Search results for: Carlos Alberto Riveros
265 Smart Material for Bacterial Detection Based on Polydiacetylene/Polyvinyl Butyrate Fiber Composites
Authors: Pablo Vidal, Misael Martinez, Carlos Hernandez, Ananta R. Adhikari, Luis Materon, Yuanbing Mao, Karen Lozano
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Conjugated polymers are smart materials that show tremendous practical applications in diverse subjects. Polydiacetylenes are conjugated polymers with special optical properties. In response to the environmental changes such as pH and molecular binding, it changes its color. Such an interesting chromic and emissive behavior of polydiacetylenes make them a highly popular polymer in wide areas, including biomedicine such as a biosensor. In this research, we used polyvinyl butyrate as a matrix to fibrillate polydiacetylenes. We initially prepared polyvinyl butyrate/diacetylene matrix using forcespinning technique. They were then polymerized to form polyvinyl butyrate/polydiacetylene (PVB/PDA). These matrices then studied for their bio-sensing response to gram-positive and gram-negative bacteria. The sensing ability of the PVB/PDA biosensor was observed as early as 30 min in the presence of bacteria at 37°C. Now our effort is to decrease this effective temperature to room temperature to make this device applicable in the general daily life. These chromic biosensors will find extensive application not only alert the infection but also find other promising applications such as wearable sensors and diagnostic systems.Keywords: smart material, conjugated polymers, biosensor, polyvinyl butyrate/polydiacetylene
Procedia PDF Downloads 128264 Modeling of Ductile Fracture Using Stress-Modified Critical Strain Criterion for Typical Pressure Vessel Steel
Authors: Carlos Cuenca, Diego Sarzosa
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Ductile fracture occurs by the mechanism of void nucleation, void growth and coalescence. Potential sites for initiation are second phase particles or non-metallic inclusions. Modelling of ductile damage at the microscopic level is very difficult and complex task for engineers. Therefore, conservative predictions of ductile failure using simple models are necessary during the design and optimization of critical structures like pressure vessels and pipelines. Nowadays, it is well known that the initiation phase is strongly influenced by the stress triaxiality and plastic deformation at the microscopic level. Thus, a simple model used to study the ductile failure under multiaxial stress condition is the Stress Modified Critical Strain (SMCS) approach. Ductile rupture has been study for a structural steel under different stress triaxiality conditions using the SMCS method. Experimental tests are carried out to characterize the relation between stress triaxiality and equivalent plastic strain by notched round bars. After calibration of the plasticity and damage properties, predictions are made for low constraint bending specimens with and without side grooves. Stress/strain fields evolution are compared between the different geometries. Advantages and disadvantages of the SMCS methodology are discussed.Keywords: damage, SMSC, SEB, steel, failure
Procedia PDF Downloads 297263 Quality of Life of the Beneficiaries of the Government’s Bolsa Família Program: A Case Study in Mateiros/TO/Brazil
Authors: Mary L. G. S. Senna, Afonso R. Aquino, Veruska C. Dutra, Carlos H. C. Tolentino
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The quality of life index, despite elucidating many discussions, the conceptual subjectivity of the term does not show precision, and consequently, many researchers seek to develop methods aiming to measure this concept, bringing it to a more concrete approach. In this study, the quality of life index method was used to analyze the population of Mateiros, Tocantins, Brazil for quality of life. After data collection, it was compared the quality of life index between the population and the group of beneficiaries of the Brazilian government assistance program Bolsa Família (Family Allowance). Some of the people interviewed receive financial aid from the federal government program Bolsa Família (22%). Comparisons were made among the final score of the quality of life index of the Mateiros population and the following factors: Gender, age, education, those working or not with tourism and those who receive or do not receive the Bolsa Família. It was observed that only the factor, Bolsa Família (p-score 0.0138), shows an association with quality of life improvement, noticing that those who have financial aid had a higher quality of life improvement than the rest of the population. It was concluded that, government assistance has shown a decisive element on the enhancement of Mateiros population quality of life, indicating that similar actions should be maintained.Keywords: quality of life index, government aid to families, sustainable tourism, Bolsa Familia
Procedia PDF Downloads 303262 Modeling Bessel Beams and Their Discrete Superpositions from the Generalized Lorenz-Mie Theory to Calculate Optical Forces over Spherical Dielectric Particles
Authors: Leonardo A. Ambrosio, Carlos. H. Silva Santos, Ivan E. L. Rodrigues, Ayumi K. de Campos, Leandro A. Machado
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In this work, we propose an algorithm developed under Python language for the modeling of ordinary scalar Bessel beams and their discrete superpositions and subsequent calculation of optical forces exerted over dielectric spherical particles. The mathematical formalism, based on the generalized Lorenz-Mie theory, is implemented in Python for its large number of free mathematical (as SciPy and NumPy), data visualization (Matplotlib and PyJamas) and multiprocessing libraries. We also propose an approach, provided by a synchronized Software as Service (SaaS) in cloud computing, to develop a user interface embedded on a mobile application, thus providing users with the necessary means to easily introduce desired unknowns and parameters and see the graphical outcomes of the simulations right at their mobile devices. Initially proposed as a free Android-based application, such an App enables data post-processing in cloud-based architectures and visualization of results, figures and numerical tables.Keywords: Bessel Beams and Frozen Waves, Generalized Lorenz-Mie Theory, Numerical Methods, optical forces
Procedia PDF Downloads 380261 Globally Attractive Mild Solutions for Non-Local in Time Subdiffusion Equations of Neutral Type
Authors: Jorge Gonzalez Camus, Carlos Lizama
