bluuebunny/crossref_metadata_2025 huggingface dataset:
Texture Analysis and Land Cover Classification of Tehran Using Polarimetric Synthetic Aperture Radar Imagery
Authors: Zakeri Homa , Yamazaki Fumio , Liu Wen
Published: May 2017

Land cover classification of built-up and bare land areas in arid or semi-arid regions from multi-spectral optical images is not simple, due to the similarity of the spectral characteristics of the ground and building materials. However, synthetic aperture radar (SAR) images could overcome this issue because of the backscattering dependency on the material and the geometry of different surface objects. Therefore, in this paper, dual-polarized data from ALOS-2 PALSAR-2 (HH, HV) and Sentinel-1 C-SAR (VV, VH) were used to classify the land cover of Tehran city, Iran, which has grown rapidly in recent years. In addition, texture analysis was adopted to improve the land cover classification accuracy. In total, eight texture measures were calculated from SAR data. Then, principal component analysis was applied, and the first three components were selected for combination with the backscattering polarized images. Additionally, two supervised classification algorithms, support vector machine and maximum likelihood, were used to detect bare land, vegetation, and three different built-up classes. The results indicate that land cover classification obtained from backscatter values has better performance than that obtained from optical images. Furthermore, the layer stacking of texture features and backscatter values significantly increases the overall accuracy.
Jointly Production and Correlated Maintenance Optimization for Parallel Leased Machines
Authors: ASKRI Tarek , HAJEJ Zied , REZG Nidhal
Published: May 2017

This paper deals with a preventive maintenance strategy optimization correlated to production for a manufacturing system made by several parallel machines under lease contract. In order to minimize the total cost of production and maintenance by reducing the production system interruptions due to maintenance activities, a correlated group preventive maintenance policy is developed using the gravity center approach (GCA). The aim of this study is to determine an economical production plan and an optimal group preventive maintenance interval Tn at which all machines are maintained simultaneously. An analytical correlation between failure rate of machines and production level is considered and the impact of the preventive maintenance policy on the production plan is studied. Finally, the proposed maintenance policy GPM is compared with an individual simple strategy approach IPM in order to illustrate its efficiency.
Graph-Based Semi-Supervised Learning for Indoor Localization Using Crowdsourced Data
Authors: Zhang Liye , Valaee Shahrokh , Xu Yubin , Ma Lin , Vedadi Farhang
Published: May 2017

Indoor positioning based on the received signal strength (RSS) of the WiFi signal has become the most popular solution for indoor localization. In order to realize the rapid deployment of indoor localization systems, solutions based on crowdsourcing have been proposed. However, compared to conventional methods, lots of different devices are used in crowdsourcing system and less RSS values are collected by each device. Therefore, the crowdsourced RSS values are more erroneous and can result in significant localization errors. In order to eliminate the signal strength variations across diverse devices, the Linear Regression (LR) algorithm is proposed to solve the device diversity problem in crowdsourcing system. After obtaining the uniform RSS values, a graph-based semi-supervised learning (G-SSL) method is used to exploit the correlation between the RSS values at nearby locations to estimate an optimal RSS value at each location. As a result, the negative effect of the erroneous measurements could be mitigated. Since the AP locations need to be known in G-SSL algorithm, the Compressed Sensing (CS) method is applied to precisely estimate the location of the APs. Based on the location of the APs and a simple signal propagation model, the RSS difference between different locations is calculated and used as an additional constraint to improve the performance of G-SSL. Furthermore, to exploit the sparsity of the weights used in the G-SSL, we use the CS method to reconstruct these weights more accurately and make a further improvement on the performance of the G-SSL. Experimental results show improved results in terms of the smoothness of the radio map and the localization accuracy.
Concentrations and Size Distributions of Bacteria-Containing Particles over Oceans from China to the Arctic Ocean
Authors: Li Ming , Yu Xiawei , Kang Hui , Xie Zhouqing , Zhang Pengfei
Published: May 2017

During the third China Arctic Research Expedition (July–September 2008), size-resolved measurements of bacteria-containing particles (BCPs) in the marine boundary layer (MBL) air were conducted during a cruise through the East China Sea, the Yellow Sea, the Japan Sea, the Okhotsk Sea, the Bering Sea, the Chukchi Sea, and the Arctic Ocean. The concentrations of total airborne BCPs (TBCPs), non-salt tolerant airborne BCPs (NSBCPs), and salt tolerant airborne BCPs (SBCPs) varied from 29 to 955 CFU m−3 (CFU = Colony Forming Unit), 16 to 919 CFU m−3, and 4 to 276 CFU m−3, with an average value of 275, 182, and 92 CFU m−3, respectively. Although the SBCP concentrations were less than the NSBCP concentrations when averaged over all measurements, there are several cases where the reverse is true (e.g., in the high Arctic Ocean). During the cruise, the TBCP sizes were dominated by the diameter >4.7 μm fraction (accounted for 46.3% on average), while the fine fraction (diameter <2.1 μm) accounted for 27.8%. For NSBCPs and SBCPs, the coarse fraction also was the dominant fraction over most regions. The influence of local meteorological conditions on the abundance, size distributions, and species of airborne bacteria is discussed. Notably, in the atmosphere over the Arctic Ocean the abundance of airborne bacteria was apparently related to the distribution of sea ice. As cultivation based methodologies may underestimate the environmental bacterial communities, it is expected that the abundance of bacteria in the ambient air would be higher than that observed in this study. In order to distinguish different species of bacteria, molecular biological techniques (e.g., 16S rDNA analysis) are required for identification in future investigations.
Elementary Processes and Kinetic Modeling for Hydrogen and Helium Plasmas
Authors: Celiberto Roberto , Capitelli Mario , Colonna Gianpiero , D’Ammando Giuliano , Esposito Fabrizio , Janev Ratko , Laporta Vincenzo , Laricchiuta Annarita , Pietanza Lucia , Rutigliano Maria , Wadehra Jogindra
Published: May 2017

