bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation Model of College English Multimedia Teaching Effect Based on Deep Convolutional Neural Networks
Authors: Geng Limei
Published: July 2021

With the acceleration of global integration, the demand for English instruction is increasingly rising. On the other hand, Chinese English learners struggle to learn spoken English due to the limited English learning environment and teaching conditions in China. The advancement of artificial intelligence technology and the advancement of language teaching and learning techniques have ushered in a new era of language learning and teaching. Deep learning technology makes it possible to solve this problem. Speech recognition and assessment technology are at the heart of language learning, and speech recognition technology is the foundation. Because of the complex changes in speech pronunciation, a large amount of speech signal data, the high dimension of speech characteristic parameters, and a large amount of speech recognition and evaluation computation, the large volume of speech signal processing requires higher requirements of hardware and software resources and algorithms. However, traditional speech recognition algorithms, such as dynamic time-warped algorithms, hidden Markov models, and artificial neural networks, have their advantages and disadvantages. They have encountered unprecedented bottlenecks, so it is difficult to improve their accuracy and speed. To solve these problems, this paper focuses on evaluating the multimedia teaching effect of college English. A multilevel residual convolutional neural network algorithm for oral English pronunciation recognition is proposed based on a deep convolutional neural network. The experiments show that our algorithm can assist learners in identifying inconsistencies between their pronunciation and standard pronunciation and correcting pronunciation errors, resulting in improved oral English learning performance.
Combined Ruxolitinib and Venetoclax Treatment in a Patient with a BCR-JAK2 Rearranged Myeloid Neoplasm
Authors: Lap Coen J. , Nassereddine Samah , Liu Min-Ling , Nava Victor E. , Aggarwal Anita
Published: July 2021

Hematological malignancies with a BCR-JAK2 rearrangement have been described only sporadically in the literature over the last three decades. Although most patients suffer from a chronic myeloid neoplasm with marked eosinophilia, the clinical presentation varies significantly and can even manifest as a lymphoid malignancy. In this case report, we present a patient with a therapy-related BCR-JAK2+ myeloid neoplasm with extensive extramedullary disease localizing in the lymph nodes. While treatment with a JAK2 inhibitor (ruxolitinib) was not able to stop disease progression, combination treatment with inhibitors of both JAK2 and BCL2 (venetoclax) resulted in disease control for over 1.5 years. Combining these two inhibitors might be strategic in these patients, not only because BCL2 is a downstream target of JAK/STAT signaling but also because BCL2 is crucial for JAK2 inhibitor resistance. The recent inclusion of JAK2-rearranged malignancies in major classification systems and guidelines emphasizes the importance of not only getting a better understanding of the clinical phenotype of these rare disorders but also of identifying alternative treatment options for patients ineligible for allogeneic stem cell transplantation. Considering the low toxicity of combination treatment with these two small molecule inhibitors, this regimen could be further explored in future studies.
Clinical Significance of Color Ultrasound, MRI, miR-21, and CA199 in the Diagnosis of Pancreatic Cancer
Authors: Yu Jing , Yang Xue , Wu Hongmei , Li Jiansheng
Published: July 2021

Background. To investigate the clinical significance of color ultrasound, magnetic resonance imaging (MRI), miR-21, and CA199 in the diagnosis of pancreatic cancer (PC). Methods. A total of 160 patients with PC admitted to our hospital from April 2018 to February 2021 were included in the PC group, and another 100 patients with benign pancreatic disease during the same period were included in the pancreatic benign disease group. Color ultrasound and MRI were used for imaging examination of the two groups of PC patients, and the sensitivity, accuracy, and specificity of the two methods for preoperative diagnosis of PC were calculated, respectively. A total of 100 healthy people who underwent physical examination during the same period were included in the control group. Serum CA199 levels of the three groups were detected by ELISA assay. The level of serum miR-21 in the three groups was detected by qRT-PCR. A receiver operating curve (ROC) was drawn to analyze and calculate the sensitivity, specificity, and accuracy of the two serum markers and the combination of color ultrasound and MRI in the detection of PC. Results. Serum CA199 and miR-21 levels in the PC group were significantly higher than those in the benign lesion group and control group. CA199 and miR-21 levels in the benign lesion group were higher than those in the control group. Both color ultrasound and MRI showed a higher detection rate for PC, and the sensitivity and accuracy were significantly higher than those of CA199 and miR-21. The sensitivity, specificity, and accuracy of combined detection were 91.88%, 96.00%, and 93.46%, respectively, which were significantly higher than those of single detection. Conclusion. The combined detection of color ultrasound, MRI, miR-21, and CA199 have a high application value in the early diagnosis of PC, which can effectively improve the sensitivity and accuracy of clinical diagnosis, reduce the probability of missed diagnosis and misdiagnosis, and provide a reference for the rational clinical treatment plan and prognosis.
The Partial Role of KLF4 and KLF5 in Gastrointestinal Tumors
Authors: Li Jun-Chen , Chen Qiu-Han , Jian Rui , Zhou Jiang-Rong , Xu Yun , Lu Fang , Li Jun-Qiao , Zhang Hao
Published: July 2021

