bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of Prognosis between Minimally Invasive and Abdominal Radical Hysterectomy for Patients with Early-Stage Cervical Cancer
Authors: Tanaka Tomohito , Ueda Shoko , Miyamoto Shunsuke , Hashida Sousuke , Terada Shinichi , Konishi Hiromi , Kogata Yuhei , Taniguchi Kohei , Komura Kazumasa , Ohmichi Masahide
Published: March 2022

Minimally invasive surgery (MIS) is performed to treat cervical cancer patients; however, a recent study showed that MIS was associated with higher recurrence and death rate compared with abdominal radical hysterectomy (ARH). In the current study, the prognosis of patients with early-stage cervical cancer who underwent MIS with vaginal closure or ARH was evaluated. One hundred and eighty-two patients underwent radical hysterectomy for cervical cancer with stage of IA2, IB1, and IIA1. MIS was performed by laparoscopy or a robot using the vaginal closure method. Disease-free survival (DFS) and overall survival (OS) were evaluated between the groups. Among the patients, 67 underwent MIS and 115 underwent ARH. The recurrence rate was 4.5% in MIS patients and 3.5% in ARH patients with a median follow-up (interquartile range) of 36 (18–60) and 78 (48–102) months, respectively. DFS and OS were not different between the groups (3y-DFS, 95.3% vs. 96.1%, p = 0.6; 3y-OS, 100% vs. 100%, p = 0.06). In early-stage cervical cancer patients, MIS with vaginal closure did not increase the risk for recurrence or death. Surgical techniques and procedures to avoid spillage of tumor cells could be important for a better prognosis.
Iodine Concentrations in Conventional and Organic Milk in the Northeastern U.S.
Authors: Sakai Nobumitsu , Esho Ola Yetunde , Mukai Motoko
Published: March 2022

Milk is a major source of dietary iodine in the United States. Due to a relatively low margin of safety for iodine intake, there are concerns for both deficiency and over-exposure. Iodine concentrations of raw milk samples from farms and retail milk in the Northeastern U.S. region were compared between seasons (winter vs. summer) and farming practices (conventional vs. organic). Overall, mean iodine concentration was 46.2% higher in raw milk from conventional farms vs. organic farms. An interaction effect between season and farming practices was observed. Organic raw milk had higher iodine content in the winter than in the summer (423 ± 54 μg/L vs. 273 ± 24 μg/L), whereas conventional raw milk had higher iodine content in the summer than in the winter (618 ± 75 μg/L vs. 398 ± 27 μg/L). Milk samples from conventional farms had 2.27-fold higher average iodine concentration compared to milk coming from organic farms in the summer but did not differ in the winter. Out of 68 and 98 raw milk samples originating from conventional and organic farms, 22 (32.4%) and 19 (19.4%) respectively, had iodine concentrations > 500 µg/L, reaching as high as 1928 μg/L. In contrast, the overall mean concentration of iodine in retail milk did not differ between conventional and organic milk (345 ± 23 vs. 320 ± 42 μg/L, respectively). The current study confirms dairy milk remains to be a good source of iodine to U.S. consumers. However, dairy farms should be aware of the potential adverse health effects of excess iodine intake. Careful considerations in dairy management may be necessary to not exceed the recommended level of iodine supplementation in both conventional and organic operations at the farm level—to maintain optimal iodine concentrations in retail fluid milk accessible to the consumers.
Clinical and Laboratory Characteristics of Normal Weight and Obese Individuals with Non-Alcoholic Fatty Liver Disease
Authors: Trifan Anca , Rotaru Adrian , Stafie Remus , Stratina Ermina , Zenovia Sebastian , Nastasa Robert , Huiban Laura , Cuciureanu Tudor , Muzîca Cristina , Chiriac Stefan , Gîrleanu Irina , Sîngeap Ana-Maria , Sfarti Catalin , Cojocariu Camelia , Stanciu Carol
Published: March 2022

Non-alcoholic fatty liver disease (NAFLD) has had, over the past few decades, a progressively growing prevalence among the general population all over the world, in parallel with metabolic conditions such as type 2 diabetes mellitus (T2DM), dyslipidemia, and obesity. However, NAFLD is also detected in 10–13% of subjects with a body mass index (BMI) ≤ 25 kg/m² (lean-NAFLD), whose major risk factors remain unknown. In this study, we aimed to characterize the clinical features and associated risk factors of lean-NAFLD in comparison with obese-NAFLD patients. Consecutive patients diagnosed with NAFLD by vibration-controlled transient elastography and controlled attenuation parameter were prospectively enrolled. Biological and clinical data obtained from the participants were stratified according to their BMI in two groups: lean-NAFLD and obese-NAFLD. In total, 331 patients (56.8% males) were included in the final analysis. Most of the subjects were obese-NAFLD (n = 258, 77.9%) and had a higher prevalence of T2DM, dyslipidemia, and components of the metabolic syndrome, together with abnormal biological parameters. Regarding liver stiffness measurements, the proportion of subjects with at least significant fibrosis (≥F2) was approximately twofold higher among obese-NAFLD (43.81%) in comparison with lean-NAFLD patients (23.29%). Moreover, obese individuals had a higher risk for liver fibrosis (OR = 2.6, 95%, CI 1.5–4.42, p < 0.001) than lean individuals. Although associated metabolic conditions and at least significant liver fibrosis were present in approximately one-quarter of the patients, these were more frequent among obese-NAFLD patients. Therefore, individualized screening strategies for NAFLD should be established according to BMI.
Comparison of Qualitative and Quantitative Analyses of MR-Arterial Spin Labeling Perfusion Data for the Assessment of Pediatric Patients with Focal Epilepsies
Authors: Tortora Domenico , Cataldi Matteo , Severino Mariasavina , Consales Alessandro , Pacetti Mattia , Parodi Costanza , Sertorio Fiammetta , Ramaglia Antonia , Cognolato Erica , Nobile Giulia , Mancardi Margherita , Prato Giulia , Siri Laura , Giacomini Thea , Striano Pasquale , Arnaldi Dario , Piatelli Gianluca , Rossi Andrea , Nobili Lino
Published: March 2022

