bluuebunny/crossref_metadata_2025 huggingface dataset:
The Role of Aberrant DNA Methylation in Misregulation of Gene Expression in Gonadotroph Nonfunctioning Pituitary Tumors
Authors: Kober Paulina , Boresowicz Joanna , Rusetska Natalia , Maksymowicz Maria , Paziewska Agnieszka , Dąbrowska Michalina , Kunicki Jacek , Bonicki Wiesław , Ostrowski Jerzy , Siedlecki Janusz A. , Bujko Mateusz
Published: October 2019

Gonadotroph nonfunctioning pituitary adenomas (NFPAs) are common intracranial tumors, but the role of aberrant epigenetic regulation in their development remains poorly understood. In this study, we investigated the effect of impaired CpG methylation in NFPAs. We determined DNA methylation and transcriptomic profiles in 32 NFPAs and normal pituitary sections using methylation arrays and sequencing, respectively. Ten percent of differentially methylated CpGs were correlated with gene expression, and the affected genes are involved in a variety of tumorigenesis-related pathways. Different proportions of gene body and promoter region localization were observed in CpGs with negative and positive correlations between methylation and gene expression, and different proportions of CpGs were located in ‘open sea’ and ‘shelf/shore’ regions. The expression of ~8% of genes differentially expressed in NFPAs was related to aberrant methylation. Methylation levels of seven CpGs located in the regulatory regions of FAM163A, HIF3A and PRSS8 were determined by pyrosequencing, and gene expression was measured by qRT-PCR and immunohistochemistry in 83 independent NFPAs. The results clearly confirmed the negative correlation between methylation and gene expression for these genes. By identifying which aberrantly methylated CpGs affect gene expression in gonadotrophinomas, our data confirm the role of aberrant methylation in pathogenesis of gonadotroph NFPAs.
Role of Non-Coding RNAs in the Progression of Liver Cancer: Evidence from Experimental Models
Authors: O’Brien April , Zhou Tianhao , Tan Christopher , Alpini Gianfranco , Glaser Shannon
Published: October 2019

Liver cancer is a devastating cancer that ranges from relatively rare (around 2% of all cancers in the United States) to commonplace (up to 50% of cancers in underdeveloped countries). Depending upon the stage of pathogenesis, prognosis, or functional liver tissue present, transplantation or partial hepatectomy may be the only available treatment option. However, due to the rise in metabolic syndrome and the increasing demand for livers, patients often wait months or years for available organs. Due to this shortage, doctors must have other treatment options available. One promising area of cancer research lies in understanding the role of regulatory non-coding RNAs (ncRNAs) as oncogenic drivers and potential targets for prospective therapies. While the role of these ncRNAs was not initially clear, many of them have since been recognized to function as important players in the regulation of gene expression, epigenetic modification, and signal transduction in both normal and cancer cell cycles. Dysregulation of these different ncRNA subtypes has been implicated in the pathogenesis and progression of many major cancers including hepatocellular carcinoma. This review summarizes current findings on the roles noncoding RNAs play in the progression of liver cancer and the various animal models used in current research to elucidate those data.
Oxygen Tension Regulates Lysosomal Activation and Receptor Tyrosine Kinase Degradation
Authors: Hong Jaewoo , Wuest Todd R. , Min Yongfen , Lin P. Charles
Published: October 2019

Oxygen sensing is crucial for adaptation to variable habitats and physiological conditions. Low oxygen tension, or hypoxia, is a common feature of solid tumors, and hypoxic tumors are often more aggressive and resistant to therapy. Here we show that, in cultured mammalian cells, hypoxia suppressed lysosomal acidification/activation and receptor tyrosine kinase (RTK) degradation. Hypoxia down-regulated mTORc1, reducing its ability to activate transcription factor EB (TFEB), a master regulator of V-ATPase, the lysosomal proton pump. Hypoxia prevented epidermal growth factor receptor (EGFR) degradation in tumor tissues, whereas activation of lysosomes enhanced tumor cell response to anti-EGFR treatment. Our results link oxygen tension and lysosomal activity, provide a molecular explanation of the malignant phenotype associated with hypoxic tumors, and suggest activation of lysosomes may provide therapeutic benefit in RTK-targeted cancer therapy.
Decreasing COD in Sugarcane Vinasse Using the Fenton Reaction: The Effect of Processing Parameters
Authors: Hakika Dhias Cahya , Sarto Sarto , Mindaryani Aswati , Hidayat Muslikhin
Published: October 2019

