bluuebunny/crossref_metadata_2025 huggingface dataset:
Bidirectional Electric-Induced Conductance Based on GeTe/Sb2Te3 Interfacial Phase Change Memory for Neuro-Inspired Computing
Authors: Kang Shin-young , Jin Soo-min , Lee Ju-young , Woo Dae-seong , Shim Tae-hun , Nam In-ho , Park Jea-gun , Sutou Yuji , Song Yun-heub
Published: November 2021

Corresponding to the principles of biological synapses, an essential prerequisite for hardware neural networks using electronics devices is the continuous regulation of conductance. We implemented artificial synaptic characteristics in a (GeTe/Sb2Te3)16 iPCM with a superlattice structure under optimized identical pulse trains. By atomically controlling the Ge switch in the phase transition that appears in the GeTe/Sb2Te3 superlattice structure, multiple conductance states were implemented by applying the appropriate electrical pulses. Furthermore, we found that the bidirectional switching behavior of a (GeTe/Sb2Te3)16 iPCM can achieve a desired resistance level by using the pulse width. Therefore, we fabricated a Ge2Sb2Te5 PCM and designed a pulse scheme, which was based on the phase transition mechanism, to compare to the (GeTe/Sb2Te3)16 iPCM. We also designed an identical pulse scheme that implements both linear and symmetrical LTP and LTD, based on the iPCM mechanism. As a result, the (GeTe/Sb2Te3)16 iPCM showed relatively excellent synaptic characteristics by implementing a gradual conductance modulation, a nonlinearity value of 0.32, and 40 LTP/LTD conductance states by using identical pulse trains. Our results demonstrate the general applicability of the artificial synaptic device for potential use in neuro-inspired computing and next-generation, non-volatile memory.
Research on Compound Sliding Mode Control of a Permanent Magnet Synchronous Motor in Electromechanical Actuators
Authors: Lin Jiachun , Zhao Yuteng , Zhang Pan , Wang Junjie , Su Hao
Published: November 2021

In order to improve the response speed and disturbance rejection ability of a permanent magnet synchronous motor (PMSM) in an electromechanical actuator (EMA), a compound sliding mode control (CSMC) is proposed. The CSMC consists of a sliding mode controller with a new reaching law and disturbance observer based on a symmetric S-type function. The stability of the CSMC is analyzed using the Lyapunov stability analysis. The effectiveness of the CSMC is confirmed by the Simulink simulation, and experiments were conducted on a semi-physical platform. The results obtained by comparing the CSMC with the proportional integral (PI) control and traditional sliding mode control show that the CSMC has a faster response and stronger disturbance rejection ability and reduces chattering.
A Class of Reduced-Order Regenerator Models
Authors: Paul Raphael , Hoffmann Karl Heinz
Published: November 2021

We present a novel class of reduced-order regenerator models that is based on Endoreversible Thermodynamics. The models rest upon the idea of an internally reversible (perfect) regenerator, even though they are not limited to the reversible description. In these models, the temperatures of the working gas that alternately streams out on the regenerator’s hot and cold sides are defined as functions of the state of the regenerator matrix. The matrix is assumed to feature a linear spatial temperature distribution. Thus, the matrix has only two degrees of freedom that can, for example, be identified with its energy and entropy content. The dynamics of the regenerator is correspondingly expressed in terms of balance equations for energy and entropy. Internal irreversibilities of the regenerator can be accounted for by introducing source terms to the entropy balance equation. Compared to continuum or nodal regenerator models, the number of degrees of freedom and numerical effort are reduced considerably. As will be shown, instead of the obvious choice of variables energy and entropy, if convenient, a different pair of variables can be used to specify the state of the regenerator matrix and formulate the regenerator’s dynamics. In total, we will discuss three variants of this endoreversible regenerator model, which we will refer to as ES, EE, and EEn-regenerator models.
Use of Energy Storage to Reduce Transmission Losses in Meshed Power Distribution Networks
Authors: Mikulski Stanisław , Tomczewski Andrzej
Published: November 2021

One of the challenges which the electrical power industry has been facing nowadays is the adaptation of the power system to the energy transition which has been taking place before our very eyes. With the increasing share of Renewable Energy Sources (RES) in energy production, the development of electromobility and the increasing environmental awareness of the society, the power system must constantly evolve to meet its expectations regarding a reliable electricity supply. This paper presents the issue of deploying energy storage facilities in the meshed power distribution network in order to reduce transmission losses. The presented multi-objective approach provides an opportunity to solve this issue using multi-objective optimisation methods such as Non-dominated Sorting Genetic Algorithm II (NSGA-II), Multiobjective Particle Swarm Optimization (MPSO) and Biased Random Keys Genetic Algorithm (BRKGA). In order to increase the efficiency optimisation process, the Pareto Adaptive ϵ-dominance (paϵ-dominance) was used. It was demonstrated that the use of energy storages that cooperate with RES can significantly reduce transmission losses.
The Importance of Wake Meandering on Wind Turbine Fatigue Loads in Wake
Authors: Rinker Jennifer Marie , Soto Sagredo Esperanza , Bergami Leonardo
Published: November 2021

