Search results for: André Luis Lima de Oliveira

Authors: Luis Guiliana, Andrea Osorio

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The lack of comprehension of the reservoir geomechanics conditions may cause operational problems that cost to the industry billions of dollars per year. The drilling operations at the Ceuta Field, Area 2 South, Maracaibo Lake, have been very expensive due to problems associated with drilling. The principal objective of this investigation is to develop a 3D geomechanical model in this area, in order to optimize the future drillings in the field. For this purpose, a 1D geomechanical model was built at first instance, following the workflow of the MEM (Mechanical Earth Model), this consists of the following steps: 1) Data auditing, 2) Analysis of drilling events and structural model, 3) Mechanical stratigraphy, 4) Overburden stress, 5) Pore pressure, 6) Rock mechanical properties, 7) Horizontal stresses, 8) Direction of the horizontal stresses, 9) Wellbore stability. The 3D MEM was developed through the geostatistic model of the Eocene C-SUP VLG-3676 reservoir and the 1D MEM. With this data the geomechanical grid was embedded. The analysis of the results threw, that the problems occurred in the wells that were examined were mainly due to wellbore stability issues. It was determined that the stress field change as the stratigraphic column deepens, it is normal to strike-slip at the Middle Miocene and Lower Miocene, and strike-slipe to reverse at the Eocene. In agreement to this, at the level of the Eocene, the most advantageous direction to drill is parallel to the maximum horizontal stress (157º). The 3D MEM allowed having a tridimensional visualization of the rock mechanical properties, stresses and operational windows (mud weight and pressures) variations. This will facilitate the optimization of the future drillings in the area, including those zones without any geomechanics information.

Keywords: geomechanics, MEM, drilling, stress

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Authors: Jackqueline Uy, Hannah Miriam Verano, Crysler Luis Verbo, Irene Gueco

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Educational tours are part of the curriculum of the College of Tourism and Hospitality Management, De La Salle University-Dasmarinas. They are highly significant to the students, especially Tourism students. The purpose of this study was to determine how effective educational tours were as a learning tool using the Experiential Learning Theory by David Kolb. This study determined the demographic profile of the third year tourism students in terms of gender, section, educational tours joined, and monthly family income and lastly, this study determined if there is a significant difference between the demographic profile of the respondents and their assessment of educational tours as a learning tool. The researchers used a historical research design with the third-year students of the bachelor of science in tourism management as the population size and used a random sampling method. The researchers made a survey questionnaire and utilized statistical tools such as weighted mean, frequency distribution, percentage, standard deviation, T-test, and ANOVA. The result of the study answered the profile of the respondents such as the gender, section, educational tour/s joined, and family monthly income. The findings of the study showed that the 3rd year tourism management students strongly agree that educational tours are a highly effective learning tool in terms of active experimentation, concrete experience, reflective observation, and abstract conceptualisation based on the data gathered from the respondents.

Keywords: CTHM, educational tours, experiential learning theory, De La Salle University Dasmarinas, tourism

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Authors: Anyi Katherine Garzon Robles, Luis Carlos Gomez Florez

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Since the advent of the Internet, the use of Information Technologies (IT) has increased exponentially. The field of informatics and telecommunications has put on the table countless possibilities for the development of different socio-economic activities, promoting a change of social paradigm and the emergence of the so-called information and knowledge society. For more than a decade, the Colombian government has been working on the incorporation of IT into the public sector through an e-government strategy. However, to date, many technological gaps has not yet been identified in the country to our knowledge, especially in rural areas and far from large cities, where factors such as low investment and the expansion of the armed conflict have led to economic and technological stagnation. This paper presents the research results obtained from the execution of a research project, which was approach from a qualitative approach and a methodological design of a participatory action research type. This design consists of nine fundamental stages divided into four work cycles. For which different strategies for data collection and analysis were established. From which, a methodology was obtained for the identification of technological gaps and the measurement of the level of technological acceptance in the rural sector, based on the TAM (Technology Acceptance Model) model, as a previous activity to the development of IT solutions framed in the e-government strategy in Colombia. The result of this research work represents a contribution from academia for the improvement of the country's technological development and a guide for the proper planning of IT solutions aimed at promoting a close relationship between government and citizens.

Keywords: E-government, knowledge society, level of technological acceptance, technological gaps, technology acceptance model

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Authors: Pedro M. Velasco, Cecilia C. Alday, Oscar C. Avello, Ximena T. Faundez, Luis M. Velasco

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Anaerobic digestion (AD) plants of food waste (FW) produced by agro-industry, have been widely developed from last decade to nowadays, because of the advantages over aerobic active sludge systems. Despite several bioreactor configurations and operation modes have been successfully improved and implemented at industrial scale in a wide range of applications, effluent behavior, after AD, does not commonly meet requirements for direct disposal into the environment without further treatments. In addition, literature has rarely shown AD of food waste at psychrophilic range. This temperature range may be of interest for making AD plant operation easier and increasing the stability of digestion. In spite of literature shows several methods for post-treatment, such as the use of microalgae, these have not been cultivated on effluents from AD at psychrophilic range. Hence, with the aim of showing the potential use of AD of FW at the psychrophilic range (25ºC) and the viability of microalgae post-treatment, single batch reactors have been used for methane potential tests at laboratory scale. Afterwards, digestates, derived from this AD of FW sludge, were diluted with fresh water at different ratios (1:0, 1:1; 1:4) and used as culture media for photoautotrophic microalgae. Several parameters, such as pH, biogas production, and chemical oxygen demand, were measured periodically over several months. Results show that methane potential is 150 ml g-1 per volatile solid with up to 57.7 % of methane content. Moreover, microalgae has been successfully cultivated on all tested effluents and in case of 1:1 and 1:4 rates, the resulting effluents meet the quality levels required for irrigation water.

