bluuebunny/crossref_metadata_2025 huggingface dataset:
Radiometric Performance of the TerraSAR-X Mission over More Than Ten Years of Operation
Authors: Schwerdt Marco , Schmidt Kersten , Klenk Patrick , Tous Ramon Núria , Rudolf Daniel , Raab Sebastian , Weidenhaupt Klaus , Reimann Jens , Zink Manfred
Published: May 2018

The TerraSAR-X mission, based on two satellites, has produced SAR data products of high quality for a number of scientific and commercial applications for more than ten years. To guarantee the stability and the reliability of these highly accurate SAR data products, both systems were first accurately calibrated during their respective commissioning phases and have been permanently monitored since then. Based on a short description of the methods applied, this paper focuses on the radiometric performance including the gain and phase properties of the transmit/receiver modules, the antenna pattern checked by evaluating scenes acquired over uniformly distributed targets and the radiometric stability derived from permanently deployed point targets. The outcome demonstrates the remarkable performance of both systems since their respective launch.
Metrology Assessment of the Accuracy of Precipitable Water Vapor Estimates from GPS Data Acquisition in Tropical Areas: The Tahiti Case
Authors: Zhang Fangzhao , Barriot Jean-Pierre , Xu Guochang , Yeh Ta-Kang
Published: May 2018

High precision Global Positioning System (GPS) receivers, with the advantages of all-weather work and low cost, are now widely used to routinely monitor precipitable water (PW) vapor. They are so successful that the progressive phasing out of the costly and sparse in situ radio soundings (RS) is now a certainty. Nevertheless, the sub-daily to annual monitoring of high levels of the PW by GPS receivers in the tropics and the equatorial area still needs to be asserted in terms of metrology accuracy. This is the subject of this paper, which focuses on a tropical site located in mid-ocean (Tahiti). The metrology assessment was divided into two steps. Firstly, a GPS internal assessment, with an in-house processing based on the Bernese GNSS Software Version 5.2 and a comparison with the Center for Orbit Determination in Europe (CODE) products. Secondly, an external assessment, with a comparison with RS PW estimates. In contrast with previous works that only used PW estimates from the Integrated Global Radiosonde Archive (IGRA) website, we estimated the RS PW from the balloon raw data. This is especially important in tropical areas, where IGRA estimates only consider balloon measurements taken below approximately 5500 m. We show that, in our case, this threshold is one of the main sources of bias between GPS and RS estimates, and that the formula used to translate the GPS zenith wet delays (ZWD) to PW estimates also needs to be revisited for high level water vapor contents in the atmosphere.
Unsupervised Classification Algorithm for Early Weed Detection in Row-Crops by Combining Spatial and Spectral Information
Authors: Louargant Marine , Jones Gawain , Faroux Romain , Paoli Jean-Noël , Maillot Thibault , Gée Christelle , Villette Sylvain
Published: May 2018

In agriculture, reducing herbicide use is a challenge to reduce health and environmental risks while maintaining production yield and quality. Site-specific weed management is a promising way to reach this objective but requires efficient weed detection methods. In this paper, an automatic image processing has been developed to discriminate between crop and weed pixels combining spatial and spectral information extracted from four-band multispectral images. Image data was captured at 3 m above ground, with a camera (multiSPEC 4C, AIRINOV, Paris) mounted on a pole kept manually. For each image, the field of view was approximately 4 m × 3 m and the resolution was 6 mm/pix. The row crop arrangement was first used to discriminate between some crop and weed pixels depending on their location inside or outside of crop rows. Then, these pixels were used to automatically build the training dataset concerning the multispectral features of crop and weed pixel classes. For each image, a specific training dataset was used by a supervised classifier (Support Vector Machine) to classify pixels that cannot be correctly discriminated using only the initial spatial approach. Finally, inter-row pixels were classified as weed and in-row pixels were classified as crop or weed depending on their spectral characteristics. The method was assessed on 14 images captured on maize and sugar beet fields. The contribution of the spatial, spectral and combined information was studied with respect to the classification quality. Our results show the better ability of the spatial and spectral combination algorithm to detect weeds between and within crop rows. They demonstrate the improvement of the weed detection rate and the improvement of its robustness. On all images, the mean value of the weed detection rate was 89% for spatial and spectral combination method, 79% for spatial method, and 75% for spectral method. Moreover, our work shows that the plant in-line sowing can be used to design an automatic image processing and classification algorithm to detect weed without requiring any manual data selection and labelling. Since the method required crop row identification, the method is suitable for wide-row crops and high spatial resolution images (at least 6 mm/pix).
Long-Term Validation of TerraSAR-X and TanDEM-X Orbit Solutions with Laser and Radar Measurements
Authors: Hackel Stefan , Gisinger Christoph , Balss Ulrich , Wermuth Martin , Montenbruck Oliver
Published: May 2018

