bluuebunny/crossref_metadata_2025 huggingface dataset:
Catalytic Evaluation of Nanoflower Structured Manganese Oxide Electrocatalyst for Oxygen Reduction in Alkaline Media
Authors: Jing Han Siow , Ameen Mariam , Hanifah Mohamad Fahrul Radzi , Aqsha Aqsha , Bilad Muhammad Roil , Jaafar Juhana , Kheawhom Soorathep
Published: July 2020

An electrochemical nanoflowers manganese oxide (MnO2) catalyst has gained much interest due to its high stability and high specific surface area. However, there are a lack of insightful studies of electrocatalyst performance in nanoflower MnO2. This study assesses the electrocatalytic performances of nanoflower structure MnO2 for both oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) in a zinc–air battery as a bifunctional electrocatalyst. The prepared catalyst was characterized in term of morphology, crystallinity, and total surface area. Cyclic voltammetry and linear sweep voltammetry were used to evaluate the electrochemical behaviors of the as-prepared nanoflower-like MnO2. The discharge performance test for zinc–air battery with a MnO2 catalyst was also conducted. The results show that the MnO2 prepared at dwell times of 2, 4 and 6 h were nanoflowers, nanoflower mixed with nanowires, and nanowires with corresponding specific surface areas of 52.4, 34.9 and 32.4 g/cm2, respectively. The nanoflower-like MnO2 catalyst exhibits a better electrocatalytic performance towards both ORR and OER compared to the nanowires. The number of electrons transferred for the MnO2 with nanoflower, nanoflower mixed with nanowires, and nanowire structures is 3.68, 3.31 and 3.00, respectively. The as-prepared MnO2 nanoflower-like structure exhibits the best discharge performance of 31% higher than the nanowires and reaches up to 30% of the theoretical discharge capacity of the zinc–air battery.
Metal Complexes Bearing Sulfur-Containing Ligands as Catalysts in the Reaction of CO2 with Epoxides
Authors: Paradiso Veronica , Capaccio Vito , Lamparelli David Hermann , Capacchione Carmine
Published: July 2020

Coupling of CO2 with epoxides is a green emerging alternative for the synthesis of cyclic organic carbonates (COC) and aliphatic polycarbonates (APC). The scope of this work is to provide a comprehensive overview of metal complexes having sulfur-containing ligands as homogeneous catalytic systems able to efficiently promote this transformation with a concise discussion of the most significant results. The crucial role of sulfur as the hemilabile ligand and its influence on the catalytic activity are highlighted as well.
DNC4mC-Deep: Identification and Analysis of DNA N4-Methylcytosine Sites Based on Different Encoding Schemes By Using Deep Learning
Authors: Wahab Abdul , Mahmoudi Omid , Kim Jeehong , Chong Kil To
Published: July 2020

N4-methylcytosine as one kind of modification of DNA has a critical role which alters genetic performance such as protein interactions, conformation, stability in DNA as well as the regulation of gene expression same cell developmental and genomic imprinting. Some different 4mC site identifiers have been proposed for various species. Herein, we proposed a computational model, DNC4mC-Deep, including six encoding techniques plus a deep learning model to predict 4mC sites in the genome of F. vesca, R. chinensis, and Cross-species dataset. It was demonstrated by the 10-fold cross-validation test to get superior performance. The DNC4mC-Deep obtained 0.829 and 0.929 of MCC on F. vesca and R. chinensis training dataset, respectively, and 0.814 on cross-species. This means the proposed method outperforms the state-of-the-art predictors at least 0.284 and 0.265 on F. vesca and R. chinensis training dataset in turn. Furthermore, the DNC4mC-Deep achieved 0.635 and 0.565 of MCC on F. vesca and R. chinensis independent dataset, respectively, and 0.562 on cross-species which shows it can achieve the best performance to predict 4mC sites as compared to the state-of-the-art predictor.
Cholesterol as an Endogenous Ligand of ERRα Promotes ERRα-Mediated Cellular Proliferation and Metabolic Target Gene Expression in Breast Cancer Cells
Authors: Ghanbari Faegheh , Mader Sylvie , Philip Anie
Published: July 2020

Breast cancer is the 2nd leading cause of cancer-related death among women. Increased risk of breast cancer has been associated with high dietary cholesterol intake. However, the underlying mechanisms are not known. The nuclear receptor, estrogen-related receptor alpha (ERRα), plays an important role in breast cancer cell metabolism, and its overexpression has been linked to poor survival. Here we identified cholesterol as an endogenous ligand of ERRα by purification from human pregnancy serum using a GST-ERRα affinity column and liquid chromatography-tandem mass spectrometry (LC-MS/MS). We show that cholesterol interacts with ERRα and induces its transcriptional activity in estrogen receptor positive (ER+) and triple negative breast cancer (TNBC) cells. In addition, we show that cholesterol enhances ERRα-PGC-1α interaction, induces ERRα expression itself, augments several metabolic target genes of ERRα, and increases cell proliferation and migration in both ER+ and TNBC cells. Furthermore, the stimulatory effect of cholesterol on metabolic gene expression, cell proliferation, and migration requires the ERRα pathway. These findings provide a mechanistic explanation for the increased breast cancer risk associated with high dietary cholesterol and possibly the pro-survival effect of statins in breast cancer patients, highlighting the clinical relevance of lowering cholesterol levels in breast cancer patients overexpressing ERRα.
Adsorption of Titanium Halides on Nitride and Oxide Surfaces during Atomic Layer Deposition: A DFT Study
Authors: Park Jeongwoo , Yu Neung Kyung , Jang Donghak , Jung Eunae , Noh Hyunsik , Moon Jiwon , Kil Deoksin , Shong Bonggeun
Published: July 2020

