bluuebunny/crossref_metadata_2025 huggingface dataset:
Iterative Phase-Only Hologram Generation Based on the Perceived Image Quality
Authors: Yang Haining , Chu Daping
Published: October 2019

Image quality metrics are a critical element in the iterative Fourier transform algorithms (IFTAs) for the computer generation of phase-only holograms. Conventional image quality metrics such as root-mean-squared error (RMSE) are sensitive to image content and unable to reflect the perceived image quality accurately. This would have a significant impact on the calculation speed and the quality of the generated hologram. In this work, the structure similarity (SSIM) was proposed as an image quality metric in IFTAs due to its ability to predict the perceived image quality in the presence of the white Gaussian noise and its independence on the image content. This would enable IFTAs to terminate when further iterations would no longer lead to improvement in the perceived image quality. As a result, up to 75% of unnecessary iterations were eliminated by the use of SSIM as the image quality metric.
Dynamic Performance Optimization of Circular Sawing Machine Gearbox
Authors: Wang Yangyu , Ni Pengcheng , Wen Donghui , Lin Qiong , Wang Dejie , Ma Changqing , Rao Yanjin , Wang Hanpeng , Tan Dapeng
Published: October 2019

To optimize the rigidity and dynamic mechanical properties of a sawing machine and improve its processing quality and stability, a design method for the sawing machine’s gearbox was proposed. First, a lightweight design of the gearbox was realized by topology optimization. Second, the sensitivity of different design variables of the new gearbox was determined via sensitivity analysis of the objective function. Finally, multi-objective optimization was used to obtain the optimal solution for the gearbox. Considering the complexity of the internal structure of the gearbox assembly and the accuracy of the numerical calculation process, a modeling method with mass points was proposed. A comparison between the numerical calculation results and the operation mode analysis revealed that the former was accurate and can be applied to the verification of the optimized gearbox. By optimizing the vibration signals before and after, and the analysis of the end face quality of the workpiece, the results revealed that the optimized gearbox has a significantly reduced amplitude under various operating conditions. In addition, the vibration stability was improved, and the end face quality of the workpiece was significantly enhanced compared to that before optimization. This study serves as a theoretical reference for multi-body dynamics modeling and optimization of machine tools, and also outlines technical solutions for high-speed stable cutting with sawing machines.
Circadian Clock Regulation of Hepatic Energy Metabolism Regulatory Circuits
Authors: Hunter Ann Louise , Ray David W.
Published: October 2019

The liver is a critical organ of energy metabolism. At least 10% of the liver transcriptome demonstrates rhythmic expression, implying that the circadian clock regulates large programmes of hepatic genes. Here, we review the mechanisms by which this rhythmic regulation is conferred, with a particular focus on the transcription factors whose actions combine to impart liver- and time-specificity to metabolic gene expression.
The HER2 S310F Mutant Can Form an Active Heterodimer with the EGFR, Which Can Be Inhibited by Cetuximab but Not by Trastuzumab as well as Pertuzumab
Authors: Shin Jung Won , Kim Soohyun , Ha Suji , Choi Byungsan , Kim Seongyeong , Im Seock-Ah , Yoon Tae-Young , Chung Junho
Published: October 2019

G309 or S310 mutations on the HER2 extracellular domain II induce receptor activation. Clinically, S310F is most frequent among HER2 extracellular domain mutations and patients with the S310F mutation without HER2 amplification responded to trastuzumab with or without the pertuzumab combination. However, the ability of S310F mutant to form homodimers or heterodimers with wild-type HER2 and other HER receptors, or their reactivity to trastuzumab and pertuzumab treatments, has not been reported. We overexpressed S310F as well as G309A, G309E and S310Y HER2 mutants and tested their reactivity to trastuzumab and pertuzumab. All mutants reacted to trastuzumab, but S310F mutant did not react to pertuzumab along with S310Y or G309E mutants. Thereafter, we tested the effects of trastuzumab and pertuzumab on 5637 cell line expressing both wild-type HER2 and S310F mutant. The ligand-independent HER2 homodimerization blocking antibody, trastuzumab, did not inhibit the activation of the HER2 receptor, suggesting that the S310F HER2 mutant did not form homodimers or heterodimers with wild-type HER2. Because 5637 cells overexpressed the EGFR, the effects of cetuximab and gefitinib were determined, and both inhibited the activation of HER2 and significantly reduced cell growth. Because pertuzumab did not inhibit the phosphorylation of HER2 while it bound to wild-type HER2, EGFR-mediated phosphorylation is expected to occur on the S310F mutant. To confirm whether the S310F mutant HER2 retained its affinity to the EGFR, single molecule interaction analyses using TIRF microscopy were performed, which showed that S310F mutant successfully formed complexes with EGFR. In conclusion, HER2 S310F mutant can form an active heterodimer with the EGFR and it can be inhibited by cetuximab, but not by trastuzumab in combination with pertuzumab.
Sex-Specific Associations of Brain-Derived Neurotrophic Factor and Cardiorespiratory Fitness in the General Population
Authors: Schmalhofer Marie-Lena , Markus Marcello R.P. , Gras Jan C. , Kopp Juliane , Janowitz Deborah , Grabe Hans-Jörgen , Groß Stefan , Ewert Ralf , Gläser Sven , Albrecht Diana , Eiffler Ina , Völzke Henry , Friedrich Nele , Nauck Matthias , Steveling Antje , Könemann Stephanie , Wenzel Kristin , Felix Stephan B. , Dörr Marcus , Bahls Martin
Published: October 2019

