bluuebunny/crossref_metadata_2025 huggingface dataset:
From High-Manganese Steels to Advanced High-Entropy Alloys
Authors: Haase Christian , Barrales-Mora Luis Antonio
Published: June 2019

Arguably, steels are the most important structural material, even to this day. Numerous design concepts have been developed to create and/or tailor new steels suited to the most varied applications. High-manganese steels (HMnS) stand out for their excellent mechanical properties and their capacity to make use of a variety of physical mechanisms to tailor their microstructure, and thus their properties. With this in mind, in this contribution, we explore the possibility of extending the alloy design concepts that haven been used successfully in HMnS to the recently introduced high-entropy alloys (HEA). To this aim, one HMnS steel and the classical HEA Cantor alloy were subjected to cold rolling and heat treatment. The evolution of the microstructure and texture during the processing of the alloys and the resulting properties were characterized and studied. Based on these results, the physical mechanisms active in the investigated HMnS and HEA were identified and discussed. The results evidenced a substantial transferability of the design concepts and more importantly, they hint at a larger potential for microstructure and property tailoring in the HEA.
Tissue-Specific Sample Dilution: An Important Parameter to Optimise Prior to Untargeted LC-MS Metabolomics
Authors: Wu Zhanxuan E. , Kruger Marlena C. , Cooper Garth J.S. , Poppitt Sally D. , Fraser Karl
Published: June 2019

When developing a sample preparation protocol for LC–MS untargeted metabolomics of a new sample matrix unfamiliar to the laboratory, selection of a suitable injection concentration is rarely described. Here we developed a simple workflow to address this issue prior to untargeted LC–MS metabolomics using pig adipose tissue and liver tissue. Bi-phasic extraction was performed to enable simultaneous optimisation of parameters for analysis of both lipids and polar extracts. A series of diluted pooled samples were analysed by LC–MS and used to evaluate signal linearity. Suitable injected concentrations were determined based on both the number of reproducible features and linear features. With our laboratory settings, the optimum concentrations of tissue mass to reconstitution solvent of liver and adipose tissue lipid fractions were found to be 125 mg/mL and 7.81 mg/mL respectively, producing 2811 (ESI+) and 4326 (ESI−) linear features from liver, 698 (ESI+) and 498 (ESI−) linear features from adipose tissue. For analysis of the polar fraction of both tissues, 250 mg/mL was suitable, producing 403 (ESI+) and 235 (ESI−) linear features from liver, 114 (ESI+) and 108 (ESI−) linear features from adipose tissue. Incorrect reconstitution volumes resulted in either severe overloading or poor linearity in our lipid data, while too dilute polar fractions resulted in a low number of reproducible features (<50) compared to hundreds of reproducible features from the optimum concentration used. Our study highlights on multiple matrices and multiple extract and chromatography types, the critical importance of determining a suitable injected concentration prior to untargeted LC–MS metabolomics, with the described workflow applicable to any matrix and LC–MS system.
Computational Investigation of Bisphosphate Inhibitors of 3-Deoxy-d-manno-octulosonate 8-phosphate Synthase
Authors: Araújo Jéssica de Oliveira , dos Santos Alberto Monteiro , Lameira Jerônimo , Alves Cláudio Nahum , Lima Anderson Henrique
Published: June 2019

The synthase, 3-deoxy-d-manno-octulosonate 8-phosphate (KDO8P), is a key enzyme for the lipopolysaccharide (LPS) biosynthesis of gram-negative bacteria and a potential target for developing new antimicrobial agents. In this study, computational molecular modeling methods were used to determine the complete structure of the KDO8P synthase from Neisseria meningitidis and to investigate the molecular mechanism of its inhibition by three bisphosphate inhibitors: BPH1, BPH2, and BPH3. Our results showed that BPH1 presented a protein–ligand complex with the highest affinity, which is in agreement with experimental data. Furthermore, molecular dynamics (MD) simulations showed that BPH1 is more active due to the many effective interactions, most of which are derived from its phosphoenolpyruvate moiety. Conversely, BPH2 exhibited few hydrogen interactions during the MD simulations with key residues located at the active sites of the KDO8P synthase. In addition, we hydroxylated BPH2 to create the hypothetical molecule named BPH3, to investigate the influence of the hydroxyl groups on the affinity of the bisphosphate inhibitors toward the KDO8P synthase. Overall, we discuss the main interactions between the KDO8P synthase and the bisphosphate inhibitors that are potential starting points for the design of new molecules with significant antibiotic activities.
Fine-Tuning the Activation Mode of an 1,3-Indandione-Based Ruthenium(II)-Cymene Half-Sandwich Complex by Variation of Its Leaving Group
Authors: Mokesch Stephan , Schwarz Daniela , Hejl Michaela , Klose Matthias H. M. , Roller Alexander , Jakupec Michael A. , Kandioller Wolfgang , Keppler Bernhard K.
Published: June 2019

