Search results for: computational methods

Authors: Sowntharya L.

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Aerodynamics is the most important factor when it comes to resistive forces such as lift, drag and side forces acting on the vehicle. In passenger vehicles, reducing the drag will not only unlock the door for higher achievable speed but will also reduce the fuel consumption of the vehicle. Generally, tyre contributes significantly to the overall aerodynamics of the vehicle. Hence, understanding the air-flow behaviour around the tyre is vital to optimize the aerodynamic performance in the early stage of design process. Nowadays, aerodynamic simulation employing Computational Fluid Dynamics (CFD) is gaining more importance as it reduces the number of physical wind-tunnel experiments during vehicle development process. This research develops a methodology to predict aerodynamic drag of a standalone tyre using Numerical CFD Solver and to validate the same using a wind tunnel experiment. A parametric study was carried out on different tread pattern tyres such as slick, circumferential groove & patterned tyre in stationary and rotating boundary conditions. In order to represent wheel rotation contact with the ground, moving reference frame (MRF) approach was used in this study. Aerodynamic parameters such as drag lift & air flow behaviour around the tire were simulated and compared with experimental results.

Keywords: aerodynamics, CFD, drag, MRF, wind-tunnel

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Authors: M. Amoura, M. Benmoussa, N. Zeraibi

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The flow and heat transfer is an important phenomenon in engineering systems due to its wide application in electronic cooling, heat exchangers, double pane windows etc.. The enhancement of heat transfer in these systems is an essential topic from an energy saving perspective. Lower heat transfer performance when conventional fluids, such as water, engine oil and ethylene glycol are used hinders improvements in performance and causes a consequent reduction in the size of such systems. The use of solid particles as an additive suspended into the base fluid is a technique for heat transfer enhancement. Therefore, the heat transfer enhancement in a horizontal circular tube that is maintained at a constant temperature under laminar regime has been investigated numerically. A computational code applied to the problem by use of the finite volume method was developed. Nanofluid was made by dispersion of Al2O3 nanoparticles in pure water and ethylene glycol. Results illustrate that the suspended nanoparticles increase the heat transfer with an increase in the nanoparticles volume fraction and for a considered range of Reynolds numbers. On the other hand, the heat transfer is very sensitive to the base fluid.

Keywords: Al2O3 nanoparticles, circular tube, heat transfert enhancement, numerical simulation

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Authors: Arup Kumar Sarma, Rohan Kar

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The development of physical model of River like Brahmaputra, which finds its origin in the Chema Yundung glacier of Tibet and flows through India and Bangladesh, is always expensive and very much time consuming. With the advancement of computational technique, mathematical modeling has found wide application. MIKE 21C is one such commercial software, developed by Danish Hydraulic Institute (DHI), with the depth-averaged approach and a two-dimensional curvilinear finite-difference model, which is capable of modeling hydrodynamic and morphological processes with some limitations. The main purpose of this study are to generate bathymetry of the River Brahmaputra starting from “Sadia” at upstream to “Dhubri,” at downstream stretching a distance of approximately 695 km, for four different years: 1957, 1971, 1977, and 1981 over the grid generated in the MIKE 21C and to carry out the hydrodynamic simulation for these years to analyze the effect of bathymetry change on the surface water elevation. The study has established that bathymetric change can influence the flood level significantly in some of the river reaches and therefore the modification or updating of regular bathymetry is very much essential for the reliable flood routing in alluvial rivers.

Keywords: bathymetry, brahmaputra river, hydrodynamic model, surface water elevation

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Authors: Yiping Meng, Yiming Sun

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The traditional construction industry is unable to meet the requirements for novel fabrication and construction. Automated construction and digital design have emerged as industry development trends that compensate for this shortcoming under the backdrop of Industrial Revolution 4.0. Benefitting from more flexible working space and more various end-effector tools compared to CNC methods, robot fabrication and construction techniques have been used in irregular architectural design. However, there is a lack of a systematic and comprehensive design and optimisation workflow considering geometric form, material, and fabrication methods. This paper aims to propose a design optimisation workflow for improving the rationality of a free-form timber structure fabricated by the robotic arm. Firstly, the free-form surface is described by NURBS, while its structure is calculated using the finite element analysis method. Then, by considering the characteristics and limiting factors of robotic timber fabrication, strain energy and robustness are set as optimisation objectives to optimise structural morphology by gradient descent method. As a result, an optimised structure with axial force as the main force and uniform stress distribution is generated after the structure morphology optimisation process. With the decreased strain energy and the improved robustness, the generated structure's bearing capacity and mechanical properties have been enhanced. The results prove the feasibility and effectiveness of the proposed optimisation workflow for free-form timber structure morphology design.

Keywords: robotic fabrication, free-form timber structure, Multi-objective optimisation, Structural morphology, rational design

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Authors: Li Chen

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For an aerofoil or hydrofoil in high Reynolds number flows, broadband noise is generated efficiently as the result of the turbulence convecting over the trailing edge. This noise can be related to the surface pressure fluctuations, which can be predicted by either CFD or empirical models. However, in reality, the aerofoil or hydrofoil often operates at an angle of attack. Under this situation, the flow is subjected to an Adverse-Pressure-Gradient (APG), and as a result, a flow separation may occur. This study is to assess trailing-edge noise models for such flows. In the present work, the trailing-edge noise from a 2D airfoil at 6 degree of angle of attach is investigated. Under this condition, the flow is experiencing a strong APG, and the flow separation occurs. The flow over the airfoil with a chord of 300 mm, equivalent to a Reynold Number 4x10⁵, is simulated using RANS with the SST k-ɛ turbulent model. The predicted surface pressure fluctuations are compared with the published experimental data and empirical models, and show a good agreement with the experimental data. The effect of the APG on the trailing edge noise is discussed, and the associated trailing edge noise is calculated.