The brain-derived neurotrophic factor (BDNF) was initially considered to be neuron-specific. Meanwhile, this neurotrophin is peripherally also secreted by skeletal muscle cells and increases due to exercise. Whether BDNF is related to cardiorespiratory fitness (CRF) is currently unclear. We analyzed the association of serum BDNF levels with CRF in the general population (Study of Health in Pomerania (SHIP-TREND) from Northeast Germany; n = 1607, 51% female; median age 48 years). Sex-stratified linear regression models adjusted for age, height, smoking, body fat, lean mass, physical activity, and depression analyzed the association between BDNF and maximal oxygen consumption (VO2peak), maximal oxygen consumption normalized for body weight (VO2peak/kg), and oxygen consumption at the anaerobic threshold (VO2@AT). In women, 1 mL/min higher VO2peak, VO2peak/kg, and VO2@AT were associated with a 2.43 pg/mL (95% confidence interval [CI]: 1.16 to 3.69 pg/mL; p = 0.0002), 150.66 pg/mL (95% CI: 63.42 to 237.90 pg/mL; p = 0.0007), and 2.68 pg/mL (95% CI: 0.5 to 4.8 pg/mL; p = 0.01) higher BDNF serum concentration, respectively. No significant associations were found in men. Further research is needed to understand the sex-specific association between CRF and BDNF.
Synthesis of Novel Analogs of Thieno[2,3-d] Pyrimidin-4(3H)-ones as Selective Inhibitors of Cancer Cell Growth
Authors: Zhang Sheng , Liu Feize , Hou Xueling , Cao Jianguo , Dai Xiling , Yu Junjie , Huang Guozheng
Published: October 2019

New 2,3-disubstituted thieno[2,3-d]pyrimidin-4(3H)-ones were synthesized via a one-pot reaction from 2H-thieno[2,3-d] [1,3]oxazine-2,4(1H)-diones, aromatic aldehydes, and benzylamine or 4-hydroxylbezylamine. The obtained compounds were tested in vitro for cancer cell growth inhibition. Compound 19 can inhibit all four types of tested cancer cells, i.e., MCF-7, A549, PC-9, and PC-3 cells. Most of the compounds inhibited the proliferation of A549 and MCF-7 cells. Compound 15 exhibited the strongest anti-proliferative effect against A549 cell lines with IC50 values of 0.94 μM, and with no toxicity to normal human liver cells. Its potency was further proved by cell clone formation assay, Hoechst 33258 staining, and evaluation on the effects of apoptosis-related proteins.
Overexpression of Macrophage Migration Inhibitory Factor and Its Homologue D-Dopachrome Tautomerase as Negative Prognostic Factor in Neuroblastoma
Authors: Cavalli Eugenio , Mazzon Emanuela , Mammana Santa , Basile Maria , Lombardo Salvo , Mangano Katia , Bramanti Placido , Nicoletti Ferdinando , Fagone Paolo , Petralia Maria
Published: October 2019

Neuroblastoma (NB) represents one of the most frequent pediatric solid tumors. Macrophage migration inhibitory factor (MIF) is a cytokine exerting multiple biological functions. More recently, a second member of the MIF family of cytokine has been identified, the D-dopachrome tautomerase (DDT), that exerts several overlapping functions with MIF. Growing evidence suggests a key role for MIF and DDT in the development of cancer. The aim of this study is to characterize the prognostic value of MIF and DDT in NB. We show that higher expression levels of MIF and DDT in Stage 4 NB samples are associated with a poorer prognosis, independently of the presence of MYCN amplification. Moreover, higher levels of MIF are mostly enriched by Th1 cells, while lower levels of MIF are associated with an increased proportion of B cells, Cytotoxic T cells, Dendritic cells and Natural Killer T cells. We also show that treatment with the histone deacetylase (HDAC) inhibitor, vorinostat, of the NB cell line, SH-SY5Y, determines a significant reduction in the expression of both MIF and DDT. Finally, MIF and DDT inhibition by short interfering RNA is able to revert vincristine sensitivity in vitro. Overall, our data suggest that MIF exert pro-tumorigenic properties in NB, likely by dampening antigen presentation and cytotoxic immune responses, and we propose the HDAC inhibitors as a potential therapeutic strategy for NB patients.
Exploiting ING2 Epigenetic Modulation as a Therapeutic Opportunity for Non-Small Cell Lung Cancer
Authors: Blondel Alice , Benberghout Amine , Pedeux Rémy , Ricordel Charles
Published: October 2019

