Search results for: ship-borne electro-optical stabilized platform

Authors: Bylhah Mugotitsa, Jim Todd, Agnes Kiragga, Jay Greenfield, Evans Omondi, Lukoye Atwoli, Reinpeter Momanyi

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The INSPIRE network aims to build an open, ethical, sustainable, and FAIR (Findable, Accessible, Interoperable, Reusable) data science platform, particularly for longitudinal mental health (MH) data. While studies have been done at the clinical and population level, there still exists limitations in data and research in LMICs, which pose a risk of underrepresentation of mental disorders. It is vital to examine the existing longitudinal MH data, focusing on how FAIR datasets are. This landscape analysis aimed to provide both overall level of evidence of availability of longitudinal datasets and degree of consistency in longitudinal studies conducted. Utilizing prompters proved instrumental in streamlining the analysis process, facilitating access, crafting code snippets, categorization, and analysis of extensive data repositories related to depression, anxiety, and psychosis in Africa. While leveraging artificial intelligence (AI), we filtered through over 18,000 scientific papers spanning from 1970 to 2023. This AI-driven approach enabled the identification of 228 longitudinal research papers meeting inclusion criteria. Quality assurance revealed 10% incorrectly identified articles and 2 duplicates, underscoring the prevalence of longitudinal MH research in South Africa, focusing on depression. From the analysis, evaluating data and metadata adherence to FAIR principles remains crucial for enhancing accessibility and quality of MH research in Africa. While AI has the potential to enhance research processes, challenges such as privacy concerns and data security risks must be addressed. Ethical and equity considerations in data sharing and reuse are also vital. There’s need for collaborative efforts across disciplinary and national boundaries to improve the Findability and Accessibility of data. Current efforts should also focus on creating integrated data resources and tools to improve Interoperability and Reusability of MH data. Practical steps for researchers include careful study planning, data preservation, machine-actionable metadata, and promoting data reuse to advance science and improve equity. Metrics and recognition should be established to incentivize adherence to FAIR principles in MH research

Keywords: longitudinal mental health research, data sharing, fair data principles, Africa, landscape analysis

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Authors: S. Paszkiewicz, A. Zubkiewicz, A. Szymczyk, D. Pawlikowska, I. Irska, E. Piesowicz, A. Linares, T. A. Ezquerra

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Over the last century, the world has become increasingly dependent on oil as its main source of chemicals and energy. Driven largely by the strong economic growth of India and China, demand for oil is expected to increase significantly in the coming years. This growth in demand, combined with diminishing reserves, will require the development of new, sustainable sources for fuels and bulk chemicals. Biomass is an attractive alternative feedstock, as it is widely available carbon source apart from oil and coal. Nowadays, academic and industrial research in the field of polymer materials is strongly oriented towards bio-based alternatives to petroleum-derived plastics with enhanced properties for advanced applications. In this context, 2,5-furandicarboxylic acid (FDCA), a biomass-based chemical product derived from lignocellulose, is one of the most high-potential biobased building blocks for polymers and the first candidate to replace the petro-derived terephthalic acid. FDCA has been identified as one of the top 12 chemicals in the future, which may be used as a platform chemical for the synthesis of biomass-based polyester. The aim of this study is to synthesize and characterize the multiblock copolymers containing rigid segments of poly(trimethylene 2,5-furanoate) (PTF) and soft segments of poly(tetramethylene oxide) (PTMO) with excellent elastic properties or aliphatic polyesters of polycaprolactone (PCL). Two series of PTF based copolymers, i.e., PTF-block-PTMO-T and PTF-block-PCL-T, with different content of flexible segments were synthesized by means of a two-step melt polycondensation process and characterized by various methods. The rigid segments of PTF, as well as the flexible PTMO/or PCL ones, were randomly distributed along the chain. On the basis of 1H NMR, SAXS and WAXS, DSC an DMTA results, one can conclude that both phases were thermodynamically immiscible and the values of phase transition temperatures varied with the composition of the copolymer. The copolymers containing 25, 35 and 45wt.% of flexible segments (PTMO) exhibited elastomeric property characteristics. Moreover, with respect to the flexible segments content, the temperatures corresponding to 5%, 25%, 50% and 90% mass loss as well as the values of tensile modulus decrease with the increasing content of aliphatic polyether or aliphatic polyester in the composition.

Keywords: furan based polymers, multiblock copolymers, supramolecular structure, functional properties

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Authors: Peter Ecke

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This research presents insights from a questionnaire study and autobiographic narrative analyses about the language and cultural backgrounds, challenges, interests, and needs, as well as perceptions about bilingualism and language learning of undergraduate students at a Public University in the southwestern United States. Participants were 650 students, enrolled in college-level general education courses, entitled “Becoming multilingual: Learning and maintaining two or more languages” between 2020 and 2024. Data were collected via pre- and post-course questionnaires administered online through the Qualtrix XM platform and complemented with analyses of excerpts from autobiographical narratives that students produced as part of the course assignments. Findings, for example, show that course participants have diverse linguistic backgrounds. The five most frequently reported L1s were English (about 50% of course participants), Spanish, Arabic, Mandarin, and Korean (in that order). The five most frequently reported L2s were English, Spanish, French, ASL, Japanese, German, and Mandarin (in that order). Participants also reported on their L2, L3, L4, and L5 if applicable. Most participants (over 60%) rated themselves bilingual or multilingual whereas 40% considered themselves to be monolingual or foreign language learners. Only about half of the participants reported feeling very or somewhat comfortable with their language skills, but these reports changed somewhat from the pre- to the post-course survey. About half of participants were mostly interested in learning how to effectively learn a foreign language. The other half of participants reported being most curious about learning about themselves as bi/multilinguals, (re)learning a language used in childhood, learning how to bring up a child as a bi/multilingual or learning about people who speak multiple languages (distributed about evenly). Participants’ comments about advantages and disadvantages of being bilingual remained relatively stable but their agreement with common myths about bilingualism and language learning changed from the pre- to the post-course survey. Students’ reflections in the autobiographical narratives and comments in (institutionally administered) anonymous course evaluations provided additional data on students’ concerns about their current language skills and uses as well as their perceptions about learning outcomes and the usefulness of the general education course for their current and future lives. It is hoped that the presented findings and discussion will spark interest among colleagues in offering similar courses as a resource for college students (and possibly other audiences), including those from migrant, indigenous, multilingual, and multicultural communities to contribute to a more harmonious bilingualism and well-being of college students who are or inspire to become bi-or multilingual.

Keywords: autobiographic narratives, general education university course, harmonious bilingualism and well-being, multilingualism, questionnaire study

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Authors: Jian Yu

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Carbo dioxide (CO2) from fossil fuel combustion is a prime green-house gas emission. It can be mitigated by microalgae through conventional photosynthesis. The algal oil is a feedstock of biodiesel, a carbon neutral liquid fuel for transportation. The conventional CO2 fixation, however, is quite slow and affected by the intermittent solar irradiation. It is also a technical challenge to reform the bio-oil into a drop-in liquid fuel that can be directly used in the modern combustion engines with expected performance. Here, an artificial photosynthesis system is presented to produce a biopolyester and liquid fuels from CO2, water, and solar power. In this green process, solar energy is captured using photovoltaic modules and converted into hydrogen as a stable energy source via water electrolysis. The solar hydrogen is then used to fix CO2 by Cupriavidus necator, a hydrogen-oxidizing bacterium. Under the autotrophic conditions, CO2 was reduced to glyceraldehyde-3-phosphate (G3P) that is further utilized for cell growth and biosynthesis of polyhydroxybutyrate (PHB). The maximum cell growth rate reached 10.1 g L-1 day-1, about 25 times faster than that of a typical bio-oil-producing microalga (Neochloris Oleoabundans) under stable indoor conditions. With nitrogen nutrient limitation, a large portion of the reduced carbon is stored in PHB (C4H6O2)n, accounting for 50-60% of dry cell mass. PHB is a biodegradable thermoplastic that can find a variety of environmentally friendly applications. It is also a platform material from which small chemicals can be derived. At a high temperature (240 - 290 oC), the biopolyester is degraded into crotonic acid (C4H6O2). On a solid phosphoric acid catalyst, PHB is deoxygenated via decarboxylation into a hydrocarbon oil (C6-C18) at 240 oC or so. Aromatics and alkenes are the major compounds, depending on the reaction conditions. A gasoline-grade liquid fuel (77 wt% oil) and a biodiesel-grade fuel (23 wt% oil) were obtained from the hydrocarbon oil via distillation. The formation routes of hydrocarbon oil from crotonic acid, the major PHB degradation intermediate, are revealed and discussed. This work shows a novel green process from which biodegradable plastics and high-grade liquid fuels can be directly produced from carbon dioxide, water and solar power. The productivity of the green polyester (5.3 g L-1 d-1) is much higher than that of microalgal oil (0.13 g L-1 d-1). Other technical merits of the new green process may include continuous operation under intermittent solar irradiation and convenient scale up in outdoor.