Various processes based on atomic layer deposition (ALD) have been reported for growing Ti-based thin films such as TiN and TiO2. To improve the uniformity and conformity of thin films grown via ALD, fundamental understanding of the precursor–substrate surface reactions is required. Herein, we present a density functional theory (DFT) study of the initial nucleation process of some titanium halide precursors (TiCl4, TiBr4, and TiI4) on Si surfaces having –OH or –NH2 functional groups. We consider the most favorable adsorption site in the reaction between the precursor and functional group of the surface, based on the thermodynamics and kinetics of the reaction. Sequential dissociation reaction mechanisms of halide ligands were systematically investigated. The exothermicity of the dissociative adsorption was found to be in the order of: TiI4 > TiBr4 > TiCl4. In addition, the precursors were observed to be more exothermic and show higher reaction rate constant when adsorbed on the –OH–terminated surface than on the –NH2–terminated surface. These observations reveal the selectivity of deposition by surface functional groups.
Fabrication of Ultralow Stress TiO2/SiO2 Optical Coatings by Plasma Ion-Assisted Deposition
Authors: Guo Chun , Kong Mingdong
Published: July 2020

Optical and mechanical properties of multilayer coatings depend on the selected layer materials and the deposition technology; therefore, knowledge of the performances of thin films is essential. In the present work, titanium dioxide (TiO2) and silicon dioxide (SiO2) thin films have been prepared by plasma ion-assisted deposition (PIAD). The optical, structural, and mechanical properties of thin films have been investigated using spectrometer/ellipsometer, X-ray diffraction (XRD), atomic force microscopy (AFM), and laser interferometer. The results show that TiO2 film fabricated by PIAD induces a high refractive index, wide optical band gap, amorphous structure, smooth surface, and tensile stress. In the case of SiO2 film, high bias voltage leads to dense structure and compressive stress. As an application, a three-wavelength high reflectance at 632.8, 808, and 1550 nm was optimized and deposited. The dependence of total stress in the multilayer on the substrate temperature was studied as well. In conclusion, it was demonstrated that PIAD is an effective method for the preparation of ultralow stress TiO2/SiO2 multilayer films. The achieved stress was as low as 1.4 MPa. The result could provide guidance to the stress optimization of most optical components without prefiguring, backside coating, and postdeposition treatments.
Investigation of Barrier Inhomogeneities and Electronic Transport on Al-Foil/p-Type-4H-SiC Schottky Barrier Diodes Using Diffusion Welding
Authors: Ziko Mehadi Hasan , Koel Ants , Rang Toomas , Rashid Muhammad Haroon
Published: July 2020

The diffusion welding (DW) is a comprehensive mechanism that can be extensively used to develop silicon carbide (SiC) Schottky rectifiers as a cheaper alternative to existing mainstream contact forming technologies. In this work, the Schottky barrier diode (SBD) fabricated by depositing Al-Foil on the p-type 4H-SiC substrate with a novel technology; DW. The electrical properties of physically fabricated Al-Foil/4H-SiC SBD have been investigated. The current-voltage (I-V) and capacitance-voltage (C-V) characteristics based on the thermionic emission model in the temperature range (300 K–450 K) are investigated. It has been found that the ideality factor and barrier heights of identically manufactured Al-Foil/p-type-4H-SiC SBDs showing distinct deviation in their electrical characteristics. An improvement in the ideality factor of Al-Foil/p-type-4H-SiC SBD has been noticed with an increase in temperature. An increase in barrier height in fabricated SBD is also observed with an increase in temperature. We also found that these increases in barrier height, improve ideality factors and abnormalities in their electrical characteristics are due to structural defects initiation, discrete energy level formation, interfacial native oxide layer formation, inhomogenous doping profile distribution and tunneling current formation at the SiC sufaces.
A State-of-the-Art Review on the Evolving Utility of Endoscopic Ultrasound in Liver Diseases Diagnosis
Authors: Sbeit Wisam , Kadah Anas , Mahamid Mahmud , Pellicano Rinaldo , Mari Amir , Khoury Tawfik
Published: July 2020

