bluuebunny/crossref_metadata_2025 huggingface dataset:
Repeat Glacier Collapses and Surges in the Amney Machen Mountain Range, Tibet, Possibly Triggered by a Developing Rock-Slope Instability
Authors: Paul Frank
Published: March 2019

Collapsing valley glaciers leaving their bed to rush down a flat hill slope at the speed of a racing car are so far rare events. They have only been reported for the Kolkaglacier (Caucasus) in 2002 and the two glaciers in the Aru mountain range (Tibet) that failed in 2016. Both events have been studied in detail using satellite data and modeling to learn more about the reasons for and processes related to such events. This study reports about a series of so far undocumented glacier collapses that occurred in the Amney Machen mountain range (eastern Tibet) in 2004, 2007, and 2016. All three collapses were associated with a glacier surge, but from 1987 to 1995, the glacier surged without collapsing. The later surges and collapses were likely triggered by a progressing slope instability that released large amounts of ice and rock to the lower glacier tongue, distorting its dynamic stability. The surges and collapses might continue in the future as more ice and rock is available to fall on the glacier. It has been speculated that the development is a direct response to regional temperature increase that destabilized the surrounding hanging glaciers. However, the specific properties of the steep rock slopes and the glacier bed might also have played a role.
Automatic Grassland Cutting Status Detection in the Context of Spatiotemporal Sentinel-1 Imagery Analysis and Artificial Neural Networks
Authors: Taravat Alireza , Wagner Matthias P. , Oppelt Natascha
Published: March 2019

Grassland contributes to carbon storage and animal feed production. Its yield is largely determined by the cutting times of grassland. Previous studies have used remote sensing data for grassland biomass estimation, but only a few studies have focused on SAR remote sensing approaches for automatic grassland cutting status detection. Due to the occurrence of multiple cuttings in a year, it is crucial to effectively monitor grassland cutting events in order to achieve accurate biomass estimations of a whole season. In this study, we examined the capabilities of multilayer perceptron neural networks for automatic grassland cutting status detection using SAR imagery. The proposed model inputs are a time series dataset of VV and VH Sentinel-1 C-band SAR and second-order texture metrics (homogeneity, entropy, contrast and dissimilarity). The proposed approach has been successfully tested on a dataset collected from several fields in Germany in 2016, with an overall accuracy of 85.71% for the validation set.
Extraction of Urban Objects in Cloud Shadows on the basis of Fusion of Airborne LiDAR and Hyperspectral Data
Authors: Man Qixia , Dong Pinliang
Published: March 2019

Feature extraction in cloud shadows is a difficult problem in the field of optical remote sensing. The key to solving this problem is to improve the accuracy of classification algorithms by fusing multi-source remotely sensed data. Hyperspectral data have rich spectral information but highly suffer from cloud shadows, whereas light detection and ranging (LiDAR) data can be acquired from beneath clouds to provide accurate height information. In this study, fused airborne LiDAR and hyperspectral data were used to extract urban objects in cloud shadows using the following steps: (1) a series of LiDAR and hyperspectral metrics were extracted and selected; (2) cloud shadows were extracted; (3) the new proposed approach was used by combining a pixel-based support vector machine (SVM) and object-based classifiers to extract urban objects in cloud shadows; (4) a pixel-based SVM classifier was used for the classification of the whole study area with the selected metrics; (5) a decision-fusion strategy was employed to get the final results for the whole study area; (6) accuracy assessment was conducted. Compared with the SVM classification results, the decision-fusion results of the combined SVM and object-based classifiers show that the overall classification accuracy is improved by 5.00% (from 87.30% to 92.30%). The experimental results confirm that the proposed method is very effective for urban object extraction in cloud shadows and thus improve urban applications such as urban green land management, land use analysis, and impervious surface assessment.
Construction of All-in-Focus Images Assisted by Depth Sensing
Authors: Liu Hang , Li Hengyu , Luo Jun , Xie Shaorong , Sun Yu
Published: March 2019

Multi-focus image fusion is a technique for obtaining an all-in-focus image in which all objects are in focus to extend the limited depth of field (DoF) of an imaging system. Different from traditional RGB-based methods, this paper presents a new multi-focus image fusion method assisted by depth sensing. In this work, a depth sensor is used together with a colour camera to capture images of a scene. A graph-based segmentation algorithm is used to segment the depth map from the depth sensor, and the segmented regions are used to guide a focus algorithm to locate in-focus image blocks from among multi-focus source images to construct the reference all-in-focus image. Five test scenes and six evaluation metrics were used to compare the proposed method and representative state-of-the-art algorithms. Experimental results quantitatively demonstrate that this method outperforms existing methods in both speed and quality (in terms of comprehensive fusion metrics). The generated images can potentially be used as reference all-in-focus images.
Toward Sensor-Based Sleep Monitoring with Electrodermal Activity Measures
Authors: Romine William , Banerjee Tanvi , Goodman Garrett
Published: March 2019

