Search results for: domain wall

Authors: Hamed Movahedi, Nicolas Bovet, Henning Friis Poulsen

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Following the advent of the Industrial Revolution, there has been a significant increase in the extraction and utilization of hydrocarbon and fossil fuel resources. However, a new era has emerged, characterized by a shift towards sustainable practices, namely the reduction of carbon emissions and the promotion of renewable energy generation. Given the substantial number of mature oil and gas wells that have been developed inside the petroleum reservoir domain, it is imperative to establish an environmental strategy and adopt appropriate measures to effectively seal and decommission these wells. In general, the cement plug serves as a material for plugging purposes. Nevertheless, there exist some scenarios in which the durability of such a plug is compromised, leading to the potential escape of hydrocarbons via fissures and fractures within cement plugs. Furthermore, cement is often not considered a practical solution for temporary plugging, particularly in the case of well sites that have the potential for future gas storage or CO2 injection. The Danish oil and gas industry has promising potential as a prospective candidate for future carbon dioxide (CO2) injection, hence contributing to the implementation of carbon capture strategies within Europe. The primary reservoir component consists of chalk, a rock characterized by limited permeability. This work focuses on the development and characterization of a novel hydrogel variant. The hydrogel is designed to be injected via a low-permeability reservoir and afterward undergoes a transformation into a high-viscosity gel. The primary objective of this research is to explore the potential of this hydrogel as a new solution for effectively plugging well flow. Initially, the synthesis of polyacrylamide was carried out using radical polymerization inside the confines of the reaction flask. Subsequently, with the application of the Hoffman rearrangement, the polymer chain undergoes partial amination, facilitating its subsequent reaction with the crosslinker and enabling the formation of a hydrogel in the subsequent stage. The organic crosslinker, glutaraldehyde, was employed in the experiment to facilitate the formation of a gel. This gel formation occurred when the polymeric solution was subjected to heat within a specified range of reservoir temperatures. Additionally, a rheological survey and gel time measurements were conducted on several polymeric solutions to determine the optimal concentration. The findings indicate that the gel duration is contingent upon the starting concentration and exhibits a range of 4 to 20 hours, hence allowing for manipulation to accommodate diverse injection strategies. Moreover, the findings indicate that the gel may be generated in environments characterized by acidity and high salinity. This property ensures the suitability of this substance for application in challenging reservoir conditions. The rheological investigation indicates that the polymeric solution exhibits the characteristics of a Herschel-Bulkley fluid with somewhat elevated yield stress prior to solidification.

Keywords: polyacrylamide, hofmann rearrangement, rheology, gel time

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Authors: Colin Schmidt, Adrien Lecossier, Pascal Crubleau, Philippe Blanchard, Simon Richir

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Introduction:The widespread availability of artificial intelligence, exemplified by Generative Pre-trained Transformers (GPT) relying on large language models (LLM), has caused a seismic shift in the realm of knowledge. Everyone now has the capacity to swiftly learn how these models can either serve them well or not. Today, conversational AI like ChatGPT is grounded in neural transformer models, a significant advance in natural language processing facilitated by the emergence of renowned LLMs constructed using neural transformer architecture. Inventiveness of an LLM : OpenAI's GPT-3 stands as a premier LLM, capable of handling a broad spectrum of natural language processing tasks without requiring fine-tuning, reliably producing text that reads as if authored by humans. However, even with an understanding of how LLMs respond to questions asked, there may be lurking behind OpenAI’s seemingly endless responses an inventive model yet to be uncovered. There may be some unforeseen reasoning emerging from the interconnection of neural networks here. Just as a Soviet researcher in the 1940s questioned the existence of Common factors in inventions, enabling an Under standing of how and according to what principles humans create them, it is equally legitimate today to explore whether solutions provided by LLMs to complex problems also share common denominators. Theory of Inventive Problem Solving (TRIZ) : We will revisit some fundamentals of TRIZ and how Genrich ALTSHULLER was inspired by the idea that inventions and innovations are essential means to solve societal problems. It's crucial to note that traditional problem-solving methods often fall short in discovering innovative solutions. The design team is frequently hampered by psychological barriers stemming from confinement within a highly specialized knowledge domain that is difficult to question. We presume ChatGPT Utilizes TRIZ 40. Hence, the objective of this research is to decipher the inventive model of LLMs, particularly that of ChatGPT, through a comparative study. This will enhance the efficiency of sustainable innovation processes and shed light on how the construction of a solution to a complex problem was devised. Description of the Experimental Protocol : To confirm or reject our main hypothesis that is to determine whether ChatGPT uses TRIZ, we will follow a stringent protocol that we will detail, drawing on insights from a panel of two TRIZ experts. Conclusion and Future Directions : In this endeavor, we sought to comprehend how an LLM like GPT addresses complex challenges. Our goal was to analyze the inventive model of responses provided by an LLM, specifically ChatGPT, by comparing it to an existing standard model: TRIZ 40. Of course, problem solving is our main focus in our endeavours.

Keywords: artificial intelligence, Triz, ChatGPT, inventiveness, problem-solving

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Authors: Sumita Srivastava

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Despite several measures taken by the Government of India, entrepreneurship is still not perceived as a viable career option by the young generation. Although the rate of startups has improved a little after the penetration of e portals as business platforms, still the numbers are not very significant. It is also important to note that entrepreneurial initiatives are mostly taken up by graduates of premier institutions of India like Indian Institute of Technology (IITs) and Indian Institute of Management (IIMs). The scenario is not very satisfactory amongst the masses graduating from mainstream universities of the country. Indian youth at large are not attracted towards entrepreneurship as a career choice. The reason probably lies in the social fabric of the country and inappropriate education system which does not support the entrepreneurship at large amongst youth in the country. Education is critical to the development of an economy from the poverty level to the level of self-sustenance and development. The current curriculum in the majority of business schools in India prepares the average graduate to become employed by the available firms or business owners in society. For graduates in other streams, employment opportunities are very limited. The aim of this study was to identify and design entrepreneurship education contents to encourage undergraduates to pursue entrepreneurship as a career choice. This comprehensive study was conducted in multiple stages. Extensive research was conducted at each stage with an appropriate methodology. These stages of the project study were interconnected with each other, and each preceding stage provided inputs for the following stage of the study. In the first stage of the study, an empirical analysis was conducted to understand the current state of entrepreneurial intentions of undergraduates of Agra city. Various stakeholders were contacted at the stage, including students (n = 500), entrepreneurs (n = 20) and academicians and field experts (n = 10). At the second stage of the project study, a systems science technique, Nominal Group Technique (NGT) was used to identify the critical elements of entrepreneurship education in India based upon the findings of stage 1. The application of the Nominal Group Technique involved a workshop format; 15 domain experts participated in the workshop. Throughout the process, a democratic process was followed to avoid individual dominance and premature focusing on a single idea. The study obtained 63 responses from experts for effective entrepreneurship education in India. The responses were reduced to seven elements after a few thematic iterations. These elements were then segregated into content (knowledge, skills and attitude) and learning interaction on the basis of experts’ responses. After identifying critical elements of entrepreneurship education in the previous stage, the course was designed and validated at stage 3 of the project. Scientific methods were used at this stage to validate the curriculum contents and training interventions experimentally. The educational and training interventions designed through this study would not only help in developing entrepreneurial intentions but also creating skills relevant to the local entrepreneurial opportunities in the vicinity.

Keywords: curriculum design, entrepreneurial intention, entrepreneuship education, nominal group technique

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Authors: L. Raczynski, P. Moskal, P. Kowalski, W. Wislicki, T. Bednarski, P. Bialas, E. Czerwinski, A. Gajos, L. Kaplon, A. Kochanowski, G. Korcyl, J. Kowal, T. Kozik, W. Krzemien, E. Kubicz, Sz. Niedzwiecki, M. Palka, Z. Rudy, O. Rundel, P. Salabura, N.G. Sharma, M. Silarski, A. Slomski, J. Smyrski, A. Strzelecki, A. Wieczorek, M. Zielinski, N. Zon

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The J-PET scanner, which allows for single bed imaging of the whole human body, is currently under development at the Jagiellonian University. The J-PET detector improves the TOF resolution due to the use of fast plastic scintillators. Since registration of the waveform of signals with duration times of few nanoseconds is not feasible, a novel front-end electronics allowing for sampling in a voltage domain at four thresholds was developed. To take fully advantage of these fast signals a novel scheme of recovery of the waveform of the signal, based on ideas from the Tikhonov regularization (TR) and Compressive Sensing methods, is presented. The prior distribution of sparse representation is evaluated based on the linear transformation of the training set of waveform of the signals by using the Principal Component Analysis (PCA) decomposition. Beside the advantage of including the additional information from training signals, a further benefit of the TR approach is that the problem of signal recovery has an optimal solution which can be determined explicitly. Moreover, from the Bayes theory the properties of regularized solution, especially its covariance matrix, may be easily derived. This step is crucial to introduce and prove the formula for calculations of the signal recovery error. It has been proven that an average recovery error is approximately inversely proportional to the number of samples at voltage levels. The method is tested using signals registered by means of the single detection module of the J-PET detector built out from the 30 cm long BC-420 plastic scintillator strip. It is demonstrated that the experimental and theoretical functions describing the recovery errors in the J-PET scenario are largely consistent. The specificity and limitations of the signal recovery method in this application are discussed. It is shown that the PCA basis offers high level of information compression and an accurate recovery with just eight samples, from four voltage levels, for each signal waveform. Moreover, it is demonstrated that using the recovered waveform of the signals, instead of samples at four voltage levels alone, improves the spatial resolution of the hit position reconstruction. The experiment shows that spatial resolution evaluated based on information from four voltage levels, without a recovery of the waveform of the signal, is equal to 1.05 cm. After the application of an information from four voltage levels to the recovery of the signal waveform, the spatial resolution is improved to 0.94 cm. Moreover, the obtained result is only slightly worse than the one evaluated using the original raw-signal. The spatial resolution calculated under these conditions is equal to 0.93 cm. It is very important information since, limiting the number of threshold levels in the electronic devices to four, leads to significant reduction of the overall cost of the scanner. The developed recovery scheme is general and may be incorporated in any other investigation where a prior knowledge about the signals of interest may be utilized.