We report cross-sections and rate coefficients for excited states colliding with electrons, heavy particles and walls useful for the description of H 2 /He plasma kinetics under different conditions. In particular, the role of the rotational states in resonant vibrational excitations of the H 2 molecule by electron impact and the calculation of the related cross-sections are illustrated. The theoretical determination of the cross-section for the rovibrational energy exchange and dissociation of H 2 molecule, induced by He atom impact, by using the quasi-classical trajectory method is discussed. Recombination probabilities of H atoms on tungsten and graphite, relevant for the determination of the nascent vibrational distribution, are also presented. An example of a state-to-state plasma kinetic model for the description of shock waves operating in H 2 and He-H 2 mixtures is presented, emphasizing also the role of electronically-excited states in affecting the electron energy distribution function of free electrons. Finally, the thermodynamic properties and the electrical conductivity of non-ideal, high-density hydrogen plasma are finally discussed, in particular focusing on the pressure ionization phenomenon in high-pressure high-temperature plasmas.
A Pilot Study on Brain Plasticity of Functional Connectivity Modulated by Cognitive Training in Mild Alzheimer’s Disease and Mild Cognitive Impairment
Authors: Barban Francesco , Mancini Matteo , Cercignani Mara , Adriano Fulvia , Perri Roberta , Annicchiarico Roberta , Carlesimo Giovanni Augusto , Ricci Claudia , Lombardi Maria Giovanna , Teodonno Valeria , Serra Laura , Giulietti Giovanni , Fadda Lucia , Federici Alessia , Caltagirone Carlo , Bozzali Marco
Published: May 2017

Alzheimer’s disease (AD) alters the functional connectivity of the default mode network (DMN) but also the topological properties of the functional connectome. Cognitive training (CT) is a tool to slow down AD progression and is likely to impact on functional connectivity. In this pilot study, we aimed at investigating brain functional changes after a period of CT and active control (AC) in a group of 26 subjects with mild AD (mAD), 26 with amnestic mild cognitive impairment (aMCI), and a control group of 29 healthy elderly (HE) people. They all underwent a CT and AC in a counterbalanced order following a crossover design. Resting-state functional MRI and neuropsychological testing were acquired before and after each period. We tested post-CT and post-AC changes of cognitive abilities, of the functional connectivity of the DMN, and of topological network properties derived from graph theory and network-based statistics. Only CT produced functional changes, increasing the functional connectivity of the posterior DMN in all three groups. mAD also showed functional changes in the medial temporal lobe and topological changes in the anterior cingulum, whereas aMCI showed more widespread topological changes involving the frontal lobes, the cerebellum and the thalamus. Our results suggest specific functional connectivity changes after CT for aMCI and mAD.
Verbs in Mothers’ Input to Six-Month-Olds: Synchrony between Presentation, Meaning, and Actions Is Related to Later Verb Acquisition
Authors: Nomikou Iris , Koke Monique , Rohlfing Katharina J.
Published: May 2017

In embodied theories on language, it is widely accepted that experience in acting generates an expectation of this action when hearing the word for it. However, how this expectation emerges during language acquisition is still not well understood. Assuming that the intermodal presentation of information facilitates perception, prior research had suggested that early in infancy, mothers perform their actions in temporal synchrony with language. Further research revealed that this synchrony is a form of multimodal responsive behavior related to the child’s later language development. Expanding on these findings, this article explores the relationship between action–language synchrony and the acquisition of verbs. Using qualitative and quantitative methods, we analyzed the coordination of verbs and action in mothers’ input to six-month-old infants and related these maternal strategies to the infants’ later production of verbs. We found that the verbs used by mothers in these early interactions were tightly coordinated with the ongoing action and very frequently responsive to infant actions. It is concluded that use of these multimodal strategies could significantly predict the number of spoken verbs in infants’ vocabulary at 24 months.
14N NMR Spectroscopy Study of Binding Interaction between Sodium Azide and Hydrated Fullerene
Authors: Chachibaia Tamar , Martin Pastor Manuel
Published: May 2017

