bluuebunny/crossref_metadata_2025 huggingface dataset:
Assisted Reproductive Technique and Abnormal Cord Insertion: A Systematic Review and Meta-Analysis
Authors: Matsuzaki Shinya , Ueda Yutaka , Matsuzaki Satoko , Nagase Yoshikazu , Kakuda Mamoru , Lee Misooja , Maeda Michihide , Kurahashi Hiroki , Hayashida Harue , Hisa Tsuyoshi , Mabuchi Seiji , Kamiura Shoji
Published: July 2022

Abnormal cord insertion (ACI) is associated with adverse obstetric outcomes; however, the relationship between ACI and assisted reproductive technology (ART) has not been examined in a meta-analysis. This study examines the association between ACI and ART, and delivery outcomes of women with ACI. A systematic review was conducted, and 16 studies (1990–2021) met the inclusion criteria. In the unadjusted pooled analysis (n = 10), ART was correlated with a higher rate of velamentous cord insertion (VCI) (odds ratio (OR) 2.14, 95% confidence interval (CI) 1.64–2.79), marginal cord insertion (n = 6; OR 1.58, 95%CI 1.26–1.99), and vasa previa (n = 1; OR 10.96, 95%CI 2.94–40.89). Nevertheless, the VCI rate was similar among the different ART types (blastocyst versus cleavage-stage transfer and frozen versus fresh embryo transfer). Regarding the cesarean delivery (CD) rate, women with VCI were more likely to have elective (n = 3; OR 1.13, 95%CI 1.04–1.22) and emergent CD (n = 5; OR 1.93, 95%CI 1.82–2.03). In conclusion, ART may be correlated with an increased prevalence of ACI. However, most studies could not exclude confounding factors; thus, further studies are warranted to characterize ART as a risk factor for ACI. In women with ACI, elective and emergent CD rates are high.
Engineering a Therapeutic Protein to Enhance the Study of Anti-Drug Immunity
Authors: Zerra Patricia E. , Parker Ernest T. , Baldwin Wallace Hunter , Healey John F. , Patel Seema R. , McCoy James W. , Cox Courtney , Stowell Sean R. , Meeks Shannon L.
Published: July 2022

The development of anti-drug antibodies represents a significant barrier to the utilization of protein-based therapies for a wide variety of diseases. While the rate of antibody formation can vary depending on the therapeutic employed and the target patient population receiving the drug, the antigen-specific immune response underlying the development of anti-drug antibodies often remains difficult to define. This is especially true for patients with hemophilia A who, following exposure, develop antibodies against the coagulation factor, factor VIII (FVIII). Models capable of studying this response in an antigen-specific manner have been lacking. To overcome this challenge, we engineered FVIII to contain a peptide (323–339) from the model antigen ovalbumin (OVA), a very common tool used to study antigen-specific immunity. FVIII with an OVA peptide (FVIII-OVA) retained clotting activity and possessed the ability to activate CD4 T cells specific to OVA323–339 in vitro. When compared to FVIII alone, FVIII-OVA also exhibited a similar level of immunogenicity, suggesting that the presence of OVA323–339 does not substantially alter the anti-FVIII immune response. Intriguingly, while little CD4 T cell response could be observed following exposure to FVIII-OVA alone, inclusion of anti-FVIII antibodies, recently shown to favorably modulate anti-FVIII immune responses, significantly enhanced CD4 T cell activation following FVIII-OVA exposure. These results demonstrate that model antigens can be incorporated into a therapeutic protein to study antigen-specific responses and more specifically that the CD4 T cell response to FVIII-OVA can be augmented by pre-existing anti-FVIII antibodies.
Thymic Extracellular Matrix in the Thymopoiesis: Just a Supporting?
Authors: Lins Marvin Paulo
Published: July 2022

The generation of T lymphocytes (thymopoiesis) is one of the major functions of the thymus that occurs throughout life. Thymic epithelial cells actively participate in this process. However, less attention has been paid to extracellular matrix (ECM) elements of thymus and their role in thymocyte differentiation. To clarify this topic, we selected some studies that deal with thymic ECM, its modulation, and its effects on thymopoiesis in different models. We emphasize that further studies are needed in order to deepen this knowledge and to propose new alternatives for thymic ECM functions during thymopoiesis.
Quantum-Chemical Modeling of the Catalytic Activity of Graphene Doped with Metal Phthalocyanines in ORR
Authors: Vinogradov Kirill Y. , Bulanova Anzhela V. , Shafigulin Roman V. , Tokranova Elena O. , Zhu Hong
Published: July 2022

The active centers of carbon catalysts doped with cobalt, nickel, copper, manganese, zinc, and chromium were modeled by density functional theory methods. Likewise, the thermodynamics of the oxygen reduction reaction (ORR) on model catalysts were determined. The features of the chemical properties of chromium-containing material, namely its spontaneous oxidation into the hydroxo form, were revealed. In addition, it was established that among the studied catalysts, graphene doped with cobalt showed the best properties.
Juglone from Walnut Produces Cardioprotective Effects against Isoproterenol-Induced Myocardial Injury in SD Rats
Authors: Ahmad Taseer , Khan Taous , Tabassum Tahira , Alqahtani Yahya S. , Mahnashi Mater H. , Alyami Bandar A. , Alqarni Ali O. , Alasmary Mohammed Y. , Almedhesh Sultan A. , Shah Abdul Jabbar
Published: July 2022

