bluuebunny/crossref_metadata_2025 huggingface dataset:
Using Sentinel-2 Multispectral Images to Map the Occurrence of the Cossid Moth (Coryphodema tristis) in Eucalyptus Nitens Plantations of Mpumalanga, South Africa
Authors: Kumbula Samuel Takudzwa , Mafongoya Paramu , Peerbhay Kabir Yunus , Lottering Romano Trent , Ismail Riyad
Published: February 2019

Coryphodema tristis is a wood-boring insect, indigenous to South Africa, that has recently been identified as an emerging pest feeding on Eucalyptus nitens, resulting in extensive damage and economic loss. Eucalyptus plantations contributes over 9% to the total exported manufactured goods of South Africa which contributes significantly to the gross domestic product. Currently, the distribution extent of the Coryphodema tristis is unknown and estimated to infest Eucalyptus nitens compartments from less than 1% to nearly 80%, which is certainly a concern for the forestry sector related to the quantity and quality of yield produced. Therefore, the study sought to model the probability of occurrence of Coryphodema tristis on Eucalyptus nitens plantations in Mpumalanga, South Africa, using data from the Sentinel-2 multispectral instrument (MSI). Traditional field surveys were carried out through mass trapping in all compartments (n = 878) of Eucalyptus nitens plantations. Only 371 Eucalyptus nitens compartments were positively identified as infested and were used to generate the Coryphodema tristis presence data. Presence data and spectral features from the area were analysed using the Maxent algorithm. Model performance was evaluated using the receiver operating characteristics (ROC) curve showing the area under the curve (AUC) and True Skill Statistic (TSS) while the performance of predictors was analysed with the jack-knife. Validation of results were conducted using the test data. Using only the occurrence data and Sentinel-2 bands and derived vegetation indices, the Maxent model provided successful results, exhibiting an area under the curve (AUC) of 0.890. The Photosynthetic vigour ratio, Band 5 (Red edge 1), Band 4 (Red), Green NDVI hyper, Band 3 (Green) and Band 12 (SWIR 2) were identified as the most influential predictor variables. Results of this study suggest that remotely sensed derived vegetation indices from cost-effective platforms could play a crucial role in supporting forest pest management strategies and infestation control.
Mapping Impervious Surfaces in Town–Rural Transition Belts Using China’s GF-2 Imagery and Object-Based Deep CNNs
Authors: Fu Yongyong , Liu Kunkun , Shen Zhangquan , Deng Jinsong , Gan Muye , Liu Xinguo , Lu Dongming , Wang Ke
Published: February 2019

Impervious surfaces play an important role in urban planning and sustainable environmental management. High-spatial-resolution (HSR) images containing pure pixels have significant potential for the detailed delineation of land surfaces. However, due to high intraclass variability and low interclass distance, the mapping and monitoring of impervious surfaces in complex town–rural areas using HSR images remains a challenge. The fully convolutional network (FCN) model, a variant of convolution neural networks (CNNs), recently achieved state-of-the-art performance in HSR image classification applications. However, due to the inherent nature of FCN processing, it is challenging for an FCN to precisely capture the detailed information of classification targets. To solve this problem, we propose an object-based deep CNN framework that integrates object-based image analysis (OBIA) with deep CNNs to accurately extract and estimate impervious surfaces. Specifically, we also adopted two widely used transfer learning technologies to expedite the training of deep CNNs. Finally, we compare our approach with conventional OBIA classification and state-of-the-art FCN-based methods, such as FCN-8s and the U-Net methods. Both of these FCN-based methods are well designed for pixel-wise classification applications and have achieved great success. Our results show that the proposed approach effectively identified impervious surfaces, with 93.9% overall accuracy. Compared with the existing methods, i.e., OBIA, FCN-8s and U-Net methods, it shows that our method achieves obviously improvement in accuracy. Our findings also suggest that the classification performance of our proposed method is related to training strategy, indicating that significantly higher accuracy can be achieved through transfer learning by fine-tuning rather than feature extraction. Our approach for the automatic extraction and mapping of impervious surfaces also lays a solid foundation for intelligent monitoring and the management of land use and land cover.
A Discriminative Feature Learning Approach for Remote Sensing Image Retrieval
Authors: Xiong Wei , Lv Yafei , Cui Yaqi , Zhang Xiaohan , Gu Xiangqi
Published: February 2019

Effective feature representations play a decisive role in content-based remote sensing image retrieval (CBRSIR). Recently, learning-based features have been widely used in CBRSIR and they show powerful ability of feature representations. In addition, a significant effort has been made to improve learning-based features from the perspective of the network structure. However, these learning-based features are not sufficiently discriminative for CBRSIR. In this paper, we propose two effective schemes for generating discriminative features for CBRSIR. In the first scheme, the attention mechanism and a new attention module are introduced to the Convolutional Neural Networks (CNNs) structure, causing more attention towards salient features, and the suppression of other features. In the second scheme, a multi-task learning network structure is proposed, to force learning-based features to be more discriminative, with inter-class dispersion and intra-class compaction, through penalizing the distances between the feature representations and their corresponding class centers. Then, a new method for constructing more challenging datasets is first used for remote sensing image retrieval, to better validate our schemes. Extensive experiments on challenging datasets are conducted to evaluate the effectiveness of our two schemes, and the comparison of the results demonstrate that our proposed schemes, especially the fusion of the two schemes, can improve the baseline methods by a significant margin.
Towards Real-Time Building Damage Mapping with Low-Cost UAV Solutions
Authors: Nex Francesco , Duarte Diogo , Steenbeek Anne , Kerle Norman
Published: February 2019

