bluuebunny/crossref_metadata_2025 huggingface dataset:
A High-Precision Energy-Efficient GPS Time-Sync Method for High-Density Seismic Surveys
Authors: Tian Ruyun , Zhang Junjie , Zhang Shuai , Wang Longxu , Yang Hongyuan , Chen Yuda , Jiang Yuanjie , Lin Jun , Zhang Linhang
Published: June 2020

Large numbers of seismic channels and high-density energy-efficient acquisition systems are the development trend of seismic instruments and have attracted high R&D interests in recent years. The combination of remote sensing and wireless sensor network technology provides superior observation capabilities for high-density seismic exploration. However, large-scale and multi-node acquisition methods place higher requirements on time synchronization performance. Seismic data with poor time synchronization will cause considerable errors in the interpretation of seismic data and even have no practical significance. Thus, the strict time synchronization performance is the prerequisite and basis for the application of cable-less storage seismograph in high-density seismic array applications. The existing time synchronization methods have high power consumption and poor time synchronization accuracy, which is not suitable for the long-time task. In addition, these methods are affected by the number of nodes and the distance. This paper presents an energy-efficient time-sharing indexed interpolation intercept method for the seismic data synchronization. The time synchronization method uses the high-precision TCXO as the main clock and records GPS time in the SD card at intervals to achieve the high-precision time-stamp for the seismic data. Then the seismic data is intercepted intermittently based on precise time stamps, which achieves the strict seismic data synchronization. Performance analysis shows that the time synchronization accuracy of the proposed method is 0.6 μs and saves 73% energy of the time-sync periods compared to the common GPS timing method. The field measurement results indicate that the time synchronization accuracy is not associated with the working time and the distance between nodes so that the proposed synchronization method is suitable for the high-density seismic survey.
Evaluating the Performance of Individual and Novel Ensemble of Machine Learning and Statistical Models for Landslide Susceptibility Assessment at Rudraprayag District of Garhwal Himalaya
Authors: Saha Sunil , Saha Anik , Hembram Tusar Kanti , Pradhan Biswajeet , Alamri Abdullah M.
Published: June 2020

Landslides are known as the world’s most dangerous threat in mountainous regions and pose a critical obstacle for both economic and infrastructural progress. It is, therefore, quite relevant to discuss the pattern of spatial incidence of this phenomenon. The current research manifests a set of individual and ensemble of machine learning and probabilistic approaches like an artificial neural network (ANN), support vector machine (SVM), random forest (RF), logistic regression (LR), and their ensembles such as ANN-RF, ANN-SVM, SVM-RF, SVM-LR, LR-RF, LR-ANN, ANN-LR-RF, ANN-RF-SVM, ANN-SVM-LR, RF-SVM-LR, and ANN-RF-SVM-LR for mapping landslide susceptibility in Rudraprayag district of Garhwal Himalaya, India. A landslide inventory map along with sixteen landslide conditioning factors (LCFs) was used. Randomly partitioned sets of 70%:30% were used to ascertain the goodness of fit and predictive ability of the models. The contribution of LCFs was analyzed using the RF model. The altitude and drainage density were found to be the responsible factors in causing the landslide in the study area according to the RF model. The robustness of models was assessed through three threshold dependent measures, i.e., receiver operating characteristic (ROC), precision and accuracy, and two threshold independent measures, i.e., mean-absolute-error (MAE) and root-mean-square-error (RMSE). Finally, using the compound factor (CF) method, the models were prioritized based on the results of the validation methods to choose best model. Results show that ANN-RF-LR indicated a realistic finding, concentrating only on 17.74% of the study area as highly susceptible to landslide. The ANN-RF-LR ensemble demonstrated the highest goodness of fit and predictive capacity with respective values of 87.83% (area under the success rate curve) and 93.98% (area under prediction rate curve), and the highest robustness correspondingly. These attempts will play a significant role in ensemble modeling, in building reliable and comprehensive models. The proposed ANN-RF-LR ensemble model may be used in the other geographic areas having similar geo-environmental conditions. It may also be used in other types of geo-hazard modeling.
Effects of Class Purity of Training Patch on Classification Performance of Crop Classification with Convolutional Neural Network
Authors: Park Soyeon , Park No-Wook
Published: June 2020

As the performance of supervised classification using convolutional neural networks (CNNs) are affected significantly by training patches, it is necessary to analyze the effects of the information content of training patches in patch-based classification. The objective of this study is to quantitatively investigate the effects of class purity of a training patch on performance of crop classification. Here, class purity that refers to a degree of compositional homogeneity of classes within a training patch is considered as a primary factor for the quantification of information conveyed by training patches. New quantitative indices for class homogeneity and variations of local class homogeneity over the study area are presented to characterize the spatial homogeneity of the study area. Crop classification using 2D-CNN was conducted in two regions (Anbandegi in Korea and Illinois in United States) with distinctive spatial distributions of crops and class homogeneity over the area to highlight the effect of class purity of a training patch. In the Anbandegi region with high class homogeneity, superior classification accuracy was obtained when using large size training patches with high class purity (7.1%p improvement in overall accuracy over classification with the smallest patch size and the lowest class purity). Training patches with high class purity could yield a better identification of homogenous crop parcels. In contrast, using small size training patches with low class purity yielded the highest classification accuracy in the Illinois region with low class homogeneity (19.8%p improvement in overall accuracy over classification with the largest patch size and the highest class purity). Training patches with low class purity could provide useful information for the identification of diverse crop parcels. The results indicate that training samples in patch-based classification should be selected based on the class purity that reflects the local class homogeneity of the study area.
A Unified Pervasive Linebroadening Function for Quantum Wells in Light Emitting Diodes
Authors: Viljanen Juha
Published: June 2020

