bluuebunny/crossref_metadata_2025 huggingface dataset:
Numerical Study on Hydrodynamics of Ships with Forward Speed Based on Nonlinear Steady Wave
Authors: Mei Tianlong , Candries Maxim , Lataire Evert , Zou Zaojian
Published: February 2020

In this paper, an improved potential flow model is proposed for the hydrodynamic analysis of ships advancing in waves. A desingularized Rankine panel method, which has been improved with the added effect of nonlinear steady wave-making (NSWM) flow in frequency domain, is employed for 3D diffraction and radiation problems. Non-uniform rational B-splines (NURBS) are used to describe the body and free surfaces. The NSWM potential is computed by linear superposition of the first-order and second-order steady wave-making potentials which are determined by solving the corresponding boundary value problems (BVPs). The so-called mj terms in the body boundary condition of the radiation problem are evaluated with nonlinear steady flow. The free surface boundary conditions in the diffraction and radiation problems are also derived by considering nonlinear steady flow. To verify the improved model and the numerical method adopted in the present study, the nonlinear wave-making problem of a submerged moving sphere is first studied, and the computed results are compared with the analytical results of linear steady flow. Subsequently, the diffraction and radiation problems of a submerged moving sphere and a modified Wigley hull are solved. The numerical results of the wave exciting forces, added masses, and damping coefficients are compared with those obtained by using Neumann–Kelvin (NK) flow and double-body (DB) flow. A comparison of the results indicates that the improved model using the NSWM flow can generally give results in better agreement with the test data and other published results than those by using NK and DB flows, especially for the hydrodynamic coefficients in relatively low frequency ranges.
Numerical Analysis of NOx Reduction Using Ammonia Injection and Comparison with Water Injection
Authors: Lamas Galdo María Isabel , Castro-Santos Laura , Rodriguez Vidal Carlos G.
Published: February 2020

This work analyzes NOx reduction in a marine diesel engine using ammonia injection directly into the cylinder and compares this procedure with water injection. A numerical model based on the so-called inert species method was applied. It was verified that ammonia injection can provide almost 80% NOx reduction for the conditions analyzed. Furthermore, it was found that the effectiveness of the chemical effect using ammonia is extremely dependent on the injection timing. The optimum NOx reduction was obtained when ammonia is injected during the expansion stroke, while the optimum injection timing using water is near top dead center. Chemical, thermal, and dilution effects of both ammonia and water injection were compared. The chemical effect was dominant in the case of ammonia injection. On the other hand, water injection reduces NOx through dilution and, more significantly, through a thermal effect.
Pricing Defaulted Italian Mortgages
Authors: Pelizza Michela , Schenk-Hoppé Klaus R.
Published: February 2020

Our paper forecasts the expected recovery rates of defaulted Italian mortgage loans backed by either residential or commercial real estate. We apply an exponential Ornstein–Uhlenbeck process to model the price dynamics at the provincial and regional level, and two haircut models to estimate the liquidation value. Compared to our findings, rating agencies such as Moody’s, which use geometric Brownian motion to model the price dynamics, paint a rosier picture with higher recovery rates. As a consequence, non-performing mortgage loans held by Italian banks might be overvalued.
Extreme Values and Financial Risk
Authors: Chan Stephen , Nadarajah Saralees
Published: February 2020

Since the 2008 financial crisis, modelling of the extreme values of financial risk has become important [...]
Vanadium-Substituted Phosphomolybdic Acids for the Aerobic Cleavage of Lignin Models—Mechanistic Aspect and Extension to Lignin
Authors: Al-Hussaini Louay , Launay Franck , Galvez Elena
Published: February 2020

This work deals with the aerobic oxidative cleavage of C-C and C-O bonds catalyzed by the Keggin-type phosphovanadomolybdic acid (H6[PMo9V3O40], noted H6PV3). The latter was synthesized by an adapted hydrothermal procedure classically used for lower vanadium content and was tested as a catalyst for the aerobic cleavage of 2-phenoxyacetophenone (noted K1HH) and 1-phenyl-2-phenoxyethanol (A1HH) used as two lignin models. The operative conditions (solvent, catalytic loading, etc.) were adjusted on K1HH and extrapolated to A1HH. The cleavage of the alcohol model required more drastic conditions and therefore further optimization. Preliminary attempts on an Organosolv wheat straw lignin were performed too. From the kinetic study, high performance liquid chromatography (HPLC) and gas chromatography–mass spectrometry (GC-MS) data, a mechanism of the cleavage of both models was proposed.
New Framework for Quality Function Deployment Using Linguistic Z-Numbers
Authors: Song Chao , Wang Jian-Qiang , Li Jun-Bo
Published: February 2020

