This study presents a literature review of models and methods for dynamic modeling of biped robots with elastic actuators. The adopted workflow consisted of executing search strategies in academic databases (2015–2026) using predefined keywords, and subsequently filtering references based on inclusion criteria such as robot type, employed method/model, research methodology, language, and publication recency. From the final set of 35 articles, relevant information was extracted and synthesized using a bibliographic matrix, comparative tables, and graphs. The results indicate that integrating elastic actuators into biped robots increases design and control complexity; however, it significantly improves locomotion speed, efficiency, motion smoothness, and the ability to emulate biological muscle behavior. Nine models were identified to represent the dynamics of these robots. The robot dynamic model is the most common for evaluating overall dynamic behavior, whereas the SLIP (Spring-Loaded Inverted Pendulum) model is preferred for control-oriented studies due to its lower complexity. In addition, the Euler–Lagrange formulation is most frequently adopted to model the robot, while differential-equation-based models or system identification techniques are typically used for the elastic actuator; nevertheless, methodologies that estimate the full robot dynamics from real data are not ruled out.
This research aims to identify the impact of raw material dimensional quality, as measured by the process capability index corrected for centering (Cpk), on productivity and economic sustainability in the final assembly processes of an industrial maquiladora. A case study was conducted at a company with high levels of waste, downtime, and rework due to out-of-specification components (Cpk < 1.0). The methodology consisted of identifying the poor quality of the raw material that affected the process, quantifying the relationship between raw material quality and productivity, as well as economic sustainability through associated costs, analyzing the lean manufacturing tool, in this case, Total Productive Maintenance (TPM), the implementation of this tool, and the standardization of parameters in order to stabilize the processes. The results show that poor raw material quality increases operating costs and decreases productivity, directly affecting the principles of efficiency and rational use of resources inherent in economic sustainability. After implementing TPM, there was a significant reduction in downtime, unproductive time, and scrap. It is concluded that ensuring raw materials with acceptable Cpk and applying continuous improvement strategies, such as TPM, are key factors in maintaining productive and economically sustainable operations in the long term.
Potato peel is an agro-industrial by-product with potential valorization as a functional ingredient due to its mineral content. However, food use requires demonstrating safety regarding chemical contaminants. This study characterized the essential mineral profile and heavy metals in raw and citric-acid–pretreated potato peel (Solanum tuberosum). Samples were collected in Ambato, Tungurahua, Ecuador, from three parishes (Pasa, Montalvo, and Izamba) and two commercial varieties (Superchola and Única). For each zone × variety combination, a 200 g peel sample was obtained and split into two treatments: raw (single potable-water wash) and pretreated (immersion in 1% w/v food-grade citric acid). Fractions were dried and milled. Essential minerals (Ca, Mg, Cu, Mn, K, Na, Fe, Zn, and P) were determined using a dry ashing approach with AOAC 975.03 as a methodological reference and quantified by atomic absorption spectrophotometry (AAS). Pb and Cd were quantified by AAS following Standard Methods 3111 B (modified), using analytical triplicates. The pretreatment induced zone- and variety-dependent shifts, with recurrent increases in Zn and Fe across several combinations. Cd remained at low levels, whereas Pb persisted at elevated concentrations in both raw and pretreated peels. When contrasted with Codex maximum levels for root and tuber vegetables, Pb emerged as the critical limiting factor for the direct feasibility of a functional ingredient under the evaluated conditions. Despite its favorable mineral potential, potato peel valorization for human consumption requires stricter raw-material control and validated mitigation strategies to reduce Pb to levels compatible with international food safety benchmarks.
The objective of this systematic review is to analyze the main scientific advances related to the use of cellulose extracted from agro-industrial residues for the formulation of biopolymers. To this end, a systematic review of the scientific literature published between 2015 and 2024 was conducted using the Dimensions database, considering studies associated with agroindustrial residues, biomaterials, and biopolymer production methods. The selected studies were evaluated through bibliometric analysis and keyword co-occurrence tools, which enabled the identification of research trends, scientific output, and predominant technological approaches. pp. 33-43 The results indicate that agro-industrial residues constitute an abundant and sustainable source of cellulose, whose valorization promotes the circular economy and reduces environmental impact. Various cellulose extraction methods were identified, including alkaline treatment, acid treatment, bleaching, enzymatic processes, and methods based on green solvents. The latter represents one of the most recent trends and, compared to other methods, yields cellulose with a high degree of purity; however, its main drawback is the high production cost. In this context, acid hydrolysis remains one of the most widely used methods despite involving corrosive reagents. Cellulose extracted from agro-industrial residues is used as a raw material in the production of biopolymers. For the fabrication of biopolymer films, molding is the most commonly employed technique. The main applications of biopolymers derived from agro-industrial residues were identified in the food industry, particularly in food packaging and containers. Overall, the literature demonstrates the growing scientific interest and technological potential of these materials as sustainable alternatives to conventional polymers.