The broadening functions for quantum wells in LEDs and laser diodes below the lasing threshold are examined. Inhomogeneous and homogeneous broadening mechanisms are included. Hydrogen-atom-like exciton and the electron-hole plasma recombination models are considered. Material disorder and the Urbach tail are reviewed as the main reasons for the inhomogeneous broadening. Charge carrier scattering and relaxation times in the conduction and valence bands are examined as the origin for the homogeneous lifetime broadening. Two homogeneous lineshapes are compared using the momentum relaxation times obtained from the electron and hole mobilities available for GaAs. In addition to crystal disorder, the mutual collision of charge carriers in the quantum wells is examined as the reason for the relaxation time shortening. The analogy to pressure broadening in gases is used to combine the proper homogeneous and inhomogeneous broadening functions to a unified quantum well lineshape.
Multi-Path Recurrent U-Net Segmentation of Retinal Fundus Image
Authors: Jiang Yun , Wang Falin , Gao Jing , Cao Simin
Published: June 2020

Diabetes can induce diseases including diabetic retinopathy, cataracts, glaucoma, etc. The blindness caused by these diseases is irreversible. Early analysis of retinal fundus images, including optic disc and optic cup detection and retinal blood vessel segmentation, can effectively identify these diseases. The existing methods lack sufficient discrimination power for the fundus image and are easily affected by pathological regions. This paper proposes a novel multi-path recurrent U-Net architecture to achieve the segmentation of retinal fundus images. The effectiveness of the proposed network structure was proved by two segmentation tasks: optic disc and optic cup segmentation and retinal vessel segmentation. Our method achieved state-of-the-art results in the segmentation of the Drishti-GS1 dataset. Regarding optic disc segmentation, the accuracy and Dice values reached 0.9967 and 0.9817, respectively; as regards optic cup segmentation, the accuracy and Dice values reached 0.9950 and 0.8921, respectively. Our proposed method was also verified on the retinal blood vessel segmentation dataset DRIVE and achieved a good accuracy rate.
Resilient Self-Triggered Control for Voltage Restoration and Reactive Power Sharing in Islanded Microgrids under Denial-of-Service Attacks
Authors: Xu Gang , Ma Liang
Published: June 2020

This paper addresses the problem of voltage restoration and reactive power sharing of inverter-based distributed generations (DGs) in an islanded microgrid subject to denial-of-service (DoS) attacks. Note that DoS attacks may block information exchange among DGs by jamming the communication network in the secondary control level of a microgrid. A two-layer distributed secondary control framework is presented, in which a state observer employing the multiagent system (MAS)-based ternary self-triggered control is implemented for discovering the average information of voltage and reactive power in a fully distributed manner while highly reducing communication burden than that the periodic communication way. The compensation for the reference signal to the primary control is acquired according to the average estimates to achieve voltage restoration while properly sharing reactive power among DGs. An improved ternary self-triggered control strategy integrating an acknowledgment (ACK)-based monitoring mechanism is established, where DoS attacks are modeled by repeated cycles of jamming and sleeping. A new triggering condition is developed to guarantee the successful information exchange between DGs when the sleep period of DoS attacks is detected. Using the Lyapunov approach, it is proved that the proposed algorithm allows agents to reach consensus regardless of the frequency of the DoS attacks, which maintains the accurate estimation of average information and the implementation of the secondary control objectives. The performance of the proposed control scheme is evaluated under simulation and experimental conditions. The results show that the proposed secondary control scheme can highly reduce the inter-agent communication as well as improve the robustness of the system to resist DoS attacks.
Data Transmission Direction Based Routing Algorithm for Improving Network Performance of IoT Systems
Authors: Noh Kyeong Mi , Park Jong Hyuk , Park Ji Su
Published: June 2020

