bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of Geometric Parameters of Longitudinal-Connected Air Suspension Based on a Double-Loop Multi-Objective Particle Swarm Optimization Algorithm
Authors: Chen Yikai , Huang Sen , Davis Lloyd , Du Haiping , Shi Qin , He Jie , Wang Qiang , Hu Wenting
Published: August 2018

Longitudinal-connected air suspension has been proven to have desirable dynamic load-sharing performances for multi-axle heavy vehicles. However, optimization approaches towards the improvement of comprehensive vehicle performance through the geometric design of longitudinal-connected air suspension have been considerably lacking. To address this, based on a 5-degrees-of-freedom nonlinear model of a three-axle semi-trailer with longitudinal air suspension, taking the changes of driving conditions (road roughness, speed, and load) into account, a height control strategy of the longitudinal-connected air suspension was proposed. Then, in view of the height of the air spring under various driving conditions, the support vector regression method was employed to fit the relationship models between the performance indices and the driving conditions, as well as the suspension geometric parameters (inside diameters of the air line and the connectors). Finally, to tackle the uncertainties of driving conditions in the optimization of suspension geometric parameters, a double-loop multi-objective particle swarm optimization algorithm (DL-MOPSO) was put forward based on the interval uncertainty theory. The simulation results indicate that compared with the longitudinal-connected air suspension using two traditional geometric parameters, the optimization ratios for dynamic load sharing coefficient and root-mean-square acceleration at various spring heights are between −1.04% and 20.75%, and 1.44% and 35.1%, respectively. Therefore, based on the signals measured from the suspension height sensors, through integrated control of inflation/deflation valves of air suspensions, as well as the valves’ inside connectors and air lines, the proposed DL-MOPSO algorithm can improve the comprehensive driving performance of the longitudinal-connected three-axle semi-trailer effectively, and in response to changes in driving conditions.
Microemulsion Encapsulated into Halloysite Nanotubes and their Applications for Cleaning of a Marble Surface
Authors: Lo Dico Giulia , Semilia Francesca , Milioto Stefana , Parisi Filippo , Cavallaro Giuseppe , Inguì Giuseppe , Makaremi Maziyar , Pasbakhsh Pooria , Lazzara Giuseppe
Published: August 2018

Halloysite nanotubes were used to incorporate anionic surfactant micelles and an organic solvent to generate a cleaning system to be applied in Cultural Heritage restoration. The targeted adsorption is driven by electrostatic interactions based on the nanotubes peculiar charge separation. Namely anionic species are driven to the positively charged inner surface while being prevented from interacting with the halloysite outer surface that possesses a positive charge density. The hybrid organic/inorganic emulsion was characterized by dynamic light scattering. Analysis of the autocorrelation function allowed us to define the presence of surfactant aggregates inside/outside the nanotube lumen as a function of the nanotube/surfactant ratio in an aqueous mixture. The application of this prepared emulsion for the controlled cleaning of a marble artifact is demonstrated. To this purpose, a membrane of nanofibrous polyacrylonitrile was prepared by electrospinning and was applied between the work of art and the cleaning agent to avoid the release of residues on the marble surface. This work represents a further step toward the opportunity to extend the use of emulsions for cleaning protocols for stone-based artifacts or in technological applications where surfactant separation is required by a simple centrifugation/sedimentation method.
Hydrogeological Study of the Glacial—Fluvioglacial Territory of Grandate (Como, Italy) and Stochastical Modeling of Groundwater Rising
Authors: La Licata Ivana , Colombo Loris , Francani Vincenzo , Alberti Luca
Published: August 2018

On November 2014, the Municipality of Grandate, near Lake Como, had to deal with a great emergency that was caused by the flooding of factory undergrounds. The authors realized a hydrogeological study to understand the causes of groundwater flooding and to prepare a pre-feasibility study concerning possible actions for groundwater control. The hydrogeological structure is rather complex and required time-consuming reconstruction of the conceptual site model. A transient numerical model was developed to analyse the system behaviour in different scenarios. The flow model was calibrated in a steady and unsteady-state using the automatic calibration code Model-Independent Parameter Estimation (PEST). The study demonstrated that the reason for floods was mainly due to the concurrence of three causes: (1) the hydrogeological structure of the area was recognized as a stagnation zone, (2) groundwater rising, and (3) extremely heavy rainfall in 2014. Through the PEST RandPar function, 100 random rainfall scenarios were generated starting from rainfall data for the last 20 years. The model was used to run 100 1-year long simulations considering the probability distribution of recharge related to the 100 randomly generated rainfall scenarios. Through collecting the piezometric heads that resulted from the simulations, monthly probability curves of groundwater exceeding a threshold level were obtained. The results provided an occurrence probability of groundwater level exceeding the underground structures level between 12% and 15%.
Increasing the Reliability of Flood Embankments with Neural Imaging Method
Authors: Kłosowski Grzegorz , Rymarczyk Tomasz , Gola Arkadiusz
Published: August 2018