Liver diseases are amongst the most common diseases worldwide and manifest as a parenchymatic and/or biliary injury due to several causes as well as focal liver lesions, ranging from benign to malignant ones. The diagnosis of liver diseases is based mainly on biochemical and advanced imaging studies and, when required, on liver biopsy. Endoscopic ultrasound (EUS), which combines endoscopy and ultrasonography, is one of the main examination techniques used in gastroenterology as it is applied to evaluate abnormalities in the lumen of the upper and lower gastrointestinal tract and to define pancreatic and hepato-biliary features, often in chronic patients. Given its high spatial resolution and its proximity to the liver, EUS is gaining popularity in the diagnostic work up of liver diseases. This is a comprehensive overview of the current literature on the diagnostic indications for EUS use in patients with liver diseases. We performed a MEDLINE\PubMed and Embase search, and all articles that were relevant, after reviewing abstracts, were assessed and the full text was analyzed to extract data regarding technical success, diagnostic yield, bioptic characteristics, and complications rate. EUS-guided imaging and biopsy techniques in liver diseases have shown consistent favorable promising results among the reports through the literature, with an excellent diagnostic yield and safety profile, especially in the context of focal lesions and portal hypertension. The application of EUS in the diagnosis of liver diseases is a promising technique and should be considered as a first-line therapeutic option in selected cases.
Randomized Trial on the Clinical Utility of a Novel Biomarker Panel to Identify Treatable Determinants of Chronic Pain
Authors: Peabody John , Paculdo David , Tamondong-Lachica Diana , Cabaluna Ian Theodore , Gunn Joshua
Published: July 2020

Millions suffer daily from chronic pain diagnosed anatomically and treated with opioids. Research shows that underlying nutritional, metabolic and oxidative stressors, which drive the development or worsening of chronic pain, are not diagnosed despite the fact that treatment of these primary pain pathways relieves pain and increases function. One of the main reasons for this gap in care is the lack of a simple diagnostic assay to help clinicians make these diagnoses. We examined the clinical utility of a urine-based pain biomarker panel. Primary care physicians were randomized into the test group and compared to controls. We measured their ability to make the diagnosis and treat a total of nine standardized patients, with common but challenging cases of chronic pain, over two rounds of data collection in a pre–post design using a fixed-effects model. Intervention doctors received educational materials on a novel pain biomarker panel after the baseline round and had access to biomarker test results. Provider responses were measured against evidence-based criteria. The two study arms at baseline provided similar, poor care for three different primary pain pathways: nutritional deficiencies (5.0% control versus 9.2% intervention treated, p = 0.208), metabolic abnormalities (1.0% control versus 0% for intervention treated, p = 0.314), and oxidative stress (1.2% control versus 0% intervention treated, p = 0.152). After the introduction of the Foundation Pain Index (FPI) biomarker test, physicians in the intervention group were 41.5% more likely to make the diagnosis of a micronutrient deficiency, 29.4% more likely to identify a treatable metabolic abnormality and 26.1% more likely to identify an oxidative stressor. These diagnostic and treatment improvements were seen across all three case types, ranging from a relative +54% (p = 0.004) for chronic neuropathic pain to +35% (p = 0.007) in chronic pain from other causes to +38% (p = 0.002) in chronic pain with associated mental health issues. Intervention doctors were also 75.1% more likely to provide a non-opioid treatment to patients on chronic opioids (O.R. 1.8, 95% C.I. 0.8–3.7), 62% less likely to order unnecessary imaging for their patients with low back pain (O.R. 0.38, 95% C.I. 0.15–0.97) and 66% less likely to order an unnecessary pain referral (O.R. 0.34, 95% C.I. 0.13–0.90). This experimental study showed significant clinical utility of a validated pain biomarker panel that determines nutritional deficiencies, metabolic abnormalities and oxidative stressors that drive underlying treatable causes of pain. When integrated into routine primary care practice, this testing approach could considerably improve diagnostic accuracy and provide more targeted, non-opioid treatments for patients suffering from chronic pain.
Option Portfolio Selection with Generalized Entropic Portfolio Optimization
Authors: Mercurio Peter Joseph , Wu Yuehua , Xie Hong
Published: July 2020

In this third and final paper of our series on the topic of portfolio optimization, we introduce a further generalized portfolio selection method called generalized entropic portfolio optimization (GEPO). GEPO extends discrete entropic portfolio optimization (DEPO) to include intervals of continuous returns, with direct application to a wide range of option strategies. This lays the groundwork for an adaptable optimization framework that can accommodate a wealth of option portfolios, including popular strategies such as covered calls, married puts, credit spreads, straddles, strangles, butterfly spreads, and even iron condors. These option strategies exhibit mixed returns: a combination of discrete and continuous returns with performance best measured by portfolio growth rate, making entropic portfolio optimization an ideal method for option portfolio selection. GEPO provides the mathematical tools to select efficient option portfolios based on their growth rate and relative entropy. We provide an example of GEPO applied to real market option portfolio selection and demonstrate how GEPO outperforms traditional Kelly criterion strategies.
Single-Shot 3D Multi-Person Shape Reconstruction from a Single RGB Image
Authors: Kim Seong Hyun , Chang Ju Yong
Published: July 2020

Although the performance of the 3D human shape reconstruction method has improved considerably in recent years, most methods focus on a single person, reconstruct a root-relative 3D shape, and rely on ground-truth information about the absolute depth to convert the reconstruction result to the camera coordinate system. In this paper, we propose an end-to-end learning-based model for single-shot, 3D, multi-person shape reconstruction in the camera coordinate system from a single RGB image. Our network produces output tensors divided into grid cells to reconstruct the 3D shapes of multiple persons in a single-shot manner, where each grid cell contains information about the subject. Moreover, our network predicts the absolute position of the root joint while reconstructing the root-relative 3D shape, which enables reconstructing the 3D shapes of multiple persons in the camera coordinate system. The proposed network can be learned in an end-to-end manner and process images at about 37 fps to perform the 3D multi-person shape reconstruction task in real time.
Intelligent Calibration of a Heavy-Duty Mechanical Arm in Coal Mine
Authors: Jia Yunhong , Zhang Xiaodong , Wang Zhenchong , Wang Wei
Published: July 2020

