Search results for: thin layer chromatography

Authors: Jui-Chien Hsieh

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Background:12-lead electrocardiography(ECG) is one of frequently-used tools to detect atrial fibrillation (AF), which might degenerate into life-threaten stroke, in clinical Practice. Based on this study, the AF detection by the clinically-used 12-lead ECG device has only 0.73~0.77 positive predictive value (ppv). Objective: It is on great demand to develop a new algorithm to improve the precision of AF detection using 12-lead ECG. Due to the progress on artificial intelligence (AI), we develop an ECG deep model that has the ability to recognize AF patterns and reduce false-positive errors. Methods: In this study, (1) 570-sample 12-lead ECG reports whose computer interpretation by the ECG device was AF were collected as the training dataset. The ECG reports were interpreted by 2 senior cardiologists, and confirmed that the precision of AF detection by the ECG device is 0.73.; (2) 88 12-lead ECG reports whose computer interpretation generated by the ECG device was AF were used as test dataset. Cardiologist confirmed that 68 cases of 88 reports were AF, and others were not AF. The precision of AF detection by ECG device is about 0.77; (3) A parallel 4-layer 1 dimensional convolutional neural network (CNN) was developed to identify AF based on limb-lead ECGs and chest-lead ECGs. Results: The results indicated that this model has better performance on AF detection than traditional computer interpretation of the ECG device in 88 test samples with 0.94 ppv, 0.98 sensitivity, 0.80 specificity. Conclusions: As compared to the clinical ECG device, this AI ECG model promotes the precision of AF detection from 0.77 to 0.94, and can generate impacts on clinical applications.

Keywords: 12-lead ECG, atrial fibrillation, deep learning, convolutional neural network

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Authors: H. C. Woo, F. Bouanis, C. S. Cojocaur

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Graphene, which consists of a single layer of carbon atoms in a honeycomb lattice, is an interesting potential optoelectronic material because of graphene’s high carrier mobility, zero bandgap, and electron–hole symmetry. Graphene can absorb light and convert it into a photocurrent over a wide range of the electromagnetic spectrum, from the ultraviolet to visible and infrared regimes. Over the last several years, a variety of graphene-based photodetectors have been reported, such as graphene transistors, graphene-semiconductor heterojunction photodetectors, graphene based bolometers. It is also reported that there are several physical mechanisms enabling photodetection: photovoltaic effect, photo-thermoelectric effect, bolometric effect, photogating effect, and so on. In this work, we report a simple approach for the realization of graphene based resistive photo-detection devices and the measurements of their photoelectrical response. The graphene were synthesized directly on the glass substrate by novel growth method patented in our lab. Then, the metal electrodes were deposited by thermal evaporation on it, with an electrode length and width of 1.5 mm and 300 μm respectively, using Co to fabricate simple graphene based resistive photosensor. The measurements show that the graphene resistive devices exhibit a photoresponse to the illumination of visible light. The observed re-sistance response was reproducible and similar after many cycles of on and off operations. This photoelectrical response may be attributed not only to the direct photocurrent process but also to the desorption of oxygen. Our work shows that the simple graphene resistive devices have potential in photodetection applications.

Keywords: graphene, resistive sensor, optoelectronics, photoresponse

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Authors: Yasin Ghasemi-Zadeh, Yousef Kavian

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Wireless body area networks (WBANs) technology has achieved lots of popularity over the last decade with a wide range of medical applications. This paper presents an asynchronous media access control (MAC) protocol based on B-MAC protocol by giving an application for medical issues. In WBAN applications, there are some serious problems such as energy, latency, link reliability (quality of wireless link) and throughput which are mainly due to size of sensor networks and human body specifications. To overcome these problems and improving link reliability, we concentrated on MAC layer that supports mobility models for medical applications. In the presented protocol, preamble frames are divided into some sub-frames considering the threshold level. Actually, the main reason for creating shorter preambles is the link reliability where due to some reasons such as water, the body signals are affected on some frequency bands and causes fading and shadowing on signals, therefore by increasing the link reliability, these effects are reduced. In case of mobility model, we use MoBAN model and modify that for some more areas. The presented asynchronous MAC protocol is modeled by OMNeT++ simulator. The results demonstrate increasing the link reliability comparing to B-MAC protocol where the packet reception ratio (PRR) is 92% also covers more mobility areas than MoBAN protocol.

Keywords: wireless body area networks (WBANs), MAC protocol, link reliability, mobility, biomedical

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Authors: Ngoc Trung Ngo, Buddhima Indraratna, Cholachat Rujikiathmakjornr

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For several hundred years, the design of railway tracks has practically remained unchanged. Traditionally, rail tracks are placed on a ballast layer due to several reasons, including economy, rapid drainage, and high load bearing capacity. The primary function of ballast is to distributing dynamic track loads to sub-ballast and subgrade layers, while also providing lateral resistance and allowing for rapid drainage. Upon repeated trainloads, the ballast becomes fouled due to ballast degradation and the intrusion of fines which adversely affects the strength and deformation behaviour of ballast. This paper presents the use of three-dimensional discrete element method (DEM) in studying the shear behaviour of the fouled ballast subjected to direct shear loading. Irregularly shaped particles of ballast were modelled by grouping many spherical balls together in appropriate sizes to simulate representative ballast aggregates. Fouled ballast was modelled by injecting a specified number of miniature spherical particles into the void spaces. The DEM simulation highlights that the peak shear stress of the ballast assembly decreases and the dilation of fouled ballast increases with an increase level of fouling. Additionally, the distributions of contact force chain and particle displacement vectors were captured during shearing progress, explaining the formation of shear band and the evolutions of volumetric change of fouled ballast.

