bluuebunny/crossref_metadata_2025 huggingface dataset:
Anti-Oxidized LDL Antibodies and Coronary Artery Disease: A Systematic Review
Authors: van den Berg Victor J. , Vroegindewey Maxime M. , Kardys Isabella , Boersma Eric , Haskard Dorian , Hartley Adam , Khamis Ramzi
Published: October 2019

Antibodies to oxidized LDL (oxLDL) may be associated with improved outcomes in cardiovascular disease. However, analysis is restricted by heterogenous study design and endpoints. Our objective was to conduct a comprehensive systematic review assessing anti-oxLDL antibodies in relation to coronary artery disease (CAD). Through a systematic literature search, we identified all studies assessing the relationship of either, IgG or IgM ox-LDL/ copper-oxLDL/ malondialdehyde-LDL, with coronary atherosclerosis or cardiovascular events in populations with, and without, established CAD. Systematic review best practices were adhered to and study quality was assessed. An initial electronic database search identified 2059 records, which was subsequently followed by abstract and full-text review. Finally, we included 18 studies with over 1811 patients with CAD. The studies varied according to populations studied, conventional cardiovascular risk factors and interventional modalities used to assess CAD. IgM anti-oxLDL antibodies were found to indicate protection from more severe CAD and possibly cardiovascular events, whilst the relationship with IgG is more complex and difficult to elucidate, with studies reporting divergent results. In this systematic review, there is evidence that suggests a relationship between anti-oxLDL antibodies and CAD, especially for the IgM subclass. However, further studies, with well-characterized prospective cohorts, will be important to clarify these associations.
Quantitative Immunomorphological Analysis of Heat Shock Proteins in Thyroid Follicular Adenoma and Carcinoma Tissues Reveals Their Potential for Differential Diagnosis and Points to a Role in Carcinogenesis
Authors: Pitruzzella Alessandro , Paladino Letizia , Vitale Alessandra , Martorana Stefania , Cipolla Calogero , Graceffa Giuseppa , Cabibi Daniela , David Sabrina , Fucarino Alberto , Bucchieri Fabio , Cappello Francesco , Conway de Macario Everly , Macario Alberto , Rappa Francesca
Published: October 2019

Hsp27, Hsp60, Hsp70, and Hsp90 are chaperones that play a crucial role in cellular homeostasis and differentiation, but they may be implicated in carcinogenesis. Follicular neoplasms of the thyroid include follicular adenoma and follicular carcinoma. The former is a very frequent benign encapsulated nodule, whereas the other is a nodule that infiltrates the capsule, blood vessels and the adjacent parenchyma, with a tendency to metastasize. The main objective was to assess the potential of the Hsps in differential diagnosis and carcinogenesis. We quantified by immunohistochemistry Hsp27, Hsp60, Hsp70, and Hsp90 on thin sections of human thyroid tissue with follicular adenoma or follicular carcinoma, comparing the tumor with the adjacent peritumoral tissue. Hsp60, Hsp70, and Hsp90 were increased in follicular carcinoma compared to follicular adenoma, while Hsp27 showed no difference. Histochemical quantification of Hsp60, Hsp70, and Hsp90 allows diagnostic distinction between follicular adenoma and carcinoma, and between tumor and adjacent non-tumoral tissue. The quantitative variations of these chaperones in follicular carcinoma suggest their involvement in tumorigenesis, for instance in processes such as invasion of thyroid parenchyma and metastasization.
Resource Utilization Scheme of Idle Virtual Machines for Multiple Large-Scale Jobs Based on OpenStack
Authors: Jeon Jueun , Park Jong Hyuk , Jeong Young-Sik
Published: October 2019

Cloud computing services that provide computing resources to users through the Internet also provide computing resources in a virtual machine form based on virtualization techniques. In general, supercomputing and grid computing have mainly been used to process large-scale jobs occurring in scientific, technical, and engineering application domains. However, services that process large-scale jobs in parallel using idle virtual machines are not provided in cloud computing at present. Generally, users do not use virtual machines anymore, or they do not use them for a long period of time, because existing cloud computing assigns all of the use rights of virtual machines to users, resulting in the low use of computing resources. This study proposes a scheme to process large-scale jobs in parallel, using idle virtual machines and increasing the resource utilization of idle virtual machines. Idle virtual machines are basically identified through specific determination criteria out of virtual machines created using OpenStack, and then they are used in computing services. This is called the idle virtual machine–resource utilization (IVM–ReU), which is proposed in this study.
False Image Injection Prevention Using iChain
Authors: Ahmed Mohiuddin
Published: October 2019

The advances in information and communication technology are consistently beneficial for the healthcare sector. A trend in the healthcare sector is the progressive shift in how data are acquired and the storage of such data in different facilities, such as in the cloud, due to the efficiency and effectiveness offered. Digital images related to healthcare are sensitive in nature and require maximum security and privacy. A malicious entity can tamper with such stored digital images to mislead healthcare personnel and the consequences of wrong diagnosis are harmful for both parties. A new type of cyber attack, a false image injection attack (FIIA) is introduced in this paper. Existing image tampering detection measures are unable to guarantee tamper-proof medical data in real time. Inspired by the effectiveness of emerging blockchain technology, a security framework, image chain (iChain) is proposed in this paper to ensure the security and privacy of the sensitive healthcare images. The practical challenges associated with the proposed framework and further research that is required are also highlighted.
Vibration Propagation on the Skin of the Arm
Authors: Shah Valay A. , Casadio Maura , Scheidt Robert A. , Mrotek Leigh A.
Published: October 2019