The role of MR Arterial-Spin-Labeling Cerebral Blood Flow maps (ASL-CBF) in the assessment of pediatric focal epilepsy is still debated. We aim to compare the Seizure Onset Zone (SOZ) detection rate of three methods of evaluation of ASL-CBF: 1) qualitative visual (qCBF), 2) z-score voxel-based quantitative analysis of index of asymmetry (AI-CBF), and 3) z-score voxel-based cluster analysis of the quantitative difference of patient’s CBF from the normative data of an age-matched healthy population (cCBF). Interictal ASL-CBF were acquired in 65 pediatric patients with focal epilepsy: 26 with focal brain lesions and 39 with a normal MRI. All hypoperfusion areas visible in at least 3 contiguous images of qCBF analysis were identified. In the quantitative evaluations, clusters with a significant z-score AI-CBF ≤ −1.64 and areas with a z-score cCBF ≤ −1.64 were considered potentially related to the SOZ. These areas were compared with the SOZ defined by the anatomo-electro-clinical data. In patients with a positive MRI, SOZ was correctly identified in 27% of patients using qCBF, 73% using AI-CBF, and 77% using cCBF. In negative MRI patients, SOZ was identified in 18% of patients using qCBF, in 46% using AI-CBF, and in 64% using cCBF (p < 0.001). Quantitative analyses of ASL-CBF maps increase the detection rate of SOZ compared to the qualitative method, principally in negative MRI patients.
Detection of Forest Tree Losses in Côte d’Ivoire Using Drone Aerial Images
Authors: Ouattara Tiodionwa Abdoulaye , Sokeng Valère-Carin Jofack , Zo-Bi Irié Casimir , Kouamé Koffi Fernand , Grinand Clovis , Vaudry Romuald
Published: March 2022

The fight against deforestation and forest degradation is now a major challenge for the preservation of global forest ecosystems. The remote sensing forest monitoring methods that are currently deployed are not always adapted to the Ivorian context because of the high cloud cover, diversity of shaded crops, and land clearing techniques. This study proposes a drone-based approach to assess intra-annual tree losses in the Bossématié classified forest. The method used is based on a detection analysis of tree losses in forest areas from a time series of aerial images acquired by drones from November 2018 to April 2019 on five sites in the studied forest. Based on photogrammetric models and photointerpretation, tree heights and tree crown sizes were estimated. Then, tree losses were detected based on the variation of tree heights during the study period. An analysis of the distribution of tree heights in Bossématié classified forest reveals that the maximum tree height was 65.06 m in November 2018 and 64.07 m in April 2019 with an average tree height of 34.29–37.00 m in November 2018 and 34.63–36.88 m in April 2019. The average tree crown area, meanwhile, was estimated to be 152 m². With an estimation accuracy of about 97%, these tree structural data indicate a minimum loss of 107 trees corresponding to a clearing area of 2 ha across all the surveyed sites from November 2018 to April 2019. This forest monitoring approach shows a considerable local loss of biodiversity and should be involved in the implementation of preservation, rehabilitation, and deployment strategies in an operational deforestation monitoring system in Côte d’Ivoire.
Numerical and Experimental Investigation of the Conjugate Heat Transfer for a High-Pressure Pneumatic Control Valve Assembly
Authors: Ngwa Mboulé , Gao Longlong , Li Baoren
Published: March 2022

