Search results for: multiple subordinated modeling

Authors: Merilin Ivanova Ivanova, Kalin Dimitrov Atanasov, Stefan Petrov Enchev

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Backgroud: Neuromyelitis optica spectrum disorder, also known as Devic’s disease, is a relapsing demyelinating autoimmune inflammatory disorder of the central nervous system associated with anti-aquaporin 4 (AQP4) antibodies that can manifest with devastating secondary neurological deficits. Most commonly affected are the optic nerves and the spinal cord-clinically this is often presented with optic neuritis (loss of vision), transverse myelitis(weakness or paralysis of extremities),lack of bladder and bowel control, numbness. APS is a core clinical entity of NMOSD and adds to the clinical representation the following symptoms: intractable nausea, vomiting and hiccup, it usually occurs isolated at onset, and can lead to a significant delay in the diagnosis. The condition may have features similar to multiple sclerosis (MS) but the episodes are worse in NMO and it is treated differently. It could be relapsing or monophasic. Possible complications are visual field defects and motor impairment, with potential blindness and irreversible motor deficits. In severe cases, myogenic respiratory failure ensues. The incidence of reported cases is approximately 0.3–4.4 per 100,000. Paediatric cases of NMOSD are rare but have been reported occasionally, comprising less than 5% of the reported cases. Objective: The case serves to show the difficulty when it comes to the diagnostic processes regarding a rare autoimmune disease with non- specific symptoms, taking large interval of rimes to reveal as complete clinical manifestation of the aforementioned syndrome, as well as the necessity of multidisciplinary approach in the setting of а general paediatric department in аn emergency hospital. Methods: itpatient's history, clinical presentation, and information from the used diagnostic tools(MRI with contrast of the central nervous system) lead us to the conclusion .This was later on confirmed by the positive results from the anti-aquaporin 4 (AQP4) antibody serology test. Conclusion: APS is a common symptom of NMOSD and is considered a challenge in a differential-diagnostic plan. Gaining an increased awareness of this disease/syndrome, obtaining a detailed patient history, and performing thorough physical examinations are essential if we are to reduce and avoid misdiagnosis.

Keywords: neuromyelitis, devic's disease, hiccup, autoimmune, MRI

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Authors: Bjorn Kierulf, Arun Chundru

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Over the past decade, collegiate rocketry teams have emerged across the country with various goals: space, liquid-fueled flight, etc. A critical piece of the development of knowledge within a club is the use of so-called "sounding rockets," whose goal is to take in-flight measurements that inform future rocket design. Common measurements include acceleration from inertial measurement units (IMU's), and altitude from barometers. With a properly tuned filter, these measurements can be used to find velocity, but are susceptible to noise, offset, and filter settings. Instead, velocity can be measured more directly and more instantaneously using a pitot tube, which operates by measuring the stagnation pressure. At supersonic speeds, an additional thermodynamic property is necessary to constrain the upstream state. One possibility is the stagnation temperature, measured by a thermocouple in the pitot tube. The routing of the pitot tube from the nosecone tip down to a pressure transducer is complicated by the nosecone's structure. Commercial-off-the-shelf (COTS) nosecones come with a removable metal tip (without a pitot tube). This provides the opportunity to make custom tips with integrated measurement systems without making the nosecone from scratch. The main design constraint is how the nosecone tip is held down onto the nosecone, using the tension in a threaded rod anchored to a bulkhead below. Because the threaded rod connects into a threaded hole in the center of the nosecone tip, the pitot tube follows a winding path, and the pressure fitting is off-center. Two designs will be presented in the paper, one with a curved pitot tube and a coaxial design that eliminates the need for the winding path by routing pressure through a structural tube. Additionally, three manufacturing methods will be presented for these designs: bound powder filament metal 3D printing, stereo-lithography (SLA) 3D printing, and traditional machining. These will employ three different materials, copper, steel, and proprietary resin. These manufacturing methods and materials are relatively low cost, thus accessible to student researchers. These designs and materials cover multiple use cases, based on how fast the sounding rocket is expected to travel and how important heating effects are - to measure and to avoid melting. This paper will include drawings showing key features and an overview of the design changes necessitated by the manufacture. It will also include a look at the successful use of these nosecone tips and the data they have gathered to date.

Keywords: additive manufacturing, machining, pitot tube, sounding rocketry

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Authors: Ahmed Borg, Elsa Aristodemou, Attia Attia

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Well control involves managing the circulating drilling fluid within the wells and avoiding kicks and blowouts as these can lead to losses in human life and drilling facilities. Current practices for good control incorporate predictions of pressure losses through computational models. Developing a realistic hydraulic model for a good control problem is a very complicated process due to the existence of a complex multiphase region, which usually contains a non-Newtonian drilling fluid and the miscibility of formation gas in drilling fluid. The current approaches assume an inaccurate flow fluid model within the well, which leads to incorrect pressure loss calculations. To overcome this problem, researchers have been considering the more complex two-phase fluid flow models. However, even these more sophisticated two-phase models are unsuitable for applications where pressure dynamics are important, such as in managed pressure drilling. This study aims to develop and implement new fluid flow models that take into consideration the miscibility of fluids as well as their non-Newtonian properties for enabling realistic kick treatment. furthermore, a corresponding numerical solution method is built with an enriched data bank. The research work considers and implements models that take into consideration the effect of two phases in kick treatment for well control in conventional drilling. In this work, a corresponding numerical solution method is built with an enriched data bank. Software STARCCM+ for the computational studies to study the important parameters to describe wellbore multiphase flow, the mass flow rate, volumetric fraction, and velocity of each phase. Results showed that based on the analysis of these simulation studies, a coarser full-scale model of the wellbore, including chemical modeling established. The focus of the investigations was put on the near drill bit section. This inflow area shows certain characteristics that are dominated by the inflow conditions of the gas as well as by the configuration of the mud stream entering the annulus. Without considering the gas solubility effect, the bottom hole pressure could be underestimated by 4.2%, while the bottom hole temperature is overestimated by 3.2%. and without considering the heat transfer effect, the bottom hole pressure could be overestimated by 11.4% under steady flow conditions. Besides, larger reservoir pressure leads to a larger gas fraction in the wellbore. However, reservoir pressure has a minor effect on the steady wellbore temperature. Also as choke pressure increases, less gas will exist in the annulus in the form of free gas.

Keywords: multiphase flow, well- control, STARCCM+, petroleum engineering and gas technology, computational fluid dynamic

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Authors: Kumar Divyendra

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Underwater Sensor Networks (UWSNs) have wide applications in areas such as water quality monitoring, marine wildlife management etc. A typical UWSN system consists of a set of sensors deployed randomly underwater which communicate with each other using acoustic links. RF communication doesn't work underwater, and GPS too isn't available underwater. Additionally Automated Underwater Vehicles (AUVs) are deployed to collect data from some special nodes called Cluster Heads (CHs). These CHs aggregate data from their neighboring nodes and forward them to the AUVs using optical links when an AUV is in range. This helps reduce the number of hops covered by data packets and helps conserve energy. We consider the three-dimensional model of the UWSN. Nodes are initially deployed randomly underwater. They attach themselves to the surface using a rod and can only move upwards or downwards using a pump and bladder mechanism. We use graph theory concepts to maximize the coverage volume while every node maintaining connectivity with at least one surface node. We treat the surface nodes as landmarks and each node finds out its hop distance from every surface node. We treat these hop-distances as coordinates and use them for AUV navigation. An AUV intending to move closer to a node with given coordinates moves hop by hop through nodes that are closest to it in terms of these coordinates. In absence of GPS, multiple different approaches like Inertial Navigation System (INS), Doppler Velocity Log (DVL), computer vision-based navigation, etc., have been proposed. These systems have their own drawbacks. INS accumulates error with time, vision techniques require prior information about the environment. We propose a method that makes use of the earth's magnetic field values for navigation and combines it with other methods that simultaneously increase the coverage volume under the UWSN. The AUVs are fitted with magnetometers that measure the magnetic intensity (I), horizontal inclination (H), and Declination (D). The International Geomagnetic Reference Field (IGRF) is a mathematical model of the earth's magnetic field, which provides the field values for the geographical coordinateson earth. Researchers have developed an inverse deep learning model that takes the magnetic field values and predicts the location coordinates. We make use of this model within our work. We combine this with with the hop-by-hop movement described earlier so that the AUVs move in such a sequence that the deep learning predictor gets trained as quickly and precisely as possible We run simulations in MATLAB to prove the effectiveness of our model with respect to other methods described in the literature.