Keywords: anaerobic digestion, biogas, food waste, microalgae, psychrophilic range

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Authors: Bruno Nascimento, Cristina Wanzeller, Jorge Silva, João A. Dias, André Barbosa, José Ribeiro

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The increasing complexity of logistics operations stems from evolving business needs, such as the shift from mass production to mass customization, which demands greater efficiency and flexibility. In response, Industry 4.0 and 5.0 technologies provide improved solutions to enhance operational agility and better meet market demands. The management of kitting zones, combined with the use of Autonomous Mobile Robots, faces challenges related to coordination, resource optimization, and rapid response to customer demand fluctuations. Additionally, implementing lean manufacturing practices in this context must be carefully orchestrated by intelligent systems and human operators to maximize efficiency without sacrificing the agility required in an advanced production environment. This paper proposes and implements a microservices-based architecture integrating principles from Industry 4.0 and 5.0 with lean manufacturing practices. The architecture enhances communication and coordination between autonomous vehicles and kitting management systems, allowing more efficient resource utilization and increased scalability. The proposed architecture focuses on the modularity and flexibility of operations, enabling seamless flexibility to change demands and the efficient allocation of resources in realtime. Conducting this approach is expected to significantly improve logistics operations’ efficiency and scalability by reducing waste and optimizing resource use while improving responsiveness to demand changes. The implementation of this architecture provides a robust foundation for the continuous evolution of kitting management and process optimization. It is designed to adapt to dynamic environments marked by rapid shifts in production demands and real-time decision-making. It also ensures seamless integration with automated systems, aligning with Industry 4.0 and 5.0 needs while reinforcing Lean Manufacturing principles.

Keywords: microservices, event-driven, kitting, AMR, lean manufacturing, industry 4.0, industry 5.0

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Authors: Laribi-Habchi Hasiba, Bouanane-Darenfed Amel, Drouiche Nadjib, Pausse André, Mameri Nabil

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Chitin, a linear 1, 4-linked N-acetyl-d-glucosamine (GlcNAc) polysaccharide is the major structural component of fungal cell walls, insect exoskeletons and shells of crustaceans. It is one of the most abundant naturally occurring polysaccharides and has attracted tremendous attention in the fields of agriculture, pharmacology and biotechnology. Each year, a vast amount of chitin waste is released from the aquatic food industry, where crustaceans (prawn, crab, Shrimp and lobster) constitute one of the main agricultural products. This creates a serious environmental problem. This linear polymer can be hydrolyzed by bases, acids or enzymes such as chitinase. In this context an extracellular chitinase (ChiA-65) was produced and purified from a newly isolated LHH100. Pure protein was obtained after heat treatment and ammonium sulphate precipitation followed by Sephacryl S-200 chromatography. Based on matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF/MS) analysis, the purified enzyme is a monomer with a molecular mass of 65,195.13 Da. The sequence of the 27 N-terminal residues of the mature ChiA-65 showed high homology with family-18 chitinases. Optimal activity was achieved at pH 4 and 75◦C. Among the inhibitors and metals tested p-chloromercuribenzoic acid, N-ethylmaleimide, Hg2+ and Hg + completelyinhibited enzyme activity. Chitinase activity was high on colloidal chitin, glycol chitin, glycol chitosane, chitotriose and chitooligosaccharide. Chitinase activity towards synthetic substrates in the order of p-NP-(GlcNAc) n (n = 2–4) was p-NP-(GlcNAc)2> p-NP-(GlcNAc)4> p-NP-(GlcNAc)3. Our results suggest that ChiA-65 preferentially hydrolyzed the second glycosidic link from the non-reducing end of (GlcNAc) n. ChiA-65 obeyed Michaelis Menten kinetics the Km and kcat values being 0.385 mg, colloidal chitin/ml and5000 s−1, respectively. ChiA-65 exhibited remarkable biochemical properties suggesting that this enzyme is suitable for bioconversion of chitin waste.

Keywords: Bacillus licheniformis LHH100, characterization, extracellular chitinase, purification

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Authors: Yanjie Zhu, André Jesus, Irwanda Laory

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Structural Health Monitoring (SHM), involving data acquisition, data interpretation and decision-making system aim to continuously monitor the structural performance of civil infrastructures under various in-service circumstances. The main value and purpose of SHM is identifying damages through data interpretation system. Research on SHM has been expanded in the last decades and a large volume of data is recorded every day owing to the dramatic development in sensor techniques and certain progress in signal processing techniques. However, efficient and reliable data interpretation for damage detection under environmental variations is still a big challenge. Structural damages might be masked because variations in measured data can be the result of environmental variations. This research reports a novel method based on single-channel Blind Signal Separation (BSS), which extracts environmental effects from measured data directly without any prior knowledge of the structure loading and environmental conditions. Despite the successful application in audio processing and bio-medical research fields, BSS has never been used to detect damage under varying environmental conditions. This proposed method optimizes and combines Ensemble Empirical Mode Decomposition (EEMD), Principal Component Analysis (PCA) and Independent Component Analysis (ICA) together to separate structural responses due to different loading conditions respectively from a single channel input signal. The ICA is applying on dimension-reduced output of EEMD. Numerical simulation of a truss bridge, inspired from New Joban Line Arakawa Railway Bridge, is used to validate this method. All results demonstrate that the single-channel BSS-based method can recover temperature effects from mixed structural response recorded by a single sensor with a convincing accuracy. This will be the foundation of further research on direct damage detection under varying environment.

Keywords: damage detection, ensemble empirical mode decomposition (EEMD), environmental variations, independent component analysis (ICA), principal component analysis (PCA), structural health monitoring (SHM)

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Authors: Armando Luis Vieira, Carlos Costa, Arthur Araújo

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The tourism system is viewable as a network of relationships amongst business partners where the success of each actor will ultimately be determined by the success of the whole network. Especially since the publication of Gümmesson’s (1996) ‘theory of imaginary organisations’, which suggests that organisational effectiveness largely depends on managing relationships and sharing resources and activities, relationship quality (RQ) has been increasingly recognised as a main source of value creation and competitive advantage. However, there is still ambiguity around this topic, and managers and researchers have been recurrently reporting the need to better understand and capitalise on the quality of interactions with business partners. This research aims at testing an RQ model from a relational, imaginary organisation’s approach. Two mail surveys provide the perceptions of 725 hotel representatives about their business relationships with tour operators, and 1,224 corporate client representatives about their business relationships with hotels (21.9 % and 38.8 % response rate, respectively). The analysis contributes to enhance our understanding on the linkages between RQ and its determinants, and identifies the role of their dimensions. Structural equation modelling results highlight trust as the dominant dimension, the crucial role of commitment and satisfaction, and suggest customer orientation as complementary building block. Findings also emphasise problem solving behaviour and selling orientation as the most relevant dimensions of customer orientation. The comparison of the two ‘dyads’ deepens the discussion and enriches the suggested theoretical and managerial guidelines concerning the contribution of quality relationships to business performance.

