bluuebunny/crossref_metadata_2025 huggingface dataset:
Polyaniline Nanofiber Wrapped Fabric for High Performance Flexible Pressure Sensors
Authors: Liu Kangning , Zhou Ziqiang , Yan Xingwu , Meng Xiang , Tang Hua , Qu Konggang , Gao Yuanyuan , Li Ying , Yu Junsheng , Li Lu
Published: July 2019

The rational design of high-performance flexible pressure sensors with both high sensitivity and wide linear range attracts great attention because of their potential applications in wearable electronics and human-machine interfaces. Here, polyaniline nanofiber wrapped nonwoven fabric was used as the active material to construct high performance, flexible, all fabric pressure sensors with a bottom interdigitated textile electrode. Due to the unique hierarchical structures, large surface roughness of the polyaniline coated fabric and high conductivity of the interdigitated textile electrodes, the obtained pressure sensor shows superior performance, including ultrahigh sensitivity of 46.48 kPa−1 in a wide linear range (<4.5 kPa), rapid response/relaxation time (7/16 ms) and low detection limit (0.46 Pa). Based on these merits, the practical applications in monitoring human physiological signals and detecting spatial distribution of subtle pressure are demonstrated, showing its potential for health monitoring as wearable electronics.
Fabrication and Properties of a Bio-Based Biodegradable Thermoplastic Polyurethane Elastomer
Authors: Wang Zhaoshan , Yan Jieqiong , Wang Tongyao , Zai Yingying , Qiu Liyan , Wang Qingguo
Published: July 2019

Using the melt polycondensation of five bio-based aliphatic monomers (succinic acid, sebacic acid, fumaric acid, 1,3-propanediol, and 1,4-butanediol), we first synthesized the more flexible and biodegradable polyester diols (BPD) with an average molecular weight of 3825. Then, the BPD was polymerized with excessive 4,4′-diphenylmethane diisocyanate (MDI). Finally, the molecular chain extender of 1,4-butanediol (BDO) was used to fabricate the biodegradable thermoplastic polyurethane elastomer (BTPU), comprising the soft segment of BPD and the hard segment polymerized by MDI and BDO. Atomic force microscope (AFM) images showed the two-phase structure of the BTPU. The tensile strength of the BTPU containing 60% BPD was about 30 MPa and elongation at break of the BTPU was over 800%. Notably, the BTPU had superior biodegradability in lipase solution and the biodegradation weight loss ratio of the BTPU containing 80% BPD reached 36.7% within 14 days in the lipase solution.
Opuntia Ficus-Indica L. Miller (Palma Forrageira) as an Alternative Source of Cellulose for Production of Pharmaceutical Dosage Forms and Biomaterials: Extraction and Characterization
Authors: de Assis Amaro César Lima , Alves Larissa Pereira , Malheiro João Paulo Tavares , Barros Alana Rafaela Albuquerque , Pinheiro-Santos Edvânia Emannuelle , de Azevedo Eduardo Pereira , Silva Alves Harley da , Oshiro-Junior João Augusto , Damasceno Bolívar Ponciano Goulart de Lima
Published: July 2019

Cellulose is among the top 5 excipients used in the pharmaceutical industry. It has been considered one of the main diluents used in conventional and modern dosage forms. Therefore, different raw materials of plant origin have been evaluated as potential alternative sources of cellulose. In this context, Opuntia ficus-indica L. Miller (palma forrageira), a plant of the cactus family that has physiological mechanisms that provide greater productivity with reduced water requirements, is an interesting and unexplored alternative for extracting cellulose. By using this source, we aim to decrease the extraction stages and increase the yields, which might result in a decreased cost for the industry and consequently for the consumer. The aim of this work was to investigate the use of Opuntia ficus-indica L. Miller as a new source for cellulose extraction, therefore providing an efficient, straight forward and low-cost method of cellulose II production. The extraction method is based on the oxidation of the lignins. The obtained cellulose was identified and characterized by spectroscopic methods (FTIR and NMR), X-ray diffraction, thermal analysis (TGA-DTG and DSC) and scanning electron microscopy. The results confirmed the identity of cellulose and its fibrous nature, which are promising characteristics for its use in the industry and a reasonable substrate for chemical modifications for the synthesis of cellulose II derivatives with different physicochemical properties that might be used in the production of drug delivery systems and biomaterials.
Sequential Recovery of Heavy and Noble Metals by Mussel-Inspired Polydopamine-Polyethyleneimine Conjugated Polyurethane Composite Bearing Dithiocarbamate Moieties
Authors: Xue Dingshuai , Li Ting , Chen Guoju , Liu Yanhong , Zhang Danping , Guo Qian , Guo Jujie , Yang Yueheng , Sun Jiefang , Su Benxun , Sun Lei , Shao Bing
Published: July 2019