This paper presents an innovative system of many artificial neural networks that enables the tomographic reconstruction of the internal structure of a flood embankment. An advantage of the proposed method is that it allows us to obtain high-resolution images, which essentially contributes to early, precise and reliable prediction of operational hazards. The method consists in training a cluster of separate neural networks, each of which generates a single point of the output image. The simultaneous and parallel application of the set of neural networks led to effective reconstruction of the internal structure of a deposition site for floatation tailings. Results obtained from the study allow us to solve the low resolution problem that usually occurs with non-invasive imaging methods. This effect was possible thanks to the design of a new intelligent image reconstruction system.
Degradation Rates of Pure Zinc, Magnesium, and Magnesium Alloys Measured by Volume Loss, Mass Loss, and Hydrogen Evolution
Authors: Liu Lumei , Gebresellasie Kassu , Collins Boyce , Zhang Honglin , Xu Zhigang , Sankar Jagannathan , Lee Young-Choon , Yun Yeoheung
Published: August 2018

Degradation rate is an important property to evaluate bioabsorbable metallic material; however, values vary depending on the method of measurement. In this study, three different methods of measuring corrosion rate are compared. The degradable samples to analyze corrosion rates include pure magnesium (Mg), lab produced Mg–Zn–Ca alloy (47-7-2), Mg–Zn–Zr–RE (rare earth) alloys (60-13, 60-14), Mg–Zn–Ca–RE alloy (59B), and pure zinc (Zn). A eudiometer was used to measure hydrogen evolution from the reaction of degradable alloys in Hank’s Balanced Salt Solution (HBSS). Corrosion rates based on volume loss of tested alloys in 30 days were calculated using Micro-computed tomography (micro-CT). Final mass change due to corrosion and corrosion removal was measured with a scale. We observed that the corrosion rates indicated by hydrogen evolution were high initially, and slowed down sharply in the following measurements. The corrosion rates of tested alloys calculated by volume loss and mass loss from high to low are: 60–13 ≈ 60–14 ≈ 47–7–2 > 59B > Mg > Zn (p < 0.05). The results provide instruction to experimental methodology to measure corrosion rates of degradable alloys.
Electrochemical-QCMD Control over S-Layer (SbpA) Recrystallization with Fe2+ as Specific Ion for Self-Assembly Induction
Authors: Iturri Jagoba , Breitwieser Andreas , Pum Dietmar , Sleytr Uwe B. , Toca-Herrera José Luis
Published: August 2018

The critical role of divalent ions (M²+) in the self-assembly of SbpA S-layer proteins (from Lysinibacillus sphaericus CCM 2177) into crystalline structures has been reported in several studies. Hence, ions such as magnesium, barium, nickel and, most commonly, calcium (Ca²+) have proven to trigger both protein-protein and protein-substrate interactions involved in the two-stage non-classical pathway recrystallization followed by SbpA units. As a result, two dimensional, crystalline nanometric sheets in a highly ordered tetrameric state (p4) can be formed on top of different surfaces. The use of iron in its ferrous state (Fe2+) as self-assembly inducing candidate has been omitted so far due to its instability under aerobic conditions, tending to natural oxidation to the ferric (Fe3+) state. In this work, the potentiality of assembling fully functional S-layers from iron (II) salts (FeCl2 and FeSO4) is described for the first time. A combination of chemical (oxidation retardants) and electrical (−1 V potential) factors has been applied to effectively act against such an oxidizing trend. Formation of the respective crystalline films has been followed by means of Electrochemical Quartz Crystal Microbalance with Dissipation (EQCM-D) measurements and complementary Atomic Force Microscopy (AFM) topography studies, which prove the presence of squared lattice symmetry at the end of the recrystallization process. Both techniques, together with additional electrochemical tests performed over the ion permeability of both types of S-layer coatings formed, show the influence of the counterion chosen (chloride vs. sulphate) in the final packing and performance of the S-layer. The presence of an underlying Secondary Cell Wall Polymer (SCWP) as in the natural case contributes to pair both systems, due to the high lateral motility freedom provided by this biopolymer to SbpA units in comparison to uncoated substrates.
Controlling the Spatial Coherence of an Optical Source Using a Spatial Filter
Authors: Hyde Milo W.
Published: August 2018

This paper presents the theory for controlling the spectral degree of coherence via spatial filtering. Starting with a quasi-homogeneous partially coherent source, the cross-spectral density function of the field at the output of the spatial filter is found by applying Fourier and statistical optics theory. The key relation obtained from this analysis is a closed-form expression for the filter function in terms of the desired output spectral degree of coherence. This theory is verified with Monte Carlo wave-optics simulations of spatial coherence control and beam shaping for potential use in free-space optical communications and directed energy applications. The simulated results are found to be in good agreement with the developed theory. The technique presented in this paper will be useful in applications where coherence control is advantageous, e.g., directed energy, free-space optical communications, remote sensing, medicine, and manufacturing.
Enhancement of CO2 Removal Efficacy of Fluidized Bed Using Particle Mixing
Authors: Al-Ghurabi Ebrahim H. , Ajbar Abdelhamid , Asif Mohammad
Published: August 2018

