bluuebunny/crossref_metadata_2025 huggingface dataset:
Geospatial Analysis of Horizontal and Vertical Urban Expansion Using Multi-Spatial Resolution Data: A Case Study of Surabaya, Indonesia
Authors: Handayani Hepi H. , Murayama Yuji , Ranagalage Manjula , Liu Fei , Dissanayake DMSLB
Published: October 2018

Urbanization addresses urban expansion, and it leads conversion of the green space into the built-up area. However, previous studies mainly focused on two-dimensional (2D) urban expansion rather than three-dimensional (3D) growth. Here, the purpose of this study is to examine the urban expansion, including built-up and green space for both horizontal and vertical dimensions using geospatial analysis including remote sensing (RS) and Geographic Information System (GIS) in the sub-Central Business District (CBD) area of Surabaya, Indonesia. The medium resolution remote sensing data for both image and Digital Surface Model (DSM) acquired by Advanced Land-Observing Satellite (ALOS) were applied for time-1 (2010). The orthophoto and DSM derived by LiDAR were used for time-2 (2016). We quantified the built-up and green expansions in 2D (area), which were extracted from land use/land cover (LU/LC) by applying hybrid classification. The built-up and green expansions in 3D (volume) were estimated by generating a surface feature model. The spatial configuration of area expansion was investigated using patch metric, while the volume growth was examined using the volume expansion rate. We got three findings. (1) The built-up and green area had expanded about 11.54% and 95.61%, respectively, from 2010 to 2016. The expansion of green area presented in a notable portion, which was mainly contributed by the conversion of bareland to playground or park. However, the expansion of built-up area was less than the volume expansion of 20.6%. It revealed that built-up growth led to vertical rather than horizontal development. (2) The built-up area expansion tended to scatter configuration, whereas, the green area expansion tended to aggregate in a linear pattern. (3) The ratio of built-up volume expansion to green volume expansion showed a mean of 3.7, indicating that the development of built-up and green volume was imbalanced. The built-up growth presented higher than the green growth, mainly in the areas with more vertical building establishment. The pressing need for higher green volume in the study area was identified in several sites located at surrounding artery and toll roads. Overall, our approach can be applied as a reference in monitoring neighborhood environment through greening programs for sustainable urban development.
Accuracy of Unmanned Aerial Vehicle (UAV) and SfM Photogrammetry Survey as a Function of the Number and Location of Ground Control Points Used
Authors: Sanz-Ablanedo Enoc , Chandler Jim H. , Rodríguez-Pérez José Ramón , Ordóñez Celestino
Published: October 2018

The geometrical accuracy of georeferenced digital surface models (DTM) obtained from images captured by micro-UAVs and processed by using structure from motion (SfM) photogrammetry depends on several factors, including flight design, camera quality, camera calibration, SfM algorithms and georeferencing strategy. This paper focusses on the critical role of the number and location of ground control points (GCP) used during the georeferencing stage. A challenging case study involving an area of 1200+ ha, 100+ GCP and 2500+ photos was used. Three thousand, four hundred and sixty-five different combinations of control points were introduced in the bundle adjustment, whilst the accuracy of the model was evaluated using both control points and independent check points. The analysis demonstrates how much the accuracy improves as the number of GCP points increases, as well as the importance of an even distribution, how much the accuracy is overestimated when it is quantified only using control points rather than independent check points, and how the ground sample distance (GSD) of a project relates to the maximum accuracy that can be achieved.
New Geodetic and Gravimetric Maps to Infer Geodynamics of Antarctica with Insights on Victoria Land
Authors: Zanutta Antonio , Negusini Monia , Vittuari Luca , Martelli Leonardo , Cianfarra Paola , Salvini Francesco , Mancini Francesco , Sterzai Paolo , Dubbini Marco , Capra Alessandro
Published: October 2018

In order to make inferences on the geodynamics of Antarctica, geodetic and gravimetric maps derived from past and new observations can be used. This paper provides new insights into the geodynamics of Antarctica by integrating data at regional and continental scales. In particular, signatures of geodynamic activity at a regional extent have been investigated in Victoria Land (VL, Antarctica) by means of Global Navigation Satellite System (GNSS) permanent station observations, data from the VLNDEF (Victoria Land Network for Deformation control) discontinuous network, and gravity station measurements. At the continental scale, episodic GNSS observations on VLNDEF sites collected for 20 years, together with continuous data from the International GNSS Service (IGS) and Polar Earth Observing Network (POLENET) sites, were processed, and the Euler pole position assessed with the angular velocity of the Antarctic plate. Both the Bouguer and the free-air gravity anomaly maps were obtained by integrating the available open-access geophysics dataset, and a compilation of 180 gravity measurements collected in the VL within the Italian National Program for Antarctic Research (PNRA) activities. As a result, new evidence has been detected at regional and continental scale. The main absolute motion of VL is towards SE (Ve 9.9 ± 0.26 mm/yr, Vn −11.9 ± 0.27 mm/yr) with a pattern similar to the transforms of the Tasman and Balleny fracture zones produced as consequence of Southern Ocean spreading. Residual velocities of the GNSS stations located in VL confirm the active role of the two main tectonic lineaments of the region, the Rennick–Aviator and the Lillie–Tucker faults with right-lateral sense of shear. The resulting VL gravity anomalies show a NW region characterized by small sized Bouguer anomaly with high uplift rates associated and a SE region with low values of Bouguer anomaly and general subsidence phenomena. The East and West Antarctica are characterized by a different thickness of the Earth’s crust, and the relative velocities obtained by the observed GNSS data confirm that movements between the two regions are negligible. In East Antarctica, the roots of the main subglacial highlands, Gamburtsev Mts and Dronning Maud Land, are present. The Northern Victoria Land (NVL) is characterized by more scattered anomalies. These confirm the differences between the Glacial Isostatic Adjustment (GIA) modeled and observed uplift rates that could be related to deep-seated, regional scale structures.
A Global Analysis of Wildfire Smoke Injection Heights Derived from Space-Based Multi-Angle Imaging
Authors: Val Martin Maria , Kahn Ralph A. , Tosca Mika G.
Published: October 2018

