bluuebunny/crossref_metadata_2025 huggingface dataset:
Numerical Study on Thermal Design of a Large-Area Hot Plate with Heating and Cooling Capability for Thermal Nanoimprint Lithography
Authors: Park Gyujin , Lee Changhee
Published: July 2019

A numerical study is conducted on the thermal performance of a large-area hot plate specifically designed as a heating and cooling tool for thermal nanoimprint lithography processes. The hot plate has the dimensions 240 mm × 240 mm × 20 mm, in which a series of cartridge heaters and cooling holes are installed. Stainless steel has been selected to endure the high molding pressures. A numerical model based on ANSYS Fluent is employed to predict the thermal behavior of the hot plate in both the heating and cooling phases. The proportional–integral–derivative (PID) thermal control of the device is modeled by adding user defined functions. The results of the numerical computations demonstrate that the use of cartridge heaters provides sufficient heat-up performance and the active liquid cooling in the cooling holes provides the required cool-down performance. However, a crucial technical issue is raised, namely that the proposed design poses a large temperature non-uniformity in the steady heating phase and in the transient cooling phase. As a remedy, a new hot plate in which heat pipes are installed in the cooling holes is considered. The numerical results show that the installation of heat pipes could enhance the temperature uniformity both in the heating and cooling phases.
Experiment Research on Micro-/Nano Processing Technology of Graphite as Basic MEMS Material
Authors: Zhang Cheng , Liu Yijin , Wu Mingge , Liao Ningbo
Published: July 2019

Graphite is expected to be a common choice for basic microelectromechanical-system (MEMS) material in the future. However, in order to become a basic MEMS material, it is very important for graphite to be adapted to the commonly-used micro-/nanoprocessing technology. Therefore, this paper used a directly lithography and etching process to study micro-, /nanoprocessing on graphite. The results show that the graphite surface is suitable for lithography, and that different shapes and sizes of photoresist patterns can be directly fabricated on the graphite surface. In addition, the micro-meter height of photoresist could still resist plasma etching when process nanometers height of graphite structures. Therefore, graphite with photoresist patterns were directly processed by etching, and nanometer amounts of graphite were etched. Moreover, micro-/nanoscale graphite structure with height ranges from 29.4 nm–30.9 nm were fabricated with about 23° sidewall.
Opacity Corrections for Resonance Silver Lines in Nano-Material Laser-Induced Plasma
Authors: EL Sherbini Ashraf M. , EL Farash Ahmed H. , EL Sherbini Tharwat M. , Parigger Christian G.
Published: July 2019

Q-switched laser radiation at wavelengths of 355, 532, and 1064 nm from a Nd: YAG laser was used to generate plasma in laboratory air at the target surface made of nano-silver particles of size 95 ± 10 nm. The emitted resonance spectra from the neutral silver at wavelengths of 327.9 nm and 338.2 nm indicate existence of self-reversal in addition to plasma self-absorption. Both lines were identified in emission spectra at different laser irradiation wavelengths with characteristic dips at the un-shifted central wavelengths. These dips are usually associated with self-reversal. Under similar conditions, plasmas at the corresponding bulk silver target were generated. The recorded emission spectra were compared to those obtained from the nano-material target. The comparisons confirm existence of self-reversal of resonance lines that emerge from plasmas produced at nano-material targets. This work suggests a method for recovery of the spectral line shapes and discusses practical examples. In addition, subsidiary calibration efforts that utilize the Balmer series Hα-line reveal that other Ag I lines at 827.35 nm and 768.7 nm are optically thin under variety of experimental conditions and are well-suited as reference lines for measurement of the laser plasma electron density.
Viability in Multiplex Lexical Networks and Machine Learning Characterizes Human Creativity
Authors: Stella Massimo , Kenett Yoed N.
Published: July 2019

Previous studies have shown how individual differences in creativity relate to differences in the structure of semantic memory. However, the latter is only one aspect of the whole mental lexicon, a repository of conceptual knowledge that is considered to simultaneously include multiple types of conceptual similarities. In the current study, we apply a multiplex network approach to compute a representation of the mental lexicon combining semantics and phonology and examine how it relates to individual differences in creativity. This multiplex combination of 150,000 phonological and semantic associations identifies a core of words in the mental lexicon known as viable cluster, a kernel containing simpler to parse, more general, concrete words acquired early during language learning. We focus on low (N = 47) and high (N = 47) creative individuals’ performance in generating animal names during a semantic fluency task. We model this performance as the outcome of a mental navigation on the multiplex lexical network, going within, outside, and in-between the viable cluster. We find that low and high creative individuals differ substantially in their access to the viable cluster during the semantic fluency task. Higher creative individuals tend to access the viable cluster less frequently, with a lower uncertainty/entropy, reaching out to more peripheral words and covering longer multiplex network distances between concepts in comparison to lower creative individuals. We use these differences for constructing a machine learning classifier of creativity levels, which leads to an accuracy of 65.0 ± 0.9 % and an area under the curve of 68.0 ± 0.8 % , which are both higher than the random expectation of 50%. These results highlight the potential relevance of combining psycholinguistic measures with multiplex network models of the mental lexicon for modelling mental navigation and, consequently, classifying people automatically according to their creativity levels.
Future-Ready Strategic Oversight of Multiple Artificial Superintelligence-Enabled Adaptive Learning Systems via Human-Centric Explainable AI-Empowered Predictive Optimizations of Educational Outcomes
Authors: HOW Meng-Leong
Published: July 2019

