bluuebunny/crossref_metadata_2025 huggingface dataset:
Emerging Corrosion Inhibitors for Interfacial Coating
Authors: Taghavikish Mona , Dutta Naba , Roy Choudhury Namita
Published: December 2017

Corrosion is a deterioration of a metal due to reaction with environment. The use of corrosion inhibitors is one of the most effective ways of protecting metal surfaces against corrosion. Their effectiveness is related to the chemical composition, their molecular structures and affinities for adsorption on the metal surface. This review focuses on the potential of ionic liquid, polyionic liquid (PIL) and graphene as promising corrosion inhibitors in emerging coatings due to their remarkable properties and various embedment or fabrication strategies. The review begins with a precise description of the synthesis, characterization and structure-property-performance relationship of such inhibitors for anti-corrosion coatings. It establishes a platform for the formation of new generation of PIL based coatings and shows that PIL corrosion inhibitors with various heteroatoms in different form can be employed for corrosion protection with higher barrier properties and protection of metal surface. However, such study is still in its infancy and there is significant scope to further develop new structures of PIL based corrosion inhibitors and coatings and study their behaviour in protection of metals. Besides, it is identified that the combination of ionic liquid, PIL and graphene could possibly contribute to the development of the ultimate corrosion inhibitor based coating.
Context-Aware Generative Adversarial Privacy
Authors: Huang Chong , Kairouz Peter , Chen Xiao , Sankar Lalitha , Rajagopal Ram
Published: December 2017

Preserving the utility of published datasets while simultaneously providing provable privacy guarantees is a well-known challenge. On the one hand, context-free privacy solutions, such as differential privacy, provide strong privacy guarantees, but often lead to a significant reduction in utility. On the other hand, context-aware privacy solutions, such as information theoretic privacy, achieve an improved privacy-utility tradeoff, but assume that the data holder has access to dataset statistics. We circumvent these limitations by introducing a novel context-aware privacy framework called generative adversarial privacy (GAP). GAP leverages recent advancements in generative adversarial networks (GANs) to allow the data holder to learn privatization schemes from the dataset itself. Under GAP, learning the privacy mechanism is formulated as a constrained minimax game between two players: a privatizer that sanitizes the dataset in a way that limits the risk of inference attacks on the individuals’ private variables, and an adversary that tries to infer the private variables from the sanitized dataset. To evaluate GAP’s performance, we investigate two simple (yet canonical) statistical dataset models: (a) the binary data model; and (b) the binary Gaussian mixture model. For both models, we derive game-theoretically optimal minimax privacy mechanisms, and show that the privacy mechanisms learned from data (in a generative adversarial fashion) match the theoretically optimal ones. This demonstrates that our framework can be easily applied in practice, even in the absence of dataset statistics.
Properties of Risk Measures of Generalized Entropy in Portfolio Selection
Authors: Zhou Rongxi , Liu Xiao , Yu Mei , Huang Kyle
Published: December 2017

This paper systematically investigates the properties of six kinds of entropy-based risk measures: Information Entropy and Cumulative Residual Entropy in the probability space, Fuzzy Entropy, Credibility Entropy and Sine Entropy in the fuzzy space, and Hybrid Entropy in the hybridized uncertainty of both fuzziness and randomness. We discover that none of the risk measures satisfy all six of the following properties, which various scholars have associated with effective risk measures: Monotonicity, Translation Invariance, Sub-additivity, Positive Homogeneity, Consistency and Convexity. Measures based on Fuzzy Entropy, Credibility Entropy, and Sine Entropy all exhibit the same properties: Sub-additivity, Positive Homogeneity, Consistency, and Convexity. These measures based on Information Entropy and Hybrid Entropy, meanwhile, only exhibit Sub-additivity and Consistency. Cumulative Residual Entropy satisfies just Sub-additivity, Positive Homogeneity, and Convexity. After identifying these properties, we develop seven portfolio models based on different risk measures and made empirical comparisons using samples from both the Shenzhen Stock Exchange of China and the New York Stock Exchange of America. The comparisons show that the Mean Fuzzy Entropy Model performs the best among the seven models with respect to both daily returns and relative cumulative returns. Overall, these results could provide an important reference for both constructing effective risk measures and rationally selecting the appropriate risk measure under different portfolio selection conditions.
Predictive Maintenance of Power Substation Equipment by Infrared Thermography Using a Machine-Learning Approach
Authors: Ullah Irfan , Yang Fan , Khan Rehanullah , Liu Ling , Yang Haisheng , Gao Bing , Sun Kai
Published: December 2017

