Search results for: fuel injection discharge curve

Authors: M. Sarraf, J. E. Moros, M. C. Sánchez

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Oleogels are self-standing systems that are able to trap edible liquid oil into a tridimensional network and also help to use less fat by forming crystallization oleogelators. There are different ways to generate oleogelation and oil structuring, including direct dispersion, structured biphasic systems, oil sorption, and indirect method (emulsion-template). The selection of processing conditions as well as the composition of the oleogels is essential to obtain a stable oleogel with characteristics suitable for its purpose. In this sense, one of the ingredients widely used in food products to produce oleogels and emulsions is polysaccharides. Basil seed gum (BSG), with the scientific name Ocimum basilicum, is a new native polysaccharide with high viscosity and pseudoplastic behavior because of its high molecular weight in the food industry. Also, proteins can stabilize oil in water due to the presence of amino and carboxyl moieties that result in surface activity. Whey proteins are widely used in the food industry due to available, cheap ingredients, nutritional and functional characteristics such as emulsifier and a gelling agent, thickening, and water-binding capacity. In general, the interaction of protein and polysaccharides has a significant effect on the food structures and their stability, like the texture of dairy products, by controlling the interactions in macromolecular systems. Using edible oleogels as oil structuring helps for targeted delivery of a component trapped in a structural network. Therefore, the development of efficient oleogel is essential in the food industry. A complete understanding of the important points, such as the ratio oil phase, processing conditions, and concentrations of biopolymers that affect the formation and stability of the emulsion, can result in crucial information in the production of a suitable oleogel. In this research, the effects of oil concentration and pressure used in the manufacture of the emulsion prior to obtaining the oleogel have been evaluated through the analysis of droplet size and rheological properties of obtained emulsions and oleogels. The results show that the emulsion prepared in the high-pressure homogenizer (HPH) at higher pressure values has smaller droplet sizes and a higher uniformity in the size distribution curve. On the other hand, in relation to the rheological characteristics of the emulsions and oleogels obtained, the predominantly elastic character of the systems must be noted, as they present values of the storage modulus higher than those of losses, also showing an important plateau zone, typical of structured systems. In the same way, if steady-state viscous flow tests have been analyzed on both emulsions and oleogels, the result is that, once again, the pressure used in the homogenizer is an important factor for obtaining emulsions with adequate droplet size and the subsequent oleogel. Thus, various routes for trapping oil inside a biopolymer matrix with adjustable mechanical properties could be applied for the creation of the three-dimensional network in order to the oil absorption and creating oleogel.

Keywords: basil seed gum, particle size, viscoelastic properties, whey protein

Procedia PDF Downloads 44

Authors: Vilas Warudkar, Dinkar Janghel, Siraj Ahmed

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Rapid development experienced by India requires huge amount of energy. Actual supply capacity additions have been consistently lower than the targets set by the government. According to World Bank 40% of residences are without electricity. In 12th five year plan 30 GW grid interactive renewable capacity is planned in which 17 GW is Wind, 10 GW is from solar and 2.1 GW from small hydro project, and rest is compensated by bio gas. Renewable energy (RE) and energy efficiency (EE) meet not only the environmental and energy security objectives, but also can play a crucial role in reducing chronic power shortages. In remote areas or areas with a weak grid, wind energy can be used for charging batteries or can be combined with a diesel engine to save fuel whenever wind is available. India according to IEC 61400-1 belongs to class IV Wind Condition; it is not possible to set up wind turbine in large scale at every place. So, the best choice is to go for small scale wind turbine at lower height which will have good annual energy production (AEP). Based on the wind characteristic available at MANIT Bhopal, rotor for small scale wind turbine is designed. Various Aero foil data is reviewed for selection of airfoil in the Blade Profile. Airfoil suited of Low wind conditions i.e. at low Reynold’s number is selected based on Coefficient of Lift, Drag and angle of attack. For designing of the rotor blade, standard Blade Element Momentum (BEM) Theory is implanted. Performance of the Blade is estimated using BEM theory in which axial induction factor and angular induction factor is optimized using iterative technique. Rotor performance is estimated for particular designed blade specifically for low wind Conditions. Power production of rotor is determined at different wind speeds for particular pitch angle of the blade. At pitch 15o and velocity 5 m/sec gives good cut in speed of 2 m/sec and power produced is around 350 Watts. Tip speed of the Blade is considered as 6.5 for which Coefficient of Performance of the rotor is calculated 0.35, which is good acceptable value for Small scale Wind turbine. Simple Load Model (SLM, IEC 61400-2) is also discussed to improve the structural strength of the rotor. In SLM, Edge wise Moment and Flap Wise moment is considered which cause bending stress at the root of the blade. Various Load case mentioned in the IEC 61400-2 is calculated and checked for the partial safety factor of the wind turbine blade.

Keywords: annual energy production, Blade Element Momentum Theory, low wind Conditions, selection of airfoil

Procedia PDF Downloads 316

Authors: Andrew N. Saylor, James R. Peters

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Scoliosis is a complex 3D deformity of the thoracic and lumbar spines, clinically diagnosed by measurement of a Cobb angle of 10 degrees or more on a coronal X-ray. The Cobb angle is the angle made by the lines drawn along the proximal and distal endplates of the respective proximal and distal vertebrae comprising the curve. Traditionally, Cobb angles are measured manually using either a marker, straight edge, and protractor or image measurement software. The task of measuring the Cobb angle can also be represented by a function taking the spine geometry rendered using X-ray imaging as input and returning the approximate angle. Although the form of such a function may be unknown, it can be approximated using artificial neural networks (ANNs). The performance of ANNs is affected by many factors, including the choice of activation function and network architecture; however, the effects of these parameters on the accuracy of scoliotic deformity measurements are poorly understood. Therefore, the objective of this study was to systematically investigate the effect of ANN architecture and activation function on Cobb angle measurement from the coronal X-rays of scoliotic subjects. The data set for this study consisted of 609 coronal chest X-rays of scoliotic subjects divided into 481 training images and 128 test images. These data, which included labeled Cobb angle measurements, were obtained from the SpineWeb online database. In order to normalize the input data, each image was resized using bi-linear interpolation to a size of 500 × 187 pixels, and the pixel intensities were scaled to be between 0 and 1. A fully connected (dense) ANN with a fixed cost function (mean squared error), batch size (10), and learning rate (0.01) was developed using Python Version 3.7.3 and TensorFlow 1.13.1. The activation functions (sigmoid, hyperbolic tangent [tanh], or rectified linear units [ReLU]), number of hidden layers (1, 3, 5, or 10), and number of neurons per layer (10, 100, or 1000) were varied systematically to generate a total of 36 network conditions. Stochastic gradient descent with early stopping was used to train each network. Three trials were run per condition, and the final mean squared errors and mean absolute errors were averaged to quantify the network response for each condition. The network that performed the best used ReLU neurons had three hidden layers, and 100 neurons per layer. The average mean squared error of this network was 222.28 ± 30 degrees2, and the average mean absolute error was 11.96 ± 0.64 degrees. It is also notable that while most of the networks performed similarly, the networks using ReLU neurons, 10 hidden layers, and 1000 neurons per layer, and those using Tanh neurons, one hidden layer, and 10 neurons per layer performed markedly worse with average mean squared errors greater than 400 degrees2 and average mean absolute errors greater than 16 degrees. From the results of this study, it can be seen that the choice of ANN architecture and activation function has a clear impact on Cobb angle inference from coronal X-rays of scoliotic subjects.

Keywords: scoliosis, artificial neural networks, cobb angle, medical imaging

Procedia PDF Downloads 101

Authors: Habib Alshuwaikhat, Nahid Hossain

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Residential sector consumes more than half of the produced electricity in Saudi Arabia, and fossil fuel is the main source of energy to meet growing household electricity demand in the Kingdom. Several studies forecasted and expressed concern that unless the domestic energy demand growth is controlled, it will reduce Saudi Arabia’s crude oil export capacity within a decade and the Kingdom is likely to be incapable of exporting crude oil within next three decades. Though the Saudi government has initiated to address the domestic energy demand growth issue, the demand side energy management policies and programs are focused on industrial and commercial sectors. It is apparent that there is an urgent need to develop a comprehensive energy efficiency strategy for addressing efficient energy use in residential sector in the Kingdom. Then again as Saudi Arabia is at its primary stage in addressing energy efficiency issues in its residential sector, there is a scope for the Kingdom to learn from global energy efficiency practices and design its own energy efficiency policies and programs. However, in order to do that sustainable, it is essential to address local contexts of energy efficiency. It is also necessary to find out the policies and programs that will fit to the local contexts. Thus the objective of this study was set to identify globally best practice energy efficiency policies and programs in residential sector that have replication potential in Saudi Arabia. In this regard two sets of multi-criteria decision analysis matrices were developed to evaluate the energy efficiency policies and programs. The first matrix was used to evaluate the global energy efficiency policies and programs, and the second matrix was used to evaluate the replication potential of global best practice energy efficiency policies and programs for Saudi Arabia. Wuppertal Institute’s guidelines for energy efficiency policy evaluation were used to develop the matrices, and the different attributes of the matrices were set through available literature review. The study reveals that the best practice energy efficiency policies and programs with good replication potential for Saudi Arabia are those which have multiple components to address energy efficiency and are diversified in their characteristics. The study also indicates the more diversified components are included in a policy and program, the more replication potential it has for the Kingdom. This finding is consistent with other studies, where it is observed that in order to be successful in energy efficiency practices, it is required to introduce multiple policy components in a cluster rather than concentrate on a single policy measure. The developed multi-criteria decision analysis matrices for energy efficiency policy and program evaluation could be utilized to assess the replication potential of other globally best practice energy efficiency policies and programs for the residential sector of the Kingdom. In addition it has potential to guide Saudi policy makers to adopt and formulate its own energy efficiency policies and programs for Saudi Arabia.

