Search results for: radiative transfer

Authors: Alla Ovsyannikova, Oksana Rymar, Elena Shakhtshneider, Mikhail Voevoda

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In Siberia endocrinologists increasingly noted young patients with the course of diabetes mellitus differing from 1 and 2 types. Therefore we did a molecular genetic study for this group of patients to verify the monogenic forms of diabetes mellitus in them and researched the characteristics of this pathology. When confirming the monogenic form of diabetes, we performed a correction therapy for many patients (transfer from insulin to tablets), prevented specific complications, examined relatives and diagnosed their diabetes at the preclinical stage, revealed phenotypic characteristics of the pathology which led to the high significance of this work. Materials and Methods: We observed 5 patients (4 families). We diagnosed MODY (Maturity Onset Diabetes of the Young) during the molecular genetic testing (direct automatic sequencing). All patients had a full clinical examination, blood samples for biochemical research, determination of C-peptide and TSH, antibodies to b-cells, microalbuminuria, abdominal ultrasound, heart and thyroid ultrasound, examination of ophthalmologist. Results: We diagnosed 3 rare types of MODY: two women had MODY8, one man – MODY6 and man and his mother - MODY12. Patients with types 8 and 12 had clinical features. Age of onset hyperglycemia ranged from 26 to 34 years. In a patient with MODY6 fasting hyperglycemia was detected during a routine examination. Clinical symptoms, complications were not diagnosed. The patient observes a diet. In the first patient MODY8 was detected during first pregnancy, she had itchy skin and mostly postprandial hyperglycemia. Upon examination we determined glycated hemoglobin 7.5%, retinopathy, non-proliferative stage, peripheral neuropathy. She uses a basic bolus insulin therapy. The second patient with MODY8 also had clinical manifestations of hyperglycemia (pruritus, thirst), postprandial hyperglycemia and diabetic nephropathy, a stage of microalbuminuria. The patient was diagnosed autoimmune thyroiditis. She used inhibitors of DPP-4. The patient with MODY12 had an aggressive course. In the detection of hyperglycemia he had complaints of visual impairment, intense headaches, leg cramps. The patient had a history of childhood convulsive seizures of non-epileptic genesis, without organic pathology, which themselves were stopped at the age of 12 years. When we diagnosed diabetes a patient was 28 years, he had hypertriglyceridemia, atherosclerotic plaque in the carotid artery, proliferative retinopathy (lacerocoagulation). Diabetes and early myocardial infarction were observed in three cases in family. We prescribe therapy with sulfonylureas and SGLT-2 inhibitors with a positive effect. At the patient's mother diabetes began at a later age (30 years) and a less aggressive course was observed. She also has hypertriglyceridemia and uses oral hypoglycemic drugs. Conclusions: 1) When young patients with hyperglycemia have extrapancreatic pathologies and diabetic complications with a short duration of diabetes we can assume they have one of type of MODY diabetes. 2) In patients with monogenic forms of diabetes mellitus, the clinical manifestations of hyperglycemia in each succeeding generation are revealed at an earlier age. Research had increased our knowledge of the monogenic forms of diabetes. The reported study was supported by RSCF, research project No. 14-15-00496-P.

Keywords: diabetes mellitus, MODY diabetes, monogenic forms, young patients

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Authors: Eduardo Martínez González, Mousumi Dey, Pekka Peljo

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Transitioning to a renewable energy model is inevitable owing to the effects of climate change. These energies are aimed at sustainability and a positive impact on the environment, but they are intermittent energies; their connection to the electrical grid depends on creating long-term, efficient, and low-cost energy storage devices. Redox flow batteries are attractive technologies to address this problem, as they store energy in solution through external tanks known as posolyte (solution to storage positive charge) and negolyte (solution to storage negative charge). During the charging process of the device, the posolyte and negolyte solutions are pumped into an electrochemical cell (which has the anode and cathode separated by an ionic membrane), where they undergo oxidation and reduction reactions at electrodes, respectively. The electrogenerated species should be stable and diffuse into the bulk solution. It has been possible to connect gigantic redox flow batteries to the electrical grid. However, the devices created do not fit with the sustainability criteria since their electroactive material consists of vanadium (material scarce and expensive) solutions dissolved in an acidic medium (e.g., 9 mol L-1 of H₂SO₄) that is highly corrosive; so, work is being done on the design of organic-electroactive electrolytes (posolytes and nogolytes) for their operation at different pH values, including neutral medium. As a main characteristic, negolyte species should have low reduction potential values, while the reverse is true for the oxidation process of posolytes. A wide variety of negolytes that store 1 and up to 2 electrons per molecule (in aqueous medium) have been publised. Gallocyanine compound was recently introduced as an electroactive material for developing alkaline flow battery negolytes. The system can storage two electrons per molecule, but its unexpectedly low water solubility was improved with an amino sulphonic acid additive. The cycling stability of and improved gallocyanine electrolyte was demonstrated by operating a flow battery cell (pairing the system to a posolyte composed of ferri/ferrocyanide solution) outside a glovebox. We also discovered that the additive improves the solubility of gallocyanine, but there is a kinetic price to pay for this advantage. Therefore, in this work, the effect of different amino sulphonic acid derivatives on the kinetics and solubility of gallocyanine compound was studied at alkaline solutions. The additive providing a faster electron transfer rate and high solubility was tested in a flow battery cell. An aqueous organic flow battery electrolyte working outside a glovebox with 15 mAhL-1 will be discussed. Acknowledgments: To Bi3BoostFlowBat Project (2021-2025), funded by the European Research Concil. For support with infrastructure, reagents, and a postdoctoral fellowship to Dr. Martínez-González.

Keywords: alkaline flow battery, gallocyanine electroactive material, amine-sulphonic acid additives, improved solubility

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Authors: Akeel A. Shah, Tong Zhang

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Computational approaches to learning the properties of materials are commonplace, motivated by the need to screen or design materials for a given application, e.g., semiconductors and energy storage. Experimental approaches can be both time consuming and costly. Unfortunately, computational approaches such as ab-initio electronic structure calculations and classical or ab-initio molecular dynamics are themselves can be too slow for the rapid evaluation of materials, often involving thousands to hundreds of thousands of candidates. Machine learning assisted approaches have been developed to overcome the time limitations of purely physics-based approaches. These approaches, on the other hand, require large volumes of data for training (hundreds of thousands on many standard data sets such as QM7b). This means that they are limited by how quickly such a large data set of physics-based simulations can be established. At high fidelity, such as configuration interaction, composite methods such as G4, and coupled cluster theory, gathering such a large data set can become infeasible, which can compromise the accuracy of the predictions - many applications require high accuracy, for example band structures and energy levels in semiconductor materials and the energetics of charge transfer in energy storage materials. In order to circumvent this problem, multi-fidelity approaches can be adopted, for example the Δ-ML method, which learns a high-fidelity output from a low-fidelity result such as Hartree-Fock or density functional theory (DFT). The general strategy is to learn a map between the low and high fidelity outputs, so that the high-fidelity output is obtained a simple sum of the physics-based low-fidelity and correction, Although this requires a low-fidelity calculation, it typically requires far fewer high-fidelity results to learn the correction map, and furthermore, the low-fidelity result, such as Hartree-Fock or semi-empirical ZINDO, is typically quick to obtain, For high-fidelity outputs the result can be an order of magnitude or more in speed up. In this work, a new multi-fidelity approach is developed, based on a graph convolutional network (GCN) combined with semi-supervised learning. The GCN allows for the material or molecule to be represented as a graph, which is known to improve accuracy, for example SchNet and MEGNET. The graph incorporates information regarding the numbers of, types and properties of atoms; the types of bonds; and bond angles. They key to the accuracy in multi-fidelity methods, however, is the incorporation of low-fidelity output to learn the high-fidelity equivalent, in this case by learning their difference. Semi-supervised learning is employed to allow for different numbers of low and high-fidelity training points, by using an additional GCN-based low-fidelity map to predict high fidelity outputs. It is shown on 4 different data sets that a significant (at least one order of magnitude) increase in accuracy is obtained, using one to two orders of magnitude fewer low and high fidelity training points. One of the data sets is developed in this work, pertaining to 1000 simulations of quinone molecules (up to 24 atoms) at 5 different levels of fidelity, furnishing the energy, dipole moment and HOMO/LUMO.

