bluuebunny/crossref_metadata_2025 huggingface dataset:
Diagnostic Efficacy of CT Examination on Early Detection of Lung Cancer during Pandemic of COVID-19
Authors: Zhao Yanjie , Wang Ruibin , Shi Feng , Wu Jiangping , Jiang Fusheng , Song Qingkun
Published: September 2022

Background: Since the outbreak of COVID-19 in 2020, routine CT examination was recommended to hospitalized patients at some hospitals and discovered lung cancer patients at an early stage. This study aimed to investigate the detection efficacy of routine CT examination on early diagnosis of lung cancer, especially on pathological characteristics. Methods: The epidemic of COVID-19 outbreak in January 2020 in China, and routine CT examination was recommended to hospitalized patients in June 2020 and ended in July 2021. Based on the time points, we compared the diagnosis efficacy between three periods: pre-period, peri-period, and the period of routine CT examination. Results: During the period of routine CT examination, more early stages of lung cancer were detected and the tumor size was reduced to 2.14 cm from 3.21 cm at pre-period (p = 0.03). The proportion of lung adenocarcinoma and early stage adenocarcinoma was increased by 12% and 30% in the period of routine CT examination, with referral to the pre-period of CT examination (p < 0.05). A total of 61% of diagnosed patients had the wild type of TP53 gene during the period of routine CT examination, compared to 45% of patients at the pre-period of CT examination (p = 0.001). The median Ki-67 index was 15% among patients diagnosed at the period of routine CT examination and increased to 35% at the pre-period of CT examination (p < 0.001). The period of routine CT examination was associated with a 78% higher probability of detecting an early stage of adenocarcinoma (OR = 1.78, 95%CI 1.03, 3.08) but no significant association was observed for squamous cell carcinoma. From the pre-period to the period of routine CT examination, the proportion of female patients and non-smoking patients increased by 57% and 44%, respectively (p < 0.001). Conclusion: Routine CT examination could detect more lung cancer at an early stage, especially for adenocarcinoma, and detect patients with less aggressive features. Further studies were warranted to confirm the findings.
Placenta, the Key Witness of COVID-19 Infection in Premature Births
Authors: Bobei Tina-Ioana , Sima Romina-Marina , Gorecki Gabriel-Petre , Poenaru Mircea-Octavian , Olaru Octavian-Gabriel , Bobirca Anca , Cirstoveanu Catalin , Chicea Radu , Topirceanu-Andreoiu Oana-Maria , Ples Liana
Published: September 2022

Adverse perinatal outcomes, such as increased risks of pre-eclampsia, miscarriage, premature birth, and stillbirth have been reported in SARS-CoV-2 infection. For a better understanding of COVID-19 complications in pregnancy, histopathological changes in the placenta, which is the interface between mother and foetus, could be the place to look at. The aim of this study was to determine placental histopathological changes and their role in preterm birth in pregnant women with SARS-CoV-2 infection. We performed a prospective, observational study in a COVID-only hospital, which included 39 pregnant women with SARS-CoV-2 infection and preterm birth compared with a control group of 39 women COVID-19 negative with preterm birth and a placental pathology exam available. The microscopic examination of all placentas revealed placental infarction (64.1% vs. 30.8%), decidual arteriopathy (66.7% vs. 23.1%), intervillous thrombi (53.8% vs. 38.5%), perivillous fibrin deposits (59% vs. 46.2%), inflammatory infiltrate (69.2% vs. 46.2%), chorangiosis (17.9% vs. 10.3%), and accelerated maturation of the villi (23.1% vs. 28.2%).
Annotation Tools in Gastrointestinal Polyp Annotation
Authors: Selnes Ola , Bjørsum-Meyer Thomas , Histace Aymeric , Baatrup Gunnar , Koulaouzidis Anastasios
Published: September 2022

Capsule endoscopy (CE) is a valid alternative to conventional gastrointestinal (GI) endoscopy tools. In CE, annotation tools are crucial in developing large and annotated medical image databases for training deep neural networks (DNN). We provide an overview of the described and in-use various annotation systems available, focusing on the annotation of adenomatous polyp pathology in the GI tract. Some studies present promising results regarding time efficiency by implementing automated labelling features in annotation systems. Thus, data are inadequate regarding the general overview for users, and may also be more specific on which features provided are necessary for polyp annotation.
The Crosstalk between Vitamin D and Pediatric Digestive Disorders
Authors: Mărginean Cristina Oana , Meliț Lorena Elena , Borka Balas Reka , Văsieșiu Anca Meda , Fleșeriu Tudor
Published: September 2022

