Search results for: plant growth models

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: Danah Al-Selahi, Sulaiman Al-Ghunaim, Bashayer Sadiq, Fatma Al-Otaibi, Ali Ameen

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In light of recent changes affecting the Oil & Gas Industry, optimization measures have become imperative for all companies globally, including Kuwait Oil Company (KOC). To keep abreast of the dynamic market, a detailed Integrated Asset Plan (IAP) was developed to drive optimization across the organization, which was facilitated through the in-house developed software “Well Inventory Data Entry” (WIDE). This comprehensive and integrated approach enabled centralization of all planned asset components for better well planning, enhancement of performance, and to facilitate continuous improvement through performance tracking and midterm forecasting. Traditionally, this was hard to achieve as, in the past, various legacy methods were used. This paper briefly describes the methods successfully adopted to meet the company’s objective. IAPs were initially designed using computerized spreadsheets. However, as data captured became more complex and the number of stakeholders requiring and updating this information grew, the need to automate the conventional spreadsheets became apparent. WIDE, existing in other aspects of the company (namely, the Workover Optimization project), was utilized to meet the dynamic requirements of the IAP cycle. With the growth of extensive features to enhance the planning process, the tool evolved into a centralized data-hub for all asset-groups and technical support functions to analyze and infer from, leading WIDE to become the reference two-year operational plan for the entire company. To achieve WIDE’s goal of operational efficiency, asset-groups continuously add their parameters in a series of predefined workflows that enable the creation of a structured process which allows risk factors to be flagged and helps mitigation of the same. This tool dictates assigned responsibilities for all stakeholders in a method that enables continuous updates for daily performance measures and operational use. The reliable availability of WIDE, combined with its user-friendliness and easy accessibility, created a platform of cross-functionality amongst all asset-groups and technical support groups to update contents of their respective planning parameters. The home-grown entity was implemented across the entire company and tailored to feed in internal processes of several stakeholders across the company. Furthermore, the implementation of change management and root cause analysis techniques captured the dysfunctionality of previous plans, which in turn resulted in the improvement of already existing mechanisms of planning within the IAP. The detailed elucidation of the 2 year plan flagged any upcoming risks and shortfalls foreseen in the plan. All results were translated into a series of developments that propelled the tool’s capabilities beyond planning and into operations (such as Asset Production Forecasts, setting KPIs, and estimating operational needs). This process exemplifies the ability and reach of applying advanced development techniques to seamlessly integrated the planning parameters of various assets and technical support groups. These techniques enables the enhancement of integrating planning data workflows that ultimately lay the founding plans towards an epoch of accuracy and reliability. As such, benchmarks of establishing a set of standard goals are created to ensure the constant improvement of the efficiency of the entire planning and operational structure.

Keywords: automation, integration, value, communication

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Authors: Lucille Alonso, Florent Renard

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The characterizations of urban heat island (UHI) and their interactions with climate change and urban climates are the main research and public health issue, due to the increasing urbanization of the population. These solutions require a better knowledge of the UHI and micro-climate in urban areas, by combining measurements and modelling. This study is part of this topic by evaluating microclimatic conditions in dense urban areas in the Lyon Metropolitan Area (France) using a combination of data traditionally used such as topography, but also from LiDAR (Light Detection And Ranging) data, Landsat 8 satellite observation and Sentinel and ground measurements by bike. These bicycle-dependent weather data collections are used to build the database of the variable to be modelled, the air temperature, over Lyon’s hyper-center. This study aims to model the air temperature, measured during 6 mobile campaigns in Lyon in clear weather, using multiple linear regressions based on 33 explanatory variables. They are of various categories such as meteorological parameters from remote sensing, topographic variables, vegetation indices, the presence of water, humidity, bare soil, buildings, radiation, urban morphology or proximity and density to various land uses (water surfaces, vegetation, bare soil, etc.). The acquisition sources are multiple and come from the Landsat 8 and Sentinel satellites, LiDAR points, and cartographic products downloaded from an open data platform in Greater Lyon. Regarding the presence of low, medium, and high vegetation, the presence of buildings and ground, several buffers close to these factors were tested (5, 10, 20, 25, 50, 100, 200 and 500m). The buffers with the best linear correlations with air temperature for ground are 5m around the measurement points, for low and medium vegetation, and for building 50m and for high vegetation is 100m. The explanatory model of the dependent variable is obtained by multiple linear regression of the remaining explanatory variables (Pearson correlation matrix with a |r| < 0.7 and VIF with < 5) by integrating a stepwise sorting algorithm. Moreover, holdout cross-validation is performed, due to its ability to detect over-fitting of multiple regression, although multiple regression provides internal validation and randomization (80% training, 20% testing). Multiple linear regression explained, on average, 72% of the variance for the study days, with an average RMSE of only 0.20°C. The impact on the model of surface temperature in the estimation of air temperature is the most important variable. Other variables are recurrent such as distance to subway stations, distance to water areas, NDVI, digital elevation model, sky view factor, average vegetation density, or building density. Changing urban morphology influences the city's thermal patterns. The thermal atmosphere in dense urban areas can only be analysed on a microscale to be able to consider the local impact of trees, streets, and buildings. There is currently no network of fixed weather stations sufficiently deployed in central Lyon and most major urban areas. Therefore, it is necessary to use mobile measurements, followed by modelling to characterize the city's multiple thermal environments.

Keywords: air temperature, LIDAR, multiple linear regression, surface temperature, urban heat island

Procedia PDF Downloads 108

Authors: Mariia V. Efremova, Iana O. Tcareva, Anastasia D. Blokhina, Ivan S. Grebennikov, Anastasia S. Garanina, Maxim A. Abakumov, Yury I. Golovin, Alexander G. Savchenko, Alexander G. Majouga, Natalya L. Klyachko

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During last decades magnetite nanoparticles (NPs) attract a deep interest of scientists due to their potential application in therapy and diagnostics. However, magnetite nanoparticles are toxic and non-stable in physiological conditions. To solve these problems, we decided to create two types of hybrid systems based on magnetite and gold which is inert and biocompatible: gold as a shell material (first type) and gold as separate NPs interfacially bond to magnetite NPs (second type). The synthesis of the first type hybrid nanoparticles was carried out as follows: Magnetite nanoparticles with an average diameter of 9±2 nm were obtained by co-precipitation of iron (II, III) chlorides then they were covered with gold shell by iterative reduction of hydrogen tetrachloroaurate with hydroxylamine hydrochloride. According to the TEM, ICP MS and EDX data, final nanoparticles had an average diameter of 31±4 nm and contained iron even after hydrochloric acid treatment. However, iron signals (K-line, 7,1 keV) were not localized so we can’t speak about one single magnetic core. Described nanoparticles covered with mercapto-PEG acid were non-toxic for human prostate cancer PC-3/ LNCaP cell lines (more than 90% survived cells as compared to control) and had high R2-relaxivity rates (>190 mМ-1s-1) that exceed the transverse relaxation rate of commercial MRI-contrasting agents. These nanoparticles were also used for chymotrypsin enzyme immobilization. The effect of alternating magnetic field on catalytic properties of chymotrypsin immobilized on magnetite nanoparticles, notably the slowdown of catalyzed reaction at the level of 35-40 % was found. The synthesis of the second type hybrid nanoparticles also involved two steps. Firstly, spherical gold nanoparticles with an average diameter of 9±2 nm were synthesized by the reduction of hydrogen tetrachloroaurate with oleylamine; secondly, they were used as seeds during magnetite synthesis by thermal decomposition of iron pentacarbonyl in octadecene. As a result, so-called dumbbell-like structures were obtained where magnetite (cubes with 25±6 nm diagonal) and gold nanoparticles were connected together pairwise. By HRTEM method (first time for this type of structure) an epitaxial growth of magnetite nanoparticles on gold surface with co-orientation of (111) planes was discovered. These nanoparticles were transferred into water by means of block-copolymer Pluronic F127 then loaded with anti-cancer drug doxorubicin and also PSMA-vector specific for LNCaP cell line. Obtained nanoparticles were found to have moderate toxicity for human prostate cancer cells and got into the intracellular space after 45 minutes of incubation (according to fluorescence microscopy data). These materials are also perspective from MRI point of view (R2-relaxivity rates >70 mМ-1s-1). Thereby, in this work magnetite-gold hybrid nanoparticles, which have a strong potential for biomedical application, particularly in targeted drug delivery and magnetic resonance imaging, were synthesized and characterized. That paves the way to the development of special medicine types – theranostics. The authors knowledge financial support from Ministry of Education and Science of the Russian Federation (14.607.21.0132, RFMEFI60715X0132). This work was also supported by Grant of Ministry of Education and Science of the Russian Federation К1-2014-022, Grant of Russian Scientific Foundation 14-13-00731 and MSU development program 5.13.

