Search results for: linear fractional differential equations

Authors: Ferzat Anka

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Many types of problems can be solved using traditional analytical methods. However, these methods take a long time and cause inefficient use of resources. In particular, different approaches may be required in solving complex and global engineering problems that we frequently encounter in real life. The bigger and more complex a problem, the harder it is to solve. Such problems are called Nondeterministic Polynomial time (NP-hard) in the literature. The main reasons for recommending different metaheuristic algorithms for various problems are the use of simple concepts, the use of simple mathematical equations and structures, the use of non-derivative mechanisms, the avoidance of local optima, and their fast convergence. They are also flexible, as they can be applied to different problems without very specific modifications. Thanks to these features, it can be easily embedded even in many hardware devices. Accordingly, this approach can also be used in trend application areas such as IoT, big data, and parallel structures. Indeed, the metaheuristic approaches are algorithms that return near-optimal results for solving large-scale optimization problems. This study is focused on the new metaheuristic method that has been merged with the chaotic approach. It is based on the chaos theorem and helps relevant algorithms to improve the diversity of the population and fast convergence. This approach is based on Chimp Optimization Algorithm (ChOA), that is a recently introduced metaheuristic algorithm inspired by nature. This algorithm identified four types of chimpanzee groups: attacker, barrier, chaser, and driver, and proposed a suitable mathematical model for them based on the various intelligence and sexual motivations of chimpanzees. However, this algorithm is not more successful in the convergence rate and escaping of the local optimum trap in solving high-dimensional problems. Although it and some of its variants use some strategies to overcome these problems, it is observed that it is not sufficient. Therefore, in this study, a newly expanded variant is described. In the algorithm called Ex-ChOA, hybrid models are proposed for position updates of search agents, and a dynamic switching mechanism is provided for transition phases. This flexible structure solves the slow convergence problem of ChOA and improves its accuracy in multidimensional problems. Therefore, it tries to achieve success in solving global, complex, and constrained problems. The main contribution of this study is 1) It improves the accuracy and solves the slow convergence problem of the ChOA. 2) It proposes new hybrid movement strategy models for position updates of search agents. 3) It provides success in solving global, complex, and constrained problems. 4) It provides a dynamic switching mechanism between phases. The performance of the Ex-ChOA algorithm is analyzed on a total of 8 benchmark functions, as well as a total of 2 classical and constrained engineering problems. The proposed algorithm is compared with the ChoA, and several well-known variants (Weighted-ChoA, Enhanced-ChoA) are used. In addition, an Improved algorithm from the Grey Wolf Optimizer (I-GWO) method is chosen for comparison since the working model is similar. The obtained results depict that the proposed algorithm performs better or equivalently to the compared algorithms.

Keywords: optimization, metaheuristic, chimp optimization algorithm, engineering constrained problems

Procedia PDF Downloads 53

Authors: Andreas Stollwitzer, Lara Bettinelli, Josef Fink

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The expansion of the high-speed rail network over the past decades has resulted in new challenges for engineers, including traffic-induced resonance vibrations of railway bridges. Excessive resonance-induced speed-dependent accelerations of railway bridges during high-speed traffic can lead to negative consequences such as fatigue symptoms, distortion of the track, destabilisation of the ballast bed, and potentially even derailment. A realistic prognosis of bridge vibrations during high-speed traffic must not only rely on the right choice of an adequate calculation model for both bridge and train but first and foremost on the use of dynamic model parameters which reflect reality appropriately. However, comparisons between measured and calculated bridge vibrations are often characterised by considerable discrepancies, whereas dynamic calculations overestimate the actual responses and therefore lead to uneconomical results. This gap between measurement and calculation constitutes a complex research issue and can be traced to several causes. One major cause is found in the dynamic properties of the ballasted track, more specifically in the persisting, substantial uncertainties regarding the consideration of the ballasted track (mechanical model and input parameters) in dynamic calculations. Furthermore, the discrepancy is particularly pronounced concerning the damping values of the bridge, as conservative values have to be used in the calculations due to normative specifications and lack of knowledge. By using a large-scale test facility, the analysis of the dynamic behaviour of ballasted track has been a major research topic at the Institute of Structural Engineering/Steel Construction at TU Wien in recent years. This highly specialised test facility is designed for isolated research of the ballasted track's dynamic stiffness and damping properties – independent of the bearing structure. Several mechanical models for the ballasted track consisting of one or more continuous spring-damper elements were developed based on the knowledge gained. These mechanical models can subsequently be integrated into bridge models for dynamic calculations. Furthermore, based on measurements at the test facility, model-dependent stiffness and damping parameters were determined for these mechanical models. As a result, realistic mechanical models of the railway bridge with different levels of detail and sufficiently precise characteristic values are available for bridge engineers. Besides that, this contribution also presents another practical application of such a bridge model: Based on the bridge model, determination equations for the damping factor (as Lehr's damping factor) can be derived. This approach constitutes a first-time method that makes the damping factor of a railway bridge calculable. A comparison of this mathematical approach with measured dynamic parameters of existing railway bridges illustrates, on the one hand, the apparent deviation between normatively prescribed and in-situ measured damping factors. On the other hand, it is also shown that a new approach, which makes it possible to calculate the damping factor, provides results that are close to reality and thus raises potentials for minimising the discrepancy between measurement and calculation.

Keywords: ballasted track, bridge dynamics, damping, model design, railway bridges

Procedia PDF Downloads 145

Authors: Frans J. Smit, Wisdom A. Munzeiwa, Hermanus C. M. Vosloo, Lyn-Marie Birkholtz, Richard K. Haynes

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Malaria and antimicrobial infections remain significant global health concerns, necessitating the continuous search for novel therapeutic approaches. This abstract presents an overview of the potential use of triazenes as effective agents against malaria and various antimicrobial pathogens. Triazenes are a class of compounds characterized by a linear arrangement of three nitrogen atoms, rendering them structurally distinct from their cyclic counterparts. This study investigates the efficacy of triazenes against malaria and explores their antimicrobial activity. Preliminary results revealed significant antimalarial activity of the triazenes, as evidenced by in vitro screening against P. falciparum, the causative agent of malaria. Furthermore, the compounds exhibited broad-spectrum antimicrobial activity, indicating their potential as effective antimicrobial agents. These compounds have shown inhibitory effects on various essential enzymes and processes involved in parasite survival, replication, and transmission. The mechanism of action of triazenes against malaria involves interactions with critical molecular targets, such as enzymes involved in the parasite's metabolic pathways and proteins responsible for host cell invasion. The antimicrobial activity of the triazenes against bacteria and fungi was investigated through disc diffusion screening. The antimicrobial efficacy of triazenes has been observed against both Gram-positive and Gram-negative bacteria, as well as multidrug-resistant strains, making them potential candidates for combating drug-resistant infections. Furthermore, triazenes possess favourable physicochemical properties, such as good stability, solubility, and low toxicity, which are essential for drug development. The structural versatility of triazenes allows for the modification of their chemical composition to enhance their potency, selectivity, and pharmacokinetic properties. These modifications can be tailored to target specific pathogens, increasing the potential for personalized treatment strategies. In conclusion, this study highlights the potential of triazenes as promising candidates for the development of novel antimalarial and antimicrobial therapeutics. Further investigations are necessary to determine the structure-activity relationships and optimize the pharmacological properties of these compounds. The results warrant additional research, including MIC studies, to further explore the antimicrobial activity of the triazenes. Ultimately, these findings contribute to the development of more effective strategies for combating malaria and microbial infections.

