bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Three Techniques for Correcting the Spatial Scaling Bias of Leaf Area Index
Authors: Jiang Jiale , Ji Xusheng , Yao Xia , Tian Yongchao , Zhu Yan , Cao Weixing , Cheng Tao
Published: February 2018

The correction of spatial scaling bias on the estimate of leaf area index (LAI) retrieved from remotely sensed data is an essential issue in quantitative remote sensing for vegetation monitoring. We analyzed three techniques, including Taylor’s theorem (TT), Wavelet-Fractal technique (WF), and Fractal theory (FT), for correcting the scaling bias of LAI with empirical models in different functions (i.e., power, exponential, logarithmic and polynomial) on both simulated data and a real dataset over a cropland site. The results demonstrated that the scaling bias became greater when the model non-linearity increased. The spatial heterogeneity, which was characterized by the class-specific proportion, the between-class spectral difference and the number of classes within each coarse pixel, was found to be the primary factor in the scaling effect. These factors influenced the scaling effect collectively and existed dependently. With the RMSE less than 0.3 × 10−6 m2/m2, TT was suggested for the correction with a polynomial LAI-NDVI functions. WF was preferred for neighboring scales rather than continuous scales. FT was not recommended for correcting the scaling bias caused by the significant non-linearity in LAI estimation models. This study illustrates the main causes of the scaling effect and provides a reference of technique selection for scaling bias correction to improve the application of remotely sensed estimates.
Normalization in Unsupervised Segmentation Parameter Optimization: A Solution Based on Local Regression Trend Analysis
Authors: Georganos Stefanos , Lennert Moritz , Grippa Tais , Vanhuysse Sabine , Johnson Brian , Wolff Eléonore
Published: February 2018

In object-based image analysis (OBIA), the appropriate parametrization of segmentation algorithms is crucial for obtaining satisfactory image classification results. One of the ways this can be done is by unsupervised segmentation parameter optimization (USPO). A popular USPO method does this through the optimization of a “global score” (GS), which minimizes intrasegment heterogeneity and maximizes intersegment heterogeneity. However, the calculated GS values are sensitive to the minimum and maximum ranges of the candidate segmentations. Previous research proposed the use of fixed minimum/maximum threshold values for the intrasegment/intersegment heterogeneity measures to deal with the sensitivity of user-defined ranges, but the performance of this approach has not been investigated in detail. In the context of a remote sensing very-high-resolution urban application, we show the limitations of the fixed threshold approach, both in a theoretical and applied manner, and instead propose a novel solution to identify the range of candidate segmentations using local regression trend analysis. We found that the proposed approach showed significant improvements over the use of fixed minimum/maximum values, is less subjective than user-defined threshold values and, thus, can be of merit for a fully automated procedure and big data applications.
Validation of Carbon Monoxide Total Column Retrievals from SCIAMACHY Observations with NDACC/TCCON Ground-Based Measurements
Authors: Hochstaffl Philipp , Schreier Franz , Lichtenberg Günter , Gimeno García Sebastian
Published: February 2018

The objective was to validate the carbon monoxide (CO) total column product inferred from Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) full-mission (2003–2011) short-wave infrared (SWIR) nadir observations using the Beer InfraRed Retrieval Algorithm (BIRRA). Globally distributed Network for the Detection of Atmospheric Composition Change (NDACC) and Total Carbon Column Observing Network (TCCON) ground-based (g-b) measurements were used as a true reference. Weighted averages of SCIAMACHY CO observations within a circle around the g-b observing system were utilized to minimize effects due to spatial mismatch of space-based (s-b) and g-b observations, i.e., disagreements due to representation errors rather than instrument and/or algorithm deficiencies. In addition, temporal weighted averages were examined and then the unweighted (classical) approach was compared to the weighted (non-classical) method. The delivered distance-based filtered SCIAMACHY data were in better agreement with respect to CO averages as compared to square-shaped sampling areas throughout the year. Errors in individual SCIAMACHY retrievals have increased substantially since 2005. The global bias was determined to be in the order of − 10 parts per billion in volume (ppbv) depending on the reference network and validation strategy used. The largest negative bias was found to occur in the northern mid-latitudes in Europe and North America, and was partly caused by insufficient a priori estimates of CO and cloud shielding. Furthermore, no significant trend was identified in the global bias throughout the mission. The global analysis of the CO columns retrieved by the BIRRA shows results that are largely consistent with similar investigations in previous works.
Facial Emotion Recognition: A Survey and Real-World User Experiences in Mixed Reality
Authors: Mehta Dhwani , Siddiqui Mohammad , Javaid Ahmad
Published: February 2018

