bluuebunny/crossref_metadata_2025 huggingface dataset:
Establishing an ANN-Based Risk Model for Ground Subsidence Along Railways
Authors: Lee Heesung , Oh Jeongho
Published: October 2018

Ground subsidence occurrences have drastically increased in the Seoul area of the Republic of Korea. The structural defects of underground utilities were found to be the primary cause of ground subsidence based on several field investigations. This paper presents a risk model that assesses the probability of occurrence of ground subsidence along railways. In this study, support vector machine (SVM) and multi-layer perceptron (MLP) approaches were successfully employed to develop an artificial neural network (ANN)-based risk model. The risk model, in conjunction with a database composed of underground utilities and geological boring data along urban railway networks, was utilized to develop a hazard map system. A limited field experimental program was conducted for the purpose of verification, resulting in a promising tool to effectively maintain railway networks.
Dynamic Pressure Analysis of Hemispherical Shell Vibrating in Unbounded Compressible Fluid
Authors: Liu Ping , Kaewunruen Sakdirat , Tang Bai-jian
Published: October 2018

This paper is the first to highlight the vibrations of a hemispherical shell structure interacting with both compressible and incompressible fluids. To precisely calculate the pressure of the shell vibrating in the air, a novel analytical approach has been established that has existed in very few publications to date. An analytical formulation that calculates pressure was developed by integrating both the ‘small-density method’ and the ‘Bessel function method’. It was considered that the hemispherical shell vibrates as a simple harmonic function, and the fluid is non-viscous. For comparison, the incompressible fluid model has been analyzed. Surprisingly, it is the first to report that the pressure of the shell surface is proportional to the vibration acceleration, and the velocity amplitude decreased at the rate of 1 r 2 when the fluid was incompressible. Otherwise, the surface pressure of the hemispherical shell was proportional to the vibration velocity, and the velocity amplitude decreased with the rate of 1 r when the fluid was compressible. The compressibility of fluid played an important role in the dynamic pressure of the shell structure. Furthermore, the scale factor derived by the theoretical approach was the product of the density and the sound velocity of the fluid ( ρ o c ) exactly. In this study, the analytical solutions were verified by the calibrated numerical simulations, and the analytical formulation were rigorously tested by extensive parametric studies. These new findings can be used to guide the optimal design of the spherical shell structure subjected to wind load, seismic load, etc.
Controlling Refraction Using Sub-Wavelength Resonators
Authors: Chen Yue , Lipton Robert
Published: October 2018

We construct metamaterials from sub-wavelength nonmagnetic resonators and consider the refraction of incoming signals traveling from free space into the metamaterial. We show that the direction of the transmitted signal is a function of its center frequency and bandwidth. The directionality of the transmitted signal and its frequency dependence is shown to be explicitly controlled by sub-wavelength resonances that can be calculated from the geometry of the sub-wavelength scatters. We outline how to construct a medium with both positive and negative index properties across different frequency bands in the near infrared and optical regime.
Differential Evolution: A Survey and Analysis
Authors: Eltaeib Tarik , Mahmood Ausif
Published: October 2018

Differential evolution (DE) has been extensively used in optimization studies since its development in 1995 because of its reputation as an effective global optimizer. DE is a population-based metaheuristic technique that develops numerical vectors to solve optimization problems. DE strategies have a significant impact on DE performance and play a vital role in achieving stochastic global optimization. However, DE is highly dependent on the control parameters involved. In practice, the fine-tuning of these parameters is not always easy. Here, we discuss the improvements and developments that have been made to DE algorithms. In particular, we present a state-of-the-art survey of the literature on DE and its recent advances, such as the development of adaptive, self-adaptive and hybrid techniques.
Modeling of Building Energy Consumption for Accommodation Buildings (Lodging Sector) in Japan—Case Study
Authors: Alkhalaf Haitham , Yan Wanglin
Published: October 2018

The energy performance of residential and commercial buildings is a vital topic because of the rapid urbanization occurring throughout the world. Accommodation buildings are considered energy intensive compared to other commercial facilities. In addition, they are the main component of the tourism industry. Therefore, various actions and policies have been introduced to improve the energy performance of accommodation buildings. This research depends on a national scale database of energy consumption of commercial buildings in Japan. It is the main source of data to conduct this study. The Database for Energy Consumption of Commercial buildings (DECC) is a national survey that is provided by the Japan Sustainable Building Consortium (JSBC). Based on the DECC, the study presents a general benchmark which is developed by applying regression and artificial neural network (ANN) methods to assess the energy performance of accommodation buildings in the Kanto region, Japan. The study presents a broad benchmark to evaluate basic energy consumption of accommodation building with three variables. In addition, the study highlights the necessity of designing the ANN model through the choosing of hidden layers and training method. The outcomes of each learning method and hidden layer was examined using main indicators to verify its accuracy.
A Review: Carbon Additives in LiMnPO4- and LiCoO2-Based Cathode Composites for Lithium Ion Batteries
Authors: Kwon Nam , Mouck-Makanda Divine , Fromm Katharina
Published: October 2018

