bluuebunny/crossref_metadata_2025 huggingface dataset:
Combining neighbourhood component analysis with dictionary learning algorithms to improve the performance of dictionary learning models for geochemical anomaly detection
Authors: Chen Yongliang , Shayilan Alina
Published: July 2022

In geochemical exploration, a geochemical anomaly detection model is usually established to describe the population distribution of geochemical data, and samples that do not conform to the model are identified as geochemical anomalies. Because the establishment of a geochemical anomaly detection model does not make use of the relationship between geochemical elements and mineralization, its performance for mineral exploration targeting is affected to a certain extent. For this reason, neighbourhood component analysis and dictionary learning algorithms were combined to detect geochemical anomalies associated with gold mineralization in the Chengde area in Hebei Province, China. Neighbourhood component analysis was used to transform geochemical data from the input space into the neighbourhood component space to enhance the separability between the geochemical anomalies associated with gold mineralization and the background. Dictionary learning models for geochemical anomaly detection were established in the neighbourhood component space. The performance of the dictionary learning models established in the neighbourhood component space was compared with that of corresponding models established in the input space in geochemical anomaly detection. The results show that the former models are superior to the latter. In addition, there is a strong consistency between the mineral exploration targeting results and metallogenic characteristics of the study area. Therefore, combining neighbourhood component analysis and dictionary learning algorithms can improve the performance of dictionary learning models in geochemical anomaly detection.
Challenges and Opportunities for Multi-Device Management in Classrooms
Authors: Lachand-Pascal Valentin , Michel Christine , Serna Audrey , Tabard Aurélien
Published: July 2022

Orchestrating digital devices in classrooms is challenging. We conducted an observational study to understand how teachers manage multi-device classrooms involving tablets, computers, and video-projectors. Two categories of device management tasks stand out: content sharing and remote control. Based on our observations, we identify 17 multi-device management tasks that are important to teachers in this specific device configuration. We conducted a second study to investigate how teachers could perform these tasks with the help of a smartwatch. For remote control tasks, participants preferred smartwatches to interact from a distance, whereas for content-sharing tasks, they preferred to interact directly with the devices displaying the content. We outline design opportunities for multi-device management controls in learning environments, and challenges for HCI research on classroom orchestration.
𝖧𝗒𝖣𝖱𝖤𝖠: Utilizing Hyperdimensional Computing for a More Robust and Efficient Machine Learning System
Authors: Morris Justin , Ergun Kazim , Khaleghi Behnam , Imani Mohen , Aksanli Baris , Simunic Tajana
Published: July 2022

Today’s systems rely on sending all the data to the cloud and then using complex algorithms, such as Deep Neural Networks, which require billions of parameters and many hours to train a model. In contrast, the human brain can do much of this learning effortlessly. Hyperdimensional (HD) Computing aims to mimic the behavior of the human brain by utilizing high-dimensional representations. This leads to various desirable properties that other Machine Learning (ML) algorithms lack, such as robustness to noise in the system and simple, highly parallel operations. In this article, we propose 𝖧𝗒𝖣𝖱𝖤𝖠, a HyperDimensional Computing system that is Robust, Efficient, and Accurate. We propose a Processing-in-Memory (PIM) architecture that works in a federated learning environment with challenging communication scenarios that cause errors in the transmitted data. 𝖧𝗒𝖣𝖱𝖤𝖠 adaptively changes the bitwidth of the model based on the signal-to-noise ratio (SNR) of the incoming sample to maintain the accuracy of the HD model while achieving significant speedup and energy efficiency. Our PIM architecture is able to achieve a speedup of 28× and 255× better energy efficiency compared to the baseline PIM architecture for Classification and achieves 32 × speed up and 289 × higher energy efficiency than the baseline architecture for Clustering. 𝖧𝗒𝖣𝖱𝖤𝖠 is able to achieve this by relaxing hardware parameters to gain energy efficiency and speedup while introducing computational errors. We show experimentally, HD Computing is able to handle the errors without a significant drop in accuracy due to its unique robustness property. For wireless noise, we found that 𝖧𝗒𝖣𝖱𝖤𝖠 is 48 × more robust to noise than other comparable ML algorithms. Our results indicate that our proposed system loses less than 1% Classification accuracy, even in scenarios with an SNR of 6.64. We additionally test the robustness of using HD Computing for Clustering applications and found that our proposed system also looses less than 1% in the mutual information score, even in scenarios with an SNR under 7 dB, which is 57 × more robust to noise than K-means.
Privacy Intelligence: A Survey on Image Privacy in Online Social Networks
Authors: Liu Chi , Zhu Tianqing , Zhang Jun , Zhou Wanlei
Published: July 2022

