bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental and Numerical Assessments of New Concrete Dry Connections concerning Potentials of the Robotic Subtractive Manufacturing Technique
Authors: Baghdadi Abtin , Heristchian Mahmoud , Ledderose Lukas , Kloft Harald
Published: January 2023

The efficient utilization of robotic construction of structures requires a review of structural material, elements and details, while traditional construction methods face difficulties in producing some dry concrete joints, robotic methods can manufacture them efficiently. With the rapid advancement of new construction methods, more effort should be directed towards developing new types of joints manufactureable by Additive Manufacturing (AM) methods. Accordingly, considering the potentials of robotic techniques, this article proposes eight new concrete dry joints. Concrete portal frames with two identical joints at the end of the beam are cast and evaluated under bending and shear. The performance of each joint, evaluated by experimental and numerical studies based on the crack distribution and stresses, was discussed. Furthermore, various aspects of the process of robotic subtractive manufacturing of the connections are discussed through the selected printed/milled geometries; likewise, geometrical accuracy by microscanning was measured, proving this technique’s capability (methodology). Based on findings, some proposed joints that can be manufactured entirely and quickly by robotic additive and subtractive techniques structurally can produce the full strength of the monolithic reference section. The range of the capacities and initial stiffness is, accordingly, [50%, 106%] and [51%, 124%] of the monolithic elements.
Hydrogen Evolution Reaction Activities of Room-Temperature Self-Grown Glycerol-Assisted Nickel Chloride Nanostructures
Authors: Shinde Nanasaheb M. , Raut Siddheshwar D. , Ghule Balaji G. , Deokate Ramesh J. , Narwade Sandesh H. , Mane Rajaram S. , Xia Qixun , Pak James J. , Kim Jeom-Soo
Published: January 2023

Three-dimensional nanomaterials of desired structural/morphological properties and highly porous with a high specific surface area are important in a variety of applications. In this work, glycerol-mediated self-growth of 3-D dandelion flower-like nickel chloride (NiCl2) from nickel-foam (NiF) is obtained for the first time using a room-temperature (27 °C) processed wet chemical method for electrocatalysis application. Glycerol-mediated self-grown NiCl2 flowers demonstrate an excellent electrocatalytic performance towards the hydrogen evolution reaction (HER), which is much superior to the NiF (303 mV) and NiCl2 electrode prepared without glycerol (208 mV) in the same electrolyte solution. With a Tafel slope of 41 mV dec−1, the NiCl2 flower electrode confirms improved reaction kinetics as compared to the other two electrodes, i.e., NiF (106 mVdec−1) and NiCl2 obtained without glycerol (56 mV dec−1). The stability of the glycerol-based NiCl2 electrode has further been carried out for 2000 cycles with the overpotential diminution of just 8 mV, approving an electrocatalyst potential of glycerol-based NiCl2 electrode towards HER kinetics. This simple and easy growth process involves nucleation, aggregation, and crystal growth steps for producing NiCl2 nanostructures for electrocatalytic water splitting application through the HER process.
Multifunctional Hybrid Nanozymes for Magnetic Enrichment and Bioelectrocatalytic Sensing of Circulating Tumor RNA during Minimal Residual Disease Monitoring
Authors: Koo Kevin M.
Published: January 2023

Iron oxide nanozymes are a form of nanomaterial with both superparamagnetic and enzyme-mimicking properties. Ongoing research efforts have been made to create multifunctional iron oxide hybrid nanozymes with auxiliary properties through biomolecular modifications. Such iron oxide hybrid nanozymes can be useful for rapid and cost-effective analysis of circulating tumor nucleic acids (ctNAs) in patient liquid biopsies during minimal residual disease (MRD) monitoring of cancer recurrence. Herein, the use of streptavidin-modified iron oxide hybrid nanozymes is reported for magnetic enrichment and bioelectrocatalytic sensing of three prostate cancer (PCa) ctRNA biomarkers with high detection specificity and sensitivity (10 copies) over an ultrabroad dynamic range (five orders of magnitude). Furthermore, the feasibility of ctRNA analysis for pre- and post-cancer treatment MRD monitoring is demonstrated using PCa urinary liquid biopsy samples.
Drug Prescriptions Requiring Compounding at a Canadian University Affiliated Pediatric Hospital: A Cross-Sectional Study
Authors: Landry Émilie Kate , Autmizguine Julie , Bérubé Sophie , Kraus Raphael , Métras Marie-Élaine , Lebel Denis , Litalien Catherine
Published: January 2023

