bluuebunny/crossref_metadata_2025 huggingface dataset:
Acinic Cell Carcinoma in the 21st Century: A Population-Based Study from the SEER Database and Review of Recent Molecular Genetic Advances
Authors: Khan Jaffar , Ullah Asad , Goodbee Mya , Lee Kue Tylor , Yasinzai Abdul Qahar Khan , Lewis James S. , Mesa Hector
Published: June 2023

Background: Acinic cell carcinoma (AciCC) comprises 6–7% of all salivary gland neoplasms and is the second most common salivary gland malignancy in children. Like many salivary gland carcinomas, it is considered low grade but occasionally it behaves aggressively. Understanding the risk factors associated with recurrence, metastasis, and death is important to determine the counseling and management of individual patients. Older population-based studies are presumed to have been confounded by the misclassification of other neoplasms as AciCC, in particular secretory carcinoma and cystadenocarcinoma. Since diagnostic tools to reliably separate these entities have been available for over a decade, reevaluation of epidemiologic data limited to the 21st century should allow a better characterization of the clinicopathological characteristics of AciCC. Methods: Our study extracted data from the Surveillance, Epidemiology, and End Results (SEER) database for the period 2000 to 2018. Cox regression model analysis was performed to identify risk factors independently affecting survival. Results: Data for 2226 patients with AciCC were extracted from the database. Most patients were females: 59%, and white: 80.5%, with a mean age at diagnosis of 51.2 (SD ± 18.7) years. Most cases (81%) were localized at presentation. Tumor size was less than 2 cm in 42%, 2–4 cm in 47%, and >4 cm in 11%. Low-grade tumors had 5-year survival > 90%, whereas high-grade tumors had survival < 50%. Of the patients with known lymph node status only 7.3% had nodal metastases. Distant metastases were documented in 1.1%, involving lungs 44%, bone 40%, liver 12%, and brain 4%. The most common treatment modality was surgery alone: 63.6% followed by surgery and adjuvant radiation: 33%. A few received chemotherapy (1.8%) or multimodality therapy (1.2%). The 5-year overall survival rate was 90.6% (95%CI 89.1–91.9), and disease-specific survival was 94.6% (95%CI 93.3–95.6). Multivariable cox regression analysis showed that undifferentiated (HR = 8.3) and poorly differentiated tumor grade (HR = 6.4), and metastasis (HR = 5.3) were the worst independent prognostic factors. Other poor risk factors included age > 50 (HR = 3.5) and tumor size > 4 cm (HR = 2.5). Conclusions: In the US, AciCC is more common in middle age white females, and most tumors are less than 4 cm and localized at diagnosis. The most relevant negative prognostic factor was high tumor grade which was associated with higher hazard ratios for death than all other variables, including regional or distant metastases at presentation.
Explainable CAD System for Classification of Acute Lymphoblastic Leukemia Based on a Robust White Blood Cell Segmentation
Authors: Diaz Resendiz Jose Luis , Ponomaryov Volodymyr , Reyes Reyes Rogelio , Sadovnychiy Sergiy
Published: June 2023

Leukemia is a significant health challenge, with high incidence and mortality rates. Computer-aided diagnosis (CAD) has emerged as a promising approach. However, deep-learning methods suffer from the “black box problem”, leading to unreliable diagnoses. This research proposes an Explainable AI (XAI) Leukemia classification method that addresses this issue by incorporating a robust White Blood Cell (WBC) nuclei segmentation as a hard attention mechanism. The segmentation of WBC is achieved by combining image processing and U-Net techniques, resulting in improved overall performance. The segmented images are fed into modified ResNet-50 models, where the MLP classifier, activation functions, and training scheme have been tested for leukemia subtype classification. Additionally, we add visual explainability and feature space analysis techniques to offer an interpretable classification. Our segmentation algorithm achieves an Intersection over Union (IoU) of 0.91, in six databases. Furthermore, the deep-learning classifier achieves an accuracy of 99.9% on testing. The Grad CAM methods and clustering space analysis confirm improved network focus when classifying segmented images compared to non-segmented images. Overall, the proposed visual explainable CAD system has the potential to assist physicians in diagnosing leukemia and improving patient outcomes.
Myo/Nog Cells: The Jekylls and Hydes of the Lens
Authors: Gerhart Jacquelyn , George-Weinstein Mindy
Published: June 2023

Herein, we review a unique and versatile lineage composed of Myo/Nog cells that may be beneficial or detrimental depending on their environment and nature of the pathological stimuli they are exposed to. While we will focus on the lens, related Myo/Nog cell behaviors and functions in other tissues are integrated into the narrative of our research that spans over three decades, examines multiple species and progresses from early stages of embryonic development to aging adults. Myo/Nog cells were discovered in the embryonic epiblast by their co-expression of the skeletal muscle-specific transcription factor MyoD, the bone morphogenetic protein inhibitor Noggin and brain-specific angiogenesis inhibitor 1. They were tracked from the epiblast into the developing lens, revealing heterogeneity of cell types within this structure. Depletion of Myo/Nog cells in the epiblast results in eye malformations arising from the absence of Noggin. In the adult lens, Myo/Nog cells are the source of myofibroblasts whose contractions produce wrinkles in the capsule. Eliminating this population within the rabbit lens during cataract surgery reduces posterior capsule opacification to below clinically significant levels. Parallels are drawn between the therapeutic potential of targeting Myo/Nog cells to prevent fibrotic disease in the lens and other ocular tissues.
Current Understanding of the Roles of Gut–Brain Axis in the Cognitive Deficits Caused by Perinatal Stress Exposure
Authors: Rubinstein Mara Roxana , Burgueño Adriana Laura , Quiroga Sofia , Wald Miriam Ruth , Genaro Ana María
Published: June 2023

