Search results for: mixed-integer non-linear programming

Authors: Moustafa Osman Mohammed

Abstract:

This paper introduces Luhmann’s autopoietic social systems starting with the original concept of autopoiesis by biologists and scientists, including the modification of general systems based on socialized medicine. A specific type of autopoietic system is explained in the three existing groups of the ecological phenomena: interaction, social and medical sciences. This hypothesis model, nevertheless, has a nonlinear interaction with its natural environment ‘interactional cycle’ for the exchange of photon energy with molecular without any changes in topology. The external forces in the systems environment might be concomitant with the natural fluctuations’ influence (e.g. radioactive radiation, electromagnetic waves). The cantilever sensor deploys insights to the future chip processor for prevention of social metabolic systems. Thus, the circuits with resonant electric and optical properties are prototyped on board as an intra–chip inter–chip transmission for producing electromagnetic energy approximately ranges from 1.7 mA at 3.3 V to service the detection in locomotion with the least significant power losses. Nowadays, therapeutic systems are assimilated materials from embryonic stem cells to aggregate multiple functions of the vessels nature de-cellular structure for replenishment. While, the interior actuators deploy base-pair complementarity of nucleotides for the symmetric arrangement in particular bacterial nanonetworks of the sequence cycle creating double-stranded DNA strings. The DNA strands must be sequenced, assembled, and decoded in order to reconstruct the original source reliably. The design of exterior actuators have the ability in sensing different variations in the corresponding patterns regarding beat-to-beat heart rate variability (HRV) for spatial autocorrelation of molecular communication, which consists of human electromagnetic, piezoelectric, electrostatic and electrothermal energy to monitor and transfer the dynamic changes of all the cantilevers simultaneously in real-time workspace with high precision. A prototype-enabled dynamic energy sensor has been investigated in the laboratory for inclusion of nanoscale devices in the architecture with a fuzzy logic control for detection of thermal and electrostatic changes with optoelectronic devices to interpret uncertainty associated with signal interference. Ultimately, the controversial aspect of molecular frictional properties is adjusted to each other and forms its unique spatial structure modules for providing the environment mutual contribution in the investigation of mass temperature changes due to pathogenic archival architecture of clusters.

Keywords: autopoiesis, nanoparticles, quantum photonics, portable energy, photonic structure, photodynamic therapeutic system

Procedia PDF Downloads 96

Authors: Elisa Boatti, Ulisse Stefanelli, Alessandro Reali, Ferdinando Auricchio

Abstract:

Thanks to their unusual properties, shape memory alloys (SMAs) are good candidates for advanced applications in a wide range of engineering fields, such as automotive, robotics, civil, biomedical, aerospace. In the last decades, the ever-growing interest for such materials has boosted several research studies aimed at modeling their complex nonlinear behavior in an effective and robust way. Since the constitutive response of SMAs is strongly thermomechanically coupled, the investigation of the non-isothermal evolution of the material must be taken into consideration. The present study considers an existing three-dimensional phenomenological model for SMAs, able to reproduce the main SMA properties while maintaining a simple user-friendly structure, and proposes a variational reformulation of the full non-isothermal version of the model. While the considered model has been thoroughly assessed in an isothermal setting, the proposed formulation allows to take into account the full nonisothermal problem. In particular, the reformulation is inspired to the GENERIC (General Equations for Non-Equilibrium Reversible-Irreversible Coupling) formalism, and is based on a generalized gradient flow of the total entropy, related to thermal and mechanical variables. Such phrasing of the model is new and allows for a discussion of the model from both a theoretical and a numerical point of view. Moreover, it directly implies the dissipativity of the flow. A semi-implicit time-discrete scheme is also presented for the fully coupled thermomechanical system, and is proven unconditionally stable and convergent. The correspondent algorithm is then implemented, under a space-homogeneous temperature field assumption, and tested under different conditions. The core of the algorithm is composed of a mechanical subproblem and a thermal subproblem. The iterative scheme is solved by a generalized Newton method. Numerous uniaxial and biaxial tests are reported to assess the performance of the model and algorithm, including variable imposed strain, strain rate, heat exchange properties, and external temperature. In particular, the heat exchange with the environment is the only source of rate-dependency in the model. The reported curves clearly display the interdependence between phase transformation strain and material temperature. The full thermomechanical coupling allows to reproduce the exothermic and endothermic effects during respectively forward and backward phase transformation. The numerical tests have thus demonstrated that the model can appropriately reproduce the coupled SMA behavior in different loading conditions and rates. Moreover, the algorithm has proved effective and robust. Further developments are being considered, such as the extension of the formulation to the finite-strain setting and the study of the boundary value problem.

Keywords: generalized gradient flow, GENERIC formalism, shape memory alloys, thermomechanical coupling

Procedia PDF Downloads 200

Authors: Daniel Tscharnuter, Eliza Truszkiewicz, Gerald Pinter

Abstract:

High-quality surfaces of plastic parts can be achieved in a very cost-effective manner using in-mold processes, where e.g. scratch resistant or high gloss polymer films are pre-formed and subsequently receive their support structure by injection molding. The pre-forming may be done by high-pressure forming. In this process, a polymer sheet is heated and subsequently formed into the mold by pressurized air. Due to the heat transfer to the cooled mold the polymer temperature drops below its glass transition temperature. This ensures that the deformed microstructure is retained after depressurizing, giving the sheet its final formed shape. The development of a forming process relies heavily on the experience of engineers and trial-and-error procedures. Repeated mold design and testing cycles are however both time- and cost-intensive. It is, therefore, desirable to study the process using reliable computer simulations. Through simulations, the construction of the mold and the effect of various process parameters, e.g. temperature levels, non-uniform heating or timing and magnitude of pressure, on the deformation of the polymer sheet can be analyzed. Detailed knowledge of the deformation is particularly important in the forming of polymer films with integrated electro-optical functions. Care must be taken in the placement of devices, sensors and electrical and optical paths, which are far more sensitive to deformation than the polymers. Reliable numerical prediction of the deformation of the polymer sheets requires sophisticated material models. Polymer films are often either transversely isotropic or orthotropic due to molecular orientations induced during manufacturing. The anisotropic behavior affects the resulting strain field in the deformed film. For example, parts of the same shape but different strain fields may be created by varying the orientation of the film with respect to the mold. The numerical simulation of the high-pressure forming of such films thus requires material models that can capture the nonlinear anisotropic mechanical behavior. There are numerous commercial polymer grades for the engineers to choose from when developing a new part. The effort required for comprehensive material characterization may be prohibitive, especially when several materials are candidates for a specific application. We, therefore, propose a class of models for compressible hyperelasticity, which may be determined from basic experimental data and which can capture key features of the mechanical response. Invariant-based hyperelastic models with a reduced number of invariants are formulated in a semi-numerical way, such that the models are determined from a single uniaxial tensile tests for isotropic materials, or two tensile tests in the principal directions for transversely isotropic or orthotropic materials. The simulation of the high pressure forming of an orthotropic polymer film is finally done using an orthotropic formulation of the hyperelastic model.

Keywords: hyperelastic, anisotropic, polymer film, thermoforming

Procedia PDF Downloads 596

Authors: Moustafa Osman Mohammed

Abstract:

This paper introduces topological order in descried social systems starting with the original concept of autopoiesis by biologists and scientists, including the modification of general systems based on socialized medicine. Topological order is important in describing the physical systems for exploiting optical systems and improving photonic devices. The stats of topological order have some interesting properties of topological degeneracy and fractional statistics that reveal the entanglement origin of topological order, etc. Topological ideas in photonics form exciting developments in solid-state materials, that being; insulating in the bulk, conducting electricity on their surface without dissipation or back-scattering, even in the presence of large impurities. A specific type of autopoiesis system is interrelated to the main categories amongst existing groups of the ecological phenomena interaction social and medical sciences. The hypothesis, nevertheless, has a nonlinear interaction with its natural environment 'interactional cycle' for exchange photon energy with molecules without changes in topology. The engineering topology of a biosensor is based on the excitation boundary of surface electromagnetic waves in photonic band gap multilayer films. The device operation is similar to surface Plasmonic biosensors in which a photonic band gap film replaces metal film as the medium when surface electromagnetic waves are excited. The use of photonic band gap film offers sharper surface wave resonance leading to the potential of greatly enhanced sensitivity. So, the properties of the photonic band gap material are engineered to operate a sensor at any wavelength and conduct a surface wave resonance that ranges up to 470 nm. The wavelength is not generally accessible with surface Plasmon sensing. Lastly, the photonic band gap films have robust mechanical functions that offer new substrates for surface chemistry to understand the molecular design structure and create sensing chips surface with different concentrations of DNA sequences in the solution to observe and track the surface mode resonance under the influences of processes that take place in the spectroscopic environment. These processes led to the development of several advanced analytical technologies: which are; automated, real-time, reliable, reproducible, and cost-effective. This results in faster and more accurate monitoring and detection of biomolecules on refractive index sensing, antibody-antigen reactions with a DNA or protein binding. Ultimately, the controversial aspect of molecular frictional properties is adjusted to each other in order to form unique spatial structure and dynamics of biological molecules for providing the environment mutual contribution in investigation of changes due to the pathogenic archival architecture of cell clusters.