Keywords: railway ballast, coal fouling, discrete element modelling, discrete element method

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Authors: M. Zareh, H. Mohammadi, B. Naser

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Atherosclerotic plaque rupture is the main trigger of heart attack and brain stroke which are the leading cause of death in developed countries. Better understanding of rupture-prone plaque can help clinicians detect vulnerable plaques- rupture prone or instable plaques- and apply immediate medical treatment to prevent these life-threatening cardiovascular events. Therefore, there are plenty of studies addressing disclosure of vulnerable plaques properties. Necrotic core and fibrous tissue are two major tissues constituting atherosclerotic plaque; using histopathological and numerical approaches, many studies have demonstrated that plaque rupture is strongly associated with a large necrotic core and a thin fibrous cap, two morphological characteristic which can be acquired by two-dimensional imaging of atherosclerotic plaque present in coronary and carotid arteries. Plaque rupture is widely considered as a mechanical failure inside plaque tissue; this failure occurs when the stress within plaque excesses the strength of tissue material; hence, finite element method, a strong numerical approach, has been extensively applied to estimate stress distribution within plaques with different compositions which is then used for assessment of various vulnerability characteristics including plaque morphology, material properties and blood pressure. This study aims to evaluate significance of three-dimensional morphology on vulnerability degree of atherosclerotic plaque. To reach this end, different two-dimensional geometrical models of atherosclerotic plaques are considered based on available data and named Main 2D Models (M2M). Then, for each of these M2Ms, two three-dimensional idealistic models are created. These two 3D models represent two possible three-dimensional morphologies which might exist for a plaque with similar 2D morphology to one of M2Ms. Finite element method is employed to estimate stress, von-Mises stress, within each 3D models. Results indicate that for each M2Ms stress can significantly varies due to possible 3D morphological changes in that plaque. Also, our results show that an atherosclerotic plaque with thick cap may experience rupture if it has a critical 3D morphology. This study highlights the effect of 3D geometry of plaque on its instability degree and suggests that 3D morphology of plaque might be necessary to more effectively and accurately assess atherosclerotic plaque vulnerability.

Keywords: atherosclerotic plaque, plaque rupture, finite element method, 3D model

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Authors: Evln Ranga Charyulu, S. P. Venu Madhavarao, S. Udaya kumar, S. V. S. S. N. V. G. Krishna Murthy

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With the advent of new nanometer process technologies, it is possible to integrate billion transistors on a single substrate. When more and more functionality included there is the possibility of multi-million transistors switching simultaneously consuming more power and dissipating more power along with more leakage of current into the substrate of porous silicon or germanium material. These results in substrate heating and thermal noise generation coupled to signals of interest. The heating process is represented by coupled nonlinear partial differential equations in porous silicon and germanium. By identifying heat sources and heat fluxes may results in designing of ultra-low power circuits. The PDEs are solved by finite difference scheme assuming that boundary layer equations in porous silicon and germanium. Local heat fluxes along the vertical isothermal surface immersed in porous SI/Ge are considered. The parameters considered for optimization are thermal diffusivity, thermal expansion coefficient, thermal diffusion ratio, permeability, specific heat at constant temperatures, Rayleigh number, amplitude of wavy surface, mass expansion coefficient. The diffusion of heat was caused by the concentration gradient. Thermal physical properties are homogeneous and isotropic. By using L8, TAGUCHI method the parameters are optimized.

Keywords: heat transfer, pde, taguchi optimization, SI/Ge

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Authors: Sheila Shahidi

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UV protection by fabrics has recently become a focus of great interest, particularly in connection with environmental degradation or ozone layer depletion. Fabrics provide simple and convenient protection against UV radiation (UVR), but not all fabrics offer sufficient UV protection. To describe the degree of UVR protection offered by clothing materials, the ultraviolet protection factor (UPF) is commonly used. UV-protective fabric can be generated by application of a chemical finish using normal wet-processing methodologies. However, traditional wet-processing techniques are known to consume large quantities of water and energy and may lead to adverse alterations of the bulk properties of the substrate. Recently, usage of plasmas to generate physicochemical surface modifications of textile substrates has become an intriguing approach to replace or enhance conventional wet-processing techniques. In this research work the effect of plasma treatment on UV protection properties of fabrics was investigated. DC magnetron sputtering was used and the parameters of plasma such as gas type, electrodes, time of exposure, power and, etc. were studied. The morphological and chemical properties of samples were analyzed using Scanning Electron Microscope (SEM) and Furrier Transform Infrared Spectroscopy (FTIR), respectively. The transmittance and UPF values of the original and plasma-treated samples were measured using a Shimadzu UV3101 PC (UV–Vis–NIR scanning spectrophotometer, 190–2, 100 nm range). It was concluded that, plasma which is an echo-friendly, cost effective and dry technique is being used in different branches of the industries, and will conquer textile industry in the near future. Also it is promising method for preparation of UV protection textile.

Keywords: fabric, plasma, textile, UV protection

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Authors: Marie Davin, Marie-Laure Fauconnier, Gilles Colinet

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In Wallonia, there are 6,000 estimated brownfields (rising to over 3.5 million in Europe) that require remediation. Polycyclic Aromatic Hydrocarbons (PAHs) are a class of recalcitrant carcinogenic/mutagenic organic compounds of major concern as they accumulate in the environment and represent 17% of all encountered pollutants. As an alternative to environmentally aggressive, expensive and often disruptive soil remediation strategies, a lot of research has been directed to developing techniques targeting organic pollutants. The following experiment, based on the observation that PAHs soil content decreases in the presence of plants, aimed at improving our understanding of the underlying mechanisms involved in phytoremediation. It focusses on plant root exudates and whether they improve PAHs solubilization, which would make them more available for bioremediation by soil microorganisms. The effect of saponin, a natural surfactant found in some plant roots such as members of the Fabaceae family, on PAHs solubilization was also investigated as part of the implementation of the experimental protocol. The experiments were conducted on soil collected from a brownfield in Saint-Ghislain (Belgium) and presenting weathered PAHs contamination. Samples of soil were extracted with different solutions containing either plant root exudates or commercial saponin. Extracted PAHs were determined in the different aqueous solutions using High-Performance Liquid Chromatography and Fluorimetric Detection (HPLC-FLD). Both root exudates of alfalfa (Medicago sativa L.) or red clover (Trifolium pratense L.) and commercial saponin were tested in different concentrations. Distilled water was used as a control. First of all, results show that PAHs are more extracted using saponin solutions than distilled water and that the amounts generally rise with the saponin concentration. However, the amount of each extracted compound diminishes as its molecular weight rises. Also, it appears that passed a certain surfactant concentration, PAHs are less extracted. This suggests that saponin might be investigated as a washing agent in polluted soil remediation techniques, either for ex-situ or in-situ treatments, as an alternative to synthetic surfactants. On the other hand, preliminary results on experiments using plant root exudates also show differences in PAHs solubilization compared to the control solution. Further results will allow discussion as to whether or not there are differences according to the exudates provenance and concentrations.