Precise orbit determination solutions for the two spacecrafts TerraSAR-X (TSX) and TanDEM-X (TDX) are operationally computed at the German Space Operations Center (GSOC/DLR). This publication makes use of 6 years of TSX and TDX orbit solutions for a detailed orbit validation. The validation compares the standard orbit products with newly determined enhanced orbit solutions, which additionally consider GPS ambiguity fixing and utilize a macro model for modeling non-gravitational forces. The technique of satellite laser ranging (SLR) serves as a key measure for validating the derived orbit solutions. In addition, the synthetic aperture radar (SAR) instruments on-board both spacecrafts are for the first time employed for orbit validation. Both the microwave instrument and the optical laser approach are compared and assessed. The average SLR residuals, obtained from the TSX and TDX enhanced orbit solutions within the analysis period, are at 1.6 ± 11.4 mm ( 1 σ ) and 1.2 ± 12.5 mm, respectively. Compared to the standard orbit products, this is an improvement of 33 % in standard deviation. The corresponding radar range biases are in the same order and amount to − 3.5 ± 12.5 mm and 4.5 ± 14.9 mm. Along with the millimeter level position offsets in radial, along-track and cross-track inferred from the SLR data on a monthly basis, the results confirm the advantage of the enhanced orbit solutions over the standard orbit products.
A Combined Gravity Compensation Method for INS Using the Simplified Gravity Model and Gravity Database
Authors: Zhou Xiao , Yang Gongliu , Wang Jing , Wen Zeyang
Published: May 2018

In recent decades, gravity compensation has become an important way to reduce the position error of an inertial navigation system (INS), especially for a high-precision INS, because of the extensive application of high precision inertial sensors (accelerometers and gyros). This paper first deducts the INS’s solution error considering gravity disturbance and simulates the results. Meanwhile, this paper proposes a combined gravity compensation method using a simplified gravity model and gravity database. This new combined method consists of two steps all together. Step 1 subtracts the normal gravity using a simplified gravity model. Step 2 first obtains the gravity disturbance on the trajectory of the carrier with the help of ELM training based on the measured gravity data (provided by Institute of Geodesy and Geophysics; Chinese Academy of sciences), and then compensates it into the error equations of the INS, considering the gravity disturbance, to further improve the navigation accuracy. The effectiveness and feasibility of this new gravity compensation method for the INS are verified through vehicle tests in two different regions; one is in flat terrain with mild gravity variation and the other is in complex terrain with fierce gravity variation. During 2 h vehicle tests, the positioning accuracy of two tests can improve by 20% and 38% respectively, after the gravity is compensated by the proposed method.
A Lightweight Protocol for Secure Video Streaming
Authors: Venčkauskas Algimantas , Morkevicius Nerijus , Bagdonas Kazimieras , Damaševičius Robertas , Maskeliūnas Rytis
Published: May 2018

The Internet of Things (IoT) introduces many new challenges which cannot be solved using traditional cloud and host computing models. A new architecture known as fog computing is emerging to address these technological and security gaps. Traditional security paradigms focused on providing perimeter-based protections and client/server point to point protocols (e.g., Transport Layer Security (TLS)) are no longer the best choices for addressing new security challenges in fog computing end devices, where energy and computational resources are limited. In this paper, we present a lightweight secure streaming protocol for the fog computing “Fog Node-End Device” layer. This protocol is lightweight, connectionless, supports broadcast and multicast operations, and is able to provide data source authentication, data integrity, and confidentiality. The protocol is based on simple and energy efficient cryptographic methods, such as Hash Message Authentication Codes (HMAC) and symmetrical ciphers, and uses modified User Datagram Protocol (UDP) packets to embed authentication data into streaming data. Data redundancy could be added to improve reliability in lossy networks. The experimental results summarized in this paper confirm that the proposed method efficiently uses energy and computational resources and at the same time provides security properties on par with the Datagram TLS (DTLS) standard.
A Novel DFT-Based DOA Estimation by a Virtual Array Extension Using Simple Multiplications for FMCW Radar
Authors: Kim Bongseok , Kim Sangdong , Lee Jonghun
Published: May 2018

We propose a novel discrete Fourier transform (DFT)-based direction of arrival (DOA) estimation by a virtual array extension using simple multiplications for frequency modulated continuous wave (FMCW) radar. DFT-based DOA estimation is usually employed in radar systems because it provides the advantage of low complexity for real-time signal processing. In order to enhance the resolution of DOA estimation or to decrease the missing detection probability, it is essential to have a considerable number of channel signals. However, due to constraints of space and cost, it is not easy to increase the number of channel signals. In order to address this issue, we increase the number of effective channel signals by generating virtual channel signals using simple multiplications of the given channel signals. The increase in channel signals allows the proposed scheme to detect DOA more accurately than the conventional scheme while using the same number of channel signals. Simulation results show that the proposed scheme achieves improved DOA estimation compared to the conventional DFT-based method. Furthermore, the effectiveness of the proposed scheme in a practical environment is verified through the experiment.
Hyperspectral Imaging and Spectrometry-Derived Spectral Features for Bitter Pit Detection in Storage Apples
Authors: Jarolmasjed Sanaz , Khot Lav , Sankaran Sindhuja
Published: May 2018