Quality function deployment (QFD) is a useful design quality control tool in service enterprises and manufacturing enterprises. However, there are several issues in extant QFD frameworks, that is, in three aspects: description of evaluation information, weight determination of expert team members (TMs), and weight identification of customer requirements (CRs). In order to address these issues, a novel QFD framework is first proposed utilizing linguistic Z-numbers (LZNs) with integrated subjective and objective weights of TMs and CRs. The LZNs can represent uncertain information and the reliability of information in a specific way while the fuzzy numbers cannot. Moreover, the order relation analysis (G1) method and improved maximum consensus (MC) method are developed to get the subjective and objective weights of TMs, respectively. Further, the step-wise weight assessment ratio analysis (SWARA) method and statistical distance (SD) method are studied to acquire combined weights of CRs. Next, the proposed QFD framework is applied to a case of logistics service provider, which illustrates the availability and utility of the framework. Then, a sensitivity analysis is conducted to prove the reliability of the framework. Finally, two comparative analyses are performed to declare the advantages of the framework. Results indicate the proposed QFD framework is better than existing models.
Impulsive Stability of Stochastic Functional Differential Systems Driven by G-Brownian Motion
Authors: Pan Lijun , Cao Jinde , Ren Yong
Published: February 2020

This paper is concerned with the p-th moment exponential stability and quasi sure exponential stability of impulsive stochastic functional differential systems driven by G-Brownian motion (IGSFDSs). By using G-Lyapunov method, several stability theorems of IGSFDSs are obtained. These new results are employed to impulsive stochastic delayed differential systems driven by G-motion (IGSDDEs). In addition, delay-dependent method is developed to investigate the stability of IGSDDSs by constructing the G-Lyapunov–Krasovkii functional. Finally, an example is given to demonstrate the effectiveness of the obtained results.
Comparing Groups of Decision-Making Units in Efficiency Based on Semiparametric Regression
Authors: Noh Hohsuk , Yang Seong J.
Published: February 2020

We consider a stochastic frontier model in which a deviation of output from the production frontier consists of two components, a one-sided technical inefficiency and a two-sided random noise. In such a situation, we develop a semiparametric regression-based test and compare the technical efficiencies of the different decision-making unit groups, assuming that the production frontier function is the same for all the groups. Our test performs better than the previously proposed ones for the same purpose in numerical studies, and also has the theoretical advantage of working under more general assumptions. To illustrate our method, we apply the proposed test to Program for International Student Assessment (PISA) 2015 data and investigate whether an efficiency difference exists between male and female student groups at a specific age in terms of learning time and achievement in mathematics.
Floridoside Exhibits Antioxidant Properties by Activating HO-1 Expression via p38/ERK MAPK Pathway
Authors: Niu Tingting , Fu Gaoqing , Zhou Jiawei , Han Hui , Chen Juanjuan , Wu Wei , Chen Haimin
Published: February 2020

Floridoside is a low-molecular-weight organic compound, which can be accumulated by red algae under stressful conditions to protect cells via its excellent antioxidant properties. In the present study, we investigated the antioxidant mechanism of floridoside toward human hepatocyte L-02 cells. We found that floridoside had no toxicity to L-02 cells, and no reactive oxidative species were induced by it either. However, the expression of hemoxygenase-1 (HO-1) protein was up-regulated upon exposure to floridoside, and two antioxidant enzymes, superoxide dismutase (SOD) and GSH-Px, were activated by floridoside. Moreover, we investigated the pathway involved in the production of these antioxidants, p38/extracellular signal-regulated kinase (ERK) MAPK-nuclear factor-erythroid-2-related factor 2 (Nrf2) pathway. ERK1/2 and p38 phosphorylation, nuclear translocation of Nrf2, and activation of ARE luciferase activity were observed upon exposure to floridoside. siRNA interference and inhibitor treatment suppressed the HO-1 expression and the phosphorylation of ERK1/2 and p38, respectively. These results indicated that floridoside exerted its antioxidant activity by activating HO-1 expression via p38/ERK MAPK-Nrf2 pathway in human hepatocyte L-02 cells.
Use of Lactic Acid Bacteria During Pikeperch (Sander lucioperca) Larval Rearing
Authors: Yanes-Roca Carlos , Leclercq Eric , Vesely Lukas , Malinovskyi Oleksandr , Policar Tomas
Published: February 2020

This trial tested the use of lactic acid bacteria (LAB) on pikeperch (Sander lucioperca) larvae during their first feeding. The trial included the use of two probiotic treatments and one control (no probiotics). Pikeperch larvae were exposed to LAB as follows: (1) the live feed (Treatment 1, live feed) or (2) via the live feed and the larval rearing water (Treatment 2, probiotic). Significant differences were found between the treatments in terms of total length (TL), myomere height (MH), overall survival, and the tolerance to a high salinity challenge. Larvae exposed to LAB via both the live feed and the rearing water had a significantly higher overall survival rate (85%) than the other two treatments at 21 dph. When both treatments were subjected to high salinity rates (18 parts per thousand (ppt)), both treatments exposed to LAB demonstrated higher survival rates than the control treatment (28% and 40% survival rate at 180 min for the live feed and probiotic treatments, respectively, as compared with a 100% mortality rate at 150 min for the control). At the same time, larvae exposed to the probiotic treatment had a significantly higher TL as compared to the control after 12 and 21 days post hatch (dph) (probiotic 7.13 ± 0.21 and 11.71 ± 1.1 mm, control 5.86 and 10.79 mm at 12 and 21 dph, respectively). The results suggest that the use of LAB in both the live feed and the rearing water has a positive effect on pikeperch larval quality by strengthening their resilience to stress conditions, as well as improving the growth and survival rates.
Interactions between Kazachstania humilis Yeast Species and Lactic Acid Bacteria in Sourdough
Authors: Carbonetto Belén , Nidelet Thibault , Guezenec Stéphane , Perez Marc , Segond Diego , Sicard Delphine
Published: February 2020