Background. KLF4 and KLF5 are members of the KLF transcription factor family, which play an important role in many gastrointestinal tumors. To gain a deeper insight into its function and role, bioinformatics was used to analyze the function and role of KLF4 and KLF5 in gastrointestinal tumors. Methods. Data were collected from several online databases. Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN database analysis, Kaplan-Meier Plotter analysis, LOGpc system, the Pathology Atlas, and the STRING website were used to analyze the data. We download relevant data from TCGA and then perform GO enrichment and KEGG enrichment analysis. The effects of KLF5 on gastric cancer cell proliferation were measured by CCK-8 assay. The effect of KLF5 on the expression of CyclinD1 and MMP9 was detected by Western blot. Results. KLF4 and KLF5 were differentially expressed in normal and tumor tissues of the gastrointestinal tract, and their differential expression is related to several genes or pathways. KEGG analysis showed that KLF5 was coexpressed with endocytosis-related genes. KLF5 promotes the proliferation of gastric cancer cells and the expression of metastasis-related molecules. Conclusion. KLF4 and KLF5 are of great significance for developing gastrointestinal tumors and can be used as therapeutic targets.
Effectiveness of Acupuncture in the Treatment of Hyperemesis Gravidarum: A Systematic Review and Meta-Analysis
Authors: Lu Haizhen , Zheng Chengwen , Zhong Yanmei , Cheng Linhao , Zhou Yi
Published: July 2021

Background. Hyperemesis gravidarum (HG) is a common gastrointestinal disease afflicting gravidas. It usually results in hospital admission in early pregnancy. Objective. Through a meta-analysis, this study intended to explore acupuncture’s clinical efficacy in treating HG. Materials and Methods. A comprehensive search of PubMed, the Cochrane Library, EMBASE, Web of Science, China National Knowledge Infrastructure (CNKI), Chinese Biological Medical (CBM), Wanfang Database, and China Science and Technology Journal (VIP) for published clinical randomized controlled trials (RCTs) of acupuncture for treating HG was conducted from the date of database creation to 20th January 2021. We also searched grey literature in four databases: Chinese Cochrane Center, Chinese Clinical Trial Registry, GreyNet International, and Open Grey from their inception to 20th January 2021. Two authors independently screened the literature, extracted data, and evaluated the quality of the literature with Cochrane Handbook 5.1.0 and Review Manager 5.2 software. Review Manager 5.2 and STATA 12.0 software were applied to analyze data. Heterogeneity analysis was performed by the Cochran Chi-square test and I2 statistic. Egger’s tests together with funnel plots were used to identify publication bias. Results. A total of 16 trials covering 1043 gravidas were included. Compared with the conventional treatment, acupuncture had a significantly higher effective rate (OR: 8.11, 95% CI: 5.29∼12.43;

P
<
0.00001

), a higher conversion rate of urine ketone (RR: 1.36, 95% CI: 1.15∼1.60;

P
=
0.0003

), an improvement rate of nausea and vomiting (OR: 26.44, 95% CI: 3.54∼197.31;

P
=
0.001

), and a relatively higher improvement rate of food intake (RR: 1.17, 95% CI: 1.01∼1.36;

P
=
0.04

). Acupuncture also shortened hospitalization time and manifested with a lower pregnancy termination rate and fewer adverse events. Nevertheless, no statistical variation in the improvement of nausea intensity, vomiting episodes, and lassitude symptom, recurrence rate, and serum potassium was observed. Conclusion. Our study suggested that acupuncture was effective in treating HG. However, as the potential inferior quality and underlying publication bias were found in the included studies, there is a need for more superior-quality RCTs to examine their effectiveness and safety. PROSPERO registration number: CRD42021232187.
Nomogram for Predicting Survival in Advanced Gastric Cancer after Neoadjuvant Chemotherapy and Radical Surgery
Authors: Chen Yonghe , Liu Dan , Xiao Jian , Xiang Jun , Liu Aihong , Chen Shi , Liu Junjie , Hu Xiansheng , Peng Junsheng
Published: July 2021

Background. Neoadjuvant chemotherapy (NAC) with subsequent radical surgery has become a popular treatment modality for advanced gastric cancer (AGC) worldwide. However, the survival benefit is still controversial, and prognostic factors remain undetermined. Aim. To identify clinical parameters that are associated with the survival of AGC patients after NAC and radical surgery and to establish a nomogram integrating multiple factors to predict survival. Methods. We reviewed the medical profiles of 215 AGC patients who received NAC and radical resection, and clinical parameters concerning NAC, surgery, pathological findings, and adjuvant chemotherapy were analyzed using a Cox regression model to determine their impact on survival. Based on these factors, a nomogram was developed and validated. Results. The overall 1-year and 3-year survival rates were 85.8% and 55.6%, respectively. Younger age (<60 years old), increased examined lymph nodes (exLNs), successful R0 resection, the achievement of pathological complete response (pCR), and acceptance of adjuvant chemotherapy were positive predictors of survival. The C-index of the established nomogram was 0.785. The area under receiver operating curve (ROC) at 1/3 years of prediction was 0.694/0.736, respectively. The model showed an ideal calibration following internal bootstrap validation. Conclusion. A nomogram predicting survival after NAC and surgery was established. Since this nomogram exhibited satisfactory and stable predictive power, it can be inferred that this is a practical tool for predicting AGC patient survival after NAC and radical surgery.
The Persian Brief Illness Perception Questionnaire: Validation in Patients with Chronic Nonspecific Low Back Pain
Authors: Karimi-Ghasemabad Sarvenaz , Akhbari Behnam , Saeedi Ahmad , Talebian Moghaddam Saeed , Nakhostin Ansari Noureddin
Published: July 2021