Bitter pit is one of the most important disorders in apples. Some of the fresh market apple varieties are susceptible to bitter pit disorder. In this study, visible–near-infrared spectrometry-based reflectance spectral data (350–2500 nm) were acquired from 2014, 2015 and 2016 harvest produce after 63 days of storage at 5 °C. Selected spectral features from 2014 season were used to classify the healthy and bitter pit samples from three years. In addition, these spectral features were also validated using hyperspectral imagery data collected on 2016 harvest produce after storage in a commercial storage facility for 5 months. The hyperspectral images were captured from either sides of apples in the range of 550–1700 nm. These images were analyzed to extract additional set of spectral features that were effective in bitter pit detection. Based on these features, an automated spatial data analysis algorithm was developed to detect bitter pit points. The pit area was extracted, and logistic regression was used to define the categorizing threshold. This method was able to classify the healthy and bitter pit apples with an accuracy of 85%. Finally, hyperspectral imagery derived spectral features were re-evaluated on the visible–near-infrared reflectance data acquired with spectrometer. The pertinent partial least square regression classification accuracies were in the range of 90–100%. Overall, the study identified salient spectral features based on both hyperspectral spectrometry and imaging techniques that can be used to develop a sensing solution to sort the fruit on the packaging lines.
A Facile Electrochemical Sensor Based on PyTS–CNTs for Simultaneous Determination of Cadmium and Lead Ions
Authors: Jiang Ruyuan , Liu Niantao , Gao Sanshuang , Mamat Xamxikamar , Su Yuhong , Wagberg Thomas , Li Yongtao , Hu Xun , Hu Guangzhi
Published: May 2018

A simple and easy method was implemented for the contemporary detection of cadmium (Cd2+) and lead (Pb2+) ions using 1,3,6,8-pyrenetetrasulfonic acid sodium salt-functionalized carbon nanotubes nanocomposites (PyTS–CNTs). The morphology and composition of the obtained PyTS–CNTs were characterized using scanning electron microscopy (SEM), energy dispersive spectrometry (EDS), and X-ray photoelectron spectroscopy (XPS). The experimental results confirmed that the fabricated PyTS–CNTs exhibited good selectivity and sensitivity for metal ion-sensing owing to the insertion of sulfonic acid groups. For Cd2+ and Pb2+, some of the electrochemical sensing parameters were evaluated by varying data such as the PyTS–CNT quantity loaded on the pyrolytic graphite electrode (PGE), pH of the acetate buffer, deposition time, and deposition potential. These parameters were optimized with differential pulse anodic sweeping voltammetry (DPASV). Under the optimal condition, the stripping peak current of the PyTS–CNTs/Nafion/PGE varies linearly with the heavy metal ion concentration, ranging from 1.0 μg L−1 to 90 μg L−1 for Cd2+ and from 1.0 μg L−1 to 110 μg L−1 for Pb2+. The limits of detection were estimated to be approximately 0.8 μg L−1 for Cd2+ and 0.02 μg L−1 for Pb2+. The proposed PyTS–CNTs/Nafion/PGE can be used as a rapid, simple, and controllable electrochemical sensor for the determination of toxic Cd2+ and Pb2+.
An Effective Palmprint Recognition Approach for Visible and Multispectral Sensor Images
Authors: Gumaei Abdu , Sammouda Rachid , Al-Salman Abdul , Alsanad Ahmed
Published: May 2018

Among several palmprint feature extraction methods the HOG-based method is attractive and performs well against changes in illumination and shadowing of palmprint images. However, it still lacks the robustness to extract the palmprint features at different rotation angles. To solve this problem, this paper presents a hybrid feature extraction method, named HOG-SGF that combines the histogram of oriented gradients (HOG) with a steerable Gaussian filter (SGF) to develop an effective palmprint recognition approach. The approach starts by processing all palmprint images by David Zhang’s method to segment only the region of interests. Next, we extracted palmprint features based on the hybrid HOG-SGF feature extraction method. Then, an optimized auto-encoder (AE) was utilized to reduce the dimensionality of the extracted features. Finally, a fast and robust regularized extreme learning machine (RELM) was applied for the classification task. In the evaluation phase of the proposed approach, a number of experiments were conducted on three publicly available palmprint databases, namely MS-PolyU of multispectral palmprint images and CASIA and Tongji of contactless palmprint images. Experimentally, the results reveal that the proposed approach outperforms the existing state-of-the-art approaches even when a small number of training samples are used.
Biomechanical Gait Variable Estimation Using Wearable Sensors after Unilateral Total Knee Arthroplasty
Authors: Youn Ik-Hyun , Youn Jong-Hoon , Zeni Joseph , Knarr Brian
Published: May 2018

Total knee arthroplasty is a common surgical treatment for end-stage osteoarthritis of the knee. The majority of existing studies that have explored the relationship between recovery and gait biomechanics have been conducted in laboratory settings. However, seamless gait parameter monitoring in real-world conditions may provide a better understanding of recovery post-surgery. The purpose of this study was to estimate kinematic and kinetic gait variables using two ankle-worn wearable sensors in individuals after unilateral total knee arthroplasty. Eighteen subjects at least six months post-unilateral total knee arthroplasty participated in this study. Four biomechanical gait variables were measured using an instrumented split-belt treadmill and motion capture systems. Concurrently, eleven inertial gait variables were extracted from two ankle-worn accelerometers. Subsets of the inertial gait variables for each biomechanical gait variable estimation were statistically selected. Then, hierarchical regressions were created to determine the directional contributions of the inertial gait variables for biomechanical gait variable estimations. Selected inertial gait variables significantly predicted trial-averaged biomechanical gait variables. Moreover, strong directionally-aligned relationships were observed. Wearable-based gait monitoring of multiple and sequential kinetic gait variables in daily life could provide a more accurate understanding of the relationships between movement patterns and recovery from total knee arthroplasty.
Non-Linear Resistance Training Program Induced Power and Strength but Not Linear Sprint Velocity and Agility Gains in Young Soccer Players
Authors: Barbalho Matheus , Gentil Paulo , Raiol Rodolfo , Del Vecchio Fabrício , Ramirez-Campillo Rodrigo , Coswig Victor
Published: May 2018