Carbon plays a critical role in improving the electronic conductivity of cathodes in lithium ion batteries. Particularly, the characteristics of carbon and its composite with electrode material strongly affect battery properties, governed by electron as well as Li+ ion transport. We have reviewed here various types of carbon materials and organic carbon sources in the production of conductive composites of nano-LiMnPO4 and LiCoO2. Various processes of making these composites with carbon or organic carbon sources and their characterization have been reviewed. Finally, the type and amount of carbon and the preparation methods of composites are summarized along with their battery performances and cathode materials. Among the different processes of making a composite, ball milling provided the benefit of dense and homogeneous nanostructured composites, leading to higher tap-density and thus increasing the volumetric energy densities of cathodes.
Variations of Alkaloid Accumulation and Gene Transcription in Nicotiana tabacum
Authors: Sun Bo , Tian Yu-Xiao , Zhang Fen , Chen Qing , Zhang Yong , Luo Ya , Wang Xiao-Rong , Lin Fu-Cheng , Yang Jun , Tang Hao-Ru
Published: October 2018

To increase the understanding of alkaloid biosynthesis in Nicotiana tabacum during whole plant growth periods, variations of the contents of alkaloids and the transcription of key biosynthetic genes in fresh leaves were investigated in three varieties at five developmental stages. Six alkaloids were analyzed by gas chromatograph–mass spectrometry (GC–MS) and the most abundant alkaloid was observed during the upper leaves maturing stage in the varieties, among which the alkaloid content of K326 was the highest. Considering the genetic effect, variance analysis indicated that the developmental stage played a predominant role in alkaloid accumulation. Moreover, the levels of biosynthetic gene transcripts in the leaves at the vigorous growing stage might contribute to the contents of alkaloids in the leaves during the maturing stages. To further illuminate the metabolism of alkaloid biosynthesis, a correlation among alkaloids was also documented.
FcRn Expression in Wildtype Mice, Transgenic Mice, and in Human Tissues
Authors: Li Tommy , Balthasar Joseph P.
Published: October 2018

Quantitative real-time PCR and Western blot methods were developed to assess neonatal Fc-receptor (FcRn) mRNA and protein expression in human FcRn transgenic mice, Swiss Webster mice, and in select human tissues. Additionally, FcRn turnover was evaluated via pulse-chase. FcRn mRNA expression was significantly higher in transgenic mice when compared to mouse FcRn mRNA in Swiss Webster mice and it ranged from 184-fold higher in the kidney to 109,000-fold higher in the skin. FcRn protein expression was found to be 13-fold lower in kidney to 5.6-fold higher in lung obtained from transgenic mice compared to FcRn protein expression in lung samples obtained from Swiss Webster mice. FcRn protein expression in human liver and small intestine tissues matched more closely with FcRn expression in Swiss Webster mice but were significantly lower when compared to values found from Swiss Webster and transgenic mice. Although FcRn mRNA expression correlated significantly with protein expression (p < 0.0005), the correlation coefficient was only 0.113. As such, the measurement of FcRn protein may be preferred to FcRn mRNA for quantitative applications. Significant differences were found in FcRn expression in transgenic mice, Swiss Webster mice, and human tissues, which may have implications for the use of mouse models in the assessment of monoclonal antibody disposition, efficacy, and safety.
Solving Multi-Objective Problems for Multifunctional and Sustainable Management in Maritime Pine Forest Landscapes
Authors: Pérez-Rodríguez Fernando , Nunes Luís , Azevedo João C.
Published: October 2018

Forest management based on sustainability and multifunctionality requires reliable and user-friendly tools to address several objectives simultaneously. In this work we present FlorNExT Pro®, a multiple-criteria landscape-scale forest planning and management computer tool, and apply it in a region in the north of Portugal to find optimized management solutions according to objectives such as maximization of net present value (NPV), volume growth, and carbon storage, and minimization of losses due to fire. Comparisons made among single- and multi-objective solutions were made to explore the range of possible indicators provided by the tool such as carbon sequestered, volume growth, probability of fire occurrence, volume of wood extracted, and evenness of harvesting in the management period. Results show that FlorNExT Pro® is a reliable, flexible, and useful tool to incorporate multiple criteria and objectives into spatially explicit complex management problems and to prepare sustainable and multifunctional forest management plans at the landscape level. FlorNExT Pro® is also suited to guiding and adapting forest management for uncertainty scenarios for the assessment of ecosystem services and fire risk, therefore playing an important role in the maintenance of sustainable landscapes in the south of Europe.
A New Technique in Rank Metric Code-Based Encryption
Authors: Lau Terry , Tan Chik
Published: October 2018