With the continuous development of wireless communication technology, the Internet of Things (IoT) is being used in a wide range of fields. The IoT collects and exchanges large amounts of data with objects, either tangible or intangible, such as sensors or physical devices, connected to the Internet. Wireless sensor networks (WSNs) are components of IoT systems. WSNs are used in various IoT systems, such as monitoring, tracking, and detection systems, to extract relevant information and deliver it to users. WSNs consist of sensor nodes with low power, low cost, and multiple functions. Because sensor nodes have limited resources, such as power and memory, a reduction in the energy efficiency of the sensor nodes in WSNs will lead to a decrease in wireless network performance and an increase in packet loss, which affects IoT system performance. Therefore, this study aimed to find an energy-efficient routing method that extends the lifetime of WSNs by minimizing the battery use of sensor nodes to improve the network performance of IoT systems. Conserving energy from sensor nodes and increasing network throughput in WSNs involves having protocols. The low-energy adaptive clustering hierarchy (LEACH ) protocol is a well-known hierarchical routing protocol in WSNs that constructs clusters and transmits data. LEACH increases energy efficiency by transmitting data from sensor nodes to the base station (BS) through the cluster head. It is widely adopted in the WSN network field, and many protocols are being studied to improve cluster header selection and data transmission to increase the energy efficiency of sensor nodes. In this study, we attempted to improve energy efficiency by removing unnecessary energy from LEACH. In LEACH, when the sensor node is located between the BS and the cluster head, the sensor node transmits data to the cluster head in the opposite direction of the BS. The data sent to the cluster head are transmitted in the direction of the BS. Thus, transmission in the opposite direction consumes unnecessary energy and affects the WSN performance of IoT systems. In this study, we propose a D-LEACH (direction-based LEACH) protocol based on the received signal strength indicator (RSSI) that improves the efficiency of transmission energy considering the data transmission direction of sensor nodes. D-LEACH aims to balance the energy of the sensor nodes and improve the performance of WSNs in the IoT system by reducing unnecessary energy consumption caused by reverse transmission considering the data transmission direction of the sensor nodes. In the course of the paper, we refer to the routing protocol of WSNs to improve network performance and describe LEACH. We also explain the D-LEACH protocol proposed in this paper and confirm the performance improvement of WSNs in an IoT system through simulation.
Appraisal of Significance of Acoustic Parameters in Contribution to Human Annoyance
Authors: Suhanek Mia , Grubeša Sanja , Đurek Ivan , Petošić Antonio
Published: June 2020

The goal of this paper was to describe a study which aimed to determine the significance of acoustic parameters in terms of some typical audio signals which occur in common urban environments. The focus when establishing the significance was set on their relevance with respect to the annoyance of the study participants. In order to carry out this experiment, an acoustic environment recording was made in which short distracting signals were inserted into the acoustic environment background sound. The recording obtained in the described way was then reproduced to listeners in laboratory conditions. Furthermore, the experiment was envisaged in a way that the participants had the option to adjust the following acoustic parameters: the amplitude, duration and the amplitude growth rates of the short signals. In order to prove the statistical significance of the obtained results from the experiment and the study premise, the chi-square test was applied. Thus, according to the results of the study, the ranking of the objective acoustic parameters was achieved with respect to the human annoyance i.e., it can be concluded that the most common reason for the human annoyance in different acoustic environments is the sound amplitude, then its duration and finally its amplitude growth rate.
Chosen Aspects of the Electromagnetic Compatibility of Plasma Reactors with Gliding Arc Discharges
Authors: Mazurek Paweł
Published: June 2020

This paper presents an analysis of electromagnetic disturbance interactions inside the three-phase gliding arc plasma generation installation. This is the main part of the electromagnetic compatibility analysis of the reactor installation. All elements of the nonthermal plasma installation are described from the point of view of disturbance generation and their influence on the power supply system. The analysis is based on the results of tests carried out in accordance with the guidelines of the electromagnetic compatibility (EMC) Directive and harmonised standards. The disturbances measured are large, over 20 dB above the limits. The disturbances measured allow valid conclusions to be reached in relation to this type of installation. The implication is the need for plasma reactors designed with elements that reduce radiated and conducted interference.
Noise Suppression of Microseismic Signals via Adaptive Variational Mode Decomposition and Akaike Information Criterion
Authors: Zhang Jinyong , Dong Linlu , Xu Nuwen
Published: June 2020

Microseismic (MS) signals recorded by sensors are often mixed with various noise, which produce some interference to the further analysis of the collected data. One problem of many existing noise suppression methods is to deal with noisy signals in a unified strategy, which results in low-frequency noise in the non-microseismic section remaining. Based on this, we have developed a novel MS denoising method combining variational mode decomposition (VMD) and Akaike information criterion (AIC). The method first applied VMD to decompose a signal into several limited-bandwidth intrinsic mode functions and adaptively determined the effective components by the difference of correlation coefficient. After reconstructing, the improved AIC method was used to determine the location of the valuable waveform, and the residual fluctuations in other positions were further removed. A synthetic wavelet signal and some synthetic MS signals with different signal-to-noise ratios (SNRs) were used to test its denoising effect with ensemble empirical mode decomposition (EEMD), complete ensemble empirical mode decomposition (CEEMD), and the VMD method. The experimental results depicted that the SNRs of the proposed method were obviously larger than that of other methods, and the waveform and spectrum became cleaner based on VMD. The processing results of the MS signal of Shuangjiangkou Hydropower Station also illustrated its good denoising ability and robust performance to signals with different characteristics.
Fungal Community Analysis and Biodeterioration of Waterlogged Wooden Lacquerware from the Nanhai No. 1 Shipwreck
Authors: Jia Yin , Yin Liuyu , Zhang Fengyu , Wang Mei , Sun Mingliang , Hu Cuiting , Liu Zijun , Chen Yue , Liu Jie , Pan Jiao
Published: June 2020

