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The present research has the objective of proposing the design of rural housing infrastructure with self-sustainable modular design strategies that allow for a regional conservation area within the Callejón de Conchucos. The absence of adequate territorial planning has led to disorganized urban growth, characterized by the lack of green areas, resulting in a negative impact on the quality of urban life of the inhabitants, increasing their risk to natural disasters. The methodology employed was the analysis of extensive research through a comprehensive literature review, urban studies and climate assessments. Sustainability strategies were implemented using various digital tools, such as Climate Consultant, Google Earth and maps, AutoCAD, Revit, SketchUp and 3D Sun path. Therefore, the proposal allows for the enhancement of comfort through spaces for the conservation of natural resources, taking advantage of its landscape and nature of the place, with the characteristics of sustainability in rural and urban housing in high Andean areas, implementing bioclimatic strategies, such as evaporative cooling, and clean technologies that allow for an energy efficiency of 50%. In conclusion, the proposal for the Callejón de Conchucos seeks to transform the region into an attractive tourist destination by providing high-quality ecosystem services and an enriched cultural experience by integrating modular design criteria and employing sustainable and appropriate technologies.

The present research aims to propose resilient urban-design strategies to mitigate the risk of landslides in Huaraz. This study addresses the growing challenge of climate change and its influence on the occurrence of avalanches in Huaraz, Peru. The methodology employed included a literature review, site analysis using digital tools, and the formulation of resilient urban-design strategies. As a result, a Master Plan for Urban Resilience is proposed, using a detailed literature review, climate studies, and topographic evaluation to design urban strategies that enhance the city’s sustainability and safety. The proposed interventions, including channel expansion, installation of gabions and containment meshes, reforestation, and strategic relocation of housing, demonstrate significant potential to reduce vulnerability to avalanches. This multidisciplinary approach underscores the necessity of integrating urban adaptations in response to extreme climate variations in the Andean regions. The proposal stands out for its innovation and resilience, precisely aligning with the unique characteristics of Huaraz. The comprehensive strategy not only focuses on urban regeneration and risk prevention but also aims to significantly improve the community’s quality of life.

In a global context, where the construction industry is a major source of CO2 emissions and resource use, is dependent on concrete and its risks, and lags behind in digitalization, a clear need arises to direct architecture towards more practical, efficient, and sustainable practices. This research introduces an alternative technique for building timber space structures, aiming to expand its applications in areas with limited access to advanced technologies such as CNCs with more than five axes and industrial robotic arms. This involves reconfiguring economic and ecological constraints to maximize the structural and architectural advantages of these systems. The method develops a parametric tool that integrates computational design and manufacturing based on two-axis laser cutting for shells with segmented hexagonal plywood plates. It uses a modified ‘half-lap joint’ mechanical joint, also made of plywood and without additional fasteners, ensuring a precise and robust connection. The results demonstrate the compatibility of the geometry with two-axis CNC machines, which simplifies manufacturing and reduces the cuts required, thus increasing economic efficiency. The prototype, with a span of 1.5 m and composed of 63 plywood panels and 163 connectors, each 6 mm thick, supported a point load of 0.8 kN with a maximum displacement of 5 mm, weighing 15.1 kg. Assembly and disassembly, carried out by two students, took 5 h and 1.45 h, respectively, highlighting the practicality and accessibility of the method. In conclusion, the technique for building timber shells based on two-axis CNC is feasible and effective, proven by practical experimentation and finite element analysis.

Introduction: Increased antimicrobial use during the COVID-19 pandemic has raised concerns about the spread of resistant bacteria. This study analyzed the frequency of device-associated infections (DAI) caused by resistant bacteria, the predictors of these infections, and 30-day all-cause mortality in patients with and without COVID-19. Methods: A retrospective cohort study was conducted on DAI patients admitted to the ICU (intensive care unit) in 20 hospitals in Medellin, Colombia (2020–2021). The exposure assessed was the COVID-19 diagnosis, and outcomes analyzed were resistant bacterial infections and 30-day mortality. Clinical and microbiological information was collected from surveillance databases. Statistical analysis included generalized linear mixed-effects models. Results: Of the 1521 patients included, 1033 (67.9%) were COVID-19-positive and 1665 DAI were presented. Carbapenem-resistant Enterobacteriaceae (CRE) infections predominated during the study (n = 98; 9.9%). The patients with COVID-19 had a higher frequency of metallo-beta-lactamase-producing CRE infections (n = 15; 33.3%) compared to patients without the disease (n = 3; 13.0%). Long-stay in the ICU (RR: 2.09; 95% CI: 1.39–3.16), diabetes (RR: 1.73; 95% CI: 1.21–2.49), and mechanical ventilation (RR: 2.13; 95% CI: 1.01–4.51) were CRE infection predictors in COVID-19 patients, with a mortality rate of 60.3%. Conclusion: CRE infections were predominant in COVID-19 patients. In pandemic situations, the strategies to control DAI should be maintained to avoid infections caused by resistant bacteria, such as length of stay in the ICU and duration of mechanical ventilation.