Sourdoughs harbor simple microbial communities usually composed of a few prevailing lactic acid bacteria species (LAB) and yeast species. However, yeast and LAB found in sourdough have been described as highly diverse. Even if LAB and yeast associations have been widely documented, the nature of the interactions between them has been poorly described. These interactions define the composition and structure of sourdough communities, and therefore, the characteristics of the final bread product. In this study, the nature of the interactions between strains of two commonly found sourdough yeast species, Kazachstania humilis and Saccharomyces cerevisiae, and lactic acid bacteria isolated from sourdoughs has been analyzed. Population density analysis showed no evidence of positive interactions, but instead revealed neutral or negative asymmetric interaction outcomes. When in coculture, the yeasts´ population size decreased in the presence of LAB regardless of the strain, while the LAB´s population size was rarely influenced by the presence of yeasts. However, a higher maltose depletion was shown in maltose-negative K. humilis and maltose-positive obligately heterofermentative LAB cocultures compared to monocultures. In addition, tested pairs of obligately heterofermentative LAB and K. humilis strains leavened dough as much as couples of LAB and S. cerevisiae strains, while K. humilis strains never leavened dough as much as S. cerevisiae when in monoculture. Taken together, our results demonstrate that even if higher fermentation levels with increased maltose depletion were detected for K. humilis and obligately heterofermentative LAB pairs, these interactions cannot be ecologically classified as positive, leading us to rethink the established hypothesis of coexistence by facilitation in sourdoughs.
Preparation of Aluminosilicate Ferrierite Zeolite Nanosheets with Controllable Thickness in the Presence of a Sole Organic Structure Directing Agent
Authors: Xu Hao , Yu YuXia , Zhu LongFeng , Bian ChaoQun , Zhai HangLing , Tong JianYing , Wu HuiZhen , Shen Chao
Published: February 2020

Preparation of aluminosilicate ferrierite (FER) zeolite nanosheets with controllable thickness in the presence of a sole organic ammonium is attractive, but still challenging. In this report, with the employment of N,N-diethyl-cis-2,6-dimethylpiperidinium (DMP) as both a structure directing agent and crystal growth inhibitor, aluminosilicate FER zeolite nanosheets, with a variety of crystal thicknesses, ranging from 6 to 200 nm, are successfully synthesized under hydrothermal conditions. Very interestingly, the amount of DMP in the starting gel is the key factor for crystal thickness control of aluminosilicate FER zeolite nanosheets. The obtained FER products, with different thicknesses, are well characterized by X-ray powder diffraction (XRD), scanning electron microscopy (SEM), N2 sorption, thermogravimetric analysis (TG), inductively coupled plasma (ICP), and magic angle spinning nuclear magnetic resonance (MAS NMR) techniques. This simple strategy might provide a novel avenue for the synthesis of other zeolite nanosheets with controllable thickness.
Multifunctional Stretchable Conductive Woven Fabric Containing Metal Wire with Durable Structural Stability and Electromagnetic Shielding in the X-Band
Authors: Wang Yong , Gordon Stuart , Baum Thomas , Xu Zhenzhen
Published: February 2020

Elastomeric, conductive composite yarns have recently received attention around the opportunity for them to offer special protective fields. A straightforward approach for fabricating tri-component elastic-conductive composite yarns (t-ECCYs) containing stainless steel wire (SSW) was proposed previously. This work mainly focuses on the electromagnetic shielding effectiveness (EMSE) of weft-stretchable woven fabric containing t-ECCY over the X-band under different testing conditions, e.g., single step-by-step elongation, cyclic stretch and lamination events. Results showed that a woven cotton fabric with weft yarn of t-ECCY not only exhibited superior weft stretch-ability to a higher elongation (>40%) compared with a pure cotton control but also had an acceptable 15-cyclic stability with 80% shape recovery retention. The t-ECCY weft fabric was effective in shielding electromagnetic radiation, and its EMSE was also enhanced at elevated elongations during stretch at parallel polarization of EM waves. There was also no decay in EMSE before and after the t-ECCY fabric was subject to 15 stretch cycles at extension of 20%. In addition, a 90° by 90° cross lamination of t-ECCY fabric remarkably improved the EMSE compared to a 0°/90° one. The scalable fabrication strategy and excellent EMSE seen in t-ECCY-incorporated fabrics represent a significant step forward in protective fields.
Application of Eco-Friendly Waterborne Polyurethane Composite Coating Incorporated with Nano Cellulose Crystalline and Silver Nano Particles on Wood Antibacterial Board
Authors: Cheng Liangsong , Ren Shaobo , Lu Xiaoning
Published: February 2020