Keywords: Saudi Arabia, residential sector, energy efficiency, policy evaluation

Procedia PDF Downloads 473

Authors: Rachael Andrews, Viktoria McMillan, Shuaib Nasser, Christopher M. Roberts

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Background and objective: The National Review of Asthma Deaths (NRAD) found that asthma management and care was inadequate in 26% of cases reviewed. Major shortfalls identified were adherence to national guidelines and standards and, particularly, the organisation of care, including supervision and monitoring in primary care, with 70% of cases reviewed having at least one avoidable factor in this area. 5.4 million people in the UK are diagnosed with and actively treated for asthma, and approximately 60,000 are admitted to hospital with acute exacerbations each year. The majority of people with asthma receive management and treatment solely in primary care. This has therefore created concern that many people within the UK are receiving sub-optimal asthma care resulting in unnecessary morbidity and risk of adverse outcome. NRAD concluded that a national asthma audit programme should be established to measure and improve processes, organisation, and outcomes of asthma care. Objective: To develop a primary care dataset enabling extraction of information from GP practices in Wales and providing robust data by which results and lessons could be drawn and drive service development and improvement. Methods: A multidisciplinary group of experts, including general practitioners, primary care organisation representatives, and asthma patients was formed and used as a source of governance and guidance. A review of asthma literature, guidance, and standards took place and was used to identify areas of asthma care which, if improved, would lead to better patient outcomes. Modified Delphi methodology was used to gain consensus from the expert group on which of the areas identified were to be prioritised, and an asthma patient and carer focus group held to seek views and feedback on areas of asthma care that were important to them. Areas of asthma care identified by both groups were mapped to asthma guidelines and standards to inform and develop primary and secondary care datasets covering both adult and pediatric care. Dataset development consisted of expert review and a targeted consultation process in order to seek broad stakeholder views and feedback. Results: Areas of asthma care identified as requiring prioritisation by the National Asthma Audit were: (i) Prescribing, (ii) Asthma diagnosis (iii) Asthma Reviews (iv) Personalised Asthma Action Plans (PAAPs) (v) Primary care follow-up after discharge from hospital (vi) Methodologies and primary care queries were developed to cover each of the areas of poor and variable asthma care identified and the queries designed to extract information directly from electronic patients’ records. Conclusion: This paper describes the methodological approach followed to develop primary care datasets for a National Asthma Audit. It sets out the principles behind the establishment of a National Asthma Audit programme in response to a national asthma mortality review and describes the development activities undertaken. Key process elements included: (i) mapping identified areas of poor and variable asthma care to national guidelines and standards, (ii) early engagement of experts, including clinicians and patients in the process, and (iii) targeted consultation of the queries to provide further insight into measures that were collectable, reproducible and relevant.

Keywords: asthma, primary care, general practice, dataset development

Procedia PDF Downloads 145

Authors: Vidya Pratap, Seena Biju, Keshavdev A.

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In the educational town of Manipal (located in southern India) households dispose their wastes without segregation. Mixed wastes (organic, inorganic and hazardous items) are collected either by private collectors or by the local municipal body in trucks and taken to dump yards. These collectors select certain recyclables from the collected trash and sell them to scrap merchants to earn some extra money. Rag pickers play a major role in picking up card board boxes, glass bottles and milk sachets from dump yards and public areas and scrap iron from construction sites for recycling. In keeping with the Indian Prime Minister’s mission of Swachh Bharat (A Clean India), the local municipal administration is taking efforts to ensure segregation of domestic waste at source. With this in mind, each household in a residential area in Manipal was given two buckets – for wet and dry wastes (wet waste referred to organic waste while dry waste included recyclable and hazardous items). A study was conducted in this locality covering a cluster of 145 households to assess the residents’ knowledge of recyclable, organic and hazardous items commonly disposed by households. Another objective of this research was to evaluate the extent to which the residents actually dispose their wastes appropriately. Questionnaires were self-administered to a member of each household with the assistance of individuals speaking the local language whenever needed. Respondents’ knowledge of whether an item was organic, inorganic or hazardous was captured through a questionnaire containing a list of 50 common items. Their behaviour was captured by asking how they disposed these items. Results show that more than 70% of respondents are aware that banana and orange peels, potato skin, egg shells and dried leaves are organic; similarly, more than 70% of them consider newspapers, notebook and printed paper are recyclable. Less than 65% of respondents are aware that plastic bags and covers and plastic bottles are recyclable. However, the results of the respondents’ recycling behaviour is less impressive. Fewer than 35% of respondents recycle card board boxes, milk sachets and glass bottles. Unfortunately, since plastic items like plastic bags and covers and plastic bottles are not accepted by scrap merchants, they are not recycled. This study shows that the local municipal authorities must find ways to recycle plastic into products, alternate fuel etc.

Keywords: behaviour, knowledge, plastic waste management, recyclables

Procedia PDF Downloads 151

Authors: Nothando Gwazani, K. R. Marembo

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An increase in the atmospheric concentration of carbon dioxide (CO₂) from fossil fuel and land use change necessitates identification of strategies for mitigating threats associated with global warming. Oceans are insufficient to offset the accelerating rate of carbon emission. However, the challenges of oceans as a source of reducing carbon footprint can be effectively overcome by the storage of carbon in terrestrial carbon sinks. The gases with special optical properties that are responsible for climate warming include carbon dioxide (CO₂), water vapors, methane (CH₄), nitrous oxide (N₂O), nitrogen oxides (NOₓ), stratospheric ozone (O₃), carbon monoxide (CO) and chlorofluorocarbons (CFC’s). Amongst these, CO₂ plays a crucial role as it contributes to 50% of the total greenhouse effect and has been linked to climate change. Because plants act as carbon sinks, interest in terrestrial carbon sequestration has increased in an effort to explore opportunities for climate change mitigation. Removal of carbon from the atmosphere is a topical issue that addresses one important aspect of an overall strategy for carbon management namely to help mitigate the increasing emissions of CO₂. Thus, terrestrial ecosystems have gained importance for their potential to sequester carbon and reduce carbon sink in oceans, which have a substantial impact on the ocean species. Field data and electromagnetic spectrum bands were analyzed using ArcGIS 10.2, QGIS 2.8 and ERDAS IMAGINE 2015 to examine the vegetation distribution. Satellite remote sensing data coupled with Normalized Difference Vegetation Index (NDVI) was employed to assess future potential changes in vegetation distributions in Eastern Cape Province of South Africa. The observed 5-year interval analysis examines the amount of carbon absorbed using vegetation distribution. In 2015, the numerical results showed low vegetation distribution, therefore increased the acidity of the oceans and gravely affected fish species and corals. The outcomes suggest that the study area could be effectively utilized for carbon sequestration so as to mitigate ocean acidification. The vegetation changes measured through this investigation suggest an environmental shift and reduced vegetation carbon sink, and that threatens biodiversity and ecosystem. In order to sustain the amount of carbon in the terrestrial ecosystems, the identified ecological factors should be enhanced through the application of good land and forest management practices. This will increase the carbon stock of terrestrial ecosystems thereby reducing direct loss to the atmosphere.

