Search results for: Carlos Alberto Riveros

Authors: Ouafek Nora, Keghouche Nassira, Dehdouh Heider, Untidt Carlos

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A lot of knowledge has been accumulated on the metal clusters supported on oxide surfaces because of their multiple applications in microelectronics, heterogeneous catalysis, and magnetic devices. In this work, the surface state of Ni / MgO has been studied by XPS (X-ray Photoemission Spectroscopy). The samples were prepared by impregnation with ion exchange Ni²⁺ / MgO, followed by either a thermal treatment in air (T = 100 -350 ° C) or a gamma irradiation (dose 100 kGy, 25 kGy dose rate h -1). The obtained samples are named after impregnation NMI, NMR after irradiation, and finally NMC(T) after calcination at the temperature T (T = 100-600 °C). A structural study by XRD and HRTEM reveals the presence of nanoscaled Ni-Mg intermetallic phases (Mg₂Ni, MgNi₂, and Mg₆Ni) and magnesium hydroxide. Mg(OH)₂ in nanometric range (2- 4 nm). Mg-Ni compounds are of great interest in energy fields (hydrogen storage…). XPS spectra show two Ni2p peaks at energies of about 856.1 and 861.9 eV, indicating that the nickel is primarily in an oxidized state on the surface. The shift of the main peak relative to the pure NiO (856.1 instead of 854.0 eV) suggests that in addition to oxygen, nickel is engaged in another link with magnesium. This is in agreement with the O1s spectra which present an overlap of peaks corresponds to NiO and MgO, at a calcination temperature T ≤ 300 °C.

Keywords: XPS, XRD, nanoparticules, Ni-MgO

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Authors: Paulo Cesar Pereira Junior, Alexandre Monteiro, Rafael da Luz Ribeiro, Antonio Carlos Sobieranski, Aldo von Wangenheim

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In this paper, we present a comparison between convolutional neural networks and classical computer vision approaches, for the specific precision agriculture problem of weed mapping on sugarcane fields aerial images. A systematic literature review was conducted to find which computer vision methods are being used on this specific problem. The most cited methods were implemented, as well as four models of convolutional neural networks. All implemented approaches were tested using the same dataset, and their results were quantitatively and qualitatively analyzed. The obtained results were compared to a human expert made ground truth for validation. The results indicate that the convolutional neural networks present better precision and generalize better than the classical models.

Keywords: convolutional neural networks, deep learning, digital image processing, precision agriculture, semantic segmentation, unmanned aerial vehicles

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Authors: Antonio Sepúlveda, Camila Marques, Carlos Bolonha, Igor De Lazari, Henrique Rangel

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The judicial practice faces a tension between normative discretion and institutional capacities. There are clarity graduations of the statutory text that might induce different specialization levels of the judges. A major problem stemming from that tension is a greater discretion without a proportional specialization. The normative clarity, although its absence can be overcome through specialization, avoids problems related to disproportionate discretion and judicial dissonance. When judicial interpretation deals with the lack of legal clarity, a significant juridical insecurity frame is verified. Decisional uniformity mechanisms are created in order to surpass these problems. Brazil brings great examples, such as the súmulas, the enunciados, and the súmulas vinculantes. Despite of the resistance presented to the latter, mainly based on judges’ independence, even countries of the Common Law tradition develop such mechanisms. The British Guidelines face the lack of legal clarity problem and promote a decisional consonance system.

Keywords: generalist judges, institutional capacities, normative clarity, normative discretion

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Authors: Emmanuel Carlos De Mata Castrejón

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Music education has shown to be connected to many areas of sciences and arts, it has also been associated with several facets of human life. The many aspects around the study of music and education, make very difficult for the music educator to find a way through, even though there are lots of methods of teaching music to young children, they are different between one another and so are the students. For the music to help improve children’s development, it is necessary for the children to explore their musicality as they explore their creativity; it must be a challenging, playful, and enjoyable activity. The purpose of this investigation is to focus the music education not in the music, nor the teaching, but the children to be guided through their own musicality. The first approach to this kind of music education comes from the Active learning methods during the nineteenth century, most of which are still used around the world, sometimes with modifications to fit a certain place or type of students. This approach on children’s musicality requires some knowledge of music, pedagogy, and developmental psychology at least, but more important than the theory or the method used for music education, the focus should be on developing the student’s musicality, considering the complexity of this concept. To get this, it is needed, indeed, far more research in the topic, so this is a call for collaborative research and for interdisciplinary teams to emerge. This is a review of authors and methods in music education trying to trace a line pointing to transdisciplinary work and pursuing the development of children’s musicality.