Dithiocarbamate-grafted polyurethane (PU) composites were synthesized by anchoring dithiocarbamate (DTC) as a chelating agent to the polyethyleneimine-polydopamine (PE-DA)-functionalized graphene-based PU matrix (PE-DA@GB@PU), as a new adsorbent material for the recovery of Cu2+, Pb2+, and Cd2+ from industrial effluents. After leaching with acidic media to recover Cu2+, Pb2+, and Cd2+, dithiocarbamate-grafted PE-DA@GB@PU (DTC-g-PE-DA@GB@PU) was decomposed and PE-DA@GP was regenerated. The latter was used to recover Pd2+, Pt4+, and Au3+ from the copper leaching residue and anode slime. The present DTC-g-PE-DA@GB@PU and PE-DA@GB@PU composites show high adsorption performance, effective separation, and quick adsorption of the target ions. The morphologies of the composites were studied by scanning electron microscopy and their structures were investigated by Fourier transform infrared (FT-IR) spectroscopy and Raman spectroscopy. The effects of pH values, contact time, and initial metal ion concentration conditions were also studied. An adsorption mechanism was proposed and discussed in terms of the FT-IR results.
Crack Propagation and Fracture Process Zone (FPZ) of Wood in the Longitudinal Direction Determined Using Digital Image Correlation (DIC) Technique
Authors: Yu Ying , Zeng Weihang , Liu Wen , Zhang He , Wang Xiaohong
Published: July 2019

As a state-of-the-art method, the digital image correlation (DIC) technique is used to capture the fracture properties of wood along the longitudinal direction, such as the crack propagation, the strain field, and the fracture process zone (FPZ). Single-edge notched (SEN) specimens made of Douglas fir (Pseudotsuga menziesii) from Canada with different notch-to-depth ratios are tested by three-point-bending (3-p-b) experiment. The crack mouth opening displacements (CMOD) measured by the clip gauge and DIC technique agree well with each other, verifying the applicability of the DIC technique. Then, the quasi-brittle fracture process of wood is analyzed by combing the load-CMOD curve and the strain field in front of the preformed crack. Additionally, the equivalent elastic crack length is calculated using the linear superposition hypothesis. The comparison between the FPZ evolution and the equivalent elastic crack shows that specimens with higher notch-to-depth ratios have better cohesive effect and higher cracking resistance.
Complementarity of X-, C-, and L-band SAR Backscatter Observations to Retrieve Forest Stem Volume in Boreal Forest
Authors: Santoro Maurizio , Cartus Oliver , Fransson Johan E. S. , Wegmüller Urs
Published: July 2019

The simultaneous availability of observations from space by remote sensing platforms operating at multiple frequencies in the microwave domain suggests investigating their complementarity in thematic mapping and retrieval of biophysical parameters. In particular, there is an interest to understand whether the wealth of short wavelength Synthetic Aperture Radar (SAR) backscatter observations at X-, C-, and L-band from currently operating spaceborne missions can improve the retrieval of forest stem volume, i.e., above-ground biomass, in the boreal zone with respect to a single frequency band. To this scope, repeated observations from TerraSAR-X, Sentinel-1 and ALOS-2 PALSAR-2 from the test sites of Remningstorp and Krycklan, Sweden, have been analyzed and used to estimate stem volume with a retrieval framework based on the Water Cloud Model. Individual estimates of stem volume were then combined linearly to form single-frequency and multi-frequency estimates. The retrieval was assessed at large 0.5 ha forest inventory plots (Remningstorp) and small 0.03 ha forest inventory plots (Krycklan). The relationship between SAR backscatter and stem volume differed depending on forest structure and environmental conditions, in particular at X- and C-band. The highest retrieval accuracy was obtained at both test sites at L-band. The combination of stem volume estimates from data acquired at two or three frequencies achieved an accuracy that was superior to values obtained at a single frequency. When combining estimates from X-, C-, and L-band data, the relative RMSE for the 0.5 ha inventory plots at Remningstorp was 31.3%. For the 0.03 ha inventory plots at Krycklan, the relative RMSE was above 50%. In a retrieval scenario involving short wavelength SAR backscatter data, these results suggest combining multiple frequencies to ensure the highest possible retrieval accuracy achievable. Retrievals should be undertaken to target spatial scales well above the size of a pixel.
Spectral-Spatial Hyperspectral Image Classification via Robust Low-Rank Feature Extraction and Markov Random Field
Authors: Cao Xiangyong , Xu Zongben , Meng Deyu
Published: July 2019

In this paper, a new supervised classification algorithm which simultaneously considers spectral and spatial information of a hyperspectral image (HSI) is proposed. Since HSI always contains complex noise (such as mixture of Gaussian and sparse noise), the quality of the extracted feature inclines to be decreased. To tackle this issue, we utilize the low-rank property of local three-dimensional, patch and adopt complex noise strategy to model the noise embedded in each local patch. Specifically, we firstly use the mixture of Gaussian (MoG) based low-rank matrix factorization (LRMF) method to simultaneously extract the feature and remove noise from each local matrix unfolded from the local patch. Then, a classification map is obtained by applying some classifier to the extracted low-rank feature. Finally, the classification map is processed by Markov random field (MRF) in order to further utilize the smoothness property of the labels. To ease experimental comparison for different HSI classification methods, we built an open package to make the comparison fairly and efficiently. By using this package, the proposed classification method is verified to obtain better performance compared with other state-of-the-art methods.
Examining the Deep Belief Network for Subpixel Unmixing with Medium Spatial Resolution Multispectral Imagery in Urban Environments
Authors: Deng Yingbin , Chen Renrong , Wu Changshan
Published: July 2019

