Search results for: large herbivores

Authors: Byoungjoon Yu, Jihwan Park, Sujung Sin, Junghyun Im, Minsoo Park, Sehwan Park, Seunghee Park

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In this paper, we propose a technology to monitor the soundness of an Internet-based bridge using a non-conductive inspection function. There has been a collapse accident due to the aging of the bridge structure, and it is necessary to prepare for the deterioration of the bridge. The NDT/SHM system for maintenance of existing bridge structures requires a large number of inspection personnel and expensive inspection costs, and access of expensive and large equipment to measurement points is required. Because current drone inspection equipment can only be inspected through camera, it is difficult to inspect inside damage accurately, and the results of an internal damage evaluation are subjective, and it is difficult for non-specialists to recognize the evaluation results. Therefore, it is necessary to develop NDT/SHM techniques for maintenance of new-concept bridge structures that allow for free movement and real-time evaluation of measurement results. This work is financially supported by Korea Ministry of Land, Infrastructure, and Transport (MOLIT) as 'Smart City Master and Doctor Course Grant Program' and a grant (14SCIP-B088624-01) from Construction Technology Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Keywords: Structural Health Monitoring, SHM, non-contact sensing, nondestructive testing, NDT, Internet of Things, autonomous self-driving drone

Procedia PDF Downloads 257

Authors: Gabrielle Peck, Ryan Hayes

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This research presents the design and creation of a drone gas analyser, aimed at addressing the need for independent data collection and analysis of gas emissions during large-scale fires, particularly wasteland fires. The analyser drone, comprising a lightweight gas analysis system attached to a remote-controlled drone, enables the real-time assessment of smoke toxicity and the monitoring of gases released into the atmosphere during such incidents. The key components of the analyser unit included two gas line inlets connected to glass wool filters, a pump with regulated flow controlled by a mass flow controller, and electrochemical cells for detecting nitrogen oxides, hydrogen cyanide, and oxygen levels. Additionally, a non-dispersive infrared (NDIR) analyser is employed to monitor carbon monoxide (CO), carbon dioxide (CO₂), and hydrocarbon concentrations. Thermocouples can be attached to the analyser to monitor temperature, as well as McCaffrey probes combined with pressure transducers to monitor air velocity and wind direction. These additions allow for monitoring of the large fire and can be used for predictions of fire spread. The innovative system not only provides crucial data for assessing smoke toxicity but also contributes to fire prediction and management. The remote-controlled drone's mobility allows for safe and efficient data collection in proximity to the fire source, reducing the need for human exposure to hazardous conditions. The data obtained from the gas analyser unit facilitates informed decision-making by emergency responders, aiding in the protection of both human health and the environment. This abstract highlights the successful development of a drone gas analyser, illustrating its potential for enhancing smoke toxicity analysis and fire prediction capabilities. The integration of this technology into fire management strategies offers a promising solution for addressing the challenges associated with wildfires and other large-scale fire incidents. The project's methodology and results contribute to the growing body of knowledge in the field of environmental monitoring and safety, emphasizing the practical utility of drones for critical applications.

Keywords: fire prediction, drone, smoke toxicity, analyser, fire management

Procedia PDF Downloads 74

Authors: I. Tzoka, V. A. Chirayath, A. Brandt, J. Asaadi, Melvin J. Aviles, Stephen Clarke, Stefan Cwik, Michael R. Foley, Cole J. Hamel, Alexey Lyashenko, Michael J. Minot, Mark A. Popecki, Michael E. Stochaj, S. Shin

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Micro-channel plate photo-multiplier tubes (MCP-PMTs) have become ubiquitous and are widely considered potential candidates for next generation High Energy Physics experiments due to their picosecond timing resolution, ability to operate in strong magnetic fields, and low noise rates. A key factor that determines the applicability of MCP-PMTs in their lifetime, especially when they are used in high event rate experiments. We have developed a novel method for the investigation of the aging behavior of an MCP-PMT on an accelerated basis. The method involves exposing a localized region of the MCP-PMT to photons at a high repetition rate. This pixel-based method was inspired by earlier results showing that damage to the photocathode of the MCP-PMT occurs primarily at the site of light exposure and that the surrounding region undergoes minimal damage. One advantage of the pixel-based method is that it allows the dynamics of photo-cathode damage to be studied at multiple locations within the same MCP-PMT under different operating conditions. In this work, we use the pixel-based accelerated lifetime test to investigate the aging behavior of a 20 cm x 20 cm Large Area Picosecond Photo Detector (LAPPD) manufactured by INCOM Inc. at multiple locations within the same device under different operating conditions. We compare the aging behavior of the MCP-PMT obtained from the first lifetime test conducted under high gain conditions to the lifetime obtained at a different gain. Through this work, we aim to correlate the lifetime of the MCP-PMT and the rate of ion feedback, which is a function of the gain of each MCP, and which can also vary from point to point across a large area (400 $cm^2$) MCP. The tests were made possible by the uniqueness of the LAPPD design, which allows independent control of the gain of the chevron stacked MCPs. We will further discuss the implications of our results for optimizing the operating conditions of the detector when used in high event rate experiments.

Keywords: electron multipliers (vacuum), LAPPD, lifetime, micro-channel plate photo-multipliers tubes, photoemission, time-of-flight

Procedia PDF Downloads 155

Authors: Shubham Damke, Md Imtiaz, Sanchita Dei

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To stimulate the well and to enhance the production from the shaly formations, fracturing is essential. Presently the chiefly employed technology is Hydraulic Fracturing. However Hydraulic Fracturing accompanies itself with problems like disposing large volumes of fracturing wastewater, removal of water from the pores, formation damage due to injection of large amount of chemicals into underground formations and many more. Therefore embarking on the path of innovation new techniques have been developed which uses different gases such as Nitrogen, Carbon dioxide, Frac Oil, LPG, etc. are used as a base fluid for fracturing formation. However LPG proves to be the most favorable of them which eliminates the use of water and chemicals. When using it as a fracturing fluid, within the surface equipment, it is stored, gelled, and proppant blended at a constant pressure. It is then pressurized with high pressure pumps to the required surface injection pressure With lowering the total cost and increasing the productivity, LPG is also very noteworthy for fracturing shale, where if the hydraulic fracturing is done the water ‘swells’ the formation and creates surface tension, both of which inhibit the flow of oil and gas. Also fracturing with LPG increases the effective fracture length and since propane, butane and pentane is used which are already present in the natural gas therefore there is no problem of back flow because these gases get mixed with the natural gas. LPG Fracturing technology can be a promising substitute of the Hydraulic Fracturing, which could substantially reduce the capital cost of fracturing shale and will also restrict the problems with the disposal of water and on the same hand increasing the fracture length and the productivity from the shale.