Considering loads when optimizing wind-farm layouts or designing farm-control strategies is important, but the computational cost of using high-fidelity wake models in the loop can be prohibitively high. Using simpler models that consider only the spatial variation of turbulence statistics is a tempting alternative, but the accuracy of these models with respect to the aeroelastic response is not well understood. This paper therefore highlights the effect of replacing wake meandering with spatially varying statistics (“profile functions”) in the inflow to a downstream turbine. Profile functions at different downstream and lateral locations are extracted from a large-eddy simulation with an upstream turbine and compared with two lower-fidelity models: one that prescribes both the mean and standard deviation of the turbulence and one that prescribes only the mean. The aeroelastic response of an NREL 5 MW wind turbine is simulated with the three different wake-model fidelities, and various quantities of interest are compared. The mean values for the power and rotor speed for the medium-and low-fidelity model match well, but the accuracy of the fatigue loads varies greatly depending on the load channel. Prescribing the profile function for the standard deviation is only beneficial for the tower-base fore-aft moment; all other DELs had similar accuracies for both the medium- and low-fidelity models. The paper concludes that blade DELs can be estimated using these simple models with some accuracy, but care should be taken with the load channels related to the shaft torsion and tower-base fore-aft bending moment.
An Analytical Modelling of Demand for Driving Torque of a Wheelchair with Electromechanical Drive
Authors: Kukla Mateusz , Wieczorek Bartosz , Warguła Łukasz , Górecki Jan , Giedrowicz Marcin
Published: November 2021

This study aimed at analysing the influence of the position of the centre of gravity variability and the movement velocity on the demand for a torque and work time coverage of a wheelchair with an electromechanical drive. The variable parameter in the study was the configuration of the wheelchair, namely changes in the position of the batteries which changed the weight distribution. An analytical model describing the demand for torque was used in the analysis. The set of equations was introduced into the numerical calculation software. Simulations were carried out which allowed it to analyse selected parameters of the wheelchair dynamics. An increase in the torque demand was observed due to the increase in the mass of the system from 427.7 N to 533.1 N, ranging from 6.1% to 31.6% at the simulated velocity v7 = 4.2 m/s. The increase in the demand for torque due to the increase in velocity of the wheelchair from v2 = 1.05 m/s to v7 = 4.2 m/s ranged from 25.9% to 31.6% compared to the reference velocity v1 = 0.525 m/s. The centre of gravity of the wheelchair structure localization has a non-linear impact on the analysed values. At the same time, it was not possible to define its nature—this issue remains open and requires further research.
A New Strategy for Pre-Selecting Gas Wells for the Water Shut-Off Treatment Based on Geological Integrated Data
Authors: Falkowicz Sławomir , Urbaniec Andrzej , Stadtműller Marek , Majkrzak Marcin
Published: November 2021

This article presents a new analytical procedure for pre-selecting gas wells for water shut-off treatments based on available at hand results of an analysis of integrated geological, reservoir and exploitation data. Attention was paid to assess the possibility of the appearance of cross flows between layers in the near wellbore zone. Their appearance always eliminated the well as a candidate for the treatment. The basis for assessing the possibility of the emergence of cross flows was based on the assessment of the presence or absence of impermeable barriers (e.g., shales or anhydrite) in intervals, completed by perforation. For this assessment, well logging data were used, which were carried out in different years with the use of various types of probes. Based on modified quantitative and qualitative interpretation techniques, permeable and impermeable layers were separated in the analysed borehole sections. In some cases, in the absence of other data, well logs are the only source of information from which a vertical profile of horizontal permeability can be made. The article describes the verification process carried out for the eight wells situated in the area of the Carpathian Foredeep, which have been preselected by the operator. As part of this procedure, the available geological, reservoir and exploitation data were used, and a preliminary assessment of the possibility of implementing the obtained results into other wells and gas fields in the area of the Carpathian Foredeep was carried out. On the basis of the well ranking, two out of the eight analysed wells were recommended as candidates for water shut-off treatment.
Uncertainty Quantification of the PHEBUS FPT-1 Test Modelling Results
Authors: Elsalamouny Noura , Kaliatka Tadas
Published: November 2021

One of the biggest experimental programs helping to improve nuclear installation safety is PHEBUS, an international cooperative research program that provides data for validating computer codes dedicated to the analysis of severe accidents and their calculation results. In the European Union, HORIZON 2020 EURATOM project MUSA (Management and Uncertainties of Severe Accidents) is in progress. Modelling of the PHEBUS FPT-1 test within the frame of this project is provided by project partners using different severe accident codes. Uncertainty quantification of the received results is provided using different methods and statistical tools. The Lithuanian Energy Institute (LEI) is taking part in the MUSA project and this uncertainty exercise. LEI is using the RELAP/SCDAPSIM severe accident code together with GRS methodology and SUSA statistical tool to evaluate the uncertainties of modelling results of PHEBUS FPT-1 test. In this article, uncertainty quantification of the PHEBUS FPT-1 test modelling results provided by LEI in the frame of MUSA project are presented. Provided uncertainty analysis for total hydrogen generation showed that upper and lower uncertainty limits are bounding the experimental data. At the end of the calculation, the upper and lower uncertainty limits of calculations are within the band of experimental uncertainties. Uncertainty analysis for Cs/I release fraction showed that uncertainty limits are bounding experimental data until the middle of the heat-up phase, but at the end of the experiment, the calculated upper uncertainty limit is lower than the experimental data. Results of sensitivity analysis showed that the thermal conductivity of the ZrO2 layer of the shroud has the dominant influence on hydrogen generation and Cs/I release fraction calculation results. Other important parameters are changing at the different experimental phases. In the future, it is planned to update the RELAP/SCDAPSIM model for the PHEBUS FPT-1 test using the results of the provided sensitivity analysis. This will allow a better agreement with experimental data.
Contribution of Oxide Supports in Nickel-Based Catalytic Elimination of Greenhouse Gases and Generation of Syngas
Authors: Khan Wasim Ullah , Khan Mohammad Rizwan , Busquets Rosa , Ahmad Naushad
Published: November 2021