Vibrotactile interfaces are an inexpensive and non-invasive way to provide performance feedback to body-machine interface users. Interfaces for the upper extremity have utilized a multi-channel approach using an array of vibration motors placed on the upper extremity. However, for successful perception of multi-channel vibrotactile feedback on the arm, we need to account for vibration propagation across the skin. If two stimuli are delivered within a small distance, mechanical propagation of vibration can lead to inaccurate perception of the distinct vibrotactile stimuli. This study sought to characterize vibration propagation across the hairy skin of the forearm. We characterized vibration propagation by measuring accelerations at various distances from a source vibration of variable intensities (100–240 Hz). Our results showed that acceleration from the source vibration was present at a distance of 4 cm at intensities >150 Hz. At distances greater than 8 cm from the source, accelerations were reduced to values substantially below vibrotactile discrimination thresholds for all vibration intensities. We conclude that in future applications of vibrotactile interfaces, stimulation sites should be separated by a distance of at least 8 cm to avoid potential interference in vibration perception caused by propagating vibrations.
Tunable Optoelectronic Chromatic Dispersion Compensation Based on Machine Learning for Short-Reach Transmission
Authors: Ranzini Stenio M. , Da Ros Francesco , Bülow Henning , Zibar Darko
Published: October 2019

In this paper, a machine learning-based tunable optical-digital signal processor is demonstrated for a short-reach optical communication system. The effect of fiber chromatic dispersion after square-law detection is mitigated using a hybrid structure, which shares the complexity between the optical and the digital domain. The optical part mitigates the chromatic dispersion by slicing the signal into small sub-bands and delaying them accordingly, before regrouping the signal again. The optimal delay is calculated in each scenario to minimize the bit error rate. The digital part is a nonlinear equalizer based on a neural network. The results are analyzed in terms of signal-to-noise penalty at the KP4 forward error correction threshold. The penalty is calculated with respect to a back-to-back transmission without equalization. Considering 32 GBd transmission and 0 dB penalty, the proposed hybrid solution shows chromatic dispersion mitigation up to 200 ps/nm (12 km of equivalent standard single-mode fiber length) for stage 1 of the hybrid module and roughly double for the second stage. A simplified version of the optical module is demonstrated with an approximated 1.5 dB penalty compared to the complete two-stage hybrid module. Chromatic dispersion tolerance for a fixed optical structure and a simpler configuration of the nonlinear equalizer is also investigated.
Fixed Grid Numerical Models for Solidification and Melting of Phase Change Materials (PCMs)
Authors: Nazzi Ehms José Henrique , De Césaro Oliveski Rejane , Oliveira Rocha Luiz Alberto , Biserni Cesare , Garai Massimo
Published: October 2019

Phase change materials (PCMs) are classified according to their phase change process, temperature, and composition. The utilization of PCMs lies mainly in the field of solar energy and building applications as well as in industrial processes. The main advantage of such materials is the use of latent heat, which allows the storage of a large amount of thermal energy with small temperature variation, improving the energy efficiency of the system. The study of PCMs using computational fluid dynamics (CFD) is widespread and has been documented in several papers, following the tendency that CFD nowadays tends to become increasingly widespread. Numerical studies of solidification and melting processes use a combination of formulations to describe the physical phenomena related to such processes, these being mainly the latent heat and the velocity transition between the liquid and the solid phases. The methods used to describe the latent heat are divided into three main groups: source term methods (E-STM), enthalpy methods (E-EM), and temperature-transforming models (E-TTM). The description of the velocity transition is, in turn, divided into three main groups: switch-off methods (SOM), source term methods (STM), and variable viscosity methods (VVM). Since a full numerical model uses a combination of at least one of the methods for each phenomenon, several combinations are possible. The main objective of the present paper was to review the numerical approaches used to describe solidification and melting processes in fixed grid models. In the first part of the present review, we focus on the PCM classification and applications, as well as analyze the main features of solidification and melting processes in different container shapes and boundary conditions. Regarding numerical models adopted in phase-change processes, the review is focused on the fixed grid methods used to describe both latent heat and velocity transition between the phases. Additionally, we discuss the most common simplifications and boundary conditions used when studying solidification and melting processes, as well as the impact of such simplifications on computational cost. Afterwards, we compare the combinations of formulations used in numerical studies of solidification and melting processes, concluding that “enthalpy–porosity” is the most widespread numerical model used in PCM studies. Moreover, several combinations of formulations are barely explored. Regarding the simulation performance, we also show a new basic method that can be employed to evaluate the computing performance in transient numerical simulations.
Economic Routing of Electric Vehicles using Dynamic Pricing in Consideration of System Voltage
Authors: Lee Hyung-Joo , Cha Hee-Jun , Won Dongjun
Published: October 2019

