bluuebunny/crossref_metadata_2025 huggingface dataset:
Surface Modifications of Biodegradable Metallic Foams for Medical Applications
Authors: Oriňaková Renáta , Gorejová Radka , Orságová Králová Zuzana , Oriňak Andrej
Published: August 2020

Significant progress was achieved presently in the development of metallic foam-like materials improved by biocompatible coatings. Material properties of the iron, magnesium, zinc, and their alloys are promising for their uses in medical applications, especially for orthopedic and bone tissue purposes. Current processing technologies and a variety of modifications of the surface and composition facilitate the design of adjusted medical devices with desirable mechanical, morphological, and functional properties. This article reviews the recent progress in the design of advanced degradable metallic biomaterials perfected by different coatings: polymer, inorganic ceramic, and metallic. Appropriate coating of metallic foams could improve the biocompatibility, osteogenesis, and bone tissue-bonding properties. In this paper, a comprehensive review of different coating types used for the enhancement of one or several properties of biodegradable porous implants is given. An outline of the conventional preparation methods of metallic foams and a brief overview of different alloys for medical applications are also provided. In addition, current challenges and future research directions of processing and surface modifications of biodegradable metallic foams for medical applications are suggested.
Numerical Simulation of Adsorption of Organic Inhibitors on C-S-H Gel
Authors: Song Zijian , Cai Huanchun , Liu Qingyang , Liu Xing , Pu Qi , Zang Yingjie , Xu Na
Published: August 2020

Corrosion inhibitors are one of the most effective anticorrosion techniques in reinforced concrete structures. Molecule dynamics (MD) was usually utilized to simulate the interaction between the inhibitor molecules and the surface of Fe to evaluate the inhibition effect, ignoring the influence of cement hydration products. In this paper, the adsorption characteristics of five types of common alkanol-amine inhibitors on C-S-H gel in the alkaline liquid environment were simulated via the MD and the grand canonical Monte Carlo (GCMC) methods. It is found that, in the MD system, the liquid phase environment had a certain impact on the adsorption configuration of compounds. According to the analysis of the energy, the binding ability of MEA on the surface of the C-S-H gel was the strongest. In the GCMC system, the adsorption of MEA was the largest at the same temperature. Furthermore, for the competitive adsorption in the GCMC system, the adsorption characteristics of the inhibitors on the C-S-H gel were to follow the order: MEA>DEA>TEA>NDE>DETA. Both MD and GCMC simulations confirmed that the C-S-H gel would adsorb the organic inhibitors to a different extent, which might have a considerable influence on the organic inhibitors to exert their inhibition effects.
Widely Tunable Angular Non-Critical Phase-Matching Wavelengths from 0.72 to 1.42 μm Based on RE1xRE21−xCOB Mixed Crystals
Authors: Li Ranran , Qi Hongwei , Liu Yanqing , Yu Fapeng , Yu Pingzhang , Wang Zhengping , Xu Xinguang , Zhao Xian
Published: August 2020

The angular non-critical phase-matching (A-NCPM) second-harmonic-generation (SHG) properties of RE1xRE21−xCOB (RE1, RE2 = Y, Gd, La, Tm, Sm, and Nd) type mixed crystals including NCPM wavelength and conversion efficiency were detailedly investigated. Theoretical calculations manifest that the A-NCPM SHG scope of these crystals is 0.72~1.42 µm, and in experiments, the A-NCPM SHG waveband of 0.72~1.25 µm has been realized, by changing the ratio of the rare-earth elements RE1 and RE2 in RE1xRE21−xCOB crystals. Comparing to the temperature-dependent A-NCPM SHG of 0.95~1.34 µm in LiB3O5 (LBO) crystal, the composition-dependent A-NCPM SHG of 0.72~0.95 µm in RE1xRE21−xCOB type crystals is unique and has special significance for the frequency conversion of Ti:Sapphire lasers. Relationships between the birefringence and radius of rare-earth ion RE3+ in RE1xRE21−xCOB mixed crystals were discussed. Aiming for the A-NCPM SHG of 0.72~1.42 µm, we supply a clear, completed, and optimized solution on how to select the compositions of RE1xRE21−xCOB mixed crystals. Under focusing light beam conditions, high efficient A-NCPM SHG for both OPO and Ti:sapphire lasers were realized experimentally by using long Y- and Z-cut RE1xRE21−xCOB crystal samples.
Comparative Ab Initio Calculations of ReO3, SrZrO3, BaZrO3, PbZrO3 and CaZrO3 (001) Surfaces
Authors: Eglitis Roberts I. , Purans Juris , Gabrusenoks Jevgenijs , Popov Anatoli I. , Jia Ran
Published: August 2020