We use self-report and electrodermal activity (EDA) wearable sensor data from 77 nights of sleep of six participants to test the efficacy of EDA data for sleep monitoring. We used factor analysis to find latent factors in the EDA data, and used causal model search to find the most probable graphical model accounting for self-reported sleep efficiency (SE), sleep quality (SQ), and the latent factors in the EDA data. Structural equation modeling was used to confirm fit of the extracted graph to the data. Based on the generated graph, logistic regression and naïve Bayes models were used to test the efficacy of the EDA data in predicting SE and SQ. Six EDA features extracted from the total signal over a night’s sleep could be explained by two latent factors, EDA Magnitude and EDA Storms. EDA Magnitude performed as a strong predictor for SE to aid detection of substantial changes in time asleep. The performance of EDA Magnitude and SE in classifying SQ demonstrates promise for using a wearable sensor for sleep monitoring. However, our data suggest that obtaining a more accurate sensor-based measure of SE will be necessary before smaller changes in SQ can be detected from EDA sensor data alone.
Three-Stage Single-Chambered Microbial Fuel Cell Biosensor Inoculated with Exiguobacterium aestuarii YC211 for Continuous Chromium (VI) Measurement
Authors: Wu Li-Chun , Wang Guey-Horng , Tsai Teh-Hua , Lo Shih-Yu , Cheng Chiu-Yu , Chung Ying-Chien
Published: March 2019

Chromium (VI) [Cr(VI)] compounds display high toxic, mutagenic, and carcinogenic potential. Biological analysis techniques (e.g., such as enzyme-based or cell-based sensors) have been developed to measure Cr(VI); however, these biological elements are sensitive to the environment, limited to measuring trace Cr(VI), and require deployment offsite. In this study, a three-stage single-chambered microbial fuel cell (SCMFC) biosensor inoculated with Exiguobacterium aestuarii YC211 was developed for in situ, real-time, and continuous Cr(VI) measurement. A negative linear relationship was observed between the Cr(VI) concentration (5–30 mg/L) and the voltage output using an SCMFC at 2-min liquid retention time. The theoretical Cr(VI) measurement range of the system could be extended to 5–90 mg/L by connecting three separate SCMFCs in series. The three-stage SCMFC biosensor could accurately measure Cr(VI) concentrations in actual tannery wastewater with low deviations (<7%). After treating the wastewater with the SCMFC, the original inoculated E. aestuarii remained dominant (>92.5%), according to the next-generation sequencing analysis. The stable bacterial community present in the SCMFC favored the reliable performance of the SCMFC biosensor. Thus, the three-stage SCMFC biosensor has potential as an early warning device with wide dynamic range for in situ, real-time, and continuous Cr(VI) measurement of tannery wastewater.
Energy-Efficient Nonuniform Content Edge Pre-Caching to Improve Quality of Service in Fog Radio Access Networks
Authors: Cen Yi , Cen Yigang , Wang Ke , Li Jingcong
Published: March 2019

The fog radio access network (F-RAN) equipped with enhanced remote radio heads (eRRHs), which can pre-store some requested files in the edge cache and support mobile edge computing (MEC). To guarantee the quality-of-service (QoS) and energy efficiency of F-RAN, a proper content caching strategy is necessary to avoid coarse content storing locally in the cache or frequent fetching from a centralized baseband signal processing unit (BBU) pool via backhauls. In this paper we investigate the relationships among eRRH/terminal activities and content requesting in F-RANs, and propose an edge content caching strategy for eRRHs by mining out mobile network behavior information. Especially, to attain the inference for appropriate content caching, we establish a pre-mapping containing content preference information and geographical influence by an efficient non-uniformed accelerated matrix completion algorithm. The energy consumption analysis is given in order to discuss the energy saving properties of the proposed edge content caching strategy. Simulation results demonstrate our theoretical analysis on the inference validity of the pre-mapping construction method in static and dynamic cases, and show the energy efficiency achieved by the proposed edge content pre-caching strategy.
Baseball Player Behavior Classification System Using Long Short-Term Memory with Multimodal Features
Authors: Sun Shih-Wei , Mou Ting-Chen , Fang Chih-Chieh , Chang Pao-Chi , Hua Kai-Lung , Shih Huang-Chia
Published: March 2019

In this paper, a preliminary baseball player behavior classification system is proposed. By using multiple IoT sensors and cameras, the proposed method accurately recognizes many of baseball players’ behaviors by analyzing signals from heterogeneous sensors. The contribution of this paper is threefold: (i) signals from a depth camera and from multiple inertial sensors are obtained and segmented, (ii) the time-variant skeleton vector projection from the depth camera and the statistical features extracted from the inertial sensors are used as features, and (iii) a deep learning-based scheme is proposed for training behavior classifiers. The experimental results demonstrate that the proposed deep learning behavior system achieves an accuracy of greater than 95% compared to the proposed dataset.
Comparison of Kalman Filters for Inertial Integrated Navigation
Authors: Zhang Mengde , Li Kailong , Hu Baiqing , Meng Chunjian
Published: March 2019