Keywords: aero-acoustics, adverse-pressure gradient, computational fluid dynamics, trailing-edge noise

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Authors: Azzaya Enkhjargal

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Context: The mining industry has a long history of human rights abuses, including forced labor, environmental pollution, and displacement of communities. In recent years, there has been growing international pressure to hold mining companies accountable for these abuses. Research Aim: This study explores the legal liabilities of mining companies for human rights abuses. The study specifically examines the case of Erdenet Mining Corporation (EMC), a large mining company in Mongolia that has been accused of human rights abuses. Methodology: The study used a mixed-methods approach, which included a review of legal literature, interviews with community members and NGOs, and a case study of EMC. Findings: The study found that mining companies can be held liable for human rights abuses under a variety of regulatory frameworks, including soft law and self-regulatory instruments in the mining industry, international law, national law, and corporate law. The study also found that there are a number of challenges to holding mining companies accountable for human rights abuses, including the lack of effective enforcement mechanisms and the difficulty of proving causation. Theoretical Importance: The study contributes to the growing body of literature on the legal liabilities of mining companies for human rights abuses. The study also provides insights into the challenges of holding mining companies accountable for human rights abuses. Data Collection: The data for the study was collected through a variety of methods, including a review of legal literature, interviews with community members and NGOs, and a case study of EMC. Analysis Procedures: The data was analyzed using a variety of methods, including content analysis, thematic analysis, and case study analysis. Conclusion: The study concludes that mining companies can be held liable for human rights abuses under a variety of legal and regulatory frameworks. There are positive developments in ensuring greater accountability and protection of affected communities and the environment in countries with a strong economy. Regrettably, access to avenues of redress is reasonably low in less developed countries, where the governments have not implemented a robust mechanism to enforce liability requirements in the mining industry. The study recommends that governments and mining companies take more ambitious steps to enhance corporate accountability.

Keywords: human rights, human rights abuses, ESG, litigation, Erdenet Mining Corporation, corporate social responsibility, soft law, self-regulation, mining industry, parent company liability, sustainability, environment, UN

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Authors: Masoud Fathi Kazerouni, Jens Schlemper, Klaus-Dieter Kuhnert

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Green planet is one of the Earth’s names which is known as a terrestrial planet and also can be named the fifth largest planet of the solar system as another scientific interpretation. Plants do not have a constant and steady distribution all around the world, and even plant species’ variations are not the same in one specific region. Presence of plants is not only limited to one field like botany; they exist in different fields such as literature and mythology and they hold useful and inestimable historical records. No one can imagine the world without oxygen which is produced mostly by plants. Their influences become more manifest since no other live species can exist on earth without plants as they form the basic food staples too. Regulation of water cycle and oxygen production are the other roles of plants. The roles affect environment and climate. Plants are the main components of agricultural activities. Many countries benefit from these activities. Therefore, plants have impacts on political and economic situations and future of countries. Due to importance of plants and their roles, study of plants is essential in various fields. Consideration of their different applications leads to focus on details of them too. Automatic recognition of plants is a novel field to contribute other researches and future of studies. Moreover, plants can survive their life in different places and regions by means of adaptations. Therefore, adaptations are their special factors to help them in hard life situations. Weather condition is one of the parameters which affect plants life and their existence in one area. Recognition of plants in different weather conditions is a new window of research in the field. Only natural images are usable to consider weather conditions as new factors. Thus, it will be a generalized and useful system. In order to have a general system, distance from the camera to plants is considered as another factor. The other considered factor is change of light intensity in environment as it changes during the day. Adding these factors leads to a huge challenge to invent an accurate and secure system. Development of an efficient plant recognition system is essential and effective. One important component of plant is leaf which can be used to implement automatic systems for plant recognition without any human interface and interaction. Due to the nature of used images, characteristic investigation of plants is done. Leaves of plants are the first characteristics to select as trusty parts. Four different plant species are specified for the goal to classify them with an accurate system. The current paper is devoted to principal directions of the proposed methods and implemented system, image dataset, and results. The procedure of algorithm and classification is explained in details. First steps, feature detection and description of visual information, are outperformed by using Scale invariant feature transform (SIFT), HARRIS-SIFT, and FAST-SIFT methods. The accuracy of the implemented methods is computed. In addition to comparison, robustness and efficiency of results in different conditions are investigated and explained.

Keywords: SIFT combination, feature extraction, feature detection, natural images, natural plant recognition, HARRIS-SIFT, FAST-SIFT

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Authors: Fernanda F. Zimmermann, Beverley Burrell, Jennifer Jordan

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Introduction: Supportive care for people affected by cancer is recognised as a priority for research but yet there is little solid evidence of the effectiveness of psychological treatments for those with advanced cancer. The literature suggests that mindfulness-based interventions may be acceptable and beneficial for this population. This study aims to develop a mindfulness intervention to provide emotional support for advanced cancer population. The treatment package includes mindfulness meditation, developing an acceptance attitude and reflections on meaning in life. Methods: This study design is a one-group pre-post test with a mixed methods approach. Participants are recruited through public and private hospitals in Christchurch, NZ. Quantitative measures are the Acceptance and Action Questionnaire-II, Mindful Coping Scale and, the Meaning in Life Questionnaire. Qualitative semi-structured interviews enquire about emotional support before and after the diagnosis, participants’ thoughts about meaning in life, expectations and reflections on the mindfulness training. Qualitative data will be analysed using thematic analysis. Treatment consists of one to one 30 minutes session weekly for 4 weeks using a pre-recorded CD/podcast of the mindfulness training. This research is part of the presenter’s PhD study. Findings: This project is currently underway. The presenter will provide preliminary data on the acceptability of the mindfulness training package being delivered to participants along with the recruitment strategies. We anticipate that this novel treatment used as a self-management tool will reduce psychological distress and enable better coping for patients with advanced cancer.