The present study proposes a cost-effective assisted fluidization technique of particle mixing to improve the carbon capture effectiveness of a fluidized bed containing fine adsorbent powder. Using activated carbon as the adsorbent, we mixed external particle of Geldart group B classification in different fractions to examine the effectiveness of the proposed strategy of particle mixing. Four different particle-mixing cases were considered by varying the amount of added particle—0, 5, 10, and 30 wt %—on external particle-free basis. The inlet flow of the nitrogen was fixed, while two different flows of carbon dioxide were used. The adsorption experiment consisted of a three step procedure comprising purging using pure nitrogen, followed by adsorption with fixed inlet CO2 concentration, and finally the desorption step. Inlet flows of both nitrogen and CO2 were separately controlled using electronic mass flow controllers with the help of data acquisition system (DAQ). The CO2 breakthrough was carefully monitored using the CO2/O2 analyzer, whose analog output was recorded using the DAQ. Best results were obtained with 10% external particles. This is in conformity with the results of our previous study of bed hydrodynamics, which pointed to clear improvement in the fluidization behavior with particle mixing.
Modeling Wildfire Smoke Pollution by Integrating Land Use Regression and Remote Sensing Data: Regional Multi-Temporal Estimates for Public Health and Exposure Models
Authors: Mirzaei Mojgan , Bertazzon Stefania , Couloigner Isabelle
Published: August 2018

To understand the health effects of wildfire smoke, it is important to accurately assess smoke exposure over space and time. Particulate matter (PM) is a predominant pollutant in wildfire smoke. In this study, we develop land-use regression (LUR) models to investigate the impact that a cluster of wildfires in the northwest USA had on the level of PM in southern Alberta (Canada), in the summer of 2015. Univariate aerosol optical depth (AOD) and multivariate AOD-LUR models were used to estimate the level of PM2.5 in urban and rural areas. For epidemiological studies, it is also important to distinguish between wildfire-related PM2.5 and PM2.5 originating from other sources. We therefore subdivided the study period into three sub-periods: (1) Pre-fire, (2) during-fire, and (3) post-fire. We then developed separate models for each sub-period. With this approach, we were able to identify different predictors significantly associated with smoke-related PM2.5 verses PM2.5 of different origin. Leave-one-out cross-validation (LOOCV) was used to evaluate the models’ performance. Our results indicate that model predictors and model performance are highly related to the level of PM2.5, and the pollution source. The predictive ability of both uni- and multi-variate models were higher in the during-fire period than in the pre- and post-fire periods.
Multi-Spectroscopic and Theoretical Analysis on the Interaction between Human Serum Albumin and a Capsaicin Derivative—RPF101
Authors: Chaves Otávio Augusto , Tavares Maurício Temotheo , Cunha Micael Rodrigues , Parise-Filho Roberto , Sant’Anna Carlos Maurício R. , Netto-Ferreira José Carlos
Published: August 2018

The interaction between the main carrier of endogenous and exogenous compounds in the human bloodstream (human serum albumin, HSA) and a potential anticancer compound (the capsaicin analogue RPF101) was investigated by spectroscopic techniques (circular dichroism, steady-state, time-resolved, and synchronous fluorescence), zeta potential, and computational method (molecular docking). Steady-state and time-resolved fluorescence experiments indicated an association in the ground state between HSA:RPF101. The interaction is moderate, spontaneous (ΔG° < 0), and entropically driven (ΔS° = 0.573 ± 0.069 kJ/molK). This association does not perturb significantly the potential surface of the protein, as well as the secondary structure of the albumin and the microenvironment around tyrosine and tryptophan residues. Competitive binding studies indicated Sudlow’s site I as the main protein pocket and molecular docking results suggested hydrogen bonding and hydrophobic interactions as the main binding forces.
Crystal Structure of the Human tRNA Guanine Transglycosylase Catalytic Subunit QTRT1
Authors: Johannsson Sven , Neumann Piotr , Ficner Ralf
Published: August 2018

RNA modifications have been implicated in diverse and important roles in all kingdoms of life with over 100 of them present on tRNAs. A prominent modification at the wobble base of four tRNAs is the 7-deaza-guanine derivative queuine which substitutes the guanine at position 34. This exchange is catalyzed by members of the enzyme class of tRNA guanine transglycosylases (TGTs). These enzymes incorporate guanine substituents into tRNAAsp, tRNAAsn tRNAHis, and tRNATyr in all kingdoms of life. In contrast to the homodimeric bacterial TGT, the active eukaryotic TGT is a heterodimer in solution, comprised of a catalytic QTRT1 subunit and a noncatalytic QTRT2 subunit. Bacterial TGT enzymes, that incorporate a queuine precursor, have been identified or proposed as virulence factors for infections by pathogens in humans and therefore are valuable targets for drug design. To date no structure of a eukaryotic catalytic subunit is reported, and differences to its bacterial counterpart have to be deducted from sequence analysis and models. Here we report the first crystal structure of a eukaryotic QTRT1 subunit and compare it to known structures of the bacterial TGT and murine QTRT2. Furthermore, we were able to determine the crystal structure of QTRT1 in complex with the queuine substrate.
Recombinant Fusion Protein Joining E Protein Domain III of Tick-Borne Encephalitis Virus and HSP70 of Yersinia pseudotuberculosis as an Antigen for the TI-Complexes
Authors: Golotin Vasily , Sanina Nina , Davydova Ludmila , Chopenko Natalia , Mazeika Andrey , Roig Manuel , Shnyrov Valery , Uversky Vladimir N. , Kostetsky Eduard
Published: August 2018

