Search results for: dense retrieval

Authors: Andrew N. Saylor, James R. Peters

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Scoliosis is a complex 3D deformity of the thoracic and lumbar spines, clinically diagnosed by measurement of a Cobb angle of 10 degrees or more on a coronal X-ray. The Cobb angle is the angle made by the lines drawn along the proximal and distal endplates of the respective proximal and distal vertebrae comprising the curve. Traditionally, Cobb angles are measured manually using either a marker, straight edge, and protractor or image measurement software. The task of measuring the Cobb angle can also be represented by a function taking the spine geometry rendered using X-ray imaging as input and returning the approximate angle. Although the form of such a function may be unknown, it can be approximated using artificial neural networks (ANNs). The performance of ANNs is affected by many factors, including the choice of activation function and network architecture; however, the effects of these parameters on the accuracy of scoliotic deformity measurements are poorly understood. Therefore, the objective of this study was to systematically investigate the effect of ANN architecture and activation function on Cobb angle measurement from the coronal X-rays of scoliotic subjects. The data set for this study consisted of 609 coronal chest X-rays of scoliotic subjects divided into 481 training images and 128 test images. These data, which included labeled Cobb angle measurements, were obtained from the SpineWeb online database. In order to normalize the input data, each image was resized using bi-linear interpolation to a size of 500 × 187 pixels, and the pixel intensities were scaled to be between 0 and 1. A fully connected (dense) ANN with a fixed cost function (mean squared error), batch size (10), and learning rate (0.01) was developed using Python Version 3.7.3 and TensorFlow 1.13.1. The activation functions (sigmoid, hyperbolic tangent [tanh], or rectified linear units [ReLU]), number of hidden layers (1, 3, 5, or 10), and number of neurons per layer (10, 100, or 1000) were varied systematically to generate a total of 36 network conditions. Stochastic gradient descent with early stopping was used to train each network. Three trials were run per condition, and the final mean squared errors and mean absolute errors were averaged to quantify the network response for each condition. The network that performed the best used ReLU neurons had three hidden layers, and 100 neurons per layer. The average mean squared error of this network was 222.28 ± 30 degrees2, and the average mean absolute error was 11.96 ± 0.64 degrees. It is also notable that while most of the networks performed similarly, the networks using ReLU neurons, 10 hidden layers, and 1000 neurons per layer, and those using Tanh neurons, one hidden layer, and 10 neurons per layer performed markedly worse with average mean squared errors greater than 400 degrees2 and average mean absolute errors greater than 16 degrees. From the results of this study, it can be seen that the choice of ANN architecture and activation function has a clear impact on Cobb angle inference from coronal X-rays of scoliotic subjects.

Keywords: scoliosis, artificial neural networks, cobb angle, medical imaging

Procedia PDF Downloads 102

Authors: Amanda Kavner, Richard Lamb

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Faster growth in science and technology of other nations may make staying globally competitive more difficult without shifting focus on how science is taught in US classes. An integral part of learning science involves visual and spatial thinking since complex, and real-world phenomena are often expressed in visual, symbolic, and concrete modes. The primary barrier to spatial thinking and visual literacy in Science, Technology, Engineering, and Math (STEM) fields is representational competence, which includes the ability to generate, transform, analyze and explain representations, as opposed to generic spatial ability. Although the relationship is known between the foundational visual literacy and the domain-specific science literacy, science literacy as a function of science learning is still not well understood. Moreover, the need for a more reliable measure is necessary to design resources which enhance the fundamental visuospatial cognitive processes behind scientific literacy. To support the improvement of students’ representational competence, first visualization skills necessary to process these science representations needed to be identified, which necessitates the development of an instrument to quantitatively measure visual literacy. With such a measure, schools, teachers, and curriculum designers can target the individual skills necessary to improve students’ visual literacy, thereby increasing science achievement. This project details the development of an artificial neural network capable of measuring science literacy using functional Near-Infrared Spectroscopy (fNIR) data. This data was previously collected by Project LENS standing for Leveraging Expertise in Neurotechnologies, a Science of Learning Collaborative Network (SL-CN) of scholars of STEM Education from three US universities (NSF award 1540888), utilizing mental rotation tasks, to assess student visual literacy. Hemodynamic response data from fNIRsoft was exported as an Excel file, with 80 of both 2D Wedge and Dash models (dash) and 3D Stick and Ball models (BL). Complexity data were in an Excel workbook separated by the participant (ID), containing information for both types of tasks. After changing strings to numbers for analysis, spreadsheets with measurement data and complexity data were uploaded to RapidMiner’s TurboPrep and merged. Using RapidMiner Studio, a Gradient Boosted Trees artificial neural network (ANN) consisting of 140 trees with a maximum depth of 7 branches was developed, and 99.7% of the ANN predictions are accurate. The ANN determined the biggest predictors to a successful mental rotation are the individual problem number, the response time and fNIR optode #16, located along the right prefrontal cortex important in processing visuospatial working memory and episodic memory retrieval; both vital for science literacy. With an unbiased measurement of science literacy provided by psychophysiological measurements with an ANN for analysis, educators and curriculum designers will be able to create targeted classroom resources to help improve student visuospatial literacy, therefore improving science literacy.

Keywords: artificial intelligence, artificial neural network, machine learning, science literacy, neuroscience

Procedia PDF Downloads 93

Authors: Marta Malo, Carlota Soto, Carmen García-Rosales, Teresa Hernández

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SiC based composites are candidates for possible use as structural and functional materials in the future fusion reactors, the main role is intended for the blanket modules. In the blanket, the neutrons produced in the fusion reaction slow down and their energy is transformed into heat in order to finally generate electrical power. In the blanket design named Dual Coolant Lead Lithium (DCLL), a PbLi alloy for power conversion and tritium breeding circulates inside hollow channels called Flow Channel Inserts (FCIs). These FCI must protect the steel structures against the highly corrosive PbLi liquid and the high temperatures, but also provide electrical insulation in order to minimize magnetohydrodynamic interactions of the flowing liquid metal with the high magnetic field present in a magnetically confined fusion environment. Due to their nominally high temperature and radiation stability as well as corrosion resistance, SiC is the main choice for the flow channel inserts. The significantly lower manufacturing cost presents porous SiC (dense coating is required in order to assure protection against corrosion and as a tritium barrier) as a firm alternative to SiC/SiC composites for this purpose. This application requires the materials to be exposed to high radiation levels and extreme temperatures, conditions for which previous studies have shown noticeable changes in both the microstructure and the electrical properties of different types of silicon carbide. Both initial properties and radiation/temperature induced damage strongly depend on the crystal structure, polytype, impurities/additives that are determined by the fabrication process, so the development of a suitable material requires full control of these variables. For this work, several SiC samples with different percentage of porosity and sintering additives have been manufactured by the so-called sacrificial template method at the Ceit-IK4 Technology Center (San Sebastián, Spain), and characterized at Ciemat (Madrid, Spain). Electrical conductivity was measured as a function of temperature before and after irradiation with 1.8 MeV electrons in the Ciemat HVEC Van de Graaff accelerator up to 140 MGy (~ 2·10 -5 dpa). Radiation-induced conductivity (RIC) was also examined during irradiation at 550 ºC for different dose rates (from 0.5 to 5 kGy/s). Although no significant RIC was found in general for any of the samples, electrical conductivity increase with irradiation dose was observed to occur for some compositions with a linear tendency. However, first results indicate enhanced radiation resistance for coated samples. Preliminary thermogravimetric tests of selected samples, together with posterior XRD analysis allowed interpret radiation-induced modification of the electrical conductivity in terms of changes in the SiC crystalline structure. Further analysis is needed in order to confirm this.

Keywords: DCLL blanket, electrical conductivity, flow channel insert, porous SiC, radiation damage, thermal stability

Procedia PDF Downloads 177

Authors: Laith F. Gulli, Nicole M. Mallory

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The undertaking to develop a psychometric instrument is monumental. Understanding the relationship between variables and events is important in structural and exploratory design of psychometric instruments. Considering this, we describe a method used to group, pair and combine multiple Philosophical Assumption statements that assisted in development of a 13 item psychometric screening instrument. We abbreviated our Philosophical Assumptions (PA)s and added parameters, which were then condensed and mathematically modeled in a specific process. This model produced clusters of combinatorics which was utilized in design and development for 1) information retrieval and categorization 2) item development and 3) estimation of interactions among variables and likelihood of events. The psychometric screening instrument measured Knowledge, Assessment (education) and Beliefs (KAB) of New Addictions Research (NAR), which we called KABNAR. We obtained an overall internal consistency for the seven Likert belief items as measured by Cronbach’s α of .81 in the final study of 40 Clinicians, calculated by SPSS 14.0.1 for Windows. We constructed the instrument to begin with demographic items (degree/addictions certifications) for identification of target populations that practiced within Outpatient Substance Abuse Counseling (OSAC) settings. We then devised education items, beliefs items (seven items) and a modifiable “barrier from learning” item that consisted of six “choose any” choices. We also conceptualized a close relationship between identifying various degrees and certifications held by Outpatient Substance Abuse Therapists (OSAT) (the demographics domain) and all aspects of their education related to EB-NAR (past and present education and desired future training). We placed a descriptive (PA)1tx in both demographic and education domains to trace relationships of therapist education within these two domains. The two perceptions domains B1/b1 and B2/b2 represented different but interrelated perceptions from the therapist perspective. The belief items measured therapist perceptions concerning EB-NAR and therapist perceptions using EB-NAR during the beginning of outpatient addictions counseling. The (PA)s were written in simple words and descriptively accurate and concise. We then devised a list of parameters and appropriately matched them to each PA and devised descriptive parametric (PA)s in a domain categorized information grid. Descriptive parametric (PA)s were reduced to simple mathematical symbols. This made it easy to utilize parametric (PA)s into algorithms, combinatorics and clusters to develop larger information grids. By using matching combinatorics we took paired demographic and education domains with a subscript of 1 and matched them to the column with each B domain with subscript 1. Our algorithmic matching formed larger information grids with organized clusters in columns and rows. We repeated the process using different demographic, education and belief domains and devised multiple information grids with different parametric clusters and geometric arrays. We found benefit combining clusters by different geometric arrays, which enabled us to trace parametric variables and concepts. We were able to understand potential differences between dependent and independent variables and trace relationships of maximum likelihoods.