Our study is the first attempt to study the interaction between NaN3 and hydrated fullerenes C60 by means of a non-chemical reaction-based approach. The aim is to study deviations of signals obtained by 14N NMR spectroscopy to detect the binding interaction between sodium azide and hydrated fullerene. We considered 14N NMR spectroscopy as one of the most suitable methods for the characterization of azides to show resonance signals corresponding to the three non-equivalent nitrogen atoms. The results demonstrate that there are changes in the chemical shift positions and line-broadening, which are related to the different molar ratios of NaN3:C60 in the samples.
Old Yellow Enzyme-Catalysed Asymmetric Hydrogenation: Linking Family Roots with Improved Catalysis
Authors: Scholtissek Anika , Tischler Dirk , Westphal Adrie , Van Berkel Willem , Paul Caroline
Published: May 2017

Asymmetric hydrogenation of activated alkenes catalysed by ene-reductases from the old yellow enzyme family (OYEs) leading to chiral products is of potential interest for industrial processes. OYEs’ dependency on the pyridine nucleotide coenzyme can be circumvented through established artificial hydride donors such as nicotinamide coenzyme biomimetics (NCBs). Several OYEs were found to exhibit higher reduction rates with NCBs. In this review, we describe a new classification of OYEs into three main classes by phylogenetic and structural analysis of characterized OYEs. The family roots are linked with their use as chiral catalysts and their mode of action with NCBs. The link between bioinformatics (sequence analysis), biochemistry (structure–function analysis), and biocatalysis (conversion, enantioselectivity and kinetics) can enable an early classification of a putative ene-reductase and therefore the indication of the binding mode of various activated alkenes.
Dynamic Processes on Gold-Based Catalysts Followed by Environmental Microscopies
Authors: Genty Eric , Jacobs Luc , Bocarmé Thierry Visart de , Barroo Cédric
Published: May 2017

Since the early discovery of the catalytic activity of gold at low temperature, there has been a growing interest in Au and Au-based catalysis for a new class of applications. The complexity of the catalysts currently used ranges from single crystal to 3D structured materials. To improve the efficiency of such catalysts, a better understanding of the catalytic process is required, from both the kinetic and material viewpoints. The understanding of such processes can be achieved using environmental imaging techniques allowing the observation of catalytic processes under reaction conditions, so as to study the systems in conditions as close as possible to industrial conditions. This review focuses on the description of catalytic processes occurring on Au-based catalysts with selected in situ imaging techniques, i.e., PEEM/LEEM, FIM/FEM and E-TEM, allowing a wide range of pressure and material complexity to be covered. These techniques, among others, are applied to unravel the presence of spatiotemporal behaviours, study mass transport and phase separation, determine activation energies of elementary steps, observe the morphological changes of supported nanoparticles, and finally correlate the surface composition with the catalytic reactivity.
Functional and Biochemical Analysis of Glucose-6-Phosphate Dehydrogenase (G6PD) Variants: Elucidating the Molecular Basis of G6PD Deficiency
Authors: Gómez-Manzo Saúl , Marcial-Quino Jaime , Ortega-Cuellar Daniel , Serrano-Posada Hugo , González-Valdez Abigail , Vanoye-Carlo America , Hernández-Ochoa Beatriz , Sierra-Palacios Edgar , Castillo-Villanueva Adriana , Reyes-Vivas Horacio
Published: May 2017

G6PD deficiency is the most common enzymopathy, leading to alterations in the first step of the pentose phosphate pathway, which interferes with the protection of the erythrocyte against oxidative stress and causes a wide range of clinical symptoms of which hemolysis is one of the most severe. The G6PD deficiency causes several abnormalities that range from asymptomatic individuals to more severe manifestations that can lead to death. Nowadays, only 9.2% of all recognized variants have been related to clinical manifestations. It is important to understand the molecular basis of G6PD deficiency to understand how gene mutations can impact structure, stability, and enzymatic function. In this work, we reviewed and compared the functional and structural data generated through the characterization of 20 G6PD variants using different approaches. These studies showed that severe clinical manifestations of G6PD deficiency were related to mutations that affected the catalytic and structural nicotinamide adenine dinucleotide phosphate (NADPH) binding sites, and suggests that the misfolding or instability of the 3D structure of the protein could compromise the half-life of the protein in the erythrocyte and its activity.
Photocatalytic Graphene-TiO2 Thin Films Fabricated by Low-Temperature Ultrasonic Vibration-Assisted Spin and Spray Coating in a Sol-Gel Process
Authors: Zabihi Fatemeh , Ahmadian-Yazdi Mohammad-Reza , Eslamian Morteza
Published: May 2017

In this work, we communicate a facile and low temperature synthesis process for the fabrication of graphene-TiO2 photocatalytic composite thin films. A sol-gel chemical route is used to synthesize TiO2 from the precursor solutions and spin and spray coating are used to deposit the films. Excitation of the wet films during the casting process by ultrasonic vibration favorably influences both the sol-gel route and the deposition process, through the following mechanisms. The ultrasound energy imparted to the wet film breaks down the physical bonds of the gel phase. As a result, only a low-temperature post annealing process is required to eliminate the residues to complete the conversion of precursors to TiO2. In addition, ultrasonic vibration creates a nanoscale agitating motion or microstreaming in the liquid film that facilitates mixing of TiO2 and graphene nanosheets. The films made based on the above-mentioned ultrasonic vibration-assisted method and annealed at 150 °C contain both rutile and anatase phases of TiO2, which is the most favorable configuration for photocatalytic applications. The photoinduced and photocatalytic experiments demonstrate effective photocurrent generation and elimination of pollutants by graphene-TiO2 composite thin films fabricated via scalable spray coating and mild temperature processing, the results of which are comparable with those made using lab-scale and energy-intensive processes.
Strain Effects by Surface Oxidation of Cu3N Thin Films Deposited by DC Magnetron Sputtering
Authors: Majumdar Abhijit , Drache Steffen , Wulff Harm , Mukhopadhyay Arun , Bhattacharyya Satyaranjan , Helm Christiane , Hippler Rainer
Published: May 2017