Keywords: Fracking, Shale, Surface Tension, Viscosity

Procedia PDF Downloads 411

Authors: Sanjeet Kumar Singh, Shanatanu Bhattacharaya

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Design of high- efficiency low, frequency (<1000Hz) soundproof window or wall absorber which is transparent to airflow is presented. Due to the massive rise in human population and modernization, environmental noise has significantly risen globally. Prolonged noise exposure can cause severe physiological and psychological symptoms like nausea, headaches, fatigue, and insomnia. There has been continuous growth in building construction and infrastructure like offices, bus stops, and airports due to urban population. Generally, a ventilated window is used for getting fresh air into the room, but at the same time, unwanted noise comes along. Researchers used traditional approaches like noise barrier mats in front of the window or designed the entire window using sound-absorbing materials. However, this solution is not aesthetically pleasing, and at the same time, it's heavy and not adequate for low-frequency noise shielding. To address this challenge, we design a transparent hexagonal panel based on Sierpiński fractal triangle, which is aesthetically pleasing, demonstrates normal incident sound absorption coefficient more than 0.96 around 700 Hz and transmission loss around 23 dB while maintaining e air circulation through triangular cutout. Next, we present a concept of fabrication of large acoustic panel for large-scale applications, which lead to suppressing the urban noise pollution.

Keywords: acoustic metamaterials, noise, functional materials, ventilated

Procedia PDF Downloads 66

Authors: Wei-Shan Wang, Klaus Vogel, Felix Gabler, Maik Wiemer, Thomas Gessner

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Metallic glasses, which are free of grain boundaries, have superior properties including large elastic limits, high strength, and excellent wear and corrosion resistance. Therefore, bulk metallic glasses (BMG) and thin film metallic glasses (TFMG) have been widely developed and investigated. Among various kinds of metallic glasses, Pd-Cu-Si TFMG, which has lower elastic modulus and better resistance of oxidation and corrosions compared to Zr- and Fe-based TFMGs, can be a promising candidate for MEMS applications. However, the study of Pd-TFMG membrane is still limited. This paper presents free-standing Pd-based metallic glass membranes with large area fabricated on wafer level for the first time. Properties of Pd-Cu-Si thin film metallic glass (TFMG) with various deposition parameters are investigated first. When deposited at 25°C, compressive stress occurs in the Pd76Cu6Si18 thin film regardless of Ar pressure. When substrate temperature is increased to 275°C, the stress state changes from compressive to tensile. Thin film stresses are slightly decreased when Ar pressure is higher. To show the influence of temperature on Pd-TFMGs, thin films without and with post annealing below (275°C) and within (370°C) supercooled liquid region are investigated. Results of XRD and TEM analysis indicate that Pd-TFMGs remain amorphous structure with well-controlled parameters. After verification of amorphous structure of the Pd-TFMGs, free-standing Pd-Cu-Si membranes were fabricated by depositing Pd-Cu-Si thin films directly on 200nm-thick silicon nitride membranes, followed by post annealing and dry etching of silicon nitride layer. Post annealing before SiNx removal is used to further release internal stress of Pd-TFMGs. The edge length of the square membrane ranges from 5 to 8mm. The effect of post annealing on Pd-Cu-Si membranes are discussed as well. With annealing at 370°C for 5 min, Pd-MG membranes are fully distortion-free after removal of SiNx layer. Results show that, by introducing annealing process, the stress-relief, distortion-free Pd-TFMG membranes with large area can be a promising candidate for sensing applications such as pressure and gas sensors.

Keywords: amorphous alloy, annealing, metallic glasses, TFMG membrane

Procedia PDF Downloads 341

Authors: Angelina Chiglintseva, Vladislav Shagapov

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We know from the geological data that quite sufficient gas reserves are concentrated in hydrates that occur on the Earth and on the ocean floor. Therefore, the development of these sources of energy and the storage of large reserves of gas hydrates is an acute global problem. An advanced technology for utilizing gas is to store it in a gas-hydrate state. Under natural conditions, storage facilities can be established, e.g., in underground reservoirs, where quite large volumes of gas can be conserved compared with reservoirs of pure gas. An analysis of the available experimental data of the kinetics and the mechanism of the gas-hydrate formation process shows the self-conservation effect that allows gas to be stored at negative temperatures and low values of pressures of up to several atmospheres. A theoretical model has been constructed for the gas-hydrate reservoir that represents a unique natural chemical reactor, and the principal possibility of the full extraction of gas from a hydrate due to the thermal reserves of the reservoirs themselves and the surrounding rocks has been analyzed. The influence exerted on the evolution of a gas hydrate reservoir by the reservoir thicknesses and the parameters that determine its initial state (a temperature, pressure, hydrate saturation) has been studied. It has been established that the shortest time of exploitation required by the reservoirs with a thickness of a few meters for the total hydrate decomposition is recorded in the cyclic regime when gas extraction alternated with the subsequent conservation of the gas hydrate deposit. The study was performed by a grant from the Russian Science Foundation (project No.15-11-20022).