Keywords: acceptance, cancer, meaning in life, mindfulness

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Authors: Marina Passero, Tianhua Zhai, Zuyi (Jacky) Huang

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Alzheimer’s disease has become a major public health issue, as indicated by the increasing populations of Americans living with Alzheimer’s disease. After decades of extensive research in Alzheimer’s disease, only seven drugs have been approved by Food and Drug Administration (FDA) to treat Alzheimer’s disease. Five of these drugs were designed to treat the dementia symptoms, and only two drugs (i.e., Aducanumab and Lecanemab) target the progression of Alzheimer’s disease, especially the accumulation of amyloid-b plaques. However, controversial comments were raised for the accelerated approvals of either Aducanumab or Lecanemab, especially with concerns on safety and side effects of these two drugs. There is still an urgent need for further drug discovery to target the biological processes involved in the progression of Alzheimer’s disease. Excessive cholesterol has been found to accumulate in the brain of those with Alzheimer’s disease. Cholesterol can be synthesized in both the blood and the brain, but the majority of biosynthesis in the adult brain takes place in astrocytes and is then transported to the neurons via ApoE. The blood brain barrier separates cholesterol metabolism in the brain from the rest of the body. Various proteins contribute to the metabolism of cholesterol in the brain, which offer potential targets for Alzheimer’s treatment. In the astrocytes, SREBP cleavage-activating protein (SCAP) binds to Sterol Regulatory Element-binding Protein 2 (SREBP2) in order to transport the complex from the endoplasmic reticulum to the Golgi apparatus. Cholesterol is secreted out of the astrocytes by ATP-Binding Cassette A1 (ABCA1) transporter. Lipoprotein receptors such as triggering receptor expressed on myeloid cells 2 (TREM2) internalize cholesterol into the microglia, while lipoprotein receptors such as Low-density lipoprotein receptor-related protein 1 (LRP1) internalize cholesterol into the neuron. Cytochrome P450 Family 46 Subfamily A Member 1 (CYP46A1) converts excess cholesterol to 24S-hydroxycholesterol (24S-OHC). Cholesterol has been approved for its direct effect on the production of amyloid-beta and tau proteins. The addition of cholesterol to the brain promotes the activity of beta-site amyloid precursor protein cleaving enzyme 1 (BACE1), secretase, and amyloid precursor protein (APP), which all aid in amyloid-beta production. The reduction of cholesterol esters in the brain have been found to reduce phosphorylated tau levels in mice. In this work, a computational pipeline was developed to identify the protein targets involved in cholesterol regulation in brain and further to identify chemical compounds as the inhibitors of a selected protein target. Since extensive evidence shows the strong correlation between brain cholesterol regulation and Alzheimer’s disease, a detailed literature review on genes or pathways related to the brain cholesterol synthesis and regulation was first conducted in this work. An interaction network was then built for those genes so that the top gene targets were identified. The involvement of these genes in Alzheimer’s disease progression was discussed, which was followed by the investigation of existing clinical trials for those targets. A ligand-protein docking program was finally developed to screen 1.5 million chemical compounds for the selected protein target. A machine learning program was developed to evaluate and predict the binding interaction between chemical compounds and the protein target. The results from this work pave the way for further drug discovery to regulate brain cholesterol to combat Alzheimer’s disease.

Keywords: Alzheimer’s disease, drug discovery, ligand-protein docking, gene-network analysis, cholesterol regulation

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Authors: Udeshika Yapa Bandara, Chamindri Witharana, Preethi Soysa

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Pomegranate fruits are used in cancer treatment in Ayurveda, Sri Lanka. Due to prevailing therapeutic effects of phytochemicals, this study was focus on anti-cancer properties of the constituents in the parts of Pomegranate fruit. Furthermore, the method of extraction, plays a crucial step of the phytochemical analysis. Therefore, this study was focus on different extraction methods. Five techniques were involved for the peel and the pericarp to evaluate the most effective extraction method; Boiling with electric burner (BL), Sonication (SN), Microwaving (MC), Heating in a 50°C water bath (WB) and Sonication followed by Microwaving (SN-MC). The presence of polyphenolic and flavonoid contents were evaluated to recognize the best extraction method for polyphenols. The total phenolic content was measured spectrophotometrically by Folin-Ciocalteu method and expressed as Gallic Acid Equivalents (w/w% GAE). Total flavonoid content was also determined spectrophotometrically with Aluminium chloride colourimetric assay and expressed as Quercetin Equivalents (w/w % QE). Pomegranate juice was taken as fermented juice (with Saccharomyces bayanus) and fresh juice. Powdered seeds were refluxed, filtered and freeze-dried. 2g of freeze-dried powder of each component was dissolved in 100ml of De-ionized water for extraction. For the comparison of antioxidant activity and total phenol content, the polyphenols were removed by the Polyvinylpolypyrrolidone (PVVP) column and fermented and fresh juice were tested for the 1, 1-diphenyl-2-picrylhydrazil (DPPH) radical scavenging activity, before and after the removal of polyphenols. For the peel samples of Pomegranate fruit, total phenol and flavonoid contents were high in Sonication (SN). In pericarp, total phenol and flavonoid contents were highly exhibited in method of Sonication (SN). A significant difference was observed (P< 0.05) in total phenol and flavonoid contents, between five extraction methods for both peel and pericarp samples. Fermented juice had a greatest polyphenolic and flavonoid contents comparative to fresh juice. After removing polyphenols of fermented juice and fresh juice using Polyvinyl polypyrrolidone (PVVP) column, low antioxidant activity was resulted for DPPH antioxidant activity assay. Seeds had a very low total phenol and flavonoid contents according to the results. Although, Pomegranate peel is the main waste component of the fruit, it has an excellent polyphenolic and flavonoid contents compared to other parts of the fruit, devoid of the method of extraction. Polyphenols play a major role for antioxidant activity.

