Search results for: route optimization

Authors: Mai Ashraf Talaat

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Objectives: The aim of this review article is to assess the success of dental implants in breast cancer patients receiving bisphosphonate therapy and to evaluate the risk of developing bisphosphonate-related osteonecrosis of the jaw following dental implant surgery. Materials and Methods: A thorough search was conducted, with no time or language restriction, using: PubMed, PubMed Central, Web of Science, and ResearchGate electronic databases. Medical Subject Headings (MeSH) terms such as “bisphosphonate”, “dental implant”, “bisphosphonate-related osteonecrosis of the jaw (BRONJ)”, “osteonecrosis”, “breast cancer, MRONJ”, and their related entry terms were used. Eligibility criteria included studies and clinical trials that evaluated the impact of bisphosphonates on dental implants. Conclusion: Breast cancer patients undergoing bisphosphonate therapy may receive dental implants. However, the risk of developing BRONJ and implant failure is high. Risk factors such as the type of BP received, the route of administration, and the length of treatment prior to surgery should be considered. More randomized controlled trials with long-term follow-ups are needed to draw more evidence-based conclusions.

Keywords: dental implants, breast cancer, bisphosphonates, osteonecrosis, bisphosphonate-related osteonecrosis of the jaw

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Authors: Sina Kazemi, Farshid Torabi, Todd Peterson

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Drilling in shale formations is frequently time-consuming, challenging, and fraught with mechanical failures such as stuck pipes or hole packing off when the cutting removal rate is not sufficient to clean the bottom hole. Crossing the heavy oil shale and sand reservoirs with active shale and microfractures is generally associated with severe fluid losses causing a reduction in the rate of the cuttings removal. These circumstances compromise a well’s integrity and result in a lower rate of penetration (ROP). This study presents collective results of field studies and theoretical analysis conducted on data from South Pars and North Dome in an Iran-Qatar offshore field. Solutions to complications related to drilling in shale formations are proposed through systemically analyzing and applying modeling techniques to select field mud logging data. Field data measurements during actual drilling operations indicate that in a shale formation where the return flow of polymer mud was almost lost in the upper dolomite layer, the performance of hole cleaning and ROP progressively change when higher string rotations are initiated. Likewise, it was observed that this effect minimized the force of rotational torque and improved well integrity in the subsequent casing running. Given similar geologic conditions and drilling operations in reservoirs targeting shale as the producing zone like the Bakken formation within the Williston Basin and Lloydminster, Saskatchewan, a drill bench dynamic modeling simulation was used to simulate borehole cleaning efficiency and mud optimization. The results obtained by altering RPM (string revolution per minute) at the same pump rate and optimized mud properties exhibit a positive correlation with field measurements. The field investigation and developed model in this report show that increasing the speed of string revolution as far as geomechanics and drilling bit conditions permit can minimize the risk of mechanically stuck pipes while reaching a higher than expected ROP in shale formations. Data obtained from modeling and field data analysis, optimized drilling parameters, and hole cleaning procedures are suggested for minimizing the risk of a hole packing off and enhancing well integrity in shale reservoirs. Whereas optimization of ROP at a lower pump rate maintains the wellbore stability, it saves time for the operator while reducing carbon emissions and fatigue of mud motors and power supply engines.

Keywords: ROP, circulating density, drilling parameters, return flow, shale reservoir, well integrity

Procedia PDF Downloads 86

Authors: Megha Rao, Søren H. Jensen, Xiufu Sun, Anke Hagen, Mogens B. Mogensen

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Solid oxide electrolysis cells have an immense potential in converting CO₂ and H₂O into syngas during co-electrolysis operation. The produced syngas can be further converted into hydrocarbons. This kind of technology is called power-to-gas or power-to-liquid. To produce hydrocarbons via this route, durability of the cells is still a challenge, which needs to be further investigated in order to improve the cells. In this work, various nickel-yttria stabilized zirconia (Ni-YSZ) fuel electrode supported or YSZ electrolyte supported cells, cerium gadolinium oxide (CGO) barrier layer, and an oxygen electrode are investigated for durability under co-electrolysis conditions in both galvanostatic and potentiostatic conditions. While changing the gas on the oxygen electrode, keeping the fuel electrode gas composition constant, a change in the gas concentration arc was observed by impedance spectroscopy. Measurements of open circuit potential revealed the presence of leaks in the setup. It is speculated that the change in concentration impedance may be related to the leaks. Furthermore, the cells were also tested under pressurized conditions to find an inter-play between the leak rate and the pressure. A mathematical modeling together with electrochemical and microscopy analysis is presented.

Keywords: co-electrolysis, durability, leaks, gas concentration arc

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Authors: Simiao Ren, En Wei

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Drowning is a significant safety issue worldwide, and a robust computer vision-based alert system can easily prevent such tragedies in swimming pools. However, due to domain shift caused by the visual gap (potentially due to lighting, indoor scene change, pool floor color etc.) between the training swimming pool and the test swimming pool, the robustness of such algorithms has been questionable. The annotation cost for labeling each new swimming pool is too expensive for mass adoption of such a technique. To address this issue, we propose a domain-aware data augmentation pipeline based on Gaussian Poisson Generative Adversarial Network (GP-GAN). Combined with YOLOv8, we demonstrate that such a domain adaptation technique can significantly improve the model performance (from 0.24 mAP to 0.82 mAP) on new test scenes. As the augmentation method only require background imagery from the new domain (no annotation needed), we believe this is a promising, practical route for preventing swimming pool drowning.