This paper uses heat transfer experiments and computational fluid dynamics (CFD) simulations to investigate the conjugate heat transfer (CHT) in a high-pressure pneumatic control valve assembly. A heat transfer test rig was constructed, and time–temperature histories of five test points placed on the valve assembly’s outer surface were recorded for study validation. The Unsteady Reynolds-Averaged Navier–Stokes (URANS) CFD methods with the standard k-ε turbulence closure equations were adopted in the numerical computations. Polyhedral grids were used; time step and mesh convergence studies were conducted. Simulated and measured temperatures profile comparisons revealed a good agreement. The CHT results obtained from CFD showed huge velocity fields downstream of the valve throat and the vent hole. The airflow through the valve was icy, mainly in the supersonic flow areas. Low temperatures below 273.15 K were recorded on the internal and external walls of the valve assembly. The consistency of the measured data with the numerical results demonstrates the effectiveness of polyhedral grids in exploring the CHT using CFD methods. The local entropy production rate analysis revealed that irreversibility is mainly due to viscous dissipation. The current CHT investigation provides a potential basis for thermostress analysis and optimization.
Robust Spike-Based Continual Meta-Learning Improved by Restricted Minimum Error Entropy Criterion
Authors: Yang Shuangming , Tan Jiangtong , Chen Badong
Published: March 2022

The spiking neural network (SNN) is regarded as a promising candidate to deal with the great challenges presented by current machine learning techniques, including the high energy consumption induced by deep neural networks. However, there is still a great gap between SNNs and the online meta-learning performance of artificial neural networks. Importantly, existing spike-based online meta-learning models do not target the robust learning based on spatio-temporal dynamics and superior machine learning theory. In this invited article, we propose a novel spike-based framework with minimum error entropy, called MeMEE, using the entropy theory to establish the gradient-based online meta-learning scheme in a recurrent SNN architecture. We examine the performance based on various types of tasks, including autonomous navigation and the working memory test. The experimental results show that the proposed MeMEE model can effectively improve the accuracy and the robustness of the spike-based meta-learning performance. More importantly, the proposed MeMEE model emphasizes the application of the modern information theoretic learning approach on the state-of-the-art spike-based learning algorithms. Therefore, in this invited paper, we provide new perspectives for further integration of advanced information theory in machine learning to improve the learning performance of SNNs, which could be of great merit to applied developments with spike-based neuromorphic systems.
The Potential Impact of COVID-19 on the Chinese GDP, Trade, and Economy
Authors: Habibi Zohal , Habibi Hamed , Mohammadi Mohammad Aqa
Published: March 2022

COVID-19, a novel Coronavirus SARS-CoV-2, has wreaked havoc on global financial markets, economies, and societies. For example, this study looks at the impact of COVID-19 on the Chinese economy and its policy responses (fiscal, monetary, and institutional). This study also examines future issues. This study is timely and essential for policymakers and investors worldwide because of China’s size, contribution to global growth, and growing influence. The research shows that the presence of COVID-19 in China has global implications. Because of the virus threat, foreigners avoid mixing with the Chinese. Global tourists have cancelled their plans to visit China, and Chinese tourists cannot visit foreign countries. The rapid spread of the COVID-19 in China has halted normal life. The intensification of the COVID-19 may have long-term effects on China’s economy.
Factors Influencing the Continuance Intention to Use Accounting Information System in Jordanian SMEs from the Perspectives of UTAUT: Top Management Support and Self-Efficacy as Predictor Factors
Authors: Lutfi Abdalwali
Published: March 2022

The primary objective of this study is to explain the factors that influence the continuance intention of accountants to use an accounting information system (AIS) in the context of Jordanian small and medium-sized enterprises (SMEs). Accountants are the main AIS users, and their system acceptance and use are crucial to evaluating the successful implementation of the system. The study conducted a cross-sectional survey on SMEs that have fully implemented an AIS. The proposed framework of the study is based on the extended unified theory of acceptance and use of technology (UTAUT) model and top management support (TMS). The results revealed that the examined variables, namely effort expectancy, performance expectancy and facilitating conditions, have a positive effect on the continuance intention of accountants to use AIS, with TMS having a significant and negative effect on such intention to use. In addition, social influence was found to be significantly related to continuance intention, confirming the need to support technologies such as AIS among SMEs. The study findings contribute to UTAUT theory as they supported the effects of TMS on continuance intention to use and established the study framework measurement accuracy in the context of Jordanian SMEs.
A 4-Channel Ultra-Low Power Front-End Electronics in 65 nm CMOS for ATLAS MDT Detectors
Authors: Shah Syed Adeel Ali , De Matteis Marcello , Kroha Hubert , Fras Markus , Kortner Oliver , Richter Robert , Baschirotto Andrea
Published: March 2022

A 4-channel front-end electronics (4 × FEE) system for the muon drift tube in the ATLAS detector in the High-Luminosity LHC is presented. The overall channel architecture is optimized to reduce the power and area of the design. Each channel comprises a charge-sensitive preamplifier (CSP), shaper, discriminator and differential low-voltage signaling drivers. The proposed channel operates with a 5–100 fC input charge and exhibits a linear sensitivity of 8 mV/fC for the entire input charge range. The peaking time delay of the analog channel is 14.6 ns. At the output, the time representation of the input signal is provided in terms of the CMOS level and in scalable low-voltage signal (SLVS). The FEE consumes a current of 10.6 mA per channel from a single 1.2 V supply voltage. The full 4 × FEE design is realized in TSMC 65 nm CMOS technology and its die-area is 2 mm × 2 mm.
Prediction of Student Academic Performance Using a Hybrid 2D CNN Model
Authors: Poudyal Sujan , Mohammadi-Aragh Mahnas J. , Ball John E.
Published: March 2022