Keywords: corporate clients, destination competitiveness, hotels, relationship quality, structural equations modelling, tour operators

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Authors: Rafael Felipe Guatura da Silva, José Luis Gomes da Silva, Luiz Antonio, Ferreira Perrone de Brito

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Noise can cause serious damage to human health, such as hearing loss, stress, irritability, fatigue, and others. Aviation is a place where your entire process should be work out with the utmost attention and commitment of human resources, thus the need to study the effects of noise in this sector, as aeronautical noise levels are high. This study aimed to evaluate the impact of noise pollution on the performance of professionals regarding the fatigue generated by aeronautical noise and time to noise exposure. The methodology used consists of measurements of sound pressure levels at 42 points of the aerodrome. The selected points are located inside the hangars and outside the airfield hangars. All points chosen are close to the professionals' work areas, seeking to identify the sound pressure levels to which they submitted. The other part of the research used the principle on the application of a self-report questionnaire to a sample of 207 people working inside the aerodrome. The 207 professionals surveyed consist of aircraft mechanics, pilots, maintenance managers, and administrative professionals. The questionnaire was intended to evaluate the knowledge that professionals have about health risks caused by sound exposure as well as to identify diseases that professionals have, and that may be associated with exposure to high levels of sound pressure. Preliminary results identify points with sound pressure levels of up to 91.7 dB, thus highlighting the need for the use of personal protective equipment that reduces noise exposure. It was also identified a large number of professionals who are bothered by the sound exposure and approximately 25% of professionals interviewed reported having a hearing disorder.

Keywords: aeronautical noise, fatigue, noise and health, noise management

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Authors: David de Oliveira Costa, Miguel Ângelo Lellis Moreira, Carlos Francisco Simões Gomes, Daniel Augusto de Moura Pereira, Marcos dos Santos

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Strategic management is a fundamental process for global companies that intend to remain competitive in an increasingly dynamic and complex market. To do so, it is necessary to maintain alignment with their principles and values. The Balanced Scorecard (BSC) proposes to ensure that the overall business performance is based on different perspectives (financial, customer, internal processes, and learning and growth). However, relying solely on the BSC may not be enough to ensure the success of strategic management. It is essential that companies also evaluate and prioritize strategic projects that need to be implemented to ensure they are aligned with the business vision and contribute to achieving established goals and objectives. In this context, the proposition involves the incorporation of the SAPEVO-M multicriteria method to indicate the degree of relevance between different perspectives. Thus, the strategic objectives linked to these perspectives have greater weight in the classification of structural projects. Additionally, it is proposed to apply the concept of the Impact & Probability Matrix (I&PM) to structure and ensure that strategic projects are evaluated according to their relevance and impact on the business. By structuring the business's strategic management in this way, alignment and prioritization of projects and actions related to strategic planning are ensured. This ensures that resources are directed towards the most relevant and impactful initiatives. Therefore, the objective of this article is to present the proposal for integrating the BSC methodology, the SAPEVO-M multicriteria method, and the prioritization matrix to establish a concrete weighting of strategic planning and obtain coherence in defining strategic projects aligned with the business vision. This ensures a robust decision-making support process.

Keywords: MCDA process, prioritization problematic, corporate strategy, multicriteria method

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Authors: Kyra Kannen, Sonja D. Roelen, Sebastian Schnieder, Jarek Krajewski, Steffen Holsteg, André Karger, Johanna Askeridis, Celina Slawik, Philip Mildner, Jens Piesk, Ruslan David, Holger Kürten, Benjamin Oster, Robert Malzan, Mike Ludemann

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Virtual Reality (VR) is increasingly recognized for its potential in transforming mental disorder treatment, offering advantages such as cost-effectiveness, time efficiency, accessibility, reduced stigma, and scalability. While the application of VR in the context of anxiety disorders has been extensively evaluated and demonstrated to be effective, the utilization of VR as a therapeutic treatment for depression remains under-investigated. Our goal is to pioneer immersive VR therapy modules for treating major depression, alongside a web-based system for home use. We develop a modular digital therapy platform grounded in psychodynamic therapy interventions which addresses stress reduction, exploration of social situations and relationship support, social skill training, avoidance behavior analysis, and psychoeducation. In addition, an automated depression monitoring system, based on acoustic voice analysis, is implemented in the form of a speech-based diary to track the affective state of the user and depression severity. The use of immersive VR facilitates patient immersion into complex and realistic interpersonal interactions with high emotional engagement, which may contribute to positive treatment acceptance and satisfaction. In a proof-of-concept study, 45 depressed patients were assigned to VR or web-platform modules, evaluating user experience, usability and additional metrics including depression severity, mindfulness, interpersonal problems, and treatment satisfaction. The findings provide valuable insights into the effectiveness and user-friendliness of VR and web modules for depression therapy and contribute to the refinement of more tailored digital interventions to improve mental health.