We performed, for first time, ab initio calculations for the ReO2-terminated ReO3 (001) surface and analyzed systematic trends in the ReO3, SrZrO3, BaZrO3, PbZrO3 and CaZrO3 (001) surfaces using first-principles calculations. According to the ab initio calculation results, all ReO3, SrZrO3, BaZrO3, PbZrO3 and CaZrO3 (001) surface upper-layer atoms relax inwards towards the crystal bulk, all second-layer atoms relax upwards and all third-layer atoms, again, relax inwards. The ReO2-terminated ReO3 and ZrO2-terminated SrZrO3, BaZrO3, PbZrO3 and CaZrO3 (001) surface band gaps at the Γ–Γ point are always reduced in comparison to their bulk band gap values. The Zr–O chemical bond populations in the SrZrO3, BaZrO3, PbZrO3 and CaZrO3 perovskite bulk are always smaller than those near the ZrO2-terminated (001) surfaces. In contrast, the Re–O chemical bond population in the ReO3 bulk (0.212e) is larger than that near the ReO2-terminated ReO3 (001) surface (0.170e). Nevertheless, the Re–O chemical bond population between the Re atom located on the ReO2-terminated ReO3 (001) surface upper layer and the O atom located on the ReO2-terminated ReO3 (001) surface second layer (0.262e) is the largest.
Formation of Three-Dimensional Electronic Networks Using Axially Ligated Metal Phthalocyanines as Stable Neutral Radicals
Authors: Sato Ryoya , Matsuda Masaki
Published: August 2020

Organic π-radical crystals are potential single-component molecular conductors, as they involve charge carriers. We fabricated new organic π-radical crystals using axially ligated metal phthalocyanine anions ([MIII(Pc)L2]−) as starting materials. Electrochemical oxidation of [MIII(Pc)L2]− afforded single crystals of organic π-radicals of the type MIII(Pc)Cl2·THF (M = Co or Fe, THF = tetrahydrofuran), where the π-conjugated macrocyclic phthalocyanine ligand is one-electron oxidized. The X-ray crystal structure analysis revealed that MIII(Pc)Cl2 formed three-dimensional networks with π-π overlaps. The electrical resistivities of CoIII(Pc)Cl2·THF and FeIII(Pc)Cl2·THF at room temperature along the a-axis were 6 × 102 and 6 × 103 Ω cm, respectively, and were almost isotropic, meaning that MIII(Pc)Cl2·THF had three-dimensional electronic systems.
Interspecific Hybridization and Introgression Influence Biodiversity—Based on Genetic Diversity of Central European Viola epipsila-V. palustris Complex
Authors: Żabicka Justyna , Migdałek Grzegorz , Słomka Aneta , Sliwinska Elwira , Mackiewicz Leszek , Keczyński Andrzej , Kuta Elżbieta
Published: August 2020

The Viola epipsila-V. palustris complex is a highly taxonomically complicated group of species in its entire circumboreal range of distribution. Habitat loss, forest flooding, and hybridization could lead to the extinction of V. epipsila. A hybrid index and principal component analysis (PCA) were used to select qualitative and quantitative morphological features to distinguish parent species and hybrids, inter simple sequence repeat (ISSR) markers to determine the genetic diversity of the populations, flow cytometry to estimate the genome size (GS), and non-coding chloroplast DNA (cpDNA) regions to indicate the directions of crosses. All taxa are very morphologically variable, and their features can change within a season. The most stable feature is the distance of the bracts on the pedicel from the rhizome. The genetic diversity of all taxa populations is low and highly influenced by selfing and vegetative propagation. The population structure is differentiated: populations of V. epipsila or V. palustris, mixed populations with both parent species, F1 hybrids and populations with introgressive forms occur in different regions. The interspecific GS variation corresponds to the ploidy level (4x = 2.52 pg, 8x = 4.26 pg, 6x = 3.42 pg). Viola epipsila is the mother plant of the hybrids. Research has shown the risk of V. epipsila extinction in Central Europe and the importance of local populations in studying the role of hybridization in reducing/maintaining/increasing biodiversity.
Machine Learning Facilitates Hotspot Classification in PSMA-PET/CT with Nuclear Medicine Specialist Accuracy
Authors: Moazemi Sobhan , Khurshid Zain , Erle Annette , Lütje Susanne , Essler Markus , Schultz Thomas , Bundschuh Ralph A.
Published: August 2020

Gallium-68 prostate-specific membrane antigen positron emission tomography (68Ga-PSMA-PET) is a highly sensitive method to detect prostate cancer (PC) metastases. Visual discrimination between malignant and physiologic/unspecific tracer accumulation by a nuclear medicine (NM) specialist is essential for image interpretation. In the future, automated machine learning (ML)-based tools will assist physicians in image analysis. The aim of this work was to develop a tool for analysis of 68Ga-PSMA-PET images and to compare its efficacy to that of human readers. Five different ML methods were compared and tested on multiple positron emission tomography/computed tomography (PET/CT) data-sets. Forty textural features extracted from both PET- and low-dose CT data were analyzed. In total, 2419 hotspots from 72 patients were included. Comparing results from human readers to those of ML-based analyses, up to 98% area under the curve (AUC), 94% sensitivity (SE), and 89% specificity (SP) were achieved. Interestingly, textural features assessed in native low-dose CT increased the accuracy significantly. Thus, ML based on 68Ga-PSMA-PET/CT radiomics features can classify hotspots with high precision, comparable to that of experienced NM physicians. Additionally, the superiority of multimodal ML-based analysis considering all PET and low-dose CT features was shown. Morphological features seemed to be of special additional importance even though they were extracted from native low-dose CTs.
Relationship between 18F-FDG Uptake in the Oral Cavity, Recent Dental Treatments, and Oral Inflammation or Infection: A Retrospective Study of Patients with Suspected Endocarditis
Authors: Dijkstra Geertruida W. , Glaudemans Andor W. J. M. , Erba Paola A. , Wouthuyzen-Bakker Marjan , Sinha Bhanu , Vállez García David , van der Sluis Luc W. M. , Slart Riemer H. J. A.
Published: August 2020

