Search results for: nonideal complex plasma
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6095

Search results for: nonideal complex plasma

4895 N-Type GaN Thinning for Enhancing Light Extraction Efficiency in GaN-Based Thin-Film Flip-Chip Ultraviolet (UV) Light Emitting Diodes (LED)

Authors: Anil Kawan, Soon Jae Yu, Jong Min Park

Abstract:

GaN-based 365 nm wavelength ultraviolet (UV) light emitting diodes (LED) have various applications: curing, molding, purification, deodorization, and disinfection etc. However, their usage is limited by very low output power, because of the light absorption in the GaN layers. In this study, we demonstrate a method utilizing removal of 365 nm absorption layer buffer GaN and thinning the n-type GaN so as to improve the light extraction efficiency of the GaN-based 365 nm UV LED. The UV flip chip LEDs of chip size 1.3 mm x 1.3 mm were fabricated using GaN epilayers on a sapphire substrate. Via-hole n-type contacts and highly reflective Ag metal were used for efficient light extraction. LED wafer was aligned and bonded to AlN carrier wafer. To improve the extraction efficiency of the flip chip LED, sapphire substrate and absorption layer buffer GaN were removed by using laser lift-off and dry etching, respectively. To further increase the extraction efficiency of the LED, exposed n-type GaN thickness was reduced by using inductively coupled plasma etching.

Keywords: extraction efficiency, light emitting diodes, n-GaN thinning, ultraviolet

Procedia PDF Downloads 421
4894 Dental Pathologies and Diet in Pre-hispanic Populations of the Equatorial Pacific Coast: Literature Review

Authors: Ricardo Andrés Márquez Ortiz

Abstract:

Objective. The objective of this literature review is to compile updated information from studies that have addressed the association between dental pathologies and diet in prehistoric populations of the equatorial Pacific coast. Materials and method. The research carried out corresponds to a documentary study of ex post facto retrospective, historiographic and bibliometric design. A bibliographic review search was carried out in the libraries of the Colombian Institute of Anthropology and History (ICANH) and the National University of Colombia for books and articles on the archeology of the region. In addition, a search was carried out in databases and the Internet for books and articles on dental anthropology, archeology and dentistry on the relationship between dental pathologies and diet in prehistoric and current populations from different parts of the world. Conclusions. The complex societies (500 BC - 300 AD) of the equatorial Pacific coast used an agricultural system of intensive monoculture of corn (Zea mays). This form of subsistence was reflected in an intensification of dental pathologies such as dental caries, dental abscesses generated by cavities, and enamel hypoplasia associated with a lower frequency of wear. The Upper Formative period (800 A.D. -16th century A.D.) is characterized by the development of polyculture, slash-and-burn agriculture, as an adaptive agricultural strategy to the ecological damage generated by the intensive economic activity of complex societies. This process leads to a more varied diet, which generates better dental health.

Keywords: dental pathologies, nutritional diet, equatorial pacific coast, dental anthropology

Procedia PDF Downloads 44
4893 Effect of Climate Change on the Genomics of Invasiveness of the Whitefly Bemisia tabaci Species Complex by Estimating the Effective Population Size via a Coalescent Method

Authors: Samia Elfekih, Wee Tek Tay, Karl Gordon, Paul De Barro

Abstract:

Invasive species represent an increasing threat to food biosecurity, causing significant economic losses in agricultural systems. An example is the sweet potato whitefly, Bemisia tabaci, which is a complex of morphologically indistinguishable species causing average annual global damage estimated at US$2.4 billion. The Bemisia complex represents an interesting model for evolutionary studies because of their extensive distribution and potential for invasiveness and population expansion. Within this complex, two species, Middle East-Asia Minor 1 (MEAM1) and Mediterranean (MED) have invaded well beyond their home ranges whereas others, such as Indian Ocean (IO) and Australia (AUS), have not. In order to understand why some Bemisia species have become invasive, genome-wide sequence scans were used to estimate population dynamics over time and relate these to climate. The Bayesian Skyline Plot (BSP) method as implemented in BEAST was used to infer the historical effective population size. In order to overcome sampling bias, the populations were combined based on geographical origin. The datasets used for this particular analysis are genome-wide SNPs (single nucleotide polymorphisms) called separately in each of the following groups: Sub-Saharan Africa (Burkina Faso), Europe (Spain, France, Greece and Croatia), USA (Arizona), Mediterranean-Middle East (Israel, Italy), Middle East-Central Asia (Turkmenistan, Iran) and Reunion Island. The non-invasive ‘AUS’ species endemic to Australia was used as an outgroup. The main findings of this study show that the BSP for the Sub-Saharan African MED population is different from that observed in MED populations from the Mediterranean Basin, suggesting evolution under a different set of environmental conditions. For MED, the effective size of the African (Burkina Faso) population showed a rapid expansion ≈250,000-310,000 years ago (YA), preceded by a period of slower growth. The European MED populations (i.e., Spain, France, Croatia, and Greece) showed a single burst of expansion at ≈160,000-200,000 YA. The MEAM1 populations from Israel and Italy and the ones from Iran and Turkmenistan are similar as they both show the earlier expansion at ≈250,000-300,000 YA. The single IO population lacked the latter expansion but had the earlier one. This pattern is shared with the Sub-Saharan African (Burkina Faso) MED, suggesting IO also faced a similar history of environmental change, which seems plausible given their relatively close geographical distributions. In conclusion, populations within the invasive species MED and MEAM1 exhibited signatures of population expansion lacking in non-invasive species (IO and AUS) during the Pleistocene, a geological epoch marked by repeated climatic oscillations with cycles of glacial and interglacial periods. These expansions strongly suggested the potential of some Bemisia species’ genomes to affect their adaptability and invasiveness.

