Search results for: healthcare waste disposal

Authors: Jaroslav Frantík, Jan Najser

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This article deals with increasing the energy efficiency of a plant in terms of optimizing the process. The European Union is striving to achieve the climate-energy package in the area increasing of energy efficiency. The goal of energy efficiency is to reduce primary energy consumption by 20% within the EU until 2020. The objective of saving energy consumption in the Czech Republic was set at 47.84 PJ (13.29 TWh). For reducing electricity consumption, it is possible to choose: a) mandatory increasing of energy efficiency, b) alternative scheme, c) combination of both actions. The Czech Republic has chosen for reducing electricity consumption using-alternative scheme. The presentation is focused on the proposal of a technological unit dealing with the gasification process of processing of biomass with an increase of power in the output. The synthesis gas after gasification of biomass is used as fuel in a cogeneration process of reciprocating internal combustion engine with the classic production of heat and electricity. Subsequently, there is an explanation of the ORC system dealing with the conversion of waste heat to electricity with the using closed cycle of the steam process with organic medium. The arising electricity is distributed to the power grid as a further energy source, or it is used for needs of the partial coverage of the technological unit. Furthermore, there is a presented schematic description of the technology with the identification of energy flows starting from the biomass treatment by drying, through its conversion to gaseous fuel, producing of electricity and utilize of thermal energy with minimizing losses. It has been found that using of ORC system increased the efficiency of the produced electricity by 7.5%.

Keywords: biomass, efficiency, gasification, ORC system

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Authors: Aya Belal, Ahmed Maher Eltair, Maggie Ahmed Mashaly

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Geopolymer concrete is gaining recognition as a sustainable alternative to conventional Portland Cement concrete due to its environmentally friendly nature, which is a key goal for Smart City initiatives. It has demonstrated its potential as a reliable material for the design of structural elements. However, the production of Geopolymer concrete is hindered by batch-to-batch variations, which presents a significant challenge to the widespread adoption of Geopolymer concrete. To date, Machine learning has had a profound impact on various fields by enabling models to learn from large datasets and predict outputs accurately. This paper proposes an integration between the current drift to Artificial Intelligence and the composition of Geopolymer mixtures to predict their mechanical properties. This study employs Python software to develop machine learning model in specific Decision Trees. The research uses the percentage oxides and the chemical composition of the Alkali Solution along with the curing conditions as the input independent parameters, irrespective of the waste products used in the mixture yielding the compressive strength of the mix as the output parameter. The results showed 90 % agreement of the predicted values to the actual values having the ratio of the Sodium Silicate to the Sodium Hydroxide solution being the dominant parameter in the mixture.

Keywords: decision trees, geopolymer concrete, machine learning, smart cities, sustainability

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Authors: Saeed Karimi, Ali Behbahaninia

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In this study, the design and optimization of combined cooling, heating, and power system (CCHP) for a sustainable building are dealt with. Sustainable buildings are environmentally responsible and help us to save energy also reducing waste, pollution and environmental degradation. CCHP systems are widely used to save energy sources. In these systems, electricity, cooling, and heating are generating using just one primary energy source. The selection of the size of components based on the maximum demand of users will lead to an increase in the total cost of energy and equipment for the building complex. For this purpose, a system was designed in which the prime mover (gas turbine), heat recovery boiler, and absorption chiller are lower than the needed maximum. The difference in months with peak consumption is supplied with the help of electrical absorption chiller and auxiliary boiler (and the national electricity network). In this study, the optimum capacities of each of the equipment are determined based on Thermo economic method, in a way that the annual capital cost and energy consumption will be the lowest. The design was done for a gas turbine prime mover, and finally, the optimum designs were investigated using exergy analysis and were compared with a traditional energy supply system.

Keywords: sustainable building, CCHP, energy optimization, gas turbine, exergy, thermo-economic

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Authors: Kehabtimer Shiferaw Kotiso, Getachew Hailemariam, Abiy Seifu Estifanos

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Introduction: Despite the highest share of low birth weight (LBW) for neonatal mortality and morbidity, predicting births with LBW for better intervention preparation is challenging. This study aims to predict LBW using a dataset encompassing 53,637 birth cohorts collected from 36 primary hospitals across seven regions in Ethiopia from February 2022 to June 2024. Methods: We identified ten explanatory variables related to maternal and neonatal characteristics, including maternal education, age, residence, history of miscarriage or abortion, history of preterm birth, type of pregnancy, number of livebirths, number of stillbirths, antenatal care frequency, and sex of the fetus to predict LBW. Using WEKA 3.8.2, we developed and compared seven machine learning algorithms. Data preprocessing included handling missing values, outlier detection, and ensuring data integrity in birth weight records. Model performance was evaluated through metrics such as accuracy, precision, recall, F1-score, and area under the Receiver Operating Characteristic curve (ROC AUC) using 10-fold cross-validation. Results: The results demonstrated that the decision tree, J48, logistic regression, and gradient boosted trees model achieved the highest accuracy (94.5% to 94.6%) with a precision of 93.1% to 93.3%, F1-score of 92.7% to 93.1%, and ROC AUC of 71.8% to 76.6%. Conclusion: This study demonstrates the effectiveness of machine learning models in predicting LBW. The high accuracy and recall rates achieved indicate that these models can serve as valuable tools for healthcare policymakers and providers in identifying at-risk newborns and implementing timely interventions to achieve the sustainable developmental goal (SDG) related to neonatal mortality.