Non-small cell lung cancer (NSCLC) has been the leading cause of cancer-related death worldwide, over the last few decades. Survival remains extremely poor in the metastatic setting and, consequently, innovative therapeutic strategies are urgently needed. Inhibitor of Growth Gene 2 (ING2) is a core component of the mSin3A/Histone deacetylases complex (HDAC), which controls the chromatin acetylation status and modulates gene transcription. This gene has been characterized as a tumor suppressor gene and its status in cancer has been scarcely explored. In this review, we focused on ING2 and other mSin3A/HDAC member statuses in NSCLC. Taking advantage of existing public databases and known pharmacological properties of HDAC inhibitors, finally, we proposed a therapeutic model based on an ING2 biomarker-guided strategy.
The Brain Penetrating and Dual TORC1/TORC2 Inhibitor, RES529, Elicits Anti-Glioma Activity and Enhances the Therapeutic Effects of Anti-Angiogenetic Compounds in Preclinical Murine Models
Authors: Gravina Giovanni Luca , Mancini Andrea , Colapietro Alessandro , Delle Monache Simona , Sferra Roberta , Pompili Simona , Vitale Flora , Martellucci Stefano , Marampon Francesco , Mattei Vincenzo , Biordi Leda , Sherris David , Festuccia Claudio
Published: October 2019

Background. Glioblastoma multiforme (GBM) is a devastating disease showing a very poor prognosis. New therapeutic approaches are needed to improve survival and quality of life. GBM is a highly vascularized tumor and as such, chemotherapy and anti-angiogenic drugs have been combined for treatment. However, as treatment-induced resistance often develops, our goal was to identify and treat pathways involved in resistance to treatment to optimize the treatment strategies. Anti-angiogenetic compounds tested in preclinical and clinical settings demonstrated recurrence associated to secondary activation of the phosphatidylinositol 3-kinase (PI3K)/AKT/mTOR pathway. Aims. Here, we determined the sensitizing effects of the small molecule and oral available dual TORC1/TORC2 dissociative inhibitor, RES529, alone or in combination with the anti-VEGF blocking antibody, bevacizumab, or the tyrosine kinase inhibitor, sunitinib, in human GBM models. Results. We observed that RES529 effectively inhibited dose-dependently the growth of GBM cells in vitro counteracting the insurgence of recurrence after bevacizumab or sunitinib administration in vivo. Combination strategies were associated with reduced tumor progression as indicated by the analysis of Time to Tumor Progression (TTP) and disease-free survival (DSF) as well as increased overall survival (OS) of tumor bearing mice. RES529 was able to reduce the in vitro migration of tumor cells and tubule formation from both brain-derived endothelial cells (angiogenesis) and tumor cells (vasculogenic mimicry). Conclusions. In summary, RES529, the first dual TORC1/TORC2 dissociative inhibitor, lacking affinity for ABCB1/ABCG2 and having good brain penetration, was active in GBM preclinical/murine models giving credence to its use in clinical trial for patients with GBM treated in association with anti-angiogenetic compounds.
Fe Speciation in Iron Modified Natural Zeolites as Sustainable Environmental Catalysts
Authors: Chávez Rivas Fernando , Rodríguez-Iznaga Inocente , Berlier Gloria , Tito Ferro Daria , Concepción-Rosabal Beatriz , Petranovskii Vitalii
Published: October 2019

Natural purified mordenite from Palmarito de Cauto (ZP) deposit, Cuba, was subjected to a hydrothermal ion exchange process in acid medium with Fe2+ or Fe3+ salts (Fe2+ZP and Fe3+ZP). The set of samples was characterized regarding their textural properties, morphology, and crystallinity, and tested in the NO reduction with CO/C3H6. Infrared spectroscopy coupled with NO as a probe molecule was used to give a qualitative description of the Fe species’ nature and distribution. The exchange process caused an increase in the iron loading of the samples and a redistribution, resulting in more dispersed Fe2+ and Fe3+ species. When contacted with the NO probe, Fe2+ZP showed the highest intensity of nitrosyl bands, assigned to NO adducts on isolated/highly dispersed Fe2+/Fe3+ extra-framework sites and FexOy clusters. This sample is also characterized by the highest NO sorption capacity and activity in NO reduction. Fe3+ZP showed a higher intensity of nitrosonium (NO+) species, without a correlation to NO storage and conversion, pointing to the reactivity of small FexOy aggregates in providing oxygen atoms for the NO to NO+ reaction. The same sites are proposed to be responsible for the higher production of CO2 observed on this sample, and thus to be detrimental to the activity in NO SCR.
Photocatalysts for Organics Degradation
Authors: Bonelli Barbara , Manzoli Maela , Freyria Francesca S. , Esposito Serena
Published: October 2019

Organics degradation is one of the challenges of Advanced Oxidation Processes (AOPs), which are mainly employed for the removal of water and air pollutants [...]
Kinetics of Fischer–Tropsch Synthesis in a 3-D Printed Stainless Steel Microreactor Using Different Mesoporous Silica Supported Co-Ru Catalysts
Authors: Mohammad Nafeezuddin , Bepari Sujoy , Aravamudhan Shyam , Kuila Debasish
Published: October 2019

