bluuebunny/crossref_metadata_2025 huggingface dataset:
Remotely-Sensed Identification of a Transition for the Two Ecosystem States Along the Elevation Gradient: A Case Study of Xinjiang Tianshan Bogda World Heritage Site
Authors: Wan Hong , Wang Xinyuan , Luo Lei , Guo Peng , Zhao Yanchuang , Wu Kai , Ren Hongge
Published: December 2019

The alpine treeline, as an ecological transition zone between montane coniferous forests and alpine meadows (two ecosystem states), is a research hotspot of global ecology and climate change. Quantitative identification of its elevation range can efficiently capture the results of the interaction between climate change and vegetation. Digital extraction and extensive analysis in such a critical elevation range crucially depend on the ability of monitoring ecosystem variables and the suitability of the experimental model, which are often restricted by the weak intersection of disciplines and the spatial-temporal continuity of the data. In this study, the existence of two states was confirmed by frequency analysis and the Akaike information criterion (AIC) as well as the Bayesian information criterion (BIC) indices. The elevation range of a transition for the two ecosystem states on the northern slope of the Bogda was identified by the potential analysis. The results showed that the elevation range of co-occurrence for the two ecosystem states was 2690–2744 m. At the elevation of 2714 m, the high land surface temperature (LST) state started to exhibit more attraction than the low LST state. This elevation value was considered as a demarcation where abrupt shifts between the two states occurred with the increase of elevation. The identification results were validated by a field survey and unmanned aerial vehicle data. Progress has been made in the transition identification for the ecosystem states along the elevation gradient in mountainous areas by combining the remotely-sensed index with a potential analysis. This study also provided a reference for obtaining the elevation of the alpine tree line quickly and accurately.
A New Multiple Hypothesis Tracker Integrated with Detection Processing
Authors: Wang Ziwei , Sun Jinping , Li Qing , Ding Guanhua
Published: December 2019

In extant radar signal processing systems, detection and tracking are carried out independently, and detected measurements are utilized as inputs to the tracking procedure. Therefore, the tracking performance is highly associated with detection accuracy, and this performance may severely degrade when detections include a mass of false alarms and missed-targets errors, especially in dense clutter or closely-spaced trajectories scenarios. To deal with this issue, this paper proposes a novel method for integrating the multiple hypothesis tracker with detection processing. Specifically, the detector acquires an adaptive detection threshold from the output of the multiple hypothesis tracker algorithm, and then the obtained detection threshold is employed to compute the score function and sequential probability ratio test threshold for the data association and track estimation tasks. A comparative analysis of three tracking algorithms in a clutter dense scenario, including the proposed method, the multiple hypothesis tracker, and the global nearest neighbor algorithm, is conducted. Simulation results demonstrate that the proposed multiple hypothesis tracker integrated with detection processing method outperforms both the standard multiple hypothesis tracker algorithm and the global nearest neighbor algorithm in terms of tracking accuracy.
Low-Input Estimation of Site-Specific Lime Demand Based on Apparent Soil Electrical Conductivity and In Situ Determined Topsoil pH
Authors: von Cossel Moritz , Druecker Harm , Hartung Eberhard
Published: December 2019

Site-specific liming helps increase efficiency in agricultural production. For adequate determination of the lime demand, a combination of apparent soil electrical conductivity (ECa) and topsoil pH can be used. Here, it was hypothesized that this can also be done at low-input level. Field measurements using the EM38 MK I (Geonics, Canada) were conducted on three experimental sites in north Germany in 2011. The topsoil pH was measured based on two approaches: on the field using a handheld pH meter (Spectrum-Technologies Ltd., Bridgend, UK) with a flat electrode (in situ), and in the lab using standard equipment (ex situ). Both soil ECa (0.4–35.9 mS m−1) and pH (5.13–7.41) were heterogeneously distributed across the sites. The same was true of the lime demand (−1.35–4.18 Mg ha−1). There was a significant correlation between in situ and ex situ determined topsoil pH (r = 0.89; p < 0.0001). This correlation was further improved through non-linear regression (r = 0.92; p < 0.0001). Thus, in situ topsoil pH was found suitable for map-overlay with ECa to determine the site-specific lime demand. Consequently, the hypothesis could be confirmed: The combined use of data from EM38 and handheld pH meters is a promising low-input approach that may help implement site-specific liming in developing countries.
A Deep Learning-Based End-to-End Composite System for Hand Detection and Gesture Recognition
Authors: MOHAMMED Adam Ahmed Qaid , Lv Jiancheng , Islam MD. Sajjatul
Published: December 2019