A variety of reasons, specifically contact issues, irregular loads, cracks in insulation, defective relays, terminal junctions and other similar issues, increase the internal temperature of electrical instruments. This results in unexpected disturbances and potential damage to power equipment. Therefore, the initial prevention measures of thermal anomalies in electrical tools are essential to prevent power-equipment failure. In this article, we address this initial prevention mechanism for power substations using a computer-vision approach by taking advantage of infrared thermal images. The thermal images are taken through infrared cameras without disturbing the working operations of power substations. Thus, this article augments the non-destructive approach to defect analysis in electrical power equipment using computer vision and machine learning. We use a total of 150 thermal pictures of different electrical equipment in 10 different substations in operating conditions, using 300 different hotspots. Our approach uses multi-layered perceptron (MLP) to classify the thermal conditions of components of power substations into “defect” and “non-defect” classes. A total of eleven features, which are first-order and second-order statistical features, are calculated from the thermal sample images. The performance of MLP shows initial accuracy of 79.78%. We further augment the MLP with graph cut to increase accuracy to 84%. We argue that with the successful development and deployment of this new system, the Technology Department of Chongqing can arrange the recommended actions and thus save cost in repair and outages. This can play an important role in the quick and reliable inspection to potentially prevent power substation equipment from failure, which will save the whole system from breakdown. The increased 84% accuracy with the integration of the graph cut shows the efficacy of the proposed defect analysis approach.
Thermal and Electromagnetic Combined Optimization Design of Dry Type Air Core Reactor
Authors: Yuan Fating , Yuan Zhao , Chen Lixue , Wang Yong , Liu Junxiang , He Junjia , Pan Yuan
Published: December 2017

In this paper, taking the minimum metal conductor usage of an air core reactor as optimization goal, the influence of air ducts width and encapsulation number on thermal efficiency and electromagnetic efficiency are analyzed. Combined with the equation constraint conditions for maximum temperature rise conservation, inductance conservation and structure function of reactor considering the change of air ducts width and encapsulation number, the thermal and electromagnetic combined optimization curves are formed, and design results are achieved based on the initial design parameters. Meanwhile, the temperature field simulation model of the reactor is established and the results verify the correctness of the optimization method. According to the design results, the proportionality factor of metal conductor usage is only 0.61 compared with the initial design parameters of the reactor, which shows that the proposed comprehensive optimization method can significantly reduce conductor usage, improving the metal conductor utilization ratio.
H-Shaped Multiple Linear Motor Drive Platform Control System Design Based on an Inverse System Method
Authors: Qin Caiyan , Zhang Chaoning , Lu Haiyan
Published: December 2017

Due to its simple mechanical structure and high motion stability, the H-shaped platform has been increasingly widely used in precision measuring, numerical control machining and semiconductor packaging equipment, etc. The H-shaped platform is normally driven by multiple (three) permanent magnet synchronous linear motors. The main challenges for H-shaped platform-control include synchronous control between the two linear motors in the Y direction as well as total positioning error of the platform mover, a combination of position deviation in X and Y directions. To deal with the above challenges, this paper proposes a control strategy based on the inverse system method through state feedback and dynamic decoupling of the thrust force. First, mechanical dynamics equations have been deduced through the analysis of system coupling based on the platform structure. Second, the mathematical model of the linear motors and the relevant coordinate transformation between dq-axis currents and ABC-phase currents are analyzed. Third, after the main concept of inverse system method being explained, the inverse system model of the platform control system has been designed after defining relevant system variables. Inverse system model compensates the original nonlinear coupled system into pseudo-linear decoupled linear system, for which typical linear control methods, like PID, can be adopted to control the system. The simulation model of the control system is built in MATLAB/Simulink and the simulation result shows that the designed control system has both small synchronous deviation and small total trajectory tracking error. Furthermore, the control program has been run on NI controller for both fixed-loop-time and free-loop-time modes, and the test result shows that the average loop computation time needed is rather small, which makes it suitable for real industrial applications. Overall, it proves that the proposed new control strategy can be used in industrial applications that have high-precision and high real-time performance requirements.
Testing for Environmental Kuznets Curve in the EU Agricultural Sector through an Eco-(in)Efficiency Index
Authors: Vlontzos George , Niavis Spyros , Pardalos Panos
Published: December 2017

Studies on agricultural production practices advance within international literature and new methods are proposed in order to assess the agricultural sustainability, either at farm or macro level. The present paper builds on these advancements and develops a synthetic Eco-(in)efficiency index by employing a directional distance function—data envelopment analysis (DEA) model. This index is used in order to assess the sustainability of the EU agricultural sector for the period 1999–2012 on a country level. Furthermore, Eco-(in)efficiency, together with the energy use and greenhouse gas (GHG) emissions are regressed on the gross domestic product (GDP) of EU countries, in order to check for any environmental Kuznets curve relationship existence. Results signify that efficiency improvements are possible, both towards output development and GHG emissions reduction. In addition, the potential of each country in adopting more sustainable production practices is not totally connected with its economic development, as Eco-(in)efficiency and GDP levels of EU countries seem to be linked with an N-Shaped curve.
Wind Speed Forecasting Based on EMD and GRNN Optimized by FOA
Authors: Niu Dongxiao , Liang Yi , Hong Wei-Chiang
Published: December 2017