Keywords: drug delivery, magnetite-gold, MRI contrast agents, nanoparticles, toxicity

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Authors: Sami El Khatib, Agnès Leroux, Jean-Louis Merlin, François Guillemin, Marie-Ange D’Hallewin

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Photodynamic therapy (PDT) is a treatment modality based on the cytotoxic effect occurring on the target tissues by interaction of a photosensitizer with light in the presence of oxygen. One of the major advances in PDT can be attributed to the use of topical aminolevulinic (ALA) to induce Protoporphyrin IX (PpIX) for the treatment of early stage cancers as well as diagnosis. ALA is a precursor of the heme synthesis pathway. Locally delivered to the target tissue ALA overcomes the negative feedback exerted by heme and promotes the transient formation of PpIX in situ to reach critical effective levels in cells and tissue. Whereas early steps of the heme pathway occur in the cytosol, PpIX synthesis is shown to be held in the mitochondrial membranes and PpIX fluorescence is expected to accumulate in close vicinity of the initial building site and to progressively diffuse to the neighboring cytoplasmic compartment or other lipophylic organelles. PpIX is known to be highly reactive and will be degraded when irradiated with light. PpIX photobleaching is believed to be governed by a singlet oxygen mediated mechanism in the presence of oxidized amino acids and proteins. PpIX photobleaching and subsequent spectral phototransformation were described widely in tumor cells incubated in vitro with ALA solution, or ex vivo in human and porcine mucosa superfused with hexylaminolevulinate (hALA). PpIX photobleaching was also studied in vivo, using animal models such as normal or tumor mice skin and orthotopic rat bladder model. Hexyl aminolevulinate a more potent lipophilic derivative of ALA was proposed as an adjunct to standard cystoscopy in the fluorescence diagnosis of bladder cancer and other malignancies. We have previously reported the effectiveness of hALA mediated PDT of rat bladder cancer. Although normal and tumor bladder epithelium exhibit similar fluorescence intensities after intravesical instillation of two hALA concentrations (8 and 16 mM), the therapeutic response at 8mM and 20J/cm2 was completely different from the one observed at 16mM irradiated with the same light dose. Where the tumor is destroyed, leaving the underlying submucosa and muscle intact after an 8 mM instillation, 16mM sensitization and subsequent illumination results in the complete destruction of the underlying bladder wall but leaves the tumor undamaged. The object of the current study is to try to unravel the underlying mechanism for this apparent contradiction. PpIX extraction showed identical amounts of photosensitizer in tumor bearing bladders at both concentrations. Photobleaching experiments revealed mono-exponential decay curves in both situations but with a two times faster decay constant in case of 16mM bladders. Fluorescence microscopy shows an identical fluorescence pattern for normal bladders at both concentrations and tumor bladders at 8mM with bright spots. Tumor bladders at 16 mM exhibit a more diffuse cytoplasmic fluorescence distribution. The different response to PDT with regard to the initial pro-drug concentration can thus be attributed to the different cellular localization.

Keywords: bladder cancer, hexyl-aminolevulinate, photobleaching, confocal fluorescence microscopy

Procedia PDF Downloads 378

Authors: Rajeswari Raguraman, Sowmya Parameswaran, Krishnakumar Subramanian, Jagat Kanwar, Rupinder Kanwar

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Background: Tumor microenvironment has been implicated in several cancers to regulate cell growth, invasion and metastasis culminating in outcome of therapy. Tumor stroma consists of multiple cell types that are in constant cross-talk with the tumor cells to favour a pro-tumorigenic environment. Not much is known about the existence of tumor microenvironment in the pediatric intraocular malignancy, Retinoblastoma (RB). In the present study, we aim to understand the multiple stromal cellular subtypes and tumor stromal interactions expressed in RB tumors. Materials and Methods: Immunohistochemistry for stromal cell markers CD31, CD68, alpha-smooth muscle (α-SMA), vimentin and glial fibrillary acidic protein (GFAP) was performed on formalin fixed paraffin embedded tissues sections of RB (n=12). The differential expression of stromal target molecules; fibroblast activation protein (FAP), tenascin-C (TNC), osteopontin (SPP1), bone marrow stromal antigen 2 (BST2), stromal derived factor 2 and 4 (SDF2 and SDF4) in primary RB tumors (n=20) and normal retina (n=5) was studied by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) and Western blotting. The differential expression was correlated with the histopathological features of RB. The interaction between RB cell lines (Weri-Rb-1, NCC-RbC-51) and Bone marrow stromal cells (BMSC) was also studied using direct co-culture and indirect co-culture methods. The functional effect of the co-culture methods on the RB cells was evaluated by invasion and proliferation assays. Global gene expression was studied by using Affymetrix 3’ IVT microarray. Pathway prediction was performed using KEGG and the key molecules were validated using qRT-PCR. Results: The immunohistochemistry revealed the presence of several stromal cell types such as endothelial cells (CD31+;Vim+/-); macrophages (CD68+;Vim+/-); Fibroblasts (Vim+; CD31-;CD68- );myofibroblasts (α-SMA+/ Vim+) and invading retinal astrocytes/ differentiated retinal glia (GFAP+; Vim+). A characteristic distribution of these stromal cell types was observed in the tumor microenvironment, with endothelial cells predominantly seen in blood vessels and macrophages near actively proliferating tumor or necrotic areas. Retinal astrocytes and glia were predominant near the optic nerve regions in invasive tumors with sparse distribution in tumor foci. Fibroblasts were widely distributed with rare evidence of myofibroblasts in the tumor. Both gene and protein expression revealed statistically significant (P<0.05) up-regulation of FAP, TNC and BST2 in primary RB tumors compared to the normal retina. Co-culture of BMSC with RB cells promoted invasion and proliferation of RB cells in direct and indirect contact methods respectively. Direct co-culture of RB cell lines with BMSC resulted in gene expression changes in ECM-receptor interaction, focal adhesion, IL-8 and TGF-β signaling pathways associated with cancer. In contrast, various metabolic pathways such a glucose, fructose and amino acid metabolism were significantly altered under the indirect co-culture condition. Conclusion: The study suggests that the close interaction between RB cells and the stroma might be involved in RB tumor invasion and progression which is likely to be mediated by ECM-receptor interactions and secretory factors. Targeting the tumor stroma would be an attractive option for redesigning treatment strategies for RB.

Keywords: gene expression profiles, retinoblastoma, stromal cells, tumor microenvironment

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Authors: Silvia Baralla, Raffaella Zucaro, Romina Lorenzetti

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Water management needs to cope with economic, societal, and environmental changes. This could be guaranteed through 'shifting from government to governance'. In the last decades, it was applied in Europe through and within important legislative pillars (Water Framework Directive and Common Agricultural Policy) and their measures focused on resilience and adaptation to climate change, with particular attention to the creation of synergies among policies and all the actors involved at different levels. Within the climate change context, the agricultural sector can play, through sustainable water management, a leading role for climate-resilient growth and environmental integrity. A recent analysis on the water management governance of different countries identified some common gaps dealing with administrative, policy, information, capacity building, funding, objective, and accountability. The ability of a country to fill these gaps is an essential requirement to make some of the changes requested by Europe, in particular the improvement of the agro-ecosystem resilience to the effect of climatic change, supporting green and digital transitions, and sustainable water use. This research aims to contribute in sharing examples of water governances and related advantages useful to fill the highlighted gaps. Italy has developed a strong and exhaustive model of water governance in order to react with strategic and synergic actions since it is one of the European countries most threatened by climate change and its extreme events (drought, floods). In particular, the Italian water governance model was able to overcome several gaps, specifically as concerns the water use in agriculture, adopting strategies as a systemic/integrated approach, the stakeholder engagement, capacity building, the improvement of planning and monitoring ability, and an adaptive/resilient strategy for funding activities. They were carried out, putting in place regulatory, structural, and management actions. Regulatory actions include both the institution of technical committees grouping together water decision-makers and the elaboration of operative manuals and guidelines by means of a participative and cross-cutting approach. Structural actions deal with the funding of interventions within European and national funds according to the principles of coherence and complementarity. Finally, management actions regard the introduction of operational tools to support decision-makers in order to improve planning and monitoring ability. In particular, two cross-functional and interoperable web databases were introduced: SIGRIAN (National Information System for Water Resources Management in Agriculture) and DANIA (National Database of Investments for Irrigation and the Environment). Their interconnection allows to support sustainable investments, taking into account the compliance about irrigation volumes quantified in SIGRIAN, ensuring a high level of attention on water saving, and monitoring the efficiency of funding. Main positive results from the Italian water governance model deal with a synergic and coordinated work at the national, regional, and local level among institutions, the transparency on water use in agriculture, a deeper understanding from the stakeholder side of the importance of their roles and of their own potential benefits and the capacity to guarantee continuity to this model, through a sensitization process and the combined use of management operational tools.