Recent research on hand detection and gesture recognition has attracted increasing interest due to its broad range of potential applications, such as human-computer interaction, sign language recognition, hand action analysis, driver hand behavior monitoring, and virtual reality. In recent years, several approaches have been proposed with the aim of developing a robust algorithm which functions in complex and cluttered environments. Although several researchers have addressed this challenging problem, a robust system is still elusive. Therefore, we propose a deep learning-based architecture to jointly detect and classify hand gestures. In the proposed architecture, the whole image is passed through a one-stage dense object detector to extract hand regions, which, in turn, pass through a lightweight convolutional neural network (CNN) for hand gesture recognition. To evaluate our approach, we conducted extensive experiments on four publicly available datasets for hand detection, including the Oxford, 5-signers, EgoHands, and Indian classical dance (ICD) datasets, along with two hand gesture datasets with different gesture vocabularies for hand gesture recognition, namely, the LaRED and TinyHands datasets. Here, experimental results demonstrate that the proposed architecture is efficient and robust. In addition, it outperforms other approaches in both the hand detection and gesture classification tasks.
A Novel RGB-D SLAM Algorithm Based on Cloud Robotics
Authors: Liu Yanli , Zhang Heng , Huang Chao
Published: December 2019

In this paper, we present a novel red-green-blue-depth simultaneous localization and mapping (RGB-D SLAM) algorithm based on cloud robotics, which combines RGB-D SLAM with the cloud robot and offloads the back-end process of the RGB-D SLAM algorithm to the cloud. This paper analyzes the front and back parts of the original RGB-D SLAM algorithm and improves the algorithm from three aspects: feature extraction, point cloud registration, and pose optimization. Experiments show the superiority of the improved algorithm. In addition, taking advantage of the cloud robotics, the RGB-D SLAM algorithm is combined with the cloud robot and the back-end part of the computationally intensive algorithm is offloaded to the cloud. Experimental validation is provided, which compares the cloud robotic-based RGB-D SLAM algorithm with the local RGB-D SLAM algorithm. The results of the experiments demonstrate the superiority of our framework. The combination of cloud robotics and RGB-D SLAM can not only improve the efficiency of SLAM but also reduce the robot’s price and size.
Development of a Flexible Dielectric Sensor for Flow Monitoring of the Liquid Resin Infusion Process
Authors: Pouchias Athanasios , Cunningham Paul R. , Stein Jasmin , Kazilas Mihalis
Published: December 2019

The analysis and design of a novel flexible dielectric sensor, which can be integrated into a composite materials manufacturing process to measure the resin frontal flow, is presented in this paper. The proposed sensor consists of two parallel line electrodes and a ground plane covered by a dielectric material. The analytical description and the electrostatic modelling were considered for the design of the sensor and to enhance the understanding of the response of the sensor to the resin impregnation of a carbon fabric during the infusion phase. The optimization of the sensor’s response and the increase of its sensitivity with regards to the geometric characteristics and the materials used were the main objectives of this study. An experimental set-up for the vacuum infusion process which includes the proposed sensor was used to measure the capacitance and validate the derived resin flow against visual measurements. The results indicate that the sensor can provide information on the resin frontal flow within 2% accuracy against visual measurements, which make this technology promising for monitoring the liquid resin infusion processes.
Nondestructive Determination of Nitrogen, Phosphorus and Potassium Contents in Greenhouse Tomato Plants Based on Multispectral Three-Dimensional Imaging
Authors: Sun Guoxiang , Ding Yongqian , Wang Xiaochan , Lu Wei , Sun Ye , Yu Hongfeng
Published: December 2019

Measurement of plant nitrogen (N), phosphorus (P), and potassium (K) levels are important for determining precise fertilization management approaches for crops cultivated in greenhouses. To accurately, rapidly, stably, and nondestructively measure the NPK levels in tomato plants, a nondestructive determination method based on multispectral three-dimensional (3D) imaging was proposed. Multiview RGB-D images and multispectral images were synchronously collected, and the plant multispectral reflectance was registered to the depth coordinates according to Fourier transform principles. Based on the Kinect sensor pose estimation and self-calibration, the unified transformation of the multiview point cloud coordinate system was realized. Finally, the iterative closest point (ICP) algorithm was used for the precise registration of multiview point clouds and the reconstruction of plant multispectral 3D point cloud models. Using the normalized grayscale similarity coefficient, the degree of spectral overlap, and the Hausdorff distance set, the accuracy of the reconstructed multispectral 3D point clouds was quantitatively evaluated, the average value was 0.9116, 0.9343 and 0.41 cm, respectively. The results indicated that the multispectral reflectance could be registered to the Kinect depth coordinates accurately based on the Fourier transform principles, the reconstruction accuracy of the multispectral 3D point cloud model met the model reconstruction needs of tomato plants. Using back-propagation artificial neural network (BPANN), support vector machine regression (SVMR), and gaussian process regression (GPR) methods, determination models for the NPK contents in tomato plants based on the reflectance characteristics of plant multispectral 3D point cloud models were separately constructed. The relative error (RE) of the N content by BPANN, SVMR and GPR prediction models were 2.27%, 7.46% and 4.03%, respectively. The RE of the P content by BPANN, SVMR and GPR prediction models were 3.32%, 8.92% and 8.41%, respectively. The RE of the K content by BPANN, SVMR and GPR prediction models were 3.27%, 5.73% and 3.32%, respectively. These models provided highly efficient and accurate measurements of the NPK contents in tomato plants. The NPK contents determination performance of these models were more stable than those of single-view models.
Requirement Assessment of the Relative Spatial Accuracy of a Motion-Constrained GNSS/INS in Shortwave Track Irregularity Measurement
Authors: Zhang Quan , Chen Qijin , Niu Xiaoji , Shi Chuang
Published: December 2019