Keywords: whitefly, RADseq, invasive species, SNP, climate change

Procedia PDF Downloads 122
4892 Programming without Code: An Approach and Environment to Conditions-On-Data Programming

Authors: Philippe Larvet

Abstract:

This paper presents the concept of an object-based programming language where tests (if... then... else) and control structures (while, repeat, for...) disappear and are replaced by conditions on data. According to the object paradigm, by using this concept, data are still embedded inside objects, as variable-value couples, but object methods are expressed into the form of logical propositions (‘conditions on data’ or COD).For instance : variable1 = value1 AND variable2 > value2 => variable3 = value3. Implementing this approach, a central inference engine turns and examines objects one after another, collecting all CODs of each object. CODs are considered as rules in a rule-based system: the left part of each proposition (left side of the ‘=>‘ sign) is the premise and the right part is the conclusion. So, premises are evaluated and conclusions are fired. Conclusions modify the variable-value couples of the object and the engine goes to examine the next object. The paper develops the principles of writing CODs instead of complex algorithms. Through samples, the paper also presents several hints for implementing a simple mechanism able to process this ‘COD language’. The proposed approach can be used within the context of simulation, process control, industrial systems validation, etc. By writing simple and rigorous conditions on data, instead of using classical and long-to-learn languages, engineers and specialists can easily simulate and validate the functioning of complex systems.

Keywords: conditions on data, logical proposition, programming without code, object-oriented programming, system simulation, system validation

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4891 Simulation of 1D Dielectric Barrier Discharge in Argon Mixtures

Authors: Lucas Wilman Crispim, Patrícia Hallack, Maikel Ballester

Abstract:

This work aims at modeling electric discharges in gas mixtures. The mathematical model mimics the ignition process in a commercial spark-plug when a high voltage is applied to the plug terminals. A longitudinal unidimensional Cartesian domain is chosen for the simulation region. Energy and mass transfer are considered for a macroscopic fluid representation, while energy transfer in molecular collisions and chemical reactions are contemplated at microscopic level. The macroscopic model is represented by a set of uncoupled partial differential equations. Microscopic effects are studied within a discrete model for electronic and molecular collisions in the frame of ZDPlasKin, a plasma modeling numerical tool. The BOLSIG+ solver is employed in solving the electronic Boltzmann equation. An operator splitting technique is used to separate microscopic and macroscopic models. The simulation gas is a mixture of atomic Argon neutral, excited and ionized. Spatial and temporal evolution of such species and temperature are presented and discussed.

Keywords: CFD, electronic discharge, ignition, spark plug

Procedia PDF Downloads 156
4890 Gold Nanoparticle: Synthesis, Characterization, Clinico-Pathological, Pathological and Bio-Distribution Studies in Rabbits

Authors: M. M. Bashandy, A. R. Ahmed, M. El-Gaffary, Sahar S. Abd El-Rahman

Abstract:

This study evaluated the acute toxicity and tissue distribution of intravenously administered gold nanoparticles (AuNPs) in male rabbits. Rabbits were exposed to single dose of AuNPs (300 µg/ kg). Toxic effects were assessed via general behavior, hematological parameters, serum biochemical parameters and histopathological examination of various rabbits’ organs. Tissue distribution of AuNPs was evaluated at a dose of 300 µg/ kg in male rabbit. Inductively coupled plasma–mass spectrometry (ICP-MS) was used to determine gold concentrations in tissue samples collected at predetermined time intervals. After one week, AuNPs exerted no obvious acute toxicity in rabbits. However, inflammatory reactions in lung and liver cells were induced in rabbits treated at the300 µg/ kg dose level. The highest gold levels were found in the spleen, followed by liver, lungs and kidneys. These results indicated that AuNPs could be distributed extensively to various tissues in the body, but primarily in the spleen and liver.

Keywords: gold nanoparticles, toxicity, pathology, hematology, liver function, kidney function

Procedia PDF Downloads 329
4889 Developing Proof Demonstration Skills in Teaching Mathematics in the Secondary School

Authors: M. Rodionov, Z. Dedovets

Abstract:

The article describes the theoretical concept of teaching secondary school students proof demonstration skills in mathematics. It describes in detail different levels of mastery of the concept of proof-which correspond to Piaget’s idea of there being three distinct and progressively more complex stages in the development of human reflection. Lessons for each level contain a specific combination of the visual-figurative components and deductive reasoning. It is vital at the transition point between levels to carefully and rigorously recalibrate teaching to reflect the development of more complex reflective understanding. This can apply even within the same age range, since students will develop at different speeds and to different potential. The authors argue that this requires an aware and adaptive approach to lessons to reflect this complexity and variation. The authors also contend that effective teaching which enables students to properly understand the implementation of proof arguments must develop specific competences. These are: understanding of the importance of completeness and generality in making a valid argument; being task focused; having an internalised locus of control and being flexible in approach and evaluation. These criteria must be correlated with the systematic application of corresponding methodologies which are best likely to achieve success. The particular pedagogical decisions which are made to deliver this objective are illustrated by concrete examples from the existing secondary school mathematics courses. The proposed theoretical concept formed the basis of the development of methodological materials which have been tested in 47 secondary schools.