Keywords: bioplastics, carbon dioxide fixation, drop-in liquid fuels, green process

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Authors: Gautier Viaud, Paul-Henry Cournède

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Plant growth models have been used extensively for the prediction of the phenotypic performance of plants. However, they remain most often calibrated for a given genotype and therefore do not take into account genotype by environment interactions. One way of achieving such an objective is to consider Bayesian hierarchical models. Three levels can be identified in such models: The first level describes how a given growth model describes the phenotype of the plant as a function of individual parameters, the second level describes how these individual parameters are distributed within a plant population, the third level corresponds to the attribution of priors on population parameters. Thanks to the Bayesian framework, choosing appropriate priors for the population parameters permits to derive analytical expressions for the full conditional distributions of these population parameters. As plant growth models are of a nonlinear nature, individual parameters cannot be sampled explicitly, and a Metropolis step must be performed. This allows for the use of a hybrid Gibbs--Metropolis sampler. A generic approach was devised for the implementation of both general state space models and estimation algorithms within a programming platform. It was designed using the Julia language, which combines an elegant syntax, metaprogramming capabilities and exhibits high efficiency. Results were obtained for Arabidopsis thaliana on both simulated and real data. An organ-scale Greenlab model for the latter is thus presented, where the surface areas of each individual leaf can be simulated. It is assumed that the error made on the measurement of leaf areas is proportional to the leaf area itself; multiplicative normal noises for the observations are therefore used. Real data were obtained via image analysis of zenithal images of Arabidopsis thaliana over a period of 21 days using a two-step segmentation and tracking algorithm which notably takes advantage of the Arabidopsis thaliana phyllotaxy. Since the model formulation is rather flexible, there is no need that the data for a single individual be available at all times, nor that the times at which data is available be the same for all the different individuals. This allows to discard data from image analysis when it is not considered reliable enough, thereby providing low-biased data in large quantity for leaf areas. The proposed model precisely reproduces the dynamics of Arabidopsis thaliana’s growth while accounting for the variability between genotypes. In addition to the estimation of the population parameters, the level of variability is an interesting indicator of the genotypic stability of model parameters. A promising perspective is to test whether some of the latter should be considered as fixed effects.

Keywords: bayesian, genotypic differentiation, hierarchical models, plant growth models

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Authors: Daniele Traversaro

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Problem: Senior citizens have been facing a challenging reality as a result of strict public health measures designed to protect people from the COVID-19 outbreak. These include the risk of social isolation due to the inability of the elderly to integrate with technology. Never before have information and communication technology (ICT) skills become essential for their everyday life. Although third-age ICT education and lifelong learning are widely supported by universities and governments, there is a lack of literature on which teaching strategy/methodology to adopt in an entirely online ICT course aimed at third-age learners. This contribution aims to present an application of the Think-Pair-Share (TPS) learning method in an ICT third-age virtual classroom with an intergenerational approach to conducting online group labs and review activities. This collaborative strategy can help increase student engagement, promote active learning and online social interaction. Research Question: Is collaborative learning applicable and effective, in terms of student engagement and learning outcomes, for an entirely online third-age ICT introductory course? Methods: In the TPS strategy, a problem is posed by the teacher, students have time to think about it individually, and then they work in pairs (or small groups) to solve the problem and share their ideas with the entire class. We performed four experiments in the ICT course of the University of the Third Age of Genova (University of Genova, Italy) on the Microsoft Teams platform. The study cohort consisted of 26 students over the age of 45. Data were collected through online questionnaires. Two have been proposed, one at the end of the first activity and another at the end of the course. They consisted of five and three close-ended questions, respectively. The answers were on a Likert scale (from 1 to 4) except two questions (which asked the number of correct answers given individually and in groups) and the field for free comments/suggestions. Results: Results show that groups perform better than individual students (with scores greater than one order of magnitude) and that most students found it helpful to work in groups and interact with their peers. Insights: From these early results, it appears that TPS is applicable to an online third-age ICT classroom and useful for promoting discussion and active learning. Despite this, our experimentation has a number of limitations. First of all, the results highlight the need for more data to be able to perform a statistical analysis in order to determine the effectiveness of this methodology in terms of student engagement and learning outcomes as a future direction.

Keywords: collaborative learning, information technology education, lifelong learning, older adult education, think-pair-share

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Authors: Rachel Cherner

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Introduction: The current study investigates several user characteristics that may predict the adoption of digital mental health supports. The extent to which individual characteristics predict preferences for functional elements of computer-mediated social support (CMSS) platforms and mental health (MH) apps is relatively unstudied. Aims: The present study seeks to illuminate the relationship between broad user characteristics and perceived attraction to CMSS platforms and MH apps. Methods: Participants (n=353) were recruited using convenience sampling methods (i.e., digital flyers, email distribution, and online survey forums). The sample was 68% male, and 32% female, with a mean age of 29. Participant racial and ethnic breakdown was 75% White, 7%, 5% Asian, and 5% Black or African American. Participants were asked to complete a 25-minute self-report questionnaire that included empirically validated measures assessing a battery of characteristics (i.e., subjective levels of anxiety/depression via PHQ-9 (Patient Health Questionnaire 9-item) and GAD-7 (Generalized Anxiety Disorder 7-item); attachment style via MAQ (Measure of Attachment Qualities); personality types via TIPI (The 10-Item Personality Inventory); growth mindset and mental health-seeking attitudes via GM (Growth Mindset Scale) and MHSAS (Mental Help Seeking Attitudes Scale)) and subsequent attitudes toward CMSS platforms and MH apps. Results: A stepwise linear regression was used to test if user characteristics significantly predicted attitudes towards key features of CMSS platforms and MH apps. The overall regression was statistically significant (R² =.20, F(1,344)=14.49, p<.000). Conclusion: This original study examines the clinical and sociocultural factors influencing decisions to use CMSS platforms and MH apps. Findings provide valuable insight for increasing adoption and engagement with digital mental health support. Fostering a growth mindset may be a method of increasing participant/patient engagement. In addition, CMSS platforms and MH apps may empower under-resourced and minority groups to gain basic access to mental health support. We do not assume this final model contains the best predictors of use; this is merely a preliminary step toward understanding the psychology and attitudes of CMSS platform/MH app users.