Keywords: remote sensing, vegetation dynamics, carbon sequestration, terrestrial carbon sink

Procedia PDF Downloads 126

Authors: Anastasia Constantinou, Panayiotis Laouris, Stephen Morris

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Background: Climate change has been reported as one of the worst threats to healthcare. The healthcare sector is a significant contributor to greenhouse gas emissions with primary care being responsible for 23% of the NHS’ total carbon footprint. Digital interventions, primarily focusing on telemedicine, offer a route to change. This systematic review aims to quantify and characterize the carbon footprint savings associated with the implementation of digital interventions in the setting of primary care. Methods: A systematic review of published literature was conducted according to PRISMA (Preferred Reporting Item for Systematic Reviews and Meta-Analyses) guidelines. MEDLINE, PubMed, and Scopus databases as well as Google scholar were searched using key terms relating to “carbon footprint,” “environmental impact,” “sustainability”, “green care”, “primary care,”, and “general practice,” using citation tracking to identify additional articles. Data was extracted and analyzed in Microsoft Excel. Results: Eight studies were identified conducted in four different countries between 2010 and 2023. Four studies used interventions to address primary care services, three studies focused on the interface between primary and specialist care, and one study addressed both. Digital interventions included the use of mobile applications, online portals, access to electronic medical records, electronic referrals, electronic prescribing, video-consultations and use of autonomous artificial intelligence. Only one study carried out a complete life cycle assessment to determine the carbon footprint of the intervention. It estimate that digital interventions reduced the carbon footprint at primary care level by 5.1 kgCO2/visit, and at the interface with specialist care by 13.4 kg CO₂/visit. When assessing the relationship between travel-distance saved and savings in emissions, we identified a strong correlation, suggesting that most of the carbon footprint reduction is attributed to reduced travel. However, two studies also commented on environmental savings associated with reduced use of paper. Patient savings in the form of reduced fuel cost and reduced travel time were also identified. Conclusion: All studies identified significant reductions in carbon footprint following implementation of digital interventions. In the future, controlled, prospective studies incorporating complete life cycle assessments and accounting for double-consulting effects, use of additional resources, technical failures, quality of care and cost-effectiveness are needed to fully appreciate the sustainable benefit of these interventions

Keywords: carbon footprint, environmental impact, primary care, sustainable healthcare

Procedia PDF Downloads 37

Authors: komal verma, V. S. Moholkar

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In this current study, the challenge of effectively treating and mineralizing industrial wastewater prior to its discharge into natural water bodies, such as rivers and lakes, is being addressed. Particularly, the focus is on the wastewater produced by chemical process industries, including refineries, petrochemicals, fertilizer, pharmaceuticals, pesticides, and dyestuff industries. These wastewaters often contain stubborn organic pollutants that conventional techniques, such as microbial processes cannot efficiently degrade. To tackle this issue, a ternary hybrid technique comprising of adsorption, heterogeneous Fenton process, and sonication has been employed. The study aims to evaluate the effectiveness of this approach for treating and mineralizing wastewater from a fertilizer industry located in Northeast India. The study comprises several key components, starting with the synthesis of the Fe3O4@AC nanocomposite using the co-precipitation method. The nanocomposite is then subjected to comprehensive characterization through various standard techniques, including FTIR, FE-SEM, EDX, TEM, BET surface area analysis, XRD, and magnetic property determination using VSM. Next, the process parameters of wastewater treatment are statistically optimized, focusing on achieving a high level of COD (Chemical Oxygen Demand) removal as the response variable. The Fe3O4@AC nanocomposite's adsorption characteristics and kinetics are also assessed in detail. The remarkable outcome of this study is the successful application of the ternary hybrid technique, combining adsorption, Fenton process, and sonication. This approach proves highly effective, leading to nearly complete mineralization (or TOC removal) of the fertilizer industry wastewater. The results highlight the potential of the Fe3O4@AC nanocomposite and the ternary hybrid technique as a promising solution for tackling challenging wastewater pollutants from various chemical process industries. This paper reports investigations in the mineralization of industrial wastewater (COD = 3246 mg/L, TOC = 2500 mg/L) using a ternary (ultrasound + Fenton + adsorption) hybrid advanced oxidation process. Fe3O4 decorated activated charcoal (Fe3O4@AC) nanocomposites (surface area = 538.88 m2/g; adsorption capacity = 294.31 mg/g) were synthesized using co-precipitation. The wastewater treatment process was optimized using central composite statistical design. At optimum conditions, viz. pH = 4.2, H2O2 loading = 0.71 M, adsorbent dose = 0.34 g/L, reduction in COD and TOC of wastewater were 94.75% and 89%, respectively. This result results from synergistic interactions among the adsorption of pollutants onto activated charcoal and surface Fenton reactions induced due to the leaching of Fe2+/Fe3+ ions from the Fe3O4 nanoparticles. Micro-convection generated due to sonication assisted faster mass transport (adsorption/desorption) of pollutants between Fe3O4@AC nanocomposite and the solution. The net result of this synergism was high interactions and reactions among and radicals and pollutants that resulted in the effective mineralization of wastewater. The Fe3O4@AC showed excellent recovery (> 90 wt%) and reusability (> 90% COD removal) in 5 successive cycles of treatment. LC-MS analysis revealed effective (> 50%) degradation of more than 25 significant contaminants (in the form of herbicides and pesticides) after the treatment with ternary hybrid AOP. Similarly, the toxicity analysis test using the seed germination technique revealed ~ 60% reduction in the toxicity of the wastewater after treatment.

Keywords: chemical oxygen demand (cod), fe3o4@ac nanocomposite, kinetics, lc-ms, rsm, toxicity

Procedia PDF Downloads 41

Authors: Debalina Ghoshal

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Nuclear security is the ‘prevention and detection of, and response to unauthorised removal, sabotage, unauthorised access, illegal transfer or other malicious acts involving nuclear or radiological material or their associated facilities.’ Ever since the end of Cold War, nuclear materials security has remained a concern for global security. However, with the increase in terrorist attacks not just in India especially, security of nuclear materials remains a priority. Therefore, India has made continued efforts to tighten its security on nuclear materials to prevent nuclear theft and radiological terrorism. Nuclear security is different from nuclear safety. Physical security is also a serious concern and India had been careful of the physical security of its nuclear materials. This is more so important since India is expanding its nuclear power capability to generate electricity for economic development. As India targets 60,000 MW of electricity production by 2030, it has a range of reactors to help it achieve its goal. These include indigenous Pressurised Heavy Water Reactors, now standardized at 700 MW per reactor Light Water Reactors, and the indigenous Fast Breeder Reactors that can generate more fuel for the future and enable the country to utilise its abundant thorium resource. Nuclear materials security can be enhanced through two important ways. One is through proliferation resistant technologies and diplomatic efforts to take non proliferation initiatives. The other is by developing technical means to prevent any leakage in nuclear materials in the hands of asymmetric organisations. New Delhi has already implemented IAEA Safeguards on their civilian nuclear installations. Moreover, the IAEA Additional Protocol has also been ratified by India in order to enhance its transparency of nuclear material and strengthen nuclear security. India is a party to the IAEA Conventions on Nuclear Safety and Security, and in particular the 1980 Convention on the Physical Protection of Nuclear Material and its amendment in 2005, Code of Conduct in Safety and Security of Radioactive Sources, 2006 which enables the country to provide for the highest international standards on nuclear and radiological safety and security. India's nuclear security approach is driven by five key components: Governance, Nuclear Security Practice and Culture, Institutions, Technology and International Cooperation. However, there is still scope for further improvements to strengthen nuclear materials and nuclear security. The NTI Report, ‘India’s improvement reflects its first contribution to the IAEA Nuclear Security Fund etc. in the future, India’s nuclear materials security conditions could be further improved by strengthening its laws and regulations for security and control of materials, particularly for control and accounting of materials, mitigating the insider threat, and for the physical security of materials during transport. India’s nuclear materials security conditions also remain adversely affected due to its continued increase in its quantities of nuclear material, and high levels of corruption among public officials.’ This paper would study briefly the progress made by India in nuclear and nuclear material security and the step ahead for India to further strengthen this.

Keywords: India, nuclear security, nuclear materials, non proliferation

Procedia PDF Downloads 325

Authors: Adewale O. Adegbenjo, Elsie Nsiah-Baafi, Mxolisi B. Shongwe, Mercy Ramakokovhu, Peter A. Olubambi

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The sintering step in powder metallurgy (P/M) processes is very sensitive as it determines to a large extent the properties of the final component produced. Spark plasma sintering over the past decade has been extensively used in consolidating a wide range of materials including metallic alloy powders. This novel, non-conventional sintering method has proven to be advantageous offering full densification of materials, high heating rates, low sintering temperatures, and short sintering cycles over conventional sintering methods. Ti6Al4V has been adjudged the most widely used α+β alloy due to its impressive mechanical performance in service environments, especially in the aerospace and automobile industries being a light metal alloy with the capacity for fuel efficiency needed in these industries. The P/M route has been a promising method for the fabrication of parts made from Ti6Al4V alloy due to its cost and material loss reductions and the ability to produce near net and intricate shapes. However, the use of this alloy has been largely limited owing to its relatively poor hardness and wear properties. The effect of sintering temperature on the densification, hardness, and wear behaviors of spark plasma sintered Ti6Al4V powders was investigated in this present study. Sintering of the alloy powders was performed in the 650–850°C temperature range at a constant heating rate, applied pressure and holding time of 100°C/min, 50 MPa and 5 min, respectively. Density measurements were carried out according to Archimedes’ principle and microhardness tests were performed on sectioned as-polished surfaces at a load of 100gf and dwell time of 15 s. Dry sliding wear tests were performed at varied sliding loads of 5, 15, 25 and 35 N using the ball-on-disc tribometer configuration with WC as the counterface material. Microstructural characterization of the sintered samples and wear tracks were carried out using SEM and EDX techniques. The density and hardness characteristics of sintered samples increased with increasing sintering temperature. Near full densification (99.6% of the theoretical density) and Vickers’ micro-indentation hardness of 360 HV were attained at 850°C. The coefficient of friction (COF) and wear depth improved significantly with increased sintering temperature under all the loading conditions examined, except at 25 N indicating better mechanical properties at high sintering temperatures. Worn surface analyses showed the wear mechanism was a synergy of adhesive and abrasive wears, although the former was prevalent.