Modern railway track health monitoring requires high accuracy measurements to ensure comfort and safety. Although Global Navigation Satellite System/Inertial Navigation System (GNSS/INS) integration has been extended to track geometry measurements to improve the work efficiency, it has been questioned due to its positioning accuracy at the centimeter or millimeter level. We propose the relative spatial accuracy based on the accuracy requirement of track health monitoring. A requirement assessment of the spatial relative accuracy is conducted for shortwave track irregularity measurements based on evaluation indicators and relative accuracy calculations. The threshold values of the relative spatial accuracy that satisfy the constraints of shortwave track irregularity measurements are derived. Motion-constrained GNSS/INS integration is performed to improve the navigation accuracy considering the dynamic characteristics of the track geometry measurement trolley. The results of field tests show that the mean square error and the Allan deviation of the relative position errors of motion-constrained GNSS/INS integration are smaller than 0.67 mm and 0.16 mm, respectively, which indicates that this approach meets the accuracy requirements of shortwave track irregularities, especially vertical irregularities. This work can provide support for the application of GNSS/INS systems in track irregularity measurement.
Comparison of a New Inertial Sensor Based System with an Optoelectronic Motion Capture System for Motion Analysis of Healthy Human Wrist Joints
Authors: Wirth Michael Alexander , Fischer Gabriella , Verdú Jorge , Reissner Lisa , Balocco Simone , Calcagni Maurizio
Published: December 2019

This study aims to compare a new inertial measurement unit based system with the highly accurate but complex laboratory gold standard, an optoelectronic motion capture system. Inertial measurement units are sensors based on accelerometers, gyroscopes, and/or magnetometers. Ten healthy subjects were recorded while performing flexion-extension and radial-ulnar deviation movements of their right wrist using inertial sensors and skin markers. Maximum range of motion during these trials and mean absolute difference between the systems were calculated. A difference of 10° ± 5° for flexion-extension and 2° ± 1° for radial-ulnar deviation was found between the two systems with absolute range of motion values of 126° and 50° in the respective axes. A Wilcoxon rank sum test resulted in a no statistical differences between the systems with p-values of 0.24 and 0.62. The observed results are even more precise than reports from previous studies, where differences between 14° and 27° for flexion-extension and differences between 6° and 17° for radial-ulnar deviation were found. Effortless and fast applicability, good precision, and low inter-observer variability make inertial measurement unit based systems applicable to clinical settings.
Managing Talent Loss in the Procurement Function: Insights from the Hospitality Industry
Authors: Daghfous Abdelkader , Belkhodja Omar
Published: December 2019

This paper sought to extend the existing talent management literature through an exploratory investigation of talent loss resulting from the possible departure of talented employees from the procurement function of hotels. Through a multiple case study of five organizations in the hospitality industry, we found that the departure of talented procurement managers disrupts supply chain operations and leads to a loss of valuable explicit, tacit, and relational knowledge. Procurement managers were found to hold critical skills and knowledge that are essential for the case organizations. Hence, more proactive management strategies were adopted. Managers seeking to minimize the negative impact of talent loss in the procurement function would be well-advised to treat this procurement function as a strategic one and to adopt proactive and documented management strategies. Firms should be aware of the type of important knowledge and of the importance of aligning their strategies with such knowledge. To retain relational knowledge in case of talent loss, strategies should be designed to reduce the firm’s reliance on personal contacts and emotion-based trust in supplier relationships. We concluded the paper with implications for future research and managerial practice for managing talent loss, with an emphasis on sustainability in the hospitality industry.
A Machine Learning Portfolio Allocation System for IPOs in Korean Markets Using GA-Rough Set Theory
Authors: Kim Jiwoo , Shin Sanghun , Lee Hee Soo , Oh Kyong Joo
Published: December 2019

An initial public offering (IPO) is a type of public offering in which a company’s shares are sold to institutional and individual investors. While the majority of studies on IPOs have focused on the efficiency of raising capital and price adequacy in IPOs, studies on portfolio allocation strategies for IPO stocks are relatively scarce. This paper develops a machine learning investment strategy for IPO stocks based on rough set theory and a genetic algorithm (GA-rough set theory). To reduce issues of information asymmetry, we use nonfinancial data that are publicly available to individual and institutional investors in the IPO process. Based on the rule sets generated from the training sets, we conduct 120 tests with various conditions involving the target days and the partition of the training and testing sets, and we find excess returns of the constructed portfolios compared to the benchmark portfolios. Investors in IPO stocks can formulate more efficient investment strategies using our system. In this sense, the system developed in this paper contributes to the efficiency of financial markets and helps achieve sustained economic growth.
Why Students Have Conflicts in Peer Assessment? An Empirical Study of an Online Peer Assessment Community
Authors: Wang Yanqing , Zong Zheng
Published: December 2019