We propose a rank metric codes based encryption based on the hard problem of rank syndrome decoding problem. We propose a new encryption with a public key matrix by considering the adding of a random distortion matrix over F q m of full column rank n. We show that IND-CPA security is achievable for our encryption under assumption of the Decisional Rank Syndrome Decoding problem. Furthermore, we also prove some bounds for the number of matrices of a fixed rank with entries over a finite field. Our proposal allows the choice of the error terms with rank up to r 2 , where r is the error-correcting capability of a code. Our encryption based on Gabidulin codes has public key size of 13 . 68 KB, which is 82 times smaller than the public key size of McEliece Cryptosystem based on Goppa codes. For similar post-quantum security level of 2 140 bits, our encryption scheme has a smaller public key size than the key size suggested by LOI17 Encryption.
Identifying Systemically Important Companies by Using the Credit Network of an Entire Nation
Authors: Poledna Sebastian , Hinteregger Abraham , Thurner Stefan
Published: October 2018

The notions of systemic importance and systemic risk of financial institutions are closely related to the topology of financial liability networks. In this work, we reconstruct and analyze the financial liability network of an entire economy using data of 50,159 firms and banks. Our analysis contains 80.2% of the total liabilities of firms towards banks and all interbank liabilities in the Austrian banking system. The combination of firm-bank networks and interbank networks allows us to extend the concept of systemic risk to the real economy. In particular, the systemic importance of individual companies can be assessed, and for the first time, the financial ties between the financial and the real economy become explicitly visible. We find that firms contribute to systemic risk in similar ways as banks do. We identify a set of mid-sized companies that carry substantial systemic risk. Their default would affect up to 40% of the Austrian financial market. We find that all firms together create more systemic risk than the entire financial sector. In 2008, the total systemic risk of the Austrian interbank network amounted to only 29% of the total systemic risk of the entire financial network consisting of firms and banks. The work demonstrates that the notions of systemically important financial institutions (SIFIs) can be directly extended to firms.
An Information-Theoretic Approach to Self-Organisation: Emergence of Complex Interdependencies in Coupled Dynamical Systems
Authors: Rosas Fernando , Mediano Pedro A.M. , Ugarte Martín , Jensen Henrik J.
Published: October 2018

Self-organisation lies at the core of fundamental but still unresolved scientific questions, and holds the promise of de-centralised paradigms crucial for future technological developments. While self-organising processes have been traditionally explained by the tendency of dynamical systems to evolve towards specific configurations, or attractors, we see self-organisation as a consequence of the interdependencies that those attractors induce. Building on this intuition, in this work we develop a theoretical framework for understanding and quantifying self-organisation based on coupled dynamical systems and multivariate information theory. We propose a metric of global structural strength that identifies when self-organisation appears, and a multi-layered decomposition that explains the emergent structure in terms of redundant and synergistic interdependencies. We illustrate our framework on elementary cellular automata, showing how it can detect and characterise the emergence of complex structures.
When Complexity Is Your Friend: Modeling the Complex Problem Space of Vocabulary
Authors: Goodwin Amanda P. , Petscher Yaacov , Reynolds Dan , Lantos Tess , Gould Sara , Tock Jamie
Published: October 2018

The history of vocabulary research has specified a rich and complex construct, resulting in calls for vocabulary research, assessment, and instruction to take into account the complex problem space of vocabulary. At the intersection of vocabulary theory and assessment modeling, this paper suggests a suite of modeling techniques that model the complex structures present in vocabulary data in ways that can build an understanding of vocabulary development and its links to instruction. In particular, we highlight models that can help researchers and practitioners identify and understand construct-relevant and construct-irrelevant aspects of assessing vocabulary knowledge. Drawing on examples from recent research and from our own three-year project to develop a standardized measure of language and vocabulary, we present four types of confirmatory factor analysis (CFA) models: single-factor, correlated-traits, bi-factor, and tri-factor models. We highlight how each of these approaches offers particular insights into the complex problem space of assessing vocabulary in ways that can inform vocabulary assessment, theory, research, and instruction. Examples include identifying construct-relevant general or specific factors like skills or different aspects of word knowledge that could link to instruction while at the same time preventing an overly-narrow focus on construct-irrelevant factors like task-specific or word-specific demands. Implications for theory, research, and practice are discussed.
Education in Sustainable Development Goals Using the Spatial Data Infrastructures and the TPACK Model
Authors: Álvarez-Otero Javier , De Lázaro y Torres María Luisa
Published: October 2018

Education in Sustainable Development Goals is a basic step in attaining its objectives, and, therefore, it has been undertaken by broad sectors of the teaching community. Nevertheless, the “sustainability curriculum” derived from the Sustainable Development Goals, in this case based on the data of the Spatial Data Infrastructures, in spite of its teaching and research potential, is something with which the teaching body is not yet familiar. The results of the fieldwork carried out (questionnaires and Delphi technique) prove this to be the case. For this reason, in order to educate geographically in reflection and collaboration with the aims of the Sustainable Development Goals, the viewing, in a GIS on the Cloud (WebGIS) of indicators of interest is proposed for the Sustainable Development Goals taken from the Spatial Data Infrastructures within the framework of the TPACK (Technological Pedagogical Content Knowledge) model. To facilitate all these learning objectives, a proposal for good practices in the classrooms of secondary schools and another proposal for university lectures have been designed, and the results applied and analyzed. These examples demonstrate empirically that, with adequate pedagogical tools, an education in geography for global understanding by integrating Sustainable Development Goals and Spatial Data Infrastructures can be achieved, which is what the TPACK model pursues.
PVT-Robust CMOS Programmable Chaotic Oscillator: Synchronization of Two 7-Scroll Attractors
Authors: Carbajal-Gomez Victor Hugo , Tlelo-Cuautle Esteban , Sanchez-Lopez Carlos , Fernandez-Fernandez Francisco Vidal
Published: October 2018

