Showing papers by "Instituto Politécnico Nacional published in 2023"
TL;DR: In this paper , the authors proposed a method to detect postharvest fungi and food-borne bacteria in a fast and reliable manner using a transductor, a compartment for data analysis and an indicator to visualize the signal.
5 citations
TL;DR: In this paper , the 15 most popular commercial brands of packaged food ice cubes in Mexico City for microplastics were detected in 100% of the samples evaluated, with concentrations ranging from 19 ± 4 to 178 ± 78 L-1.
2 citations
TL;DR: In this paper , a control strategy consisting of a bounded attractive component to ensure convergence to a specific geometrical pattern and a complementary repulsive component to guarantee collision-free rearrangement is proposed.
Abstract: This paper deals with the formation control problem without collisions for second-order multi-agent systems. We propose a control strategy which consists of a bounded attractive component to ensure convergence to a specific geometrical pattern and a complementary repulsive component to guarantee collision-free rearrangement. For convergence purposes, it is assumed that the communication graph contains at least a directed spanning tree. The avoidance complementary component is formed by applying repulsive vector fields with unstable focus structure. Using the well-known input-to-state stability property a control law for second-order agents is derived in a constructive manner starting from the first-order case. We consider that every agent is able to detect the presence of any other agent in the surrounding area and also can measure and share both position and velocity with his predefined set of neighbours. The resulting control law ensures the convergence to the desired geometrical pattern without collisions during the transient behaviour, as well as bounded velocities and accelerations. Numerical simulations are provided to show the performance and effectiveness of the proposed strategy.
2 citations
TL;DR: In this article , the authors present 13 antimicrobial peptides with theoretical action against Pseudomonas aeruginosa, all of which were evaluated in silico in this work and the results suggest that the AMPs have a carpet-like mode of action with a membranolytic function in Gram-positive and Gram-negative bacteria.
Abstract: Abstract: Pseudomonas aeruginosa (P. aeruginosa) is a bacterium of medical concern, known for its potential to persist in diverse environments due to its metabolic capacity. Its survival ability is linked to its relatively large genome of 5.5-7 Mbp, from which several genes are employed in overcoming conventional antibiotic treatments and promoting resistance. The worldwide prevalence of antibiotic-resistant clones of P. aeruginosa necessitates novel approaches to researching their multiple resistance mechanisms, such as the use of antimicrobial peptides (AMPs). In this review, we briefly discuss the epidemiology of the resistant strains of P. aeruginosa and then describe their resistance mechanisms. Next, we explain the biology of AMPs, enlist the present database platforms that describe AMPs, and discuss their usefulness and limitations in treating P. aeruginosa strains. Finally, we present 13 AMPs with theoretical action against P. aeruginosa, all of which we evaluated in silico in this work. Our results suggest that the AMPs we evaluated have a carpet-like mode of action with a membranolytic function in Gram-positive and Gram-negative bacteria, with clear potential of synthesis for in vitro evaluation.
2 citations
TL;DR: In this paper , the authors presented the diagnosis and management proposal for the Valsequillo wetland, Puebla, Mexico, which performs a biofiltration process by reducing the pollutant load of the water.
1 citations
TL;DR: In this paper , the causes and mechanisms contributing to NAFLD development in normal-weight individuals were investigated. But little attention has been paid to the causes of the development of NAS in normalweight individuals.
Abstract: While non-alcoholic fatty liver disease (NAFLD) without inflammation or fibrosis is considered a relatively 'benign' disease, non-alcoholic steatohepatitis (NASH), by contrast, is characterized by marked inflammation in addition to lipid accumulation, and may include fibrosis, progression to cirrhosis and hepatocellular carcinoma. Obesity and type II diabetes are frequently associated with NAFLD/NASH; however, a significant number of lean individuals may develop these diseases. Little attention has been paid to the causes and mechanisms contributing to NAFLD development in normal-weight individuals. One of the main causes of NAFLD in normal-weight individuals is the accumulation of visceral and muscular fat and its interaction with the liver. Myosteatosis (triglyceride accumulation in the muscle) induces a loss of muscle by reducing blood flow and insulin diffusion, contributing to NAFLD. Normal-weight patients with NAFLD exhibit higher serum markers of liver damage and C-reactive protein levels, as well as more pronounced insulin resistance, compared to healthy controls. Notably, increased levels of C-reactive protein and insulin resistance are strongly correlated with the risk of developing NAFLD/NASH. Gut dysbiosis has also been associated with NAFLD/NASH progression in normal-weight individuals. More investigation is required to elucidate the mechanisms leading to NAFLD in normal-weight individuals.
