bluuebunny/crossref_metadata_2025 huggingface dataset:
Potential Circulating Biomarkers of Recurrence after Hepatic Resection or Liver Transplantation in Hepatocellular Carcinoma Patients
Authors: Duda Dan G. , Dima Simona O. , Cucu Dana , Sorop Andrei , Klein Sebastian , Ancukiewicz Marek , Kitahara Shuji , Iacob Speranta , Bacalbasa Nicolae , Tomescu Dana , Herlea Vlad , Tanase Cristiana , Croitoru Adina , Popescu Irinel
Published: May 2020

Background: Improving surgical outcomes in hepatocellular carcinoma (HCC) patients would greatly benefit from biomarkers. Angiogenesis and inflammation are hallmarks of HCC progression and therapeutic targets. Methods: We retrospectively evaluated preoperative clinical variables and circulating (plasma) biomarkers of angiogenesis and inflammation in a cohort of HCC patients who underwent liver resection (LR) or transplantation (LT). Biomarker correlation with outcomes—freedom of liver recurrence (FLR), disease-free survival (DFS) and overall survival (OS)—was tested using univariate and multivariate Cox regression analyses. Results: Survival outcomes associated with sVEGFR1, VEGF and VEGF-C in LT patients and with IL-10 in LR patients. Moreover, in LT patients within Milan criteria, higher plasma VEGF and sVEGFR1 were associated with worse outcomes, while in those outside Milan criteria lower plasma VEGF-C associated with better outcomes. Multivariate analysis indicated that adding plasma VEGF or VEGF-C to a predictive model including Milan criteria and AFP improved prediction of DFS and OS (all p < 0.05). Conclusion: Survival outcomes after LR or LT differentially associated with angiogenic and inflammatory biomarkers. High plasma VEGF correlated with poorer prognosis within Milan criteria while low plasma VEGF-C associated with better prognosis outside Milan criteria. These candidate biomarkers should be further validated to improve patient stratification.
Oxidative Dehydrogenation of Methane When Using TiO2- or WO3-Doped Sm2O3 in the Presence of Active Oxygen Excited with UV-LED
Authors: Sugiyama Shigeru , Hayashi Yasunori , Okitsu Ikumi , Shimoda Naohiro , Katoh Masahiro , Furube Akihiro , Kato Yuki , Ninomiya Wataru
Published: May 2020

There are active oxygen species that contribute to oxidative coupling or the partial oxidation during the oxidative dehydrogenation of methane when using solid oxide catalysts, and those species have not been definitively identified. In the present study, we clarify which of the active oxygen species affect the oxidative dehydrogenation of methane by employing photo-catalysts such as TiO2 or WO3, which generate active oxygen from UV-LED irradiation conditions under an oxygen flow. These photo-catalysts were studied in combination with Sm2O3, which is a methane oxidation coupling catalyst. For this purpose, we constructed a reaction system that could directly irradiate UV-LED to a solid catalyst via a normal fixed-bed continuous-flow reactor operated at atmospheric pressure. Binary catalysts prepared from TiO2 or WO3 were either supported on or kneaded with Sm2O3 in the present study. UV-LED irradiation clearly improved the partial oxidation from methane to CO and/or slightly improved the oxidative coupling route from methane to ethylene when binary catalysts consisting of Sm2O3 and TiO2 are used, while negligible UV-LED effects were detected when using Sm2O3 and WO3. These results indicate that with UV-LED irradiation the active oxygen of O2− from TiO2 certainly contributes to the activation of methane during the oxidative dehydrogenation of methane when using Sm2O3, while the active oxygen of H2O2 from WO3 under the same conditions afforded only negligible effects on the activation of methane.
Focus on the Role of Klotho Protein in Neuro-Immune Interactions in HT-22 Cells Upon LPS Stimulation
Authors: Rusinek Kinga , Sołek Przemysław , Tabęcka-Łonczyńska Anna , Koziorowski Marek , Mytych Jennifer
Published: May 2020

Neuroinflammation is defined as the activation of the brain’s innate immune system in response to an inflammatory challenge and is considered to be a prominent feature of neurodegenerative diseases. The contribution of overactivated neuroglial cells to neuroinflammation and neurodegenerative disorders is well documented, however, the role of hippocampal neurons in the neuroinflammatory process remains fragmentary. In this study, we show for the first time, that klotho acts as a signal transducer between pro-survival and pro-apoptotic crosstalk mediated by ER stress in HT-22 hippocampal neuronal cells during LPS challenge. In control HT-22 cells, LPS treatment results in activation of the IRE1α-p38 MAPK pathway leading to increased secretion of anti-inflammatory IL-10, and thus, providing adaptation mechanism. On the other hand, in klotho-deficient HT-22 cells, LPS induces oxi-nitrosative stress and genomic instability associated with telomere dysfunctions leading to p53/p21-mediated cell cycle arrest and, in consequence, to ER stress, inflammation as well as of apoptotic cell death. Therefore, these results indicate that klotho serves as a part of the cellular defense mechanism engaged in the protection of neuronal cells against LPS-mediated neuroinflammation, emerging issues linked with neurodegenerative disorders.
Fractionation-Dependent Radiosensitization by Molecular Targeting of Nek1
Authors: Freund Isabel , Hehlgans Stephanie , Martin Daniel , Ensminger Michael , Fokas Emmanouil , Rödel Claus , Löbrich Markus , Rödel Franz
Published: May 2020