Designing chaotic oscillators using complementary metal-oxide-semiconductor (CMOS) integrated circuit technology for generating multi-scroll attractors has been a challenge. That way, we introduce a current-mode piecewise-linear (PWL) function based on CMOS cells that allow programmable generation of 2–7-scroll chaotic attractors. The mathematical model of the chaotic oscillator designed herein has four coefficients and a PWL function, which can be varied to provide a high value of the maximum Lyapunov exponent. The coefficients are implemented electronically by designing operational transconductance amplifiers that allow programmability of their transconductances. Design simulations of the chaotic oscillator are provided for the 0.35 μ m CMOS technology. Post-layout and process–voltage–temperature (PVT) variation simulations demonstrate robustness of the multi-scroll chaotic attractors. Finally, we highlight the synchronization of two seven-scroll attractors in a master–slave topology by generalized Hamiltonian forms and observer approach. Simulation results show that the synchronized CMOS chaotic oscillators are robust to PVT variations and are suitable for chaotic secure communication applications.
Event-Triggered and Memory-Based Sliding Mode Variable Structure Control for Memristive Systems
Authors: Zheng Bo-Chao , Fei Shumin , Liu Xiaoguang
Published: October 2018

This paper is concerned with a novel event-triggered sliding mode variable structure control (ESMC) scheme to achieve robust stabilization of memristive systems (MSs). First, a memory-based sliding surface, including the past and the current information of the system states, is introduced. Two switching gain matrices of such kinds of switching surfaces, which satisfy the guaranteed cost performance of the sliding reduced order dynamics, are achieved by employing linear matrix inequality techniques. Second, a sliding mode controller using an event-triggered mechanism is constructed to ensure that the trajectories of the uncertain MS slide towards the proposed memory-based switching hyperplane, and thus, the stabilization of entire MSs is reached. Finally, the effectiveness of the proposed results is demonstrated through simulations.
Active EMI Reduction Using Chaotic Modulation in a Buck Converter with Relaxed Output LC Filter
Authors: Nguyen Van Ha , Huynh Hai Au , Kim SoYoung , Song Hanjung
Published: October 2018

DC-DC buck converters are widely used in portable applications because of their high power efficiency. However, their inherent fast switching releases electromagnetic emissions, making them prominent sources of electromagnetic interference (EMI). This paper proposes a voltage-controlled buck converter that reduces EMI by using a chaotic pulse-width modulation (PWM) technique based on a chaotic triangular ramp generator. The chaotic triangular ramp generator is constructed from a simple on-chip chaotic circuit linked with a symmetrically triangular ramp circuit. The proposed converter can thus operate in the chaotic mode reducing the EMI without requiring any EMI filters. Additionally, using the triangular ramp signal can relax the requirement for a large LC output filter in chaotic mode. The effectiveness of the proposed scheme was experimentally verified with a chaotic triangular ramp generator embedded in a voltage-mode controller buck converter using a 0.18 µm Complementary Metal Oxide Semiconductor (CMOS) process. The measurement results from a prototype showed that the EMI improvement from the proposed scheme is approximately 14.53 dB at the fundamental switching frequency with respect to the standard fixed-frequency PWM reference case.
Simulation Model of a 2-kW IPT Charger with Phase-Shift Control: Validation through the Tuning of the Coupling Factor
Authors: Vázquez Javier , Roncero-Sánchez Pedro , Parreño Torres Alfonso
Published: October 2018

When applied to road vehicle electrification, inductive power transfer (IPT) technology has the potential to boost the transition from combustion engines to electric motors powered by a battery pack. This work focuses on the validation of a PSpice circuit model developed as a replica of a 2-kW IPT prototype with series-series compensation operating at 18.65 kHz. The laboratory prototype has the three stages commonly found in an IPT system: an inverter, controlled by the phase-shift technique, a coil coupling and a load. Simulations were run with the circuit model for three different distances between the two coils of the inductive coupling, all of which are of interest for practical chargers: 125, 150 and 175 mm. The validation approach was based on tuning the magnetic coupling factor for each distance and a set of ten load resistances, until the best match between the simulated and the experimental peak currents supplied by the inverter was found in each case. The coupling factors obtained from the simulation work are in good agreement with their experimental counterparts for the three distances, provided the duty cycle of the inverter output voltage is not too small. The circuit model developed is, therefore, able to reproduce the behavior of the laboratory prototype with sufficient accuracy over a wide range of distances between coils and loading conditions.
Engineering Dielectric Liquid Applications
Authors: Fofana Issouf , Rao U. Mohan
Published: October 2018