Background: The present study evaluated the effects of resistance training (RT) following a non-linear periodization model in the physical fitness of young soccer athletes. Methods: Young soccer players (n = 23) were allocated into two groups: an RT group (RTG), and the control group (CON). The RTG underwent 15 weeks of non-linear RT periodization in three weekly sessions in addition to their specific soccer training. The CON continued performing the specific soccer training. Before and after the training period, all of the subjects performed one-repetition maximum (RM) tests for speed, agility, and power (vertical and horizontal jump). Results: The RTG obtained significant gains in one-RM tests (before 64.1 ± 5.8 kg, after 79.1 ± 3.3 kg) and power (vertical jump (before 56 ± 2.7 cm, after 61.3 ± 1.7 cm) and horizontal jump (before 184.5 ± 5.5 cm, after 213.6 ± 3.2 cm)). In contrast, the CON group presented a non-significant increase in one-RM tests and horizontal jump, and a significant reduction in vertical jump (before 55.4 ± 2.2 cm, after 51.3 ± 1.5 cm). Neither group presented significant gains in speed (CON: p = 0.27; RTG: p = 0.72) and agility (CON: p = 0.19; RTG: p = 0.58). Conclusion: Our data suggest that non-linear RT should be inserted into the routine of young soccer athletes for improving strength and power without impairing speed and agility.
Consumers’ Willingness to Pay for Net-Zero Energy Apartment in South Korea
Authors: Kim Ju-Hee , Kim Hyo-Jin , Yoo Seung-Hoon
Published: May 2018

In South Korea, buildings account for more than 25% of the nation’s total greenhouse gas emissions. Therefore, the government aims to make zero energy buildings mandatory from 2025, onward. For the housing sector, the government has recently built and operated a pilot net-zero energy apartment (NZEA) and plans to expand it to several cities. This article attempts to obtain information about the consumers’ willingness to pay (WTP) for the NZEAs. To this end, households’ additional WTP for the NZEAs over a conventional apartment was investigated, applying the contingent valuation (CV) approach. The data on the WTP were gathered from a CV survey of 1000 interviewees and analyzed, employing a dichotomous choice question and the spike model, respectively. The mean value of the additional WTP is obtained as KRW 0.46 million (USD 424) per m2, which is statistically significant. This value corresponds to 17.0% of the conventional apartment price per m2 (KRW 2.76 million, USD 2436). It can be concluded that the households in South Korea place a significant value on a NZEA over a conventional apartment. In addition, we have investigated the characteristics of consumers which affect the probability that consumers accept additional payment of an amount of money for NZEA over a conventional apartment, finding that higher income earners, higher education, and male consumers have a higher probability.
The Cultural Value of Protected Areas as Models of Sustainable Development
Authors: Saviano Marialuisa , Di Nauta Primiano , Montella Marta , Sciarelli Fabiana
Published: May 2018

In recognition of the urgent need to drive the transition to truly sustainable development, it is our belief that the divisions still distinguishing economic, social and environmental dimensions of human activities can impede the creation of conditions for sustainable development. Our paper investigates reference models for integrating such economic, social and environmental perspectives of sustainable development, proposing a systems approach. We take into consideration protected areas as models of sustainable development by means of a case study, discussing (1) the need to integrate the economic, social and environmental dimensions of human activity; and (2) opportunities offered by protected areas as reference models for promoting sustainable development in the wider surrounding territory. Findings highlight the cultural value of protected areas as models of sustainable development leveraging territorial governance on the basis of a systems approach.
Risks of Developing Concentrated Rural Settlement after the Wenchuan Earthquake in China
Authors: Peng Yi , Li Xuewen , Huang Li , Jiang Shuli , Xu Yelin , Lai Yani
Published: May 2018

Concentrated rural settlement (CRS) reconstruction was promoted as a sustainable rural reconstruction way after the Wenchuan earthquake in China. Despite the various benefits of CRS, haphazard CRS reconstruction presents risks to future sustainable development. However, such risks have been rarely investigated. Thus, this study examines the risk factors with eight CRS reconstruction cases after the Wenchuan earthquake. The existence and interactions of economic, social, environmental, and disaster relief risks are observed after reconstruction. A conceptual model is proposed for systematically interpreting the risks. Results obtained can help the local government judiciously consider the risk factors in order to achieve sustainable development when initiating rapid reconstruction.
Integrated Harvest and Distribution Scheduling with Time Windows of Perishable Agri-Products in One-Belt and One-Road Context
Authors: Jiang Yiping , Chen Liangqi , Fang Yan
Published: May 2018