NIMA (never-in-mitosis gene A)-related kinase 1 (Nek1) is shown to impact on different cellular pathways such as DNA repair, checkpoint activation, and apoptosis. Its role as a molecular target for radiation sensitization of malignant cells, however, remains elusive. Stably transduced doxycycline (Dox)-inducible Nek1 shRNA HeLa cervix and siRNA-transfected HCT-15 colorectal carcinoma cells were irradiated in vitro and 3D clonogenic radiation survival, residual DNA damage, cell cycle distribution, and apoptosis were analyzed. Nek1 knockdown (KD) sensitized both cell lines to ionizing radiation following a single dose irradiation and more pronounced in combination with a 6 h fractionation (3 × 2 Gy) regime. For preclinical analyses we focused on cervical cancer. Nek1 shRNA HeLa cells were grafted into NOD/SCID/IL-2Rγc−/− (NSG) mice and Nek1 KD was induced by Dox-infused drinking water resulting in a significant cytostatic effect if combined with a 6 h fractionation (3 × 2 Gy) regime. In addition, we correlated Nek1 expression in biopsies of patients with cervical cancer with histopathological parameters and clinical follow-up. Our results indicate that elevated levels of Nek1 were associated with an increased rate of local or distant failure, as well as with impaired cancer-specific and overall survival in univariate analyses and for most endpoints in multivariable analyses. Finally, findings from The Cancer Genome Atlas (TCGA) validation cohort confirmed a significant association of high Nek1 expression with a reduced disease-free survival. In conclusion, we consider Nek1 to represent a novel biomarker and potential therapeutic target for drug development in the context of optimized fractionation intervals.
Anxiety and Depression Are Related to Higher Activity of Sphingolipid Metabolizing Enzymes in the Rat Brain
Authors: Zoicas Iulia , Mühle Christiane , Schmidtner Anna K. , Gulbins Erich , Neumann Inga D. , Kornhuber Johannes
Published: May 2020

Changes in sphingolipid metabolism have been suggested to contribute to the pathophysiology of major depression. In this study, we investigated the activity of acid and neutral sphingomyelinases (ASM, NSM) and ceramidases (AC, NC), respectively, in twelve brain regions of female rats selectively bred for high (HAB) versus low (LAB) anxiety-like behavior. Concomitant with their highly anxious and depressive-like phenotype, HAB rats showed increased activity of ASM and NSM as well as of AC and NC in multiple brain regions associated with anxiety- and depressive-like behavior, including the lateral septum, hypothalamus, ventral hippocampus, ventral and dorsal mesencephalon. Strong correlations between anxiety-like behavior and ASM activity were found in female HAB rats in the amygdala, ventral hippocampus and dorsal mesencephalon, whereas NSM activity correlated with anxiety levels in the dorsal mesencephalon. These results provide novel information about the sphingolipid metabolism, especially about the sphingomyelinases and ceramidases, in major depression and comorbid anxiety.
Circular RNA in Diseased Heart
Authors: Wang Ying , Liu Bin
Published: May 2020

Heart disease remains the leading cause of death globally and leads to tremendous socio-economic burden. Despite advances in the field of cardiovascular research, novel theranostics are still in urgent need. Remarkable progress has been made in understanding aberrant protein interactions and signaling pathways in the diseased heart, but less is known regarding epigenetic regulation. Non-coding RNAs have emerged as important regulators of cardiac function and have been implicated in disease. While significant progress has been made in understanding the roles of microRNAs and long non-coding RNAs, the functional roles of circular RNAs are less explored. Recent studies have provided ample evidence supporting their roles in multiple physiological processes including regulating the function of the heart. Compared with other RNAs, circular RNAs exhibit higher stability and more versatile functional modes: including sponging microRNAs, scaffolding proteins, regulating transcription, and even encoding small regulatory peptides. These characteristics make circular RNAs promising candidates for the development of diagnostic tools and therapies for heart disease. In this review, we will discuss the biogenesis of circular RNAs and provide an update of their functional implications in heart disease, with an emphasis on heart failure and arrhythmias.
Allogeneic ADSCs Induce the Production of Alloreactive Memory-CD8 T Cells through HLA-ABC Antigens
Authors: Chang Sung-Ho , Kim Hyun Je , Park Chung-Gyu
Published: May 2020

We investigated the immunogenicity of allogeneic human adipose-derived mesenchymal stem cells (ADSCs) through the production of alloreactive-CD8 T and -memory CD8 T cells, based on their human leukocyte antigen (HLA) expression. In surface antigen analysis, ADSCs do not express co-stimulatory molecules, but expresses HLA-ABC, which is further increased by exposure to the pro-inflammatory cytokines as well as IFN-γ alone. For immunogenicity analysis, allogeneic ADSCs cultured in xenofree medium (XF-ADSCs) were incubated with the recipient immune cells for allogeneic–antigen stimulation. As a result, XF-ADSCs induced IFN-γ and IL-17A release by alloreactive-CD8 T cells and the production of alloreactive-CD8 T cell through a direct pathway, although they have immunomodulatory activity. In the analysis of alloreactive memory CD8 T cells, XF-ADSCs also significantly induced the production of CFSE-low-CD8 TEM and -CD8 TCM cells. However, HLA-blocking antibodies significantly inhibited the production of CFSE-low memory-CD8 T cells, indicating that HLAs are the main antigens responsible for the development of allogeneic ADSCs’ immunogenicity. These results suggested that HLA surface antigens expressed in allogeneic MSCs should be solved in order to address concerns related to the immunogenicity problem.
Thermal Initiators as Additives for Photopolymerization of Methacrylates upon Blue Light
Authors: Bonardi Aude-Héloise , Zahouily Soraya , Dietlin Céline , Graff Bernadette , Dumur Frédéric , Ibrahim-Ouali Malika , Gigmes Didier , Lalevée Jacques
Published: May 2020

