Search results for: linear matrix inequality
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5636

Search results for: linear matrix inequality

1196 Empirical Modeling and Optimization of Laser Welding of AISI 304 Stainless Steel

Authors: Nikhil Kumar, Asish Bandyopadhyay

Abstract:

Laser welding process is a capable technology for forming the automobile, microelectronics, marine and aerospace parts etc. In the present work, a mathematical and statistical approach is adopted to study the laser welding of AISI 304 stainless steel. A robotic control 500 W pulsed Nd:YAG laser source with 1064 nm wavelength has been used for welding purpose. Butt joints are made. The effects of welding parameters, namely; laser power, scanning speed and pulse width on the seam width and depth of penetration has been investigated using the empirical models developed by response surface methodology (RSM). Weld quality is directly correlated with the weld geometry. Twenty sets of experiments have been conducted as per central composite design (CCD) design matrix. The second order mathematical model has been developed for predicting the desired responses. The results of ANOVA indicate that the laser power has the most significant effect on responses. Microstructural analysis as well as hardness of the selected weld specimens has been carried out to understand the metallurgical and mechanical behaviour of the weld. Average micro-hardness of the weld is observed to be higher than the base metal. Higher hardness of the weld is the resultant of grain refinement and δ-ferrite formation in the weld structure. The result suggests that the lower line energy generally produce fine grain structure and improved mechanical properties than the high line energy. The combined effects of input parameters on responses have been analyzed with the help of developed 3-D response surface and contour plots. Finally, multi-objective optimization has been conducted for producing weld joint with complete penetration, minimum seam width and acceptable welding profile. Confirmatory tests have been conducted at optimum parametric conditions to validate the applied optimization technique.

Keywords: ANOVA, laser welding, modeling and optimization, response surface methodology

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1195 Determining the Factors Affecting Social Media Addiction (Virtual Tolerance, Virtual Communication), Phubbing, and Perception of Addiction in Nurses

Authors: Fatima Zehra Allahverdi, Nukhet Bayer

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Objective: Three questions were formulated to examine stressful working units (intensive care units, emergency unit nurses) utilizing the self-perception theory and social support theory. This study provides a distinctive input by inspecting the combination of variables regarding stressful working environments. Method: The descriptive research was conducted with the participation of 400 nurses working at Ankara City Hospital. The study used Multivariate Analysis of Variance (MANOVA), regression analysis, and a mediation model. Hypothesis one used MANOVA followed by a Scheffe post hoc test. Hypothesis two utilized regression analysis using a hierarchical linear regression model. Hypothesis three used a mediation model. Result: The study utilized mediation analyses. Findings supported the hypotheses that intensive care units have significantly high scores in virtual communication and virtual tolerance. The number of years on the job, virtual communication, virtual tolerance, and phubbing significantly predicted 51% of the variance of perception of addiction. Interestingly, the number of years on the job, while significant, was negatively related to perception of addiction. Conclusion: The reasoning behind these findings and the lack of significance in the emergency unit is discussed. Around 7% of the variance of phubbing was accounted for through working in intensive care units. The model accounted for 26.80 % of the differences in the perception of addiction.

Keywords: phubbing, social media, working units, years on the job, stress

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1194 Optimization of Municipal Solid Waste Management in Peshawar Using Mathematical Modelling and GIS with Focus on Incineration

Authors: Usman Jilani, Ibad Khurram, Irshad Hussain

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Environmentally sustainable waste management is a challenging task as it involves multiple and diverse economic, environmental, technical and regulatory issues. Municipal Solid Waste Management (MSWM) is more challenging in developing countries like Pakistan due to lack of awareness, technology and human resources, insufficient funding, inefficient collection and transport mechanism resulting in the lack of a comprehensive waste management system. This work presents an overview of current MSWM practices in Peshawar, the provincial capital of Khyber Pakhtunkhwa, Pakistan and proposes a better and sustainable integrated solid waste management system with incineration (Waste to Energy) option. The diverted waste would otherwise generate revenue; minimize land fill requirement and negative impact on the environment. The proposed optimized solution utilizing scientific techniques (like mathematical modeling, optimization algorithms and GIS) as decision support tools enhances the technical & institutional efficiency leading towards a more sustainable waste management system through incorporating: - Improved collection mechanisms through optimized transportation / routing and, - Resource recovery through incineration and selection of most feasible sites for transfer stations, landfills and incineration plant. These proposed methods shift the linear waste management system towards a cyclic system and can also be used as a decision support tool by the WSSP (Water and Sanitation Services Peshawar), agency responsible for the MSWM in Peshawar.

Keywords: municipal solid waste management, incineration, mathematical modeling, optimization, GIS, Peshawar

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1193 Simplified Stress Gradient Method for Stress-Intensity Factor Determination

Authors: Jeries J. Abou-Hanna

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Several techniques exist for determining stress-intensity factors in linear elastic fracture mechanics analysis. These techniques are based on analytical, numerical, and empirical approaches that have been well documented in literature and engineering handbooks. However, not all techniques share the same merit. In addition to overly-conservative results, the numerical methods that require extensive computational effort, and those requiring copious user parameters hinder practicing engineers from efficiently evaluating stress-intensity factors. This paper investigates the prospects of reducing the complexity and required variables to determine stress-intensity factors through the utilization of the stress gradient and a weighting function. The heart of this work resides in the understanding that fracture emanating from stress concentration locations cannot be explained by a single maximum stress value approach, but requires use of a critical volume in which the crack exists. In order to understand the effectiveness of this technique, this study investigated components of different notch geometry and varying levels of stress gradients. Two forms of weighting functions were employed to determine stress-intensity factors and results were compared to analytical exact methods. The results indicated that the “exponential” weighting function was superior to the “absolute” weighting function. An error band +/- 10% was met for cases ranging from a steep stress gradient in a sharp v-notch to the less severe stress transitions of a large circular notch. The incorporation of the proposed method has shown to be a worthwhile consideration.