There is a growing market for electric vehicles (EVs) in recent years. Due to this, many studies on electric vehicles are in progress and research on charging operations for EVs are especially active. Recent research trends on electric vehicle routes rely on the stochastic modelling of various factors such as convenience of a user’s point of view, charging station (CS), location, destination, and so on. In this paper, a charging control scheme for electric vehicles is proposed from the point of view of the system operators rather than the user. From a user’s point of view, the EV route can be set up directly, but it is difficult for the system operator to directly participate in the route of the EV. In this paper, a method is proposed to indirectly change the route of the EV by changing the charging cost through real-time dynamic pricing, in order to prevent risks in the system operation due to voltage fluctuations in the system. With dynamic pricing, the voltage of the system is kept within a stable range, and the EV user sets the route with an economic benefit. The proposed scheme is verified through Dijkstra’s algorithm and a control strategy via a simulation model using MATLAB.
Predicting Heating Load in Energy-Efficient Buildings Through Machine Learning Techniques
Authors: Moayedi Hossein , Bui Dieu Tien , Dounis Anastasios , Lyu Zongjie , Foong Loke Kok
Published: October 2019

The heating load calculation is the first step of the iterative heating, ventilation, and air conditioning (HVAC) design procedure. In this study, we employed six machine learning techniques, namely multi-layer perceptron regressor (MLPr), lazy locally weighted learning (LLWL), alternating model tree (AMT), random forest (RF), ElasticNet (ENet), and radial basis function regression (RBFr) for the problem of designing energy-efficient buildings. After that, these approaches were used to specify a relationship among the parameters of input and output in terms of the energy performance of buildings. The calculated outcomes for datasets from each of the above-mentioned models were analyzed based on various known statistical indexes like root relative squared error (RRSE), root mean squared error (RMSE), mean absolute error (MAE), correlation coefficient (R2), and relative absolute error (RAE). It was found that between the discussed machine learning-based solutions of MLPr, LLWL, AMT, RF, ENet, and RBFr, the RF was nominated as the most appropriate predictive network. The RF network outcomes determined the R2, MAE, RMSE, RAE, and RRSE for the training dataset to be 0.9997, 0.19, 0.2399, 2.078, and 2.3795, respectively. The RF network outcomes determined the R2, MAE, RMSE, RAE, and RRSE for the testing dataset to be 0.9989, 0.3385, 0.4649, 3.6813, and 4.5995, respectively. These results show the superiority of the presented RF model in estimation of early heating load in energy-efficient buildings.
Flexible Shear and Normal Force Sensor Using only One Layer of Polyvinylidene Fluoride Film
Authors: Lee Ye Rim , Chung Jaehoon , Oh Yonghwan , Cha Youngsu
Published: October 2019

We have proposed a flexible sensor that can sense shear and normal forces, and can be fabricated through a simple process using only one layer of polyvinylidene fluoride (PVDF) film. For the measurement of shear and normal forces, one layer of PVDF film was sealed in a three-dimensionally structured polydimethylsiloxane (PDMS). In the structure, the sensor produced voltage signals corresponding to the shear and normal forces. Using this property, we aimed to demonstrate how to sense the magnitude and direction of the force applied to the sensor from its output voltages. Furthermore, the proposed sensor with a 2 × 2 array was able to measure the applied force in real time.
Application of Three Metaheuristic Techniques in Simulation of Concrete Slump
Authors: Moayedi Hossein , Kalantar Bahareh , Foong Loke Kok , Tien Bui Dieu , Motevalli Alireza
Published: October 2019

Slump is a workability-related characteristic of concrete mixture. This paper investigates the efficiency of a novel optimizer, namely ant lion optimization (ALO), for fine-tuning of a neural network (NN) in the field of concrete slump prediction. Two well-known optimization techniques, biogeography-based optimization (BBO) and grasshopper optimization algorithm (GOA), are also considered as benchmark models to be compared with ALO. Considering seven slump effective factors, namely cement, slag, water, fly ash, superplasticizer (SP), fine aggregate (FA), and coarse aggregate (CA), the mentioned algorithms are synthesized with a neural network to determine the best-fitted neural parameters. The most appropriate complexity of each ensemble is also found by a population-based sensitivity analysis. The findings revealed that the proposed ALO-NN model acquires a good approximation of concrete slump, regarding the calculated root mean square error (RMSE = 3.7788) and mean absolute error (MAE = 3.0286). It also outperformed both BBO-NN (RMSE = 4.1859 and MAE = 3.3465) and GOA-NN (RMSE = 4.9553 and MAE = 3.8576) ensembles.
Estimation of Seismically-Induced Crest Settlement of Earth Core Rockfill Dams
Authors: Park Ki-Chun , Nguyen Van-Quang , Kim Jung-Hyun , Park Duhee , Choi Byoung-Han
Published: October 2019