Keywords: children, methods, music education, musicality

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Authors: Guilherme Gorgulho, Carlos Roberto Camello Lima

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Over the past five years between 2011 and 2015, the license plate of cars, light commercial vehicles, trucks and buses have suffered retraction. This sector's decline can be explained by economic and national policy in the Brazilian industry operates. In parallel to the reduction of sales and license plate of vehicles, their suppliers are also affected influencing its results, among these vendors, there is the auto parts sector. The existence of international companies, and featured strongly in Asia and Mexico due to low production costs, encourage companies to constantly seek continuous improvement and operational efficiency. Under this argument, the decision making based on lean manufacturing tools it is essential for the management of operations. The purpose of this article is to analyze between lean practices in Brazilian auto parts industries, through the application of a questionnaire with employees who practice lean thinking in organizations. The purpose is to confront the extracted data in the questionnaires, and debate on which of lean tools help organizations as a competitive advantage.

Keywords: autoparts, brazilian industry, lean practices, survey

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Authors: Guilherme Gorgulho, Carlos Roberto Camello Lima

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Due to the competitive market in which companies are currently engaged, the constant changes require companies to react quickly regarding the variability of demand and process. The changes are caused by customers, or by demand fluctuations or variations of products, or the need to serve customers within agreed delivery taking into account the continuous search for quality and competitive prices in products. These changes end up influencing directly or indirectly the activities of the Planning and Production Control (PPC), which does business in strategic, tactical and operational levels of production systems. One area of concern for organizations is in the short term (operational level), because this planning stage any error or divergence will cause waste and impact on the delivery of products on time to customers. Thus, this study aims to optimize the efficiency of production scheduling, using different sequencing strategies in an automotive company. Seeking to aim the proposed objective, we used the computer simulation in conjunction with lean manufacturing to build and validate the current model, and subsequently the creation of future scenarios.

Keywords: computational simulation, lean manufacturing, production scheduling, sequencing strategies

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Authors: Javier Fernandez, Mayte Medina, Rafael Fernandez de Canete, Nuria Alcain, Juan Carlos Ramos-Diaz

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At present, the experimentation of anesthetic drugs on patients requires a regulation protocol, and the response of each patient to several doses of entry drug must be well known. Therefore, the development of pharmacological dose control systems is a promising field of research in anesthesiology. In this paper, it has been developed a non-linear compartmental the pharmacokinetic-pharmacodynamical model which describes the anesthesia depth effect in a sufficiently reliable way over a set of patients with the depth effect quantified by the Bi-Spectral Index. Afterwards, an Artificial Neural Network (ANN) predictive controller has been designed based on the depth of anesthesia model so as to keep the patient in the optimum condition while he undergoes surgical treatment. For the purpose of quantifying the efficiency of the neural predictive controller, a classical proportional-integral-derivative controller has also been developed to compare both strategies. Results show the superior performance of predictive neural controller during BiSpectral Index reference tracking.

Keywords: anesthesia, bi-spectral index, neural network control, pharmacokinetic-pharmacodynamical model

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Authors: Patricia O. Carvalho, Marcia C. F. Messias, Laura Credidio, Carlos A. R. Martinez

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Lipidomic strategy can provide important information regarding cancer pathogenesis mechanisms and could reveal new biomarkers to enable early diagnosis of rectal adenocarcinoma (RAC). This study set out to evaluate lipoperoxidation biomarkers, and lipidomic signature by gas chromatography (GC) and electrospray ionization-qToF-mass spectrometry (ESI-qToF-MS) combined with multivariate data analysis in plasma from 23 RAC patients (early- or advanced-stages cancer) and 18 healthy controls. The most abundant ions identified in the RAC patients were those of phosphatidylcholine (PC) and phosphatidylethanolamine (PE) while those of lisophosphatidylcholine (LPC), identified as LPC (16:1), LPC (18:1) and LPC (18:2), were down-regulated. LPC plasmalogen containing palmitoleic acid (LPC (P-16:1)), with highest VIP score, showed a low tendency in the cancer patients. Malondialdehyde plasma levels were higher in patients with advanced cancer (III/IV stages) than in the early stages groups and the healthy group (p<0.05). No differences in F2-isoprostane levels were observed between these groups. This study shows that the reduction in plasma levels of LPC plasmalogens associated to an increase in MDA levels may indicate increased oxidative stress in these patients and identify the metabolite LPC (P-16:1) as new biomarkers for RAC.