Keywords: computer-mediated social support platforms, digital mental health, growth mindset, health-seeking attitudes, mental health apps, user characteristics

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Authors: A. Rezaei, M. Huisman, W. Van Paepegem

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Atomic interactions in molecular systems are mainly studied by particle mechanics. Nevertheless, researches have also put on considerable effort to simulate them using continuum methods. In early 2000, simple equivalent finite element models have been developed to study the mechanical properties of carbon nanotubes and graphene in composite materials. Afterward, many researchers have employed similar structural simulation approaches to obtain mechanical properties of nanostructured materials, to simplify interface behavior of fiber-reinforced composites, and to simulate defects in carbon nanotubes or graphene sheets, etc. These structural approaches, however, are limited to small deformations due to complicated local rotational coordinates. This article proposes a method for the finite element simulation of molecular mechanics. For ease in addressing the approach, here it is called Structural Finite Element Molecular Modeling (SFEMM). SFEMM method improves the available structural approaches for large deformations, without using any rotational degrees of freedom. Moreover, the method simulates molecular conformation, which is a big advantage over the previous approaches. Technically, this method uses nonlinear multipoint constraints to simulate kinematics of the atomic multibody interactions. Only truss elements are employed, and the bond potentials are implemented through constitutive material models. Because the equilibrium bond- length, bond angles, and bond-torsion potential energies are intrinsic material parameters, the model is independent of initial strains or stresses. In this paper, the SFEMM method has been implemented in ABAQUS finite element software. The constraints and material behaviors are modeled through two Fortran subroutines. The method is verified for the bond-stretch, bond-angle and bond-torsion of carbon atoms. Furthermore, the capability of the method in the conformation simulation of molecular structures is demonstrated via a case study of a graphene sheet. Briefly, SFEMM builds up a framework that offers more flexible features over the conventional molecular finite element models, serving the structural relaxation modeling and large deformations without incorporating local rotational degrees of freedom. Potentially, the method is a big step towards comprehensive molecular modeling with finite element technique, and thereby concurrently coupling an atomistic domain to a solid continuum domain within a single finite element platform.

Keywords: finite element, large deformation, molecular mechanics, structural method

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Authors: Ivan Maguire, Ciprian Briciu, Alan Barrett, Dara Kervick, Jens Ducrèe, Fiona Regan

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With the ever-increasing myriad of applications of which microfluidic devices are capable, reliable fluidic actuation development has remained fundamental to the success of these microfluidic platforms. There are a number of approaches which can be taken in order to integrate liquid actuation on microfluidic platforms, which can usually be split into two primary categories; active microvalves and passive microvalves. Active microvalves are microfluidic valves which require a physical parameter change by external, or separate interaction, for actuation to occur. Passive microvalves are microfluidic valves which don’t require external interaction for actuation due to the valve’s natural physical parameters, which can be overcome through sample interaction. The purpose of this paper is to illustrate how further improvements to past microvalve solutions can largely enhance systematic reliability and performance, with both novel active and passive microvalves demonstrated. Covered within this scope will be two alternative and novel microvalve solutions for centrifugal microfluidic platforms; a revamped pneumatic-dissolvable film active microvalve (PAM) strategy and a spray-on Sol-Gel based hydrophobic passive microvalve (HPM) approach. Both the PAM and the HPM mechanisms were demonstrated on a centrifugal microfluidic platform consisting of alternating layers of 1.5 mm poly(methyl methacrylate) (PMMA) (for reagent storage) sheets and ~150 μm pressure sensitive adhesive (PSA) (for microchannel fabrication) sheets. The PAM approach differs from previous SOLUBON™ dissolvable film methods by introducing a more reliable and predictable liquid delivery mechanism to microvalve site, thus significantly reducing premature activation. This approach has also shown excellent synchronicity when performed in a multiplexed form. The HPM method utilises a new spray-on and low curing temperature (70°C) sol-gel material. The resultant double layer coating comprises a PMMA adherent sol-gel as the bottom layer and an ultra hydrophobic silica nano-particles (SNPs) film as the top layer. The optimal coating was integrated to microfluidic channels with varying cross-sectional area for assessing microvalve burst frequencies consistency. It is hoped that these microvalving solutions, which can be easily added to centrifugal microfluidic platforms, will significantly improve automation reliability.

Keywords: centrifugal microfluidics, hydrophobic microvalves, lab-on-a-disc, pneumatic microvalves

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Authors: Ray Bryant

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3Strands Global Foundation (3SGF), a non-profit with a mission to mobilize communities to combat human trafficking through prevention education and reintegration programs, launched a groundbreaking study that calls out the usage and benefits of artificial intelligence in the war against human trafficking. Having gathered more than 30,000 stories from counselors and school staff who have gone through its PROTECT Prevention Education program, 3SGF sought to develop a methodology to measure the effectiveness of the training, which helps educators and school staff identify physical signs and behaviors indicating a student is being victimized. The program further illustrates how to recognize and respond to trauma and teaches the steps to take to report human trafficking, as well as how to connect victims with the proper professionals. 3SGF partnered with Levity, a leader in no-code Artificial Intelligence (AI) automation, to create the research study utilizing natural language processing, a branch of artificial intelligence, to measure the effectiveness of their prevention education program. By applying the logic created for the study, the platform analyzed and categorized each story. If the story, directly from the educator, demonstrated one or more of the desired outcomes; Increased Awareness, Increased Knowledge, or Intended Behavior Change, a label was applied. The system then added a confidence level for each identified label. The study results were generated with a 99% confidence level. Preliminary results show that of the 30,000 stories gathered, it became overwhelmingly clear that a significant majority of the participants now have increased awareness of the issue, demonstrated better knowledge of how to help prevent the crime, and expressed an intention to change how they approach what they do daily. In addition, it was observed that approximately 30% of the stories involved comments by educators expressing they wish they’d had this knowledge sooner as they can think of many students they would have been able to help. Objectives Of Research: To solve the problem of needing to analyze and accurately categorize more than 30,000 data points of participant feedback in order to evaluate the success of a human trafficking prevention program by using AI and Natural Language Processing. Methodologies Used: In conjunction with our strategic partner, Levity, we have created our own NLP analysis engine specific to our problem. Contributions To Research: The intersection of AI and human rights and how to utilize technology to combat human trafficking.

Keywords: AI, technology, human trafficking, prevention

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Authors: Josh Felton

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There’s a common misconception that sports is an escape from the reality of life, and that it is what disconnects us from the agendas of tomorrow. While this may be true for a select few, there’s more to sports than just competition and banter. The bearing and impact society has on the sports we know and love has always existed and is greater than ever. However, to many in the national media, it is almost seen as a taboo subject. Whether one realizes it or not, sports and society intersect at every turn and it’s not a coincidence. In collaboration with the Woodrow Wilson Fellowship at Johns Hopkins University, a video and podcast series titled Intersection of sports and society (ISS), dedicated to studying some of the most polarizing and some of the least recognized issues in the world of sports that have a powerful social bearing on every demographic will debut in the Summer of 2023. Issues like race, gender, and sexuality, as well as how they have been challenged and addressed historically in the sports realm will be discussed to a great extent in the series. With the collaboration of many authors, researchers, and former athletes, the podcast will be a platform for them to not only share their discoveries but to have an extensive dialogue on the impact their work and current events have had on the issues. Set to be released in the summer of 2023, the series will have a list of great researchers and authors, headlined by New York Times writer and best-selling author Jonathan Abrams, who in 2017, published a book titled Boys Among Men: How the Prep-to-Pro Generation Redefined the NBA and Sparked a Basketball Revolution. His expertise on the matters of the high school and collegiate sports will be reflected in a very important conversation on the evolution of the high school-to-professional route, the historic exploitation of black student athletes by the NCAA, and how the new rules allowing for greater freedom of choice for young athletes has benefitted minority athletes coming from impoverished backgrounds. This episode is just a preview of a list of important topics that to the author’s best knowledge aren't typically discussed by the national media. Many more topics include women’s sports representation, the struggle for achieving fair minority representation in NFL coaching and front office positions, the story of race and baseball within the Boston Red Sox organization, and what the rise of the black quarterback means for America. Many people fail to realize how the sports we all know and love have any social bearing on them and the athletes who play them. The hope with this project is to shed light on the social relevance that exists in the realm of sports, where we have for years failed to see and acknowledge a connection between sports and society.

