bluuebunny/crossref_metadata_2025 huggingface dataset:
Aircraft Trajectory Clustering in Terminal Airspace Based on Deep Autoencoder and Gaussian Mixture Model
Authors: Zeng Weili , Xu Zhengfeng , Cai Zhipeng , Chu Xiao , Lu Xiaobo
Published: September 2021

The aircraft trajectory clustering analysis in the terminal airspace is conducive to determining the representative route structure of the arrival and departure trajectory and extracting their typical patterns, which is important for air traffic management such as airspace structure optimization, trajectory planning, and trajectory prediction. However, the current clustering methods perform poorly due to the large flight traffic, high density, and complex airspace structure in the terminal airspace. In recent years, the continuous development of Deep Learning has demonstrated its powerful ability to extract internal potential features of large dataset. Therefore, this paper mainly tries a deep trajectory clustering method based on deep autoencoder (DAE). To this end, this paper proposes a trajectory clustering method based on deep autoencoder (DAE) and Gaussian mixture model (GMM) to mine the prevailing traffic flow patterns in the terminal airspace. The DAE is trained to extract feature representations from historical high-dimensional trajectory data. Subsequently, the output of DAE is input into GMM for clustering. This paper takes the terminal airspace of Guangzhou Baiyun International Airport in China as a case to verify the proposed method. Through the direct visualization and dimensionality reduction visualization of the clustering results, it is found that the traffic flow patterns identified by the clustering method in this paper are intuitive and separable.
Improved Conservation of Coffee (Coffea arabica L.) Germplasm via Micropropagation and Cryopreservation
Authors: Valdés Yanelis Castilla , Shukla Mukund R. , González Vega María Esther , Saxena Praveen K.
Published: September 2021

Coffee (Coffea spp.) is an important tropical agricultural crop that has significant economic and social importance in the world. The ex situ conservation of plant genetic resources through seeds is not feasible due to the sensitivity of coffee seed to desiccation and low temperatures. The cryopreservation of zygotic embryos may allow for an efficient and long-term storage of coffee germplasm. This study describes the cryopreservation methods for conserving zygotic embryos of Coffea arabica L. for the long-term conservation of currently available germplasm. Zygotic embryos were successfully cryopreserved in liquid nitrogen at −196 °C under controlled environmental conditions with either droplet-vitrification or encapsulation–vitrification protocols without dehydration. Zygotic embryos had the highest regrowth (100%) following droplet-vitrification cryopreservation using the Plant Vitrification Solution 3 (PVS3) for 40 min at 23 °C. In the case of encapsulation–vitrification using PVS3 for 40 min at 23 °C, the embryo regeneration response was 78%. Plantlets were recovered following shoot multiplication using a temporary immersion system (TIS) and in vitro rooting. The prolific rooting of shoots was observed after 4 weeks of culture in the liquid medium with plugs made of the inert substrate Oasis® In vitro Express (IVE) compared to the semi-solid medium. The successful cryopreservation of coffee zygotic embryos using droplet vitrification and encapsulation–vitrification followed by micropropagation in temporary immersion culture system has not been reported earlier and together these technologies are anticipated to further facilitate the initiatives for the conservation and distribution of coffee germplasm.
Alternatives to Fight Vancomycin-Resistant Staphylococci and Enterococci
Authors: Baëtz Benjamin , Boudrioua Abdelhakim , Hartke Axel , Giraud Caroline
Published: September 2021

Gram positive pathogens are a significant cause of healthcare-associated infections, with Staphylococci and Enterococci being the most prevalent ones. Vancomycin, a last resort glycopeptide, is used to fight these bacteria but the emergence of resistance against this drug leaves some patients with few therapeutic options. To counter this issue, new generations of antibiotics have been developed but resistance has already been reported. In this article, we review the strategies in place or in development to counter vancomycin-resistant pathogens. First, an overview of traditional antimicrobials already on the market or in the preclinical or clinical pipeline used individually or in combination is summarized. The second part focuses on the non-traditional antimicrobials, such as antimicrobial peptides, bacteriophages and nanoparticles. The conclusion is that there is hitherto no substitute equivalent to vancomycin. However, promising strategies based on drugs with multiple mechanisms of action and treatments based on bacteriophages possibly combined with conventional antibiotics are hoped to provide treatment options for vancomycin-resistant Gram-positive pathogens.
Spatiotemporal Correlation-Based Accurate 3D Face Imaging Using Speckle Projection and Real-Time Improvement
Authors: Xiong Wei , Yang Hongyu , Zhou Pei , Fu Keren , Zhu Jiangping
Published: September 2021