As a kind of clean and renewable energy, wind power is winning more and more attention across the world. Regarding wind power utilization, safety is a core concern and such concern has led to many studies on predicting wind speed. To obtain a more accurate prediction of the wind speed, this paper adopts a new hybrid forecasting model, combing empirical mode decomposition (EMD) and the general regression neural network (GRNN) optimized by the fruit fly optimization algorithm (FOA). In this new model, the original wind speed series are first decomposed into a collection of intrinsic mode functions (IMFs) and a residue. Next, the inherent relationship (partial correlation) of the datasets is analyzed, and the results are then used to select the input for the forecasting model. Finally, the GRNN with the FOA to optimize the smoothing factor is used to predict each sub-series. The mean absolute percentage error of the forecasting results in two cases are respectively 8.95% and 9.87%, suggesting that the hybrid approach outperforms the compared models, which provides guidance for future wind speed forecasting.
Phase-Inductance-Based Position Estimation Method for Interior Permanent Magnet Synchronous Motors
Authors: Qiu Xin , Wang Weiye , Yang Jianfei , Jiang Jie , Yang Jiquan
Published: December 2017

This paper presents a phase-inductance-based position estimation method for interior permanent magnet synchronous motors (IPMSMs). According to the characteristics of phase induction of IPMSMs, the corresponding relationship of the rotor position and the phase inductance is obtained. In order to eliminate the effect of the zero-sequence component of phase inductance and reduce the rotor position estimation error, the phase inductance difference is employed. With the iterative computation of inductance vectors, the position plane is further subdivided, and the rotor position is extracted by comparing the amplitudes of inductance vectors. To decrease the consumption of computer resources and increase the practicability, a simplified implementation is also investigated. In this method, the rotor position information is achieved easily, with several basic math operations and logical comparisons of phase inductances, without any coordinate transformation or trigonometric function calculation. Based on this position estimation method, the field orientated control (FOC) strategy is established, and the detailed implementation is also provided. A series of experiment results from a prototype demonstrate the correctness and feasibility of the proposed method.
Energy Performance and Economic Feasibility Study of Historical Building in the City of Matera, Southern Italy
Authors: Rospi Gianluca , Cardinale Nicola , Negro Elisabetta
Published: December 2017

In this paper a careful energy audit and an energy restoration of some historical buildings was performed. In particular, three cultural heritages buildings situated in the city of Matera in Southern Italy were analysed. To analyse these buildings, an integrated approach based on measurements in situ and on dynamic energy simulations was used. Then, some energy efficiency actions were performed, safeguarding the authenticity value of these structures. The thermal conductance, the indoor temperature and the energy consumption were measured in situ and then the numerical virtual model was created by the Energy Plus code (Energy Plus is free, open-source, and cross-platform developed by the U.S. Department of Energy’s and Building Technologies Office) (U.S. Department of Energy’s (DOE) Building Technologies Office (BTO), Washington, DC, USA). The numerical model was validated by using the Inequality Coefficient (IC) and then different parametric energy analyses were performed. The paper analysed different energy improvements and a techno-economic feasibility study was performed for each improvement. This analysis was conducted in dynamic regime by using the Energy-Plus code. In these buildings the thermal system improvements have a better payback time than envelope improvements. Two different thermal system improvements were analysed: the absorption heat pump with thermostatic valves and the compression heat pump with fan coil unit. Moreover, the replacement of present lighting with LED technologies has a payback time near one year.
Experimental Study on Bluff-Body Stabilized Premixed Flame with a Central Air/Fuel Jet
Authors: Tong Yiheng , Chen Shuang , Li Mao , Li Zhongshan , Klingmann Jens
Published: December 2017

Bluff-body flame holders are commonly employed in many industrial applications. A bluff-body is usually adopted to enhance the downstream mixing of the combustion products and the fresh fuel-air mixtures, thus to improve the flame stability and to control the combustion process. In the present paper, flames stabilized by a conical-shape bluff-body flame holder with a central air/fuel jet were studied. Effects of both a central air jet and a central fuel jet on the structures and lean blowout limits of the premixed annular flames, and on the temperature on the upper surface of the bluff-body were investigated and presented. It was revealed that a central jet led to a considerable reduction of the temperature on the upper surface of the bluff-body. It was proposed to be caused by the alternation of flow structures (in the case with a central air jet) altogether with the flame lifting from the burner (in the case with a central fuel jet). Thus, it might be used to solve the problem of the bluff-body with high heat loads in practical applications. The flame stability characteristics, for example the unstable flame dynamics and the lean blowout limits, varied with the injection of an air or fuel jet through the central pipe. Different blowout behaviors, being with or without the occurrence of flame split and flashing, caused by a central air jet were presented in the paper. In addition, when a small amount of central fuel jet (i.e., Uf/Ua = 0.045) was injected into the flow fields, an unsteady circular motion of the flame tip along the outer edge of the bluff-body was observed as well. Whereas, with an increase in the amount of the central fuel jet, the flame detached from the outer edge of the bluff-body and then became much more unstable. With a central air or fuel jet injecting into the flow field, premixed flames stabilized by the bluff-body became more unstable and easier to blowout.
Indirect State-of-Health Estimation for Lithium-Ion Batteries under Randomized Use
Authors: Yu Jinsong , Mo Baohua , Tang Diyin , Yang Jie , Wan Jiuqing , Liu Jingjing
Published: December 2017

