bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance Evaluation Model of Short-Term Mutual Funds Based on Return-Variance-Liquidity
Authors: Tian Ye , Wan Guanjiang , Shi Jianing , Liu Yufei , Liu Wenbin , Shen Wanfang
Published: May 2022

In the past, research on evaluating the portfolio efficiency of mutual funds was mostly based on the mean-variance framework proposed by Markowitz. However, for Chinese short-term mutual funds (CSTMF), short-term mutual funds with different lock-up periods will automatically roll over after the lock up period to restart the funds unless instructed to terminate. By reducing the liquidity of their investments, the lock-up period generates an opportunity cost for investors. The liquidity impacts of different CSTMFs will depend on their lock-up periods. In this paper, we evaluate the portfolio efficiency of the funds by justifying using the lock-up period as a measurement to measure the liquidity risk faced by the investors from the perspective of investors. Therefore, here, we propose to use the return-variance-liquidity framework to evaluate the performance of the funds. Furthermore, we select 28 CSTMF funds to conduct empirical analysis with appropriate DEA models. Firstly, we carry out some comparisons with the traditional mean-variance framework. The results show that the length of the lock-up periods has a significant impact on the fund’s performance, which has important guidance for the investment strategy. Finally, we conduct the benchmarking analysis for the 28 funds and introduce a new DEA model, present how to reduce liquidity risk under the premise of given return and variance, and provide valuable investment advices by combining these with sensitivity analysis. Overall, there are three conclusions: (1) most inefficient funds can be improved using portfolios consisting of funds with shorter lock-up period. (2) For some inefficient funds with shorter lock-up period, the current return and variance levels can be achieved by a portfolio. (3) Among the funds with higher efficiency scores, funds with shorter lock-up period have higher stability.
Integrating ANFIS and Qt Framework to Develop a Mobile-Based Typhoon Rainfall Forecasting System
Authors: Lin Shiu-Shin , Zhu Kai-Yang , Wang Jun-Yuan , Liao Ying-Po
Published: May 2022

Machine learning methods such as Adaptive Network-Based Fuzzy Inference System (ANFIS) have been widely employed in intelligent urban storm water disaster warning for the purpose of smart city. However, there exists lack of research proposed for applying ANFIS and mobile application (App) to reach the purpose of smart city. In order to accomplish the goal, the study integrates ANFIS and Qt Framework to develop a Typhoon Rainfall Forecasting System to real-time typhoon rainfall forecast via a mobile device. The Service is first built by applying cluster analysis to typhoon data (Tamsui Weather Station of Taiwan) during June 1967 and November 2020 to classify the data into four groups and then applying the ANFIS to construct the Service with data in each group. The fuzzy rule of ANFIS is established by grid partition method. Both the Service and App employ Qt Framework as the cross-operating development tool, and the App is transformed to a smart mobile device App of different platforms. The simulated results show the following: (1) Taking the example of typhoon Nakri in group 1, the lowest root mean square error (7.898 mm) and the lowest computation time (178 sec) were obtained for training with 1000 steps and three membership functions. (2) Using the optimal parameters of the typhoon belonging to that group can obtain better prediction results. The developed typhoon rainfall forecasting system App in the supplementary information demonstrates that the user can use the smart mobile device for real-time typhoon forecasting at the most three hours ahead easily.
Wideband Low-Profile 8 × 8 MIMO Antenna Based IFA Pair for Ultrathin 5G Smartphones
Authors: Zhou Hui , Wu Di , Zhu Mingmin , Qiu Yang , Yu Guoliang , Zhou Hao-Miao
Published: May 2022

In this paper, a wideband 8 × 8 MIMO antenna is proposed. The proposed antenna can realize the low profile of 4 mm and the 3.18–4.40 GHz broadband coverage only by adjusting the ground edge structure of the deformed inverted-F antenna. Based on the original antenna, the 5G new radio (NR) band n77 (3.3–4.2 GHz) can be covered without adding any structure. In addition, the coupling between the antenna elements has also been improved, decreasing from −9.7 dB to −13.37 dB. A dual-element IFA pair is simulated, fabricated, and measured, the results show the bandwidth of 3.07–4.43 GHz, and the isolation of −13.89 dB can be achieved. An eight-element MIMO antenna is formed by placing four sets of antenna pairs along the two long edges of the substrate. The experimental results show that the bandwidth is 3.18–4.40 GHz, the isolation between any two ports is better than −12.25 dB, and the total efficiency is 61.14%–93.97%. By placing the planar antenna vertically, the ground clearance of the antenna can be reduced to zero, and the performances are similar to the planar MIMO antenna. The proposed MIMO antenna has a good profile and efficient radiation performance compared with the other works, so it has an important application value in ultrathin 5G smartphones.
Analysis of TV Film Scoring and Communication Efficiency Based on Artificial Intelligence
Authors: Xian Yue
Published: May 2022