Image sharing on online social networks (OSNs) has become an indispensable part of daily social activities, but it has also increased the risk of privacy invasion. An online image can reveal various types of sensitive information, prompting the public to rethink individual privacy needs in OSN image sharing critically. However, the interaction of images and OSN makes the privacy issues significantly complicated. The current real-world solutions for privacy management fail to provide adequate personalized, accurate, and flexible privacy protection. Constructing a more intelligent environment for privacy-friendly OSN image sharing is urgent in the near future. Meanwhile, given the dynamics in both users’ privacy needs and OSN context, a comprehensive understanding of OSN image privacy throughout the entire sharing process is preferable to any views from a single side, dimension, or level. To fill this gap, we contribute a survey of “privacy intelligence” that targets modern privacy issues in dynamic OSN image sharing from a user-centric perspective. Specifically, we present the important properties and a taxonomy of OSN image privacy, along with a high-level privacy analysis framework based on the lifecycle of OSN image sharing. The framework consists of three stages with different principles of privacy by design. At each stage, we identify typical user behaviors in OSN image sharing and their associated privacy issues. Then a systematic review of representative intelligent solutions to those privacy issues is conducted, also in a stage-based manner. The analysis results in an intelligent “privacy firewall” for closed-loop privacy management. Challenges and future directions in this area are also discussed.
Construction of Ag-AgInS2/In2S3/TNR Nanoarray High-Performance Photocatalyst and its Degradation Performance of Tetracycline Hydrochloride
Authors: Qi Shihan , Yin Zhuangzhuang , Deng Shangkun , Ding Chunsheng , Chen Peng , Li Ziliang , Gan Wei , Guo Jun , Zhang Miao , Sun Zhaoqi
Published: July 2022

In this work, Ag quantum dot-modified AgInS2/In2S3/TNR nanoarray photocatalysts were prepared by a secondary hydrothermal and wet chemical method. Compared with the unmodified TNR arrays, the modified Ag-AgInS2/In2S3/TNR samples showed a significant increase in light absorption and could utilize more solar energy. In addition, the Ag-AgInS2/In2S3/TNR samples can effectively promote the separation and transfer of electron-hole pairs to enhance the photoelectrochemical and photocatalytic performance of the composites, and the degradation rate of the optimal Ag-AgInS2/In2S3/TNR samples can reach 95.73% for TC-HCl, which is of great importance for environmental protection. The main reasons for the enhanced catalytic performance are: the presence of surface Ag quantum dots and AgInS2 sensitizers greatly increases the absorption of sunlight, allowing more energy to enter the catalytic system; the stepped energy level arrangement of AgInS2/In2S3/TNR nanoarrays can spatially separate electrons and holes, improving the separation efficiency and enhancing the overall performance of the material.
Selective Detection of Chloroquine in Human Urine with Application at the Point-of-Care
Authors: Glasco Dalton L. , Mamaril Art Matthew , Sheelam Anjaiah , Ho Nguyen H. B. , Bell Jeffrey G.
Published: July 2022

Chloroquine is an important, and commonly prescribed, antimalarial drug which can lead to the development of retinopathy and potential blindness. This paper reports on the design and fabrication of a highly selective potentiometric sensor for chloroquine, demonstrating the first use of ionophore-doped ion-selective electrodes (ISEs) for its detection. Several molecules, with known affinity for chloroquine, were investigated as potential ionophores for the chloroquine ISE. Incorporating melanin as the ionophore resulted in a linear detection range of 10 mM to 2.4 μM and a limit of detection of 630 nM. Importantly, the melanin-doped ISE resulted in an increased selectivity by several orders of magnitude compared to an ionophore-free ISE. This added selectivity allowed for detection of chloroquine without interference from other commonly prescribed antimalarials, hydroxychloroquine and quinine that have similar molecular structures. To determine the applicability of the melanin-doped ISE, chloroquine was successfully measured in human urine samples, and the results of the sensor were validated using a High-Performance Liquid Chromatography (HPLC) protocol. To demonstrate the utility of the sensor, the components of the ISE were translated to a paper-based potentiometric device capable of detecting chloroquine between 10 mM and 100 μM, covering the biologically relevant range excreted in human urine.
Whole body lipid oxidation during exercise is impaired with poor insulin sensitivity but not with obesity per se
Authors: Arad Avigdor D. , DiMenna Fred J. , Kittrell Hannah D. , Kissileff Harry R. , Albu Jeanine B.
Published: July 2022

In this study, we have shown that the capacity to oxidize lipid during exercise is influenced by metabolic health of the exerciser regardless of body composition, but not by body composition per se. This observation refutes the belief that a reduced capacity to oxidize lipid is an obligatory characteristic of the overweight/obese condition while supporting the contention that exercise should be prescribed with specificity based on both absence/presence of overweight/obesity and compromise/lack thereof in metabolic health.
Leptin receptor-expressing cells in the ventromedial nucleus of the hypothalamus contribute to enhanced CCK-induced satiety following central leptin injection
Authors: Ahn WonMo , Latremouille John , Harris Ruth B. S.
Published: July 2022

Leptin is a feedback signal in the control of energy balance, whereas cholecystokinin (CCK) is a short-term satiety signal that inhibits meal size. The two hormones synergize to promote satiety. We tested whether leptin receptors in the ventromedial nucleus of the hypothalamus (VMH) contribute to the synergy. The results suggest that there is a requirement for a baseline level of activation of leptin receptors in the VMH in order for CCK to promote satiety.
Age-related increases in reaction time result from slower preparation, not delayed initiation
Authors: Hardwick Robert M. , Forrence Alexander D. , Costello M. Gabriela , Zackowski Kathy , Haith Adrian M.
Published: July 2022