The current research on integrated navigation is mainly focused on filtering or integrated navigation equipment. Studies systematically comparing and analyzing how to choose appropriate integrated filtering methods under different circumstances are lacking. This paper focuses on integrated navigation filters that are used by different filters and attitude parameters for inertial integrated navigation. We researched integrated navigation filters, established algorithms, and examined the relative merits for practical integrated navigation. Some suggestions for the use of filtering algorithms are provided. We completed simulations and car-mounted experiments for low-cost strapdown inertial navigation system (SINS) to assess the performance of the integrated navigation filtering algorithms.
Erratum: Li, D.; Scarano, S.; Lisi, S.; Palladino, P.; Minunni, M. Real-Time Tau Protein Detection by Sandwich-Based Piezoelectric Biosensing: Exploring Tubulin as a Mass Enhancer. Sensors 2018, 18, 946
Authors: Li Dujuan , Scarano Simona , Lisi Samuele , Palladino Pasquale , Minunni Maria
Published: March 2019

The authors wish to make the following erratum to this paper [...]
Small-Target Detection between SAR Images Based on Statistical Modeling of Log-Ratio Operator
Authors: Chen Chao , Huang Kuihua , Gao Gui
Published: March 2019

The log-ratio (LR) operator is well suited for change detection in synthetic aperture radar (SAR) amplitude or intensity images. In applying the LR operator to change detection in multi-temporal SAR images, a crucial problem is how to develop precise models for the LR statistics. In this study, we first derive analytically the probability density function (PDF) of the LR operator. Subsequently, the PDF of the LR statistics is parameterized by three parameters, i.e., the number of looks, the coherence magnitude, and the true intensity ratio. Then, the maximum-likelihood (ML) estimates of parameters in the LR PDF are also derived. As an example, the proposed statistical model and corresponding ML estimation are used in an operational application, i.e., determining the constant false alarm rate (CFAR) detection thresholds for small target detection between SAR images. The effectiveness of the proposed model and corresponding ML estimation are verified by applying them to measured multi-temporal SAR images, and comparing the results to the well-known generalized Gaussian (GG) distribution; the usefulness of the proposed LR PDF for small target detection is also shown.
High Temperature Effects during High Energy Laser Strikes on Embedded Fiber Bragg Grating Sensors
Authors: Ross Michael J. , Jenkins R. Brian , Nelson Charles , Joyce Peter
Published: March 2019

As the applications of fiber Bragg gratings (FBGs) continue to grow and become more advanced, it becomes necessary to understand their behavior when exposed to high temperatures in unique situations. In these experiments, uniform 1530-nm fiber Bragg gratings and Type K Cr-Al thermocouples were embedded in three-ply carbon fiber composites. A 100 W high energy laser (HEL) heated the composites to high temperatures over timespans less than one second, and FBG spectral data and thermocouple temperature data were collected during each HEL heating test. The data from three high energy laser tests that represent different levels of damage to the FBG are analyzed to explore the spectral response and thermal decay of embedded FBG sensors when exposed to high temperatures over short timespans. Results are compared to a previously proposed power-law model describing the decay of FBGs in bare fiber when held at constant temperatures over much longer timespans.
Organoleptic Analysis of Drinking Water Using an Electronic Tongue Based on Electrochemical Microsensors
Authors: Gutiérrez-Capitán Manuel , Brull-Fontserè Marta , Jiménez-Jorquera Cecilia
Published: March 2019

The standards that establish water’s quality criteria for human consumption include organoleptic analysis. These analyses are performed by taste panels that are not available to all water supply companies with the required frequency. In this work, we propose the use of an electronic tongue to perform organoleptic tests in drinking water. The aim is to automate the whole process of these tests, making them more economical, simple, and accessible. The system is composed by an array of electrochemical microsensors and chemometric tools for multivariable processing to extract the useful chemical information. The array of sensors is composed of six Ion-Sensitive Field Effect Transistors (ISFET)-based sensors, one conductivity sensor, one redox potential sensor, and two amperometric electrodes, one gold microelectrode for chlorine detection, and one nanocomposite planar electrode for sensing electrochemical oxygen demand. A previous study addressed to classify water samples according to taste/smell descriptors (sweet, acidic, salty, bitter, medicinal, chlorinous, mouldy, and earthy) was performed. A second study comparing the results of two organoleptic tests (hedonic evaluation and ranking test) with the electronic tongue, using Partial Least Squares regression, was conducted. The results show that the proposed electronic tongue is capable of analyzing water samples according to their organoleptic characteristics, which can be used as an alternative method to the taste panel.
A Real-Time Detection Method for BDS Signal in Space Anomalies
Authors: Cheng Chun , Zhao Yuxin , Li Liang , Zhao Lin
Published: March 2019

Signal In Space (SIS) anomalies in satellite navigation systems can degrade satellite-based navigation and positioning performance. The occurrence of SIS anomalies from the BeiDou navigation satellite System (BDS) may be more frequent than for the Global Positioning System (GPS). In order to guarantee the integrity of BDS users, detecting and excluding SIS anomalies is indispensable. The traditional method through the comparison between the final precision ephemeris and the broadcast ephemeris is limited by the issue of long latency of precision ephemeris release. Through the statistical characteristics analysis of Signal In Space User Range Error (SISURE), we propose a real-time Instantaneous SISURE (IURE) estimation method by using the Kalman filtering-based carrier-smoothed-code to detect and exclude BDS SIS anomalies, in which the threshold for BDS IURE anomaly detection are obtained from the integrity requirement. The experimental results based on 1 Hz data from ground observations show that the proposed method has an estimation accuracy of 1.1 m for BDS IURE. The test results show that the proposed method can effectively detect the SIS anomalies caused by either orbit faults or clock faults.
High-Rise Building 3D Reconstruction with the Wrapped Interferometric Phase
Authors: Guo Rui , Wang Fan , Zang Bo , Jing GuoBin , Xing Mengdao
Published: March 2019

