Search results for: parameter selection

Authors: Vaso K. Kapnopoulou, Piero Caridis

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The fatigue of ship structural details is of major concern in the maritime industry as it can generate fracture issues that may compromise structural integrity. In the present study, a fatigue analysis of the lower hopper knuckle connection of a bulk carrier was conducted using the Finite Element Method by means of ABAQUS/CAE software. The fatigue life was calculated using Miner’s Rule and the long-term distribution of stress range by the use of the two-parameter Weibull distribution. The cumulative damage ratio was estimated using the fatigue damage resulting from the stress range occurring at each load condition. For this purpose, a cargo hold model was first generated, which extends over the length of two holds (the mid-hold and half of each of the adjacent holds) and transversely over the full breadth of the hull girder. Following that, a submodel of the area of interest was extracted in order to calculate the hot spot stress of the connection and to estimate the fatigue life of the structural detail. Two hot spot locations were identified; one at the top layer of the inner bottom plate and one at the top layer of the hopper plate. The IACS Common Structural Rules (CSR) require that specific dynamic load cases for each loading condition are assessed. Following this, the dynamic load case that causes the highest stress range at each loading condition should be used in the fatigue analysis for the calculation of the cumulative fatigue damage ratio. Each load case has a different effect on ship hull response. Of main concern, when assessing the fatigue strength of the lower hopper knuckle connection, was the determination of the maximum, i.e. the critical value of the stress range, which acts in a direction normal to the weld toe line. This acts in the transverse direction, that is, perpendicularly to the ship's centerline axis. The load cases were explored both theoretically and numerically in order to establish the one that causes the highest damage to the location examined. The most severe one was identified to be the load case induced by beam sea condition where the encountered wave comes from the starboard. At the level of the cargo hold model, the model was assumed to be simply supported at its ends. A coarse mesh was generated in order to represent the overall stiffness of the structure. The elements employed were quadrilateral shell elements, each having four integration points. A linear elastic analysis was performed because linear elastic material behavior can be presumed, since only localized yielding is allowed by most design codes. At the submodel level, the displacements of the analysis of the cargo hold model to the outer region nodes of the submodel acted as boundary conditions and applied loading for the submodel. In order to calculate the hot spot stress at the hot spot locations, a very fine mesh zone was generated and used. The fatigue life of the detail was found to be 16.4 years which is lower than the design fatigue life of the structure (25 years), making this location vulnerable to fatigue fracture issues. Moreover, the loading conditions that induce the most damage to the location were found to be the various ballasting conditions.

Keywords: dynamic load cases, finite element method, high cycle fatigue, lower hopper knuckle

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Authors: Lise Paesen, Marielle Leijten

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People diagnosed with probable Alzheimer disease suffer from an impairment of their language capacities; a gradual impairment which affects both their spoken and written communication. Our study aims at characterising the language decline in DAT patients with the use of congeneric elicited writing tasks. Within these tasks, a descriptive text has to be written based upon images with which the participants are confronted. A randomised set of images allows us to present the participants with a different task on every encounter, thus allowing us to avoid a recognition effect in this iterative study. This method is a revision from previous studies, in which participants were presented with a larger picture depicting an entire scene. In order to create the randomised set of images, existing pictures were adapted following strict criteria (e.g. frequency, AoA, colour, ...). The resulting data set contained 50 images, belonging to several categories (vehicles, animals, humans, and objects). A pre-test was constructed to validate the created picture set; most images had been used before in spoken picture naming tasks. Hence the same reaction times ought to be triggered in the typed picture naming task. Once validated, the effectiveness of the descriptive tasks was assessed. First, the participants (n=60 students, n=40 healthy elderly) performed a typing task, which provided information about the typing speed of each individual. Secondly, two descriptive writing tasks were carried out, one simple and one complex. The simple task contains 4 images (1 animal, 2 objects, 1 vehicle) and only contains elements with high frequency, a young AoA (<6 years), and fast reaction times. Slow reaction times, a later AoA (≥ 6 years) and low frequency were criteria for the complex task. This task uses 6 images (2 animals, 1 human, 2 objects and 1 vehicle). The data were collected with the keystroke logging programme Inputlog. Keystroke logging tools log and time stamp keystroke activity to reconstruct and describe text production processes. The data were analysed using a selection of writing process and product variables, such as general writing process measures, detailed pause analysis, linguistic analysis, and text length. As a covariate, the intrapersonal interkey transition times from the typing task were taken into account. The pre-test indicated that the new images lead to similar or even faster reaction times compared to the original images. All the images were therefore used in the main study. The produced texts of the description tasks were significantly longer compared to previous studies, providing sufficient text and process data for analyses. Preliminary analysis shows that the amount of words produced differed significantly between the healthy elderly and the students, as did the mean length of production bursts, even though both groups needed the same time to produce their texts. However, the elderly took significantly more time to produce the complex task than the simple task. Nevertheless, the amount of words per minute remained comparable between simple and complex. The pauses within and before words varied, even when taking personal typing abilities (obtained by the typing task) into account.

Keywords: Alzheimer's disease, experimental design, language decline, writing process

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Authors: Carolina Cuéllar, Paz González

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Research has shown that school leadership has a significant indirect effect on students’ achievements. In Chile, evidence has also revealed that this impact is stronger in vulnerable schools. With the aim of strengthening school leadership, public policy has taken up the challenge of enhancing capabilities of novice principals through the implementation of induction programs, which include a mentoring component, entrusting the task of delivering these programs to universities. The importance of using mentoring or coaching models in the preparation of novice school leaders has been emphasized in the international literature. Thus, it can be affirmed that building leadership capacity through partnership is crucial to facilitate cognitive and affective support required in the initial phase of the principal career, gain role clarification and socialization in context, stimulate reflective leadership practice, among others. In Chile, mentoring is a recent phenomenon in the field of school leadership and it is even more new in the preparation of new principals who work in public schools. This study, funded by the Chilean Ministry of Education, sought to explore the challenges and lessons arising from the design and implementation of mentoring processes which are part of the induction programs, according to the perception of the different actors involved: ministerial agents, university coordinators, mentors and novice principals. The investigation used a qualitative design, based on a study of three cases (three induction programs). The sources of information were 46 semi-structured interviews, applied in two moments (at the beginning and end of mentoring). Content analysis technique was employed. Data focused on the uniqueness of each case and the commonalities within the cases. Five main challenges and lessons emerged in the design and implementation of mentoring within the induction programs for new principals from Chilean public schools. They comprised the need of (i) developing a shared conceptual framework on mentoring among the institutions and actors involved, which helps align the expectations for the mentoring component within the induction programs, along with assisting in establishing a theory of action of mentoring that is relevant to the public school context; (ii) recognizing trough actions and decisions at different levels that the role of a mentor differs from the role of a principal, which challenge the idea that an effective principal will always be an effective mentor; iii) improving mentors’ selection and preparation processes trough the definition of common guiding criteria to ensure that a mentor takes responsibility for developing critical judgment of novice principals, which implies not limiting the mentor’s actions to assist in the compliance of prescriptive practices and standards; (iv) generating common evaluative models with goals, instruments and indicators consistent with the characteristics of mentoring processes, which helps to assess expected results and impact; and (v) including the design of a mentoring structure as an outcome of the induction programs, which helps sustain mentoring within schools as a collective professional development practice. Results showcased interwoven elements that entail continuous negotiations at different levels. Taking action will contribute to policy efforts aimed at professionalizing the leadership role in public schools.

Keywords: induction programs, mentoring, novice principals, school leadership preparation

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Authors: Chen Jiang, Eric Jordan, Maurice Gell, Balakrishnan Nair

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Nuclear fusion, one of the most promising options for reliably generating large amounts of carbon-free energy in the future, has seen a plethora of ground-breaking technological advances in recent years. An efficient and durable “breeding blanket”, needed to ensure a reactor’s self-sufficiency by maintaining the optimal coolant temperature as well as by minimizing radiation dosage behind the blanket, still remains a technological challenge for the various reactor designs for commercial fusion power plants. A relatively new dual-coolant lead-lithium (DCLL) breeder design has exhibited great potential for high-temperature (>700oC), high-thermal-efficiency (>40%) fusion reactor operation. However, the structural material, namely reduced activation ferritic-martensitic (RAFM) steel, is not chemically stable in contact with molten Pb-17%Li coolant. Thus, to utilize this new promising reactor design, the demand for effective corrosion-resistant coatings on RAFM steels represents a pressing need. Solution Spray Technologies LLC (SST) is developing a double-layer ceramic coating design to address the corrosion protection of RAFM steels, using a novel solution and solution/suspension plasma spray technology through a US Department of Energy-funded project. Plasma spray is a coating deposition method widely used in many energy applications. Novel derivatives of the conventional powder plasma spray process, known as the solution-precursor and solution/suspension-hybrid plasma spray process, are powerful methods to fabricate thin, dense ceramic coatings with complex compositions necessary for the corrosion protection in DCLL breeders. These processes can be used to produce ultra-fine molten splats and to allow fine adjustment of coating chemistry. Thin, dense ceramic coatings with chosen chemistry for superior chemical stability in molten Pb-Li, low activation properties, and good radiation tolerance, is ideal for corrosion-protection of RAFM steels. A key challenge is to accommodate its CTE mismatch with the RAFM substrate through the selection and incorporation of appropriate bond layers, thus allowing for enhanced coating durability and robustness. Systematic process optimization is being used to define the optimal plasma spray conditions for both the topcoat and bond-layer, and X-ray diffraction and SEM-EDS are applied to successfully validate the chemistry and phase composition of the coatings. The plasma-sprayed double-layer corrosion resistant coatings were also deposited onto simulated RAFM steel substrates, which are being tested separately under thermal cycling, high-temperature moist air oxidation as well as molten Pb-Li capsule corrosion conditions. Results from this testing on coated samples, and comparisons with bare RAFM reference samples will be presented and conclusions will be presented assessing the viability of the new ceramic coatings to be viable corrosion prevention systems for DCLL breeders in commercial nuclear fusion reactors.