An experiment on Fenton degradation of sugarcane vinasse was carried out to determine its effect on the wastewater characteristics. Vinasse, a by-product of distillation in the bioethanol industry, contains high organic matter, as the value of chemical oxygen demand (COD) is >100,000 mg/L and BOD5 is 31,250 mg/L. The Fenton reaction is one of the advanced oxidation process (AOP) methods which has been widely applied for the treatment of wastewater containing organic pollutants and contaminants. This method utilizes hydroxyl radical (•OH) produced from the catalyzing reaction between Fe2+ or Fe3+ and hydrogen peroxide. The effect of pH, the ratio of [H2O2] and [COD], and the ratio of [H2O2] to [Fe3+] were studied in this research to evaluate the Fenton reaction. Results from this experiment showed that treatment of vinasse using the Fenton reaction decreased the COD value to 48.10%, and its biodegradability enhanced almost two times at a pH value of 3.8, a ratio of [H2O2] to [COD] of 0.62, and a ratio of [H2O2] to [Fe3+] of 50 (g/g), which demonstrated that the Fenton treatment was effective to reduce organic matter of sugarcane vinasse. Three kinetic models (first order, second order, and Behnajad–Modirshahla–Ghanbery (BMG) kinetic model) were used to evaluate the degradation of the COD value. On the basis of the value of R2 (coefficient of determination), we suggested that BMG represented the best kinetic model. This study finds that the Fenton treatment is able to mitigate the environmental impacts of sugarcane vinasse.
Ion Exchange of One-Pot Synthesized Cu-SAPO-44 with NH4NO3 to Promote Cu Dispersion and Activity for Selective Catalytic Reduction of NOx with NH3
Authors: Zhang Nana , Xin Ying , Li Qian , Ma Xicheng , Qi Yongxin , Zheng Lirong , Zhang Zhaoliang
Published: October 2019

Cu-containing CHA type (Cu-CHA) zeolites have been widely investigated owing to their excellent low-temperature activity and high hydrothermal stability in selective catalytic reduction of NOx with NH3 (NH3-SCR). Herein, a series of Cu-SAPO-44 zeolites were prepared by one-pot method with dual-amine templates and the subsequent ion exchange (IE) with NH4NO3. The effect of NH4NO3 treatment on Cu species was investigated by X-ray powder diffraction (XRD), N2 adsorption-desorption isotherm, inductively coupled plasma (ICP); field-emission scanning electron microscope (FE-SEM), high-resolution transmission electron microscope (HRTEM), X-ray absorption fine structure (XAFS), and H2-temperature-programmed reduction (H2-TPR). The results indicated that—besides the main SAPO-44 structure—the CuO phase was detected by XRD in original samples. After IE with NH4NO3, the Cu contents decreased greatly from ICP analysis. The removal of CuO agglomerations and the presence of highly dispersed CuO nanoparticles (~2.36 nm) were confirmed by SEM, TEM and H2-TPR. Furthermore, a significant increase in the proportion of isolated Cu2+ was derived from XAFS. As a result, the activity at higher temperature (≥350 °C) was improved a lot.
Effect of Surface Composition and Structure of the Mesoporous Ni/KIT-6 Catalyst on Catalytic Hydrodeoxygenation Performance
Authors: Zhang Xianming , Chen Shuang , Wang Fengjiao , Deng Lidan , Ren Jianmin , Jiao Zhaojie , Zhou Guilin
Published: October 2019

A series of Ni/KIT6 catalyst precursors with 25 wt.% Ni loading amount were reduced in H2 at 400, 450, 500, and 550 °C, respectively. The studied catalysts were investigated by XRD, Quasi in-situ XPS, BET, TEM, and H2-TPD/Ranalysis methods. It was found that reduction temperature is an important factor affecting the hydrodeoxygenation (HDO) performance of the studied catalysts because of the Strong Metal Support Interaction Effect (SMSI). The reduction temperature influences mainly the content of active components, crystal size, and the abilityfor adsorbing and activating H2. The developed pore structure and large specific surface area of the KIT-6 support favored the Ni dispersion. The RT450 catalyst, which was prepared in H2 atmosphere at 450 °C, has the best HDO performance. Ethyl acetate can be completely transformed and maintain 96.8% ethane selectivity and 3.2% methane selectivity at 300 °C. The calculated apparent activation energies of the prepared catalysts increased in the following order: RT550 > RT400 > RT500 > RT450.
Vpr and Its Cellular Interaction Partners: R We There Yet?
Authors: Fabryova Helena , Strebel Klaus
Published: October 2019

Vpr is a lentiviral accessory protein that is expressed late during the infection cycle and is packaged in significant quantities into virus particles through a specific interaction with the P6 domain of the viral Gag precursor. Characterization of the physiologically relevant function(s) of Vpr has been hampered by the fact that in many cell lines, deletion of Vpr does not significantly affect viral fitness. However, Vpr is critical for virus replication in primary macrophages and for viral pathogenesis in vivo. It is generally accepted that Vpr does not have a specific enzymatic activity but functions as a molecular adapter to modulate viral or cellular processes for the benefit of the virus. Indeed, many Vpr interacting factors have been described by now, and the goal of this review is to summarize our current knowledge of cellular proteins targeted by Vpr.
Caffeine and Clinical Outcomes in Premature Neonates
Authors: Kumar Vasantha H.S. , Lipshultz Steven E.
Published: October 2019