The timely and efficient generation of detailed damage maps is of fundamental importance following disaster events to speed up first responders’ (FR) rescue activities and help trapped victims. Several works dealing with the automated detection of building damages have been published in the last decade. The increasingly widespread availability of inexpensive UAV platforms has also driven their recent adoption for rescue operations (i.e., search and rescue). Their deployment, however, remains largely limited to visual image inspection by skilled operators, limiting their applicability in time-constrained real conditions. This paper proposes a new solution to autonomously map building damages with a commercial UAV in near real-time. The solution integrates different components that allow the live streaming of the images on a laptop and their processing on the fly. Advanced photogrammetric techniques and deep learning algorithms are combined to deliver a true-orthophoto showing the position of building damages, which are already processed by the time the UAV returns to base. These algorithms have been customized to deliver fast results, fulfilling the near real-time requirements. The complete solution has been tested in different conditions, and received positive feedback by the FR involved in the EU funded project INACHUS. Two realistic pilot tests are described in the paper. The achieved results show the great potential of the presented approach, how close the proposed solution is to FR’ expectations, and where more work is still needed.
A Flexible Architecture for Extracting Metro Tunnel Cross Sections from Terrestrial Laser Scanning Point Clouds
Authors: Cao Zhen , Chen Dong , Shi Yufeng , Zhang Zhenxin , Jin Fengxiang , Yun Ting , Xu Sheng , Kang Zhizhong , Zhang Liqiang
Published: February 2019

This paper presents a novel framework to extract metro tunnel cross sections (profiles) from Terrestrial Laser Scanning point clouds. The entire framework consists of two steps: tunnel central axis extraction and cross section determination. In tunnel central extraction, we propose a slice-based method to obtain an initial central axis, which is further divided into linear and nonlinear circular segments by an enhanced Random Sample Consensus (RANSAC) tunnel axis segmentation algorithm. This algorithm transforms the problem of hybrid linear and nonlinear segment extraction into a sole segmentation of linear elements defined at the tangent space rather than raw data space, significantly simplifying the tunnel axis segmentation. The extracted axis segments are then provided as input to the step of the cross section determination which generates the coarse cross-sectional points by intersecting a series of straight lines that rotate orthogonally around the tunnel axis with their local fitted quadric surface, i.e., cylindrical surface. These generated profile points are further refined and densified via solving a constrained nonlinear least squares problem. Our experiments on Nanjing metro tunnel show that the cross sectional fitting error is only 1.69 mm. Compared with the designed radius of the metro tunnel, the RMSE (Root Mean Square Error) of extracted cross sections’ radii only keeps 1.60 mm. We also test our algorithm on another metro tunnel in Shanghai, and the results show that the RMSE of radii only keeps 4.60 mm which is superior to a state-of-the-art method of 6.00 mm. Apart from the accurate geometry, our approach can maintain the correct topology among cross sections, thereby guaranteeing the production of geometric tunnel model without crack defects. Moreover, we prove that our algorithm is insensitive to the missing data and point density.
A Fast Linearly Wavelength Step-Swept Light Source Based on Recirculating Frequency Shifter and Its Application to FBG Sensor Interrogation
Authors: Yuan Quan , Wang Zhaoying , Song Lipei , Lu Zhaoyu , Hu Diannan , Qin Jiaqi , Yang Tianxin
Published: February 2019

A wavelength step-swept light source (WSSL) using a recirculating frequency shifter loop (RFSL) based on a single-side-band (SSB) modulator is proposed, in order to achieve a linear and fast wavelength-sweeping. The swept step can be tuned from 1.2 pm to 128 pm by adjusting a precise and stable radio frequency (RF) signal that is applied to the SSB modulator. The swept rate can be tuned up to 99 kHz in a range of over 5.12 nm. Wavelength-to-time mapping is used to measure static strain-induced or temperature-induced shifting of the reflected central wavelength of a fiber Bragg grating (FBG). Because of the high linearity of the light source, the interrogation linearity of the strain and the temperature are as high as 0.99944 and 0.99946, respectively. When a dynamic periodic strain applied to FBG sensor, the dynamic performance of the FBG sensor is successfully recorded in the time domain and its power spectral density of a fast Fourier transform (FFT) is calculated. The signal-to-noise ratio (SNR) of the power spectral density is over 40 dB for a 100 Hz dynamic strain and the calculated sensitivity is 0.048 με/Hz1/2. A sharp change in the strain frequency from 100 Hz to 500 Hz is captured in real time.
A Chair-Based Unconstrained/Nonintrusive Cuffless Blood Pressure Monitoring System Using a Two-Channel Ballistocardiogram
Authors: Lee Kwang Jin , Roh Jongryun , Cho Dongrae , Hyeong Joonho , Kim Sayup
Published: February 2019