We report the self-buckling (or peeling off) of cubic Cu3N films deposited by DC magnetron sputtering of a Cu target in a nitrogen environment at a gas pressure of 1 Pa. The deposited layer partially peels off as it is exposed to ambient air at atmospheric pressure, but still adheres to the substrate. The chemical composition of the thin film as investigated by means of X-ray photoelectron spectroscopy (XPS) shows a considerable surface oxidation after exposure to ambient air. Grazing incidence X-ray diffraction (GIXRD) confirms the formation of a crystalline Cu3N phase of the quenched film. Notable are the peak shifts in the deposited film to smaller angles in comparison to stress-free reference material. The X-ray pattern of Cu3N exhibits clear differences in the integral width of the line profiles. Changes in the film microstructure are revealed by X-ray diffraction, making use of X-ray line broadening (Williamson–Hall and Stokes–Fourier/Warren–Averbach method); it indicates that the crystallites are anisotropic in shape and show remarkable stress and micro-strain.
A Specified Procedure for Distress Identification and Assessment for Urban Road Surfaces Based on PCI
Authors: Loprencipe Giuseppe , Pantuso Antonio
Published: May 2017

In this paper, a simplified procedure for the assessment of pavement structural integrity and the level of service for urban road surfaces is presented. A sample of 109 Asphalt Concrete (AC) urban pavements of an Italian road network was considered to validate the methodology. As part of this research, the most recurrent defects, those never encountered and those not defined with respect to the list collected in the ASTM D6433 have been determined by statistical analysis. The goal of this research is the improvement of the ASTM D6433 Distress Identification Catalogue to be adapted to urban road surfaces. The presented methodology includes the implementation of a Visual Basic for Application (VBA) language-based program for the computerization of Pavement Condition Index (PCI) calculation with interpolation by the parametric cubic spline of all of the density/deduct value curves of ASTM D6433 distress types. Also, two new distress definitions (for manholes and for tree roots) and new density/deduct curve values were proposed to achieve a new distress identification manual for urban road pavements. To validate the presented methodology, for the 109 urban pavements considered, the PCI was calculated using the new distress catalogue and using the ASTM D6433 implemented on PAVERTM. The results of the linear regression between them and their statistical parameters are presented in this paper. The comparison of the results shows that the proposed method is suitable for the identification and assessment of observed distress in urban pavement surfaces at the PCI-based scale.
Cooperative Particle Filtering for Tracking ERP Subcomponents from Multichannel EEG
Authors: Monajemi Sadaf , Jarchi Delaram , Ong Sim-Heng , Sanei Saeid
Published: May 2017

In this study, we propose a novel method to investigate P300 variability over different trials. The method incorporates spatial correlation between EEG channels to form a cooperative coupled particle filtering method that tracks the P300 subcomponents, P3a and P3b, over trials. Using state space systems, the amplitude, latency, and width of each subcomponent are modeled as the main underlying parameters. With four electrodes, two coupled Rao-Blackwellised particle filter pairs are used to recursively estimate the system state over trials. A number of physiological constraints are also imposed to avoid generating invalid particles in the estimation process. Motivated by the bilateral symmetry of ERPs over the brain, the channels further share their estimates with their neighbors and combine the received information to obtain a more accurate and robust solution. The proposed algorithm is capable of estimating the P300 subcomponents in single trials and outperforms its non-cooperative counterpart.
Fractional Diffusion in a Solid with Mass Absorption
Authors: Povstenko Yuriy , Kyrylych Tamara , Rygał Grażyna
Published: May 2017

The space-time-fractional diffusion equation with the Caputo time-fractional derivative and Riesz fractional Laplacian is considered in the case of axial symmetry. Mass absorption (mass release) is described by a source term proportional to concentration. The integral transform technique is used. Different particular cases of the solution are studied. The numerical results are illustrated graphically.
Fréchet Distribution Applied to Salary Incomes in Spain from 1999 to 2014. An Engineering Approach to Changes in Salaries’ Distribution
Authors: Pindado Santiago , Pindado Carlos , Cubas Javier
Published: May 2017

