Search results for: hydrodynamic methods
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 15671

Search results for: hydrodynamic methods

13901 Numerical Solution of Portfolio Selecting Semi-Infinite Problem

Authors: Alina Fedossova, Jose Jorge Sierra Molina

Abstract:

SIP problems are part of non-classical optimization. There are problems in which the number of variables is finite, and the number of constraints is infinite. These are semi-infinite programming problems. Most algorithms for semi-infinite programming problems reduce the semi-infinite problem to a finite one and solve it by classical methods of linear or nonlinear programming. Typically, any of the constraints or the objective function is nonlinear, so the problem often involves nonlinear programming. An investment portfolio is a set of instruments used to reach the specific purposes of investors. The risk of the entire portfolio may be less than the risks of individual investment of portfolio. For example, we could make an investment of M euros in N shares for a specified period. Let yi> 0, the return on money invested in stock i for each dollar since the end of the period (i = 1, ..., N). The logical goal here is to determine the amount xi to be invested in stock i, i = 1, ..., N, such that we maximize the period at the end of ytx value, where x = (x1, ..., xn) and y = (y1, ..., yn). For us the optimal portfolio means the best portfolio in the ratio "risk-return" to the investor portfolio that meets your goals and risk ways. Therefore, investment goals and risk appetite are the factors that influence the choice of appropriate portfolio of assets. The investment returns are uncertain. Thus we have a semi-infinite programming problem. We solve a semi-infinite optimization problem of portfolio selection using the outer approximations methods. This approach can be considered as a developed Eaves-Zangwill method applying the multi-start technique in all of the iterations for the search of relevant constraints' parameters. The stochastic outer approximations method, successfully applied previously for robotics problems, Chebyshev approximation problems, air pollution and others, is based on the optimal criteria of quasi-optimal functions. As a result we obtain mathematical model and the optimal investment portfolio when yields are not clear from the beginning. Finally, we apply this algorithm to a specific case of a Colombian bank.

Keywords: outer approximation methods, portfolio problem, semi-infinite programming, numerial solution

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13900 The Findings EEG-LORETA about Epilepsy

Authors: Leila Maleki, Ahmad Esmali Kooraneh, Hossein Taghi Derakhshi

Abstract:

Neural activity in the human brain starts from the early stages of prenatal development. This activity or signals generated by the brain are electrical in nature and represent not only the brain function but also the status of the whole body. At the present moment, three methods can record functional and physiological changes within the brain with high temporal resolution of neuronal interactions at the network level: the electroencephalogram (EEG), the magnet oencephalogram (MEG), and functional magnetic resonance imaging (fMRI); each of these has advantages and shortcomings. EEG recording with a large number of electrodes is now feasible in clinical practice. Multichannel EEG recorded from the scalp surface provides a very valuable but indirect information about the source distribution. However, deep electrode measurements yield more reliable information about the source locations، Intracranial recordings and scalp EEG are used with the source imaging techniques to determine the locations and strengths of the epileptic activity. As a source localization method, Low Resolution Electro-Magnetic Tomography (LORETA) is solved for the realistic geometry based on both forward methods, the Boundary Element Method (BEM) and the Finite Difference Method (FDM). In this paper, we review The findings EEG- LORETA about epilepsy.

Keywords: epilepsy, EEG, EEG-LORETA

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13899 Mine Project Evaluations in the Rising of Uncertainty: Real Options Analysis

Authors: I. Inthanongsone, C. Drebenstedt, J. C. Bongaerts, P. Sontamino

Abstract:

The major concern in evaluating the value of mining projects related to the deficiency of the traditional discounted cash flow (DCF) method. This method does not take uncertainties into account and, hence it does not allow for an economic assessment of managerial flexibility and operational adaptability, which are increasingly determining long-term corporate success. Such an assessment can be performed with the real options valuation (ROV) approach, since it allows for a comparative evaluation of unforeseen uncertainties in a project life cycle. This paper presents an economic evaluation model for open pit mining projects based on real options valuation approach. Uncertainties in the model are caused by metal prices and cost uncertainties and the system dynamics (SD) modeling method is used to structure and solve the real options model. The model is applied to a case study. It can be shown that that managerial flexibility reacting to uncertainties may create additional value to a mining project in comparison to the outcomes of a DCF method. One important insight for management dealing with uncertainty is seen in choosing the optimal time to exercise strategic options.

Keywords: DCF methods, ROV approach, system dynamics modeling methods, uncertainty

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13898 The Effect of Different Surface Cleaning Methods on Porosity Formation and Mechanical Property of AA6xxx Aluminum Gas Metal Arc Welds

Authors: Fatemeh Mirakhorli

Abstract:

Porosity is the main issue during welding of aluminum alloys, and surface cleaning has a critical influence to reduce the porosity level by removing the oxidized surface layer before fusion welding. Developing an optimum and economical surface cleaning method has an enormous benefit for aluminum welding industries to reduce costs related to repairing and repeating welds as well as increasing the mechanical properties of the joints. In this study, several mechanical and chemical surface cleaning methods were examined for butt joint welding of 2 mm thick AA6xxx alloys using ER5556 filler metal. The effects of each method on porosity formation and tensile properties are evaluated. It has been found that, compared to the conventional mechanical cleaning method, the use of chemical cleaning leads to an important reduction in porosity level even after a significant delay between cleaning and welding. The effect of the higher porosity level in the fusion zone to reduce the tensile strength of the welds is shown.