Fischer–Tropsch (FT) synthesis was carried out in a 3D printed stainless steel (SS) microchannel microreactor using bimetallic Co-Ru catalysts on three different mesoporous silica supports. CoRu-MCM-41, CoRu-SBA-15, and CoRu-KIT-6 were synthesized using a one-pot hydrothermal method and characterized by Brunner–Emmett–Teller (BET), temperature programmed reduction (TPR), SEM-EDX, TEM, and X-ray photoelectron spectroscopy (XPS) techniques. The mesoporous catalysts show the long-range ordered structure as supported by BET and low-angle XRD studies. The TPR profiles of metal oxides with H2 varied significantly depending on the support. These catalysts were coated inside the microchannels using polyvinyl alcohol and kinetic performance was evaluated at three different temperatures, in the low-temperature FT regime (210–270 °C), at different Weight Hourly Space Velocity (WHSV) in the range of 3.15–25.2 kgcat.h/kmol using a syngas ratio of H2/CO = 2. The mesoporous supports have a significant effect on the FT kinetics and stability of the catalyst. The kinetic models (FT-3, FT-6), based on the Langmuir–Hinshelwood mechanism, were found to be statistically and physically relevant for FT synthesis using CoRu-MCM-41 and CoRu-KIT-6. The kinetic model equation (FT-2), derived using Eley–Rideal mechanism, is found to be relevant for CoRu-SBA-15 in the SS microchannel microreactor. CoRu-KIT-6 was found to be 2.5 times more active than Co-Ru-MCM-41 and slightly more active than CoRu-SBA-15, based on activation energy calculations. CoRu-KIT-6 was ~3 and ~1.5 times more stable than CoRu-SBA-15 and CoRu-MCM-41, respectively, based on CO conversion in the deactivation studies.
Review on Techniques for Plant Leaf Classification and Recognition
Authors: Azlah Muhammad Azfar Firdaus , Chua Lee Suan , Rahmad Fakhrul Razan , Abdullah Farah Izana , Wan Alwi Sharifah Rafidah
Published: October 2019

Plant systematics can be classified and recognized based on their reproductive system (flowers) and leaf morphology. Neural networks is one of the most popular machine learning algorithms for plant leaf classification. The commonly used neutral networks are artificial neural network (ANN), probabilistic neural network (PNN), convolutional neural network (CNN), k-nearest neighbor (KNN) and support vector machine (SVM), even some studies used combined techniques for accuracy improvement. The utilization of several varying preprocessing techniques, and characteristic parameters in feature extraction appeared to improve the performance of plant leaf classification. The findings of previous studies are critically compared in terms of their accuracy based on the applied neural network techniques. This paper aims to review and analyze the implementation and performance of various methodologies on plant classification. Each technique has its advantages and limitations in leaf pattern recognition. The quality of leaf images plays an important role, and therefore, a reliable source of leaf database must be used to establish the machine learning algorithm prior to leaf recognition and validation.
Ice Crystals
Authors: Furukawa Yoshinori
Published: October 2019

The special issue on “Ice Crystals” includes seven contributed papers, which give the wide varieties of topics related to ice crystals. They focus on the interface structure of ice, the physical properties of hydrate crystals and the freezing properties of water controlled by antifreeze proteins. The present issue can be considered as a status report reviewing the research that has been made recently on ice crystals. These papers provide research information about the recent development of ice crystal research to readers.
Limnology and Aquatic Microbial Ecology of Byers Peninsula: A Main Freshwater Biodiversity Hotspot in Maritime Antarctica
Authors: Rochera Carlos , Camacho Antonio
Published: October 2019

Here we present a comprehensive review of the diversity revealed by research in limnology and microbial ecology conducted in Byers Peninsula (Livingston Island, South Shetland Islands, Antarctica) during the last two decades. The site constitutes one of the largest ice-free areas within the Antarctic Peninsula region. Since it has a high level of environmental protection, it is less human-impacted compared to other sites within the South Shetland archipelago. The main investigations in Byers Peninsula focused on the physical and chemical limnology of the lakes, ponds, rivers, and wetlands, as well as on the structure of their planktonic and benthic microbial communities, and on the functional ecology of the microbial food webs. Lakes and ponds in Byers range along a productivity gradient that extends from the less productive lakes located upland to the eutrophic coastal lakes. Their planktonic assemblages include viruses, bacteria, a metabolically diverse community of protists (i.e., autotrophs, heterotrophs, and mixotrophs), and a few metazooplankton species. Most of the studies conducted in the site demonstrate the strong influence of the physical environment (i.e., temperature, availability of light, and water) and nutrient availability in structuring these microbial communities. However, top-down biotic processes may occur in summer, when predation by zooplankton can exert a strong influence on the abundance of protists, including flagellates and ciliated protozoa. As a consequence, bacterioplankton could be partly released from the grazing pressure exerted by these protists, and proliferates fueled by external nutrient subsidies from the lake’s catchment. As summer temperatures in this region are slightly above the melting point of water, biotic processes, such as those related to the productivity of lakes during ice-free periods, could become even more relevant as warming induced by climate change progresses. The limnological research carried out at the site proves that Byers Peninsula deserves special attention in the framework of the research in extreme environments. Together with nearby sites, such as Signy Island, Byers Peninsula comprises a featuring element of the Maritime Antarctic region that represents a benchmark area relative to the global distribution and diversity of aquatic microorganisms.
Capacity Allocation of Game Tickets Using Dynamic Pricing
Authors: Dutta Aniruddha
Published: October 2019