Keywords: brownfield, Medicago sativa, phytoremediation, polycyclic aromatic hydrocarbons, root exudates, saponin, solubilization, Trifolium pratense

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Authors: Jiajia Yao, Guanlin Wu, Fang Liu, Junshuai Xue, Yue Hao

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This study reports on the epitaxial growth of a GaN-based resonant tunneling diode (RTD) structure with stable and repeatable double negative differential resistance (NDR) characteristics at room temperature on a c-plane GaN-on-sapphire template using plasma-assisted molecular beam epitaxy (PA-MBE) technology. In this structure, two independent AlN/GaN RTDs are epitaxially connected in series in the vertical growth direction through a silicon-doped GaN layer. As the collector electrode bias voltage increases, the two RTDs respectively align the ground state energy level in the quantum well with the 2DEG energy level in the emitter accumulation well to achieve quantum resonant tunneling and then reach the negative differential resistance (NDR) region. The two NDR regions exhibit similar peak current densities and peak-to-valley current ratios, which are 230 kA/cm² and 249 kA/cm², 1.33 and 1.38, respectively, for a device with a collector electrode mesa diameter of 1 µm. The consistency of the NDR is much higher than the results of on-chip discrete RTD device interconnection, resulting from the smaller chip area, fewer interconnect parasitic parameters, and less process complexity. The methods and results presented in this paper show the brilliant prospects of GaN RTDs in the development of multi-value logic digital circuits.

Keywords: MBE, AlN/GaN, RTDs, double NDR

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Authors: A. Kampker, K. Kreisköther, C. Reinders

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Since additive manufacturing technologies constantly advance, the use of this technology in mold making seems reasonable. Many manufacturers of additive manufacturing machines, however, do not offer any suggestions on how to parameterize the machine to achieve optimal results for mold making. The purpose of this research is to determine the interdependencies of different materials and parameters within the PolyJet process by using design of experiments (DoE), to additively manufacture molds, e.g. for thermoforming and injection molding applications. Therefore, the general requirements of thermoforming molds, such as heat resistance, surface quality and hardness, have been identified. Then, different materials and parameters of the PolyJet process, such as the orientation of the printed part, the layer thickness, the printing mode (matte or glossy), the distance between printed parts and the scaling of parts, have been examined. The multifactorial analysis covers the following properties of the printed samples: Tensile strength, tensile modulus, bending strength, elongation at break, surface quality, heat deflection temperature and surface hardness. The key objective of this research is that by joining the results from the DoE with the requirements of the mold making, optimal and tailored molds can be additively manufactured with the PolyJet process. These additively manufactured molds can then be used in prototyping processes, in process testing and in small to medium batch production.

Keywords: additive manufacturing, design of experiments, mold making, PolyJet, 3D-Printing

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Authors: Sajid Shah, Yoshimitsu Uemura, Katsuki Kusakabe

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Sol-gel derived hydrophobic silica membranes with pore sizes less than 1 nm are quite attractive for gas separation in a wide range of temperatures. A nano-structured hydrophobic membrane was prepared by sol-gel technique on a porous α–Al₂O₃ tubular support with yttria stabilized zirconia (YSZ) as an intermediate layer. Bistriethoxysilylethane (BTESE) derived sol was modified by adding phenyltriethoxysilylethane (PhTES) as an organic template. Six times dip coated modified silica membrane having a thickness of about 782 nm was characterized by field emission scanning electron microscopy. Thermogravimetric analysis, together along contact angle and Fourier transform infrared spectroscopy, showed that hydrophobic properties were improved by increasing the PhTES content. The contact angle of water droplet increased from 37° for pure to 111.5° for the modified membrane. The permeance of single gas H₂ was higher than H₂:CO₂ ratio of 75:25 binary feed mixtures. However, the permeance of H₂ for 60:40 H₂:CO₂ was found lower than single and binary mixture 75:25 H₂:CO₂. The binary selectivity values for 75:25 H₂:CO₂ were 24.75, 44, and 57, respectively. Selectivity had an inverse relation with PhTES content. Hydrophobicity properties were improved by increasing PhTES content in the silica matrix. The system exhibits proper three layers adhesion or integration, and smoothness. Membrane system suitable in steam environment and high-temperature separation. It was concluded that the hydrophobic silica membrane is highly promising for the separation of H₂/CO₂ mixture from various H₂-containing process streams.

Keywords: gas separation, hydrophobic properties, silica membrane, sol–gel method

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Authors: Stewart A. Keir, Faik A. Hamad

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This study aims to use both analytical and experimental methods of analysis to examine the accuracy of Computational Fluid Dynamics (CFD) models that can then be used for more complex analyses, accurately representing more elaborate flow phenomena such as internal shockwaves and boundary layers. The geometry used in the analytical study and CFD model is taken from the experimental rig. The analytical study is undertaken using isentropic and adiabatic relationships and the output of the analytical study, the 'shockwave location tool', is created. The results from the analytical study are then used to optimize the redesign an experimental rig for more favorable placement of pressure taps and gain a much better representation of the shockwaves occurring in the divergent section of the nozzle. The CFD model is then optimized through the selection of different parameters, e.g. turbulence models (Spalart-Almaras, Realizable k-epsilon & Standard k-omega) in order to develop an accurate, robust model. The results from the CFD model can then be directly compared to experimental and analytical results in order to gauge the accuracy of each method of analysis. The CFD model will be used to visualize the variation of various parameters such as velocity/Mach number, pressure and turbulence across the shock. The CFD results will be used to investigate the interaction between the shock wave and the boundary layer. The validated model can then be used to modify the nozzle designs which may offer better performance and ease of manufacture and may present feasible improvements to existing high-speed flow applications.