Opportunities to apply data mining techniques to analyze educational data and improve learning are increasing. A multitude of data are being produced by institutional technology, e-learning resources, and online and virtual courses. These data could be used by educators to analyze and understand the learning behaviors of students. The obtained data are raw data that must be analyzed, requiring educational data mining to predict useful information about students, such as academic performance, among other things. Many researchers have used traditional machine learning to predict the academic performance of students, and very little research has been conducted on the architecture of convolutional neural networks (CNNs) in the context of the pedagogical domain. We built a hybrid 2D CNN model by combining two different 2D CNN models to predict academic performance. Our sample comprised 1D data, so we transformed it to 2D image data to test the performance of our hybrid model. We compared the performance of our model with that of different traditional baseline models. Our model outperformed baseline models, such as k-nearest neighbor, naïve Bayes, decision trees, and logistic regression, in terms of accuracy.
Design of Chained Document HTML Generation Technique Based on Blockchain for Trusted Document Communication
Authors: Hwang Hyun-Cheon , Kim Woo-Je
Published: March 2022

Digital document communication between an enterprise and a customer is becoming a primary form of communication rather than the traditional physical document communication. A PDF document, the most popular document format, provides an identical document layout regardless of OS or device and has a content integrity verification feature with a digital signature. However, it has a bad user experience, such as low readability on a mobile device. On the other hand, an HTML document has a weakness in verifying the content integrity even though it is the primary document format and provides a good user experience on mobile devices. There are certified document services using blockchain technology, but it is still vulnerable to verifying content integrity. Furthermore, research on the document HTML has proposed the trusted document generation technique by HTML conformance and digital signature; however, this research does not provide content delivery verification, and there is a file size overhead. In this paper, we have developed the chained document HTML by defining HTML conformance, digital signature, and blockchain technology. First, the chained document HTML has to embed all resources and does not allow loading content on-demand. Second, the file is signed by a digital signature, and the signature value is added in the file header. Lastly, the metadata to verify the content integrity is inserted in a blockchain node. We have created the chained document HTML generation and verification experiment environment by Ethereum and Python. We have confirmed that the chained document HTML provides content and delivery integrity verification in the research. We expect the chained document HTML will be widely used in document communication between an enterprise and a customer, especially if the document has sensitive personal information that might have a legal dispute.
TdmTracker: Multi-Object Tracker Guided by Trajectory Distribution Map
Authors: Gao Yuxuan , Gu Xiaohui , Gao Qiang , Hou Runmin , Hou Yuanlong
Published: March 2022

With the great progress of object detection, some detection-based multiple object tracking (MOT) paradigms begin to emerge, including tracking-by-detection, joint detection and tracking, and attention mechanism-based MOT. Due to the separately executed detection, embedding, and data association, tracking-by-detection-based methods are much less efficient than other end-to-end MOT methods. Therefore, recent works are devoted to integrating these separate processes into an end-to-end paradigm. Some of the transformer-based end-to-end methods introducing track queries to detect targets have achieved good results. Self-attention and track query of these methods has given us some inspiration. Moreover, we adopt optimized class query instead of static learned object query to detect new-coming objects of target category. In this work, we present a novel anchor-free attention mechanism-based end-to-end model TdmTracker, where we propose a trajectory distribution map to guide position prediction, and introduce an adaptive query embedding set and query-key attention mechanism to detect tracked objects in the current frame. The experimental results on MOT17 dataset show that the TdmTracker achieves a good speed-accuracy trade-off compared with other state-of-the-arts.
Finite-Size and Illumination Conditions Effects in All-Dielectric Metasurfaces
Authors: Ciarella Luca , Tognazzi Andrea , Mangini Fabio , De Angelis Costantino , Pattelli Lorenzo , Frezza Fabrizio
Published: March 2022

Dielectric metasurfaces have emerged as a promising alternative to their plasmonic counterparts due to lower ohmic losses, which hinder sensing applications and nonlinear frequency conversion, and their larger flexibility to shape the emission pattern in the visible regime. To date, the computational cost of full-wave numerical simulations has forced the exploitation of the Floquet theorem, which implies infinitely periodic structures, in designing such devices. In this work, we show the potential pitfalls of this approach when considering finite-size metasurfaces and beam-like illumination conditions, in contrast to the typical infinite plane-wave illumination compatible with the Floquet theorem.
Wearable and Flexible Humidity Sensor Integrated to Disposable Diapers for Wetness Monitoring and Urinary Incontinence
Authors: Tekcin Meltem , Sayar Ersin , Yalcin Mehmet Kursat , Bahadir Senem Kursun
Published: March 2022