Keywords: .materials screening, computational materials, machine learning, multi-fidelity, graph convolutional network, semi-supervised learning

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Authors: Vijayabhaskar Reddy Kandula, Peter Provost Taillac, Balasubramanya M. A., Ram Krishnan Nair, Gokul Toshnival, Vibhu Dhawan, Vijaya Karanam, Buffy Cramer

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Introduction: The lack of Emergency Care Services (ECS) is a cause of extensive and serious public health problems in low- and middle-income countries (LMIC), Many LMIC countries have ambulance services that allow timely transfer of ill patients but due to poor care during the ‘Golden Hour’ many deaths occur which are otherwise preventable. Lack of adequate training as evidenced by a study in India is a major reason for poor care during the ‘Golden Hour’. Adapting developed country models which includes staffing specialty-trained doctors in emergency care, is neither feasible nor guarantees cost-effective ECS. Methods: Based on our assessment and felt needs by first-line doctors providing emergency care in 2014, Rajiv Gandhi Health Sciences University’s JeevaRaksha Trust in partnership with the University of Utah, USA, designed, piloted and successfully implemented a 4-day Comprehensive-Emergency Care and Life Support course (C-ECLS) for allopathic doctors. 1730 doctors completed the 4-day course between June 2014 and December- 2020. Subsequently, we conducted a survey to investigate the utilization rates and usefulness of the training. 1662 were contacted but only 309 completed the survey. The respondents had the following designations: Senior faculty (33%), junior faculty (25), Resident (16%), Private-Practitioners (8%), Medical-Officer (16%) and not-working (11%). 51% were generalists (51%) and the rest were specialists (>30 specialties). Results: 97% (271/280) felt they are better doctors because of C-ECLS. 79% (244/309) reported that training helped to save life- specialists more likely than generalists (91% v/s 68%. P<0.05). 64% agreed that they were confident of managing COVID-19 symptomatic patients better because of C-ECLS. 27% (77) were neutral; 9% (24) disagreed. 66% agreed that training helps to be confident in managing COVID-19 critically ill patients. 26% (72) were neutral; 8% (23) disagreed. Frequency of use of C-ECLS skills: Hemorrhage-control (70%), Airway (67%), circulation skills (62%), Safe-transport and communication (60%), managing critically ill patients (58%), cardiac arrest (51%), Trauma (49%), poisoning/animal bites/stings (44%), neonatal-resuscitation (39%), breathing (36%), post-partum-hemorrhage and eclampsia (35%). Among those who used the skills, the majority (ranging from (88%-94%) reported that they were able to apply the skill more effectively because of ECLS training. Conclusion: JeevaRaksha’s C-ECLS is the world’s first comprehensive training. It improves the confidence of front-line doctors and enables them to provide quality care during the ‘Golden Hour’ of emergency. It also prepares doctors to manage unknown emergencies (e.g., COVID-19). C-ECLS was piloted in Morocco, and Uzbekistan and implemented countrywide in Bhutan. C-ECLS is relevant to most settings and offers a replicable model across LMIC.

Keywords: comprehensive emergency care and life support, training, capacity building, low- and middle-income countries, developing countries

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Authors: Alberto Veses, Olga Sanhauja, María Soledad Callén, Tomás García

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The appropriate use of renewable sources emerges as a decisive point to minimize the environmental impact caused by fossil fuels use. Particularly, the use of lignocellulosic biomass becomes one of the best promising alternatives since it is the only carbon-containing renewable source that can produce bioproducts similar to fossil fuels and it does not compete with food market. Among all the processes that can valorize lignocellulosic biomass, pyrolysis is an attractive alternative because it is the only thermochemical process that can produce a liquid biofuel (bio-oil) in a simple way and solid and gas fractions that can be used as energy sources to support the process. However, in order to incorporate bio-oils in current infrastructures and further process in future biorefineries, their quality needs to be improved. Introducing different low-cost catalysts and/or incorporating different polymer residues to the process are some of the new, simple and low-cost strategies that allow the user to directly obtain advanced bio-oils to be used in future biorefineries in an economic way. In this manner, from previous thermogravimetric analyses, local agricultural wastes such as grape seeds (GS) were selected as lignocellulosic biomass while, waste tires (WT) were selected as polymer residue. On the other hand, CaO was selected as low-cost catalyst based on previous experiences by the group. To reach this aim, a specially-designed fixed bed reactor using N₂ as a carrier gas was used. This reactor has the peculiarity to incorporate a vertical mobile liner that allows the user to introduce the feedstock in the oven once the selected temperature (550 ºC) is reached, ensuring higher heating rates needed for the process. Obtaining a well-defined phase distribution in the resulting bio-oil is crucial to ensure the viability to the process. Thus, once experiments were carried out, not only a well-defined two layers was observed introducing several mixtures (reaching values up to 40 wt.% of WT) but also, an upgraded organic phase, which is the one considered to be processed in further biorefineries. Radical interactions between GS and WT released during the pyrolysis process and dehydration reactions enhanced by CaO can promote the formation of better-quality bio-oils. The latter was reflected in a reduction of water and oxygen content of bio-oil and hence, a substantial increase of its heating value and its stability. Moreover, not only sulphur content was reduced from solely WT pyrolysis but also potential and negative issues related to a strong acidic environment of conventional bio-oils were minimized due to its basic pH and lower total acid numbers. Therefore, acidic compounds obtained in the pyrolysis such as CO₂-like substances can react with the CaO and minimize acidic problems related to lignocellulosic bio-oils. Moreover, this CO₂ capture promotes H₂ production from water gas shift reaction favoring hydrogen-transfer reactions, improving the final quality of the bio-oil. These results show the great potential of grapes seeds to carry out the catalytic co-pyrolysis process with different plastic residues in order to produce a liquid bio-oil that can be considered as a high-quality renewable vector.

Keywords: advanced bio-oils, biorefinery, catalytic co-pyrolysis of biomass and waste tires, lignocellulosic biomass

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Authors: Luiza Melo De Lima, Tito Trindade, Jose M. Oliveira

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The development of thermoplastic-based graphene nanocomposites has been of great interest not only to the scientific community but also to different industrial sectors. Due to the possible improvement of performance and weight reduction, thermoplastic nanocomposites are a great promise as a new class of materials. These nanocomposites are of relevance for the automotive industry, namely because the emission limits of CO2 emissions imposed by the European Commission (EC) regulations can be fulfilled without compromising the car’s performance but by reducing its weight. Thermoplastic polymers have some advantages over thermosetting polymers such as higher productivity, lower density, and recyclability. In the automotive industry, for example, poly(propylene) (PP) is a common thermoplastic polymer, which represents more than half of the polymeric raw material used in automotive parts. Graphene-based materials (GBM) are potential nanofillers that can improve the properties of polymer matrices at very low loading. In comparison to other composites, such as fiber-based composites, weight reduction can positively affect their processing and future applications. However, the properties and performance of GBM/polymer nanocomposites depend on the type of GBM and polymer matrix, the degree of dispersion, and especially the type of interactions between the fillers and the polymer matrix. In order to take advantage of the superior mechanical strength of GBM, strong interfacial strength between GBM and the polymer matrix is required for efficient stress transfer from GBM to the polymer. Thus, chemical compatibilizers and physicochemical modifications have been reported as important tools during the processing of these nanocomposites. In this study, PP-based nanocomposites were obtained by a simple melt blending technique, using a Brabender type mixer machine. Graphene nanoplatelets (GnPs) were applied as structural reinforcement. Two compatibilizers were used to improve the interaction between PP matrix and GnPs: PP graft maleic anhydride (PPgMA) and PPgMA modified with tertiary amine alcohol (PPgDM). The samples for tensile and Charpy impact tests were obtained by injection molding. The results suggested the GnPs presence can increase the mechanical strength of the polymer. However, it was verified that the GnPs presence can promote a decrease of impact resistance, turning the nanocomposites more fragile than neat PP. The compatibilizers’ incorporation increases the impact resistance, suggesting that the compatibilizers can enhance the adhesion between PP and GnPs. Compared to neat PP, Young’s modulus of non-compatibilized nanocomposite increase demonstrated that GnPs incorporation can promote a stiffness improvement of the polymer. This trend can be related to the several physical crosslinking points between the PP matrix and the GnPs. Furthermore, the decrease of strain at a yield of PP/GnPs, together with the enhancement of Young’s modulus, confirms that the GnPs incorporation led to an increase in stiffness but to a decrease in toughness. Moreover, the results demonstrated that incorporation of compatibilizers did not affect Young’s modulus and strain at yield results compared to non-compatibilized nanocomposite. The incorporation of these compatibilizers showed an improvement of nanocomposites’ mechanical properties compared both to those the non-compatibilized nanocomposite and to a PP sample used as reference.

Keywords: graphene nanoplatelets, mechanical properties, melt blending processing, poly(propylene)-based nanocomposites

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Authors: Mohammad M. Khan, Pankaj Agarwal

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The present investigation deals with the microstructures, mechanical and detailed wear characteristics of in situ TiC particles reinforced zinc aluminum-based metal matrix composites. The composites have been synthesized by liquid metallurgy route using vortex technique. The composite was found to be harder than the matrix alloy due to high hardness of the dispersoid particles therein. The former was also lower in ultimate tensile strength and ductility as compared to the matrix alloy. This could be explained to be due to the use of coarser size dispersoid and larger interparticle spacing. Reasonably uniform distribution of the dispersoid phase in the alloy matrix and good interfacial bonding between the dispersoid and matrix was observed. The composite exhibited predominantly brittle mode of fracture with microcracking in the dispersoid phase indicating effective easy transfer of load from matrix to the dispersoid particles. To study the wear behavior of the samples three different types of tests were performed namely: (i) sliding wear tests using a pin on disc machine under dry condition, (ii) high stress (two-body) abrasive wear tests using different combinations of abrasive media and specimen surfaces under the conditions of varying abrasive size, traversal distance and load, and (iii) low-stress (three-body) abrasion tests using a rubber wheel abrasion tester at various loads and traversal distances using different abrasive media. In sliding wear test, significantly lower wear rates were observed in the case of base alloy over that of the composites. This has been attributed to the poor room temperature strength as a result of increased microcracking tendency of the composite over the matrix alloy. Wear surfaces of the composite revealed the presence of fragmented dispersoid particles and microcracking whereas the wear surface of matrix alloy was observed to be smooth with shallow grooves. During high-stress abrasion, the presence of the reinforcement offered increased resistance to the destructive action of the abrasive particles. Microcracking tendency was also enhanced because of the reinforcement in the matrix. The negative effect of the microcracking tendency was predominant by the abrasion resistance of the dispersoid. As a result, the composite attained improved wear resistance than the matrix alloy. The wear rate increased with load and abrasive size due to a larger depth of cut made by the abrasive medium. The wear surfaces revealed fine grooves, and damaged reinforcement particles while subsurface regions revealed limited plastic deformation and microcracking and fracturing of the dispersoid phase. During low-stress abrasion, the composite experienced significantly less wear rate than the matrix alloy irrespective of the test conditions. This could be explained to be due to wear resistance offered by the hard dispersoid phase thereby protecting the softer matrix against the destructive action of the abrasive medium. Abraded surfaces of the composite showed protrusion of dispersoid phase. The subsurface regions of the composites exhibited decohesion of the dispersoid phase along with its microcracking and limited plastic deformation in the vicinity of the abraded surfaces.