Keywords: breeding blanket, corrosion protection, coating, plasma spray

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Authors: Paola Clerici Maestosi

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Positive Energy District (PED) is a rather recent concept whose aim is to contribute to the main objectives of the Energy Union strategy. It is based on an integrated multi-sectoral approach in response to Europe's most complex challenges. PED integrates energy efficiency, renewable energy production, and energy flexibility in an integrated, multi-sectoral approach at the city level. The core idea behind Positive Energy Districts (PEDs) is to establish an urban area that can generate more energy than it consumes. Additionally, it should be flexible enough to adapt to changes in the energy market. This is crucial because a PED's goal is not just to achieve an annual surplus of net energy but also to help reduce the impact on the interconnected centralized energy networks. It achieves this by providing options to increase on-site load matching and self-consumption, employing technologies for short- and long-term energy storage, and offering energy flexibility through smart control. Thus, it seems that PEDs can encompass all types of buildings in the city environment. Given this which is the added value of having green buildings being constitutive part of PEDS? The paper will present a systematic literature review identifying the role of green building in Positive Energy District to provide answer to following questions: (RQ1) the state of the art of PEDs implementation; (RQ2) penetration of green building in Positive Energy District selected case studies. Methodological approach is based on a broad holistic study of bibliographic sources according to Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) further data will be analysed, mapped and text mining through VOSviewer. Main contribution of research is a cognitive framework on Positive Energy District in Europe and a selection of case studies where green building supported the transition to PED. The inclusion of green buildings within Positive Energy Districts (PEDs) adds significant value for several reasons. Firstly, green buildings are designed and constructed with a focus on environmental sustainability, incorporating energy-efficient technologies, materials, and design principles. As integral components of PEDs, these structures contribute directly to the district's overall ability to generate more energy than it consumes. Secondly, green buildings typically incorporate renewable energy sources, such as solar panels or wind turbines, further boosting the district's capacity for energy generation. This aligns with the PED objective of achieving a surplus of net energy. Moreover, green buildings often feature advanced systems for on-site energy management, load-matching, and self-consumption. This enhances the PED's capability to respond to variations in the energy market, making the district more agile and flexible in optimizing energy use. Additionally, the environmental considerations embedded in green buildings align with the broader sustainability goals of PEDs. By reducing the ecological footprint of individual structures, PEDs with green buildings contribute to minimizing the overall impact on centralized energy networks and promote a more sustainable urban environment. In summary, the incorporation of green buildings within PEDs not only aligns with the district's energy objectives but also enhances environmental sustainability, energy efficiency, and the overall resilience of the urban environment.

Keywords: positive energy district, renewables energy production, energy flexibility, energy efficiency

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Authors: Ankit Khurana

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The sufficient heat storage capacity or ability to dissipate heat is the most decisive parameter to have an effective and efficient functioning of Friction-based Brake Disc systems. The primary aim of the research was to analyse the effect of multiple coatings on lightweight disk rotors surface which not only alleviates the mass of vehicle & also, augments heat transfer. This research is projected to aid the automobile fraternity with an enunciated view over the thermal aspects in a braking system. The results of the project indicate that with the advent of modern coating technologies a brake system’s thermal curtailments can be removed and together with forced convection, heat transfer processes can see a drastic improvement leading to increased lifetime of the brake rotor. Other advantages of modifying the surface of a lightweight rotor substrate will be to reduce the overall weight of the vehicle, decrease the risk of thermal brake failure (brake fade and fluid vaporization), longer component life, as well as lower noise and vibration characteristics. A mathematical model was constructed in MATLAB which encompassing the various thermal characteristics of the proposed coatings and substrate materials required to approximate the heat flux values in a free and forced convection environment; resembling to a real-time braking phenomenon which could easily be modelled into a full cum scaled version of the alloy brake rotor part in ABAQUS. The finite element of a brake rotor was modelled in a constrained environment such that the nodal temperature between the contact surfaces of the coatings and substrate (Wrought Aluminum alloy) resemble an amalgamated solid brake rotor element. The initial results obtained were for a Plasma Electrolytic Oxidized (PEO) substrate wherein the Aluminum alloy gets a hard ceramic oxide layer grown on its transitional phase. The rotor was modelled and then evaluated in real-time for a constant ‘g’ braking event (based upon the mathematical heat flux input and convective surroundings), which reflected the necessity to deposit a conducting coat (sacrificial) above the PEO layer in order to inhibit thermal degradation of the barrier coating prematurely. Taguchi study was then used to bring out certain critical factors which may influence the maximum operating temperature of a multi-coated brake disc by simulating brake tests: a) an Alpine descent lasting 50 seconds; b) an Autobahn stop lasting 3.53 seconds; c) a Six–high speed repeated stop in accordance to FMVSS 135 lasting 46.25 seconds. Thermal Barrier coating thickness and Vane heat transfer coefficient were the two most influential factors and owing to their design and manufacturing constraints a final optimized model was obtained which survived the 6-high speed stop test as per the FMVSS -135 specifications. The simulation data highlighted the merits for preferring Wrought Aluminum alloy 7068 over Grey Cast Iron and Aluminum Metal Matrix Composite in coherence with the multiple coating depositions.

Keywords: lightweight brakes, surface modification, simulated braking, PEO, aluminum

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Authors: Alena Nesterenko, Svetlana Petrikova

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Research evaluation is one of the most important elements of self-regulation and development of researchers as it is impartial and independent process of assessment. The method of expert evaluations as a scientific instrument solving complicated non-formalized problems is firstly a scientifically sound way to conduct the assessment which maximum effectiveness of work at every step and secondly the usage of quantitative methods for evaluation, assessment of expert opinion and collective processing of the results. These two features distinguish the method of expert evaluations from long-known expertise widespread in many areas of knowledge. Different typical problems require different types of expert evaluations methods. Several issues which arise with these methods are experts’ selection, management of assessment procedure, proceeding of the results and remuneration for the experts. To address these issues an on-line system was created with the primary purpose of development of a versatile application for many workgroups with matching approaches to scientific work management. Online documentation assessment and statistics system allows: - To realize within one platform independent activities of different workgroups (e.g. expert officers, managers). - To establish different workspaces for corresponding workgroups where custom users database can be created according to particular needs. - To form for each workgroup required output documents. - To configure information gathering for each workgroup (forms of assessment, tests, inventories). - To create and operate personal databases of remote users. - To set up automatic notification through e-mail. The next stage is development of quantitative and qualitative criteria to form a database of experts. The inventory was made so that the experts may not only submit their personal data, place of work and scientific degree but also keywords according to their expertise, academic interests, ORCID, Researcher ID, SPIN-code RSCI, Scopus AuthorID, knowledge of languages, primary scientific publications. For each project, competition assessments are processed in accordance to ordering party demands in forms of apprised inventories, commentaries (50-250 characters) and overall review (1500 characters) in which expert states the absence of conflict of interest. Evaluation is conducted as follows: as applications are added to database expert officer selects experts, generally, two persons per application. Experts are selected according to the keywords; this method proved to be good unlike the OECD classifier. The last stage: the choice of the experts is approved by the supervisor, the e-mails are sent to the experts with invitation to assess the project. An expert supervisor is controlling experts writing reports for all formalities to be in place (time-frame, propriety, correspondence). If the difference in assessment exceeds four points, the third evaluation is appointed. As the expert finishes work on his expert opinion, system shows contract marked ‘new’, managers commence with the contract and the expert gets e-mail that the contract is formed and ready to be signed. All formalities are concluded and the expert gets remuneration for his work. The specificity of interaction of the examination officer with other experts will be presented in the report.