Artificial intelligence-enabled adaptive learning systems (AI-ALS) have been increasingly utilized in education. Schools are usually afforded the freedom to deploy the AI-ALS that they prefer. However, even before artificial intelligence autonomously develops into artificial superintelligence in the future, it would be remiss to entirely leave the students to the AI-ALS without any independent oversight of the potential issues. For example, if the students score well in formative assessments within the AI-ALS but subsequently perform badly in paper-based post-tests, or if the relentless algorithm of a particular AI-ALS is suspected of causing undue stress for the students, they should be addressed by educational stakeholders. Policy makers and educational stakeholders should collaborate to analyze the data from multiple AI-ALS deployed in different schools to achieve strategic oversight. The current paper provides exemplars to illustrate how this future-ready strategic oversight could be implemented using an artificial intelligence-based Bayesian network software to analyze the data from five dissimilar AI-ALS, each deployed in a different school. Besides using descriptive analytics to reveal potential issues experienced by students within each AI-ALS, this human-centric AI-empowered approach also enables explainable predictive analytics of the students’ learning outcomes in paper-based summative assessments after training is completed in each AI-ALS.
The Influence of the Initial Condition in the Transient Thermal Field Simulation Inside a Wall
Authors: Zozulák Marek , Vertaľ Marián , Katunský Dušan
Published: July 2019

The envelope structures of buildings are exposed to heat-humidity conditions. The heat and humidity flow through these structures depends on the boundary conditions of the indoor and outdoor environments. This paper shows different initial conditions for the determination of temperature spread. The aim is to bring certain results of temperature calculated considering the initial conditions. When temperature changes, heat flow also rapidly changes. In certain specific cases, it is necessary to consider the initial conditions of temperature—for example; when transient energy simulations of real buildings are carried out. The reasons as to why it is necessary to consider the initial conditions, are shown in the examples of one-layer assemblies. The test walls exposed to the transient hygrothermal conditions are placed in the outdoor test cell. The cell has a stable temperature and relative humidity, and outdoor weather conditions change. The measured data on these walls and the calculated values of the temperatures in the wall structure, according to the different initial conditions, are compared. The average difference of the mean by the simulation and the measured values is significant. For a simulation time of about five days, the initial condition for calculating the temperature in the center of the masonry is necessary.
Novel Apoptosis-Inducing Agents for the Treatment of Cancer, a New Arsenal in the Toolbox
Authors: Lim Bora , Greer Yoshimi , Lipkowitz Stanley , Takebe Naoko
Published: July 2019

Evasion from apoptosis is an important hallmark of cancer cells. Alterations of apoptosis pathways are especially critical as they confer resistance to conventional anti-cancer therapeutics, e.g., chemotherapy, radiotherapy, and targeted therapeutics. Thus, successful induction of apoptosis using novel therapeutics may be a key strategy for preventing recurrence and metastasis. Inhibitors of anti-apoptotic molecules and enhancers of pro-apoptotic molecules are being actively developed for hematologic malignancies and solid tumors in particular over the last decade. However, due to the complicated apoptosis process caused by a multifaceted connection with cross-talk pathways, protein–protein interaction, and diverse resistance mechanisms, drug development within the category has been extremely challenging. Careful design and development of clinical trials incorporating predictive biomarkers along with novel apoptosis-inducing agents based on rational combination strategies are needed to ensure the successful development of these molecules. Here, we review the landscape of currently available direct apoptosis-targeting agents in clinical development for cancer treatment and update the related biomarker advancement to detect and validate the efficacy of apoptosis-targeted therapies, along with strategies to combine them with other agents.
Immune Resistance and EGFR Antagonists in Colorectal Cancer
Authors: Giordano Guido , Remo Andrea , Porras Almudena , Pancione Massimo
Published: July 2019