Keywords: autopoiesis, photonics systems, quantum topology, molecular structure, biosensing

Procedia PDF Downloads 64

Authors: Richele P. Severino, Maria M. F. Alchaar, Lorena R. F. De Sousa, Patrik S. Vital, Ana G. Silva, Rosy I. M. A. Ribeiro

Abstract:

Recognized as a global biodiversity hotspot, the Cerrado (Brazil) presents an extreme abundance of endemic species and it is considered to be one of the biologically richest tropical savanna regions in the world. Erythroxylum genus is found in Cerrado and chemically is characterized by the presence of tropane alkaloids, among them cocaine, a natural alkaloid produced by Erythroxylum coca Lam., which was used as a local anesthetic in small surgeries. However, cocaine gained notoriety due to its psychoactive activity in the Central Nervous System (CNS), becoming one of the major problems of public health today. Some species of Erythroxylum are referred to in the literature as having pharmacological potential, which provide alkaloids, terpenoids, and flavonoids. E. vacciniifolium Mart., commonly known as 'catuaba', is used as a central nervous system stimulant and has aphrodisiac properties and E. pelleterianum A. St.-Hil. in the treatment of stomach pains. Already E. myrsinites Mart. and E. suberosum A. St.-Hil. are used in the tannery industry. Species of Erythroxylum are also used in folk medicine for various diseases, against diabetes, antiviral, fungicidal, cytotoxicity, among others. The Cerrado is recognized as the richer savannah in the world in biodiversity but little explored from the chemical view. In our on-going study of the chemistry of Erythroxylum genus, we have investigated four specimens collected in central Cerrado of Brazil: E. campestre (EC), E. deciduum (ED), E. suberosum (ES) and E. tortuosum (ET). The cytotoxic activity of extracts was evaluated using HeLa cells, in vitro assays. The chemical investigation was performed preparing the extracts using n-hexane (H), dichloromethane (D), ethyl acetate (E) and methanol (M). The cells were treated with increasing concentrations of extracts (50, 75 and 100 μg/mL) diluted in DMSO (1%) and DMEM (0.5% FBS and 1% P/S). The IC₅₀ values were determined measured spectrophotometrically at 570 nm, after incubation of HeLa cell line for 48 hours using the MTT (SIGMA M5655), and calculated by nonlinear regression analysis using GraphPad Prism software. All the assays were done in triplicate and repeated at least two times. The cytotoxic assays showed some promising results with IC₅₀ values less than 100 μg/mL (ETD = 38.5 μg/mL; ETM = 92.3 μg/mL; ESM = 67.8 μg/mL; ECD = 24.0 μg/mL; ECM = 32.9; EDA = 44.2 μg/mL). The chemical profile study of ethyl acetate (E) and methanolic (M) extracts of E. tortuosum leaves was performed by LC-MS, and the structures of the compounds were determined by analysis of ¹H, HSQC and HMBC spectra, and confirmed by comparison with the literature data. The investigation led to six substances: α-amyrin, β-amyrin, campesterol, stigmastan-3,5-diene, β-sitosterol and 7,4’-di-O-methylquercetin-3-O-β-rutinoside, with flavonoid the major compound of extracts. By alkaline extraction of the methanolic extract, it was possible to identify three alkaloids: tropacocaine, cocaine and 6-methoxy-8-methyl-8-azabicyclo[3.2.1]octan-3-ol. The results obtained are important for the chemical knowledge of the Cerrado biodiversity and brought a contribution to the chemistry of Erythroxylum genus.

Keywords: cytotoxicity, Erythroxylum, chemical profile, secondary metabolites

Procedia PDF Downloads 118

Authors: Hadi S. Hosseini, Larry A. Taber

Abstract:

In the embryo, heart is initially a simple tubular structure that undergoes complex morphological changes as it transforms into a four-chambered pump. This work focuses on mechanisms that create heart tube (HT). The early embryo is composed of three relatively flat primary germ layers called endoderm, mesoderm, and ectoderm. Precardiac cells located within bilateral regions of the mesoderm called heart fields (HFs) fold and fuse along the embryonic midline to create the HT. The right and left halves of this plate fold symmetrically to bring their upper edges into contact along the midline, where they fuse. In a region near the fusion line, these layers then separate to generate the primitive HT and foregut, which then extend vertically. The anterior intestinal portal (AIP) is the opening at the caudal end of the foregut, which descends as the HT lengthens. The biomechanical mechanisms that drive this folding are poorly understood. Our central hypothesis is that folding is caused by differences in growth between the endoderm and mesoderm while subsequent extension is driven by contraction along the AIP. The feasibility of this hypothesis is examined using experiments with chick embryos and finite-element modeling (FEM). Fertilized white Leghorn chicken eggs were incubated for approximately 22-33 hours until appropriate Hamburger and Hamilton stage (HH5 to HH9) was reached. To inhibit contraction, embryos were cultured in media containing blebbistatin (myosin II inhibitor) for 18h. Three-dimensional models were created using ABAQUS (D. S. Simulia). The initial geometry consists of a flat plate including two layers representing the mesoderm and endoderm. Tissue was considered as a nonlinear elastic material with growth and contraction (negative growth) simulated using a theory, in which the total deformation gradient is given by F=F^*.G, where G is growth tensor and F* is the elastic deformation gradient tensor. In embryos exposed to blebbistatin, initial folding and AIP descension occurred normally. However, after HFs partially fused to create the upper part of the HT, fusion, and AIP descension stopped, and the HT failed to grow longer. These results suggest that cytoskeletal contraction is required only for the later stages of HT formation. In the model, a larger biaxial growth rate in the mesoderm compared to the endoderm causes the bilayered plate to bend ventrally, as the upper edge moves toward the midline, where it 'fuses' with the other half . This folding creates the upper section of the HT, as well as the foregut pocket bordered by the AIP. After this phase completes by stage HH7, contraction along the arch-shaped AIP pulls the lower edge of the plate downward, stretching the two layers. Results given by model are in reasonable agreement with experimental data for the shape of HT, as well as patterns of stress and strain. In conclusion, results of our study support our hypothesis for the creation of the heart tube.

Keywords: heart tube formation, FEM, chick embryo, biomechanics

Procedia PDF Downloads 278

Authors: Vijaya Dixit Aasheesh Dixit

Abstract:

Shipbuilding industry operates in Engineer Procure Construct (EPC) context. Product mix of a shipyard comprises of various types of ships like bulk carriers, tankers, barges, coast guard vessels, sub-marines etc. Each order is unique based on the type of ship and customized requirements, which are engineered into the product right from design stage. Thus, to execute every new project, a shipyard needs to upgrade its production expertise. As a result, over the long run, holistic learning occurs across different types of projects which contributes to the knowledge base of the shipyard. Simultaneously, in the short term, during execution of a project comprising of multiple sister ships, repetition of similar tasks leads to learning at activity level. This research aims to capture above learnings of a shipyard and incorporate learning curve effect in project scheduling and materials procurement to improve project performance. Extant literature provides support for the existence of such learnings in an organization. In shipbuilding, there are sequences of similar activities which are expected to exhibit learning curve behavior. For example, the nearly identical structural sub-blocks which are successively fabricated, erected, and outfitted with piping and electrical systems. Learning curve representation can model not only a decrease in mean completion time of an activity, but also a decrease in uncertainty of activity duration. Sister ships have similar material requirements. The same supplier base supplies materials for all the sister ships within a project. On one hand, this provides an opportunity to reduce transportation cost by batching the order quantities of multiple ships. On the other hand, it increases the inventory holding cost at shipyard and the risk of obsolescence. Further, due to learning curve effect the production scheduled of each consequent ship gets compressed. Thus, the material requirement schedule of every next ship differs from its previous ship. As more and more ships get constructed, compressed production schedules increase the possibility of batching the orders of sister ships. This work aims at integrating materials management with project scheduling of long duration projects for manufacturing of multiple sister ships. It incorporates the learning curve effect on progressively compressing material requirement schedules and addresses the above trade-off of transportation cost and inventory holding and shortage costs while satisfying budget constraints of various stages of the project. The activity durations and lead time of items are not crisp and are available in the form of probabilistic distribution. A Stochastic Mixed Integer Programming (SMIP) model is formulated which is solved using evolutionary algorithm. Its output provides ordering dates of items and degree of order batching for all types of items. Sensitivity analysis determines the threshold number of sister ships required in a project to leverage the advantage of learning curve effect in materials management decisions. This analysis will help materials managers to gain insights about the scenarios: when and to what degree is it beneficial to treat a multiple ship project as an integrated one by batching the order quantities and when and to what degree to practice distinctive procurement for individual ship.