Domain III (DIII) of the tick-borne encephalitis virus (TBEV) protein E contains epitopes, which induce antibodies capable of neutralizing the virus. To enhance the immunogenicity of this protein, which has a low molecular weight, the aim of the present work was to express, isolate, and characterize a chimeric protein based on the fusion of the bacterial chaperone HSP70 of Yersinia pseudotuberculosis and EIII (DIII + stem) as a prospective antigen for an adjuvanted delivery system, the tubular immunostimulating complex (TI-complex). The chimeric construction was obtained using pET-40b(+) vector by ligating the respective genes. The resulting plasmid was transformed into DE3 cells for the heterologous expression of the chimeric protein, which was purified by immobilized metal affinity chromatography (IMAC). ELISA, differential scanning calorimetry, intrinsic fluorescence, and computational analysis were applied for the characterization of the immunogenicity and conformation of the chimeric protein. Mice immunization showed that the chimeric protein induced twice the number of anti-EIII antibodies in comparison with EIII alone. In turn, the incorporation of the HSP70/EIII chimeric protein in the TI-complex resulted in a twofold increase in its immunogenicity. The formation of this vaccine construction was accompanied by significant conformational changes in the chimeric protein. Using HSP70 in the content of the chimeric protein represents an efficient means for presenting the main antigenic domain of the TBEV envelope protein to the immune system, whereas the incorporation of this chimeric protein into the TI-complex further contributes to the development of a stronger immune response against the TBEV infection.
Molecular Modeling Applied to Nucleic Acid-Based Molecule Development
Authors: Krüger Arne , Zimbres Flávia , Kronenberger Thales , Wrenger Carsten
Published: August 2018

Molecular modeling by means of docking and molecular dynamics (MD) has become an integral part of early drug discovery projects, enabling the screening and enrichment of large libraries of small molecules. In the past decades, special emphasis was drawn to nucleic acid (NA)-based molecules in the fields of therapy, diagnosis, and drug delivery. Research has increased dramatically with the advent of the SELEX (systematic evolution of ligands by exponential enrichment) technique, which results in single-stranded DNA or RNA sequences that bind with high affinity and specificity to their targets. Herein, we discuss the role and contribution of docking and MD to the development and optimization of new nucleic acid-based molecules. This review focuses on the different approaches currently available for molecular modeling applied to NA interaction with proteins. We discuss topics ranging from structure prediction to docking and MD, highlighting their main advantages and limitations and the influence of flexibility on their calculations.
Target Value Design Inspired Practices to Deliver Sustainable Buildings
Authors: Silveira Samia S. , Alves Thais da C. L.
Published: August 2018

The design of environmentally-friendly buildings relies on the work of interdisciplinary teams who have to look at problems in a holistic way. Teams need to communicate, collaborate, and make decisions not solely based on first cost considerations. For this purpose, Target Value Design (TVD) related practices are being used to deliver green buildings in Southern California while meeting strict code requirements and addressing the needs of multiple stakeholders in a collaborative fashion. This study did not quantify costs associated with design and construction of sustainable buildings. It used an analytical process that compared and contrasted available literature on TVD and interviews with industry practitioners to investigate the use of TVD-inspired practices in the construction industry in Southern California and identify the current use of TVD-inspired practices in the design of green buildings. The study revealed that, even though practitioners might not be aware of how TVD can be fully implemented in these projects, a number of TVD-inspired practices are currently being used. Examples are provided to illustrate their practical use in the design of sustainable buildings and how practice compares to theory regarding TVD implementation.
Effect of In-Situ Dehydration on Activity and Stability of Cu–Ni–K2O/Diatomite as Catalyst for Direct Synthesis of Dimethyl Carbonate
Authors: Han Dongmei , Chen Yong , Wang Shuanjin , Xiao Min , Lu Yixin , Meng Yuezhong
Published: August 2018

An in-situ dehydrating system built in a continuous flow fixed-bed bubbling reactor for direct synthesis of dimethyl carbonate (DMC) was designed. 3A molecular sieve (MS) was selected as the ideal dehydrating agent and the water trapping efficiency was studied. The effect of dehydrating agent/catalyst ratio, the dehydrating temperature and pressure, as well as the space velocity on the direct DMC synthesis catalyzed by K2O-promoted Cu–Ni was further investigated. These results demonstrated that 3A MS could effectively dehydrate the reaction system at the optimal conditions of 120 °C and 1.0 MPa with gas space velocity (GHSV) of 600 h−1, thereby greatly shifting the reaction equilibrium toward high DMC yield. Higher DMC yield of 13% was achieved compared with undehydrated reaction. Moreover, the catalyst can be highly stabilized by 3A MS dehydration with stable performs over 22 h.
Carbon Aerogel-Supported Nickel and Iron for Gasification Gas Cleaning. Part I: Ammonia Adsorption
Authors: Gómez-Cápiro Oscar , Hinkle Adrian , Delgado Aaron M. , Fernández Camila , Jiménez Romel , Arteaga-Pérez Luis E.
Published: August 2018