Targeting the epidermal growth factor receptor (EGFR) either alone or in combination with chemotherapy in patients with RAS wild type metastatic colorectal cancer (mCRC) has revolutionized the treatment of CRC, but with less results than initially envisaged. In recent years, the discovery of multiple pathways leading to the escape from anti-EGFR therapy has revealed an enormous complexity and heterogeneity of human CRC due to the intrinsic genomic instability and immune/cancer cell interaction. Therefore, understanding the mechanistic basis of acquired resistance to targeted therapies represents a major challenge to improve the clinical outcomes of patients with CRC. The latest findings strongly suggest that complex molecular alterations coupled with changes of the immune tumor microenvironment may substantially contribute to the clinical efficacy of EGFR antagonist. In this review, we discuss the most recent findings that contribute to both primary and acquired anti-EGFR therapy resistance. In addition, we analyze how strategies aiming to enhance the favorable effects in the tumor microenvironment may contribute to overcome resistance to EGFR therapies.
Microwave-Mediated Continuous Hydrogen Abstraction Reaction from 2-PrOH Catalyzed by Platinum on Carbon Bead
Authors: Ichikawa Tomohiro , Matsuo Tomohiro , Tachikawa Takumu , Teranishi Wataru , Yamada Tsuyoshi , Sawama Yoshinari , Monguchi Yasunari , Sajiki Hironao
Published: July 2019

We developed a microwave-mediated continuous hydrogen production method from 2-PrOH using platinum on a spherical carbon-bead catalyst. The catalyst cartridge consisted of helical glass part, and straight glass part (helix−straight cartridge) was newly developed for the effective microwave heating of 2-PrOH in the presence of 5% Pt/CB. The microwave resonance was properly adjusted within 2.4−2.5 GHz using the helix−straight cartridge with the glass resonance-adjuster tube. The reaction was conducted by the irradiation of only 10 W of single-frequency microwaves and the catalyst was used continuously for at least 13 h without any loss of catalyst activity.
Destabilization of Eukaryote mRNAs by 5′ Proximal Stop Codons Can Occur Independently of the Nonsense-Mediated mRNA Decay Pathway
Authors: Gorgoni Barbara , Zhao Yun-Bo , Krishnan J. , Stansfield Ian
Published: July 2019

In eukaryotes, the binding of poly(A) binding protein (PAB) to the poly(A) tail is central to maintaining mRNA stability. PABP interacts with the translation termination apparatus, and with eIF4G to maintain 3′–5′ mRNA interactions as part of an mRNA closed loop. It is however unclear how ribosome recycling on a closed loop mRNA is influenced by the proximity of the stop codon to the poly(A) tail, and how post-termination ribosome recycling affects mRNA stability. We show that in a yeast disabled for nonsense mediated mRNA decay (NMD), a PGK1 mRNA with an early stop codon at codon 22 of the reading frame is still highly unstable, and that this instability cannot be significantly countered even when 50% stop codon readthrough is triggered. In an NMD-deficient mutant yeast, stable reporter alleles with more 3′ proximal stop codons could not be rendered unstable through Rli1-depletion, inferring defective Rli1 ribosome recycling is insufficient in itself to trigger mRNA instability. Mathematical modelling of a translation system including the effect of ribosome recycling and poly(A) tail shortening supports the hypothesis that impaired ribosome recycling from 5′ proximal stop codons may compromise initiation processes and thus destabilize the mRNA. A model is proposed wherein ribosomes undergo a maturation process during early elongation steps, and acquire competency to re-initiate on the same mRNA as translation elongation progresses beyond the very 5′ proximal regions of the mRNA.
Emerging Topics in Cardiometabolic and Psychologic Sequelae, Pathogenesis, and Treatment of Polycystic Ovarian Syndrome: A Review
Authors: Shah Rachana
Published: July 2019

Polycystic ovarian syndrome (PCOS) is a common endocrine disorder, affecting 6–10% of reproductive age women and influences the reproductive, metabolic, dermatologic, and psychiatric health of affected girls and women. Despite its prevalence, the pathogenesis of the disease is largely unknown, and treatment options are limited. Thus, PCOS has been a ripe area for research in recent years, and novel etiologic pathways, diagnostic parameters, and treatment options are being explored. This review focuses on recent data suggesting pathogenic and therapeutic considerations, as well as the psychiatric and metabolic sequelae of PCOS.
Fire Protection Performance and Thermal Behavior of Thin Film Intumescent Coating
Authors: Beh Jing Han , Yew Ming Chian , Yew Ming Kun , Saw Lip Huat
Published: July 2019

This paper presents the heat release characteristics, char formation and fire protection performance of thin-film intumescent coatings that integrate eggshell (ES) as an innovative and renewable flame-retardant bio-filler. A cone calorimeter was used to determine the thermal behavior of the samples in the condensed phase in line with the ISO 5660-1 standard. The fire resistance of the coatings was evaluated using a Bunsen burner test to examine the equilibrium temperature and formation of the char layer. The fire propagation test was also conducted according to BS 476: Part 6. On exposure, the samples X, Y, and Z were qualified to be Class 0 materials due to the indexes of fire propagation being below 12. Samples Y and Z reinforced with 3.50 wt.% and 2.50 wt.% of ES bio-filler, respectively, showed a significant improvement in reducing the heat release rate, providing a more uniform and thicker char layer. As a result, the addition of bio-filler content has proven to be efficient in stopping the fire propagation as well as reducing the total heat released and equilibrium temperature of the intumescent coatings.
State Transfer via On-Line State Estimation and Lyapunov-Based Feedback Control for a N-Qubit System
Authors: Harraz Sajede , Cong Shuang
Published: July 2019