Fine-tuning of the properties of a recently reported 1,3-indandione-based organoruthenium complex is attempted to optimize the stability under physiological conditions. Previous work has shown its capacity of inhibiting topoisomerase IIα; however, fast aquation leads to undesired reactions and ligand cleavage in the blood stream before the tumor tissue is reached. Exchange of the chlorido ligand for six different N-donor ligands resulted in new analogs that were stable at pH 7.4 and 8.5. Only a lowered pH level, as encountered in the extracellular space of the tumor tissue, was capable of aquating the complexes. The 50% inhibitory concentration (IC50) values in three human cancer cell lines differed only slightly, and their dependence on the utilized leaving group was smaller than what would be expected from their differences in cellular accumulation, but in accordance with the very minor variation revealed in measurements of the complexes’ lipophilicity.
Unique Constant Phase Element Behavior of the Electrolyte–Graphene Interface
Authors: Sun Jianbo , Liu Yuxin
Published: June 2019

We report a unique constant phase element (CPE) behavior ( 1 Z = Q 0 ( j ω ) α ) of the electrolyte–graphene interface with both Q 0 and α showing dependence on the gate voltage. The frequency response of the electrolyte–graphene interface was studied using electrochemical impedance spectroscopy (EIS). The result suggests that (1) the electrolyte–graphene interface should be characterized as a CPE ( α < 1), rather than an ideal capacitor; and (2) both Q 0 and α show ambipolar dependence on the applied voltage. We speculate that the CPE behavior of the electrolyte–graphene interface arises from the charged impurities on the substrate and the defects in the graphene lattice, which could introduce inhomogeneity of local density of states (DOS). The low density of states of graphene makes α sensitive to these local DOS near the Dirac point, and thus showing dependence on the gate voltage. Measurement of the electrolyte–graphene interface capacitance based on multi-frequency capacitance-voltage (CV) profiling was demonstrated, and the extraction of the carrier mobility was performed. The study could lead to a more accurate understanding of the capacitive behavior of the electrolyte–graphene interface, which is instructive for the design and analysis of devices involving the electrolyte–graphene interface for nanoelectronics and bioelectronics applications.
Synthesis, Characterization and Fabrication of Graphene/Boron Nitride Nanosheets Heterostructure Tunneling Devices
Authors: Sajjad Muhammad , Makarov Vladimir , Mendoza Frank , Sultan Muhammad S. , Aldalbahi Ali , Feng Peter X. , Jadwisienczak Wojciech M. , Weiner Brad R. , Morell Gerardo
Published: June 2019

Various types of 2D/2D prototype devices based on graphene (G) and boron nitride nanosheets (BNNS) were fabricated to study the charge tunneling phenomenon pertinent to vertical transistors for digital and high frequency electronics. Specifically, G/BNNS/metal, G/SiO2, and G/BNNS/SiO2 heterostructures were investigated under direct current (DC-bias) conditions at room temperature. Bilayer graphene and BNNS were grown separately and transferred subsequently onto the substrates to fabricate 2D device architectures. High-resolution transmission electron microscopy confirmed the bilayer graphene structure and few layer BNNS sheets having a hexagonal B3-N3 lattice. The current vs voltage I(V) data for the G/BNNS/Metal devices show Schottky barrier characteristics with very low forward voltage drop, Fowler-Nordheim behavior, and 10−4 Ω/sq. sheet resistance. This result is ascribed to the combination of fast electron transport within graphene grains and out-of-plane tunneling in BNNS that circumvents grain boundary resistance. A theoretical model based on electron tunneling is used to qualitatively describe the behavior of the 2D G/BNNS/metal devices.
Decreased Conflict Control in Overweight Chinese Females: Behavioral and Event-Related Potentials Evidence
Authors: Liu Yong , Quan Huan , Song Shiqing , Zhang Xuemeng , Yang Chao , Chen Hong
Published: June 2019

Overweight or obesity is related to a decrease in cognitive control, especially conflict control. However, research on conflict control in overweight/obese individuals are still controversial. This study was conducted to explore general and food-related conflict control in overweight Chinese females (OWs) with a color–word Stroop task and a food-related conflict task. Event-related potentials (ERPs) were recorded during the food-related conflict task. Behavioral results showed that, OWs had a longer reaction time (RT) than normal-weight Chinese females (NWs), in both tasks. ERP results in the food-related conflict task showed that there was a reduction of N2 and N450 response strength in OWs, and the P3 and late positive component (LPC) response strength was enhanced. Results indicated that OWs might be less efficient in monitoring and resolving conflict, and OWs tended to have a higher motivational or emotional involvement in processing food-related stimuli, which was likely to contribute to their difficulty in losing weight.
The Acute Effect of Various Doses of Caffeine on Power Output and Velocity during the Bench Press Exercise among Athletes Habitually Using Caffeine
Authors: Wilk Michal , Filip Aleksandra , Krzysztofik Michal , Maszczyk Adam , Zajac Adam
Published: June 2019