Keywords: malaria, anti-microbials, triazene, resistance

Procedia PDF Downloads 74

Authors: Sayantan Saha, Sambit Supriya Dash, Vinayak Malhotra

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Efficient propulsive systems development is an area of major interest and concern in aerospace industry. Combustion forms the most reliable and basic form of propulsion for ground and space applications. The generation of large amount of energy from a small volume relates mostly to the flaming combustion. This study deals with instabilities associated with flaming combustion. Combustion is always accompanied by acoustics be it external or internal. Chemical propulsion oriented rockets and space systems are well known to encounter acoustic instabilities. Acoustic brings in changes in inter-energy conversion and alter the reaction rates. The modified heat fluxes, owing to wall temperature, reaction rates, and non-linear heat transfer are observed. The thermoacoustic instabilities significantly result in reduced combustion efficiency leading to uncontrolled liquid rocket engine performance, serious hazards to systems, assisted testing facilities, enormous loss of resources and every year a substantial amount of money is spent to prevent them. Present work attempts to fundamentally understand the mechanisms governing the thermoacoustic combustion in liquid rocket engine using a simplified experimental setup comprising a butane cylinder and an impinging acoustic source. Rocket engine produces sound pressure level in excess of 153 Db. The RL-10 engine generates noise of 180 Db at its base. Systematic studies are carried out for varying fuel flow rates, acoustic levels and observations are made on the flames. The work is expected to yield a good physical insight into the development of acoustic devices that when coupled with the present propulsive devices could effectively enhance combustion efficiency leading to better and safer missions. The results would be utilized to develop impinging acoustic devices that impinge sound on the combustion chambers leading to stable combustion thus, improving specific fuel consumption, specific impulse, reducing emissions, enhanced performance and fire safety. The results can be effectively applied to terrestrial and space application.

Keywords: combustion instability, fire safety, improved performance, liquid rocket engines, thermoacoustics

Procedia PDF Downloads 123

Authors: Adriana Haulica

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Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

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Authors: Benjamin Mugisha Bugingo

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Healthcare staffhas been considered as asignificant pillar to the health care system. However, the contest of human resources for health in terms of the turnover of health workers in Uganda has been more distinct in the latest years. The objective of the paper, therefore, were to investigate the influence Role Human resource management functions in on employeeperformance of professional health workers in public district hospitals in Kampala. The study objectives were: to establish the effect of performance management function, financialincentives, non-financial incentives, participation, and involvement in the decision-making on the employee performance of professional health workers in public district hospitals in Kampala. The study was devised in the social exchange theory and the equity theory. This study adopted a descriptive research design using quantitative approaches. The study used a cross-sectional research design with a mixed-methods approach. With a population of 402 individuals, the study considered a sample of 252 respondents, including doctors, nurses, midwives, pharmacists, and dentists from 3 district hospitals. The study instruments entailed a questionnaire as a quantitative data collection tool and interviews and focus group discussions as qualitative data gathering tools. To analyze quantitative data, descriptive statistics were used to assess the perceived status of Human resource management functions and the magnitude of intentions to stay, and inferential statistics were used to show the effect of predictors on the outcome variable by plotting a multiple linear regression. Qualitative data were analyzed in themes and reported in narrative and verbatim quotes and were used to complement descriptive findings for a better understanding of the magnitude of the study variables. The findings of this study showed a significant and positive effect of performance management function, financialincentives, non-financial incentives, and participation and involvement in decision-making on employee performance of professional health workers in public district hospitals in Kampala. This study is expected to be a major contributor for the improvement of the health system in the country and other similar settings as it has provided the insights for strategic orientation in the area of human resources for health, especially for enhanced employee performance in relation with the integrated human resource management approach

Keywords: human resource functions, employee performance, employee wellness, profecial workers

Procedia PDF Downloads 67

Authors: Iñaki Iturria, Pasquale Russo, Montserrat Nacher-Vázquez, Giuseppe Spano, Paloma López, Miguel Angel Pardo

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Introduction: It is known that some Lactic Acid Bacteria (LAB) present an interesting probiotic effect. Probiotic bacteria stimulate host resistance to microbial pathogens and thereby aid in immune response, and modulate the host's immune responses to antigens with a potential to down-regulate hypersensitivity reactions. Therefore, probiotic therapy is valuable against intestinal infections and may be beneficial in the treatment of Inflammatory Bowel Disease (IBD). Several in vitro tests are available to evaluate the probiotic potential of a LAB strain. However, an in vivo model is required to understand the interaction between the host immune system and the bacteria. During the last few years, zebrafish (Danio rerio) has gained interest as a promising vertebrate model in this field. This organism has been extensively used to study the interaction between the host and the microbiota, as well as the host immune response under several microbial infections. In this work, we report on the use of the zebrafish model to investigate in vivo the colonizing ability and the immunomodulatory effect of probiotic LAB. Methods: Lactobacillus strains belonging to different LAB species were fluorescently tagged and used to colonize germ-free zebrafish larvae gastrointestinal tract (GIT). Some of the strains had a well-documented probiotic effect (L. acidophilus LA5); while others presented an exopolysaccharide (EPS) producing phenotype, thus allowing evaluating the influence of EPS in the colonization and immunomodulatory effect. Bacteria colonization was monitored for 72 h by direct observation in real time using fluorescent microscopy. CFU count per larva was also evaluated at different times. The immunomodulatory effect was assessed analysing the differential expression of several innate immune system genes (MyD88, NF-κB, Tlr4, Il1β and Il10) by qRT- PCR. The anti-inflammatory effect was evaluated using a chemical enterocolitis zebrafish model. The protective effect against a pathogen was also studied. To that end, a challenge test was developed using a fluorescently tagged pathogen (Vibrio anguillarum-GFP+). The progression of the infection was monitored up to 3 days using a fluorescent stereomicroscope. Mortality rates and CFU counts were also registered. Results and conclusions: Larvae exposed to EPS-producing bacteria showed a higher fluorescence and CFU count than those colonized with no-EPS phenotype LAB. In the same way, qRT-PCR results revealed an immunomodulatory effect on the host after the administration of the strains with probiotic activity. A downregulation of proinflammatory cytoquines as well as other cellular mediators of inflammation was observed. The anti-inflammatory effect was found to be particularly marked following exposure to LA% strain, as well as EPS producing strains. Furthermore, the challenge test revealed a protective effect of probiotic administration. As a matter of fact, larvae fed with probiotics showed a decrease in the mortality rate ranging from 20 to 35%. Discussion: In this work, we developed a promising model, based on the use of gnotobiotic zebrafish coupled with a bacterial fluorescent tagging in order to evaluate the probiotic potential of different LAB strains. We have successfully used this system to monitor in real time the colonization and persistence of exogenous LAB within the gut of zebrafish larvae, to evaluate their immunomodulatory effect and for in vivo competition assays. This approach could bring further insights into the complex microbial-host interactions at intestinal level.

Keywords: gnotobiotic, immune system, lactic acid bacteria, probiotics, zebrafish

Procedia PDF Downloads 299

Authors: Chyong-Ru Liu, Wen-Shiung Huang, Wan-Ching Tang, Shan-Pei Chen

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Two of the biggest challenges companies involved in sports and exercise information services face are how to strengthen participation in virtual sports/exercise communities and how to increase the ongoing participatoriness of those communities. In the past, relatively little research has explored mechanisms for strengthening alignment practice and community response from the perspective of self-construal, and as such this study seeks to explore the self-construal of virtual sports/exercise communities, the role it plays in the emotional commitment of forming communities, and the factor that can strengthen alignment practice. Moreover, which factor of the emotional commitment of forming virtual communities have the effect of strengthening interference in the process of transforming customer citizenship behaviors? This study collected 625 responses from the two leading websites in terms of fan numbers in the provision of information on road race and marathon events in Taiwan, with model testing conducted through linear structural equation modelling and the bootstrapping technique to test the proposed hypotheses. The results proved independent construal had a stronger positive direct effect on affective commitment to fellow customers than did interdependent construal, and the influences of affective commitment to fellow customers in enhancing customer citizenship behavior. Public self-consciousness moderates the relationships among independent self-construal and interdependent self-construal on effective commitment to fellow customers. Perceived playfulness moderates the relationships between effective commitment to fellow customers and customer citizenship behavior. The findings of this study provide significant insights for the researchers and related organizations. From the theoretical perspective, this is empirical research that investigated the self-construal theory and responses (i.e., affective commitment to fellow customers, customer citizenship behavior) in virtual sports/exercise communities. We further explore how to govern virtual sports/exercise community participants’ heterogeneity through public self-consciousness mechanism to align participants’ affective commitment. Moreover, perceived playfulness has the effect of strengthening effective commitment to fellow customers with customer citizenship behaviors. The results of this study can provide a foundation for the construction of future theories and can be provided to related organizations for reference in their planning of virtual communities.