Vitamin D is a cyclopentane polyhydrophenanthrene compound involved mainly in bone health and calcium metabolism but also autophagy, modulation of the gut microbiota, cell proliferation, immune functions and intestinal barrier integrity. The sources of vitamin D include sunlight, diet and vitamin D supplements. Vitamin D3, the most effective vitamin D isoform is produced in the human epidermis as a result of sunlight exposure. Vitamin D undergoes two hydroxylation reactions in the liver and kidney to reach its active form, 1,25-dihydroxyvitamin D. Recent studies highlighted a complex spectrum of roles regarding the wellbeing of the gastrointestinal tract. Based on its antimicrobial effect, it was recently indicated that vitamin D supplementation in addition to standard eradication therapy might enhance H. pylori eradication rates. Moreover, it was suggested that low levels of vitamin D might also be involved in the acquisition of H. pylori infection. In terms of celiac disease, the negative effects of vitamin D deficiency might begin even during intrauterine life in the setting of maternal deficiency. Moreover, vitamin D is strongly related to the integrity of the gut barrier, which represents the core of the pathophysiology of celiac disease onset, in addition to being correlated with the histological findings of disease severity. The relationship between vitamin D and cystic fibrosis is supported by the involvement of this micronutrient in preserving lung function by clearing airway inflammation and preventing pathogen airway colonization. Moreover, this micronutrient might exert anticatabolic effects in CF patients. Inflammatory bowel disease patients also experience major benefits if they have a sufficient level of circulating vitamin D, proving its involvement in both induction and remission in these patients. The findings regarding the relationship between vitamin D, food allergies, diarrhea and constipation remain controversial, but vitamin D levels should be monitored in these patients in order to avoid hypo- and hypervitaminosis. Further studies are required to fill the remaining gaps in term of the complex impact of vitamin D on gastrointestinal homeostasis.
Complete Blood Cell Count-Derived Biomarkers and Clinical Studies: Is It Time for New Reporting Criteria? Comment on Anand et al. Utility of Red Cell Distribution Width (RDW) as a Noninvasive Biomarker for the Diagnosis of Acute Appendicitis: A Systematic Review and Meta-Analysis of 5222 Cases. Diagnostics 2022, 12, 1011
Authors: Frater John L. , Hurley M. Yadira
Published: September 2022

We read with great interest the article entitled “Utility of Red Cell Distribution Width (RDW) as a Noninvasive Biomarker for the Diagnosis of Acute Appendicitis: A Systematic Review and Meta-Analysis of 5222 Cases” by S. Anand et al. which has been recently published in Diagnostics [...]
Association of In-Hospital Mortality and Trauma Team Activation: A 10-Year Study
Authors: Chien Da-Sen , Yiang Giou-Teng , Liu Chi-Yuan , Tzeng I-Shiang , Chang Chun-Yu , Hou Yueh-Tseng , Chen Yu-Long , Lin Po-Chen , Wu Meng-Yu
Published: September 2022

Background: Early trauma team activation (TTA) may improve clinical outcomes through early diagnosis and timely intervention by a dedicated multidisciplinary team. Controversy seems to exist about the effect of establishing trauma team systems in traumatic injury populations. Our aim was to identify factors that may be associated with clinical outcomes in trauma injury and to investigate the effect of trauma team activation. Method: This retrospective descriptive study included all traumatic patients from the Taipei Tzu Chi Hospital Trauma Database. All prehospital vital signs, management, injury type, injury mechanisms, hospitalization history, and clinical outcomes were analyzed, and multivariable logistic regression was used to investigate the association between trauma team activation and clinical outcomes. Subgroups of TTA in minor injury and non-TTA in major injury were also analyzed. Result: In this study, a total of 11,946 patients were included, of which 10,831 (90.7%) patients were minor injury (ISS < 16), and 1115 (9.3%) patients were major injury (ISS ≥ 16). In the minor injury population, TTA had a higher intensive care unit (ICU) admission rate, operation rate, re-operation rate, and prolonged total length of stay (LOS). In the major injury population, TTA had a higher mortality rate, prolonged total LOS, and prolonged ICU LOS. After adjusting for mechanism of injury and injury severity, there was no association between in-hospital mortality and TTA, compared with the non-TTA group. However, the TTA group had a higher risk of ICU admission, prolonged ICU LOS, and prolonged total LOS. The subgroup analysis showed trauma team activation had a higher risk of mortality in the 60- to 80-year-old population, major injury (ISS ≥ 16), consciousness clear population, and non-head injury group. Conclusions: We found there was no significant association between in-hospital mortality and TTA. However, in the TTA group, there was a higher risk of ICU admission, prolonged total, LOS, and prolonged ICU LOS. In the subgroup analysis, TTA had a higher risk of mortality in the 60- to 80-year-old population, major injury (ISS ≥ 16), consciousness clear population, and non-head injury group. Our results reflect TTA-criteria-selected patients with greater ISS and a high risk of mortality.
Fungal Periprosthetic Hip Joint Infections
Authors: Koutserimpas Christos , Naoum Symeon , Giovanoulis Vasileios , Raptis Konstantinos , Alpantaki Kalliopi , Dretakis Konstantinos , Vrioni Georgia , Samonis George
Published: September 2022