This study examines a pricing approach that is applicable in the field of online ticket sales for game tickets. The mathematical principle of dynamic programing is combined with empirical data analysis to determine demand functions for university football game tickets. Based on the calculated demand functions, the application of DP strategies is found to generate more revenues than a fixed price strategy. The other important result is the capacity distribution of tickets according to the football game intensity. Prior studies have shown that it is sometimes more profitable or football clubs to allocate a share of tickets to a retailer and earn a commission based on the sales, rather than selling the entire capacity of tickets by itself. This paper finds that in a high intensity game, where the demand is generally high, it is optimal for the club to sell all tickets by itself. Whereas, for less popular games, where there is considerable fluctuation in demand, the capacity allocation problem for maximized revenues from ticket sales, becomes a harder optimization challenge for the club. According to DP optimization, when the demand for tickets is relatively low, it is optimal for the club to retain 20–40% of the tickets and the rest of the capacity should be sold to online retailers. In the real world, this pricing technique has been used by football clubs and thus the secondary market online retailers like Ticketmaster and Vivid Seats have become popular in the last decade.
State Clustering of the Hot Strip Rolling Process via Kernel Entropy Component Analysis and Weighted Cosine Distance
Authors: Wang Chaojun , He Fei
Published: October 2019

In the hot strip rolling process, many process parameters are related to the quality of the final products. Sometimes, the process parameters corresponding to different steel grades are close to, or even overlap, each other. In reality, locating overlap regions and detecting products with abnormal quality are crucial, yet challenging. To address this challenge, in this work, a novel method named kernel entropy component analysis (KECA)-weighted cosine distance is introduced for fault detection and overlap region locating. First, KECA is used to cluster the training samples of multiple steel grades, and the samples with incorrect classes are seen as the boundary of the sample distribution. Next, the concepts of recursive-based regional center and weighted cosine distance are introduced. For each steel grade, the regional center and the weight coefficients are determined. Finally, the weighted cosine distance between the testing sample and the regional center is chosen as the index to judge abnormal batches. The samples in the overlap region of multiple steel grades need to be focused on in the real production process, which is conducive to quality grade and combined production. The weighted cosine distances between the testing sample and different regional centers are used to locate the overlap region. A dataset from a hot steel rolling process is used to evaluate the performance of the proposed methods.
Electric Vehicles: A Data Science Perspective Review
Authors: Pevec Dario , Babic Jurica , Podobnik Vedran
Published: October 2019

Current trends are showing that the popularity of electric vehicles (EVs) has significantly increased over the last few years, causing changes not only in the transportation industry but generally in business and society. This paper covers one possible angle to the (r) evolution instigated by EVs, i.e., it provides the data science perspective review of the interdisciplinary area at the intersection of green transportation, energy informatics, and economics. Namely, the review summarizes data-driven research in EVs by identifying two main research streams: (i) socio–economic, and (ii) socio–technical. The socio–economic stream includes research in: (i) acceptance of green transportation in countries and among different populations, (ii) current trends in the EV market, and (iii) forecasting future sales for the green transportation. The socio–technical stream includes research in: (i) electric vehicle battery price and capacity and (ii) charging station management. This kind of study is especially important now when the question is no longer whether the transition from internal-combustion engine vehicles to clean-fuel vehicles is going to happen but how fast it will happen and what are going to be implications for society, governmental policies, and industry. Based on the presented literature review, the paper also outlines the most significant open questions and challenges that are yet to be solved: (i) scarcity of trustworthy (open) data, and (ii) designing a generalized methodology for charging station deployment.
Analysis of Energy Consumption and Optimization Techniques for Writing Energy-Efficient Code
Authors: Corral-García Javier , Lemus-Prieto Felipe , González-Sánchez José-Luis , Pérez-Toledano Miguel-Ángel
Published: October 2019

The unprecedented growth of connected devices, together with the remarkable convergence of a wide variety of technologies, have led to an exponential increase in the services that the internet of things (IoT) can offer, all aimed at improving quality of life. Consequently, in order to meet the numerous challenges this produces, the IoT has become a major subject of research. One of these challenges is the reduction of energy consumption given the significant limitations of some devices. In addition, although the search for energy efficiency was initially focused on hardware, it has become a concern for software developers too. In fact, it has become an intense area of research with the principal objective of analyzing and optimizing the energy consumption of software systems. This research analyzes the energy saving that can be achieved when using a broad set of techniques for writing energy-efficient code for Raspberry Pi devices. It also demonstrates that programmers can save more energy if they apply the proposed techniques manually than when relying on other automatic optimization options offered by the GNU compiler collection (GCC). Thus, it is important that programmers are aware of the significant impact these techniques can have on an application’s energy consumption.
LLC Resonant Voltage Multiplier-Based Differential Power Processing Converter Using Voltage Divider with Reduced Voltage Stress for Series-Connected Photovoltaic Panels under Partial Shading
Authors: Uno Masatoshi , Nakane Toru , Shinohara Toshiki
Published: October 2019

