bluuebunny/crossref_metadata_2025 huggingface dataset:
Shallow Landslide Prediction Using a Novel Hybrid Functional Machine Learning Algorithm
Authors: Tien Bui Dieu , Shahabi Himan , Omidvar Ebrahim , Shirzadi Ataollah , Geertsema Marten , Clague John , Khosravi Khabat , Pradhan Biswajeet , Pham Binh , Chapi Kamran , Barati Zahra , Bin Ahmad Baharin , Rahmani Hosein , Gróf Gyula , Lee Saro
Published: April 2019

We used a novel hybrid functional machine learning algorithm to predict the spatial distribution of landslides in the Sarkhoon watershed, Iran. We developed a new ensemble model which is a combination of a functional algorithm, stochastic gradient descent (SGD) and an AdaBoost (AB) Meta classifier namely ABSGD model to predict the landslides. The model incorporates 20 landslide conditioning factors, which we ranked using the least-square support vector machine (LSSVM) technique. For the modeling, we considered 98 landslide locations, of which 70% (79) were used for training and 30% (19) for validation processes. Model validation was performed using sensitivity, specificity, accuracy, the root mean square error (RMSE) and the area under the receiver operatic characteristic (AUC) curve. We also used soft computing benchmark models, including SGD, logistic regression (LR), logistic model tree (LMT) and functional tree (FT) algorithms for model validation and comparison. The selected conditioning factors were significant in landslide occurrence but distance to road was found to be the most important factor. The ABSGD model (AUC= 0.860) outperformed the LR (0.797), SGD (0.776), LMT (0.740) and FT (0.734) models. Our results confirm that the combined use of a functional algorithm and a Meta classifier prevents over-fitting, reduces noise and enhances the power prediction of the individual SGD algorithm for the spatial prediction of landslides.
Variable-Fidelity Simulation Models and Sparse Gradient Updates for Cost-Efficient Optimization of Compact Antenna Input Characteristics
Authors: Koziel Slawomir , Pietrenko-Dabrowska Anna
Published: April 2019

Design of antennas for the Internet of Things (IoT) applications requires taking into account several performance figures, both electrical (e.g., impedance matching) and field (gain, radiation pattern), but also physical constraints, primarily concerning size limitation. Fulfillment of stringent specifications necessitates the development of topologically complex structures described by a large number of geometry parameters that need tuning. Conventional optimization procedures are typically too expensive when the antenna is evaluated using high-fidelity electromagnetic (EM) analysis, otherwise required to ensure accuracy. This paper proposes a novel surrogate-assisted optimization algorithm for computationally efficient design optimization of antenna structures. In the paper, the optimization of antenna input characteristic is presented, specifically, minimization of the antenna reflection coefficient in a given bandwidth. Our methodology involves variable-fidelity EM simulations as well as a dedicated procedure to reduce the cost of estimating the antenna response gradients. The latter is based on monitoring the variations of the antenna response sensitivities along the optimization path. The procedure suppresses the finite-differentiation-based sensitivity updates for variables that exhibit stable gradient behavior. The proposed algorithm is validated using three compact wideband antennas and demonstrated to outperform both the conventional trust region algorithm and the pattern search procedure, as well as surrogate-based procedures while retaining acceptable design quality.
Effect of Epoxy Resin on the Actuating Performance of Piezoelectric Fiber Composites
Authors: Wang Xiaoyu , Yuan Xi , Wu Mingliang , Gao Feng , Yan Xuemei , Zhou Kechao , Zhang Dou
Published: April 2019

Piezoelectric fiber composites (PFC) have shown excellent performance in the areas of vibration control and deformation control. The viscosity and rigidity of the epoxy resin before and after curing, respectively, were very important factors that affected the performance of PFC. In this paper, Aradite 2020, DP 460, and DP 490 epoxy resins, with the viscosities of 0.15, 25.0, and 250.0 Pa·s, respectively, were employed to encapsulate the piezoelectric fiber composite. The PFC that was packaged with Araldite 2020 had the best free strain of 1420 ppm and tip displacement of 17.8 mm. DP 490 caused the lowest performance of PFC, due to the highest viscosity. When the environmental temperature increased from −40 to +80 °C, the free strain of PFC with Aradite 2020 increased at first and then decreased, reaching a maximum value of 1440 ppm at 30 °C, which was mainly related to the mismatch of the resin/ceramic thermal expansion coefficient.
Highly Sensitive and Durable Structured Fibre Sensors for Low-Pressure Measurement in Smart Skin
Authors: Yang Bao , Liu Su , Wang Xi , Yin Rong , Xiong Ying , Tao Xiaoming
Published: April 2019