Keywords: biomarkers, lipidomic, plasmalogen, rectal adenocarcinoma

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Authors: Francys Souza, Alberto Ohashi, Dorival Leao

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We present a general solution for finding the ε-optimal controls for non-Markovian stochastic systems as stochastic differential equations driven by Brownian motion, which is a problem recognized as a difficult solution. The contribution appears in the development of mathematical tools to deal with modeling and control of non-Markovian systems, whose applicability in different areas is well known. The methodology used consists to discretize the problem through a random discretization. In this way, we transform an infinite dimensional problem in a finite dimensional, thereafter we use measurable selection arguments, to find a control on an explicit form for the discretized problem. Then, we prove the control found for the discretized problem is a ε-optimal control for the original problem. Our theory provides a concrete description of a rather general class, among the principals, we can highlight financial problems such as portfolio control, hedging, super-hedging, pairs-trading and others. Therefore, our main contribution is the development of a tool to explicitly the ε-optimal control for non-Markovian stochastic systems. The pathwise analysis was made through a random discretization jointly with measurable selection arguments, has provided us with a structure to transform an infinite dimensional problem into a finite dimensional. The theory is applied to stochastic control problems based on path-dependent stochastic differential equations, where both drift and diffusion components are controlled. We are able to explicitly show optimal control with our method.

Keywords: dynamic programming equation, optimal control, stochastic control, stochastic differential equation

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Authors: Matteo Rossini, Alberto Portioli Staudacher

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The market competition is moving from the single firm to the whole supply chain one because of increasing competition and growing need for operational efficiencies and customer orientation. Supply chain management allows companies to look beyond their organizational boundaries to develop and leverage resources and capabilities of their supply chain partners. This leads to create competitive advantages in the marketplace and because of this SCM has acquired strategic importance. Lean Approach is a management strategy that focuses on reducing every type of waste present in an organization. This approach is becoming more and more popular among supply chain managers. The supply chain application of lean approach is low diffused. It is not well studied which are the impacts of lean approach principles in a supply chain context. In literature there are only few studies simulating the lean approach performance in single products supply chain. This research work studies the impacts of lean principles implementation along a supply chain. To achieve this, a simulation model of a three-echelon multiproduct product supply chain has been built. Kanban system (and several priority policies) and setup time reduction degrees are implemented in the lean-configured supply chain to apply pull and lot-sizing decrease principles respectively. To evaluate the benefits of lean approach, lean supply chain is compared with an EOQ-configured supply chain. The simulation results show that Kanban system and setup-time reduction improve inventory stock level. They also show that logistics efforts are affected to lean implementation degree. The paper concludes describing performances of lean supply chain in different contexts.

Keywords: inventory policy, Kanban, lean supply chain, simulation study, supply chain management, planning

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Authors: Bernabeo R. Alberto

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Unmanned aerial vehicles (UAV) platforms or remotely piloted aircraft system (Rpas) - with dedicated sensors - are fundamental support to the planning, running, and control of the territory in which public safety is or may be at risk for post-disaster assessments such as flooding or landslides, for searching lost people, for crime and accident scene photography, for assisting traffic control at major events, for teaching geography, history, natural science and all those subjects that require a continuous cyclical process of observation, evaluation and interpretation. Through the use of proximal remote sensing information related to anthropic landscape and nature integration, there is an opportunity to improve knowledge and management decision-making for the safeguarding of the environment, for farming, wildlife management, land management, mapping, glacier monitoring, atmospheric monitoring, for the conservation of archeological, historical, artistic and architectural sites, allowing an exact delimitation of the site in the territory. This paper will go over many different mission types. Within each mission type, it will give a broad overview to familiarize the reader but not make them an expert. It will also give detailed information on the payloads and other testing parameters the Unmanned Aerial Vehicles (UAV) use to complete a mission. The project's goal is to improve satellite maps about the stress of the plants, air quality monitoring, and related health issues.

Keywords: proximal remote sensing, remotely piloted aircraft system, risk, safety, unmanned aerial vehicle

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Authors: Edward Guillén, Jeisson Sánchez, Carlos Omar Ramos

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In recent years, a wide variety of applications are developed with Support Vector Machines -SVM- methods and Artificial Neural Networks -ANN-. In general, these methods depend on intrusion knowledge databases such as KDD99, ISCX, and CAIDA among others. New classes of detectors are generated by machine learning techniques, trained and tested over network databases. Thereafter, detectors are employed to detect anomalies in network communication scenarios according to user’s connections behavior. The first detector based on training dataset is deployed in different real-world networks with mobile and non-mobile devices to analyze the performance and accuracy over static detection. The vulnerabilities are based on previous work in telemedicine apps that were developed on the research group. This paper presents the differences on detections results between some network scenarios by applying traditional detectors deployed with artificial neural networks and support vector machines.