Keywords: learning curve, materials management, shipbuilding, sister ships

Procedia PDF Downloads 474

Authors: Ogechi Nzeagwu, Assumpta Osuagwu, Charlse Nkwoala

Abstract:

Malnutrition in infants due to poverty, poor feeding practices, and high cost of commercial complementary foods among others is a concern in developing countries. The study evaluated the proximate, vitamin and mineral compositions, antinutrients and functional properties, biochemical, haematological and sensory evaluation of complementary food made from sorghum, groundnut, crayfish and paw-paw flour blends using standard procedures. The blends were formulated on protein requirement of infants (18 g/day) using Nutrisurvey linear programming software in ratio of sorghum(S), groundnut(G), crayfish(C) and pawpaw(P) flours as 50:25:10:15(SGCP1), 60:20:10:10 (SGCP2), 60:15:15:10 (SGCP3) and 60:10:20:10 (SGCP4). Plain-pap (fermented maize flour)(TCF) and cerelac (commercial complementary food) served as basal and control diets. Thirty weanling male albino rats aged 28-35 days weighing 33-60 g were purchased and used for the study. The rats after acclimatization were fed with gruel produced with the experimental diets and the control with water ad libitum daily for 35days. Effect of the blends on lipid profile, blood glucose, haematological (RBC, HB, PCV, MCV), liver and kidney function and weight gain of the rats were assessed. Acceptability of the gruel was conducted at the end of rat feeding on forty mothers of infants’ ≥ 6 months who gave their informed consent to participate using a 9 point hedonic scale. Data was analyzed for means and standard deviation, analysis of variance and means were separated using Duncan multiple range test and significance judged at 0.05, all using SPSS version 22.0. The results indicated that crude protein, fibre, ash and carbohydrate of the formulated diets were either comparable or higher than values in cerelac. The formulated diets (SGCP1- SGCP4) were significantly (P>0.05) higher in vitamin A and thiamin compared to cerelac. The iron content of the formulated diets SGCP1- SGCP4 (4.23-6.36 mg/100) were within the recommended iron intake of infants (0.55 mg/day). Phytate (1.56-2.55 mg/100g) and oxalate (0.23-0.35 mg/100g) contents of the formulated diets were within the permissible limits of 0-5%. In functional properties, bulk density, swelling index, % dispersibility and water absorption capacity significantly (P<0.05) increased and compared favourably with cerelac. The essential amino acids of the formulated blends were within the amino acid profile of the FAO/WHO/UNU reference protein for children 0.5 -2 years of age. Urea concentration of rats fed with SGCP1-SGCP4 (19.48 mmol/L),(23.76 mmol/L),(24.07 mmol/L),(23.65 mmol/L) respectively was significantly higher than that of rat fed cerelac (16.98 mmol/L); however, plain pap had the least value (9.15 mmol/L). Rats fed with SGCP1-SGCP4 (116 mg/dl), (119 mg/dl), (115 mg/dl), (117 mg/dl) respectively had significantly higher glucose levels those fed with cerelac (108 mg/dl). Liver function parameters (AST, ALP and ALT), lipid profile (triglyceride, HDL, LDL, VLDL) and hematological parameters of rats fed with formulated diets were within normal range. Rats fed SGCP1 gained more weight (90.45 g) than other rats fed with SGCP2-SGCP4 (71.65 g, 79.76 g, 75.68 g), TCF (20.13 g) and cerelac (59.06 g). In all the sensory attributes, the control was preferred with respect to the formulated diets. The formulated diets were generally adequate and may likely have potentials to meet nutrient requirements of infants as complementary food.

Keywords: biochemical, chemical evaluation, complementary food, quadrimix

Procedia PDF Downloads 134

Authors: Thilina Ranaweera, Enes Makalic, John L. Hopper, Adrian Bickerstaffe

Abstract:

Data are the primary asset of biomedical researchers, and the engine for both discovery and research translation. As the volume and complexity of research datasets increase, especially with new technologies such as large single nucleotide polymorphism (SNP) chips, so too does the requirement for software to manage, process and analyze the data. Researchers often need to execute complicated queries and conduct complex analyzes of large-scale datasets. Existing tools to analyze such data, and other types of high-dimensional data, unfortunately suffer from one or more major problems. They typically require a high level of computing expertise, are too simplistic (i.e., do not fit realistic models that allow for complex interactions), are limited by computing power, do not exploit the computing power of large-scale parallel architectures (e.g. supercomputers, GPU clusters etc.), or are limited in the types of analysis available, compounded by the fact that integrating new analysis methods is not straightforward. Solutions to these problems, such as those developed and implemented on parallel architectures, are currently available to only a relatively small portion of medical researchers with access and know-how. The past decade has seen a rapid expansion of data management systems for the medical domain. Much attention has been given to systems that manage phenotype datasets generated by medical studies. The introduction of heterogeneous genomic data for research subjects that reside in these systems has highlighted the need for substantial improvements in software architecture. To address this problem, we have developed SPARK, an enabling and translational system for medical research, leveraging existing high performance computing resources, and analysis techniques currently available or being developed. It builds these into The Ark, an open-source web-based system designed to manage medical data. SPARK provides a next-generation biomedical data management solution that is based upon a novel Micro-Service architecture and Big Data technologies. The system serves to demonstrate the applicability of Micro-Service architectures for the development of high performance computing applications. When applied to high-dimensional medical datasets such as genomic data, relational data management approaches with normalized data structures suffer from unfeasibly high execution times for basic operations such as insert (i.e. importing a GWAS dataset) and the queries that are typical of the genomics research domain. SPARK resolves these problems by incorporating non-relational NoSQL databases that have been driven by the emergence of Big Data. SPARK provides researchers across the world with user-friendly access to state-of-the-art data management and analysis tools while eliminating the need for high-level informatics and programming skills. The system will benefit health and medical research by eliminating the burden of large-scale data management, querying, cleaning, and analysis. SPARK represents a major advancement in genome research technologies, vastly reducing the burden of working with genomic datasets, and enabling cutting edge analysis approaches that have previously been out of reach for many medical researchers.

Keywords: biomedical research, genomics, information systems, software

Procedia PDF Downloads 239

Authors: Yi-Hao Wong, Li-Li Chan, Chee-Onn Leong, Stephen Ambu, Joon-Wah Mak, Priyasashi Sahu

Abstract:

Background: Acanthamoeba is a genus of amoebae which lives as a free-living in nature or as a human pathogen that causes severe brain and eye infections. Virulence potential of Acanthamoeba is not constant and can change with growth conditions. DNA methylation, an epigenetic process which adds methyl groups to DNA, is used by eukaryotic cells, including several human parasites to control their gene expression. We used qPCR, siRNA gene silencing, and RNA sequencing (RNA-Seq) to study DNA-methyltransferase gene family (DNMT) in order to indicate the possibility of its involvement in programming Acanthamoeba virulence potential. Methods: A virulence-attenuated Acanthamoeba isolate (designation: ATCC; original isolate: ATCC 50492) was subjected to mouse passages to restore its pathogenicity; a virulence-reactivated isolate (designation: AC/5) was generated. Several established factors associated with Acanthamoeba virulence phenotype were examined to confirm the succession of reactivation process. Differential gene expression of DNMT between ATCC and AC/5 isolates was performed by qPCR. Silencing on DNMT gene expression in AC/5 isolate was achieved by siRNA duplex. Total RNAs extracted from ATCC, AC/5, and siRNA-treated (designation: si-146) were subjected to RNA-Seq for comparative transcriptomic analysis in order to identify the genome-wide effect of DNMT in regulating Acanthamoeba gene expression. qPCR was performed to validate the RNA-Seq results. Results: Physiological and cytophatic assays demonstrated an increased in virulence potential of AC/5 isolate after mouse passages. DNMT gene expression was significantly higher in AC/5 compared to ATCC isolate (p ≤ 0.01) by qPCR. si-146 duplex reduced DNMT gene expression in AC/5 isolate by 30%. Comparative transcriptome analysis identified the differentially expressed genes, with 3768 genes in AC/5 vs ATCC isolate; 2102 genes in si-146 vs AC/5 isolate and 3422 genes in si-146 vs ATCC isolate, respectively (fold-change of ≥ 2 or ≤ 0.5, p-value adjusted (padj) < 0.05). Of these, 840 and 1262 genes were upregulated and downregulated, respectively, in si-146 vs AC/5 isolate. Eukaryotic orthologous group (KOG) assignments revealed a higher percentage of downregulated gene expression in si-146 compared to AC/5 isolate, were related to posttranslational modification, signal transduction and energy production. Gene Ontology (GO) terms for those downregulated genes shown were associated with transport activity, oxidation-reduction process, and metabolic process. Among these downregulated genes were putative genes encoded for heat shock proteins, transporters, ubiquitin-related proteins, proteins for vesicular trafficking (small GTPases), and oxidoreductases. Functional analysis of similar predicted proteins had been described in other parasitic protozoa for their survival and pathogenicity. Decreased expression of these genes in si146-treated isolate may account in part for Acanthamoeba reduced pathogenicity. qPCR on 6 selected genes upregulated in AC/5 compared to ATCC isolate corroborated the RNA sequencing findings, indicating a good concordance between these two analyses. Conclusion: To the best of our knowledge, this study represents the first genome-wide analysis of DNA methylation and its effects on gene expression in Acanthamoeba spp. The present data indicate that DNA methylation has substantial effect on global gene expression, allowing further dissection of the genome-wide effects of DNA-methyltransferase gene in regulating Acanthamoeba pathogenicity.