Keywords: computer vision, deep learning, YOLOv8, detection, swimming pool, drowning, domain adaptation, generative adversarial network, GAN, GP-GAN

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Authors: A. Clementking, C. Jothi Venkateswaran

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Mathematical and computational functionalities such as descriptive mining, optimization, and predictions are espoused to resolve natural resource planning. The water quality prediction and its attributes influence determinations are adopted optimization techniques. The water properties are tainted while merging water resource one with another. This work aimed to predict influencing water resource distribution connectivity in accordance to water quality and sediment using an innovative proposed master-slave neural network back-propagation model. The experiment results are arrived through collecting water quality attributes, computation of water quality index, design and development of neural network model to determine water quality and sediment, master–slave back propagation neural network back-propagation model to determine variations on water quality and sediment attributes between the water resources and the recommendation for connectivity. The homogeneous and parallel biochemical reactions are influences water quality and sediment while distributing water from one location to another. Therefore, an innovative master-slave neural network model [M (9:9:2)::S(9:9:2)] designed and developed to predict the attribute variations. The result of training dataset given as an input to master model and its maximum weights are assigned as an input to the slave model to predict the water quality. The developed master-slave model is predicted physicochemical attributes weight variations for 85 % to 90% of water quality as a target values.The sediment level variations also predicated from 0.01 to 0.05% of each water quality percentage. The model produced the significant variations on physiochemical attribute weights. According to the predicated experimental weight variation on training data set, effective recommendations are made to connect different resources.

Keywords: master-slave back propagation neural network model(MSBPNNM), water quality analysis, multivariate analysis, environmental mining

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Authors: Eyob Messele Sefene, Atinkut Atinafu Yilma

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The highest strength-to-weight ratio criterion has fascinated increasing curiosity in virtually all areas where weight reduction is indispensable. One of the recent advances in manufacturing to achieve this intention endears friction stir welding (FSW). The process is widely used for joining similar and dissimilar non-ferrous materials. In FSW, the mechanical properties of the weld joints are impelled by property-selected process parameters. This paper presents verdicts of optimum process parameters in attempting to attain enhanced mechanical properties of the weld joint. The experiment was conducted on a 5 mm 6061 aluminum alloy sheet. A butt joint configuration was employed. Process parameters, rotational speed, traverse speed or feed rate, axial force, dwell time, tool material and tool profiles were utilized. Process parameters were also optimized, making use of a mixed L18 orthogonal array and the Grey relation analysis method with larger is better quality characteristics. The mechanical properties of the weld joint are examined through the tensile test, hardness test and liquid penetrant test at ambient temperature. ANOVA was conducted in order to investigate the significant process parameters. This research shows that dwell time, rotational speed, tool shape, and traverse speed have become significant, with a joint efficiency of about 82.58%. Nine confirmatory tests are conducted, and the results indicate that the average values of the grey relational grade fall within the 99% confidence interval. Hence the experiment is proven reliable.

Keywords: friction stir welding, optimization, 6061 AA, Taguchi

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Authors: Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević, Lidija R. Jevrić

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Prion is a protein substance whose certain form is considered as infectious agent. It is presumed to be the cause of the transmissible spongiform encephalopathies (TSEs). The protein it is composed of, called PrP, can fold in structurally distinct ways. At least one of those 3D structures is transmissible to other prion proteins. Prions can be found in brain tissue of healthy people and have certain biological role. The structure of prions naturally occurring in healthy organisms is marked as PrPc, and the structure of infectious prion is labeled as PrPSc. PrPc may play a role in synaptic plasticity and neuronal development. Also, it may be required for neuronal myelin sheath maintenance, including a role in iron uptake and iron homeostasis. PrPSc can be considered as an environmental pollutant. The main aim of this study was to carry out the molecular modeling and calculation of molecular descriptors (lipophilicity, physico-chemical and topological descriptors) of structurally diverse compounds which can be considered as anti-prion agents. Molecular modeling was conducted applying ChemBio3D Ultra version 12.0 software. The obtained 3D models were subjected to energy minimization using molecular mechanics force field method (MM2). The cutoff for structure optimization was set at a gradient of 0.1 kcal/Åmol. The Austin Model 1 (AM-1) was used for full geometry optimization of all structures. The obtained set of molecular descriptors is applied in analysis of similarities and dissimilarities among the tested compounds. This study is an important step in further development of quantitative structure-activity relationship (QSAR) models, which can be used for prediction of anti-prion activity of newly synthesized compounds.

Keywords: chemometrics, molecular modeling, molecular descriptors, prions, QSAR

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Authors: Arunkumar Balamurugan, G. Soundharya Lakshmi, V. Thenmozhi, M. Jegannath, V. R. Sanal Kumar

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Aerodynamics of insects is of topical interest in aeronautical industries due to its wide applications on various types of Micro Air Vehicles (MAVs). Note that the MAVs are having smaller geometric dimensions operate at significantly lower speeds on the order of 10 m/s and their Reynolds numbers range is approximately 1,50,000 or lower. In this paper, numerical study has been carried out to capture the flow physics of a biological inspired Swallowtail Butterfly with fixed wing having twin tail at a flight speed of 10 m/s. Comprehensive numerical simulations have been carried out on swallow butterfly with twin tail flying at a speed of 10 m/s with uniform upper and lower angles of attack in both lateral and longitudinal position for identifying the best wing orientation with better aerodynamic efficiency. Grid system in the computational domain is selected after a detailed grid refinement exercises. Parametric analytical studies have been carried out with different lateral and longitudinal angles of attack for finding the better aerodynamic efficiency at the same flight speed. The results reveal that lift coefficient significantly increases with marginal changes in the longitudinal angle and vice versa. But in the case of drag coefficient the conventional changes have been noticed, viz., drag increases at high longitudinal angles. We observed that the change of twin tail section has a significant impact on the formation of vortices and aerodynamic efficiency of the MAV’s. We concluded that for every lateral angle there is an exact longitudinal orientation for the existence of an aerodynamically efficient flying condition of any MAV. This numerical study is a pointer towards for the design optimization of Twin tail MAVs with flapping wings.