We present an analysis of over 23,000 globally distributed wildfire smoke plume injection heights derived from Multi-angle Imaging SpectroRadiometer (MISR) space-based, multi-angle stereo imaging. Both pixel-weighted and aerosol optical depth (AOD)-weighted results are given, stratified by region, biome, and month or season. This offers an observational resource for assessing first-principle plume-rise modelling, and can provide some constraints on smoke dispersion modelling for climate and air quality applications. The main limitation is that the satellite is in a sun-synchronous orbit, crossing the equator at about 10:30 a.m. local time on the day side. Overall, plumes occur preferentially during the northern mid-latitude burning season, and the vast majority inject smoke near-surface. However, the heavily forested regions of North and South America, and Africa produce the most frequent elevated plumes and the highest AOD values; some smoke is injected to altitudes well above 2 km in nearly all regions and biomes. Planetary boundary layer (PBL) versus free troposphere injection is a critical factor affecting smoke dispersion and environmental impact, and is affected by both the smoke injection height and the PBL height; an example assessment is made here, but constraining the PBL height for this application warrants further work.
Interference-Aware Adaptive Beam Alignment for Hyper-Dense IEEE 802.11ax Internet-of-Things Networks
Authors: Kwon Dohyun , Kim Sang-Wook , Kim Joongheon , Mohaisen Aziz
Published: October 2018

The increasing use of Internet of Things (IoT) devices in specific areas results in an interference among them and the quality of communications can be severely degraded. To deal with this interference issue, the IEEE 802.11ax standard has been established in hyper-dense wireless networking systems. The 802.11ax adopts a new candidate technology that is called multiple network allocation vector in order to mitigate the interference problem. In this paper, we point out a potential problem in multiple network allocation vector which can cause delays to communication among IoT devices in hyper-dense wireless networks. Furthermore, this paper introduces an adaptive beam alignment algorithm for interference resolution, and analyzes the potential delays of communications among IoT devices under interference conditions. Finally, we simulate our proposed algorithm in densely deployed environments and show that the interference can be mitigated and the IEEE 802.11ax-based IoT devices can utilize air interface more fairly compared to conventional IEEE 802.11 distributed coordination function.
Horizontal Plasmonic Ruler Based on the Scattering Far-Field Pattern
Authors: Shin Eunso , Lee Young Jin , Kim Youngsoo , Kwon Soon-Hong
Published: October 2018

A novel method is proposed to detect the horizontal shift of a specific nanoblock relative to a reference nanoblock using surface plasmon modes at nanometer resolution. To accomplish this task, two orthogonal localized surface plasmon resonances were excited within the air gap region between the silver nanoblocks at the respective wavelengths, 890 nm, and 1100 nm. This technique utilized the scattering far-field intensities of the two block nanostructures at the two specific wavelengths at two specific directional spots. The ratio of the scattering intensities at the two spots changed according to the horizontal shift of the block that moved. Correspondingly, this ratio can be used to provide the precise location of the block. This method can be applied to many fields, including label-free bio-sensing, bio-analysis and alignment during nano-fabrication, owing to the high resolution and simplicity of the process.
A Novel Method for the Micro-Clearance Measurement of a Precision Spherical Joint Based on a Spherical Differential Capacitive Sensor
Authors: Wang Wen , Yang He , Zhang Min , Chen Zhanfeng , Shi Guang , Lu Keqing , Xiang Kui , Ju Bingfeng
Published: October 2018