The spread of TV movies has brought free participation in film reviews. Movies have brought freedom of time and space for comments. You can publish your own comments at any time without time restrictions. You can publish comments on forums, blogs, vote, and various websites, film companies, and even individuals to hold special online film competitions or film review activities. With the gradual maturity of film types, a series of subtypes such as artificial intelligence, interstellar civilization, and alien species have been derived. These contents have different emphases on type characteristics and narrative characteristics, although the subtypes of films have some common characteristics in essence. Based on artificial intelligence, this paper studies the scoring analysis and communication efficiency of TV and film. By adjusting the recommendation through user feedback, the average absolute error has been improved by 18% and the accuracy has been improved by 24%. Moreover, through four rounds of feedback, the accuracy of online computing recommendation for new users is very close to that for old users. This shows the superiority of artificial intelligence algorithm in solving the problems of cold start and complex interest recommendation. It can be predicted that artificial intelligence will become a unique cultural phenomenon. Its cultural connotation is all inclusive and worthy of continuous research and exploration by future generations. Artificial intelligence appears more and more frequently in science fiction films and presents more rich and detailed diversity and complexity.
[Retracted] Left Heart Failure Caused by Capacity Overload in Peritoneal Dialysis Patients
Authors: Zhang Lin , Zhang Xiaocui , Xue Song
Published: May 2022

Background. This study sets out to investigate the incidence of acute left ventricular failure in peritoneal dialysis patients with different volume loads and to analyze the related risk factors for LVF in these patients. Methods. This study involved patients who received peritoneal dialysis in our hospital between September 2018 and January 2021. The demographic data and biochemical indicators of the patients were collected. The bioimpedance analysis method was used to determine the volume overload [overhydration (OH)] level of patients, and cardiac color Doppler ultrasound was used to detect changes in their cardiac structure. According to the LVF diagnostic criteria of symptoms and laboratory tests, the patients were divided into the LVF and non‐LVF groups and then divided according to their OH level into the normal volume (OH ≤1.1 L) and volume overload (OH >1.1 L) groups. The incidence of LVF in was analyzed in patients with different volume loads, and logistic regression was used to identify the risk factors for LVF. Results. Among the 226 peritoneal dialysis patients enrolled in this study, 125 patients (55.3%) had LVF. The normal volume group (n = 68, 30.1%) included 22 patients (32.4%) with LVF, and the volume overload group (n = 158, 69.9%) included 84 patients (53.2%) with LVF. In the volume overload group, 74 patients (46.8%) had subclinical volume overload, including 35 patients (47.3%) with LVF, and 84 patients (53.2%) had clinical volume overload, including 65 patients (77.4%) LVF. Multivariate logistic regression analysis revealed a high OH level (OR = 1.862, 95% CI: 1.353–2.668, P < 0.001) and low hemoglobin level (OR = 0.845, 95% CI: 0.721–0.980, P = 0.008) to be independent risk factors for LVF. Conclusions. LVF has a high incidence in peritoneal dialysis patients, especially those with volume overload. A high OH level and low hemoglobin level are independent risk factors for LVF.
UAV Routing Protocol Based on Link Stability and Selectivity of Neighbor Nodes in ETX Metrics
Authors: Huang Jinze , Zan Fengbiao , Liu Xin , Chen Da
Published: May 2022

With the extensive application of UAVs in various fields, it becomes more important to design a routing protocol that ensures stable transmit between UAV groups. This is because UAV groups are densely packed, move fast, and communication links are fragile. Aiming at the intensive and highly maneuverable UAV group, the AODV-NLS-ETX—a routing protocol based on the link stability of neighbor nodes—is proposed on the basis of the ETX metric based AODV protocol. The protocol is simulated and compared with other protocols. The simulation results show that AODV-NLS-ETX is superior to other protocols in packet delivery rate and throughput under high shift speed, dense nodes, and high routing overhead. It can effectively reduce the high delay brought by the ETX mechanism. The delay is the most stable and is not easy to cause network congestion. It can be better applied to dense and highly mobile unmanned aerial vehicles.
Compressive Strength Prediction Using Coupled Deep Learning Model with Extreme Gradient Boosting Algorithm: Environmentally Friendly Concrete Incorporating Recycled Aggregate
Authors: Falah Mayadah W. , Hussein Sadaam Hadee , Saad Mohammed Ayad , Ali Zainab Hasan , Tran Tan Huy , Ghoniem Rania M. , Ewees Ahmed A.
Published: May 2022

The application of recycled aggregate as a sustainable material in construction projects is considered a promising approach to decrease the carbon footprint of concrete structures. Prediction of compressive strength (CS) of environmentally friendly (EF) concrete containing recycled aggregate is important for understanding sustainable structures’ concrete behaviour. In this research, the capability of the deep learning neural network (DLNN) approach is examined on the simulation of CS of EF concrete. The developed approach is compared to the well‐known artificial intelligence (AI) approaches named multivariate adaptive regression spline (MARS), extreme learning machines (ELMs), and random forests (RFs). The dataset was divided into three scenarios 70%‐30%, 80%‐20%, and 90%‐10% for training/testing to explore the impact of data division percentage on the capacity of the developed AI model. Extreme gradient boosting (XGBoost) was integrated with the developed AI models to select the influencing variables on the CS prediction. Several statistical measures and graphical methods were generated to evaluate the efficiency of the presented models. In this regard, the results confirmed that the DLNN model attained the highest value of prediction performance with minimal root mean squared error (RMSE = 2.23). The study revealed that the highest prediction performance could be attained by increasing the number of variables in the prediction problem and using 90%‐10% data division. The results demonstrated the robustness of the DLNN model over the other AI models in handling the complex behaviour of concrete. Due to the high accuracy of the DLNN model, the developed method can be used as a practical approach for future use of CS prediction of EF concrete.
On Fuzzy Derivation of Ideals of BF‐Algebras
Authors: Dejen Gerima Tefera , Gebrekidan Tsige
Published: May 2022