Keywords: low birth weight, machine learning, classification, neonatal mortality, Ethiopia

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Authors: Nazanin Gerami, Shirin Adlparvar

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In the present time in the laboratory, one can create an ionized gas, that is to say, plasma from room temperature up to ten times more than the temperature of the sun center (150,000,000). All these temperature spectrums of plasma have applications in different disciplines, including dentistry, medicine, science, surface treatment, nuclear waste disinfection, nuclear fusion technology, etc. However, for the sick of simplicity, all these plasma temperature spectrums are classified as cold or low-pressure non-thermal plasma and warm or high-pressure equilibrium plasma. The cold plasma, as we are interested in this paper, exists at lower ion and neutral temperatures with respect to electron temperature, but in the equilibrium plasma, the temperatures of ion and electron are fairly equal. The cold plasma is a partially ionized gas comprising ions, electrons, ultraviolet photons and reactive neutrals such as radicals, excited and ground-state molecules. Cold atmospheric pressure plasmas are widely used in diverse fields of dental medicine, such as the titanium surface of dental implants, which helps in reducing contact angle and supporting the spread of osteoblastic cells and is known to aid in osteoblastic proliferation and osseointegration, thus increasing the success rates of implants. This article focuses on the anticipated uses of a newly designed water-cooled adjustable cathode cold atmospheric pressure plasma Jet (CAPPJ) for titanium surface treatment in dental implant placement.

Keywords: CAPPJ, surface modification, osseointegration, plasma medicine, dentistry

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Authors: Arunkumar Thirugnanasambantham, Velraj Ramalingam

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An experimental attempt has been made to study the effect of system integration by two different concentrator assisted desalting systems. The compound parabolic concentrator (CPC) and compound conical concentrator (CCC) are used in this research work. Two solar desalination systems, the single slope solar still (SSSS) and pyramid solar still (PSS), have been integrated with a CCC and compound parabolic concentrator-concentric circular tubular solar still (CPC-CCTSS). To study the effect of system integration, a thick cloth prevents the entry of sunlight into the solar still top. Additionally, the concentrator assisted desalting systems are equipped with phase change material (PCM) for enhancement. In CCC-SSSS, PCM has been filled inside copper balls and placed on the SSSS basin. The PCM is loaded in the specially designed circular trough of the tubular solar still. Here, the used concentrators and distillers are not the same. Two methodologies are followed here to produce the fresh water even while the distillers are blocked from the sunlight. They are (1) thermosyphon effect in CCC-SSSS and (2) waste heat recovery from CPC-CCTSS. The results showed that the productivity of CCC-SSSS, CCC-SSSS with PCM and CCC-SSSS (PCM) top cover shaded were found as 2680 ml / m² / day, 3240 ml / m² / day, and 1646 ml / m² / day. Similarly, the productivity of the CPC-CCTSS-PSS, CPC-CCTSS (PCM)-PSS and CPC-CCTSS (PCM)-PSS top cover shaded were found as 7160 ml / m² / day, 7346 ml / m² / day, and ml / m² / day. The productivity of the CCC-SSSS and CPC-CCTSS-PSS is examined, and conclusions are drawn such as the solar radiation blocked distillers productivity did not drop to zero.

Keywords: compound conical concentrator, compound parabolic concentrator, desalination, system integration

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Authors: Hadi Gholizadeh, Ali Tajdin

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To have effective production planning, it is necessary to control the quality of processes. This paper aims at improving the performance of the disposable essentials process using statistical quality control and goal programming in a vague environment. That is expressed uncertainty because there is always a measurement error in the real world. Therefore, in this study, the conditions are examined in a vague environment that is a distance-based environment. The disposable essentials process in Kach Company was studied. Statistical control tools were used to characterize the existing process for four factor responses including the average of disposable glasses’ weights, heights, crater diameters, and volumes. Goal programming was then utilized to find the combination of optimal factors setting in a vague environment which is measured to apply uncertainty of the initial information when some of the parameters of the models are vague; also, the fuzzy regression model is used to predict the responses of the four described factors. Optimization results show that the process capability index values for disposable glasses’ average of weights, heights, crater diameters and volumes were improved. Such increasing the quality of the products and reducing the waste, which will reduce the cost of the finished product, and ultimately will bring customer satisfaction, and this satisfaction, will mean increased sales.

Keywords: goal programming, quality control, vague environment, disposable glasses’ optimization, fuzzy regression

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Authors: Taha SamadSoltani, Peyman Rezaei Hachesu, Marjan GhaziSaeedi, Maryam Zolnoori

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Introduction: Data mining defined as a process to find patterns and relationships along data in the database to build predictive models. Application of data mining extended in vast sectors such as the healthcare services. Medical data mining aims to solve real-world problems in the diagnosis and treatment of diseases. This method applies various techniques and algorithms which have different accuracy and precision. The purpose of this study was to apply knowledge discovery and data mining techniques for the diagnosis of asthma based on patient symptoms and history. Method: Data mining includes several steps and decisions should be made by the user which starts by creation of an understanding of the scope and application of previous knowledge in this area and identifying KD process from the point of view of the stakeholders and finished by acting on discovered knowledge using knowledge conducting, integrating knowledge with other systems and knowledge documenting and reporting.in this study a stepwise methodology followed to achieve a logical outcome. Results: Sensitivity, Specifity and Accuracy of KNN, SVM, Naïve bayes, NN, Classification tree and CN2 algorithms and related similar studies was evaluated and ROC curves were plotted to show the performance of the system. Conclusion: The results show that we can accurately diagnose asthma, approximately ninety percent, based on the demographical and clinical data. The study also showed that the methods based on pattern discovery and data mining have a higher sensitivity compared to expert and knowledge-based systems. On the other hand, medical guidelines and evidence-based medicine should be base of diagnostics methods, therefore recommended to machine learning algorithms used in combination with knowledge-based algorithms.