Keywords: Acanthamoeba, DNA methylation, RNA sequencing, virulence

Procedia PDF Downloads 170

Authors: Caspar Goeke, Holger Finger, Dorena Diekamp, Peter König

Abstract:

Online-based research has recently gained increasing attention from various fields of research in the cognitive sciences. Technological advances in the form of online crowdsourcing (Amazon Mechanical Turk), open data repositories (Open Science Framework), and online analysis (Ipython notebook) offer rich possibilities to improve, validate, and speed up research. However, until today there is no cross-platform integration of these subsystems. Furthermore, implementation of online studies still suffers from the complex implementation (server infrastructure, database programming, security considerations etc.). Here we propose and test a new JavaScript framework that enables researchers to conduct any kind of behavioral research in the browser without the need to program a single line of code. In particular our framework offers the possibility to manipulate and combine the experimental stimuli via a graphical editor, directly in the browser. Moreover, we included an action-event system that can be used to handle user interactions, interactively change stimuli properties or store participants’ responses. Besides traditional recordings such as reaction time, mouse and keyboard presses, the tool offers webcam based eye and face-tracking. On top of these features our framework also takes care about the participant recruitment, via crowdsourcing platforms such as Amazon Mechanical Turk. Furthermore, the build in functionality of google translate will ensure automatic text translations of the experimental content. Thereby, thousands of participants from different cultures and nationalities can be recruited literally within hours. Finally, the recorded data can be visualized and cleaned online, and then exported into the desired formats (csv, xls, sav, mat) for statistical analysis. Alternatively, the data can also be analyzed online within our framework using the integrated Ipython notebook. The framework was designed such that studies can be used interchangeably between researchers. This will support not only the idea of open data repositories but also constitutes the possibility to share and reuse the experimental designs and analyses such that the validity of the paradigms will be improved. Particularly, sharing and integrating the experimental designs and analysis will lead to an increased consistency of experimental paradigms. To demonstrate the functionality of the framework we present the results of a pilot study in the field of spatial navigation that was conducted using the framework. Specifically, we recruited over 2000 subjects with various cultural backgrounds and consequently analyzed performance difference in dependence on the factors culture, gender and age. Overall, our results demonstrate a strong influence of cultural factors in spatial cognition. Such an influence has not yet been reported before and would not have been possible to show without the massive amount of data collected via our framework. In fact, these findings shed new lights on cultural differences in spatial navigation. As a consequence we conclude that our new framework constitutes a wide range of advantages for online research and a methodological innovation, by which new insights can be revealed on the basis of massive data collection.

Keywords: cultural differences, crowdsourcing, JavaScript framework, methodological innovation, online data collection, online study, spatial cognition

Procedia PDF Downloads 233

Authors: N. Šarlija, S. Pfeifer, M. Jeger, A. Bilandžić

Abstract:

Enterprise growth is generally considered as a key driver of competitiveness, employment, economic development and social inclusion. As such, it is perceived to be a highly desirable outcome of entrepreneurship for scholars and decision makers. The huge academic debate resulted in the multitude of theoretical frameworks focused on explaining growth stages, determinants and future prospects. It has been widely accepted that enterprise growth is most likely nonlinear, temporal and related to the variety of factors which reflect the individual, firm, organizational, industry or environmental determinants of growth. However, factors that affect growth are not easily captured, instruments to measure those factors are often arbitrary, causality between variables and growth is elusive, indicating that growth is not easily modeled. Furthermore, in line with heterogeneous nature of the growth phenomenon, there is a vast number of measurement constructs assessing growth which are used interchangeably. Differences among various growth measures, at conceptual as well as at operationalization level, can hinder theory development which emphasizes the need for more empirically robust studies. In line with these highlights, the main purpose of this paper is twofold. Firstly, to compare structure and performance of three growth prediction models based on the main growth measures: Revenues, employment and assets growth. Secondly, to explore the prospects of financial indicators, set as exact, visible, standardized and accessible variables, to serve as determinants of enterprise growth. Finally, to contribute to the understanding of the implications on research results and recommendations for growth caused by different growth measures. The models include a range of financial indicators as lag determinants of the enterprises’ performances during the 2008-2013, extracted from the national register of the financial statements of SMEs in Croatia. The design and testing stage of the modeling used the logistic regression procedures. Findings confirm that growth prediction models based on different measures of growth have different set of predictors. Moreover, the relationship between particular predictors and growth measure is inconsistent, namely the same predictor positively related to one growth measure may exert negative effect on a different growth measure. Overall, financial indicators alone can serve as good proxy of growth and yield adequate predictive power of the models. The paper sheds light on both methodology and conceptual framework of enterprise growth by using a range of variables which serve as a proxy for the multitude of internal and external determinants, but are unlike them, accessible, available, exact and free of perceptual nuances in building up the model. Selection of the growth measure seems to have significant impact on the implications and recommendations related to growth. Furthermore, the paper points out to potential pitfalls of measuring and predicting growth. Overall, the results and the implications of the study are relevant for advancing academic debates on growth-related methodology, and can contribute to evidence-based decisions of policy makers.

Keywords: growth measurement constructs, logistic regression, prediction of growth potential, small and medium-sized enterprises

Procedia PDF Downloads 229

Authors: Egemen Sert, Leila Hedayatifar, Rachel A. Rigg, Amir Akhavan, Olha Buchel, Dominic Elias Saadi, Aabir Abubaker Kar, Alfredo J. Morales, Yaneer Bar-Yam

Abstract:

The complexity of providing timely and cost-effective distribution of finished goods from industrial facilities to customers makes effective operational coordination difficult, yet effectiveness is crucial for maintaining customer service levels and sustaining a business. Logistics planning becomes increasingly complex with growing numbers of customers, varied geographical locations, the uncertainty of future orders, and sometimes extreme competitive pressure to reduce inventory costs. Linear optimization methods become cumbersome or intractable due to a large number of variables and nonlinear dependencies involved. Here we develop a complex systems approach to optimizing logistics networks based upon dimensional reduction methods and apply our approach to a case study of a manufacturing company. In order to characterize the complexity in customer behavior, we define a “customer space” in which individual customer behavior is described by only the two most relevant dimensions: the distance to production facilities over current transportation routes and the customer's demand frequency. These dimensions provide essential insight into the domain of effective strategies for customers; direct and indirect strategies. In the direct strategy, goods are sent to the customer directly from a production facility using box or bulk trucks. In the indirect strategy, in advance of an order by the customer, goods are shipped to an external warehouse near a customer using trains and then "last-mile" shipped by trucks when orders are placed. Each strategy applies to an area of the customer space with an indeterminate boundary between them. Specific company policies determine the location of the boundary generally. We then identify the optimal delivery strategy for each customer by constructing a detailed model of costs of transportation and temporary storage in a set of specified external warehouses. Customer spaces help give an aggregate view of customer behaviors and characteristics. They allow policymakers to compare customers and develop strategies based on the aggregate behavior of the system as a whole. In addition to optimization over existing facilities, using customer logistics and the k-means algorithm, we propose additional warehouse locations. We apply these methods to a medium-sized American manufacturing company with a particular logistics network, consisting of multiple production facilities, external warehouses, and customers along with three types of shipment methods (box truck, bulk truck and train). For the case study, our method forecasts 10.5% savings on yearly transportation costs and an additional 4.6% savings with three new warehouses.

Keywords: logistics network optimization, direct and indirect strategies, K-means algorithm, dimensional reduction

Procedia PDF Downloads 112

Authors: Maryam Shahbazi, Amy B. Cerato

Abstract:

The importance of a systems’ natural frequency (fn) emerges when the vibration force frequency is equivalent to foundation's fn which causes response amplitude (resonance) that may cause irreversible damage to the structure. Several factors such as pile geometry (e.g., length and diameter), soil density, load magnitude, pile condition, and physical structure affect the fn of a soil-pile system; some of these parameters are evaluated in this study. Although experimental and analytical studies have assessed the fn of a soil-pile system, few have included individual and grouped helical piles. Thus, the current study aims to provide quantitative data on dynamic characteristics of helical pile-soil systems from full-scale shake table tests that will allow engineers to predict more realistic dynamic response under motions with variable frequency ranges. To evaluate the fn of single and grouped helical piles in dry dense sand, full-scale shake table tests were conducted in a laminar box (6.7 m x 3.0 m with 4.6 m high). Two different diameters (8.8 cm and 14 cm) helical piles were embedded in the soil box with corresponding lengths of 3.66m (excluding one pile with length of 3.96) and 4.27m. Different configurations were implemented to evaluate conditions such as fixed and pinned connections. In the group configuration, all four piles with similar geometry were tied together. Simulated real earthquake motions, in addition to white noise, were applied to evaluate the wide range of soil-pile system behavior. The Fast Fourier Transform (FFT) of measured time history responses using installed strain gages and accelerometers were used to evaluate fn. Both time-history records using accelerometer or strain gages were found to be acceptable for calculating fn. In this study, the existence of a pile reduced the fn of the soil slightly. Greater fn occurred on single piles with larger l/d ratios (higher slenderness ratio). Also, regardless of the connection type, the more slender pile group which is obviously surrounded by more soil, yielded higher natural frequencies under white noise, which may be due to exhibiting more passive soil resistance around it. Relatively speaking, within both pile groups, a pinned connection led to a lower fn than a fixed connection (e.g., for the same pile group the fn’s are 5.23Hz and 4.65Hz for fixed and pinned connections, respectively). Generally speaking, a stronger motion causes nonlinear behavior and degrades stiffness which reduces a pile’s fn; even more, reduction occurs in soil with a lower density. Moreover, fn of dense sand under white noise signal was obtained 5.03 which is reduced by 44% when an earthquake with the acceleration of 0.5g was applied. By knowing the factors affecting fn, the designer can effectively match the properties of the soil to a type of pile and structure to attempt to avoid resonance. The quantitative results in this study assist engineers in predicting a probable range of fn for helical pile foundations under potential future earthquake, and machine loading applied forces.