Free radical polymerization is often performed by thermal initiation but also more and more by light-assisted polymerization processes. This second approach allows the polymerization to be carried out under mild conditions (under air, upon blue light exposure, under low light intensity). The aim and the originality of the present paper is to perform photopolymerization in the presence of a thermal initiator, i.e., we can take advantage of the exothermicity of the photopolymerization process to decompose the thermal initiator, leading to enhanced polymerization rates. The performance of the photoinitiating system is discussed in the present study based on real-time Fourier-transform infrared spectroscopy measurements (following the C=C bond content evolution vs. time) and by thermal imaging experiments. Mechanisms of the new system proposed in this work are also fully detailed using cyclic voltammetry, electron spin resonance (ESR) spin trapping, and UV-visible absorption properties.
Determination of the Complex Dielectric Function of Ion-Implanted Amorphous Germanium by Spectroscopic Ellipsometry
Authors: Lohner Tivadar , Szilágyi Edit , Zolnai Zsolt , Németh Attila , Fogarassy Zsolt , Illés Levente , Kótai Endre , Petrik Peter , Fried Miklós
Published: May 2020

Accurate reference dielectric functions play an important role in the research and development of optical materials. Libraries of such data are required in many applications in which amorphous semiconductors are gaining increasing interest, such as in integrated optics, optoelectronics or photovoltaics. The preparation of materials of high optical quality in a reproducible way is crucial in device fabrication. In this work, amorphous Ge (a-Ge) was created in single-crystalline Ge by ion implantation. It was shown that high optical density is available when implanting low-mass Al ions using a dual-energy approach. The optical properties were measured by multiple angle of incidence spectroscopic ellipsometry identifying the Cody-Lorentz dispersion model as the most suitable, that was capable of describing the dielectric function by a few parameters in the wavelength range from 210 to 1690 nm. The results of the optical measurements were consistent with the high material quality revealed by complementary Rutherford backscattering spectrometry and cross-sectional electron microscopy measurements, including the agreement of the layer thickness within experimental uncertainty.
Yttrium Oxyfluoride Coatings Deposited by Suspension Plasma Spraying Using Coaxial Feeding
Authors: Lee Jaehoo , Lee Seungjun , Han Heung Nam , Kim Woongsik , Hwang Nong-Moon
Published: May 2020

The recently discovered yttrium oxyfluoride (YOF) coating has been found to be a highly promising plasma-resistant material which can be coated onto the inner wall of the dry etching chambers used in the manufacturing of the three-dimensional stacking circuits of semiconductors, such as vertical NAND flash memory. Here, the coating behavior of the YOF coating which was deposited by suspension plasma spraying was investigated using a high-output coaxial feeding method. Both the deposition rate and density of YOF coatings increased with the plasma power, which was determined by the gas ratio of Ar/H2/N2 and the arc current. The coating thicknesses were 58 ± 3.4, 25.8 ± 2.1, 5.6 ± 0.6, and 0.93 ± 0.4 µm at plasma powers of 112, 83, 67, and 59 kW, respectively, for 20 scans with a feeding rate of the suspension at 0.045 standard liters per minute (slm). The porosities were 0.15% ± 0.01%, 0.25% ± 0.01%, and 5.50% ± 0.40% at corresponding plasma powers of 112, 83, and 67 kW. High-resolution X-ray diffraction (HRXRD) shows that the major and minor peaks of the coatings which were deposited at 112 kW stem from trigonal YOF and cubic Y2O3, respectively. Increasing the flow rate of the atomizing gas from 15 slm to 30 slm decreased the porosity of the YOF coating from 0.22% ± 0.03% to 0.07% ± 0.03%. The Vickers hardness of the YOF coating containing some Y2O3 deposited at 112 kW was 550 ± 70 HV.
Standartox: Standardizing Toxicity Data
Authors: Scharmüller Andreas , Schreiner Verena C. , Schäfer Ralf B.
Published: May 2020

An increasing number of chemicals such as pharmaceuticals, pesticides and synthetic hormones are in daily use all over the world. In the environment, chemicals can adversely affect populations and communities and in turn related ecosystem functions. To evaluate the risks from chemicals for ecosystems, data on their toxicity, which are typically produced in standardized ecotoxicological laboratory tests, is required. The results from ecotoxicological tests are compiled in (meta-)databases such as the United States Environmental Protection Agency (EPA) ECOTOXicology Knowledgebase (ECOTOX). However, for many chemicals, multiple ecotoxicity data are available for the same test organism. These can vary strongly, thereby causing uncertainty of related analyses. Given that most current databases lack aggregation steps or are confined to specific chemicals, we developed Standartox, a tool and database that continuously incorporates the ever-growing number of test results in an automated process workflow that ultimately leads to a single aggregated data point for a specific chemical-organism test combination, representing the toxicity of a chemical. Standartox can be accessed through a web application and an R package.
Urinary Extracellular Vesicles as Biomarkers of Kidney Disease: From Diagnostics to Therapeutics
Authors: Sun In O. , Lerman Lilach O.
Published: May 2020