Keywords: asthma, datamining, classification, machine learning

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Authors: M. Bilal Ishfaq, Adnan N. Qureshi

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COVID-19 is the most infectious disease these days, it was first reported in Wuhan, the capital city of Hubei in China then it spread rapidly throughout the whole world. Later on 11 March 2020, the World Health Organisation (WHO) declared it a pandemic. Since COVID-19 is highly contagious, it has affected approximately 219M people worldwide and caused 4.55M deaths. It has brought the importance of accurate diagnosis of respiratory diseases such as pneumonia and COVID-19 to the forefront. In this paper, we propose a hybrid approach for the automated detection of COVID-19 using medical imaging. We have presented the hybridization of manually extracted and convolutional features. Our approach combines Haralick texture features and convolutional features extracted from chest X-rays and CT scans. We also employ a minimum redundancy maximum relevance (MRMR) feature selection algorithm to reduce computational complexity and enhance classification performance. The proposed model is evaluated on four publicly available datasets, including Chest X-ray Pneumonia, COVID-19 Pneumonia, COVID-19 CTMaster, and VinBig data. The results demonstrate high accuracy and effectiveness, with 0.9925 on the Chest X-ray pneumonia dataset, 0.9895 on the COVID-19, Pneumonia and Normal Chest X-ray dataset, 0.9806 on the Covid CTMaster dataset, and 0.9398 on the VinBig dataset. We further evaluate the effectiveness of the proposed model using ROC curves, where the AUC for the best-performing model reaches 0.96. Our proposed model provides a promising tool for the early detection and accurate diagnosis of COVID-19, which can assist healthcare professionals in making informed treatment decisions and improving patient outcomes. The results of the proposed model are quite plausible and the system can be deployed in a clinical or research setting to assist in the diagnosis of COVID-19.

Keywords: COVID-19, feature engineering, artificial neural networks, radiology images

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Authors: Grant Bifolchi

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As global environmental problems continue to have highly adverse effects, finding long-term, sustainable solutions to combat ecological distress are of growing paramount concern. Ghost Gear—also known as abandoned, lost or otherwise discarded fishing gear (ALDFG) and derelict fishing gear (DFG)—represents one of the greatest threats to the world’s oceans, posing a significant hazard to human health, livelihoods, and global food security. In fact, according to the UN Food and Agriculture Organization (FAO), abandoned, lost and discarded fishing gear represents approximately 10% of marine debris by volume. Around the world, many governments, governmental and non-profit organizations are doing their best to manage the reporting and retrieval of nets, lines, ropes, traps, floats and more from their respective bodies of water. However, these organizations’ ability to effectively manage files and documents about the environmental problem further complicates matters. In Ghost Gear monitoring and management, organizations face additional complexities. Whether it’s data ingest, industry regulations and standards, garnering actionable insights into the location, security, and management of data, or the application of enforcement due to disparate data—all of these factors are placing massive strains on organizations struggling to save the planet from the dangers of Ghost Gear. In this 90-minute educational session, globally recognized Ghost Gear technology expert Grant Bifolchi CET, BBA, Bcom, will provide real-world insight into how governments currently manage Ghost Gear and the technology that can accelerate success in combatting ALDFG and DFG. In this session, attendees will learn how to: • Identify specific technologies to solve the ingest and management of Ghost Gear data categories, including type, geo-location, size, ownership, regional assignment, collection and disposal. • Provide enhanced access to authorities, fisheries, independent fishing vessels, individuals, etc., while securely controlling confidential and privileged data to globally recognized standards. • Create and maintain processing accuracy to effectively track ALDFG/DFG reporting progress—including acknowledging receipt of the report and sharing it with all pertinent stakeholders to ensure approvals are secured. • Enable and utilize Business Intelligence (BI) and Analytics to store and analyze data to optimize organizational performance, maintain anytime-visibility of report status, user accountability, scheduling, management, and foster governmental transparency. • Maintain Compliance Reporting through highly defined, detailed and automated reports—enabling all stakeholders to share critical insights with internal colleagues, regulatory agencies, and national and international partners.

Keywords: ghost gear, ALDFG, DFG, abandoned, lost or otherwise discarded fishing gear, data, technology

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Authors: Ben Salah Nahla

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The problem of water in Tunisia affects the quality and quantity. Tunisia is in a situation of water shortage. It was estimated that 4.6 Mm3/an. Moreover, the quality of water in Tunisia is also mediocre. In fact, 50% of the water has a high salinity (> 1.5g/l). There are several parameters which affect water quality such as sodium, fluoride. An excess of this parameter may induce some human health. Furthermore, the mining basin area has a problem of industrial waste. This problem may affect the water quality of the groundwater. Therefore, the purpose of this work is to assess the water quality in Basin Mining and the impact of fluorine. For this research, some water samples were done in the field and specific water analysis was implemented in the laboratory. Sampling is carried out on eight drilling in the area of the mining region. In the following, we will look at water view composition, physical and chemical quality. A physical-chemical analysis of water from a survey of the Mining area of Tunisia was performed and showed an excess for the following items: fluorine, sodium, sulfate. So many chemicals may be present in water. However, only a small number of them immediately concern in terms of health in all circumstances. Fluorine (F) is one particular chemical that is considered both necessary for the human body, but an excess of the rate of this chemical causes serious diseases. Sodium fluoride and sodium silicofluoride are more soluble and may spread in animals and plants where their toxicity largest organizations. The more complex particles such as cryolite and fluorite, almost insoluble, are more stable and less toxic. Thereafter, we will study the problem of excess fluorine in the water. The latter intended for human consumption must always comply with the limits for microbiological quality parameters and physical-chemical parameters defined by European standards (1.5 mg/l) and Tunisian (2 mg/l).