Lithium-ion batteries are widely used in many systems. Because they provide a power source to the whole system, their state-of-health (SOH) is very important for a system’s proper operation. A direct way to estimate the SOH is through the measurement of the battery’s capacity; however, this measurement during the battery’s operation is not that easy in practice. Moreover, the battery is always running under randomized loading conditions, which makes the SOH estimation even more difficult. Therefore, this paper proposes an indirect SOH estimation method that relies on indirect health indicators (HIs) that can be measured easily during the battery’s operation. These indicators are extracted from the battery’s voltage and current and the number of cycles the battery has been through, which are far easier to measure than the battery’s capacity. An empirical model based on an elastic net is developed to build the quantitative relationship between the SOH and these indirect HIs, considering the possible multi-collinearity between these HIs. To further improve the accuracy of SOH estimation, we introduce a particle filter to automatically update the model when capacity data are obtained occasionally. We use a real dataset to demonstrate our proposed method, showing quite a good performance of the SOH estimation. The results of the SOH estimation in the experiment are quite satisfactory, which indicates that the method is effective and accurate enough to be used in real practice.
Orthogonal Test Analysis on Conditions Affecting Electricity Generation Performance of an Enhanced Geothermal System at Yangbajing Geothermal Field
Authors: Zeng Yuchao , Tang Liansheng , Wu Nengyou , Song Jing , Cao Yifei
Published: December 2017

The main conditions affecting electricity generation performance of an enhanced geothermal system (EGS) include reservoir porosity, reservoir permeability, rock heat conductivity, water production rate and injection temperature. Presently there is lack of systematic research the relative importance of the five aforementioned conditions. The orthogonal test method is a statistical approach to analyze multi-factor and multi-level influence on system performance. In this work, based on the geological data at Yangbajing geothermal field, we analyzed the five conditions affecting the electricity generation performance of EGS, and ranked the relative importance of the five factors. The results show that the order of the relative importance of the conditions on electric power is water production rate > injection temperature > reservoir porosity > rock heat conductivity > reservoir permeability; the order of the relative importance of the conditions on reservoir impedance is reservoir permeability > injection temperature > water production rate > reservoir porosity > rock heat conductivity; the order of the relative importance of the conditions on pump power is water production rate > reservoir permeability > injection temperature > reservoir porosity > rock heat conductivity, and; the order of the relative importance of the conditions on energy efficiency is water production rate > reservoir permeability > reservoir porosity > injection temperature > rock heat conductivity. The construction of an EGS reservoir should be located at a formation with higher reservoir porosity or rock heat conductivity, while the determination of reservoir permeability, water production rate and injection temperature should be based on the comprehensive target.
Maximum Power Point Tracking Control of a Thermoelectric Generation System Using the Extremum Seeking Control Method
Authors: Twaha Ssennoga , Zhu Jie , Maraaba Luqman , Huang Kuo , Li Bo , Yan Yuying
Published: December 2017

This study proposes and implements maximum power Point Tracking (MPPT) control on thermoelectric generation system using an extremum seeking control (ESC) algorithm. The MPPT is applied to guarantee maximum power extraction from the TEG system. The work has been carried out through modelling of thermoelectric generator/dc-dc converter system using Matlab/Simulink. The effectiveness of ESC technique has been assessed by comparing the results with those of the Perturb and Observe (P&O) MPPT method under the same operating conditions. Results indicate that ESC MPPT method extracts more power than the P&O technique, where the output power of ESC technique is higher than that of P&O by 0.47 W or 6.1% at a hot side temperature of 200 °C. It is also noted that the ESC MPPT based model is almost fourfold faster than the P&O method. This is attributed to smaller MPPT circuit of ESC compared to that of P&O, hence we conclude that the ESC MPPT method outperforms the P&O technique.
National Options for a Sustainable Nuclear Energy System: MCDM Evaluation Using an Improved Integrated Weighting Approach
Authors: Gao Ruxing , Nam Hyo , Ko Won , Jang Hong
Published: December 2017

While the prospects look bright for nuclear energy development in China, no consensus about an optimum transitional path towards sustainability of the nuclear fuel cycle has been achieved. Herein, we present a preliminary study of decision making for China’s future nuclear energy systems, combined with a dynamic analysis model. In terms of sustainability assessment based on environmental, economic, and social considerations, we compared and ranked the four candidate options of nuclear fuel cycles combined with an integrated evaluation analysis using the Multi-Criteria Decision Making (MCDM) method. An improved integrated weighting method was first applied in the nuclear fuel cycle evaluation study. This method synthesizes diverse subjective/objective weighting methods to evaluate conflicting criteria among the competing decision makers at different levels of expertise and experience. The results suggest that the fuel cycle option of direct recycling of spent fuel through fast reactors is the most competitive candidate, while the fuel cycle option of direct disposal of all spent fuel without recycling is the least attractive for China, from a sustainability perspective. In summary, this study provided a well-informed decision-making tool to support the development of national nuclear energy strategies.
Identification of Power Transformer Winding Mechanical Fault Types Based on Online IFRA by Support Vector Machine
Authors: Zhao Zhongyong , Tang Chao , Zhou Qu , Xu Lingna , Gui Yingang , Yao Chenguo
Published: December 2017