Hypertension is a well-known chronic disease that causes complications such as cardiovascular diseases or stroke, and thus needs to be continuously managed by using a simple system for measuring blood pressure. The existing method for measuring blood pressure uses a wrapping cuff, which makes measuring difficult for patients. To address this problem, cuffless blood pressure measurement methods that detect the peak pressure via signals measured using photoplethysmogram (PPG) and electrocardiogram (ECG) sensors and use it to calculate the pulse transit time (PTT) or pulse wave velocity (PWV) have been studied. However, a drawback of these methods is that a user must be able to recognize and establish contact with the sensor. Furthermore, the peak of the PPG or ECG cannot be detected if the signal quality drops, leading to a decrease in accuracy. In this study, a chair-type system that can monitor blood pressure using polyvinylidene fluoride (PVDF) films in a nonintrusive manner to users was developed. The proposed method also uses instantaneous phase difference (IPD) instead of PTT as the feature value for estimating blood pressure. Experiments were conducted using a blood pressure estimation model created via an artificial neural network (ANN), which showed that IPD could estimate more accurate readings of blood pressure compared to PTT, thus demonstrating the possibility of a nonintrusive blood pressure monitoring system.
Validation of Thigh Angle Estimation Using Inertial Measurement Unit Data against Optical Motion Capture Systems
Authors: Abhayasinghe Nimsiri , Murray Iain , Sharif Bidabadi Shiva
Published: February 2019

Inertial measurement units are commonly used to estimate the orientation of sections of sections of human body in inertial navigation systems. Most of the algorithms used for orientation estimation are computationally expensive and it is difficult to implement them in real-time embedded systems with restricted capabilities. This paper discusses a computationally inexpensive orientation estimation algorithm (Gyro Integration-Based Orientation Filter—GIOF) that is used to estimate the forward and backward swing angle of the thigh (thigh angle) for a vision impaired navigation aid. The algorithm fuses the accelerometer and gyroscope readings to derive the single dimension orientation in such a way that the orientation is corrected using the accelerometer reading when it reads gravity only or otherwise integrate the gyro reading to estimate the orientation. This strategy was used to reduce the drift caused by the gyro integration. The thigh angle estimated by GIOF was compared against the Vicon Optical Motion Capture System and reported a mean correlation of 99.58% for 374 walking trials with a standard deviation of 0.34%. The Root Mean Square Error (RMSE) of the thigh angle estimated by GIOF compared with Vicon measurement was 1.8477°. The computation time on an 8-bit microcontroller running at 8 MHz for GIOF is about a half of that of Complementary Filter implementation. Although GIOF was only implemented and tested for estimating pitch of the IMU, it can be easily extended into 2D to estimate both pitch and roll.
An Unsupervised Multichannel Artifact Detection Method for Sleep EEG Based on Riemannian Geometry
Authors: Saifutdinova Elizaveta , Congedo Marco , Dudysova Daniela , Lhotska Lenka , Koprivova Jana , Gerla Vaclav
Published: February 2019

In biomedical signal processing, we often face the problem of artifacts that distort the original signals. This concerns also sleep recordings, such as EEG. Artifacts may severely affect or even make impossible visual inspection, as well as automatic processing. Many proposed methods concentrate on certain artifact types. Therefore, artifact-free data are often obtained after sequential application of different methods. Moreover, single-channel approaches must be applied to all channels alternately. The aim of this study is to develop a multichannel artifact detection method for multichannel sleep EEG capable of rejecting different artifact types at once. The inspiration for the study is gained from recent advances in the field of Riemannian geometry. The method we propose is tested on real datasets. The performance of the proposed method is measured by comparing detection results with the expert labeling as a reference and evaluated against a simpler method based on Riemannian geometry that has previously been proposed, as well as against the state-of-the-art method FASTER. The obtained results prove the effectiveness of the proposed method.
Electrodeposition of Pd-Pt Nanocomposites on Porous GaN for Electrochemical Nitrite Sensing
Authors: Xi Rui , Zhang Shao-Hui , Zhang Long , Wang Chao , Wang Lu-Jia , Yan Jing-Hui , Pan Ge-Bo
Published: February 2019

In recent years, nitrite pollution has become a subject of great concern for human lives, involving a number of fields, such as environment, food industry and biological process. However, the effective detection of nitrite is an instant demand as well as an unprecedented challenge. Here, a novel nitrite sensor was fabricated by electrochemical deposition of palladium and platinum (Pd-Pt) nanocomposites on porous gallium nitride (PGaN). The obtained Pd-Pt/PGaN sensor provides abundant electrocatalytic sites, endowing it with excellent performances for nitrite detection. The sensor also shows a low detection limit of 0.95 µM, superior linear ampere response and high sensitivity (150 µA/mM for 1 to 300 µM and 73 µA/mM for 300 to 3000 µM) for nitrite. In addition, the Pd-Pt/PGaN sensor was applied and evaluated in the determination of nitrite from the real environmental samples. The experimental results demonstrate that the sensor has good reproducibility and long-term stability. It provides a practical way for rapidly and effectively monitoring nitrite content in the practical application.
Determination of the Porosity Distribution during an Erosion Test Using a Coaxial Line Cell
Authors: Bittner Tilman , Bajodek Mathieu , Bore Thierry , Vourc’h Eric , Scheuermann Alexander
Published: February 2019