Caffeine is the most widely used drug by both adults and children worldwide due to its ability to promote alertness and elevate moods. It is effective in the management of apnea of prematurity in premature infants. Caffeine for apnea of prematurity reduces the incidence of bronchopulmonary dysplasia in very-low-birth-weight infants and improves survival without neurodevelopmental disability at 18–21 months. Follow-up studies of the infants in the Caffeine for Apnea of Prematurity trial highlight the long-term safety of caffeine in these infants, especially relating to motor, behavioral, and intelligence skills. However, in animal models, exposure to caffeine during pregnancy and lactation adversely affects neuronal development and adult behavior of their offspring. Prenatal caffeine predisposes to intrauterine growth restriction and small growth for gestational age at birth. However, in-utero exposure to caffeine is also associated with excess growth, obesity, and cardio-metabolic changes in children. Caffeine therapy is a significant advance in newborn care, conferring immediate benefits in preterm neonates. Studies should help define the appropriate therapeutic window for caffeine treatment along with with the mechanisms relating to its beneficial effects on the brain and the lung. The long-term consequences of caffeine in adults born preterm are being studied and may depend on the ability of caffeine to modulate both the expression and the maturation of adenosine receptors in infants treated with caffeine.
Computational Study of Lithium Intercalation in Silicene Channels on a Carbon Substrate after Nuclear Transmutation Doping
Authors: Galashev Alexander , Ivanichkina Ksenia , Katin Konstantin , Maslov Mikhail
Published: October 2019

Silicene is considered to be the most promising anode material for lithium-ion batteries. In this work, we show that transmutation doping makes silicene substantially more suitable for use as an anode material. Pristine and modified bilayer silicene was simulated on a graphite substrate using the classical molecular dynamics method. The parameters of Morse potentials for alloying elements were determined using quantum mechanical calculations. The main advantage of modified silicene is its low deformability during lithium intercalation and its possibility of obtaining a significantly higher battery charge capacity. Horizontal and vertical profiles of the density of lithium as well as distributions of the most significant stresses in the walls of the channels were calculated both in undoped and doped systems with different gaps in silicene channels. The energies of lithium adsorption on silicene, including phosphorus-doped silicene, were determined. High values of the self-diffusion coefficient of lithium atoms in the silicene channels were obtained, which ensured a high cycling rate. The calculations showed that such doping increased the normal stress on the walls of the channel filled with lithium to 67% but did not provoke a loss of mechanical strength. In addition, doping achieved a greater battery capacity and higher charging/discharging rates.
Zooplankton Abundance and Diversity in the Tropical and Subtropical Ocean
Authors: Fernández de Puelles Mᵃ Luz , Gazá Magdalena , Cabanellas-Reboredo Miguel , Santandreu Mᵃ del Mar , Irigoien Xabier , González-Gordillo Juan Ignacio , Duarte Carlos M. , Hernández-León Santiago
Published: October 2019

The abundance and composition of zooplankton down to 3000 m depth was studied in the subtropical and tropical latitudes across the Atlantic, Pacific and Indian Oceans (35 °N–40 °S). Samples were collected from December 2010 to June 2011 during the Malaspina Circumnavigation Expedition. Usually, low abundances were observed with the highest values found in the North Pacific Ocean, Benguela, and off Mauritania, and the lowest in the South Pacific Ocean. No significant differences in abundance and zooplankton composition were found among oceans, with depth being consistently the most important factor affecting their distribution. Each depth strata were inhabited by distinct copepod assemblages, which significantly differed among the strata. The contribution of copepods to the zooplankton community increased with the depth although, as expected, their abundance strongly decreased. Among the copepods, 265 species were identified but 85% were rare and contributed less than 1% in abundance. Clausocalanus furcatus and Nannocalanus minor dominated the epipelagic strata. Pleuromamma abdominalis and Lucicutia clausi were of importance in the mesopelagic layer, and Pareucalanus, Triconia, Conaea and Metridia brevicauda in the bathypelagic layer. Our results provide a global-scale assessment of copepod biodiversity and distribution, providing a contemporary benchmark to follow future ocean changes at low latitudes.
Fusing Feature Distribution Entropy with R-MAC Features in Image Retrieval
Authors: Liu Pingping , Gou Guixia , Guo Huili , Zhang Danyang , Zhao Hongwei , Zhou Qiuzhan
Published: October 2019

Image retrieval based on a convolutional neural network (CNN) has attracted great attention among researchers because of the high performance. The pooling method has become a research hotpot in the task of image retrieval in recent years. In this paper, we propose the feature distribution entropy (FDE) to measure the difference of regional distribution information in the feature maps from CNNs. We propose a novel pooling method, which fuses our proposed FDE with region maximum activations of convolutions (R-MAC) features to improve the performance of image retrieval, as it takes the advantage of regional distribution information in the feature maps. Compared with the descriptors computed by R-MAC pooling, our proposed method considers not only the most significant feature values of each region in feature map, but also the distribution difference in different regions. We utilize the histogram of feature values to calculate regional distribution entropy and concatenate the regional distribution entropy into FDE, which is further normalized and fused with R-MAC feature vectors by weighted summation to generate the final feature descriptors. We have conducted experiments on public datasets and the results demonstrate that our proposed method could produce better retrieval performances than existing state-of-the-art algorithms. Further, higher performance could be achieved by performing these post-processing on the improved feature descriptors.
A Pseudo-Random Beamforming Technique for Improving Physical-Layer Security of MIMO Cellular Networks
Authors: Son Woong , Jang Han Seung , Jung Bang Chul
Published: October 2019

