bluuebunny/crossref_metadata_2025 huggingface dataset:
Paeoniflorin Ameliorates Hyperprolactinemia-Induced Inhibition of Osteoblastogenesis by Suppressing the NF-κB Signaling Pathway
Authors: Sun Xiaohong , Zhu Keda , Feng Chengcheng , Zhu Jie , Chen Shuangshuang , Tang Wenkai , Wang Zhifang , Xiao Long , Li Hong , Geng Dechun , Wang Zhirong
Published: April 2022

Hyperprolactinemia is a common endocrine disease in women of reproductive age. Research has shown that patients with hyperprolactinemia often have decreased bone mineral density and an increased risk of fractures. However, there is still a lack of effective treatments. Paeoniflorin, one of the primary bioactive components in peony, is widely used in traditional Chinese medicine. Research has shown that paeoniflorin promotes osteoblast differentiation. However, whether paeoniflorin plays a role in hyperprolactinemia-induced osteoblastogenesis inhibition is not yet clear. In this study, we investigated the effect of paeoniflorin on prolactin (PRL)-mediated inhibition of osteoblast function. Our results showed that prolactin significantly reduced the expression of alkaline phosphatase (ALP), Osterix, and runt-related transcription factor 2 (RUNX2) in MC3T3-E1 cells cultured in an osteoblast differentiation medium, suggesting that prolactin inhibited osteoblast function. After treatment with paeoniflorin (PF), the expression of these osteoblast markers was upregulated. In addition, our findings proved that paeoniflorin increased the absorbance values of ALP-positive cells and the areas of alizarin red S (ARS) deposition compared to those in the prolactin group, suggesting that paeoniflorin reversed the PRL-induced reduction in osteoblast differentiation. The PRL-induced activation of nuclear factor kappa B (NF-κB) was significantly reversed by paeoniflorin, indicating that paeoniflorin promoted osteoblast function by inhibiting the NF-κB signaling pathway. In summary, these results showed that paeoniflorin alleviated the inhibitory effect of prolactin on osteoblastogenesis by suppressing the NF-κB signaling pathway.
A Novel Efficient Data Gathering Algorithm for Disconnected Sensor Networks Based on Mobile Edge Computing
Authors: Sun Zeyu , Lan Lan , Zeng Cao , Liao Guisheng
Published: April 2022

Employing mobile elements is an efficient solution to the performance improvement of wireless sensor networks (WSNs). We propose an efficient data gathering mechanism for disconnected WSNs with rendezvous points (DGM-RPs). The mobile sink traverses the entire network and stops only at the rendezvous points (RPs) while gathers the data from sensors in every disconnected segment. In this paper, mobile sinks perform the task of edge computing and alleviate the load of upper cloud. We measure the shape of disconnected segments, layering them by use of the convex hull, and then design the travelling path of the mobile sink to minimize the travel latency to visit all disconnected segments. At least one RPs will be selected in a segment firstly, and then, on this basis, we consider the distribution density of sensor nodes and the location of the RPs already exist to adding new RPs, which make good use of the margin to reducing the energy consumption and prolong the network lifetime.
Improved Lossless Data Hiding for JPEG Images Based on Optimized VLC Mapping
Authors: Zheng Yang , He Junhui
Published: April 2022

Most reversible data hiding (RDH) schemes embed data into JPEG images through DCT coefficients modification, but they will cause unavoidable visual distortion in the marked images. Lossless data hiding (LDH) can not only restore the cover JPEG images in a lossless way after extraction of the embedded data but also generate marked images without any visual distortion. For LDH schemes based on variable length code (VLC) mapping, the performance depends mainly on the mapping mode. In this paper, a new LDH scheme for JPEG images based on optimized VLC mapping is proposed. First, for a given mapping mode, a mathematical model of file size change is established. Then, based on the Run/Size frequency of a cover image and the estimation of frequency change caused by simulated data embedding, an iterative method is used to find the optimal mapping mode that leads to the smallest file size increments. Lastly, data is embedded in the cover image using the optimal VLC mapping. Experimental results show that the proposed LDH scheme based on optimized VLC mapping can achieve small increase in the file size of marked images.
Construction and Analysis of lncRNA‐Associated ceRNA Network in Atherosclerotic Plaque Formation
Authors: Li Danyu , Ma Yunci , Deng Weiqian , Feng Jianhua
Published: April 2022