The detection of porosity changes within a soil matrix caused by internal erosion is beneficial for a better understanding of the mechanisms that induce and maintain the erosion process. In this paper, an electromagnetic approach using Spatial Time Domain Reflectometry (STDR) and a transmission line model is proposed for this purpose. An original experimental setup consisting of a coaxial cell which acts as an electromagnetic waveguide was developed. It is connected to a transmitter/receiver device both measuring the transmitted and corresponding reflected electromagnetic pulses at the cell entrance. A gradient optimization method based on a computational model for simulating the wave propagation in a transmission line is applied in order to reconstruct the spatial distribution of the soil dielectric permittivity along the cell based on the measured signals and an inversion algorithm. The spatial distribution of the soil porosity is deduced from the dielectric permittivity profile by physically based mixing rules. Experiments were carried out with glass bead mixtures of known dielectric permittivity profiles and subsequently known spatial porosity distributions to validate and to optimize both, the proposed computational model and the inversion algorithm. Erosion experiments were carried out and porosity profiles determined with satisfying spatial resolution were obtained. The RMSE between measured and physically determined porosities varied among less than 3% to 6%. The measurement rate is sufficient to be able to capture the transient process of erosion in the experiments presented here.
Automatic Recognition of Ripening Tomatoes by Combining Multi-Feature Fusion with a Bi-Layer Classification Strategy for Harvesting Robots
Authors: Wu Jingui , Zhang Baohua , Zhou Jun , Xiong Yingjun , Gu Baoxing , Yang Xiaolong
Published: February 2019

Automatic recognition of ripening tomatoes is a main hurdle precluding the replacement of manual labour by robotic harvesting. In this paper, we present a novel automatic algorithm for recognition of ripening tomatoes using an improved method that combines multiple features, feature analysis and selection, a weighted relevance vector machine (RVM) classifier, and a bi-layer classification strategy. The algorithm operates using a two-layer strategy. The first-layer classification strategy aims to identify tomato-containing regions in images using the colour difference information. The second classification strategy is based on a classifier that is trained on multi-medium features. In our proposed algorithm, to simplify the calculation and to improve the recognition efficiency, the processed images are divided into 9 × 9 pixel blocks, and these blocks, rather than single pixels, are considered as the basic units in the classification task. Six colour-related features, namely the Red (R), Green (G), Blue (B), Hue (H), Saturation (S) and Intensity (I) components, respectively, colour components, and five textural features (entropy, energy, correlation, inertial moment and local smoothing) were extracted from pixel blocks. Relevant features and their weights were analysed using the iterative RELIEF (I-RELIEF) algorithm. The image blocks were classified into different categories using a weighted RVM classifier based on the selected relevant features. The final results of tomato recognition were determined by combining the block classification results and the bi-layer classification strategy. The algorithm demonstrated the detection accuracy of 94.90% on 120 images, this suggests that the proposed algorithm is effective and suitable for tomato detection
Numerical and Experimental Evaluation of Error Estimation for Two-Way Ranging Methods
Authors: Lian Sang Cung , Adams Michael , Hörmann Timm , Hesse Marc , Porrmann Mario , Rückert Ulrich
Published: February 2019

The Two-Way Ranging (TWR) method is commonly used for measuring the distance between two wireless transceiver nodes, especially when clock synchronization between the two nodes is not available. For modeling the time-of-flight (TOF) error between two wireless transceiver nodes in TWR, the existing error model, described in the IEEE 802.15.4-2011 standard, is solely based on clock drift. However, it is inadequate for in-depth comparative analysis between different TWR methods. In this paper, we propose a novel TOF Error Estimation Model (TEEM) for TWR methods. Using the proposed model, we evaluate the comparative analysis between different TWR methods. The analytical results were validated with both numerical simulation and experimental results. Moreover, we demonstrate the pitfalls of the symmetric double-sided TWR (SDS-TWR) method, which is the most highlighted TWR method in the literature because of its highly accurate performance on clock-drift error reduction when reply times are symmetric. We argue that alternative double-sided TWR (AltDS-TWR) outperforms SDS-TWR. The argument was verified with both numerical simulation and experimental evaluation results.
Smartphone-Based Activity Recognition for Indoor Localization Using a Convolutional Neural Network
Authors: Zhou Baoding , Yang Jun , Li Qingquan
Published: February 2019

In the indoor environment, the activity of the pedestrian can reflect some semantic information. These activities can be used as the landmarks for indoor localization. In this paper, we propose a pedestrian activities recognition method based on a convolutional neural network. A new convolutional neural network has been designed to learn the proper features automatically. Experiments show that the proposed method achieves approximately 98% accuracy in about 2 s in identifying nine types of activities, including still, walk, upstairs, up elevator, up escalator, down elevator, down escalator, downstairs and turning. Moreover, we have built a pedestrian activity database, which contains more than 6 GB of data of accelerometers, magnetometers, gyroscopes and barometers collected with various types of smartphones. We will make it public to contribute to academic research.
Understanding Eye Movement Signal Characteristics Based on Their Dynamical and Fractal Features
Authors: Harezlak Katarzyna , Kasprowski Pawel
Published: February 2019

