Search results for: mixed-methods approach

Authors: Dewi Retno Sari Saputro, Purnami Widyaningsih, Hendrika Handayani

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Extreme data on an observation can occur due to unusual circumstances in the observation. The data can provide important information that can’t be provided by other data so that its existence needs to be further investigated. The method for obtaining extreme data is one of them using maxima block method. The distribution of extreme data sets taken with the maxima block method is called the distribution of extreme values. Distribution of extreme values is Gumbel distribution with two parameters. The parameter estimation of Gumbel distribution with maximum likelihood method (ML) is difficult to determine its exact value so that it is necessary to solve the approach. The purpose of this study was to determine the parameter estimation of Gumbel distribution with quasi-Newton BFGS method. The quasi-Newton BFGS method is a numerical method used for nonlinear function optimization without constraint so that the method can be used for parameter estimation from Gumbel distribution whose distribution function is in the form of exponential doubel function. The quasi-New BFGS method is a development of the Newton method. The Newton method uses the second derivative to calculate the parameter value changes on each iteration. Newton's method is then modified with the addition of a step length to provide a guarantee of convergence when the second derivative requires complex calculations. In the quasi-Newton BFGS method, Newton's method is modified by updating both derivatives on each iteration. The parameter estimation of the Gumbel distribution by a numerical approach using the quasi-Newton BFGS method is done by calculating the parameter values that make the distribution function maximum. In this method, we need gradient vector and hessian matrix. This research is a theory research and application by studying several journals and textbooks. The results of this study obtained the quasi-Newton BFGS algorithm and estimation of Gumbel distribution parameters. The estimation method is then applied to daily rainfall data in Purworejo District to estimate the distribution parameters. This indicates that the high rainfall that occurred in Purworejo District decreased its intensity and the range of rainfall that occurred decreased.

Keywords: parameter estimation, Gumbel distribution, maximum likelihood, broyden fletcher goldfarb shanno (BFGS)quasi newton

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Authors: Francisco Pereira, António Augusto Vicente, Filipe Vaz, Joel Borges, Pedro Geada

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Light is a growth-limiting factor in microalgae cultivation, where factors like spectral components, intensity, and duration, often characterized by its wavelength, are well-reported to have a substantial impact on cell growth rates and, consequently, photosynthetic performance and mitigation of CO2, one of the most significant greenhouse gases (GHGs). Photobioreactors (PBRs) are commonly used to grow microalgae under controlled conditions, but they often fail to provide an even light distribution to the cultures. For this reason, there is a pressing need for innovations aiming at enhancing the efficient utilization of light. So, one potential approach to address this issue is by implementing plasmonic films, such as the localized surface plasmon resonance (LSPR). LSPR is an optical phenomenon connected to the interaction of light with metallic nanostructures. LSPR excitation is characterized by the oscillation of unbound conduction electrons of the nanoparticles coupled with the electromagnetic field from incident light. As a result of this excitation, highly energetic electrons and a strong electromagnetic field are generated. These effects lead to an amplification of light scattering, absorption, and extinction of specific wavelengths, contingent on the nature of the employed nanoparticle. Thus, microalgae might benefit from this biotechnology as it enables the selective filtration of inhibitory wavelengths and harnesses the electromagnetic fields produced, which could lead to enhancements in both biomass and metabolite productivity. This study aimed at implementing and evaluating a “plasmon-enhanced PBR”. The goal was to utilize LSPR thin films to enhance the growth and CO2 bio-fixation rate of Chlorella vulgaris. The internal/external walls of the PBRs were coated with a TiO2 matrix containing different nanoparticles (Au, Ag, and Au-Ag) in order to evaluate the impact of this approach on microalgae’s performance. Plasmonic films with distinct compositions resulted in different Chlorella vulgaris growth, ranging from 4.85 to 6.13 g.L-1. The highest cell concentrations were obtained with the metallic Ag films, demonstrating a 14% increase compared to the control condition. Moreover, it appeared to be no differences in growth between PBRs with inner and outer wall coatings. In terms of CO2 bio-fixation, distinct rates were obtained depending on the coating applied, ranging from 0.42 to 0.53 gCO2L-1d-1. Ag coating was demonstrated to be the most effective condition for carbon fixation by C. vulgaris. The impact of LSPR films on the biochemical characteristics of biomass (e.g., proteins, lipids, pigments) was analysed as well. Interestingly, Au coating yielded the most significant enhancements in protein content and total pigments, with increments of 15 % and 173 %, respectively, when compared to the PBR without any coating (control condition). Overall, the incorporation of plasmonic films in PBRs seems to have the potential to improve the performance and efficiency of microalgae cultivation, thereby representing an interesting approach to increase both biomass production and GHGs bio-mitigation.

Keywords: CO₂ bio-fixation, plasmonic effect, photobioreactor, photosynthetic microalgae

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Authors: Warnakulasuriya Arachichige Malisha Ann Rosary Fernando, Udalamatta Gamage Omila Chalanka Jinadasa, Bihini Pabasara Amandi Amarasinghe, Manul Thisuraka Mandalawatta, Uthpala Samarakoon, Manori Gamage

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The surge in sexually transmitted diseases (STDs) has become a critical public health crisis demanding urgent attention and action. Like many other nations, Sri Lanka is grappling with a significant increase in STDs due to a lack of education and awareness regarding their dangers. Presently, the available applications for tracking and managing STDs cover only a limited number of easily detectable infections, resulting in a significant gap in effectively controlling their spread. To address this gap and combat the rising STD rates, it is essential to leverage technology and data. Employing technology to enhance the tracking and management of STDs is vital to prevent their further propagation and to enable early intervention and treatment. This requires adopting a comprehensive approach that involves raising public awareness about the perils of STDs, improving access to affordable healthcare services for early detection and treatment, and utilizing advanced technology and data analysis. The proposed mobile application aims to cater to a broad range of users, including STD patients, recovered individuals, and those unaware of their STD status. By harnessing cutting-edge technologies like image detection, symptom-based identification, prevention methods, doctor and clinic recommendations, and virtual counselor chat, the application offers a holistic approach to STD management. In conclusion, the escalating STD rates in Sri Lanka and across the globe require immediate action. The integration of technology-driven solutions, along with comprehensive education and healthcare accessibility, is the key to curbing the spread of STDs and promoting better overall public health.