Keywords: sports, society, race, gender

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Authors: Tanima Chatterjee, Maitree Bhattacharyya

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The global challenge of type 2 diabetes mellitus is a major health concern in this millennium, and researchers are continuously exploring new targets to develop a novel therapeutic strategy. Type 2 diabetes mellitus (T2DM) is often coupled with dyslipidemia increasing the risks for cardiovascular (CVD) complications. Enhanced oxidative and nitrosative stresses appear to be the major risk factors underlying insulin resistance, dyslipidemia, β-cell dysfunction, and T2DM pathogenesis. Autophagy emerges to be a promising defense mechanism against stress-mediated cell damage regulating tissue homeostasis, cellular quality control, and energy production, promoting cell survival. In this study, we have attempted to explore the pivotal role of autophagy in T2DM subjects with or without dyslipidemia in peripheral blood mononuclear cells and insulin-resistant HepG2 cells utilizing flow cytometric platform, confocal microscopy, and molecular biology techniques like western blotting, immunofluorescence, and real-time polymerase chain reaction. In the case of T2DM with dyslipidemia higher population of autophagy, positive cells were detected compared to patients with the only T2DM, which might have resulted due to higher stress. Autophagy was observed to be triggered both by oxidative and nitrosative stress revealing a novel finding of our research. LC3 puncta was observed in peripheral blood mononuclear cells and periphery of HepG2 cells in the case of the diabetic and diabetic-dyslipidemic conditions. Increased expression of ATG5, LC3B, and Beclin supports the autophagic pathway in both PBMC and insulin-resistant Hep G2 cells. Upon blocking autophagy by 3-methyl adenine (3MA), the apoptotic cell population increased significantly, as observed by caspase‐3 cleavage and reduced expression of Bcl2. Autophagy has also been evidenced to control oxidative stress-mediated up-regulation of inflammatory markers like IL-6 and TNF-α. To conclude, this study elucidates autophagy to play a protective role in the case of diabetes mellitus with dyslipidemia. In the present scenario, this study demands to have a significant impact on developing a new therapeutic strategy for diabetic dyslipidemic subjects by enhancing autophagic activity.

Keywords: autophagy, apoptosis, dyslipidemia, reactive oxygen species, reactive nitrogen species, Type 2 diabetes

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Authors: Krishna Nand, Mohammad Taufik

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Fused Filament Fabrication (FFF) is one of the most popular additive manufacturing (AM) technology. In FFF technology, a wire form material (filament) is fed inside a heated chamber, where it gets converted into semi-solid form and extruded out of a nozzle to be deposited on the build platform to fabricate the part. FFF technology is expanding and covering the market at a very rapid rate, so the need of raw materials for 3D printing is also increasing. The cost of 3D printing is directly affected by filament cost. To make 3D printing more economic, a compact and portable filament/wire extrusion system is needed. Wire extrusion systems to extrude ordinary wire/filament made of a single material are available in the market. However, extrusion system to make a composite wire/filament are not available. Hence, in this study, initial efforts have been made to develop a table-top composite wire extruder. The developed system is consisted of mechanical parts, electronics parts, and a control system. A multiple channel hopper, extrusion screw, melting chamber and nozzle, cooling zone, and spool winder are some mechanical parts. While motors, heater, temperature sensor, cooling fans are some electronics parts, which are used to develop this system. A control board has been used to control the various process parameters like – temperature and speed of motors. For the production of composite wire/filament, two different materials could be fed through two channels of hopper, which will be mixed and carried to the heated zone by extrusion screw. The extrusion screw is rotated by a motor, and the speed of this motor will be controlled by the controller as per the requirement of material extrusion rate. In the heated zone, the material will melt with the help of a heating element and extruded out of the nozzle in the form of wire. The developed system occupies less floor space due to the vertical orientation of its heating chamber. It is capable to extrude ordinary filament as well as composite filament, which are compatible with 3D printers available in the market. Further, the developed system could be employed in the research and development of materials, processing, and characterization for 3D printer. The developed system presented in this study could be a better choice for hobbyists and researchers dealing with the fused filament fabrication process to reduce the 3D printing cost significantly by recycling the waste material into 3D printer feed material. Further, it could also be explored as a better alternative for filament production at the commercial level.

Keywords: additive manufacturing, 3D Printing, filament extrusion, pellet extrusion

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Authors: Fatemeh Moosavi, Tumelo Franck Nkoshwane

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Peter Drucker the renowned management guru once said, “The best way to predict the future is to create it.” Mr. Drucker is also the man who placed human capital as the most vital resource of any institution. As such any institution bent on creating a better future, requires a competent human capital, one that is able to execute with efficiency and effectiveness the objective a society aspires to. Technology today is accelerating the rate at which many societies transition to knowledge based societies. In this accelerated paradigm, it is imperative that those in leadership establish a platform capable of sustaining the planned future; intellectual capital. The capitalist economy going into the future will not just be sustained by dollars and cents, but by individuals who possess the creativity to enterprise, innovate and create wealth from ideas. This calls for cities of the future, to have this premise at the heart of their future plan, if the objective of designing sustainable and liveable future cities will be realised. The knowledge economy, now transitioning to the creative economy, requires cities of the future to be ‘gardens’ of inspiration, to be places where knowledge, creativity, and innovation can thrive as these instruments are becoming critical assets for creating wealth in the new economic system. Developing nations must accept that learning is a lifelong process that requires keeping abreast with change and should invest in teaching people how to keep learning. The need to continuously update one’s knowledge, turn these cities into vibrant societies, where new ideas create knowledge and in turn enriches the quality of life of the residents. Cities of the future must have as one of their objectives, the ability to motivate their citizens to learn, share knowledge, evaluate the knowledge and use it to create wealth for a just society. The five functional factors suggested by Kevin Lynch;-vitality, meaning/sense, adaptability, access, control, and monitoring should form the basis on which policy makers and urban designers base their plans for future cities. The authors of this paper believe that developing nations “creative economy clusters”, cities where creative industries drive the need for constant new knowledge creating sustainable learning creative cities. Obviously the form, shape and size of these districts should be cognisant of the environmental, cultural and economic characteristics of each locale. Gaborone city in the republic of Botswana is presented as the case study for this paper.

Keywords: learning city, sustainable creative city, creative industry, good city form

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Authors: Hailemeleak Regassa

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Traditional medicines use medicinal plants as a source of ingredients, and many modern medications are indirectly derived from plants. Consumers in affluent nations are growing disenchanted with contemporary healthcare and looking for alternatives. Oxidative stress is the primary cause of multiple diseases, and exogenous antioxidant supplementation or strengthening the body's endogenous antioxidant defenses are potential ways to counteract the negative effects of oxidative damage. Plants can biosynthesize non-enzymatic antioxidants that can reduce ROS-induced oxidative damage. Aging often aids the propagation and development of carcinogenesis, and older animals and older people exhibit increased vulnerability to tumor promoters. Cancer is a major public health issue, with several anti-cancer medications in clinical use. Potential drugs such as flavopiridol, roscovitine, combretastatin A-4, betulinic acid, and silvestrol are in the clinical or preclinical stages of research. Methodology: Microbial Growth media, Dimethyl sulfoxide (DMSO), methanol, ethyl acetate, and n-hexane were obtained from Himedia Labs, Mumbai, India. plant were collected from the Herbal Garden of Shoolini University campus, Solan, India (Latitude - 30.8644° N and longitude - 77.1184° E). The identity was confirmed by Dr. Y.S. Parmar University of Horticulture and Forestry, Nauni, Solan (H.P.), India, and documented in Voucher specimens - UHF- Herbarium no. 13784; vide book no. 3818 Receipt No. 086. The plant materials were washed with tap water, and 0.1% mercury chloride for 2 minutes, rinsed with distilled water, air dried, and kept in a hot air oven at 40ºc on blotting paper until all the water evaporated and became well dried for grinding. After drying, the plant materials were grounded using a mixer grinder into fine powder transferred into airtight containers with proper labeling, and stored at 4ºc for future use (Horablaga et al., 2023). The extraction process was done according to Altemimi et al., 2017. The 5g powder was mixed with 15 ml of the respective solvents (n-hexane, ethyl acetate, and methanol), and kept for 4-5 days on the platform shaker. The solvents used are based on their increasing polarity index. Then the extract was centrifuged at 10,000rpm for 5 minutes and filtered using No.1 Whatman filter paper.