Mixed pixels in medium spatial resolution imagery create major challenges in acquiring accurate pixel-based land use and land cover information. Deep belief network (DBN), which can provide joint probabilities in land use and land cover classification, may serve as an alternative tool to address this mixed pixel issue. Since DBN performs well in pixel-based classification and object-based identification, examining its performance in subpixel unmixing with medium spatial resolution multispectral image in urban environments would be of value. In this study, (1) we examined DBN’s ability in subpixel unmixing with Landsat imagery, (2) explored the best-fit parameter setting for the DBN model and (3) evaluated its performance by comparing DBN with random forest (RF), support vector machine (SVM) and multiple endmember spectral mixture analysis (MESMA). The results illustrated that (1) DBN performs well in subpixel unmixing with a mean absolute error (MAE) of 0.06 and a root mean square error (RMSE) of 0.0077. (2) A larger sample size (e.g., greater than 3000) can provide stable and high accuracy while two-RBM-layer and 50 batch sizes are the best parameters for DBN in this study. Epoch size and learning rate should be decided by specific applications since there is not a consistent pattern in our experiments. Finally, (3) DBN can provide comparable results compared to RF, SVM and MESMA. We concluded that DBN can be viewed as an alternative method for subpixel unmixing with Landsat imagery and this study provides references for other scholars to use DBN in subpixel unmixing in urban environments.
Automated Extraction of Built-Up Areas by Fusing VIIRS Nighttime Lights and Landsat-8 Data
Authors: Liu Chang , Yang Kang , Bennett Mia , Guo Ziyan , Cheng Liang , Li Manchun
Published: July 2019

As the world urbanizes and builds more infrastructure, the extraction of built-up areas using remote sensing is crucial for monitoring land cover changes and understanding urban environments. Previous studies have proposed a variety of methods for mapping regional and global built-up areas. However, most of these methods rely on manual selection of training samples and classification thresholds, leading to low extraction efficiency. Furthermore, thematic accuracy is limited by interference from other land cover types like bare land, which hinder accurate and timely extraction and monitoring of dynamic changes in built-up areas. This study proposes a new method to map built-up areas by combining VIIRS (Visible Infrared Imaging Radiometer Suite) nighttime lights (NTL) data and Landsat-8 multispectral imagery. First, an adaptive NTL threshold was established, vegetation and water masks were superimposed, and built-up training samples were automatically acquired. Second, the training samples were employed to perform supervised classification of Landsat-8 data before deriving the preliminary built-up areas. Third, VIIRS NTL data were used to obtain the built-up target areas, which were superimposed onto the built-up preliminary classification results to obtain the built-up area fine classification results. Four major metropolitan areas in Eurasia formed the study areas, and the high spatial resolution (20 m) built-up area product High Resolution Layer Imperviousness Degree (HRL IMD) 2015 served as the reference data. The results indicate that our method can accurately and automatically acquire built-up training samples and adaptive thresholds, allowing for accurate estimates of the spatial distribution of built-up areas. With an overall accuracy exceeding 94.7%, our method exceeded accuracy levels of the FROM-GLC and GUL built-up area products and the PII built-up index. The accuracy and efficiency of our proposed method have significant potential for global built-up area mapping and dynamic change monitoring.
Interferometric DEM-Assisted High Precision Imaging Method for ArcSAR
Authors: Wang Yanping , Song Yang , Lin Yun , Li Yang , Zhang Yuan , Hong Wen
Published: July 2019

Ground-based arc-scanning synthetic aperture radar (ArcSAR) is the novel ground-based synthetic aperture radar (GBSAR). It scans 360-degree surrounding scenes by the antenna attached to rotating boom. Therefore, compared with linear scanning GBSAR, ArcSAR has larger field of view. Although the feasibility of ArcSAR has been verified in recent years, its imaging algorithm still presents difficulties. The imaging accuracy of ArcSAR is affected by terrain fluctuation. For rotating scanning ArcSAR, even if targets in scenes have the same range and Doppler with antenna, if the heights of targets are different, their range migration will be different. Traditional ArcSAR imaging algorithms achieve imaging on reference plane. The height difference between reference plane and target in scenes will cause the decrease of imaging quality or even image defocusing because the range migration cannot be compensated correctly. For obtaining high-precision ArcSAR image, we propose interferometric DEM (digital elevation model)-assisted high precision imaging method for ArcSAR. The interferometric ArcSAR is utilized to acquire DEM. With the assist of DEM, target in scenes can be imaged on its actual height. In this paper, we analyze the error caused by ArcSAR imaging on reference plane. The method of extracting DEM on ground range for assisted ArcSAR imaging is also given. Besides, DEM accuracy and deformation monitoring accuracy of proposed method are analyzed. The effectiveness of the proposed method was verified by experiments.
Optical and Electrical Method Characterizing the Dynamic Behavior of the Fused Silica Cylindrical Resonator
Authors: Qiu Zhinan , Qu Tianliang , Pan Yao , Jia Yonglei , Fan Zhenfang , Yang Kaiyong , Yuan Jie , Luo Hui
Published: July 2019