Atherosclerosis (AS) is a vascular disease with plaque formation. Unstable plaques can be expected to result in cardiovascular disease, such as myocardial infarction and stroke. Studies have verified that long noncoding RNAs (lncRNAs) play a critical role in atherosclerotic plaque formation (APF), including MALAT1, GAS5, and H19. A ceRNA network is a combination of these two interacting processes, which regulate the occurrence and progression of many diseases. However, lncRNA‐associated ceRNA network in terms of APF is limited. This study sought to discover novel potential biomarkers and ceRNA network for APF. We designed a triple network based on the lncRNA‐miRNA and mRNA‐miRNA pairs obtained from lncRNASNP and starBase. Differentially expressed genes (DEGs) and lncRNAs in human vascular tissues derived from the Gene Expression Omnibus database (GSE43292, GSE97210) were systematically selected and analyzed. A ceRNA network was constructed by hypergeometric test, including 8 lncRNAs, 243 miRNAs, and 8 mRNAs. APF‐related ceRNA structure was discovered for the first time by combining network analysis and statistical validation. Topological analysis determined the key lncRNAs with the highest centroid. GO and KEGG enrichment analysis indicated that the ceRNA network was primarily enriched in “regulation of platelet‐derived growth factor receptor signaling pathway,” “negative regulation of leukocyte chemotaxis,” and “axonal fasciculation.” A functional lncRNA, HAND2‐AS1, was identified in the ceRNA network, and the main miRNA (miRNA‐570‐3p) regulated by HAND2‐AS1 was further screened. This present study elucidated the important function of lncRNA in the origination and progression of APF and indicated the potential use of these hub nodes as diagnostic biomarkers and therapeutic targets.
An Optimization Method of Sports Service Network Layout Based on Network Communication
Authors: Qi Lu
Published: April 2022

Sports culture industry (CI), as a new sunrise industry, has achieved unprecedented development in the world, and many developed countries regard it as a pillar industry. In our country, the sports CI is quickly growing and contributing significantly to national economic growth. The layout mode of the sports CI is crucial in identifying regional growth advantages and resource development, as well as maximizing industrial function allocation and creating sports CI development strategy. This paper takes Dalian’s sports CI as the research object and expounds the concept of sports culture, sports CI, and spatial layout of sports CI through analyzing and sorting out previous research results. This study analyses the evolution and spatial distribution of the Dalian sports CI, as well as the current challenges, using theories and methodologies from sports science and economic geography and proposes countermeasures for Dalian to develop its sports CI. Regional development theories, such as central place theory, growth pole theory, point axis theory, and Maslow’s hierarchy of needs theory, have important theoretical value and practical guiding significance for the rationalization of spatial distribution of Dalian sports CI. On the basis of analyzing the resources, traffic network, and economic development of Dalian sports CI, the paper constructs the spatial distribution mode of Dalian sports CI, namely, two core points, three development axes, and multiple nodes, and puts forward the measures to optimize the spatial distribution of Dalian sports CI. This paper examines the current condition, resource architecture, and major structure of supply of leisure sports service items in the Zhejiang coastline area using the literature and field inquiry methodologies. On this basis, the optimization countermeasures of combining Zhejiang coastal leisure sports service products with recreational fishery and yacht economy are put forward to perfect the system of coastal leisure sports service products and improve the supply capacity.
Real-Time Twitter Spam Detection and Sentiment Analysis using Machine Learning and Deep Learning Techniques
Authors: Rodrigues Anisha P , Fernandes Roshan , A Aakash , B Abhishek , Shetty Adarsh , K Atul , Lakshmanna Kuruva , Shafi R. Mahammad
Published: April 2022

In this modern world, we are accustomed to a constant stream of data. Major social media sites like Twitter, Facebook, or Quora face a huge dilemma as a lot of these sites fall victim to spam accounts. These accounts are made to trap unsuspecting genuine users by making them click on malicious links or keep posting redundant posts by using bots. This can greatly impact the experiences that users have on these sites. A lot of time and research has gone into effective ways to detect these forms of spam. Performing sentiment analysis on these posts can help us in solving this problem effectively. The main purpose of this proposed work is to develop a system that can determine whether a tweet is “spam” or “ham” and evaluate the emotion of the tweet. The extracted features after preprocessing the tweets are classified using various classifiers, namely, decision tree, logistic regression, multinomial naïve Bayes, support vector machine, random forest, and Bernoulli naïve Bayes for spam detection. The stochastic gradient descent, support vector machine, logistic regression, random forest, naïve Bayes, and deep learning methods, namely, simple recurrent neural network (RNN) model, long short-term memory (LSTM) model, bidirectional long short-term memory (BiLSTM) model, and 1D convolutional neural network (CNN) model are used for sentiment analysis. The performance of each classifier is analyzed. The classification results showed that the features extracted from the tweets can be satisfactorily used to identify if a certain tweet is spam or not and create a learning model that will associate tweets with a particular sentiment.
Analysis of Multiple Vitamins Serum Levels and Disease-Related Factors in Children with Acute Leukemia
Authors: Song Zeliang , Li Juanjuan , Cao Jing , Zhang Lei , Zhang Zhaoxia , Feng Shunqiao , Zhong Dixiao , Yue Mei , Hu Mengze , Liu Rong
Published: April 2022

Objective. To explore the relationship between vitamins levels and disease-related indicators in children with acute leukemia (AL). Methods. A total of 107 hospitalized children with AL were enrolled in this study and assigned to one group in each of the following categories: infected group (n = 52) and noninfected group (n = 55); treatment remission group (n = 56) and nonremission group (n = 51); high-risk (HR) group (n = 44), intermediate risk (IR) group (n = 53), and slight risk (SR) group (n = 8); cyclophosphamide + cytosine arabinoside+6-mercaptopurine + pegaspargase group (CAML, n = 15); methotrexate group (MTX, n = 9); and vindesine + daunomycin + L-asparaginasum + prednisone (VALP, n = 38). Hematological and serological parameters, hepatic and renal function, and changes in vitamins A, B1, B2, B6, B9, B12, C, D, and E serum content in children with AL were analyzed to investigate their relationship with AL disease-related factors. Results. The vitamin D level was significantly higher in the noninfected group than in the infected group (

