Search results for: prediction capability

Authors: Ahmad Idris, Armaya`u Suleiman Labo, Ado Yusuf Abdulfatah, Murtala Umar

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Super pave is the short form of Superior Performing Asphalt Pavement and represents a basis for specifying component materials, asphalt mixture design and analysis, and pavement performance prediction. This new technology is the result of long research projects conducted by the strategic Highway Research program (SHRP) of the Federal Highway Administration. This research was aimed at examining the suitability of Aggregates found in Kano for used in super pave design method. Aggregates samples were collected from different sources in Kano Nigeria and their Engineering properties, as they relate to the SUPERPAVE design requirements were determined. The average result of Coarse Aggregate Angularity in Kano was found to be 87% and 86% of one fractured face and two or more fractured faces respectively with a standard of 80% and 85% respectively. Fine Aggregate Angularity average result was found to be 47% with a requirement of 45% minimum. A flat and elongated particle which was found to be 10% has a maximum criterion of 10%. Sand equivalent was found to be 51% with the criteria of 45% minimum. Strength tests were also carried out, and the results reflect the requirements of the standards. The tests include Impact value test, Aggregate crushing value and Aggregate Abrasion tests and the results are 27.5%, 26.7% and 13% respectively with a maximum criteria of 30%. Specific gravity was also carried out and the result was found to have an average value of 2.52 with a criterion of 2.6 to 2.9 and Water absorption was found to be 1.41% with maximum criteria of 0.6%. From the study, the result of the tests indicated that the aggregates properties have met the requirements of Super pave design method based on the specifications of ASTMD 5821, ASTM D 4791, AASHTO T176, AASHTO T33 and BS815.

Keywords: aggregates, construction, road design, super pave

Procedia PDF Downloads 238

Authors: Sayantika Biswas, Dipanshu Sur, Amitoj Athwal, Ratnabali Chakravorty

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Title: Impact of serum estrogen and progesterone levels in the outcome pregnancy rate in frozen embryo transfer cycles. A prospective cohort study Objective: The aim of the current study was to evaluate the effect of serum estradiol (E2) and progesterone (P4) levels at different time points on pregnancy outcomes in frozen embryo transfer (FET) cycles. Materials & Method: A prospective cohort study was performed in patients undergoing frozen embryo transfer. Patients under age 37 years of age with at least one good blastocyst or three good day 3 embryos were included in the study. For endometrial preparation, 14 days of oral estradiol use (2X2 mg for 5 days. 3X2 mg for 4 days, and 4X2 mg for 5 days) was followed by vaginal progesterone twice a day and 50 mg intramuscular progesterone twice a day. Embryo transfer was scheduled 72-76 hrs or 116-120hrs after the initiation of progesterone. Serum E2 and P4 levels were examined at 4 times a) at the start of the menstrual cycle prior to the hormone supplementation. b) on the day of P4 start. c) on the day of ET. d) on the third day after ET. Result: A total 41 women were included in this study (mean age 31.8; SD 2.8). Clinical pregnancy rate was 65.55%. Serum E2 levels on at the start of the menstrual cycle prior to the hormone supplementation and on the day of P4 start were high in patients who achieved pregnancy compared to who did not (P=0.005 and P=0.019 respectively). P4 levels on on the day of ET were also high in patients with clinical pregnancy. On the day of P4 start, a serum E2 threshold of 186.4 pg/ml had a sensitivity of 82%, and P4 had a sensitivity of 71% for the prediction of clinical pregnancy at the threshold value 16.00 ng/ml. Conclusion: In women undergoing FET with hormone replacement, serum E2 level >186.4 pg/ml on the day of the start of progesterone and serum P4 levels >16.00 ng/ml on embryo transfer day are associated with clinical pregnancy.

Keywords: serum estradiol, serum progesterone, clinical pregnancy, frozen embryo transfer

Procedia PDF Downloads 80

Authors: Thewodros K. Geberemariam

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The rapid physical expansion of urbanization coupled with aging infrastructure presents a unique decision and management challenges for many big city municipalities. Cities must therefore upgrade and maintain the existing aging urban drainage infrastructure systems to keep up with the demands. Given the overall contribution of assets to municipal revenue and the importance of infrastructure to the success of a livable city, many municipalities are currently looking for a robust and smart urban drainage infrastructure asset management solution that combines management, financial, engineering and technical practices. This robust decision-making shall rely on sound, complete, current and relevant data that enables asset valuation, impairment testing, lifecycle modeling, and forecasting across the multiple asset portfolios. On this paper, predictive computational intelligence (CI) and multi-class machine learning (ML) coupled with online, offline, and historical record data that are collected from an array of multi-parameter sensors are used for the extraction of different operational and non-conforming patterns hidden in structured and unstructured data to determine and produce actionable insight on the current and future states of the network. This paper aims to improve the strategic decision-making process by identifying all possible alternatives; evaluate the risk of each alternative, and choose the alternative most likely to attain the required goal in a cost-effective manner using historical and near real-time urban drainage infrastructure data for urban drainage infrastructures assets that have previously not benefited from computational intelligence and machine learning advancements.

Keywords: computational intelligence, machine learning, urban drainage infrastructure, machine learning, classification, prediction, asset management space

Procedia PDF Downloads 152

Authors: Elvis Munyoka

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While the number of African refugees settling in Australia has significantly increased since the mid-1990s, the marginalisation and exclusion of young people from refugee backgrounds in employment remain a critical challenge. Unemployment or underemployment can negatively impact refugees in multiple areas, such as income, housing, life satisfaction, and social status. Higher rates of unemployment among refugees are linked in part to the intersection of pre-migration and daily challenges like trauma, racism, gender identity, and English language competency, all of which generate multiple employability disadvantages. However, the intersection of gender, race, social class, and age in impacting African refugee youth’s access to employment has received less attention. Using a qualitative case study approach, the presentation will explore how gender, race, social class, and age influence African refugee youth graduates’ access to employment in South Australia. The intersectionality theory and capability approach to social justice is used to explore intersecting factors impacting African refugee youth’s access to employment in South Australia. Participants were 16 African refugee graduates aged 18-30 living in South Australia who took part in the study for one year. Based on the trends in the data, the results suggest that long-term unemployment and underemployment, coupled with ongoing racism and marginalisation, have the potential to make refugees more vulnerable to several mental disorders such as depression, hopelessness, and suicidal thoughts. The analysis also reveals that resettlement challenges may limit refugees’ ability to recover from pre-migration trauma. The impact of resettlement challenges on refugee mental health highlights the need for comprehensive policy interventions to address the barriers refugees face in finding employment in resettlement communities. With African refugees constituting such an important part of Australian society, they should have equal access to meaningful employment, as decent work promotes good mental health, successful resettlement, hope, and self-sufficiency.