Fused silica cylindrical resonant gyroscope (CRG) is a novel high-precision solid-wave gyroscope, whose performance is primarily determined by the cylindrical resonator’s frequency split and quality factor (Q factor). The laser Doppler vibrometer (LDV) is extensively used to measure the dynamic behavior of fused silica cylindrical resonators. An electrical method was proposed to characterize the dynamic behavior of the cylindrical resonator to enhance the measurement efficiency and decrease the equipment cost. With the data acquisition system and the designed signal analysis program based on LabVIEW software, the dynamic behavior of the fused silica cylindrical resonator can be analyzed automatically and quickly. We compared all the electrical measurement results with the optical detection by LDV, demonstrating that the fast Fourier transform (FFT) result of the resonant frequency measured by the electrical method was 0.12 Hz higher than that with the optical method. Thus, the frequency split measured by the electrical and optical methods was the same in 0.18 Hz, and the measurement of the Q factor was basically the same in 730,000. We conducted all measurements under the same operation condition, and the optical method was used as a reference, demonstrating that the electrical method could characterize the dynamic behavior of the fused silica cylindrical resonator and enhance the measurement efficiency.
Integration of a Balanced Scorecard, DEMATEL, and ANP for Measuring the Performance of a Sustainable Healthcare Supply Chain
Authors: Leksono Eko Budi , Suparno Suparno , Vanany Iwan
Published: July 2019

The main purpose of this study is to develop a sustainable healthcare supply chain performance measurement (SHSCPM) model, which simultaneously considers intangible characteristics and sustainability aspects to ensure customer and/or stakeholder satisfaction. This model combines a balanced scorecard (BSC) with a decision-making trial and evaluation laboratory (DEMATEL) and analytical network process (ANP). After the arrangement and classification of perspectives and indicators from a literature review, the strategy map of the BSC is designed with DEMATEL. Furthermore, this study used a survey with in-depth interviews of seven expert respondents to make a pair-wise comparison between perspectives and indicators in order to determine the weights of indicators, perspectives, and sustainability aspects on ANP. The study finds the following. First, the innovation and learning perspective that reflects intangible assets has the most influence on the others but is not important, while the customer perspective has the most importance for SHSC performance. Second, the economic aspect has the greatest weight, followed by social and environmental aspects. Finally, indicators of the financial and customer perspectives as drivers of SHSC performance consist of profit, quality of service, revenue, customer satisfaction, and stakeholder satisfaction. Further, indicators of the economic aspect of sustainability have the most effect on SHSC performance, followed by social and environmental aspects. Furthermore, human resources, as an intangible asset and key factor in social aspects, are main factor in improving SHSC performance.
Simulation of Spatiotemporal Land Use Changes for Integrated Model of Socioeconomic and Ecological Processes in China
Authors: Jiang Honglei , Xu Xia , Guan Mengxi , Wang Lingfei , Huang Yongmei , Liu Yinghui
Published: July 2019

Land use/land cover changes (LULCC) have been affected by ecological processes as well as socioeconomic and human activities, resulting in several environmental problems. The study of the human–environment system combined with land use/land cover dynamics has received considerable attention in recent decades. We aimed to provide an integrated model that couples land use, socioeconomic influences, and ecosystem processes to explore the future dynamics of land use under two scenarios in China. Under Scenario A, the yield of grain continues to increase, and under Scenario B, the yield of grain remains constant. This study created a LULCC model by integrating a simple global socioeconomic model, a Terrestrial ecosystem simulator (TESim), and a land use allocation model. The results were analyzed by comparing spatiotemporal differences under predicted land use conditions in the two alternative scenarios. The simulation results showed patterns that varied between the two scenarios. In Scenario A, grassland will expand in the future and a large reduction in cropland will be observed. In Scenario B, the augmented expansion of cropland and a drastic shrinkage of forest area will be the main land use conversion features. Scenario A is more promising because more land is preserved for ecological restoration and urbanization, which is in line with China’s Grain for Green Program. Economic development should be based on ecological protection. The results are expected to add insight to sustainable land use development and regional natural resource management in China.
A Case Study of Environmental Policies and Guidelines for the Use of Coal Ash as Mine Reclamation Filler: Relevance for Needed South Korean Policy Updates
Authors: Cho Hanna , Ji Sang-woo , Shin Hee-young , Jo Hwanju
Published: July 2019

The South Korean government is pursuing a national project to use the complex carbonates found in coal ash to capture CO2 and promote coal ash recycling. One possible approach is the use of coal ash as fill material in mine reclamation, but environmental concerns have so far blocked the implementation of this procedure, and no relevant regulations or guidelines exist. In this study, we review international approaches to the environmental management of coal ash recycling and consider how the lessons learned can be applied to South Korea. Each studied country was proactively using coal ash for beneficial uses under locally suitable conditions. The United States, European Union, United Kingdom, Australia, and Japan are all putting coal ash to beneficial use following thorough analyses of the environmental impact based on several considerations, including bulk concentration, coal ash leachate concentration, field inspections, and water quality monitoring. Our findings can contribute to the development of proper regulations and policies to encourage the use of recycled coal ash in South Korea as an approach to managing carbon emissions and climate changes. There are currently no relevant regulations in South Korea, so we consider the adoption of the strictest standards at each stage of the other cases at the time of introduction. Based on our findings, detailed and appropriate management guidelines can be developed in the future. Establishing management plans for complex carbonates, verifying their environmental stability, and using them as fill material will provide clear benefits for South Korea in the future.
Effect of Press Construction on Yield and Quality of Apple Juice
Authors: Wilczyński Kamil , Kobus Zbigniew , Dziki Dariusz
Published: July 2019