A transformer is the most valuable and expensive property for power utility, thus ensuring its reliable operation is a major task for both operators and researchers. Online impulse frequency response analysis has proven to be a promising technique for detecting transformer internal winding mechanical deformation faults when a power transformer is in service. However, as so far, there is still no reliable standard code for frequency response signature interpretation and quantification. This paper tries to utilize a machine learning method, namely the support vector machine, to identify and classify the winding mechanical fault types, based on online impulse frequency response analysis. Actual transformer fault data from a specially manufactured model transformer are collected and analyzed. Two feature vectors are proposed and the diagnostic results are predicted. The diagnostic results indicate the satisfied classifying accuracy by the proposed method.
Hybrid Electromagnetic and Triboelectric Nanogenerators with Multi-Impact for Wideband Frequency Energy Harvesting
Authors: Zhu Jianxiong , Wang Aochen , Hu Haibing , Zhu Hua
Published: December 2017

We present a hybrid electromagnetic generator (EMG) and triboelectric nanogenerator (TENG) using a multi-impact approach for broad-bandwidth-frequency (10–45 Hz) energy harvesting. The TENG and the EMG were located at the middle and the free end of the cantilever beam, respectively. When the system was subjected to an external vibration, the cantilever beam would be in a nonlinear response with multiple impacts from a low frequency oscillator. The mathematical model included a TENG oscillator which can have multiple impacts on the cantilever, and the nonlinear Lorenz force which comes from the motion of the coil in the electromagnetic field. Due to the strong nonlinearity of the impacts from the TENG oscillator and the limited space for the free tip of the cantilever, the dynamic response of the cantilever presented a much broader bandwidth, with a frequency range from 10–45 Hz. We also found that the average generated power from TENG and EMG can reach up to 30 μW/m2 and 53 μW, respectively. Moreover, the dynamic responses of the hybrid EMG and TENG were carefully analyzed, and we found that the measured experimental results and the numerical simulations results were in good agreement.
Research on CO2 Emission Reduction Mechanism of China’s Iron and Steel Industry under Various Emission Reduction Policies
Authors: Duan Ye , Li Nan , Mu Hailin , Gui Shusen
Published: December 2017

In this paper, a two-stage dynamic game model of China’s iron and steel industry is constructed. Carbon tax levy, product subsidy, carbon capture and sequestration (CCS) and other factors are included in the emission reduction mechanism. The effects of emissions reduction and the economic impact of China’s overall steel industry (and that of its six main regions) are investigated for the first time under different scenarios. As new findings, we report the following: (1) Not all factors declined. The overall social welfare, consumer surplus, output and emissions decrease with a gradual increase in the reduction target, whereas the carbon tax value, unit value of product subsidies and total subsidies show a rising trend; (2) A combination of multiple emissions reduction policies is more effective than a single policy. With the implementation of a combined policy, regional output polarization has eased; (3) Steel output does not exceed 950 million tons, far below the current peak. These results will help the industry to formulate reasonable emissions reduction and output targets. In short, in effort to eliminate industry poverty and to alleviate overcapacity, the industry should not only adopt the various coordinated reduction policies, but also fully consider regional differences and reduction needs.
Predicting Future Seed Sourcing of Platycladus orientalis (L.) for Future Climates Using Climate Niche Models
Authors: Hu Xian-Ge , Wang Tongli , Liu Si-Si , Jiao Si-Qian , Jia Kai-Hua , Zhou Shan-Shan , Jin Yuqing , Li Yue , El-Kassaby Yousry A. , Mao Jian-Feng
Published: December 2017

Climate niche modeling has been widely used to assess the impact of climate change on forest trees at the species level. However, geographically divergent tree populations are expected to respond differently to climate change. Considering intraspecific local adaptation in modeling species responses to climate change will thus improve the credibility and usefulness of climate niche models, particularly for genetic resources management. In this study, we used five Platycladus orientalis (L.) seed zones (Northwestern; Northern; Central; Southern; and Subtropical) covering the entire species range in China. A climate niche model was developed and used to project the suitable climatic conditions for each of the five seed zones for current and various future climate scenarios (Representative Concentration Pathways: RCP2.6, RCP4.5, RCP6.0, and RCP8.5). Our results indicated that the Subtropical seed zone would show consistent reduction for all climate change scenarios. The remaining seed zones, however, would experience various degrees of expansion in suitable habitat relative to their current geographic distributions. Most of the seed zones would gain suitable habitats at their northern distribution margins and higher latitudes. Thus, we recommend adjusting the current forest management strategies to mitigate the negative impacts of climate change.
Linear Polarization Properties of Parsec-Scale AGN Jets
Authors: Pushkarev Alexander , Kovalev Yuri , Lister Matthew , Savolainen Tuomas , Aller Margo , Aller Hugh , Hodge Mary
Published: December 2017