Carbon dioxide and/or dry methane reforming serves as an effective pathway to mitigate these greenhouse gases. This work evaluates different oxide supports including alumina, Y-zeolite and H-ZSM-5 zeolite for the catalysis of dry reforming methane with Nickel (Ni). The composite catalysts were prepared by impregnating the supports with Ni (5%) and followed by calcination. The zeolite supported catalysts exhibited more reducibility and basicity compared to the alumina supported catalysts, this was assessed with temperature programmed reduction using hydrogen and desorption using carbon dioxide. The catalytic activity, in terms of CH4 conversion, indicated that 5 wt% Ni supported on alumina exhibited higher CH4 conversion (80.5%) than when supported on Y-zeolite (71.8%) or H-ZSM-5 (78.5%). In contrast, the H-ZSM-5 catalyst led to higher CO2 conversion (87.3%) than Y-zeolite (68.4%) and alumina (83.9%) supported catalysts. The stability tests for 9 h time-on-stream showed that Ni supported with H-ZSM-5 had less deactivation (just 2%) due to carbon deposition. The characterization of spent catalysts using temperature programmed oxidation (O2-TPO), X-ray diffraction (XRD) and thermo-gravimetric analysis (TGA) revealed that carbon deposition was a main cause of deactivation and that it occurred in the lowest degree on the Ni H-ZSM-5 catalyst.
Banks’ Energy Behavior: Impacts of the Disparity in the Quality and Quantity of the Disclosures
Authors: Klimontowicz Monika , Losa-Jonczyk Anna , Zacny Bogna
Published: November 2021

Environmental, social, and governance (ESG) factors are becoming increasingly relevant for banks as entities that play an essential role in supporting the development of enterprises, individuals and the whole economy. The paper aims to evaluate the impact of the ESC directive on banks’ energy behavior disclosures, explicitly relating to behaviors towards energy use and its impact on banks’ performance. We developed a methodology to provide the objective characteristic of banks’ energy behavior. In the paper, the banks’ energy behavior (BEB) index is calculated using sixteen indicators, followed by further analysis of its relationship with banks’ performance measured by indexes referring to banks’ characteristics, efficiency, and solvency. Our results are based on an analysis of the disclosures in nonfinancial reports. We find correlations that indicate that banks that are more likely to demonstrate energy behaviors (with a high BEB index) are those that better manage their costs and are more attractive for investors. Further analysis suggests that banks’ energy behavior has no statistically significant correlation with other performance indicators. We find only limited evidence of statistical associations between energy behavior and the net interest margin. We argue that our results contribute to the significant body of literature supporting the role of ESG in active engagement with energy issues.
A Multiscale Electricity Price Forecasting Model Based on Tensor Fusion and Deep Learning
Authors: Xie Xiaoming , Li Meiping , Zhang Du
Published: November 2021

The price of electricity is an important factor in the electricity market. Accurate electricity price forecasting (EPF) is very important to all competing electricity market parties. Decision-making in the electricity market is highly dependent on electricity prices, making an EPF model an important part of the orderly and efficient operation of the electricity market. Especially during the COVID-19 pandemic, the prices of raw materials for electricity production, such as coal, have risen sharply. Forecasting electricity prices has become particularly important. Currently, existing EPF prediction models face two main challenges: First, how to integrate multiscale electricity price data to obtain a higher prediction accuracy. Second, how to solve the problem of data noise caused by the fusion of EPF samples and multiscale data. To solve the above problems, we innovatively propose a tensor decomposition method to integrate multiscale electricity price data and use L1 regularization and wavelet transform to remove data noise. In general, this paper proposes a deep learning EPF prediction model, named the WT_TDLSTM model, based on tensor decomposition, a wavelet transform, and long short-term memory (LSTM). Among them, the LSTM method is used to predict electricity prices. We conducted experiments on three datasets. The experimental results of three data prove that the WT_TDLSTM model is better than the compared EPF model. The indicators of MSE and RMSE are 33.65–99.97% better than the comparison model. We believe that the WT_TDLSTM model is a good supplement to the EPF model.
Fatty Acid Profile of Microalgal Oils as a Criterion for Selection of the Best Feedstock for Biodiesel Production
Authors: Hawrot-Paw Małgorzata , Ratomski Patryk , Koniuszy Adam , Golimowski Wojciech , Teleszko Mirosława , Grygier Anna
Published: November 2021