Disposable diapers are widely used by individuals with urinary incontinence. Diapers should be checked frequently for elderly, disabled, and hospital patients. Wet diapers that are not changed properly can cause health problems. The importance of electronic devices that provide warning in case of wetness is increasing in health monitoring. A disposable and wearable printed humidity sensor was designed and fabricated to detect wetness. The sensor was printed on polyamide-based taffeta label fabric by the inkjet printing method using specifically formulated PEDOT:PSS-based conductive polymer ink. The sensor sensitivity was tested under different relative humidity levels inside a controlled chamber. The resistance of the sensor decreased from 17.05 ± 0.05 MΩ to 2.09 ± 0.06 MΩ as the relative humidity increased from 35 to 100%, while the moisture value of the fabric increased from 4.8 to 23%. The response and recovery times were 42 s and 82 s. This sensor was integrated into the adult diaper to evaluate wetness. The sensor resistance change comparing to the dry state resistance (15.52 MΩ) was determined as 3.81 MΩ to 13.62 MΩ by dripping 0.1 mL to 100 mL salty water on the diaper. Due to its flexible structure and low-cost printability onto fabric, the wearable printed humidity sensor has the potential to be used as a disposable sensor for healthcare applications, particularly for urinary incontinence and capturing wetness in diapers.
A Novel Feature Set Extraction Based on Accelerometer Sensor Data for Improving the Fall Detection System
Authors: Le Hong-Lam , Nguyen Duc-Nhan , Nguyen Thi-Hau , Nguyen Ha-Nam
Published: March 2022

Because falls are the second leading cause of injury deaths, especially in the elderly according to WHO statistics, there have been a lot of studies on developing a fall detection and warning system. Many approaches based on wearable sensors, cameras, Infrared sensors, radar, etc., have been proposed to detect falls efficiently. However, it still faces many challenges due to noise and no clear definition of fall activities. This paper proposes a new way to extract 44 features based on the time domain, frequency domain, and Hjorth parameters to deal with this. The effect of the proposed feature set has been evaluated on several classification algorithms, such as SVM, k-NN, ANN, J48, and RF. Our method achieves a relative high performance (F1-Score metric) in detecting fall and non-fall activities, i.e., 95.23% (falls), 99.11% (non-falls), and 96.16% (falls), 99.90% (non-falls) for the MobileAct 2.0 and UP-Fall datasets, respectively.
Selection and Optimization of Hyperparameters in Warm-Started Quantum Optimization for the MaxCut Problem
Authors: Truger Felix , Beisel Martin , Barzen Johanna , Leymann Frank , Yussupov Vladimir
Published: March 2022

Today’s quantum computers are limited in their capabilities, e.g., the size of executable quantum circuits. The Quantum Approximate Optimization Algorithm (QAOA) addresses these limitations and is, therefore, a promising candidate for achieving a near-term quantum advantage. Warm-starting can further improve QAOA by utilizing classically pre-computed approximations to achieve better solutions at a small circuit depth. However, warm-starting requirements often depend on the quantum algorithm and problem at hand. Warm-started QAOA (WS-QAOA) requires developers to understand how to select approach-specific hyperparameter values that tune the embedding of classically pre-computed approximations. In this paper, we address the problem of hyperparameter selection in WS-QAOA for the maximum cut problem using the classical Goemans–Williamson algorithm for pre-computations. The contributions of this work are as follows: We implement and run a set of experiments to determine how different hyperparameter settings influence the solution quality. In particular, we (i) analyze how the regularization parameter that tunes the bias of the warm-started quantum algorithm towards the pre-computed solution can be selected and optimized, (ii) compare three distinct optimization strategies, and (iii) evaluate five objective functions for the classical optimization, two of which we introduce specifically for our scenario. The experimental results provide insights on efficient selection of the regularization parameter, optimization strategy, and objective function and, thus, support developers in setting up one of the central algorithms of contemporary and near-term quantum computing.
Performance Modeling and Analysis of LTE/Wi-Fi Coexistence
Authors: Zreikat Aymen I. , Alabed Samer
Published: March 2022

In wireless communications, the fundamental challenge facing mobile operators nowadays is the scarcity of the spectrum and the license fees. Because of the increased traffic, critical performance analysis becomes important to overcome such issues. To tackle these issues and improve the network performance and capacity, a coexistence model of LTE and Wi-Fi with two virtual zones is suggested. The inner zone is the secondary zone, which represents Wi-Fi with an unlicensed spectrum to serve the best effort user data and the outer zone is the primary zone, which represents LTE with licensed spectrum to serve all data connections. The numerical solution of the model is presented using MOSEL-2 simulation and the mathematical solution is derived to validate the model. A threshold minimum bit rate established the user admission. Based on a priority level of the service, most of the traffic is served by the primary LTE zone, however, low priority traffic is moved from the primary LTE zone to the secondary Wi-Fi zone so that the traffic of the entire network is balanced. Although this coexistence sometimes harms LTE performance, the simulation results demonstrate the efficiency of the proposed model in balancing the load over the network, and, consequently, the network performance is improved.
Optimal 3D Placement of UAV-BS for Maximum Coverage Subject to User Priorities and Distributions
Authors: Moon Inseok , Dung Le The , Kim Taejoon
Published: March 2022