Keywords: CFD, nozzle, fluent, gas dynamics, shock-wave

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Authors: Peikun Zhang, Chunhua Cui

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Photoelectrochemical (PEC) water splitting provides a promising pathway to convert solar energy into renewable fuels. However, the main and seemingly insurmountable obstacle is that the sluggish kinetics of oxygen evolution reaction (OER) severely jeopardizes the overall efficiency, thus exploring highly active, stable, and appreciable catalysts is urgently requested. Herein a competitive coordination strategy was demonstrated to form a reversible hybrid homo-heterogeneous catalyst for efficient OER in alkaline media. The dynamic process involves an in-situ anchoring of soluble nickel–bipyridine pre-catalyst to a conductive substrate under OER and a re-dissolution course under open circuit potential, induced by the competitive coordination between nickel–bipyridine and nickel-hydroxyls. This catalyst allows to elaborately self-modulate a charge-transfer layer thickness upon the catalytic on-off operation, which affords substantially increased active sites, yet remains light transparency, and sustains the stability of over 200 hours of continuous operation. The integration of this catalyst with exemplified state-of-the-art Ni-sputtered Si photoanode can facilitate a ~250 mV cathodic shift at a current density of 20 mA cm-2. This finding helps the understanding of catalyst from a “dynamic” perspective, which represents a viable alternative to address remaining hurdles toward solar-driven water oxidation.

Keywords: molecular catalyst, oxygen evolution reaction, solar energy, transition metal complex, water splitting

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Authors: Hebberly Ahatlan

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The process of digitizing energy systems involves transforming traditional energy infrastructure into interconnected, data-driven systems that enhance efficiency, sustainability, and responsiveness. As smart grids become increasingly integral to the efficient distribution and management of electricity from both fossil and renewable energy sources, the energy industry faces strategic challenges associated with digitalization and interoperability — particularly in the context of modern energy business models, such as virtual power plants (VPPs). The critical challenge in modern smart grids is to seamlessly integrate diverse technologies and systems, including virtualization, grid computing and service-oriented architecture (SOA), across the entire energy ecosystem. Achieving this requires addressing issues like semantic interoperability, IT/OT convergence, and digital asset scalability, all while ensuring security and risk management. This paper proposes a four-layer digitalization framework to tackle these challenges, encompassing persistent data protection, trusted key management, secure messaging, and authentication of IoT resources. Data assets generated through this framework enable AI systems to derive insights for improving smart grid operations, security, and revenue generation. Furthermore, this paper also proposes a Trusted Energy Interoperability Alliance as a universal guiding standard in the development of this digitalization framework to support more dynamic and interoperable energy markets.

Keywords: digitalization, IT/OT convergence, semantic interoperability, VPP, energy blockchain

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Authors: Akhila Sara Varughese

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In the postmodern society, visual narratives became an emerging genre in the field of literature. Graphic literature focuses on the literal and symbolic layer of interpretation. The most salient feature of graphic literature is its exploration of the public history of events and life narratives. The Indian graphic literature re-interprets the canon, style and the form of texts in Indian Writing in English and it demands a new literacy and the structure of the English literature. With the help of visual-verbal language, the graphic narratives discuss various facets of contemporary India. Graphic novels have firmly identified itself with the art of storytelling because of its capability of expressing human experiences to the most. In the textual novels, the author usually deserts the imagination of the readers, but in the case of graphic narratives, due to the presence of visual elements, the interpretation becomes simpler. India is the second most populous country in the world with a long tradition of history and culture. Indian literature always tries to reconstruct Indian history in various modes of representation. The present paper focuses on the fictional articulation of Indian history through the graphic narratives and analyses how some historical events in India portrays. The paper also traces the differences in rendering the history in graphic novels with that of textual novels. The paper discusses how much the blending of words and images helps in represent the Indian history by analyzing the graphic novels like Kashmir Pending by Naseer Ahmed, Delhi Calm by Vishwajyoti Ghosh and Munnu by Malik Sajad.

Keywords: graphic novels, Indian history, representation, visual-verbal literacy

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Authors: Yi-Ting Chen, Yu-Fang Huang, Pei-Wei Wang, Hai-Wei Liang, Chun-Hao Lai, Mei-Lien Chen