Background: Previously studies confirm ergogenic effects of caffeine (CAF); however there is no available scientific data regarding the influence of acute CAF intake on power output in athletes habitually consuming CAF. The main goal of this study was to assess the acute effect of 3, 6, 9 mg/kg/b.m. doses of CAF intake on power output and bench press bar velocity in athletes habitually consuming CAF. Methods: The study included 15 healthy strength-trained male athletes (age = 26.8 ± 6.2 years, body mass = 82.6 ± 9.7 kg; BMI = 24.8 ± 2.7; bench press 1RM = 122.3 ± 24.5 kg). All participants were habitual caffeine consumers (5.2 ± 1.2 mg/kg/b.m.; 426 ± 102 mg of caffeine per day). This study had a randomized, crossover, double-blind study design where each participant performed four different experimental sessions, with one week interval between each trial. In every experimental session participants performed bench press, three sets of five repetitions at 50% 1RM. The power output and bar velocity assessments under four different conditions: a placebo (PLAC), and three doses of caffeine ingestion: 3 mg/kg/b.m. (CAF-3), 6 mg/kg/b.m. (CAF-6) and 9 mg/kg/b.m. (CAF-9). Results: The statistical significance was set at p < 0.05. The repeated measures ANOVA between PLAC and CAF-3; CAF-6; CAF-9 revealed no statistically significant differences in power output and velocity of the bar during the bench press exercise. A large effect size (ES) in mean power-output was found between PLAC and CAF-9 in Sets 1 and 2. A large ES in peak power-output was found between PLAC and CAF-6 in Set 2, and between PLAC and CAF-9 in Sets 1 and 2. A large ES in peak velocity was found between PLAC and CAF-9 in Sets 1–3. Conclusion: The results of the present study indicate that acute doses of CAF before exercise does not have a significant effect on power output and bar velocity in a group of habitual caffeine users.
Wind Energy Generation Assessment at Specific Sites in a Peninsula in Malaysia Based on Reliability Indices
Authors: Ali Kadhem Athraa , Abdul Wahab Noor Izzri , N. Abdalla Ahmed
Published: June 2019

This paper presents a statistical analysis of wind speed data that can be extremely useful for installing a wind generation as a stand-alone system. The main objective is to define the wind power capacity’s contribution to the adequacy of generation systems for the purpose of selecting wind farm locations at specific sites in Malaysia. The combined Sequential Monte Carlo simulation (SMCS) technique and the Weibull distribution models are employed to demonstrate the impact of wind power in power system reliability. To study this, the Roy Billinton Test System (RBTS) is considered and tested using wind data from two sites in Peninsular Malaysia, Mersing and Kuala Terengganu, and one site, Kudat, in Sabah. The results showed that Mersing and Kudat were best suitable for wind sites. In addition, the reliability indices are compared prior to the addition of the two wind farms to the considered RBTS system. The results reveal that the reliability indices are slightly improved for the RBTS system with wind power generation from both the potential sites.
A Fuzzy Multicriteria Decision-Making (MCDM) Model for Sustainable Supplier Evaluation and Selection Based on Triple Bottom Line Approaches in the Garment Industry
Authors: Wang Chia-Nan , Yang Ching-Yu , Cheng Hung-Chun
Published: June 2019

Vietnam’s garment industry is facing many challenges, including domestic competition and the global market. The free trade agreement, which Vietnam signed, includes environmental barriers, sustainable development, and green development. The agreement further requires businesses to make efforts to improve not only product quality but also the production process. In cases when enterprises cause environmental pollution in the production process and do not apply solutions to reduce waste, save energy, and natural resources, there is a risk of no longer receiving orders or orders being rejected, especially orders from the world’s major branded garment companies. In this research, the authors propose a multicriteria decision-making model (MCDM) for optimizing the supplier evaluation and selection process for the garment industry using sustainability considerations. In the first stage of this research, all criteria affecting supplier selection are determined by a triple bottom line (TBL) model (economic, environmental, and social aspects) and literature reviews; in addition, the fuzzy analytic hierarchy process (FAHP) method was utilized to identify the weight of all criteria in the second stage. The technique for order preference by similarity to an ideal solution (TOPSIS) is a multicriteria decision analysis method, which is used for ranking potential suppliers in the final stage. As a result, decision-making unit 10 (DMU/10) is found to be the best supplier for the garment industry. The contribution of this research includes modeling the supplier selection decision problem based on the TBL concept. The proposed model also addresses different complex problems in supplier selection, is a flexible design model for considering the evaluation criteria, and is applicable to supplier selection in other industries.
The DOAJ Spring Cleaning 2016 and What Was Removed—Tragic Loss or Good Riddance?
Authors: Frantsvåg Jan Erik
Published: June 2019

In December 2012, DOAJ’s (The Directory of Open Access Journals) parent company, IS4OA, announced they would introduce new criteria for inclusion in DOAJ and that DOAJ would collect vastly more information from journals as part of the accreditation process—journals already included would need to reapply in order to be kept in the registry. My working hypothesis was that the journals removed from DOAJ on May 9th 2016 would chiefly be journals from small publishers (mostly single journal publishers) and that DOAJ journal metadata information would reveal that they were journals with a lower level of publishing competence than those that would remain in the DOAJ. Among indicators of publishing competence could be the use of APCs (Article Processing Charges), permanent article identifiers, journal licenses, article level metadata deposited with DOAJ, archiving policy/solutions and/or having a policy in SHERPA/RoMEO, the database containing self-archiving policies for more than 30,000 journals. The analysis shows my concerns to be correct.
Forming “Mediators and Instruments of Grace”: The Emerging Role of Monastics in Teaching Contemplative Ambiguity and Practice to the Laity
Authors: Pryce Paula
Published: June 2019