Keywords: conservation, equilibrium state, gas hydrate reservoir, rocks

Procedia PDF Downloads 285

Authors: Armen Grigoryan, Milena Arakelyan

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The idea of smart logistics is still quite a complicated one. It can be used to market products to a large number of customers or to acquire raw materials of the highest quality at the lowest cost in geographically dispersed areas. The use of smart contracts in logistics and supply chain management has the potential to revolutionize the way that goods are tracked, transported, and managed. Smart contracts are simply computer programs written in one of the blockchain programming languages (Solidity, Rust, Vyper), which are capable of self-execution once the predetermined conditions are met. They can be used to automate and streamline many of the traditional manual processes that are currently used in logistics and supply chain management, including the tracking and movement of goods, the management of inventory, and the facilitation of payments and settlements between different parties in the supply chain. Currently, logistics is a core area for companies which is concerned with transporting products between parties. Still, the problem of this sector is that its scale may lead to detainments and defaults in the delivery of goods, as well as other issues. Moreover, large distributors require a large number of workers to meet all the needs of their stores. All this may contribute to big detainments in order processing and increases the potentiality of losing orders. In an attempt to break this problem, companies have automated all their procedures, contributing to a significant augmentation in the number of businesses and distributors in the logistics sector. Hence, blockchain technology and smart contracted legal agreements seem to be suitable concepts to redesign and optimize collaborative business processes and supply chains. The main purpose of this paper is to examine the scope of blockchain technology and smart contracts in the field of logistics and supply chain management. This study discusses the research question of how and to which extent smart contracts and blockchain technology can facilitate and improve the implementation of collaborative business structures for sustainable entrepreneurial activities in smart supply chains. The intention is to provide a comprehensive overview of the existing research on the use of smart contracts in logistics and supply chain management and to identify any gaps or limitations in the current knowledge on this topic. This review aims to provide a summary and evaluation of the key findings and themes that emerge from the research, as well as to suggest potential directions for future research on the use of smart contracts in logistics and supply chain management.

Keywords: smart contracts, smart logistics, smart supply chain management, blockchain and smart contracts in logistics, smart contracts for controlling supply chain management

Procedia PDF Downloads 78

Authors: Sanjeet Kumar Singh, Shantanu Bhatacharya

Abstract:

Design of high-efficiency low, frequency (<1000Hz) soundproof window or wall absorber which is transparent to airflow is presented. Due to the massive rise in human population and modernization, environmental noise has significantly risen globally. Prolonged noise exposure can cause severe physiological and psychological symptoms like nausea, headaches, fatigue, and insomnia. There has been continuous growth in building construction and infrastructure like offices, bus stops, and airports due to the urban population. Generally, a ventilated window is used for getting fresh air into the room, but at the same time, unwanted noise comes along. Researchers used traditional approaches like noise barrier mats in front of the window or designed the entire window using sound-absorbing materials. However, this solution is not aesthetically pleasing, and at the same time, it's heavy and not adequate for low-frequency noise shielding. To address this challenge, we design a transparent hexagonal panel based on the Sierpiński fractal triangle, which is aesthetically pleasing and demonstrates a normal incident sound absorption coefficient of more than 0.96 around 700 Hz and transmission loss of around 23 dB while maintaining e air circulation through the triangular cutout. Next, we present a concept of fabrication of large acoustic panels for large-scale applications, which leads to suppressing urban noise pollution.

Keywords: acoustic metamaterials, ventilation, urban noise pollution, noise control

Procedia PDF Downloads 100

Authors: Matthew Baucum

Abstract:

With the increasing popularity of fMRI as an experimental method, psychology and neuroscience can greatly benefit from advanced techniques for summarizing and synthesizing large amounts of data from brain imaging studies. One promising avenue is automated meta-analyses, in which natural language processing methods are used to identify the brain regions consistently associated with certain semantic concepts (e.g. “social”, “reward’) across large corpora of studies. This study builds on this approach by demonstrating how, in fMRI meta-analyses, individual voxels can be treated as vectors in a semantic space and evaluated for their “proximity” to terms of interest. In this technique, a low-dimensional semantic space is built from brain imaging study texts, allowing words in each text to be represented as vectors (where words that frequently appear together are near each other in the semantic space). Consequently, each voxel in a brain mask can be represented as a normalized vector sum of all of the words in the studies that showed activation in that voxel. The entire brain mask can then be visualized in terms of each voxel’s proximity to a given term of interest (e.g., “vision”, “decision making”) or collection of terms (e.g., “theory of mind”, “social”, “agent”), as measured by the cosine similarity between the voxel’s vector and the term vector (or the average of multiple term vectors). Analysis can also proceed in the opposite direction, allowing word cloud visualizations of the nearest semantic neighbors for a given brain region. This approach allows for continuous, fine-grained metrics of voxel-term associations, and relies on state-of-the-art “open vocabulary” methods that go beyond mere word-counts. An analysis of over 11,000 neuroimaging studies from an existing meta-analytic fMRI database demonstrates that this technique can be used to recover known neural bases for multiple psychological functions, suggesting this method’s utility for efficient, high-level meta-analyses of localized brain function. While automated text analytic methods are no replacement for deliberate, manual meta-analyses, they seem to show promise for the efficient aggregation of large bodies of scientific knowledge, at least on a relatively general level.

Keywords: FMRI, machine learning, meta-analysis, text analysis

Procedia PDF Downloads 435

Authors: Chao Sima, Shanaz Ghandhi, Sally A. Amundson, Michael L. Bittner, David J. Brenner

Abstract:

In a large-scale radiologic emergency, potentially affected population need to be triaged efficiently using various biomarkers where personal dosimeters are not likely worn by the individuals. It has long been established that radiation injury can be estimated effectively using panels of genetic biomarkers. Furthermore, the rate of radiation, in addition to dose of radiation, plays a major role in determining biological responses. Therefore, a better and more accurate triage involves estimating both the dose level of the exposure and the length of time of that exposure. To that end, a large in vivo study was carried out on mice with internal emitter caesium-137 (¹³⁷Cs). Four different injection doses of ¹³⁷Cs were used: 157.5 μCi, 191 μCi, 214.5μCi, and 259 μCi. Cohorts of 6~7 mice from the control arm and each of the dose levels were sacrificed, and blood was collected 2, 3, 5, 7 and 14 days after injection for microarray RNA gene expression analysis. Using a generalized linear model with penalized maximum likelihood, a panel of 244 genes was established and both the doses of injection and the number of days after injection were accurately predicted for all 155 subjects using this panel. This has proven that microarray gene expression can be used effectively in radiation biodosimetry in predicting both the dose levels and the length of exposure time, which provides a more holistic view on radiation exposure and helps improving radiation damage assessment and treatment.