Keywords: helical pile, natural frequency, pile group, shake table, stiffness

Procedia PDF Downloads 109

Authors: Arturo Galvan, Jatziri Y. Moreno-Martinez, Daniel Arroyo-Montoya, Jose M. Gutierrez-Villalobos

Abstract:

Bridges are one of the most seismically vulnerable structures on highway transportation systems. The general process for assessing the seismic vulnerability of a bridge involves the evaluation of its overall capacity and demand. One of the most common procedures to obtain this capacity is by means of pushover analysis of the structure. Typically, the bridge capacity is assessed using non-linear static methods or non-linear dynamic analyses. The non-linear dynamic approaches use step by step numerical solutions for assessing the capacity with the consuming computer time inconvenience. In this study, a nonlinear static analysis (‘pushover analysis’) was performed to predict the collapse mechanism of a typical bridge built in the central zone of Mexico (Celaya, Guanajuato). The bridge superstructure consists of three simple supported spans with a total length of 76 m: 22 m of the length of extreme spans and 32 m of length of the central span. The deck width is of 14 m and the concrete slab depth is of 18 cm. The bridge is built by means of frames of five piers with hollow box-shaped sections. The dimensions of these piers are 7.05 m height and 1.20 m diameter. The numerical model was created using a commercial software considering linear and non-linear elements. In all cases, the piers were represented by frame type elements with geometrical properties obtained from the structural project and construction drawings of the bridge. The deck was modeled with a mesh of rectangular thin shell (plate bending and stretching) finite elements. The moment-curvature analysis was performed for the sections of the piers of the bridge considering in each pier the effect of confined concrete and its reinforcing steel. In this way, plastic hinges were defined on the base of the piers to carry out the pushover analysis. In addition, time history analyses were performed using 19 accelerograms of real earthquakes that have been registered in Guanajuato. In this way, the displacements produced by the bridge were determined. Finally, pushover analysis was applied through the control of displacements in the piers to obtain the overall capacity of the bridge before the failure occurs. It was concluded that the lateral deformation of the piers due to a critical earthquake occurred in this zone is almost imperceptible due to the geometry and reinforcement demanded by the current design standards and compared to its displacement capacity, they were excessive. According to the analysis, it was found that the frames built with five piers increase the rigidity in the transverse direction of the bridge. Hence it is proposed to reduce these frames of five piers to three piers, maintaining the same geometrical characteristics and the same reinforcement in each pier. Also, the mechanical properties of materials (concrete and reinforcing steel) were maintained. Once a pushover analysis was performed considering this configuration, it was concluded that the bridge would continue having a “correct” seismic behavior, at least for the 19 accelerograms considered in this study. In this way, costs in material, construction, time and labor would be reduced in this study case.

Keywords: collapse mechanism, moment-curvature analysis, overall capacity, push-over analysis

Procedia PDF Downloads 128

Authors: Andrey Cherdantsev, Mikhail Cherdantsev, Sergey Isaenkov, Dmitriy Markovich

Abstract:

In annular gas-liquid flow, liquid flows as a film along pipe walls sheared by high-velocity gas stream. Film surface is covered by large-scale disturbance waves which affect pressure drop and heat transfer in the system and are necessary for entrainment of liquid droplets from film surface into the core of gas stream. Disturbance waves are a highly complex and their properties are affected by numerous parameters. One of such aspects is flow development, i.e., change of flow properties with the distance from the inlet. In the present work, this question is studied using brightness-based laser-induced fluorescence (BBLIF) technique. This method enables one to perform simultaneous measurements of local film thickness in large number of points with high sampling frequency. In the present experiments first 50 cm of upward and downward annular flow in a vertical pipe of 11.7 mm i.d. is studied with temporal resolution of 10 kHz and spatial resolution of 0.5 mm. Thus, spatiotemporal evolution of film surface can be investigated, including scenarios of formation, acceleration and coalescence of disturbance waves. The behaviour of disturbance waves' velocity depending on phases flow rates and downstream distance was investigated. Besides measuring the waves properties, the goal of the work was to investigate the interrelation between disturbance waves properties and integral characteristics of the flow such as interfacial shear stress and flow rate of dispersed phase. In particular, it was shown that the initial acceleration of disturbance waves, defined by the value of shear stress, linearly decays with downstream distance. This lack of acceleration which may even lead to deceleration is related to liquid entrainment. Flow rate of disperse phase linearly grows with downstream distance. During entrainment events, liquid is extracted directly from disturbance waves, reducing their mass, area of interaction to the gas shear and, hence, velocity. Passing frequency of disturbance waves at each downstream position was measured automatically with a new algorithm of identification of characteristic lines of individual disturbance waves. Scenarios of coalescence of individual disturbance waves were identified. Transition from initial high-frequency Kelvin-Helmholtz waves appearing at the inlet to highly nonlinear disturbance waves with lower frequency was studied near the inlet using 3D realisation of BBLIF method in the same cylindrical channel and in a rectangular duct with cross-section of 5 mm by 50 mm. It was shown that the initial waves are generally two-dimensional but are promptly broken into localised three-dimensional wavelets. Coalescence of these wavelets leads to formation of quasi two-dimensional disturbance waves. Using cross-correlation analysis, loss and restoration of two-dimensionality of film surface with downstream distance were studied quantitatively. It was shown that all the processes occur closer to the inlet at higher gas velocities.

Keywords: annular flow, disturbance waves, entrainment, flow development

Procedia PDF Downloads 229

Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

Abstract:

To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

Procedia PDF Downloads 52

Authors: Madan Chandra Maurya, A. R. Dar

Abstract:

Among the entire natural calamities earthquake is the one which is most devastating. If the losses due to all other calamities are added still it will be very less than the losses due to earthquakes. So it means we must be ready to face such a situation, which is only possible if we make our structures earthquake resistant. A review of structural damages to the braced frame systems after several major earthquakes—including recent earthquakes—has identified some anticipated and unanticipated damage. This damage has prompted many engineers and researchers around the world to consider new approaches to improve the behavior of braced frame systems. Extensive experimental studies over the last fourty years of conventional buckling brace components and several braced frame specimens have been briefly reviewed, highlighting that the number of studies on the full-scale concentric braced frames is still limited. So for this reason the study surrounds the words plastic behavior, steel structure, brace frame system. In this study, there are two different analytical approaches which have been used to predict the behavior and strength of an un-braced frame. The first is referred as incremental elasto-plastic analysis a plastic approach. This method gives a complete load-deflection history of the structure until collapse. It is based on the plastic hinge concept for fully plastic cross sections in a structure under increasing proportional loading. In this, the incremental elasto-plastic analysis- hinge by hinge method is used in this study because of its simplicity to know the complete load- deformation history of two storey un-braced scaled model. After that the experiments were conducted on two storey scaled building model with and without bracing system to know the true or experimental load deformation curve of scaled model. Only way, is to understand and analyze these techniques and adopt these techniques in our structures. The study named as Plastic Behavior of Steel Frames using Different Concentric Bracing Configurations deals with all this. This study aimed at improving the already practiced traditional systems and to check the behavior and its usefulness with respect to X-braced system as reference model i.e. is how plastically it is different from X-braced. Laboratory tests involved determination of plastic behavior of these models (with and without brace) in terms of load-deformation curve. Thus, the aim of this study is to improve the lateral displacement resistance capacity by using new configuration of brace member in concentric manner which is different from conventional concentric brace. Once the experimental and manual results (using plastic approach) compared, simultaneously the results from both approach were also compared with nonlinear static analysis (pushover analysis) approach using ETABS i.e how both the previous results closely depicts the behavior in pushover curve and upto what limit. Tests results shows that all the three approaches behaves somewhat in similar manner upto yield point and also the applicability of elasto-plastic analysis (hinge by hinge method) to know the plastic behavior. Finally the outcome from three approaches shows that the newer one configuration which is chosen for study behaves in-between the plane frame (without brace or reference frame) and the conventional X-brace frame.

Keywords: elasto-plastic analysis, concentric steel braced frame, pushover analysis, ETABS

Procedia PDF Downloads 206

Authors: Georgios A. Fragkiadakis, Antonia Psaroudaki, Theodora Mouratidou, Eirini Sfakianaki

Abstract:

Research: Within the project "Actions for the optimal utilization of the potential of carob in the Region of Crete" which is financed-supervised by the Region, with collaboration of Crete University and Hellenic Mediterranean University, a SWOT (strengths, weaknesses, opportunities, threats) survey was carried out, to evaluate the prospects of carob in human nutrition, in Crete. Results and conclusions: 1). Strengths: There exists a local production of carob for human consumption, based on international reports, and local-product reports. The data on products in the market (over 100 brands of carob food), indicates a sufficiency of carob materials offered in Crete. The variety of carob food products retailed in Crete indicates a strong demand-production-consumption trend. There is a stable number (core) of businesses that invest significantly (Creta carob, Cretan mills, etc.). The great majority of the relevant food stores (bakery, confectionary etc.) do offer carob products. The presence of carob products produced in Crete is strong on the internet (over 20 main professionally designed websites). The promotion of the carob food-products is based on their variety and on a few historical elements connected with the Cretan diet. 2). Weaknesses: The international prices for carob seed affect the sector; the seed had an international price of €20 per kg in 2021-22 and fell to €8 in 2022, causing losses to carob traders. The local producers do not sort the carobs they deliver for processing, causing 30-40% losses of the product in the industry. The occasional high price triggers the collection of degraded raw material; large losses may emerge due to the action of insects. There are many carob trees whose fruits are not collected, e.g. in Apokoronas, Chania. The nutritional and commercial value of the wild carob fruits is very low. Carob trees-production is recorded by Greek statistical services as "other cultures" in combination with prickly pear i.e., creating difficulties in retrieving data. The percentage of carob used for human nutrition, in contrast to animal feeding, is not known. The exact imports of carob are not closely monitored. We have no data on the recycling of carob by-products in Crete. 3). Opportunities: The development of a culture of respect for carob trade may improve professional relations in the sector. Monitoring carob market and connecting production with retailing-industry needs may allow better market-stability. Raw material evaluation procedures may be implemented to maintain carob value-chain. The state agricultural services may be further involved in carob-health protection. The education of farmers on carob cultivation/management, can improve the quality of the product. The selection of local productive varieties, may improve the sustainability of the culture. Connecting the consumption of carob with health-food products, may create added value in the sector. The presence and extent of wild carob threes in Crete, represents, potentially, a target for grafting. 4). Threats: The annual fluctuation of carob yield challenges the programming of local food industry activities. Carob is a forest species also - there is danger of wrong classification of crops as forest areas, where land ownership is not clear.