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In this work is proved the existence of at least one globally attractive mild solution to the Cauchy problem, for fractional evolution equation of neutral type, involving the fractional derivate in Caputo sense. An almost sectorial operator on a Banach space X and a kernel belonging to a large class appears in the equation, which covers many relevant cases from physics applications, in particular, the important case of time - fractional evolution equations of neutral type. The main tool used in this work was the Hausdorff measure of noncompactness and fixed point theorems, specifically Darbo-type. Initially, the equation is a Cauchy problem, involving a fractional derivate in Caputo sense. Then, is formulated the equivalent integral version, and defining a convenient functional, using the analytic integral resolvent operator, and verifying the hypothesis of the fixed point theorem of Darbo type, give us the existence of mild solution for the initial problem. Furthermore, each mild solution is globally attractive, a property that is desired in asymptotic behavior for that solution.Keywords: attractive mild solutions, integral Volterra equations, neutral type equations, non-local in time equations
Procedia PDF Downloads 158260 Extending BDI Multiagent Systems with Agent Norms
Authors: Francisco José Plácido da Cunha, Tassio Ferenzini Martins Sirqueira, Marx Leles Viana, Carlos José Pereira de Lucena
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Open Multiagent Systems (MASs) are societies in which heterogeneous and independently designed entities (agents) work towards similar, or different ends. Software agents are autonomous and the diversity of interests among different members living in the same society is a fact. In order to deal with this autonomy, these open systems use mechanisms of social control (norms) to ensure a desirable social order. This paper considers the following types of norms: (i) obligation — agents must accomplish a specific outcome; (ii) permission — agents may act in a particular way, and (iii) prohibition — agents must not act in a specific way. All of these characteristics mean to encourage the fulfillment of norms through rewards and to discourage norm violation by pointing out the punishments. Once the software agent decides that its priority is the satisfaction of its own desires and goals, each agent must evaluate the effects associated to the fulfillment of one or more norms before choosing which one should be fulfilled. The same applies when agents decide to violate a norm. This paper also introduces a framework for the development of MASs that provide support mechanisms to the agent’s decision-making, using norm-based reasoning. The applicability and validation of this approach is demonstrated applying a traffic intersection scenario.Keywords: BDI agent, BDI4JADE framework, multiagent systems, normative agents
Procedia PDF Downloads 232259 Scoping Review of Biological Age Measurement Composed of Biomarkers
Authors: Diego Alejandro Espíndola-Fernández, Ana María Posada-Cano, Dagnóvar Aristizábal-Ocampo, Jaime Alberto Gallo-Villegas
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Background: With the increase in life expectancy, aging has been subject of frequent research, and therefore multiple strategies have been proposed to quantify the advance of the years based on the known physiology of human senescence. For several decades, attempts have been made to characterize these changes through the concept of biological age, which aims to integrate, in a measure of time, structural or functional variation through biomarkers in comparison with simple chronological age. The objective of this scoping review is to deepen the updated concept of measuring biological age composed of biomarkers in the general population and to summarize recent evidence to identify gaps and priorities for future research. Methods: A scoping review was conducted according to the five-phase methodology developed by Arksey and O'Malley through a search of five bibliographic databases to February 2021. Original articles were included with no time or language limit that described the biological age composed of at least two biomarkers in those over 18 years of age. Results: 674 articles were identified, of which 105 were evaluated for eligibility and 65 were included with information on the measurement of biological age composed of biomarkers. Articles from 1974 of 15 nationalities were found, most observational studies, in which clinical or paraclinical biomarkers were used, and 11 different methods described for the calculation of the composite biological age were informed. The outcomes reported were the relationship with the same measured biomarkers, specified risk factors, comorbidities, physical or cognitive functionality, and mortality. Conclusions: The concept of biological age composed of biomarkers has evolved since the 1970s and multiple methods of its quantification have been described through the combination of different clinical and paraclinical variables from observational studies. Future research should consider the population characteristics, and the choice of biomarkers against the proposed outcomes to improve the understanding of aging variables to direct effective strategies for a proper approach.Keywords: biological age, biological aging, aging, senescence, biomarker
Procedia PDF Downloads 186258 Extraction of Forest Plantation Resources in Selected Forest of San Manuel, Pangasinan, Philippines Using LiDAR Data for Forest Status Assessment
Authors: Mark Joseph Quinto, Roan Beronilla, Guiller Damian, Eliza Camaso, Ronaldo Alberto
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Forest inventories are essential to assess the composition, structure and distribution of forest vegetation that can be used as baseline information for management decisions. Classical forest inventory is labor intensive and time-consuming and sometimes even dangerous. The use of Light Detection and Ranging (LiDAR) in forest inventory would improve and overcome these restrictions. This study was conducted to determine the possibility of using LiDAR derived data in extracting high accuracy forest biophysical parameters and as a non-destructive method for forest status analysis of San Manual, Pangasinan. Forest resources extraction was carried out using LAS tools, GIS, Envi and .bat scripts with the available LiDAR data. The process includes the generation of derivatives such as Digital Terrain Model (DTM), Canopy Height Model (CHM) and Canopy Cover Model (CCM) in .bat scripts followed by the generation of 17 composite bands to be used in the extraction of forest classification covers using ENVI 4.8 and GIS software. The Diameter in Breast Height (DBH), Above Ground Biomass (AGB) and Carbon Stock (CS) were estimated for each classified forest cover and Tree Count Extraction was carried out using GIS. Subsequently, field validation was conducted for accuracy assessment. Results showed that the forest of San Manuel has 73% Forest Cover, which is relatively much higher as compared to the 10% canopy cover requirement. On the extracted canopy height, 80% of the tree’s height ranges from 12 m to 17 m. CS of the three forest covers based on the AGB were: 20819.59 kg/20x20 m for closed broadleaf, 8609.82 kg/20x20 m for broadleaf plantation and 15545.57 kg/20x20m for open broadleaf. Average tree counts for the tree forest plantation was 413 trees/ha. As such, the forest of San Manuel has high percent forest cover and high CS.Keywords: carbon stock, forest inventory, LiDAR, tree count