This study highlights the issues in the process of peer assessment in an online environment. As an interactive learning platform, peer assessment will likely lead to conflicts among students, which will hinder the sustainability of peer assessment learning environments. It is still unclear about the particular factors that influence and cause the behavioral conflicts which arise within learning groups and learning environments. To overcome this issue, the current study explores why peer assessment could trigger conflict over a student’s task. The results of a negative binomial regression model with user fixed effects indicate that student’s knowledge self-efficacy, cognitive diversity of general knowledge, and network density have a positive impact on task conflict. Interactive experience and cognition diversity of specific knowledge are not powerful motivations for task conflict in the peer assessment. The findings of this study may be helpful for educators in understanding why students have task conflict in a specific learning environment.
A Four-Dimensional Evaluation of the Urban Comprehensive Carrying Capacity of the Yangtze River Delta, China
Authors: Shao Qinglong , Li Jiaying , Zhao Lingling
Published: December 2019

The evaluation of urban comprehensive carrying capacity (UCC) is of great importance in maintaining urban socio-economic sustainable development. However, UCC is still in its nascent period with limited applications and a lack of credible assessment methods. To enrich this field, this study constructed an objective scientific index to evaluate the UCC of the Yangtze River Delta (YRD) region from a four-dimensional perspective, examining economy, society, environmental, and transportation subsystems. The improved entropy method based on 18 weighted indicators was used to measure the UCC of the 26 cities of the YRD for the period 1990–2018. Results indicate that nine cities were overloaded in 2018, meaning comprehensive carrying capacity demand exceeds supply, and the other seventeen were in loadable condition, meaning such demand did not exceed supply; the social and transportation subsystems are the most important because their index weights and UCC levels are higher than the other two subsystems; the overall UCC for all cities in the YRD is at a medium level, and there are large disparities between the various cities. The empirical results imply that the government should take effective measures to improve UCC in these cities, combining cities’ specific advantages to enhance the efficiency of resource allocation and utilization and improve carrying capacities, and changing the mode of economic development. Based on UCC levels, it is also important to improve environmental conditions and coordination and integration in the development of urbanization. Policy implications on improving UCC have been highlighted in the final section.
Environmental Impact of Freight Signal Priority with Connected Trucks
Authors: Park Sangjun , Ahn Kyoungho , Rakha Hesham A.
Published: December 2019

Traffic signal priority is an operational technique employed for the smooth progression of a specific type of vehicle at signalized intersections. Transit signal priority is the most common type of traffic signal priority, and it has been researched extensively. Conversely, the impacts of freight signal priority (FSP) has not been widely investigated. Hence, this study aims to evaluate the energy and environmental impacts of FSP under connected vehicle environment by utilizing a simulation testbed developed for the multi-modal intelligent transportation signal system. The simulation platform consists of VISSIM microscopic traffic simulation software, a signal request messages distributor program, an RSE module, and an Econolite ASC/3 traffic controller emulator. The MOVES model was employed to estimate the vehicle fuel consumption and emissions. The simulation study revealed that the implementation of FSP significantly reduced the fuel consumption and emissions of connected trucks and general passenger cars; the network-wide fuel consumption was reduced by 11.8%, and the CO2, HC, CO, and NOX emissions by 11.8%, 28.3%, 24.8%, and 25.9%, respectively. However, the fuel consumption and emissions of the side-street vehicles increased substantially due to the reduced green signal times on the side streets, especially in the high truck composition scenario.
Estimating the Leaf Area Index of Winter Wheat Based on Unmanned Aerial Vehicle RGB-Image Parameters
Authors: Hasan Umut , Sawut Mamat , Chen Shuisen
Published: December 2019

The leaf area index (LAI) is not only an important parameter for monitoring crop growth, but also an important input parameter for crop yield prediction models and hydrological and climatic models. Several studies have recently been conducted to estimate crop LAI using unmanned aerial vehicle (UAV) multispectral and hyperspectral data. However, there are few studies on estimating the LAI of winter wheat using unmanned aerial vehicle (UAV) RGB images. In this study, we estimated the LAI of winter wheat at the jointing stage on simple farmland in Xinjiang, China, using parameters derived from UAV RGB images. According to gray correlation analysis, UAV RGB-image parameters such as the Visible Atmospherically Resistant Index (VARI), the Red Green Blue Vegetation Index (RGBVI), the Digital Number (DN) of Blue Channel (B) and the Green Leaf Algorithm (GLA) were selected to develop models for estimating the LAI of winter wheat. The results showed that it is feasible to use UAV RGB images for inverting and mapping the LAI of winter wheat at the jointing stage on the field scale, and the partial least squares regression (PLSR) model based on the VARI, RGBVI, B and GLA had the best prediction accuracy (R2 = 0.776, root mean square error (RMSE) = 0.468, residual prediction deviation (RPD) = 1.838) among all the regression models. To conclude, UAV RGB images not only have great potential in estimating the LAI of winter wheat, but also can provide more reliable and accurate data for precision agriculture management.
A Study of Integrative Bargaining Model with Argumentation-Based Negotiation
Authors: Park Jinsoo , Rahman Hamirahanim Abdul , Suh Jihae , Hussin Hazami
Published: December 2019