Keywords: hardness, powder metallurgy, spark plasma sintering, wear

Procedia PDF Downloads 245

Authors: Eleonora Di Salvo, Antonio Panebianco, Graziella Ziino

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Background: Vibrio parahaemolyticus is a human pathogen that is widely distributed in marine environments. It is frequently isolated from raw seafood, particularly shellfish. Consumption of raw or undercooked seafood contaminated with V. parahaemolyticus may lead to acute gastroenteritis. Vibrio spp. has excellent resistance to low temperatures so it can be found in frozen products for a long time. Recently, the viable but non-culturable state (VBNC) of bacteria has attracted great attention, and more than 85 species of bacteria have been demonstrated to be capable of entering this state. VBNC cells cannot grow in conventional culture medium but are viable and maintain metabolic activity, which may constitute an unrecognized source of food contamination and infection. Also V. parahaemolyticus could exist in VBNC state under nutrient starvation or low-temperature conditions. Aim: The aim of the present study was to optimize methods and investigate V. parahaemolyticus VBNC cells and their presence in frozen bivalve molluscs, regularly marketed. Materials and Methods: propidium monoazide (PMA) was integrated with real-time polymerase chain reaction (qPCR) targeting the tl gene to detect and quantify V. parahaemolyticus in the VBNC state. PMA-qPCR resulted highly specific to V. parahaemolyticus with a limit of detection (LOD) of 10-1 log CFU/mL in pure bacterial culture. A standard curve for V. parahaemolyticus cell concentrations was established with the correlation coefficient of 0.9999 at the linear range of 1.0 to 8.0 log CFU/mL. A total of 77 samples of frozen bivalve molluscs (35 mussels; 42 clams) were subsequently subjected to the qualitative (on alkaline phosphate buffer solution) and quantitative research of V. parahaemolyticus on thiosulfate-citrate-bile salts-sucrose (TCBS) agar (DIFCO) NaCl 2.5%, and incubation at 30°C for 24-48 hours. Real-time PCR was conducted on homogenate samples, in duplicate, with and without propidium monoazide (PMA) dye, and exposed for 45 min under halogen lights (650 W). Total DNA was extracted from cell suspension in homogenate samples according to bolliture protocol. The Real-time PCR was conducted with species-specific primers for V. parahaemolitycus. The RT-PCR was performed in a final volume of 20 µL, containing 10 µL of SYBR Green Mixture (Applied Biosystems), 2 µL of template DNA, 2 µL of each primer (final concentration 0.6 mM), and H2O 4 µL. The qPCR was carried out on CFX96 TouchTM (Bio-Rad, USA). Results: All samples were negative both to the quantitative and qualitative detection of V. parahaemolyticus by the classical culturing technique. The PMA-qPCR let us individuating VBNC V. parahaemolyticus in the 20,78% of the samples evaluated with a value between the Log 10-1 and Log 10-3 CFU/g. Only clams samples were positive for PMA-qPCR detection. Conclusion: The present research is the first evaluating PMA-qPCR assay for detection of VBNC V. parahaemolyticus in bivalve molluscs samples, and the used method was applicable to the rapid control of marketed bivalve molluscs. We strongly recommend to use of PMA-qPCR in order to identify VBNC forms, undetectable by the classic microbiological methods. A precise knowledge of the V.parahaemolyticus in a VBNC form is fundamental for the correct risk assessment not only in bivalve molluscs but also in other seafood.

Keywords: food safety, frozen bivalve molluscs, PMA dye, Real-time PCR, VBNC state, Vibrio parahaemolyticus

Procedia PDF Downloads 108

Authors: Suliman Al-Fayoumi, Sherri Amberg, Huafeng Zhou, Jack W. Singer, James P. Dean

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Pacritinib is an oral kinase inhibitor with specificity for JAK2, FLT3, IRAK1, and CSF1R. In clinical studies, pacritinib was well tolerated with clinical activity in patients with myelofibrosis. The most frequent adverse events (AEs) observed with pacritinib are gastrointestinal (diarrhea, nausea, and vomiting; mostly grade 1-2 in severity) and typically resolve within 2 weeks. A human ADME mass balance study demonstrated that pacritinib is predominantly cleared via hepatic metabolism and biliary excretion (>85% of administered dose). The major hepatic metabolite identified, M1, is not thought to materially contribute to the pharmacological activity of pacritinib. Hepatic diseases are known to impair hepatic blood flow, drug-metabolizing enzymes, and biliary transport systems and may affect drug absorption, disposition, efficacy, and toxicity. This phase 1 study evaluated the pharmacokinetics (PK) and safety of pacritinib and the M1 metabolite in study subjects with mild, moderate, or severe hepatic impairment (HI) and matched healthy subjects with normal liver function to determine if pacritinib dosage adjustments are necessary for patients with varying degrees of hepatic insufficiency. Study participants (aged 18-85 y) were enrolled into 4 groups based on their degree of HI as defined by Child-Pugh Clinical Assessment Score: mild (n=8), moderate (n=8), severe (n=4), and healthy volunteers (n=8) matched for age, BMI, and sex. Individuals with concomitant renal dysfunction or progressive liver disease were excluded. A single 400 mg dose of pacritinib was administered to all participants. Blood samples were obtained for PK evaluation predose and at multiple time points postdose through 168 h. Key PK parameters evaluated included maximum plasma concentration (Cmax), time to Cmax (Tmax), area under the plasma concentration time curve (AUC) from hour zero to last measurable concentration (AUC0-t), AUC extrapolated to infinity (AUC0-∞), and apparent terminal elimination half-life (t1/2). Following treatment, pacritinib was quantifiable for all study participants at 1 h through 168 h postdose. Systemic pacritinib exposure was similar between healthy volunteers and individuals with mild HI. However, there was a significant difference between those with moderate and severe HI and healthy volunteers with respect to peak concentration (Cmax) and plasma exposure (AUC0-t, AUC0-∞). Mean Cmax decreased by 47% and 57% respectively in participants with moderate and severe HI vs matched healthy volunteers. Similarly, mean AUC0-t decreased by 36% and 45% and mean AUC0-∞ decreased by 46% and 48%, respectively in individuals with moderate and severe HI vs healthy volunteers. Mean t1/2 ranged from 51.5 to 74.9 h across all groups. The variability on exposure ranged from 17.8% to 51.8% across all groups. Systemic exposure of M1 was also significantly decreased in study participants with moderate or severe HI vs. healthy participants and individuals with mild HI. These changes were not significantly dissimilar from the inter-patient variability in these parameters observed in healthy volunteers. All AEs were grade 1-2 in severity. Diarrhea and headache were the only AEs reported in >1 participant (n=4 each). Based on these observations, it is unlikely that dosage adjustments would be warranted in patients with mild, moderate, or severe HI treated with pacritinib.

Keywords: pacritinib, myelofibrosis, hepatic impairment, pharmacokinetics

Procedia PDF Downloads 275

Authors: Paula Quiterio, Arlete Apolinario, Celia T. Sousa, Joao Azevedo, Paula Dias, Adelio Mendes, Joao P. Araujo

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Nowadays one of the mankind's greatest challenges has been the supply of low-cost and environmentally friendly energy sources as an alternative to non-renewable fossil fuels. Hydrogen has been considered a promising solution, representing a clean and low-cost fuel. It can be produced directly from clean and abundant resources, such as sunlight and water, using photoelectrochemical cells (PECs), in a process that mimics the nature´s photosynthesis. Hematite (alpha-Fe2O3) has attracted considerable attention as a promising photoanode for solar water splitting, due to its high chemical stability, nontoxicity, availability and low band gap (2.2 eV), which allows reaching a high thermodynamic solar-to-hydrogen efficiency of 16.8 %. However, the main drawbacks of hematite such as the short hole diffusion length and the poor conductivity that lead to high electron-hole recombination result in significant PEC efficiency losses. One strategy to overcome these limitations and to increase the PEC efficiency is to use 1D nanostructures, such as nanotubes (NTs) and nanowires (NWs), which present high aspect ratios and large surface areas providing direct pathways for electron transport up to the charge collector and minimizing the recombination losses. In particular, due to the ultrathin walls of the NTs, the holes can reach the surface faster than in other nanostructures, representing a key factor for the NTs photoresponse. In this work, we prepared hematite NWs and NTs, respectively by hydrothermal process and electrochemical anodization. For hematite NWs growing, we studied the effect of variable hydrothermal conditions, different annealing temperatures and time, and the use of Ti and Sn dopants on the morphology and PEC performance. The crystalline phase characterization by X-ray diffraction was crucial to distinguish the formation of hematite and other iron oxide phases, alongside its effect on the photoanodes conductivity and consequent PEC efficiency. The conductivity of the as-prepared NWs is very low, in the order of 10-5 S cm-1, but after doping and annealing optimization it increased by a factor of 105. A high photocurrent density of 1.02 mA cm-2 at 1.45 VRHE was obtained under simulated sunlight, which is a very promising value for this kind of hematite nanostructures. The stability of the photoelectrodes was also tested, presenting good stability after several J-V measurements over time. The NTs, synthesized by fast anodizations with potentials ranging from 20-100 V, presented a linear growth of the NTs pore walls, with very low thicknesses from 10 - 18 nm. These preliminary results are also very promising for the use of hematite photoelectrodes on PEC hydrogen applications.