Phytoremediation using aquatic macrophytes is a sustainable strategy for the removal of coliforms and Escherichia coli in wastewater, although its efficiency is subject to variations in environmental parameters such as pH, temperature, and total dissolved solids (TDS). This study developed a first-order kinetic mathematical model, incorporating an environmental penalty mechanism based on a Gaussian function to dynamically adjust the removal coefficient (k) according to physicochemical conditions. Six species of macrophytes (Azolla, Salvinia, Pistia, Ceratopteris, Spirodela, and Eichhornia) were experimentally evaluated alongside a positive control (Lemna) and a negative control (no plant), with daily measurements of bacterial concentrations and environmental parameters over seven days. The results showed that the model adequately described removal trends in several treatments, especially for E. coli. The environmental penalty allowed pH, temperature, and TDS effects on k to be evaluated, producing more conservative predictions. Ceratopteris and Azolla showed the best fits for coliforms (R² > 0.99), while Spirodela, Salvinia, and Eichhornia exhibited low performance. It is concluded that the model is a useful tool for predicting removal efficiency under variable environmental conditions, though further research into species-specific thresholds and microbial variables is required to optimize its applicability in real-world scenarios.
This study evaluates the relationship between public science and technology policies (PSTP) and natural risk management (NRM) to identify tools and frameworks that enhance community resilience within the Sendai Framework. A Systematic Literature Review (SLR) was conducted using PRISMA and ASReview (Active Learning) on Web of Science and Scopus (2013–2024). From an initial pool of 4,522 records, a final corpus of 59 high-impact documents was analyzed. Brazil and China were identified as the leading contributors to scientific production. Results categorize PSTP into investments (EWS, susceptibility maps) and specific programs, highlighting a persistent implementation gap in Latin America. The study provides a two-phase guiding framework to integrate scientific innovation with community participation for resilient policy design.
Human Action Recognition (HAR) has become a field of great importance and interest for solving problems and accomplishing tasks across diverse areas. While the literature is vast, researchers face significant challenges in selecting optimal architectures, models and datasets that balance high accuracy with computational efficiency. To address this, the present systematic comprehensive review, conducted using the SALSA methodology, analyzes 81 articles and explores the best performing HAR methods. The review identified key benchmarks, notably NTU-RGB+D60 (15.15%) and UCF101 (12.12%). Most reviewed studies indicate that the most suitable models for these tasks are Convolutional Neural Networks (CNNs), which have demonstrated outstanding performance in analyzing graphical material, followed by Three-Dimensional Convolutional Neural Networks (3D CNNs) with temporal modeling (e.g., LSTMs) consistently yielding superior performance. Notably, advanced hybrid and skeleton-based models achieved peak accuracy rates of 98.3% and 98.7% on complex benchmarks, significantly outperforming traditional approaches.
The following work presents a proposal to improve the brake drum cooling system of a 650 HP drawworks, which is crucial in oil well workover operations. To achieve this, a computational fluid dynamic (CFD) and thermal analysis was performed using ANSYS Student software, where the current system was modeled and different cooling scenarios were simulated. The behavior of the cooling fluid was evaluated, and a more efficient solution including a heat exchanger was designed. The results indicated that, with an initial drum temperature of 300 °C, the current water cooling system heats the fluid to 56 °C, after which it goes directly to a 30 m3 tank that serves as a thermal buffer, which, due to its large capacity, manages to cool the water to a range between 31 and 32 ºC in a transient state. The proposed improvement, by implementing a heat exchanger, directly reduces the cooling water temperature to 32 °C in a transient state. In addition, the tank volume was improved from 30 m3 to only 6 m3, which considerably reduces water consumption without affecting thermal performance. Finally, it was verified that the centrifugal pump used is adequate to maintain the required pressure throughout the circuit. The following proposal not only improves the efficiency of the system, but also reduces the risk of mechanical failures, saves resources, and improves operative efficiency.