The great development of high-resolution SAR system gives more opportunities to observe building structures in detail, especially the advanced interferometric SAR (InSAR), which techniques attract more attention on exploiting useful information on urban infrastructures. Considering that the high-rise buildings in urban areas are quite common in big cities, it is of great importance to retrieve the three-dimension (3D) information of the urban high-rise buildings in urban remote sensing applications. In this paper, the 3D reconstruction of high-rise buildings using the wrapped InSAR phase image was studied, referring to the geometric modulation in very high resolution (VHR) SAR images, such as serious layover cause by high-rise buildings. Under the assumption of a rectangular shape, the high-rise buildings were detected and building façades were extracted based on the local frequency analysis of the layover fringe patterns. Then 3D information of buildings were finally extracted according to the detected façade geometry. Except for testing on a small urban area from the TanDEM-X data, the experiment carried on the single-pass InSAR wrapped phase in the wide urban scene, which was collected by the Chinese airborne N-SAR system, also demonstrated the possibility and applicability of the approach.
Use of Time-Dependent Multispectral Representation of Magnetic Barkhausen Noise Signals for the Needs of Non-Destructive Evaluation of Steel Materials
Authors: Maciusowicz Michal , Psuj Grzegorz
Published: March 2019

Due to the existing relationship between microstructural properties and magnetic ones of the ferromagnetic materials, the application potential of the magnetic Barkhausen noise (BN) method to non-destructive testing is constantly growing. However, the stochastic nature of the Barkhausen effect requires the use of advanced signal processing methods. Recently, the need to apply time-frequency (TF) transformations to the processing of BN signals arose. However, various TF methods have been used in the majority of cases for qualitative signal conditioning and no extensive analysis of TF-based information has been conducted so far. Therefore, in this paper, the wide analysis of BN TF representation was carried out. Considering the properties of TF transformations, the Short-Time Fourier Transform (STFT) was used. A procedure for definition of the envelopes of the TF characteristic was proposed. To verify the quality of extracted features, an analysis was performed on the basis of BN signals acquired during stress loading experiments of steel elements. First, the preliminary experiments were processed for various parameters of the measuring system and calculation procedures. The feature extraction procedure was performed for different modes of TF representations. Finally, the distributions of TF features over the loading stages are presented and their information content was validated using commonly used features derived from time T and frequency F domains.
A Dual-Chamber Serial–Parallel Piezoelectric Pump with an Integrated Sensor for Flow Rate Measurement
Authors: Chen Song , Yu Mai , Kan Junwu , Li Jianping , Zhang Zhonghua , Xie Xinyi , Wang Xiaomin
Published: March 2019

A new concept of a dual-chamber serial-parallel piezoelectric pump with an integrated sensor (DSPPIS) is presented in this paper. By means of dividing a piezoelectric bimorph into an actuator and a sensor, sensing function is integrated onto the DSPPIS for flow rate measurement. A prototype of the DSPPIS was manufactured and assembled from a finished piezoelectric bimorph. Then, frequency and voltage characteristics were tested to evaluate the performance of the DSPPIS with serial and parallel connection. Experimental results show that the optimal frequency range of DSPPIS can be achieved and determined by itself through monitoring the sensing voltage when driven by a fixed voltage of 150 Vpp and a frequency range of 40–400 Hz. For a fixed frequency of 100 Hz and a voltage range of 50–250 Vpp, both the sensing voltage and output flow rate increase with the increase of driving voltage. It is observed that there is a positive correlation between sensing voltage and output flow rate, which was further fitted by using linear function. The correlation coefficients for the DSPPIS with serial and parallel connection are calculated as 0.9716 and 0.9054, respectively. As a result, the DSPPIS demonstrated in this paper has realized the measurement of flow rate without the additional flow-sensing equipment both in serial and parallel connection.
Effect of Poly-l-Lysine Polycation on the Glucose Oxidase/Ferricyanide Composite-Based Second-Generation Blood Glucose Sensors
Authors: Lin Ming-Jie , Wu Ching-Chou , Chang Ko-Shing
Published: March 2019