Background. Illness perceptions may influence coping behaviors as well as treatment and recovery among patients with chronic pain including low back pain (LBP). These perceptions may vary across different conditions. The Brief Illness Perception Questionnaire (BIPQ) is used as an instrument to assess the patients’ perception of illness. Although the BIPQ has been previously translated into Persian, its psychometric properties have not been evaluated among patients with chronic nonspecific LBP. The aim of this study was to determine the reliability and validity of the Persian BIPQ in patients with chronic nonspecific LBP. Methods. 116 patients with chronic nonspecific LBP with a mean (standard deviation) age of 36.4 years (10.7) participated in this cross-sectional study. Fifty patients were reexamined after 10 to 12 days for test-retest reliability. Internal consistency reliability, construct validity, concurrent criterion validity, and structural validity were evaluated. The concurrent validity was examined by using the Short Form-36 Health Survey. Results. There were no floor and ceiling effects. Cronbach’s alpha for the total score was 0.90. The intraclass correlation coefficient (ICC) for test-retest reliability was 0.90. The standard error of measurement and the minimal detectable change was found to be 3.26 and 9.04, respectively. The convergent correlations confirmed the construct validity. The concurrent criterion validity was demonstrated by significant negative correlations with the SF-36. The Exploratory Factor Analysis produced the 2 factors (emotional illness representations and cognitive illness representations) with an eigenvalue >1.0 that jointly accounted for 58.86% of the total variance. Conclusion. The Persian BIPQ is a reliable and 2-factor instrument and can be used for assessing illness perception in patients with chronic nonspecific LBP.
Effects of Sheep Manure Combined with Chemical Fertilizers on Maize Yield and Quality and Spatial and Temporal Distribution of Soil Inorganic Nitrogen
Authors: Yang Chun , Du Wenbin , Zhang Lili , Dong Zhaorong
Published: July 2021

In order to explore the influences of sheep manure mixed with chemical fertilizers upon the yield and quality of maize and the spatial and temporal distribution of soil inorganic nitrogen under the wheat‐maize rotation system, achieve increased yield and efficiency with rational fertilization of maize in this area, and at the same time provide a reasonable scientific basis for green production, an experiment was performed at Wanbei Comprehensive Experimental Station of Anhui Agricultural University in 2020 accordingly. The soil for the experiment is sand ginger black soil, and the subject is Zhengdan 958. The experiment adopts a randomized block design with 6 treatments: no fertilizer (T1), single application of the chemical fertilizer (T2), 15% sheep manure mixed with the chemical fertilizer (T3), 30% sheep manure combined with the chemical fertilizer (T4), 45% sheep manure added with the chemical fertilizer (T5), and only sheep manure (T6). The amount of nitrogen, phosphorus, and potassium applied in each treatment remains the same. The result of the experiment shows that T1 treatment has the lowest yield, followed by T6 treatment. The yield of sheep manure combined with the chemical fertilizer is much higher than that of pure sheep manure and no fertilizer. Among them, the yield of T3 is the highest and T4 is the lowest. There is no obvious variation between the combined treatments. Compared with single usage of the chemical fertilizer, the fat content of maize kernels treated with T3 and T4 is 8.9% and 5.6% higher than that of T2 treatment. The protein content of maize kernels treated with T3, T4, and T5 is 2.3%, 2.5%, and 2% higher than that of T2. It shows that the mixture of sheep manure and chemical fertilizer can improve the quality of maize kernels in some degree. The partial productivity of the nitrogen fertilizer in T3 and T5 treatments is 3.7% and 0.8% higher than that of T2 treatment, and the agronomic utilization rate of the nitrogen fertilizer is 10.9% and 1.6% higher than that of T2 treatment. T6 is much lower than that of T2 treatment. It certifies that the combined application of chemical fertilizers with sheep manure can increase the partial productivity and the agronomic utilization rate of the nitrogen fertilizer and increase crop yields and farmers’ income. The nitrate nitrogen of 40–60 cm soil layer is increased by 30.4%, 60–80 cm soil layer is increased by 56.5%, and 80–100 cm soil layer is increased by 11.6%. It shows that the mixed usage of organic and inorganic fertilizers can prevent nitrate nitrogen from moving to deep soil and reduce groundwater pollution.
A Note on the Generalized Nonlinear Vector Variational-Like Inequality Problem
Authors: Gupta Ankit , Kumar Satish , Sarma Ratna Dev , Garg Pankaj Kumar , George Reny
Published: July 2021

In this paper, we discuss two variants of the generalized nonlinear vector variational-like inequality problem. We provide their solutions by adopting topological approach. Topological properties such as compactness, closedness, and net theory are used in the proof. The admissibility of the function space topology and KKM-Theorem have played important role in proving the results.
Classification of Lung Adenocarcinoma Based on Immune Checkpoint and Screening of Related Genes
Authors: Zhou Ting , Yang Ping , Tang Sanyuan , Zhu Zhongshan , Li Xiaobing , Yang Zhou , Wu Ruoxia , Tian Xuefei , Li Liang
Published: July 2021