We used 15 GHz multi-epoch Very Long Baseline Array (VLBA) polarization sensitive observations of 484 sources within a time interval 1996–2016 from the MOJAVE program, and also from the NRAO data archive. We have analyzed the linear polarization characteristics of the compact core features and regions downstream, and their changes along and across the parsec-scale active galactic nuclei (AGN) jets. We detected a significant increase of fractional polarization with distance from the radio core along the jet as well as towards the jet edges. Compared to quasars, BL Lacs have a higher degree of polarization and exhibit more stable electric vector position angles (EVPAs) in their core features and a better alignment of the EVPAs with the local jet direction. The latter is accompanied by a higher degree of linear polarization, suggesting that compact bright jet features might be strong transverse shocks, which enhance magnetic field regularity by compression.
Synthesis of Rhizobial Exopolysaccharides and Their Importance for Symbiosis with Legume Plants
Authors: Marczak Małgorzata , Mazur Andrzej , Koper Piotr , Żebracki Kamil , Skorupska Anna
Published: December 2017

Rhizobia dwell and multiply in the soil and represent a unique group of bacteria able to enter into a symbiotic interaction with plants from the Fabaceae family and fix atmospheric nitrogen inside de novo created plant organs, called nodules. One of the key determinants of the successful interaction between these bacteria and plants are exopolysaccharides, which represent species-specific homo- and heteropolymers of different carbohydrate units frequently decorated by non-carbohydrate substituents. Exopolysaccharides are typically built from repeat units assembled by the Wzx/Wzy-dependent pathway, where individual subunits are synthesized in conjunction with the lipid anchor undecaprenylphosphate (und-PP), due to the activity of glycosyltransferases. Complete oligosaccharide repeat units are transferred to the periplasmic space by the activity of the Wzx flippase, and, while still being anchored in the membrane, they are joined by the polymerase Wzy. Here we have focused on the genetic control over the process of exopolysaccharides (EPS) biosynthesis in rhizobia, with emphasis put on the recent advancements in understanding the mode of action of the key proteins operating in the pathway. A role played by exopolysaccharide in Rhizobium–legume symbiosis, including recent data confirming the signaling function of EPS, is also discussed.
Agronomic Management for Enhancing Plant Tolerance to Abiotic Stresses—Drought, Salinity, Hypoxia, and Lodging
Authors: Mariani Luigi , Ferrante Antonio
Published: December 2017

Abiotic stresses are currently responsible for significant losses in quantity and reduction in quality of global crop productions. In consequence, resilience against such stresses is one of the key aims of farmers and is attained by adopting both suitable genotypes and management practices. This latter aspect was reviewed from an agronomic point of view, taking into account stresses due to drought, water excess, salinity, and lodging. For example, drought tolerance may be enhanced by using lower plant density, anticipating the sowing or transplant as much as possible, using grafting with tolerant rootstocks, and optimizing the control of weeds. Water excess or hypoxic conditions during winter and spring can be treated with nitrate fertilizers, which increase survival rate. Salinity stress of sensitive crops may be alleviated by maintaining water content close to the field capacity by frequent and low-volume irrigation. Lodging can be prevented by installing shelterbelts against dominant winds, adopting equilibrated nitrogen fertilization, choosing a suitable plant density, and optimizing the management of pests and biotic diseases harmful to the stability and mechanic resistance of stems and roots.
Correction: Nabeshima, Y., et al. Analysis of Japanese Articles about Suicides Involving Charcoal Burning or Hydrogen Sulfide Gas. Int. J. Environ. Res. Public Health 2016, 13, 1013
Authors: Nabeshima Yoshihiro , Onozuka Daisuke , Kitazono Takanari , Hagihara Akihito
Published: December 2017

We wish to make the following three corrections to the published paper [...]
Exposure to Night-Time Traffic Noise, Melatonin-Regulating Gene Variants and Change in Glycemia in Adults
Authors: Eze Ikenna , Imboden Medea , Foraster Maria , Schaffner Emmanuel , Kumar Ashish , Vienneau Danielle , Héritier Harris , Rudzik Franziska , Thiesse Laurie , Pieren Reto , Von Eckardstein Arnold , Schindler Christian , Brink Mark , Wunderli Jean-Marc , Cajochen Christian , Röösli Martin , Probst-Hensch Nicole
Published: December 2017

Traffic noise has been linked to diabetes, with limited understanding of its mechanisms. We hypothesize that night-time road traffic noise (RTN) may impair glucose homeostasis through circadian rhythm disturbances. We prospectively investigated the relationship between residential night-time RTN and subsequent eight-year change in glycosylated hemoglobin (ΔHbA1c) in 3350 participants of the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA), adjusting for diabetes risk factors and air pollution levels. Annual average RTN (Lnight) was assigned to participants in 2001 using validated Swiss noise models. HbA1c was measured in 2002 and 2011 using liquid chromatography. We applied mixed linear models to explore RTN–ΔHbA1c association and its modification by a genetic risk score of six common circadian-related MTNR1B variants (MGRS). A 10 dB difference in RTN was associated with a 0.02% (0.003–0.04%) increase in mean ΔHbA1c in 2142 non-movers. RTN–ΔHbA1c association was modified by MGRS among diabetic participants (Pinteraction = 0.001). A similar trend in non-diabetic participants was non-significant. Among the single variants, we observed strongest interactions with rs10830963, an acknowledged diabetes risk variant also implicated in melatonin profile dysregulation. Night-time RTN may impair glycemic control, especially in diabetic individuals, through circadian rhythm disturbances. Experimental sleep studies are needed to test whether noise control may help individuals to attain optimal glycemic levels.
Impact of Cost Efficiency on Bank Capital and the Cost of Financial Intermediation: Evidence from BRICS Countries
Authors: Rahman Mohammed , Ashraf Badar , Zheng Changjun , Begum Munni
Published: December 2017