Previous research argues that older adults have slower response times because they hesitate to react, favoring accuracy over speed. The present results challenge this proposal. We found the delay between the minimum time required to prepare movements and the self-selected time at which they initiated remained consistent at ∼90 ms from ages 21 to 80. We therefore suggest older adults’ slower response times can be attributed to changes in their ability to process stimuli and prepare movements.
Laryngeal and swallow dysregulation following acute cervical spinal cord injury
Authors: Pitts Teresa , Iceman Kimberly E. , Huff Alyssa , Musselwhite M. Nicholas , Frazure Michael L. , Young Kellyanna C. , Greene Clinton L. , Howland Dena R.
Published: July 2022

This is the first manuscript to determine the impact of cSCI on laryngeal and swallow function, and to describe a possible mechanism for dysphagia and altered airway protection after injury.
Response of toadfish (Opsanus tau) utricular afferents to multimodal inputs
Authors: Rogers Loranzie S. , Van Wert Jacey C. , Mensinger Allen F.
Published: July 2022

The inner ear of teleost fishes is composed of three paired multimodal otolithic end organs, which are sensitive to vestibular and auditory inputs. Previous studies investigating inner ear functions have primarily focused on the effects of unimodal stimuli; therefore, it remains unclear how otolithic end organs simultaneously encode multiple stimuli. Here, we show that utricular afferents remain sensitive to behaviorally relevant acoustic stimuli during swimming.
A Two-Way Update Resource Allocation Strategy in Mobile Edge Computing
Authors: Yang Zhe , Chen Yi-peng , Gu Fei , Wang Jin , Zhao Lei
Published: July 2022

Existing studies of mobile edge computing resource allocation strategy problem merely optimize delay and energy cost, seldom considering the benefit of edge servers. So, a two-way update strategy based on game theory (TUSGT) was proposed. TUSGT converts the task competition relationship among edge servers into a noncollaborative game issue and adopts a potential game-based joint optimization strategy, allowing edge servers to determine task selection preference by maximizing their own benefit as the objective. At mobile device side, the EWA algorithm of online learning was used to update parameters, exerting impact on edge server’s task selection preference from a global perspective and improving overall deadline hit rate. The simulation test results show that, compared to BGTA, MILP, greedy strategy, random strategy, and ideal strategy, TUSGT promotes deadline hit rate by up to 30% and increases edge server’s average benefit by up to 65%.
[Retracted] Renal Denervation Reduces Blood Pressure and Improves Cardiac Function: Results from a 12‐Month Study
Authors: Luo Di , Lu Chengzhi
Published: July 2022

Background. Previous studies showed that a decline in BP can reverse pressure‐overloaded left ventricular hypertrophy in the long term. Whether this structural remodeling and improved cardiac function were due to reduced BP levels or sympathetic tone is unclear. The aim of this study was to evaluate the efficacy of renal denervation (RDN) on cardiac function and left ventricular hypertrophy in patients diagnosed with resistant hypertension with systolic and diastolic dysfunction. Methods. Thirteen patients diagnosed with resistant hypertension underwent bilateral RDN (RDN group), and 13 patients were selected as the control group (drug group) who received regular antihypertensive drugs for the first time. Demographic analysis and hematologic tests were performed to determine renal function as well as BNP levels. Echocardiogram was performed at baseline and 12 months after RDN. Results. All the baseline characteristics are comparable in two groups. Both RDN and drug regiments resulted in significant reduction from baseline in SBP/DBP at 12‐month follow‐up (all P values < 0.01), and the decline due to two interventions showed no statistically significant difference (F = 1.64, P = 0.213 and F = 0.124, P = 0.853 for SBP and DBP, respectively). RDN significantly reduced mean LV mass index (LVMI) from 151.43 ± 46.91 g/m2 to 136.02 ± 37.76 g/m2 (P = 0.038) and ejection fraction (LVEF) increased from 57.15 ± 5.49% at baseline to 59.54 ± 4.18% at 12 months (P = 0.039). No similar changes were detected in the drug group (P values, 0.90 for EF and 0.38 for LVMI). Renal parameters including BUN, Cr, UA, and eGFR at baseline, 3 months, and 12 months showed no marked difference (P = 0.497, 0.223, 0.862, 0.075, respectively). Conclusions. Our findings show that in addition to hypertension and its progression, elevated sympathetic hyperactivity is related to left ventricular hypertrophy and cardiac function.
The Effects of WhatsApp and Telegram on Student Engagement: An Analysis from the Mixed-Methods Approach
Authors: Estrada Molina Odiel
Published: July 2022

One of the most studied variables in virtual online education is engagement because it contributes to retention and academic performance. Several studies show that the didactic design of the virtual course, the role of the teacher, interactivity, interaction, time spent in the virtual environment, and the use of digital social networks increase engagement. However, there is a lack of research that compares which of the two digital social networks, WhatsApp or Telegram, promotes higher levels of engagement. This study’s objective is to analyze the effect of the educational use of Telegram on student engagement. An experiment (pretest and posttest with a control group) is designed using a mixed-methods approach based on a convergent or concurrent triangulation design. The study populations (coincides with the sample) are those enrolled (n = 229) in the six editions of a virtual postgraduate course. The techniques used for data analysis were scatter plots, content analysis of teachers’ narratives, and statistical methods. The triangulation of the quantitative and qualitative results confirms that the educational use of digital social networks promotes engagement in all experimental groups (use of the virtual learning environment and Telegram) obtaining greater significant differences than in the control groups. It is concluded that the use of the following Telegram functionalities, chat groups, peer assessments, support for various types of online interaction, the exchange of digital media, and the design of surveys contributed, under the guidance of teachers, is to increase the student’s engagement.
The Clinical Application Value of the Prognostic Nutritional Index for the Overall Survival Prognosis of Patients with Esophageal Cancer: A Robust Real-World Observational Study in China
Authors: Kang Juanjuan , Yang Guishu , Wang Dongsheng , Lin Ying , Wang Qifeng , Luo Huaichao
Published: July 2022