Keywords: aerodynamics of insects, MAV, swallowtail butterfly, twin tail MAV design

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Authors: Jamshid Hussain, Kuen Song Lin

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For prospective applications, chemists and materials scientists are particularly interested in creating 3D-micro/nanocomposite structures with shapes and unique characteristics. Ceria has recently been produced with a variety of morphologies, including one-dimensional structures (nanoparticles, nanorods, nanowires, and nanotubes). It is anticipated that this material can be used in different fields, such as catalysis, methanol decomposition, carbon monoxide oxidation, optical materials, and environmental protection. Distinct three-dimensional hydrated ceria-BTC (CeO₂-1,3,5-Benzenetricarboxylic-acid) microstructures were successfully synthesized via a hydrothermal route in an aqueous solution. FE-SEM and XRD patterns reveal that a ceria-BTC framework diameter and length are approximately 1.45–2.4 and 5.5–6.5 µm, respectively, at 130 oC and with pH 2 for 72 h. It was demonstrated that the reaction conditions affected the 3D ceria-BTC architecture. The hexagonal ceria-BTC microrod comprises organic linkers, which are transformed into hierarchical ceria microrod in the presences of air at 400 oC was confirmed by Fourier transform infrared spectroscopy. The Ce-O bonding of the hierarchical ceria microrod (HCMs) species has a bond distance and coordination number of 2.44 and 6.89, respectively, which attenuates the EXAFS spectra. Compared to the ceria powder, the HCMs produced more oxygen vacancies and Ce3+ as shown by the XPS and XANES/EXAFS analyses.

Keywords: hierarchical ceria microrod, three-dimensional ceria, methanol decomposition, reaction mechanism, XANES/EXAFS

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Authors: Emma Whewell, Lee Waters, Mark Wall

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This paper is a mixed methods investigation into the perceived barriers to attainment and progression. Initially entry level data was analysed to identify some of the key characteristics of the student cohort- for example entry route, age and ethnic background. Secondly, a phenomenological case study of the lived experiences of 15 level 5 sport and exercise students was conducted. It aimed to understand the complexities of success in higher education, far beyond entry qualifications, indices of deprivation and POLAR characteristics, to offer a first-hand account of student perceptions and interpretations of the barriers they face in progression, retention and completion on their programme. Using focus groups and interviews with students from a range of indices we offer a set of rich case studies exploring the interpretations of our students’ lived experiences and challenges. Findings demonstrate a complex set of circumstances that centre on managing workload, use of support services and aspirations of students that conflict with university priorities. Conclusions centre on the role of academic and pastoral support, assumptions about priorities of students and practical interventions to support achievement.

Keywords: access and participation, higher education, progression and retention, barriers

Procedia PDF Downloads 109

Authors: S. Hatamikia, A. Biguri, H. Furtado, G. Kronreif, J. Kettenbach, W. Birkfellner

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Nowadays, three dimensional Cone Beam CT (CBCT) has turned into a widespread clinical routine imaging modality for interventional radiology. In conventional CBCT, a circular sourcedetector trajectory is used to acquire a high number of 2D projections in order to reconstruct a 3D volume. However, the accumulated radiation dose due to the repetitive use of CBCT needed for the intraoperative procedure as well as daily pretreatment patient alignment for radiotherapy has become a concern. It is of great importance for both health care providers and patients to decrease the amount of radiation dose required for these interventional images. Thus, it is desirable to find some optimized source-detector trajectories with the reduced number of projections which could therefore lead to dose reduction. In this study we investigate some source-detector trajectories with the optimal arbitrary orientation in the way to maximize performance of the reconstructed image at particular regions of interest. To achieve this approach, we developed a box phantom consisting several small target polytetrafluoroethylene spheres at regular distances through the entire phantom. Each of these spheres serves as a target inside a particular region of interest. We use the 3D Point Spread Function (PSF) as a measure to evaluate the performance of the reconstructed image. We measured the spatial variance in terms of Full-Width-Half-Maximum (FWHM) of the local PSFs each related to a particular target. The lower value of FWHM shows the better spatial resolution of reconstruction results at the target area. One important feature of interventional radiology is that we have very well-known imaging targets as a prior knowledge of patient anatomy (e.g. preoperative CT) is usually available for interventional imaging. Therefore, we use a CT scan from the box phantom as the prior knowledge and consider that as the digital phantom in our simulations to find the optimal trajectory for a specific target. Based on the simulation phase we have the optimal trajectory which can be then applied on the device in real situation. We consider a Philips Allura FD20 Xper C-arm geometry to perform the simulations and real data acquisition. Our experimental results based on both simulation and real data show our proposed optimization scheme has the capacity to find optimized trajectories with minimal number of projections in order to localize the targets. Our results show the proposed optimized trajectories are able to localize the targets as good as a standard circular trajectory while using just 1/3 number of projections. Conclusion: We demonstrate that applying a minimal dedicated set of projections with optimized orientations is sufficient to localize targets, may minimize radiation.

Keywords: CBCT, C-arm, reconstruction, trajectory optimization

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Authors: A. Ballard

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The ability to track goods and products en route in the delivery system, in the warehouse, and on the top floor is a huge advantage to shippers and retailers. Recently the emergence of radio frequency identification (RFID) technology has enabled this better than ever before. However, a significant problem exists in that RFID technology depends on the quality of the information stored for each tagged product. Because of the profusion of names for colours, it is very difficult to ascertain that stored values are recognised by all users who view the product visually. This paper reports the findings of a study in which 50 consumers and 50 logistics workers were shown colour swatches and asked to choose the name of the colour from a multiple choice list. They were then asked to match consumer products, including toasters, jumpers, and toothbrushes, with the identifying inventory information available for each one. The findings show that the ability to match colours was significantly stronger with the color swatches than with the consumer products and that while logistics professionals made more frequent correct identification than the consumers, their results were still unsatisfactorily low. Based on these findings, a proposed universal model of colour identification numbers has been developed.

