bluuebunny/crossref_metadata_2025 huggingface dataset:
Movie Special Effects Processing Based on Computer Imaging Technology
Authors: Cheng Yidong , Wang Yi
Published: January 2022

The film space is the image of social life represented on the screen, which determines that the form of the film and television picture is a plane model, and it can only use a two-dimensional plane space to express an objective scene with a three-dimensional space. In order to improve the effects of special effects processing in movies, this paper applies computer imaging technology to the processing of movie characteristics. When performing specific scene simulations, the specific structure of each computer imaging particle system is derived on the basis of the general structure of the computer imaging particle system. In addition, this paper combines the improved algorithm to carry out several case analyses, and the reliability of this method is verified through simulation experiments, which promotes the application and promotion of computer imaging technology in movie special effects processing.
Leber’s Hereditary Optic Neuropathy Plus Causing Recurrent Myelopathy due to an MT-DN1 Mutation at G3635A
Authors: Lackey Elijah , Lefland Ariel , Eckstein Christopher
Published: January 2022

A 51-year-old man with known Leber’s hereditary optic neuropathy (LHON) presented with worsening lower extremity weakness and numbness. Following an episode of myelopathy two years before, he had been ambulating with a walker but over two weeks became wheelchair bound. He also developed a sensory level below the T4 dermatome to light touch, pinprick, and vibration. MRI of his cervical and thoracic spine showed a nonenhancing T2 hyperintense lesion extending from C2 to T12. At his presentation two years earlier, he was found to have a longitudinally extensive myelopathy attributed to his LHON. Genetic testing revealed a 3635 guanine to adenine mutation. MRI at that presentation demonstrated a C1-T10 lesion involving the central and posterior cord but, unlike the new lesion, did not involve the ventral and lateral horns. Given the similarity to his prior presentation and a negative evaluation for alternative etiologies, he was thought to have recurrent myelopathy secondary to Leber’s Plus. To our knowledge, recurrent myelopathy due specifically to the G3635A mutation in Leber’s Plus has not been reported previously.
A Novel Diabetes Healthcare Disease Prediction Framework Using Machine Learning Techniques
Authors: Krishnamoorthi Raja , Joshi Shubham , Almarzouki Hatim Z. , Shukla Piyush Kumar , Rizwan Ali , Kalpana C. , Tiwari Basant
Published: January 2022

Diabetes is a chronic disease that continues to be a significant and global concern since it affects the entire population’s health. It is a metabolic disorder that leads to high blood sugar levels and many other problems such as stroke, kidney failure, and heart and nerve problems. Several researchers have attempted to construct an accurate diabetes prediction model over the years. However, this subject still faces significant open research issues due to a lack of appropriate data sets and prediction approaches, which pushes researchers to use big data analytics and machine learning (ML)-based methods. Applying four different machine learning methods, the research tries to overcome the problems and investigate healthcare predictive analytics. The study’s primary goal was to see how big data analytics and machine learning-based techniques may be used in diabetes. The examination of the results shows that the suggested ML-based framework may achieve a score of 86. Health experts and other stakeholders are working to develop categorization models that will aid in the prediction of diabetes and the formulation of preventative initiatives. The authors perform a review of the literature on machine models and suggest an intelligent framework for diabetes prediction based on their findings. Machine learning models are critically examined, and an intelligent machine learning-based architecture for diabetes prediction is proposed and evaluated by the authors. In this study, the authors utilize our framework to develop and assess decision tree (DT)-based random forest (RF) and support vector machine (SVM) learning models for diabetes prediction, which are the most widely used techniques in the literature at the time of writing. It is proposed in this study that a unique intelligent diabetes mellitus prediction framework (IDMPF) is developed using machine learning. According to the framework, it was developed after conducting a rigorous review of existing prediction models in the literature and examining their applicability to diabetes. Using the framework, the authors describe the training procedures, model assessment strategies, and issues associated with diabetes prediction, as well as solutions they provide. The findings of this study may be utilized by health professionals, stakeholders, students, and researchers who are involved in diabetes prediction research and development. The proposed work gives 83% accuracy with the minimum error rate.
Pragmatic Applications and Universality of DNA Barcoding for Substantial Organisms at Species Level: A Review to Explore a Way Forward
Authors: Ahmed Sarfraz , Ibrahim Muhammad , Nantasenamat Chanin , Nisar Muhammad Farrukh , Malik Aijaz Ahmad , Waheed Rashem , Ahmed Muhammad Z. , Ojha Suvash Chandra , Alam Mohammad Khursheed
Published: January 2022

