bluuebunny/crossref_metadata_2025 huggingface dataset:
A Triple-Band Hybridization Coherent Perfect Absorber Based on Graphene Metamaterial
Authors: Jiang Xinpeng , Zhang Zhaojian , Wen Kui , Li Guofeng , He Jie , Yang Junbo
Published: March 2020

In this paper, a triple-band hybridization coherent perfect absorber based on graphene metamaterial is proposed, which consists of graphene concentric nanorings with different sizes and a metallic mirror separated by SiO2 layer. Based on the finite-difference time-domain (FDTD) solution, triple-band coherent perfect absorption is achieved at frequencies from 0.6 THz to 1.8 THz, which results from the surface plasmon resonance hybridization. The wavelength of the absorption peak can be rapidly changed by varying the Fermi level of graphene. Most importantly, the wavelength of the absorption peak can be independently tuned by varying the Fermi level of the single graphene nanoring. Moreover, the triple hybridization perfect absorber is angle-insensitive because of the perfect symmetry structure of the graphene nanorings. Therefore, our results may widely inspire optoelectronic and micro-nano applications, such as cloaking, tunable sensor, etc.
Study on the Coupling Relationship of Low Temperature Fluidity and Oxidation Stability of Biodiesel
Authors: Lv Shuaishuai , Zhang Jiaqiao , Ni Hongjun , Wang Xingxing , Zhu Yu , Chen Lei
Published: March 2020

Low temperature fluidity and oxidation stability are important indicators for the measurement of the performance of biodiesel, which are currently two major issues in association with the use of biodiesel on diesel engines. In the current work, actors affecting the low temperature fluidity and oxidation stability of biodiesel, such as adding reagents, changing the blending ratio, were studied separately. Then, the influencing factors were comprehensively analyzed to simultaneously improve the low temperature fluidity and oxidation stability of biodiesel through adjusting the proportion of fatty acid methyl esters (FAMEs). The results show that the cold fluidity improver (CFI) exerts the greatest influence on the biodiesel blending oil B10. When the CFI is added to 0.6%, the cold filter plugging point (CFPP) of B10 is reduced to a minimum of −17 °C. Additionally, blending ratio also has a great influence on the CFPP of biodiesel blended fuel. When the amount of biodiesel added is 5%, the CFPP of biodiesel blended fuel is equivalent to the CFPP of 0 petrol diesel (0PD). When the amount of biodiesel added exceeds 50%, the oxidation induction time (OIT) of biodiesel with different blending ratios can be made greater than 6 h by adding butylated hydroxyanisole (BHA) with a ratio of 0.1%. The CFPP and OIT of the blended fuel increase with the increasing of PME addition ratio. When the blending ratio of palm oil methyl ester (PME) and rapeseed oil methyl ester (RME) is R60P40, the CFPP is 0 °C, and the OIT is 5.9 h.
Super-Gain Optical Parametric Amplification in Dielectric Micro-Resonators via BFGS Algorithm-Based Non-Linear Programming
Authors: Aşırım Özüm Emre , Kuzuoğlu Mustafa
Published: March 2020

The goal of this paper is to show that super-gain optical parametric amplification can be achieved even in a small micro-resonator using high-intensity ultrashort pump waves, provided that the frequencies of the ultrashort pulses are tuned to maximize the intracavity magnitude of the wave to be amplified, which we call the stimulus wave. In order to accomplish this, we have performed a dispersion analysis via computational modeling of the electric polarization density in terms of the non-linear electron cloud motion and we have concurrently solved the electric polarization density and the wave equation for the electric field. Based on a series of non-linear programming-integrated finite difference time-domain simulations, we have identified the optimal pump wave frequencies that simultaneously maximize the stored electric energy density and the polarization density inside a micro-resonator by using the Broyden–Fletcher–Goldfarb–Shanno (BFGS) optimization algorithm. When the intracavity energy and the polarization density (which acts as an energy coupling coefficient) are simultaneously high, an input wave can be strongly amplified by efficiently drawing energy from a highly energized cavity. Therefore, we propose that micrometer-scale achievement of super-gain optical parametric amplification is possible in a micro-resonator via high-intensity ultrashort “pump wave” pulses, by determining the optimal frequencies that concurrently maximize the stored electric energy density and the polarization density in a dielectric interaction medium.
Virtual PLC Lab Enabled Physical Layer Improvement Proposals for PRIME and G3-PLC Standards
Authors: Llano Asier , Angulo Itziar , de la Vega David , Marron Laura
Published: March 2020