Keywords: virtual reality therapy, digital health, depression, psychotherapy

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Authors: Dhouibi Mohamed, Stirbu Bogdan, Chabotier André, Pirlot Marc

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Effects of erosion and wear on the performance of small caliber guns have been analyzed throughout numerical and experimental studies. Mainly, qualitative observations were performed. Correlations between the volume change of the chamber and the maximum pressure are limited. This paper focuses on the development of a numerical model to predict the maximum pressure evolution when the interior shape of the chamber changes in the different weapon’s life phases. To fulfill this goal, an experimental campaign, followed by a numerical simulation study, is carried out. Two test barrels, « 5.56x45mm NATO » and « 7.62x51mm NATO,» are considered. First, a Coordinate Measuring Machine (CMM) with a contact scanning probe is used to measure the interior profile of the barrels after each 300-shots cycle until their worn out. Simultaneously, the EPVAT (Electronic Pressure Velocity and Action Time) method with a special WEIBEL radar are used to measure: (i) the chamber pressure, (ii) the action time, (iii) and the bullet velocity in each barrel. Second, a numerical simulation study is carried out. Thus, a coupled interior ballistic model is developed using the dynamic finite element program LS-DYNA. In this work, two different models are elaborated: (i) coupled Eularien Lagrangian method using fluid-structure interaction (FSI) techniques and a coupled thermo-mechanical finite element using a lumped parameter model (LPM) as a subroutine. Those numerical models are validated and checked through three experimental results, such as (i) the muzzle velocity, (ii) the chamber pressure, and (iii) the surface morphology of fired projectiles. Results show a good agreement between experiments and numerical simulations. Next, a comparison between the two models is conducted. The projectile motions, the dynamic engraving resistances and the maximum pressures are compared and analyzed. Finally, using this obtained database, a statistical correlation between the muzzle velocity, the maximum pressure and the chamber volume is established.

Keywords: engraving process, finite element analysis, gun barrel erosion, interior ballistics, statistical correlation

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Authors: Rita Yuniatun, Dewi Fadlilah Firdausi, Anida Hanifah, Putrisuvi Nurjannah Zalqis, Erza Nur Afrilia, Akrima Fajrin Nurimani, Andrew Luis Krishna

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Manganese (Mn) is one of the potential contaminants minerals geothermal water. Preliminary studies conducted in Ketenger village, the nearest village with Baturaden hot spring, showed that the concentration of Mn in water supply has exceeded the reference value. Mineral contamination problem in Ketenger village is not only Mn, but also other potential geothermal minerals, such as chromium (Cr), iron (Fe), sulfide (S2-), nickel (Ni), cobalt (Co), and zinc (Zn). It becomes a concern because generally the residents still use ground water as the water source for their daily needs, including drinking and cooking. Therefore, this study aimed to determine the distribution of mineral contamination in drinking water and food and to estimate the health risks possibility from the exposure. Four minerals (Mn, Fe, S2-, and Cr6+) were analyzed in drinking water, carbohydrate sources, vegetables, fishes, and fruits. The test results indicate that Mn concentration in drinking water is 0.35 mg/L, has exceeded the maximum contaminant level (MCL) according to the US EPA (MCL = 0.005 mg/L), whereas other minerals still comply with the standards. In addition, we found that the average of Mn concentration in the carbohydrate sources is quite high (1.87 mg/Kg). Measurement results in Chronic Daily Intake (CDI) and the Risk Quotient (RQ) found that exposure to manganese and other geothermal minerals in drinking water and food are safe from the non-carcinogenic effects in each age group (RQ<1). So, geothermal mineral concentrations in drinking water and food has no effect on non-carcinogenic risk in Ketenger’s residents because of CDI is also influenced by other parameters such as the duration of exposure and the rate of consumption. However, it was found that intake of essential minerals (Mn and Fe) are deficient in every age group. So that, the addition of Mn and Fe intake is recommended.

Keywords: CDI, contaminant, geothermal minerals, manganese, RQ

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Authors: João F. A. Martos, Felipe J. Costa, Sergio N. P. Laiton, Bruno C. Lima, Israel S. Rêgo, Paulo P. G. Toro

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Nowadays, the scramjet is a topic that has attracted the attention of several scientific communities (USA, Australia, Germany, France, Japan, India, China, Russia), that are investing in this in this type of propulsion system due its interest to facilitate access to space and reach hypersonic speed, who have invested in this type of propulsion due to the interest in facilitating access to space. The Brazilian hypersonic scramjet aerospace vehicle 14-X B is a technological demonstrator of a hypersonic airbreathing propulsion system based on the supersonic combustion (scramjet) intended to be tested in flight into the Earth's atmosphere at 30 km altitude and Mach number 7. The 14-X B has been designed at the Prof. Henry T. Nagamatsu Laboratory of Aerothermodynamics and Hypersonics of the Institute for Advanced Studies (IEAv) in Brazil. The IEAv Hypersonic Shock Tunnel, named T3, is a ground-test facility able to reproduce the flight conditions as the Mach number as well as pressure and temperature in the test section close to those encountered during the test flight of the vehicle 14-X B into design conditions. A 1-m long stainless steel 14-X B model was experimentally investigated at T3 Hypersonic Shock Tunnel, for freestream Mach number 7. Static pressure measurements along the lower surface of the 14-X B model, along with high-speed schlieren photographs taken from the 5.5° leading edge and the 14.5° deflection compression ramp, provided experimental data that were compared to the analytical-theoretical solutions and the computational fluid dynamics (CFD) simulations. The results show a good qualitative agreement, and in consequence demonstrating the importance of these methods in the project of the 14-X B hypersonic aerospace vehicle.

Keywords: 14-X, CFD, hypersonic, hypersonic shock tunnel, scramjet

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Authors: Mateus Silva Mendonça, Wender Pereira de Oliveira, Gabriel Heleno de Paula Araújo, Hiago Tenório Teixeira Santana Rocha, Augusto César Teixeira Malaquias, José Guilherme Coelho Baeta

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The stricter legislation and the greater demand of the population regard to gas emissions and their effects on the environment as well as on human health make the automotive industry reinforce research focused on reducing levels of contamination. This reduction can be achieved through the implementation of improvements in internal combustion engines in such a way that they promote the reduction of both specific fuel consumption and air pollutant emissions. These improvements can be obtained through numerical simulation, which is a technique that works together with experimental tests. The aim of this paper is to build, with support of the GT-Suite software, a one-dimensional model of a single-cylinder research engine to analyze the impact of the variation of swirl and tumble coefficients on the performance and on the air pollutant emissions of an engine. Initially, the discharge coefficient is calculated through the software Converge CFD 3D, given that it is an input parameter in GT-Power. Mesh sensitivity tests are made in 3D geometry built for this purpose, using the mass flow rate in the valve as a reference. In the one-dimensional simulation is adopted the non-predictive combustion model called Three Pressure Analysis (TPA) is, and then data such as mass trapped in cylinder, heat release rate, and accumulated released energy are calculated, aiming that the validation can be performed by comparing these data with those obtained experimentally. Finally, the swirl and tumble coefficients are introduced in their corresponding objects so that their influences can be observed when compared to the results obtained previously.