DNA barcodes are regarded as hereditary succession codes that serve as a recognition marker to address several queries relating to the identification, classification, community ecology, and evolution of certain functional traits in organisms. The mitochondrial cytochrome c oxidase 1 (CO1) gene as a DNA barcode is highly efficient for discriminating vertebrate and invertebrate animal species. Similarly, different specific markers are used for other organisms, including ribulose bisphosphate carboxylase (rbcL), maturase kinase (matK), transfer RNA‐H and photosystem II D1‐ApbsArabidopsis thaliana (trnH‐psbA), and internal transcribed spacer (ITS) for plant species; 16S ribosomal RNA (16S rRNA), elongation factor Tu gene (Tuf gene), and chaperonin for bacterial strains; and nuclear ITS for fungal strains. Nevertheless, the taxon coverage of reference sequences is far from complete for genus or species‐level identification. Applying the next‐generation sequencing approach to the parallel acquisition of DNA barcode sequences could greatly expand the potential for library preparation or accurate identification in biodiversity research. Overall, this review articulates on the DNA barcoding technology as applied to different organisms, its universality, applicability, and innovative approach to handling DNA‐based species identification.
Hand Gesture of Recognition Pattern Analysis by Image Treatment Techniques
Authors: Alhamazani Khalid Twarish , Alshudukhi Jalawi , Aljaloud Saud , Abebaw Solomon
Published: January 2022

The goal of this project is to write a program in the C++ language that can recognize motions made by a subject in front of a camera. To do this, in the first place, a sequence of distance images has been obtained using a depth camera. Later, these images are processed through a series of blocks into which the program has been divided; each of them will yield a numerical or logical result, which will be used later by the following blocks. The blocks into which the program has been divided are three; the first detects the subject’s hands, the second detects if there has been movement (and therefore a gesture has been made), and the last detects the type of gesture that has been made accomplished. On the other hand, it intends to present to the reader three unique techniques for acquiring 3D images: stereovision, structured light, and flight time, in addition to exposing some of the most used techniques in image processing, such as morphology and segmentation.
Back-Propagation Neural Network and ARIMA Algorithm for GDP Trend Analysis
Authors: Hua Siqi
Published: January 2022

GDP (gross domestic product) is a key indicator for assessing a country’s or region’s macroeconomic situation, as well as a foundation for the government to develop economic development strategies and macroeconomic policies. Currently, the majority of methods for forecasting GDP are linear methods, which only take into account the linear factors that affect GDP. GDP (gross domestic product) is widely regarded as the most accurate indicator of a country’s economic health. GDP not only reflects a country’s economic development over time but can also reflect its national strength and wealth. As a result, the GDP trend forecast partially reflects China’s transformation and future development. The time series ARIMA (Autoregressive Integrated Moving Average) model and the BPNN (BP neural network) model are combined in this article to create the ARIMA-BPNN fusion prediction model. The predicted values of the two models were then weighted averaged to obtain the predicted values of the linear part of the improved fusion model. To get the predicted values of the improved fusion model, we weighted average the residual parts of the two models, predict the nonlinear residual with BPNN, and add the predicted values of the two parts. It is applied to the actual GDP forecast in H province from 2019 to 2022, and the actual forecast verifies the effectiveness of the fusion forecast model in the actual forecast.
An Empirical Study on the Segmentation of Potential Users of Shared Parking Spaces considering Individual Heterogeneity
Authors: Wang Ange , Guan Hongzhi , Guo Jun , Han Yan , Bian Hangjin
Published: January 2022

Shared parking has become the most effective way to utilize existing parking resources. Little attention has been focused on drivers’ intention to use shared parking spaces in residential areas considering individual heterogeneity. To fill this gap, this paper explores the influencing factors and mechanism of shared parking use intention (SPUI) and further studies the preferences for the shared parking of different types of drivers. Firstly, based on the extended unified theory of acceptance and use of technology that includes psychological factors, personal attributes, and travel characteristics, the multiple indicator multiple cause (MIMIC) model was employed for parameter estimation and model assessment. Secondly, using MIMIC’s output results as input variables, the segmentation method of the latent class model (LCM) was adopted to explore drivers’ preferences regarding SPUI. Finally, a quantitative study was carried out through questionnaire data. The empirical results show that: (a) the extended unified theory of acceptance and use of technology has good explanatory power for SPUI. SPUI is directly affected by perceived risk (PR), behavioral habit (BH), social influence (SI), facilitating conditions (FCs), and effort expectancy (EE), while performance expectancy (PE) have no significant effect on SPUI. In addition, some factors of personal attributes and travel characteristics affect SPUI through psychological factors. (b) According to individual heterogeneity, the surveyed driver groups are divided into four segments: sensitive type (36%), conservative type (29.6%), neutral type (24.5%), and approved type (9.9%), respectively. There are significant differences in psychological observation variables such as EE, PE, FC, and SI among the four segments of drivers. According to the influence mechanism of psychological factors and preferences analysis of different types of drivers, the shared parking promotion strategy can be formulated from the aspects of management, operation, and technology.
Research on the Impact of Technological Finance on Financial Stability: Based on the Perspective of High‐Quality Economic Growth
Authors: Shen Lu , He Guohua , Yan Huan
Published: January 2022