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Background: Bisphenol A (BPA) is commonly used in consumer products, such as inner coatings of cans and polycarbonated bottles. BPA is considered to be an endocrine disrupting substance (EDs) that affects normal human hormones and may cause adverse effects on human health. Pregnant women and fetuses are susceptible groups of endocrine disrupting substances. Prenatal exposure to BPA has been shown to affect the fetus through the placenta. Therefore, it is important to evaluate the potential health risk of fetal exposure to BPA during pregnancy. The aims of this study were (1) to determine the urinary concentration of BPA in pregnant women, and (2) to investigate the association between BPA exposure during pregnancy and birth outcomes. Methods: This study recruited 117 pregnant women and their fetuses from 2012 to 2014 from the Taiwan Maternal- Infant Cohort Study (TMICS). Maternal urine samples were collected in the third trimester and questionnaires were used to collect socio-demographic characteristics, eating habits and medical conditions of the participants. Information about birth outcomes of the fetus was obtained from medical records. As for chemicals analysis, BPA concentrations in urine were determined by off-line solid-phase extraction-ultra-performance liquid chromatography coupled with a Q-Tof mass spectrometer. The urinary concentrations were adjusted with creatinine. The association between maternal concentrations of BPA and birth outcomes was estimated using the logistic regression model. Results: The detection rate of BPA is 99%; the concentration ranges (μg/g) from 0.16 to 46.90. The mean (SD) BPA levels are 5.37(6.42) μg/g creatinine. The mean ±SD of the body weight, body length, head circumference, chest circumference and gestational age at birth are 3105.18 ± 339.53 g, 49.33 ± 1.90 cm, 34.16 ± 1.06 cm, 32.34 ± 1.37 cm and 38.58 ± 1.37 weeks, respectively. After stratifying the exposure levels into two groups by median, pregnant women in higher exposure group would have an increased risk of lower body weight (OR=0.57, 95%CI=0.271-1.193), smaller chest circumference (OR=0.70, 95%CI=0.335-1.47) and shorter gestational age at birth newborn (OR=0.46, 95%CI=0.191-1.114). However, there are no associations between BPA concentration and birth outcomes reach a significant level (p < 0.05) in statistics. Conclusions: This study presents prenatal BPA profiles and infants in northern Taiwan. Women who have higher BPA concentrations tend to give birth to lower body weight, smaller chest circumference or shorter gestational age at birth newborn. More data will be included to verify the results. This report will also present the predictors of BPA concentrations for pregnant women.

Keywords: bisphenol A, birth outcomes, biomonitoring, prenatal exposure

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Authors: Harsh Agarwal, Pratikkumar Patel, Maharshi Pathak

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Recently the low prices of Crude oil and increase in strict environmental regulations limit limits the use of diesel based muds as these muds are relatively costlier and toxic, as a result disposal of cuttings into the eco-system is a major issue faced by the drilling industries. To overcome these issues faced by the Oil Industry, an attempt has been made to develop oil-in-water emulsion mud system using nettlespurge oil. Nettlespurge oil could be easily available and its cost is around ₹30/litre which is about half the price of diesel in India. Oil-based mud (OBM) was formulated with Nettlespurge oil extracted from Nettlespurge seeds using the Soxhlet extraction method. The formulated nettlespurge oil mud properties were analysed with diesel oil mud properties. The compared properties were rheological properties, yield point and gel strength, and mud density and filtration loss properties, fluid loss and filter cake. The mud density measurement showed that nettlespurge OBM was slightly higher than diesel OBM with mud density values of 9.175 lb/gal and 8.5 lb/gal, respectively, at barite content of 70 g. Thus it has a higher lubricating property. Additionally, the filtration loss test results showed that nettlespurge mud fluid loss volumes, oil was 11 ml, compared to diesel oil mud volume of 15 ml. The filtration loss test indicated that the nettlespurge oil mud with filter cake thickness of 2.2 mm had a cake characteristic of thin and squashy while the diesel oil mud resulted in filter cake thickness of 2.7 mm with cake characteristic of tenacious, rubbery and resilient. The filtration loss test results showed that nettlespurge oil mud fluid loss volumes was much less than the diesel based oil mud. The filtration loss test indicated that the nettlespurge oil mud filter cake thickness less than the diesel oil mud filter cake thickness. So Low formation damage and the emulsion stability effect was analysed with this experiment. The nettlespurge oil-in-water mud system had lower coefficient of friction than the diesel oil based mud system. All the rheological properties have shown better results relative to the diesel based oil mud. Therefore, with all the above mentioned factors and with the data of the conducted experiment we could conclude that the Nettlespurge oil based mud is economically and well as eco-logically much more feasible than the worn out and shabby diesel-based oil mud in the Drilling Industry.

Keywords: economical feasible, ecological feasible, emulsion stability, nettle spurge oil, rheological properties, soxhlet extraction method

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Authors: Nadia Allouache

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Energy conservation is one of the major concerns in the modern high tech era due to the limited amount of energy resources and the increasing cost of energy. Predicting an efficient use of energy in thermal systems like heat exchangers can only be achieved if the second law of thermodynamics is accounted for. The performance of heat exchangers can be substantially improved by many passive heat transfer augmentation techniques. These letters permit to improve heat transfer rate and to increase exchange surface, but on the other side, they also increase the friction factor associated with the flow. This raises the question of how to employ these passive techniques in order to minimize the useful energy. The objective of this present study is to use a porous substrate attached to the walls as a passive enhancement technique in heat exchangers and to find the compromise between the hydrodynamic and thermal performances under turbulent flow conditions, by using a second law approach. A modified k- ε model is used to simulating the turbulent flow in the porous medium and the turbulent shear flow is accounted for in the entropy generation equation. A numerical modeling, based on the finite volume method is employed for discretizing the governing equations. Effects of several parameters are investigated such as the porous substrate properties and the flow conditions. Results show that under certain conditions of the porous layer thickness, its permeability, and its effective thermal conductivity the minimum rate of entropy production is obtained.

Keywords: second law approach, annular heat exchanger, turbulent flow, porous medium, modified model, numerical analysis

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Authors: Krishang Surapaneni

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The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

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Authors: Njabulo Ncube, Elena Kulinskaya, Nicholas Steel, Dmitry Pshezhetskiy