Partial shading on photovoltaic (PV) strings consisting of multiple panels connected in series is known to trigger severe issues, such as reduced energy yield and the occurrence of multiple power point maxima. Various kinds of differential power processing (DPP) converters have been proposed and developed to prevent partial shading issues. Voltage stresses of switches and capacitors in conventional DPP converters, however, are prone to soar with the number of panels connected in series, likely resulting in impaired converter performance and increased circuit volume. This paper proposes a DPP converter using an LLC resonant voltage multiplier (VM) with a voltage divider (VD) to reduce voltage stresses of switches and capacitors. The VD can be arbitrarily extended by adding switches and capacitors, and the voltage stresses can be further reduced by extending the VD. Experimental verification tests for four PV panels connected in series were performed emulating partial shading conditions in a laboratory and outdoor. The results demonstrated the proposed DPP converter successfully precluded the negative impacts of partial shading with mitigating the voltage stress issues.
A Smart Overvoltage Monitoring and Hierarchical Pattern Recognizing System for Power Grid with HTS Cables
Authors: Jiang Kaihua , Du Lin , Wang Yubo , Li Jianwei
Published: October 2019

As one part of the power system, high-temperature superconducting (HTS) cables may be subject to various system faults, such as overvoltage. When overvoltage occurs, HTS cables may quench and the resistance of HTS tapes will increase rapidly, which will result in reduction of transmission capacity, increase of power loss and even electrical insulation breakdown. To protect the operation safety of power system, the level of overvoltage should be investigated in the system. This paper proposes a non-contact variable frequency sampling and hierarchical pattern recognizing system for overvoltage. Lightning and internal overvoltage signals are captured by specially designed non-contact voltage sensors. The sensors are installed at the grounding tap of transformer bushings and the cross arm of transmission towers. A variable sampling technique is employed to solve the conflict between sampling speed and storage capacity. A hierarchical pattern recognizing system is proposed to subdivide each overvoltage into specific types. Seven common overvoltages are discussed and analyzed. Wavelet theory and S-transform singular value decomposition (SVD) theory are adopted to extract the feature parameters of different overvoltages. Particle swarm optimization is employed to maintain a high classification rate and improve the initial set of the support vector machine (SVM) used as recognition algorithm. Field-acquired overvoltage data from an 110 kV substation validate the effectiveness of the proposed recognition system.
Single JFET Front-End Amplifier for Low Frequency Noise Measurements with Cross Correlation-Based Gain Calibration
Authors: Scandurra Graziella , Giusi Gino , Ciofi Carmine
Published: October 2019

We propose an open loop voltage amplifier topology based on a single JFET front-end for the realization of very low noise voltage amplifiers to be used in the field of low frequency noise measurements. With respect to amplifiers based on differential input stages, a single transistor stage has, among others, the advantage of a lower background noise. Unfortunately, an open loop approach, while simplifying the realization, has the disadvantage that because of the dispersions in the characteristics of the active device, it cannot ensure that a well-defined gain be obtained by design. To address this issue, we propose to add two simple operational amplifier-based auxiliary amplifiers with known gain as part of the measurement chain and employ cross correlation for the calibration of the gain of the main amplifier. With proper data elaboration, gain calibration and actual measurements can be carried out at the same time. By using the approach we propose, we have been able to design a low noise amplifier relying on a simplified hardware and with background noise as low as 6 nV/√Hz at 200 mHz, 1.7 nV/√Hz at 1 Hz, 0.7 nV/√Hz at 10 Hz, and less than 0.6 nV/√Hz at frequencies above 100 Hz.
A Stochastic-CVaR Optimization Model for CCHP Micro-Grid Operation with Consideration of Electricity Market, Wind Power Accommodation and Multiple Demand Response Programs
Authors: Wang Yuwei , Yang Yuanjuan , Tang Liu , Sun Wei , Zhao Huiru
Published: October 2019

Combined cooling, heating and power (CCHP) micro-grids have the advantage of high energy efficiency, and can be integrated with renewable energies and demand response programs (DRPs). With the deepening of electricity market (EM) reforms, how to carry out operation optimization under EM circumstances will become a key problem for CCHP micro-grid development. This paper proposed a stochastic-CVaR (conditional value at risk) optimization model for CCHP micro-grid operation with consideration of EM participation, wind power accommodation and multiple DRPs. Specifically, based on the stochastic scenarios for EM clearing prices and wind power outputs uncertainties, the stochastic optimization method was applied to ensure the realization of operational cost minimization and wind power accommodation; the CVaR method was implemented to control the potential risk of operational cost increase. Moreover, by introducing multiple DRPs, the electrical, thermal and cooling loads can be transformed as flexible sources for CCHP micro-grid operation. Simulations were performed to show the following outcomes: (1) by applying the proposed stochastic-CVaR approach and considering multiple DRPs, CCHP micro-grid operation can reach better performance in terms of cost minimization, risk control and wind power accommodation etc.; (2) higher energy utilization efficiency can be achieved by coordinately optimizing EM power biddings; etc.
Maximum Perturbation Step Size in MPP-Tracking Control for Ensuring Predicted PV Power Settling Behavior
Authors: Suntio Teuvo , Kuperman Alon
Published: October 2019