Keywords: expertise, management of research evaluation, method of expert evaluations, research evaluation

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Authors: Eliska Smidova, Petr Kabele

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This paper describes non-linear finite element simulation of laminated veneer lumber (LVL) under tensile and shear loads that induce cracking along fibers. For this purpose, we use 2D homogeneous orthotropic constitutive model of tensile and shear fracture in timber that has been recently developed and implemented into ATENA® finite element software by the authors. The model captures (i) material orthotropy for small deformations in both linear and non-linear range, (ii) elastic behavior until anisotropic failure criterion is fulfilled, (iii) inelastic behavior after failure criterion is satisfied, (iv) different post-failure response for cracks along and across the grain, (v) unloading/reloading behavior. The post-cracking response is treated by fixed smeared crack model where Reinhardt-Hordijk function is used. The model requires in total 14 input parameters that can be obtained from standard tests, off-axis test results and iterative numerical simulation of compact tension (CT) or compact tension-shear (CTS) test. New engineered timber composites, such as laminated veneer lumber (LVL), offer improved structural parameters compared to sawn timber. LVL is manufactured by laminating 3 mm thick wood veneers aligned in one direction using water-resistant adhesives (e.g. polyurethane). Thus, 3 main grain directions, namely longitudinal (L), tangential (T), and radial (R), are observed within the layered LVL product. The core of this work consists in 3 numerical simulations of experiments where Radiata Pine LVL and Yellow Poplar LVL were involved. The first analysis deals with calibration and validation of the proposed model through off-axis tensile test (at a load-grain angle of 0°, 10°, 45°, and 90°) and CTS test (at a load-grain angle of 30°, 60°, and 90°), both of which were conducted for Radiata Pine LVL. The second finite element simulation reproduces load-CMOD curve of compact tension (CT) test of Yellow Poplar with the aim of obtaining cohesive law parameters to be used as an input in the third finite element analysis. That is four point bending test of small-size arch of 780 mm span that is made of Yellow Poplar LVL. The arch is designed with a through crack between two middle layers in the crown. Curved laminated beams are exposed to high radial tensile stress compared to timber strength in radial tension in the crown area. Let us note that in this case the latter parameter stands for tensile strength in perpendicular direction with respect to the grain. Standard tests deliver most of the relevant input data whereas traction-separation law for crack along the grain can be obtained partly by inverse analysis of compact tension (CT) test or compact tension-shear test (CTS). The initial crack was modeled as a narrow gap separating two layers in the middle the arch crown. Calculated load-deflection curve is in good agreement with the experimental ones. Furthermore, crack pattern given by numerical simulation coincides with the most important observed crack paths.

Keywords: compact tension (CT) test, compact tension shear (CTS) test, fixed smeared crack model, four point bending test, laminated arch, laminated veneer lumber LVL, off-axis test, orthotropic elasticity, orthotropic fracture criterion, Radiata Pine LVL, traction-separation law, yellow poplar LVL, 2D constitutive model

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Authors: Waleed Al-Nuaimy, Luke Anastassiou, Manjinder Kainth

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As the process of teaching has evolved with the advent of new technologies over the ages, so has the process of learning. Educators have perpetually found themselves on the lookout for new technology-enhanced methods of teaching in order to increase learning efficiency and decrease ever expanding workloads. Shortly after the invention of the internet, web-based learning started to pick up in the late 1990s and educators quickly found that the process of providing learning material and marking assignments could change thanks to the connectivity offered by the internet. With the creation of early web-based virtual learning environments (VLEs) such as SPIDER and Blackboard, it soon became apparent that VLEs resulted in higher reported computer self-efficacy among students, but at the cost of students being less satisfied with the learning process . It may be argued that the impersonal nature of VLEs, and their limited functionality may have been the leading factors contributing to this reported dissatisfaction. To this day, often faced with the prospects of assigning colossal engineering cohorts their homework and assessments, educators may frequently choose optimally curated assessment formats, such as multiple-choice quizzes and numerical answer input boxes, so that automated grading software embedded in the VLEs can save time and mark student submissions instantaneously. A crucial skill that is meant to be learnt during most science and engineering undergraduate degrees is gaining the confidence in using, solving and deriving mathematical equations. Equations underpin a significant portion of the topics taught in many STEM subjects, and it is in homework assignments and assessments that this understanding is tested. It is not hard to see that this can become challenging if the majority of assignment formats students are engaging with are multiple-choice questions, and educators end up with a reduced perspective of their students’ ability to manipulate equations. Artificial intelligence (AI) has in recent times been shown to be an important consideration for many technologies. In our paper, we explore the use of new AI based software designed to work in conjunction with current VLEs. Using our experience with the software, we discuss its potential to solve a selection of problems ranging from impersonality to the reduction of educator workloads by speeding up the marking process. We examine the software’s potential to increase learning efficiency through its features which claim to allow more customized and higher-quality feedback. We investigate the usability of features allowing students to input equation derivations in a range of different forms, and discuss relevant observations associated with these input methods. Furthermore, we make ethical considerations and discuss potential drawbacks to the software, including the extent to which optical character recognition (OCR) could play a part in the perpetuation of errors and create disagreements between student intent and their submitted assignment answers. It is the intention of the authors that this study will be useful as an example of the implementation of AI in a practical assessment scenario insofar as serving as a springboard for further considerations and studies that utilise AI in the setting and marking of science and engineering assignments.

Keywords: engineering education, assessment, artificial intelligence, optical character recognition (OCR)

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Authors: Lily Ranjbar, Haori Yang

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Online education has been around for several decades, but the importance of online education became evident after the COVID-19 pandemic. Eventhough the online delivery approach works well for knowledge building through delivering content and oversight processes, it has limitations in developing hands-on laboratory skills, especially in the STEM field. During the pandemic, many education institutions faced numerous challenges in delivering lab-based courses, especially in the STEM field. Also, many students worldwide were unable to practice working with lab equipment due to social distancing or the significant cost of highly specialized equipment. The laboratory plays a crucial role in nuclear science and engineering education. It can engage students and improve their learning outcomes. In addition, online education and virtual labs have gained substantial popularity in engineering and science education. Therefore, developing virtual labs is vital for institutions to deliver high-class education to their students, including their online students. The School of Nuclear Science and Engineering (NSE) at Oregon State University, in partnership with SpectralLabs company, has developed an Advanced Virtual Radiation Detection and Measurement Lab (AVR-DML) to offer a fully online Master of Health Physics program. It was essential for us to use a system that could simulate nuclear modules that accurately replicate the underlying physics, the nature of radiation and radiation transport, and the mechanics of the instrumentations used in the real radiation detection lab. It was all accomplished using a Realistic, Adaptive, Interactive Learning System (RAILS). RAILS is a comprehensive software simulation-based learning system for use in training. It is comprised of a web-based learning management system that is located on a central server, as well as a 3D-simulation package that is downloaded locally to user machines. Users will find that the graphics, animations, and sounds in RAILS create a realistic, immersive environment to practice detecting different radiation sources. These features allow students to coexist, interact and engage with a real STEM lab in all its dimensions. It enables them to feel like they are in a real lab environment and to see the same system they would in a lab. Unique interactive interfaces were designed and developed by integrating all the tools and equipment needed to run each lab. These interfaces provide students full functionality for data collection, changing the experimental setup, and live data collection with real-time updates for each experiment. Students can manually do all experimental setups and parameter changes in this lab. Experimental results can then be tracked and analyzed in an oscilloscope, a multi-channel analyzer, or a single-channel analyzer (SCA). The advanced virtual radiation detection and measurement laboratory developed in this study enabled the NSE school to offer a fully online MHP program. This flexibility of course modality helped us to attract more non-traditional students, including international students. It is a valuable educational tool as students can walk around the virtual lab, make mistakes, and learn from them. They have an unlimited amount of time to repeat and engage in experiments. This lab will also help us speed up training in nuclear science and engineering.

Keywords: advanced radiation detection and measurement, virtual laboratory, realistic adaptive interactive learning system (rails), online education in stem fields, student engagement, stem online education, stem laboratory, online engineering education

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Authors: Noury Bakrim

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When dealing with motivation/arbitrariness, forming form (Forma Formans) and morphodynamics are to be grasped as relevant implications of enunciation/enactment, schematization within the specificity of language as sound/meaning articulation. Thus, the fact that a language is a form does not contradict stasis/dynamic enunciation (reflexivity vs double articulation). Moreover, some languages exemplify the role of the forming form, uttering, and schematization (roots in Semitic languages, the Chinese case). Beyond the evolutionary biosemiotic process (form/substance bifurcation, the split between realization/representation), non-isomorphism/asymmetry between linguistic form/norm and linguistic realization (phonetics for instance) opens up a new horizon problematizing the role of Brain – sensorimotor contribution in the continuous forming form. Therefore, we hypothesize biotization as both process/trace co-constructing motivation/forming form. Henceforth, referring to our findings concerning distribution and motivation patterns within Berber written texts (pulse based obstruents and nasal-lateral levels in poetry) and oral storytelling (consonant intensity clustering in quantitative and semantic/prosodic motivation), we understand consonant clustering, motivation and schematization as a complex phenomenon partaking in patterns of oral/written iconic prosody and reflexive metalinguistic representation opening the stable form. We focus our inquiry on both Amazigh and English clusters (/spl/, /spr/) and iconic consonant iteration in [gnunnuy] (to roll/tumble), [smummuy] (to moan sadly or crankily). For instance, the syllabic structures of /splaeʃ/ and /splaet/ imply an anamorphic representation of the state of the world: splash, impact on aquatic surfaces/splat impact on the ground. The pair has stridency and distribution as distinctive features which specify its phonetic realization (and a part of its meaning) /ʃ/ is [+ strident] and /t/ is [+ distributed] on the vocal tract. Schematization is then a process relating both physiology/code as an arthron vocal/bodily, vocal/practical shaping of the motor-articulatory system, leading to syntactic/semantic thematization (agent/patient roles in /spl/, /sm/ and other clusters or the tense uvular /qq/ at the initial position in Berber). Furthermore, the productivity of serial syllable sequencing in Berber points out different expressivity forms. We postulate two Components of motivated formalization: i) the process of memory paradigmatization relating to sequence modeling under sensorimotor/verbal specific categories (production/perception), ii) the process of phonotactic selection - prosodic unconscious/subconscious distribution by virtue of iconicity. Basing on multiple tests including a questionnaire, phonotactic/visual recognition and oral/written reproduction, we aim at patterning/conceptualizing consonant schematization and motivation among EFL and Amazigh (Berber) learners and speakers integrating biolinguistic hypotheses.