The settlement at the dam crest induced by earthquake loading is an important design parameter widely used to evaluate the seismic performance of dams. Two-dimensional nonlinear dynamic analyses were performed to calculate the dam crest settlement of earth core rockfill dams (ECRDs). The numerical model was first validated against centrifuge test measurements. Comparisons showed that the numerical model provided reasonable estimates of the measured response. A series of dynamic numerical analyses were performed for a wide range of ground motions. The calculated settlements were revealed to compare well with field recordings of dam crest settlements. The settlements were also plotted against ground motion parameters, including free-field surface peak ground acceleration (PGA), peak ground velocity (PGV), Arias intensity (Ia), and moment magnitude (M). Predictive equations for the crest settlement were also presented. It wes demonstrated that PGA provided a good estimate of the settlement, but Ia provided the most favorable fit according to the calculations. Additionally, multiple parameters models were also presented to enhance the accuracy of the predictions.
Real-Time Pre-Identification and Cascaded Detection for Tiny Faces
Authors: Yang Ziyuan , Li Jing , Min Weidong , Wang Qi
Published: October 2019

Although the face detection problem has been studied for decades, searching tiny faces in the whole image is still a challenging task, especially in low-resolution images. Traditional face detection methods are based on hand-crafted features, but the features of tiny faces are different from those of normal-sized faces, and thus the detection robustness cannot be guaranteed. In order to alleviate the problem in existing methods, we propose a pre-identification mechanism and a cascaded detector (PMCD) for tiny-face detection. This pre-identification mechanism can greatly reduce background and other irrelevant information. The cascade detector is designed with two stages of deep convolutional neural network (CNN) to detect tiny faces in a coarse-to-fine manner, i.e., the face-area candidates are pre-identified as region of interest (RoI) based on a real-time pedestrian detector and the pre-identification mechanism, the set of RoI candidates is the input of the second sub-network instead of the whole image. Benefiting from the above mechanism, the second sub-network is designed as a shallow network which can keep high accuracy and real-time performance. The accuracy of PMCD is at least 4% higher than the other state-of-the-art methods on detecting tiny faces, while keeping real-time performance.
Effect of Nanodisks at Different Positions on the Fano Resonance of Graphene Heptamers
Authors: Zhou Hengjie , Qiu Weibin , Wang Zeyu , Ren Junbo , Zhao Zeyang , Lin Zhili , Qiu Pingping , Kan Qiang
Published: October 2019

The formation of Fano resonance based on graphene heptamers with D 6 h symmetry and the effect of nanoparticles at different positions on the collective behavior are investigated in this paper. The significances of central nanodisks on the whole structure are studied first by varying the chemical potential. In addition, the effect of six graphene nanodisks placed in the ring on collective behaviors is also investigated. The influence of the nanodisks at different positions of the ring on the Fano resonance spectrum of the whole oligomer is researched by changing the chemical potential and radius. The proposed nanostructures may find broad applications in the fields of chemical and biochemical sensing.
Density Fluctuations in the Lower Thermosphere of Mars Retrieved From the ExoMars Trace Gas Orbiter (TGO) Aerobraking
Authors: Jesch David , Medvedev Alexander S. , Castellini Francesco , Yiğit Erdal , Hartogh Paul
Published: October 2019

The upper atmosphere of Mars is constantly perturbed by small-scale gravity waves propagating from below. As gravity waves strongly affect the large-scale dynamics and thermal state, constraining their statistical characteristics is of great importance for modeling the atmospheric circulation. We present a new data set of density perturbation amplitudes derived from accelerometer measurements during aerobraking of the European Space Agency’s Trace Gas Orbiter. The obtained data set presents features found by three previous orbiters: the lower thermosphere polar warming in the winter hemisphere, and the lack of links between gravity wave activity and topography. In addition, the orbits allowed for demonstrating a very weak diurnal variability in wave activity at high latitudes of the southern winter hemisphere for the first time. The estimated vertical damping rates of gravity waves agree well with theoretical predictions. No clear anticorrelation between perturbation amplitudes and the background temperature has been found. This indicates differences in dissipation mechanisms of gravity waves in the lower and upper thermosphere.
Sugary Kefir: Microbial Identification and Biotechnological Properties
Authors: Syrokou Maria K. , Papadelli Marina , Ntaikou Ioanna , Paramithiotis Spiros , Drosinos Eleftherios H.
Published: October 2019