Keywords: clustering, deep learning, network backbone, parallel computing

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Authors: Zeite Shumneiyang Koireng

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Liberation is the act of liberating or the state of being liberated. Indian philosophy, in general, understands liberation as moksa, which etymological is derived from the Sanskrit root muc+ktin meaning to loose, set free, to let go, discharge, release, liberate, deliver, etc. According to Indian schools of thought, moksa is the highest value on realizing which nothing remains to be realized. It is the cessation of birth and death, all kinds of pain and at the same time, it is the realization of one’s own self. Sankara’s Advaita philosophy is based on the following propositions: Brahman is the only Reality; the world has apparent reality, and the soul is not different from Brahman. According to Sankara, Brahman is the basis on which the world form appears; it is the sustaining ground of all various modification. It is the highest self and the self of all reveals himself by dividing himself [ as it was in the form of various objects] in multiple ways. The whole world is the manifestation of the Supreme Being. Brahman modifying itself into the Atman or internal self of all things is the world. Since Brahman is the Upadhana karana of the world, the sruti speaks of the world as the modification of Brahman into the Atman of the effect. Contemplation as the fulfillment of man finds a radical foundation in Aquinas teaching concerning the natural end or as he also referred to it, natural desire. The third book of the Summa Contra Gentiles begins the study of happiness with a consideration of natural desire. According to him, all creatures, even those devoid of understanding are ordered to God as an ultimate end. Intrinsically, a part of every nature is a tendency or inclination, originating in the natural form and tendency toward the end for which the possessor of nature exists. It is the study of the nature and finality of inclination that Aquinas establishes through an argument of induction man’s Contemplation of God as the fulfillment of his nature. The present paper is attempted to critically approach two important, seminal and originated thought, representing Indian and Western traditions which mark on the thinking of their respective times. Both these thoughts- Advaitic concept of Liberation in the Indian tradition and the concept of Contemplation in Thomas Aquinas’ Summa Contra Gentiles’- confront directly the question of the ultimate meaning of human existence. According to Sankara, it is knowledge and knowledge alone which is the means of moksa and the highest knowledge is moksa itself. Liberation in Sankara Vedanta is attained as a process of purification of self, which gradually and increasingly turns into purer and purer intentional construction. Man’s inner natural tendency for Aquinas is towards knowledge. The human subject is driven to know more and more about reality and in particular about the highest reality. Contemplation of this highest reality is fulfillment in the philosophy of Aquinas. Rather, Contemplation is the perfect activity in man’s present state of existence.

Keywords: liberation, Brahman, contemplation, fulfillment

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Authors: S. Vivek, Sharad Sharan, R. Arvind, D. V. Praveen, J. Vigneshwar, S. Ajith, V. R. Sanal Kumar

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In this paper numerical studies have been carried out to examine the starting transient flow features of high-performance solid propellant rocket motors with different port geometries but with same propellant loading density. Numerical computations have been carried out using a 3D SST k-ω turbulence model. This code solves standard k-omega turbulence equations with shear flow corrections using a coupled second order implicit unsteady formulation. In the numerical study, a fully implicit finite volume scheme of the compressible, Reynolds-Averaged, Navier-Stokes equations are employed. We have observed from the numerical results that in solid rocket motors with highly loaded propellants having divergent port geometry the hot igniter gases can create pre-ignition thrust oscillations due to flow unsteadiness and recirculation. Under these conditions the convective flux to the surface of the propellant will be enhanced, which will create reattachment point far downstream of the transition region and it will create a situation for secondary ignition and formation of multiple-flame fronts. As a result the effective time required for the complete burning surface area to be ignited comes down drastically giving rise to a high pressurization rate (dp/dt) in the second phase of starting transient. This in effect could lead to starting thrust oscillations and eventually a hard start of the solid rocket motor. We have also observed that the igniter temperature fluctuations will be diminished rapidly and will reach the steady state value faster in the case of solid propellant rocket motors with convergent port than the divergent port irrespective of the igniter total pressure. We have concluded that the thrust oscillations and unexpected thrust spike often observed in solid rockets with non-uniform ports are presumably contributed due to the joint effects of the geometry dependent driving forces, transient burning and the chamber gas dynamics forces. We also concluded that the prudent selection of the port geometry, without altering the propellant loading density, for damping the total temperature fluctuations within the motor is a meaningful objective for the suppression and control of instability and/or pressure/thrust oscillations often observed in solid propellant rocket motors with non-uniform port geometry.

Keywords: ignition transient, solid rockets, starting transient, thrust transient

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Authors: A. Kesraoui, M. Seffen

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Applications of adsorption onto activated carbon for water treatment are well known. The process has been demonstrated to be widely effective for removing dissolved organic substances from wastewaters, but this treatment has a major drawback is the high operating cost. The main goal of our research work is to improve the retention capacity of Tunisian biomass for the depollution of industrial wastewater and retention of pollutants considered toxic. The biosorption process is based on the retention of molecules and ions onto a solid surface composed of biological materials. The evaluation of the potential use of these materials is important to propose as an alternative to the adsorption process generally expensive, used to remove organic compounds. Indeed, these materials are very abundant in nature and are low cost. Certainly, the biosorption process is effective to remove the pollutants, but it presents a slow kinetics. The improvement of the biosorption rates is a challenge to make this process competitive with respect to oxidation and adsorption onto lignocellulosic fibers. In this context, the alternating current appears as a new alternative, original and a very interesting phenomenon in the acceleration of chemical reactions. Our main goal is to increase the retention acceleration of dyes (indigo carmine, methylene blue) and phenol by using a new alternative: alternating current. The adsorption experiments have been performed in a batch reactor by adding some of the adsorbents in 150 mL of pollutants solution with the desired concentration and pH. The electrical part of the mounting comprises a current source which delivers an alternating current voltage of 2 to 15 V. It is connected to a voltmeter that allows us to read the voltage. In a 150 mL capacity cell, we plunged two zinc electrodes and the distance between two Zinc electrodes has been 4 cm. Thanks to alternating current, we have succeeded to improve the performance of activated carbon by increasing the speed of the indigo carmine adsorption process and reducing the treatment time. On the other hand, we have studied the influence of the alternating current on the biosorption rate of methylene blue onto Luffa cylindrica fibers and the hybrid material (Luffa cylindrica-ZnO). The results showed that the alternating current accelerated the biosorption rate of methylene blue onto the Luffa cylindrica and the Luffa cylindrica-ZnO hybrid material and increased the adsorbed amount of methylene blue on both adsorbents. In order to improve the removal of phenol, we performed the coupling between the alternating current and the biosorption onto two adsorbents: Luffa cylindrica and the hybrid material (Luffa cylindrica-ZnO). In fact, the alternating current has succeeded to improve the performance of adsorbents by increasing the speed of the adsorption process and the adsorption capacity and reduce the processing time.

Keywords: adsorption, alternating current, dyes, modeling

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Authors: Jill Stephenson, Marie Vaganay, Robert Cameron, Caoimhe McGurk, Neil Hewitt

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Purpose: The key aim of the research was to identify the secondary stressors experienced by businesses affected by single or repeated flooding and to determine to what extent businesses were affected by these stressors, along with any resulting impact on health. Additionally, the research aimed to establish the likelihood of businesses being re-exposed to the secondary stressors through assessing awareness of flood risk, implementation of property protection measures and level of community resilience. Design/methodology/approach: The chosen research method involved the distribution of a questionnaire survey to businesses affected by either single or repeated flood events. The questionnaire included the Impact of Event Scale (a 15-item self-report measure which assesses subjective distress caused by traumatic events). Findings: 55 completed questionnaires were returned by flood impacted businesses. 89% of the businesses had sustained internal flooding while 11% had experienced external flooding. The results established that the key secondary stressors experienced by businesses, in order of priority, were: flood damage, fear of reoccurring flooding, prevention of access to the premise/closure, loss of income, repair works, length of closure and insurance issues. There was a lack of preparedness for potential future floods and consequent vulnerability to the emergence of secondary stressors among flood affected businesses, as flood resistance or flood resilience measures had only been implemented by 11% and 13% respectively. In relation to the psychological repercussions, the Impact of Event scores suggested that potential prevalence of post-traumatic stress disorder (PTSD) was noted among 8 out of 55 respondents (l5%). Originality/value: The results improve understanding of the enduring repercussions of flood events on businesses, indicating that not only residents may be susceptible to the detrimental health impacts of flood events and single flood events may be just as likely as reoccurring flooding to contribute to ongoing stress. Lack of financial resources is a possible explanation for the lack of implementation of property protection measures among businesses, despite 49% experiencing flooding on multiple occasions. Therefore it is recommended that policymakers should consider potential sources of financial support or grants towards flood defences for flood impacted businesses. Any form of assistance should be made available to businesses at the earliest opportunity as there was no significant association between the time of the last flood event and the likelihood of experiencing PTSD symptoms.