A spherical joint is a commonly used mechanical hinge with the advantages of compact structure and good flexibility, and it becomes a key component in many types of equipment, such as parallel mechanisms, industrial robots, and automobiles. Real-time detection of a precision spherical joint clearance is of great significance in analyzing the motion errors of mechanical systems and improving the transmission accuracy. This paper presents a novel method for the micro-clearance measurement with a spherical differential capacitive sensor (SDCS). First, the structure and layout of the spherical capacitive plates were designed according to the measuring principle of capacitive sensors with spacing variation. Then, the mathematical model for the spatial eccentric displacements of the ball and the differential capacitance was established. In addition, equipotential guard rings were used to attenuate the fringe effect on the measurement accuracy. Finally, a simulation with Ansoft Maxwell software was carried out to calculate the capacitance values of the spherical capacitors at different eccentric displacements. Simulation results indicated that the proposed method based on SDCS was feasible and effective for the micro-clearance measurement of the precision spherical joints with small eccentricity.
Multivariate-Time-Series-Driven Real-time Anomaly Detection Based on Bayesian Network
Authors: Ding Nan , Gao Huanbo , Bu Hongyu , Ma Haoxuan , Si Huaiwei
Published: October 2018

Anomaly detection is an important research direction, which takes the real-time information system from different sensors and conditional information sources into consideration. Based on this, we can detect possible anomalies expected of the devices and components. One of the challenges is anomaly detection in multivariate-sensing time-series in this paper. Based on this situation, we propose RADM, a real-time anomaly detection algorithm based on Hierarchical Temporal Memory (HTM) and Bayesian Network (BN). First of all, we use HTM model to evaluate the real-time anomalies of each univariate-sensing time-series. Secondly, a model of anomalous state detection in multivariate-sensing time-series based on Naive Bayesian is designed to analyze the validity of the above time-series. Lastly, considering the real-time monitoring cases of the system states of terminal nodes in Cloud Platform, the effectiveness of the methodology is demonstrated using a simulated example. Extensive simulation results show that using RADM in multivariate-sensing time-series is able to detect more abnormal, and thus can remarkably improve the performance of real-time anomaly detection.
Multi-Target Intense Human Motion Analysis and Detection Using Channel State Information
Authors: Liu Jialin , Wang Lei , Fang Jian , Guo Linlin , Lu Bingxian , Shu Lei
Published: October 2018

Intense human motion, such as hitting, kicking, and falling, in some particular scenes indicates the occurrence of abnormal events like violence and school bullying. Camera-based human motion detection is an effective way to analyze human behavior and detect intense human motion. However, even if the camera is properly deployed, it will still generate blind spots. Moreover, camera-based methods cannot be used in places such as restrooms and dressing rooms due to privacy issues. In this paper, we propose a multi-target intense human motion detection scheme using commercial Wi-Fi infrastructures. Compared with human daily activities, intense human motion usually has the characteristics of intensity, rapid change, irregularity, large amplitude, and continuity. We studied the changing pattern of Channel State Information (CSI) influenced by intense human motion, and extracted features in the pattern by conducting a large number of experiments. Considering occlusion exists in some complex scenarios, we distinguished the Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) conditions in the case of obstacles appearing between the transmitter and the receiver, which further improves the overall performance. We implemented the intense human motion detection system using single commercial Wi-Fi devices, and evaluated it in real indoor environments. The experimental results show that our system can achieve intense human motion detection rate of 90%.
Self-Calibration of an Industrial Robot Using a Novel Affordable 3D Measuring Device
Authors: Gaudreault Martin , Joubair Ahmed , Bonev Ilian
Published: October 2018

This work shows the feasibility of calibrating an industrial robot arm through an automated procedure using a new, low-cost, wireless measuring device mounted on the robot’s flange. The device consists of three digital indicators that are fixed orthogonally to each other on an aluminum support. Each indicator has a measuring accuracy of 3 µm. The measuring instrument uses a kinematic coupling platform which allows for the definition of an accurate and repeatable tool center point (TCP). The idea behind the calibration method is for the robot to bring automatically this TCP to three precisely-known positions (the centers of three precision balls fixed with respect to the robot’s base) and with different orientations of the robot’s end-effector. The self-calibration method was tested on a small six-axis industrial robot, the ABB IRB 120 (Vasteras, Sweden). The robot was modeled by including all its geometrical parameters and the compliance of its joints. The parameters of the model were identified using linear regression with the least-square method. Finally, the performance of the calibration was validated with a laser tracker. This validation showed that the mean and the maximum absolute position errors were reduced from 2.628 mm and 6.282 mm to 0.208 mm and 0.482 mm, respectively.
Diffusion Logarithm-Correntropy Algorithm for Parameter Estimation in Non-Stationary Environments over Sensor Networks
Authors: Hu Limei , Chen Feng , Duan Shukai , Wang Lidan
Published: October 2018

This paper considers the parameter estimation problem under non-stationary environments in sensor networks. The unknown parameter vector is considered to be a time-varying sequence. To further promote estimation performance, this paper suggests a novel diffusion logarithm-correntropy algorithm for each node in the network. Such an algorithm can adopt both the logarithm operation and correntropy criterion to the estimation error. Moreover, if the error gets larger due to the non-stationary environments, the algorithm can respond immediately by taking relatively steeper steps. Thus, the proposed algorithm achieves smaller error in time. The tracking performance of the proposed logarithm-correntropy algorithm is analyzed. Finally, experiments verify the validity of the proposed algorithmic schemes, which are compared to other recent algorithms that have been proposed for parameter estimation.
Multi-Frequency Based Direction-of-Arrival Estimation for 2q-Level Nested Radar & Sonar Arrays
Authors: Zhou Hao , Hu Guoping , Shi Junpeng , Feng Ziang
Published: October 2018