Keywords: agricultural sustainability, governance model, water management, water policies

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Authors: Rupesh S. Gundewar, Kanchan C. Khare

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Runoff contribution from urban areas is generally from manmade structures and few natural contributors. The manmade structures are buildings; roads and other paved areas whereas natural contributors are groundwater and overland flows etc. Runoff alleviation is done by manmade as well as natural storages. Manmade storages are storage tanks or other storage structures such as soakways or soak pits which are more common in western and European countries. Natural storages are catchment slope, infiltration, catchment length, channel rerouting, drainage density, depression storage etc. A literature survey on the manmade and natural storages/inflow has presented percentage contribution of each individually. Sanders et.al. in their research have reported that a vegetation canopy reduces runoff by 7% to 12%. Nassif et el in their research have reported that catchment slope has an impact of 16% on bare standard soil and 24% on grassed soil on rainfall runoff. Infiltration being a pervious/impervious ratio dependent parameter is catchment specific. But a literature survey has presented a range of 15% to 30% loss of rainfall runoff in various catchment study areas. Catchment length and channel rerouting too play a considerable role in reduction of rainfall runoff. Ground infiltration inflow adds to the runoff where the groundwater table is very shallow and soil saturates even in a lower intensity storm. An approximate percent contribution through this inflow and surface inflow contributes to about 2% of total runoff volume. Considering the various contributing factors in runoff it has been observed during a literature survey that integrated modelling approach needs to be considered. The traditional storm water network models are able to predict to a fair/acceptable degree of accuracy provided no interaction with receiving water (river, sea, canal etc), ground infiltration, treatment works etc. are assumed. When such interactions are significant then it becomes difficult to reproduce the actual flood extent using the traditional discrete modelling approach. As a result the correct flooding situation is very rarely addressed accurately. Since the development of spatially distributed hydrologic model the predictions have become more accurate at the cost of requiring more accurate spatial information.The integrated approach provides a greater understanding of performance of the entire catchment. It enables to identify the source of flow in the system, understand how it is conveyed and also its impact on the receiving body. It also confirms important pain points, hydraulic controls and the source of flooding which could not be easily understood with discrete modelling approach. This also enables the decision makers to identify solutions which can be spread throughout the catchment rather than being concentrated at single point where the problem exists. Thus it can be concluded from the literature survey that the representation of urban details can be a key differentiator to the successful understanding of flooding issue. The intent of this study is to accurately predict the runoff from impermeable areas from urban area in India. A representative area has been selected for which data was available and predictions have been made which are corroborated with the actual measured data.

Keywords: runoff, urbanization, impermeable response, flooding

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Authors: Alper T. Celebi, Ali Beskok

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Electroosmotic (EO) slip flows in nanochannels are investigated using non-equilibrium molecular dynamics (MD) simulations, and the results are compared with analytical solution of Poisson-Boltzmann and Stokes (PB-S) equations with slip contribution. The ultimate objective of this study is to show that well-known continuum flow model can accurately predict the EO velocity profiles in nanochannels using the slip lengths and apparent viscosities obtained from force-driven flow simulations performed at various liquid-wall interaction strengths. EO flow of aqueous NaCl solution in silicon nanochannels are simulated under realistic electrochemical conditions within the validity region of Poisson-Boltzmann theory. A physical surface charge density is determined for nanochannels based on dissociations of silanol functional groups on channel surfaces at known salt concentration, temperature and local pH. First, we present results of density profiles and ion distributions by equilibrium MD simulations, ensuring that the desired thermodynamic state and ionic conditions are satisfied. Next, force-driven nanochannel flow simulations are performed to predict the apparent viscosity of ionic solution between charged surfaces and slip lengths. Parabolic velocity profiles obtained from force-driven flow simulations are fitted to a second-order polynomial equation, where viscosity and slip lengths are quantified by comparing the coefficients of the fitted equation with continuum flow model. Presence of charged surface increases the viscosity of ionic solution while the velocity-slip at wall decreases. Afterwards, EO flow simulations are carried out under uniform electric field for different liquid-wall interaction strengths. Velocity profiles present finite slips near walls, followed with a conventional viscous flow profile in the electrical double layer that reaches a bulk flow region in the center of the channel. The EO flow enhances with increased slip at the walls, which depends on wall-liquid interaction strength and the surface charge. MD velocity profiles are compared with the predictions from analytical solutions of the slip modified PB-S equation, where the slip length and apparent viscosity values are obtained from force-driven flow simulations in charged silicon nano-channels. Our MD results show good agreements with the analytical solutions at various slip conditions, verifying the validity of PB-S equation in nanochannels as small as 3.5 nm. In addition, the continuum model normalizes slip length with the Debye length instead of the channel height, which implies that enhancement in EO flows is independent of the channel height. Further MD simulations performed at different channel heights also shows that the flow enhancement due to slip is independent of the channel height. This is important because slip enhanced EO flow is observable even in micro-channels experiments by using a hydrophobic channel with large slip and high conductivity solutions with small Debye length. The present study provides an advanced understanding of EO flows in nanochannels. Correct characterization of nanoscale EO slip flow is crucial to discover the extent of well-known continuum models, which is required for various applications spanning from ion separation to drug delivery and bio-fluidic analysis.

Keywords: electroosmotic flow, molecular dynamics, slip length, velocity-slip

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Authors: Àidan Higgins

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Higher education will be crucial in the coming decades in helping to make Ireland a nation is known for innovation, competitive enterprise, and ongoing academic success, as well as a desirable location to live and work with a high quality of life, vibrant culture, and inclusive social structures. Higher education institutions will actively connect with each student community, society, and business; they will help students develop a sense of place and identity in Ireland and provide the tools they need to contribute significantly to the global community. It will also serve as a catalyst for novel ideas through research, many of which will become the foundation for long-lasting inventive businesses in the future as part of the 2030 National Strategy on Education focuses on change and developing our education system with a focus on how we carry out Research. The emphasis is central to knowledge transfer and a consistent research framework with exploiting opportunities and having the necessary expertise. The newly formed Technological Universities (TU) in Ireland are based on a government initiative to create a new type of higher education institution that focuses on applied and industry-focused research and education. The basis of the TU is to bring together two or more existing institutes of technology to create a larger and more comprehensive institution that offers a wider range of programs and services to students and industry partners. The TU model aims to promote collaboration between academia, industry, and community organizations to foster innovation, research, and economic development. The TU model also aims to enhance the student experience by providing a more seamless pathway from undergraduate to postgraduate studies, as well as greater opportunities for work placements and engagement with industry partners. Additionally, the TUs are designed to provide a greater emphasis on applied research, technology transfer, and entrepreneurship, with the goal of fostering innovation and contributing to economic growth. A project is a collection of organised tasks carried out precisely to produce a singular output (product or service) within a given time frame. Project management is a set of activities that facilitates the successful implementation of a project. The significant differences between research and development projects are the (lack of) precise requirements and (the inability to) plan an outcome from the beginning of the project. The evaluation criteria for a research project must consider these and other "particularities" in works; for instance, proving something cannot be done may be a successful outcome. This study intends to explore how a newly established multi-campus technological university manages research projects effectively. The study will identify the potential and difficulties of managing research projects, the tools, resources and processes available in a multi-campus Technological University context and the methods and approaches employed to deal with these difficulties. Key stakeholders like project managers, academics, and administrators will be surveyed as part of the study, which will also involve an explorative investigation of current literature and data. The findings of this study will contribute significantly to creating best practices for project management in this setting and offer insightful information about the efficient management of research projects within a multi-campus technological university.

Keywords: project management, research and research-related projects, multi-campus technology university, processes

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Authors: Antonis Skouloudis, Konstantinos Evangelinos, Walter Leal-Filho, Panagiotis Vouros, Ioannis Nikolaou

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Organizational resilience capacity to extreme weather events (EWEs) has sparked a growth in scholarly attention over the past decade as an essential aspect in business continuity management, with supporting evidence for this claim to suggest that it retains a key role in successful responses to adverse situations, crises and shocks. Small and medium-sized enterprises (SMEs) are more vulnerable to face floods compared to their larger counterparts, so they are disproportionately affected by such extreme weather events. The limited resources at their disposal, the lack of time and skills all conduce to inadequate preparedness to challenges posed by floods. SMEs tend to plan in the short-term, reacting to circumstances as they arise and focussing on their very survival. Likewise, they share less formalised structures and codified policies while they are most usually owner-managed, resulting in a command-and-control management culture. Such characteristics result in them having limited opportunities to recover from flooding and quickly turnaround their operation from a loss making to a profit making one. Scholars frame the capacity of business entities to be resilient upon an EWE disturbance (such as flash floods) as the rate of recovery and restoration of organizational performance to pre-disturbance conditions, the amount of disturbance (i.e. threshold level) a business can absorb before losing structural and/or functional components that will alter or cease operation, as well as the extent to which the organization maintains its function (i.e. impact resistance) before performance levels are driven to zero. Nevertheless, while it seems to be accepted as an essential trait of firms effectively transcending uncertain conditions, research deconstructing the enabling conditions and/or inhibitory factors of SMEs resilience capacity to natural hazards is still sparse, fragmentary and mostly fuelled by anecdotal evidence or normative assumptions. Focusing on the individual level of analysis, i.e. the individual enterprise and its endeavours to succeed, the emergent picture from this relatively new research strand delineates the specification of variables, conceptual relationships or dynamic boundaries of resilience capacity components in an attempt to provide prescriptions for policy-making as well as business management. This study will present the development of a flood resilience capacity index (FRCI) and its application to Greek SMEs. The proposed composite indicator pertains to cognitive, behavioral/managerial and contextual factors that influence an enterprise’s ability to shape effective responses to meet flood challenges. Through the proposed indicator-based approach, an analytical framework is set forth that will help standardize such assessments with the overarching aim of reducing the vulnerability of SMEs to flooding. This will be achieved by identifying major internal and external attributes explaining resilience capacity which is particularly important given the limited resources these enterprises have and that they tend to be primary sources of vulnerabilities in supply chain networks, generating Single Points of Failure (SPOF).

