Search results for: spectral solver

Authors: Pandiyarajan Thangaraj, Mangalaraja Ramalinga Viswanathan, Karthikeyan Balasubramanian, Héctor D. Mansilla, José Ruiz

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Rare earth ions doped semiconductor nanostructures gained much attention due to their novel physical and chemical properties which lead to potential applications in laser technology as inexpensive luminescent materials. Doping of rare earth ions into ZnO semiconductor alter its electronic structure and emission properties. Surface modification (polymer covering) is one of the simplest techniques to modify the emission characteristics of host materials. The present work reports the synthesis and structural properties of PVA:Zn97Pr3O polymer nanocomposite free standing films. To prepare Pr3+ doped ZnO nanostructures and PVA:Zn97Pr3O polymer nanocomposite free standing films, the colloidal chemical and solution casting techniques were adopted, respectively. The formation of PVA:Zn97Pr3O films were confirmed through X-ray diffraction (XRD), absorption and Fourier transform infrared (FTIR) spectroscopy analyses. XRD measurements confirm the prepared materials are crystalline having hexagonal wurtzite structure. Polymer composite film exhibits the diffraction peaks of both PVA and ZnO structures. TEM images reveal the pure and Pr3+ doped ZnO nanostructures exhibit sheet like morphology. Optical absorption spectra show free excitonic absorption band of ZnO at 370 nm and, the PVA:Zn97Pr3O polymer film shows absorption bands at ~282 and 368 nm and these arise due to the presence of carbonyl containing structures connected to the PVA polymeric chains, mainly at the ends and free excitonic absorption of ZnO nanostructures, respectively. Transmission spectrum of as prepared film shows 57 to 69% of transparency in the visible and near IR region. FTIR spectral studies confirm the presence of A1 (TO) and E1 (TO) modes of Zn-O bond vibration and the formation of polymer composite materials.

Keywords: rare earth doped ZnO, polymer composites, structural characterization, surface modification

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Authors: Zhuanfang Fred Zhang, Tim C. Johnson, Yilin Fang, Chris E. Strickland

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A variety of geophysical techniques are available to image the opaque subsurface with little or no contact with the soil. It is common to conduct time-lapse surveys of different types for a given site for improved results of subsurface imaging. Regardless of the chosen survey methods, it is often a challenge to process the massive amount of survey data. The currently available software applications are generally based on the one-dimensional assumption for a desktop personal computer. Hence, they are usually incapable of imaging the three-dimensional (3D) processes/variables in the subsurface of reasonable spatial scales; the maximum amount of data that can be inverted simultaneously is often very small due to the capability limitation of personal computers. Presently, high-performance or integrating software that enables real-time integration of multi-process geophysical methods is needed. E4D-MP enables the integration and inversion of time-lapsed large-scale data surveys from geophysical methods. Using the supercomputing capability and parallel computation algorithm, E4D-MP is capable of processing data across vast spatiotemporal scales and in near real time. The main code and the modules of E4D-MP for inverting individual or combined data sets of time-lapse 3D electrical resistivity, spectral induced polarization, and gravity surveys have been developed and demonstrated for sub-surface imaging. E4D-MP provides capability of imaging the processes (e.g., liquid or gas flow, solute transport, cavity development) and subsurface properties (e.g., rock/soil density, conductivity) critical for successful control of environmental engineering related efforts such as environmental remediation, carbon sequestration, geothermal exploration, and mine land reclamation, among others.

Keywords: gravity survey, high-performance computing, sub-surface monitoring, electrical resistivity tomography

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Authors: Arturo Daag

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The Philippine Institute of Volcanology and Seismology (PHIVOLCS) is enhancing its liquefaction hazard map towards a detailed probabilistic approach using SDS and geophysical data. Target sites for liquefaction assessment are public schools in Metro Manila. Since target sites are in highly urbanized-setting, the objective of the project is to conduct both non-destructive geotechnical studies using Screw Driving Testing (SDFS) combined with geophysical data such as refraction microtremor array (ReMi), 3 component microtremor Horizontal to Vertical Spectral Ratio (HVSR), and ground penetrating RADAR (GPR). Initial test data was conducted in liquefaction impacted areas from the Mw 6.1 earthquake in Central Luzon last April 22, 2019 Province of Pampanga. Numerous accounts of liquefaction events were documented areas underlain by quaternary alluvium and mostly covered by recent lahar deposits. SDS estimated values showed a good correlation to actual SPT values obtained from available borehole data. Thus, confirming that SDS can be an alternative tool for liquefaction assessment and more efficient in terms of cost and time compared to SPT and CPT. Conducting borehole may limit its access in highly urbanized areas. In order to extend or extrapolate the SPT borehole data, non-destructive geophysical equipment was used. A 3-component microtremor obtains a subsurface velocity model in 1-D seismic shear wave velocity of the upper 30 meters of the profile (Vs30). For the ReMi, 12 geophone array with 6 to 8-meter spacing surveys were conducted. Microtremor data were computed through the Factor of Safety, which is the quotient of Cyclic Resistance Ratio (CRR) and Cyclic Stress Ratio (CSR). Complementary GPR was used to study the subsurface structure and used to inferred subsurface structures and groundwater conditions.

Keywords: screw drive testing, microtremor, ground penetrating RADAR, liquefaction

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Authors: Ruichong Zhang, Fadi Sawaged, Lotfi Gargab

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This paper introduces a wave-based approach for system identification of high-rise building structures with a pair of seismic recordings, which can be used to evaluate structural integrity and detect damage in post-earthquake structural condition assessment. The fundamental of the approach is based on wave features of generalized impulse and frequency response functions (GIRF and GFRF), i.e., wave responses at one structural location to an impulsive motion at another reference location in time and frequency domains respectively. With a pair of seismic recordings at the two locations, GFRF is obtainable as Fourier spectral ratio of the two recordings, and GIRF is then found with the inverse Fourier transformation of GFRF. With an appropriate continuous model for the structure, a closed-form solution of GFRF, and subsequent GIRF, can also be found in terms of wave transmission and reflection coefficients, which are related to structural physical properties above the impulse location. Matching the two sets of GFRF and/or GIRF from recordings and the model helps identify structural parameters such as wave velocity or shear modulus. For illustration, this study examines ten-story Millikan Library in Pasadena, California with recordings of Yorba Linda earthquake of September 3, 2002. The building is modelled as piecewise continuous layers, with which GFRF is derived as function of such building parameters as impedance, cross-sectional area, and damping. GIRF can then be found in closed form for some special cases and numerically in general. Not only does this study reveal the influential factors of building parameters in wave features of GIRF and GRFR, it also shows some system-identification results, which are consistent with other vibration- and wave-based results. Finally, this paper discusses the effectiveness of the proposed model in system identification.