Keywords: consonant motivation and prosody, language and order of life, anamorphic representation, represented representation, biotization, sensori-motor and brain representation, form, formalization and schematization

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Authors: Kavitha Madhu, Karthik K. Srinivasan, R. Sivanandan

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Indian traffic can be considered as mixed and heterogeneous due to the presence of various types of vehicles that operate with weak lane discipline. Consequently, vehicles can position themselves anywhere in the traffic stream depending on availability of gaps. The choice of lateral positioning is an important component in representing and characterizing mixed traffic. The field data provides evidence that the trajectory of vehicles in Indian urban roads have significantly varying longitudinal and lateral components. Further, the notion of headway which is widely used for homogeneous traffic simulation is not well defined in conditions lacking lane discipline. From field data it is clear that following is not strict as in homogeneous and lane disciplined conditions and neighbouring vehicles ahead of a given vehicle and those adjacent to it could also influence the subject vehicles choice of position, speed and acceleration. Given these empirical features, the suitability of using headway distributions to characterize mixed traffic in Indian cities is questionable, and needs to be modified appropriately. To address these issues, this paper attempts to analyze the time gap distribution between consecutive vehicles (in a time-sense) crossing a section of roadway. More specifically, to characterize the complex interactions noted above, the influence of composition, manoeuvre types, and lateral placement characteristics on time gap distribution is quantified in this paper. The developed model is used for evaluating various performance measures such as link speed, midblock delay and intersection delay which further helps to characterise the vehicular fuel consumption and emission on urban roads of India. Identifying and analyzing exact interactions between various classes of vehicles in the traffic stream is essential for increasing the accuracy and realism of microscopic traffic flow modelling. In this regard, this study aims to develop and analyze time gap distribution models and quantify it by lead lag pair, manoeuvre type and lateral position characteristics in heterogeneous non-lane based traffic. Once the modelling scheme is developed, this can be used for estimating the vehicle kilometres travelled for the entire traffic system which helps to determine the vehicular fuel consumption and emission. The approach to this objective involves: data collection, statistical modelling and parameter estimation, simulation using calibrated time-gap distribution and its validation, empirical analysis of simulation result and associated traffic flow parameters, and application to analyze illustrative traffic policies. In particular, video graphic methods are used for data extraction from urban mid-block sections in Chennai, where the data comprises of vehicle type, vehicle position (both longitudinal and lateral), speed and time gap. Statistical tests are carried out to compare the simulated data with the actual data and the model performance is evaluated. The effect of integration of above mentioned factors in vehicle generation is studied by comparing the performance measures like density, speed, flow, capacity, area occupancy etc under various traffic conditions and policies. The implications of the quantified distributions and simulation model for estimating the PCU (Passenger Car Units), capacity and level of service of the system are also discussed.

Keywords: lateral movement, mixed traffic condition, simulation modeling, vehicle following models

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Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

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We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: autonomous surveillance, Bayesian reasoning, decision support, interventions, patterns of life, predictive analytics, predictive insights

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Authors: Ricardo Alberto Chiong Zevallos, Eduardo Moraes Rego Reis

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Pancreatic adenocarcinoma (PDAC) patients have a less than 10% 5-year survival rate. PDAC has no defined diagnostic and prognostic biomarkers. Gemcitabine is the first-line drug in PDAC and several other cancers. Long non-coding RNAs (lncRNAs) contribute to the tumorigenesis and are potential biomarkers for PDAC. Although lncRNAs aren’t translated into proteins, they have important functions. LncRNAs can decoy or recruit proteins from the epigenetic machinery, act as microRNA sponges, participate in protein translocation through different cellular compartments, and even promote chemoresistance. The chromatin remodeling enzyme EZH2 is a histone methyltransferase that catalyzes the methylation of histone 3 at lysine 27, silencing local expression. EZH2 is ambivalent, it can also activate gene expression independently of its histone methyltransferase activity. EZH2 is overexpressed in several cancers and interacts with lncRNAs, being recruited to a specific locus. EZH2 can be recruited to activate an oncogene or silence a tumor suppressor. The lncRNAs misregulation in cancer can result in the differential recruitment of EZH2 and in a distinct epigenetic landscape, promoting chemoresistance. The relevance of the EZH2-lncRNAs interaction to chemoresistant PDAC was assessed by Real Time quantitative PCR (RT-qPCR) and RNA Immunoprecipitation (RIP) experiments with naïve and gemcitabine-resistant PDAC cells. The expression of several lncRNAs and EZH2 gene targets was evaluated contrasting naïve and resistant cells. Selection of candidate genes was made by bioinformatic analysis and literature curation. Indeed, the resistant cell line showed higher expression of chemoresistant-associated lncRNAs and protein coding genes. RIP detected lncRNAs interacting with EZH2 with varying intensity levels in the cell lines. During RIP, the nuclear fraction of the cells was incubated with an antibody for EZH2 and with magnetic beads. The RNA precipitated with the beads-antibody-EZH2 complex was isolated and reverse transcribed. The presence of candidate lncRNAs was detected by RT-qPCR, and the enrichment was calculated relative to INPUT (total lysate control sample collected before RIP). The enrichment levels varied across the several lncRNAs and cell lines. The EZH2-lncRNA interaction might be responsible for the regulation of chemoresistance-associated genes in multiple cancers. The relevance of the lncRNA-EZH2 interaction to PDAC was assessed by siRNA knockdown of a lncRNA, followed by the analysis of the EZH2 target expression by RT-qPCR. The chromatin immunoprecipitation (ChIP) of EZH2 and H3K27me3 followed by RT-qPCR with primers for EZH2 targets also assess the specificity of the EZH2 recruitment by the lncRNA. This is the first report of the interaction of EZH2 and lncRNAs HOTTIP and PVT1 in chemoresistant PDAC. HOTTIP and PVT1 were described as promoting chemoresistance in several cancers, but the role of EZH2 is not clarified. For the first time, the lncRNA LINC01133 was detected in a chemoresistant cancer. The interaction of EZH2 with LINC02577, LINC00920, LINC00941, and LINC01559 have never been reported in any context. The novel lncRNAs-EZH2 interactions regulate chemoresistant-associated genes in PDAC and might be relevant to other cancers. Therapies targeting EZH2 alone weren’t successful, and a combinatorial approach also targeting the lncRNAs interacting with it might be key to overcome chemoresistance in several cancers.

Keywords: epigenetics, chemoresistance, long non-coding RNAs, pancreatic cancer, histone modification

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Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

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Authors: Stephanie J. Sedberry, William J. Gerace, Ian D. Beatty, Michael J. Kane

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Increasing the number of US university students who attain degrees in STEM and enter the STEM workforce is a national priority. Demographic groups vary in their rates of participation in STEM, and the US produces just 10% of the world’s science and engineering degrees (2014 figures). To address these gaps, we have developed and tested a practical, 30-minute, single-session classroom-based intervention to improve students’ self-efficacy and academic performance in University STEM courses. Self-efficacy is a psychosocial construct that strongly correlates with academic success. Self-efficacy is a construct that is internal and relates to the social, emotional, and psychological aspects of student motivation and performance. A compelling body of research demonstrates that university students’ self-efficacy beliefs are strongly related to their selection of STEM as a major, aspirations for STEM-related careers, and persistence in science. The development of an intervention to increase students’ self-efficacy is motivated by research showing that short, social-psychological interventions in education can lead to large gains in student achievement. Our intervention addresses STEM self-efficacy via two strong, but previously separate, lines of research into attitudinal/affect variables that influence student success. The first is ‘attributional retraining,’ in which students learn to attribute their successes and failures to internal rather than external factors. The second is ‘mindset’ about fixed vs. growable intelligence, in which students learn that the brain remains plastic throughout life and that they can, with conscious effort and attention to thinking skills and strategies, become smarter. Extant interventions for both of these constructs have significantly increased academic performance in the classroom. We developed a 34-item questionnaire (Likert scale) to measure STEM Self-efficacy, Perceived Academic Control, and Growth Mindset in a University STEM context, and validated it with exploratory factor analysis, Rasch analysis, and multi-trait multi-method comparison to coded interviews. Four iterations of our 42-week research protocol were conducted across two academic years (2017-2018) at three different Universities in North Carolina, USA (UNC-G, NC A&T SU, and NCSU) with varied student demographics. We utilized a quasi-experimental prospective multiple-group time series research design with both experimental and control groups, and we are employing linear modeling to estimate the impact of the intervention on Self-Efficacy,wth-Mindset, Perceived Academic Control, and final course grades (performance measure). Preliminary results indicate statistically significant effects of treatment vs. control on Self-Efficacy, Growth-Mindset, Perceived Academic Control. Analyses are ongoing and final results pending. This intervention may have the potential to increase student success in the STEM classroom—and ownership of that success—to continue in a STEM career. Additionally, we have learned a great deal about the complex components and dynamics of self-efficacy, their link to performance, and the ways they can be impacted to improve students’ academic performance.