P
<
0.05

). Compared with the nonremission group, the level of vitamin B1 in the treatment remission group was significantly higher, while the levels of vitamin B6 and B12 were notably lower (

P
<
0.05

). The levels of vitamins B6 and B12 were notably different among the treatment groups. Multivariate analysis showed that hemoglobin (Hb) and C-reactive protein (CRP) were predisposing factors of AL in children. The disease type (acute lymphoblastic leukemia/acute myelogenous leukemia) was the factor affecting remission in AL children. Abnormal kidney function and the occurrence of icterus were the influencing factors for the risk degree in AL children. Platelet (PLT) count, activated partial thromboplastin time (APTT), neutrophils (N), and immunophenotype were shown to affect the choice of therapeutic regimens. Conclusion. There are notable vitamins imbalances in children with AL. The imbalances influence disease-related factors and therefore provide some references for the prognosis and treatment of AL.
Genome Editing: A Promising Approach for Achieving Abiotic Stress Tolerance in Plants
Authors: Kaur Navdeep , Sharma Shubham , Hasanuzzaman Mirza , Pati Pratap Kumar
Published: April 2022

The susceptibility of crop plants towards abiotic stresses is highly threatening to assure global food security as it results in almost 50% annual yield loss. To address this issue, several strategies like plant breeding and genetic engineering have been used by researchers from time to time. However, these approaches are not sufficient to ensure stress resilience due to the complexity associated with the inheritance of abiotic stress adaptive traits. Thus, researchers were prompted to develop novel techniques with high precision that can address the challenges connected to the previous strategies. Genome editing is the latest approach that is in the limelight for improving the stress tolerance of plants. It has revolutionized crop research due to its versatility and precision. The present review is an update on the different genome editing tools used for crop improvement so far and the various challenges associated with them. It also highlights the emerging potential of genome editing for developing abiotic stress-resilient crops.
Expression and Clinical Significance of lncRNA NEAT1 in Patients with Spinal Tuberculosis
Authors: Zheng Jianping , Wang Xiangxin , Shi Jiandang , Tian Jun , Chang Xiuqin , Wang Xiaoping , Ye Qiang
Published: April 2022

Background. Spinal tuberculosis (STB) often leads to irreversible neurological injury, resulting in serious social and economic problems. With the emergence of drug resistance, the management becomes even more challenging, given the treatment courses are generally longer for skeletal than pulmonary tuberculosis (PTB). The development and validation of nonsputum biomarkers for diagnosis and tailoring of treatment duration to enable personalized and evidence-based management of such diseases to improve treatment outcomes is being called for globally. Studies have demonstrated that lncRNA NEAT1 was highly expressed in pulmonary tuberculosis (TB) and was related to its progression and recovery. However, the expression and clinical significance of lncRNA NEAT1 in STB remains unclear. Methods. The relative expression of lncRNA NEAT1 was quantified by relative real-time reverse transcription PCR (RT-PCR). The prognostic value was assessed by receiver-operating characteristic (ROC) curve analysis. Pearson and Spearman correlation coefficient and chi-square test were used to analyze the correlation between the lncRNA NEAT1 expression and the clinical characteristics. Univariate and multivariate logistic regression analyses were used to analyze independent predictors of STB recurrence. Results. Compared with normal healthy individuals, the expression level of lncRNA NEAT1 in peripheral blood and granulomatous tissues of STB patients was significantly increased. The results of the in vitro Mycobacterium tuberculosis- (Mtb-) infected cell model showed that the expression level of lncRNA NEAT1 was significantly upregulated in macrophages infected with Mtb, and the difference was statistically significant compared with Mtb-uninfected group. The expression level of lncRNA NEAT1 in granulomatous tissue of STB was significantly higher than that in peripheral blood. The expression of lncRNA NEAT1 was related to segments of the lesions, paraspinal abscesses, anti-TB treatment, drug resistance, interleukin-6 (IL-6), C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR). Multivariate analysis results showed that relatively high expression of lncRNA NEAT1_1, the shorter transcript of the NEAT1 gene, was an independent prognostic factor of STB outcome. Conclusion. LncRNA NEAT1 was highly expressed in peripheral blood mononuclear cells (PBMCs) and granulomatous tissue from patients with STB, as well as in Mtb-infected THP-1 cell lines. LncRNA NEAT1 expression was significantly associated with clinical characteristics (paraspinal abscesses, segments of the lesions and anti-TB treatment, IL-6, CRP, and ESR) of patients in STB. Increased expression of lncRNA NEAT1_1 predicted good prognosis of STB and might become a prognostic biomarker for STB.
Underuse of Epinephrine for the Treatment of Anaphylaxis in the Prehospital Setting
Authors: Dami Fabrice , Enggist Roxane , Comte Denis , Pasquier Mathieu
Published: April 2022