In vitro techniques for Solanum transcendental crops were developed, including propagation from tomato seed, micropropagation of potato by tuber sprouts, and sweet pepino anther culture. At all stages of tomato, and potato a completely randomized design (CRD) with or without factorial arrangement was used; and culture media were assessed for sweet pepino anthers. Tomatoes Floradade (V1), and Montego (V2), potatoes Chaucha (CH), Leona Blanca (LB), and Leona Negra (LN), and sweet pepino New Generation (NG) were utilized, as well as two disinfection treatments (TD), different concentrations of gentamicin (50, 68.8, and 75 mg & centerdot; L-1), fungicides (FF), bacteriostatic and bactericidal (BB). Tomato germination with contamination < 10% was obtained with V1-TD1-68.8ppm = 86.67%, and V2- TD1-68.8ppm = 80.00%; while explant length (mean +/- S.E.) ranging from V2-TD1-68.8ppm = 12.63 cm +/- 0.49, to V2-TD2- 68.8ppm = 3.40 cm +/- 1.23 was significantly different; and ex vitro plantlet length was different between V1 = 12.64 cm +/- 0.68, and V2 = 17.17 cm +/- 0.69. In the micropropagation of potato (contamination 0.0-6.67% and survival 93.33-100%), leaf number was different among CH-FFBB-75ppm = 7.60 +/- 0.43 (A), LB-FFBB75ppm = 4.00 +/- 0.58 (B), and LN-FFBB-75ppm = 1.50 +/- 0.27 (C), and explant length was similar, with 2.14, 1.79, and 1.96 cm, respectively. Two calluses from sweet pepino anthers were obtained on media with kinetin (0.01-0.1 ppm), auxin, and cytokinin.
The genus Bacillus is a critical ally in combating phytopathogens such as Alternaria sp. and Botrytis sp., which cause losses to the agricultural sector in Ecuador. Bacillus subtilis generates important lipoproteins belonging to the fengicin and iturin families; therefore, this study analyzed the expression of genes involved in the synthesis of FEND and ITUDI lipoproteins. In addition, the antagonism of Bacillus subtilis against phytopathogenic microorganisms was analyzed through the PICR (percentage of radial growth). Using molecular techniques such as RT-qPCR, the expression levels of the aforementioned genes were quantified on three specific days: 1, 5 and 9 when Bacillus subtilis is in confrontation with phytopathogens. For this purpose, three treatments with the phytopathogens mentioned above were carried out. Total RNA was extracted, followed by retrotranscription, and finally, the cDNA was subjected to qPCR analysis to determine gene expression values. It was determined that the gene coding for phengicins is expressed seven times on the fifth day of treatment when Bacillus subtilis is in the presence of Alternaria sp. It was also determined that the ITUDI gene is expressed an average of 4.56 times more on the fifth day of treatment in the presence of Alternaria sp. Finally, the expression levels of FEND and ITUDI are expressed an average of 3.6 and 2.3 times, respectively, when it is in antagonism with Botrytis sp.
- Mamba is a recent State Space Model (SSM) architecture to improve the computational and scalability limitations of transformer-based sequence models. In this review, we synthesize and compare Mamba's core design-interleaved SSM and feed-forward layers with hardware-aware memory management-to standard Transformers, highlighting its linear complexity and ability to process extremely long contexts. We analyze published benchmarks showing that Mamba outperforms or matches open-source baselines (e.g. Pythia, RWKV) of similar and even twice the size on zero-shot tasks, scales more efficiently on genomic sequences (processing >1 M tokens with only 74 K parameters), and supports variants such as Jamba (MoE extension), Falcon Mamba 7B, Mamba-2 (Structured SSM), and Mamba-4 with further speed or capacity gains. We discuss adaptations to vision (VIM) and dependency parsing (DepMamba), and emerging hybrids (e.g. Bamba, IBM Granite) that fuse SSM efficiency with Transformer accuracy. Finally, we interpret these findings in the context of real-world constraints-compute cost, energy, and tooling maturity-outlining where Mamba excels, and hybrid models may be preferable, and which areas require further optimization. Our conclusions suggest that Mamba and its derivatives offer a viable path toward more sustainable, scalable sequence modeling.
- Present study aims to evaluate thirteen rice genotypes, comprising seven imported and six local varieties, along with the check cultivar IR24 (originating from China, RRI Kala-Shah-Kaku, and ICI, Pakistan), for resistance to bacterial leaf blight (BLB), brown spot (BS), and grain discoloration (GD) under artificial field inoculation conditions. The evaluation revealed significant differences between the hybrids and local rice types across various parameters. None of the varieties exhibited complete resistance to BLB, BS, or GD diseases. However, three varieties (CH3, CH9, and CH11) demonstrated moderate resistance (MR) to BLB. CH11 showed moderate resistance to BS, whereas CH3 and CH9 were moderately susceptible (MS). For GD, three genotypes (CH5, CH6, and CH7) were found to be susceptible (S) compared to the other genotypes. In terms of paddy yield, CH12 and CH13 recorded higher yields (10447 kg ha-1 and 10064 kg ha-1, respectively) than the other hybrids and varieties. While conventional rice types had moderate disease incidence and severity, exhibited the lowest yield and yield-contributing characteristics compared to hybrid varieties.