The concept of fuzzy derivation of ideals of BF algebra is introduced. In addition, fuzzy left derivation of ideals of BF‐algebras and fuzzy right derivation of ideals of BF‐ algebra are discussed. We also investigated fuzzy left (right) derivation of Cartesian product of ideals of BF‐algebra. We initiated the idea of level cut in fuzzy derivation of ideals of BF‐algebra and showed that the intersection of any set of left (right) fuzzy derivations of ideals of BF‐algebra is also fuzzy left (right) derivation of ideals of BF‐algebra.
Effect of Dietary Polyherbal Mixture on Growth Performance, Haemato-Immunological Indices, Antioxidant Responses, and Intestinal Morphometry of African Catfish, Clarias gariepinus
Authors: Fawole Femi J. , Yisa Rihanat O. , Jayeoba Oluwole O. , Adeshina Ibrahim , Ahmed Akeem O. , Emikpe Benjamin O.
Published: May 2022

A 56-day feeding trial was conducted to evaluate the dietary effect of Nigeria polyherbal mixture (PHB) on growth, haemato-immune parameters, antioxidant enzyme activities, and intestinal morphometry of African catfish, Clarias gariepinus. Four diets were formulated with PHB powder at inclusion of 0 g/kg (control), 0.5 g/kg (PHB 0.5), 1.0 g/kg (PHB 1.0), and 2.0 g/kg (PHB 2.0) and fed to African catfish (

6.32
±
0.02
 
g

/fish, 15 fish/50 L tank) in triplicates. Fish fed PHB 2.0 recorded higher final weight, weight gain, and specific growth rate (

p
<
0.05

) compared to the control. There were no statistical differences (

p
>
0.05

) in feed conversion ratio and protein efficiency ratio among the dietary groups. The haematological profile indicates that the fish fed PHB-1.0 had higher Hb, RBCs count, and Hct, and blood performance (

p
<
0.05

) compared to the control. ALT levels were found higher in the control and the lowest values recorded in PHB groups (

p
<
0.05

); however, AST did not differ significantly among the groups (

p
>
0.05

). The highest heterophil counts and respiratory burst activity were recorded in PHB-1.0 and PHB-0.5 and PHB-2.0, respectively, while a numerically improved total immunoglobulin value was recorded in PHB-0.5 compared to the control (

p
>
0.05

). Antioxidant enzymes such as superoxide dismutase and catalase had a significant improvement in fish fed PHB-based diet compared to the control (

p
<
0.05

), while glutathione peroxidase showed no statistical differences between the groups (

p
>
0.05

). Intestinal morphometric measurements showed that the fish fed PHB-1.0 had the highest villus height, area of absorption, and villus height/cryptal depth ratio compared to the control. Muscle thickness increased (

p
<
0.05

) with increasing PHB level with the highest value recorded PHB-2.0. In conclusion, dietary PHB could improve growth, blood profile, immunity, antioxidant enzyme capacity, and intestinal morphometry of African catfish without any significant alteration in the liver function enzymes.
A Comprehensive Study on the Effect of Dimethyl Carbonate Oxygenate and EGR on Emission Reduction, Combustion Analysis, and Performance Enhancement of a CRDI Diesel Engine Using a Blend of Diesel and Prosopis juliflora Biodiesel
Authors: Ramesh T. , Sathiyagnanam A.P. , Poures Melvin Victor De , Murugan P.
Published: May 2022

This paper examines the combined effects of ignition improvers (DMC) and EGR on the CRDI small single-cylinder diesel engine’s performance, combustion, and emissions. In this experimentation, 20% (B20) optimal mix of Prosopis juliflora oil biodiesel (PJOB) and 5 ml dimethyl carbonate (DMC) additive was used as test fuel. The fuel handling CRDI system factors such as injection pressure set at 600 bar and injection timing set to 21 (bTDC) with a compression ratio of 16 were considered for the study. For the EGR trial, 20% of the exhaust gas was recirculated under various BMEP circumstances. The test was performed with and without EGR and DMC additive conditions like (i) diesel @ 0% EGR, (ii) diesel + 5 ml DMC @ 20% EGR, (iii) B20 @ 0% EGR, and (iv) B20 + 5 ml DMC @ 20% EGR at the engine power output. The amalgamation of dimethyl carbonate (DMC) additives and EGR reduces NOx and smoke while increasing CO and HC emissions. In addition, the DMC additive and EGR improve thermal efficiency slightly. The overall clubbing of DMC additive and EGR rate indicates better performance for the selected factors than a CRDI engine with a six-hole conventional mechanical fuel injection system. The outcome of the work clearly demonstrates that both the 5 ml DMC additive and the 20% EGR rate of the B20 blend show optimum values of BTE, BSFC, and EGT of 32.93%, 0.27 kg/kw·hr, and 310.89°C, which is closer to diesel. Factors of combustion like cylinder peak pressure (CPP) and heat release rate (HRR) are 70.93 bar and 58.13 J/deg. The tailpipe exhaust of NOx and smoke is 1681 ppm and 31.30 (% vol), which is less than diesel. The HC and CO levels are 93 ppm and 0.38 (% vol), respectively, which are significantly higher than diesel fuel.
Duchesnea indica Extract Ameliorates LPS-Induced Septic Shock in Mice
Authors: Lee Yuan Yee , Yuk Heung Joo , Saba Evelyn , Kim Sung Dae , Kim Dong-Seon , Kopalli Spandana Rajendra , Oh Jae-Wook , Rhee Man Hee
Published: May 2022