1 citations
TL;DR: In this article , the microhardness of boride layer micro-hardness was quantified over cross-section specimens, with the aim of characterizing the mechanical resistance under different conditions.
Abstract: The mechanical performance of API 5L grade B steel, after undergoing a thermochemical boriding process, was assessed. We quantified the boride layer microhardness over cross-section specimens, with the aim of characterizing the mechanical resistance under different conditions. The pipeline steel was analyzed because of the changes in yield strength, ultimate tensile strength, and ductility after treatment with boron. These oil and gas pipelines must work in aggressive environments, so borided pipeline steel specimens were tested to assess their erosion–corrosion resistance. Another important characteristic to evaluate was the wearing resistance, because the pipelines tend to suffer scratches when they are under construction. We also present a discussion of the results of the total research work (Part I and Part II), including the results of the boride layer characterization as well as the changes in the substrate, with the goal of selecting the best conditions under which to treat pipeline steel. More extreme treatment conditions can help to form more stable and resistant boride layers, but they can considerably modify some mechanical characteristics of the API 5L grade B steel. For this reason, the boriding treatment conditions must be chosen in a synergistic way.
1 citations
TL;DR: In this article , the authors developed an automatic job offers classifier using a dataset collected from the largest job bank of Mexico known as Bumeran, using machine learning algorithms such as Support Vector Machines, Naive-Bayes, Logistic Regression, Random Forest, and deep learning Long Short Term Memory (LSTM).
Abstract: Both policy and research benefit from a better understanding of individuals’ jobs. However, as large-scale administrative records are increasingly employed to represent labor market activity, new automatic methods to classify jobs will become necessary. We developed an automatic job offers classifier using a dataset collected from the largest job bank of Mexico known as Bumeran. We applied machine learning algorithms such as Support Vector Machines, Naive-Bayes, Logistic Regression, Random Forest, and deep learning Long-Short Term Memory (LSTM). Using these algorithms, we trained multi-class models to classify job offers in one of the 23 classes (not uniformly distributed): Sales, Administration, Call Center, Technology, Trades, Human Resources, Logistics, Marketing, Health, Gastronomy, Financing, Secretary, Production, Engineering, Education, Design, Legal, Construction, Insurance, Communication, Management, Foreign Trade, and Mining. We used the SMOTE, Geometric-SMOTE, and ADASYN synthetic oversampling algorithms to handle imbalanced classes. The proposed convolutional neural network architecture achieved the best results when applied the Geometric-SMOTE algorithm.
01 Jan 2023
TL;DR: In this article , the authors developed and evaluated the storage system of an electric bus under dynamic impact, and the results showed the impact's stress and deformation in the battery module.
Abstract: Safety failures in energy storage systems are gradually increasing in urban electric transport. Under mechanical impact conditions, lithium-ion cells can present damage. The main objective is to develop and evaluate the storage system of an electric bus under dynamic impact. The dynamic simulation has been done in LS Dyna® to analyze indenter effects, at different heights, on a battery module placed on the roof of an electric bus. A simplified CAD model of the main components of the module was proposed. Similarly, only the protective housings were analyzed for the modeling of the 18650 cells. The results show the impact's stress and deformation in the cells.
TL;DR: This paper examined the performance of four different types of well-known state-of-the-art transformer models for text classification, such as Bidirectional Encoder Representations from Transformers (BERT), Robustly Optimized BERT Pre-training Approach (RoBERTa), DistilBERT, and a large bidirectional neural network architecture (XLNet) were compared.
Abstract: The use of transfer learning methods is largely responsible for the present breakthrough in Natural Learning Processing (NLP) tasks across multiple domains. In order to solve the problem of sentiment detection, we examined the performance of four different types of well-known state-of-the-art transformer models for text classification. Models such as Bidirectional Encoder Representations from Transformers (BERT), Robustly Optimized BERT Pre-training Approach (RoBERTa), a distilled version of BERT (DistilBERT), and a large bidirectional neural network architecture (XLNet) were proposed. The performance of the four models that were used to detect disaster in the text was compared. All the models performed well enough, indicating that transformer-based models are suitable for the detection of disaster in text. The RoBERTa transformer model performs best on the test dataset with a score of 82.6% and is highly recommended for quality predictions. Furthermore, we discovered that the learning algorithms’ performance was influenced by pre-processing techniques, the nature of words in the vocabulary, unbalanced labeling, and the model parameters.