Keywords: human nutrition, carob food, SWOT analysis, crete, greece

Procedia PDF Downloads 54

Authors: Jana Abu Ahmada, Zaineb Mohamed, Ilyasse Aksikas

Abstract:

The linear quadratic control system of hyperbolic first order partial differential equations (PDEs) are presented. The aim of this research is to control chemical reactions. This is achieved by converting the PDEs system to ordinary differential equations (ODEs) using the method of characteristics to reduce the system to control it by using the integral reinforcement learning. The designed controller is applied to a catalytic cracking reactor. Background—Transport-Reaction systems cover a large chemical and bio-chemical processes. They are best described by nonlinear PDEs derived from mass and energy balances. As a main application to be considered in this work is the catalytic cracking reactor. Indeed, the cracking reactor is widely used to convert high-boiling, high-molecular weight hydrocarbon fractions of petroleum crude oils into more valuable gasoline, olefinic gases, and others. On the other hand, control of PDEs systems is an important and rich area of research. One of the main control techniques is feedback control. This type of control utilizes information coming from the system to correct its trajectories and drive it to a desired state. Moreover, feedback control rejects disturbances and reduces the variation effects on the plant parameters. Linear-quadratic control is a feedback control since the developed optimal input is expressed as feedback on the system state to exponentially stabilize and drive a linear plant to the steady-state while minimizing a cost criterion. The integral reinforcement learning policy iteration technique is a strong method that solves the linear quadratic regulator problem for continuous-time systems online in real time, using only partial information about the system dynamics (i.e. the drift dynamics A of the system need not be known), and without requiring measurements of the state derivative. This is, in effect, a direct (i.e. no system identification procedure is employed) adaptive control scheme for partially unknown linear systems that converges to the optimal control solution. Contribution—The goal of this research is to Develop a characteristics-based optimal controller for a class of hyperbolic PDEs and apply the developed controller to a catalytic cracking reactor model. In the first part, developing an algorithm to control a class of hyperbolic PDEs system will be investigated. The method of characteristics will be employed to convert the PDEs system into a system of ODEs. Then, the control problem will be solved along the characteristic curves. The reinforcement technique is implemented to find the state-feedback matrix. In the other half, applying the developed algorithm to the important application of a catalytic cracking reactor. The main objective is to use the inlet fraction of gas oil as a manipulated variable to drive the process state towards desired trajectories. The outcome of this challenging research would yield the potential to provide a significant technological innovation for the gas industries since the catalytic cracking reactor is one of the most important conversion processes in petroleum refineries.

Keywords: PDEs, reinforcement iteration, method of characteristics, riccati equation, cracking reactor

Procedia PDF Downloads 67

Authors: Oscar Bareiro, Johannes Sackmann, Thomas Gries

Abstract:

Carbon fiber reinforced polymer composites (CFRP) are used in a wide variety of applications due to its advantageous properties and design versatility. The braiding process enables the manufacture of components with good toughness and fatigue strength. However, failure mechanisms of CFRPs are complex and still present challenges associated with their maintenance and repair. Within the broad scope of structural health monitoring (SHM), strain monitoring can be applied to composite materials to improve reliability, reduce maintenance costs and safely exhaust service life. Traditional SHM systems employ e.g. fiber optics, piezoelectrics as sensors, which are often expensive, time consuming and complicated to implement. A cost-efficient alternative can be the exploitation of the conductive properties of fiber-based sensors such as carbon, copper, or constantan - a copper-nickel alloy – that can be utilized as sensors within composite structures to achieve strain monitoring. This allows the structure to provide feedback via electrical signals to a user which are essential for evaluating the structural condition of the structure. This work presents a strategy for the in-process integration of resistance-based sensors (Elektrisola Feindraht AG, CuNi23Mn, Ø = 0.05 mm) into textile preforms during its manufacture via the braiding process (Herzog RF-64/120) to achieve strain monitoring of braided composites. For this, flat samples of instrumented composite laminates of carbon fibers (Toho Tenax HTS40 F13 24K, 1600 tex) and epoxy resin (Epikote RIMR 426) were manufactured via vacuum-assisted resin infusion. These flat samples were later cut out into test specimens and the integrated sensors were wired to the measurement equipment (National Instruments, VB-8012) for data acquisition during the execution of mechanical tests. Quasi-static tests were performed (tensile, 3-point bending tests) following standard protocols (DIN EN ISO 527-1 & 4, DIN EN ISO 14132); additionally, dynamic tensile tests were executed. These tests were executed to assess the sensor response under different loading conditions and to evaluate the influence of the sensor presence on the mechanical properties of the material. Several orientations of the sensor with regards to the applied loading and sensor placements inside the laminate were tested. Strain measurements from the integrated sensors were made by programming a data acquisition code (LabView) written for the measurement equipment. Strain measurements from the integrated sensors were then correlated to the strain/stress state for the tested samples. From the assessment of the sensor integration approach it can be concluded that it allows for a seamless sensor integration into the textile preform. No damage to the sensor or negative effect on its electrical properties was detected during inspection after integration. From the assessment of the mechanical tests of instrumented samples it can be concluded that the presence of the sensors does not alter significantly the mechanical properties of the material. It was found that there is a good correlation between resistance measurements from the integrated sensors and the applied strain. It can be concluded that the correlation is of sufficient accuracy to determinate the strain state of a composite laminate based solely on the resistance measurements from the integrated sensors.

Keywords: braiding process, in-process sensor integration, instrumented composite material, resistance-based sensor, strain monitoring

Procedia PDF Downloads 83

Authors: Quan Wen, Tianxiao Chang, Shaolu Shi, Yushi Wang, Guangyu Wang

Abstract:

As a kind of working environment of the fuze, the spin rate decaying law of projectile in exterior trajectory is of great value in the design of the rotation count fixed distance fuze. In addition, it is significant in the field of devices for simulation tests of fuze exterior ballistic environment, flight stability, and dispersion accuracy of gun projectile and opening and scattering design of submunition and illuminating cartridges. Besides, the self-destroying mechanism of the fuze in small-caliber projectile often works by utilizing the attenuation of centrifugal force. In the theory of projectile aerodynamics and fuze design, there are many formulas describing the change law of projectile angular velocity in external ballistic such as Roggla formula, exponential function formula, and power function formula. However, these formulas are mostly semi-empirical due to the poor test conditions and insufficient test data at that time. These formulas are difficult to meet the design requirements of modern fuze because they are not accurate enough and have a narrow range of applications now. In order to provide more accurate ballistic environment parameters for the design of a hemispherical head projectile fuze, the projectile’s spin rate decaying law in exterior trajectory under the effect of air resistance was studied. In the analysis, the projectile shape was simplified as hemisphere head, cylindrical part, rotating band part, and anti-truncated conical tail. The main assumptions are as follows: a) The shape and mass are symmetrical about the longitudinal axis, b) There is a smooth transition between the ball hea, c) The air flow on the outer surface is set as a flat plate flow with the same area as the expanded outer surface of the projectile, and the boundary layer is turbulent, d) The polar damping moment attributed to the wrench hole and rifling mark on the projectile is not considered, e) The groove of the rifle on the rotating band is uniform, smooth and regular. The impacts of the four parts on aerodynamic moment of the projectile rotation were obtained by aerodynamic theory. The surface friction stress of the projectile, the polar damping moment formed by the head of the projectile, the surface friction moment formed by the cylindrical part, the rotating band, and the anti-truncated conical tail were obtained by mathematical derivation. After that, the mathematical model of angular spin rate attenuation was established. In the whole trajectory with the maximum range angle (38°), the absolute error of the polar damping torque coefficient obtained by simulation and the coefficient calculated by the mathematical model established in this paper is not more than 7%. Therefore, the credibility of the mathematical model was verified. The mathematical model can be described as a first-order nonlinear differential equation, which has no analytical solution. The solution can be only gained as a numerical solution by connecting the model with projectile mass motion equations in exterior ballistics.