The indicators allow for measuring, monitoring, and evaluating performance in critical areas, making effective management of these indicators fundamental for the development of an intelligent tourist destination. The research focuses on developing an Indicator Management System that measures the performance of the destination and generates objective, relevant, and timely information for decision-making. Various research methods were employed, including historical-logical analysis, synthesis, induction-deduction, systemic modeling, interviews, document review, direct observation, and expert judgment. This approach enabled the analysis of the evolution of indicator management systems, identification of functional and non-functional requirements of the system, modeling of business processes, and collection of key information about customer needs. The system allows for the registration and tracking of logistical indicators to facilitate decision-making and improve administrative productivity by effectively utilizing the data generated, processed, and stored by the tool. It is based on an MVC architecture and primarily uses open-source technologies such as Laravel, Bootstrap, and PostgreSQL, providing flexibility and low maintenance costs. The key principles that an information system for indicators should have such as systemic character, flexibility, organizational adequacy, continuous improvement, and interactivity are highlighted in the final result.
This paper analyses the water flow in curved channels, which may present particular hydrodynamic patterns such as streamline alteration, cross-wave formation, recirculation zones and possible contour flow separations, all of which require detailed hydrodynamic analysis. The analysis focuses on a case study of a hydroelectric power plant intake with a side grate, which includes a curved (small-radius) gravel-removing channel connecting the intake works to two desanding chambers. This design results in an unequal distribution of flow to the desanding chambers, causing neither chamber to function properly, and a recirculation zone upstream of the left desanding chamber. The methodology uses three-dimensional numerical modelling in OpenFOAM, based on prototype data. The model was calibrated with a flow rate of 8,8 m3/s. Subsequently, the transit of the design flow of 13 m3/s was simulated and an uneven flow distribution in the desanding chambers was verified. To address this problem, and considering the higher-velocity streamlines, two groups of alternatives were considered: the first consisted of placing two panels of different special shapes (straight, broken, and curved) in the desilting chamber; the second examined the flow behavior with an increased number of panels and alteration aspect ratio. For the first group, the scenarios tested did not modify the flow distribution in the sand removal chambers; however, the panels locally changed the hydrodynamic conditions and successfully altered the recirculation zone location. The scenarios in the second group yielded the best operational results regarding flow distribution.
This study evaluated the efficiency of the natural biocoagulants Prunus serotina and Mespilus germanica in the removal of turbidity and total suspended solids (TSS) in a river in Apurimac, Peru. A 3 & times;2 & times;2 factorial design was applied, considering three coagulant doses (0,1; 0,5; and 1,0 g/500 mL), two stirring speeds (50 and 150 rpm), and two settling times (30 and 60 min), with three replicates per treatment. Significant reductions were observed, reaching maximum values of 92,71 % in turbidity and 90,92 % in TSS with M. germanica, and 90,16 % in turbidity and 88,73 % in TSS with P. serotina. Analysis of variance (ANOVA) confirmed that the dose and sedimentation time significantly influenced the removal of turbidity and TSS (p < 0,05), while the agitation speed was relevant only for P. serotina. These findings demonstrate that seed extracts of P. serotina and M. germanica represent viable, sustainable, and low-cost alternatives for water treatment in rural Andean communities.
- The purpose of this research was to develop a solid waste management model for the Bolivar canton, considering environmental, economic, social, and technical criteria through a multicriteria analysis approach. The supply chain was characterized through a detailed analysis of the urban solid waste management process in the Bolivar canton, including its different stages and stakeholders. Supply chain flows were defined by identifying and quantifying the waste streams currently circulating within the chain. Finally, the solid waste management model was determined based on the requirements proposed by the AME (Mexico City Association of Solid Waste) in its comprehensive management project for non-hazardous solid waste generated in Ecuador. This research is proposed as a strategic tool for moving toward more sustainable and resilient cities. Consequently, investing in this type of model entails short-, medium-, and long-term benefits, ensuring balanced development across the environmental, social, and economic spheres. The results show that solid waste generation in the Bolivar canton is 0,72 kg/inhabitant/day, with minimal variations across parishes. In the residential sector, generation reaches 0.36 kg/inhabitant/day, equivalent to 50 % of the total. Furthermore, the monthly cost per household for the GIRS (Mexico City Association of Solid Waste) is estimated at USD 6.60. This information is key for planning and optimizing the collection system, contributing to more efficient and sustainable management.