Background. Anaphylaxis is a life-threatening reaction. Its key management is rapid diagnosis and prompt administration of intramuscular epinephrine. There are many barriers to epinephrine use. Objective. To assess the performance of dispatchers at suspecting anaphylaxis, proposing epinephrine treatment, helping find an epinephrine autoinjector (EAI) and using it. Methods. This is a retrospective study. Calls classified as “anaphylaxis” or “allergy” were included, and voice recordings were reviewed. Clinical, environmental, and operational variables were collected. Anaphylaxis was suspected if sudden dyspnoea, abdominal symptoms (vomiting, abdominal pain, or diarrhoea), dizziness, or loss of consciousness were present. Results. The dispatch handled 120,618 dispatch calls. Dispatchers suspected 611 (0.5%) cases of allergy. Among those, 437 (72%) were deemed consistent with anaphylaxis: 65 patients received epinephrine prior to the dispatcher’s advice, and dispatchers proposed the use of an EAI to 141 patients (38%). An EAI was available in 45 situations. The proposition was accepted on 18 cases and performed in 16 cases. The median time from the EAI being in hand and the injection was 50 seconds. Conclusions. Trained dispatchers are able to suspect anaphylaxis, decide when to treat and provide guidance on using an EAI, although their performance can be improved. There is a need for easier access to EAIs in public places.
Biogenic Synthesis of Magnetite Nanoparticles Using Leaf Extract of Thymus schimperi and Their Application for Monocomponent Removal of Chromium and Mercury Ions from Aqueous Solution
Authors: Geneti Sintayehu Tamenne , Mekonnen Gemechis Asfaw , Murthy H. C. Ananda , Mohammed Endale Tsegaye , Ravikumar C. R. , Gonfa Bedasa Abdisa , Sabir Fedlu Kedir
Published: April 2022

Currently, plant templated synthesis of magnetite iron oxide nanoparticles (Fe3O4 NPs) was emerged for multifunctional purposes. In this study, the leaf extract of the plant Thymus schimperi was utilized to synthesize Fe3O4 NPs. The synthesized NPs were characterized by using technical tools such as X‐ray diffraction (XRD) spectroscopy, Fourier transform infrared (FT‐IR) spectroscopy, scanning electron microscopy‐energy dispersive X‐ray (SEM‐EDX) analysis, and ultraviolet‐visible (UV‐Vis) spectroscopy, and thermal analysis (TGA‐DTA). The XRD result corroborated the presence of desired phase formation having pure cubic face centered phase structure with average crystallite particle size ranging from 20 nm to 30 nm. SEM micrographs confirmed microstructural homogeneities and remarkably different morphology of Fe3O4 NPs. Mercury (II) and chromium (VI) removal efficiencies of Fe3O4 NPs were found to be 90% and 86% from aqueous solution at initial concentration of 20 mg/L, respectively. Various factors which affect the metal ion removal efficiency such as metal ion initial concentrations, pH, contact time, and adsorbent dosage were also studied. The optimum pH and contact time for chromium ion adsorption were pH 5 and 60 min and that of mercury were observed to be pH 7 and 90 min, respectively. The Langmuir isotherm was best fitted for sorption of Hg(II) ion, and the Freundlich isotherm was best fitted with sorption of Cr(VI) ion onto the surface of Fe3O4 NPs. The mechanism of adsorption of both Hg(II) and Cr(VI) ions was obeyed pseudo 2nd order kinetics. The recorded percent removal efficiencies revealed that these Fe3O4 NPs synthesized through leaf extract of the plant called Thymus schimperi have demonstrated excellent potentiality in the remediation of heavy metal ions. The synthesized Fe3O4 NPs were regenerated (reused) for adsorptive removal of Hg(II) and Cr(VI) for five consecutive cycles without significant loss of removal efficiency. Fe3O4 NPs were reused with only 4.17% loss of removal efficiency against Hg(II) and only 3% loss of removal efficiency against Cr(VI) metal ions.
Structural and Vibrational Investigation of Benzil-(1,2-Diphenylethane-1,2-Dione): Experimental and Theoretical Studies
Authors: Kanagathara N. , Senthilkumar K. , Sabari V. , Ragavendran V. , Elangovan S.
Published: April 2022

Single crystals of benzil commonly known as 1,2-diphenylethane-1,2-dione are grown by the slow evaporation method at room temperature. Gaussian 09 program is applied for theoretical calculations with B3LYP/6-311++G(d,p) basis set. The structure is optimized, and the energy, structural parameters, vibrational frequencies, IR, and Raman intensities are determined. Complete natural bonding orbital (NBO) analysis is carried out to analyze the intramolecular electronic interactions and their stabilization energies. From the second-order perturbation theory analysis of the benzil molecule, it is observed that there exists a hyperconjugative intramolecular stabilization energy between 17.45 and 22.76 KJmol-1. HOMO-LUMO analysis has been performed to identify the charges transferred within the molecule. The energy gap is calculated to be 2.919 eV and thus establishes the soft nature of the molecule. The molecular electrostatic potential (MEP) of the grown crystal was analyzed using the B3LYP method with 6-311++G(d,p) basis set. First-order hyperpolarizability calculations reveal the nonlinear optical microscopic behavior of the benzil molecule with nonzero values. The total value of the first-order hyperpolarizability (βtot) is of the order of41.5246×10−31 esu, which is found to be 11.135 times that of urea. Hence, benzil can be referred to as a good material for nonlinear optical applications.
Modified Floyd–Warshall’s Algorithm for Maximum Connectivity in Wireless Sensor Networks under Uncertainty
Authors: Sahoo Laxminarayan , Sen Supriyan , Tiwary Kalishankar , Samanta Sovan , Senapati Tapan
Published: April 2022