Background: The aim of the present study was to assess the microecosystem composition of three different fruit kefir grains used for the fermentation of apple juice (NAJ), cherry juice (SCN), and a solution of sugary water, enriched with plums (BSS). Methods: Yeast and bacterial populations were enumerated using classical microbiological techniques, clustered by RAPD-PCR genotyping, and identified by sequencing of the D1/D2 region of 26S-rRNA gene and the V1-V3 region of 16S-rRNA gene, respectively. The caseinolytic/lipolytic activities and the production of antimicrobial compounds were assessed by well diffusion assays. The proteolytic and lipolytic capacity were further assessed by SDS-PAGE and titrimetric assay, respectively. Results: Yeast and bacterial populations were enumerated at 6.28, 6.58, and 6.41 log CFU/g and at 4.32, 4.85, and 4.34 log CFU/g, regarding BSS, NAJ, and SCN, respectively. Saccharomyces cerevisiae dominated all three sugary kefir grains; Kluyveromyces marxianus formed a secondary microbiota in BSS and NAJ. Bacillus amyloliquefaciens dominated NAJ and SCN; Lactobacillus rhamnosus dominated BSS. Four bacteria and nine yeast isolates exhibited proteolytic activity. Forty bacteria and 45 yeast isolates possessed lipolytic activity. No antibacterial activity was detected. Conclusions: Prevalence of yeast over bacterial populations was evident in all samples assessed. Several bacterial and yeast strains exhibited proteolytic and lipolytic activities, making them suitable candidates for inclusion in starter cultures for milk and sugary kefir fermentation.
The Role of the Embodiment Disturbance in the Anorexia Nervosa Psychopathology: A Network Analysis Study
Authors: Cascino Giammarco , Castellini Giovanni , Stanghellini Giovanni , Ricca Valdo , Cassioli Emanuele , Ruzzi Valeria , Monteleone Palmiero , Monteleone Alessio Maria
Published: October 2019

Anorexia Nervosa (AN) is characterized by body image distortion. From a phenomenological perspective, body image disturbance has been associated with a more profound disturbance encompassing disorders of the way persons experience their own body. The aim of this study was to disentangle the complex dynamics that connect the experience of one’s own body and self-identity to the psychopathological features of AN by applying a network analysis. Fifty-seven patients with AN restrictive subtype and 27 with AN binge–purging subtype participated in the study. Eating Disorders Inventory-2 and Identity and Eating Disorders subscores, measuring the embodiment dimensions, were included in the network. Two of the main dimensions of embodiment—feeling extraneous from one’s own body and feeling oneself through objective measures—were the nodes with the highest strength together with interoceptive awareness (IA). IA was a node included in several pathways connecting embodiment dimensions with most of the AN psychopathological dimensions. The centrality of the embodiment disorder suggests the importance of considering the body image disturbance in people with AN as resulting from their difficulty in experiencing inner states and as a tool to build its own self. This assumption may orient therapeutic interventions.
Fischer–Tropsch Synthesis: Computational Sensitivity Modeling for Series of Cobalt Catalysts
Authors: Williams Harrison , Gnanamani Muthu K. , Jacobs Gary , Shafer Wilson D. , Coulliette David
Published: October 2019

Nearly a century ago, Fischer and Tropsch discovered a means of synthesizing organic compounds ranging from C1 to C70 by reacting carbon monoxide and hydrogen on a catalyst. Fischer–Tropsch synthesis (FTS) is now known as a pseudo-polymerization process taking a mixture of CO as H2 (also known as syngas) to produce a vast array of hydrocarbons, along with various small amounts of oxygenated materials. Despite the decades spent studying this process, it is still considered a black-box reaction with a mechanism that is still under debate. This investigation sought to improve our understanding by taking data from a series of experimental Fischer–Tropsch synthesis runs to build a computational model. The experimental runs were completed in an isothermal continuous stirred-tank reactor, allowing for comparison across a series of completed catalyst tests. Similar catalytic recipes were chosen so that conditional comparisons of pressure, temperature, SV, and CO/H2 could be made. Further, results from the output of the reactor that included the deviations in product selectivity, especially that of methane and CO2, were considered. Cobalt was chosen for these exams for its industrial relevance and respectfully clean process as it does not intrinsically undergo the water–gas shift (WGS). The primary focus of this manuscript was to compare runs using cobalt-based catalysts that varied in two oxide catalyst supports. The results were obtained by creating two differential equations, one for H2 and one for CO, in terms of products or groups of products. These were analyzed using sensitivity analysis (SA) to determine the products or groups that impact the model the most. The results revealed a significant difference in sensitivity between the two catalyst–support combinations. When the model equations for H2 and CO were split, the results indicated that the CO equation was significantly more sensitive to CO2 production than the H2 equation.
Fermentative Conversion of Two-Step Pre-Treated Lignocellulosic Biomass to Hydrogen
Authors: Kucharska Karolina , Cieśliński Hubert , Rybarczyk Piotr , Słupek Edyta , Łukajtis Rafał , Wychodnik Katarzyna , Kamiński Marian
Published: October 2019