Objective. Duchesnea indica has been reported for its anti-inflammatory properties. However, its efficacy in sepsis has yet to be reported. In this study, we studied the ability of Duchesnea indica extract (DIE) to rescue mice from septic shock and sepsis. Methods. In vitro studies included the measurement of secreted nitric oxide, cell viability, gene and protein expression via real-time polymerase chain reaction and western blot, and confocal microscopy in RAW 264.7 cells. In vivo studies include a model of septic shock and sepsis in BALB/c mice induced by a lethal and sub-lethal dose of lipopolysaccharide (LPS). Results. DIE suppressed the expression of proinflammatory cytokines induced by LPS and prevented the translocation of NFκB into the nucleus of RAW 264.7 cells. It also prevented reactive oxygen species damage induced by LPS in murine bone marrow-derived macrophages. Models of sepsis and septic shock were established in BALB/c mice and DIE-rescued mice from septic shock. DIE also reversed the increase in tumor necrosis factor-α and nitrite levels in the serum of mice induced with sepsis. DIE also prevented the translocation of NFκB from the cytosol into the nucleus in murine lungs. Histopathological damage induced by sepsis was reversed in the testis, liver, and lungs of mice. Conclusion. In conclusion, DIE is a suitable candidate for development as a therapeutic agent for sepsis.
Hypoxia Promotes Glioma Stem Cell Proliferation by Enhancing the 14-3-3β Expression via the PI3K Pathway
Authors: Cao Weidong , Zhou Qiang , Wang Hongwei , Rao Wei , Cheng Gang , Wang Peng , Guo Shengli , Ren Bin , Zhang Jianning
Published: May 2022

Glioma is a serious fatal type of cancer with the shorter median survival period and poor quality of living. The overall 5-year survival rate remains low due to high recurrence rates. Glioma stem cells (GSCs) play the important roles in the development of gliomas. Examination of the numerous biomarkers or cancer-associated genes involved in the development or prevention of glioma may therefore serve the discovery of novel strategies to treat patients with glioma. Hypoxia induced by using CoCl2 application and 14-3-3β protein knockdown by specific small interfering RNA transfection were performed in GSCs both in vitro and in vivo to observe their role in glioma progression and metastasis occurrence by using western blot analysis and MTT assay. The results demonstrated that CoCl2 application enhanced the 14-3-3β protein expression and mRNA levels via the PI3K pathway in GSCs. Furthermore, hypoxia promoted GSC cell proliferation and activated the expression of proliferating cell nuclear antigen, which was inhibited following 14-3-3β knockdown. In addition, tumor growth in mice was enhanced by CoCl2 application but reversed following 14-3-3β knockdown, which also enhanced GSC cell apoptosis. In conclusion, the present study demonstrated that hypoxia promoted glioma growth both in vitro and in vivo by increasing the 14-3-3β expression via the PI3K signaling pathway. 14-3-3β and HIF-1α may therefore be considered as the potential therapeutic target to treat patients with glioma.
Climatic Factors Associated with Heavy Rainfall in Northern Vietnam in Boreal Spring
Authors: Nguyen Van Thang , Nguyen Dang Mau , Mai Van Khiem , Trinh Hoang Duong , Duong Van Kham , Tran Thanh Thuy , Vu Quoc Tuan , Thai Thi Thanh Minh
Published: May 2022

Heavy rainfall occurs frequently in Northern Vietnam and causes severe floods and landslides. Heavy rainfall not only appears in rainy seasons (May–October) but also regularly occurs in spring (February–April). This study is devoted to identifying the climatic factors that influence the variation of rainfall, particularly heavy rainfall in Northern Vietnam in the dry season. Analysis based on the observed rainfall, PERSIANN satellite rainfall data, and ERA5 reanalysis reveals that spring should not be considered a dry season, but the first period of a rainy season in Northern Vietnam. Spring rainfall is caused by collaborative effects of cold surge, subtropical high, and the deepening of the low pressure over the Northeastern Tibetan Plateau and Bay of Bengal (BOB). Based on the composite analysis of heavy rainfall events in Northern Vietnam in the transitional season, two heavy rainfall patterns are recognized. The first is related to the southward movement of a meso-scale vortex and the cold surge, while the second one is induced by the interaction of cold surge and the deepening of an upper-level trough.
The Optimization Design of the Accurate Community Navigation Map for the Terminal Distribution to Promote the Development of E-Commerce New Retail
Authors: Liu Lijin
Published: May 2022