[18F]-fluorodeoxyglucose positron emission tomography ([18F]FDG PET/CT) has proven to be a useful diagnostic tool in patients with suspected infective endocarditis (IE), but is conflicting in relation to dental procedures. Questions: Is there a correlation between [18F]FDG PET/CT findings, recent dental treatment, and an affected oral cavity? (2) Is there a correlation between infective endocarditis (IE), oral health status, and (extra)cardiac findings on [18F]FDG PET/CT? Methods: This retrospective study included 52 patients. All [18F]FDG PET/CT scans were examined visually by pattern recognition using a three-point scale and semi-quantified within the volume of interest (VOI) using SUVmax. Results: 19 patients were diagnosed with IE (group 1), 14 with possible IE (group 2), and 19 without IE based on the modified Duke criteria (group 3). No correlation was found between visual PET and SUVmax and sites of oral inflammation and infection. The visual PET scores and SUVmax were not significantly different between all groups. A significant difference in the SUVmax of the valve between all groups was observed. Conclusions: This study suggests that no correlation exists between the PET findings in the oral cavity and dental treatments or inflammation/infection. No correlation between IE, actual oral health status, and extra-cardiac findings was demonstrated. Additional research is needed to conclude whether [18F]FDG PET/CT imaging is a reliable diagnostic modality for oral inflammation and infection sites.
Time-Limited Codewords over Band-Limited Channels: Data Rates and the Dimension of the W-T Space
Authors: Jaffal Youssef , Abou-Faycal Ibrahim
Published: August 2020

We consider a communication system whereby T-seconds time-limited codewords are transmitted over a W-Hz band-limited additive white Gaussian noise channel. In the asymptotic regime as WT→∞, it is known that the maximal achievable rates with such a scheme converge to Shannon’s capacity with the presence of 2WT degrees of freedom. In this work we study the degrees of freedom and the achievable information rates for finite values of WT. We use prolate spheroidal wave functions to obtain an information lossless equivalent discrete formulation and then we apply Polyanskiy’s results on coding in the finite block-length regime. We derive upper and lower bounds on the achievable rates and the corresponding degrees of freedom and we numerically evaluate them for sample values of 2WT. The bounds are asymptotically tight and numerical computations show the gap between them decreases as 2WT increases. Additionally, the possible decrease from 2WT in the available degrees of freedom is upper-bounded by a logarithmic function of 2WT.
Statistical and Proactive Analysis of an Inter-Laboratory Comparison: The Radiocarbon Dating of the Shroud of Turin
Authors: Di Lazzaro Paolo , Atkinson Anthony C. , Iacomussi Paola , Riani Marco , Ricci Marco , Wadhams Peter
Published: August 2020

We review the sampling and results of the radiocarbon dating of the archaeological cloth known as the Shroud of Turin, in the light of recent statistical analyses of both published and raw data. The statistical analyses highlight an inter-laboratory heterogeneity of the means and a monotone spatial variation of the ages of subsamples that suggest the presence of contaminants unevenly removed by the cleaning pretreatments. We consider the significance and overall impact of the statistical analyses on assessing the reliability of the dating results and the design of correct sampling. These analyses suggest that the 1988 radiocarbon dating does not match the current accuracy requirements. Should this be the case, it would be interesting to know the accurate age of the Shroud of Turin. Taking into account the whole body of scientific data, we discuss whether it makes sense to date the Shroud again.
A Linearity Improvement Front End with Subharmonic Current Commutating Passive Mixer for 2.4 GHz Direct Conversion Receiver in 0.13 μm CMOS Technology
Authors: Huo Dongquan , Mao Luhong , Wu Liji , Zhang Xiangmin
Published: August 2020

Direct conversion receiver (DCR) architecture is a promising candidate in the radio frequency (RF) front end because of its low power consumption, low cost and ease of integration. However, flicker noise and direct current (DC) offset are large issues. Owing to the local oscillator (LO) frequency, which is half of the RF frequency, and the absence of a DC bias current that introduces no flicker noise, the subharmonic passive mixer (SHPM) core topology front end overcomes the shortcoming effectively. When more and more receivers (RX) and transmitters (TX) are integrated into one chip, the linearity of the receiver front end becomes a very important performer that handles the TX and RX feedthrough. Another reason for the requirement of good linearity is the massive electromagnetic interference that exists in the atmosphere. This paper presents a linearity-improved RF front end with a feedforward body bias (FBB) subharmonic mixer core topology that satisfies modern RF front end demands. A novel complementary derivative superposition (DS) method is presented in low noise amplifier (LNA) design to cancel both the third- and second-order nonlinearities. To the best knowledge of the authors, this is the first time FBB technology is used in the SHPM core to improve linearity. A Volterra series is introduced to provide an analytical formula for the FBB of the SHPM core. The design was fabricated in a 0.13 μm complementary metal oxide semiconductor (CMOS) process with a chip area of 750 μm × 1270 μm. At a 2.4 GHz working frequency, the measurement result shows a conversion gain of 36 dB, double side band (DSB) noise figure (NF) of 6.8 dB, third-order intermodulation intercept point (IIP3) of 2 dBm, LO–RF isolation of 90 dB and 0.8 mW DC offset with 14.4 mW power consumption at 1.2 V supply voltage. These results exhibit better LO–RF feedthrough and DC offset, good gain and NF, moderate IIP3 and the highest figure of merit compared to the state-of-the-art publications.
Multiphysics CFD Simulation for Design and Analysis of Thermoelectric Power Generation
Authors: Högblom Olle , Andersson Ronnie
Published: August 2020

