bluuebunny/crossref_metadata_2025 huggingface dataset:
Synergistic Mechanisms Underlie the Peroxide and Coagent Improvement of Natural-Rubber-Toughened Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) Mechanical Performance
Authors: Zhao Xiaoying , Cornish Katrina , Vodovotz Yael
Published: March 2019

Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) is a promising bio-based and biodegradable thermoplastic with restricted industrial applications due to its brittleness and poor processability. Natural rubber (NR) has been used as a toughening agent, but further physical improvements are desired. In this study, rubber toughening efficiency was significantly improved through the synergistic use of a trifunctional acrylic coagent and an organic peroxide during reactive extrusion of PHBV and NR. The rheological, crystallization, thermal, morphological, and mechanical properties of PHBV/NR blends with 15% rubber loading were characterized. The peroxide and coagent synergistically crosslinked the rubber phase and grafted PHBV onto rubber backbones, leading to enhanced rubber modulus and cohesive strength as well as improved PHBV–rubber compatibility and blend homogeneity. Simultaneously, the peroxide–coagent treatment decreased PHBV crystallinity and crystal size and depressed peroxy-radical-caused PHBV degradation. The new PHBV/NR blends had a broader processing window, 75% better toughness (based on the notched impact strength data), and 100% better ductility (based on the tensile elongation data) than pristine PHBV. This new rubber-toughened PHBV material has balanced mechanical performance comparable to that of conventional thermoplastics and is suitable for a wide range of plastic applications.
Comparison of Membrane Inlet and Capillary Introduction Miniature Mass Spectrometry for Liquid Analysis
Authors: Shi Wenyan , Lu Xinqiong , Zhang Jinbo , Zhao Jianhong , Yang Lili , Yu Quan , Wang Xiaohao
Published: March 2019

Membrane inlet mass spectrometry (MIMS) is commonly used for detecting the components in liquid samples. When a liquid sample flows through a membrane, certain analytes will permeate into the vacuum chamber of a mass spectrometer from the solution. The properties of the membrane directly determine the substances that can be detected by MIMS. A capillary introduction (CI) method we previously proposed can also be used to analyze gas and volatile organic compounds (VOCs) dissolved in liquids. When CI analysis is carried out, the sample is drawn into the mass spectrometer with no species discrimination. The performance of these two injection methods was compared in this study, and similar response time and limit of detection (LOD) can be acquired. Specifically, MIMS can provide better detection sensitivity for most inorganic gases and volatile organic compounds. In contrast, capillary introduction shows wider compatibility on analyte types and quantitative range, and it requires less sample consumption. As the two injection methods have comparable characteristics and can be coupled with a miniature mass spectrometer, factors such as cost, pollution, device size, and sample consumption should be comprehensively considered when choosing a satisfactory injection method in practical applications.
Exploring Matrix Effects on Binding Properties and Characterization of Cotinine Molecularly Imprinted Polymer on Paper-Based Scaffold
Authors: Larpant Nutcha , Suwanwong Yaneenart , Boonpangrak Somchai , Laiwattanapaisal Wanida
Published: March 2019

Commercially available sorbent materials for solid-phase extraction are widely used in analytical laboratories. However, non-selective binding is a major obstacle for sample analysis. To overcome this problem, molecularly imprinted polymers (MIPs) were used as selective adsorbent materials prior to determining target analysts. In this study, the use of non-covalent molecularly imprinted polymers (MIPs) for cotinine adsorption on a paper-based scaffold was studied. Fiberglass paper was used as a paper scaffold for cotinine-selective MIP adsorption with the use of 0.5% agarose gel. The effects of salt, pH, sample matrix, and solvent on the cotinine adsorption and extraction process were investigated. Under optimal conditions, the adsorption isotherm of synthesized MIPs increased to 125.41 µg/g, whereas the maximum adsorption isotherm of non-imprinted polymers (NIPs) was stable at 42.86 µg/g. The ability of the MIP paper scaffold to absorb cotinine in water medium was approximately 1.8–2.8-fold higher than that of the NIP scaffold. From Scatchard analysis, two dissociation constants of MIPs were calculated to be 2.56 and 27.03 µM. Nicotine, myosmine, and N-nitrosonornicotine were used for selectivity testing, and the calculated selectivity factor of cotinine to nicotine, myosmine, and N-nitrosonornicotine was 1.56, 2.69, and 2.05, respectively. Overall, the MIP paper scaffold is promising for simple onsite sampling of cotinine and can be used to assess tobacco smoke exposure.
Polymer Having Dicationic Structure in Dumbbell Shape for Forward Osmosis Process
Authors: Kim Taehyung , Ju Changha , Park Chanhyuk , Kang Hyo
Published: March 2019