Over last two decades, emerging and developing nations have desperately endeavored for efficient banking sectors. In this study, we argue that bank efficiency generates incentives that can impact banks’ capital holdings and the cost of financial intermediation. Analyzing a panel dataset of 1190 banks from BRICS (Brazil, Russia, India, China, South Africa) countries over the period 2007–2015, we find robust evidence that more efficient banks hold higher capital and charge lower financial intermediation costs. In an extended sample over the period 2000–2015, we observe that cost efficiency had a marginal positive impact on bank capital during the global financial crisis of 2007–2009. We also observe that on average, banks increased the cost of financial intermediation during the crisis, however, greater efficiency helped banks to not charge higher intermediation costs. Our results imply the beneficial impact of bank efficiency for bank stability and real economy.
Species Distribution Modeling: Comparison of Fixed and Mixed Effects Models Using INLA
Authors: Dutra Silva Lara , Brito de Azevedo Eduardo , Bento Elias Rui , Silva Luís
Published: December 2017

Invasive alien species are among the most important, least controlled, and least reversible of human impacts on the world’s ecosystems, with negative consequences affecting biodiversity and socioeconomic systems. Species distribution models have become a fundamental tool in assessing the potential spread of invasive species in face of their native counterparts. In this study we compared two different modeling techniques: (i) fixed effects models accounting for the effect of ecogeographical variables (EGVs); and (ii) mixed effects models including also a Gaussian random field (GRF) to model spatial correlation (Matérn covariance function). To estimate the potential distribution of Pittosporum undulatum and Morella faya (respectively, invasive and native trees), we used geo-referenced data of their distribution in Pico and São Miguel islands (Azores) and topographic, climatic and land use EGVs. Fixed effects models run with maximum likelihood or the INLA (Integrated Nested Laplace Approximation) approach provided very similar results, even when reducing the size of the presences data set. The addition of the GRF increased model adjustment (lower Deviance Information Criterion), particularly for the less abundant tree, M. faya. However, the random field parameters were clearly affected by sample size and species distribution pattern. A high degree of spatial autocorrelation was found and should be taken into account when modeling species distribution.
An Automatic K-Means Clustering Algorithm of GPS Data Combining a Novel Niche Genetic Algorithm with Noise and Density
Authors: Zhou Xiangbing , Gu Jianggang , Shen Shaopeng , Ma Hongjiang , Miao Fang , Zhang Hua , Gong Huaming
Published: December 2017

Rapidly growing Global Positioning System (GPS) data plays an important role in trajectory and their applications (e.g., GPS-enabled smart devices). In order to employ K-means to mine the better origins and destinations (OD) behind the GPS data and overcome its shortcomings including slowness of convergence, sensitivity to initial seeds selection, and getting stuck in a local optimum, this paper proposes and focuses on a novel niche genetic algorithm (NGA) with density and noise for K-means clustering (NoiseClust). In NoiseClust, an improved noise method and K-means++ are proposed to produce the initial population and capture higher quality seeds that can automatically determine the proper number of clusters, and also handle the different sizes and shapes of genes. A density-based method is presented to divide the number of niches, with its aim to maintain population diversity. Adaptive probabilities of crossover and mutation are also employed to prevent the convergence to a local optimum. Finally, the centers (the best chromosome) are obtained and then fed into the K-means as initial seeds to generate even higher quality clustering results by allowing the initial seeds to readjust as needed. Experimental results based on taxi GPS data sets demonstrate that NoiseClust has high performance and effectiveness, and easily mine the city’s situations in four taxi GPS data sets.
Transdisciplinary Foundations of Geospatial Data Science
Authors: Xie Yiqun , Eftelioglu Emre , Ali Reem , Tang Xun , Li Yan , Doshi Ruhi , Shekhar Shashi
Published: December 2017

Recent developments in data mining and machine learning approaches have brought lots of excitement in providing solutions for challenging tasks (e.g., computer vision). However, many approaches have limited interpretability, so their success and failure modes are difficult to understand and their scientific robustness is difficult to evaluate. Thus, there is an urgent need for better understanding of the scientific reasoning behind data mining and machine learning approaches. This requires taking a transdisciplinary view of data science and recognizing its foundations in mathematics, statistics, and computer science. Focusing on the geospatial domain, we apply this crucial transdisciplinary perspective to five common geospatial techniques (hotspot detection, colocation detection, prediction, outlier detection and teleconnection detection). We also describe challenges and opportunities for future advancement.
α-Glucosidase and Protein Tyrosine Phosphatase 1B Inhibitory Activity of Plastoquinones from Marine Brown Alga Sargassum serratifolium
Authors: Ali Md. , Kim Da , Seong Su , Kim Hyeung-Rak , Jung Hyun , Choi Jae
Published: December 2017