Keywords: plastic scintillators, positron emission tomography, statistical analysis, tikhonov regularization

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Authors: Weijing Zhou, Yuting Lei, Francis Nolan

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In the domain of second language acquisition, whenever pronunciation errors or acquisition difficulties are found, researchers habitually attribute them to the negative transfer of the native language or local dialect. To what extent do Mandarin and local dialects affect English phonological acquisition for Chinese learners of English as a foreign language (EFL)? Little evidence, however, has been found via empirical research in China. To address this core issue, the present study conducted phonetic experiments to explore the roles of local dialects and Mandarin in Chinese EFL learners’ acquisition of L2 English consonants. Besides Mandarin, the sole national language in China, Suzhou dialect was selected as the target local dialect because of its distinct phonology from Mandarin. The experimental group consisted of 30 junior English majors at Yangzhou University, who were born and lived in Suzhou, acquired Suzhou Dialect since their early childhood, and were able to communicate freely and fluently with each other in Suzhou Dialect, Mandarin as well as English. The consonantal target segments were all the consonants of English, Mandarin and Suzhou Dialect in typical carrier words embedded in the carrier sentence Say again. The control group consisted of two Suzhou Dialect experts, two Mandarin radio broadcasters, and two British RP phoneticians, who served as the standard speakers of the three languages. The reading corpus was recorded and sampled in the phonetic laboratories at Yangzhou University, Soochow University and Cambridge University, respectively, then transcribed, segmented and analyzed acoustically via Praat software, and finally analyzed statistically via EXCEL and SPSS software. The main findings are as follows: First, in terms of correct acquisition rates (CARs) of all the consonants, Mandarin ranked top (92.83%), English second (74.81%) and Suzhou Dialect last (70.35%), and significant differences were found only between the CARs of Mandarin and English and between the CARs of Mandarin and Suzhou Dialect, demonstrating Mandarin was overwhelmingly more robust than English or Suzhou Dialect in subjects’ multilingual phonological ecology. Second, in terms of typical acoustic features, the average duration of all the consonants plus the voice onset time (VOT) of plosives, fricatives, and affricatives in 3 languages were much longer than those of standard speakers; the intensities of English fricatives and affricatives were higher than RP speakers but lower than Mandarin and Suzhou Dialect standard speakers; the formants of English nasals and approximants were significantly different from those of Mandarin and Suzhou Dialects, illustrating the inconsistent acoustic variations between the 3 languages. Thirdly, in terms of typical pronunciation variations or errors, there were significant interlingual interactions between the 3 consonant systems, in which Mandarin consonants were absolutely dominant, accounting for the strong transfer from L1 Mandarin to L2 English instead of from earlier-acquired L1 local dialect to L2 English. This is largely because the subjects were knowingly exposed to Mandarin since their nursery and were strictly required to speak in Mandarin through all the formal education periods from primary school to university.

Keywords: acquisition of L2 English consonants, role of Mandarin, role of local dialect, Chinese EFL learners from Suzhou Dialect areas

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Authors: Takoua Soltani, Imen Soltani, Taoufik Aguili

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The communications' and radar systems' demands give rise to new developments in the domain of active integrated antennas (AIA) and arrays. The main advantages of AIA arrays are the simplicity of fabrication, low cost of manufacturing, and the combination between free space power and the scanner without a phase shifter. The integrated active antenna modeling is the coupling between the electromagnetic model and the transport model that will be affected in the high frequencies. Global modeling of active circuits is important for simulating EM coupling, interaction between active devices and the EM waves, and the effects of EM radiation on active and passive components. The current review focuses on the modeling of the active element which is a MESFET transistor immersed in a rectangular waveguide. The proposed EM analysis is based on the Method of Moments combined with the Generalised Equivalent Circuit method (MOM-GEC). The Method of Moments which is the most common and powerful software as numerical techniques have been used in resolving the electromagnetic problems. In the class of numerical techniques, MOM is the dominant technique in solving of Maxwell and Transport’s integral equations for an active integrated antenna. In this situation, the equivalent circuit is introduced to the development of an integral method formulation based on the transposition of field problems in a Generalised equivalent circuit that is simpler to treat. The method of Generalised Equivalent Circuit (MGEC) was suggested in order to represent integral equations circuits that describe the unknown electromagnetic boundary conditions. The equivalent circuit presents a true electric image of the studied structures for describing the discontinuity and its environment. The aim of our developed method is to investigate the antenna parameters such as the input impedance and the current density distribution and the electric field distribution. In this work, we propose a global EM modeling of the MESFET AsGa transistor using an integral method. We will begin by describing the modeling structure that allows defining an equivalent EM scheme translating the electromagnetic equations considered. Secondly, the projection of these equations on common-type test functions leads to a linear matrix equation where the unknown variable represents the amplitudes of the current density. Solving this equation resulted in providing the input impedance, the distribution of the current density and the electric field distribution. From electromagnetic calculations, we were able to present the convergence of input impedance for different test function number as a function of the guide mode numbers. This paper presents a pilot study to find the answer to map out the variation of the existing current evaluated by the MOM-GEC. The essential improvement of our method is reducing computing time and memory requirements in order to provide a sufficient global model of the MESFET transistor.

Keywords: active integrated antenna, current density, input impedance, MESFET transistor, MOM-GEC method

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Authors: Razieh Karimi Aghcheh, Christian Kubicek, Joseph Strauss, Gerhard Braus

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Filamentous fungi are of considerable economic and social significance for human health, nutrition and in white biotechnology. These organisms are dominant producers of a range of primary metabolites such as citric acid, microbial lipids (biodiesel) and higher unsaturated fatty acids (HUFAs). In particular, they produce also important but structurally complex secondary metabolites with enormous therapeutic applications in pharmaceutical industry, for example: cephalosporin, penicillin, taxol, zeranol and ergot alkaloids. Several fungal secondary metabolites, which are significantly relevant to human health do not only include antibiotics, but also e.g. lovastatin, a well-known antihypercholesterolemic agent produced by Aspergillus. terreus, or aflatoxin, a carcinogen produced by A. flavus. In addition to their roles for human health and agriculture, some fungi are industrially and commercially important: Species of the ascomycete genus Hypocrea spp. (teleomorph of Trichoderma) have been demonstrated as efficient producer of highly active cellulolytic enzymes. This trait makes them effective in disrupting and depolymerization of lignocellulosic materials and thus applicable tools in number of biotechnological areas as diverse as clothes-washing detergent, animal feed, and pulp and fuel productions. Fungal LaeA/LAE1 (Loss of aflR Expression A) homologs their gene products act at the interphase between secondary metabolisms, cellulase production and development. Lack of the corresponding genes results in significant physiological changes including loss of secondary metabolite and lignocellulose degrading enzymes production. At the molecular level, the encoded proteins are presumably methyltransferases or demethylases which act directly or indirectly at heterochromatin and interact with velvet domain proteins. Velvet proteins bind to DNA and affect expression of secondary metabolites (SMs) genes and cellulases. The dynamic interplay between LaeA/LAE1, velvet proteins and additional interaction partners is the key for an understanding of the coordination of metabolic and morphological functions of fungi and is required for a biotechnological control of the formation of desired bioactive products. Aspergilli and Trichoderma represent different biotechnologically significant species with significant differences in the LaeA/LAE1-Velvet protein machinery and their target proteins. We, therefore, performed a comparative study of the interaction partners of this machinery and the dynamics of the various protein-protein interactions using our robust proteomic and mass spectrometry techniques. This enhances our knowledge about the fungal coordination of secondary metabolism, cellulase production and development and thereby will certainly improve recombinant fungal strain construction for the production of industrial secondary metabolite or lignocellulose hydrolytic enzymes.

