bluuebunny/crossref_metadata_2025 huggingface dataset:
Nilotinib: A Tyrosine Kinase Inhibitor Mediates Resistance to Intracellular Mycobacterium Via Regulating Autophagy
Authors: Hussain Tariq , Zhao Deming , Shah Syed Zahid Ali , Sabir Naveed , Wang Jie , Liao Yi , Song Yinjuan , Dong Haodi , Hussain Mangi Mazhar , Ni Jiamin , Yang Lifeng , Zhou Xiangmei
Published: May 2019

Nilotinib, a tyrosine kinase inhibitor, has been studied extensively in various tumor models; however, no information exists about the pharmacological action of nilotinib in bacterial infections. Mycobacterium bovis (M. bovis) and Mycobacterium avium subspecies paratuberculosis (MAP) are the etiological agents of bovine tuberculosis and Johne’s disease, respectively. Although M. bovis and MAP cause distinct tissue tropism, both of them infect, reside, and replicate in mononuclear phagocytic cells of the infected host. Autophagy is an innate immune defense mechanism for the control of intracellular bacteria, regulated by diverse signaling pathways. Here we demonstrated that nilotinib significantly inhibited the intracellular survival and growth of M. bovis and MAP in macrophages by modulating host immune responses. We showed that nilotinib induced autophagic degradation of intracellular mycobacterium occurred via the inhibition of PI3k/Akt/mTOR axis mediated by abelson (c-ABL) tyrosine kinase. In addition, we observed that nilotinib promoted ubiquitin accumulation around M. bovis through activation of E3 ubiquitin ligase parkin. From in-vivo experiments, we found that nilotinib effectively controlled M. bovis growth and survival through enhanced parkin activity in infected mice. Altogether, our data showed that nilotinib regulates protective innate immune responses against intracellular mycobacterium, both in-vitro and in-vivo, and can be exploited as a novel therapeutic remedy for the control of M. bovis and MAP infections.
E3 Ubiquitin Ligase TRIM Proteins, Cell Cycle and Mitosis
Authors: Venuto Santina , Merla Giuseppe
Published: May 2019

The cell cycle is a series of events by which cellular components are accurately segregated into daughter cells, principally controlled by the oscillating activities of cyclin-dependent kinases (CDKs) and their co-activators. In eukaryotes, DNA replication is confined to a discrete synthesis phase while chromosome segregation occurs during mitosis. During mitosis, the chromosomes are pulled into each of the two daughter cells by the coordination of spindle microtubules, kinetochores, centromeres, and chromatin. These four functional units tie chromosomes to the microtubules, send signals to the cells when the attachment is completed and the division can proceed, and withstand the force generated by pulling the chromosomes to either daughter cell. Protein ubiquitination is a post-translational modification that plays a central role in cellular homeostasis. E3 ubiquitin ligases mediate the transfer of ubiquitin to substrate proteins determining their fate. One of the largest subfamilies of E3 ubiquitin ligases is the family of the tripartite motif (TRIM) proteins, whose dysregulation is associated with a variety of cellular processes and directly involved in human diseases and cancer. In this review we summarize the current knowledge and emerging concepts about TRIMs and their contribution to the correct regulation of cell cycle, describing how TRIMs control the cell cycle transition phases and their involvement in the different functional units of the mitotic process, along with implications in cancer progression.
The Kansas City Transportation and Local-Scale Air Quality Study (KC-TRAQS): Integration of Low-Cost Sensors and Reference Grade Monitoring in a Complex Metropolitan Area. Part 1: Overview of the Project
Authors: Kimbrough Sue , Krabbe Stephen , Baldauf Richard , Barzyk Timothy , Brown Matthew , Brown Steven , Croghan Carry , Davis Michael , Deshmukh Parikshit , Duvall Rachelle , Feinberg Stephen , Isakov Vlad , Logan Russell , McArthur Tim , Shields Amy
Published: May 2019

Emissions from transportation sources can impact local air quality and contribute to adverse health effects. The Kansas City Transportation and Local-Scale Air Quality Study (KC-TRAQS), conducted over a 1-year period, researched emissions source characterization in the Argentine, Turner, and Armourdale, Kansas (KS) neighborhoods and the broader southeast Kansas City, KS area. This area is characterized as a near-source environment with impacts from large railyard operations, major roadways, and commercial and industrial facilities. The spatial and meteorological effects of particulate matter less than 2.5 µm (PM2.5), and black carbon (BC) pollutants on potential population exposures were evaluated at multiple sites using a combination of regulatory grade methods and instrumentation, low-cost sensors, citizen science, and mobile monitoring. The initial analysis of a subset of these data showed that mean reference grade PM2.5 concentrations (gravimetric) across all sites ranged from 7.92 to 9.34 µg/m3. Mean PM2.5 concentrations from low-cost sensors ranged from 3.30 to 5.94 µg/m3 (raw, uncorrected data). Pollution wind rose plots suggest that the sites are impacted by higher PM2.5 and BC concentrations when the winds originate near known source locations. Initial data analysis indicated that the observed PM2.5 and BC concentrations are driven by multiple air pollutant sources and meteorological effects. The KC-TRAQS overview and preliminary data analysis presented will provide a framework for forthcoming papers that will further characterize emission source attributions and estimate near-source exposures. This information will ultimately inform and clarify the extent and impact of air pollutants in the Kansas City area.
Attitudes of Farmers and Rural Area Residents Toward Climate Change Adaptation Measures: Their Preferences and Determinants of Their Attitudes
Authors: Baba Kenshi , Tanaka Mitsuru
Published: May 2019