Keywords: flood event, flood resilience, flood resistance, PTSD, secondary stressors

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Authors: Petra Hofmann, Dana Koniel, Jussi Luukkanen, Walter Nieminen, Lea Hannola, Ilkka Donoghue

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The Covid-19 pandemic forced people to isolate and become physically less connected. The pandemic hasnot only reshaped people’s behaviours and needs but also accelerated digital transformation (DT). DT of cities has become an imperative with the outlook of converting them into smart cities in the future. Embedding digital infrastructure and smart city initiatives as part of the normal design, construction, and operation of cities provides a unique opportunity to improve connection between people. Internet of Things (IoT) is an emerging technology and one of the drivers in DT. It has disrupted many industries by introducing different services and business models, and IoT solutions are being applied in multiple fields, including smart cities. As IoT and data are fundamentally linked together, IoT solutions can only create value if the data generated by the IoT devices is analysed properly. Extracting relevant conclusions and actionable insights by using established techniques, data analytics contributes significantly to the growth and success of IoT applications and investments. Companies must grasp DT and be prepared to redesign their offerings and business models to remain competitive in today’s marketplace. As there are many IoT solutions available today, the amount of data is tremendous. The challenge for companies is to understand what solutions to focus on and how to prioritise and which data to differentiate from the competition. This paper explains how IoT and data analytics can impact competitive advantage and how companies should approach IoT and data analytics to translate them into concrete offerings and solutions in the smart city context. The study was carried out as a qualitative, literature-based research. A case study is provided to validate the preservation of company’s competitive advantage through smart city solutions. The results of the researchcontribution provide insights into the different factors and considerations related to creating competitive advantage through IoT and data analytics deployment in the smart city context. Furthermore, this paper proposes a framework that merges the factors and considerations with examples of offerings and solutions in smart cities. The data collected through IoT devices, and the intelligent use of it, can create a competitive advantage to companies operating in smart city business. Companies should take into consideration the five forces of competition that shape industries and pay attention to the technological, organisational, and external contexts which define factors for consideration of competitive advantages in the field of IoT and data analytics. Companies that can utilise these key assets in their businesses will most likely conquer the markets and have a strong foothold in the smart city business.

Keywords: internet of things, data analytics, smart cities, competitive advantage

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Authors: Rosaline Govender, Shubnam Rambharos

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Universities are, to a certain extent, the source of under-preparedness ideologically, structurally, and pedagogically, particularly since organizational cultures often alienate students by failing to enable epistemological access. This is evident in the unsustainably low graduation rates that characterize South African higher education, which indicate that under 30% graduate in minimum time, under two-thirds graduate within 6 years, and one-third have not graduated after 10 years. Although the statistics for the Faculty of Accounting and Informatics at the Durban University of Technology (DUT) in South Africa have improved significantly from 2019 to 2021, the graduation (32%), throughput (50%), and dropout rates (16%) are still a matter for concern as the graduation rates, in particular, are quite similar to the national statistics. For our students to succeed, higher education should take a multi-pronged approach to ensure student success, and student engagement is one of the ways to support our students. Student engagement depends not only on students’ teaching and learning experiences but, more importantly, on their social and academic integration, their sense of belonging, and their emotional connections in the institution. Such experiences need to challenge students academically and engage their intellect, grow their communication skills, build self-discipline, and promote confidence. The aim of this mixed methods study is to explore the multi-pronged nature of student success within the Faculty of Accounting and Informatics at DUT and focuses on the enabling and constraining factors of student success. The sources of data were the Mid-year student experience survey (N=60), the Hambisa Student Survey (N=85), and semi structured focus group interviews with first, second, and third year students of the Faculty of Accounting and Informatics Hambisa program. The Hambisa (“Moving forward”) focus area is part of the Siyaphumelela 2.0 project at DUT and seeks to understand the multiple challenges that are impacting student success which create a large “middle” cohort of students that are stuck in transition within academic programs. Using the lens of the sociocultural influences on student engagement framework, we conducted a thematic analysis of the two surveys and focus group interviews. Preliminary findings indicate that living conditions, choice of program, access to resources, motivation, institutional support, infrastructure, and pedagogical practices impact student engagement and, thus, student success. It is envisaged that the findings from this project will assist the university in being better prepared to enable student success.

Keywords: social and academic integration, socio-cultural influences, student engagement, student success

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Authors: Sevinj Asgarova

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Within the last few decades, major advances in the field of prenatal testing have transpired yet little research regarding the experiences of mothers who chose to continue their pregnancies after prenatally receiving a diagnosis of Down Syndrome (DS) has been undertaken. Using social constructionism and interpretive description, this retrospective research study explores this topic from the point of view of the mothers involved and provides insight as to how the experience could be improved. Using purposive sampling, 23 mothers were recruited from British Columbia (n=11) and Ontario (n=12) in Canada. Data retrieved through semi-structured in-depth interviews were analyzed using inductive, constant comparative analysis, the major analytical techniques of interpretive description. Four primary phases emerged from the data analysis 1) healthcare professional-mothers communications, 2) initial emotional response, 3) subsequent decision-making and 4) an adjustment and reorganization of lifestyle to the preparation for the birth of the child. This study validates the individualized and contextualized nature of mothers’ decisions as influenced by multiple factors, with moral values/spiritual beliefs being significant. The mothers’ ability to cope was affected by the information communicated to them about their unborn baby’s diagnosis and the manner in which that information was delivered to them. Mothers used emotional coping strategies, dependent upon support from partners, family, and friends, as well as from other families who have children with DS. Additionally, they employed practical coping strategies, such as engaging in healthcare planning, seeking relevant information, and reimagining and reorganizing their lifestyle. Over time many families gained a sense of control over their situation and readjusted to the preparation for the birth of the child. Many mothers expressed the importance of maintaining positivity and hopefulness with respect to positive outcomes and opportunities for their children. The comprehensive information generated through this study will also provide healthcare professionals with relevant information to assist them in understanding the informational and emotional needs of these mothers. This should lead to an improvement in their practice and enhance their ability to intervene appropriately and effectively, better offering improved support to parents dealing with a diagnosis of DS for their child.

Keywords: continuing affected pregnancy, decision making, disability, down syndrome, eugenic social attitudes, inequalities, life change events, prenatal care, prenatal testing, qualitative research, social change, social justice

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Authors: Rebecca Richards Steed, James Van Derslice, Ken Smith, Richard Medina, Amanda Bakian

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Elucidating gene-environment interactions for heritable disease outcomes is an emerging area of disease research, with genetic studies informing hypotheses for environment and gene interactions underlying some of the most confounding diseases of our time, like autism spectrum disorder (ASD). Geography has thus far played a key role in identifying environmental factors contributing to disease, but its use can be broadened to include genetic and environmental factors that have a synergistic effect on disease. Through the use of family pedigrees and disease outcomes with life-course residential histories, space-time clustering of generations at critical developmental windows can provide further understanding of (1) environmental factors that contribute to disease patterns in families, (2) susceptible critical windows of development most impacted by environment, (3) and that are most likely to lead to an ASD diagnosis. This paper introduces a retrospective case-control study that utilizes pedigree data, health data, and residential life-course location points to find space-time clustering of ancestors with a grandchild/child with a clinical diagnosis of ASD. Finding space-time clusters of ancestors at critical developmental windows serves as a proxy for shared environmental exposures. The authors refer to geographic life-course exposures as geographic legacies. Identifying space-time clusters of ancestors creates a bridge for researching exposures of past generations that may impact modern-day progeny health. Results from the space-time cluster analysis show multiple clusters for the maternal and paternal pedigrees. The paternal grandparent pedigree resulted in the most space-time clustering for birth and childhood developmental windows. No statistically significant clustering was found for adolescent years. These results will be further studied to identify the specific share of space-time environmental exposures. In conclusion, this study has found significant space-time clusters of parents, and grandparents for both maternal and paternal lineage. These results will be used to identify what environmental exposures have been shared with family members at critical developmental windows of time, and additional analysis will be applied.