Accurate positioning of an airborne heavy-duty mechanical arm in coal mine, such as a roof bolter, is important for the efficiency and safety of coal mining. Its positioning accuracy is affected not only by geometric errors but also by nongeometric errors such as link and joint compliance. In this paper, a novel calibration method based on error limited genetic algorithm (ELGA) and regularized extreme learning machine (RELM) is proposed to improve the positioning accuracy of a roof bolter. To achieve the improvement, the ELGA is firstly implemented to identify the geometric parameters of the roof bolter’s kinematics model. Then, the residual positioning errors caused by nongeometric facts are compensated with the regularized extreme learning machine (RELM) network. Experiments were carried out to validate the proposed calibration method. The experimental results show that the root mean square error (RMSE) and the mean absolute error (MAE) between the actual mast end position and the nominal mast end position are reduced by more than 78.23%. It also shows the maximum absolute error (MAXE) between the actual mast end position and the nominal mast end position is reduced by more than 58.72% in the three directions of Cartesian coordinate system.
Energy Supply Preferences as Multicriteria Decision Problems: Developing a System of Criteria from Survey Data
Authors: Börcsök Endre , Ferencz Zoltán , Groma Veronika , Gerse Ágnes , Fülöp János , Bozóki Sándor , Osán János , Török Szabina , Horváth Ákos
Published: July 2020

Decision support techniques have a key role in investment and strategic decisions in the energy sector. As complex decision-making problems involve the simultaneous consideration of an extensive set of different factors, it is an essential part of the methodology to define, structure, and integrate the criteria. The main purpose of the study was to develop a system of criteria and weights that are suitable for general application in the energy sector and can best describe the decision-making mechanisms present in society and various social groups. When developing the system of criteria, we moved away from the hierarchical approach related to the three pillars of sustainability; therefore, a wide range of notions were assessed based on a population representative survey data collected in Hungary. We used algebraic methods to explore the internal structure of the set of criteria that had been previously defined by means of social sciences, while the importance weights were specified by applying the method of analytic network process. Furthermore, the ranking of heating and electricity generation alternatives were determined.
Distributed Power Hardware-in-the-Loop Testing Using a Grid-Forming Converter as Power Interface
Authors: Vogel Steffen , Nguyen Ha Thi , Stevic Marija , Jensen Tue Vissing , Heussen Kai , Rajkumar Vetrivel Subramaniam , Monti Antonello
Published: July 2020

This paper presents an approach to extend the capabilities of smart grid laboratories through the concept of Power Hardware-in-the-Loop (PHiL) testing by re-purposing existing grid-forming converters. A simple and cost-effective power interface, paired with a remotely located Digital Real-time Simulator (DRTS), facilitates Geographically Distributed Power Hardware Loop (GD-PHiL) in a quasi-static operating regime. In this study, a DRTS simulator was interfaced via the public internet with a grid-forming ship-to-shore converter located in a smart-grid testing laboratory, approximately 40 km away from the simulator. A case study based on the IEEE 13-bus distribution network, an on-load-tap-changer (OLTC) controller and a controllable load in the laboratory demonstrated the feasibility of such a setup. A simple compensation method applicable to this multi-rate setup is proposed and evaluated. Experimental results indicate that this compensation method significantly enhances the voltage response, whereas the conservation of energy at the coupling point still poses a challenge. Findings also show that, due to inherent limitations of the converter’s Modbus interface, a separate measurement setup is preferable. This can help achieve higher measurement fidelity, while simultaneously increasing the loop rate of the PHiL setup.
An Efficient Robust Predictive Control of Main Steam Temperature of Coal-Fired Power Plant
Authors: Wang Di , Wu Xiao , Shen Jiong
Published: July 2020

Regulating performance of the main steam temperature (MST) system concerns the economy and safety of the coal-fired power plant (CFPP). This paper develops an offset-free offline robust model predictive control (RMPC) strategy for the MST system of CFPP. Zonotope-type uncertain model is utilized as the prediction model in the proposed RMPC design owing to its features of higher accuracy, compactness of representation and less complexity. An offline RMPC aiming at the system robustness and computational efficiency is then developed to maintain the desired steam temperature in case of wide operating condition change. The proposed RMPC is realized by two stages: in the first stage, the RMPC law set, which is the piecewise affine (PWA) of the MST system state is designed offline; then in the second stage, the explicit control law is selected online according to the current state. To achieve an offset-free tracking performance, a manipulated variable target observer is employed to update the chosen RMPC law. The control simulations using on-site operating data of a 1000 MW ultra-supercritical power plant show that the proposed approach can achieve satisfactory control performance and online computation efficiency even under complicated operating conditions.
Assessment and Evaluation of the Thermal Performance of Various Working Fluids in Parabolic Trough Collectors of Solar Thermal Power Plants under Non-Uniform Heat Flux Distribution Conditions
Authors: Abed Nabeel , Afgan Imran , Cioncolini Andrea , Iacovides Hector , Nasser Adel
Published: July 2020