To endow wood plate with antimicrobial properties, waterborne polyurethane (WPU) coatings incorporated with nano cellulose crystalline (NCC) and silver nanoparticles (AgNPs) were prepared. AgNPs were obtained by the chemical reactions of silver nitrate solution and sodium borohydride solution. The scribe testing results showed that the adhesion of the NCC-WPU composites was improved with the addition of NCC. The adhesion reached its peak when the amount of NCC added was 1%. Scanning electron microscopy (SEM) observation displayed that the NCC dispersed into the WPU without aggregation. NCC was well able to bind WPU and wood cell walls tightly together. Atomic force microscopy (AFM) and ultraviolet-visible (UV-vis) results revealed that WPU/NCC/AgNPs composites were homogeneous. This compatibility was also confirmed by transmission electron microscopy (TEM) analysis. The antibacterial property was improved too. When the adding amount of NCC was 0.5%, and the proportion of silver elements added was 5%, the antibacterial effect was at its best. As a comparison, the antibacterial effect of hybrid colloid without the addition of NCC was far less than that of including NCC. The WPU/NCC/AgNPs composite could be applied as an antibacterial coating in wood materials.
Stochastic Mortality Modelling for Dependent Coupled Lives
Authors: Henshaw Kira , Constantinescu Corina , Menoukeu Pamen Olivier
Published: February 2020

Broken-heart syndrome is the most common form of short-term dependence, inducing a temporary increase in an individual’s force of mortality upon the occurrence of extreme events, such as the loss of a spouse. Socioeconomic influences on bereavement processes allow for suggestion of variability in the significance of short-term dependence between couples in countries of differing levels of economic development. Motivated by analysis of a Ghanaian data set, we propose a stochastic mortality model of the joint mortality of paired lives and the causal relation between their death times, in a less economically developed country than those considered in existing studies. The paired mortality intensities are assumed to be non-mean-reverting Cox–Ingersoll–Ross processes, reflecting the reduced concentration of the initial loss impact apparent in the data set. The effect of the death on the mortality intensity of the surviving spouse is given by a mean-reverting Ornstein–Uhlenbeck process which captures the subsiding nature of the mortality increase characteristic of broken-heart syndrome. Inclusion of a population wide volatility parameter in the Ornstein–Uhlenbeck bereavement process gives rise to a significant non-diversifiable risk, heightening the importance of the dependence assumption in this case. Applying the model proposed to an insurance pricing problem, we obtain the appropriate premium under consideration of dependence between coupled lives through application of the indifference pricing principle.
Hy-Bridge: A Hybrid Blockchain for Privacy-Preserving and Trustful Energy Transactions in Internet-of-Things Platforms
Authors: Daghmehchi Firoozjaei Mahdi , Ghorbani Ali , Kim Hyoungshick , Song JaeSeung
Published: February 2020

In the current centralized IoT ecosystems, all financial transactions are routed through IoT platform providers. The security and privacy issues are inevitable with an untrusted or compromised IoT platform provider. To address these issues, we propose Hy-Bridge, a hybrid blockchain-based billing and charging framework. In Hy-Bridge, the IoT platform provider plays no proxy role, and IoT users can securely and efficiently share a credit with other users. The trustful end-to-end functionality of blockchain helps us to provide accountability and reliability features in IoT transactions. Furthermore, with the blockchain-distributed consensus, we provide a credit-sharing feature for IoT users in the energy and utility market. To provide this feature, we introduce a local block framework for service management in the credit-sharing group. To preserve the IoT users’ privacy and avoid any information leakage to the main blockchain, an interconnection position, called bridge, is introduced to isolate IoT users’ peer-to-peer transactions and link the main blockchain to its subnetwork blockchain(s) in a hybrid model. To this end, a k-anonymity protection is performed on the bridge. To evaluate the performance of the introduced hybrid blockchain-based billing and charging, we simulated the energy use case scenario using Hy-Bridge. Our simulation results show that Hy-Bridge could protect user privacy with an acceptable level of information loss and CPU and memory usage.
FDD Channel Estimation Via Covariance Estimation in Wideband Massive MIMO Systems
Authors: González-Coma José P. , Suárez-Casal Pedro , Castro Paula M. , Castedo Luis
Published: February 2020

A method for channel estimation in wideband massive Multiple-Input Multiple-Output systems using hybrid digital analog architectures is developed. The proposed method is useful for Frequency-Division Duplex at either sub-6 GHz or millimeter wave frequency bands and takes into account the beam squint effect caused by the large bandwidth of the signals. To circumvent the estimation of large channel vectors, the posed algorithm relies on the slow time variation of the channel spatial covariance matrix, thus allowing for the utilization of very short training sequences. This is possibledue to the exploitation of the channel structure. After identifying the channel covariance matrix, the channel is estimated on the basis of the recovered information. To that end, we propose a novel method that relies on estimating the tap delays and the gains as sociated with each path. As a consequence, the proposed channel estimator achieves low computational complexity and significantly reduces the training overhead. Moreover, our numerical simulations show better performance results compared to the minimum mean-squared error solution.
On the Achievable Capacity of MIMO-OFDM Systems in the CathLab Environment
Authors: Guerreiro João , Dinis Rui , Campos Luís
Published: February 2020