In recent years, the modeling and simulation of lithium-ion batteries have garnered attention due to the rising demand for reliable energy storage. Accurate charge cycle predictions are fundamental for optimizing battery performance and lifespan. This study compares particle swarm optimization (PSO) and grey wolf optimization (GWO) algorithms in modeling a commercial lithium-ion battery, emphasizing the voltage behavior and the current delivered to the battery. Bio-inspired optimization tunes parameters to reduce the root mean square error (RMSE) between simulated and experimental outputs. The model, implemented in MATLAB/Simulink, integrates electrochemical parameters and estimates battery behavior under varied conditions. The assessment of terminal voltage revealed notable enhancements in the model through both the PSO and GWO algorithms compared to the non-optimized model. The GWO-optimized model demonstrated superior performance, with a reduced RMSE of 0.1700 (25 °C; 3.6 C, 455 s) and 0.1705 (25 °C; 3.6 C, 10,654 s) compared to the PSO-optimized model, achieving a 42% average RMSE reduction. Battery current was identified as a key factor influencing the model analysis, with optimized models, particularly the GWO model, exhibiting enhanced predictive capabilities and slightly lower RMSE values than the PSO model. This offers practical implications for battery integration into energy systems. Analyzing the execution time with different population values for PSO and GWO provides insights into computational complexity. PSO exhibited greater-than-linear dynamics, suggesting a polynomial complexity of O(nk), while GWO implied a potential polynomial complexity within the range of O(nk) or O(2n) based on execution times from populations of 10 to 1000.

The Bologna Plan adopted by European universities ended the hegemony of an evaluation system exclusively based on the performance of traditional examinations. In this area, with a view to revitalizing grading models in university education, a wide range of evaluation mechanisms has been developed in recent years. Using them, teachers may evaluate the learning levels of their students, including both the specific competences of the taught subject and the transversal competences that help students further develop their professional careers. This article presents a methodology based on a multi-criteria procedure through which students could be evaluated from different points of view, based on different types of evaluation mechanisms that are diversely weighted. Therefore, their levels of learning could be assessed more objectively. This article shows a practical case of applying this methodology, which has been used for the last five years in a course on energy markets taught as part of the Degree in Energy Engineering at the UPV.

Nowadays, the measurement of heat stress indices is of principal importance due to the escalating impact of global warming. As temperatures continue to rise, the well-being and health of individuals are increasingly at risk, which can lead to a detrimental effect on human performance and behavior. Hence, monitoring and assessing heat stress indices have become necessary for ensuring the safety and comfort of individuals. Thermal comfort indices, such as wet-bulb globe temperature (WBGT), Tropical Summer Index (TSI), and Predicted Heat Strain (PHS), as well as parameters like mean radiant temperature (MRT), are typically used for assessing and controlling heat stress conditions in working and urban environments. Therefore, measurement and monitoring of these parameters should be obtained for any environment in which people are constantly exposed. Modern cities collect and publish this relevant information following the Smart City concept. To monitor large cities, cost-effective solutions must be developed. This work presents the results of a Heat Stress Monitoring (HSM) system prototype network tested in the Benicalap-Ciutat Fallera district in Valencia, Spain. The scope of this work is to design, commission, and test a low-cost prototype that is able to measure heat stress indices. The Heat Stress Monitoring system comprises a central unit or receiver and several transmitters communicating via radiofrequency. The transmitter accurately measures wind speed, air temperature, relative humidity, atmospheric pressure, solar irradiation, and black globe temperature. The receiver has a 4G modem that sends the data to an SQL database in the cloud. The devices were tested over one year, showing that radio data transmission is reliable up to 700 m from the receiver. The system’s power supply, composed of a Photovoltaic panel and Lithium-ion batteries, provided off-grid capabilities to the transmitter, with a tested backup autonomy of up to 36 days per charge. Then, indicators such as WBGT, TSI, and MRT were successfully estimated using the data collected by the devices. The material cost of a 12-point network is around EUR 2430 with a competitive price of EUR 190 per device.