Keywords: abrasive wear, liquid metallurgy, metal martix composite, SEM

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Authors: Rajashekar Badam, Vedarajan Raman, Noriyoshi Matsumi

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Efficiency of energy converting and storage systems like fuel cells and Li-Air battery principally depended on oxygen reduction reaction (ORR) which occurs at cathode. As the kinetics of the ORR is very slow, it becomes the rate determining step. Exploring carbon substrates for enhancing the dispersion and activity of the metal catalyst and commercially viable simple preparation method is a very crucial area of research in the field of energy materials. Hence, many researchers made large number of carbon-based ORR materials today. But, there are hardly few studies on the effect of interaction between Pt-carbon and carbon-electrolyte on activity. In this work, we have prepared functionalized carbon-based Pt catalyst (Pt-FAB) with enhanced interfacial properties that lead to efficient ORR catalysis. The present work deals with a single-pot method to exfoliate and functionalized acetylene black with enhanced interaction with Pt as well as electrolyte. Acetylene black was functionalized and exfoliated using a facile single pot acid treatment method. The resulted FAB was further decorated with Pt-nano particles (Pt-np). The TEM images of Pt-FAB with uniformly decorated Pt-np of ~3 nm. Further, XPS studies of Pt 4f peak revealed that Pt0 peak was shifted by 0.4 eV in Pt-FAB compared to binding energy of typical Pt⁰ found in Pt/C. The shift can be ascribed to the modulation of electronic state and strong electronic interaction of Pt with carbon. Modulated electronic structure of Pt and strong electronic interaction of Pt with FAB enhances the catalytic activity and durability respectively. To understand the electrode electrolyte interface, electrochemical impedance spectroscopy was carried out. These measurements revealed that the charge transfer resistance of electrode to electrolyte for Pt-FAB is 10 times smaller than that of conventional Pt/C. The interaction with electrolyte helps reduce the interface boundaries, which in turn affects the overall catalytic performance of the electrode. Cyclic voltammetric measurements in 0.1M HClO₄ aq. at a potential scan rate of 50 mVs-1 was employed to evaluate electrochemical surface area (ECSA) of Pt. ECSA of Pt-FAB was found to be as high as 67.2 m²g⁻¹. The three-electrode system showed very high ORR catalytic activity. Mass activity at 0.9 V vs. RHE showed 460 A/g which is much higher than the DOE target values for the year 2020. Further, it showed enhanced performance by showing 723 mW/cm² of highest power density and 1006 mA/cm² of current density at 0.6 V in fuel cell single cell type configuration and 1030 mAhg⁻¹ of rechargeable capacity in Li air battery application. The higher catalytic activity can be ascribed to the improved interaction of FAB with Pt and electrolyte. The aforementioned results evince that Pt-FAB will be a promising cathode material for efficient ORR with significant cyclability for its application in fuel cells and Li-Air batteries. In conclusion, a disordered material was prepared from AB and was systematically characterized. The extremely high ORR activity and ease of preparation make it competent for replacing commercially available ORR materials.

Keywords: functionalized acetylene black, oxygen reduction reaction, fuel cells, Functionalized battery

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Authors: Anahita Mortazavi Manesh, Mojtaba Bagherzadeh

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Metalloporphyrins are well known to mimic the activity of monooxygenase enzymes. In this regard, metalloporphyrin complexes have been largely employed as valuable biomimetic catalysts, owing to the critical roles they play in oxygen transfer processes in catalytic oxidation reactions. Investigating in this area is based on different strategies to design selective, stable and high turnover catalytic systems. Immobilization of expensive metalloporphyrin catalysts onto supports appears to be a good way to improve their stability, selectivity and the catalytic performance because of the support environment and other advantages with respect to recovery, reuse. In other words, supporting metalloporphyrins provides a physical separation of active sites, thus minimizing catalyst self-destruction and dimerization of unhindered metalloporphyrins. Furthermore, heterogeneous catalytic oxidations have become an important target since their process are used in industry, helping to minimize the problems of industrial waste treatment. Hence, the immobilization of these biomimetic catalysts is much desired. An attractive approach is the preparation of the heterogeneous catalyst involves immobilization of complexes on silica coated magnetic nano-particles. Fe3O4@SiO2 magnetic nanoparticles have been studied extensively due to their superparamagnetism property, large surface area to volume ratio and easy functionalization. Using heterogenized homogeneous catalysts is an attractive option to facile separation of catalyst, simplified product work-up and continuity of catalytic system. Homogeneous catalysts immobilized on magnetic nanoparticles (MNPs) surface occupy a unique position due to combining the advantages of both homogeneous and heterogeneous catalysts. In addition, superparamagnetic nature of MNPs enable very simple separation of the immobilized catalysts from the reaction mixture using an external magnet. In the present work, an efficient heterogeneous catalyst was prepared by immobilizing manganese porphyrin on functionalized magnetic nanoparticles through the amino propyl linkage. The prepared catalyst was characterized by elemental analysis, FT-IR spectroscopy, X-ray powder diffraction, atomic absorption spectroscopy, UV-Vis spectroscopy, and scanning electron microscopy. Application of immobilized metalloporphyrin in the oxidation of various organic substrates was explored using Gas chromatographic (GC) analyses. The results showed that the supported Mn-porphyrin catalyst (Fe3O4@SiO2-NH2@MnPor) is an efficient and reusable catalyst in oxidation reactions. Our catalytic system exhibits high catalytic activity in terms of turnover number (TON) and reaction conditions. Leaching and recycling experiments revealed that nanocatalyst can be recovered several times without loss of activity and magnetic properties. The most important advantage of this heterogenized catalytic system is the simplicity of the catalyst separation in which the catalyst can be separated from the reaction mixture by applying a magnet. Furthermore, the separation and reuse of the magnetic Fe3O4 nanoparticles were very effective and economical.

Keywords: Fe3O4 nanoparticle, immobilized metalloporphyrin, magnetically separable nanocatalyst, oxidation reactions

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Authors: Carin Chuang, Kuan-Chou Chen

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An Enterprise Resource Planning (ERP) system is an integrated information system that supports the seamless integration of all the business processes of a company. Implementing an ERP system can increase efficiencies and decrease the costs while helping improve productivity. Many organizations including large, medium and small-sized companies have already adopted an ERP system for decades. Although ERP system can bring competitive advantages to organizations, the lack of proper training approach in ERP implementation is still a major concern. Organizations understand the importance of ERP training to adequately prepare managers and users. The low return on investment, however, for the ERP training makes the training difficult for knowledgeable workers to transfer what is learned in training to the jobs at workplace. Inadequate and inefficient ERP training limits the value realization and success of an ERP system. That is the need to call for a profound change and innovation for ERP training in both workplace at industry and the Information Systems (IS) education in academia. The innovated ERP training approach can improve the users’ knowledge in business processes and hands-on skills in mastering ERP system. It also can be instructed as educational material for IS students in universities. The purpose of the study is to examine the use of ERP simulation games via the ERPsim system to train the IS students in learning ERP implementation. The ERPsim is the business simulation game developed by ERPsim Lab at HEC Montréal, and the game is a real-life SAP (Systems Applications and Products) ERP system. The training uses the ERPsim system as the tool for the Internet-based simulation games and is designed as online student competitions during the class. The competitions involve student teams with the facilitation of instructor and put the students’ business skills to the test via intensive simulation games on a real-world SAP ERP system. The teams run the full business cycle of a manufacturing company while interacting with suppliers, vendors, and customers through sending and receiving orders, delivering products and completing the entire cash-to-cash cycle. To learn a range of business skills, student needs to adopt individual business role and make business decisions around the products and business processes. Based on the training experiences learned from rounds of business simulations, the findings show that learners have reduced risk in making mistakes that help learners build self-confidence in problem-solving. In addition, the learners’ reflections from their mistakes can speculate the root causes of the problems and further improve the efficiency of the training. ERP instructors teaching with the innovative approach report significant improvements in student evaluation, learner motivation, attendance, engagement as well as increased learner technology competency. The findings of the study can provide ERP instructors with guidelines to create an effective learning environment and can be transferred to a variety of other educational fields in which trainers are migrating towards a more active learning approach.