Keywords: wave-based approach, seismic responses of buildings, wave propagation in structures, construction

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Authors: Lorenzo Cocola, Massimo Fedel, Dragiša Savić, Bojana Danilović, Luca Poletto

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An instrument for the detection and evaluation of gaseous carbon dioxide in the headspace of closed containers has been developed in the context of Packsensor Italian-Serbian joint project. The device is based on Tunable Diode Laser Absorption Spectroscopy (TDLAS) with a Wavelength Modulation Spectroscopy (WMS) technique in order to accomplish a non-invasive measurement inside closed containers of fermented dairy products (yogurts and fermented cheese in cups and bottles). The purpose of this instrument is the continuous monitoring of carbon dioxide concentration during incubation and storage of products over a time span of the whole shelf life of the product, in the presence of different microorganisms. The instrument’s optical front end has been designed to be integrated in a thermally stabilized incubator. An embedded computer provides processing of spectral artifacts and storage of an arbitrary set of calibration data allowing a properly calibrated measurement on many samples (cups and bottles) of different shapes and sizes commonly found in the retail distribution. A calibration protocol has been developed in order to be able to calibrate the instrument on the field also on containers which are notoriously difficult to seal properly. This calibration protocol is described and evaluated against reference measurements obtained through an industry standard (sampling) carbon dioxide metering technique. Some sets of validation test measurements on different containers are reported. Two test recordings of carbon dioxide concentration evolution are shown as an example of instrument operation. The first demonstrates the ability to monitor a rapid yeast growth in a contaminated sample through the increase of headspace carbon dioxide. Another experiment shows the dissolution transient with a non-saturated liquid medium in presence of a carbon dioxide rich headspace atmosphere.

Keywords: TDLAS, carbon dioxide, cups, headspace, measurement

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Authors: Arushi Singh, Anjana Jain, Prakash Vyavahare

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Recently, Li-Fi(light-fiedelity) has been launched based on VLC(visible light communication) technique, 100 times faster than WiFi. Now 5G mobile communication system is proposed to use VLC-OFDM as the transmission technique. The VLC system focused on visible rays, is considered for efficient spectrum use and easy intensity modulation through LEDs. The reason of high speed in VLC is LED, as they flicker incredibly fast(order of MHz). Another advantage of employing LED is-it acts as low pass filter results no out-of-band emission. The VLC system falls under the category of ‘green technology’ for utilizing LEDs. In present scenario, OFDM is used for high data-rates, interference immunity and high spectral efficiency. Inspite of the advantages OFDM suffers from large PAPR, ICI among carriers and frequency offset errors. Since, the data transmission technique used in VLC system is OFDM, the system suffers the drawbacks of OFDM as well as VLC, the non-linearity dues to non-linear characteristics of LED and PAPR of OFDM due to which the high power amplifier enters in non-linear region. The proposed paper focuses on reduction of PAPR in VLC-OFDM systems. Many techniques are applied to reduce PAPR such as-clipping-introduces distortion in the carrier; selective mapping technique-suffers wastage of bandwidth; partial transmit sequence-very complex due to exponentially increased number of sub-blocks. The paper discusses three companding techniques namely- µ-law, A-law and advance A-law companding technique. The analysis shows that the advance A-law companding techniques reduces the PAPR of the signal by adjusting the companding parameter within the range. VLC-OFDM systems are the future of the wireless communication but non-linearity in VLC-OFDM is a severe issue. The proposed paper discusses the techniques to reduce PAPR, one of the non-linearities of the system. The companding techniques mentioned in this paper provides better results without increasing the complexity of the system.

Keywords: non-linear companding techniques, peak to average power ratio (PAPR), visible light communication (VLC), VLC-OFDM

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Authors: C. Amer, M. Sahin

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The design of an optimised horizontal axis 5-meter-long wind turbine rotor blade in according with IEC 61400-2 standard is a research and development project in order to fulfil the requirements of high efficiency of torque from wind production and to optimise the structural components to the lightest and strongest way possible. For this purpose, a research study is presented here by focusing on the structural characteristics of a composite wind turbine blade via finite element modelling and analysis tools. In this work, first, the required data regarding the general geometrical parts are gathered. Then, the airfoil geometries are created at various sections along the span of the blade by using CATIA software to obtain the two surfaces, namely; the suction and the pressure side of the blade in which there is a hat shaped fibre reinforced plastic spar beam, so-called chassis starting at 0.5m from the root of the blade and extends up to 4 m and filled with a foam core. The root part connecting the blade to the main rotor differential metallic hub having twelve hollow threaded studs is then modelled. The materials are assigned as two different types of glass fabrics, polymeric foam core material and the steel-balsa wood combination for the root connection parts. The glass fabrics are applied using hand wet lay-up lamination with epoxy resin as METYX L600E10C-0, is the unidirectional continuous fibres and METYX XL800E10F having a tri-axial architecture with fibres in the 0,+45,-45 degree orientations in a ratio of 2:1:1. Divinycell H45 is used as the polymeric foam. The finite element modelling of the blade is performed via MSC PATRAN software with various meshes created on each structural part considering shell type for all surface geometries, and lumped mass were added to simulate extra adhesive locations. For the static analysis, the boundary conditions are assigned as fixed at the root through aforementioned bolts, where for dynamic analysis both fixed-free and free-free boundary conditions are made. By also taking the mesh independency into account, MSC NASTRAN is used as a solver for both analyses. The static analysis aims the tip deflection of the blade under its own weight and the dynamic analysis comprises normal mode dynamic analysis performed in order to obtain the natural frequencies and corresponding mode shapes focusing the first five in and out-of-plane bending and the torsional modes of the blade. The analyses results of this study are then used as a benchmark prior to modal testing, where the experiments over the produced wind turbine rotor blade has approved the analytical calculations.

Keywords: dynamic analysis, fiber reinforced composites, horizontal axis wind turbine blade, hand-wet layup, modal testing

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Authors: Massimo Miccoli, Luca Marangoni, Alberto Aniello Scaringi, Alessandro Marceddu, Alessandro Amicone

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The susceptibility of deep neural networks (DNNs) to adversarial manipulations is a recognized challenge within the computer vision domain. Adversarial examples, crafted by adding subtle yet malicious alterations to benign images, exploit this vulnerability. Various defense strategies have been proposed to safeguard DNNs against such attacks, stemming from diverse research hypotheses. Building upon prior work, our approach involves the utilization of autoencoder models. Autoencoders, a type of neural network, are trained to learn representations of training data and reconstruct inputs from these representations, typically minimizing reconstruction errors like mean squared error (MSE). Our autoencoder was trained on a dataset of benign examples; learning features specific to them. Consequently, when presented with significantly perturbed adversarial examples, the autoencoder exhibited high reconstruction errors. The architecture of the autoencoder was tailored to the dimensions of the images under evaluation. We considered various image sizes, constructing models differently for 256x256 and 512x512 images. Moreover, the choice of the computer vision model is crucial, as most adversarial attacks are designed with specific AI structures in mind. To mitigate this, we proposed a method to replace image-specific dimensions with a structure independent of both dimensions and neural network models, thereby enhancing robustness. Our multi-modal autoencoder reconstructs the spectral representation of images across the red-green-blue (RGB) color channels. To validate our approach, we conducted experiments using diverse datasets and subjected them to adversarial attacks using models such as ResNet50 and ViT_L_16 from the torch vision library. The autoencoder extracted features used in a classification model, resulting in an MSE (RGB) of 0.014, a classification accuracy of 97.33%, and a precision of 99%.