The term ‘perinatal environment’ refers to the period surrounding birth, which plays a crucial role in brain development. It has been suggested that dynamic communication between the neuro–immune system and gut microbiota is essential in maintaining adequate brain function. This interaction depends on the mother’s status during pregnancy and/or the newborn environment. Here, we show experimental and clinical evidence that indicates that the perinatal period is a critical window in which stress-induced immune activation and altered microbiota compositions produce lasting behavioral consequences, although a clear causative relationship has not yet been established. In addition, we discuss potential early treatments for preventing the deleterious effect of perinatal stress exposure. In this sense, early environmental enrichment exposure (including exercise) and melatonin use in the perinatal period could be valuable in improving the negative consequences of early adversities. The evidence presented in this review encourages the realization of studies investigating the beneficial role of melatonin administration and environmental enrichment exposure in mitigating cognitive alteration in offspring under perinatal stress exposure. On the other hand, direct evidence of microbiota restoration as the main mechanism behind the beneficial effects of this treatment has not been fully demonstrated and should be explored in future studies.
Study on the Wear Performance of Polyethylene Inner Lining Pipe under Different Load and Mineralization Conditions
Authors: Ding Liqin , Wang Lei , Li Jie , Qi Suoping , Zhang Wanli , Xi Yuntao , Zhang Keren , Xu Shanna , Liu Haitao , Wen Lei , Xiao Xinke , Ji Jiangtao
Published: June 2023

This study conducted pin disc friction and wear performance tests on polyethylene-lined oil pipes and four types of centralizing materials (45# steel, nylon, polytetrafluoroethylene (PTFE), and surface alloy coating) in oil fields. The friction coefficient and wear rate were tested, and the wear mechanism was analyzed using scanning electron microscopy (SEM) and three-dimensional confocal microscopy. Using a combination of experimental testing analysis and theoretical research, a comprehensive evaluation of the current wellbore centering and anti-wear technology for oil was conducted. The experimental results indicate that the usage limit of polyethylene-lined oil pipes is 400 N, and compared to metal oil pipe materials, the wear rate of both stabilizing material and tubing material is lower, indicating that it has a certain service life. From the perspective of testing load, taking into account the factors of friction coefficient and wear rate, the recommended sequence of straightening material for polyethylene lined oil pipes is (1) surface alloy coating, (2) nylon, (3) PTFE, and (4) 45# steel.
Corrosion Protection Mechanism Study of Nitrite-Modified CaAl-LDH in Epoxy Coatings
Authors: Xue Junhao , Wang Jingjing , Cao Yanhui , Zhang Xinyue , Zhang Lili , Chen Kaifeng , Huang Congshu
Published: June 2023

In this work, nitrite and molybdate-modified CaAl layered double hydroxide(CaAl-LDH) was first synthesized, and the corrosion protection mechanism of CaAl-LDH intercalated with nitrites in epoxy coatings was investigated. Scanning electronic microscopy (SEM) and the energy dispersive spectroscopy (EDS) was used to characterize the morphology and element composition of the synthesized powder. Fourier transform infrared spectroscopy (FTIR) was used to characterize the information of chemical composition, and X-ray diffraction (XRD) was used to analyze the structure. The SEM and XRD results indicated that the LDH structure was destroyed in the molybdate modification process, and CaMoO4 precipitates were formed. Therefore, molybdates cannot be used to be loaded in CaAl-LDH interlayer space for synthesis of an active corrosion inhibition container. The nitrite release curve and the chloride concentration decreasing curve were measured to study the anion-exchange reaction by UV-Vis spectroscopy and a home-made Ag/AgCl probe, respectively. The corrosion protection effect of the CaAl-LDH loaded with nitrites towards the carbon steel was evaluated in 0.02 M NaCl solution by electrochemical impedance spectroscopy (EIS). Then the powder was added in the epoxy coating with 2% addition (weight vs. epoxy resin). The coating morphology and roughness were evaluated by SEM and laser microscopy, and the corrosion protection effect was investigated by EIS in an immersion period of 21 d. The fitted coating resistance of the sample with 2% LDH intercalated with nitrites was one order of magnitude higher than that with 2% LDH, and the latter one was two orders of magnitude higher than the blank sample. Local electrochemical impedance spectra (LEIS) was used to characterize the corrosion development process in micro-corrosion sites. The corrosion product of the scratched area after salt spray exposure was analyzed by EDS and Raman spectroscopy. The corrosion protection mechanism of the CaAl-LDH loaded with nitrites was proposed based on the above experimental results.
Cardiac MRI Findings in Patients Clinically Referred for Evaluation of Post-Acute Sequelae of SARS-CoV-2 Infection
Authors: Halfmann Moritz , Luetkens Julian , Langenbach Isabel , Kravchenko Dmitrij , Wenzel Philip , Emrich Tilman , Isaak Alexander
Published: June 2023