Keywords: business simulations, ERP implementation training, ERPsim, game-based learning, instructional strategy, training innovation

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Authors: Hongmei Wang, Ziyun Xiang, Ying liu, Li Yu, Dongsheng Yue

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Intro: The COVID-19 (Corona Virus Disease 2019) has greatly changed the global economic, political and financial ecology. The mutation of the coronavirus in the UK in December 2020 has brought new panic to the world. Deep learning was performed on Chest Computed tomography (CT) of COVID-19 and Influenza and describes their characteristics. The predominant features of COVID-19 pneumonia was ground-glass opacification, followed by consolidation. Lesion density: most lesions appear as ground-glass shadows, and some lesions coexist with solid lesions. Lesion distribution: the focus is mainly on the dorsal side of the periphery of the lung, with the lower lobe of the lungs as the focus, and it is often close to the pleura. Other features it has are grid-like shadows in ground glass lesions, thickening signs of diseased vessels, air bronchi signs and halo signs. The severe disease involves whole bilateral lungs, showing white lung signs, air bronchograms can be seen, and there can be a small amount of pleural effusion in the bilateral chest cavity. At the same time, this year's flu season could be near its peak after surging throughout the United States for months. Chest CT for Influenza infection is characterized by focal ground glass shadows in the lungs, with or without patchy consolidation, and bronchiole air bronchograms are visible in the concentration. There are patchy ground-glass shadows, consolidation, air bronchus signs, mosaic lung perfusion, etc. The lesions are mostly fused, which is prominent near the hilar and two lungs. Grid-like shadows and small patchy ground-glass shadows are visible. Deep neural networks have great potential in image analysis and diagnosis that traditional machine learning algorithms do not. Method: Aiming at the two major infectious diseases COVID-19 and influenza, which are currently circulating in the world, the chest CT of patients with two infectious diseases is classified and diagnosed using deep learning algorithms. The residual network is proposed to solve the problem of network degradation when there are too many hidden layers in a deep neural network (DNN). The proposed deep residual system (ResNet) is a milestone in the history of the Convolutional neural network (CNN) images, which solves the problem of difficult training of deep CNN models. Many visual tasks can get excellent results through fine-tuning ResNet. The pre-trained convolutional neural network ResNet is introduced as a feature extractor, eliminating the need to design complex models and time-consuming training. Fastai is based on Pytorch, packaging best practices for in-depth learning strategies, and finding the best way to handle diagnoses issues. Based on the one-cycle approach of the Fastai algorithm, the classification diagnosis of lung CT for two infectious diseases is realized, and a higher recognition rate is obtained. Results: A deep learning model was developed to efficiently identify the differences between COVID-19 and influenza using chest CT.

Keywords: COVID-19, Fastai, influenza, transfer network

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Authors: Aditya Purohit, Neha Bansal

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Unplanned urbanization and multidirectional sprawl of the cities have resulted in increased motorization and deteriorating transport conditions like traffic congestion, longer commuting, pollution, increased carbon footprint, and above all increased fatalities. In order to overcome these problems, various practices have been adopted including– promoting and implementing mass transport; traffic junction channelization; smart transport etc. However, these methods are found to be primarily focusing on vehicular mobility rather than people accessibility. With this research gap, this paper tries to resolve the mobility issues for Ahmedabad city in India, which being the economic capital Gujarat state has a huge commuter and visitor inflow. This research aims to resolve the traffic congestion and urban mobility issues focusing on Gujarat State Regional Transport Corporation (GSRTC) for the city of Ahmadabad by analyzing the existing operations and network structure of GSRTC followed by finding possibilities of integrating it with other modes of urban transport. The network restructuring (NR) methodology is used with appropriate variations, based on commuter demand and growth pattern of the city. To do these ‘scenarios’ based on priority issues (using 12 parameters) and their best possible solution, are established after route network analysis for 2700 population sample of 20 traffic junctions/nodes across the city. Approximately 5% sample (of passenger inflow) at each node is considered using random stratified sampling technique two scenarios are – Scenario 1: Resolving mobility issues by use of Special Purpose Vehicle (SPV) in joint venture to GSRTC and Private Operators for establishing feeder service, which shall provide a transfer service for passenger for movement from inner city area to identified peripheral terminals; and Scenario 2: Augmenting existing mass transport services such as BRTS and AMTS for using them as feeder service to the identified peripheral terminals. Each of these has now been analyzed for the best suitability/feasibility in network restructuring. A desire-line diagram is constructed using this analysis which indicated that on an average 62% of designated GSRTC routes are overlapping with mass transportation service routes of BRTS and AMTS in the city. This has resulted in duplication of bus services causing traffic congestion especially in the Central Bus Station (CBS). Terminating GSRTC services on the periphery of the city is found to be the best restructuring network proposal. This limits the GSRTC buses at city fringe area and prevents them from entering into the city core areas. These end-terminals of GSRTC are integrated with BRTS and AMTS services which help in segregating intra-state and inter-state bus services. The research concludes that absence of integrated multimodal transport network resulted in complexity of transport access to the commuters. As a further scope of research comparing and understanding of value of access time in total travel time and its implication on generalized cost on trip and how it varies city wise may be taken up.

Keywords: mass transportation, multi-modal integration, network restructuring, travel behavior, urban transport

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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: Ahmad Kayvani Fard, Yehia Manawi

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Qatar’s primary source of fresh water is through seawater desalination. Amongst the major processes that are commercially available on the market, the most common large scale techniques are Multi-Stage Flash distillation (MSF), Multi Effect distillation (MED), and Reverse Osmosis (RO). Although commonly used, these three processes are highly expensive down to high energy input requirements and high operating costs allied with maintenance and stress induced on the systems in harsh alkaline media. Beside that cost, environmental footprint of these desalination techniques are significant; from damaging marine eco-system, to huge land use, to discharge of tons of GHG and huge carbon footprint. Other less energy consuming techniques based on membrane separation are being sought to reduce both the carbon footprint and operating costs is membrane distillation (MD). Emerged in 1960s, MD is an alternative technology for water desalination attracting more attention since 1980s. MD process involves the evaporation of a hot feed, typically below boiling point of brine at standard conditions, by creating a water vapor pressure difference across the porous, hydrophobic membrane. Main advantages of MD compared to other commercially available technologies (MSF and MED) and specially RO are reduction of membrane and module stress due to absence of trans-membrane pressure, less impact of contaminant fouling on distillate due to transfer of only water vapor, utilization of low grade or waste heat from oil and gas industries to heat up the feed up to required temperature difference across the membrane, superior water quality, and relatively lower capital and operating cost. To achieve the objective of this study, state of the art flat-sheet cross-flow DCMD bench scale unit was designed, commissioned, and tested. The objective of this study is to analyze the characteristics and morphology of the membrane suitable for DCMD through SEM imaging and contact angle measurement and to study the water quality of distillate produced by DCMD bench scale unit. Comparison with available literature data is undertaken where appropriate and laboratory data is used to compare a DCMD distillate quality with that of other desalination techniques and standards. Membrane SEM analysis showed that the PTFE membrane used for the study has contact angle of 127º with highly porous surface supported with less porous and bigger pore size PP membrane. Study on the effect of feed solution (salinity) and temperature on water quality of distillate produced from ICP and IC analysis showed that with any salinity and different feed temperature (up to 70ºC) the electric conductivity of distillate is less than 5 μS/cm with 99.99% salt rejection and proved to be feasible and effective process capable of consistently producing high quality distillate from very high feed salinity solution (i.e. 100000 mg/L TDS) even with substantial quality difference compared to other desalination methods such as RO and MSF.

Keywords: membrane distillation, waste heat, seawater desalination, membrane, freshwater, direct contact membrane distillation

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Authors: Rafat Fazeli, Reza Fazeli

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This paper focuses on the study of the welfare state and social wage in the leading liberal economy of the United States. The welfare state acquired a broad acceptance as a major socioeconomic achievement of the liberal democracy in the Western industrialized countries during the postwar boom period. The modern and modified vision of capitalist democracy offered, on the one hand, the possibility of high growth rate and, on the other hand, the possibility of continued progression of a comprehensive system of social support for a wider population. The economic crises of the 1970s, provided the ground for a great shift in economic policy and ideology in several Western countries, most notably the United States and the United Kingdom (and to a lesser extent Canada under Prime Minister Brian Mulroney). In the 1980s, the free market oriented reforms undertaken under Reagan and Thatcher greatly affected the economic outlook not only of the United States and the United Kingdom, but of the whole Western world. The movement which was behind this shift in policy is often called neo-conservatism. The neoconservatives blamed the transfer programs for the decline in economic performance during the 1970s and argued that cuts in spending were required to go back to the golden age of full employment. The agenda for both Reagan and Thatcher administrations was rolling back the welfare state, and their budgets included a wide range of cuts for social programs. The question is how successful were Reagan and Thatcher’s efforts to achieve retrenchment? The paper involves an empirical study concerning the distributive role of the welfare state in the two countries. Other studies have often concentrated on the redistributive effect of fiscal policy on different income brackets. This study examines the net benefit/ burden position of the working population with respect to state expenditures and taxes in the postwar period. This measurement will enable us to find out whether the working population has received a net gain (or net social wage). This study will discuss how the expansion of social expenditures and the trend of the ‘net social wage’ can be linked to distinct forms of economic and social organizations. This study provides an empirical foundation for analyzing the growing significance of ‘social wage’ or the collectivization of consumption and the share of social or collective consumption in total consumption of the working population in the recent decades. The paper addresses three other major questions. The first question is whether the expansion of social expenditures has posed any drag on capital accumulation and economic growth. The findings of this study provide an analytical foundation to evaluate the neoconservative claim that the welfare state is itself the source of economic stagnation that leads to the crisis of the welfare state. The second question is whether the increasing ideological challenges from the right and the competitive pressures of globalization have led to retrenchment of the American welfare states in the recent decades. The third question is how social policies have performed in the presence of the rising inequalities in the recent decades.