Fermentative hydrogen production via dark fermentation with the application of lignocellulosic biomass requires a multistep pre-treatment procedure, due to the complexed structure of the raw material. Hence, the comparison of the hydrogen productivity potential of different lignocellulosic materials (LCMs) in relation to the lignocellulosic biomass composition is often considered as an interesting field of research. In this study, several types of biomass, representing woods, cereals and grass were processed by means of mechanical pre-treatment and alkaline and enzymatic hydrolysis. Hydrolysates were used in fermentative hydrogen production via dark fermentation process with Enterobacter aerogenes (model organism). The differences in the hydrogen productivity regarding different materials hydrolysates were analyzed using chemometric methods with respect to a wide dataset collected throughout this study. Hydrogen formation, as expected, was positively correlated with glucose concentration and total reducing sugars amount (YTRS) in enzymatic hydrolysates of LCMs, and negatively correlated with concentrations of enzymatic inhibitors i.e., HMF, furfural and total phenolic compounds in alkaline-hydrolysates LCMs, respectively. Interestingly, high hydrogen productivity was positively correlated with lignin content in raw LCMs and smaller mass loss of LCM after pre-treatment step. Besides results of chemometric analysis, the presented data analysis seems to confirm that the structure and chemical composition of lignin and hemicellulose present in the lignocellulosic material is more important to design the process of its bioconversion than the proportion between the cellulose, hemicellulose and lignin content in this material. For analyzed LCMs we found remarkable higher potential of hydrogen production via bioconversion process of woods i.e., beech (24.01 mL H2/g biomass), energetic poplar (23.41 mL H2/g biomass) or energetic willow (25.44 mL H2/g biomass) than for cereals i.e., triticale (17.82 mL H2/g biomass) and corn (14.37 mL H2/g biomass) or for meadow grass (7.22 mL H2/g biomass).
Potential Therapeutic Application of Estrogen in Gender Disparity of Nonalcoholic Fatty Liver Disease/Nonalcoholic Steatohepatitis
Authors: Lee Chanbin , Kim Jieun , Jung Youngmi
Published: October 2019

Nonalcoholic fatty liver disease (NAFLD) caused by fat accumulation in the liver is globally the most common cause of chronic liver disease. Simple steatosis can progress to nonalcoholic steatohepatitis (NASH), a more severe form of NAFLD. The most potent driver for NASH is hepatocyte death induced by lipotoxicity, which triggers inflammation and fibrosis, leading to cirrhosis and/or liver cancer. Despite the significant burden of NAFLD, there is no therapy for NAFLD/NASH. Accumulating evidence indicates gender-related NAFLD progression. A higher incidence of NAFLD is found in men and postmenopausal women than premenopausal women, and the experimental results, showing protective actions of estradiol in liver diseases, suggest that estrogen, as the main female hormone, is associated with the progression of NAFLD/NASH. However, the mechanism explaining the functions of estrogen in NAFLD remains unclear because of the lack of reliable animal models for NASH, the imbalance between the sexes in animal experiments, and subsequent insufficient results. Herein, we reviewed the pathogenesis of NAFLD/NASH focused on gender and proposed a feasible association of estradiol with NAFLD/NASH based on the findings reported thus far. This review would help to expand our knowledge of the gender differences in NAFLD and for developing gender-based treatment strategies for NAFLD/NASH.
Prospective Climate Change Impacts upon Energy Prices in the 21ST Century: A Case Study in Italy
Authors: Bombelli Giovanni Martino , Soncini Andrea , Bianchi Alberto , Bocchiola Daniele
Published: October 2019

The assessment of the effect of the electricity price on energy production is important when studying the profitability and benefits of energy systems. The demand and price of electricity depends upon societal and economic development, but it is subject to a seasonal, weather-dependent variability, and possibly to long-term variation under climate change. Here, we developed a methodology to model the energy demand and electricity price in response to gross domestic product (GDP), temperatures, and random factors, usable for the purpose of cost/benefit analysis of production systems. The method was applied to the case study of the Italian electricity market, showing acceptable capacity of modelling recently observed price fluctuations. Then, we gathered climate projections until 2100 from three global climate models of the IPCC AR5, under RCP2.6, RCP4.5, and RCP8.5, and we produced future scenarios of price fluctuations for two reference decades, half-century 2040–2049, and end-of-century 2090–2099. Our scenarios displayed a potential for the reduction of energy demand in winter, and an increase in summer and spring, and for the similarly-changing electricity price throughout the 21st century. We discuss the application of our model with the specific aim of the projection of future hydropower production, as controlled by climate, hydrology, demand, and price constraints, with examples from recent studies. Our results provide a tool for modelling the behaviour of energy systems based upon knowledge of external factors, usable for further investigation of energy systems, such as hydropower, and others, taking into account the key variables affecting energy production and energy price.
LED as Transmitter and Receiver of Light: A Simple Tool to Demonstration Photoelectric Effect
Authors: Schirripa Spagnolo Giuseppe , Leccese Fabio , Leccisi Mariagrazia
Published: October 2019

The experimental observations of the photoelectric effect show the properties of quantum mechanics of the electromagnetic field. For this reason, this important effect is commonly used as an introductory topic for the study of quantum physics. The “classical” demonstration of the photoelectric effect is very incisive; unfortunately, the experimental apparatus is not cheap and easy to realize. The typical use of LEDs is as light emitters, but they can be used even as photosensors and, in this case, they are sensitive to wavelengths equal to or shorter than the predominant wavelength it emits. Furthermore, a LED used as detector is sensitive to wavelengths equal to or shorter than the predominant wavelength it emits. This ability of LEDs offers the possibility of developing a simple tool able to demonstrate the photoelectric effect. This paper describes the realization of an economic, simple, easy and safe system to use for the experimental demonstration of the photoelectric effect, based on the LED to LED structure. The paper has educational purposes, oriented towards laboratory teaching activities.
Conjugate Heat Transfer Investigation on Swirl-Film Cooling at the Leading Edge of a Gas Turbine Vane
Authors: Du Haifen , Mei Ziyue , Zou Jiayao , Jiang Wei , Xie Danmei
Published: October 2019