Persistent or recurrent cardiovascular symptoms have been identified as one of the hallmarks of long-COVID or post-acute sequelae of SARS-CoV-2 infection (PASC). The purpose of this study was to determine the prevalence and extent of cardiac abnormalities in patients referred for cardiac MRI due to clinical evidence of PASC. To investigate this, two tertiary care hospitals identified all patients who were referred for cardiac MRI under the suspicion of PASC in a 2-year period and retrospectively included them in this study. Patients with previously known cardiac diseases were excluded. This resulted in a total cohort of 129 patients (63, 51% female; age 41 ± 16 years). The majority of patients (57%) showed normal cardiac results. No patient had active myocarditis or an acute myocardial infarction. However, 30% of patients had evidence of non-ischemic myocardial fibrosis, which exceeds the prevalence in the normal adult population and suggests that a possible history of myocarditis might explain persistent symptoms in the PASC setting.
Preliminary Prognostication for Good Neurological Outcomes in the Early Stage of Post-Cardiac Arrest Care
Authors: Lee Sunghyuk , Park Jung Soo , You Yeonho , Min Jin Hong , Jeong Wonjoon , Ahn Hong Joon , In Yong Nam , Cho Yong Chul , Lee In Ho , Lee Jae Kwang , Kang Changshin
Published: June 2023

We investigated prognostic strategies for predicting good outcomes in the early stage of post-cardiac-arrest care using multiple prognostic tests that are available until 24 h after the return of spontaneous circulation (ROSC). A retrospective analysis was conducted on 138 out-of-hospital cardiac-arrest patients who underwent prognostic tests, including the gray–white-matter ratio (GWR-BG), the Glasgow Coma Scale motor (GCS-M) score before sedative administration, and the neuron-specific enolase (NSE) level measured at 24 h after the ROSC. We investigated the prognostic performances of the tests as single predictors and in various combination strategies. Classification and regression-tree analysis were used to provide a reliable model for the risk stratification. Out of all the patients, 55 (44.0%) had good outcomes. The NSE level showed the highest prognostic performance as a single prognostic test and provided improved specificities (>70%) and sensitivities (>98%) when used in combination strategies. Low NSE levels (≤32.1 ng/mL) and high GCS-M (≥4) scores identified good outcomes without misclassification. The overall accuracy for good outcomes was 81.8%. In comatose patients with low NSE levels or high GCS-M scores, the premature withdrawal of life-sustaining therapy should be avoided, thereby complying with the formal prognostication-strategy algorithm after at least 72 h from the ROSC.
Vaccines in Breast Cancer: Challenges and Breakthroughs
Authors: Fatima Gul Naz , Fatma Hera , Saraf Shailendra K.
Published: June 2023

Breast cancer is a problem for women’s health globally. Early detection techniques come in a variety of forms ranging from local to systemic and from non-invasive to invasive. The treatment of cancer has always been challenging despite the availability of a wide range of therapeutics. This is either due to the variable behaviour and heterogeneity of the proliferating cells and/or the individual’s response towards the treatment applied. However, advancements in cancer biology and scientific technology have changed the course of the cancer treatment approach. This current review briefly encompasses the diagnostics, the latest and most recent breakthrough strategies and challenges, and the limitations in fighting breast cancer, emphasising the development of breast cancer vaccines. It also includes the filed/granted patents referring to the same aspects.
Association between the Temporomandibular Joint Morphology and Chewing Pattern
Authors: Sritara Sasin , Matsumoto Yoshiro , Lou Yixin , Qi Jia , Aida Jun , Ono Takashi
Published: June 2023

This study aimed to investigate whether the morphology of the temporomandibular joint (TMJ) is associated with chewing patterns while considering skeletal morphology, sex, age, and symptoms of temporomandibular disorder (TMD). A cross-sectional observational study of 102 TMJs of 80 patients (age 16–40 years) was performed using pretreatment records of cone-beam computed tomography imaging of the TMJ, mandibular kinesiographic records of gum chewing, lateral and posteroanterior cephalometric radiographs, patient history, and pretreatment questionnaires. To select appropriate TMJ measurements, linear regression analyses were performed using TMJ measurements as dependent variables and chewing patterns as the independent variable with adjustment for other covariates, including Nasion-B plane (SNB) angle, Frankfort-mandibular plane angle (FMA), amount of lateral mandibular shift, sex, age, and symptoms of TMD. In multiple linear regression models adjusted for other covariates, the length of the horizontal short axis of the condyle and radius of the condyle at 135° from the medial pole were significantly (p < 0.05) associated with the chewing patterns in the frontal plane on the working side. “Non-bilateral grinding” displayed a more rounded shape of the mandibular condyle. Conversely, “bilateral grinding” exhibited a flatter shape in the anteroposterior aspect. These findings suggest that the mandibular condyle morphology might be related to skeletal and masticatory function, including chewing patterns.
Glycans as Potential Diagnostic Markers of Traumatic Brain Injury in Children
Authors: Kvist Mårten , Välimaa Lasse , Harel Adrian , Malmi Sari , Tuomisto Aleksi
Published: June 2023