The thermal-responsive polymers, poly(alkane-1,#-diylbis(tri-n-butylphosphonium) 4-vinylbenzenesulfonate) (PSSBP#, # = 8, 6, and 4), where # is the number of carbon atoms in the central bridge structure of the dicationic phosphonium moiety, were synthesized to examine their potential application as draw solutes in forward osmosis (FO). The polymers exhibited low critical solution temperature (LCST) characteristics in aqueous solutions, which is essential for recovering a draw solute from pure water. The LCSTs of the 20 wt% aqueous solutions of PSSBP8, PSSBP6, and PSSBP4 were confirmed to be approximately 30, 38, and 26 °C, respectively, which is advantageous in terms of energy requirements for the recovering draw solute. When the concentration of the PSSBP4 draw solution was 20 wt%, water flux and reverse solute flux were approximately 1.61 LMH and 0.91 gMH, respectively, in the active layer facing the draw solution (AL-DS) system when the feed solution was distilled water. The PSSBP# thermal-responsive draw solute has considerable potential for use as a next-generation draw solute because of its excellent osmotic performance and efficient recovery. Therefore, this study provides inspiration for novel ideas regarding structural transformations of polymers and their applicability as draw solutes.
Strategic Framework for Parameterization of Cell Culture Models
Authors: Kotidis Pavlos , Kontoravdi Cleo
Published: March 2019

Global Sensitivity Analysis (GSA) is a technique that numerically evaluates the significance of model parameters with the aim of reducing the number of parameters that need to be estimated accurately from experimental data. In the work presented herein, we explore different methods and criteria in the sensitivity analysis of a recently developed mathematical model to describe Chinese hamster ovary (CHO) cell metabolism in order to establish a strategic, transferable framework for parameterizing mechanistic cell culture models. For that reason, several types of GSA employing different sampling methods (Sobol’, Pseudo-random and Scrambled-Sobol’), parameter deviations (10%, 30% and 50%) and sensitivity index significance thresholds (0.05, 0.1 and 0.2) were examined. The results were evaluated according to the goodness of fit between the simulation results and experimental data from fed-batch CHO cell cultures. Then, the predictive capability of the model was tested against four different feeding experiments. Parameter value deviation levels proved not to have a significant effect on the results of the sensitivity analysis, while the Sobol’ and Scrambled-Sobol’ sampling methods and a 0.1 significance threshold were found to be the optimum settings. The resulting framework was finally used to calibrate the model for another CHO cell line, resulting in a good overall fit. The results of this work set the basis for the use of a single mechanistic metabolic model that can be easily adapted through the proposed sensitivity analysis method to the behavior of different cell lines and therefore minimize the experimental cost of model development.
A Novel Multiphase Methodology Simulating Three Phase Flows in a Steel Ladle
Authors: Ramírez-Argáez Marco A. , Dutta Abhishek , Amaro-Villeda A. , González-Rivera C. , Conejo A. N.
Published: March 2019

Mixing phenomena in metallurgical steel ladles by bottom gas injection involves three phases namely, liquid molten steel, liquid slag and gaseous argon. In order to numerically solve this three-phase fluid flow system, a new approach is proposed which considers the physical nature of the gas being a dispersed phase in the liquid, while the two liquids namely, molten steel and slag are continuous phases initially separated by a sharp interface. The model was developed with the combination of two algorithms namely, IPSA (inter phase slip algorithm) where the gas bubbles are given a Eulerian approach since are considered as an interpenetrating phase in the two liquids and VOF (volume of fluid) in which the liquid is divided into two separate liquids but depending on the physical properties of each liquid they are assigned a mass fraction of each liquid. This implies that both the liquid phases (steel and slag) and the gas phase (argon) were solved for the mass balance. The Navier–Stokes conservation equations and the gas-phase turbulence in the liquid phases were solved in combination with the standard k-ε turbulence model. The mathematical model was successfully validated against flow patterns obtained experimentally using particle image velocimetry (PIV) and by the calculation of the area of the slag eye formed in a 1/17th water–oil physical model. The model was applied to an industrial ladle to describe in detail the turbulent flow structure of the multiphase system.
Designing Supply Networks in Automobile and Electronics Manufacturing Industries: A Multiplex Analysis
Authors: Kim Myung Kyo , Narasimhan Ram
Published: March 2019

This study investigates the process of how the original equipment manufacturers (OEMs) in automobile and consumer electronics industries design their supply networks. In contrast to the sociological viewpoint, which regards the emergence of networks as a social and psychological phenomenon occurring among non-predetermined individuals, this paper attempts to provide a strategic supply network perspective that views the supply network as a strategic choice made by an OEM. Anchored in the multiplex investigation of supply network architectures, this study looks into the following specific questions: (1) Are an OEM’s strategic intent choices associated with supply network architecture and (2) If so, what differential effects do those strategic intents have on the architectural properties of the supply network? Further field investigations were conducted to provide deeper insights into the quantitative and qualitative findings from statistical analyses.
A Dynamic Biofilm Model for a Microbial Electrolysis Cell
Authors: Flores-Estrella René Alejandro , de Jesús Garza-Rubalcava Uriel , Haarstrick Andreas , Alcaraz-González Victor
Published: March 2019

In this work, a mathematical description of a Microbial Electrolysis Cell (MEC) is proposed, taking into account the global mass balances of the different species in the system and considering that all the involved microorganisms are attached to the anodic biological film. Three main biological reactions are introduced, which were obtained from the solution of partial differential equations describing the spatial distribution of potential and substrate in the biofilm. The simulation of the model was carried out using numerical methods, and the results are discussed.
Laban-Inspired Task-Constrained Variable Motion Generation on Expressive Aerial Robots
Authors: Cui Hang , Maguire Catherine , LaViers Amy
Published: March 2019