Keywords: fracture mechanics, finite element method, stress intensity factor, stress gradient

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1192 Phase Optimized Ternary Alloy Material for Gas Turbines

Authors: Mayandi Ramanathan

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Gas turbine blades see the most aggressive thermal stress conditions within the engine, due to Turbine Entry Temperatures in the range of 1500 to 1600°C, but in synchronization with other functional components, they must readily deliver efficient performance, whilst incurring minimal overhaul and repair costs during its service life up to 5 million flying miles. The blades rotate at very high rotation rates and remove significant amount of thermal power from the gas stream. At high temperatures the major component failure mechanism is creep. During its service over time under high temperatures and loads, the blade will deform, lengthen and rupture. High strength and stiffness in the longitudinal direction up to elevated service temperatures are certainly the most needed properties of turbine blades. The proposed advanced Ti alloy material needs a process that provides strategic orientation of metallic ordering, uniformity in composition and high metallic strength. 25% Ta/(Al+Ta) ratio ensures TaAl3 phase formation, where as 51% Al/(Al+Ti) ratio ensures formation of α-Ti3Al and γ-TiAl mixed phases fand the three phase combination ensures minimal Al excess (~1.4% Al excess), unlike Ti-47Al-2Cr-2Nb which has significant excess Al (~5% Al excess) that could affect the service life of turbine blades. This presentation will involve the summary of additive manufacturing and heat treatment process conditions to fabricate turbine blade with Ti-43Al matrix alloyed with optimized amount of refractory Ta metal. Summary of thermo-mechanical test results such as high temperature tensile strength, creep strain rate, thermal expansion coefficient and fracture toughness will be presented. Improvement in service temperature of the turbine blades and corrosion resistance dependence on coercivity of the alloy material will be reported. Phase compositions will be quantified, and a summary of its correlation with creep strain rate will be presented.

Keywords: gas turbine, aerospace, specific strength, creep, high temperature materials, alloys, phase optimization

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1191 Optimization Technique for the Contractor’s Portfolio in the Bidding Process

Authors: Taha Anjamrooz, Sareh Rajabi, Salwa Bheiry

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Selection between the available projects in bidding processes for the contractor is one of the essential areas to concentrate on. It is important for the contractor to choose the right projects within its portfolio during the tendering stage based on certain criteria. It should align the bidding process with its origination strategies and goals as a screening process to have the right portfolio pool to start with. Secondly, it should set the proper framework and use a suitable technique in order to optimize its selection process for concertation purpose and higher efforts during the tender stage with goals of success and winning. In this research paper, a two steps framework proposed to increase the efficiency of the contractor’s bidding process and the winning chance of getting the new projects awarded. In this framework, initially, all the projects pass through the first stage screening process, in which the portfolio basket will be evaluated and adjusted in accordance with the organization strategies to the reduced version of the portfolio pool, which is in line with organization activities. In the second stage, the contractor uses linear programming to optimize the portfolio pool based on available resources such as manpower, light equipment, heavy equipment, financial capability, return on investment, and success rate of winning the bid. Therefore, this optimization model will assist the contractor in utilizing its internal resource to its maximum and increase its winning chance for the new project considering past experience with clients, built-relation between two parties, and complexity in the exertion of the projects. The objective of this research will be to increase the contractor's winning chance in the bidding process based on the success rate and expected return on investment.

Keywords: bidding process, internal resources, optimization, contracting portfolio management

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1190 Classification of Forest Types Using Remote Sensing and Self-Organizing Maps

Authors: Wanderson Goncalves e Goncalves, José Alberto Silva de Sá

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Human actions are a threat to the balance and conservation of the Amazon forest. Therefore the environmental monitoring services play an important role as the preservation and maintenance of this environment. This study classified forest types using data from a forest inventory provided by the 'Florestal e da Biodiversidade do Estado do Pará' (IDEFLOR-BIO), located between the municipalities of Santarém, Juruti and Aveiro, in the state of Pará, Brazil, covering an area approximately of 600,000 hectares, Bands 3, 4 and 5 of the TM-Landsat satellite image, and Self - Organizing Maps. The information from the satellite images was extracted using QGIS software 2.8.1 Wien and was used as a database for training the neural network. The midpoints of each sample of forest inventory have been linked to images. Later the Digital Numbers of the pixels have been extracted, composing the database that fed the training process and testing of the classifier. The neural network was trained to classify two forest types: Rain Forest of Lowland Emerging Canopy (Dbe) and Rain Forest of Lowland Emerging Canopy plus Open with palm trees (Dbe + Abp) in the Mamuru Arapiuns glebes of Pará State, and the number of examples in the training data set was 400, 200 examples for each class (Dbe and Dbe + Abp), and the size of the test data set was 100, with 50 examples for each class (Dbe and Dbe + Abp). Therefore, total mass of data consisted of 500 examples. The classifier was compiled in Orange Data Mining 2.7 Software and was evaluated in terms of the confusion matrix indicators. The results of the classifier were considered satisfactory, and being obtained values of the global accuracy equal to 89% and Kappa coefficient equal to 78% and F1 score equal to 0,88. It evaluated also the efficiency of the classifier by the ROC plot (receiver operating characteristics), obtaining results close to ideal ratings, showing it to be a very good classifier, and demonstrating the potential of this methodology to provide ecosystem services, particularly in anthropogenic areas in the Amazon.

Keywords: artificial neural network, computational intelligence, pattern recognition, unsupervised learning

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1189 The Influence of Microscopic Features on the Self-Cleaning Ability of Developed 3D Printed Fabric-Like Structures Using Different Printing Parameters

Authors: Ayat Adnan Atwah, Muhammad A. Khan

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Self-cleaning surfaces are getting significant attention in industrial fields. Especially for textile fabrics, it is observed that self-cleaning textile fabric surfaces are created by manipulating the surface features with the help of coatings and nanoparticles, which are considered costly and far more complicated. However, controlling the fabrication parameters of textile fabrics at the microscopic level by exploring the potential for self-cleaning has not been addressed. This study aimed to establish the context of self-cleaning textile fabrics by controlling the fabrication parameters of the textile fabric at the microscopic level. Therefore, 3D-printed textile fabrics were fabricated using the low-cost fused filament fabrication (FFF) technique. The printing parameters, such as orientation angle (O), layer height (LH), and extruder width (EW), were used to control the microscopic features of the printed fabrics. The combination of three printing parameters was created to provide the best self-cleaning textile fabric surface: (LH) (0.15, 0.13, 0.10 mm) and (EW) (0.5, 0.4, 0.3 mm) along with two different (O) of (45º and 90º). Three different thermoplastic flexible filament materials were used: (TPU 98A), (TPE felaflex), and (TPC flex45). The printing parameters were optimised to get the optimum self-cleaning ability of the printed specimens. Furthermore, the impact of these characteristics on mechanical strength at the fabric-woven structure level was investigated. The study revealed that the printing parameters significantly affect the self-cleaning properties after adjusting the selected combination of layer height, extruder width, and printing orientation. A linear regression model was effectively developed to demonstrate the association between 3D printing parameters (layer height, extruder width, and orientation). According to the experimental results, (TPE felaflex) has a better self-cleaning ability than the other two materials.