Keywords: consumer preferences, supply chain logistics, radio frequency identification, RFID, colour preference

Procedia PDF Downloads 121

Authors: D. López-Mancilla, J. M. Roblero-Villa

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Since 1990, the research on chaotic dynamics has received considerable attention, particularly in light of potential applications of this phenomenon in secure communications. Data encryption using chaotic systems was reported in the 90's as a new approach for signal encoding that differs from the conventional methods that use numerical algorithms as the encryption key. The algorithms for image encryption have received a lot of attention because of the need to find security on image transmission in real time over the internet and wireless networks. Known algorithms for image encryption, like the standard of data encryption (DES), have the drawback of low level of efficiency when the image is large. The encrypting based on chaos proposes a new and efficient way to get a fast and highly secure image encryption. In this work, a user interface for image encryption and a novel and easiest way to encrypt images using chaos are presented. The main idea is to reshape any image into a n-dimensional vector and combine it with vector extracted from a chaotic system, in such a way that the vector image can be hidden within the chaotic vector. Once this is done, an array is formed with the original dimensions of the image and turns again. An analysis of the security of encryption from the images using statistical analysis is made and is used a stage of optimization for image encryption security and, at the same time, the image can be accurately recovered. The user interface uses the algorithms designed for the encryption of images, allowing you to read an image from the hard drive or another external device. The user interface, encrypt the image allowing three modes of encryption. These modes are given by three different chaotic systems that the user can choose. Once encrypted image, is possible to observe the safety analysis and save it on the hard disk. The main results of this study show that this simple method of encryption, using the optimization stage, allows an encryption security, competitive with complicated encryption methods used in other works. In addition, the user interface allows encrypting image with chaos, and to submit it through any public communication channel, including internet.

Keywords: image encryption, chaos, secure communications, user interface

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Authors: S. Gowri, K. Narayanasamy, R. Krishnamurthy

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Plasma spraying, from the point of value engineering, is considered as a cost-effective technique to deposit high performance ceramic coatings on ferrous substrates for use in the aero,automobile,electronics and semiconductor industries. High-performance ceramics such as Alumina, Zirconia, and titania-based ceramics have become a key part of turbine blades,automotive cylinder liners,microelectronic and semiconductor components due to their ability to insulate and distribute heat. However, as the industries continue to advance, improved methods are needed to increase both the flexibility and speed of ceramic processing in these applications. The ceramics mentioned were individually coated on structural steel substrate with NiCr bond coat of 50-70 micron thickness with the final thickness in the range of 150 to 200 microns. Optimal spray parameters were selected based on bond strength and porosity. The 'optimal' processed specimens were super finished by lapping using diamond and green SiC abrasives. Interesting results could be observed as follows: The green SiC could improve the surface finish of lapped surfaces almost as that by diamond in case of alumina and titania based ceramics but the diamond abrasives could improve the surface finish of PSZ better than that by green SiC. The conventional random scratches could be absent in alumina and titania ceramics but in PS those marks were found to be less. However, the flatness accuracy could be improved unto 60 to 85%. The surface finish and geometrical accuracy were measured and modeled. The abrasives in the midrange of their particle size could improve the surface quality faster and better than the particles of size in low and high ranges. From the experimental investigations after lapping process, the optimal lapping time, abrasive size, lapping pressure etc could be evaluated.

Keywords: atmospheric plasma spraying, ceramics, lapping, surface qulaity, optimization

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Authors: Tolulope Aremu

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The key process steps to produce liquid detergent products will introduce potential defects, such as formulation, mixing, filling, and packaging, which might compromise product quality, consumer safety, and operational efficiency. Real-time identification and characterization of such defects are of prime importance for maintaining high standards and reducing waste and costs. Usually, defect detection is performed by human inspection or rule-based systems, which is very time-consuming, inconsistent, and error-prone. The present study overcomes these limitations in dealing with optimization in defect characterization within the process for making liquid detergents using Machine Learning algorithms. Performance testing of various machine learning models was carried out: Support Vector Machine, Decision Trees, Random Forest, and Convolutional Neural Network on defect detection and classification of those defects like wrong viscosity, color deviations, improper filling of a bottle, packaging anomalies. These algorithms have significantly benefited from a variety of optimization techniques, including hyperparameter tuning and ensemble learning, in order to greatly improve detection accuracy while minimizing false positives. Equipped with a rich dataset of defect types and production parameters consisting of more than 100,000 samples, our study further includes information from real-time sensor data, imaging technologies, and historic production records. The results are that optimized machine learning models significantly improve defect detection compared to traditional methods. Take, for instance, the CNNs, which run at 98% and 96% accuracy in detecting packaging anomaly detection and bottle filling inconsistency, respectively, by fine-tuning the model with real-time imaging data, through which there was a reduction in false positives of about 30%. The optimized SVM model on detecting formulation defects gave 94% in viscosity variation detection and color variation. These values of performance metrics correspond to a giant leap in defect detection accuracy compared to the usual 80% level achieved up to now by rule-based systems. Moreover, this optimization with models can hasten defect characterization, allowing for detection time to be below 15 seconds from an average of 3 minutes using manual inspections with real-time processing of data. With this, the reduction in time will be combined with a 25% reduction in production downtime because of proactive defect identification, which can save millions annually in recall and rework costs. Integrating real-time machine learning-driven monitoring drives predictive maintenance and corrective measures for a 20% improvement in overall production efficiency. Therefore, the optimization of machine learning algorithms in defect characterization optimum scalability and efficiency for liquid detergent companies gives improved operational performance to higher levels of product quality. In general, this method could be conducted in several industries within the Fast moving consumer Goods industry, which would lead to an improved quality control process.