Procedia PDF Downloads 388257 Evaluation of Green Logistics Performance: An Application of Analytic Hierarchy Process Method for Ranking Environmental Indicators
Authors: Eduarda Dutra De Souza, Gabriela Hammes, Marina Bouzon, Carlos M. Taboada Rodriguez
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The search for minimizing harmful impacts on the environment has become the focus of global society, affecting mainly how to manage organizations. Thus, companies have sought to transform their activities into environmentally friendly initiatives by applying green practices throughout their supply chains. In the logistics domain, the implementation of environmentally sound practices is still in its infancy in emerging countries such as Brazil. Given the need to reduce these environmental damages, this study aims to evaluate the performance of green logistics (GL) in the plastics industry sector in order to help to improve environmental performance within organizations and reduce the impact caused by their activities. The performance tool was based on theoretical research and the use of experts in the field. The Analytic Hierarchy Process (AHP) was used to prioritize green practices and assign weight to the indicators contained in the proposed tool. The tool also allows the co-production of a single indicator. The developed tool was applied in an industry of the plastic packaging sector. However, this tool may be applied in different industry sectors, and it is adaptable to different sizes of companies. Besides the contributions to the literature, this work also presents future paths of research in the field of green logistics.Keywords: AHP, green logistics, green supply chain, performance evaluation
Procedia PDF Downloads 159256 Effect of Plastic Deformation on the Carbide-Free Bainite Transformation in Medium C-Si Steel
Authors: Mufath Zorgani, Carlos Garcia-Mateo, Mohammad Jahazi
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In this study, the influence of pre-strained austenite on the extent of isothermal bainite transformation in medium-carbon, high-silicon steel was investigated. Different amounts of deformations were applied at 600°C on the austenite right before quenching to the region, where isothermal bainitic transformation is activated. Four different temperatures of 325, 350, 375, and 400°C considering similar holding time 1800s at each temperature, were selected to investigate the extent of isothermal bainitic transformation. The results showed that the deformation-free austenite transforms to the higher volume fraction of CFB bainite when the isothermal transformation temperature reduced from 400 to 325°C, the introduction of plastic deformation in austenite prior to the formation of bainite invariably involves a delay of the same or identical isothermal treatment. On the other side, when the isothermal transformation temperature and deformation increases, the volume fraction and the plate thickness of bainite decreases and the amount of retained austenite increases. The shape of retained austenite is mostly representing blocky-shape one due to the less amount of transformed bainite. Moreover, the plate-like shape bainite cannot be resolved when the deformation amount reached 30%, and the isothermal transformation temperatures are of 375 and 400°C. The amount of retained austenite and the percentage of its transformation to martensite during the final cooling stage play a significant role in the variation of hardness level for different thermomechanical regimes.Keywords: ausforming, carbide free bainite, dilatometry, microstructure
Procedia PDF Downloads 128255 Species Selection for Phytoremediation of Barium Polluted Flooded Soils
Authors: Fabio R. Pires, Paulo R. C. C. Ribeiro, Douglas G. Viana, Robson Bonomo, Fernando B. Egreja Filho, Alberto Cargnelutti Filho, Luiz F. Martins, Leila B. S. Cruz, Mauro C. P. Nascimento
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The use of barite (BaSO₄) as a weighting agent in drilling fluids for oil and gas activities makes barium a potential contaminant in the case of spills onto flooded soils, where barium sulfate solubility is increased due to low redox conditions. In order to select plants able to remove barium in such scenarios, seven plant species were evaluated on barium phytoextraction capacity: Brachiaria arrecta; Cyperus cf. papyrus; Eleocharis acutangula; Eleocharis interstincta; Nephrolepsis cf. rivularis; Paspalum conspersum and Typha domingensis. Plants were grown in pots with 13 kg of soil each, and exposed to six barium concentrations (established with BaCl₂): 0; 2.5; 5.0; 10.0; 30.0; 65.0 mg kg-1. To simulate flooding conditions, every pot was manteined with a thin irrigation water depth over soil surface (~1.0 cm). Treatments were carried out in triplicate, and pots were distributed randomly inside the greenhouse. Biometric and chemical analyses were performed throughout the experiment, including Ba²⁺ accumulation in shoots and roots. The highest amount of barium was observed in T. domingensis biomass, followed by C. cf. papyrus. However, the latter exported most of the barium to shoot, especially in higher BaCl₂ doses, while the former accumulated barium preferentially in roots. Thus, barium removal with C. cf. papyrus could be achieved by simply harvesting aerial biomass. The amount of barium in C. cf. papyrus was a consequence of high biomass production rather than barium concentration in plant tissues, whereas T. domingensis showed high barium concentration in plant tissues and high biomass production as well. These results make T. domingensis and C. cf. papyrus potential candidates to be applied in phytoremediation schemes to remove barium from flooded soils.Keywords: barium sulfate, cyperus, drilling fluids, phytoextraction, Typha
Procedia PDF Downloads 271254 Classification of Factors Influencing Buyer-Supplier Relationship: A Case Study from the Cement Industry