In recent years, the development of e-commerce new retail formats is in full swing, and the terminal distribution has become a hot research topic under the background of new retail. The accuracy of the community navigation map is related to the low cost and high efficiency of terminal distribution and then affects the development of new e-commerce retail. However, in large communities, the existing navigation map software can only locate the main entrance of the community, and there is a lack of effective positioning for the location of buildings. Therefore, based on the existing navigation map, this paper expects to correct its application defects and carry out optimization design from the design principle, design idea, product function, product customization, and product application effect, so as to make the community navigation more accurate, faster, and more efficient, to help the low cost and efficient development of door-to-door distribution under the new retail of e-commerce.
5G Converged Network Resource Allocation Strategy Based on Reinforcement Learning in Edge Cloud Computing Environment
Authors: Li Xuezhu
Published: May 2022

Aiming at the problem that computing power and resources of Mobile Edge Computing (MEC) servers are difficult to process long-period intensive task data, this study proposes a 5G converged network resource allocation strategy based on reinforcement learning in edge cloud computing environment. n order to solve the problem of insufficient local computing power, the proposed strategy offloads some tasks to the edge of network. Firstly, we build a multi-MEC server and multi-user mobile edge system, and design optimization objectives to minimize the average response time of system tasks and total energy consumption. Then, task offloading and resource allocation process is modeled as Markov decision process. Furthermore, the deep Q-network is used to find the optimal resource allocation scheme. Finally, the proposed strategy is analyzed experimentally based on TensorFlow learning framework. Experimental results show that when the number of users is 110, final energy consumption is about 2500 J, which effectively reduces task delay and improves the utilization of resources.
Research on Online Rapid Sorting Method of Waste Textiles Based on Near-Infrared Spectroscopy and Generative Adversity Network
Authors: Hu Jinquan , Yang Huihua , Zhao Guoliang , Zhou Ruizhi
Published: May 2022

In this paper, aiming at the application of online rapid sorting of waste textiles, a large number of effective high-content blending data are generated by using generative adversity network to deeply mine the combination relationship of blending spectra, and A BEGAN-RBF-SVM classification model is constructed by compensating the imbalance of negative samples in the data set. Various experiments show that the model can effectively extract the spectrum of pure textile samples. The classification model has high robustness and high speed, reaches the performance of similar products in the world, and has a broad application market.
The Study of Immersive Physiology Courses Based on Intelligent Network through Virtual Reality Technology in the Context of 5G
Authors: Ma Ling , Zhang Wei , Lv ManJin , Li JingNing
Published: May 2022

The current boom in Internet technology has paved the way for the research and evolution of various technologies related to it. One such technology is immersive virtual reality (IVR). Immersive technology is referred to as creating a reality-like experience by combining the physical world with digital reality. There are two main types of immersive technologies. Immersion in virtual reality is the perception of being physically present in an artificially created world. Perception is artificially created by images, videos, sounds, or other stimuli with the help of a virtual reality (VR) system that the user is connected to. VR uses rendered computer-generated simulations and results in a complete sense of immersion. Immersive virtual reality (immersive VR) refers to engaging users in an artificial environment that replaces their natural surroundings and fully engages them with the artificially created environment. In this research, we will research immersive physiology courses based on artificial intelligence combined with wireless network VR technology in the context of 5G. The teaching methodology has been kept up-to-date along with the technology. Teaching physiology courses also incorporate new technologies like immersive technologies. The use of technology in anatomy and physiology courses allows students to view structures and physiological concepts in a realistic environment. Virtual dissection in 3D is available with a life-like artificial environment. Students can attend the classes with VR headsets, laptops, or smartphones to experience immersive and interactive 3D classes. This advanced technology enhances and empowers the students to learn from real-life situations like those available in the classes. In this research, CNN with AI is proposed for effective learning of physiology courses. This algorithm is compared with the existing NNGA, KNN, and Random Forest, and it is observed that the proposed model has obtained an accuracy of 99%.
Improving Fluency of Spoken Mandarin for Nonnative Speakers by Prosodic Boundary Prediction Based on Deep Learning
Authors: Yang Hongwu , Li Dong , Yan Yajing
Published: May 2022

Nonnative Mandarin speakers always have some unnatural pauses when speaking Mandarin due to their native pronunciation habits. Accurately predicting the prosodic structure of Chinese sentences is the key to improving fluency in Mandarin for nonnative speakers. This paper investigated the influence of the Chinese prosodic boundaries on the Mandarin spoken by international students. First, we proposed a new method to predict the prosodic word and prosodic phrase boundaries from Chinese sentences to obtain the prosodic boundaries automatically. Then, we used the predicted results to improve the Mandarin spoken fluency of international students. To train the prosodic boundary prediction model, we firstly constructed a Chinese prosodic boundary corpus that includes 100,000 Chinese sentences with manually labeled prosodic boundaries under the guidance of a linguist. We also proposed an end-to-end Chinese prosodic boundary prediction model based on the sequence-to-sequence model with a new feature named number of syntax hierarchy (NSH). Finally, we assess the fluency score of Mandarin using 1300 utterances recorded by six international students and a native Mandarin speaker. The utterances are recorded without/with the predicted prosodic boundaries. The experimental results show that the