Diagnosing mild traumatic brain injury (TBI) in the acute setting is challenging due to the nonspecific and often transient or delayed symptoms. Further, the criteria for acute head imaging are frequently not fulfilled, which may lead to a missed diagnosis. A rapid test to diagnose TBI using body fluids would be highly useful. Urine and saliva samples were collected from 28 pediatric patients (mean [SD] age, eight years two months [four years three months]) with acute, clinically diagnosed mild TBI and 30 healthy volunteers at Satasairaala Hospital, Pori, Finland, over 11 months. The mean (SD) time from trauma to first sampling was 3 h 56 min (1 h 14 min). Samples were analyzed to determine the number of lectin-binding glycan molecules, indicating nerve tissue damage. The relative levels of several lectin-bound glycans were measured by fluorescence. Compared with healthy controls, the TBI group showed significant increases (p < 0.05, Wilcoxon rank-sum two-sided test) in nine glycans in the saliva, one glycan in the urine, and a significant decrease in seven glycans in the urine. These findings of potentially diagnostic glycans in body fluids after TBI warrant further research and may enable the development of a rapid body fluid-based point-of-care test to identify pediatric patients with TBI after a head injury.
Predicting the Efficacy of Neoadjuvant Chemotherapy for Pancreatic Cancer Using Deep Learning of Contrast-Enhanced Ultrasound Videos
Authors: Shao Yuming , Dang Yingnan , Cheng Yuejuan , Gui Yang , Chen Xueqi , Chen Tianjiao , Zeng Yan , Tan Li , Zhang Jing , Xiao Mengsu , Yan Xiaoyi , Lv Ke , Zhou Zhuhuang
Published: June 2023

Contrast-enhanced ultrasound (CEUS) is a promising imaging modality in predicting the efficacy of neoadjuvant chemotherapy for pancreatic cancer, a tumor with high mortality. In this study, we proposed a deep-learning-based strategy for analyzing CEUS videos to predict the prognosis of pancreatic cancer neoadjuvant chemotherapy. Pre-trained convolutional neural network (CNN) models were used for binary classification of the chemotherapy as effective or ineffective, with CEUS videos collected before chemotherapy as the model input, and with the efficacy after chemotherapy as the reference standard. We proposed two deep learning models. The first CNN model used videos of ultrasound (US) and CEUS (US+CEUS), while the second CNN model only used videos of selected regions of interest (ROIs) within CEUS (CEUS-ROI). A total of 38 patients with strict restriction of clinical factors were enrolled, with 76 original CEUS videos collected. After data augmentation, 760 and 720 videos were included for the two CNN models, respectively. Seventy-six-fold and 72-fold cross-validations were performed to validate the classification performance of the two CNN models. The areas under the curve were 0.892 and 0.908 for the two models. The accuracy, recall, precision and F1 score were 0.829, 0.759, 0.786, and 0.772 for the first model. Those were 0.864, 0.930, 0.866, and 0.897 for the second model. A total of 38.2% and 40.3% of the original videos could be clearly distinguished by the deep learning models when the naked eye made an inaccurate classification. This study is the first to demonstrate the feasibility and potential of deep learning models based on pre-chemotherapy CEUS videos in predicting the efficacy of neoadjuvant chemotherapy for pancreas cancer.
Tear Cytokine Levels in Sicca Syndrome-Related Dry Eye: A Meta-Analysis
Authors: Aljohani Suad , Jazzar Ahoud
Published: June 2023

Sjogren’s syndrome (SS) is an autoimmune disease that affects exocrine glands, mainly salivary and lacrimal glands. Several studies have investigated cytokine profiles in tears in order to understand the pathogenesis of SS and find additional diagnostic markers. This systematic review and meta-analysis aimed to analyze cytokines in tears of SS patients. A systematic literature search of the Cochrane, Medline via PubMed, Scopus, and Web of Science databases was conducted using key terms related to “Sjögren’s syndrome” and “tears” combined with “biomarker”, “cytokines”, “interleukin”, and “chemokines”, following PRISMA guidelines. Article selection was subjected to certain eligibility criteria. A total of 17 articles (from 1998 and 2022) were selected for the quantitative and qualitative analysis. When compared to controls, concentrations of IFN-γ, TNF-α, IL-1α, IL-1 Ra, IL-4, IL-6, IL-8, IL-10, IL-17, IL-21 and IL-22 were consistently higher; however, IL-23 was significantly lower in patients with SS compared to the controls. Tear levels of some cytokines were significantly elevated among SS groups compared to control groups. Therefore, these cytokines could be potential biomarkers of SS. However, standardization of sample collection and analytical methods is necessary in order to translate these findings into clinical practice.
Mirroring Perinatal Outcomes in a Romanian Adolescent Cohort of Pregnant Women from 2015 to 2021
Authors: Matasariu Daniela Roxana , Dumitrascu Irina , Bujor Iuliana Elena , Cristofor Alexandra Elena , Boiculese Lucian Vasile , Mandici Cristina Elena , Grigore Mihaela , Socolov Demetra , Nechifor Florin , Ursache Alexandra
Published: June 2023