Changing the heat transfer fluid (HTF) is a viable approach to study the corresponding effect on the thermal and hydraulic performances of parabolic trough collectors (PTC). Three categorized-types of pure fluids are used in this study; water, Therminol® VP-1 and molten salt. The parametric comparison between pure fluids is also studied considering the effect of various inlet fluid temperatures and different Reynolds ( R e ) numbers on the thermal performance. Two low-Reynolds turbulence models are used; Launder and Sharma (LS) k-epsilon and Shear Stress Transport (SST) k-omega models. In order to assess the performance of each fluid, a number of parameters are analyzed including average Nusselt ( N u ) number, specific pressure drop distributions, thermal losses, thermal stresses and overall thermal efficiency of the PTC system. Results confirmed that changing the working fluid in the PTC enhances the overall heat transfer thereby improving thermal efficiency. For a temperature-range of (320–500) K, the Therminol® VP-1 performed better than water, resulting in higher N u numbers, lower thermal stresses and higher thermal efficiencies. On the other hand, for the common temperature-range, both Therminol® VP-1 and molten salt preformed more or less the same with Therminol® VP-1 case depicting lower thermal stresses. The molten salt is thus the best choice for high operating temperatures (up to 873 K) as it does not depict any significant reduction in the overall thermal efficiency at high temperatures; this leads to a better performance for the Rankine cycle. For the highest tested Reynolds number for an inlet fluid temperature of 320 K, a comparison of heat transfer performance (Nusselt number) and the overall thermal efficiency between Therminol® VP-1 and water showed that Therminol® VP-1 is the best candidate, whereas the molten salt is the best choice for a higher inlet temperature of 600 K. For example, at an inlet temperature of 320 K, the Nusselt number and overall thermal efficiency of therminol VP-1 were 910 and 49% respectively as opposed to 443 and 38% for water. On the other hand, at the higher inlet temperature of 600 K, these two parameters (Nusselt number and overall thermal efficiency) were recorded as 614 and 41 % for molten salt and 500 and 39 % for Therminol® VP-1.
A Mixed Integer Linear Programming Model for the Optimization of Steel Waste Gases in Cogeneration: A Combined Coke Oven and Converter Gas Case Study
Authors: García García Sergio , Rodríguez Montequín Vicente , Morán Palacios Henar , Mones Bayo Adriano
Published: July 2020

Off-gas is one of the by-products of the steelmaking process. Its potential energy can be transformed into heat and electricity by means of cogeneration. A case study using a coke oven and Linz–Donawitz converter gas is presented. This work addresses the gas allocation problem for a cogeneration system producing steam and electricity. In the studied facility, located in northern Spain, the annual production of the plant requires 95,000 MWh of electrical energy and 525,000 MWh of thermal energy. The installed electrical and thermal power is 20.4 MW and 81 MW, respectively. A mixed integer linear programming model is built to optimize gas allocation, thus maximizing its benefits. This model is applied to a 24-h scenario with real data from the plant, where gas allocation decision-making was performed by the plant operators. Application of the model generated profit in a scenario where there were losses, increasing benefits by 16.9%. A sensitivity analysis is also performed. The proposed model is useful not only from the perspective of daily plant operation but also as a tool to simulate different design scenarios, such as the capacity of gasholders.
A Bidirectional Electrical Vehicle Charger and Grid Interface for Grid Voltage Dip Mitigation
Authors: Saadeh Osama , Al Nawasrah Anwar , Dalala Zakariya
Published: July 2020

Power quality issues have recently become a source of major concern due to the large increase in load demand and the addition of various sources of disturbance at the distribution level. Power quality mainly refers to voltage quality. Sudden load variations can lead to a fall in the line voltage magnitude, creating what is called a voltage sag. Many solutions have been proposed and implemented for voltage sag compensation. Power electronics-based solutions such as grid-connected converters and AC/DC schemes are considered basic units for transient voltage fault ride-through capability. This paper describes a multifunctional intelligent bidirectional electrical vehicle (EV) charger that is able to charge the EV battery at different power ratings in addition to voltage sag compensation. The performance of the proposed system is verified and validated through MATLAB/Simulink simulations (R2020A). The proposed solution can effectively meet three main requirements: charging the EV battery at different power ratings, detecting the voltage sag event, and providing the required active and reactive power compensation for voltage sag compensation.
Uncertainty Quantification of the Effects of Blade Damage on the Actual Energy Production of Modern Wind Turbines
Authors: Papi Francesco , Cappugi Lorenzo , Salvadori Simone , Carnevale Mauro , Bianchini Alessandro
Published: July 2020