Keywords: adversarial attacks, malicious images detector, binary classifier, multimodal transformer autoencoder

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Authors: Cóndor C. José, Rodrigues E. Camila, Noronha L. Irene, Dos Santos Fernando, Irigoyen M. Claudia, Andrade Lúcia

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Sepsis induces alterations in hemodynamics and autonomic nervous system (ASN). The autonomic activity can be calculated by measuring heart rate variability (HRV) that represents the complex interplay between ASN and cardiac pacemaker cells. Wharton’s jelly mesenchymal stem cells (WJ-MSCs) are known to express genes and secreted factors involved in neuroprotective and immunological effects, also to improve the survival in experimental septic animals. We hypothesized, that WJ-MSCs present an important role in the autonomic activity and in the hemodynamic effects in a cecal ligation and puncture (CLP) model of sepsis. Methods: We used flow cytometry to evaluate WJ-MSCs phenotypes. We divided Wistar rats into groups: sham (shamoperated); CLP; and CLP+MSC (106 WJ-MSCs, i.p., 6 h after CLP). At 24 h post-CLP, we recorded the systolic arterial pressure (SAP) and heart rate (HR) over 20 min. The spectral analysis of HR and SAP; also the spontaneous baroreflex sensitivity (measure by bradycardic and tachycardic responses) were evaluated after recording. The one-way ANOVA and the post hoc Student– Newman– Keuls tests (P< 0.05) were used to data comparison Results: WJ-MSCs were negative for CD3, CD34, CD45 and HLA-DR, whereas they were positive for CD73, CD90 and CD105. The CLP group showed a reduction in variance of overall variability and in high-frequency power of HR (heart parasympathetic activity); furthermore, there is a low-frequency reduction of SAP (blood vessels sympathetic activity). The treatment with WJ-MSCs improved the autonomic activity by increasing the high and lowfrequency power; and restore the baroreflex sensitive. Conclusions: WJ-MSCs attenuate the impairment of autonomic control of the heart and vessels and might therefore play a protective role in sepsis. (Supported by FAPESP).

Keywords: baroreflex response, heart rate variability, sepsis, wharton’s jelly-derived mesenchymal stem cells

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Authors: Daniel Martin Fellows, Sean P. Walton, Jennifer Thompson, Oubay Hassan, Kevin Tinkham, Ella Quigley

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Structural integrity for cladding products is a key performance parameter, especially concerning fire performance. Cladding products such as PIR-based sandwich panels are tested rigorously, in line with industrial standards. Physical fire tests are necessary to ensure the customer's safety but can give little information about critical behaviours that can help develop new materials. Numerical modelling is a tool that can help investigate a fire's behaviour further by replicating the fire test. However, fire is an interdisciplinary problem as it is a chemical reaction that behaves fluidly and impacts structural integrity. An analysis using Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) is needed to capture all aspects of a fire performance test. One method is a two-way coupling analysis that imports the updated changes in thermal data, due to the fire's behaviour, to the FEA solver in a series of iterations. In light of our recent work with Tata Steel U.K using a two-way coupling methodology to determine the fire performance, it has been shown that a program called FDS-2-Abaqus can make predictions of a BS 476 -22 furnace test with a degree of accuracy. The test demonstrated the fire performance of Tata Steel U.K Trisomet product, a Polyisocyanurate (PIR) based sandwich panel used for cladding. Previous works demonstrated the limitations of the current version of the program, the main limitation being the computational cost of modelling three Trisomet panels, totalling an area of 9 . The computational cost increases substantially, with the intention to scale up to an LPS 1181-1 test, which includes a total panel surface area of 200 .The FDS-2-Abaqus program is developed further within this paper to overcome this obstacle and better accommodate Tata Steel U.K PIR sandwich panels. The new developments aim to reduce the computational cost and error margin compared to experimental data. One avenue explored is a multi-scale approach in the form of Reduced Order Modeling (ROM). The approach allows the user to include refined details of the sandwich panels, such as the overlapping joints, without a computationally costly mesh size.Comparative studies will be made between the new implementations and the previous study completed using the original FDS-2-ABAQUS program. Validation of the study will come from physical experiments in line with governing body standards such as BS 476 -22 and LPS 1181-1. The physical experimental data includes the panels' gas and surface temperatures and mechanical deformation. Conclusions are drawn, noting the new implementations' impact factors and discussing the reasonability for scaling up further to a whole warehouse.

Keywords: fire testing, numerical coupling, sandwich panels, thermo fluids

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Authors: Chaitanya H. Acharya, Pavan Kumar P., Gopalakrishna Narayana

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In the realm of aerodynamics, numerous vehicles incorporate moving components to enhance their performance. For instance, airliners deploy hydraulically operated flaps and ailerons during take-off and landing, while Formula 1 racing cars utilize hydraulic tubes and actuators for various components, including the Drag Reduction System (DRS). The DRS, consisting of a rear wing and adjustable flaps, plays a crucial role in overtaking manoeuvres. The DRS has two positions: the default position with the flaps down, providing high downforce, and the lifted position, which reduces drag, allowing for increased speed and aiding in overtaking. Swift deployment of the DRS during races is essential for overtaking competitors. The fluid flow over the rear wing flap becomes intricate during deployment, involving flow reversal and operational changes, leading to unsteady flow physics that significantly influence aerodynamic characteristics. Understanding the drag and downforce during DRS deployment is crucial for determining race outcomes. While experiments can yield accurate aerodynamic data, they can be expensive and challenging to conduct across varying speeds. Computational Fluid Dynamics (CFD) emerges as a cost-effective solution to predict drag and downforce across a range of speeds, especially with the rapid deployment of the DRS. This study employs the finite volume-based solver Ansys Fluent, incorporating dynamic mesh motions and a turbulent model to capture the complex flow phenomena associated with the moving rear wing flap. A dedicated section for the rare wing-flap is considered in the present simulations, and the aerodynamics of these sections closely resemble S1223 aerofoils. Before delving into the simulations of the rare wing-flap aerofoil, numerical results undergo validation using experimental data from an NLR flap aerofoil case, encompassing different flap angles at two distinct angles of attack was carried out. The increase in flap angle as increase in lift and drag is observed for a given angle of attack. The simulation methodology for the rare-wing-flap aerofoil case involves specific time durations before lifting the flap. During this period, drag and downforce values are determined as 330 N and 1800N, respectively. Following the flap lift, a noteworthy reduction in drag to 55 % and a decrease in downforce to 17 % are observed. This understanding is critical for making instantaneous decisions regarding the deployment of the Drag Reduction System (DRS) at specific speeds, thereby influencing the overall performance of the Formula 1 racing car. Hence, this work emphasizes the utilization of dynamic mesh motion methodology to predict the aerodynamic characteristics during the deployment of the DRS in a Formula 1 racing car.