Keywords: STD, machine learning, NLP, artificial intelligence

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Authors: Ferzat Anka

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Many types of problems can be solved using traditional analytical methods. However, these methods take a long time and cause inefficient use of resources. In particular, different approaches may be required in solving complex and global engineering problems that we frequently encounter in real life. The bigger and more complex a problem, the harder it is to solve. Such problems are called Nondeterministic Polynomial time (NP-hard) in the literature. The main reasons for recommending different metaheuristic algorithms for various problems are the use of simple concepts, the use of simple mathematical equations and structures, the use of non-derivative mechanisms, the avoidance of local optima, and their fast convergence. They are also flexible, as they can be applied to different problems without very specific modifications. Thanks to these features, it can be easily embedded even in many hardware devices. Accordingly, this approach can also be used in trend application areas such as IoT, big data, and parallel structures. Indeed, the metaheuristic approaches are algorithms that return near-optimal results for solving large-scale optimization problems. This study is focused on the new metaheuristic method that has been merged with the chaotic approach. It is based on the chaos theorem and helps relevant algorithms to improve the diversity of the population and fast convergence. This approach is based on Chimp Optimization Algorithm (ChOA), that is a recently introduced metaheuristic algorithm inspired by nature. This algorithm identified four types of chimpanzee groups: attacker, barrier, chaser, and driver, and proposed a suitable mathematical model for them based on the various intelligence and sexual motivations of chimpanzees. However, this algorithm is not more successful in the convergence rate and escaping of the local optimum trap in solving high-dimensional problems. Although it and some of its variants use some strategies to overcome these problems, it is observed that it is not sufficient. Therefore, in this study, a newly expanded variant is described. In the algorithm called Ex-ChOA, hybrid models are proposed for position updates of search agents, and a dynamic switching mechanism is provided for transition phases. This flexible structure solves the slow convergence problem of ChOA and improves its accuracy in multidimensional problems. Therefore, it tries to achieve success in solving global, complex, and constrained problems. The main contribution of this study is 1) It improves the accuracy and solves the slow convergence problem of the ChOA. 2) It proposes new hybrid movement strategy models for position updates of search agents. 3) It provides success in solving global, complex, and constrained problems. 4) It provides a dynamic switching mechanism between phases. The performance of the Ex-ChOA algorithm is analyzed on a total of 8 benchmark functions, as well as a total of 2 classical and constrained engineering problems. The proposed algorithm is compared with the ChoA, and several well-known variants (Weighted-ChoA, Enhanced-ChoA) are used. In addition, an Improved algorithm from the Grey Wolf Optimizer (I-GWO) method is chosen for comparison since the working model is similar. The obtained results depict that the proposed algorithm performs better or equivalently to the compared algorithms.

Keywords: optimization, metaheuristic, chimp optimization algorithm, engineering constrained problems

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Authors: Dragos Dragomir-Stanciu, Leon Marsh

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Background As a response to the gaps identified in recent research in the provision of residential care to address co-occurring health needs, including mental health problems and complexities Gamble Aware has facilitated the possibility to provide a new service which would extend the NGTS provision of residential rehabilitation for gambling disorder with complex and co-morbid presentation. Gordon Moody, together with Adferiad have been successful in securing the tender for this service and this presentation aims to introduce FOLD, the resulting model of treatment developed for the delivery of the service. Setting As a partnership, we have come together to coproduce a model which allows us to share our clinical and industry knowledge and build on our reputations as trusted treatment providers. The presentation will outline our expertise share in development of a unified approach to recovery-oriented models of care, clinical governance, risk assessment and management and aftercare and continuous recovery. We will also introduce our innovative specialist referral portal which will offer referring partners the ability to include the service user in planning their own recovery journey. Outcomes Our collaboration has resulted in the development of the FOLD model which includes three agile and flexible treatment packages aimed at offering the most enhanced and comprehensive treatment in UK, to date, for those most affected by gambling harm. The paper will offer insight into each treatment package and all recovery model stages involved, as well as into the partnership work with NGST providers, local mental health and social care providers and lived experience organisation that will enable us to offer support to more 100 people a year who would otherwise get “lost in the system”. Conclusion FOLD offers a great opportunity to develop, implement and evaluate a new, much needed, whole-person and whole-system approach to counter gambling related harms.

Keywords: gambling treatment, partnership working, integrated care pathways, NGTS, complex needs

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Authors: Nalanda Roy

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The project will offer a fresh and critical perspective into the Tokyo Trial judgment led by the Indian Jurist Dr. Radha Binod Pal. The project will focus on the Third World Approach to International Law (TWAIL) methodology to examine the relevance of international law from the post-colonial perspectives. The project will analyze Pal’s dissenting arguments from a new and comparative perspective, apply for work from other disciplines, and create an understanding of the significance of the historic judgment considering its contemporary relevance, and fill in the gaps that exist in the call for global justice.