Keywords: African refugees, employment, mental health, Australia, underemployment

Procedia PDF Downloads 102

Authors: Carlos Gonzales, Zaida Quiroz, Marcos Prates

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Several spatial variables collected at the same location that share a common spatial distribution can be modeled simultaneously through a multivariate geostatistical model that takes into account the correlation between these variables and the spatial autocorrelation. The main goal of this model is to perform spatial prediction of these variables in the region of study. Here we focus on a geostatistical multivariate formulation that relies on sharing common spatial random effect terms. In particular, the first response variable can be modeled by a mean that incorporates a shared random spatial effect, while the other response variables depend on this shared spatial term, in addition to specific random spatial effects. Each spatial random effect is defined through a Gaussian process with a valid covariance function, but in order to improve the computational efficiency when the data are large, each Gaussian process is approximated to a Gaussian random Markov field (GRMF), specifically to the block nearest neighbor Gaussian process (Block-NNGP). This approach involves dividing the spatial domain into several dependent blocks under certain constraints, where the cross blocks allow capturing the spatial dependence on a large scale, while each individual block captures the spatial dependence on a smaller scale. The multivariate geostatistical model belongs to the class of Latent Gaussian Models; thus, to achieve fast Bayesian inference, it is used the integrated nested Laplace approximation (INLA) method. The good performance of the proposed model is shown through simulations and applications for massive data.

Keywords: Block-NNGP, geostatistics, gaussian process, GRMF, INLA, multivariate models.

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Authors: Samy A. Khalil, U. Ali Rahoma

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The measurements of solar radiation, satellite data has been routinely utilize to estimate solar energy. However, the temporal coverage of satellite data has some limits. The reanalysis, also known as "retrospective analysis" of the atmosphere's parameters, is produce by fusing the output of NWP (Numerical Weather Prediction) models with observation data from a variety of sources, including ground, and satellite, ship, and aircraft observation. The result is a comprehensive record of the parameters affecting weather and climate. The effectiveness of reanalysis datasets (ERA-5) for North Africa was evaluate against high-quality surfaces measured using statistical analysis. Estimating the distribution of global solar radiation (GSR) over five chosen areas in North Africa through ten-years during the period time from 2011 to 2020. To investigate seasonal change in dataset performance, a seasonal statistical analysis was conduct, which showed a considerable difference in mistakes throughout the year. By altering the temporal resolution of the data used for comparison, the performance of the dataset is alter. Better performance is indicate by the data's monthly mean values, but data accuracy is degraded. Solar resource assessment and power estimation are discuses using the ERA-5 solar radiation data. The average values of mean bias error (MBE), root mean square error (RMSE) and mean absolute error (MAE) of the reanalysis data of solar radiation vary from 0.079 to 0.222, 0.055 to 0.178, and 0.0145 to 0.198 respectively during the period time in the present research. The correlation coefficient (R2) varies from 0.93 to 99% during the period time in the present research. This research's objective is to provide a reliable representation of the world's solar radiation to aid in the use of solar energy in all sectors.

Keywords: solar energy, ERA-5 analysis data, global solar radiation, North Africa

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Authors: O. Fiquet, P. Lemarignier

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Additive manufacturing may find numerous applications in the nuclear industry, for the same reason as for other industries, to enlarge design possibilities and performances and develop fabrication methods as a flexible route for future innovation. Additive Manufacturing applications in the design of structural metallic components for reactors are already developed at a high Technology Readiness Level (TRL). In the case of a Pressured Water Reactor using uranium oxide fuel pellets, which are ceramics, the transposition of already optimized Additive Manufacturing (AM) processes to UO₂ remains a challenge, and the progress remains slow because, to our best knowledge, only a few laboratories have the capability of developing processes applicable to UO₂. After the Fukushima accident, numerous research fields emerged with the study of ATF (Accident tolerant Fuel) fuel concepts, which aimed to improve fuel behaviour. One item concerns the increase of the pellet thermal performance by, for example, the addition of high thermal conductivity material into fissile UO₂. This additive phase may be metallic, and the end product will constitute a CERMET composite. Innovative designs of an internal metallic framework are proposed based on predictive calculations. However, because the well-known reference pellet manufacturing methods impose many limitations, manufacturing such a composite remains an arduous task. Therefore, the AM process appears as a means of broadening the design possibilities of CERMET manufacturing. If the external form remains a standard cylindrical fuel pellet, the internal metallic design remains to be optimized based on process capabilities. This project also considers the limitation to a maximum of 10% volume of metal, which is a constraint neutron physics considerations impose. The AM technique chosen for this development is robocasting because of its simplicity and low-cost equipment. It remains, however, a challenge to adapt a ceramic 3D printing process for the fabrication of UO₂ fuel. The investigation starts with surrogate material, and the optimization of slurry feedstock is based on alumina. The paper will present the first printing of Al2O3-Mo CERMET and the expected transition from ceramic-based alumina to UO₂ CERMET.

Keywords: nuclear, fuel, CERMET, robocasting

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Authors: Elvis Munyoka

Abstract:

While the number of African refugees settling in Australia has significantly increased since the mid-1990s, the marginalisation and exclusion of young people from refugee backgrounds in employment remain a critical challenge. Unemployment or underemployment can negatively impact refugees in multiple areas, such as income, housing, life satisfaction, and social status. Higher rates of unemployment among refugees are linked in part to the intersection of pre-migration and daily challenges like trauma, racism, gender identity, and English language competency, all of which generate multiple employability disadvantages. However, the intersection of gender, race, social class, and age in impacting African refugee youth’s access to employment has received less attention. Using a qualitative case study approach, the paper will explore how gender, race, social class, and age influence African refugee youth graduates’ access to employment in South Australia. The intersectionality theory and capability approach to social justice is used to explore intersecting factors impacting African refugee youth’s access to employment in South Australia. Participants were 16 African refugee graduates aged 18-30 living in South Australia who took part in the study for one year. Based on the trends in the data, the results suggest that long-term unemployment and underemployment, coupled with ongoing racism and marginalisation, have the potential to make refugees more vulnerable to several mental disorders such as depression, hopelessness, and suicidal thoughts. The analysis also reveals that resettlement challenges may limit refugees’ ability to recover from pre-migration trauma. The impact of resettlement challenges on refugee mental health highlights the need for comprehensive policy interventions to address the barriers refugees face in finding employment in resettlement communities. With African refugees constituting such an important part of Australian society, they should have equal access to meaningful employment, as decent work promotes good mental health, successful resettlement, hope, and self-sufficiency.