To avoid the lacquerware of the Nanhai No. 1 shipwreck from being corroded by microorganisms and to improve the knowledge on microbial ecology of the wood lacquers, we conducted a series of tests on the two water samples storing the lacquerware and colonies on the surface of the lacquerware. The high-throughput sequencing detected dominant fungal communities. After that, the fungal strains were isolated and then identified by amplification of ITS- 18S rRNA. Then the activity of ligninolytic and cellulolytic enzymes was detected on potato dextrose agar (PDA) plates with 0.04% (v/v) guaiacol and carboxymethyl cellulose (CMC) agar plates. Finally, we tested the biocide susceptibility of these fungi. Penicillium chrysogenum (NK-NH3) and Fusarium solani (NK- NH1) were the dominant fungi in the sample collected in April 2016 and June 2017. What is more, both showed activity of ligninolytic and cellulolytic enzymes. Four biocidal products (Preventol® D7, P91, BIT 20N, and Euxyl® K100) inhibited the growth of the fungal species in vitro effectively. In further research, the microbial community and environmental parameters in the museum should be monitored to assess the changes in the community and to detect potential microbial outbreaks.
X-ray Visualization and Quantification Using Fibrous Color Dosimeter Based on Leuco Dye
Authors: Phong Vo Phu , Ngoc Doan Hoan , Kinashi Kenji , Sakai Wataru , Tsutsumi Naoto , Phu Huynh Dai
Published: June 2020

A polystyrene (PS)-based fibrous color dosimeter, comprising a color former based on 2-(phenylamino)-6-(dipentylamino)-3-methylspiro[9H-xanthene-9,3′-phthalide] (Black305) fluoran leuco dye and a 2-(4-methoxystyryl)-4,6-bis(trichloromethyl)-1,3,5-triazine (MBTT) photoacid generator, was developed for visual detection of X-ray doses of 15 Gy and higher. The composite fiber was produced by using a centrifugal spinning method, and the obtained composite fiber exhibited a stable and uniform morphology with a fiber diameter of 10 μm or less and had sufficient mechanical strength. As an example of practical application, we successfully processed the composite fiber into an apron and clearly and visually confirmed that the color change from yellow to black occurs on the surface of the fabric under X-ray exposure.
Numerical Study on the Phase Sensitivity Variation in Low Frequency Primary Microphone Calibrations
Authors: Zhang Fan , Liu Di , Liu Aibing , Gang Xianyue , Li Lijun
Published: June 2020

The low frequency phase characteristics of microphones in a monitoring system are crucial for characterizing large-scale natural and artificial activities—e.g., earthquakes, nuclear explosions, or rocket launchings. At present, microphones are simultaneously calibrated using in-situ or calibrator methods to get their phase consistency. However, the essential primary calibration, which traces their phase sensitivity to basic physical quantities, is grossly overlooked. Recently, we speculated that the microphone phase sensitivity is acoustically controlled by the pressure leakage and heat conduction effects in its back chamber, which will vary at low frequencies. Therefore, by means of the FEA (Finite Element Analysis) technique, simulations of laser pistonphone-based primary microphone calibrations are conducted both in the frequency and time domains. The frequency domain simulation quantifies the phase variation, while the time domain analysis helps us to understand the variation mechanism. It is found that the low frequency phase sensitivity is greatly influenced by its geometries and the venting state and should be pre-calibrated before serving.
Online Estimation of Short-Circuit Fault Level in Active Distribution Network
Authors: Wang Xiaohui , Wang Peng , Wang Yunbo , Shi Fang
Published: June 2020

The potential short-circuit current in active distribution network features time-variance with the increasing distributed generations. This feature makes the online estimation of fault level necessary. In this paper, a novel online estimation method is proposed to be implemented by either phasor measurement unit (PMU) or the measurements from protection relays. The equivalent circuit of the radial distribution network with distributed generators (DGs), e.g., wind turbines and photovoltaic cells, is derived with necessary simplifications. The natural disturbances downstream are used to evaluate the parameters of the equivalent circuit so that the potential fault level can be estimated in advance of the actual fault occurrence. A fuzzy logic identifier is presented to rank the confidence of the measurements incurred by the disturbance and to distinguish the qualified disturbance to launch the estimation. The mechanism based on multi-measurements and confidence indices was applied, to improve the accuracy. A typical distribution network in the United Kingdom (UK) with DGs was taken, as an example, to validate the proposed method under various load fluctuation. The results confirm the effectiveness of the proposed method, which is suitable for online estimation of short-circuit fault level in active distribution networks.
One-Step and Morphology-Controlled Synthesis of Ni-Co Binary Hydroxide on Nickel Foam for High-Performance Supercapacitors
Authors: Fan Xiao , Ohlckers Per , Chen Xuyuan
Published: June 2020