In this paper, we propose a pseudo-random beamforming (PRBF) technique for improving physical-layer security (PLS) in multiple input multiple output (MIMO) downlink cellular networks consisting of a legitimate base station (BS), multiple legitimate mobile stations (MSs) and potential eavesdroppers. The legitimate BS can obtain available potential eavesdroppers’ channel state information (CSI), which is registered in an adjacent cell. In the proposed PRBF technique, the legitimate BS pseudo-randomly generates multiple candidates of the transmit beamforming (BF) matrix, in which each transmit BF matrix consists of multiple orthonormal BF vectors and shares BF information with legitimate MSs before data transmission. Each legitimate MS generates receive BF vectors to maximize the receive signal-to-interference-plus-noise (SINR) for all pseudo-randomly generated transmit beams and calculates the corresponding SINR. Then, each legitimate MS sends a single beam index and the corresponding SINR value of the BF vector that maximizes the received SINR for each BF matrix since a single spatial stream is sent to each legitimate MS. Based on the feedback information from legitimate MSs and the CSI from the legitimate BS to eavesdroppers, the legitimate BS selects the optimal transmit BF matrix and the legitimate MSs that maximizes secrecy sum-rate. We also propose a codebook-based opportunistic feedback (CO-FB) strategy to reduce feedback overhead at legitimate MSs. Based on extensive computer simulations, the proposed PRBF with the proposed CO-FB significantly outperforms the conventional random beamforming (RBF) with the conventional opportunistic feedback (O-FB) strategies in terms of secrecy sum-rate and required feedback bits.
To Be or Not to Be: Social Justice in Networked Learning
Authors: Öztok Murat
Published: October 2019

The potential for more egalitarian or democratic forms of engagements among people is accepted to be somehow actualised naturally within collaborative or cooperative forms of learning. There is an urgent need for a theoretical framework that does not limit social justice with access or participation, but focuses on the otherwise hidden ways in which group work can yield suboptimal outcomes. This article aims to expand the current understandings of social justice in networked learning practices by challenging the ways in which online subjectivities are conceptualised in communal settings. It is argued that the mediated experience in online spaces should be conceptualised in tandem with one’s social presence and social absence if education is to be studied more rigorously and if claims of justice are to be made in networked learning.
FrogVLE Application in Science Teaching in Secondary Schools in North Malaysia: Teachers’ Perspective
Authors: Ramli Nofaizah , Saleh Salmiza
Published: October 2019

The frogVLE application was launched in Malaysia to provide a virtual learning environment in order to produce competitive and relevant students in the 21st century. As science is one of the most important subjects for the development of a nation, the perspective of teachers as policy implementers should be taken into account in ensuring that the desire is achieved. Hence, this study aimed to investigate the level of application of frogVLE in secondary school science teaching in the northern peninsular of Malaysia. This qualitative study involved 50 secondary school science teachers in Perak, Kedah, Penang and Perlis. Each respondent was required to answer a questionnaire which consists of 20 questions. Five teachers were randomly interviewed by the researcher. The data were analyzed descriptively. The analysis results provide a real picture of how the frogVLE application is used in teaching, as well as the issues, challenges and suggestions for improvements in frogVLE while teaching secondary school science subjects. The findings from this study are expected to help the Ministry of Education to develop programs and improve the use of the frogVLE application in teaching science in secondary schools. In conclusion, a virtual learning environment such as the frogVLE application can only be used optimally to help improve science teaching excellence if the relevant issues are solved and supportis received from all parties.
Motivations Influencing the Surgeon’s Healthcare Unit Choice to Perform Surgery: A Confirmatory Study in Portugal
Authors: Nora Diana , Vidal Diogo Guedes , Viterbo Lilian Monteiro Ferrari , Dinis Maria Alzira Pimenta , Sousa Hélder Fernando Pedrosa
Published: October 2019

Quality surgical practice is a fundamental subject in health institutions, and it is important to understand the structural and organizational conditions of the operating room (OR). The present exploratory study sought to understand the motivations that underlie the choice of surgeons for the best healthcare unit to perform surgery, as well as the characteristics of those professionals regarding age, years of work experience, and sex. A questionnaire survey was administered to a convenience sample of 99 surgeons, 67.3% male and 32.7% female, aged 37 to 66 (M = 23.7; Std = 8.92). The results show that at the top of the surgeons’ motivations to perform surgery is the 77.8% attributed to the human resources and equipment available and at the other extreme the 3% to the previous online visit to facilities. This study opens important clues to the development of more in-depth and comparative approaches, necessary for the continuous improvement of the healthcare provided in the context of surgical practice.
Deployment of a Software to Simulate Control Systems in the State-Space
Authors: Flores María , Payá Luis , Valiente David , Gallego Julio , Reinoso Oscar
Published: October 2019

In this work, we present a simulation software that permits designing and testing several types of controllers based on both classical and modern control theory. It has been created using Easy JavaScript Simulations, since this software permits implementing interactive simulations of physical systems in a quick and intuitive way. This laboratory contains a SISO (Single-Input and Single-Output) and a MIMO (Multiple-Input and Multiple-Output) plant, which are hydraulic and nonlinear, thus the linear model (linearized equations) and the original model (nonlinerized equations) have been implemented. The user can choose any of these physical systems and they have the options to control them using either continuous-time or discrete-time controllers. All parameters of the plant are fully configurable by the user. After that, the controller can be designed and tested. This simulation software offers several configurations: (a) PID (Proportional, Integral and Derivative controller); (b) state feedback; (c) observer and state feedback; and (d) integral controller, observer and state feedback control. The evolution of the controlled system is visualized using an animation of the virtual plant and a graphical representation of the evolution of the most important variables. In this paper, the steps for the implementation of this simulation software are detailed.
Model Update Strategies about Object Tracking: A State of the Art Review
Authors: Wang Deyu , Fang Weidong , Chen Wei , Sun Tongfeng , Chen and Tingjie
Published: October 2019