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Day-Ahead Hierarchical Steady State Optimal Operation for Integrated Energy System Based on Energy Hub
Authors: Zhong Yongjie , Xie Dongliang , Zhai Suwei , Sun Yonghui
Published: October 2018

The integrated energy system (IES) has the characteristic of energy system integrated/multi-energy coupling that involves heat, cooling, electricity, natural gas, and various other energy forms, which can maximize the synergistic effects and complementary benefits among various energy forms and their comprehensive utilization. In this paper, based on energy hub (EH), the day-ahead hierarchical steady state optimal operation for IES is discussed, in which the coupling natural gas system, electricity transmission system, and district heating system are all considered. Firstly, the model architecture of EH with diverse storage devices, renewable energy, and different energy conversion equipment is proposed and the steady state mathematical model of different energy networks in IES is developed, respectively. Secondly, the day-ahead operating cost of EH is minimized by an optimizing strategy to maximize the benefits of all kinds of energy demand users, where different types of energy power input into EH can be obtained. Then, the day-ahead optimal operation mode for IES considering minimization of operating fuel cost index is proposed via an energy management system, which provides various energy power data that are uploaded from EH. Finally, numerical results are presented to verify the effectiveness and usefulness of the day-ahead hierarchical optimal operation and steady state calculation analysis for IES, which could further illustrate that the proposed optimal operation can meet the requirements of practical engineering applications.
Comparing Crude Oils with Different API Gravities on a Molecular Level Using Mass Spectrometric Analysis. Part 2: Resins and Asphaltenes
Authors: Santos Jandyson M. , Vetere Alessandro , Wisniewski Alberto , Eberlin Marcos N. , Schrader Wolfgang
Published: October 2018

The combination of fractionation methods for crude oils, such as saturate, aromatic, resin and asphaltene (SARA) fractionation, in combination with analysis by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) has been used for reducing the complexity and improving the characterization of crude oils. We have used the FT-ICR MS techniques in conjunction with electrospray ionization (ESI(±)) and atmospheric pressure photoionization (APPI(+)) to find trends between MS data of SARA fractions of crude oils with different American Petroleum Institute (API) gravities from the Sergipe-Alagoas basin (Brazil), focusing on the resin and asphaltene fractions. For the first time, an adaptation of the SARA fractionation has been performed to obtain a second resin fraction, which presented compounds with an intermediate aromaticity level between the first resins and asphaltene fraction. Both the first and second resin and the asphaltene fractions were studied on a molecular level using multiple ionization techniques and FT-ICR MS to find a direct relationship between the API gravities of a heavy, medium and light crude oil. For the FT-ICR MS data and the API gravities an aromaticity tendency was found. The data show that the use of SARA fractionation with FT-ICR MS offers a tool for comprehensive characterization of individual fractions and selective chemical characterization of the components in crude oils.
Large Eddy Simulation of Turbulent Attached Cavitating Flows around Different Twisted Hydrofoils
Authors: Hu Changli , Chen Guanghao , Yang Long , Wang Guoyu
Published: October 2018

In this paper, the turbulent attached cavitating flows around two different twisted hydrofoils, named as NACA0009 and Clark-y, are studied numerically, with emphasis on cavity shedding dynamic behavior and the turbulence flow structures. The computational method of large eddy simulation (LES) coupled with a homogeneous cavitation model is applied and assessed by previous experimental data. It was found that the predicted results were in good agreement with that of the experiment. The unsteady cavity morphology of the two hydrofoils undergoes a similar quasi-periodic process, but has different shedding dynamic behavior. The scale of the U-type shedding structures forming on the suction surface of NACA0009 is larger than that of Clark-y. This phenomenon is also present in the iso-surface distributions of Q-criterion. Otherwise, the time-averaged cavity morphology is dramatically different for the two hydrofoils, and it is found that the attached location of the cavity is closely related to the hydrofoil geometry. The time fluctuation of the lift force coefficients is affected significantly by the cavity shedding dynamics. Compared with NACA0009, the lift force of Clark-y shows more fluctuation, due to its complicated shedding behavior. Further analysis of the turbulent structure indicates that the more violent shedding behaviors can induce higher levels of turbulence velocity fluctuations.
Energy Consumption, Economic Growth, and CO2 Emissions in G20 Countries: Application of Adaptive Neuro-Fuzzy Inference System
Authors: Mardani Abbas , Streimikiene Dalia , Nilashi Mehrbakhsh , Arias Aranda Daniel , Loganathan Nanthakumar , Jusoh Ahmad
Published: October 2018