This paper investigates the relationship between technological finance, high‐quality economic growth, and financial stability. Based on data of 30 provinces (including autonomous regions and municipalities) collected between 2004 and 2017, this paper adopts the method of factor analysis to construct comprehensive indexes of technological finance and financial stability before calculating green total factor productivity as the index of high‐quality development, using the CRS Multiplicative Model. Then it constructs the spatial SAC model and PVAR model for analyses of the just‐mentioned relationship based on the total sample of the nation and regional samples in eastern, middle, and western China, respectively. The results reveal that (1) All samples, whether the total national samples or regional samples of eastern, middle, and western China demonstrate the positive influence of technological finance on high‐quality economic development, with an obvious spatial spillover effect. The impact factor is the highest in the eastern region, while the western region holds the lowest factor among the three. (2) Judging by the general national sample, technological finance has an obvious negative shock effect on financial stability within a short period, but the effect gradually dwindles as time goes by. This rule applies to the sample of the eastern region, as its technological finance poses a short‐time negative shock effect on financial stability, before gradually diminishing to 0. Neither western nor middle regions have displayed an obvious shock impact on financial stability.
Brand Awareness via Online Media: An Evidence Using Instagram Medium with Statistical Analysis
Authors: Yantian Mi , Ahmad Zubair , Alkhairy Ibrahim , Alsuhabi Hassan , Alizadeh Morad , Mouhamed M. R.
Published: January 2022

Online marketing refers to the practices of promoting a company’s brand to its potential customers. It helps the companies to find new venues and trade worldwide. Numerous online media such as Facebook, YouTube, Twitter, and Instagram are available for marketing to promote and sell a company’s product. However, in this study, we use Instagram as a marketing medium to see its impact on sales. To carry out the computational process, the approach of linear regression modeling is adopted. Certain statistical tests are implemented to check the significance of Instagram as a marketing tool. Furthermore, a new statistical model, namely a new generalized inverse Weibull distribution, is introduced. This model is obtained using the inverse Weibull model with the new generalized family approach. Certain mathematical properties of the new generalized inverse Weibull model such as moments, order statistics, and incomplete moments are derived. A complete mathematical treatment of the heavy-tailed characteristics of the new generalized inverse Weibull distribution is also provided. Different estimation methods are discussed to obtain the estimators of the new model. Finally, the applicability of the new generalized inverse Weibull model is established via analyzing Instagram advertising data. The comparison of the new distribution is made with two other models. Based on seven analytical tools, it is observed that the new distribution is a better model to deal with data in the business, finance, and management sectors.
Modeling and Analysis of the Impact of Big Data on the Development of Education Network
Authors: Yang Qin
Published: January 2022

The arrival of the big data era not only provides corresponding technical support for the development of Educational Networking but also promotes the acceleration of Educational Networking. Therefore, this paper puts forward the research on the impact of big data on the development of education network and constructs a Bayesian knowledge tracking model to collect and analyze the behavior data of teachers and learners in network education. The experimental results show that big data technology provides greater development space for Education Networking. Its market scale has reached 502.47 billion yuan in 2021, and there is a trend of continuous growth. At the same time, the increase in the number of users also makes its teaching content richer and teaching methods more diversified and personalized. And, through the analysis of relevant data, learners and teachers can more comprehensively and truly understand their own level, achieve the purpose of accurate assistance to learners and teachers, and help learners and teachers find their own problems and make targeted adjustments. In addition, the campus intelligent management system based on big data technology can achieve the purpose of multipurpose and information management.
The Effect of Improving Preoperative Sleep Quality on Perioperative Pain by Zolpidem in Patients Undergoing Laparoscopic Colorectal Surgery: A Prospective, Randomized Study
Authors: Xiao Zhennan , Long Bo , Zhao Zeji
Published: January 2022

Background and Objectives. Opioids are essential in pain management after laparoscopic colorectal surgery while large dose may induce constipation and pneumonia. Ample evidence has demonstrated that postoperative analgesia can improve sleep quality. But the effects of improvement in sleep quality on postoperative pain have yet to be determined. The aim of this study was to investigate the effect of improving preoperative sleep quality by zolpidem on intraoperative analgesia and postoperative pain. Methods. A prospective, randomized study was conducted with 88 patients undergoing laparoscopic colorectal surgery. The experimental group (S group, n = 44) was given 10 mg of zolpidem tartrate one night before the surgical procedure, while no medication was given to the control group (C group, n = 44). The primary outcome was the intraoperative remifentanil consumption. Sufentanil consumption, average patient-controlled analgesia (PCA) effective press times, the visual analog scale (VAS) scores, and incidences of postoperative nausea and vomiting (PONV) were recorded at 6 h (T1), 12 h (T2), and 24 h (T3) postoperatively. Results. The intraoperative remifentanil consumption was significantly lower in the S group than that in the C group (

p
<
0.01

). Sufentanil consumption at 6 h and 12 h postoperatively was significantly lower in the S group than that in the C group (

p
<
0.05

); average PCA effective press times and VAS scores, at 6 h and 12 h postoperatively, were significantly lower in the S group than those in the C group (

p
<
0.01

); differences between groups 24 h postoperatively were not significant. No significant between-group difference was noted in the incidence of nausea and vomiting. Conclusion. Improving patients’ sleep quality the night before surgical procedure by zolpidem can decrease the usage of intraoperative analgesics and reduce postoperative pain.
Applying Knowledge Graph to Analyze the Historical Landscape Based on CiteSpace
Authors: Teng Youping , Huang Yue , Yang Shuai
Published: January 2022