Keywords: DRS, CFD, drag, downforce, dynamics mesh motion

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Authors: Eiman A. Al-Enezi, Gin Jose, Sikha Saha, Paul Millner

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Rare earth nanotechnology has gained a considerable amount of interest in the field of biosensing due to the unique luminescence properties of lanthanides. Chelating rare earth ions plays a significant role in biological labelling applications including medical diagnostics, due to their different excitation and emission wavelengths, variety of their spectral properties, sharp emission peaks and long fluorescence lifetimes. We aimed to develop a platform for biosensors based on Europium (Eu³⁺) chelates against biomarkers of cardiac injury (heart-type fatty acid binding protein; H-FABP3) and stroke (glial fibrillary acidic protein; GFAP). Additional novelty in this project is the use of synthetic binding proteins (Affimers), which could offer an excellent alternative targeting strategy to the existing antibodies. Anti-GFAP and anti-HFABP3 Affimer binders were modified to increase the number of carboxy functionalities. Europium nitrate then incubated with the modified Affimer. The luminescence characteristics of the Eu³⁺ complex with modified Affimers and antibodies against anti-GFAP and anti-HFABP3 were measured against different concentrations of the respective analytes on excitation wavelength of 395nm. Bovine serum albumin (BSA) was used as a control against the IgG/Affimer Eu³⁺ complexes. The emission spectrum of Eu³⁺ complex resulted in 5 emission peaks ranging between 550-750 nm with the highest intensity peaks were at 592 and 698 nm. The fluorescence intensity of Eu³⁺ chelates with the modified Affimer or antibodies increased significantly by 4-7 folder compared to the emission spectrum of Eu³⁺ complex. The fluorescence intensity of the Affimer complex was quenched proportionally with increased analyte concentration, but this did not occur with antibody complex. In contrast, the fluorescence intensity for Eu³⁺ complex increased slightly against increased concentration of BSA. These data demonstrate that modified Affimers Eu³⁺ complexes can function as nanobiosensors with potential diagnostic and analytical applications.

Keywords: lanthanides, europium, chelates, biosensors

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Authors: Teng Li, Kamran Mohseni

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This paper presents an inviscid regularization technique that is capable of regularizing the shocks and sharp interfaces simultaneously in the shock-interface interaction simulations. The direct numerical simulation of flows involving shocks has been investigated for many years and a lot of numerical methods were developed to capture the shocks. However, most of these methods rely on the numerical dissipation to regularize the shocks. Moreover, in high Reynolds number flows, the nonlinear terms in hyperbolic Partial Differential Equations (PDE) dominates, constantly generating small scale features. This makes direct numerical simulation of shocks even harder. The same difficulty happens in two-phase flow with sharp interfaces where the nonlinear terms in the governing equations keep sharpening the interfaces to discontinuities. The main idea of the proposed technique is to average out the small scales that is below the resolution (observable scale) of the computational grid by filtering the convective velocity in the nonlinear terms in the governing PDE. This technique is named “observable method” and it results in a set of hyperbolic equations called observable equations, namely, observable Navier-Stokes or Euler equations. The observable method has been applied to the flow simulations involving shocks, turbulence, and two-phase flows, and the results are promising. In the current paper, the observable method is examined on the performance of regularizing shocks and interfaces at the same time in shock-interface interaction problems. Bubble-shock interactions and Richtmyer-Meshkov instability are particularly chosen to be studied. Observable Euler equations will be numerically solved with pseudo-spectral discretization in space and third order Total Variation Diminishing (TVD) Runge Kutta method in time. Results are presented and compared with existing publications. The interface acceleration and deformation and shock reflection are particularly examined.

Keywords: compressible flow simulation, inviscid regularization, Richtmyer-Meshkov instability, shock-bubble interactions.

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Authors: Sudipto Sarkar, Anamika Paul

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Pseudoplastic (n<1, n is the power index) fluids have great importance in food, pharmaceutical and chemical process industries which require a lot of attention. Unfortunately, due to its complex flow behavior inadequate research works can be found even in laminar flow regime. A practical problem is solved in the present research work by numerical simulation where we tried to control the vortex shedding from a square cylinder using a horizontal splitter plate placed at the downstream flow region. The position of the plate is at the centerline of the cylinder with varying distance from the cylinder to calculate the critical gap-ratio. If the plate is placed inside this critical gap, the vortex shedding from the cylinder suppressed completely. The Reynolds number considered here is in unsteady laminar vortex shedding regime, Re = 100 (Re = U∞a/ν, where U∞ is the free-stream velocity of the flow, a is the side of the cylinder and ν is the maximum value of kinematic viscosity of the fluid). Flow behavior has been studied for three different gap-ratios (G/a = 2, 2.25 and 2.5, where G is the gap between cylinder and plate) and for a fluid with three different flow behavior indices (n =1, 0.8 and 0.5). The flow domain is constructed using Gambit 2.2.30 and this software is also used to generate the mesh and to impose the boundary conditions. For G/a = 2, the domain size is considered as 37.5a × 16a with 316 × 208 grid points in the streamwise and flow-normal directions respectively after a thorough grid independent study. Fine and equal grid spacing is used close to the geometry to capture the vortices shed from the cylinder and the boundary layer developed over the flat plate. Away from the geometry meshes are unequal in size and stretched out. For other gap-ratios, proportionate domain size and total grid points are used with similar kind of mesh distribution. Velocity inlet (u = U∞), pressure outlet (Neumann condition), symmetry (free-slip boundary condition) at upper and lower domain boundary conditions are used for the simulation. Wall boundary condition (u = v = 0) is considered both on the cylinder and the splitter plate surfaces. Discretized forms of fully conservative 2-D unsteady Navier Stokes equations are then solved by Ansys Fluent 14.5. SIMPLE algorithm written in finite volume method is selected for this purpose which is a default solver inculcate in Fluent. The results obtained for Newtonian fluid flow agree well with previous works supporting Fluent’s usefulness in academic research. A thorough analysis of instantaneous and time-averaged flow fields are depicted both for Newtonian and pseudoplastic fluid flow. It has been observed that as the value of n reduces the stretching of shear layers also reduce and these layers try to roll up before the plate. For flow with high pseudoplasticity (n = 0.5) the nature of vortex shedding changes and the value of critical gap-ratio reduces. These are the remarkable findings for laminar periodic vortex shedding regime in pseudoplastic flow environment.

Keywords: CFD, pseudoplastic fluid flow, wake-boundary layer interactions, critical gap-ratio

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Authors: Irsa Ejaz, Siyang He, Wei Li, Naiyue Hu, Chaochen Tang, Songbo Li, Meng Li, Boubacar Diallo, Guanghui Xie, Kang Yu

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Background: Near-infrared spectroscopy (NIR) is a non-destructive, fast, and low-cost method to measure the grain quality of different cereals. Previously reported NIR model calibrations using the whole grain spectra had moderate accuracy. Improved predictions are achievable by using the spectra of whole grains, when compared with the use of spectra collected from the flour samples. However, the feasibility for determining the critical biochemicals, related to the classifications for food, feed, and fuel products are not adequately investigated. Objectives: To evaluate the feasibility of using NIRS and the influence of four sample types (whole grains, flours, hulled grain flours, and hull-less grain flours) on the prediction of chemical components to improve the grain sorting efficiency for human food, animal feed, and biofuel. Methods: NIR was applied in this study to determine the eight biochemicals in four types of sorghum samples: hulled grain flours, hull-less grain flours, whole grains, and grain flours. A total of 20 hybrids of sorghum grains were selected from the two locations in China. Followed by NIR spectral and wet-chemically measured biochemical data, partial least squares regression (PLSR) was used to construct the prediction models. Results: The results showed that sorghum grain morphology and sample format affected the prediction of biochemicals. Using NIR data of grain flours generally improved the prediction compared with the use of NIR data of whole grains. In addition, using the spectra of whole grains enabled comparable predictions, which are recommended when a non-destructive and rapid analysis is required. Compared with the hulled grain flours, hull-less grain flours allowed for improved predictions for tannin, cellulose, and hemicellulose using NIR data. Conclusion: The established PLSR models could enable food, feed, and fuel producers to efficiently evaluate a large number of samples by predicting the required biochemical components in sorghum grains without destruction.