Keywords: hematite, nanotubes, nanowires, photoelectrochemical cells

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Authors: Pedro Llanos, Diego García

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This paper is addressed to expanding our understanding of the effects of hypoxia training on our bodies to better model its dynamics and leverage some of its implications and effects on human health. Hypoxia training is a recommended practice for military and civilian pilots that allow them to recognize their early hypoxia signs and symptoms, and Scientist Astronaut Candidates (SACs) who underwent hypobaric hypoxia (HH) exposure as part of a training activity for prospective suborbital flight applications. This observational-analytical study describes physiologic responses and symptoms experienced by a SAC group before, during and after HH exposure and proposes a model for assessing predicted versus observed physiological responses. A group of individuals with diverse Science Technology Engineering Mathematics (STEM) backgrounds conducted a hypobaric training session to an altitude up to 22,000 ft (FL220) or 6,705 meters, where heart rate (HR), breathing rate (BR) and core temperature (Tc) were monitored with the use of a chest strap sensor pre and post HH exposure. A pulse oximeter registered levels of saturation of oxygen (SpO₂), number and duration of desaturations during the HH chamber flight. Hypoxia symptoms as described by the SACs during the HH training session were also registered. This data allowed to generate a preliminary predictive model of the oxygen desaturation and O₂ pressure curve for each subject, which consists of a sixth-order polynomial fit during exposure, and a fifth or fourth-order polynomial fit during recovery. Data analysis showed that HR and BR showed no significant differences between pre and post HH exposure in most of the SACs, while Tc measures showed slight but consistent decrement changes. All subjects registered SpO₂ greater than 94% for the majority of their individual HH exposures, but all of them presented at least one clinically significant desaturation (SpO₂ < 85% for more than 5 seconds) and half of the individuals showed SpO₂ below 87% for at least 30% of their HH exposure time. Finally, real time collection of HH symptoms presented temperature somatosensory perceptions (SP) for 65% of individuals, and task-focus issues for 52.5% of individuals as the most common HH indications. 95% of the subjects experienced HH onset symptoms below FL180; all participants achieved full recovery of HH symptoms within 1 minute of donning their O₂ mask. The current HH study performed on this group of individuals suggests a rapid and fully reversible physiologic response after HH exposure as expected and obtained in previous studies. Our data showed consistent results between predicted versus observed SpO₂ curves during HH suggesting a mathematical function that may be used to model HH performance deficiencies. During the HH study, real-time HH symptoms were registered providing evidenced SP and task focusing as the earliest and most common indicators. Finally, an assessment of HH signs of symptoms in a group of heterogeneous, non-pilot individuals showed similar results to previous studies in homogeneous populations of pilots.

Keywords: slow onset hypoxia, hypobaric chamber training, altitude sickness, symptoms and altitude, pressure cabin

Procedia PDF Downloads 97

Authors: Jacqueline Eleonora Ek, Michael Spiteri, Chris Giordimaina, Pierre Agius

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Background: Malta is known for being a key player as a frontline country with regard to irregular immigration from Africa to Europe. Every year the island experiences an influx of migrants as boat movement across the Mediterranean continues to be a humanitarian challenge. Irregular immigration and applying for asylum is both a lengthy and mentally demanding process. Those doing so are often faced with multiple challenges, which can adversely affect their mental health. Between January and August 2020, Malta disembarked 2 162 people rescued at sea, 463 of them between July & August. Given the small size of the Maltese islands, this regulation places a disproportionately large burden on the country, creating a backlog in the processing of asylum applications resulting in increased time periods of detention. These delays reverberate throughout multiple management pathways resulting in prolonged periods of detention and challenging access to health services. Objectives: To better understand the spatial dimensions of this humanitarian crisis, this study aims to assess disparities in the acute medical management of migrants presenting to the emergency department (ED) with acute mental health presentations as compared to that of local and non-local residents. Method: In this retrospective study, 17795 consecutive ED attendances were reviewed to look for acute mental health presentations. These were further evaluated to assess discrepancies in transportation routes to hospital, nature of presenting complaint, effects of language barriers, use of CT brain, treatment given at ED, availability of psychiatric reviews, and final admission/discharge plans. Results: Of the ED attendances, 92.3% were local residents, and 7.7% were non-locals. Of the non-locals, 13.8% were migrants, and 86.2% were other-non-locals. Acute mental health presentations were seen in 1% of local residents; this increased to 20.6% in migrants. 56.4% of migrants attended with deliberate self-harm; this was lower in local residents, 28.9%. Contrastingly, in local residents, the most common presenting complaint was suicidal thought/ low mood 37.3%, the incidence was similar in migrants at 33.3%. The main differences included 12.8% of migrants presenting with refused oral intake while only 0.6% of local residents presented with the same complaints. 7.7% of migrants presented with a reduced level of consciousness, no local residents presented with this same issue. Physicians documented a language barrier in 74.4% of migrants. 25.6% were noted to be completely uncommunicative. Further investigations included the use of a CT scan in 12% of local residents and in 35.9% of migrants. The most common treatment administered to migrants was supportive fluids 15.4%, the most common in local residents was benzodiazepines 15.1%. Voluntary psychiatric admissions were seen in 33.3% of migrants and 24.7% of locals. Involuntary admissions were seen in 23% of migrants and 13.3% of locals. Conclusion: Results showed multiple disparities in health management. A meeting was held between entities responsible for migrant health in Malta, including the emergency department, primary health care, migrant detention services, and Malta Red Cross. Currently, national quality-improvement initiatives are underway to form new pathways to improve patient-centered care. These include an interpreter unit, centralized handover sheets, and a dedicated migrant health service.

Keywords: emergency department, communication, health, migration

Procedia PDF Downloads 86

Authors: Eiji Nakamachi, Tsuyoshi Eguchi, Sayo Yamamoto, Yusuke Morita, H. Sakamoto

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In this study, we aim to reveal the relationship between the meniscal tearing and the articular cartilage injury of knee joint by using the dynamic explicit finite element (FE) method. Meniscal injuries reduce its functional ability and consequently increase the load on the articular cartilage of knee joint. In order to prevent the induction of osteoarthritis (OA) caused by meniscal injuries, many medical treatment techniques, such as artificial meniscus replacement and meniscal regeneration, have been developed. However, it is reported that these treatments are not the comprehensive methods. In order to reveal the fundamental mechanism of OA induction, the mechanical characterization of meniscus under the condition of normal and injured states is carried out by using FE analyses. At first, a FE model of the human knee joint in the case of normal state – ‘intact’ - was constructed by using the magnetron resonance (MR) tomography images and the image construction code, Materialize Mimics. Next, two types of meniscal injury models with the radial tears of medial and lateral menisci were constructed. In FE analyses, the linear elastic constitutive law was adopted for the femur and tibia bones, the visco-hyperelastic constitutive law for the articular cartilage, and the visco-anisotropic hyperelastic constitutive law for the meniscus, respectively. Material properties of articular cartilage and meniscus were identified using the stress-strain curves obtained by our compressive and the tensile tests. The numerical results under the normal walking condition revealed how and where the maximum compressive stress occurred on the articular cartilage. The maximum compressive stress and its occurrence point were varied in the intact and two meniscal tear models. These compressive stress values can be used to establish the threshold value to cause the pathological change for the diagnosis. In this study, FE analyses of knee joint were carried out to reveal the influence of meniscal injuries on the cartilage injury. The following conclusions are obtained. 1. 3D FE model, which consists femur, tibia, articular cartilage and meniscus was constructed based on MR images of human knee joint. The image processing code, Materialize Mimics was used by using the tetrahedral FE elements. 2. Visco-anisotropic hyperelastic constitutive equation was formulated by adopting the generalized Kelvin model. The material properties of meniscus and articular cartilage were determined by curve fitting with experimental results. 3. Stresses on the articular cartilage and menisci were obtained in cases of the intact and two radial tears of medial and lateral menisci. Through comparison with the case of intact knee joint, two tear models show almost same stress value and higher value than the intact one. It was shown that both meniscal tears induce the stress localization in both medial and lateral regions. It is confirmed that our newly developed FE analysis code has a potential to be a new diagnostic system to evaluate the meniscal damage on the articular cartilage through the mechanical functional assessment.