Keywords: gas metal arc welding (GMAW), aluminum alloy, surface cleaning, porosity formation, mechanical property

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13897 Effect of Open-Ended Laboratory toward Learners Performance in Environmental Engineering Course: Case Study of Civil Engineering at Universiti Malaysia Sabah

Authors: N. Bolong, J. Makinda, I. Saad

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Laboratory activities have produced benefits in student learning. With current drives of new technology resources and evolving era of education methods, renewal status of learning and teaching in laboratory methods are in progress, for both learners and the educators. To enhance learning outcomes in laboratory works particularly in engineering practices and testing, learning via hands-on by instruction may not sufficient. This paper describes and compares techniques and implementation of traditional (expository) with open-ended laboratory (problem-based) for two consecutive cohorts studying environmental laboratory course in civil engineering program. The transition of traditional to problem-based findings and effect were investigated in terms of course assessment student feedback survey, course outcome learning measurement and student performance grades. It was proved that students have demonstrated better performance in their grades and 12% increase in the course outcome (CO) in problem-based open-ended laboratory style than traditional method; although in perception, students has responded less favorable in their feedback.

Keywords: engineering education, open-ended laboratory, environmental engineering lab

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13896 Transfer Rate of Organic Water Contaminants through a Passive Sampler Membrane of Polyethersulfone (PES)

Authors: Hamidreza Sharifan, Audra Morse

Abstract:

Accurate assessments of contaminant concentrations based on traditional grab sampling methods are not always possible. Passive samplers offer an attractive alternative to traditional sampling methods that overcomes these limitations. The POCIS approach has been used as a screening tool for determining the presence/absence, possible sources and relative amounts of organic compounds at field sites. The objective for the present research is on mass transfer of five water contaminants (atrazine, caffeine, bentazon, ibuprofen, atenolol) through the Water Boundary Layer (WBL) and membrane. More specific objectives followed by establishing a relationship between the sampling rate and water solubility of the compounds, as well as comparing the molecular weight of the compounds and concentration of the compounds at the time of equilibrium. To determine whether water boundary layer effects transport rate through the membrane is another main objective in this paper. After GC mass analysis of compounds, regarding the WBL effect in this experiment, Sherwood number for the experimental tank developed. A close relationship between feed concentration of compound and sampling rate has been observed.

Keywords: passive sampler, water contaminants, PES-transfer rate, contaminant concentrations

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13895 Flavonoids: Essential Players in Nutrition

Authors: D. Baranova, E. Neborak

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Polyphenols, particularly flavonoids like quercetin, fisetin, and kaempferol, have gained significant attention in nutrition due to their antioxidant, senolytic, and anti-inflammatory properties. These compounds are commonly found in various plant-based foods and are represented by diverse subclasses, each with unique health benefits. Understanding their absorption, metabolism, and bioactivity within the human body is crucial for unlocking their full potential. Quercetin, for instance, exists in multiple forms, impacting its solubility and absorption in the intestine. Its intake, often derived from sources like apples, is affected by cooking methods, with medium heat retaining its potency. Fisetin, also present in fruits and vegetables, demonstrates neuroprotective qualities and stability under varied conditions compared to quercetin. Similarly, kaempferol, found in fruits and vegetables, displays antioxidative effects but is influenced by cooking techniques, with specific methods preserving its polyphenolic content better. Overall, these polyphenols offer promising health benefits, yet their optimal dosage and specific dietary recommendations warrant further research to harness their full nutritional potential.

Keywords: polyphenols, flavonoids, absorption, quercetin, kaempferol, fisetin, senolytics, absorption, cooking method

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13894 Assessing Artificial Neural Network Models on Forecasting the Return of Stock Market Index

Authors: Hamid Rostami Jaz, Kamran Ameri Siahooei

Abstract:

Up to now different methods have been used to forecast the index returns and the index rate. Artificial intelligence and artificial neural networks have been one of the methods of index returns forecasting. This study attempts to carry out a comparative study on the performance of different Radial Base Neural Network and Feed-Forward Perceptron Neural Network to forecast investment returns on the index. To achieve this goal, the return on investment in Tehran Stock Exchange index is evaluated and the performance of Radial Base Neural Network and Feed-Forward Perceptron Neural Network are compared. Neural networks performance test is applied based on the least square error in two approaches of in-sample and out-of-sample. The research results show the superiority of the radial base neural network in the in-sample approach and the superiority of perceptron neural network in the out-of-sample approach.

Keywords: exchange index, forecasting, perceptron neural network, Tehran stock exchange

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13893 Sustainable Renovation and Restoration of the Rural — Based on the View Point of Psychology

Authors: Luo Jin China, Jin Fang

Abstract:

Countryside has been generally recognized and regarded as a characteristic symbol which presents in human memory for a long time. As a result of the change of times, because of it’s failure to meet the growing needs of the growing life and mental decline, the vast rural area began to decline. But their history feature image which accumulated by the ancient tradition provides people with the origins of existence on the spiritual level, such as "identity" and "belonging", makes people closer to the others in the spiritual and psychological aspects of a common experience about the past, thus the sense of a lack of culture caused by the losing of memory symbols is weakened. So, in the modernization process, how to repair its vitality and transform and planning it in a sustainable way has become a hot topics in architectural and urban planning. This paper aims to break the constraints of disciplines, from the perspective of interdiscipline, using the research methods of systems science to analyze and discuss the theories and methods of rural form factors, which based on the viewpoint of memory in psychology. So, we can find a right way to transform the Rural to give full play to the role of the countryside in the actual use and the shape of history spirits.