In this paper, we propose a Lyapunov-based state feedback control for state transfer based on the on-line quantum state estimation (OQSE). The OQSE is designed based on continuous weak measurements and compressed sensing. The controlled system is described by quantum master equation for open quantum systems, and the continuous measurement operators are derived according to the dynamic equation of system. The feedback control law is designed based on the Lyapunov stability theorem, and a strict proof of proposed control laws are given. At each sampling time, the state is estimated on-line, which is used to design the control law. The simulation experimental results show the effectiveness of the proposed feedback control strategy.
Mobile Technology and Generation Z in the English Language Classroom—A Preliminary Study
Authors: Poláková Petra , Klímová Blanka
Published: July 2019

Every generation of students has different characteristics that reflect the conditions of the time period they were growing in. It is important for educators from all fields of study, especially English language teachers, to understand the generational differences and the learning preferences of students in order to create productive learning environments. In today’s technology driven era, students have different learning needs in comparison with their predecessors. To enhance language learning in the new generation, it is recommended to use mobile technology in class. Mobile devices and applications offer a wide range of activities that support language learning. The aim of this study was to discover if the students using mobile devices in the class got higher scores in tests than the students using traditional methods. The methods included pre- and post-tests, as well as a questionnaire survey. The results of this study reveal that the use of a mobile application had a positive effect on students’ achievement results as far as the vocabulary learning was concerned. The students using the app seemed to retain more words than the students in the control group. Furthermore, the results of the questionnaire showed that using the app was more enjoyable for students than the traditional teaching methods. In addition, it contributed to collaborative learning. However, the results also indicate that being a Generation Z student does not make him/her automatically interested in using mobile applications in the process of language acquisition. Considering the small number of participants, further studies are planned to confirm the results from the current preliminary study.
A Dynamic Learning Method for the Classification of the HEp-2 Cell Images
Authors: Vununu Caleb , Lee Suk-Hwan , Kwon Oh-Jun , Kwon Ki-Ryong
Published: July 2019

The complete analysis of the images representing the human epithelial cells of type 2, commonly referred to as HEp-2 cells, is one of the most important tasks in the diagnosis procedure of various autoimmune diseases. The problem of the automatic classification of these images has been widely discussed since the unfolding of deep learning-based methods. Certain datasets of the HEp-2 cell images exhibit an extreme complexity due to their significant heterogeneity. We propose in this work a method that tackles specifically the problem related to this disparity. A dynamic learning process is conducted with different networks taking different input variations in parallel. In order to emphasize the localized changes in intensity, the discrete wavelet transform is used to produce different versions of the input image. The approximation and detail coefficients are fed to four different deep networks in a parallel learning paradigm in order to efficiently homogenize the features extracted from the images that have different intensity levels. The feature maps from these different networks are then concatenated and passed to the classification layers to produce the final type of the cellular image. The proposed method was tested on a public dataset that comprises images from two intensity levels. The significant heterogeneity of this dataset limits the discrimination results of some of the state-of-the-art deep learning-based methods. We have conducted a comparative study with these methods in order to demonstrate how the dynamic learning proposed in this work manages to significantly minimize this heterogeneity related problem, thus boosting the discrimination results.
Practical Evaluation of VMAF Perceptual Video Quality for WebRTC Applications
Authors: García Boni , López-Fernández Luis , Gortázar Francisco , Gallego Micael
Published: July 2019

WebRTC is the umbrella term for several emergent technologies aimed to exchange real-time media in the Web. Like other media-related services, the perceived quality of WebRTC communication can be measured using Quality of Experience (QoE) indicators. QoE assessment methods can be classified as subjective (users’ evaluation scores) or objective (models computed as a function of different parameters). In this paper, we focus on VMAF (Video Multi-method Assessment Fusion), which is an emergent full-reference objective video quality assessment model developed by Netflix. VMAF is typically used to assess video streaming services. This paper evaluates the use of VMAF in a different type of application: WebRTC. To that aim, we present a practical use case built on the top of well-known open source technologies, such as JUnit, Selenium, Docker, and FFmpeg. In addition to VMAF, we also calculate other objective QoE video metrics such as Visual Information Fidelity in the pixel domain (VIFp), Structural Similarity (SSIM), or Peak Signal-to-Noise Ratio (PSNR) applied to a WebRTC communication in different network conditions in terms of packet loss. Finally, we compare these objective results with a subjective evaluation using a Mean Opinion Score (MOS) scale to the same WebRTC streams. As a result, we found a strong correlation of the subjective video quality perceived in WebRTC video calls with the objective results computed with VMAF and VIFp in comparison with SSIM and PSNR and their variants.
Exploiting Scalable Machine-Learning Distributed Frameworks to Forecast Power Consumption of Buildings
Authors: Cerquitelli Tania , Malnati Giovanni , Apiletti Daniele
Published: July 2019