Therapeutic and/or preventive interventions using phytochemical constituents for ischemic heart disease have gained considerable attention worldwide, mainly due to their antioxidant activity. This study investigated the cardioprotective effect and possible mechanism of juglone, a major constituent of the walnut tree, using an isoproterenol (ISO)-induced myocardial infarction (MI) model in rats. Rats were pretreated for five (5) days with juglone (1, 3 mg/kg, i.p) and atenolol (1 mg/kg, i.p) in separate experiments before inducing myocardial injury by administration of ISO (80 mg/kg, s.c) at an interval of 24 h for 2 consecutive days (4th and 5th day). The cardioprotective effect of juglone was confirmed through a lead II electrocardiograph (ECG), cardiac biomarkers (cTnI, CPK, CK-MB, LDH, ALT and AST) and histopathological study. The results of our present study suggest that prior administration of juglone (1 and 3 mg/kg) proved to be effective as a cardioprotective therapeutic agent in reducing the extent of myocardial damage (induced by ISO) by fortifying the myocardial cell membrane, preventing elevated T-waves, deep Q-waves in the ECG, heart to body weight ratio, infarction and also by normalizing cardiac marker enzymes (cTnI, CPK, CK-MB, LDH, ALT and AST) and histopathological changes, such as inflammation, edema and necrosis. In conclusion, this study has identified phytochemical constituents, in particular juglone, as a potential cardioprotective agent.
Contactless Material Tensile Testing Using a High-Resolution Camera
Authors: Bulava Jaroslav , Hargaš Libor , Koniar Dušan
Published: July 2022

This article deals with the use of contactless measurement with a high-resolution imaging device during tensile testing of materials in a universal tearing machine (UTM). Setting the material parameters in tensile testing is based on changes in the geometrical properties of the sample being tested. In this article, authors propose the method and system for automated measuring the height, width, and crack occurrence during tensile testing. The system is also able to predict the location of crack occurrence. The proposed method is based on selected algorithms of image analysis, feature extraction, and template matching. Our video extensometry, working with common inspection cameras operating in visible range, can be an alternative method to expensive laser extensometry machines. The motivation of our work was to develop an automated measurement system for use in a UTM.
Consensus Recommendations to Optimize Testing for New Targetable Alterations in Non-Small Cell Lung Cancer
Authors: Ionescu Diana N. , Stockley Tracy L. , Banerji Shantanu , Couture Christian , Mather Cheryl A. , Xu Zhaolin , Blais Normand , Cheema Parneet K. , Chu Quincy S.-C. , Melosky Barbara , Leighl Natasha B.
Published: July 2022

Non-small cell lung cancer (NSCLC) has historically been associated with a poor prognosis and low 5-year survival, but the use of targeted therapies in NSCLC has improved patient outcomes over the past 10 years. The pace of development of new targeted therapies is accelerating, with the associated need for molecular testing of new targetable alterations. As the complexity of biomarker testing in NSCLC increases, there is a need for guidance on how to manage the fluid standard-of-care in NSCLC, identify pragmatic molecular testing requirements, and optimize result reporting. An expert multidisciplinary working group with representation from medical oncology, pathology, and clinical genetics convened via virtual meetings to create consensus recommendations for testing of new targetable alterations in NSCLC. The importance of accurate and timely testing of all targetable alterations to optimize disease management using targeted therapies was emphasized by the working group. Therefore, the panel of experts recommends that all targetable alterations be tested reflexively at NSCLC diagnosis as part of a comprehensive panel, using methods that can detect all relevant targetable alterations. In addition, comprehensive biomarker testing should be performed at the request of the treating clinician upon development of resistance to targeted therapy. The expert multidisciplinary working group also made recommendations for reporting to improve clarity and ease of interpretation of results by treating clinicians and to accommodate the rapid evolution in clinical actionability of these alterations. Molecular testing of all targetable alterations in NSCLC is the key for treatment decision-making and access to new therapies. These consensus recommendations are intended as a guide to further optimize molecular testing of new targetable alterations.
A Scoping Review on Outcomes and Outcome Measurement Instruments in Rehabilitative Interventions for Patients with Haematological Malignancies Treated with Allogeneic Stem Cell Transplantation
Authors: Manettas Anastasios I. , Tsaklis Panagiotis , Kohlbrenner Dario , Mokkink Lidwine B.
Published: July 2022