This study aims to evaluate the accuracy of vegetation indices generated using the SoPI software, based on Sentinel-2 imagery collected between 2020 and 2024. Following a structured methodological framework, the process included the selection and acquisition of satellite images, image processing, generation of NDVI maps and histograms, spatial adjustment of outputs to the study area, and the subsequent analysis and interpretation of results. The NDVI was derived from spectral bands obtained through the Copernicus Open Access Hub, and the outputs generated with SoPI were compared with the official NDVI products available via the Copernicus Browser using histogram-based analysis. Furthermore, the temporal variability of vegetation indices was examined using four satellite images captured on distinct dates, focusing on the Loma Alta Communal Ecological Reserve, located in Santa Elena, Ecuador. This analysis aimed to identify correlations between the indices and seasonal vegetation dynamics characteristic of the region, while also contextualizing the findings in light of existing literature. Overall, the study contributes to vegetation monitoring efforts in protected ecosystems by validating the reliability and applicability of SoPI.
- The Internet of Things (IoT) and Artificial Intelligence (AI) have become key technologies for advancing precision agriculture. This systematic literature review explores their integration in Ecuadorian agriculture, addressing four main aspects: AI techniques applied for pest detection and crop monitoring, types of agricultural data utilized, the most commonly implemented IoT platforms, and sensors employed in monitoring systems. The review encompasses 40 studies published between 2020 and 2025, revealing a predominance of machine learning approaches, with notable applications of Convolutional Neural Networks (CNN) and Artificial Neural Networks (ANN), achieving accuracy levels between 0,80 and 0,95. Environmental and agricultural production data were the most frequently used, while platforms such as ThingSpeak and ThingsBoard, together with local solutions, were commonly employed for real-time management. The findings highlight current technological trends and challenges related to connectivity, costs, and data quality, emphasizing the need for future research to enhance productivity and sustainability in strategic Ecuadorian crops such as banana, cacao, mango, and rice.
- The following work presents a proposal to improve the brake drum cooling system of a 650 HP drawworks, which is crucial in oil well workover operations. To achieve this, a computational fluid dynamic (CFD) and thermal analysis was performed using ANSYS Student software, where the current system was modeled and different cooling scenarios were simulated. The behavior of the cooling fluid was evaluated, and a more efficient solution including a heat exchanger was designed. The results indicated that, with an initial drum temperature of 300 degrees C, the current water cooling system heats the fluid to 56 degrees C, after which it goes directly to a 30 m3 tank that serves as a thermal buffer, which, due to its large capacity, manages to cool the water to a range between 31 and 32 degrees C in a transient state. The proposed improvement, by implementing a heat exchanger, directly reduces the cooling water temperature to 32 degrees C in a transient state. In addition, the tank volume was improved from 30 m3 to only 6 m3, which considerably reduces water consumption without affecting thermal performance. Finally, it was verified that the centrifugal pump used is adequate to maintain the required pressure throughout the circuit. The following proposal not only improves the efficiency of the system, but also reduces the risk of mechanical failures, saves resources, and improves operative efficiency.
The growth of urbanization has generated an increase in the use of motorized transport, which has intensified problems such as road congestion, environmental impact and health and safety risks. Currently, the automotive field is responsible for more than 10% of global greenhouse gas (GHG) emissions. In response to this problem, manufacturers have developed several solutions, with electric vehicles playing the leading role as a sustainable alternative. Electric motorcycles have shown a growth in sales in recent years in Ecuador; however, their growth is limited by factors such as lack of infrastructure and government regulations. Manufacturers focus on aerodynamics as a key aspect to improve efficiency; to optimize their design, tools such as wind tunnels or computational simulations are used, the latter being a more accessible option. This study proposes the design of a fairing for an electric motorcycle using CAD/CAE software, based on the IDes process. Three proposals were developed, evaluating their aerodynamic performance under the conditions of Loja province. The results indicated that design 3 obtained the best performance, with an average drag coefficient of 0.283 and a lift coefficient of -0.273, subjected to different speeds. From the structural point of view, epoxy resin with unidirectional prepreg S-glass fiber was selected for its balance between mechanical properties and cost. The simulation showed a maximum deformation of 0.35339 mm under various stresses. Furthermore, in the modal analysis, at 78.022 Hz, the fairing presented a deformation of 15.788 mm with a maximum amplitude of 6.5 Hz, validating its ability to withstand the dynamic conditions of the motorcycle without compromising its structure.