Keywords: academic performance, affect variables, growth mindset, intervention, perceived academic control, psycho-social variables, self-efficacy, STEM, university classrooms

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Authors: Yagmur Soylu, Emir Ozeren, Erol Esen, Digdem M. Siyez, Ozlem Belkis, Ezgi Burc, Gülce Demirgurz

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The aim of the study is to determine the predictive power of personal growth initiative, socio-demographic variables (such as sex, grade, and working condition) on career adaptability and optimism of bachelor students in Dokuz Eylul University in Turkey. According to career construction theory, career adaptability is viewed as a psychosocial construct, which refers to an individual’s resources for dealing with current and expected tasks, transitions and traumas in their occupational roles. Career optimism is defined as positive results for future career development of individuals in the expectation that it will achieve or to put the emphasis on the positive aspects of the event and feel comfortable about the career planning process. Personal Growth Initiative (PGI) is defined as being proactive about one’s personal development. Additionally, personal growth is defined as the active and intentional engagement in the process of personal. A study conducted on college students revealed that individuals with high self-development orientation make more effort to discover the requirements of the profession and workspaces than individuals with low levels of personal development orientation. University life is a period that social relations and the importance of academic activities are increased, the students make efforts to progress through their career paths and it is also an environment that offers opportunities to students for their self-realization. For these reasons, personal growth initiative is potentially an important variable which has a key role for an individual during the transition phase from university to the working life. Based on the review of the literature, it is expected that individual’s personal growth initiative, sex, grade, and working condition would significantly predict one’s career adaptability. In the relevant literature, it can be seen that there are relatively few studies available on the career adaptability and optimism of university students. Most of the existing studies have been carried out with limited respondents. In this study, the authors aim to conduct a comprehensive research with a large representative sample of bachelor students in Dokuz Eylul University, Izmir, Turkey. By now, personal growth initiative and career development constructs have been predominantly discussed in western contexts where individualistic tendencies are likely to be seen. Thus, the examination of the same relationship within the context of Turkey where collectivistic cultural characteristics can be more observed is expected to offer valuable insights and provide an important contribution to the literature. The participants in this study were comprised of 1500 undergraduate students being included from thirteen faculties in Dokuz Eylul University. Stratified and random sampling methods were adopted for the selection of the participants. The Personal Growth Initiative Scale-II and Career Futures Inventory were used as the major measurement tools. In data analysis stage, several statistical analysis concerning the regression analysis, one-way ANOVA and t-test will be conducted to reveal the relationships of the constructs under investigation. At the end of this project, we will be able to determine the level of career adaptability and optimism of university students at varying degrees so that a fertile ground is likely to be created to carry out several intervention techniques to make a contribution to an emergence of a healthier and more productive youth generation in psycho-social sense.

Keywords: career optimism, career adaptability, personal growth initiative, university students

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Authors: Bensaid A., Mostephaoui T., Nedjai R.

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Nowadays, wetlands are the subject of contradictory debates opposing scientific, political and administrative meanings. Indeed, given their multiple services (drinking water, irrigation, hydrological regulation, mineral, plant and animal resources...), wetlands concentrate many socio-economic and biodiversity issues. In some regions, they can cover vast areas (>100 thousand ha) of the landscape, such as the Camargue area in the south of France, inside the Rhone delta. The high biological productivity of wetlands, the strong natural selection pressures and the diversity of aquatic environments have produced many species of plants and animals that are found nowhere else. These environments are tremendous carbon sinks and biodiversity reserves depending on their age, composition and surrounding environmental conditions, wetlands play an important role in global climate projections. Covering more than 3% of the earth's surface, wetlands have experienced since the beginning of the 1990s a tremendous revival of interest, which has resulted in the multiplication of inventories, scientific studies and management experiments. The geographical and physical characteristics of the wetlands of the central region conceal a large number of natural habitats that harbour a great biological diversity. These wetlands, one of the natural habitats, are still influenced by human activities, especially agriculture, which affects its layout and functioning. In this perspective, decision-makers need to delimit spatial objects (natural habitats) in a certain way to be able to take action. Thus, wetlands are no exception to this rule even if it seems to be a difficult exercise to delimit a type of environment as whose main characteristic is often to occupy the transition between aquatic and terrestrial environment. However, it is possible to map wetlands with databases, derived from the interpretation of photos and satellite images, such as the European database Corine Land cover, which allows quantifying and characterizing for each place the characteristic wetland types. Scientific studies have shown limitations when using high spatial resolution images (SPOT, Landsat, ASTER) for the identification and characterization of small wetlands (1 hectare). To address this limitation, it is important to note that these wetlands generally represent spatially complex features. Indeed, the use of very high spatial resolution images (>3m) is necessary to map small and large areas. However, with the recent evolution of artificial intelligence (AI) and deep learning methods for satellite image processing have shown a much better performance compared to traditional processing based only on pixel structures. Our research work is also based on spectral and textural analysis on THR images (Spot and IRC orthoimage) using two object-oriented approaches, the nearest neighbour approach (k-NN) and the Super Vector Machine approach (SVM). The k-NN approach gave good results for the delineation of wetlands (wet marshes and moors, ponds, artificial wetlands water body edges, ponds, mountain wetlands, river edges and brackish marshes) with a kappa index higher than 85%.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

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Authors: Islam Sherif, Ahmed Ashour, Ahmed Hassan, Hatem Osman

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Anterior Cruciate Ligament (ACL) injuries are common among athletes and individuals participating in sports with sudden stops, pivots, and changes in direction. Arthroscopic surgery is the gold standard for ACL reconstruction, aiming to restore knee stability and function. Recent years have witnessed significant advancements in arthroscopic surgery techniques, graft materials, and technological innovations, revolutionizing the field of ACL reconstruction. This presentation delves into the latest advancements in arthroscopic surgery techniques for ACL reconstruction and their potential impact on patient outcomes. Traditionally, autografts from the patellar tendon, hamstring tendon, or quadriceps tendon have been commonly used for ACL reconstruction. However, recent studies have explored the use of allografts, synthetic scaffolds, and tissue-engineered grafts as viable alternatives. This abstract evaluates the benefits and potential drawbacks of each graft type, considering factors such as graft incorporation, strength, and risk of graft failure. Moreover, the application of augmented reality (AR) and virtual reality (VR) technologies in surgical planning and intraoperative navigation has gained traction. AR and VR platforms provide surgeons with detailed 3D anatomical reconstructions of the knee joint, enhancing preoperative visualization and aiding in graft tunnel placement during surgery. We discuss the integration of AR and VR in arthroscopic ACL reconstruction procedures, evaluating their accuracy, cost-effectiveness, and overall impact on surgical outcomes. Beyond graft selection and surgical navigation, patient-specific planning has gained attention in recent research. Advanced imaging techniques, such as MRI-based personalized planning, enable surgeons to tailor ACL reconstruction procedures to each patient's unique anatomy. By accounting for individual variations in the femoral and tibial insertion sites, this personalized approach aims to optimize graft placement and potentially improve postoperative knee kinematics and stability. Furthermore, rehabilitation and postoperative care play a crucial role in the success of ACL reconstruction. This abstract explores novel rehabilitation protocols, emphasizing early mobilization, neuromuscular training, and accelerated recovery strategies. Integrating technology, such as wearable sensors and mobile applications, into postoperative care can facilitate remote monitoring and timely intervention, contributing to enhanced rehabilitation outcomes. In conclusion, this presentation provides an overview of the cutting-edge advancements in arthroscopic surgery techniques for ACL reconstruction. By embracing innovative graft materials, augmented reality, patient-specific planning, and technology-driven rehabilitation, orthopedic surgeons and sports medicine specialists can achieve superior outcomes in ACL injury management. These developments hold great promise for improving the functional outcomes and long-term success rates of ACL reconstruction, benefitting athletes and patients alike.

Keywords: arthroscopic surgery, ACL, autograft, allograft, graft materials, ACL reconstruction, synthetic scaffolds, tissue-engineered graft, virtual reality, augmented reality, surgical planning, intra-operative navigation

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Authors: Mukul Sharma, Madhusmita Das, Sundeep Chaitanya Vedithi

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Leprosy is a chronic human disease caused by Mycobacterium leprae, that cannot be cultured in vitro. Though treatable with multidrug therapy (MDT), recently, bacteria reported resistance to multiple antibiotics. Targeting DNA replication and repair pathways can serve as the foundation of developing new anti-leprosy drugs. Due to the absence of an axenic culture medium for the propagation of M. leprae, studying cellular processes, especially those belonging to DNA repair pathways, is challenging. Genomic understanding of M. Leprae harbors several protein-coding genes with no previously assigned function known as 'hypothetical proteins'. Here, we report identification and expression of known and hypothetical DNA repair genes from a human skin biopsy and mouse footpads that are involved in base excision repair, direct reversal repair, and SOS response. Initially, a bioinformatics approach was employed based on sequence similarity, identification of known protein domains to screen the hypothetical proteins in the genome of M. leprae, that are potentially related to DNA repair mechanisms. Before testing on clinical samples, pure stocks of bacterial reference DNA of M. leprae (NHDP63 strain) was used to construct standard graphs to validate and identify lower detection limit in the qPCR experiments. Primers were designed to amplify the respective transcripts, and PCR products of the predicted size were obtained. Later, excisional skin biopsies of newly diagnosed untreated, treated, and drug resistance leprosy cases from SIHR & LC hospital, Vellore, India were taken for the extraction of RNA. To determine the presence of the predicted transcripts, cDNA was generated from M. leprae mRNA isolated from clinically confirmed leprosy skin biopsy specimen across all the study groups. Melting curve analysis was performed to determine the integrity of the amplification and to rule out primer‑dimer formation. The Ct values obtained from qPCR were fitted to standard curve to determine transcript copy number. Same procedure was applied for M. leprae extracted after processing a footpad of nude mice of drug sensitive and drug resistant strains. 16S rRNA was used as positive control. Of all the 16 genes involved in BER, DR, and SOS, differential expression pattern of the genes was observed in terms of Ct values when compared to human samples; this was because of the different host and its immune response. However, no drastic variation in gene expression levels was observed in human samples except the nth gene. The higher expression of nth gene could be because of the mutations that may be associated with sequence diversity and drug resistance which suggests an important role in the repair mechanism and remains to be explored. In both human and mouse samples, SOS system – lexA and RecA, and BER genes AlkB and Ogt were expressing efficiently to deal with possible DNA damage. Together, the results of the present study suggest that DNA repair genes are constitutively expressed and may provide a reference for molecular diagnosis, therapeutic target selection, determination of treatment and prognostic judgment in M. leprae pathogenesis.