E-commerce is increasingly competitive and there is a constant need for new approaches and technology to facilitate exchange. Emerging techniques include the use of artificial intelligence (AI). One AI tool that has sparked interest in e-commerce is the automated negotiation agent (negotiation-agent). This study examines such agents, and proposes an offer strategy model of integrative negotiation for a negotiation-agent with a focus on negotiation agent-to-human interaction. More specifically, a new offer strategy was developed based on the integrative bargaining model, which emphasizes the importance of exchanging information among negotiators and multi-issue negotiation that includes package offers to achieve an integrative (win-win) outcome. This study incorporated an argumentation-based negotiation and the negotiation tactic of multiple equivalent simultaneous offers, which was programmed into the negotiation-agent. An experiment was conducted performing 49 negotiation-agent-to-human negotiations over three issues in online purchase tasks to demonstrate the effectiveness of the proposed strategy. Experimental results indicated that the proposed offer strategy with agent negotiation can enhance the persuasiveness of an offer and the performance of negotiation outcome (human counterpart’s perception toward negotiation process, opponent–agent and desire for future negotiation). The findings confirmed the effectiveness of the proposed design and demonstrated an innovative approach to e-commerce transactions.
Towards a Circular Economy: Using Stakeholder Subjectivity to Identify Priorities, Consensus, and Conflict in the Irish EPS/XPS Market
Authors: Black Jeffrey E , Kopke Kathrin , O’Mahony Cathal
Published: December 2019

In European Seas, plastic litter from fishing activities, river transport, and poor waste management is one of the fastest growing threats to the health of the marine environment. Extruded polystyrene (XPS) and expanded polystyrene (EPS), specifically, have become some of the most prominent types of marine litter found around Europe’s coastlines. To combat this problem, the European Commission has ratified a series of regulations and policies, including the Single-Use Plastics Directive and the EU Action Plan for the Circular Economy. However, in order to ensure that the benefits of such regulations and policies are realized at a scale that can adequately address the scope of the problem, decision-makers will need to integrate the opinions, values, and priorities of relevant stakeholders who operate across the EPS/XPS product lifecycle. In this study, we apply a 35-statement Q-methodology to identify the priorities of stakeholders as they relate to the Irish EPS/XPS market and the wider societal transition to a circular economy. Based on the responses of nineteen individuals representing industry, policy-makers, and community leaders, we identified three distinct perspectives: System Overhaul; Incremental Upgrade; and Market Innovation. The results demonstrate that the type and format of policy interventions linked to Ireland’s EPS/XPS circular economy are heavily contested, which presents significant challenges for driving the debate forward. These results provide valuable information on viewpoints that can be used by different stakeholders at national and EU levels to address areas of conflict, ultimately fostering the development of more effective, broadly supported co-developed policies.
Trust in Sharing Economy Business Models from the Perspective of Customers in Szczecin, Poland
Authors: Wagner Natalia , Strulak-Wójcikiewicz Roma , Landowska Anna
Published: December 2019

The concept of a sharing economy, as part of a wider collaborative economy concept, is among the most important economic and technological trends that will influence socioeconomic development in the future. Interest in using the opportunities offered by sharing platforms is increasing; hence, the subject is a current and important issue. Confidence in technology, service providers and application providers is a key issue when making decisions about using such solutions. The aim of the paper is to examine the level of trust in sharing economy business models considering two groups of factors, trust in people and in technology, among several demographic groups. The paper has an empirical character and the results are provided on the basis of a survey conducted in Szczecin, Poland, with 403 respondents who are current and potential users of sharing platforms. The obtained results show that platform management requires more attention focused on building mutual trust networks among participants rather than strengthening the confidence in using the technology.
Residents’ Negative Perceptions towards Tourism, Loyalty and Happiness: The Case of Fuengirola, Spain
Authors: Sánchez-Teba Eva María , Benítez-Márquez María Dolores , Romero-Navas Teresa
Published: December 2019

Current studies suggest focusing on the study of residents’ negative perceptions towards tourism. This study estimates a confirmatory model of structural equations based on variance. The negative perceptions of residents living in Fuengirola (Spain), divided into three dimensions (negative economic impact, negative social impact, and negative environmental impact), according to social exchange theory, and, also the residents’ loyalty to their city are considered to be predictors of residents’ happiness. We have proposed a construct of residents’ loyalty to their tourism destination residence as a novelty, being composed of two indicators. The model has been computed based on partial least squares-structural equation modeling. The following hypotheses have been tested: (a) negative perceptions have positive effects on each other; (b) negative perceptions have a negative effect on happiness; and, (c) residents’ loyalty has a positive effect on happiness. The hypotheses were not rejected. Moreover, the loyalty of the residents has the highest direct positive impact, while the negative impacts have weak negative effects, direct and indirect, on the happiness of the residents. The result of the positive relationship between place loyalty and happiness referred by those persons who perceive their living place (neighborhood) as prestigious is consistent with our findings, which is, an increase of loyalty was found to be associated with an increase in happiness.
Design a Stratiform Metamaterial with Precise Optical Property
Authors: Jen Yi-Jun , Liu Wei-Chin
Published: December 2019