In the last years, the evolution of digital communications has been harnessed by medical applications. In that context, wireless communications are preferable over wired communications, as they facilitate the work of health technicians by reducing cabling on the stretchers. However, the use of wireless communications is challenging, especially when high data rates and low latencies are required. In those scenarios, multiple-input multiple-output (MIMO) techniques might have an important role, thanks to the high capacity gains that they can exhibit, which ideally increase with the MIMO size. In this work, we study the propagation scenario of a typical medical laboratory through ray-tracing techniques. By taking into account the derived channel model, we study the potential of MIMO techniques in an IEEE 802.11ax environment. Through a set of performance results regarding the system capacity, we show that the MIMO gains might not be as high as supposed in the medical laboratory, being far from the ideal scenario. Therefore, the large data rates required by the modern medical imaging applications might only be achieved with a combination of MIMO systems and large bandwidths.
Novel Metamaterials-Based Hypersensitized Liquid Sensor Integrating Omega-Shaped Resonator with Microstrip Transmission Line
Authors: Abdulkarim Yadgar , Deng Lianwen , Karaaslan Muharrem , Altıntaş Olcay , Awl Halgurd , Muhammadsharif Fahmi , Liao Congwei , Unal Emin , Luo Heng
Published: February 2020

In this paper, a new metamaterials-based hypersensitized liquid sensor integrating omega-shaped resonator with microstrip transmission line is proposed. Microwave transmission responses to industrial energy-based liquids are investigated intensively from both numerical and experimental point of view. Simulation results concerning three-dimensional electromagnetic fields have shown that the transmission coefficient of the resonator could be monitored by the magnetic coupling between the transmission line and omega resonator. This sensor structure has been examined by methanol–water and ethanol–water mixtures. Moreover, the designed sensor is demonstrated to be very sensitive for identifying clean and waste transformer oils. A linear response characteristic of shifting the resonance frequency upon the increment of chemical contents/concentrations or changing the oil condition is observed. In addition to the high agreement of transmission coefficients (S21) between simulations and experiments, obvious resonant-frequency shift of transmission spectrum is recognized for typical pure chemical liquids (i.e., PEG 300, isopropyl alcohol, PEG1500, ammonia, and water), giving rise to identify the type and concentration of the chemical liquids. The novelty of the work is to utilize Q factor and minimum value of S21 as sensing agent in the proposed structure, which are seen to be well compatible at different frequencies ranging from 1–20 GHz. This metamaterial integrated transmission line-based sensor is considered to be promising candidate for precise detection of fluidics and for applications in the field of medicine and chemistry.
Human Fall Detection Based on Body Posture Spatio-Temporal Evolution
Authors: Zhang Jin , Wu Cheng , Wang Yiming
Published: February 2020

Abnormal falls in public places have significant safety hazards and can easily lead to serious consequences, such as trampling by people. Vision-driven fall event detection has the huge advantage of being non-invasive. However, in actual scenes, the fall behavior is rich in diversity, resulting in strong instability in detection. Based on the study of the stability of human body dynamics, the article proposes a new model of human posture representation of fall behavior, called the “five-point inverted pendulum model”, and uses an improved two-branch multi-stage convolutional neural network (M-CNN) to extract and construct the inverted pendulum structure of human posture in real-world complex scenes. Furthermore, we consider the continuity of the fall event in time series, use multimedia analytics to observe the time series changes of human inverted pendulum structure, and construct a spatio-temporal evolution map of human posture movement. Finally, based on the integrated results of computer vision and multimedia analytics, we reveal the visual characteristics of the spatio-temporal evolution of human posture under the potentially unstable state, and explore two key features of human fall behavior: motion rotational energy and generalized force of motion. The experimental results in actual scenes show that the method has strong robustness, wide universality, and high detection accuracy.
In-Field Calibration of Triaxial Accelerometer Based on Beetle Swarm Antenna Search Algorithm
Authors: Wang Pengfei , Gao Yanbin , Wu Menghao , Zhang Fan , Li Guangchun
Published: February 2020

Traditional calibration method is usually performed with expensive equipments such as three-axis turntable in a laboratory environment. However in practice, in order to ensure the accuracy and stability of the inertial navigation system (INS), it is usually necessary to recalibrate the inertial measurement unit (IMU) without external equipment in the field. In this paper, a new in-field recalibration method for triaxial accelerometer based on beetle swarm antenna search (BSAS) algorithm is proposed. Firstly, as a new intelligent optimization algorithm, BSAS algorithm and its improvements based on basic beetle antennae search (BAS) algorithm are introduced in detail. Secondly, the nonlinear mathematical model of triaxial accelerometer is established for higher calibration accuracy, and then 24 optimal measurement positions are designed by theoretical analysis. In addition, the calibration procedures are improved according to the characteristics of BSAS algorithm, then 15 calibration parameters in the nonlinear method are optimized by BSAS algorithm. Besides, the results of BSAS algorithm and basic BAS algorithm are compared by simulation, which shows the priority of BSAS algorithm in calibration field. Finally, two experiments demonstrate that the proposed method can achieve high precision in-field calibration without any external equipment, and meet the accuracy requirements of the INS.
Dynamic Modelling and Experimental Characterization of a Self-Powered Structural Health-Monitoring System with MFC Piezoelectric Patches
Authors: Di Rito Gianpietro , Chiarelli Mario Rosario , Luciano Benedetto
Published: February 2020