Rationale: Allogeneic hematopoietic stem cell transplantation (HSCT) is associated with increased treatment-related mortality, loss of physical vitality, and impaired quality of life. Future research will investigate the effects of multidisciplinary rehabilitative interventions in alleviating these problems. Nevertheless, published studies in this field show considerable heterogeneity in selected outcomes and the outcome measurement instruments used. The purpose of this scoping review is to provide an overview of the outcomes and outcome measurement instruments used in studies examining the effects of rehabilitative interventions for patients treated with allogeneic HSCT. Methods: We conducted a scoping review that included randomized controlled trials, pilot studies, and feasibility studies published up to 28 February 2022. Results: We included n = 39 studies, in which n = 84 different outcomes were used 227 times and n = 125 different instruments were used for the measurements. Conclusions: Research in the field of rehabilitation for patients with haematological malignancies treated with allogeneic HSCT is hampered by the excess outcomes used, the inconsistent outcome terminology, and the inconsistent use of measurement instruments in terms of setting and timing. Researchers in this field should reach a consensus with regard to the use of a common terminology for the outcomes of interest and a homogeneity when selecting measurement instruments and measurement timing methods.
Emerging Biomarker-Guided Therapies in Prostate Cancer
Authors: Deluce Jasna E. , Cardenas Luisa , Lalani Aly-Khan , Maleki Vareki Saman , Fernandes Ricardo
Published: July 2022

Prostate cancer remains one of the leading causes of cancer death in men worldwide. In the past decade, several new treatments for advanced prostate cancer have been approved. With a wide variety of available drugs, including cytotoxic agents, androgen receptor axis-targeted therapies, and alpha-emitting radiation therapy, identifying their optimal sequencing remains a challenge. Progress in the understanding of the biology of prostate cancer has provided an opportunity for a more refined and personalized treatment selection process. With the advancement of molecular sequencing techniques, genomic precision through the identification of potential treatment targets and predictive biomarkers has been rapidly evolving. In this review, we discussed biomarker-driven treatments for advanced prostate cancer. First, we presented predictive biomarkers for established, global standard treatments for advanced diseases, such as chemotherapy and androgen receptor axis-targeted agents. We also discussed targeted agents with recent approval for special populations, such as poly ADP ribose polymerase (PARP) inhibitors in patients with metastatic castrate-resistant prostate cancer with homologous recombination repair-deficient tumors, pembrolizumab in patients with high levels of microsatellite instability or high tumor mutational burden, and prostate-specific membrane antigen (PSMA) directed radioligand theragnostic treatment for PSMA expressing tumors. Additionally, we discussed evolving treatments, such as cancer vaccines, chimeric antigen receptor T-cells (CAR-T), Bispecific T-cell engagers (BiTEs), other targeted agents such as AKT inhibitors, and various combination treatments. In summary, advances in molecular genetics have begun to propel personalized medicine forward in the management of advanced prostate cancer, allowing for a more precise, biomarker-driven treatment selection with the goal of improving overall efficacy.
Small Cell Lung Cancer in the Course of Idiopathic Pulmonary Fibrosis—Case Report and Literature Review
Authors: Grodkiewicz Maria , Koziel Pawel , Chmielewska Izabela , Korbel Marta Adamczyk , Milanowski Janusz
Published: July 2022

Idiopathic pulmonary fibrosis is a poorly prognosed form of progressive interstitial pneumonia. Patients with IPF have a significantly increased risk of developing lung cancer, which further worsens the course of the disease. The most common histological types of LC among patients with IPF are squamous cell carcinoma and adenocarcinoma. Furthermore, all LC treatment modalities can lead to developing an acute IPF exacerbation. In this report, we present a rare case of coexistence of IPF and small cell lung cancer in a 76-year-old patient with chronic obstructive pulmonary disease, and a former smoker. For over 2 years, the patient was treated with an anti-fibrotic drug-pirfenidone, which slowed down the progression of IPF. Unfortunately, after being diagnosed with an active SCLC, the patient was excluded from further participation in the pirfenidone drug program. SCLC is characterized by high aggressiveness, rapid growth and high metastatic potential; therefore, it is necessary to apply antitumor treatment as soon as possible. The described patient was treated with carboplatin–etoposide chemotherapy. Early treatment tolerance was good and after two cycles of cytotoxic treatment, a partial response was present in CT. The presented case emphasizes the need for further research to determine the treatment regimens in patients with coexisting IPF and LC and the appropriateness of antifibrotic treatment in them. In addition, it can help to choose the treatment method for similar patients, indicating a combination of carboplatin and etoposide as an effective and, at the same time, relatively safes method in terms of the risk of IPF’s exacerbation.
Conserved Control Path in Multilayer Networks
Authors: Wang Bingbo , Ma Xiujuan , Wang Cunchi , Zhang Mingjie , Gong Qianhua , Gao Lin
Published: July 2022

The determination of directed control paths in complex networks is important because control paths indicate the structure of the propagation of control signals through edges. A challenging problem is to identify them in complex networked systems characterized by different types of interactions that form multilayer networks. In this study, we describe a graph pattern called the conserved control path, which allows us to model a common control structure among different types of relations. We present a practical conserved control path detection method (CoPath), which is based on a maximum-weighted matching, to determine the paths that play the most consistent roles in controlling signal transmission in multilayer networks. As a pragmatic application, we demonstrate that the control paths detected in a multilayered pan-cancer network are statistically more consistent. Additionally, they lead to the effective identification of drug targets, thereby demonstrating their power in predicting key pathways that influence multiple cancers.
Quantitative Identification of Internal and External Wire Rope Damage Based on VMD-AWT Noise Reduction and PSO-SVM
Authors: Tian Jie , Li Pengbo , Wang Wei , Ma Jianwu , Sun Ganggang , Wang Hongyao
Published: July 2022