Sargassum serratifolium C. Agardh (Phaeophyceae, Fucales) is a marine brown alga that belongs to the family Sargassaceae. It is widely distributed throughout coastal areas of Korea and Japan. S. serratifolium has been found to contain high concentrations of plastoquinones, which have strong anti-cancer, anti-inflammatory, antioxidant, and neuroprotective activity. This study aims to investigate the anti-diabetic activity of S. serratifolium and its major constituents through inhibition of protein tyrosine phosphatase 1B (PTP1B), α-glucosidase, and ONOO−-mediated albumin nitration. S. serratifolium ethanolic extract and fractions exhibited broad PTP1B and α-glucosidase inhibitory activity (IC50, 1.83~7.04 and 3.16~24.16 µg/mL for PTP1B and α-glucosidase, respectively). In an attempt to identify bioactive compounds, three plastoquinones (sargahydroquinoic acid, sargachromenol and sargaquinoic acid) were isolated from the active n-hexane fraction of S. serratifolium. All three plastoquinones exhibited dose-dependent inhibitory activity against PTP1B in the IC50 range of 5.14–14.15 µM, while sargachromenol and sargaquinoic acid showed dose-dependent inhibitory activity against α-glucosidase (IC50 42.41 ± 3.09 and 96.17 ± 3.48 µM, respectively). In the kinetic study of PTP1B enzyme inhibition, sargahydroquinoic acid and sargaquinoic acid led to mixed-type inhibition, whereas sargachromenol displayed noncompetitive-type inhibition. Moreover, plastoquinones dose-dependently inhibited ONOO−-mediated albumin nitration. Docking simulations of these plastoquinones demonstrated negative binding energies and close proximity to residues in the binding pocket of PTP1B and α-glucosidase, indicating that these plastoquinones have high affinity and tight binding capacity towards the active site of the enzymes. These results demonstrate that S. serratifolium and its major plastoquinones may have the potential as functional food ingredients for the prevention and treatment of type 2 diabetes.
The Anti-Inflammatory Effect and Structure of EPCP1-2 from Crypthecodinium cohnii via Modulation of TLR4-NF-κB Pathways in LPS-Induced RAW 264.7 Cells
Authors: Ma Xiaolei , Xie Baolong , Du Jin , Zhang Aijun , Hao Jianan , Wang Shuxun , Wang Jing , Cao Junrui
Published: December 2017

Exopolysaccharide from Crypthecodinium cohnii (EPCP1-2) is a marine exopolysaccharide that evidences a variety of biological activities. We isolated a neutral polysaccharide from the fermentation liquid of Crypthecodinium cohnii (CP). In this study, a polysaccharide that is derived from Crypthecodinium cohnii were analyzed and its anti-inflammatory effect was evaluated on protein expression of toll-like receptor 4 and nuclear factor κB pathways in macrophages. The structural characteristics of EPCP1-2 were characterized by GC (gas chromatography) and GC-MS (gas Chromatography-Mass Spectrometer) analyses. The molecular weight was about 82.5 kDa. The main chain of EPCP1-2 consisted of (1→6)-linked mannopyranosyl, (1→6)-linked glucopyranosyl, branched-chain consisted of (1→3,6)-linked galactopyranosyl and terminal consisted of t-l-Rhapyranosyl. The in vitro anti-inflammatory activity was representated through assay of proliferation rate, pro-inflammatory factor (NO) and expressions of proteins on RAW 264.7, the macrophage cell line. The results revealed that EPCP1-2 exhibited significant anti-inflammatory activity by regulating the expression of toll-like receptor 4, mitogen-activated protein kinases, and Nuclear Factor-κB protein.
Antinociceptive Activity of Macaranga denticulata Muell. Arg. (Family: Euphorbiaceae): In Vivo and In Silico Studies
Authors: Hasanat Abul , Chowdhury Tanvir , Kabir Mohammad , Chowdhury Mohammed , Chy Md. , Barua Jackie , Chakrabarty Nishan , Paul Arkajyoti
Published: December 2017

Background: The present study was conducted to investigate the antinociceptive activity of methanol extract of Macaranga denticulata (Met.MD) in an animal model, followed by molecular docking analysis. Methods: Antinociceptive activity was determined by acetic acid-induced writhing and formalin-induced licking test in mice. Then, molecular docking study was performed to identify compounds having maximum activity against the COX-1 enzyme using Schrödinger Maestro (version 10.1) to determine docking fitness. Results: A preliminary phytochemical analysis of Met.MD revealed that it contained alkaloids, carbohydrates, phenols, flavonoids, tannins, and terpenoids. Met.MD exhibited a dose-dependent and statistically significant antinociceptive activity in the acetic acid and formalin test at the doses of 200 and 400 mg/kg. In addition, our docking study showed that macarangin had the best fitness score of −5.81 with COX-1 enzyme among six major compounds of M. denticulata. Conclusions: Results of the present study confirmed the potential antinociceptive activity of M. denticulata leaf extract in both in vivo and in silico models.