Keywords: education, teaching of mathematics, proof, deductive reasoning, secondary school

Procedia PDF Downloads 238
4888 Legislating for Public Participation and Environmental Justice: Whether It Solves or Prevent Disputes

Authors: Deborah A. Hollingworth

Abstract:

The key tenets associated with ‘environmental justice’, were first articulated in a global context in Principle 10 of the United Nations Declaration on Environment and Development at Rio de Janeiro in 1992 (the Rio Declaration). The elements can be conflated to require: public participation in decision-making; the provision of relevant information to those affected about environmental hazards issues; access to judicial and administrative proceeding; and the opportunity for redress where remedy where required. This paper examines the legislative and regulatory arrangements in place for the implementation these elements in a number of industrialised democracies, including Australia. Most have, over time made regulatory provision for these elements – even if they are not directly attributed Principle 10 or the notion of environmental justice. The paper proposes, that of these elements the most critical to the achievement of good environmental governance, is a legislated recognition and role of public participation. However, the paper considers that notwithstanding sound legislative and regulatory practices, environmental regulators frequently struggle, where there is a complex decision-making scenario or long-standing enmity between a community and industry to achieve effective engagement with the public. This study considers the dilemma confronted by environmental regulators to given meaningful effect to the principles enshrined in Principle 10 – that even when the legislative expression of Principle 10 is adhered to – does not prevent adverse outcomes. In particular, it considers, as a case study a prominent environmental incident in 2014 in Australia in which an open-cut coalmine located in the regional township of Morwell caught fire during bushfire season. The fire, which took 45 days to be extinguished had a significant and adverse impact on the community in question, but compounded a complex, and sometime antagonistic history between the mine and township. The case study exemplifies the complex factors that will often be present between industry, the public and regulatory bodies, and which confound the concept of environmental justice, and the elements of enshrined in the Principle 10 of the Rio Declaration. The study proposes that such tensions and complex examples will commonly be the reality of communities and regulators. However, to give practical effect to outcomes contemplated by Principle 10, the paper considers that regulators will may consider public intervention more broadly as including early interventions and formal opportunities for “conferencing” between industry, community and regulators. These initiatives help to develop a shared understanding and identification of issues. It is proposed that although important, options for “alternative dispute resolution” are not sufficiently preventative, as they come into play when a dispute has arise. Similarly “restorative justice” programs, while important once an incident or adverse environmental outcome has occurred, are post event and therefore necessarily limited. The paper considers the examples of how public participation at the outset – at the time of a proposal, before issues arise or eventuate to ensure, is demonstrably the most effective way for building commonality and an agreed methodology for working to resolve issues once they occur.

Keywords: environmental justice, alternative dispute resolution, domestic environmental law, international environmental law

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4887 Simulation of the Visco-Elasto-Plastic Deformation Behaviour of Short Glass Fibre Reinforced Polyphthalamides

Authors: V. Keim, J. Spachtholz, J. Hammer

Abstract:

The importance of fibre reinforced plastics continually increases due to the excellent mechanical properties, low material and manufacturing costs combined with significant weight reduction. Today, components are usually designed and calculated numerically by using finite element methods (FEM) to avoid expensive laboratory tests. These programs are based on material models including material specific deformation characteristics. In this research project, material models for short glass fibre reinforced plastics are presented to simulate the visco-elasto-plastic deformation behaviour. Prior to modelling specimens of the material EMS Grivory HTV-5H1, consisting of a Polyphthalamide matrix reinforced by 50wt.-% of short glass fibres, are characterized experimentally in terms of the highly time dependent deformation behaviour of the matrix material. To minimize the experimental effort, the cyclic deformation behaviour under tensile and compressive loading (R = −1) is characterized by isothermal complex low cycle fatigue (CLCF) tests. Combining cycles under two strain amplitudes and strain rates within three orders of magnitude and relaxation intervals into one experiment the visco-elastic deformation is characterized. To identify visco-plastic deformation monotonous tensile tests either displacement controlled or strain controlled (CERT) are compared. All relevant modelling parameters for this complex superposition of simultaneously varying mechanical loadings are quantified by these experiments. Subsequently, two different material models are compared with respect to their accuracy describing the visco-elasto-plastic deformation behaviour. First, based on Chaboche an extended 12 parameter model (EVP-KV2) is used to model cyclic visco-elasto-plasticity at two time scales. The parameters of the model including a total separation of elastic and plastic deformation are obtained by computational optimization using an evolutionary algorithm based on a fitness function called genetic algorithm. Second, the 12 parameter visco-elasto-plastic material model by Launay is used. In detail, the model contains a different type of a flow function based on the definition of the visco-plastic deformation as a part of the overall deformation. The accuracy of the models is verified by corresponding experimental LCF testing.

Keywords: complex low cycle fatigue, material modelling, short glass fibre reinforced polyphthalamides, visco-elasto-plastic deformation

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4886 A Mixed-Methods Design and Implementation Study of ‘the Attach Project’: An Attachment-Based Educational Intervention for Looked after Children in Northern Ireland

Authors: Hannah M. Russell

Abstract:

‘The Attach Project’ (TAP), is an educational intervention aimed at improving educational and socio-emotional outcomes for children who are looked after. TAP is underpinned by Attachment Theory and is adapted from Dyadic Developmental Psychotherapy (DDP), which is a treatment for children and young people impacted by complex trauma and disorders of attachment. TAP has been implemented in primary schools in Northern Ireland throughout the 2018/19 academic year. During this time, a design and implementation study has been conducted to assess the promise of effectiveness for the future dissemination and ‘scaling-up’ of the programme for a larger, randomised control trial. TAP has been designed specifically for implementation in a school setting and is comprised of a whole school element and a more individualised Key Adult-Key Child pairing. This design and implementation study utilises a mixed-methods research design consisting of quantitative, qualitative, and observational measures with stakeholder input and involvement being considered an integral component. The use of quantitative measures, such as self-report questionnaires prior to and eight months following the implementation of TAP, enabled the analysis of the strengths and direction of relations between the various components of the programme, as well as the influence of implementation factors. The use of qualitative measures, incorporating semi-structured interviews and focus groups, enabled the assessment of implementation factors, identification of implementation barriers, and potential methods of addressing these issues. Observational measures facilitated the continual development and improvement of ‘TAP training’ for school staff. Preliminary findings have provided evidence of promise for the effectiveness of TAP and indicate the potential benefits of introducing this type of attachment-based intervention across other educational settings. This type of intervention could benefit not only children who are looked after but all children who may be impacted by complex trauma or disorders of attachment. Furthermore, findings from this study demonstrate that it is possible for children to form a secondary attachment relationship with a significant adult in school. However, various implementation factors which should be addressed were identified throughout the study, such as the necessity of protected time being introduced to facilitate the development of a positive Key Adult- Key Child relationship. Furthermore, additional ‘re-cap’ training is required in future dissemination of the programme, to maximise ‘attachment friendly practice’ in the whole staff team. Qualitative findings have also indicated that there is a general opinion across school staff that this type of Key Adult- Key Child pairing could be more effective if it was introduced as soon as children begin primary school. This research has provided ample evidence for the need to introduce relationally based interventions in schools, to help to ensure that children who are looked after, or who are impacted by complex trauma or disorders of attachment, can thrive in the school environment. In addition, this research has facilitated the identification of important implementation factors and barriers to implementation, which can be addressed prior to the ‘scaling-up’ of TAP for a robust, randomised controlled trial.

Keywords: attachment, complex trauma, educational interventions, implementation

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4885 Automatic and High Precise Modeling for System Optimization

Authors: Stephanie Chen, Mitja Echim, Christof Büskens

Abstract:

To describe and propagate the behavior of a system mathematical models are formulated. Parameter identification is used to adapt the coefficients of the underlying laws of science. For complex systems this approach can be incomplete and hence imprecise and moreover too slow to be computed efficiently. Therefore, these models might be not applicable for the numerical optimization of real systems, since these techniques require numerous evaluations of the models. Moreover not all quantities necessary for the identification might be available and hence the system must be adapted manually. Therefore, an approach is described that generates models that overcome the before mentioned limitations by not focusing on physical laws, but on measured (sensor) data of real systems. The approach is more general since it generates models for every system detached from the scientific background. Additionally, this approach can be used in a more general sense, since it is able to automatically identify correlations in the data. The method can be classified as a multivariate data regression analysis. In contrast to many other data regression methods this variant is also able to identify correlations of products of variables and not only of single variables. This enables a far more precise and better representation of causal correlations. The basis and the explanation of this method come from an analytical background: the series expansion. Another advantage of this technique is the possibility of real-time adaptation of the generated models during operation. Herewith system changes due to aging, wear or perturbations from the environment can be taken into account, which is indispensable for realistic scenarios. Since these data driven models can be evaluated very efficiently and with high precision, they can be used in mathematical optimization algorithms that minimize a cost function, e.g. time, energy consumption, operational costs or a mixture of them, subject to additional constraints. The proposed method has successfully been tested in several complex applications and with strong industrial requirements. The generated models were able to simulate the given systems with an error in precision less than one percent. Moreover the automatic identification of the correlations was able to discover so far unknown relationships. To summarize the above mentioned approach is able to efficiently compute high precise and real-time-adaptive data-based models in different fields of industry. Combined with an effective mathematical optimization algorithm like WORHP (We Optimize Really Huge Problems) several complex systems can now be represented by a high precision model to be optimized within the user wishes. The proposed methods will be illustrated with different examples.

Keywords: adaptive modeling, automatic identification of correlations, data based modeling, optimization

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4884 Deep Well Grounded Magnetite Anode Chains Retrieval and Installation for Raslanuf Complex Impressed Current Cathodic Protection System Rectification

Authors: Mohamed Ahmed Khali

Abstract:

Numbers of deep well anode ground beds (GBs) have been retrieved due to un operated anode chains. New identical magnetite anode chains(MAC) have been installed at Raslanuf complex impressed current Cathodic protection(ICCP) system, distributed at different plants(Utility, ethylene and polyethylene). All problems associated with retrieving and installation of MACs have been discussed, rectified and presented. All GB associated severely corroded wellhead casings were well maintained and/ or replaced by new fabricated and modified ones. The main cause of wellhead casings internal corrosion was discussed, and the conducted remedy action to overcome future corrosion problem is presented. All GB connected anode junction boxes (AJBs) and shunts were closely inspected, maintained, and necessary replacement/and or modification were carried out on shunts. All damaged GB concrete foundations (CF) have been inspected and completely replaced. All GB associated Transformer-Rectifiers units (TRUs) were subjected to through inspection, and necessary maintenance has been performed on each individual TRU. After completion of all MACs and TRU maintenance activities, each cathodic protection station (CPS) has been re-operated. An alternative current (AC), direct current (DC), voltage and structure to soil potential (S/P) measurements have been conducted, recorded, and all obtained test results are presented. DC current outputs has been adjusted, and DC current outputs of each MAC has been recorded for each GB AJB.