Narrowband (NB) powerline communication (PLC) is extensively adopted by utilities for the communication in advanced metering infrastructure (AMI) systems. PLC technology needs to overcome channel disturbances present in certain grid segments. This study analyzes improvement proposals of the physical layer of the main narrowband PLC technologies approved by international communication organizations that are currently deployed in Europe: Powerline Intelligent Metering Evolution (PRIME) 1.3.6, PRIME 1.4, and G3-PLC, in order to improve PLC performance under channel disturbances. This thorough study is based on simulations carried out by an innovative ad hoc Virtual PLC Lab, developed by the authors, applied in replicable, fully-automated, and cost reduced test scenarios. The analysis is performed by applying standardized test methods and metrics, and by evaluating the influence of a set of representative channel disturbances defined by the European Telecommunications Standards Institute (ETSI) and selected noises generated by distributed energy resources (DER) in normal operation. PLC performance improvements in terms of equalizer curve fitting, error correction codes, and noisy subcarrier suppression mechanisms are presented. The performance gain due to each physical improvement proposal is accurately measured and compared under the same conditions in a replicable and automated test environment in order to evaluate the use of the proposals in the evolution of future PLC technologies.
A Novel T Cell-Engaging Bispecific Antibody for Treating Mesothelin-Positive Solid Tumors
Authors: Yoon Aerin , Lee Shinai , Lee Sua , Lim Sojung , Park Yong-Yea , Song Eunjung , Kim Dong-Sik , Kim Kisu , Lim Yangmi
Published: March 2020

As mesothelin is overexpressed in various types of cancer, it is an attractive target for therapeutic antibodies. T-cell bispecific antibodies bind to target cells and engage T cells via binding to CD3, resulting in target cell killing by T-cell activation. However, the affinity of the CD3-binding arm may influence CD3-mediated plasma clearance or antibody trapping in T-cell-containing tissues. This may then affect the biodistribution of bispecific antibodies. In this study, we used scFab and knob-into-hole technologies to construct novel IgG-based 1 + 1 MG1122-A and 2 + 1 MG1122-B bispecific antibodies against mesothelin and CD3ε. MG1122-B was designed to be bivalent to mesothelin and monovalent to CD3ε, using a 2 + 1 head-to-tail format. Activities of the two antibodies were evaluated in mesothelin-positive tumor cells in vitro and xenograft models in vivo. Although both antibodies exhibited target cell killing efficacy and produced regression of xenograft tumors with CD8+ T-cell infiltration, the antitumor efficacy of MG1122-B was significantly higher. MG1122-B may improve tumor targeting because of its bivalency for tumor antigen. It may also reduce systemic toxicity by limiting the activation of circulating T cells. Thus, MG1122-B may be useful for treating mesothelin-positive solid tumors.
Analyzing the Open/Deep Web to Better Understand the New/Novel Psychoactive Substances (NPS) Scenarios: Suggestions from CASSANDRA and NPS.Finder Research Projects
Authors: Schifano Fabrizio
Published: March 2020

New/novel psychoactive substances (NPS) are defined as new narcotic/psychotropic drugs which are not controlled by the United Nations’ 1961 Narcotic Drugs/1971 Psychotropic Substances conventions, but which may pose a public health threat [...]
Abnormal Emotional Processing and Emotional Experience in Patients with Peripheral Facial Nerve Paralysis: An MEG Study
Authors: Kheirkhah Mina , Brodoehl Stefan , Leistritz Lutz , Götz Theresa , Baumbach Philipp , Huonker Ralph , Witte Otto W. , Volk Gerd Fabian , Guntinas-Lichius Orlando , Klingner Carsten M.
Published: March 2020

Abnormal emotional reactions of the brain in patients with facial nerve paralysis have not yet been reported. This study aims to investigate this issue by applying a machine-learning algorithm that discriminates brain emotional activities that belong either to patients with facial nerve paralysis or to healthy controls. Beyond this, we assess an emotion rating task to determine whether there are differences in their experience of emotions. MEG signals of 17 healthy controls and 16 patients with facial nerve paralysis were recorded in response to picture stimuli in three different emotional categories (pleasant, unpleasant, and neutral). The selected machine learning technique in this study was the logistic regression with LASSO regularization. We demonstrated significant classification performances in all three emotional categories. The best classification performance was achieved considering features based on event-related fields in response to the pleasant category, with an accuracy of 0.79 (95% CI (0.70, 0.82)). We also found that patients with facial nerve paralysis rated pleasant stimuli significantly more positively than healthy controls. Our results indicate that the inability to express facial expressions due to peripheral motor paralysis of the face might cause abnormal brain emotional processing and experience of particular emotions.
The Brain Differentially Prepares Inner and Overt Speech Production: Electrophysiological and Vascular Evidence
Authors: Stephan Franziska , Saalbach Henrik , Rossi Sonja
Published: March 2020

Speech production not only relies on spoken (overt speech) but also on silent output (inner speech). Little is known about whether inner and overt speech are processed differently and which neural mechanisms are involved. By simultaneously applying electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), we tried to disentangle executive control from motor and linguistic processes. A preparation phase was introduced additionally to the examination of overt and inner speech directly during naming (i.e., speech execution). Participants completed a picture-naming paradigm in which the pure preparation phase of a subsequent speech production and the actual speech execution phase could be differentiated. fNIRS results revealed a larger activation for overt rather than inner speech at bilateral prefrontal to parietal regions during the preparation and at bilateral temporal regions during the execution phase. EEG results showed a larger negativity for inner compared to overt speech between 200 and 500 ms during the preparation phase and between 300 and 500 ms during the execution phase. Findings of the preparation phase indicated that differences between inner and overt speech are not exclusively driven by specific linguistic and motor processes but also impacted by inhibitory mechanisms. Results of the execution phase suggest that inhibitory processes operate during phonological code retrieval and encoding.
Pulling Simulations and Hydrogen Sorption Modelling on Carbon Nanotube Bundles
Authors: Gotzias Anastasios , Sapalidis Andreas
Published: March 2020