Understanding the relationships among CO2 emissions, energy consumption, and economic growth helps nations to develop energy sources and formulate energy policies in order to enhance sustainable development. The present research is aimed at developing a novel efficient model for analyzing the relationships amongst the three aforementioned indicators in G20 countries using an adaptive neuro-fuzzy inference system (ANFIS) model in the period from 1962 to 2016. In this regard, the ANFIS model has been used with prediction models using real data to predict CO2 emissions based on two important input indicators, energy consumption and economic growth. This study made use of the fuzzy rules through ANFIS to generalize the relationships of the input and output indicators in order to make a prediction of CO2 emissions. The experimental findings on a real-world dataset of World Development Indicators (WDI) revealed that the proposed model efficiently predicted the CO2 emissions based on energy consumption and economic growth. The direction of the interrelationship is highly important from the economic and energy policy-making perspectives for this international forum, as G20 countries are primarily focused on the governance of the global economy.
Soaking in Aqueous Ammonia (SAA) Pretreatment of Whole Corn Kernels for Cellulosic Ethanol Production from the Fiber Fractions
Authors: Norvell Katherine L. , Nghiem Nhuan P.
Published: October 2018

Corn fiber is a co-product of commercial ethanol dry-grind plants, which is processed into distillers dried grains with solubles (DDGS) and used as animal feed, yet it holds high potential to be used as feedstock for additional ethanol production. Due to the tight structural make-up of corn fiber, a pretreatment step is necessary to make the cellulose and hemicellulose polymers in the solid fibrous matrix more accessible to the hydrolytic enzymes. A pretreatment process was developed in which whole corn kernels were soaked in aqueous solutions of 2.5, 5.0, 7.5, and 10.0 wt% ammonia at 105 °C for 24 h. The pretreated corn then was subjected to a conventional mashing procedure and subsequent ethanol fermentation using a commercial strain of natural Saccharomyces cerevisiae with addition of a commercial cellulase. Pretreatment of the corn with 7.5 wt% ammonia solution plus cellulase addition gave the highest ethanol production, which improved the yield in fermentation using 25 wt% solid from 334 g ethanol/kg corn obtained in the control (no pretreatment and no cellulase addition) to 379 g ethanol/kg corn (a 14% increase). The process developed can potentially be implemented in existing dry-grind ethanol facilities as a “bolt-on” process for additional ethanol production from corn fiber, and this additional ethanol can then qualify as “cellulosic ethanol” by the Environmental Protection Agency’s (EPA’s) Renewable Fuels Standard and thereby receive RINs (Renewable Identification Numbers).
Simulations of Moisture Gradients in Wood Subjected to Changes in Relative Humidity and Temperature Due to Climate Change
Authors: Bylund Melin Charlotta , Hagentoft Carl-Eric , Holl Kristina , Nik Vahid M. , Kilian Ralf
Published: October 2018

Climate change is a growing threat to cultural heritage buildings and objects. Objects housed in historic buildings are at risk because the indoor environments in these buildings are difficult to control and often influenced by the outdoor climate. Hygroscopic materials, such as wood, will gain and release moisture during changes in relative humidity and temperature. These changes cause swelling and shrinkage, which may result in permanent damage. To increase the knowledge of climate-induced damage to heritage objects, it is essential to monitor moisture transport in wood. Simulation models need to be developed and improved to predict the influence of climate change. In a previous work, relative humidity and temperature was monitored at different depths inside wooden samples subjected to fluctuating climate over time. In this article, two methods, the hygrothermal building simulation software WUFI® Pro and the Simplified model, were compared in relation to the measured data. The conclusion was that both methods can simulate moisture diffusion and transport in wooden object with a sufficient accuracy. Using the two methods for predicted climate change data show that the mean RH inside wood is rather constant, but the RH minimum and maximum vary with the predicted scenario and the type of building used for the simulation.
Acid Neutralization by Mining Waste Dissolution under Conditions Relevant for Agricultural Applications
Authors: Van Noort Reinier , Mørkved Pål Tore , Dundas Siv Hjorth
Published: October 2018

The acidification of agricultural soils in high rainfall regions is usually countered by the application of finely ground calcite or dolomite. As this carbonate dissolves, soil pH is raised, but CO2 is released. Mining activities often produce large quantities of very fine silicate rock-derived powders that are commonly deposited in stockpiles. However, the dissolution of such powders can also result in an increase in pH, without any direct release of CO2. Of particular interest are those silicate powders that have a high reactivity and higher capacity for raising pH. In this contribution, we report experimental work addressing the dissolution of various silicate rock-derived powders that were produced during mining activities in Norway under conditions that were representative of weathering in agricultural soils. Three different powders—derived from Åheim dunite, Stjernøya nepheline syenite, or Tellnes ilmenite norite—were exposed to different acids at pH 4 in unstirred flow cells, and dissolution or leaching kinetics were determined from the changes in the fluid composition. Based on these kinetics, pH neutralization rates were determined for the individual powders and compared to expected values for carbonates. Based on this comparison, it is concluded that the application of silicate rock-derived powder dissolution to replace carbonate-based liming may not be feasible due to slower reaction rates, unless larger quantities of a finer particle size than normal are used. The application of larger volumes of slower-reacting silicates may have the additional benefit of reducing the required frequency of liming.
CCR6–CCL20 Axis in IBD: What Have We Learnt in the Last 20 Years?
Authors: Ranasinghe Ranmali , Eri Rajaraman
Published: October 2018