Keywords: the welfare state, social wage, The United States, limits to growth

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Authors: Golson Mohamed, Yasmine Gamasy, Khaled EL-Khatib, Anas Al-Natour, Shady Fadel, Haytham Rashwan, Haytham Badawy, Nadia Farghaly

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Introduction: Wilm's tumor is the most common malignant renal tumor in children. Much progress has been made in the management of patients with this malignancy over the last 3 decades. Today treatments are based on several trials and studies conducted by the International Society of Pediatric Oncology (SIOP) in Europe and National Wilm's Tumor Study Group (NWTS) in the USA. It is necessary for us to understand why do we follow either of the protocols, NWTS which follows the upfront surgery principle or the SIOP which follows the upfront chemotherapy principle in all stages of the disease. Objective: The aim of is to assess outcome in patients treated with preoperative chemotherapy and patients treated with upfront surgery to compare their effect on overall survival. Study design: to decide which protocol to follow, study was carried out on records for patients aged 1 day to 18 years old suffering from Wilm's tumor who were admitted to Alexandria University Hospital, pediatric oncology, pediatric urology and pediatric surgery departments, with a retrospective survey records from 2010 to 2015, Design and editing of the transfer sheet with a (PRISMA flow study) Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Data were fed to the computer and analyzed using IBM SPSS software package version 20.0. (11) Qualitative data were described using number and percent. Quantitative data were described using Range (minimum and maximum), mean, standard deviation and median. Comparison between different groups regarding categorical variables was tested using Chi-square test. When more than 20% of the cells have expected count less than 5, correction for chi-square was conducted using Fisher’s Exact test or Monte Carlo correction. The distributions of quantitative variables were tested for normality using Kolmogorov-Smirnov test, Shapiro-Wilk test, and D'Agstino test, if it reveals normal data distribution, parametric tests were applied. If the data were abnormally distributed, non-parametric tests were used. For normally distributed data, a comparison between two independent populations was done using independent t-test. For abnormally distributed data, comparison between two independent populations was done using Mann-Whitney test. Significance of the obtained results was judged at the 5% level. Results: A significantly statistical difference was observed for survival between the two studied groups favoring the upfront chemotherapy(86.4%)as compared to the upfront surgery group (59.3%) where P=0.009. As regard complication, 20 cases (74.1%) out of 27 were complicated in the group of patients treated with upfront surgery. Meanwhile, 30 cases (68.2%) out of 44 had complications in patients treated with upfront chemotherapy. Also, the incidence of intraoperative complication (rupture) was less in upfront chemotherapy group as compared to upfront surgery group. Conclusion: Upfront chemotherapy has superiority over upfront surgery.As the patient who started with upfront chemotherapy shown, higher survival rate, less percent in complication, less percent needed for radiotherapy, and less rate in recurrence.

Keywords: Wilm's tumor, renal tumor, chemotherapy, surgery

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Authors: Huda Abdelrhman Osman Ahmed, Paul Feyi Waboso

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Introduction: Placenta accreta spectrum (PAS) disorders present a significant challenge in obstetric management due to the high risk of hemorrhage and potential complications at delivery. This case describes a 27+3 weeks gestation in a patient with placenta accreta managed with classical cesarean section and peripartum hysterectomy. Case Description: AGravida 4P3 patient presented at 27+3 weeks gestation with painless, unprovoked vaginal bleeding and an estimated blood loss (EBL) of 300 mL. At the 20+5 week anomaly scan, a placenta previa was identified anterior, covering the os anterior uterus and containing lacunae with signs of myometrial thinning. At a 24+1 week scan conducted at a tertiary center, further imaging indicated placenta increta with invasion into the myometrium and potential areas of placenta percreta. The patient’s past obstetric history included three previous cesarean sections, with no significant medical or surgical history. Social history revealed heavy smoking but no alcohol use. No drug allergies were reported. Given the risks associated with PAS, a management plan was formulated, including an MRI at a later stage and cesarean delivery with a possible hysterectomy between 34-36 weeks. However, at 27+3 weeks, the patient experienced another episode of vaginal bleeding EBL 500 ml, necessitating immediate intervention. Management: As the patient was unstable, she was not transferred to the tertiary center. Completed and informed consent was obtained. MDT planning-group and cross-matching 4 units, uterotonics. Tranexamic acid blood products, cryo, cell salvage, 2 obstetric consultants and an anesthetic consultant, blood bank aware and hematologist. HDU bed and ITU availability. This study assisted in performing a classical Caesarean section, Where the urologist inserted JJ ureteric stents. Following this, we also assisted in a total abdominal hysterectomy with the conservation of ovaries. 4 units RBC and 1 unit FFP were transfused. The total blood loss was 2.3 L. Outcome: The procedure successfully achieved hemostasis, and the neonate was delivered with subsequent transfer to a neonatal intensive care unit for management. The patient’s postoperative course was monitored closely with no immediate complications. Discussion: This case highlights the complexity and urgency in managing placenta accreta spectrum disorders, particularly with the added challenges posed by remote location and limited tertiary support. The need for rapid decision-making and interdisciplinary coordination is emphasized in such high-risk obstetric cases. The case also underscores the potential for surgical intervention and the importance of family involvement in emergent care decisions. Conclusion: Placenta accreta spectrum disorders demand meticulous planning and timely intervention. This case contributes to understanding PAS management at earlier gestational ages and provides insights into the challenges posed by access to tertiary care, especially in urgent situations.

Keywords: Accreta, Hysterectomy, 3MDT, prematurity

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Authors: Zografou Konstantina, Anagnostellis Konstantinos, Brokaki Marina, Kaltsouni Eleftheria, Dimaki Maria, Kati Vassiliki

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Body size is crucial to ecology, influencing everything from individual reproductive success to the dynamics of communities and ecosystems. Understanding how temperature affects variations in body size is vital for both theoretical and practical purposes, as changes in size can modify trophic interactions by altering predator-prey size ratios and changing the distribution and transfer of biomass, which ultimately impacts food web stability and ecosystem functioning. Notably, a decrease in body size is frequently mentioned as the third "universal" response to climate warming, alongside shifts in distribution and changes in phenology. This trend is backed by ecological theories like the temperature-size rule (TSR) and Bergmann's rule, which have been observed in numerous species, indicating that many species are likely to shrink in size as temperatures rise. However, the thermal responses related to body size are still contradictory, and further exploration is needed. To tackle this challenge, we developed the MEIOSIS project, aimed at providing valuable insights into the relationship between the body size of species, species’ traits, environmental factors, and their response to climate change. We combined a digitized collection of butterflies from the Swiss Federal Institute of Technology in Zürich with our newly digitized butterfly collection from Goulandris Natural History Museum in Greece to analyse trends in time. For a total of 23868 images, the length of the right forewing was measured using ImageJ software. Each forewing was measured from the point at which the wing meets the thorax to the apex of the wing. The forewing length of museum specimens has been shown to have a strong correlation with wing surface area and has been utilized in prior studies as a proxy for overall body size. Temperature data corresponding to the years of collection were also incorporated into the datasets. A second dataset was generated when a custom computer vision tool was implemented for the automated morphological measuring of samples for the digitized collection in Zürich. Using the second dataset, we corrected manual measurements with ImageJ, and a final dataset containing 31922 samples was used for analysis. Setting time as a smoother variable, species identity as a random factor, and the length of right-wing size (a proxy for body size) as the response variable, we ran a global model for a maximum period of 110 years (1900 – 2010). Then, we investigated functional variability between different terrestrial biomes in a second model. Both models confirmed our initial hypothesis and resulted in a decreasing trend in body size over the years. We expect that this first output can be provided as basic data for the next challenge, i.e., to identify the ecological traits that influence species' temperature-size responses, enabling us to predict the direction and intensity of a species' reaction to rising temperatures more accurately.