Precise measurements of low pressure are highly necessary for many applications. This study developed novel structured fibre sensors embedded in silicone, forming smart skin with high sensitivity, high durability, and good immunity to crosstalk for precise measurement of pressure below 10 kPa. The transduction principle is that an applied pressure leads to bending and stretching of silicone and optical fibre over a purposely made groove and induces the axial strain in the gratings. The fabricated sensor showed high pressure sensitivity up to 26.8 pm/kPa and experienced over 1,000,000 cycles compression without obvious variation. A theoretical model of the sensor was presented and verified to have excellent agreement with experimental results. The prototype of smart leg mannequin and wrist pulse measurements indicated that such optical sensors can precisely measure low-pressure and can easily be integrated for smart skins for mapping low pressure on three-dimensional surfaces.
A First Implementation of Underwater Communications in Raw Water Using the 433 MHz Frequency Combined with a Bowtie Antenna
Authors: Ryecroft Samuel , Shaw Andrew , Fergus Paul , Kot Patryk , Hashim Khalid , Moody Adam , Conway Laura
Published: April 2019

In 2016, there were 317 serious water pollution incidents in the UK, with 78,000 locations where businesses discharge controlled quantities of pollutants into rivers; therefore, continuous monitoring is vital. Since 1998, the environment agency has taken over 50 million water samples for water quality monitoring. The Internet of Things has grown phenomenally in recent years, reaching all aspects of our lives, many of these connected devices use wireless sensor networks to relay data to internet-connected nodes, where data can be processed, analyzed and consumed. However, Underwater wireless communications rely mainly on alternative communication methods such as optical and acoustic, with radio frequencies being an under-exploited method. This research presents real world results conducted in the Leeds and Liverpool Canal for the novel use of the 433 MHz radio frequency combined with a bowtie antenna in underwater communications in raw water, achieving distances of 7 m at 1.2 kbps and 5 m at 25 kbps.
An Optimized Node Deployment Solution Based on a Virtual Spring Force Algorithm for Wireless Sensor Network Applications
Authors: Deng Xiaohua , Yu Zhiyong , Tang Rongxin , Qian Xin , Yuan Kai , Liu Shiyun
Published: April 2019

How to effectively deploy all wireless sensors and save a system’s energy consumption is a key issue in current wireless sensor network (WSN) applications. Theoretical analysis has proven that a hexagonal structure is the best topology in the two-dimensional network, which can provide the maximum coverage area with the minimum number of sensor nodes and minimum energy consumption. Recently, many scientists presented their self-deployment strategies based on different virtual forces and discussed the corresponding efficiency via several case studies. However, according to our statistical analysis, some virtual force algorithms, e.g., virtual spring force, can still cause holes or twisted structure in a small region of the final network distribution, which cannot achieve the ideal network topology and will waste the system energy in real applications. In this paper, we first statistically analyzed the convergence and deployment effect of the virtual spring force algorithm to derive our question. Then we presented an optimized strategy that sensor deployment begins from the center of the target region by adding an external central force. At the early stage, the external force will be added to the most peripheral nodes to promote the formation of hexagonal topology and avoid covering holes or unusual structure. Finally, a series of independent simulation experiments and corresponding statistical results proved that our optimized deployment solution is very stable and effective, which can improve the energy consumption of the whole sensor network and be used in the application of a large scale WSN.
Object Tracking Based on Vector Convolutional Network and Discriminant Correlation Filters
Authors: Liu Yuan , Sui Xiubao , Kuang Xiaodong , Liu Chengwei , Gu Guohua , Chen Qian
Published: April 2019

Due to the fast speed and high efficiency, discriminant correlation filter (DCF) has drawn great attention in online object tracking recently. However, with the improvement of performance, the costs are the increase in parameters and the decline of speed. In this paper, we propose a novel visual tracking algorithm, namely VDCFNet, and combine DCF with a vector convolutional network (VCNN). We replace one traditional convolutional filter with two novel vector convolutional filters in the convolutional stage of our network. This enables our model with few memories (only 59 KB) trained offline to learn the generic image features. In the online tracking stage, we propose a coarse-to-fine search strategy to solve drift problems under fast motion. Besides, we update model selectively to speed up and increase robustness. The experiments on OTB benchmarks demonstrate that our proposed VDCFNet can achieve a competitive performance while running over real-time speed.
Effects of Offset Pixel Aperture Width on the Performances of Monochrome CMOS Image Sensors for Depth Extraction
Authors: Lee Jimin , Choi Byoung-Soo , Kim Sang-Hwan , Lee Jewon , Lee Junwoo , Chang Seunghyuk , Park JongHo , Lee Sang-Jin , Shin Jang-Kyoo
Published: April 2019

