Description: In this study, an inexact stochastic fuzzy programming (ISFP) model is proposed for land-use allocation (LUA) and environmental/ecological planning at a watershed level, where uncertainties associated with land-use parameters, benefit functions, and environmental/ecological requirements are described as discrete intervals, probabilities and fuzzy sets. In this model, an interval stochastic fuzzy programming model is used to support quantitative optimization under uncertainty. Complexities in land-use planning systems can be systematically reflected, thus applicability of the modeling process can be highly enhanced. The proposed method is applied to planning land use/ecological balance in Poyang Lake watershed, China. The objective of the ISFP is maximizing net benefit from the LUA system and the constraints including economic constraints, social constraints, land suitability constraints, environmental constraints, ecological constraints and technical constraints. Modeling results indicate that the desired system benefit will be between [15.17, 18.29] × 1012 yuan under the minimum violating probabilities; the optimized areas of commercial land, industrial land, agricultural land, transportation land, residential land, water land, green land, landfill land and unused land will be optimized cultivated land, forest land, grass land, water land, urban land, unused land and landfill will be [228234, 237844] ha, [47228, 58451] ha, [20982, 23718] ha, [33897, 35280] ha, [15215, 15907] ha, [528, 879] ha and [1023, 1260] ha. These data can be used for generating decision alternatives under different scenarios and thus help decision makers identify desired policies under various system-reliability constraints of ecological requirement and environmental capacity. Tradeoffs between system benefits and constraint-violation risks can be tackled. They are helpful for supporting (a) decision of land-use allocation and government investment; (b) formulation of local policies regarding ecological protection, environment protection and economic development; (c) analysis of interactions among economic benefits, system reliability and ecological requirements.

Description: The effectiveness of subsidies in improving the performance of renewable energy firms has aroused significant research attention in recent years. As subsidy modes may affect corporate financial performance,we have chosen companies specializing in wind and solar energy in the Shanghai and Shenzhen stock markets as samples.The relationships between the subsidy modes and financial performance of these two types of companies are investigated with a panel data model. Results of the total sample indicate that both indirect and non-innovative subsidy have significant effects on the financial performance of renewable energy companies. The regressive coefficient of the former,however, is a negative value, which illustrates that taxation, bonus, and other market-based mechanisms impair corporate profitability. Moreover, the influence of innovative subsidy is weak, which means that the subsidy used for research and development, technical demonstration, and other innovations of renewable energy enterprises have failed to effectively enhance corporate financial performance. In terms of sub-industries, the direct subsidy for wind energy companies has achieved a significant effect. Incomparison, the indirect subsidy and innovative subsidy acquired by solar energy companies have notably reduced corporate profitability. Thissuggests an urgent reform of subsidy policy for this industry is needed. The government should consider differences in the effects subsidies have for wind and solar energy companies when improving subsidy policy. In addition, market-based subsidy mechanisms should be perfected, and the structure of innovative subsidies should be ameliorated.

Description: In a complex system, condition monitoring (CM) can collect the system working status. The condition is mainly sensed by the pre-deployed sensors in/on the system. Most existing works study how to utilize the condition information to predict the upcoming anomalies, faults, or failures. There is also some research which focuses on the faults or anomalies of the sensing element (i.e., sensor) to enhance the system reliability. However, existing approaches ignore the correlation between sensor selecting strategy and data anomaly detection, which can also improve the system reliability. To address this issue, we study a new scheme which includes sensor selection strategy and data anomaly detection by utilizing information theory and Gaussian Process Regression (GPR). The sensors that are more appropriate for the system CM are first selected. Then, mutual information is utilized to weight the correlation among different sensors. The anomaly detection is carried out by using the correlation of sensor data. The sensor data sets that are utilized to carry out the evaluation are provided by National Aeronautics and Space Administration (NASA) Ames Research Center and have been used as Prognostics and Health Management (PHM) challenge data in 2008. By comparing the two different sensor selection strategies, the effectiveness of selection method on data anomaly detection is proved.