The official data in relation to salaries paid in Spain from 1999 to 2014 has been analyzed. The inadequate data format does not reflect the whole salary distribution. Fréchet distributions have been fitted to the data. This simple distribution has similar accuracy in relation to the data when compared to other distributions (Log-Normal, Gamma, Dagum, GB2). Analysis of the data through the fitted Fréchet distributions reveals a tendency towards more balanced (i.e., less skewed) salary distributions from 2002 to 2014 in Spain.
Conceptualizations of Students with and without Disabilities as Mathematical Problem Solvers in Educational Research: A Critical Review
Authors: Lambert Rachel , Tan Paulo
Published: May 2017

Students with disabilities are often framed as “the problem” and have limited opportunities to engage in standards based mathematics, leading to persistent underachievement. In this paper, we investigate a research divide between mathematics educational research for students with and without disabilities, a divide with significant differences in the theoretical orientations and research methodologies used to understand learners. Based on an analysis of 149 mathematics educational research articles published between 2013 and 2015, we found significant differences between articles focused on learners with and without disabilities. For those with disabilities, mathematical problem solving was understood primarily from behavioral and information processing theoretical perspectives, while for those without disabilities, problem solving was understood primarily through constructivist and sociocultural perspectives. While 86% of research on problem-solving including students with disabilities was quantitative, only 35% of research on students without disabilities was quantitative. Fifty percent of problem-solving research on students without disabilities was qualitative, compared to only 6% of research on students with disabilities. Problem solving, then, is studied in very different ways for learners with and without disabilities. Students without disabilities are studied through close analysis of learning, often individual. Students with disabilities are most often studied quantitatively, in groups, with little analysis of individual thinking. By offering only a limited range of methods and theoretical orientations, this research divide reifies deficit constructions of students with disabilities.
Comparison of Solar Radiation Models to Estimate Direct Normal Irradiance for Korea
Authors: Lee Hyun-Jin , Kim Shin-Young , Yun Chang-Yeol
Published: May 2017

Reliable solar radiation data are important for energy simulations in buildings and solar energy systems. Although direct normal irradiance (DNI) is required for simulations, in addition to global horizontal irradiance (GHI), a lack of DNI measurement data is quite often due to high cost and maintenance. Solar radiation models are widely used in order to overcome the limitation, but only a few studies have been devoted to solar radiation data and modeling in Korea. This study investigates the most suitable solar radiation model that converts GHI into DNI for Korea, using measurement data of the city of Daejeon from 2007 to 2009. After ten existing models were evaluated, the Reindl-2 model was selected as the best. A new model was developed for further improvement, and it substantially decreased estimation errors compared to the ten investigated models. The new model was also evaluated for nine major cities other than Daejeon from the standpoint of typical meteorological year (TMY) data, and consistent evaluation results confirmed that the new model is reliably applicable across Korea.
Electricity Production by the Application of a Low Voltage DC-DC Boost Converter to a Continuously Operating Flat-Plate Microbial Fuel Cell
Authors: Song Young , Boghani Hitesh , Kim Hong , Kim Byung , Lee Taeho , Jeon Byong-Hun , Premier Giuliano , Kim Jung
Published: May 2017

An ultra-low voltage customized DC-DC booster circuit was developed using a LTC3108 converter, and used continuously on a flat-plate microbial fuel cell (FPM) system. The boost converter successfully stepped up the microbial fuel cell (MFC) voltage from ~0.5 V to 3.3 and 5.0 V of outputs. The designed circuit and system displayed the dynamic variations of the source FPM as well as the output voltage through the designed three connection points within the booster circuit. The source MFC voltage was interrelated with the booster circuit and its performance, and it adapted to the set points of the booster dynamically. The maximum output power density of the MFC with the DC-DC booster circuit was 8.16 W/m3 compared to the maximum source FPM input power of 14.27 W/m3 at 100 Ω, showing a conversion efficiency of 26–57%, but with a 10-fold higher output than that of the source voltage. The combined LTC3108 with FPM supplied power for electronic devices using synthetic and real domestic wastewater. This report presents a promising strategy for utilizing the electrical energy produced from MFCs, and expands the applicability of bioelectrochemical systems with an improved energy efficiency of the present wastewater treatment system.
China’s Energy Transition in the Power and Transport Sectors from a Substitution Perspective
Authors: Han Shangfeng , Zhang Baosheng , Sun Xiaoyang , Han Song , Höök Mikael
Published: May 2017

Facing heavy air pollution, China needs to transition to a clean and sustainable energy system, especially in the power and transport sectors, which contribute the highest greenhouse gas (GHG) emissions. The core of an energy transition is energy substitution and energy technology improvement. In this paper, we forecast the levelized cost of electricity (LCOE) for power generation in 2030 in China. Cost-emission effectiveness of the substitution between new energy vehicles and conventional vehicles is also calculated in this study. The results indicate that solar photovoltaic (PV) and wind power will be cost comparative in the future. New energy vehicles are more expensive than conventional vehicles due to their higher manufacturer suggested retail price (MSRP). The cost-emission effectiveness of the substitution between new energy vehicles and conventional vehicles would be $96.7/ton or $114.8/ton. Gasoline prices, taxes, and vehicle insurance will be good directions for policy implementation after the ending of subsidies.
Management System for Large Li-Ion Battery Packs with a New Adaptive Multistage Charging Method
Authors: Velho Ricardo , Beirão Miguel , Calado Maria , Pombo José , Fermeiro João , Mariano Sílvio
Published: May 2017