The unique characteristics of perishable agri-products are a short lifespan and rapid quality deterioration. This establishes the need to significantly reduce the time from harvest to distribution. These features require reducing the processing time from harvest to distribution to being as short as possible. In this study, we focus on an integrated perishable agri-products scheduling problem that combines harvest and distribution simultaneously, with the purpose of reducing processing time and quality decay. We propose this problem as a mixed integer nonlinear programming model (MINLP) to optimize the harvest time and the vehicle routing to consumers, and this MINIP is formulated as a vehicle routing problem with time windows (VRPTW). We introduce a big M method to transform the nonlinear model into a linear model, then apply CPLEX to solve the transformed model. Numerical experiments and sensitive analysis are conducted to verify the efficiency of the proposed model and to provide managerial insights.
Agri-Food Supply Chain Management: Bibliometric and Content Analyses
Authors: Luo Jianli , Ji Chen , Qiu Chunxiao , Jia Fu
Published: May 2018

Agri-food supply chain management (ASCM) research has gained attraction in recent years. This study aims to examine the knowledge structure, trace the evolution of, and propose future research directions for ASCM by a systematic literature review combined with bibliometric and content analyses. A total of 1770 articles were selected from Scopus for bibliometric analyses. We conducted a content analysis based on 188 articles in six clusters selected from the co-citation analysis. This review provides insights into key authors, their affiliations, journal quality, and the prestige of the reviewed articles, aspects that have not been fully captured or evaluated by previous reviews. Using bibliometric tools, we identified six clusters for ASCM, based on which, future research directions are proposed. Content analysis provides additional insights in each cluster. In particular, sustainability runs through all the themes identified except for one.
A Fusion Approach for Exploring the Key Factors of Corporate Governance on Corporate Social Responsibility Performance
Authors: Hu Kuang-Hua , Lin Sin-Jin , Hsu Ming-Fu
Published: May 2018

It is widely recognized that a firm’s well-established corporate governance (CG) has a considerable impact on its corporate social responsibility (CSR) performance. How to determine the main trigger among CG’s indicators for strengthening CSR performance is thus an urgent and complicated task due to its (i.e., CSR) multi-dimensional and numerous perspectives. In order to solve this critical problem, the study breaks down CSR into four dimensions and further examines the impact of CG’s indicators on each CSR dimension by joint utilization of rough set theory (RST) and decision tree (DT). By doing so, users can realize which one CG indicator is the most essential to CSR performance. Managers can take the results as a reference to allocate valuable and scarce resources to the right place so as to enhance CSR performance in the future. To solidify our research finding, we transform the CSR forecasting model selection into a multiple criteria decision making (MCDM) task and execute a MCDM algorithm. By implementing the MCDM algorithm, users can achieve a much more reliable and consensus decision in today’s highly turbulent economic environment. The proposed mechanism, examined by real cases, is a promising alternative for CSR performance forecasting.
Selection of the Most Suitable Alternative Fuel Depending on the Fuel Characteristics and Price by the Hybrid MCDM Method
Authors: Erdogan Sinan , Sayin Cenk
Published: May 2018

In recent years, in order to increase the quality of life of people, energy usage has become very important. Researchers are constantly searching for new sources of energy due to increased energy demand. Engine tests are being conducted to investigate the feasibility of the new sources of energy such as alternative fuels. In the engine tests, engine performance, combustion characteristics and exhaust emissions are evaluated by obtaining the results. The effect of newly developed fuels on engine lifetime, safe transport and storage are also examined for fuel availability. In addition, the potential and the price of fuels are important in terms of sustainability. In these studies, laboratory environments are needed for experimental setups. It is difficult to determine the availability of the most suitable alternative fuel since numerous results are obtained in the engine tests and studies. This integrated model provides a great advantage in terms of time and cost. The physical and chemical properties of the fuel affect experimental results such as engine performance, combustion, and exhaust emission. The suggested model can be making the most efficient and eco-friendly fuel choice without the need for experimental studies by using physical and chemical properties of the fuel. It also can offer the best fuel for cost, safety and maintenance processes. In this study, animal fat biodiesel derived from waste animal fats and vegetable oil biodiesel produced from aspir-canola oils were investigated. Biodiesel fuels are mixed with diesel at 5%, 20%, and 50%, and nine different fuels prepared with three pure fuels, and six different fuel blends are compared. Before using these fuels in an experimental study, estimates are made about which fuels may be more advantageous in terms of many criteria. In the process, nine varied fuel specifications are taken as references such as calorific value, cetane number, oxygen content rate, fuel price, flash point, viscosity, lubricity, iodine number and water content. The criteria weights are determined with SWARA (Step-Wise Weight Assessment Ratio Analysis) from multi-criteria decision-making models, and MULTIMOORA (Multi-Objective Optimization on the basis of Ratio Analysis) is ranked according to fuels’ characteristics from the best to the worst. While theoretically, the best fuel is ultimately VOB20, VOB50 and AFB20 were selected as the second fuel and the third fuel.
Private Protection Initiatives in Mountain Areas of Southern Chile and Their Perceived Impact on Local Development—The Case of Pumalín Park
Authors: Hora Benedikt
Published: May 2018