Object tracking has always been an interesting and essential research topic in the domain of computer vision, of which the model update mechanism is an essential work, therefore the robustness of it has become a crucial factor influencing the quality of tracking of a sequence. This review analyses on recent tracking model update strategies, where target model update occasion is first discussed, then we give a detailed discussion on update strategies of the target model based on the mainstream tracking frameworks, and the background update frameworks are discussed afterwards. The experimental performances of the trackers in recent researches acting on specific sequences are listed in this review, where the superiority and some failure cases on each of them are discussed, and conclusions based on those performances are then drawn. It is a crucial point that design of a proper background model as well as its update strategy ought to be put into consideration. A cascade update of the template corresponding to each deep network layer based on the contributions of them to the target recognition can also help with more accurate target location, where target saliency information can be utilized as a tool for state estimation.
A Novel Ensemble of Hybrid Intrusion Detection System for Detecting Internet of Things Attacks
Authors: Khraisat Ansam , Gondal Iqbal , Vamplew Peter , Kamruzzaman Joarder , Alazab Ammar
Published: October 2019

The Internet of Things (IoT) has been rapidly evolving towards making a greater impact on everyday life to large industrial systems. Unfortunately, this has attracted the attention of cybercriminals who made IoT a target of malicious activities, opening the door to a possible attack to the end nodes. Due to the large number and diverse types of IoT devices, it is a challenging task to protect the IoT infrastructure using a traditional intrusion detection system. To protect IoT devices, a novel ensemble Hybrid Intrusion Detection System (HIDS) is proposed by combining a C5 classifier and One Class Support Vector Machine classifier. HIDS combines the advantages of Signature Intrusion Detection System (SIDS) and Anomaly-based Intrusion Detection System (AIDS). The aim of this framework is to detect both the well-known intrusions and zero-day attacks with high detection accuracy and low false-alarm rates. The proposed HIDS is evaluated using the Bot-IoT dataset, which includes legitimate IoT network traffic and several types of attacks. Experiments show that the proposed hybrid IDS provide higher detection rate and lower false positive rate compared to the SIDS and AIDS techniques.
A Long-Term Cost-Oriented Cloudlet Planning Method in Wireless Metropolitan Area Networks
Authors: Guan Xinjie , Wan Xili , Wang Tianjing , Li Yifeng
Published: October 2019

As an extension of remote cloud data centers, cloudlets process the workloads from mobile users at the network edge, thereby satisfying the requirements of resource-intensive and latency-sensitive applications. One of the fundamental yet important issues for cloudlet infrastructure providers (ISP) is how to plan the placement and capacities of cloudlets so that minimize their long-term cost with a guarantee on service delay. However, existing work mostly focuses on resource provision or resource management for mobile services on existing cloudlets, while very little attention has been paid to the cloudlet placement and capacity planning problem. In contrast to those studies, we aim to optimize the long-term total cost of cloudlets’ ISPs through intelligently planning the location and capacities of cloudlets under constraints on the service delay experienced by mobile users. This problem is then decomposed into two sub-problems and algorithms are devised to solve it. Evaluations on randomly generated traces and real traces exhibit the superior performance of the proposed solution on saving ISP’s long-term cost.
Vehicular Systems Technologies: Challenges and Trends Across Transportation Means
Authors: Santa Jose , Sanchez-Iborra Ramon
Published: October 2019

The Intelligent Transportation Systems (ITS) paradigm embraces a plethora of innovations for different transportation means; hence, several multidisciplinary fields are involved in the extensive research related to this topic [...]
Technologies, Design, and Applications of Low-Noise Amplifiers at Millimetre-Wave: State-of-the-Art and Perspectives
Authors: Longhi Patrick Ettore , Pace Lorenzo , Colangeli Sergio , Ciccognani Walter , Limiti Ernesto
Published: October 2019

An overview of applicable technologies and design solutions for monolithic microwave integrated circuit (MMIC) low-noise amplifiers (LNAs) operating at millimeter-wave are provided in this paper. The review starts with a brief description of the targeted applications and corresponding systems. Advanced technologies are presented highlighting potentials and drawbacks related to the considered possibilities. Design techniques, applicable to different requirements, are presented and analyzed. An LNA operating at V-band (59–66 GHz) is designed and tested following the presented guidelines, demonstrating state-of-the-art results in terms of noise figure (average NF < 2 dB). A state-of-the-art table, reporting recent results available in open literature on this topic, is provided and examined, focusing on room temperature operation and performance in cryogenic environment. Finally, trends versus frequency and perspectives are outlined.
Comparison of the Emissions, Noise, and Fuel Consumption Comparison of Direct and Indirect Piezoelectric and Solenoid Injectors in a Low-Compression-Ratio Diesel Engine
Authors: d’Ambrosio Stefano , Ferrari Alessandro , Mancarella Alessandro , Mancò Salvatore , Mittica Antonio
Published: October 2019