The multiphysics simulation methodology presented in this paper permits extension of computational fluid dynamics (CFD) simulations to account for electric power generation and its effect on the energy transport, the Seebeck voltage, the electrical currents in thermoelectric systems. The energy transport through Fourier, Peltier, Thomson and Joule mechanisms as a function of temperature and electrical current, and the electrical connection between thermoelectric modules, is modeled using subgrid CFD models which make the approach computational efficient and generic. This also provides a solution to the scale separation problem that arise in CFD analysis of thermoelectric heat exchangers and allows the thermoelectric models to be fully coupled with the energy transport in the CFD analysis. Model validation includes measurement of the relevant fluid dynamic properties (pressure and temperature distribution) and electric properties (current and voltage) for a turbulent flow inside a thermoelectric heat exchanger designed for automotive applications. Predictions of pressure and temperature drop in the system are accurate and the error in predicted current and voltage is less than 1.5% at all exhaust gas flow rates and temperatures studied which is considered very good. Simulation results confirm high computational efficiency and stable simulations with low increase in computational time compared to standard CFD heat-transfer simulations. Analysis of the results also reveals that even at the lowest heat transfer rate studied it is required to use a full two way coupling in the energy transport to accurately predict the electric power generation.
Thermodynamic and Economic Analyses of a New Waste-to-Energy System Incorporated with a Biomass-Fired Power Plant
Authors: Pan Peiyuan , Zhang Meiyan , Xu Gang , Chen Heng , Song Xiaona , Liu Tong
Published: August 2020

A novel design has been developed to improve the waste-to-energy process through the integration with a biomass-fired power plant. In the proposed scheme, the superheated steam generated by the waste-to-energy boiler is fed into the low-pressure turbine of the biomass power section for power production. Besides, the feedwater from the biomass power section is utilized to warm the combustion air of the waste-to-energy boiler, and the feedwater of the waste-to-energy boiler is offered by the biomass power section. Based on a 35-MW biomass-fired power plant and a 500-t/d waste-to-energy plant, the integrated design was thermodynamically and economically assessed. The results indicate that the net power generated from waste can be enhanced by 0.66 MW due to the proposed solution, and the waste-to-electricity efficiency increases from 20.49% to 22.12%. Moreover, the net present value of the waste-to-energy section is raised by 5.02 million USD, and the dynamic payback period is cut down by 2.81 years. Energy and exergy analyses were conducted to reveal the inherent mechanism of performance enhancement. Besides, a sensitivity investigation was undertaken to examine the performance of the new design under various conditions. The insights gained from this study may be of assistance to the advancement of waste-to-energy technology.
Optimal Condition-Based Maintenance Strategy for Multi-Component Systems under Degradation Failures
Authors: Wang Kui , Deng Chao , Ding Lili
Published: August 2020

This paper proposes a condition-based maintenance strategy for multi-component systems under degradation failures. The maintenance decision is based on the minimum long-run average cost rate (LACR) and the maximum residual useful lifetime (RUL), respectively. The aim of this paper is to determine the optimal monitoring interval and critical level for multi-component systems under different optimization objectives. A preventive maintenance (PM) is triggered when the degradation of component exceeds the corresponding critical level. Afterwards, the paper discusses the relationship between the critical level and the monitoring interval with regards to the LACR and RUL. Methods are also proposed to determine the optimal monitoring interval and the critical level under two decision models. Finally, the impact of maintenance decision variables on the LACR and RUL is discussed through a case study. A comparison with conventional maintenance policy shows an outstanding performance of the new model.
Modeling and Compensation for Dead-Time Effect in High Power IGBT/IGCT Converters with SHE-PWM Modulation
Authors: Cheng Jingling , Chen Dongdong , Chen Guozhu
Published: August 2020

Research on applying selective harmonic elimination pulse width modulation (SHE-PWM) to high power converters has drawn tremendous interest, due to the advantages of low switching frequency and high output harmonic performance. In the fields of high power converters such as variable speed traction motor drives and static synchronous compensators (STATCOM), the adoption of high voltage but slow speed semiconductor devices, i.e., IGBT/IGCT, results in a longer dead time of several microseconds, which leads to a motor vibration in the former case or the distortion of grid current in the latter case. This paper analyzes in detail the mechanism of the dead-time effect on 3-level SHE-PWM with different operating conditions considered. For the first time, a general mathematical model describing the relationship between the dead time and harmonic distribution of SHE-PWM wave is established. Based on which an open-loop compensation method by inserting a margin time into the effective switching angles is proposed. Furthermore, a closed-loop controller that implements online adaptive adjustment of the margin time is designed in case of a variable frequency application. The effectiveness of the proposed method in different scenarios is verified through simulation results.
RDF from Compost-Like-Output’s Produced in the MBT Installation in the Case of Marszów, Poland
Authors: Połomka Jacek , Jędrczak Andrzej
Published: August 2020