Keywords: African refugee youth, mental health, employment, resettlement, racism

Procedia PDF Downloads 69

Authors: Brindha Senthil Kumar, Payel Chakraborty, Senthil Kumar Nachimuthu, Arindam Maitra, Prem Nath

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Gastric cancer is predominantly caused by demographic and diet factors as compared to other cancer types. The aim of the study is to predict Early Gastric Cancer (ECG) from diet and lifestyle factors using supervised machine learning algorithms. For this study, 160 healthy individual and 80 cases were selected who had been followed for 3 years (2016-2019), at Civil Hospital, Aizawl, Mizoram. A dataset containing 11 features that are core risk factors for the gastric cancer were extracted. Supervised machine algorithms: Logistic Regression, Naive Bayes, Support Vector Machine (SVM), Multilayer perceptron, and Random Forest were used to analyze the dataset using Python Jupyter Notebook Version 3. The obtained classified results had been evaluated using metrics parameters: minimum_false_positives, brier_score, accuracy, precision, recall, F1_score, and Receiver Operating Characteristics (ROC) curve. Data analysis results showed Naive Bayes - 88, 0.11; Random Forest - 83, 0.16; SVM - 77, 0.22; Logistic Regression - 75, 0.25 and Multilayer perceptron - 72, 0.27 with respect to accuracy and brier_score in percent. Naive Bayes algorithm out performs with very low false positive rates as well as brier_score and good accuracy. Naive Bayes algorithm classification results in predicting ECG showed very satisfactory results using only diet cum lifestyle factors which will be very helpful for the physicians to educate the patients and public, thereby mortality of gastric cancer can be reduced/avoided with this knowledge mining work.

Keywords: Early Gastric cancer, Machine Learning, Diet, Lifestyle Characteristics

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Authors: Joonas Pääkkönen

Abstract:

In sports, individuals and teams are typically interested in final rankings. Final results, such as times or distances, dictate these rankings, also known as places. Places can be further associated with ordered random variables, commonly referred to as order statistics. In this work, we introduce a simple, yet accurate order statistical ordinal regression function that predicts relay race places with changeover-times. We call this function the Fenton-Wilkinson Order Statistics model. This model is built on the following educated assumption: individual leg-times follow log-normal distributions. Moreover, our key idea is to utilize Fenton-Wilkinson approximations of changeover-times alongside an estimator for the total number of teams as in the notorious German tank problem. This original place regression function is sigmoidal and thus correctly predicts the existence of a small number of elite teams that significantly outperform the rest of the teams. Our model also describes how place increases linearly with changeover-time at the inflection point of the log-normal distribution function. With real-world data from Jukola 2019, a massive orienteering relay race, the model is shown to be highly accurate even when the size of the training set is only 5% of the whole data set. Numerical results also show that our model exhibits smaller place prediction root-mean-square-errors than linear regression, mord regression and Gaussian process regression.

Keywords: Fenton-Wilkinson approximation, German tank problem, log-normal distribution, order statistics, ordinal regression, orienteering, sports analytics, sports modeling

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Authors: Takuro Kida, Yuichi Kida

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In this paper, it is shown a base of the new trend of algorithm mathematically that treats a historical reason of continuous discrimination in the world as well as its solution by introducing new concepts of parallel world that includes an invisible set of errors as its companion. With respect to a matrix operator-filter bank that the matrix operator-analysis-filter bank H and the matrix operator-sampling-filter bank S are given, firstly, we introduce the detail algorithm to derive the optimum matrix operator-synthesis-filter bank Z that minimizes all the worst-case measures of the matrix operator-error-signals E(ω) = F(ω) − Y(ω) between the matrix operator-input-signals F(ω) and the matrix operator-output-signals Y(ω) of the matrix operator-filter bank at the same time. Further, feedback is introduced to the above approximation theory, and it is indicated that introducing conversations with feedback do not superior automatically to the accumulation of existing knowledge of signal prediction. Secondly, the concept of category in the field of mathematics is applied to the above optimum signal approximation and is indicated that the category-based approximation theory is applied to the set-theoretic consideration of the recognition of humans. Based on this discussion, it is shown naturally why the narrow perception that tends to create isolation shows an apparent advantage in the short term and, often, why such narrow thinking becomes intimate with discriminatory action in a human group. Throughout these considerations, it is presented that, in order to abolish easy and intimate discriminatory behavior, it is important to create a parallel world of conception where we share the set of invisible error signals, including the words and the consciousness of both worlds.

Keywords: matrix filterbank, optimum signal approximation, category theory, simultaneous minimization

Procedia PDF Downloads 143

Authors: Amir Shafiee Kisomi, Mehrdad Mofidi

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Nowadays, fuel cells as a promising alternative for power source have been widely studied owing to their security, high energy density, low operation temperatures, renewable capability and low environmental pollutant emission. The nanoparticles of core-shell type could be widely described in a combination of a shell (outer layer material) and a core (inner material), and their characteristics are greatly conditional on dimensions and composition of the core and shell. In addition, the change in the constituting materials or the ratio of core to the shell can create their special noble characteristics. In this study, a fast technique for the fabrication of a Pd-Co/G/GCE modified electrode is offered. Thermal decomposition reaction of cobalt (II) formate salt over the surface of graphene/glassy carbon electrode (G/GCE) is utilized for the synthesis of Co nanoparticles. The nanoparticles of Pd-Co decorated on the graphene are created based on the following method: (1) Thermal decomposition reaction of cobalt (II) formate salt and (2) the galvanic replacement process Co by Pd2+. The physical and electrochemical performances of the as-prepared Pd-Co/G electrocatalyst are studied by Field Emission Scanning Electron Microscopy (FESEM), Energy Dispersive X-ray Spectroscopy (EDS), Cyclic Voltammetry (CV), and Chronoamperometry (CHA). Galvanic replacement method is utilized as a facile and spontaneous approach for growth of Pd nanostructures. The Pd-Co/G is used as an anode catalyst for ethanol oxidation in alkaline media. The Pd-Co/G not only delivered much higher current density (262.3 mAcm-2) compared to the Pd/C (32.1 mAcm-2) catalyst, but also demonstrated a negative shift of the onset oxidation potential (-0.480 vs -0.460 mV) in the forward sweep. Moreover, the novel Pd-Co/G electrocatalyst represents large electrochemically active surface area (ECSA), lower apparent activation energy (Ea), higher levels of durability and poisoning tolerance compared to the Pd/C catalyst. The paper demonstrates that the catalytic activity and stability of Pd-Co/G electrocatalyst are higher than those of the Pd/C electrocatalyst toward ethanol oxidation in alkaline media.