Despite ongoing international efforts, many drugs administered to children must be compounded from dosage forms designed for adults because they remain unavailable in commercial formulations that suit their needs. Even though oral drug compounding is common in pediatrics, the extent of this practice has not been well described in recent years. This cross-sectional and retrospective study was conducted at a Canadian university-affiliated, 484-bed, tertiary care pediatric hospital and its rehabilitation centre on two randomly selected days. A total of 606 hospitalized children with 5465 prescriptions were included. Overall, compounded drugs for enteral administration (CDEA) represented 13% of all prescriptions (enteral and parenteral) and 23% of prescriptions for enteral administration. Of the 390 prescribed drugs, 122 required compounding. CDEA were mostly liquids (n = 478 [67%]) and mainly included drugs of the central nervous (35%), cardiovascular (21%), and gastro-intestinal (12%) systems. Nearly half (N = 298 [49%]) of children had at least one CDEA prescribed in their medical file. Many CDEA are available as commercial products in other jurisdictions. Collaboration is needed between all stakeholders to make these drugs available to Canadian children.
A Link between Parental Psychopathology and Preschool Depression: Take Care of Parents to Take Care of Children
Authors: Martucci Melania , Aceti Franca , Giacchetti Nicoletta , Scarselli Veronica , Sogos Carla
Published: January 2023

There is a lot of evidence in the literature showing that early-onset depression determines an emotional and cognitive vulnerability for psychiatric disorders in subsequent years. AIMS: The first aim of this outcome research was to analyze the impact of parental support treatment in a sample of depressed preschool children divided into two groups of comparison (under-reactive and over-reactive) through evolution in the Clinical Global Impression (CGI). The second aim was to analyze the correlation between the presence of parental psychopathology and the severity of children’s disorders. METHODS: Our clinical sample consisted of 32 preschool-age children with a final diagnosis of MDD. The children’s assessment included a psychiatric assessment to establish a diagnosis of MDD, confirmed by means of a semi-structured interview, which was administered again one month after the end of parental treatment. All the parents began a six-month parent training treatment conducted by experienced child psychiatrists, whereas children were not treated. During this period, the Clinical Global Impression Scale (CGI) was filled out monthly in order to observe the evolution of the children’s disorders. Results: Post-hoc tests showed a significant difference from before the treatment to after the treatment only in the over-reactive group (p = 0.00). Regarding parental psychiatric disorders, in the over-reactive group, only 3 children had no parents with psychopathology. In the under-reactive group, no child lacked a parent with psychopathology. Conclusion: Parent training treatment seems to be a valid intervention to improve preschool depression, especially in over-reactive groups, and to prevent dysfunctional parental styles connected to parental psychopathology.
Conservation and Management of Protected Areas in China and India: A Literature Review (1990–2021)
Authors: Gao Wen , Huang Jiefan , Qiu Quan , Shrestha Anil , Yuan Changyan , Anand Subhash , Wang Guibin , Wang Guangyu
Published: January 2023

Protected areas (PAs) are key to biodiversity conservation. As two highly populous and biodiverse countries, China and India are facing similar socioenvironmental pressures in the management of PAs. A comparative analysis of studies of PA policies in these two countries provides an objective assessment of policy concerns. This study involved a bibliometric analysis of studies of PA policies in China and India. Relevant publications were retrieved from the Web of Science and Scopus. The analysis was carried out using the Bibliometrix R Package, CiteSpace, and VOSviewer. The results indicate that PA policies studies in China are growing at an exponential rate, while Indian studies were cited significantly more often. “Environmental protection” was the main focus of the Chinese studies, with top keywords including “forest ecosystem” and “strategic approach”. In India, research was mainly focused on “wildlife management”, and the top keywords were “climate change” and “ecosystem service”. Studies from both countries were concerned with natural resource conservation and endangered species. Studies in India began relatively earlier and were more developed. India focused on people-related themes, while China emphasized strategic approaches. China is improving its system of PA and should learn from India to consider the relationship between environmental protection and people.
Enhancing the Structural, Optical, Thermal, and Electrical Properties of PVA Filled with Mixed Nanoparticles (TiO2/Cu)
Authors: Al-Hakimi Ahmed , Asnag G. , Alminderej Fahad , Alhagri Ibrahim , Al-Hazmy Sadeq , Qahtan Talal
Published: January 2023

In this work, new samples of PVA-TiO2/Cu nanocomposites were prepared via the casting method. The prepared samples were examined using different analytical methods. An XRD analysis showed the semi-crystalline nature of the PVA polymer, as well as showing a decrease in the degree of the crystallinity of the PVA structure as a result of the addition of the mixed nanoparticles. TEM images indicate the spherical shape of the Cu NPs, with a size ranging from 2 to 22 nm, and the rectangular shape of the TiO2 NPs, with a size ranging from 5 to 25 nm. It was evident via FTIR measurements that there were interactions between the functional groups of the PVA and the TiO2/Cu NPs. The optical properties of the PVA nanocomposites were improved with an increase in the content of the TiO2/Cu nanoparticles, as shown via a UV/Vis analysis. DSC curves showed an improvement in the thermal stability of the PVA-TiO2/Cu nanocomposites after the embedding of the TiO2/Cu nanoparticles. It was evident using impedance spectroscopy that the AC conductivity was improved by adding the TiO2 and Cu nanoparticles to the polymeric matrix. The maximum AC conductivity was found at 1.60 wt.% of TiO2/Cu nanoparticles in the PVA polymer, and this was 13.80 × 10−6 S/cm at room temperature. Relaxation occurred as a result of the charge carrier hopping between the localized state and the correlated barriers hopping model, describing the dominant mechanism, as presented in an electrical modulus analysis. These results indicate that the PVA-TiO2/Cu nanocomposite samples can be used in energy storage capacitor applications and in the alternative separator-rechargeable lithium-ion battery industry.
Analysis of Survival in Complete Pathological Response after Long-Course Chemoradiotherapy in Patients with Advanced Rectal Cancer
Authors: Ulusoy Cemal , Kamalı Gülçin Harman , Nikolovski Andrej
Published: January 2023