Wind turbine blade deterioration issues have come to the attention of researchers and manufacturers due to the relevant impact they can have on the actual annual energy production (AEP). Research has shown how after prolonged exposure to hail, rain, insects or other abrasive particles, the outer surface of wind turbine blades deteriorates. This leads to increased surface roughness and material loss. The trailing edge (TE) of the blade is also often damaged during assembly and transportation according to industry veterans. This study aims at investigating the loss of AEP and efficiency of modern multi-MW wind turbines due to such issues using uncertainty quantification. Such an approach is justified by the stochastic and widely different environmental conditions in which wind turbines are installed. These cause uncertainties regarding the blade’s conditions. To this end, the test case selected for the study is the DTU 10 MW reference wind turbine (RWT), a modern reference turbine with a rated power of 10 MW. Blade damage is modelled through shape modification of the turbine’s airfoils. This is done with a purposely developed numerical tool. Lift and drag coefficients for the damaged airfoils are calculated using computational fluid dynamics. The resulting lift and drag coefficients are used in an aero-servo-elastic model of the wind turbine using NREL’s code OpenFAST. An arbitrary polynomial chaos expansion method is used to estimate the probability distributions of AEP and power output of the model when blade damage is present. Average AEP losses of around 1% are predicted mainly due to leading-edge blade damage. Results show that the proposed method is able to account for the uncertainties and to give more meaningful information with respect to the simulation of a single test case.
Impact of Diethyl Ether/Rapeseed Oil Blends on Performance and Emissions of a Light-Duty Diesel Vehicle
Authors: Smigins Ruslans , Zakis Arturs
Published: July 2020

This article presents results of experimental study of diesel, rapeseed oil and three different blends of 10%, 20% and 30% diethyl ether addition to rapeseed oil, tested on VW Golf vehicle on chassis dynamometer Mustang MD-1750. Fuel consumption and emission tests were conducted at different testing conditions: idling, 50 km/h, 90 km/h, as also IM-240 cycle. The analysis of obtained results have shown reduction of engine power by 6.2%–17.3% and increase of fuel consumption by 0.6%–15.5% (based on testing conditions) for all blends based on DEE addition compared to RO, demonstrating better perspectives for low level blends. Emission tests have shown decrease of hydrocarbons and nitrogen oxides (NOx) for all blends with DEE content in almost all testing conditions and also slight increase of carbon monoxides and carbon dioxides compared to rapeseed oil. Largest decrease of NOx was observed during 90 km/h and cycle IM-240 reaching almost 24% reduction for 20DEE and 30DEE in comparison to neat RO.
Linear Active Disturbance Rejection Control of Grid-Connected Photovoltaic Inverter Based on Deviation Control Principle
Authors: Zhou Xuesong , Wang Jiayao , Ma Youjie
Published: July 2020

Photovoltaic grid-connected power generation systems are easily affected by external factors, and their anti-interference performance is poor. For example, changes in illumination and fluctuations in the power grid affect the operation ability of the system. Linear active disturbance rejection control (LADRC) can extract the “summation disturbance” information from the system and eliminate the disturbance at the fastest speed by controlling the signal before it affects the final output of the system. In this paper, an improved linear ADRC based on the principle of deviation control is proposed, and the voltage outer loop is controlled by an improved LADRC. This improved LADRC takes the deviation between each state variable and its observed value as the regulation basis for each state variable of the linear extended state observer (LESO). Based on the analysis of the bode diagram in the frequency domain, it can be concluded that, compared with the unimproved LADRC, the new LADRC has better disturbance rejection performance. The simulation results show that the control performance of the new, improved LADRC is better than that of the unimproved LADRC under different operating conditions, and it has better stability performance and anti-disturbance performance.
A Comparison of the Structure and Properties of Opaque and Semi-Transparent NIP/PIN-Type Scalable Perovskite Solar Cells
Authors: Lemercier Thibault , Perrin Lara , Planès Emilie , Berson Solenn , Flandin Lionel
Published: July 2020

For over a decade, single-junction perovskite solar cells (PSCs) have experienced an unprecedent increase in efficiencies and even offer opportunities to surpass the Shockley–Queisser limit in multijunction configuration. There is consequently an intense need for easily processable semi-transparent PSCs as a basis of affordable tandems. The current study reports the comparison of negative-intrinsic-positive (NIP) and positive-intrinsic-negative (PIN) architectures based on CH3NH3PbI3{Cl}-based perovskite. Both devices could be prepared with the same N-type (SnO2 nanoparticles) and P-type (poly-triarylamine (PTAA) polymer) materials. Each layer (except for electrodes) was deposited using solvent-based low temperature processes, contrasting with other literature studies, especially SnO2 for PIN-type purposes. A thorough experimental comparison of the two architectures reveals rather similar optical and structural properties for perovskites, whether deposited on an N- or P-type underlayer, with also comparable efficiencies in the final devices. A compatible deposition process for sputtered indium tin oxide (ITO) as a semi-transparent electrode was then performed for both architectures. Upon varying the illuminated devices’ side, the semi-transparent cells exhibited different photocurrent behaviors, the magnitude of which depended on the device’s architecture. In conclusion, despite slightly better efficiencies for the semi-transparent NIP-type devices, the semi-transparent PIN-type counterparts also appear to be optically attractive for (two-terminal) tandem applications.
Importance of Temporal Scale in Assessing Changes in Soil-Water Storage in Apple Orchards on the Chinese Loess Plateau
Authors: Mu Yan , Wang Di , Wang Yanping
Published: July 2020