In this study, data obtained from an online survey were analyzed to identify the perception gap between farmers and nonfarmers (rural area residents) toward climate change adaptation measures with conventional and new elements of the psychological mechanism. Key findings from the study were as follows. First, the perception of climate change risk and awareness of impacts of climate change had strong effects on the preferences for and willingness to participate in measures rather than trusting the government and values pertaining to the policy decision-making process. Second, farmers tended to prefer “protection” and “transfer of risks (insurance)” as climate change adaptation measures more than nonfarmers did. Farmers also tended to be unwilling to participate in “withdrawal”, reflecting the difficulty of relocating agricultural land. Third, farmers’ willingness to participate in climate change adaptation measures was determined strongly by their preferences. Therefore, to increase preference, there needs to be communication about multiple risks including climate change risks associated with not only “adjustment” and “protection”, which tend to be preferred, but also “withdrawal”, which tends to not be preferred. Contrasting with these, nonfarmers tended to prefer any particular climate change adaptation measures statistically-significantly, but they tended to be willing to accept “self-help” absolutely and “withdrawal” relatively. Also, farmers’ willingness to participate in climate change adaptation measures was determined strongly by their preference. One of the ways to increase the preference is communicating about the multiple risks including climate change risks associated with “adjustment,” “protection” and “transfer” which tend to be preferred more than nonfarmers did. Finally, trust in the government and values pertaining to the policy decision-making process did not necessarily have a serious impact on policy preferences and willingness to participate, both for farmers and nonfarmers. More analyses for other sectors will be needed for further study.
A Statistical Method for Determining Optical and Geometrical Characteristics of Cirrus Clouds
Authors: Nellore Manoj Kumar , Kannan Venkatramanan , Vellaisamy Arul Lenus Roy
Published: May 2019

Altitude occurrences of cirrus clouds, their base, mid, and top heights are identified by using a powerful statistical approach called the Variance Centroid Method (VCM). This method is effective in determining the geometrical properties of cirrus clouds at a height range of 8 km to 20 km. This statistical method provides in-depth information on Generation Circulation Models (GCM’s) because of its significant role in the radiative balance of the earth’s atmosphere. The output related to geometrical and optical properties of cirrus clouds obtained from this statistical method for the years 2014 and 2015 are studied. Altitude distributions of base, mid, top, and thickness of tropical cirrus clouds are analyzed in terms of percentage occurrences. For the year 2014, it was found that 14.8%, 75.2%, and 9.9% of cirrus clouds were sub-visual, thin, and thick clouds and for the year 2015, 71.2% and 28.7% of cirrus clouds were found to be thin and thick clouds, and sub-visual types of clouds were not observed. The interdependence of optical depth with the depolarization ratio is discussed and it is observed that the correlation is negative (−0.0303) for the year 2014 and positive (0.1311) for the year 2015. High optical depths with values from 0.502 to 0.849 are observed in the height regions from 9 km to 15 km (for 2014) and for the year 2015, the observed value ranges from 0.514 to 0.822 for the height regions from 9 km to 11 km. Statistical variation of characteristics of tropical cirrus clouds is presented for the period of study. The characterization of these cirrus clouds is highly useful for climate modeling studies, and their impact plays a vital role in the Earth’s radiation budget at the top of the atmosphere.
Effect of Heating Treatment on the Microstructure and Properties of Cr–Mo Duplex-Alloyed Coating Prepared by Double Glow Plasma Surface Alloying
Authors: Hu Jianjun , Wang Jing , Jiang Jie , Yang Xian , Xu Hongbin , Li Hui , Guo Ning
Published: May 2019

In this study, Cr–Mo duplex-alloyed coating was prepared on carbon steel by double glow plasma surface alloying (DGPSA). The effect of annealing and quenching and tempering (Q&T) treatments on the microstructure and performance of the coating was investigated by X-ray diffraction (XRD), energy dispersive spectrometry (EDS), backscattering electron imaging (BSEI) and electron backscattering diffraction (EBSD) techniques. The results show that a gradient structured coating composed of an Fe–Cr–Mo solid solution (Fe–Cr–Mo SS) layer and an alloyed pearlite layer was obtained on the steel surface. The affected layer was adjacent to the coating. After annealing or Q&T, more carbides precipitated in the Fe–Cr–Mo SS layer and alloyed pearlite layer. Most of the C atoms in the subsurface were dragged into the coating to form carbides in the Fe–Cr–Mo SS and alloyed pearlite layers of the coating, transforming the affected layers into a carbon-poor zone. Annealing and Q&T hardly modified the thickness of the coating, but greatly changed the hardness and corrosion resistance of the coating. The Q&T treated samples had higher hardness and better corrosion resistance than the as-DGPSA treated and the annealed samples.
Microstructure and Mechanical Property Investigation of TaSiN Thin Films Deposited by Reactive Magnetron Sputtering
Authors: Zaman Anna , Shen Yi , Meletis Efstathios I.
Published: May 2019