Keywords: self-construal theory, public self-consciousness, affective commitment, customer citizenship behavior

Procedia PDF Downloads 80

Authors: Hamed Kalhori, Lin Ye

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In this study, an inverse method was developed to reconstruct the magnitude and duration of impact forces exerted to a rectangular carbon fibre-epoxy composite honeycomb sandwich panel. The dynamic signals captured by Piezoelectric (PZT) sensors installed on the panel remotely from the impact locations were utilized to reconstruct the impact force generated by an instrumented hammer through an extended deconvolution approach. Two discretized forms of convolution integral are considered; the traditional one with an explicit transfer function and the modified one without an explicit transfer function. Deconvolution, usually applied to reconstruct the time history (e.g. magnitude) of a stochastic force at a defined location, is extended to identify both the location and magnitude of the impact force among a number of potential impact locations. It is assumed that a number of impact forces are simultaneously exerted to all potential locations, but the magnitude of all forces except one is zero, implicating that the impact occurs only at one location. The extended deconvolution is then applied to determine the magnitude as well as location (among the potential ones), incorporating the linear superposition of responses resulted from impact at each potential location. The problem can be categorized into under-determined (the number of sensors is less than that of impact locations), even-determined (the number of sensors equals that of impact locations), or over-determined (the number of sensors is greater than that of impact locations) cases. For an under-determined case, it comprises three potential impact locations and one PZT sensor for the rectangular carbon fibre-epoxy composite honeycomb sandwich panel. Assessments are conducted to evaluate the factors affecting the precision of the reconstructed force. Truncated Singular Value Decomposition (TSVD) and the Tikhonov regularization are independently chosen to regularize the problem to find the most suitable method for this system. The selection of optimal value of the regularization parameter is investigated through L-curve and Generalized Cross Validation (GCV) methods. In addition, the effect of different width of signal windows on the reconstructed force is examined. It is observed that the impact force generated by the instrumented impact hammer is sensitive to the impact locations of the structure, having a shape from a simple half-sine to a complicated one. The accuracy of the reconstructed impact force is evaluated using the correlation co-efficient between the reconstructed force and the actual one. Based on this criterion, it is concluded that the forces reconstructed by using the extended deconvolution without an explicit transfer function together with Tikhonov regularization match well with the actual forces in terms of magnitude and duration.

Keywords: honeycomb composite panel, deconvolution, impact localization, force reconstruction

Procedia PDF Downloads 511

Authors: Arindam Chaudhuri

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Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

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Authors: B. Petrović, M. Petrović, L. Rutonjski, I. Djan, V. Ivanović

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Objective: Cardiac pacemakers are very sensitive to radiotherapy treatment from two sources: electromagnetic influence from the medical linear accelerator producing ionizing radiation- influencing electronics within the pacemaker, and the absorption of dose to the device. On the other hand, patients with cardiac pacemakers at the place of a tumor are rather rare, and single clinic hardly has experience with the management of such patients. The widely accepted international guidelines for management of radiation oncology patients recommend that these patients should be closely monitored and examined before, during and after radiotherapy treatment by cardiologist, and their device and condition followed up. The number of patients having both cancer and pacemaker, is growing every year, as both cancer incidence, as well as cardiac diseases incidence, are inevitably growing figures. Materials and methods: Female patient, age 69, was diagnozed with valvular cardiomyopathy and got implanted a pacemaker in 2005 and prosthetic mitral valve in 1993 (cancer was diagnosed in 2012). She was stable cardiologically and came to radiation therapy department with the diagnosis of right breast cancer, with the tumor in upper lateral quadrant of the right breast. Since she had all lymph nodes positive (28 in total), she had to have irradiated the supraclavicular region, as well as the breast with the tumor bed. She previously received chemotherapy, approved by the cardiologist. The patient was estimated to be with the high risk as device was within the field of irradiation, and the patient had high dependence on her pacemaker. The radiation therapy plan was conducted as 3D conformal therapy. The delineated target was breast with supraclavicular region, where the pacemaker was actually placed, with the addition of a pacemaker as organ at risk, to estimate the dose to the device and its components as recommended, and the breast. The targets received both 50 Gy in 25 fractions (where 20% of a pacemaker received 50 Gy, and 60% of a device received 40 Gy). The electrode to the heart received between 1 Gy and 50 Gy. Verification of dose planned and delivered was performed. Results: Evaluation of the patient status according to the guidelines and especially evaluation of all associated risks to the patient during treatment was done. Patient was irradiated by prescribed dose and followed up for the whole year, with no symptoms of failure of the pacemaker device during, or after treatment in follow up period. The functionality of a device was estimated to be unchanged, according to the parameters (electrode impedance and battery energy). Conclusion: Patient was closely monitored according to published guidelines during irradiation and afterwards. Pacemaker irradiated with the full dose did not show any signs of failure despite recommendations data, but in correlation with other published data.

Keywords: cardiac pacemaker, breast cancer, radiotherapy treatment planning, complications of treatment

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Authors: Narendra Akhadkar, Silvestre Cano, Christophe Gourru

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Injection-molded parts are widely used in power system protection products. One of the biggest challenges in an injection molding process is shrinkage and warpage of the molded parts. All these geometrical variations may have an adverse effect on the quality of the product, functionality, cost, and time-to-market. The situation becomes more challenging in the case of intricate shapes and in mass production using multi-cavity tools. To control the effects of shrinkage and warpage, it is very important to correctly find out the input parameters that could affect the product performance. With the advances in the computer-aided engineering (CAE), different tools are available to simulate the injection molding process. For our case study, we used the MoldFlow insight tool. Our aim is to predict the spread of the functional dimensions and geometrical variations on the part due to variations in the input parameters such as material viscosity, packing pressure, mold temperature, melt temperature, and injection speed. The input parameters may vary during batch production or due to variations in the machine process settings. To perform the accurate product assembly variation simulation, the first step is to perform an individual part variation simulation to render realistic tolerance ranges. In this article, we present a method to simulate part variations coming from the input parameters variation during batch production. The method is based on computer simulations and experimental validation using the full factorial design of experiments (DoE). The robustness of the simulation model is verified through input parameter wise sensitivity analysis study performed using simulations and experiments; all the results show a very good correlation in the material flow direction. There exists a non-linear interaction between material and the input process variables. It is observed that the parameters such as packing pressure, material, and mold temperature play an important role in spread on functional dimensions and geometrical variations. This method will allow us in the future to develop accurate/realistic virtual prototypes based on trusted simulated process variation and, therefore, increase the product quality and potentially decrease the time to market.

Keywords: correlation, molding process, tolerance, sensitivity analysis, variation simulation

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Authors: Natalia Bustos Sierra, Katrien Tersago

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It is currently proven that both extremes of temperature are associated with increased mortality and that air pollution is associated with temperature. This relationship is complex, and in countries with important seasonal variations in weather such as Belgium, some effects can appear as non-significant when the analysis is done over the entire year. We, therefore, analyzed the effect of short-term outdoor air pollution exposure on cardiovascular mortality during the warmer and colder months separately. We used daily cardiovascular deaths from acute cardiovascular diagnostics according to the International Classification of Diseases, 10th Revision (ICD-10: I20-I24, I44-I49, I50, I60-I66) during the period 2008-2013. The environmental data were population-weighted concentrations of particulates with an aerodynamic diameter less than 10 µm (PM₁₀) and less than 2.5 µm (PM₂.₅) (daily average), nitrogen dioxide (NO₂) (daily maximum of the hourly average) and ozone (O₃) (daily maximum of the 8-hour running mean). A Generalized linear model was applied adjusting for the confounding effect of season, temperature, dew point temperature, the day of the week, public holidays and the incidence of influenza-like illness (ILI) per 100,000 inhabitants. The relative risks (RR) were calculated for an increase of one interquartile range (IQR) of the air pollutant (μg/m³). These were presented for the four hottest months (June, July, August, September) and coldest months (November, December, January, February) in Belgium. We applied both individual lag model and unconstrained distributed lag model methods. The cumulative effect of a four-day exposure (day of exposure and three consecutive days) was calculated from the unconstrained distributed lag model. The IQR for PM₁₀, PM₂.₅, NO₂, and O₃ were respectively 8.2, 6.9, 12.9 and 25.5 µg/m³ during warm months and 18.8, 17.6, 18.4 and 27.8 µg/m³ during cold months. The association with CV mortality was statistically significant for the four pollutants during warm months and only for NO₂ during cold months. During the warm months, the cumulative effect of an IQR increase of ozone for the age groups 25-64, 65-84 and 85+ was 1.066 (95%CI: 1.002-1.135), 1.041 (1.008-1.075) and 1.036 (1.013-1.058) respectively. The cumulative effect of an IQR increase of NO₂ for the age group 65-84 was 1.066 (1.020-1.114) during warm months and 1.096 (1.030-1.166) during cold months. The cumulative effect of an IQR increase of PM₁₀ during warm months reached 1.046 (1.011-1.082) and 1.038 (1.015-1.063) for the age groups 65-84 and 85+ respectively. Similar results were observed for PM₂.₅. The short-term effect of air pollution on cardiovascular mortality is greater during warm months for lower pollutant concentrations compared to cold months. Spending more time outside during warm months increases population exposure to air pollution and can, therefore, be a confounding factor for this association. Age can also affect the length of time spent outdoors and the type of physical activity exercised. This study supports the deleterious effect of air pollution on cardiovascular mortality (CV) which varies according to season and age groups in Belgium. Public health measures should, therefore, be adapted to seasonality.