Authors: Alberto Piatto, Zaza Nadja Lee Hansen, Peter Jacobsen
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This paper examines the quantitative and qualitative factors influencing the buyer-supplier relationship. Understanding and acting on the right factors influencing supplier relationship management is crucial when a company outsource an important part of its business as it can be for engineering to order (ETO) company executing only the designing part in-house. Acting on these factors increase the quality of the relationship obtaining for both parties what they want and expect from an improved relationship. Best practices in supplier relationship management are considered and a case study of a large global company, called Cement A/S, operating in the cement business is carried out. One study is conducted including a large international company and hundreds of its suppliers. Data from the company is collected using semi-structured interviews and data from the suppliers is collected using a survey. Based on these inputs and an extensive literature review a classification of factors influencing the relationship buyer-supplier is presented and discussed. The results show that different managers among the company are assessing supplier from various perspectives, a standard approach to measure the performance of suppliers does not exist. The factors used nowadays in the company to measure performances of the suppliers are mostly related to time and cost. Quality is a key factor, but it has not been addressed properly since no data are available in the system. From a practical perspective, managers can learn from this paper which factors to consider when applying best practices of Supplier Relationship Management. Furthermore, from a theoretical perspective, this paper contributes with new knowledge in the area as limited research in collaboration with the company has been conducted. For this reason, a company, its suppliers and few studies for this type of industry have been conducted. For further research, it is suggested to define the correlation of factors to the profitability of the company and calculate its impact. When conducting this analysis it is important to focus on the efficient and effective use of factors that can be measurable and accepted from the supplier.Keywords: buyer-supplier relationship, cement industry, classification of factors, ETO
Procedia PDF Downloads 282253 Assessing Innovation Activity in Mexico and South Korea: An Econometric Approach
Authors: Mario Gómez, Won Ho Kim, Ángel Licona, José Carlos Rodríguez
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This article analyzes innovation activity in Mexico and South Korea. It develops an econometric model to test for structural breaks in the number of patent applications filed by residents and nonresidents in these countries during the period of 1965 to 2012. These changes may suggest that firms’ innovative capabilities have changed because of implementing different science, technology and innovation (STI) policies in Mexico and South Korea. Two important features characterize this research from others already developed by these authors. First, the theoretical research framework in this research is the debate between the assimilation view of growth and the accumulation view of growth. This characteristic suggests that trade liberalization should be accompanied by an adequate STI policy to boost competitiveness among indigenous firms. Second, the analysis in this research stresses the importance of key actors (e.g. governments) to successfully develop innovation capabilities among indigenous firms. Therefore, the question conducting this research is how STI policies in Mexico and South Korea contributed to develop firms’ innovation capabilities in these countries during last decades? The results from this research suggests that STI policy in South Korea was more suitable to boost innovation firms to compete in markets. Data to develop this research was released by the World Intellectual Property Organization (WIPO).Keywords: innovation, Mexico, South Korea, science, technology and innovation policy
Procedia PDF Downloads 204252 Characterization of Shiga Toxin Escherichia coli Recovered from a Beef Processing Facility within Southern Ontario and Comparative Performance of Molecular Diagnostic Platforms
Authors: Jessica C. Bannon, Cleso M. Jordao Jr., Mohammad Melebari, Carlos Leon-Velarde, Roger Johnson, Keith Warriner
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There has been an increased incidence of non-O157 Shiga Toxin Escherichia coli (STEC) with six serotypes (Top 6) being implicated in causing haemolytic uremic syndrome (HUS). Beef has been suggested to be a significant vehicle for non-O157 STEC although conclusive evidence has yet to be obtained. The following aimed to determine the prevalence of the Top 6 non-O157 STEC in beef processing using three different diagnostic platforms then characterize the recovered isolates. Hide, carcass and environmental swab samples (n = 60) were collected from a beef processing facility over a 12 month period. Enriched samples were screened using Biocontrol GDS, BAX or PALLgene molecular diagnostic tests. Presumptive non-O157 STEC positive samples were confirmed using conventional PCR and serology. STEC was detected by GDS (55% positive), BAX (85% positive), and PALLgene (93%). However, during confirmation testing only 8 of the 60 samples (13%) were found to harbour STEC. Interestingly, the presence of virulence factors in the recovered isolates was unstable and readily lost during subsequent sub-culturing. There is a low prevalence of Top 6 non-O157 STEC associated with beef although other serotypes are encountered. Yet, the instability of the virulence factors in recovered strains would question their clinical relevance.Keywords: beef, food microbiology, shiga toxin, STEC
Procedia PDF Downloads 461251 Methodology of Preliminary Design and Performance of a Axial-Flow Fan through CFD
Authors: Ramiro Gustavo Ramirez Camacho, Waldir De Oliveira, Eraldo Cruz Dos Santos, Edna Raimunda Da Silva, Tania Marie Arispe Angulo, Carlos Eduardo Alves Da Costa, Tânia Cristina Alves Dos Reis