Description: The rapid development and increasing availability of high-resolution satellite (HRS) images provides increased opportunities to monitor large scale land cover. However, inefficiency and excessive independence on expert knowledge limits the usage of HRS images on a large scale. As a knowledge organization and representation method, ontology can assist in improving the efficiency of automatic or semi-automatic land cover information extraction, especially for HRS images. This paper presents an ontology-based framework that was used to model the land cover extraction knowledge and interpret HRS remote sensing images at the regional level. The land cover ontology structure is explicitly defined, accounting for the spectral, textural, and shape features, and allowing for the automatic interpretation of the extracted results. With the help of regional prototypes for land cover class stored in Web Ontology Language (OWL) file, automated land cover extraction of the study area is then attempted. Experiments are conducted using ZY-3 (Ziyuan-3) imagery, which were acquired for the Jiangxia District, Wuhan, China, in the summers of 2012 and 2013.The experimental method provided good land cover extraction results as the overall accuracy reached 65.07%. Especially for bare surfaces, highways, ponds, and lakes, whose producer and user accuracies were both higher than 75%. The results highlight the capability of the ontology-based method to automatically extract land cover using ZY-3 HRS images.

Description: Sensors, Vol. 17, Pages 2260: CuFusion: Accurate Real-Time Camera Tracking and Volumetric Scene Reconstruction with a Cuboid Sensors doi: 10.3390/s17102260 Authors: Chen Zhang Yu Hu Given a stream of depth images with a known cuboid reference object present in the scene, we propose a novel approach for accurate camera tracking and volumetric surface reconstruction in real-time. Our contribution in this paper is threefold: (a) utilizing a priori knowledge of the precisely manufactured cuboid reference object, we keep drift-free camera tracking without explicit global optimization; (b) we improve the fineness of the volumetric surface representation by proposing a prediction-corrected data fusion strategy rather than a simple moving average, which enables accurate reconstruction of high-frequency details such as the sharp edges of objects and geometries of high curvature; (c) we introduce a benchmark dataset CU3D that contains both synthetic and real-world scanning sequences with ground-truth camera trajectories and surface models for the quantitative evaluation of 3D reconstruction algorithms. We test our algorithm on our dataset and demonstrate its accuracy compared with other state-of-the-art algorithms. We release both our dataset and code as open-source (https://github.com/zhangxaochen/CuFusion) for other researchers to reproduce and verify our results.

Description: Location-based service information, provided by social networks, provides new data sources and perspectives to research tourism activities, especially in highly populated mega-cities. Based on three years (2012–2014) of approximately 340,000 check-in records collected from Sina micro-blog at 86 tourist attractions in Shenzhen, a first-tier city in southern China, we conducted a comprehensive study of the attraction features involving different aspects, such as tourist source, duration of stay, check-in activity index, and attraction correlation degree. The results showed that (1) theme parks established in the early 1990s were the most popular tourist attractions in Shenzhen, but a negative trend was detected in the check-in population; (2) compared with check-in times from surrounding activities and the kernel density of tourists, most destinations in Shenzhen showed a lack of attraction, failing to make the most of their geographic accessibility; and (3) the homogeneity and inconvenient traffic conditions of major tourist destinations leading to the construction of a tourism tour chain has become a challenge. The results of this study demonstrate the potential of big-data mining and provide valuable insights into tourism market design and management in mega-cities.

Description: Detection of trace levels of persistent pollutants in the environment is difficult but significant. Organic pollutant homologues, due to their similar physical and chemical properties, are even more difficult to distinguish, especially in trace amounts. We report here a simple method to detect polychlorinated biphenyls (PCBs) in soil and distilled spirit samples by the surface-enhanced Raman scattering technique using Ag nanorod arrays as substrates. By this method, polychlorinated biphenyls can be detected to a concentration of 5 μg/g in dry soil samples within 1 minute. Furthermore, based on simulation and understanding of the Raman characteristics of PCBs, we recognized homologues of tetrachlorobiphenyl by using the surface-enhance Raman scattering method even in trace amounts in acetone solutions, and their characteristic Raman peaks still can be distinguished at a concentration of 10-6 mol/L. This study provides a fast, simple and sensitive method for the detection and recognition of organic pollutants such as polychlorinated biphenyls.

Description: Symmetry, Vol. 10, Pages 419: Probabilistic Single-Valued (Interval) Neutrosophic Hesitant Fuzzy Set and Its Application in Multi-Attribute Decision Making Symmetry doi: 10.3390/sym10090419 Authors: Songtao Shao Xiaohong Zhang Yu Li Chunxin Bo The uncertainty and concurrence of randomness are considered when many practical problems are dealt with. To describe the aleatory uncertainty and imprecision in a neutrosophic environment and prevent the obliteration of more data, the concept of the probabilistic single-valued (interval) neutrosophic hesitant fuzzy set is introduced. By definition, we know that the probabilistic single-valued neutrosophic hesitant fuzzy set (PSVNHFS) is a special case of the probabilistic interval neutrosophic hesitant fuzzy set (PINHFS). PSVNHFSs can satisfy all the properties of PINHFSs. An example is given to illustrate that PINHFS compared to PSVNHFS is more general. Then, PINHFS is the main research object. The basic operational relations of PINHFS are studied, and the comparison method of probabilistic interval neutrosophic hesitant fuzzy numbers (PINHFNs) is proposed. Then, the probabilistic interval neutrosophic hesitant fuzzy weighted averaging (PINHFWA) and the probability interval neutrosophic hesitant fuzzy weighted geometric (PINHFWG) operators are presented. Some basic properties are investigated. Next, based on the PINHFWA and PINHFWG operators, a decision-making method under a probabilistic interval neutrosophic hesitant fuzzy circumstance is established. Finally, we apply this method to the issue of investment options. The validity and application of the new approach is demonstrated.