Ni-Co binary hydroxide grown on nickel foam was synthesized through a facile one-step process for pseudocapacitive electrode application. The morphology of the fabricated binary hydroxide, evolving from nanosheet to nanowire, was highly controllable by tuning the Ni:Co ratio. In systematical electrochemical measurements, the prepared binary material on nickel foam could be employed as a binder-free working electrode directly. The optimal composition obtained at the Ni:Co ratio of 5:5 in integrated nanosheet/nanowire geometry exhibited high specific capacitances of 2807 and 2222 F/g at current densities of 1 and 20 A/g, equivalent to excellent rate capability. The capacitance loss was 19.8% after 2000 cycles, demonstrating good long-term cyclic stability. The outstanding supercapacitors behaviors benefited from unique structure and synergistic contributions, indicating the great potential of the obtained binary hydroxide electrode for high-performance energy storage devices.
Strain Influence Factor Charts for Settlement Evaluation of Spread Foundations based on the Stress–Strain Method
Authors: Pantelidis Lysandros
Published: June 2020

In this paper, the stress–strain method for the elastic settlement analysis of shallow foundations is revisited, offering a great number of strain influence factor charts covering the most common cases met in civil engineering practice. The calculation of settlement based on strain influence factors has the advantage of considering soil elastic moduli values rapidly varying with depth, such as those often obtained in practice using continuous probing tests, e.g., the Cone Penetration Test (CPT) and Standard Penetration Test (SPT). It also offers the advantage of the convenient calculation of the correction factor for future water table rise into the influence depth of footing. As is known, when the water table rises into the influence zone of footing, it reduces the soil stiffness and thus additional settlement is induced. The proposed strain influence factors refer to flexible circular footings (at distances 0, R/3, 2R/3 and R from the center; R is the radius of footing), rigid circular footings, flexible rectangular footings (at the center and corner), triangular embankment loading of width B and length L (L/B = 1, 2, 3, 4, 5 and 10) and trapezoidal embankment loading of infinite length and various widths. The strain influence factor values are given for Poisson’s ratio value of soil, ranging from 0 to 0.5 with 0.1 interval. The compatibility of the so-called “characteristic point” of flexible footings with the stress–strain method is also investigated; the settlement under this point is considered to be the same as the uniform settlement of the respective rigid footing. The analysis showed that, despite the effectiveness of the “characteristic point” concept in homogenous soils, the method in question is not suitable for non-homogenous soils, as it largely overestimates settlement at shallow depths (for z/B < 0.35) and underestimates it at greater depths (for z/B > 0.35; z is the depth below the footing and B is the footing width).
Chemical Analysis of Fluorobenzenes via Multinuclear Detection in the Strong Heteronuclear J-Coupling Regime
Authors: Kaseman Derrick C. , Janicke Michael T. , Frankle Rachel K. , Nelson Tammie , Angles-Tamayo Gary , Batrice Rami J. , Magnelind Per E. , Espy Michelle A. , Williams Robert F.
Published: June 2020

Chemical analysis via nuclear magnetic resonance (NMR) spectroscopy using permanent magnets, rather than superconducting magnets, is a rapidly developing field. Performing the NMR measurement in the strong heteronuclear J-coupling regime has shown considerable promise for the chemical analysis of small molecules. Typically, the condition for the strong heteronuclear J-coupling regime is satisfied at µT magnetic field strengths and enables high resolution J-coupled spectra (JCS) to be acquired. However, the JCS response to systematic chemical structural changes has largely not been investigated. In this report, we investigate the JCS of C6H6−xFx (x = 0, 1, 2, …, 6) fluorobenzene compounds via simultaneous excitation and detection of 19F and 1H at 51.5 µT. The results demonstrate that JCS are quantitative, and the common NMR observables, including Larmor frequency, heteronuclear and homonuclear J-couplings, relative signs of the J-coupling, chemical shift, and relaxation, are all measurable and are differentiable between molecules at low magnetic fields. The results, corroborated by ab initio calculations, provide new insights into the impact of chemical structure and their corresponding spin systems on JCS. In several instances, the JCS provided more chemical information than traditional high field NMR, demonstrating that JCS can be used for robust chemical analysis.
A Semantic Focused Web Crawler Based on a Knowledge Representation Schema
Authors: Hernandez Julio , Marin-Castro Heidy M. , Morales-Sandoval Miguel
Published: June 2020