Second-generation glucose biosensors are presently the mainstream commercial solution for blood glucose measurement of diabetic patients. Screen-printed carbon electrodes (SPCEs) are the most-used substrate for glucose testing strips. This study adopted hydrophilic and positively charged α-poly-l-lysine (αPLL) as the entrapment matrix for the immobilization of negatively charged glucose oxidase (GOx) and ferricyanide (FIC) on SPCEs to construct a disposable second-generation glucose biosensor. The αPLL modification is shown to facilitate the redox kinetics of FIC and ferrocyanide on the SPCEs. The SPCEs coated with 0.5 mM GOx, 99.5 mM FIC, and 5 mM αPLL had better sensitivity for glucose detection due to the appreciable effect of protonated αPLL on the promotion of electron transfer between GOx and FIC. Moreover, the SPCEs coated with 0.5 mM GOx, 99.5 mM FIC, and 5 mM αPLL were packaged as blood glucose testing strips for the measurement of glucose-containing human serum samples. The glucose testing strips had good linearity from 2.8 mM to 27.5 mM and a detection limit of 2.3 mM. Moreover, the 5 mM αPLL-based glucose testing strips had good long-term stability to maintain GOx activity in aging tests at 50 °C.
Bed-Embedded Heart and Respiration Rates Detection by Longitudinal Ballistocardiography and Pattern Recognition
Authors: Albukhari Almothana , Lima Frederico , Mescheder Ulrich
Published: March 2019

In this work, a low-cost, off-the-shelf load cell is installed on a typical hospital bed and implemented to measure the longitudinal ballistocardiogram (BCG) in order to evaluate its utility for successful contactless monitoring of heart and respiration rates. The major focus is placed on the beat-to-beat heart rate monitoring task, for which an unsupervised machine learning algorithm is employed, while its performance is compared to an electrocardiogram (ECG) signal that serves as a reference. The algorithm is a modified version of a previously published one, which had successfully detected 49.2% of recorded heartbeats. However, the presented system was tested with seven volunteers and four different lying positions, and obtained an improved overall detection rate of 83.9%.
Endocrine Disrupting Compounds Removal Methods from Wastewater in the United Kingdom: A Review
Authors:   China K. Gadupudi,   Louis Rice,   Libin Xiao,   Komali Kantamaneni
Published: March 2019

Endocrine disrupting compounds (EDCs) are contaminants with estrogenic or androgenic activity that negatively impact human and animal communities. These compounds have become one of the significant concerns for wastewater treatment in recent decades. Several studies have evaluated EDC removal methods from wastewater across the globe including the United Kingdom (UK). Accordingly, the current study reviews EDC removal methods from municipal/domestic wastewater in the United Kingdom (UK) for the period of 2010–2017. The research highlights that despite the relative efficacy of existing chemical and physical methods for removing certain EDCs from wastewater there is emerging evidence supporting the need for more widespread application of nature-based and biological approaches, particularly the use of biofilms. The analysis reveals that there have been relatively few research studies on EDC removal methods have been carried out in the UK in the 2010–2017 period and none of the research focused on EDC removal using biofilms. Finally, this review suggests that more research is needed to remove EDCs, particularly through the application of biofilms, from municipal wastewater in current scenarios.
Victimization, Social Structure and Psychosocial Variables: The Case of Spain in 1999 and 2016
Authors: Herranz de Rafael Gonzalo , Fernández-Prados Juan Sebastián
Published: March 2019

This article reviews the research on the factors influencing victimization and explores the case of Spain. The first section presents a comparative analysis of the data for 1999 and 2016 in terms of perceptions, profiles and the most significant sociodemographic and socioeconomic variables. The second section shows an explanatory analysis based on multivariate logistical regression models, using as independent variables sociodemographic and psychosocial items, and the dependent variable is whether one is described as one is described as a victim or no in the 2016 survey. The results point towards an explanatory model of victimization in which sociodemographic variables play a less important role, whereas psychosocial variables related to lifestyle and subjective perceptions make a significant contribution to greater understanding of the nature of being the victim of a crime and offer suggestions on how to improve Crime Prevention Through Environmental Design (CPTED).
Shrub Encroachment Shapes Soil Nutrient Concentration, Stoichiometry and Carbon Storage in an Abandoned Subalpine Grassland
Authors: Ding Leilei , Wang Puchang , Zhang Wen , Zhang Yu , Li Shige , Wei Xin , Chen Xi , Zhang Yujun , Yang Fuli
Published: March 2019

Soil nutrient stoichiometry plays a substantial role in terrestrial carbon and nutrient cycling. However, the changes in soil nutrient stoichiometry with shrub encroachment (SE) remain poorly understood, especially in subalpine areas. We examined the changes in soil nutrient concentration, nutrient stoichiometry, and organic carbon (OC) storage (at a depth of 0–5, 5–10 and 10–20 cm) in three successional shrub encroachment stages (early, mid and late) in an abandoned subalpine Eulalia pallens (Hackel) Kuntze grassland. An ANOVA showed that SE did not produce serious soil acidification, but significantly increased the soil OC and total phosphorous (TP) concentration, and improved the stoichiometry ratio of soil OC to total nitrogen (OC:TN) in all layers. OC storage tended to increase with SE. SE thus did not indicate degradation of the grassland. A redundancy analysis (RDA) and partial RDA revealed that the shrub relative cover and soil water content were the most important factors affecting the soil nutrient concentration, that the soil available phosphorous (AP), nitrogen, potassium, calcium (ACa), and magnesium concentration and shrub relative cover were the most important factors influencing soil nutrient stoichiometry ratios, and that soil OC:TN, TN:TP, OC:TN:TP, and AP:ACa ratios, bulk density, and pH were the most important factors influencing soil OC storage over SE. Our study provides insights into SE in grassland areas, and potentially provides a useful reference for ongoing grassland conservation and restoration in subalpine regions.
CSR Maturity in Polish Listed Companies: A Qualitative Diagnosis Based on a Progression Model
Authors: Witek-Crabb Anna
Published: March 2019