The pervasive and increasing deployment of smart meters allows collecting a huge amount of fine-grained energy data in different urban scenarios. The analysis of such data is challenging and opening up a variety of interesting and new research issues across energy and computer science research areas. The key role of computer scientists is providing energy researchers and practitioners with cutting-edge and scalable analytics engines to effectively support their daily research activities, hence fostering and leveraging data-driven approaches. This paper presents SPEC, a scalable and distributed engine to predict building-specific power consumption. SPEC addresses the full analytic stack and exploits a data stream approach over sliding time windows to train a prediction model tailored to each building. The model allows us to predict the upcoming power consumption at a time instant in the near future. SPEC integrates different machine learning approaches, specifically ridge regression, artificial neural networks, and random forest regression, to predict fine-grained values of power consumption, and a classification model, the random forest classifier, to forecast a coarse consumption level. SPEC exploits state-of-the-art distributed computing frameworks to address the big data challenges in harvesting energy data: the current implementation runs on Apache Spark, the most widespread high-performance data-processing platform, and can natively scale to huge datasets. As a case study, SPEC has been tested on real data of an heating distribution network and power consumption data collected in a major Italian city. Experimental results demonstrate the effectiveness of SPEC to forecast both fine-grained values and coarse levels of power consumption of buildings.
Evaluation of the Multiple Reference Frame Approach for the Modelling of an Axial Cooling Fan
Authors: Franzke Randi , Sebben Simone , Bark Tore , Willeson Emil , Broniewicz Alexander
Published: July 2019

The modelling of rotating parts, such as axial fans, is one of the main challenges of current CFD simulations of industrial applications. Different methods are available, but the most commonly used is the multiple reference frame (MRF) method. This paper investigates how different flow properties, such as temperature, pressure and velocity, develop when passing through the MRF domain. The results are compared to the more physical rigid body motion (RBM) approach. It is found that the MRF method transports the upstream properties with the streamlines of the relative velocity from the upstream to the downstream interface. This leads to a non-physical rotation by an angle that is dependent on the length of the domain and the ratio between axial and tangential velocity in the MRF region. The temperature field is more affected than the flow field, since wake structures from upstream obstacles are destroyed due to the wake of the blades. Downstream structures affect the flow in the upstream region by an increase in static pressure, which causes the streamlines in the MRF zone to slow down. Depending on the size of the obstacle, this can cause substantial distortions in the upstream and downstream flow field.
Experimental Research on Controllability and Emissions of Jet-Controlled Compression Ignition Engine
Authors: Tian Hua , Cui Jingchen , Yang Tianhao , Fu Yao , Tian Jiangping , Long Wuqiang
Published: July 2019

Low-temperature combustions (LTCs), such as homogeneous charge compression ignition (HCCI), could achieve high thermal efficiency and low engine emissions by combining the advantages of spark-ignited (SI) engines and compression-ignited (CI) engines. Robust control of the ignition timing, however, still remains a hurdle to practical use. A novel technology of jet-controlled compression ignition (JCCI) was proposed to solve the issue. JCCI combustion phasing was controlled by hot jet formed from pre-chamber spark-ignited combustion. Experiments were done on a modified high-speed marine engine for JCCI characteristics research. The JCCI principle was verified by operating the engine individually in the mode of JCCI and in the mode of no pre-chamber jet under low- and medium-load working conditions. Effects of pre-chamber spark timing and intake charge temperature on JCCI process were tested. It was proven that the combustion phasing of the JCCI engine was closely related to the pre-chamber spark timing. A 20 °C temperature change of intake charge only caused a 2° crank angle change of the start of combustion. Extremely low nitrogen oxides (NOx) emission was achieved by JCCI combustion while keeping high thermal efficiency. The JCCI could be a promising technology for dual-fuel marine engines.
Online Parameter Identification and Joint Estimation of the State of Charge and the State of Health of Lithium-Ion Batteries Considering the Degree of Polarization
Authors: Xia Bizhong , Chen Guanghao , Zhou Jie , Yang Yadi , Huang Rui , Wang Wei , Lai Yongzhi , Wang Mingwang , Wang Huawen
Published: July 2019

The state of charge (SOC) and the state of health (SOH) are the two most important indexes of batteries. However, they are not measurable with transducers and must be estimated with mathematical algorithms. A precise model and accurate available battery capacity are crucial to the estimation results. An improved speed adaptive velocity particle swarm optimization algorithm (SAVPSO) based on the Thevenin model is used for online parameter identification, which is used with an unscented Kalman filter (UKF) to estimate the SOC. In order to achieve the cyclic update of the SOH, the concept of degree of polarization (DOP) is proposed. The cyclic update of available capacity is thus obtainable to conversely promote the estimation accuracy of the SOC. The estimation experiments in the whole aging process of batteries show that the proposed method can enhance the SOC estimation accuracy in the full battery life cycle with the cyclic update of the SOH, even in cases of operating aged batteries and under complex operating conditions.
The Development of Electromobility in Poland and EU States as a Tool for Management of CO2 Emissions
Authors: Tucki Karol , Orynycz Olga , Świć Antoni , Mitoraj-Wojtanek Mateusz
Published: July 2019