F
1

scores of the prosodic word prediction model and the prosodic phrase prediction model are 98.14% and 85.24%, respectively. The fluency assessment results show that the fluency score labeled with the prosodic boundaries is higher than the fluency score of the international students when they read freely. The improvement of the score is between 7 and 16. Therefore, our method can be applied to the Mandarin education system to improve the spoken Mandarin fluency of nonnative speakers.
Marine-Derived Stichloroside C2 Inhibits Epithelial–Mesenchymal Transition and Induces Apoptosis through the Mitogen-Activated Protein Kinase Signalling Pathway in Triple-Negative Breast Cancer Cells
Authors: Cui Chuang , Ding Chen-Huan , Liu Fang-Fang , Lu Jing-Rong , Zheng Shi-Yun , Lin Hou-Wen , Zhu Wei-Kang , Yang Fan , Li He
Published: May 2022

Background. Triterpenoid saponins from sea cucumbers exhibit significant antitumour, antifungal, and antibacterial activities. However, the associated molecular mechanisms have yet to be elucidated. In this study, we screened and explored the antitumour activity and underlying mechanisms of triterpenoid saponins isolated from Thelenota ananas. Methods. We isolated and purified sea cucumber saponins, determined their chemical structures, and confirmed their function in vitro. We also screened and explored the antitumour activity and underlying mechanisms of triterpenoid saponins isolated from Thelenota ananas. Results. Four saponins were discovered from sea cucumber Thelenota ananas collected from the South China Sea. We found that stichloroside C2 (STC2) inhibited the proliferation and clonogenesis of the human triple-negative breast cancer (TNBC) cell line MDA-MB-231 and mouse TNBC cell line 4 T1 in a dose-dependent manner and induced apoptosis and cycle arrest in these two TNBC cell lines. STC2 induced DNA damage in two TNBC cell lines and significantly increased the protein expression level of the DNA double-strand break marker γ-H2AX. STC2 downregulated the protein expression levels of phosphorylated cyclin-dependent kinase 1 (CDK1), cyclin B1, CDK2, and cyclin A2 in MDA-MB-231 and 4 T1 cells. STC2 upregulated Bax and cleaved PARP protein expression in two types of breast cancer cells. In addition, STC2 promoted E-cadherin expression; inhibited vimentin expression; upregulated the phosphorylation levels of the mitogen-activated protein kinase (MAPK) signalling pathway-related proteins p38, JNK, and ERK1/2; and downregulated Akt phosphorylation. Conclusions. STC2 exerts anti-TNBC activity, inhibits epithelial–mesenchymal transition (EMT), and induces apoptosis by regulating the cell cycle, EMT-related proteins, and MAPK signalling pathway.
[Retracted] On Multiplicative Topological Invariants of Magnesium Iodide Structure
Authors: Zhang Zhiqiang , Ali Haidar , Naseem Asim , Babar Usman , Zhang Xiujun , Ali Parvez
Published: May 2022

In recent times, the applications of graph theory in molecular and chemical structure research have far exceeded human expectations and have grown exponentially. In this paper, we have determined the multiplicative Zagreb indices, multiplicative hyper‐Zagreb indices, multiplicative universal Zagreb indices, sum and product connectivity of multiplicative indices, multiplicative atom‐bond connectivity index, and multiplicative geometric‐arithmetic index of a famous crystalline structure, magnesium iodide (MgI2).
Real-Time Control of Intelligent Prosthetic Hand Based on the Improved TCN
Authors: Liu Xiaoguang , Wang Jiawei , Han Tingwen , Lou Cunguang , Liang Tie , Wang Hongrui , Liu Xiuling
Published: May 2022

Intelligent prosthetic hand is an important branch of intelligent robotics. It can remotely replace humans to complete various complex tasks and also help humans to complete rehabilitation training. In human-computer interaction technology, the prosthetic hand can be accurately controlled by surface electromyography (sEMG). This paper proposes a new multichannel fusion scheme (MSFS) to extend the virtual channels of sEMG and improve the accuracy of gesture recognition. In addition, the Temporal Convolutional Network (TCN) in deep learning has been improved to enhance the performance of the network. Finally, the sEMG is collected by the Myo armband and the prosthetic hand is controlled in real time to validate the new method. The experimental results show that the method proposed in this paper can improve the accuracy of the control intelligent prosthetic hand, and the accuracy rate is 93.69%.
Effect of Programmed Nursing Plan Based on Thinking Map Guidance Mode on Hemodynamics and Intestinal Function Recovery of Patients Undergoing Endoscopic Retrograde Cholangiopancreatography
Authors: Lu Yan , Wang Feifei
Published: May 2022

ERCP is an effective method for the diagnosis and treatment of pancreatic and biliary diseases. With the improvement of endoscopes by researchers and the intubation and angiography technologies of medical workers, the role of ERCP in the diagnosis and treatment of pancreatic and biliary diseases has become increasingly important. Although ERCP is a minimally invasive diagnostic technique, it still falls into the category of surgery, and thus the physical and psychological dysfunction of patients undergoing ERCP caused by various factors such as surgery cannot be ignored. This study explored the effects of the procedural nursing plan based on the thinking map guidance mode on hemodynamics and intestinal function recovery of ERCP patients. The results showed that this plan could reduce the effects of ERCP on hemodynamics of patients, promote intestinal function recovery, relieve their bad psychology, reduce postoperative complications, and help to improve patients’ satisfaction with the nursing work, and it was worthy of promotion.
Effect of Ethyl Acetate Fraction from Eucommia ulmoides Leaves on PM2.5-Induced Inflammation and Cognitive Dysfunction
Authors: Kim Min Ji , Kang Jin Yong , Kim Jong Min , Moon Jong Hyun , Lee Hyo Lim , Jeong Hye Rin , Go Min Ji , Lee Uk , Heo Ho Jin
Published: May 2022