Although the rates of adolescent pregnancies appear to have dropped according to the World Health Organization (WHO), the decrease in the age of the first menarche and better nutrition seems to contribute to the otherwise high rate of adolescent pregnancy worldwide, despite the efforts of different organizations to improve upon this trend. We conducted a population-based retrospective cohort study from January 2015 to December 2021 using our hospitals’ database. We totaled 2.954 adolescent and 6.802 adult pregnancies. First, we compared younger adolescents’ outcomes with those of older adolescents, as well as with adolescents aged between 18 and 19 years old; secondly, we compared adolescent pregnancies with adult ones. We detected higher percentages of cephalo-pelvic disproportion (43.2%), cervical dystocia (20.7%), and twin pregnancy (2.7%) in underage adolescents compared with 32%, 14.1%, and 1% in older underage adolescents, respectively, and 15.3%, 3.1%, and 0.6% in older ones. As teens became older, the likelihood of malpresentations and previous C-sections rose, whereas the likelihood of vaginal lacerations declined. When comparing adolescents with adult women, we found more cases that required episiotomy (48.1% compared with 34.6%), instrumental delivery (2.1% compared with 1%), and cervical laceration (10.7% compared with 8.4%) in the adolescent group, but the rates of malpresentation (11.4% compared with 13.5%), previous C-section (13.9% compared with 17.7%), and placenta and vasa praevia (4.5.6% compared with 14%) were higher in the adult women group. Adolescent pregnancy is prone to being associated with higher risks and complications and continues to represent a challenge for our medical system.
PFFNET: A Fast Progressive Feature Fusion Network for Detecting Drones in Infrared Images
Authors: Han Ziqiang , Zhang Cong , Feng Hengzhen , Yue Mingkai , Quan Kangnan
Published: June 2023

The rampant misuse of drones poses a serious threat to national security and human life. Currently, CNN (Convolutional Neural Networks) are widely used to detect drones. However, small drone targets often reduced amplitude or even lost features in infrared images which traditional CNN cannot overcome. This paper proposes a Progressive Feature Fusion Network (PFFNET) and designs a Pooling Pyramid Fusion (PFM) to provide more effective global contextual priors for the highest downsampling output. Then, the Feature Selection Model (FSM) is designed to improve the use of the output coding graph and enhance the feature representation of the target in the network. Finally, a lightweight segmentation head is designed to achieve progressive feature fusion with multi-layer outputs. Experimental results show that the proposed algorithm has good real-time performance and high accuracy in drone target detection. On the public dataset, the intersection over union (IOU) is improved by 2.5% and the detection time is reduced by 81%.
Inhibitory Control, Social Cognition, and Peer Social Competence among Children with and without a Migration Background in Italy
Authors: Dicataldo Raffaele , Moscardino Ughetta , Roch Maja , Mammarella Irene C.
Published: June 2023

Executive functions and social cognition (i.e., the mental operations that underlie social interaction) are essential for children’s successful interactions, yet their role in peer social competence among children with and without a migration background is still underexplored. This study investigated the influence of inhibitory control and two domains of social cognition (theory of mind and facial emotion recognition) on children’s peer social competence exploring moderation by children’s migration background. First graders in Italy (n = 321, M age = 6.4 years, 45% girls, and 39% with a migration background) completed standardized tests, while teachers rated students’ peer social competence. The results indicated that immigrant-origin children were perceived as being less socially competent than their non-immigrant counterparts. Among children with a migration background, better inhibitory control and facial emotion recognition skills were linked to increased peer social competence. Following the presentation of these results, we will discuss the implications for both developmental theory and practice.
Hybrid Phishing Detection Based on Automated Feature Selection Using the Chaotic Dragonfly Algorithm
Authors: Alshammari Gharbi , Alshammari Majdah , Almurayziq Tariq S. , Alshammari Abdullah , Alsaffar Mohammad
Published: June 2023

Due to the increased frequency of phishing attacks, network security has gained the attention of researchers. In addition to this, large volumes of data are created every day, and these data include inappropriate and unrelated features that influence the accuracy of machine learning. There is therefore a need for a robust method of detecting phishing threats and improving detection accuracy. In this study, three classifiers were applied to improve the accuracy of a detection algorithm: decision tree, k-nearest neighbors (KNN), and support vector machine (SVM). Selecting the relevant features improves the detection accuracy for a target class and determines the class label with the greatest probability. The proposed work clearly describes how feature selection using the Chaotic Dragonfly Algorithm provides more accurate results than all other baseline classifiers. It also indicates the appropriate classifier to be applied when detecting phishing websites. Three publicly available datasets were used to evaluate the method. They are reliable datasets for training the model and measuring prediction accuracy.
High-Frequency Oscillation Suppression Strategy for Flexible DC Transmission Systems Based on Additional Joint Damping
Authors: Chao Wujie , Deng Chaoping , Dai Liyu , Huang Junwei , Tan Zipeng , Cheng Yangfan , Wang Hongyao , Wang Yuhong , Liao Jianquan
Published: June 2023