01 Jan 2023
TL;DR: In this paper , a three-stage mechanism composed of an epicyclic gear train, bevel gears and a rack and pinion system was used to evaluate the mechanical properties of liver tissue.
Abstract: This work presents a system for evaluating the mechanical properties of liver tissue. This system is composed of a three-stage mechanism. The first stage consists of an epicyclic gear train. The second stage consists of bevel gears and a rack and pinion system. The three stages generate the conversion from rotary to linear motion at four points. The system can generate a compression load on the surface of a liver tissue sample. Results show the deformation and displacement values of the components of the testbed.
TL;DR: In this paper , the authors compared the performance of the LeNet5 neural network with a quantum version of itself, in which a fixed non-trainable quantum circuit is used as a quanvolution kernel.
Abstract: At present, quantum computing and its applications are still in research. Nonetheless, the need to accelerate significantly computational processing that requires a considerable amount of time through classical computing for solving complex problems; are just a few reasons why quantum machine learning algorithms are being implemented in this field. Image classification is a frequent computer vision problems to solve using deep learning algorithms, evaluating their performance via well-known datasets. In this work, we compare the performance of the LeNet5 neural network with a quantum version of itself, in which a fixed non-trainable quantum circuit is used as a quanvolution kernel. The contribution of this work focuses on analyzing the disadvantages and advantages of a quanvolution kernel in image classification problems. The results show that using a quanvolutional layer achieves a favorable performance tradeoff over a classical CNN LeNet5 model. We used the MNIST hand-written digits dataset to perform the evaluation using well-known metrics such as accuracy, precision, F1 score, latency, throughput, and others.
01 Jan 2023
TL;DR: The first sandwich complex involving beryllium-and boron, B7Be6B7, was presented in this article , where the global minimum of this combination adopts a unique architecture having a D6h geometry, featuring an unprecedented monocyclic Be6 ring sandwiched between two quasiplanar B7 motifs.
Abstract: Planar boron clusters have often been regarded as “pi-analogous” to aromatic arenes because of their similar delocalized pi-bonding. However, unlike arenes such as C5H5− and C6H6, boron clusters have not previously shown the ability to form sandwich complexes. In this study, we present the first sandwich complex involving beryllium-and boron, B7Be6B7. The global minimum of this combination adopts a unique architecture having a D6h geometry, featuring an unprecedented monocyclic Be6 ring sandwiched between two quasi-planar B7 motifs. The thermochemical and kinetic stability of B7Be6B7 can be attributed to strong electrostatic and covalent interactions between the fragments. Chemical bonding analysis shows that B7Be6B7 can be considered as a [B7]3−[Be6]6+[B7]3− complex. Moreover, there is a significant electron delocalization within this cluster, supported by the local diatropic contributions of the B7 and Be6 rings.
TL;DR: In this article , the influence of thermocapillary flow on the atomization by surface acoustic waves (SAWs) of a sessile water droplet exposed to a high-frequency acoustic field and placed over a substrate with slippage at the wall is theoretically analyzed.
TL;DR: In this paper , the efficacy of public administration strategies has been gauged on how they handle pandemics and the knock-on effects that occur on the environment or society, and in this case, in the rural water supply in Mexico in times of Pandemics.
Abstract: The efficacy of public administration strategies has been gauged on how they handle pandemics and the knock-on effects that occur on the environment or society, and in this case, in the rural water supply in Mexico in times of pandemics. Water access in rural Mexico and how the government has managed the rise in demand during pandemics are explored using a systematic review into 51 documents. Mexico’s water system is below par and there is a need for more investments to be pumped into community management schemes. The involvement of the public in the development of community management schemes is necessary to find a solution to the changing demand and supply.
TL;DR: The publicación no representar una carga extraordinaria del trabajo académico, por el contrario, es fundamental del proceso de investigación: el de comunicar el quehacer científico as mentioned in this paper .