Keywords: ammunition engineering, fuze technology, spin rate, numerical simulation

Procedia PDF Downloads 111

Authors: Andres Nieto-Leal, Victor N. Kaliakin, Tania P. Molina

Abstract:

The nature of most engineering materials is quite complex. It is, therefore, difficult to devise a general mathematical model that will cover all possible ranges and types of excitation and behavior of a given material. As a result, the development of mathematical models is based upon simplifying assumptions regarding material behavior. Such simplifications result in some material idealization; for example, one of the simplest material idealization is to assume that the material behavior obeys the elasticity. However, soils are nonhomogeneous, anisotropic, path-dependent materials that exhibit nonlinear stress-strain relationships, changes in volume under shear, dilatancy, as well as time-, rate- and temperature-dependent behavior. Over the years, many constitutive models, possessing different levels of sophistication, have been developed to simulate the behavior geomaterials, particularly cohesive soils. Early in the development of constitutive models, it became evident that elastic or standard elastoplastic formulations, employing purely isotropic hardening and predicated in the existence of a yield surface surrounding a purely elastic domain, were incapable of realistically simulating the behavior of geomaterials. Accordingly, more sophisticated constitutive models have been developed; for example, the bounding surface elastoplasticity. The essence of the bounding surface concept is the hypothesis that plastic deformations can occur for stress states either within or on the bounding surface. Thus, unlike classical yield surface elastoplasticity, the plastic states are not restricted only to those lying on a surface. Elastoplastic bounding surface models have been improved; however, there is still need to improve their capabilities in simulating the response of anisotropically consolidated cohesive soils, especially the response in extension tests. Thus, in this work an improved constitutive model that can more accurately predict diverse stress-strain phenomena exhibited by cohesive soils was developed. Particularly, an improved rotational hardening rule that better simulate the response of cohesive soils in extension. The generalized definition of the bounding surface model provides a convenient and elegant framework for unifying various previous versions of the model for anisotropically consolidated cohesive soils. The Generalized Bounding Surface Model for cohesive soils is a fully three-dimensional, time-dependent model that accounts for both inherent and stress induced anisotropy employing a non-associative flow rule. The model numerical implementation in a computer code followed an adaptive multistep integration scheme in conjunction with local iteration and radial return. The one-step trapezoidal rule was used to get the stiffness matrix that defines the relationship between the stress increment and the strain increment. After testing the model in simulating the response of cohesive soils through extensive comparisons of model simulations to experimental data, it has been shown to give quite good simulations. The new model successfully simulates the response of different cohesive soils; for example, Cardiff Kaolin, Spestone Kaolin, and Lower Cromer Till. The simulated undrained stress paths, stress-strain response, and excess pore pressures are in very good agreement with the experimental values, especially in extension.

Keywords: bounding surface elastoplasticity, cohesive soils, constitutive model, modeling of geomaterials

Procedia PDF Downloads 293

Authors: Sofia Quaglia, Carmine Di Martino, Brendan Tierney

Abstract:

Artificial Intelligence (A.I.) constitutes various aspects of modern life, from the Machine Learning algorithms predicting the stocks on Wall streets to the killing of belligerents and innocents alike on the battlefield. Moreover, the end goal is to create autonomous A.I.; this means that the presence of humans in the decision-making process will be absent. The question comes naturally: when an A.I. does something wrong when its behavior is harmful to the community and its actions go against the law, which is to be held responsible? This research’s subject matter in A.I. and Robot Ethics focuses mainly on Robot Rights and its ultimate objective is to answer the questions: (i) What is the function of rights? (ii) Who is a right holder, what is personhood and the requirements needed to be a moral agent (therefore, accountable for responsibility)? (iii) Can an A.I. be a moral agent? (ontological requirements) and finally (iv) if it ought to be one (ethical implications). With the direction to answer this question, this research project was done via a collaboration between the School of Computer Science in the Technical University of Dublin that oversaw the technical aspects of this work, as well as the Department of Philosophy in the University of Milan, who supervised the philosophical framework and argumentation of the project. Firstly, it was found that all rights are positive and based on consensus; they change with time based on circumstances. Their function is to protect the social fabric and avoid dangerous situations. The same goes for the requirements considered necessary to be a moral agent: those are not absolute; in fact, they are constantly redesigned. Hence, the next logical step was to identify what requirements are regarded as fundamental in real-world judicial systems, comparing them to that of ones used in philosophy. Autonomy, free will, intentionality, consciousness and responsibility were identified as the requirements to be considered a moral agent. The work went on to build a symmetrical system between personhood and A.I. to enable the emergence of the ontological differences between the two. Each requirement is introduced, explained in the most relevant theories of contemporary philosophy, and observed in its manifestation in A.I. Finally, after completing the philosophical and technical analysis, conclusions were drawn. As underlined in the research questions, there are two issues regarding the assignment of moral agency to artificial agent: the first being that all the ontological requirements must be present and secondly being present or not, whether an A.I. ought to be considered as an artificial moral agent. From an ontological point of view, it is very hard to prove that an A.I. could be autonomous, free, intentional, conscious, and responsible. The philosophical accounts are often very theoretical and inconclusive, making it difficult to fully detect these requirements on an experimental level of demonstration. However, from an ethical point of view it makes sense to consider some A.I. as artificial moral agents, hence responsible for their own actions. When considering artificial agents as responsible, there can be applied already existing norms in our judicial system such as removing them from society, and re-educating them, in order to re-introduced them to society. This is in line with how the highest profile correctional facilities ought to work. Noticeably, this is a provisional conclusion and research must continue further. Nevertheless, the strength of the presented argument lies in its immediate applicability to real world scenarios. To refer to the aforementioned incidents, involving the murderer of innocents, when this thesis is applied it is possible to hold an A.I. accountable and responsible for its actions. This infers removing it from society by virtue of its un-usability, re-programming it and, only when properly functioning, re-introducing it successfully

Keywords: artificial agency, correctional system, ethics, natural agency, responsibility

Procedia PDF Downloads 159

Authors: João Coutinho-Rodrigues, Nuno Sousa, Luís Alçada-Almeida

Abstract:

Transportation infrastructure systems are fundamental in modern society and economy. However, they need modernizing, maintaining, and reinforcing interventions which require large investments. In many countries, accumulated intervention delays arise from aging and intense use, being magnified by financial constraints of the past. The decision problem of managing the renewal of large backlogs is common to several types of important transportation infrastructures (e.g., railways, roads). This problem requires considering financial aspects as well as operational constraints under a multidimensional framework. The present research introduces a linear programming multiobjective model for managing railway infrastructure asset renewal. The model aims at minimizing three objectives: (i) yearly investment peak, by evenly spreading investment throughout multiple years; (ii) total cost, which includes extra maintenance costs incurred from renewal backlogs; (iii) priority delays related to work start postponements on the higher priority railway sections. Operational constraints ensure that passenger and freight services are not excessively delayed from having railway line sections under intervention. Achieving a balanced annual investment plan, without compromising the total financial effort or excessively postponing the execution of the priority works, was the motivation for pursuing the research which is now presented. The methodology, inspired by a real case study and tested with real data, reflects aspects of the practice of an infrastructure management company and is generalizable to different types of infrastructure (e.g., railways, highways). It was conceived for treating renewal interventions in infrastructure assets, which is a railway network may be rails, ballasts, sleepers, etc.; while a section is under intervention, trains must run at reduced speed, causing delays in services. The model cannot, therefore, allow for an accumulation of works on the same line, which may cause excessively large delays. Similarly, the lines do not all have the same socio-economic importance or service intensity, making it is necessary to prioritize the sections to be renewed. The model takes these issues into account, and its output is an optimized works schedule for the renewal project translatable in Gantt charts The infrastructure management company provided all the data for the first test case study and validated the parameterization. This case consists of several sections to be renewed, over 5 years and belonging to 17 lines. A large instance was also generated, reflecting a problem of a size similar to the USA railway network (considered the largest one in the world), so it is not expected that considerably larger problems appear in real life; an average of 25 years backlog and ten years of project horizon was considered. Despite the very large increase in the number of decision variables (200 times as large), the computational time cost did not increase very significantly. It is thus expectable that just about any real-life problem can be treated in a modern computer, regardless of size. The trade-off analysis shows that if the decision maker allows some increase in max yearly investment (i.e., degradation of objective ii), solutions improve considerably in the remaining two objectives.

Keywords: transport infrastructure, asset renewal, railway maintenance, multiobjective modeling

Procedia PDF Downloads 124

Authors: Bidzina Matsaberidze, Anna Sikharulidze, Gia Sirbiladze, Bezhan Ghvaberidze

Abstract:

In the modern world emergency management decision support systems are actively used by state organizations, which are interested in extreme and abnormal processes and provide optimal and safe management of supply needed for the civil and military facilities in geographical areas, affected by disasters, earthquakes, fires and other accidents, weapons of mass destruction, terrorist attacks, etc. Obviously, these kinds of extreme events cause significant losses and damages to the infrastructure. In such cases, usage of intelligent support technologies is very important for quick and optimal location-transportation of emergency service in order to avoid new losses caused by these events. Timely servicing from emergency service centers to the affected disaster regions (response phase) is a key task of the emergency management system. Scientific research of this field takes the important place in decision-making problems. Our goal was to create an expert knowledge-based intelligent support system, which will serve as an assistant tool to provide optimal solutions for the above-mentioned problem. The inputs to the mathematical model of the system are objective data, as well as expert evaluations. The outputs of the system are solutions for Fuzzy Multi-Objective Emergency Location-Transportation Problem (FMOELTP) for disasters’ regions. The development and testing of the Intelligent Support System were done on the example of an experimental disaster region (for some geographical zone of Georgia) which was generated using a simulation modeling. Four objectives are considered in our model. The first objective is to minimize an expectation of total transportation duration of needed products. The second objective is to minimize the total selection unreliability index of opened humanitarian aid distribution centers (HADCs). The third objective minimizes the number of agents needed to operate the opened HADCs. The fourth objective minimizes the non-covered demand for all demand points. Possibility chance constraints and objective constraints were constructed based on objective-subjective data. The FMOELTP was constructed in a static and fuzzy environment since the decisions to be made are taken immediately after the disaster (during few hours) with the information available at that moment. It is assumed that the requests for products are estimated by homeland security organizations, or their experts, based upon their experience and their evaluation of the disaster’s seriousness. Estimated transportation times are considered to take into account routing access difficulty of the region and the infrastructure conditions. We propose an epsilon-constraint method for finding the exact solutions for the problem. It is proved that this approach generates the exact Pareto front of the multi-objective location-transportation problem addressed. Sometimes for large dimensions of the problem, the exact method requires long computing times. Thus, we propose an approximate method that imposes a number of stopping criteria on the exact method. For large dimensions of the FMOELTP the Estimation of Distribution Algorithm’s (EDA) approach is developed.