Keywords: 1D simulation, single-cylinder research engine, swirl coefficient, three pressure analysis, tumble coefficient

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Authors: Osvaldo N. Oliveira Jr.

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The control of molecular architecture inherent in some experimental methods to produce nanostructured films has had great impact on devices of various types, including sensors and biosensors. The self-assembly monolayers (SAMs) and the electrostatic layer-by-layer (LbL) techniques, for example, are now routinely used to produce tailored architectures for biosensing where biomolecules are immobilized with long-lasting preserved activity. Enzymes, antigens, antibodies, peptides and many other molecules serve as the molecular recognition elements for detecting an equally wide variety of analytes. The principles of detection are also varied, including electrochemical methods, fluorescence spectroscopy and impedance spectroscopy. In this presentation an overview will be provided of biosensors made with nanostructured films to detect antibodies associated with tropical diseases and HIV, in addition to detection of analytes of medical interest such as cholesterol and triglycerides. Because large amounts of data are generated in the biosensing experiments, use has been made of computational and statistical methods to optimize performance. Multidimensional projection techniques such as Sammon´s mapping have been shown more efficient than traditional multivariate statistical analysis in identifying small concentrations of anti-HIV antibodies and for distinguishing between blood serum samples of animals infected with two tropical diseases, namely Chagas´ disease and Leishmaniasis. Optimization of biosensing may include a combination of another information visualization method, the Parallel Coordinate technique, with artificial intelligence methods in order to identify the most suitable frequencies for reaching higher sensitivity using impedance spectroscopy. Also discussed will be the possible convergence of technologies, through which machine learning and other computational methods may be used to treat data from biosensors within an expert system for clinical diagnosis.

Keywords: clinical diagnosis, information visualization, nanostructured films, layer-by-layer technique

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Authors: Ola Jon Mork, Lars Andre Giske, Emil Bjørlykhaug

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Stabilization of critical processes in order to have the right quality of the products, more efficient production and smoother flow is a key issue in lean production. This paper presents how simulation of key welding processes can stabilize complicated welding processes in small scale production, and how simulation can impact the entire production concept seen from the perspective of lean production. First, a field study was made to learn the production processes in the factory, and subsequently the field study was transformed into a value stream map to get insight into each operation, the quality issues, operation times, lead times and flow of materials. Valuable practical knowledge of how the welding operations were done by operators, appropriate tools and jigs, and type of robots that could be used, was collected. All available information was then implemented into a simulation environment for further elaboration and development. Three researchers, the management of the company and skilled operators at the work floor where working on the project over a period of eight months, and a detailed description of the process was made by the researchers. The simulation showed that simulation could solve a number of technical challenges, the robot program can be tuned in off line mode, and the design and testing of the robot cell could be made in the simulator. Further on the design of the product could be optimized for robot welding and the jigs could be designed and tested in simulation environment. This means that a key issue of lean production can be solved; the welding operation will work with almost 100% performance when it is put into real production. Stabilizing of one key process is critical to gain control of the entire value chain, then a Takt Time can be established and the focus can be directed towards the next process in the production which should be stabilized. Results show that industrial parameters like welding time, welding cost and welding quality can be defined on the simulation stage. Further on, this gives valuable information for calculation of the factories business performance, like manufacturing volume and manufacturing efficiency. Industrial impact from simulation is more efficient implementation of lean manufacturing, since the welding process can be stabilized. More research should be done to gain more knowledge about simulation as a tool for implementation of lean, especially where there complex processes.

Keywords: simulation, lean, stabilization, welding process

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Authors: Camilo A. Guerrero-Martin, Erik Montes Paez, Marcia C. K. Oliveira, Jonathan Campos, Elizabete F. Lucas

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Asphaltenes precipitation is considered as a formation damage problem, which can reduce the oil recovery factor. It fouls piping and surface installations, as well as cause serious flow assurance complications and decline oil well production. Therefore, researchers have shown an interest in chemical treatments to control this phenomenon. The aim of this paper is to assess the asphaltenes precipitation onset of crude oils in the presence of cardanol, by titrating the crude with n-heptane. Moreover, based on this results obtained at atmosphere pressure, the asphaltenes precipitation onset pressure were calculated to predict asphaltenes precipitation in the reservoir, by using differential liberation and refractive index data of the oils. The influence of cardanol concentrations in the asphaltenes stabilization of three Brazilian crude oils samples (with similar API densities) was studied. Therefore, four formulations of cardanol in toluene were prepared: 0, 3, 5, 10 and 15 m/m%. The formulations were added to the crude at 2:98 ratio. The petroleum samples were characterized by API density, elemental analysis and differential liberation test. The asphaltenes precipitation onset (APO) was determined by titrating with n-heptane and monitoring with near-infrared (NIR). UV-Vis spectroscopy experiments were also done to assess the precipitate asphaltenes content. The asphaltenes precipitation envelopes (APE) were also determined by numerical simulation (Multiflash). In addition, the adequate artificial lift systems (ALS) for the oils were selected. It was based on the downhole well profile and a screening methodology. Finally, the oil flowrates were modelling by NODAL analysis production system in the PIPESIM software. The results of this study show that the asphaltenes precipitation onset of the crude oils were 2.2, 2.3 and 6.0 mL of n-heptane/g of oil. The cardanol was an effective inhibitor of asphaltenes precipitation for the crude oils used in this study, since it displaces the precipitation pressure of the oil to lower values. This indicates that cardanol can increase the oil wells productivity.