Keywords: 3D printing, self-cleaning fabric, microscopic features, printing parameters, fabrication

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1188 Maximizing Profit Using Optimal Control by Exploiting the Flexibility in Thermal Power Plants

Authors: Daud Mustafa Minhas, Raja Rehan Khalid, Georg Frey

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The next generation power systems are equipped with abundantly available free renewable energy resources (RES). During their low-cost operations, the price of electricity significantly reduces to a lower value, and sometimes it becomes negative. Therefore, it is recommended not to operate the traditional power plants (e.g. coal power plants) and to reduce the losses. In fact, it is not a cost-effective solution, because these power plants exhibit some shutdown and startup costs. Moreover, they require certain time for shutdown and also need enough pause before starting up again, increasing inefficiency in the whole power network. Hence, there is always a trade-off between avoiding negative electricity prices, and the startup costs of power plants. To exploit this trade-off and to increase the profit of a power plant, two main contributions are made: 1) introducing retrofit technology for state of art coal power plant; 2) proposing optimal control strategy for a power plant by exploiting different flexibility features. These flexibility features include: improving ramp rate of power plant, reducing startup time and lowering minimum load. While, the control strategy is solved as mixed integer linear programming (MILP), ensuring optimal solution for the profit maximization problem. Extensive comparisons are made considering pre and post-retrofit coal power plant having the same efficiencies under different electricity price scenarios. It concludes that if the power plant must remain in the market (providing services), more flexibility reflects direct economic advantage to the plant operator.

Keywords: discrete optimization, power plant flexibility, profit maximization, unit commitment model

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1187 Processing and Characterization of Oxide Dispersion Strengthened (ODS) Fe-14Cr-3W-0.5Ti-0.3Y₂O₃ (14YWT) Ferritic Steel

Authors: Farha Mizana Shamsudin, Shahidan Radiman, Yusof Abdullah, Nasri Abdul Hamid

Abstract:

Oxide dispersion strengthened (ODS) ferritic steels are amongst the most promising candidates for large scale structural materials to be applied in next generation fission and fusion nuclear power reactors. This kind of material is relatively stable at high temperature, possess remarkable mechanical properties and comparatively good resistance from neutron radiation damage. The superior performance of ODS ferritic steels over their conventional properties is attributed to the high number density of nano-sized dispersoids that act as nucleation sites and stable sinks for many small helium bubbles resulting from irradiation, and also as pinning points to dislocation movement and grain growth. ODS ferritic steels are usually produced by powder metallurgical routes involving mechanical alloying (MA) process of Y2O3 and pre-alloyed or elemental metallic powders, and then consolidated by hot isostatic pressing (HIP) or hot extrusion (HE) techniques. In this study, Fe-14Cr-3W-0.5Ti-0.3Y₂O₃ (designated as 14YWT) was produced by mechanical alloying process and followed by hot isostatic pressing (HIP) technique. Crystal structure and morphology of this sample were identified and characterized by using X-ray Diffraction (XRD) and field emission scanning electron microscope (FESEM) respectively. The magnetic measurement of this sample at room temperature was carried out by using a vibrating sample magnetometer (VSM). FESEM micrograph revealed a homogeneous microstructure constituted by fine grains of less than 650 nm in size. The ultra-fine dispersoids of size between 5 nm to 19 nm were observed homogeneously distributed within the BCC matrix. The EDS mapping reveals that the dispersoids contain Y-Ti-O nanoclusters and from the magnetization curve plotted by VSM, this sample approaches the behavior of soft ferromagnetic materials. In conclusion, ODS Fe-14Cr-3W-0.5Ti-0.3Y₂O₃ (14YWT) ferritic steel was successfully produced by HIP technique in this present study.

Keywords: hot isostatic pressing, magnetization, microstructure, ODS ferritic steel

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1186 Fast Robust Switching Control Scheme for PWR-Type Nuclear Power Plants

Authors: Piyush V. Surjagade, Jiamei Deng, Paul Doney, S. R. Shimjith, A. John Arul

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In sophisticated and complex systems such as nuclear power plants, maintaining the system's stability in the presence of uncertainties and disturbances and obtaining a fast dynamic response are the most challenging problems. Thus, to ensure the satisfactory and safe operation of nuclear power plants, this work proposes a new fast, robust optimal switching control strategy for pressurized water reactor-type nuclear power plants. The proposed control strategy guarantees a substantial degree of robustness, fast dynamic response over the entire operational envelope, and optimal performance during the nominal operation of the plant. To improve the robustness, obtain a fast dynamic response, and make the system optimal, a bank of controllers is designed. Various controllers, like a baseline proportional-integral-derivative controller, an optimal linear quadratic Gaussian controller, and a robust adaptive L1 controller, are designed to perform distinct tasks in a specific situation. At any instant of time, the most suitable controller from the bank of controllers is selected using the switching logic unit that designates the controller by monitoring the health of the nuclear power plant or transients. The proposed switching control strategy optimizes the overall performance and increases operational safety and efficiency. Simulation studies have been performed considering various uncertainties and disturbances that demonstrate the applicability and effectiveness of the proposed switching control strategy over some conventional control techniques.

Keywords: switching control, robust control, optimal control, nuclear power control

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1185 The Impact of the Board of Directors’ Characteristics on Tax Aggressiveness in USA Companies

Authors: jihen ayadi sellami

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The rapid evolution of the global financial landscape has led to increased attention to corporate tax policies and the need to understand the factors that influence their tax behavior. In order to mitigate any residual loss for shareholders resulting from tax aggressiveness and resolve the agency problem, appropriate systems that separate the function of management from that of controlling are needed. In this context of growing concerns to limit aggressive corporate taxation practices through governance, this study discusses. Its aims is to examine the influence of six key characteristics of the board of directors (board size, diligence, CEO duality, presence of audit committees, gender diversity and independence of directors), given a governance mechanism, on the tax decisions of non-financial corporations in the United State. In fact, using a sample of 90 non-financial US firms from S&P 500 over a period of 4 years going from 2014 to 2017, the results based on a multivariate linear regression highlight significant associations between these characteristics and corporate tax policy. Notably, larger board, gender diversity, diligence and increased director independence appear to play an important role in reducing aggressive taxation. While duality has a positive and significant correlation with tax aggressiveness, that can be explained by the fact that the manager did properly exploit his specific position within the company. These findings contribute to a deeper understanding of how board characteristics can influence corporate tax management, providing avenues for more effective corporate governance and more responsible tax decision-making

Keywords: tax aggressiveness, board of directors, board size, CEO duality, audit committees, gender diversity, director independence, diligence, corporate governance, united states