Aims. Lung adenocarcinoma (LUAD) cells could escape from the monitoring of immune cells and metastasize rapidly through immune escape. Therefore, we aimed to develop a method to predict the prognosis of LUAD patients based on immune checkpoints and their associated genes, thus providing guidance for LUAD treatment. Methods. Gene sequencing data were downloaded from the Cancer Genome Atlas (TCGA) and analyzed by R software and R Bioconductor software package. Based on immune checkpoint genes, kmdist clustering in ConsensusClusterPlus R software package was utilized to classify LUAD. CIBERSORT was used to quantify the abundance of immune cells in LUAD samples. LM22 signature was performed to distinguish 22 phenotypes of human infiltrating immune cells. Gene set variation analysis (GSVA) was performed on immune checkpoint cluster and immune checkpoint score using GSVA R software package. The risk score was calculated by LASSO regression coefficient. Gene Ontology (GO), Hallmark, and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed. PROC was performed to generate the ROC curve and calculate the area under the curve (AUC). Results. According to the immune checkpoint, LUAD was classified into clusters 1 and 2. Survival rate, immune infiltration patterns, TMB, and immune score were significantly different between the two clusters. Functional prediction showed that the functions of cluster 1 focused on apoptosis, JAK/STAT signaling pathway, TNF-α/NFκB signaling pathway, and STAT5 signaling pathway. The risk score model was constructed based on nine genes associated with immune checkpoints. Survival analysis and ROC analysis showed that patients with high-risk score had poor prognosis. The risk score was significantly correlated with cancer status (with tumor), male proportion, status, tobacco intake, and cancer stage. With the increase of the risk score, the enrichment of 22 biological functions increased, such as p53 signaling pathway. The signature was verified in IMvigor immunotherapy dataset with excellent diagnostic accuracy. Conclusion. We established a nine-gene signature based on immune checkpoints, which may contribute to the diagnosis, prognosis, and clinical treatment of LUAD.
Hydrogeochemical Characteristics and Formation of Low-Temperature Geothermal Waters in Mangbang-Longling Area of Western Yunnan, China
Authors: Chang Xing-Wang , Xu Mo , Jiang Liang-Wen , Li Xiao , Zhang Yun-Hui
Published: July 2021

Numerous low-temperature geothermal waters are distributed extensively in Mangbang-Longling of western Yunnan in China, whose formation mechanism has not been completely investigated yet. This study focused on the hydrogeochemical evolution, reservoir temperature, and recharge origin of geothermal waters using hydrogeochemical and deuterium-oxygen (D-O) isotopic studies. The low-temperature geothermal waters were characterized by HCO3-Na type, while shallow cold spring was of the hydrochemical type of HCO3-Ca. The hydrogeochemical characteristics of low-temperature geothermal waters were mainly determined by the dissolution of silicate minerals based on the geological condition and correlations of major and minor ions. The reservoir temperatures of low-temperature geothermal waters ranged from 111°C to 126°C estimated by silica geothermometry and the silicon-enthalpy graphic method. Low-temperature geothermal waters circulated at the largest depth of 1794–2077 m where deep high-temperature geothermal waters were involved. The data points of δD and δ18O of the hot spring water samples in the study area show a linear right-up trend, indicating the δ18O reaction between the water and rock and a possible mixture of magmatic water from below. The low-temperature thermal waters were recharged by meteoric water at the elevation of 2362–3653 m calculated by δD values. Upwelling by heating energy, low-temperature geothermal waters were exposed as geothermal springs in the fault and fracture intersection and mixed by up to 72% shallow cold waters at surface. Based on acquired data, a conceptual model of the low-temperature geothermal waters in the Mangbang-Longling area was proposed for future exploitation.
Application of Implantable Polylactic-Co-Glycolic Acid Microcapsule in Repairing Alveolar Bone Defects
Authors: Jiang Jun , Xiao Jianpeng , Wang Dongqing , Cai Huazhong
Published: July 2021

Alveolar bone defects (ABDs) were a perennial problem, especially in the aged. Bisphosphonates, especially etidronate sodium (ET), were frequently used in clinical treatment of ABD. However, the oral administration of ET had poor absorption (<1%). Therefore, optimization of a suitable dosage form substituted with ET to locally repair the ABD was a straightforward approach. Polylactide-co-glycolide (PLGA) is a biodegradable material and had been used in locally implanted medical devices. Therefore, an ET-PLGA microcapsule may help local delivery and prolong the activity of healing ABD. In this paper, a preparation method of ET-PLGA microcapsule was optimized by the single-factor investigation and response surface method. Subsequently, the rat ABD model was used to evaluate the enhancement effect of these microcapsules. Finally, the optimum parameters were determined as follows: 40% dichloromethane, 160 mg/mL PLGA, 10% internal aqua/oil phase, 4% PVA, and emulsifying for 10 min. These microcapsules were spherical in shape and fairly monodisperse in a particle size of 27,51 μm (PDI = 0.3), encapsulation rate 96.6%, and drug loading 4.58%. Compared with the ET groups, the total healing volume of ABD in ET-PLGA groups was significantly increased