Cell-derived extracellular vesicles (EVs) can be isolated from various body fluids, including urine. Urinary EVs have gained important recognition as potential diagnostic biomarkers in renal disease since their cargo includes nucleic acids, proteins, and other cellular components, which likely mirror the physiological and possibly pathophysiological state of cells along the nephron. Accumulating evidence highlights the feasibility of using EVs as biomarkers for diagnostic, prognostic, and therapeutic purposes in several forms of renal disease, such as acute kidney injury, glomerulonephritis, and renal transplantation. Additionally, exogenous delivery of EVs released in vitro by cells in culture may have salutary benefits for renal diseases. In this review, we introduce recent studies that attempt to identify urinary EVs as candidate biomarkers for human kidney diseases and consider their potential implication as a therapeutic option in key kidney diseases.
Biomarkers of Muscle Metabolism in Peripheral Artery Disease: A Dynamic NIRS-Assisted Study to Detect Adaptations Following Revascularization and Exercise Training
Authors: Manfredini Fabio , Lamberti Nicola , Ficarra Valentina , Tsolaki Elpiniki , Straudi Sofia , Zamboni Paolo , Basaglia Nino , Gasbarro Vincenzo
Published: May 2020

We assessed whether muscle metabolism biomarkers (MMb) identified by near-infrared spectroscopy (NIRS) are valid for determining adaptations following revascularization or exercise training in peripheral artery disease (PAD). Eighteen patients (males n = 13; 69 ± 7 years) were randomized to receive revascularization (Rev = 6) or pain-free home-based exercise (Ex = 12). MMb were safely collected via a NIRS-assisted treadmill test as area-under-curve for the spectra of oxygenated (-oxy), deoxygenated (-deoxy), differential (-diff) and total (-tot) hemoglobin traces. MMb, ankle–brachial index (ABI), pain-free (PFWD) and 6-min (6MWD) walking distances were assessed at baseline and after four months. MMb were correlated at baseline with ABI (MMb-oxy r = 0.46) and 6MWD (MMb-tot r = 0.51). After treatments, MMb-oxy showed an expected increase, which was more relevant for Rev group than the Ex (56% vs. 20%), with trends towards normalization for the other MMb. These changes were significantly correlated with variations in ABI (MMb-oxy r = 0.71; p = 0.002) and 6MWD (MMb-tot r = 0.58; p = 0.003). The MMb-diff in Rev group and MMb-deoxy in Ex group at baseline predicted clinical outcomes being correlated with PFWD improvements after 4-month (r = −0.94; p = 0.005 and r = −0.57; p = 0.05, respectively). A noninvasive NIRS-based test, feasible in a clinical setting, identified muscle metabolism biomarkers in PAD. The novel MMb were associated with validated outcome measures, selectively modified after different interventions and able to predict long-term functional improvements after surgery or exercise training.
Current Data Regarding the Relationship between Type 2 Diabetes Mellitus and Cardiovascular Risk Factors
Authors: Vesa Cosmin Mihai , Popa Loredana , Popa Amorin Remus , Rus Marius , Zaha Andreea Atena , Bungau Simona , Tit Delia Mirela , Corb Aron Raluca Anca , Zaha Dana Carmen
Published: May 2020

Reducing cardiovascular risk (CVR) is the main focus of diabetes mellitus (DM) management nowadays. Complex pathogenic mechanisms that are the subject of this review lead to early and severe atherosclerosis in DM patients. Although it is not a cardiovascular disease equivalent at the moment of diagnosis, DM subjects are affected by numerous cardiovascular complications, such as acute coronary syndrome, stroke, or peripheral artery disease, as the disease duration increases. Therefore, early therapeutic intervention is mandatory and recent guidelines focus on intensive CVR factor management: hyperglycaemia, hypertension, and dyslipidaemia. Most important, the appearance of oral or injectable antidiabetic medication such as SGLT-2 inhibitors or GLP-1 agonists has proven that an antidiabetic drug not only reduces glycaemia, but also reduces CVR by complex mechanisms. A profound understanding of intimate mechanisms that generate atherosclerosis in DM and ways to inhibit or delay them are of the utmost importance in a society where cardiovascular morbidity and mortality are predominant.
Goal-Directed Planning for Habituated Agents by Active Inference Using a Variational Recurrent Neural Network
Authors: Matsumoto Takazumi , Tani Jun
Published: May 2020

It is crucial to ask how agents can achieve goals by generating action plans using only partial models of the world acquired through habituated sensory-motor experiences. Although many existing robotics studies use a forward model framework, there are generalization issues with high degrees of freedom. The current study shows that the predictive coding (PC) and active inference (AIF) frameworks, which employ a generative model, can develop better generalization by learning a prior distribution in a low dimensional latent state space representing probabilistic structures extracted from well habituated sensory-motor trajectories. In our proposed model, learning is carried out by inferring optimal latent variables as well as synaptic weights for maximizing the evidence lower bound, while goal-directed planning is accomplished by inferring latent variables for maximizing the estimated lower bound. Our proposed model was evaluated with both simple and complex robotic tasks in simulation, which demonstrated sufficient generalization in learning with limited training data by setting an intermediate value for a regularization coefficient. Furthermore, comparative simulation results show that the proposed model outperforms a conventional forward model in goal-directed planning, due to the learned prior confining the search of motor plans within the range of habituated trajectories.
Optimal Design of Aperiodic Reconfigurable Antenna Array Suitable for Broadcasting Applications
Authors: Gravas Ioannis P. , Zaharis Zaharias D. , Lazaridis Pavlos I. , Yioultsis Traianos V. , Kantartzis Nikolaos V. , Antonopoulos Christos S. , Chochliouros Ioannis P. , Xenos Thomas D.
Published: May 2020