Recent progress in molecular simulation technology has developed an interest in modernizing the usual computational methods and approaches. For instance, most of the theoretical work on hydrogen adsorption on carbon nanotubes was conducted a decade ago. It should be insightful to reinvestigate the field and take advantage of code improvements and features implemented in contemporary software. One example of such features is the pulling simulation modules now available in many molecular dynamics programs. We conduct pulling simulations on pairs of carbon nanotubes and measure the inter-tube distance before they dissociate in water. We use this distance to set the interval size between adjacent nanotubes as we arrange them in bundle configurations. We consider bundles with triangular, intermediate and honeycomb patterns, and armchair nanotubes with a chiral index from n = 5 to n = 10. Then, we simulate low pressure hydrogen adsorption isotherms at 77 K, using the grand canonical Monte Carlo method. The different bundle configurations adsorb great hydrogen amounts that may exceed 2% wt at ambient pressures. The computed hydrogen capacities are considered large for physisorption on carbon nanostructures and attributed to the ultra-microporous network and extraordinary high surface area of the configured models.
Lymph Node and Bone Marrow Micrometastases Define the Prognosis of Patients with pN0 Esophageal Cancer
Authors: Karstens Karl-F. , Ghadban Tarik , Effenberger Katharina , Sauter Guido , Pantel Klaus , Izbicki Jakob R. , Vashist Yogesh , König Alexandra , Reeh Matthias
Published: March 2020

Background: Pathological routine lymph node staging is postulated to be the main oncological prognosticator in esophageal cancer (EC). However, micrometastases in lymph nodes (LNMM) and bone marrow (BNMM) are discussed as the key events in tumor recurrence. We assessed the prognostic significance of the LNMM/BNMM status in initially pN0 staged patients with curative esophagectomy. Methods: From 110 patients bone marrow aspirates and lymph node tissues were analyzed. For LNMM detection immunohistochemistry was performed using the anticytokeratin antibody AE1/AE3. To detect micrometastases in the bone marrow a staining with the pan-keratin antibody A45-B/B3 was done. Results were correlated with clinicopathologic parameters as well as recurrence and death during follow-up time. Results: Thirty-eight (34.5%) patients showed LNMM, whereas in 54 (49.1%) patients BNMM could be detected. LNMM and BNMM positive patients showed a correlation to an increased pT category (p = 0.017). Univariate and multivariate analyses revealed that the LNMM/BNMM status and especially LNMM skipping the anatomical lymph node chain were significant independent predictors of overall survival and recurrence-free survival. Conclusions: This study indicates that routine pathological staging of EC is insufficient. Micrometastases in lymph nodes and the bone marrow seem to be the main reason for tumor recurrence and they are a strong prognosticator following curative treatment of pN0 EC.
Kinetics of Prostate-Specific Antigen after Carbon Ion Radiotherapy for Prostate Cancer
Authors: Darwis Narisa Dewi Maulany , Oike Takahiro , Kawamura Hidemasa , Kawahara Masahiro , Kubo Nobuteru , Sato Hiro , Miyasaka Yuhei , Katoh Hiroyuki , Ishikawa Hitoshi , Matsui Hiroshi , Miyazawa Yoshiyuki , Ito Kazuto , Suzuki Kazuhiro , Gondhowiardjo Soehartati , Nakano Takashi , Ohno Tatsuya
Published: March 2020

This study aimed to first elucidate prostate-specific antigen (PSA) kinetics in prostate cancer patients treated with carbon ion radiotherapy (CIRT). From 2010 to 2015, 131 patients with prostate adenocarcinoma treated with CIRT (57.6 Gy relative biological effectiveness (RBE) in 16 fractions) alone were recruited. PSA was measured at 1, 2, 3, 6, 9, 12, 15, 18, 21, 24, 30, 36, 42, 48, 54, and 60 months post-CIRT. PSA bounce was defined as PSA increase over a cutoff followed by spontaneous decrease to or below the pre-bounce nadir. PSA failure was determined using the Phoenix criteria (nadir + 2.0 ng/mL). As a result, non-failure-associated temporary increase in PSA exhibited two distinct patterns, namely a classical bounce and a surge at one month. PSA bounce of ≥0.2 ng/mL was observed in 55.7% of the patients. Bounce amplitude was <2.0 ng/mL in 97.6% of cases. Bounce occurred significantly earlier than PSA failure. Younger age was a significant predictor of bounce occurrence. Bounce positivity was a significant predictor of favorable 5-year PSA failure-free survival. Meanwhile, a PSA surge of ≥0.2 ng/mL was observed in 67.9% of patients. Surge amplitude was significantly larger than bounce amplitude. Larger prostate volume was a significant predictor of PSA surge occurrence. PSA surge positivity did not significantly predict PSA failure. In summary, PSA bounce was distinguishable from PSA failure with regard to timing of occurrence and amplitude (earlier and lower for bounce, respectively). These data are useful for post-CIRT surveillance of prostate cancer patients.
Influence of the Preparation Method of Ag-K/CeO2-ZrO2-Al2O3 Catalysts on Their Structure and Activity for the Simultaneous Removal of Soot and NOx
Authors: Cooper Anna , Davies Thomas E. , Morgan David J. , Golunski Stan , Taylor Stuart H.
Published: March 2020

