bluuebunny/crossref_metadata_2025 huggingface dataset:
A Review of Traditional Chinese Medicine on Treatment of Diabetic Nephropathy and the Involved Mechanisms
Authors: Liu Xiao-Juan , Hu Xiang-Ka , Yang He , Gui Liu-Ming , Cai Zeng-Xiaorui , Qi Mu-Shuang , Dai Chun-Mei
Published: October 2022

Diabetic nephropathy (DN) is a common microvascular complication of diabetes mellitus (DM), which can lead to renal failure in diabetic patients. At present, the first-line drugs for DN are mainly the renin–angiotensin system (RAS) inhibitors or angiotensin receptor blockers, and the latest approved aldosterone receptor antagonist finerenone, which delay the progression of DN to end-stage renal disease (ESRD), but the therapeutic effect is still not ideal. With a history of thousands of years, traditional Chinese medicine (TCM) has rich experience in the treatment of DN. Based on the theory of TCM, the clinical treatment of DN mainly focuses on generating fluid and nourishing blood, nourishing Qi and Yin, detoxifying and detumescent. In recently years, the therapeutic effects and mechanisms of TCM prescription, Chinese herbal medicine, and its active components on DN have received extensive attention in new drug development. This paper reviews the research progress of the mechanism of TCM on DN.
Hematite Crystallization from a Two-Line Ferrihydrite Suspension
Authors: Zhu Guomin , De Yoreo James J.
Published: October 2022

Rational design and synthesis of materials, determination of environmental conditions at the time of mineral formation, and definition of mechanisms in biomineralizing systems all require an understanding of the effect of multiple factors on modulating crystallization pathways. In this study, we investigate the influence of temperature, oxalate additive, aging time, and addition of seed crystals on hematite (α-Fe2O3, Hm) crystallization from a two-line ferrihydrite (Fe2O3·xH2O, Fh) suspension. We also investigate the effect of temperature on the aging of spindle-shaped Hm mesocrystals, which we synthesize through the addition of sodium oxalate. The results show that Hm mesocrystals form in a temperature window of 45 °C−130 °C. Temperatures ≥ 140 °C favor formation of rhombohedral Hm, suggesting classical monomer-by-monomer growth dominates, whereas crystallization by particle attachment (CPA) is dominant between 45 and 90 °C, while the two processes compete in the intermediate temperature range. Aging of mesocrystals in the original solution at 90 °C or 180 °C leads to a slow morphological evolution towards rhombohedral crystals due to Ostwald ripening. Finally, by utilizing rhombohedral Hm and rod-shaped goethite as substrates on which to assemble the mesocrystals, we demonstrate formation of complex heterogeneous structures.
Coordination of pancreatic islet rhythmic activity by delayed negative feedback
Authors: Bruce N. , Wei I.-A. , Leng W. , Oh Y. , Chiu Y.-C. , Roper M. G. , Bertram R.
Published: October 2022

Insulin secretion from islets of Langerhans is rhythmic, and these rhythms are coordinated to produce oscillatory plasma insulin levels. Using a combination of microfluidics and computational modeling, we demonstrate that coordination can occur through negative feedback of the type provided by the liver, even if that feedback is delayed by several minutes. We also demonstrate that a second, slower, mode of oscillations can occur when feedback is delayed where faster oscillations are grouped into episodes.
Fibroblast growth factor homologous factor 2 attenuates excitability of DRG neurons
Authors: Effraim Philip R. , Estacion Mark , Zhao Peng , Sosniak Daniel , Waxman Stephen G. , Dib-Hajj Sulayman D.
Published: October 2022

FHF2 is known to bind to and modulate the function of Nav1.7. FHF2 expression is also reduced after nerve injury. We demonstrate that knockdown of FHF2 expression increases DRG neuronal excitability. More importantly, overexpression of FHF2 reduces DRG excitability in basal conditions and in the presence of inflammatory mediators (a model of inflammatory pain). These results suggest that FHF2 could potentially be used as a tool to reduce DRG neuronal excitability and to treat pain.
Effects of Remimazolam Combined with Esketamine Anesthesia on Circulatory and Respiratory Function during Painless Gastroenteroscopy
Authors: Lu Cheng , Ren Jun , Guo Xin , Qian Jiang
Published: October 2022