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1184 Use of a Chagas Urine Nanoparticle Test (Chunap) to Correlate with Parasitemia Levels in T. cruzi/HIV Co-Infected Patients

Authors: Yagahira E. Castro-Sesquen, Robert H. Gilman, Carolina Mejia, Daniel E. Clark, Jeong Choi, Melissa J. Reimer-Mcatee, Rocio Castro, Jorge Flores, Edward Valencia-Ayala, Faustino Torrico, Ricardo Castillo-Neyra, Lance Liotta, Caryn Bern, Alessandra Luchini

Abstract:

Early diagnosis of reactivation of Chagas disease in HIV patients could be lifesaving; however, in Latin American the diagnosis is performed by detection of parasitemia by microscopy which lacks sensitivity. To evaluate if levels of T. cruzi antigens in urine determined by Chunap (Chagas urine nanoparticle test) are correlated with parasitemia levels in T. cruzi/HIV co-infected patients. T. cruzi antigens in urine of HIV patients (N=55: 31 T. cruzi infected and 24 T. cruzi serology negative) were concentrated using hydrogel particles and quantified by Western Blot and a calibration curve. The percentage of Chagas positive patients determined by Chunap compared to blood microscopy, qPCR, and ELISA was 100% (6/6), 95% (18/19) and 74% (23/31), respectively. Chunap specificity was 91.7%. Linear regression analysis demonstrated a direct relationship between parasitemia levels (determined by qPCR) and urine T. cruzi antigen concentrations (p<0.001). A cut-off of > 105 pg was chosen to determine patients with reactivation of Chagas disease (6/6). Urine antigen concentration was significantly higher among patients with CD4+ lymphocyte counts below 200/mL (p=0.045). Chunap shows potential for early detection of reactivation and with appropriate adaptation can be used for monitoring Chagas disease status in T. cruzi/HIV co-infected patients.

Keywords: antigenuria, Chagas disease, Chunap, nanoparticles, parasitemia, poly N-isopropylacrylamide (NIPAm)/trypan blue particles (polyNIPAm/TB), reactivation of Chagas disease.

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1183 Generating a Functional Grammar for Architectural Design from Structural Hierarchy in Combination of Square and Equal Triangle

Authors: Sanaz Ahmadzadeh Siyahrood, Arghavan Ebrahimi, Mohammadjavad Mahdavinejad

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Islamic culture was accountable for a plethora of development in astronomy and science in the medieval term, and in geometry likewise. Geometric patterns are reputable in a considerable number of cultures, but in the Islamic culture the patterns have specific features that connect the Islamic faith to mathematics. In Islamic art, three fundamental shapes are generated from the circle shape: triangle, square and hexagon. Originating from their quiddity, each of these geometric shapes has its own specific structure. Even though the geometric patterns were generated from such simple forms as the circle and the square, they can be combined, duplicated, interlaced, and arranged in intricate combinations. So in order to explain geometrical interaction principles between square and equal triangle, in the first definition step, all types of their linear forces individually and in the second step, between them, would be illustrated. In this analysis, some angles will be created from intersection of their directions. All angles are categorized to some groups and the mathematical expressions among them are analyzed. Since the most geometric patterns in Islamic art and architecture are based on the repetition of a single motif, the evaluation results which are obtained from a small portion, is attributable to a large-scale domain while the development of infinitely repeating patterns can represent the unchanging laws. Geometric ornamentation in Islamic art offers the possibility of infinite growth and can accommodate the incorporation of other types of architectural layout as well, so the logic and mathematical relationships which have been obtained from this analysis are applicable in designing some architecture layers and developing the plan design.

Keywords: angle, equal triangle, square, structural hierarchy

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1182 Government Size and Economic Growth: Testing the Non-Linear Hypothesis for Nigeria

Authors: R. Santos Alimi

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Using time-series techniques, this study empirically tested the validity of existing theory which stipulates there is a nonlinear relationship between government size and economic growth; such that government spending is growth-enhancing at low levels but growth-retarding at high levels, with the optimal size occurring somewhere in between. This study employed three estimation equations. First, for the size of government, two measures are considered as follows: (i) share of total expenditures to gross domestic product, (ii) share of recurrent expenditures to gross domestic product. Second, the study adopted real GDP (without government expenditure component), as a variant measure of economic growth other than the real total GDP, in estimating the optimal level of government expenditure. The study is based on annual Nigeria country-level data for the period 1970 to 2012. Estimation results show that the inverted U-shaped curve exists for the two measures of government size and the estimated optimum shares are 19.81% and 10.98%, respectively. Finally, with the adoption of real GDP (without government expenditure component), the optimum government size was found to be 12.58% of GDP. Our analysis shows that the actual share of government spending on average (2000 - 2012) is about 13.4%.This study adds to the literature confirming that the optimal government size exists not only for developed economies but also for developing economy like Nigeria. Thus, a public intervention threshold level that fosters economic growth is a reality; beyond this point economic growth should be left in the hands of the private sector. This finding has a significant implication for the appraisal of government spending and budgetary policy design.

Keywords: public expenditure, economic growth, optimum level, fully modified OLS

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1181 Electrochemical Detection of the Chemotherapy Agent Methotrexate in vitro from Physiological Fluids Using Functionalized Carbon Nanotube past Electrodes

Authors: Shekher Kummari, V. Sunil Kumar, K. Vengatajalabathy Gobi

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A simple, cost-effective, reusable and reagent-free electrochemical biosensor is developed with functionalized multiwall carbon nanotube paste electrode (f-CNTPE) for the sensitive and selective determination of the important chemotherapeutic drug methotrexate (MTX), which is widely used for the treatment of various cancer and autoimmune diseases. The electrochemical response of the fabricated electrode towards the detection of MTX is examined by cyclic voltammetry (CV), differential pulse voltammetry (DPV) and square wave voltammetry (SWV). CV studies have shown that f-CNTPE electrode system exhibited an excellent electrocatalytic activity towards the oxidation of MTX in phosphate buffer (0.2 M) compared with a conventional carbon paste electrode (CPE). The oxidation peak current is enhanced by nearly two times in magnitude. Applying the DPV method under optimized conditions, a linear calibration plot is achieved over a wide range of concentration from 4.0×10⁻⁷ M to 5.5×10⁻⁶ M with the detection limit 1.6×10⁻⁷ M. further, by applying the SWV method a parabolic calibration plot was achieved starting from a very low concentration of 1.0×10⁻⁸ M, and the sensor could detect as low as 2.9×10⁻⁹ M MTX in 10 s and 10 nM were detected in steady state current-time analysis. The f-CNTPE shows very good selectivity towards the specific recognition of MTX in the presence of important biological interference. The electrochemical biosensor detects MTX in-vitro directly from pharmaceutical sample, undiluted urine and human blood serum samples at a concentration range 5.0×10⁻⁷ M with good recovery limits.