Knowledge of changes in soil-water storage (SWS) at multiple scales in apple orchards is important for formulating policies for the scientific management and sound planning of apple plantations on the Loess Plateau in China. In this study, we measured precipitation, partitioned evapotranspiration (ET) into canopy interception, transpiration, and soil evaporation, and calculated the changes in SWS using the water-balance method at multiple scales in two neighbouring apple orchards (8 and 18 years old) on the Loess Plateau from May to September in 2013, 2014, 2015, and 2016. The results showed that ET was consistently lower for the 8- than the 18-year-old orchard in each year at the same scale (p < 0.05). The changes in SWS differed between the two orchards at the same scale, but the trends of change were similar in each year. The trend of the change in SWS at the same scale differed amongst the years for both orchards. The maximum supply of water from soil reservoirs for the two orchards also differed at different scales in each year and was higher at a daily cumulative scale than a monthly and annual scale in 2013, 2014, and 2016. The daily cumulative scale was thus a more suitable scale for representing the maximum contribution of the soil reservoir to supply water for the growth of the orchards during the study periods. Changes in SWS at a daily cumulative scale should be considered when assessing the effect of apple orchards on regional soil reservoirs on the Loess Plateau or in other water-limited regions.
The Effect of Alternative Forest Management Models on the Forest Harvest and Emissions as Compared to the Forest Reference Level
Authors: Gusti Mykola , Di Fulvio Fulvio , Biber Peter , Korosuo Anu , Forsell Nicklas
Published: July 2020

Background and Objectives: Under the Paris Agreement, the European Union (EU) sets rules for accounting the greenhouse gas emissions and removals from forest land (FL). According to these rules, the average FL emissions of each member state in 2021–2025 (compliance period 1, CP1) and in 2026–2030 (compliance period 2, CP2) will be compared to a projected forest reference level (FRL). The FRL is estimated by modelling forest development under fixed forest management practices, based on those observed in 2000–2009. In this context, the objective of this study was to estimate the effects of large-scale uptake of alternative forest management models (aFMMs), developed in the ALTERFOR project (Alternative models and robust decision-making for future forest management), on forest harvest and forest carbon sink, considering that the proposed aFMMs are expanded to most of the suitable areas in EU27+UK and Turkey. Methods: We applied the Global Forest Model (G4M) for projecting the harvest and sink with the aFMMs and compared our results to previous FRL projections. The simulations were performed under the condition that the countries should match the harvest levels estimated for their FRLs as closely as possible. A representation of such aFMMs as clearcut, selective logging, shelterwood logging and tree species change was included in G4M. The aFMMs were modeled under four scenarios of spatial allocation and two scenarios of uptake rate. Finally, we compared our results to the business as usual. Results: The introduction of the aFMMs enhanced the forest sink in CP1 and CP2 in all studied regions when compared to the business as usual. Conclusions: Our results suggest that if a balanced mixture of aFMMs is chosen, a similar level of wood harvest can be maintained as in the FRL projection, while at the same time enhancing the forest sink. In particular, a mixture of multifunctional aFMMs, like selective logging and shelterwood, could enhance the carbon sink by up to 21% over the ALTERFOR region while limiting harvest leakages.
Preliminary Evidence for Domestication Effects on the Genetic Diversity of Guazuma crinita in the Peruvian Amazon
Authors: Tuisima-Coral Lady Laura , Hlásná Čepková Petra , Weber John C. , Lojka Bohdan
Published: July 2020

Guazuma crinita, a fast-growing timber tree species, was chosen for domestication in the Peruvian Amazon because it can be harvested at an early age and it contributes to the livelihood of local farmers. Although it is in an early stage of domestication, we do not know the impact of the domestication process on its genetic resources. Amplified fragment length polymorphic (AFLP) fingerprints were used to estimate the genetic diversity of G. crinita populations in different stages of domestication. Our objectives were (i) to estimate the level of genetic diversity in G. crinita using AFLP markers, (ii) to describe how the genetic diversity is distributed within and among populations and provenances, and (iii) to assess the genetic diversity in naturally regenerated, cultivated and semi-domesticated populations. We generated fingerprints for 58 leaf samples representing eight provenances and the three population types. We used seven selective primer combinations. A total of 171 fragments were amplified with 99.4% polymorphism at the species level. Nei’s genetic diversity and Shannon information index were slightly higher in the naturally regenerated population than in the cultivated and semi-domesticated populations (He = 0.10, 0.09 and 0.09; I = 0.19, 0.15 and 0.16, respectively). The analysis of molecular variation showed higher genetic diversity within rather than among provenances (84% and 4%, respectively). Cluster analysis (unweighted pair group method with arithmetic mean) and principal coordinate analysis did not show correspondence between genetic and geographic distance. There was significant genetic differentiation among population types (Fst = 0.12 at p ˂ 0.001). The sample size was small, so the results are considered as preliminary, pending further research with larger sample sizes. Nevertheless, these results suggest that domestication has a slight but significant effect on the diversity levels of G. crinita and this should be considered when planning a domestication program.
Numerical Solution of Open-Loop Nash Differential Games Based on the Legendre Tau Method
Authors: Dehghan Banadaki Mojtaba , Navidi Hamidreza
Published: July 2020