The reconstruction of 3D face data is widely used in the fields of biometric recognition and virtual reality. However, the rapid acquisition of 3D data is plagued by reconstruction accuracy, slow speed, excessive scenes and contemporary reconstruction-technology. To solve this problem, an accurate 3D face-imaging implementation framework based on coarse-to-fine spatiotemporal correlation is designed, improving the spatiotemporal correlation stereo matching process and accelerating the processing using a spatiotemporal box filter. The reliability of the reconstruction parameters is further verified in order to resolve the contention between the measurement accuracy and time cost. A binocular 3D data acquisition device with a rotary speckle projector is used to continuously and synchronously acquire an infrared speckle stereo image sequence for reconstructing an accurate 3D face model. Based on the face mask data obtained by the high-precision industrial 3D scanner, the relationship between the number of projected speckle patterns, the matching window size, the reconstruction accuracy and the time cost is quantitatively analysed. An optimal combination of parameters is used to achieve a balance between reconstruction speed and accuracy. Thus, to overcome the problem of a long acquisition time caused by the switching of the rotary speckle pattern, a compact 3D face acquisition device using a fixed three-speckle projector is designed. Using the optimal combination parameters of the three speckles, the parallel pipeline strategy is adopted in each core processing unit to maximise system resource utilisation and data throughput. The most time-consuming spatiotemporal correlation stereo matching activity was accelerated by the graphical processing unit. The results show that the system achieves real-time image acquisition, as well as 3D face reconstruction, while maintaining acceptable systematic precision.
Reinforcement Learning and Physics
Authors: Martín-Guerrero José D. , Lamata Lucas
Published: September 2021

Machine learning techniques provide a remarkable tool for advancing scientific research, and this area has significantly grown in the past few years. In particular, reinforcement learning, an approach that maximizes a (long-term) reward by means of the actions taken by an agent in a given environment, can allow one for optimizing scientific discovery in a variety of fields such as physics, chemistry, and biology. Morover, physical systems, in particular quantum systems, may allow one for more efficient reinforcement learning protocols. In this review, we describe recent results in the field of reinforcement learning and physics. We include standard reinforcement learning techniques in the computer science community for enhancing physics research, as well as the more recent and emerging area of quantum reinforcement learning, inside quantum machine learning, for improving reinforcement learning computations.
Online Control for Biped Robot with Incremental Learning Mechanism
Authors: Yang Liang , Lai Guanyu , Chen Yong , Guo Zhihui
Published: September 2021

In this paper, we develop a new online walking controller for biped robots, which integrates a neural-network estimator and an incremental learning mechanism to improve the control performance in dynamic environment. With the aid of an iteration algorithm for updating, some newly incoming data can be used straightforwardly to update into the original well-trained model, in order to avoid a time-consuming retraining procedure. On the other hand, how to maintain the zero-moment-point stability and counteract the effect of yaw moment simultaneously is also a key technical problem to be addressed. To this end, an interval type-2 fuzzy weight identifier is newly developed, which assigns weight for each walking sample to deal with the imbalanced distribution problem of training data. The effectiveness of the proposed control scheme has been verified through a full-dynamics simulation and a practical robot experiment.
OT-Equator® Attachments Comparison for Retaining an Early Loaded Implant Overdenture on Two or Three Implants: 1 Year RCT Preliminary Data
Authors: Tallarico Marco , Cervino Gabriele , Montanari Marco , Scrascia Roberto , Ferrari Emiliano , Casucci Alessio , Xhanari Erta , Lupi Saturnino Marco , Meloni Silvio , Ceruso Francesco Mattia , Rodriguez y Baena Ruggero , Cicciù Marco
Published: September 2021

The purpose of this multicenter randomized controlled trial was to compare the clinical, radiographic, and patient-centered outcomes of early loaded mandibular overdentures deliberately placed on two or three implants. The outcomes were: implant and prosthesis success and survival rates; biological and technical complications; marginal bone loss; patient satisfaction; and periodontal parameters. The results showed no differences between the groups in any of the outcomes analyzed. With the limitations of the present study, and looking at long-term follow-up, the gold standard of prosthetic rehabilitations with attachments, in agreement with the scientific community, should prefer two non-splinted implants.
High-Efficiency Closed-Loop Control of a Robotic Fish via Virtual Musculoskeletal Methodology
Authors: Xu Dong , Zhang Yuanlin , Fan Hongjie , Meng Cai
Published: September 2021

Improving propulsion efficiency holds the promise of enabling the robotic fish to work for a long time with a limited battery in its small body. In this paper, for the swimming of a bionic robotic fish, we present a virtual musculoskeletal control method from the bionic model of the joint driven by agonist muscle and antagonist muscle. A closed-loop method composed of two loops is proposed as a rule of thumb for the speed control of the robotic fish. The outer loop adjusts the swimming speed using the speed deviation; the inner loop regulates the stiffness according to the virtual muscle spindle feedback to fit the water environment. Compared with the proportion control, the evaluation results show that the virtual musculoskeletal methodology increases the efficiency by 3.4% in the steady flow and 7% in the Karman-vortex flow. This algorithm provides a new idea for the joint-space control of the bionic robots that need to reduce the energy consumption of movements.
Identification of Bioactive Plant Volatiles for the Carob Moth by Means of GC-EAD and GC-Orbitrap MS
Authors: Hosseini Seyed Ali , Goldansaz Seyed Hossein , Groot Astrid T. , Menken Steph B. J. , Van Der Wielen Frans , Wissel Cedric , Vercammen Joeri , De Rijke Eva , Roessingh Peter
Published: September 2021