The paper deals with theoretical and experimental studies for the development of a self-powered structural health monitoring (SHM) system using macro-fiber composite (MFC) patches. The basic idea is to integrate the actuation, sensing, and energy harvesting capabilities of the MFC patches in a SHM system operating in different regimes. As an example, during flight, under the effects of normal structural vibrations, the patches can work as energy harvesters by maintaining or restoring the battery charge of the stand-by SHM electronic board; on the other hand, if relevant/abnormal loadings are applied, or if local faults produce a noticeable stiffness variation of the monitored component, the patches can act as sensors for the power-up SHM board. During maintenance, the patches can then work as actuators, to stress the structure with pre-defined load profiles, as well as sensors, to monitor the structural response. In this paper, the investigation, based on the electromechanical impedance technique, is carried out on a system prototype made of a cantilevered composite laminate with six MFC patches. A high-fidelity nonlinear model of the system, including the piezoelectric hysteresis of the patches and three vibration modes of the laminate beam, is presented and validated with experiments. The results support the potential feasibility of the system, pointing out that the energy storage can be used for recharging a 3V-65mAh Li-ion battery, suitable for low-power electronic boards. The model is finally used to characterize a condition-monitoring algorithm in terms of false alarms rejection and vulnerability to dormant faults, by simulating built-in tests to be performed during maintenance.
Performance Analysis of Direct GPS Spoofing Detection Method with AHRS/Accelerometer
Authors: Kwon Keum-Cheol , Shim Duk-Sun
Published: February 2020

The global positioning system (GPS) is an essential technology that provides positioning capabilities and is used in various applications such as navigation, surveying, mapping, robot simultaneous localization and mapping (SLAM), location-based service (LBS), etc. However, the GPS is known to be vulnerable to intentional attacks such as spoofing because of its simple signal structure. In this study, a direct method is proposed for GPS spoofing detection, using Attitude and Heading Reference System (AHRS) accelerometer and analyzing the detection performance with corresponding probability density functions (PDFs). The difference in the acceleration between the GPS receiver and the accelerometer is used to detect spoofing. The magnitude of the acceleration error may be used as a decision variable. Additionally, using the magnitude of the north (or east) component of the acceleration error as another decision variable is proposed, which shows better performance in some conditions. The performance of the two decision variables is compared by calculating the probability of spoofing detection and the detectable minimum spoofing acceleration (DMSA), given a pre-defined false alarm probability and a pre-defined detection probability. It turns out that both decision variables need to be used together to obtain the best spoofing detection performance.
Spatial Attention Fusion for Obstacle Detection Using MmWave Radar and Vision Sensor
Authors: Chang Shuo , Zhang Yifan , Zhang Fan , Zhao Xiaotong , Huang Sai , Feng Zhiyong , Wei Zhiqing
Published: February 2020

For autonomous driving, it is important to detect obstacles in all scales accurately for safety consideration. In this paper, we propose a new spatial attention fusion (SAF) method for obstacle detection using mmWave radar and vision sensor, where the sparsity of radar points are considered in the proposed SAF. The proposed fusion method can be embedded in the feature-extraction stage, which leverages the features of mmWave radar and vision sensor effectively. Based on the SAF, an attention weight matrix is generated to fuse the vision features, which is different from the concatenation fusion and element-wise add fusion. Moreover, the proposed SAF can be trained by an end-to-end manner incorporated with the recent deep learning object detection framework. In addition, we build a generation model, which converts radar points to radar images for neural network training. Numerical results suggest that the newly developed fusion method achieves superior performance in public benchmarking. In addition, the source code will be released in the GitHub.
Increase of Input Resistance of a Normal-Mode Helical Antenna (NMHA) in Human Body Application
Authors: Zainudin Norsiha , Abdul Latef Tarik , Aridas Narendra Kumar , Yamada Yoshihide , Kamardin Kamilia , Abd Rahman Nurul Huda
Published: February 2020