This paper presents a method for creating expressive aerial robots through an algorithmic procedure for creating variable motion under given task constraints. This work is informed by the close study of the Laban/Bartenieff movement system, and movement observation from this discipline will provide important analysis of the method, offering descriptive words and fitting contexts—a choreographic frame—for the motion styles produced. User studies that use utilize this qualitative analysis then validate that the method can be used to generate appropriate motion in in-home contexts. The accuracy of an individual descriptive word for the developed motion is up to 77% and context accuracy is up to 83%. A capacity for state discernment from motion profile is essential in the context of projects working toward developing in-home robots.
Long-Term Adaptivity in Distributed Intelligent Systems: Study of ViaBots in a Simulated Environment
Authors: Ardavs Arturs , Pudane Mara , Lavendelis Egons , Nikitenko Agris
Published: March 2019

This paper proposes a long-term adaptive distributed intelligent systems model which combines an organization theory and multi-agent paradigm—ViaBots. Currently, the need for adaptivity in autonomous intelligent systems becomes crucial due to the increase in the complexity and diversity of the tasks that autonomous robots are employed for. To deal with the design complexity of such systems within the ViaBots model, each part of the modeled system is designed as an autonomous agent and the entire model, as a multi-agent system. Based on the viable system model, which is widely used to ensure viability, (i.e., long-term autonomy of organizations), the ViaBots model defines the necessary roles a system must fulfill to be capable to adapt both to changes in its environment (like changes in the task) and changes within the system itself (like availability of a particular robot). Along with static role assignments, ViaBots propose a mechanism for role transition from one agent to another as one of the key elements of long term adaptivity. The model has been validated in a simulated environment using an example of a conveyor system. The simulated model enabled the multi-robot system to adapt to the quantity and characteristics of the available robots, as well as to the changes in the parts to be processed by the system.
A Non-Reference Temperature Histogram Method for Determining Tc from Ground-Based Thermal Imagery of Orchard Tree Canopies
Authors: Salgadoe Arachchige Surantha Ashan , Robson Andrew James , Lamb David William , Schneider Derek
Published: March 2019

Obtaining average canopy temperature (Tc) by thresholding canopy pixels from on-ground thermal imagery has historically been undertaken using ‘wet’ and ‘dry’ reference surfaces in the field (reference temperature thresholding). However, this method is extremely time inefficient and can suffer inaccuracies if the surfaces are non-standardised or unable to stabilise with the environment. The research presented in this paper evaluates non-reference techniques to obtain average canopy temperature (Tc) from thermal imagery of avocado trees, both for the shaded side and sunlit side, without the need of reference temperature values. A sample of 510 thermal images (from 130 avocado trees) were acquired with a FLIR B250 handheld thermal imaging camera. Two methods based on temperature histograms were evaluated for removing non-canopy-related pixel information from the analysis, enabling Tc to be determined. These approaches included: 1) Histogram gradient thresholding based on temperature intensity changes (HG); and 2) histogram thresholding at one or more standard deviation (SD) above and below the mean. The HG method was found to be more accurate (R2 > 0.95) than the SD method in defining canopy pixels and calculating Tc from each thermal image (shaded and sunlit) when compared to the standard reference temperature thresholding method. The results from this study present an alternative non-reference method for determining Tc from ground-based thermal imagery without the need of calibration surfaces. As such, it offers a more efficient and computationally autonomous method that will ultimately support the greater adoption of non-invasive thermal technologies within a precision agricultural system.
3D Forest Mapping Using A Low-Cost UAV Laser Scanning System: Investigation and Comparison
Authors: Li Jianping , Yang Bisheng , Cong Yangzi , Cao Lin , Fu Xiaoyao , Dong Zhen
Published: March 2019

Automatic 3D forest mapping and individual tree characteristics estimation are essential for forest management and ecosystem maintenance. The low-cost unmanned aerial vehicle (UAV) laser scanning (ULS) is a newly developed tool for cost-effectively collecting 3D information and attempts to use it for 3D forest mapping have been made, due to its capability to provide 3D information with a lower cost and higher flexibility than the standard ULS and airborne laser scanning (ALS). As the direct georeferenced point clouds may suffer from distortion caused by the poor performance of a low-cost inertial measurement unit (IMU), and 3D forest mapping using low-cost ULS poses a great challenge. Therefore, this paper utilized global navigation satellite system (GNSS) and IMU aided Structure-from-Motion (SfM) for trajectory estimation, and, hence, overcomes the poor performance of low-cost IMUs. The accuracy of the low-cost ULS point clouds was compared with the ground truth data collected by a commercial ULS system. Furthermore, the effectiveness of individual trees segmentation and tree characteristics estimation derived from the low-cost ULS point clouds were accessed. Experiments were undertaken in Dongtai forest farm, Yancheng City, Jiangsu Province, China. The results showed that the low-cost ULS achieved good point clouds quality from visual inspection and comparable individual tree segmentation results (P = 0.87, r = 0.84, F = 0.85) with the commercial system. Individual tree height estimation performed well (coefficient of determination (R2) = 0.998, root-mean-square error (RMSE) = 0.323 m) using the low-cost ULS. As for individual tree crown diameter estimation, low-cost ULS achieved good results (R2 = 0.806, RMSE = 0.195 m) after eliminating outliers. In general, such results illustrated the high potential of the low-cost ULS in 3D forest mapping, even though 3D forest mapping using the low-cost ULS requires further research.
Analyzing the Uncertainty of Estimating Forest Aboveground Biomass Using Optical Imagery and Spaceborne LiDAR
Authors: Sun Xiaofang , Li Guicai , Wang Meng , Fan Zemeng
Published: March 2019