The aim of this study was to validate a workflow that allows structural identification of plant volatiles that induce a behavioral response in insects. Due to the complexity of plant volatile emissions and the low levels at which these bioactive components tend to occur, gas chromatography-electroantennography (GC-EAD) was applied as the prime differentiator technique, i.e., to indicate particular peaks of interest in the chromatogram. In a next step, the analysis was repeated under identical conditions using GC-Orbitrap mass spectrometry (MS). Combining electron impact (EI) ionization and chemical ionization (CI) with the superior spectral resolution and mass accuracy of the technique enabled straightforward identification of these unknowns, with high confidence in a minute amount of time. Moreover, because of the intrinsic sensitivity of the technique, components that occur at trace amounts but may induce disproportional large behavioral responses are evenly well-identified. We were able to positively identify β-caryophyllene as a bioactive compound in female carob moths. Behavioral attraction was negatively correlated with the amount of β-caryophyllene in host fruits. In an oviposition experiment on filter paper, β-caryophyllene was stimulated in the range of 40–100 ng, while concentrations above 200 ng inhibited oviposition.
Removal of Heavy Metals (Cd2+, Cu2+, Ni2+, Pb2+) from Aqueous Solution Using Hizikia fusiformis as an Algae-Based Bioadsorbent
Authors: Pham Bich Ngoc , Kang Jin-Kyu , Lee Chang-Gu , Park Seong-Jik
Published: September 2021

This study investigated the applicability of algae (Hizikia fusiformis, Green gracilaria, and Codium fragile) for removing heavy metals (Cd2+, Cu2+, Ni2+, and Pb2+) from aqueous solutions. Among the algae, H. fusiformis was chosen as a bioadsorbent and modified with NaOH and HCl. The results showed that the biosorption capacity of H. fusiformis improved significantly after treatment with NaOH; however, H. fusiformis modified with HCl did not achieve the expected value. The NaOH treatment enhanced the biosorption of metals on the treated H. fusiformis because of the hydrolysis reaction producing carboxylic (–COOH) and hydroxyl groups (–OH). The kinetics for Cd2+, Cu2+, Ni2+, and Pb2+ biosorption well fitted to pseudo-first-order, pseudo-second-order, and Elovich models, with R2 of >0.994. The Freundlich model provided a good fit for the equilibrium biosorption of Cd2+, Cu2+, and Ni2+ by both algae and the Langmuir model for Pb2+. The maximum biosorption of metals was in the order Pb2+ >> Cu2+ ≈ Ni2+ > Cd2+, with qmax of 167.73, 45.09, 44.38, and 42.08 mg/g, respectively. With an increase in the solution pH, metal biosorption was enhanced, and considerable enhancement was observed in the pH range of 2–4. Thus, H. fusiformis is expected to be considered a superior candidate for metal biosorption.
Analysis of Tidal Accelerations in the Solar System and in Extrasolar Planetary Systems
Authors: Paschek Klaus , Roßmann Arthur , Hausmann Michael , Hildenbrand Georg
Published: September 2021

Volcanism powered by tidal forces inside celestial bodies can provide enough energy to keep important solvents for living systems in the liquid phase. A prerequisite to calculate such tidal interactions and consequences is depending on simulations for tidal accelerations in a multi-body system. Unfortunately, from measurements in many extrasolar planetary systems, only few physical and orbital parameters are well-known enough for investigated celestial bodies. For calculating tidal acceleration vectors under missing most orbital parameter exactly, a simulation method is developed that is only based on a few basic parameters, easily measurable even in extrasolar planetary systems. Such a method as the one presented here allows finding a relation between the tidal acceleration vectors and potential heating inside celestial objects. Using the values and results of our model approach to our solar system as a “gold standard” for feasibility allowed us to classify this heating in relation to different forms of volcanism. This “gold standard” approach gave us a classification measure for the relevance of tidal heating in other extrasolar systems with a reduced availability of exact physical parameters. We help to estimate conditions for the identification of potential candidates for further sophisticated investigations by more complex established methods such as viscoelastic multi-body theories. As a first example, we applied the procedures developed here to the extrasolar planetary system TRAPPIST-1 as an example to check our working hypothesis.
Cross-Correlation Wavelet-Domain-Based Particle Swarm Optimization for Lightning Mapping
Authors: Alammari Ammar , Alkahtani Ammar Ahmed , Ahmad Mohd Riduan , Aljanad Ahmed , Noman Fuad , Kawasaki Zen
Published: September 2021

Several processing methods have been proposed for estimating the real pattern of the temporal location and spatial map of the lightning strikes. However, due to the complexity of lightning signals, providing accurate lightning maps estimation remains a challenging task. This paper presents a cross-correlation wavelet-domain-based particle swarm optimization (CCWD-PSO) technique for an accurate and robust representation of lightning mapping. The CCWD method provides an initial estimate of the lightning map, while the PSO attempts to optimize the trajectory of the lightning map by finding the optimal sliding window of the cross-correlation. The technique was further enhanced through the introduction of a novel lightning event extraction method that enables faster processing of the lightning mapping. The CCWD-PSO method was validated and verified using three narrow bipolar events (NBEs) flashes. The observed results demonstrate that this technique offers high accuracy in representing the real lightning mapping with low estimation errors.
Statistical Riemann and Lebesgue Integrable Sequence of Functions with Korovkin-Type Approximation Theorems
Authors: Srivastava Hari Mohan , Jena Bidu Bhusan , Paikray Susanta Kumar
Published: September 2021