The paper presents the possibility of applying different press constructions for juice extraction in small farms. The research was carried out with three different varieties of apples, namely, Rubin, Mutsu, and Jonaprince. Two types of presses were tested: a basket press and a screw press. Generally, application of the screw press makes it possible to obtain a higher yield of extraction compared to the basket press. In our study, the differences in the pressing yield among press machines also depended on the apple variety used. The juices obtained on the screw press were found to be of a higher quality characterized by a higher content of soluble solids, higher viscosity, higher total content of polyphenols, higher antioxidant activity, and lower acidity. Thus, the selection of an appropriate press is the key to producing high-quality apple juice with health-promoting properties for manufacturers of apple juice at the local marketplace.
Science Mapping the Knowledge Base on Sustainable Tourism Development, 1990–2018
Authors: Yoopetch Chanin , Nimsai Suthep
Published: July 2019

Robust literature on sustainable tourism development has emerged globally both in economically developed and emerging economies. Over the past several decades, policymakers and business practitioners increasingly acknowledge that the long-term development and sustainability of tourism destinations require clear guidelines and direction. The impetus for sustainable tourism development has become ever more urgent as a result of dual trends of climate change and massification of the global tourism industry. The current research review used science mapping techniques to examine 1596 Scopus-indexed documents published on sustainable tourism development. The objectives of the review were to document the size, growth, and global distribution of this literature, identify its key journals, authors, and documents, highlight emerging topics, and illuminate the underlying intellectual structure of this literature. The review also provides guidelines for scholars to develop research that can aid in future sustainable tourism development.
The Complexity of Simple Goals: Case Study of a User-Centred Thermoregulation System for Smart Living and Optimal Energy Use
Authors: Pillan Margherita , Costa Fiammetta , Aureggi Marco
Published: July 2019

There are currently several systems for home automation and energy management available on the market. These systems are intended to reduce the use of energy, while ensuring optimal and customizable comfort conditions. The advances in technology (Internet of Things, sensors, cloud computing, data processing and thermal modelling) and in the design of interfaces should facilitate the adoption of convenient behaviours by final users, thereby producing more sustainable use of energy at home. Conversely, the effectiveness and efficiency of smart home systems for thermo-regulation is a complex activity, requiring the collaboration of multiple stakeholders and experts. In this paper, the authors report a case study about the design of a system for thermal regulation at home developed in a multidisciplinary research team for research and industrial purposes. The paper reports results including: a discussion on a number of issues involved in the design of smart home solutions for sustainability and on the importance of developing an integrated approach to their design; the needs analysis of users and of their functional requirements based on investigation with residents and profiling; final remarks about the role of User Experience Design methods and tools in the development of smart home solutions, understood as socio-technical systems.
Environmental and Economic Benefits from the Phase-out of Residential Oil Heating: A Study from the Aosta Valley Region (Italy)
Authors: Casasso Alessandro , Capodaglio Pietro , Simonetto Fulvio , Sethi Rajandrea
Published: July 2019

Although its use is declining, oil heating is still used in areas not covered by the methane grid. Oil heating is becoming more and more expensive, requires frequent tank refill operations, and has high emissions of greenhouse gas (GHG) and air pollutants such as SOx. In addition, spills from oil underground storage tanks (USTs) represent a serious environmental threat to soil and groundwater quality. In this paper, we present a comprehensive analysis on technical alternatives to oil heating with reference to the Aosta Valley (NW Italy), where this fuel is still often used and numerous UST spills have been reported in the last 20 years. We assess operational issues, GHG and pollutant emissions, and unit costs of the heat produced for several techniques: LPG boilers, wood boilers (logs, chips, pellets) and heat pumps (air-source, geothermal closed-loop and open-loop systems). We examine the investment to implement such solutions in two typical cases, a detached house and a block of flats, deriving payback times of about 3–8 years. Wood log boilers turn out to be the most economically convenient solutions; however, heat pumps provide several benefits from the operational and environmental points of view. In addition, including solar thermal panels for domestic hot water or a photovoltaic plant would have payback times of about 6–9 years. The results highlight the economic feasibility and the multiple benefits of a rapid phase-out of oil heating in Italy.
Multi-Objective Neighborhood Search Algorithm Based on Decomposition for Multi-Objective Minimum Weighted Vertex Cover Problem
Authors: Hu Shuli , Wu Xiaoli , Liu Huan , Wang Yiyuan , Li Ruizhi , Yin Minghao
Published: July 2019