Keywords: rural, sustainable renovation, restoration, psychology, memory

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13892 System Identification in Presence of Outliers

Authors: Chao Yu, Qing-Guo Wang, Dan Zhang

Abstract:

The outlier detection problem for dynamic systems is formulated as a matrix decomposition problem with low-rank, sparse matrices and further recast as a semidefinite programming (SDP) problem. A fast algorithm is presented to solve the resulting problem while keeping the solution matrix structure and it can greatly reduce the computational cost over the standard interior-point method. The computational burden is further reduced by proper construction of subsets of the raw data without violating low rank property of the involved matrix. The proposed method can make exact detection of outliers in case of no or little noise in output observations. In case of significant noise, a novel approach based on under-sampling with averaging is developed to denoise while retaining the saliency of outliers and so-filtered data enables successful outlier detection with the proposed method while the existing filtering methods fail. Use of recovered “clean” data from the proposed method can give much better parameter estimation compared with that based on the raw data.

Keywords: outlier detection, system identification, matrix decomposition, low-rank matrix, sparsity, semidefinite programming, interior-point methods, denoising

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13891 A Framework of Dynamic Rule Selection Method for Dynamic Flexible Job Shop Problem by Reinforcement Learning Method

Authors: Rui Wu

Abstract:

In the volatile modern manufacturing environment, new orders randomly occur at any time, while the pre-emptive methods are infeasible. This leads to a real-time scheduling method that can produce a reasonably good schedule quickly. The dynamic Flexible Job Shop problem is an NP-hard scheduling problem that hybrid the dynamic Job Shop problem with the Parallel Machine problem. A Flexible Job Shop contains different work centres. Each work centre contains parallel machines that can process certain operations. Many algorithms, such as genetic algorithms or simulated annealing, have been proposed to solve the static Flexible Job Shop problems. However, the time efficiency of these methods is low, and these methods are not feasible in a dynamic scheduling problem. Therefore, a dynamic rule selection scheduling system based on the reinforcement learning method is proposed in this research, in which the dynamic Flexible Job Shop problem is divided into several parallel machine problems to decrease the complexity of the dynamic Flexible Job Shop problem. Firstly, the features of jobs, machines, work centres, and flexible job shops are selected to describe the status of the dynamic Flexible Job Shop problem at each decision point in each work centre. Secondly, a framework of reinforcement learning algorithm using a double-layer deep Q-learning network is applied to select proper composite dispatching rules based on the status of each work centre. Then, based on the selected composite dispatching rule, an available operation is selected from the waiting buffer and assigned to an available machine in each work centre. Finally, the proposed algorithm will be compared with well-known dispatching rules on objectives of mean tardiness, mean flow time, mean waiting time, or mean percentage of waiting time in the real-time Flexible Job Shop problem. The result of the simulations proved that the proposed framework has reasonable performance and time efficiency.

Keywords: dynamic scheduling problem, flexible job shop, dispatching rules, deep reinforcement learning

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13890 Bayesian Using Markov Chain Monte Carlo and Lindley's Approximation Based on Type-I Censored Data

Authors: Al Omari Moahmmed Ahmed

Abstract:

These papers describe the Bayesian Estimator using Markov Chain Monte Carlo and Lindley’s approximation and the maximum likelihood estimation of the Weibull distribution with Type-I censored data. The maximum likelihood method can’t estimate the shape parameter in closed forms, although it can be solved by numerical methods. Moreover, the Bayesian estimates of the parameters, the survival and hazard functions cannot be solved analytically. Hence Markov Chain Monte Carlo method and Lindley’s approximation are used, where the full conditional distribution for the parameters of Weibull distribution are obtained via Gibbs sampling and Metropolis-Hastings algorithm (HM) followed by estimate the survival and hazard functions. The methods are compared to Maximum Likelihood counterparts and the comparisons are made with respect to the Mean Square Error (MSE) and absolute bias to determine the better method in scale and shape parameters, the survival and hazard functions.

Keywords: weibull distribution, bayesian method, markov chain mote carlo, survival and hazard functions

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13889 Enhanced Extra Trees Classifier for Epileptic Seizure Prediction

Authors: Maurice Ntahobari, Levin Kuhlmann, Mario Boley, Zhinoos Razavi Hesabi

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For machine learning based epileptic seizure prediction, it is important for the model to be implemented in small implantable or wearable devices that can be used to monitor epilepsy patients; however, current state-of-the-art methods are complex and computationally intensive. We use Shapley Additive Explanation (SHAP) to find relevant intracranial electroencephalogram (iEEG) features and improve the computational efficiency of a state-of-the-art seizure prediction method based on the extra trees classifier while maintaining prediction performance. Results for a small contest dataset and a much larger dataset with continuous recordings of up to 3 years per patient from 15 patients yield better than chance prediction performance (p < 0.004). Moreover, while the performance of the SHAP-based model is comparable to that of the benchmark, the overall training and prediction time of the model has been reduced by a factor of 1.83. It can also be noted that the feature called zero crossing value is the best EEG feature for seizure prediction. These results suggest state-of-the-art seizure prediction performance can be achieved using efficient methods based on optimal feature selection.