Keywords: family pedigree, environmental exposure, geographic legacy, medical geography, transgenerational inheritance

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Authors: Barbara Peric

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The study of acquiring a third and additional language has garnered significant focus within second language acquisition (SLA) research. Initially, it was commonly viewed as merely an extension of second language acquisition (SLA). However, in the last two decades, numerous researchers have emphasized the need to recognize the unique characteristics of third language acquisition (TLA). This recognition is crucial for understanding the intricate cognitive processes that arise from the interaction of more than two linguistic systems in the learner's mind. This study investigates cross-linguistic influences in the acquisition of Spanish as a fourth language by students who have Croatian as a first language (L1). English as a second language (L2), and Italian as a third language (L3). Observational data suggests that influence or transfer of linguistic elements can arise not only from one's native language (L1) but also from non-native languages. This implies that, for individuals proficient in multiple languages, the native language doesn't consistently hold a superior position. Instead, it should be examined alongside other potential sources of linguistic transfer. Earlier studies have demonstrated that high proficiency in a second language can significantly impact cross-linguistic influences when acquiring a third and additional language. Among the extensively examined factors, the typological relationship stands out as one of the most scrutinized variables. The goal of the present study was to explore whether language typology and formal similarity or proficiency in the second language had a more significant impact on L4 acquisition. Participants in this study were third-year undergraduate students at Rochester Institute of Technology’s subsidiary in Croatia (RIT Croatia). All the participants had exclusively Croatian as L1, English as L2, Italian as L3 and were learning Spanish as L4 at the time of the study. All the participants had a high level of proficiency in English and low level of proficiency in Italian. Based on the error analysis the findings indicate that for some types of lexical errors such as coinage, language typology had a more significant impact and Italian language was the preferred source of transfer despite the law proficiency in that language. For some other types of lexical errors, such as calques, second language proficiency had a more significant impact, and English language was the preferred source of transfer. On the other hand, Croatian, Italian, and Spanish are more similar in the area of morphology due to higher degree of inflection compared to English and the strongest influence of the Croatian language was precisely in the area of morphology. The results emphasize the need to consider linguistic resemblances between the native language (L1) and the third and additional language as well as the learners' proficiency in the second language when developing successful teaching strategies for acquiring the third and additional language. These conclusions add to the expanding knowledge in the realm of Second Language Acquisition (SLA) and offer practical insights for language educators aiming to enhance the effectiveness of learning experiences in acquiring a third and additional language.

Keywords: third and additional language acquisition, cross-linguistic influences, language proficiency, language typology

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Authors: Mohd Azman Abdul Latif, Erwan Basiron

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A flaw or drift from expected operational performance in one component (NAND, PMIC, controller, DRAM, etc.) may affect the reliability of the entire Solid State Drive (SSD) system. Therefore, it is important to ensure the required quality of each individual component through qualification testing specified using standards or user requirements. Qualification testing is time-consuming and comes at a substantial cost for product manufacturers. A highly technical team, from all the eminent stakeholders is embarking on reliability prediction from beginning of new product development, identify critical to reliability parameters, perform full-blown characterization to embed margin into product reliability and establish control to ensure the product reliability is sustainable in the mass production. The paper will discuss a comprehensive development framework, comprehending SSD end to end from design to assembly, in-line inspection, in-line testing and will be able to predict and to validate the product reliability at the early stage of new product development. During the design stage, the SSD will go through intense reliability margin investigation with focus on assembly process attributes, process equipment control, in-process metrology and also comprehending forward looking product roadmap. Once these pillars are completed, the next step is to perform process characterization and build up reliability prediction modeling. Next, for the design validation process, the reliability prediction specifically solder joint simulator will be established. The SSD will be stratified into Non-Operating and Operating tests with focus on solder joint reliability and connectivity/component latent failures by prevention through design intervention and containment through Temperature Cycle Test (TCT). Some of the SSDs will be subjected to the physical solder joint analysis called Dye and Pry (DP) and Cross Section analysis. The result will be feedbacked to the simulation team for any corrective actions required to further improve the design. Once the SSD is validated and is proven working, it will be subjected to implementation of the monitor phase whereby Design for Assembly (DFA) rules will be updated. At this stage, the design change, process and equipment parameters are in control. Predictable product reliability at early product development will enable on-time sample qualification delivery to customer and will optimize product development validation, effective development resource and will avoid forced late investment to bandage the end-of-life product failures. Understanding the critical to reliability parameters earlier will allow focus on increasing the product margin that will increase customer confidence to product reliability.

Keywords: e2e reliability prediction, SSD, TCT, solder joint reliability, NUDD, connectivity issues, qualifications, characterization and control

Procedia PDF Downloads 174

Authors: Md. Rafiul Biswas, Uzair Shah, Mohammad Alkayal, Zubair Shah, Othman Althawadi, Kamila Swart

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Background: Social media platforms play a significant role in the mediated consumption of sport, especially so for sport mega-event. The characteristics of Twitter data (e.g., user mentions, retweets, likes, #hashtag) accumulate the users in one ground and spread information widely and quickly. Analysis of Twitter data can reflect the public attitudes, behavior, and sentiment toward a specific event on a larger scale than traditional surveys. Qatar is going to be the first Arab country to host the mega sports event FIFA World Cup 2022 (Q22). Qatar has hosted the FIFA Arab Cup 2021 (FAC21) to serve as a preparation for the mega-event. Objectives: This study investigates public sentiments and experiences about FAC21 and provides an insight to enhance the public experiences for the upcoming Q22. Method: FCA21-related tweets were downloaded using Twitter Academic research API between 01 October 2021 to 18 February 2022. Tweets were divided into three different periods: before T1 (01 Oct 2021 to 29 Nov 2021), during T2 (30 Nov 2021 -18 Dec 2021), and after the FAC21 T3 (19 Dec 2021-18 Feb 2022). The collected tweets were preprocessed in several steps to prepare for analysis; (1) removed duplicate and retweets, (2) removed emojis, punctuation, and stop words (3) normalized tweets using word lemmatization. Then, rule-based classification was applied to remove irrelevant tweets. Next, the twitter-XLM-roBERTa-base model from Huggingface was applied to identify the sentiment in the tweets. Further, state-of-the-art BertTopic modeling will be applied to identify trending topics over different periods. Results: We downloaded 8,669,875 Tweets posted by 2728220 unique users in different languages. Of those, 819,813 unique English tweets were selected in this study. After splitting into three periods, 541630, 138876, and 139307 were from T1, T2, and T3, respectively. Most of the sentiments were neutral, around 60% in different periods. However, the rate of negative sentiment (23%) was high compared to positive sentiment (18%). The analysis indicates negative concerns about FAC21. Therefore, we will apply BerTopic to identify public concerns. This study will permit the investigation of people’s expectations before FAC21 (e.g., stadium, transportation, accommodation, visa, tickets, travel, and other facilities) and ascertain whether these were met. Moreover, it will highlight public expectations and concerns. The findings of this study can assist the event organizers in enhancing implementation plans for Q22. Furthermore, this study can support policymakers with aligning strategies and plans to leverage outstanding outcomes.