Keywords: psychometric, parametric, domains, grids, therapists

Procedia PDF Downloads 250

Authors: Anshu Anshu

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In the red corridor famed for the Left Wing Extremism, lies small district of Jamui in Bihar, India. The district lies at 24º20´ N latitude and 86º13´ E longitude, covering an area of 3,122.8 km2 The undulating topography, with widespread forests provides pristine environment for invigorating experience of tourists. Natural landscape in form of forests, wildlife, rivers, and cultural landscape dotted with historical and religious places is highly purposive for tourism. The study is primarily related to the identification of potential ecotourism sites, using Geographic Information System. Data preparation, analysis and finally identification of ecotourism sites is done. Secondary data used is Survey of India Topographical Sheets with R.F.1:50,000 covering the area of Jamui district. District Census Handbook, Census of India, 2011; ERDAS Imagine and Arc View is used for digitization and the creation of DEM’s (Digital Elevation Model) of the district, depicting the relief and topography and generate thematic maps. The thematic maps have been refined using the geo-processing tools. Buffer technique has been used for the accessibility analysis. Finally, all the maps, including the Buffer maps were overlaid to find out the areas which have potential for the development of ecotourism sites in the Jamui district. Spatial data - relief, slopes, settlements, transport network and forests of Jamui District were marked and identified, followed by Buffer Analysis that was used to find out the accessibility of features like roads, railway stations to the sites available for the development of ecotourism destinations. Buffer analysis is also carried out to get the spatial proximity of major river banks, lakes, and dam sites to be selected for promoting sustainable ecotourism. Overlay Analysis is conducted using the geo-processing tools. Digital Terrain Model (DEM) generated and relevant themes like roads, forest areas and settlements were draped on the DEM to make an assessment of the topography and other land uses of district to delineate potential zones of ecotourism development. Development of ecotourism in Jamui faces several challenges. The district lies in the portion of Bihar that is part of ‘red corridor’ of India. The hills and dense forests are the prominent hideouts and training ground for the extremists. It is well known that any kind of political instability, war, acts of violence directly influence the travel propensity and hinders all kind of non-essential travels to these areas. The development of ecotourism in the district can bring change and overall growth in this area with communities getting more involved in economically sustainable activities. It is a known fact that poverty and social exclusion are the main force that pushes people, resorting towards violence. All over the world tourism has been used as a tool to eradicate poverty and generate good will among people. Tourism, in sustainable form should be promoted in the district to integrate local communities in the development process and to distribute fruits of development with equity.

Keywords: buffer analysis, digital elevation model, ecotourism, red corridor

Procedia PDF Downloads 230

Authors: Xingyu Gao, Qiang Wu, Yuanyuan Liu, Yue Yang

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In the era of the knowledge economy, the relationship between scientific knowledge and patents has garnered significant attention. Understanding the intricate interplay between the foundations of science and technological innovation has emerged as a pivotal challenge for both researchers and policymakers. This study establishes a coupled network of artificial intelligence patents based on co-cited scientific papers. Leveraging centrality metrics from network analysis offers a fresh perspective on understanding the influence of information flow and knowledge sharing within the network on patent impact. The study initially obtained patent numbers for 446,890 granted US AI patents from the United States Patent and Trademark Office’s artificial intelligence patent database for the years 2002-2020. Subsequently, specific information regarding these patents was acquired using the Lens patent retrieval platform. Additionally, a search and deduplication process was performed on scientific non-patent references (SNPRs) using the Web of Science database, resulting in the selection of 184,603 patents that cited 37,467 unique SNPRs. Finally, this study constructs a coupled network comprising 59,379 artificial intelligence patents by utilizing scientific papers co-cited in patent backward citations. In this network, nodes represent patents, and if patents reference the same scientific papers, connections are established between them, serving as edges within the network. Nodes and edges collectively constitute the patent coupling network. Structural characteristics such as node degree centrality, betweenness centrality, and closeness centrality are employed to assess the scientific connections between patents, while citation count is utilized as a quantitative metric for patent influence. Finally, a negative binomial model is employed to test the nonlinear relationship between these network structural features and patent influence. The research findings indicate that network structural features such as node degree centrality, betweenness centrality, and closeness centrality exhibit inverted U-shaped relationships with patent influence. Specifically, as these centrality metrics increase, patent influence initially shows an upward trend, but once these features reach a certain threshold, patent influence starts to decline. This discovery suggests that moderate network centrality is beneficial for enhancing patent influence, while excessively high centrality may have a detrimental effect on patent influence. This finding offers crucial insights for policymakers, emphasizing the importance of encouraging moderate knowledge flow and sharing to promote innovation when formulating technology policies. It suggests that in certain situations, data sharing and integration can contribute to innovation. Consequently, policymakers can take measures to promote data-sharing policies, such as open data initiatives, to facilitate the flow of knowledge and the generation of innovation. Additionally, governments and relevant agencies can achieve broader knowledge dissemination by supporting collaborative research projects, adjusting intellectual property policies to enhance flexibility, or nurturing technology entrepreneurship ecosystems.

Keywords: centrality, patent coupling network, patent influence, social network analysis

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Authors: Yasemin Ilkay

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Urban spatial pattern interacts with the minds and bodies of citizens and influences their perception and attitudes, which leads to a two-folded map of the same space: physical and Psychogeographic maps. Psychogeography is a field of inquiry (rooted in literature and fiction) investigating how the environment affects the feelings and behaviors of individuals. This term was posed by Situationist International Movement in the 1950s by Guy Debord; in the course of time, the artistic framework evolved into a political issue, especially with the term Dérive, which indicates ‘deviation’ and ‘resistance’ to the existing spatial reality. The term Dérive appeared on the track of Flânéur after one hundred years; and turned out to be a political tool to transform everyday urban life. The three main concepts of psychogeography [walking, dérive, and palimpsest] construct the epistemological framework for a psychogeographic spatial analysis. Mental representations investigating this framework would provide a designer to capture the invisible layers of the gap between ‘how a space is conceived’ and ‘how the same space is perceived and experienced.’ This gap is a neglected but critical issue to discuss in the planning discipline, and psychogeography provides methodological inputs to cover the interrelation among top-down designs of urban patterning and bottom-up reproductions of ‘the soul’ of urban space at the intersection of geography and psychology. City centers and university campuses exemplify opposite poles of spatial organization and walking practice, which may result in differentiated spatial appropriation forms. There is a traditional city center in Van, located at the core of the city with a dense population and several activities, but not connected to Van Lake, which is the largest lake in the country. On the other hand, the university campus is located at the periphery, and although it has a promenade along the lake’s coast and a regional hospital, it presents a limited walking experience with ambiguous forms of spatial appropriation. The city center draws a vivid urban everyday life; however, the campus presents a relatively natural life far away from the center. This paper aims to reveal the differentiated psychogeographic maps of spatial appropriation at the city center vs. the university campus, which is located at the periphery of the city and along the coast of the largest lake in Turkey. The main question of the paper is, “how do the psychogeographic maps of spatial appropriation differentiate at the city center and university campus in Van within the walking experience with reference to the two-folded map assumption.” The experiential maps of a core group of 15 planning students will be created with the techniques of mental mapping, photographing, and narratives through attentive walks conducted together on selected routes; in addition to these attentive walks, 30 more in-depth interviews will be conducted by the core group. The narrative of psychogeographic mapping of spatial appropriation at the two spatial poles would display the conflicting soul of the city with reference to sub-behavioural regions of walking, differentiated forms of derive and layers of palimpsest.

Keywords: attentive walk, body, cognitive geography, derive, experiential maps, psychogeography, Van, Turkey

Procedia PDF Downloads 49

Authors: V. Mantey, N. Findlay, I. Maddox

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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

Procedia PDF Downloads 151

Authors: Aamir Shahzad, Mao-Gang He

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Currently, dusty plasmas motivated the researchers' widespread interest. Since the last two decades, substantial efforts have been made by the scientific and technological community to investigate the transport properties and their nonlinear behavior of three-dimensional and two-dimensional nonideal complex (dusty plasma) liquids (NICDPLs). Different calculations have been made to sustain and utilize strongly coupled NICDPLs because of their remarkable scientific and industrial applications. Understanding of the thermophysical properties of complex liquids under various conditions is of practical interest in the field of science and technology. The determination of thermal conductivity is also a demanding question for thermophysical researchers, due to some reasons; very few results are offered for this significant property. Lack of information of the thermal conductivity of dense and complex liquids at different parameters related to the industrial developments is a major barrier to quantitative knowledge of the heat flux flow from one medium to another medium or surface. The exact numerical investigation of transport properties of complex liquids is a fundamental research task in the field of thermophysics, as various transport data are closely related with the setup and confirmation of equations of state. A reliable knowledge of transport data is also important for an optimized design of processes and apparatus in various engineering and science fields (thermoelectric devices), and, in particular, the provision of precise data for the parameters of heat, mass, and momentum transport is required. One of the promising computational techniques, the homogenous nonequilibrium molecular dynamics (HNEMD) simulation, is over viewed with a special importance on the application to transport problems of complex liquids. This proposed work is particularly motivated by the FIRST TIME to modify the problem of heat conduction equations leads to polynomial velocity and temperature profiles algorithm for the investigation of transport properties with their nonlinear behaviors in the NICDPLs. The aim of proposed work is to implement a NEMDS algorithm (Poiseuille flow) and to delve the understanding of thermal conductivity behaviors in Yukawa liquids. The Yukawa system is equilibrated through the Gaussian thermostat in order to maintain the constant system temperature (canonical ensemble ≡ NVT)). The output steps will be developed between 3.0×105/ωp and 1.5×105/ωp simulation time steps for the computation of λ data. The HNEMD algorithm shows that the thermal conductivity is dependent on plasma parameters and the minimum value of lmin shifts toward higher G with an increase in k, as expected. New investigations give more reliable simulated data for the plasma conductivity than earlier known simulation data and generally the plasma λ0 by 2%-20%, depending on Γ and κ. It has been shown that the obtained results at normalized force field are in satisfactory agreement with various earlier simulation results. This algorithm shows that the new technique provides more accurate results with fast convergence and small size effects over a wide range of plasma states.