Keywords: Floods, Small & Medium-Sized enterprises, organizational resilience capacity, index development

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Authors: F. Tang, S. Boskovich, A. Raheja, Z. Aliyazicioglu, S. Bhandari, N. Tsuchiya

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Calpoly Autonomous Transportation Experience (CATE) is a driverless vehicle that we are developing to provide safe, accessible, and efficient transportation of passengers throughout the Cal Poly Pomona campus for events such as orientation tours. Unlike the other self-driving vehicles that are usually developed to operate with other vehicles and reside only on the road networks, CATE will operate exclusively on walk-paths of the campus (potentially narrow passages) with pedestrians traveling from multiple locations. Safety becomes paramount as CATE operates within the same environment as pedestrians. As driverless vehicles assume greater roles in today’s transportation, this project will contribute to autonomous driving with pedestrian traffic in a highly dynamic environment. The CATE project requires significant interdisciplinary work. Researchers from mechanical engineering, electrical engineering and computer science are working together to attack the problem from different perspectives (hardware, software and system). In this abstract, we describe the software aspects of the project, with a focus on the requirements and the major components. CATE shall provide a GUI interface for the average user to interact with the car and access its available functionalities, such as selecting a destination from any origin on campus. We have developed an interface that provides an aerial view of the campus map, the current car location, routes, and the goal location. Users can interact with CATE through audio or manual inputs. CATE shall plan routes from the origin to the selected destination for the vehicle to travel. We will use an existing aerial map for the campus and convert it to a spatial graph configuration where the vertices represent the landmarks and edges represent paths that the car should follow with some designated behaviors (such as stay on the right side of the lane or follow an edge). Graph search algorithms such as A* will be implemented as the default path planning algorithm. D* Lite will be explored to efficiently recompute the path when there are any changes to the map. CATE shall avoid any static obstacles and walking pedestrians within some safe distance. Unlike traveling along traditional roadways, CATE’s route directly coexists with pedestrians. To ensure the safety of the pedestrians, we will use sensor fusion techniques that combine data from both lidar and stereo vision for obstacle avoidance while also allowing CATE to operate along its intended route. We will also build prediction models for pedestrian traffic patterns. CATE shall improve its location and work under a GPS-denied situation. CATE relies on its GPS to give its current location, which has a precision of a few meters. We have implemented an Unscented Kalman Filter (UKF) that allows the fusion of data from multiple sensors (such as GPS, IMU, odometry) in order to increase the confidence of localization. We also noticed that GPS signals can easily get degraded or blocked on campus due to high-rise buildings or trees. UKF can also help here to generate a better state estimate. In summary, CATE will provide on-campus transportation experience that coexists with dynamic pedestrian traffic. In future work, we will extend it to multi-vehicle scenarios.

Keywords: driverless vehicle, path planning, sensor fusion, state estimate

Procedia PDF Downloads 117

Authors: Abdullah Al Mohiuddin

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Bangladesh is one of the poorest countries in the world, and ranks low on almost all measures of economic development, thus leaving the population extremely vulnerable to natural disasters and climate events. 20% of GDP come from agriculture but more than 60% of the population relies on agriculture as their main source of income making the entire economy vulnerable to climate change and natural disasters. High population density exacerbates the exposure to and effect of climate events, and increases the levels of vulnerability, as does the poor institutional development of the country. The most vulnerable sectors to climate change impacts in Bangladesh are agriculture, coastal zones, water resources, forestry, fishery, health, biomass, and energy. High temperatures, heavy rainfall, high humidity and fairly marked seasonal variations characterize the climate in Bangladesh: Mild winter, hot humid summer and humid, warm rainy monsoon. Much of the country is flooded during the summer monsoon. The Department of Environment (DOE) under the Ministry of Environment and Forestry (MoEF) is the focal point for the United Nations Framework Convention on Climate Change (UNFCCC) and coordinates climate related activities in the country. Recently, a Climate Change Cell (CCC) has been established to address several issues including adaptation to climate change. The climate change focus started with The National Environmental Management Action Plan (NEMAP) which was prepared in 1995 in order to initiate the process to address environmental and climate change issues as long-term environmental problems for Bangladesh. Bangladesh was one of the first countries to finalise a NAPA (Preparation of a National Adaptation Plan of Action) which addresses climate change issues. The NAPA was completed in 2005, and is the first official initiative for mainstreaming adaptation to national policies and actions to cope with climate change and vulnerability. The NAPA suggests a number of adaptation strategies, for example: - Providing drinking water to coastal communities to fight the enhanced salinity caused by sea level rise, - Integrating climate change in planning and design of infrastructure, - Including climate change issues in education, - Supporting adaptation of agricultural systems to new weather extremes, - Mainstreaming CCA into policies and programmes in different sectors, e.g. disaster management, water and health, - Dissemination of CCA information and awareness raising on enhanced climate disasters, especially in vulnerable communities. Bangladesh has geared up its environment conservation steps to save the world’s poorest countries from the adverse effects of global warming. Now it is turning towards green economy policies to save the degrading ecosystem. Bangladesh is a developing country and always fights against Natural Disaster. At the same time we also fight for establishing ecological environment through promoting Green Economy/Energy by Youth Networking. ANTAR is coordinating a big Youth Network in the southern part of Bangladesh where 30 Youth group involved. It can be explained as the economic development based on sustainable development which generates growth and improvement in human’s lives while significantly reducing environmental risks and ecological scarcities. Green economy in Bangladesh promotes three bottom lines – sustaining economic, environment and social well-being.

Keywords: resilience, networking, mobilizing, resource

Procedia PDF Downloads 284

Authors: Richard McGregor, Carmen Reaiche, Stephen Boyle

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Cyber threats are a relatively recent phenomenon and offer cyber insurers a dynamic and intelligent peril. As individuals en mass become increasingly digitally dependent, Personal Cyber Insurance (PCI) offers an attractive option to mitigate cyber risk at a personal level. This abstract proposes a literature review that conceptualises a framework for siting Personal Cyber Insurance (PCI) within the context of cyberspace. The lack of empirical research within this domain demonstrates an immediate need to define the scope of PCI to allow cyber insurers to understand personal cyber risk threats and vectors, customer awareness, capabilities, and their associated needs. Additionally, this will allow cyber insurers to conceptualise appropriate frameworks allowing effective management and distribution of PCI products and services within a landscape often in-congruent with risk attributes commonly associated with traditional personal line insurance products. Cyberspace has provided significant improvement to the quality of social connectivity and productivity during past decades and allowed enormous capability uplift of information sharing and communication between people and communities. Conversely, personal digital dependency furnish ample opportunities for adverse cyber events such as data breaches and cyber-attacksthus introducing a continuous and insidious threat of omnipresent cyber risk–particularly since the advent of the COVID-19 pandemic and wide-spread adoption of ‘work-from-home’ practices. Recognition of escalating inter-dependencies, vulnerabilities and inadequate personal cyber behaviours have prompted efforts by businesses and individuals alike to investigate strategies and tactics to mitigate cyber risk – of which cyber insurance is a viable, cost-effective option. It is argued that, ceteris parabus, the nature of cyberspace intrinsically provides characteristic peculiarities that pose significant and bespoke challenges to cyber insurers, often in-congruent with risk attributes commonly associated with traditional personal line insurance products. These challenges include (inter alia) a paucity of historical claim/loss data for underwriting and pricing purposes, interdependencies of cyber architecture promoting high correlation of cyber risk, difficulties in evaluating cyber risk, intangibility of risk assets (such as data, reputation), lack of standardisation across the industry, high and undetermined tail risks, and moral hazard among others. This study proposes a thematic overview of the literature deemed necessary to conceptualise the challenges to issuing personal cyber coverage. There is an evident absence of empirical research appertaining to PCI and the design of operational business models for this business domain, especially qualitative initiatives that (1) attempt to define the scope of the peril, (2) secure an understanding of the needs of both cyber insurer and customer, and (3) to identify elements pivotal to effective management and profitable distribution of PCI - leading to an argument proposed by the author that postulates that the traditional general insurance customer journey and business model are ill-suited for the lineaments of cyberspace. The findings of the review confirm significant gaps in contemporary research within the domain of personal cyber insurance.