The Web has become the main source of information in the digital world, expanding to heterogeneous domains and continuously growing. By means of a search engine, users can systematically search over the web for particular information based on a text query, on the basis of a domain-unaware web search tool that maintains real-time information. One type of web search tool is the semantic focused web crawler (SFWC); it exploits the semantics of the Web based on some ontology heuristics to determine which web pages belong to the domain defined by the query. An SFWC is highly dependent on the ontological resource, which is created by domain human experts. This work presents a novel SFWC based on a generic knowledge representation schema to model the crawler’s domain, thus reducing the complexity and cost of constructing a more formal representation as the case when using ontologies. Furthermore, a similarity measure based on the combination of the inverse document frequency (IDF) metric, standard deviation, and the arithmetic mean is proposed for the SFWC. This measure filters web page contents in accordance with the domain of interest during the crawling task. A set of experiments were run over the domains of computer science, politics, and diabetes to validate and evaluate the proposed novel crawler. The quantitative (harvest ratio) and qualitative (Fleiss’ kappa) evaluations demonstrate the suitability of the proposed SFWC to crawl the Web using a knowledge representation schema instead of a domain ontology.
Engine Performance and Emissions Analysis in a Cold, Intermediate and Hot Start Diesel Engine
Authors: Lodi Faisal , Zare Ali , Arora Priyanka , Stevanovic Svetlana , Jafari Mohammad , Ristovski Zoran , Brown Richard J. , Bodisco Timothy
Published: June 2020

Presented in this paper is an in-depth analysis of the impact of engine start during various stages of engine warm up (cold, intermediate, and hot start stages) on the performance and emissions of a heavy-duty diesel engine. The experiments were performed at constant engine speeds of 1500 and 2000 rpm on a custom designed drive cycle. The intermediate start stage was found to be longer than the cold start stage. The oil warm up lagged the coolant warm up by approximately 10 °C. During the cold start stage, as the coolant temperature increased from ~25 to 60 °C, the brake specific fuel consumption (BSFC) decreased by approximately 2% to 10%. In the intermediate start stage, as the coolant temperature reached 70 °C and the injection retarded, the indicated mean effective pressure (IMEP) and the brake mean effective pressure (BMEP) decreased by approximately 2% to 3%, while the friction mean effective pressure (FMEP) decreased by approximately 60%. In this stage, the NOx emissions decreased by approximately 25% to 45%, while the HC emissions increased by approximately 12% to 18%. The normalised FMEP showed that higher energy losses at lower loads were most likely contributing to the heating of the lubricating oil.
True Equalization of Polarization-Dependent Loss in Presence of Fast Rotation of SOP
Authors: Cui Nan , Zhang Xiaoguang , Zhang Wenbo , Tang Xianfeng , Xi Lixia
Published: June 2020

In an optical fiber communication system, polarization-dependent loss (PDL), referring to polarization-dependent optical power attenuation, might be a main system performance limiting factor. PDL causes a difference in signal power and imbalance of optical signal-to-noise ratio (OSNR) between the two polarization branches. The OSNR asymmetry will eventually deteriorate the overall system performance. At present, most of the equalization methods of PDL in the literature can only accomplish power imbalance equalization and are, thus, not the true equalization of PDL. Besides, in some extreme environments, like lightning strikes, Kerr and Faraday effects would generate ultra-fast rotation of state of polarization (RSOP), as fast as mega-radian per second. The fast RSOP in combination with PDL makes the eigenmodes of the PDL randomly time-varying, which will put a heavy burden on the equalization module of the receiver. Faced with this dilemma, in this paper, we propose a scheme for the true equalization of PDL in the presence of fast RSOP through an approach based on the combination of the polarization-time code and Kalman filter. The proposed approach is proved to be very effective and provides significant performance. With a 1.2 dB OSNR penalty, it can jointly equalize large PDL (7 dB) and fast RSOP (up to 1 Mrad/s).
Spatial-Temporal Pattern of Black Carbon (BC) Emission from Biomass Burning and Anthropogenic Sources in New South Wales and the Greater Metropolitan Region of Sydney, Australia
Authors: Duc Hiep Nguyen , Shingles Kristina , White Stephen , Salter David , Chang Lisa Tzu-Chi , Gunashanhar Gunaratnam , Riley Matthew , Trieu Toan , Dutt Upma , Azzi Merched , Beyer Kathleen , Hynes Robert , Kirkwood John
Published: June 2020

Biomass burnings either due to Hazards Reduction Burnings (HRBs) in late autumn and early winter or bushfires during summer periods in various part of the world (e.g., CA, USA or New South Wales, Australia) emit large amount of gaseous pollutants and aerosols. The emissions, under favourable meteorological conditions, can cause elevated atmospheric particulate concentrations in metropolitan areas and beyond. One of the pollutants of concern is black carbon (BC), which is a component of aerosol particles. BC is harmful to health and acts as a radiative forcing agent in increasing the global warming due to its light absorption properties. Remote sensing data from satellites have becoming increasingly available for research, and these provide rich datasets available on global and local scale as well as in situ aethalometer measurements allow researchers to study the emission and dispersion pattern of BC from anthropogenic and natural sources. The Department of Planning, Industry and Environment (DPIE) in New South Wales (NSW) has installed recently from 2014 to 2019 a total of nine aethalometers to measure BC in its state-wide air quality network to determine the source contribution of BC and PM2.5 (particulate Matter less than 2.5 μm in diameter) in ambient air from biomass burning and anthropogenic combustion sources. This study analysed the characteristics of spatial and temporal patterns of black carbon (BC) in New South Wales and in the Greater Metropolitan Region (GMR) of Sydney, Australia, by using these data sources as well as the trajectory HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) modelling tool to determine the source of high BC concentration detected at these sites. The emission characteristics of BC in relation to PM2.5 is dependent on the emission source and is analysed using regression analysis of BC with PM2.5 time series at the receptor site for winter and summer periods. The results show that, during the winter, correlation between BC and PM2.5 is found at nearly all sites while little or no correlation is detected during the summer period. Traffic vehicle emission is the main BC emission source identified in the urban areas but was less so in the regional sites where biomass burnings/wood heating is the dominant source in winter. The BC diurnal patterns at all sites were strongly influenced by meteorology.
Computational Biomechanics: In-Silico Tools for the Investigation of Surgical Procedures and Devices
Authors: Carniel Emanuele Luigi , Toniolo Ilaria , Fontanella Chiara Giulia
Published: June 2020