In this paper, an efficient implementation of the Tau method is presented for finding the open-loop Nash equilibrium of noncooperative nonzero-sum two-player differential game problems with a finite-time horizon. Regarding this approach, the two-point boundary value problem derived from Pontryagin’s maximum principle is reduced to a system of algebraic equations that can be solved numerically. Finally, a differential game arising from bioeconomics among firms harvesting a common renewable resource is included to illustrate the accuracy and efficiency of the proposed method and a comparison is made with the result obtained by fourth order Runge–Kutta method.
Neogene Tree Trunk Fossils from the Meshgin Shahr Area, Northwest Iran
Authors: Mustoe George E. , Abbassi Nasrollah , Hosseini Afsaneh , Mahdizadeh Yousef
Published: July 2020

In 2016, an extensive fossil forest was discovered near Meshgin Shahr, northwest Iran. Silicified tree trunks occur in Miocene fluvial sediments and at multiple stratigraphic levels within a 27-m thick sequence of Pleistocene volcaniclastics. The Miocene trunks likely represent stream transport. Pleistocene examples originated during repeated eruptive events when volcaniclastic sediments buried a standing forest. The site, informally named Meshgin Shahr Fossil Forest, was registered in 2017 as a national natural monument by the Iranian Cultural, Handicraft and Tourism Organization. To date, 16 fossilized trunks have been found, all but one of them representing gymnosperms. The ancient coniferous forest was very different from modern forests in Iran and adjacent Azerbaijan, a result of climatic changes that were principally caused by the demise of the Paratethys Sea and by rain shadow effects caused by the uplift of the Alborz and Zagros mountain ranges. X-ray diffraction patterns reveal that woods from the fossil forest contain three types of silica: opal-CT, pure quartz, and a mixture of opal-CT and quartz. In addition, optical photomicrographs show the abundant presence of amorphous opal-A. Mineralogic variations occur among different fossil trees and within a single trunk. These silica polymorphs resulted from a combination of processes: silica minerals precipitated in multiple episodes under differing geochemical conditions and the diagenetic transformation of an opaline parent material.
The View from the Sea: The Power of a Blue Comparative Literature
Authors: Ritson Katie
Published: July 2020

This paper advocates for a blue comparative literature that uses the view from the sea to provide new axes for comparison. Roy Jacobsen’s De usynlige (The Unseen, 2013) and Sarah Moss’s Night Waking (2011) explore subsistence lives on small islands in the northern Atlantic at different moments in the past, when inhabitants were dependent on the sea for food and transport. By looking at them together, as texts linked by their engagement with the physical world of the northern Atlantic, the two novels show how marginal populations on small islands can represent a space for the imagination of the human past and future in the Anthropocene.
The Relationship between Environmental Regulation and Green Total Factor Productivity in China: An Empirical Study Based on the Panel Data of 177 Cities
Authors: Zhao Mingliang , Liu Fangyi , Sun Wei , Tao Xin
Published: July 2020

Promoting the coordinated development of industrialization and the environment is a goal pursued by all of the countries of the world. Strengthening environmental regulation (ER) and improving green total factor productivity (GTFP) are important means to achieving this goal. However, the relationship between ER and GTFP has been debated in the academic circles, which reflects the complexity of this issue. This paper empirically tested the relationship between ER and GTFP in China by using panel data and a systematic Gaussian Mixed Model (GMM) of 177 cities at the prefecture level. The research shows that the relationship between ER and GTFP is complex, which is reflected in the differences and nonlinearity between cities with different monitoring levels and different economic development levels. (1) The relationship between ER and GTFP is linear and non-linear in different urban groups. A positive linear relationship was found in the urban group with high economic development level, while a U-shaped nonlinear relationship was found in other urban groups. (2) There are differences in the inflection point value and the variable mean of ER in different urban groups, which have different promoting effects on GTFP. In key monitoring cities and low economic development level cities, the mean value of ER had not passed the inflection point, and ER was negatively correlated with GTFP. The mean values of ER variables in the whole sample, the non-key monitoring and the middle economic development level cities had all passed the inflection point, which gradually promoted the improvement of GTFP. (3) Among the control variables of the different city groups, science and technology input and the financial development level mainly had positive effects on GTFP, while foreign direct investment (FDI) and fixed asset investment variables mainly had negative effects.
Moving Average Based Index for Judging the Peak of the COVID-19 Epidemic
Authors: He Yunting , Wang Xiaojin , He Hao , Zhai Jing , Wang Bingshun
Published: July 2020

A pneumonia outbreak caused by a novel coronavirus (COVID-19) has spread around the world. A total of 2,314,621 laboratory-confirmed cases, including 157,847 deaths (6.8%) were reported globally by 20 April 2020. Common symptoms of COVID-19 pneumonia include fever, fatigue, and dry cough. Faced with such a sudden outbreak of emerging infectious disease, traditional models for predicting the peak of the epidemic often show inconsistent results. With the aim to timely judge the epidemic peak and provide support for decisions for resuming production and returning to normal life based on publicly reported data, we used a seven-day moving average of log-transformed daily new cases (LMA) to establish a new index named the “epidemic evaluation index” (EEI). We used SARS epidemic data from Hong Kong to verify the practicability of the new index, and then applied it to the COVID-19 epidemic analysis. The results showed that the epidemic peaked, respectively, on 9 February and 5 February 2020, in Hubei Province and other provinces in China. The proposed index can be applied for judging the epidemic peak. While the global COVID-19 epidemic reached its peak in the middle of April, the epidemic peaks in some countries have not yet appeared. Global and united efforts are still needed to eventually eliminate the epidemic.