Keywords: caesium-137, gene expression microarray, multivariate responses prediction, radiation biodosimetry

Procedia PDF Downloads 186

Authors: Siyang Wang, Yujin Hu, Xuelin Wang, Wenqian Zhang

Abstract:

Austenitic stainless steels are widely used in nuclear industry to manufacture critical components owing to their excellent corrosion resistance at high temperatures. Almost all the components used in nuclear power plants are produced by surface finishing (surface cold work) such as milling, grinding and so on. The change of surface states induced by machining has great influence on the corrosion behavior. In the present study, long time oxidation behavior of machined 316 austenitic stainless steel exposed to simulated pressure water reactor environment was investigated considering different surface states. Four surface finishes were produced by electro-polishing (P), grinding (G), and two milling (M and M1) processes respectively. Before oxidation, the surface Vickers micro-hardness, surface roughness of each type of sample was measured. Corrosion behavior of four types of sample was studied by using oxidation weight gain method for six oxidation periods. The oxidation time of each period was 120h, 216h, 336h, 504h, 672h and 1344h, respectively. SEM was used to observe the surface morphology of oxide film in several period. The results showed that oxide film on austenitic stainless steel has a duplex-layer structure. The inner oxide film is continuous and compact, while the outer layer is composed of oxide particles. The oxide particle consisted of large particles (nearly micron size) and small particles (dozens of nanometers to a few hundred nanometers). The formation of oxide particle could be significantly affected by the machined surface states. The large particle on cold worked samples (grinding and milling) appeared earlier than electro-polished one, and the milled sample has the largest particle size followed by ground one and electro-polished one. For machined samples, the large particles were almost distributed along the direction of machining marks. Severe exfoliation was observed on one milled surface (M) which had the most heavily cold worked layer, while rare local exfoliation occurred on the ground sample (G) and the other milled sample (M1). The electro-polished sample (P) entirely did not exfoliate.

Keywords: austenitic stainless steel, oxidation, machining, SEM

Procedia PDF Downloads 275

Authors: Anna Lower, Michal Lower, Robert Masztalski, Agnieszka Szumilas

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Contemporary cities are facing serious congestion and parking problems. In urban transport policy the introduction of the park and ride system (P&R) is an increasingly popular way of limiting vehicular traffic. The determining of P&R facilities location is a key aspect of the system. Criteria for assessing the quality of the selected location are formulated generally and descriptively. The research outsourced to specialists are expensive and time consuming. The most focus is on the examination of a few selected places. The practice has shown that the choice of the location of these sites in a intuitive way without a detailed analysis of all the circumstances, often gives negative results. Then the existing facilities are not used as expected. Methods of location as a research topic are also widely taken in the scientific literature. Built mathematical models often do not bring the problem comprehensively, e.g. assuming that the city is linear, developed along one important communications corridor. The paper presents a new method where the expert knowledge is applied to fuzzy inference model. With such a built system even a less experienced person could benefit from it, e.g. urban planners, officials. The analysis result is obtained in a very short time, so a large number of the proposed location can also be verified in a short time. The proposed method is intended for testing of car parks location in a city. The paper will show selected examples of locations of the P&R facilities in cities planning to introduce the P&R. The analysis of existing objects will also be shown in the paper and they will be confronted with the opinions of the system users, with particular emphasis on unpopular locations. The research are executed using the fuzzy inference model which was built and described in more detail in the earlier paper of the authors. The results of analyzes are compared to documents of P&R facilities location outsourced by the city and opinions of existing facilities users expressed on social networking sites. The research of existing facilities were conducted by means of the fuzzy model. The results are consistent with actual users feedback. The proposed method proves to be good, but does not require the involvement of a large experts team and large financial contributions for complicated research. The method also provides an opportunity to show the alternative location of P&R facilities. The performed studies show that the method has been confirmed. The method can be applied in urban planning of the P&R facilities location in relation to the accompanying functions. Although the results of the method are approximate, they are not worse than results of analysis of employed experts. The advantage of this method is ease of use, which simplifies the professional expert analysis. The ability of analyzing a large number of alternative locations gives a broader view on the problem. It is valuable that the arduous analysis of the team of people can be replaced by the model's calculation. According to the authors, the proposed method is also suitable for implementation on a GIS platform.

Keywords: fuzzy logic inference, park and ride system, P&R facilities, P&R location

Procedia PDF Downloads 316

Authors: Şemsettin Şahin, Ahmet Oğuz Aktürk, İsmail Çelik

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This study investigated the views of teachers, students and students' parents on the FATIH (Movement of Enhancing Opportunities and Improving Technology) Project, which was put into service by the Ministry of National Education in cooperation with the Ministry of Transportation in Turkey in November 2010 for the purpose of increasing students' success and planned to be completed within 5 years. The study group consisted of teachers employed in a pilot school in the province of Karaman in central Turkey included within the scope of the FATIH Project, students attending this school and parents whose children are students in that school. The research data were collected through forms developed by the researchers to determine the views of teachers, students and students' parents on the FATIH Project. The descriptive analysis method, one of the qualitative research methods, was used in the study. An analysis of the data revealed that a large majority of the teachers and the students believed that if computers were used to serve their set purpose, then they could make considerable contributions to education. A large majority of the students' parents, on the other hand, regard the use of computers in education as a great opportunity for the students. The views of the teachers, students and students' parents on the FATIH Project usually overlap. Most of the participants in the study pointed out that the FATIH Project was intended to use technology effectively in education. Moreover, each individual participant described their role in the FATIH Project in accordance with their relative position and stated that they could perform whatever was expected of them for the effective and efficient use and progress of the project. The views of the participants regarding the FATİH Project vary according to the kind of the participants.