In this work, a stratiform metamaterial is arranged as multiple periods of metal-dielectric symmetrical film stack to provide precise equivalent refractive index and admittance. There are multiple solutions of equivalent refractive index retrieved from the characteristic matrix of the film stack. The correct refractive index is derived by connecting different branches of solution at different ranges of wavelength or thickness of the dielectric layer. The refractive index of an Ag-TiO2 five-layered symmetrical film stack shown in previous work is demonstrated to be positive real instead of negative real. The associated type I iso-frequency curve supports negative refraction. In order to extend the operating wavelength of type I metamaterial, the number of the metal-dielectric symmetrical film stack is increased to reduce the thickness of the dielectric film to approach subwavelength requirement.
Complex Asymptotics in λ for the Gegenbauer Functions

C
λ
α

(
z
)

and

D
λ
α

(
z
)

with z ∈ (−1, 1)
Authors: Durand Loyal
Published: December 2019

We derive asymptotic results for the Gegenbauer functions C λ α ( z ) and D λ α ( z ) of the first and second kind for complex z and the degree | λ | → ∞ , apply the results to the case z ∈ ( − 1 , 1 ) , and establish the connection of these results to asymptotic Bessel-function approximations of the functions for z → ± 1 .
High Diversity of Microcystin Chemotypes within a Summer Bloom of the Cyanobacterium Microcystis botrys
Authors: Johansson Emma , Legrand Catherine , Björnerås Caroline , Godhe Anna , Mazur-Marzec Hanna , Säll Torbjörn , Rengefors Karin
Published: December 2019

The fresh-water cyanobacterium Microcystis is known to form blooms world-wide, and is often responsible for the production of microcystins found in lake water. Microcystins are non-ribosomal peptides with toxic effects, e.g. on vertebrates, but their function remains largely unresolved. Moreover, not all strains produce microcystins, and many different microcystin variants have been described. Here we explored the diversity of microcystin variants within Microcystis botrys, a common bloom-former in Sweden. We isolated a total of 130 strains through the duration of a bloom in eutrophic Lake Vomb, and analyzed their microcystin profiles with tandem mass spectrometry (LC-MS/MS). We found that microcystin producing (28.5%) and non-producing (71.5%) M. botrys strains, co-existed throughout the bloom. However, microcystin producing strains were more prevalent towards the end of the sampling period. Overall, 26 unique M. botrys chemotypes were identified, and while some chemotypes re-occurred, others were found only once. The M. botrys chemotypes showed considerable variation both in terms of number of microcystin variants, as well as in what combinations the variants occurred. To our knowledge, this is the first report on microcystin chemotype variation and dynamics in M. botrys. In addition, our study verifies the co-existence of microcystin and non-microcystin producing strains, and we propose that environmental conditions may be implicated in determining their composition.
Detection of a New Genetic Cluster of Influenza D Virus in Italian Cattle
Authors: Chiapponi Chiara , Faccini Silvia , Fusaro Alice , Moreno Ana , Prosperi Alice , Merenda Marianna , Baioni Laura , Gabbi Valentina , Rosignoli Carlo , Alborali Giovanni L. , Cavicchio Lara , Monne Isabella , Torreggiani Camilla , Luppi Andrea , Foni Emanuela
Published: December 2019

Influenza D virus (IDV) has been increasingly reported all over the world. Cattle are considered the major viral reservoir. Based on the hemagglutinin-esterase (HEF) gene, three main genetic and antigenic clusters have been identified: D/OK distributed worldwide, D/660 detected only in the USA and D/Japan in Japan. Up to 2017, all the Italian IDV isolates belonged to the D/OK genetic cluster. From January 2018 to May 2019, we performed virological surveillance for IDV from respiratory outbreaks in 725 bovine farms in Northern Italy by RT-PCR. Seventy-four farms were positive for IDV. A full or partial genome sequence was obtained from 29 samples. Unexpectedly, a phylogenetic analysis of the HEF gene showed the presence of 12 strains belonging to the D/660 cluster, previously unreported in Europe. The earliest D/660 strain was collected in March 2018 from cattle imported from France. Moreover, we detected one viral strain with a reassortant genetic pattern (PB2, PB1, P42, HEF and NP segments in the D/660 cluster, whilst P3 and NS segments in the D/OK cluster). These results confirm the circulation of IDV in the Italian cattle population and highlight the need to monitor the development of the spreading of this influenza virus in order to get more information about the epidemiology and the ecology of IDV viruses.
Viruses Infecting the Plant Pathogenic Fungus Rhizoctonia solani
Authors: Abdoulaye Assane Hamidou , Foda Mohamed Frahat , Kotta-Loizou Ioly
Published: December 2019