Keywords: water, minier basin, fluorine, silicofluoride

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

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

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

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Authors: Donatella Cimini, Sergio D’ambrosio, Saba Sadiq, Chiara Schiraldi

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Chondroitin sulfate (CS), as well as modified CS, and unsulfated chondroitin, are largely applied in research today. CS is a linear glycosaminoglycan normally present in cartilage-rich tissues and bones in the form of proteoglycans decorated with sulfate groups in different positions. CS is used as an effective non-pharmacological alternative for the treatment of osteoarthritis, and other potential applications in the biomedical field are being investigated. Some bacteria, such as E. coli K4, produce a polysaccharide that is a precursor of CS (unsulfated chondroitin). This work focused on the construction of integrative E. coli K4 recombinant strains overexpressing genes (kfoA, kfoF, pgm and galU in different combinations) involved in the biosynthesis of the nucleotide sugars necessary for polysaccharide synthesis. Strain growth and polymer production were evaluated using renewable waste materials as substrates in shake flasks and small-scale batch fermentation processes. Results demonstrated the potential to replace pure sugars with cheaper medium components to establish environmentally sustainable and cost-effective production routes for potential industrial development. In fact, although excellent fermentation results have been described so far by employing strains that naturally produce chondroitin-like polysaccharides on semi-defined media, there is still the need to reduce manufacturing costs by providing a cost-effective biotechnological alternative to currently used animal-based extraction procedures.

Keywords: E. coli K4, chondroitin, microbial cell factories, glycosaminoglycans, renewable resources

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Authors: Fatima Taqi, Abrar Alanzi

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Objectives: The objective of this study is to determine and assess the level of knowledge and attitudes of dental patients attending Kuwait University Dental Clinics (KUDC) regarding the infection control protocols practiced in the clinic. The results would highlight the importance of conducting awareness campaigns in the community to promote good oral healthcare in Kuwait. Materials and Methods: A cross-sectional descriptive survey was carried out among dental patients attending KUDC. A structured questionnaire, in both Arabic and English languages, was used for data collection about the socio-demographic characteristics, knowledge about the dental cross-infection, and attitudes and self-reported practices regarding infection transmission and control in dentistry. Results: A response rate of 80% (202/250) was reported. 47% of respondents had poor knowledge about dental infection transmission, and only 19.8% had satisfactory knowledge. Female participants obtained a higher satisfactory score (14.3%) compared to males (5.5%). Patients with a university degree or higher education had a better level of knowledge compared to patients with a lower educational level (p < 0.05). The majority of participants agreed that the dentist should wear gloves (95.5%), masks (89.6%), safety glasses (70.3%), and gowns (84.7%). Many patients believed that the protection measures are mainly to stop the infection transmission from patient to patient via the dentist. Half of the participants would ask if the instruments are sterilized and might accept treatment from non-vaccinated dentists. Conclusions: Many dental patients attending KUDC have obtained poor knowledge scores regarding infection transmission in the dental clinic. The educational level was significantly associated with their level of knowledge. An overall positive attitude was reported regarding the infection control protocols practiced in the dental clinic. Raising awareness among dental patients about dental infection transmission and protective measures is of utmost importance.

Keywords: dental infection, knowledge, dental patients, infection control

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Authors: F. Javier Benitez, Francisco J. Real, Juan Luis Acero, Francisco Casas

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Three emerging contaminants (amitriptyline hydrochloride, methyl salicylate and 2-phenoxyethanol) frequently found in waste-waters were selected to be individually degraded in ultra-pure water by the combined advanced oxidation process constituted by UV radiation and chlorine. The influence of pH, initial chlorine concentration and nature of the contaminants was firstly explored. The trend for the reactivity of the selected compounds was deduced: amitriptyline hydrochloride > methyl salicylate > 2-phenoxyethanol. A later kinetic study was carried out and focused on the specific evaluation of the first-order rate constants and the determination of the partial contribution to the global reaction of the direct photochemical pathway and the radical pathway. A comparison between the rate constant values among photochemical experiments without and with the presence of Cl₂ reveals a clear increase in the oxidation efficiency of the combined process with respect to the photochemical reaction alone. In a second stage, the simultaneous oxidation of mixtures of the selected contaminants in several types of water (ultrapure water, surface water from a reservoir, and two secondary effluents) was also performed by the same combination UV/Cl₂ under more realistic operating conditions. The efficiency of this combined system UV/Cl₂ was compared to other oxidants such as the UV/S₂O₈^2- and UV/H₂O₂ AOPs. Results confirmed that the UV/Cl₂ system provides higher elimination efficiencies among the AOPs tested.