Abstract: Desde nuestra editorial en el número 24(1) (Cantoral, 2021) se vislumbró el complejo panorama de la publicación científica en nuestra disciplina, al menos en el contexto regional, a propósito del requisito de publicación para la graduación en el posgrado. Esta exigencia va fortaleciendo el proceso de naturalizar un sistema que ejerce presión –laboral más que académica– para favorecer la contratación, continuidad o promoción de quienes publican. Per se la publicación no tendría que representar una carga extraordinaria del trabajo académico, por el contrario, es una pieza fundamental del proceso de investigación: el de comunicar el quehacer científico. Sin embargo, se ha convertido en ello por la exigencia de hacerlo continuamente y casi de forma exclusiva en las revistas con el mayor factor de impacto. En su mayoría, los sistemas de evaluación han volcado su atención en el Journal Citation Reports (JCR) y en el SCImago Journal & Country Rank (SJR). Se ha llegado a extremos tales que instituciones o sistemas de evaluación científica de algunos países otorgan valor al trabajo científico, ya no solo por el índice (Web of Science, Scopus o el correspondiente nacional) al que pertenece la revista donde se publica, sino por el cuartil –es decir, el indicador que evalúa su importancia en relación con las revistas de su área– donde se ubica dentro de dicho índice.
TL;DR: In this paper , the HOXC13 and HOXD13 genes were found to be associated with carcinogenesis in women with cervical cancer and healthy women, and the functional impact of the proteins was determined with two bioinformatics servers (SIFT and PolyPhen-2), and the oncogenic potential of identified nonsynonymous variants was determined using the CGI server.
Abstract: HOX genes have been associated with carcinogenesis. However, the molecular mechanism by which tumors are generated remains unclear. The HOXC13 and HOXD13 genes are of interest for their involvement in the development of genitourinary structures. The aim of this first study in the Mexican population was to search for and analyze variants in the coding region of the HOXC13 and HOXD13 genes in women with cervical cancer. Samples from Mexican women with cervical cancer and healthy women were sequenced (50/50). Allelic and genotypic frequencies were compared between groups. The functional impact of the proteins was determined with two bioinformatics servers (SIFT and PolyPhen-2), and the oncogenic potential of the identified nonsynonymous variants was determined using the CGI server. We identified five unreported gene variants: c.895C>A p.(Leu299Ile) and c.777C>T p.(Arg259Arg) in the HOXC13 gene and c.128T>A p.(Phe43Tyr), c.204G>A p.(Ala68Ala), and c.267G>A p.(Ser89Ser) in the HOXD13 gene. In this study, we suggest that the non-synonymous variants c.895C>A p.(Leu299Ile) and c.128T>A p.(Phe43Tyr) could represent a risk factor for the development of the disease, although additional studies in larger patient populations and in different ethnic groups are needed in order to support the results observed.
TL;DR: In this article , the results of a study of T(pyridine)2[Fe (CN)5NO] with T = Mn, Fe, Co, Ni, Cu, and Zn, for polycrystalline samples (powders) suspended in water, both in the darkness and exposed to white light.
Abstract: The 3D transition metal nitroprussides have been extensively studied considering their interesting coordination chemistry, and physical and functional properties. Related to the electronic configuration of the nitrosyl group, these materials show certain instability in the presence of water under light, which we have recently documented. Their 2D analogs with organic molecules as pillars between adjacent layers are anhydrous solids and, in principle, could have higher stability under the light. Under this hypothesis, in this contribution we are reporting the results of a study of T(pyridine)2[Fe (CN)5NO] with T = Mn, Fe, Co, Ni, Cu, and Zn, for polycrystalline samples (powders) suspended in water, both in the darkness and exposed to white light. Such a study was conducted monitoring the suspension pH, and characterizing the recovery solid fractions using IR and Mössbauer spectroscopies, and XRD powder patterns. Although all samples show photodegradation, the extension and the mechanistic path are highly dependent on the polarizing power of the cation. For the metals (T) with low polarizing power, the pyridine loss triggers the formation of the 3D nitroprussides as intermediate species, while for those with high polarizing power, the unbound axial CN ligand is the key factor in promoting degradation.
TL;DR: In this article , the authors studied the influence of the structure of relationships in the commercial network of fishery products in the economic performance and profits distribution among actors, taking the shark market in Mexico as a case study.
28 Mar 2023
TL;DR: In el Centro de Enseñanza de Lenguas Extranjeras Unidad Santo Tomás (CENLEX-UST) as mentioned in this paper , 183 estudiantes contestaron un cuestionario basado on the instrumentos MAALE (Minera, 2010) and SILL (Oxford, 1989).