Keywords: thermal decomposition, nanostructures, galvanic replacement, electrocatalyst, ethanol oxidation, alkaline media

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Authors: Zahidul Islam

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This study investigates the effectiveness of resourcing in post-disaster housing reconstruction with reference to Cyclones Sidr and Aila in Bangladesh. Through evaluating three key theories- Build Back Better approach, Balance Scorecard approach and Dynamic Competency theories, the synthesis of literature, and empirical fieldwork, this research develops a dynamic theoretical framework that moves the trajectory of post-disaster housing reconstruction towards the reconstruction of more resilient houses. The ultimate goal of any post-disaster housing reconstruction project is to provide quality houses and to achieve high levels of satisfaction for beneficiaries. However, post-disaster reconstruction projects often fail in their stated objectives; only 10-20% housing needs are met, with most houses constructed on a temporary rather than permanent basis. A number of scholars have argued that access to resources can significantly increase the capacity and capability of disaster victims to rebuild their lives, including the construction of new homes. This study draws on structured interviews of 285 villagers affected by cyclones to investigate the effectiveness of resourcing in rebuilding houses after Cyclone Sidr in 2007 and Cyclone Aila in 2009. Furthermore, semi-structured interviews were conducted with 20 key stakeholders in UNDP, Oxfam, government officials, and national and international NGOs. The results of this study show that recovery rate of cyclone resilient houses that can withstand cyclone is very low and majority of the population are still vulnerable. Furthermore, hierarchical regression of survey data and thematic analyses of qualitative data indicate that access to resources, level of education, quality of building materials and income generating activities of the respondents are critical for effective post-disaster recovery. Conversely, resource availability, lack of coordination among participant organisations, corruption and lack of access to appropriate land constituted significant obstacles to livelihood recovery. Finally, this study makes significant theoretical contributions to theories of post-disaster recovery by introducing new variables and measures for evaluating the quality and effectiveness of post-disaster housing.

Keywords: disaster, resourcing, housing, resilience

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Authors: Bi-Huei Tsai

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This work explores the inter-region investment behaviors of integrated circuit (IC) design industry from Taiwan to China using the amount of foreign direct investment (FDI). According to the mutual dependence among different IC design industrial locations, Lotka-Volterra model is utilized to explore the FDI interactions between South and East China. Effects of inter-regional collaborations on FDI flows into China are considered. Evolutions of FDIs into South China for IC design industry significantly inspire the subsequent FDIs into East China, while FDIs into East China for Taiwan’s IC design industry significantly hinder the subsequent FDIs into South China. The supply chain along IC industry includes IC design, manufacturing, packing and testing enterprises. I C manufacturing, packaging and testing industries depend on IC design industry to gain advanced business benefits. The FDI amount from Taiwan’s IC design industry into East China is the greatest among the four regions: North, East, Mid-West and South China. The FDI amount from Taiwan’s IC design industry into South China is the second largest. If IC design houses buy more equipment and bring more capitals in South China, those in East China will have pressure to undertake more FDIs into East China to maintain the leading position advantages of the supply chain in East China. On the other hand, as the FDIs in East China rise, the FDIs in South China will successively decline since capitals have concentrated in East China. Prediction of Lotka-Volterra model in FDI trends is accurate because the industrial interactions between the two regions are included. Finally, this work confirms that the FDI flows cannot reach a stable equilibrium point, so the FDI inflows into East and South China will expand in the future.

Keywords: Lotka-Volterra model, foreign direct investment, competitive, Equilibrium analysis

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Authors: Theresa Ukamaka Nwagha, Angela Ogechukwu Ugwu, Martins Nweke

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Background and Objectives: Blood transfusion is an effective and proven treatment for some severe complications of sickle cell disease. Recurrent transfusions have put patients with sickle cell disease at risk of developing antibodies against the various antigens they were exposed to. This study aims to investigate the frequency of red blood cell alloimmunization in patients with sickle disease in Africa. Materials and Methods: This is a systematic review of peer-reviewed literature published in English. The review was conducted consistent with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. Data sources for the review include MEDLINE, PubMed, CINAHL, and Academic Search Complete. Included in this review are articles that reported the frequency/prevalence of red blood cell alloimmunization in sickle cell disease patients in Africa. Eligible studies were subjected to independent full-text screening and data extraction. Risk of bias assessment was conducted with the aid of the mixed method appraisal tool. We employed a random-effects model of meta-analysis to estimate the pooled prevalence. We computed Cochrane’s Q statistics and I2 and prediction interval to quantify heterogeneity in effect size. Results: The prevalence estimates range from 2.6% to 29%. Pooled prevalence was estimated to be 10.4% (CI 7.7.–13.8); PI = 3.0 – 34.0%), with significant heterogeneity (I2 = 84.62; PI = 2.0-32.0%) and publication bias (Egger’s t-test = 1.744, p = 0.0965). Conclusion: The frequency of red cell alloantibody varies considerably in Africa. The alloantibodies appeared frequent in this order: the Rhesus, Kell, Lewis, Duffy, MNS, and Lutheran

Keywords: frequency, red blood cell, alloimmunization, sickle cell disease, Africa

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Authors: Emmanuel U. Unuafe, Oyegoke T. Bukoye, Sandhya Sastry, Yanqing Duan