Direction finding is a hot research area in radar and sonar systems. In the case of q ≥ 2, the 2qth-order cumulant based direction of arrival (DOA) estimation algorithm for the 2q-level nested array can achieve high resolution performance. A virtual 2qth-order difference co-array, which contains O(N2q) virtual sensors in the form of a uniform linear array (ULA), is yielded and the Gaussian noise is eliminated. However, some virtual elements are separated by the holes among the 2qth-order difference co-array and cannot be fully used. Even though the application of the multi-frequency method for minimum frequency separation (MFMFS) can fill the holes with low computation complexity, it requires that the number of frequencies must increase with the number of holes. In addition, the signal spectra have to be proportional for all frequencies, which is hard to satisfy when the number of holes is large. Aiming at this, we further propose a multi-frequency method for a minimum number of frequencies (MFMNF) and discuss the best frequency choice under two specific situations. Simulation results verify that, compared with the MFMFS method, the proposed MFMNF method can use only one frequency to fill all the holes while achieving a longer virtual array and the DOA estimation performance is, therefore, improved.
Real-Time Recursive Fingerprint Radio Map Creation Algorithm Combining Wi-Fi and Geomagnetism
Authors: Seong Ju-Hyeon , Seo Dong-Hoan
Published: October 2018

Fingerprint is a typical indoor-positioning algorithm, which measures the strength of wireless signals and creates a radio map. Using this radio map, the position is estimated through comparisons with the received signal strength measured in real-time. The radio map has a direct effect on the positioning performance; therefore, it should be designed accurately and managed efficiently, according to the type of wireless signal, amount of space, and wireless-signal density. This paper proposes a real-time recursive radio map creation algorithm that combines Wi-Fi and geomagnetism. The proposed method automatically recreates the radio map using geomagnetic radio-map dual processing (GRDP), which reduces the time required to create it. It also reduces the size of the radio map by actively optimizing its dimensions using an entropy-based minimum description length principle (MDLP) method. Experimental results in an actual building show that the proposed system exhibits similar map creation time as a system using a Wi-Fi–based radio map. Geomagnetic radio maps exhibiting over 80% positioning accuracy were created, and the dimensions of the radio map that combined the two signals were found to be reduced by 23.81%, compared to the initially prepared radio map. The dimensions vary according to the wireless signal state, and are automatically reduced in different environments.
The Corporate Social Responsibility of Hydropower Companies in Alpine Regions—Theory and Policy Recommendations
Authors: Hediger Werner
Published: October 2018

Hydropower activities must increasingly be evaluated from a sustainable development perspective. Corporate social responsibility (CSR) is the principle frequently applied to evaluate corporate contributions in this regard, though there exists no conceptual and theoretical basis that is common to the various approaches. With the present work, we fill this gap and provide a generic model that formally integrates the corporate and societal perspectives of hydropower activities within a welfare-economic framework that encompasses both externalities and distributional concerns. Building on this background and focusing on the current situation in Switzerland, the water tower of Western Europe, we particularly address the issues of water rights, resource rents and governance. This is crucial when analyzing investment projects of hydropower companies with shared private and public ownership; i.e., if external stakeholders are also sensitive shareholders who grant, at the same time, the company the right to operate. Altogether, this contribution shall support better informed decision making on both corporate and policy levels, especially regarding new and retrofitting investments in hydropower when social concerns are at stake.
Roaming through the Maze of Maize in Northern Ghana. A Systems Approach to Explore the Long-Term Effects of a Food Security Intervention
Authors: Mangnus Ellen , Van Westen A.C.M. (Guus)
Published: October 2018

Central to food security interventions in Sub-Saharan Africa stands the value chain approach. The underlying idea is that connecting farmers to input and output markets and sources of knowledge and technology will enhance their food security status. In spite of positive impacts measured in especially food supply, there is scant evidence of the long-term effects on food security. For a better grasp of the impacts of a maize value chain intervention in North Ghana, we have experimented with an approach that focuses on interactions and feedback loops between the value chain and its local context. Such approach allowed us to identify dynamics that affect food security in the long run. In the case of Northern Ghana farming systems, household income and diets are increasingly dependent on maize, which increases risk of food insecurity in case of climate setbacks or market shocks. The exercise reveals how a linear value chain approach obscures the dynamic effects cascading from the intervention that may actually hamper food security in the long run. A systems approach may help to better grasp the consequences of external interventions at the local level.
Forming a Social Partnership between a Small Social Enterprise and a Large Corporation: A Case of the Joint Platform, H-JUMP
Authors: Park Jaehong , Hwang Kumju , Kim Sang-Joon
Published: October 2018