Keywords: machine learning, seizure prediction, extra tree classifier, SHAP, epilepsy

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13888 Creative Skills Supported by Multidisciplinary Learning: Case Innovation Course at the Seinäjoki University of Applied Sciences

Authors: Satu Lautamäki

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This paper presents findings from a multidisciplinary course (bachelor level) implemented at Seinäjoki University of Applied Sciences, Finland. The course aims to develop innovative thinking of students, by having projects given by companies, using design thinking methods as a tool for creativity and by integrating students into multidisciplinary teams working on the given projects. The course is obligatory for all first year bachelor students across four faculties (business and culture, food and agriculture, health care and social work, and technology). The course involves around 800 students and 30 pedagogical coaches, and it is implemented as an intensive one-week course each year. The paper discusses the pedagogy, structure and coordination of the course. Also, reflections on methods for the development of creative skills are given. Experts in contemporary, global context often work in teams, which consist of people who have different areas of expertise and represent various professional backgrounds. That is why there is a strong need for new training methods where multidisciplinary approach is at the heart of learning. Creative learning takes place when different parties bring information to the discussion and learn from each other. When students in different fields are looking for professional growth for themselves and take responsibility for the professional growth of other learners, they form a mutual learning relationship with each other. Multidisciplinary team members make decisions both individually and collectively, which helps them to understand and appreciate other disciplines. Our results show that creative and multidisciplinary project learning can develop diversity of knowledge and competences, for instance, students’ cultural knowledge, teamwork and innovation competences, time management and presentation skills as well as support a student’s personal development as an expert. It is highly recommended that higher education curricula should include various studies for students from different study fields to work in multidisciplinary teams.

Keywords: multidisciplinary learning, creative skills, innovative thinking, project-based learning

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13887 Reservoir Fluids: Occurrence, Classification, and Modeling

Authors: Ahmed El-Banbi

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Several PVT models exist to represent how PVT properties are handled in sub-surface and surface engineering calculations for oil and gas production. The most commonly used models include black oil, modified black oil (MBO), and compositional models. These models are used in calculations that allow engineers to optimize and forecast well and reservoir performance (e.g., reservoir simulation calculations, material balance, nodal analysis, surface facilities, etc.). The choice of which model is dependent on fluid type and the production process (e.g., depletion, water injection, gas injection, etc.). Based on close to 2,000 reservoir fluid samples collected from different basins and locations, this paper presents some conclusions on the occurrence of reservoir fluids. It also reviews the common methods used to classify reservoir fluid types. Based on new criteria related to the production behavior of different fluids and economic considerations, an updated classification of reservoir fluid types is presented in the paper. Recommendations on the use of different PVT models to simulate the behavior of different reservoir fluid types are discussed. Each PVT model requirement is highlighted. Available methods for the calculation of PVT properties from each model are also discussed. Practical recommendations and tips on how to control the calculations to achieve the most accurate results are given.

Keywords: PVT models, fluid types, PVT properties, fluids classification

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13886 The Effectiveness of Self-Compassion Training: A Field Trial Study

Authors: Esmaeil Sarikhani

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Objectives: Considering the importance of introducing new methods of improving self-compassion and compassion to the others in nursing students, this study intends to evaluate the effect of self-compassion training on nursing students. Methods: This is a field trial study in which 52 nursing interns from Isfahan University of Medical Sciences were selected using convenience sampling method and divided in two experimental and control groups. The sampling was done during two phases: before and after the intervention. The intervention consisted of eight sessions over eight weeks of self-compassion training. The data were collected using the self-compassion standard questionnaire with 26 questions before and after the intervention. Data were then analyzed by the SPSS18 software and independent and paired T-tests, and also Chi-square and Mann-Whitney tests. Results: The results obtained from the independent t-test showed that the mean score of self-compassion and its components in the experimental group was significantly increased compared to the control group (p < 0.001). Comparing the groups, the mean overall score difference of self-compassion and its components had also a statistically significant change after the intervention (p < 0.001). Conclusion: Self-compassion training program, leads to improving nursing students' self-compassion. As it seems, this method can be used as an important training course in order to improve compassion of nursing students to themselves and the others.

Keywords: self-compassion, student, nursing students, field trial

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13885 Comparative Analysis of Enzyme Activities Concerned in Decomposition of Toluene

Authors: Ayuko Itsuki, Sachiyo Aburatani

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In recent years, pollutions of the environment by toxic substances become a serious problem. While there are many methods of environmental clean-up, the methods by microorganisms are considered to be reasonable and safety for environment. Compost is known that it catabolize the meladorous substancess in its production process, however the mechanism of its catabolizing system is not known yet. In the catabolization process, organic matters turn into inorganic by the released enzymes from lots of microorganisms which live in compost. In other words, the cooperative of activated enzymes in the compost decomposes malodorous substances. Thus, clarifying the interaction among enzymes is important for revealing the catabolizing system of meladorous substance in compost. In this study, we utilized statistical method to infer the interaction among enzymes. We developed a method which combined partial correlation with cross correlation to estimate the relevance between enzymes especially from time series data of few variables. Because of using cross correlation, we can estimate not only the associative structure but also the reaction pathway. We applied the developed method to the enzyme measured data and estimated an interaction among the enzymes in decomposition mechanism of toluene.