Keywords: anomaly detection, back-propagation neural networks, network intrusion detection systems, support vector machines

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Authors: Mario Gómez, José Carlos Rodríguez

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This paper analyzes the Environmental Kuznets Curve (EKC) hypothesis to test the causality relationship between economic activity, trade openness and carbon dioxide emissions in Mexico (1971-2011). The results achieved in this research show that there are three long-run relationships between production, trade openness, energy consumption and carbon dioxide emissions. The EKC hypothesis was not verified in this research. Indeed, it was found evidence of a short-term unidirectional causality from GDP and GDP squared to carbon dioxide emissions, from GDP, GDP squared and TO to EC, and bidirectional causality between TO and GDP. Finally, it was found evidence of long-term unidirectional causality from all variables to carbon emissions. These results suggest that a reduction in energy consumption, economic activity, or an increase in trade openness would reduce pollution.

Keywords: causality, cointegration, energy consumption, economic growth, environmental Kuznets curve

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Authors: Luther Ollier, Sylvie Thiria, Anastase Charantonis, Carlos E. Mejia, Michel Crépon

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Sea Surface Height Anomaly (SLA) is a signature of the sub-mesoscale dynamics of the upper ocean. Sea Surface Temperature (SST) is driven by these dynamics and can be used to improve the spatial interpolation of SLA fields. In this study, we focused on the temporal evolution of SLA fields. We explored the capacity of deep learning (DL) methods to predict short-term SLA fields using SST fields. We used simulated daily SLA and SST data from the Mercator Global Analysis and Forecasting System, with a resolution of (1/12)◦ in the North Atlantic Ocean (26.5-44.42◦N, -64.25–41.83◦E), covering the period from 1993 to 2019. Using a slightly modified image-to-image convolutional DL architecture, we demonstrated that SST is a relevant variable for controlling the SLA prediction. With a learning process inspired by the teaching-forcing method, we managed to improve the SLA forecast at five days by using the SST fields as additional information. We obtained predictions of a 12 cm (20 cm) error of SLA evolution for scales smaller than mesoscales and at time scales of 5 days (20 days), respectively. Moreover, the information provided by the SST allows us to limit the SLA error to 16 cm at 20 days when learning the trajectory.

Keywords: deep-learning, altimetry, sea surface temperature, forecast

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Authors: Cristie Ann Jaca-Delfin, Felino Javines Jr.

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Teachers especially those who are teaching elementary and high school students need to upgrade their teaching practices in order to become effective and efficient facilitators of learning. It is in this context that this study is conducted in order to present the perceived teaching-learning activities needs among basic education teachers in the three campuses of the University of San Carlos, Cebu City, the Philippines as expressed during their In-Service Teacher Training. The study employed the quantitative-qualitative research design and used the researcher-made survey questionnaire to look into the ten items under Teaching-Learning Activities to determine which item teachers need to be trained and retrained on. The data were solicited during the teachers’ In-Service Teacher Training period conducted in May 2015. It was found out that designing interesting and meaningful classroom activities, strategies in teaching and assessment procedures were identified as the most needed areas teachers want to be included in their in-service training. As these expressed needs were identified, the teachers’ in-service training must a venue for teachers’ instructional development needs to be addressed so as to maximize the students’ learning outcomes

Keywords: in-service teacher training, perceived needs, teaching-learning activities, teaching practices

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Authors: Cecilia Espindola, Juan Carlos Palacios

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Flavonoids are a large group of natural compounds which are found in many fruits and vegetables. A subgroup of these called flavanones display a wide range of biological activities, and they also have an important physiological role in plants. The ionic liquid (ILs) are compounds consisting of an organic cation with an organic or inorganic anion. Due to its unique properties such as high electrical conductivity, wide temperature range of the liquid state, thermal and electrochemical stability, high ionic density and low volatility and flammability, are considered as ecological solvents in organic synthesis, catalysis, electrolytes in accumulators, and electrochemistry, non-volatile plasticizers, and chemical separation. It was synthesized ionic liquid IL 1-butyl-3-methylimidazolium bromide free-solvent and used as reaction medium for flavanones synthesis, under several reaction conditions of temperature, time and production. The obtained compounds were analyzed by melting point, elemental analysis, IR and UV-vis spectroscopy.