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Life expectancy in the United Kingdom (UK) has been near constant since 2010, particularly for the individuals of 65 years and older. This trend has been also noted in several other countries. This slowdown in the increase of life expectancy was concurrent with the increase in the number of deaths caused by non-communicable diseases. Of particular concern is the world-wide exponential increase in the number of diabetes related deaths. Previous studies have reported increased mortality hazards among diabetics compared to non-diabetics, and on the differing effects of antidiabetic drugs on mortality hazards. This study aimed to estimate the all-cause mortality hazards and related life expectancies among type 2 diabetes (T2DM) patients in the UK using the time-variant Gompertz-Cox model with frailty. The study also aimed to understand the major causes of the change in life expectancy growth in the last decade. A total of 221 182 (30.8% T2DM, 57.6% Males) individuals aged 50 years and above, born between 1930 and 1960, inclusive, and diagnosed between 2000 and 2016, were selected from The Health Improvement Network (THIN) database of the UK primary care data and followed up to 31 December 2016. About 13.4% of participants died during the follow-up period. The overall all-cause mortality hazard ratio of T2DM compared to non-diabetic controls was 1.467 (1.381-1.558) and 1.38 (1.307-1.457) when diagnosed between 50 to 59 years and 60 to 74 years, respectively. The estimated life expectancies among T2DM individuals without further comorbidities diagnosed at the age of 60 years were 2.43 (1930-1939 birth cohort), 2.53 (1940-1949 birth cohort) and 3.28 (1950-1960 birth cohort) years less than those of non-diabetic controls. However, the 1950-1960 birth cohort had a steeper hazard function compared to the 1940-1949 birth cohort for both T2DM and non-diabetic individuals. In conclusion, mortality hazards for people with T2DM continue to be higher than for non-diabetics. The steeper mortality hazard slope for the 1950-1960 birth cohort might indicate the sub-population contributing to a slowdown in the growth of the life expectancy.

Keywords: T2DM, Gompetz-Cox model with frailty, all-cause mortality, life expectancy

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Authors: Alper Taner, Yesim Benal Oztekin, Huseyin Duran

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In this study, an Artificial Neural Network (ANN) was developed in order to classify barley varieties. For this purpose, physical properties of barley varieties were determined and ANN techniques were used. The physical properties of 8 barley varieties grown in Turkey, namely thousand kernel weight, geometric mean diameter, sphericity, kernel volume, surface area, bulk density, true density, porosity and colour parameters of grain, were determined and it was found that these properties were statistically significant with respect to varieties. As ANN model, three models, N-l, N-2 and N-3 were constructed. The performances of these models were compared. It was determined that the best-fit model was N-1. In the N-1 model, the structure of the model was designed to be 11 input layers, 2 hidden layers and 1 output layer. Thousand kernel weight, geometric mean diameter, sphericity, kernel volume, surface area, bulk density, true density, porosity and colour parameters of grain were used as input parameter; and varieties as output parameter. R2, Root Mean Square Error and Mean Error for the N-l model were found as 99.99%, 0.00074 and 0.009%, respectively. All results obtained by the N-l model were observed to have been quite consistent with real data. By this model, it would be possible to construct automation systems for classification and cleaning in flourmills.

Keywords: physical properties, artificial neural networks, barley, classification

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Authors: Morteza Ghorbani, Reza Ghorbani

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Cavitation phenomenon has attracted much attention in the mechanical and biomedical technologies. Despite the simplicity and mostly low cost of the devices generating cavitation bubbles, the physics behind the generation and collapse of these bubbles particularly in micro/nano scale has still not well understood. In the chemical industry, micro/nano bubble generation is expected to be applicable to the development of porous materials such as microcellular plastic foams. Moreover, it was demonstrated that the presence of micro/nano bubbles on a surface reduced the adsorption of proteins. Thus, the micro/nano bubbles could act as antifouling agents. Micro and nano bubbles were also employed in water purification, froth floatation, even in sonofusion, which was not completely validated. Small bubbles could also be generated using micro scale hydrodynamic cavitation. In this study, compared to the studies available in the literature, we are proposing a novel approach in micro scale utilizing the energy produced during the interaction of the spray affected by the hydrodynamic cavitating flow and a thin aluminum plate. With a decrease in the size, cavitation effects become significant. It is clearly shown that with the aid of hydrodynamic cavitation generated inside the micro/mini-channels in addition to the optimization of the distance between the tip of the microchannel configuration and the solid surface, surface temperatures can be increased up to 50C under the conditions of this study. The temperature rise on the surfaces near the collapsing small bubbles was exploited for energy harvesting in small scale, in such a way that miniature, cost-effective, and environmentally friendly energy-harvesting devices can be developed. Such devices will not require any external power and moving parts in contrast to common energy-harvesting devices, such as those involving piezoelectric materials and micro engine. Energy harvesting from thermal energy has been widely exploited to achieve energy savings and clean technologies. We are proposing a cost effective and environmentally friendly solution for the growing individual energy needs thanks to the energy application of cavitating flows. The necessary power for consumer devices, such as cell phones and laptops, can be provided using this approach. Thus, this approach has the potential for solving personal energy needs in an inexpensive and environmentally friendly manner and can trigger a shift of paradigm in energy harvesting.

Keywords: cavitation, energy, harvesting, micro scale

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Authors: Shackira Am, Jos T. Puthur

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The phytostabilization potential of a halophyte Acanthus ilicifolius L. has been evaluated with special attention to the nutritional as well as anatomical adaptations developed by the plant. Distribution of essential elements influenced by the excess Zn²⁺ ions in the root tissue was studied by FEG-SEM EDX microanalysis. Significant variations were observed in the uptake and allocation of mineral elements like Mg, P, K, S, Na, Si and Al in the root of A. ilicifolius. The increase in S is in correlation with the increased synthesis of glutathione which might be involved in the biosynthesis of phytochelatins. This in turn might be aiding the plant to tolerate the adverse environmental conditions by stabilizing the excess Zn in the root tissue itself. Moreover it is revealed that most of the Zn were accumulated towards the central region near the vascular tissue. Treatment with ZnSO₄ in A. ilicifolius caused significant increase in the number of glandular trichomes on the adaxial leaf surface as compared to the leaves of control plants. In addition to this, A. ilicifolius when treated with ZnSO₄, exhibited a deeply stained layer of cells immediate to the endodermis, forming more or less a ring like structure around the xylem vessels. Phloem cells in these plants were crushed/reduced in numbers. There were no such deeply stained cells forming a ring around the xylem vessels in the control plants. These adaptive responses make the plant a suitable candidate for the phytostabilization of Zn. In addition the nutritional adjustment of the plant equips them for a better survival under increased concentration of Zn²⁺.