Description: Sustainability, Vol. 10, Pages 2151: Coal Power Environmental Stress Testing in China Sustainability doi: 10.3390/su10072151 Authors: Jiahai Yuan Mengya Wu Weirong Zhang Yu Guo Minpeng Xiong The development of China’s coal power industry is accompanied by various environmental risks. In this paper, typical coal power enterprises are taken as examples to establish a tool for environmental cost internalization and environmental risk analysis under the risk constraints of energy efficiency standards, environmental protection tax, national carbon market, water resources tax, overcapacity and renewable energy substitution. The study considered the impact on the value of coal power companies under different stress scenarios and constructed a stress testing framework for environmental risks that affect financial costs. The results show that the impacts of overcapacity and carbon market on enterprise value for individual risks are the main risk drivers that most regions face in different scenarios. In the comprehensive risk stress test, the enterprise value of the 1000 MW ultra-supercritical units in each region was found to have a small difference from the corporate value of the reasonable return in the optimistic and pessimistic scenarios, while the 300 MW and 600 MW sub critical units were more likely to deviate from the reasonable return due to low energy efficiency and high operating costs. With continuous increase in the severity of environmental risks, the environmental stress test helps coal power companies and financial institutions understand the impact of environmental risks on the financial status of the company and thus influence investment decisions.

Description: Minerals, Vol. 8, Pages 345: Eogenetic Karst Control of Carbonate Reservoirs during a Transient Exposure: A Case Study of the Ordovician Yingshan Formation in the Northern Slope of the Tazhong Uplift, Tarim Basin, China Minerals doi: 10.3390/min8080345 Authors: Yong Dan Liangbiao Lin Bin Liang Qingyu Zhang Yu Yu Jianwen Cao Jingrui Li The Tazhong area of the Tarim Basin contains abundant oil and gas resources in Ordovician carbonate rocks, especially in the karst pores and caves of the Yingshan Formation. Research has indicated that the Yingshan Formation underwent a 7–11 Ma exposure during the middle Caledonian Period, resulting in large-scale karst pores and caves. However, the continental freshwater karst model cannot adequately explain the origin and distribution of karst pores and caves. In order to develop a more accurate karst model to guide petroleum exploration in the region, we analyzed the karst morphology, cave development statistics, and paleokarst environments. Karst reservoir characteristics were analyzed on the basis of the following analysis: (1) Karst morphological analyses based on core description and formation micro-imager (FMI) log analyses. The results showed that alveolar-like and Swiss cheese-like solution pores, spongy dissolution zones, pit cenotes, and small continuous karst caves developed in the Yingshan Formation. (2) The statistical analysis of pore and cave characteristics indicated that most of the karst pores and caves developed within 50 m below the unconformity where the average height of these features ranged from 0.1 to 3.0 m and their widths ranged up to 100 m. These pores and caves were commonly filled with gravel, clay, and calcite. Horizontal well and seismic attribute analysis indicated that these pores and caves were distributed over a large area. In plain view, the karst pore-cave system is comprised of cross-linked anastomosing networks of horizontal cave passages. And (3) Cathode luminescence and electron microprobe analyses suggested that clay filling within karst caves was freshwater related, while calcite filling was of seawater origin. Cements within solution pores showed three phases of luminescence, suggesting an alternating freshwater and seawater environment. Based on these characteristics, the karsts of the Yingshan Formation in the Tazhong area are interpreted to be similar to the eogenetic karsts in the Yucatan Peninsula of modern Mexico. Accordingly, this study indicates that the pore-caves of the Yingshan Formation can be subdivided into three sections. Further, the development and filling of these pore-cave sections are interpreted to have formed by eogenetic mixed-water karstification during three phases of relatively stable sea level in a coastal margin environment.