Keywords: enzyme activities, comparative analysis, compost, toluene

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13884 Importance of Assessing Racial Trauma after George Floyd in Children of Color in Schools

Authors: Gabriela Macera DiFilippo

Abstract:

The world watched in disbelief as George Floyd was killed by a policeman. The images from the scene were made more memorable by Mr. Floyd’s pleas and cries for his mother. In the aftermath of this tragedy, the Black Lives Matter movement gained momentum. Weeks and months after the protests, global interest in learning about tackling systemic racism erupted. One must wonder how school children of color viewed and processed this trauma. This study will examine the kinds of trauma experienced by children of color and the opportunity for school mental health providers to support these children. This study used literature searches that were previously conducted for proven and practical assessment methods that can help deal with racial trauma for children. As part of the assessment, trauma symptoms experienced by children of color were summarized and characterized in a non-imperial manner. The research was also will be done in practical ways to make adequate and effective mental health services available in schools and lessen the stigma. This research study found that there is a need to provide an analysis of the ongoing racial trauma of children of color after the death of George Floyd. Impactful and appropriate assessment methods, such as surveys, were presented to all school professionals. Lastly, this paper attempted to provide mental health professionals with the tools to screen and provide guidance based on unequivocal, unbiased methods for helping these children. There is a need for both schools and community leaders to ensure that every child has access to mental health care and is being assessed for their overall well-being. There is a need to educate the communities about racial trauma and its impact on individuals, especially children. School mental health professionals are encouraged to offer and educate schools and communities about racial trauma awareness, its importance, and ways to cope with it in different settings. The delivery of these informed services should focus on behavioral health and must be sensitive to children of color and different ways of self-care.

Keywords: trauma, children, black psychology, students

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13883 Evaluation of Two DNA Extraction Methods for Minimal Porcine (Pork) Detection in Halal Food Sample Mixture Using Taqman Real-time PCR Technique

Authors: Duaa Mughal, Syeda Areeba Nadeem, Shakil Ahmed, Ishtiaq Ahmed Khan

Abstract:

The identification of porcine DNA in Halal food items is critical to ensuring compliance with dietary restrictions and religious beliefs. In Islam, Porcine is prohibited as clearly mentioned in Quran (Surah Al-Baqrah, Ayat 173). The purpose of this study was to compare two DNA extraction procedures for detecting 0.001% of porcine DNA in processed Halal food sample mixtures containing chicken, camel, veal, turkey and goat meat using the TaqMan Real-Time PCR technology. In this research, two different commercial kit protocols were compared. The processed sample mixtures were prepared by spiking known concentration of porcine DNA to non-porcine food matrices. Afterwards, TaqMan Real-Time PCR technique was used to target a particular porcine gene from the extracted DNA samples, which was quantified after extraction. The results of the amplification were evaluated for sensitivity, specificity, and reproducibility. The results of the study demonstrated that two DNA extraction techniques can detect 0.01% of porcine DNA in mixture of Halal food samples. However, as compared to the alternative approach, Eurofins| GeneScan GeneSpin DNA Isolation kit showed more effective sensitivity and specificity. Furthermore, the commercial kit-based approach showed great repeatability with minimal variance across repeats. Quantification of DNA was done by using fluorometric assay. In conclusion, the comparison of DNA extraction methods for detecting porcine DNA in Halal food sample mixes using the TaqMan Real-Time PCR technology reveals that the commercial kit-based approach outperforms the other methods in terms of sensitivity, specificity, and repeatability. This research helps to promote the development of reliable and standardized techniques for detecting porcine DNA in Halal food items, religious conformity and assuring nutritional.

Keywords: real time PCR (qPCR), DNA extraction, porcine DNA, halal food authentication, religious conformity

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13882 Assessment of Soil Quality Indicators in Rice Soils Under Rainfed Ecosystem