Extensive possibilities of applications have made emotion recognition ineluctable and challenging in the field of computer science. The use of non-verbal cues such as gestures, body movement, and facial expressions convey the feeling and the feedback to the user. This discipline of Human–Computer Interaction places reliance on the algorithmic robustness and the sensitivity of the sensor to ameliorate the recognition. Sensors play a significant role in accurate detection by providing a very high-quality input, hence increasing the efficiency and the reliability of the system. Automatic recognition of human emotions would help in teaching social intelligence in the machines. This paper presents a brief study of the various approaches and the techniques of emotion recognition. The survey covers a succinct review of the databases that are considered as data sets for algorithms detecting the emotions by facial expressions. Later, mixed reality device Microsoft HoloLens (MHL) is introduced for observing emotion recognition in Augmented Reality (AR). A brief introduction of its sensors, their application in emotion recognition and some preliminary results of emotion recognition using MHL are presented. The paper then concludes by comparing results of emotion recognition by the MHL and a regular webcam.
Estimation of Foot Plantar Center of Pressure Trajectories with Low-Cost Instrumented Insoles Using an Individual-Specific Nonlinear Model
Authors: Hu Xinyao , Zhao Jun , Peng Dongsheng , Sun Zhenglong , Qu Xingda
Published: February 2018

Postural control is a complex skill based on the interaction of dynamic sensorimotor processes, and can be challenging for people with deficits in sensory functions. The foot plantar center of pressure (COP) has often been used for quantitative assessment of postural control. Previously, the foot plantar COP was mainly measured by force plates or complicated and expensive insole-based measurement systems. Although some low-cost instrumented insoles have been developed, their ability to accurately estimate the foot plantar COP trajectory was not robust. In this study, a novel individual-specific nonlinear model was proposed to estimate the foot plantar COP trajectories with an instrumented insole based on low-cost force sensitive resistors (FSRs). The model coefficients were determined by a least square error approximation algorithm. Model validation was carried out by comparing the estimated COP data with the reference data in a variety of postural control assessment tasks. We also compared our data with the COP trajectories estimated by the previously well accepted weighted mean approach. Comparing with the reference measurements, the average root mean square errors of the COP trajectories of both feet were 2.23 mm (±0.64) (left foot) and 2.72 mm (±0.83) (right foot) along the medial–lateral direction, and 9.17 mm (±1.98) (left foot) and 11.19 mm (±2.98) (right foot) along the anterior–posterior direction. The results are superior to those reported in previous relevant studies, and demonstrate that our proposed approach can be used for accurate foot plantar COP trajectory estimation. This study could provide an inexpensive solution to fall risk assessment in home settings or community healthcare center for the elderly. It has the potential to help prevent future falls in the elderly.
The Effects of Graphene Stacking on the Performance of Methane Sensor: A First-Principles Study on the Adsorption, Band Gap and Doping of Graphene
Authors: Yang Ning , Yang Daoguo , Zhang Guoqi , Chen Liangbiao , Liu Dongjing , Cai Miao , Fan Xuejun
Published: February 2018

The effects of graphene stacking are investigated by comparing the results of methane adsorption energy, electronic performance, and the doping feasibility of five dopants (i.e., B, N, Al, Si, and P) via first-principles theory. Both zigzag and armchair graphenes are considered. It is found that the zigzag graphene with Bernal stacking has the largest adsorption energy on methane, while the armchair graphene with Order stacking is opposite. In addition, both the Order and Bernal stacked graphenes possess a positive linear relationship between adsorption energy and layer number. Furthermore, they always have larger adsorption energy in zigzag graphene. For electronic properties, the results show that the stacking effects on band gap are significant, but it does not cause big changes to band structure and density of states. In the comparison of distance, the average interlamellar spacing of the Order stacked graphene is the largest. Moreover, the adsorption effect is the result of the interactions between graphene and methane combined with the change of graphene’s structure. Lastly, the armchair graphene with Order stacking possesses the lowest formation energy in these five dopants. It could be the best choice for doping to improve the methane adsorption.
A Simple Surface-Enhanced Raman Spectroscopic Method for on-Site Screening of Tetracycline Residue in Whole Milk
Authors: Dhakal Sagar , Chao Kuanglin , Huang Qing , Kim Moon , Schmidt Walter , Qin Jianwei , Broadhurst C.
Published: February 2018

Therapeutic and subtherapeutic use of veterinary drugs has increased the risk of residue contamination in animal food products. Antibiotics such as tetracycline are used for mastitis treatment of lactating cows. Milk expressed from treated cows before the withdrawal period has elapsed may contain tetracycline residue. This study developed a simple surface-enhanced Raman spectroscopic (SERS) method for on-site screening of tetracycline residue in milk and water. Six batches of silver colloid nanoparticles were prepared for surface enhancement measurement. Milk-tetracycline and water-tetracycline solutions were prepared at seven concentration levels (1000, 500, 100, 10, 1, 0.1, and 0.01 ppm) and spiked with silver colloid nanoparticles. A 785 nm Raman spectroscopic system was used for spectral measurement. Tetracycline vibrational modes were observed at 1285, 1317 and 1632 cm−1 in water-tetracycline solutions and 1322 and 1621 cm−1 (shifted from 1317 and 1632 cm−1, respectively) in milk-tetracycline solutions. Tetracycline residue concentration as low as 0.01 ppm was detected in both the solutions. The peak intensities at 1285 and 1322 cm−1 were used to estimate the tetracycline concentrations in water and milk with correlation coefficients of 0.92 for water and 0.88 for milk. Results indicate that this SERS method is a potential tool that can be used on-site at field production for qualitative and quantitative detection of tetracycline residues.
Game Theory-Based Cooperation for Underwater Acoustic Sensor Networks: Taxonomy, Review, Research Challenges and Directions
Authors: Muhammed Dalhatu , Anisi Mohammad , Zareei Mahdi , Vargas-Rosales Cesar , Khan Anwar
Published: February 2018