P
<
0.05

. ET-PLGA microcapsules significantly enhanced the effect of ET on ABD. This study provided important technical support for the treatment of ABD with bisphosphonates by local administration. This paper has an exploratory significance for the development of water-soluble bioactive components with low bioavailability for ABD.
Dynamics of Tuberculosis (TB) with Drug Resistance to First-Line Treatment and Leaky Vaccination: A Deterministic Modelling Perspective
Authors: Otoo Dominic , Osman Shaibu , Poku Stephen Atta , Donkoh Elvis Kobina
Published: July 2021

A deterministic model was formulated and employed in the analysis of the dynamics of tuberculosis with a keen emphasis on vaccination and drug resistance as the first line of treatment. It was assumed that some of the susceptible population were vaccinated but with temporal immunity. This is due to the fact that vaccines do not confer permanent immunity. Moreover, part of the infected individual after treatment grows resistance to the drug. Infective immigrants were also considered to be part of the population. The basic reproductive number for the model is estimated using the next-generation matrix method. The equilibrium points of the TB model and their local and global stability were determined. It was established that if the basic reproductive number was less than unity

R

0

<
1

, then the disease free equilibrium is stable and unstable if

R

0

>
1

. Furthermore, we investigated the optimal prevention, treatment, and vaccination as control measures for the disease. As the objective functional was optimised, there have been a significant reduction in the number of infections and an increase in the number of recovery. The best control measure in combating tuberculosis infections is prevention and vaccination of the susceptible population.
Study on Deformation and Failure Characteristics of Surrounding Rock of Overlying Roadway under Upward Mining in the Deep Mine
Authors: Xiong Teng-Gen , Chang Ju-Cai , He Kai , Su Ya-Feng , Qi Chao
Published: July 2021

To study the impact of mining of the lower protective layer on the deformation and failure characteristics of the upper roadway, these characteristics of an 879 gas drainage roadway were studied and analyzed during the mining of the II 1051 working face of the Zhuxianzhuang coal mine using similar simulation experiments and numerical simulation methods. The results indicate that with the continuous excavation of the working face, the range of impact of the mining stress gradually spreads and exceeds the level of the roadway. At the present time, the roadway is in a mining stress-rising area. The two sides of the roadway are sheared, and the roof and floor are under tension–shear composite failure. The floor is the most gravely damaged—the depth of its damage is 2.5 m, and the depths of damage on either side and of the roof are approximately 1–2 m. During the advancing process of the working face, the deformation of the roadway increases slowly at first, then increases sharply, and tends to be stable thereafter. The deformation of the floor is the largest, followed by those of the two sides and the roof; the values are 800, 400, and 300 mm, respectively.
Basketball Data Analysis Using Spark Framework and K-Means Algorithm
Authors: Hong Xijun
Published: July 2021

With the rapid development, different information relating to sports may now be recorded forms of useful big data through wearable and sensing technology. Big data technology has become a pressing challenge to tackle in the present basketball training, which improves the effect of baseball analysis. In this study, we propose the Spark framework based on in-memory computing for big data processing. First, we use a new swarm intelligence optimization cuckoo search algorithm because the algorithm has fewer parameters, powerful global search ability, and support of fast convergence. Second, we apply the traditional K-clustering algorithm to improve the final output using clustering means in Spark distributed environment. Last, we examine the aspects that could lead to high-pressure game circumstances to study professional athletes’ defensive performance. Both recruiters and trainers may use our technique to better understand essential player’s qualities and eventually, to assess and improve a team’s performance. The experimental findings reveal that the suggested approach outperforms previous methods in terms of clustering performance and practical utility. It has the greatest influence on the shooting training impact when moving, yielding complimentary outcomes in the training effect.
Frontier Enhanced Oil Recovery (EOR) Research on the Application of Imbibition Techniques in High-Pressure Forced Soaking of Hydraulically Fractured Shale Oil Reservoirs
Authors: Li Guanqun , Su Yuliang , Guo Yingchun , Hao Yongmao , Li Lei
Published: July 2021

Shale reservoirs are characterized by low porosity and low permeability, and volume fracturing of horizontal wells is a key technology for the benefits development of shale oil resources. The results from laboratory and field tests show that the backflow rate of fracturing fluid is less than 50%, and the storage amount of fracturing fluid after large-scale hydraulic fracturing is positively correlated with the output of single well. The recovery of crude oil is greatly improved by means of shut-in and imbibition, therefore attracting increasing attention from researchers. In this review, we summarize the recent advances in the migration mechanisms and stimulation mechanisms of horizontal well high pressure forced soaking technology in the reservoirs. However, due to the diversity of shale mineral composition and the complexity of crude oil composition, the stimulation mechanism and effect of this technology are not clear in shale reservoir. Therefore, the mechanism of enhanced oil recovery by imbibition and the movable lower limit of imbibition cannot be characterized quantitatively. It is necessary to solve fragmentation research in the full-period fluid transport mechanisms in the follow-up research.
High-Affinity Anti-VISTA Antibody Protects against Sepsis by Inhibition of T Lymphocyte Apoptosis and Suppression of the Inflammatory Response
Authors: Tao Tianzhu , Bo Lulong , Li Teng , Shi Longbao , Zhang Hui , Ye Bo , Xu Yuhai , Ma Qingqing , Deng Xiaoming , Zhang Guorong
Published: July 2021