Keywords: air pollution, cardiovascular, mortality, season

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Authors: Gulfam Haider, sana danish

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Convolutional Neural Networks (CNNs) have emerged as powerful tools for image classification, and the choice of optimizers profoundly affects their performance. The study of optimizers and their adaptations remains a topic of significant importance in machine learning research. While numerous studies have explored and advocated for various optimizers, the efficacy of these optimization techniques is still subject to scrutiny. This work aims to address the challenges surrounding the effectiveness of optimizers by conducting a comprehensive analysis and evaluation. The primary focus of this investigation lies in examining the performance of different optimizers when employed in conjunction with the popular activation function, Rectified Linear Unit (ReLU). By incorporating ReLU, known for its favorable properties in prior research, the aim is to bolster the effectiveness of the optimizers under scrutiny. Specifically, we evaluate the adjustment of these optimizers with both the original Softmax activation function and the modified ReLU activation function, carefully assessing their impact on overall performance. To achieve this, a series of experiments are conducted using a well-established benchmark dataset for image classification tasks, namely the Canadian Institute for Advanced Research dataset (CIFAR-10). The selected optimizers for investigation encompass a range of prominent algorithms, including Adam, Root Mean Squared Propagation (RMSprop), Adaptive Learning Rate Method (Adadelta), Adaptive Gradient Algorithm (Adagrad), and Stochastic Gradient Descent (SGD). The performance analysis encompasses a comprehensive evaluation of the classification accuracy, convergence speed, and robustness of the CNN models trained with each optimizer. Through rigorous experimentation and meticulous assessment, we discern the strengths and weaknesses of the different optimization techniques, providing valuable insights into their suitability for image classification tasks. By conducting this in-depth study, we contribute to the existing body of knowledge surrounding optimizers in CNNs, shedding light on their performance characteristics for image classification. The findings gleaned from this research serve to guide researchers and practitioners in making informed decisions when selecting optimizers and activation functions, thus advancing the state-of-the-art in the field of image classification with convolutional neural networks.

Keywords: deep neural network, optimizers, RMsprop, ReLU, stochastic gradient descent

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Authors: Takuya Suzuki, Atsushi Shirai, Takashi Seki

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Acupuncture therapy is one of the treatments in traditional Chinese medicine. Recently, some reports have shown the effectiveness of acupuncture. However, its full acceptance has been hindered by the lack of understanding on mechanism of the therapy. Acupuncture applied to Zusanli (ST-36) enhances blood flow volume in superior mesenteric artery (SMA), yielding peripheral vascular resistance – regulated blood flow of SMA dominated by the parasympathetic system and inhibition of sympathetic system. In this study, a lumped-parameter approximation model of blood flow in the systemic arteries was developed. This model was extremely simple, consisting of the aorta, carotid arteries, arteries of the four limbs and SMA, and their peripheral vascular resistances. Here, the individual artery was simplified to a tapered tube and the resistances were modelled by a linear resistance. We numerically investigated contribution of the peripheral vascular resistance of SMA to the systemic blood distribution using this model. In addition to the upstream end of the model, which correlates with the left ventricle, two types of boundary condition were applied; mean left ventricular pressure which correlates with blood pressure (BP) and mean cardiac output which corresponds to cardiac index (CI). We examined it to reproduce the experimentally obtained hemodynamic change, in terms of the ratio of the aforementioned hemodynamic parameters from their initial values before the acupuncture, by regulating the peripheral vascular resistances and the upstream boundary condition. First, only the peripheral vascular resistance of SMA was changed to show contribution of the resistance to the change in blood flow volume in SMA, expecting reproduction of the experimentally obtained change. It was found, however, this was not enough to reproduce the experimental result. Then, we also changed the resistances of the other arteries together with the value given at upstream boundary. Here, the resistances of the other arteries were changed simultaneously in the same amount. Consequently, we successfully reproduced the hemodynamic change to find that regulation of the upstream boundary condition to the value experimentally obtained after the stimulation is necessary for the reproduction, though statistically significant changes in BP and CI were not observed in the experiment. It is generally known that sympathetic and parasympathetic tones take part in regulation of whole the systemic circulation including the cardiac function. The present result indicates that stimulation to ST-36 could induce vasodilation of peripheral circulation of SMA and vasoconstriction of that of other arteries. In addition, it implies that experimentally obtained small changes in BP and CI induced by the acupuncture may be involved in the therapeutic response.

Keywords: acupuncture, hemodynamics, lumped-parameter approximation, modeling, systemic vascular resistance

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Authors: T. Schmitt, J. Rosin, C. Butenweg

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Seismic design of buried pipeline systems for energy and water supply is not only important for plant and operational safety, but in particular for the maintenance of supply infrastructure after an earthquake. Past earthquakes have shown the vulnerability of pipeline systems. After the Kobe earthquake in Japan in 1995 for instance, in some regions the water supply was interrupted for almost two months. The present paper shows special issues of the seismic wave impacts on buried pipelines, describes calculation methods, proposes approaches and gives calculation examples. Buried pipelines are exposed to different effects of seismic impacts. This paper regards the effects of transient displacement differences and resulting tensions within the pipeline due to the wave propagation of the earthquake. Other effects are permanent displacements due to fault rupture displacements at the surface, soil liquefaction, landslides and seismic soil compaction. The presented model can also be used to calculate fault rupture induced displacements. Based on a three-dimensional Finite Element Model parameter studies are performed to show the influence of several parameters such as incoming wave angle, wave velocity, soil depth and selected displacement time histories. In the computer model, the interaction between the pipeline and the surrounding soil is modeled with non-linear soil springs. A propagating wave is simulated affecting the pipeline punctually independently in time and space. The resulting stresses mainly are caused by displacement differences of neighboring pipeline segments and by soil-structure interaction. The calculation examples focus on pipeline bends as the most critical parts. Special attention is given to the calculation of long-distance heat pipeline systems. Here, in regular distances expansion bends are arranged to ensure movements of the pipeline due to high temperature. Such expansion bends are usually designed with small bending radii, which in the event of an earthquake lead to high bending stresses at the cross-section of the pipeline. Therefore, Karman's elasticity factors, as well as the stress intensity factors for curved pipe sections, must be taken into account. The seismic verification of the pipeline for wave propagation in the soil can be achieved by observing normative strain criteria. Finally, an interpretation of the results and recommendations are given taking into account the most critical parameters.