Abstract: El presente estudio se centró en la motivación, las actitudes y uso de estrategias de aprendizaje por parte de estudiantes de niveles A1 y B1 de alemán, francés, italiano, japonés y portugués como terceras lenguas, con conocimiento de español como primera lengua e inglés como segunda lengua. En el Centro de Enseñanza de Lenguas Extranjeras Unidad Santo Tomás (CENLEX-UST) del Instituto Politécnico Nacional (IPN) 183 estudiantes contestaron un cuestionario basado en los instrumentos MAALE (Minera, 2010) y SILL (Oxford, 1989). Los resultados indican que los estudiantes cuentan con un alto grado de motivación, especialmente intrínseca, y una muy buena actitud hacia sí mismos como aprendientes y hacia las lenguas extranjeras, independientemente de su nivel de competencia. También se encontró un alto uso de estrategias de aprendizaje cognitivas, metacognitivas, afectivas y sociales, y un uso medio de las estrategias de memorización y compensatorias. Los resultados muestran que el uso de estrategias está motivado por las características de la lengua meta, las experiencias previas de aprendizaje de lenguas y el nivel de competencia de los alumnos. Estos resultados tienen implicaciones para considerar las necesidades de enseñanza específicas de los estudiantes de terceras lenguas con miras a desarrollar habilidades plurilingües a largo plazo.
TL;DR: In this paper , a comprehensive analysis of various machine and deep learning approaches, as well as how the systems perform in identifying fake Urdu news, which are submitted in the shared tasks named UrduFake@FIRE2020 and Urdufake@ FIRE2021, is provided.
Abstract: The fact that it might be difficult to distinguish between real news and fake news is of the utmost significance. It is difficult, time-consuming, and expensive to manually review enormous volumes of digital data in order to detect false news, which is information that is not real in line with the facts. There is a new piece of fake news published every second; hence, the creation of automated systems is absolutely necessary in order to detect instances of fake news. This study provides a comprehensive analysis of various machine and deep learning approaches, as well as how the systems perform in identifying fake Urdu news, which are submitted in the shared tasks named UrduFake@FIRE2020 and UrduFake@FIRE2021. It was hoped that the shared tasks would attract new researchers to come up with algorithms that could detect Urdu fake news articles available in the digital media. More than 50 teams from ten different nations participated to find a solution to this binary classification issue. The objective of the shared tasks was to classify a given Urdu news instance as either real or fake, and the teams proposed numerous algorithms to achieve this goal. Among the several methods of text representation that have been investigated in this study are count-based BoW features and word vector embeddings. Traditional neural and non-neural network approaches, including BERT, XLNet and RoBERTa are also examined, and their analysis is presented. Moreover, precision, recall, F1Real, F1Fake, and F1Macro are used for evaluation. The winning system in 2021 employed the linear classifier function and achieved 0.679 F1Macro, while the highest performing system in 2020 was based on BERT and obtained 0.907 F1Macro. Thus, the results of this research show that machine learning classifiers underperformed in detecting Urdu fake news than deep learning techniques.
TL;DR: In this paper , a taxonomy of educational data science (EDS) is proposed to organize EDS labor and shed light on the nature of the novel domain, where the first covers related fields and the second pursues the definition of its own identity to gain a distinctive place in the arena.
Abstract: Among the recent domains specialized in the arena of tracking, examining, and interpreting educational big data (EBD), educational data science (EDS) emerges as a domain that fosters teaching and learning settings, particularly those that use computers and mobile devices linked to the Internet with the aim of adapting and personalizing educational practice according to learners’ profiles. However, so far there is no a clear concept of what really is EDS. Hence, in order to give an answer to the question, this chapter shapes a landscape of EDS that covers from the background and baseline to the trends. In this pathway, a profile of some EDS-related works is outlined, and a taxonomy of EDS is proposed to organize EDS labor and shed light on the nature of the novel domain. As a result, one of the findings reveals EDS is coined from a dual view, where the first covers related fields and the second pursues the definition of its own identity to gain a distinctive place in the arena. Hence, one conclusion acknowledges the convenience of both concepts, inclusive and exclusive, for practical and technical purposes, respectively.
14 Feb 2023
TL;DR: In this article , a study of different nanodiamonds concentrations in terms of their fluorescent activity was investigated in the range of 0.1-10 mg/mL by means of fluorescence spectroscopy with the purpose of determining which concentration of nanoprobes suspended in milliQ water achieves the maximum intensity.