As a common load-bearing component, mining wire rope produces different types of damage during a long period of operation, especially in the case of damage inside the wire rope, which cannot be identified by the naked eye, and it is difficult to accurately detect such damage using the present technology. In this study we designed a non-destructive testing device based on leakage magnetism, which can effectively detect the internal defects of wire rope damage, and carried out simulation analysis to lay a theoretical foundation for the subsequent experiments. To address the noise reduction problem in the design process, a variational mode decomposition–adaptive wavelet thresholding noise reduction method is proposed, which can improve the signal-to-noise ratio and also calculate the wavelet energy entropy in the reconstructed signal to construct multi-dimensional feature vectors. For the quantitative identification of system damage, a particle swarm optimization–support vector machine algorithm is proposed. Moreover, based on the signal following the noise reduction step, seven different feature vectors, namely, the waveform area, peak value, peak-valley value, wavelet energy entropy classification, and identification of internal and external damage defects, have been determined. The results show that the device can be used to effectively identify internal damage defects. In addition, the comparative analysis showed that the algorithm can reduce the system noise and effectively identify internal and external damage defects with a certain superiority.
Rate-Distortion-Based Stego: A Large-Capacity Secure Steganography Scheme for Hiding Digital Images
Authors: Pan Yi-Lun , Wu Ja-Ling
Published: July 2022

Steganography is one of the most crucial methods for information hiding, which embeds secret data on an ordinary file or a cover message for avoiding detection. We designed a novel rate-distortion-based large-capacity secure steganographic system, called rate-distortion-based Stego (RD-Stego), to effectively solve the above requirement. The considered effectiveness of our system design includes embedding capacity, adaptability to chosen cover attacks, and the stability of the trained model. The proposed stego scheme can hide multiple three-channel color images and QR codes within another three-channel color image with low visual distortion. Empirically, with a certain degree of robustness against the chosen cover attack, we state that the system offers up to 192+ bits-per-pixel (bpp) embedding of a payload and leaks no secret-related information. Moreover, to provide theoretical foundations for our cost function design, a mutual information-based explanation of the choices of regulation processes is herein included. Finally, we justify our system’s claimed advantages through a series of experiments with publicly available benchmark datasets.
Consensus, Polarization and Hysteresis in the Three-State Noisy q-Voter Model with Bounded Confidence
Authors: Doniec Maciej , Lipiecki Arkadiusz , Sznajd-Weron Katarzyna
Published: July 2022

In this work, we address the question of the role of the influence of group size on the emergence of various collective social phenomena, such as consensus, polarization and social hysteresis. To answer this question, we study the three-state noisy q-voter model with bounded confidence, in which agents can be in one of three states: two extremes (leftist and rightist) and centrist. We study the model on a complete graph within the mean-field approach and show that, depending on the size q of the influence group, saddle-node bifurcation cascades of different length appear and different collective phenomena are possible. In particular, for all values of q>1, social hysteresis is observed. Furthermore, for small values of q∈(1,4), disagreement, polarization and domination of centrists (a consensus understood as the general agreement, not unanimity) can be achieved but not the domination of extremists. The latter is possible only for larger groups of influence. Finally, by comparing our model to others, we discuss how a small change in the rules at the microscopic level can dramatically change the macroscopic behavior of the model.
An Algorithmic Approach to Emergence
Authors: Bédard Charles Alexandre , Bergeron Geoffroy
Published: July 2022

We suggest a quantitative and objective notion of emergence. Our proposal uses algorithmic information theory as a basis for an objective framework in which a bit string encodes observational data. A plurality of drops in the Kolmogorov structure function of such a string is seen as the hallmark of emergence. Our definition offers some theoretical results, in addition to extending the notions of coarse-graining and boundary conditions. Finally, we confront our proposal with applications to dynamical systems and thermodynamics.
The Residual ISI for Which the Convolutional Noise Probability Density Function Associated with the Blind Adaptive Deconvolution Problem Turns Approximately Gaussian
Authors: Pinchas Monika
Published: July 2022

In a blind adaptive deconvolution problem, the convolutional noise observed at the output of the deconvolution process, in addition to the required source signal, is—according to the literature—assumed to be a Gaussian process when the deconvolution process (the blind adaptive equalizer) is deep in its convergence state. Namely, when the convolutional noise sequence or, equivalently, the residual inter-symbol interference (ISI) is considered small. Up to now, no closed-form approximated expression is given for the residual ISI, where the Gaussian model can be used to describe the convolutional noise probability density function (pdf). In this paper, we use the Maximum Entropy density technique, Lagrange’s Integral method, and quasi-moment truncation technique to obtain an approximated closed-form equation for the residual ISI where the Gaussian model can be used to approximately describe the convolutional noise pdf. We will show, based on this approximated closed-form equation for the residual ISI, that the Gaussian model can be used to approximately describe the convolutional noise pdf just before the equalizer has converged, even at a residual ISI level where the “eye diagram” is still very closed, namely, where the residual ISI can not be considered as small.
On Entanglement-Assisted Multistatic Radar Techniques
Authors: Djordjevic Ivan B.
Published: July 2022