Authors: R. Kaleeswari

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An investigation was carried out to assess the soil biological quality parameters in rice soils under rainfed and to compare soil quality indexing methods viz., Principal component analysis, Minimum data set and Indicator scoring method and to develop soil quality indices for formulating soil and crop management strategies.Soil samples were collected and analyzed for soil biological properties by adopting standard procedure. Biological indicators were determined for soil quality assessment, viz., microbial biomass carbon and nitrogen (MBC and MBN), potentially mineralizable nitrogen (PMN) and soil respiration and dehydrogenease activity. Among the methods of rice cultivation, Organic nutrition, Integrated Nutrient Management (INM) and System of Rice Intensification (SRI ), rice cultivation registered higher values of MBC, MBN and PMN. Mechanical and conventional rice cultivation registered lower values of biological quality indicators. Organic nutrient management and INM enhanced the soil respiration rate. SRI and aerobic rice cultivation methods increased the rate of soil respiration, while conventional and mechanical rice farming lowered the soil respiration rate. Dehydrogenase activity (DHA) was registered to be higher in soils under organic nutrition and Integrated Nutrient Management INM. System of Rice Intensification SRI and aerobic rice cultivation enhanced the DHA; while conventional and mechanical rice cultivation methods reduced DHA. The microbial biomass carbon (MBC) of the rice soils varied from 65 to 244 mg kg-1. Among the nutrient management practices, INM registered the highest available microbial biomass carbon of 285 mg kg-1.Potentially mineralizable N content of the rice soils varied from 20.3 to 56.8 mg kg-1. Aerobic rice farming registered the highest potentially mineralizable N of 78.9 mg kg-1..The soil respiration rate of the rice soils varied from 60 to 125 µgCO2 g-1. Nutrient management practices ofINM practice registered the highest. soil respiration rate of 129 µgCO2 g-1.The dehydrogenase activity of the rice soils varied from 38.3 to 135.3µgTPFg-1 day-1. SRI method of rice cultivation registered the highest dehydrogenase activity of 160.2 µgTPFg-1 day-1. Soil variables from each PC were considered for minimum soil data set (MDS). Principal component analysis (PCA) was used to select the representative soil quality indicators. In intensive rice cultivating regions, soil quality indicators were selected based on factor loading value and contribution percentage value using principal component analysis (PCA).Variables having significant difference within production systems were used for the preparation of minimum data set (MDS).

Keywords: soil quality, rice, biological properties, PCA analysis

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13881 An Exploratory Case Study of Pre-Service Teachers' Learning to Teach Mathematics to Culturally Diverse Students through a Community-Based After-School Field Experience

Authors: Eugenia Vomvoridi-Ivanovic

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It is broadly assumed that participation in field experiences will help pre-service teachers (PSTs) bridge theory to practice. However, this is often not the case since PSTs who are placed in classrooms with large numbers of students from diverse linguistic, cultural, racial, and ethnic backgrounds (culturally diverse students (CDS)) usually observe ineffective mathematics teaching practices that are in contrast to those discussed in their teacher preparation program. Over the past decades, the educational research community has paid increasing attention to investigating out-of-school learning contexts and how participation in such contexts can contribute to the achievement of underrepresented groups in Science, Technology, Engineering, and mathematics (STEM) education and their expanded participation in STEM fields. In addition, several research studies have shown that students display different kinds of mathematical behaviors and discourse practices in out-of-school contexts than they do in the typical mathematics classroom since they draw from a variety of linguistic and cultural resources to negotiate meanings and participate in joint problem solving. However, almost no attention has been given to exploring these contexts as field experiences for pre-service mathematics teachers. The purpose of this study was to explore how participation in a community based after-school field experience promotes understanding of the content pedagogy concepts introduced in elementary mathematics methods courses, particularly as they apply to teaching mathematics to CDS. This study draws upon a situated, socio-cultural theory of teacher learning that centers on the concept of learning as situated social practice, which includes discourse, social interaction, and participation structures. Consistent with exploratory case study methodology, qualitative methods were employed to investigate how a cohort of twelve participating pre-service teacher's approach to pedagogy and their conversations around teaching and learning mathematics to CDS evolved through their participation in the after-school field experience, and how they connected the content discussed in their mathematics methods course with their interactions with the CDS in the after-school. Data were collected over a period of one academic year from the following sources: (a) audio recordings of the PSTs' interactions with the students during the after-school sessions, (b) PSTs' after-school field-notes, (c) audio-recordings of weekly methods course meetings, and (d) other document data (e.g., PST and student generated artifacts, PSTs' written course assignments). The findings of this study reveal that the PSTs benefitted greatly through their participation in the after-school field experience. Specifically, after-school participation promoted a deeper understanding of the content pedagogy concepts introduced in the mathematics methods course and gained a greater appreciation for how students learn mathematics with understanding. Further, even though many of PSTs' assumptions about the mathematical abilities of CDS were challenged and PSTs began to view CDSs' cultural and linguistic backgrounds as resources (rather than obstacles) for learning, some PSTs still held negative stereotypes about CDS and teaching and learning mathematics to CDS in particular. Insights gained through this study contribute to a better understanding of how informal mathematics learning contexts may provide a valuable context for pre-service teacher's learning to teach mathematics to CDS.

Keywords: after-school mathematics program, pre-service mathematical education of teachers, qualitative methods, situated socio-cultural theory, teaching culturally diverse students

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13880 The Child Attachment Interview: A Psychometric Longitudinal Validation Study in a German Sample

Authors: Jorn Meyer, Stefan Sturmer

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The assessment of attachment patterns in toddlers and adults has been well researched, and valid diagnostic methods (e.g., Strange Situation Test, Adult Attachment Interview) are applicable. For middle and late childhood, on the other hand, there are only few validated methods available so far. For the Child Attachment Interview (CAI) promising validation studies from English-speaking countries are available, but so far a comprehensive study on the validity of a German sample is lacking. Within the scope of a longitudinal project, the results of the first point of measurement are reported in this study. A German-language version of the CAI was carried out with 111 primary school children (56% female; age: M = 8.34, SD = 0.49). In relation to psychometric quality criteria, parameters on interrater reliability, construct validity and discriminant, and convergent validity are reported. Analyses of the correlations between attachment patterns and internalizing and externalizing behavior problems from parent and teacher reports are presented. The implications for the German-language assessment of attachment in middle and late childhood in research and individual case diagnostics, e.g., in the context of conducting expert evaluation reports for family courts, are discussed.