This study aimed to evaluate the protective effect of the ethyl acetate from Eucommia ulmoides leaves (EFEL) on PM2.5-induced cognitive impairment in BALB/c mice. EFEL improved PM2.5-induced cognitive decline by improving spontaneous alternative behavioral and long-term memory ability. EFEL increased ferric reducing activity power (FRAP) in serum. In addition, EFEL increased superoxide dismutase (SOD) and reduced glutathione (GSH) contents and inhibited the production of malondialdehyde (MDA) in lung and brain tissues. EFEL also restored the mitochondrial function by regulating reactive oxygen species (ROS) production, mitochondrial membrane potential (MMP) level, and ATP level in lung and brain tissues. EFEL ameliorated the cholinergic system by regulating the acetylcholine (ACh) content and acetylcholinesterase (AChE) activity in the brain tissue and the expression of AChE and choline acetyltransferase (ChAT) in the whole brain and hippocampal tissues. EFEL reduced PM2.5-induced excessive expression of inflammatory protein related to the lung, whole brain, olfactory bulb, and hippocampus. Physiological compounds of EFEL were identified as 5-O-caffeolyquinic acid, rutin, quercetin, and quercetin glycosides. As a result, EFEL has anti-inflammation and anti-amnesic effect on PM2.5-induced cognitive impairment by regulating the inflammation and inhibiting the lung and brain tissue dysfunction, and its effect is considered to be due to the physiological compounds of EFEL.
Staphylococcus hominis Infective Endocarditis Presenting with Embolic Splenic and Renal Infarcts and Spinal Discitis
Authors: Vasconcellos David , Weng Bruce , Wu Patrick , Thompson Gary , Sutjita Made
Published: May 2022

Staphylococcus hominis (S. hominis) is a Gram-positive, coagulase-negative bacteria that occurs as a normal commensal organism on the skin and may rarely cause native valve endocarditis (NVE). We present a 62-year-old male with type 2 diabetes mellitus, coronary artery disease, and hypertension presenting with fever and abdominal pain. CT (computerized tomography) of the abdomen revealed splenic and renal infarcts; further imaging with MRI (magnetic resonance imaging) revealed enhancements consistent with discitis in T5-6 and L1-2. Three sets of blood cultures were positive for S. hominis sensitive to methicillin on antimicrobial susceptibility tests, and echocardiogram showed posterior mitral valve vegetation. The patient was initially treated with 10 weeks of nafcillin IV (intravenous) 2 g q4 hours. He had recurrent bouts of S. hominis bacteremia that was treated with IV vancomycin. His clinical course was complicated by new-onset atrial fibrillation with rapid ventricular response and congestive heart failure. Once bacteremia was cleared, his infective endocarditis was successfully definitively treated with mitral valve replacement and tricuspid repair.
Generalization Contractive Mappings on Rectangular
b
-Metric Space
Authors: Patil Jayshree , Hardan Basel , Hamoud Ahmed A. , Bachhav Amol , Emadifar Homan , Günerhan Hatira
Published: May 2022

In this paper, we introduce new coincidence fixed point theorems for generalized

ϕ
,
ψ

-contractive mappings fulfilling kind of an admissibility provision in a Hausdorff

b

-rectangular metric space with the support of C-functions. We applied our results to establish the existence of a solution for some integralitions. Finally, an example is presented to clarify our theorem.
Network Extraction and Analysis of Character Relationships in Chinese Literary Works
Authors: Fan Chao , Li Yu
Published: May 2022

Character relationships in literary works can be interpreted and analyzed from the perspective of social networks. Analysis of intricate character relationships helps to better understand the internal logic of plot development and explore the significance of a literary work. This paper attempts to extract social networks from Chinese literary works based on co-word analysis. In order to analyze character relationships, both social network analysis and cluster analysis are carried out. Network analysis is performed by calculating degree distribution, clustering coefficient, shortest path length, centrality, etc. Cluster analysis is used for partitioning characters into groups. In addition, an improved visualization method of hierarchical clustering is proposed, which can clearly exhibit character relationships within clusters and the hierarchical structure of clusters. Finally, experimental results demonstrate that the proposed method succeeds in establishing a comprehensive framework for extracting networks and analyzing character relationships in Chinese literary works.
Comparing Long-Term Survival Outcomes for Muscle-Invasive Bladder Cancer Patients Who Underwent with Radical Cystectomy and Bladder-Sparing Trimodality Therapy: A Multicentre Cohort Analysis
Authors: Qiu Junlan , Zhang Haifeng , Xu Dongkui , Li Lin , Xu Lingkai , Jiang Yiqing , Wen Tao , Lu Shun , Meng Fang , Feng Lin , Shu Xiaochen
Published: May 2022