Keywords: education, FATIH project, technology, students

Procedia PDF Downloads 431

Authors: Yazid Abdullahi Abubakar, Jay Mitra

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This paper is concerned with entrepreneurial high-impact firms, which are firms that generate ‘both’ disproportionate levels of employment and sales growth, and have high levels of innovative activity. It investigates differences in factors influencing high-impact growth between indigenous and foreign firms. The study is based on an analysis of data from United Kingdom (UK) Innovation Scoreboard on 865 firms, which were divided into high-impact firms (those achieving positive growth in both sales and employment) and low-impact firms (negative or no growth in sales or employment); in order to identifying the critical differences in regional, sectorial and size related factors that facilitate knowledge spillovers and high-impact growth between indigenous and foreign firms. The findings suggest that: 1) Firms’ access to regional knowledge spillovers (from businesses and higher education institutions) is more significantly associated with high-impact growth of UK firms in comparison to foreign firms, 2) Because high-tech sectors have greater use of knowledge spillovers (compared to low-tech sectors), high-tech sectors are more associated with high-impact growth, but the relationship is stronger for UK firms compared to foreign firms, 3) Because small firms have greater need for knowledge spillovers (relative to large firms), there is a negative relationship between firm size and high-impact growth, but the negative relationship is greater for UK firms in comparison to foreign firms.

Keywords: entrepreneurship, high-growth, indigenous firms, foreign firms, small firms, large firms

Procedia PDF Downloads 415

Authors: Nadine Maier, Martin Mensinger, Enea Tallushi

Abstract:

In general, today, two types of launching bearings are used in the construction of large steel and steel concrete composite bridges. These are sliding rockers and systems with hydraulic bearings. The advantages and disadvantages of the respective systems are under discussion. During incremental launching, the center of the webs of the superstructure is not perfectly in line with the center of the launching bearings due to unavoidable tolerances, which may have an influence on the buckling behavior of the web plates. These imperfections are not considered in the current design against plate buckling, according to DIN EN 1993-1-5. It is therefore investigated whether the design rules have to take into account any eccentricities which occur during incremental launching and also if this depends on the respective launching bearing. Therefore, at the Technical University Munich, large-scale buckling tests were carried out on longitudinally stiffened plates under biaxial stresses with the two different types of launching bearings and eccentric load introduction. Based on the experimental results, a numerical model was validated. Currently, we are evaluating different parameters for both types of launching bearings, such as load introduction length, load eccentricity, the distance between longitudinal stiffeners, the position of the rotation point of the spherical bearing, which are used within the hydraulic bearings, web, and flange thickness and imperfections. The imperfection depends on the geometry of the buckling field and whether local or global buckling occurs. This and also the size of the meshing is taken into account in the numerical calculations of the parametric study. As a geometric imperfection, the scaled first buckling mode is applied. A bilinear material curve is used so that a GMNIA analysis is performed to determine the load capacity. Stresses and displacements are evaluated in different directions, and specific stress ratios are determined at the critical points of the plate at the time of the converging load step. To evaluate the load introduction of the transverse load, the transverse stress concentration is plotted on a defined longitudinal section on the web. In the same way, the rotation of the flange is evaluated in order to show the influence of the different degrees of freedom of the launching bearings under eccentric load introduction and to be able to make an assessment for the case, which is relevant in practice. The input and the output are automatized and depend on the given parameters. Thus we are able to adapt our model to different geometric dimensions and load conditions. The programming is done with the help of APDL and a Python code. This allows us to evaluate and compare more parameters faster. Input and output errors are also avoided. It is, therefore, possible to evaluate a large spectrum of parameters in a short time, which allows a practical evaluation of different parameters for buckling behavior. This paper presents the results of the tests as well as the validation and parameterization of the numerical model and shows the first influences on the buckling behavior under eccentric and multi-axial load introduction.

Keywords: buckling behavior, eccentric load introduction, incremental launching, large scale buckling tests, multi axial stress states, parametric numerical modelling

Procedia PDF Downloads 101

Authors: L. Pu, C. Unluer

Abstract:

MgO cements have the potential to sequester CO2 in construction products, and can be partial or complete replacement of PC in concrete. Construction block is a promising application for reactive MgO cements. Main advantages of blocks are: (i) suitability for sequestering CO2 due to their initially porous structure; (ii) lack of need for in-situ treatment as carbonation can take place during fabrication; and (iii) high potential for commercialization. Both strength gain and carbon sequestration of MgO cements depend on carbonation process. Fly ash and ground granulated blast-furnace slag (GGBS) are pozzolanic material and are proved to improve many of the performance characteristics of the concrete, such as strength, workability, permeability, durability and corrosion resistance. A very limited amount of work has been reported on the production of MgO blocks on a large scale so far. A much more extensive study, wherein blocks with different mix design is needed to verify the feasibility of commercial production. The changes in the performance of the samples were evaluated by compressive strength testing. The properties of the carbonation products were identified by X-ray diffraction (XRD) and scanning electron microscopy (SEM)/ field emission scanning electron microscopy (FESEM), and the degree of carbonation was obtained by thermogravimetric analysis (TGA), XRD and energy dispersive X-ray (EDX). The results of this study enabled the understanding the relationship between lab-scale samples and scale-up blocks based on their mechanical performance and microstructure. Results indicate that for both scaled-up and lab-scale samples, MgO samples always had the highest strength results, followed by MgO-fly ash samples and MgO-GGBS had relatively lowest strength. The lower strength of MgO with fly ash/GGBS samples at early stage is related to the relatively slow hydration process of pozzolanic materials. Lab-scale cubic samples were observed to have higher strength results than scaled-up samples. The large size of the scaled-up samples made it more difficult to let CO2 to reach inner part of the samples and less carbonation products formed. XRD, TGA and FESEM/EDX results indicate the existence of brucite and HMCs in MgO samples, M-S-H, hydrotalcite in the MgO-fly ash samples and C-S-H, hydrotalctie in the MgO-GGBS samples. Formation of hydration products (M-S-H, C-S-H, hydrotalcite) and carbonation products (hydromagnecite, dypingite) increased with curing duration, which is the reason of increasing strength. This study verifies the advantage of large-scale MgO blocks over common PC blocks and the feasibility of commercial production of MgO blocks.