Microalgae are considered to be potentially attractive feedstocks for biodiesel production, mainly due to their fast growth rate and high oil content accumulated in their cells. In this study, the suitability for biofuel production was tested for Chlorella vulgaris, Chlorella fusca, Oocystis submarina, and Monoraphidium strain. The effect of nutrient limitation on microalgae biomass growth, lipid accumulation, ash content, fatty acid profile, and selected physico-chemical parameters of algal biodiesel were analysed. The study was carried out in vertical tubular photobioreactors of 100 L capacity. The highest biomass content at 100% medium dose was found for Monoraphidium 525 ± 29 mg·L−1. A 50% reduction of nutrients in the culture medium decreased the biomass content by 23% for O. submarina, 19% for Monoraphidium, 13% for C. vulgaris and 9% for C. fusca strain. Nutrient limitation increased lipid production and reduced ash content in microalgal cells. The highest values were observed for Oocystis submarina, with a 90% increase in lipids and a 45% decrease in ash content in the biomass under stress conditions. The fatty acid profile of particular microalgae strains was dominated by palmitic, oleic, linoleic, and linoleic acids. Nutrient stress increased the amount of saturated and unsaturated fatty acids affecting the quality of biodiesel, but this was determined by the type of strain.
Development of Stable Mixed Microbiota for High Yield Power to Methane Conversion
Authors: Szuhaj Márk , Wirth Roland , Bagi Zoltán , Maróti Gergely , Rákhely Gábor , Kovács Kornél L.
Published: November 2021

The performance of a mixed microbial community was tested in lab-scale power-to-methane reactors at 55 °C. The main aim was to uncover the responses of the community to starvation and stoichiometric H2/CO2 supply as the sole substrate. Fed-batch reactors were inoculated with the fermentation effluent of a thermophilic biogas plant. Various volumes of pure H2/CO2 gas mixtures were injected into the headspace daily and the process parameters were followed. Gas volumes and composition were measured by gas-chromatography, the headspace was replaced with N2 prior to the daily H2/CO2 injection. Total DNA samples, collected at the beginning and end (day 71), were analyzed by metagenome sequencing. Low levels of H2 triggered immediate CH4 evolution utilizing CO2/HCO3− dissolved in the fermentation effluent. Biomethanation continued when H2/CO2 was supplied. On the contrary, biomethane formation was inhibited at higher initial H2 doses and concomitant acetate formation indicated homoacetogenesis. Biomethane production started upon daily delivery of stoichiometric H2/CO2. The fed-batch operational mode allowed high H2 injection and consumption rates albeit intermittent operation conditions. Methane was enriched up to 95% CH4 content and the H2 consumption rate attained a remarkable 1000 mL·L−1·d−1. The microbial community spontaneously selected the genus Methanothermobacter in the enriched cultures.
3DHIP-Calculator—A New Tool to Stochastically Assess Deep Geothermal Potential Using the Heat-In-Place Method from Voxel-Based 3D Geological Models
Authors: Piris Guillem , Herms Ignasi , Griera Albert , Colomer Montse , Arnó Georgina , Gomez-Rivas Enrique
Published: November 2021

The assessment of the deep geothermal potential is an essential task during the early phases of any geothermal project. The well-known “Heat-In-Place” volumetric method is the most widely used technique to estimate the available stored heat and the recoverable heat fraction of deep geothermal reservoirs at the regional scale. Different commercial and open-source software packages have been used to date to estimate these parameters. However, these tools are either not freely available, can only consider the entire reservoir volume or a specific part as a single-voxel model, or are restricted to certain geographical areas. The 3DHIP-Calculator tool presented in this contribution is an open-source software designed for the assessment of the deep geothermal potential at the regional scale using the volumetric method based on a stochastic approach. The tool estimates the Heat-In-Place and recoverable thermal energy using 3D geological and 3D thermal voxel models as input data. The 3DHIP-Calculator includes an easy-to-use graphical user interface (GUI) for visualizing and exporting the results to files for further postprocessing, including GIS-based map generation. The use and functionalities of the 3DHIP-Calculator are demonstrated through a case study of the Reus-Valls sedimentary basin (NE, Spain).
Computational Studies of Air-Mist Spray Cooling in Continuous Casting
Authors: Anisiuba Vitalis , Ma Haibo , Silaen Armin , Zhou Chenn
Published: November 2021

Due to the significant reduction in water droplet size caused by the strong air-water interaction in the spray nozzle, air-mist spray is one of the promising technologies for achieving high-rate heat transfer. This study numerically analyzed air-mist spray produced by a flat-fan atomizer using three-dimensional computational fluid dynamics simulations, and a multivariable linear regression was used to develop a correlation to predict the heat transfer coefficient using the casting operating conditions such as air-pressure, water flow rate, casting speed, and standoff distance. A four-step simulation approach was used to simulate the air-mist spray cooling capturing the turbulence and mixing of the two fluids in the nozzle, droplet formation, droplet transport and impingement heat transfer. Validations were made on the droplet size and on the VOF-DPM model which were in good agreement with experimental results. A 33% increase in air pressure increases the lumped HTC by 3.09 ± 2.07% depending on the other casting parameters while an 85% increase in water flow rate reduces the lumped HTC by 4.61 ± 2.57%. For casting speed, a 6.5% decrease in casting speed results in a 1.78 ± 1.42% increase in the lumped HTC. The results from this study would provide useful information in the continuous casting operations and optimization.
Feasibility of Low Carbon Renewable Energy City Integrated with Hybrid Renewable Energy Systems
Authors: Kim Min-Hwi , Kim Deuk-Won , Lee Dong-Won
Published: November 2021