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It presents a preliminary design methodology of an axial fan based on the lift wing theory and the potential vortex hypothesis. The literature considers a study of acoustic and engineering expertise to model a fan with low noise. Axial fans with inadequate intake geometry, often suffer poor condition of the flow at the entrance, varying from velocity profiles spatially asymmetric to swirl floating with respect to time, this produces random forces acting on the blades. This produces broadband gust noise which in most cases triggers the tonal noise. The analysis of the axial flow fan will be conducted for the solution of the Navier-Stokes equations and models of turbulence in steady and transitory (RANS - URANS) 3-D, in order to find an efficient aerodynamic design, with low noise and suitable for industrial installation. Therefore, the process will require the use of computational optimization methods, aerodynamic design methodologies, and numerical methods as CFD- Computational Fluid Dynamics. The objective is the development of the methodology of the construction axial fan, provide of design the geometry of the blade, and evaluate aerodynamic performanceKeywords: Axial fan design, CFD, Preliminary Design, Optimization
Procedia PDF Downloads 395250 Effective Validation Model and Use of Mobile-Health Apps for Elderly People
Authors: Leonardo Ramirez Lopez, Edward Guillen Pinto, Carlos Ramos Linares
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The controversy brought about by the increasing use of mHealth apps and their effectiveness for disease prevention and diagnosis calls for immediate control. Although a critical topic in research areas such as medicine, engineering, economics, among others, this issue lacks reliable implementation models. However, projects such as Open Web Application Security Project (OWASP) and various studies have helped to create useful and reliable apps. This research is conducted under a quality model to optimize two mHealth apps for older adults. Results analysis on the use of two physical activity monitoring apps - AcTiv (physical activity) and SMCa (energy expenditure) - is positive and ideal. Through a theoretical and practical analysis, precision calculations and personal information control of older adults for disease prevention and diagnosis were performed. Finally, apps are validated by a physician and, as a result, they may be used as health monitoring tools in physical performance centers or any other physical activity. The results obtained provide an effective validation model for this type of mobile apps, which, in turn, may be applied by other software developers that along with medical staff would offer digital healthcare tools for elderly people.Keywords: model, validation, effective, healthcare, elderly people, mobile app
Procedia PDF Downloads 218249 Creative Applications for Socially Assistive Robots to Support Mental Health: A Patient-Centered Feasibility Study
Authors: Andreas Kornmaaler Hansen, Carlos Gomez Cubero, Elizabeth Jochum
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The use of the arts in therapy and rehabilitation is well established, and there is growing recognition of the value of the arts for improving health and well-being across diverse populations. Combining arts with socially assistive robots is a relatively under-explored research area. This paper presents the results of a feasibility study conducted within an existing arts and health program to scope the possibility of combining visual arts with socially assistive robots to promote mental health and well-being. Using a participatory research design with participant-led perspectives, we present the results of our feasibility study with a collaborative drawing robot among an adult population with mild to severe mental illness. We identify key methodological challenges and advantages of working with participatory and human-centered approaches. Based on the results of three pilot workshops with participants and lay health workers, we outline suggestions for authentic engagement with real stakeholders toward the development of socially assistive robots in community health contexts. Working closely with a patient population at all levels of the research process is key for developing tools and interventions that center patient experience and priorities while minimizing the risks of alienating patients and communities.Keywords: arts and health, visual art, health promotion, mental health, collaborative robots, creativity, socially assistive robots
Procedia PDF Downloads 64248 Emotional Skills and Musical Performance in the Elementary Music Education in Conservatoires: An Exploratory Study
Authors: Emilia A. Campayo-Munoz, Alberto Cabedo-Mas
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Music students have to face the challenges of musical practice -such as discipline in study, competitiveness, or performance anxiety- that require good emotional management to enable successful performance. However, few rigorous implementations focused on studying the influence of emotional skills in student's musical performance. Responding to this gap in the literature, this study aims to explore the relationship between emotional skills and musical performance in the context of elementary music education in conservatoires. Given the individual nature of the instrumental studies and the difficult availability of teachers to be trained in emotional education, it was decided to conduct a multiple case study in a Spanish music conservatoire. Author 1 carried out the implementation of the research with three 10-year-old students who were selected from her piano class. All of them attended the third year of their piano studies. The research processes consisted of the implementation of a set of specific and cross-sectional activities designed 'ad hoc' to be articulated in the subjects of individual instrument -piano- and ensemble in parallel to the contents of musical nature. The CE-360º questionnaire was used to measure different aspects of the students' emotional skills from a multi-angle perspective, each of the questionnaires being responded by oneself, three teachers and three peers, before and after the implementation. The data from the questionnaire were compared with the grades that the students obtained during the first and last quarter of the school year in the attended subjects. Acknowledging the complexity of emotional development, the results indicate possible relations between emotional skills and musical performance in music education in conservatoires. The results show that for the cases explored; there exists a relationship between emotional skills and musical performance. Although generalizations cannot be made, this study reinforces the need to further explore emotional development in instrumental teaching and suggest the importance of inviting teachers to reflect on the pedagogical practices extended in the conservatoires and to develop and implement those that promote the work of the students' emotions.Keywords: conservatoires, emotional skills, music education, musical performance
Procedia PDF Downloads 244247 Kinetic Study of the Esterification of Unsaturated Fatty Acids from Salmon Oil (Salmosalar L.)