The cosmopolitan fungus Rhizoctonia solani has a wide host range and is the causal agent of numerous crop diseases, leading to significant economic losses. To date, no cultivars showing complete resistance to R. solani have been identified and it is imperative to develop a strategy to control the spread of the disease. Fungal viruses, or mycoviruses, are widespread in all major groups of fungi and next-generation sequencing (NGS) is currently the most efficient approach for their identification. An increasing number of novel mycoviruses are being reported, including double-stranded (ds) RNA, circular single-stranded (ss) DNA, negative sense (−)ssRNA, and positive sense (+)ssRNA viruses. The majority of mycovirus infections are cryptic with no obvious symptoms on the hosts; however, some mycoviruses may alter fungal host pathogenicity resulting in hypervirulence or hypovirulence and are therefore potential biological control agents that could be used to combat fungal diseases. R. solani harbors a range of dsRNA and ssRNA viruses, either belonging to established families, such as Endornaviridae, Tymoviridae, Partitiviridae, and Narnaviridae, or unclassified, and some of them have been associated with hypervirulence or hypovirulence. Here we discuss in depth the molecular features of known viruses infecting R. solani and their potential as biological control agents.
Mycobacterium avium Subspecies paratuberculosis DNA and Antibodies in Dairy Goat Colostrum and Milk
Authors: Lievaart-Peterson Karianne , Luttikholt Saskia , Gonggrijp Maaike , Ruuls Robin , Ravesloot Lars , Koets Ad P.
Published: December 2019

Mycobacterium avium subspecies paratuberculosis (MAP) is endemic in the Dutch dairy goat population causing economic loss, and negatively influencing welfare. Moreover, there are concerns about a potential zoonotic risk. Therefore the industry’s objectives are to decrease MAP prevalence, limit economic losses as well as reduce the concentration of MAP in (bulk) milk. To diminish within-farm spread of infection, vaccination, age dependent group housing with separation of newborns from adults, as well as rearing on artificial or treated colostrum and milk replacers are implemented. However, the importance of MAP contaminated colostrum and milk as a route of infection in dairy goat herds is unknown. Therefore the aim of this study was to detect the presence of MAP DNA in colostrum and milk from dairy goats in infected herds. A convenience sample of 120 colostrum samples and 202 milk samples from MAP infected dairy goat herds were tested by IS900 real-time Polymerase Chain Reaction (PCR) for MAP DNA. Furthermore, 22 colostrum samples and 27 post mortem milk samples of goats with clinical signs consistent with paratuberculosis from known infected herds were tested. The majority of samples were from goats vaccinated against MAP. Positive or doubtful PCR results were obtained in none of the 120 and two of the 22 colostrum samples, and in eight of the 202 and four of the 27 milk samples Negative PCR results were obtained in the remaining 140 (99%) colostrum samples and 217 (95%) milk samples.
Exploring the Risk Posed by Animals with an Inconclusive Reaction to the Bovine Tuberculosis Skin Test in England and Wales
Authors: May Elizabeth , Prosser Alison , Downs Sara H. , Brunton Lucy A.
Published: December 2019

The single intradermal comparative cervical tuberculin (SICCT) test is the primary test for ante-mortem diagnosis of bovine tuberculosis (TB) in England and Wales. When an animal is first classified as an inconclusive reactor (IR) using this test, it is not subject to compulsory slaughter, but it must be isolated from the rest of the herd. To understand the risk posed by these animals, a case-control study was conducted to measure the association between IR status of animals and the odds of them becoming a reactor to the SICCT at a subsequent test. The study included all animals from herds in which only IR animals were found at the first whole herd test in 2012 and used data from subsequent tests up until the end of 2016. Separate mixed-effects logistic regression models were developed to examine the relationship between IR status and subsequent reactor status for each risk area of England and for Wales, adjusting for other explanatory variables. The odds of an animal becoming a subsequent reactor during the study period were greater for IR animals than for negative animals in the high-risk area (odds ratio (OR): 6.85 (5.98–7.86)) and edge area (OR: 8.79 (5.92–13.04)) of England and in Wales (OR: 6.87 (5.75–8.22)). In the low-risk area of England, the odds were 23 times greater, although the confidence interval around this estimate was larger due to the smaller sample size (11–48, p < 0.001). These findings support the need to explore differential controls for IR animals to reduce the spread of TB, and they highlight the importance of area-specific policies.
Efficient Degradation of Mordant Blue 9 Using the Fenton-Activated Persulfate System
Authors: Pervez Md. Nahid , Telegin Felix Y. , Cai Yingjie , Xia Dongsheng , Zarra Tiziano , Naddeo Vincenzo
Published: December 2019