Keywords: molecular dynamics simulation, thermal conductivity, nonideal complex plasma, Poiseuille flow

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Authors: Yashas Bedre Raghavendra, Pim Vullers

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This study presents the design and implementation of an abstract cryptographic coprocessor, leveraging AMBA(Advanced Microcontroller Bus Architecture) protocols - APB (Advanced Peripheral Bus) and AHB (Advanced High-performance Bus), to enable seamless integration with the main CPU(Central processing unit) and enhance the coprocessor’s algorithm flexibility. The primary objective is to create a versatile coprocessor that can execute various cryptographic algorithms, including ECC(Elliptic-curve cryptography), RSA(Rivest–Shamir–Adleman), and AES (Advanced Encryption Standard) while providing a robust and secure solution for modern secure embedded systems. To achieve this goal, the coprocessor is equipped with a tightly coupled memory (TCM) for rapid data access during cryptographic operations. The TCM is placed within the coprocessor, ensuring quick retrieval of critical data and optimizing overall performance. Additionally, the program memory is positioned outside the coprocessor, allowing for easy updates and reconfiguration, which enhances adaptability to future algorithm implementations. Direct links are employed instead of DMA(Direct memory access) for data transfer, ensuring faster communication and reducing complexity. The AMBA-based communication architecture facilitates seamless interaction between the coprocessor and the main CPU, streamlining data flow and ensuring efficient utilization of system resources. The abstract nature of the coprocessor allows for easy integration of new cryptographic algorithms in the future. As the security landscape continues to evolve, the coprocessor can adapt and incorporate emerging algorithms, making it a future-proof solution for cryptographic processing. Furthermore, this study explores the addition of custom instructions into RISC-V ISE (Instruction Set Extension) to enhance cryptographic operations. By incorporating custom instructions specifically tailored for cryptographic algorithms, the coprocessor achieves higher efficiency and reduced cycles per instruction (CPI) compared to traditional instruction sets. The adoption of RISC-V 128-bit architecture significantly reduces the total number of instructions required for complex cryptographic tasks, leading to faster execution times and improved overall performance. Comparisons are made with 32-bit and 64-bit architectures, highlighting the advantages of the 128-bit architecture in terms of reduced instruction count and CPI. In conclusion, the abstract cryptographic coprocessor presented in this study offers significant advantages in terms of algorithm flexibility, security, and integration with the main CPU. By leveraging AMBA protocols and employing direct links for data transfer, the coprocessor achieves high-performance cryptographic operations without compromising system efficiency. With its TCM and external program memory, the coprocessor is capable of securely executing a wide range of cryptographic algorithms. This versatility and adaptability, coupled with the benefits of custom instructions and the 128-bit architecture, make it an invaluable asset for secure embedded systems, meeting the demands of modern cryptographic applications.

Keywords: abstract cryptographic coprocessor, AMBA protocols, ECC, RSA, AES, tightly coupled memory, secure embedded systems, RISC-V ISE, custom instructions, instruction count, cycles per instruction

Procedia PDF Downloads 45

Authors: Angelos Evangelou, Katerina Loizou, Loukas Koutsokeras, Orestes Marangos, Giorgos Constantinides, Stylianos Yiatros, Katerina Sofocleous, Vasileios Drakonakis

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Owing to their outstanding strength to weight properties, carbon fiber reinforced polymer (CFRPs) composites have attracted significant attention finding use in various fields (sports, automotive, transportation, etc.). The current momentum indicates that there is an increasing demand for their employment in high value bespoke applications such as avionics and electronic casings, damage sensing structures, EMI (electromagnetic interference) structures that dictate the use of materials with increased electrical conductivity both in-plane and through the thickness. Several efforts by research groups have focused on enhancing the through-thickness electrical conductivity of FRPs, in an attempt to combine the intrinsically high relative strengths exhibited with improved z-axis electrical response as well. However, only a limited number of studies deal with printing of nano-enhanced polymer inks to produce a pattern on dry fabric level that could be used to fabricate CFRPs with improved through thickness electrical conductivity. The present study investigates the employment of screen-printing process on technical dry fabrics using nano-reinforced polymer-based inks to achieve the required through thickness conductivity, opening new pathways for the application of fiber reinforced composites in niche products. Commercially available inks and in-house prepared inks reinforced with electrically conductive nanoparticles are employed, printed in different patterns. The aim of the present study is to investigate both the effect of the nanoparticle concentration as well as the droplet patterns (diameter, inter-droplet distance and coverage) to optimize printing for the desired level of conductivity enhancement in the lamina level. The electrical conductivity is measured initially at ink level to pinpoint the optimum concentrations to be employed using a “four-probe” configuration. Upon printing of the different patterns, the coverage of the dry fabric area is assessed along with the permeability of the resulting dry fabrics, in alignment with the fabrication of CFRPs that requires adequate wetting by the epoxy matrix. Results demonstrated increased electrical conductivities of the printed droplets, with increase of the conductivity from the benchmark value of 0.1 S/M to between 8 and 10 S/m. Printability of dense and dispersed patterns has exhibited promising results in terms of increasing the z-axis conductivity without inhibiting the penetration of the epoxy matrix at the processing stage of fiber reinforced composites. The high value and niche prospect of the resulting applications that can stem from CFRPs with increased through thickness electrical conductivities highlights the potential of the presented endeavor, signifying screen printing as the process to to nano-enable z-axis electrical conductivity in composite laminas. This work was co-funded by the European Regional Development Fund and the Republic of Cyprus through the Research and Innovation Foundation (Project: ENTERPRISES/0618/0013).

Keywords: CFRPs, conductivity, nano-reinforcement, screen-printing

Procedia PDF Downloads 130

Authors: Xingyu Gao, Qiang Wu

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Patents play a crucial role in protecting innovation and intellectual property. Early prediction of the impact of artificial intelligence (AI) patents helps researchers and companies allocate resources and make better decisions. Understanding the key factors that influence patent impact can assist researchers in gaining a better understanding of the evolution of AI technology and innovation trends. Therefore, identifying highly impactful patents early and providing support for them holds immeasurable value in accelerating technological progress, reducing research and development costs, and mitigating market positioning risks. Despite the extensive research on AI patents, accurately predicting their early impact remains a challenge. Traditional methods often consider only single factors or simple combinations, failing to comprehensively and accurately reflect the actual impact of patents. This paper utilized the artificial intelligence patent database from the United States Patent and Trademark Office and the Len.org patent retrieval platform to obtain specific information on 35,708 AI patents. Using six machine learning models, namely Multiple Linear Regression, Random Forest Regression, XGBoost Regression, LightGBM Regression, Support Vector Machine Regression, and K-Nearest Neighbors Regression, and using early indicators of patents as features, the paper comprehensively predicted the impact of patents from three aspects: technical, social, and economic. These aspects include the technical leadership of patents, the number of citations they receive, and their shared value. The SHAP (Shapley Additive exPlanations) metric was used to explain the predictions of the best model, quantifying the contribution of each feature to the model's predictions. The experimental results on the AI patent dataset indicate that, for all three target variables, LightGBM regression shows the best predictive performance. Specifically, patent novelty has the greatest impact on predicting the technical impact of patents and has a positive effect. Additionally, the number of owners, the number of backward citations, and the number of independent claims are all crucial and have a positive influence on predicting technical impact. In predicting the social impact of patents, the number of applicants is considered the most critical input variable, but it has a negative impact on social impact. At the same time, the number of independent claims, the number of owners, and the number of backward citations are also important predictive factors, and they have a positive effect on social impact. For predicting the economic impact of patents, the number of independent claims is considered the most important factor and has a positive impact on economic impact. The number of owners, the number of sibling countries or regions, and the size of the extended patent family also have a positive influence on economic impact. The study primarily relies on data from the United States Patent and Trademark Office for artificial intelligence patents. Future research could consider more comprehensive data sources, including artificial intelligence patent data, from a global perspective. While the study takes into account various factors, there may still be other important features not considered. In the future, factors such as patent implementation and market applications may be considered as they could have an impact on the influence of patents.