The theory of “urban historical landscape” is gradually emerging in cultural heritage protection and urban planning in recent years. It was first proposed and promoted by UNESCO. In this study, the identification and evaluation are taken as the prerequisite for the protection and management of historical landscape. This paper uses CiteSpace to analyze the map of knowledge data to collect and sort out the global research status of urban historical landscape. In addition, the clustering function of knowledge graph software VOSviewer is used to analyze the knowledge clustering in the research field of urban historical landscape, and the research process and interdisciplinary development of urban historical landscape are obtained, to make some guiding suggestions for the future study of urban historical landscape. The results show that the study of urban historical landscape has experienced three stages. The early stage is the introduction and tracing stage, the middle stage is the diversification and enrichment stage, and the recent stage is the practice and construction stage. At present, it has become a multidisciplinary and multiperspective international research. The in-depth study of urban historical landscape undoubtedly opens a door for the traditional thought of urban heritage protection. At the same time, it gradually turned to more active management of urban historical landscape and also promoted the intersection of city, architecture, landscape architecture, anthropology, sociology, economics, and other disciplines from the side, with far-reaching influence. Reviewing and looking forward to studying urban historical landscape is more conducive to sustainable construction of the future. CiteSpace, as an excellent bibliometrics software, can help researchers sort out and display past research tracks in a novel visual way, to conduct future research better.
Oxidative Stress Aggravates Apoptosis of Nucleus Pulposus Cells through m6A Modification of MAT2A Pre-mRNA by METTL16
Authors: Chen Peng-Bo , Shi Gui-Xun , Liu Tao , Li Bo , Jiang Sheng-Dan , Zheng Xin-Feng , Jiang Lei-Sheng
Published: January 2022

The process of intervertebral disc degeneration (IVDD) is complex, and its mechanism is considered multifactorial. Apoptosis of oxidative stressed nucleus pulposus cells (NPCs) should be a fundamental element in the pathogenesis of IVDD. In our pilot study, we found that the expression of MAT2A decreased, and METTL16 increased in the degenerative nucleus pulposus tissues. Previous studies have shown that the balance of splicing, maturation, and degradation of MAT2A pre-mRNA is regulated by METTL16 m6A modification. In the current study, we aimed to figure out whether this mechanism was involved in the aberrant apoptosis of NPCs and IVDD. Human NPCs were isolated and cultured under oxidative stress. An IVDD animal model was established. It showed that significantly higher METTL16 expression and lower MAT2A expression were seen in either the NPCs under oxidative stress or the degenerative discs of the animal model. MAT2A was inhibited with siRNA in vitro or cycloleucine in vivo. METTL16 was overexpressed with lentivirus in vitro or in vivo. Downregulation of MAT2A or upregulation of METTL16 aggravated nucleus pulposus cell apoptosis and disc disorganization. The balance of splicing, maturation, and degradation of MAT2A pre-mRNA was significantly inclined to degradation in the NPCs with the overexpression of METTL16. Increased apoptosis of NPCs under oxidative stress could be rescued by reducing the expression of METTL16 using siRNA with more maturation of MAT2A pre-mRNA. Collectively, oxidative stress aggravates apoptosis of NPCs through disrupting the balance of splicing, maturation, and degradation of MAT2A pre-mRNA, which is m6A modified by METTL16.
(–)-Epicatechin Alters Reactive Oxygen and Nitrogen Species Production Independent of Mitochondrial Respiration in Human Vascular Endothelial Cells
Authors: Sadler Daniel G. , Barlow Jonathan , Draijer Richard , Jones Helen , Thijssen Dick H. J. , Stewart Claire E.
Published: January 2022

Introduction. Vascular endothelial dysfunction is characterised by lowered nitric oxide (NO) bioavailability, which may be explained by increased production of reactive oxygen species (ROS), mitochondrial dysfunction, and altered cell signalling. (-)-Epicatechin (EPI) has proven effective in the context of vascular endothelial dysfunction, but the underlying mechanisms associated with EPI’s effects remain unclear. Objective(s). Our aim was to investigate whether EPI impacts reactive oxygen and nitrogen species (RONS) production and mitochondrial function of human vascular endothelial cells (HUVECs). We hypothesised that EPI would attenuate ROS production, increase NO bioavailability, and enhance indices of mitochondrial function. Methods. HUVECs were treated with EPI (0-20 μM) for up to 48 h. Mitochondrial and cellular ROS were measured in the absence and presence of antimycin A (AA), an inhibitor of the mitochondrial electron transport protein complex III, favouring ROS production. Genes associated with mitochondrial remodelling and the antioxidant response were quantified by RT-qPCR. Mitochondrial bioenergetics were assessed by respirometry and signalling responses determined by western blotting. Results. Mitochondrial superoxide production without AA was increased 32% and decreased 53% after 5 and 10 μM EPI treatment vs. CTRL (

P
<
0.001

). With AA, only 10 μM EPI increased mitochondrial superoxide production vs. CTRL (25%,