Keywords: cyberspace, personal cyber risk, personal cyber insurance, customer journey, business model

Procedia PDF Downloads 78

Authors: Mohammed S. Razali, Kamel Khimeche, Dahah Hichem, Ammar Boudjellal, Djamel E. Kaderi, Nourddine Ramdani

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The use of additive manufacturing technologies has revolutionized various aspects of our daily lives. In particular, 3D printing has greatly advanced biomedical applications. While fused filament fabrication (FFF) technologies have made it easy to produce or prototype various medical devices, it is crucial to minimize the risk of contamination. New materials with antibacterial properties, such as those containing compounded silver nanoparticles, have emerged on the market. In a previous study, we prepared a newly sintered seashell filler (SSh) from bio-based seashells found along the Mediterranean coast using a suitable heat treatment process. We then prepared a series of polylactic acid (PLA) and polybutylene succinate (PBS) biocomposites filled with these SSh particles using a melt mixing technique with a twin-screw extruder to use them as feedstock filaments for 3D printing. The study consisted of two parts: evaluating the antibacterial activity of newly prepared biocomposites made of PLA and PBS reinforced with a sintered seashell in the first part and experimental and modeling analysis of the non-isothermal crystallization kinetics of these biocomposites in the second part. In the first part, the bactericidal activity of the biocomposites against three different bacteria, including Gram-negative bacteria such as (E. coli and Pseudomonas aeruginosa), as well as Gram-positive bacteria such as (Staphylococcus aureus), was examined. The PLA-based biocomposite containing 20 wt.% of SSh particles exhibited an inhibition zone with radial diameters of 8mm and 6mm against E. coli and Pseudo. Au, respectively, while no bacterial activity was observed against Staphylococcus aureus. In the second part, the focus was on investigating the effect of the sintered seashell filler particles on the non-isothermal crystallization kinetics of PLA and PBS 3D-printing composite materials. The objective was to understand the impact of the filler particles on the crystallization mechanism of both PLA and PBS during the cooling process of a melt-extruded filament in (FFF) to manage the dimensional accuracy and mechanical properties of the final printed part. We conducted a non-isothermal melt crystallization kinetic study of a series of PLA-SS and PBS-SS composites using differential scanning calorimetry at various cooling rates. We analyzed the obtained kinetic data using different crystallization kinetic models such as modified Avrami, Ozawa, and Mo's methods. Dynamic mode describes the relative crystallinity as a function of temperature; it found that time half crystallinity (t1/2) of neat PLA decreased from 17 min to 7.3 min for PLA+5 SSh and the (t1/2) of virgin PBS was reduced from 3.5 min to 2.8 min for the composite containing 5wt.% of SSh. We found that the coated SS particles with stearic acid acted as nucleating agents and had a nucleation activity, as observed through polarized optical microscopy. Moreover, we evaluated the effective energy barrier of the non-isothermal crystallization process using the Iso conversional methods of Flynn-Wall-Ozawa (F-W-O) and Kissinger-Akahira-Sunose (K-A-S). The study provides significant insights into the crystallization behavior of PLA and PBS biocomposites.

Keywords: avrami model, bio-based reinforcement, dsc, gram-negative bacteria, gram-positive bacteria, isoconversional methods, non-isothermal crystallization kinetics, poly(butylene succinate), poly(lactic acid), antbactirial activity

Procedia PDF Downloads 50

Authors: Nervana Elbakary, Sami Ouanes, Sadaf Riaz, Oraib Abdallah, Islam Mahran, Noriya Al-Khuzaei, Yassin Eltorki

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Major Depressive Disorder (MDD) requires therapeutic interventions during the initial month after being diagnosed for better disease outcomes. International guidelines recommend a duration of 4–12 weeks for an initial antidepressant (IAD) trial at an optimized dose to get a response. If depressive symptoms persist after this duration, guidelines recommend switching, augmenting, or combining strategies as the next step. Most patients with MDD in the mental health setting have been labeled incorrectly as treatment-resistant where in fact they have not been subjected to an adequate trial of guideline-recommended therapy. Premature discontinuation of IAD due to ineffectiveness can cause unfavorable consequences. Avoiding irrational practices such as subtherapeutic doses of IAD, premature switching between the ADs, and refraining from unjustified polypharmacy can help the disease to go into a remission phase We aimed to determine the prevalence and the patterns of strategies applied after an IAD was changed because of a suboptimal response as a primary outcome. Secondary outcomes included the median survival time on IAD before any change; and the predictors that were associated with IAD change. This was a retrospective cross- sectional study conducted in Mental Health Services in Qatar. A dataset between January 1, 2018, and December 31, 2019, was extracted from the electronic health records. Inclusion and exclusion criteria were defined and applied. The sample size was calculated to be at least 379 patients. Descriptive statistics were reported as frequencies and percentages, in addition, to mean and standard deviation. The median time of IAD to any change strategy was calculated using survival analysis. Associated predictors were examined using two unadjusted and adjusted cox regression models. A total of 487 patients met the inclusion criteria of the study. The average age for participants was 39.1 ± 12.3 years. Patients with first experience MDD episode 255 (52%) constituted a major part of our sample comparing to the relapse group 206(42%). About 431 (88%) of the patients had an occurrence of IAD change to any strategy before end of the study. Almost half of the sample (212 (49%); 95% CI [44–53%]) had their IAD changed less than or equal to 30 days. Switching was consistently more common than combination or augmentation at any timepoint. The median time to IAD change was 43 days with 95% CI [33.2–52.7]. Five independent variables (age, bothersome side effects, un-optimization of the dose before any change, comorbid anxiety, first onset episode) were significantly associated with the likelihood of IAD change in the unadjusted analysis. The factors statistically associated with higher hazard of IAD change in the adjusted analysis were: younger age, un-optimization of the IAD dose before any change, and comorbid anxiety. Because almost half of the patients in this study changed their IAD as early as within the first month, efforts to avoid treatment failure are needed to ensure patient-treatment targets are met. The findings of this study can have direct clinical guidance for health care professionals since an optimized, evidence-based use of AD medication can improve the clinical outcomes of patients with MDD; and also, to identify high-risk factors that could worsen the survival time on IAD such as young age and comorbid anxiety

Keywords: initial antidepressant, dose optimization, major depressive disorder, comorbid anxiety, combination, augmentation, switching, premature discontinuation

Procedia PDF Downloads 113

Authors: Salvatore Brischetto, Domenico Cesare

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Major improvements in future aircraft and spacecraft could be those dependent on an increasing use of conventional and unconventional multilayered structures embedding composite materials, functionally graded materials, piezoelectric or piezomagnetic materials, and soft foam or honeycomb cores. Layers made of such materials can be combined in different ways to obtain structures that are able to fulfill several structural requirements. The next generation of aircraft and spacecraft will be manufactured as multilayered structures under the action of a combination of two or more physical fields. In multifield problems for multilayered structures, several physical fields (thermal, hygroscopic, electric and magnetic ones) interact each other with different levels of influence and importance. An exact 3D shell model is here proposed for these types of analyses. This model is based on a coupled system including 3D equilibrium equations, 3D Fourier heat conduction equation, 3D Fick diffusion equation and electric and magnetic divergence equations. The set of partial differential equations of second order in z is written using a mixed curvilinear orthogonal reference system valid for spherical and cylindrical shell panels, cylinders and plates. The order of partial differential equations is reduced to the first one thanks to the redoubling of the number of variables. The solution in the thickness z direction is obtained by means of the exponential matrix method and the correct imposition of interlaminar continuity conditions in terms of displacements, transverse stresses, electric and magnetic potentials, temperature, moisture content and transverse normal multifield fluxes. The investigated structures have simply supported sides in order to obtain a closed form solution in the in-plane directions. Moreover, a layerwise approach is proposed which allows a 3D correct description of multilayered anisotropic structures subjected to field loads. Several results will be proposed in tabular and graphical formto evaluate displacements, stresses and strains when mechanical loads, temperature gradients, moisture content gradients, electric potentials and magnetic potentials are applied at the external surfaces of the structures in steady-state conditions. In the case of inclusions of piezoelectric and piezomagnetic layers in the multilayered structures, so called smart structures are obtained. In this case, a free vibration analysis in open and closed circuit configurations and a static analysis for sensor and actuator applications will be proposed. The proposed results will be useful to better understand the physical and structural behaviour of multilayered advanced composite structures in the case of multifield interactions. Moreover, these analytical results could be used as reference solutions for those scientists interested in the development of 3D and 2D numerical shell/plate models based, for example, on the finite element approach or on the differential quadrature methodology. The correct impositions of boundary geometrical and load conditions, interlaminar continuity conditions and the zigzag behaviour description due to transverse anisotropy will be also discussed and verified.