CC chemokine receptor 6 (CCR6) and its specific partner CC chemokine ligand 20 (CCL20) are known to play a pivotal role in intestinal inflammation. CCR6-associated inflammatory bowel disease (IBD) is already at the forefront of experimental inflammatory disease models, being the subject of numerous analytical studies. IBD is associated with two sub phenotypes, Crohn’s disease (CD) and ulcerative colitis (UC). Both these disease entities produce potent immune dysregulation followed by intense tissue damage within the gut mucosal system, initiating symptoms that are severely debilitating. Multiple causative factors are said to be responsible for IBD, but direct immune dysfunction is kindled by overplay of innate and adaptive immune responses produced against the luminal contents through the weakened or leaky gut epithelial barrier. Once immune homeostasis is not achieved by endogenous protective mechanisms, the self-assertive adaptive immunity mobilizes its various T and B cell cohorts, initializing their immune mechanisms by deploying the immune cells towards the site of infection. CCR6 and its unique solitary ligand CCL20 are small protein molecules that are abundantly expressed by T and B lymphocytes and act as chemotactic immune-modulatory envoys that help in the deployment of the effector lymphocyte arm of the immune system and produce two directly opposing outcomes in IBD. This dichotomous immunity consists of either immune tolerance or inflammation which then develops into a chronic state, remaining unresponsive to inherent immunity or targeted clinical therapy. In this review, we have identified large numbers of experimental studies that have employed both mouse models and clinical subjects spanning a period of nearly two decades and we have clustered these into 13 different groups. This review will provide greater understanding of the CCR6–CCL20 axis in IBD and identify gaps in the literature that can be filled in the future.
Development and Assessment of a Diagnostic DNA Oligonucleotide Microarray for Detection and Typing of Meningitis-Associated Bacterial Species
Authors: Bannister Stephanie A. , Kidd Stephen P. , Kirby Elizabeth , Shah Sonal , Thomas Anvy , Vipond Richard , Elmore Michael J. , Telfer Brunton Andrew , Marsh Peter , Green Steve , Silman Nigel J. , Kempsell Karen E.
Published: October 2018

Meningitis is commonly caused by infection with a variety of bacterial or viral pathogens. Acute bacterial meningitis (ABM) can cause severe disease, which can progress rapidly to a critical life-threatening condition. Rapid diagnosis of ABM is critical, as this is most commonly associated with severe sequelae with associated high mortality and morbidity rates compared to viral meningitis, which is less severe and self-limiting. We have designed a microarray for detection and diagnosis of ABM. This has been validated using randomly amplified DNA targets (RADT), comparing buffers with or without formamide, in glass slide format or on the Alere ArrayTubeTM (Alere Technologies GmbH) microarray platform. Pathogen-specific signals were observed using purified bacterial nucleic acids and to a lesser extent using patient cerebral spinal fluid (CSF) samples, with some technical issues observed using RADT and glass slides. Repurposing the array onto the Alere ArrayTubeTM platform and using a targeted amplification system increased specific and reduced nonspecific hybridization signals using both pathogen nucleic and patient CSF DNA targets, better revealing pathogen-specific signals although sensitivity was still reduced in the latter. This diagnostic microarray is useful as a laboratory diagnostic tool for species and strain designation for ABM, rather than for primary diagnosis.
The Guatemalan Construction Industry: Approach of Knowledge Regarding Work Risks Prevention
Authors: Hernández-Arriaza Francisco Arturo , Pérez-Alonso José , Gómez-Galán Marta , Salata Ferdinando
Published: October 2018

In the present work, the results are presented for the characterization of work risk prevention in the Guatemalan construction industry. This characterization has been carried out using a simple random sampling technique, employing a questionnaire that was structured into 3 groups of variables: 1. General company data; 2. Prevention and management activities regarding health and safety in the company and on the worksite; and 3. Health and safety in the contractor companies. Following the sampling phase, the data were introduced in a database format, and a preliminary analysis was performed on the studied variables, followed by a descriptive analysis and a multiple correspondence analysis. The main findings of the study emphasize that companies in the Guatemalan construction sector are characterized as dedicating most of their activity (52.0%) indistinctly between civil engineering work, building construction and other specialized construction, mainly working as contractors (47.5%). These are “medium-sized” companies, employing an average of 81.1 on-site workers, having an average of 6.8 on-site work crews, and grossing an average turnover of 1.29 million euros annually. Likewise, it found that the larger construction companies adopt better prevention and management measures for worksite health and safety the larger companies are correlated with a high awareness of experiencing worksite accidents, while medium-sized companies have medium-level awareness. Companies with fewer workers manage workplace risk prevention worse, with low accident risk awareness. This correlation between these indicative variables of company size and workplace risk management and prevention is clearly reflected in the four company “clusters” that have been identified as having homogenous characteristics using the multiple correspondence analysis technique. Companies in the Guatemalan construction sector should make a greater effort to improve manager and worker training regarding workplace risk prevention to increase the effectiveness of company prevention management.
Contemplative Practices: A Strategy to Improve Health and Reduce Disparities
Authors: Bruce Marino A. , Skrine Jeffers Kia , King Robinson Jan , Norris Keith C.
Published: October 2018