Keywords: liquid detergent manufacturing, defect detection, machine learning, support vector machines, convolutional neural networks, defect characterization, predictive maintenance, quality control, fast-moving consumer goods

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Authors: Z. Ž. Lazarević, Č. Jovalekić, V. N. Ivanovski, N. Ž. Romčević

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Nickel-zinc ferrite, Ni0.5Zn0.5Fe2O4 was prepared by mechanochemical route in a planetary ball mill starting from mixture of the appropriate quantities of the Ni(OH)2, Zn(OH)2 and Fe(OH)3 hydroxide powders. In order to monitor the progress of chemical reaction and confirm phase formation, powder samples obtained after 5 h and 10 h of milling were characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), IR, Raman and Mössbauer spectroscopy. It is shown that the soft mechanochemical method, i.e. mechanochemical activation of hydroxides, produces high quality single phase Ni0.5Zn0.5Fe2O4 samples in much more efficient way. From the IR spectroscopy of single phase samples it is obvious that energy of modes depends on the ratio of cations. It is obvious that all samples have more than 5 Raman active modes predicted by group theory in the normal spinel structure. Deconvolution of measured spectra allows one to conclude that all complex bands in the spectra are made of individual peaks with the intensities that vary from spectrum to spectrum. The deconvolution of Raman spectra alows to separate contributions of different cations to a particular type of vibration and to estimate the degree of inversion.

Keywords: ferrite, X-ray diffraction, infrared spectroscopy, Raman spectroscopy, Mössbauer spectroscopy

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Authors: Pedro J. Rolim-Neto, Leslie R. M. Ferraz, Fabiana L. A. Santos, Pablo A. Ferreira, Ricardo T. L. Maia-Jr., Magaly A. M. Lyra, Danilo A F. Fonte, Salvana P. M. Costa, Amanda C. Q. M. Vieira, Larissa A. Rolim

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Initially developed as an antimalarial agent, hydroxychloroquine (HCQ) sulfate is often used as a slow-acting antirheumatic drug in the treatment of disorders of connective tissue. The United States Pharmacopeia (USP) 37 provides a reversed-phase HPLC method for quantification of HCQ. However, this method was not reproducible, producing asymmetric peaks in a long analysis time. The asymmetry of the peak may cause an incorrect calculation of the concentration of the sample. Furthermore, the analysis time is unacceptable, especially regarding the routine of a pharmaceutical industry. The aiming of this study was to develop a fast, easy and efficient method for quantification of HCQ sulfate by High Performance Liquid Chromatography (HPLC) based on the Quality by Design (QbD) methodology. This method was optimized in terms of peak symmetry using the surface area graphic as the Design of Experiments (DoE) and the tailing factor (TF) as an indicator to the Design Space (DS). The reference method used was that described at USP 37 to the quantification of the drug. For the optimized method, was proposed a 33 factorial design, based on the QbD concepts. The DS was created with the TF (in a range between 0.98 and 1.2) in order to demonstrate the ideal analytical conditions. Changes were made in the composition of the USP mobile-phase (USP-MP): USP-MP: Methanol (90:10 v/v, 80:20 v/v and 70:30 v/v), in the flow (0.8, 1.0 and 1.2 mL) and in the oven temperature (30, 35, and 40ºC). The USP method allowed the quantification of drug in a long time (40-50 minutes). In addition, the method uses a high flow rate (1,5 mL.min-1) which increases the consumption of expensive solvents HPLC grade. The main problem observed was the TF value (1,8) that would be accepted if the drug was not a racemic mixture, since the co-elution of the isomers can become an unreliable peak integration. Therefore, the optimization was suggested in order to reduce the analysis time, aiming a better peak resolution and TF. For the optimization method, by the analysis of the surface-response plot it was possible to confirm the ideal setting analytical condition: 45 °C, 0,8 mL.min-1 and 80:20 USP-MP: Methanol. The optimized HPLC method enabled the quantification of HCQ sulfate, with a peak of high resolution, showing a TF value of 1,17. This promotes good co-elution of isomers of the HCQ, ensuring an accurate quantification of the raw material as racemic mixture. This method also proved to be 18 times faster, approximately, compared to the reference method, using a lower flow rate, reducing even more the consumption of the solvents and, consequently, the analysis cost. Thus, an analytical method for the quantification of HCQ sulfate was optimized using QbD methodology. This method proved to be faster and more efficient than the USP method, regarding the retention time and, especially, the peak resolution. The higher resolution in the chromatogram peaks supports the implementation of the method for quantification of the drug as racemic mixture, not requiring the separation of isomers.

Keywords: analytical method, hydroxychloroquine sulfate, quality by design, surface area graphic

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Authors: Ajit Rai, Hamza Deroui, Blandine Vacher, Khwansiri Ninpan, Arthur Aumont, Francesco Vitillo, Robert Plana

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Large-scale critical industrial scheduling problems are based on Resource-Constrained Project Scheduling Problems (RCPSP), that necessitate integration with other optimization problems (e.g., vehicle routing, supply chain, or unique industrial ones), thus requiring practical solutions (i.e., modular, computationally efficient with feasible solutions). To the best of our knowledge, the current industrial state of the art is not addressing this holistic problem. We propose an original modular solution that answers the issues exhibited by the delivery of complex projects. With three interlinked entities (project, task, resources) having their constraints, it uses a greedy heuristic with a dynamic cost function for each task with a situational assessment at each time step. It handles large-scale data and can be easily integrated with other optimization problems, already existing industrial tools and unique constraints as required by the use case. The solution has been tested and validated by domain experts on three use cases: outage management in Nuclear Power Plants (NPPs), planning of future NPP maintenance operation, and application in the defense industry on supply chain and factory relocation. In the first use case, the solution, in addition to the resources’ availability and tasks’ logical relationships, also integrates several project-specific constraints for outage management, like, handling of resource incompatibility, updating of tasks priorities, pausing tasks in a specific circumstance, and adjusting dynamic unit of resources. With more than 20,000 tasks and multiple constraints, the solution provides a feasible schedule within 10-15 minutes on a standard computer device. This time-effective simulation corresponds with the nature of the problem and requirements of several scenarios (30-40 simulations) before finalizing the schedules. The second use case is a factory relocation project where production lines must be moved to a new site while ensuring the continuity of their production. This generates the challenge of merging job shop scheduling and the RCPSP with location constraints. Our solution allows the automation of the production tasks while considering the rate expectation. The simulation algorithm manages the use and movement of resources and products to respect a given relocation scenario. The last use case establishes a future maintenance operation in an NPP. The project contains complex and hard constraints, like on Finish-Start precedence relationship (i.e., successor tasks have to start immediately after predecessors while respecting all constraints), shareable coactivity for managing workspaces, and requirements of a specific state of "cyclic" resources (they can have multiple states possible with only one at a time) to perform tasks (can require unique combinations of several cyclic resources). Our solution satisfies the requirement of minimization of the state changes of cyclic resources coupled with the makespan minimization. It offers a solution of 80 cyclic resources with 50 incompatibilities between levels in less than a minute. Conclusively, we propose a fast and feasible modular approach to various industrial scheduling problems that were validated by domain experts and compatible with existing industrial tools. This approach can be further enhanced by the use of machine learning techniques on historically repeated tasks to gain further insights for delay risk mitigation measures.