The multi-objective minimum weighted vertex cover problem aims to minimize the sum of different single type weights simultaneously. In this paper, we focus on the bi-objective minimum weighted vertex cover and propose a multi-objective algorithm integrating iterated neighborhood search with decomposition technique to solve this problem. Initially, we adopt the decomposition method to divide the multi-objective problem into several scalar optimization sub-problems. Meanwhile, to find more possible optimal solutions, we design a mixed score function according to the problem feature, which is applied in initializing procedure and neighborhood search. During the neighborhood search, three operators ( A d d , D e l e t e , S w a p ) explore the search space effectively. We performed numerical experiments on many instances, and the results show the effectiveness of our new algorithm (combining decomposition and neighborhood search with mixed score) on several experimental metrics. We compared our experimental results with the classical multi-objective algorithm non-dominated sorting genetic algorithm II. It was obviously shown that our algorithm can provide much better results than the comparative algorithm considering the different metrics.
Contested Development Paths and Rural communities: Sustainable Energy or Sustainable Tourism in Iceland?
Authors: Sæþórsdóttir Anna Dóra , Hall C. Michael
Published: July 2019

The Icelandic economy has transitioned from being dependent on fishing and agriculture to having tourism and refined aluminum as its main exports. Nevertheless, the new main industries still rely on the country’s natural resources, as the power intensive industry uses energy from rivers and geothermal areas whereas tourism uses the natural landscape, where geysers, waterfalls and thermal pools are part of the attraction to visitors. Although both industries claim to contribute to sustainability they utilize the same resources, and land-use conflicts can be expected, illustrating the contestation that can occur between different visions and understandings of sustainability. This paper focuses on the attitudes of Icelandic tourism operators towards power production and proposed power plants using data from questionnaires and face-to-face interviews. Results show that the majority of Icelandic tourism operators assume further power utilization would be in conflict with nature-based tourism, and they are generally negative towards all types of renewable energy development and power plant infrastructure. Respondents are most negative towards transmission lines, reservoirs and hydro power plants in the country’s interior Highlands. About 40% of the respondents perceive that existing power plants have negatively affected tourism, while a similar proportion think they had no impact. According to the respondents, the two industries could co-exist with improved spatial planning, management and inter-sectoral cooperation.
Corporate Social Responsibility and Financial Performance: The Moderating Role of Ownership Concentration in Turkey
Authors: Akben-Selcuk Elif
Published: July 2019

The objective of this study is to investigate the impact of corporate social responsibility (CSR) engagement on firm financial performance in a developing country, Turkey, and to analyze the moderating role of ownership concentration in the CSR–financial performance relationship. The sample consists of non-financial public firms listed on the Borsa Istanbul (BIST)-100 index and covers the period between 2014 and 2018. Empirical results using an instrumental variable approach show that corporate social responsibility has a positive relationship with financial performance. Furthermore, findings indicate that this relationship is negatively moderated by ownership concentration even when endogeneity is controlled for.
A DIY Approach for the Design of Mission-Planning Architecture Using Autonomous Task–Object Mapping and the Deployment Model in Mission-Critical IoT Systems
Authors: Ahmad Shabir , Mehmood Faisal , Kim Do-Hyeun
Published: July 2019

Recently, the World Economic Forum (WEF) highlighted mission-critical Internet of Things (MC-IoT) applications as one of the six enablers of sustainable development of smart cities. MC-IoT refers to systems which exacerbate properties like availability, reliability, safety, and security in an application environment of heterogeneously connected physical things and virtual things whose failure could lead to severe consequences such as life loss. The sole characteristic of the mission-critical system is its compliance with real-time behavior. As a result of the critical nature of these systems, it is essential to design the system with sufficient clarity so that none of the requirements is misinterpreted. For this, the involvement of non-technical stakeholders and policymakers is crucial. Previous studies on mission-critical structures mainly focus on the communication overheads, and overlook the design and planning of them. Therefore, in this paper, we present an architecture which enables mission planning on a do-it-yourself plane. We present a task–object mapping and deployment model where different tasks are mapped onto virtual objects and deployed on physical hardware in a task–object pair. The system uses semantic knowledge for autonomous task mapping and suggestions to further aid the orchestration of the process. The tasks are autonomously mapped onto the devices based on the correlation index; this is computed based on the attribute similarities, thus making the system flexible. The performance of the proposed architecture is evaluated with different key performance indicators under different load conditions and the response time is found to be under a few seconds even at peak load conditions.
Gauge Theories: From Kaluza–Klein to noncommutative gravity theories
Authors: Manolakos George , Manousselis Pantelis , Zoupanos George
Published: July 2019

First, the Coset Space Dimensional Reduction scheme and the best particle physics model so far resulting from it are reviewed. Then, a higher-dimensional theory in which the extra dimensions are fuzzy coset spaces is described and a dimensional reduction to four-dimensional theory is performed. Afterwards, another scheme including fuzzy extra dimensions is presented, but this time the starting theory is four-dimensional while the fuzzy extra dimensions are generated dynamically. The resulting theory and its particle content is discussed. Besides the particle physics models discussed above, gravity theories as gauge theories are reviewed and then, the whole methodology is modified in the case that the background spacetimes are noncommutative. For this reason, specific covariant fuzzy spaces are introduced and, eventually, the program is written for both the 3-d and 4-d cases.
3D Flow Entropy Contour Fitting Segmentation Algorithm Based on Multi-Scale Transform Contour Constraint
Authors: Wu Hongtao , Liu Liyuan , Lan Jinhui
Published: July 2019