Keywords: DNA repair, human biopsy, hypothetical proteins, mouse footpads, Mycobacterium leprae, qPCR

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Authors: Berna Çalışkan

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The integrated water management is a colloborative approach to planning that brings together institutions that influence all elements of the water cycle, waterways, watershed characteristics, wetlands, ponds, lakes, floodplain areas, stream channel structure. It encourages collaboration where it will be beneficial and links between water planning and other planning processes that contribute to improving sustainable urban development and liveability. Hydraulic considerations can influence the selection of a highway corridor and the alternate routes within the corridor. widening a roadway, replacing a culvert, or repairing a bridge. Because of this, the type and amount of data needed for planning studies can vary widely depending on such elements as environmental considerations, class of the proposed highway, state of land use development, and individual site conditions. The extraction of drainage networks provide helpful preliminary drainage data from the digital elevation model (DEM). A case study was carried out using the Arc Hydro extension within ArcGIS in the study area. It provides the means for processing and presenting spatially-referenced Stream Model. Study area’s flow routing, stream levels, segmentation, drainage point processing can be obtained using DEM as the 'Input surface raster'. These processes integrate the fields of hydrologic, engineering research, and environmental modeling in a multi-disciplinary program designed to provide decision makers with a science-based understanding, and innovative tools for, the development of interdisciplinary and multi-level approach. This research helps to manage transport project planning and construction phases to analyze the surficial water flow, high-level streams, wetland sites for development of transportation infrastructure planning, implementing, maintenance, monitoring and long-term evaluations to better face the challenges and solutions associated with effective management and enhancement to deal with Low, Medium, High levels of impact. Transport projects are frequently perceived as critical to the ‘success’ of major urban, metropolitan, regional and/or national development because of their potential to affect significant socio-economic and territorial change. In this context, sustaining and development of economic and social activities depend on having sufficient Water Resources Management. The results of our research provides a workflow to build a stream network how can classify suitability map according to stream levels. Transportation projects establish, develop, incorporate and deliver effectively by selecting best location for reducing construction maintenance costs, cost-effective solutions for drainage, landslide, flood control. According to model findings, field study should be done for filling gaps and checking for errors. In future researches, this study can be extended for determining and preventing possible damage of Sensitive Areas and Vulnerable Zones supported with field investigations.

Keywords: water resources management, hydro tool, water protection, transportation

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Authors: L. R. Valencia Pérez, J. M. Peña Aguilar, A. Lamadrid Álvarez, A. Pastrana Palma, H. F. Valencia Pérez, M. Vivanco Vargas

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This work proposes a Cooperation-Competitive (Coopetitive) approach that allows coordinated work among the Secretary of Public Education (SEP), the Autonomous University of Querétaro (UAQ) and government funds from National Council for Science and Technology (CONACYT) or some other international organizations. To work on an overall knowledge transfer strategy with e-learning over the Cloud, where experts in junior high and high school education, working in multidisciplinary teams, perform analysis, evaluation, design, production, validation and knowledge transfer at large scale using a Cloud Computing platform. Allowing teachers and students to have all the information required to ensure a homologated nationally knowledge of topics such as mathematics, statistics, chemistry, history, ethics, civism, etc. This work will start with a pilot test in Spanish and initially in two regional dialects Otomí and Náhuatl. Otomí has more than 285,000 speaking indigenes in Queretaro and Mexico´s central region. Náhuatl is number one indigenous dialect spoken in Mexico with more than 1,550,000 indigenes. The phase one of the project takes into account negotiations with indigenous tribes from different regions, and the Information and Communication technologies to deliver the knowledge to the indigenous schools in their native dialect. The methodology includes the following main milestones: Identification of the indigenous areas where Otomí and Náhuatl are the spoken dialects, research with the SEP the location of actual indigenous schools, analysis and inventory or current schools conditions, negotiation with tribe chiefs, analysis of the technological communication requirements to reach the indigenous communities, identification and inventory of local teachers technology knowledge, selection of a pilot topic, analysis of actual student competence with traditional education system, identification of local translators, design of the e-learning platform, design of the multimedia resources and storage strategy for “Cloud Computing”, translation of the topic to both dialects, Indigenous teachers training, pilot test, course release, project follow up, analysis of student requirements for the new technological platform, definition of a new and improved proposal with greater reach in topics and regions. Importance of phase one of the project is multiple, it includes the proposal of a working technological scheme, focusing in the cultural impact in Mexico so that indigenous tribes can improve their knowledge about new forms of crop improvement, home storage technologies, proven home remedies for common diseases, ways of preparing foods containing major nutrients, disclose strengths and weaknesses of each region, communicating through cloud computing platforms offering regional products and opening communication spaces for inter-indigenous cultural exchange.

Keywords: Mexicans indigenous tribes, education, knowledge transfer, cloud computing, otomi, Náhuatl, language

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Authors: Rachana Tank, Donald. M. Lyall, Kristin Flegal, Joey Ward, Jonathan Cavanagh

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Alzheimer’s research UK estimates by 2050, 2 million individuals will be living with Late Onset Alzheimer’s disease (LOAD). However, individuals experience considerable cognitive deficits and brain pathology over decades before reaching clinically diagnosable LOAD and studies have utilised gene candidate studies such as genome wide association studies (GWAS) and polygenic risk (PGR) scores to identify high risk individuals and potential pathways. This investigation aims to determine whether high genetic risk of LOAD is associated with worse brain MRI and cognitive performance in healthy older adults within the UK Biobank cohort. Previous studies investigating associations of PGR for LOAD and measures of MRI or cognitive functioning have focused on specific aspects of hippocampal structure, in relatively small sample sizes and with poor ‘controlling’ for confounders such as smoking. Both the sample size of this study and the discovery GWAS sample are bigger than previous studies to our knowledge. Genetic interaction between loci showing largest effects in GWAS have not been extensively studied and it is known that APOE e4 poses the largest genetic risk of LOAD with potential gene-gene and gene-environment interactions of e4, for this reason we  also analyse genetic interactions of PGR with the APOE e4 genotype. High genetic loading based on a polygenic risk score of 21 SNPs for LOAD is associated with worse brain MRI and cognitive outcomes in healthy individuals within the UK Biobank cohort. Summary statistics from Kunkle et al., GWAS meta-analyses (case: n=30,344, control: n=52,427) will be used to create polygenic risk scores based on 21 SNPs and analyses will be carried out in N=37,000 participants in the UK Biobank. This will be the largest study to date investigating PGR of LOAD in relation to MRI. MRI outcome measures include WM tracts, structural volumes. Cognitive function measures include reaction time, pairs matching, trail making, digit symbol substitution and prospective memory. Interaction of the APOE e4 alleles and PGR will be analysed by including APOE status as an interaction term coded as either 0, 1 or 2 e4 alleles. Models will be adjusted partially for adjusted for age, BMI, sex, genotyping chip, smoking, depression and social deprivation. Preliminary results suggest PGR score for LOAD is associated with decreased hippocampal volumes including hippocampal body (standardised beta = -0.04, P = 0.022) and tail (standardised beta = -0.037, P = 0.030), but not with hippocampal head. There were also associations of genetic risk with decreased cognitive performance including fluid intelligence (standardised beta = -0.08, P<0.01) and reaction time (standardised beta = 2.04, P<0.01). No genetic interactions were found between APOE e4 dose and PGR score for MRI or cognitive measures. The generalisability of these results is limited by selection bias within the UK Biobank as participants are less likely to be obese, smoke, be socioeconomically deprived and have fewer self-reported health conditions when compared to the general population. Lack of a unified approach or standardised method for calculating genetic risk scores may also be a limitation of these analyses. Further discussion and results are pending.