Injection molds are production tools that require detailed analysis based on the quality of the resulting part, the impact on cycle times, and the expected production volume. Cooling channels also play a critical role in mold performance and product quality as they largely determine cycle time. Designs that incorporate conformal cooling channel (CCC) geometries that conform to or align with the part contour are currently being explored as an alternative to conventional cooling channel designs in injection molds. In this study, a simulation of CCC geometries was performed and their effects on mold temperatures and warpage were investigated. Two cross-sectional geometries, circular and square, were selected for a three-factor level design of experiments (DOE) analysis. The response variables used were mold temperatures and part warpage. A cup-shaped part with upper and lower diameters of 54 and 48 mm, respectively, a height of 23 mm and a thickness of 3 mm was used for the injection molded part. A comparison was also made between two materials for the injection mold, steel and polycarbonate. The DOE results showed that the distance between the CCC and the injected part and the diameter or side of the square have significant effects on the response variables for both systems (steel and polycarbonate molds). In addition, a comparison between conventional and conformal cooling channels was analyzed using a cup-shaped part and a less rigid part geometry. The finite element simulation results show a 9.26% reduction in final warpage in the cup-shaped part using CCCs compared with the conventional cooling methods in steel. When using parts with lower geometry stiffness, the use of CCCs reduced final part warpage by 32.4% in metal molds and by 59.8% in polymer molds.

In this paper we propose the Recurrent Embedded Topic Model (RETM) which is a modification of the Embedded Topic Modelling (ETM) by reusing the Continuous Bag of Words (CBOW) that the model had implemented and applying it to a recurrent neural network (LSTM), using the order of the words of the text, in the CBOW space as the recurrency of the LSTM, while calculating the topic–document distribution of the model. This approach is novel because the ETM and Latent Dirichlet Allocation (LDA) do not use the order of the words while calculating the topic proportions for each text, making worse predictions in the end. The RETM is a topic-modelling technique that vastly improves (by more than 15 times in train data and between 10% and 90% better based on test dataset values for perplexity) the quality of the topics that were calculated for the datasets used in this paper. This model is explained in detail throughout the paper and presents results on different use cases on how the model performs against ETM and LDA. The RETM can be used with better accuracy for any topic model-related problem.

Proton Exchange Membrane Fuel Cells (PEMFCs) are critical components in renewable hybrid systems, demanding reliable fault diagnosis to ensure optimal performance and prevent costly damages. This study presents a novel model-based fault diagnosis algorithm for commercial hydrogen fuel cells using LabView. Our research focused on power generation and storage using hydrogen fuel cells. The proposed algorithm accurately detects and isolates the most common faults in PEMFCs by combining virtual and real sensor data fusion. The fault diagnosis process began with simulating faults using a validated mathematical model and manipulating selected input signals. A statistical analysis of 12 residues from each fault resulted in a comprehensive fault matrix, capturing the unique fault signatures. The algorithm successfully identified and isolated 14 distinct faults, demonstrating its effectiveness in enhancing reliability and preventing performance deterioration or system shutdown in hydrogen fuel cell-based power generation systems.

The degree of quality of thermoplastic injection-molded parts can be established based on their weight, appearance, and defects. However, the conditions of the injection process may induce effects on the mechanical performance of the injected parts, and the residual stresses can cause cracks or early failures when an external load or force is applied. To evaluate these mechanical behaviors, different experimental techniques have been reported in the literature, where digital photoelasticity has stood out both for being a non-contact technique and for achieving quantitative results through sophisticated computational algorithms. Against this background, our proposal consists of analyzing the overall residual stress distribution of parts injected under different molding conditions by using digital photoelasticity. In this case, the specimens are subjected to bending strength tests to identify possible effects of the injection process conditions. The findings show that, at mold temperatures of 80 °C, flow-induced residual stresses increase with packing pressure. However, these internal stress levels do not affect the external load applied by the mechanical bending test, while the mass injected at higher levels of packing pressure helps to increase the bending strength of the injected part. At lower mold temperatures (50 °C), the mechanical strength of the injected part is slightly reduced, possibly due to a lower effect of the packing pressure.