Keywords: buried pipeline, earthquake, seismic impact, transient displacement

Procedia PDF Downloads 163

Authors: Yanping Liao, Zenan Wu, Ruigang Zhao

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Frequency diverse array (FDA) beamforming is a technology developed in recent years, and its antenna pattern has a unique angle-distance-dependent characteristic. However, the beam is always required to have strong concentration, high resolution and low sidelobe level to form the point-to-point interference in the concentrated set. In order to eliminate the angle-distance coupling of the traditional FDA and to make the beam energy more concentrated, this paper adopts a multi-carrier FDA structure based on proposed power exponential frequency offset to improve the array structure and frequency offset of the traditional FDA. The simulation results show that the beam pattern of the array can form a dot-shape beam with more concentrated energy, and its resolution and sidelobe level performance are improved. However, the covariance matrix of the signal in the traditional adaptive beamforming algorithm is estimated by the finite-time snapshot data. When the number of snapshots is limited, the algorithm has an underestimation problem, which leads to the estimation error of the covariance matrix to cause beam distortion, so that the output pattern cannot form a dot-shape beam. And it also has main lobe deviation and high sidelobe level problems in the case of limited snapshot. Aiming at these problems, an adaptive beamforming technique based on exponential correction for multi-carrier FDA is proposed to improve beamforming robustness. The steps are as follows: first, the beamforming of the multi-carrier FDA is formed under linear constrained minimum variance (LCMV) criteria. Then the eigenvalue decomposition of the covariance matrix is ​​performed to obtain the diagonal matrix composed of the interference subspace, the noise subspace and the corresponding eigenvalues. Finally, the correction index is introduced to exponentially correct the small eigenvalues ​​of the noise subspace, improve the divergence of small eigenvalues ​​in the noise subspace, and improve the performance of beamforming. The theoretical analysis and simulation results show that the proposed algorithm can make the multi-carrier FDA form a dot-shape beam at limited snapshots, reduce the sidelobe level, improve the robustness of beamforming, and have better performance.

Keywords: adaptive beamforming, correction index, limited snapshot, multi-carrier frequency diverse array, robust

Procedia PDF Downloads 105

Authors: Ahmed S. Fayed, Umima M. Mansour

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Three polyvinyl chloride membrane sensors were developed for the electrochemical evaluation of ferrous, manganese and zinc ions. The sensors were used for assaying metal ions in cervical mucus (CM) of Egyptian river buffalo-cows (Bubalus bubalis) as their levels vary dependent on cyclical hormone variation during different phases of estrus cycle. The presented sensors are based on using ionophores, β-cyclodextrin (β-CD), hydroxypropyl β-cyclodextrin (HP-β-CD) and sulfocalix-4-arene (SCAL) for sensors 1, 2 and 3 for Fe²⁺, Mn²⁺ and Zn²⁺, respectively. Dioctyl phthalate (DOP) was used as the plasticizer in a polymeric matrix of polyvinylchloride (PVC). For increasing the selectivity and sensitivity of the sensors, each sensor was enriched with a suitable complexing agent, which enhanced the sensor’s response. For sensor 1, β-CD was mixed with bathophenanthroline; for sensor 2, porphyrin was incorporated with HP-β-CD; while for sensor 3, oxine was the used complexing agent with SCAL. Linear responses of 10^-7-10^-2 M with cationic slopes of 53.46, 45.01 and 50.96 over pH range 4-8 were obtained using coated graphite sensors for ferrous, manganese and zinc ionic solutions, respectively. The three sensors were validated, according to the IUPAC guidelines. The obtained results by the presented potentiometric procedures were statistically analyzed and compared with those obtained by atomic absorption spectrophotometric method (AAS). No significant differences for either accuracy or precision were observed between the two techniques. Successful application for the determination of the three studied cations in CM, for the purpose to determine the proper time for artificial insemination (AI) was achieved. The results were compared with those obtained upon analyzing the samples by AAS. Proper detection of estrus and correct time of AI was necessary to maximize the production of buffaloes. In this experiment, 30 multi-parous buffalo-cows were in second to third lactation and weighting 415-530 kg, and were synchronized with OVSynch protocol. Samples were taken in three times around ovulation, on day 8 of OVSynch protocol, on day 9 (20 h before AI) and on day 10 (1 h before AI). Beside analysis of trace elements (Fe²⁺, Mn²⁺ and Zn²⁺) in CM using the three sensors, the samples were analyzed for the three cations and also Cu²⁺ by AAS in the CM samples and blood samples. The results obtained were correlated with hormonal analysis of serum samples and ultrasonography for the purpose of determining of the optimum time of AI. The results showed significant differences and powerful correlation with Zn²⁺ composition of CM during heat phase and the ovulation time, indicating that the parameter could be used as a tool to decide optimal time of AI in buffalo-cows.

Keywords: PVC Sensors, buffalo-cows, cyclodextrins, atomic absorption spectrophotometry, artificial insemination, OVSynch protocol

Procedia PDF Downloads 194

Authors: Siti Nur Syazni Mohd Zuki, Tan Ling Ling, Nina Suhaity Azmi, Chong Kwok Feng, Lee Yook Heng

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Nitrite (NO2-) ion is used prevalently as a preservative in processed meat. Elevated levels of nitrite also found in edible bird’s nests (EBNs). Consumption of NO2- ion at levels above the health-based risk may cause cancer in humans. Spectrophotometric Griess test is the simplest established standard method for NO2- ion detection, however, it requires careful control of pH of each reaction step and susceptible to strong oxidants and dyeing interferences. Other traditional methods rely on the use of laboratory-scale instruments such as GC-MS, HPLC and ion chromatography, which cannot give real-time response. Therefore, it is of significant need for devices capable of measuring nitrite concentration in-situ, rapidly and without reagents, sample pretreatment or extraction step. Herein, we constructed a microspheres-based microbial optode for visual quantitation of NO2- ion. Raoutella planticola, the bacterium expressing NAD(P)H nitrite reductase (NiR) enzyme has been successfully extracted by microbial technique from EBN collected from local birdhouse. The whole cells and the lipophilic Nile Blue chromoionophore were physically absorbed on the photocurable poly(n-butyl acrylate-N-acryloxysuccinimide) [poly (nBA-NAS)] microspheres, whilst the reduced coenzyme NAD(P)H was covalently immobilized on the succinimide-functionalized acrylic microspheres to produce a reagentless biosensing system. Upon the NiR enzyme catalyzes the oxidation of NAD(P)H to NAD(P)+, NO2- ion is reduced to ammonium hydroxide, and that a colour change from blue to pink of the immobilized Nile Blue chromoionophore is perceived as a result of deprotonation reaction increasing the local pH in the microspheres membrane. The microspheres-based optosensor was optimized with a reflectance spectrophotometer at 639 nm and pH 8. The resulting microbial bio-optode membrane could quantify NO2- ion at 0.1 ppm and had a linear response up to 400 ppm. Due to the large surface area to mass ratio of the acrylic microspheres, it allows efficient solid state diffusional mass transfer of the substrate to the bio-recognition phase, and achieve the steady state response as fast as 5 min. The proposed optical microbial biosensor requires no sample pre-treatment step and possesses high stability as the whole cell biocatalyst provides protection to the enzymes from interfering substances, hence it is suitable for measurements in contaminated samples.

Keywords: acrylic microspheres, microbial bio-optode, nitrite ion, reflectometric

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Authors: Priscila A. Bernardes, Marcos E. Buzanskas, Luciana C. A. Regitano, Ricardo V. Ventura, Danisio P. Munari

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The best linear unbiased predictor (BLUP) is a method commonly used in genetic evaluations of breeding programs. However, this approach can lead to higher inbreeding coefficients in the population due to the intensive use of few bulls with higher genetic potential, usually presenting some degree of relatedness. High levels of inbreeding are associated to low genetic viability, fertility, and performance for some economically important traits and therefore, should be constantly monitored. Unreliable pedigree data can also lead to misleading results. Genomic information (i.e., single nucleotide polymorphism – SNP) is a useful tool to estimate the inbreeding coefficient. Runs of homozygosity have been used to evaluate homozygous segments inherited due to direct or collateral inbreeding and allows inferring population selection history. This study aimed to evaluate runs of homozygosity (ROH) and inbreeding in a population of Nelore beef cattle. A total of 814 animals were genotyped with the Illumina BovineHD BeadChip and the quality control was carried out excluding SNPs located in non-autosomal regions, with unknown position, with a p-value in the Hardy-Weinberg equilibrium lower than 10⁻⁵, call rate lower than 0.98 and samples with the call rate lower than 0.90. After the quality control, 809 animals and 509,107 SNPs remained for analyses. For the ROH analysis, PLINK software was used considering segments with at least 50 SNPs with a minimum length of 1Mb in each animal. The inbreeding coefficient was calculated using the ratio between the sum of all ROH sizes and the size of the whole genome (2,548,724kb). A total of 25.711 ROH were observed, presenting mean, median, minimum, and maximum length of 3.34Mb, 2Mb, 1Mb, and 80.8Mb, respectively. The number of SNPs present in ROH segments varied from 50 to 14.954. The longest ROH length was observed in one animal, which presented a length of 634Mb (24.88% of the genome). Four bulls were among the 10 animals with the longest extension of ROH, presenting 11% of ROH with length higher than 10Mb. Segments longer than 10Mb indicate recent inbreeding. Therefore, the results indicate an intensive use of few sires in the studied data. The distribution of ROH along the chromosomes showed that chromosomes 5 and 6 presented a large number of segments when compared to other chromosomes. The mean, median, minimum, and maximum inbreeding coefficients were 5.84%, 5.40%, 0.00%, and 24.88%, respectively. Although the mean inbreeding was considered low, the ROH indicates a recent and intensive use of few sires, which should be avoided for the genetic progress of breed.