Eye movement is one of the biological signals whose exploration may reveal substantial information, enabling greater understanding of the biology of the brain and its mechanisms. In this research, eye movement dynamics were studied in terms of chaotic behavior and self-similarity assessment to provide a description of young, healthy, oculomotor system characteristics. The first of the investigated features is present and advantageous for many biological objects or physiological phenomena, and its vanishing or diminishment may indicate a system pathology. Similarly, exposed self-similarity may prove useful for indicating a young and healthy system characterized by adaptability. For this research, 24 young people with normal vision were involved. Their eye movements were registered with the usage of a head-mounted eye tracker, using infrared oculography, embedded in the sensor, measuring the rotations of the left and the right eye. The influence of the preprocessing step in the form of the application of various filtering methods on the assessment of the final dynamics was also explored. The obtained results confirmed the existence of chaotic behavior in some parts of eye movement signal; however, its strength turned out to be dependent on the filter used. They also exposed the long-range correlation representing self-similarity, although the influence of the applied filters on these outcomes was not unveiled.
Bio-inspired Printed Monopole Antenna Applied to Partial Discharge Detection
Authors: Cruz Josiel do Nascimento , Serres Alexandre Jean René , de Oliveira Adriano Costa , Xavier George Victor Rocha , de Albuquerque Camila Caroline Rodrigues , da Costa Edson Guedes , Freire Raimundo Carlos Silverio
Published: February 2019

A new, bio-inspired printed monopole antenna (PMA) model is applied to monitor partial discharge (PD) activity in high voltage insulating systems. An optimized sensor was obtained by designing a PMA in accordance with the characteristics of the electromagnetic signal produced by PD. An ultra-wideband (UWB) antenna was obtained by applying the truncated ground plane technique. The patch geometry was bio-inspired by that of the Inga Marginata leaf, resulting in a significant reduction in size. To verify the operating frequency and gain of the PMA, measurements were carried out in an anechoic chamber. The results show that the antenna operating bandwidth covers most of the frequency range of PD occurrence. Moreover, the antenna presented a good sensitivity (mean gain of 3.63 dBi). The antenna performance was evaluated through comparative results with the standard IEC 60270 method. For this purpose, simultaneous tests were carried out in a PD generator arrangement, composed by an oil cell with point-to-plane electrode configurations. The developed PMA can be classified as an optimized sensor for PD detection and suitable for substation application, since it is able to measure PD radiated signals with half the voltage levels obtained from the IEC method and is immune to corona discharges.
Explorations of Charm Factors and Development of Fishing in Southern Taiwan Based on Miryoku Engineering and the Analytic Network Process
Authors: Zhang Yang , Liu Shuo-Fang , Wang Kun
Published: February 2019

Fishing is a popular leisure activity all over the world. However, due to the differences in local customs and cultures, fishing shows regional differences. This study aims to explore the charm of fishing in Southern Taiwan. In this study, the Miryoku engineering method was used to analyze and determine the charm characteristics of fishing in Southern Taiwan and draw the EGM evaluation structure chart. Thereafter, with the analytic network process method, the evaluation model was established in order to calculate the weight and ranking of each charm item. Then the weights of the 35 items in the summit, middle and bottom levels were obtained. The analysis results showed that fishing in Southern Taiwan was similar to that in other parts of the world, but the charm factors of fishing in Southern Taiwan had its relaxation and leisure characteristics. According to the analysis results of the charm factors of fishing, we discussed the future development direction of fishing industry based on the charm characteristics of fishing in Southern Taiwan.
Cycling the Smart and Sustainable City: Analyzing EC Policy Documents on Internet of Things, Mobility and Transport, and Smart Cities
Authors: Behrendt Frauke
Published: February 2019

This article asks how cycling, a sustainable form of urban mobility, is discussed in the context of smart cities and the Internet of Things in European Commission (EC) policy documents, and how this compares to discussions around cars. Sustainable forms of transport, such as cycling, are a key issue for cities across the globe, including smart cities, while transport is increasingly becoming part of the Internet of Things (IoT). This article contributes to an understanding of how cars and bicycles are discussed in this context. To do so, 39 relevant EC policy documents (2014–2018) were identified and examined through keyword searches and rigorous document analysis. The results show how the vast majority of policy discussions in this area revolve around cars (including autonomous cars and smart vehicles), while cycling is hardly considered, with a strong affinity between IoT and cars. In addition, recent EC policy debates take place more around IoT than around Smart Cities, while sustainability is not considered much in the IoT context. The conclusion highlights the implications of sustainable urban modes of transport such as cycling being absent from IoT/smart debates, including lack of policy visibility and funding opportunities, underlining the significance of this research, and it also makes policy suggestions for addressing these issues and for future research.
The Impact of Educational Investment on Sustainable Economic Growth in Guangdong, China: A Cointegration and Causality Analysis
Authors: Liao Liping , Du Minzhe , Wang Bing , Yu Yanni
Published: February 2019