Keywords: patent influence, interpretable machine learning, predictive models, SHAP

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Authors: Bhupendra Kumar Poudel, Sadhana Amatya, Tirtha Maiya Shrestha, Bharatmani Pokhrel, Mohan Prasad Amatya

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Background: H. salicifolia is a dense, branched, multipurpose, deciduous, nitrogen fixing, thorny willow-like small to moderate tree, restricted to the Himalaya. Among the two species of Nepal (Hippophae salicifolia and H. tibetana), it has been traditionally used as food additive, anticancer (bark), and treating toothache, tooth inflammation (anti-inflammatory) and radiation injury; while people of Western Nepal have largely undermined its veiled treasure by using it for fuel, wood and soil stabilization only. Therefore, the main objective of this study was to explore biological properties (analgesic, antidiabetic, cytotoxic and anti-inflammatory properties of this plant. Methodology: The transverse section of leaves and stems were viewed under microscope. Extracts obtained from soxhlation subjected to tests for phytochemical and biological studies. Rats (used to study antidiabetic and anti-inflammatory properties) and mice (used to study analgesic, CNS depressant, muscle relaxant and locomotor properties) were assumed to be normally distributed; then ANOVA and post hoc tukey test was used to find significance. The data obtained were analyzed by SPSS 17 and Excel 2007. Results and Conclusion: Pharmacognostical analysis revealed the presence of long stellate trichomes, double layered vascular bundle 5-6 in number and double layered compact sclerenchyma. The preliminary phytochemical screening of the extracts was found to exhibit the positive reaction tests for glycoside, steroid, tannin, flavonoid, saponin, coumarin and reducing sugar. The brine shrimp lethality bioassay tested in 1000, 100 and 10 ppm revealed cytotoxic activity inherent in methanol, water, chloroform and ethyl acetate extracts with LC50 (μg/ml) values of 61.42, 99.77, 292.72 and 277.84 respectively. The cytotoxic activity may be due to presence of tannins in the constituents. Antimicrobial screening of the extracts by cup diffusion method using Staphylococcus aereus, Escherichia coli and Pseudomonas aeruginosa against standard antibiotics (oxacillin, gentamycin and amikacin respectively) portrayed no activity against the microorganisms tested. The methanol extract of the stems and leaves showed various pharmacological properties: and antidiabetic, anti-inflammatory, analgesic [chemical writhing method], CNS depressant, muscle relaxant and locomotor activities in a dose-dependent fashion, indicating the possibility of the presence of different constituents in the stems and leaves responsible for these biological activities. All the effects when analyzed by post hoc tukey test were found to be significant at 95% confidence level. The antidiabetic activity was presumed to be due to flavonoids present in extract. Therefore, it can be concluded that this plant’s secondary metabolites possessed strong antidiabetic, anti-inflammatory and cytotoxic activity which could be isolated for further investigation.

Keywords: Hippophae salicifolia, constituents, antidiabetic, inflammatory, brine shrimp

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Authors: V. Jayanthi

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Urbanization and pace of urbanization have increased tremendously in last few decades. More towns are now getting converted into cities. Urbanization trend is seen all over the world but is becoming most dominant in Asia. Today, the scale of urbanization in India is so huge that Indian cities are among the fastest-growing in the world, including Bangalore, Hyderabad, Pune, Chennai, Delhi, and Mumbai. Urbanization remains a single predominant factor that is continuously linked to the destruction of urban green spaces. With reference to Chennai as a case study, which is suffering from rapid deterioration of its green spaces, this paper sought to fill this gap by exploring key factors aside urbanization that is responsible for the destruction of green spaces. The paper relied on a research approach and triangulated data collection techniques such as interviews, focus group discussion, personal observation and retrieval of archival data. It was observed that apart from urbanization, problem of ownership of green space lands, low priority to green spaces, poor maintenance, enforcement of development controls, wastage of underpass spaces, and uncooperative attitudes of the general public, play a critical role in the destruction of urban green spaces. Therefore the paper narrows down to a point, that for a city to have a proper sustainable urban green space, broader city development plans are essential. Though rapid urbanization is an indicator of positive development, it is also accompanied by a host of challenges. Chennai lost a lot of greenery, as the city urbanized rapidly that led to a steep fall in vegetation cover. Environmental deterioration will be the big price we pay if Chennai continues to grow at the expense of greenery. Soaring skyscrapers, multistoried complexes, gated communities, and villas, frame the iconic skyline of today’s Chennai city which reveals that we overlook the importance of our green cover, which is important to balance our urban and lung spaces. Chennai, with a clumped landscape at the center of the city, is predicted to convert 36% of its total area into urban areas by 2026. One major issue is that a city designed and planned in isolation creates underused spaces all around the cities which are of negligence. These urban voids are dead, underused, unused spaces in the cities that are formed due to inefficient decision making, poor land management, and poor coordination. Urban voids have huge potential of creating a stronger urban fabric, exploited as public gathering spaces, pocket parks or plazas or just enhance public realm, rather than dumping of debris and encroachments. Flyovers need to justify their existence themselves by being more than just traffic and transport solutions. The vast, unused space below the Kathipara flyover is a case in point. This flyover connects three major routes: Tambaram, Koyambedu, and Adyar. This research will focus on the concept of urban voids, how these voids under the flyovers, can be used for place making process, how this space beneath flyovers which are neglected, can be a part of the urban realm through urban design and landscaping.

Keywords: landscape design, flyovers, public spaces, reclaiming lost spaces, urban voids

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Authors: Fernando Martinez Soto, Gaetano Di Mino

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The application of rubber into bituminous mixtures requires attention and care during mixing and compaction. Rubber modifies the properties because it reacts in the internal structure of bitumen at high temperatures changing the performance of the mixture (interaction process of solvents with binder-rubber aggregate). The main change is the increasing of the viscosity and elasticity of the binder due to the larger sizes of the rubber particles by dry process but, this positive effect is counteracted by short mixing times, compared to wet technology, and due to the transport processes, curing time and post-compaction of the mixtures. Therefore, negative effects as swelling of rubber particles, rebounding effect of the specimens and thermal changes by different expansion of the structure inside the mixtures, can change the mechanical properties of the rubberized blends. Based on the dry technology, different asphalt-rubber binders using devulcanized or natural rubber (truck and bus tread rubber), have served to demonstrate these effects and how to solve them into two dense-gap graded rubber modified asphalt concrete mixes (RUMAC) to enhance the stability, workability and durability of the compacted samples by Superpave gyratory compactor method. This paper specifies the procedures developed in the Department of Civil Engineering of the University of Palermo during September 2016 to March 2017, for characterizing the post-compaction and mix-stability of the one conventional mixture (hot mix asphalt without rubber) and two gap-graded rubberized asphalt mixes according granulometry for rail sub-ballast layers with nominal size of Ø22.4mm of aggregates according European standard. Thus, the main purpose of this laboratory research is the application of ambient ground rubber from scrap tires processed at conventional temperature (20ºC) inside hot bituminous mixtures (160-220ºC) as a substitute for 1.5%, 2% and 3% by weight of the total aggregates (3.2%, 4.2% and, 6.2% respectively by volumetric part of the limestone aggregates of bulk density equal to 2.81g/cm³) considered, not as a part of the asphalt binder. The reference bituminous mixture was designed with 4% of binder and ± 3% of air voids, manufactured for a conventional bitumen B50/70 at 160ºC-145ºC mix-compaction temperatures to guarantee the workability of the mixes. The proportions of rubber proposed are #60-40% for mixtures with 1.5 to 2% of rubber and, #20-80% for mixture with 3% of rubber (as example, a 60% of Ø0.4-2mm and 40% of Ø2-4mm). The temperature of the asphalt cement is between 160-180 ºC for mixing and 145-160 ºC for compaction, according to the optimal values for viscosity using Brookfield viscometer and 'ring and ball' - penetration tests. These crumb rubber particles act as a rubber-aggregate into the mixture, varying sizes between 0.4mm to 2mm in a first fraction, and 2-4mm as second proportion. Ambient ground rubber with a specific gravity of 1.154g/cm³ is used. The rubber is free of loose fabric, wire, and other contaminants. It was found optimal results in real beams and cylindrical specimens with each HMA mixture reducing the swelling effect. Different factors as temperature, particle sizes of rubber, number of cycles and pressures of compaction that affect the interaction process are explained.

Keywords: crumb-rubber, gyratory compactor, rebounding effect, superpave mix-design, swelling, sub-ballast railway

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Authors: Nada Poropat Jeletic, Gordana Hrzica

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Bilingual conversational corpora represent a meaningful and the most comprehensive data source for investigating the genuine contact phenomena in non-monitored bi-lingual speech productions. They can be particularly useful for bilingual research since some features of bilingual interaction can hardly be accessed with more traditional methodologies (e.g., elicitation tasks). The method of language sampling provides the resources for describing language interaction in a bilingual community and/or in bilingual situations (e.g. code-switching, amount of languages used, number of languages used, etc.). To capture these phenomena in genuine communication situations, such sampling should be as close as possible to spontaneous communication. Bilingual spoken corpus design is methodologically demanding. Therefore this paper aims at describing the methodological challenges that apply to the corpus design of the conversational corpus design of the Istrian Istrovenetian-Croatian Bilingual Corpus. Croatian is the first official language of the Croatian-Italian officially bilingual Istria County, while Istrovenetian is a diatopic subvariety of Venetian, a longlasting lingua franca in the Istrian peninsula, the mother tongue of the members of the Italian National Community in Istria and the primary code of informal everyday communication among the Istrian Italophone population. Within the CLARIN infrastructure, TalkBank is being used, as it provides relevant procedures for designing and analyzing bilingual corpora. Furthermore, it allows public availability allows for easy replication of studies and cumulative progress as a research community builds up around the corpus, while the tools developed within the field of corpus linguistics enable easy retrieval and analysis of information. The method of language sampling employed is kept at the level of spontaneous communication, in order to maximise the naturalness of the collected conversational data. All speakers have provided written informed consent in which they agree to be recorded at a random point within the period of one month after signing the consent. Participants are administered a background questionnaire providing information about the socioeconomic status and the exposure and language usage in the participants social networks. Recording data are being transcribed, phonologically adapted within a standard-sized orthographic form, coded and segmented (speech streams are being segmented into communication units based on syntactic criteria) and are being marked following the CHAT transcription system and its associated CLAN suite of programmes within the TalkBank toolkit. The corpus consists of transcribed sound recordings of 36 bilingual speakers, while the target is to publish the whole corpus by the end of 2020, by sampling spontaneous conversations among approximately 100 speakers from all the bilingual areas of Istria for ensuring representativeness (the participants are being recruited across three generations of native bilingual speakers in all the bilingual areas of the peninsula). Conversational corpora are still rare in TalkBank, so the Corpus will contribute to BilingBank as a highly relevant and scientifically reliable resource for an internationally established and active research community. The impact of the research of communities with societal bilingualism will contribute to the growing body of research on bilingualism and multilingualism, especially regarding topics of language dominance, language attrition and loss, interference and code-switching etc.