Among the wide diversity of existing technologically mature batteries, lithium-ion (Li-ion) batteries have become popular because of their longevity, high energy density, high efficiency and lack of memory effect. Differential charging of cells with age has turned balancing management systems into an important research subject. This paper proposes a new battery management system (BMS) to improve the capacity usage and lifespan of large Li-ion battery packs and a new charging algorithm based on the traditional multistage method. The main advantages of the proposed system are its versatility and ability to implement different charging and balancing methods in a very accessible way. The combination of charging methods with balancing methods represents an evolution when compared with other works in the literature.
Optimization of Hybrid Energy Storage Systems at the Building Level with Combined Heat and Power Generation
Authors: Yu Dongmin , Liu Huanan , Yan Gangui , Jiang Jing , Le Blond Simon
Published: May 2017

The average daily benefit to cost ratio of a building energy storage system is mainly constrained by the battery lifetime. This paper aims to minimize the average daily cost of a hybrid energy storage system (HESS) (comprised of a battery and supercapacitor) by optimizing the battery capacity. A novel optimization model is proposed with the objective to find the minimum average daily investment cost of the HESS. The objective function has two parts: (1) the investment cost formula for the battery is derived as a function of the battery capacity, which has an interdependence with the minimum state of charge (SOC) and the maximum discharge current; (2) the investment cost formula for the supercapacitor is also established as a function of battery capacity by matching the maximum battery power with that of the supercapacitor. Case studies demonstrate several ways to increase the average daily benefit to cost ratio: (1) adopting a suitable control strategy to avoid capacity saturation; (2) reducing the battery SOC to increase the threshold for the maximum discharge current (MDC) saturation; and (3) increasing MDC to raise the threshold for the SOC saturation. Results show that the average daily benefit to cost ratio is doubled compared to previous work.
Harvesting-Aware Energy Management for Environmental Monitoring WSN
Authors: Rodway James , Musilek Petr
Published: May 2017

Wireless sensor networks can be used to collect data in remote locations, especially when energy harvesting is used to extend the lifetime of individual nodes. However, in order to use the collected energy most effectively, its consumption must be managed. In this work, forecasts of diurnal solar energies were made based on measurements of atmospheric pressure. These forecasts were used as part of an adaptive duty cycling scheme for node level energy management. This management was realized with a fuzzy logic controller that has been tuned using differential evolution. Controllers were created using one and two days of energy forecasts, then simulated in software. These controllers outperformed a human-created reference controller by taking more measurements while using less reserve energy during the simulated period. The energy forecasts were comparable to other available methods, while the method of tuning the fuzzy controller improved overall node performance. The combination of the two is a promising method of energy management.
A Data-Driven Method for Energy Consumption Prediction and Energy-Efficient Routing of Electric Vehicles in Real-World Conditions
Authors: De Cauwer Cedric , Verbeke Wouter , Coosemans Thierry , Faid Saphir , Van Mierlo Joeri
Published: May 2017

Limited driving range remains one of the barriers for widespread adoption of electric vehicles (EVs). To address the problem of range anxiety, this paper presents an energy consumption prediction method for EVs, designed for energy-efficient routing. This data-driven methodology combines real-world measured driving data with geographical and weather data to predict the consumption over any given road in a road network. The driving data are linked to the road network using geographic information system software that allows to separate trips into segments with similar road characteristics. The energy consumption over road segments is estimated using a multiple linear regression (MLR) model that links the energy consumption with microscopic driving parameters (such as speed and acceleration) and external parameters (such as temperature). A neural network (NN) is used to predict the unknown microscopic driving parameters over a segment prior to departure, given the road segment characteristics and weather conditions. The complete proposed model predicts the energy consumption with a mean absolute error (MAE) of 12–14% of the average trip consumption, of which 7–9% is caused by the energy consumption estimation of the MLR model. This method allows for prediction of energy consumption over any route in the road network prior to departure, and enables cost-optimization algorithms to calculate energy efficient routes. The data-driven approach has the advantage that the model can easily be updated over time with changing conditions.
An Energy Aware Unified Ant Colony System for Dynamic Virtual Machine Placement in Cloud Computing
Authors: Liu Xiao-Fang , Zhan Zhi-Hui , Zhang Jun
Published: May 2017

Energy efficiency is a significant topic in cloud computing. Dynamic consolidation of virtual machines (VMs) with live migration is an important method to reduce energy consumption. However, frequent VM live migration may cause a downtime of service. Therefore, the energy save and VM migration are two conflict objectives. In order to efficiently solve the dynamic VM consolidation, the dynamic VM placement (DVMP) problem is formed as a multiobjective problem in this paper. The goal of DVMP is to find a placement solution that uses the fewest servers to host the VMs, including two typical dynamic conditions of the assignment of new coming VMs and the re-allocation of existing VMs. Therefore, we propose a unified algorithm based on an ant colony system (ACS), termed the unified ACS (UACS), that works on both conditions. The UACS firstly uses sufficient servers to host the VMs and then gradually reduces the number of servers. With each especial number of servers, the UACS tries to find feasible solutions with the fewest VM migrations. Herein, a dynamic pheromone deposition method and a special heuristic information strategy are also designed to reduce the number of VM migrations. Therefore, the feasible solutions under different numbers of servers cover the Pareto front of the multiobjective space. Experiments with large-scale random workloads and real workload traces are conducted to evaluate the performance of the UACS. Compared with traditional heuristic, probabilistic, and other ACS based algorithms, the proposed UACS presents competitive performance in terms of energy consumption, the number of VM migrations, and maintaining quality of services (QoS) requirements.
Energy Return on Investment of Canadian Oil Sands Extraction from 2009 to 2015
Authors: Wang Ke , Vredenburg Harrie , Wang Jianliang , Xiong Yi , Feng Lianyong
Published: May 2017