Accurate estimation of forest aboveground biomass (AGB) is important for carbon accounting. Forest AGB estimation has been conducted with a variety of data sources and prediction methods, but many uncertainties still exist. In this study, six prediction methods, including Gaussian processes, stepwise linear regression, nonlinear regression using a logistic model, partial least squares regression, random forest, and support vector machines were used to estimate forest AGB in Jiangxi Province, China, by combining Geoscience Laser Altimeter System (GLAS) data, Moderate Resolution Imaging Spectroradiometer (MODIS) data, and field measurements. We compared the effect of three factors (prediction methods, sample sizes of field measurements, and cross-validation settings) on the predictive quality of the methods. The results showed that the prediction methods had the most considerable effect on the prediction quality. In most cases, random forest produced more accurate estimates than the other methods. The sample sizes had an obvious effect on accuracy, especially for the random forest model. The accuracy increased with increasing sample sizes. The random forest algorithm with a large number of field measurements, was the most precise (coefficient of determination (R2) = 0.73, root mean square error (RMSE) = 23.58 Mg/ha). Increasing the number of folds within the cross-validation settings improved the R2 values. However, no apparent change occurred in RMSE for different numbers of folds. Finally, the wall-to-wall forest AGB map over the study area was generated using the random forest model.
Spatio-Temporal Analysis of Vegetation Dynamics as a Response to Climate Variability and Drought Patterns in the Semiarid Region, Eritrea
Authors: Measho Simon , Chen Baozhang , Trisurat Yongyut , Pellikka Petri , Guo Lifeng , Arunyawat Sunsanee , Tuankrua Venus , Ogbazghi Woldeselassie , Yemane Tecle
Published: March 2019

There is a growing concern over change in vegetation dynamics and drought patterns with the increasing climate variability and warming trends in Africa, particularly in the semiarid regions of East Africa. Here, several geospatial techniques and datasets were used to analyze the spatio-temporal vegetation dynamics in response to climate (precipitation and temperature) and drought in Eritrea from 2000 to 2017. A pixel-based trend analysis was performed, and a Pearson correlation coefficient was computed between vegetation indices and climate variables. In addition, vegetation condition index (VCI) and standard precipitation index (SPI) classifications were used to assess drought patterns in the country. The results demonstrated that there was a decreasing NDVI (Normalized Difference Vegetation Index) slope at both annual and seasonal time scales. In the study area, 57.1% of the pixels showed a decreasing annual NDVI trend, while the significance was higher in South-Western Eritrea. In most of the agro-ecological zones, the shrublands and croplands showed decreasing NDVI trends. About 87.16% of the study area had a positive correlation between growing season NDVI and precipitation (39.34%, p < 0.05). The Gash Barka region of the country showed the strongest and most significant correlations between NDVI and precipitation values. The specific drought assessments based on VCI and SPI summarized that Eritrea had been exposed to recurrent droughts of moderate to extreme conditions during the last 18 years. Based on the correlation analysis and drought patterns, this study confirms that low precipitation was mainly attributed to the slowly declining vegetation trends and increased drought conditions in the semi-arid region. Therefore, immediate action is needed to minimize the negative impact of climate variability and increasing aridity in vegetation and ecosystem services.
NDVI Identification and Survey of a Roman Road in the Northern Spanish Province of Álava
Authors: Fuldain González Juan José , Varón Hernández Félix Rafael
Published: March 2019

The Iter 34 (Antonine Itinerary XXXIV) is the name of the Roman road that crosses the province of Álava from west to east. Since no specific path was officially recognized before our study, the remains of the road did not benefit from heritage protection. In 2017, we made a project to determine the course of the road through rural Álava. In addition to traditional archaeological excavation and prospecting techniques, we used UAVs (unmanned aerial vehicle) to produce NDVI (normalized difference vegetation index) orthomosaic plans of ten cultivated areas through which the road is conjectured to pass. NDVI orthomosaics let us see crop marks better than with conventional photography, allowing us to detect the crop marks during times of the year and in places where conventional photography would fail to show them. Thanks to the NDVI orthomosaics, remains of the road were identified not only in places where we knew it existed, but also in previously unknown locations. Furthermore, other archaeological features were identified close to the roadway. This technique heralds a great advance in non-invasive methods of archaeological surveying. By using precision farming techniques we have identified the course of the Roman road Iter 34 in several locations in a short period of time and with few resources.
Identifying Mangrove Deforestation Hotspots in South Asia, Southeast Asia and Asia-Pacific
Authors: Gandhi Samir , Jones Trevor Gareth
Published: March 2019