The usage of unmanned aerial vehicle (UAV) as a base station is in the spotlight to overcome the severe attenuation characteristics of short-wavelength radio in high-speed wireless networks. In this paper, we propose an optimal UAV deployment algorithm, considering the priority of ground nodes (GNs) in different wireless communication environments. Specifically, the optimal position of a UAV is determined so that as many high-priority GNs can be served rather than covering as many GNs as possible. The proposed optimization problem deals with two groups of GNs with different priorities and finds the optimal position of the UAV by solving the mixed-integer second-order cone problem (MISOCP). To verify the effectiveness of the proposed optimal UAV deployment algorithm, we conduct various evaluating scenarios with different urban environments and GN spatial distributions. We also compare the performance of the proposed algorithm with the conventional one. Simulation results show that the proposed scheme achieves superior coverage efficiency, throughput, and delay performance compared to the conventional algorithm, even when the environment and the spatial distribution of GNs are changed.
Experimental Investigation of the Hydrodynamic Performance of Land-Fixed Nearshore and Onshore Oscillating Water Column Systems with a Thick Front Wall
Authors: Medina Rodríguez Ayrton Alfonso , Posada Vanegas Gregorio , Silva Casarín Rodolfo , Mendoza Baldwin Edgar Gerardo , Vega Serratos Beatriz Edith , Puc Cutz Felipe Ernesto , Mangas Che Enrique Alejandro
Published: March 2022

Most experimental research on land-fixed Oscillating Water Column (OWC) systems assume that the OWC-water wave interaction happens with waves that propagate normally towards the device. However, the angle of incidence of the waves can determine the performance of the OWC, in particular the wave period at which the device resonates. In this study, an experimental investigation to examine the interaction of regular, oblique, water waves with a land-fixed, thick-front wall OWC device in terms of its hydrodynamic performance is reported. A 1:20 Froude scale was used to replicate a single chamber of the Mutriku Wave Energy Plant (MWEP), and a series of tests were carried out in a spectral wave basin. The goal of this study is to look at how incident wave direction and device location affect the hydrodynamic performance of land-fixed OWC systems in regular wave conditions with varying wave heights. The hydraulic performance includes the assessment of the wave amplification factor, hydrodynamic efficiency, the non-dimensional air pressure inside the chamber and non-dimensional water pressures on the chamber walls. The findings show that, for the nearshore OWC device, the period at which resonance occurs decreases when the incident wave angle increases. For the corresponding wave angles, similar results were found for the onshore and nearshore OWC devices, with a slight frequency shift in the bandwidth of the hydrodynamic efficiency. Furthermore, it was found that when wave height increases, the hydrodynamic efficiency improves for both short and long wave periods, with the exception of the resonance period, where the trend is reversed. Finally, regardless of the location, an OWC device with a thick front wall performs well when interacting with intermediate and long-period waves.
Analysis and Design of the Split-Capacitor-Based Sub-Modules Equipped for Hybrid Modular Multilevel Converter
Authors: Huang Ming , Li Jianhua
Published: March 2022

The hybrid modular multilevel converter (MMC) is always featured and profited by the merits of the equipped power valves. Referring to this, a novel hybrid MMC topology equipped with the split-capacitor-based sub-modules (SCSMs) on the AC side is proposed. It aims to increase the utilization of the DC bus voltage with DC fault blocking capability. Especially compared to the hybrid MMC equipped with the full-bridge-based sub-modules (FBSMs) on the AC side, smaller power losses can be achieved for the proposed hybrid MMC, due to the reason that only one semiconductor device of the SCSM is inserted into the current flow route. Structurally, the proposed converter mainly consists of the half-bridge-based sub-module (HBSM) stacks and SCSM stacks. The HBSMs located on the DC converter side of the proposed hybrid MMC are in charge of exchanging active powers, while the SCSMs located on the AC converter side are in charge of shaping the circuit waveforms. Additionally, profited by the specific structure of the SCSM, the DC fault current could be cut off by imposing inversed voltages collected from the SCSM capacitor voltages on the uncontrollable diodes of the IGBTs. For the deep study, a detailed mathematical model and modulation control of the proposed hybrid MMC are analyzed. In addition, an analysis of the balancing control for SCSMs is also provided. Finally, the simulation and experimental results are proposed to verify the effectiveness of the theoretical analysis.
Synthesis of the Current Controller of the Vector Control System for Asynchronous Traction Drive of Electric Locomotives
Authors: Goolak Sergey , Tkachenko Viktor , Sapronova Svitlana , Lukoševičius Vaidas , Keršys Robertas , Makaras Rolandas , Keršys Artūras , Liubarskyi Borys
Published: March 2022

This paper deals with the analysis of the operating conditions of traction drives of the electric locomotives with asynchronous traction motors. The process of change of the catenary system voltage was found to have a stochastic character. The method of current controller synthesis based on the Wiener–Hopf equation was proposed to enable efficient performance of the traction drive control system under the condition of the stochastic nature of the catenary system voltage and the presence of interferences, when measuring the stator current values of the tractor motor. Performance simulation of the proposed current controller and the current controller used in the existing vector control systems of the traction drives used in the electric locomotives was implemented. The results of the performance simulation of the proposed current controller were compared with the performance of the current controller in existing vector control systems of the traction drives. The results are applicable to the design of vector control systems of traction drives in electric locomotives and to the study of the influence of performance of electric traction drives in electric locomotives on the quality indicators of the power supplied by the traction power supply system under the actual operating conditions of the locomotive.
Heat Pumps, Wood Biomass and Fossil Fuel Solutions in the Renovation of Buildings: A Techno-Economic Analysis Applied to Piedmont Region (NW Italy)
Authors: Ruffino Edoardo , Piga Bruno , Casasso Alessandro , Sethi Rajandrea
Published: March 2022