Keywords: conversational corpora, bilingual corpora, code-switching, language sampling, corpus design methodology

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Authors: Gabriela Borilova, Monika Petrakova, Petr Kralik

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Nowadays, European producers are increasingly interested in the production of halal meat products. Halal meat has been increasingly appearing in the EU's market network and meat products from European producers are being exported to Islamic countries. Halal criteria are mainly related to the origin of muscle used in production, and also to the way products are obtained and processed. Although the EU has legislatively addressed the question of food authenticity, the circumstances of previous years when products with undeclared horse or poultry meat content appeared on EU markets raised the question of the effectiveness of control mechanisms. Replacement of expensive or not-available types of meat for low-priced meat has been on a global scale for a long time. Likewise, halal products may be contaminated (falsified) by pork or food components obtained from pigs. These components include collagen, offal, pork fat, mechanically separated pork, emulsifier, blood, dried blood, dried blood plasma, gelatin, and others. These substances can influence sensory properties of the meat products - color, aroma, flavor, consistency and texture or they are added for preservation and stabilization. Food manufacturers sometimes access these substances mainly due to their dense availability and low prices. However, the use of these substances is not always declared on the product packaging. Verification of the presence of declared ingredients, including the detection of undeclared ingredients, are among the basic control procedures for determining the authenticity of food. Molecular biology methods, based on DNA analysis, offer rapid and sensitive testing. The PCR method and its modification can be successfully used to identify animal species in single- and multi-ingredient raw and processed foods and qPCR is the first choice for food analysis. Like all PCR-based methods, it is simple to implement and its greatest advantage is the absence of post-PCR visualization by electrophoresis. qPCR allows detection of trace amounts of nucleic acids, and by comparing an unknown sample with a calibration curve, it can also provide information on the absolute quantity of individual components in the sample. Our study addresses a problem that is related to the fact that the molecular biological approach of most of the work associated with the identification and quantification of animal species is based on the construction of specific primers amplifying the selected section of the mitochondrial genome. In addition, the sections amplified in conventional PCR are relatively long (hundreds of bp) and unsuitable for use in qPCR, because in DNA fragmentation, amplification of long target sequences is quite limited. Our study focuses on finding a suitable genomic DNA target and optimizing qPCR to reduce variability and distortion of results, which is necessary for the correct interpretation of quantification results. In halal products, the impact of falsification of meat products by the addition of components derived from pigs is all the greater that it is not just about the economic aspect but above all about the religious and social aspect. This work was supported by the Ministry of Agriculture of the Czech Republic (QJ1530107).

Keywords: food fraud, halal food, pork, qPCR

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Authors: Serap Durkut, A. Eser Elcin, Y. Murat Elcin

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Stimuli-sensitive polymeric hydrogels have received extensive attention in the biomedical field due to their sensitivity to physical and chemical stimuli (temperature, pH, ionic strength, light, etc.). This study describes the rheological properties of a novel thermoresponsive poly(N-vinylcaprolactam)-g-collagen hydrogel. In the study, we first synthesized a facile and novel synthetic carboxyl group-terminated thermo-responsive poly(N-vinylcaprolactam)-COOH (PNVCL-COOH) via free radical polymerization. Further, this compound was effectively grafted with native collagen, by utilizing the covalent bond between the carboxylic acid groups at the end of the chains and amine groups of the collagen using cross-linking agent (EDC/NHS), forming PNVCL-g-Col. Newly-formed hybrid hydrogel displayed novel properties, such as increased mechanical strength and thermoresponsive characteristics. PNVCL-g-Col showed low critical solution temperature (LCST) at 38ºC, which is very close to the body temperature. Rheological studies determine structural–mechanical properties of the materials and serve as a valuable tool for characterizing. The rheological properties of hydrogels are described in terms of two dynamic mechanical properties: the elastic modulus G′ (also known as dynamic rigidity) representing the reversible stored energy of the system, and the viscous modulus G″, representing the irreversible energy loss. In order to characterize the PNVCL-g-Col, the rheological properties were measured in terms of the function of temperature and time during phase transition. Below the LCST, favorable interactions allowed the dissolution of the polymer in water via hydrogen bonding. At temperatures above the LCST, PNVCL molecules within PNVCL-g-Col aggregated due to dehydration, causing the hydrogel structure to become dense. When the temperature reached ~36ºC, both the G′ and G″ values crossed over. This indicates that PNVCL-g-Col underwent a sol-gel transition, forming an elastic network. Following temperature plateau at 38ºC, near human body temperature the sample displayed stable elastic network characteristics. The G′ and G″ values of the PNVCL-g-Col solutions sharply increased at 6-9 minute interval, due to rapid transformation into gel-like state and formation of elastic networks. Copolymerization with collagen leads to an increase in G′, as collagen structure contains a flexible polymer chain, which bestows its elastic properties. Elasticity of the proposed structure correlates with the number of intermolecular cross-links in the hydrogel network, increasing viscosity. However, at 8 minutes, G′ and G″ values sharply decreased for pure collagen solutions due to the decomposition of the elastic and viscose network. Complex viscosity is related to the mechanical performance and resistance opposing deformation of the hydrogel. Complex viscosity of PNVCL-g-Col hydrogel was drastically changed with temperature and the mechanical performance of PNVCL-g-Col hydrogel network increased, exhibiting lesser deformation. Rheological assessment of the novel thermo-responsive PNVCL-g-Col hydrogel, exhibited that the network has stronger mechanical properties due to both permanent stable covalent bonds and physical interactions, such as hydrogen- and hydrophobic bonds depending on temperature.

Keywords: poly(N-vinylcaprolactam)-g-collagen, thermoresponsive polymer, rheology, elastic modulus, stimuli-sensitive

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Authors: Nabamita Nath, Sanghamitra Sarkar

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Urban development in traditional neighbourhoods of cities is undergoing a sea change due to imposition of irregular development patterns on a predominantly inclusive urban fabric. In recent times, traditional neighbourhoods of Kolkata have experienced irregular urban development which has resulted in transformation of its immediate urban character. The goal is to study and analyse impact of new urban developments within traditional neighbourhoods of Kolkata and establish development guidelines to balance the old with the new. Various cities predominantly in third world countries are also experiencing similar development patterns in their traditional neighbourhoods. Existing literature surveys of development patterns in such neighbourhoods have established 9 major parameters viz. edge, movement, node, landmark, size-density, pattern-grain-texture, open spaces, urban spaces, urban form and views-vistas of the neighbourhood. To evaluate impact of urban development in traditional neighbourhoods of Kolkata, 3 different areas have been chronologically selected based on their settlement patterns. Parameters established through literature surveys have been applied to the selected areas to study and analyse the existing patterns of development. The main sources of this study included extensive on-site surveys, academic archive, census data, organisational records and informational websites. Applying the established parameters, 5 major conclusions were derived. Firstly, it was found that pedestrian friendly neighbourhoods of the city were becoming more car-centric. This has resulted in loss of interactive and social spaces which defined the cultural heritage of Kolkata. Secondly, the urban pattern which was composed of dense and compact fabric is gradually losing its character due to incorporation of new building typologies. Thirdly, the new building typologies include gated communities with private open spaces which is a stark departure from the existing built typology. However, these open spaces have not contributed in creation of inclusive public places for the community which are a significant part of such heritage neighbourhood precincts. Fourthly, commercial zones that primarily developed along major access routes have now infiltrated within these neighbourhoods. Gated communities do not favour formation of on-street commercial activities generating haphazard development patterns. Lastly, individual residential buildings that reflected Indo-saracenic and Neo-gothic architectural styles are converting into multi-storeyed residential apartments. As a result, the axis that created a definite visual identity for a neighbourhood is progressively following an irregular pattern. Thus, uniformity of the old skyline is gradually becoming inconsistent. The major issue currently is threat caused by irregular urban development to heritage zones and buildings of traditional neighbourhoods. Streets, lanes, courtyards, open spaces and buildings of old neighbourhoods imparted a unique cultural identity to the city that is disappearing with emerging urban development patterns. It has been concluded that specific guidelines for urban development should be regulated primarily based on existing urban form of traditional neighbourhoods. Such neighbourhood development strategies should be formulated for various cities of third world countries to control irregular developments thereby balancing heritage and development.

Keywords: heritage, Kolkata, traditional neighbourhood, urban development

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Authors: Vinti Davar

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Introduction: Childhood overweight increases the risk for certain medical and psychological conditions. Millions of school-age children worldwide are affected by serious yet easily treatable and preventable illnesses that inhibit their ability to learn. Healthier children stay in school longer, attend more regularly, learn more and become healthier and more productive adults. Schools are an important setting for nutrition education because one can reach most children, teachers and parents. These years offer a key window for shaping their lifetime habits, which have an impact on their health throughout life. Against this background, an attempt was made to impart nutrition education to school children in Haryana state of India to promote healthy food choices and assess the effectiveness of this program. Methodology: This study was completed in two phases. During the first phase, pre-intervention anthropometric and dietary survey was conducted; the teaching materials for nutrition intervention program were developed and tested; and the questionnaire was validated. In the second phase, an intervention was implemented in two schools of Kurukshetra, Haryana for six months by personal visits once a week. A total of 350 children in the age group of 6-12 years were selected. Out of these, 279 children, 153 boys and 126 girls completed the study. The subjects were divided into four groups namely: underweight, normal, overweight and obese based on body mass index-for-age categories. A power point colorful presentation to improve the quality of tiffin, snacks and meals emphasizing inclusion of all food groups especially vegetables every day and fruits at least 3-4 days per week was used. An extra 20 minutes of aerobic exercise daily was likewise organized and a healthy school environment created. Provision of clean drinking water by school authorities was ensured. Selling of soft drinks and energy-dense snacks in the school canteen as well as advertisements about soft drink and snacks on the school walls were banned. Post intervention, anthropometric indices and food selections were reassessed. Results: The results of this study reiterate the critical role of nutrition education and promotion in improving the healthier food choices by school children. It was observed that normal, overweight and obese children participating in nutrition education intervention program significantly (p≤0.05) increased their daily seasonal fruit and vegetable consumption. Fat and oil consumption was significantly reduced by overweight and obese subjects. Fast food intake was controlled by obese children. The nutrition knowledge of school children significantly improved (p≤0.05) from pre to post intervention. A highly significant increase (p≤0.00) was noted in the nutrition attitude score after intervention in all four groups. Conclusion: This study has shown that a well-planned nutrition education program could improve nutrition knowledge and promote positive changes in healthy food choices. A nutrition program inculcates wholesome eating and active life style habits in children and adolescents that could not only prevent them from chronic diseases and early death but also reduce healthcare cost and enhance the quality of life of citizens and thereby nations.