Keywords: amperometry, electrochemical detection, human blood serum, methotrexate, MWCNT, SWV

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1180 Comparison of Mini-BESTest versus Berg Balance Scale to Evaluate Balance Disorders in Parkinson's Disease

Authors: R. Harihara Prakash, Shweta R. Parikh, Sangna S. Sheth

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The purpose of this study was to explore the usefulness of the Mini-BESTest compared to the Berg Balance Scale in evaluating balance in people with Parkinson's Disease (PD) of varying severity. Evaluation were done to obtain (1) the distribution of patients scores to look for ceiling effects, (2) concurrent validity with severity of disease, and (3) the sensitivity & specificity of separating people with or without postural response deficits. Methods and Material: Seventy-seven(77) people with Parkinson's Disease were tested for balance deficits using the Berg Balance Scale, Mini-BESTest. Unified Parkinson’s Disease Rating Scale (UPDRS) III and the Hoehn & Yahr (H&Y) disease severity scales were used for classification. Materials used in this study were case record sheet, chair without arm rests or wheels, Incline ramp, stopwatch, a box, 3 meter distance measured out and marked on the floor with tape [from chair]. Statistical analysis used: Multiple Linear regression was carried out of UPDRS jointly on the two scores for the Berg and Mini-BESTest. Receiver operating characteristic curves for classifying people into two groups based on a threshold for the H&Y score, to discriminate between mild PD versus more severe PD.Correlation co-efficient to find relativeness between the two variables. Results: The Mini-BESTest is highly correlated with the Berg (r = 0.732,P < 0.001), but avoids the ceiling compression effect of the Berg for mild PD (skewness −0.714 Berg, −0.512 Mini-BESTest). Consequently, the Mini-BESTest is more effective than the Berg for predicting UPDRS Motor score (P < 0.001 Mini-BESTest versus P = 0.72 Berg), and for discriminating between those with and without postural response deficits as measured by the H&Y (ROC).

Keywords: balance, berg balance scale, MINI BESTest, parkinson's disease

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1179 Magnetohydrodynamic Flow of Viscoelastic Nanofluid and Heat Transfer over a Stretching Surface with Non-Uniform Heat Source/Sink and Non-Linear Radiation

Authors: Md. S. Ansari, S. S. Motsa

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In this paper, an analysis has been made on the flow of non-Newtonian viscoelastic nanofluid over a linearly stretching sheet under the influence of uniform magnetic field. Heat transfer characteristics is analyzed taking into the effect of nonlinear radiation and non-uniform heat source/sink. Transport equations contain the simultaneous effects of Brownian motion and thermophoretic diffusion of nanoparticles. The relevant partial differential equations are non-dimensionalized and transformed into ordinary differential equations by using appropriate similarity transformations. The transformed, highly nonlinear, ordinary differential equations are solved by spectral local linearisation method. The numerical convergence, error and stability analysis of iteration schemes are presented. The effects of different controlling parameters, namely, radiation, space and temperature-dependent heat source/sink, Brownian motion, thermophoresis, viscoelastic, Lewis number and the magnetic force parameter on the flow field, heat transfer characteristics and nanoparticles concentration are examined. The present investigation has many industrial and engineering applications in the fields of coatings and suspensions, cooling of metallic plates, oils and grease, paper production, coal water or coal–oil slurries, heat exchangers’ technology, and materials’ processing and exploiting.

Keywords: magnetic field, nonlinear radiation, non-uniform heat source/sink, similar solution, spectral local linearisation method, Rosseland diffusion approximation

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1178 Characterisation of Extracellular Polymeric Substances from Bacteria Isolated from Acid Mine Decant in Gauteng, South Africa

Authors: Nonhlanhla Nkosi, Kulsum Kondiah

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The toxicological manifestation of heavy metals motivates interest towards the development of a reliable, eco-friendly biosorption process. With that being said, the aim of the current study was to characterise the EPS from heavy-metal resistant bacteria isolated from acid mine decant on the West Rand, Gauteng, South Africa. To achieve this, six exopolysaccharide (EPS) producing, metal resistant strains (Pb101, Pb102, Pb103, Pb204, Co101, and Ni101) were identified as Bacillus safensis strain NBRC 100820, Bacillus proteolyticus, Micrococcus luteus, Enterobacter sp. Pb204, Bacillus wiedmannii and Bacillus zhangzhouensis, respectively with 16S rRNA sequencing. Thereafter, EPS was extracted using chemical (formaldehyde/NaOH) and physical (ultrasonification) methods followed by physicochemical characterisation of carbohydrate, DNA, and protein contents using chemical assays and spectroscopy (FTIR- Fourier transformed infrared and 3DEEM- three-dimensional excitation-emission matrix fluorescence spectroscopy). EPS treated with formaldehyde/NaOH showed better recovery of macromolecules than ultrasonification. The results of the present study showed that carbohydrates were more abundant than proteins, with carbohydrate and protein concentrations of 8.00 mg/ml and 0.22 mg/ml using chemical method in contrast to 5.00 mg/ml and 0.77 mg/ml using physical method, respectively. The FTIR spectroscopy results revealed that the extracted EPS contained hydroxyl, amide, acyl, and carboxyl groups that corresponded to the aforementioned chemical analysis results, thus asserting the presence of carbohydrates, DNA, polysaccharides, and proteins in the EPS. These findings suggest that identified functional groups of EPS form surface charges, which serve as the binding sites for suspended particles, thus possibly mediating adsorption of divalent cations and heavy metals. Using the extracted EPS in the development of a cost-effective biosorption solution for industrial wastewater treatment is attainable.