Keywords: Alzheimer's dementia, cognition, polygenic risk, MRI

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Authors: Parag Katira, Frederika Rentzeperis, Zuzanna Nowicka, Giada Fiandaca, Thomas Veith, Jack Farinhas, Noemi Andor

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Resource limitations shape the outcome of competitions between genetically heterogeneous pre-malignant cells. One example of such heterogeneity is in the ploidy (DNA content) of pre-malignant cells. A whole-genome duplication (WGD) transforms a diploid cell into a tetraploid one and has been detected in 28-56% of human cancers. If a tetraploid subclone expands, it consistently does so early in tumor evolution, when cell density is still low, and competition for nutrients is comparatively weak – an observation confirmed for several tumor types. WGD+ cells need more resources to synthesize increasing amounts of DNA, RNA, and proteins. To quantify resource limitations and how they relate to ploidy, we performed a PAN cancer analysis of WGD, PET/CT, and MRI scans. Segmentation of >20 different organs from >900 PET/CT scans were performed with MOOSE. We observed a strong correlation between organ-wide population-average estimates of Oxygen and the average ploidy of cancers growing in the respective organ (Pearson R = 0.66; P= 0.001). In-vitro experiments using near-diploid and near-tetraploid lineages derived from a breast cancer cell line supported the hypothesis that DNA content influences Glucose- and Oxygen-dependent proliferation-, death- and migration rates. To model how subpopulations with variable DNA content compete in the resource-limited environment of the human brain, we developed a stochastic state-space model of the brain (S3MB). The model discretizes the brain into voxels, whereby the state of each voxel is defined by 8+ variables that are updated over time: stiffness, Oxygen, phosphate, glucose, vasculature, dead cells, migrating cells and proliferating cells of various DNA content, and treat conditions such as radiotherapy and chemotherapy. Well-established Fokker-Planck partial differential equations govern the distribution of resources and cells across voxels. We applied S3MB on sequencing and imaging data obtained from a primary GBM patient. We performed whole genome sequencing (WGS) of four surgical specimens collected during the 1ˢᵗ and 2ⁿᵈ surgeries of the GBM and used HATCHET to quantify its clonal composition and how it changes between the two surgeries. HATCHET identified two aneuploid subpopulations of ploidy 1.98 and 2.29, respectively. The low-ploidy clone was dominant at the time of the first surgery and became even more dominant upon recurrence. MRI images were available before and after each surgery and registered to MNI space. The S3MB domain was initiated from 4mm³ voxels of the MNI space. T1 post and T2 flair scan acquired after the 1ˢᵗ surgery informed tumor cell densities per voxel. Magnetic Resonance Elastography scans and PET/CT scans informed stiffness and Glucose access per voxel. We performed a parameter search to recapitulate the GBM’s tumor cell density and ploidy composition before the 2ⁿᵈ surgery. Results suggest that the high-ploidy subpopulation had a higher Glucose-dependent proliferation rate (0.70 vs. 0.49), but a lower Glucose-dependent death rate (0.47 vs. 1.42). These differences resulted in spatial differences in the distribution of the two subpopulations. Our results contribute to a better understanding of how genomics and microenvironments interact to shape cell fate decisions and could help pave the way to therapeutic strategies that mimic prognostically favorable environments.

Keywords: tumor evolution, intra-tumor heterogeneity, whole-genome doubling, mathematical modeling

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Authors: Marina Nechayeva, Malgorzata Marciniak, Vladimir Przhebelskiy, A. Dragutan, S. Lamichhane, S. Oikawa

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This presentation is a progress report on a faculty-student research collaboration at CUNY LaGuardia Community College (LaGCC) aimed at designing a small horizontal axis wind turbine optimized for the wind patterns on the roof of our campus. Our project combines statistical and engineering research. Our wind modeling protocol is based upon a recent wind study by a faculty-student research group at MIT, and some of our blade design methods are adopted from a senior engineering project at CUNY City College. Our use of genetic algorithms has been inspired by the work on small wind turbines’ design by David Wood. We combine these diverse approaches in our interdisciplinary project in a way that has not been done before and improve upon certain techniques used by our predecessors. We employ several estimation methods to determine the best fitting parametric probability distribution model for the local wind speed data obtained through correlating short-term on-site measurements with a long-term time series at the nearby airport. The model serves as a foundation for engineering research that focuses on adapting and implementing genetic algorithms (GAs) to engineering optimization of the wind turbine design using Blade Element Momentum Theory. GAs are used to create new airfoils with desirable aerodynamic specifications. Small scale models of best performing designs are 3D printed and tested in the wind tunnel to verify the accuracy of relevant calculations. Genetic algorithms are applied to selected airfoils to determine the blade design (radial cord and pitch distribution) that would optimize the coefficient of power profile of the turbine. Our approach improves upon the traditional blade design methods in that it lets us dispense with assumptions necessary to simplify the system of Blade Element Momentum Theory equations, thus resulting in more accurate aerodynamic performance calculations. Furthermore, it enables us to design blades optimized for a whole range of wind speeds rather than a single value. Lastly, we improve upon known GA-based methods in that our algorithms are constructed to work with XFoil generated airfoils data which enables us to optimize blades using our own high glide ratio airfoil designs, without having to rely upon available empirical data from existing airfoils, such as NACA series. Beyond its immediate goal, this ongoing project serves as a training and selection platform for CUNY Research Scholars Program (CRSP) through its annual Aerodynamics and Wind Energy Research Seminar (AWERS), an undergraduate summer research boot camp, designed to introduce prospective researchers to the relevant theoretical background and methodology, get them up to speed with the current state of our research, and test their abilities and commitment to the program. Furthermore, several aspects of the research (e.g., writing code for 3D printing of airfoils) are adapted in the form of classroom research activities to enhance Calculus sequence instruction at LaGCC.

Keywords: engineering design optimization, genetic algorithms, horizontal axis wind turbine, wind modeling

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Authors: Kashima Arora, Monika Tomar, Vinay Gupta

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Biosensors have found potential applications ranging from environmental testing and biowarfare agent detection to clinical testing, health care, and cell analysis. This is driven in part by the desire to decrease the cost of health care and to obtain precise information more quickly about the health status of patient by the development of various biosensors, which has become increasingly prevalent in clinical testing and point of care testing for a wide range of biological elements. Uric acid is an important byproduct in human body and a number of pathological disorders are related to its high concentration in human body. In past few years, rapid growth in the development of new materials and improvements in sensing techniques have led to the evolution of advanced biosensors. In this context, metal oxide thin film based matrices due to their bio compatible nature, strong adsorption ability, high isoelectric point (IEP) and abundance in nature have become the materials of choice for recent technological advances in biotechnology. In the past few years, wide band-gap metal oxide semiconductors including ZnO, SnO₂ and CeO₂ have gained much attention as a matrix for immobilization of various biomolecules. Tin oxide (SnO₂), wide band gap semiconductor (Eg =3.87 eV), despite having multifunctional properties for broad range of applications including transparent electronics, gas sensors, acoustic devices, UV photodetectors, etc., it has not been explored much for biosensing purpose. To realize a high performance miniaturized biomolecular electronic device, rf sputtering technique is considered to be the most promising for the reproducible growth of good quality thin films, controlled surface morphology and desired film crystallization with improved electron transfer property. Recently, iron oxide and its composites have been widely used as matrix for biosensing application which exploits the electron communication feature of Fe, for the detection of various analytes using urea, hemoglobin, glucose, phenol, L-lactate, H₂O₂, etc. However, to the authors’ knowledge, no work is being reported on modifying the electronic properties of SnO₂ by implanting with suitable metal (Fe) to induce the redox couple in it and utilizing it for reagentless detection of uric acid. In present study, Fe implanted SnO₂ based matrix has been utilized for reagentless uric acid biosensor. Implantation of Fe into SnO₂ matrix is confirmed by energy-dispersive X-Ray spectroscopy (EDX) analysis. Electrochemical techniques have been used to study the response characteristics of Fe modified SnO₂ matrix before and after uricase immobilization. The developed uric acid biosensor exhibits a high sensitivity to about 0.21 mA/mM and a linear variation in current response over concentration range from 0.05 to 1.0 mM of uric acid besides high shelf life (~20 weeks). The Michaelis-Menten kinetic parameter (Km) is found to be relatively very low (0.23 mM), which indicates high affinity of the fabricated bioelectrode towards uric acid (analyte). Also, the presence of other interferents present in human serum has negligible effect on the performance of biosensor. Hence, obtained results highlight the importance of implanted Fe:SnO₂ thin film as an attractive matrix for realization of reagentless biosensors towards uric acid.

Keywords: Fe implanted tin oxide, reagentless uric acid biosensor, rf sputtering, thin film

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Authors: Nikhilesh Singh, Shishir Gaur, Anitha K. Sharma

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Climate change and anthropogenic stress have severely affected ecosystems all over the globe. Indian rivers are under immense pressure, facing challenges like pollution, encroachment, extreme fluctuation in the flow regime, local ignorance and lack of coordination between stakeholders. To counter all these issues a holistic river rejuvenation plan is needed that tests, innovates and implements sustainable solutions in the river space for sustainable river management. Smart Laboratory for Clean Rivers (SLCR) an Indo-Danish collaboration project, provides a living lab setup that brings all the stakeholders (government agencies, academic and industrial partners and locals) together to engage, learn, co-creating and experiment for a clean and sustainable river that last for ages. Just like every mega project requires piloting, SLCR has opted for a small catchment of the Varuna River, located in the Middle Ganga Basin in India. Considering the integrated approach of river rejuvenation, SLCR embraces various techniques and upgrades for rejuvenation. Likely, maintaining flow in the channel in the lean period, Managed Aquifer Recharge (MAR) is a proven technology. In SLCR, Floa-TEM high-resolution lithological data is used in MAR models to have better decision-making for MAR structures nearby of the river to enhance the river aquifer exchanges. Furthermore, the concerns of quality in the river are a big issue. A city like Varanasi which is located in the last stretch of the river, generates almost 260 MLD of domestic waste in the catchment. The existing STP system is working at full efficiency. Instead of installing a new STP for the future, SLCR is upgrading those STPs with an IoT-based system that optimizes according to the nutrient load and energy consumption. SLCR also advocate nature-based solutions like a reed bed for the drains having less flow. In search of micropollutants, SLCR uses fingerprint analysis involves employing advanced techniques like chromatography and mass spectrometry to create unique chemical profiles. However, rejuvenation attempts cannot be possible without involving the entire catchment. A holistic water management plan that includes storm management, water harvesting structure to efficiently manage the flow of water in the catchment and installation of several buffer zones to restrict pollutants entering into the river. Similarly, carbon (emission and sequestration) is also an important parameter for the catchment. By adopting eco-friendly practices, a ripple effect positively influences the catchment's water dynamics and aids in the revival of river systems. SLCR has adopted 4 villages to make them carbon-neutral and water-positive. Moreover, for the 24×7 monitoring of the river and the catchment, robust IoT devices are going to be installed to observe, river and groundwater quality, groundwater level, river discharge and carbon emission in the catchment and ultimately provide fuel for the data analytics. In its completion, SLCR will provide a river restoration manual, which will strategise the detailed plan and way of implementation for stakeholders. Lastly, the entire process is planned in such a way that will be managed by local administrations and stakeholders equipped with capacity-building activity. This holistic approach makes SLCR unique in the field of river rejuvenation.