Keywords: children, eating habits healthy food, obesity, school going, fast foods

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Authors: Diana Reckien

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Vulnerability assessments are increasingly used to support policy-making in complex environments, like urban areas. Usually, vulnerability studies include the construction of aggregate (sub-) indices and the subsequent mapping of indices across an area of interest. Vulnerability studies show a couple of advantages: they are great communication tools, can inform a wider general debate about environmental issues, and can help allocating and efficiently targeting scarce resources for adaptation policy and planning. However, they also have a number of challenges: Vulnerability assessments are constructed on the basis of a wide range of methodologies and there is no single framework or methodology that has proven to serve best in certain environments, indicators vary highly according to the spatial scale used, different variables and metrics produce different results, and aggregate or composite vulnerability indicators that are mapped easily distort or bias the picture of vulnerability as they hide the underlying causes of vulnerability and level out conflicting reasons of vulnerability in space. So, there is urgent need to further develop the methodology of vulnerability studies towards a common framework, which is one reason of the paper. We introduce a social vulnerability approach, which is compared with other approaches of bio-physical or sectoral vulnerability studies relatively developed in terms of a common methodology for index construction, guidelines for mapping, assessment of sensitivity, and verification of variables. Two approaches are commonly pursued in the literature. The first one is an additive approach, in which all potentially influential variables are weighted according to their importance for the vulnerability aspect, and then added to form a composite vulnerability index per unit area. The second approach includes variable reduction, mostly Principal Component Analysis (PCA) that reduces the number of variables that are interrelated into a smaller number of less correlating components, which are also added to form a composite index. We test these two approaches of constructing indices on the area of New York City as well as two different metrics of variables used as input and compare the outcome for the 5 boroughs of NY. Our analysis yields that the mapping exercise yields particularly different results in the outer regions and parts of the boroughs, such as Outer Queens and Staten Island. However, some of these parts, particularly the coastal areas receive the highest attention in the current adaptation policy. We imply from this that the current adaptation policy and practice in NY might need to be discussed, as these outer urban areas show relatively low social vulnerability as compared with the more central parts, i.e. the high dense areas of Manhattan, Central Brooklyn, Central Queens and the Southern Bronx. The inner urban parts receive lesser adaptation attention, but bear a higher risk of damage in case of hazards in those areas. This is conceivable, e.g., during large heatwaves, which would more affect more the inner and poorer parts of the city as compared with the outer urban areas. In light of the recent planning practice of NY one needs to question and discuss who in NY makes adaptation policy for whom, but the presented analyses points towards an under representation of the needs of the socially vulnerable population, such as the poor, the elderly, and ethnic minorities, in the current adaptation practice in New York City.

Keywords: vulnerability mapping, social vulnerability, additive approach, Principal Component Analysis (PCA), New York City, United States, adaptation, social sensitivity

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Authors: Tim Bolle, Franziska Kreimendahl, Thomas Gries, Stefan Jockenhoevel

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The therapeutic treatment of extensive, deep wounds is limited. Autologous split-skin grafts are used as a so-called ‘gold standard’. Most common deficits are the defects at the donor site, the risk of scarring as well as the limited availability and quality of the autologous grafts. The aim of this project is a tissue engineered dermal-epidermal skin replacement to overcome the limitations of the gold standard. A key requirement for the development of such a three-dimensional implant is the formation of a functional capillary-like network inside the implant to ensure a sufficient nutrient and gas supply. Tailored three-dimensional warp knitted spacer fabrics are used to reinforce the mechanically week fibrin gel-based scaffold and further to create a directed in vitro pre-vascularization along the parallel-oriented pile yarns within a co-culture. In this study various three-dimensional warp knitted spacer fabrics were developed in a factorial design to analyze the influence of the machine parameters such as the stitch density and the pattern of the fabric on the scaffold performance and further to determine suitable parameters for a successful fibrin gel-incorporation and a physiological performance of the scaffold. The fabrics were manufactured on a Karl Mayer double-bar raschel machine DR 16 EEC/EAC. A fine machine gauge of E30 was used to ensure a high pile yarn density for sufficient nutrient, gas and waste exchange. In order to ensure a high mechanical stability of the graft, the fabrics were made of biocompatible PVDF yarns. Key parameters such as the pore size, porosity and stress/strain behavior were investigated under standardized, controlled climate conditions. The influence of the input parameters on the mechanical and morphological properties as well as the ability of fibrin gel incorporation into the spacer fabric was analyzed. Subsequently, the pile yarns of the spacer fabrics were colonized with Human Umbilical Vein Endothelial Cells (HUVEC) to analyze the ability of the fabric to further function as a guiding structure for a directed vascularization. The cells were stained with DAPI and investigated using fluorescence microscopy. The analysis revealed that the stitch density and the binding pattern have a strong influence on both the mechanical and morphological properties of the fabric. As expected, the incorporation of the fibrin gel was significantly improved with higher pore sizes and porosities, whereas the mechanical strength decreases. Furthermore, the colonization trials revealed a high cell distribution and density on the pile yarns of the spacer fabrics. For a tailored reinforcing structure, the minimum porosity and pore size needs to be evaluated which still ensures a complete incorporation of the reinforcing structure into the fibrin gel matrix. That will enable a mechanically stable dermal graft with a dense vascular network for a sufficient nutrient and oxygen supply of the cells. The results are promising for subsequent research in the field of reinforcing mechanically weak biological scaffolds and develop functional three-dimensional scaffolds with an oriented pre-vascularization.

Keywords: fibrin-gel, skin replacement, spacer fabric, pre-vascularization

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Authors: Nitika Sharma, Yogesh Jain

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Introduction: An efficient Information System helps in improving the service delivery as well provides the foundation for policy and regulation of other building blocks of Health System. Health care organizations require an integrated working of its various sub-systems. An efficient EMR software boosts the teamwork amongst the various sub-systems thereby resulting in improved service delivery. Although there has been a huge impetus to EMR under the Digital India initiative, it has still not been mandated in India. It is generally implemented in huge funded public or private healthcare organizations only. Objective: The study was conducted to understand the factors that lead to the successful adoption of an affordable EMR in the low level healthcare organization. It intended to understand the design of the EMR and address the solutions to the challenges faced in adoption of the EMR. Methodology: The study was conducted in a non-profit registered Healthcare organization that has been providing healthcare facilities to more than 2500 villages including certain areas that are difficult to access. The data was collected with help of field notes, in-depth interviews and participant observation. A total of 16 participants using the EMR from different departments were enrolled via purposive sampling technique. The participants included in the study were working in the organization before the implementation of the EMR system. The study was conducted in one month period from 25 June-20 July 2018. The Ethical approval was taken from the institute along with prior approval of the participants. Data analysis: A word document of more than 4000 words was obtained after transcribing and translating the answers of respondents. It was further analyzed by focused coding, a line by line review of the transcripts, underlining words, phrases or sentences that might suggest themes to do thematic narrative analysis. Results: Based on the answers the results were thematically grouped under four headings: 1. governance of organization, 2. architecture and design of the software, 3. features of the software, 4. challenges faced in adoption and the solutions to address them. It was inferred that the successful implementation was attributed to the easy and comprehensive design of the system which has facilitated not only easy data storage and retrieval but contributes in constructing a decision support system for the staff. Portability has lead to increased acceptance by physicians. The proper division of labor, increased efficiency of staff, incorporation of auto-correction features and facilitation of task shifting has lead to increased acceptance amongst the users of various departments. Geographical inhibitions, low computer literacy and high patient load were the major challenges faced during its implementation. Despite of dual efforts made both by the architects and administrators to combat these challenges, there are still certain ongoing challenges faced by organization. Conclusion: Whenever any new technology is adopted there are certain innovators, early adopters, late adopters and laggards. The same pattern was followed in adoption of this software. He challenges were overcome with joint efforts of organization administrators and users as well. Thereby this case study provides a framework of implementing similar systems in public sector of countries that are struggling for digitizing the healthcare in presence of crunch of human and financial resources.