The article analyzes the dynamics of the development of the electromobility sector in Poland in the context of the European Union and due to the economic situation and development of the electromobility sector in the contexts of Switzerland and Norway. On the basis of obtained data, a forecast was made which foresees the most likely outlook of the electric car market in the coming years. The forecast was made using the creeping trend method, and extended up to 2030. As part of the analysis of the effect of the impact of electromobility, an original method was proposed for calculating the primary energy factor (PEF) primary energy ratio in the European Union and in its individual countries, which illustrates the conversion efficiency of primary energy into electricity and the overall efficiency of the power system. The original method was also verified, referring to the methods proposed by the Fraunhofer-Institut. On the basis of all previous actions and analyses, an assessment was made of the impact of the development of the electromobility sector on air quality in the countries studied. Carbon dioxide tank-to-wheels emission reductions which result from the conversion of the car fleet from conventional vehicles to electric motors were then calculated. In addition to reducing carbon dioxide emissions, other pollutant emissions were also calculated, such as carbon monoxide (CO), nitrogen oxides (NOx) and particulate matter (PM). The increase in the demand for electricity resulting from the needs of electric vehicles was also estimated. On this basis, and also on the basis of previously calculated primary energy coefficients, the emission reduction values have been adjusted for additional emissions resulting from the generation of electricity in power plants.
Determining the Optimized Hub Height of Wind Turbine Using the Wind Resource Map of South Korea
Authors: Lee Jung-Tae , Kim Hyun-Goo , Kang Yong-Heack , Kim Jin-Young
Published: July 2019

Although the size of the wind turbine has become larger to improve the economic feasibility of wind power generation, whether increases in rotor diameter and hub height always lead to the optimization of energy cost remains to be seen. This paper proposes an algorithm that calculates the optimized hub height to minimize the cost of energy (COE) using the regional wind profile database. The optimized hub height was determined by identifying the minimum COE after calculating the annual energy production (AEP) and cost increase, according to hub height increase, by using the wind profiles of the wind resource map in South Korea and drawing the COE curve. The optimized hub altitude was calculated as 75~80 m in the inland plain but as 60~70 m in onshore or mountain sites, where the wind profile at the lower layer from the hub height showed relatively strong wind speed than that in inland plain. The AEP loss due to the decrease in hub height was compensated for by increasing the rotor diameter, in which case COE also decreased in the entire region of South Korea. The proposed algorithm of identifying the optimized hub height is expected to serve as a good guideline when determining the hub height according to different geographic regions.
Characterization of Aminoacyl-tRNA Synthetases in Chromerids
Authors: Sharaf Abdoallah , Gruber Ansgar , Jiroutová Kateřina , Oborník Miroslav
Published: July 2019

Aminoacyl-tRNA synthetases (AaRSs) are enzymes that catalyze the ligation of tRNAs to amino acids. There are AaRSs specific for each amino acid in the cell. Each cellular compartment in which translation takes place (the cytosol, mitochondria, and plastids in most cases), needs the full set of AaRSs; however, individual AaRSs can function in multiple compartments due to dual (or even multiple) targeting of nuclear-encoded proteins to various destinations in the cell. We searched the genomes of the chromerids, Chromera velia and Vitrella brassicaformis, for AaRS genes: 48 genes encoding AaRSs were identified in C. velia, while only 39 AaRS genes were found in V. brassicaformis. In the latter alga, ArgRS and GluRS were each encoded by a single gene occurring in a single copy; only PheRS was found in three genes, while the remaining AaRSs were encoded by two genes. In contrast, there were nine cases for which C. velia contained three genes of a given AaRS (45% of the AaRSs), all of them representing duplicated genes, except AsnRS and PheRS, which are more likely pseudoparalogs (acquired via horizontal or endosymbiotic gene transfer). Targeting predictions indicated that AaRSs are not (or not exclusively), in most cases, used in the cellular compartment from which their gene originates. The molecular phylogenies of the AaRSs are variable between the specific types, and similar between the two investigated chromerids. While genes with eukaryotic origin are more frequently retained, there is no clear pattern of orthologous pairs between C. velia and V. brassicaformis.
Special Issue “Adductomics: Elucidating the Environmental Causes of Disease”
Authors: Pereira Sofia A. , Antunes Alexandra M. M.
Published: July 2019

Adductomics studies represent effective tools for providing additional insights into how exposure to reactive metabolites can underlie disease mechanisms. This special issue is focused not only on summarizing the analytical methodologies used for DNA, protein, and mercapturic acid adductomics tools but also on highlighting the opportunities and challenges for the application of this type of studies in biomedical research.
Contraceptive Behaviors in Polish Women Aged 18–35—A Cross-Sectional Study
Authors: Zgliczynska Magdalena , Szymusik Iwona , Sierocinska Aleksandra , Bajaka Armand , Rowniak Martyna , Sochacki-Wojcicka Nicole , Wielgos Miroslaw , Kosinska-Kaczynska Katarzyna
Published: July 2019