The main objective of this paper is to find the duration of maximum time connectivity of sensor nodes under uncertainty utilizing the prespecified voltage/power of each sensor node. Wireless sensor networks (WSNs) are composed of nodes that transmit data between each other over routing. A variety of routing protocols and algorithms exist, each related to a particular set of conditions. There are a variety of routing algorithms available, some of which can be used in WSNs for routing. The goal of the fastest distance routing algorithms in a WSN is to use the least amount of energy possible. In a WSN, Dijkstra’s algorithm is typically used for shortest path routing. The Floyd–Warshall’s algorithm is used to compute the shortest paths between distinct nodes in a regular graph, but due to the absence of a communication mode, this algorithm is not ideal for routing in wireless networks. In this research work, we have considered a WSN to find out the maximum connectivity time utilizing optimum voltage. On the other hand, duration of connectivity and energy/voltage are two vital parameters that are difficult to manage. Because of limited resources and safety concerns, safety implementation is limited. Also, due to the irregular/hazardous environmental situations, the distance between sensor nodes and its voltage to link up the nodes are totally unpredictable. In this work, we employ triangular fuzzy numbers to express unpredictability. Then, utilizing defuzzification of fuzzy numbers, the associated WSN problem was transformed into a crisp one. The widely used signed distance approach has been applied for the defuzzification of fuzzy numbers in this case. To determine the best outcome and to illustrate the usefulness of the suggested technique, a numerical example has been solved using the modified Floyd–Warshall’s algorithm. Finally, concluding remarks on the proposed approach as well as future studies have been provided.
Analysis of Clinicopathological Factors Associated with Radiation-Induced Cystitis in Patients with Cervical Cancer
Authors: He Ling , Wang Zhenyu , Chen Jianhui , Chen Ling , Chen Peijuan , Cai Wenzhi
Published: April 2022

Objective. To analyze the clinicopathological characteristics associated with radiation-induced cystitis (RIC) in patients with cervical cancer treated with chemoradiotherapy (CRT) alone or postoperational (post-op) CRT. Methods. 107 patients with cervical cancer were retrospectively recruited into the study. The surgical status, FIGO staging, total and fractionated doses of radiotherapy (RT), and multiparameters including the dose, volume irradiated to the total bladder, and bladder wall were evaluated for RIC. The criteria on RIC were referred to CTCAE v5.0. Results. Surgical operation and post-op CRT were delivered in 65 patients and CRT or RT alone in 42 patients. Among those with post-op CRT, 33/34 (97.06%), 22/43 (51.16%), and 10/30 (33.33%) patients were classified as FIGO stage I, II, and III/IV, respectively. The incidence of RIC was 30.84% for the whole group with 87.87% occurred in stage I and II patients. The incidence of CTCAE grade 2 and beyond was significantly higher in patients treated with post-op CRT than those with CRT alone (13.85% vs 2.38%,

p

 = 0.043). Further analyses showed that the CTCAE level of RIC in the post-op CRT group was related to the relatively smaller average bladder volume (

p

 = 0.029), whereas the difference in volume of bladder and bladder wall irradiated to 35.0 Gy or 40.0 Gy was not statistically significant between patients with or without RIC. Conclusion. The combination of surgery and post-op CRT may increase the incidence and severity of radiation-induced cystitis when compared to CRT alone, suggesting that bladder dysfunction associated with surgical procedure might increase the frequency and severity radiation related bladder toxicity. Further study is merited.
Analysis of the Effect of Applying Ultrasound-Guided Nerve Block Anesthesia to Fracture Patients in the Context of Internet-Based Blockchain
Authors: Cai Qiang , Han Yi , Gao Meiling , Ni Shuqin
Published: April 2022

In the process of surgical treatment, the introduction of ultrasound technology to implement nerve block anesthesia can make the operations of patients with fractures under visualization and it can also significantly improve the anesthesia effect. With this technology, it is possible to minimize the anesthesia operation causing accidental injury and lay a good foundation for the smooth operation of surgical treatment. Blockchain technology is a new decentralized infrastructure and distributed computing paradigm. This technology has great development opportunities in the medical field and is expected to play an important role in the construction of Internet medical ecology. This study aims to investigate the effect of ultrasound-guided nerve block anesthesia on fracture treatment in the context of blockchain. This method has high application value and potential in medical data sharing, reducing treatment costs, improving the medical claims system, strengthening medical management, and optimizing medical decision-making using blockchain technology. This study also addresses the uniqueness and complexity of ultrasound-guided nerve block anesthesia itself and analyzes the effect of the proposed method. The analysis shows that using the internet-based blockchain ultrasound-guided subacromial nerve block anesthesia for fracture patients is effective, and the patient's vital signs are stable, and the block is effective.
Direct Detection of Antibiotic Resistance in Chinese Helicobacter pylori Clinical Isolates by Sequencing-Based Approach
Authors: Tian Lixia , Yao Yi , Yin Li , Wang Lanxiang , An Ze , Kang Lin , Ru Chenglin , Li Jinping
Published: April 2022