Keywords: Acanthus ilicifolius, mineral elements, phytostabilization, zinc

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Authors: Merzak Laribi, Abdelmadjid Kasser

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Thermal spraying processes are widely used to produce coatings on original constructions as well as in repair and maintenance of long standing structures. A lot of efforts forwarding to develop thermal spray coatings technology have been focused on improving mechanical characteristics, minimizing residual stress level and reducing porosity of the coatings. The specific aim of this paper is to determine either residual stresses distribution or wear resistance of stainless steel coating thermally sprayed on a carbon steel substrate. Internal stresses determination was performed using an extensometric method in combination with a simultaneous progressive electrolytic polishing. The procedure consists of measuring micro-deformations using a bi-directional extensometric gauges glued on the substrate side of the materials. Very thin layers of the deposits are removed by electrochemical polishing across the sample surface. Micro-deformations are instantaneously measured, leading to residual stresses calculation after each removal. Wear resistance of the coating has been determined using a ball-on-plate tribometer. Friction coefficient is instantaneously measured during the tribological test. Attention was particularly focused on the influence of a post-annealing at 850 °C for one hour in vacuum either on the residual stresses distribution or on the wear resistance behavior under specific wear and lubrication conditions. The obtained results showed that the microstructure of the obtained arc sprayed stainless steel coating is classical. It is homogeneous and contains un-melted particles, metallic oxides and also pores and micro-cracks. The internal stresses are in compression in the coating. They are more or less scattered between -50 and -270 MPa on the surface and decreased more at the interface. The value at the surface of the substrate is about –700 MPa, partially due to the molten particles impact with the substrate. The post annealing has reduced the residual stresses in both coating and surface of the steel substrate so that the hole material becomes more relaxed. Friction coefficient has an average value of 0.3 and 0.4 respectively for non annealed and annealed specimen. It is rather oil lubrication which is really benefit so that friction coefficient is decreased to about 0.06.

Keywords: residual stresses, wear resistance, stainless steel, coating, thermal spraying, annealing, lubrication

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Authors: Muna K. Abbass, Laith A. Mohammed, Muntaha K. Abbas

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The oxidation of Al-Li base alloy containing small amounts of rare earth (RE) oxides such as 0.2 wt% Y2O3 and 0.2wt% Nd2O3 particles have been studied at temperatures: 400ºC, 500ºC and 550°C for 60hr in a dry air. Alloys used in this study were prepared by melting and casting in a permanent steel mould under controlled atmosphere. Identification of oxidation kinetics was carried out by using weight gain/surface area (∆W/A) measurements while scanning electron microscopy (SEM) and x-ray diffraction analysis were used for micro structural morphologies and phase identification of the oxide scales. It was observed that the oxidation kinetic for all studied alloys follows the parabolic law in most experimental tests under the different oxidation temperatures. It was also found that the alloy containing 0.2 wt %Y 2O3 particles possess the lowest oxidation rate and shows great improvements in oxidation resistance compared to the alloy containing 0.2 wt % Nd2O3 particles and Al-Li base alloy. In this work, Taguchi method is performed to estimate the optimum weight gain /area (∆W/A) parameter in oxidation process of Al-Li base alloys to obtain a minimum thickness of oxidation layer. Taguchi method is used to formulate the experimental layout, to analyses the effect of each parameter (time, temperature and alloy type) on the oxidation generation and to predict the optimal choice for each parameter and analyzed the effect of these parameters on the weight gain /area (∆W/A) parameter. The analysis shows that, the temperature significantly affects on the (∆W/A) parameter.

Keywords: Al-Li base alloy, oxidation, Taguchi method, temperature

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Authors: Amr Sadek, Abdelrahaman Al-Qahtany, Turkey Salem Al-Qahtany

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In this study, a backpropagation artificial neural network (ANN) model has been used to predict the cooling and heating capacities of air conditioners (AC) under different conditions. Sufficiently large measurement results were obtained from the national energy-efficiency laboratories in Saudi Arabia and were used for the learning process of the ANN model. The parameters affecting the performance of the AC, including temperature, humidity level, specific heat enthalpy indoors and outdoors, and the air volume flow rate of indoor units, have been considered. These parameters were used as inputs for the ANN model, while the cooling and heating capacity values were set as the targets. A backpropagation ANN model with two hidden layers and one output layer could successfully correlate the input parameters with the targets. The characteristics of the ANN model including the input-processing, transfer, neurons-distance, topology, and training functions have been discussed. The performance of the ANN model was monitored over the training epochs and assessed using the mean squared error function. The model was then used to predict the performance of the AC under conditions that were not included in the measurement results. The optimum performance of the AC was also predicted under the different environmental conditions in Saudi Arabia. The uncertainty of the ANN model predictions has been evaluated taking into account the randomness of the data and lack of learning.

Keywords: artificial neural network, uncertainty of model predictions, efficiency of air conditioners, cooling and heating capacities

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Authors: S: Kayesth, K. K. Gupta