Keywords: 1-butyl-3-methylimidazolium bromide, flavonoids, free-solvent, IR spectroscopy

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Authors: Luyao Zhang, Tianyu Wu, Jiayi Li, Carlos-Gustavo Salas-Flores, Saad Lahrichi

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Recent advances in AI have made algorithmic trading a central role in finance. However, current research and applications are disconnected information islands. We propose a generally applicable pipeline for designing, programming, and evaluating algorithmic trading of stock and crypto tokens. Moreover, we provide comparative case studies for four conventional algorithms, including moving average crossover, volume-weighted average price, sentiment analysis, and statistical arbitrage. Our study offers a systematic way to program and compare different trading strategies. Moreover, we implement our algorithms by object-oriented programming in Python3, which serves as open-source software for future academic research and applications.

Keywords: algorithmic trading, AI for finance, fintech, machine learning, moving average crossover, volume weighted average price, sentiment analysis, statistical arbitrage, pair trading, object-oriented programming, python3

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Authors: Harold Mauricio Díaz-Vargas, Cristian Alfonso Jimenez-Castaño, David Augusto Cárdenas-Peña, Guillermo Alberto Ortiz-Gómez, Alvaro Angel Orozco-Gutierrez

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Precise identification of the nerves is a crucial task performed by anesthesiologists for an effective Peripheral Nerve Blocking (PNB). Now, anesthesiologists use ultrasound imaging equipment to guide the PNB and detect nervous structures. However, visual identification of the nerves from ultrasound images is difficult, even for trained specialists, due to artifacts and low contrast. The recent advances in deep learning make neural networks a potential tool for accurate nerve segmentation systems, so addressing the above issues from raw data. The most widely spread U-Net network yields pixel-by-pixel segmentation by encoding the input image and decoding the attained feature vector into a semantic image. This work proposes a conditioning approach and encoder pre-training to enhance the nerve segmentation of traditional U-Nets. Conditioning is achieved by the one-hot encoding of the kind of target nerve a the network input, while the pre-training considers five well-known deep networks for image classification. The proposed approach is tested in a collection of 619 US images, where the best C-UNet architecture yields an 81% Dice coefficient, outperforming the 74% of the best traditional U-Net. Results prove that pre-trained models with the conditional approach outperform their equivalent baseline by supporting learning new features and enriching the discriminant capability of the tested networks.

Keywords: nerve segmentation, U-Net, deep learning, ultrasound imaging, peripheral nerve blocking

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Authors: Carlos Gonzalez, Neil Slatcher, Marcus Properzi, Kan Seah

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In many underground mining operations, shotcrete is used for permanent rock support. Shotcrete thickness is a critical measure of the success of this process. 3D Laser Mapping, in conjunction with Jetcrete, has developed a 3D laser scanning system specifically for measuring the thickness of shotcrete. The system is mounted on the shotcrete spraying machine and measures the rock faces before and after spraying. The calculated difference between the two 3D surface models is measured as the thickness of the sprayed concrete. Typical work patterns for the shotcrete process required a rapid and automatic system. The scanning takes place immediately before and after the application of the shotcrete so no convergence takes place in the interval between scans. Automatic alignment of scans without targets was implemented which allows for the possibility of movement of the spraying machine between scans. Case studies are presented where accuracy tests are undertaken and automatic audit reports are calculated. The use of 3D imaging data for the calculation of shotcrete thickness is an important tool for geotechnical engineers and contract managers, and this could become the new state-of-the-art methodology for the mining industry.

Keywords: 3D imaging, shotcrete, surface model, tunnel stability

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Authors: Miguel Arlenzo Duran Sarmiento, Luis Alfonso Del Portillo Valdés, Carlos Borras Pinilla

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Brake energy regeneration systems have the capacity to transform part of the vehicle's kinetic energy during deceleration into useful energy. These systems can be implemented in hybrid vehicles, which can be electric or hydraulic in type, and contribute to reducing the energy required to propel the vehicle thanks to the accumulation of energy. This paper presents the modeling and simulation of a braking energy regeneration system applied in hydraulic hybrid vehicles configured in parallel, the modeling and simulation were performed in Simulink of Matlab, where a performance comparison of the regenerated torque as a function of vehicle load, the displacement of the hydraulic regeneration device and the vehicle speed profile. The speed profiles used in the simulation are standard profiles such as the NEDC and WLTP profiles. The vehicle loads range from 1500 kg to 12000 kg. The results show the comparison of the torque required by the vehicle, the torque regenerated by the system subjected to the different speed and load conditions.