Keywords: asphaltenes, NODAL analysis production system, precipitation pressure onset, inhibitory molecule

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Authors: Luis C. Parra

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The significant wave height prediction is an issue of great interest in the field of coastal activities because of the non-linear behavior of the wave height and its complexity of prediction. This study aims to present a machine learning model to forecast the significant wave height of the oceanographic wave measuring buoys anchored at Mooloolaba of the Queensland Government Data. Modeling was performed by a multilayer perceptron neural network-genetic algorithm (GA-MLP), considering Relu(x) as the activation function of the MLPNN. The GA is in charge of optimized the MLPNN hyperparameters (learning rate, hidden layers, neurons, and activation functions) and wrapper feature selection for the window width size. Results are assessed using Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The GAMLPNN algorithm was performed with a population size of thirty individuals for eight generations for the prediction optimization of 5 steps forward, obtaining a performance evaluation of 0.00104 MSE, 0.03222 RMSE, 0.02338 MAE, and 0.71163% of MAPE. The results of the analysis suggest that the MLPNNGA model is effective in predicting significant wave height in a one-step forecast with distant time windows, presenting 0.00014 MSE, 0.01180 RMSE, 0.00912 MAE, and 0.52500% of MAPE with 0.99940 of correlation factor. The GA-MLP algorithm was compared with the ARIMA forecasting model, presenting better performance criteria in all performance criteria, validating the potential of this algorithm.

Keywords: significant wave height, machine learning optimization, multilayer perceptron neural networks, evolutionary algorithms

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Authors: Mohamed Dhouibi, Bogdan Stirbu, Chabotier André, Marc Pirlot

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Internal barrel wear is a major factor affecting the performance of small caliber guns in their different life phases. Wear analysis is, therefore, a very important process for understanding how wear occurs, where it takes place, and how it spreads with the aim on improving the accuracy and effectiveness of small caliber weapons. This paper discusses the measurement and analysis of combustion chamber wear for a small-caliber gun using a Coordinate Measuring Machine (CMM). Initially, two different NATO small caliber guns: 5.56x45mm and 7.62x51mm, are considered. A Micura Zeiss Coordinate Measuring Machine (CMM) equipped with the VAST XTR gold high-end sensor is used to measure the inner profile of the two guns every 300-shot cycle. The CMM parameters, such us (i) the measuring force, (ii) the measured points, (iii) the time of masking, and (iv) the scanning velocity, are investigated. In order to ensure minimum measurement error, a statistical analysis is adopted to select the reliable CMM parameters combination. Next, two measurement strategies are developed to capture the shape and the volume of each gun chamber. Thus, a task-specific measurement uncertainty (TSMU) analysis is carried out for each measurement plan. Different approaches of TSMU evaluation have been proposed in the literature. This paper discusses two different techniques. The first is the substitution method described in ISO 15530 part 3. This approach is based on the use of calibrated workpieces with similar shape and size as the measured part. The second is the Monte Carlo simulation method presented in ISO 15530 part 4. Uncertainty evaluation software (UES), also known as the Virtual Coordinate Measuring Machine (VCMM), is utilized in this technique to perform a point-by-point simulation of the measurements. To conclude, a comparison between both approaches is performed. Finally, the results of the measurements are verified through calibrated gauges of several dimensions specially designed for the two barrels. On this basis, an experimental database is developed for further analysis aiming to quantify the relationship between the volume of wear and the muzzle velocity of small caliber guns.

Keywords: coordinate measuring machine, measurement uncertainty, erosion and wear volume, small caliber guns

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Authors: Elucir Gir, Laelson Rochelle Milanês Sousa, Renata Karina Reis, Soraia Assad Nasbine Rabeh, Mayra Gonçalves Menegueti, Ana Cristina de Oliveira e Silva, Sheila Araújo Teles

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Context and significance: Nursing team professionals faced challenges in combating the COVID-19 pandemic around the world. They were subjected to exhausting workloads and prolonged use of Personal Protective Equipment. Using N95 masks for long periods of time can cause skin changes. In this context, health professionals who worked on the front lines of fighting the pandemic were more exposed to possible physical and psychological changes. Objective: The aim of the study was to analyze the factors associated with skin lesions resulting from the use of N95 masks among nursing team professionals. Method: The study was carried out in all regions of Brazil from October to December 2020, with professionals from the nursing team who worked in health care during the COVID-19 pandemic. Participants were recruited via social media, and information was collected electronically and stored on the Survey Monkey platform. Descriptive statistics were used to characterize the sample, association tests (Chi-square), with a statistical significance level of p < 0.05. Factors associated with skin lesions resulting from the use of an N95 mask were determined by Binary Logistic Regression, with a significance level of 5% (α = 0.05). Results: 8,405 nursing professionals participated in the study, 5,492 nurses (65.3%), 2,747 nursing technicians (32.7%), and 7,084 females (84.3%). Female nursing team professionals were 1.4 times more likely to develop skin lesions due to the use of N95 masks when compared to males (OR 1.4 [CI95% 1.22 – 1.59] p < 0.001). The following protective factors were identified: nursing technician (ORA 0.608 [CI95% 0.43 – 0.86] p = 0.005) and not having provided assistance in field hospitals for COVID-19 (0.73 [CI95% 0.65-0.81] p<0.000). Conclusion: It was concluded that female nursing team professionals were more likely to have skin changes related to the use of N95 masks. The need for intervention studies is emphasized in order to explore measures to prevent these types of injuries. Descritores: Nursing professionals; COVID-19; SARS-CoV-2; Brazil.

Keywords: nursing professionals, COVID-19, SARS-CoV-2, Brazil

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Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

Procedia PDF Downloads 622

Authors: Debora C. Mendes, Matthias Eckert, Claudia S. Moço, Helio Martins, Jean-Pierre Gonçalves, Miguel Oliveira, Jose P. Da Silva

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Disposal of construction and demolition waste (C&DW) in embankments in the periphery of cities causes both environmental and social problems. To achieve the management of C&DW, a detailed analysis of the properties of these materials should be done. In this work we report a comparative study of the physical, chemical and environmental properties of natural and C&DW aggregates from 25 different origins. Assays were performed according to European Standards. Analysis of heavy metals and organic compounds, namely polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs), were performed. Finally, properties of concrete prepared with C&DW aggregates are reported. Physical analyses of C&DW aggregates indicated lower quality properties than natural aggregates, particularly for concrete preparation and unbound layers of road pavements. Chemical properties showed that most samples (80%) meet the values required by European regulations for concrete and unbound layers of road pavements. Analyses of heavy metals Cd, Cr, Cu, Pb, Ni, Mo and Zn in the C&DW leachates showed levels below the limits established by the Council Decision of 19 December 2002. Identification and quantification of PCBs and PAHs indicated that few samples shows the presence of these compounds. The measured levels of PCBs and PAHs are also below the limits. Other compounds identified in the C&DW leachates include phthalates and diphenylmethanol. The characterized C&DW aggregates show lower quality properties than natural aggregates but most samples showed to be environmentally safe. A continuous monitoring of the presence of heavy metals and organic compounds should be made to trial safe C&DW aggregates. C&DW aggregates provide a good economic and environmental alternative to natural aggregates.