In this study, a Fenton-activated persulfate (Fe2+/PS) system was introduced for the efficient degradation of Mordant Blue 9 (MB 9) as a textile dye in an aqueous solution. Results showed that the degradation of MB 9 was markedly influenced by operational parameters, such as initial pH, PS concentration, Fe2+ concentration, and initial dye concentration. Optimal reaction conditions were then determined. Inorganic anions, such as Cl− and HCO3−, enhanced the degradation efficiency of MB 9 under optimal conditions. Addition of HCO3− reduced the degradation performance of MB 9, whereas the addition of Cl− increased the degradation percentage of MB 9. In addition, quenching experiments were conducted using methanol and tert-butyl alcohol as scavengers, and methanol was identified as an effective scavenger. Thus, the degradation of MB 9 was attributed to S O 4 • − and •OH radicals. The degradation and mineralization efficiency of MB 9 was significantly reduced using the conventional Fenton process i.e., Fe2+/ hydrogen peroxide (HP) because of the formation of a Fe complex during degradation. Meanwhile, the Fe2+/persulfate (PS) system improved the degradation and mineralization performance.
A Data-Driven Probabilistic Rainfall-Inundation Model for Flash-Flood Warnings
Authors: Pan Tsung-Yi , Lin Hsuan-Tien , Liao Hao-Yu
Published: December 2019

Owing to their short duration and high intensity, flash floods are among the most devastating natural disasters in metropolises. The existing warning tools—flood potential maps and two-dimensional numerical models—are disadvantaged by time-consuming computation and complex model calibration. This study develops a data-driven, probabilistic rainfall-inundation model for flash-flood warnings. Applying a modified support vector machine (SVM) to limited flood information, the model provides probabilistic outputs, which are superior to the Boolean functions of the traditional rainfall-flood threshold method. The probabilistic SVM-based model is based on a data preprocessing framework that identifies the expected durations of hazardous rainfalls via rainfall pattern analysis, ensuring satisfactory training data, and optimal rainfall thresholds for validating the input/output data. The proposed model was implemented in 12 flash-flooded districts of the Xindian River. It was found that (1) hydrological rainfall pattern analysis improves the hazardous event identification (used for configuring the input layer of the SVM); (2) brief hazardous events are more critical than longer-lasting events; and (3) the SVM model exports the probability of flash flooding 1 to 3 h in advance.
Changes in the Risk of Extreme Climate Events over East Asia at Different Global Warming Levels
Authors: Zhang Jintao , Wang Fang
Published: December 2019

Limiting the global temperature increase to a level that would prevent “dangerous anthropogenic interference with the climate system” is the focus of intergovernmental climate negotiations, and the cost-benefit analysis to determine this level requires an understanding of how the risk associated with climate extremes varies with different warming levels. We examine daily extreme temperature and precipitation variances with continuous global warming using a non-stationary extreme value statistical model based on the Coupled Model Intercomparison Project Phase 5 (CMIP5). Our results show the probability of extreme warm and heavy precipitation events over East Asia (EA) will increase, while that of cold extremes over EA will decrease as global warming increases. A present-day 1-in-20-year heavy precipitation extreme in EA is projected to increase to 1.3, 1.6, 2.5, and 3.4 times more frequently of the current climatology, at the global mean warming levels of 1.5 °C, 2 °C, 3 °C, and 4 °C above the preindustrial era, respectively. Moreover, the relative changes in probability are larger for rarer events. These results contribute to an improved understanding of the future risk associated with climate extremes, which helps scientists create mitigation measures for global warming and facilitates policy-making.
Hydraulic Properties in Different Soil Architectures of a Small Agricultural Watershed: Implications for Runoff Generation
Authors: Dai Cuiting , Wang Tianwei , Zhou Yiwen , Deng Jun , Li Zhaoxia
Published: December 2019

Soil architecture exerts an important control on soil hydraulic properties and hydrological responses. However, the knowledge of hydraulic properties related to soil architecture is limited. The objective of this study was to investigate the influences of soil architecture on soil physical and hydraulic properties and explore their implications for runoff generation in a small agricultural watershed in the Three Gorges Reservoir Area (TGRA) of southern China. Six types of soil architecture were selected, including shallow loam sandy soil in grassland (SLSG) and shallow loam sandy soil in cropland (SLSC) on the shoulder; shallow sandy loam in grassland (SSLG) and shallow sandy loam in cropland (SSLC) on the backslope; and deep sandy loam in grassland (DSLG) and deep sandy loam in cropland (DSLC) on the footslope. The results showed that saturated hydraulic conductivity (Ksat) was significantly higher in shallow loamy sand soil under grasslands (8.57 cm h−1) than under croplands (7.39 cm h−1) at the topsoil layer. Total porosity was highest for DSLC and lowest for SSLG, averaged across all depths. The proportion of macropores under SLSG was increased by 60% compared with under DSLC, which potentially enhanced water infiltration and decreased surface runoff. The landscape location effect showed that at the shoulder, Ksat values were 20% and 47% higher than values at the backslope and footslope, respectively. It was inferred by comparing Ksat values with 30 min maximum rainfall intensity at the watershed, that surface runoff would be generated in SSLC, DSLG, and DSLC sites by storms, but that no overland flow is generated in both sites at the shoulder and SSLG. The significantly higher Ksat under grasslands in comparison to croplands at the backslope indicated that planting grasses would increase infiltration capacity and mitigate runoff generation during storm events. The findings demonstrated that croplands in footslope positions might be hydrologically sensitive areas in this small agricultural watershed.