Keywords: Tokyo trial, third world, judgment, international law

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Authors: A. R. Nor Azlina, H. Salwana, I. Zuraeda, A. R. Rashidah, O. Normah

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Transitioning towards globalization in the business environment has necessitated more essential growing changes such as competition, business strategy, innovation in technology and effectiveness of societal trends on adopting corporate governance are seen to be drivers of the future. This transformations on business environment has a significant impact to organizations’ performances. Many organizations are demanding for more proactive entrepreneurs with dynamic team, who can run and steer their business to success. Changing on strategy, roles, tasks, entrepreneurial skills and implementing corporate governance in relationship development is important to enhance the organization’s performance towards being more cost-efficient and subsequently increase its efficiency. Small Medium Enterprises (SMEs) in most developing countries are contributors to the economic growth of a nation. However, the potential of Microfinance Institutions (MFIs) is always overlooked in contributing towards SMEs development. The adoption of corporate governance and accountability in MFIs as driving forces for these SMEs is not incorporated in measurements of organization performance. This paper attempts to address some of the governance issues associated with dimensions of accountability in improving performances of microfinance institutions. Qualitative approach was adopted in this study to analyze the data collected. The qualitative approach emerges as contributing factor in understanding and critiquing accountability processes, as well as addressing the concerns of practitioners and policymakers. A close researcher engagement with the field which concerns process, embracing of situational complexity, as well as critical and reflective understandings of organizational phenomena remain as hallmarks of the tradition. It is concluded that in describing and scrutinizing an understanding of managerial behavior, organizational factors and macro-economic relationship in SMEs firm need to be improved. This is also the case in MFIs. A framework is developed to explore the linkage of corporate governance and accountability issues related to entrepreneurship as factors affecting MFIs performances in facing ongoing transformation of organization performance within Malaysian SMEs industries.

Keywords: accountability, corporate governance, microfinance, organization performance

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Authors: Roxane A. Legaie, Kjiana E. Schwab, Caroline E. Gargett

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Studies looking at the changes in gene expression from RNAseq data often make use of linear models. It is also common practice to focus on a subset of data for a comparison of interest, leaving aside the samples not involved in this particular comparison. This work shows the importance of including all observations in the modeling process to better estimate variance parameters, even when the samples included are not directly used in the comparison under test. The human endometrium is a dynamic tissue, which undergoes cycles of growth and regression with each menstrual cycle. The mesenchymal stem cells (MSCs) present in the endometrium are likely responsible for this remarkable regenerative capacity. However recent studies suggest that MSCs also plays a role in the pathogenesis of endometriosis, one of the most common medical conditions affecting the lower abdomen in women in which the endometrial tissue grows outside the womb. In this study we compared gene expression profiles between MSCs and non-stem cell counterparts (‘non-MSC’) obtained from women with (‘E’) or without (‘noE’) endometriosis from RNAseq. Raw read counts were used for differential expression analysis using a linear model with the limma-voom R package, including either all samples in the study or only the samples belonging to the subset of interest (e.g. for the comparison ‘E vs noE in MSC cells’, including only MSC samples from E and noE patients but not the non-MSC ones). Using the full dataset we identified about 100 differentially expressed (DE) genes between E and noE samples in MSC samples (adj.p-val < 0.05 and |logFC|>1) while only 9 DE genes were identified when using only the subset of data (MSC samples only). Important genes known to be involved in endometriosis such as KLF9 and RND3 were missed in the latter case. When looking at the MSC vs non-MSC cells comparison, the linear model including all samples identified 260 genes for noE samples (including the stem cell marker SUSD2) while the subset analysis did not identify any DE genes. When looking at E samples, 12 genes were identified with the first approach and only 1 with the subset approach. Although the stem cell marker RGS5 was found in both cases, the subset test missed important genes involved in stem cell differentiation such as NOTCH3 and other potentially related genes to be used for further investigation and pathway analysis.

Keywords: differential expression, endometriosis, linear model, RNAseq

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Authors: Priyanka Ghosh, Priti Kumar Roy

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Every year a considerable number of people die due to methyl alcohol poisoning, in which most of them die even before proper treatment. This work gives a simple and cheap first aid to those affected individuals by the administration of activated charcoal. In this article, we emphasise on the adsorption capability of activated charcoal for the treatment of poisoning and use an impulsive differential equation to study the effect of activated charcoal during adsorption. We also investigate the effects of various parameters on the adsorption which are incorporated in the model system.

Keywords: activated charcoal, adsorption, impulsive differential equation, methanol poisoning

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Authors: Andrea Musumeci

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General theory of translation has suffered the lack of a homogeneous academic dialect, a holistic methodology to account for the diversity of factors involved in the discipline. An underlying pattern amongst theories of translation belonging to different periods and schools has been identified. Such pattern, which is linguistics oriented, could play a role towards unified academic and professional environments, both in terms of research and as a professional category. The implementation of such an approach has also led to a critique of the concept of equivalence, as being not the best of ways to account for translating phenomena.

Keywords: optimal, translating, research translation theory, methodology, descriptive analysis

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Authors: Lucia Carrion Gordon, Jaime Santiago Sanchez Reinoso

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According to the relation of Digital Preservation and the Health field as a case of study, the architectural model help us to explain that definitions. .The principal goal of Data Preservation is to keep information for a long term. Regarding of Mediacal information, in order to perform a heart transplant, physicians need to preserve this organ in an adequate way. This approach between the two perspectives, the medical and the technological allow checking the similarities about the concepts of preservation. Digital preservation and medical advances are related in the same level as knowledge improvement.

Keywords: medical management, digital, data, heritage, preservation

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Authors: David X. Dong, Qingming Zhang, Meng Lu