Keywords: FIFA Arab Cup, FIFA, Twitter, machine learning

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Authors: Hui-Ling Yang, Kuei-Ru Chou

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Background: Studies show that cognitive training can effectively delay cognitive failure. However, there are several gaps in the previous studies of cognitive training in mild cognitive impairment: 1) previous studies enrolled mostly healthy older adults, with few recruiting older adults with cognitive impairment; 2) they also had limited generalizability and lacked long-term follow-up data and measurements of the activities of daily living functional impact. Moreover, only 37% were randomized controlled trials (RCT). 3) Limited cognitive training has been specifically developed for mild cognitive impairment. Objective: This study sought to investigate the changes in cognitive function, activities of daily living and degree of depressive symptoms in older adults with mild cognitive impairment after cognitive training. Methods: This double-blind randomized controlled study has a 2-arm parallel group design. Study subjects are older adults diagnosed with mild cognitive impairment in residential care facilities. 124 subjects will be randomized by the permuted block randomization, into intervention group (Cognitive training, CT), or active control group (Passive information activities, PIA). Therapeutic adherence, sample attrition rate, medication compliance and adverse events will be monitored during the study period, and missing data analyzed using intent-to-treat analysis (ITT). Results: Training sessions of the CT group are 45 minutes/day, 3 days/week, for 12 weeks (36 sessions each). The training of active control group is the same as CT group (45min/day, 3days/week, for 12 weeks, for a total of 36 sessions). The primary outcome is cognitive function, using the Mini-Mental Status Examination (MMSE); the secondary outcome indicators are: 1) activities of daily living, using the Lawton’s Instrumental Activities of Daily Living (IADLs) and 2) degree of depressive symptoms, using the Geriatric Depression Scale-Short form (GDS-SF). Latent growth curve modeling will be used in the repeated measures statistical analysis to estimate the trajectory of improvement by examining the rate and pattern of change in cognitive functions, activities of daily living and degree of depressive symptoms for intervention efficacy over time, and the effects will be evaluated immediate post-test, 3 months, 6 months and one year after the last session. Conclusions: We constructed a rigorous CT program adhering to the Consolidated Standards of Reporting Trials (CONSORT) reporting guidelines. We expect to determine the improvement in cognitive function, activities of daily living and degree of depressive symptoms of older adults with mild cognitive impairment after using the CT.

Keywords: mild cognitive impairment, cognitive training, randomized controlled study

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Authors: Benjamin Castillo, Luis Pastenes, Fernando Cerdova

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The contamination of food by microbial agents is a common problem in the industry, especially regarding the elaboration of animal source products. Incorrect manipulation of the machinery or on the raw materials can cause a decrease in production or an epidemiological outbreak due to intoxication. In order to improve food product quality, different methods have been used to reduce or, at least, to slow down the growth of the pathogens, especially deteriorated, infectious or toxigenic bacteria. These methods are usually carried out under low temperatures and short processing time (abiotic agents), along with the application of antibacterial substances, such as bacteriocins (biotic agents). This, in a controlled and efficient way that fulfills the purpose of bacterial control without damaging the final product. Therefore, the objective of the present study is to design a secondary mathematical model that allows the prediction of both the biotic and abiotic factor impact associated with animal source food processing. In order to accomplish this objective, the authors propose a three-dimensional differential equation model, whose components are: bacterial growth, release, production and artificial incorporation of bacteriocins and changes in pH levels of the medium. These three dimensions are constantly being influenced by the temperature of the medium. Secondly, this model adapts to an idealized situation of cross-contamination animal source food processing, with the study agents being both the animal product and the contact surface. Thirdly, the stochastic simulations and the parametric sensibility analysis are compared with referential data. The main results obtained from the analysis and simulations of the mathematical model were to discover that, although bacterial growth can be stopped in lower temperatures, even lower ones are needed to eradicate it. However, this can be not only expensive, but counterproductive as well in terms of the quality of the raw materials and, on the other hand, higher temperatures accelerate bacterial growth. In other aspects, the use and efficiency of bacteriocins are an effective alternative in the short and medium terms. Moreover, an indicator of bacterial growth is a low-level pH, since lots of deteriorating bacteria are lactic acids. Lastly, the processing times are a secondary agent of concern when the rest of the aforementioned agents are under control. Our main conclusion is that when acclimating a mathematical model within the context of the industrial process, it can generate new tools that predict bacterial contamination, the impact of bacterial inhibition, and processing method times. In addition, the mathematical modeling proposed logistic input of broad application, which can be replicated on non-meat food products, other pathogens or even on contamination by crossed contact of allergen foods.

Keywords: bacteriocins, cross-contamination, mathematical model, temperature

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Authors: Samantha Meyerholz

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MSKCC offers patients cutting edge cancer care with the highest quality standards. However, many patients and industry members do not realize that the operations of the Immunology Histology Lab (IHC) are the backbone for carrying out this mission. The IHC lab manufactures blocks and slides containing critical tissue samples that will be read by a Pathologist to diagnose and dictate a patient’s treatment course. The lab processes 200 requests daily, leading to the generation of approximately 2,000 slides and 1,100 blocks each day. Lab material is transported through labeling, cutting, staining and sorting manufacturing stations, while being managed by multiple techs throughout the space. The quality of the stain as well as wait times associated with processing requests, is directly associated with patients receiving rapid treatments and having a wider range of care options. This project aims to improve slide request turnaround time for rush and non-rush cases, while increasing the quality of each request filled (no missing slides or poorly stained items). Rush cases are to be filled in less than 24 hours, while standard cases are allotted a 48 hour time period. Reducing turnaround times enable patients to communicate sooner with their clinical team regarding their diagnosis, ultimately leading faster treatments and potentially better outcomes. Additional project goals included streamlining tech and material workflow, while reducing waste and increasing efficiency. This project followed a DMAIC structure with emphasis on lean and ergonomic principles that could be integrated into an evolving lab culture. Load times and batching processes were analyzed using process mapping, FMEA analysis, waste analysis, engineering observation, 5S and spaghetti diagramming. Reduction of lab technician movement as well as their body position at each workstation was of top concern to pathology leadership. With new equipment being brought into the lab to carry out workflow improvements, screen and tool placement was discussed with the techs in focus groups, to reduce variation and increase comfort throughout the workspace. 5S analysis was completed in two phases in the IHC lab, helping to drive solutions that reduced rework and tech motion. The IHC lab plans to continue utilizing these techniques to further reduce the time gap between tissue analysis and cancer care.

Keywords: engineering, ergonomics, healthcare, lean

Procedia PDF Downloads 223

Authors: Mohammad Bagher Anvari, Arman Shojaei

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Incremental launching, a widely adopted bridge erection technique, offers numerous advantages for bridge designers. However, accurately simulating and modeling the dynamic behavior of the bridge during each step of the launching process proves to be tedious and time-consuming. The perpetual variation of internal forces within the deck during construction stages adds complexity, exacerbated further by considerations of other load cases, such as support settlements and temperature effects. As a result, there is an urgent need for a reliable, simple, economical, and fast algorithmic solution to model bridge construction stages effectively. This paper presents a novel Finite Element (FE) model that focuses on studying the static behavior of bridges during the launching process. Additionally, a simple method is introduced to normalize all quantities in the problem. The new FE model overcomes the limitations of previous models, enabling the simulation of all stages of launching, which conventional models fail to achieve due to underlying assumptions. By leveraging the results obtained from the new FE model, this study proposes solutions to improve the accuracy of conventional models, particularly for the initial stages of bridge construction that have been neglected in previous research. The research highlights the critical role played by the first span of the bridge during the initial stages, a factor often overlooked in existing studies. Furthermore, a new and simplified model termed the "semi-infinite beam" model, is developed to address this oversight. By utilizing this model alongside a simple optimization approach, optimal values for launching nose specifications are derived. The practical applications of this study extend to optimizing the nose-deck system of incrementally launched bridges, providing valuable insights for practical usage. In conclusion, this paper introduces a comprehensive Finite Element model for studying the static behavior of bridges during incremental launching. The proposed model addresses limitations found in previous approaches and offers practical solutions to enhance accuracy. The study emphasizes the importance of considering the initial stages and introduces the "semi-infinite beam" model. Through the developed model and optimization approach, optimal specifications for launching nose configurations are determined. This research holds significant practical implications and contributes to the optimization of incrementally launched bridges, benefiting both the construction industry and bridge designers.