Keywords: magnatite anode, deep well, ground bed, cathodic protection, transformer rectifies, impreced current, junction box

Procedia PDF Downloads 100
4883 The Study of the Perspectives on Economic Development in Bilateral Investment Treaties

Authors: Anuj Kumar Vaksha

Abstract:

In the post cold war era the foreign direct investments have come to be considered as one of the most critical factors for economic development of a country particularly for the capital scarce countries like the developing and the under developed countries. The rush for foreign direct investments have led to intense competition between the countries treaties to attract foreign investments by entering into alluring Bilateral Investment Treaties (BITs). The Bilateral Investment Treaties are the intergovernmental legal framework for the promotion of private investments from one country to other. With more than 3000 BITs, the web of such BITs are the most dominant development of International Law in the post cold war era. The essence of all these BITs are bilateral cooperation for economic development and thus it is actually the theme of economic development around which the International Law had developed most dominantly in the post cold war era. Within the framework of two generally accepted premises that foreign direct investments are critical for economic development and the bilateral investment treaties are critical for promotion of foreign direct investments, the research paper seeks to explore the perspectives and paradigms on economic development as embodied in various Bilateral Investment Treaties. It seeks to address how and in what manners the perspectives on economic development as embodied in bilateral investment varies between the developed, developing and underdeveloped countries. It goes without saying that economic development is a very broad, complex and operationally intricate concept. In the paradigm of International Law it becomes much more complex and intricate. Understanding the concept of economic development from the perspectives of Bilateral Investment Treaties is a novel idea with far reaching significance. Such a perspective on economic development would help in enriching the contemporary International Law perspectives and paradigms on economic development.

Keywords: bilateral investment treaties, economic development, international Law, perspectives

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4882 Predicting Costs in Construction Projects with Machine Learning: A Detailed Study Based on Activity-Level Data

Authors: Soheila Sadeghi

Abstract:

Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

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4881 NiO-CeO2 Nano-Catalyst for the Removal of Priority Organic Pollutants from Wastewater through Catalytic Wet Air Oxidation at Mild Conditions

Authors: Anushree, Chhaya Sharma, Satish Kumar

Abstract:

Catalytic wet air oxidation (CWAO) is normally carried out at elevated temperature and pressure. This work investigates the potential of NiO-CeO2 nano-catalyst in CWAO of paper industry wastewater under milder operating conditions of 90 °C and 1 atm. The NiO-CeO2 nano-catalysts were synthesized by a simple co-precipitation method and characterized by X-ray diffraction (XRD), before and after use, in order to study any crystallographic change during experiment. The extent of metal-leaching from the catalyst was determined using the inductively coupled plasma optical emission spectrometry (ICP-OES). The catalytic activity of nano-catalysts was studied in terms of total organic carbon (TOC), adsorbable organic halides (AOX) and chlorophenolics (CHPs) removal. Interestingly, mixed oxide catalysts exhibited higher activity than the corresponding single-metal oxides. The maximum removal efficiency was achieved with Ce40Ni60 catalyst. The results indicate that the CWAO process is efficient in removing the priority organic pollutants from wastewater, as it exhibited up to 59% TOC, 55% AOX, and 54 % CHPs removal.

Keywords: catalysis, nano-materials, NiO-CeO2, paper mill, wastewater, wet air oxidation

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4880 Assessment of Heavy Metal Contamination in Ground Water in the Coastal Part of Cauvery Deltaic Region, South India

Authors: Gnanachandrasamy G., Zhou Y., Ramkumar T., Venkatramanan S., Wang S., Mo Liping, Jingru Zhang

Abstract:

In order to assess the heavy metal contamination totally fourty five groundwater samples were collected from the coastal part of Cauvery deltaic region, South India, during monsoon season in the year of 2017. The study area lies between longitudes 79º15’ to 79º 50’ E and latitudes 10º10’ to 11º20’ N with total area of 2,569 km². The concentration of As, Ba, Cd, Cr, Co, Cu, Ni, Pb, Se, and Zn were analyzed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The heavy metals ranged between 0.007-117.8 µg/l for As, 8.503-1281 µg/l for Ba, 0.006-0.12 µg/l for Cd, 0.23-5.572µg/l for Cr, 0.44-17.9 µg/l for Co, 0.633-11.56 µg/l for Cu, 0.467-29.34 µg/l for Ni, 0.008-5.756 µg/l for Pb, 0.979 to 45.49 µg/l for Se, and 2.712-10480 µg/l for Zn in the groundwaters. A comparison of heavy metal concentration with WHO and BIS drinking water standards shows that Ni, Zn, As, Se, and Ba level is higher than the drinking water standards in some of the groundwater samples, and the concentrations of all the other heavy metals were lower than the drinking water standards. The present levels of heavy metal concentration in the studied area groundwaters are moderate to severe to public health and environmental concerns and need attention.

Keywords: cauvery delta, drinking water, groundwater, heavy metals

Procedia PDF Downloads 340
4879 A Machine Learning Approach for Efficient Resource Management in Construction Projects

Authors: Soheila Sadeghi

Abstract:

Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

Procedia PDF Downloads 29
4878 Highly Stretchable, Intelligent and Conductive PEDOT/PU Nanofibers Based on Electrospinning and in situ Polymerization

Authors: Kun Qi, Yuman Zhou, Jianxin He

Abstract:

A facile fabrication strategy via electrospinning and followed by in situ polymerization to fabricate a highly stretchable and conductive Poly(3,4-ethylenedioxythiophene)/Polyurethane (PEDOT/PU) nanofibrous membrane is reported. PU nanofibers were prepared by electrospinning and then PEDOT was coated on the plasma modified PU nanofiber surface via in-situ polymerization to form flexible PEDOT/PU composite nanofibers with conductivity. The results show PEDOT is successfully synthesized on the surface of PU nanofiber and PEDOT/PU composite nanofibers possess skin-core structure. Furthermore, the experiments indicate the optimal technological parameters of the polymerization process are as follow: The concentration of EDOT monomers is 50 mmol/L, the polymerization time is 24 h and the temperature is 25℃. The PEDOT/PU nanofibers exhibit excellent electrical conductivity ( 27.4 S/cm). In addition, flexible sensor made from conductive PEDOT/PU nanofibers shows highly sensitive response towards tensile strain and also can be used to detect finger motion. The results demonstrate promising application of the as-obtained nanofibrous membrane in flexible wearable electronic fields.