Keywords: biosorbent, exopolysaccharides, heavy metals, wastewater treatment

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1177 A West Coast Estuarine Case Study: A Predictive Approach to Monitor Estuarine Eutrophication

Authors: Vedant Janapaty

Abstract:

Estuaries are wetlands where fresh water from streams mixes with salt water from the sea. Also known as “kidneys of our planet”- they are extremely productive environments that filter pollutants, absorb floods from sea level rise, and shelter a unique ecosystem. However, eutrophication and loss of native species are ailing our wetlands. There is a lack of uniform data collection and sparse research on correlations between satellite data and in situ measurements. Remote sensing (RS) has shown great promise in environmental monitoring. This project attempts to use satellite data and correlate metrics with in situ observations collected at five estuaries. Images for satellite data were processed to calculate 7 bands (SIs) using Python. Average SI values were calculated per month for 23 years. Publicly available data from 6 sites at ELK was used to obtain 10 parameters (OPs). Average OP values were calculated per month for 23 years. Linear correlations between the 7 SIs and 10 OPs were made and found to be inadequate (correlation = 1 to 64%). Fourier transform analysis on 7 SIs was performed. Dominant frequencies and amplitudes were extracted for 7 SIs, and a machine learning(ML) model was trained, validated, and tested for 10 OPs. Better correlations were observed between SIs and OPs, with certain time delays (0, 3, 4, 6 month delay), and ML was again performed. The OPs saw improved R² values in the range of 0.2 to 0.93. This approach can be used to get periodic analyses of overall wetland health with satellite indices. It proves that remote sensing can be used to develop correlations with critical parameters that measure eutrophication in situ data and can be used by practitioners to easily monitor wetland health.

Keywords: estuary, remote sensing, machine learning, Fourier transform

Procedia PDF Downloads 67
1176 Impure CO₂ Solubility Trapping in Deep Saline Aquifers: Role of Operating Conditions

Authors: Seyed Mostafa Jafari Raad, Hassan Hassanzadeh

Abstract:

Injection of impurities along with CO₂ into saline aquifers provides an exceptional prospect for low-cost carbon capture and storage technologies and can potentially accelerate large-scale implementation of geological storage of CO₂. We have conducted linear stability analyses and numerical simulations to investigate the effects of permitted impurities in CO₂ streams on the onset of natural convection and dynamics of subsequent convective mixing. We have shown that the rate of dissolution of an impure CO₂ stream with H₂S highly depends on the operating conditions such as temperature, pressure, and composition of impurity. Contrary to findings of previous studies, our results show that an impurity such as H₂S can potentially reduce the onset time of natural convection and can accelerate the subsequent convective mixing. However, at the later times, the rate of convective dissolution is adversely affected by the impurities. Therefore, the injection of an impure CO₂ stream can be engineered to improve the rate of dissolution of CO₂, which leads to higher storage security and efficiency. Accordingly, we have identified the most favorable CO₂ stream compositions based on the geophysical properties of target aquifers. Information related to the onset of natural convection such as the scaling relations and the most favorable operating conditions for CO₂ storage developed in this study are important in proper design, site screening, characterization and safety of geological storage. This information can be used to either identify future geological candidates for acid gas disposal or reviewing the current operating conditions of licensed injection sites.

Keywords: CO₂ storage, solubility trapping, convective dissolution, storage efficiency

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1175 Investigation of the Functional Impact of Amblyopia on Visual Skills in Children

Authors: Chinmay V. Deshpande

Abstract:

Purpose: To assess the efficiency of visual functions and visual skills in strabismic & anisometropic amblyopes and to assess visual acuity and contrast sensitivity in anisometropic amblyopes with spectacles & contact lenses. Method: In a prospective clinical study, 32 children ageing from 5 to 15 years presenting with amblyopia in a pediatric department of Shri Ganapati Netralaya Jalna, India, were assessed for a period of three & half months. Visual acuity was measured with Snellen’s and Bailey-Lovie log MAR charts whereas contrast sensitivity was measured with Pelli-Robson chart with spectacles and contact lenses. Saccadic movements were assessed with SCCO scoring criteria and accommodative facility was checked with ±1.50 DS flippers. Stereopsis was assessed with TNO test. Results: By using Wilcoxon sign rank test p-value < 0.05 (< 0.001), the mean linear visual acuity was 0.29 (≈ 6/21) and mean single optotype visual acuity found to be 0.36 (≈ 6/18). Mean visual acuity of 0.27(≈ 6/21) with spectacles improved to 0.33 (≈ 6/18) with contact lenses in amblyopic eyes. The mean Log MAR visual acuity with spectacles and contact lens were found to be 0.602( ≈6/24) and 0.531(≈ 6/21) respectively. The contrast threshold out of 20 amblyopic eyes shows that mean contrast threshold changed in 9 patients from spectacles 0.27 to contact lens 0.19 respectively. The mean accommodative facility assessed was 5.31(± 2.37). 24 subjects (75%) revealed marked saccadic defects on the test applied. 78% subjects didn’t show even gross stereoscopic ability on TNO test. Conclusion: This study supports the facts about amblyopia and associated deficits in visual skills which are claimed in previous studies. In addition, anisometropic amblyopia can be managed better with contact lenses.

Keywords: strabismus, anisometropia, amblyopia, contrast sensitivity, saccades, stereopsis

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1174 Comprehensive Validation of High-Performance Liquid Chromatography-Diode Array Detection (HPLC-DAD) for Quantitative Assessment of Caffeic Acid in Phenolic Extracts from Olive Mill Wastewater

Authors: Layla El Gaini, Majdouline Belaqziz, Meriem Outaki, Mariam Minhaj

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In this study, it introduce and validate a high-performance liquid chromatography method with diode-array detection (HPLC-DAD) specifically designed for the accurate quantification of caffeic acid in phenolic extracts obtained from olive mill wastewater. The separation process of caffeic acid was effectively achieved through the use of an Acclaim Polar Advantage column (5µm, 250x4.6mm). A meticulous multi-step gradient mobile phase was employed, comprising water acidified with phosphoric acid (pH 2.3) and acetonitrile, to ensure optimal separation. The diode-array detection was adeptly conducted within the UV–VIS spectrum, spanning a range of 200–800 nm, which facilitated precise analytical results. The method underwent comprehensive validation, addressing several essential analytical parameters, including specificity, repeatability, linearity, as well as the limits of detection and quantification, alongside measurement uncertainty. The generated linear standard curves displayed high correlation coefficients, underscoring the method's efficacy and consistency. This validated approach is not only robust but also demonstrates exceptional reliability for the focused analysis of caffeic acid within the intricate matrices of wastewater, thus offering significant potential for applications in environmental and analytical chemistry.