Keywords: epsilon-constraint method, estimation of distribution algorithm, fuzzy multi-objective combinatorial programming problem, fuzzy multi-objective emergency location/transportation problem

Procedia PDF Downloads 293

Authors: Sabina Huč, Staffan Svensson, Tomaž Hozjan

Abstract:

Timber structures may be exposed to various environmental conditions during their service life. Often, the structures have to resist extreme changes in the relative humidity of surrounding air, with simultaneously carrying the loads. Wood material response for this load case is seen as increasing deformation of the timber structure. Relative humidity variations cause moisture changes in timber and consequently shrinkage and swelling of the material. Moisture changes and loads acting together result in mechano-sorptive creep, while sustained load gives viscoelastic creep. In some cases, magnitude of the mechano-sorptive strain can be about five times the elastic strain already at low stress levels. Therefore, analyzing mechano-sorptive creep and its influence on timber structures’ long-term behavior is of high importance. Relatively many one-dimensional rheological models for rheological behavior of wood can be found in literature, while a number of models coupling creep response in each material direction is limited. In this study, mathematical formulation of a coupled two-dimensional mechano-sorptive model and its application to the experimental results are presented. The mechano-sorptive model constitutes of a moisture transport model and a mechanical model. Variation of the moisture content in wood is modelled by multi-Fickian moisture transport model. The model accounts for processes of the bound-water and water-vapor diffusion in wood, that are coupled through sorption hysteresis. Sorption defines a nonlinear relation between moisture content and relative humidity. Multi-Fickian moisture transport model is able to accurately predict unique, non-uniform moisture content field within the timber member over time. Calculated moisture content in timber members is used as an input to the mechanical analysis. In the mechanical analysis, the total strain is assumed to be a sum of the elastic strain, viscoelastic strain, mechano-sorptive strain, and strain due to shrinkage and swelling. Mechano-sorptive response is modelled by so-called spring-dashpot type of a model, that proved to be suitable for describing creep of wood. Mechano-sorptive strain is dependent on change of moisture content. The model includes mechano-sorptive material parameters that have to be calibrated to the experimental results. The calibration is made to the experiments carried out on wooden blocks subjected to uniaxial compressive loaded in tangential direction and varying humidity conditions. The moisture and the mechanical model are implemented in a finite element software. The calibration procedure gives the required, distinctive set of mechano-sorptive material parameters. The analysis shows that mechano-sorptive strain in transverse direction is present, though its magnitude and variation are substantially lower than the mechano-sorptive strain in the direction of loading. The presented mechano-sorptive model enables observing real temporal and spatial distribution of the moisture-induced strains and stresses in timber members. Since the model’s suitability for predicting mechano-sorptive strains is shown and the required material parameters are obtained, a comprehensive advanced analysis of the stress-strain state in timber structures, including connections subjected to constant load and varying humidity is possible.

Keywords: mechanical analysis, mechano-sorptive creep, moisture transport model, timber

Procedia PDF Downloads 220

Authors: Norma Binti Alias, Che Rahim Che The, Norfarizan Mohd Said, Sakinah Abdul Hanan, Akhtar Ali

Abstract:

This paper discusses on the transportation of magnetic drug targeting through blood within vessels, tissues and cells. There are three integrated mathematical models to be discussed and analyze the concentration of drug and blood flow through magnetic nanoparticles. The cell therapy brought advancement in the field of nanotechnology to fight against the tumors. The systematic therapeutic effect of Single Cells can reduce the growth of cancer tissue. The process of this nanoscale phenomena system is able to measure and to model, by identifying some parameters and applying fundamental principles of mathematical modeling and simulation. The mathematical modeling of single cell growth depends on three types of cell densities such as proliferative, quiescent and necrotic cells. The aim of this paper is to enhance the simulation of three types of models. The first model represents the transport of drugs by coupled partial differential equations (PDEs) with 3D parabolic type in a cylindrical coordinate system. This model is integrated by Non-Newtonian flow equations, leading to blood liquid flow as the medium for transportation system and the magnetic force on the magnetic nanoparticles. The interaction between the magnetic force on drug with magnetic properties produces induced currents and the applied magnetic field yields forces with tend to move slowly the movement of blood and bring the drug to the cancer cells. The devices of nanoscale allow the drug to discharge the blood vessels and even spread out through the tissue and access to the cancer cells. The second model is the transport of drug nanoparticles from the vascular system to a single cell. The treatment of the vascular system encounters some parameter identification such as magnetic nanoparticle targeted delivery, blood flow, momentum transport, density and viscosity for drug and blood medium, intensity of magnetic fields and the radius of the capillary. Based on two discretization techniques, finite difference method (FDM) and finite element method (FEM), the set of integrated models are transformed into a series of grid points to get a large system of equations. The third model is a single cell density model involving the three sets of first order PDEs equations for proliferating, quiescent and necrotic cells change over time and space in Cartesian coordinate which regulates under different rates of nutrients consumptions. The model presents the proliferative and quiescent cell growth depends on some parameter changes and the necrotic cells emerged as the tumor core. Some numerical schemes for solving the system of equations are compared and analyzed. Simulation and computation of the discretized model are supported by Matlab and C programming languages on a single processing unit. Some numerical results and analysis of the algorithms are presented in terms of informative presentation of tables, multiple graph and multidimensional visualization. As a conclusion, the integrated of three types mathematical modeling and the comparison of numerical performance indicates that the superior tool and analysis for solving the complete set of magnetic drug delivery system which give significant effects on the growth of the targeted cancer cell.

Keywords: mathematical modeling, visualization, PDE models, magnetic nanoparticle drug delivery model, drug release model, single cell effects, avascular tumor growth, numerical analysis

Procedia PDF Downloads 400

Authors: Michael Ray Brunt

Abstract:

China has been the site of some of the most significant earthquakes in history; however, earthquake monitoring has long been the provenance of universities and research institutions. The China Digital Seismographic Network was initiated in 1983 and improved significantly during 1992-1993. Data from the CDSN is widely used by government and research institutions, and, generally, this data is not readily accessible to middle and high school students. An educational seismic network in China is needed to provide collaboration and research opportunities for students and engaging students around the country in scientific understanding of earthquake hazards and risks while promoting community awareness. In 2022, the Tsinghua International School (THIS) Seismology Team, made up of enthusiastic students and facilitated by two experienced teachers, was established. As a group, the team’s objective is to install seismographs in schools throughout China, thus creating an educational seismic network that shares data from the THIS Educational Seismic Network (THIS-ESN) and facilitates collaboration. The THIS-ESN initiative will enhance education and outreach in China about earthquake risks and hazards, introduce seismology to a wider audience, stimulate interest in research among students, and develop students’ programming, data collection and analysis skills. It will also encourage and inspire young minds to pursue science, technology, engineering, the arts, and math (STEAM) career fields. The THIS-ESN utilizes small, low-cost RaspberryShake seismographs as a powerful tool linked into a global network, giving schools and the public access to real-time seismic data from across China, increasing earthquake monitoring capabilities in the perspective areas and adding to the available data sets regionally and worldwide helping create a denser seismic network. The RaspberryShake seismograph is compatible with free seismic data viewing platforms such as SWARM, RaspberryShake web programs and mobile apps are designed specifically towards teaching seismology and seismic data interpretation, providing opportunities to enhance understanding. The RaspberryShake is powered by an operating system embedded in the Raspberry Pi, which makes it an easy platform to teach students basic computer communication concepts by utilizing processing tools to investigate, plot, and manipulate data. THIS Seismology Team believes strongly in creating opportunities for committed students to become part of the seismological community by engaging in analysis of real-time scientific data with tangible outcomes. Students will feel proud of the important work they are doing to understand the world around them and become advocates spreading their knowledge back into their homes and communities, helping to improve overall community resilience. We trust that, in studying the results seismograph stations yield, students will not only grasp how subjects like physics and computer science apply in real life, and by spreading information, we hope students across the country can appreciate how and why earthquakes bear on their lives, develop practical skills in STEAM, and engage in the global seismic monitoring effort. By providing such an opportunity to schools across the country, we are confident that we will be an agent of change for society.

Keywords: collaboration, outreach, education, seismology, earthquakes, public awareness, research opportunities

Procedia PDF Downloads 36

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

Abstract:

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

Procedia PDF Downloads 28