An aperiodic reconfigurable microstrip antenna array is designed to serve as a DVB-T base station antenna operating in a single broadcasting channel. The antenna array is optimized at 698 MHz (center frequency of DVB-T channel 49) to concurrently achieve a particular radiation pattern shaping with high forward gain, main lobe tilting and null filling inside the service area, as well as low sidelobe level outside the service area, and low standing wave ratio at the inputs of all the array elements. To concurrently satisfy all the above requirements, both the geometry dimensions and the array feeding weights (amplitudes and phases) are optimized, thus leading to a complex multi-variable and multi-objective problem. The problem is solved by applying a recently developed particle swarm optimization (PSO) improved variant, called PSO with velocity mutation, in conjunction with the CST software package, which is employed by the PSOvm every time a full-wave analysis is required. Furthermore, all the optimization methods found in the CST environment are compared with the PSOvm. The results show that the PSOvm is capable of producing an antenna array geometry, which is closer to the predefined requirements than the geometries derived by the rest of the optimizers, in the least amount of computational time.
Optimal Design of an X-Band, Fully-Coaxial, Easily-Tunable Broadband Power Equalizer for a Microwave Power Module
Authors: Lo Gerfo Fabio Paolo , Livreri Patrizia
Published: May 2020

A microwave power module (MPM), which is a hybrid combination of a solid-state power amplifier (SSPA) as a driver and a traveling-wave tube amplifier (TWT) as the final high power stage, is a high-power device largely used for radar applications. A gain equalizer is often required to flatten the TWT output power gain owing to its big gain fluctuations over the operating frequency range. In this paper, the design of an X-band, fully-coaxial, easily-tunable broadband power equalizer for an MPM is presented. The structure is composed of a coaxial waveguide as the main transmission line and a coaxial cavity loaded with absorbing material as a resonant unit. Sensitivity analyses of the attenuation amplitude and resonant frequency of the equalizer in terms of coaxial cavity length, thickness of the absorbing disc, and insertion depth of the probe were carried out. The measured results were in good agreement with the simulated ones, showing that the equalization curve met the requirements well and proved that this optimal structure has the advantages of a large power capacity, a wide operating frequency band, is easily tunable, and good transmission performance.
Analysis of Algorithm Efficiency for Heat Diffusion at Nanoscale Based on a MEMS Structure Investigation
Authors: Raszkowski Tomasz , Zubert Mariusz
Published: May 2020

This paper presents an analysis of the time complexity of algorithms prepared for solving heat transfer problems at nanoscale. The first algorithm uses the classic Dual-Phase-Lag model, whereas the second algorithm employs a reduced version of the model obtained using a Krylov subspace method. This manuscript includes a description of the finite difference method approximation prepared for analysis of the real microelectromechanical system (MEMS) structure manufactured by the Polish Institute of Electron Technology. In addition, an approximation scheme of the model, as well as the Krylov subspace-based model order reduction technique are also described. The paper considers simulation results obtained using both investigated versions of the Dual-Phase-Lag model. Moreover, the relative error generated by the reduced model, as well as the computational complexity of both algorithms, and a convergence of the proposed approach are analyzed. Finally, all analyses are discussed in detail.
Current Harmonics Controller for Reduction of Acoustic Noise, Vibrations and Torque Ripple Caused by Cogging Torque in PM Motors under FOC Operation
Authors: Sumega Martin , Rafajdus Pavol , Stulrajter Marek
Published: May 2020

This article presents an effective algorithm to reduce acoustic noise, vibrations and torque ripple caused by cogging torque in three-phase Permanent Magnet (PM) motors under Field Oriented Control (FOC) operation. Cogging torque profile is suitably included into q-axis current reference, which must be then precisely tracked in order to mitigate acoustic noise, vibrations, torque ripple and speed ripple caused by cogging torque. Conventional FOC structure has been extended by a Current Harmonics Controller (CHC) to achieve precise control of dq current harmonics for all operation speeds, which is crucial to reduce impact of cogging torque and increase performance of electric drive with PM motor. Effectiveness of proposed control technique is experimentally verified by vibrations and acoustic noise measurements.
Forecasting the Structure of Energy Production from Renewable Energy Sources and Biofuels in Poland
Authors: Brodny Jarosław , Tutak Magdalena , Saki Saqib Ahmad
Published: May 2020