In this work we introduce and investigate the ideas of statistical Riemann integrability, statistical Riemann summability, statistical Lebesgue integrability and statistical Lebesgue summability via deferred weighted mean. We first establish some fundamental limit theorems connecting these beautiful and potentially useful notions. Furthermore, based upon our proposed techniques, we establish the Korovkin-type approximation theorems with algebraic test functions. Finally, we present two illustrative examples under the consideration of positive linear operators in association with the Bernstein polynomials to exhibit the effectiveness of our findings.
Adding New Pieces to the Puzzle of Karyotype Evolution in Harttia (Siluriformes, Loricariidae): Investigation of Amazonian Species
Authors: Sassi Francisco de M. C. , Moreira-Filho Orlando , Deon Geize A. , Sember Alexandr , Bertollo Luiz A. C. , Liehr Thomas , Oliveira Vanessa C. S. , Viana Patrik F. , Feldberg Eliana , Vicari Marcelo R. , Cioffi Marcelo de B.
Published: September 2021

A remarkable morphological diversity and karyotype variability can be observed in the Neotropical armored catfish genus Harttia. These fishes offer a useful model to explore both the evolution of karyotypes and sex chromosomes, since many species possess male-heterogametic sex chromosome systems and a high rate of karyotype repatterning. Based on the karyotype organization, the chromosomal distribution of several repetitive DNA classes, and the rough estimates of genomic divergences at the intraspecific and interspecific levels via Comparative Genomic Hybridization, we identified shared diploid chromosome numbers (2n = 54) but different karyotype compositions in H. dissidens (20m + 26sm + 8a) and Harttia sp. 3 (16m + 18sm + 14st + 6a), and different 2n in H. guianensis (2n = 58; 20m + 26sm + 2st + 10a). All species further displayed similar patterns of chromosomal distribution concerning constitutive heterochromatin, 18S ribosomal DNA (rDNA) sites, and most of the surveyed microsatellite motifs. Furthermore, differences in the distribution of 5S rDNA sites and a subset of microsatellite sequences were identified. Heteromorphic sex chromosomes were lacking in H. dissidens and H. guianensis at the scale of our analysis. However, one single chromosome pair in Harttia sp. 3 males presented a remarkable accumulation of male genome-derived probe after CGH, pointing to a tentative region of early sex chromosome differentiation. Thus, our data support already previously outlined evidence that Harttia is a vital model for the investigation of teleost karyotype and sex chromosome dynamics.
Microorganisms of Two Thermal Pools on Kunashir Island, Russia
Authors: Rozanov Aleksei S. , Korzhuk Anton V. , Shekhovtsov Sergei V. , Vasiliev Gennady V. , Peltek Sergei E.
Published: September 2021

The Kuril Archipelago is a part of the Circum-Pacific Belt (Ring of Fire). These islands have numerous thermal springs. There are very few studies on these microbial communities, and none of them have been conducted by modern molecular biological methods. Here we performed the first metagenomic study on two thermophilic microbial communities of Kunashir Island. Faust Lake is hot (48 °C) and highly acidic (pH 2.0). We constructed 28 metagenome-assembled genomes as well as 17 16S ribosomal RNA sequences. We found that bottom sediments of Faust Lake are dominated by a single species of red algae belonging to the Cyanidiaceae family. Archaeans in Faust Lake are more diverse than bacteria but less abundant. The Tretyakovsky Thermal Spring is also hot (52 °C) but only weakly acidic (pH 6.0). It has much higher microbial diversity (233 metagenome-assembled genomes; 93 16S ribosomal RNAs) and is dominated by bacteria, with only several archaeans and one fungus. Despite their geographic proximity, these two thermal springs were found to not share any species. A comparison of these two lakes with other thermal springs of the Circum-Pacific Belt revealed that only a few members of the communities are shared among different locations.
Genetically Encoded Sensor Cells for the Screening of Glucocorticoid Receptor (GR) Effectors in Herbal Extracts
Authors: Kang Chungwon , Kim Soyoun , Lee Euiyeon , Ryu Jeahee , Lee Minhyeong , Kwon Youngeun
Published: September 2021

Although in vitro sensors provide facile low-cost ways to screen for biologically active targets, their results may not accurately represent the molecular interactions in biological systems. Cell-based sensors have emerged as promising platforms to screen targets in biologically relevant environments. However, there are few examples where cell-based sensors have been practically applied for drug screening. Here, we used engineered cortisol-detecting sensor cells to screen for natural mimetics of cortisol. The sensor cells were designed to report the presence of a target through signal peptide activation and subsequent fluorescence signal translocation. The developed sensor cells were able to detect known biological targets from human-derived analytes as well as natural product extracts, such as deer antlers and ginseng. The multi-use capability and versatility to screen in different cellular environments were also demonstrated. The sensor cells were used to identify novel GR effectors from medicinal plant extracts. Our results suggest that decursin from dongquai had the GR effector function as a selective GR agonist (SEGRA), making it a potent drug candidate with anti-inflammatory activity. We demonstrated the superiority of cell-based sensing technology over in vitro screening, proving its potential for practical drug screening applications that leads to the function-based discovery of target molecules.
Industry 4.0, Disaster Risk Management and Infrastructure Resilience: A Systematic Review and Bibliometric Analysis
Authors: Habibi Rad Mahyar , Mojtahedi Mohammad , Ostwald Michael J.
Published: September 2021