Exploring and monitoring the underwater world using underwater sensors is drawing a lot of attention these days. In this field cooperation between acoustic sensor nodes has been a critical problem due to the challenging features such as acoustic channel failure (sound signal), long propagation delay of acoustic signal, limited bandwidth and loss of connectivity. There are several proposed methods to improve cooperation between the nodes by incorporating information/game theory in the node’s cooperation. However, there is a need to classify the existing works and demonstrate their performance in addressing the cooperation issue. In this paper, we have conducted a review to investigate various factors affecting cooperation in underwater acoustic sensor networks. We study various cooperation techniques used for underwater acoustic sensor networks from different perspectives, with a concentration on communication reliability, energy consumption, and security and present a taxonomy for underwater cooperation. Moreover, we further review how the game theory can be applied to make the nodes cooperate with each other. We further analyze different cooperative game methods, where their performance on different metrics is compared. Finally, open issues and future research direction in underwater acoustic sensor networks are highlighted.
On-Line Temperature Estimation for Noisy Thermal Sensors Using a Smoothing Filter-Based Kalman Predictor
Authors: Li Xin , Ou Xingtao , Li Zhi , Wei Henglu , Zhou Wei , Duan Zhemin
Published: February 2018

Dynamic thermal management (DTM) mechanisms utilize embedded thermal sensors to collect fine-grained temperature information for monitoring the real-time thermal behavior of multi-core processors. However, embedded thermal sensors are very susceptible to a variety of sources of noise, including environmental uncertainty and process variation. This causes the discrepancies between actual temperatures and those observed by on-chip thermal sensors, which seriously affect the efficiency of DTM. In this paper, a smoothing filter-based Kalman prediction technique is proposed to accurately estimate the temperatures from noisy sensor readings. For the multi-sensor estimation scenario, the spatial correlations among different sensor locations are exploited. On this basis, a multi-sensor synergistic calibration algorithm (known as MSSCA) is proposed to improve the simultaneous prediction accuracy of multiple sensors. Moreover, an infrared imaging-based temperature measurement technique is also proposed to capture the thermal traces of an advanced micro devices (AMD) quad-core processor in real time. The acquired real temperature data are used to evaluate our prediction performance. Simulation shows that the proposed synergistic calibration scheme can reduce the root-mean-square error (RMSE) by 1.2 ∘ C and increase the signal-to-noise ratio (SNR) by 15.8 dB (with a very small average runtime overhead) compared with assuming the thermal sensor readings to be ideal. Additionally, the average false alarm rate (FAR) of the corrected sensor temperature readings can be reduced by 28.6%. These results clearly demonstrate that if our approach is used to perform temperature estimation, the response mechanisms of DTM can be triggered to adjust the voltages, frequencies, and cooling fan speeds at more appropriate times.
A Real-Time Reaction Obstacle Avoidance Algorithm for Autonomous Underwater Vehicles in Unknown Environments
Authors: Yan Zheping , Li Jiyun , Zhang Gengshi , Wu Yi
Published: February 2018

A novel real-time reaction obstacle avoidance algorithm (RRA) is proposed for autonomous underwater vehicles (AUVs) that must adapt to unknown complex terrains, based on forward looking sonar (FLS). To accomplish this algorithm, obstacle avoidance rules are planned, and the RRA processes are split into five steps Introduction only lists 4 so AUVs can rapidly respond to various environment obstacles. The largest polar angle algorithm (LPAA) is designed to change detected obstacle’s irregular outline into a convex polygon, which simplifies the obstacle avoidance process. A solution is designed to solve the trapping problem existing in U-shape obstacle avoidance by an outline memory algorithm. Finally, simulations in three unknown obstacle scenes are carried out to demonstrate the performance of this algorithm, where the obtained obstacle avoidance trajectories are safety, smooth and near-optimal.
Design Optimization and Fabrication of a Novel Structural SOI Piezoresistive Pressure Sensor with High Accuracy
Authors: Li Chuang , Cordovilla Francisco , Jagdheesh R. , Ocaña José
Published: February 2018