Objective. The detection of Helicobacter pylori mutations that result in antimicrobial resistance can serve as a guideline of antimicrobial therapeutics and probably prevent the failure of clinical treatments. Evaluating the potential of Sanger sequencing to identify genetically resistant determinants in Helicobacter pylori clinical isolates will be important. Methods. 180 cultured strains have been tested using agar dilution for antibiotic susceptibility. NCBI BLAST was used to perform genotypic analysis on the sequencing data. Sanger sequencing was evaluated as an alternative method to detect resistant genotypes and susceptibility. Results. By the conventional E-test, resistance to levofloxacin, amoxicillin, metronidazole, and clarithromycin was 67.3%, 15.1%, 96.4%, and 25.5%, respectively. In contrast, tetracycline had no resistance. Resistance to multiple drugs was observed in 8.12% of the strains. The genetic determinants of resistance to CLA was 23s rRNA, the determinants of resistance to amoxicillin was Pbp1, the determinants of resistance to metronidazole was rdxA, and the determinants of resistance to levofloxacin were GyrA and GyrB. However, there was no association of resistance in tetracycline. Conclusion. We found increased rates of metronidazole antibiotic resistance, highlighting the necessity for alternative therapies and periodic evaluation. Sanger sequencing has proved to be highly effective and holds the potential to be implemented in policies catering to local treatments.
Key Feature Extraction Method of Electroencephalogram Signal by Independent Component Analysis for Athlete Selection and Training
Authors: Huang Zhongwei , Cheng Lifen , Liu Yang
Published: April 2022

Emotion is an important expression generated by human beings to external stimuli in the process of interaction with the external environment. It affects all aspects of our lives all the time. Accurate identification of human emotional states and further application in artificial intelligence can better improve and assist human life. Therefore, the research on emotion recognition has attracted the attention of many scholars in the field of artificial intelligence in recent years. Brain electrical signal conversion becomes critical, and it needs a brain electrical signal processing method to extract the effective signal to realize the human-computer interaction However, nonstationary nonlinear characteristics of EEG signals bring great challenge in characteristic signal extraction. At present, although there are many feature extraction methods, none of them can reflect the global feature of the signal. The following solutions are used to solve the above problems: (1) this paper proposed an ICA and sample entropy algorithm-based framework for feature extraction of EEG signals, which has not been applied for EEG and (2) simulation signals were used to verify the feasibility of this method, and experiments were carried out on two real-world data sets, to show the advantages of the new algorithm in feature extraction of EEG signals.
Clinical and Imaging Data-Based Model for Predicting Reversible Posterior Leukoencephalopathy Syndrome (RPLS) in Pregnant Women With Severe Preeclampsia or Eclampsia and Analysis of Perinatal Outcomes
Authors: An Peng , Zhang Junyan , Li Yang , Duan Peng , Hu Yan , Li Xiumei , Wang Zhongqiu
Published: April 2022

Objective. This study aimed to investigate the risk factors of reversible posterior leukoencephalopathy syndrome (RPLS) in pregnant women with severe preeclampsia or eclampsia (SPE/E) based on a predicting model and to analyze the perinatal outcomes. Methods. From January 2015 to March 2020, 78 pregnant women data diagnosed with severe preeclampsia or eclampsia with cranial magnetic resonance imaging (MRI) and transcranial Doppler (TCD) screening in Xiangyang No. 1 People’s Hospital and Jiangsu Province Hospital of Chinese Medicine were analyzed retrospectively. They were divided into the RPLS group (n = 33) and non-RPLS group (n = 45) based on the MRI results. The general clinical data (blood pressure, BMI, symptoms, and so forth), laboratory examination, TCD results, and perinatal outcomes in the two groups were compared. The risk factors of severe preeclampsia or eclampsia complicated with RPLS were analyzed by multivariate logistic regression. The prediction model and decision curve (DCA) were established according to the clinical-imaging data. Results. The univariate analysis showed that poor placental perfusion, hypertension emergency, use of two or more oral antihypertensive drugs, headache, white blood cell (WBC) count, platelet (PLT) count, lactate dehydrogenase (LDH), alanine aminotransferase (ALT), uric acid (UA), serum albumin (ALB), average flow velocity, and resistance index of the posterior cerebral and basilar arteries were significantly different in the RPLS group compared with the non-RPLS group (all

P
<
0.05

). The multivariate logistic regression analysis showed that hypertensive emergency, headache, WBC, PLT, ALT, and average flow velocity of the basilar artery (BAAFV) were the risk factors in the RPLS group. The aforementioned clinical-imaging data modeling (general data model, laboratory examination model, TCD model, and combined model) showed that the combined model predicted RPLS better. DCA also confirmed that the net benefit of the combined model was higher. In addition, the incidence of postpartum hemorrhage, stillbirth, and preterm infants was higher in the RPLS group than in the non-RPLS group (all