An experimental investigation has been carried out to compare the performance and emissions of a low-compression-ratio Euro 5 diesel engine featuring high EGR rates, equipped with different injector technologies, i.e., solenoid, indirect-acting, and direct-acting piezoelectric. The comparisons, performed with reference to a state-of-the-art double fuel injection calibration, i.e., pilot-Main (pM), are presented in terms of engine-out exhaust emissions, combustion noise (CN), and fuel consumption, at low–medium engine speeds and loads. The differences in engine performance and emissions of the solenoidal, indirect-acting, and direct-acting piezoelectric injector setups have been found on the basis of experimental results to mainly depend on the specific features of their hydraulic circuits rather than on the considered injector driving system.
AD/RANS Simulations of Wind Turbine Wake Flow Employing the RSM Turbulence Model: Impact of Isotropic and Anisotropic Inflow Conditions
Authors: Tian Linlin , Song Yilei , Zhao Ning , Shen Wenzhong , Wang Tongguang
Published: October 2019

The Reynolds-averaged Navier–Stokes (RANS)-based generalized actuator disc method along with the Reynolds stress model (AD/RANS_RSM) is assessed for wind turbine wake simulation. The evaluation is based on validations with four sets of experiments for four horizontal-axis wind turbines with different geometrical characteristics operating in a wide range of wind conditions. Additionally, sensitivity studies on inflow profiles (representing isotropic and anisotropic turbulence) for predicting wake effects are carried out. The focus is on the prediction of the evolution of wake flow in terms of wind velocity and turbulence intensity. Comparisons between the computational results and the measurements demonstrate that in the near and transition wake region with strong anisotropic turbulence, the AD/RANS_RSM methodology exhibits a reasonably good match with all the experimental data sets; however, in the far wake region that is characterized by isotropic turbulence, the AD/RANS_RSM predicts the wake velocity quite accurately but appears to over-estimate the wake turbulence level. While the introduction of the overall turbulence intensity is found to give an improved agreement with the experiments. The performed sensitivity study proves that the anisotropic inflow condition is recommended as the profile of choice to represent the incoming wind flow.
Reactive Power Management Considering Stochastic Optimization under the Portuguese Reactive Power Policy Applied to DER in Distribution Networks
Authors: Abreu Tiago , Soares Tiago , Carvalho Leonel , Morais Hugo , Simão Tiago , Louro Miguel
Published: October 2019

Challenges in the coordination between the transmission system operator (TSO) and the distribution system operator (DSO) have risen continuously with the integration of distributed energy resources (DER). These technologies have the possibility to provide reactive power support for system operators. Considering the Portuguese reactive power policy as an example of the regulatory framework, this paper proposes a methodology for proactive reactive power management of the DSO using the renewable energy sources (RES) considering forecast uncertainty available in the distribution system. The proposed method applies a stochastic sequential alternative current (AC)-optimal power flow (SOPF) that returns trustworthy solutions for the DSO and optimizes the use of reactive power between the DSO and DER. The method is validated using a 37-bus distribution network considering real data. Results proved that the method improves the reactive power management by taking advantage of the full capabilities of the DER and by reducing the injection of reactive power by the TSO in the distribution network and, therefore, reducing losses.
Comparative Study on Parameter Identification Methods for Dual-Polarization Lithium-Ion Equivalent Circuit Model
Authors: Kalogiannis Theodoros , Hosen Md , Sokkeh Mohsen , Goutam Shovon , Jaguemont Joris , Jin Lu , Qiao Geng , Berecibar Maitane , Van Mierlo Joeri
Published: October 2019

A lithium-ion battery cell’s electrochemical performance can be obtained through a series of standardized experiments, and the optimal operation and monitoring is performed when a model of the Li-ions is generated and adopted. With discrete-time parameter identification processes, the electrical circuit models (ECM) of the cells are derived. Over their wide range, the dual-polarization (DP) ECM is proposed to characterize two prismatic cells with different anode electrodes. In most of the studies on battery modeling, attention is paid to the accuracy comparison of the various ECMs, usually for a certain Li-ion, whereas the parameter identification methods of the ECMs are rarely compared. Hence in this work, three different approaches are performed for a certain temperature throughout the whole SoC range of the cells for two different load profiles, suitable for light- and heavy-duty electromotive applications. Analytical equations, least-square-based methods, and heuristic algorithms used for model parameterization are compared in terms of voltage accuracy, robustness, and computational time. The influence of the ECMs’ parameter variation on the voltage root mean square error (RMSE) is assessed as well with impedance spectroscopy in terms of Ohmic, internal, and total resistance comparisons. Li-ion cells are thoroughly electrically characterized and the following conclusions are drawn: (1) All methods are suitable for the modeling, giving a good agreement with the experimental data with less than 3% max voltage relative error and 30 mV RMSE in most cases. (2) Particle swarm optimization (PSO) method is the best trade-off in terms of computational time, accuracy, and robustness. (3) Genetic algorithm (GA) lack of computational time compared to PSO and LS (4) The internal resistance behavior, investigated for the PSO, showed a positive correlation to the voltage error, depending on the chemistry and loading profile.
Study on the Optimum Design of a Ground Heat Pump System Using Optimization Algorithms
Authors: Moon Hyeongjin , Kim Hongkyo , Nam Yujin
Published: October 2019