This study evaluated the energy saving potential of renewable energy generation systems based on integrated solar energy in an urban environment. The solar city concept was implemented using photovoltaic (PV) and solar thermal systems. As a case study, the Sejong national pilot smart city in South Korea was selected to evaluate the renewable energy penetration rate. For evaluating the proposed renewable energy systems, the electrical and thermal loads of the smart city were estimated using field measurement data. Then, the renewable energy penetration rate of the city was evaluated. The HomerPro software was used to analyze the PV generation and operating energy consumption of the natural gas (NG) generator with a district heating network. The thermal load-supporting potential of the solar thermal system was estimated using the TRNSYS software. The results showed that the proposed urban integrated renewable energy system could meet over 30% of the renewable energy penetration rate and the levelized cost of energy and total net present cost was 7% lower than the base case system (i.e., NG generator). The proposed system also exhibited 38% less CO2 emissions than the base case system.
Estimating Mean Surface Backscatter from GPM Surface Backscatter Observations
Authors: Durden Stephen L.
Published: November 2021

The radar on the Global Precipitation Measurement (GPM) mission observes precipitation at 13.6 GHz (Ku-band) and 35.6 GHz (Ka-band) and also receives echoes from the earth’s surface. Statistics of surface measurements for non-raining conditions are saved in a database for later use in estimating the precipitation path-integrated attenuation. Previous work by Meneghini and Jones (2011) showed that while averaging over larger latitude/longitude bins increase the number of samples, it can also increase sample variance due to spatial inhomogeneity in the data. As a result, Meneghini and Kim (2017) proposed a new, adaptive method of database construction, in which the number of measurements averaged depends on the spatial homogeneity. The purpose of this work is to re-visit previous, single-frequency results using dual-frequency data and optimal interpolation (kriging). Results include that (1) temporal inhomogeneity can create similar results as spatial, (2) Ka-band behavior is similar to Ku-band, (3) the Ku-/Ka-band difference has less spatial inhomogeneity than either band by itself, and (4) kriging and the adaptive method can reduce the sample variance. The author concludes that finer spatial and temporal resolution is necessary in constructing the database for single frequencies but less so for the Ku-/Ka-band difference. The adaptive approach reduces sample standard deviation with a relatively modest computational increase.
Turning AGN Bubbles into Radio Relics with Sloshing: Modeling CR Transport with Realistic Physics
Authors: ZuHone John , Ehlert Kristian , Weinberger Rainer , Pfrommer Christoph
Published: November 2021

Radio relics are arc-like synchrotron sources at the periphery of galaxy clusters, produced by cosmic-ray electrons in a μG magnetic field, which are believed to have been (re-)accelerated by merger shock fronts. However, not all relics appear at the same location as shocks as seen in the X-ray. In a previous work, we suggested that the shape of some relics may result from the pre-existing spatial distribution of cosmic-ray electrons, and tested this hypothesis using simulations by launching AGN jets into a cluster atmosphere with sloshing gas motions generated by a previous merger event. We showed that these motions could transport the cosmic ray-enriched material of the AGN bubbles to large radii and stretch it in a tangential direction, producing a filamentary shape resembling a radio relic. In this work, we improve our physical description for the cosmic rays by modeling them as a separate fluid which undergoes diffusion and Alfvén losses. We find that, including this additional cosmic ray physics significantly diminishes the appearance of these filamentary features, showing that our original hypothesis is sensitive to the modeling of cosmic ray physics in the intracluster medium.
Structural and Chemical Properties of Geopolymer Gels Incorporated with Neodymium and Samarium
Authors: Nenadović Snežana S. S. , Kljajević Ljiljana M. , Ivanović Marija M. , Mirković Miljana M. , Radmilović Nadežda , Rakočević Lazar Z. , Nenadović Miloš T.
Published: November 2021

The present work was focused on doping of 1% and 5% both of Nd2O3 and Sm2O3 in geopolymer gels. One of the main goals was to determine the influence of the behavior of Nd and Sm as dopants and structural nanoparticles changes of the final geopolymer formed. It is shown that the disorder formed by alkali activation of metakaolin can accommodate the rare earth cations Nd3+ and Sm3+ into their aluminosilicate framework structure. The main geopolymerization product identified in gels is Al-rich (Na)-AS-H gel comprising Al and Si in tetrahedral coordination. Na+ ions were balancing the negative charge resulting from Al3+ in tetrahedral coordination. The changes in the structures of the final product (geopolymer/Nd2O3; Sm2O3), has been characterized using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM) analysis with energy dispersive spectrometry (EDS). Nucleation at the seed surfaces leads to the formation of phase-separated gels from rare earth phase early in the reaction process. It is confirmed that Nd and Sm have been shown to form unstable hydroxides Nd(OH)3 and Sm(OH)3 that are in equilibrium with the corresponding oxides.
Quantitative Phosphoproteomics of cipk3/9/23/26 Mutant and Wild Type in Arabidopsis thaliana
Authors: Yin Ziyi , Shi Jisen , Zhen Yan
Published: November 2021