Introduction: Fungal hip prosthetic joint infections (PJIs) are rare but severe infections. Their incidence has increased in the last decades due to the aging population, as well as due to the increased number of immunosuppressed hosts. The present review of all published fungal PJIs in hip arthroplasties aims to present as much data as possible for both medical and surgical treatment options, so that the best applicable management may be concluded. Methods: A meticulous review of all published fungal hip PJIs was conducted. Information regarding demographics, causative fungus, antifungal treatment (AFT), surgical management as well as the infection outcome was recorded. Results: A total of 89 patients suffering fungal hip PJI were identified. The patients’ mean age was 66.9 years. The mean time from initial arthroplasty to onset of symptoms was 69.3 months, while 40.4% of the patients were immunocompromised. The most common imaging method indicating diagnosis was plain X-ray or CT scan (20.2%), while definite diagnosis had become possible through cultures in most cases (98.9%), and/or histology (44.9%). The most frequently isolated fungus was C. albicans (49.4%), followed by C. parapsilosis (18%) and C. glabrata (12.4%), while bacterial co-infection was present in 32 cases (36%). Two-stage revision arthroplasty (TSRA) was the most commonly performed procedure (52.8%), with mean time between the two stages = 7.9 months. Regarding antifungal treatment (AFT), fluconazole was the preferred agent (62.9%), followed by amphotericin B (36%), while the mean duration of AFT was 5.1 months. Outcome was successful in 68 cases (76.4%). Conclusions: Both diagnosis and management of fungal PJIs in patients having undergone total hip arthroplasty are quite demanding. A multidisciplinary approach is of utmost importance, since the combination of AFT and TSRA appears to be the proper treatment method.
Comparing Distal-Jet with Dental Anchorage to Distal-Jet with Skeletal Anchorage: A Prospective Parallel Cohort Study
Authors: Altieri Federica , Mezio Martina , Guarnieri Rosanna , Cassetta Michele
Published: September 2022

The use of traditional intra-oral devices in maxillary molar distalization is not without undesirable consequences. The aim of the present study was to compare the miniscrew-supported distal-jet appliance to a traditional distal-jet appliance by evaluating the amount of upper first molar distalization and the dentoalveolar side effects. Data of 600 subjects visited at the orthodontic unit of Sapienza University of Rom were analyzed. Only 46 patients met the inclusion criteria and were selected and treated. Subjects were assigned randomly to receive treatment either with miniscrew-supported distal-jet appliance (Group A) or with a traditional distal-jet appliance (Group B). In Group A, miniscrews were inserted using a computer-guided surgical guide. The amount of upper first molar distalization and the dentoalveolar side effects were assessed both on the digital casts and on the lateral cephalometric radiograph at the end of the distalization phase. A descriptive statistical analysis that included the mean values and the standard deviation was conducted to evaluate the molar distalization and the dentoalveolar effects in two groups. Intergroup differences were determined using the Student’s t-test. The significance was set at p ≤ 0.05. In Group A, greater maxillary first molar distalization and a spontaneous distalization of the first premolars and a palatal inclination of central incisors were observed. By contrast, in Group B, the first premolars tipped mesially and a proclination of the maxillary central incisors was observed. In both groups, the transverse widths of the dental arch increased while a greater tendency of first premolar extrusion and of maxillary first molar rotation was observed in Group B. The skeletal anchorage device achieved greater first molar distalization and did not cause dento-alveolar side effects.
Decentralized Sampled-Data Fuzzy Tracking Control for a Quadrotor UAV with Communication Delay
Authors: Jang Yong Hoon , Han Tae Joon , Kim Han Sol
Published: September 2022

This study deals with the decentralized sampled-data fuzzy tracking control of a quadrotor unmanned aerial vehicle (UAV) considering the communication delay of the feedback signal. A decentralized Takagi–Sugeno (T–S) fuzzy approach is adopted to represent the quadrotor UAV as two subsystems: the position control system and the attitude control system. Unlike most previous studies, a novel decentralized controller considering the communication delay for the position control system is proposed. In addition, to minimize the increase in computational complexity, the Lyapunov–Krasovskii functional (LKF) is configured as the only state required for each subsystem. The design conditions guaranteeing the tracking performance of the quadrotor UAV are derived as linear matrix inequalities (LMIs) that are numerically solved. Lastly, the validity of the proposed design method is verified by comparing the results through simulation examples with and without communication delay.
Speeding up Training of Linear Predictors for Multi-Antenna Frequency-Selective Channels via Meta-Learning
Authors: Park Sangwoo , Simeone Osvaldo
Published: September 2022

An efficient data-driven prediction strategy for multi-antenna frequency-selective channels must operate based on a small number of pilot symbols. This paper proposes novel channel-prediction algorithms that address this goal by integrating transfer and meta-learning with a reduced-rank parametrization of the channel. The proposed methods optimize linear predictors by utilizing data from previous frames, which are generally characterized by distinct propagation characteristics, in order to enable fast training on the time slots of the current frame. The proposed predictors rely on a novel long short-term decomposition (LSTD) of the linear prediction model that leverages the disaggregation of the channel into long-term space-time signatures and fading amplitudes. We first develop predictors for single-antenna frequency-flat channels based on transfer/meta-learned quadratic regularization. Then, we introduce transfer and meta-learning algorithms for LSTD-based prediction models that build on equilibrium propagation (EP) and alternating least squares (ALS). Numerical results under the 3GPP 5G standard channel model demonstrate the impact of transfer and meta-learning on reducing the number of pilots for channel prediction, as well as the merits of the proposed LSTD parametrization.
An Application of Inverse Reinforcement Learning to Estimate Interference in Drone Swarms
Authors: Kim Keum Joo , Santos Eugene , Nguyen Hien , Pieper Shawn
Published: September 2022