The heuristic perturb-and-observe-based maximum-power-point tracking (MPPT) algorithm of photovoltaic (PV) generator is still the most popular technique in use, despite the broad spectrum of developed other MPPT algorithms. The correct direction of the next perturbation step requires that the previous perturbation is settled down properly and the applied perturbation step size is large enough to overcome the PV-power changes induced by the varying irradiation level and/or the power-grid-originated PV-voltage ripple. The requirements for the minimum perturbation step size are well defined in the available literature. The design equations to predict the PV-power settling time are derived by assuming that the PV-interfacing converter operates in continuous conduction mode (CCM). A large perturbation step size may drive the interfacing converter to enter into discontinuous conduction mode (DCM), which will delay the PV-power settling process and destroy the validity of the predicted settling times. In order to avoid confusing the MPPT process, the maximum perturbation step size has to be limited as well. This paper provides theoretical foundations for the proper design of the maximum step size based on the DC-DC interfacing-converter dynamic behavior. The theoretical findings are validated with experiments as well as by simulations by means of a boost-type DC-DC converter and real PV panel.
Energy Poverty and Life Satisfaction: Structural Mechanisms and Their Implications
Authors: Druică Elena , Goschin Zizi , Ianole-Călin Rodica
Published: October 2019

This paper investigates the distinct mechanisms through which energy poverty is linked to life satisfaction, via health status and one’s satisfaction with one’s own socioeconomic status, using data from the Life in Transition survey. Our sample contains 19,598 individuals from 11 former communist states located in Central and Eastern Europe, and two developed countries for comparison. We estimated a partial least squared–path model and found that both health status and socioeconomic status are relevant mediators. Our results also indicate that gender moderates the relation between health status and life satisfaction. Energy poverty has a low contribution to health status but a larger contribution to satisfaction with socioeconomic status, thus indicating that interventions on energy poverty may not greatly improve the level of health, but can have an influence on how people feel about their life. The contribution of our paper is twofold. On the one side, we continue to consolidate the existing link between energy poverty and self-reported health status with a new focus on the Central and Eastern European countries; on another side, we propose a theoretical framework expansion by including totally novel factors to be analyzed in this context: satisfaction with socioeconomic status, economic environment improvement, and intolerance.
Efficient Model Predictive Control with Natural Fault-Tolerance in Asymmetrical Six-Phase Induction Machines
Authors: Gonzalez-Prieto Angel , Gonzalez-Prieto Ignacio , Duran Mario J. , Barrero Federico
Published: October 2019

Multiphase machines allow enhancing the performance of wind energy conversion systems from the point of view of reliability and efficiency. The enhanced robustness has been traditionally achieved with a mandatory post-fault control reconfiguration. Nevertheless, when the regulation of x-y currents in multiphase drives is done in open-loop mode, the reconfiguration can be avoided. As a consequence, the reliability of the system increases because fault detection errors or delays have no impact on the post-fault performance. This capability has been recently defined as natural fault tolerance. From the point of view of the efficiency, multiphase machines present a better power density than three-phase machines and lower per-phase currents for the same voltage rating. Moreover, the implementation of control strategies based on a variable flux level can further reduce the system losses. Targeting higher reliability and efficiency for multiphase wind energy conversion systems, this work proposes the implementation of an efficient model predictive control using virtual voltage vectors for six-phase induction machines. The use of virtual voltage vectors allows regulation of the x-y currents in open-loop mode and achieving the desired natural fault tolerance. Then, a higher efficiency can be achieved with a simple and universal cost function, which is valid both in pre- and post-fault situations. Experimental results confirm the viability and goodness of the proposal.
Research on a Temperature Control Device for Seawater Hydraulic Systems Based on a Natural Gas Hydrate Core Sample Pressure-Retaining and Transfer Device
Authors: Zhang Peihao , Chen Jiawang , Gao Qiaoling , Xiao Bo , Geng Xueqiao , Zhou Peng
Published: October 2019

In the study of natural gas hydrates, the maintenance of the low-temperature and high-pressure state of the core sample under in situ conditions is highly important for cutting, transferring, and subsequent analysis. The pressure maintenance and temperature control device (PMTCD) for natural gas hydrate core samples described in this paper is a subsystem of the pressure-retaining and transfer device. The device consists of a water tank, seawater chillers, a plunger pump and a thermoelectrical refrigeration device. The device cools the seawater to 2 °C, and then pressurizes it to inject it into the sample cylinder. Due to the inevitable heat generated by the pressurization and heat exchange with environment, there is a thermoelectrical refrigeration device to compensate for temperature rise. Finally, the seawater temperature entering the sample cylinder is no higher than 3 °C, effectively preventing the decomposition and deterioration of the natural gas hydrate core in the sample cylinder. In this paper, the temperature increase of the device and its compensation capacity are analyzed in detail on the basis of calculation and simulation. On the basis of testing with the device, it is verified that even at the ambient temperature, the water temperature can still be maintained at 3 °C.
Fault Ride-Through Enhancement of Grid Supporting Inverter-Based Microgrid Using Delayed Signal Cancellation Algorithm Secondary Control
Authors: Buraimoh Elutunji , Davidson Innocent E. , Martinez-Rodrigo Fernando
Published: October 2019