Keywords: finite element analysis, hyperelastic constitutive law, knee joint injury, meniscal tear, stress concentration

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Authors: Berengere Vire, Nicolas Salvetat, Yoann Lannay, Guillaume Marcellin, Siem Van Der Laan, Franck Molina, Dinah Weissmann

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Predicting suicidal behaviors is one of the most complex challenges of daily psychiatric practices. Today, suicide risk prediction using biological tools is not validated and is only based on subjective clinical reports of the at-risk individual. Therefore, there is a great need to identify biomarkers that would allow early identification of individuals at risk of suicide. Alterations of adenosine-to-inosine (A-to-I) RNA editing of neurotransmitter receptors and other proteins have been shown to be involved in etiology of different psychiatric disorders and linked to suicidal behavior. RNA editing is a co- or post-transcriptional process leading to a site-specific alteration in RNA sequences. It plays an important role in the epi transcriptomic regulation of RNA metabolism. On postmortem human brain tissue (prefrontal cortex) of depressed suicide victims, Alcediag found specific alterations of RNA editing activity on the mRNA coding for the serotonin 2C receptor (5-HT2cR). Additionally, an increase in expression levels of ADARs, the RNA editing enzymes, and modifications of RNA editing profiles of prime targets, such as phosphodiesterase 8A (PDE8A) mRNA, have also been observed. Interestingly, the PDE8A gene is located on chromosome 15q25.3, a genomic region that has recurrently been associated with the early-onset major depressive disorder (MDD). In the current study, we examined whether modifications in RNA editing profile of prime targets allow identifying disease-relevant blood biomarkers and evaluating suicide risk in patients. To address this question, we performed a clinical study to identify an RNA editing signature in blood of depressed patients with and without the history of suicide attempts. Patient’s samples were drawn in PAXgene tubes and analyzed on Alcediag’s proprietary RNA editing platform using next generation sequencing technology. In addition, gene expression analysis by quantitative PCR was performed. We generated a multivariate algorithm comprising various selected biomarkers to detect patients with a high risk to attempt suicide. We evaluated the diagnostic performance using the relative proportion of PDE8A mRNA editing at different sites and/or isoforms as well as the expression of PDE8A and the ADARs. The significance of these biomarkers for suicidality was evaluated using the area under the receiver-operating characteristic curve (AUC). The generated algorithm comprising the biomarkers was found to have strong diagnostic performances with high specificity and sensitivity. In conclusion, we developed tools to measure disease-specific biomarkers in blood samples of patients for identifying individuals at the greatest risk for future suicide attempts. This technology not only fosters patient management but is also suitable to predict the risk of drug-induced psychiatric side effects such as iatrogenic increase of suicidal ideas/behaviors.

Keywords: blood biomarker, next-generation-sequencing, RNA editing, suicide

Procedia PDF Downloads 233

Authors: Elena I. Oprita, Oana Craciunescu, Rodica Tatia, Teodora Ciucan, Reka Barabas, Orsolya Raduly, Anca Oancea

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Healing of osteochondral defects requires repair of the damaged articular cartilage, the underlying subchondral bone and the interface between these tissues (the functional calcified layer). For this purpose, developing a single monophasic scaffold that can regenerate two specific lineages (cartilage and bone) becomes a challenge. The aim of this work was to develop variants of biodegradable cross-linked composite hydrogel based on natural polypeptides (gelatin), polysaccharides components (chondroitin-4-sulphate and hyaluronic acid), in a ratio of 2:0.08:0.02 (w/w/w) and mixed with Si-hydroxyapatite (Si-Hap), in two ratios of 1:1 and 2:1 (w/w). Si-Hap was synthesized and characterized as a better alternative to conventional Hap. Subsequently, both composite hydrogel variants were cross-linked with (N, N-(3-dimethylaminopropyl)-N-ethyl carbodiimide (EDC) and enriched with a small bioactive molecule (icariin). The small molecule icariin (Ica) (C33H40O15) is the main active constituent (flavonoid) of Herba epimedium used in traditional Chinese medicine to cure bone- and cartilage-related disorders. Ica enhances osteogenic and chondrogenic differentiation of bone marrow mesenchymal stem cells (BMSCs), facilitates matrix calcification and increases the specific extracellular matrix (ECM) components synthesis by chondrocytes. Afterward, the composite hydrogels were characterized for their physicochemical properties in terms of the enzymatic biodegradation in the presence of type I collagenase and trypsin, the swelling capacity and the degree of crosslinking (TNBS assay). The cumulative release of Ica and real-time concentration were quantified at predetermined periods of time, according to the standard curve of standard Ica, after hydrogels incubation in saline buffer at physiological parameters. The obtained cross-linked composite hydrogels enriched with small-molecule Ica were also characterized for morphology by scanning electron microscopy (SEM). Their cytocompatibility was evaluated according to EN ISO 10993-5:2009 standard for medical device testing. Thus, analyses regarding cell viability (Live/Dead assay), cell proliferation (Neutral Red assay) and cell adhesion to composite hydrogels (SEM) were performed using NCTC clone L929 cell line. The final results showed that both cross-linked composite hydrogel variants enriched with Ica presented optimal physicochemical, structural and biological properties to be used as a natural scaffold able to repair osteochondral defects. The data did not reveal any toxicity of composite hydrogels in NCTC stabilized cell lines within the tested range of concentrations. Moreover, cells were capable of spreading and proliferating on both composite hydrogel surfaces. In conclusion, the designed biodegradable cross-linked composites enriched with Si and Ica are recommended for further testing as natural temporary scaffolds, which can allow cell migration and synthesis of new extracellular matrix within osteochondral defects.

Keywords: composites, gelatin, osteochondral defect, small molecule

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Authors: Lorenzo Petrucci

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This paper is intended to give insight into the potential use of small-scale off-grid trigeneration systems powered by biogas generated in a dairy farm. The off-grid plant object of analysis comprises a dual-fuel Genset as well as electrical and thermal storage equipment and an adsorption machine. The loads are the different apparatus used in the dairy farm, a household where the workers live and a small electric vehicle whose batteries can also be used as a power source in case of emergency. The insertion in the plant of an adsorption machine is mainly justified by the abundance of thermal energy and the simultaneous high cooling demand associated with the milk-chilling process. In the evaluated operational scenario, our research highlights the importance of prioritizing specific small loads which cannot sustain an interrupted supply of power over time. As a consequence, a photovoltaic and thermal panel is included in the plant and is tasked with providing energy independently of potentially disruptive events such as engine malfunctioning or scarce and unstable supplies of fuels. To efficiently manage the plant an energy dispatch strategy is created in order to control the flow of energy between the power sources and the thermal and electric storages. In this article we elaborate on models of the equipment and from these models, we extract parameters useful to build load-dependent profiles of the prime movers and storage efficiencies. We show that under reasonable assumptions the analysis provides a sensible estimate of the generated energy. The simulations indicate that a Diesel Generator sized to a value 25% higher than the total electrical peak demand operates 65% of the time below the minimum acceptable load threshold. To circumvent such a critical operating mode, dump loads are added through the activation and deactivation of small resistors. In this way, the excess of electric energy generated can be transformed into useful heat. The combination of PVT and electrical storage to support the prioritized load in an emergency scenario is evaluated in two different days of the year having the lowest and highest irradiation values, respectively. The results show that the renewable energy component of the plant can successfully sustain the prioritized loads and only during a day with very low irradiation levels it also needs the support of the EVs’ battery. Finally, we show that the adsorption machine can reduce the ice builder and the air conditioning energy consumption by 40%.

Keywords: hybrid power plants, mathematical modeling, off-grid plants, renewable energy, trigeneration

Procedia PDF Downloads 153

Authors: Yogesh Kumar Singh, T. S. Murugesh Prabhu, Upasana Dutta, Girishchandra Yendargaye, Rahul Yadav, Rohini Gopinath Kale, Binay Kumar, Manoj Khare

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The Indian subcontinent is severely affected by floods that cause intense irreversible devastation to crops and livelihoods. With increased incidences of floods and their related catastrophes, an Early Warning System for Flood Prediction and an efficient Flood Management System for the river basins of India is a must. Accurately modeled hydrological conditions and a web-based early warning system may significantly reduce economic losses incurred due to floods and enable end users to issue advisories with better lead time. This study describes the design and development of an EWS-FP using advanced computational tools/methods, viz. High-Performance Computing (HPC), Remote Sensing, GIS technologies, and open-source tools for the Mahanadi River Basin of India. The flood prediction is based on a robust 2D hydrodynamic model, which solves shallow water equations using the finite volume method. Considering the complexity of the hydrological modeling and the size of the basins in India, it is always a tug of war between better forecast lead time and optimal resolution at which the simulations are to be run. High-performance computing technology provides a good computational means to overcome this issue for the construction of national-level or basin-level flash flood warning systems having a high resolution at local-level warning analysis with a better lead time. High-performance computers with capacities at the order of teraflops and petaflops prove useful while running simulations on such big areas at optimum resolutions. In this study, a free and open-source, HPC-based 2-D hydrodynamic model, with the capability to simulate rainfall run-off, river routing, and tidal forcing, is used. The model was tested for a part of the Mahanadi River Basin (Mahanadi Delta) with actual and predicted discharge, rainfall, and tide data. The simulation time was reduced from 8 hrs to 3 hrs by increasing CPU nodes from 45 to 135, which shows good scalability and performance enhancement. The simulated flood inundation spread and stage were compared with SAR data and CWC Observed Gauge data, respectively. The system shows good accuracy and better lead time suitable for flood forecasting in near-real-time. To disseminate warning to the end user, a network-enabled solution is developed using open-source software. The system has query-based flood damage assessment modules with outputs in the form of spatial maps and statistical databases. System effectively facilitates the management of post-disaster activities caused due to floods, like displaying spatial maps of the area affected, inundated roads, etc., and maintains a steady flow of information at all levels with different access rights depending upon the criticality of the information. It is designed to facilitate users in managing information related to flooding during critical flood seasons and analyzing the extent of the damage.