Entanglement-based quantum sensors have much better sensitivity than corresponding classical sensors in a noisy and lossy regime. In our recent paper, we showed that the entanglement-assisted (EA) joint monostatic–bistatic quantum radar performs much better than conventional radars. Here, we propose an entanglement-assisted (EA) multistatic radar that significantly outperforms EA bistatic, coherent state-based quantum, and classical radars. The proposed EA multistatic radar employs multiple entangled transmitters performing transmit-side optical phase conjugation, multiple coherent detection-based receivers serving as EA detectors, and a joint detector.
Essential Conditions for the Full Synergy of Probability of Occurrence Distributions
Authors: Mondaini Rubem P. , de Albuquerque Neto Simão C.
Published: July 2022

In this contribution, we specify the conditions for assuring the validity of the synergy of the distribution of probabilities of occurrence. We also study the subsequent restriction on the maximal extension of the strict concavity region on the parameter space of Sharma–Mittal entropy measures, which has been derived in a previous paper in this journal. The present paper is then a necessary complement to that publication. Some applications of the techniques introduced here are applied to protein domain families (Pfam databases, versions 27.0 and 35.0). The results will show evidence of their usefulness for testing the classification work performed with methods of alignment that are used by expert biologists.
Multi-Image Encryption Method via Computational Integral Imaging Algorithm
Authors: Li Xiaowu , Yu Chuying , Guo Junfeng
Published: July 2022

Under the framework of computational integral imaging, a multi-image encryption scheme based on the DNA-chaos algorithm is proposed. In this scheme, multiple images are merged to one image by a computational integral imaging algorithm, which significantly improves the efficiency of image encryption. Meanwhile, the computational integral imaging algorithm can merge images at different depth distances, thereby the different depth distances of multiple images can also be used as keys to increase the security of the encryption method. In addition, the high randomness of the chaos algorithm is combined to address the outline effect caused by the DNA encryption algorithm. We have experimentally verified the proposed multi-image encryption scheme. The entropy value of the encrypted image is 7.6227, whereas the entropy value of the merge image with two input images is 3.2886, which greatly reduces the relevance of the image. The simulation results also confirm that the proposed encryption scheme has high key security and can protect against various attacks.
CSU-Net: A CNN-Transformer Parallel Network for Multimodal Brain Tumour Segmentation
Authors: Chen Yu , Yin Ming , Li Yu , Cai Qian
Published: July 2022

Medical image segmentation techniques are vital to medical image processing and analysis. Considering the significant clinical applications of brain tumour image segmentation, it represents a focal point of medical image segmentation research. Most of the work in recent times has been centred on Convolutional Neural Networks (CNN) and Transformers. However, CNN has some deficiencies in modelling long-distance information transfer and contextual processing information, while Transformer is relatively weak in acquiring local information. To overcome the above defects, we propose a novel segmentation network with an “encoder–decoder” architecture, namely CSU-Net. The encoder consists of two parallel feature extraction branches based on CNN and Transformer, respectively, in which the features of the same size are fused. The decoder has a dual Swin Transformer decoder block with two learnable parameters for feature upsampling. The features from multiple resolutions in the encoder and decoder are merged via skip connections. On the BraTS 2020, our model achieves 0.8927, 0.8857, and 0.8188 for the Whole Tumour (WT), Tumour Core (TC), and Enhancing Tumour (ET), respectively, in terms of Dice scores.
Machine Learning Approach for Care Improvement of Children and Youth with Type 1 Diabetes Treated with Hybrid Closed-Loop System
Authors: Campanella Sara , Sabbatini Luisiana , Cherubini Valentino , Tiberi Valentina , Marino Monica , Pierleoni Paola , Belli Alberto , Boccolini Giada , Palma Lorenzo
Published: July 2022

Type 1 diabetes is a disease affecting beta cells of the pancreas and it’s responsible for a decreased insulin secretion, leading to an increased blood glucose level. The traditional method for glucose treatment is based on finger-stick measurement of the blood glucose concentration and consequent manual insulin injection. Nowadays insulin pumps and continuous glucose monitoring systems are replacing them, being simpler and automatized. This paper focuses on analyzing and improving the knowledge about which Machine Learning algorithms can work best with glycaemic data and tries to find out the relation between insulin pump settings and glycaemic control. The dataset is composed of 90 days of recordings taken from 16 children and adolescents. Three Machine Learning approaches, two for classification, Logistic Regression (LR) and Random Forest (RL), and one for regression, Multivariate Linear Regression (MLR), have been used for the purpose. Specifically, the pump settings analysis was performed based on the Time In Range (TIR) computation and comparison consequent to pump setting changes. RF and MLR have shown the best results, while, for the settings’ analysis, the data show a discrete correlation between changes and TIRs. This study provides an interesting closer look at the data recorded by the insulin pump and a suitable starting point for a thorough and complete analysis of them.
A Hybrid Inductive Power Transfer System with High Misalignment Tolerance Using Double-DD Quadrature Pads
Authors: Gong Zhaowei , Li Jingang , Tong Xiangqian , Fu Yongsheng
Published: July 2022