Mangroves inhabit highly productive inter-tidal ecosystems in >120 countries in the tropics and subtropics providing critical goods and services to coastal communities and contributing to global climate change mitigation owing to substantial carbon stocks. Despite their importance, global mangrove distribution continues to decline primarily due to anthropogenic drivers which vary by region/country. South Asia, Southeast Asia and Asia-Pacific contain approximately 46% of the world’s mangrove ecosystems, including the most biodiverse mangrove forests. This region also exhibits the highest global rates of mangrove loss. Remotely sensed data provides timely and accurate information on mangrove distribution and dynamics critical for targeting loss hotspots and guiding intervention. This report inventories, describes and compares all known single- and multi-date remotely sensed datasets with regional coverage and provides areal mangrove extents by country. Multi-date datasets were used to estimate dynamics and identify loss hotspots (i.e., countries that exhibit greatest proportional loss). Results indicate Myanmar is the primary mangrove loss hotspot, exhibiting 35% loss from 1975–2005 and 28% between 2000–2014. Rates of loss in Myanmar were four times the global average from 2000–2012. The Philippines is additionally identified as a loss hotspot, with secondary hotspots including Malaysia, Cambodia and Indonesia. This information helps inform and guide mangrove conservation, restoration and managed-use within the region.
Automated Mapping of Woody Debris over Harvested Forest Plantations Using UAVs, High-Resolution Imagery, and Machine Learning
Authors: Windrim Lloyd , Bryson Mitch , McLean Michael , Randle Jeremy , Stone Christine
Published: March 2019

Surveying of woody debris left over from harvesting operations on managed forests is an important step in monitoring site quality, managing the extraction of residues and reconciling differences in pre-harvest inventories and actual timber yields. Traditional methods for post-harvest survey involving manual assessment of debris on the ground over small sample plots are labor-intensive, time-consuming, and do not scale well to heterogeneous landscapes. In this paper, we propose and evaluate new automated methods for the collection and interpretation of high-resolution, Unmanned Aerial Vehicle (UAV)-borne imagery over post-harvested forests for estimating quantities of fine and coarse woody debris. Using high-resolution, geo-registered color mosaics generated from UAV-borne images, we develop manual and automated processing methods for detecting, segmenting and counting both fine and coarse woody debris, including tree stumps, exploiting state-of-the-art machine learning and image processing techniques. Results are presented using imagery over a post-harvested compartment in a Pinus radiata plantation and demonstrate the capacity for both manual image annotations and automated image processing to accurately detect and quantify coarse woody debris and stumps left over after harvest, providing a cost-effective and scalable survey method for forest managers.
Guide Star Selection for the Three-FOV Daytime Star Sensor
Authors: Wu Liang , Xu Qian , Wang Haojing , Lyu Hongwu , Li Kaipeng
Published: March 2019

To realize the application of the star sensor in the all-day carrier platform, a three-field-of-view (three-FOV) star sensor in short-wave infrared (SWIR) band is considered. This new prototype employs new techniques that can improve the detection capability of the star sensor, when the huge size of star identification feature database becomes a big obstacle. Hence, a way to thin the guide star catalog for three-FOV daytime star sensor is studied. Firstly, an introduction of three-FOV star sensor and an example of three-FOV daytime star sensor with narrow FOV are presented. According to this model and the requirement of triangular star identification method, two constraints based on the number and the brightness of the stars in FOV are put forward for guide star selection. Then on the basis of these constraints, the improved spherical spiral method (ISSM) is proposed and the optimal number of reference points of ISSM is discussed. Finally, to demonstrate the performance of the ISSM, guide star catalogs are generated by ISSM, magnitude filter method (MFM), 1st order self-organizing guide star selection method (1st-SOPM) and the spherical spiral method (SSM), respectively. The results show that the guide star catalog generated by ISSM has the smallest size and the number and brightness characteristics of its guide stars are better than the other methods. ISSM is effective for the guide star selection in the three-FOV daytime star sensor.
Deformation Monitoring of Earth Fissure Hazards Using Terrestrial Laser Scanning
Authors: Ge Yunfeng , Tang Huiming , Gong Xulong , Zhao Binbin , Lu Yi , Chen Yong , Lin Zishan , Chen Hongzhi , Qiu Yashi
Published: March 2019

Deformation monitoring is a powerful tool to understand the formation mechanism of earth fissure hazards, enabling the engineering and planning efforts to be more effective. To assess the evolution characteristics of the Yangshuli earth fissure hazard more completely, terrestrial laser scanning (TLS), a remote sensing technique which is regarded as one of the most promising surveying technologies in geohazard monitoring, was employed to detect the changes to ground surfaces and buildings in small- and large-scales, respectively. Time-series of high-density point clouds were collected through 5 sequential scans from 2014 to 2017 and then pre-processing was performed to filter the noise data of point clouds. A tiny deformation was observed on both the scarp and the walls, based on the local displacement analysis. The relative height differences between the two sides of the scarp increase slowly from 0.169 m to 0.178 m, while no obvious inclining (the maximum tilt reaches just to 0.0023) happens on the two walls, based on tilt measurement. Meanwhile, global displacement analysis indicates that the overall settlement slowly increases for the ground surface, but the regions in the left side of scarp are characterized by a relatively larger vertical displacement than the right. Furthermore, the comparisons of monitoring results on the same measuring line are discussed in this study and TLS monitoring results have an acceptable consistency with the global positioning system (GPS) measurements. The case study shows that the TLS technique can provide an adequate solution in deformation monitoring of earth fissure hazards, with high effectiveness and applicability.
A Post-Training Study on the Budgeting Criteria Set and Priority for MALE UAS Design
Authors: Chi Li-Pin , Fu Chen-Hua , Chyng Jeng-Pyng , Zhuang Zheng-Yun , Huang Jen-Hung
Published: March 2019