Drawing from long-term ethnographic research with a global network of contemplative Christians, this paper discusses an emerging teaching role for North American monasteries as the numbers of avowed religious decline. Since the Trappist community of St. Joseph’s Abbey in Spencer, Massachusetts, first developed the Christian meditation technique called Centering Prayer in the 1970s, monks and nuns have increasingly become teachers, models, and stabilizers of non-monastic practitioners who attempt to transform their ways of being and thinking towards monastic-inspired sensibilities. Their guidance includes the use of face-to-face, literary, and virtual means to teach methods of contemplative intersubjectivity and a commitment to lives based on service, hospitality, and humility, as well as on study and formalized rites. The paper focuses on non-monastics’ strong attraction to monastic teachings on ambiguity as a source of creativity and wonder in uncertain times, as practiced through a combination of cataphatic and apophatic ritual, including Centering Prayer. The number of monastic postulants continues to falter, yet a much larger, “non-gathered” community of non-monastic oblates and neo-monastic contemplatives has grown increasingly reliant on monastics to help provide alternatives. The rising interdependence of monastics and non-monastics may become the basis of a transformation of Christian monasticism and a new concept of religious community.
An Efficient Representation-Based Subspace Clustering Framework for Polarized Hyperspectral Images
Authors: Chen Zhengyi , Zhang Chunmin , Mu Tingkui , Yan Tingyu , Chen Zeyu , Wang Yanqiang
Published: June 2019

Recently, representation-based subspace clustering algorithms for hyperspectral images (HSIs) have been developed with the assumption that pixels belonging to the same land-cover class lie in the same subspace. Polarization is regarded to be a complement to spectral information, but related research only focus on the clustering for HSIs without considering polarization, and cannot effectively process large-scale hyperspectral datasets. In this paper, we propose an efficient representation-based subspace clustering framework for polarized hyperspectral images (PHSIs). Combining with spectral information and polarized information, this framework is extensible for most existing representation-based subspace clustering algorithms. In addition, with a sampling-clustering-classification strategy which firstly clusters selected in-sample data into several classes and then matches the out-of-sample data into these classes by collaborative representation-based classification, the proposed framework significantly reduces the computational complexity of clustering algorithms for PHSIs. Some experiments were carried out to demonstrate the accuracy, efficiency and potential capabilities of the algorithms under the proposed framework.
City-Level Comparison of Urban Land-Cover Configurations from 2000–2015 across 65 Countries within the Global Belt and Road
Authors: Pan Tao , Kuang Wenhui , Hamdi Rafiq , Zhang Chi , Zhang Shu , Li Zhili , Chen Xin
Published: June 2019

The configuration of urban land-covers is essential for improving dwellers’ environments and ecosystem services. A city-level comparison of land-cover changes along the Belt and Road is still unavailable due to the lack of intra-urban land products. A synergistic classification methodology of sub-pixel un-mixing, multiple indices, decision tree classifier, unsupervised (SMDU) classification was established in the study to examine urban land covers across 65 capital cities along the Belt and Road during 2000–2015. The overall accuracies of the 15 m resolution urban products (i.e., the impervious surface area, vegetation, bare soil, and water bodies) derived from Landsat Enhanced Thematic Mapper Plus (ETM+)/Operational Land Imager (OLI) images were 92.88% and 93.19%, with kappa coefficients of 0.84 and 0.85 in 2000 and 2015, respectively. The built-up areas of 65 capital cities increased from 23,696.25 km2 to 29,257.51 km2, with an average growth rate of 370.75 km2/y during 2000–2015. Moreover, urban impervious surface area (ISA) expanded with an average rate of 401.92 km2/y, while the total area of urban green space (UGS) decreased with an average rate of 17.59 km2/y. In different regions, UGS changes declined by 7.37% in humid cities but increased by 14.61% in arid cities. According to the landscape ecology indicators, urban land-cover configurations became more integrated (△Shannon’s Diversity Index (SHDI) = −0.063; △Patch Density (PD) = 0.054) and presented better connectivity (△Connectance Index (CON) = +0.594). The proposed method in this study improved the separation between ISA and bare soil in mixed pixels, and the 15 m intra-urban land-cover product provided essential details of complex urban landscapes and urban ecological needs compared with contemporary global products. These findings provide valuable information for urban planners dealing with human comfort and ecosystem service needs in urban areas.
Sensitivity Analysis and Minimal Measurement Geometry for the Target-Based Calibration of High-End Panoramic Terrestrial Laser Scanners
Authors: Medić Tomislav , Kuhlmann Heiner , Holst Christoph
Published: June 2019