Keywords: butterflies, shrinking body size, museum specimens, climate change

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Authors: Magdalena Orth, Gunnar Gotz

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Background: Domestic accountability, budget transparency and public financial management (PFM) are considered vital components of good governance in developing countries. The aid modality budget support (BS) promotes these governance functions in developing countries. BS engages in political decision-making and provides financial and technical support to poverty reduction strategies of the partner countries. Nevertheless, many donors have withdrawn their support from this modality due to cases of corruption, fraud or human rights violations. This exit from BS is leaving a finance and governance vacuum in the countries. The evaluation team analyzed the consequences of terminating the use of this modality and found particularly negative effects for good governance outcomes. Methodology: The evaluation uses a qualitative (theory-based) approach consisting of a comparative case study design, which is complemented by a process-tracing approach. For the case studies, the team conducted over 100 semi-structured interviews in Malawi, Uganda, Rwanda and Zambia and used four country-specific, tailor-made budget analysis. In combination with a previous DEval evaluation synthesis on the effects of BS, the team was able to create a before-and-after comparison that yields causal effects. Main Findings: In all four countries domestic accountability and budget transparency declined if other forms of pressure are not replacing BS´s mutual accountability mechanisms. In Malawi a fraud scandal created pressure from the society and from donors so that accountability was improved. In the other countries, these pressure mechanisms were absent so that domestic accountability declined. BS enables donors to actively participate in political processes of the partner country as donors transfer funds into the treasury of the partner country and conduct a high-level political dialogue. The results confirm that the exit from BS created a governance vacuum that, if not compensated through external/internal pressure, leads to a deterioration of good governance. For example, in the case of highly aid dependent Malawi did the possibility of a relaunch of BS provide sufficient incentives to push for governance reforms. Overall the results show that the three good governance areas are negatively affected by the exit from BS. This stands in contrast to positive effects found before the exit. The team concludes that the relationship is causal, because the before-and-after comparison coherently shows that the presence of BS correlates with positive effects and the absence with negative effects. Conclusion: These findings strongly suggest that BS is an effective modality to promote governance and its abolishment is likely to cause governance disruptions. Donors and partner governments should find ways to re-engage in closely coordinated policy-based aid modalities. In addition, a coordinated and carefully managed exit-strategy should be in place before an exit from similar modalities is considered. Particularly a continued framework of mutual accountability and a high-level political dialogue should be aspired to maintain pressure and oversight that is required to achieve good governance.

Keywords: budget support, domestic accountability, public financial management and budget transparency, Sub-Sahara Africa

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Authors: Banafsheh Nikmehr, Mohsen Bahrami, Yueqiang Song, Anuradha Koduru, Ayse K. Vuruskan, Hongkun Lu, Mallory Pitts, Tolga B. Mesen, Tamer M. Yalcinkaya

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The number of people who receive in vitro fertilization (IVF) treatment has increased on a startling trajectory over the past two decades. Despite advances in this field, particularly the introduction of intracytoplasmic sperm injection (ICSI) and the preimplantation genetic screening (PGS), the IVF success remains low. A major factor contributing to IVF failure is embryonic aneuploidy (abnormal chromosome content), which often results in miscarriage and birth defects. Although PGS is often used as the standard diagnostic tool to identify aneuploid embryos, it is an invasive approach that could affect the embryo development, and yet inaccessible to many patients due its high costs. As such, there is a clear need for a non-invasive cost-effective approach to identify euploid embryos for single embryo transfer (SET). The reported differences between morphokinetic behaviors of aneuploid and euploid embryos has shown promise to address this need. However, current literature is inconclusive and further research is urgently needed to translate current findings into clinical diagnostics. In this ongoing study, we found significant differences between morphokinetic behaviors of euploid and aneuploid embryos that provides important insights and reaffirms the promise of such behaviors for developing non-invasive methodologies. Methodology—A total of 242 embryos (euploid: 149, aneuploid: 93) from 74 patients who underwent IVF treatment in Carolinas Fertility Clinics in Winston-Salem, NC, were analyzed. All embryos were incubated in an EmbryoScope incubator. The patients were randomly selected from January 2019 to June 2021 with most patients having both euploid and aneuploid embryos. All embryos reached the blastocyst stage and had known PGS outcomes. The ploidy assessment was done by a third-party testing laboratory on day 5-7 embryo biopsies. The morphokinetic variables of each embryo were measured by the EmbryoViewer software (Uniesense FertiliTech) on time-lapse images using 7 focal depths. We compared the time to: pronuclei fading (tPNf), division to 2,3,…,9 cells (t2, t3,…,t9), start of embryo compaction (tSC), Morula formation (tM), start of blastocyst formation (tSC), blastocyst formation (tB), and blastocyst expansion (tEB), as well as intervals between them (e.g., c23 = t3 – t2). We used a mixed regression method for our statistical analyses to account for the correlation between multiple embryos per patient. Major Findings— The average age of the patients was 35.04 yrs. The average patient age associated with euploid and aneuploid embryos was not different (P = 0.6454). We found a significant difference in c45 = t5-t4 (P = 0.0298). Our results indicated this interval on average lasts significantly longer for aneuploid embryos - c45(aneuploid) = 11.93hr vs c45(euploid) = 7.97hr. In a separate analysis limited to embryos from the same patients (patients = 47, total embryos=200, euploid=112, aneuploid=88), we obtained the same results (P = 0.0316). The statistical power for this analysis exceeded 87%. No other variable was different between the two groups. Conclusion— Our results demonstrate the importance of morphokinetic variables as potential biomarkers that could aid in non-invasively characterizing euploid and aneuploid embryos. We seek to study a larger population of embryos and incorporate the embryo quality in future studies.

Keywords: IVF, embryo, euploidy, aneuploidy, morphokinteic

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Authors: Martina Curtin, Rosalind Herman

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Background: Deaf children can experience difficulties with understanding how social interaction works, particularly when communicating with unfamiliar hearing people. Deaf children often struggle with integrating into a mainstream, hearing environments. These negative experiences can lead to social isolation, depression and other mental health difficulties later in life. smiLE Therapy (Schamroth, 2015) is a video-based social communication intervention that aims to teach deaf children skills to confidently communicate with unfamiliar hearing people. Although two previous studies have reported improvements in communication skills immediately post intervention, evidence for maintenance of gains or generalisation of skills (i.e., the transfer of newly learnt skills to untrained situations) has not to date been demonstrated. Parental involvement has been shown to support deaf children’s therapy outcomes. Therefore, this study added parent training to the therapy children received to investigate the benefits to generalisation of children’s skills. Parents were also invited to present their perspective on the training they received. Aims: (1) To assess pupils’ progress from pre- to post-intervention in trained and untrained tasks, (2) to investigate if training parents improved their (a) understanding of their child’s needs and (b) their skills in supporting their child appropriately in smiLE Therapy tasks, (3) to assess if parent training had an impact on the pupil’s ability to (a) maintain their skills in trained tasks post-therapy, and (b) generalise their skills in untrained, community tasks. Methods: This was a mixed-methods, repeated measures study. 31 deaf pupils (aged between 7 and 14) received an hour of smiLE Therapy per week, for 6 weeks. Communication skills were assessed pre-, post- and 3-months post-intervention using the Communication Skills Checklist. Parents were then invited to attend two training sessions and asked to bring a video of their child communicating in a shop or café. These videos were used to assess whether, after parent training, the child was able to generalise their skills to a new situation. Finally, parents attended a focus group to discuss the effectiveness of the therapy, particularly the wider impact, i.e., more child participation within the hearing community. Results: All children significantly improved their scores following smiLE therapy and maintained these skills to high level. Children generalised a high percentage of their newly learnt skills to an untrained situation. Parents reported improved understanding of their child’s needs, their child’s potential and in how to support them in real-life situations. Parents observed that their children were more confident and independent when carrying out communication tasks with unfamiliar hearing people. Parents realised they needed to ‘let go’ and embrace their child’s independence and provide more opportunities for them to participate in their community. Conclusions: This study adds to the evidence base on smiLE Therapy; it is an effective intervention that develops deaf children’s ability to interact competently with unfamiliar, hearing, communication partners. It also provides preliminary evidence of the benefits of parent training in helping children to generalise their skills to other situations. These findings will be of value to therapists wishing to develop deaf children’s communication skills beyond the therapy setting.

Keywords: deaf children, generalisation, parent involvement, social communication

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Authors: Li Jiuen Ong, Magdalin Cheong, Sri Rahayu, Lek Alexander, Pei Ting Tan

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Background: Previous programme evaluations from the diabetes training programme conducted in Changi General Hospital revealed that healthcare professionals (HCPs) are keen to receive advance diabetes training and education, specifically in medical, nutritional therapy. HCPs also expressed a preference for interactive activities over didactic teaching methods to enhance their learning. Since the War on Diabetes was initiated by MOH in 2016, HCPs are challenged to be actively involved in continuous education to be better equipped to reduce the growing burden of diabetes. Hence, streamlining training to incorporate an element of fun is of utmost importance. Aim: The nutrition programme incorporates game play using an interactive board game that aims to provide a more conducive and less stressful environment for learning. The board game could be adapted for training of community HCPs, health ambassadors or caregivers to cope with the increasing demand of diabetes care in the hospital and community setting. Methodology: Stages for game’s conception (Jaffe, 2001) were adopted in the development of the interactive board game ‘Sweet Score™ ’ Nutrition concepts and topics in diabetes self-management are embedded into the game elements of varying levels of difficulty (‘Easy,’ ‘Medium,’ ‘Hard’) including activities such as a) Drawing/ sculpting (Pictionary-like) b)Facts/ Knowledge (MCQs/ True or False) Word definition) c) Performing/ Charades To study the effects of game play on knowledge acquisition and perceived experiences, participants were randomised into two groups, i.e., lecture group (control) and game group (intervention), to test the difference. Results: Participants in both groups (control group, n= 14; intervention group, n= 13) attempted a pre and post workshop quiz to assess the effectiveness of knowledge acquisition. The scores were analysed using paired T-test. There was an improvement of quiz scores after attending the game play (mean difference: 4.3, SD: 2.0, P<0.001) and the lecture (mean difference: 3.4, SD: 2.1, P<0.001). However, there was no significance difference in the improvement of quiz scores between gameplay and lecture (mean difference: 0.9, 95%CI: -0.8 to 2.5, P=0.280). This suggests that gameplay may be as effective as a lecture in terms of knowledge transfer. All the13 HCPs who participated in the game rated 4 out of 5 on the likert scale for the favourable learning experience and relevance of learning to their job, whereas only 8 out of 14 HCPs in the lecture reported a high rating in both aspects. 16. Conclusion: There is no known board game currently designed for diabetes training for HCPs.Evaluative data from future training can provide insights and direction to improve the game format and cover other aspects of diabetes management such as self-care, exercise, medications and insulin management. Further testing of the board game to ensure learning objectives are met is important and can assist in the development of awell-designed digital game as an alternative training approach during the COVID-19 pandemic. Learning through gameplay increases opportunities for HCPs to bond, interact and learn through games in a relaxed social setting and potentially brings more joy to the workplace.