Geothermal energy has attracted attention as a high-efficiency energy source that can be used year-round, but it has a relatively higher initial investment cost. For the design of ground source heat pump (GSHP) systems, a calculation method to determine the capacity of a system to meet the peak load of the target building is usually used. However, this method requires excessive system capacity design, especially regarding buildings with partial load operations. In this study, the optimization of a system design was performed in the view of the cost of the lifecycle cost. Several optimization algorithms were considered, such as the discrete Armijo gradient algorithm, a particle swarm optimization (PSO) algorithm, and a coordinate search method algorithm. The results of the optimization described the system capacity (heat pump, ground heat exchanger, thermal storage tank, etc.) and the cost performance, showing that the total investment cost was reduced compared to the existing design.
A Double-Bed Adsorptive Heat Transformer for Upgrading Ambient Heat: Design and First Tests
Authors: Tokarev Mikhail
Published: October 2019

A full scale lab prototype of an adsorptive heat transformer (AHT), consisting of two adsorbers, an evaporator, and a condenser, was designed and tested in subsequent cycles of heat upgrading. The composite LiCl/SiO2 was used as an adsorbent with methanol as an adsorbtive substance under boundary temperatures of TL/TM/TH = −30/20/30 °C. Preliminary experiments demonstrated the feasibility of the tested AHT in continuous heat generation, with specific power output of 520 W/kg over 1–1.5 h steady-state cycling. The formal and experimental thermal efficiency of the tested rig were found to be 0.5 and 0.44, respectively. Although the low potential heat to be upgraded was available for free from a natural source, the electric efficiency of the prototype was found to be as high as 4.4, which demonstrates the promising potential of the “heat from cold” concept. Recommendations for further improvements are also outlined and discussed in this paper.
A Modified DSC-Based Grid Synchronization Method for a High Renewable Penetrated Power System Under Distorted Voltage Conditions
Authors: Li Tie , Li Yunlu , Yang Junyou , Ge Weichun , Hu Bo
Published: October 2019

With the increasing penetration of renewable energy, a weak grid with declining inertia and distorted voltage conditions becomes a significant problem for wind and solar energy integration. Grid frequency is prone to deviate from its nominal value. Grid voltages become more easily polluted by unbalanced and harmonic components. Grid synchronization technique, as a significant method used in wind and solar energy grid-connected converters, can easily become ineffective. As probably the most widespread grid synchronization technique, phase-locked loop (PLL) is required to detect the grid frequency and phase rapidly and precisely even under such undesired conditions. While the amount of filtering techniques can remove disturbances, they also deteriorate the dynamic performance of PLL, which may not meet the standard requirements of grid codes. The objective of this paper is to propose an effective PLL to tackle this challenge. The proposed PLL is based on quasi-type-1 PLL (QT1-PLL), which provides a good filtering capability by using a moving average filter (MAF). To accelerate the transient behavior when disturbance occurs, a modified delay signal cancellation (DSC) operator is proposed and incorporated into the filtering stage of QT1-PLL. By using modified DSCs and MAFs in a cascaded way, the settling time of the proposed method is reduced to around one cycle of grid fundamental frequency without degrading any disturbance rejection capability. To verify the performance, several test cases, which usually happen in high renewable penetrated power systems, are carried out to demonstrate the effectiveness of the proposed PLL.
Numerical Simulation and Validation of Thermoeletric Generator Based Self-Cooling System with Airflow
Authors: Lin Cheng-Xian , Kiflemariam Robel
Published: October 2019

In this paper, a general numerical methodology is developed and validated for the simulation of steady as well as transient thermal and electrical behaviors of thermoelectric generator (TEG)-based air flow self-cooling systems. The present model provides a comprehensive framework to advance the study of self-cooling applications by combining fluid flow, heat transfer and electric circuit simulations. The methodology is implemented by equation-based coupled modeling capabilities from multidisciplinary fields to capture the dynamic thermos-electric interaction in TEG elements, enabling the simulation of overall heating/cooling/power characteristics as well as spatially distributed thermal and flow fields in the entire device. Experiments have been conducted on two types of self-cooling arrangements to measure the device temperature, voltage and power produced by TEG modules. It was found that the computational model was able to predict the experimental results within 5% error. A parametric study was carried out using the validated model to study the effect of heat sink geometry and TEG arrangements on device temperature and power produced by the device. It was found that the power for self-cooling could be maximized by proper matching of the TEG modules to the fluid mover. Although an increase in fin density results in a rise in fan power consumption, a marked increase in net power and decreases in thermal resistance are observed.
Modeling and Simulation of Temperature and Relative Humidity Inside a Growth Chamber
Authors: Díaz-Flórez Germán , Mendiola-Santibañez Jorge , Solís-Sánchez Luis , Gómez-Meléndez Domingo , Terol-Villalobos Ivan , Gutiérrez-Bañuelos Hector , Araiza-Esquivel Ma. , Espinoza-García Gustavo , García-Escalante Juan , Olvera-Olvera Carlos
Published: October 2019