Keywords: cancer, phytomedicine, medicinal plants, oncology

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Authors: Caja Thimm

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Already well before the Corona pandemic hit the world, ‘fake news‘ were no longer regarded as harmless twists of the truth but as intentionally composed disinformation, often with the goal of manipulative populist propaganda. During the Corona crisis, particularly conspiracy narratives have become a worldwide phenomenon with dangerous consequences (anti vaccination myths). The success of these manipulated news need s to be counteracted by trustworthy news, which in Europe particularly includes public broadcasting media and their social media channels. To understand better how the main public broadcasters in Germany, the UK, and France used Instagram strategically, a comparative study was carried out. The study – comparative analysis of Instagram during the Corona Crisis In our empirical study, we compared the activities by selected formats during the Corona crisis in order to see how the public broadcasters reached their audiences and how this might, in the longer run, affect journalistic strategies on social media platforms. First analysis showed that the increase in the use of social media overall was striking. Almost one in two adult online users (48 %) obtained information about the virus in social media, and in total, 38% of the younger age group (18-24) looked for Covid19 information on Instagram, so the platform can be regarded as one of the central digital spaces for Corona related information searches. Quantitative measures showed that 47% of recent posts by the broadcasters were related to Corona, and 7% treated conspiracy myths. For the more detailed content analysis, the following categories of analysis were applied: • Digital storytelling and instastories • Textuality and semantic keys • links to information • stickers • videochat • fact checking • news ticker • service • infografics and animated tables Additionally to these basic features, we particularly looked for new formats created during the crisis. Journalistic use of social media platforms opens up immediate and creative ways of applying the media logics of the respective platforms, and particularly the BBC and ARD formats proved to be interactive, responsive, and entertaining. Among them were new formats such as a space for user questions and personal uploads, interviews, music, comedy, etc. Particularly the fact checking channel got a lot of attention, as many user questions were focused on the conspiracy theories, which dominated the public discourse during many weeks in 2020. In the presentation, we will introduce eight particular strategies that show how public broadcasting journalism can adopt digital platforms and use them creatively and, hence help to counteract against conspiracy narratives and fake news.

Keywords: fake news, social media, digital journalism, digital methods

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Authors: Shobrina Silmi Qori Tarlita, Fariz Kukuh Harwinda

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Indonesia has 81.000 kilometers coastal line and 70% water surface which is known as the country who has a huge potential in fisheries sector and also which is able to support more than 50 % of Gross Domestic Product. But according to Department of Marine and Fisheries data, fisheries sector supported only 20% of Total GDP in 1998. Not only that, the highest decline in fisheries sector income occured in 2009. Those conditions occur, because of some factors contributed to the lack of integrated working platform for the fisheries and marine management in some areas which have a high productivity to increase the economical profit every year for the country, especially Indonesia, besides the labor requirement for every company, whether a big company or smaller one, depends on the natural condition that makes a lot of people become unemployed if the weather condition or any other conditions dealing with the natural condition is bad for creating fisheries and marine management, especially in aquaculture and fish – captured operation. Not only those, a lot of fishermen, especially in Indonesia, mostly make their job profession as an additional job or side job to fulfill their own needs, although they are averagely poor. Another major problem are the lack of the sustainable developmental program to stabilize the productivity of fisheries and marine natural source, like protecting the environment for fish nursery ground and migration channel, that makes the low productivity of fisheries and marine natural resource, even though the growth of the society in Indonesia has increased for years and needs more food resource to comply the high demand nutrition for living. The development of Minapolitan Area is one of the alternative solution to build a better place for aqua-culturist as well as the fishermen which focusing on systemic and business effort for fisheries and marine management. Minapolitan is kind of integration area which gathers and integrates the ones who is focusing their effort and business in fisheries sector, so that Minapolitan is capable of triggering the fishery activity on the area which using Minapolitan management intensively. From those things, finally, Minapolitan is expected to reinforce the sustainable development through increasing the productivity of fish – capturing operation as well as aquaculture, and it is also expected that Minapolitan will be able to increase GDP, the earning for a lot of people and also will be able to bring prosperity around the world. From those backgrounds, this paper will explain more about the Minapolitan Area and the design of reinforcing the Minapolitan Area by zonation in the Fishery and Marine exploitation area with high productivity as well as low productivity. Hopefully, this solution will be able to answer the economical and social issue for declining food resource, especially fishery and marine resource.

Keywords: Minapolitan, fisheries, economy, Indonesia

Procedia PDF Downloads 463

Authors: Inje Cho

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The leading health risks threatening the world today are associated with a modern lifestyle characterized by sedentary behavior, stress, anxiety, and an obesogenic food environment. To counter this alarming trend, the Centers for Disease Control and Prevention have proffered Physical Activity guidelines to bolster physical engagement. Concurrently, the burgeon of smartphones and mobile applications has witnessed a proliferation of fitness applications aimed at invigorating exercise adherence and real-time activity monitoring. Grounded in the Uses and gratification theory, this study delves into the technological affordances of mobile fitness applications, discerning the mediating influences of escapism and social outcome expectations on attitudes and exercise intention. The theory explains how individuals employ distinct communication mediums to satiate their exigencies and desires. Technological affordances manifest as attributes of emerging technologies that galvanize personal engagement in physical activities. Several features of mobile fitness applications include affordances for goal setting, virtual rewards, peer support, and exercise information. Escapism, denoting the inclination to disengage from normal routines, has emerged as a salient motivator for the consumption of new media. This study postulates that individual’s perceptions technological affordances within mobile fitness applications, can affect escapism and social outcome expectations, potentially influencing attitude, and behavior formation. Thus, the integrated model has been developed to empirically examine the interrelationships between technological affordances, escapism, social outcome expectations, and exercise intention. Structural Equation Modelling serves as the methodological tool, and a cohort of 400 Fitbit users shall be enlisted from the Prolific, data collection platform. A sequence of multivariate data analyses will scrutinize both the measurement and hypothesized structural models. By delving into the effects of mobile fitness applications, this study contributes to the growing of new media studies in sport management. Moreover, the novel integration of the uses and gratification theory, technological affordances, via the prism of escapism, illustrates the dynamics that underlies mobile fitness user’s attitudes and behavioral intentions. Therefore, the findings from this study contribute to theoretical understanding and provide pragmatic insights to developers and practitioners in optimizing the impact of mobile fitness applications.

Keywords: technological affordances, uses and gratification, mobile fitness apps, escapism, physical activity

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Authors: Eiman Kattan, Hong Wei

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In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

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Authors: David Ofosu-Hamilton, John K. E. Edumadze

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Universities have come to recognize the role Information and Communication Technology (ICT) skills plays in the daily activities of tertiary students. The ability to use ICT – essentially, computers and their diverse applications – are important resources that influence an individual’s economic and social participation and human capital development. Our society now increasingly relies on the Internet, and the Cloud as a means to communicate and disseminate information. The educated individual should, therefore, be able to use ICT to create and share knowledge that will improve society. It is, therefore, important that universities require incoming students to demonstrate a level of computer proficiency or trained to do so at a minimal cost by deploying advanced educational technologies. The training and standardized assessment of all in-coming first-year students of the University of Cape Coast in Information Technology Skills (ITS) have become a necessity as students’ most often than not highly overestimate their digital skill and digital ignorance is costly to any economy. The one-semester course is targeted at fresh students and aimed at enhancing the productivity and software skills of students. In this respect, emphasis is placed on skills that will enable students to be proficient in using Microsoft Office and Google Apps for Education for their academic work and future professional work whiles using emerging digital multimedia technologies in a safe, ethical, responsible, and legal manner. The course is delivered in blended mode - online and self-paced (student centered) using Alison’s free cloud-based tutorial (Moodle) of Microsoft Office videos. Online support is provided via discussion forums on the University’s Moodle platform and tutor-directed and assisted at the ICT Centre and Google E-learning laboratory. All students are required to register for the ITS course during either the first or second semester of the first year and must participate and complete it within a semester. Assessment focuses on Alison online assessment on Microsoft Office, Alison online assessment on ALISON ABC IT, Peer assessment on e-portfolio created using Google Apps/Office 365 and an End of Semester’s online assessment at the ICT Centre whenever the student was ready in the cause of the semester. This paper, therefore, focuses on the digital culture approach of hybrid teaching, learning and paperless examinations and the possible adoption by other courses or programs at the University of Cape Coast.