Keywords: active learning, game, diabetes, nutrition

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Authors: Andy Alubaidy

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In this work, a robotic additive manufacturing system (RAMS) that is capable of three-dimensional (3D) printing in six degrees of freedom (DOF) with very high accuracy and virtually on any surface has been designed and built. One of the major shortcomings in existing 3D printer technology is the limitation to three DOF, which results in prolonged fabrication time. Depending on the techniques used, it usually takes at least two hours to print small objects and several hours for larger objects. Another drawback is the size of the printed objects, which is constrained by the physical dimensions of most low-cost 3D printers, which are typically small. In such cases, large objects are produced by dividing them into smaller components that fit the printer’s workable area. They are then glued, bonded or otherwise attached to create the required object. Another shortcoming is material constraints and the need to fabricate a single part using different materials. With the flexibility of a six-DOF robot, the RAMS has been designed to overcome these problems. A feeding mechanism using an adaptive Proportional-Integral-Derivative (PID) controller is utilized along with a national instrument compactRIO (NI cRIO), an ABB robot, and off-the-shelf sensors. The RAMS have the ability to 3D print virtually anywhere in six degrees of freedom with very high accuracy. It is equipped with an ABB IRB 120 robot to achieve this level of accuracy. In order to convert computer-aided design (CAD) files to digital format that is acceptable to the robot, Hypertherm Robotic Software Inc.’s state-of-the-art slicing software called “ADDMAN” is used. ADDMAN is capable of converting any CAD file into RAPID code (the programing language for ABB robots). The robot uses the generated code to perform the 3D printing. To control the entire process, National Instrument (NI) compactRIO (cRio 9074), is connected and communicated with the robot and a feeding mechanism that is designed and fabricated. The feeding mechanism consists of two major parts, cold-end and hot-end. The cold-end consists of what is conventionally known as an extruder. Typically, a stepper-motor is used to control the push on the material, however, for optimum control, a DC motor is used instead. The hot-end consists of a melt-zone, nozzle, and heat-brake. The melt zone ensures a thorough melting effect and consistent output from the nozzle. Nozzles are made of brass for thermo-conductivity while the melt-zone is comprised of a heating block and a ceramic heating cartridge to transfer heat to the block. The heat-brake ensures that there is no heat creep-up effect as this would swell the material and prevent consistent extrusion. A control system embedded in the cRio is developed using NI Labview which utilizes adaptive PID to govern the heating cartridge in conjunction with a thermistor. The thermistor sends temperature feedback to the cRio, which will issue heat increase or decrease based on the system output. Since different materials have different melting points, our system will allow us to adjust the temperature and vary the material.

Keywords: robotic, additive manufacturing, PID controller, cRIO, 3D printing

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Authors: Dominic Sagar

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Manchester ‘King Cotton’, the first truly industrial city of the nineteenth century, passing on the baton to Detroit ‘Motor City’, is the first truly modern city. We are exploring the tales of the two cities, their rise and fall and subsequent post-industrial decline, their transitions and transformations, whilst alongside paralleling their corresponding, commercial, cultural, industrial and even agricultural, artistic and musical transactions and connections. The paper will briefly contextualize how technologies of the industrial age and modern age have been instrumental in the development of these cities and other similar cities including New York. However, the main focus of the study will be the present and more importantly the future, how globalisation and the advancements of digital technologies and industries have shaped the cities developments from AlanTuring and the making of the first programmable computer to the effect of digitalisation and digital initiatives. Manchester now has a thriving creative digital infrastructure of Digilabs, FabLabs, MadLabs and hubs, the study will reference the Smart Project and the Manchester Digital Development Association whilst paralleling similar digital and creative industrial initiatives now starting to happen in Detroit. The paper will explore other topics including the need to allow for zones of experimentation, areas to play, think and create in order develop and instigate new initiatives and ideas of production, carrying on the tradition of influential inventions throughout the history of these key cities. Other topics will be briefly touched on, such as urban farming, citing the Biospheric foundation in Manchester and other similar projects in Detroit. However, the main thread will focus on the music industries and how they are contributing to the regeneration of cities. Musically and artistically, Manchester and Detroit have been closely connected by the flow and transmission of information and transfer of ideas via ‘cars and trains and boats and planes’ through to the new ‘super highway’. From Detroit to Manchester often via New York and Liverpool and back again, these musical and artistic connections and flows have greatly affected and influenced both cities and the advancement of technology are still connecting the cities. In summary two hugely important industrial cities, subsequently both experienced massive decline in fortunes, having had their large industrial hearts ripped out, ravaged leaving dying industrial carcasses and car crashes of despair, dereliction, desolation and post-industrial wastelands vacated by a massive exodus of the cities’ inhabitants. To examine the affinity, similarity and differences between Manchester & Detroit, from their industrial importance to their post-industrial decline and their current transmutations, transformations, transient transgressions, cities in transition; contrasting how they have dealt with these problems and how they can learn from each other. With a view to framing these topics with regard to how various communities have shaped these cities and the creative industries and design [the new cotton/car manufacturing industries] are reinventing post-industrial cities, to speculate on future development of these themes in relation to Globalisation, digitalisation and how cities can function to develop solutions to communal living in cities of the future.

Keywords: cultural capital, digital developments, musical initiatives, zones of experimentation

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Authors: Hanee Ryu

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The former president Lee Myung-bak's administration of Korea presented “green growth” as a catchphrase from 2008. He declared “low-carbon, green growth” the nation's vision for the next decade according to United Nation Framework on Climate Change. The government designed omnidirectional policy for low-carbon and green growth with concentrating all effort of departments. The structural change was expected because this slogan is the identity of the government, which is strongly driven with the whole department. After his administration ends, the purpose of this paper is to quantify the policy effect and to compare with the value of the other OECD countries. The major target values under direct policy objectives were suggested, but it could not capture the entire landscape on which the policy makes changes. This paper figures out the policy impacts through comparing the value of ex-ante between the one of ex-post. Furthermore, each index level of Korea’s low-carbon and green growth comparing with the value of the other OECD countries. To measure the policy effect, indicators international organizations have developed are considered. Environmental Sustainable Index (ESI) and Environmental Performance Index (EPI) have been developed by Yale University’s Center for Environmental Law and Policy and Columbia University’s Center for International Earth Science Information Network in collaboration with the World Economic Forum and Joint Research Center of European Commission. It has been widely used to assess the level of natural resource endowments, pollution level, environmental management efforts and society’s capacity to improve its environmental performance over time. Recently OCED publish the Green Growth Indicator for monitoring progress towards green growth based on internationally comparable data. They build up the conceptual framework and select indicators according to well specified criteria: economic activities, natural asset base, environmental dimension of quality of life and economic opportunities and policy response. It considers the socio-economic context and reflects the characteristic of growth. Some selected indicators are used for measuring the level of changes the green growth policies have induced in this paper. As results, the CO2 productivity and energy productivity show trends of declination. It means that policy intended industry structure shift for achieving carbon emission target affects weakly in the short-term. Increasing green technologies patents might result from the investment of previous period. The increasing of official development aids which can be immediately embarked by political decision with no time lag present only in 2008-2009. It means international collaboration and investment to developing countries via ODA has not succeeded since the initial stage of his administration. The green growth framework makes the public expect structural change, but it shows sporadic effect. It needs organization to manage it in terms of the long-range perspectives. Energy, climate change and green growth are not the issue to be handled in the one period of the administration. The policy mechanism to transfer cost problem to value creation should be developed consistently.