Biomass gasification is a promising way to obtain “green energy”, but the gas composition makes it unsuitable for use in traditional technologies (i.e., IC engine). Gas purification over nickel and/or iron catalysts is an attractive alternative. Cellulose-based carbon aerogels (CAGs) have shown suitable physical chemical properties for use as catalyst supports. In this work, nickel and iron catalysts are supported on CAG made from cellulose microfibers. Microfibers were impregnated with (NH4)2SO4 to increase the mass yield. Carbonization was evaluated at different heating rates, maximum temperatures, and dwell times to generate CAGs. Resulting chars were characterized by N2 adsorption, X-ray diffraction (XRD), and Raman spectroscopy. The CAG with better properties (specific surface, pore size, thermal resistance) was impregnated with the metal precursor salt via incipient wetness and treated with H2. Catalysts were characterized by transmission electron microscopy (TEM), XRD, N2 adsorption, and inductively coupled plasma optical emission spectrometry (ICP-OES). Ammonia adsorption was studied over CAG and catalysts to estimate the thermodynamic parameters. The impregnation with ((NH4)2SO4 improves thermal resistance of the char obtained from carbonization. The catalysts exhibit higher adsorption capacity than CAG (without metal), indicating chemical interaction between ammonia and metals. The metal-ammonia interaction is stronger on Fe than on Ni catalyst, which is consistent with reported theoretical calculations.
Sequential Biotransformation of Antcin K by Bacillus subtilis ATCC 6633
Authors: Chang Te-Sheng , Chiang Chien-Min , Siao Yi-Yun , Wu Jiumn-Yih
Published: August 2018

The biotransformation of antcin K, a major ergostane triterpenoid from the fruiting bodies of Antrodia cinnamomea, by Bacillus subtilis (B. subtilis) ATCC 6633 was studied. Four metabolites from the biotransformation were isolated with preparative high-performance liquid chromatography and identified as 25S-antcin K 26-O-β-glucoside, 25R-antcin K 26-O-β-glucoside, 25S-antcin K 26-O-β-(6′-O-succinyl)-glucoside, and 25R-antcin K 26-O-β-(6′-O-succinyl)-glucoside with mass and nuclear magnetic resonance spectral analysis. By using either 25S-antcin K 26-O-β-glucoside or 25R-antcin K 26-O-β-glucoside as the biotransformation precursor, it was proven that 25S-antcin K 26-O-β-(6′-O-succinyl)-glucoside and 25R-antcin K 26-O-β-(6′-O-succinyl)-glucoside were biotransformed from 25S-antcin K 26-O-β-glucoside and 25R-antcin K 26-O-β-glucoside, respectively. To the best of our knowledge, this is the first study on the glycosylation of triterpenoids from A. cinnamomea, and the first time the succinylation of triterpenoid glycosides by microorganisms has been found. In addition, all four antcin K glucoside derivatives are new compounds.
Ubiquitin Regulation: The Histone Modifying Enzyme′s Story
Authors: Wang Jianlin , Qiu Zhaoping , Wu Yadi
Published: August 2018

Histone post-translational modifications influence many fundamental cellular events by regulating chromatin structure and gene transcriptional activity. These modifications are highly dynamic and tightly controlled, with many enzymes devoted to the addition and removal of these modifications. Interestingly, these modifying enzymes are themselves fine-tuned and precisely regulated at the level of protein turnover by ubiquitin-proteasomal processing. Here, we focus on recent progress centered on the mechanisms regulating ubiquitination of histone modifying enzymes, including ubiquitin proteasomal degradation and the reverse process of deubiquitination. We will also discuss the potential pathophysiological significance of these processes.
Identification and Characterization of LRR-RLK Family Genes in Potato Reveal Their Involvement in Peptide Signaling of Cell Fate Decisions and Biotic/Abiotic Stress Responses
Authors: Li Xiaoxu , Ahmad Salman , Guo Cun , Yu Jing , Cao Songxiao , Gao Xiaoming , Li Wei , Li Hong , Guo Yongfeng
Published: August 2018

Leucine-rich repeat receptor-like kinases (LRR-RLKs) represent the largest subfamily of receptor-like kinases (RLKs) and play important roles in regulating growth, development, and stress responses in plants. In this study, 246 LRR-RLK genes were identified in the potato (Solanum tuberosum) genome, which were further classified into 14 subfamilies. Gene structure analysis revealed that genes within the same subgroup shared similar exon/intron structures. A signature small peptide recognition motif (RxR) was found to be largely conserved within members of subfamily IX, suggesting that these members may recognize peptide signals as ligands. 26 of the 246 StLRR-RLK genes were found to have arisen from tandem or segmental duplication events. Expression profiling revealed that StLRR-RLK genes were differentially expressed in various organs/tissues, and several genes were found to be responsive to different stress treatments. Furthermore, StLRR-RLK117 was found to be able to form homodimers and heterodimers with StLRR-RLK042 and StLRR-RLK052. Notably, the overlapping expression region of StLRR-RLK117 with Solanum tuberosum WUSCHEL (StWUS) suggested that the CLV3–CLV1/BAM–WUS feedback loop may be conserved in potato to maintain stem cell homeostasis within the shoot apical meristem.
Functionalized Electrospun Fibers for the Design of Novel Hydrophobic and Anticorrosive Surfaces
Authors: Rivero Pedro J. , Yurrita David , Berlanga Carlos , Palacio José F. , Rodríguez Rafael
Published: August 2018