Oil sands, as unconventional oil, are so essential to both Canada and the world that special attention should be paid to their extraction status, especially their energy efficiency. One of the most commonly used methods to evaluate energy efficiency is the Energy Return on Investment (EROI) analysis. This paper focuses on EROI analysis for both in situ oil sands and mining oil sands over the period of 2009 to 2015. This time period represents an extension to periods previously considered by other analyses. An extended Input-Output model is used to quantify indirect energy input, which has been ignored by previous analyses of oil sands extraction. Results of this paper show that EROI of both mining oil sands (range of value: 3.9–8) and in situ oil sands (range of value: 3.2–5.4) display an upward trend over the past 7 years; EROI of mining oil sands is generally higher, but is more fluctuating than the EROI of in situ oil sands. Compared with EROI of other hydrocarbons, the EROI of oil sands is still quite low, despite the fact that it is increasing gradually.
Research on Control Strategies of an Open-End Winding Permanent Magnet Synchronous Driving Motor (OW-PMSM)-Equipped Dual Inverter with a Switchable Winding Mode for Electric Vehicles
Authors: Chu Liang , Jia Yi-fan , Chen Dong-sheng , Xu Nan , Wang Yan-wei , Tang Xin , Xu Zhe
Published: May 2017

An open-end winding permanent magnet synchronous motor (PMSM) has a larger range of speed regulation than normal PMSM with the same DC voltage, and the control method is more flexible. It can also manage energy distribution between two power sources without a DC/DC converter. This paper aims at an electric vehicle equipped with OW-PMSM drive system with dual power sources and dual inverters; based on analyzing the external characteristics of each winding mode, we propose a winding mode switching strategy whose torque saturation judgmental algorithm, which is insensitive to motor’s parameters, could automatically realize upswitching of the winding mode. The proposed multi-level current hysteresis modulation algorithm could set the major power source and switch it at any time in independent mode, which accomplishes energy distribution between two power sources; its two control methods, low switching frequency method and high power difference method, could achieve different energy distribution effects. Simulation results confirm the validity and effectiveness of the winding mode switching strategy and current modulation method. They also show that an electric vehicle under the proposed control methods has better efficiency than one equipped with a traditional OW-PMSM drive system under traditional control.
Driver or Passenger: Epigenomes in Alzheimer’s Disease
Authors: Hoffmann Anke , Sportelli Vincenza , Ziller Michael , Spengler Dietmar
Published: May 2017

Alzheimer’s disease (AD) is a fatal neurodegenerative disease which is on the rise worldwide. Despite a wealth of information, genetic factors contributing to the emergence of AD still remain incompletely understood. Sporadic AD is polygenetic in nature and is associated with various environmental risks. Epigenetic mechanisms are well-recognized in the mediation of gene environment interactions, and analysis of epigenetic changes at the genome scale can offer new insights into the relationship between brain epigenomes and AD. In fact, recent epigenome-wide association studies (EWAS) indicate that changes in DNA methylation are an early event preceding clinical manifestation and are tightly associated with AD neuropathology. Further, candidate genes from EWAS interact with those from genome-wide association studies (GWAS) that can undergo epigenetic changes in their upstream gene regulatory elements. Functionally, AD-associated DNA methylation changes partially influence transcription of candidate genes involved in pathways relevant to AD. The timing of epigenomic changes in AD together with the genes affected indicate a critical role, however, further mechanistic insight is required to corroborate this hypothesis. In this respect, recent advances in neuronal reprogramming of patient-derived cells combined with new genome-editing techniques offer unprecedented opportunities to dissect the functional and mechanistic role of epigenomic changes in AD.
Cross-Talk between Physiological and Metabolic Adjustments Adopted by Quercus cerris to Mitigate the Effects of Severe Drought and Realistic Future Ozone Concentrations
Authors: Cotrozzi Lorenzo , Remorini Damiano , Pellegrini Elisa , Guidi Lucia , Lorenzini Giacomo , Massai Rossano , Nali Cristina , Landi Marco
Published: May 2017