Despite the increasing applications, demands, and capabilities of drones, in practice they have only limited autonomy for accomplishing complex missions, resulting in slow and vulnerable operations and difficulty adapting to dynamic environments. To lessen these weaknesses, we present a computational framework for deducing the original intent of drone swarms by monitoring their movements. We focus on interference, a phenomenon that is not initially anticipated by drones but results in complicated operations due to its significant impact on performance and its challenging nature. We infer interference from predictability by first applying various machine learning methods, including deep learning, and then computing entropy to compare against interference. Our computational framework begins by building a set of computational models called double transition models from the drone movements and revealing reward distributions using inverse reinforcement learning. These reward distributions are then used to compute the entropy and interference across a variety of drone scenarios specified by combining multiple combat strategies and command styles. Our analysis confirmed that drone scenarios experienced more interference, higher performance, and higher entropy as they became more heterogeneous. However, the direction of interference (positive vs. negative) was more dependent on combinations of combat strategies and command styles than homogeneity.
Development of a 3D Eulerian/Lagrangian Aircraft Icing Simulation Solver Based on OpenFOAM
Authors: Han Han , Yin Zifei , Ning Yijun , Liu Hong
Published: September 2022

A 3D icing simulation code is developed in the open-source CFD toolbox OpenFOAM. A hybrid Cartesian/body-fitted meshing method is used to generate high-quality meshes around complex ice shapes. Steady-state 3D Reynolds-averaged Navier-Stokes (RANS) equations are solved to provide the ensemble-averaged flow around the airfoil. Considering the multi-scale nature of droplet size distribution, and more importantly, to represent the less uniform nature of the Super-cooled Large Droplets (SLD), two droplet tracking methods are realized: the Eulerian method is used to track the small-size droplets (below 50 μm) for the sake of efficiency; the Lagrangian method with random sampling is used to track the large droplets (above 50 μm); the heat transfer of the surface overflow is solved on a virtual surface mesh; the ice accumulation is estimated via the Myers model; finally, the final ice shape is predicted by time marching. Limited by the availability of experimental data, validations are performed on 3D simulations of 2D geometries using the Eulerian and Lagrangian methods, respectively. The code proves to be feasible and accurate enough in predicting ice shapes. Finally, an icing simulation result of the M6 wing is presented to illustrate the full 3D capability.
Analysis of Imperfect Rephasing in Photon Echo-Based Quantum Memories
Authors: Ham Byoung S.
Published: September 2022

Over the last two decades, quantum memories have been intensively studied for potential applications of quantum repeaters in quantum networks. Various protocols have also been developed. To satisfy no noise echoes caused by spontaneous emission processes, a conventional two-pulse photon-echo scheme has been modified. The resulting methods include double-rephasing, ac Stark, dc Stark, controlled echo, and atomic frequency comb methods. In these methods, the main purpose of modification is to remove any chance of a population residual on the excited state during the rephasing process. Here, we investigate a typical Gaussian rephasing pulse-based double-rephasing photon-echo scheme. For a complete understanding of the coherence leakage by the Gaussian pulse itself, ensemble atoms are thoroughly investigated for all temporal components of the Gaussian pulse, whose maximum echo efficiency is 26% in amplitude, which is unacceptable for quantum memory applications.
On the Criticality of Adaptive Boolean Network Robots
Authors: Braccini Michele , Roli Andrea , Barbieri Edoardo , Kauffman Stuart
Published: September 2022

Systems poised at a dynamical critical regime, between order and disorder, have been shown capable of exhibiting complex dynamics that balance robustness to external perturbations and rich repertoires of responses to inputs. This property has been exploited in artificial network classifiers, and preliminary results have also been attained in the context of robots controlled by Boolean networks. In this work, we investigate the role of dynamical criticality in robots undergoing online adaptation, i.e., robots that adapt some of their internal parameters to improve a performance metric over time during their activity. We study the behavior of robots controlled by random Boolean networks, which are either adapted in their coupling with robot sensors and actuators or in their structure or both. We observe that robots controlled by critical random Boolean networks have higher average and maximum performance than that of robots controlled by ordered and disordered nets. Notably, in general, adaptation by change of couplings produces robots with slightly higher performance than those adapted by changing their structure. Moreover, we observe that when adapted in their structure, ordered networks tend to move to the critical dynamical regime. These results provide further support to the conjecture that critical regimes favor adaptation and indicate the advantage of calibrating robot control systems at dynamical critical states.
Entropy Production Analysis of a Vertical Mixed-Flow Pump Device with Different Guide Vane Meridians
Authors: Li Yanjun , Zhong Yi , Meng Fan , Zheng Yunhao , Sun Danghang
Published: September 2022