Keywords: assessment, blended, cloud, paperless

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Authors: Jae-Hyeon Kim, Michael Lee

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Intrinsic and acquired resistance limits the therapeutic benefits of oncogenic BRAF inhibitors in melanoma. MicroRNAs (miRNA) regulate the expression of target mRNAs by repressing their translation. Thus, we investigated miRNA expression patterns in melanoma cell lines to identify candidate biomarkers for acquired resistance to BRAF inhibitor. Here, we used Affymetrix miRNA V3.0 microarray profiling platform to compare miRNA expression levels in three cell lines containing BRAF inhibitor-sensitive A375P BRAF V600E cells, their BRAF inhibitor-resistant counterparts (A375P/Mdr), and SK-MEL-2 BRAF-WT cells with intrinsic resistance to BRAF inhibitor. The miRNAs with at least a two-fold change in expression between BRAF inhibitor-sensitive and –resistant cell lines, were identified as differentially expressed. Averaged intensity measurements identified 138 and 217 miRNAs that were differentially expressed by 2 fold or more between: 1) A375P and A375P/Mdr; 2) A375P and SK-MEL-2, respectively. The hierarchical clustering revealed differences in miRNA expression profiles between BRAF inhibitor-sensitive and –resistant cell lines for miRNAs involved in intrinsic and acquired resistance to BRAF inhibitor. In particular, 43 miRNAs were identified whose expression was consistently altered in two BRAF inhibitor-resistant cell lines, regardless of intrinsic and acquired resistance. Twenty five miRNAs were consistently upregulated and 18 downregulated more than 2-fold. Although some discrepancies were detected when miRNA microarray data were compared with qPCR-measured expression levels, qRT-PCR for five miRNAs (miR-3617, miR-92a1, miR-1246, miR-1936-3p, and miR-17-3p) results showed excellent agreement with microarray experiments. To further investigate cellular functions of miRNAs, we examined effects on cell proliferation. Synthetic oligonucleotide miRNA mimics were transfected into three cell lines, and proliferation was quantified using a colorimetric assay. Of the 5 miRNAs tested, only miR-1246 altered cell proliferation of A375P/Mdr cells. The transfection of miR-1246 mimic strongly conferred PLX-4720 resistance to A375P/Mdr cells, implying that miR-1246 upregulation confers acquired resistance to BRAF inhibition. We also found that PLX-4720 caused much greater G2/M arrest in A375P/Mdr cells transfected with miR-1246mimic than that seen in scrambled RNA-transfected cells. Additionally, miR-1246 mimic partially caused a resistance to autophagy induction by PLX-4720. These results indicate that autophagy does play an essential death-promoting role inPLX-4720-induced cell death. Taken together, these results suggest that miRNA expression profiling in melanoma cells can provide valuable information for a network of BRAF inhibitor resistance-associated miRNAs.

Keywords: microRNA, BRAF inhibitor, drug resistance, autophagy

Procedia PDF Downloads 325

Authors: Julia R. Beulig, Stefan Ohla, Detlev Belder

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In contrast to off-line analytical methods, lab-on-a-chip technology delivers direct information about the observed reaction. Therefore, microfluidic devices make an important scientific contribution, e.g. in the field of synthetic chemistry. Herein, the rapid generation of analytical data can be applied for the optimization of chemical reactions. These microfluidic devices enable a fast change of reaction conditions as well as a resource saving method of operation. In the presented work, we focus on the investigation of multiphase regimes, more specifically on a biphasic microfluidic droplet systems. Here, every single droplet is a reaction container with customized conditions. The biggest challenge is the rapid qualitative and quantitative readout of information as most detection techniques for droplet systems are non-specific, time-consuming or too slow. An exception is the electrospray mass spectrometry (ESI-MS). The combination of a reaction screening platform with a rapid and specific detection method is an important step in droplet-based microfluidics. In this work, we present a novel approach for synthesis optimization on the nanoliter scale with direct ESI-MS detection. The development of a droplet-based microfluidic device, which enables the modification of different parameters while simultaneously monitoring the effect on the reaction within a single run, is shown. By common soft- and photolithographic techniques a polydimethylsiloxane (PDMS) microfluidic chip with different functionalities is developed. As an interface for the MS detection, we use a steel capillary for ESI and improve the spray stability with a Teflon siphon tubing, which is inserted underneath the steel capillary. By optimizing the flow rates, it is possible to screen parameters of various reactions, this is exemplarity shown by a Domino Knoevenagel Hetero-Diels-Alder reaction. Different starting materials, catalyst concentrations and solvent compositions are investigated. Due to the high repetition rate of the droplet production, each set of reaction condition is examined hundreds of times. As a result, of the investigation, we receive possible reagents, the ideal water-methanol ratio of the solvent and the most effective catalyst concentration. The developed system can help to determine important information about the optimal parameters of a reaction within a short time. With this novel tool, we make an important step on the field of combining droplet-based microfluidics with organic reaction screening.

Keywords: droplet, mass spectrometry, microfluidics, organic reaction, screening

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Authors: Paresh Patel, Priya Patel, Vaidehi Sorathiya, Navin Sheth

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The aim of present work was to fabricate Salmeterol Xinafoate (SX) metered dose inhaler (MDI) for asthma and to evaluate the SX loaded solid lipid nanoparticles (SLNs) for pulmonary delivery. Solid lipid nanoparticles can be used to deliver particles to the lungs via MDI. A modified solvent emulsification diffusion technique was used to prepare Salmeterol Xinafoate loaded solid lipid nanoparticles by using compritol 888 ATO as lipid, tween 80 as surfactant, D-mannitol as cryoprotecting agent and L-leucine was used to improve aerosolization behaviour. Box-Behnken design was applied with 17 runs. 3-D surface response plots and contour plots were drawn and optimized formulation was selected based on minimum particle size and maximum % EE. % yield, in vitro diffusion study, scanning electron microscopy, X-ray diffraction, DSC, FTIR also characterized. Particle size, zeta potential analyzed by Zetatrac particle size analyzer and aerodynamic properties was carried out by cascade impactor. Pre convulsion time was examined for control group, treatment group and compare with marketed group. MDI was evaluated for leakage test, flammability test, spray test and content per puff. By experimental design, particle size and % EE found to be in range between 119-337 nm and 62.04-76.77% by solvent emulsification diffusion technique. Morphologically, particles have spherical shape and uniform distribution. DSC & FTIR study showed that no interaction between drug and excipients. Zeta potential shows good stability of SLNs. % respirable fraction found to be 52.78% indicating reach to the deep part of lung such as alveoli. Animal study showed that fabricated MDI protect the lungs against histamine induced bronchospasm in guinea pigs. MDI showed sphericity of particle in spray pattern, 96.34% content per puff and non-flammable. SLNs prepared by Solvent emulsification diffusion technique provide desirable size for deposition into the alveoli. This delivery platform opens up a wide range of treatment application of pulmonary disease like asthma via solid lipid nanoparticles.