Keywords: antioxidant activity, flavonoids, polyphenols, pomegranate

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Authors: Benoit Jauniaux, Azzam Ismail

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Objectives: The aims were to identify all incident adult cases of idiopathic inflammatory myopathies (IIMs) in the City of Leeds, UK, and to estimate the risk of cancer in IIMs as compared with the general population. Methods: Cases of IIMs were ascertained by review of all muscle biopsy reports from the Neuropathology Laboratory. A review of medical records was undertaken for each case to review the clinical diagnosis and collect epidemiological data such as age, ethnicity, sex, and comorbidities, including cancer. Leeds denominator population numbers were publicly obtainable. Results: Two hundred and six biopsy reports were identified, and after review, 50 incident cases were included in the study between June 2010 and January 2021. Out of the 50 cases, 27 were male, and 23 were female. The mean incidence rate of IIMs in Leeds throughout the study period was 7.42/1 000 000 person years. The proportion of IIMs cases with a confirmed malignancy was 22%. Compared to the general population, the relative risk of cancer was significantly greater in the IIMs population(31.56, P < 0.01). Conclusions: The incidence rate of IIMs in Leeds was consistent with data from previous literature, however, disagreement exists between different methods of IIMs case inclusion due to varying clinical criteria and definitions. IIMs are associated with increased risk of cancer however, the pathogenesis of this relationship still requires investigating. This study supports the practice of malignancy screening and long-term surveillance in patients with IIMs.

Keywords: idiopathic inflammatory myopathies, myositis, polymyositis, dermatomyositis, malignancy, epidemiology, incidence rate, relative risk

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Authors: Ankita Gupta, Sudhakar Srivastava

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Arsenic stress in plants poses a significant threat to human health, which raises the need to mitigate this issue using sustainable methods. Melatonin (MT) is one such pleiotropic molecule that not only helps in arsenic amelioration but also in increasing the rice (Oryza sativa L.) yield, which is a staple food for many. This study investigated the effects of melatonin on the growth and yield of Rajendra Kasturi rice, a local variety cultivated under control and arsenic-stress field conditions. Melatonin was applied using two methods: seed priming at concentrations of 100 µM and 500 µM and foliar spray at 100 µM. The results demonstrated that both seed priming and foliar application of melatonin significantly increased rice yield. The yield of all the MT-treated plants in the As-stress conditions was 41.7-68.9% higher than the untreated plants, and the yield of all the MT-treated plants among the control conditions was 5.6-44.6% higher than the untreated plants. Furthermore, these treatments appeared to promote proper rice growth even under stress induced by arsenic exposure. The fresh weight of shoot & root, shoot length, tiller number and protein content were observed to be elevated in the melatonin-treated plants under control and arsenic-stress conditions. The most important finding of this study is that melatonin can lower the burden in rice grains and enhance plant development in addition to yield. In order to lessen the toxicity of as by preventing its transfer to grains in contaminated areas, melatonin supplementation through seed soaking and spraying can be a workable technique to develop rice with minimal arsenic in rice grains.

Keywords: arsenic, melatonin, rice, yield

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Authors: Nesrine Gaaliche

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This study provides a finite element dynamic model for analyzing rolling bearing system vibration response. The vibration responses of polypropylene bearings with and without defects are studied using FE analysis and compared to experimental data. The viscoelastic behavior of thermoplastic is investigated in this work to evaluate the influence of material flexibility and damping viscosity. The vibrations are detected using 3D dynamic analysis. Peak vibrations are more noticeable in an inner ring defect than in an outer ring defect, according to test data. The performance of thermoplastic bearings is compared to that of metal parts using vibration signals. Both the test and numerical results show that Polypropylene bearings exhibit less vibration than steel counterparts. Unlike bearings made from metal, polypropylene bearings absorb vibrations and handle shaft misalignments. Following validation of the overall vibration spectrum data, Von Mises stresses inside the rings are assessed under high loads. Stress is significantly high under the balls, according to the simulation findings. For the test cases, the computational findings correspond closely to the experimental results.

Keywords: viscoelastic, FE analysis, polypropylene, bearings

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Authors: Jalil Boudjadar

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Dynamic Voltage and Frequency Scaling (DVFS) multicore platforms are promising execution platforms that enable high computational performance, less energy consumption and flexibility in scheduling the system processes. However, the resulting interleaving and memory interference together with per-core frequency tuning make real-time guarantees hard to be delivered. Besides, energy consumption represents a strong constraint for the deployment of such systems on energy-limited settings. Identifying the system configurations that would achieve a high performance and consume less energy while guaranteeing the system schedulability is a complex task in the design of modern embedded systems. This work studies the trade-off between energy consumption, cores utilization and memory bottleneck and their impact on the schedulability of DVFS multicore time-critical systems with a hierarchy of shared memories. We build a model-based framework using Parametrized Timed Automata of UPPAAL to analyze the mutual impact of performance, energy consumption and schedulability of DVFS multicore systems, and demonstrate the trade-off on an actual case study.