Ag/CeO2-ZrO2-Al2O3, a known catalyst for the simultaneous removal of NOx and soot, was modified by the addition of K, and was prepared using various techniques: wet impregnation, incipient wetness, and chemical vapor impregnation at different temperatures. The effect of the preparation method on catalyst activity was studied. It was found that catalysts prepared via wet impregnation, incipient wetness, and chemical vapor impregnation at 80 °C were able to utilize in situ formed N2O at low temperatures, to simultaneously remove NOx and soot. The difference in preparation method affected the catalyst’s ability to produce and use N2O as an oxidant for soot. The temperature at which chemical vapor impregnation was performed greatly influenced the catalyst’s ability to oxidize soot. The introduction of K to the Ag/CeO2-ZrO2-Al2O3 vastly improved the soot oxidation activity, particularly for the catalyst prepared via wet impregnation. However, the incorporation of K had an adverse effect on the reduction of NOx.
The Role of Granulocyte-Macrophage Colony-Stimulating Factor in Murine Models of Multiple Sclerosis
Authors: Monaghan Kelly L. , Wan Edwin C.K.
Published: March 2020

Multiple sclerosis (MS) is an immune-mediated disease that predominantly impacts the central nervous system (CNS). Animal models have been used to elucidate the underpinnings of MS pathology. One of the most well-studied models of MS is experimental autoimmune encephalomyelitis (EAE). This model was utilized to demonstrate that the cytokine granulocyte-macrophage colony-stimulating factor (GM-CSF) plays a critical and non-redundant role in mediating EAE pathology, making it an ideal therapeutic target. In this review, we will first explore the role that GM-CSF plays in maintaining homeostasis. This is important to consider, because any therapeutics that target GM-CSF could potentially alter these regulatory processes. We will then focus on current findings related to the function of GM-CSF signaling in EAE pathology, including the cell types that produce and respond to GM-CSF and the role of GM-CSF in both acute and chronic EAE. We will then assess the role of GM-CSF in alternative models of MS and comment on how this informs the understanding of GM-CSF signaling in the various aspects of MS immunopathology. Finally, we will examine what is currently known about GM-CSF signaling in MS, and how this has promoted clinical trials that directly target GM-CSF.
Decoding the Role of Interleukin-30 in the Crosstalk between Cancer and Myeloid Cells
Authors: Di Carlo Emma
Published: March 2020

In the last few years, a new actor hit the scene of the tumor microenvironment, the p28 subunit of interleukin (IL)-27, known as IL-30. Its molecular structure allows it to function as an autonomous cytokine and, alternatively, to pair with other subunits to form heterodimeric complexes and enables it to play different, and not fully elucidated, roles in immunity. However, data from the experimental models and clinical samples, suggest IL-30′s engagement in the relationship between cancer and myeloid cells, which fosters the tumor microenvironment and the cancer stem cell niche, boosting the disease progression. Activated myeloid cells are the primary cellular source and one of the targets of IL-30, which can also be produced by cancer cells, especially, in aggressive tumors, as observed in the breast and prostate. This review briefly reports on the immunobiology of IL-30 and related cytokines, by comparing mouse and human counterparts, and then focuses on the mechanisms whereby IL-30 amplifies intratumoral myeloid cell infiltrate and triggers a vicious cycle that worsens immunosuppression in the tumor microenvironment (TME) and constitutes a real threat for a successful immunotherapeutic strategy.
Immunotherapy, Inflammation and Colorectal Cancer
Authors: Lichtenstern Charles Robert , Ngu Rachael Katie , Shalapour Shabnam , Karin Michael
Published: March 2020

Colorectal cancer (CRC) is the third most common cancer type, and third highest in mortality rates among cancer-related deaths in the United States. Originating from intestinal epithelial cells in the colon and rectum, that are impacted by numerous factors including genetics, environment and chronic, lingering inflammation, CRC can be a problematic malignancy to treat when detected at advanced stages. Chemotherapeutic agents serve as the historical first line of defense in the treatment of metastatic CRC. In recent years, however, combinational treatment with targeted therapies, such as vascular endothelial growth factor, or epidermal growth factor receptor inhibitors, has proven to be quite effective in patients with specific CRC subtypes. While scientific and clinical advances have uncovered promising new treatment options, the five-year survival rate for metastatic CRC is still low at about 14%. Current research into the efficacy of immunotherapy, particularly immune checkpoint inhibitor therapy (ICI) in mismatch repair deficient and microsatellite instability high (dMMR–MSI-H) CRC tumors have shown promising results, but its use in other CRC subtypes has been either unsuccessful, or not extensively explored. This Review will focus on the current status of immunotherapies, including ICI, vaccination and adoptive T cell therapy (ATC) in the treatment of CRC and its potential use, not only in dMMR–MSI-H CRC, but also in mismatch repair proficient and microsatellite instability low (pMMR-MSI-L).
Modulation of the Pol II CTD Phosphorylation Code by Rac1 and Cdc42 Small GTPases in Cultured Human Cancer Cells and Its Implication for Developing a Synthetic-Lethal Cancer Therapy
Authors: Zhang Bo , Zhong Xuelin , Sauane Moira , Zhao Yihong , Zheng Zhi-Liang
Published: March 2020