This paper presents the effects of offset pixel aperture width on the performance of monochrome (MONO) CMOS image sensors (CISs) for a three-dimensional image sensor. Using a technique to integrate the offset pixel aperture (OPA) inside each pixel, the depth information can be acquired using a disparity from OPA patterns. The OPA is classified into two pattern types: Left-offset pixel aperture (LOPA) and right-offset pixel aperture (ROPA). These OPAs are divided into odd and even rows and integrated in a pixel array. To analyze the correlation between the OPA width and the sensor characteristics, experiments were conducted by configuring the test elements group (TEG) regions. The OPA width of the TEG region for the measurement varied in the range of 0.3–0.5 μm. As the aperture width decreased, the disparity of the image increased, while the sensitivity decreased. It is possible to acquire depth information by the disparity obtained from the proposed MONO CIS using the OPA technique without an external light source. Therefore, the proposed MONO CIS with OPA could easily be applied to miniaturized devices. The proposed MONO CIS was designed and manufactured using the 0.11 μm CIS process.
Inspection of Aircraft Wing Panels Using Unmanned Aerial Vehicles
Authors: Tzitzilonis Vasileios , Malandrakis Konstantinos , Zanotti Fragonara Luca , Gonzalez Domingo Jose Angel , Avdelidis Nicolas P. , Tsourdos Antonios , Forster Kevin
Published: April 2019

In large civil aircraft manufacturing, a time-consuming post-production process is the non-destructive inspection of wing panels. This work aims to address this challenge and improve the defects’ detection by performing automated aerial inspection using a small off-the-shelf multirotor. The UAV is equipped with a wide field-of-view camera and an ultraviolet torch for implementing non-invasive imaging inspection. In particular, the UAV is programmed to perform the complete mission and stream video, in real-time, to the ground control station where the defects’ detection algorithm is executed. The proposed platform was mathematically modelled in MATLAB/SIMULINK in order to assess the behaviour of the system using a path following method during the aircraft wing inspection. In addition, two defect detection algorithms were implemented and tested on a dataset containing images obtained during inspection at Airbus facilities. The results show that for the current dataset the proposed methods can identify all the images containing defects.
Joint Source-Relay Optimization for MIMO Full-Duplex Bidirectional Wireless Sensor Networks with SWIPT
Authors: Liu Dan , Wen Zhigang , Liu Xiaoqing , Li Shan , Zou Junwei
Published: April 2019

The simultaneous wireless information and power transfer (SWIPT) technique has been considered as a promising approach to prolong the lifetime of energy-constraint wireless sensor networks (WSNs). In this paper, a multiple-input multiple-output (MIMO) full-duplex (FD) bidirectional wireless sensor network (BWSN) with SWIPT is investigated. Based on minimum total mean-square-error (total-MSE) criterion, a joint optimization problem for source and relay beamforming and source receiving subject to transmitting power and harvesting energy constraints is established. Since this problem is non-convex, an iterative algorithm based on feasible point pursuit-successive convex approximation (FPP-SCA) is derived to obtain a local optimum. Moreover, considering the scenarios in which source and relay nodes equipped with the same and different numbers of antennas, a low-complexity diagonalizing design-based scheme is employed to simplify each non-convex subproblem into convex problems and to reduce the computational complexity. Numerical results of the total-MSE and bit error rate (BER) are implemented to demonstrate the performance of the two different schemes.
State-of-the-Art Internet of Things in Protected Agriculture
Authors: Shi Xiaojie , An Xingshuang , Zhao Qingxue , Liu Huimin , Xia Lianming , Sun Xia , Guo Yemin
Published: April 2019

The Internet of Things (IoT) has tremendous success in health care, smart city, industrial production and so on. Protected agriculture is one of the fields which has broad application prospects of IoT. Protected agriculture is a mode of highly efficient development of modern agriculture that uses artificial techniques to change climatic factors such as temperature, to create environmental conditions suitable for the growth of animals and plants. This review aims to gain insight into the state-of-the-art of IoT applications in protected agriculture and to identify the system structure and key technologies. Therefore, we completed a systematic literature review of IoT research and deployments in protected agriculture over the past 10 years and evaluated the contributions made by different academicians and organizations. Selected references were clustered into three application domains corresponding to plant management, animal farming and food/agricultural product supply traceability. Furthermore, we discussed the challenges along with future research prospects, to help new researchers of this domain understand the current research progress of IoT in protected agriculture and to propose more novel and innovative ideas in the future.
Fall Risk in Older Adults Transitioning between Different Flooring Materials
Authors: Kim Hyung Nam , Lockhart Thurmon E.
Published: April 2019

As there is lack of understanding about the effect of transitioning between different flooring materials on the gait of older adults, this study investigated the effect of transitioning between a carpeted floor and a vinyl floor on the gait characteristics of older adults. Fourteen older (65 years old and over) and 14 younger (18 to 35 years old) adults walked on different transitional floors by measuring various gait parameters. While the older participants had greater toe clearance than their younger counterparts, the older participants had smaller toe clearance on a carpeted floor than on a vinyl floor, which would increase the probability of a trip-induced fall. Further, the study found the slower transitional acceleration of the whole body COM and the increased friction demand, especially during the toe-off phase, rather than heel contact phase, which will lead to a slip-induced fall on a vinyl floor shortly after transitioning from a carpeted floor to a vinyl floor. Although the increased likelihood of a slip or trip accident was found throughout the changes in gait parameters, the older participants did not perceive of slipping and tripping much. Therefore, the elderly are recommended to be made aware of the danger of slipping and tripping while transitioning between different flooring materials.
An On-Line Flow-Injection Sorbent Extraction System Coupled with Flame Atomic Absorption Spectrometry for Thallium Determination Using a PTFE Turning-Packed Column
Authors: Kazantzi Viktoria , Anthemidis Aristidis
Published: April 2019