Health has many dimensions, and intolerance and lack of compassion may contribute to the poor health and disparities in our nation. Tolerance can convey an inherent paradox or dissonance that can be associated with stress. However, tolerance has a dimension of acceptance, an acknowledgement and acceptance of what “is” at the present moment, that can relieve tension associated with differing beliefs and practices. Compassionate consideration of others can be combined with acceptance to create harmony within and across individuals. In this article, we explore how contemplative practices can cultivate tolerance and compassion and contribute to improvements in individual and population health.
Combining AHP-Entropy Approach with GIS for Construction Waste Landfill Selection—A Case Study of Shenzhen
Authors: Ding Zhikun , Zhu Menglian , Wu Zezhou , Fu Yanbin , Liu Xia
Published: October 2018

With the recent fast economy development and rapid urbanization, the huge generation of construction waste has become a threat to sustainable development in China. Though efforts have been made to promote reuse and recycling of construction waste, landfilling of waste remains the most commonly adapted approach for construction waste disposal. As the space for landfills is limited and because of the negative issues in terms of environmental and social aspects that may be caused, the appropriate site selection of landfills is crucial. With this background, this paper aims to establish a framework for facilitating landfill selection for construction waste. To begin with, a total of sixteen factors that may influence landfill site selection were identified from a literature review. Then, based on the combined analytic hierarchy process (AHP) and entropy method, the weights and the final comprehensive scores of the identified factors were calculated. According to the derived results, potential sites for landfills were divided into three levels, namely the most appropriate (0.38%), appropriate (17.58%), and inappropriate (82.04%). The proposed decision-making methods in this paper can provide a valuable reference for the selection of construction waste landfill sites.
Association between Dry Eye Disease, Air Pollution and Weather Changes in Taiwan
Authors: Zhong Jia-Yu , Lee Yuan-Chieh , Hsieh Chia-Jung , Tseng Chun-Chieh , Yiin Lih-Ming
Published: October 2018

Dry eye disease (DED) has become a common eye disease in recent years and appears to be influenced by environmental factors. This study aimed to examine the association between the first occurrence of DED, air pollution and weather changes in Taiwan. We used the systematic sampling cohort database containing 1,000,000 insureds of the National Health Insurance of Taiwan from 2004 to 2013, and identified a total of 25,818 eligible DED subjects. Environmental data, including those of air pollutants, temperature and relative humidity, were retrieved from the environmental monitoring stations adjacent to subjects’ locations of clinics as exposure information. We applied the case-crossover design, which used the same subjects experiencing exposures on diagnosis days as cases and those on other days as controls. The descriptive statistics showed that the first occurrences of DED were the most for the elderly by age (53.6%), women by gender (68.9%), and spring by season (25.9%). Multivariate conditional logistic regression analyses indicated that carbon monoxide (CO), nitrogen dioxide (NO2), and temperature were positively associated with DED (p < 0.05), while relative humidity was negatively related (p < 0.001). Because CO and NO2 together are considered a surrogate of traffic emission, which is easier to control than the uprising temperature, it is suggested that efficient management and control of traffic emission may lower the probability of DED occurrence.
The Effect of Exchange Rate Volatility on International Trade and Foreign Direct Investment (FDI) in Developing Countries along “One Belt and One Road”
Authors: Latief Rashid , Lefen Lin
Published: October 2018

The “One Belt and One Road” (OBOR) project was started by the Chinese government with the aim of achieving sustainable economic development and increasing cooperation with other countries. This project has five major objectives, which include (i) increasing trade flow, (ii) encouraging policy coordination, (iii) improving connectivity, (iv) obtaining financial integration, and (v) fortifying closeness between people. This paper aims to analyze the effect of exchange rate volatility on international trade and foreign direct investment (FDI) in developing countries along “One Belt and One Road”. We selected seven developing countries which are part of this project, namely Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan and Sri Lanka. We collected panel data for the period 1995 to 2016 from the U.S. Heritage Foundation, International Financial Statistics (IFS) (a database developed by the International Monetary Fund), and World Development Indicators (WDI) (a database developed by the World Bank). We applied Generalized Autoregressive Conditional Heteroscedasticity (GARCH) (1,1) and threshold-Generalized Autoregressive Conditional Heteroscedasticity (TGARCH) (1,1) models to measure the exchange rate volatility. Furthermore, we employed a fixed effect model to analyze the relationship of exchange rate volatility with international trade and FDI. The results of this paper revealed that exchange rate volatility affects both international trade and FDI significantly but negatively in OBOR-related countries, which correlates with the economic theory arguing that exchange rate volatility may hurt international trade and FDI. It can be concluded that exchange rate volatility can adversely affect international trade and FDI inflows in OBOR-related countries.