Rho GTPases, including Rho, Cdc42, Rac and ROP subfamilies, are key signaling molecules in RNA polymerase II (Pol II) transcriptional control. Our prior work has shown that plant ROP and yeast Cdc42 GTPases similarly modulate Ser2 and Ser5 phosphorylation status of the C-terminal domain (CTD) of the Pol II largest subunit by regulating CTD phosphatase degradation. Here, we present genetic and pharmacological evidence showing that Cdc42 and Rac1 GTPase signaling modulates a similar CTD Ser2 and Ser5 phosphorylation code in cultured human cancer cells. While siRNA knockdown of Cdc42 and Rac1, respectively, in HeLa cells increased the level of CTD Ser phosphatases RPAP2 and FCP1, they both decreased the level of CTD kinases CDK7 and CDK13. In addition, the protein degradation inhibitor MG132 reversed the effect of THZ1, a CDK7 inhibitor which could decrease the cell number and amount of CDK7 and CDK13, accompanied by a reduction in the level of CTD Ser2 and Ser5 phosphorylation and DOCK4 and DOCK9 (the activators for Rac1 and Cdc42, respectively). Conversely, treatments of Torin1 or serum deprivation, both of which promote protein degradation, could enhance the effect of THZ1, indicating the involvement of protein degradation in controlling CDK7 and CDK13. Our results support an evolutionarily conserved signaling shortcut model linking Rho GTPases to Pol II transcription across three kingdoms, Fungi, Plantae and Animalia, and could lead to the development of a potential synthetic-lethal strategy in controlling cancer cell proliferation or death.
The G Protein-Coupled Estrogen Receptor (GPER) Expression Correlates with Pro-Metastatic Pathways in ER-Negative Breast Cancer: A Bioinformatics Analysis
Authors: Talia Marianna , De Francesco Ernestina , Rigiracciolo Damiano , Muoio Maria , Muglia Lucia , Belfiore Antonino , Maggiolini Marcello , Sims Andrew , Lappano Rosamaria
Published: March 2020

The G protein-coupled estrogen receptor (GPER, formerly known as GPR30) is a seven-transmembrane receptor that mediates estrogen signals in both normal and malignant cells. In particular, GPER has been involved in the activation of diverse signaling pathways toward transcriptional and biological responses that characterize the progression of breast cancer (BC). In this context, a correlation between GPER expression and worse clinical-pathological features of BC has been suggested, although controversial data have also been reported. In order to better assess the biological significance of GPER in the aggressive estrogen receptor (ER)-negative BC, we performed a bioinformatics analysis using the information provided by The Invasive Breast Cancer Cohort of The Cancer Genome Atlas (TCGA) project and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) datasets. Gene expression correlation and the statistical analysis were carried out with R studio base functions and the tidyverse package. Pathway enrichment analysis was evaluated with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway on the Database for Annotation, Visualization and Integrated Discovery (DAVID) website, whereas gene set enrichment analysis (GSEA) was performed with the R package phenoTest. The survival analysis was determined with the R package survivALL. Analyzing the expression data of more than 2500 primary BC, we ascertained that GPER levels are associated with pro-migratory and metastatic genes belonging to cell adhesion molecules (CAMs), extracellular matrix (ECM)-receptor interaction, and focal adhesion (FA) signaling pathways. Thereafter, evaluating the disease-free interval (DFI) in ER-negative BC patients, we found that the subjects expressing high GPER levels exhibited a shorter DFI in respect to those exhibiting low GPER levels. Overall, our results may pave the way to further dissect the network triggered by GPER in the breast malignancies lacking ER toward a better assessment of its prognostic significance and the action elicited in mediating the aggressive features of the aforementioned BC subtype.
Variability in Measured Real-World Operational Energy Use and Emission Rates of a Plug-In Hybrid Electric Vehicle
Authors: Frey H. Christopher , Zheng Xiaohui , Hu Jiangchuan
Published: March 2020

Compared to comparably sized conventional light duty gasoline vehicles (CLDGVs), plug-in hybrid electric vehicles (PHEVs) may offer benefits of improved energy economy, reduced emissions, and the flexibility to use electricity as an energy source. PHEVs operate in either charge depleting (CD) or charge sustaining (CS) mode; the engine has the ability to turn on and off; and the engine can have multiple cold starts. A method is demonstrated for quantifying the real-world activity, energy use, and emissions of PHEVs, taking into account these operational characteristics and differences in electricity generation resource mix. A 2013 Toyota Prius plug-in was measured using a portable emission measurement system. Vehicle specific power (VSP) based modal average energy use and emission rates are inferred to assess trends in energy use and emissions with respect to engine load and for comparisons of engine on versus engine off, and cold start versus hot stabilized running. The results show that, compared to CLDGVs, the PHEV operating in CD mode has improved energy efficiency and lower CO2, CO, HC, NOx, and PM2.5 emission rates for a wide range of power generation fuel mixes. However, PHEV energy use and emission rates are highly variable, with periods of relatively high on-road emission rates related to cold starts.
Application of a Model-Based Controller for Improving Internal Combustion Engines Fuel Economy
Authors: Castiglione Teresa , Morrone Pietropaolo , Falbo Luigi , Perrone Diego , Bova Sergio
Published: March 2020