P
<
0.001

). NO bioavailability was increased by 45% with 10 μM EPI vs. CTRL (

P
=
0.010

). However, EPI did not impact mitochondrial respiration. NRF2 mRNA expression was increased 1.5- and 1.6-fold with 5 and 10 μM EPI over 48 h vs. CTRL (

P
=
0.015

and

P
=
0.001

, respectively). Finally, EPI transiently enhanced ERK1/2 phosphorylation (2.9 and 3.2-fold over 15 min and 1 h vs. 0 h, respectively;

P
=
0.035

and

P
=
0.011

). Conclusion(s). EPI dose-dependently alters RONS production of HUVECs but does not impact mitochondrial respiration. The induction of NRF2 mRNA expression with EPI might relate to enhanced ERK1/2 signalling, rather than RONS production. In humans, EPI may improve vascular endothelial dysfunction via alteration of RONS and activation of cell signalling.
Diagnosis of Peripheral Facial Palsy Associated with Parvovirus B19 Infection by Polymerase Chain Reaction
Authors: Fukuta Taro , Kawano Yoshihiko , Ikeda Maiko , Kawada Jun-ichi , Ito Yoshinori , Hara Shinya
Published: January 2022

Human parvovirus B19 (PVB19) infection causes neurological manifestations, including encephalitis, meningitis, and neuropathy, but facial nerve palsy is rare. Moreover, no case of facial nerve palsy related to PVB19 infection that was diagnosed by PCR and serology has been reported. A 19-month-old boy without the medical history developed facial nerve palsy and was treated with prednisolone and valacyclovir. On the 19th day, erythema appeared on his body, and the PVB19-specific IgM and PVB19 DNA were detected in the serum, leading to the diagnosis of infectious erythema associated with PVB19 infection. This case indicates that PVB19 may be one of the causative agents of facial nerve palsy.
Serum Cytokine Alterations Associated with Age of Patients with Nephropathia Epidemica
Authors: Shakirova Venera , Khaertynova Ilseyar , Markelova Maria , Tarlinton Rachael , Behnke Jerzy , Martynova Ekaterina , Garanina Ekaterina , Rizvanov Albert , Khaiboullina Svetlana
Published: January 2022

Nephropathia epidemica (NE) is a zoonotic disease caused by hantaviruses transmitted from rodents, endemic in the Republic of Tatarstan, Russia. The disease presents clinically with mild, moderate, and severe forms, and time‐dependent febrile, oliguric, and polyuric stages of the disease are also recognized. The patient’s cytokine responses have been suggested to play a central role in disease pathogenesis; however, little is known about the different patterns of cytokine expression in NE in cohorts of different ages and sexes. Serum samples and clinical records were collected from 139 patients and 57 controls (healthy donors) and were used to analyze 48 analytes with the Bio‐Plex multiplex magnetic bead‐based antibody detection kits. Principal component analysis of 137 patient and 55 controls (for which there was full data) identified two components that individually accounted for >15% of the total variance in results and together for 38% of the total variance. PC1 represented a proinflammatory TH17/TH2 cell antiviral cytokine profile and PC2 a more antiviral cytokine profile with patients tending to display one or the other of these. Severity of disease and stage of illness did not show any correlation with PC1 profiles; however, significant differences were seen in patients with high PC1 profiles vs. lower for a number of individual clinical parameters: High PC1 patients showed a reduced number of febrile days, but higher maximum urine output, higher creatinine levels, and lower platelet levels. Overall, the results of this study point towards a stronger proinflammatory profile occurring in younger NE patients, this being associated with markers of acute kidney injury and low levels of high‐density cholesterol. This is consistent with previous work indicating that the pathology of NE is immune driven, with an inflammatory immune response being associated with disease and that this immune response is more extreme in younger patients.
A Cognitive Diagnosis Method in Adaptive Learning System Based on Preconceptions
Authors: Wang Jue , Liang Kaihua
Published: January 2022

One advantage of an adaptive learning system is the ability to personalize learning to the needs of individual users. Realizing this personalization requires first a precise diagnosis of individual users’ relevant attributes and characteristics and the provision of adaptability-enabling resources and pathways for feedback. In this paper, a preconcept system is constructed to diagnose users' cognitive status of specific learning content, including learning progress, specific preconcept viewpoint, preconcept source, and learning disability. The “Force and Movement” topic from junior high school physics is used as a case study to describe the method for constructing a preconception system. Based on the preconception system, a method and application process for diagnosing user cognition is introduced. This diagnosis method is used in three ways: firstly, as a diagnostic dimension for an adaptive learning system, improving the ability of highly-adaptive learning systems to support learning activities, such as through visualization of the cognition states of students; secondly, for an attribution analysis of preconceptions to provide a basis for adaptive learning organizations; and finally, for predicting the obstacles users may face in the learning process, in order to provide a basis for adaptive learning pathways.
Polydopamine Induced Wettability Switching of Cellulose Nanofibers/n-Dodecanethiol Composite Aerogels
Authors: Gao Runan , Shang Ying , Jiao Peng , Jiao Yue , Li Jian , Lu Yun
Published: January 2022