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Nitrites enter waterways as runoff from croplands and are discharged from many industrial sites. Excessive nitrite inputs to water bodies lead to eutrophication. On-site rapid detection of nitrite is of increasing interest for managing fertilizer application and monitoring water source quality. Existing methods for detecting nitrites use spectrophotometry, ion chromatography, electrochemical sensors, ion-selective electrodes, chemiluminescence, and colorimetric methods. However, these methods either suffer from high cost or provide low measurement accuracy due to their poor selectivity to nitrites. Therefore, it is desired to develop an accurate and economical method to monitor nitrites in environments. We report a low-cost optical sensor, in conjunction with a machine learning (ML) approach to enable high-accuracy detection of nitrites in water sources. The sensor works under the principle of measuring molecular absorptions of nitrites at three narrowband wavelengths (295 nm, 310 nm, and 357 nm) in the ultraviolet (UV) region. These wavelengths are chosen because they have relatively high sensitivity to nitrites; low-cost light-emitting devices (LEDs) and photodetectors are also available at these wavelengths. A regression model is built, trained, and utilized to minimize cross-sensitivities of these wavelengths to the same analyte, thus achieving precise and reliable measurements with various interference ions. The measured absorbance data is input to the trained model that can provide nitrite concentration prediction for the sample. The sensor is built with i) a miniature quartz cuvette as the test cell that contains a liquid sample under test, ii) three low-cost UV LEDs placed on one side of the cell as light sources, with each LED providing a narrowband light, and iii) a photodetector with a built-in amplifier and an analog-to-digital converter placed on the other side of the test cell to measure the power of transmitted light. This simple optical design allows measuring the absorbance data of the sample at the three wavelengths. To train the regression model, absorbances of nitrite ions and their combination with various interference ions are first obtained at the three UV wavelengths using a conventional spectrophotometer. Then, the spectrophotometric data are inputs to different regression algorithm models for training and evaluating high-accuracy nitrite concentration prediction. Our experimental results show that the proposed approach enables instantaneous nitrite detection within several seconds. The sensor hardware costs about one hundred dollars, which is much cheaper than a commercial spectrophotometer. The ML algorithm helps to reduce the average relative errors to below 3.5% over a concentration range from 0.1 ppm to 100 ppm of nitrites. The sensor has been validated to measure nitrites at three sites in Ames, Iowa, USA. This work demonstrates an economical and effective approach to the rapid, reagent-free determination of nitrites with high accuracy. The integration of the low-cost optical sensor and ML data processing can find a wide range of applications in environmental monitoring and management.

Keywords: optical sensor, regression model, nitrites, water quality

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Authors: Faizan Tariq, Moayid Ali Zaidi

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Facial emotion recognition algorithms are expanding rapidly now a day. People are using different algorithms with different combinations to generate best results. There are six basic emotions which are being studied in this area. Author tried to recognize the facial expressions using object detector algorithms instead of traditional algorithms. Two object detection algorithms were chosen which are Faster R-CNN and YOLO. For pre-processing we used image rotation and batch normalization. The dataset I have chosen for the experiments is Static Facial Expression in Wild (SFEW). Our approach worked well but there is still a lot of room to improve it, which will be a future direction.

Keywords: face recognition, emotion recognition, deep learning, CNN

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Authors: S. F. Kanaan, Fatima Al-Kadi, H. Khrais

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Background: Fibromyalgia is a chronic condition that is characterized by chronic pain that limits physical and functional activities. To our best knowledge, there is currently no key physiotherapy approach recommended to reduce pain and improve function. In addition, there are scarce studies that investigated the effect of manual therapy in the management of Fibromyalgia, and no study investigated the efficacy of Mulligan´s mobilization with movement (MWM) in particular. Methods: A 51-year-old female diagnosed with Fibromyalgia for more than a year. The patient was complaining of generalized pain including neck, lower back, shoulders, elbows, hips, and knees. In addition, the patient reported severe limitation in activities and inability to complete her work as a lawyer. The Intervention provided for the patient consisted of 4 sessions (in two weeks) of MWM for neck, lower back, shoulders, elbows, sacroiliac joint, hips, and knees. The Visual Analogue Scale of pain (VAS), Range of Motion (ROM), 10-minute walk test, Roland Morris Low Back Pain and Disability Questionnaire (RMQ), Disability of the Arm, Shoulder and Hand Score (DASH) were collected at the baseline and at the end of treatment. Results: Average improvement of ROM in the neck, lower back, shoulder, elbows, hips, and knees was 45%. VAS scale changed from pre-treatment to post-treatment as the following: neck pain (9 to 0), lower back pain (8 to 1), shoulders pain (8 to 2), elbows pain (7 to 1), and knees pain (9 to 0). The patient demonstrated improvement in all functional scale from pre-intervention to post-intervention: 10-meter walk test (9.8 to 4.5 seconds), RMQ (21 to 11/24), and DASH (88.7% to 40.5%). The patient did not report any side effect of using this approach. Conclusion: Fibromyalgia can cause joint 'faulty position' leading to pain and dysfunction, which can be reversed by using MWM. MWM showed to have clinically significant improvement in ROM, pain, and ability to walk and a clinically significant reduction in disability in only 4 sessions. This work can be expanded in a larger sample.

Keywords: mobilization, fibromyalgia, dysfunction, manual therapy

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Authors: David Nieto Simavilla, Wilco M. H. Verbeeten

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The viscoelastic behavior of polymeric flows under isothermal conditions has been extensively researched. However, most of the processing of polymeric materials occurs under non-isothermal conditions and understanding the linkage between the thermo-physical properties and the process state variables remains a challenge. Furthermore, the cost and energy required to manufacture, recycle and dispose polymers is strongly affected by the thermo-physical properties and their dependence on state variables such as temperature and stress. Experiments show that thermal conductivity in flowing polymers is anisotropic (i.e. direction dependent). This phenomenon has been previously omitted in the study and simulation of industrially relevant flows. Our work combines experimental evidence of a universal relationship between thermal conductivity and stress tensors (i.e. the stress-thermal rule) with differential constitutive equations for the viscoelastic behavior of polymers to provide predictions for the anisotropy in thermal conductivity in uniaxial, planar, equibiaxial and shear flow in commercial polymers. A particular focus is placed on the eXtended Pom-Pom model which is able to capture the non-linear behavior in both shear and elongation flows. The predictions provided by this approach are amenable to implementation in finite elements packages, since viscoelastic and thermal behavior can be described by a single equation. Our results include predictions for flow-induced anisotropy in thermal conductivity for low and high density polyethylene as well as confirmation of our method through comparison with a number of thermoplastic systems for which measurements of anisotropy in thermal conductivity are available. Remarkably, this approach allows for universal predictions of anisotropy in thermal conductivity that can be used in simulations of complex flows in which only the most fundamental rheological behavior of the material has been previously characterized (i.e. there is no need for additional adjusting parameters other than those in the constitutive model). Accounting for polymers anisotropy in thermal conductivity in industrially relevant flows benefits the optimization of manufacturing processes as well as the mechanical and thermal performance of finalized plastic products during use.