Transformation from a centrally planned economy to a market economy in 1989 created new challenges for the enterprises in Poland. Free market brought economic liberty, but also the need to take responsibility for the business’ impact on the environment. The last 20 years have brought intensive development of Corporate Social Responsibility (CSR) in Polish conditions: The institutional context supporting CSR has improved and so did the implementation of the CSR by the business. Intensive growth of CSR practices demands a reflection on the effectiveness of the implementation. This study’s contribution is a comprehensive diagnosis of CSR maturity of the enterprises in Poland using a conceptual CSR maturity model. The model is comprised of three perspectives: CSR process maturity, CSR formal maturity and CSR developmental maturity. CSR practices of 93 listed companies from nine industries were studied in 2016–2017. A qualitative content analysis of the enterprises websites was used as the method of study. The main finding was that the level of CSR practices of the enterprises in Poland is still rather low. Forty-seven percent of the enterprises implement incidental CSR, 30% tactical CSR and 23% apply strategic CSR. CSR maturity level is company size- and industry-dependent.
The Influence of Internet Entrepreneur-Related Word-of-Mouth (WOM) on Corporate Image Association
Authors: Yuan Bing , Peluso Alessandro M.
Published: March 2019

Both the consumer’s corporate social responsibility association and enterprise production capacity association are beneficial to business sustainable development. Based on Chinese traditional culture and from the perspective of Stereotype Content Model, this paper explores the relationship between two types of entrepreneur-related Word-of-mouth (WOM) and the two afore-mentioned types of consumer’s associations. On the one hand, the results show that the entrepreneur-related WOM labeled as “making yourself a person”, which emphasizes the personal qualities of the entrepreneur, may prompt consumers to form corporate social responsibility associations. On the other hand, the entrepreneur-related WOM labeled as “managing your own affairs”, which emphasizes the ability of the entrepreneur, may cause consumers to form associations regarding the enterprise’s production capacity. The mechanism underlying these effects is that the former type of entrepreneur-related WOM stimulates the consumer’s perception of the entrepreneur’s warmth, while the latter stimulates the consumer’s perception of the entrepreneur’s competence.
Exploring Urban Expansion and Socioeconomic Vitality Using NPP-VIIRS Data in Xia-Zhang-Quan, China
Authors: Jiang Yuantong , Sun Shoukai , Zheng Shuanning
Published: March 2019

Studying the spatiotemporal evolution of urban expansion in the Xia-Zhang-Quan metropolitan area (XZQ) is of crucial importance, to effectively guide coordinated development and industrial adjustment during urbanization. Based on National Polar Partnership-Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) data this study used an analytical method of irregular spatial grids to explore and evaluate the dynamics of urban spatial expansion and urban socioeconomic vitality in XZQ between 2013 and 2017. The results show that the gulf-type urban development strategy of Xiamen has played a key role in the integration and development of XZQ. The urban area increased by 20–30% and increased intensity of socioeconomic activities was demonstrated by observed increases in the total brightness of urban nighttime light. Due to its unique advantages in the agricultural industries, Zhangzhou made significant economic progress during 2013–2017. At the same time, driven by spatial processes in Xiamen, areas such as the Zhangzhou Port Area and Longhai also achieved significant progress. This is also the case in Quanzhou and thus, collectively there is evidence of multi-polar growth. Jinjiang and Shishi effectively utilized coastal port economy development advantages to play a key role in the integration and development of XZQ. There were both commonalities and differences in terms of the characteristics of spatial expansion in different cities of XZQ. In summary, this study provides evidence to support further promotion of coordinated development in XZQ, and with appropriate caveats these findings could also be transferred to other urban agglomerations.
Solar PV Grid Power Flow Analysis
Authors: Alsafasfeh Qais , Saraereh Omar A. , Khan Imran , Kim Sunghwan
Published: March 2019

As the unconstrained integration of distributed photovoltaic (PV) power into a power grid will cause changes in the power flow of the distribution network, voltage deviation, voltage fluctuation, and so on, system operators focus on how to determine and improve the integration capacity of PV power rationally. By giving full consideration to the static security index constraints and voltage fluctuation, this paper proposes a maximum integration capacity optimization model of the PV power, according to different power factors for the PV power. Moreover, the proposed research analyzes the large-scale PV grid access capacity, PV access point, and multi-PV power plant output, by probability density distribution, sensitivity analysis, standard deviation analysis, and over-limit probability analysis. Furthermore, this paper establishes accessible capacity maximization problems from the Institute of Electrical and Electronics Engineers (IEEE) standard node system and power system analysis theory for PV power sources with constraints of voltage fluctuations. A MATLAB R2017B simulator is used for the performance analysis and evaluation of the proposed work. Through the simulation of the IEEE 33-node system, the integration capacity range of the PV power is analyzed, and the maximum integration capacity of the PV power at each node is calculated, providing a rational decision-making scheme for the planning of integrating the distributed PV power into a small-scale power grid. The results indicate that the fluctuations and limit violation probabilities of the power system voltage and load flow increase with the addition of the PV capacity. Moreover, the power loss and PV penetration level are influenced by grid-connected spots, and the impact of PV on the load flow is directional.
Dirty Banking: Probing the Gap in Sustainable Finance
Authors: Urban Michael , Wójcik Dariusz
Published: March 2019