CBL-interacting protein kinases 3/9/23/26 (CIPK3/9/23/26) are central regulation components of magnesium ion homeostasis. CBL2/3 interacts with CIPK3/9/23/26, which phosphorylates their downstream targets, suggesting that protein phosphorylation is a key factor influencing the maintenance of cellular magnesium homeostasis in higher plants. The cipk3/9/23/26 quadruple mutant is very sensitive to high levels of magnesium. In this study, TMT quantitative phosphoproteomics were used to compare the global variations in phosphoproteins in wild type and cipk3/9/23/26 quadruple mutant seedlings of Arabidopsis thaliana, and 12,506 phosphorylation modification sites on 4537 proteins were identified, of which 773 phosphorylated proteins exhibited significant variations at the phosphorylation level under magnesium sensitivity. Subsequently, we used bioinformatics methods to systematically annotate and analyze the data. Certain transporters and signaling components that could be associated with magnesium sensitivity, such as ATP-binding cassette transporters and mitogen-activated protein kinases, were identified. The results of this study further our understanding of the molecular mechanisms of CIPK3/9/23/26 in mediating magnesium homeostasis.
Functional and Morphological Transformations of the Urban Block—Contribution to the Expected Modernization of Zagreb’s Historical Core
Authors: Gašparović Sanja , Jukić Tihomir , Mrđa Ana
Published: November 2021

The paper explores the possibilities of the structural and functional transformation of blocks in the historical center of Zagreb as a part of modernization after many years of neglect as well as earthquakes in 2020. The research aims to determine how the existing block tissue corresponds with the needs of today’s residents and the possibility of its improvement. The historical circumstances in which the blocks were formed and underwent the most significant changes and modern processes that affect the state and value are determined. There is a special focus on the interior of the block (courtyards), as well as on the spaces on the ground floors of street facades, where numerous, unexplored changes can be observed. The findings provide starting points for desirable structural–functional transformations of blocks and stem from the synthesis and interpretation of knowledge from four interrelated parts of the research. The characteristics of blocks have changed during city development stages, as depicted by an analysis and graphic interpretation of historical maps and urban plans (1864–2021). Influences of modern processes on changes of the city are determined on the basis of the synthesis of previous research from different interdisciplinary points of view; a detailed analysis of the structural–functional changes is conducted on the example of three selected blocks. Transformation models for three selected blocks are proposed.
Efficacy of Different Concentrations of NAA on Selected Ornamental Woody Shrubs Cuttings
Authors: Kentelky Endre , Jucan Denisa , Cantor Maria , Szekely-Varga Zsolt
Published: November 2021

Ornamental woody shrubs are used in landscape design worldwide. Their propagation can be made generatively and vegetatively. Vegetative propagation methods are mostly used by nurseries, as such methods are quick and the newly propagated plants inherit the genetics of the mother plant. However, rooting in some woody plants is slow and, unfortunately, sometimes produces only a small number of rooted cuttings. In this study, shoot cuttings from six selected ornamental woody shrubs were subjected to different concentrations of rooting stimulators (0.5 (NAA5) and 0.8 (NAA8) % concentrations of 1-Naphthylacetic acid; cuttings without treatment were considered as control) and propagated in two different periods (spring and summer). Our results show that significant changes were obtained in the plants under the different treatments. Most of the plants showed a positive response to both treatments, expect for Cotinus coggygria ‘Royal Purple’, which, compared to control, registered decreases in all the tested parameters under NAA5 treatment. Ilex aquifolium was the species that showed increments in all the parameters when NAA treatments were applied. In conclusion, our research suggests that NAA increases rooting in ornamental woody shrubs, although in some cases rooting could be a species-dependent process.
Hydrologic Utility of Satellite-Based and Gauge-Based Gridded Precipitation Products in the Huai Bang Sai Watershed of Northeastern Thailand
Authors: Gunathilake Miyuru B. , Zamri M. N. M. , Alagiyawanna Tharaka  P. , Samarasinghe Jayanga T. , Baddewela Pavithra K. , Babel Mukand S. , Jha Manoj K. , Rathnayake Upaka S.
Published: November 2021