Keywords: salmeterol xinafoate, solid lipid nanoparticles, box-behnken design, solvent emulsification diffusion technique, pulmonary delivery

Procedia PDF Downloads 451

Authors: Z. Sun

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Health communication is essential in promoting healthy lifestyles, managing disease conditions, and eventually reducing health disparities. The key elements of successful health communication always include the development of communication strategies to engage people in thinking about their health, inform them about healthy choices, persuade them to adopt safe and healthy behaviours, and eventually achieve public health objectives. The use of 'Narrative' is recognised as a kind of health communication strategy to enhance personal and public health due to its potential persuasive effect in motivating and supporting individuals change their beliefs and behaviours by inviting them into a narrative world, breaking down their cognitive and emotional resistance and enhance their acceptance of the ideas portrayed in narratives. Meanwhile, the popularity of social media has provided a novel means of communication for both healthcare stakeholders, and a special group of active social media users (influencers) have started playing a pivotal role in providing health ‘solutions’. Such individuals are often referred to as ‘influencers’ because of their central position in the online communication system and the persuasive effect their actions may have on audiences. They may have established a positive rapport with their audience, earned trust and credibility in a specific area, and thus, their audience considers the information they delivered to be authentic and influential. To our best knowledge, to date, there is no published research that examines the effect of diabetes narratives presented by social media influencers and their impacts on health-related outcomes. The primary aim of this study is to investigate the diabetes narratives presented by social media influencers in the UK because of the new dimension they bring to health communication and the potential impact they may have on audiences' health outcomes. This study is situated within the interpretivist and narrative paradigms. A mixed methodology combining both quantitative and qualitative approaches has been adopted. Qualitative data has been derived to provide a better understanding of influencers’ personal experiences and how they construct meanings and make sense of their world, while quantitative data has been accumulated to identify key social media influencers in the UK and measure the impact of diabetes narratives on audiences. Twitter has been chosen as the social media platform to initially identify key influencers. Two groups of participants are the top 10 key social media influencers in the UK and 100 audiences of each influencer, which means a total of 1000 audiences have been invited. This paper is going to discuss, first of all, the background of the research under the context of health communication; Secondly, the necessity and contribution of this research; then, the major research questions being explored; and finally, the methods to be used.

Keywords: diabetes, health communication, narratives, social media influencers

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Authors: Ifeanyi Adigwe, Thomas Van der Walt

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Digital media has been integrated into the social and entertainment life of young children, and as such, the impact of digital media appears to affect young people of all ages and it is believed that this will continue to shape the world of young children. Since, technological advancement of digital media presents adolescents with diverse contexts, platforms and avenues to engage with digital media outside the home environment and from parents' supervision, a wide range of new challenges has further complicated the already difficult tasks for parents and altered the landscape of parenting. Despite the fact that adolescents now have access to a wide range of digital media technologies both at home and in the learning environment, parenting practices such as active, restrictive, co-use, participatory and technical mediations are important in mitigating of online risks adolescents may encounter as a result of digital media use. However, these mediation practices only focus on the home environment including digital media present in the home and may not necessarily transcend outside the home and other learning environments where adolescents use digital media for school work and other activities. This poses the question of who mediates adolescent's digital media use outside the home environment. The learning environment could be a ''loose platform'' where an adolescent can maximise digital media use considering the fact that there is no restriction in terms of content and time allotted to using digital media during school hours. That is to say that an adolescent can play the ''bad boy'' online in school because there is little or no restriction of digital media use and be exposed to online risks and play the ''good boy'' at home because of ''heavy'' parental mediation. This is the reason why parent mediation practices have been ineffective because a parent may not be able to track adolescents digital media use considering the diversity of contexts, platforms and avenues adolescents use digital media. This study argues that due to the diverse nature of digital media technology, parents may not be able to monitor the 'whereabouts' of their children in the digital space. This is because adolescent digital media usage may not only be confined to the home environment but other learning environments like schools. This calls for urgent attention on the part of teachers to understand the intricacies of how digital media continue to shape the world in which young children are developing and learning. It is, therefore, imperative for parents to liaise with the schools of their children to mediate digital media use during school hours. The implication of parents- teachers mediation practices are discussed. The article concludes by suggesting that third party mediation by teachers in schools and other learning environments should be encouraged and future research needs to consider the emergent strategy of teacher-children mediation approach and the implication for policy for both the home and learning environments.

Keywords: digital media, digital age, parent mediation, third party mediation

Procedia PDF Downloads 158

Authors: I. Valdez, J. Perdomo, M. Colindres, N. Castro

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Today, digital servo systems are extensively used in industrial manufacturing processes, robotic applications, vehicles and other areas. In such control systems, control action is provided by digital controllers with different compensation algorithms, which are designed to meet specific requirements for a given application. Due to the constant search for optimization in industrial processes, it is of interest to design digital controllers that offer ease of realization, improved computational efficiency, affordable return rates, and ease of tuning that ultimately improve the performance of the controlled actuators. There is a vast range of options of compensation algorithms that could be used, although in the industry, most controllers used are based on a PID structure. This research article compares different types of digital compensators implemented in a servo system for DC motor position control. PID compensation is evaluated on its two most common architectures: PID position form (1 DOF), and PID speed form (2 DOF). State feedback algorithms are also evaluated, testing two modern control theory techniques: discrete state observer for non-measurable variables tracking, and a linear quadratic method which allows a compromise between the theoretical optimal control and the realization that most closely matches it. The compared control systems’ performance is evaluated through simulations in the Simulink platform, in which it is attempted to model accurately each of the system’s hardware components. The criteria by which the control systems are compared are reference tracking and disturbance rejection. In this investigation, it is considered that the accurate tracking of the reference signal for a position control system is particularly important because of the frequency and the suddenness in which the control signal could change in position control applications, while disturbance rejection is considered essential because the torque applied to the motor shaft due to sudden load changes can be modeled as a disturbance that must be rejected, ensuring reference tracking. Results show that 2 DOF PID controllers exhibit high performance in terms of the benchmarks mentioned, as long as they are properly tuned. As for controllers based on state feedback, due to the nature and the advantage which state space provides for modelling MIMO, it is expected that such controllers evince ease of tuning for disturbance rejection, assuming that the designer of such controllers is experienced. An in-depth multi-dimensional analysis of preliminary research results indicate that state feedback control method is more satisfactory, but PID control method exhibits easier implementation in most control applications.

Keywords: control, DC motor, discrete PID, discrete state feedback

Procedia PDF Downloads 266

Authors: Kuniaki Kudo, Raviraj Solanki, Kaushal Patel, Yash Virani

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This research mainly concerns optimizing UI test automation for large-scale web applications. The test target application is the HHAexchange homecare management WEB application that seamlessly connects providers, state Medicaid programs, managed care organizations (MCOs), and caregivers through one platform with large-scale functionalities. This study focuses on user interface automation testing for the WEB application. The quality assurance team must execute many manual users interface test cases in the development process to confirm no regression bugs. The team automated 346 test cases; the UI automation test execution time was over 17 hours. The business requirement was reducing the execution time to release high-quality products quickly, and the quality assurance automation team modernized the test automation framework to optimize the execution time. The base of the WEB UI automation test environment is Selenium, and the test code is written in Python. Adopting a compilation language to write test code leads to an inefficient flow when introducing scalability into a traditional test automation environment. In order to efficiently introduce scalability into Test Automation, a scripting language was adopted. The scalability implementation is mainly implemented with AWS's serverless technology, an elastic container service. The definition of scalability here is the ability to automatically set up computers to test automation and increase or decrease the number of computers running those tests. This means the scalable mechanism can help test cases run parallelly. Then test execution time is dramatically decreased. Also, introducing scalable test automation is for more than just reducing test execution time. There is a possibility that some challenging bugs are detected by introducing scalable test automation, such as race conditions, Etc. since test cases can be executed at same timing. If API and Unit tests are implemented, the test strategies can be adopted more efficiently for this scalability testing. However, in WEB applications, as a practical matter, API and Unit testing cannot cover 100% functional testing since they do not reach front-end codes. This study applied a scalable UI automation testing strategy to the large-scale homecare management system. It confirmed the optimization of the test case execution time and the detection of a challenging bug. This study first describes the detailed architecture of the scalable test automation environment, then describes the actual performance reduction time and an example of challenging issue detection.