Keywords: autozygosity, Bos taurus indicus, genomic information, single nucleotide polymorphism

Procedia PDF Downloads 127

Authors: Mohammed S. Razali, Kamel Khimeche, Dahah Hichem, Ammar Boudjellal, Djamel E. Kaderi, Nourddine Ramdani

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The use of additive manufacturing technologies has revolutionized various aspects of our daily lives. In particular, 3D printing has greatly advanced biomedical applications. While fused filament fabrication (FFF) technologies have made it easy to produce or prototype various medical devices, it is crucial to minimize the risk of contamination. New materials with antibacterial properties, such as those containing compounded silver nanoparticles, have emerged on the market. In a previous study, we prepared a newly sintered seashell filler (SSh) from bio-based seashells found along the Mediterranean coast using a suitable heat treatment process. We then prepared a series of polylactic acid (PLA) and polybutylene succinate (PBS) biocomposites filled with these SSh particles using a melt mixing technique with a twin-screw extruder to use them as feedstock filaments for 3D printing. The study consisted of two parts: evaluating the antibacterial activity of newly prepared biocomposites made of PLA and PBS reinforced with a sintered seashell in the first part and experimental and modeling analysis of the non-isothermal crystallization kinetics of these biocomposites in the second part. In the first part, the bactericidal activity of the biocomposites against three different bacteria, including Gram-negative bacteria such as (E. coli and Pseudomonas aeruginosa), as well as Gram-positive bacteria such as (Staphylococcus aureus), was examined. The PLA-based biocomposite containing 20 wt.% of SSh particles exhibited an inhibition zone with radial diameters of 8mm and 6mm against E. coli and Pseudo. Au, respectively, while no bacterial activity was observed against Staphylococcus aureus. In the second part, the focus was on investigating the effect of the sintered seashell filler particles on the non-isothermal crystallization kinetics of PLA and PBS 3D-printing composite materials. The objective was to understand the impact of the filler particles on the crystallization mechanism of both PLA and PBS during the cooling process of a melt-extruded filament in (FFF) to manage the dimensional accuracy and mechanical properties of the final printed part. We conducted a non-isothermal melt crystallization kinetic study of a series of PLA-SS and PBS-SS composites using differential scanning calorimetry at various cooling rates. We analyzed the obtained kinetic data using different crystallization kinetic models such as modified Avrami, Ozawa, and Mo's methods. Dynamic mode describes the relative crystallinity as a function of temperature; it found that time half crystallinity (t1/2) of neat PLA decreased from 17 min to 7.3 min for PLA+5 SSh and the (t1/2) of virgin PBS was reduced from 3.5 min to 2.8 min for the composite containing 5wt.% of SSh. We found that the coated SS particles with stearic acid acted as nucleating agents and had a nucleation activity, as observed through polarized optical microscopy. Moreover, we evaluated the effective energy barrier of the non-isothermal crystallization process using the Iso conversional methods of Flynn-Wall-Ozawa (F-W-O) and Kissinger-Akahira-Sunose (K-A-S). The study provides significant insights into the crystallization behavior of PLA and PBS biocomposites.

Keywords: avrami model, bio-based reinforcement, dsc, gram-negative bacteria, gram-positive bacteria, isoconversional methods, non-isothermal crystallization kinetics, poly(butylene succinate), poly(lactic acid), antbactirial activity

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Authors: A. Odoom, A. Salama, H. Ibrahim

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Hydrogen is a clean source of energy for power production and transportation. The main source of hydrogen in this research is biodiesel. Glycerol also called glycerine is a by-product of biodiesel production by transesterification of vegetable oils and methanol. This is a reliable and environmentally-friendly source of hydrogen production than fossil fuels. A typical composition of crude glycerol comprises of glycerol, water, organic and inorganic salts, soap, methanol and small amounts of glycerides. Crude glycerol has limited industrial application due to its low purity thus, the usage of crude glycerol can significantly enhance the sustainability and production of biodiesel. Reforming techniques is an approach for hydrogen production mainly Steam Reforming (SR), Autothermal Reforming (ATR) and Partial Oxidation Reforming (POR). SR produces high hydrogen conversions and yield but is highly endothermic whereas POR is exothermic. On the downside, PO yields lower hydrogen as well as large amount of side reactions. ATR which is a fusion of partial oxidation reforming and steam reforming is thermally neutral because net reactor heat duty is zero. It has relatively high hydrogen yield, selectivity as well as limits coke formation. The complex chemical processes that take place during the production phases makes it relatively difficult to construct a reliable and robust numerical model. Numerical model is a tool to mimic reality and provide insight into the influence of the parameters. In this work, we introduce a finite volume numerical study for an 'in-house' lab-scale experiment of ATR. Previous numerical studies on this process have considered either using Comsol or nodal finite difference analysis. Since Comsol is a commercial package which is not readily available everywhere and lab-scale experiment can be considered well mixed in the radial direction. One spatial dimension suffices to capture the essential feature of ATR, in this work, we consider developing our own numerical approach using MATLAB. A continuum fixed bed reactor is modelled using MATLAB with both pseudo homogeneous and heterogeneous models. The drawback of nodal finite difference formulation is that it is not locally conservative which means that materials and momenta can be generated inside the domain as an artifact of the discretization. Control volume, on the other hand, is locally conservative and suites very well problems where materials are generated and consumed inside the domain. In this work, species mass balance, Darcy’s equation and energy equations are solved using operator splitting technique. Therefore, diffusion-like terms are discretized implicitly while advection-like terms are discretized explicitly. An upwind scheme is adapted for the advection term to ensure accuracy and positivity. Comparisons with the experimental data show very good agreements which build confidence in our modeling approach. The models obtained were validated and optimized for better results.

Keywords: autothermal reforming, crude glycerol, hydrogen, numerical model

Procedia PDF Downloads 120

Authors: Hannah R. Devens, Phillip L. Davidson, Dione Deaker, Kathryn E. Smith, Gregory A. Wray, Maria Byrne

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Marine invertebrate species with calcifying larvae are especially vulnerable to ocean acidification (OA) caused by rising atmospheric CO₂ levels. Acidic conditions can delay development, suppress metabolism, and decrease the availability of carbonate ions in the ocean environment for skeletogenesis. These stresses often result in increased larval mortality, which may lead to significant ecological consequences including alterations to the larval settlement, population distribution, and genetic connectivity. Importantly, many of these physiological and developmental effects are caused by genetic and molecular level changes. Although many studies have examined the effect of near-future oceanic pH levels on gene expression in marine invertebrates, little is known about the impact of OA on gene expression in a developmental context. Here, we performed mRNA-sequencing to investigate the impact of environmental acidity on gene expression across three developmental stages in the sea urchin Heliocidaris erythrogramma. We collected RNA from gastrula, early larva, and 1-day post-metamorphic juvenile sea urchins cultured at present-day and predicted future oceanic pH levels (pH 8.1 and 7.7, respectively). We assembled an annotated reference transcriptome encompassing development from egg to ten days post-metamorphosis by combining these data with datasets from two previous developmental transcriptomic studies of H. erythrogramma. Differential gene expression and time course analyses between pH conditions revealed significant alterations to developmental transcription that are potentially associated with pH stress. Consistent with previous investigations, genes involved in biomineralization and ion transport were significantly upregulated under acidic conditions. Differences in gene expression between the two pH conditions became more pronounced post-metamorphosis, suggesting a development-dependent effect of OA on gene expression. Furthermore, many differences in gene expression later in development appeared to be a result of broad downregulation at pH 7.7: of 539 genes differentially expressed at the juvenile stage, 519 of these were lower in the acidic condition. Time course comparisons between pH 8.1 and 7.7 samples also demonstrated over 500 genes were more lowly expressed in pH 7.7 samples throughout development. Of the genes exhibiting stage-dependent expression level changes, over 15% of these diverged from the expected temporal pattern of expression in the acidic condition. Through these analyses, we identify novel candidate genes involved in development, metabolism, and transcriptional regulation that are possibly affected by pH stress. Our results demonstrate that pH stress significantly alters gene expression dynamics throughout development. A large number of genes differentially expressed between pH conditions in juveniles relative to earlier stages may be attributed to the effects of acidity on transcriptional regulation, as a greater proportion of mRNA at this later stage has been nascent transcribed rather than maternally loaded. Also, the overall downregulation of many genes in the acidic condition suggests that OA-induced developmental delay manifests as suppressed mRNA expression, possibly from lower transcription rates or increased mRNA degradation in the acidic environment. Further studies will be necessary to determine in greater detail the extent of OA effects on early developing marine invertebrates.