Keywords: concrete preparation, construction and demolition waste, heavy metals, organic pollutants

Procedia PDF Downloads 361

Authors: Carolina Aparicio-Fernández, Alejandro Vilar Abad, Mar Cañada Soriano, Jose-Luis Vivancos

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The building sector is responsible for 40% of the total energy consumption in the European Union (EU). Thus, implementation of strategies for quantifying and reducing buildings energy consumption is indispensable for reaching the EU’s carbon neutrality and energy efficiency goals. Each Member State has transposed the European Directives according to its own peculiarities: existing technical legislation, constructive solutions, climatic zones, etc. Therefore, in accordance with the Energy Performance of Buildings Directive, Member States have developed different Energy Performance Certificate schemes, using proposed energy simulation software-tool for each national or regional area. Energy Performance Certificates provide a powerful and comprehensive information to predict, analyze and improve the energy demand of new and existing buildings. Energy simulation software and databases allow a better understanding of the current constructive reality of the European building stock. However, Energy Performance Certificates still have to face several issues to consider them as a reliable and global source of information since different calculation tools are used that do not allow the connection between them. In this document, TRNSYS (TRaNsient System Simulation program) software is used to calculate the energy demand of a building, and it is compared with the energy labeling obtained with Spanish Official software-tools. We demonstrate the possibility of using not official software-tools to calculate the Energy Performance Certificate. Thus, this approach could be used throughout the EU and compare the results in all possible cases proposed by the EU Member States. To implement the simulations, an isolated single-family house with different construction solutions is considered. The results are obtained for every climatic zone of the Spanish Technical Building Code.

Keywords: energy demand, energy performance certificate EPBD, trnsys, buildings

Procedia PDF Downloads 127

Authors: Javier Comes Fayos, Isabel RodríGuez Moreno, Sara Bressanutti, Marisol Lila, Angel Romero MartíNez, Luis Moya Albiol

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Given the great impact produced by gender-based violence, its comprehensive approach seems essential. Consequently, research has focused on risk factors for violent behaviour, linking various psychosocial variables, as well as cognitive and neuropsychological deficits with the aggressors. However, studies on affective processing are scarce, so the present study investigates possible emotional alterations in men convicted of gender violence. The participants were 51 aggressors, who attended the CONTEXTO program with sentences of less than two years, and 47 men with no history of violence. The sample did not differ in age, socioeconomic level, education, or alcohol and other substances consumption. Anger, alexithymia and facial recognition of other people´s emotions were assessed through the State-Trait Anger Expression Inventory (STAXI-2), the Toronto Alexithymia Scale (TAS-20) and Reading the mind in the eyes (REM), respectively. Men convicted of gender-based violence showed higher scores on the anger trait and temperament dimensions, as well as on the anger expression index. They also scored higher on alexithymia and in the identification and emotional expression subscales. In addition, they showed greater difficulties in the facial recognition of emotions by having a lower score in the REM. These results seem to show difficulties in different affective areas in men condemned for gender violence. The deficits are reflected in greater difficulty in identifying and expressing emotions, in processing anger and in recognizing the emotions of others. All these difficulties have been related to the use of violent behavior. Consequently, it is essential and necessary to include emotional regulation in intervention programs for men who have been convicted of gender-based violence.

Keywords: alexithymia, anger, emotional processing, emotional recognition, empathy, intimate partner violence

Procedia PDF Downloads 202

Authors: Farhana Arefeen Mila, Luis Emilio Morales, Nam Hoang, Sujana Adapa, Garry Griffith

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This study investigates the existence of price transmission asymmetries and imperfections among the coastal and freshwater fish species in Bangladesh. Using a Structural Vector Autoregression (SVAR) model, we explore how price changes in one fish species impact the prices of others in the retail market. Monthly data from the Department of Agricultural Marketing (DAM) covering the period from 2012 to 2023 was analyzed. Price series were detrended using the Hodrick-Prescott filter, and unit root tests confirmed stationarity after detrending. The findings indicate that there are significant interdependencies and asymmetries in price transmission, particularly the strong influence of Hilsha on the broader fish market. Hilsha’s price shocks generate immediate responses across other species, reflecting its cultural and economic importance. Silver Pomfret demonstrates some independence but is still affected by broader market fluctuations, particularly those involving Hilsha. Meanwhile, Rohu and Catla exhibit high interdependence, where price changes in one species closely impact the other, underscoring their substitutable nature in consumer preferences. These findings emphasize the need for joint interventions and market monitoring to stabilize prices effectively. Stakeholders are encouraged to monitor Hilsha’s market, consider coordinated interventions for Rohu and Catla, and establish data-sharing partnerships to enhance market stability. Additionally, promoting consumer awareness of price trends and sustainable practices can further support market resilience and long-term sustainability in the fisheries sector.