P
<
0.05

). Conclusions. More postpartum complications were detected in pregnant women with severe preeclampsia or eclampsia complicated with RPLS. Hypertensive emergency, headache, WBC, PLT, ALT, and BAAFV were the important risk factors for RPLS. The combined model had a better effect in predicting RPLS.
Higher Education during Lockdown: Literature Review and Implications on Technology Design
Authors: Laato Samuli , Farooq Ali , Vilppu Henna , Airola Antti , Murtonen Mari
Published: April 2022

Countries globally reacted to the COVID-19 pandemic by imposing lockdowns, and as a consequence, higher education institutions were forced to rapidly transition into distance learning. Here, technology played a paramount role as the enabler of remote learning and shaping teaching practices. The aim of this study is to understand the broad trends in higher education during the early lockdown transitions and the role of technology in this process through a literature review approach. After searching for literature and applying inclusion and exclusion criteria, 61 relevant publications were discovered, which were sorted into three clusters using co-word analysis: (1) teaching and learning; (2) policy and managerial issues; and (3) students’ psychological well-being. Each theme was further divided into subthemes based on a thematic clustering approach. Based on this review, implications on learning technology design during the time of a pandemic were derived. First, due to the lack of social contacts resulting from isolation measures, emphasis is needed on interstudent interaction. Second, mobile distance learning technologies and teaching methods could be designed to enable students to move or exercise while learning. Third, diverse pedagogical approaches should be looked into to bring variety into students’ lives.
Stability Analysis for Differential Equations of the General Conformable Type
Authors: Ben Makhlouf Abdellatif , El-Hady El-Sayed , Boulaaras Salah , Hammami Mohamed Ali
Published: April 2022

Fractional calculus is nowadays an efficient tool in modelling many interesting nonlinear phenomena. This study investigates, in a novel way, the Ulam–Hyers (HU) and Ulam–Hyers–Rassias (HUR) stability of differential equations with general conformable derivative (GCD). In our analysis, we employ some version of Banach fixed‐point theory (FPT). In this way, we generalize several earlier interesting results. Two examples are given at the end to illustrate our results.
Construction and Application of University Education Management Model Based on Intelligent Programming Analysis Method
Authors: Chen Sijing , Zhu Rukui , Huang Jinshun
Published: April 2022

The intelligent programming analysis system based on Internet has attracted more and more attention in the field of education management. The problem of how to flexibly master the application capabilities of intelligent programming and development tools, debugging and optimizing programs, and project deployment is becoming more and more serious. Based on the intelligent programming analysis method, this paper systematically introduces the research and design process of education management model and designs modules such as distributed parallel PhpDig, information analyzer, and information resource database. The system adopts client/middleware/server (C/M/S) three-tier architecture planning and design. The server-side carries the resource manager, the middleware carries the intelligent work tasks (information analyzer, resource collection agent), and the client implements user interaction and data representation solves the storage load problem of a large amount of data. The experimental results show that the semantic processing of search object attributes can improve the retrieval performance, and the retrieval rate and tolerance factor reach 87.6% and 0.041, respectively, which effectively promotes the integration of the analysis data on the chain level and the education system.
A Convolutional Neural Network-Based Model for Supply Chain Financial Risk Early Warning
Authors: Yin Li-Li , Qin Yi-Wen , Hou Yuan , Ren Zhao-Jun
Published: April 2022

At present, there are widespread financing difficulties in China's trade circulation industry. Supply chain finance can provide financing for small- and medium-sized enterprises in China’s trade circulation industry, but it will produce financing risks such as credit risks. It is necessary to analyze the causes of the risks in the supply chain finance of the trade circulation industry and measure these risks by establishing a credit risk assessment system. In this article, a supply chain financial risk early warning index system is established, including 4 first-level indicators and 29 third-level indicators. Then, on the basis of the supply chain financial risk early warning index system, combined with the method of convolution neural network, the supply chain financial risk early warning model of trade circulation industry is constructed, and the evaluation index is measured by the method of principal component analysis. Finally, the relevant data of trade circulation enterprises are selected to make an empirical analysis of the model. The conclusion shows that the supply chain financial risk early warning model and risk control measures established in this article have certain reference value for the commercial circulation industry to carry out supply chain finance. It also provides guidance for trade circulation enterprises to deal with supply chain financial risks effectively.
Performance Analysis of PSDRCT-RFEH-DF in Cooperative Networks
Authors: Zhou Yongqiang , Dai Lei , Qian Huan , Li Suoping
Published: April 2022

To prolong the lifetime of energy-constrained cooperative networks, radio frequency energy harvesting (RFEH) technology can effectively solve the energy constraints of nodes batteries, and we consider the maximum ratio combining (MRC) method at the destination node to improve the reliability of the link transmission. Thus, we propose the power splitting-based double-relay cooperative transmission (PSDRCT) protocol with RFEH in the decode-and-forward (DF) mode in this study. According to the transmission process of the proposed protocol, the analytical expressions of outage probability, throughput, and energy efficiency are obtained. Numerical simulation results demonstrate that the location of the relay nodes, power allocation ratio, energy conversion efficiency, and transmission power are the key factors affecting the performance of the protocol. In addition, the proposed protocol has lower outage probability than the time switching-based double-relay cooperative transmission (TSDRCT) protocol under the same power allocation ratio and energy conversion efficiency.
Rendering and Optimization Algorithm of Digital City’s 3D Artistic Landscape Based on Virtual Reality
Authors: Zheng Zhongbiao , Zhou Yan
Published: April 2022