Keywords: braking energy, energy regeneration, hybrid vehicles, kinetic energy, torque

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Authors: Abrahão S. Fontes, Carlos A. V. Cardoso, Levi P. B. Oliveira

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The induction motors are used worldwide in various industries. Several maintenance techniques are applied to increase the operating time and the lifespan of these motors. Among these, the predictive maintenance techniques such as Motor Current Signature Analysis (MCSA), Motor Square Current Signature Analysis (MSCSA), Park's Vector Approach (PVA) and Park's Vector Square Modulus (PVSM) are used to detect and diagnose faults in electric motors, characterized by patterns in the stator current frequency spectrum. In this article, these techniques are applied and compared on a real motor, which has the fault of eccentricity in the air-gap. It was used as a theoretical model of an electric induction motor without fault in order to assist comparison between the stator current frequency spectrum patterns with and without faults. Metrics were purposed and applied to evaluate the sensitivity of each technique fault detection. The results presented here show that the above techniques are suitable for the fault of eccentricity in the air gap, whose comparison between these showed the suitability of each one.

Keywords: eccentricity in the air-gap, fault diagnosis, induction motors, predictive maintenance

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Authors: Estefania Ponce-Amaya, Ana Lidia Arellano-Ortiz, Cecilia Diaz-Hernandez, Jose Alberto Lopez-Diaz, Antonio De La Mora-Covarrubias, Claudia Lucia Vargas-Requena, Mauricio Salcedo-Vargas, Florinda Jimenez-Vega

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Cervical Cancer (CC) is the second leading cause of death among women worldwide and it had been associated with a persistent infection of human papillomavirus (HPV). The goal of the current study was to identify the prevalence of HPV infection in women with abnormal Pap smear who were attended at Dysplasia Clinic of Ciudad Juarez, Mexico. Methods: Cervical samples from 146 patients, who attended the Colposcopy Clinic at Sanitary Jurisdiction II of Cd Juarez, were collected for histopathology and molecular study. DNA was isolated for the HPV detection by Polymerase Chain Reaction (PCR) using MY09/011 and GP5/6 primers. The associated risk factors were assessed by a questionnaire. The statistical analysis was performed by ANOVA, using EpiINFO V7 software. Results: HPV infection was present in 142 patients (97.3 %). The prevalence of HPV infection was distributed in a 96% of all evaluated groups, low-grade squamous intraepithelial lesion (LSIL), high-grade squamous intraepithelial lesion (HISIL) and CC. We found a statistical significance (α = <0.05) between gestation and number of births as risk factors. The median values showed an ascending tend according with the lesion progression. However, CC showed a statistically significant difference with respect to the pre-carcinogenic stages. Conclusions: In these Mexican patients exists a high prevalence of HPV infection, and for that reason, we are studying the most prevalent HPV genotypes in this population.

Keywords: cervical cancer, HPV, prevalence hpv, squamous intraepithelial lesion

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Authors: Carlos Marden Cabral Coutinho, Jose Luis Bolzan de Morais

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The article proposed intends to analyze the possibility (and conditions) of a media regulation law in a democratic rule of law in the twenty-first century. To do so, will be presented initially the idea of the public sphere (by Jürgen Habermas), showing how it is presented as an interface between the citizen and the state (or the private and public) and how important is it in a deliberative democracy. Based on this paradigm, the traditional perception of the role of public information (such as system functional element) and on the possibility of media regulation will be exposed, due to the public nature of their activity. A critical argument will then be displayed from two different perspectives: a) the formal function of the current media information, considering that the digital age has fragmented the information access; b) the concept of a constructive democracy, which reduces the need for representation, changing the strategic importance of the public sphere. The question to be addressed (based on the comparative law) is if the regulation is justified in a polycentric democracy, especially when it operates under the digital age (with immediate and virtual communication). The proposal is to be presented in the sense that even in a twenty-first century the media in a democratic rule of law still has an extremely important role and may be subject to regulation, but this should be on terms very different (and narrower) from those usually defended.