Flexible DC transmission systems experience negative damping characteristics in the high-frequency range due to the delay in the system control link. This can lead to interactions between the impedance of modular multilevel converters (MMCs) and AC transmission lines, resulting in high-frequency oscillation (HFO) issues. To resolve this problem, a simplified MMC control model was developed, taking into account the current inner loop control link. The Sobol method was employed to analyze the factors influencing the impedance characteristics of MMC. Additionally, a combined approach involving a virtual passive filtering method and an equivalent current sampling method was proposed to provide additional damping. The study compared and analyzed the impact of additional damping control on the impedance characteristics and system stability of MMCs. Lastly, a flexible direct current grid connection simulation model was constructed using PSCAD to validate the effectiveness of the proposed additional damping control strategy.
Current-Mode First-Order Versatile Filter Using Translinear Current Conveyors with Controlled Current Gain
Authors: Kumngern Montree , Jongchanachavawat Wirote , Phatsornsiri Punnavich , Wongprommoon Natapong , Khateb Fabian , Kulej Tomasz
Published: June 2023

This paper offers a new current-mode first-order versatile filter employing two translinear current conveyors with controlled current gain and one grounded capacitor. The proposed filter offers the following features: realization of first-order transfer functions of low-pass, high-pass, and all-pass current responses from single topology, availability of non-inverting and inverting transfer functions for all current responses, electronic control of current gain for all current responses, no requirement of component-matching conditions for realizing all current responses, low-input impedance and high-output impedance which are required for current-mode circuits, and electronic control of the pole frequency for all current responses. The proposed first-order versatile filter is used to realize a quadrature sinusoidal oscillator to confirm the advantage of the new topology. To confirm the functionality and workability of new circuits, the proposed circuit and its application are simulated by the SPICE program using transistor model process parameters NR100N (NPN) and PR100N (PNP) of bipolar arrays ALA400-CBIC-R from AT&T.
Virtual Reality in Education: A Review of Learning Theories, Approaches and Methodologies for the Last Decade
Authors: Marougkas Andreas , Troussas Christos , Krouska Akrivi , Sgouropoulou Cleo
Published: June 2023

In the field of education, virtual reality (VR) offers learners an immersive and interactive learning experience, allowing them to comprehend challenging concepts and ideas more efficiently and effectively. VR technology has enabled educators to develop a wide range of learning experiences, from virtual field trips to complex simulations, that may be utilized to engage students and help them learn. Learning theories and approaches are essential for understanding how students learn and how to design effective learning experiences. This study examines the most recent published findings in educational theories and approaches connected to the use of VR systems for educational and tutoring purposes. Seventeen research studies that meet the search criteria have been found in the database, and each of them focuses on at least one learning theory or learning approach related to educational systems using VR. These studies yielded five educational approaches, one methodology, five learning theories and one theoretical framework, which are presented in the context of virtual reality in education. These include constructivism learning, experiential learning, gamification of learning, John Dewey’s theory of learning by doing, flow theory, Cognitive Theory of Multimedia Learning, design thinking, learning through problem solving, scientific discovery learning, social constructivism, cognitive load theory and the Technology Pedagogical Content Knowledge Framework (TPACK). A major finding of this study is that constructivism learning is the most often utilized learning theory/method, Experiential Learning is most appropriate for VR and the gamification of learning has the greatest future potential.
Heavy Ion Single Event Effects in CMOS Image Sensors: SET and SEU
Authors: Yang Zhikang , Wen Lin , Li Yudong , Feng Jie , Zhou Dong , Liu Bingkai , Zhao Zitao , Guo Qi
Published: June 2023

High-energy particles in space often induce single event effects in CMOS image sensors, resulting in performance degradation and functional failure. This paper focuses on the formation and morphology of transient bright spots in CMOS image sensors and analyzes the formation process of transient bright spots by conducting heavy ion irradiation experiments to obtain the variation law of transient bright spots with heavy ion linear energy transfer values and background gray values; in addition, we classify the single event upset that occurred in the experiments according to the state of transient bright spots and extract the characteristics of different single event upsets. The failure mechanisms of different single event upsets are analyzed according to their characteristics and are combined with the information given by transient bright spots. This provides an essential reference for rapidly evaluating single event effects and the reinforcement design of CMOS image sensors.
System Design and Signal Processing in Spaceborne Squint Sliding Spotlight SAR with Sub-Aperture Block-Varying PRF
Authors: Xu Wei , Zhang Zhuo , Huang Pingping , Tan Weixian , Qi Yaolong
Published: June 2023

To tackle the problems of Doppler spectrum, aliasing caused by azimuth beam scanning and azimuthal serious non-uniform sampling in squint sliding spotlight synthetic aperture radar (SAR) with varying repetition frequency technology, the azimuth sampling method of sub-aperture block-varying pulse repetition frequency (SBV-PRF) is proposed, where the sub-aperture division judgement makes the azimuth acquisition time of each sub-block small enough so that the Doppler bandwidth caused by the Doppler center change can be ignored. Based on the echo signal characteristics of a SBV-PRF transmission scheme, an azimuth pre-processing method combining SBV-PRF transmission scheme with sub-aperture division is proposed. Using this method, de-skewing is first performed on each set of sub-aperture data to eliminate the additional Doppler bandwidth introduced by the squint angle, and then the azimuth signal resampling is performed to ensure different sub-aperture data have the same sampling rate. The SBV-PRF technology reduces the difficulty of azimuth signal pre-processing while ensuring the complete acquisition of the complete echo data of the squint sliding spotlight mode. The effectiveness of the SBV-PRF system design and the signal processing method is verified by the point target echo simulation and imaging simulation results.
EA-ConvNeXt: An Approach to Script Identification in Natural Scenes Based on Edge Flow and Coordinate Attention
Authors: Zhang Zhiyun , Eli Elham , Mamat Hornisa , Aysa Alimjan , Ubul Kurban
Published: June 2023