Target-based calibration is the most widely used calibration procedure for terrestrial laser scanners. Nevertheless, the current implementations of this procedure are suboptimal due to the high complexity of their calibration fields. Therefore, designing calibration fields, by selecting optimal target locations with respect to the instrument, is a pending research question. Answering this question would lead to a more efficient and user-friendly calibration, as well as improved calibration results. Herein, we conduct a detailed analysis of the most sensitive target-to-instrument measurement configuration to estimate individual calibration parameters. Based on this analysis, we derive a minimal measurement geometry, sensitive to all mechanical misalignments, relevant for high-end panoramic terrestrial laser scanners. We support our sensitivity analysis by a simulation and empirical experiments followed by a discussion about the advantages and shortcomings of the proposed minimal measurement geometry.
Soil Texture Estimation Using Radar and Optical Data from Sentinel-1 and Sentinel-2
Authors: Bousbih Safa , Zribi Mehrez , Pelletier Charlotte , Gorrab Azza , Lili-Chabaane Zohra , Baghdadi Nicolas , Ben Aissa Nadhira , Mougenot Bernard
Published: June 2019

This paper discusses the combined use of remotely sensed optical and radar data for the estimation and mapping of soil texture. The study is based on Sentinel-1 (S-1) and Sentinel-2 (S-2) data acquired between July and early December 2017, on a semi-arid area about 3000 km2 in central Tunisia. In addition to satellite acquisitions, texture measurement samples were taken in several agricultural fields, characterized by a large range of clay contents (between 13% and 60%). For the period between July and August, various optical indicators of clay content Short-Wave Infrared (SWIR) bands and soil indices) were tested over bare soils. Satellite moisture products, derived from combined S-1 and S-2 data, were also tested as an indicator of soil texture. Algorithms based on the support vector machine (SVM) and random forest (RF) methods are proposed for the classification and mapping of clay content and a three-fold cross-validation is used to evaluate both approaches. The classifications with the best performance are achieved using the soil moisture indicator derived from combined S-1 and S-2 data, with overall accuracy (OA) of 63% and 65% for the SVM and RF classifications, respectively.
RETRACTED: Zhang et al. Estimation of Vegetation Productivity Using a Landsat 8 Time Series in a Heavily Urbanized Area, Central China. Remote Sensing. 2019, 11, 133
Authors: Zhang Meng , Lin Hui , Sun Hua , Cai Yaotong
Published: June 2019

We have been made aware that the experimental data, methodological framework, and description of the corresponding sections in this article are similar to those of another publication (in Chinese with an English abstract) by the first author himself, Zhang and Zeng [...]
Visual and Thermal Image Processing for Facial Specific Landmark Detection to Infer Emotions in a Child-Robot Interaction
Authors: Goulart Christiane , Valadão Carlos , Delisle-Rodriguez Denis , Funayama Douglas , Favarato Alvaro , Baldo Guilherme , Binotte Vinícius , Caldeira Eliete , Bastos-Filho Teodiano
Published: June 2019

Child-Robot Interaction (CRI) has become increasingly addressed in research and applications. This work proposes a system for emotion recognition in children, recording facial images by both visual (RGB—red, green and blue) and Infrared Thermal Imaging (IRTI) cameras. For this purpose, the Viola-Jones algorithm is used on color images to detect facial regions of interest (ROIs), which are transferred to the thermal camera plane by multiplying a homography matrix obtained through the calibration process of the camera system. As a novelty, we propose to compute the error probability for each ROI located over thermal images, using a reference frame manually marked by a trained expert, in order to choose that ROI better placed according to the expert criteria. Then, this selected ROI is used to relocate the other ROIs, increasing the concordance with respect to the reference manual annotations. Afterwards, other methods for feature extraction, dimensionality reduction through Principal Component Analysis (PCA) and pattern classification by Linear Discriminant Analysis (LDA) are applied to infer emotions. The results show that our approach for ROI locations may track facial landmarks with significant low errors with respect to the traditional Viola-Jones algorithm. These ROIs have shown to be relevant for recognition of five emotions, specifically disgust, fear, happiness, sadness, and surprise, with our recognition system based on PCA and LDA achieving mean accuracy (ACC) and Kappa values of 85.75% and 81.84%, respectively. As a second stage, the proposed recognition system was trained with a dataset of thermal images, collected on 28 typically developing children, in order to infer one of five basic emotions (disgust, fear, happiness, sadness, and surprise) during a child-robot interaction. The results show that our system can be integrated to a social robot to infer child emotions during a child-robot interaction.
Vehicle Counting in Video Sequences: An Incremental Subspace Learning Approach
Authors: Rosas-Arias Leonel , Portillo-Portillo Jose , Hernandez-Suarez Aldo , Olivares-Mercado Jesus , Sanchez-Perez Gabriel , Toscano-Medina Karina , Perez-Meana Hector , Sandoval Orozco Ana Lucila , García Villalba Luis Javier
Published: June 2019