Image segmentation is a crucial topic in image analysis and understanding, and the foundation of target detection and recognition. Image segmentation, essentially, can be considered as classifying the image according to the consistency of the region and the inconsistency between regions, it is widely used in medical and criminal investigation, cultural relic identification, monitoring and so forth. There are two outstanding common problems in the existing segmentation algorithm, one is the lack of accuracy, and the other is that it is not widely applicable. The main contribution of this paper is to present a novel segmentation method based on the information entropy theory and multi-scale transform contour constraint. Firstly, the target contour is initially obtained by means of a multi-scale sample top-hat and bottom-hat transform and an improved watershed method. Subsequently, in terms of this initial contour, the interesting areas can be finely segmented out with an innovative 3D flow entropy method. Finally, the sufficient synthetic and real experiments proved that the proposed algorithm can greatly improve the segmentation effect. In addition, it is widely applicable.
Accelerating Density Peak Clustering Algorithm
Authors: Lin Jun-Lin
Published: July 2019

The Density Peak Clustering (DPC) algorithm is a new density-based clustering method. It spends most of its execution time on calculating the local density and the separation distance for each data point in a dataset. The purpose of this study is to accelerate its computation. On average, the DPC algorithm scans half of the dataset to calculate the separation distance of each data point. We propose an approach to calculate the separation distance of a data point by scanning only the neighbors of the data point. Additionally, the purpose of the separation distance is to assist in choosing the density peaks, which are the data points with both high local density and high separation distance. We propose an approach to identify non-peak data points at an early stage to avoid calculating their separation distances. Our experimental results show that most of the data points in a dataset can benefit from the proposed approaches to accelerate the DPC algorithm.
Segmentation of Articular Cartilage and Early Osteoarthritis based on the Fuzzy Soft Thresholding Approach Driven by Modified Evolutionary ABC Optimization and Local Statistical Aggregation
Authors: Kubicek Jan , Penhaker Marek , Augustynek Martin , Cerny Martin , Oczka David
Published: July 2019

Articular cartilage assessment, with the aim of the cartilage loss identification, is a crucial task for the clinical practice of orthopedics. Conventional software (SW) instruments allow for just a visualization of the knee structure, without post processing, offering objective cartilage modeling. In this paper, we propose the multiregional segmentation method, having ambitions to bring a mathematical model reflecting the physiological cartilage morphological structure and spots, corresponding with the early cartilage loss, which is poorly recognizable by the naked eye from magnetic resonance imaging (MRI). The proposed segmentation model is composed from two pixel’s classification parts. Firstly, the image histogram is decomposed by using a sequence of the triangular fuzzy membership functions, when their localization is driven by the modified artificial bee colony (ABC) optimization algorithm, utilizing a random sequence of considered solutions based on the real cartilage features. In the second part of the segmentation model, the original pixel’s membership in a respective segmentation class may be modified by using the local statistical aggregation, taking into account the spatial relationships regarding adjacent pixels. By this way, the image noise and artefacts, which are commonly presented in the MR images, may be identified and eliminated. This fact makes the model robust and sensitive with regards to distorting signals. We analyzed the proposed model on the 2D spatial MR image records. We show different MR clinical cases for the articular cartilage segmentation, with identification of the cartilage loss. In the final part of the analysis, we compared our model performance against the selected conventional methods in application on the MR image records being corrupted by additive image noise.
Differential Effect of the Deletion of African Swine Fever Virus Virulence-Associated Genes in the Induction of Attenuation of the Highly Virulent Georgia Strain
Authors: Ramirez-Medina Elizabeth , Vuono Elizabeth , O’Donnell Vivian , Holinka Lauren G. , Silva Ediane , Rai Ayushi , Pruitt Sarah , Carrillo Consuelo , Gladue Douglas P. , Borca Manuel V.
Published: July 2019

African swine fever virus (ASFV) is the etiological agent of an often lethal disease of domestic pigs, African swine fever (ASF). The ASFV Georgia 2007 isolate (ASFV-G) is responsible for the current epidemic situation in Europe and Asia. Genetically modified ASFVs containing deletions of virulence-associated genes have produced attenuated phenotypes and induced protective immunity in swine. Here we describe the differential behavior of two viral genes, NL (DP71L) and UK (DP96R), both originally described as being involved in virus virulence. Deletion of either of these genes efficiently attenuated ASFV strain E70. We demonstrated that deletion of the UK gene from the ASFV-G genome did not decrease virulence when compared to the parental virus. Conversely, deletion of the NL gene produced a heterogeneous response, with early death in one of the animals and transient fever in the other animals. With this knowledge, we attempted to increase the safety profile of the previously reported experimental vaccine ASFV-GΔ9GL/ΔUK by deleting the NL gene. A triple gene-deletion virus was produced, ASFV-GΔ9GL/ΔNL/ΔUK. Although ASFV-GΔ9GL/ΔNL/ΔUK replicated in primary cell cultures of swine macrophages, it demonstrated a severe replication deficiency in pigs, failing to induce protection against challenge with parental ASFV-G.
Detection and Characterization of Invertebrate Iridoviruses Found in Reptiles and Prey Insects in Europe over the Past Two Decades
Authors: Papp Tibor , Marschang Rachel E.
Published: July 2019