Keywords: electrospinning, polyurethane, PEDOT, conductive nanofiber, flexible senor

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4877 Fluid-Structure Interaction Study of Fluid Flow past Marine Turbine Blade Designed by Using Blade Element Theory and Momentum Theory

Authors: Abu Afree Andalib, M. Mezbah Uddin, M. Rafiur Rahman, M. Abir Hossain, Rajia Sultana Kamol

Abstract:

This paper deals with the analysis of flow past the marine turbine blade which is designed by using the blade element theory and momentum theory for the purpose of using in the field of renewable energy. The designed blade is analyzed for various parameters using FSI module of Ansys. Computational Fluid Dynamics is used for the study of fluid flow past the blade and other fluidic phenomena such as lift, drag, pressure differentials, energy dissipation in water. Finite Element Analysis (FEA) module of Ansys was used to analyze the structural parameter such as stress and stress density, localization point, deflection, force propagation. Fine mesh is considered in every case for more accuracy in the result according to computational machine power. The relevance of design, search and optimization with respect to complex fluid flow and structural modeling is considered and analyzed. The relevancy of design and optimization with respect to complex fluid for minimum drag force using Ansys Adjoint Solver module is analyzed as well. The graphical comparison of the above-mentioned parameter using CFD and FEA and subsequently FSI technique is illustrated and found the significant conformity between both the results.

Keywords: blade element theory, computational fluid dynamics, finite element analysis, fluid-structure interaction, momentum theory

Procedia PDF Downloads 296
4876 The Role of Metaheuristic Approaches in Engineering Problems

Authors: Ferzat Anka

Abstract:

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

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4875 Geo-Collaboration Model between a City and Its Inhabitants to Develop Complementary Solutions for Better Household Waste Collection

Authors: Abdessalam Hijab, Hafida Boulekbache, Eric Henry

Abstract:

According to several research studies, the city as a whole is a complex, spatially organized system; its modeling must take into account several factors, socio-economic, and political, or geographical, acting at multiple scales of observation according to varied temporalities. Sustainable management and protection of the environment in this complex system require significant human and technical investment, particularly for monitoring and maintenance. The objective of this paper is to propose an intelligent approach based on the coupling of Geographic Information System (GIS) and Information and Communications Technology (ICT) tools in order to integrate the inhabitants in the processes of sustainable management and protection of the urban environment, specifically in the processes of household waste collection in urban areas. We are discussing a collaborative 'city/inhabitant' space. Indeed, it is a geo-collaborative approach, based on the spatialization and real-time geo-localization of topological and multimedia data taken by the 'active' inhabitant, in the form of geo-localized alerts related to household waste issues in their city. Our proposal provides a good understanding of the extent to which civil society (inhabitants) can help and contribute to the development of complementary solutions for the collection of household waste and the protection of the urban environment. Moreover, it allows the inhabitant to contribute to the enrichment of a data bank for future uses. Our geo-collaborative model will be tested in the Lamkansa sampling district of the city of Casablanca in Morocco.

Keywords: geographic information system, GIS, information and communications technology, ICT, geo-collaboration, inhabitants, city

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4874 Optimization of Ultrasound-Assisted Extraction and Microwave-Assisted Acid Digestion for the Determination of Heavy Metals in Tea Samples

Authors: Abu Harera Nadeem, Kingsley Donkor

Abstract:

Tea is a popular beverage due to its flavour, aroma and antioxidant properties—with the most consumed varieties being green and black tea. Antioxidants in tea can lower the risk of Alzheimer’s and heart disease and obesity. However, these teas contain heavy metals such as Hg, Cd, or Pb, which can cause autoimmune diseases like Graves disease. In this study, 11 heavy metals in various commercial green, black, and oolong tea samples were determined using inductively coupled plasma-mass spectrometry (ICP-MS). Two methods of sample preparation were compared for accuracy and precision, which were microwave-assisted digestion and ultrasonic-assisted extraction. The developed method was further validated by detection limit, precision, and accuracy. Results showed that the proposed method was highly sensitive with detection limits within parts-per-billion levels. Reasonable method accuracy was obtained by spiked experiments. The findings of this study can be used to delve into the link between tea consumption and disease and to provide information for future studies on metal determination in tea.

Keywords: ICP-MS, green tea, black tea, microwave-assisted acid digestion, ultrasound-assisted extraction

Procedia PDF Downloads 118
4873 Reinforcement Learning for Robust Missile Autopilot Design: TRPO Enhanced by Schedule Experience Replay

Authors: Bernardo Cortez, Florian Peter, Thomas Lausenhammer, Paulo Oliveira

Abstract:

Designing missiles’ autopilot controllers have been a complex task, given the extensive flight envelope and the nonlinear flight dynamics. A solution that can excel both in nominal performance and in robustness to uncertainties is still to be found. While Control Theory often debouches into parameters’ scheduling procedures, Reinforcement Learning has presented interesting results in ever more complex tasks, going from videogames to robotic tasks with continuous action domains. However, it still lacks clearer insights on how to find adequate reward functions and exploration strategies. To the best of our knowledge, this work is a pioneer in proposing Reinforcement Learning as a framework for flight control. In fact, it aims at training a model-free agent that can control the longitudinal non-linear flight dynamics of a missile, achieving the target performance and robustness to uncertainties. To that end, under TRPO’s methodology, the collected experience is augmented according to HER, stored in a replay buffer and sampled according to its significance. Not only does this work enhance the concept of prioritized experience replay into BPER, but it also reformulates HER, activating them both only when the training progress converges to suboptimal policies, in what is proposed as the SER methodology. The results show that it is possible both to achieve the target performance and to improve the agent’s robustness to uncertainties (with low damage on nominal performance) by further training it in non-nominal environments, therefore validating the proposed approach and encouraging future research in this field.