The aim was to evaluate contraceptive behaviors, and factors affecting them, in the population of Polish-speaking women. A cross-sectional study was performed on 6763 women, current contraceptive users, aged 18 to 35. An anonymous and voluntary questionnaire written in Polish, containing 33 questions, was distributed online from January to February 2017. The Internet and doctors were the most popular sources of information about contraception (82% and 73%, respectively). Upon choosing contraception, women paid the most attention to its efficacy (85%) and its impact on health (59%). The most common methods were combined oral contraceptives (38%) and condoms (24%). In total, 51% had chosen hormonal contraception, of which 68% experienced side effects. The most frequent were decreased libido (39%) and weight gain (22%). Factors associated with the usage of hormonal or non-hormonal contraception were: education, relationship status, parenthood, number of sexual partners, frequency of intercourses, sources of information about contraception, and factors considered most important when choosing a contraceptive method. The choice between short-acting and long-acting reversible contraception was influenced by age, relationship status, parenthood, smoking, sources of information about contraception, and factors considered most important when choosing a contraceptive method. Wide access to contraception, high-quality education, and counselling should become priorities in family planning healthcare.
Glyphosate’s Synergistic Toxicity in Combination with Other Factors as a Cause of Chronic Kidney Disease of Unknown Origin
Authors: Gunatilake Sarath , Seneff Stephanie , Orlando Laura
Published: July 2019

Chronic kidney disease of unknown etiology (CKDu) is a global epidemic. Sri Lanka has experienced a doubling of the disease every 4 or 5 years since it was first identified in the North Central province in the mid-1990s. The disease primarily affects people in agricultural regions who are missing the commonly known risk factors for CKD. Sri Lanka is not alone: health workers have reported prevalence of CKDu in Mexico, Nicaragua, El Salvador, and the state of Andhra Pradesh in India. A global search for the cause of CKDu has not identified a single factor, but rather many factors that may contribute to the etiology of the disease. Some of these factors include heat stroke leading to dehydration, toxic metals such as cadmium and arsenic, fluoride, low selenium, toxigenic cyanobacteria, nutritionally deficient diet and mycotoxins from mold exposure. Furthermore, exposure to agrichemicals, particularly glyphosate and paraquat, are likely compounding factors, and may be the primary factors. Here, we argue that glyphosate in particular is working synergistically with most of the other factors to increase toxic effects. We propose, further, that glyphosate causes insidious harm through its action as an amino acid analogue of glycine, and that this interferes with natural protective mechanisms against other exposures. Glyphosate’s synergistic health effects in combination with exposure to other pollutants, in particular paraquat, and physical labor in the ubiquitous high temperatures of lowland tropical regions, could result in renal damage consistent with CKDu in Sri Lanka.
Synergistic Effects of Climate Change and Marine Pollution: An Overlooked Interaction in Coastal and Estuarine Areas
Authors: Cabral Henrique , Fonseca Vanessa , Sousa Tânia , Costa Leal Miguel
Published: July 2019

Coastal areas have been increasingly affected by human activities, marine pollution and climate change are among the most important pressures affecting these environments. Human-induced pressures occur in a cumulative way and generate additive, antagonistic or synergistic effects. Knowledge on synergistic effects is crucial to coastal zone management, since they may imply a change in human uses of these systems, as well as dedicated action plans in order to reduce hazards and environmental risks. In this work, we provide an overview of the available literature on synergistic effects between climate change and chemical pollution, and discuss current knowledge, methodological approaches, and research gaps and needs. Interactions between these two pressures may be climate change dominant (climate change leads to an increase in contaminant exposure or toxicity) or contaminant-dominant (chemical exposure leads to an increase in climate change susceptibility), but the mechanistic drivers of such processes are not well known. Results from a few meta-analyses studies and reviews showed that synergistic interactions tend to be more frequent compared to additive and antagonistic ones. However, most of the studies are individual-based and assess the cumulative effects of a few contaminants individually in laboratory settings together with few climate variables, particularly temperature and pH. Nevertheless, a wide diversity of contaminants have already been individually tested, spanning from metals, persistent organic pollutants and, more recently, emergent pollutants. Population and community based approaches are less frequent but have generated very interesting and more holistic perspectives. Methodological approaches are quite diverse, from laboratory studies to mesocosm and field studies, or based on statistical or modelling tools, each with their own potential and limitations. More holistic comparisons integrating several pressures and their combinations and a multitude of habitats, taxa, life-stages, among others, are needed, as well as insights from meta-analyses and systematic reviews.
An Optimization-Based Approach to Social Network Group Decision Making with an Application to Earthquake Shelter-Site Selection
Authors: Zhang Hengjie , Wang Fang , Tang Huali , Dong Yucheng
Published: July 2019