Improvements in internal combustion engine efficiency can be achieved with proper thermal management. In this work, a simulation tool for the preliminary analysis of the engine cooling control is developed and a model-based controller, which enforces the coolant flow rate by means of an electrically driven pump is presented. The controller optimizes the coolant flow rate under each engine operating condition to guarantee that the engine temperatures and the coolant boiling levels are kept inside prescribed constraints, which guarantees efficient and safe engine operation. The methodology is validated at the experimental test rig. Several control strategies are analyzed during a standard homologation cycle and a comparison of the proposed methodology and the adoption of the standard belt-driven pump is provided. The results show that, according to the control strategy requirements, a fuel consumption reduction of up to about 8% with respect to the traditional cooling system can be achieved over a whole driving cycle. This proves that the proposed methodology is a useful tool for appropriately cooling the engine under the whole range of possible operating conditions.
Experimentally Measured Thermal Masses of Adsorption Heat Exchangers
Authors: Gluesenkamp Kyle R. , Frazzica Andrea , Velte Andreas , Metcalf Steven , Yang Zhiyao , Rouhani Mina , Blackman Corey , Qu Ming , Laurenz Eric , Rivero-Pacho Angeles , Hinmers Sam , Critoph Robert , Bahrami Majid , Füldner Gerrit , Hallin Ingemar
Published: March 2020

The thermal masses of components influence the performance of many adsorption heat pump systems. However, typically when experimental adsorption systems are reported, data on thermal mass are missing or incomplete. This work provides original measurements of the thermal masses for experimental sorption heat exchanger hardware. Much of this hardware was previously reported in the literature, but without detailed thermal mass data. The data reported in this work are the first values reported in the literature to thoroughly account for all thermal masses, including heat transfer fluid. The impact of thermal mass on system performance is also discussed, with detailed calculation left for future work. The degree to which heat transfer fluid contributes to overall effective thermal mass is also discussed, with detailed calculation left for future work. This work provides a framework for future reporting of experimental thermal masses. The utilization of this framework will enrich the data available for model validation and provide a more thorough accounting of adsorption heat pumps.
Adaptive Droop Gain-Based Event-Triggered Consensus Reactive Power Sharing in Microgrids
Authors: Xiong Linyun , Li Penghan , Wang Chao , Huang Sunhua , Wang Jie
Published: March 2020

This paper proposes an adaptive droop gain-based consensus approach for reactive power sharing in microgrids (MGs) with the event triggered communication protocol (ETCP). A multi-agent system-based network is constructed to establish the communication with distributed generators (DGs) in MGs. An ETCP is proposed to reduce the communication among agents to save resources and improve system reliability, as the communication is only needed when the event triggered condition is fulfilled. A stability analysis is conducted to guarantee the existence of the equilibrium point and the freeness of the Zeno solution. Moreover, an adaptive droop gain is designed to reduce the impact of imbalanced feeder impedances. Four case studies are conducted to verify the effectiveness and performance of the proposed method. The simulation results show that the ETCP-based approach is capable of achieving power sharing consensus, communication reduction and shifting the information exchange mode based on the operation scenarios.
Development and Experimental Validation of a Supercapacitor Frequency Domain Model for Industrial Energy Applications Considering Dynamic Behaviour at High Frequencies
Authors: Navarro Gustavo , Nájera Jorge , Torres Jorge , Blanco Marcos , Santos Miguel , Lafoz Marcos
Published: March 2020

Supercapacitors, one of the most promising energy storage technologies for high power density industrial applications, exchange the energy mostly through power electronic converters, operating under high frequency components due to the commutation. The high frequency produces important effects on the performance of the supercapacitors in relation to their capacitance, inductance and internal resistance (ESR). These parameters are fundamental to evaluate the efficiency of this energy storage system. The aim of the paper is to obtain an accurate model of two supercapacitors connected in series (functional and extrapolated unit) to represent the frequency effects for a wide range of frequencies. The methodology is based on the definition of an appropriate equivalent electric circuit with voltage dependance, obtaining their parameters from experimental tests, carried out by means of electrochemical impedance spectroscopy (EIS) and the use of specific software tools such as EC-Lab® and Statgraphics Centurion®. The paper concludes with a model which reproduces with accuracy both the frequency response of the model BCAP3000 supercapacitors, provided by the manufacturer, and the experimental results obtained by the authors.
Logistics Design for Mobile Battery Energy Storage Systems
Authors: Hayajneh Hassan , Zhang Xuewei
Published: March 2020