Keywords: Reinforcement Learning, flight control, HER, missile autopilot, TRPO

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4872 Insights Into Serotonin-Receptor Binding and Stability via Molecular Dynamics Simulations: Key Residues for Electrostatic Interactions and Signal Transduction

Authors: Arunima Verma, Padmabati Mondal

Abstract:

Serotonin-receptor binding plays a key role in several neurological and biological processes, including mood, sleep, hunger, cognition, learning, and memory. In this article, we performed molecular dynamics simulation to examine the key residues that play an essential role in the binding of serotonin to the G-protein-coupled 5-HT₁ᴮ receptor (5-HT₁ᴮ R) via electrostatic interactions. An end-point free energy calculation method (MM-PBSA) determines the stability of the 5-HT1B R due to serotonin binding. The single-point mutation of the polar or charged amino acid residues (Asp129, Thr134) on the binding sites and the calculation of binding free energy validate the importance of these residues in the stability of the serotonin-receptor complex. Principal component analysis indicates the serotonin-bound 5-HT1BR is more stabilized than the apo-receptor in terms of dynamical changes. The difference dynamic cross-correlations map shows the correlation between the transmembrane and mini-Go, which indicates signal transduction happening between mini-Go and the receptor. Allosteric communication reveals the key nodes for signal transduction in 5-HT1BR. These results provide useful insights into the signal transduction pathways and mutagenesis study to regulate the functionality of the complex. The developed protocols can be applied to study local non-covalent interactions and long-range allosteric communications in any protein-ligand system for computer-aided drug design.

Keywords: allostery, CADD, MD simulations, MM-PBSA

Procedia PDF Downloads 80
4871 Study and Solving High Complex Non-Linear Differential Equations Applied in the Engineering Field by Analytical New Approach AGM

Authors: Mohammadreza Akbari, Sara Akbari, Davood Domiri Ganji, Pooya Solimani, Reza Khalili

Abstract:

In this paper, three complicated nonlinear differential equations(PDE,ODE) in the field of engineering and non-vibration have been analyzed and solved completely by new method that we have named it Akbari-Ganji's Method (AGM) . As regards the previous published papers, investigating this kind of equations is a very hard task to do and the obtained solution is not accurate and reliable. This issue will be emerged after comparing the achieved solutions by Numerical Method. Based on the comparisons which have been made between the gained solutions by AGM and Numerical Method (Runge-Kutta 4th), it is possible to indicate that AGM can be successfully applied for various differential equations particularly for difficult ones. Furthermore, It is necessary to mention that a summary of the excellence of this method in comparison with the other approaches can be considered as follows: It is noteworthy that these results have been indicated that this approach is very effective and easy therefore it can be applied for other kinds of nonlinear equations, And also the reasons of selecting the mentioned method for solving differential equations in a wide variety of fields not only in vibrations but also in different fields of sciences such as fluid mechanics, solid mechanics, chemical engineering, etc. Therefore, a solution with high precision will be acquired. With regard to the afore-mentioned explanations, the process of solving nonlinear equation(s) will be very easy and convenient in comparison with the other methods. And also one of the important position that is explored in this paper is: Trigonometric and exponential terms in the differential equation (the method AGM) , is no need to use Taylor series Expansion to enhance the precision of the result.

Keywords: new method (AGM), complex non-linear partial differential equations, damping ratio, energy lost per cycle

Procedia PDF Downloads 461
4870 Achieving Quality of Life and Sustainability in Mexican Cities, the Case of the Housing Complex “Villa del Campo”, Tijuana, Mexico

Authors: María de los Ángeles Zárate López, Juan Antonio Pitones Rubio

Abstract:

Quality of life and sustainability in cities are among the most important challenges faced by designers, city planners and urban managers. The Mexican city of Tijuana has a particular dynamic in its demographics which has been accelerated by its border city condition, putting to the test the ability from authorities to provide the population with the necessary services to aspire for a deserving quality of life. In the recent story of Tijuana, we found that the housing policy and the solutions presented by private housing developers have not met the best living conditions for end users by far, thereby adding issues to current social problems which impact the whole metropolitan area, including damage to the natural environment. Therefore this research presents the case study about the situation of a suburban housing development near Tijuana named “Villa del Campo” and exposes the problems of this specific project (originally labelled as a “sustainable” proposal) demonstrating that, once built, the place does not reflect the quality of life that it promised as a project. Currently, this housing development has a number of problematic issues such as the faulty operating conditions of public utilities and serious cases of crime inside the neighborhood. There is no intention to only expose the negative side of this case study, but to explore some alternatives which could help solving the most serious problems at the place, considering possible architectural and landscape interventions within the housing complex to help achieve the optimal conditions of livability and sustainability required by their inhabitants.