A recent study proposed a systematic “(budgeting) knowledge discovery educational framework” (BKDEF). This BKDEF is focused on guiding staff training courses for enhancing the ability to allocate the “large but limited” budget for single, high-cost product design. However, except for its initial application to support the budget planning for the next generation fighter design, the framework’s effectiveness is still awaiting further scrutiny. This study fills the gap by providing the “second application” of BKDEF, which is to support another similar decision for designing the medium-altitude long-endurance unmanned aerial system (MALE UAS). This paper verified the effectiveness of the framework through an empirical application and obtained the knowledge required to allocate a budget for MALE UAS design following the group-opinion basis. In addition, the original analytical style for the last “decision analysis” phase of BKDEF, which included pure quantitative analytical items in order to understand the similarities and diversities in the individual opinions, was replaced by a comparative study to discover the homogeneity and heterogeneity between the two budgeting decisions in a larger scope. As a consequence, the two criteria sets did not overlap despite both decisions being related to military aircraft design. The absolute weights for the MALE UAS design criteria were more balanced than those for the air-superior fighter design, even if the size of the criteria set was larger. The results pave a way for future studies on how other military aircrafts are designed, as more confidence about the use of a BKDEF can be gained from increasing applications, thus more insightful aerospace knowledge can be exploited in comparisons with these works.
Impact of Biogas and Waste Fats Methyl Esters on NO, NO2, CO, and PM Emission by Dual Fuel Diesel Engine
Authors: Golimowski Wojciech , Krzaczek Paweł , Marcinkowski Damian , Gracz Weronika , Wałowski Grzegorz
Published: March 2019

The aim of this study was to perform a comparative analysis of the unit gas emission value in the exhaust of a dual fuel diesel engine. The results of the effects of a diesel engine’s applications in biogas plants and the method for calculating mass gas emissions per unit of produced electricity are shown. The test was performed using a two-cylinder, naturally aspirated, liquid-cooled diesel engine. The diesel engine powered a generator connected to the grid. The engine was fed with liquid fuels—waste cooking oil methyl ester (UCOME) and diesel fuel (DF)—and with a gas fuel, biogas (BG). The engine ran at a constant rotational speed (2000 rpm ± 30 rpm) with variable load. The gas analyzer measured the amount of CO, NO, NO2, and PM (particulate matter) in exhaust gas. This gas content share was then converted to mass per engine generated energy unit. This experiment showed the effect of BG introduced to the intake manifold on fuel combustion, as well as an increase in CO and NO2 emission and decrease in NO and PM. In terms of dependence of exhaust emissions on the type of liquid fuel used, the use of UCOME as opposed to diesel fuel resulted in PM reduction and increase of NO emissions.
Application of Nonnegative Tensor Factorization for Intercity Rail–Air Transport Supply Configuration Pattern Recognition
Authors: Zhong Han , Qi Geqi , Guan Wei , Hua Xiaochen
Published: March 2019

With the rapid expansion of the railway represented by high-speed rail (HSR) in China, competition between railway and aviation will become increasingly common on a large scale. Beijing, Shanghai, and Guangzhou are the busiest cities and the hubs of railway and aviation transportation in China. Obtaining their supply configuration patterns can help identify defects in planning. To achieve that, supply level is proposed, which is a weighted supply traffic volume that takes population and distance factors into account. Then supply configuration can be expressed as the distribution of supply level over time periods with different railway stations, airports, and city categories. Furthermore, nonnegative tensor factorization (NTF) is applied to pattern recognition by introducing CP (CANDECOMP/PARAFAC) decomposition and the block coordinate descent (BCD) algorithm for the selected data set. Numerical experiments show that the designed method has good performance in terms of computation speed and solution quality. Recognition results indicate the significant pattern characteristics of rail–air transport for Beijing, Shanghai, and Guangzhou are extracted, which can provide some theoretical references for practical policymakers.
The Social Costs of Marine Litter along the East China Sea: Evidence from Ten Coastal Scenic Spots of Zhejiang Province, China
Authors: Shen Manhong , Mao Di , Xie Huiming , Li Chuanzhong
Published: March 2019