Keywords: time-critical systems, multicore systems, schedulability analysis, energy consumption, performance analysis

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Authors: Sirine Sayed, Mahrez Ait Mohammed, Mourad Nachtane, Abdelwahed Barkaoui, Khalid Bouziane, Mostapha Tarfaoui

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This study addresses a critical challenge in transitioning to a hydrogen-based economy by introducing and validating a one-dimensional (1D) tool for modelling hydrogen permeability through hybrid materials, focusing on tank applications. The model developed integrates rigorous experimental validation, published data, and advanced computational modelling using the PanDiffusion framework, significantly enhancing its validity and applicability. By elucidating complex interactions between material properties, storage system configurations, and operational parameters, the tool demonstrates its capability to optimize design and operational parameters in real-world scenarios, as illustrated through a case study of hydrogen leakage. This comprehensive approach to assessing hydrogen permeability contributes significantly to overcoming key barriers in hydrogen infrastructure development, potentially accelerating the widespread adoption of hydrogen technology across various industrial sectors and marking a crucial step towards a more sustainable energy future.

Keywords: hydrogen storage, composite tank, permeability modelling, PanDiffusion, energy carrier, transportation technology

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Authors: Belyihun Muchie

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Teaching strategies significantly influence the effectiveness of language teaching practices. Macro/micro ELT strategies realizes the practicality of language teaching in the classroom, where the teacher and students play together. The study aimed to identify teaching strategies employed by primary English language teachers in EFL classrooms. It also analyzed the alignment of teaching strategies with the contemporary language teaching approaches and principles. More over, the study evaluated primary English language teachers' perceptions of the challenges and benefits of implementing innovative teaching strategies. The study used a descriptive survey research design with mixed methods approaches and convergent parallel mixed methods of data collection and analysis. Ten primary schools were selected conveniently, including 60 teachers in total. To collect the adequate data classroom observation, questionnaire and document analysis were used. From the analysis, it was found that primary school English language teachers were not teaching English using innovative teaching strategies. Hence, the alignment of their teaching strategies with the principles and syllabus of the English subject was mismatched. Finally, although there were hindrances of employing innovative teaching strategies, teachers’ commitment of trying much alternatives, was found to be less. They voiced concerns about the erosion of respect for the teaching profession, low salaries, lack of incentives for best practices, insufficient teaching resources, and autocratic leadership within schools. Therefore, as teachers found it increasingly difficult to teach English, it was concluded that primary school English language teachers were not employing innovative ELT strategies in their EFL classroom for effective language teaching in Ethiopia.

Keywords: ELT strategies, descriptive survey research design, innovative teaching strategies, primary school English language teachers

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Authors: Eugene Rybin

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Reduction of nutrient losses when using mineral fertilizers is a very important and urgent challenge, which is of both economic and environmental significance. This paper shows the production of slow- and controlled release fertilizers through application of inorganic coatings, which make the released nutrients plant-available. The method of production of coated fertilizers with inorganic cover material is an alternative to other methods where polymer coatings are used. The method is based on spraying an aqueous slurry onto the surface of granules with simultaneous drying in drums under certain conditions and subsequent cooling of granules. This method of production of slow- and controlled-release fertilizers is more ecofriendly compared with others because inorganic materials are used to create a membrane. That is why the coating material is definitely biodegradable. There is also shown the effect of these coatings on the properties of fertilizers, as well as on the agrochemical efficiency and nutrient efficiency/ availability to the plants. The agrochemical tests have proved the increase of nutrient efficiency for every nutrient in compound fertilizers (NPK, NPS) for 3 consecutive years by 10-20 % and by 25-28% for urea, as well as an increase in crop yield, by 10-15% in general, and its quality. Moreover, the decrease in caking by almost 70% was proven as well as slowing down the release rate of nutrients from fertilizers. Control of the release rate was achieved by regulation of thickness and contents of coating materials. All of those characteristics were researched according to the standard-used methods. The performed research has developed the fertilizer technology of slow- and controlled release of nutrients through applying of plant-available inorganic coatings. It leads to a better synchronization of nutrient release rate and plants needs, as well as reduces the harmful effects on the environment from the fertilizers applied.

Keywords: controlled release, fertilizers, nutrients, plant-available coatings

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Authors: Aliaa M. El-Borai, Ehab A. Beltagy, Eman E. Gadallah, Samy A. ElAssar

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Bioremediation technology is now used for treatment instead of traditional metal removal methods. A strain was isolated from Marsa Alam, Red sea, Egypt showed high resistance to high lead concentration and was identified by the 16S rRNA gene sequencing technique as Halomonas sp. ES015. Medium optimization was carried out using Plackett-Burman design, and the most significant factors were yeast extract, casamino acid and inoculums size. The optimized media obtained by the statistical design raised the removal efficiency from 84% to 99% from initial concentration 250 ppm of lead. Moreover, Box-Behnken experimental design was applied to study the relationship between yeast extract concentration, casamino acid concentration and inoculums size. The optimized medium increased removal efficiency to 97% from initial concentration 500 ppm of lead. Immobilized Halomonas sp. ES015 cells on sponge cubes, using optimized medium in loop bioremediation column, showed relatively constant lead removal efficiency when reused six successive cycles over the range of time interval. Also metal removal efficiency was not affected by flow rate changes. Finally, the results of this research refer to the possibility of lead bioremediation by free or immobilized cells of Halomonas sp. ES015. Also, bioremediation can be done in batch cultures and semicontinuous cultures using column technology.