Accurate rainfall estimates are important in many hydrologic activities. Rainfall data are retrieved from rain gauges (RGs), satellites, radars, and re-analysis products. The accuracy of gauge-based gridded precipitation products (GbGPPs) relies on the distribution of RGs and the quality of rainfall data records obtained from these. The accuracy of satellite-based precipitation products (SbPPs) depends on many factors, including basin climatology, basin topography, precipitation mechanism, etc. The hydrologic utility of different precipitation products was examined in many developed regions; however, less focused on the developing world. The Huai Bang Sai (HBS) watershed in north-eastern Thailand is a less focused but an important catchment that significantly contributes to the water resources in Thailand. Therefore, this research presents the investigation results of the hydrologic utility of SbPPs and GbGPPs in the HBS watershed. The efficiency of nine SbPPs (including 3B42, 3B42-RT, PERSIANN, PERSIANN-CCS, PERSIANN-CDR, CHIRPS, CMORPH, IMERG, and MSWEP) and three GbGPPs (including APHRODITE_V1801, APHRODITE_V1901, and GPCC) was examined by simulating streamflow of the HBS watershed through the Soil & Water Assessment Tool (SWAT), hydrologic model. Subsequently, the streamflow simulation capacity of the hydrological model for different precipitation products was compared against observed streamflow records by using the same set of calibrated parameters used for an RG simulated scenario. The 3B42 product outperformed other SbPPS with a higher Nash–Sutcliffe Efficiency (NSEmonthly>0.55), while APHRODITE_V1901 (NSEmonthly>0.53) performed fairly well in the GbGPPs category with closer agreements with observed streamflow. In addition, the CMORPH precipitation product has not performed well in capturing observed rainfall and subsequently in simulating streamflow (NSEmonthly<0) of the HBS. Furthermore, MSWEP and CHIRPS products have performed fairly well during calibration; however, they showcased a lowered performance for validation. Therefore, the results suggest that accurate precipitation data is the major governing factor in streamflow modeling performances. The research outcomes would capture the interest of all stakeholders, including farmers, meteorologists, agriculturists, river basin managers, and hydrologists for potential applications in the tropical humid regions of the world. Moreover, 3B42 and APHRODITE_V1901 precipitation products show promising prospects for the tropical humid regions of the world for hydrologic modeling and climatological studies.
Particulate Air Pollution and Risk of Neuropsychiatric Outcomes. What We Breathe, Swallow, and Put on Our Skin Matters
Authors: Calderón-Garcidueñas Lilian , Stommel Elijah W. , Rajkumar Ravi Philip , Mukherjee Partha S. , Ayala Alberto
Published: November 2021

We appraise newly accumulated evidence of the impact of particle pollution on the brain, the portals of entry, the neural damage mechanisms, and ultimately the neurological and psychiatric outcomes statistically associated with exposures. PM pollution comes from natural and anthropogenic sources such as fossil fuel combustion, engineered nanoparticles (NP ≤ 100 nm), wildfires, and wood burning. We are all constantly exposed during normal daily activities to some level of particle pollution of various sizes—PM2.5 (≤2.5 µm), ultrafine PM (UFP ≤ 100 nm), or NPs. Inhalation, ingestion, and dermal absorption are key portals of entry. Selected literature provides context for the US Environmental Protection Agency (US EPA) ambient air quality standards, the conclusions of an Independent Particulate Matter Review Panel, the importance of internal combustion emissions, and evidence suggesting UFPs/NPs cross biological barriers and reach the brain. NPs produce oxidative stress and neuroinflammation, neurovascular unit, mitochondrial, endoplasmic reticulum and DNA damage, protein aggregation and misfolding, and other effects. Exposure to ambient PM2.5 concentrations at or below current US standards can increase the risk for TIAs, ischemic and hemorrhagic stroke, cognitive deficits, dementia, and Alzheimer’s and Parkinson’s diseases. Residing in a highly polluted megacity is associated with Alzheimer neuropathology hallmarks in 99.5% of residents between 11 months and ≤40 y. PD risk and aggravation are linked to air pollution and exposure to diesel exhaust increases ALS risk. Overall, the literature supports that particle pollution contributes to targeted neurological and psychiatric outcomes and highlights the complexity of the pathophysiologic mechanisms and the marked differences in pollution profiles inducing neural damage. Factors such as emission source intensity, genetics, nutrition, comorbidities, and others also play a role. PM2.5 is a threat for neurological and psychiatric diseases. Thus, future research should address specifically the potential role of UFPs/NPs in inducing neural damage.
SARC-F and the Risk of Falling in Middle-Aged and Older Community-Dwelling Postmenopausal Women
Authors: Alzar-Teruel María , Hita-Contreras Fidel , Martínez-Amat Antonio , Lavilla-Lerma María , Fábrega-Cuadros Raquel , Jiménez-García José , Aibar-Almazán Agustín
Published: November 2021

(1) Background: The objective of the present study was to determine the ability of the SARC-F questionnaire to identify individuals at risk of falling among middle-aged and older community-dwelling postmenopausal women. (2) Methods: An analytical cross-sectional study was conducted on 157 women (70.80 ± 8.37 years). The SARC-F questionnaire was used to screen for risk of sarcopenia. Fear of falling and balance confidence, as measured by the Falls Efficacy Scale-International (FES-I) and the Activities-Specific balance Scale-16 items (ABC-16) respectively, were used to assess risk of falling. Anxiety and depression (Hospital Anxiety and Depression Scale), fatigue (Fatigue Severity Scale), body mass index, waist-to-hip ratio, and sleep duration were also determined. (3) Results: Logistic regression showed that higher risk of falling as assessed by FES-I was associated with higher SARC-F scores (OR = 1.656), anxiety levels (OR = 1.147), and age (OR = 1.060), while increased SARC-F scores (OR = 1.612), fatigue (OR = 1.044), and shorter sleep duration (OR = 0.75) were related to ABC-16 scores. In addition, a SARC-F cutoff of 1.50 (83.33% sensitivity and 59.13% specificity) and 3.50 (44.44% sensitivity and 89.26% specificity) were shown to be able to discriminate participants at risk of falling according to the FES-I and the ABC-16, respectively. (4) Conclusions: our results show that SARC-F is an independent predictor of the risk of falling among middle-aged and older community-dwelling postmenopausal women.
Family Capital, Learning Engagement, and Students’ Higher Education Gains: An Empirical Study in Mainland China
Authors: Wang Shutao , Huang Cui
Published: November 2021