Keywords: EMR, healthcare technology, e-health, EHR

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Authors: Hameed Rukayat Opeyemi, Pericles Pilidis Pagone Emmanuele, Agbadede Roupa, Allison Isaiah

Abstract:

Climate change represents one of the single most challenging problems facing the world today. According to the National Oceanic and Administrative Association, Atmospheric temperature rose almost 25% since 1958, Artic sea ice has shrunk 40% since 1959 and global sea levels have risen more than 5.5cm since 1990. Power plants are the major culprits of GHG emission to the atmosphere. Several technologies have been proposed to reduce the amount of GHG emitted to the atmosphere from power plant, one of which is the less researched Advanced zero-emission power plant. The advanced zero emission power plants make use of mixed conductive membrane (MCM) reactor also known as oxygen transfer membrane (OTM) for oxygen transfer. The MCM employs membrane separation process. The membrane separation process was first introduced in 1899 when Walter Hermann Nernst investigated electric current between metals and solutions. He found that when a dense ceramic is heated, the current of oxygen molecules move through it. In the bid to curb the amount of GHG emitted to the atmosphere, the membrane separation process was applied to the field of power engineering in the low carbon cycle known as the Advanced zero emission power plant (AZEP cycle). The AZEP cycle was originally invented by Norsk Hydro, Norway and ABB Alstom power (now known as Demag Delaval Industrial turbomachinery AB), Sweden. The AZEP drew a lot of attention because its ability to capture ~100% CO2 and also boasts of about 30-50% cost reduction compared to other carbon abatement technologies, the penalty in efficiency is also not as much as its counterparts and crowns it with almost zero NOx emissions due to very low nitrogen concentrations in the working fluid. The advanced zero emission power plants differ from a conventional gas turbine in the sense that its combustor is substituted with the mixed conductive membrane (MCM-reactor). The MCM-reactor is made up of the combustor, low-temperature heat exchanger LTHX (referred to by some authors as air preheater the mixed conductive membrane responsible for oxygen transfer and the high-temperature heat exchanger and in some layouts, the bleed gas heat exchanger. Air is taken in by the compressor and compressed to a temperature of about 723 Kelvin and pressure of 2 Mega-Pascals. The membrane area needed for oxygen transfer is reduced by increasing the temperature of 90% of the air using the LTHX; the temperature is also increased to facilitate oxygen transfer through the membrane. The air stream enters the LTHX through the transition duct leading to inlet of the LTHX. The temperature of the air stream is then increased to about 1150 K depending on the design point specification of the plant and the efficiency of the heat exchanging system. The amount of oxygen transported through the membrane is directly proportional to the temperature of air going through the membrane. The AZEP cycle was developed using the Fortran software and economic analysis was conducted using excel and Matlab followed by optimization case study. The Simple bleed gas heat exchange layout (100 % CO2 capture), Bleed gas heat exchanger layout with flue gas turbine (100 % CO2 capture), Pre-expansion reheating layout (Sequential burning layout)–AZEP 85% (85% CO2 capture) and Pre-expansion reheating layout (Sequential burning layout) with flue gas turbine–AZEP 85% (85% CO2 capture). This paper discusses monte carlo risk analysis of four possible layouts of the AZEP cycle.

Keywords: gas turbine, global warming, green house gas, fossil fuel power plants

Procedia PDF Downloads 369

Authors: Lassi Lehto, Jaakko Kahkonen, Juha Oksanen, Tapani Sarjakoski

Abstract:

The use of raster-formatted data sets in geospatial analysis is increasing rapidly. At the same time, geographic data are being introduced into disciplines outside the traditional domain of geoinformatics, like climate change, intelligent transport, and immigration studies. These developments call for better methods to deliver raster geodata in an efficient and easy-to-use manner. Data cube technologies have traditionally been used in the geospatial domain for managing Earth Observation data sets that have strict requirements for effective handling of time series. The same approach and methodologies can also be applied in managing other types of geospatial data sets. A cloud service-based geodata cube, called GeoCubes Finland, has been developed to support online delivery and analysis of most important geospatial data sets with national coverage. The main target group of the service is the academic research institutes in the country. The most significant aspects of the GeoCubes data repository include the use of multiple resolution levels, cloud-optimized file structure, and a customized, flexible content access API. Input data sets are pre-processed while being ingested into the repository to bring them into a harmonized form in aspects like georeferencing, sampling resolutions, spatial subdivision, and value encoding. All the resolution levels are created using an appropriate generalization method, selected depending on the nature of the source data set. Multiple pre-processed resolutions enable new kinds of online analysis approaches to be introduced. Analysis processes based on interactive visual exploration can be effectively carried out, as the level of resolution most close to the visual scale can always be used. In the same way, statistical analysis can be carried out on resolution levels that best reflect the scale of the phenomenon being studied. Access times remain close to constant, independent of the scale applied in the application. The cloud service-based approach, applied in the GeoCubes Finland repository, enables analysis operations to be performed on the server platform, thus making high-performance computing facilities easily accessible. The developed GeoCubes API supports this kind of approach for online analysis. The use of cloud-optimized file structures in data storage enables the fast extraction of subareas. The access API allows for the use of vector-formatted administrative areas and user-defined polygons as definitions of subareas for data retrieval. Administrative areas of the country in four levels are available readily from the GeoCubes platform. In addition to direct delivery of raster data, the service also supports the so-called virtual file format, in which only a small text file is first downloaded. The text file contains links to the raster content on the service platform. The actual raster data is downloaded on demand, from the spatial area and resolution level required in each stage of the application. By the geodata cube approach, pre-harmonized geospatial data sets are made accessible to new categories of inexperienced users in an easy-to-use manner. At the same time, the multiresolution nature of the GeoCubes repository facilitates expert users to introduce new kinds of interactive online analysis operations.

Keywords: cloud service, geodata cube, multiresolution, raster geodata

Procedia PDF Downloads 109

Authors: Ed de Jong

Abstract:

Avantium is a leading technology development company and a frontrunner in renewable chemistry. Avantium develops disruptive technologies that enable the production of sustainable high value products from renewable materials and actively seek out collaborations and partnerships with like-minded companies and academic institutions globally, to speed up introductions of chemical innovations in the marketplace. In addition, Avantium helps companies to accelerate their catalysis R&D to improve efficiencies and deliver increased sustainability, growth, and profits, by providing proprietary systems and services to this regard. Many chemical building blocks and materials can be produced from biomass, nowadays mainly from 1st generation based carbohydrates, but potential for competition with the human food chain leads brand-owners to look for strategies to transition from 1st to 2nd generation feedstock. The use of non-edible lignocellulosic feedstock is an equally attractive source to produce chemical intermediates and an important part of the solution addressing these global issues (Paris targets). Avantium’s Dawn Technology™ separates the glucose, mixed sugars, and lignin available in non-food agricultural and forestry residues such as wood chips, wheat straw, bagasse, empty fruit bunches or corn stover. The resulting very pure lignin is dense in energy and can be used for energy generation. However, such a material might preferably be deployed in higher added value applications. Bitumen, which is fossil based, are mostly used for paving applications. Traditional hot mix asphalt emits large quantities of the GHG’s CO₂, CH₄, and N₂O, which is unfavorable for obvious environmental reasons. Another challenge for the bitumen industry is that the petrochemical industry is becoming more and more efficient in breaking down higher chain hydrocarbons to lower chain hydrocarbons with higher added value than bitumen. This has a negative effect on the availability of bitumen. The asphalt market, as well as governments, are looking for alternatives with higher sustainability in terms of GHG emission. The usage of alternative sustainable binders, which can (partly) replace the bitumen, contributes to reduce GHG emissions and at the same time broadens the availability of binders. As lignin is a major component (around 25-30%) of lignocellulosic material, which includes terrestrial plants (e.g., trees, bushes, and grass) and agricultural residues (e.g., empty fruit bunches, corn stover, sugarcane bagasse, straw, etc.), it is globally highly available. The chemical structure shows resemblance with the structure of bitumen and could, therefore, be used as an alternative for bitumen in applications like roofing or asphalt. Applications such as the use of lignin in asphalt need both fundamental research as well as practical proof under relevant use conditions. From a fundamental point of view, rheological aspects, as well as mixing, are key criteria. From a practical point of view, behavior in real road conditions is key (how easy can the asphalt be prepared, how easy can it be applied on the road, what is the durability, etc.). The paper will discuss the fundamentals of the use of lignin as bitumen replacement as well as the status of the different demonstration projects in Europe using lignin as a partial bitumen replacement in asphalts and will especially present the results of using Dawn Technology™ lignin as partial replacement of bitumen.

Keywords: biorefinery, wood fractionation, lignin, asphalt, bitumen, sustainability

Procedia PDF Downloads 129

Authors: Hameed Rukayat Opeyemi, Pericles Pilidis, Pagone Emanuele

Abstract:

Climate change represents one of the single most challenging problems facing the world today. According to the National Oceanic and Administrative Association, Atmospheric temperature rose almost 25% since 1958, Artic sea ice has shrunk 40% since 1959 and global sea levels have risen more than 5.5 cm since 1990. Power plants are the major culprits of GHG emission to the atmosphere. Several technologies have been proposed to reduce the amount of GHG emitted to the atmosphere from power plant, one of which is the less researched Advanced zero emission power plant. The advanced zero emission power plants make use of mixed conductive membrane (MCM) reactor also known as oxygen transfer membrane (OTM) for oxygen transfer. The MCM employs membrane separation process. The membrane separation process was first introduced in 1899 when Walter Hermann Nernst investigated electric current between metals and solutions. He found that when a dense ceramic is heated, current of oxygen molecules move through it. In the bid to curb the amount of GHG emitted to the atmosphere, the membrane separation process was applied to the field of power engineering in the low carbon cycle known as the Advanced zero emission power plant (AZEP cycle). The AZEP cycle was originally invented by Norsk Hydro, Norway and ABB Alstom power (now known as Demag Delaval Industrial turbo machinery AB), Sweden. The AZEP drew a lot of attention because its ability to capture ~100% CO2 and also boasts of about 30-50 % cost reduction compared to other carbon abatement technologies, the penalty in efficiency is also not as much as its counterparts and crowns it with almost zero NOx emissions due to very low nitrogen concentrations in the working fluid. The advanced zero emission power plants differ from a conventional gas turbine in the sense that its combustor is substituted with the mixed conductive membrane (MCM-reactor). The MCM-reactor is made up of the combustor, low temperature heat exchanger LTHX (referred to by some authors as air pre-heater the mixed conductive membrane responsible for oxygen transfer and the high temperature heat exchanger and in some layouts, the bleed gas heat exchanger. Air is taken in by the compressor and compressed to a temperature of about 723 Kelvin and pressure of 2 Mega-Pascals. The membrane area needed for oxygen transfer is reduced by increasing the temperature of 90% of the air using the LTHX; the temperature is also increased to facilitate oxygen transfer through the membrane. The air stream enters the LTHX through the transition duct leading to inlet of the LTHX. The temperature of the air stream is then increased to about 1150 K depending on the design point specification of the plant and the efficiency of the heat exchanging system. The amount of oxygen transported through the membrane is directly proportional to the temperature of air going through the membrane. The AZEP cycle was developed using the Fortran software and economic analysis was conducted using excel and Matlab followed by optimization case study. This paper discusses techno-economic analysis of four possible layouts of the AZEP cycle. The Simple bleed gas heat exchange layout (100 % CO2 capture), Bleed gas heat exchanger layout with flue gas turbine (100 % CO2 capture), Pre-expansion reheating layout (Sequential burning layout) – AZEP 85 % (85 % CO2 capture) and Pre-expansion reheating layout (Sequential burning layout) with flue gas turbine– AZEP 85 % (85 % CO2 capture). This paper discusses Montecarlo risk analysis of four possible layouts of the AZEP cycle.