Marine litter poses numerous threats to the global environment. To estimate the social costs of marine litter in China, two stated preference methods, namely the contingent valuation model (CVM) and the choice experiment model (CEM), were used in this research. This paper conducted surveys at ten different beaches along the East China Sea in Zhejiang province in October 2017. The results indicate that approximately 74.1% of the interviewees are willing to volunteer to participate in clean-up programmes and are willing to spend 1.5 days per month on average in their daily lives, which equates to a potential loss of income of USD 1.08 per day. The willingness to pay for the removal of the main types of litter ranges from USD 0.12–0.20 per visitor across the four sample cities, which is mainly determined by the degree of the removal, the crowdedness of the beach and the visitor’s perception. The social costs are USD 1.08–1.40 per visitor when the contingent valuation method is applied and USD 1.00–1.07 per visitor when the choice experiment method is adopted, which accounts for 8–14% of the beach entrance fee. The analysis of the social costs of marine litter yielded some useful implications regarding future coastal management policy, including extra entrance fee, the quality-oriented environmental strategy and more incentives to volunteers.
Using RISKPLAN for Earthquake Risk Assessment in Sichuan Province, China
Authors: Shi Yan , Seeland Klaus
Published: March 2019

Sichuan Province of China is a prominent population and economic growth center as well as an earthquake-stricken region. A sound understanding of the seismic risk that Sichuan Province is facing is useful to raise risk awareness, achieve disaster risk reduction (DRR), and guarantee sustainable socio-economic development. Earthquake risk assessment is the first step in these efforts. This study strives to demonstrate the feasibility of applying an integrated earthquake risk assessment in Sichuan Province of China using RISKPLAN, a risk evaluation tool of natural hazards developed by the Swiss Federal Office for the Environment (FOEN). The time and location of seismic events in Sichuan were incorporated into three scenarios and calculated with respect to expected losses under different assumed conditions of earthquake occurrence, such as the recurrence interval and magnitude. Furthermore, cost-effectiveness calculations were made regarding the various possible scenarios to assess the ratio of expected losses and the required financial means for prevention and mitigation measures against the effects of seismic activities in Sichuan. Our results show that when the magnitude of the seismic event is greater than expected, reduction and mitigation investments for a possible earthquake risk will be all the more rewarding.
Transit versus Nature. Depreciation of Environmental Values of the Road Alleys. Case Study: Gamerki-Jonkowo, Poland
Authors: Suchocka Marzena , Błaszczyk Magdalena , Juźwiak Adam , Duriasz Joanna , Bohdan Adam , Stolarczyk Jerzy
Published: March 2019

Road alleys are multifunctional features in open landscapes that serve as ecological corridors connecting habitats, and play an important role in sustaining ecological stability. However, multiple road authorities claim that tree-lined routes pose a threat to traffic safety and should therefore be removed. This aspect of safety seems crucial to authorities, significantly overwhelming the benefits of road alleys. Problems with the vitality of the trees (which are mainly mature and aging) deliver arguments for cutting them down. The aim of this paper is to examine the environmental and natural value of road alleys based on a 14 km long section of the Gamerki—Jonkowo Road in the Province of Warmia (Northeast Poland). Further, we aim to verify the degree of hazard posed by trees to be felled for safety reasons. An examination framework with six components was developed for the research. This framework includes a tree risk assessment and vitality evaluation, pulling tests, an examination of the protected hermit beetle and lichen species, and an examination of bat fauna. The results revealed that no trees were in the resignation phase and confirmed that the alley is a unique natural habitat with protected species of lichen, a few bats, and valuable insect species, among others the hermit beetle (Osmoderma barnabita). Therefore, the alley cannot be perceived only as a component of the road infrastructure. The maintenance of the trees seems to be essential when taking into account the environmental stability of the region.
Do Amphibians and Cash Crops Compete for Scarce Water? A Spatial Correlation Analysis
Authors: Moran Daniel , Petersone Milda , Verones Francesca
Published: March 2019

It has been argued that the trade of water intensive crops may be beneficial as it helps alleviate regional differences in water scarcity by effectively transporting moisture from humid regions to arid ones. However, the incentive to grow export crops can also intensify pressure on local water resources. Water abstraction for use in growing cash crops can affect rivers and wetlands with rich biodiversity reserves. In many macro-level environmental assessments, it is assumed that water use is a proxy for biodiversity pressure. Here we use correlation analysis to test the degree of spatial overlap between areas with high scarce-water consumption for cash crop production (i.e., crops where a majority is exported) and areas with high species richness or vulnerability of Red-Listed amphibians. We find that, globally, there is relatively little spatial overlap between areas where scarce water is used for export production and the habitat range of stressed amphibians.
Residents’ Attitudes towards Overtourism from the Perspective of Tourism Impacts and Cooperation—The Case of Ljubljana
Authors: Kuščer Kir , Mihalič Tanja
Published: March 2019

Increasing worldwide evidence on disruptive unsustainable impacts, caused by growing overtourism, is shaking tourism research agendas and destination management styles. Monitoring the risks of overtourism is becoming a relevant issue for every destination. This paper combines the existing sustainability–responsibility tourism framework from academic research with current industry research on overtourism in order to propose a sustainable tourism impact and stakeholder cooperation based on the overtourism risk monitoring model. Data-based social science statistical methodology and tools were used to identify the residents’ attitudes about tourism impacts and cooperation in the destination of Ljubljana, Slovenia. Ljubljana represents a case of a fast-growing tourism destination, which might lead to overtourism. Research has confirmed some impact factors that negatively influence the satisfaction of local residents with tourism presence. Furthermore, it has been confirmed that increased cooperation mitigates the negative perceptions of residents on tourism presence. In its present form, the proposed monitoring model can be used to examine the overtourism situation and to inform sustainable tourism policy and management for every destination.
Influence of Cattaneo–Christov Heat Flux on MHD Jeffrey, Maxwell, and Oldroyd-B Nanofluids with Homogeneous-Heterogeneous Reaction
Authors: Saeed Anwar , Islam Saeed , Dawar Abdullah , Shah Zahir , Kumam Poom , Khan Waris
Published: March 2019