The fourth industrial era, known as ‘Industry 4.0’ (I4.0), aided and abetted by the digital revolution, has attracted increasing attention among scholars and practitioners in the last decade. The adoption of I4.0 principles in Disaster Risk Management (DRM) research and associated industry practices is particularly notable, although its origins, impacts and potential are not well understood. In response to this knowledge gap, this paper conducts a systematic literature review and bibliometric analysis of the application and contribution of I4.0 in DRM. The systematic literature review identified 144 relevant articles and then employed descriptive and content analysis of a focused set of 70 articles published between 2011 and 2021. The results of this review trace the growing trend for adoption of I4.0 tools and techniques in disaster management, and in parallel their influence in resilient infrastructure and digital construction fields. The results are used to identify six dominant clusters of research activity: big data analytics, Internet of Things, prefabrication and modularization, robotics and cyber-physical systems. The research in each cluster is then mapped to the priorities of the Sendai framework for DRR, highlighting the ways it can support this international agenda. Finally, this paper identifies gaps within the literature and discusses possible future research directions for the combination of I4.0 and DRM.
Iron-Zinc Co-Doped Titania Nanocomposite: Photocatalytic and Photobiocidal Potential in Combination with Molecular Docking Studies
Authors: Riaz Nadia , Fen Debra Adelina Chia Siew , Khan Muhammad Saqib , Naz Sadia , Sarwar Rizwana , Farooq Umar , Bustam Mohamad Azmi , Batiha Gaber El-Saber , El Azab Islam H. , Uddin Jalal , Khan Ajmal
Published: September 2021

In the current research study, iron-zinc co-doped TiO2 was reported as an energy efficient material for the degradation of DIPA and inactivation of E. coli and S. aureus under visible light irradiation. In addition, molecular docking simulation was performed to provide further insight into possible targets for inhibiting bacterial development. The synthesized nanocomposites were screened and optimized for different synthesis and reaction parameters. The physicochemical properties of the synthesized nanocomposites were evaluated through different characterization techniques. The wet impregnation (WI) approach was among the most successful methods for the synthesis of Fe-Zn-TiO2 nanocomposite (NC) utilizing anatase titanium. Moreover, 66.5% (60 min reaction time) and 100% (190 min reaction time) chemical oxygen demand (COD) removal was obtained through optimized NC, i.e., 0.1Fe-0.4Zn metal composition and 300 °C calcination temperature. The energy consumption for the best NC was 457.40 KW h m−3. Moreover, 0.1Fe-0.4Zn-TiO2-300 was more efficient against S. aureus compared to E. coli with 100% reduction in 90 min of visible light irradiations. Furthermore, 0.1Fe-0.4Zn-TiO2-300 NC showed that the binding score for best docked conformation was −5.72 kcal mol−1 against β-lactamase from E. coli and −3.46 kcal mol−1 from S. aureus. The studies suggested the Fe-Zn in combination with TiO2 to be a possible inhibitor of β-lactamase that can be further tested in enzyme inhibition studies.
Motivation and Sense of Belonging in the Large Enrollment Introductory General and Organic Chemistry Remote Courses
Authors: Cox Charles T. , Stepovich Nicole , Bennion Alexandra , Fauconier Jessie , Izquierdo Nicole
Published: September 2021

The rapid shift from face-to-face to remote instruction in 2020 has resulted in recalibration of lecture and laboratory pedagogy. This research analyzed the impact of remote learning on student motivation and sense of belonging in large enrollment chemistry courses. Student responses were parsed according to specific demographics including gender, academic standing, first-generation status, and ethnicity. Research objectives included the analysis of how remote learning impacted specific demographics to develop guidelines for best practices moving forward for hybrid or online courses. Our findings show that second year students (sophomores) were the most impacted of the academic standing cohorts. Sophomores reported a statistically greater change in motivation after the start of the semester and statistically lower satisfaction with their performance on assignments. Females reported statistically lower motivation and a statistically lower sense of belonging in the course and science, technology, engineering, and mathematics (STEM) fields. Black/African students reported a statistically lower motivation for remote learning than Asian/Pacific Islander and White/Caucasian students. Finally, both White/Caucasian and Black/African students reported a statistically lower sense of belonging in the course and in STEM fields than Asian/Pacific islander students. Finally, statistical differences were not observed based upon first-generation status. The research indicates that students were differentially impacted by the shift to remote learning. From these findings, a stronger understanding of how specific demographics are differentially impacted by remote learning in STEM courses is provided, granting greater insight into best practices moving forward.
Analysis of an Inhomogeneous Circularly Polarized Hollow Dielectric Resonator Antenna Using Perturbation Theory
Authors: Sehrawat Neetu , Kanaujia Binod Kumar , Agarwal Anshul , Varshney Gaurav
Published: September 2021