This paper aims to identify the socio-economic impacts perceived by the local community to be caused by Pumalín Park, one of the biggest and most remarkable private protected areas in Chile. In recent years, the Pumalín Park project has had a tremendous influence on the local economy by providing job opportunities for local entrepreneurs, protecting native forest and strengthening social awareness, particularly in the nearby town of Chaitén, which was stricken in 2008 by a volcanic eruption. The methods used were secondary data review, semi-structured interviews with key informants and questionnaires aimed at assessing the local population’s perception of the park’s contribution to their community. The results indicate that Pumalín Park plays an important role in local development, enhancing not only conservation of fragile mountain ecosystems, but also revitalizing the economic base of this rural and marginalized area of southern Chile.
Linguistic Neutrosophic Generalized Partitioned Bonferroni Mean Operators and Their Application to Multi-Attribute Group Decision Making
Authors: Wang Yumei , Liu Peide
Published: May 2018

To solve the problems related to inhomogeneous connections among the attributes, we introduce a novel multiple attribute group decision-making (MAGDM) method based on the introduced linguistic neutrosophic generalized weighted partitioned Bonferroni mean operator (LNGWPBM) for linguistic neutrosophic numbers (LNNs). First of all, inspired by the merits of the generalized partitioned Bonferroni mean (GPBM) operator and LNNs, we combine the GPBM operator and LNNs to propose the linguistic neutrosophic GPBM (LNGPBM) operator, which supposes that the relationships are heterogeneous among the attributes in MAGDM. Then, we discuss its desirable properties and some special cases. In addition, aimed at the different importance of each attribute, the weighted form of the LNGPBM operator is investigated, which we call the LNGWPBM operator. Then, we discuss some of its desirable properties and special examples accordingly. In the end, we propose a novel MAGDM method on the basis of the introduced LNGWPBM operator, and illustrate its validity and merit by comparing it with the existing methods.
Searching on Encrypted E-Data Using Random Searchable Encryption (RanSCrypt) Scheme
Authors: Ahsan M , Idna Bin Idris Mohd , Bin Abdul Wahab Ainuddin , Ali Ihsan , Khan Nawsher , Al-Garwi Mohammed , Rahman Atiq
Published: May 2018

Cloud computing is intensifying the necessity for searchable encryption (SE) for data protection in cloud storage. SE encrypts data to preserve its confidentiality while offering a secure search facility on the encrypted data. Typical index-based SEs in data sharing scenarios can effectively search secure keyword indexes. However, due to the smaller size of the keyword space, SEs using a public key are susceptible to a Keyword Guessing Attack (KGA) and other statistical information leakage. In this paper, for secure search in a data sharing scenario, we propose Random Searchable enCryption (RanSCrypt) that adds randomness to a transformed keyword to increase its space and aspires to make it irreversible. At the core of the mechanism, two keywords are garbled with randomness, still enabling another party to determine if the two garbled keywords (RanSCrypt’s terms REST and Trapdoor) are the same or not without knowing the actual keywords. As SE in a public key setting suffers from vulnerability to KGA, RanSCrypt transfers into a symmetric key setting with minimum overhead and without losing the features of a data sharing scenario. RanSCrypt also adulterates the search result to add perplexity and provides full control of access only to the data receiver. The receiver can cull out the erroneous results from the search result locally. Finally, we introduce a new type of attack on SE, namely, the Keyword Luring Attack (KLA), and show that RanSCrypt is safe from KLA attack due to adulteration of the result. Our security analysis proves RanSCrypt is invulnerable against KGA and leaks no information.
An Online Algorithm for Dynamic NFV Placement in Cloud-Based Autonomous Response Networks
Authors: Ochoa-Aday Leonardo , Cervelló-Pastor Cristina , Fernández-Fernández Adriana , Grosso Paola
Published: May 2018

Autonomous response networks are becoming a reality thanks to recent advances in cloud computing, Network Function Virtualization (NFV) and Software-Defined Networking (SDN) technologies. These enhanced networks fully enable autonomous real-time management of virtualized infrastructures. In this context, one of the major challenges is how virtualized network resources can be effectively placed. Although this issue has been addressed before in cloud-based environments, it is not yet completely resolved for the online placement of virtual machines. For such a purpose, this paper proposes an online heuristic algorithm called Topology-Aware Placement of Virtual Network Functions (TAP-VNF) as a low-complexity solution for such dynamic infrastructures. As a complement, we provide a general formulation of the network function placement using the service function chaining concept. Furthermore, two metrics called consolidation and aggregation validate the efficiency of the proposal in the experimental simulations. We have compared our approach with optimal solutions, in terms of consolidation and aggregation ratios, showing a more suitable performance for dynamic cloud-based environments. The obtained results show that TAP-VNF also outperforms existing approaches based on traditional bin packing schemes.
Integrated Hybrid Second Order Algorithm for Orthogonal Projection onto a Planar Implicit Curve
Authors: Li Xiaowu , Pan Feng , Cheng Taixia , Wu Zhinan , Liang Juan , Hou Linke
Published: May 2018