Keywords: flood, modeling, HPC, FOSS

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Authors: M. Duk, L. Grabowski, P. Magryta

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Today's very important element relating to air transport is the environment impact issues. Nowadays there are no emissions standards for turbine and piston engines used in air transport. However, it should be noticed that the environmental effect in the form of exhaust gases from aircraft engines should be as small as possible. For this purpose, R&D centers often use special software to simulate and to estimate the negative effect of engine working process. For cooperation between the Lublin University of Technology and the Polish aviation company WSK "PZL-KALISZ" S.A., to achieve more effective operation of the ASz62IR engine, one of such tools have been used. The AVL Boost software allows to perform 1D simulations of combustion process of piston engines. ASz62IR is a nine-cylinder aircraft engine in a radial configuration. In order to analyze the impact of its working process on the environment, the mathematical model in the AVL Boost software have been made. This model contains, among others, model of the operation cycle of the cylinders. This model was based on a volume change in combustion chamber according to the reciprocating movement of a piston. The simplifications that all of the pistons move identically was assumed. The changes in cylinder volume during an operating cycle were specified. Those changes were important to determine the energy balance of a cylinder in an internal combustion engine which is fundamental for a model of the operating cycle. The calculations for cylinder thermodynamic state were based on the first law of thermodynamics. The change in the mass in the cylinder was calculated from the sum of inflowing and outflowing masses including: cylinder internal energy, heat from the fuel, heat losses, mass in cylinder, cylinder pressure and volume, blowdown enthalpy, evaporation heat etc. The model assumed that the amount of heat released in combustion process was calculated from the pace of combustion, using Vibe model. For gas exchange, it was also important to consider heat transfer in inlet and outlet channels because of much higher values there than for flow in a straight pipe. This results from high values of heat exchange coefficients and temperature coefficients near valves and valve seats. A Zapf modified model of heat exchange was used. To use the model with the flight scenarios, the impact of flight altitude on engine performance has been analyze. It was assumed that the pressure and temperature at the inlet and outlet correspond to the values resulting from the model for International Standard Atmosphere (ISA). Comparing this model of operation cycle with the others submodels of the ASz62IR engine, it could be noticed, that a full analysis of the performance of the engine, according to the ISA conditions, can be made. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under

Keywords: aviation propulsion, AVL Boost, engine model, operation cycle, aircraft engine

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Authors: Amir Asadi, Karim Habib, Robert J. Moon, Kyriaki Kalaitzidou

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There has been considerable interest in cellulose nanomaterials (CN) as polymer and polymer composites reinforcement due to their high specific modulus and strength, low density and toxicity, and accessible hydroxyl side groups that can be readily chemically modified. The focus of this study is making lightweight composites for better fuel efficiency and lower CO2 emission in auto industries with no compromise on mechanical performance using a scalable technique that can be easily integrated in sheet molding compound (SMC) manufacturing lines. Light weighting will be achieved by replacing part of the heavier components, i.e. glass fibers (GF), with a small amount of cellulose nanocrystals (CNC) in short GF/epoxy composites made using SMC. CNC will be introduced as coating of the GF rovings prior to their use in the SMC line. The employed coating method is similar to the fiber sizing technique commonly used and thus it can be easily scaled and integrated to industrial SMC lines. This will be an alternative route to the most techniques that involve dispersing CN in polymer matrix, in which the nanomaterials agglomeration limits the capability for scaling up in an industrial production. We have demonstrated that incorporating CNC as a coating on GF surface by immersing the GF in CNC aqueous suspensions, a simple and scalable technique, increases the interfacial shear strength (IFSS) by ~69% compared to the composites produced by uncoated GF, suggesting an enhancement of stress transfer across the GF/matrix interface. As a result of IFSS enhancement, incorporation of 0.17 wt% CNC in the composite results in increases of ~10% in both elastic modulus and tensile strength, and 40 % and 43 % in flexural modulus and strength respectively. We have also determined that dispersing 1.4 and 2 wt% CNC in the epoxy matrix of short GF/epoxy SMC composites by sonication allows removing 10 wt% GF with no penalty on tensile and flexural properties leading to 7.5% lighter composites. Although sonication is a scalable technique, it is not quite as simple and inexpensive as coating the GF by passing through an aqueous suspension of CNC. In this study, the above findings are integrated to 1) investigate the effect of CNC content on mechanical properties by passing the GF rovings through CNC aqueous suspension with various concentrations (0-5%) and 2) determine the optimum ratio of the added CNC to the removed GF to achieve the maximum possible weight reduction with no cost on mechanical performance of the SMC composites. The results of this study are of industrial relevance, providing a path toward producing high volume lightweight and mechanically enhanced SMC composites using cellulose nanomaterials.

Keywords: cellulose nanocrystals, light weight polymer-matrix composites, mechanical properties, sheet molding compound (SMC)

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Authors: Ammar Alali, Mahmoud Abughaban

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Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

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Authors: Robert Pečenko, Karin Tomažič, Igor Planinc, Sabina Huč, Tomaž Hozjan

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Timber is favourable structural material due to high strength to weight ratio, recycling possibilities, and green credentials. Despite being flammable material, it has relatively high fire resistance. Everyday engineering practice around the word is based on an outdated design of timber structures considering standard fire exposure, while modern principles of performance-based design enable use of advanced non-standard fire curves. In Europe, standard for fire design of timber structures EN 1995-1-2 (Eurocode 5) gives two methods, reduced material properties method and reduced cross-section method. In the latter, fire resistance of structural elements depends on the effective cross-section that is a residual cross-section of uncharred timber reduced additionally by so called zero strength layer. In case of standard fire exposure, Eurocode 5 gives a fixed value of zero strength layer, i.e. 7 mm, while for non-standard parametric fires no additional comments or recommendations for zero strength layer are given. Thus designers often implement adopted 7 mm rule also for parametric fire exposure. Since the latest scientific evidence suggests that proposed value of zero strength layer can be on unsafe side for standard fire exposure, its use in the case of a parametric fire is also highly questionable and more numerical and experimental research in this field is needed. Therefore, the purpose of the presented study is to use advanced calculation methods to investigate the thickness of zero strength layer and parametric charring rates used in effective cross-section method in case of parametric fire. Parametric studies are carried out on a simple solid timber beam that is exposed to a larger number of parametric fire curves Zero strength layer and charring rates are determined based on the numerical simulations which are performed by the recently developed advanced two step computational model. The first step comprises of hygro-thermal model which predicts the temperature, moisture and char depth development and takes into account different initial moisture states of timber. In the second step, the response of timber beam simultaneously exposed to mechanical and fire load is determined. The mechanical model is based on the Reissner’s kinematically exact beam model and accounts for the membrane, shear and flexural deformations of the beam. Further on, material non-linear and temperature dependent behaviour is considered. In the two step model, the char front temperature is, according to Eurocode 5, assumed to have a fixed temperature of around 300°C. Based on performed study and observations, improved levels of charring rates and new thickness of zero strength layer in case of parametric fires are determined. Thus, the reduced cross section method is substantially improved to offer practical recommendations for designing fire resistance of timber structures. Furthermore, correlations between zero strength layer thickness and key input parameters of the parametric fire curve (for instance, opening factor, fire load, etc.) are given, representing a guideline for a more detailed numerical and also experimental research in the future.