Esophageal cancer is a kind of cancer with high morbidity and mortality, which is accompanied by a profound poor prognosis. A prognostic nutritional index, based on serum albumin levels and peripheral lymphocyte count, has been confirmed to be significantly associated with various cancers. This study was aimed at exploring the prognostic significance of PNI in the overall survival prognosis of patients with esophageal cancer. As a real-world study based on the big database, clinical data of 2661 patients with esophageal cancer were evaluated retrospectively, and the individuals were randomly divided into training and testing cohorts. In these two cohorts, patients are classified into a high-risk group (

PNI
<
49

) and a low-risk group (

PNI
≥
49

). Univariate and multivariate analyses were performed to analyze the independent risk factors for the prognosis of esophageal cancer patients by using the Cox proportional hazards regression model. In this study, whether in the training cohort or the testing cohort, according to the univariate analysis, gender, tumor size, tumor grade, T stage, N stage, M stage, TNM stage, and PNI were significantly correlated with overall survival. Furthermore, the multivariate analysis showed that gender, T stage, N stage, M stage, TNM stage, and PNI were independent prognostic risk factors for esophageal cancer. PNI can be regarded as an independent prognostic factor combined with gender, T stage, N stage, M stage, and TNM stage, and it might be a novel reliable biomarker for esophageal cancer.
Ameliorating Effect on Glycolipid Metabolism of Spirulina Functional Formulation Combination from Traditional Chinese Medicine
Authors: Huang Zifeng , Wang Chang’e , Chen Jie , He Xiaoyu , Chen Kewen , Jiang Xiaoqin , Zhao Chao , Liu Bin
Published: July 2022

Insulin resistance is the major factor involved in the pathogenesis of type 2 diabetes. Although the oral drug metformin (MH) is widely used to reduce hyperglycemia, it is associated with adverse effects. Therefore, there is an urgent need to search for safe and natural foods that do not cause adverse effects as alternatives to commercial drugs. In this study, the active substances from Spirulina platensis, Grifola frondosa, Panax ginseng, and chromium-rich yeast were used to obtain Spirulina functional formulations (SFFs), and its therapeutic effects on mice with glycolipid metabolism disorder (GLD) were investigated. Results showed that SFFs not only improved glycolipid metabolism and reduced inflammation in mice with GLD but also showed good regenerative effects on the liver, jejunum, and cecum tissues. Moreover, SFFs could inhibit the growth of harmful microbes in the intestine and promote the proliferation of beneficial bacteria, thereby promoting the production of short-chain fatty acids and further regulating GLD. Additionally, SFFs significantly increased the expression of INS, INSR, IRS-1, PI3K, AKT-1, and GLUT-4 genes and significantly decreased that of GSK-3β in the INS/PI3K/GLUT-4 signaling pathway. Therefore, the findings of this study suggest that SFFs can be further developed as a new class of therapeutic agents against GLD.
Design of Data Sharing Platform Based on Blockchain and IPFS Technology
Authors: Li Weijing , Zhou Zicheng , Fan Wen , Gao Juan
Published: July 2022

With the continuous development of the information age, data sharing and exchange are gradually increasing. The Internet and big data technology provide a guarantee for data sharing and transmission. At present, as the amount of data increases rapidly, how to realize data sharing has become a huge challenge. To solve this problem, this paper proposes a data sharing platform based on the combination of blockchain and interplanetary file system (IPFS) technology to solve the data sharing and storage. Firstly, by constructing the alliance blockchain, the consensus mechanism of computing power competition is used to maintain the data written into the blockchain, and the IPFS data storage system is established to store data using distributed storage, file splitting, and splicing technologies. Secondly, a data sharing platform composed of blockchain module, IPFS module, encryption and decryption module, and fast retrieval module is built. Data encryption is processed by encryption and decryption module, and the processed data is uploaded to THE IPFS module; the abstract and other information are finally written into the blockchain through the blockchain module. The fast retrieval module can quickly locate the required data according to the retrieval conditions in the mass blockchain data; finally, the security and storage of data sharing platform are guaranteed through security and performance evaluation. The research results solve the problem of large amount of data sharing, realize the data decentralization, and ensure the data storage security.
Blockchain Technology-Based Electronic Payment Strategy for City Mobile Pass Cards
Authors: Li Xiaozhen , Shen Xueli
Published: July 2022