Background: Neoadjuvant chemoradiotherapy prior to surgery is the standard treatment for locally advanced rectal cancer. This consists in the patient’s complete pathological response being achieved with no residual tumor presence in the resected specimen, which results in survival improvement. Methods: This retrospective study aimed to examine the rate of complete pathological response in patients with advanced rectal cancer treated with neoadjuvant long-course chemoradiotherapy and to examine the survival differences between the different tumor regression grade (TRG) scores. Results: A total of 154 patients were operated prior to long-course chemoradiotherapy with a total of 50 Gy plus FOLFOX protocol. Complete pathologic response was achieved in 29 (18.8%) patients. There was no statistical difference for the different pathologic responses according to gender, type of surgery, and number of harvested lymph nodes. Mean survival for all the groups was 37.2 months. Survival within a different TRG score exhibited statistical significance (p = 0.006). Overall, the survival rate during the follow-up period was of 81.8%. Conclusions: The complete pathological response rate in this study was of 18.8%. High tumor regression grade scores (TRG0 and TRG1) had a survival rate of over 90% during follow-up. Multivariate analysis identified perineural invasion and tumor regression grade as independent factors that affect survival.
Fast Track Diagnostic Tools for Clinical Management of Sepsis: Paradigm Shift from Conventional to Advanced Methods
Authors: Gupta Ena , Saxena Juhi , Kumar Sanni , Sharma Umang , Rastogi Saundarya , Srivastava Vijay Kumar , Kaushik Sanket , Jyoti Anupam
Published: January 2023

Sepsis is one of the deadliest disorders in the new century due to specific limitations in early and differential diagnosis. Moreover, antimicrobial resistance (AMR) is becoming the dominant threat to human health globally. The only way to encounter the spread and emergence of AMR is through the active detection and identification of the pathogen along with the quantification of resistance. For better management of such disease, there is an essential requirement to approach many suitable diagnostic techniques for the proper administration of antibiotics and elimination of these infectious diseases. The current method employed for the diagnosis of sepsis relies on the conventional culture of blood suspected infection. However, this method is more time consuming and generates results that are false negative in the case of antibiotic pretreated samples as well as slow-growing microbes. In comparison to the conventional method, modern methods are capable of analyzing blood samples, obtaining accurate results from the suspicious patient of sepsis, and giving all the necessary information to identify the pathogens as well as AMR in a short period. The present review is intended to highlight the culture shift from conventional to modern and advanced technologies including their limitations for the proper and prompt diagnosing of bloodstream infections and AMR detection.
Natural Language Processing Applications for Computer-Aided Diagnosis in Oncology
Authors: Li Chengtai , Zhang Yiming , Weng Ying , Wang Boding , Li Zhenzhu
Published: January 2023

In the era of big data, text-based medical data, such as electronic health records (EHR) and electronic medical records (EMR), are growing rapidly. EHR and EMR are collected from patients to record their basic information, lab tests, vital signs, clinical notes, and reports. EHR and EMR contain the helpful information to assist oncologists in computer-aided diagnosis and decision making. However, it is time consuming for doctors to extract the valuable information they need and analyze the information from the EHR and EMR data. Recently, more and more research works have applied natural language processing (NLP) techniques, i.e., rule-based, machine learning-based, and deep learning-based techniques, on the EHR and EMR data for computer-aided diagnosis in oncology. The objective of this review is to narratively review the recent progress in the area of NLP applications for computer-aided diagnosis in oncology. Moreover, we intend to reduce the research gap between artificial intelligence (AI) experts and clinical specialists to design better NLP applications. We originally identified 295 articles from the three electronic databases: PubMed, Google Scholar, and ACL Anthology; then, we removed the duplicated papers and manually screened the irrelevant papers based on the content of the abstract; finally, we included a total of 23 articles after the screening process of the literature review. Furthermore, we provided an in-depth analysis and categorized these studies into seven cancer types: breast cancer, lung cancer, liver cancer, prostate cancer, pancreatic cancer, colorectal cancer, and brain tumors. Additionally, we identified the current limitations of NLP applications on supporting the clinical practices and we suggest some promising future research directions in this paper.
Computer-Aided Detection and Classification of Monkeypox and Chickenpox Lesion in Human Subjects Using Deep Learning Framework
Authors: Uzun Ozsahin Dilber , Mustapha Mubarak Taiwo , Uzun Berna , Duwa Basil , Ozsahin Ilker
Published: January 2023