Keywords: bioremediation, lead, Box–Behnken, Halomonas sp. ES015, loop bioremediation, Plackett-Burman

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Authors: Christine Winberg, James Garraway

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Many key university documents, such as vision and mission statements and strategic plans, are aspirational and future-oriented. There is a wide range of future-oriented methods that are used in planning applications, ranging from mathematical modelling to expert opinions. Many of these methods have limitations, and planners using these tools might, for example, make the technical-rational assumption that their plans will unfold in a logical and inevitable fashion, thus underestimating the many complex forces that are at play in planning for an unknown future. This is the issue that this study addresses. The overall project aim was to assist a new university of technology in developing appropriate responses to its social responsibility, graduate employability and research missions in its strategic plan. The specific research question guiding the research activities and approach was: how might the use of innovative future-oriented planning tools enable or constrain a strategic planning process? The research objective was to engage collaborating groups in the use of an innovative tool to develop and assess future scenarios, for the purpose of developing deeper understandings of possible futures and their challenges. The scenario planning tool chosen was ‘fictive scripting’, an analytical technique derived from Technology Forecasting and Innovation Studies. Fictive scripts are future projections that also take into account the present shape of the world and current developments. The process thus began with a critical diagnosis of the present, highlighting its tensions and frictions. The collaborative groups then developed fictive scripts, each group producing a future scenario that foregrounded different institutional missions, their implications and possible consequences. The scripts were analyzed with a view to identifying their potential contribution to the university’s strategic planning exercise. The unfolding fictive scripts revealed a number of insights in terms of unexpected benefits, unexpected challenges, and unexpected consequences. These insights were not evident in previous strategic planning exercises. The contribution that this study offers is to show how better choices can be made and potential pitfalls avoided through a systematic foresight exercise. When universities develop strategic planning documents, they are looking into the future. In this paper it is argued that the use of appropriate tools for future-oriented exercises, can help planners to understand more fully what achieving desired outcomes might entail, what challenges might be encountered, and what unexpected consequences might ensue.

Keywords: fictive scripts, scenarios, strategic planning, technological forecasting

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Authors: Samedin Mehmeti

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The rationale behind this study is considering combating and preventing the phenomenon of trafficking in human beings from a multidisciplinary perspective that involves many layers of the society. Trafficking in human beings is an abhorrent phenomenon highly affecting negatively the victims and their families in both human and material aspect, sometimes causing irreversible damages. The longer term effects of this phenomenon, in countries with a weak economic development and extremely young and dynamic population, such as Kosovo, without proper measures to prevented and control can cause tremendous damages in the society. Given the fact that a complete eradication of this phenomenon is almost impossible, efforts should be concentrated at least on the prevention and controlling aspects. Treating trafficking in human beings based on traditional police tactics, methods and proceedings cannot bring satisfactory results. There is no doubt that a multi-disciplinary approach is an irreplaceable requirement, in other words, a combination of authentic and functional proactive and reactive methods, techniques and tactics. Obviously, police must exercise its role in preventing and combating trafficking in human beings, a role sanctioned by the law, however, police role and contribution cannot by any means considered complete if all segments of the society are not included in these efforts. Naturally, civil society should have an important share in these collaborative and interactive efforts especially in preventive activities such as: awareness on trafficking risks and damages, proactive engagement in drafting appropriate legislation and strategies, law enforcement monitoring and direct or indirect involvement in protective and supporting activities which benefit the victims of trafficking etc.

Keywords: civil society, cooperation, police, human trafficking

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Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

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Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

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Authors: D. S. Malatesh, K. J. Ananda, C. Ansar Kamran, K. Ganesh Udupa

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Dirofilaria repens is a mosquito-borne filarioid nematode of dogs and other carnivores and accidentally affects humans. D. repens is reported in many countries, including India. Subcutaneous dirofilariosis caused by D. repens is a zoonotic disease, widely distributed throughout Europe, Asia, and Africa, with higher prevalence reported in dogs from Sri Lanka (30-60%), Iran (61%) and Italy (21-25%). Dirofilariasis in dogs was diagnosed by detection of microfilariae in blood. Identification of different Dirofilaria species was done by using molecular methods like polymerase chain reaction (PCR). Even though many researchers reported molecular evidence of D. repens across India, to our best knowledge there is no data available on molecular diagnosis of D. repens in dogs and its zoonotic implication in Karnataka state a southern state in India. The aim of the present study was to identify the Dirofilaria species occurring in dogs from Karnataka, India. Out of 310 samples screened for the presence of microfilariae using traditional diagnostic methods, 99 (31.93%) were positive for the presence of microfilariae. Based on the morphometry, the microfilariae were identified as D. repens. For confirmation of species, the samples were subjected to PCR using pan filarial primers (DIDR-F1, DIDR-R1) for amplification of internal transcribed spacer region 2 (ITS2) of the ribosomal DNA. The PCR product of 484 base pairs on agarose gel was indicative of D. repens. Hence, a single PCR reaction using pan filarial primers can be used to differentiate filarial species found in dogs. The present study confirms that dirofilarial species occurring in dogs from Karnataka is D. repens and further sequencing studies are needed for genotypic characterization of D. repens.