Keywords: constructive democracy, media, digital age, public sphere

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Authors: Hassan Badkoobehi, Pradip Peter Dey, Mohammad Amin, Milan Jose Carlos, Basmal Hana, Fadi Zaco

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The economy of coastline areas depends on the natural splendor of estuaries. When estuaries are improperly managed or polluted, long or short term damage to local economy or harm to local life forms can be caused. Estuaries are shelters for thousands of species such as birds, mammals, fish, crustaceans, insects, reptiles, and amphibians. The delicate balance of these life forms in estuaries requires careful planning for the benefit of all. The commercial value of estuaries is very important; recreational activities that people enjoy like boating, kayaking, windsurfing, swimming, bird-watching and fishing are marketable. Estuaries are national treasures with vital community and ecological resources. Years of estuarine environmental studies have produced extensive results that merit consideration. This study reviews research results from various sources and suggests best strategies for maintaining healthy estuaries in the current socioeconomic conditions. The main hypothesis is that many estuaries can be restored to their original healthy status in a cost effective manner with restoration or prevention plans suggested in published studies.

Keywords: environment, pollution, sustainable, wildlife

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Authors: Carlos David Carrillo Trujillo, Rebelín Echeverría Echeverría, Nancy Evia Alamilla, Rocío Quintal López

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Gender as a social construct is a term now widely studied. Within the social sciences it has become very important. In this sense, psychology tries to make some contributions from your area. The intention is to promote equal opportunities for men and women. Social, employment and educational inequities perpetuate sexism, violence and other important social problems in Mexico. The gender perspective is conceptualized as a tool to promote laws, policies, plans, programs and procedures where women are made ​​visible and empowered. The aim of this is the pursuit of equality. Thus, gender mainstreaming is one of the main challenges of education in Mexico. Only a few universities have programs, research or subjects related to the topic. Human resources, and time allocated to teachers are identified as obstacles to the institutionalization of gender. The objective was to make a diagnosis on course offerings and policies on gender. A documentary study and interviews with managers of at least 20 higher education institutions (IES's) were performed. The results indicate the need for greater gender courses, research projects and intervention. The need to promote policies that seek equal opportunities between men and women is also noted.

Keywords: gender mainstreaming, institutionalization, universities, intervention

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Authors: Leonardo C. Pacheco-Londoño, Nataly J Galan-Freyle, Lisandro Pacheco-Lugo, Antonio Acosta-Hoyos, Elkin Navarro, Gustavo Aroca-Martinez, Karin Rondón-Payares, Alberto C. Espinosa-Garavito, Samuel P. Hernández-Rivera

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At the Life Science Research Center at Simon Bolivar University, a primary focus is the diagnosis of various diseases, and the use of gold nanoparticles (Au-NPs) in diverse biomedical applications is continually expanding. In the present study, Au-NPs were employed as substrates for Surface-Enhanced Raman Spectroscopy (SERS) aimed at diagnosing kidney diseases arising from Lupus Nephritis (LN), preeclampsia (PC), and Hypertension (H). Discrimination models were developed for distinguishing patients with and without kidney diseases based on the SERS signals from urine samples by partial least squares-discriminant analysis (PLS-DA). A comparative study of the Raman signals across the three conditions was conducted, leading to the identification of potential metabolite signals. Model performance was assessed through cross-validation and external validation, determining parameters like sensitivity and specificity. Additionally, a secondary analysis was performed using machine learning (ML) models, wherein different ML algorithms were evaluated for their efficiency. Models’ validation was carried out using cross-validation and external validation, and other parameters were determined, such as sensitivity and specificity; the models showed average values of 0.9 for both parameters. Additionally, it is not possible to highlight this collaborative effort involved two university research centers and two healthcare institutions, ensuring ethical treatment and informed consent of patient samples.

Keywords: SERS, Raman, PLS-DA, kidney diseases

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Authors: Eric Mensah, Carlos Mensah

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The road maintenance backlogs created as a result of deferred maintenance especially in developing countries has caused considerable deterioration of many road assets. This is usually due to difficulties encountered in selecting and prioritising maintainable roads based on objective criteria rather than some political or other less important criteria. In order to ensure judicious use of limited resources for road maintenance, five factors were identified as the most important criteria for road management within the study area. This was based on the judgements of 40 experts. The results were further used to develop weightings using the Multi-Criteria Decision Process (MCDP) to analyse and select road alternatives according to maintenance goal. Using Geographical Information Systems (GIS), maintainable roads were grouped using the Jenk’s natural breaks to allow for further prioritised in order of importance for display on a dashboard of maps, charts, and tables. This reduces the problems of subjective maintenance and road selections, thereby reducing wastage of resources and easing the maintenance process through an object organised spatial decision support system.