In 2016, the Global Sustainable Investment Alliance estimated the market for sustainable investments to have reached 22.89 trillion USD of assets under management. While financial institutions have embraced the idea of sustainable finance as a business opportunity, they have arguably done little, but to piggy-back on investors’ demand. Today, it is not unusual for a single firm to retail fossil free investment funds and concomitantly offer commercial loans towards fracking, coal, and Arctic drilling. This paradox is underpinned by a major gap in the way sustainability has permeated primary and secondary markets which, we argue, calls for a serious rethinking of the sustainability transition in finance. This article proposes two contributions in this direction. First, we develop an original conceptualisation of finance as a socio-technical system to discuss the dynamics that both hinder and promote a transition from mainstream to sustainable finance. Second, we propose to study how investment banks integrate sustainability in their underwriting services. To do so, we filter through close to half a million of debt and equity underwriting deals (2005–2017) using the Government Pension Fund Global of Norway’s list of 153 excluded companies. Our results suggest that investment banks do not shy away from underwriting companies that have been flagged for major environmental, social, and governance misconduct, neither do they restrain from underwriting companies providing contentious products, such as tobacco, coal, and nuclear weapons. Moving forward, we suggest ways to address this problem and call for further research on the responsibility and agency of finance and advanced business services firms in sustainability transitions.
Research on the Application of Palm Mat Geotextiles for Sand Fixation in the Hobq Desert
Authors: Zhong Shuai , Han Zhiwen , Li Aimin , Du Heqiang
Published: March 2019

Traditional sand fixation measures have many limitations. For example, engineering sand fixation measures using barriers cannot completely stabilize sand dunes. Biological sand fixation measures utilizing planted vegetation are very difficult to build during the early stages of desertification control. Chemical sand fixation measures spray chemically bonded materials on sand dunes to form a consolidated layer to prevent sand flow, but the cost of the materials used is relatively high. Therefore, new sand fixation technologies and methods urgently need to be developed. This study demonstrates a new sand fixation method, which uses palm mat geotextiles to stabilize sand dunes and to plant grass. We investigated the physical properties of these palm mat geotextiles in the laboratory and observed vegetation growth in the Hobq Desert. The results showed the following: (1) Palm mat geotextiles are lighter and tougher than common straw mat geotextiles. The average weight, thickness, and tensile strength of palm mat geotextiles are 2023 g/m2, 20.14 mm, and 842–860 kPa, respectively. After a year of field observations, the tensile strength decreased by only 2%. (2) Palm mat geotextiles have excellent water retention capacity and scouring resistance; the maximum water content reached 227%, and the substrate lost 2.9% after laboratory simulation of heavy rainfall for three hours with a rainfall intensity of 30 mm h−1. (3) Palm mat geotextiles significantly decreased the soil temperature and increased moisture in summer. The results showed that the palm mat geotextiles had the largest influence on soil temperature in the upper 5 cm of soil and the largest influence on soil moisture in the upper 10 cm of soil. (4) The field experimental results showed that, by the end of the experiment, the vegetation coverage and the biomass of the palm mat geotextiles with dimensions of 2 × 2 m were 3.9 times and 4.1 times that of the control group and 1.7 times and 1.8 times that of the group of high-banded Salix psammophila sand barriers, which are widely used in the Hobq Desert at present. Palm mat geotextiles are a promising material for sand fixation in the Hobq Desert.
Identification of Key Influencing Factors of Sustainable Development for Traditional Power Generation Groups in a Market by Applying an Extended MCDM Model
Authors: Dong Jun , Liu Dongran , Wang Dongxue , Zhang Qi
Published: March 2019

With the deepening reform of the power market, the external environment of China’s power industry is going through a huge change. China’s traditional power generation groups (TPGGs), with assets all over the country, are, due to a lack of market awareness about energy policies, facing serious challenges in developing competitive advantages, improving power transaction modes, optimizing profit models, and even realizing basic corporate strategies. In this study, we focus on identifying the key factors influencing sustainable development in an unprecedented market environment for TPGGs, so as to achieve overall sustainable development for the whole power generation sector in China. A hybrid framework based on Multiple-Criteria Decision-Making (MCDM) was proposed to recognize the key influencing factors under vague rule conditions. We developed a novel method combining three different MCDM methods with triangular fuzzy numbers (TFNs), fuzzy Delphi, fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL), and Analytic Network Process (ANP), to cover uncertainty and make the problem-solving approach closer to the actual problem. A series of analyses indicate that the final 14 factors covering the five dimensions are considered to be important factors in the sustainable development of TPGGs. Based on the results, it can be said that “Gross energy margin” and “Pricing bidding strategy” dominate the impacts of TPGG’s sustainable development. Finally, we give some advice relating to practical measures to help TPGGs achieve sustainable development in the market-oriented industry environment.
Discussion on the Reinforcement of Reinforced Concrete Slab Structures
Authors: Hsu Wei-Ling , Liu Chen-Chung , Shiau Yan-Chyuan , Lin Wen-Chin
Published: March 2019