The world’s economic development depends on access to cheap energy sources. So far, energy has been obtained mainly from conventional sources like coal, gas and oil. Negative climate changes related to the high emissions of the economy based on the combustion of hydrocarbons and the growing public awareness have made it necessary to look for new ecological energy sources. This condition can be met by renewable energy sources. Both social pressure and international activities force changes in the structure of sources from which energy is produced. This also applies to the European Union countries, including Poland. There are no scientific studies in the area of forecasting energy production from renewable energy sources for Poland. Therefore, it is reasonable to investigate this subject since such a forecast can have a significant impact on investment decisions in the energy sector. At the same time, it must be as reliable as possible. That is why a modern method was used for this purpose, which undoubtedly involves artificial neural networks. The following article presents the results of the analysis of energy production from renewable energy sources in Poland and the forecasts for this production until 2025. Artificial neural networks were used to make the forecast. The analysis covered eight main sources from which this energy is produced in Poland. Based on the production volume since 1990, predicted volumes of renewable energy sources until 2025 were determined. These forecasts were prepared for all studied renewable energy sources. Renewable energy production plans and their share in total energy consumption in Poland were also examined and included in climate plans. The research was carried out using artificial neural networks. The results should be an important source of information on the effects of implementing climate policies in Poland. They should also be utilized to develop action plans to achieve the objectives of the European Green Deal strategy.
Modular Isolated DC-DC Converters for Ultra-Fast EV Chargers: A Generalized Modeling and Control Approach
Authors: ElMenshawy Mena , Massoud Ahmed
Published: May 2020

Electric Vehicles (EVs) play a significant role in the reduction of CO2 emissions and other health-threatening air pollutants Accordingly, several research studies are introduced owing to replacing conventional gasoline-powered vehicles with battery-powered EVs. However, the ultra-fast charging (UFC) of the battery pack or the rapid recharging of the battery requires specific demands, including both: the EV battery and the influence on the power grid. In this regard, advanced power electronics technologies are emerging significantly to replace the currently existing gas station infrastructures with the EV charging stations to move from conventional charging (range of hours) to UFC (range of minutes). Among these power electronics conversion systems, the DC-DC conversion stage plays an essential role in supplying energy to the EV via charging the EV’s battery. Accordingly, this paper aims to present possible architectures of connecting multiple Dual Active Bridge (DAB) units as the DC-DC stage of the EV fast charger and study their Small-Signal Modeling (SSM) and their control scheme. These are, namely, Input-Series Output-Series (ISOS), Input-Series Output-Parallel (ISOP), Input-Parallel Output-Parallel (IPOP), and Input-Parallel Output-Series (IPOS). The control scheme for each system is studied through controlling the output filter inductor current such that the current profile is based on Reflex Charging (RC). The main contribution of this paper can be highlighted in providing generalized SSM as well as providing a generalized control approach for the Input-Series Input-Parallel Output-Series Output-Parallel (ISIP-OSOP) connection. The generalized model is verified with three different architectures. The control strategy for each architecture is studied to ensure equal power sharing, where simulation results are provided to elucidate the presented concept considering a three-module ISOS, IPOP, ISOP, and IPOS DC-DC converters.
Development and Testing of a Single-Axis Photovoltaic Sun Tracker through the Internet of Things
Authors: Gutierrez Sebastian , Rodrigo Pedro M. , Alvarez Jeronimo , Acero Arturo , Montoya Alejandro
Published: May 2020

Solar tracking systems enable increased efficiency of a photovoltaic system through a continuous adjustment of its position with respect to the sun, thus increasing the generation of electrical energy. The integration of photovoltaic solar tracking systems in buildings and houses enables the energy needs of users in a broader way to be covered. This integration is facilitated through the existence of technologies such as access to the Internet through Wi-Fi, which allows developing systems to be encompassed within the domain of the “Internet of Things” (IoT). In this study, a first-of-its-kind “open-loop” solar tracker was designed and developed, which executes the tracking algorithm in the Firebase web service and allows the exchange of data with said service through a NodeMCU development board, which has an integrated Wi-Fi module. After an experimental campaign in Aguascalientes, central Mexico, gains in terms of collected energy on average were measured at 29.9% in May compared to an optimally tilted fixed photovoltaic system. This study opens the possibility of integrating power generation systems into the IoT domain, which, among other things, allows for constant monitoring of the behavior of the system.
A Method for the Combined Estimation of Battery State of Charge and State of Health Based on Artificial Neural Networks
Authors: Bonfitto Angelo
Published: May 2020

This paper proposes a method for the combined estimation of the state of charge (SOC) and state of health (SOH) of batteries in hybrid and full electric vehicles. The technique is based on a set of five artificial neural networks that are used to tackle a regression and a classification task. In the method, the estimation of the SOC relies on the identification of the ageing of the battery and the estimation of the SOH depends on the behavior of the SOC in a recursive closed-loop. The networks are designed by means of training datasets collected during the experimental characterizations conducted in a laboratory environment. The lithium battery pack adopted during the study is designed to supply and store energy in a mild hybrid electric vehicle. The validation of the estimation method is performed by using real driving profiles acquired on-board of a vehicle. The obtained accuracy of the combined SOC and SOH estimator is around 97%, in line with the industrial requirements in the automotive sector. The promising results in terms of accuracy encourage to deepen the experimental validation with a deployment on a vehicle battery management system.
Fabrication of Mn-N-C Catalyst for Oxygen Reduction Reactions Using Mn-Embedded Carbon Nanofiber
Authors: Kim Hyo-Young , Ju Young-Wan
Published: May 2020