Keywords: high-performance liquid chromatography (HPLC-DAD), caffeic acid analysis, olive mill wastewater phenolics, analytical method validation

Procedia PDF Downloads 33
1173 Collagen Gel in Hip Cartilage Repair: in vivo Preliminary Study

Authors: A. Bajek, J. Skopinska-Wisniewska, A. Rynkiewicz, A. Jundzill, M. Bodnar, A. Marszalek, T. Drewa

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Traumatic injury and age-related degenerative diseases associated with cartilage are major health problems worldwide. The articular cartilage is comprised of a relatively small number of cells, which have a relatively slow rate of turnover. Therefore, damaged articular cartilage has a limited capacity for self-repair. New clinical methods have been designed to achieve better repair of injured cartilage. However, there is no treatment that enables full restoration of it. The aim of this study was to evaluate how collagen gel with bone marrow mesenchymal stem cells (MSCs) and collagen gel alone will influence on the hip cartilage repair after injury. Collagen type I was isolated from rats’ tails and cross-linked with N-hydroxysuccinimide in 24-hour process. MSCs were isolated from rats’ bone marrow. The experiments were conducted according to the guidelines for animal experiments of Ethics Committee. Fifteen 8-week-old Wistar rats were used in this study. All animals received hip joint surgery with a total of 30 created cartilage defects. Then, animals were randomly divided into three groups and filled, respectively, with collagen gel (group 1), collagen gel cultured with MSCs (group II) or left untreated as a control (control group). Immunohistochemy and radiological evaluation was carried out 11 weeks post implantation. It has been proved that the surface of the matrix is non-toxic, and its porosity promotes cell adhesion and growth. However, the in vivo regeneration process was poor. We observed the low integration rate of biomaterial. Immunohistochemical evaluation of cartilage after 11 weeks of treatment showed low II and high X collagen expression in two tested groups in comparison to the control one, in which we observed the high II collagen expression. What is more, after radiological analysis, we observed the best regeneration process in control group. The biomaterial construct and mesenchymal stem cells, as well as the use of the biomaterial itself was not sufficient to regenerate the hip cartilage surfaces. These results suggest that the collagen gel based biomaterials, even with MSCs, are not satisfactory in repar of hip cartilage defect. However, additional evaluation is needed to confirm these results.

Keywords: collafen gel, MSCs, cartilage repair, hip cartilage

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1172 Modelling and Simulation Efforts in Scale-Up and Characterization of Semi-Solid Dosage Forms

Authors: Saurav S. Rath, Birendra K. David

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Generic pharmaceutical industry has to operate in strict timelines of product development and scale-up from lab to plant. Hence, detailed product & process understanding and implementation of appropriate mechanistic modelling and Quality-by-design (QbD) approaches are imperative in the product life cycle. This work provides example cases of such efforts in topical dosage products. Topical products are typically in the form of emulsions, gels, thick suspensions or even simple solutions. The efficacy of such products is determined by characteristics like rheology and morphology. Defining, and scaling up the right manufacturing process with a given set of ingredients, to achieve the right product characteristics presents as a challenge to the process engineer. For example, the non-Newtonian rheology varies not only with CPPs and CMAs but also is an implicit function of globule size (CQA). Hence, this calls for various mechanistic models, to help predict the product behaviour. This paper focusses on such models obtained from computational fluid dynamics (CFD) coupled with population balance modelling (PBM) and constitutive models (like shear, energy density). In a special case of the use of high shear homogenisers (HSHs) for the manufacture of thick emulsions/gels, this work presents some findings on (i) scale-up algorithm for HSH using shear strain, a novel scale-up parameter for estimating mixing parameters, (ii) non-linear relationship between viscosity and shear imparted into the system, (iii) effect of hold time on rheology of product. Specific examples of how this approach enabled scale-up across 1L, 10L, 200L, 500L and 1000L scales will be discussed.

Keywords: computational fluid dynamics, morphology, quality-by-design, rheology

Procedia PDF Downloads 240
1171 The role of Financial Development and Institutional Quality in Promoting Sustainable Development through Tourism Management

Authors: Hashim Zameer

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Effective tourism management plays a vital role in promoting sustainability and supporting ecosystems. A common principle that has been in practice over the years is “first pollute and then clean,” indicating countries need financial resources to promote sustainability. Financial development and the tourism management both seems very important to promoting sustainable development. However, without institutional support, it is very difficult to succeed. In this context, it seems prominently significant to explore how institutional quality, tourism development, and financial development could promote sustainable development. In the past, no research explored the role of tourism development in sustainable development. Moreover, the role of financial development, natural resources, and institutional quality in sustainable development is also ignored. In this regard, this paper aims to investigate the role of tourism development, natural resources, financial development, and institutional quality in sustainable development in China. The study used time-series data from 2000–2021 and employed the Bayesian linear regression model because it is suitable for small data sets. The robustness of the findings was checked using a quantile regression approach. The results reveal that an increase in tourism expenditures stimulates the economy, creates jobs, encourages cultural exchange, and supports sustainability initiatives. Moreover, financial development and institution quality have a positive effect on sustainable development. However, reliance on natural resources can result in negative economic, social, and environmental outcomes, highlighting the need for resource diversification and management to reinforce sustainable development. These results highlight the significance of financial development, strong institutions, sustainable tourism, and careful utilization of natural resources for long-term sustainability. The study holds vital insights for policy formulation to promote sustainable tourism.

Keywords: sustainability, tourism development, financial development, institutional quality

Procedia PDF Downloads 46
1170 Combining Multiscale Patterns of Weather and Sea States into a Machine Learning Classifier for Mid-Term Prediction of Extreme Rainfall in North-Western Mediterranean Sea

Authors: Pinel Sebastien, Bourrin François, De Madron Du Rieu Xavier, Ludwig Wolfgang, Arnau Pedro

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Heavy precipitation constitutes a major meteorological threat in the western Mediterranean. Research has investigated the relationship between the states of the Mediterranean Sea and the atmosphere with the precipitation for short temporal windows. However, at a larger temporal scale, the precursor signals of heavy rainfall in the sea and atmosphere have drawn little attention. Moreover, despite ongoing improvements in numerical weather prediction, the medium-term forecasting of rainfall events remains a difficult task. Here, we aim to investigate the influence of early-spring environmental parameters on the following autumnal heavy precipitations. Hence, we develop a machine learning model to predict extreme autumnal rainfall with a 6-month lead time over the Spanish Catalan coastal area, based on i) the sea pattern (main current-LPC and Sea Surface Temperature-SST) at the mesoscale scale, ii) 4 European weather teleconnection patterns (NAO, WeMo, SCAND, MO) at synoptic scale, and iii) the hydrological regime of the main local river (Rhône River). The accuracy of the developed model classifier is evaluated via statistical analysis based on classification accuracy, logarithmic and confusion matrix by comparing with rainfall estimates from rain gauges and satellite observations (CHIRPS-2.0). Sensitivity tests are carried out by changing the model configuration, such as sea SST, sea LPC, river regime, and synoptic atmosphere configuration. The sensitivity analysis suggests a negligible influence from the hydrological regime, unlike SST, LPC, and specific teleconnection weather patterns. At last, this study illustrates how public datasets can be integrated into a machine learning model for heavy rainfall prediction and can interest local policies for management purposes.