With the aim of investigating the influence of guide vane meridians on the external characteristics and internal flow field of the mixed-flow pump device, this research constructed seven guide vane meridians and applied computational fluid dynamic (CFD) and entropy production theory to investigate the spread of hydraulic loss in a mixed-flow pump. As observed, when the guide vane outlet diameter Dgvo decreased from 350 mm to 275 mm, the head and efficiency increased by 2.78% and 3.05% at 0.7 Qdes, respectively. At 1.3 Qdes, when Dgvo increased from 350 mm to 425 mm, the head and efficiency increased by 4.49% and 3.71%, respectively. At 0.7 Qdes and 1.0 Qdes, the entropy production of the guide vane increased with the increase of Dgvo due to flow separation. When Dgvo < 350 mm, at 1.0 Qdes and 1.3 Qdes, entropy production of the outlet channel increased as Dgvo decreased owing to the excessive flow rate, but at 0.7 Qdes, entropy production did not change much. When Dgvo > 350 mm, at 0.7 Qdes and 1.0 Qdes, due to the expansion of the channel section, the flow separation intensified, which resulted in an increase of the entropy production, but the entropy production decreased slightly at 1.3 Qdes. These results provide guidance for improving the efficiency of pumping stations.
Blended Learning Reimagined: Teaching and Learning in Challenging Contexts
Authors: Divaharan Shanti , Chia Alexius
Published: September 2022

The COVID-19 global pandemic has caused disruptions around the world with devastating consequences socially and economically. Education was not spared. Schools and institutions of higher learning (IHLs) had to grapple with new sets of demands. With most countries forced into lockdown to stem the spread of the virus, some turned to technology-mediated learning to provide some kind continuity for learning to still take place. This concept paper will share some of the key learning points and strategies culled from experiences having to pivot almost overnight to embracing technology and new learning environments, which were sometimes remote or neglected in a milieu and culture that often prided itself in effective physical face-to-face interactions. This article will then draw upon how the Blended Learning approach, undergirded by Connectivism, was implemented in a local IHL. Examples of the different types of blended learning designs that were employed will be described alongside examples on how educators can distinguish between them to engage their learners in both modes.
Towards a Pedagogy of Trauma: Experiences of Paramedics and Firefighters in a COVID-19 Era and Opportunities for Transformative Learning
Authors: Eschenbacher Saskia , Fleming Ted
Published: September 2022

Many workers, especially first responders, experience trauma at work. We gathered experiences of frontline workers in Berlin during COVID-19 and theorize those experiences within an education paradigm. Their experiences were written as part of their reflective writing on a hazard prevention course for emergency workers in 2022. The theorizing focuses on the struggle for meaning precipitated by the student’s experiences of trauma and makes a case for understanding how this may prompt significant learning—even transformative learning—for individuals and possibly the broader society. This theoretical analysis is informed by Carol Gilligan, Axel Honneth, Oskar Negt and Jack Mezirow who help reconnect professional with personal interests and thinking with the emotional dimensions of work. We propose a critical analysis of the ways in which the instrumental, procedural and professional imperatives are disconnected from the personal and emotional dimensions of trauma work. Their struggle for recognition also assists in understanding these connections. The thinking/emotional divide and professional/personal splits are themselves a trauma and the pedagogy of reconnection is transformative.
Pretrained Configuration of Power-Quality Grayscale-Image Dataset for Sensor Improvement in Smart-Grid Transmission
Authors: Chen Yeong-Chin , Syamsudin Mariana , Berutu Sunneng S.
Published: September 2022

The primary source of the various power-quality-disruption (PQD) concerns in smart grids is the large number of sensors, intelligent electronic devices (IEDs), remote terminal units, smart meters, measurement units, and computers that are linked by a large network. Because real-time data exchange via a network of various sensors demands a small file size without an adverse effect on the information quality, one measure of the power-quality monitoring in a smart grid is restricted by the vast volume of the data collection. In order to provide dependable and bandwidth-friendly data transfer, the data-processing techniques’ effectiveness was evaluated for precise power-quality monitoring in wireless sensor networks (WSNs) using grayscale PQD image data and employing pretrained PQD data with deep-learning techniques, such as ResNet50, MobileNet, and EfficientNetB0. The suggested layers, added between the pretrained base model and the classifier, modify the pretrained approaches. The result shows that advanced MobileNet is a fairly good-fitting model. This model outperforms the other pretraining methods, with 99.32% accuracy, the smallest file size, and the fastest computation time. The preprocessed data’s output is anticipated to allow for reliable and bandwidth-friendly data-packet transmission in WSNs.
Linear Active Disturbance Rejection Control of New Double Full-Bridge ZVZCS Converter for Beam Supply
Authors: Dong Haiying , Wang Huaijiang , Li Guosheng , Zhai Hao
Published: September 2022

In view of the unstable output voltage of the new double full bridge ZVZCS converter of beam power supply when it is disturbed by external disturbance or internal parameter change in practical application, combined with the characteristics of the beam power supply system model, this paper proposes a beam power supply control strategy based on linear active disturbance rejection control (LADRC). Firstly, the working principle of the new double full bridge ZVZCS converter of beam power supply is analyzed, and considering the parasitic parameters and effective duty cycle of circuit components, the small signal equivalent model under two working modes is established. Secondly, combined with the system model and linear active disturbance rejection control theory, a double closed-loop controller is designed, which takes the second-order LADRC as the outer voltage loop and PI control as the inner current loop. Finally, the simulation and experimental results show that the designed controller has stronger robustness, anti-interference and better dynamic response speed than the traditional double closed-loop PI controller in load switching and dual-mode switching, and has a good development prospect.
Methods for Model Complexity Reduction for the Nonlinear Calibration of Amplifiers Using Volterra Kernels
Authors: Centurelli Francesco , Monsurrò Pietro , Scotti Giuseppe , Tommasino Pasquale , Trifiletti Alessandro
Published: September 2022