Keywords: development, gene expression, ocean acidification, RNA-sequencing, sea urchins

Procedia PDF Downloads 130

Authors: Banu Pradheepa Kamarajan, Muthusamy Ananthasubramanian

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Biofilm forming Pseudomonads occupy the top third position in causing hospital acquired infections. P. aeruginosa is notoriously known for its tendency to develop drug resistance. Major classes of drug such as β-lactams, aminoglycosides, quinolones, and polymyxins are found ineffective against multi-drug resistance Pseudomonas. To combat the infections, rather than administration of a single antibiotic, use of combinations (tobramycin and essential oils from plants and/or silver nanoparticles, chitosan, nitric oxide, cis-2-decenoic acid) in single formulation are suggested to control P. aeruginosa biofilms. Conventional techniques to prevent hospital-acquired implant infections such as coatings with antibiotics, controlled release of antibiotics from the implant material, contact-killing surfaces, coating the implants with functional DNase I and, coating with glycoside hydrolase are being followed. Coatings with bioactive components besides having limited shelf-life, require cold-chain and, are likely to fail when bacteria develop resistance. Recently identified nano-scale physical architectures on the insect wings are expected to have potential bactericidal property. Nanopillars are bactericidal to Staphylococcus aureus, Bacillus subtilis, K. pnuemoniae and few species of Pseudomonas. Our study aims to investigate the survival rate of biofilm forming Pseudomonas aeruginosa strain over non-biofilm forming strain on the nanopillar architecture of dragonfly (Pantala flavescens) wing. Dragonflies were collected near house-hold areas and, insect identification was carried out by the Department of Entomology, Tamilnadu Agricultural University, Coimbatore, India. Two strains of P. aeruginosa such as PAO1 (potent biofilm former) and MTCC 1688 (non-weak biofilm former) were tested against the glass coverslip (control) and wings of dragonfly (test) for 48 h. The wings/glass coverslips were incubated with bacterial suspension in 48-well plate. The plates were incubated at 37 °C under static condition. Bacterial attachment on the nanopillar architecture of the wing surface was visualized using FESEM. The survival rate of P. aeruginosa was tested using colony counting technique and flow cytometry at 0.5 h, 1 h, 2 h, 7 h, 24 h, and 48 h post-incubation. Cell death was analyzed using propidium iodide staining and DNA quantification. The results indicated that the survival rate of non-biofilm forming P. aeruginosa is 0.2 %, whilst that of biofilm former is 45 % on the dragonfly wings at the end of 48 h. The reduction in the survival rate of biofilm and non-biofilm forming P. aeruginosa was 20% and 40% respectively on the wings compared to the glass coverslip. In addition, Fourier Transformed Infrared Radiation was used to study the modification in the surface chemical composition of the wing during bacterial attachment and, post-sonication. This result indicated that the chemical moieties are not involved in the bactericidal property of nanopillars by the conserved characteristic peaks of chitin pre and post-sonication. The nanopillar architecture of the dragonfly wing efficiently deters the survival of non-biofilm forming P. aeruginosa, but not the biofilm forming strain. The study highlights the ability of biofilm formers to survive on wing architecture. Understanding this survival strategy will help in designing the architecture that combats the colonization of biofilm forming pathogens.

Keywords: biofilm, nanopillars, Pseudomonas aeruginosa, survival rate

Procedia PDF Downloads 153

Authors: Gabriel Malgaresi, Sara Borazjani, Hadi Madani, Pavel Bedrikovetsky

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Suspension-Colloidal flow in porous media occurs in numerous engineering fields, such as industrial water treatment, the disposal of industrial wastes into aquifers with the propagation of contaminants and low salinity water injection into petroleum reservoirs. The main effects are particle mobilization and captured by the porous rock, which can cause pore plugging and permeability reduction which is known as formation damage. Various factors such as fluid salinity, pH, temperature, and rock properties affect particle detachment. Formation damage is unfavorable specifically near injection and production wells. One way to control formation damage is pre-treatment of the rock with nanoparticles. Adsorption of nanoparticles on fines and rock surfaces alters zeta-potential of the surfaces and enhances the attachment force between the rock and fine particles. The main objective of this study is to develop a two-stage mathematical model for (1) flow and adsorption of nanoparticles on the rock in the pre-treatment stage and (2) fines migration and permeability reduction during the water production after the pre-treatment. The model accounts for adsorption and desorption of nanoparticles, fines migration, and kinetics of particle capture. The system of equations allows for the exact solution. The non-self-similar wave-interaction problem was solved by the Method of Characteristics. The analytical model is new in two ways: First, it accounts for the specific boundary and initial condition describing the injection of nanoparticle and production from the pre-treated porous media; second, it contains the effect of nanoparticle sorption hysteresis. The derived analytical model contains explicit formulae for the concentration fronts along with pressure drop. The solution is used to determine the optimal injection concentration of nanoparticle to avoid formation damage. The mathematical model was validated via an innovative laboratory program. The laboratory study includes two sets of core-flood experiments: (1) production of water without nanoparticle pre-treatment; (2) pre-treatment of a similar core with nanoparticles followed by water production. Positively-charged Alumina nanoparticles with the average particle size of 100 nm were used for the rock pre-treatment. The core was saturated with the nanoparticles and then flushed with low salinity water; pressure drop across the core and the outlet fine concentration was monitored and used for model validation. The results of the analytical modeling showed a significant reduction in the fine outlet concentration and formation damage. This observation was in great agreement with the results of core-flood data. The exact solution accurately describes fines particle breakthroughs and evaluates the positive effect of nanoparticles in formation damage. We show that the adsorbed concentration of nanoparticle highly affects the permeability of the porous media. For the laboratory case presented, the reduction of permeability after 1 PVI production in the pre-treated scenario is 50% lower than the reference case. The main outcome of this study is to provide a validated mathematical model to evaluate the effect of nanoparticles on formation damage.

Keywords: nano-particles, formation damage, permeability, fines migration

Procedia PDF Downloads 592

Authors: Mustafa Alhamdi

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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