Authors: André Luis Lima de Oliveira, Vera Lúcia Viana do Nascimento, Victória Maura Silva Bermudez, Mauricio Nunes Kleinberg, João Carlos da Costa Assunção, José Osvaldo Beserra Carioca
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The objective of this study was to synthesize a triglyceride with high content of unsaturated fatty acids from salmon oil (Salmo salar L.) by esterification with glycerol catalyzed dealuminized zeolite. A kinetic study was conducted to determine the reaction order and the activation energy. A statistical study was conducted to determine optimal reaction conditions. Initially, the crude oil was refined salmon physically and chemically. The crude oil was hydrolyzed and unsaturated free fatty acids were separated by urea complexation method. An experimental project to verify the parameters (temperature, glycerin and catalyst) with the greatest impact on the reaction was developed. In experiments aliquots were taken at predetermined times to measure the amount of free fatty acids. Pareto, surface, contour and hub graphs were used to determine the factors that maximized the reaction. According to the graphs the best reaction conditions were: temperature 80 ° C, the proportion glycerine/oil 5: 1 and 1% of catalyst. The kinetic data showed that the system was compatible with a second-order reaction. After analyzing the rate constant versus temperature charts a value of 85.31 kJ/mol was obtained for the reaction activation energy.Keywords: esterification, kinect, oil, salmon
Procedia PDF Downloads 521246 Autonomous Kuka Youbot Navigation Based on Machine Learning and Path Planning
Authors: Carlos Gordon, Patricio Encalada, Henry Lema, Diego Leon, Dennis Chicaiza
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The following work presents a proposal of autonomous navigation of mobile robots implemented in an omnidirectional robot Kuka Youbot. We have been able to perform the integration of robotic operative system (ROS) and machine learning algorithms. ROS mainly provides two distributions; ROS hydro and ROS Kinect. ROS hydro allows managing the nodes of odometry, kinematics, and path planning with statistical and probabilistic, global and local algorithms based on Adaptive Monte Carlo Localization (AMCL) and Dijkstra. Meanwhile, ROS Kinect is responsible for the detection block of dynamic objects which can be in the points of the planned trajectory obstructing the path of Kuka Youbot. The detection is managed by artificial vision module under a trained neural network based on the single shot multibox detector system (SSD), where the main dynamic objects for detection are human beings and domestic animals among other objects. When the objects are detected, the system modifies the trajectory or wait for the decision of the dynamic obstacle. Finally, the obstacles are skipped from the planned trajectory, and the Kuka Youbot can reach its goal thanks to the machine learning algorithms.Keywords: autonomous navigation, machine learning, path planning, robotic operative system, open source computer vision library
Procedia PDF Downloads 177245 The Effect of Internal Electrical Ion Mobility on Molten Salts through Atomistic Simulations
Authors: Carlos F. Sanz-Navarro, Sonia Fereres
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Binary and ternary mixtures of molten salts are excellent thermal energy storage systems and have been widely used in commercial tanks both in nuclear and solar thermal applications. However, the energy density of the commercially used mixtures is still insufficient, and therefore, new systems based on latent heat storage (or phase change materials, PCM) are currently being investigated. In order to shed some light on the macroscopic physical properties of the molten salt phases, knowledge of the microscopic structure and dynamics is required. Several molecular dynamics (MD) simulations have been performed to model the thermal behavior of (Li,K)2CO3 mixtures. Up to this date, this particular molten salt mixture has not been extensively studied but it is of fundamental interest for understanding the behavior of other commercial salts. Molten salt diffusivities, the internal electrical ion mobility, and the physical properties of the solid-liquid phase transition have been calculated and compared to available data from literature. The effect of anion polarization and the application of a strong external electric field have also been investigated. The influence of electrical ion mobility on local composition is explained through the Chemla effect, well known in electrochemistry. These results open a new way to design optimal high temperature energy storage materials.Keywords: atomistic simulations, thermal storage, latent heat, molten salt, ion mobility
Procedia PDF Downloads 326244 Analyzing the Performance of Machine Learning Models to Predict Alzheimer's Disease and its Stages Addressing Missing Value Problem
Authors: Carlos Theran, Yohn Parra Bautista, Victor Adankai, Richard Alo, Jimwi Liu, Clement G. Yedjou
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Alzheimer's disease (AD) is a neurodegenerative disorder primarily characterized by deteriorating cognitive functions. AD has gained relevant attention in the last decade. An estimated 24 million people worldwide suffered from this disease by 2011. In 2016 an estimated 40 million were diagnosed with AD, and for 2050 is expected to reach 131 million people affected by AD. Therefore, detecting and confirming AD at its different stages is a priority for medical practices to provide adequate and accurate treatments. Recently, Machine Learning (ML) models have been used to study AD's stages handling missing values in multiclass, focusing on the delineation of Early Mild Cognitive Impairment (EMCI), Late Mild Cognitive Impairment (LMCI), and normal cognitive (CN). But, to our best knowledge, robust performance information of these models and the missing data analysis has not been presented in the literature. In this paper, we propose studying the performance of five different machine learning models for AD's stages multiclass prediction in terms of accuracy, precision, and F1-score. Also, the analysis of three imputation methods to handle the missing value problem is presented. A framework that integrates ML model for AD's stages multiclass prediction is proposed, performing an average accuracy of 84%.Keywords: alzheimer's disease, missing value, machine learning, performance evaluation
Procedia PDF Downloads 250243 Advantages of Neural Network Based Air Data Estimation for Unmanned Aerial Vehicles
Authors: Angelo Lerro, Manuela Battipede, Piero Gili, Alberto Brandl