Currently, there are three major barriers toward a greener energy landscape in the future: (a) Curtailed grid integration of energy from renewable sources like wind and solar; (b) The low investment attractiveness of large-scale battery energy storage systems; and, (c) Constraints from the existing electric infrastructure on the development of charging station networks to meet the increasing electrical transportation demands. A new conceptual design of mobile battery energy storage systems has been proposed in recent studies to reduce the curtailment of renewable energy while limiting the public costs of battery energy storage systems. This work designs a logistics system in which electric semi-trucks ship batteries between the battery energy storage system and electric vehicle charging stations, enabling the planning and operation of power grid independent electric vehicle charging station networks. This solution could be viable in many regions in the United States (e.g., Texas) where there are plenty of renewable resources and little congestion pressure on the road networks. With Corpus Christi, Texas and the neighboring Chapman Ranch wind farm as the test case, this work implement such a design and analyze its performance based on the simulation of its operational processes. Further, we formulate an optimization problem to find design parameters that minimize the total costs. The main design parameters include the number of trucks and batteries. The results in this work, although preliminary, will be instrumental for potential stakeholders to make investment or policy decisions.
Machine Learning for Benchmarking Models of Heating Energy Demand of Houses in Northern Canada
Authors: Bezyan Behrad , Zmeureanu Radu
Published: March 2020

In most cases, the benchmarking models of energy use in houses are developed based on current and past data, and they continue to be used without any update. This paper proposes the method of retraining of benchmarking models by applying machine learning techniques when new measurements are made available. The method uses as a case study the measurements of heating energy demand from two semi-detached houses of Northern Canada. The results of the prediction of heating energy demand using static or augmented window techniques are compared with measurements. The daily energy signature is used as a benchmarking model due to its simplicity and performance. However, the proposed retraining method can be applied to any form of benchmarking model. The method should be applied in all possible situations, and be an integral part of intelligent building automation and control systems (BACS) for the ongoing commissioning for building energy-related applications.
Development of Vacuum Insulation Panels with Utilization of Organic By-Products
Authors: Zach Jiří , Novák Vítězslav , Peterková Jitka , Bubeník Jan
Published: March 2020

The need for the development of new, advanced building materials increases every year, especially due to the necessary diminution of energy performance for building structures and for building production itself (including the production of building materials). Along with the energy performance problems in construction, the issue of CO2 emission associated with building and the production of building materials is also important. In the field of advanced thermal insulation materials, vacuum insulation panels (VIPs) give the best results. However, their high-energy performance and material consumption present a problem. This work represents an initial part of the development of alternative insulators, based on agricultural and textile industry waste usable in the production of VIP. This article recapitulates basic knowledge regarding key thermal insulation properties of developed insulators and their fire reactions, which impact possible usage in building structures.
Micro- and Macroscale Consequences of Interactions between CO2 and Shale Rocks
Authors: Bhuiyan Mohammad H. , Agofack Nicolaine , Gawel Kamila M. , Cerasi Pierre R.
Published: March 2020

In carbon storage activities, and in shale oil and gas extraction (SOGE) with carbon dioxide (CO2) as stimulation fluid, CO2 comes into contact with shale rock and its pore fluid. As a reactive fluid, the injected CO2 displays a large potential to modify the shale’s chemical, physical, and mechanical properties, which need to be well studied and documented. The state of the art on shale–CO2 interactions published in several review articles does not exhaust all aspects of these interactions, such as changes in the mechanical, petrophysical, or petrochemical properties of shales. This review paper presents a characterization of shale rocks and reviews their possible interaction mechanisms with different phases of CO2. The effects of these interactions on petrophysical, chemical and mechanical properties are highlighted. In addition, a novel experimental approach is presented, developed and used by our team to investigate mechanical properties by exposing shale to different saturation fluids under controlled temperatures and pressures, without modifying the test exposure conditions prior to mechanical and acoustic measurements. This paper also underlines the major knowledge gaps that need to be filled in order to improve the safety and efficiency of SOGE and CO2 storage.
Thickness Distribution Prediction for Tectonically Deformed Coal with a Deep Belief Network: A Case Study
Authors: Wang Xin , Chen Tongjun , Xu Hui
Published: March 2020

Thickness of tectonically deformed coal (TDC) has positive correlations with the susceptible gas outbursts in coal mines. To predict the TDC thickness of the coalbed, we proposed a prediction method using seismic attributes based on the deep belief network (DBN) and dimensionality reduction. Firstly, we built a DBN prediction model using the extracted attributes from a synthetic seismic section. Next, we transformed the possibly correlated seismic attributes into principal components through principal components analysis. Then, we compared the true TDC thickness with the predicted TDC thicknesses to evaluate the prediction accuracy of different models, i.e., a DBN model, a support vector machine model, and an extreme learning machine model. Finally, we used the DBN model to predict the TDC thickness of coalbed No. 8 in an operational coal mine based on synthetic experiments. Our studies showed that the predicted distribution of TDC thickness followed the regional characteristics of TDC development well and was positively correlated with the burial depth, coalbed thickness, and tectonic development. In summary, the proposed DBN model provided a reliable method for predicting TDC thickness and reducing gas outbursts in coal mine operations.
District Heating Tariffs, Economic Optimisation and Local Strategies during Radical Technological Change
Authors: Djørup Søren , Sperling Karl , Nielsen Steffen , Østergaard Poul Alborg , Zinck Thellufsen Jakob , Sorknæs Peter , Lund Henrik , Drysdale David
Published: March 2020