Education, as an investment in human capital, is regarded as an important determinant of sustainable economic growth [1,2]. The purpose of this study is to explore the cointegration and causality between the investment in education and sustainable economic growth in Guangdong province by using the panel data of 21 cities from 2000 to 2016. We construct a variable intercept panel data model with an individual fixed effect based on the Cobb-Douglas production function, estimating the contribution of the investment in education to economic growth by introducing lags. The findings show the existence of the feedback causality between education and sustainable economic growth. Also, the results reveal that the local financial investment in education plays a positive and statistically significant role in promoting sustainable economic growth. However, the contribution of the local financial investment in education to economic growth varies in different areas. The investment in education in the Pearl River Delta region have the most obvious pull effects on its regional economy, whereas the Western region takes the second place. Meanwhile, the local financial investment in education for its role in promoting economic growth obviously has a two-year hysteresis effect. These findings have important implications for Guangdong’s solution to the imbalance between regional educational investment and sustainable economic growth.
Evolutionary Game Research on Symmetry of Workers’ Behavior in Coal Mine Enterprises
Authors: Yu Kai , Zhou Lujie , Cao Qinggui , Li Zhen
Published: February 2019

Statistics show that humans’ unsafe behaviors are the main cause of accidents. Because of the asymmetry of game benefits between managers and coal miners, the stability of workers’ behaviors is affected and unsafe behaviors are produced. In this paper, the symmetry of the behavior benefits of coal mine workers is studied, using game theory. In order to observe the dynamic game evolution process of behavioral stability, the paper establishes a system dynamics (SD) model and simulates it. The SD simulation results show that with the continuation of the game, when the benefits for safety managers and workers are asymmetric and the safety manager’s safety inspection benefits are less than the non-inspection benefits, the manager may not conduct safety inspections, which poses a great hidden danger to safety production. Through dynamic incentives to regulate the symmetry of income of coal mine safety managers and coal mine workers, the purpose of enhancing the stability of safety behavior is achieved. The research results of the paper have been successfully applied to coal mine enterprises.
Analysis of the Digital Divide Using Fuzzy Forecasting
Authors: Ziemba Paweł , Becker Jarosław
Published: February 2019

In the countries of the former Eastern Bloc (Central and Eastern Europe) belonging to the European Union, a gradual elimination of the technological gap, greater expenditures, competitiveness and productivity can be noticed. In this context, analysis and forecast of the level of accessibility and use of ICT (information and communication technologies) by households in these countries has become interesting. It allows for the selection of digitally excluded regions, or those threatened with this phenomenon in the coming years (2018–2020). To carry out the analysis, a framework based on fuzzy numbers and the NEAT F-PROMETHEE (New Easy Approach To Fuzzy-PROMETHEE) method was developed. The potential of the fuzzy outranking approach taking into account the uncertainty of input data (criteria and preferences) has been demonstrated as an alternative to the IDI (ICT Development Index) methodology widely used in research on regional ICT development based on composite indices. Research has shown that Estonia is the leader in the area of ICT expansion among households, and in the next three years will definitely maintain its dominant position. Slovenia follows shortly after, followed by Latvia. At the end of the ranking were the countries with the largest percentage in Central and Eastern Europe of population excluded digitally or threatened with this phenomenon; these are: Poland, Slovakia, Bulgaria and, in last place, Romania. Within this framework, the robustness of the obtained rankings to change in the degree of uncertainty of preferences was also examined. It turned out that eliminating the uncertainty of preferences resulted in an increase in the uncertainty of the aggregate, fuzzy grades obtained at the output.
Centipede KCNQ Inhibitor SsTx Also Targets KV1.3
Authors: Du Canwei , Li Jiameng , Shao Zicheng , Mwangi James , Xu Runjia , Tian Huiwen , Mo Guoxiang , Lai Ren , Yang Shilong
Published: February 2019

It was recently discovered that Ssm Spooky Toxin (SsTx) with 53 residues serves as a key killer factor in red-headed centipede’s venom arsenal, due to its potent blockage of the widely expressed KCNQ channels to simultaneously and efficiently disrupt cardiovascular, respiratory, muscular, and nervous systems, suggesting that SsTx is a basic compound for centipedes’ defense and predation. Here, we show that SsTx also inhibits KV1.3 channel, which would amplify the broad-spectrum disruptive effect of blocking KV7 channels. Interestingly, residue R12 in SsTx extends into the selectivity filter to block KV7.4, however, residue K11 in SsTx replaces this ploy when toxin binds on KV1.3. Both SsTx and its mutant SsTx_R12A inhibit cytokines production in T cells without affecting the level of KV1.3 expression. The results further suggest that SsTx is a key molecule for defense and predation in the centipedes’ venoms and it evolves efficient strategy to disturb multiple physiological targets.
Erratum: Thadi A.; et al. Early Investigations and Recent Advances in Intraperitoneal Immunotherapy for Peritoneal Metastasis. Vaccines 2018, 6, 54
Authors: Thadi Anusha , Khalili Marian , Morano William F. , Richard Scott D. , Katz Steven C. , Bowne Wilbur B.
Published: February 2019

The authors wish to make the following corrections to this paper [...]
Evaluation and Analysis of Grid Precipitation Fusion Products in Jinsha River Basin Based on China Meteorological Assimilation Datasets for the SWAT Model
Authors: Guo Dandan , Wang Hantao , Zhang Xiaoxiao , Liu Guodong
Published: February 2019