Keywords: FT-NIR, sorghum grains, biochemical composition, food, feed, fuel, PLSR

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Authors: M. A. Ferhat, M. N. Boukhatem, F. Chemat

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Eucalyptus essential oil is extracted from Eucalyptus globulus of the Myrtaceae family and is also known as Tasmanian blue gum or blue gum. Despite the reputation earned by aromatic and medicinal plants of Algeria. The objectives of this study were: (i) the extraction of the essential oil from the leaves of Eucalyptus globulus Labill., Myrtaceae grown in Algeria, and the quantification of the yield thereof, (ii) the identification and quantification of the compounds in the essential oil obtained, and (iii) the determination of physical and chemical properties of EGEO. The chemical constituents of Eucalyptus globulus essential oil (EGEO) of Blida origin has not previously been investigated. Thus, the present study has been conducted for the determination of chemical constituents and different physico-chemical properties of the EGEO. Chemical composition of the EGEO, grown in Algeria, was analysed by Gas Chromatography-Mass Spectrometry. The chemical components were identified on the basis of Retention Time and comparing with mass spectral database of standard compounds. Relative amounts of detected compounds were calculated on the basis of GC peak areas. Fresh leaves of E. globulus on steam distillation yielded 0.96% (v/w) of essential oil whereas the analysis resulted in the identification of a total of 11 constituents, 1.8 cineole (85.8%), α-pinene (7.2%), and β-myrcene (1.5%) being the main components. Other notable compounds identified in the oil were β-pinene, limonene, α-phellandrene, γ-terpinene, linalool, pinocarveol, terpinen-4-ol, and α-terpineol. The physical properties such as specific gravity, refractive index and optical rotation and the chemical properties such as saponification value, acid number and iodine number of the EGEO were examined. The oil extracted has been analyzed to have 1.4602-1.4623 refractive index value, 0.918-0.919 specific gravity (sp.gr.), +9 - +10 optical rotation that satisfy the standards stipulated by European Pharmacopeia. All the physical and chemical parameters were in the range indicated by the ISO standards. Our findings will help to access the quality of the Eucalyptus oil which is important in the production of high value essential oils that will help to improve the economic condition of the community as well as the nation.

Keywords: chemical composition, essential oil, eucalyptol, gas chromatography

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Authors: Q. Ni, J. A. Serna, D. Holland, X. Wang

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The objective of this study is to develop Nuclear Magnetic Resonance (NMR) techniques to enhance bone related research applied on normal and disuse (Biglycan knockout) mice bone in vitro by using both low-field and high-field NMR simultaneously. It is known that the total amplitude of T₂ relaxation envelopes, measured by the Carr-Purcell-Meiboom-Gill NMR spin echo train (CPMG), is a representation of the liquid phase inside the pores. Therefore, the NMR CPMG magnetization amplitude can be transferred to the volume of water after calibration with the NMR signal amplitude of the known volume of the selected water. In this study, the distribution of mobile water, porosity that can be determined by using low-field (20 MHz) CPMG relaxation technique, and the pore size distributions can be determined by a computational inversion relaxation method. It is also known that the total proton intensity of magnetization from the NMR free induction decay (FID) signal is due to the water present inside the pores (mobile water), the water that has undergone hydration with the bone (bound water), and the protons in the collagen and mineral matter (solid-like protons). Therefore, the components of total mobile and bound water within bone that can be determined by low-field NMR free induction decay technique. Furthermore, the bound water in solid phase (mineral and organic constituents), especially, the dominated component of calcium hydroxyapatite (Ca₁₀(OH)₂(PO₄)₆) can be determined by using high-field (400 MHz) magic angle spinning (MAS) NMR. With MAS technique reducing NMR spectral linewidth inhomogeneous broadening and susceptibility broadening of liquid-solid mix, in particular, we can conduct further research into the ¹H and ³¹P elements and environments of bone materials to identify the locations of bound water such as OH- group within minerals and bone architecture. We hypothesize that with low-field and high-field magic angle spinning NMR can provide a more complete interpretation of water distribution, particularly, in bound water, and these data are important to access bone quality and predict the mechanical behavior of bone.

Keywords: bone, mice bone, NMR, water in bone

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Authors: Zeina Merabi, Arij Dao

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The temporal order of information processing in the brain is an important code in many acoustic signals, including speech, music, and animal vocalizations. Despite its significance, surprisingly little is known about its underlying cellular mechanisms and network manifestations. In the songbird telencephalic nucleus HVC, a subset of neurons shows temporal combination sensitivity (TCS). These neurons show a high temporal specificity, responding differently to distinct patterns of spectral elements and their combinations. HVC neuron types include basal-ganglia-projecting HVCX, forebrain-projecting HVCRA, and interneurons (HVC¬INT), each exhibiting distinct cellular, electrophysiological and functional properties. In this work, we develop conductance-based neural network models connecting the different classes of HVC neurons via different wiring scenarios, aiming to explore possible neural mechanisms that orchestrate the combination sensitivity property exhibited by HVCX, as well as replicating in vivo firing patterns observed when TCS neurons are presented with various auditory stimuli. The ionic and synaptic currents for each class of neurons that are presented in our networks and are based on pharmacological studies, rendering our networks biologically plausible. We present for the first time several realistic scenarios in which the different types of HVC neurons can interact to produce this behavior. The different networks highlight neural mechanisms that could potentially help to explain some aspects of combination sensitivity, including 1) interplay between inhibitory interneurons’ activity and the post inhibitory firing of the HVCX neurons enabled by T-type Ca2+ and H currents, 2) temporal summation of synaptic inputs at the TCS site of opposing signals that are time-and frequency- dependent, and 3) reciprocal inhibitory and excitatory loops as a potent mechanism to encode information over many milliseconds. The result is a plausible network model characterizing auditory processing in HVC. Our next step is to test the predictions of the model.