Keywords: reactive MgO, fly ash, ground granulated blast-furnace slag, carbonation, CO₂

Procedia PDF Downloads 177

Authors: Moon Moon Devi, Ran Budnik

Abstract:

The current large area cosmic ray detector surface arrays typically measure only the net flux and arrival-time of the charged particles produced in an extensive air shower (EAS). Measurement of the individual charged particles at a surface array will provide additional distinguishing parameters to identify the primary and to map the very high energy interactions in the upper layers of the atmosphere. In turn, these may probe anomalies in QCD interactions at energies beyond the reach of current accelerators. The recent attempts of studying the individual muon tracks are limited in their expandability to larger arrays and can only probe primary particles with energy up to about 10^15.5 eV. New developments in detector technology allow for a realistic cost of large area detectors, however with limitations on energy resolutions, directional information, and dynamic range. In this study, we perform a simulation study using CORSIKA to combine the energy spectrum and lateral spread of the muons with the longitudinal depth (Xmax) of an EAS initiated by a primary at ultra high energies (10¹⁶ – 10¹⁹) eV. Using proton and iron as the shower primaries, we show that the muon observables and Xmax together can be used to distinguish the primary. This study can be used to design a future detector for the surface array, which will be able to enhance our knowledge of primaries and QCD interactions.

Keywords: ultra high energy extensive air shower, muon tracking, air shower primaries, QCD interactions

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Authors: Josiel Delgadillo, Johnson Kinyua, Charles Mutigwe

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The purpose of sentiment analysis is to determine the sentiment strength (e.g., positive, negative, neutral) from a textual source for good decision-making. Natural language processing in domains such as financial markets requires knowledge of domain ontology, and pre-trained language models, such as BERT, have made significant breakthroughs in various NLP tasks by training on large-scale un-labeled generic corpora such as Wikipedia. However, sentiment analysis is a strong domain-dependent task. The rapid growth of social media has given users a platform to share their experiences and views about products, services, and processes, including financial markets. StockTwits and Twitter are social networks that allow the public to express their sentiments in real time. Hence, leveraging the success of unsupervised pre-training and a large amount of financial text available on social media platforms could potentially benefit a wide range of financial applications. This work is focused on sentiment analysis using social media text on platforms such as StockTwits and Twitter. To meet this need, SkyBERT, a domain-specific language model pre-trained and fine-tuned on financial corpora, has been developed. The results show that SkyBERT outperforms current state-of-the-art models in financial sentiment analysis. Extensive experimental results demonstrate the effectiveness and robustness of SkyBERT.

Keywords: BERT, financial markets, Twitter, sentiment analysis

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Authors: Feng Yin

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Clouds are inevitable contaminants in optical satellite imagery, and prevent the satellite imaging systems from acquiring clear view of the earth surface. The presence of clouds in satellite imagery bring negative influences for remote sensing land resources investigation. As a consequence, detecting the locations of clouds in satellite imagery is an essential preprocessing step, and further remove the existing clouds is crucial for the application of imagery. In this paper, a multi-temporal based satellite imagery cloud detection and removal method is proposed, which will be used for large-scale land resource investigation. The proposed method is mainly composed of four steps. First, cloud masks are generated for cloud contaminated images by single temporal cloud detection based on multiple spectral features. Then, a cloud-free reference image of target areas is synthesized by weighted averaging time-series images in which cloud pixels are ignored. Thirdly, the refined cloud detection results are acquired by multi-temporal analysis based on the reference image. Finally, detected clouds are removed via multi-temporal linear regression. The results of a case application in Hubei province indicate that the proposed multi-temporal cloud detection and removal method is effective and promising for large-scale land resource investigation.

Keywords: cloud detection, cloud remove, multi-temporal imagery, land resources investigation

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Authors: Kavindan Balakrishnan

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Root cause Identification of the Vibration phenomenon in a feedwater pumping station was the main objective of this research. First, the mode shapes of the pumping structure were investigated using numerical and analytical methods. Then the flow pressure and streamline distribution in the pump sump were examined using C.F.D. simulation, which was hypothesized can be a cause of vibration in the pumping station. As the problem specification of this research states, the vibration phenomenon in the pumping station, with four parallel pumps operating at the same time and heavy vibration recorded even after several maintenance steps. They also specified that a relatively large amplitude of vibration exited by pumps 1 and 4 while others remain normal. As a result, the focus of this research was on determining the cause of such a mode of vibration in the pump station with the assistance of Finite Element Analysis tools and Analytical methods. Major outcomes were observed in structural behavior which is favorable to the vibration pattern phenomenon in the pumping structure as a result of this research. Behaviors of the numerical and analytical models of the pump structure have similar characteristics in their mode shapes, particularly in their 2nd mode shape, which is considerably related to the exact cause of the research problem statement. Since this study reveals several possible points of flow visualization in the pump sump model that can be a favorable cause of vibration in the system, there is more room for improved investigation on flow conditions relating to pump vibrations.

Keywords: vibration, simulation, analysis, Ansys, Matlab, mode shapes, pressure distribution, structure

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Authors: Rezeda Khairutdinova, Chulpan Gromova, Dina Birman

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The paper presents results of an exploratory study of teachers’ social attitudes toward ethnic and religious diversity, and variables influencing such attitudes. The study was conducted in Russia and is focused on school teachers, given their special role in culturally diverse modern societies. Using the social distance scale (adapted from Bogardus, 1926), we sampled 355 school teachers from two Russian regions known for their high cultural diversity: Moscow and Moscow region, Kazan and Republic of Tatarstan, and measured teacher attitudes toward large religious and ethnic groups (including migrants). The findings showed that teachers hold mostly tolerant attitudes with respect to members belonging to culturally and religiously diverse groups. The social distance between respondents and native residents of their region was minimal. Social distance was larger with respect to such ethnic groups as migrants from the Caucasian and Central Asian countries. The analysis of perception of different religious groups also showed positive attitudes toward these groups and readiness to interact with them. Teacher attitudes were not related to their age or ethnicity. The findings indicated that there was a significant correlation between social distance and the region of residence on the one hand, and between social distance and the degree of social interaction on the other. The results of this study will be used to develop a large-scale study to contribute to a better understanding of teacher attitudes toward immigrant students in public schools.