Monkeypox is a zoonotic viral disease caused by the monkeypox virus. After its recent outbreak, it has become clear that a rapid, accurate, and reliable diagnosis may help reduce the risk of a future outbreak. The presence of skin lesions is one of the most prominent symptoms of the disease. However, this symptom is also peculiar to chickenpox. The resemblance in skin lesions in the human subject may disrupt effective diagnosis and, as a result, lead to misdiagnosis. Such misdiagnosis can lead to the further spread of the disease as it is a communicable disease and can eventually result in an outbreak. As deep learning (DL) algorithms have recently been regarded as a promising technique in medical fields, we have been attempting to integrate a well-trained DL algorithm to assist in the early detection and classification of skin lesions in human subjects. This study used two open-sourced digital skin images for monkeypox and chickenpox. A two-dimensional convolutional neural network (CNN) consisting of four convolutional layers was applied. Afterward, three MaxPooling layers were used after the second, third, and fourth convolutional layers. Finally, we evaluated the performance of our proposed model with state-of-the-art deep-learning models for skin lesions detection. Our proposed CNN model outperformed all DL models with a test accuracy of 99.60%. In addition, a weighted average precision, recall, F1 score of 99.00% was recorded. Subsequently, Alex Net outperformed other pre-trained models with an accuracy of 98.00%. The VGGNet consisting of VGG16 and VGG19 performed least well with an accuracy of 80.00%. Due to the uniqueness of the proposed model and image augmentation techniques applied, the proposed CNN model is generalized and avoids over-fitting. This model would be helpful for the rapid and accurate detection of monkeypox using digital skin images of patients with suspected monkeypox.
Sand Discharge Simulation and Flow Path Optimization of a Particle Separator
Authors: Du Zhou , Ma Yulin , Xu Quanyong , Wu Feng
Published: January 2023

A numerical simulation method is used to optimize the removal of sand from a helicopter engine particle separator. First, the classic configuration of a particle separator based on the literature is simulated using two boundary conditions. The results show that the boundary conditions for the total pressure inlet and mass flow outlet are much more closely aligned with the experimental environment. By modifying the material at the front of the shroud, the separation efficiencies of coarse Arizona road dust (AC-Coarse) and MIL-E-5007C (C-Spec) can be improved to 93.3% and 97.6%, respectively. Configuration modifications of the particle separator with dual protection can increase the separation efficiencies of AC-Coarse and C-Spec to 91.7% and 97.7%.
On the Image Reconstruction of Capacitively Coupled Electrical Resistance Tomography (CCERT) with Entropy Priors
Authors: Su Zenglan , Soleimani Manuchehr , Jiang Yandan , Ji Haifeng , Wang Baoliang
Published: January 2023

Regularization with priors is an effective approach to solve the ill-posed inverse problem of electrical tomography. Entropy priors have been proven to be promising in radiation tomography but have received less attention in the literature of electrical tomography. This work aims to investigate the image reconstruction of capacitively coupled electrical resistance tomography (CCERT) with entropy priors. Four types of entropy priors are introduced, including the image entropy, the projection entropy, the image-projection joint entropy, and the cross-entropy between the measurement projection and the forward projection. Correspondingly, objective functions with the four entropy priors are developed, where the first three are implemented under the maximum entropy strategy and the last one is implemented under the minimum cross-entropy strategy. Linear back-projection is adopted to obtain the initial image. The steepest descent method is utilized to optimize the objective function and obtain the final image. Experimental results show that the four entropy priors are effective in regularization of the ill-posed inverse problem of CCERT to obtain a reasonable solution. Compared with the initial image obtained by linear back projection, all the four entropy priors make sense in improving the image quality. Results also indicate that cross-entropy has the best performance among the four entropy priors in the image reconstruction of CCERT.
Mining Mobile Network Fraudsters with Augmented Graph Neural Networks
Authors: Hu Xinxin , Chen Haotian , Chen Hongchang , Li Xing , Zhang Junjie , Liu Shuxin
Published: January 2023

With the rapid evolution of mobile communication networks, the number of subscribers and their communication practices is increasing dramatically worldwide. However, fraudsters are also sniffing out the benefits. Detecting fraudsters from the massive volume of call detail records (CDR) in mobile communication networks has become an important yet challenging topic. Fortunately, Graph neural network (GNN) brings new possibilities for telecom fraud detection. However, the presence of the graph imbalance and GNN oversmoothing problems makes fraudster detection unsatisfactory. To address these problems, we propose a new fraud detector. First, we transform the user features with the help of a multilayer perceptron. Then, a reinforcement learning-based neighbor sampling strategy is designed to balance the number of neighbors of different classes of users. Next, we perform user feature aggregation using GNN. Finally, we innovatively treat the above augmented GNN as weak classifier and integrate multiple weak classifiers using the AdaBoost algorithm. A balanced focal loss function is also used to monitor the model training error. Extensive experiments are conducted on two open real-world telecom fraud datasets, and the results show that the proposed method is significantly effective for the graph imbalance problem and the oversmoothing problem in telecom fraud detection.
Entanglement of Signal Paths via Noisy Superconducting Quantum Devices
Authors: Shi Wenbo , Malaney Robert
Published: January 2023