This research article deals with the determination of magnetohydrodynamic steady flow of three combile nanofluids (Jefferey, Maxwell, and Oldroyd-B) over a stretched surface. The surface is considered to be linear. The Cattaneo–Christov heat flux model was considered necessary to study the relaxation properties of the fluid flow. The influence of homogeneous-heterogeneous reactions (active for auto catalysts and reactants) has been taken in account. The modeled problem is solved analytically. The impressions of the magnetic field, Prandtl number, thermal relaxation time, Schmidt number, homogeneous–heterogeneous reactions strength are considered through graphs. The velocity field diminished with an increasing magnetic field. The temperature field diminished with an increasing Prandtl number and thermal relaxation time. The concentration field upsurged with the increasing Schmidt number which decreased with increasing homogeneous-heterogeneous reactions strength. Furthermore, the impact of these parameters on skin fraction, Nusselt number, and Sherwood number were also accessible through tables. A comparison between analytical and numerical methods has been presented both graphically and numerically.
A New Ranking Methodology for Pythagorean Trapezoidal Uncertain Linguistic Fuzzy Sets Based on Einstein Operations
Authors: Khan Arshad Ahmad , Abdullah Saleem , Shakeel Muhammad , Khan Faisal , Amin Noor ul , Luo Jianchao
Published: March 2019

In this article, we proposed new Pythagorean trapezoidal uncertain linguistic fuzzy aggregation information—namely, the Pythagorean trapezoidal uncertain linguistic fuzzy Einstein weighted averaging (PTULFEWA) operator, the Pythagorean trapezoidal uncertain linguistic fuzzy Einstein ordered weighted averaging (PTULFEOWA) operator, and the Pythagorean trapezoidal uncertain linguistic fuzzy Einstein hybrid weighted averaging (PTULFEHWA) operator—using the Einstein operational laws. We studied some important properties of the suggested aggregation operators and showed that the PTULFEHWA is more general than the other proposed operators, which simplifies these aggregation operators. Furthermore, we presented a multiple attribute group decision making (MADM) process for the proposed aggregation operators under the Pythagorean trapezoidal uncertain linguistic fuzzy (PTULF) environment. A numerical example was constructed to determine the effectiveness and practicality of the proposed approach. Lastly, a comparative analysis was performed of the presented approach with existing approaches to show that the proposed method is consistent and provides more information that may be useful for complex problems in the decision-making process.
A Novel Approach to Multi-Attribute Group Decision-Making based on Interval-Valued Intuitionistic Fuzzy Power Muirhead Mean
Authors: Xu Wuhuan , Shang Xiaopu , Wang Jun , Li Weizi
Published: March 2019

This paper focuses on multi-attribute group decision-making (MAGDM) course in which attributes are evaluated in terms of interval-valued intuitionistic fuzzy (IVIF) information. More explicitly, this paper introduces new aggregation operators for IVIF information and further proposes a new IVIF MAGDM method. The power average (PA) operator and the Muirhead mean (MM) are two powerful and effective information aggregation technologies. The most attractive advantage of the PA operator is its power to combat the adverse effects of ultra-evaluation values on the information aggregation results. The prominent characteristic of the MM operator is that it is flexible to capture the interrelationship among any numbers of arguments, making it more powerful than Bonferroni mean (BM), Heronian mean (HM), and Maclaurin symmetric mean (MSM). To absorb the virtues of both PA and MM, it is necessary to combine them to aggregate IVIF information and propose IVIF power Muirhead mean (IVIFPMM) operator and the IVIF weighted power Muirhead mean (IVIFWPMM) operator. We investigate their properties to show the strongness and flexibility. Furthermore, a novel approach to MAGDM problems with IVIF decision-making information is introduced. Finally, a numerical example is provided to show the performance of the proposed method.
Constructing True Model-Based Requirements in SysML
Authors: Salado Alejandro , Wach Paul
Published: March 2019

Some authors suggest that transitioning requirements engineering from the traditional statements in natural language with shall clauses to model-based requirements within a Model-Based Systems Engineering (MBSE) environment could improve communication, requirements traceability, and system decomposition, among others. Requirement elements in the Systems Modeling Language (SysML) fail to fulfill this objective, as they are really a textual requirement in natural language as a model element. Current efforts to directly leverage behavioral and structural models of the system lack an overarching theoretical framework with which to assess the adequacy of how those models are used to capture requirements. This paper presents an approach to construct true model-based requirements in SysML. The presented approach leverages some of SysML’s behavioral and structural models and diagrams, with specific construction rules derived from Wymore’s mathematical framework for MBSE and taxonomies of requirements and interfaces. The central proposition of the approach is that every requirement can be modeled as an input/output transformation. Examples are used to show how attributes traditionally thought of as non-functional requirements can be captured, with higher precision, as functional transformations.