In this work, a novel coating was deposited on aluminum alloy samples by using a combination of electrospinning and chemical vapor deposition (CVD-silanization) techniques in order to create a functionalized film with an enhancement of both corrosion resistance and hydrophobicity. The electrospinning technique makes the fabrication of highly crosslinked electrospun fibers possible by the combination of both poly(acrylic acid) and β-cyclodextrin, respectively, which can be easily functionalized in a further step by using the CVD-silanization process due to the evaporation of a hydrophobic molecule such as 1H,1H,2H,2H-Perflurodecyltriethoxysilane. In addition, the resultant electrospun fibers with a high degree of insolubility have been successfully fabricated and metal oxide nanoparticles (TiO2NPs) have been incorporated into the electrospun polymeric solution in order to improve the corrosion protection. The surface morphology has been determined by using light optical microscopy, atomic force microscopy, scanning electron microscopy, and water contact angle (WCA) measurements. The corrosion resistance has been evaluated by using both potentiodynamic polarization and pitting corrosion tests. Finally, the results related to WCA measurements after CVD-silanization corroborate that the surfaces have been successfully functionalized with a hydrophobic behavior in comparison with the electrospinning process, showing a considerable difference in the roughness.
Developing a New Storage Format and a Warp-Based SpMV Kernel for Configuration Interaction Sparse Matrices on the GPU
Authors: Mahmoud Mohammed , Hoffmann Mark , Reza Hassan
Published: August 2018

Sparse matrix-vector multiplication (SpMV) can be used to solve diverse-scaled linear systems and eigenvalue problems that exist in numerous, and varying scientific applications. One of the scientific applications that SpMV is involved in is known as Configuration Interaction (CI). CI is a linear method for solving the nonrelativistic Schrödinger equation for quantum chemical multi-electron systems, and it can deal with the ground state as well as multiple excited states. In this paper, we have developed a hybrid approach in order to deal with CI sparse matrices. The proposed model includes a newly-developed hybrid format for storing CI sparse matrices on the Graphics Processing Unit (GPU). In addition to the new developed format, the proposed model includes the SpMV kernel for multiplying the CI matrix (proposed format) by a vector using the C language and the Compute Unified Device Architecture (CUDA) platform. The proposed SpMV kernel is a vector kernel that uses the warp approach. We have gauged the newly developed model in terms of two primary factors, memory usage and performance. Our proposed kernel was compared to the cuSPARSE library and the CSR5 (Compressed Sparse Row 5) format and already outperformed both.
Investigation of the Grain Boundary Character and Dislocation Density of Different Types of High Performance Multicrystalline Silicon
Authors: Stokkan Gaute , Song Adolphus , Ryningen Birgit
Published: August 2018

Wafers from three heights and two different lateral positions (corner and centre) of four industrial multicrystalline silicon ingots were analysed with respect to their grain structure and dislocation density. Three of the ingots were non-seeded and one ingot was seeded. It was found that there is a strong correlation between the ratio of the densities of (coincidence site lattice) CSL grain boundaries and high angle grain boundaries in the bottom of a block and the dislocation cluster density higher in the block. In general, the seeded blocks, both the corner and centre block, have a lower dislocation cluster density than in the non-seeded blocks, which displayed a large variation. The density of the random angle boundaries in the corner blocks of the non-seeded ingots was similar to the density in the seeded ingots, while the density in the centre blocks was lower. However, the density of CSL boundaries was higher in all the non-seeded than in the seeded ingots. It appears that both of these grain boundary densities influence the presence of dislocation clusters, and we propose they act as dislocation sinks and sources, respectively. The ability to generate small grain size material without seeding appears to be correlated to the morphology of the coating, which is generally rougher in the corner positions than in the middle. Furthermore, the density of twins and CSL boundaries depends on the growth mode during initial growth and thus on the degree of supercooling. Controlling both these properties is important in order to be able to successfully produce uniform quality high-performance multicrystalline silicon by the advantageous non-seeding method.
Convex Optimization via Symmetrical Hölder Divergence for a WLAN Indoor Positioning System
Authors: Abdullah Osamah
Published: August 2018