The perturbation approach is presented here for the first time for the analysis of an inhomogeneous circularly polarized rectangular dielectric resonator (DR) antenna (DRA). The inhomogeneous permittivity is created by perturbing a rectangle-shaped region of different material inside the rectangular dielectric resonator antenna (RDRA). The orthogonal degenerate modes with a phase difference of TE111x, and TE111y, are excited simultaneously for achieving circular polarization. A simple expression for the calculation of the resonant frequency and optimal axial ratio point for a circularly polarized (CP) inhomogeneous RDRA is presented here. Theoretical results obtained from the proposed theory are compared with theoretical, simulated, and experimental data available in the literature. The proposed analysis results show optimal axial ratio point calculations within a 1% range of the simulated and experimental data, which is better than the previous transverse transmission line reported method, having an error of approximately 4%. The advantages, accuracy, and simplicity of perturbation theory for DR are discussed in detail. The proposed theory can be easily extended for higher order modes and other shapes of material perturbation and anisotropic DRAs. The proposed technique will help in incorporation of the perturbation in the DR so that CP radiation can be obtained in an easy way.
Extending OTDR Distance Span by External Front-End Optical Preamplifier
Authors: Lipovac Adriana , Lipovac Vlatko , Hamza Mirza , Batoš Vedran
Published: September 2021

Optical time-domain reflectometer (OTDR) is used to characterize fiber optic links by identifying and localizing various refractive and reflective events such as breaks, splices, and connectors, and measuring insertion/return loss and fiber length. Essentially, OTDR inserts a pulsed signal into the fiber, from which a small portion that is commonly referred to as Rayleigh backscatter, is continuously reflected back with appropriate delays of the reflections expressed as the power loss versus distance, by conveniently scaling the time axis. Specifically, for long-distance events visibility and measurement accuracy, the crucial OTDR attribute is dynamic range, which determines how far downstream the fiber can the strongest transmitted optical pulse reach. As many older-generation but still operable OTDR units have insufficient dynamic range to test the far-end of longer fibers, we propose a simple and cost-effective solution to reactivate such an OTDR by inserting a low-noise high-gain optical preamplifier in front of it to lower the noise figure and thereby the noise floor. Accordingly, we developed an appropriate dynamic range and distance span extension model which provided the exemplar prediction values of 30 dB and 75 km, respectively, for the fiber under test at 1550 nm. These values were found to closely match the dynamic range and distance span extensions obtained for the same values of the relevant parameters of interest by the preliminary practical OTDR measurements conducted with the front-end EDFA optical amplifier, relative to the measurements with the OTDR alone. This preliminary verifies that the proposed concept enables a significantly longer distance span than the OTDR alone. We believe that the preliminary results reported here could serve as a hint and a framework for a more comprehensive test strategy in terms of both test diversification and repeating rate, which can be implemented in a network operator environment or professional lab.
Soliton Waves in Lossy Nonlinear Transmission Lines at Microwave Frequencies: Analytical, Numerical and Experimental Studies
Authors: Sekulic Dalibor L. , Samardzic Natasa M. , Mihajlovic Zivorad , Sataric Miljko V.
Published: September 2021

In this paper, we performed analytical, numerical and experimental studies on the generation of soliton waves in discrete nonlinear transmission lines (NLTL) with varactors, as well as the analysis of the losses impact on the propagation of these waves. Using the reductive perturbation method, we derived a nonlinear Schrödinger (NLS) equation with a loss term and determined an analytical expression that completely describes the bright soliton profile. Our theoretical analysis predicts the carrier wave frequency threshold above which a formation of bright solitons can be observed. We also performed numerical simulations to confirm our analytical results and we analyzed the space–time evolution of the soliton waves. A good agreement between analytical and numerical findings was obtained. An experimental prototype of the lossy NLTL, built at the discrete level, was used to validate our proposed model. The experimental shape of the envelope solitons is well fitted by the theoretical waveforms, which take into account the amplitude damping due to the losses in commercially available varactors and inductors used in a prototype. Experimentally observed changes in soliton amplitude and half–maximum width during the propagation along lossy NLTL are in good accordance with the proposed model defined by NLS equation with loss term.
Implementation of Snubber Circuits in a PV-Based Off-Grid Electric Vehicle Charging Station—Comparative Case Studies
Authors: Krishnan Nair Divya , Prasad Krishnamachar , Lie Tek Tjing
Published: September 2021

With the penetration of electric vehicles (EVs), there have been paradigm shifts in the transportation sector. EVs are ideally considered to be clean and eco-friendly, but they can overload the existing grid infrastructure and significantly contribute towards carbon emissions depending on the source of charging. The ideal solution is to develop a charging infrastructure for EVs that is integrated with solar energy technology. This paper presents the design of a zero-voltage switching snubber-based bidirectional converter for an off-grid charging station for EVs. The proposed system includes a solar array with a boost converter, a bidirectional converter with snubber circuits and an energy storage unit. A comprehensive comparison between various types of snubbers, such as the resistive capacitive diode snubber, active clamp snubber and flyback snubber, is presented. This type of system configuration clamps the rail voltage, due to the difference in current between leakage inductance and low voltage side-fed inductor currents, resulting in reduced current spikes at the converter’s switches. Such a converter, therefore, leads to higher efficiency of the charging station for EVs. The design of a snubber-based off-grid charging station for EVs is formulated and validated in the MATLAB/Simulink environment.
Impact of Wind and Solar Generation on the Italian Zonal Electricity Price
Authors: Hosseini Imani Mahmood , Bompard Ettore , Colella Pietro , Huang Tao
Published: September 2021