Because of global environmental changes and the continued warming of the planet, the increase in carbon dioxide emissions has had a major impact on the environment. The development of zero-carbon buildings, the promotion of energy conservation and carbon reduction, and the concept of green environmental protection are regarded as important issues for humanity to achieve sustainable development. In Taiwan, the combination of moisture and high salt content in the environment, corrosion caused by chloride ions, and earthquakes often lead to the formation of crevices in buildings. These crevices can cause rebar oxidation and corrosion and even concrete structure damage or spalling. Conventional structural damages can be repaired with epoxy resin grout. However, such practices are incapable of removing the rusted components of the rebars inside the structures and thus subject the internal rebars to continuous oxidation in the original rust-covered environment. Components located deep within the structures would still swell as a result of continuous rebar oxidation and cause concrete breaking and spalling, making previous repair efforts ineffective. This study proposes an improved repair and retrofit technique that includes the removal of rust from oxidated rebar parts, by applying low viscosity epoxy resin to the slab base and allowing it to fully penetrate the concrete cracks and surface of the rebars inside, thus producing a protective layer and repairing the bond. Additionally, carbon-fiber reinforced plastic (CFRP) patches were adopted as repair materials and attached to the beams and slab (ceiling) surfaces. Angle steels were used at the edges and installed to connect the beams to the slab with chemical anchors. The gaps between the angle steels and the slab were filled with epoxy resin grouts. On the short side of the slab, small steel H-beams were installed 1 m apart as a means of retrofit. Because the epoxy resin expands by 8% after undergoing chemical reactions, it bonds perfectly with concrete, CFRP patches, and steel materials. Approximately 10 years have elapsed since the case-study was repaired using the proposed technique, and the retrofit effect has yielded excellent results to the present day, with no occurrence of internal swelling or spalling from rebar oxidation. The proposed retrofit technique can reduce construction costs, while ensuring effective repair and maintenance of structural safety, and extend the service life of structures.
Smallholder Agroprocessors’ Willingness to Pay for Value-Added Solid-Waste Management Solutions
Authors: Omilani Olaoluwa , Abass Adebayo Busura , Okoruwa Victor Olusegun
Published: March 2019

The paper examined the willingness of smallholder cassava processors to pay for value-added solid wastes management solutions in Nigeria. We employed a multistage sampling procedure to obtain primary data from 403 cassava processors from the forest and Guinea savannah zones of Nigeria. Contingent valuation and logistic regression were used to determine the willingness of the processors to pay for improved waste management options and the factors influencing their decision on the type of waste management system adopted and willingness to pay for a value-added solid-waste management system option. Women constituted the largest population of smallholder cassava processors, and the processors generated a lot of solid waste (605–878 kg/processor/season). Waste was usually dumped (59.6%), given to others (58.1%), or sold in wet (27.8%) or dry (35.5%) forms. The factors influencing the processors’ decision on the type of waste management system to adopt included sex of processors, membership of an association, quantity of cassava processed and ownership structure. Whereas the processors were willing to pay for new training on improved waste management technologies, they were not willing to pay more than US$3. However, US$3 may be paid for training in mushroom production. It is expected that public expenditure on training to empower processors to use solid-waste conversion technologies for generating value-added products will lead to such social benefits as lower exposure to environmental toxins from the air, rivers and underground water, among others, and additional income for the smallholder processors. The output of the study can serve as the basis for developing usable and affordable solid-waste management systems for community cassava processing units in African countries involved in cassava production.
Straw Utilization in China—Status and Recommendations
Authors: Ren Jiqin , Yu Peixian , Xu Xiaohong
Published: March 2019

As the world’s largest grain producer, China’s straw yield was 700 million tonnes in 2014. With a national utilization rate of 80% in 2015, there is still a large amount of straw burned in open-field, resulting in air pollution and a reduction in the quantity available as a source of bioenergy. This paper conducts a literature review of success stories and major challenges in comprehensive straw utilization in and out of China. It is noted that nationwide long-term feasible and sustainable straw utilization at a high rate is a highly complex operation, involving most societal sectors, many people and facilities often at different regions. Scenarios were analyzed to estimate the energy potential and air emission reductions China would accomplish in 2020 by converting an additional 5 or 10% of straw-yield to biofuel. Currently, the approach to control straw burning in China is primarily administrative, relying heavily on prohibition and penalties, inconsistent across policy areas and geography, and lacking in long-term planning. Consequently, the effectiveness of the current approach is limited. The main cause of burning is a lack of infrastructure, effective preventive measures, and viable alternatives. Recommendations aimed at promoting a circular bio-economy around using crop straw as resources were provided, including improving straw utilization rates and reducing open-field burning.