Objective. To investigate the effect of applying remimazolam combined with esketamine for anesthesia in painless gastroenteroscopy on patients’ circulatory and respiratory function. Method. In this study, 106 patients who had undergone painless gastroenteroscopy in Xinjiang Production and Construction Corps (XPCC) Hospital between July 2021 and January 2022 were selected as study subjects, which were grouped according to the anesthetic drugs used in the surgery and divided into control group (n = 53 cases) and observation group (n = 53 cases), while those who were anesthetized with propofol + sufentanil during the operation were the control group and those who were anesthetized with remimazolam + esketamine were the observation group. To compare the induction time of anesthesia, patient awakening and recovery time of orientation, circulatory and respiratory function, intraoperative adverse effects, and postoperative complications in the two study groups. Results. There was no statistical difference in induction of anesthesia, patient awakening, and recovery time of orientation between the two groups (P > 0.05) and no statistical difference in postoperative complications (P > 0.05). The observation group had a better occurrence of local pain at the injection site, circulatory and respiratory function of patients after anesthesia, and intraoperative adverse reactions than the control group (P < 0.05). Conclusion. Remimazolam combined with esketamine anesthesia has the same advantages of rapid awakening compared with propofol anesthesia. Moreover, it has fewer side effects on patients’ circulatory and respiratory functions with fewer adverse effects, as a suitable anesthetic method for painless gastroenteroscopy.
Analysis of Computer Visualized Sound Parameters of Vocal Music Singing Based on Deep Learning
Authors: Mo Na , Ai Jin Shun , Ran Shi Yi
Published: October 2022

The first impression of the early historical recordings on the contemporary audience is often not ideal; the overall speed is relatively fast, the rhythm is relatively loose and free, and the strings are slippery. In recent years, a large number of research achievements have emerged at home and abroad that apply computer visualization analysis methods to music performance practice. It is feasible and necessary to gradually apply the visual audio parameter analysis method to music research and performance practice teaching. In this study, a prosody hierarchy prediction model based on the CNN (convective neural network) is proposed, and word vectors are added as semantic features. The DL (deep learning) method is applied to vocal music recognition, and a recognition method based on the DL framework is proposed by combining traditional audio signal processing methods. After introducing word vectors as features in the CNN model, the F-score value increased from 77% to 80%. The feasibility of the proposed vocal music recognition algorithm based on DL is verified by experiments.
Multicluster Analysis and Design of Hybrid Wireless Sensor Networks Using Solar Energy
Authors: Vino T. , Sivaraju S. S. , Krishna R. V. V. , Karthikeyan T. , Sharma Yogesh kumar , Venkatesan K. G. S. , Manikandan G. , Selvameena R. , Markos Mebratu
Published: October 2022

A wireless touch network is a distributed, self-organizing network of multiple sensors and actuators in combination with multiple sensors and a radio channel. Also, the security area of such a network can be several meters to several meters. The main difference between wireless sensor networks from traditional computer and telephone networks is the lack of a fixed infrastructure owned by a specific operator or provider. Each user terminal in a touch network is capable of acting as a terminal device only. Despite the long history of sensor networks, the concept of building a sensor network is not finally imposed and expressed in some software and hardware (platform) solutions. In this paper, the design and analysis of multicluster model of the sensor nodes in wireless sensor network with the help of solar energy. This proposed model provides the required energy to transmit the information between two end nodes in different cluster. The communication between the end to end clusters was increased based on this design. The implementation of sensory networks at the current stage depends largely on the specific needs of the industrial problem. The architecture, software, and hardware implementation technology is at an intensive development stage, attracting the attention of developers looking for a technological niche of future makers.
A Comparison of the Celiacomesenteric Trunk in the Caribbean with Global Prevalence Calculated by a Systematic Review
Authors: Cawich Shamir O. , Fortune Maurice , Deshpande Rahul , Gardner Michael , Pearce Neil , Johnson Peter , Naraynsingh Vijay
Published: October 2022