Keywords: comparing ex-ante between ex-post indicator, green growth indicator, implication for green growth policy, measuring policy effect

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Authors: Ali Ateş, Ansar B. Mwimbo, Ali H. Abdulkarim

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General transport equation has a wide range of application in Fluid Mechanics and Heat Transfer problems. In this equation, generally when φ variable which represents a flow property is used to represent fluid velocity component, general transport equation turns into momentum equations or with its well known name Navier-Stokes equations. In these non-linear differential equations instead of seeking for analytic solutions, preferring numerical solutions is a more frequently used procedure. Finite difference method is a commonly used numerical solution method. In these equations using velocity and pressure gradients instead of stress tensors decreases the number of unknowns. Also, continuity equation, by integrating the system, number of equations is obtained as number of unknowns. In this situation, velocity and pressure components emerge as two important parameters. In the solution of differential equation system, velocities and pressures must be solved together. However, in the considered grid system, when pressure and velocity values are jointly solved for the same nodal points some problems confront us. To overcome this problem, using staggered grid system is a referred solution method. For the computerized solutions of the staggered grid system various algorithms were developed. From these, two most commonly used are SIMPLE and SIMPLER algorithms. In this study Navier-Stokes equations were numerically solved for Newtonian flow, whose mass or gravitational forces were neglected, for incompressible and laminar fluid, as a hydro dynamically fully developed region and in two dimensional cartesian coordinate system. Finite difference method was chosen as the solution method. This is a parametric study in which varying values of velocity components, pressure and Reynolds numbers were used. Differential equations were discritized using central difference and hybrid scheme. The discritized equation system was solved by Gauss-Siedel iteration method. SIMPLE and SIMPLER were used as solution algorithms. The obtained results, were compared for central difference and hybrid as discritization methods. Also, as solution algorithm, SIMPLE algorithm and SIMPLER algorithm were compared to each other. As a result, it was observed that hybrid discritization method gave better results over a larger area. Furthermore, as computer solution algorithm, besides some disadvantages, it can be said that SIMPLER algorithm is more practical and gave result in short time. For this study, a code was developed in DELPHI programming language. The values obtained in a computer program were converted into graphs and discussed. During sketching, the quality of the graph was increased by adding intermediate values to the obtained result values using Lagrange interpolation formula. For the solution of the system, number of grid and node was found as an estimated. At the same time, to indicate that the obtained results are satisfactory enough, by doing independent analysis from the grid (GCI analysis) for coarse, medium and fine grid system solution domain was obtained. It was observed that when graphs and program outputs were compared with similar studies highly satisfactory results were achieved.

Keywords: finite difference method, GCI analysis, numerical solution of the Navier-Stokes equations, SIMPLE and SIMPLER algoritms

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Authors: Pedro A. V. Ramos, Duarte M. S. Albuquerque, José C. F. Pereira

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Global warming mitigation is one of the main challenges of this century, having the net balance of greenhouse gas (GHG) emissions to be null or negative in 2050. Industry electrification is one of the main paths to achieving carbon neutrality within the goals of the Paris Agreement. Microwave heating is becoming a popular industrial heating mechanism due to the absence of direct GHG emissions, but also the rapid, volumetric, and efficient heating. In the present study, a mathematical model is used to simulate the production using microwave heating of two ceramic pigments, at high temperatures (above 1200 Celsius degrees). The two pigments studied were the yellow (Pr, Zr)SiO₂ and the brown (Ti, Sb, Cr)O₂. The chemical conversion of reactants into products was included in the model by using the kinetic triplet obtained with the model-fitting method and experimental data present in the Literature. The coupling between the electromagnetic, thermal, and chemical interfaces was also included. The simulations were computed in COMSOL Multiphysics. The geometry includes a moving plunger to allow for the cavity impedance matching and thus maximize the electromagnetic efficiency. To accomplish this goal, a MATLAB controller was developed to automatically search the position of the moving plunger that guarantees the maximum efficiency. The power is automatically and permanently adjusted during the transient simulation to impose stationary regime and total conversion, the two requisites of every converged solution. Both 2D and 3D geometries were used and a parametric study regarding the axial bed velocity and the heat transfer coefficient at the boundaries was performed. Moreover, a Verification and Validation study was carried out by comparing the conversion profiles obtained numerically with the experimental data available in the Literature; the numerical uncertainty was also estimated to attest to the result's reliability. The results show that the model-fitting method employed in this work is a suitable tool to predict the chemical conversion of reactants into the pigment, showing excellent agreement between the numerical results and the experimental data. Moreover, it was demonstrated that higher velocities lead to higher thermal efficiencies and thus lower energy consumption during the process. This work concludes that the electromagnetic heating of materials having high loss tangent and low thermal conductivity, like ceramic materials, maybe a challenge due to the presence of hot spots, which may jeopardize the product quality or even the experimental apparatus. The MATLAB controller increased the electromagnetic efficiency by 25% and global efficiency of 54% was obtained for the titanate brown pigment. This work shows that electromagnetic heating will be a key technology in the decarbonization of the ceramic sector as reductions up to 98% in the specific GHG emissions were obtained when compared to the conventional process. Furthermore, numerical simulations appear as a suitable technique to be used in the design and optimization of microwave applicators, showing high agreement with experimental data.

Keywords: automatic impedance matching, ceramic pigments, efficiency maximization, high-temperature microwave heating, input power control, numerical simulation

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Authors: Dominik Kowitzke

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Housing constructions have direct and indirect environmental impacts especially caused by soil sealing and gray energy consumption related to the use of construction materials. Accordingly, the German government introduced regulations limiting additional annual soil sealing. At the same time, in many regions like metropolitan areas the demand for further housing is high and of current concern in the media and politics. It is argued that meeting this demand by making better use of the existing housing supply is more sustainable than the construction of new housing units. In this context, targeting the phenomenon of so-called over the housing of empty nest households seems worthwhile to investigate for its potential to free living space and thus, reduce the need for new housing constructions and related environmental harm. Over housing occurs if no space adjustment takes place in household lifecycle stages when children move out from home and the space formerly created for the offspring is from then on under-utilized. Although in some cases the housing space consumption might actually meet households’ equilibrium preferences, frequently space-wise adjustments to the living situation doesn’t take place due to transaction or information costs, habit formation, or government intervention leading to increasing costs of relocations like real estate transfer taxes or tenant protection laws keeping tenure rents below the market price. Moreover, many detached houses are not long-term designed in a way that freed up space could be rent out. Findings of this research based on socio-economic survey data, indeed, show a significant difference between the living space of empty nest and a comparison group of households which never had children. The approach used to estimate the average difference in living space is a linear regression model regressing the response variable living space on a two-dimensional categorical variable distinguishing the two groups of household types and further controls. This difference is assumed to be the under-utilized space and is extrapolated to the total amount of empty nests in the population. Supporting this result, it is found that households that move, despite market frictions impairing the relocation, after children left their home tend to decrease the living space. In the next step, only for areas with tight housing markets in Germany and high construction activity, the total under-utilized space in empty nests is estimated. Under the assumption of full substitutability of housing space in empty nests and space in new dwellings in these locations, it is argued that in a perfect market with empty nest households consuming their equilibrium demand quantity of housing space, dwelling constructions in the amount of the excess consumption of living space could be saved. This, on the other hand, would prevent environmental harm quantified in carbon dioxide equivalence units related to average constructions of detached or multi-family houses. This study would thus provide information on the amount of under-utilized space inside dwellings which is missing in public data and further estimates the external effect of over housing in environmental terms.

Keywords: empty nests, environment, Germany, households, over housing

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Authors: Sofia N. Gonçalves, Duarte M. S. Albuquerque, José C. F. Pereira

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The energy transition is spurred by structural changes in energy demand, supply, and prices. Microwave technology was first proposed as a faster alternative for cooking food. It was found that food heated instantly when interacting with high-frequency electromagnetic waves. The dielectric properties account for a material’s ability to absorb electromagnetic energy and dissipate this energy in the form of heat. Many energy-intense industries could benefit from electromagnetic heating since many of the raw materials are dielectric at high temperatures. Limestone sedimentary rock is a dielectric material intensively used in the cement industry to produce unslaked lime. A numerical 3D model was implemented in COMSOL Multiphysics to study the limestone continuous processing under microwave heating. The model solves the two-way coupling between the Energy equation and Maxwell’s equations as well as the coupling between heat transfer and chemical interfaces. Complementary, a controller was implemented to optimize the overall heating efficiency and control the numerical model stability. This was done by continuously matching the cavity impedance and predicting the required energy for the system, avoiding energy inefficiencies. This controller was developed in MATLAB and successfully fulfilled all these goals. The limestone load influence on thermal decomposition and overall process efficiency was the main object of this study. The procedure considered the Verification and Validation of the chemical kinetics model separately from the coupled model. The chemical model was found to correctly describe the chosen kinetic equation, and the coupled model successfully solved the equations describing the numerical model. The interaction between flow of material and electric field Poynting vector revealed to influence limestone decomposition, as a result from the low dielectric properties of limestone. The numerical model considered this effect and took advantage from this interaction. The model was demonstrated to be highly unstable when solving non-linear temperature distributions. Limestone has a dielectric loss response that increases with temperature and has low thermal conductivity. For this reason, limestone is prone to produce thermal runaway under electromagnetic heating, as well as numerical model instabilities. Five different scenarios were tested by considering a material fill ratio of 30%, 50%, 65%, 80%, and 100%. Simulating the tube rotation for mixing enhancement was proven to be beneficial and crucial for all loads considered. When uniform temperature distribution is accomplished, the electromagnetic field and material interaction is facilitated. The results pointed out the inefficient development of the electric field within the bed for 30% fill ratio. The thermal efficiency showed the propensity to stabilize around 90%for loads higher than 50%. The process accomplished a maximum microwave efficiency of 75% for the 80% fill ratio, sustaining that the tube has an optimal fill of material. Electric field peak detachment was observed for the case with 100% fill ratio, justifying the lower efficiencies compared to 80%. Microwave technology has been demonstrated to be an important ally for the decarbonization of the cement industry.

Keywords: CFD numerical simulations, efficiency optimization, electromagnetic heating, impedance matching, limestone continuous processing

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Authors: Yan Zhang

Abstract:

Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

Procedia PDF Downloads 386