A novel time-based flow-injection–solid-phase extraction system (FI–SPE) coupled with flame atomic absorption spectrometry (FAAS) for automatic on-line preconcentration and determination of thallium was developed. The efficiency of poly-tetrafluoroethylene (PTFE) turnings packed into a column as sorbent material was investigated for thallium extraction. Total thallium was determined by oxidizing thallium(I) to thallium(III), adding bromine in acidic solution. The formed [TlBr4]− anionic bromo complex was retained onto the PTFE turnings by on-line mixing with sodium diethyl dithiocarbamate (DDTC). The preconcentrated Tl(III)-DDTC complex was then effectively eluted with methyl isobutyl ketone (MIBK) and introduced into the flame atomizer for measurement and quantification. The column proved to be effective, stable, and reproducible, with a long lifetime. The enrichment factor was 105 for 60 s preconcentration time, and the sampling frequency 40 h−1. The detection limit was 1.93 μg L−1, and the relative standard deviation (RSD) was 3.2% at 50.0 μg L−1 concentration. The accuracy of the proposed method was estimated by analyzing certified reference materials and environmental and biological samples.
Regional Inequality and Influencing Factors of Primary PM Emissions in the Yangtze River Delta, China
Authors: Xia Haibin , Wang Hui , Ji Guangxing
Published: April 2019

In recent years, haze pollution has become more and more serious in the Yangtze River Delta (YRD). However, the impact mechanism of socio-economic factors on primary particulate matter (PM) emissions remains unclear. Based on the provincial primary PM emission data in the YRD from 1995 to 2014, this paper used Slope, Theil index, and Stochastic Impacts by Regression on Population, Affluence, and Technology (STIAPAT) models to quantitatively identify the regional differences of primary PM emissions and explore the key influencing factors. The results showed that primary fine particulate matter (PM2.5), inhalable particulate (PM10), and total suspended particulate (TSP) emissions all featured an upward trend of fluctuation over the study period. The regional differences in primary TSP emissions in the YRD region was gradually shrinking and the regional differences of primary PM2.5 and PM10 emissions presented a rising trend of fluctuation. The estimated coefficient of population size, energy structure, and fixed assets investment (FAI) were all significantly positive at the level of 1%. The negative effect of economic growth on energy PM emissions was significant under the level of 1%. The increase of foreign direct investment (FDI) had different effects on primary PM2.5, PM10, and TSP emissions. In addition, the influence of energy intensity on primary PM emission from energy consumption are mainly negative but not significant even under the level of 10%. These conclusions have guiding significance for the formulation of PM emission reduction policy without affecting YRD’s economic development.
Climate Change and Economic Growth: The Role of Environmental Policy Stringency
Authors: de Angelis Enrico Maria , Di Giacomo Marina , Vannoni Davide
Published: April 2019

The paper investigates the relationship between economic growth and environmental quality in the context of the Kuznets curve, which foresees that growth, while initially causing negative externalities for the environment, eventually can be seen also as the solution to environmental degradation. The novelty of the paper is to analyze the role of environmental policies, and in particular the use of market-based and non-market instruments to challenge the pollution plague and mitigate climate change. The results of fixed effects estimates on a sample of 32 countries observed for the period 1992–2012 show the existence of an inverted U-shaped relationship between per capita gross domestic product (GDP) and per-capita CO2 emissions for the quadratic specification, as well as of an N-shaped pattern for the cubic specification. Most importantly, the stringency indexes, i.e., the proxies used to account for environmental regulation, exhibit negative and strongly significant coefficients, suggesting that the policies are effective in reducing environmental damages associated with economic growth.
Application of the Operational Research Method to Determine the Optimum Transport Collection Cycle of Municipal Waste in a Predesignated Urban Area
Authors: Stopka Ondrej , Stopkova Maria , Kampf Rudolf
Published: April 2019

This paper deals with waste management. The aim is to find out whether the number of municipal mixed waste bins can be reduced due to the impact of waste separation and to determine the optimum municipal waste collection cycle within a predesignated area with an existing urban road network. The number of mixed waste bins depends on two factors—household waste volume and household waste composition. Both of these factors have a significant impact on the number of mixed waste bins required, with household waste composition being of particular importance when it comes to calculating the potential reduction in the number of mixed waste bins required due to waste separation. The calculations for the weight and volume of mixed household waste per person and the composition (types) thereof are presented accordingly. The results reveal which types of waste are the most useful in minimising the number of mixed waste bins by up to 30–50%. To determine the optimum waste collection cycle within the predesignated area with a real urban road network, the Nearest Neighbour Search method was applied. In the discussion, the focus is on whether other methods, including the Two-Phase Heuristic approach and the Bellman-Ford Algorithm, could be applied to solve the problem, whereby parameters such as application time and the capacity of the waste collection vehicle are compared.
Carbon Footprint Estimation in Road Construction: La Abundancia–Florencia Case Study
Authors: Espinoza Marianela , Campos Noelia , Yang Rebekah , Ozer Hasan , Aguiar-Moya José P. , Baldi Alejandra , Loría-Salazar Luis G. , Al-Qadi Imad L.
Published: April 2019