Keywords: anisotropy, differential constitutive models, flow simulations in polymers, thermal conductivity

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Authors: Dan Frederick Orcherton

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This research explores the fusion of "Critical Pedagogy of Place" and "Indigenous Education Philosophy" to create a holistic pedagogical framework within Instructional Theory, focusing on its application in Distance Education, specifically within two Pacific Island cultures. The study's objectives included investigating culturally relevant instructional techniques, strategies, and technologies for the Itaukei (Indigenous Fijian) and ni-Vanuatu cultures, enhancing appreciation for culturally sensitive pedagogical methods. Methodologically, a qualitative inquiry phenomenological approach was employed within a constructivist paradigm, utilizing a comprehensive qualitative scoping review and online literature search. Key findings include the prioritization of cultural inclusivity and indigenous knowledge integration in both indigenous education philosophies and various instructional approaches. Learner-centered methods like constructivist andragogy and the learning cycle are applicable and effective in distance education within these cultures, aligning with indigenous learners' values and preferences. Place-based education and critical pedagogy of place are particularly pertinent, fostering a deeper connection between education, local environments, and social justice. Integrating digital technologies in culturally responsive education bridges geographical gaps and preserves cultural knowledge. Lastly, blending Western and Indigenous Science, influenced by a Two-Eyed Seeing approach, informs pedagogy by combining Western and Indigenous Science. This research underscores the importance of acknowledging cultural diversity and respecting indigenous knowledge in distance education. It highlights the value of learner-centered approaches, place-based education, and technology integration. The study enriches the educational experience within the Itaukei and niVanuatu cultures and provides insights for educators and policymakers aiming to bridge cultural gaps in distance education.

Keywords: critical pedegory of place, Itaukei (indigenous Fijian) and ni-Vanuatu cultures, placed-based education, indigenous knowledge, distance education

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Authors: Majid Amidpour, Parisa Karimi, Marzieh Joda

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For the last few years, release of burned undesirable by-products has become a challenging issue in oil industries. Flaring, as one of the main sources of air contamination, involves detrimental and long-lasting effects on human health and is considered a substantial reason for energy losses worldwide. This research involves studying the implications of two main flare gas recovery methods at three oil refineries, all in Iran as the case I, case II, and case III in which the production capacities are increasing respectively. In the proposed methods, flare gases are converted into more valuable products, before combustion by the flare networks. The first approach involves collecting, compressing and converting the flare gas to smokeless fuel which can be used in the fuel gas system of the refineries. The other scenario includes utilizing the flare gas as a feed into liquefied petroleum gas (LPG) production unit already established in the refineries. The processes of these scenarios are simulated, and the capital investment is calculated for each procedure. The cumulative profits of the scenarios are evaluated using Net Present Value method. Furthermore, the sensitivity analysis based on total propane and butane mole fraction is carried out to make a rational comparison for LPG production approach, and the results are illustrated for different mole fractions of propane and butane. As the mole fraction of propane and butane contained in LPG differs in summer and winter seasons, the results corresponding to LPG scenario are demonstrated for each season. The results of the simulations show that cumulative profit in fuel gas production scenario and LPG production rate increase with the capacity of the refineries. Moreover, the investment return time in LPG production method experiences a decline, followed by a rising trend with an increase in C₃ and C₄ content. The minimum value of time return occurs at propane and butane sum concentration values of 0.7, 0.6, and 0.7 in case I, II, and III, respectively. Based on comparison of the time of investment return and cumulative profit, fuel gas production is the superior scenario for three case studies.

Keywords: flare gas reduction, liquefied petroleum gas, fuel gas, net present value method, sensitivity analysis

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Authors: Susana Sousa Machado

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The debate on the use of religious symbols has been highlighted in modern societies, especially in the field of labour relationships. As litigiousness appears to be growing, the matter requires a careful study from a legal perspective. In this context, a description and critical analysis of the most recent case law is conducted regarding the use of symbols by the employee in the workplace, delivered both by the European Court of Human Rights and by the Court of Justice of the European Union. From this comparative analysis we highlight the most relevant aspects in order to seek a common core regarding the juridical-argumentative approach of case law.

Keywords: religion, religious symbols, workplace, discrimination

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Authors: Niaz Gharavi, Hexin Zhang

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In the structural timber design, the shear modulus of the timber beam is an important factor that needs to be determined accurately. According to BS EN 408, shear modulus can be determined using torsion test or shear field test method. Although torsion test creates pure shear status in the beam, it does not represent the real-life situation when the beam is in the service. On the other hand, shear field test method creates similar loading situation as in reality. The latter method is based on shear distortion measurement of the beam at the zone with the constant transverse load in the standardized four-point bending test as indicated in BS EN 408. Current testing practice code advised using two metallic arms act as an instrument to measure the diagonal displacement of the constructing square. Timber is not a homogenous material, but a heterogeneous and this characteristic makes timber to undergo a non-uniform deformation. Therefore, the dimensions and the location of the constructing square in the area with the constant transverse force might alter the shear modulus determination. This study aimed to investigate the impact of the shape, size, and location of the square in the shear field test method. A binocular stereo vision system was developed to capture the 3D displacement of a grid of target points. This approach is an accurate and non-contact method to extract the 3D coordination of targeted object using two cameras. Two group of three glue laminated beams were produced and tested by the mean of four-point bending test according to BS EN 408. Group one constructed using two materials, laminated bamboo lumber and structurally graded C24 timber and group two consisted only structurally graded C24 timber. Analysis of Variance (ANOVA) was performed on the acquired data to evaluate the significance of size and location of the square in the determination of shear modulus of the beam. The results have shown that the size of the square is an affecting factor in shear modulus determination. However, the location of the square in the area with the constant shear force does not affect the shear modulus.