Keywords: advanced numerical modelling, parametric fire exposure, timber structures, zero strength layer

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Authors: G. Magalhães-Mota, C. Magro, S. Sério, E. Mateus, P. A. Ribeiro, A. B. Ribeiro, M. Raposo

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Triclosan [5-chloro-2-(2,4-dichlorophenoxy) phenol], belonging to the class of Pharmaceuticals and Personal Care Products (PPCPs), is a broad-spectrum antimicrobial agent and bactericide. Because of its antimicrobial efficacy, it is widely used in personal health and skin care products, such as soaps, detergents, hand cleansers, cosmetics, toothpastes, etc. However, it has been considered to disrupt the endocrine system, for instance, thyroid hormone homeostasis and possibly the reproductive system. Considering the widespread use of triclosan, it is expected that environmental and food safety problems regarding triclosan will increase dramatically. Triclosan has been found in river water samples in both North America and Europe and is likely widely distributed wherever triclosan-containing products are used. Although significant amounts are removed in sewage plants, considerable quantities remain in the sewage effluent, initiating widespread environmental contamination. Triclosan undergoes bioconversion to methyl-triclosan, which has been demonstrated to bio accumulate in fish. In addition, triclosan has been found in human urine samples from persons with no known industrial exposure and in significant amounts in samples of mother's milk, demonstrating its presence in humans. The action of sunlight in river water is known to turn triclosan into dioxin derivatives and raises the possibility of pharmacological dangers not envisioned when the compound was originally utilized. The aim of this work is to detect low concentrations of triclosan in an aqueous complex matrix through the use of a sensor array system, following the electronic tongue concept based on impedance spectroscopy. To achieve this goal, we selected the appropriate molecules to the sensor so that there is a high affinity for triclosan and whose sensitivity ensures the detection of concentrations of at least nano-molar. Thin films of organic molecules and oxides have been produced by the layer-by-layer (LbL) technique and sputtered onto glass solid supports already covered by gold interdigitated electrodes. By submerging the films in complex aqueous solutions with different concentrations of triclosan, resistance and capacitance values were obtained at different frequencies. The preliminary results showed that an array of interdigitated electrodes sensor coated or uncoated with different LbL and films, can be used to detect TCS traces in aqueous solutions in a wide range concentration, from 10⁻¹² to 10⁻⁶ M. The PCA method was applied to the measured data, in order to differentiate the solutions with different concentrations of TCS. Moreover, was also possible to trace a curve, the plot of the logarithm of resistance versus the logarithm of concentration, which allowed us to fit the plotted data points with a decreasing straight line with a slope of 0.022 ± 0.006 which corresponds to the best sensitivity of our sensor. To find the sensor resolution near of the smallest concentration (Cs) used, 1pM, the minimum measured value which can be measured with resolution is 0.006, so the ∆logC =0.006/0.022=0.273, and, therefore, C-Cs~0.9 pM. This leads to a sensor resolution of 0.9 pM for the smallest concentration used, 1pM. This attained detection limit is lower than the values obtained in the literature.

Keywords: triclosan, layer-by-layer, impedance spectroscopy, electronic tongue

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Authors: Natalie Hoyer

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Usually, steel structures are designed for the upper region of the steel toughness-temperature curve. To address the reduced toughness properties in the temperature transition range, additional safety assessments based on fracture mechanics are necessary. These assessments enable the appropriate selection of steel materials to prevent brittle fracture. In this context, recommendations were established in 2011 to regulate the appropriate selection of steel grades for bridge bearing components. However, these recommendations are no longer fully aligned with more recent insights: Designing bridge bearings and their components in accordance with DIN EN 1337 and the relevant sections of DIN EN 1993 has led to an increasing trend of using large plate thicknesses, especially for long-span bridges. However, these plate thicknesses surpass the application limits specified in the national appendix of DIN EN 1993-2. Furthermore, compliance with the regulations outlined in DIN EN 1993-1-10 regarding material toughness and through-thickness properties requires some further modifications. Therefore, these standards cannot be directly applied to the material selection for bearings without additional information. In addition, recent findings indicate that certain bridge bearing components are subjected to high fatigue loads, necessitating consideration in structural design, material selection, and calculations. To address this issue, the German Center for Rail Traffic Research initiated a research project aimed at developing a proposal to enhance the existing standards. This proposal seeks to establish guidelines for the selection of steel materials for bridge bearings to prevent brittle fracture, particularly for thick plates and components exposed to specific fatigue loads. The results derived from theoretical analyses, including finite element simulations and analytical calculations, are verified through component testing on a large-scale. During these large-scale tests, where a brittle failure is deliberately induced in a bearing component, an artificially generated defect is introduced into the specimen at the predetermined hotspot. Subsequently, a dynamic load is imposed until the crack initiation process transpires, replicating realistic conditions akin to a sharp notch resembling a fatigue crack. To stop the action of the dynamic load in time, it is important to precisely determine the point at which the crack size transitions from stable crack growth to unstable crack growth. To achieve this, the potential drop measurement method is employed. The proposed paper informs about the choice of measurement method (alternating current potential drop (ACPD) or direct current potential drop (DCPD)), presents results from correlations with created FE models, and may proposes a new approach to introduce beach marks into the fracture surface within the framework of potential drop measurement.

Keywords: beach marking, bridge bearing design, brittle fracture, design for fatigue, potential drop

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Authors: Benjamin Blat Belmonte, Stephan Rinderknecht

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The transition to electric vehicles (EVs) stands at the forefront of innovative strategies designed to address environmental concerns and reduce fossil fuel dependency. As the number of EVs on the roads increases, so too does the potential for their integration into energy markets. This research dives deep into the transformative possibilities of using electric vehicle fleets, specifically electric bus fleets, not just as consumers but as active participants in the energy market. This paper investigates the feasibility and grid effects of electric vehicle fleet operators in the energy market. Our objective centers around a comprehensive exploration of the sector coupling domain, with an emphasis on the economic potential in both electricity and balancing markets. Methodologically, our approach combines data mining techniques with thorough pre-processing, pulling from a rich repository of electricity and balancing market data. Our findings are grounded in the actual operational realities of the bus fleet operator in Darmstadt, Germany. We employ a Mixed Integer Linear Programming (MILP) approach, with the bulk of the computations being processed on the High-Performance Computing (HPC) platform ‘Lichtenbergcluster’. Our findings underscore the compelling economic potential of EV fleets in the energy market. With electric buses becoming more prevalent, the considerable size of these fleets, paired with their substantial battery capacity, opens up new horizons for energy market participation. Notably, our research reveals that economic viability is not the sole advantage. Participating actively in the energy market also translates into pronounced positive effects on grid stabilization. Essentially, EV fleet operators can serve a dual purpose: facilitating transport while simultaneously playing an instrumental role in enhancing grid reliability and resilience. This research highlights the symbiotic relationship between the growth of EV fleets and the stabilization of the energy grid. Such systems could lead to both commercial and ecological advantages, reinforcing the value of electric bus fleets in the broader landscape of sustainable energy solutions. In conclusion, the electrification of transport offers more than just a means to reduce local greenhouse gas emissions. By positioning electric vehicle fleet operators as active participants in the energy market, there lies a powerful opportunity to drive forward the energy transition. This study serves as a testament to the synergistic potential of EV fleets in bolstering both economic viability and grid stabilization, signaling a promising trajectory for future sector coupling endeavors.

Keywords: electric vehicle fleet, sector coupling, optimization, electricity market, balancing market

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Authors: Joshua Kaufman, Felix Tan, Morgan Monroe, Ayman Abouraddy

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Textiles and clothing have been a staple of human existence for millennia, yet the basic structure and functionality of textile fibers and yarns has remained unchanged. While color and appearance are essential characteristics of a textile, an advancement in the fabrication of yarns that allows for user-controlled dynamic changes to the color or appearance of a garment has been lacking. Touch-activated and photosensitive pigments have been used in textiles, but these technologies are passive and cannot be controlled by the user. The technology described here allows the owner to control both when and in what pattern the fabric color-change takes place. In addition, the manufacturing process is compatible with mass-producing the user-controlled, color-changing yarns. The yarn fabrication utilizes a fiber spinning system that can produce either monofilament or multifilament yarns. For products requiring a more robust fabric (backpacks, purses, upholstery, etc.), larger-diameter monofilament yarns with a coarser weave are suitable. Such yarns are produced using a thread-coater attachment to encapsulate a 38-40 AWG metal wire inside a polymer sheath impregnated with thermochromic pigment. Conversely, products such as shirts and pants requiring yarns that are more flexible and soft against the skin comprise multifilament yarns of much smaller-diameter individual fibers. Embedding a metal wire in a multifilament fiber spinning process has not been realized to date. This research has required collaboration with Hills, Inc., to design a liquid metal-injection system to be combined with fiber spinning. The new system injects molten tin into each of 19 filaments being spun simultaneously into a single yarn. The resulting yarn contains 19 filaments, each with a tin core surrounded by a polymer sheath impregnated with thermochromic pigment. The color change we demonstrate is distinct from garments containing LEDs that emit light in various colors. The pigment itself changes its optical absorption spectrum to appear a different color. The thermochromic color-change is induced by a temperature change in the inner metal wire within each filament when current is applied from a small battery pack. The temperature necessary to induce the color change is near body temperature and not noticeable by touch. The prototypes already developed either use a simple push button to activate the battery pack or are wirelessly activated via a smart-phone app over Wi-Fi. The app allows the user to choose from different activation patterns of stripes that appear in the fabric continuously. The power requirements are mitigated by a large hysteresis in the activation temperature of the pigment and the temperature at which there is full color return. This was made possible by a collaboration with Chameleon International to develop a new, customized pigment. This technology enables a never-before seen capability: user-controlled, dynamic color and pattern change in large-area woven and sewn textiles and fabrics with wide-ranging applications from clothing and accessories to furniture and fixed-installation housing and business décor. The ability to activate through Wi-Fi opens up possibilities for the textiles to be part of the ‘Internet of Things.’ Furthermore, this technology is scalable to mass-production levels for wide-scale market adoption.

Keywords: activation, appearance, color, manufacturing

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

Procedia PDF Downloads 47