Numerical calculation of conjugate heat transfer was carried out to study the effect of combined film and swirl cooling at the leading edge of a gas turbine vane with a cooling chamber inside. Two cooling chambers (C1 and C2 cases) were specially designed to generate swirl in the chamber, which could enhance overall cooling effectiveness at the leading edge. A simple cooling chamber (C0 case) was designed as a baseline. The effects of different cooling chambers were studied. Compared with the C0 case, the cooling chamber in the C1 case consists of a front cavity and a back cavity and two cavities are connected by a passage on the pressure side to improve the overall cooling effectiveness of the vane. The area-averaged overall cooling effectiveness of the leading edge ( ϕ ¯ ¯ ) was improved by approximately 57%. Based on the C1 case, the passage along the vane was divided into nine segments in the C2 case to enhance the cooling effectiveness at the leading edge, and ϕ ¯ ¯ was enhanced by 75% compared with that in the C0 case. Additionally, the cooling efficiency on the pressure side was improved significantly by using swirl-cooling chambers. Pressure loss in the C2 and C1 cases was larger than that in the C0 case.
Expert Finding Considering Dynamic Profiles and Trust in Social Networks
Authors: Bok Kyoungsoo , Jeon Inbae , Lim Jongtae , Yoo Jaesoo
Published: October 2019

Recently, social network services that express individual opinions and thoughts have been significantly developed. As unreliable information is generated and shared by arbitrary users in social network services, many studies have been conducted to find users who provide reliable and professional information. In this paper, we propose an expert finding scheme to discover users who can answer users’ questions professionally in social network services. We use a dynamic profile to extract the user’s latest interest through an analysis of the user’s recent activity. To improve the accuracy of the expert finding results, we consider the user trust and response quality. We conduct a performance evaluation with the existing schemes through various experiments to verify the superiority of the proposed scheme.
Droop Control in DQ Coordinates for Fixed Frequency Inverter-Based AC Microgrids
Authors: Toub Mohamed , Bijaieh Mehrzad M. , Weaver Wayne W. , Robinett Rush D. , Maaroufi Mohamed , Aniba Ghassane
Published: October 2019

This paper presents a proof-of-concept for a novel dq droop control technique that applies DC droop control methods to fixed frequency inverter-based AC microgrids using the dq0 transformation. Microgrids are usually composed of distributed generation units (DGUs) that are electronically coupled to each other through power converters. An inherent property of inverter-based microgrids is that, unlike microgrids with spinning machines, the frequency of the parallel-connected DGUs is a global variable independent from the output power since the inverters can control the output waveform frequency with a high level of precision. Therefore, conventional droop control methods that distort the system frequency are not suitable for microgrids operating at a fixed frequency. It is shown that the proposed distributed droop control allows accurate sharing of the active and reactive power without altering the microgrid frequency. The simulation and hardware-in-the-loop (HIL) results are presented to demonstrate the efficacy of the proposed droop control. Indeed, following a load change, the dq droop controller was able to share both active and reactive power between the DGUs, whereas maintaining the microgrid frequency deviation at 0% and the bus voltage deviations below 6% of their respective nominal values.
Impact of Aging on Three-Dimensional Facial Verification
Authors: Heravi Farnaz Majid Zadeh , Farazdaghi Elham , Fournier Régis , Nait-ali Amine
Published: October 2019

Age progression is associated with poor performance of verification systems. Thus, there is a need for further research to overcome this problem. Three-dimensional facial aging modeling for employment in verification systems is highly serviceable, and able to acknowledge how variations in depth and pose can provide additional information to accurately represent faces. In this article, the impact of aging on the performance of three-dimensional facial verification is studied. For this purpose, we employed three-dimensional (3D) faces obtained from a 3D morphable face aging model (3D F-FAM). The proposed 3D F-FAM was able to simulate the facial appearance of a young adult in the future. A performance evaluation was completed based on three metrics: structural texture quality, mesh geometric distortion and morphometric landmark distances. The collection of 500 textured meshes from 145 subjects, which were used to construct our own database called FaceTim V.2.0, was applied in performance evaluation. The experimental results demonstrated that the proposed model produced satisfying results and could be applicable in 3D facial verification systems. Furthermore, the verification rates proved that the 3D faces achieved from the proposed model enhanced the performance of the 3D verification process.
Study on Spontaneous Combustion Tendency of Coals with Different Metamorphic Grade at Low Moisture Content Based on TPO-DSC
Authors: Fan Jiuyuan , Wang Gang , Zhang Jiuling
Published: October 2019