Quantum routers will provide for important functionality in emerging quantum networks, and the deployment of quantum routing in real networks will initially be realized on low-complexity (few-qubit) noisy quantum devices. A true working quantum router will represent a new application for quantum entanglement—the coherent superposition of multiple communication paths traversed by the same quantum signal. Most end-user benefits of this application are yet to be discovered, but a few important use-cases are now known. In this work, we investigate the deployment of quantum routing on low-complexity superconducting quantum devices. In such devices, we verify the quantum nature of the routing process as well as the preservation of the routed quantum signal. We also implement quantum random access memory, a key application of quantum routing, on these same devices. Our experiments then embed a five-qubit quantum error-correcting code within the router, outlining the pathway for error-corrected quantum routing. We detail the importance of the qubit-coupling map for a superconducting quantum device that hopes to act as a quantum router, and experimentally verify that optimizing the number of controlled-X gates decreases hardware errors that impact routing performance. Our results indicate that near-term realization of quantum routing using noisy superconducting quantum devices within real-world quantum networks is possible.
Information Systems Strategy and Security Policy: A Conceptual Framework
Authors: Kamariotou Maria , Kitsios Fotis
Published: January 2023

As technology evolves, businesses face new threats and opportunities in the areas of information and information assets. These areas include information creation, refining, storage, and dissemination. Governments and other organizations around the world have begun prioritizing the protection of cyberspace as a pressing international issue, prompting a renewed emphasis on information security strategy development and implementation. While every nation’s information security strategy is crucial, there has not been much work conducted to define a method for gauging national cybersecurity attitudes that takes into account factors and indicators that are specific to that nation. In order to develop a framework that incorporates issues based on the current research in this area, this paper will examine the fundamentals of the information security strategy and the factors that affect its integration. This paper contributes by providing a model based on the ITU cybersecurity decisions, with the goal of developing a roadmap for the successful development and implementation of the National Cybersecurity Strategy in Greece, as well as identifying the factors at the national level that may be aligned with a country’s cybersecurity level.
Efficiency, Cost, and Volume Comparison of SiC-Based and IGBT-Based Full-Scale Converter in PMSG Wind Turbine
Authors: Loncarski Jelena , Hussain Hussain A. , Bellini Alberto
Published: January 2023

Power electronics, as an enabling technology in most renewable energy systems, is gaining attention as the penetration of renewable energy sources increases. Wide-bandgap power electronics are of particular interest due to their superior voltage blocking capabilities and fast switching speeds. They can viably be considered in the renewable energy sources, especially as the penetration of wind energy is expected to increase by a great extent in the upcoming years. In this paper, a comparison of Silicon Carbide-based and Silicon-based wind energy conversion systems has been performed, as it is crucial in understanding the benefits of adopting wide-bandgap-based solutions at a commercial level. For this analysis, a 2 MW permanent magnet synchronous generator-based wind conversion system with a bidirectional full-scale frequency converter comprised of two back-to-back inverters is considered. The efficiency, cost, and total volume of the passive components comparison have been conducted for Silicon- and Silicon Carbide-based converters. The comparison presented is a fair comparison, meaning that the converters are designed with modules of the same power ratings. Wind energy systems are compared both for the same switching frequency (low switching frequency suitable for IGBT modules) and also considering a Silicon Carbide-MOSFET-based converter working at high switching frequencies. The comparison is performed in PLECS simulation tool, using the PLECS libraries for different modules obtained from the manufacturers’ experimental data. The results show the benefits of using the Silicon Carbide-based converter when it comes to volume reduction in the passive components and provide insights to what is missing in order to achieve overall system volume and cost savings.
Real-Time Center of Gravity Estimation for Intelligent Connected Vehicle Based on HEKF-EKF
Authors: Wu Fuwei , Sun Chuan , Li Haoran , Zheng Sifa
Published: January 2023

The vehicle center of gravity estimation is the key technology to the vehicle active safety system in intelligent connected vehicles. In this study, an integrated estimation approach for center of gravity (CG) combining Huber Extended Kalman Filter and Extended Kalman Filter (HEKF-EKF) is proposed. First, HEKF algorithm is used to estimate the distance between the CG and the front axle at the current time. Then, the CG height obtained by HEKF and EKF algorithms is weighted to obtain the optimal estimate value. Finally, the results show that the algorithm’s estimation convergence time is 2 s, its longitudinal position estimation error is less than 2%, and its center of gravity height estimation error is less than 3%. The longitudinal and vertical positions of the vehicle CG can be accurately estimated using this method. This method can help advance the development of active safety technology.
Metaverse Security: Issues, Challenges and a Viable ZTA Model
Authors: Gupta Ankur , Khan Habib , Nazir Shah , Shafiq Muhammad , Shabaz Mohammad
Published: January 2023

The metaverse is touted as an exciting new technology amalgamation facilitating next-level immersive experiences for users. However, initial experiences indicate that a host of privacy, security and control issues will need to be effectively resolved for its vision to be realized. This paper highlights the security issues that will need to be resolved in the metaverse and the underlying enabling technologies/platforms. It also discussed the broader challenges confronting the developers, the service providers and other stakeholders in the metaverse ecosystem which if left unaddressed may hamper its broad adoption and appeal. Finally, some ideas on building a viable Zero-Trust Architecture (ZTA) model for the metaverse are presented.
Graded Bandgap Ultrathin CIGS Solar Cells
Authors: Boukortt Nour , Patanè Salvatore , Hadri Baghdad , Crupi Giovanni
Published: January 2023