Tantalum silicon nitride (Ta–Si–N) films were synthesized on Si substrate via magnetron sputtering. The structure and properties of the Ta–Si–N films were investigated as a function of the N2 content in the N2/Ar gas mixture. Increasing the N2 percentage in the gas mixture from 7% to 20% changed the film structure from textured hexagonal (hex) Ta2N to nontextured hex Ta2N to a mixture of face-centered cubic (fcc) TaN and hex Ta2N, and finally to fcc TaN. X-ray photoelectron spectroscopy showed Ta–N and Si–N bonds in the films. The film microstructure was found to change from columnar morphology with visible amorphous boundaries (at 13% N2) to columnar morphology with absence of amorphous boundaries (at 15% N2). Increasing N2 content increased hardness in the films with those deposited with 13–15% N2 displaying the highest hardness of ~40 ± 2 GPa. In addition, the 13% N2 films showed a ratio of H/E* > 0.11, elastic recovery of ~60%, low coefficient of friction of 0.6, reduced wear rate (7.09 × 10−6 mm3/N·m), and remained thermally stable up to 800 °C. The results suggest that the Ta–Si–N films have high potential as hard tribological nanocomposite coatings.
Protective Performance of Zn-Al-Mg-TiO2 Coating Prepared by Cold Spraying on Marine Steel Equipment
Authors: Wang Kunkun , Wang Shouren , Xiong Tianying , Wen Daosheng , Wang Gaoqi , Liu Wentao , Du Hao
Published: May 2019

According to research, we have learned that zinc has excellent cathodic protection performance, that the corrosion products of aluminum and magnesium can form dense and stable passivation films to protect internal materials of coatings, and that TiO2 has excellent photocatalytic self-cleaning performance which will form a physical adsorption film on the surface to isolate the external corrosion solution. In this paper, a Zn-Al-Mg-TiO2 pseudo alloy coating was prepared by cold spray technique on a Q235 substrate. The protective performance of Zn-Al-Mg-TiO2 for marine metal equipment was studied using dynamic salt water corrosion testing, electrochemical testing, and friction and wear testing. The microstructure, composition, and wear marks of coatings were observed using a scanning electron microscope (SEM), energy dispersive spectrometer (EDS), and white-light interferometer. The results show that the Zn-Al-Mg-TiO2 coating has excellent corrosion and wear resistance, which can provide long-term and stable protection for the substrate.
Molecular Dynamics Study on the Tribological Properties of Phosphorene/Polyethylene Composites
Authors: Peng Yong , Li Jiahao , Tang Xianqiong , Yang Wei , Chen Xuanzhen , Fan Chaojie , Wang Kui
Published: May 2019

This study aimed to investigate the mechanism of phosphorene in enhancing the friction behaviors of polyethylene using molecular dynamics. A sliding model was constructed to investigate the coefficient of friction and abrasion rate of composites by applying a tangential velocity on a rigid tip. Both the size and number of layers of phosphorene had positive effects on the friction force of composites but through different mechanisms. The former was because the interaction between phosphorene and polyethylene increased with the size of phosphorene, while the latter was through influencing the thermal transport across phosphorene and polyethylene interfaces. The rate of improvement decreased with the increased layer number of phosphorene due to the fact that the phosphorene tended to congregate together and thus formed multi-layer agglomerates. The friction behavior of the composites was highly anisotropic because of the high divergence of potential-energy on the phosphorene surface. These findings have provided insights into enhancing the friction behavior of polymer filled by phosphorene.
The Role of Substrate Temperature and Magnetic Filtering for DLC by Cathodic Arc Evaporation
Authors: Lux Helge , Edling Matthias , Lucci Massimiliano , Kitzmann Julia , Villringer Claus , Siemroth Peter , De Matteis Fabio , Schrader Sigurd
Published: May 2019

Diamond-like carbon (DLC) films were deposited using two different types of high current arc evaporation. The first process used a magnetic particle filter to remove droplets from the plasma. For the second process, the samples were put into a metallic cage which was placed directly above the plasma source. For both processes, we varied the substrate temperature from 21 to 350 °C in order to investigate the temperature effect. The samples were characterized using SEM, AFM, XPS, Raman Spectroscopy, Ellipsometry, Photometry, and Nano Indentation in order to compare both methods of deposition and provide a careful characterization of such DLC films. We found that the sp3 content and the hardness can be precisely adjusted by changing the substrate temperature. Furthermore, in the case of unfiltered deposition, the optical constants can be shifted in the direction of higher absorbance in order to produce black and hard carbon coatings.
A Sparse Analysis-Based Single Image Super-Resolution
Authors: Anari Vahid , Razzazi Farbod , Amirfattahi Rasoul
Published: May 2019