Keywords: attitudes of teachers, cultural diversity, migrants, social distance

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Authors: Kun Xu, Yuan Xu, Jia Qiao

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The document detection plays an important role in optical character recognition and text analysis. Because the traditional detection methods have weak generalization ability, and deep neural network has complex structure and large number of parameters, which cannot be well applied in mobile devices, this paper proposes a lightweight Document Corner Detection Network (DCDNet). DCDNet is a two-stage architecture. The first stage with Encoder-Decoder structure adopts depthwise separable convolution to greatly reduce the network parameters. After introducing the Feature Attention Union (FAU) module, the second stage enhances the feature information of spatial and channel dim and adaptively adjusts the size of receptive field to enhance the feature expression ability of the model. Aiming at solving the problem of the large difference in the number of pixel distribution between corner and non-corner, Weighted Binary Cross Entropy Loss (WBCE Loss) is proposed to define corner detection problem as a classification problem to make the training process more efficient. In order to make up for the lack of Dataset of document corner detection, a Dataset containing 6620 images named Document Corner Detection Dataset (DCDD) is made. Experimental results show that the proposed method can obtain fast, stable and accurate detection results on DCDD.

Keywords: document detection, corner detection, attention mechanism, lightweight

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Authors: Beverly Wang

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Background: Rosai-Dorfman disease (RDD), aka sinus histiocytosis with massive lymphadenopathy, is a rare, idiopathic histiocytic proliferative disorder. Although RDD can be seen involving the head and neck lymph nodes, rarely it can affect other extranodal sites. It present 3 unique cases of RDD affecting the nasal cavity, paranasal sinuses, and ear canal. The initial clinical presentation on two cases mimicked a malignant neoplasm. The 3rd case of RDD co-existed with a cholesteatoma of the ear canal. The clinical presentation, histology and immunohistochemical stains, and radiographic findings are discussed. Design: An overview of 3 cases of RDD affected sinonasal cavity and ear canal from UCI Medical Center was conducted. Case 1: A 61 year old male complaining of breathing difficulty presented with bilateral polypoid sinonasal masses and severe nasal obstruction. The masses elevated the nasal floor, and involved the anterior nasal septum to lateral wall. It was endoscopically excised. At intraoperative consultation, frozen section reported a pleomorphic spindle cell neoplasm with scattered large atypical spindle cells, resembling a high grade sarcoma. Case 2: A 46 year old male presented with recurrent bilateral maxillary chronic sinusitis with mass formation, clinically suspicious for malignant lymphoma. Excisional tissue sample showed large irregular spindled histiocytes with abundant granular and vacuolated cytoplasm. Case 3: A 36 year old female with a history of asthma initially presented with left-sided chronic otalgia, occasional nausea, vertigo, and fluctuating pain exacerbated by head movement and temperature changes. CT scan revealed an external auditory canal mass extending to the middle ear, coexisting with a small cholesteatoma. Results: The morphology of all cases revealed large atypical spindled histiocytes resembling fibrohistiocytic or myofibroblastic proliferative neoplasms. Scattered emperipolesis was seen. All 3 cases were confirmed as extranodal sinus RDD, confirmed by immunohistochemistry. The large atypical cells were positive for S100, CD68, and CD163. No evidence for malignancy was identified. Case 3 showed concurrent RDD co-existing with a cholesteatoma. Conclusion: Due to its rarity and variable clinical presentations, the diagnosis of RDD is seldom clinically considered. Extranodal sinus RDD morphologically can be pitfall as mimicker of spindly neoplasm, especially at intraoperative consultation. It can create diagnostic and therapeutic challenges. Correlation of radiological findings with histologic features will help to reach the diagnosis.

Keywords: head and neck, extranodal, rosai-dorfman disease, mimicker, immunohistochemistry

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Authors: Sergey Kopysov, Nikita Nedozhogin, Leonid Tonkov

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The article presents a parallel iterative solver for large sparse linear systems which can be used on a heterogeneous platform. Traditionally, the problem of solving linear systems does not scale well on multi-CPU/multi-GPUs clusters. For example, most of the attempts to implement the classical conjugate gradient method were at best counted in the same amount of time as the problem was enlarged. The paper proposes the pipelined variant of the conjugate gradient method (PCG), a formulation that is potentially better suited for hybrid CPU/GPU computing since it requires only one synchronization point per one iteration instead of two for standard CG. The standard and pipelined CG methods need the vector entries generated by the current GPU and other GPUs for matrix-vector products. So the communication between GPUs becomes a major performance bottleneck on multi GPU cluster. The article presents an approach to minimize the communications between parallel parts of algorithms. Additionally, computation and communication can be overlapped to reduce the impact of data exchange. Using the pipelined version of the CG method with one synchronization point, the possibility of asynchronous calculations and communications, load balancing between the CPU and GPU for solving the large linear systems allows for scalability. The algorithm is implemented with the combined use of technologies: MPI, OpenMP, and CUDA. We show that almost optimum speed up on 8-CPU/2GPU may be reached (relatively to a one GPU execution). The parallelized solver achieves a speedup of up to 5.49 times on 16 NVIDIA Tesla GPUs, as compared to one GPU.

Keywords: conjugate gradient, GPU, parallel programming, pipelined algorithm

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Authors: D. Kaczorek

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Internal insulation of external walls is often problematic due to increased moisture content in the wall and interstitial or surface condensation risk. In this paper, the hygrothermal performance of prefabricated, concrete, large panel, external wall typical for WK70 system, commonly used in Poland in the 70’s, with inside, additional insulation was investigated. Thermal insulation board made out of hygroscopic, natural materials with moisture buffer capacity and extruded polystyrene (EPS) board was used as interior insulation. Experience with this natural insulation is rare in Poland. The analysis was performed using WUFI software. First of all, the impact of various standard boundary conditions on the behavior of the different wall assemblies was tested. The comparison of results showed that the moisture class according to the EN ISO 13788 leads to too high values of total moisture content in the wall since the boundary condition according to the EN 15026 should be usually applied. Then, hygrothermal 1D-simulations were conducted by WUFI Pro for analysis of internally added insulation, and the weak point like the joint of the wall with the concrete ceiling was verified using 2D simulations. Results showed that, in the Warsaw climate and the indoor conditions adopted in accordance with EN 15026, in the tested wall assemblies, regardless of the type of interior insulation, there would not be any problems with moisture - inside the structure and on the interior surface.