The environmental impact of road construction and rehabilitation can be associated with the increase of greenhouse gas (GHG) emissions, which are highly related to climate change. Consequently, departments of transportation have recently focused on the development and implementation of tools to evaluate the performance of projects and minimize GHG emissions. An example is the use of life cycle assessment (LCA) to analyze and quantify the environmental impact of a product, system, or process, from cradle to grave. In this regard, the present case study quantifies the carbon footprint associated with the construction of the La Abundancia–Florencia highway, located in the province of San Carlos in Costa Rica. The analysis is also intended to generate consciousness both in the public and private sectors on the environmental impacts of road construction. After an LCA study, it was determined that the construction of the hot mix asphalt (HMA) layer generates a carbon footprint of 65.8 kg of CO2e per km of road. In addition, it was evident that HMA production generates the greatest environmental impact, among all the considered LCA production and construction stages, with a GHG contribution of 38% to 39% from bitumen only. Consequently, special attention to HMA production is required in order to minimize GHG emissions.
Greenhouse Gas Emissions from Landfills: A Review and Bibliometric Analysis
Authors: Zhang Chengliang , Xu Tong , Feng Hualiang , Chen Shaohua
Published: April 2019

The landfill is an important method of disposal of municipal solid waste. In particular, the landfill is especially vital in many developing countries, with it being the main biodegradable waste disposal method due to its simple management and ability for mass manipulation. Landfills have recently been shown to be an important source of greenhouse gas (GHG) emissions by researchers in different countries. However, few reviews have been conducted within the related fields, which means that there is still a lack of comprehensive understanding related to relevant study achievements. In this study, a bibliometric analysis of articles published from 1999 to 2018 on landfill GHG emissions was presented to assess the current trends, using the Web of Science (WOS) database. The most productive countries/territories, authors and journals were analyzed. Moreover, the overall research structure was characterized based on co-cited references, emerging keywords and reference citations by means of bibliometric analysis. Due to the increasing amount of attention being paid to the GHG emissions and their mitigation methods, this study provided comprehensive bibliometric information on GHG emissions from landfills over the past two decades and highlighted the importance of the development and dissemination of updated knowledge frameworks.
Spatial Pattern of the Unidirectional Trends in Thermal Bioclimatic Indicators in Iran
Authors: Hadi Pour Sahar , Abd Wahab Ahmad , Shahid Shamsuddin , Wang Xiaojun
Published: April 2019

Changes in bioclimatic indicators can provide valuable information on how global warming induced climate change can affect humans, ecology and the environment. Trends in thermal bioclimatic indicators over the diverse climate of Iran were assessed in this study to comprehend their spatio-temporal changes in different climates. The gridded temperature data of Princeton Global Meteorological Forcing with a spatial resolution of 0.25° and temporal extent of 1948–2010 was used for this purpose. Autocorrelation and wavelets analyses were conducted to assess the presence of self-similarity and cycles in the data series. The modified version of the Mann–Kendall (MMK) test was employed to estimate unidirectional trends in 11 thermal bioclimatic indicators through removing the influence of natural cycles on trend significance. A large decrease in the number of grid points showing significant trends was noticed for the MMK in respect to the classical Mann–Kendall (MK) test which indicates that the natural variability of the climate should be taken into consideration in bioclimatic trend analyses in Iran. The unidirectional trends obtained using the MMK test revealed changes in almost all of the bioclimatic indicators in different parts of Iran, which indicates rising temperature have significantly affected the bioclimate of the country. The semi-dry region along the Persian Gulf in the south and mountainous region in the northeast were found to be more affected in terms of the changes in a number of bioclimatic indicators.
Regional Multivariate Indices of Water Use Potential for the Continental United States
Authors: White Jonah D. , Mack Elizabeth A. , Harlan Sharon L. , Krayenhoff E. Scott , Georgescu Matei , Redican Kyle
Published: April 2019

The necessity of freshwater for sustaining human life has prompted the development of numerous estimation techniques and metrics for understanding where, when, and why water is used. While estimates are valuable, techniques for estimating water use vary, and may be difficult to replicate and/or unavailable on an annual basis or at the regional scale. To address these drawbacks, this paper proposes a series of regional indices for the continental United States that could serve as proxies for water use that are based on key variables associated with water use. Regional indices at the county level are computed, compared against each other, and compared to water withdrawal estimates from the United States Geological Survey (USGS). These comparisons highlight differences amongst the derived indices and the water withdrawal estimates. They also demonstrate promise for future development and implementation of related indices, given their similarities with water withdrawal estimates. Using only a small set of variables, these indices achieve some degree of similarity (~20%) to estimates of water withdrawals. The comparative data availability and ease of estimating these indices, as well as the ability to decompose the additive indices into their constituent use categories and constituent variables, renders them practically useful to water managers and other decision makers for identification of locally specific drivers of water use and implementation of more geographically-appropriate policies to manage scarce water resources.
Effects of Vegetation Restoration on Soil Bacterial Communities, Enzyme Activities, and Nutrients of Reconstructed Soil in a Mining Area on the Loess Plateau, China
Authors: Li Pengfei , Zhang Xingchang , Hao Mingde , Cui Yongxing , Zhu Shilei , Zhang Yanjiang
Published: April 2019