Biomechanical investigations of surgical procedures and devices are usually developed by means of human or animal models. The exploitation of computational methods and tools can reduce, refine, and replace (3R) the animal experimentations for scientific purposes and for pre-clinical research. The computational model of a biological structure characterizes both its geometrical conformation and the mechanical behavior of its building tissues. Model development requires coupled experimental and computational activities. Medical images and anthropometric information provide the geometrical definition of the computational model. Histological investigations and mechanical tests on tissue samples allow for characterizing biological tissues’ mechanical response by means of constitutive models. The assessment of computational model reliability requires comparing model results and data from further experimentations. Computational methods allow for the in-silico analysis of surgical procedures and devices’ functionality considering many different influencing variables, the experimental investigation of which should be extremely expensive and time consuming. Furthermore, computational methods provide information that experimental methods barely supply, as the strain and the stress fields that regulate important mechano-biological phenomena. In this work, general notes about the development of biomechanical tools are proposed, together with specific applications to different fields, as dental implantology and bariatric surgery.
VLSI Structures for DNA Sequencing—A Survey
Authors: Islam Mohammad A. , Datta Palash K. , Myler Harley
Published: June 2020

DNA sequencing is a critical functionality in biomedical research, and technical advances that improve it have important implications for human health. Novel methods by which sequencing can be accomplished in more accurate, high-throughput, and faster ways are in development. Here, we review VLSI biosensors for nucleotide detection and DNA sequencing. Implementation strategies are discussed and split into function-specific architectures that are presented for reported design examples from the literature. Lastly, we briefly introduce a new approach to sequencing using Gate All-Around (GAA) nanowire Metal Oxide Semiconductor Field Effect Transistors (MOSFETs) that has significant implications for the field.
Synthesis and In Vitro Photodynamic Activity of Cationic Boron Dipyrromethene-Based Photosensitizers Against Methicillin-Resistant Staphylococcus aureus
Authors: Dharmaratne Priyanga , Wong Roy C. H. , Wang Jun , Lo Pui-Chi , Wang Baiyan , Chan Ben C. L. , Lau Kit-Man , Lau Clara B. S. , Fung Kwok-Pui , Ip Margaret , Ng Dennis K. P.
Published: June 2020

A series of cationic boron dipyrromethene (BODIPY) derivatives were synthesized and characterized with various spectroscopic methods. Having the ability to generate singlet oxygen upon irradiation, these compounds could potentially serve as photosensitizers for antimicrobial photodynamic therapy. Of the five BODIPYs being examined, the dicationic aza-BODIPY analogue (compound 5) demonstrated the highest potency against a broad spectrum of clinically relevant methicillin-resistant Staphylococcus aureus (MRSA), including four ATCC-type strains (ATCC 43300, ATCC BAA-42, ATCC BAA-43, and ATCC BAA-44), two strains carrying specific antibiotic resistance mechanisms [-AAC(6’)-APH(2”) and RN4220/pUL5054], and ten non-duplicate clinical strains from hospital- and community-associated MRSAs of the important clonal types ST239, ST30, and ST59, which have previously been documented to be prevalent in Hong Kong and its neighboring countries. The in vitro anti-MRSA activity of compound 5 was achieved upon irradiation with near-infrared light (>610 nm) with minimal bactericidal concentrations (MBCs) ranging from 12.5 to 25 µM against the whole panel of MRSAs, except the hospital-associated MRSAs for which the MBCs were in the range of 50–100 µM. Compound 5 was significantly (p < 0.05) more potent than methylene blue, which is a clinically approved photosensitizer, indicating that it is a promising antimicrobial agent that is worthy of further investigation.
Caterpillar Venom: A Health Hazard of the 21st Century
Authors: Seldeslachts Andrea , Peigneur Steve , Tytgat Jan
Published: June 2020