In the environments of various open coal storage sites, mining-affected coalbeds, and goafs, etc., some coal bodies are often affected by external environmental factors. They are highly prone to spontaneous combustion in low moisture content (≤8%). In order to examine the effect of low moisture content on the spontaneous combustion tendency of coals with different metamorphic grade, we conducted a temperature programmed oxidation (TPO) experiment and differential scanning calorimetry (DSC) experiment to study the spontaneous combustion characteristics of coals with different metamorphic grade at four different low moisture contents. The change laws of the characteristic parameters of four different metamorphic grade coals at four different low moisture contents were comparatively analyzed. The experimental results indicate that: (1) Compared other low moisture content, anthracite and fat coal at a low moisture content of 1.2 % show a stronger tendency for spontaneous combustion, and long flame coal and lignite at a low moisture content of 3.4% and 5.6% are more prone to spontaneous combustion. (2) Four different metamorphic grade coals at a low moisture content of 7.8% are less prone to spontaneous combustion.
Research on CBM of the Intelligent Substation SCADA System
Authors: Gu Jyh-Cherng , Liu Chun-Hung , Chou Kai-Ying , Yang Ming-Ta
Published: October 2019

An equipment status management and maintenance platform of an intelligent substation monitoring and control system is built in the Tai-Tam substation of the Taipower company. The real-time operating status of the equipment, such as the server, supervisory control and data acquisition (SCADA) human–machine interface (HMI) software, switches, intelligent electronic devices (IEDs), merging units (MUs), as well as the entire SCADA system, are evaluated comprehensively. First, the status information of all equipment is collected, and the theory of relative deterioration degree (RDD) and fuzzy theory (FT) are applied to calculate the fuzzy evaluation matrix of the equipment influencing factors. Then, the subjective analytic hierarchy process (AHP) and the objective entropy method for weighting are combined to calculate the comprehensive weights of the equipment influencing factors. Finally, the result of the equipment status evaluation is obtained using the fuzzy comprehensive evaluation (FCE) method and is presented at the equipment status management and maintenance platform. Such equipment status evaluation results can be used by the inspection and maintenance personnel to determine the priority for equipment maintenance and repair. The result of this study may serve as a valuable reference to utility companies when making maintenance plans.
Challenges of Fast Charging for Electric Vehicles and the Role of Red Phosphorous as Anode Material: Review
Authors: Zhao Hong , Wang Li , Chen Zonghai , He Xiangming
Published: October 2019

Electric vehicles (EVs) are being endorsed as the uppermost successor to fuel-powered cars, with timetables for banning the sale of petrol-fueled vehicles announced in many countries. However, the range and charging times of EVs are still considerable concerns. Fast charging could be a solution to consumers’ range anxiety and the acceptance of EVs. Nevertheless, it is a complicated and systematized challenge to realize the fast charging of EVs because it includes the coordinated development of battery cells, including electrode materials, EV battery power systems, charging piles, electric grids, etc. This paper aims to serve as an analysis for the development of fast-charging technology, with a discussion of the current situation, constraints and development direction of EV fast-charging technologies from the macroscale and microscale perspectives of fast-charging challenges. If the problem of fast-charging can be solved, it will satisfy consumers’ demand for 10-min charging and accelerate the development of electric vehicles. This paper summarized the development statuses, issues, and trends of the macro battery technology and micro battery technology. It is emphasized that to essentially solve the problem of fast charging, the development of new battery materials, especially anode materials with improved lithium ion diffusion coefficients, is the key. Finally, it is highlighted that red phosphorus is one of the most promising anodes that can simultaneously satisfy the double standards of high-energy density and fast-charging performance to a maximum degree.
A Modified Free Wake Vortex Ring Method for Horizontal-Axis Wind Turbines
Authors: Dong Jing , Viré Axelle , Ferreira Carlos Simao , Li Zhangrui , van Bussel Gerard
Published: October 2019

A modified free-wake vortex ring model is proposed to compute the dynamics of a floating horizontal-axis wind turbine, which is divided into two parts. The near wake model uses a blade bound vortex model and trailed vortex model, which is developed based on vortex filament method with straight lifting lines assumption. By contrast, the far wake model is based on the vortex ring method. The proposed model is a good compromise between accuracy and computational cost, for example when compared with more complex vortex methods. The present model is used to assess the influence of floating platform motions on the performance of a horizontal-axis wind turbine rotor. The results are validated on the 5 MW NREL rotor and compared with other aerodynamic models for the same rotor subjected to different platform motions. The results show that the proposed method is reliable. In addition, the proposed method is less time consuming and has similar accuracy when comparing with more advanced vortex based methods.
Applying Virtual Inertia Control Topology to SMES System for Frequency Stability Improvement of Low-Inertia Microgrids Driven by High Renewables
Authors: Kerdphol Thongchart , Watanabe Masayuki , Mitani Yasunori , Phunpeng Veena
Published: October 2019

To integrate renewable energy into microgrids with a favorable inertia property, a virtual inertia control application is needed. Considering the inertia emulation capabilities, insufficient emulation of inertia power due to the lower and short-term power of storage systems could significantly cause system instability and failure. To enhance such capability, this paper applies a virtual inertia control topology to the superconducting magnetic energy storage (SMES) technology. The SMES-based virtual inertia control system is implemented in a microgrid with renewables to emulate sufficient inertia power and maintain good system frequency stability. The efficacy and control performance of the proposed control method are compared with those of the traditional virtual inertia control system. Simulation results show that the shortage of system inertia due to renewable penetration is properly compensated by the proposed control method, improving system frequency stability and maintaining the robustness of system operations.