Keywords: deterministic scheduling, optimization coupling, modular scheduling, RCPSP

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Authors: M. Pacio, H. Juárez, R. Pérez-Cuapio E. Rosendo, T. Díaz, G. García

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In this study, zinc oxide (ZnO) quantum dots (QDs) have been prepared by a simple route. The growth parameters for ZnO QDs were systematically studied inside a SiO2 shell; this shell acts as a capping agent and also enhances stability of the nanoparticles in water. ZnO QDs in silica shell could be produced by initially synthesizing a ZnO colloid (containing ZnO nanoparticles in methanol solution) and then was mixed with 3-aminopropylsiloxane used as SiO2 precursor. ZnO QDs were deposited onto silicon substrates (100) orientation by spin-coating technique. ZnO QDs into a SiO2 shell were pre-heated at 300 °C for 10 min after each coating, that procedure was repeated five times. The films were subsequently annealing in air atmosphere at 500 °C for 2 h to remove the trapped fluid inside the amorphous silica cage. ZnO QDs showed hexagonal wurtzite structure and about 5 nm in diameter. The composition of the films at the surface and in the bulk was obtained by Secondary Ion Mass Spectrometry (SIMS), the spectra revealed the presence of Zn- and Si- related clusters associated to the chemical species in the solid matrix. Photoluminescence (PL) spectra under 325 nm of excitation only show a strong UV emission band corresponding to ZnO QDs, such emission is enhanced with annealing. Our results showed that the method is appropriate for the preparation of ZnO QDs films embedded in a SiO2 shell with high UV photoluminescence.

Keywords: ZnO QDs, sol gel, functionalization

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Authors: Yannis Stavrakakis, Damian Gordon

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Critical Thinking and Reflective Practice are two vital skills that students undertaking postgraduate studies should ideally possess. To help students develop and enhance these skills, this research developed several authentic activities to be undertaken as part of a module that is delivered early in a taught MSc to enhance these skills. One of the challenges of these topics is that they are somewhat ill-defined in terms of precisely what they mean, and also, there is no clear route to operationalizing the teaching of these skills. This research focuses on identifying suitable models of these skills and delivering them in a manner that is both clear and highly motivating. To achieve this, a class of 22 Master's students was divided into two groups, one was provided with a presentation and checklist about critical thinking skills, and the other group was given the same materials on the reflective practice process. The groups were given two scenarios each to analyze using their respective checklists and were asked to present their outcomes to each other and give peer review. The results were coded and compared, and key differences were noted, including the fact that the Critical Thinking outcomes were more future-focused, and the Reflective Practice outcomes were more past-focused and present-focused, as well as the fact that the Reflective Practice process generated a significantly wider range of perspectives on the scenarios.

Keywords: critical thinking, ethical scenarios, formative assessment, reflective practice

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Authors: Esther Lorrayne M. Pereira, Adriana Souza M. Batista, Fabíola A. S. Ribeiro, Adelina P. Santos, Clascídia A. Furtado, Luiz O. Faria

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The combination of multi–walled carbon nanotubes (MWCNTs) with polymers offers an attractive route to reinforce the macromolecular compounds as well as the introduction of new properties based on morphological modifications or electronic interactions between the two constituents. As they are only a few nanometers in dimension, it offers ultra-large interfacial area per volume between the nano-element and polymer matrix. Nevertheless, the use of MWCNTs as a rough material in different applications has been largely limited by their poor processability, insolubility, and infusibility. Studies concerning the nanofiller reinforced polymer composites are justified in an attempt to overcome these limitations. This work presents one preliminary study of MWCNTs dispersion into the PVDF homopolymer. For preparation, the composite components were diluted in n,n-dimethylacetamide (DMAc) with mechanical agitation assistance. After complete dilution, followed by slow evaporation of the solvent at 60°C, the samples were dried. Films of about 80 μm were obtained. FTIR and UV-Vis spectroscopic techniques were used to characterize the nanocomposites. The appearance of absorption bands in the FTIR spectra of nanofilled samples, when compared to the spectrum of pristine PVDF samples, are discussed and compared with the UV-Vis measurements.