This paper presents a novel structural piezoresistive pressure sensor with four-grooved membrane combined with rood beam to measure low pressure. In this investigation, the design, optimization, fabrication, and measurements of the sensor are involved. By analyzing the stress distribution and deflection of sensitive elements using finite element method, a novel structure featuring high concentrated stress profile (HCSP) and locally stiffened membrane (LSM) is built. Curve fittings of the mechanical stress and deflection based on FEM simulation results are performed to establish the relationship between mechanical performance and structure dimension. A combination of FEM and curve fitting method is carried out to determine the structural dimensions. The optimized sensor chip is fabricated on a SOI wafer by traditional MEMS bulk-micromachining and anodic bonding technology. When the applied pressure is 1 psi, the sensor achieves a sensitivity of 30.9 mV/V/psi, a pressure nonlinearity of 0.21% FSS and an accuracy of 0.30%, and thereby the contradiction between sensitivity and linearity is alleviated. In terms of size, accuracy and high temperature characteristic, the proposed sensor is a proper choice for measuring pressure of less than 1 psi.
Development of a Preliminary Model for Evaluating Occupational Health and Safety Risk Management Maturity in Small and Medium-Sized Enterprises
Authors: Kaassis Bilal , Badri Adel
Published: February 2018

Management of occupational health and safety (OHS) risks is a crucial component of any business. Numerous investigations have shown that work-related injuries and deaths occur disproportionately in small-to-medium-sized enterprises (SMEs) and that this is clearly due to deficient management of OHS risks. The main goal of this work is to develop a base of indicators suitable for evaluating OHS risk management maturity in industrial SMEs. A preliminary model is then proposed for this evaluation, based on a small number of relevant indicators selected from a careful bibliographic review. The work begins with a critical review of the literature and analysis of known concepts, methods, tools and models of measurement of risk analysis maturity in order to extract relevant indicators. The most suitable indicators are then grouped to form the basis of a preliminary model for evaluating OHS risk management maturity in the SME setting. Our findings will help managers of SMEs make sound decisions in their quest to improve the OHS performance of their businesses.
A Molecular Investigation of Soil Organic Carbon Composition across a Subalpine Catchment
Authors: Hsu Hsiao-Tieh , Lawrence Corey , Winnick Matthew , Bargar John , Maher Katharine
Published: February 2018

The dynamics of soil organic carbon (SOC) storage and turnover are a critical component of the global carbon cycle. Mechanistic models seeking to represent these complex dynamics require detailed SOC compositions, which are currently difficult to characterize quantitatively. Here, we address this challenge by using a novel approach that combines Fourier transform infrared spectroscopy (FT-IR) and bulk carbon X-ray absorption spectroscopy (XAS) to determine the abundance of SOC functional groups, using elemental analysis (EA) to constrain the total amount of SOC. We used this SOC functional group abundance (SOC-fga) method to compare variability in SOC compositions as a function of depth across a subalpine watershed (East River, Colorado, USA) and found a large degree of variability in SOC functional group abundances between sites at different elevations. Soils at a lower elevation are predominantly composed of polysaccharides, while soils at a higher elevation have more substantial portions of carbonyl, phenolic, or aromatic carbon. We discuss the potential drivers of differences in SOC composition between these sites, including vegetation inputs, internal processing and losses, and elevation-driven environmental factors. Although numerical models would facilitate the understanding and evaluation of the observed SOC distributions, quantitative and meaningful measurements of SOC molecular compositions are required to guide such models. Comparison among commonly used characterization techniques on shared reference materials is a critical next step for advancing our understanding of the complex processes controlling SOC compositions.
Sustainability Orientation and Entrepreneurship Orientation: Is There a Tradeoff Relationship between Them?
Authors: Sung Chang , Park Joo
Published: February 2018

Sustainability and entrepreneurship are often regarded as binary concepts that have a tradeoff relationship, meaning that the higher the social and environmental consideration, the lower the private and economic benefits. The purpose of this study is to investigate the effect of individual sustainability orientation on opportunity recognition and sustainable entrepreneurship intention, and examine whether it has a tradeoff relationship with entrepreneurship orientation. The result of this study shows that sustainability orientation has a positive relationship with opportunity recognition and entrepreneurship intention related to sustainability. Analysis of the moderating effects of entrepreneurship orientation reveals the positive effect with sustainability orientation but negative effect with opportunity recognition on sustainable entrepreneurship intention. This study would suggest implications to entrepreneurs on how to balance sustainability and entrepreneurship and promote sustainability entrepreneurship.
Significance of Submarine Groundwater Discharge in Nutrient Budgets in Tropical Sanya Bay, China
Authors: Wang Guizhi , Wang Shuling , Wang Zhangyong , Jing Wenping
Published: February 2018

To quantify the contribution of submarine groundwater discharge (SGD) to the nutrient budget in tropical embayments, naturally occurring radium isotopes (223Ra, 224Ra, 226Ra, and 228Ra) were investigated as SGD tracers in Sanya Bay, China. Higher activities of radium were present along the north coast and near the Sanya River estuary. Using the activity ratio of 224Ra/228Ra, the apparent water age in Sanya Bay was estimated to be 0–13.2 days, with an average of 7.2 ± 3.2 days. Based on the mass balance of 226Ra and 228Ra, SGD was calculated to be 2.79 ± 1.39–5.07 ± 2.67 × 106 m3 d−1 (or 4.3 ± 2.1–7.8 ± 4.1 cm d−1). SGD associated dissolved inorganic nutrient fluxes into Sanya Bay were estimated to be 3.94 ± 2.00–7.15 ± 3.85 × 105 mol d−1 for oxidized inorganic nitrogen, 4.64 ± 2.74–8.42 ± 5.19 × 103 mol d−1 for phosphate, and 6.63 ± 3.29–12.0 ± 6.34 × 105 mol d−1 for silicate. The estuarine nutrient flux from the Sanya River was a few times smaller than the phosphate flux via SGD and at least an order of magnitude smaller than the oxidized inorganic nitrogen and silicate fluxes carried by SGD. SGD was also more important than atmospheric deposition and nitrogen fixation in the nutrient budget. Our results demonstrate that SGD compensated for at least 15% phosphate, 90% oxidized inorganic nitrogen, and 60% silicate of the nutrients sink in Sanya Bay.
Potential and Realized Absorptive Capacity as Complementary Drivers of Green Product and Process Innovation Performance
Authors: Albort-Morant Gema , Henseler Jörg , Cepeda-Carrión Gabriel , Leal-Rodríguez Antonio
Published: February 2018