This study illustrates how partnerships in asymmetric power relationships, such as social enterprises and large established firms, can be made in the context of social partnership. We acknowledge that partnerships with large corporations can help social enterprises to overcome several structural barriers they may encounter in forming and sustaining their business models. However, these partnerships can be situated in asymmetric power relationships as resource dependence unfolds. Thus, paradoxically, a partnership with a large corporation can be another challenge to the social enterprise. In absorbing these constraints, we propose that a social enterprise should come up with a stylized social partnership model, utilizing their social capital when engaging in the formation of such a power-imbalanced partnership. We conducted an in-depth case study which presents how a small and young social enterprise can achieve a viable partnership with a large, established firm. Our findings show that social enterprises can form and develop long-term sustainable partnerships with large corporations using a stylized platform strategy with social capital and relational governance in the process of collective value creation.
Assessment of Cultivated Land Productivity and Its Spatial Differentiation in Dongting Lake Region: A Case Study of Yuanjiang City, Hunan Province
Authors: Zhao Chong , Zhou Yong , Li Xigui , Xiao Pengnan , Jiang Jinhui
Published: October 2018

Cultivated land is an important carrier of grain production, and scientific assessing of cultivated land productivity is of great significance to ensure food security. This paper assessed the overall productivity of cultivated land in Yuanjiang city from the perspectives of quantitative structure, spatial distribution and correlation with national land use. We applied statistical and GIS (geographic information system) spatial analysis methods to 16 secondary indicators of productivity. The results showed that the productivity index of cultivated land ranged from 1642.79 to 4140.09, concentrated in classes 2–6, among the most productive of 15 classes in total. The cultivated productivity indexes of most towns showed quantitative structural patterns of “inverted pyramid” and “dumbbell” types. Cultivated lands with high productivity showed a spatial distribution that decreased from the north to the south and increased from the center to the periphery. The spatial distribution of the higher-level classes in the cultivated land productivity index and the national cultivated land use index was similar. The correlation coefficient between the indexes for cultivated land productivity and the annual standard crop yield was 0.8817, implying that the index reflected local grain production capacity very well. In general, the research offered a reference and technical support for the sustainable use of cultivated land resources and enhanced regional cultivated land production capacity.
Impact of Information Intervention on the Recycling Behavior of Individuals with Different Value Orientations—An Experimental Study on Express Delivery Packaging Waste
Authors: Chen Feiyu , Chen Hong , Yang Jiahui , Long Ruyin , Li Qianwen
Published: October 2018

Changing residents’ recycling behavior at the source of waste generation is a fundamental way to solve the environmental and resource problems caused by express delivery packaging waste. Information intervention is a common means to help transform individual environmental protection behavior. In this study, behavioral experiments were used to examine the changes in individual express packaging waste recycling behaviors under the intervention of written and pictorial information. Differences in information processing and behavior decision-making among individuals (N = 660) categorized as self-interested, pro-relation, or pro-social were analyzed. Results showed that (1) recycling behavior is divided into persuasive, purchasing, disposal, and civil behavior. (2) Recycling behavior is differs significantly due to an individual’s education background, state of health, and interpersonal relationships. (3) Both written and pictorial information can positively change an individual’s recycling behavior, and their effectiveness is not significantly different. (4) Pictorial information has a stronger impact on purchasing behavior than written information. (5) Feedback from written information cannot effectively promote the overall recycling behavior of self-interested groups, but it can improve the overall recycling behavior of pro-relationship groups and pro-social groups. (6) Information intervention cannot effectively impact civil behavior, even among pro-social individuals. The research provides an important theoretical reference and practical basis for improving individual recycling behavior at its source.
New Similarity Measures of Single-Valued Neutrosophic Multisets Based on the Decomposition Theorem and Its Application in Medical Diagnosis
Authors: Hu Qingqing , Zhang Xiaohong
Published: October 2018

Cut sets, decomposition theorem and representation theorem have a great influence on the realization of the transformation of fuzzy sets and classical sets, and the single-valued neutrosophic multisets (SVNMSs) as the generalization of fuzzy sets, which cut sets, decomposition theorem and representation theorem have the similar effects, so they need to be studied in depth. In this paper, the decomposition theorem, representation theorem and the application of a new similarity measures of SVNMSs are studied by using theoretical analysis and calculations. The following are the main results: (1) The notions, operation and operational properties of the cut sets and strong cut sets of SVNMSs are introduced and discussed; (2) The decomposition theorem and representation theorem of SVNMSs are established and rigorously proved. The decomposition theorem and the representation theorem of SVNMSs are the theoretical basis for the development of SVNMSs. The decomposition theorem provides a new idea for solving the problem of SVNMSs, and points out the direction for the principle of expansion of SVNMSs. (3) Based on the decomposition theorem and representation theorem of SVNMSs, a new notion of similarity measure of SVNMSs is proposed by applying triple integral. And this new similarity is applied to the practical problem of multicriteria decision-making, which explains the efficacy and practicability of this decision-making method. The new similarity is not only a way to solve the problem of multi-attribute decision-making, but also contains an important mathematical idea, that is, the idea of transformation.
A Note on Modified Degenerate Gamma and Laplace Transformation
Authors: Kim YunJae , Kim Byung Moon , Jang Lee-Chae , Kwon Jongkyum
Published: October 2018