Keywords: composite structures, 3D shell model, stress analysis, multifield loads, exponential matrix method, layer wise approach

Procedia PDF Downloads 38

Authors: Alison C. Essary, Victor Trastek

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Introduction: The current state of the health care system in the U.S. is characterized by an unprecedented number of people living with multiple chronic conditions, unsustainable rise in health care costs, inadequate access to care, and wide variation in health outcomes throughout the country. An estimated two-thirds of Americans are living with two or more chronic conditions, contributing to 75% of all health care spending. In 2013, the School for the Science of Health Care Delivery (SHCD) was charged with redesigning the health care system through education and research. Faculty in business, law, and public policy, and thought leaders in health care delivery, administration, public health and health IT created undergraduate, graduate, and executive academic programs to address this pressing need. Faculty and students work across disciplines, and with community partners and employers to improve care delivery and increase value for patients. Methods: Curricula apply content in health care administration and operations within the clinical context. Graduate modules are team-taught by faculty across academic units to model team-based practice. Seminars, team-based assignments, faculty mentoring, and applied projects are integral to student success. Cohort-driven models enhance networking and collaboration. This observational study evaluated two years of admissions data, and one year of graduate data to assess program outcomes and inform the current graduate-level curricula. Descriptive statistics includes means, percentages. Results: Fall 2013, the program received 51 applications. The mean GPA of the entering class of 37 students was 3.38. Ninety-seven percent of the fall 2013 cohort successfully completed the program (n=35). Sixty-six percent are currently employed in the health care industry (n=23). Of the remaining 12 graduates, two successfully matriculated to medical school; one works in the original field of study; four await results on the MCAT or DAT, and five were lost to follow up. Attrition of one student was attributed to non-academic reasons. Fall 2014, the program expanded to include both on-ground and online cohorts. Applications were evenly distributed between on-ground (n=70) and online (n=68). Thirty-eight students enrolled in the on-ground program. The mean GPA was 3.95. Ninety-five percent of students successfully completed the program (n=36). Thirty-six students enrolled in the online program. The mean GPA was 3.85. Graduate outcomes are pending. Discussion: Challenges include demographic variability between online and on-ground students; yet, both profiles are similar in that students intend to become change agents in the health care system. In the past two years, on-ground applications increased by 31%, persistence to graduation is > 95%, mean GPA is 3.67, graduates report admission to six U.S. medical schools, the Mayo Medical School integrates SHCD content within their curricula, and there is national interest in collaborating on industry and academic partnerships. This places SHCD at the forefront of developing innovative curricula in order to improve high-value, patient-centered care.

Keywords: delivery science, education, health care delivery, high-value care, innovation in education, patient-centered

Procedia PDF Downloads 258

Authors: Lauren B. Birney

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The BOP-CCERS (Billion Oyster Project- Curriculum and Community Enterprise for Restoration Science) Near-Peer Mentoring Program provides the long-term (five-year) support network to motivate and guide students toward restoration science-based CTE pathways. Students are selected from middle schools with actively participating BOP-CCERS teachers. Teachers will nominate students from grades 6-8 to join cohorts of between 10 and 15 students each. Cohorts are comprised primarily of students from the same school in order to facilitate mentors' travel logistics as well as to sustain connections with students and their families. Each cohort is matched with an exceptional undergraduate or graduate student, either a BOP research associate or STEM mentor recruited from collaborating City University of New York (CUNY) partner programs. In rare cases, an exceptional high school junior or senior may be matched with a cohort in addition to a research associate or graduate student. In no case is a high school student or minor be placed individually with a cohort. Mentors meet with students at least once per month and provide at least one offsite field visit per month, either to a local STEM Hub or research lab. Keeping with its five-year trajectory, the near-peer mentoring program will seek to retain students in the same cohort with the same mentor for the full duration of middle school and for at least two additional years of high school. Upon reaching the final quarter of 8th grade, the mentor will develop a meeting plan for each individual mentee. The mentee and the mentor will be required to meet individually or in small groups once per month. Once per quarter, individual meetings will be substituted for full cohort professional outings. The mentor will organize the entire cohort on a field visit or educational workshop with a museum or aquarium partner. In addition to the mentor-mentee relationship, each participating student will also be asked to conduct and present his or her own BOP field research. This research is ideally carried out with the support of the students’ regular high school STEM subject teacher; however, in cases where the teacher or school does not permit independent study, the student will be asked to conduct the research on an extracurricular basis. Near-peer mentoring affects students’ social identities and helps them to connect to role models from similar groups, ultimately giving them a sense of belonging. Qualitative and quantitative analytics were performed throughout the study. Interviews and focus groups also ensued. Additionally, an external evaluator was utilized to ensure project efficacy, efficiency, and effectiveness throughout the entire project. The BOP-CCERS Near Peer Mentoring program is a peer support network in which high school students with interest or experience in BOP (Billion Oyster Project) topics and activities (such as classroom oyster tanks, STEM Hubs, or digital platform research) provide mentorship and support for middle school or high school freshmen mentees. Peer mentoring not only empowers those students being taught but also increases the content knowledge and engagement of mentors. This support provides the necessary resources, structure, and tools to assist students in finding success.

Keywords: STEM education, environmental science, citizen science, near peer mentoring

Procedia PDF Downloads 67

Authors: Lynette Lincoln, Sunil S. More

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With the rising demand of sugar used today, it is proposed that world sugar is expected to escalate up to 203 million tonnes by 2021. Hydrolysis of sucrose (table sugar) into glucose and fructose equimolar mixture is catalyzed by β-D-fructofuranoside fructohydrolase (EC 3.2.1.26), commonly called as invertase. For fluid filled center in chocolates, preparation of artificial honey, as a sweetener and especially to ensure that food stuffs remain fresh, moist and soft for longer spans invertase is applied widely and is extensively being used. From an industrial perspective, properties such as increased solubility, osmotic pressure and prevention of crystallization of sugar in food products are highly desired. Screening for invertase does not involve plate assay/qualitative test to determine the enzyme production. In this study, we use a three-step screening strategy for identification of a novel bacterial isolate from soil which is positive for invertase production. The primary step was serial dilution of soil collected from sugarcane fields (black soil, Maddur region of Mandya district, Karnataka, India) was grown on a Czapek-Dox medium (pH 5.0) containing sucrose as the sole C-source. Only colonies with the capability to utilize/breakdown sucrose exhibited growth. Bacterial isolates released invertase in order to take up sucrose, splitting the disaccharide into simple sugars. Secondly, invertase activity was determined from cell free extract by measuring the glucose released in the medium at 540 nm. Morphological observation of the most potent bacteria was examined by several identification tests using Bergey’s manual, which enabled us to know the genus of the isolate to be Bacillus. Furthermore, this potent bacterial colony was subjected to 16S rDNA PCR amplification and a single discrete PCR amplicon band of 1500 bp was observed. The 16S rDNA sequence was used to carry out BLAST alignment search tool of NCBI Genbank database to obtain maximum identity score of sequence. Molecular sequencing and identification was performed by Xcelris Labs Ltd. (Ahmedabad, India). The colony was identified as Bacillus sp. BAB-3434, indicating to be the first novel strain for extracellular invertase production. Molasses, a by-product of the sugarcane industry is a dark viscous liquid obtained upon crystallization of sugar. An enhanced invertase production and optimization studies were carried out by one-factor-at-a-time approach. Crucial parameters such as time course (24 h), pH (6.0), temperature (45 °C), inoculum size (2% v/v), N-source (yeast extract, 0.2% w/v) and C-source (molasses, 4% v/v) were found to be optimum demonstrating an increased yield. The findings of this study reveal a simple screening method of an extracellular invertase from a rapidly growing Bacillus sp., and selection of best factors that elevate enzyme activity especially utilization of molasses which served as an ideal substrate and also as C-source, results in a cost-effective production under submerged conditions. The invert mixture could be a replacement for table sugar which is an economic advantage and reduce the tedious work of sugar growers. On-going studies involve purification of extracellular invertase and determination of transfructosylating activity as at high concentration of sucrose, invertase produces fructooligosaccharides (FOS) which possesses probiotic properties.

Keywords: Bacillus sp., invertase, molasses, screening, submerged fermentation

Procedia PDF Downloads 208

Authors: Aliasghar Mehdizadeh Dastjerdi, Francisco Camara Pereira

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The increasing complexity and demand of transport services strains transportation systems especially in urban areas with limited possibilities for building new infrastructure. The solution to this challenge requires changes of travel behavior. One of the proposed means to induce such change is multimodal travel apps. This paper describes a study of the intention to use a real-time multi-modal travel app aimed at motivating travel behavior change in the Greater Copenhagen Region (Denmark) toward promoting sustainable transport options. The proposed app is a multi-faceted smartphone app including both travel information and persuasive strategies such as health and environmental feedback, tailoring travel options, self-monitoring, tunneling users toward green behavior, social networking, nudging and gamification elements. The prospective for mobility management travel apps to stimulate sustainable mobility rests not only on the original and proper employment of the behavior change strategies, but also on explicitly anchoring it on established theoretical constructs from behavioral theories. The theoretical foundation is important because it positively and significantly influences the effectiveness of the system. However, there is a gap in current knowledge regarding the study of mobility-management travel app with support in behavioral theories, which should be explored further. This study addresses this gap by a social cognitive theory‐based examination. However, compare to conventional method in technology adoption research, this study adopts a reverse approach in which the associations between theoretical constructs are explored by Max-Min Hill-Climbing (MMHC) algorithm as a hybrid causal discovery method. A technology-use preference survey was designed to collect data. The survey elicited different groups of variables including (1) three groups of user’s motives for using the app including gain motives (e.g., saving travel time and cost), hedonic motives (e.g., enjoyment) and normative motives (e.g., less travel-related CO2 production), (2) technology-related self-concepts (i.e. technophile attitude) and (3) use Intention of the travel app. The questionnaire items led to the formulation of causal relationships discovery to learn the causal structure of the data. Causal relationships discovery from observational data is a critical challenge and it has applications in different research fields. The estimated causal structure shows that the two constructs of gain motives and technophilia have a causal effect on adoption intention. Likewise, there is a causal relationship from technophilia to both gain and hedonic motives. In line with the findings of the prior studies, it highlights the importance of functional value of the travel app as well as technology self-concept as two important variables for adoption intention. Furthermore, the results indicate the effect of technophile attitude on developing gain and hedonic motives. The causal structure shows hierarchical associations between the three groups of user’s motive. They can be explained by “frustration-regression” principle according to Alderfer's ERG (Existence, Relatedness and Growth) theory of needs meaning that a higher level need remains unfulfilled, a person may regress to lower level needs that appear easier to satisfy. To conclude, this study shows the capability of causal discovery methods to learn the causal structure of theoretical model, and accordingly interpret established associations.