Keywords: composites materials, FTIR, MWNTs, PVDF, UV-vis

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Authors: Ali Akbar, Seungho Shin, Sukkee Um

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The composition of catalyst layers (CLs) plays an important role in the overall performance and cost of the proton exchange membrane fuel cells (PEMFCs). Low platinum loading, high utilization, and more durable catalyst still remain as critical challenges for PEMFCs. In this study, a three-dimensional material network model is developed to visualize the nanostructure of carbon supported platinum Pt/C and Pt/VACNT catalysts in pursuance of maximizing the catalyst utilization. The quadruple-phase randomly generated CLs domain is formulated using quasi-random stochastic Monte Carlo-based method. This unique statistical approach of four-phase (i.e., pore, ionomer, carbon, and platinum) model is closely mimic of manufacturing process of CLs. Various CLs compositions are simulated to elucidate the effect of electrons, ions, and mass transport paths on the catalyst utilization factor. Based on simulation results, the effect of key factors such as porosity, ionomer contents and Pt weight percentage in Pt/C catalyst have been investigated at the represented elementary volume (REV) scale. The results show that the relationship between ionomer content and Pt utilization is in good agreement with existing experimental calculations. Furthermore, this model is implemented on the state-of-the-art Pt/VACNT CLs. The simulation results on Pt/VACNT based CLs show exceptionally high catalyst utilization as compared to Pt/C with different composition ratios. More importantly, this study reveals that the maximum catalyst utilization depends on the distance spacing between the carbon nanotubes for Pt/VACNT. The current simulation results are expected to be utilized in the optimization of nano-structural construction and composition of Pt/C and Pt/VACNT CLs.

Keywords: catalyst layer, platinum utilization, proton exchange membrane fuel cell, stochastic modeling

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Authors: Tamrat Tesfaye, Bruce Sithole

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Box-Behnken Response surface methodology was used to determine the optimum processing conditions that give maximum extraction yield and whiteness index from mango seed. The steeping time ranges from 2 to 12 hours and slurring of the steeped seed in sodium metabisulphite solution (0.1 to 0.5 w/v) was carried out. Experiments were designed according to Box-Behnken Design with these three factors and a total of 15 runs experimental variables of were analyzed. At linear level, the concentration of sodium metabisulphite had significant positive influence on percentage yield and whiteness index at p<0.05. At quadratic level, sodium metabisulphite concentration and sodium metabisulphite concentration2 had a significant negative influence on starch yield; sodium metabisulphite concentration and steeping time*temperature had significant (p<0.05) positive influence on whiteness index. The adjusted R2 above 0.8 for starch yield (0.906465) and whiteness index (0.909268) showed a good fit of the model with the experimental data. The optimum sodium metabisulphite concentration, steeping hours, and temperature for starch isolation with maximum starch yield (66.428%) and whiteness index (85%) as set goals for optimization with the desirability of 0.91939 was 0.255w/v concentration, 2hrs and 50 °C respectively. The determined experimental value of each response based on optimal condition was statistically in accordance with predicted levels at p<0.05. The Mango seeds are the by-products obtained during mango processing and possess disposal problem if not handled properly. The substitution of food based sizing agents with mango seed starch can contribute as pertinent resource deployment for value-added product manufacturing and waste utilization which might play significance role of food security in Ethiopia.

Keywords: mango, synthetic sizing agent, starch, extraction, textile, sizing

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Authors: Mihaja Razafimbelo, Guillaume Herve-Secourgeon, Fabrice Gatuingt, Marina Bottoni, Tulio Honorio-De-Faria

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The challenge of the research is to provide engineering with a robust, semi-automatic method for calculating optimal reinforcement for massive structural elements. In the absence of such a digital post-processing tool, design office engineers make intensive use of plate modelling, for which automatic post-processing is available. Plate models in massive areas, on the other hand, produce conservative results. In addition, the theoretical foundations of automatic post-processing tools for reinforcement are those of reinforced concrete beam sections. As long as there is no suitable alternative for automatic post-processing of plates, optimal modelling and a significant improvement of the constructability of massive areas cannot be expected. A method called strut-and-tie is commonly used in civil engineering, but the result itself remains very subjective to the calculation engineer. The tool developed will facilitate the work of supporting the engineers in their choice of structure. The method implemented consists of defining a ground-structure built on the basis of the main constraints resulting from an elastic analysis of the structure and then to start an optimization of this structure according to the fully stressed design method. The first results allow to obtain a coherent return in the first network of connecting struts and ties, compared to the cases encountered in the literature. The evolution of the tool will then make it possible to adapt the obtained latticework in relation to the cracking states resulting from the loads applied during the life of the structure, cyclic or dynamic loads. In addition, with the constructability constraint, a final result of reinforcement with an orthogonal arrangement with a regulated spacing will be implemented in the tool.

Keywords: strut and tie, optimization, reinforcement, massive structure

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Authors: Katarzyna Czarnota, Inga Hajdarowicz

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Political mechanisms of legal, social and economic segregation of refugees and migrants have reproduced and deepened existing hierarchies and inequalities in global labour relations. The consequences of these processes strengthened by current, so called, ‘refugee crisis’, tightening of border regimes, militarisation and closing of Balkan Route, will have a significant impact on future integration policies. One of the fields that require further research is limited access to labour rights of migrants and refugees. Although this phenomenon is experienced by a significant proportion of migrant population, these are the poorest who are also exposed to economic racism. The presentation will tackle the influence of current migration policies on increasing social and class inequalities between migrants, refugees, on the example of Syrian labours in Turkish textile factories. The authors will critically analyse examples of integration policies, especially planned changes in labour law as well as examples of violation of labour rights and exploitation of refugees and migrants in textile factories and industry. The presentation will be based on interviews with Syrian workers, conducted in Turkey and Greece in 2016.

Keywords: refugee crisis, economic racism, global labour relations, exploatation

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Authors: Iftikhar Ahmad, Mohammad Islam

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Thermally exfoliated graphene nanomaterial was reinforced into Al2O3 ceramic and the nanocomposites were consolidated using rapid high-frequency induction heat sintering route. The resulting nanocomposites demonstrated higher mechanical properties due to efficient GNS incorporation and chemical interaction with the Al2O3 matrix grains. The enhancement in mechanical properties is attributed to (i) uniformly-dispersed GNS in the consolidated structure (ii) ability of GNS to decorate Al2O3 nanoparticles and (iii) strong GNS/Al2O3 chemical interaction during colloidal mixing and pullout/crack bridging toughening mechanisms during mechanical testing. The GNS/Al2O3 interaction during different processing stages was thoroughly examined by thermal and structural investigation of the interfacial area. The formation of an intermediate aluminum oxycarbide phase (Al2OC) via a confined carbothermal reduction reaction at the GNS/Al2O3 interface was observed using advanced electron microscopes. The GNS surface roughness improves GNS/Al2O3 mechanical locking and chemical compatibility. The sturdy interface phase facilitates efficient load transfer and delayed failure through impediment of crack propagation. The resulting nanocomposites, therefore, offer superior toughness.