Keywords: suburban, housing, quality of life, sustainability, Tijuana, demographics

Procedia PDF Downloads 381
4869 The Using of Liquefied Petroleum Gas (LPG) on a Low Heat Loss Si Engine

Authors: Hanbey Hazar, Hakan Gul

Abstract:

In this study, Thermal Barrier Coating (TBC) application is performed in order to reduce the engine emissions. Piston, exhaust, and intake valves of a single-cylinder four-cycle gasoline engine were coated with chromium carbide (Cr3C2) at a thickness of 300 µm by using the Plasma Spray coating method which is a TBC method. Gasoline engine was converted into an LPG system. The study was conducted in 4 stages. In the first stage, the piston, exhaust, and intake valves of the gasoline engine were coated with Cr3C2. In the second stage, gasoline engine was converted into the LPG system and the emission values in this engine were recorded. In the third stage, the experiments were repeated under the same conditions with a standard (uncoated) engine and the results were recorded. In the fourth stage, data obtained from both engines were loaded on Artificial Neural Networks (ANN) and estimated values were produced for every revolution. Thus, mathematical modeling of coated and uncoated engines was performed by using ANN. While there was a slight increase in exhaust gas temperature (EGT) of LPG engine due to TBC, carbon monoxide (CO) values decreased.

Keywords: LPG fuel, thermal barrier coating, artificial neural network, mathematical modelling

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4868 Experimental Investigation on Effect of the Zirconium + Magnesium Coating of the Piston and Valve of the Single-Cylinder Diesel Engine to the Engine Performance and Emission

Authors: Erdinç Vural, Bülent Özdalyan, Serkan Özel

Abstract:

The four-stroke single cylinder diesel engine has been used in this study, the pistons and valves of the engine have been stabilized, the aluminum oxide (Al2O3) in different ratios has been added in the power of zirconium (ZrO2) magnesium oxide (MgO), and has been coated with the plasma spray method. The pistons and valves of the combustion chamber of the engine are coated with 5 different (ZrO2 + MgO), (ZrO2 + MgO + 25% Al2O3), (ZrO2 + MgO + 50% Al2O3), (ZrO2 + MgO + 75% Al2O3), (Al2O3) sample. The material tests have been made for each of the coated engine parts with the scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX) and X-ray diffraction (XRD) using Cu Kα radiation surface analysis methods. The engine tests have been repeated for each sample in any electric dynamometer in full power 1600 rpm, 2000 rpm, 2400 rpm and 2800 rpm engine speeds. The material analysis and engine tests have shown that the best performance has been performed with (ZrO2 + MgO + 50% Al2O3). Thus, there is no significant change in HC and Smoke emissions, but NOx emission is increased, as the engine improves power, torque, specific fuel consumption and CO emissions in the tests made with sample A3.

Keywords: ceramic coating, material characterization, engine performance, exhaust emissions

Procedia PDF Downloads 366
4867 Deep Well-Grounded Magnetite Anode Chains Retrieval and Installation for Raslanuf Complex Impressed Current Cathodic Protection System Rectification

Authors: Mohamed Ahmed Khalil

Abstract:

The number of deep well anode ground beds (GBs) have been retrieved due to unoperated anode chains. New identical magnetite anode chains (MAC) have been installed at Raslanuf complex impressed current Cathodic protection (ICCP) system, distributed at different plants (Utility, ethylene and polyethylene). All problems associated with retrieving and installation of MACs have been discussed, rectified and presented. All GB-associated severely corroded wellhead casings were well maintained and/or replaced by new fabricated and modified ones. The main cause of the wellhead casing's severe internal corrosion was discussed and the conducted remedy action to overcome future corrosion problems is presented. All GB-connected anode junction boxes (AJBs) and shunts were closely inspected, maintained and necessary replacement and/or modifications were carried out on shunts. All damaged GB concrete foundations (CF) have been inspected and completely replaced. All GB-associated Transformer-Rectifiers Units (TRU) were subjected to thorough inspection and necessary maintenance was performed on each individual TRU. After completion of all MACs and TRU maintenance activities, each cathodic protection station (CPS) has been re-operated, alternative current (AC), direct current (DC), voltage and structure to soil potential (S/P) measurements have been conducted, recorded and all obtained test results are presented. DC current outputs have been adjusted and DC current outputs of each MAC have been recorded for each GB AJB.

Keywords: magnetite anodes, deep well, ground beds, cathodic protection, transformer rectifier, impressed current, junction boxes

Procedia PDF Downloads 111
4866 Nuclear Mitochondrial Pseudogenes in Anastrepha fraterculus Complex

Authors: Pratibha Srivastava, Ayyamperumal Jeyaprakash, Gary Steck, Jason Stanley, Leroy Whilby

Abstract:

Exotic, invasive tephritid fruit flies (Diptera: Tephritidae) are a major threat to fruit and vegetable industries in the United States. The establishment of pest fruit fly in the agricultural industries and produce severe ecological and economic impacts on agricultural diversification and trade. Detection and identification of these agricultural pests in a timely manner will facilitate the possibility of eradication from newly invaded areas. Identification of larval stages to species level is difficult, but is required to determine pest loads and their pathways into the United States. The aim of this study is the New World genus, Anastrepha which includes pests of major economic importance. Mitochondrial cytochrome c oxidase I (COI) gene sequences were amplified from Anastrepha fraterculus specimens collected from South America (Ecuador and Peru). Phylogenetic analysis was performed to characterize the Anastrepha fraterculus complex at a molecular level. During phylogenetics analysis numerous nuclear mitochondrial pseudogenes (numts) were discovered in different specimens. The numts are nonfunctional copies of the mtDNA present in the nucleus and are easily coamplified with the mitochondrial COI gene copy by using conserved universal primers. This is problematic for DNA Barcoding, which attempts to characterize all living organisms by using the COI gene. This study is significant for national quarantine use, as morphological diagnostics to separate larvae of the various members remain poorly developed.

Keywords: tephritid, Anastrepha fraterculus, COI, numts

Procedia PDF Downloads 232