Background. B7 family members and ligands have been identified as critical checkpoints in orchestrating the immune response during sepsis. V-domain Ig suppressor of T cell activation (VISTA) is a new inhibitory immune checkpoint involved in restraining T cell response. Previous studies demonstrated that VISTA engagement on T cells and myeloid cells could transmit inhibitory signals, resulting in reduced activation and function. The current study was designed to determine the potential therapeutic effects of a high-affinity anti-VISTA antibody (clone MH5A) in a murine model of sepsis. Methods. Polymicrobial sepsis was induced in male C57BL/6 mice via cecal ligation and puncture. Expression profiles of VISTA on T lymphocytes and macrophage were examined at 24 and 72 h postsurgery. The effects of anti-VISTA mAb on the 7-day survival, lymphocyte apoptosis, cytokine expression, bacterial burden, and vital organ damage were determined. Furthermore, the effects of anti-VISTA mAb on CD3+ T cell apoptosis and macrophage activation were determined in vitro. Results. VISTA was substantially expressed on T cells and macrophages in sham-operated mice; septic peritonitis did not induce significant changes in the expression profiles. Treatment with MH5A improved the survival of septic mice, accompanied by reduced lymphocyte apoptosis, decreased cytokine expression, and enhanced bacterial clearance. Engagement of VISTA receptor with MH5A mitigated CD3+ T cell apoptosis cultured from CLP mice and suppressed LPS-induced cytokine production by macrophage in vitro. Conclusion. The present study identified VISTA as a novel immune checkpoint in the regulation of T cell and macrophage response during sepsis. Modulation of the VISTA pathway might offer a promising opportunity in the immunotherapy for sepsis.
Experimental Study on an Innovative Hollow Concrete Floor System Assembled with Precast Panels and Self‐Thermal‐Insulation Infills
Authors: Gong Liang , Chen Zhongfan , Feng Yan , Ruan Sihan , Tu Liuhui
Published: July 2021

This paper presents an innovative hollow concrete floor system comprising hollow precast panels and self‐thermal‐insulation infills. The precast panels are connected by welded reinforcement bars and cast‐in‐situ concrete joints. To study the vertical load‐carrying capacity and the working mechanism of this innovative floor system, a static loading test was carried out on a 1/2 scale model. The specimen consists of six precast slab members, four precast reinforced concrete beams and columns, respectively. Experimental and simulation results related to the crack development and vertical load‐carrying capacity were analyzed. It is found that the innovative floor system could meet the capacity requirements of the Chinese code. Furthermore, the crack development of the innovative system shows similar characteristics with the solid floor. To explore the feasibility of the existed analysis methods, the specimen was simulated and compared by nonlinear analysis in ABAQUS. The comparison illustrates that the analogue cross beam method is more accurate and suitable for the simulation of the innovative hollow concrete floor system.
Adaptive Differentiator‐Based Predefined‐Time Control for Nonlinear Systems Subject to Pure‐Feedback Form and Unknown Disturbance
Authors: Yang Man , Zhang Qiang , Xu Ke , Chen Ming
Published: July 2021

In this article, by utilizing the predefined‐time stability theory, the predefined‐time output tracking control problem for perturbed uncertain nonlinear systems with pure‐feedback structure is addressed. The nonaffine structure of the original system is simplified as an affine form via the property of the mean value theorem. Furthermore, the design difficulty from the uncertain nonlinear function is overcome by the excellent approximation performance of RBF neural networks (NNs). An adaptive predefined‐time controller is designed by introducing the finite‐time differentiator which is used to decrease the computational complexity problem appeared in the traditional backstepping control. It is proved that the proposed control method guarantees all signals in the closed‐loop system remain bound and the tracking error converges to zero within the predefined time. Based on the controller designed in this paper, the expected results can be obtained in predefined time, which can be illustrated by the simulation results.
The Interactive Effect of Organizational Identification and Organizational Climate on Employees’ Taking Charge Behavior: A Complexity Perspective
Authors: Liu Yun , Chen Lingjuan , Zhao Liangjie , Li Chengai
Published: July 2021

In the view of complexity theory, the emergency behavior of individual is nonlinear and influenced not only by individual variables but also by many other environmental variables. Based on complexity perspective, this article explored why employees’ taking charge behavior occurs in organizations from a multilevel approach. Specifically, this study has explored the cross‐level interactive effect of organization‐level factor (organizational justice climate and psychological safety climate) and individual‐level factor (organizational identification) on employees’ taking charge behavior. Using a total of 806 valid matching questionnaires from 91 firms in China, this study found that first, organizational identification is positively related with employees’ taking charge behavior. Second, distributive justice climate positively moderates the influence of organizational identification on employees’ taking charge behavior. Third, psychological safety climate negatively moderates the influence of organizational identification on employees’ taking charge behavior. According to our results, organizational policies and practices should be made to foster employees’ identification with the organization, to construct a fair environment within the organization, and to convince employees that taking charge behavior will not entail political risks, especially for those employees with low organizational identification.
Efficient Utility Tree‐Based Algorithm to Mine High Utility Patterns Having Strong Correlation
Authors: Saeed Rashad , Rauf Azhar , Quradaa Fahmi H. , Asim Syed Muhammad
Published: July 2021