In the current study, we were inspired by sparse analysis signal representation theory to propose a novel single-image super-resolution method termed “sparse analysis-based super resolution” (SASR). This study presents and demonstrates mapping between low and high resolution images using a coupled sparse analysis operator learning method to reconstruct high resolution (HR) images. We further show that the proposed method selects more informative high and low resolution (LR) learning patches based on image texture complexity to train high and low resolution operators more efficiently. The coupled high and low resolution operators are used for high resolution image reconstruction at a low computational complexity cost. The experimental results for quantitative criteria peak signal to noise ratio (PSNR), root mean square error (RMSE), structural similarity index (SSIM) and elapsed time, human observation as a qualitative measure, and computational complexity verify the improvements offered by the proposed SASR algorithm.
Improved Measures of Redundancy and Relevance for mRMR Feature Selection
Authors: Jo Insik , Lee Sangbum , Oh Sejong
Published: May 2019

Many biological or medical data have numerous features. Feature selection is one of the data preprocessing steps that can remove the noise from data as well as save the computing time when the dataset has several hundred thousand or more features. Another goal of feature selection is improving the classification accuracy in machine learning tasks. Minimum Redundancy Maximum Relevance (mRMR) is a well-known feature selection algorithm that selects features by calculating redundancy between features and relevance between features and class vector. mRMR adopts mutual information theory to measure redundancy and relevance. In this research, we propose a method to improve the performance of mRMR feature selection. We apply Pearson’s correlation coefficient as a measure of redundancy and R-value as a measure of relevance. To compare original mRMR and the proposed method, features were selected using both of two methods from various datasets, and then we performed a classification test. The classification accuracy was used as a measure of performance comparison. In many cases, the proposed method showed higher accuracy than original mRMR.
Recent Advances in Adaptive Liquid Crystal Lenses
Authors: Algorri José Francisco , Zografopoulos Dimitrios C. , Urruchi Virginia , Sánchez-Pena José Manuel
Published: May 2019

An adaptive-focus lens is a device that is capable of tuning its focal length by means of an external stimulus. Numerous techniques for the demonstration of such devices have been reported thus far. Moving beyond traditional solutions, several new approaches have been proposed in recent years based on the use of liquid crystals, which can have a great impact in emerging applications. This work focuses on the recent advances in liquid crystal lenses with diameters larger than 1 mm. Recent demonstrations and their performance characteristics are reviewed, discussing the advantages and disadvantages of the reported technologies and identifying the challenges and future prospects in the active research field of adaptive-focus liquid crystal (LC) lenses.
Effect of Site Attributes and Matrix Composition on Neotropical Primate Species Richness and Functional Traits: A Comparison Among Regions
Authors: Calle-Rendón Bayron R. , Hilário Renato R. , de Toledo José Julio
Published: May 2019

Fragmentation threatens biodiversity and forest-dwelling animals can be especially vulnerable. Neotropical primates inhabit forests and play ecological roles in maintaining forest biodiversity. Currently, many primate communities are restricted to forest fragments. We (1) evaluated the influence of environmental, matrix, and site attributes on species richness and functional traits of primates in the Neotropics; and (2) evaluated the effect of the sub-region on the relationships between primates and environmental, matrix, and site attributes. We conducted literature searches to find published data on primate communities in forest fragments throughout the Neotropics. Each fragment was assigned to 1 of 11 sub-regions: Mesoamerica, Tumbes-Chocó-Magdalena, Caribbean, Orinoco, Amazon, Atlantic Forest, Cerrado, Chaco, Andes, Caatinga, and Pampa. Based on actual and expected species occurrences, we calculated the proportion of primate species retained in the fragments, the mass retained, and dietary items retained considering reproductive and vegetative plant parts and prey. We used linear mixed models to correlate primate variables with environmental, matrix, and site attributes. Fragment area was more important for primate retention than environmental, matrix, and site attributes, with primate retention being higher in larger fragments. Fragment size was positively correlated with all primate variables, except for retention of prey consumption, whose retention decreased as water bodies and density of buildings in the matrix increased. Fragments within protected areas retained larger species than unprotected fragments. The proportion of extant mass retained and vegetative plant parts in the diet were highest in Mesoamerica and lowest in the Atlantic Forest. Conservation planning of Neotropical primates should consider both the differences among sub-regions, forest restoration to increase fragment size, and the creation of new protected areas, even in fragmented landscapes.
The Importance of Isotopic Turnover for Understanding Key Aspects of Animal Ecology and Nutrition
Authors: Carter Wales A. , Bauchinger Ulf , McWilliams Scott R.
Published: May 2019