At most of the installations for the mechanical and biological treatment of waste operated in Poland, the 0–80 mm fraction, separated from the municipal waste stream, are completely stored after biostabilization. Such an action does not fit into the EU strategy focused on circular waste management. The purpose of this study was to assess the technical feasibility of recovering the mineral fractions contained in the compost-like-output (CLO) on a technological line designed for glass recovery. The research started in January 2019, lasted for the next 12 months, and covered 29 measurement series. The following two high-energy fractions were separated from the CLO: 10–35 mm light fraction after separation in the air separator (M-1) and 35–80 mm light fraction after separation in the air separator (M-2). The stabilization processing on the glass recovery line allowed for the recovery of two high energy fractions in the total amount of 24.5% of the processed, and it stabilized the product’s mass. In terms of materials, the M-1 and M-2 wastes were a mixture of organic, paper, and plastic materials. Under the Refuse Derived Fuel (RDF) classification, according to the European Committee for Standardization, the tested waste fell within the following classes: waste M-1: 4NCV2Cl4Hg and M-2: 4NCV1Cl4Hg.
Numerical Modeling and Performance Evaluation of Standing Wave Thermoacoustic Refrigerators with a Multi-Layered Stack
Authors: Bhatti Umar Nawaz , Bashmal Salem , Khan Sikandar , Ben-Mansour Rached
Published: August 2020

Thermoacoustic refrigerators have huge potential to replace conventional refrigeration systems as an alternative clean refrigeration technology. These devices utilize conversion of acoustic power and heat energy to generate the desired cooling. The stack plays a pivotal role in the performance of Standing Wave Thermoacoustic Refrigerators (SWTARs), as the heat transfer takes place across it. Performance of stacks can be significantly improved by making an arrangement of different materials inside the stack, resulting in anisotropic thermal properties along the length. In the present numerical study, the effect of multi-layered stack on the refrigeration performance of a SWTAR has been evaluated in terms of temperature drop across the stack, acoustic power consumed and device Coefficient of Performance (COP). Two different aspects of multi-layered stack, namely, different material combinations and different lengths of stacked layers, have been investigated. The combinations of four stack materials and length ratios have been investigated. The numerical results showed that multi-layered stacks produce lower refrigeration temperatures, consume less energy and have higher COP value than their homogeneous counterparts. Among all the material combinations of multi-layered stack investigated, stacks composed of a material layer with low thermal conductivity at the ends, i.e., RVC, produced the best performance with an increase of 26.14% in temperature drop value, reduction in the acoustic power consumption by 4.55% and COP enhancement of 5.12%. The results also showed that, for a constant overall length, an increase in length of side stacked material layer results in an increase in values of both temperature drop and COP.
Forecasting the Energy Consumption of an Actual Air Handling Unit and Absorption Chiller Using ANN Models
Authors: Kim Jee-Heon , Seong Nam-Chul , Choi Wonchang
Published: August 2020

Air conditioning in buildings accounts for 60% of the total energy consumption. Therefore, accurate predictions of energy consumption are needed to properly manage the energy consumption of buildings. For this purpose, many studies have been conducted recently on the prediction of energy consumption of buildings using machine learning techniques. The energy consumption of the air handling unit (AHU) and absorption chiller in an actual building’s air conditioning system is predicted in this paper using prediction models that are based on artificial neural networks (ANNs), which simply and accurately allow us to forecast energy consumption with limited variables. Using these ANN models, the energy usage of the AHU and chiller could be predicted by collecting a month’s worth of driving data during the summer cooling period. After the forecast models had been verified, the AHU prediction model showed performance in the ranges of 13.27% to 15.25% and 19.42% to 19.53% for the training period and testing period, respectively, and the mean bias error (MBE) ranges were 4.03% to 4.97% and 3.48% to 4.39% for the training period and testing period, respectively. The chiller prediction model satisfied the energy consumption forecast performance criteria presented by American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) guideline 14 (the measurement of energy and demand savings), with a performance of 24.64~25.58% and 7.12~29.39% in the training period and testing period, respectively, and MBE ranges of 2.59~3.40% and 1.35~2.87% in the training period and testing period, respectively. When the training period and testing period were combined for the AHU data, the actual energy usage forecast showed a lower error rate range of 0.22% to 1.11% for the training period and 0.17% to 2.44% for the testing period. For the chiller data, the error rate range was 0.22% to 2.12% for the entire training period, but was somewhat higher at 11.67% to 15.18% for the testing period. The study found that, even if the performance criteria were met, high accuracy results were not obtained, which was due to the poor data set quality. Although the forecast model based on artificial neural network can achieve relatively high-accuracy results with sufficient amounts of data, it is believed that this will require a thorough verification of the data used, as well as improvements in the predictive model to avoid overfitting and underfitting, to achieve such good results.
Energy Consumption Optimization and User Comfort Maximization in Smart Buildings Using a Hybrid of the Firefly and Genetic Algorithms
Authors: Wahid Fazli , Fayaz Muhammad , Aljarbouh Ayman , Mir Masood , Aamir Muhammad , Imran
Published: August 2020