Keywords: gas turbine, global warming, green house gases, power plants

Procedia PDF Downloads 450

Authors: George Kyriakopoulos, Photini Pazartzis, Anthi Koskina, Crystalie Bourcha

Abstract:

The need for securing safe access to and return from outer space, as well as ensuring the viability of outer space operations, maintains vivid the debate over the promotion of organization of space traffic through a Space Traffic Management System (STM). The proliferation of outer space activities in recent years as well as the dynamic emergence of the private sector has gradually resulted in a diverse universe of actors operating in outer space. The said developments created an increased adverse impact on outer space sustainability as the case of the growing number of space debris clearly demonstrates. The above landscape sustains considerable threats to outer space environment and its operators that need to be addressed by a combination of scientific-technological measures and regulatory interventions. In this context, recourse to recent technological advancements and, in particular, to Artificial Intelligence (AI) and machine learning systems, could achieve exponential results in promoting space traffic management with respect to collision avoidance as well as launch and re-entry procedures/phases. New technologies can support the prospects of a successful space traffic management system at an international scale by enabling, inter alia, timely, accurate and analytical processing of large data sets and rapid decision-making, more precise space debris identification and tracking and overall minimization of collision risks and reduction of operational costs. What is more, a significant part of space activities (i.e. launch and/or re-entry phase) takes place in airspace rather than in outer space, hence the overall discussion also involves the highly developed, both technically and legally, international (and national) Air Traffic Management System (ATM). Nonetheless, from a regulatory perspective, the use of AI for the purposes of space traffic management puts forward implications that merit particular attention. Key issues in this regard include the delimitation of AI-based activities as space activities, the designation of the applicable legal regime (international space or air law, national law), the assessment of the nature and extent of international legal obligations regarding space traffic coordination, as well as the appropriate liability regime applicable to AI-based technologies when operating for space traffic coordination, taking into particular consideration the dense regulatory developments at EU level. In addition, the prospects of institutionalizing international cooperation and promoting an international governance system, together with the challenges of establishment of a comprehensive international STM regime are revisited in the light of intervention of AI technologies. This paper aims at examining regulatory implications advanced by the use of AI technology in the context of space traffic management operations and its key correlating concepts (SSA, space debris mitigation) drawing in particular on international and regional considerations in the field of STM (e.g. UNCOPUOS, International Academy of Astronautics, European Space Agency, among other actors), the promising advancements of the EU approach to AI regulation and, last but not least, national approaches regarding the use of AI in the context of space traffic management, in toto. Acknowledgment: The present work was co-funded by the European Union and Greek national funds through the Operational Program "Human Resources Development, Education and Lifelong Learning " (NSRF 2014-2020), under the call "Supporting Researchers with an Emphasis on Young Researchers – Cycle B" (MIS: 5048145).

Keywords: artificial intelligence, space traffic management, space situational awareness, space debris

Procedia PDF Downloads 222

Authors: Nikola Toshikj, Michel Ramonda, Sylvain Catrouillet, Jean-Jacques Robin, Sebastien Blanquer

Abstract:

Biodegradable and biocompatible block copolymers have risen as the golden materials in both medical and environmental applications. Moreover, if their architecture is of controlled manner, higher applications can be foreseen. In the meantime, organocatalytic ROP has been promoted as more rapid and immaculate route, compared to the traditional organometallic catalysis, towards efficient synthesis of block copolymer architectures. Therefore, herein we report novel organocatalytic pathway with guanidine molecules (TBD) for supported synthesis of trimethylene carbonate initiated by poly(caprolactone) as pre-polymer. Pristine PTMC-b-PCL-b-PTMC block copolymer structure, without any residual products and clear desired block proportions, was achieved under 1.5 hours at room temperature and verified by NMR spectroscopies and size-exclusion chromatography. Besides, when elaborating block copolymer films, further stability and amelioration of mechanical properties can be achieved via additional reticulation step of precedently methacrylated block copolymers. Subsequently, stimulated by the insufficient studies on the phase-separation/crystallinity relationship in these semi-crystalline block copolymer systems, their intrinsic thermal and morphology properties were investigated by differential scanning calorimetry and atomic force microscopy. Firstly, by DSC measurements, the block copolymers with χABN values superior to 20 presented two distinct glass transition temperatures, close to the ones of the respecting homopolymers, demonstrating an initial indication of a phase-separated system. In the interim, the existence of the crystalline phase was supported by the presence of melting temperature. As expected, the crystallinity driven phase-separated morphology predominated in the AFM analysis of the block copolymers. Neither crosslinking at melted state, hence creation of a dense polymer network, disturbed the crystallinity phenomena. However, the later revealed as sensible to rapid liquid nitrogen quenching directly from the melted state. Therefore, AFM analysis of liquid nitrogen quenched and crosslinked block copolymer films demonstrated a thermodynamically driven phase-separation clearly predominating over the originally crystalline one. These AFM films remained stable with their morphology unchanged even after 4 months at room temperature. However, as demonstrated by DSC analysis once rising the temperature above the melting temperature of the PCL block, neither the crosslinking nor the liquid nitrogen quenching shattered the semi-crystalline network, while the access to thermodynamical phase-separated structures was possible for temperatures under the poly (caprolactone) melting point. Precisely this coexistence of dual crosslinked/crystalline networks in the same copolymer structure allowed us to establish, for the first time, the shape-memory properties in such materials, as verified by thermomechanical analysis. Moreover, the response temperature to the material original shape depended on the block copolymer emplacement, hence PTMC or PCL as end-block. Therefore, it has been possible to reach a block copolymer with transition temperature around 40°C thus opening potential real-life medical applications. In conclusion, the initial study of phase-separation/crystallinity relationship in PTMC-b-PCL-b-PTMC block copolymers lead to the discovery of novel shape memory materials with superior properties, widely demanded in modern-life applications.

Keywords: biodegradable block copolymers, organocatalytic ROP, self-assembly, shape-memory

Procedia PDF Downloads 107

Authors: Ayesha Selwyn, Annapoorni Chandrashekar, Kumar Ashwarya, Nishant Baghel

Abstract:

Project-based learning (PBL) activities are typically implemented in technology-enabled schools by highly trained teachers. In rural India, students have limited access to technology and quality education. Implementing typical PBL activities is challenging. This study details how Pratham Education Foundation’s Hybrid Learning model was used to implement two PBL activities related to music in 900 remote Indian villages with 46,000 students aged 10-14. The activities were completed by 69% of groups that submitted a total of 15,000 videos (completed projects). Pratham’s H-Learning model reaches 100,000 students aged 3-14 in 900 Indian villages. The community-driven model engages students in 20,000 self-organized groups outside of school. The students are guided by 6,000 youth volunteers and 100 facilitators. The students partake in learning activities across subjects with the support of community stakeholders and offline digital content on shared Android tablets. A training and implementation toolkit for PBL activities is designed by subject experts. This toolkit is essential in ensuring efficient implementation of activities as facilitators aren’t highly skilled and have limited access to training resources. The toolkit details the activity at three levels of student engagement - enrollment, participation, and completion. The subject experts train project leaders and facilitators who train youth volunteers. Volunteers need to be trained on how to execute the activity and guide students. The training is focused on building the volunteers’ capacity to enable students to solve problems, rather than developing the volunteers’ subject-related knowledge. This structure ensures that continuous intervention of subject matter experts isn’t required, and the onus of judging creativity skills is put on community members. 46,000 students in the H-Learning program were engaged in two PBL activities related to Music from April-June 2019. For one activity, students had to conduct a “musical survey” in their village by designing a survey and shooting and editing a video. This activity aimed to develop students’ information retrieval, data gathering, teamwork, communication, project management, and creativity skills. It also aimed to identify talent and document local folk music. The second activity, “Pratham Idol”, was a singing competition. Students participated in performing, producing, and editing videos. This activity aimed to develop students’ teamwork and creative skills and give students a creative outlet. Students showcased their completed projects at village fairs wherein a panel of community members evaluated the videos. The shortlisted videos from all villages were further evaluated by experts who identified students and adults to participate in advanced music workshops. The H-Learning framework enables students in low resource settings to engage in PBL and develop relevant skills by leveraging community support and using video creation as a tool. In rural India, students do not have access to high-quality education or infrastructure. Therefore designing activities that can be implemented by community members after limited training is essential. The subject experts have minimal intervention once the activity is initiated, which significantly reduces the cost of implementation and allows the activity to be implemented at a massive scale.

Keywords: community supported learning, project-based learning, self-organized learning, education technology

Procedia PDF Downloads 152