The counting of vehicles plays an important role in measuring the behavior patterns of traffic flow in cities, as streets and avenues can get crowded easily. To address this problem, some Intelligent Transport Systems (ITSs) have been implemented in order to count vehicles with already established video surveillance infrastructure. With this in mind, in this paper, we present an on-line learning methodology for counting vehicles in video sequences based on Incremental Principal Component Analysis (Incremental PCA). This incremental learning method allows us to identify the maximum variability (i.e., motion detection) between a previous block of frames and the actual one by using only the first projected eigenvector. Once the projected image is obtained, we apply dynamic thresholding to perform image binarization. Then, a series of post-processing steps are applied to enhance the binary image containing the objects in motion. Finally, we count the number of vehicles by implementing a virtual detection line in each of the road lanes. These lines determine the instants where the vehicles pass completely through them. Results show that our proposed methodology is able to count vehicles with 96.6% accuracy at 26 frames per second on average—dealing with both camera jitter and sudden illumination changes caused by the environment and the camera auto exposure.
Multifunctional Ground Control Points with a Wireless Network for Communication with a UAV
Authors: Han Xiongzhe , Thomasson J. , Xiang Yang , Gharakhani Hussein , Yadav Pappu , Rooney William
Published: June 2019

Ground control points (GCPs) are commonly used for georeferencing in remote sensing. Precise position measurement of the GCPs typically requires careful ground surveying, which is time-consuming and labor-intensive and thus excessively costly if it needs to be repeated multiple times in a season. A system of multifunctional GCPs and a wireless network for communication with an unmanned aerial vehicle (UAV) was developed to improve the speed of GCP setup and provide GCP data collection in real-time during the flight. While testing the system, a single-board computer on a fixed-wing UAV used in the study successfully recorded position data from all the GCPs during the flight. The multifunctional GCPs were also tested for use as references for calibration of reflectance and height for field objects like crops. The test of radiometric calibration resulted in an average reflectance error of 2.0% and a strong relationship (R2 = 0.99) between UAV-based estimates and ground reflectance. Furthermore, the average height difference between UAV-based height estimates and ground measurements was within 10 cm.
Motor Imagery EEG Classification Using Capsule Networks
Authors: Ha Kwon-Woo , Jeong Jin-Woo
Published: June 2019

Various convolutional neural network (CNN)-based approaches have been recently proposed to improve the performance of motor imagery based-brain-computer interfaces (BCIs). However, the classification accuracy of CNNs is compromised when target data are distorted. Specifically for motor imagery electroencephalogram (EEG), the measured signals, even from the same person, are not consistent and can be significantly distorted. To overcome these limitations, we propose to apply a capsule network (CapsNet) for learning various properties of EEG signals, thereby achieving better and more robust performance than previous CNN methods. The proposed CapsNet-based framework classifies the two-class motor imagery, namely right-hand and left-hand movements. The motor imagery EEG signals are first transformed into 2D images using the short-time Fourier transform (STFT) algorithm and then used for training and testing the capsule network. The performance of the proposed framework was evaluated on the BCI competition IV 2b dataset. The proposed framework outperformed state-of-the-art CNN-based methods and various conventional machine learning approaches. The experimental results demonstrate the feasibility of the proposed approach for classification of motor imagery EEG signals.
A Predictive Guidance Obstacle Avoidance Algorithm for AUV in Unknown Environments
Authors: Li Juan , Zhang Jianxin , Zhang Honghan , Yan Zheping
Published: June 2019

A predictive guidance obstacle avoidance algorithm (PGOA) in unknown environments is proposed for autonomous underwater vehicle (AUV) that must adapt to multiple complex obstacle environments. Using the environmental information collected by the Forward-looking Sonar (FLS), the obstacle boundary is simplified by the convex algorithm and Bessel interpolation. Combining the predictive control secondary optimization function and the obstacle avoidance weight function, the predicting obstacle avoidance trajectory parameters are obtained. According to different types of obstacle environments, the corresponding obstacle avoidance rules are formulated. Lastly, combining with the obstacle avoidance parameters and rules, the AUV’s predicting obstacle avoidance trajectory point is obtained. Then AUV can successfully achieve obstacle avoidance using the guidance algorithm. The simulation results show that the PGOA algorithm can better predict the trajectory point of the obstacle avoidance path of AUV, and the secondary optimization function can successfully achieve collision avoidance for different complex obstacle environments. Lastly, comparing the execution efficiency and cost of different algorithms, which deal with various complex obstacle environments, simulation experiment results indicate the high efficiency and great adaptability of the proposed algorithm.
Detection of Driver Braking Intention Using EEG Signals During Simulated Driving
Authors: Nguyen Trung-Hau , Chung Wan-Young
Published: June 2019

In this work, we developed a novel system to detect the braking intention of drivers in emergency situations using electroencephalogram (EEG) signals. The system acquired eight-channel EEG and motion-sensing data from a custom-designed EEG headset during simulated driving. A novel method for accurately labeling the training data during an extremely short period after the onset of an emergency stimulus was introduced. Two types of features, including EEG band power-based and autoregressive (AR)-based, were investigated. It turned out that the AR-based feature in combination with artificial neural network classifier provided better detection accuracy of the system. Experimental results for ten subjects indicated that the proposed system could detect the emergency braking intention approximately 600 ms before the onset of the executed braking event, with high accuracy of 91%. Thus, the proposed system demonstrated the feasibility of developing a brain-controlled vehicle for real-world applications.
“I’m a Poler, and Proud of It”: South Korean Women’s Managed Experiences in a Stigmatized Serious Leisure Activity
Authors: Kim Yunjung , Kwon Sun-Yong
Published: June 2019