This study aimed to determine whether learning engagement plays a mediating effect on the relationship between family capital and students’ higher education gains in mainland China. We used family capital, learning engagement, and higher education gains as measures and analyzed data using a structural equation model. Data were collected from 1334 students at a Chinese university. The results show that family cultural capital had the most significant effect on students’ learning engagement, while economic capital also played a positive role, and social capital had no significant impact. Learning engagement played a mediating role in the relationship between cultural capital and higher education gains, as did the relationship between economic capital and higher education gains. However, learning engagement did not have a mediating effect on the relationship between social capital and higher education gains. Our results show that we should focus on the importance of students’ learning engagement, improve the cultural capital of disadvantaged groups, and provide financial support for students from low-income families.
Burnout of Healthcare Workers Amid the COVID-19 Pandemic: A Follow-Up Study
Authors: Nishimura Yoshito , Miyoshi Tomoko , Sato Asuka , Hasegawa Kou , Hagiya Hideharu , Kosaki Yoshinori , Otsuka Fumio
Published: November 2021

The coronavirus disease 2019 (COVID-19) pandemic has posed a significant challenge to the modern healthcare system and led to increased burnout among healthcare workers (HCWs). We previously reported that HCWs who engaged in COVID-19 patient care had a significantly higher prevalence of burnout (50.0%) than those who did not in November 2020 (period 1). We performed follow-up surveys in HCWs in a Japanese national university hospital, including basic demographics, whether a participant engaged in care of COVID-19 patients in the past 2 weeks, and the Maslach Burnout Inventory in February 2021 (period 2) and May 2021 (period 3). Periods 1 and 3 were amid the surges of COVID-19 cases, and period 2 was a post-surge period with a comparatively small number of COVID-19 patients requiring hospitalization. Response rates to the surveys were 33/130 (25.4%) in period 1, 36/130 (27.7%) in period 2, and 56/162 (34.6%) in period 3, respectively. While no consistent tendency in the prevalence of burnout based on variables was observed throughout the periods, the prevalence of burnout tends to be higher in periods 1 and 3 in those who engaged in COVID-19 patient care in the last 2 weeks (50.0%, 30.8%, 43.1% in period 1, 2, and 3, respectively). Given the prolonged pandemic causing stigmatization and hatred against HCWs leading to increased prevalence of burnout, high-level interventions and supports are warranted.
Descriptive and Quasi-Experimental Studies about Moral Emotions, Online Empathy, Anger Management, and Their Relations with Key Competencies in Primary Education
Authors: González-Gómez Antonio L. , Farrington David P. , Llorent Vicente J.
Published: November 2021

Background: Antisocial behaviours make social interactions difficult among students. Moral emotions, online empathy, and anger management are social and emotional variables related to prosocial and antisocial behaviours and health problems. This research aims to assess the impact of Cooperative Project-Based Learning intervention on these three variables for Primary Education students. Additionally, the relations of these variables with key competencies, such as social and emotional competencies and literacy competence, were studied. Method: This research is made up of two studies, descriptive and quasi-experimental, during regular school hours. The descriptive study was carried out with a sample of 516 primary school students and aimed to assess the development of the three variables, taking into account personal and ethnic-cultural factors. The quasi-experimental study, with pre-test and post-test data, had the participation of 145 students to study the incidence of these variables after Cooperative Project-Based Learning intervention in Primary Education. Results: The results show the relation among the cited variables and the positive impact of the intervention on moral emotions and anger management in the experimental group compared to the control group. Experimental group girls presented higher scores in moral emotions than control group girls. Conclusion: These results open new research lines in relation to the intervention as a programme to prevent the appearance of antisocial behaviours and health problems at school.
The Effectiveness of Intervening on Social Isolation to Reduce Mortality during Heat Waves in Aged Population: A Retrospective Ecological Study
Authors: Orlando Stefano , Mosconi Claudia , De Santo Carolina , Emberti Gialloreti Leonardo , Inzerilli Maria Chiara , Madaro Olga , Mancinelli Sandro , Ciccacci Fausto , Marazzi Maria Cristina , Palombi Leonardo , Liotta Giuseppe
Published: November 2021

Background: Heat waves are correlated with increased mortality in the aged population. Social isolation is known as a vulnerability factor. This study aims at evaluating the correlation between an intervention to reduce social isolation and the increase in mortality in the population over 80 during heat waves. Methods: This study adopted a retrospective ecologic design. We compared the excess mortality rate (EMR) in the over-80 population during heat waves in urban areas of Rome (Italy) where a program to reduce social isolation was implemented, to others where it was not implemented. We measured the mortality of the summer periods from 2015 to 2019 compared with 2014 (a year without heat waves). Winter mortality, cadastral income, and the proportion of people over 90 were included in the multivariate Poisson regression. Results: The EMR in the intervention and controls was 2.70% and 3.81%, respectively. The rate ratio was 0.70 (c.i. 0.54–0.92, p-value 0.01). The incidence rate ratio (IRR) of the interventions, with respect to the controls, was 0.76 (c.i. 0.59–0.98). After adjusting for other variables, the IRR was 0.44 (c.i. 0.32–0.60). Conclusions: Reducing social isolation could limit the impact of heat waves on the mortality of the elderly population.