This research work proposed a hybrid model to maximize energy consumption and maximize user comfort in residential buildings. The proposed model consists of two widely used optimization algorithms named the firefly algorithm (FA) and genetic algorithm (GA). The hybridization of two optimization approaches results in a better optimization process, leading to better performance of the process in terms of minimum power consumption and maximum occupant’s comfort. The inputs of the optimization model are illumination, temperature, and air quality from the user, in addition with the external environment. The outputs of the proposed model are the optimized values of illumination, temperature, and air quality, which are, in turn, used in computing the values of user comfort. After the computation of the comfort index, these values enter the fuzzy controllers, which are used to adjust the cooling/heating system, illumination system, and ventilation system according to the occupant’s requirement. A user-friendly environment for power consumption minimization and user comfort maximization using data from different sensors, user, processes, power control systems, and various actuators is proposed in this work. The results obtained from the hybrid model have been compared with many state-of-the-art optimization algorithms. The final results revealed that the proposed approach performed better as compared to the standard optimization techniques.
Estimating the Impact of Electric Vehicle Demand Response Programs in a Grid with Varying Levels of Renewable Energy Sources: Time-of-Use Tariff versus Smart Charging
Authors: Jeon Wooyoung , Cho Sangmin , Lee Seungmoon
Published: August 2020

An increase in variable renewable energy sources and soaring electricity demand at peak hours undermines the efficiency and reliability of the power supply. Conventional supply-side solutions, such as additional gas turbine plants and energy storage systems, can help mitigate these problems; however, they are not cost-effective. This study highlights the potential value of electric vehicle demand response programs by analyzing three separate scenarios: electric vehicle charging based on a time-of-use tariff, smart charging controlled by an aggregator through virtual power plant networks, and smart control with vehicle-to-grid capability. The three programs are analyzed based on the stochastic form of a power system optimization model under two hypothetical power system environments in Jeju Island, Korea: one with a low share of variable renewable energy in 2019 and the other with a high share in 2030. The results show that the cost saving realized by the electric vehicle demand response program is higher in 2030 and a smart control with vehicle-to-grid capability provides the largest cost saving. When the costs of implementing an electric vehicle demand response are considered, the difference in cost saving between the scenarios is reduced; however, the benefits are still large enough to attract customers to participate.
Continuation Power Flow Based Distributed Energy Resource Hosting Capacity Estimation Considering Renewable Energy Uncertainty and Stability in Distribution Systems
Authors: Kim Hyun-Tae , Lee Jungju , Yoon Myungseok , Lee Moon-Jeong , Cho Namhun , Choi Sungyun
Published: August 2020

Recently, the demand for electricity has been increasing worldwide. Thus, more attention has been paid to renewable energy. There are acceptable limits during the integration of renewable energy into distribution systems because there are many effects of integrating renewable energy. Unlike previous studies that have estimated the distributed energy resource (DER) hosting capacity using the standard high voltage and probability approach, in this study, we propose an algorithm to estimate the DER hosting capacity by considering DER outages due to abrupt disturbances or uncertainties based on the generator ramp rate and voltage stability, which involves analysis of the low-voltage aspects. Furthermore, this method does not involve a complicated process or need large amounts of data to estimate the DER hosting capacity because it requires only minimum data for power flow. The proposed algorithm was applied to the IEEE-33 radial distribution system. According to the DER capacity, a voltage stability analysis based on continuation power flow (CPF) was conducted in a case of DER outage to estimate the DER hosting capacity in this case study. Thus, the DER hosting capacity was estimated for the IEEE-33 radial distribution system.
Simulation Models of Skidder Conventional and Hybrid Drive
Authors: Karlušić Juraj , Cipek Mihael , Pavković Danijel , Benić Juraj , Šitum Željko , Pandur Zdravko , Šušnjar Marijan
Published: August 2020

The paper presents a hypothetical conversion of a conventional cable skidder powertrain to its hybrid version. Simulations of skidder operation were made for two existing forest paths, based on the technical characteristics of the engine, transmission system and the characteristics of the winch. Fuel and time consumption were calculated per working cycle considering the operating conditions (slope, load mass). The model was then converted to a hybrid version by adding a battery energy storage system in parallel with the electrical power generator and by employing an energy management control strategy. The dimensions of the battery and the power generator were chosen based on the characteristics of the existing winch with the aim of completely taking over its operation. The management strategy was selected using the specific fuel consumption map. All simulations were repeated for the hybrid drive under the same operating conditions. The results show that fuel savings of around 13% can be achieved with the selected hybrid drive and steering strategy.
Erratum: Form Factors of an Economically Valuable Sal Tree (Shorea robusta) of Nepal. Forests 2020, 11, 754
Authors: Baral Sony , Neumann Mathias , Basnyat Bijendra , Gauli Kalyan , Gautam Sishir , Bhandari Shes Kanta , Vacik Harald
Published: August 2020

The authors found some minus signs were omitted in Table 4 and the Equations (1) and (8), and have requested that the following changes be made to their paper [...]
Estimating Individual Conifer Seedling Height Using Drone-Based Image Point Clouds
Authors: Castilla Guillermo , Filiatrault Michelle , McDermid Gregory J. , Gartrell Michael
Published: August 2020