Keywords: emerging contaminants, UV/chlorine advanced oxidation process, amitriptyline, methyl salicylate, 2-phenoxyethanol, chlorination, photolysis

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Authors: Rene Davids

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Urban undergrounds spaces such as parking garages or metro stations are perceived as interludes before reaching desired destinations, as commodities devoid of aesthetic value. Within the encoded space of the city, commercial underground spaces are the closest expression to pure to structures of consumption and commodity. Even in the house, the cellar is associated with castoffs and waste or, as scholar Mircea Eliade has pointed out at best, with a place to store abandoned household and childhood objects, which lie forgotten and on rediscovery evoke a nostalgic and uncanny sense of the past. Despite a growing body of evidence presented by an increasing number of buildings situated entirely below or semi underground that feature exemplary spatial and sensuous qualities, critics and scholars see them largely as efforts to produce efforts in producing low consumption non-renewable energy. Buildings that also free space above ground. This critical approach neglects to mention and highlight other project drivers such as the notion that the ground and sky can be considered a building’s fundamental context, that underground spaces are conducive to the exploration of pure space, namely an architecture that doesn’t have to deal with facades and or external volumes and that digging into geology can inspire the textural and spatial richness. This paper will argue that while the assessment about the reduced energy consumption of underground construction is important, it does not do justice to the qualities underground buildings can contribute to a city’s expanded urban and or landscape experiences.

Keywords: low non-renewable energy consumption, pure space, underground buildings, urban and landscape experience

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Authors: Kulwinder Singh Mann, Manmohan Singh Heer, Asha Rani

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The safe storage of radioactive materials has become an important issue. Nuclear engineering necessitates the safe handling of radioactive materials emitting high energy gamma-rays. Hazards involved in handling radioactive materials insist suitable shielded enclosures. With overgrowing use of nuclear energy for meeting the increasing demand of power, there is a need to investigate the shielding behavior of cost effective shielded enclosure (CESE) made from clay-bricks (CB) and fire-bricks (FB). In comparison to the lead-bricks (conventional-shielding), the CESE are the preferred choice in nuclear waste management. The objective behind the present investigation is to evaluate the double layered transmission exposure buildup factors (DLEBF) for gamma-rays for CESE in energy range 0.5-3MeV. For necessary computations of shielding parameters, using existing huge data regarding gamma-rays interaction parameters of all periodic table elements, two computer programs (GRIC-toolkit and BUF-toolkit) have been designed. It has been found that two-layered slabs show effective shielding for gamma-rays in orientation CB followed by FB than the reverse. It has been concluded that the arrangement, FB followed by CB reduces the leakage of scattered gamma-rays from the radioactive source.

Keywords: buildup factor, clay bricks, fire bricks, nuclear wastage management, radiation protective double layered slabs

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Authors: Priyal Motwani

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The current market for bamboo products in India is about Rs. 21000 crores and is highly unorganised and fragmented. In this study, we have closely analysed the structure and functions of a major bamboo craft based organisation in Kerela, India and elaborated about its value chain, product mix, pricing strategy and supply chain, collaborations and competitive landscape. We have identified six major bottlenecks that are prevalent in such organisations, based on the Indian context, in relation to their product mix, asset management, and supply chain- corresponding waste management and retail network. The study has identified that the target customers for the bamboo based products and alternative revenue streams (eco-tourism, microenterprises, training), by carrying out secondary and primary research (5000 sample space), that can boost the existing revenue by 150%. We have then recommended an optimum product mix-covering premium, medium and low valued processing, for medium sized bamboo based organisations, in accordance with their capacity to maximize their revenue potential. After studying such organisations and their counter parts, the study has established an optimum retail network, considering B2B, B2C physical and online retail, to maximize their sales to their target groups. On the basis of the results obtained from the analysis of the future and present trends, our study gives recommendations to improve the revenue potential of bamboo based organisation in India and promote sustainability.

Keywords: bamboo, bottlenecks, optimization, product mix, retail network, value chain

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Authors: Joshna Rani S., Ahmadi Banu

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Artificial Intelligence (AI) has a significant task to carry out in the medical care contributions of things to come. As AI, it is the essential capacity behind the advancement of accuracy medication, generally consented to be a painfully required development in care. Albeit early endeavors at giving analysis and treatment proposals have demonstrated testing, we anticipate that AI will at last dominate that area too. Given the quick propels in AI for imaging examination, it appears to be likely that most radiology, what's more, pathology pictures will be inspected eventually by a machine. Discourse and text acknowledgment are now utilized for assignments like patient correspondence and catch of clinical notes, and their utilization will increment. The best test to AI in these medical services areas isn't regardless of whether the innovations will be sufficiently skilled to be valuable, but instead guaranteeing their appropriation in day by day clinical practice. For far reaching selection to happen, AI frameworks should be affirmed by controllers, coordinated with EHR frameworks, normalized to an adequate degree that comparative items work likewise, instructed to clinicians, paid for by open or private payer associations, and refreshed over the long haul in the field. These difficulties will, at last, be survived, yet they will take any longer to do as such than it will take for the actual innovations to develop. Therefore, we hope to see restricted utilization of AI in clinical practice inside 5 years and more broad use inside 10 years. It likewise appears to be progressively evident that AI frameworks won't supplant human clinicians for a huge scope, yet rather will increase their endeavors to really focus on patients. Over the long haul, human clinicians may advance toward errands and work plans that draw on remarkably human abilities like sympathy, influence, and higher perspective mix. Maybe the lone medical services suppliers who will chance their professions over the long run might be the individuals who will not work close by AI

Keywords: artificial intellogence, health care, breast cancer, AI applications

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Authors: Tzu-Jung Tseng, Pei-Hsuen Han, Tsung-Hsueh Lu