Volterra models allow modeling nonlinear dynamical systems, even though they require the estimation of a large number of parameters and have, consequently, potentially large computational costs. The pruning of Volterra models is thus of fundamental importance to reduce the computational costs of nonlinear calibration, and improve stability and speed, while preserving accuracy. Several techniques (LASSO, DOMP and OBS) and their variants (WLASSO and OBD) are compared in this paper for the experimental calibration of an IF amplifier. The results show that Volterra models can be simplified, yielding models that are 4–5 times sparser, with a limited impact on accuracy. About 6 dB of improved Error Vector Magnitude (EVM) is obtained, improving the dynamic range of the amplifiers. The Symbol Error Rate (SER) is greatly reduced by calibration at a large input power, and pruning reduces the model complexity without hindering SER. Hence, pruning allows improving the dynamic range of the amplifier, with almost an order of magnitude reduction in model complexity. We propose the OBS technique, used in the neural network field, in conjunction with the better known DOMP technique, to prune the model with the best accuracy. The simulations show, in fact, that the OBS and DOMP techniques outperform the others, and OBD, LASSO and WLASSO are, in turn, less efficient. A methodology for pruning in the complex domain is described, based on the Frisch–Waugh–Lovell (FWL) theorem, to separate the linear and nonlinear sections of the model. This is essential because linear models are used for equalization and cannot be pruned to preserve model generality vis-a-vis channel variations, whereas nonlinear models must be pruned as much as possible to minimize the computational overhead. This methodology can be extended to models other than the Volterra one, as the only conditions we impose on the nonlinear model are that it is feedforward and linear in the parameters.
A Self-Adaptable Angular Based K-Medoid Clustering Scheme (SAACS) for Dynamic VANETs
Authors: Bijalwan Akhilesh , Purohit Kamlesh Chandra , Malik Preeti , Mittal Mohit
Published: September 2022

Prior study suggests that VANET has two types of communications: Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communications. V2V is very important and ensures cooperative communications between vehicles and safety measures. It is also defined as Inter-Vehicle Communication (IVC).The communication is based on clustering the nodes to transmit the data from vehicle to vehicle. The overhead and stability are considered as main challenges that need to be addressed during vehicle intersections. In this paper, a novel self-adaptable Angular based k-medoid Clustering Scheme (SAACS) is proposed to form flexible clusters. The clusters are formed by estimating the road length and transmission ranges to minimize the network delay. And the Cluster Head (CH) is elected from a novel performance metric, ‘cosine-based node uncoupling frequency,’ that finds the best nodes irrespective of their current network statistics. The parametric analysis varies according to the number of vehicular nodes with the transmission range. The experimental results have proven that the proposed technique serves better in comparison to existing approaches such as Cluster Head Lifetime (CHL), Cluster Member Lifetime (CML), Cluster Number (CL), Cluster Overhead (CO), Packet Loss Ratio (PLR) and Average Packet Delay (APD). CHL is enhanced 40% as compare to Real-Time Vehicular Communication (RTVC), Efficient Cluster Head Selection (ECHS) whereas CML is 50% better than RTVC and ECHS. Packet loss ratio and overhead is 45% better in our proposed algorithm than RTVC and ECHS. It is observed from the results that the incorporation of cosine-based node uncoupling frequency has minimized the incongruity between vehicular nodes placed in dense and sparse zones of highways.
2nd-Order Pipelined Noise-Shaping SAR ADC Using Error-Feedback Structure
Authors: Baek Jihyun , Lee Juyong , Kim Jintae , Chae Hyungil
Published: September 2022

This paper presents a pipelined noise-shaping SAR (PLNS-SAR) ADC for high SNDR, wide bandwidth, and low power consumption. The proposed design achieves a sharp second-order NTF of an error feedback structure, without a multi-input comparator and additional residue amplifier. Additionally, the SNDR is improved via zero optimization. Additionally, the speed is enhanced via prediction logic and alternately using the passive switched capacitor FIR filter. This consequently achieves the high-power efficiency of the ADC. The simulated SNDR is 79.97 dB; it achieves a 12.5-MHz BW at a 175-MHz sampling rate, with OSR of 7. The total power consumption of the ADC is 4.27 mW at a 1.1-V supply. The FoMS,SNDR is 174.6 dB. The proposed structure achieves high resolution and wide bandwidth with good energy efficiency.
Access-Control Model of Super Business System Based on Business Entity
Authors: Zhao Bin , Zheng Guiyue , Gao Yilong , Zhao Yanchen
Published: September 2022