High Utility Itemset Mining (HUIM) is one of the most investigated tasks of data mining. It has broad applications in domains such as product recommendation, market basket analysis, e‐learning, text mining, bioinformatics, and web click stream analysis. Insights from such pattern analysis provide numerous benefits, including cost cutting, improved competitive advantage, and increased revenue. However, HUIM methods may discover misleading patterns as they do not evaluate the correlation of extracted patterns. As a consequence, a number of algorithms have been proposed to mine correlated HUIs. These algorithms still suffer from the issue of the computational cost in terms of both time and memory consumption. This paper presents an algorithm, named Efficient Correlated High Utility Pattern Mining (ECoHUPM), to efficiently mine the high utility patterns having strong correlation items. A new data structure based on utility tree (UTtree) named CoUTlist is proposed to store sufficient information for mining the desired patterns. Three pruning properties are introduced to reduce the search space and improve the mining performance. Experiments on sparse, very sparse, dense, and very dense datasets indicate that the proposed ECoHUPM algorithm is efficient as compared to the state‐of‐the‐art CoHUIM and CoHUI‐Miner algorithms in terms of both time and memory consumption.
Gene Mutation Classification through Text Evidence Facilitating Cancer Tumour Detection
Authors: Gupta Meenu , Wu Hao , Arora Simrann , Gupta Akash , Chaudhary Gopal , Hua Qiaozhi
Published: July 2021

A cancer tumour consists of thousands of genetic mutations. Even after advancement in technology, the task of distinguishing genetic mutations, which act as driver for the growth of tumour with passengers (Neutral Genetic Mutations), is still being done manually. This is a time-consuming process where pathologists interpret every genetic mutation from the clinical evidence manually. These clinical shreds of evidence belong to a total of nine classes, but the criterion of classification is still unknown. The main aim of this research is to propose a multiclass classifier to classify the genetic mutations based on clinical evidence (i.e., the text description of these genetic mutations) using Natural Language Processing (NLP) techniques. The dataset for this research is taken from Kaggle and is provided by the Memorial Sloan Kettering Cancer Center (MSKCC). The world-class researchers and oncologists contribute the dataset. Three text transformation models, namely, CountVectorizer, TfidfVectorizer, and Word2Vec, are utilized for the conversion of text to a matrix of token counts. Three machine learning classification models, namely, Logistic Regression (LR), Random Forest (RF), and XGBoost (XGB), along with the Recurrent Neural Network (RNN) model of deep learning, are applied to the sparse matrix (keywords count representation) of text descriptions. The accuracy score of all the proposed classifiers is evaluated by using the confusion matrix. Finally, the empirical results show that the RNN model of deep learning has performed better than other proposed classifiers with the highest accuracy of 70%.
Immunohistochemistry for (Pro)renin Receptor in Humans
Authors: Morimoto Satoshi , Morishima Noriko , Watanabe Daisuke , Kato Yoichiro , Shibata Noriyuki , Ichihara Atsuhiro
Published: July 2021

The (pro)renin receptor is a multifunctional protein with roles in angiotensin-II-dependent and -independent intracellular cell signaling and roles as an intracellular accessory protein for the vacuolar H+-ATPase, including hormone secretion. While (pro)renin receptor mRNA is widely expressed in various human tissues, localization of (pro)renin receptor protein expression has not yet been systemically determined. Therefore, this study localized (pro)renin receptor protein expression in human organs. Systemic immunohistochemical examination of (pro)renin receptor expression was performed in whole body organs of autopsy cases. (Pro)renin receptor immunostaining was observed in the cytoplasm of cells in almost all human organs. It was observed in thyroid follicular epithelial cells, hepatic cells, pancreatic duct epithelial cells, zona glomerulosa and zona reticularis of the cortex and medulla of the adrenal gland, proximal and distal tubules and collecting ducts of the kidney, cardiomyocytes, and skeletal muscle cells. In the brain, (pro)renin receptor staining was detected in neurons throughout all areas, especially in the medulla oblongata, paraventricular nucleus and supraoptic nucleus of the hypothalamus, cerebrum, granular layer of the hippocampus, Purkinje cell layer of the cerebellum, and the pituitary anterior and posterior lobes. In the anterior lobe of the pituitary gland, all types of anterior pituitary hormone-positive cells showed double staining with (pro)renin receptor. These data showed that (pro)renin receptor protein was expressed in almost all organs of the human body. Its expression pattern was not uniform, and cell-specific expression pattern was observed, supporting the notion that (pro)renin receptor plays numerous physiological roles in each human organ.
Assessing the Adequacy of Hemodialysis Patients via the Graph-Based Takagi-Sugeno-Kang Fuzzy System
Authors: Du Aiyan , Shi Xiaofen , Guo Xiaoyi , Pei Qixiao , Ding Yijie , Zhou Wei , Lu Qun , Shi Hua
Published: July 2021

Maintenance hemodialysis is the main method for the treatment of end-stage renal disease in China. The