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Globally, there is increasing interest in project management due to a shortage in infrastructure services supply capability. Hence, it is of utmost importance that organisations understand that choosing a particular project over another is an opportunity cost – tying up the organisations resources. In order to devise constructive ways to bring direction, structure, and oversight to the process of project selection has led to the development of tools and techniques by researchers and practitioners. However, despite the development of various frameworks to assist in the appraisal and selection of government projects, failures are still being recorded with government projects. In developing countries, where frameworks are rarely used, the problems are compounded. To improve the situation, this study will investigate the current practice of construction project selection processes within the Nigeria public sector in order to inform theories of decision making from the perspective of developing nations and project management practice. Unlike other research around construction projects in Nigeria this research concentrate on factors influencing the selection process within the Nigeria public sector, which has received limited study. The authors report the findings of semi-structured interviews of top management in the Nigerian public sector and draw conclusions in terms of decision making extant theory and current practice. Preliminary results from the data analysis show that groups make project selection decisions and this forces sub-optimal decisions due to pressure on time, clashes of interest, lack of standardised framework for selecting projects, lack of accountability and poor leadership. Consequently, because decision maker is usually drawn from different fields, religious beliefs, ethnic group and with different languages. The choice of a project by an individual will be greatly influence by experience, political precedence than by realistic investigation as well as his understanding of the desired outcome of the project, in other words, the individual’s ideology and their level of fairness.

Keywords: factors influencing project selection, public sector construction project selection, projects portfolio selection, strategic decision-making

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Authors: Muhammed Ashiq Villanthenkodath, Shreya Pal

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Purpose: This study scrutinizes the impact of economic globalization on ecological footprint while endogenizing economic growth and energy consumption from 1990 to 2018 in India. Design/methodology/approach: The standard unit root test has been employed for time series analysis to unveil the integration order. Then, the cointegration was confirmed using autoregressive distributed lag (ARDL) analysis. Further, the study executed the dynamic ARDL simulation model to estimate long-run and short-run results along with simulation and robotic prediction. Findings: The cointegration analysis confirms the existence of a long-run association among variables. Further, economic globalization reduces the ecological footprint in the long run. Similarly, energy consumption decreases the ecological footprint. In contrast, economic growth spurs the ecological footprint in India. Originality/value: This study contributes to the literature in many ways. First, unlike studies that employ CO2 emissions and globalization nexus, this study employs ecological footprint for measuring environmental quality; since it is the broader measure of environmental quality, it can offer a wide range of climate change mitigation policies for India. Second, the study executes a multivariate framework with updated series from 1990 to 2018 in India to explore the link between EF, economic globalization, energy consumption, and economic growth. Third, the dynamic autoregressive distributed lag (ARDL) model has been used to explore the short and long-run association between the series. Finally, to our limited knowledge, this is the first study that uses economic globalization in the EF function of India amid facing a trade-off between sustainable economic growth and the environment in the era of globalization.

Keywords: economic globalization, ecological footprint, India, dynamic ARDL simulation model

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Authors: Zhengming Wu

Abstract:

NanoFrazor lithography systems were developed as a first true alternative or extension to standard mask-less nanolithography methods like electron beam lithography (EBL). In contrast to EBL they are based on thermal scanning probe lithography (t-SPL). Here a heatable ultra-sharp probe tip with an apex of a few nm is used for patterning and simultaneously inspecting complex nanostructures. The heat impact from the probe on a thermal responsive resist generates those high-resolution nanostructures. The patterning depth of each individual pixel can be controlled with better than 1 nm precision using an integrated in-situ metrology method. Furthermore, the inherent imaging capability of the Nanofrazor technology allows for markerless overlay, which has been achieved with sub-5 nm accuracy as well as it supports stitching layout sections together with < 10 nm error. Pattern transfer from such resist features below 10 nm resolution were demonstrated. The technology has proven its value as an enabler of new kinds of ultra-high resolution nanodevices as well as for improving the performance of existing device concepts. The application range for this new nanolithography technique is very broad spanning from ultra-high resolution 2D and 3D patterning to chemical and physical modification of matter at the nanoscale. Nanometer-precise markerless overlay and non-invasiveness to sensitive materials are among the key strengths of the technology. However, while patterning at below 10 nm resolution is achieved, significantly increasing the patterning speed at the expense of resolution is not feasible by using the heated tip alone. Towards this end, an integrated laser write head for direct laser sublimation (DLS) of the thermal resist has been introduced for significantly faster patterning of micrometer to millimeter-scale features. Remarkably, the areas patterned by the tip and the laser are seamlessly stitched together and both processes work on the very same resist material enabling a true mix-and-match process with no developing or any other processing steps in between. The presentation will include examples for (i) high-quality metal contacting of 2D materials, (ii) tuning photonic molecules, (iii) generating nanofluidic devices and (iv) generating spintronic circuits. Some of these applications have been enabled only due to the various unique capabilities of NanoFrazor lithography like the absence of damage from a charged particle beam.

Keywords: nanofabrication, grayscale lithography, 2D materials device, nano-optics, photonics, spintronic circuits

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Authors: Živilė Jurgelėnė, Vitalijus Karabanovas, Augustas Morkvėnas, Reda Dzingelevičienė, Nerijus Dzingelevičius, Saulius Raugelė, Boguslaw Buszewski

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The short- and long-term effects of COVID-19 antiviral drug molnupiravir and micro/nanoplastics on the early development of Salmo trutta were investigated using accumulation and exposure studies. Salmo trutta were used as standardized test organisms in toxicity studies of COVID-19 waste contaminants. The 2D/3D imaging was performed using confocal fluorescence spectral imaging microscopy to assess the uptake, bioaccumulation, and distribution of molnupiravir and micro/nanoplastics complex in live fish. Our study results demonstrated that molnupiravir may interact with a micro/nanoplastics and modify their spectroscopic parameters and toxicity to S. trutta embryos and larvae. The 0.2 µm size microplastics at a concentration of 10 mg/L were found to be stable in aqueous media than 0.02 µm, and 2 µm sizes polymeric particles. This study demonstrated that polymeric particles can adsorb molnupiravir that are present in mixtures and modify the accumulation of molnupiravir in Salmo trutta embryos and larvae. In addition, 2D/3D confocal fluorescence imaging showed that the single polymeric particle hardly accumulates and couldn't penetrate outer tissues of the tested organism. However, co-exposure micro/nanoplastics and molnupiravir could significantly enhance the polymeric particles capability of accumulating on surface tissues and penetrating surface tissue of fish in early development. Exposure to molnupiravir at 2 g/L concentration and co-exposure to micro/nanoplastics and molnupiravir did not bring about survival changes in in the early stages of Salmo trutta development, but we observed the reduction in heart rate and decrease in gill ventilation. The statistical analysis confirmed that micro/nanoplastics used in combination with molnupiravir enhance the toxicity of the latter micro/nanoplastics to embryos and larvae. This research has received funding from the European Regional Development Fund (project No 13.1.1-LMT-K-718-05-0014) under a grant agreement with the Research Council of Lithuania (LMTLT), and it was funded as part of the European Union’s measure in response to the COVID-19 pandemic.