Keywords: shear field test method, BS EN 408, timber shear modulus, photogrammetry approach

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Authors: Pranjal Srivastava, Piyali Sengupta

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The performance of marine drilling risers is crucial in the offshore oil and gas industry to ensure safe drilling operation with minimum downtime. Experimental investigations on marine drilling risers are limited in the literature owing to the expensive and exhaustive test setup required to replicate the realistic riser model and ocean environment in the laboratory. Therefore, this study presents an analytical model of marine drilling riser for determining its fragility under ocean environmental loading. In this study, the marine drilling riser is idealized as a continuous beam having a concentric circular cross-section. Hydrodynamic loading acting on the marine drilling riser is determined by Morison’s equations. By considering the equilibrium of forces on the marine drilling riser for the connected and normal drilling conditions, the governing partial differential equations in terms of independent variables z (depth) and t (time) are derived. Subsequently, the Runge Kutta method and Finite Difference Method are employed for solving the partial differential equations arising from the analytical model. The proposed analytical approach is successfully validated with respect to the experimental results from the literature. From the dynamic analysis results of the proposed analytical approach, the critical design parameters peak displacements, upper and lower flex joint rotations and von Mises stresses of marine drilling risers are determined. An extensive parametric study is conducted to explore the effects of top tension, drilling depth, ocean current speed and platform drift on the critical design parameters of the marine drilling riser. Thereafter, incremental dynamic analysis is performed to derive the fragility functions of shallow water and deep-water marine drilling risers under ocean environmental loading. The proposed methodology can also be adopted for downtime estimation of marine drilling risers incorporating the ranges of uncertainties associated with the ocean environment, especially at deep and ultra-deepwater.

Keywords: drilling riser, marine, analytical model, fragility

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Authors: Deepa Kapoor, Rajshree Singh

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This paper appreciates the emergence and growing importance as a new production factor makes the development of technologies, methodologies and strategies for measurement, creation, and diffusion into one of the main priorities of the organizations in the knowledge society. There are many models for creation and management of knowledge and diverse and varied perspectives for study, analysis, and understanding. In this article, we will conduct a theoretical approach to the type of models for the creation and management of knowledge; we will discuss some of them and see some of the difficulties and the key factors that determine the success of the processes for the creation and management of knowledge.

Keywords: knowledge creation, knowledge management, organizational development, organization learning

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Authors: Sebastian van Delden, Matthew Anuszkiewicz, Jayse White, Scott Stolarski

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Industrial robotic manipulators have been commonplace in the manufacturing world since the early 1960s, and unmanned aerial vehicles (drones) have only begun to realize their full potential in the service industry and the military. The omnipresence of these technologies in their respective fields will only become more potent in coming years. While these technologies have greatly evolved over the years, the typical approach to human interaction with these robots has not. In the industrial robotics realm, a manipulator is typically jogged around using a teach pendant and programmed using a networked computer or the teach pendant itself via a proprietary software development platform. Drones are typically controlled using a two-handed controller equipped with throttles, buttons, and sticks, an app that can be downloaded to one’s mobile device, or a combination of both. This application-oriented work offers a novel approach to human interaction with both unmanned aerial vehicles and industrial robotic manipulators via hand gestures and movements. Two systems have been implemented, both of which use a Myo™ armband to control either a drone (DJI Spark™) or a robotic arm (Stäubli™ TX40). The methodologies developed by this work present a mapping of armband gestures (fist, finger spread, swing hand in, swing hand out, swing arm left/up/down/right, etc.) to either drone or robot arm movements. The findings of this study present the efficacy and limitations (precision and ergonomic) of hand gesture control of two distinct types of robotic technology. All source code associated with this project will be open sourced and placed on GitHub. In conclusion, this study offers a framework that maps hand and arm gestures to drone and robot arm control. The system has been implemented using current ubiquitous technologies, and these software artifacts will be open sourced for future researchers or practitioners to use in their work.

Keywords: human robot interaction, drones, gestures, robotics

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Authors: Dirson Santos De Campos, Deller James Ferreira, Anderson Cavalcante Gonçalves, Uyara Ferreira Silva

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Rubrics to learning research provide many evaluation criteria and expected performance standards linked to defined student activity for learning and pedagogical objectives. Despite the rubric being used in education at all levels, academic literature on rubrics as a tool to support research in SQL Education is quite rare. There is a large class of SQL queries is syntactically correct, but certainly, not all are semantically correct. Detecting and correcting errors is a recurring problem in SQL education. In this paper, we usthe Rubric Abstract Framework (RAF), which consists of steps, that allows us to map the information to measure student performance guided by didactic objectives defined by the teacher as long as it is contextualized domain modeling by rubric. An empirical study was done that demonstrates how rubrics can mitigate student difficulties in finding logical errors and easing teacher workload in SQL education. Detecting and correcting logical errors is an important skill for students. Researchers have proposed several ways to improve SQL education because understanding this paradigm skills are crucial in software engineering and computer science. The RAF instantiation was using in an empirical study developed during the COVID-19 pandemic in database course. The pandemic transformed face-to-face and remote education, without presential classes. The lab activities were conducted remotely, which hinders the teaching-learning process, in particular for this research, in verifying the evidence or statements of knowledge, skills, and abilities (KSAs) of students. Various research in academia and industry involved databases. The innovation proposed in this paper is the approach used where the results obtained when using rubrics to map logical errors in query formulation have been analyzed with gains obtained by students empirically verified. The research approach can be used in the post-pandemic period in both classroom and distance learning.