The novel wettability switchable cellulose nanofiber- (CNF-) based aerogel was conveniently prepared by polydopamine mediated composition of CNF and n-dodecanethiol. The wettability of aerogels can be controlled by adjusting the PDA and n-dodecanethiol loading content, which leads to a variation of water contact angle from 0-149°. The PDA was coated on cellulose nanofibers via hydrogen bonds and then n-dodecanethiol was anchored onto the scaffolds by Michael addition reaction, which was revealed by XPS and FTIR spectra. The composite aerogel can selectively absorb a series of oily liquids from the oil/water mixture, with the maximum absorption capacity of 68 g/g. This work presented a facile strategy to prepare wettability switchable CNF-based heterogenous aerogel and exhibited the potential of the composite aerogel for oil/water separation.
Bracket Failure in Orthodontic Patients: The Incidence and the Influence of Different Factors
Authors: Khan Haris , Mheissen Samer , Iqbal Ayesha , Jafri Ali Raza , Alam Mohammad Khursheed
Published: January 2022

Failure of brackets is a common problem in orthodontics. This affects the treatment time, cost, and compliance of the patient. This study was conducted to estimate the bracket failure rate and the related factors for the long term. Methodology. This ambidirectional cohort study included 150 nonsyndromic orthodontic patients undergoing fixed appliance therapy for the last two years. The same patients were followed for 7 months. Different variables related to bracket failure were evaluated. The available data were analyzed descriptively, and the Kaplan‐Meier estimate was used to measure the bracket survival rate from the date of bonding to failure. Results. A total of 180 bracket bond failures in the 150 included patients (52.2% males and 47.8% females) with a median age of 17 years (range 10‐25 years). 69% of brackets failures were reported within the first 6 months after bonding. About 58.3% of bracket failure was noticed in adolescent patients before the age of 18 years. The majority of the cohort (81.1%) has good oral hygiene. The failure rate in patients with normal overbite was 41.1%, in decreased overbite cases was 15%, while in deep bite cases the failure rate was 43.9% with a statistically significant difference. Adults show less bracket failure (41.7%) than adolescent patients (58.3%). More bracket failure was noted in the lower arch (55%) than the upper arch (45%), and there were more bond failures posteriorly (61%) than on the anterior teeth (39%). Majority (41.1%) of the bracket failed on round NiTi wires. Conclusion. The bracket failure rate was 6.4%, with most bracket failure occurring in the first 6 months after bonding with individual difference. There was more incidence of bond failure in an increased overbite, adolescents, lower arch, posterior teeth, and lighter alignment wires.
The Inhibitory Effects of Naringin in a Rat Model of Postoperative Intraperitoneal Adhesion Formation
Authors: Shi Xiaoqiang , Wu Yunhua , Li Enmeng , Zhang Li , Ma Yanfei , Wei Guangbing , Li Xuqi , Wang Shufeng
Published: January 2022

Background. Many attempts have been made to inhibit the formation of postoperative intraperitoneal adhesions, but the results have been discouraging. Therefore, the identification of effective preventative measures or treatments is of great importance. In this study, the substantial potential of naringin (NG) to reduce peritoneal adhesions was validated in a rat model. Materials and Methods. A rat peritoneal adhesion model was established by abrasion of the cecum and its opposite intraperitoneal region under aseptic surgical conditions. After the operation, three groups of NG-treated rats were given 2 mL of NG by gavage at different concentrations (40, 60, or 80 mg/kg/d). The sham, control, and hyaluronan (HA) groups were given equal volumes of normal saline daily. On the 8th day, all rats were sacrificed 30 min after the administration of an activated carbon solution (10 mL/kg) by oral gavage. Intraperitoneal adhesion formation was adequately evaluated by necropsy, hematoxylin and eosin (HE) staining, Sirius red staining, immunofluorescence staining, enzyme-linked immunosorbent assays, and reactive oxygen species (ROS) probes. The gastrointestinal dynamics of the rats were assessed on the basis of a small intestinal charcoal powder propulsion test and the detection of motilin and gastrin levels in serum. Results. Intraperitoneal adhesions were markedly reduced in the group of rats receiving high-dose NG. Compared with the control group, the high-dose NG group showed clear reductions in inflammatory reactions, oxidative stress, collagen deposition, and fibroblast formation in the adhesion tissue and enhanced gastrointestinal dynamics (

P

 < 0.05). Conclusion. NG alleviated the severity of intraperitoneal adhesions in a rat model by reducing inflammation, oxidative stress, collagen deposition, and fibroblast formation, highlighting the potential of NG as a drug candidate to prevent postoperative peritoneal adhesion formation.
Algorithmic Study on Position and Movement Method of Badminton Doubles
Authors: Xie Yu , Xie Xiaodong , Xia Huan , Zhao Zhe
Published: January 2022