This paper assesses the impact of increasing wind and solar power generation on zonal market prices in the Italian electricity market from 2015 to 2019, employing a multivariate regression model. A significant aspect to be considered is how the additional wind and solar generation brings changes in the inter-zonal export and import flows. We constructed a zonal dataset consisting of electricity price, demand, wind and solar generation, net input flow, and gas price. In the first and second steps of this study, the impact of additional wind and solar generation that is distributed across zonal borders is calculated separately based on an empirical approach. Then, the Merit Order Effect of the intermittent renewable energy sources is quantified in every six geographical zones of the Italian day-ahead market. The results generated by the multivariate regression model reveal that increasing wind and solar generation decreases the daily zonal electricity price. Therefore, the Merit Order Effect in each zonal market is confirmed. These findings also suggest that the Italian electricity market operator can reduce the National Single Price by accelerating wind and solar generation development. Moreover, these results allow to generate knowledge advantageous for decision-makers and market planners to predict the future market structure.
Reliability Updating of Offshore Wind Substructures by Use of Digital Twin Information
Authors: Augustyn Dawid , Ulriksen Martin D. , Sørensen John D.
Published: September 2021

This paper presents a probabilistic framework for updating the structural reliability of offshore wind turbine substructures based on digital twin information. In particular, the information obtained from digital twins is used to quantify and update the uncertainties associated with the structural dynamics and load modeling parameters in fatigue damage accumulation. The updated uncertainties are included in a probabilistic model for fatigue damage accumulation used to update the structural reliability. The updated reliability can be used as input to optimize decision models for operation and maintenance of existing structures and design of new structures. The framework is exemplified based on two numerical case studies with a representative offshore wind turbine and information acquired from previously established digital twins. In this context, the effect of updating soil stiffness and wave loading, which constitute two highly uncertain and sensitive parameters, is investigated. It is found that updating the soil stiffness significantly affects the reliability of the joints close to the mudline, while updating the wave loading significantly affects the reliability of the joints localized in the splash zone. The increased uncertainty related to virtual sensing, which is employed to update wave loading, reduces structural reliability.
Management of Lignocellulosic Waste towards Energy Recovery by Pyrolysis in the Framework of Circular Economy Strategy
Authors: Poskart Anna , Skrzyniarz Magdalena , Sajdak Marcin , Zajemska Monika , Skibiński Andrzej
Published: September 2021

The article presents the possibilities of effective management of lignocellulosic waste by including it in the circular economy. The pyrolysis process was chosen as the thermal conversion method. This approach, due to a high flexibility of the obtained products, better quality of the solid residue (char), and the lower emission of pollutants into the atmosphere, e.g., SO2 and NOx, is a competitive solution compared to combustion process. Wood waste from alder and pine were analyzed. As part of laboratory tests, the elementary composition was determined, i.e., C, H, N, S, and O. The pyrolysis process was carried out at a temperature of 600 °C on an experimental stand for the conversion of solid fuels in a stationary bed. For the obtained data, using the Ansys Chemkin-Pro calculation tool, the detailed chemical composition of gaseous products of the pyrolysis process was modeled for a varying temperature range and residence time in the reactor. The studies have shown that for certain process conditions it is possible to obtain a high calorific value of pyrolytic gas, up to 25 MJ/m3.
Automatic Generation Control of Multi-Source Interconnected Power System Using FOI-TD Controller
Authors: Daraz Amil , Malik Suheel Abdullah , Waseem Athar , Azar Ahmad Taher , Haq Ihsan Ul , Ullah Zahid , Aslam Sheraz
Published: September 2021

Automatic Generation Control (AGC) delivers a high quality electrical energy to energy consumers using efficient and intelligent control systems ensuring nominal operating frequency and organized tie-line power deviation. Subsequently, for the AGC analysis of a two-area interconnected hydro-gas-thermal-wind generating unit, a novel Fractional Order Integral-Tilt Derivative (FOI-TD) controller is proposed that is fine-tuned by a powerful meta-heuristic optimization technique referred as Improved-Fitness Dependent Optimizer (I-FDO) algorithm. For more realistic analysis, various constraints, such as Boiler Dynamics (BD), Time Delay (TD), Generation Rate Constraint (GRC), and Governor Dead Zone (GDZ) having non-linear features are incorporated in the specified system model. Moreover, a comparative analysis of I-FDO algorithm is performed with state-of-the-art approaches, such as FDO, teaching learning based optimization, and particle swarm optimization algorithms. Further, the proposed I-FDO tuned controller is compared with Fractional Order Tilt Integral Derivative (FOTID), PID, and Integral-Tilt Derivative (I-TD) controllers. The performance analysis demonstrates that proposed FOI-TD controller provides better performance and show strong robustness by changing system parameters and load condition in the range of Â ± 50%, compared to other controllers.
Air-Gap Flux Oriented Vector Control Based on Reduced-Order Flux Observer for EESM
Authors: Cai Feng , Li Ke , Sun Xiaodong , Wu Minkai
Published: September 2021