Keywords: rubric, logical error, structured query language (SQL), empirical study, SQL education

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Authors: Elnaz Kanani-Kuchesfehani, Andrea Schiffauerova

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Due to the novelty of the nanotechnology science, its highly knowledge intensive content, and its invaluable application in almost all technological fields, the close interaction between university and industry is essential. A possible gap between academic strengths to generate good nanotechnology ideas and industrial capacity to receive them can thus have far-reaching consequences. In order to be able to enhance the collaboration between the two parties, a better understanding of knowledge transfer within the university-industry relationship is needed. The objective of this research is to investigate the research collaboration between academia and industry in Canadian nanotechnology and to propose the best cooperative strategy to maximize the quality of the produced knowledge. First, a network of all Canadian academic and industrial nanotechnology inventors is constructed using the patent data from the USPTO (United States Patent and Trademark Office), and it is analyzed with social network analysis software. The actual level of university-industry collaboration in Canadian nanotechnology is determined and the significance of each group of actors in the network (academic vs. industrial inventors) is assessed. Second, a novel methodology is proposed, in which the network of nanotechnology inventors is assessed from a game theoretic perspective. It involves studying a cooperative game with n players each having at most n-1 decisions to choose from. The equilibrium leads to a strategy for all the players to choose their co-worker in the next period in order to maximize the correlated payoff of the game. The payoffs of the game represent the quality of the produced knowledge based on the citations of the patents. The best suggestion for the next collaborative relationship is provided for each actor from a game theoretic point of view in order to maximize the quality of the produced knowledge. One of the major contributions of this work is the novel approach which combines game theory and social network analysis for the case of large networks. This approach can serve as a powerful tool in the analysis of the strategic interactions of the network actors within the innovation systems and other large scale networks.

Keywords: cooperative strategy, game theory, industry-university collaboration, knowledge production, social network analysis

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Authors: Maelle Noir

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International Human rights norms prescribe the obligation to protect refugee women against violence which requires, inter alia, state provision of justiciable, accessible, affordable and non-discriminatory access to justice. However, the interpretation and application of the law still lack gender sensitivity, intersectionality and a trauma-informed approach. Consequently, many refugee survivors face important structural obstacles preventing access to justice and often experience secondary traumatisation when navigating the legal system. This paper argues that the unique nature of the experiences of refugees with gender-based violence against women exacerbated throughout the migration journey calls for a tailored practice of the law to ensure adequate access to justice. The argument developed here is that the obligation to provide survivors with justiciable, accessible, affordable and non-discriminatory access to justice implies radically transforming the practice of the law altogether. This paper, therefore, proposes feminist lawyering as an alternative approach to the practice of the law when addressing gender-based violence against women refugees. First, this paper discusses the specific nature of gender-based violence against refugees with a particular focus on two aspects of the power-violence nexus: the analysis of the shift in gender roles and expectations following displacement as one of the causes of gender-based violence against women refugees and the argument that the asylum situation itself constitutes a form of state-sponsored and institutional violence. Second, the re-traumatising and re-victimising nature of the legal system is explored with the objective to demonstrate States’ failure to comply with their legal obligation to provide refugee women with effective access to justice. Third, this paper discusses some key practical strategies that have been proposed and implemented to transform the practice of the law when dealing with gender-based violence outside of the refugee context. Lastly, this analysis is applied to the specificities of the experiences of refugee survivors of gender-based violence.

Keywords: feminist lawyering, feminist legal theory, gender-based violence, human rights law, intersectionality, refugee protection

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Authors: Simona Lucakova, Irena Branyikova

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Eutrophication, a condition when water becomes over-enriched with nutrients (P, N), can lead to undesirable excessive growth of phytoplankton, so-called algal bloom. This process results in the accumulation of toxin-producing cyanobacteria and oxygen depletion, both possibly leading to the collapse of the whole ecosystem. In real conditions, the limiting nutrient, which determines the possible growth of harmful algal bloom, is usually phosphorus. Algicides or flocculants have been applied in the eutrophicated waterbody in order to reduce the phytoplankton growth, which leads to the introduction of toxic chemicals into the water. In our laboratory, the idea of the prevention of harmful phytoplankton growth by the intentional cultivation of non-toxic cyanobacteria Tolypothrix tenuis in semi-open floating photobioreactors directly on the surface of phosphorus-rich waterbody is examined. During the process of cultivation, redundant phosphorus is incorporated into cyanobacterial biomass, which can be subsequently used for the production of biofuels, cosmetics, pharmaceuticals, or biostimulants for agricultural use. To determine the ability of phosphorus incorporation, batch-cultivation of Tolypothrix biomass in media simulating eutrophic water (10% BG medium) and in effluent from municipal wastewater treatment plant, both with the initial phosphorus concentration in the range 0.5-1.0 mgP/L was performed in laboratory-scale models of floating photobioreactors. After few hours of cultivation, the phosphorus content was decreased below the target limit of 0.035 mgP/L, which was given as a borderline for the algal bloom formation. Under laboratory conditions, the effect of several parameters on the rate of phosphorus decrease was tested (illumination, temperature, stirring speed/aeration gas flow, biomass to medium ratio). Based on the obtained results, a bench-scale floating photobioreactor was designed and will be tested for Tolypothrix growth in real conditions. It was proved that intentional cultivation of cyanobacteria Tolypothrix could be a suitable approach for extracting redundant phosphorus from eutrophic waters as prevention of algal bloom formation.

Keywords: cyanobacteria, eutrophication, floating photobioreactor, Tolypothrix

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Authors: Jungyeol Hong, Dongjoo Park