Keywords: combination sensitivity, songbirds, neural networks, spatiotemporal integration

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Authors: Silvia Ximena Barrios, Diego Armando Villamizar Mantilla, Raquel Elvira Ocazionez, , Elena E. Stashenko, María Pilar Vinardell, Jorge Luis Fuentes

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Introduction: Skin overexposure to solar radiation has been a serious public health concern, because of its potential carcinogenicity. Therefore, preventive protection strategies using photoprotective agents are critical to counteract the harmful effect of solar radiation. Plants may be a source of photoprotective compounds that inhibit cellular mutations involved in skin cancer initiation. This work evaluated the photoprotective and antigenotoxic effects against ultraviolet B (UVB) radiation of a mixture of Posoqueria latifolia flower extract and Kaempferol (MixPoKa). Methods: The photoprotective efficacy of MixPoka (Posoqueria latifolia flower extract 250 μg/ml and Kaempferol 349.5 μM) was evaluated using in vitro indices such as sun protection factor SPFᵢₙ ᵥᵢₜᵣₒ and critical wavelength (λc). The MixPoKa photostability (Eff) at human minimal erythema doses (MED), according to the Fitzpatrick skin scale, was also estimated. Cytotoxicity and genotoxicity/antigenotoxicity were studied in MRC5 human fibroblasts using the trypan blue exclusion and Comet assays, respectively. Kinetics of the genetic damage repair post irradiation in the presence and absence of the MixPoka, was also evaluated. Results: The MixPoka -UV absorbance spectrum was high across the spectral bands between 200 and 400 nm. The UVB photoprotection efficacy of MixPoka was high (SPFᵢₙ ᵥᵢₜᵣₒ = 25.70 ± 0.06), showed wide photoprotection spectrum (λc = 380 ± 0), and resulted photostable (Eff = 92.3–100.0%). The MixPoka was neither cytotoxic nor genotoxic in MRC5 human fibroblasts; but presented significant antigenotoxic effect against UVB radiation. Additionally, MixPoka stimulate DNA repair post-irradiation. The potential of this phytochemical mixture as sunscreen ingredients was discussed. Conclusion: MixPoka showed a significant antigenotoxic effect against UVB radiation and stimulated DNA repair after irradiation. MixPoka could be used as an ingredient in a sunscreen cream.

Keywords: flower extract, photoprotection, antigenotoxicity, cytotoxicity, genotoxicit

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Authors: Thomas Monahan, Nicolas Gorius, Thanh Nguyen

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Exoplanet atmospheric parameters retrieval is a complex, computationally intensive, inverse modeling problem in which an exoplanet’s atmospheric composition is extracted from an observed spectrum. Traditional Bayesian sampling methods require extensive time and computation, involving algorithms that compare large numbers of known atmospheric models to the input spectral data. Runtimes are directly proportional to the number of parameters under consideration. These increased power and runtime requirements are difficult to accommodate in space missions where model size, speed, and power consumption are of particular importance. The use of traditional Bayesian sampling methods, therefore, compromise model complexity or sampling accuracy. The Atmospheric Retrievals conditional Generative Adversarial Network (ARcGAN) is a deep convolutional generative adversarial network that improves on the previous model’s speed and accuracy. We demonstrate the efficacy of artificial intelligence to quickly and reliably predict atmospheric parameters and present it as a viable alternative to slow and computationally heavy Bayesian methods. In addition to its broad applicability across instruments and planetary types, ARcGAN has been designed to function on low power application-specific integrated circuits. The application of edge computing to atmospheric retrievals allows for real or near-real-time quantification of atmospheric constituents at the instrument level. Additionally, edge computing provides both high-performance and power-efficient computing for AI applications, both of which are critical for space missions. With the edge computing chip implementation, ArcGAN serves as a strong basis for the development of a similar machine-learning algorithm to reduce the downlinked data volume from the Compact Ultraviolet to Visible Imaging Spectrometer (CUVIS) onboard the DAVINCI mission to Venus.

Keywords: deep learning, generative adversarial network, edge computing, atmospheric parameters retrieval

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Authors: Amanina Iymia Jeffree, Reena Thriumani, Mohammad Iqbal Omar, Ammar Zakaria, Yumi Zuhanis Has-Yun Hashim, Ali Yeon Md Shakaff

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Metabolite profiling is a strategy to be approached in the pattern recognition method focused on three types of cancer cell line that driving the most to death specifically lung, breast, and colon cancer. The purpose of this study was to discriminate the VOCs pattern among cancerous and control group based on metabolite profiling. The sampling was executed utilizing the cell culture technique. All culture flasks were incubated till 72 hours and data collection started after 24 hours. Every running sample took 24 minutes to be completed accordingly. The comparative metabolite patterns were identified by the implementation of headspace-solid phase micro-extraction (HS-SPME) sampling coupled with gas chromatography-mass spectrometry (GCMS). The optimizations of the main experimental variables such as oven temperature and time were evaluated by response surface methodology (RSM) to get the optimal condition. Volatiles were acknowledged through the National Institute of Standards and Technology (NIST) mass spectral database and retention time libraries. To improve the reliability of significance, it is of crucial importance to eliminate background noise which data from 3rd minutes to 17th minutes were selected for statistical analysis. Targeted metabolites, of which were annotated as known compounds with the peak area greater than 0.5 percent were highlighted and subsequently treated statistically. Volatiles produced contain hundreds to thousands of compounds; therefore, it will be optimized by chemometric analysis, such as principal component analysis (PCA) as a preliminary analysis before subjected to a pattern classifier for identification of VOC samples. The volatile organic compound profiling has shown to be significantly distinguished among cancerous and control group based on metabolite profiling.

Keywords: in vitro cancer cell line, metabolite profiling, pattern recognition, volatile organic compounds

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Authors: Ali Kadir, O. Anwar Beg

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Thermal barrier coatings are among the most popular methods for providing corrosion protection in high temperature applications including aircraft engine systems, external spacecraft structures, rocket chambers etc. Many different materials are available for such coatings, of which ceramics generally perform the best. Motivated by these applications, the current investigation presents detailed finite element simulations of coating stress analysis for a 3- dimensional, 3-layered model of a test sample representing a typical gas turbine component scenario. Structural steel is selected for the main inner layer, Titanium (Ti) alloy for the middle layer and Silicon Carbide (SiC) for the outermost layer. The model dimensions are 20 mm (width), 10 mm (height) and three 1mm deep layers. ANSYS software is employed to conduct three types of analysis- static structural, thermal stress analysis and also computational fluid dynamic erosion/corrosion analysis (via ANSYS FLUENT). The specified geometry which corresponds to corrosion test samples exactly is discretized using a body-sizing meshing approach, comprising mainly of tetrahedron cells. Refinements were concentrated at the connection points between the layers to shift the focus towards the static effects dissipated between them. A detailed grid independence study is conducted to confirm the accuracy of the selected mesh densities. To recreate gas turbine scenarios; in the stress analysis simulations, static loading and thermal environment conditions of up to 1000 N and 1000 degrees Kelvin are imposed. The default solver was used to set the controls for the simulation with the fixed support being set as one side of the model while subjecting the opposite side to a tabular force of 500 and 1000 Newtons. Equivalent elastic strain, total deformation, equivalent stress and strain energy were computed for all cases. Each analysis was duplicated twice to remove one of the layers each time, to allow testing of the static and thermal effects with each of the coatings. ANSYS FLUENT simulation was conducted to study the effect of corrosion on the model under similar thermal conditions. The momentum and energy equations were solved and the viscous heating option was applied to represent improved thermal physics of heat transfer between the layers of the structures. A Discrete Phase Model (DPM) in ANSYS FLUENT was employed which allows for the injection of continuous uniform air particles onto the model, thereby enabling an option for calculating the corrosion factor caused by hot air injection (particles prescribed 5 m/s velocity and 1273.15 K). Extensive visualization of results is provided. The simulations reveal interesting features associated with coating response to realistic gas turbine loading conditions including significantly different stress concentrations with different coatings.