The levelized cost of heat (LCOH) and the technical feasibility in the specific context of building construction or renovation are the major drivers of users’ choices for space heating and cooling solutions. In this work, the LCOH was assessed for the most diffused heating technologies in Piedmont (NW Italy): that is, fossil fuels (methane, heating oil and liquefied petroleum gas—LPG), wood biomass (wood logs and pellet) and heat pumps (air-source and ground-source), both in heating-only and in a heating and cooling configuration. A sensitivity analysis of the main LCOH drivers was performed to assess whether and how each technology is vulnerable to energy price and upfront cost changes. The results show that heat pumps are competitive against gas boilers, but they are heavily dependent on refurbishment incentives and penalized by the high electricity prices in Italy; on the other hand, wood biomasses are competitive even in the absence of incentives. The analysis confirmed that LPG and heating oil are no more competitive with renewable heating. Acting on the taxation of natural gas and electricity is key to making heat pumps the most economically convenient solution to cover the heating and cooling needs of buildings.
Environmental Impact Assessment of Different Strategies for the Remanufacturing of User Electronics
Authors: Mann Angad , Saxena Prateek , Almanei Mohamed , Okorie Okechukwu , Salonitis Konstantinos
Published: March 2022

Over the years, the innovation and development of electrical and electronic equipment have been on a steep rise. Millions of electronics are being sold or discarded every year in the form of waste. Sustainable IT (Green IT or Circular Computing) is one of the most environment-friendly methods of reusing discarded or waste user electronics. The remanufacturing of a computer refers to the disassembly, repair, and upgrade of the original computer to give it a new life, along with a warranty that is as good as a new product. The goal of this work includes studying and assessing the total environmental impact of refurbishing a computer using life cycle assessment (LCA) integrated with discrete event simulation (DES), to compare two business models: (1) a case of centralized remanufacturing where the plants are in the Middle East, which is the hub for receiving waste electronics and distributing remanufactured goods; (2) a case of decentralized remanufacturing where the plants are situated in each continent for over a range of computer models. The environmental assessment was conducted using the openLCA software in combination with the WITNESS Horizon software for the DES. The results show that decentralized remanufacturing is a much more environmentally friendly option for the remanufacturing of computers, and the decentralized remanufacturing operation has a better throughput as well as efficiency, as compared to the centralized remanufacturing operation. The centralized remanufacturing scenario has a climate change impact of 1035.19 kg of CO2-Eq, as compared to the decentralized remanufacturing scenario with an impact of 816.12 kg of CO2-Eq. In terms of the impact on the marine life, decentralized remanufacturing was found to have 0.28 kg of N-Eq impact, as compared to centralized remanufacturing (0.22 kg of N-Eq). However, this does not give us a complete picture, as the environmental impact of the computer in its previous life remains unknown. Multi life cycle assessment is the assessment process that can be used to get a clearer picture of the ecological footprint of the computer during its multiple life cycles.
Experimental Study on Connection Characteristics of Rough Fractures Induced by Multi-Stage Hydraulic Fracturing in Tight Reservoirs
Authors: Zhang Yanjun , Yan Le , Ge Hongkui , Liu Shun , Zhou Desheng
Published: March 2022

The well spacing for the development of tight reservoirs by multi-stage fracturing is continuously narrowed. Consequently, interwell interference during fracturing is more and more serious, accompanied by a host of issues in fracturing design and oil and gas production. However, the mechanism of interwell interference during fracturing is not explicit. The corresponding laws of the connectivity of rough fractures during fracturing, which plays a critical role in interwell interference, are not fully understood. In this study, on the basis of characterizing the roughness of fractures, a laboratory evaluation method for fracture connectivity was established. The connectivity characteristics of rough fractures and factors affecting the fracture connectivity are studied. The time and scale effects of fracture connectivity were discussed and their application in interwell interference was analyzed. The results show that the connectivity performance of rough fractures can be characterized by the time for pressure decay. The upstream pressure gradually decreases over time, and the decline rate is related to the fracture aperture, the fracture surface roughness, the contact area of the closed fractures, and liquid properties. Specifically, the decrease in fracture aperture and the increase in fluid viscosity leads to a significant reduction in fracture connectivity. While larger fracture surface roughness and contact area can make fracture connectivity better. The connectivity of the fracture system is one of the significant mechanisms causing interwell interference during fracturing. The connectivity of rough fractures formed during fracturing has remarkable scale and time effects. This study can effectively guide the fracturing design and the evaluation of the impact of fracture connectivity on production.
A Modified Whale Optimizer for Single- and Multi-Objective OPF Frameworks
Authors: El-Dabah Mahmoud , Ebrahim Mohamed A. , El-Sehiemy Ragab A. , Alaas Z. , Ramadan M. M.
Published: March 2022