Nowadays, companies need to absorb new knowledge from external sources to grasp environmental issues. However, the internal mechanisms through which external knowledge is turned into green innovations remain scarcely addressed. Hence, this paper aims to investigate the relationships between the two dimensions of absorptive capacity (potential and realized) with green products and process innovation performance. This study contributes to the literature by disentangling how companies need to acquire, assimilate, transform and exploit external environmental knowledge to develop green innovations. To this aim, this empirical study is based on a sample shaped by 112 firms belonging to the Spanish automotive components manufacturing sector. The results provide evidence to show that potential and realized absorptive capacities are positively related to both green product innovation performance and green process innovation performance.
Comparing Social Media Data and Survey Data in Assessing the Attractiveness of Beijing Olympic Forest Park
Authors: Wang Zhifang , Jin Yue , Liu Yu , Li Dong , Zhang Bo
Published: February 2018

Together with the emerging popularity of big data in numerous studies, increasing theoretical discussions of the challenges and limitations of such data sources exist. However, there is a clear research gap in the empirical comparison studies on different data sources. The goal of this paper is to use “attractiveness” as a medium to examine the similarity and differences of Social media data (SMD) and survey data in academic research, based on a case study of the Beijing Olympic Forest Park, in Beijing, China. SMD was extracted from two social media platforms and two surveys were conducted to assess the attractiveness of various locations and landscape elements. Data collection, keyword extraction and keyword prioritization were used and compared in the data gathering and analysis process. The findings revealed that SMD and survey data share many similarities. Both data sources confirm that natural ambience is more appreciated than cultural elements, particularly the naturalness of the park. Spaces of practical utility are more appreciated than facilities designed to have cultural meanings and iconic significance. Despite perceived similarities, this study concludes that SMD exhibits exaggerated and aggregated bias. This resulted from the intrinsic character of SMD as volunteered and unstructured data selected through an emotional process rather than from a rational synthesis. Exciting events were reported more often than daily experiences. Reflecting upon the strength and weakness of SMD and survey data, this study would recommend a combined landscape assessment process, which first utilizes SMD to build up an assessment framework, then applies conventional surveys for supplementary and detailed information. This would ultimately result in comprehensive understanding.
A Comparison of the Water Environment Policy of Europe and South Korea in Response to Climate Change
Authors: Kim Heejung , Lee Kang-Kun
Published: February 2018

Climate change not only increases the atmospheric temperature, but also changes the precipitation conditions and patterns, which can lead to an increase in the frequency of occurrence of natural disasters, such as flooding and drought. The Intergovernmental Panel on Climate Change (IPCC) has reported fluctuations in the precipitation levels for each country from 1900 to 2005, based on global climate change, suggesting that environmental changes due to climate change manifest very differently based on the region. According to the results of studies that have been carried out recently, changes in the precipitation patterns based on climate change result in changes in the water environment, including alterations to the vegetation, land use, and river flow, while considerably influencing the rate of development of groundwater as well. In this study, the 3Is, which are the important variables of Ideas, Institutions, and Interests that are universal to the international field of political science, were used to comparatively analyze the water environment policies of South Korea and Europe. The first variable, Ideas, examined the influence of awareness on establishing the water environment policy in response to climate change. In particular, differences in the conceptual awareness of the water environment with regard to hyporheic zones were studied. The second variable, Institutions, examined the differences in the water environment policy within the national administration in response to climate change. The South Korean administration’s Ministry of Land, Infrastructure, and Transport and the Ministry of Environment were used in a case study. Finally, the results drawn from the third variable, i.e., Interests, for South Korea appear to differ from those of Europe, in terms of water environment policy. In this study, the water environment policy of South Korea was analyzed and compared to that of Europe in order to identify problems in South Korea’s water environment policy in response to climate change, while seeking a sole solution for a comprehensive water environment policy direction for South Korea.
Formation Mechanism and Coping Strategy of Public Emergency for Urban Sustainability: A Perspective of Risk Propagation in the Sociotechnical System
Authors: Deng Xiuquan , Lu Zhu , Yang Xinmiao , Zhao Qiuhong , Gao Dehua , Bai Bing
Published: February 2018