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Background: Ensuring patients with ST-elevation myocardial infarction (STEMI) access to hospitals that could perform percutaneous coronary intervention (PCI) in time is an important concern of healthcare managers. One commonly used the method to assess the coverage of population access to PCI hospital is the use GIS-estimated linear distance (crow's fly distance) between the district centroid and the nearest PCI hospital. If the distance is within a given distance (such as 20 km), the entire population of that district is considered to have appropriate access to PCI. The premise of using district centroid to estimate the coverage of population resident in that district is that the people live in the district are evenly distributed. In reality, the population density is not evenly distributed within the administrative district, especially in rural districts. Fortunately, the Taiwan government released basic statistical area (on average 450 population within the area) recently, which provide us an opportunity to estimate the coverage of population access to PCI services more accurate. Objectives: We aimed in this study to compare the population covered by a give PCI hospital according to traditional administrative district versus basic statistical area. We further examined if the differences between two geographic units used would be larger in a rural area than in urban area. Method: We selected two hospitals in Tainan City for this analysis. Hospital A is in urban area, hospital B is in rural area. The population in each traditional administrative district and basic statistical area are obtained from Taiwan National Geographic Information System, Ministry of Internal Affairs. Results: Estimated population live within 20 km of hospital A and B was 1,515,846 and 323,472 according to traditional administrative district and was 1,506,325 and 428,556 according to basic statistical area. Conclusion: In urban area, the estimated access population to PCI services was similar between two geographic units. However, in rural areas, the access population would be overestimated.

Keywords: accessibility, basic statistical area, modifiable areal unit problem (MAUP), percutaneous coronary intervention (PCI)

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Authors: Ru-Yu Lien, Shih-Hsin Hung, Shu-Fen Lu, Ju-Jen Shie, Wen-Ju Yang, Yuann-Meei Tzeng, Chien-Ying Wang

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Background: The quality of care in intensive care units (ICUs) is crucial, especially for terminally ill patients. Shared decision-making (SDM) with families is essential to ensure appropriate care and reduce suffering. Aim: This study explores the effectiveness of an end-of-life decision support Patient Decision Aid (PDA) in an ICU setting. Methods: This study employed a cross-sectional research design conducted in an ICU from August 2020 to June 2023. Participants included family members of end-of-life patients aged 20 or older. A total of 319 participants. Family members of end-of-life patients received the PDA, and data were collected after they made medical decisions. Data collection involved providing family members with a PDA during family meetings. A post-PDA questionnaire with 17 questions assessed PDA effectiveness and anxiety levels. Statistical analysis was performed using SPSS 22.0. Results: The PDA significantly reduced anxiety levels among family members (p < 0.001). It helped them organize their thoughts, prepare for discussions with doctors, and understand critical decision factors. Most importantly, it influenced decision outcomes, with a shift towards palliative care and withdrawal of life-sustaining treatment. Conclusion: This study highlights the importance of family-centered end-of-life care in ICUs. PDAs promote informed decision-making, reduce conflicts, and enhance patient and family involvement. These tools align patient values and goals with medical recommendations, ultimately leading to decisions that prioritize comfort and quality of life. Implementing PDAs in healthcare systems can ensure that patients' care aligns with their values.

Keywords: shared decision-making, patient decision aid, end-of-life care, intensive care unit, family-centered care

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Authors: Preethi Grace Theva Neethi Dhas

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A healthy human gut microbiome has commensal and symbiotic functions in digestion and is a decisive factor for human health. The soil microbiome is a crucial component in the ecosystem of soils and their health and resilience. Changes in soil microbiome are linked to human health. Ever since the industrial era, the human and the soil microbiome have been going through drastic changes. The soil microbiome has changed due to industrialization and extensive agricultural practices, whereas humans have less contact with soil and increased intake of highly processed foods, leading to changes in the human gut microbiome. Regenerating the soil becomes crucial in maintaining a healthy ecosystem. The nutrients, once obtained from the soil, need to be given back to the soil. Soil degradation needs to be addressed in effective ways, like adding organic nutrients back to the soil. Manure from animals and humans needs to be returned to the soil, which can complete the nutrient cycle in the soil. On the other hand, fecal sludge management (FSM) is a growing concern in many parts of the developing world. Hence, it becomes crucial to treat and reuse fecal sludge in a safe manner, i.e., low in risk to human health. Co-composting fecal sludge with organic wastes is a practice that allows the safe management of fecal sludge and the safe application of nutrients to the soil. This paper will discuss the possible impact of co-composting fecal sludge with coconut choir waste on the soil, water, and ecosystem at large. Impact parameters like nitrogen, phosphorus, and fecal coliforms will be analyzed. The overall impact of fecal sludge application on the soil will be researched and presented in this study.

Keywords: fecal sludge management, nutrient cycle, soil health, composting

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Authors: Oladipo Oluwaseun Peter

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Daily consumption of crude oil is alarming as a result of increasing demand for energy. Waste generation tends to rise with the level of economic advancement of a nation. Hence, this project work researches how wastes which could pose toxic if left unattended to can be processed through biodigestion in order to generate biofuel which could serve as a good substitute for petroleum, a non renewable energy source, so as to reduce over-dependence on petroleum and to prevent environmental pollution. Anaerobic digestion was carried out on organic wastes comprising brewery spent grains, rice husks and poultry droppings in a plastic biodigester of 1000 liters volume using the poultry droppings as a natural inoculums source. The feed composition in ratio 5:3:2, spent grain, rice husks and poultry droppings were mixed with water in the ratio 1:6. Thus, 600 Kg of water was used to prepare the slurry with 100 Kg of feed materials. A plastic biodigester was successfully constructed, and the problem of corrosion and rusting were completely overcome as a result of the use of non-corroding materials of construction. A reasonable quantity of biogas, 33.63m3, was generated over a period of 60 days of biodigestion. The bioslurry was processed through two different process routes; evaporation and filteration. Evaporation process of analysis shows high values of 0.64%, 2.11% and 0.034% for nitrogen, phosphorous and potassium respectively, while filteration process gives 00.61%, 1.93% and 0.026% for nitrogen, phosphorous and potassium respectively.