Kim-Kim studied some properties of the degenerate gamma and degenerate Laplace transformation and obtained their properties. In this paper, we define modified degenerate gamma and modified degenerate Laplace transformation and investigate some properties and formulas related to them.
Global Mittag—Leffler Synchronization for Neural Networks Modeled by Impulsive Caputo Fractional Differential Equations with Distributed Delays
Authors: Agarwal Ravi , Hristova Snezhana , O’Regan Donal
Published: October 2018

The synchronization problem for impulsive fractional-order neural networks with both time-varying bounded and distributed delays is studied. We study the case when the neural networks and the fractional derivatives of all neurons depend significantly on the moments of impulses and we consider both the cases of state coupling controllers and output coupling controllers. The fractional generalization of the Razumikhin method and Lyapunov functions is applied. Initially, a brief overview of the basic fractional derivatives of Lyapunov functions used in the literature is given. Some sufficient conditions are derived to realize the global Mittag–Leffler synchronization of impulsive fractional-order neural networks. Our results are illustrated with examples.
Missing Data Probability Estimation-Based Bayesian Outlier Detection for Plant-Wide Processes with Multisampling Rates
Authors: Tian Ying , Yin Zhong , Huang Miao
Published: October 2018

Traditional outlier detection methods assume that the sampling time and interval are the same. However, for plant-wide processes, since the signal change rate of different devices may vary by several orders of magnitude, the measured data in real-world systems usually have different sampling rates, resulting in missing data. To achieve reliable outlier detection, a missing data probability estimation-based Bayesian outlier detection method is adopted. In this strategy, the expectation–maximization (EM) algorithm is first used to estimate the likelihood probability of different evidence under different process statuses by using the history dataset which contains complete and incomplete samplings. Secondly, the realization of unavailable parts in the monitoring point is estimated as a probability through historical data and online moving horizon data. Bayesian theory and likelihood probability are then used to calculate the outlier posterior probability of different realization. Finally, the outlier probability of the monitoring sampling is calculated by the probability of different realizations and the corresponding outlier probability. Using the Tennessee Eastman (TE) dataset, a simulation indicates that the proposed method exhibits a significant improvement over the complete data method.
Multiwalled Carbon Nanotube for One-Step Cleanup of 21 Mycotoxins in Corn and Wheat Prior to Ultraperformance Liquid Chromatography–Tandem Mass Spectrometry Analysis
Authors: Jiang Dongmei , Wei Dizhe , Wang Liuqing , Ma Shuai , Du Yuanfang , Wang Meng
Published: October 2018

One-step solid-phase extraction (SPE) using a multiwalled carbon nanotube (MWCNT) for simultaneous analysis of 21 mycotoxins, including nine trichothecenes, zearalenone (ZEN) and its derivatives, four aflatoxins, and two ochratoxins, in corn and wheat was developed. Several key parameters affecting the performance of the one-step SPE procedure—types of MWCNT, combinations with five sorbents (octadecylsilyl (C18), hydrophilic–lipophilic balance (HLB), mixed-mode cationic exchange (MCX), silica gel, and amino-propyl (NH2)), and filling amounts of the MWCNTs—were thoroughly investigated. The combination of 20 mg carboxylic MWCNT and 200 mg C18 was proven to be the most effective, allowing the quantification of all analyzed mycotoxins in corn and wheat. Under the optimized cleanup procedure prior to ultraperformance liquid chromatography–tandem mass spectrometry (UPLC–MS/MS) analysis, the method was validated by analyzing samples spiked at the limit of quantification (LOQ), two-times LOQ, and 10-times LOQ. Satisfactory linearity (r2 ≥ 0.9910), high sensitivity (LOQ in different ranges of 0.5–25 μg L−1), good recovery (75.6–110.3%), and acceptable precision (relative standard deviation (RSD), 0.3–10.7%) were obtained. The applicability of the method was further confirmed using raw samples of corn and wheat. In conclusion, the established method was rapid, simple and reliable for simultaneous analysis of 21 mycotoxins in corn and wheat.
Strain-Dependent Consequences of Zika Virus Infection and Differential Impact on Neural Development
Authors: Goodfellow Forrest T. , Willard Katherine A. , Wu Xian , Scoville Shelley , Stice Steven L. , Brindley Melinda A.
Published: October 2018

Maternal infection with Zika virus (ZIKV) during pregnancy can result in neonatal abnormalities, including neurological dysfunction and microcephaly. Experimental models of congenital Zika syndrome identified neural progenitor cells as a target of viral infection. Neural progenitor cells are responsible for populating the developing central nervous system with neurons and glia. Neural progenitor dysfunction can lead to severe birth defects, namely, lissencephaly, microcephaly, and cognitive deficits. For this study, the consequences of ZIKV infection in human pluripotent stem cell-derived neural progenitor (hNP) cells and neurons were evaluated. ZIKV isolates from Asian and African lineages displayed lineage-specific replication kinetics, cytopathic effects, and impacts on hNP function and neuronal differentiation. The currently circulating ZIKV isolates exhibit a unique profile of virulence, cytopathic effect, and impaired cellular functions that likely contribute to the pathological mechanism of congenital Zika syndrome. The authors found that infection with Asian-lineage ZIKV isolates impaired the proliferation and migration of hNP cells, and neuron maturation. In contrast, the African-lineage infections resulted in abrupt and extensive cell death. This work furthers the understanding of ZIKV-induced brain pathology.
Potential Application of Bacteriophages in Enrichment Culture for Improved Prenatal Streptococcus agalactiae Screening
Authors: Uchiyama Jumpei , Matsui Hidehito , Murakami Hironobu , Kato Shin-ichiro , Watanabe Naoki , Nasukawa Tadahiro , Mizukami Keijiro , Ogata Masaya , Sakaguchi Masahiro , Matsuzaki Shigenobu , Hanaki Hideaki
Published: October 2018