Urban public emergencies now break out frequently, causing heavy losses and threatening urban sustainability at the same time. To help better curb public emergencies, minimize their damage to cities, and maintain the sustainable operation of the city, this paper takes the urban public emergency as the research object, discussing the formation mechanism of urban public emergencies and putting forward feasible countermeasures. First, we propose the concept of risk propagation chain and construct an urban socio-technical system risk propagation chain model by introducing the Tropos Goal-Risk framework. The risk propagation chain formation mechanism and the emergency formation mechanism are researched by using this model to analyze the specific conditions and paths of risk propagation. Then the targeted countermeasures are put forward to prevent and manage emergencies, advancing the goal of sustainable development. Finally, a case is used to verify the theory and model. This study not only provides a theoretical framework for the formation of urban public emergencies but also provides a practical method for modeling public emergencies and dealing with urban sustainability problems.
Selection of Policies on Typhoon and Rainstorm Disasters in China: A Content Analysis Perspective
Authors: Cai Yang , Li Lianshui , Elahi Ehsan , Qiu Yueming
Published: February 2018

China is a country often subjected to severe meteorological disasters. Analyzing the evolution of policies concerning the prevention and reduction of disasters is of great practical significance for the management of such natural events. We focus on typhoons and rainstorms as disaster sources and examine policy documents from two dimensions: basic policy instruments and disaster chains. Results indicate that (1) two levels of government (central and local) focus on five policy instruments; namely, they are fund and material input, infrastructure construction and management, information sharing and support, goal programming, and regulations. Other policies, however, such as engineering construction of disaster prevention, or material reserves and international cooperation, are relatively few. (2) At present, both the Central and Local governments prefer both supply-oriented policies and environment-oriented policies to focusing on demand-oriented policies. (3) As for the disaster chains, the typhoon and rainstorm disaster policies are focused on disaster defense, disaster warning, and disaster relief, neglecting disaster evaluation and post-disaster reconstruction. Finally, we put forward suggestions for perfecting the policies of disaster evaluation and post-disaster reconstruction, and point out the importance of demand-oriented policies.
On the High-Energy Neutrino Emission from Active Galactic Nuclei
Authors: Kun Emma , Biermann Peter , Britzen Silke , Gergely László
Published: February 2018

We review observational aspects of the active galactic nuclei and their jets in connection with the detection of high-energy neutrinos by the Antarctic IceCube Neutrino Observatory. We propose that a reoriented jet generated by the spin-flipping supermassive black hole in a binary merger is likely the source of such high-energy neutrinos. Hence they encode important information on the afterlife of coalescing supermassive black hole binaries. As the gravitational radiation emanating from them will be monitored by the future LISA space mission, high-energy neutrino detections could be considered a contributor to multi-messenger astronomy.
Multi-Stakeholder Development of a Serious Game to Explore the Water-Energy-Food-Land-Climate Nexus: The SIM4NEXUS Approach
Authors: Sušnik Janez , Chew Chengzi , Domingo Xavier , Mereu Simone , Trabucco Antonio , Evans Barry , Vamvakeridou-Lyroudia Lydia , Savić Dragan , Laspidou Chrysi , Brouwer Floor
Published: February 2018

Water, energy, food, land and climate form a tightly-connected nexus in which actions on one sector impact other sectors, creating feedbacks and unanticipated consequences. This is especially because at present, much scientific research and many policies are constrained to single discipline/sector silos that are often not interacting (e.g., water-related research/policy). However, experimenting with the interaction and determining how a change in one sector could impact another may require unreasonable time frames, be very difficult in practice and may be potentially dangerous, triggering any one of a number of unanticipated side-effects. Current modelling often neglects knowledge from practice. Therefore, a safe environment is required to test the potential cross-sectoral implications of policy decisions in one sector on other sectors. Serious games offer such an environment by creating realistic ‘simulations’, where long-term impacts of policies may be tested and rated. This paper describes how the ongoing (2016–2020) Horizon2020 project SIM4NEXUS will develop serious games investigating potential plausible cross-nexus implications and synergies due to policy interventions for 12 multi-scale case studies ranging from regional to global. What sets these games apart is that stakeholders and partners are involved in all aspects of the modelling definition and process, from case study conceptualisation, quantitative model development including the implementation and validation of each serious game. Learning from playing a serious game is justified by adopting a proof-of-concept for a specific regional case study in Sardinia (Italy). The value of multi-stakeholder involvement is demonstrated, and critical lessons learned for serious game development in general are presented.
Well Salinization Risk and Effects of Baltic Sea Level Rise on the Groundwater-Dependent Island of Öland, Sweden
Authors: Eriksson Marcus , Ebert Karin , Jarsjö Jerker
Published: February 2018