Inductive power transfer (IPT) has been widely adopted as an efficient and convenient charging manner for both static and in-motion EVs. In this paper, a new hybrid topology is presented to improve the coupling tolerance under pad misalignment. The double inductor–capacitor–capacitor (LCC-LCC) network and series hybrid network combining the LCC-LCC topology and series-series (SS) topology are connected in parallel to provide better tolerance against self- and mutual inductance changes, particularly with a large Z-axis transmission distance. A double-DD quadrature pad (DD2Q) consists of a Q pad, and double orthogonal DD pads are analyzed in detail, which are employed to decouple the cross-mutual inductance. Moreover, a parametric design method based on the misalignment characteristics of the DD2Q pads is also proposed to maintain relatively constant power output. A 650-W hybrid topology with a fixed operating frequency of 85 kHz was built to verify the system’s feasibility. The size of the DD2Q pads was 280 mm × 280 mm, and the air gap was 100 mm. The results clearly show that the proposed hybrid topology can achieve a fluctuation within 5% in the output current with load varying from 100% full load to 25% light load conditions when the Z-axis transmission distance varies from 80 mm to 150 mm, and the maximum efficiency can reach 91% when the Z-axis transmission distance is 80 mm.
QoS Support Path Selection for Inter-Domain Flows Using Effective Delay and Directed Acyclic Graph in Multi-Domain SDN
Authors: Lee Gyu-min , Lee Cheol-woong , Roh Byeong-hee
Published: July 2022

Currently, network applications, such as audio, video, and augmented reality, have different stringent service requirements. They require service provision through end-to-end connections via other networks with different operating environments or service conditions. Therefore, network operators require information on their own and other networks to provide end-to-end services traversing several networks while guaranteeing their quality of service (QoS) requirements. This study proposes an inter-domain flow decision method that satisfies QoS requirements using a directed acyclic graph (DAG) in multi-domain and hierarchical software defined networking (SDN) networks. There are multiple local networks with SDN controllers that are connected to the global SDN controller. The flow decision in the proposed method is based on the effective bandwidth theory of the martingale process. The effectiveness of the proposed method is demonstrated by comparing it with existing SDN-based path selection methods using the Riverbed Modeler (older, OPNET) and OpenDaylight SDN controllers.
A Survey on Intelligent-Reflecting-Surface-Assisted UAV Communications
Authors: Park Ki-Won , Kim Hyeon Min , Shin Oh-Soon
Published: July 2022

Both the unmanned aerial vehicle (UAV) and intelligent reflecting surface (IRS) are attracting growing attention as enabling technologies for future wireless networks. In particular, IRS-assisted UAV communication, which incorporates IRSs into UAV communications, is emerging to overcome the limitations and problems of UAV communications and improve the system performance. This article aims to provide a comprehensive survey on IRS-assisted UAV communications. We first present six representative scenarios that integrate IRSs and UAVs according to the installation point of IRSs and the role of UAVs. Then, we introduce and discuss the technical features of the state-of-the-art relevant works on IRS-assisted UAV communications systems from the perspective of the main performance criteria, i.e., spectral efficiency, energy efficiency, security, etc. We also introduce machine learning algorithms adopted in the previous works. Finally, we highlight technical issues and research challenges that need to be addressed to realize IRS-assisted UAV communications systems.
A New Explicit Numerical Schemes for Time-Dependent PDEs with Application to Pressure Driven Fluid Flow in a Rectangular Duct
Authors: Nawaz Yasir , Arif Muhammad Shoaib , Shatanawi Wasfi , Bibi Mairaj
Published: July 2022

A modified class of temporal discretization schemes for partial differential equations (PDEs) is proposed, explicit and second to fifth-order accurate in time. In time, the stability region of the proposed modified second-order scheme is larger than the standard second-order Adams–Bashforth method constructed on two time levels. A modification made for the Du Fort–Frankel method was also implemented in the proposed second-order scheme, which permits the little larger stability region, but the scheme becomes first-order accurate. Since the Du Fort–Frankel method cannot be employed without a modification of averaging in time levels, the proposed second-order scheme can be used without any modification. The proposed modified scheme with different orders in space and second orders in time was implemented for heat and mass transfer of chemically reactive fluid flow in a rectangular duct. The flow is generated due to applying different pressure gradients. The contour plots of velocity, temperature, and concentration profiles are portrayed at different pressure gradients; Péclet number in heat transfer, Péclet number in mass transfer, reaction parameter, and at different times. In addition, stability and convergence conditions for the considered system of linear and non-linear PDEs consisting of non-dimensional momentum, energy, and concentration equations were found for two cases. The displayed graphs depict the transfer of heat in the fluid, which rises due to heated boundaries, and the transfer of mass in the fluid at various moments. Classical models can be solved using the proposed method, which has a faster convergence rate than the standard or classical approach. This approach is illustrated through computer simulations that demonstrate its key computational features. It is believed that the data presented in this study will serve as a useful source for future fluid flow investigations to be conducted in an industrial setting within an enclosed area.
Sub-Optimal Stabilizers of the Pendubot Using Various State Space Representations
Authors: Pazderski Dariusz , Parulski Paweł , Bartkowiak Patryk , Herman Przemysław
Published: July 2022