Stable isotope-based methods have proved to be immensely valuable for ecological studies ranging in focus from animal movements to species interactions and community structure. Nevertheless, the use of these methods is dependent on assumptions about the incorporation and turnover of isotopes within animal tissues, which are oftentimes not explicitly acknowledged and vetted. Thus, the purpose of this review is to provide an overview of the estimation of stable isotope turnover rates in animals, and to highlight the importance of these estimates for ecological studies in terrestrial, freshwater, and marine systems that may use a wide range of stable isotopes. Specifically, we discuss 1) the factors that contribute to variation in turnover among individuals and across species, which influences the use of stable isotopes for diet reconstructions, 2) the differences in turnover among tissues that underlie so-called ‘isotopic clocks’, which are used to estimate the timing of dietary shifts, and 3) the use of turnover rates to estimate nutritional requirements and reconstruct histories of nutritional stress from tissue isotope signatures. As we discuss these topics, we highlight recent works that have effectively used estimates of turnover to design and execute informative ecological studies. Our concluding remarks suggest several steps that will improve our understanding of isotopic turnover and support its integration into a wider range of ecological studies.
Electrochemical Methodology for Evaluating Skin Oxidative Stress Status (SOSS)
Authors: Joël Pincemail , Mouna-Messaouda Kaci , Jean-Paul Cheramy-Bien , Jean-Olivier Defraigne , Smail Meziane
Published: May 2019

For the purpose of human disease prevention, several methods have been developed, and are still developing, to assess the oxidative stress status (OSS) of individuals. In the present paper, we describe an approach based on electrochemical detection able to evaluate skin oxidative stress status (SOSS) as a PAOT (Pouvoir AntiOxydant Total)-Skin Score®. Normal reference values for the PAOT-Skin Score® were: 0–62.94 (n = 263). Intra- and inter-assay coefficients of variation were, respectively, 12.47 ± 4.29% and 7.0 ± 2.5%. Our technology showed increased skin antioxidant activity following topical application of reduced coeznyme Q10 cream or vitamin C intake as orange juice or supplements. Moreover, we found significant correlations between some blood oxidative stress biomarkers and the PAOT-Skin Score® (γ-tocopherol/α-tocopherol ratio (r = 0.43, p = 0.020); copper (r = −0.42, p = 0.022); copper/zinc ratio (r = −0.49, p = 0.006), and lipid peroxides (r = −0.43, p = 0.002)). In addition to being non–invasive, the present electrochemical methodology is also not expensive, fast, and easy to use.
A SOM-Based Membrane Optimization Algorithm for Community Detection
Authors: Liu Chuang , Du Yingkui , Lei Jiahao
Published: May 2019

The real world is full of rich and valuable complex networks. Community structure is an important feature in complex networks, which makes possible the discovery of some structure or hidden related information for an in-depth study of complex network structures and functional characteristics. Aimed at community detection in complex networks, this paper proposed a membrane algorithm based on a self-organizing map (SOM) network. Firstly, community detection was transformed as discrete optimization problems by selecting the optimization function. Secondly, three elements of the membrane algorithm, objects, reaction rules, and membrane structure were designed to analyze the properties and characteristics of the community structure. Thirdly, a SOM was employed to determine the number of membranes by learning and mining the structure of the current objects in the decision space, which is beneficial to guiding the local and global search of the proposed algorithm by constructing the neighborhood relationship. Finally, the simulation experiment was carried out on both synthetic benchmark networks and four real-world networks. The experiment proved that the proposed algorithm had higher accuracy, stability, and execution efficiency, compared with the results of other experimental algorithms.
On the Exact Variance of Tsallis Entanglement Entropy in a Random Pure State
Authors: Wei Lu
Published: May 2019

The Tsallis entropy is a useful one-parameter generalization to the standard von Neumann entropy in quantum information theory. In this work, we study the variance of the Tsallis entropy of bipartite quantum systems in a random pure state. The main result is an exact variance formula of the Tsallis entropy that involves finite sums of some terminating hypergeometric functions. In the special cases of quadratic entropy and small subsystem dimensions, the main result is further simplified to explicit variance expressions. As a byproduct, we find an independent proof of the recently proven variance formula of the von Neumann entropy based on the derived moment relation to the Tsallis entropy.
EduSciFIT: A Computer-Based Blended and Scaffolding Toolbox to Support Numerical Concepts for Flipped Science Education
Authors: González-Gómez David , Jeong Jin Su
Published: May 2019