Invertebrate iridoviruses (IIVs), while mostly described in a wide range of invertebrate hosts, have also been repeatedly detected in diagnostic samples from poikilothermic vertebrates including reptiles and amphibians. Since iridoviruses from invertebrate and vertebrate hosts differ strongly from one another based not only on host range but also on molecular characteristics, a series of molecular studies and bioassays were performed to characterize and compare IIVs from various hosts and evaluate their ability to infect a vertebrate host. Eight IIV isolates from reptilian and orthopteran hosts collected over a period of six years were partially sequenced. Comparison of eight genome portions (total over 14 kbp) showed that these were all very similar to one another and to an earlier described cricket IIV isolate, thus they were given the collective name lizard–cricket IV (Liz–CrIV). One isolate from a chameleon was also subjected to Illumina sequencing and almost the entire genomic sequence was obtained. Comparison of this longer genome sequence showed several differences to the most closely related IIV, Invertebrate iridovirus 6 (IIV6), the type species of the genus Iridovirus, including several deletions and possible recombination sites, as well as insertions of genes of non-iridoviral origin. Three isolates from vertebrate and invertebrate hosts were also used for comparative studies on pathogenicity in crickets (Gryllus bimaculatus) at 20 and 30 °C. Finally, the chameleon isolate used for the genome sequencing studies was also used in a transmission study with bearded dragons. The transmission studies showed large variability in virus replication and pathogenicity of the three tested viruses in crickets at the two temperatures. In the infection study with bearded dragons, lizards inoculated with a Liz–CrIV did not become ill, but the virus was detected in numerous tissues by qPCR and was also isolated in cell culture from several tissues. Highest viral loads were measured in the gastro-intestinal organs and in the skin. These studies demonstrate that Liz–CrIV circulates in the pet trade in Europe. This virus is capable of infecting both invertebrates and poikilothermic vertebrates, although its involvement in disease in the latter has not been proven.
Cytokine Storm Combined with Humoral Immune Response Defect in Fatal Hemorrhagic Fever with Renal Syndrome Case, Tatarstan, Russia
Authors: Garanina Ekaterina , Martynova Ekaterina , Davidyuk Yuriy , Kabwe Emmanuel , Ivanov Konstantin , Titova Angelina , Markelova Maria , Zhuravleva Margarita , Cherepnev Georgiy , Shakirova Venera G. , Khaertynova Ilseyar , Tarlinton Rachael , Rizvanov Albert , Khaiboullina Svetlana , Morzunov Sergey
Published: July 2019

Hemorrhagic fever with renal syndrome (HFRS) is endemic in Tatarstan, where thousands of cases are registered annually. Puumala orthohantavirus is commonly detected in human case samples as well as in captured bank voles, the rodent hosts. The pathogenesis of HFRS is still not well described, although the cytokine storm hypothesis is largely accepted. In this study, we present a comprehensive analysis of a fatal HFRS case compared with twenty four non-fatal cases where activation of the humoral and cellular immune responses, pro-inflammatory cytokines and disturbed blood coagulation were detected using immunological, histological, genetic and clinical approaches. Multiple organ failure combined with disseminated intravascular coagulation syndrome and acute renal failure was the cause of death. Decreased Interleukin (IL)-7 and increased IL-18, chemokine (C-C motif) ligand (CCL)-5, stem cell growth factor (SCGF)-b and tumor necrosis factor-beta (TNF-β) serum levels were found, supporting the cytokine storm hypothesis of hantavirus pathogenesis.
Variation of Diatoms and Silicon in a Tributary of the Three Gorges Reservoir: Evidence of Interaction
Authors: Xiao Wei , Huang Yubo , Mi Wujuan , Wu Hongyan , Bi Yonghong
Published: July 2019

To gain insight into the variation of diatoms and silicon and their interaction in a tributary of the Three Gorges Reservoir (TGR), the Xiangxi River was chosen as a representative tributary, and dissolved silicon (DSi) and biogenic silicon (BSi) were investigated monthly from February 2015 to December 2016, accompanied by diatom species composition and cell density analyses. The results showed that the diatom population and its relationship with silicon concentration were significantly different between the lacustrine zone and riverine zone (P < 0.05). The cell density in the lacustrine zone (6.20 × 105 ~ 9.97 × 107 cells/L) was significantly higher than that in the riverine zone (7.90 × 104 ~ 1.81 × 107 cells/L) (P < 0.01). Water velocity was a key factor in determining the diatom species composition. Centric diatoms were the dominant species in the lacustrine zone, and pennate diatoms were the primary species in the riverine zone, which indicated that centric diatoms outcompete pennate diatoms under the influence of the TGR’s operation. BSi showed a significant linear relationship with the cell density. DSi had a significant negative relationship with the cell density in the lacustrine zone, while no significant relationship was found in the riverine zone. This meant that the main contributor to BSi was diatoms, but DSi was primarily affected by water discharge, not diatom uptake. It could be deduced that the spatiotemporal heterogeneity of diatom communities was influenced by the TGR’s operation. Silicon cycling in the tributary was significantly affected by diatoms, and the current concentration of DSi was sufficient for diatom growth and showed no significant effects on the diatom community.