Soil microbes are the main driving forces and influencing factors of biochemical reactions in the environment. Study of ecological recovery after mining activities has prompted wider recognition of the importance of microbial diversity to ecosystem recovery; however, the response of soil bacterial communities to vegetation restoration types and soil biochemical properties remains poorly understood. The purpose of this research was to explore the soil bacterial communities and soil biochemical properties at four sampling sites (brushland (BL), forestland (FL), grassland (GL) and unreclaimed land (UL)) on the Loess Plateau, China, to evaluate the effect of vegetation restoration on the reconstructed soil in mining areas. In August 2017, samples were collected at the Heidaigou coal mine dumps. Illumina MiSeq sequencing was used to identify the structure of the soil bacterial community and evaluate its relationships with soil biochemical properties. The results showed that soil biochemical properties (soil organic matter, available phosphorus, urease, sucrase, microbial biomass carbon and microbial biomass nitrogen) were significantly increased in BL, FL and GL relative to UL, indicating that the soil quality was significantly improved by vegetation restoration. In addition, the results showed that the vegetation restoration on the reconstructed soil in the mining area could significantly improve the operational taxonomic units (OTUs), abundance (ACE and Chao1) and diversity (Shannon and Simpson) indices of bacterial community and the dominant phyla were Proteobacteria, Actinobacteria and Acidobacteria. With vegetation restoration, the relative abundance of Proteobacteria and Acidobacteria showed an increasing trend, while that of Actinobacteria showed a decreasing trend, and the dominant phyla were only significantly correlated with a few biochemical properties. Moreover, there were no changes in soil bacterial community structures across the four sampling sites and the response of the bacterial community to biochemical properties was not obvious. This implies that, although the region has experienced about 20 years of vegetation restoration, the microbial community still maintains good stability and lagging response to soil biochemical properties. Since the BL soil had better biochemical properties and higher bacterial richness and diversity, it was recommended as the optimum vegetation restoration type for soil reclamation in this area.
Relationship between Ability-Based Emotional Intelligence, Cognitive Intelligence, and Job Performance
Authors: Nguyen Nhu Ngoc , Nham Phong Tuan , Takahashi Yoshi
Published: April 2019

Based on previous findings, which found that the three facets of ability-based emotional intelligence (EI) have varying effects on job performance, this study investigates the relationship between emotional intelligence, cognitive intelligence (CI), and job performance. The use of a cascade model suggests a progressive pattern, starting from emotion perception, followed by emotional understanding and emotion regulation, with downstream effects on job performance. Considering the advantages and disadvantages of both measurements, we employed the performance-based ability measurement, the Mayer–Salovey–Caruso Emotional Intelligence Test (MSCEIT) and the self-reporting ability EI measurement, Wong Law Emotional Intelligence Scale (WLEIS). Our findings supported the cascade model, but in the case of WLEIS measures, both self-emotion appraisal and others’ emotion appraisal precede emotion regulation, leading to a positive effect on job performance. Moreover, CI moderated the relationship between EI and job performance, such that a decline in CI rendered the relationship more positive. The MSCEIT and WLEIS showed similar results, thus supporting the cascading model and moderating effects.
Application of Cluster Analysis in Marketing Communications in Small and Medium-Sized Enterprises: An Empirical Study in the Slovak Republic
Authors: Ližbetinová Lenka , Štarchoň Peter , Lorincová Silvia , Weberová Dagmar , Průša Petr
Published: April 2019

Creating an effective marketing strategy according to current trends is a key process needed to achieve sustainable growth that can result in attracting a great number of existing as well as potential customers. Moreover, an enterprise’s success is affected by the aforementioned process. The aim of the paper is to determine the clusters of small and medium-sized enterprises operating in the Slovak Republic and the use of marketing communication tools in the future. The research into marketing communications and customer relationship management (CRM) building in companies was carried out in Slovakia in the years 2017 and 2018. In total, 1,009 small and medium-sized enterprises from Slovakia participated in the research. Following a K-means clustering algorithm, three clusters were determined. Descriptive statistics, cluster analysis using K-means clustering, and an analysis of variance (ANOVA) were used to identify no statistically significant difference in terms of the size of enterprises.
Enhancing Employee Creativity for A Sustainable Competitive Advantage through Perceived Human Resource Management Practices and Trust in Management
Authors: Lee Juil , Kim Sangsoon , Lee Jiman , Moon Sungok
Published: April 2019