Caterpillar envenomation is a global health threat in the 21st century. Every direct or indirect contact with the urticating hairs of a caterpillar results in clinical manifestations ranging from local dermatitis symptoms to potentially life-threatening systemic effects. This is mainly due to the action of bioactive components in the venom that interfere with targets in the human body. The problem is that doctors are limited to relieve symptoms, since an effective treatment is still lacking. Only for Lonomia species an effective antivenom does exist. The health and economical damage are an underestimated problem and will be even more of a concern in the future. For some caterpillar species, the venom composition has been the subject of investigation, while for many others it remains unknown. Moreover, the targets involved in the pathophysiology are poorly understood. This review aims to give an overview of the knowledge we have today on the venom composition of different caterpillar species along with their pharmacological targets. Epidemiology, mode of action, clinical time course and treatments are also addressed. Finally, we briefly discuss the future perspectives that may open the doors for future research in the world of caterpillar toxins to find an adequate treatment.
Biomimetic Nanomembranes: An Overview
Authors: Jakšić Zoran , Jakšić Olga
Published: June 2020

Nanomembranes are the principal building block of basically all living organisms, and without them life as we know it would not be possible. Yet in spite of their ubiquity, for a long time their artificial counterparts have mostly been overlooked in mainstream microsystem and nanosystem technologies, being a niche topic at best, instead of holding their rightful position as one of the basic structures in such systems. Synthetic biomimetic nanomembranes are essential in a vast number of seemingly disparate fields, including separation science and technology, sensing technology, environmental protection, renewable energy, process industry, life sciences and biomedicine. In this study, we review the possibilities for the synthesis of inorganic, organic and hybrid nanomembranes mimicking and in some way surpassing living structures, consider their main properties of interest, give a short overview of possible pathways for their enhancement through multifunctionalization, and summarize some of their numerous applications reported to date, with a focus on recent findings. It is our aim to stress the role of functionalized synthetic biomimetic nanomembranes within the context of modern nanoscience and nanotechnologies. We hope to highlight the importance of the topic, as well as to stress its great applicability potentials in many facets of human life.
Development and Evaluation of the Chromatic Behavior of an Intelligent Packaging Material Based on Cellulose Acetate Incorporated with Polydiacetylene for an Efficient Packaging
Authors: Ardila-Diaz Lina D. , Oliveira Taíla V. de , Soares Nilda de F. F.
Published: June 2020

Global growth of the food industry and the demand for new products with natural characteristics, safe conditions and traceability have driven researches for the development of technologies such as intelligent packaging, capable to fulfil those needs. Polydiacetylene (PDA) is a synthetic material that has been highlighted in research field as a sensor substance, which can be used to produce intelligent packaging capable to detect chemical or biochemical changes in foods and in their environment due to PDA’s color transition from blue to red. This work focused on the development and optimization of an intelligent packaging constituted of a polymeric matrix of cellulose acetate-based incorporated with PDA as the substance sensor. Cellulose acetate films (3% wt.) were developed by a casting method, and the amounts of triethyl citrate plasticizer (TEC) (0–25% wt. of cellulose-acetate) and PDA (0–60 mg) were analyzed to optimize the conditions for the best color transitioning at this study range. The compound amounts incorporated into polymeric matrices were established according to Central Composite Designs (CCD). Three more design variables were analyzed, such as the polymerization time of PDA under UV light exposition (0–60 min), pH values (4–11) and temperature exposure on the film (0–100 °C), important factors on the behavior of PDA’s color changing. In this study, film thickness and film color coordinates were measured in order to study the homogeneity and the color transitioning of PDA films under different pH and temperature conditions, with the purpose of maximizing the color changes through the optimization of PDA and TEC concentrations into the cellulose acetate matrix and the polymerization degree trigged by UV light irradiation. The optimal film conditions were obtained by adding 50.48 g of PDA and 10% of TEC, polymerization time of 18 min under UV light, at 100 °C ± 2 °C of temperature exposure. The changes in pH alone did not statistically influence the color coordinates measured at the analyzed ratio; however, variations in pH associated with other factors had a significant effect on visual color changes, and observations were described. PDA films were optimized to maximize color change in order to obtain a cheap and simple technology to produce intelligent packaging capable to monitor food products along the distribution chain in real time, improving the food quality control and consumer safety.
Infants’ Gaze Patterns for Same-Race and Other-Race Faces, and the Other-Race Effect
Authors: Krasotkina Anna , Götz Antonia , Höhle Barbara , Schwarzer Gudrun
Published: June 2020

The other-race effect (ORE) can be described as difficulties in discriminating between faces of ethnicities other than one’s own, and can already be observed at approximately 9 months of age. Recent studies also showed that infants visually explore same-and other-race faces differently. However, it is still unclear whether infants’ looking behavior for same- and other-race faces is related to their face discrimination abilities. To investigate this question we conducted a habituation–dishabituation experiment to examine Caucasian 9-month-old infants’ gaze behavior, and their discrimination of same- and other-race faces, using eye-tracking measurements. We found that infants looked longer at the eyes of same-race faces over the course of habituation, as compared to other-race faces. After habituation, infants demonstrated a clear other-race effect by successfully discriminating between same-race faces, but not other-race faces. Importantly, the infants’ ability to discriminate between same-race faces significantly correlated with their fixation time towards the eyes of same-race faces during habituation. Thus, our findings suggest that for infants old enough to begin exhibiting the ORE, gaze behavior during habituation is related to their ability to differentiate among same-race faces, compared to other-race faces.