Keywords: fish, micro/nanoplastics, molnupiravir, toxicity

Procedia PDF Downloads 95

Authors: Zhongmin Wang, Wudong Fan, Hengshan Zhang, Yimin Zhou

Abstract:

In data-driven prognostic methods, the prediction accuracy of the estimation for remaining useful life of bearings mainly depends on the performance of health indicators, which are usually fused some statistical features extracted from vibrating signals. However, the existing health indicators have the following two drawbacks: (1) The differnet ranges of the statistical features have the different contributions to construct the health indicators, the expert knowledge is required to extract the features. (2) When convolutional neural networks are utilized to tackle time-frequency features of signals, the time-series of signals are not considered. To overcome these drawbacks, in this study, the method combining convolutional neural network with gated recurrent unit is proposed to extract the time-frequency image features. The extracted features are utilized to construct health indicator and predict remaining useful life of bearings. First, original signals are converted into time-frequency images by using continuous wavelet transform so as to form the original feature sets. Second, with convolutional and pooling layers of convolutional neural networks, the most sensitive features of time-frequency images are selected from the original feature sets. Finally, these selected features are fed into the gated recurrent unit to construct the health indicator. The results state that the proposed method shows the enhance performance than the related studies which have used the same bearing dataset provided by PRONOSTIA.

Keywords: continuous wavelet transform, convolution neural net-work, gated recurrent unit, health indicators, remaining useful life

Procedia PDF Downloads 133

Authors: Tugba Bayoglu

Abstract:

Aerodynamic parameter estimation is very crucial in missile design phase, since accurate high fidelity aerodynamic model is required for designing high performance and robust control system, developing high fidelity flight simulations and verification of computational and wind tunnel test results. However, in literature, there is not enough missile aerodynamic parameter identification study for three main reasons: (1) most air to air missiles cannot fly with constant speed, (2) missile flight test number and flight duration are much less than that of fixed wing aircraft, (3) variation of the missile aerodynamic parameters with respect to Mach number is higher than that of fixed wing aircraft. In addition to these challenges, identification of aerodynamic parameters for high wind angles by using classical estimation techniques brings another difficulty in the estimation process. The reason for this, most of the estimation techniques require employing polynomials or splines to model the behavior of the aerodynamics. However, for the missiles with a large variation of aerodynamic parameters with respect to flight variables, the order of the proposed model increases, which brings computational burden and complexity. Therefore, in this study, it is aimed to solve nonlinear aerodynamic parameter identification problem for a supersonic air to air missile by using Artificial Neural Networks. The method proposed will be tested by using simulated data which will be generated with a six degree of freedom missile model, involving a nonlinear aerodynamic database. The data will be corrupted by adding noise to the measurement model. Then, by using the flight variables and measurements, the parameters will be estimated. Finally, the prediction accuracy will be investigated.

Keywords: air to air missile, artificial neural networks, open loop simulation, parameter identification

Procedia PDF Downloads 279

Authors: Mohammed Saleh Rezk, Reza Kashani

Abstract:

Auxiliary damping has gained popularity in recent years, especially in structures such as mid- and high-rise buildings. Distributed damping systems (typically viscous and viscoelastic) or reactive damping systems (such as tuned mass dampers) are the two types of damping choices for such structures. Distributed VE dampers are normally configured as braces or damping panels, which are engaged through relatively small movements between the structural members when the structure sways under wind or earthquake loading. In addition to being used as stand-alone dampers in distributed damping applications, VE dampers can also be incorporated into the suspension element of tuned mass dampers (TMDs). In this study, analytical and numerical tools for modeling and design of multilayer viscoelastic damping devices to be used in dampening the vibration of large structures are developed. Considering the limitations of analytical models for the synthesis and analysis of realistic, large, multilayer VE dampers, the emphasis of the study has been on numerical modeling using the finite element method. To verify the finite element models, a two-layer VE damper using ½ inch synthetic viscoelastic urethane polymer was built, tested, and the measured parameters were compared with the numerically predicted ones. The numerical model prediction and experimentally evaluated damping and stiffness of the test VE damper were in very good agreement. The effectiveness of VE dampers in adding auxiliary damping to larger structures is numerically demonstrated by chevron bracing one such damper numerically into the model of a massive frame subject to an abrupt lateral load. A comparison of the responses of the frame to the aforementioned load, without and with the VE damper, clearly shows the efficacy of the damper in lowering the extent of frame vibration.

Keywords: viscoelastic, damper, distributed damping, tuned mass damper

Procedia PDF Downloads 107

Authors: Mikiale Gebreslase Gebremariam, Chai Huaqi, Tesfay Gebretsdkan Gebremichael, Dawit Nega Bekele

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In recent years, brownfield redevelopment projects (BRPs) have contributed to the overarching paradigm of the United Nations 2030 agendas. In the present circumstance, most developed nations adopted BRPs, an efficacious urban policy tool. However, in developing and some advanced countries, BRPs are lacking due to limitations of awareness, policy tools, and financial capability for cleaning up brownfield sites. For example, the growth and development of Ethiopian cities were achieved at the cost of poor urban planning, including no community consultations and excessive urbanization for future growth. The demand for land resources is more and more urgent as the result of an intermigration to major cities and towns for socio-economic reasons and population growth. In the past, the development mode of spreading major cities has made horizontal urbanizations stretching outwards. Expansion in search of more land resources, while the outer cities are growing, the inner cities are polluted by environmental pollution. It is noteworthy that the rapid development of cities has not brought about an increase in people's happiness index. Thus, the proposed management framework for managing brownfields in Ethiopia as a lesson to the developing nation facing similar challenges and growth will add immense value in solving the problems and give insights into brownfield land utilization. Under the umbrella of the grey incidence decision-making model and with the consideration of multiple stakeholders and tight environmental and economic constraints, the proposed management framework integrates different criteria from economic, social, environmental, technical, and risk aspects into the grey incidence decision-making model and gives useful guidance to manage brownfields in Ethiopia. Furthermore, it will contribute to the future development of the social economy and the missions of the 2030 UN sustainable development goals.