Global climate change represents a moving target for plant acclimation and/or adaptation, especially in the Mediterranean basin. In this study, the interactions of severe drought (20% of the effective daily evapotranspiration) and O3 fumigation (80 ppb, 5 h day−1, for 28 consecutive days) on (i) photosynthetic performance, (ii) cell membrane stability, (iii) hydric relations, (iv) accumulation of compatible solutes, and (v) lipophilic antioxidant compounds were investigated in young Quercus cerris plants. In addition to the typical drought-induced stomatal closure, imposition of water withholding dramatically influenced the profile of stress-associated metabolites, i.e., abscisic acid (ABA), proline, and lipophilic antioxidants. However, plants were not able to delay or prevent the negative effects of water deficit, the greatest impacting factor in this study. This translated into a steep decline of photosynthetic efficiency, leaf hydration, and membrane fluidity and permeability. When water stress was coupled with O3, plants orchestrated cross-talk among ABA, proline, and sugar in fully-expanded mature leaves, partially leading to a premature senescence.
The Effect of Urban Green Spaces on the Urban Thermal Environment and Its Seasonal Variations
Authors: Yang Chaobin , He Xingyuan , Wang Ranghu , Yan Fengqin , Yu Lingxue , Bu Kun , Yang Jiuchun , Chang Liping , Zhang Shuwen
Published: May 2017

Urban green spaces have been shown to decrease land surface temperature (LST) significantly. However, few studies have explored the relationships between urban green spaces and LST across different seasons at different spatial scales. In this study, using Changchun, China as a case study, landscape ecology and comparative approaches were employed quantitatively to investigate the effects of the composition and configuration of urban green spaces on the urban thermal environments. LST maps were retrieved from Landsat 8 Thermal Infrared Sensor (TIRS) data acquired on four dates that represented four different seasons, and detailed information of urban green spaces was extracted from high resolution imagery GF-1. Normalized differential vegetation index (NDVI) and six landscape metrics at patch, class, and landscape level were used to characterize the spatial patterns of urban green spaces. The results showed that urban green spaces did have significant cooling effects in all seasons, except for winter, but the effects varied considerably across the different seasons and green types, and seemed to depend on the NDVI and size of urban green spaces. Compared to shape metrics, the negative relationships between the LST and the area and the NDVI of urban green spaces were more significant. Both the composition and configuration of urban green spaces can affect the distribution of LST. Based on findings with one city, given a fixed area of urban green spaces, the number of green patches can positively or negatively affect the LST, depending on if the number is larger than a threshold or not, and the threshold varies according to the given area. These findings provide new perspectives, and further research is also suggested, to generate a better understanding of how urban green spaces affect the urban thermal environment.
Private and Secure Distribution of Targeted Advertisements to Mobile Phones
Authors: Mamais Stylianos , Theodorakopoulos George
Published: May 2017

Online Behavioural Advertising (OBA) enables promotion companies to effectively target users with ads that best satisfy their purchasing needs. This is highly beneficial for both vendors and publishers who are the owners of the advertising platforms, such as websites and app developers, but at the same time creates a serious privacy threat for users who expose their consumer interests. In this paper, we categorize the available ad-distribution methods and identify their limitations in terms of security, privacy, targeting effectiveness and practicality. We contribute our own system, which utilizes opportunistic networking in order to distribute targeted adverts within a social network. We improve upon previous work by eliminating the need for trust among the users (network nodes) while at the same time achieving low memory and bandwidth overhead, which are inherent problems of many opportunistic networks. Our protocol accomplishes this by identifying similarities between the consumer interests of users and then allows them to share access to the same adverts, which need to be downloaded only once. Although the same ads may be viewed by multiple users, privacy is preserved as the users do not learn each other’s advertising interests. An additional contribution is that malicious users cannot alter the ads in order to spread malicious content, and also, they cannot launch impersonation attacks.
Developing a Water Quality Index (WQI) for an Irrigation Dam
Authors: De La Mora-Orozco Celia , Flores-Lopez Hugo , Rubio-Arias Hector , Chavez-Duran Alvaro , Ochoa-Rivero Jesus
Published: May 2017

Pollution levels have been increasing in water ecosystems worldwide. A water quality index (WQI) is an available tool to approximate the quality of water and facilitate the work of decision-makers by grouping and analyzing numerous parameters with a single numerical classification system. The objective of this study was to develop a WQI for a dam used for irrigation of about 5000 ha of agricultural land. The dam, La Vega, is located in Teuchitlan, Jalisco, Mexico. Seven sites were selected for water sampling and samples were collected in March, June, July, September, and December 2014 in an initial effort to develop a WQI for the dam. The WQI methodology, which was recommended by the Mexican National Water Commission (CNA), was used. The parameters employed to calculate the WQI were pH, electrical conductivity (EC), dissolved oxygen (DO), total dissolved solids (TDS), total hardness (TH), alkalinity (Alk), total phosphorous (TP), Cl−, NO3, SO4, Ca, Mg, K, B, As, Cu, and Zn. No significant differences in WQI values were found among the seven sampling sites along the dam. However, seasonal differences in WQI were noted. In March and June, water quality was categorized as poor. By July and September, water quality was classified as medium to good. Quality then decreased, and by December water quality was classified as medium to poor. In conclusion, water treatment must be applied before waters from La Vega dam reservoir can be used for irrigation or other purposes. It is recommended that the water quality at La Vega dam is continually monitored for several years in order to confirm the findings of this short-term study.