworks that have regulated this crime, followed by a comparative study between El Salvador and Chile. Subsequently, two Ecuadorian cases are presented that demonstrate the perpetration of this type of suicide in contexts of gender violence. Objective: The main objective of this research is to demonstrate the need to typify the crime of feminicide suicide by inducement or aid in the Organic Integral Penal Code, using the information and collaboration of multicompetent judges and a prosecutor to enrich this analysis.  Methodology: The research was carried out through the collection of information from doctrinarians and analysis of international legal frameworks. Two Latin American countries, El Salvador and Chile, were selected for a comparative study, followed by the identification of Ecuadorian cases that exemplify this type of crime. The collaboration of multicompetent judges and a prosecutor considerably enriched the information gathered.  Results: The results obtained reinforce the need to typify the crime of feminicide suicide by inducement or aid in the Organic Integral Penal Code. The cases analyzed show how the victims, after suffering physical, psychological and sexual violence, are driven to suicide in a context of discrimination and subordination. Conclusion: The typification of this crime in the legal framework is expected to be a starting point for the implementation of public policies and the necessary legislative intervention to eradicate gender violence. It is imperative to address this problem that takes the lives of women through the induction of suicide, thus promoting a more just and egalitarian society.  

Introduction: Human Papillomavirus (HPV) is a sexually transmitted infection which has closely been linked to oropharyngeal cancer. Some evidence suggests that sexual behaviors may increase the risk of oropharyngeal cancer. Objectives: To summarize the current information about HPV-related oropharyngeal cancer and its relationship with sexual behaviors. Methodology: Google Scholar was used to find electronic databases about HPV-associated oropharyngeal cancer cases and review articles from 2020 and 2023. Results: 8 studies revealed that sexual behaviors may increase the risk of oropharyngeal cancer, whereas 2 studies claim that there is no correlation between HPV infections and sexual habits. Conclusion: safe sexual practices may reduce the risk of HPV infections and the risk of developing oropharyngeal cancer. General field of ​​study: Medicine. Specific field of ​​study: Virology. Type of study: review article.

Introduction. Static Timing Analysis (STA), fundamental in the design of integrated circuits, involves evaluating the temporal performance of digital circuits under various conditions to meet certain constraints, through simulation. Despite its importance, traditional ATS faces several limitations when considering the increasing complexity of the integrated circuit manufacturing process in its models. The inclusion of Artificial Intelligence (AI) is seen as a promising solution to improve the precision and efficiency of the ATS, thus reducing design cycles in the electronics industry. Objective. To study the influence that the inclusion of AI has, and may have in the future, for the optimization of the ATS, and therefore to reduce design cycles in the electronics industry. Methodology. AI has been integrated into Static Time Analysis (STA), improving accuracy and efficiency when estimating delays, modeling process variations, and optimizing routes and synthesis processes. This integration addresses the complexity and variability of modern integrated circuits, accelerating design convergence, reducing iterations, and improving design quality. Additionally, AI is applied in model characterization for ATS, using adaptive simulations to accelerate the verification process and significantly reduce time to market, crucial in the semiconductor industry. This article reviews the current state and future projections of the contribution of AI in the ATS. Discussion. The future of STA promises a series of advances that seek to improve its capabilities and address emerging challenges in integrated circuit design. These developments include greater integration with Machine Learning (ML) to improve accuracy and efficiency. With the evolution towards smaller process nodes, STA will need to adapt to manage the increased complexity and variability introduced, employing more sophisticated ML algorithms. Additionally, STA is expected to focus more on power and reliability considerations, incorporating additional metrics and more complex data analysis, with the help of AI, to ensure energy efficiency and robustness against reliability issues. Conclusion. The future of ATS is shaping up to be constant innovation and adaptation to meet the changing needs of the semiconductor industry. Technological and methodological advances will play a crucial role in ensuring the timely delivery of high-performance and reliable integrated circuit designs. Given AI's data analysis and optimization capabilities, its revolutionary potential in ATS is considerable, especially with the growing inclusion of increasingly demanding requirements.