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Redundancy requirements for UAV (Unmanned Aerial Vehicle) are hardly faced due to the generally restricted amount of available space and allowable weight for the aircraft systems, limiting their exploitation. Essential equipment as the Air Data, Attitude and Heading Reference Systems (ADAHRS) require several external probes to measure significant data as the Angle of Attack or the Sideslip Angle. Previous research focused on the analysis of a patented technology named Smart-ADAHRS (Smart Air Data, Attitude and Heading Reference System) as an alternative method to obtain reliable and accurate estimates of the aerodynamic angles. This solution is based on an innovative sensor fusion algorithm implementing soft computing techniques and it allows to obtain a simplified inertial and air data system reducing external devices. In fact, only one external source of dynamic and static pressures is needed. This paper focuses on the benefits which would be gained by the implementation of this system in UAV applications. A simplification of the entire ADAHRS architecture will bring to reduce the overall cost together with improved safety performance. Smart-ADAHRS has currently reached Technology Readiness Level (TRL) 6. Real flight tests took place on ultralight aircraft equipped with a suitable Flight Test Instrumentation (FTI). The output of the algorithm using the flight test measurements demonstrates the capability for this fusion algorithm to embed in a single device multiple physical and virtual sensors. Any source of dynamic and static pressure can be integrated with this system gaining a significant improvement in terms of versatility.Keywords: aerodynamic angles, air data system, flight test, neural network, unmanned aerial vehicle, virtual sensor
Procedia PDF Downloads 221242 Out of Pocket Costs for Patients with Tuberculosis in Colombia: Evidence from Three Metropolitan Areas
Authors: Jose Hernandez, Lina Martínez, Gustavo Gonzalez, Carlos Lázaro, Diana Castrillon, Jonathan Cardona, Laura Mejía, Yina Sanchez, Luisa Ochoa, Evert Jimenez
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Objectives: Economic analyses of tuberculosis control interventions are usually focused on the payer’s perspective. To assess the overall economic impact of the disease, out-of-pocket and indirect costs are also required. This research is aimed to estimate overall economic impact under DOTS-strategy (Directly Observed Therapy Short Course). Methods: A cross-sectional survey of 91 adult tuberculosis patients in treatment for at least two months was conducted from the society perspective. A standardized questionnaire was used in three different cities of Colombia: Medellin (poverty is 17.7%), Monteria (poverty is 36.9%) and Quibdó (poverty is 51.2%). Costs were converted to 2013 USD and categorized into two periods: diagnostics phase and treatment. Results: The median cost during diagnostics was 13$ (±SD 9.5). The median monthly patient out-of-pocket costs during treatment were 32$ (±SD 6.8), equivalent to 17% of patient’s median monthly income, estimated in 186$ (±SD 23). Costs recorded in Medellin were 47$ in Monteria was 18$ and in Quibdó was 13$. Conclusion: Patient costs under DOTS strategy are high even when services are provided free of charge. The creation or strengthening of community-based treatment supervisors could greatly impact costs of tuberculosis and lower drop-outs.Keywords: tuberculosis, costs and cost analysis, health promotion, Colombia
Procedia PDF Downloads 367241 Increasing the Resilience of Cyber Physical Systems in Smart Grid Environments using Dynamic Cells
Authors: Andrea Tundis, Carlos García Cordero, Rolf Egert, Alfredo Garro, Max Mühlhäuser
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Resilience is an important system property that relies on the ability of a system to automatically recover from a degraded state so as to continue providing its services. Resilient systems have the means of detecting faults and failures with the added capability of automatically restoring their normal operations. Mastering resilience in the domain of Cyber-Physical Systems is challenging due to the interdependence of hybrid hardware and software components, along with physical limitations, laws, regulations and standards, among others. In order to overcome these challenges, this paper presents a modeling approach, based on the concept of Dynamic Cells, tailored to the management of Smart Grids. Additionally, a heuristic algorithm that works on top of the proposed modeling approach, to find resilient configurations, has been defined and implemented. More specifically, the model supports a flexible representation of Smart Grids and the algorithm is able to manage, at different abstraction levels, the resource consumption of individual grid elements on the presence of failures and faults. Finally, the proposal is evaluated in a test scenario where the effectiveness of such approach, when dealing with complex scenarios where adequate solutions are difficult to find, is shown.Keywords: cyber-physical systems, energy management, optimization, smart grids, self-healing, resilience, security
Procedia PDF Downloads 326240 Resisting Adversarial Assaults: A Model-Agnostic Autoencoder Solution
Authors: Massimo Miccoli, Luca Marangoni, Alberto Aniello Scaringi, Alessandro Marceddu, Alessandro Amicone
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The susceptibility of deep neural networks (DNNs) to adversarial manipulations is a recognized challenge within the computer vision domain. Adversarial examples, crafted by adding subtle yet malicious alterations to benign images, exploit this vulnerability. Various defense strategies have been proposed to safeguard DNNs against such attacks, stemming from diverse research hypotheses. Building upon prior work, our approach involves the utilization of autoencoder models. Autoencoders, a type of neural network, are trained to learn representations of training data and reconstruct inputs from these representations, typically minimizing reconstruction errors like mean squared error (MSE). Our autoencoder was trained on a dataset of benign examples; learning features specific to them. Consequently, when presented with significantly perturbed adversarial examples, the autoencoder exhibited high reconstruction errors. The architecture of the autoencoder was tailored to the dimensions of the images under evaluation. We considered various image sizes, constructing models differently for 256x256 and 512x512 images. Moreover, the choice of the computer vision model is crucial, as most adversarial attacks are designed with specific AI structures in mind. To mitigate this, we proposed a method to replace image-specific dimensions with a structure independent of both dimensions and neural network models, thereby enhancing robustness. Our multi-modal autoencoder reconstructs the spectral representation of images across the red-green-blue (RGB) color channels. To validate our approach, we conducted experiments using diverse datasets and subjected them to adversarial attacks using models such as ResNet50 and ViT_L_16 from the torch vision library. The autoencoder extracted features used in a classification model, resulting in an MSE (RGB) of 0.014, a classification accuracy of 97.33%, and a precision of 99%.Keywords: adversarial attacks, malicious images detector, binary classifier, multimodal transformer autoencoder
Procedia PDF Downloads 112239 Machine Learning and Metaheuristic Algorithms in Short Femoral Stem Custom Design to Reduce Stress Shielding
Authors: Isabel Moscol, Carlos J. Díaz, Ciro Rodríguez