Currently, there has been a paradigm shifted in the storing of electronic payment records (EPRs) on mobile distributed systems, wherein mobile devices are coupled with cloud computing to ease financial data transfers between consumers and stakeholders. This enhanced architecture allows low-cost online payment services with high versatility and EPR accessibility. Nevertheless, for e-payment platforms, such a new paradigm poses worries about data privacy and network security. A difficult challenge is how to reliably disseminate EPRs across mobile users while maintaining high-security security standards in the mobile cloud. This paper investigates and demonstrates the electronic payment approach of urban mobile pass cards’ dependability and excellence. Furthermore, on a mobile cloud platform, our technology integrates blockchain with the decentralized interplanetary file system (IPFS). We specifically create a reliable access control method on smart contracts to ensure secure EPR sharing across various clients and stakeholders. Our empirical results indicate that our concept provides a viable solution for data transfers on mobile clouds while protecting critical payment information from potential attacks. When compared to previous data sharing models, the system evaluation and security analysis show performance gains in lightweight access control architecture, minimal network latency with excellent security and data confidentiality levels.
Design and Implementation of an Online Learning Behavior Evaluation System Based on Data Mining
Authors: Zhang Bo , Xie Jiali
Published: July 2022

In order to study the problem that most of the existing Web-based distance education systems lack the monitoring of the learning process and the evaluation of students’ online learning behavior, a method of designing an online learning behavior evaluation system based on data mining is proposed, and an online learning behavior evaluation system is implemented. The system evaluates students’ online learning and gives formative evaluation results. The evaluation results are more accurate, and the recognition of teachers and students is more than 90%. The application of the system provides methods and means for objective, fair, and reasonable evaluation of students’ online learning and plays a guiding role for students in rationally arranging online learning; 99% of users said that the application of this system has a greater effect on promoting ordinary online learning help. The application of the system promotes students’ online learning to a certain extent, and the “learning behavior-effect” model constructed by the system has guiding significance for students to reasonably arrange online learning.
A Note about Young’s Inequality with Different Measures
Authors: Mehmood Saba , Eridani Eridani , Fatmawati Fatmawati
Published: July 2022

The key purpose of this paper is to work on the boundedness of generalized Bessel–Riesz operators defined with doubling measures in Lebesgue spaces with different measures. Relating Bessel decaying the kernel of the operators is satisfying some elementary properties. Doubling measure, Young's inequality, and Minköwski’s inequality will be used in proofs of boundedness of integral operators. In addition, we also explore the relation between the parameters of the kernel and generalized integral operators and see the norm of these generalized operators which will also be bounded by the norm of their kernel with different measures.
Automated Periotome versus Conventional Periotome in Intra-Alveolar Extraction of Sheep Jaw: An In Vitro Study
Authors: Kuriadom Sam Thomas , Al-Chalabi Sarmad , Hadi Karrar M. H. , Ishbair Ashraf M.
Published: July 2022

Background. Atraumatic dental extraction is the way forward in modern dentistry. This study aims to compare the effectiveness of automated periotome with conventional periotome with regard to operating time, postoperative gingival laceration, and bone and tooth structure fractures. Methods. This is an in vitro study of forty posterior teeth of sheep mandibles. Ten sound healthy mandibles were selected, and each mandible was then divided into two quadrants with two teeth in each quadrant. Teeth were then extracted by conventional periotome for the first group (one quadrant) and by automated periotome for the second group (other quadrants). A statistically significantPvalue is set at below 0.05 with a 95% confidence interval. Results. No bone fracture was seen in any of the cases of automated periotome with a significance of 0.004 when compared to the fractures seen in seven cases in the conventional group. Whereas comparing the other parameters among the different groups did not show any significant difference. Conclusion. It is worthwhile to use the automated periotome in simple extractions, especially when implants are considered in the treatment plan.
Astragalus Polysaccharides Inhibit Pancreatic Cancer Progression by Downregulation of TLR4/NF‐κB Signaling Pathway
Authors: Fang Jingjing , Wu Zongyang , Wang Jinbo , Feng Jiye , Ying Liping
Published: July 2022

Background. Pancreatic cancer (PC) leads to high human malignancy mortality worldwide. This study explored the role of Astragalus polysaccharide (APS) on human PC PANC‐1 cells and its underlying mechanisms. Method. Cell viability, proliferation, apoptosis, invasion, and migration were measured by CCK‐8, EdU incorporation, flow cytometry, Transwell, and wound healing assay, respectively. ELISA assay was utilized to detect the IL‐1α, IL‐4, IL‐6, IL‐8, and TNF‐α levels. The western blot assay was performed to measure the level changes of cell function‐related proteins. The transportation of NF‐κB P65 protein was detected through immunofluorescence assay. Results. Compared with the control group, APS treatment could significantly inhibit cell proliferation. APS treatment could also suppress cell migration and invasion ability and induce apoptosis and inflammation in PANC‐1 cells. Furthermore, APS inhibited the activation of TLR4/NF‐κB signaling pathway via suppressing the phosphorylation and transportation of NF‐κB P65 into the PANC‐1 cell nucleus. Conclusion. APS suppresses PANC‐1 cell viability, proliferation, migration, and invasion while inducing inflammation and apoptosis. APS might regulate PC cell motility via downregulating TLR4/NF‐κB signaling pathway.
Astragaloside IV Protects Detrusor from Partial Bladder Outlet Obstruction-Induced Oxidative Stress by Activating Mitophagy through AMPK-ULK1 Pathway
Authors: Zhu Xiaoyu , Tao Fangze , Zhang Li , Yu Yajie , Xu Yanchao , Yang Gang , Wei Zhifeng , Cheng Yidong , Yin Xuelai , Zhang Xinyuan , Wei Wu , Wang Anxi
Published: July 2022