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The urban transit system is a critical part of a solution to the economic, energy, and environmental challenges. Furthermore, it ultimately contributes the improvement of people’s quality of lives. For taking these kinds of advantages, the city of Seoul has tried to construct an integrated transit system including both subway and buses. The effort led to the fact that approximately 6.9 million citizens use the integrated transit system every day for their trips. Diagnosing the current transit network is a significant task to provide more convenient and pleasant transit environment. Therefore, the critical objective of this study is to establish a methodological framework for the analysis of an integrated bus-subway network and to examine the relationship between subway ridership and parameters such as network topology measures, bus demand, and a variety of commercial business facilities. Regarding a statistical approach to estimate subway ridership at a station level, many previous studies relied on Ordinary Least Square regression, but there was lack of studies considering the endogeneity issues which might show in the subway ridership prediction model. This study focused on both discovering the impacts of integrated transit network topology measures and endogenous effect of bus demand on subway ridership. It could ultimately contribute to developing more accurate subway ridership estimation accounting for its statistical bias. The spatial scope of the study covers Seoul city in South Korea, and it includes 243 subway stations and 10,120 bus stops with the temporal scope set during twenty-four hours with one-hour interval time panels each. The subway and bus ridership information in detail was collected from the Seoul Smart Card data in 2015 and 2016. First, integrated subway-bus network topology measures which have characteristics regarding connectivity, centrality, transitivity, and reciprocity were estimated based on the complex network theory. The results of integrated transit network topology analysis were compared to subway-only network topology. Also, the non-recursive approach which is Three-Stage Least Square was applied to develop the daily subway ridership model as capturing the endogeneity between bus and subway demands. Independent variables included roadway geometry, commercial business characteristics, social-economic characteristics, safety index, transit facility attributes, and dummies for seasons and time zone. Consequently, it was found that network topology measures were significant size effect. Especially, centrality measures showed that the elasticity was a change of 4.88% for closeness centrality, 24.48% for betweenness centrality while the elasticity of bus ridership was 8.85%. Moreover, it was proved that bus demand and subway ridership were endogenous in a non-recursive manner as showing that predicted bus ridership and predicted subway ridership is statistically significant in OLS regression models. Therefore, it shows that three-stage least square model appears to be a plausible model for efficient subway ridership estimation. It is expected that the proposed approach provides a reliable guideline that can be used as part of the spectrum of tools for evaluating a city-wide integrated transit network.

Keywords: integrated transit system, network topology measures, three-stage least squared, endogeneity, subway ridership

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Authors: Emmanuel Benjamin, Matthias Blum

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Purpose – We address smallholder farmers’ restricted possibilities to adopt sustainable technologies which have direct and indirect benefits. Smallholders often face little asset endowment due to small farm size und insecure property rights, therefore experiencing constraints in adopting agricultural innovation. A program involving payments for ecosystem services (PES) benefits poor smallholder farmers in developing countries in many ways and has been suggested as a means of easing smallholder farmers’ financial constraints. PES may also provide additional mainstay which can eventually result in more favorable credit contract terms due to the availability of collateral substitute. Results of this study may help to understand the barriers, motives and incentives for smallholders’ participation in PES and help in designing a strategy to foster participation in beneficial programs. Design/methodology/approach – This paper uses a random utility model and a logistic regression approach to investigate factors that influence agroforestry adoption. We investigate non-monetary factors, such as information spillover, that influence the decision to adopt such conservation strategies. We collected original data from non-government-run agroforestry mitigation programs with PES that have been implemented in the Mount Kenya region. Preliminary Findings – We find that spread of information, existing networks and peer involvement in such programs drive participation. Conversely, participation by smallholders does not seem to be influenced by education, land or asset endowment. Contrary to some existing literature, we found weak evidence for a positive correlation between the adoption of agroforestry with PES and age of smallholder, e.g., one increases with the other, in the Mount Kenyan region. Research implications – Poverty alleviation policies for developing countries should target social capital to increase the adoption rate of modern technologies amongst smallholders.

Keywords: agriculture innovation, agroforestry adoption, smallholders, payment for ecosystem services, Sub-Saharan Africa

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Authors: A. Odoom, A. Salama, H. Ibrahim

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Hydrogen is a clean source of energy for power production and transportation. The main source of hydrogen in this research is biodiesel. Glycerol also called glycerine is a by-product of biodiesel production by transesterification of vegetable oils and methanol. This is a reliable and environmentally-friendly source of hydrogen production than fossil fuels. A typical composition of crude glycerol comprises of glycerol, water, organic and inorganic salts, soap, methanol and small amounts of glycerides. Crude glycerol has limited industrial application due to its low purity thus, the usage of crude glycerol can significantly enhance the sustainability and production of biodiesel. Reforming techniques is an approach for hydrogen production mainly Steam Reforming (SR), Autothermal Reforming (ATR) and Partial Oxidation Reforming (POR). SR produces high hydrogen conversions and yield but is highly endothermic whereas POR is exothermic. On the downside, PO yields lower hydrogen as well as large amount of side reactions. ATR which is a fusion of partial oxidation reforming and steam reforming is thermally neutral because net reactor heat duty is zero. It has relatively high hydrogen yield, selectivity as well as limits coke formation. The complex chemical processes that take place during the production phases makes it relatively difficult to construct a reliable and robust numerical model. Numerical model is a tool to mimic reality and provide insight into the influence of the parameters. In this work, we introduce a finite volume numerical study for an 'in-house' lab-scale experiment of ATR. Previous numerical studies on this process have considered either using Comsol or nodal finite difference analysis. Since Comsol is a commercial package which is not readily available everywhere and lab-scale experiment can be considered well mixed in the radial direction. One spatial dimension suffices to capture the essential feature of ATR, in this work, we consider developing our own numerical approach using MATLAB. A continuum fixed bed reactor is modelled using MATLAB with both pseudo homogeneous and heterogeneous models. The drawback of nodal finite difference formulation is that it is not locally conservative which means that materials and momenta can be generated inside the domain as an artifact of the discretization. Control volume, on the other hand, is locally conservative and suites very well problems where materials are generated and consumed inside the domain. In this work, species mass balance, Darcy’s equation and energy equations are solved using operator splitting technique. Therefore, diffusion-like terms are discretized implicitly while advection-like terms are discretized explicitly. An upwind scheme is adapted for the advection term to ensure accuracy and positivity. Comparisons with the experimental data show very good agreements which build confidence in our modeling approach. The models obtained were validated and optimized for better results.

Keywords: autothermal reforming, crude glycerol, hydrogen, numerical model

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Authors: Samara E., Kilintzis P., Katsoras E., Martinidis G.

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Regions play an important role in the global economy by driving research and innovation policies through a major tool, the Regional Innovation System (RIS). RIS is a social system that encompasses the systematic interaction of the various organizations that comprise it in order to improve local knowledge and innovation. This article describes the methodological framework for developing and validating a RIS model utilizing system dynamics. This model focuses on the functional structure of the RIS, separating it in six diverse, interacting sub-systems.

Keywords: innovations, regional development, systems thinking, social system

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