In multilingual scene text understanding, script identification is an important prerequisite step for text image recognition. Due to the complex background of text images in natural scenes, severe noise, and common symbols or similar layouts in different language families, the problem of script identification has not been solved. This paper proposes a new script identification method based on ConvNext improvement, namely EA-ConvNext. Firstly, the method of generating an edge flow map from the original image is proposed, which increases the number of scripts and reduces background noise. Then, based on the feature information extracted by the convolutional neural network ConvNeXt, a coordinate attention module is proposed to enhance the description of spatial position feature information in the vertical direction. The public dataset SIW-13 has been expanded, and the Uyghur script image dataset has been added, named SIW-14. The improved method achieved identification rates of 97.3%, 93.5%, and 92.4% on public script identification datasets CVSI-2015, MLe2e, and SIW-13, respectively, and 92.0% on the expanded dataset SIW-14, verifying the superiority of this method.
Vehicle Detection Based on Information Fusion of mmWave Radar and Monocular Vision
Authors: Cai Guizhong , Wang Xianpeng , Shi Jinmei , Lan Xiang , Su Ting , Guo Yuehao
Published: June 2023

Single sensors often fail to meet the needs of practical applications due to their lack of robustness and poor detection accuracy in harsh weather and complex environments. A vehicle detection method based on the fusion of millimeter wave (mmWave) radar and monocular vision was proposed to solve this problem in this paper. The method successfully combines the benefits of mmWave radar for measuring distance and speed with the vision for classifying objects. Firstly, the raw point cloud data of mmWave radar can be processed by the proposed data pre-processing algorithm to obtain 3D detection points with higher confidence. Next, the density-based spatial clustering of applications with noise (DBSCAN) clustering fusion algorithm and the nearest neighbor algorithm were also used to correlate the same frame data and adjacent frame data, respectively. Then, the effective targets from mmWave radar and vision were matched under temporal-spatio alignment. In addition, the successfully matched targets were output by using the Kalman weighted fusion algorithm. Targets that were not successfully matched were marked as new targets for tracking and handled in a valid cycle. Finally, experiments demonstrated that the proposed method can improve target localization and detection accuracy, reduce missed detection occurrences, and efficiently fuse the data from the two sensors.
A Wide-Band Modeling Research of Voltage Transformer in EMU
Authors: Wu Yan , Che Yongwang , Wang Qingfeng , Zhang Jianqiong , Li Xiangqiang , Tang Xianfeng
Published: June 2023

Considering that current voltage transformer models of electrical multiple units (EMUs) are narrow-band models or transformer models, this paper introduces a wide-band model of EMU voltage transformers based on the vector fitting method, circuit synthesis theory and black-box model theory. The admittances of voltage transformers from 30 kHz to 5 MHz are measured by the vector network analyzer, the branch admittances in the pi-type equivalent circuit are calculated according to the equation of a two-port network equivalent circuit. Based on the vector matching method, the rational function formulas of branch admittances are obtained, and the formulas are converted into the circuit models by circuit synthesis theory. The pi-type equivalent circuit model is constructed in the simulation software, and so is the voltage transformer model in the range of 30 kHz–5 MHz. The frequency sweeping method is used to measure the transmission characteristics from direct current (DC)to 30 kHz. The pi-type model is modified according to transmission characteristics, whereby the wide-band model in DC-5 MHz is obtained. Fast pulse experiments are carried out on the voltage transformer, and the actual injected fast pulse voltage is used as the excitation source in the simulation model. The measurement and simulation results on the secondary side of the voltage transformer show that the wide-band model has a high accuracy.
Assessing Coastal Erosion and Climate Change Adaptation Measures: A Novel Participatory Approach
Authors: Coelho Carlos , Lima Márcia , Alves Filipe M. , Roebeling Peter , Pais-Barbosa Joaquim , Marto Marco
Published: June 2023

This work aims to provide a more complete characterization of coastal erosion mitigation and climate change adaptation measures by presenting a participatory approach that integrates medium- to long-term perspectives, considering simultaneously social, environmental, economic and engineering dimensions to help decision makers implement sustainable climate change adaptation (CCA) strategies. The work lists, explains and characterizes existing climate change mitigation and adaptation measures as well as their costs and positive and negative social, environmental and economic impacts, in three distinct databases. These databases are discussed, complemented and validated in participatory moments with local stakeholders of the Ovar Municipality, Portugal, which represents the case study to support the proposed methodology. Although Ovar is a pilot case, the integrated framework for resilient CCA has a global application with respect to methodologies and concepts. The proposed approach is useful to help coastal management entities to engage in more efficient, effective and beneficial planned action to mitigate coastal erosion and adapt to future climate change effects. The open-source databases and the participatory approach facilitate decision makers and coastal communities to navigate the complexity of solutions and build consensus around collective actions for coastal areas.
Soil Organic Carbon Turnover Response to Nitrogen and Phosphorus Additions in Eastern China: Evidence from Stable Carbon Isotopes
Authors: Chen Leiru , Wen Zhengyu , Yin Ruoyong , Deng Pengfei , Gao Yu , Xu Hui , Xu Xiaoniu
Published: June 2023