Keywords: decision support, geographical information systems, multi-criteria decision process, weighted sum

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Authors: J. Carlos Kuri, Varun Vij, Raymond J. Turner, Orly Yadid-Pecht

Abstract:

Celiac disease (CD) is an immune system disorder that is triggered by ingesting gluten. As a gluten-free (GF) diet has become a concern of many people for health reasons, a gold standard had to be nominated. Enzyme-linked immunosorbent assay (ELISA) has taken the seat of this role. However, multiple limitations were discovered, and with that, the desire for an alternative method now exists. Nucleic acid-based aptamers have become of great interest due to their selectivity, specificity, simplicity, and rapid-testing advantages. However, fluorescence-based aptasensors have been tagged as unstable, but lifespan details are rarely stated. In this work, the lifespan stability of a fluorescence-based aptasensor is shown over an 8-week-long study displaying the accuracy of the sensor and false negatives. This study follows 22 different samples, including GF and gluten-rich (GR) and soy sauce products, off-the-shelf products, and reference material from laboratories, giving a total of 836 tests. The analysis shows an accuracy of correctly classifying GF and GR products of 96.30% and 100%, respectively when the protocol is augmented with molecular sieves. The overall accuracy remains around 94% within the first four weeks and then decays to 63%.

Keywords: aptasensor, PEG, rGO, FAM, RM, ELISA

Procedia PDF Downloads 121

Authors: Carlos A. Domínguez Torres, Antonio Domínguez Delgado

Abstract:

In this work we study the thermodynamic behavior of some ventilated facades under summer operating conditions in Southern Spain. Under these climatic conditions, indoor comfort implies a high energetic demand due to high temperatures that usually are reached in this season in the considered geographical area. The aim of this work is to determine if during summer operating conditions in Southern Spain, ventilated façades provide some energy saving compared to the non-ventilated façades and to deduce their behavior patterns in terms of energy efficiency. The modeling of the air flow in the channel has been performed by using Navier-Stokes equations for thermodynamic flows. Numerical simulations have been carried out with a 2D Finite Element approach. This way, we analyze the behavior of ventilated façades under different weather conditions as variable wind, variable temperature and different levels of solar irradiation. CFD computations show that the combined effect of the shading of the external wall and the ventilation by the natural convection into the air gap achieve a reduction of the heat load during the summer period. This reduction has been evaluated by comparing the thermodynamic performances of two ventilated and two unventilated façades with the same geometry and thermophysical characteristics.

Keywords: passive cooling, ventilated façades, energy-efficient building, CFD, FEM

Procedia PDF Downloads 354

Authors: Renata Rank Miranda, Arandi Ginane Bezerra, Ciro Alberto Oliveira Ribeiro, Marco AntôNio Ferreira Randi, Carmen Lúcia Voigt, Lilian Skytte, Kaare Lund Rasmussen, Francisco Filipak Neto, Frank Kjeldsen

Abstract:

Synergetic and antagonistic effects of drugs are well-known concerns in pharmacological assessments of dose and toxicity. Similar approach should be used in assessing cellular uptake and cytotoxicity of nanoparticles. Since nanoparticles are released into the aquatic environment they may interact with existing xenobiotics. Here we used biochemical assays and quantitative proteomics to assess the cytotoxicity of silver nanoparticles (AgNP) when human hepatoma HepG2 cells were co-exposed to 2 nm AgNP together with either Cd2+ or Hg2+ ions. Time-course experiments (2h, 4h, and 24h) were conducted to assess the first response to the exposure studies. The general trend was that a synergetic toxicological response was observed in cells exposed to both AgNP and Cd2+ or Hg2+, with AgNP and Cd2+ being more toxic. This was observed by a significant increase in the ROS and superoxide level of >35% in the case of AgNP+Cd2+ compared to the sum of responses of AgNP and Cd2+, individually. Metabolic activity and viability also dropped more for AgNP+Cd2+ (>10%) than for AgNP and Cd2+ combined. We used inductively coupled plasma mass spectrometry to investigate if AgNP facilitates larger influx of toxic metal ions into HepG2 cells. Only Hg2+ ions was found to be more efficiently engulfed as the concentration of Hg2+ was found 2.8 times larger compared to exposure experiments with only Hg2+. This effect was not observed for Cd2+. We now continue with deep proteomics studies to obtain wider details on the mechanism of the toxicity related to AgNP, Cd2+, and AgNP+Cd2+, respectively.

Keywords: nanotoxicology, silver nanoparticles, proteomics, human cell line

Procedia PDF Downloads 346