The development of efficient and cost-effective electrocatalysts for oxygen reduction reactions (ORR) is one of the most crucial goals in the field of energy conversion devices such as fuel cells or metal-air batteries. Until now, the platinum-based catalyst has been considered the gold standard electrocatalyst and is widely used for ORR. In recent times, transition metal-nitrogen (N)-carbon (C)-based electrocatalysts have verified ORR performances comparable to novel metal-based catalysts. However, due to the complex production methods and low yield, their high price is their one major disadvantage compared to platinum-based catalysts. Herein, we present a transition metal-N-C electrochemical catalyst prepared by simple electrospinning and heat treatment. The metal- and nitrogen-embedded carbon nanofiber represents considerably enhanced activity for oxygen reduction reactions compared to pristine carbon nanofiber.
Dynamic Residential Energy Management for Real-Time Pricing
Authors: Yao Leehter , Hashim Fazida Hanim , Lai Chien-Chi
Published: May 2020

A home energy management system (HEMS) was designed in this paper for a smart home that uses integrated energy resources such as power from the grid, solar power generated from photovoltaic (PV) panels, and power from an energy storage system (ESS). A fuzzy controller is proposed for the HEMS to optimally manage the integrated power of the smart home. The fuzzy controller is designed to control the power rectifier for regulating the AC power in response to the variations in the residential electric load, solar power from PV panels, power of the ESS, and the real-time electricity prices. A self-learning scheme is designed for the proposed fuzzy controller to adapt with short-term and seasonal climatic changes and residential load variations. A parsimonious parameterization scheme for both the antecedent and consequent parts of the fuzzy rule base is utilized so that the self-learning scheme of the fuzzy controller is computationally efficient.
Hawthorn (Crataegus spp.): An Updated Overview on Its Beneficial Properties
Authors: Nazhand Amirhossein , Lucarini Massimo , Durazzo Alessandra , Zaccardelli Massimo , Cristarella Santo , Souto Selma B. , Silva Amélia M. , Severino Patrícia , Souto Eliana B. , Santini Antonello
Published: May 2020

Medicinal plants, many of which are wild, have recently been under the spotlight worldwide due to growing requests for natural and sustainable eco-compatible remedies for pathological conditions with beneficial health effects that are able to support/supplement a daily diet or to support and/or replace conventional pharmacological therapy. The main requests for these products are: safety, minimum adverse unwanted effects, better efficacy, greater bioavailability, and lower cost when compared with synthetic medications available on the market. One of these popular herbs is hawthorn (Crataegus spp.), belonging to the Rosaceae family, with about 280 species present in Europe, North Africa, West Asia, and North America. Various parts of this herb, including the berries, flowers, and leaves, are rich in nutrients and beneficial bioactive compounds. Its chemical composition has been reported to have many health benefits, including medicinal and nutraceutical properties. Accordingly, the present review gives a snapshot of the in vitro and in vivo therapeutic potential of this herb on human health.
A Financial Assessment of Windstorm Risks for Scots Pine Stands in Hemiboreal Forests
Authors: Donis Janis , Saleniece Renate , Krisans Oskars , Dubrovskis Edgars , Kitenberga Mara , Jansons Aris
Published: May 2020

Windstorms are a significant disturbance in northern European Scots pine forests. Mechanistic models for assessment of their impact have been developed. The aim of our study was to assess the impact of windstorms on the financial value of Scots pine (Pinus sylvestris L.) stands. Wind damage probability in stands with certain dimensions (linked to age and site index) and the reduced value retrieved from salvage logging instead of planned harvest in undamaged stands were used for calculation. Equivalent annual annuity with interest rates of 3%, 4%, and 5%, three different commercial thinning regimes, and different planting densities were used to assess the mean influence. Wind damage risk had a notable and significant negative effect on the financial value of Scots pine forest stands. Equivalent annual annuity decreased sharply with stand age, especially in the most productive sites (SI 36). The negative financial impact could be reduced by selection of a lower initial planting density (1000–2000 trees ha−1 instead of 3000) and by reducing the rotation period, for example, by using target diameter as the criteria for the time of final harvest.
Gravitational Focusing of Low-Velocity Dark Matter on the Earth’s Surface
Authors: Sofue Yoshiaki
Published: May 2020

We show that the Earth acts as a high-efficiency gravitational collector of low-velocity flow of dark matter (DM). The focal point appears on the Earth’s surface, when the DM flow speed is about 17 km/s with respect to the geo-center. We discuss diurnal modulation of the local DM density influenced by the Earth’s gravity. We also touch upon similar effects on galactic and solar system objects.
The Q223R Polymorphism of the Leptin Receptor Gene as a Predictor of Weight Gain in Childhood Obesity and the Identification of Possible Factors Involved
Authors: Marcos-Pasero Helena , Aguilar-Aguilar Elena , Colmenarejo Gonzalo , Ramírez de Molina Ana , Reglero Guillermo , Loria-Kohen Viviana
Published: May 2020