The computation of the minimum distance between a point and a planar implicit curve is a very important problem in geometric modeling and graphics. An integrated hybrid second order algorithm to facilitate the computation is presented. The proofs indicate that the convergence of the algorithm is independent of the initial value and demonstrate that its convergence order is up to two. Some numerical examples further confirm that the algorithm is more robust and efficient than the existing methods.
High Production of LukMF’ in Staphylococcus aureus Field Strains Is Associated with Clinical Bovine Mastitis
Authors: Hoekstra Jurriaan , Rutten Victor , Sommeling Laura , Van Werven Tine , Spaninks Mirlin , Duim Birgitta , Benedictus Lindert , Koop Gerrit
Published: May 2018

Staphylococcus aureus, a major cause of bovine mastitis, produces a wide range of immune-evasion molecules. The bi-component leukocidin LukMF’ is a potent killer of bovine neutrophils in vitro. Since the role of LukMF’ in development of bovine mastitis has not been studied in natural infections, we aimed to clarify whether presence of the lukM-lukF’ genes and production levels of LukMF’ are associated with clinical severity of the disease. Staphylococcus aureus was isolated from mastitis milk samples (38 clinical and 17 subclinical cases) from 33 different farms. The lukM-lukF’ genes were present in 96% of the isolates. Remarkably, 22% of the lukM-lukF’-positive S. aureus isolates displayed a 10-fold higher in vitro LukMF’ production than the average of the lower-producing ones. These high producing isolates were cultured significantly more frequently from clinical than subclinical mastitis cases. Also, the detection of LukM protein in milk samples was significantly associated with clinical mastitis and high production in vitro. The high producing LukMF’ strains all belonged to the same genetic lineage, spa-type t543. Analysis of their global toxin gene regulators revealed a point mutation in the Repressor of toxins (rot) gene which results in a non-functional start codon, preventing translation of rot. This mutation was only identified in high LukMF’ producing isolates and not in low LukMF’ producing isolates. Since rot suppresses the expression of various toxins including leukocidins, this mutation is a possible explanation for increased LukMF’ production. Identification of high LukMF’ producing strains is of clinical relevance and can potentially be used as a prognostic marker for severity of mastitis.
A Review of the Ongoing Research on Zika Virus Treatment
Authors: Da Silva Suely , Oliveira Silva Martins Daniel , Jardim Ana
Published: May 2018

The Zika fever is an arboviral disease resulting from the infection with Zika virus (ZIKV). The virus is transmitted to humans by the bite of Aedes mosquitos, mainly Aedes aegypti and Aedes albopictus. ZIKV has been detected for decades in African and Asian regions and, since 2007, has spread to other continents; among them, infections are most reported in the Americas. This can be explained by the presence of vectors in highly populated and tropical regions where people are susceptible to contamination. ZIKV has been considered by the World Health Organization a serious public health problem because of the increasing number of cases of congenital malformation and neurological disorders related to its infection, such as microcephaly, Guillain–Barré syndrome, meningoencephalitis, and myelitis. There is no vaccine or specific antiviral against ZIKV. The infection is best prevented by avoiding mosquito bite, and the treatment of infected patients is palliative. In this context, the search for efficient antivirals is necessary but remains challenging. Here, we aim to review the molecules that have been described to interfere with ZIKV life cycle and discuss their potential use in ZIKV therapy.
Bioinformatics Meets Virology: The European Virus Bioinformatics Center’s Second Annual Meeting
Authors: Ibrahim Bashar , Arkhipova Ksenia , Andeweg Arno , Posada-Céspedes Susana , Enault François , Gruber Arthur , Koonin Eugene , Kupczok Anne , Lemey Philippe , McHardy Alice , McMahon Dino , Pickett Brett , Robertson David , Scheuermann Richard , Zhernakova Alexandra , Zwart Mark , Schönhuth Alexander , Dutilh Bas , Marz Manja
Published: May 2018

The Second Annual Meeting of the European Virus Bioinformatics Center (EVBC), held in Utrecht, Netherlands, focused on computational approaches in virology, with topics including (but not limited to) virus discovery, diagnostics, (meta-)genomics, modeling, epidemiology, molecular structure, evolution, and viral ecology. The goals of the Second Annual Meeting were threefold: (i) to bring together virologists and bioinformaticians from across the academic, industrial, professional, and training sectors to share best practice; (ii) to provide a meaningful and interactive scientific environment to promote discussion and collaboration between students, postdoctoral fellows, and both new and established investigators; (iii) to inspire and suggest new research directions and questions. Approximately 120 researchers from around the world attended the Second Annual Meeting of the EVBC this year, including 15 renowned international speakers. This report presents an overview of new developments and novel research findings that emerged during the meeting.
Blackcurrant Leaf Chlorosis Associated Virus: Evidence of the Presence of Circular RNA during Infections
Authors: James Delano , Phelan James , Sanderson Daniel
Published: May 2018