The primary purpose of this study is to explore the experiences of South Korean women “doing serious leisure” in what is widely known as a stigmatized activity, pole dance. It seeks to understand the experiences of South Korean women participating in pole dance and to investigate the strategies that are used to cope with the stigma that is experienced during participation. A qualitative research method was applied with an “insider” approach to collecting data. Data were collected through participation observations and in-depth interviews. The findings suggest that South Korean pole participants construct unstigmatized identities through their engagement in pole with its social stereotypes and stigma. Participants’ identities have been firmly embedded as “pole dancers”, “pole athletes”, or “polers”, which they do not feel the need to elucidate to those who are not active members. Their identities are surrounded and intertwined with their rationalized reason for participating in pole dance as serious leisure, along with their individual dedication which manifests their commitment by entering competitions and upgrading their pole skills. Participants and the pole dance community create a social atmosphere where their participation is not taken with stigma but rather with serious dedication to form their own interpretation of pole dance.
Employee Motivation as a Tool to Achieve Sustainability of Business Processes
Authors: Lorincová Silvia , Štarchoň Peter , Weberová Dagmar , Hitka Miloš , Lipoldová Martina
Published: June 2019

Employee performance and their new ideas, as well as their efforts to promote the company in positive ways help build the values of an enterprise. Properly motivated managers, white-collar, and blue-collar workers use their performance to affect the business efficiency, and therefore the success and sustainability of the enterprise. Selecting the right structure of motivation factors, especially those aimed at job category and gender, is the main role of enterprise management. The aim of this study is to analyze and define differences in the perception of the preferred level of motivation in terms of gender and job category. The questionnaires were given to randomly selected employees working in Slovak enterprises in order to ensure variability and randomness of respondent selection which is necessary for relevant data acquisition. Following the average, the order of the importance of motivation factors of 3720 respondents was defined. The Student’s t-test and Tukey’s HSD test were used. We confirmed that there are statistically significant differences in the perception of the motivation in terms of job category. Moreover, we proved the significant differences between genders in the job category of blue-collar workers. We did not observe differences between genders in the other job categories studied. The results reported should be accepted and implemented in motivational programs by the employees of human resource departments as a way to keep up with strategic human resource management.
Leveraging Circular Economy through a Methodology for Smart Service Systems Engineering
Authors: Halstenberg Friedrich A. , Lindow Kai , Stark Rainer
Published: June 2019

Product Service Systems (PSS) and Smart Services are powerful means for deploying Circular Economy (CE) goals in industrial practices, through dematerialization, extension of product lifetime and efficiency increase by digitization. Within this article, approaches from PSS design, Smart Service design and Model-based Systems Engineering (MBSE) are combined to form a Methodology for Smart Service Architecture Definition (MESSIAH). First, analyses of present system modelling procedures and systems modelling notations in terms of their suitability for Smart Service development are presented. The results indicate that current notations and tools do not entirely fit the requirements of Smart Service development, but that they can be adapted in order to do so. The developed methodology includes a modelling language system, the MESSIAH Blueprinting framework, a systematic procedure and MESSIAH CE, which is specifically designed for addressing CE strategies and practices. The methodology was validated on the example of a Smart Sustainable Street Light System for Cycling Security (SHEILA). MESSIAH proved useful to help Smart Service design teams develop service-driven and robust Smart Services. By applying MESSIAH CE, a sustainable Smart Service, which addresses CE goals, has been developed.
Risk Factor Identification of Sustainable Guarantee Network Based on Logistic Regression Algorithm
Authors: He Han , Li Sicheng , Hu Lin , Duarte Nelson , Manta Otilia , Yue Xiao-Guang
Published: June 2019

In order to investigate the factors influencing the sustainable guarantee network and its differences in different spatial and temporal scales, logistic regression algorithm is used to analyze the data of listed companies in 31 provinces, municipalities and autonomous regions in China from 2008 to 2017 (excluding Hong Kong, Macau and Taiwan). The study finds that, overall, companies with better profitability, poor solvency, poor operational capability and higher levels of economic development are more likely to join the guarantee network. On the temporal scale, solvency and regional economic development exert increasing higher impact on the companies’ accession to the guarantee network, and operational capacity has increasingly smaller impact. On the spatial scale, the less close link between company executives and companies in the western region suggests higher possibility to join the guarantee network. The predictive accuracy test results of the logistic regression algorithm show that the training model of the western sample enterprises has the highest prediction accuracy when predicting enterprise behavior of joining the guarantee network, while the accuracy is the lowest in the central region. When forecasting enterprises’ failure to join the guarantee network, the training model of the central sample enterprise has the highest accuracy, while the accuracy is the lowest in the eastern region. This paper discusses the internal and external factors influencing the guarantee network risk from the perspective of spatial and temporal differences of the guarantee network, and discriminates the prediction accuracy of the training model, which means certain guiding significance for listed company management, bank and government to identify and control the guarantee network risk.
Projection of Long-Term Care Costs in China, 2020–2050: Based on the Bayesian Quantile Regression Method
Authors: Xu Xiaocang , Chen Linhong
Published: June 2019