Aims. Bladder outlet obstruction (BOO) and the consequent low contractility of detrusor are the leading causes of voiding dysfunction. In this study, we aimed to evaluate the pharmacological activity of astragaloside IV (AS-IV), an antioxidant biomolecule that possess beneficial effect in many organs, on detrusor contractility and bladder wall remodeling process. Methods. Partial BOO (pBOO) was created by urethral occlusion in female rats, followed by oral gavage of different dose of AS-IV or vehicle. Cystometric evaluation and contractility test were performed. Bladder wall sections were used in morphology staining, and bladder tissue lysate was used for ELISA assay. Primary smooth muscle cells (SMCs) derived from detrusor were used for mechanism studies. Results. Seven weeks after pBOO, the bladder compensatory enlarged, and the contractility in response to electrical or chemical stimuli was reduced, while AS-IV treatment reversed this effect dose-dependently. AS-IV also showed beneficial effect on reversing the bladder wall remodeling process, as well as reducing ROS level. In mechanism study, AS-IV activated mitophagy and alleviated oxidative stress via an AMPK-dependent pathway. Conclusion. Out data suggested that AS-IV enhanced the contractility of detrusor and protected the bladder from obstruction induced damage, via enhancing the mitophagy and restoring mitochondria function trough an AMPK-dependent way.
Path Planning of Storage and Logistics Mobile Robot Based on ACA-E Algorithm
Authors: Zhao Yue
Published: July 2022

In this paper, warehouse logistics robot as the research object, starting from the reality of modern e-commerce logistics industry, proposed a warehousing logistics mobile robot path planning method. Ant colony algorithm is used to plan the forward path of mobile robot in static and dynamic environment of warehouse logistics. The results show that the elite-based strategy improves the global search capability of ACA and eliminates redundant nodes in the path, and the path length of the obtained plan is significantly better than that of traditional ACA, which is reduced by 3.46% and 5.90%, respectively, indicating that the elite-based strategy and the central-point-based smoothing method play their roles. The path length of the robot’s final operation is larger than that of the global path planning, which increases by 1, accounting for 6.67% of the original path length. Therefore, the storage and logistics mobile robot based on ACA-E algorithm has short driving distance and superior obstacle avoidance ability.
Identifying miRNAs Associated with the Progression of Keloid through mRNA‐miRNA Network Analysis and Validating the Targets of miR‐29a‐3p in Keloid Fibroblasts
Authors: He Yan , Zhang Zexin , Yin Bin , Li Shu , Wang Peng , Lan Junhong , Lian Wenqin , Jia Chiyu
Published: July 2022

Background. Keloid has brought great trouble to people and currently has no uniformly successful treatment. It is urgent to find new targets to effectively prevent the progress of keloid. The current research mainly identifies the differentially expressed genes (DEGs) in keloid through high‐throughput sequencing technology and bioinformatics analysis technology, to screen new therapeutic targets and potential biomarkers. However, due to the different samples, different control groups, and small sample sizes, the sequencing results obtained from different studies are quite different and lack reliability. It is necessary to analyze the existing datasets in a reasonable way. Methods. Datasets about keloid were filtered in Gene Expression Omnibus (GEO) and ArrayExpress databases according to the inclusion and exclusion criteria. The discovery datasets were used for summarizing significant DEGs, and the validation datasets were to validate the mRNA and miRNA expression levels. The Encyclopedia of RNA Interactomes (ENCORI) online platform was used to predict the interactions between miRNAs and their target mRNAs. Protein‐protein interaction network (PPI network) analysis and functional enrichment analysis were conducted. miRNA‐mRNA network was established by Cytoscape software and verified in keloid tissue (n = 8) by RT‐qPCR. miR‐29a‐3p mimic and inhibitor were transfected into keloid fibroblasts (KFs) to preliminary verify its targets, the prognostic value of which was estimated by the receiver operating characteristic (ROC) curve. Results. A total of 6 datasets involving 20 patients were included. 15 miRNAs and 12 target mRNAs were identified as potential biomarkers for keloid patients. The RT‐qPCR results showed that miR‐29a‐3p, miR‐92a‐3p, and miR‐143‐3p were downregulated, and all their target mRNAs were upregulated in keloid tissue (P < 0.05). The expression of COL1A1, COL1A2, COL3A1, COL5A1, and COL5A2 decreased when miR‐29a‐3p was overexpressed but increased when miR‐29a‐3p was knocked down (P < 0.05). And these genes had a good performance in the diagnosis of keloid, especially when using keloid nonlesional skin or normal scar tissues as controls. Conclusion. The miRNA‐mRNA network, especially miR‐29a‐3p and its targets, may provide insights into the underlying pathogenesis of keloid and serve as potential biomarkers for keloid treatment.
Data Mining Optimization Software and Its Application in Financial Audit Data Analysis
Authors: Shan Rui , Xiao Xianfei , Che Junwen , Du Jingfang , Li Yuwu
Published: July 2022