Highly accurate and high-quality precipitation products that can act as substitutes for ground precipitation observations have important significance for research development in the meteorology and hydrology of river basins. In this paper, statistical analysis methods were employed to quantitatively assess the usage accuracy of three precipitation products, China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS), next-generation Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) and Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), for the Jinsha River Basin, a region characterized by a large spatial scale and complex terrain. The results of statistical analysis show that the three kinds of data have relatively high accuracy on the average grid scale and the correlation coefficients are all greater than 0.8 (CMADS:0.86, IMERG:0.88 and TMPA:0.81). The performance in the average grid scale is superior than that in grid scale. (CMADS: 0.86(basin), 0.6 (grid); IMERG:0.88 (basin),0.71(grid); TMPA:0.81(basin),0.42(grid)). According to the results of hydrological applicability analysis based on SWAT model, the three kinds of data fail to obtain higher accuracy on hydrological simulation. CMADS performs best (NSE:0.55), followed by TMPA (NSE:0.50) and IMERG (NSE:0.45) in the last. On the whole, the three types of satellite precipitation data have high accuracy on statistical analysis and average accuracy on hydrological simulation in the Jinsha River Basin, which have certain hydrological application potential.
MIMIC approach to assessing differential item functioning with control of extreme response style
Authors: Jin Kuan-Yu , Chen Hui-Fang
Published: February 2019

Likert or rating scales may elicit an extreme response style (ERS), which means that responses to scales do not reflect the ability that is meant to be measured. Research has shown that the presence of ERS could lead to biased scores and thus influence the accuracy of differential item functioning (DIF) detection. In this study, a new method under the multiple-indicators multiple-causes (MIMIC) framework is proposed as a means to eliminate the impact of ERS in DIF detection. The findings from a series of simulations showed that a difference in ERS between groups caused inflated false-positive rates and deflated true-positive rates in DIF detection when ERS was not taken into account. The modified MIMIC model, as compared to conventional MIMIC, logistic discriminant function analysis, ordinal logistic regression, and their extensions, could control false-positive rates across situations and yielded trustworthy true-positive rates. An empirical example from a study of Chinese marital resilience was analyzed to demonstrate the proposed model.
Chemical structure of cichorinotoxin, a cyclic lipodepsipeptide that is produced by Pseudomonas cichorii and causes varnish spots on lettuce
Authors: Komatsu Hidekazu , Shirakawa Takashi , Uchiyama Takeo , Hoshino Tsutomu
Published: February 2019

Pseudomonas cichorii, which causes varnish spots on lettuce and seriously damages lettuce production during the summer season in the highland areas of Japan (e.g., Nagano and Iwate prefectures) was isolated. The structure of a toxin produced by this organism was analyzed based on the detailed evaluation of its 2D NMR and FABMS spectra, and this compound has not been reported previously. We propose the name cichorinotoxin for this toxin. In conjunction with the D or L configurations of each amino acid, which were determined by Marfey’s method, we propose the structure of cichorinotoxin to be as follows: 3-hydroxydecanoyl-(Z)-dhThr1-D-Pro2-D-Ala3-D-Ala4-D-Ala5-D-Val6-D-Ala7-(Z)-dhThr8-Ala9-Val10-D-Ile11-Ser12-Ala13-Val14-Ala15-Val16-(Z)-dhThr17-D-alloThr18-Ala19-L-Dab20-Ser21-Val22, and an ester linkage is present between D-alloThr18 and Val22 (dhThr: 2-aminobut-2-enoic acid; Dab: 2,4-diaminobutanoic acid). Thus, the toxin is a lipodepsipeptide with 22 amino acids. The mono- and tetraacetate derivatives and two alkaline hydrolysates, compounds A and B, were prepared. We discuss here the structure–activity relationships between the derivatives and their necrotic activities toward lettuce.
HARMONIZED DECISION‐MAKING IN MANAGING RELIABILITY AND SAFETY
Authors: Ben-Yair Avner , Golenko-Ginzburg Dimitri , Laslo Zohar
Published: February 2019

A hierarchical technical system functioning under random disturbances and being subject to critical failures at the bottom level which may result in an accident or a hazardous condition including environmental safety violations at the upper level is considered. Certain primary elements at the bottom level, together with their corresponding primary failures, can be refined by undertaking technical improvement. The list of the latter is pre‐given as well. Assume that by means of simulation modeling (SM) it is possible to evaluate the increment of the system's reliability by implementing any set of technical improvements. The harmonization models center on determining an optimal sub‐set of technical improvements in order:

either to maximize the system's reliability subject to a restricted budget assigned for the improvements’ implementation, or

to minimize the system's budget subject to a reliability value restricted from below.
CREATION OF KNOWLEDGE - BASED ECONOMY IN THE EUROPEAN UNION: THE MAIN TYPICALITIES AND NEW IDEAS OF CLUSTERIZATION
Authors: Melnikas Borisas
Published: February 2019

Possibilities for the development of new forms of economic, social and technological headway designed to create and further improve economies based on knowledge are analyzed here.