Keywords: thermal coating, corrosion, ANSYS FEA, CFD

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Authors: Sarre Nzaba, Bulelwa Ntsendwana, Bekkie Mamba, Alex Kuvarega

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The discharge of azo dyes such as Brilliant black (BB) into the water bodies has carcinogenic and mutagenic effects on humankind and the ecosystem. Conventional water treatment techniques fail to degrade these dyes completely thereby posing more problems. Advanced oxidation processes (AOPs) are promising technologies in solving the problem. Anatase type nitrogen-platinum (N, Pt) co-doped TiO₂ photocatalysts were prepared by a modified sol-gel method using amine terminated polyamidoamine generation 1 (PG1) as a template and source of nitrogen. The resultant photocatalysts were characterized by X‐ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X‐ray photoelectron spectroscopy (XPS), UV‐Vis diffuse reflectance spectroscopy, photoluminescence spectroscopy (PL), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy (RS), thermal gravimetric analysis (TGA). The results showed that the calcination atmosphere played an important role in the morphology, crystal structure, spectral absorption, oxygen vacancy concentration, and visible light photocatalytic performance of the catalysts. Anatase phase particles ranging between 9- 20 nm were also confirmed by TEM, SEM, and analysis. The origin of the visible light photocatalytic activity was attributed to both the elemental N and Pd dopants and the existence of oxygen vacancies. Co-doping imparted a shift in the visible region of the solar spectrum. The visible light photocatalytic activity of the samples was investigated by monitoring the photocatalytic degradation of brilliant black dye. Co-doped TiO₂ showed greater photocatalytic brilliant black degradation efficiency compared to singly doped N-TiO₂ or Pd-TiO₂ under visible light irradiation. The highest reaction rate constant of 3.132 x 10-2 min⁻¹ was observed for N, Pd co-doped TiO₂ (2% Pd). The results demonstrated that the N, Pd co-doped TiO₂ (2% Pd) sample could completely degrade the dye in 3 h, while the commercial TiO₂ showed the lowest dye degradation efficiency (52.66%).

Keywords: brilliant black, Co-doped TiO₂, polyamidoamine generation 1 (PAMAM G1), photodegradation

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Authors: I. Asanuma, T. Yamaguchi, J. Park, K. J. Mackin

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Fishery lights on the surface could be detected by the Day and Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (Suomi-NPP). The DNB covers the spectral range of 500 to 900 nm and realized a higher sensitivity. The DNB has a difficulty of identification of fishing lights from lunar lights reflected by clouds, which affects observations for the half of the month. Fishery lights and lights of the surface are identified from lunar lights reflected by clouds by a method using the DNB and the infrared band, where the detection limits are defined as a function of the brightness temperature with a difference from the maximum temperature for each level of DNB radiance and with the contrast of DNB radiance against the background radiance. Fishery boats or structures on islands could be detected by the Synthetic Aperture Radar (SAR) on the polar orbit satellites using the reflected microwave by the surface reflecting targets. The SAR has a difficulty of tradeoff between spatial resolution and coverage while detecting the small targets like fishery boats. A distribution of fishery boats and island activities were detected by the scan-SAR narrow mode of Radarsat-2, which covers 300 km by 300 km with various combinations of polarizations. The fishing boats were detected as a single pixel of highly scattering targets with the scan-SAR narrow mode of which spatial resolution is 30 m. As the look angle dependent scattering signals exhibits the significant differences, the standard deviations of scattered signals for each look angles were taken into account as a threshold to identify the signal from fishing boats and structures on the island from background noise. It was difficult to validate the detected targets by DNB with SAR data because of time lag of observations for 6 hours between midnight by DNB and morning or evening by SAR. The temporal changes of island activities were detected as a change of mean intensity of DNB for circular area for a certain scale of activities. The increase of DNB mean intensity was corresponding to the beginning of dredging and the change of intensity indicated the ending of reclamation and following constructions of facilities.

Keywords: day night band, SAR, fishery, South China Sea

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Authors: N. Tochukwu, M. Mukhopadhyay, A. Mohamed

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It is no new that Nigeria faces a continual power shortage problem due to its vast population power demand and heavy reliance on nonrenewable forms of energy such as thermal power or fossil fuel. Many researchers have recommended using geothermal energy as an alternative; however, Past studies focus on the geophysical & geochemical investigation of this energy in the sedimentary and basement complex; only a few studies incorporated the remote sensing methods. Therefore, in this study, the preliminary examination of geothermal resources in the Middle Benue was carried out using satellite imagery in ArcMap. Landsat 8 scene (TIR, NIR, Red spectral bands) was used to estimate the Land Surface Temperature (LST). The Maximum Likelihood Classification (MLC) technique was used to classify sites with very low, low, moderate, and high LST. The intermediate and high classification happens to be possible geothermal zones, and they occupy 49% of the study area (38077km2). Riverline were superimposed on the LST layer, and the identification tool was used to locate high temperate sites. Streams that overlap on the selected sites were regarded as geothermal springs as. Surprisingly, the LST results show lower temperatures (<36°C) at the famous thermal springs (Awe & Wukari) than some unknown rivers/streams found in Kwande (38°C), Ussa, (38°C), Gwer East (37°C), Yola Cross & Ogoja (36°C). Studies have revealed that temperature increases with depth. However, this result shows excellent geothermal resources potential as it is expected to exceed the minimum geothermal gradient of 25.47 with an increase in depth. Therefore, further investigation is required to estimate the depth of the causative body, geothermal gradients, and the sustainability of the reservoirs by geophysical and field exploration. This method has proven to be cost-effective in locating geothermal resources in the study area. Consequently, the same procedure is recommended to be applied in other regions of the Precambrian basement complex and the sedimentary basins in Nigeria to save a preliminary field survey cost.

Keywords: ArcMap, geothermal resources, Landsat 8, LST, thermal springs, MLC

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Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

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Authors: D. F. Zeynalov, T. V. Kartseva, O. V. Sorokin

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Currently, approaches to assess cardiointervalography are based on the calculation of data variance intervals RR. However, they do not allow the evaluation of features related to a period of the cardiac cycle, so how electromechanical phenomena during cardiac subphase are characterized by differently directed changes. Therefore, we have proposed a method of subphase analysis of the cardiac cycle, developed in the department of hominal physiology Novosibirsk State Medical University to identify the features of the dispersion subphase of the cardiac cycle. In the present paper we have examined the 5-minute intervals cardiointervalography (CIG) to isolate RR-, QT-, ST-ranges in healthy children and children with acute respiratory diseases (ARD) in comparison. It is known that primary school-aged children suffer at ARD 5-7 times per year. Consequently, it is one of the most relevant problems in pediatrics. It is known that the spectral indices and indices of temporal analysis of heart rate variability are highly sensitive to the degree of intoxication during immunological process. We believe that the use of subphase analysis of heart rate will allow more thoroughly evaluate responsiveness of the child organism during the course of ARD. The study involved 60 primary school-aged children (30 boys and 30 girls). In order to assess heart rhythm regulation, the record CIG was used on the "VNS-Micro" device of Neurosoft Company (Ivanovo) for 5 minutes in the supine position and 5 minutes during active orthostatic test. Subphase analysis of variance QT-interval and ST-segment was performed on the "KardioBOS" software Biokvant Company (Novosibirsk). In assessing the CIG in the supine position and in during orthostasis of children with acute respiratory diseases only RR-intervals are observed typical trend of general biological reactions through pressosensitive compensation mechanisms to lower blood pressure, but compared with healthy children the severity of the changes is different, of sick children are more pronounced indicators of heart rate regulation. But analysis CIG RR-intervals and analysis subphase ST-segment have yielded conflicting trends, which may be explained by the different nature of the intra- and extracardiac influences on regulatory mechanisms that implement the various phases of the cardiac cycle.