This paper considers the issue of linear-quadratic regulator (LQR) design for nonlinear systems with the use of smooth state and input transformations. The proposed design methodology is considered in the stabilisation task of the Pendubot, which is based on the concept of feedback equivalent control systems. It turns out that it is possible to find a controller that ensures comparable dynamics of the closed-loop system in the vicinity of the set point regardless of the state-space representation adopted. In addition, the synthesis of suboptimal controllers according to the LQR strategy ensuring equal dynamics at the equilibrium point is presented. The properties of the studied controllers were investigated in a simulation environment and using experimental tests. The detailed forms of transformations and linear approximations given can be regarded as ready-made procedures that can be applied to stabilise similar mechanical systems in robotics.
Proposal on New Tariffs with a Price Option per Use Time: Application to the Cooperativa Eléctrica San Pedro de Atacama (CESPA) Microgrid in Chile
Authors: García-Santander Luis , Pérez Martínez Jorge , Carrizo Dante , Ulloa Vásquez Fernando , Esparza Vladimir , Araya José
Published: July 2022

In this paper, a pricing alternative based on the scheme of Time of Use Pricing (TOUP) is proposed for customers connected to the Cooperativa Eléctrica San Pedro de Atacama (CESPA) microgrid, located in the far north of Chile. With this proposal, the promotion of Demand-Side Management, DSM, aims at optimizing both the use of electric energy and the available infrastructure. The pricing proposal replaces the current tariff scheme based on sections of energy consumption and does not give an incentive for customers to efficiently manage their energy consumption. The proposal considers the creation of time bands and their corresponding tariff formulas, to obtain economic benefits both for customers and the electric company. Study cases consider the operation of a photovoltaic plant of 2 MWp in the electric system of CESPA, which is currently underway. The obtained results report benefits for all parts of the electric market. For customers, favorable pricing up to a 19.1% monthly reduction in electric bills is shown, whereas the company presents an increment in their average monthly income of about 7.7%.
A Review on Industrial Perspectives and Challenges on Material, Manufacturing, Design and Development of Compressed Hydrogen Storage Tanks for the Transportation Sector
Authors: Alves Mariana Pimenta , Gul Waseem , Cimini Junior Carlos Alberto , Ha Sung Kyu
Published: July 2022

Hydrogen fuel cell technology is securing a place in the future of advanced mobility and the energy revolution, as engineers explore multiple paths in the quest for decarbonization. The feasibility of hydrogen-based fuel cell vehicles particularly relies on the development of safe, lightweight and cost-competitive solutions for hydrogen storage. After the demonstration of hundreds of prototype vehicles, today, commercial hydrogen tanks are in the first stages of market introduction, adopting configurations that use composite materials. However, production rates remain low and costs high. This paper intends to provide an insight into the evolving scenario of solutions for hydrogen storage in the transportation sector. Current applications in different sectors of transport are covered, focusing on their individual requirements. Furthermore, this work addresses the efforts to produce economically attractive composite tanks, discussing the challenges surrounding material choices and manufacturing practices, as well as cutting-edge trends pursued by research and development teams. Key issues in the design and analysis of hydrogen tanks are also discussed. Finally, testing and certification requirements are debated once they play a vital role in industry acceptance.
Relationships between Combustion Behavior in Air and the Chemical Structure of Bituminous Coal during Combustion Processes
Authors: Qiu Shuxing , Reddy Ramana G. , Huang Xianyou , Yin Chen , Zhang Shengfu
Published: July 2022

The structural parameters of five bituminous coals were analyzed by using X-ray diffraction and attenuated total reflection–Fourier transform infrared spectroscopy. The combustion behavior of coal was investigated by using a thermogravimetric analyzer under air conditions. Furthermore, the relationships between combustion parameters and the coal structure were established. The results show that bituminous coals contain crystalline and amorphous carbon. The aromaticity, interlayer spacing, average stacking height, aliphatic chain length, and the hydrocarbon-generating potential varied with the different bituminous coals. The coal samples exhibited similar weight changes during the combustion process, and the combustion parameters increased with increments in heating rate. The maximum combustion rate and activation energy increased with declining interlayer spacing and hydrocarbon-generating potential and increasing aromaticity, average stacking height, and aliphatic chain length. The bituminous coal for the utilization of combustion should have high aromaticity, a degree of graphitization, crystalline, long aliphatic chain length, and weak hydrocarbon-generating potential.
Circuit-Based Rainflow Counting Algorithm in Application of Power Device Lifetime Estimation
Authors: Cheng Tian , Lu Dylan Dah-Chuan , Siwakoti Yam P.
Published: July 2022