Electrically excited synchronous motor (EESM) has the characteristics of high order, nonlinear and strong coupling, so it is difficult to be controlled. However, it has the advantages of adjustable power factor, high efficiency, and high precision torque control, so it is widely used in high-power applications. The accuracy of a flux observer influences the speed control system of EESM. Based on state observer in modern control theory and electrical excitation synchronous machine state equation, a reduced-order flux observer is designed. Using the first-order difference method and forward bilinear transformation method, the reduced-order flux observer is discrete, and the stability of the motor system is analyzed. The analysis shows that the stability of the system using the bilinear transformation method is better than that using the first order forward difference method. In motor operation, motor parameters will be affected by the factors of temperature, magnetic saturation, and motor frequency. In this paper, the influence of parameter variation on the motor system is studied by using the variation of the pole distribution. Finally, the speed regulation system using the reduced-order observer is simulated, which verifies the accuracy of the reduced-order flux observer observation.
Preference for Number of Friends in Online Social Networks
Authors: Meng Fanhui , Sun Haoming , Xie Jiarong , Wang Chengjun , Wu Jiajing , Hu Yanqing
Published: September 2021

Preferences or dislikes for specific numbers are ubiquitous in human society. In traditional Chinese culture, people show special preference for some numbers, such as 6, 8, 10, 100, 200, etc. By analyzing the data of 6.8 million users of Sina Weibo, one of the largest online social media platforms in China, we discover that users exhibit a distinct preference for the number 200, i.e., a significant fraction of users prefer to follow 200 friends. This number, which is very close to the Dunbar number that predicts the cognitive limit on the number of stable social relationships, motivates us to investigate how the preference for numbers in traditional Chinese culture is reflected on social media. We systematically portray users who prefer 200 friends and analyze their several important social features, including activity, popularity, attention tendency, regional distribution, economic level, and education level. We find that the activity and popularity of users with the preference for the number 200 are relatively lower than others. They are more inclined to follow popular users, and their social portraits change relatively slowly. Besides, users who have a stronger preference for the number 200 are more likely to be located in regions with underdeveloped economies and education. That indicates users with the preference for the number 200 are likely to be vulnerable groups in society and are easily affected by opinion leaders.
Changes of the Microbiota Composition on the Surface of Pig Carcasses during Chilling and Its Associations with Alterations in Chiller’s Temperature and Air Humidity
Authors: Jia Xiaonan , Nian Yingqun , Zhao Di , Wu Juqing , Li Chunbao
Published: September 2021

In this study, we investigated changes of microbiota composition on the surface of pig carcasses during chilling and their associations with temporal and spatial changes of wind speed, air temperature, and air humidity. The composition of microbiota on a carcass surface varied greatly with sampling sites; in particular, the surfaces of forelegs and neck had higher load of microorganisms and different microbiota composition compared to in the air and other carcass parts. However, such a difference in the microbiota composition decreased as chilling time extended. The positive detection ratios of microbial genes resistant to sulfonamides, quinolones, tetracyclines, and β-lactams were found different greatly with chilling time and sampling sites. The β-lactam and tetracycline resistant genes were observed in higher ratios in airborne microorganisms in the chiller, while the sulfa and tetracycline resistant genes had higher ratios in the microbiota on pig carcasses. Actual measurements and dynamic simulation showed that air temperature and humidity varied greatly among different places in a chiller within the first 8 h of chilling, with higher values close to the door, but the differences became smaller afterwards. The micro-environmental differences and changes in the chiller may cause the different composition of microbiota on pig carcasses.
Leaf Morpho-Colorimetric Characterization of Different Grapevine Varieties through Changes on Plant Water Status
Authors: Gutiérrez-Gamboa Gastón , Torres-Huerta Nicolás , Araya-Alman Miguel , Verdugo-Vásquez Nicolás , Moreno-Simunovic Yerko , Valdés-Gómez Héctor , Acevedo-Opazo César
Published: September 2021

(1) Background: Currently, some ampelographic methods are developing in order to identify grapevine varieties. For this purpose, morpho-colorimetric parameters in leaves have been analyzed by digital imagen analysis, but some environmental conditions may affect their determinations. (2) Methods: A research study was conducted to characterize leaf morpho-colorimetric parameters in five grapevine varieties growing under different plant water status and to discriminate them under these conditions. Leaves were collected in vines, and twelve leaf morpho-colorimetric and fractal dimension variables were assessed. (3) Results: Merlot presented the highest values of perimeter and area to perimeter ratio in leaves and higher leaf area than Chardonnay in both plant water conditions. Most of the leaf morpho-colorimetric variables allowed discriminating the grapevine varieties under the contrasted hydric conditions. Under non-water stress, Carmenère was not related to any measured parameters. Merlot was positively related to most of the leaf morphometric parameters, whereas Chardonnay presented the opposite behavior. RGB color system variables allowed discriminating the grapevine varieties under water stress conditions, and Sauvignon Blanc was not related to any measured parameter. Chardonnay and Pinot Noir were positively related to green color and negatively related to most of the leaf morphometric parameters, whereas Merlot showed the opposite behavior. (4) Conclusions: Leaf morpho-colorimetric and fractal dimension parameters were affected by plant water stress and more variables should be incorporated into the new ampelographic methods in order to characterize leaf morpho-colorimetric parameters of the different grapevine varieties more clearly.