In this paper, we physically modeled passivated ultrathin Cu (In1−xGax) Se2 solar cells with different bandgap grading configurations. Firstly, we have designed the cell architecture according to the fabricated model. The novelty in this work is the modeling of passivated u-CIGS solar cells with different bandgap grading profile configurations in order to achieve high efficiency with a thickness of 500 nm. A significant influence on device performance has been observed while changing absorber doping density, electron affinity, and operating temperature (range of 10–70 °C) for the investigated samples. ZnS has been used as a buffer layer to replace the conventional CdS material in order to improve cell efficiency. The impact of the buffer doping density and electron affinity on u-CIGS cell performance is explored. The simulation results show that a high bandgap at the front and rear sides with an acceptor density of 2 × 1016 provide the best electrical cell parameters: Jsc of 31.53 mA/cm2, Voc of 742.78 mV, FF of 77.50%, η of 18.15%. Our findings can be considered guidelines for new single and/or tandem cell optimization to achieve high efficiency.
Detecting Stepping-Stone Intrusion and Resisting Intruders’ Manipulation via Cross-Matching Network Traffic and Random Walk
Authors: Yang Jianhua , Wang Lixin , Qin Maochang , Neundorfer Noah
Published: January 2023

Attackers can exploit compromised hosts to launch attacks over the Internet. This protects an intruder, placing them behind a long connection chain consisting of multiple compromised hosts. Such attacks are called stepping-stone intrusions. Many algorithms have been proposed to detect stepping-stone intrusions, but most detection algorithms are weak in resisting intruders’ session manipulation, such as chaff-perturbation. This paper proposes a novel detection algorithm: Packet Cross-Matching and RTT-based two-dimensional random walk. Theoretical proof shows network traffic cross matching can be effective in resisting attackers’ chaff attack. Our experimental results over the AWS cloud show that the proposed algorithm can resist attackers’ chaff attacks up to a chaff rate of 100%.
Roadway Embedded Smart Illumination Charging System for Electric Vehicles
Authors: Fernandez Daniel , Sebastian Ann , Raby Patience , Genedy Moneeb , Ahn Ethan C. , Taha Mahmoud M. Reda , Dessouky Samer , Ahmed Sara
Published: January 2023

Inspired by the fact that there is an immense amount of renewable energy sources available on the roadways, such as mechanical pressure, this study presents the development and implementation of an innovative charging technique for electric vehicles (EVs) by fully utilizing the existing roadways and state-of-the-art nanotechnology and power electronics. The developed Smart Illuminative Charging is a novel wireless charging system that uses LEDs powered by piezoelectric materials as the energy transmitter source and thin film solar panels placed at the bottom of the EVs as the receiver, which is then poised to deliver the harvested energy to the vehicle’s battery. The piezoelectric materials were tested for their mechanical-to-electrical energy conversion capabilities and the relatively large-area EH2N samples (2 cm × 2 cm) produced high output voltages of up to 52 mV upon mechanical pressure. Furthermore, a lab-scale prototype device was developed to testify the proposed mechanism of illuminative charging (i.e., “light” coupled pavement and vehicle as a wireless energy transfer medium).
Rheological Phase Reaction (RPR) as an Industrial Method for the Production of High Quality Metal Oxides towards Battery Applications
Authors: Pavithra S. , Sakunthala A. , Reddy M. V. Venkatashamy
Published: January 2023

Although research on the preparation of metal oxides and other materials for various applications increases exponentially, it is more important to understand the need for eco-friendly methods of preparation to preserve the environment. Most of the methods available today are expensive, environmentally harmful, and inefficient with respect to mass production. The present review has explored the Rheological Phase Reaction (RPR) method, which has been extensively utilized as an eco-friendly industrial method for the preparation of metal oxides and metal oxide/carbon composite for lithium ion battery applications. Based on the literature reports, this review has two motivations: to identify the Rheological Phase Reaction (RPR) as the mass production method for preparing metal oxides, metal oxide/carbon composites, and other materials for different applications, to discuss the preparation steps involved, its advantages, the drawbacks associated; and to give a detailed review of the electrochemical performance of different metal oxides by the RPR method for application on the lithium ion battery, with particular emphasis on lithium trivanadate (LiV3O8).
Effects of Quantity and Arrangement of a Flame-Retardant Cable on Burning Characteristics in Open and Compartment Environments
Authors: Yun Hong-Seok , Hwang Cheol-Hong
Published: January 2023