The aging population in China highlights the significance of elderly long-term care (LTC) services. The number of people aged 65 and above increased from 96 million in 2003 to 150 million in 2016, some of whom were disabled due to chronic diseases or the natural effects of aging on bodily functions. Therefore, the measurement of future LTC costs is of crucial value. Following the basic framework but using different empirical methods from those presented in previous literature, this paper attempts to use the Bayesian quantile regression (BQR) method, which has many advantages over traditional linear regression. Another innovation consists of setting and measuring the high, middle, and low levels of LTC cost prediction for each disability state among the elderly in 2020–2050. Our projections suggest that by 2020, LTC costs will increase to median values of 39.46, 8.98, and 20.25 billion dollars for mild, moderate, and severe disabilities, respectively; these numbers will reach 141.7, 32.28, and 72.78 billion dollars by 2050. The median level of daily life care for mild, moderate, and severe disabilities will increase to 26.23, 6.36, and 27 billion dollars. Our results showed that future LTC cost increases will be enormous, and therefore, the establishment of a reasonable individual-social-government payment mechanism is necessary for the LTC system. The future design of an LTCI system must take into account a variety of factors, including the future elderly population, different care conditions, the financial burden of the government, etc., in order to maintain the sustainable development of the LTC system.
Energy-Efficient Real Estate or How It Is Perceived by Potential Homebuyers in Four Latin American Countries
Authors: Encinas Felipe , Marmolejo-Duarte Carlos , Wagemann Elizabeth , Aguirre Carlos
Published: June 2019

This article analyses how energy efficiency regulatory frameworks have been developed in Argentina, Brazil, Mexico and Chile, within a context of developing countries, and it discusses if this context has been able to influence a culture of buildings’ energy efficiency in consumers. An online survey was applied to consumers who wanted to buy a house, aiming to understand their position regarding sustainability, and the role of the state versus the individual role, among other issues. The aim of the study is to identify consumer’s perception of energy efficiency and sustainability to promote a future research agenda in the Latin American context. In general, consumers value sustainability, except when they are presented in opposition to economic growth and social protection. However, it is possible to identify differences between Chile, with an established neoliberal economy, and countries that have economies in transition. Indeed, Argentina and Brazil show differences in terms of the role of the State, or the thermal comfort, which is considered a matter of habits rather than a mere technological problem. For driving more sustainable behaviours, consumers should be engaged in the implementation of these standards, creating a twofold process including homebuyers on one hand and mandatory requirements on the other.
What Do University Students Know about Sustainable Development Goals? A Realistic Approach to the Reception of this UN Program Amongst the Youth Population
Authors: Zamora-Polo Francisco , Sánchez-Martín Jesús , Corrales-Serrano Mario , Espejo-Antúnez Luis
Published: June 2019

The Sustainable Development Goals (SDGs) constitute a working agenda for the international community with the aim of ensuring a better world for future generations. In this context, the development of competences related to SDGs is a challenge for Higher Education Institutions. Although there are several studies that address the relationship between SDGs and university teaching, the students’ knowledge about this subject has not been set out yet. In order to evaluate students’ knowledge, a questionnaire was designed, validated, and administered to students from different degrees. Statistical analysis showed a high reliability for the constructs (Smallest Cronbach’s Alfa = 0.859). The results showed interesting insights, either with descriptive analysis or inferential ones. For example, a low knowledge, in a general way, of SDGs was identified in the whole sample; significant differences between the scores obtained in professional and personal implications of SDGs were also detected and several differences arose between Health and Education students, the latter being more professionally involved with SDGs than the rest of the students.
Configuring a Trust-based Inter-organizational Cooperation Network for Post-industrial Tourist Organizations on a Tourist Route
Authors: Naramski Mateusz , Szromek Adam R.
Published: June 2019

The aim of the paper was to create a configuration model of an inter-organizational network for post-industrial tourist organizations. Nowadays, establishing organized and structured cooperation is necessary not only from a single organization’s perspective, which fights for survival on a highly competitive market, but also from the perspective of a whole touristic region. The quality and social responsibility of a regional touristic product is determined not by a single organization, but by their collective outcome. The main goal was achieved by the analysis of tourist sites, their function within the Industrial Monuments Route (IMR) in Poland, as a case for the conducted study. The authors used trust level indicators as determinants for designating inter-organizational relations in the wrought network model. Those relations concern various forms of cooperation that the researched organizations have selected during a structured interview and were willing to undertake under given conditions. The result is a multi-dimensional model of a cooperation network that can be implemented at IMR and used as a guideline for creating similar models for other thematic tourist routes.