Modern indoor positioning system services are important technologies that play vital roles in modern life, providing many services such as recruiting emergency healthcare providers and for security purposes. Several large companies, such as Microsoft, Apple, Nokia, and Google, have researched location-based services. Wireless indoor localization is key for pervasive computing applications and network optimization. Different approaches have been developed for this technique using WiFi signals. WiFi fingerprinting-based indoor localization has been widely used due to its simplicity, and algorithms that fingerprint WiFi signals at separate locations can achieve accuracy within a few meters. However, a major drawback of WiFi fingerprinting is the variance in received signal strength (RSS), as it fluctuates with time and changing environment. As the signal changes, so does the fingerprint database, which can change the distribution of the RSS (multimodal distribution). Thus, in this paper, we propose that symmetrical Hölder divergence, which is a statistical model of entropy that encapsulates both the skew Bhattacharyya divergence and Cauchy–Schwarz divergence that are closed-form formulas that can be used to measure the statistical dissimilarities between the same exponential family for the signals that have multivariate distributions. The Hölder divergence is asymmetric, so we used both left-sided and right-sided data so the centroid can be symmetrized to obtain the minimizer of the proposed algorithm. The experimental results showed that the symmetrized Hölder divergence consistently outperformed the traditional k nearest neighbor and probability neural network. In addition, with the proposed algorithm, the position error accuracy was about 1 m in buildings.
Bayesian Computational Methods for Sampling from the Posterior Distribution of a Bivariate Survival Model, Based on AMH Copula in the Presence of Right-Censored Data
Authors: Saraiva Erlandson Ferreira , Suzuki Adriano Kamimura , Milan Luis Aparecido
Published: August 2018

In this paper, we study the performance of Bayesian computational methods to estimate the parameters of a bivariate survival model based on the Ali–Mikhail–Haq copula with marginal distributions given by Weibull distributions. The estimation procedure was based on Monte Carlo Markov Chain (MCMC) algorithms. We present three version of the Metropolis–Hastings algorithm: Independent Metropolis–Hastings (IMH), Random Walk Metropolis (RWM) and Metropolis–Hastings with a natural-candidate generating density (MH). Since the creation of a good candidate generating density in IMH and RWM may be difficult, we also describe how to update a parameter of interest using the slice sampling (SS) method. A simulation study was carried out to compare the performances of the IMH, RWM and SS. A comparison was made using the sample root mean square error as an indicator of performance. Results obtained from the simulations show that the SS algorithm is an effective alternative to the IMH and RWM methods when simulating values from the posterior distribution, especially for small sample sizes. We also applied these methods to a real data set.
New Fault-Tolerant Control Strategy of Five-Phase Induction Motor with Four-Phase and Three-Phase Modes of Operation
Authors: Rangari Sonali , Suryawanshi Hiralal , Renge Mohan
Published: August 2018

The developed torque with minimum oscillations is one of the difficulties faced when designing drive systems. High ripple torque contents result in fluctuations and acoustic noise that impact the life of a drive system. A multiphase machine can offer a better alternative to a conventional three-phase machine in faulty situations by reducing the number of interruptions in industrial operation. This paper proposes a unique fault-tolerant control strategy for a five-phase induction motor. The paper considers a variable-voltage, variable-frequency control five-phase induction motor in one- and two-phase open circuit faults. The four-phase and three-phase operation modes for these faults are utilized with a modified voltage reference signal. The suggested remedial strategy is the method for compensating a faulty open phase of the machine through a modified reference signal. A modified voltage reference signal can be efficiently executed by a carrier-based pulse width modulation (PWM) system. A test bench for the execution of the fault-tolerant control strategy of the motor drive system is presented in detail along with the experimental results.
Multiple UAV Systems for Agricultural Applications: Control, Implementation, and Evaluation
Authors: Ju Chanyoung , Son Hyoung Il
Published: August 2018

The introduction of multiple unmanned aerial vehicle (UAV) systems into agriculture causes an increase in work efficiency and a decrease in operator fatigue. However, systems that are commonly used in agriculture perform tasks using a single UAV with a centralized controller. In this study, we develop a multi-UAV system for agriculture using the distributed swarm control algorithm and evaluate the performance of the system. The performance of the proposed agricultural multi-UAV system is quantitatively evaluated and analyzed through four experimental cases: single UAV with autonomous control, multiple UAVs with autonomous control, single UAV with remote control, and multiple UAVs with remote control. Moreover, the performance of each system was analyzed through seven performance metrics: total time, setup time, flight time, battery consumption, inaccuracy of land, haptic control effort, and coverage ratio. Experimental results indicate that the performance of the multi-UAV system is significantly superior to the single-UAV system.
Low Carbon Energy Transitions in the Nordic Countries: Evidence from the Environmental Kuznets Curve
Authors: Urban Frauke , Nordensvärd Johan
Published: August 2018

Low carbon energy transitions are important to mitigate climate change, reduce air pollution, and reduce fossil fuel resource depletion. The Nordic countries (Denmark, Finland, Iceland, Norway, Sweden) are seen as leaders in low carbon energy transitions. This paper provides a comparative data analysis of low carbon energy transitions in the Nordic countries from the 1960s to 2015, and assesses evidence of the Environmental Kuznets Curve (EKC). The paper finds that the EKC has been observed in Denmark, Iceland, and Sweden in terms of total CO2 emissions, but not in Norway and Finland. For per capita CO2 emissions, there is evidence for the EKC in Denmark, Finland, Iceland, and Sweden, but not for Norway. For energy use per capita, the EKC is only observed for Denmark, while improvements are needed for the other countries. Norway is an outlier, in comparison with the other Nordic countries, hence the country should implement more stringent climate change mitigation policies to reduce its emissions. Overall, the research suggests that the Nordic countries, particularly Denmark, Iceland, and Sweden, can provide valuable lessons for national, regional, and global low carbon energy transitions.
Methodology for Extracting Potential Customized Bus Routes Based on Bus Smart Card Data
Authors: Li Jing , Lv Yongbo , Ma Jihui , Ouyang Qi
Published: August 2018