The results of cable burning experiments conducted in a well-controlled or open environment may differ from fire phenomena in an actual installation environment of cables where the effects of ventilation conditions and thermal feedback exist. In order to prevent the misunderstanding of fire phenomena due to these differences, the changes in burning characteristics in open and compartment environments were investigated for a flame-retardant (TFR-8) cable and general PVC (VCTF) cable arranged on three-layer trays. As a result, it was confirmed that the fire scale, fire spread area, and cable damage varied greatly depending on the cable arrangement under the same cable quantity condition. Furthermore, the maximum heat release rate (HRR) and fire growth rate of TFR-8 in the compartment environment increased more than 3-times compared to the open environment, and showed a similar level of fire risk to VCTF even though it is a flame-retardant cable. Additional experiments using vertical and horizontal openings of various shapes were conducted to evaluate the individual contributions of thermal feedbacks from the wall and smoke layer to the changes in burning characteristics within the compartment. The results of this study can be used as basic data to reduce fire damage while providing an essential understanding of cable fire phenomena.
Techno-Economic Strategy for the Load Dispatch and Power Flow in Power Grids Using Peafowl Optimization Algorithm
Authors: Ali Mohammed Hamouda , El-Rifaie Ali M. , Youssef Ahmed A. F. , Tulsky Vladimir N. , Tolba Mohamed A.
Published: January 2023

The purpose of this paper is to address an urgent operational issue referring to optimal power flow (OPF), which is associated with a number of technical and financial aspects relating to issues of environmental concern. In the last few decades, OPF has become one of the most significant issues in nonlinear optimization research. OPF generally improves the performance of electric power distribution, transmission, and production within the constraints of the control system. It is the purpose of an OPF to determine the most optimal way to run a power system. For the power system, OPFs can be created with a variety of financial and technical objectives. Based on these findings, this paper proposes the peafowl optimization algorithm (POA). A powerful meta-heuristic optimization algorithm inspired by collective foraging activities among peafowl swarms. By balancing local exploitation with worldwide exploration, the OPF is able to strike a balance between exploration and exploitation. In order to solve optimization problems involving OPF, using the standard IEEE 14-bus and 57-bus electrical network, a POA has been employed to find the optimal values of the control variables. Further, there are five study cases, namely, reducing fuel costs, real energy losses, voltage skew, fuel cost as well as reducing energy loss and voltage skew, and reducing fuel costs as well as reducing energy loss and voltage deviation, as well as reducing emissions costs. The use of these cases facilitates a fair and comprehensive evaluation of the superiority and effectiveness of POA in comparison with the coot optimization algorithm (COOT), golden jackal optimization algorithm (GJO), heap-based optimizer (HPO), leader slime mold algorithm (LSMA), reptile search algorithm (RSA), sand cat optimization algorithm (SCSO), and the skills optimization algorithm (SOA). Based on simulations, POA has been demonstrated to outperform its rivals, including COOT, GJO, HPO, LSMA, RSA, SCSO, and SOA. In addition, the results indicate that POA is capable of identifying the most appropriate worldwide solutions. It is also successfully investigating preferred search locations, ensuring a fast convergence speed and enhancing the search engine’s capabilities.
Data-Driven Fault Detection and Diagnosis: Research and Applications for HVAC Systems in Buildings
Authors: Rosato Antonio , Piscitelli Marco Savino , Capozzoli Alfonso
Published: January 2023

The main goal of Fault Detection and Diagnosis (FDD) processes is to identify faults, determine their sources, and recognize solutions before the system is further harmed or service is lost [...]
Analysis of the Path Optimization of the Sustainable Development of Coal-Energy Cities Based on TOPSIS Evaluation Model
Authors: Huang Hailiang , Shi Changfeng
Published: January 2023

At present, various contradictions in most coal-energy cities have become increasingly prominent, which has become a disharmonious factor restricting the optimization and upgrading of coal-energy cities. Since the turn of the century, taking effective improvement and protection measures and promoting the economic transformation of cities reliant on coal as an energy source has been the primary job of departments at all levels in order to secure the sustainable growth of cities. In this paper, the economic transformation and sustainable growth of coal-energy cities are included in the enhanced TOPSIS economic transformation evaluation model based on the proposed entropy weight. This study examines the industrialization of cities that rely on coal energy resources, assesses the industrial efficacy of coal energy using the DEA technique, and proposes a plan for the industrialization of cities that rely on coal energy resources. This paper summarizes the industrial transformation process of coal-energy cities and designs an evaluation method for the industrial economic transformation of coal-energy cities. This paper determines a set of evaluation index systems suitable for the economic transformation of coal-based energy cities; constructs an evaluation model for the economic transformation of improved TOPSIS coal-based energy cities based on entropy weight; and, finally, calculates and analyzes the industrial economic statistics of a city over the years. It is found that, at the economic structure level, the transformation score of driving forces increases from 0.606 to 0.871; at the level of social economic structures, the transition score of the pressure system increases from 0.476 to 0.779, and the transition score of the state system increases from 0.401 to 0.699; at the level of urban construction structures, the transformation score of the pressure system increases from 0.467 to 0.568; and at the level of comprehensive transformation structures, the transformation score affecting the system increases from 0.611 to 0.716. This shows that, in the process of transformation, the driving force of industrial and economic development in coal-energy-based cities is sufficient, while the pressure of social and economic transformation is great. In the process of transformation, we should strengthen infrastructure construction and protect the urban environment.
Hybrid-Model-Based Digital Twin of the Drivetrain of a Wind Turbine and Its Application for Failure Synthetic Data Generation
Authors: Pujana Ainhoa , Esteras Miguel , Perea Eugenio , Maqueda Erik , Calvez Philippe
Published: January 2023