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Hip replacement becomes necessary when a person suffers severe pain or considerable functional limitations and the best option to enhance their quality of life is through the replacement of the damaged joint. One of the main components in femoral prostheses is the stem which distributes the loads from the joint to the proximal femur. To preserve more bone stock and avoid weakening of the diaphysis, a short starting stem was selected, generated from the intramedullary morphology of the patient's femur. It ensures the implantability of the design and leads to geometric delimitation for personalized optimization with machine learning (ML) and metaheuristic algorithms. The present study attempts to design a cementless short stem to make the strain deviation before and after implantation close to zero, promoting its fixation and durability. Regression models developed to estimate the percentage change of maximum principal stresses were used as objective optimization functions by the metaheuristic algorithm. The latter evaluated different geometries of the short stem with the modification of certain parameters in oblique sections from the osteotomy plane. The optimized geometry reached a global stress shielding (SS) of 18.37% with a determination factor (R²) of 0.667. The predicted results favour implantability integration in the short stem optimization to effectively reduce SS in the proximal femur.Keywords: machine learning techniques, metaheuristic algorithms, short-stem design, stress shielding, hip replacement
Procedia PDF Downloads 195238 SiO2-Ag+Chlorex vs SilverSulfaDiazine: An 'in vitro' and 'in vivo' Silver Challenge
Authors: Roberto Cassino, Valeria Dissette, Carlo Alberto Bignozzi, Daniele Pazzi
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Background and Aims: The aim of this work was to investigate, both ‘in vitro’ and ‘in vivo’, if the new SCX technology (SiO2-Ag+Chlorex) can easily defeat infections and it is really more effective than SSD (SilverSulfaDiazine). ‘In vitro’ methods: we tested ‘in vitro’ the effectiveness of both silver materials using a pool of 5 strains: Pseudomonas Aeruginosa, Staphylococcus aureus, Escherichia Coli, Enterococcus hirae and Candida Albicans. 100 µl of this pool have been seeded on Petri dishes and kept for 24 hours in incubation at 37 C°. ‘In vivo’ methods: we enrolled patients with multiple infectious chronic wounds (according with cutting & harding criteria for infection); after a qualitative evaluation of the wounds bacterial population, taking a sample by plug, we included in the study 6 patients for a total of 10 wounds, infected by one or more of the microorganisms used for the ‘in vitro’ test. The protocol consisted of a treatment with a spray powder of SSD every 48 hours for 14 days; in case of worsening we should have to start a new treatment with a spray powder containing silicon dioxide, ionic silver and chlorexidine (SiO2-Ag+Chlorex) every 48 hours for 14 days. We evaluated the number of clinical signs of infection and the disappearance or not of the wound edge erithema. ‘In vitro’ results: SSD demonstrated a wide zone of inhibition within 24 hours, but after 5 days there was no more signs of inhibition; on the contrary SCX had a good inhibition ring that lasted more than 5 days. ‘In vivo’ results: all wounds treated with SSD got worse; the signs of infection increased and the wound edge erithema did not disappear. According with the protocol, we treated then all wounds with SCX and they all improved within the period of observation with complete disappearance of clinical signs of infection and no more wound edge erithema. Conclusions: the study demonstrated the effectiveness of SiO2-Ag+Chlorex, especially in terms of long lasting antimicrobial action. We had the same results ‘in vitro’, so that there has been a perfect correspondence between the laboratory outcomes and the clinical ones.Keywords: chronic wounds, infections, ionic silver, SSD
Procedia PDF Downloads 334237 Automatic Early Breast Cancer Segmentation Enhancement by Image Analysis and Hough Transform
Authors: David Jurado, Carlos Ávila
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Detection of early signs of breast cancer development is crucial to quickly diagnose the disease and to define adequate treatment to increase the survival probability of the patient. Computer Aided Detection systems (CADs), along with modern data techniques such as Machine Learning (ML) and Neural Networks (NN), have shown an overall improvement in digital mammography cancer diagnosis, reducing the false positive and false negative rates becoming important tools for the diagnostic evaluations performed by specialized radiologists. However, ML and NN-based algorithms rely on datasets that might bring issues to the segmentation tasks. In the present work, an automatic segmentation and detection algorithm is described. This algorithm uses image processing techniques along with the Hough transform to automatically identify microcalcifications that are highly correlated with breast cancer development in the early stages. Along with image processing, automatic segmentation of high-contrast objects is done using edge extraction and circle Hough transform. This provides the geometrical features needed for an automatic mask design which extracts statistical features of the regions of interest. The results shown in this study prove the potential of this tool for further diagnostics and classification of mammographic images due to the low sensitivity to noisy images and low contrast mammographies.Keywords: breast cancer, segmentation, X-ray imaging, hough transform, image analysis
Procedia PDF Downloads 83236 Power Ultrasound Application on Convective Drying of Banana (Musa paradisiaca), Mango (Mangifera indica L.) and Guava (Psidium guajava L.)
Authors: Erika K. Méndez, Carlos E. Orrego, Diana L. Manrique, Juan D. Gonzalez, Doménica Vallejo
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High moisture content in fruits generates post-harvest problems such as mechanical, biochemical, microbial and physical losses. Dehydration, which is based on the reduction of water activity of the fruit, is a common option for overcoming such losses. However, regular hot air drying could affect negatively the quality properties of the fruit due to the long residence time at high temperature. Power ultrasound (US) application during the convective drying has been used as a novel method able to enhance drying rate and, consequently, to decrease drying time. In the present study, a new approach was tested to evaluate the effect of US on the drying time, the final antioxidant activity (AA) and the total polyphenol content (TPC) of banana slices (BS), mango slices (MS) and guava slices (GS). There were also studied the drying kinetics with nine different models from which water effective diffusivities (Deff) (with or without shrinkage corrections) were calculated. Compared with the corresponding control tests, US assisted drying for fruit slices showed reductions in drying time between 16.23 and 30.19%, 11.34 and 32.73%, and 19.25 and 47.51% for the MS, BS and GS respectively. Considering shrinkage effects, Deff calculated values ranged from 1.67*10-10 to 3.18*10-10 m2/s, 3.96*10-10 and 5.57*10-10 m2/s and 4.61*10-10 to 8.16*10-10 m2/s for the BS, MS and GS samples respectively. Reductions of TPC and AA (as DPPH) were observed compared with the original content in fresh fruit data in all kinds of drying assays.Keywords: banana, drying, effective diffusivity, guava, mango, ultrasound
Procedia PDF Downloads 535