The algorithms used by schedulers depend on the complexity of the schedule and constraints for each problem. The position and movement of badminton players in badminton doubles competition is one of the key factors to improve the athletes’ transition efficiency of offense and defense and the rate of winning matches and to save energy consumption. From the perspective of basic theory, the author conducts research on the position and movement of badminton doubles. Based on the numerical analysis method, the optimal model of standing position and direction composed of 7 nonlinear equations is established. In addition, the final of 10 matches of the super series of the world badminton federation in 2019 was selected as the sample of speed parameters. With the help of MATLAB mathematical analysis software, the numerical model established by the least square method was adopted to optimize the specific standing position and walking model. Ultimately, the optimal solution has been obtained, which can be represented on a plane graph. The optimal position of the attack station should be the blocking area (saddle-shaped area) and the hanging area (circular arc area in the middle). The optimal defensive positioning should be left defensive positioning area (left front triangle area) and right defensive positioning area (right front triangle area), which is consistent with our current experience and research results. The research results use mathematical tools to calculate the accurate optimal position in doubles matches, which has guiding significance to the choice of athletes’ position and walking position in actual combat and can also be used as a reference for training, providing a certain theoretical basis for the standing and walking of badminton doubles confrontation. The data collection and operation methods in this study can provide better calculation materials for artificial intelligence optimization and fuzzy operation of motion displacement, which is of great significance in the field of motion, simulation, and the call of parametric functions.
Management of Bladder Pain Syndrome (BPS): A Practical Guide
Authors: Juliebø-Jones Patrick , Hjelle Karin M. , Mohn Jannike , Gudbrandsdottir Gigja , Roth Ingunn , Chaudhry Adeel Asghar , Bergesen Anne Kvåle , Beisland Christian
Published: January 2022

Bladder pain syndrome (BPS) is a prevalent and pervasive disease. The physical and psychological sequelae can be very burdensome for the patient, and the condition represents a real challenge for the clinician as well. With no simple pathognomonic test, finding harmony in navigating patient care can be demanding. Diagnosis and management rely upon a multidisciplinary and holistic approach. Treatment options include conservative measures and pharmacotherapies as well as bladder instillation therapies. Ultimately, surgery may be offered but only in cases of refractory disease. This article offers a pragmatic guide for clinicians managing this challenging disease.
Autonomous Orbit Determination System of Navigation Satellite Based on Spaceborne GPS Technology
Authors: Yang Li , Ruan Haote , Zhang Yunhan
Published: January 2022

In recent years, many low-orbit satellites have been widely used in the field of scientific research and national defense in China. In order to meet the demand of high-precision satellite orbit in China’s space, surveying and mapping, and other related fields, navigation satellites are of great significance. The UKF (unscented Kalman filter) method is applied to space targets’ spaceborne GPS autonomous orbit determination. In this paper, the UKF algorithm based on UT transformation is mainly introduced. In view of the situation that the system noise variance matrix is unknown or the dynamic model is not accurate, an adaptive UKF filtering algorithm is proposed. Simulation experiments are carried out with CHAMP satellite GPS data, and the results show that the filtering accuracy and stability are improved, which proves the algorithm’s effectiveness. The experimental results show that the Helmert variance component estimation considering the dynamics model can solve the problem of reasonable weight determination of BDS/GPS observations and effectively weaken the influence of coarse error and improve the accuracy of orbit determination. The accuracy of autonomous orbit determination by spaceborne BDS/GPS is 1.19 m and 2.35 mm/s, respectively.
Production and Evaluation of Porous Photocatalyst Concrete Filter (deNOx PCF) for NOx Reduction
Authors: Park Jung Joon , Park Gi Joon , Kim Moon Kyung , Yeo Wooseok , Joo Jin Chul , Kim Jong Kyu
Published: January 2022

A porous photocatalyst concrete filter (deNOx PCF) is successfully manufactured to reduce NOx by mixing TiO2 photocatalyst with lightweight aerated concrete. From the results, 4% infusion rate of each foaming agent provided the smallest change of the height, and the optimal quality of the air bubbles can be produced by using foaming agent B with 4% of infusion rate. When 3% of TiO2 photocatalyst was mixed, less irregular and relatively homogeneous pores were formed on the surface with white color due to the proper amount of photocatalyst applied. For 3% of photocatalyst mixed with deNOx PCF, 1.03 μmol/hr of NO was reduced equivalent to 10.99% of NO reduction, suggesting that the TiO2 photocatalyst dispersed in the continuous and well‐developed pores inside the specimen successfully performed the removal of NO flowing through deNOx PCF using synergistic effects of adsorption and photodegradation reaction. Finally, the specimen of porous deNOx PCF for reducing NOx developed in this study can be applied to various construction sites and the air quality can be solved by reducing NOx contributing to the formation of fine particles.
Crack Detection Method of Sleeper Based on Cascade Convolutional Neural Network
Authors: Li Liming , Zheng Shubin , Wang Chenxi , Zhao Shuguang , Chai Xiaodong , Peng Lele , Tong Qianqian , Wang Ji
Published: January 2022