Keywords: incremental launching, bridge construction, finite element model, optimization

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Authors: Antonio Pratelli, Lorenzo Brocchini, Reginald Roy Souleyrette

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A rotary is a traffic circle intersection where vehicles entering from branches give priority to circulating flow. Vehicles entering the intersection from converging roads move around the central island and weave out of the circle into their desired exiting branch. This creates merging and diverging conflicts among any entry and its successive exit, i.e., a section. Therefore, rotary capacity models are usually based on the weaving of the different movements in any section of the circle, and the maximum rate of flow value is then related to each weaving section of the rotary. Nevertheless, the single-section capacity value does not lead to the typical performance characteristics of the intersection, such as the entry average delay which is directly linked to its level of service. From another point of view, modern roundabout capacity models are based on the limitation of the flow entering from the single entrance due to the amount of flow circulating in front of the entrance itself. Modern roundabouts capacity models generally lead also to a performance evaluation. This paper aims to incorporate a modern roundabout capacity model into an old rotary capacity method to obtain from the latter the single input capacity and ultimately achieve the related performance indicators. Put simply; the main objective is to calculate the average delay of each single roundabout entrance to apply the most common Highway Capacity Manual, or HCM, criteria. The paper is organized as follows: firstly, the rotary and roundabout capacity models are sketched, and it has made a brief introduction to the model combination technique with some practical instances. The successive section is deserved to summarize the TRRL old rotary capacity model and the most recent HCM-7th modern roundabout capacity model. Then, the two models are combined through an iteration-based algorithm, especially set-up and linked to the concept of roundabout total capacity, i.e., the value reached due to a traffic flow pattern leading to the simultaneous congestion of all roundabout entrances. The solution is the average delay for each entrance of the rotary, by which is estimated its respective level of service. In view of further experimental applications, at this research stage, a collection of existing rotary intersections operating with the priority-to-circle rule has already started, both in the US and in Italy. The rotaries have been selected by direct inspection of aerial photos through a map viewer, namely Google Earth. Each instance has been recorded by location, general urban or rural, and its main geometrical patterns. Finally, conclusion remarks are drawn, and a discussion on some further research developments has opened.

Keywords: mixed methods, old rotary and modern roundabout capacity models, total capacity algorithm, level of service estimation

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Authors: Carolin Schulze

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Characterized by a positive interdependence of learners, cooperative learning (CL) is one possibility of successfully dealing with the increasing heterogeneity of students. Various positive effects of CL on the mental, physical and social health of students have already been documented. However, this structure is still rarely used in physical education (PE). Moreover, there is a lack of information about factors that determine the successful implementation of CL in PE. Therefore, the objective of the current study was to find out factors that determine the successful implementation of CL in PE using a digital questionnaire that was conducted from November to December 2022. In addition to socio-demographic data (age, gender, teaching experience, and education level), frequency of using CL, implementation strategies (theory-led, student-centred), and positive and negative effects of CL were measured. Furthermore, teachers were asked to rate the success of implementation on a 6-point rating scale (1-very successful to 6-not successful at all). For statistical analysis, multiple linear regression was performed, setting the success of implementation as the dependent variable. A total of 224 teachers (mean age=44.81±10.60 years; 58% male) took part in the current study. Overall, 39% of participants stated that they never use CL in their PE classes. Main reasons against the implementations of CL in PE were no time for preparation (74%) or for implementation (61%) and high heterogeneity of students (55%). When using CL, most of the reported difficulties are related to uncertainties about the correct procedure (54%) and the heterogeneous performance of students (54%). The most frequently mentioned positive effect was increased motivation of students (42%) followed by an improvement of psychological abilities (e.g. self-esteem, self-concept; 36%) and improved class cohesion (31%). Reported negative effects were unpredictability (29%), restlessness (24%), confusion (24%), and conflicts between students (17%). The successful use of CL is related to a theory-based preparation (e.g., heterogeneous formation of groups, use of rules and rituals) and a flexible implementation tailored to the needs and conditions of students (e.g., the possibility of individual work, omission of CL phases). Compared to teachers who solely implemented CL theory-led or student-adapted, teachers who switched from theory-led preparation to student-centred implementation of CL reported more successful implementation (t=5.312; p<.001). Neither frequency of using CL in PE nor the gender, age, the teaching experience, or the education level of the teacher showed a significant connection with the successful use of CL. Corresponding to the results of the current study, it is advisable that teachers gather enough knowledge about CL during their education and to point out the need to adapt the learning structure according to the diversity of their students. In order to analyse implementation strategies of teachers more deeply, qualitative methods and guided interviews with teachers are needed.

Keywords: diversity, educational technology, physical education, teaching styles

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Authors: Dino Carpentras, Paul J. Maher, Caoimhe O'Reilly, Michael Quayle

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Opinion dynamics is a sub-field of agent-based modeling that focuses on people’s opinions and their evolutions over time. Despite the rapid increase in the number of publications in this field, it is still not clear how to apply these models to real-world scenarios. Indeed, there is no agreement on how people update their opinion while interacting. Furthermore, it is not clear if different topics will show the same dynamics (e.g., more polarized topics may behave differently). These problems are mostly due to the lack of experimental validation of the models. Some previous studies started bridging this gap in the literature by directly measuring people’s opinions before and after the interaction. However, these experiments force people to express their opinion as a number instead of using natural language (and then, eventually, encoding it as numbers). This is not the way people normally interact, and it may strongly alter the measured dynamics. Another limitation of these studies is that they usually average all the topics together, without checking if different topics may show different dynamics. In our work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions in natural language (“agree” or “disagree”). We also measured the certainty of their answer, expressed as a number between 1 and 10. However, this value was not shown to other participants to keep the interaction based on natural language. We then showed the opinion (and not the certainty) of another participant and, after a distraction task, we repeated the measurement. To make the data compatible with opinion dynamics models, we multiplied opinion and certainty to obtain a new parameter (here called “continuous opinion”) ranging from -10 to +10 (using agree=1 and disagree=-1). We firstly checked the 5 topics individually, finding that all of them behaved in a similar way despite having different initial opinions distributions. This suggested that the same model could be applied for different unpolarized topics. We also observed that people tend to maintain similar levels of certainty, even when they changed their opinion. This is a strong violation of what is suggested from common models, where people starting at, for example, +8, will first move towards 0 instead of directly jumping to -8. We also observed social influence, meaning that people exposed with “agree” were more likely to move to higher levels of continuous opinion, while people exposed with “disagree” were more likely to move to lower levels. However, we also observed that the effect of influence was smaller than the effect of random fluctuations. Also, this configuration is different from standard models, where noise, when present, is usually much smaller than the effect of social influence. Starting from this, we built an opinion dynamics model that explains more than 80% of data variance. This model was also able to show the natural conversion of polarization from unpolarized states. This experimental approach offers a new way to build models grounded on experimental data. Furthermore, the model offers new insight into the fundamental terms of opinion dynamics models.

Keywords: experimental validation, micro-dynamics rule, opinion dynamics, update rule

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Authors: Ante Turudic, Filip Varga, Zlatko Liber, Jernej Jakse, Zlatko Satovic, Ivan Radosavljevic, Martina Grdisa

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Microsatellites (SSRs) are highly informative repetitive sequences of 2-6 base pairs, which are the most used molecular markers in assessing the genetic diversity of plant species. Dalmatian pyrethrum (Tanacetum cinerariifolium /Trevir./ Sch. Bip) is an outcrossing diploid (2n = 18) endemic to the eastern Adriatic coast and source of the natural insecticide pyrethrin. Due to the high repetitiveness and large size of the genome (haploid genome size of 9,58 pg), previous attempts to develop microsatellite markers using the standard methods were unsuccessful. A next-generation sequencing (NGS) approach was applied on genomic DNA extracted from fresh leaves of Dalmatian pyrethrum. The sequencing was conducted using NovaSeq6000 Illumina sequencer, after which almost 400 million high-quality paired-end reads were obtained, with a read length of 150 base pairs. Short reads were assembled by combining two approaches; (1) de-novo assembly and (2) joining of overlapped pair-end reads. In total, 6.909.675 contigs were obtained, with the contig average length of 249 base pairs. Of the resulting contigs, 31.380 contained one or multiple microsatellite sequences, in total 35.556 microsatellite loci were identified. Out of detected microsatellites, dinucleotide repeats were the most frequent, accounting for more than half of all microsatellites identifies (21,212; 59.7%), followed by trinucleotide repeats (9,204; 25.9%). Tetra-, penta- and hexanucleotides had similar frequency of 1,822 (5.1%), 1,472 (4.1%), and 1,846 (5.2%), respectively. Contigs containing microsatellites were further filtered by SSR pattern type, transposon occurrences, assembly characteristics, GC content, and the number of occurrences against the draft genome of T. cinerariifolium published previously. After the selection process, 50 microsatellite loci were used for primer design. Designed primers were tested on samples from five distinct populations, and 25 of them showed a high degree of polymorphism. The selected loci were then genotyped on 20 samples belonging to one population resulting in 17 microsatellite markers. Availability of codominant SSR markers will significantly improve the knowledge on population genetic diversity and structure as well as complex genetics and biochemistry of this species. Acknowledgment: This work has been fully supported by the Croatian Science Foundation under the project ‘Genetic background of Dalmatian pyrethrum (Tanacetum cinerariifolium /Trevir/ Sch. Bip.) insecticidal potential’ - (PyrDiv) (IP-06-2016-9034).