The social network has emerged as an essential component in group decision making (GDM) problems. Thus, this paper investigates the social network GDM (SNGDM) problem and assumes that decision makers offer their preferences utilizing additive preference relations (also called fuzzy preference relations). An optimization-based approach is devised to generate the weights of decision makers by combining two reliable resources: in-degree centrality indexes and consistency indexes. Based on the obtained weights of decision makers, the individual additive preference relations are aggregated into a collective additive preference relation. Further, the alternatives are ranked from best to worst according to the obtained collective additive preference relation. Moreover, earthquakes have occurred frequently around the world in recent years, causing great loss of life and property. Earthquake shelters offer safety, security, climate protection, and resistance to disease and ill health and are thus vital for disaster-affected people. Selection of a suitable site for locating shelters from potential alternatives is of critical importance, which can be seen as a GDM problem. When selecting a suitable earthquake shelter-site, the social trust relationships among disaster management experts should not be ignored. To this end, the proposed SNGDM model is applied to evaluate and select earthquake shelter-sites to show its effectiveness. In summary, this paper constructs a novel GDM framework by taking the social trust relationship into account, which can provide a scientific basis for public emergency management in the major disasters field.
Comparative Proteomics and Physiological Analyses Reveal Important Maize Filling-Kernel Drought-Responsive Genes and Metabolic Pathways
Authors: Wang Xuan , Zenda Tinashe , Liu Songtao , Liu Guo , Jin Hongyu , Dai Liang , Dong Anyi , Yang Yatong , Duan Huijun
Published: July 2019

Despite recent scientific headway in deciphering maize (Zea mays L.) drought stress responses, the overall picture of key proteins and genes, pathways, and protein–protein interactions regulating maize filling-kernel drought tolerance is still fragmented. Yet, maize filling-kernel drought stress remains devastating and its study is critical for tolerance breeding. Here, through a comprehensive comparative proteomics analysis of filling-kernel proteomes of two contrasting (drought-tolerant YE8112 and drought-sensitive MO17) inbred lines, we report diverse but key molecular actors mediating drought tolerance in maize. Using isobaric tags for relative quantification approach, a total of 5175 differentially abundant proteins (DAPs) were identified from four experimental comparisons. By way of Venn diagram analysis, four critical sets of drought-responsive proteins were mined out and further analyzed by bioinformatics techniques. The YE8112-exclusive DAPs chiefly participated in pathways related to “protein processing in the endoplasmic reticulum” and “tryptophan metabolism”, whereas MO17-exclusive DAPs were involved in “starch and sucrose metabolism” and “oxidative phosphorylation” pathways. Most notably, we report that YE8112 kernels were comparatively drought tolerant to MO17 kernels attributable to their redox post translational modifications and epigenetic regulation mechanisms, elevated expression of heat shock proteins, enriched energy metabolism and secondary metabolites biosynthesis, and up-regulated expression of seed storage proteins. Further, comparative physiological analysis and quantitative real time polymerase chain reaction results substantiated the proteomics findings. Our study presents an elaborate understanding of drought-responsive proteins and metabolic pathways mediating maize filling-kernel drought tolerance, and provides important candidate genes for subsequent functional validation.
Chemerin and Cancer
Authors: Treeck Oliver , Buechler Christa , Ortmann Olaf
Published: July 2019

Chemerin is a multifunctional adipokine with established roles in inflammation, adipogenesis and glucose homeostasis. Increasing evidence suggest an important function of chemerin in cancer. Chemerin’s main cellular receptors, chemokine-like receptor 1 (CMKLR1), G-protein coupled receptor 1 (GPR1) and C-C chemokine receptor-like 2 (CCRL2) are expressed in most normal and tumor tissues. Chemerin’s role in cancer is considered controversial, since it is able to exert both anti-tumoral and tumor-promoting effects, which are mediated by different mechanisms like recruiting innate immune defenses or activation of endothelial angiogenesis. For this review article, original research articles on the role of chemerin and its receptors in cancer were considered, which are listed in the PubMed database. Additionally, we included meta-analyses of publicly accessible DNA microarray data to elucidate the association of expression of chemerin and its receptors in tumor tissues with patients’ survival.
Critical-Angle Differential Refractometry of Lossy Media: A Theoretical Study and Practical Design Issues
Authors: Koutsoumpos Spyridon , Giannios Panagiotis , Triantis Dimos , Moutzouris Konstantinos
Published: July 2019

At a critical angle of incidence, Fresnel reflectance at an interface between a front transparent and a rear lossy medium exhibits sensitive dependencies on the complex refractive index of the latter. This effect facilitates the design of optical sensors exploiting single (or multiple) reflections inside a prism (or a parallel plate). We determine an empirical framework that captures performance specifications of this sensing scheme, including sensitivity, detection limit, range of linearity and—what we define here as—angular acceptance bandwidth. Subsequently, we develop an optimization protocol that accounts for all relevant optical or geometrical variables and that can be utilized in any application.