Research Highlights: This is the most comprehensive analysis to date of the accuracy of height estimates for individual conifer seedlings derived from drone-based image point clouds (DIPCs). We provide insights into the effects on accuracy of ground sampling distance (GSD), phenology, ground determination method, seedling size, and more. Background and Objectives: Regeneration success in disturbed forests involves costly ground surveys of tree seedlings exceeding a minimum height. Here we assess the accuracy with which conifer seedling height can be estimated using drones, and how height errors translate into counting errors in stocking surveys. Materials and Methods: We compared height estimates derived from DIPCs of different GSD (0.35 cm, 0.75 cm, and 3 cm), phenological state (leaf-on and leaf-off), and ground determination method (based on either the DIPC itself or an ancillary digital terrain model). Each set of height estimates came from data acquired in up to three linear disturbances in the boreal forest of Alberta, Canada, and included 22 to 189 surveyed seedlings, which were split into two height strata to assess two survey scenarios. Results: The best result (root mean square error (RMSE) = 24 cm; bias = −11 cm; R2 = 0.63; n = 48) was achieved for seedlings >30 cm with 0.35 cm GSD in leaf-off conditions and ground elevation from the DIPC. The second-best result had the same GSD and ground method but was leaf-on and not significantly different from the first. Results for seedlings ≤30 cm were unreliable (nil R2). Height estimates derived from manual softcopy interpretation were similar to the corresponding DIPC results. Height estimation errors hardly affected seedling counting errors (best balance was 8% omission and 6% commission). Accuracy and correlation were stronger at finer GSDs and improved with seedling size. Conclusions: Millimetric (GSD <1 cm) DIPC can be used for estimating the height of individual conifer seedlings taller than 30 cm.
Modelling Bushfire Fuel Hazard Using Biophysical Parameters
Authors: Jenkins Meaghan E. , Bedward Michael , Price Owen , Bradstock Ross A.
Published: August 2020

Environmental gradients or biophysical parameters such as climate, topography and geology drive landscape-scale vegetation structure, species distribution and productivity. These gradients have the potential to provide detailed, fine-scale spatial prediction of the accumulation of bushfire fuels and hence fire hazard by elucidating patterns in field information in a consistent and repeatable way. Rapid visual assessment of bushfire fuel hazard via ratings provides fire and land management agencies with a measure of the probability of first attack success and general suppression difficulty of bushfires at a location. This study used generalised additive modelling to examine how measures of fuel hazard, recorded for locations in New South Wales, Australia, varied in response to environmental gradients and whether these gradients could be used to predict fuel hazard at a landscape scale. We found that time since last fire, temperature and precipitation were strong predictors of fuel hazard. Our model predictions for fuel hazard outperformed current operational methods; however, both methods tended to overestimate lower fuel hazard and underestimate higher fuel hazard. Biophysical modelling of fuel hazard provides significant advancement for predicting fuel hazard. These models have the capability to be improved and developed as additional fuel hazard data, fire history mapping and remote sensing of environmental variables advance both spatially and temporally.
A Distributed Architecture for Smart Recycling Using Machine Learning
Authors: Ziouzios Dimitris , Tsiktsiris Dimitris , Baras Nikolaos , Dasygenis Minas
Published: August 2020

Recycling is vital for a sustainable and clean environment. Developed and developing countries are both facing the problem of solid management waste and recycling issues. Waste classification is a good solution to separate the waste from the recycle materials. In this work, we propose a cloud based classification algorithm for automated machines in recycling factories using machine learning. We trained an efficient MobileNet model, able to classify five different types of waste. The inference can be performed in real-time on a cloud server. Various techniques are described and used in order to improve the classification accuracy, such as data augmentation and hyper-parameter tuning. Multiple industrial stations are supported and interconnected via custom data transmission protocols, along with security features. Experimental results indicated that our solution can achieve excellent performance with 96.57% accuracy utilizing a cloud server.
The Effect of Rosa spinosissima Fruits Extract on Lactic Acid Bacteria Growth and Other Yoghurt Parameters
Authors: Szołtysik Marek , Kucharska Alicja Z. , Sokół-Łętowska Anna , Dąbrowska Anna , Bobak Łukasz , Chrzanowska Józefa
Published: August 2020

The aim of the study was to evaluate the effect of purified extract from Rosa spinosissima fruits on the quality characteristics and antioxidant properties of yoghurt. The extract, added to yoghurt at a concentration of 0.1% and 0.2%, contained high quantities of phenolic compounds and exhibited high antioxidant activity due to the presence of anthocyanins flavan-3-ols, flavonols and ellagitannins. Yoghurt physicochemical properties, microbiology and antioxidant properties were evaluated after 1, 7 and 14 days of storage at a temperature of 4 °C. The data revealed a positive influence of rose preparation on yoghurt’s microflora and on its other properties. The highest count of traditional yoghurt microflora was observed in samples with 0.2% of extract. Its addition had a positive effect on the yoghurts’ color, giving them a characteristic pink color of an intensity dependent on additive concentration. It also significantly affected the yoghurts’ antioxidant properties, which were stable during storage, as well as the content of the introduced phenolic compounds.
How to Become an Apomixis Model: The Multifaceted Case of Paspalum
Authors: Ortiz Juan Pablo A. , Pupilli Fulvio , Acuña Carlos A. , Leblanc Olivier , Pessino Silvina C.
Published: August 2020