This paper is concerned with an imperative operational problem, called the optimal power flow (OPF), which has several technical and economic points of view with respect the environmental concerns. This paper proposes a multiple-objective optimizer NSWOA (non-dominated sorting whale optimization algorithm) for resolving single-objective OPFs, as well as multi-objective frameworks. With a variety of technical and economic power system objectives, the OPF can be formulated. These objectives are treated as single- and multi-objective OPF issues that are deployed with the aid of the proposed NSWOA to solve these OPF formulations. The proposed algorithm modifies the Pareto ranking and analyzes the optimum compromise solution based on the optimal Euclidian distances. This proposed strategy ensures high convergence speed and improves search capabilities. To achieve this study, an IEEE 30-bus (sixth-generation unit system) is investigated, with eight scenarios studied that highlight technical and environmental operational needs. When compared to previous optimization approaches, the suggested NSWOA achieves considerable techno-economic improvements. Additionally, the statical analyses are carried out for 20 separate runs. This analysis proves the high robustness of the proposed NSWOA at low levels of standard deviation.
Evaluation Metrics to Assess the Most Suitable Energy Community End-Users to Participate in Demand Response
Authors: Barreto Ruben , Gonçalves Calvin , Gomes Luis , Faria Pedro , Vale Zita
Published: March 2022

In the energy sector, prosumers are becoming relevant entities for energy management systems since they can share energy with their citizen energy community (CEC). Thus, this paper proposes a novel methodology based on demand response (DR) participation in a CEC context, where unsupervised learning algorithms such as convolutional neural networks and k-means are used. This novel methodology can analyze future events on the grid and balance the consumption and generation using end-user flexibility. The end-users’ invitations to the DR event were according to their ranking obtained through three metrics. These metrics were energy flexibility, participation ratio, and flexibility history of the end-users. During the DR event, a continuous balancing assessment is performed to allow the invitation of additional end-users. Real data from a CEC with 50 buildings were used, where the results demonstrated that the end-users’ participation in two DR events allows reduction of energy costs by EUR 1.31, balancing the CEC energy resources.
An Experimental Comparison between an Ironless and a Traditional Permanent Magnet Linear Generator for Wave Energy Conversion
Authors: Curto Domenico , Franzitta Vincenzo , Guercio Andrea , Miceli Rosario , Nevoloso Claudio , Raimondi Francesco Maria , Trapanese Marco
Published: March 2022

Permanent Magnet Linear Generators (PMLGs) are currently being studied for sea wave energy harvesting. Typically, a PMLG consists of an iron-made armature and a moving translator. The permanent magnets adoption produces parasitic effects, such as cogging force, and the machine weight increment. A solution could be the adoption of an ironless configuration, accepting a power density reduction. This paper investigates the use of ironless PMLGs in sea wave energy conversion systems by an experimental comparative analysis between an iron PMLG prototype and an ironless PMLG prototype, which share the same geometry. The main electrical and mechanical parameters (resistance, mass, and magnetic fields) were preliminarily measured. Subsequently, open-circuit and load tests were carried out to compare the induced voltages, the energy transferred to a resistive load, efficiency and the load average power. The reported comparison shows that iron PMLG performances are significantly superior to the ironless ones during the open-circuit tests, as expected. However, the analysis carried out through the load tests shows that the cogging force significantly limits the energy production, obtaining similar values in both machines. Therefore, the experimental tests justify the use of ironless machines in sea wave energy harvesting, where the maximization of energy production is a relevant target.
The Bias Analysis of Oil and Gas Companies’ Credit Ratings Based on Textual Risk Disclosures
Authors: Wei Lu , Han Chen , Yao Yinhong
Published: March 2022

Credit rating bias would affect the capital funding of oil and gas companies, and thus influence the development of the whole economy. Credit rating bias has been mostly analyzed based on different quantitative data sources, and inconsistent results have been obtained. This study first analyzes credit rating bias from the perspective of qualitative textual risk disclosures. By comparing the external credit rating with the internal risk perception expressed in the textual risk disclosures of Form 10-K filings, we can study the consistency of risk assessment of the company by the company’s management and the third-party rating agency. To be specific, four internal textual risk measures and one external risk measure are constructed to quantify the internal risk perception and external risk assessment on oil and gas companies. Then, Spearman’s rho is applied to measure the direction and magnitude of credit rating bias. In the experiment, based on the 357 samples of 174 U.S. oil and gas companies, ranging from 2009 to 2018, we find that the credit ratings mostly overestimate the internal risks perceived by the company managers, and the bias is becoming larger with the credit ratings downgraded from AAA to D.
The Role of Spatial Policy Tools in Renewable Energy Investment
Authors: Nowak Maciej J. , James Valentine Udoh , Golubchikov Oleg
Published: March 2022

There is an extensive and rapidly growing body of literature on renewable energy [...]