Keywords: Dirofilaria repens, molecular characterization, polymerase chain reaction, Karnataka, India

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Authors: Timir Baran Roy, Luis Guerreiro, Ashutosh Bagchi

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Dynamic study is important in order to design, repair and rehabilitation of structures. It has played an important role in the behavior characterization of structures; such as bridges, dams, high-rise buildings etc. There had been a substantial development in this area over the last few decades, especially in the field of dynamic identification techniques of structural systems. Frequency Domain Decomposition (FDD) and Time Domain Decomposition are most commonly used methods to identify modal parameters; such as natural frequency, modal damping, and mode shape. The focus of the present research is to study the dynamic characteristics of typical timber masonry walls commonly used in Portugal. For that purpose, a multi-storey structural prototypes of such walls have been tested on a seismic shake table at the National Laboratory for Civil Engineering, Portugal (LNEC). Signal processing has been performed of the output response, which is collected from the shaking table experiment of the prototype using accelerometers. In the present work signal processing of the output response, based on the input response has been done in two ways: FDD and Stochastic Subspace Identification (SSI). In order to estimate the values of the modal parameters, algorithms for FDD are formulated, and parametric functions for the SSI are computed. Finally, estimated values from both the methods are compared to measure the accuracy of both the techniques.

Keywords: frequency domain decomposition (fdd), modal parameters, signal processing, stochastic subspace identification (ssi), time domain decomposition

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Authors: Rubin Dan, Xingcai Wang, Ziyang Chen

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A chaotic time series noise reduction method based on the fusion of the local projection method, wavelet transform, and particle swarm algorithm (referred to as the LW-PSO method) is proposed to address the problem of false recognition due to noise in the recognition process of chaotic time series containing noise. The method first uses phase space reconstruction to recover the original dynamical system characteristics and removes the noise subspace by selecting the neighborhood radius; then it uses wavelet transform to remove D1-D3 high-frequency components to maximize the retention of signal information while least-squares optimization is performed by the particle swarm algorithm. The Lorenz system containing 30% Gaussian white noise is simulated and verified, and the phase space, SNR value, RMSE value, and K value of the 0-1 test method before and after noise reduction of the Schreiber method, local projection method, wavelet transform method, and LW-PSO method are compared and analyzed, which proves that the LW-PSO method has a better noise reduction effect compared with the other three common methods. The method is also applied to the classical system to evaluate the noise reduction effect of the four methods and the original system identification effect, which further verifies the superiority of the LW-PSO method. Finally, it is applied to the Chengdu rainfall chaotic sequence for research, and the results prove that the LW-PSO method can effectively reduce the noise and improve the chaos recognition rate.

Keywords: Schreiber noise reduction, wavelet transform, particle swarm optimization, 0-1 test method, chaotic sequence denoising

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Authors: Linda Chularojmontri, Seewaboon Sireeratawong, Suvara Wattanapitayakul

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Terminalia arjuna Roxb. (family Combretaceae) is commonly known as ‘Sa maw thet’ in Thai. The fruit is used in traditional medicine as natural mild laxatives, carminative and expectorant. Aim of the study: This research aims to study the anti-inflammatory, analgesic and antipyretic activities of Terminalia arjuna extract by using animal models in comparison to the reference drugs. Materials and Methods: The anti-inflammatory study was conducted by two experimental animal models namely ethyl phenylpropionate (EPP)-induced ear edema and carrageenan-induced paw edema. The study of analgesic activity used two methods of pain induction including acetic acid and heat-induced pain. In addition, the antipyretic activity study was performed by induced hyperthermia with yeast. Results: The results showed that the oral administration of Terminalia arjuna extract possessed acute anti-inflammatory effect in carrageenan-induced paw edema. Terminalia arjuna extract showed the analgesic activity in acetic acid-induced writhing response and heat-induced pain. This indicates its peripheral effect by inhibiting the biosynthesis and/or release of some pain mediators and some mechanism through Central nervous system. Moreover, Terminalia arjuna extract at the dose of 1000 and 1500 mg/kg body weight showed the antipyretic activity, which might be because of the inhibition of prostaglandins. Conclusion: The findings of this study indicated that the Terminalia arjuna extract possesses the anti-inflammatory, analgesic and antipyretic activities in animals.

Keywords: analgesic activity, anti-inflammatory activity, antipyretic activity, Terminalia arjuna extract

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Authors: Pavel V. Balabanov, Daria A. Liubimova, Aleksandr P. Savenkov

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The increase of technogenic and natural accidents, accompanied by air pollution, for example, by combustion products, leads to the necessity of respiratory protection. This work is devoted to the development of a calorimetric method and a device which allow investigating quickly the kinetics of carbon dioxide sorption by chemo-sorbents on the base of potassium superoxide in order to assess the protective properties of respiratory protective closed-circuit apparatus. The features of the traditional approach for determining the sorption properties in a thin layer of chemo-sorbent are described, as well as methods and devices, which can be used for the sorption kinetics study. The authors of the paper developed an approach (as opposed to the traditional approach) based on the power measurement of internal heat sources in the chemo-sorbent layer. The emergence of the heat sources is a result of the exothermic reaction of carbon dioxide sorption. This approach eliminates the necessity of chemical analysis of samples and can significantly reduce the time and material expenses during chemo-sorbents testing. The error of determining the volume fraction of adsorbed carbon dioxide by the developed method does not exceed 12%. Taking into account the efficiency of the method, we consider that it is a good alternative to traditional methods of chemical analysis under the assessment of the protection sorbents quality.

Keywords: carbon dioxide chemisorption, exothermic reaction, internal heat sources, respiratory protective apparatus

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Authors: Farhad Shafiepour Motlagh, Narges Salehi

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Purpose: The aim of the present study was a paradigm model of educational policy review strategies for the development of Professional schools in Iran. Research Methodology: The research method was based on Grounded theory. The statistical population included all articles of the ten years 2022-2010 and the method of sampling in a purposeful manner to the extent of theoretical saturation to 31 articles. For data analysis, open coding, axial coding and selective coding were used. Results: The results showed that causal conditions include social requirements (social expectations, educational justice, social justice); technology requirements (use of information and communication technology, use of new learning methods), educational requirements (development of educational territory, Development of educational tools and development of learning methods), contextual conditions including dual dimensions (motivational-psychological context, context of participation and cooperation), strategic conditions including (decentralization, delegation, organizational restructuring), intervention conditions (poor knowledge) Human resources, centralized system governance) and outcomes (school productivity, school professionalism, graduate entry into the labor market) were obtained. Conclusion: A review of educational policy is necessary to develop Iran's Professional schools, and this depends on decentralization, delegation, and, of course, empowerment of school principals.