Keywords: cellulases, LaeA/1, proteomics, secondary metabolites

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Authors: Ammar Asma, Bouafia Nabiha, Dhahri Meriem, Ben Cheikh Asma, Ezzi Olfa, Chafai Rim, Njah Mansour

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Despite recent advances in treatment of the lung cancer patients, the prognosis remains poor. Information is limited regarding health related quality of life (QOL) status of advanced lung cancer patients. The purposes of this study were: to assess patient reported symptom burden, to measure their QOL, and to identify determinant factors associated with QOL. Materials/Methods: A cross sectional study of 60 patients was carried out from over the period of 03 months from February 1st to 30 April 2016. Patients were recruited in two department of health care: Pneumology department in a university hospital in Sousse and an oncology unit in a University Hospital in Kairouan. Patients with advanced stage (III and IV) of lung cancer who were hospitalized or admitted in the day hospital were recruited by convenience sampling. We used a questionnaire administrated and completed by a trained interviewer. This questionnaire is composed of three parts: demographic, clinical and therapeutic information’s, QOL measurements: based on the SF-36 questionnaire, Symptom’s burden measurement using the Lung Cancer Symptom Scale (LCSS). To assess Correlation between symptoms burden and QOL, we compared the scores of two scales two by two using the Pearson correlation. To identify factors influencing QOL in Lung cancer, a univariate statistical analysis then, a stepwise backward approach, wherein the variables with p< 0.2, were carried out to determine the association between SF-36 scores and different variables. Results: During the study period, 60 patients consented to complete symptom and quality of life questionnaires at a single point time (72% were recruited from day hospital). The majority of patients were male (88%), age ranged from 21 to 79 years with a mean of 60.5 years. Among patients, 48 (80%) were diagnosed as having non-small cell lung carcinoma (NSCLC). Approximately, 60 % (n=36) of patients were in stage IV, 25 % in stage IIIa and 15 % in stage IIIb. For symptom burden, the symptom burden index was 43.07 (Standard Deviation, 21.45). Loss of appetite and fatigue were rated as the most severe symptoms with mean scores (SD): 49.6 (25.7) and 58.2 (15.5). The average overall score of SF36 was 39.3 (SD, 15.4). The physical and emotional limitations had the lowest scores. Univariate analysis showed that factors which influence negatively QOL were: married status (p<0.03), smoking cessation after diagnosis (p<0.024), LCSS total score (p<0.001), LCSS symptom burden index (p<0.001), fatigue (p<0.001), loss of appetite (p<0.001), dyspnea (p<0.001), pain (p<0.002), and metastatic stage (p<0.01). In multivariate analysis, unemployment (p<0.014), smoking cessation after diagnosis (p<0.013), consumption of analgesic (p<0.002) and the indication of an analgesic radiotherapy (p<0.001) are revealed as independent determinants of QOL. The result of the correlation analyses between total LCSS scores and the total and individual domain SF36 scores was significant (p<0.001); the higher total LCSS score is, the poorer QOL is. Conclusion: A built in support of lung cancer patients would better control the symptoms and promote the QOL of these patients.

Keywords: quality of life, lung cancer, metastasis, symptoms burden

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Authors: Lalanthica Yogendran, Manassa Hany, Saira Pasha, Benjamin Chaucer, Simarpreet Kaur, Christopher Janusz

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Children and adolescent patients visit the Psychiatric Emergency Department (ED) for multiple reasons. Visiting the Psychiatric ED itself can be a traumatic experience that can affect an adolescents mental well-being, regardless of a history of mental illness. Despite this, limited research exists in this domain. Prospective studies have correlated adverse psychosocial determinants among adolescents to risk factors for poor well-being and unfavorable behavior outcomes. Studies have also shown that physiological stress is a contributor in the development of health problems and an increase in substance abuse in adolescents. This study aimed to retrospectively determine which psychosocial factors are associated with an increase in psychiatric ED visits. 600 charts of patients who had a psychiatric ED and inpatient admission visit from January 2014 through December 2014 were reviewed. Sociodemographics, diagnoses, ED visits and inpatient admissions were collected. Descriptive statistics, chi-square tests and independent t-test analyses were utilized to examine differences in the sample to determine which factors affected ED visits and admissions. The sample was 50% female, 35.2% self-identified black, and had a mean age of 13 years. The majority, 85%, went to public school and 17% were in special education. Attention Deficit Hyperactivity Disorder was the most common admitting diagnosis, found in 132(23%) responders. Most patients came from single parent household 305 (53%). The mean ages of patients that were sexually active, with legal issues, and reporting marijuana substance abuse were 15, 14.35, and 15 years respectively. Patients from two biological parent households had significantly fewer ED visits (1.2 vs. 1.7, p < 0.01) and admissions (0.09 vs. 0.26, p < 0.01). Among social factors, those who reported sexual, physical or emotional abuse had a significantly greater number of ED visits (2.1 vs. 1.5, p < 0.01) and admissions (0.61 vs. 0.14, p < 0.01) than those who did not. Patients that were sexually active or had legal issues or substance abuse with marijuana had a significantly greater number of admissions (0.43 vs. 0.17, p < 0.01), (0.54 vs. .18, p < 0.01) and (0.46 vs. 0.18, p < 0.01) respectively. This data supports the theory of the stability of a two parent home. Dual parenting plays a role in creating a safe space where a child can develop; this is shown by subsequent decreases in psychiatric ED visits and admissions. This may highlight the psychological protective role of a two parent household. Abuse can exacerbate existing psychiatric illness or initiate the onset of new disease. Substance abuse and legal issues result in early induction to the criminal system. Results show that this causes an increase in frequency of visits and severity of symptoms. Only marijuana, but not other illicit substances, correlated with higher incidence of psychiatric ED visits. This may speak to the psychotropic nature of tetrahydrocannabinols and their role in mental illness. This study demonstrates the array of psychosocial factors that lead to increased ED visits and admissions in children and adolescents.

Keywords: adolescent, child psychiatry, emergency department, substance abuse

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Authors: Nioofar Margarite Rouhani

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Using a case study methodology, this study explores the lived experiences of elite women footballers (soccer) team in the United Arab Emirates (UAE) and the challenges and enablers women in this country encountered in their journey to competing at an international level. Through a series of face-to-face interviews with members of the first all-Emirati (people with UAE passport) women’s football team, members of the team’s coaching staff and key policymakers, the study sought to explore the social and cultural conditions that enabled the emergence of this team. A key aim of the study was to analyze the cultural shifts that have seemingly facilitated changes to gender relations in the UAE and to highlight possibilities for future gender equality work. The study explores the significance of sport in UAE society and its role in disrupting traditional gender boundaries. To do this, the study identifies and analyses contemporary social (religion, class, and culture) conditions that facilitate, and/or restrict, women’s sports participation in the public sphere of sport. Drawing on a feminist poststructural framework the study sought to analyse the discursive enactment of (disruptive) gender identity positions, using lenses such as ‘discourse’ and ‘power’. With a particular focus on elite women’s sport, the study sought to build knowledge around the advance of female participation in what has long been considered as a masculine domain. Here, the study sought to explore the lived experience of social change through a series of face-to-face interviews with members of the first all-Emirati- women’s football team and key support personnel. To maintain representational integrity, the principles of narrative methodology were employed for their ability to privilege the voices of participants while integrating contextual forces that comprised the stories they told about their experiences and the key people who participated in them. This approach supported a key aim of the study, being to analyse the cultural shifts that have supported changes in gender performance in the UAE and to highlight possibilities for future gender disruption. While the results of the study convey a growing sense of opportunity for aspiring sportswomen in the UAE, they also reveal that the participant pathways were full of contestation and restriction. What we learn from the stories of the first Emirate women’s football team is that where the will is strong enough, there can be a way. While it is reasonable to assume that such pathways will become easier in the future, as the participation of women in such sporting arenas becomes less exceptional, there are factors that are likely to enable and disable such journeys. Prominent here is the presence of a ‘powerful’ guardian and mentor who can offer sustained support, and influence. In a society where males continue to have disproportionate access to social and domestic power, such support can be extremely influential. Guardians and mentors can play a crucial role in garnering the support of dominant male figures, or helping to find ways to work around it.

Keywords: gender equality, women, sport, Middle East

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Authors: M. N. Nwodo, Y. P. Cheng, N. H. Minh

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In the process of recovering oil in weak sandstone formations, the strength of sandstones around the wellbore is weakened due to the increase of effective stress/load from the completion activities around the cavity. The weakened and de-bonded sandstone may be eroded away by the produced fluid, which is termed sand production. It is one of the major trending subjects in the petroleum industry because of its significant negative impacts, as well as some observed positive impacts. For efficient sand management therefore, there has been need for a reliable study tool to understand the mechanism of sanding. One method of studying sand production is the use of the widely recognized Discrete Element Method (DEM), Particle Flow Code (PFC3D) which represents sands as granular individual elements bonded together at contact points. However, there is limited knowledge of the particle-scale behavior of the weak sandstone, and the parameters that affect sanding. This paper aims to investigate the reliability of using PFC3D and a simple Darcy flow in understanding the sand production behavior of a weak sandstone. An isotropic tri-axial test on a weak oil sandstone sample was first simulated at a confining stress of 1MPa to calibrate and validate the parallel bond models of PFC3D using a 10m height and 10m diameter solid cylindrical model. The effect of the confining stress on the number of bonds failure was studied using this cylindrical model. With the calibrated data and sample material properties obtained from the tri-axial test, simulations without and with fluid flow were carried out to check on the effect of Darcy flow on bonds failure using the same model geometry. The fluid flow network comprised of every four particles connected with tetrahedral flow pipes with a central pore or flow domain. Parametric studies included the effects of confining stress, and fluid pressure; as well as validating flow rate – permeability relationship to verify Darcy’s fluid flow law. The effect of model size scaling on sanding was also investigated using 4m height, 2m diameter model. The parallel bond model successfully calibrated the sample’s strength of 4.4MPa, showing a sharp peak strength before strain-softening, similar to the behavior of real cemented sandstones. There seems to be an exponential increasing relationship for the bigger model, but a curvilinear shape for the smaller model. The presence of the Darcy flow induced tensile forces and increased the number of broken bonds. For the parametric studies, flow rate has a linear relationship with permeability at constant pressure head. The higher the fluid flow pressure, the higher the number of broken bonds/sanding. The DEM PFC3D is a promising tool to studying the micromechanical behavior of cemented sandstones.