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The indiscriminate use of insecticides causes environmental contamination, adversely affects non-target organisms and develops resistance among insects and pests. There has always been felt a need for methods of control which can overcome these environmental and other ecological issues. The present study was designed to evaluate the effect of different plants volatiles on survival, longevity, growth, development and reproduction of Dysdercus koenigii. The hexane extract of three different plants (Catharanthus roseus, Ocimum sanctum and Lantana camara) was used. The fifth instars were exposed to hexane extract with concentrations of 10%, 5%, 2.5%, 1.25%, 0.1%, 0.5%, 0.25%, 0.13% and 0.06% while adults were treated with 10%, 5%, 2.5% and 1.25%. 1-ml of each of these concentrations was used to make a thin film in sterilized glass jars of 500 ml capacity. Fifteen newly emerged fifth instar nymphs and ten pairs of adult bugs were treated separately with the extracts for 24 hour exposure to the plant volatiles. The effect of these plant extract was observed and readings were recorded for 23 days. Survival and longevity of both fifth instars and adults were in correlation with the concentrations of the plant extracts. The extracts did not influence growth of fifth instars significantly but impaired their development significantly at higher concentrations. The treated nymphs at higher concentrations either could not moult or died and those which could moult moulted into supranumery instars, adultoids or adults with wing deformities. The supranumery insects retained the nymphal characters except increased body size and wing pads. The adultoids had wing deformities and non-functional reproductive organs. Adultoids exhibited courtship and mounting attempts but were not able to mate. At lower concentrations from 0.1 to 0.06% the fifth instars developed into adults with fewer deformities. At these concentrations, the fecundity and fertility of these adults were drastically reduced. On the contrary, the treated adults also had reduced fecundity and fertility compared to control. Among three plant extracts Ocimcum was most toxic for both fifth instars and adults in terms of survival and longevity. Catharanthus, Ocimum and Lantana appeared to have potential molecules which possessed insect juvenile hormone like activity. Potential application of these plant extracts in IPM was discussed.

Keywords: Catharanthus, Ocimum, Lantana, Dysdercus koenigii

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Authors: Zhou Luchen, Wu Yubing, Burra Venkata Durga Kumar

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As the scale of the network becomes larger and more complex than before, the density of user devices is also increasing. The development of Unmanned Aerial Vehicle (UAV) networks is able to collect and transform data in an efficient way by using software-defined networks (SDN) technology. This paper proposed a three-layer distributed and dynamic cluster architecture to manage UAVs by using an AI-based resource allocation calculation algorithm to address the overloading network problem. Through separating services of each UAV, the UAV hierarchical cluster system performs the main function of reducing the network load and transferring user requests, with three sub-tasks including data collection, communication channel organization, and data relaying. In this cluster, a head node and a vice head node UAV are selected considering the Central Processing Unit (CPU), operational (RAM), and permanent (ROM) memory of devices, battery charge, and capacity. The vice head node acts as a backup that stores all the data in the head node. The k-means clustering algorithm is used in order to detect high load regions and form the UAV layered clusters. The whole process of detecting high load areas, forming and selecting UAV clusters, and moving the selected UAV cluster to that area is proposed as offloading traffic algorithm.

Keywords: k-means, resource allocation, SDN, UAV network, unmanned aerial vehicles

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Authors: Aleš Florian, Lenka Ševelová

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Complex sensitivity analysis of stresses in a concrete slab of the real type of rigid pavement made from recycled materials is performed. The computational model of the pavement is designed as a spatial (3D) model, is based on a nonlinear variant of the finite element method that respects the structural nonlinearity, enables to model different arrangements of joints, and the entire model can be loaded by the thermal load. Interaction of adjacent slabs in joints and contact of the slab and the subsequent layer are modeled with the help of special contact elements. Four concrete slabs separated by transverse and longitudinal joints and the additional structural layers and soil to the depth of about 3m are modeled. The thickness of individual layers, physical and mechanical properties of materials, characteristics of joints, and the temperature of the upper and lower surface of slabs are supposed to be random variables. The modern simulation technique Updated Latin Hypercube Sampling with 20 simulations is used. For sensitivity analysis the sensitivity coefficient based on the Spearman rank correlation coefficient is utilized. As a result, the estimates of influence of random variability of individual input variables on the random variability of principal stresses s1 and s3 in 53 points on the upper and lower surface of the concrete slabs are obtained.

Keywords: concrete, FEM, pavement, sensitivity, simulation

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Authors: Engy Shokry, Giancarlo La Marca, Maria Luisa Della Bona

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Newborn screening for Congenital Adrenal Hyperplasia (CAH) relies on quantification of 17α-hydroxyprogesterone using enzyme immunoassays. These assays, in spite of being rapid, readily available and easy to perform, its reliability was found questionable due to lack of selectivity and specificity resulting in large number of false-positives, consequently family anxiety and associated hospitalization costs. To improve specificity of conventional 17α-hydroxyprogesterone screening which may experience false transient elevation in preterm, low birth weight or acutely ill neonates, steroid profiling by LC-MS/MS as a second-tier test was implemented. Unlike the previously applied LC-MS/MS methods, with the disadvantage of requiring a relatively high number of blood drops. Since newborn screening tests are increasing, it is necessary to minimize the sample volume requirement to make the maximum use of blood samples collected on filter paper. The proposed new method requires just one 3.2 mm dried blood spot (DBS) punch. Extraction was done using methanol: water: formic acid (90:10:0.1, v/v/v) containing deuterium labelled internal standards. Extracts were evaporated and reconstituted in 10 % acetone in water. Column switching strategy for on-line sample clean-up was applied to improve the chromatographic run. The first separative step retained the investigated steroids and passed through the majority of high molecular weight impurities. After the valve switching, the investigated steroids are back flushed from the POROS® column onto the analytical column and separated using gradient elution. Found quantitation limits were 5, 10 and 50 nmol/L for 17α-hydroxyprogesterone, androstenedione and cortisol respectively with mean recoveries of between 98.31-103.24 % and intra-/ inter-assay CV% < 10 % except at LLOQ. The method was validated using standard addition calibration and isotope dilution strategies. Reference ranges were determined by analysing samples from 896 infants of various ages at the time of sample collection. The method was also applied on patients with confirmed CAH. Our method represents an attractive combination of low sample volume requirement, minimal sample preparation time without derivatization and quick chromatography (5 min). The three steroid profile and the concentration ratios (17OHP + androstenedione/cortisol) allowed better screening outcomes of CAH reducing false positives, associated costs and anxiety.

Keywords: congenital adrenal hyperplasia (CAH), 17α-hydroxyprogesterone, androstenedione, cortisol, LC-MS/MS

Procedia PDF Downloads 423