To alleviate traffic congestion and traffic-related environmental pollution caused by the increasing numbers of private cars, public transport (PT) is highly recommended to travelers. However, there is an obvious contradiction between the diversification of travel demands and simplification of PT service. Customized bus (CB), as an innovative supplementary mode of PT service, aims to provide demand-responsive and direct transit service to travelers with similar travel demands. But how to obtain accurate travel demands? It is passive and limited to conducting online surveys, additionally inefficient and costly to investigate all the origin-destinations (ODs) aimlessly. This paper proposes a methodological framework of extracting potential CB routes from bus smart card data to provide references for CB planners to conduct purposeful and effective investigations. The framework consists of three processes: trip reconstruction, OD area division and CB route extraction. In the OD area division process, a novel two-step division model is built to divide bus stops into different areas. In the CB route extraction process, two spatial-temporal clustering procedures and one length constraint are implemented to cluster similar trips together. An improved density-based spatial clustering of application with noise (DBSCAN) algorithm is used to complete these procedures. In addition, a case study in Beijing is conducted to demonstrate the effectiveness of the proposed methodological framework and the resulting analysis provides useful references to CB planners in Beijing.
Stochastic Hybrid Estimator Based Fault Detection and Isolation for Wind Energy Conversion Systems with Unknown Fault Inputs
Authors: Shi Yun-Tao , Zhang Yuan , Xiang Xiang , Wang Li , Lei Zhen-Wu , Sun De-Hui
Published: August 2018

In recent years, the wind energy conversion system (WECS) has been becoming the vital system to acquire wind energy. However, the high failure rate of WECSs leads to expensive costs for the maintenance of WECSs. Therefore, how to detect and isolate the faults of WECSs with stochastic dynamics is the pressing issue in the literature. This paper proposes a novel comprehensive fault detection and isolation (FDI) method for WECSs. First, a stochastic model predictive control (SMPC) controller is studied to construct the closed-loop system of the WECS. This controller is based on the Markov-jump linear model, which could precisely establish the stochastic dynamics of the WECS. Meanwhile, the SMPC controller has satisfied control performance for the WECS. Second, based on the closed-loop system with SMPC, the stochastic hybrid estimator (SHE) is designed to estimate the continuous and discrete states of the WECS. Compared with the existing estimators for WECSs, the proposed estimator is more suitable for WECSs since it considers both the continuous and discrete states of WECSs. In addition, the proposed estimator is robust to the fault input. Finally, with the proposed estimator, the comprehensive FDI method is given to detect and isolate the actuators’ faults of the WECS. Both the system status and the actuators’ faults can be detected by the FDI method and it can effectively quantify the actuators’ fault by the fault residuals. The simulation results suggest that the SHE could effectively estimate the hybrid states of the WECS, and the proposed FDI method gives satisfied fault detection performance for the actuators of the WECS.
Research on Methods of Active Steering Control Based on Receding Horizon Control
Authors: Feng Jiwei , Bao Chunjiang , Wu Jian , Cheng Shuo , Xu Guangfei , Liu Shifu
Published: August 2018

Active steering technology is a key technology for automatic driving vehicles to achieve route tracking and obstacle avoidance and risk avoidance, and its performance will affect the stability control of the vehicle. For solving the stability control issues of vehicles, which have uncertainty in model and robustness in system, this paper proposes an active steering control method based on the receding horizon control model. It calculates the optimal control law by this method by using the real-time vehicle state so that it can compensate for the uncertainty caused by model mismatch, interference, etc. The design of the controller is implemented by using the yaw rate deviation of the vehicle as the input of the receding horizon linear quadratic controller model and then inputting the calculated superposition angle into the vehicle model in real time. We built a Simulink control model to implement co-simulation with CarSim to verify the control effect of the controller. In addition, we built a steering hardware-in-the-loop platform based on the LabVIEW RT system. The experimental results show that the active steering system adopting a receding horizon control method had better system robustness and robust stability.
Power Generation via Small Length Scale Thermo-Mechanical Systems: Current Status and Challenges, a Review
Authors: Burugupally Sindhu , Weiss Leland
Published: August 2018

There has been significant interest and work toward the development of small length scale (micrometer to centimeter) energy conversion systems—heat engines and thermal energy harvesters—that operate on different thermal sources. Small combustion driven heat engines offer high power densities and longer operating durations, and present an opportunity to replace large and heavy chemical batteries. Thermal energy harvesters provide a great opportunity to harness the freely available thermal energy: solar, geothermal, and human body heat. These systems can contribute to significant energy savings when coupled to an existing, larger power generation system (e.g., vehicles and diesel generators) for the purpose of energy recovery. In this review, we discuss technological challenges, opportunities, and recent progress in small length scale energy conversion systems with special focus on free piston devices (engines and expanders) and phase-change driven devices. We discuss in detail four important design considerations that can have significant effect on small length scale device performance.