Keywords: travel app, behavior change, persuasive technology, travel information, causality

Procedia PDF Downloads 115

Authors: Milos Travar, Jovana Nikolov, Andrej Vranicar, Natasa Todorovic

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Over the years, High Purity Germanium (HPGe) detectors proved to be an excellent practical tool and, as such, have established their today's wide use in low background γ-spectrometry. One of the advantages of gamma-ray spectrometry is its easy sample preparation as chemical processing and separation of the studied subject are not required. Thus, with a single measurement, one can simultaneously perform both qualitative and quantitative analysis. One of the most prominent features of HPGe detectors, besides their excellent efficiency, is their superior resolution. This feature virtually allows a researcher to perform a thorough analysis by discriminating photons of similar energies in the studied spectra where otherwise they would superimpose within a single-energy peak and, as such, could potentially scathe analysis and produce wrongly assessed results. Naturally, this feature is of great importance when the identification of radionuclides, as well as their activity concentrations, is being practiced where high precision comes as a necessity. In measurements of this nature, in order to be able to reproduce good and trustworthy results, one has to have initially performed an adequate full-energy peak (FEP) efficiency calibration of the used equipment. However, experimental determination of the response, i.e., efficiency curves for a given detector-sample configuration and its geometry, is not always easy and requires a certain set of reference calibration sources in order to account for and cover broader energy ranges of interest. With the goal of overcoming these difficulties, a lot of researches turned towards the application of different software toolkits that implement the Monte Carlo method (e.g., MCNP, FLUKA, PENELOPE, Geant4, etc.), as it has proven time and time again to be a very powerful tool. In the process of creating a reliable model, one has to have well-established and described specifications of the detector. Unfortunately, the documentation that manufacturers provide alongside the equipment is rarely sufficient enough for this purpose. Furthermore, certain parameters tend to evolve and change over time, especially with older equipment. Deterioration of these parameters consequently decreases the active volume of the crystal and can thus affect the efficiencies by a large margin if they are not properly taken into account. In this study, the optimisation method of two HPGe detectors through the implementation of the Geant4 toolkit developed by CERN is described, with the goal of further improving simulation accuracy in calculations of FEP efficiencies by investigating the influence of certain detector variables (e.g., crystal-to-window distance, dead layer thicknesses, inner crystal’s void dimensions, etc.). Detectors on which the optimisation procedures were carried out were a standard traditional co-axial extended range detector (XtRa HPGe, CANBERRA) and a broad energy range planar detector (BEGe, CANBERRA). Optimised models were verified through comparison with experimentally obtained data from measurements of a set of point-like radioactive sources. Acquired results of both detectors displayed good agreement with experimental data that falls under an average statistical uncertainty of ∼ 4.6% for XtRa and ∼ 1.8% for BEGe detector within the energy range of 59.4−1836.1 [keV] and 59.4−1212.9 [keV], respectively.

Keywords: HPGe detector, γ spectrometry, efficiency, Geant4 simulation, Monte Carlo method

Procedia PDF Downloads 90

Authors: Joy Chiu, Colin Hemez, Emma Ryan, Jia Sun, Robert Dubrow, Michael Pascucilla

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The popularity of recreational boating is on the rise in the United States, which raises numerous national-level challenges in the management of air and water pollution, aquatic habitat destruction, and waterway access. The need to control sewage discharge from recreational vessels underlies all of these challenges. The release of raw human waste into aquatic environments can lead to eutrophication and algal blooms; can increase human exposure to pathogenic viruses, bacteria, and parasites; can financially impact commercial shellfish harvest/fisheries and marine bathing areas; and can negatively affect access to recreational and/or commercial waterways to the detriment of local economies. Because of the damage that unregulated sewage discharge can do to environments and human health/marine life, recreational vessels in the United States are required by law to 'pump-out' sewage from their holding tanks into sewage treatment systems in all designated 'no discharge areas'. Many pump-out boats, which transfer waste out of recreational vessels, are operated and maintained using funds allocated through the Federal Clean Vessel Act (CVA). The East Shore District Health Department of Branford, Connecticut is protecting this estuary by pioneering the design and construction of the first-in-the-nation zero-emissions, the solar-electric pump-out boat of its size to replace one of its older traditional gasoline-powered models through a Connecticut Department of Energy and Environmental Protection CVA Grant. This study, conducted in collaboration with the East Shore District Health Department, the Connecticut Department of Energy and Environmental Protection, States Organization for Boating Access and Connecticut’s CVA program coordinators, had two aims: (1) To perform a national assessment of pump-out boat programs, supplemented by a limited international assessment, to establish best pump-out boat practices (regardless of how the boat is powered); and (2) to estimate the cost, greenhouse gas emissions, and environmental and public health impacts of solar-electric versus traditional gasoline-powered pump-out boats. A national survey was conducted of all CVA-funded pump-out program managers and selected pump-out boat operators to gauge best practices; costs associated with gasoline-powered pump-out boat operation and management; and the regional, cultural, and policy-related issues that might arise from the adoption of solar-electric pump-out boat technology. We also conducted life-cycle analyses of gasoline-powered and solar-electric pump-out boats to compare their greenhouse gas emissions; production of air, soil and water pollution; and impacts on human health. This work comprises the most comprehensive study into pump-out boating practices in the United States to date, in which information obtained at local, state, national, and international levels is synthesized. This study aims to enable CVA programs to make informed recommendations for sustainable pump-out boating practices and identifies the challenges and opportunities that remain for the wide adoption of solar-electric pump-out boat technology.

Keywords: pump-out boat, marine water, solar-electric, zero emissions

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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: Elena Parmentier, Henrik Endeman

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Introduction: Large mediastinal masses often present with diagnostic and clinical challenges due to compression of the respiratory and hemodynamic system. We present a case of a mediastinal mass with symptomatic mechanical compression of the trachea, resulting in challenging airway management. Methods: We present a case of 66-year-old male, complaining of progressive dysphagia. Initial esophagogastroscopy revealed a stenosis secondary to external compression, biopsies were inconclusive. Additional CT scan showed a large mediastinal mass of unknown origin, situated between the vertebrae and esophagus. Symptoms progressed and patient developed dyspnea and stridor. A new CT showed quick growth of the mass with compression of the trachea, subglottic to just above the carina. A tracheal covered stent was successfully placed. Endobronchial ultrasound revealed a large irregular mass without tracheal invasion, biopsies were taken. 4 days after stent placement, the patients’ condition deteriorated with worsening of stridor, dyspnea and desaturation. Migration of the tracheal stent into the right main bronchus was seen on chest X ray, with obstruction of the left main bronchus and secondary atelectasis. Different methods have been described in the literature for tracheobronchial stent removal (surgical, endoscopic, fluoroscopyguided), our first choice in this case was flexible bronchoscopy. However, this revealed tracheal compression above the migrated stent and passage of the scope occurred impossible. Patient was admitted to the ICU, high-flow nasal oxygen therapy was started and the situation stabilized, giving time for extensive assessment and preparation of the airway management approach. Close cooperation between the intensivist, pulmonologist, anesthesiologist and otorhinolaryngologist was essential. Results: In case of sudden deterioration, a protocol for emergency situations was made. Given the increased risk of additional tracheal compression after administration of neuromuscular blocking agents, an approach with awake fiberoptic intubation maintaining spontaneous ventilation was proposed. However, intubation without retrieval of the tracheal stent was found undesirable due to expected massive shunting over the left atelectatic lung. As rescue option, assistance of extracorporeal circulation was considered and perfusionist was kept on standby. The patient stayed stable and was transferred to the operating theatre. High frequency jet ventilation under general anesthesia resulted in desaturations up to 50%, making rigid bronchoscopy impossible. Subsequently an endotracheal tube size 8 could be placed successfully and the stent could be retrieved via bronchoscopy over (and with) the tube, after which the patient was reintubated. Finally, a tracheostomy (Shiley™ Tracheostomy Tube With Cuff, size 8) was placed, fiberoptic control showed a patent airway. Patient was readmitted to the ICU and could be quickly weaned of the ventilator. Pathology was positive for rhabdomyosarcoma, without indication for systemic therapy. Extensive surgery (laryngectomy, esophagectomy) was suggested, but patient refused and palliative care was started. Conclusion: Due to meticulous planning in an interdisciplinary team, we showed a successful airway management approach in this complicated case of critical airway compression secondary to a rare rhabdomyosarcoma, complicated by tracheal stent migration. Besides presenting our thoughts and considerations, we support exploring other possible approaches of this specific clinical problem.