Keywords: Brownfields, environmental sustainability, Ethiopia, grey-incidence decision-making, sustainable urban development

Procedia PDF Downloads 91

Authors: Mohanad Al-Behadili, Xiang Song, Djamila Ouelhadj, Alex Fraess-Ehrfeld

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In off-shore wind farms, turbine blade inspection accessibility under various sea states is very challenging and greatly affects the downtime of wind turbines. Maintenance of any offshore system is not an easy task due to the restricted logistics and accessibility. The multirotor unmanned helicopter is of increasing interest in inspection applications due to its manoeuvrability and payload capacity. These advantages increase when many of them are deployed simultaneously in a swarm. Hence this paper proposes a drone swarm framework for inspecting offshore wind turbine blades and nacelles so as to reduce downtime. One of the big challenges of this task is that when operating a drone swarm, an individual drone may not have enough power to fly and communicate during missions and it has no capability of refueling due to its small size. Once the drone power is drained, there are no signals transmitted and the links become intermittent. Vessels equipped with 5G masts and small power units are utilised as platforms for drones to recharge/swap batteries. The research work aims at designing a smart energy management system, which provides automated vessel and drone routing and recharging plans. To achieve this goal, a novel mathematical optimisation model is developed with the main objective of minimising the number of drones and vessels, which carry the charging stations, and the downtime of the wind turbines. There are a number of constraints to be considered, such as each wind turbine must be inspected once and only once by one drone; each drone can inspect at most one wind turbine after recharging, then fly back to the charging station; collision should be avoided during the drone flying; all wind turbines in the wind farm should be inspected within the given time window. We have developed a real-time Ant Colony Optimisation (ACO) algorithm to generate real-time and near-optimal solutions to the drone swarm routing problem. The schedule will generate efficient and real-time solutions to indicate the inspection tasks, time windows, and the optimal routes of the drones to access the turbines. Experiments are conducted to evaluate the quality of the solutions generated by ACO.

Keywords: drone swarm, routing, scheduling, optimisation model, ant colony optimisation

Procedia PDF Downloads 266

Authors: Ashirgul Kozhagulova, Ainash Shabdirova, Galym Tokazhanov, Minh Nguyen

Abstract:

The synthetic rocks have been advantageous over the natural rocks in terms of availability and the consistent studying the impact of a particular parameter. The artificial rocks can be fabricated using variety of techniques such as mixing sand and Portland cement or gypsum, firing the mixture of sand and fine powder of borosilicate glass or by in-situ precipitation of calcite solution. In this study, sodium silicate solution has been used as the cementing agent for the quartz sand. The molded soft cylindrical sandstone samples are placed in the gas-tight pressure vessel, where the hardening of the material takes place as the chemical reaction between carbon dioxide and the silicate solution progresses. The vessel allows uniform disperse of carbon dioxide and control over the ambient gas pressure. Current paper shows how the bonding material is initially distributed in the intergranular space and the surface of the sand particles by the usage of Electron Microscopy and the Energy Dispersive Spectroscopy. During the study, the strength of the cement bond as a function of temperature is observed. The impact of cementing agent dosage on the micro and macro characteristics of the sandstone is investigated. The analysis of the cement bond at micro level helps to trace the changes to particles bonding damage after a potential yielding. Shearing behavior and compressional response have been examined resulting in the estimation of the shearing resistance and cohesion force of the sandstone. These are considered to be main input values to the mathematical prediction models of sand production from weak clastic oil reservoir formations.

Keywords: artificial sanstone, cement bond, microstructure, SEM, triaxial shearing

Procedia PDF Downloads 168

Authors: Ashis Mallick, Rajeev Ranjan

Abstract:

The closed form solution for thermal stresses in an annular fin with hyperbolic profile is derived using Adomian decomposition method (ADM). The conductive-convective fin with variable thermal conductivity is considered in the analysis. The nonlinear heat transfer equation is efficiently solved by ADM considering insulated convective boundary conditions at the tip of fin. The constant of integration in the solution is to be estimated using minimum decomposition error method. The solution of temperature field is represented in a polynomial form for convenience to use in thermo-elasticity equation. The non-dimensional thermal stress fields are obtained using the ADM solution of temperature field coupled with the thermo-elasticity solution. The influence of the various thermal parameters in temperature field and stress fields are presented. In order to show the accuracy of the ADM solution, the present results are compared with the results available in literature. The stress fields in fin with hyperbolic profile are compared with those of uniform thickness profile. Result shows that hyperbolic fin profile is better choice for enhancing heat transfer. Moreover, less thermal stresses are developed in hyperbolic profile as compared to rectangular profile. Next, Nelder-Mead based simplex search method is employed for the inverse estimation of unknown non-dimensional thermal parameters in a given stress fields. Owing to the correlated nature of the unknowns, the best combinations of the model parameters which are satisfying the predefined stress field are to be estimated. The stress fields calculated using the inverse parameters give a very good agreement with the stress fields obtained from the forward solution. The estimated parameters are suitable to use for efficient and cost effective fin designing.

Keywords: Adomian decomposition, inverse analysis, hyperbolic fin, variable thermal conductivity

Procedia PDF Downloads 327

Authors: Omar Bouledroua, Djamel Zelmati, Zahreddine Hafsi, Milos B. Djukic

Abstract:

Transporting hydrogen gas through the existing natural gas pipeline network offers an efficient solution for energy storage and conveyance. Hydrogen generated from excess renewable electricity can be conveyed through the API 5L steel-made pipelines that already exist. In recent years, there has been a growing demand for the transportation of hydrogen through existing gas pipelines. Therefore, numerical and experimental tests are required to verify and ensure the mechanical integrity of the API 5L steel pipelines that will be used for pressurized hydrogen transportation. Internal pressure loading is likely to accelerate hydrogen diffusion through the internal pipe wall and consequently accentuate the hydrogen embrittlement of steel pipelines. Furthermore, pre-cracked pipelines are susceptible to quick failure, mainly under a time-dependent cyclic pressure loading that drives fatigue crack propagation. Meanwhile, after several loading cycles, the initial cracks will propagate to a critical size. At this point, the remaining service life of the pipeline can be estimated, and inspection intervals can be determined. This paper focuses on the hydrogen embrittlement of API 5L steel-made pipeline under cyclic pressure loading. Pressurized hydrogen gas is transported through a network of pipelines where demands at consumption nodes vary periodically. The resulting pressure profile over time is considered a cyclic loading on the internal wall of a pre-cracked pipeline made of API 5L steel-grade material. Numerical modeling has allowed the prediction of fatigue crack evolution and estimation of the remaining service life of the pipeline. The developed methodology in this paper is based on the ASME B31.12 standard, which outlines the guidelines for hydrogen pipelines.