Keywords: biodigestion, biofuel, digestion, slurry, biogas

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Authors: Abimbola M. Enitan, J. Adeyemo

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Anaerobic modeling is a useful tool to describe and simulate the condition and behaviour of anaerobic treatment units for better effluent quality and biogas generation. The present investigation deals with the anaerobic treatment of brewery wastewater with varying organic loads. The chemical oxygen demand (COD) and total suspended solids (TSS) of the influent and effluent of the bioreactor were determined at various retention times to generate data for kinetic coefficients. The bio-kinetic coefficients in the modified Stover–Kincannon kinetic and methane generation models were determined to study the performance of anaerobic digestion process. At steady-state, the determination of the kinetic coefficient (K), the endogenous decay coefficient (Kd), the maximum growth rate of microorganisms (µmax), the growth yield coefficient (Y), ultimate methane yield (Bo), maximum utilization rate constant Umax and the saturation constant (KB) in the model were calculated to be 0.046 g/g COD, 0.083 (dˉ¹), 0.117 (d-¹), 0.357 g/g, 0.516 (L CH4/gCODadded), 18.51 (g/L/day) and 13.64 (g/L/day) respectively. The outcome of this study will help in simulation of anaerobic model to predict usable methane and good effluent quality during the treatment of industrial wastewater. Thus, this will protect the environment, conserve natural resources, saves time and reduce cost incur by the industries for the discharge of untreated or partially treated wastewater. It will also contribute to a sustainable long-term clean development mechanism for the optimization of the methane produced from anaerobic degradation of waste in a close system.

Keywords: brewery wastewater, methane generation model, environment, anaerobic modeling

Procedia PDF Downloads 270

Authors: Susan Diamond

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Machine Learning workloads have traditionally been run in high-performance computing (HPC) environments, where users log in to dedicated machines and utilize the attached GPUs to run training jobs on huge datasets. Training of large neural network models is very resource intensive, and even after exploiting parallelism and accelerators such as GPUs, a single training job can still take days. Consequently, the cost of hardware is a barrier to entry. Even when upfront cost is not a concern, the lead time to set up such an HPC environment takes months from acquiring hardware to set up the hardware with the right set of firmware, software installed and configured. Furthermore, scalability is hard to achieve in a rigid traditional lab environment. Therefore, it is slow to react to the dynamic change in the artificial intelligent industry. Watson Deep Learning as a service, a cloud-based deep learning platform that mitigates the long lead time and high upfront investment in hardware. It enables robust and scalable sharing of resources among the teams in an organization. It is designed for on-demand cloud environments. Providing a similar user experience in a multi-tenant cloud environment comes with its own unique challenges regarding fault tolerance, performance, and security. Watson Deep Learning as a service tackles these challenges and present a deep learning stack for the cloud environments in a secure, scalable and fault-tolerant manner. It supports a wide range of deep-learning frameworks such as Tensorflow, PyTorch, Caffe, Torch, Theano, and MXNet etc. These frameworks reduce the effort and skillset required to design, train, and use deep learning models. Deep Learning as a service is used at IBM by AI researchers in areas including machine translation, computer vision, and healthcare. 

Keywords: deep learning, machine learning, cognitive computing, model training

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Authors: W. Ketren, J. Wannapeera, Z. Heishun, A. Ryuichi, K. Toshiteru, M. Kouichi, O. Hideaki

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Degradative solvent extraction is the method developed for biomass upgrading by dewatering and fractionation of biomass under the mild condition. However, the conversion mechanism of the degradative solvent extraction method has not been fully understood so far. The rice straw was treated in 1-methylnaphthalene (1-MN) at a different solvent-treatment temperature varied from 250 to 350 ^oC with the residence time for 60 min. The liquid membrane-Fourier Transform Infrared Spectroscopy (FTIR) technique is applied to study the processing mechanism in-depth without separation of the solvent. It has been found that the strength of the oxygen-hydrogen stretching  (3600-3100 cm^-1) decreased slightly with increasing temperature in the range of 300-350 ^oC. The decrease of the hydroxyl group in the solvent soluble suggested dehydration reaction taking place between 300 and 350 ^oC. FTIR spectra in the carbonyl stretching region (1800-1600 cm^-1) revealed the presence of esters groups, carboxylic acid and ketonic groups in the solvent-soluble of biomass. The carboxylic acid increased in the range of 200 to 250 ^oC and then decreased. The prevailing of aromatic groups showed that the aromatization took place during extraction at above 250 ^oC. From 300 to 350 ^oC, the carbonyl functional groups in the solvent-soluble noticeably decreased. The removal of the carboxylic acid and the decrease of esters into the form of carbon dioxide indicated that the decarboxylation reaction occurred during the extraction process.