Anthropogenic activities have drastically increased nitrogen (N) deposition, resulting in increased N availability. The continuous increase of N availability may exacerbate phosphorus (P) deficiency, which would limit forest productivity in subtropical forests. Effects of long-time N and N + P additions on SOC turnover in subtropical forests is therefore crucial for understanding the global carbon (C) cycle. The argument of whether N and N + P addition accelerates or slows SOC turnover has been under debate, particularly in P-limited subtropical forests. This study mainly aims to confirm this argument. A ten-year field experiment was conducted in a subtropical evergreen broad-leaved forest in southern Anhui, China. We measured the soil δ13CSOC contents and physicochemical properties under N (100 kg N·ha−1·a−1), N + P (100 kg N ha−1·a−1 + 50 kg P ha−1·a−1) additions, and the control (CK, no N and P additions). We also estimated the β value, which represents the soil organic carbon (SOC) turnover rate, from the slope of the regression between the log10-transformed SOC content and δ13CSOC in soil depth profiles. Our findings revealed that N addition significantly affected soil δ13CSOC compared to CK on both mid-slope and flat ridge sites. The β values responded differently to various treatments and sites. On the mid-slope, the β values did not show significant change with N and N + P additions. On the flat ridge, however, the β value decreased significantly in N and N + P additions, implying an increased SOC turnover rate. In addition, analysis of soil C–N–P stoichiometric ratios and physicochemical properties showed that N and N + P additions could affect β values by modifying soil nutrient content and composition. In general, our findings indicate that N and N + P additions could accelerate the SOC turnover in subtropical forest ecosystems, albeit with close dependence on site-specific factors.
Identification of Ecological Security Patterns for the Qiandongnan Ecotourism Area in Southwest China Using InVEST and Circuit Theory
Authors: Li Jiatong , Liu Yang , Gani Arni Abdul , Wu Jianli , Dai Yunchuan
Published: June 2023

The establishment of ecological security patterns (ESPs) represents a significant paradigm shift in the approach to sustainable development. ESPs aim to reconcile the typically conflicting interests of ecological conservation and economic growth by guaranteeing the sustainability of critical ecosystem services and preserving the ecological integrity of the region while promoting socio-economic development. The primary objective of ESPs is to achieve a balanced and harmonious relationship between human society and the natural environment. The Qiandongnan Ecotourism Area (QEA) located in Southwest China is renowned for its high biodiversity; however, the ecological environment in the region is highly fragile. In light of this, there is an urgent need to establish ESPs for QEA that can promote ecological protection and sustainable economic development. In this study, we used land-use and land-cover change data and human disturbance factors to identify the ESPs of the Qiandongnan Ecotourism Area (QEA), employing the InVEST model and Circuit Theory. Our results revealed that (1) the ecological quality of the study area is relatively high, with high-quality habitat areas covering 19,554.76 km2, which account for approximately 64.57% of the study area and the overall ecological environment is in a healthy condition; (2) the total area of ecological sources covers approximately 17,616.27 km2, accounting for approximately 58.17% of the study area, primarily distributed in Liping, Rongjiang, and Congjiang, which respectively account for 16.28%, 12.44%, and 11.86% of the total ecological source area; (3) the ESPs are composed of 13 key ecological nodes, 17 ecological corridors (with a length of approximately 1474.47 km), and 21 ecological source clusters. The ecological corridors are distributed in a ring shape, connecting various ecological nodes and sources along mountains, forests, rivers, and valleys. These findings provide a theoretical foundation for the protection of the ecological system’s integrity and the development of social and economic activities in the QEA.
Main Factors of Professional Experience on People’s Visual Behavior and Re-Viewing Intention in Different In-Forest Landscapes
Authors: Gao Yu , Wang Yalin , Zhang Weikang , Meng Huan , Zhang Zhi , Zhang Tong , Sun Xiaomei
Published: June 2023

Background: With the acceleration of urbanization, the demand for people to return to forests and their desire for nature is also increasing annually. However, whether the visual behaviors and aesthetic preferences of users vary with background attributes when viewing forest landscapes remains to be further explored. This information will help forest landscape planners and managers to create a forest landscape space suitable for different groups of people. Purpose: This study mainly discusses whether people’s professional background will affect their visual behavior, satisfaction preference and re-viewing intention of a landscape and discusses the relationship among them. Main results: (1) Under the background of an in-forest landscape, the visual behavior of users in different layouts presents great similarity. (2) Satisfaction preference for landscapes is not significantly influenced by the user’s background, but there is a significant linear relationship between satisfaction preference and re-viewing intention (Adj. R2 = 0.412 − 0.697, sig. = 0.000). (3) The spatial cognition that affects users’ visual behavior and satisfaction preference in a scene will change with the landscape layout and users’ professional background. Therefore, we suggest that landscape planners and managers should consider not only the spatial layout of the landscape itself but also the user’s own attributes (whether they have professional knowledge of the landscape) when optimizing the visual behavior and satisfaction preference of in-forest landscape space. This will ensure that users have a high sense of identity and attachment to the scene in a targeted way, thus arousing a greater “desire” to re-view the scene. In addition, our results can identify a more satisfactory course for tour routes according to the user’s professional background, thus enhancing the rate of tourists who decide to “visit again”.