To address the problem that the traditional access-control model is no longer suitable for access control and authorization in the super business system—which has the characteristics of many businesses and complex permissions—a business entity-based access-control model (BE-BAC) is proposed in this paper. The BE-BAC model realizes the relationship between users, business entities, and business permissions. Firstly, according to the characteristics of the super business system, the concept of business entity is put forward, introducing the composition and relationship of the business entity. Secondly, the business entity is introduced into the access-control model, formally describing the basic relationship, constraint, mapping, and authorization strategy of the BE-BAC model. Finally, the access-control workflow, based on the business entity, is designed, and the security analysis and comprehensive comparison of the model are carried out. Compared with the existing access-control model, the BE-BAC model has higher security and flexibility, and better protects resources, through more secure access-request decisions.
Position Design for Reconfigurable Intelligent-Surface-Aided Indoor Visible Light Communication Systems
Authors: Wu Qi , Zhang Jian , Guo Jia-Ning
Published: September 2022

As an emerging technology, reconfigurable intelligent surfaces (RISs) have been investigated to apply to visible light communication (VLC) systems to enhance the transmission capability of the systems, recently. However, the optimization of RIS location in VLC has not been studied. In this study, we first investigated RIS positioning design in VLC. Specifically, we set two indoor VLC scenarios with a VLC RIS composed of a mirror array. We set the achievable rates in different scenarios as the utility functions to optimize the position of the RIS array according to the placement of the access point (AP) and user. We found that the problems are nondeterministic polynomial (NP)-hard. Aiming at the different optimization problems, the particle swarm optimization (PSO) algorithm was used to confirm the optimal position of the RIS array. Unlike the traditional algorithm, we added an adaptive mutation mechanism to the algorithm to guarantee the randomness of the particle to search for the optimal solution. Finally, our simulation results showed that the proper position design of the RIS array can improve the communication performance to a greater degree, while the computational complexity required to solve the position optimization problems through the PSO algorithm can be significantly reduced compared with that required for the exhaustive search method in the case where both of the algorithms find the optimal solution.
Compact Ultra-Wideband Wilkinson Power Dividers Using Linearly Tapered Transmission Lines
Authors: Razzaz Faroq , Saeed Saud M. , Alkanhal Majeed A. S.
Published: September 2022

In this work, compact extended ultra-wideband (UWB) Wilkinson power dividers (WPDs) using tapered transmission lines are analyzed, designed, and measured. Utilizing carefully designed tapered transmission sections results in widening the operational bandwidth and reducing the element dimensions. Analytical models and design procedures of simple and compact and equal and unequal UWB WPDs based on linearly tapered transmission lines are developed and outlined in this paper. Four different configurations of equal and unequal power dividers are designed and presented. The number and locations of the isolation resistors have a noticeable effect on extending the operational bandwidth of the dividers. The presented designs of the WPDs have superior performance over extended bandwidths. The simulation and experimental results are in very good agreement with good insertion and return loss, good matching, and isolation, over the extended UWB operational bandwidth from 3 GHz to 27 GHz.
Unsupervised Domain Adaptive Person Re-Identification Method Based on Transformer
Authors: Yan Xiai , Ding Shengkai , Zhou Wei , Shi Weiqi , Tian Hua
Published: September 2022

Person re-identification (ReID) is the problem of cross-camera target retrieval. The extraction of robust and discriminant features is the key factor in realizing the correct correlation of targets. A model based on convolutional neural networks (CNNs) can extract more robust image features. Still, it completes the extraction of images from local information to global information by continuously accumulating convolution layers. As a complex CNN, a vision transformer (ViT) captures global information from the beginning to extract more powerful features. This paper proposes an unsupervised domain adaptive person re-identification model (ViTReID) based on the vision transformer, taking the ViT model trained on ImageNet as the pre-training weight and a transformer encoder as the feature extraction network, which makes up for some defects of the CNN model. At the same time, the combined loss function of cross-entropy and triplet loss function combined with the center loss function is used to optimize the network; the person’s head is evaluated and trained as a local feature combined with the global feature of the whole body, focusing on the head, to enhance the head feature information. The experimental results show that ViTReID exceeds the baseline method (SSG) by 14% (Market1501 → MSMT17) in mean average precision (mAP). In MSMT17 → Market1501, ViTReID is 1.2% higher in rank-1 (R1) accuracy than a state-of-the-art method (SPCL); in PersonX → MSMT17, the mAP is 3.1% higher than that of the MMT-dbscan method, and in PersonX → Market1501, the mAP is 1.5% higher than that of the MMT-dbscan method.
A Path Load-Aware Based Caching Strategy for Information-Centric Networking
Authors: Chao Yichao , Ni Hong , Han Rui
Published: September 2022

Ubiquitous in-network caching plays an important role in improving the efficiency of content access and distribution in Information-Centric Networks (ICN). Content placement strategies, which determine the location distribution of content replicas in the network, have a decisive impact on the performance of the cache system. Existing strategies primarily focus on pushing popular content to the network edge, aiming to improve the overall cache hit ratio while neglecting to effectively balance the traffic load between network links; this leads to insufficient utilization of network bandwidth resources and further excessive content delivery time and user QoE degradation. In this paper, a Path Load-Aware Based Caching strategy (PLABC) is proposed, in which content-related information and dynamic network-related information are comprehensively considered to make cache decisions. Specifically, the utility of caching the content at each on-path node is calculated according to the bandwidth consumption savings and the load level of the transmission path, and the node with the greatest utility value is selected as the caching node. Extensive simulations are conducted to compare the performance of PLABC with other state-of-the-art schemes by quantitative analysis. Simulation results validate the PLABC strategy’s effectiveness, especially in balancing link load and reducing content delivery time.
Using a Double-Core Structure to Reduce the LUT Count in FPGA-Based Mealy FSMs
Authors: Barkalov Alexander , Titarenko Larysa , Krzywicki Kazimierz
Published: September 2022