Keywords: biomass waste, degradative solvent extraction, mechanism, upgrading

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Authors: Chioma J. Nwakamma, Blessing O. Oyedemi, Garuba Omosun

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This research surveys and documents information on medicinal plants and their botanical preparations used in the treatment of children’s ailments in South-Eastern Nigeria. Children under the age of 5 in developing countries suffer from diseases with high morbidity and mortality rate yearly due to inaccessible and unaffordable healthcare. Structured questionnaires were administered to herbal sellers, traditional medicine practitioners, nursing mothers, and adult dwellers to collect data on the names of plants used to treat the conditions, methods of preparation, duration of treatment, adverse effects, and the methods of administration of the plant materials. A total of 135 plants belonging to 55 families were identified for the management of children’s health in the area. Common pediatric ailments which were said to be treated with herbal remedies by the respondents included malaria, pneumonia, stomach ache, diarrhea, dysentery, measles, chickenpox/smallpox, convulsion, jaundice, pile, ringworm, scabies, eczema, stubborn cough, scurvy, catarrh, wounds, boils, insect bites, food poison, cholera, and umbilical cord complications. Percentages of respondents were; herbal sellers (48.2%), traditional medical practitioners (21.6%), nursing mothers (11.1%), and others (19.1%). The most occurring plant families were Euphorbiaceae, Fabaceae, and Apocynaceae, with 8 species of plants each followed by Annonaceae and Asteriaceae with 7 and 6 species, respectively. The recipes were made from the combination of different parts of two or more plant species, and others were made from single plant parts. Methods of extraction were mostly decoction and raw-squeezing out of the juice and infusion, while oral administration was the main route of administration.

Keywords: ethno-botanicals, children’s health, medicinal plants, South-Eastern Nigeria

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Authors: Nioushasadat Haji Seyed Javadi, Ailar Hajimohammadi, Nasser Khalili

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Currently, the recycling of plastic wastes has been the subject of much research attention, especially in pavement constructions, where virgin polymers can be replaced by recycled plastics for asphalt binder modification. Among the plastic types, recycled linear low-density polyethylene (RLLDPE) has been one of the common and largely available plastics for bitumen modification. However, it is important to note that during the recycling process, LLDPE can easily be contaminated with other plastic types, especially with low-density polyethylene (LDPE), high-density polyethylene (HDPE), and polypropylene (PP). The cross-contamination of LLDPE with other plastics lowers its quality and, consequently, can affect the asphalt modification process. This study aims to assess the effect of LLDPE cross-contamination on bitumen modification. To do so, samples of bitumen modified with LLDPE and blends of LLDPE with LDPE, HDPE, and PP were prepared and compared through physical and rheological evaluations. The experimental tests, including softening point, penetration, viscosity at 135 °C, and dynamic shear rheometer, were conducted. The results indicated that the effect of cross-contamination on softening point and rutting resistance was negligible. On the other side, penetration and viscosity were highly impacted. The results also showed that among contamination of LLDPE with the other plastic types, PP had the highest influence in comparison with HDPE and LDPE on changing the properties of the LLDPE- modified bitumen.

Keywords: recycled polyethylene, polymer cross-contamination, waste plastic, bitumen, rutting resistance

Procedia PDF Downloads 127

Authors: Sri Rejeki, Tamrin Tamrin, RH. F. Faradilla, Muhammad N. Ibrahim, Mariana M., Irnawati Irnawati

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Cocoa bean shells, despite their antioxidant and antimicrobial properties, are still considered as an underutilized agricultural waste. The functional properties and their lignocelluloses content make cocoa bean shells a potential material for paper-based food packaging. In our previous research, we have successfully produced papers from cocoa bean shells that had antioxidant and antibacterial activities. However, the hydrophilic nature of the lignocelluloses of cocoa bean shells hinders the application of the paper to be used as a food packaging. In this research, we aimed to study the effects of beeswax coating on the wettability and mechanical properties of the paper. The coating was done by dipping the papers in beeswax solution several times and in three different beeswax concentrations. The number of dipping and beeswax concentration significantly (p<0.05) affected the water contact angle of the papers. Results show that the water contact angle increases dramatically due to the coating treatment. The control paper or uncoated paper had a contact angle of 40.50o, while the contact angle of the best-coated paper (D3B3: 3x dipping, 3g/10mL beeswax) reached 96.93o. Both tensile strength and percent elongation were not significantly (p>0.05) affected by the coating treatment. This showed that beeswax was a potential organic material to improve the hydrophobicity of paper from cocoa bean shells without any undesirable effects on the mechanical properties of the paper.

Keywords: cocoa bean shell, paper, beeswax, coating, contact angle

Procedia PDF Downloads 148

Authors: Oluwagbenga B. Fatile, Felix U. Idu, Olajide T. Sanya

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This paper reports the viability of developing Zn-27Al alloy matrix hybrid composites reinforced with alumina, graphite and fly ash (a solid waste byproduct of coal in thermal power plants). This research work was aimed at developing low cost-high performance Zn-27Al matrix composite with low density. Alumina particulates (Al2O3), graphite added with 0, 2, 3, 4, and 5 wt% fly ash were utilized to prepare 10wt% reinforcing phase with Zn-27Al alloy as matrix using two-step stir casting method. Density measurement estimated percentage porosity, tensile testing, micro hardness measurement, and optical microscopy were used to assess the performance of the composites produced. The results show that the hardness, ultimate tensile strength, and percent elongation of the hybrid composites decrease with increase in fly ash content. The maximum decrease in hardness and ultimate tensile strength of 13.72% and 15.25% respectively were observed for composite grade containing 5wt% fly ash. The percentage elongation of composite sample without fly ash is 8.9% which is comparable with that of the sample containing 2wt% fly ash with percentage elongation of 8.8%. The fracture toughness of the fly ash containing composites was, however, superior to those of composites without fly ash with 5wt% fly ash containing composite exhibiting the highest fracture toughness. The results show that fly ash can be utilized as complementary reinforcement in ZA-27 alloy matrix composite to reduce cost.

Keywords: fly ash, hybrid composite, mechanical behaviour, stir-cast

Procedia PDF Downloads 335