The scope of finance is very wide, data also plays a very important role in the financial industry, a small data change, and it may have a great impact on the economy. Therefore, the author proposes data mining optimization software and its application in financial audit data analysis. First, discuss the decision tree method, the main function module design of the system software, the financial analysis software method of weighted multiple random decision trees is described. To conduct verification experiments, the decision-making effect of constructing 10 random decision trees is the best. So, the author constructed a total of 10 random decision trees to analyze the data, since the tree is constructed using a random method, in order to verify the stability of decision tree classification, a total of 5 experiments were carried out, the training data set for each experiment, randomly select 1200 pieces of data from the original data set as training data, the tree is constructed by randomly selecting 12 attributes from 24 attributes. The remaining 300 pieces of data are used as verification data. As can be seen from the results, the accuracy of the random decision tree method is about 10% higher than that of C4.5. In order to improve the accuracy rate of high risk, 300 pieces of high-risk data were added to the training data set. To change the original random sampling into stratified sampling, according to the high, medium, and low risk, the original data is stratified; random sampling is used for each layer, thereby ensuring the amount of training data with high risk. The accuracy of decision tree classification is related to the number of samples of the training data, the larger the number of samples, the more accurate the classification of the constructed decision tree.
Evaluation of Four eGFR Calculating Formulae in Predicting Postoperative Acute Kidney Injury in Adult Patients Undergoing Open‐Heart Surgery with Cardiopulmonary Bypass
Authors: Wu Xiaoyun , Qiu Feng , Jin Xianglan , Liu Qiang , Zhou Jian , Duan Xia
Published: July 2022

Objective. There are four widely‐used formulae to calculate the perioperative glomerular filtration rate (GFR) of patients undergoing cardiac surgery. We assessed the predictive values of these formulae in the occurrence of postoperative acute kidney injury (AKI). Methods. Patients who underwent open‐heart valvular surgery with cardiopulmonary bypass from January 2015 to October 2017 were enrolled in this retrospective study. Demographic data and perioperative serum creatinine levels were collected. The estimated GFR (eGFR) was calculated using four formulae: Cockcroft Gault (CG), body surface area (BSA) corrected CG, simplified modification of diet in renal disease (MDRD), and chronic kidney disease‐epidemiology collaboration (CKD‐EPI) formula. The incidence of post‐operative AKI was calculated and the predictive capability of these formulae was evaluated. Results. A total of 290 patients were included. 136 patients (46.90%) developed AKI after surgery. The eGFR in the AKI group was significantly lower than those in the non‐AKI group at all investigated time points. In addition, the eGFR in the non‐AKI group increased temporarily on the day of operation, then decreased on the following days, and returned to preoperative level about one week after surgery. However, in the AKI group, the eGFR decreased from the day of operation, which still did not recover to the preoperative level by the end of the first week after surgery. The eGFR calculated by the BSA‐standardized CG formula had the highest AUC ROC curves of 0.699 and 0.774 before operation and on the day of operation, respectively. While eGFR calculated by CKD‐EPI formula had the highest AUC ROC of 0.874 and 0.887 at the first and second postoperative day. Conclusions. The eGFR formula is a powerful tool for perioperative renal function assessment. The BSA‐corrected CG and CKD‐EPI formula have better performance in predicting postoperative AKI after cardiopulmonary bypass than serum creatinine level and other formulae.
Anti-inflammatory Mechanism of Action of Benzoylmesaconine in Lipopolysaccharide-Stimulated RAW264.7 Cells
Authors: Zhou Changkai , Gao Jing , Qu Haijun , Xu Long , Zhang Bin , Guo Qie , Jing Fanbo
Published: July 2022

Background. Benzoylmesaconine (BMA), the most abundant monoester alkaloid in Aconitum plants, has some biological activities and is a potential therapeutic agent for inflammation-related diseases. However, the potential anti-inflammatory mechanisms of BMA have not been clarified. Purpose. This study aimed to investigate the underlying molecular mechanisms of the anti-inflammatory action of this compound using lipopolysaccharide (LPS)-activated RAW264.7 macrophages. Methods. The release of pro-inflammatory cytokines and mediators were detected by nitric oxide (NO) assays, reactive oxygen species (ROS) assays, and enzyme-linked immunosorbent assays (ELISA) in LPS-activated RAW264.7 macrophage cells. Quantitative real-time PCR was used to measure the gene expression of interleukin (IL)-1β, tumor necrosis factor (TNF)-α, IL-6, inducible nitric oxide synthase (iNOS), and cyclooxygenase-2 (COX-2). Cell viability was determined using a cell counting kit-8 (CCK-8) assay. The expression of iNOS, COX-2, mitogen-activated protein kinase (MAPK), and nuclear factor-κB (NF-κB)-related proteins were detected by western blot, and nuclear translocation of p65 was observed by immunofluorescence. Results. BMA significantly decreased the production of IL-1β, IL-6, TNF-α, PGE2, NO, and ROS and inhibited the protein and mRNA levels of COX-2 and iNOS in LPS-activated RAW264.7 macrophages. Moreover, LPS-induced phosphorylation of IκBα, JNK, p38, and ERK; degradation of IκBα; and nuclear translocation of p65 were significantly suppressed by BMA treatment. Conclusion. These findings demonstrate that the anti-inflammatory effect of BMA was through the suppression of the NF-κB and MAPK signaling pathways and that it may be a therapeutic agent targeting specific signal transduction events required for inflammation-related diseases.
Peripheral Repetitive Transcranial Magnetic Stimulation(rTMS) for Idiopathic Facial Nerve Palsy: A Prospective, Randomized Controlled Trial
Authors: Liu Zicai , Xie Dongling , Wen Xin , Wang Risheng , Yang Quan , Liu Huiyu , Shao Yuchun , Liu Tingting
Published: July 2022