In recent years, the development of healthcare monitoring devices requires high performance and compact in-body sensor antennas. A normal-mode helical antenna (NMHA) is one of the most suitable candidates that meets the criteria, especially with the ability to achieve high efficiency when the antenna structure is in self-resonant mode. It was reported that when the antenna was placed in a human body, the antenna efficiency was decreased due to the increase of its input resistance (Rin). However, the reason for Rin increase was not clarified. In this paper, the increase of Rin is ensured through experiments and the physical reasons are validated through electromagnetic simulations. In the simulation, the Rin is calculated by placing the NMHA inside a human’s stomach, skin and fat. The dependency of Rin to conductivity (σ) is significant. Through current distribution calculation, it is verified that the reason of the increase in Rin is due to the decrease of antenna current. The effects of Rin to bandwidth (BW) and electrical field are also numerically clarified. Furthermore, by using the fabricated human body phantom, the measured Rin and bandwidth are also obtained. From the good agreement between the measured and simulated results, the condition of Rin increment is clarified.
An Optical Urate Biosensor Based on Urate Oxidase and Long-Lifetime Metalloporphyrins
Authors: Falohun Tokunbo , McShane Michael J.
Published: February 2020

Gout is a condition that affects over 8 million Americans. This condition is characterized by severe pain, and in more advanced cases, bone erosion and joint destruction. This study explores the fabrication and characterization of an optical, enzymatic urate biosensor for gout management, and the optimization of the biosensor response through the tuning of hydrogel matrix properties. Sensors were fabricated through the co-immobilization of oxygen-quenched phosphorescent probes with an oxidoreductase within a biocompatible copolymer hydrogel matrix. Characterization of the spectral properties and hydrogel swelling was conducted, as well as evaluation of the response sensitivity and long-term stability of the urate biosensor. The findings indicate that increased acrylamide concentration improved the biosensor response by yielding an increased sensitivity and reduced lower limit of detection. However, the repeatability and stability tests highlighted some possible areas of improvement, with a consistent response drift observed during repeatability testing and a reduction in response seen after long-term storage tests. Overall, this study demonstrates the potential of an on-demand, patient-friendly gout management tool, while paving the way for a future multi-analyte biosensor based on this sensing platform.
Matrix Effect in the Isolation of Breast Cancer-Derived Nanovesicles by Immunomagnetic Separation and Electrochemical Immunosensing—A Comparative Study
Authors: Lima Moura Silio , Martì Mercè , Pividori María Isabel
Published: February 2020

Exosomes are cell-derived nanovesicles released into biological fluids, which are involved in cell-to-cell communication. The analysis of the content and the surface of the exosomes allow conclusions about the cells they are originating from and the underlying condition, pathology or disease. Therefore, the exosomes are currently considered good candidates as biomarkers to improve the current methods for clinical diagnosis, including cancer. However, due to their low concentration, conventional procedures for exosome detection including biosensing usually require relatively large sample volumes and involve preliminary purification and preconcentration steps by ultracentrifugation. In this paper, the immunomagnetic separation is presented as an alternative method for the specific isolation of exosomes in serum. To achieve that, a rational study of the surface proteins in exosomes, which can be recognized by magnetic particles, is presented. The characterization was performed in exosomes obtained from cell culture supernatants of MCF7, MDA-MB-231 and SKBR3 breast cancer cell lines, including TEM and nanoparticle tracking analysis (NTA). For the specific characterization by flow cytometry and confocal microscopy, different commercial antibodies against selected receptors were used, including the general tetraspanins CD9, CD63 and CD81, and cancer-related receptors (CD24, CD44, CD54, CD326 and CD340). The effect of the serum matrix on the immunomagnetic separation was then carefully evaluated by spiking the exosomes in depleted human serum. Based on this study, the exosomes were preconcentrated by immunomagnetic separation on antiCD81-modified magnetic particles in order to achieve further magnetic actuation on the surface of the electrode for the electrochemical readout. The performance of this approach is discussed and compared with classical characterization methods.
Electrochemical Paper-Based Biosensor Devices for Rapid Detection of Biomarkers
Authors: Gutiérrez-Capitán Manuel , Baldi Antonio , Fernández-Sánchez César
Published: February 2020

In healthcare, new diagnostic tools that help in the diagnosis, prognosis, and monitoring of diseases rapidly and accurately are in high demand. For in-situ measurement of disease or infection biomarkers, point-of-care devices provide a dramatic speed advantage over conventional techniques, thus aiding clinicians in decision-making. During the last decade, paper-based analytical devices, combining paper substrates and electrochemical detection components, have emerged as important point-of-need diagnostic tools. This review highlights significant works on this topic over the last five years, from 2015 to 2019. The most relevant articles published in 2018 and 2019 are examined in detail, focusing on device fabrication techniques and materials applied to the production of paper fluidic and electrochemical cell architectures as well as on the final device assembly. Two main approaches were identified, that are, on one hand, those ones where the fabrication of the electrochemical cell is done on the paper substrate, where the fluidic structures are also defined, and, on the other hand, the fabrication of those ones where the electrochemical cell and liquid-driving paper component are defined on different substrates and then heterogeneously assembled. The main limitations of the current technologies are outlined and an outlook on the current technology status and future prospects is given.
Hydroacoustic System in a Biomimetic Underwater Vehicle to Avoid Collision with Vessels with Low-Speed Propellers in a Controlled Environment
Authors: Piskur Pawel , Szymak Piotr , Jaskólski Krzysztof , Flis Leszek , Gąsiorowski Marek
Published: February 2020