Procedia PDF Downloads 123

Authors: Sima Shakoorjavan, Mahdieh Eskafi, Dawid Stawski, Somaye Akbari

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In this study, poly (amidoamine) dendritic material (PAMAM) and poly (acrylic acid) (PAA) as polycation and polyanion were deposited on surface charged polylactide (PLA) nonwoven to study the relationship of dye absorption capacity of layered-PLA with the number of deposited layers. To produce negatively charged-PLA, acrylic acid (AA) was grafted on the PLA surface (PLA-g-AA) through a chemical redox reaction with the strong oxidizing agent. Spectroscopy analysis, water contact measurement, and FTIR-ATR analysis confirm the successful grafting of AA on the PLA surface through the chemical redox reaction method. In detail, an increase in dye absorption percentage by 19% and immediate absorption of water droplets ensured hydrophilicity of PLA-g-AA surface; and the presence of new carbonyl bond at 1530 cm-¹ and a wide peak of hydroxyl between 3680-3130 cm-¹ confirm AA grafting. In addition, PLA as linear polyester can undergo aminolysis, which is the cleavage of ester bonds and replacement with amid bonds when exposed to an aminolysis agent. Therefore, to produce positively charged PLA, PAMAM as amine-terminated dendritic material was introduced to PLA molecular chains at different conditions; (1) at 60 C for 0.5, 1, 1.5, 2 hours of aminolysis and (2) at room temperature (RT) for 1, 2, 3, and 4 hours of aminolysis. Weight changes and spectrophotometer measurements showed a maximum in weight gain graph and K/S value curve indicating the highest PAMAM attachment at 60 C for 1 hour and RT for 2 hours which is considered as an optimum condition. Also, the emerging new peak around 1650 cm-1 corresponding to N-H bending vibration and double wide peak at around 3670-3170 cm-1 corresponding to N-H stretching vibration confirm PAMAM attachment in selected optimum condition. In the following, regarding the initial surface charge of grafted-PLA, lbl deposition was performed and started with PAA or PAMAM. FTIR-ATR results confirm chemical changes in samples due to deposition of the first layer (PAA or PAMAM). Generally, spectroscopy analysis indicated that an increase in layer number costed dye absorption capacity. It can be due to the partial deposition of a new layer on the previously deposited layer; therefore, the available PAMAM at the first layer is more than the third layer. In detail, in the case of layer-PLA starting lbl with negatively charged, having PAMAM as the first top layer (PLA-g-AA/PAMAM) showed the highest dye absorption of both cationic and anionic model dye.

Keywords: surface modification, layer-by-layer technique, dendritic materials, PAMAM, dye absorption capacity, PLA nonwoven

Procedia PDF Downloads 61

Authors: Binger Lu

Abstract:

It remains unclear whether second language (L2) speakers could use discourse context cues to predict upcoming information as native speakers do during online comprehension. Some researchers propose that L2 learners may have a reduced ability to generate predictions during discourse processing. At the same time, there is evidence that discourse-level cues are weighed more heavily in L2 processing than in L1. Previous studies showed that L1 prediction is sensitive to the global validity of predictive cues. The current study aims to explore whether and to what extent L2 learners can dynamically and strategically adjust their prediction in accord with the global validity of predictive cues in L2 discourse comprehension as native speakers do. In a self-paced reading experiment, Chinese native speakers (N=128), C-E bilinguals (N=128), and English native speakers (N=128) read high-predictable (e.g., Jimmy felt thirsty after running. He wanted to get some water from the refrigerator.) and low-predictable (e.g., Jimmy felt sick this morning. He wanted to get some water from the refrigerator.) discourses in two-sentence frames. The global validity of predictive cues was manipulated by varying the ratio of predictable (e.g., Bill stood at the door. He opened it with the key.) and unpredictable fillers (e.g., Bill stood at the door. He opened it with the card.), such that across conditions, the predictability of the final word of the fillers ranged from 100% to 0%. The dependent variable was reading time on the critical region (the target word and the following word), analyzed with linear mixed-effects models in R. C-E bilinguals showed reliable prediction across all validity conditions (β = -35.6 ms, SE = 7.74, t = -4.601, p< .001), and Chinese native speakers showed significant effect (β = -93.5 ms, SE = 7.82, t = -11.956, p< .001) in two of the four validity conditions (namely, the High-validity and MedLow conditions, where fillers ended with predictable words in 100% and 25% cases respectively), whereas English native speakers didn’t predict at all (β = -2.78 ms, SE = 7.60, t = -.365, p = .715). There was neither main effect (χ^²(3) = .256, p = .968) nor interaction (Predictability: Background: Validity, χ^²(3) = 1.229, p = .746; Predictability: Validity, χ^²(3) = 2.520, p = .472; Background: Validity, χ^²(3) = 1.281, p = .734) of Validity with speaker groups. The results suggest that prediction occurs in L2 discourse processing but to a much less extent in L1, witha significant effect in some conditions of L1 Chinese and anull effect in L1 English processing, consistent with the view that L2 speakers are more sensitive to discourse cues compared with L1 speakers. Additionally, the pattern of L1 and L2 predictive processing was not affected by the global validity of predictive cues. C-E bilinguals’ predictive processing could be partly transferred from their L1, as prior research showed that discourse information played a more significant role in L1 Chinese processing.

Keywords: bilingualism, discourse processing, global validity, prediction, self-paced reading

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Authors: Bader Eddin Al Asali, N. Srinivasa Reddy

Abstract:

Cities are dynamic in nature and are characterized by concentration of people, infrastructure, services and markets, which offer opportunities for production and consumption. Often growth and development in urban areas is not systematic, and is directed by number of factors like natural growth, land prices, housing availability, job locations-the central business district (CBD’s), transportation routes, distribution of resources, geographical boundaries, administrative policies, etc. One sided spatial and geographical development in cities leads to the unequal spatial distribution of population and jobs, resulting in high transportation activity. City development can be measured by the parameters such as urban size, urban form, urban shape, and urban structure. Urban Size is the city size and defined by the population of the city, and urban form is the location and size of the economic activity (CBD) over the geographical space. Urban shape is the geometrical shape of the city over which the distribution of population and economic activity occupied. And Urban Structure is the transport network within which the population and activity centers are connected by hierarchy of roads. Among the urban land-use systems transportation plays significant role and is one of the largest energy consuming sector. Transportation interaction among the land uses is measured in Passenger-Km and mean trip length, and is often used as a proxy for measurement of energy consumption in transportation sector. Among the trips generated in cities, work trips constitute more than 70 percent. Work trips are originated from the place of residence and destination to the place of employment. To understand the role of urban parameters on transportation interaction, theoretical cities of different size and urban specifications are generated through building block exercise using a specially developed interactive C++ programme and land use transportation modeling is carried. The land-use transportation modeling exercise helps in understanding the role of urban parameters and also to classify the cities for their urban form, structure, and shape. Muscat the capital city of Oman underwent rapid urbanization over the last four decades is taken as a case study for its classification. Also, a pilot survey is carried to capture urban travel characteristics. Analysis of land-use transportation modeling with field data classified Muscat as a linear city with polycentric CBD. Conclusions are drawn suggestion are given for policy making for the sustainability of Muscat City.

Keywords: land-use transportation, transportation modeling urban form, urban structure, urban rule parameters

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Authors: A. B. Moldes, X. Vecino, L. Rodriguez-López, J. M. Dominguez, J. M. Cruz

Abstract:

The concept of the circular economy is focus on the importance of providing goods and services sustainably. Thus, in a future it will be necessary to respond to the environmental contamination and to the use of renewables substrates by moving to a more restorative economic system that drives towards the utilization and revalorization of residues to obtain valuable products. During its evolution our industrial economy has hardly moved through one major characteristic, established in the early days of industrialization, based on a linear model of resource consumption. However, this industrial consumption system will not be maintained during long time. On the other hand, there are many industries, like the corn milling industry, that although does not consume high amount of non renewable substrates, they produce valuable streams that treated accurately, they could provide additional, economical and environmental, benefits by the extraction of interesting commercial renewable products, that can replace some of the substances obtained by chemical synthesis, using non renewable substrates. From this point of view, the use of streams from corn milling industry to obtain surface-active compounds will decrease the utilization of non-renewables sources for obtaining this kind of compounds, contributing to a circular and global economy. However, the success of the circular economy depends on the interest of the industrial sectors in the revalorization of their streams by developing relevant and new business models. Thus, it is necessary to invest in the research of new alternatives that reduce the consumption of non-renewable substrates. In this study is proposed the utilization of a corn milling industry stream to obtain an extract with surfactant capacity. Once the biosurfactant is extracted, the corn milling stream can be commercialized as nutritional media in biotechnological process or as animal feed supplement. Usually this stream is combined with other ingredients obtaining a product namely corn gluten feed or may be sold separately as a liquid protein source for beef and dairy feeding, or as a nutritional pellet binder. Following the productive scheme proposed in this work, the corn milling industry will obtain a biosurfactant extract that could be incorporated in its productive process replacing those chemical detergents, used in some point of its productive chain, or it could be commercialized as a new product of the corn manufacture. The biosurfactants obtained from corn milling industry could replace the chemical surfactants in many formulations, and uses, and it supposes an example of the potential that many industrial streams could offer for obtaining valuable products when they are manage properly.

Keywords: biosurfactantes, circular economy, corn, sustainability

Procedia PDF Downloads 236