In this study, we estimate baseline conditions in terms of the current risk of well salinization on the Baltic Sea island of Öland, Sweden, and assess the effects of future sea level rise on the land area, infrastructure and cultural values. We use a multicriterion geographical information systems (GIS) approach. Geomorphological and physical parameters affect the risk of saltwater intrusion into freshwater aquifers, including their hydrology, geomorphology, and climatology; the spatial distribution of the current risk of salinization is mapped in this study. In the event of a future 2 m sea level rise, a total land area of 67 km2 will be inundated on Öland, corresponding to approximately 5% of the island’s land surface. Inundation includes urban areas, nature reserves, and animal protection areas, implying the loss of environmental and socioeconomic values. A future 2 m sea level rise will also cause direct inundation of 3% of all wells on the island. Currently, 17.5% of all wells are at a high risk of becoming saltwater contaminated. More generally, the present results add evidence showing a relatively high vulnerability of major Baltic Sea islands and their infrastructure to future sea level rise. The approach used here and related results, including salinization risk maps, may prove useful for decision-makers in the planning of infrastructure. Drilling of new wells could for instance preferably be done in areas with identified lower risk-index values, which would facilitate an overall higher freshwater withdrawal in the interest of the entire island.
Gene Expression Programming Coupled with Unsupervised Learning: A Two-Stage Learning Process in Multi-Scale, Short-Term Water Demand Forecasts
Authors: Shabani Sina , Candelieri Antonio , Archetti Francesco , Naser Gholamreza
Published: February 2018

This article proposes a new general approach in short-term water demand forecasting based on a two-stage learning process that couples time-series clustering with gene expression programming (GEP). The approach was tested on the real life water demand data of the city of Milan, in Italy. Moreover, multi-scale modeling using a series of head-time was deployed to investigate the optimum temporal resolution under study. Multi-scale modeling was performed based on rearranging hourly based patterns of water demand into 3, 6, 12, and 24 h lead times. Results showed that GEP should receive more attention among the emerging nonlinear modelling techniques if coupled with unsupervised learning algorithms in detailed spherical k-means.
Quantifying Climatic Impact on Reference Evapotranspiration Trends in the Huai River Basin of Eastern China
Authors: Li Meng , Chu Ronghao , Shen Shuanghe , Islam Abu
Published: February 2018

Reference evapotranspiration (ETref) is an important study object for hydrological cycle processes in the context of drought-flood risks of the Huai River Basin (HRB). In this study, the FAO-56 Penman–Monteith (PM) model was employed to calculate seasonal and annual ETref based on 137 meteorological station data points in HRB from 1961 to 2014. The Mann–Kendall (MK) trend analysis was adopted together with Theil–Sen’s estimator to detect tendencies of ETref and climate factors. Furthermore, a developed differential equation method based on the FAO-56 PM model was applied to quantify the sensitivities of ETref to meteorological factors and their contributions to ETref trends. The results showed that the ETref demonstrated a strong spatially heterogeneity in the whole HRB at each time scale. ETref showed a significant decreasing trend in the upper-middle HRB and Yi-Shu-Si River Basin, especially at the annual time scale, in growing season and summer, while a generally increasing trend in ETref was detected in the lower HRB, and the significance only showed in spring. These phenomena could be reasonably explained by a significantly increasing mean temperature (TA), a significantly decreasing wind speed (WS), solar radiation (SR), and a slightly decreasing relative humidity (RH). The most sensitive factor to ETref was RH in most sub-regions and most time scales, except in the growing season and summer. Based on the developed differential equation method, the dominant factor of the decreasing ETref was WS in the annual time scale, spring, autumn, and winter in most sub-regions, except the lower HRB, which then shifted to SR in the growing season and summer. However, in the lower HRB, the significantly decreasing RH was the most dominant factor, especially in the annual time scale, growing season, and spring, which might be responsible for the slightly increasing ETref there.
A First Estimation of County-Based Green Water Availability and Its Implications for Agriculture and Bioenergy Production in the United States
Authors: Xu Hui , Wu May
Published: February 2018

Green water is vital for the terrestrial ecosystem, but water resource assessment often focuses on blue water. In this study, we estimated green water availability for major crops (i.e., corn, soybean, and wheat) and all other users (e.g., forest, grassland, and ecosystem services) at the county level in the United States. We estimated green water resources from effective rain (ER) using three different methods: Smith, U.S. Department of Agriculture—Soil Conservation Service (USDA-SCS), and the NHD plus V2 dataset. The analysis illustrates that, if green water meets all crop water demands, the fraction of green water resources available to all other users varies significantly across regions, from the Northern Plains (0.71) to the Southeast (0.98). At the county level, this fraction varies from 0.23 to 1.0. Green water resources estimated using the three different ER methods present diverse spatiotemporal distribution patterns across regions, which could affect green water availability estimates. The water availability index for green water (WAI_R) was measured taking into account crop water demand and green water resources aggregated at the county level. Beyond these parameters, WAI_R also depends on the precipitation pattern, crop type and spatially differentiated regions. In addition, seasonal analysis indicated that WAI_R is sensitive to the temporal boundary of the analysis.
Probing Extragalactic Planets Using Quasar Microlensing
Authors: Dai Xinyu , Guerras Eduardo
Published: February 2018