Keywords: genome assembly, NGS, SSR, Tanacetum cinerariifolium

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Authors: Elizabeth O. Odewale, Sachithra T. Wanasinghe, Aaron S. Rury

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Cavity polaritons form when molecular excitons strongly couple to photons in carefully constructed optical cavities. These polaritons, which are hybrid light-matter states possessing a unique combination of photonic and excitonic properties, present the opportunity to manipulate the properties of various semiconductor materials. The systematic manipulation of materials through polariton formation could potentially improve the functionalities of many optoelectronic devices such as lasers, light-emitting diodes, photon-based quantum computers, and solar cells. However, the prospects of leveraging polariton formation for novel devices and device operation depend on more complete connections between the properties of molecular chromophores, and the hybrid light-matter states they form, which remains an outstanding scientific goal. Specifically, for most optoelectronic applications, it is paramount to understand how polariton formation affects the spectra of light absorbed by molecules coupled strongly to cavity photons. An essential feature of a polariton state is its dispersive energy, which occurs due to the enhanced spatial delocalization of the polaritons relative to bare molecules. To leverage the spatial delocalization of cavity polaritons, angle-resolved photoluminescence excitation spectroscopy was employed in characterizing light emission from the polaritonic states. Using lasers of appropriate energies, the polariton branches were resonantly excited to understand how molecular light absorption changes under different strong light-matter coupling conditions. Since an excited state has a finite lifetime, the photon absorbed by the polariton decays non-radiatively into lower-lying molecular states, from which radiative relaxation to the ground state occurs. The resulting fluorescence is collected across several angles of excitation incidence. By modeling the behavior of the light emission observed from the lower-lying molecular state and combining this result with the output of angle-resolved transmission measurements, inferences are drawn about how the behavior of molecules changes when they form polaritons. These results show how the intrinsic properties of molecules, such as the excitonic lifetime, affect the rate at which the polaritonic states relax. While it is true that the lifetime of the photon mediates the rate of relaxation in a cavity, the results from this study provide evidence that the lifetime of the molecular exciton also limits the rate of polariton relaxation.

Keywords: flourescece, molecules in cavityies, optical cavity, photoluminescence excitation, spectroscopy, strong coupling

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Authors: Shin Yoneda, Mikiya Kato, Kosuke Murate, Kodo Kawase

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In recent years, there have been numerous attempts to smuggle narcotic drugs and chemicals by concealing them in international mail. Combatting this requires a non-destructive technique that can identify such illicit substances in mail. Terahertz (THz) waves can pass through a wide variety of materials, and many chemicals show specific frequency-dependent absorption, known as a spectral fingerprint, in the THz range. Therefore, it is reasonable to investigate non-destructive mail inspection techniques that use THz waves. For this reason, in this work, we tried to identify reagents under high attenuation shielding materials using injection-seeded THz-wave parametric generator (is-TPG). Our THz spectroscopic imaging system using is-TPG consisted of two non-linear crystals for emission and detection of THz waves. A micro-chip Nd:YAG laser and a continuous wave tunable external cavity diode laser were used as the pump and seed source, respectively. The pump beam and seed beam were injected to the LiNbO₃ crystal satisfying the noncollinear phase matching condition in order to generate high power THz-wave. The emitted THz wave was irradiated to the sample which was raster scanned by the x-z stage while changing the frequencies, and we obtained multispectral images. Then the transmitted THz wave was focused onto another crystal for detection and up-converted to the near infrared detection beam based on nonlinear optical parametric effects, wherein the detection beam intensity was measured using an infrared pyroelectric detector. It was difficult to identify reagents in a cardboard box because of high noise levels. In this work, we introduce improvements for noise reduction and image clarification, and the intensity of the near infrared detection beam was converted correctly to the intensity of the THz wave. A Gaussian spatial filter is also introduced for a clearer THz image. Through these improvements, we succeeded in identification of reagents hidden in a 42-mm thick cardboard box filled with several obstacles, which attenuate 56 dB at 1.3 THz, by improving analysis methods. Using this system, THz spectroscopic imaging was possible for saccharides and may also be applied to cases where illicit drugs are hidden in the box, and multiple reagents are mixed together. Moreover, THz spectroscopic imaging can be achieved through even thicker obstacles by introducing an NIR detector with higher sensitivity.

Keywords: nondestructive inspection, principal component analysis, terahertz parametric source, THz spectroscopic imaging

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Authors: S. R. Dehghani, Y. S. Muzychka, G. F. Naterer

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The ice accretion of salt water on cold substrates creates brine-spongy ice. This type of ice is a mixture of pure ice and liquid brine. A real case of creation of this type of ice is superstructure icing which occurs on marine vessels and offshore structures in cold and harsh conditions. Transient heat transfer through this medium causes phase changes between brine pockets and pure ice. Salt rejection during the process of transient heat conduction increases the salinity of brine pockets to reach a local equilibrium state. In this process the only effect of passing heat through the medium is not changing the sensible heat of the ice and brine pockets; latent heat plays an important role and affects the mechanism of heat transfer. In this study, a new analytical model for evaluating heat transfer through brine-spongy ice is suggested. This model considers heat transfer and partial solidification and melting together. Properties of brine-spongy ice are obtained using properties of liquid brine and pure ice. A numerical solution using Method of Lines discretizes the medium to reach a set of ordinary differential equations. Boundary conditions are chosen using one of the applicable cases of this type of ice; one side is considered as a thermally isolated surface, and the other side is assumed to be suddenly affected by a constant temperature boundary. All cases are evaluated in temperatures between -20 C and the freezing point of brine-spongy ice. Solutions are conducted using different salinities from 5 to 60 ppt. Time steps and space intervals are chosen properly to maintain the most stable and fast solution. Variation of temperature, volume fraction of brine and brine salinity versus time are the most important outputs of this study. Results show that transient heat conduction through brine-spongy ice can create a various range of salinity of brine pockets from the initial salinity to that of 180 ppt. The rate of variation of temperature is found to be slower for high salinity cases. The maximum rate of heat transfer occurs at the start of the simulation. This rate decreases as time passes. Brine pockets are smaller at portions closer to the colder side than that of the warmer side. A the start of the solution, the numerical solution tends to increase instabilities. This is because of sharp variation of temperature at the start of the process. Changing the intervals improves the unstable situation. The analytical model using a numerical scheme is capable of predicting thermal behavior of brine spongy ice. This model and numerical solutions are important for modeling the process of freezing of salt water and ice accretion on cold structures.

Keywords: method of lines, brine-spongy ice, heat conduction, salt water

Procedia PDF Downloads 217

Authors: Gabriel Montague, Max Vilgalys, Catherine H. Crawford, Jorge Ortiz, Dava Newman

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There has never been so much publicly accessible atmospheric and environmental data. The possibilities of these data are exciting, but the sheer volume of available datasets represents a new challenge for researchers. The task of identifying and working with a new dataset has become more difficult with the amount and variety of available data. Datasets are often documented in ways that differ substantially from the common English used to describe the same topics. This presents a barrier not only for new scientists, but for researchers looking to find comparisons across multiple datasets or specialists from other disciplines hoping to collaborate. This paper proposes a method for addressing this obstacle: creating a knowledge graph to bridge the gap between everyday English language and the technical language surrounding these datasets. Knowledge graph generation is already a well-established field, although there are some unique challenges posed by working with Earth data. One is the sheer size of the databases – it would be infeasible to replicate or analyze all the data stored by an organization like The National Aeronautics and Space Administration (NASA) or the European Space Agency. Instead, this approach identifies topics from metadata available for datasets in NASA’s Earthdata database, which can then be used to directly request and access the raw data from NASA. By starting with a single metadata standard, this paper establishes an approach that can be generalized to different databases, but leaves the challenge of metadata harmonization for future work. Topics generated from the metadata are then linked to topics from a collection of English queries through a variety of standard and custom natural language processing (NLP) methods. The results from this method are then compared to a baseline of elastic search applied to the metadata. This comparison shows the benefits of the proposed knowledge graph system over existing methods, particularly in interpreting natural language queries and interpreting topics in metadata. For the research community, this work introduces an application of NLP to the ecological and environmental sciences, expanding the possibilities of how machine learning can be applied in this discipline. But perhaps more importantly, it establishes the foundation for a platform that can enable common English to access knowledge that previously required considerable effort and experience. By making this public data accessible to the full public, this work has the potential to transform environmental understanding, engagement, and action.