Keywords: sustainable management, holistic approach, living lab, integrated river management

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Authors: Marielle Leijten, Catherine Meulemans, Sven De Maeyer, Luuk Van Waes

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For the diagnosis of Alzheimer's disease (AD), a large variety of neuropsychological tests are available. In some of these tests, linguistic processing - both oral and written - is an important factor. Language disturbances might serve as a strong indicator for an underlying neurodegenerative disorder like AD. However, the current diagnostic instruments for language assessment mainly focus on product measures, such as text length or number of errors, ignoring the importance of the process that leads to written or spoken language production. In this study, it is our aim to describe and test differences between cognitive and impaired elderly on the basis of a selection of writing process variables (inter- and intrapersonal characteristics). These process variables are mainly related to pause times, because the number, length, and location of pauses have proven to be an important indicator of the cognitive complexity of a process. Method: Participants that were enrolled in our research were chosen on the basis of a number of basic criteria necessary to collect reliable writing process data. Furthermore, we opted to match the thirteen cognitively impaired patients (8 MCI and 5 AD) with thirteen cognitively healthy elderly. At the start of the experiment, participants were each given a number of tests, such as the Mini-Mental State Examination test (MMSE), the Geriatric Depression Scale (GDS), the forward and backward digit span and the Edinburgh Handedness Inventory (EHI). Also, a questionnaire was used to collect socio-demographic information (age, gender, eduction) of the subjects as well as more details on their level of computer literacy. The tests and questionnaire were followed by two typing tasks and two picture description tasks. For the typing tasks participants had to copy (type) characters, words and sentences from a screen, whereas the picture description tasks each consisted of an image they had to describe in a few sentences. Both the typing and the picture description tasks were logged with Inputlog, a keystroke logging tool that allows us to log and time stamp keystroke activity to reconstruct and describe text production processes. The main rationale behind keystroke logging is that writing fluency and flow reveal traces of the underlying cognitive processes. This explains the analytical focus on pause (length, number, distribution, location, etc.) and revision (number, type, operation, embeddedness, location, etc.) characteristics. As in speech, pause times are seen as indexical of cognitive effort. Results. Preliminary analysis already showed some promising results concerning pause times before, within and after words. For all variables, mixed effects models were used that included participants as a random effect and MMSE scores, GDS scores and word categories (such as determiners and nouns) as a fixed effect. For pause times before and after words cognitively impaired patients paused longer than healthy elderly. These variables did not show an interaction effect between the group participants (cognitively impaired or healthy elderly) belonged to and word categories. However, pause times within words did show an interaction effect, which indicates pause times within certain word categories differ significantly between patients and healthy elderly.

Keywords: Alzheimer's disease, keystroke logging, matching, writing process

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Authors: Fiona Whittington-Walsh

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Including All Citizens Pathway (IACP) is addressing the systems wide discrimination that students with disabilities experience throughout the education system. IACP offers a wide, institutional support structure so that all students, including students with intellectual/developmental disabilities, are included and can succeed. The entire process from admissions, course selection, course instruction, graduation is designed to address systemic discrimination while supporting learners and faculty. The inclusive and accessible pedagogical model that is the foundation of IACP opens the doors of post-secondary education by making existing academic courses environments where all students can participate and succeed. IACP is about transforming teaching, not modifying, or adapting the curriculum or essential knowledge and skill sets that are required learning outcomes. Universal Design for Learning (UDL) principles are applied to instructional teaching strategies such as lectures, presentations, and assessment tools. Created in 2016 as a research pilot, IACP is one of the first fully inclusive for credit post-secondary options available. The pilot received numerous external and internal grants to support its initiative to investigate and assess the teaching strategies and techniques that support student learning of essential knowledge and skill sets. IACP pilot goals included: (1) provide a successful pilot as a model of inclusive and accessible pedagogy; (2) create a teacher’s guide to assist other instructors in transforming their teaching to reach a wide range of learners; (3) identify policy barriers located within the educational system; and (4) provide leadership and encouraging innovative and inclusive pedagogical practices. The pilot was a success and in 2020 the first cohort of students graduated with an exit credential that pre-exists IACP and consists of ten academic courses. The University has committed to continue IACP and has developed a sustainable model. Each new academic year a new cohort of IACP students starts their post-secondary educational journey, while two additional instructors are mentored with the pedagogy. The pedagogical foundation of IACP has far-reaching potential including, but not limited to, programs that offer services for international students whose first language is not English as well as influencing pedagogical reform in secondary and post-secondary education. IACP also supports universities in satisfying educational standards that are or will be included in accessibility/disability legislation. This session will present information about IACP, share examples of systems transformation, hear from students and instructors, and provide participatory experiential activities that demonstrate the transformative techniques. We will be drawing from the experiences of a recent course that explored research documenting the lived experiences of students with disabilities in post-secondary institutes in B.C (Whittington-Walsh). Students created theatrical scenes out of the data and presented it using Forum Theatre method. Forum Theatre was used to create conversations, challenge stereotypes, and build connections between ableism, disability justice, Indigeneity, and social policy.

Keywords: disability justice, inclusive education, pedagogical transformation, systems transformation

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Authors: Clara Tramuta, Lucia Decastelli, Elisa Barcucci, Sandra Fragassi, Samantha Lupi, Enrico Arletti, Melissa Bizzarri, Daniela Manila Bianchi

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Introdution: Food allergies occurs, in the Western World, 2% of adults and up to 8% of children. The protection of allergic consumers is guaranted, in Eurrope, by Regulation (EU) No 1169/2011 of the European Parliament which governs the consumer's right to information and identifies 14 food allergens to be mandatory indicated on the label. Among these, mustard is a popular spice added to enhance the flavour and taste of foods. It is frequently present as an ingredient in spice blends, marinades, salad dressings, sausages, and other products. Hypersensitivity to mustard is a public health problem since the ingestion of even low amounts can trigger severe allergic reactions. In order to protect the allergic consumer, high performance methods are required for the detection of allergenic ingredients. Food safety laboratories rely on validated methods that detect hidden allergens in food to ensure the safety and health of allergic consumers. Here we present the test results for the validation and accreditation of a Real time PCR assay (RT-PCR: SPECIALfinder MC Mustard, Generon), for the detection of mustard traces in food. Materials and Methods. The method was tested on five classes of food matrices: bakery and pastry products (chocolate cookies), meats (ragù), ready-to-eat (mixed salad), dairy products (yogurt), grains, and milling products (rice and barley flour). Blank samples were spiked starting with the mustard samples (Sinapis Alba), lyophilized and stored at -18 °C, at a concentration of 1000 ppm. Serial dilutions were then prepared to a final concentration of 0.5 ppm, using the DNA extracted by ION Force FAST (Generon) from the blank samples. The Real Time PCR reaction was performed by RT-PCR SPECIALfinder MC Mustard (Generon), using CFX96 System (BioRad). Results. Real Time PCR showed a limit of detection (LOD) of 0.5 ppm in grains and milling products, ready-to-eat, meats, bakery, pastry products, and dairy products (range Ct 25-34). To determine the exclusivity parameter of the method, the ragù matrix was contaminated with Prunus dulcis (almonds), peanut (Arachis hypogaea), Glycine max (soy), Apium graveolens (celery), Allium cepa (onion), Pisum sativum (peas), Daucus carota (carrots), and Theobroma cacao (cocoa) and no cross-reactions were observed. Discussion. In terms of sensitivity, the Real Time PCR confirmed, even in complex matrix, a LOD of 0.5 ppm in five classes of food matrices tested; these values are compatible with the current regulatory situation that does not consider, at international level, to establish a quantitative criterion for the allergen considered in this study. The Real Time PCR SPECIALfinder kit for the detection of mustard proved to be easy to use and particularly appreciated for the rapid response times considering that the amplification and detection phase has a duration of less than 50 minutes. Method accuracy was rated satisfactory for sensitivity (100%) and specificity (100%) and was fully validated and accreditated. It was found adequate for the needs of the laboratory as it met the purpose for which it was applied. This study was funded in part within a project of the Italian Ministry of Health (IZS PLV 02/19 RC).

Keywords: allergens, food, mustard, real time PCR

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