Keywords: concrete large panel wall, hygrothermal simulation, internal insulation, moisture related issues

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Authors: David Percy

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Landslides are a geologic phenomenon that affects a large number of inhabited places and are constantly being monitored and studied for the prediction of future occurrences. Reconstructability analysis (RA) is a methodology for extracting informative models from large volumes of data that work exclusively with discrete data. While RA has been used in medical applications and social science extensively, we are introducing it to the spatial sciences through applications like landslide prediction. Since RA works exclusively with discrete data, such as soil classification or bedrock type, working with continuous data, such as porosity, requires that these data are binned for inclusion in the model. RA constructs models of the data which pick out the most informative elements, independent variables (IVs), from each layer that predict the dependent variable (DV), landslide occurrence. Each layer included in the model retains its classification data as a primary encoding of the data. Unlike other machine learning algorithms that force the data into one-hot encoding type of schemes, RA works directly with the data as it is encoded, with the exception of continuous data, which must be binned. The usual physical and derived layers are included in the model, and testing our results against other published methodologies, such as neural networks, yields accuracy that is similar but with the advantage of a completely transparent model. The results of an RA session with a data set are a report on every combination of variables and their probability of landslide events occurring. In this way, every combination of informative state combinations can be examined.

Keywords: reconstructability analysis, machine learning, landslides, raster analysis

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Authors: Seshi Reddy Kasu, Florian Misoc

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The use of hydroelectric pump-storage system at large scale, MW-size systems, is already widespread around the world. Designed for large scale applications, pump-storage station can be scaled-down for small, remote residential applications. Given the cost and complexity associated with installing a substation further than 100 miles from the main transmission lines, a remote, independent and self-sufficient system is by far the most feasible solution. This article is aiming at the design of wind and solar power generating system, by means of pumped-storage to replace the wind and/or solar power systems with a battery bank energy storage. Wind and solar pumped-storage power generating system can reduce the cost of power generation system, according to the user's electricity load and resource condition and also can ensure system reliability of power supply. Wind and solar pumped-storage power generation system is well suited for remote residential applications with intermittent wind and/or solar energy. This type of power systems, installed in these locations, could be a very good alternative, with economic benefits and positive social effects. The advantage of pumped storage power system, where wind power regulation is calculated, shows that a significant smoothing of the produced power is obtained, resulting in a power-on-demand system’s capability, concomitant to extra economic benefits.

Keywords: battery bank, photo-voltaic, pump-storage, wind energy

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Authors: R. P. Hewawasam, M. H. A. D. de Silva, M. A. G. Iresha

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In recent years childhood obesity has increased to pan-epidemic proportions along with a concomitant increase in obesity-associated morbidity. Birth weight is an important determinant of later adult health, with neonates at both ends of the birth weight spectrum at risk of future health complications. Consequently, infants who are born large for gestational age (LGA) are more likely to be obese in childhood and adolescence and are at risk of cardiovascular and metabolic complications later in life. Adipose tissue plays a role in linking events in fetal growth to the subsequent development of adult diseases. In addition to its role as a storage depot for fat, adipose tissue produces and secrets a number of hormones of importance in modulating metabolism and energy homeostasis. Cord blood leptin level has been positively correlated with fetal adiposity at birth. It is established that Asians have lower skeletal muscle mass, low bone mineral content and excess body fat for a given body mass index indicating a genetic predisposition in the occurrence of obesity. To our knowledge, studies have never been conducted in Sri Lanka to determine the relationship between adipocytokine profile in cord blood and anthropometric parameters in newborns. Thus, the objective of this study is to establish the above relationship for the Sri Lankan population to implement awareness programs to minimize childhood obesity in the future. Umbilical cord blood was collected from 90 newborns (Male 40, Female 50; gestational age 35-42 weeks) after double clamping the umbilical cord before separation of the placenta and the concentration of leptin was measured by ELISA technique. Anthropometric parameters of the newborn such as birth weight, length, ponderal index, occipital frontal, chest, hip and calf circumferences were measured. Pearson’s correlation was used to assess the relationship between leptin and anthropometric parameters while the Mann-Whitney U test was used to assess the differences in cord blood leptin levels between small for gestational age (SGA), appropriate for gestational age (AGA) and LGA infants. There was a significant difference (P < 0.05) between the cord blood leptin concentrations of LGA infants (12.67 ng/mL ± 2.34) and AGA infants (7.10 ng/mL ± 0.90). However, a significant difference was not observed between leptin levels of SGA infants (8.86 ng/mL ± 0.70) and AGA infants. In both male and female neonates, umbilical leptin levels showed significant positive correlations (P < 0.05) with birth weight of the newborn, pre-pregnancy maternal weight and pre pregnancy BMI between the infants of large and appropriate for gestational ages. Increased concentrations of leptin levels in the cord blood of large for gestational age infants suggest that they may be involved in regulating fetal growth. Leptin concentration of Sri Lankan population was not significantly deviated from published data of Asian populations. Fetal leptin may be an important predictor of neonatal adiposity; however, interventional studies are required to assess its impact on the possible risk of childhood obesity.

Keywords: appropriate for gestational age, childhood obesity, leptin, anthropometry

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Authors: Lingling Shui, Shuting Xie

Abstract:

As alternatives to electronic devices, optically active structures from responsive nanomaterials offer great opportunity buildup smart functional sensors. Hereby, we report on droplet microfluidics enabled construction and application of photonic microcapsules (PMCs) for colorimetric temperature microsensors, enabling miniaturization for injectable local micro-area sensing and integration for large-area sensing. Monodispersed PMCs are produced by in-situ photopolymerization of hydrogel shells of cholesteric liquid crystal (CLC)-in-water-in-oil double emulsion droplets prepared using microfluidic devices, with controllable physical structures and chemical compositions. Constructed PMCs exhibit thermal responsive structural color according to the selective Bragg reflection of CLC’s periodical helical structures within the microdroplet’s spherical confinement. Constructed PMCs with tunable size and composition have been successfully applied for monitoring the living cell extracellular temperature via co-incubation with cell suspension, and for detecting human body temperature via a flexible device from assembled PMCs. These PMCs could be flexibly applied in either micro-environment or large-area surface, enabling wide applications for precision temperature monitoring biological activities (e.g. cells or organs), optoelectronic devices working conditions (e.g. temperature indicators under extreme conditions), and etc.

Keywords: droplet, microfluidics, assembly, soft materials, microsensor

Procedia PDF Downloads 70