Purpose. The purpose of this study was to evaluate the clinical efficacy of peripheral repetitive transcranial magnetic stimulation (rTMS) in the treatment of idiopathic facial paralysis, to explore an ideal treatment scheme for idiopathic facial paralysis, and to provide evidence for clinical rehabilitation. Methods. 65 patients with idiopathic facial nerve palsy with the first onset were recruited and randomly divided into rTMS group and control group. Both groups received conventional treatment, rTMS group received additional repetitive transcranial magnetic stimulation to the affected side once a day, 5 times a week for 2 weeks. House-Brackmann (HB) grading scale, Sunnybrook facial grading system (SFGS), and modified Portmann scale (MPS) were used to assess facial nerve function before and after treatment, and the time for patients to return to normal facial nerve function and adverse reaction (AR) was also the main observation index. Results. After a 2-week intervention, HB, SFGS, and MPS increased in both groups (

P
<
0.01

); the improvement of HB, SFGS, and MPS in rTMS group was significantly higher than that in control group (

P
<
0.01

). The effective improvement rate of the TMS group after 2 weeks was 90.0%, and that of the control group was 53.3%, and the difference was statistically significant (

P
<
0.01

). Conclusions. Repetitive transcranial magnetic stimulation is a safe and effective noninvasive method for the treatment of idiopathic facial paralysis, which can significantly accelerate the recovery of facial nerve function and provide a new treatment idea for further improving the prognosis of patients with idiopathic facial paralysis.
Economic Policy Uncertainty, Investor Sentiment, and Stock Price Synchronisation: Evidence from China
Authors: Wu Jing
Published: July 2022

This paper explores the general decision mechanism of stock price synchronicity through in-depth research on the two main viewpoints of information efficiency view and irrational behaviour view. On this basis, we explore the effect of China’s economic policy uncertainty gradually on the synchronisation of stock prices and provide a reasonable explanation for it. Based on the China Economic Policy Uncertainty Index developed by Baker et al., this paper takes China’s A-share listed firms from 2010 to 2019 as the primary sample and tests the effect of China’s economic policy uncertainty on the synchronicity of stock prices by constructing a comprehensive mediation effect test procedure. The fundamental effect and its internal mechanism of action have been supplemented and verified from investor sentiment. Strengthening the research on economic policy uncertainty and stock price synchronisation may deeply explore the internal mechanism of the listed firms’ stock price changes, help in improving the information production function and information transmission function of the securities market, help in improving the resource allocation capacity of the entire capital market, and then promote the long-term healthy development of China’s capital market. The main findings of this paper are as follows: (1) in China’s stock market, which is driven by noise, the increase of economic policy uncertainty will significantly reduce the synchronisation of stock prices; (2) increased uncertainty about China’s economic policy will fuel the investor sentiment and reduce stock price synchronicity, with investor sentiment playing an intermediary role.
Ferroptosis: A Novel Therapeutic Direction of Spinal Cord Injury
Authors: Zhao Qianlong , Liu Feifei , Zhou Bangyu , Liu Hongzhi , Wang Xiaowei , Li Shaobo
Published: July 2022

An injury to the spinal cord results in a crucial central nervous system event that further causes irreversible impairment or loss of motor, autonomic, and sensory functions. A progressive pathophysiological cascade following spinal cord injury (SCI) includes ischemia/reperfusion injury, oxidative stress, proapoptotic signaling, peripheral inflammatory cell infiltration, and glutamate-mediated excitotoxicity, and regulated cell death. These complex pathological and physiological changes continue to cause cell injury over the long-term and severely limit the efficacy of clinical treatment strategies in restoring the injured nervous system. Ferroptosis is a nonapoptotic, iron-regulated kind of cell death that has recently been discovered. It is distinguished by iron overload-induced toxic lipid peroxidation associated with mitochondrial morphological changes during the cell death process. For example, after SCI, iron overload activates the reactive oxygen species generation, dysregulation of glutathione/glutathione peroxidase 4 (GSH/GPX4) metabolism, and accumulation of lipid peroxides, which cause lipid membrane deterioration and ferroptosis. Conversely, knockout or differential expression of key genes and application of lipid peroxidation inhibitors and iron chelators (e.g., deferoxamine) (e.g., SRS-16-86) can block ferroptosis and promote neuronal repair for functional recovery after SCI. Although the findings of numerous investigations have been confirmed the importance of ferroptosis in several human neurologic sicknesses and its potential in SCI, the mechanism of ferroptosis and its application in SCI has not been elucidated. This review highlights current ferroptosis research and its impact on SCI, as well as the key molecular mechanism of ferroptosis in promoting the recovery from SCI. Understanding ferroptosis’ process and function in SCI could provide useful insight into the treatment and avoidance of such a destructive injury.