Keywords: extreme hazards, sensitivity analysis, heavy rainfall, machine learning, sea-atmosphere modeling, precipitation forecasting

Procedia PDF Downloads 105
1169 Conjunctive Management of Surface and Groundwater Resources under Uncertainty: A Retrospective Optimization Approach

Authors: Julius M. Ndambuki, Gislar E. Kifanyi, Samuel N. Odai, Charles Gyamfi

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Conjunctive management of surface and groundwater resources is a challenging task due to the spatial and temporal variability nature of hydrology as well as hydrogeology of the water storage systems. Surface water-groundwater hydrogeology is highly uncertain; thus it is imperative that this uncertainty is explicitly accounted for, when managing water resources. Various methodologies have been developed and applied by researchers in an attempt to account for the uncertainty. For example, simulation-optimization models are often used for conjunctive water resources management. However, direct application of such an approach in which all realizations are considered at each iteration of the optimization process leads to a very expensive optimization in terms of computational time, particularly when the number of realizations is large. The aim of this paper, therefore, is to introduce and apply an efficient approach referred to as Retrospective Optimization Approximation (ROA) that can be used for optimizing conjunctive use of surface water and groundwater over a multiple hydrogeological model simulations. This work is based on stochastic simulation-optimization framework using a recently emerged technique of sample average approximation (SAA) which is a sampling based method implemented within the Retrospective Optimization Approximation (ROA) approach. The ROA approach solves and evaluates a sequence of generated optimization sub-problems in an increasing number of realizations (sample size). Response matrix technique was used for linking simulation model with optimization procedure. The k-means clustering sampling technique was used to map the realizations. The methodology is demonstrated through the application to a hypothetical example. In the example, the optimization sub-problems generated were solved and analysed using “Active-Set” core optimizer implemented under MATLAB 2014a environment. Through k-means clustering sampling technique, the ROA – Active Set procedure was able to arrive at a (nearly) converged maximum expected total optimal conjunctive water use withdrawal rate within a relatively few number of iterations (6 to 7 iterations). Results indicate that the ROA approach is a promising technique for optimizing conjunctive water use of surface water and groundwater withdrawal rates under hydrogeological uncertainty.

Keywords: conjunctive water management, retrospective optimization approximation approach, sample average approximation, uncertainty

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1168 Modification of Polyolefin Membrane Using Supercritical Carbon Dioxide for Redox Flow Batteries

Authors: Vadim V. Zefirov, Victor E. Sizov, Marina A. Pigaleva, Igor V. Elmanovich, Mikhail S. Kondratenko, Marat O. Gallyamov

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This work presents a novel method for treating porous hydrophobic polyolefin membranes using supercritical carbon dioxide that allows usage of the modified membrane in redox flow batteries with an aqueous electrolyte. Polyolefin membranes are well known and widely used, however, they cannot be used as separators in redox flow batteries with an aqueous electrolyte since they have insufficient wettability, and therefore do not provide sufficient proton conductivity. The main aim of the presented work was the development of hydrophilic composites based on cheap membranes and precursors. Supercritical fluid was used as a medium for the deposition of the hydrophilic phase on the hydrophobic surface of the membrane. Due to the absence of negative capillary effects in a supercritical medium, a homogeneous composite is obtained as a result of synthesis. The in-situ synthesized silicon oxide nanoparticles and the chitosan polymer layer act as the hydrophilic phase and not only increase the affinity of the membrane towards the electrolyte, but also reduce the pore size of the polymer matrix, which positively affects the ion selectivity of the membrane. The composite material obtained as a result of synthesis has enhanced hydrophilic properties and is capable of providing proton conductivity in redox flow batteries. The morphology of the obtained composites was characterized by electron microscopy. To analyze the phase composition, infrared spectroscopy was used. The hydrophilic properties were studied by water contact angle measurements. In addition, the proton conductivity and ion selectivity of the obtained samples were studied, and tests in real redox flow batteries were performed. As a result, modified membrane was characterised in detail and moreover it was shown that modified cheap polyolefin membranes have pronounced proton conductivity and high ion selectivity, so their performance in a real redox flow battery approaches expensive commercial analogues, reaching 70% of energy efficiency.

Keywords: carbon dioxide, chitosan, polymer membrane, redox flow batteries, silica nanoparticles, supercritical fluid

Procedia PDF Downloads 114
1167 Synthesis and Two-Photon Polymerization of a Cytocompatibility Tyramine Functionalized Hyaluronic Acid Hydrogel That Mimics the Chemical, Mechanical, and Structural Characteristics of Spinal Cord Tissue

Authors: James Britton, Vijaya Krishna, Manus Biggs, Abhay Pandit

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Regeneration of the spinal cord after injury remains a great challenge due to the complexity of this organ. Inflammation and gliosis at the injury site hinder the outgrowth of axons and hence prevent synaptic reconnection and reinnervation. Hyaluronic acid (HA) is the main component of the spinal cord extracellular matrix and plays a vital role in cell proliferation and axonal guidance. In this study, we have synthesized and characterized a photo-cross-linkable HA-tyramine (tyr) hydrogel from a chemical, mechanical, electrical, biological and structural perspective. From our experimentation, we have found that HA-tyr can be synthesized with controllable degrees of tyramine substitution using click chemistry. The complex modulus (G*) of HA-tyr can be tuned to mimic the mechanical properties of the native spinal cord via optimization of the photo-initiator concentration and UV exposure. We have examined the degree of tyramine-tyramine covalent bonding (polymerization) as a function of UV exposure and photo-initiator use via Photo and Nuclear magnetic resonance spectroscopy. Both swelling and enzymatic degradation assays were conducted to examine the resilience of our 3D printed hydrogel constructs in-vitro. Using a femtosecond 780nm laser, the two-photon polymerization of HA-tyr hydrogel in the presence of riboflavin photoinitiator was optimized. A laser power of 50mW and scan speed of 30,000 μm/s produced high-resolution spatial patterning within the hydrogel with sustained mechanical integrity. Using dorsal root ganglion explants, the cytocompatibility of photo-crosslinked HA-tyr was assessed. Using potentiometry, the electrical conductivity of photo-crosslinked HA-tyr was assessed and compared to that of native spinal cord tissue as a function of frequency. In conclusion, we have developed a biocompatible hydrogel that can be used for photolithographic 3D printing to fabricate tissue engineered constructs for neural tissue regeneration applications.

Keywords: 3D printing, hyaluronic acid, photolithography, spinal cord injury

Procedia PDF Downloads 131