This paper addresses economic aspects of heat savings in the context of strategic heat planning. The analysis uses the city of Aalborg, Denmark, as a case where municipalisation through a recent acquisition of a coal-fired cogeneration of heat and power (CHP) plant has made an update of a municipal strategic energy plan necessary. Combining datasets on buildings and insulation techniques with economic methods, we investigate how the local district heating tariff can be adapted to improve the conditions for heat savings and support the transition to lower supply temperatures in line with the requirements of future fourth generation district heating systems. The paper concludes that implementing a fully variable heat tariff scheme improves the financial incentive for heat savings, while also making the system development less vulnerable to fluctuations and shortages in capital markets. The paper supplements existing literature on heat savings with novelty in its approach and in its systematic investigation of the interplay between tariff policies and interest rates.
Practical Implementation of Adaptive SRF-PLL for Three-Phase Inverters Based on Sensitivity Function and Real-Time Grid-Impedance Measurements
Authors: Luhtala Roni , Alenius Henrik , Roinila Tomi
Published: March 2020

Rapidly increasing demand for renewable energy has created a need for the photovoltaic and wind farms to be placed in various locations that have diverse and possibly time-variant grid conditions. A mismatch between the grid impedance and output admittance of an inverter causes impedance-based stability issues, which appear as power quality problems and poor transient performance. Grid synchronization with phase-locked loop (PLL) introduces a negative-resistance-like behavior to inverter output admittance. High control bandwidth of the PLL makes the system sensitive to impedance-based stability issues when the inverter is connected to a weak grid that has high impedance. However, very conservative tunings lead to overly damped dynamic responses in strong grids, where the control performance and power quality can be improved by applying higher PLL control bandwidths. Continuous evaluation of grid conditions makes it possible to avoid the risk of instability and poor dynamic responses, as the inverter output admittance can be re-shaped online to continuously match the grid conditions. The present work proposes method for adaptive control of the PLL based on the real-time measurements of the grid impedance, applying pseudo-random binary sequence (PRBS) injections. The method limits the PLL bandwidth in weak grids to avoid stability issues and increases the control bandwidth in strong grids to improve voltage-tracking, and thus overall control performance. The method is verified through simulations and experimental laboratory tests in a kW-scale system. The results show that optimizing the PLL bandwidth with respect to the grid conditions is highly beneficial for system performance and stability.
Reliability Evaluation for Aviation Electric Power System in Consideration of Uncertainty
Authors: Wang Yao , Gao Xinqin , Cai Yuanfeng , Yang Mingshun , Li Shujuan , Li Yan
Published: March 2020

With the rapid development of more electric aircraft (MEA) in recent years, the aviation electric power system (AEPS) has played an increasingly important role in safe flight. However, as a highly reliable system, because of its complicated flight conditions and architecture, it often proves significant uncertainty in its failure occurrence and consequence. Thus, more and more stakeholders, e.g., passengers, aviation administration departments, are dissatisfied with the traditional system reliability analysis, in which failure uncertainty is not considered and system reliability probability is a constant value at a given time. To overcome this disadvantage, we propose a new methodology in the AEPS reliability evaluation. First, we perform a random sampling from the probability distributions of components’ failure rates and compute the system reliability at each sample point; after that, we use variance, confidence interval, and probability density function to quantify the uncertainty of system reliability. Finally, we perform the new method on a series–parallel system and an AEPS. The results show that the power supply reliability of AEPS is uncertain and the uncertainty varies with system time even though the uncertainty of each component’s failure is quite small; therefore it is necessary to quantify system uncertainty for safer flight, and our proposed method could be an effective way to accomplish this quantization task.
Hybrid Control Strategy of MPC and DBC to Achieve a Fixed Frequency and Superior Robustness
Authors: Zhang Yuhan , Du Guiping , Li Jiajian , Lei Yanxiong
Published: March 2020

In this paper, a hybrid control strategy for power converters, based on improved deadbeat control (DBC) and improved finite control set model predictive control (MPC), is proposed. The presented control strategy employs a switched method to achieve a fixed switching frequency while maintaining a fast transient time. Moreover, the proposal incorporates error correction to achieve superior robustness. A prototype of a single-phase voltage source rectifier is established to verify the performance of the proposal. The comparative results with conventional MPC are given and illustrate the merits of the proposed control method.
The Effect of Air leakage through the Air Cavities of Building Walls on Mold Growth Risks
Authors: Li Yonghui , Dang Xinyuan , Xia Changchang , Ma Yan , Ogura Daisuke , Hokoi Shuichi
Published: March 2020

Mold growth poses a high risk to a large number of existing buildings and their users. Air leakage through the air cavities of the building walls, herein gaps between walls and air conditioner pipes penetrating the walls, may increase the risks of interstitial condensation, mold growth and other moisture-related problems. In order to quantify the mold growth risks due to air leakage through air cavity, an office room in a historical masonry building in Nanjing, China, was selected, and its indoor environment has been studied. Fungi colonization can be seen on the surface of air conditioner pipes in the interior side near air cavity of the wall. Hygrothermometers and thermocouples logged interior and exterior temperature and relative humidity from June 2018 to January 2020. The measured data show that in summer the outdoor humidity remained much higher than that of the room, while the temperature near the air cavity stays lower than those of the other parts in the room. Hot and humid outdoor air may condense on the cold wall surface near an air cavity. A two-dimensional hygrothermal simulation was made. Air leakage through the air cavities of walls proved to be a crucial factor for mold growth.