In education, the use of information, computers, and the Internet as a form of blended technology has been receiving increased attention and consideration. Additionally, increasing attention is being paid toward a scaffolding mechanism that can be integrated into science classrooms in order to solve technological challenges. This work describes a computer-based blended and scaffolding learning toolbox to support numerical concepts for flipped science education, particularly one which is developed and implemented in a MATLAB environment and framed in Adobe Captivate 6 as a HTML5-based e-Learning application, which can be used for science laboratory exercises. This toolbox, named SciEduFIT, is one of the blended and scaffolding learning systems available for use in science education. Through this toolbox, students can acquire the skills to establish the numerical concepts in a flipped science classroom. A survey was conducted to measure the suitability of the proposed toolbox, specifically A to E screens of SciEduFIT. The positive results of the survey indicate that this novel toolbox should be introduced into science classrooms in order to supplement other existing tools currently in use in the area of flipped science education. Therefore, the research shows a general positive perception of the toolbox and highlights the feasibility of the toolbox to achieve significant science learning.
Time Series Analysis to Predict End-to-End Quality of Wireless Community Networks
Authors: Millan Pere , Aliagas Carles , Molina Carlos , Dimogerontakis Emmanouil , Meseguer Roc
Published: May 2019

Community Networks have been around us for decades being initially deployed in the USA and Europe. They were designed by individuals to provide open and free “do it yourself” Internet access to other individuals in the same community and geographic area. In recent years, they have evolved as a viable solution to provide Internet access in developing countries and rural areas. Their social impact is measurable, as the community is provided with the right and opportunity of communication. Community networks combine wired and wireless links, and the nature of the wireless medium is unreliable. This poses several challenges to the routing protocol. For instance, Link-State routing protocols deal with End-to-End Quality tracking to select paths that maximize the delivery rate and minimize traffic congestion. In this work, we focused on End-to-End Quality prediction by means of time-series analysis to foresee which paths are more likely to change their quality. We show that it is possible to accurately predict End-to-End Quality with a small Mean Absolute Error in the routing layer of large-scale, distributed, and decentralized networks. In particular, we analyzed the path ETX behavior and properties to better identify the best prediction algorithm. We also analyzed the End-to-End Quality prediction accuracy some steps ahead in the future, as well as its dependency on the hour of the day. Besides, we quantified the computational cost of the prediction. Finally, we evaluated the impact of the usage for routing of our approach versus a simplified OLSR (ETX + Dijkstra) on an overloaded network.
A Low-Cost, High-Precision Method for Ripple Voltage Measurement Using a DAC and Comparators
Authors: Liu Jincheng , Yue Jiguang , Wang Li , Wu Chenhao , Lyu Feng
Published: May 2019

As the core of electronic system, the switched-mode power supply (SMPS) will lead to serious accidents and catastrophes if it suddenly fails. According to the related research, the monitoring of ripple can acquire the health degree of SMPS indirectly. To realize low-cost, high-precision, and automatic ripple measurement, this paper proposes a new ripple voltage (peak-to-peak value) measuring scheme, utilizing a DAC and two high-speed comparators. Within this scheme, the DC component of SMPS output is blocked by a high-pass filter (HPF). Then, the filtered signal and the reference voltage from a DAC together compose the input of a high-speed comparator. Finally, output pulses of the comparator are captured by a microcontroller unit (MCU), which readjusts the output of the DAC by calculation, and this process is repeated until the DAC output is exactly equal to the peak (or valley) value of ripple. Moreover, in order to accelerate the measurement process, a peak estimation method is specially designed to calculate the output ripple peak (or valley) value of buck topology through merely two measurements. Then the binary search method is utilized to obtain a more exact value on the basis of estimative results. Additionally, an analysis of the measurement error of this ripple measurement system is executed, which shows that the theoretical error is less than 0.5% where the ripple value is larger than 500 mV. Furthermore, appropriate components are selected, and a prototype is manufactured to verify the validity of the proposed theory.
Jet Features: Hardware-Friendly, Learned Convolutional Kernels for High-Speed Image Classification
Authors: Simons Taylor , Lee Dah-Jye
Published: May 2019

This paper explores a set of learned convolutional kernels which we call Jet Features. Jet Features are efficient to compute in software, easy to implement in hardware and perform well on visual inspection tasks. Because Jet Features can be learned, they can be used in machine learning algorithms. Using Jet Features, we make significant improvements on our previous work, the Evolution Constructed Features (ECO Features) algorithm. Not only do we gain a 3.7× speedup in software without loosing any accuracy on the CIFAR-10 and MNIST datasets, but Jet Features also allow us to implement the algorithm in an FPGA using only a fraction of its resources. We hope to apply the benefits of Jet Features to Convolutional Neural Networks in the future.
EEkNN: k-Nearest Neighbor Classifier with an Evidential Editing Procedure for Training Samples
Authors: Jiao Lianmeng , Geng Xiaojiao , Pan Quan
Published: May 2019