Keywords: price transmission, cross commodity, fish, Bangladesh, CCF, SVAR, IRF

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Authors: Luísa P. Cruz-Lopes, Hugo Costa e Silva, Idalina Domingos, José Ferreira, Luís Teixeira de Lemos, Bruno Esteves

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The liquefaction process of cork based tree barks has led to an increase of interest due to its potential innovation in the lumber and wood industries. In this particular study the bark of Quercus cerris (Turkish oak) is used due to its appreciable amount of cork tissue, although of inferior quality when compared to the cork provided by other Quercus trees. This study aims to optimize alkaline catalysis liquefaction conditions, regarding several parameters. To better comprehend the possible chemical characteristics of the bark of Quercus cerris, a complete chemical analysis was performed. The liquefaction process was performed in a double-jacket reactor heated with oil, using glycerol and a mixture of glycerol/ethylene glycol as solvents, potassium hydroxide as a catalyst, and varying the temperature, liquefaction time and granulometry. Due to low liquefaction efficiency resulting from the first experimental procedures a study was made regarding different washing techniques after the filtration process using methanol and methanol/water. The chemical analysis stated that the bark of Quercus cerris is mostly composed by suberin (ca. 30%) and lignin (ca. 24%) as well as insolvent hemicelluloses in hot water (ca. 23%). On the liquefaction stage, the results that led to higher yields were: using a mixture of methanol/ethylene glycol as reagents and a time and temperature of 120 minutes and 200 ºC, respectively. It is concluded that using a granulometry of <80 mesh leads to better results, even if this parameter barely influences the liquefaction efficiency. Regarding the filtration stage, washing the residue with methanol and then distilled water leads to a considerable increase on final liquefaction percentages, which proves that this procedure is effective at liquefying suberin content and lignocellulose fraction.

Keywords: liquefaction, Quercus cerris, polyalcohol liquefaction, temperature

Procedia PDF Downloads 334

Authors: Marcio Mesquita, Diogo Henrique Morato de Moraes, Henrique Fonseca Elias de Oliveira, Rilner Alves Flores, Mateus Rodrigues Ferreira, Dalva Graciano Ribeiro

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This study aimed to analyze the movement of water in irrigated and non-irrigated rice (Oryza sativa L.) leaves, from the xylem to the stomata, through numerical simulations. Through three-dimensional modeling, it was possible to determine how the spacing of parenchyma cells and the permeability of these cells influence the apoplastic flow and the opening of the stomata. The thickness of the cuticle and the number of vascular bundles are greater in plants subjected to water stress, indicating an adaptive response of plants to environments with water deficit. In addition, numerical simulations revealed that the opening of the stomata, the permeability of the parenchyma cells and the cell spacing have significant impacts on the energy loss and the speed of water movement. It was observed that a more open stoma facilitates water flow, decreasing the resistance and energy required for transport, while higher levels of permeability reduce energy loss, indicating that a more permeable tissue allows for more efficient water transport. Furthermore, it was possible to note that stomatal aperture, parenchyma permeability and cell spacing are crucial factors in the efficient water management of plants, especially under water stress conditions. These insights are essential for the development of more effective agricultural management strategies and for the breeding of plant varieties that are more resistant to adverse growing conditions. Computed fluid dynamics has allowed us to overcome the limitations of conventional techniques by providing a means to visualize and understand the complex hydrodynamic processes within the vascular system of plants.

Keywords: numerical modeling, vascular anatomy, vascular hydrodynamics, xylem, Oryza sativa L.

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Authors: Jefferson Camacho Mejia, Jenny Paola Forero Pachon, Luis Carlos Gomez Florez

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The innumerable possibilities offered by the use of Information Technology (IT) in the development of different socio-economic activities has made a change in the social paradigm and the emergence of the so-called information and knowledge society. The Colombian government, aware of this reality, has been promoting the use of IT as part of the E-government strategy adopted in the country. However, it is well known that the use of IT implies the existence of certain threats that put the security of information in the digital environment at risk. One of the priorities of the Colombian government is to improve access to alternative justice through IT, in particular, access to Alternative Dispute Resolution (ADR): conciliation, arbitration and friendly composition; by means of which it is sought that the citizens directly resolve their differences. To this end, a trend has been identified in the use of Online Dispute Resolution (ODR) systems, which extend the benefits of ADR to the digital environment through the use of IT. This article presents a process for the analysis of information security risks associated with the incorporation of ODR systems in the context of conciliation in Colombia, based on four fundamental stages identified in the literature: (I) Identification of assets, (II) Identification of threats and vulnerabilities (III) Estimation of the impact and 4) Estimation of risk levels. The methodological design adopted for this research was the grounded theory, since it involves interactions that are applied to a specific context and from the perspective of diverse participants. As a result of this investigation, the activities to be followed are defined to carry out an analysis of information security risks, in the context of the conciliation in Colombia supported by ODR systems, thus contributing to the estimation of the risks to make possible its subsequent treatment.

Keywords: alternative dispute resolution, conciliation, information security, online dispute resolution systems, process, risk analysis

Procedia PDF Downloads 241

Authors: Nádia Pereira, Paula Ferreira, Sofia Francisco, Sofia Oliveira, Sidclay Souza, Paula Paulino, Ana Margarida Veiga Simão

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Social media has progressed into a platform for hate speech among its users, and thus, there is an increasing need to develop automatic detection classifiers of offense and conflicts to help decrease the prevalence of such incidents. Online communication can be used to intentionally harm someone, which is why such classifiers could be essential in social networks. A possible application of these classifiers is the automatic detection of cyberbullying. Even though identifying the aggressive language used in online interactions could be important to build cyberbullying datasets, there are other criteria that must be considered. Being able to capture the language, which is indicative of the intent to harm others in a specific context of online interaction is fundamental. Offense and hate speech may be the foundation of online conflicts, which have become commonly used in social media and are an emergent research focus in machine learning and natural language processing. This study presents two Portuguese language offense-related datasets which serve as examples for future research and extend the study of the topic. The first is similar to other offense detection related datasets and is entitled Aggressiveness dataset. The second is a novelty because of the use of the history of the interaction between users and is entitled the Conflicts/Attacks dataset. Both datasets were developed in different phases. Firstly, we performed a content analysis of verbal aggression witnessed by adolescents in situations of cyberbullying. Secondly, we computed frequency analyses from the previous phase to gather lexical and linguistic cues used to identify potentially aggressive conflicts and attacks which were posted on Twitter. Thirdly, thorough annotation of real tweets was performed byindependent postgraduate educational psychologists with experience in cyberbullying research. Lastly, we benchmarked these datasets with other machine learning classifiers.

Keywords: aggression, classifiers, cyberbullying, datasets, hate speech, machine learning

Procedia PDF Downloads 229