Previously, planets have been detected only in the Milky Way galaxy. Here, we show that quasar microlensing provides a means to probe extragalactic planets in the lens galaxy, by studying the microlensing properties of emission close to the event horizon of the supermassive black hole of the background quasar, using the current generation telescopes. We show that a population of unbound planets between stars with masses ranging from Moon to Jupiter masses is needed to explain the frequent Fe Kα line energy shifts observed in the gravitationally lensed quasar RXJ 1131–1231 at a lens redshift of z = 0.295 or 3.8 billion lt-yr away. We constrain the planet mass-fraction to be larger than 0.0001 of the halo mass, which is equivalent to 2000 objects ranging from Moon to Jupiter mass per main-sequence star.
K2 Reveals Pulsed Accretion Driven by the 2 Myr Old Hot Jupiter CI Tau b
Authors: Biddle Lauren I. , Johns-Krull Christopher M. , Llama Joe , Prato Lisa , Skiff Brian A.
Published: February 2018

CI Tau is a young (∼2 Myr) classical T Tauri star located in the Taurus star-forming region. Radial velocity observations indicate it hosts a Jupiter-sized planet with an orbital period of approximately 9 days. In this work, we analyze time series of CI Tau’s photometric variability as seen by K2. The light curve reveals the stellar rotation period to be ∼6.6 days. Although there is no evidence that CI Tau b transits the host star, a ∼9 day signature is also present in the light curve. We believe this is most likely caused by planet–disk interactions that perturb the accretion flow onto the star, resulting in a periodic modulation of the brightness with the ∼9 day period of the planet’s orbit.
The Impact of Crustal Magnetic Fields on the Thermal Structure of the Martian Upper Atmosphere
Authors: Cui J. , Yelle R. V. , Zhao L.-L. , Stone S. , Jiang F.-Y. , Cao Y.-T. , Yao M.-J. , Koskinen T. T. , Wei Y.
Published: February 2018

Using the Mars Atmosphere and Volatile Evolution Neutral Gas and Ion Mass Spectrometer data, we investigate the possible impact of crustal magnetic fields on the thermal structure of the Martian upper atmosphere. Our analysis reveals a clear enhancement in temperature over regions with strong crustal magnetic fields during two deep dip campaigns covering the periods of April 17–22 and September 2–8, both in 2015. Several controlling factors, such as solar EUV irradiance, relative atomic O abundance, and non-migrating tides, do not help to explain the observed temperature enhancement, and a magnetically driven scenario is favored. We evaluate the roles of several heating mechanisms that are likely modulated by the presence of crustal magnetic fields, including Joule heating, ion chemical heating, as well as electron impact heating via either precipitating solar wind electrons or locally produced photoelectrons. The respective heating rates of these mechanisms are substantially lower than the solar EUV heating rate, implying that none of them is able to interpret the observations.
Integral Field Spectroscopy of Supernova Remnant 1E0102–7219 Reveals Fast-moving Hydrogen and Sulfur-rich Ejecta
Authors: Seitenzahl Ivo R. , Vogt Frédéric P. A. , Terry Jason P. , Ghavamian Parviz , Dopita Michael A. , Ruiter Ashley J. , Sukhbold Tuguldur
Published: February 2018

We study the optical emission from heavy element ejecta in the oxygen-rich young supernova remnant 1E 0102.2–7219 (1E 0102) in the Small Magellanic Cloud. We have used the Multi-Unit Spectroscopic Explorer optical integral field spectrograph at the Very Large Telescope on Cerro Paranal and the wide field spectrograph (WiFeS) at the ANU 2.3 m telescope at Siding Spring Observatory to obtain deep observations of 1E 0102. Our observations cover the entire extent of the remnant from below 3500 Å to 9350 Å. Our observations unambiguously reveal the presence of fast-moving ejecta emitting in [S ii], [S iii], [Ar iii], and [Cl ii]. The sulfur-rich ejecta appear more asymmetrically distributed compared to oxygen or neon, a product of carbon burning. In addition to the forbidden line emission from products of oxygen burning (S, Ar, Cl), we have also discovered Hα and Hβ emission from several knots of low surface brightness, fast-moving ejecta. The presence of fast-moving hydrogen points toward a progenitor that had not entirely shed its hydrogen envelope prior to the supernova. The explosion that gave rise to 1E 0102 is therefore commensurate with a Type IIb supernova.
The Hubble Constant from SN Refsdal
Authors: Vega-Ferrero J. , Diego J. M. , Miranda V. , Bernstein G. M.
Published: February 2018

Hubble Space Telescope observations from 2015 December 11 detected the expected fifth counter-image of supernova (SN) Refsdal at z = 1.49. In this Letter, we compare the time-delay predictions from numerous models with the measured value derived by Kelly et al. from very early data in the light curve of the SN Refsdal and find a best value for

(68% CL), in excellent agreement with predictions from cosmic microwave background and recent weak lensing data + baryon acoustic oscillations + Big Bang nucleosynthesis (from the DES Collaboration). This is the first constraint on H
0 derived from time delays between multiple-lensed SN images, and the first with a galaxy cluster lens, subject to systematic effects different from other time-delay H
0 estimates. Additional time-delay measurements from new multiply imaged SNe will allow derivation of competitive constraints on H
0.