The k-nearest neighbor (kNN) rule is one of the most popular classification algorithms applied in many fields because it is very simple to understand and easy to design. However, one of the major problems encountered in using the kNN rule is that all of the training samples are considered equally important in the assignment of the class label to the query pattern. In this paper, an evidential editing version of the kNN rule is developed within the framework of belief function theory. The proposal is composed of two procedures. An evidential editing procedure is first proposed to reassign the original training samples with new labels represented by an evidential membership structure, which provides a general representation model regarding the class membership of the training samples. After editing, a classification procedure specifically designed for evidently edited training samples is developed in the belief function framework to handle the more general situation in which the edited training samples are assigned dependent evidential labels. Three synthetic datasets and six real datasets collected from various fields were used to evaluate the performance of the proposed method. The reported results show that the proposal achieves better performance than other considered kNN-based methods, especially for datasets with high imprecision ratios.
Accelerometer-Based Gyroscope Drift Compensation Approach in a Dual-Axial Stabilization Platform
Authors: Li Shutong , Gao Yanbin , Meng Gong , Wang Gang , Guan Lianwu
Published: May 2019

An accelerometer-based gyro drift compensation approach in a dual-axial stabilization platform is introduced in this paper. The stabilization platform consists of platform framework, drive motor, gyro and accelerometer module and contorl board. Gyro is an angular rate detecting element to achieve angular rate and rotation angle of the dynamic platform system. However, the platform system has an unstable factor because of the drift of gyro. The main contribution of this paper is to implement a convenient gyro drift compensation approach by using the accelerometer. In contrast to a kalman filtering method, this approach is simpler and practical due to the high-precision characteristic of the accelerometer. Data filtering algorithm and limit of threshold setting of total acceleration values are applied in this approach. The validity and feasibility of the proposed approach are evaluated by four tests under various conditions.
Effects of the Heat Treatment in the Properties of Fibrous Aerogel Thermal Insulation
Authors: Lakatos Ákos , Csík Attila , Trník Anton , Budai István
Published: May 2019

Nowadays, besides the use of conventional insulations (plastic foams and wool materials), aerogels are one of the most promising thermal insulation materials. As one of the lightest solid materials available today, aerogels are manufactured through the combination of a polymer with a solvent, forming a gel. For buildings, the fiber-reinforced types are mainly used. In this paper, the changes both in the thermal performance and the material structure of the aerogel blanket are followed after thermal annealing. The samples are put under isothermal heat treatments at 70 °C for weeks, as well as at higher temperatures (up to 210 °C) for one day. The changes in the sorption properties that result from the annealing are presented. Furthermore, the changes in the thermal conductivity are followed by a Holometrix Lambda heat flow meter. The changes in the structure and surface of the material due to the heat treatment are investigated by X-ray diffraction and with scanning electron microscopy. Besides, the above-mentioned measurement results of differential scanning calorimetry experiments are also presented. As a result of using equipment from different laboratories that support each other, we found that the samples go through structural changes after undergoing thermal annealing. We manifested that the aerogel granules separate down from the glass fibers and grow up. This phenomenon might be responsible for the change in the thermal conductivity of the samples.
Solar Still Efficiency Enhancement by Using Graphene Oxide/Paraffin Nano-PCM
Authors: Safaei Mohammad Reza , Goshayeshi Hamid Reza , Chaer Issa
Published: May 2019

Solar-driven water desalination technologies are rapidly developing with various links to other renewable sources. However, the efficiency of such systems severely depends on the design parameters. The present study focused on using graphene oxide (GO) with the Φ = 0.2, 0.4 and 0.6 wt.% dispersed in paraffin, as phase-change materials (PCMs), to improve the productivity of a solar still for desalination applications. The outcomes showed that by adding more graphene oxide to paraffin, the melting temperature got reduced. Solar still with GO/paraffin showed 25% productivity improvement in comparison with the solar still with only PCM. The obtained Nusselt number during the melting time also represented that free convection heat transfer into the melted region of the solar still has been enhanced by adding dispersed GO to the PCM, compared to the base paraffin. Also, increasing the hot wall temperature augments the Nusselt number. Finally, an empirical equation was derived to correlate the average Nusselt number as a function of Rayleigh number (Ra), the Stefan number (Ste), the subcooling factor (Sb), and the Fourier number (Fo). The obtained correlation depicted that Nusselt number enhancement has a reverse relation with Fourier number.
Recognition and Classification of Incipient Cable Failures Based on Variational Mode Decomposition and a Convolutional Neural Network
Authors: Deng Jiaying , Zhang Wenhai , Yang Xiaomei
Published: May 2019

To avoid power supply hazards caused by cable failures, this paper presents an approach of incipient cable failure recognition and classification based on variational mode decomposition (VMD) and a convolutional neural network (CNN). By using VMD, the original current signal is decomposed into seven modes with different center frequencies. Then, 42 features are extracted for the seven modes and used to construct a feature vector as input of the CNN to classify incipient cable failure through deep learning. Compared with using the original signals directly as the CNN input, the proposed approach is more efficient and robust. Experiments on different classifiers, namely, the decision tree (DT), K-nearest neighbor (KNN), BP neural network (BP) and support vector machine (SVM), and show that the CNN outperforms the other classifiers in terms of accuracy.
Multi-Input Ćuk-Derived Buck-Boost Voltage Source Inverter for Photovoltaic Systems in Microgrid Applications
Authors: Abdeen Eltaib , Gaafar Mahmoud A. , Orabi Mohamed , Ahmed Emad M. , El Aroudi Abdelali
Published: May 2019