Keywords: discrete element method, fluid flow, parametric study, sand production/bonds failure

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Authors: Ramprasad Srinivasan

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Engineers create inventions and put their ideas in concrete terms to design new products. Design drivers must be established, which requires, among other things, a complete understanding of the product design, load paths, etc. For Aerospace Vehicles, weight/strength ratio, strength, stiffness and stability are the important design drivers. A complex built-up structure is made up of an assemblage of primitive structural forms of arbitrary shape, which include 1D structures like beams and frames, 2D structures like membranes, plate and shell structures, and 3D solid structures. Justification through simulation involves a check for all the quantities of interest, namely stresses, deformation, frequencies, and buckling loads and is normally achieved through the finite element (FE) method. Over the past few decades, Fiber-reinforced composites are fast replacing the traditional metallic structures in the weight-sensitive aerospace and aircraft industries due to their high specific strength, high specific stiffness, anisotropic properties, design freedom for tailoring etc. Composite panel constructions are used in aircraft to design primary structure components like wings, empennage, ailerons, etc., while thin-walled composite beams (TWCB) are used to model slender structures like stiffened panels, helicopter, and wind turbine rotor blades, etc. The TWCB demonstrates many non-classical effects like torsional and constrained warping, transverse shear, coupling effects, heterogeneity, etc., which makes the analysis of composite structures far more complex. Conventional FE formulations to model 1D structures suffer from many limitations like shear locking, particularly in slender beams, lower convergence rates due to material coupling in composites, inability to satisfy, equilibrium in the domain and natural boundary conditions (NBC) etc. For 2D structures, the limitations of conventional displacement-based FE formulations include the inability to satisfy NBC explicitly and many pathological problems such as shear and membrane locking, spurious modes, stress oscillations, lower convergence due to mesh distortion etc. This mandates frequent re-meshing to even achieve an acceptable mesh (satisfy stringent quality metrics) for analysis leading to significant cycle time. Besides, currently, there is a need for separate formulations (u/p) to model incompressible materials, and a single unified formulation is missing in the literature. Hence coupled field formulation (CFF) is a unified formulation proposed by the author for the solution of complex 1D and 2D structures addressing the gaps in the literature mentioned above. The salient features of CFF and its many advantages over other conventional methods shall be presented in this paper.

Keywords: coupled field formulation, kinematic and material coupling, natural boundary condition, locking free formulation

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Authors: Dinara F. Gaynutdinova, Vladimir Ya Modorsky, Nikolay A. Shevelev

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The problem under research is that of unpredictable modes occurring in two-stage centrifugal hydraulic pump as a result of hydraulic processes caused by vibrations of structural components. Numerical, analytical and experimental approaches are considered. A hypothesis was developed that the problem of unpredictable pressure decrease at the second stage of centrifugal pumps is caused by cavitation effects occurring upon vibration. The problem has been studied experimentally and theoretically as of today. The theoretical study was conducted numerically and analytically. Hydroelastic processes in dynamic “liquid – deformed structure” system were numerically modelled and analysed. Using ANSYS CFX program engineering analysis complex and computing capacity of a supercomputer the cavitation parameters were established to depend on vibration parameters. An influence domain of amplitudes and vibration frequencies on concentration of cavitation bubbles was formulated. The obtained numerical solution was verified using CFM program package developed in PNRPU. The package is based on a differential equation system in hyperbolic and elliptic partial derivatives. The system is solved by using one of finite-difference method options – the particle-in-cell method. The method defines the problem solution algorithm. The obtained numerical solution was verified analytically by model problem calculations with the use of known analytical solutions of in-pipe piston movement and cantilever rod end face impact. An infrastructure consisting of an experimental fast hydro-dynamic processes research installation and a supercomputer connected by a high-speed network, was created to verify the obtained numerical solutions. Physical experiments included measurement, record, processing and analysis of data for fast processes research by using National Instrument signals measurement system and Lab View software. The model chamber end face oscillated during physical experiments and, thus, loaded the hydraulic volume. The loading frequency varied from 0 to 5 kHz. The length of the operating chamber varied from 0.4 to 1.0 m. Additional loads weighed from 2 to 10 kg. The liquid column varied from 0.4 to 1 m high. Liquid pressure history was registered. The experiment showed dependence of forced system oscillation amplitude on loading frequency at various values: operating chamber geometrical dimensions, liquid column height and structure weight. Maximum pressure oscillation (in the basic variant) amplitudes were discovered at loading frequencies of approximately 1,5 kHz. These results match the analytical and numerical solutions in ANSYS and CFM.

Keywords: computing experiment, hydroelasticity, physical experiment, vibration

Procedia PDF Downloads 244

Authors: Bashar Mahmoud, Lee Mortimer, Michael Fairweather

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New methods have recently been introduced to improve the thermal property values of molten nitrate salts (a binary mixture of NaNO3:KNO3in 60:40 wt. %), by doping them with minute concentration of nanoparticles in the range of 0.5 to 1.5 wt. % to form the so-called: Nano-heat-transfer-fluid, apt for thermal energy transfer and storage applications. The present study aims to assess the stability of these nanofluids using the advanced computational modelling technique, Lagrangian particle tracking. A multi-phase solid-liquid model is used, where the motion of embedded nanoparticles in the suspended fluid is treated by an Euler-Lagrange hybrid scheme with fixed time stepping. This technique enables measurements of various multi-scale forces whose characteristic (length and timescales) are quite different. Two systems are considered, both consisting of 50 nm Al2O3 ceramic nanoparticles suspended in fluids of different density ratios. This includes both water (5 to 95 °C) and molten nitrate salt (220 to 500 °C) at various volume fractions ranging between 1% to 5%. Dynamic properties of both phases are coupled to the ambient temperature of the fluid suspension. The three-dimensional computational region consists of a 1μm cube and particles are homogeneously distributed across the domain. Periodic boundary conditions are enforced. The particle equations of motion are integrated using the fourth order Runge-Kutta algorithm with a very small time-step, Δts, set at 10-11 s. The implemented technique demonstrates the key dynamics of aggregated nanoparticles and this involves: Brownian motion, soft-sphere particle-particle collisions, and Derjaguin, Landau, Vervey, and Overbeek (DLVO) forces. These mechanisms are responsible for the predictive model of aggregation of nano-suspensions. An energy transport-based method of predicting the thermal conductivity of the nanofluids is also used to determine thermal properties of the suspension. The simulation results confirms the effectiveness of the technique. The values are in excellent agreement with the theoretical and experimental data obtained from similar studies. The predictions indicates the role of Brownian motion and DLVO force (represented by both the repulsive electric double layer and an attractive Van der Waals) and its influence in the level of nanoparticles agglomeration. As to the nano-aggregates formed that was found to play a key role in governing the thermal behavior of nanofluids at various particle concentration. The presentation will include a quantitative assessment of these forces and mechanisms, which would lead to conclusions about nanofluids, heat transfer performance and thermal characteristics and its potential application in solar thermal energy plants.

Keywords: thermal energy storage, molten salt, nano-fluids, multi-scale computational modelling

Procedia PDF Downloads 191

Authors: Gerhard Gritsch, Ana Skupch, Manfred Hartmann, Wolfgang Frühwirt, Hannes Perko, Dieter Grossegger, Tilmann Kluge

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Rehabilitation of stroke patients is dominated by classical physiotherapy. Nowadays, a field of research is the application of neurofeedback techniques in order to help stroke patients to get rid of their motor impairments. Especially, if a certain limb is completely paralyzed, neurofeedback is often the last option to cure the patient. Certain exercises, like the imagination of the impaired motor function, have to be performed to stimulate the neuroplasticity of the brain, such that in the neighboring parts of the injured cortex the corresponding activity takes place. During the exercises, it is very important to keep the motivation of the patient at a high level. For this reason, the missing natural feedback due to a movement of the effected limb may be replaced by a synthetic feedback based on the motor-related brain function. To generate such a synthetic feedback a system is needed which measures, detects, localizes and visualizes the motor related µ-rhythm. Fast therapeutic success can only be achieved if the feedback features high specificity, comes in real-time and without large delay. We describe such an approach that offers a 3D visualization of µ-rhythms in real time with a delay of 500ms. This is accomplished by combining smart EEG preprocessing in the frequency domain with source localization techniques. The algorithm first selects the EEG channel featuring the most prominent rhythm in the alpha frequency band from a so-called motor channel set (C4, CZ, C3; CP6, CP4, CP2, CP1, CP3, CP5). If the amplitude in the alpha frequency band of this certain electrode exceeds a threshold, a µ-rhythm is detected. To prevent detection of a mixture of posterior alpha activity and µ-activity, the amplitudes in the alpha band outside the motor channel set are not allowed to be in the same range as the main channel. The EEG signal of the main channel is used as template for calculating the spatial distribution of the µ - rhythm over all electrodes. This spatial distribution is the input for a inverse method which provides the 3D distribution of the µ - activity within the brain which is visualized in 3D as color coded activity map. This approach mitigates the influence of lid artifacts on the localization performance. The first results of several healthy subjects show that the system is capable of detecting and localizing the rarely appearing µ-rhythm. In most cases the results match with findings from visual EEG analysis. Frequent eye-lid artifacts have no influence on the system performance. Furthermore, the system will be able to run in real-time. Due to the design of the frequency transformation the processing delay is 500ms. First results are promising and we plan to extend the test data set to further evaluate the performance of the system. The relevance of the system with respect to the therapy of stroke patients has to be shown in studies with real patients after CE certification of the system. This work was performed within the project ‘LiveSolo’ funded by the Austrian Research Promotion Agency (FFG) (project number: 853263).