Keywords: attachment, attachment assessment, developmental psychology, longitudinal study

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13879 The Relationship between Psychological Capital and Mental Health in Economically Disadvantaged Youth: The Mediating Role of Family Cohesion

Authors: Chang Li-Yu

Abstract:

Aims: This study investigates the impact of psychological capital on the mental health of economically disadvantaged youth and examines whether family cohesion acts as a mediating variable between psychological capital and mental health. Methods: The sample for the study was drawn from the "Taiwan Poverty Children's Database: Survey on the Living Trends of Disadvantaged Children and Youth." The data analysis methods included descriptive statistics, confirmatory factor analysis, and structural equation modeling. Results: The results indicated that both psychological capital and family cohesion can significantly negatively predict mental health, with psychological capital significantly positively predicting family cohesion. The mediation effect analysis revealed that family cohesion fully mediates the relationship between psychological capital and mental health, meaning that psychological capital influences mental health through family cohesion. Recommendations: Based on these findings, the study concretely discusses the significance of psychological capital and family cohesion for the mental health of economically disadvantaged youth and offers suggestions for psychological counseling, therapy, and future research.

Keywords: psychological capital, mental health, economically disadvantaged youth, family cohesion

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13878 Theory and Practice of Wavelets in Signal Processing

Authors: Jalal Karam

Abstract:

The methods of Fourier, Laplace, and Wavelet Transforms provide transfer functions and relationships between the input and the output signals in linear time invariant systems. This paper shows the equivalence among these three methods and in each case presenting an application of the appropriate (Fourier, Laplace or Wavelet) to the convolution theorem. In addition, it is shown that the same holds for a direct integration method. The Biorthogonal wavelets Bior3.5 and Bior3.9 are examined and the zeros distribution of their polynomials associated filters are located. This paper also presents the significance of utilizing wavelets as effective tools in processing speech signals for common multimedia applications in general, and for recognition and compression in particular. Theoretically and practically, wavelets have proved to be effective and competitive. The practical use of the Continuous Wavelet Transform (CWT) in processing and analysis of speech is then presented along with explanations of how the human ear can be thought of as a natural wavelet transformer of speech. This generates a variety of approaches for applying the (CWT) to many paradigms analysing speech, sound and music. For perception, the flexibility of implementation of this transform allows the construction of numerous scales and we include two of them. Results for speech recognition and speech compression are then included.

Keywords: continuous wavelet transform, biorthogonal wavelets, speech perception, recognition and compression

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13877 Biosurfactant-Mediated Nanoparticle Synthesis by Bacillus subtilis

Authors: Satya Eswari Jujjavarapu, Swasti Dhagat, Lata Upadhyay, Reecha Sahu

Abstract:

Silver nanoparticles have a broad range of antimicrobial and antifungal properties ranging from soaps, pastes to sterilization and drug delivery systems. These can be synthesized by physical, chemical and biological methods; biological methods being the most popular owing to their non-toxic nature and reduced energy requirements. Microbial surfactants, produced on the microbial cell surface or excreted extracellularly are an alternative to synthetic surfactants for the production of silver nanoparticles. Hence, they are also called as green molecules. Microbial lipopeptide surfactants (biosurfactant) exhibit anti-tumor and anti-microbial properties and can be used as drug delivery agents. In this study, biosurfactant was synthesized by using a strain of acillus subtilis. The biosurfactant thus produced was analysed by emulsification assay, oil spilling test, and haemolytic test. Biosurfactant-mediated silver nanoparticles were synthesised by microwave irradiation of the culture supernatant and further characterized by UV–vis spectroscopy for a range of 400-600 nm. The UV–vis spectra showed a surface plasmon resonance vibration band at 410 nm corresponding to the peak of silver nanoparticles.

Keywords: biosurfactant, Bacillus subtilis, silver nano particle, lipopeptide

Procedia PDF Downloads 242
13876 The Assessment of the Comparative Efficiency of Reforms through the Integral Index of Transformation

Authors: Samson Davoyan, Ashot Davoyan, Ani Khachatryan

Abstract:

The indexes (Global Competitiveness Index, Economic Freedom Index, Human Development Index, etc.) developed by different international and non-government organizations in time and space express the quantitative and qualitative features of different fields of various reforms implemented in different countries. The main objective of our research is to develop new methodology that we will use to create integral index based on many indexes and that will include many areas of reforms. To achieve our aim we have used econometric methods (regression model for panel data method). The basis of our methodology is the development of the new integral index based on quantitative assessment of the change of two main parameters: the score of the countries by different indexes and the change of the ranks of countries for following two periods of time. As a result of the usage of methods for analyzes we have defined the indexes that are used to create the new integral index and the scales for each of them. Analyzing quantitatively and qualitatively analysis through the integral index for more than 100 countries for 2009-2014, we have defined comparative efficiency that helps to conclude in which directions countries have implemented reforms more effectively compared to others and in which direction reforms have implemented less efficiently.