Keywords: ceramics, nanocomposites, interfaces, nanostructures, electron microscopy, Al2O3

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Authors: Neha Asthana, Vishal Krishna Prasad

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Collaborative planning and forecasting are the innovative and systematic approaches towards productive integration and assimilation of data synergized into information. The changing and variable market dynamics have persuaded global business chains to incorporate collaborative planning and forecasting as an imperative tool. Thus, it is essential for the supply chains to constantly improvise, update its nature, and mould as per changing global environment.

Keywords: information transfer, forecasting, optimization, supply chain management

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Authors: Muammer Kaya

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The main purpose of this article is to provide a comprehensive review of various physical and chemical processes for electronic waste (e-waste) recycling, their advantages and shortfalls towards achieving a cleaner process of waste utilization, with especial attention towards extraction of metallic values. Current status and future perspectives of waste printed circuit boards (PCBs) recycling are described. E-waste characterization, dismantling/ disassembly methods, liberation and classification processes, composition determination techniques are covered. Manual selective dismantling and metal-nonmetal liberation at – 150 µm at two step crushing are found to be the best. After size reduction, mainly physical separation/concentration processes employing gravity, electrostatic, magnetic separators, froth floatation etc., which are commonly used in mineral processing, have been critically reviewed here for separation of metals and non-metals, along with useful utilizations of the non-metallic materials. The recovery of metals from e-waste material after physical separation through pyrometallurgical, hydrometallurgical or biohydrometallurgical routes is also discussed along with purification and refining and some suitable flowsheets are also given. It seems that hydrometallurgical route will be a key player in the base and precious metals recoveries from e-waste. E-waste recycling will be a very important sector in the near future from economic and environmental perspectives.

Keywords: e-waste, WEEE, recycling, metal recovery, hydrometallurgy, pirometallurgy, biometallurgy

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Authors: Alessandro Balbo, Gianvito Colucci, Matteo Nicoli, Laura Savoldi

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Hydrogen is expected to become an undisputed player in the ecological transition throughout the next decades. The decarbonization potential offered by this energy vector provides various opportunities for the so-called “hard-to-abate” sectors, including industrial production of iron and steel, glass, refineries and the heavy-duty transport. In this regard, Italy, in the framework of decarbonization plans for the whole European Union, has been considering a wider use of hydrogen to provide an alternative to fossil fuels in hard-to-abate sectors. This work aims to assess and compare different options concerning the pathway to be followed in the development of the future Italian energy system in order to meet decarbonization targets as established by the Paris Agreement and by the European Green Deal, and to infer a techno-economic analysis of the required asset alternatives to be used in that perspective. To accomplish this objective, the Energy System Optimization Model TEMOA-Italy is used, based on the open-source platform TEMOA and developed at PoliTo as a tool to be used for technology assessment and energy scenario analysis. The adopted assessment strategy includes two different scenarios to be compared with a business-as-usual one, which considers the application of current policies in a time horizon up to 2050. The studied scenarios are based on the up-to-date hydrogen-related targets and planned investments included in the National Hydrogen Strategy and in the Italian National Recovery and Resilience Plan, with the purpose of providing a critical assessment of what they propose. One scenario imposes decarbonization objectives for the years 2030, 2040 and 2050, without any other specific target. The second one (inspired to the national objectives on the development of the sector) promotes the deployment of the hydrogen value-chain. These scenarios provide feedback about the applications hydrogen could have in the Italian energy system, including transport, industry and synfuels production. Furthermore, the decarbonization scenario where hydrogen production is not imposed, will make use of this energy vector as well, showing the necessity of its exploitation in order to meet pledged targets by 2050. The distance of the planned policies from the optimal conditions for the achievement of Italian objectives is be clarified, revealing possible improvements of various steps of the decarbonization pathway, which seems to have as a fundamental element Carbon Capture and Utilization technologies for its accomplishment. In line with the European Commission open science guidelines, the transparency and the robustness of the presented results is ensured by the adoption of the open-source open-data model such as the TEMOA-Italy.

Keywords: decarbonization, energy system optimization models, hydrogen, open-source modeling, TEMOA

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Authors: Kalpeshkumar Patel, Nikita Manvi

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The paper is an attempt to understand the influence and depiction of power in an urban space by throwing light across a few examples across the architectural timeline. Power has been the medium through which ideologies function, as witnessed across the timeline. The center to understand this ideology is to apprehend how power is formed, captured, owned, traded, and distorted. Every urban space has power embedded in it, either for the people who are imposing it or for the public who are receiving it. The most fundamental question in the issue of power is who – who will judge, whose tastes will matter and whose interests are being served. Power is expressed and reinforced by regular means, a boundary and gates, a parade route, a dominant landmark, play of shape or scale in elevation, ceremonial axis, boulevards and avenues, the vista, bilateral symmetry, or regular order. Even if people accept the psychological efficacy of these forms, the way they perceive them may vary depending on the subject. They are cold devices of power used to make some people submit to others. Yet it is also true that these symbolic forms are attractive because they speak to the deep emotions of people. They do indeed give us a sense of security, stability and continuity, awe and pride. The Urban Space for mass assembly is an idea that continues to seduce dictators and democracies. It is a tradition as old as an agora and as manipulative as Baroque Rome.

Keywords: urban space, aggrandization, city planning, landscape, supremacy, democratic

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