Vertical transmission of Streptococcus agalactiae can cause neonatal infections. A culture test in the late stage of pregnancy is used to screen for the presence of maternal S. agalactiae for intrapartum antibiotic prophylaxis. For the test, a vaginal–rectal sample is recommended to be enriched, followed by bacterial identification. In some cases, Enterococcus faecalis overgrows in the enrichment culture. Consequently, the identification test yields false-negative results. Bacteriophages (phages) can be used as antimicrobial materials. Here, we explored the feasibility of using phages to minimize false-negative results in an experimental setting. Phage mixture was prepared using three phages that specifically infect E. faecalis: phiEF24C, phiEF17H, and phiM1EF22. The mixture inhibited the growth of 86.7% (26/30) of vaginal E. faecalis strains. The simple coculture of E. faecalis and S. agalactiae was used as an experimental enrichment model. Phage mixture treatment led to suppression of E. faecalis growth and facilitation of S. agalactiae growth. In addition, testing several sets of S. agalactiae and E. faecalis strains, the treatment with phage mixture in the enrichment improved S. agalactiae detection on chromogenic agar. Our results suggest that the phage mixture can be usefully employed in the S. agalactiae culture test to increase test accuracy.
Derivation of the Spatial Distribution of Free Water Storage Capacity Based on Topographic Index
Authors: Tong Bingxing , Li Zhijia , Yao Cheng , Wang Jingfeng , Huang Yingchun
Published: October 2018

Free water storage capacity, an important characteristic of land surface related to runoff process, has a significant influence on runoff generation and separation. It is thus necessary to derive reasonable spatial distribution of free water storage capacity for rainfall-runoff simulation, especially in distributed modeling. In this paper, a topographic index based approach is proposed for the derivation of free water storage capacity spatial distribution. The topographic index, which can be obtained from digital elevation model (DEM), are used to establish a functional relationship with free water storage capacity in the proposed approach. In this case, the spatial variability of free water storage capacity can be directly estimated from the characteristics of watershed topography. This approach was tested at two medium sized watersheds, including Changhua and Chenhe, with the drainage areas of 905 km2 and 1395 km2, respectively. The results show that locations with larger values of free water storage capacity generally correspond to locations with higher topographic index values, such as riparian region. The estimated spatial distribution of free water storage capacity is also used in a distributed, grid-based Xinanjiang model to simulate 10 flood events for Chenhe Watershed and 17 flood events for Changhua Watershed. Our analysis indicates that the proposed approach based on topographic index can produce reasonable spatial variability of free water storage capacity and is more suitable for flood simulation.
Model-Based Analysis of Increased Loads on the Performance of Activated Sludge and Waste Stabilization Ponds
Authors: Ho Long , Pompeu Cassia , Van Echelpoel Wout , Thas Olivier , Goethals Peter
Published: October 2018

In a way to counter criticism on low cost-effective conventional activated sludge (AS) technology, waste stabilization ponds (WSPs) offer a valid alternative for wastewater treatment due to their simple and inexpensive operation. To evaluate this alternative with respect to its robustness and resilience capacity, we perform in silico experiments of different peak-load scenarios in two mathematical models representing the two systems. A systematic process of quality assurance for these virtual experiments is implemented, including sensitivity and identifiability analysis, with non-linear error propagation. Moreover, model calibration of a 210-day real experiment with 31 days of increased load was added to the evaluation. Generally speaking, increased-load scenarios run in silico showed that WSP systems are more resilient towards intermediate disturbances, hence, are suitable to treat not only municipal wastewater, but also industrial wastewater, such as poultry wastewater, and paperboard wastewater. However, when disturbances are extreme (over 7000 mg COD·L−1), the common design of the natural system fails to perform better than AS. Besides, the application of sensitivity analysis reveals the most influential parameters on the performance of the two systems. In the AS system, parameters related to autotrophic bacteria have the highest influence on the dynamics of particulate organic matter, while nitrogen removal is largely driven by nitrification and denitrification. Conversely, with an insignificant contribution of heterotrophs, the nutrient removal in the pond system is mostly done by algal assimilation. Furthermore, this systematic model-based analysis proved to be a suitable means for investigating the maximum load of wastewater treatment systems, and from that avoiding environmental problems and high economic costs for cleaning surface waters after severe overload events.
An Unsteady Boundary Element Model for Hydrodynamic Performance of a Multi-Blade Vertical-Axis Tidal Turbine
Authors: Li Guangnian , Chen Qingren , Gu Hanbin
Published: October 2018