This paper presents a multi-input Ćuk-derived Buck-Boost voltage source inverter (CBBVSI) for Photovoltaic (PV) systems. The proposed topology consists of a single-stage DC-AC inverter that combines both DC-DC and DC-AC stages. The DC-DC stage is used for stepping-up the voltage from the PV generator. Simultaneously, the DC-AC stage is used for interfacing the PV source with the AC grid. The topology allows three sources to utilize the antiparallel diodes for each inverter leg for transferring the energy. The proposed system exhibits several features such as a reduction of the number of components compared to typical two-stage structures, and Split-Source Inverter (SSI), and Z-Source Inverter (ZSI) topologies. Moreover, the power of each PV source can be harvested either simultaneously or separately since independent Maximum Power Point Tracking (MPPT) is performed. The system was simulated using MATLAB/SIMULINK software and a 1 kW laboratory prototype was implemented to verify the operation of the proposed CBBVSI. The numerical simulations are presented together with the experimental results, showing a good agreement.
Research Insights and Knowledge Headways for Developing Remote, Off-Grid Microgrids in Developing Countries
Authors: Chatterjee Abhi , Burmester Daniel , Brent Alan , Rayudu Ramesh
Published: May 2019

Recent reports from international energy agencies indicate that more than a billion of the population in the world is deprived of basic electricity provisions, confined mainly to the remote communities of developing nations. Microgrids are promoted as a potential technology for electricity provisions to off-grid rural communities, but have failed to reach their value proposition in the context of rural electrification access. In view of the rampant rural electrification issues, the objective of this paper is to furnish an understanding of, and advance the knowledge into, methods to facilitate the design and development of microgrid systems for remote communities in developing countries. The methodology involves an integrative review process of an annotated bibliography to summarise past empirical or theoretical literature. As such, this research is based on evaluation attributes, and identifies the challenges and barriers for remote microgrids through an analysis of 19 case studies. The paper concludes by proposing key aspects that need to be considered for developing a framework to improve the sustainability of electricity provisions for off-grid rural communities in developing countries.
Energy Management Strategies for Hybrid Construction Machinery: Evolution, Classification, Comparison and Future Trends
Authors: Zhang Wei , Wang Jixin , Du Shaofeng , Ma Hongfeng , Zhao Wenjun , Li Haojie
Published: May 2019

Hybrid Construction Machinery (HCM), known as an effective and crucial solution for the issues of environment pollution and energy shortage, has aroused increasing attention from manufacturers and researchers. A suitable energy management strategy is the vital technology to determine the energy saving and emission reduction performance of HCM. In the present paper, the difference between construction machinery and automobiles is first analyzed from the perspective of configuration, and the energy-based HCM configuration classification method is introduced and analyzed. Second, the development of HCM energy management strategy is reviewed along with relevant references, and the HCM energy management strategies are classified and summarized. In the meantime, the characteristics of each strategy are compared and analyzed, and the application of HCM energy management strategy is analyzed based on the relevant research results. Lastly, the state, challenges facing and the trend of HCM energy management strategy are analyzed on the levels of theory, manufacturer and market. According to the analysis, though progress has been achieved in energy management technology of HCM driven by market and policy, many challenges and problems remain in the electrification and intellectualization of HCM and the testing, application and improvement of the strategy. The contribution of this paper can be identified in three points: First, it can be referenced to solve relevant engineering problems. Second, it lays the foundation for the proposal of new ideas. Third, it highlights the state-of-the-art trends and avoids what has already been done.
Analysis of Research Topics and Scientific Collaborations in Energy Saving Using Bibliometric Techniques and Community Detection
Authors: de la Cruz-Lovera Carmen , Perea-Moreno Alberto-Jesus , de la Cruz-Fernández José Luis , G. Montoya Francisco , Alcayde Alfredo , Manzano-Agugliaro Francisco
Published: May 2019

Concern about everything related to energy is increasingly latent in the world and therefore the use of energy saving concepts has been increasing over the past several years. The interest in the subject has allowed a conceptual evolution in the scientific community regarding the understanding of the adequate use of energy. The objective of this work is to determine the contribution made by international institutions to the specialized publications in the area of energy-saving from 1939 to 2018, using Scopus Database API Interface. The methodology followed in this research was to perform a bibliometric analysis of the whole scientific production indexed in Scopus. The world’s scientific production has been analysed in the following domains: First the trend over time, types of publications and countries, second, the main subjects and keywords, third, main institutions and their main topics, and fourth, the main journals and proceedings that publish on this topic. Then, these data are presented using community detection algorithms and graph visualization software. With these techniques, it is possible to determine the main areas of research activity as well as to identify the structures of the collaboration network in the field of renewable energy. The results of the work show that the literature in this field have substantially increased during the last 10 years.