Keywords: aws, elastic container service, scalability, serverless, ui automation test

Procedia PDF Downloads 106

Authors: Sujata Sharma, Avinash Singh, Lovely Gautam, Pradeep Sharma, Mau Sinha, Asha Bhushan, Punit Kaur, Tej P. Singh

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Peptidyl-tRNA hydrolase (Pth) Pth is an essential bacterial enzyme that catalyzes the release of free tRNA and peptide moeities from peptidyl tRNAs during stalling of protein synthesis. In order to design inhibitors of Pth from Pseudomonas aeruginosa (PaPth), we have determined the structures of PaPth in its native state and in the bound states with two compounds, amino acylate-tRNA analogue (AAtA) and 5-azacytidine (AZAC). The peptidyl-tRNA hydrolase gene from Pseudomonas aeruginosa was amplified by Phusion High-Fidelity DNA Polymerase using forward and reverse primers, respectively. The E. coliBL21 (λDE3) strain was used for expression of the recombinant peptidyl-tRNA hydrolase from Pseudomonas aeruginosa. The protein was purified using a Ni-NTA superflow column. The crystallization experiments were carried out using hanging drop vapour diffusion method. The crystals diffracted to 1.50 Å resolution. The data were processed using HKL-2000. The polypeptide chain of PaPth consists of 194 amino acid residues from Met1 to Ala194. The centrally located β-structure is surrounded by α-helices from all sides except the side that has entrance to the substrate binding site. The structures of the complexes of PaPth with AAtA and AZAC showed the ligands bound to PaPth in the substrate binding cleft and interacted with protein atoms extensively. The residues that formed intermolecular hydrogen bonds with the atoms of AAtA included Asn12, His22, Asn70, Gly113, Asn116, Ser148, and Glu161 of the symmetry related molecule. The amino acids that were involved in hydrogen bonded interactions in case of AZAC included, His22, Gly113, Asn116, and Ser148. As indicated by fittings of two ligands and the number of interactions made by them with protein atoms, AAtA appears to be a more compatible with the structure of the substrate binding cleft. However, there is a further scope to achieve a better stacking than that of O-tyrosyl moiety because it is not still ideally stacked. These observations about the interactions between the protein and ligands have provided the information about the mode of binding of ligands, nature and number of interactions. This information may be useful for the design of tight inhibitors of Pth enzymes.

Keywords: peptidyl tRNA hydrolase, Acinetobacter baumannii, Pth enzymes, O-tyrosyl

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Authors: Madhuka G. P. D. Udantha, Gihan V. Dias, Surangika Ranathunga

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Today Websites contain very interesting applications. But there are only few methodologies to analyze User navigations through the Websites and formulating if the Website is put to correct use. The web logs are only used if some major attack or malfunctioning occurs. Web Logs contain lot interesting dealings on users in the system. Analyzing web logs has become a challenge due to the huge log volume. Finding interesting patterns is not as easy as it is due to size, distribution and importance of minor details of each log. Web logs contain very important data of user and site which are not been put to good use. Retrieving interesting information from logs gives an idea of what the users need, group users according to their various needs and improve site to build an effective and efficient site. The model we built is able to detect attacks or malfunctioning of the system and anomaly detection. Logs will be more complex as volume of traffic and the size and complexity of web site grows. Unsupervised techniques are used in this solution which is fully automated. Expert knowledge is only used in validation. In our approach first clean and purify the logs to bring them to a common platform with a standard format and structure. After cleaning module web session builder is executed. It outputs two files, Web Sessions file and Indexed URLs file. The Indexed URLs file contains the list of URLs accessed and their indices. Web Sessions file lists down the indices of each web session. Then DBSCAN and EM Algorithms are used iteratively and recursively to get the best clustering results of the web sessions. Using homogeneity, completeness, V-measure, intra and inter cluster distance and silhouette coefficient as parameters these algorithms self-evaluate themselves to input better parametric values to run the algorithms. If a cluster is found to be too large then micro-clustering is used. Using Cluster Signature Module the clusters are annotated with a unique signature called finger-print. In this module each cluster is fed to Associative Rule Learning Module. If it outputs confidence and support as value 1 for an access sequence it would be a potential signature for the cluster. Then the access sequence occurrences are checked in other clusters. If it is found to be unique for the cluster considered then the cluster is annotated with the signature. These signatures are used in anomaly detection, prevent cyber attacks, real-time dashboards that visualize users, accessing web pages, predict actions of users and various other applications in Finance, University Websites, News and Media Websites etc.

Keywords: anomaly detection, clustering, pattern recognition, web sessions

Procedia PDF Downloads 288

Authors: Mina Naeini, Thomas A. Adams II

Abstract:

Solid Oxide Fuel Cells (SOFCs) feature high electrical efficiency and generate substantial amounts of waste heat that make them suitable for integrated community energy systems (ICEs). By harvesting and distributing the waste heat through hot water pipelines, SOFCs can meet thermal demand of the communities. Therefore, they can replace traditional gas boilers and reduce greenhouse gas (GHG) emissions. Despite these advantages of SOFCs over competing power generation units, this technology has not been successfully commercialized in large-scale to replace traditional generators in ICEs. One reason is that SOFC performance deteriorates over long-term operation, which makes it difficult to find the proper sizing of the cells for a particular ICE system. In order to find the optimal sizing and operating conditions of SOFCs in a community, a proper knowledge of degradation mechanisms and effects of operating conditions on SOFCs long-time performance is required. The simplified SOFC models that exist in the current literature usually do not provide realistic results since they usually underestimate rate of performance drop by making too many assumptions or generalizations. In addition, some of these models have been obtained from experimental data by curve-fitting methods. Although these models are valid for the range of operating conditions in which experiments were conducted, they cannot be generalized to other conditions and so have limited use for most ICEs. In the present study, a general, detailed degradation-based model is proposed that predicts the performance of conventional SOFCs over a long period of time at different operating conditions. Conventional SOFCs are composed of Yttria Stabilized Zirconia (YSZ) as electrolyte, Ni-cermet anodes, and LaSr₁₋ₓMnₓO₃ (LSM) cathodes. The following degradation processes are considered in this model: oxidation and coarsening of nickel particles in the Ni-cermet anodes, changes in the pore radius in anode, electrolyte, and anode electrical conductivity degradation, and sulfur poisoning of the anode compartment. This model helps decision makers discover the optimal sizing and operation of the cells for a stable, efficient performance with the fewest assumptions. It is suitable for a wide variety of applications. Sulfur contamination of the anode compartment is an important cause of performance drop in cells supplied with hydrocarbon-based fuel sources. H₂S, which is often added to hydrocarbon fuels as an odorant, can diminish catalytic behavior of Ni-based anodes by lowering their electrochemical activity and hydrocarbon conversion properties. Therefore, the existing models in the literature for H₂-supplied SOFCs cannot be applied to hydrocarbon-fueled SOFCs as they only account for the electrochemical activity reduction. A regression model is developed in the current work for sulfur contamination of the SOFCs fed with hydrocarbon fuel sources. The model is developed as a function of current density and H₂S concentration in the fuel. To the best of authors' knowledge, it is the first model that accounts for impact of current density on sulfur poisoning of cells supplied with hydrocarbon-based fuels. Proposed model has wide validity over a range of parameters and is consistent across multiple studies by different independent groups. Simulations using the degradation-based model illustrated that SOFCs voltage drops significantly in the first 1500 hours of operation. After that, cells exhibit a slower degradation rate. The present analysis allowed us to discover the reason for various degradation rate values reported in literature for conventional SOFCs. In fact, the reason why literature reports very different degradation rates, is that literature is inconsistent in definition of how degradation rate is calculated. In the literature, the degradation rate has been calculated as the slope of voltage versus time plot with the unit of voltage drop percentage per 1000 hours operation. Due to the nonlinear profile of voltage over time, degradation rate magnitude depends on the magnitude of time steps selected to calculate the curve's slope. To avoid this issue, instantaneous rate of performance drop is used in the present work. According to a sensitivity analysis, the current density has the highest impact on degradation rate compared to other operating factors, while temperature and hydrogen partial pressure affect SOFCs performance less. The findings demonstrated that a cell running at lower current density performs better in long-term in terms of total average energy delivered per year, even though initially it generates less power than if it had a higher current density. This is because of the dominant and devastating impact of large current densities on the long-term performance of SOFCs, as explained by the model.

Keywords: degradation rate, long-term performance, optimal operation, solid oxide fuel cells, SOFCs

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