(1) Background: Childhood rapid weight gain during development has been postulated as a predictor of obesity. The objective of this study was to investigate the effect of single nucleotide polymorphisms (SNPs) on the annual weight gain and height growth, as well as identifying possible lifestyle factors involved. (2) Methods: As part of the GENYAL study, 221 children (6–8 years old) of Madrid (Spain) were enrolled. A total of 11 SNPs associated with high childhood body mass indexes (BMIs) were assessed. Anthropometric measurements, dietary and physical activity data, were collected in 2017 and 2018. Bonferroni-corrected linear models were used to fit the data. (3) Results: A significant association between the Q223R LEPR and the weight growth was found, showing a different behavior between GA and GG genotypes (p = 0.001). Regarding lifestyle factors, an interaction between Q223R genotypes and total active weekly hours/week to predict the weight growth (kg/year) was observed (p = 0.023). In all the genotypes, a beneficial effect against rapid weight growth was observed, but the effect size of the interaction was much more significant in homozygous (GG) minor homozygous (β = −0.61 (−0.95, −0.26) versus heterozygous (AG) and wild-type homozygous (AA) genotypes (β = −0.07 (−0.24, 0.09) and β = −0.12 (−0.32, 0.08), respectively). (4) Conclusions: These results may contribute to more personalized recommendations to prevent childhood obesity.
Exome-Wide Analysis of the DiscovEHR Cohort Reveals Novel Candidate Pharmacogenomic Variants for Clinical Pharmacogenomics
Authors: Pandi Maria-Theodora , Williams Marc S. , van der Spek Peter , Koromina Maria , Patrinos George P.
Published: May 2020

Recent advances in next-generation sequencing technology have led to the production of an unprecedented volume of genomic data, thus further advancing our understanding of the role of genetic variation in clinical pharmacogenomics. In the present study, we used whole exome sequencing data from 50,726 participants, as derived from the DiscovEHR cohort, to identify pharmacogenomic variants of potential clinical relevance, according to their occurrence within the PharmGKB database. We further assessed the distribution of the identified rare and common pharmacogenomics variants amongst different GnomAD subpopulations. Overall, our findings show that the use of publicly available sequence data, such as the DiscovEHR dataset and GnomAD, provides an opportunity for a deeper understanding of genetic variation in pharmacogenes with direct implications in clinical pharmacogenomics.
Analysis of Necessary Support in the 2011 Great East Japan Earthquake Disaster Area
Authors: Harada Moeka , Ishikawa-Takata Kazuko , Tsuboyama-Kasaoka Nobuyo
Published: May 2020

Altogether, 1588 dietitians were dispatched from the Japan Dietetic Association (JDA) to a disaster area for the first time on a nationwide scale following the 2011 Great East Japan Earthquake. Various studies have been conducted based on the activity reports, but the support that the disaster area requested was not documented. The purpose of this study is to identify the support that was needed in the disaster area. Therefore, we investigated the necessary support desired by dietitians who lived in the disaster areas. Questionnaires were sent to 1911 dietitians who were members of the JDA and lived in 3 affected prefectures in August 2012. In total, 435 dietitians (22.8%) completed the questionnaire. Among the questions on the questionnaire, we analyzed answers to the open-ended question: “Please write freely about the support that you wanted at the time of the disaster” (n = 332). Using qualitative descriptive analysis, we extracted data from the answers and categorized and labeled them into similar groups. These groups were divided into four categories: (1) “goods,” (2) “establishing a system in advance of a large-scale disaster,” (3) “information,” and (4) “human resources.” To provide “goods,” “information,” and “human resources” to the disaster area smoothly, it is important to plan a “system” in advance of large-scale disasters.
Histological and Histomorphometrical Evaluation of a New Implant Macrogeometry. A Sheep Study
Authors: Gehrke Sergio Alexandre , Tumedei Margherita , Aramburú Júnior Jaime , Treichel Tiago Luis Eirles , Kolerman Roni , Lepore Stefania , Piattelli Adriano , Iezzi Giovanna
Published: May 2020

Decompression or healing chambers between the threads have been proposed to improve and accelerate the osseointegration process of dental implants. The aim of the present work was to test, in an in vivo sheep study, if healing chambers between the threads could produce a better osseointegration process. Thirty titanium implants (15 conventional design (control) and 15 implants with healing chambers (test)) were inserted in a random fashion in the tibia of 3 sheep. The animals were euthanized after 30 days of healing, and the retrieved specimens treated to obtain thin ground sections. Histological observations showed that the quantity of newly formed bone growing in an apical direction was lower in the control group (1095 µm) when compared to the Test group (1658 µm). This difference was statistically significant. Moreover, a layer of osteogenic matrix was present around the portion of implants immersed in the marrow spaces. This osteogenic tissue was thicker in the test group. In conclusion, the present study confirmed the very good results in implants with healing chambers that presented a higher percentage of new bone formation.
Using Life History Calendars to Estimate in Utero and Early Life Pesticide Exposure of Latinx Children in Farmworker Families
Authors: Quandt Sara A. , Mora Dana C. , Seering Theresa L. , Chen Haiying , Arcury Thomas A. , Laurienti Paul J.
Published: May 2020

(1) Background: Early life exposure to neurotoxic chemicals can have later impacts on child health. Most research designs must assume that current exposure is similar to past. Life history calendar methods can help to provide data on early life exposure. (2) Methods: Life history calendars were completed by mothers of 8-year-old children from Latinx farmworker and non-farmworker families (n = 73 and 65, respectively). Measures were created of months exposure through living adjacent to farm fields and having household members who worked in jobs exposing them to toxic chemicals. Data were divided into time periods of in utero, early childhood (birth-35 months) and later childhood (36–96 months). Cluster analysis compared the measures for children from farmworker and non-farmworker parents. (3) Results: Although, as a group, children from farmworker families have greater lifetime months of probable exposure to pesticides than children in non-farmworker families, cluster analysis reveals groups of children who do not follow that pattern. (4) Conclusions: The life history calendar is a technique for obtaining data on early life toxic chemical exposure that may help assign children to proper exposure groups. Conducting secondary analyses using such information can help to clarify the association of exposures to health outcomes.