The software-assisted reliability assessment of power electronic converters is increasingly important due to its multi-domain nature and extensive parametric calculations. The rainflow counting algorithm is gaining popularity for its low relative error in device lifetime estimation. Nevertheless, the offline operation of the algorithm prevents most simulation software packages considering other parameters for the device under study, such as aging and the current state of health in the estimation, as it requires a complete loading profile to run recursive comparison. This also brings difficulties in realization in circuit simulators such as SPICE. To tackle the issue, an in-the-loop circuit-based rainflow counting algorithm is proposed in this paper, and applied to estimate the consumed lifetime of the MOSFET in a boost converter for illustration. Instantaneous electrical and thermal performances, and the accumulated stress of the device can be monitored. Not only does this assist in evaluating the state of health of a device, but also allows the possibility of integrating the aging into the lifetime evaluation. The method follows the four-point rainflow counting algorithms, which continuously compares three adjacent temperature fluctuations ΔTj to select full cycles for two rounds, and the remaining cycles are counted as half cycles. To validate the performance, a comparative analysis in terms of counting accuracy and simulation speed was performed alongside the proposed method, MATLAB® and also with a well-accepted half-cycle counting method. Reported results show that the proposed method has an improved counting accuracy compared to the half-cycle counting from 24% to 3.5% on average under different load stresses and length conditions. The accuracy can be effectively improved by a further 1.3–2% by adding an extra comparison round.
Performance Analysis Based on Thermal Aging Tests of Sol-Gel and Polymer Insulated Wires by Enameling and Extrusion Technology
Authors: Pereira dos Santos Lima Giovana , Ait-Amar Sonia , Velu Gabriel , Frezel Philippe , Boudiba Abdelhamid , Poelman Mireille , Nicolay Arnaud , Herze Pierre-Yves
Published: July 2022

This research activity aims to evaluate electrical insulation system (EIS) intended for electrical machine winding wires. The evaluation is based on mechanical, thermal, and electrical properties tests following international standards for enameled wires. Dielectric parameters such as dissipation factor, partial discharge inception voltage (PDIV), parallel capacitance, and parallel resistance behavior of different insulator configurations on twisted-pair samples are observed during thermal aging tests. Those configurations are formed of different combinations of dielectric layers based on conventional polymers (polyester-imide (PEI), polyamide-imide (PAI), polyimide (PI)) used as coating wires. A study using two mineral varnishes (silica-based) obtained by the sol-gel process integrated on these classical enamels an outer layer of extrusion of thermoplastic polymer with and without mineral fillers. Given the high consummation of energy and the use of unsustainable materials involving the production of wires, the principal interest of this work is to exploit new configurations of coating wire produced, with less environmental impact than conventional ones. This work investigates the impact of filled resins on the performance of insulating samples and the influence of the use of sol-gel solutions (mineral varnishes) on the insulated wire to increase the thermal class.
Smart Hydropower Water Distribution Networks, Use of Artificial Intelligence Methods and Metaheuristic Algorithms to Generate Energy from Existing Water Supply Networks
Authors: Karakatsanis Diamantis , Theodossiou Nicolaos
Published: July 2022

In this paper, the possibility of installing small hydraulic turbines in existing water-supply networks, which exploit the daily pressure fluctuations in order to produce energy, is examined. For this purpose, a network of five pressure sensors is developed, which is connected to an artificial intelligence system in order to predict the daily pressure values of all nodes of the network. The sensors are placed at the critical nodes of the network. The locations of the critical nodes are implemented by applying graph theory algorithms to the water distribution network. EPANET software is used to generate the artificial intelligence training data with an appropriate external call from a Python script. Then, an improvement model is implemented using the Harmony Search Algorithm in order to calculate the daily pressure program, which can be allocated to the turbines and, consequently, the maximum energy production. The proposed methodology is applied to a benchmark water supply network and the results are presented.
Defining and Operationalizing Sustainability in the Context of Energy
Authors: Reijnders Lucas
Published: July 2022

The terms sustainable and sustainability are currently often used in scientific journals, including Energies. There are cases where these terms are defined or operationalized, but more often they are not. This is problematic, as there are reportedly hundreds of (different) definitions and operationalizations (in terms of standards or goals) of sustainability. This large number has its roots in history. Many current definitions and operationalizations of sustainability are social constructs. As these constructs vary, there can be variation in the characterization of specific ways to provide energy as sustainable or not sustainable. There are also definitions of sustainability that have emerged from the sciences. These definitions can also lead to differences in the characterization of specific ways to provide energy as sustainable or not sustainable. In view thereof, there is a case to define and/or operationalize sustainable and sustainability when these terms are used in the context of energy.
Continuous Line Loss Calculation Method for Distribution Network Considering Collected Data of Different Densities
Authors: Li Yuying , Ma Xiping , Liang Chen , Li Yaxin , Cai Zhou , Jiang Tong
Published: July 2022

In order to find the causes of statistical line loss abnormalities and propose better loss reduction strategies, it is necessary to improve the accuracy of theoretical line loss calculations. Since Distributed Generation (DG) access to the distribution network causes variability of power flow in the distribution network within a short period, the error of the traditional line loss calculation method increases. For the line loss calculation of medium-voltage distribution networks containing DGs with high-density collection data, a continuous line loss calculation method for the distribution network was proposed, aiming at improving the accuracy compared with the traditional line loss calculation method. The proposed method makes full use of the high-density collection data on the dispatch side and DG side, distributing the supply power to each load node by power to calculate real-time power flow, thus obtaining a more credible line loss value. The effectiveness and accuracy of the proposed method were verified in the IEEE 17-node distribution system.