An unsteady boundary element model is developed to simulate the unsteady flow induced by the motion of a multi-blade vertical axis turbine. The distribution of the sources, bound vortices and wake vortices of the blades are given in detail. In addition, to make the numerical solution more robust, the Kutta condition is also introduced. The developed model is used to predict the hydrodynamic performance of a vertical axis tidal turbine and is validated by comparison with experimental data and other numerical solutions available in the literature. Good agreement is achieved and the calculation of the proposed model is simpler and more efficient than prior numerical solutions. The proposed model shows its capability for future profile design and optimization of vertical axis tidal turbines.
A Single Tube Contactor for Testing Membrane Ozonation
Authors: Zoumpouli Garyfalia A. , Baker Robert , Taylor Caitlin M. , Chippendale Matthew J. , Smithers Chloë , Ho Sean S. X. , Mattia Davide , Chew Y. M. John , Wenk Jannis
Published: October 2018

A membrane ozonation contactor was built to investigate ozonation using tubular membranes and inform computational fluid dynamics (CFD) studies. Non-porous tubular polydimethylsiloxane (PDMS) membranes of 1.0–3.2 mm inner diameter were tested at ozone gas concentrations of 110–200 g/m3 and liquid side velocities of 0.002–0.226 m/s. The dissolved ozone concentration could be adjusted to up to 14 mg O3/L and increased with decreasing membrane diameter and liquid side velocity. Experimental mass transfer coefficients and molar fluxes of ozone were 2.4 × 10−6 m/s and 1.1 × 10−5 mol/(m2 s), respectively, for the smallest membrane. CFD modelling could predict the final ozone concentrations but slightly overestimated mass transfer coefficients and molar fluxes of ozone. Model contaminant degradation experiments and UV light absorption measurements of ozonated water samples in both ozone (O3) and peroxone (H2O2/O3) reaction systems in pure water, river water, wastewater effluent, and solutions containing humic acid show that the contactor system can be used to generate information on the reactivity of ozone with different water matrices. Combining simple membrane contactors with CFD allows for prediction of ozonation performance under a variety of conditions, leading to improved bubble-less ozone systems for water treatment.
Verification and Correction of the Hydrologic Routing in the Soil and Water Assessment Tool
Authors: Nguyen Van Tam , Dietrich Jörg , Uniyal Bhumika , Tran Dang An
Published: October 2018

The Soil and Water Assessment Tool (SWAT) is one of the most widely used eco-hydrological models. SWAT has been undergoing constant changes since its development. However, compartment review and testing of SWAT, especially the hydrologic routing functions, are comparably limited. In this study, the daily hydrologic routing subroutines of different SWAT versions were reviewed and tested using a well observed segment of the Weser River located in Germany. Results show several problems with the routing subroutines of SWAT. The variable storage subroutine of SWAT (Revision 664) does not transform the stream flow. Unphysical results could be obtained with the variable storage routing of SWAT (Revision 528). The Muskingum subroutine of SWAT (Revisions 664 and 528) overestimates daily channel evaporation (resulting in a bias of up to 6.3% in streamflow in our case studies) and underestimates daily transmission losses. Simulated results show that the timing and shape of flood waves, as well as the volume of low flows, could be improved with a corrected Muskingum subroutine. Based on the results of this study, we suggest that the SWAT user community review their existing SWAT models to see how the aforementioned issues will affect their methods, findings, and conclusions.
Automated Floodway Determination Using Particle Swarm Optimization
Authors: Cho Huidae , Yee Tien M. , Heo Joonghyeok
Published: October 2018

The floodway plays an important role in flood modeling. In the United States, the Federal Emergency Management Agency requires the floodway to be determined using an approved computer program for developed communities. It is a local government’s interest to minimize the floodway area because encroachment areas may be permitted for human activities. However, manual determination of the floodway can be time-consuming and subjective depending on the modeler’s knowledge and judgments, and may not necessarily produce a small floodway especially when there are many cross sections because of their correlation. Very little work has been done in terms of floodway optimization. In this study, we propose an optimization method for minimizing the floodway area using the Isolated-Speciation-based Particle Swarm Optimization algorithm and the Hydrologic Engineering Center’s River Analysis System (HEC-RAS). This method optimizes the floodway by defining an objective function that considers the floodway area and hydraulic requirements, and automating operations of HEC-RAS. We used a floodway model provided by HEC-RAS and compared the proposed, manual, and default HEC-RAS methods. The proposed method consistently improved the objective function value by 1–40%. We believe that this method can provide an automated tool for optimizing the floodway model using HEC-RAS.
Synthesis of functionalised β-keto amides by aminoacylation/domino fragmentation of β-enamino amides
Authors: Yanev Pavel , Angelov Plamen
Published: October 2018

Ethylenediamine-derived β-enamino amides are used as equivalents of amide enolate synthons in C-acylation reactions with N-protected amino acids. Domino fragmentation of the obtained intermediates leads to functionalised β-keto amides, bearing a protected amino group in their side chain.