Keywords: airway management, rhabdomyosarcoma, stent displacement, tracheal stenosis

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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: 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: Chris Fersterer, Col Fay, Tobias Danielmeier, Kat Achterberg, Scott Willis

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New Zealand, an island nation, has an extensive coastline peppered with small communities of iconic buildings known as Bachs. Post WWII, these modest buildings were constructed by their owners as retreats and generally were small, low cost, often using recycled material and often they fell below current acceptable building standards. In the latter part of the 20^th century, real estate prices in many of these communities remained low and these areas became permanent residences for people attracted to this affordable lifestyle choice. The Blueskin Resilient Communities Trust (BRCT) is an organisation that recognises the vulnerability of communities in low lying settlements as now being prone to increased flood threat brought about by climate change and sea level rise. Some of the inhabitants of Blueskin Bay, Otago, NZ have already found their properties to be un-insurable because of increased frequency of flood events and property values have slumped accordingly. Territorial authorities also acknowledge this increased risk and have created additional compliance measures for new buildings that are less than 2 m above tidal peaks. Community resilience becomes an additional concern where inhabitants are attracted to a lifestyle associated with a specific location and its people when this lifestyle is unable to be met in a suburban or city context. Traditional models of social housing fail to provide the sense of community connectedness and identity enjoyed by the current residents of Blueskin Bay. BRCT have partnered with the Otago Polytechnic Design School to design a new form of community housing that can react to this environmental change. It is a longitudinal project incorporating participatory approaches as a means of getting people ‘on board’, to understand complex systems and co-develop solutions. In the first period, they are seeking industry support and funding to develop a transportable and fully self-contained housing model that exploits current technologies. BRCT also hope that the building will become an educational tool to highlight climate change issues facing us today. This paper uses the Climate Safe House (CSH) as a case study for education in architectural sustainability through experiential learning offered as part of the Otago Polytechnics Bachelor of Design. Students engage with the project with research methodologies, including site surveys, resident interviews, data sourced from government agencies and physical modelling. The process involves collaboration across design disciplines including product and interior design but also includes connections with industry, both within the education institution and stakeholder industries introduced through BRCT. This project offers a rich learning environment where students become engaged through project based learning within a community of practice, including architecture, construction, energy and other related fields. The design outcomes are expressed in a series of public exhibitions and forums where community input is sought in a truly participatory process.

Keywords: community resilience, problem based learning, project based learning, case study

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Authors: Junkal Gutierrez, Hernane S. Barud, Sidney J. L. Ribeiro, Agnieszka Tercjak

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Nowadays the interest on green nanocomposites and on the development of more environmental friendly products has been increased. Bacterial cellulose has been recently investigated as an attractive environmentally friendly material for the preparation of low-cost nanocomposites. The formation of cellulose by laboratory bacterial cultures is an interesting and attractive biomimetic access to obtain pure cellulose with excellent properties. Additionally, properties as molar mass, molar mass distribution, and the supramolecular structure could be control using different bacterial strain, culture mediums and conditions, including the incorporation of different additives. This kind of cellulose is a natural nanomaterial, and therefore, it has a high surface-to-volume ratio which is highly advantageous in composites production. Such property combined with good biocompatibility, high tensile strength, and high crystallinity makes bacterial cellulose a potential material for applications in different fields. The aim of this investigation work was the fabrication of novel hybrid inorganic-organic composites based on bacterial cellulose, cultivated in our laboratory, as a template. This kind of biohybrid nanocomposites gathers together excellent properties of bacterial cellulose with the ones displayed by typical inorganic nanoparticles like optical, magnetic and electrical properties, luminescence, ionic conductivity and selectivity, as well as chemical or biochemical activity. In addition, the functionalization of cellulose with inorganic materials opens new pathways for the fabrication of novel multifunctional hybrid materials with promising properties for a wide range of applications namely electronic paper, flexible displays, solar cells, sensors, among others. In this work, different pathways for fabrication of multifunctional biohybrid nanopapers with tunable properties based on BC modified with amphiphilic poly(ethylene oxide-b-propylene oxide-b-ethylene oxide) (EPE) block copolymer, sol-gel synthesized nanoparticles (titanium, vanadium and a mixture of both oxides) and functionalized iron oxide nanoparticles will be presented. In situ (biosynthesized) and ex situ (at post-production level) approaches were successfully used to modify BC membranes. Bacterial cellulose based biocomposites modified with different EPE block copolymer contents were developed by in situ technique. Thus, BC growth conditions were manipulated to fabricate EPE/BC nanocomposite during the biosynthesis. Additionally, hybrid inorganic/organic nanocomposites based on BC membranes and inorganic nanoparticles were designed via ex-situ method, by immersion of never-dried BC membranes into different nanoparticle solutions. On the one hand, sol-gel synthesized nanoparticles (titanium, vanadium and a mixture of both oxides) and on the other hand superparamagnetic iron oxide nanoparticles (SPION), Fe2O3-PEO solution. The morphology of designed novel bionanocomposites hybrid materials was investigated by atomic force microscopy (AFM) and scanning electron microscopy (SEM). In order to characterized obtained materials from the point of view of future applications different techniques were employed. On the one hand, optical properties were analyzed by UV-vis spectroscopy and spectrofluorimetry and on the other hand electrical properties were studied at nano and macroscale using electric force microscopy (EFM), tunneling atomic force microscopy (TUNA) and Keithley semiconductor analyzer, respectively. Magnetic properties were measured by means of magnetic force microscopy (MFM). Additionally, mechanical properties were also analyzed.

Keywords: bacterial cellulose, block copolymer, advanced characterization techniques, nanoparticles

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Authors: Chandra Shekhar Prasad, Ludek Pesek Prasad

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In the present day fan blade of aero engine, turboprop propellers, gas turbine or steam turbine low-pressure blades are getting bigger, lighter and thus, become more flexible. Therefore, flutter, forced blade response and vibration related failure of the high aspect ratio blade are of main concern for the designers, thus need to be address properly in order to achieve successful component design. At the preliminary design stage large number of design iteration is need to achieve the utter free safe design. Most of the numerical method used for aeroelastic analysis is based on field-based methods such as finite difference method, finite element method, finite volume method or coupled. These numerical schemes are used to solve the coupled fluid Flow-Structural equation based on full Naiver-Stokes (NS) along with structural mechanics’ equations. These type of schemes provides very accurate results if modeled properly, however, they are computationally very expensive and need large computing recourse along with good personal expertise. Therefore, it is not the first choice for aeroelastic analysis during preliminary design phase. A reduced order aeroelastic model (ROAM) with acceptable accuracy and fast execution is more demanded at this stage. Similar ROAM are being used by other researchers for aeroelastic and force response analysis of turbomachinery. In the present paper new medium fidelity ROAM is successfully developed and implemented in numerical tool to simulated the aeroelastic stability phenomena in turbomachinery and well as flexible wings. In the present, a hybrid flow solver based on 3D viscous-inviscid coupled 3D panel method (PM) and 3d discrete vortex particle method (DVM) is developed, viscous parameters are estimated using boundary layer(BL) approach. This method can simulate flow separation and is a good compromise between accuracy and speed compared to CFD. In the second phase of the research work, the flow solver (PM) will be coupled with ROM non-linear beam element method (BEM) based FEM structural solver (with multibody capabilities) to perform the complete aeroelastic simulation of a steam turbine bladed disk, propellers, fan blades, aircraft wing etc. The partitioned based coupling approach is used for fluid-structure interaction (FSI). The numerical results are compared with experimental data for different test cases and for the blade cascade test case, experimental data is obtained from in-house lab experiments at IT CAS. Furthermore, the results from the new aeroelastic model will be compared with classical CFD-CSD based aeroelastic models. The proposed methodology for the aeroelastic stability analysis of gas turbine or steam turbine blades, or propellers or fan blades will provide researchers and engineers a fast, cost-effective and efficient tool for aeroelastic (classical flutter) analysis for different design at preliminary design stage where large numbers of design iteration are required in short time frame.

Keywords: aeroelasticity, beam element method (BEM), discrete vortex particle method (DVM), classical flutter, fluid-structure interaction (FSI), panel method, reduce order aeroelastic model (ROAM), turbomachinery, viscous-inviscid coupling

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