Keywords: real-time EEG neuroimaging, neurofeedback, stroke, EEG–signal processing, rehabilitation

Procedia PDF Downloads 388

Authors: Sînziana Iancu

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In an era marked by rapid urbanization and technological advancement, the concept of smart cities has emerged as a pivotal solution to address the complex challenges faced by urban centres. As cities strive to enhance the quality of life for their residents, the development of smart cities has gained prominence. This study embarks on a comparative analysis of two distinct smart city models, Singapore and Bucharest, to assess their resilience and technological advancements. The significance of this study lies in its potential to provide valuable insights into the strategies, strengths, and areas of improvement in smart city development, ultimately contributing to the advancement of urban planning and sustainability. Methodologies: This comparative study employs a multifaceted approach to comprehensively analyse the smart city development in Singapore and Bucharest: * Comparative Analysis: A systematic comparison of the two cities is conducted, focusing on key smart city indicators, including digital infrastructure, integrated public services, urban planning and sustainability, transportation and mobility, environmental monitoring, safety and security, innovation and economic resilience, and community engagement; * Case Studies: In-depth case studies are conducted to delve into specific smart city projects and initiatives in both cities, providing real-world examples of their successes and challenges; * Data Analysis: Official reports, statistical data, and relevant publications are analysed to gather quantitative insights into various aspects of smart city development. Major Findings: Through a comprehensive analysis of Singapore and Bucharest's smart city development, the study yields the following major findings: * Singapore excels in digital infrastructure, integrated public services, safety, and innovation, showcasing a high level of resilience across these domains; * Bucharest is in the early stages of smart city development, with notable potential for growth in digital infrastructure and community engagement.; * Both cities exhibit a commitment to sustainable urban planning and environmental monitoring, with room for improvement in integrating these aspects into everyday life; * Transportation and mobility solutions are a priority for both cities, with Singapore having a more advanced system, while Bucharest is actively working on improving its transportation infrastructure; * Community engagement, while important, requires further attention in both cities to enhance the inclusivity of smart city initiatives. Conclusion: In conclusion, this study serves as a valuable resource for urban planners, policymakers, and stakeholders in understanding the nuances of smart city development and resilience. While Singapore stands as a beacon of success in various smart city indicators, Bucharest demonstrates potential and a willingness to adapt and grow in this domain. As cities worldwide embark on their smart city journeys, the lessons learned from Singapore and Bucharest provide invaluable insights into the path toward urban sustainability and resilience in the digital age.

Keywords: bucharest, resilience, Singapore, smart city

Procedia PDF Downloads 69

Authors: Anna-Maria Ramezanzadeh

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Demand for Arabic language is growing worldwide, driven by increased interest in the multifarious purposes the language serves, both for the population of heritage learners and those studying Arabic as a foreign language. The diglossic, or indeed multiglossic nature of the language as used in Arabic speaking communities however, is seldom represented in the content of classroom courses. This disjoint between the nature of provision and students’ expectations can severely impact their engagement with course material, and their motivation to either commence or continue learning the language. The nature of motivation and its relationship to multiglossia is sparsely explored in current literature on Arabic. The theoretical framework here proposed aims to address this gap by presenting a model and instruments for the measurement of Arabic learners’ motivation in relation to the multiple strands of the language. It adopts and develops the Second Language Motivation Self-System model (L2MSS), originally proposed by Zoltan Dörnyei, which measures motivation as the desire to reduce the discrepancy between leaners’ current and future self-concepts in terms of the second language (L2). The tripartite structure incorporates measures of the Current L2 Self, Future L2 Self (consisting of an Ideal L2 Self, and an Ought-To Self), and the L2 Learning Experience. The strength of the self-concepts is measured across three different domains of Arabic: Classical, Modern Standard and Colloquial. The focus on learners’ self-concepts allows for an exploration of the effect of multiple factors on motivation towards Arabic, including religion. The relationship between Islam and Arabic is often given as a prominent reason behind some students’ desire to learn the language. Exactly how and why this factor features in learners’ L2 self-concepts has not yet been explored. Specifically designed surveys and interview protocols are proposed to facilitate the exploration of these constructs. The L2 Learning Experience component of the model is operationalized as learners’ task-based engagement. Engagement is conceptualised as multi-dimensional and malleable. In this model, situation-specific measures of cognitive, behavioural, and affective components of engagement are collected via specially designed repeated post-task self-report surveys on Personal Digital Assistant over multiple Arabic lessons. Tasks are categorised according to language learning skill. Given the domain-specific uses of the different varieties of Arabic, the relationship between learners’ engagement with different types of tasks and their overall motivational profiles will be examined to determine the extent of the interaction between the two constructs. A framework for this data analysis is proposed and hypotheses discussed. The unique combination of situation-specific measures of engagement and a person-oriented approach to measuring motivation allows for a macro- and micro-analysis of the interaction between learners and the Arabic learning process. By combining cross-sectional and longitudinal elements with a mixed-methods design, the model proposed offers the potential for capturing a comprehensive and detailed picture of the motivation and engagement of Arabic learners. The application of this framework offers a number of numerous potential pedagogical and research implications which will also be discussed.

Keywords: Arabic, diglossia, engagement, motivation, multiglossia, sociolinguistics

Procedia PDF Downloads 166

Authors: Nikitha Francis, Anjana Hoode, Vinitha George, Jayashree S. Bhat

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The interaction between cognition and language, referred as cognitive-communication, is very intricate, involving several mental processes such as perception, memory, attention, lexical retrieval, decision making, motor planning, self-monitoring and knowledge. Cognitive-communication disorders are difficulties in communicative competencies that result from underlying cognitive impairments of attention, memory, organization, information processing, problem solving, and executive functions. Traumatic brain injury (TBI) is an acquired, non - progressive condition, resulting in distinct deficits of cognitive communication abilities such as naming, word-finding, self-monitoring, auditory recognition, attention, perception and memory. Cognitive-communication intervention in TBI is individualized, in order to enhance the person’s ability to process and interpret information for better functioning in their family and community life. The present case report illustrates the cognitive-communicative behaviors and the intervention outcomes of an adult with TBI, who was brought to the Department of Audiology and Speech Language Pathology, with cognitive and communicative disturbances, consequent to road traffic accident. On a detailed assessment, she showed naming deficits along with perseverations and had severe difficulty in recalling the details of the accident, her house address, places she had visited earlier, names of people known to her, as well as the activities she did each day, leading to severe breakdowns in her communicative abilities. She had difficulty in initiating, maintaining and following a conversation. She also lacked orientation to time and place. On administration of the Manipal Manual of Cognitive Linguistic Abilities (MMCLA), she exhibited poor performance on tasks related to visual and auditory perception, short term memory, working memory and executive functions. She attended 20 sessions of cognitive-communication intervention which followed a domain-general, adaptive training paradigm, with tasks relevant to everyday cognitive-communication skills. Compensatory strategies such as maintaining a dairy with reminders of her daily routine, names of people, date, time and place was also recommended. MMCLA was re-administered and her performance in the tasks showed significant improvements. Occurrence of perseverations and word retrieval difficulties reduced. She developed interests to initiate her day-to-day activities at home independently, as well as involve herself in conversations with her family members. Though she lacked awareness about her deficits, she actively involved herself in all the therapy activities. Rehabilitation of moderate to severe head injury patients can be done effectively through a holistic cognitive retraining with a focus on different cognitive-linguistic domains. Selection of goals and activities should have relevance to the functional needs of each individual with TBI, as highlighted in the present case report.