A method is proposed which aims at reducing the numbers of look-up table (LUT) elements in logic circuits of Mealy finite state machines (FSMs). The FSMs with twofold state assignment are discussed. The reduction is achieved due to using two cores of LUTs for generating partial Boolean functions. One core is based on maximum binary state codes. The second core uses extended state codes. Such an approach allows reducing the number of LUTs in the block of state codes’ transformation. The proposed approach leads to LUT-based Mealy FSM circuits having three levels of logic blocks. Each partial function for any core is represented by a single-LUT circuit. A formal method is proposed for redistribution of states between these cores. An example of synthesis is shown to explain peculiarities of the proposed method. An example of state redistribution is given. The results of experiments conducted with standard benchmarks show that the double-core approach produces LUT-based FSM circuits with better area-temporal characteristics than they are for circuits produced by other investigated methods (Auto and One-hot of Vivado, JEDI, and twofold state assignment). Both the LUT counts and maximum operating frequencies are improved. The gain in LUT counts varies from 5.74% to 36.92%, and the gain in frequency varies from 5.42% to 12.4%. These improvements are connected with a very small growth of the power consumption (less than 1%). The advantages of the proposed approach increase as the number of FSM inputs and states increases.
13.2 kV Class 3-Phase Solid State Transformer System Based on EtherCAT Communication
Authors: Jeong Dong-Keun , Yun Hyeok-Jin , Park Si-Ho , Kim Myoung-Ho , Ryu Myung-Hyo , Baek Ju-Won , Kim Ho-Sung
Published: September 2022

This paper presents a 13.2 kV class 3-phase solid-state transformer (SST) based on EtherCAT communication. In general, when the structure of the unit module is determined, the number of high-frequency isolated transformers (HFIT) is also proportional to the number of modules. The structure most considered in SST is a 1:1 combination of AC/DC converter and DC/DC converter. To optimally implement a 3-phase SST, a topology for reducing passive elements such as switching elements and HFIT is proposed. It also describes the design of HFIT used in DC/DC converter. EtherCAT communication with high transmission speed and expandability is applied to control the SST composed of unit modules stably, and a multi-core microcontroller unit (MCU) is applied to achieve both a high-speed communication cycle and complicated control algorithm execution. The discussions are validated using a 300 kW 13.2 kV class 3-phase SST prototype in various conditions.
Parametric Performance Analysis of the Cooling Potential of Earth-to-Air Heat Exchangers in Hot and Humid Climates
Authors: Bughio Mushk , Bahale Swati , Mahar Waqas Ahmed , Schuetze Thorsten
Published: September 2022

Earth-to-air heat exchangers (EAHEs) are widely used to reduce the indoor temperature and associated cooling energy demand of buildings. This study investigated the potential reduction in indoor temperatures via energy-efficient ventilation through EAHEs in an existing architectural campus building (ACB) with an energy-efficient renovated building envelope in the hot and humid climate of Karachi, Pakistan. The building information modeling (BIM) program Autodesk Revit was used to develop a virtual ACB BIM model. An EnergyPlus parametric analysis of the ACB BIM model in DesignBuilder facilitated quantification of the influences of operating parameters such as pipe installation depth and pipe diameter for EAHEs with similar total pipe lengths and air-exchange rates on the performance of the EAHEs during the cooling season. A 3 m deep and 0.1 m diameter pipe layout in open space significantly reduces indoor temperature via a specific duct layout in an exemplary ACB. The results show that a pipe diameter above 0.1 m is unsuitable because of the reduction in convective heat transfer due to the increase in the pipe’s surface area and the decrease in pressure in the pipe. The findings of this study can be used to improve the indoor thermal comfort of buildings in climates with comparable properties.
Evaluation of Technical Solutions to Improve Transient Stability in Power Systems with Wind Power Generation
Authors: Tina Giuseppe Marco , Maione Giovanni , Licciardello Sebastiano
Published: September 2022

Reliability and safety must be carefully considered in today’s power systems, which are rapidly evolving toward ever higher penetration of renewable, inverter-based generation units. Power systems are constantly stressed by active power disturbances, which can be exacerbated by wind and solar systems that are subject to rapid fluctuations in primary energy. In this framework, a comparative technical analysis of solutions to improve transient stability, both rotor angle stability and frequency stability, is carried out. These solutions can be adopted by the transmission system operator (e.g., an additional parallel transmission line), by the generation companies (e.g., a fast excitation system), or by both, such as SVC (static VAR compensator) and STATCOM (static synchronous compensator). Sensitivity analyses were carried out to assess the impact of the location of the wind turbines in the buses of the grid on their rated power and level of production. On the basis of these analyses, the worst-case fault was considered, and the critical fault recovery time was determined as an engineering parameter to compare the different solutions. For the numerical analysis, a modified IEEE 9-bus system was considered, and the PowerWorld software tool was used. Rotor angle and frequency stability analyses were performed.