Blackcurrant leaf chlorosis associated virus (BCLCaV) was detected recently by next-generation sequencing (NGS) and a new and distinct species in the genus Idaeovirus was proposed. Analysis of NGS-derived paired-end reads revealed the existence of bridge reads encompassing the 3′-terminus and 5′-terminus of RNA-2 or RNA-3 of BCLCaV. The full RNA-2 or RNA-3 could be amplified using outward facing or abutting primers; also, RNA-2/RNA-3 could be detected even after three consecutive RNase R enzyme treatments, with denaturation at 95 °C preceding each digestion. Evidence was obtained indicating that there are circular forms of BCLCaV RNA-2 and RNA-3.
New Screening tool for Obtaining Concentration Statistics of Pollution Generated by Rivers in Estuaries
Authors: Galešić Morena , Andričević Roko , Divić Vladimir , Šakić Trogrlić Robert
Published: May 2018

Rivers represent an essential pathway for waterborne transport, and therefore estuaries are critical coastal areas for a pollution hazard that might lead to eutrophication and general water quality deterioration. When addressing these problems, the decision makers and coastal managers often need additional skills and specialists, so they engage consultants in developing models and providing potential solutions. Different stakeholders’ interests present a challenge in the implementation process of proposed solutions. Nevertheless, if the relevant institutions were presented with a screening tool, enabling them with a certain level of solution ownership, potentially more involvement would occur. There are numerous intertwined physical processes present in the estuary ecosystem, including river discharge, tidal forces, wind-induced stress and water density variations. This research utilizes an analytical model based on ensemble averaging and near-field approximation of the advective-diffusion equation for the case of continuous, steady, conservative solute transport in a stratified, river-dominated estuary. Such an approach significantly reduces the costs and time needed to obtain enough measured data required for common statistical analysis or the need for a more complex numerical model. The developed methodology is implemented into a simple software named CPoRT (Coastal Pollution Risk Tool) within a recently conducted research project funded by European Social Fund.
Impact of Real World Drive Cycles on PHEV Fuel Efficiency and Cost for Different Powertrain and Battery Characteristics
Authors: Moawad Ayman , Singh Gurhari , Hagspiel Simeon , Fellah Mohamed , Rousseau Aymeric
Published: May 2018

For the past couple of years, Plug-in Hybrid Electric Vehicles (PHEVs) demonstrated their ability to significantly reduce petroleum consumptions. However, more than any other vehicle powertrain, their benefits are dependent on the driving cycles from both an aggressiveness and distance point of view. In this paper, two powertrain configurations will be defined. A power split configuration will be used for low battery energy and a series configuration for high battery energy. For each vehicle we will evaluate several control strategies, including electrical dominant and blended, on real world drive cycles. A conventional vehicle will be defined to use as a baseline. The trade-off between fuel displacement and cost will be evaluated for each option.
Next Generation Fuel Cell Technology for Passenger Cars and Buses
Authors: Mohrdieck Dr.
Published: May 2018

Daimler is presenting its latest fuel cell vehicle, the Mercedes-Benz B-Class F-CELL in 2009. Being one of the first series-produced fuel cell vehicles so far, the B-Class F-CELL will be a milestone on the road to commercialization of hydrogen-powered fuel cell vehicles. Equipped with advanced fuel cell technology it is suited for everyday operation and designed to fully meet customers´ expectations. From 2010 onwards, this zero emission vehicle is going to be operated by selected customers in different countries. In addition, a new generation of fuel cell buses, the Mercedes-Benz Citaro FuelCELL–Hybrid is presented in 2009.
Analysis of the Impact of Plug-In Hybrid Electric Vehicles on Residential Distribution Grids by using Quadratic and Dynamic Programming
Authors: Clement-Nyns Kristien , Haesen Edwin , Driesen Johan
Published: May 2018

The charging of batteries of plug-in hybrid electric vehicles at home at standard outlets has an impact on the distribution grid which may require serious investments in grid expansion. The coordination of the charging gives an improvement of the grid exploitation in terms of reduced power losses and voltage deviations with respect to uncoordinated charging. The vehicles must be dispatchable to achieve the most efficient solution. As the exact forecasting of household loads is not possible, stochastic programming is introduced. Two main techniques are analyzed in this paper: quadratic and dynamic programming. Both techniques are compared in results and storage requirements. The charging can be coordinated directly or indirectly by the grid utility or an aggregator who will sell the aggregated demand of PHEVs at the utility. PHEVs can also discharge and so inject energy in the grid to restrict voltage drops. The amount of energy that is injected in the grid depends on the price tariffs, the charging and discharging efficiencies and the battery energy content. The impact of a voltage controller embedded in a PHEV charger is regarded in this paper. A day and night tariff are applied. The charging and discharging of vehicles can respond to real-time pricing or on a price-schedule as well. Voltage control is the first step in the utilization of distributed resources like PHEVs for ancillary services.
Capacitors for Internal Combustion Engine Starting with Green Technology DLCAPTM
Authors: Furukawa Toshihiko
Published: May 2018

In the past internal combustion engines in commercial trucks, buses, and automobiles were often allowed to idle during stops, whether short or extended. This practice mitigated engine non-starts but increased fuel usage along with air emissions and accelerated engine wear. Engine starting can be performed more reliability by electrochemical capacitors rather than by batteries, especially at low temperatures. Capacitor modules are now available to start engines of all sizes. This paper will discuss the starting requirements of large diesel engines and present low-temperature engine cranking results using Nippon Chemi-Con DLCAP non-toxic-electrolyte electrochemical capacitor.