More than half of the world population live in urban settlements which are responsible for a large share of energy consumption and, consequently, carbon emissions. The transition towards a more sustainable urban environment requires a change in paradigm in terms of how we design and manage our cities. Urban areas require innovative technologies and strategies to reduce energy consumption and carbon emissions, and to be included in comprehensive plans encompassing all technical, social and economic dimensions which characterise cities. This involves the transformation of urban contexts, with a focus on local and urban-level mitigation measures, such as the construction of positive energy buildings, deployment of renewable energy, promotion of a sustainable mobility, creation of resilient urban infrastructure, implementation of circular economy and recycling practices, etc. The present article provides a perspective on the sustainable energy transition in cities, focusing on the building and transportation sectors. Furthermore, insights on supporting mechanisms and innovative management strategies are presented.

Additive manufacturing (AM) is a relatively new option in mold manufacturing for rapid tooling (RT) in injection processes. This paper presents the results of experiments with mold inserts and specimens obtained by stereolithography (SLA), which is a kind of AM. A mold insert obtained by AM and a mold produced by traditional subtractive manufacturing were compared to evaluate the performance of the injected parts. In particular, mechanical tests (in accordance with ASTM D638) and temperature distribution performance tests were carried out. The tensile test results of specimens obtained in a 3D printed mold insert were better (almost 15%) than those produced in the duralumin mold. The simulated temperature distribution closely matched its experimental counterpart—the difference in average temperatures was merely 5.36 °C. These findings support the use of AM in injection molding and RT as an excellent alternative for small and medium-sized production runs in the global injection industry.

The currently growing demand for metallic and polymeric products has undoubtedly changed the rules of manufacturing, enabling customers to more functionally define their products based on their needs. Nowadays, a new technique for rapid tooling, Additive Manufacturing (AM), can create customized products with more complex geometries and short life cycles (flexibility) in order to keep up with the new variables imposed by the manufacturing environment. In the last two decades, the migration from subtractive manufacturing to AM has materialized such products with reduced costs and cycle times. AM has been recently promoted to develop polymer molds for product manufacturing. This paper reviews the main findings in the literature concerning polymer molds created by AM compared to conventional (metal) molds obtained by subtractive manufacturing. Information about specific topics is scarce or nonexistent, for example, about the characterization of the most commonly injected materials and molds used in this type of technology, their mechanical properties (part and mold), designs for all types of geometries, and costs. These aspects are addressed in this literature review, highlighting the advantages of this alternative manufacturing process, which is considered a desirable technology worldwide.

Human papilloma virus (HPV) can infect any of the mucosal areas of the body and cause cervical cancer. Until recently, no specific treatments were available for this condition; therefore, any damaged tissue had to be removed or destroyed, which may have presented obstetrical repercussions for some women. Recently, new drugs have been developed that have shown to be effective for the cure of HPV infection. Glycyrrhizinic acid (GA) has shown fewer side effects and its systemic use makes it possible to reach difficultto- treat lesions. The purpose of this study was to evaluate the clinical outcome of GA to eliminate the epithelial lesion and HPV. We carried out a longitudinal, descriptive study that included women of reproductive age who were diagnosed with HPV associated with low-grade squamous intraepithelial lesion (LSIL). Subjects began treatment based on GA using two routes of administration - systemic (oral) and topical (spray) - with assessments every month to determine the clinical changes of the lesions through colposcopy and Papanicolaou (Pap) smear. Simple statistics were used along with two-tailed Student’s t-test; P

The objective of this study was to evaluate the long-term effects of piling secondary forest residue (after 3 decades) on soil chemical properties, growth, and nutrition of Pinus taeda and weeds at three locations. After secondary forest removal and residue piling, areas were cultivated with P. taeda (22 years), followed by eucalyptus (7 years), and returned to P. taeda. At 2 years of age, tree height and needle-nutrient levels of ongoing P. taeda from areas influenced by residue piling and areas outside the piling zone were evaluated. Biomass and nutrient levels of herbaceous and shrub weeds, NDVI indices (via a drone), and soil chemistry were also evaluated. Residue-piled areas displayed a decrease in soil pH and an increase in available soil P and K. Although herbaceous and shrub-weed biomass increased 2.5 to 10 times in residue-piling areas, this did not compromise pine growth. While residue piling had little impact on the nutritional status of pine and weeds, NDVI values indicated greater plant growth in piling areas. In general, the long-term effect of residue piling was an important factor associated with the large variation in tree growth and weed incidence after 3 decades.