Keywords: cognitive-communication, executive functions, memory, traumatic brain injury

Procedia PDF Downloads 347

Authors: Mehari Teshome, Lara Agostini, Anna Nosella

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The current knowledge-based economy extends intellectual property rights (IPRs) legal research themes into a more strategic and organizational perspectives. From the diverse types of IPRs, patents are the strongest and well-known form of legal protection that influences commercial success and market value. Indeed, from our pilot survey, we understood that firms are less likely to manage their patents and actively used it as a tool for achieving competitive advantage rather they invest resource and efforts for patent application. To this regard, the literature also confirms that insights into how firms manage their patents from a holistic, strategic perspective, and how the portfolio value of patents can be optimized are scarce. Though patent management is an important business tool and there exist few scales to measure some dimensions of patent management, at the best of our knowledge, no systematic attempt has been made to develop a valid and comprehensive measure of it. Considering this theoretical and practical point of view, the aim of this article is twofold: to develop a framework for patent management encompassing all relevant dimensions with their respective constructs and measurement items, and to validate the measurement using survey data from practitioners. Methodology: We used six-step methodological approach (i.e., specify the domain of construct, item generation, scale purification, internal consistency assessment, scale validation, and replication). Accordingly, we carried out a systematic review of 182 articles on patent management, from ISI Web of Science. For each article, we mapped relevant constructs, their definition, and associated features, as well as items used to measure these constructs, when provided. This theoretical analysis was complemented by interviews with experts in patent management to get feedbacks that are more practical on how patent management is carried out in firms. Afterwards, we carried out a questionnaire survey to purify our scales and statistical validation. Findings: The analysis allowed us to design a framework for patent management, identifying its core dimensions (i.e., generation, portfolio-management, exploitation and enforcement, intelligence) and support dimensions (i.e., strategy and organization). Moreover, we identified the relevant activities for each dimension, as well as the most suitable items to measure them. For example, the core dimension generation includes constructs as: state-of-the-art analysis, freedom-to-operate analysis, patent watching, securing freedom-to-operate, patent potential and patent-geographical-scope. Originality and the Study Contribution: This study represents a first step towards the development of sound scales to measure patent management with an overarching approach, thus laying the basis for developing a recognized landmark within the research area of patent management. Practical Implications: The new scale can be used to assess the level of sophistication of the patent management of a company and compare it with other firms in the industry to evaluate their ability to manage the different activities involved in patent management. In addition, the framework resulting from this analysis can be used as a guide that supports managers to improve patent management in firms.

Keywords: patent, management, scale, development, intellectual property rights (IPRs)

Procedia PDF Downloads 148

Authors: N. Agon, T. Kavka, J. Vierendeels, M. Hrabovský, G. Van Oost

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A plasma jet model was developed with a rigorous method for calculating the thermophysical properties of the gas mixture without mixing rules. A simplified model approach to account for the anode effects was incorporated in this model to allow the valorization of the simulations with experimental results. The radial heat transfer was under-predicted by the model because of the limitations of the radiation model, but the calculated evolution of centerline temperature, velocity and gas composition downstream of the torch exit corresponded well with the measured values. The CFD modeling of thermal plasmas is either focused on development of the plasma arc or the flow of the plasma jet outside of the plasma torch. In the former case, the Maxwell equations are coupled with the Navier-Stokes equations to account for electromagnetic effects which control the movements of the anode arc attachment. In plasma jet simulations, however, the computational domain starts from the exit nozzle of the plasma torch and the influence of the arc attachment fluctuations on the plasma jet flow field is not included in the calculations. In that case, the thermal plasma flow is described by temperature, velocity and concentration profiles at the torch exit nozzle and no electromagnetic effects are taken into account. This simplified approach is widely used in literature and generally acceptable for plasma torches with a circular anode inside the torch chamber. The unique DC hybrid water/gas-stabilized plasma torch developed at the Institute of Plasma Physics of the Czech Academy of Sciences on the other hand, consists of a rotating anode disk, located outside of the torch chamber. Neglecting the effects of the anode arc attachment downstream of the torch exit nozzle leads to erroneous predictions of the flow field. With the simplified approach introduced in this model, the Joule heating between the exit nozzle and the anode attachment position of the plasma arc is modeled by a volume heat source and the jet deflection caused by the anode processes by a momentum source at the anode surface. Furthermore, radiation effects are included by the net emission coefficient (NEC) method and diffusion is modeled with the combined diffusion coefficient method. The time-averaged simulation results are compared with numerous experimental measurements. The radial temperature profiles were obtained by spectroscopic measurements at different axial positions downstream of the exit nozzle. The velocity profiles were evaluated from the time-dependent evolution of flow structures, recorded by photodiode arrays. The shape of the plasma jet was compared with charge-coupled device (CCD) camera pictures. In the cooler regions, the temperature was measured by enthalpy probe downstream of the exit nozzle and by thermocouples in radial direction around the torch nozzle. The model results correspond well with the experimental measurements. The decrease in centerline temperature and velocity is predicted within an acceptable range and the shape of the jet closely resembles the jet structure in the recorded images. The temperatures at the edge of the jet are underestimated due to the absence of radial radiative heat transfer in the model.

Keywords: anode arc attachment, CFD modeling, experimental comparison, thermal plasma jet

Procedia PDF Downloads 367

Authors: Mbonigaba Swale

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Malaria is an infection or disease caused by parasites (Plasmodium Falciparum — causes severe Malaria, plasmodium Vivax, Plasmodium Ovale, and Plasmodium Malariae), transmitted by bites of infected anopheles (female) mosquitoes to humans. These vectors comprise of two types in Africa, particularly in Uganda, i.e. anopheles fenestus and Anopheles gambaie (‘example Anopheles arabiensis,,); feeds on man inside the house mainly at dusk, mid-night and dawn and rests indoors and makes them effective transmitters (vectors) of the disease. People in both urban and rural areas have consistently become prone to repetitive attacks of malaria, causing a lot of deaths and significantly increasing the poverty levels of the rural poor. Malaria is a national problem; it causes a lot of maternal pre-natal and antenatal disorders, anemia in pregnant mothers, low birth weights for the newly born, convulsions and epilepsy among the infants. Cumulatively, it kills about one million children every year in sub-Saharan Africa. It has been estimated to account for 25-35% of all outpatient visits, 20-45% of acute hospital admissions and 15-35% of hospital deaths. Uganda is the leading victim country, for which Rakai and Masaka districts are the most affected. So, it is not clear whether these abhorrent situations and episodes of recurrences and failure to cure from the disease are a result of poor diagnosis, prescription and dosing, treatment habits and compliance of the patients to the drugs or the ethical domain of the stake holders in relation to the main stream methodology of malaria management. The research is aimed at offering an alternative approach to manage and deal absolutely with problem by using a knowledge based software model of Artificial Intelligence (Al) that is capable of performing common-sense and cognitive reasoning so as to take decisions like the human brain would do to provide instantaneous expert solutions so as to avoid speculative simulation of the problem during differential diagnosis in the most accurate and literal inferential aspect. This system will assist physicians in many kinds of medical diagnosis, prescribing treatments and doses, and in monitoring patient responses, basing on the body weight and age group of the patient, it will be able to provide instantaneous and timely information options, alternative ways and approaches to influence decision making during case analysis. The computerized system approach, a new model in Uganda termed as “Software Aided Treatment” (SAT) will try to change the moral and ethical approach and influence conduct so as to improve the skills, experience and values (social and ethical) in the administration and management of the disease and drugs (combination therapy and generics) by both the patient and the health worker.

Keywords: knowledge based software, management, treatment, diagnosis

Procedia PDF Downloads 57

Authors: A. Bortkiewcz, A. Dudarewicz, P. Małecki, M. Kłaczyński, T. Wszołek, Małgorzata Pawlaczyk-Łuszczyńska

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Low-frequency noise (LFN) has been recognized as a special environmental pollutant. It is usually considered a broadband noise with the dominant content of low frequencies from 10 Hz to 250 Hz. A growing body of data shows that LFN differs in nature from other environmental noises, which are at comparable levels but not dominated by low-frequency components. The primary and most frequent adverse effect of LFN exposure is annoyance. Moreover, some recent investigations showed that LFN at relatively low A-weighted sound pressure levels (40−45 dB) occurring in office-like areas could adversely affect the mental performance, especially of high-sensitive subjects. It is well documented that high-frequency noise disturbs various types of human functions; however, there is very little data on the impact of LFN on well-being and health, including the cardiovascular system. Heart rate variability (HRV) is a sensitive marker of autonomic regulation of the circulatory system. Walker and co-workers found that LFN has a significantly more negative impact on cardiovascular response than exposure to high-frequency noise and that changes in HRV parameters resulting from LFN exposure tend to persist over time. The negative reactions of the cardiovascular system in response to LFN generated by wind turbines (20-200 Hz) were confirmed by Chiu. The scientific aim of the study is to assess the relationship between the spectral-temporal characteristics of LFN and the activity of the autonomic nervous system, considering the subjective assessment of annoyance, sensitivity to this type of noise, and cognitive and general health status. The study will be conducted in 20 male students in a special, acoustically prepared, constantly supervised room. Each person will be tested 4 times (4 sessions), under conditions of non-exposure (sham) and exposure to noise of wind turbines recorded at a distance of 250 meters from the turbine with different frequencies and frequency ranges: acoustic band 20 Hz-20 kHz, infrasound band 5-20 Hz, acoustic band + infrasound band. The order of sessions of the experiment will be randomly selected. Each session will last 1 h. There will be a 2-3 days break between sessions to exclude the possibility of the earlier session influencing the results of the next one. Before the first exposure, a questionnaire will be conducted on noise sensitivity, general health status using the GHQ questionnaire, hearing organ status and sociodemographic data. Before each of the 4 exposures, subjects will complete a brief questionnaire on their mood and sleep quality the night before the test. After the test, the subjects will be asked about any discomfort and subjective symptoms during the exposure. Before the test begins, Holter ECG monitoring equipment will be installed. HRV will be analyzed from the ECG recordings, including time and frequency domain parameters. The tests will always be performed in the morning (9-12) to avoid the influence of diurnal rhythm on HRV results. Students will perform psychological tests 15 minutes before the end of the test (Vienna Test System).