Keywords: acute respiratory diseases, cardiointervalography, subphase analysis, cardiac cycle

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Authors: Anusha P. Wijesundara, Dulap I. Rathnayake, Nihal D. Perera

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Bathymetric information is fundamental importance to coastal and marine planning and management, nautical navigation, and scientific studies of marine environments. Satellite-derived bathymetry data provide detailed information in areas where conventional sounding data is lacking and conventional surveys are inaccessible. The two empirical approaches of log-linear bathymetric inversion model and non-linear bathymetric inversion model are applied for deriving bathymetry from high-resolution multispectral satellite imagery. This study compares these two approaches by means of geographical error analysis for the site Kankesanturai using WorldView-2 satellite imagery. Based on the Levenberg-Marquardt method calibrated the parameters of non-linear inversion model and the multiple-linear regression model was applied to calibrate the log-linear inversion model. In order to calibrate both models, Single Beam Echo Sounding (SBES) data in this study area were used as reference points. Residuals were calculated as the difference between the derived depth values and the validation echo sounder bathymetry data and the geographical distribution of model residuals was mapped. The spatial autocorrelation was calculated by comparing the performance of the bathymetric models and the results showing the geographic errors for both models. A spatial error model was constructed from the initial bathymetry estimates and the estimates of autocorrelation. This spatial error model is used to generate more reliable estimates of bathymetry by quantifying autocorrelation of model error and incorporating this into an improved regression model. Log-linear model (R²=0.846) performs better than the non- linear model (R²=0.692). Finally, the spatial error models improved bathymetric estimates derived from linear and non-linear models up to R²=0.854 and R²=0.704 respectively. The Root Mean Square Error (RMSE) was calculated for all reference points in various depth ranges. The magnitude of the prediction error increases with depth for both the log-linear and the non-linear inversion models. Overall RMSE for log-linear and the non-linear inversion models were ±1.532 m and ±2.089 m, respectively.

Keywords: log-linear model, multi spectral, residuals, spatial error model

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Authors: Mingyan Hong, Shuozhao Hou

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Collaborative Strategic Learning (CSL) teaches students to use learning strategies while working cooperatively. Student strategies include the following steps: defining the learning task and purpose; conducting ongoing negotiation of the learning materials by deciding "click" (I get it and I can teach it – green card, I get it –yellow card) or "clunk" (I don't get it – red card) at the end of each learning unit; "getting the gist" of the most important parts of the learning materials; and "wrapping up" key ideas. Find out how to help students of mixed achievement levels apply learning strategies while learning content area in materials in small groups. The design of CSL is based on social-constructivism and Vygotsky’s best-known concept of the Zone of Proximal Development (ZPD). The definition of ZPD is the distance between the actual acquisition level as decided by individual problem solution case and the level of potential acquisition level, similar to Krashen (1980)’s i+1, as decided through the problem-solution case under the facilitator’s guidance, or in group work with other more capable members (Vygotsky, 1978). Vygotsky claimed that learners’ ideal learning environment is in the ZPD. An ideal teacher or more-knowledgable-other (MKO) should be able to recognize a learner’s ZPD and facilitates them to develop beyond it. Then the MKO is able to leave the support step by step until the learner can perform the task without aid. Steven Krashen (1980) proposed Input hypothesis including i+1 hypothesis. The input hypothesis models are the application of ZPD in second language acquisition and have been widely recognized until today. Krashen (2019)’s optimal language learning environment (2019) further developed the application of ZPD and added the component of strategic group learning. The strategic group learning is composed of desirable learning materials learners are motivated to learn and desirable group members who are more capable and are therefore able to offer meaningful input to the learners. Purpose-driven Collaborative Strategic Learning Model is a strategic integration of ZPD, i+1 hypothesis model, and Optimal Language Learning Environment Model. It is purpose driven to ensure group members are motivated. It is collaborative so that an optimal learning environment where meaningful input from meaningful conversation can be generated. It is strategic because facilitators in the model strategically assign each member a meaningful and collaborative role, e.g., team leader, technician, problem solver, appraiser, offer group learning instrument so that the learning process is structured, and integrate group learning and team building making sure holistic development of each participant. Using data collected from college year one and year two students’ English courses, this presentation will demonstrate how purpose-driven collaborative strategic learning model is implemented in the second/foreign language classroom, using the qualitative data from questionnaire and interview. Particular, this presentation will show how second/foreign language learners grow from functioning with facilitator or more capable peer’s aid to performing without aid. The implication of this research is that purpose-driven collaborative strategic learning model can be used not only in language learning, but also in any subject area.

Keywords: collaborative, strategic, optimal input, second language acquisition

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Authors: Fang Liu, JunShuai Xue, JiaJia Yao, GuanLin Wu, ZuMaoLi, XueYan Yang, HePeng Zhang, ZhiPeng Sun

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Terahertz spectra is in great demand since last two decades for many photonic and electronic applications. III-Nitride resonant tunneling diode is one of the promising candidates for portable and compact THz sources. Room temperature microwave oscillator based on GaN/AlN resonant tunneling diode was reported in this work. The devices, grown by plasma-assisted molecular-beam epitaxy on free-standing c-plane GaN substrates, exhibit highly repeatable and robust negative differential resistance (NDR) characteristics at room temperature. To improve the interface quality at the active region in RTD, indium surfactant assisted growth is adopted to enhance the surface mobility of metal atoms on growing film front. Thanks to the lowered valley current associated with the suppression of threading dislocation scattering on low dislocation GaN substrate, a positive peak current density of record-high 2.1 MA/cm2 in conjunction with a peak-to-valley current ratio (PVCR) of 1.2 are obtained, which is the best results reported in nitride-based RTDs up to now considering the peak current density and PVCR values simultaneously. When biased within the NDR region, microwave oscillations are measured with a fundamental frequency of 0.31 GHz, yielding an output power of 5.37 µW. Impedance mismatch results in the limited output power and oscillation frequency described above. The actual measured intrinsic capacitance is only 30fF. Using a small-signal equivalent circuit model, the maximum intrinsic frequency of oscillation for these diodes is estimated to be ~260GHz. This work demonstrates a microwave oscillator based on resonant tunneling effect, which can meet the demands of terahertz spectral devices, more importantly providing guidance for the fabrication of the complex nitride terahertz and quantum effect devices.

Keywords: GaN resonant tunneling diode, peak current density, microwave oscillation, intrinsic capacitance

Procedia PDF Downloads 107