In the past decades, the grasses of the Paspalum genus have emerged as a versatile model allowing evolutionary, genetic, molecular, and developmental studies on apomixis as well as successful breeding applications. The rise of such an archetypal system progressed through integrative phases, which were essential to draw conclusions based on solid standards. Here, we review the steps adopted in Paspalum to establish the current body of knowledge on apomixis and provide model breeding programs for other agronomically important apomictic crops. In particular, we discuss the need for previous detailed cytoembryological and cytogenetic germplasm characterization; the establishment of sexual and apomictic materials of identical ploidy level; the development of segregating populations useful for inheritance analysis, positional mapping, and epigenetic control studies; the development of omics data resources; the identification of key molecular pathways via comparative gene expression studies; the accurate molecular characterization of genomic loci governing apomixis; the in-depth functional analysis of selected candidate genes in apomictic and model species; the successful building of a sexual/apomictic combined breeding scheme.
Relevance of Copy Number Variation at Chromosome X in Male Fetuses Inherited from the Mother May Be Ascertained by Including Male Relatives from the Maternal Lineage in Addition to Trio Analyses
Authors: Chen Ming , Wu Wan-Ju , Lee Mei-Hui , Ku Tien-Hsiung , Ma Gwo-Chin
Published: August 2020

Chromosome microarray analysis has been used for prenatal detection of copy number variations (CNVs) and genetic counseling of CNVs has been greatly improved after the accumulation of knowledge from postnatal outcomes in terms of the genotype-phenotype correlation. However, a significant number of CNVs are still regarded as variants of unknown significance (VUS). CNVs at the chromosome X (X-CNVs) represent a unique group of genetic changes in genetic counseling; X-CNVs are similar to X-linked recessive monogenic disorders in that the prognosis in males is expected to be poor. Trio analysis is typically advised to patients with X-CNVs but such an approach may be inadequate in prenatal settings since the clinical relevance is sometimes uninformative, particularly for the maternally inherited X-CNVs in male fetuses. Here, we reported four healthy women whose male fetuses were found to have X-CNVs inherited from the mothers. The X-CNVs were initially recognized as VUS or likely pathogenic in males according to the publicly available information. After extending genetic analyses to male relatives of the maternal lineages, however, the relevance of the X-CNVs was reconsidered to be likely benign. The results highlight that an extended analysis to include more relatives, in addition to the parents, provides further information for genetic counseling when X-CNVs are encountered in prenatal settings.
Development of Chromosome Segment Substitution Lines (CSSLs) Derived from Guangxi Wild Rice (Oryza rufipogon Griff.) under Rice (Oryza sativa L.) Background and the Identification of QTLs for Plant Architecture, Agronomic Traits and Cold Tolerance
Authors: Yuan Ruizhi , Zhao Neng , Usman Babar , Luo Liang , Liao Shanyue , Qin Yufen , Nawaz Gul , Li Rongbai
Published: August 2020

Common wild rice contains valuable resources of novel alleles for rice improvement. It is well known that genetic populations provide the basis for a wide range of genetic and genomic studies. In particular, chromosome segment substitution lines (CSSLs) ais a powerful tool for fine mapping of quantitative traits, new gene discovery and marker-assisted breeding. In this study, 132 CSSLs were developed from a cultivated rice (Oryza sativa) cultivar (93-11) and common wild rice (Oryza rufipogon Griff. DP30) by selfing-crossing, backcrossing and marker-assisted selection (MAS). Based on the high-throughput sequencing of the 93-11 and DP30, 285 pairs of Insertion-deletions (InDel) markers were selected with an average distance of 1.23 Mb. The length of this DP30-CSSLs library was 536.4 cM. The coverage rate of substitution lines cumulatively overlapping the whole genome of DP30 was about 91.55%. DP30-CSSLs were used to analyze the variation for 17 traits leading to the detection of 36 quantitative trait loci (QTLs) with significant phenotypic effects. A cold-tolerant line (RZ) was selected to construct a secondary mapping F2 population, which revealed that qCT2.1 is in the 1.7 Mb region of chromosome 2. These CSSLs may, therefore, provide powerful tools for genome wide large-scale gene discovery in wild rice. This research will also facilitate fine mapping and cloning of QTLs and genome-wide study of wild rice. Moreover, these CSSLs will provide a foundation for rice variety improvement.
PreLnc: An Accurate Tool for Predicting lncRNAs Based on Multiple Features
Authors: Cao Lei , Wang Yupeng , Bi Changwei , Ye Qiaolin , Yin Tongming , Ye Ning
Published: August 2020

Accumulating evidence indicates that long non-coding RNAs (lncRNAs) have certain similarities with messenger RNAs (mRNAs) and are associated with numerous important biological processes, thereby demanding methods to distinguish them. Based on machine learning algorithms, a variety of methods are developed to identify lncRNAs, providing significant basic data support for subsequent studies. However, many tools lack certain scalability, versatility and balance, and some tools rely on genome sequence and annotation. In this paper, we propose a convenient and accurate tool “PreLnc”, which uses high-confidence lncRNA and mRNA transcripts to build prediction models through feature selection and classifiers. The false discovery rate (FDR) adjusted p-value and Z-value were used for analyzing the tri-nucleotide composition of transcripts of different species. Conclusions can be drawn from the experiment that there were significant differences in RNA transcripts among plants, which may be related to evolutionary conservation and the fact that plants are under evolutionary pressure for a longer time than animals. Combining with the Pearson correlation coefficient, we use the incremental feature selection (IFS) method and the comparison of multiple classifiers to build the model. Finally, the balanced random forest was used to construct the classifier, and PreLnc obtained 91.09% accuracy for 349,186 transcripts of animals and plants. In addition, by comparing standard performance measurements, PreLnc performed better than other prediction tools.