Background. Although radical cystectomy (RC) is the clinical practice guideline-recommended treatment of muscle-invasive bladder cancer (MIBC), bladder-sparing trimodality therapy (TMT) has emerged as a valid treatment option. Findings comparing the survival outcomes for MIBC patients who underwent RC and TMT are inconclusive. Objective. We designed a large hospital-based multicohort study to compare the effectiveness of TMT with RC. Methods. Information on deaths was jointly retrieved from EMR (electronic medical record), cause of death registry, and chronic disease surveillance as well as study-specific questionnaire. To avoid the systematical difference between patients who received two modalities, RC-MIBC cohort was propensity score-matched to TMT-MIBC cohort, and the Cox proportional hazard regression was used to calculate the overall survival (OS) and disease-specific survival (DSS). Results. There were 891 MIBC patients treated with RC and another 891 MIBC patients who underwent with TMT in the propensity score matching. Comparable effectiveness between two modalities was observed for DSS (HR, 1.20; 95% confidence interval (CI), 0.94 to 1.49) and OS (HR, 1.17; 95% CI, 0.91 to 1.43) according to multiple adjustment after a median follow-up of approximately 9.3 years. However, a relatively higher mortality rate around 5 years after TMT treatment was found compared to RC (HR, 1.26; 95% CI, 1.01 to 1.53). The respective 5-year OS rates were 69% and 73% for TMT cohort and RC cohort, respectively. Conclusions. Our findings supported that MIBC patients with TMT yielded survival outcomes comparable to MIBC patients who underwent RC overall. Treatment options should be suggested considering patients’ age and willingness.
Intelligent Classification Method of Archive Data Based on Multigranular Semantics
Authors: Jiang Xiaobo
Published: May 2022

With the rapid development of information technology, the amount of data in various digital archives has exploded. How to reasonably mine and analyze archive data and improve the effect of intelligent management of newly included archives has become an urgent problem to be solved. The existing archival data classification method is manual classification oriented to management needs. This manual classification method is inefficient and ignores the inherent content information of the archives. In addition, for the discovery and utilization of archive information, it is necessary to further explore and analyze the correlation between the contents of the archive data. Facing the needs of intelligent archive management, from the perspective of the text content of archive data, further analysis of manually classified archives is carried out. Therefore, this paper proposes an intelligent classification method for archive data based on multigranular semantics. First, it constructs a semantic-label multigranular attention model; that is, the output of the stacked expanded convolutional coding module and the label graph attention module are jointly connected to the multigranular attention Mechanism network, the weighted label output by the multigranularity attention mechanism network is used as the input of the fully connected layer, and the output value of the fully connected layer used to map the predicted label is input into a Sigmoid layer to obtain the predicted probability of each label; then, the model for training: use the multilabel data set to train the constructed semantic-label multigranularity attention model, adjust the parameters until the semantic-label multigranularity attention model converges, and obtain the trained semantic-label multigranularity attention model. Taking the multilabel data set to be classified as input, the semantic-label multigranularity attention model after training outputs the classification result.
Prevalence and Risk Factors of Work-Related Upper Extremity Disorders among University Teaching Staff in Ethiopia, 2021: An Institution-Based Cross-Sectional Study
Authors: Tesfaye Amensisa Hailu , Mekonnen Tesfaye Hambisa , Alemayehu Mekuriaw , Abere Giziew
Published: May 2022

Background. Work-related upper extremity disorders (WRUEDs) are aches, pains, tension, and discomfort in the neck, shoulders, arms, wrists, hands, and fingers. The situation is escalating in educational sectors due to a lousy working environment intertwined with extracurricular deeds. However, empirical evidence focusing on academicians in higher education society is negligible. The purpose of this study is to examine the prevalence and risk factors of WRUEDs among university teaching staff in Ethiopia. Materials and Methods. We conducted a cross-sectional study design from March to April 2021. A sample of 607 academicians were recruited using a stratified sampling technique, and a self-administered structured Nordic Musculoskeletal questionnaire was used to assess upper extremity disorders during the past 12 months. The collected data were entered into EpiData version 4.6 and analyzed using STATA version 14 software. The association between dependent and independent variables was computed with a binary logistic regression. The association was ascertained using an adjusted odds ratio (AOR) with a 95% confidence interval (CI) at a

p

value of <0.05. Results. A total of 607 participants correctly completed the questionnaire (response rate of 95.44%). Age ranges from 21 to 70 with a mean of 32.39 (SD ± 6.80)) years, and the majority (76.28%) of them were males. The prevalence of WRUED during the last 12 months was 59.14% [95% CI (55.1, 63.1)]. There is no significant difference in prevalence between males and females (45.14% versus 14%), respectively; χ2 = 0.001;

p
=
0.974

. Working more than 8 hours per day [AOR: 2.37; 95% CI (1.40, 4.00)], not performing physical exercise [AOR: 2.34; 95% CI (1.6, 3.45)], and job dissatisfaction [AOR: 2.50; 95% CI (1.69, 3.68)] were factors significantly increased the risk of experiencing WRUEDs. Conclusion. This study divulged upper extremity disorder among university teaching staff is pervasive, with more than three-fifth of the academicians were suffering from the condition, and it also indicates that males experienced higher proportions of pain than females. The manifestation of upper extremity disorder was affected by working hours per day, physical activity, and job satisfaction. Optimizing working hours, having a group regular exercise, and proper management of workplace conditions related to job satisfaction are recommended to lessen the condition.