This study explores the black box of the relationship between perceived human resource management (HRM) practices and employees’ creativity. Building on the literatures on social exchange and creativity, this study advances a moderated mediation framework of the link between perceived HRM practices and employees’ creativity. We develop the argument that the positive relationship between perceived HRM practices and employees’ creativity is mediated by trust in management and that the mediated relationship is stronger for permanent employees than for temporary employees. Our study finds strong support for the moderated mediation model in a survey study of 285 employees in 14 research institutes funded by the Korean government. We discuss the theoretical and practical implications of our findings.
Learning Curve Analysis of Wind Power and Photovoltaics Technology in US: Cost Reduction and the Importance of Research, Development and Demonstration
Authors: Zhou Yi , Gu Alun
Published: April 2019

The strategic transition from fossil energy to renewable energy is an irreversible global trend, but the pace of renewable energy deployment and the path of cost reduction are uncertain. In this paper, a two-factor learning-curve model of wind power and photovoltaics (PV) was established based on the latest empirical data from the United States, and the paths of cost reduction and corresponding social impacts were explored through scenario analysis. The results demonstrate that both of the technologies are undergoing a period of rapid development, with the learning-by-searching ratio (LSR) being greatly improved in comparison with the previous literature. Research, development, and demonstration (RD&D) have contributed to investment cost reduction in the past decade, and the cost difference between high and low RD&D spending scenarios is predicted to be 5.5%, 8.9%, and 11.27% for wind power, utility-scale PV, and residential PV, respectively, in 2030. Although higher RD&D requires more capital, it can effectively promote cost reduction, reduce the total social cost of deploying renewable energy, and reduce the abatement carbon price that is needed to promote deployment. RD&D and the institutional support behind it are of great importance in allowing renewables to penetrate the commercial market and contribute to long-term social welfare.
A Multicriteria Planning Framework to Locate and Select Sustainable Urban Drainage Systems (SUDS) in Consolidated Urban Areas
Authors: Jiménez Ariza Sara Lucía , Martínez José Alejandro , Muñoz Andrés Felipe , Quijano Juan Pablo , Rodríguez Juan Pablo , Camacho Luis Alejandro , Díaz-Granados Mario
Published: April 2019

The implementation of sustainable urban drainage systems (SUDS) is increasing due to their advantages, which transcend runoff control. As a result, it is important to find the appropriate SUDS locations to maximize the benefits for the watershed. This study develops a multiscale methodology for consolidated urban areas that allows the analysis of environmental, social, and economic aspects of SUDS implementation according to multiple objectives (i.e., runoff management, water quality improvements, and amenity generation). This methodology includes three scales: (a) citywide, (b) local, and (c) microscale. The citywide scale involves the definition of objectives through workshops with the participation of the main stakeholders, and the development of spatial analyses to identify (1) priority urban drainage sub-catchments: areas that need intervention, and (2) strategic urban drainage sub-catchments: zones with the opportunity to integrate SUDS due the presence of natural elements or future urban redevelopment plans. At a local scale, prospective areas are analyzed to establish the potential of SUDS implementation. Microscale comprises the use of the results from the previous scales to identify the best SUDS placement. In the latter scale, the SUDS types and treatment trains are selected. The methodology was applied to the city of Bogotá (Colombia) with a population of nearly seven million inhabitants living in an area of approximately 400 km2. Results include: (a) The identification of priority urban drainage sub-catchments, where the implementation of SUDS could bring greater benefits; (b) the determination of strategic urban drainage sub-catchments considering Bogotá’s future urban redevelopment plans, and green and blue-green corridors; and (c) the evaluation of SUDS suitability for public and private areas. We found that the most suitable SUDS types for public areas in Bogotá are tree boxes, cisterns, bioretention zones, green swales, extended dry detention basins, and infiltration trenches, while for private residential areas they are rain barrels, tree boxes, green roofs, and green swales.
A Study on the Preference of Healing Products for Single Office Workers of Various Lifestyles
Authors: Tu Jui-Che , Cui Yang , Liu Li-Xia , Lin Meng-Hui
Published: April 2019

The world has entered an era of singleness, with even Taiwan moving toward the global trend of singleness. Single people are facing criticism over their social values, as well as the psychological pressure caused by work. As a result, how to relieve this pressure and adjust the negative emotions of single people has become a very important issue. Therefore, related healing products that can relax the bodies and minds of single people and provide psychological comfort and a release function are being developed accordingly. In view of this, the purpose of this study is to determine the preference of single office workers with different lifestyles regarding healing products. The lifestyle characteristics and preferences of single office workers were investigated via a questionnaire survey. Through SPSS statistical software, the preference factors of single office workers of different groups regarding different healing products were analyzed, and the lifestyle characteristics and preferences of each group were subsequently obtained. The results show that the lifestyle of single office workers could be divided into three groups. On the whole, single office workers considered healing products to be interesting and impressive with attractive and charming appearances, as well as offer the function of transforming negative emotions. This study hopes that the design principles obtained can provide an important reference for product designers to design relevant healing products for single office workers.
Non-Unique Fixed Point Theorems in Modular Metric Spaces
Authors: Hussain Sharafat
Published: April 2019