“Digital city” in a broad sense refers to urban informatization. That is to say, the digital city will gradually realize the informatization of the urban national economy and society by building infrastructure platforms such as broadband multimedia information network and geographic information system, integrating urban information resources, establishing e-government, e-commerce, labor, social insurance, and other information communities, to make the city in an invincible position in the competition of the information age. The virtual reality technology of urban three-dimensional landscape, or the establishment of a virtual city, is an important part of the vast project of digital city construction. This research mainly discusses the rendering and optimization algorithm of digital city 3D artistic landscape based on virtual reality. The article uses image stitching technology. Clean up unnecessary furniture in the CAD floor plan, and try to keep only the wall structure. Export drawings and save as dwg files for 3DMAX modeling. For adjacent overlapping images, the common features of the overlapping parts are determined by image matching, so that the images taken at different shooting positions and different viewing directions with a small angle of intersection are calculated to be unified. Take the photo coordinate system, and then find out the overlapping range of each direction for splicing. In the actual data acquisition process, most of the spatial data such as existing maps are used. It mainly includes topographic maps and the latest planning drawings, as well as planning and design drawings of various residential areas. In addition to determining the specific location of each feature, various maps are used to make a surface image (texture) of an urban area based on these data using Photoshop. The editing of roaming space is the key to realizing 3D panoramic virtual city browsing. Combined with the navigation of 3D panoramic map, using key technologies such as hotspot connection and command button, the 3D panoramic images collected in different places in the city can be effectively integrated into one, assisting with various multimedia elements, such as background music, animated videos, and language commentary, show the true appearance of the virtual city in all directions. Compared with the SURF algorithm, the SIFT algorithm extracts more feature points and more correctly matched point pairs, and the minimum time is 0.524 s. This research will contribute to the construction of the three-dimensional landscape of the digital city.
Water Removal from an Ethanol-Water Mixture at Azeotropic Condition by Adsorption Technique
Authors: Mekala Mallaiah , Neerudi Bhoopal , Are Padma Rao , Surakasi Raviteja , Manikandan G. , Kakara Vighneswara Rao , Dhumal Aditya Abhaykumar
Published: April 2022

The separation of ethanol-water mixture is employed in the present work to produce pure ethanol, the present investigation on the separation of water from the ethanol to achieve pure ethanol by adsorption process. The different parameters like quantity of adsorbent, flow rate of feed mixture, and different adsorbents which are zeolite 3A, zeolite 4A, and silica gel are selected to study purification of ethanol by adsorption. The effect of process parameter for purification is also recorded and studied to evaluate the performance of adsorption equipment and adsorbent. The experiments are conducted at 30°C. The feed mixture is 95.6% (v/v) concentration of ethanol and 4.4% (v/v) of water. The designed adsorption column is suitable for purification of ethanol. The highest ethanol concentration 99.9443% obtained at 20 ml/min flow rate of feed mixture using 50 g of zeolite.
Stabilization of Uncertain Switched Systems with Frequent Asynchronism via Event‐Triggered Dynamic Output‐Feedback Control
Authors: Zhang Jin-E , Xing Xiangru
Published: April 2022

This article investigates stabilization for a group of uncertain switched systems with frequent asynchronism. Without the limitation of minimum residence time, the average dwell‐time strategy makes it possible for switched systems with uncertain parameters to switch frequently over successive event intervals. Since it is highbrow and expensive to obtain the whole state information in practice, the dynamic output‐feedback controller is applied. With the aid of a controller‐pattern‐related Lyapunov functional and an event‐triggered dynamic output‐feedback controller, sufficient conditions are established to ensure the stability of the resulting uncertain closed‐loop system. To appropriately deal with the uncertain parameters, some inequalities of the linear matrix are tactfully utilized together with the Lyapunov functional and controller gains are constructed by the strategy of the block matrix. Furthermore, the presence of the lower boundary on adjacent event intervals is earnestly discussed to eliminate the Zeno behavior. Eventually, the feasibility and availability of the theoretical results are illuminated by a numerical simulation.
Risk Assessment of Agricultural Economic Management Based on the Multivariate Statistical Computing Method
Authors: Zhou Yan
Published: April 2022

The modernization process of Chinese agriculture has posed new challenges to agriculture economic management. However, existing studies focus on financial and ecological and environmental risks of agriculture economic management while lacking the necessary attention to other types of agricultural economic management. Therefore, we first propose that the risk of agricultural economic management is of five types—economic, social, political, cultural, and ecological and environmental risks—and further clarify the interactions among the five risk types. Given that the five types of risks are nested with each other, we adopted a multivariate statistical algorithm based on complex network theory to scientifically evaluate the risk management of agriculture economy. The results show the applicability of the algorithm to risk clustering analysis and risk coefficient estimation. The article concludes with the corresponding theoretical and practical implications.