Keywords: school productivity, professional schools, educational policy, paradigm

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Authors: G. Natuhwera, M. Rabwoni, P. Ellis, A. Merriman

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Aims: Health workers are likely to document patients’ care inaccurately, especially when using new and revised case tools, and this could negatively impact patient care. This study set out to; (1) assess nurses’ and clinicians’ documentation practices when using a new patients’ continuation case sheet (PCCS) and (2) explore nurses’ and clinicians’ experiences regarding documentation of patients’ information in the new PCCS. The purpose of introducing the PCCS was to improve continuity of care for patients attending clinics at which they were unlikely to see the same clinician or nurse consistently. Methods: This was a mixed methods study. The cross-sectional inquiry retrospectively reviewed 100 case notes of active patients on hospice and palliative care program. Data was collected using a structured questionnaire with constructs formulated from the new PCCS under study. The qualitative element was face-to-face audio-recorded, open-ended interviews with a purposive sample of one palliative care clinician, and four palliative care nurse specialists. Thematic analysis was used. Results: Missing patients’ biogeographic information was prevalent at 5-10%. Spiritual and psychosocial issues were not documented in 42.6%, and vital signs in 49.2%. Poorest documentation practices were observed in past medical history part of the PCCS at 40-63%. Four themes emerged from interviews with clinicians and nurses-; (1) what remains unclear and challenges, (2) comparing the past with the present, (3) experiential thoughts, and (4) transition and adapting to change. Conclusions: The PCCS seems to be a comprehensive and simple tool to be used to document patients’ information at subsequent visits. The comprehensiveness and utility of the PCCS does paper to be limited by the failure to train staff in its use prior to introducing. The authors find the PCCS comprehensive and suitable to capture patients’ information and recommend it can be adopted and used in other palliative and hospice care settings, if suitable introductory training accompanies its introduction. Otherwise, the reliability and validity of patients’ information collected by this PCCS can be significantly reduced if some sections therein are unclear to the clinicians/nurses. The study identified clinicians- and nurses-related pitfalls in documentation of patients’ care. Clinicians and nurses need to prioritize accurate and complete documentation of patient care in the PCCS for quality care provision. This study should be extended to other sites using similar tools to ensure representative and generalizable findings.

Keywords: documentation, information case sheet, palliative care, quality improvement

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Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos

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Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.

Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology

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Authors: Alejandra Martin-Dominguez, Javier Canto-Rios, Velitchko Tzatchkov

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Electrocoagulation is a water treatment technology that consists of generating coagulant species in situ by electrolytic oxidation of sacrificial anode materials triggered by electric current. It removes suspended solids, heavy metals, emulsified oils, bacteria, colloidal solids and particles, soluble inorganic pollutants and other contaminants from water, offering an alternative to the use of metal salts or polymers and polyelectrolyte addition for breaking stable emulsions and suspensions. The method essentially consists of passing the water being treated through pairs of consumable conductive metal plates in parallel, which act as monopolar electrodes, commonly known as ‘sacrificial electrodes’. Physicochemical, electrochemical and hydraulic processes are involved in the efficiency of this type of treatment. While the physicochemical and electrochemical aspects of the technology have been extensively studied, little is known about the influence of the hydraulics. However, the hydraulic process is fundamental for the reactions that take place at the electrode boundary layers and for the coagulant mixing. Electrocoagulation reactors can be open (with free water surface) and closed (pressurized). Independently of the type of rector, hydraulic head loss is an important factor for its design. The present work focuses on the study of the total hydraulic head loss and flow velocity and pressure distribution in electrocoagulation reactors with single or multiple concentric annular cross sections. An analysis of the head loss produced by hydraulic wall shear friction and accessories (minor head losses) is presented, and compared to the head loss measured on a semi-pilot scale laboratory model for different flow rates through the reactor. The tests included laminar, transitional and turbulent flow. The observed head loss was compared also to the head loss predicted by several known conceptual theoretical and empirical equations, specific for flow in concentric annular pipes. Four single concentric annular cross section and one multiple concentric annular cross section reactor configuration were studied. The theoretical head loss resulted higher than the observed in the laboratory model in some of the tests, and lower in others of them, depending also on the assumed value for the wall roughness. Most of the theoretical models assume that the fluid elements in all annular sections have the same velocity, and that flow is steady, uniform and one-dimensional, with the same pressure and velocity profiles in all reactor sections. To check the validity of such assumptions, a computational fluid dynamics (CFD) model of the concentric annular pipe reactor was implemented using the ANSYS Fluent software, demonstrating that pressure and flow velocity distribution inside the reactor actually is not uniform. Based on the analysis, the equations that predict better the head loss in single and multiple annular sections were obtained. Other factors that may impact the head loss, such as the generation of coagulants and gases during the electrochemical reaction, the accumulation of hydroxides inside the reactor, and the change of the electrode material with time, are also discussed. The results can be used as tools for design and scale-up of electrocoagulation reactors, to be integrated into new or existing water treatment plants.

Keywords: electrocoagulation reactors, hydraulic head loss, concentric annular pipes, computational fluid dynamics model

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