This paper is devoted to the study of Ćirić-type non-unique fixed point results in modular metric spaces. We obtain various theorems about a fixed point and periodic points for a self-map on modular spaces which are not necessarily continuous and satisfy certain contractive conditions. Our results extend the results of Ćirić, Pachpatte, and Achari in modular metric spaces.
Optimal Design and Singularity Analysis of a Spatial Parallel Manipulator
Authors: Wu Xiaoyong
Published: April 2019

Optimal design and singularity analysis are two important aspects of mechanism design, and they are discussed within a spatial parallel manipulator in this work. Resorting to matrix transformation, the parametric kinematic model is established, upon which the inverse position and Jacobian are analyzed. As for optimal design, dexterity and payload indices are taken into consideration. From the simulation results, two optimal configurations are obtained, namely, the star-shaped one and the T-shaped one, and they respectively own the best payload performance and the best dexterity performance. Moreover, the concept of shape singularity is introduced and generalized, which is a special type of singularity that will lead to the singularity in all configurations. The shape singularity of the proposed manipulator is indicated by dexterity index and identified by screw theory. A case study is presented to demonstrate the implication of the shape singularity. Both optimal and singular configurations are useful, and new devices can thus be envisaged for this type of application.
Efficient Uncertainty Assessment in EM Problems via Dimensionality Reduction of Polynomial-Chaos Expansions
Authors: Salis Christos , Kantartzis Nikolaos , Zygiridis Theodoros
Published: April 2019

The uncertainties in various Electromagnetic (EM) problems may present a significant effect on the properties of the involved field components, and thus, they must be taken into consideration. However, there are cases when a number of stochastic inputs may feature a low influence on the variability of the outputs of interest. Having this in mind, a dimensionality reduction of the Polynomial Chaos (PC) technique is performed, by firstly applying a sensitivity analysis method to the stochastic inputs of multi-dimensional random problems. Therefore, the computational cost of the PC method is reduced, making it more efficient, as only a trivial accuracy loss is observed. We demonstrate numerical results about EM wave propagation in two test cases and a patch antenna problem. Comparisons with the Monte Carlo and the standard PC techniques prove that satisfying outcomes can be extracted with the proposed dimensionality-reduction technique.
Comparison of the Respiratory Toxicity and Total Cholinesterase Activities in Dimethyl Versus Diethyl Paraoxon-Poisoned Rats
Authors: Houzé Pascal , Hutin Alice , Lejay Marc , Baud Frédéric J.
Published: April 2019

The chemical structure of organophosphate compounds (OPs) is a well-known factor which modifies the acute toxicity of these compounds. We compared ventilation at rest and cholinesterase activities in male Sprague-Dawley rats poisoned with dimethyl paraoxon (DMPO) and diethyl paraoxon (DEPO) at a subcutaneous dose corresponding to 50% of the median lethal dose (MLD). Ventilation at rest was recorded by whole body plethysmography. Total cholinesterase activities were determined by radiometric assay. Both organophosphates decreased significantly the respiratory rate, resulting from an increase in expiratory time. Dimethyl-induced respiratory toxicity spontaneously reversed within 120 min post-injection. Diethyl-induced respiratory toxicity was long-lasting, more than 180 min post-injection. Both organophosphates decreased cholinesterase activities from 10 to 180 min post-injection with the same degree of inhibition of total cholinesterase within an onset at the same times after injection. There were no significant differences in residual cholinesterase activities between dimethyl and diethyl paraoxon groups at any time. The structure of the alkoxy-group is a determinant factor of the late phase of poisoning, conditioning duration of toxicity without significant effects on the magnitude of alteration of respiratory parameters. For same duration and magnitude of cholinesterase inhibition, there was a strong discrepancy in the time-course of effects between the two compounds.
Dynamics of Bacterial and Viral Communities in Paddy Soil with Irrigation and Urea Application
Authors: Li Yuting , Sun Hao , Yang Weichao , Chen Guanxiong , Xu Hui
Published: April 2019

Viruses are ubiquitous in natural systems. By influencing bacterial abundance (BA) and community structure through lysis-lysogenic conversion, viruses are involved in various ecological processes. In agricultural management, nitrogen addition and irrigation should be considered as important factors that can modify soil viral dynamics but have been ignored. In our study, short-term dynamics of autochthonous soil viral and bacterial abundance and diversity after irrigation and urea application were examined in a long-term experimental paddy field. Urea addition delayed the emergence of peak viral abundance for three days, suggesting that viruses are sensitive to N addition. Under short-term eutrophic conditions through urea application, viruses undertake a lysogenic-biased strategy. Moreover, nitrogen-fixing bacteria were most likely specifically lysed in urea-treated soil, which suggests that soil viruses block N accumulation by killing nitrogen-fixing bacteria. To the best of our knowledge, this study is the first to investigate dynamic changes in autochthonous viruses in paddy fields.