Keywords: development, rank, reforms, comparative, index, economic, corruption, social, program

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13875 The Impact of the Flipped Classroom Instructional Model on MPharm Students in Two Pharmacy Schools in the UK

Authors: Mona Almanasef, Angel Chater, Jane Portlock

Abstract:

Introduction: A 'flipped classroom' uses technology to shift the traditional lecture outside the scheduled class time and uses the face-to-face time to engage students in interactive activities. Aim of the Study: Assess the feasibility, acceptability, and effectiveness of using the 'flipped classroom' teaching format with MPharm students in two pharmacy schools in the UK: UCL School of Pharmacy and the School of Pharmacy and Biomedical Sciences at University of Portsmouth. Methods: An experimental mixed methods design was employed, with final year MPharm students in two phases; 1) a qualitative study using focus groups, 2) a quasi-experiment measuring knowledge acquisition and satisfaction by delivering a session on rheumatoid arthritis, in two teaching formats: the flipped classroom and the traditional lecture. Results: The flipped classroom approach was preferred over the traditional lecture for delivering a pharmacy practice topic, and it was comparable or better than the traditional lecture with respect to knowledge acquisition. In addition, this teaching approach was found to overcome the perceived challenges of the traditional lecture method such as fast pace instructions, student disengagement and boredom due to lack of activities and/or social anxiety. However, high workload and difficult or new concepts could be barriers to pre-class preparation, and therefore successful flipped classroom. The flipped classroom encouraged learning scaffolding where students could benefit from application of knowledge, and interaction with peers and the lecturer, which might, in turn, facilitate learning consolidation and deep understanding. This research indicated that the flipped classroom was beneficial for all learning styles. Conclusion: Implementing the flipped classroom at both pharmacy institutions was successful and well received by final year MPharm students. Given the attention now being put on the Teaching Excellence Framework (TEF), understanding effective methods of teaching to enhance student achievement and satisfaction is now more valuable than ever.

Keywords: blended learning, flipped classroom, inverted classroom, pharmacy education

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13874 Non-Invasive Imaging of Tissue Using Near Infrared Radiations

Authors: Ashwani Kumar Aggarwal

Abstract:

NIR Light is non-ionizing and can pass easily through living tissues such as breast without any harmful effects. Therefore, use of NIR light for imaging the biological tissue and to quantify its optical properties is a good choice over other invasive methods. Optical tomography involves two steps. One is the forward problem and the other is the reconstruction problem. The forward problem consists of finding the measurements of transmitted light through the tissue from source to detector, given the spatial distribution of absorption and scattering properties. The second step is the reconstruction problem. In X-ray tomography, there is standard method for reconstruction called filtered back projection method or the algebraic reconstruction methods. But this method cannot be applied as such, in optical tomography due to highly scattering nature of biological tissue. A hybrid algorithm for reconstruction has been implemented in this work which takes into account the highly scattered path taken by photons while back projecting the forward data obtained during Monte Carlo simulation. The reconstructed image suffers from blurring due to point spread function. This blurred reconstructed image has been enhanced using a digital filter which is optimal in mean square sense.

Keywords: least-squares optimization, filtering, tomography, laser interaction, light scattering

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13873 Petra: Simplified, Scalable Verification Using an Object-Oriented, Compositional Process Calculus

Authors: Aran Hakki, Corina Cirstea, Julian Rathke

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Formal methods are yet to be utilized in mainstream software development due to issues in scaling and implementation costs. This work is about developing a scalable, simplified, pragmatic, formal software development method with strong correctness properties and guarantees that are easy prove. The method aims to be easy to learn, use and apply without extensive training and experience in formal methods. Petra is proposed as an object-oriented, process calculus with composable data types and sequential/parallel processes. Petra has a simple denotational semantics, which includes a definition of Correct by Construction. The aim is for Petra is to be standard which can be implemented to execute on various mainstream programming platforms such as Java. Work towards an implementation of Petra as a Java EDSL (Embedded Domain Specific Language) is also discussed.

Keywords: compositionality, formal method, software verification, Java, denotational semantics, rewriting systems, rewriting semantics, parallel processing, object-oriented programming, OOP, programming language, correct by construction

Procedia PDF Downloads 147
13872 An Implementation of Multi-Media Applications in Teaching Structural Design to Architectural Students

Authors: Wafa Labib

Abstract:

Teaching methods include lectures, workshops and tutorials for the presentation and discussion of ideas have become out of date; were developed outside the discipline of architecture from the college of engineering and do not satisfy the architectural students’ needs and causes them many difficulties in integrating structure into their design. In an attempt to improve structure teaching methods, this paper focused upon proposing a supportive teaching/learning tool using multi-media applications which seeks to better meet the architecture student’s needs and capabilities and improve the understanding and application of basic and intermediate structural engineering and technology principles. Before introducing the use of multi-media as a supportive teaching tool, a questionnaire was distributed to third year students of a structural design course who were selected as a sample to be surveyed forming a sample of 90 cases. The primary aim of the questionnaire was to identify the students’ learning style and to investigate whether the selected method of teaching could make the teaching and learning process more efficient. Students’ reaction on the use of this method was measured using three key elements indicating that this method is an appropriate teaching method for the nature of the students and the course as well.

Keywords: teaching method, architecture, learning style, multi-media

Procedia PDF Downloads 442