Keywords: hydrogen embrittlement, pipelines, transient flow, cyclic pressure, fatigue crack growth

Procedia PDF Downloads 88

Authors: Mauro Iannazzone, Carmine D'Agostino

Abstract:

Off-shore wind turbines are currently considered as a reliable source of renewable energy Worldwide and especially in the UK. Most of the operational off-shore wind turbines located in shallow waters (i.e. < 30 m) are supported on monopiles. Monopiles are open-ended steel tubes with diameter ranging between 4 to 6 m. It is expected that future off-shore wind farms will be located in water depths as high as 70 m. Therefore, alternative foundation arrangements are needed. Foundations for off-shore structures normally consist of open-ended piles driven into the soil by means of impact hammers. During pile installation, the soil inside the pile may be mobilized by the increasing shear strength such as to prevent more soil from entering the pile. This phenomenon is known as soil plugging, and represents an important issue as it may change significantly the driving resistance of open-ended piles. In fact, if the plugging formation is unexpected, the installation may require more powerful and more expensive hammers. Engineers need to estimate whether the driven pile will be installed in a plugged or unplugged mode. As a consequence, a prediction of the degree of soil plugging is required in order to correctly predict the drivability of the pile. This work presents a brief review of the state-of-the-art of pile driving and approaches used to predict formation of soil plugs. In addition, a novel analytical approach is proposed, which is based on the vertical equilibrium of a plugged pile. Differently from previous studies, this research takes into account the enhancement of the stress within the soil plug. Finally, the work presents and discusses a series of experimental tests, which are carried out on small-scale models piles to validate the analytical solution.

Keywords: off-shore wind turbines, pile installation, soil plugging, wind energy

Procedia PDF Downloads 312

Authors: Olawale S. Fatoba, Stephen A. Akinlabi, Esther T. Akinlabi, Rezvan Gharehbaghi

Abstract:

The performance of material surface under wear and corrosion environments cannot be fulfilled by the conventional surface modifications and coatings. Therefore, different industrial sectors need an alternative technique for enhanced surface properties. Titanium and its alloys possess poor tribological properties which limit their use in certain industries. This paper focuses on the effect of hybrid coatings Al-Cu-Fe on a grade five titanium alloy using laser metal deposition (LMD) process. Icosahedral Al-Cu-Fe as quasicrystals is a relatively new class of materials which exhibit unusual atomic structure and useful physical and chemical properties. A 3kW continuous wave ytterbium laser system (YLS) attached to a KUKA robot which controls the movement of the cladding process was utilized for the fabrication of the coatings. The titanium cladded surfaces were investigated for its hardness, corrosion and tribological behaviour at different laser processing conditions. The samples were cut to corrosion coupons, and immersed into 3.65% NaCl solution at 28oC using Electrochemical Impedance Spectroscopy (EIS) and Linear Polarization (LP) techniques. The cross-sectional view of the samples was analysed. It was found that the geometrical properties of the deposits such as width, height and the Heat Affected Zone (HAZ) of each sample remarkably increased with increasing laser power due to the laser-material interaction. It was observed that there are higher number of aluminum and titanium presented in the formation of the composite. The indentation testing reveals that for both scanning speed of 0.8 m/min and 1m/min, the mean hardness value decreases with increasing laser power. The low coefficient of friction, excellent wear resistance and high microhardness were attributed to the formation of hard intermetallic compounds (TiCu, Ti2Cu, Ti3Al, Al3Ti) produced through the in situ metallurgical reactions during the LMD process. The load-bearing capability of the substrate was improved due to the excellent wear resistance of the coatings. The cladded layer showed a uniform crack free surface due to optimized laser process parameters which led to the refinement of the coatings.

Keywords: Al-Cu-Fe coating, corrosion, intermetallics, laser metal deposition, Ti-6Al-4V alloy, wear resistance

Procedia PDF Downloads 178

Authors: Z. Arabshahi, I. Afara, A. Oloyede, H. Moody, J. Kashani, T. Klein

Abstract:

Articular cartilage is a fluid-swollen tissue of synovial joints that functions by providing a lubricated surface for articulation and to facilitate the load transmission. The biomechanical function of this tissue is highly dependent on the integrity of its ultrastructural matrix. Any alteration of articular cartilage matrix, either by injury or degenerative conditions such as osteoarthritis (OA), compromises its functional behaviour. Therefore, the assessment of articular cartilage is important in early stages of degenerative process to prevent or reduce further joint damage with associated socio-economic impact. Therefore, there has been increasing research interest into the functional assessment of articular cartilage. This study developed a characterization parameter for articular cartilage assessment based on the response of cartilage surface to loading/unloading. This is because the response of articular cartilage to compressive loading is significantly depth-dependent, where the superficial zone and underlying matrix respond differently to deformation. In addition, the alteration of cartilage matrix in the early stages of degeneration is often characterized by PG loss in the superficial layer. In this study, it is hypothesized that the response of superficial layer is different in normal and proteoglycan depleted tissue. To establish the viability of this hypothesis, samples of visually intact and artificially proteoglycan-depleted bovine cartilage were subjected to compression at a constant rate to 30 percent strain using a ring-shaped indenter with an integrated ultrasound probe and then unloaded. The response of articular surface which was indirectly loaded was monitored using ultrasound during the time of loading/unloading (deformation/recovery). It was observed that the rate of cartilage surface response to loading/unloading was different for normal and PG-depleted cartilage samples. Principal Component Analysis was performed to identify the capability of the cartilage surface response to loading/unloading, to distinguish between normal and artificially degenerated cartilage samples. The classification analysis of this parameter showed an overlap between normal and degenerated samples during loading. While there was a clear distinction between normal and degenerated samples during unloading. This study showed that the cartilage surface response to loading/unloading has the potential to be used as a parameter for cartilage assessment.

Keywords: cartilage integrity parameter, cartilage deformation/recovery, cartilage functional assessment, ultrasound

Procedia PDF Downloads 192