Keywords: neurovegetative control, heart rate variability (HRV), cognitive processes, low frequency noise

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Authors: Benjamin Arazi

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Blockchain is the technology behind cryptocurrencies like Bitcoin. It revolutionizes the meaning of trust in the sense of offering total reliability without relying on any central entity that controls or supervises the system. The Wall Street Journal states: “Blockchain Marks the Next Step in the Internet’s Evolution”. Blockchain was listed as #1 in Linkedin – The Learning Blog “most in-demand hard skills needed in 2020”. As stated there: “Blockchain’s novel way to store, validate, authorize, and move data across the internet has evolved to securely store and send any digital asset”. GSMA, a leading Telco organization of mobile communications operators, declared that “Blockchain has the potential to be for value what the Internet has been for information”. Motivated by these seminal observations, this paper presents the foundations of a Blockchain-based “Internet of Assets” academic program that joins under one roof leading application areas that are characterized by the transfer of assets over communication lines. Two such areas, which are pillars of our economy, are Fintech – Financial Technology and mobile communications services. The next application in line is Healthcare. These challenges are met based on available extensive professional literature. Blockchain-based assets communication is based on extending the principle of Bitcoin, starting with the basic question: If digital money that travels across the universe can ‘prove its own validity’, can this principle be applied to digital content. A groundbreaking positive answer here led to the concept of “smart contract” and consequently to DLT - Distributed Ledger Technology, where the word ‘distributed’ relates to the non-existence of reliable central entities or trusted third parties. The terms Blockchain and DLT are frequently used interchangeably in various application areas. The World Bank Group compiled comprehensive reports, analyzing the contribution of DLT/Blockchain to Fintech. The European Central Bank and Bank of Japan are engaged in Project Stella, “Balancing confidentiality and auditability in a distributed ledger environment”. 130 DLT/Blockchain focused Fintech startups are now operating in Switzerland. Blockchain impact on mobile communications services is treated in detail by leading organizations. The TM Forum is a global industry association in the telecom industry, with over 850 member companies, mainly mobile operators, that generate US$2 trillion in revenue and serve five billion customers across 180 countries. From their perspective: “Blockchain is considered one of the digital economy’s most disruptive technologies”. Samples of Blockchain contributions to Fintech (taken from a World Bank document): Decentralization and disintermediation; Greater transparency and easier auditability; Automation & programmability; Immutability & verifiability; Gains in speed and efficiency; Cost reductions; Enhanced cyber security resilience. Samples of Blockchain contributions to the Telco industry. Establishing identity verification; Record of transactions for easy cost settlement; Automatic triggering of roaming contract which enables near-instantaneous charging and reduction in roaming fraud; Decentralized roaming agreements; Settling accounts per costs incurred in accordance with agreement tariffs. This clearly demonstrates an academic education structure where fundamental technologies are studied in classes together with these two application areas. Advanced courses, treating specific implementations then follow separately. All are under the roof of “Internet of Assets”.

Keywords: blockchain, education, financial technology, mobile telecommunications services

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Authors: Vikrant Gupta, Amrit Goswami

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The fixed income market forms the basis of the modern financial market. All other assets in financial markets derive their value from the bond market. Owing to its over-the-counter nature, corporate bonds have relatively less data publicly available and thus is researched upon far less compared to Equities. Bond price prediction is a complex financial time series forecasting problem and is considered very crucial in the domain of finance. The bond prices are highly volatile and full of noise which makes it very difficult for traditional statistical time-series models to capture the complexity in series patterns which leads to inefficient forecasts. To overcome the inefficiencies of statistical models, various machine learning techniques were initially used in the literature for more accurate forecasting of time-series. However, simple machine learning methods such as linear regression, support vectors, random forests fail to provide efficient results when tested on highly complex sequences such as stock prices and bond prices. hence to capture these intricate sequence patterns, various deep learning-based methodologies have been discussed in the literature. In this study, a recurrent neural network-based deep learning model using long short term networks for prediction of corporate bond prices has been discussed. Long Short Term networks (LSTM) have been widely used in the literature for various sequence learning tasks in various domains such as machine translation, speech recognition, etc. In recent years, various studies have discussed the effectiveness of LSTMs in forecasting complex time-series sequences and have shown promising results when compared to other methodologies. LSTMs are a special kind of recurrent neural networks which are capable of learning long term dependencies due to its memory function which traditional neural networks fail to capture. In this study, a simple LSTM, Stacked LSTM and a Masked LSTM based model has been discussed with respect to varying input sequences (three days, seven days and 14 days). In order to facilitate faster learning and to gradually decompose the complexity of bond price sequence, an Empirical Mode Decomposition (EMD) has been used, which has resulted in accuracy improvement of the standalone LSTM model. With a variety of Technical Indicators and EMD decomposed time series, Masked LSTM outperformed the other two counterparts in terms of prediction accuracy. To benchmark the proposed model, the results have been compared with traditional time series models (ARIMA), shallow neural networks and above discussed three different LSTM models. In summary, our results show that the use of LSTM models provide more accurate results and should be explored more within the asset management industry.

Keywords: bond prices, long short-term memory, time series forecasting, empirical mode decomposition

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

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Authors: Adil Murtaza, Muhammad Tahir Khan, Awais Ghani, Chao Zhou, Sen Yang, Xiaoping Song

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The morphotropic phase boundary (MPB); a boundary between two different crystallographic symmetries in the composition–temperature phase diagram has been widely studied in ferroelectrics and recently has drawn interest in ferromagnets for obtaining enhanced large field-induced strain. At MPB, the system gets a compressed free energy state, which allows the polarization to freely rotate and hence results in a high magnetoelastic response (e.g., high magnetization, low coercivity, and large magnetostriction). Based on the same mechanism, we designed MPB in a ferromagnetic Tb₁₋ₓNdₓCo₂ system. The temperature-dependent magnetization curves showed spin reorientation (SR); which can be explained by a two-sublattice model. Contrary to previously reported MPB involved ferromagnetic systems, the MPB composition of Tb₀.₃₅Nd₀.₆₅Co₂ exhibits a low saturation magnetization (MS), indicating a compensation of the Tb and Nd magnetic moments at MPB. The coercive field (HC) under a low magnetic field and first anisotropy constant (K₁) shows a minimum value at MPB composition of x=0.65. A detailed spin configuration diagram is provided for the Tb₁₋ₓNdₓCo₂ around the composition for the anisotropy compensation; this can guide the development of novel magnetostrictive materials. The anisotropic magnetostriction (λS) first decreased until x=0.8 and then continuously increased in the negative direction with further increase of Nd concentration. In addition, the large ratio between magnetostriction and the absolute values of the first anisotropy constant (λS/K₁) appears at MPB, indicating that Tb₀.₃₅Nd₀.₆₅Co₂ has good magnetostrictive properties. Present work shows an anomalous type of MPB in ferromagnetic materials, revealing that MPB can also lead to a weakening of magnetoelastic behavior as shown in the ferromagnetic Tb₁₋ₓNdₓCo₂ system. Our work shows the universal presence of MPB in ferromagnetic materials and suggests the differences between different ferromagnetic MPB systems that are important for substantial improvement of magnetic and magnetostrictive properties. Based on the results of this study, similar MPB effects might be achieved in other ferroic systems that can be used for technological applications. The finding of magnetic MPB in the ferromagnetic system leads to some important significances. First, it provides a better understanding of the fundamental concept of spin reorientation transitions (SRT) like ferro-ferro transitions are not only reorientation of magnetization but also crystal symmetry change upon magnetic ordering. Second, the flattened free energy corresponding to a low energy barrier for magnetization rotation and enhanced magnetoelastic response near MPB. Third, to attain large magnetostriction with MPB approach two terminal compounds have different easy magnetization directions below Curie temperature Tc in order to accomplish the weakening of magnetization anisotropy at MPB (as in ferroelectrics), thus easing the magnetic domain switching and the lattice distortion difference between two terminal compounds should be large enough, e.g., lattice distortion of R symmetry ˃˃ lattice distortion of T symmetry). So that the MPB composition agrees to a nearly isotropic state along with large ‘net’ lattice distortion, which is revealed in a higher value of magnetostriction.