In this paper, a hydroacoustic system designed for a biomimetic underwater vehicle (BUV) is presented. The Biomimetic Underwater Vehicle No. 2 (BUV2) is a next-generation BUV built within the ambit of SABUVIS, a European Defense Agency project (category B). Our main efforts were devoted to designing the system so that it will avoid collisions with vessels with low-speed propellers, e.g., submarines. Verification measurements were taken in a lake using a propeller-driven pontoon with a spectrum similar to that produced by a submarine propulsion system. Here, we describe the hydroacoustic signal used, with careful consideration of the filter and method of estimation for the bearings of the moving obstacle. Two algorithms for passive obstacle detection were used, and the results are discussed herein.
Deep Learning in Physiological Signal Data: A Survey
Authors: Rim Beanbonyka , Sung Nak-Jun , Min Sedong , Hong Min
Published: February 2020

Deep Learning (DL), a successful promising approach for discriminative and generative tasks, has recently proved its high potential in 2D medical imaging analysis; however, physiological data in the form of 1D signals have yet to be beneficially exploited from this novel approach to fulfil the desired medical tasks. Therefore, in this paper we survey the latest scientific research on deep learning in physiological signal data such as electromyogram (EMG), electrocardiogram (ECG), electroencephalogram (EEG), and electrooculogram (EOG). We found 147 papers published between January 2018 and October 2019 inclusive from various journals and publishers. The objective of this paper is to conduct a detailed study to comprehend, categorize, and compare the key parameters of the deep-learning approaches that have been used in physiological signal analysis for various medical applications. The key parameters of deep-learning approach that we review are the input data type, deep-learning task, deep-learning model, training architecture, and dataset sources. Those are the main key parameters that affect system performance. We taxonomize the research works using deep-learning method in physiological signal analysis based on: (1) physiological signal data perspective, such as data modality and medical application; and (2) deep-learning concept perspective such as training architecture and dataset sources.
Anti-p53 Autoantibody Detection in Automatic Glass Capillary Immunoassay Platform for Screening of Oral Cavity Squamous Cell Carcinoma
Authors: Lin Yen-Heng , Wu Chih-Ching , Chen Wan-Ling , Chang Kai-Ping
Published: February 2020

The incidence of oral squamous cell carcinoma (OSCC), which is one of the most common cancers worldwide, has been increasing. Serum anti-p53 autoantibody is one of the most sensitive biomarkers for OSCC. Currently, the most commonly used method on clinical screening platforms is the enzyme-linked immunosorbent assay, owing to its high specificity and repeatability. However, conducting immunoassays on 96-well plates is typically time consuming, thereby limiting its clinical applications for fast diagnosis and immediate prognosis of rapidly progressive diseases. The present study performed immunoassays in glass capillaries of 1-mm internal diameter, which increases the surface to volume ratio of the reaction, to shorten the time needed for immunoassay. The immunoassay was automated while using linear motorized stages and a syringe pump. The results indicated that, when compared with the 96-well plate immunoassay, the glass capillary immunoassay decreased the reaction time from typical 120 min to 45 min, reduced the amount of reagent from typical 50 µL to 15 µL, and required only simple equipment setup. Moreover, the limit of detection for glass capillary anti-p53 autoantibody immunoassay was 0.46 ng mL−1, which is close to the 0.19 ng mL−1 value of the conventional 96-well plate assay, and the glass capillary method had a broader detection range. The apparatus was used to detect the serum anti-p53 autoantibody concentration in clinical patients and compare its results with the conventional 96-well plate method results, which suggested that both of the methods detect the same trend in the relative concentration of serum anti-p53 autoantibody in healthy individuals or patients with OSCC.
Reconsidering McKenzie’s Six Adventure Education Programming Elements Using an Ecological Dynamics Lens and Its Implications for Health and Wellbeing
Authors: King Jason , Hardwell Ashley , Brymer Eric , Bedford Andrew
Published: February 2020

Two decades ago, McKenzie’s meta-analysis of literature provided six fundamental elements of adventure education programme design still used to guide research and practice today. While the value of McKenzie’s early work should not be underestimated, adventure education has undergone considerable changes. Adventurous activities are now available in urban and indoor contexts and used to facilitate a growing health and wellbeing agenda. The use of risk as part of adventure education programming has also been critiqued. This paper reflects on contemporary notions of adventure, risk and the emergent narratives emphasising the associated psychological benefits. The Ecological Dynamics framework, along with representative design delivery, are presented as a viable way of building on McKenzie’s work. Both consider how effective outcomes in adventure education programmes are achieved through designs that focus on the unique relationship between the individual and their environment. While McKenzie’s six elements recognise the importance of human relationships, Ecological Dynamics forefronts relational elements, not just between participants but, importantly, the task and the environment. Individual participant needs in relation to their everyday life therefore become the focus of adventure education expanding beyond the traditional long-standing narratives of risk and danger. Through these two important concepts, this paper advocates an approach to the design of adventure representative of a participant’s everyday environment. In this way, adventure education outcomes translate beyond the adventure-specific context and align more holistically with the needs of individual participants while also assuring emphasis on individual health and wellbeing.