The growing level of grid-connected renewable energy sources in the form of microgrids has made it highly imperative for grid-connected microgrids to contribute to the overall system stability. Consequently, secondary services which include the fault ride-through (FRT) capability are expected to be possessed characteristics by inverter-based microgrids. This enhances the stable operation of the main grid and sustained microgrid grid interconnection during grid faults in conformity with the emerging national grid codes. This paper proposes an effective FRT secondary control strategy to coordinate power injection during balanced and unbalanced fault conditions. This complements the primary control to form a two-layer hierarchical control structure in the microgrids. The primary level is comprised of voltage/power and current inner loops fed by a droop control. The droop control coordinates grid power-sharing amongst the voltage source inverters. When a fault occurs, the participating inverters operate to support the grid voltage, by injecting supplementary reactive power based on their droop gains. Similarly, under unbalanced voltage condition due to asymmetrical faults in the grid, the proposed secondary control ensures the positive sequence component compensation and negative and zero sequence components clearance using a delayed signal cancellation (DSC) algorithm and power electronic switched series impedance placed in-between the point of common coupling (PCC) and the main grid. While ensuring that FRT ancillary service is rendered to the main utility, the strategy proposed ensures relatively interrupted quality power is supplied to the microgrid load. Consequently, this strategy ensures the microgrid ride-through the voltage sag and supports the grid utility voltage during the period of the main utility grid fault. Results of the study are presented and discussed.
Computational Analysis of the Performance of a Vertical Axis Turbine in a Water Pipe
Authors: Yeo Honggu , Seok Woochan , Shin Soyong , Huh Young Cheol , Jung Byung Chang , Myung Cheol-Soo , Rhee Shin Hyung
Published: October 2019

In this study, a computational analysis was performed for a vertical-axis turbine which was installed in a water pipe to collect unused energy from the flow inside the pipe. The optimized operating conditions of the turbine were identified by comparing the energy-collecting performance obtained at different tip-speed ratios (TSRs). The turbine achieved the maximum efficiency of 22% at a TSR of 2.4 and collected 33 kW. Additional analyses were conducted to verify the effects of tip clearance, which is the distance between the turbine blades and the pipe wall, which showed that a higher efficiency was obtained with a smaller tip clearance. We also verified the effects of the turbine’s operating conditions and tip clearance on the flow field around the blades and wake of the turbine.
Design of an Electromagnetic Variable Valve Train with a Magnetorheological Buffer
Authors: Guo He , Liu Liang , Zhu Xiangbin , Chang Siqin , Xu Zhaoping
Published: October 2019

In this paper, an electromagnetic variable valve train with a magnetorheological buffer (EMVT with MR buffer) is proposed. This system is mainly composed of an electromagnetic linear actuator (EMLA) and a magnetorheological buffer (MR buffer). The valves of an internal combustion engine are driven by the EMLA directly to open and close, which can adjust the valve lift and phase angle of the engine. At the same time, MR buffer can reduce the seat velocity of the valve and realize the seat buffer of the electromagnetic variable valve. In this paper, the overall design scheme of the system is proposed and the structure design, finite element simulation of the EMLA, and the MR buffer are carried out. The electromagnetic force characteristics of the EMLA and buffer force of the MR buffer are measured, and the seat buffering performance is verified as well. Experiments and simulation results show that the electromagnetic force of the EMLA can reach 320.3 N when the maximum coil current is 40 A. When the current of the buffer coil is 2.5 A and the piston’s motion frequency is 5 Hz, the buffering force can reach 35 N. At the same time, a soft landing can be realized when the valve is seated.
Research on the Real-Time Distributed Economic Dispatch Strategy for Microgrids
Authors: Le Jian , Zhou Qian , Zhao Liangang , Wang Yang
Published: October 2019

A microgrid (MG) is one of the most efficient ways to cope with the grid-connection of a large number of small-sized distributed energy resources. This paper presents a consensus-based fully distributed economic dispatch (ED) strategy for MGs, with the aim of tackling the difficulties of existing algorithms in modeling network power loss and providing global information. The external power grid to which the MG connects is treated as a special power source called a virtual generator, and participates in the economic dispatch process. Taking the incremental cost of a power generator as the consensus variable, a distributed ED model was formulated based on consensus protocol and a sub-gradient-based optimization method for solving this model has been proposed. The convergence of the distributed ED system was investigated by utilizing matrix spectrum radius analysis theory. The effectiveness of the proposed strategy was verified by carrying out simulation under normal operation of the MG, both with and without the consideration of network power loss. Moreover, simulation results under several scenarios, including exchanged power order variation and distributed generation plug and play, are provided to demonstrate the robustness of the distributed ED strategy.
Differential Expression of Genes Related to the Formation of Giant Leaves in Triploid Poplar
Authors: Du Kang , Han Qiang , Zhang Ying , Kang Xiangyang
Published: October 2019

Plant polyploids tend to have large leaves, but their formation mechanism has not yet been well explained. Therefore, daily transcriptomic differences between triploids and diploids from a synthetic Populus sect. Tacamahaca three times a day (i.e., 04:00, 09:00, and 21:00) were investigated using high-throughput RNA-seq analysis. In this study, we identified several transcription factors associated with giant leaves. The combined effects included the high expression of several transcription factors (WRKY, MYB, etc.) and hormone-related genes (e.g., activates auxin, cytokine, and brassinosteroid synthesis-related genes) that accelerate the synthesis and accumulation of endogenous hormones. High levels of growth hormones were maintained by reducing the genes’ expression of hormone metabolism and degradation. The coordination of hormones accumulated sufficient materials and energy for leaf growth and development. Thereby, cell division and growth were accelerated which enhanced the photosynthesis of leaves, and the increased accumulation of photosynthetic products led to giant triploid leaves. This study lays the foundation for revealing the molecular mechanisms in the formation of giant leaves in polyploids.