Keywords: magnetization, magnetostriction, morphotropic phase boundary (MPB), phase transition

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Authors: Casta Guillaume, Robert Jagers, Deborah Rivas-Drake

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Civically engaged youth are critical to maintaining and/or improving the functioning of local, national and global communities and their institutions. The present study investigated how school climate and academic beliefs (academic self-efficacy and school belonging) may inform emergent civic behaviors (emergent citizenship) among self-identified middle school youth of color (African American, Multiracial or Mixed, Latino, Asian American or Pacific Islander, Native American, and other). Study aims: 1) Understand whether and how school climate is associated with civic engagement behaviors, directly and indirectly, by fostering a positive sense of connection to the school and/or engendering feelings of self-efficacy in the academic domain. Accordingly, we examined 2) The association of youths’ sense of school connection and academic self-efficacy with their personally responsible and participatory civic behaviors in school and community contexts—both concurrently and longitudinally. Data from two subsamples of a larger study of social/emotional development among middle school students were used for longitudinal and cross sectional analysis. The cross-sectional sample included 324 6th-8th grade students, of which 43% identified as African American, 20% identified as Multiracial or Mixed, 18% identified as Latino, 12% identified as Asian American or Pacific Islander, 6% identified as Other, and 1% identified as Native American. The age of the sample ranged from 11 – 15 (M = 12.33, SD = .97). For the longitudinal test of our mediation model, we drew on data from the 6th and 7th grade cohorts only (n =232); the ethnic and racial diversity of this longitudinal subsample was virtually identical to that of the cross-sectional sample. For both the cross-sectional and longitudinal analyses, full information maximum likelihood was used to deal with missing data. Fit indices were inspected to determine if they met the recommended thresholds of RMSEA below .05 and CFI and TLI values of at least .90. To determine if particular mediation pathways were significant, the bias-corrected bootstrap confidence intervals for each indirect pathway were inspected. Fit indices for the latent variable mediation model using the cross-sectional data suggest that the hypothesized model fit the observed data well (CFI = .93; TLI =. 92; RMSEA = .05, 90% CI = [.04, .06]). In the model, students’ perceptions of school climate were significantly and positively associated with greater feelings of school connectedness, which were in turn significantly and positively associated with civic engagement. In addition, school climate was significantly and positively associated with greater academic self-efficacy, but academic self-efficacy was not significantly associated with civic engagement. Tests of mediation indicated there was one significant indirect pathway between school climate and civic engagement behavior. There was an indirect association between school climate and civic engagement via its association with sense of school connectedness, indirect association estimate = .17 [95% CI: .08, .32]. The aforementioned indirect association via school connectedness accounted for 50% (.17/.34) of the total effect. Partial support was found for the prediction that students’ perceptions of a positive school climate are linked to civic engagement in part through their role in students’ sense of connection to school.

Keywords: civic engagement, early adolescence, school climate, school belonging, developmental niche

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Authors: Augustas Vaitkevicius, Mikhail Korjik, Eugene Tretyak, Ekaterina Trusova, Gintautas Tamulaitis

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Silicate materials are widely used as luminescent materials in amorphous and crystalline phase. Lithium silicate glass is popular for making neutron sensitive scintillation glasses. Cerium-doped single crystalline silicates of rare earth elements and yttrium have been demonstrated to be good scintillation materials. Due to their high thermal and photo-stability, silicate glass ceramics are supposed to be suitable materials for producing light converters for high power white light emitting diodes. In this report, the influence of glass composition and crystallization on photoluminescence (PL) of different silicate glasses was studied. Barium (BaO-2SiO₂) and lithium (Li₂O-2SiO₂) glasses were under study. Cerium, dysprosium, erbium and europium ions as well as their combinations were used for doping. The influence of crystallization was studied after transforming the doped glasses into glass ceramics by heat treatment in the temperature range of 550-850 degrees Celsius for 1 hour. The study was carried out by comparing the photoluminescence (PL) spectra, spatial distributions of PL parameters and quantum efficiency in the samples under study. The PL spectra and spatial distributions of their parameters were obtained by using confocal PL microscopy. A WITec Alpha300 S confocal microscope coupled with an air cooled CCD camera was used. A CW laser diode emitting at 405 nm was exploited for excitation. The spatial resolution was in sub-micrometer domain in plane and ~1 micrometer perpendicularly to the sample surface. An integrating sphere with a xenon lamp coupled with a monochromator was used to measure the external quantum efficiency. All measurements were performed at room temperature. Chromatic properties of the light emission from the glasses and glass ceramics have been evaluated. We observed that the quantum efficiency of the glass ceramics is higher than that of the corresponding glass. The investigation of spatial distributions of PL parameters revealed that heat treatment of the glasses leads to a decrease in sample homogeneity. In the case of BaO-2SiO₂: Eu, 10 micrometer long needle-like objects are formed, when transforming the glass into glass ceramics. The comparison of PL spectra from within and outside the needle-like structure reveals that the ratio between intensities of PL bands associated with Eu²⁺ and Eu³⁺ ions is larger in the bright needle-like structures. This indicates a higher degree of crystallinity in the needle-like objects. We observed that the spectral positions of the PL bands are the same in the background and the needle-like areas, indicating that heat treatment imposes no significant change to the valence state of the europium ions. The evaluation of chromatic properties confirms applicability of the glasses under study for fabrication of white light sources with high thermal stability. The ability to combine barium and lithium glass matrixes and doping by Eu, Ce, Dy, and Tb enables optimization of chromatic properties.

Keywords: glass ceramics, luminescence, phosphor, silicate

Procedia PDF Downloads 317

Authors: Abdelkader Soumaya, Aymen Arfaoui, Noureddine Ben Ayed, Ali Kadri

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The Chotts belt represents the southernmost folded structure in the Tunisian Atlas domain. It is dominated by inherited deep extensional E-W trending fault zones, which are reactivated as strike-slip faults during the Cenozoic compression. By examining the geological maps at different scales and based on the fieldwork data, we propose new structural interpretations for the geometries and fault kinematics in the Chotts chain. A set of ENE-WSW right-lateral en echelon folds, with curved shapes and steeply inclined southern limbs, is visible in the map view of this belt. These asymmetric tight anticlines are affected by E-W trending fault segments linked by local bends and stepovers. The revealed kinematic indicators along one of these E-W striated faults (Tafferna segment), such as breccias and gently inclined slickenlines (N094, 80N, 15°W pitch angles), show direct evidence of dextral strike-slip movement. The calculated stress tensors from corresponding faults slip data reveal an overall strike-slip tectonic regime with reverse component and NW-trending sub-horizontal σ1 axis ranking between N130 to N150. From west to east, we distinguished several types of structures along the segmented dextral fault system of the Chotts Range. The NE-SW striking fold-thrust belt (~25 km-long) between two continuously linked E-W fault segments (NW of Tozeur town) has been suggested as a local restraining bend. The central part of the Chotts chain is occupied by the ENE-striking Ksar Asker anticlines (Taferna, Torrich, and Sif Laham), which are truncated by a set of E-W strike-slip fault segments. Further east, the fault segments of Hachichina and Sif Laham connected across the NW-verging asymmetric fold-thrust system of Bir Oum Ali, which can be interpreted as a left-stepping contractional bend (~20 km-long). The oriental part of the Chotts belt corresponds to an array of subparallel E-W oriented fault segments (i.e., Beidha, Bouloufa, El Haidoudi-Zemlet El Beidha) with similar lengths (around 10 km). Each of these individual separated segments is associated with curved ENE-trending en echelon right-stepping anticlines. These folds are affected by a set of conjugate R and R′ shear-type faults indicating a dextral strike-lip motion. In addition, the relay zones between these E-W overstepping fault segments define local releasing stepovers dominated by NW-SE subsidiary faults. Finally, the Chotts chain provides well-exposed examples of strike-slip tectonics along E-W distributed fault segments. Each fault zone shows a typical strike-slip architecture, including parallel fault segments connecting via local stepovers or bends. Our new structural interpretations for this region reveal a great influence of the E-W deep fault segments on regional tectonic deformations and stress field during the Cenozoic shortening.

Keywords: chotts belt, tunisian atlas, strike-slip fault, stepovers, fault segments

Procedia PDF Downloads 69

Authors: Egemen Sert, Leila Hedayatifar, Rachel A. Rigg, Amir Akhavan, Olha Buchel, Dominic Elias Saadi, Aabir Abubaker Kar, Alfredo J. Morales, Yaneer Bar-Yam

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The complexity of providing timely and cost-effective distribution of finished goods from industrial facilities to customers makes effective operational coordination difficult, yet effectiveness is crucial for maintaining customer service levels and sustaining a business. Logistics planning becomes increasingly complex with growing numbers of customers, varied geographical locations, the uncertainty of future orders, and sometimes extreme competitive pressure to reduce inventory costs. Linear optimization methods become cumbersome or intractable due to a large number of variables and nonlinear dependencies involved. Here we develop a complex systems approach to optimizing logistics networks based upon dimensional reduction methods and apply our approach to a case study of a manufacturing company. In order to characterize the complexity in customer behavior, we define a “customer space” in which individual customer behavior is described by only the two most relevant dimensions: the distance to production facilities over current transportation routes and the customer's demand frequency. These dimensions provide essential insight into the domain of effective strategies for customers; direct and indirect strategies. In the direct strategy, goods are sent to the customer directly from a production facility using box or bulk trucks. In the indirect strategy, in advance of an order by the customer, goods are shipped to an external warehouse near a customer using trains and then "last-mile" shipped by trucks when orders are placed. Each strategy applies to an area of the customer space with an indeterminate boundary between them. Specific company policies determine the location of the boundary generally. We then identify the optimal delivery strategy for each customer by constructing a detailed model of costs of transportation and temporary storage in a set of specified external warehouses. Customer spaces help give an aggregate view of customer behaviors and characteristics. They allow policymakers to compare customers and develop strategies based on the aggregate behavior of the system as a whole. In addition to optimization over existing facilities, using customer logistics and the k-means algorithm, we propose additional warehouse locations. We apply these methods to a medium-sized American manufacturing company with a particular logistics network, consisting of multiple production facilities, external warehouses, and customers along with three types of shipment methods (box truck, bulk truck and train). For the case study, our method forecasts 10.5% savings on yearly transportation costs and an additional 4.6% savings with three new warehouses.

Keywords: logistics network optimization, direct and indirect strategies, K-means algorithm, dimensional reduction

Procedia PDF Downloads 139