Modeling and simulation of internal variables such as temperature and relative humidity are relevant for designing future climate control systems. In this paper, a mathematical model is proposed to predict the internal variables temperature and relative humidity (RH) of a growth chamber (GCH). Both variables are incorporated in a set of first-order differential equations, considering an energy-mass balance. The results of the model are compared and assessed in terms of the coefficients of determination (R2) and the root mean squared error (RMSE). The R2 and RMSE computed were R2 = 0.96, R2 = 0.94, RMSE = 0.98 °C, and RMSE = 1.08 °C, respectively, for the temperature during two consecutive weeks; and R2 = 0.83, R2 = 0.81, RMSE = 5.45%RH, and RMSE = 5.48%RH, respectively, for the relative humidity during the same period. Thanks to the passive systems used to control internal conditions, the growth chamber gives average differences between inside and outside of +0.34 °C for temperature, and +15.7%RH for humidity without any climate control system. Operating, the GCH proposed in this paper produces 3.5 kg of wet hydroponic green forage (HGF) for each kilogram of seed (corn or barley) harvested on average.
A Common Risk Classification Concept for Safety Related Gas Leaks and Fugitive Emissions?
Authors: Log Torgrim , Pedersen Wegar Bjerkeli
Published: October 2019

Gas leaks in the oil and gas industry represent a safety risk as they, if ignited, may result in severe fires and/or explosions. Unignited, they have environmental impacts. This is particularly the case for methane leaks due to a significant Global Warming Potential (GWP). Since gas leak rates may span several orders of magnitude, that is, from leaks associated with potential major accidents to fugitive emissions on the order of 10−6 kg/s, it has been difficult to organize the leaks in an all-inclusive leak categorization model. The motivation for the present study was to develop a simple logarithmic table based on an existing consequence matrix for safety related incidents extended to include non-safety related fugitive emissions. An evaluation sheet was also developed as a guide for immediate risk evaluations when new leaks are identified. The leak rate table and evaluation guide were tested in the field at five land-based oil and gas facilities during Optical Gas Inspection (OGI) campaigns. It is demonstrated how the suggested concept can be used for presenting and analysing detected leaks to assist in Leak Detection and Repair (LDAR) programs. The novel categorization table was proven valuable in prioritizing repair of “super-emitter” components rather than the numerous minor fugitive emissions detected by OGI cameras, which contribute little to the accumulated emissions. The study was limited to five land based oil and gas facilities in Norway. However, as the results regarding leak rate distribution and “super-emitter” contributions mirror studies from other regions, the methodology should be generally applicable. To emphasize environmental impact, it is suggested to include leaking gas GWP in future research on the categorization model, that is, not base prioritization solely on leak rates. Research on OGI campaign frequency is recommended since frequent coarse campaigns may give an improved cost benefit ratio.
A Decision-Making Tool for Electric Distribution Network Planning Based on Heuristics and Georeferenced Data
Authors: Valenzuela Alex , Montalvo Iván , Inga Esteban
Published: October 2019

Designing and planning of electrical distribution systems is a task that design engineers perform during their daily activities. These designs, which are completed manually, are made according to the expertise of the designer; as a consequence, the obtained product varies depending on the person in charge of executing the layout, highlighting the fact that those designs are susceptible to involuntary human mistakes resulting in no optimal solutions and high cost consequences. The work presented below explains the implementation of an intelligent decision tool that allows the design of network distribution system planning considering the current electrical company standards, in order to have a clear and quick initial overview of the configuration that an electricity network should have in response to an increasing demand, considering not only the coverage and capacity of the transformers but also voltage drop along the conductors, which must not exceed 3% of the nominal value. The objective of this design tool is that it can be applicable in real scenarios; for this reason, the routing of the conductors and the location of the transformers are based on a georeferenced map. It is important to mention that the optimization problem is focused on minimizing the amount of transformers and at the same time ensuring a total coverge of 100% end users connected to the grid. This tool would be very useful in the educational and practical fields, since private and public electricity companies could use it to obtain a quick and efficient base product on which they could start to develop expansion and planning of distribution networks. The concept and development of such a tool is the subject of this paper.
Suppression Effects of Hydroxy Acid Modified Montmorillonite Powders on Methane Explosions
Authors: Wang Yan , Feng Hao , Zhang Yimin , Lin Chendi , Zheng Ligang , Ji Wentao , Han Xuefeng
Published: October 2019

In this paper, montmorillonite inhibitors modified with polyhydroxy functional groups by gluconic acid (GA) were successfully prepared. The particle size distribution, composition, surface functional groups, and pyrolysis characteristics of the pure montmorillonite powders (Mt) and the gluconic acid modified powders (G-Mt) were analyzed by using a laser particle analyzer, X-ray diffraction (XRD), Fourier transform infrared (FTIR) and thermogravimetry–differential scanning calorimetry (TG-DSC), respectively. The suppression effect of Mt and G-Mt on the 9.5% methane–air premixed gas was tested in a 20 L spherical explosion device and a 5 L pipeline experimental system. The results show that G-Mt displays a much better suppression property than that of Mt. The optimal explosion suppression effect concentration of Mt or G-Mt powders is about 0.25 g·L−1. In this concentration, for G-Mt, the maximum explosion pressure declined by 26.7%, the maximum rate of pressure rise declined by 74.63%, and the time for the flame front to reach the top of the pipe was delayed by 242.5%. On the basis of the experimental data, the better suppression effect of G-Mt than Mt might be attributed to the presence of more hydroxyl groups on the surface.