This work presents a new method for sleeper crack identification based on cascade convolutional neural network (CNN) to address the problem of low efficiency and poor accuracy in the traditional detection method of sleeper crack identification. The proposed algorithm mainly includes improved You Only Look Once version 3 (YOLOv3) and the crack recognition network, where the crack recognition network includes two modules, the crack encoder-decoder network (CEDNet) and the crack residual refinement network (CRRNet). The improved YOLOv3 network is used to identify and locate cracks on sleepers and segment them after the sleeper on the ballast bed is extracted by using the gray projection method. The sleeper is inputted into CEDNet for crack feature extraction to predict the coarse crack saliency map. The prediction graph is inputted into CRRNet to improve its edge information and local region to achieve optimization. The accuracy of the crack identification model is improved by using a mixed loss function of binary cross-entropy (BCE), structural similarity index measure (SSIM), and intersection over union (IOU). Results show that this method can accurately detect the sleeper crack image. During object detection, the proposed method is compared with YOLOv3 in terms of directly locating sleeper cracks. It has an accuracy of 96.3%, a recall rate of 91.2%, a mean average precision (mAP) of 91.5%, and frames per second (FPS) of 76.6/s. In the crack extraction part, the F-weighted is 0.831, mean absolute error (MAE) is 0.0157, and area under the curve (AUC) is 0.9453. The proposed method has better recognition, higher efficiency, and robustness compared with the other network models.
Regulatory Effects of Astragaloside IV on Hyperglycemia-Induced Mitophagy in Schwann Cells
Authors: Wei Xiaoyi , Zheng Yalin , Ai Yanke , Li Buman
Published: January 2022

Objective. This study aimed to observe the regulatory effects of astragaloside IV (AS-IV) on hyperglycemia-induced mitochondrial damage and mitophagy in Schwann cells and to provide references for clinical trials on AS-IV in the treatment of diabetic peripheral neuropathy. Methods. Schwann cells were grown in a high-glucose medium to construct an autophagy model; the cells were then treated with AS-IV and N-acetylcysteine (control) to observe the regulatory effects of AS-IV on oxidative stress and mitophagy. Results. AS-IV exhibited antioxidant activity and inhibited the overactivation of autophagy in Schwann cells, significantly reducing the level of reactive oxygen species and downregulating the expression of autophagy-related proteins (LC3, PINK, and Parkin) under hyperglycemic conditions, thereby exerting a protective effect on mitochondrial morphology and membrane potential. Conclusion. AS-IV can maintain the mitochondrial function of Schwann cells under hyperglycemic conditions by effectively alleviating oxidative stress and overactivation of mitophagy. The evidence from this study supports an AS-IV-based therapeutic strategy against diabetic peripheral neuropathy.
Circular RNA circFGFR1 Functions as an Oncogene in Glioblastoma Cells through Sponging to hsa-miR-224-5p
Authors: Zhang Qian , Chen Shan , Zhen Yingwei , Gao Peng , Zhang Zhenyu , Guo Hao , Wang Yong
Published: January 2022

Recently, increased studies have shown the important regulatory role of circular RNA (circRNA) in cancer progression and development, including glioblastoma (GBM). However, the function of circRNAs in glioblastoma is still largely unclear. Here, we state that circFGFR1 is elevated in glioma cells, resulting in aggravated glioma aggravated malignancy. The upregulation of circFGFR1 also promotes glioma growth in mouse xenograft models. Furthermore, CXCR4 level in glioma cells is positively correlated with circFGFR1 level, and higher CXCR4 expression is found in circFGFR1 overexpression groups. The effect of circFGFR1 on glioma malignancy is abolished in CXCR4 knockout cells. Then, RIP, RNA pull-down, and luciferase reporter assay results showed that hsa-miR-224-5p directly binds to circFGFR1 and CXCR4 mRNA. The CXCR4 3

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-untranslated region (UTR) activated luciferase activity was reduced with hsa-miR-224-5p transfection, while it is reversed when cotransfected with circFGFR1, indicating that circFGFR1 acts as a hsa-miR-244-5p sponge to increase CXCR4 expression. The hsa-miR-224-5p expression is negatively corrected with the glioma malignancy through inhibiting CXCR4 level. Besides, the circFGFR1-induced regulation in glioma malignancy is also abrogated in hsa-miR-224-5p knockout cells. Taken together, our findings suggest that circFGFR1 plays a critical role in the tumorigenic behaviors in glioma cells by upregulating CXCR4 expression via sponging to hsa-miR-224-5p. These findings provide a new perspective on circRNAs during GBM development.
Jumping Risk Communities in the Energy Industry: An Empirical Analysis Based on Time‐Varying Complex Networks
Authors: Wang Hui , Jiang Lili , Duan Hongjun , Wang Yifeng , Jiang Yichen , Zhang Xiaolei
Published: January 2022

This paper uses the 5‐five‐minute high‐frequency data of energy‐listed companies in China's A‐share market to extract the jump of energy stock prices and build a dynamic stock price jump complex network. Then, we analyze the clustering effect of the complex network. The research shows that the energy stock price jump is an important part of stock price volatility, and the complex network of energy stock jump risk has obvious time‐varying characteristics. However, the infection problem of stock price jump risks needs specific analysis. China's coal industry has an important influence on the development of China's energy industry. According to the clustering analysis results of the network community, the clustering effect of the network community has time‐varying characteristics. After October 2017, the clustering effect of the jumping risk of the coal industry and the new energy industry is obvious. The risk contagion within the new energy industry community is a key point for the development of the new energy industry.