Computer modelling and digitalization are integral to the wind energy sector since they provide tools with which to improve the design and performance of wind turbines, and thus reduce both capital and operational costs. The massive sensor rollout and increase in big data processing capacity over the last decade has made data collection and analysis more efficient, allowing for the development and use of digital twins. This paper presents a methodology for developing a hybrid-model-based digital twin (DT) of a power conversion system of wind turbines. This DT allows knowledge to be acquired from real operation data while preserving physical design relationships, can generate synthetic data from events that never happened, and helps in the detection and classification of different failure conditions. Starting from an initial physics-based model of a wind turbine drivetrain, which is trained with real data, the proposed methodology has two major innovative outcomes. The first innovation aspect is the application of generative stochastic models coupled with a hybrid-model-based digital twin (DT) for the creation of synthetic failure data based on real anomalies observed in SCADA data. The second innovation aspect is the classification of failures based on machine learning techniques, that allows anomaly conditions to be identified in the operation of the wind turbine. Firstly, technique and methodology were contrasted and validated with operation data of a real wind farm owned by Engie, including labelled failure conditions. Although the selected use case technology is based on a double-fed induction generator (DFIG) and its corresponding partial-scale power converter, the methodology could be applied to other wind conversion technologies.
Demand Response in Smart Grids
Authors: Faria Pedro , Vale Zita
Published: January 2023

The Special Issue “Demand Response in Smart Grids” includes 10 papers [...]
Energy Saving Thermal Management of Space Remote Sensor and Validation
Authors: Lu Pan , Gao Teng , Chen Quanwang , Ren Xiaohan
Published: January 2023

An energy-efficient thermal control management method for space remote sensors using optical, mechanical, electrical, and thermal integration is proposed. The satellite power resources are insufficient, so an energy-efficient loop heat pipe (LHP) is designed for six intermittently operating detectors. The charge-coupled device (CCD) has a total heat generation of 72 W and operates for 8 min per orbital cycle. The LHP includes a capillary pump, six cold plates, and two radiators. The working fluid of the LHP is high-purity ammonia and the material of the wick is ceramic. The drive power on the capillary pump evaporator automatically switches between 30 W and 90 W depending on the operating mode of the remote sensor, resulting in an average power saving of about 58.2% compared to a conventional LHP. For the optical structure, a three-stage insulation technology was developed to save heater power and improve temperature stability. A transient numerical simulation model of the LHP was developed to study the vapor–liquid zone of two radiators under the condition of rapid power change. Vacuum thermal tests were conducted and the test data agreed well with the numerical simulation results. The in-orbit temperature data showed that the temperature fluctuations of the optical structure and CCD were less than ±0.2 °C and ±0.8 °C, respectively.
The Experimentally Measured Influence of the Si-MOSFET Replacement Switches to WBG Transistors in the Voltage Source Inverters as the Source of Radiation Noise
Authors: Bernacki Krzysztof , Rymarski Zbigniew
Published: January 2023

The aim of the paper is to present the change in the radiation noise of the single-phase voltage source inverter (VSI) when the Si-MOSFET transistors are replaced by the wide-band-gap (WBG) SiC-MOSFET and GaN transistors. The power spectral density of the near-field interference is used to visualise the change of the radiation noise of the VSI. The conclusions concern the results of the experimental replacement of the switches to the WBG technology in the existing inverters. Three switching frequencies and two gate circuits were used to show the change in the radiation noise. The measurements of the experimental VSI are presented.
Electricity Markets, Electricity Prices and Green Energy Transition
Authors: Bojnec Štefan
Published: January 2023

Here, we seek to review the relevant literature and published articles on the subjects of electricity markets, electricity prices and green energy transition [...]
Study of the Effects of Regenerative Braking System on a Hybrid Diagnostic Train
Authors: Cutrignelli Francesco , Saponaro Gianmarco , Stefanizzi Michele , Torresi Marco , Camporeale Sergio Mario
Published: January 2023

Nowadays, mobility represents a key sector to achieve the goal of carbon neutrality. Indeed, the development of hybrid powertrains is contributing to a reduction in the environmental impact of vehicles. One of the most promising energy-saving solutions is regenerative braking, which enables deceleration while recovering energy, otherwise wasted. Even though much scientific community effort has been addressed to the optimization of this technology in the automotive field, the increase of energy storage systems efficiencies enables the overcoming of the constraints related to the reuse of electric energy in railway vehicles. This solution could be extremely useful for those railway vehicles which operate on non-electrified lines, where traction is usually provided by diesel engines. For this reason, the present work focuses on how regenerative braking technology could be exploited in diesel-powered rail applications. In further detail, a diagnostic train working on real railway lines has been considered as a case study. Given the real duty-cycle of the vehicle, a simulation model has been developed with the aim of evaluating the amount of energy recovered during braking phases and, consequently, the fuel saving and the avoided CO2 emissions. As a result, the analysis shows an improved energy efficiency of propulsion system. Compared with a pure diesel operation, it leads to fuel savings of 20%, a reduction of CO2 emissions of 22.3 kg with 23.25 kWh stored in the battery at the end of the route.