Keywords: earth metadata, knowledge graphs, natural language processing, question-answer systems

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Authors: Alexander Heckman, Rohan Goswami, Zachi Attia, Paul Friedman, Peter Noseworthy, Demilade Adedinsewo, Pablo Moreno-Franco, Rickey Carter, Tathagat Narula

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Background: Postoperative atrial fibrillation (POAF) is associated with adverse health consequences, higher costs, and longer hospital stays. Utilizing existing predictive models that rely on clinical variables and circulating biomarkers, multiple societies have published recommendations on the treatment and prevention of POAF. Although reasonably practical, there is room for improvement and automation to help individualize treatment strategies and reduce associated complications. Methods and Results: In this retrospective cohort study of solid organ transplant recipients, we evaluated the diagnostic utility of a previously developed AI-based ECG prediction for silent AF on the development of POAF within 30 days of transplant. A total of 2261 non-cardiac transplant patients without a preexisting diagnosis of AF were found to have a 5.8% (133/2261) incidence of POAF. While there were no apparent sex differences in POAF incidence (5.8% males vs. 6.0% females, p=.80), there were differences by race and ethnicity (p<0.001 and 0.035, respectively). The incidence in white transplanted patients was 7.2% (117/1628), whereas the incidence in black patients was 1.4% (6/430). Lung transplant recipients had the highest incidence of postoperative AF (17.4%, 37/213), followed by liver (5.6%, 56/1002) and kidney (3.6%, 32/895) recipients. The AUROC in the sample was 0.62 (95% CI: 0.58-0.67). The relatively low discrimination may result from undiagnosed AF in the sample. In particular, 1,177 patients had at least 1 AI-ECG screen for AF pre-transplant above .10, a value slightly higher than the published threshold of 0.08. The incidence of POAF in the 1104 patients without an elevated prediction pre-transplant was lower (3.7% vs. 8.0%; p<0.001). While this supported the hypothesis that potentially undiagnosed AF may have contributed to the diagnosis of POAF, the utility of the existing AI-ECG screening algorithm remained modest. When the prediction for POAF was made using the first postoperative ECG in the sample without an elevated screen pre-transplant (n=1084 on account of n=20 missing postoperative ECG), the AUROC was 0.66 (95% CI: 0.57-0.75). While this discrimination is relatively low, at a threshold of 0.08, the AI-ECG algorithm had a 98% (95% CI: 97 – 99%) negative predictive value at a sensitivity of 66% (95% CI: 49-80%). Conclusions: This study's principal finding is that the incidence of POAF is rare, and a considerable fraction of the POAF cases may be latent and undiagnosed. The high negative predictive value of AI-ECG screening suggests utility for prioritizing monitoring and evaluation on transplant patients with a positive AI-ECG screening. Further development and refinement of a post-transplant-specific algorithm may be warranted further to enhance the diagnostic yield of the ECG-based screening.

Keywords: artificial intelligence, atrial fibrillation, cardiology, transplant, medicine, ECG, machine learning

Procedia PDF Downloads 137

Authors: Deisy Becerra, Edwar Perez, Nicolas Rios, Miguel Asuaje

Abstract:

Progressing Cavity Pump (PCP) is a type of positive displacement pump that is being awarded greater importance as capable artificial lift equipment in the heavy oil field. The most commonly PCP used is driven single lobe pump that consists of a single external helical rotor turning eccentrically inside a double internal helical stator. This type of pump was analyzed by the experimental and Computational Fluid Dynamic (CFD) approach from the DCAB031 model located in a closed-loop arrangement. Experimental measurements were taken to determine the pressure rise and flow rate with a flow control valve installed at the outlet of the pump. The flowrate handled was measured by a FLOMEC-OM025 oval gear flowmeter. For each flowrate considered, the pump’s rotational speed and power input were controlled using an Invertek Optidrive E3 frequency driver. Once a steady-state operation was attained, pressure rise measurements were taken with a Sper Scientific wide range digital pressure meter. In this study, water and three Newtonian oils of different viscosities were tested at different rotational speeds. The CFD model implementation was developed on Star- CCM+ using an Overset Mesh that includes the relative motion between rotor and stator, which is one of the main contributions of the present work. The simulations are capable of providing detailed information about the pressure and velocity fields inside the device in laminar and unsteady regimens. The simulations have a good agreement with the experimental data due to Mean Squared Error (MSE) in under 21%, and the Grid Convergence Index (GCI) was calculated for the validation of the mesh, obtaining a value of 2.5%. In this case, three different rotational speeds were evaluated (200, 300, 400 rpm), and it is possible to show a directly proportional relationship between the rotational speed of the rotor and the flow rate calculated. The maximum production rates for the different speeds for water were 3.8 GPM, 4.3 GPM, and 6.1 GPM; also, for the oil tested were 1.8 GPM, 2.5 GPM, 3.8 GPM, respectively. Likewise, an inversely proportional relationship between the viscosity of the fluid and pump performance was observed, since the viscous oils showed the lowest pressure increase and the lowest volumetric flow pumped, with a degradation around of 30% of the pressure rise, between performance curves. Finally, the Productivity Index (PI) remained approximately constant for the different speeds evaluated; however, between fluids exist a diminution due to the viscosity.

Keywords: computational fluid dynamic, CFD, Newtonian fluids, overset mesh, PCP pressure rise

Procedia PDF Downloads 128

Authors: Vaikunthan Rajaratnam

Abstract:

Maintaining continuous professional development among clinicians has been a challenge. Hand surgery is a unique speciality with the coming together of orthopaedics, plastics and trauma surgeons. The requirements for a team-based approach to care with the inclusion of other experts such as occupational, physiotherapist and orthotic and prosthetist provide the impetus for the creation of communities of practice. This study analysed the community of practice in hand surgery that was created through a social networking website for professionals. The main objectives were to discover the usefulness of this community of practice created in the platform of the group function of LinkedIn. The second objective was to determine the usability of this platform for the purposes of continuing professional development among members of this community of practice. The methodology used was one of mixed methods which included a quantitative analysis on the usefulness of the social network website as a community of practice, using the analytics provided by the LinkedIn platform. Further qualitative analysis was performed on the various postings that were generated by the community of practice within the social network website. This was augmented by a respondent driven survey conducted online to assess the usefulness of the platform for continuous professional development. A total of 31 respondents were involved in this study. This study has shown that it is possible to create an engaging and interactive community of practice among hand surgeons using the group function of this professional social networking website LinkedIn. Over three years the group has grown significantly with members from multiple regions and has produced engaging and interactive conversations online. From the results of the respondents’ survey, it can be concluded that there was satisfaction of the functionality and that it was an excellent platform for discussions and collaboration in the community of practice with a 69 % of satisfaction. Case-based discussions were the most useful functions of the community of practice. This platform usability was graded as excellent using the validated usability tool. This study has shown that the social networking site LinkedIn’s group function can be easily used as a community of practice effectively and provides convenience to professionals and has made an impact on their practice and better care for patients. It has also shown that this platform was easy to use and has a high level of usability for the average healthcare professional. This platform provided the improved connectivity among professionals involved in hand surgery care which allowed for the community to grow and with proper support and contribution of relevant material by members allowed for a safe environment for the exchange of knowledge and sharing of experience that is the foundation of a community practice.

Keywords: community of practice, online community, hand surgery, lifelong learning, LinkedIn, social media, continuing professional development

Procedia PDF Downloads 317