The main emphasis is put on national and regional economic specialization and creation of new networks of clusters in the situation of the development of the European Union. We have found that clusterization oriented towards the increase of efficiency of various national and regional economies is a critical precondition for successful creation of modern economy based on knowledge, both in the whole space of the European Union and particular countries.

Another idea - a concept of creation of regional and cross-regional clusters and their networks also known as ,,economic oazes"‐ is suggested here. It is explained in the paper that in the economies based on knowledge development of clusters and their networks will soon become one of the core forms of economic and technological advancement.
ANALYSIS AND MODELING OF THE LITHUANIAN REAL ESTATE SECTOR
Authors: Zavadskas Edmundas Kazimieras , Ginevičius Romualdas , Kaklauskas Artūras , Banaitis Audrius
Published: February 2019

The model for an efficient real estate sector as suggested by this research is based on the presumption that the efficiency of a real estate sector depends on many macro and micro level variables. The presence of specific macro and micro level variable factors right away imposes objective limitations for efficient activities within the real estate sector. The real estate sector, in the presence of these objective limitations, tries to perform its functions within their bounds with the utmost efficiency. The research aimed at producing a model of a rational real estate sector by undertaking a complex analysis of micro and macro environment factors that affect it and to provide recommendations that would increase its competitive ability. In order to demonstrate the application of the above research by developing a model for an efficient real estate sector, a selection of rational housing investment instruments and lenders will be considered in this paper as a sample.
ENCOURAGING ETHICAL BEHAVIOUR IN PUBLIC ADMINISTRATION BY HUMAN RESOURCE MANAGEMENT
Authors: Dvoráková Zuzana
Published: February 2019

The public administration reform in the Czech Republic set off with a reform of the territorial public administration at the end of the 90s. The reform established a joint public administration model in the territories, power decentralization, and de‐concentration of operative functions from ministries to regions and municipalities. The reform outcomes largely depend on the quality of human resources in public administration, their ethical values, and status in the society. The public sector always needs to solve a traditional ethics dilemma whether public officials serve citizen or politician purposes. The paper is aimed at ethical values in the Czech public administration, ethics dilemmas in the public sector, and human resource management in territorial self‐governments supporting ethical behaviour. An abnormal situation comes into being in the Czech Republic as public officials incline to serving neither citizens nor politicians. Some municipal authorities strive to improve public administration ethics by designing and implementing new HR practices, codes of ethics and anticorruption programmes.
OPERATION AND DEVELOPMENT OF ELECTRONIC MARKETS AS PROGNOSTIC INSTRUMENT FOR BUSINESS PLANNING
Authors: Schieg Martin
Published: February 2019

Strategic planning is crucial for the survival of a company, wide‐ranging decisions about future action must be taken. The information basis for such decisions is often gained from forecasts about the future with more or less accurate probability of the assumed event occurring. Electronic markets have been the subject matter of numerous investigations in recent years and if organized correctly show a high degree of accuracy in forecasting future events relevant to the business of a company. In major enterprises prediction markets have already been used successfully as a new kind of prognostic instrument. It is also suitable, however, for small and medium‐sized enterprises for the gathering and assessment of the information available to the employees. When developing prognostic markets it is necessary to take into consideration psychological factors, which could favour incorrect results.
INFLUENCE OF HEAT TREATMENT ON MICROSTRUCTURAL EVOLUTION AND MECHANICAL CHARACTERISTICS OF AA6061 ALUMINUM ALLOY / TERMINIO APDOROJIMO ĮTAKA ALIUMINIO LYDINIO AA6061 MIKROSTRUKTŪRAI IR MECHANINĖMS SAVYBĖMS
Authors: Chabba Hanae , Gedzevičius Irmantas , Varnauskas Valentinas , Dafir Driss , Belmir Fouzi
Published: February 2019

This study aims to understand the influence of heat treatment on behavior of AA6061 aluminum alloy at room temperature for various heat treatment. Two experimental parameters for this alloy are defined: micro hardness and the electrical resistivity, as a function of heat treatment at ambient temperature. The results show that the heat treatment conditions have an effective influence in mechanical properties of Al-Mg-Si aluminum alloy. This variation of the mechanical properties is the result of microstructural changes which have been observed using optical microscopy. When the material is subjected to a solution heat treatment followed by quenching and artificial aging, its mechanical properties, especially micro hardness and electrical resistivity, reach their highest levels and become very good compared to the other heat treatment applied to the same alloy.
APSAUGINIŲ KOMPOZICINIŲ DANGŲ METALINĖS NIKELIO MATRICOS PAGRINDU TYRIMAS / INVESTIGATION OF PROTECTIVE COMPOSITE COATINGS ON THE BASIS OF NICKEL METAL MATRIX
Authors: Gendvilis Ainis , Škamat Jelena
Published: February 2019

In the present study, the opportunity to improve the coatings properties using re-melting technique is studied. In the aim to determine the influence of the re-melting on the properties of coatings, the experimental study was performed. The surface of S235J0 steel was coated using three different re-melting methods with different heating duration. The mixture of NiCrFeCSiB alloy powders and carbides of WC type was used for spraying. The principal characteristics of the sprayed coatings were examined and compared with each other. The tests allowed concluding that the introduction of the re-melting process of different duration has tangible impact upon the structure, hardness and wearing resistance of the coatings