K
t
/
V

value is the gold standard of hemodialysis adequacy. However,

K
t
/
V

requires repeated blood drawing and evaluation; it is hard to monitor dialysis adequacy frequently. In order to meet the need for repeated clinical assessments of dialysis adequacy, we want to find a noninvasive way to assess dialysis adequacy. Therefore, we collect some clinically relevant data and develop a machine learning- (ML-) based model to predict dialysis adequacy for clinical hemodialysis patients. We collect 250 patients, including gender, age, ultrafiltration (UF), predialysis body weight (preBW), postdialysis body weights (postBW), blood pressure (BP), heart rate (HR), and blood flow (BF). An efficient graph-based Takagi-Sugeno-Kang Fuzzy System (G-TSK-FS) model is proposed to predict the dialysis adequacy of hemodialysis patients. The root mean square error (RMSE) of our model is 0.1578. The proposed model can be used as a feasible method to predict dialysis adequacy, providing a new way for clinical practice. Our G-TSK-FS model could be used as a feasible method to predict dialysis adequacy, providing a new way for clinical practice.
Fault Diagnosis of Signal Equipment on the Lanzhou‐Xinjiang High‐Speed Railway Using Machine Learning for Natural Language Processing
Authors: Shi Lei , Zhu Yulin , Zhang Youpeng , Su Zhongji
Published: July 2021

The Lanzhou‐Xinjiang (Lan‐Xin) high‐speed railway is one of the principal sections of the railway network in western China, and signal equipment is of great importance in ensuring the safe and efficient operation of the high‐speed railway. Over a long period, in the railway operation and maintenance process, the railway signaling and communications department has recorded a large amount of unstructured text information about equipment faults in the form of natural language. However, due to irregularities in the recording methods of these data, it is difficult to use directly. In this paper, a method based on natural language processing (NLP) was adopted to analyze and classify this information. First, the Latent Dirichlet Allocation (LDA) topic model was used to extract the semantic features of the text, which were then expressed in the corresponding topic feature space. Next, the Support Vector Machine (SVM) algorithm was used to construct a signal equipment fault diagnostic model that reduced the impact of sample data imbalance on the classification accuracy. This was compared and analyzed with the traditional Naive Bayes (NB), Logistic Regression (LR), Random Forest (RF), and K‐Nearest Neighbor (KNN) algorithms. This study used signal equipment failure text data from the Lan‐Xin high‐speed railway to conduct experimental analysis and verify the effectiveness of the proposed method. Experiments showed that the accuracy of the SVM classification algorithm could reach 0.84 after being combined with the LDA topic model, which verifies that the natural language processing method can effectively realize the fault diagnosis of signal equipment and has certain guiding significance for the maintenance of field signal equipment.
Risk Factors of Invasive Pulmonary Fungal Infections in Patients with Hepatitis B Virus Related Acute-on-Chronic Liver Failure
Authors: He Xinchun , Tang Shigang , Chen Liang , Feng Yuqing , Zhu Baining , Yang Caixia
Published: July 2021

To analyze the risk factors of invasive pulmonary fungal infections in patients with HBV-ACL, the clinical data and risk factors of 60 patients with HBV-ACLF complicated IPFI were analyzed retrospectively including clinical parameters, broad-spectrum antibiotics usage, neutropenia, invasive medical manipulations, serum total bilirubin, international normalized ratio (INR), and MELD scores were compared with non-IPFI. Risk factors were analyzed using mathematical tools. Candida species and Aspergillus were detected as the most prominent fungal strains (61.11% and 33.33%, respectively). The risk factors included prolong broad-spectrum antibiotic usage

OR
=
4.362
,
P
=
0.008

, neutropenia

OR
=
3.288
,
P
=
0.007

, invasive procedures

OR
=
3.263
,
P
=
0.010

, serum total bilirubin

OR
=
1.006
,
P
=
0.011

, INR

OR
=
2.101
,
P
=
0.007

, and MELD scores

OR
=
1.074
,
P
=
0.008

. Candida is the main IPFI strains in patients with HBV-ACLF. Broad-spectrum antibiotics usage, neutropenia, invasive manipulations, and the severity of ACLF might be risk factors for IPFI in patients with HBV-ACLF.
Offline Single-Polarization Radar Quantitative Precipitation Estimation Based on a Spatiotemporal Deep Fusion Model
Authors: Zhang Yonghong , Chen Shiwei , Tian Wei , Ma Guangyi , Chen Shuai
Published: July 2021

Quantitative precipitation estimation (QPE) based on Doppler radar plays an important role in severe weather monitoring, industrial and agricultural production, and natural disaster prediction and prevention. However, the temporal and spatial variability of precipitation leads to large errors in radar estimates of mixed precipitation. To improve the accuracy of radar QPE, we propose an offline spatiotemporal deep fusion model that uses the reflectivity data of the Shijiazhuang Doppler radar Z9311 and the precipitation data from 17 national weather stations (NWSs) and 260 automatic weather stations (AWSs). Considering the abrupt spatial changes in precipitation, a three-dimensional radar data structure is proposed, and the spatial features of multielevation and multiscale radar data are extracted and merged using the feature fusion network (FFNet). Finally, the time dependence of the precipitation is captured using the long short-term memory (LSTM) network, and the precipitation estimation is obtained. Based on a comparison of the results of the proposed model (FFNet-LSTM) with those of the ordinary kriging (OK) interpolation, two Z-R relationship, the multilayer perceptron (MLP), the LSTM, and the FFNet, the proposed method is superior to these models, has a promising performance, and is a general-purpose rainfall algorithm.