Background. Typically, the celiac trunk and superior mesenteric artery branch off separately from the anterior aspect of the abdominal aorta. The celiacomesenteric trunk (CMT) is a rare variant in which those arteries share a common origin. We sought to compare the prevalence of CMT in the Caribbean with the global prevalence as calculated by a systematic review. Methods. In this study, we evaluated all consecutive patients who had multiphase contrast-enhanced CT scans at two major referral centres in the Caribbean from August 30, 2017, to September 1, 2019. In patients with a CMT, we recorded demographic and anatomic details. We then conducted a systematic literature search and retrieved raw data to calculate the global prevalence (number of individuals with a CMT divided by the sum total of study samples). We compared CMT prevalence in our sample with the global prevalence using Pearson’s chi-square and Fisher’s exact tests. Statistical significance was considered to be present when thePvalue was <0.05. Results. From 832 CTs, 665 scans met the inclusion criteria. There were 16 (2.41%) CMTs: 3 (0.45%) classic CMTs, 12 (1.8%) hepato-mesenteric trunks, and 1 (0.15%) hepato-spleno-mesenteric trunk. Forty-two studies reported on CMTs in a total of 74,320 persons. The global CMT prevalence was comparable (3.88%;P=0.054), but the incidence of hepato-mesenteric variants was significantly lower in our sample (1.8% vs. 3.24%;P=0.0352). Conclusion. There was no difference in the prevalence of a classic CMT in the Caribbean compared to the global prevalence. However, the hepato-mesenteric trunk (incomplete CMT variant) was significantly less prevalent in the Caribbean. Advances in Knowledge: Healthcare professionals performing hepatobiliary interventions must be aware of these differences in order to minimize morbidity during their interventions.
Prediction and Management of Regional Economic Scale Based on Machine Learning Model
Authors: Jiang Zhiqiang
Published: October 2022

The country is developing rapidly and the economy is taking off. For the country, the economic development of each region is very important, and the economy is the key to measuring the development of a region. To this end, the machine learning model is combined with regional economic scale prediction and management, and the two are studied together to obtain the following: (1) The key to measuring the regional economy is the growth rate of GDP and GDP. For the economic comparison between region A and region B, the economic scale is predicted by machine learning model. The regional economic development is better, which has an important basis for the comparison of the following methods. (2) There are many ways to improve the regional economy. Among them, the development of the industrial economy has the highest degree of regional economic indicators GDP and GDP growth rate. (3) The machine learning model has many benefits in the development of regional economic forecasting. Among them, reducing errors has the greatest impact on the regional economy. By comparison, it can be known that the accuracy of the regional economic forecasting under the machine learning model and the required forecasting time have been greatly optimized.
MGPM Methods for Rectangular Single-Size Printed Circuit Board Orthogonal Packing Problems
Authors: Pan Pengfei , Han Yi , Lv Hexin , Dai Guoyong , Jin Zhiyong
Published: October 2022

Printed circuit board (PCB) orthogonal packing problems derive from the massive circuit board production process in the electronic industry. In the early stage, it mainly relied on human experiences to make decisions on how to make the most of each sheet while meeting customers’ orders. Up till now, researchers in enterprises and academic circles are still trying to explore effective mathematical models and feasible optimization methods. In most cases, what PCB companies generally face is the orthogonal layout decision, which considers positioning each rectangle PCB piece (PCB-P) on a rectangle sheet board (panel) in an ideal way so that each panel has the minimal remains with the most PCB-Ps. In this paper, multi-round gradual packing methods (MGPMs) are proposed based on the idea of combinatorial optimization and dynamic programming. MGPMs include the depth priority-based method (MGPM-DP) and breadth priority-based branch-and-prune method (MGPM-BC). The former has the advantage of finding better solutions, while the latter has the advantage of consuming short computational time. Through extensive computational tests on real data from a PCB production enterprise in China, both MGPM-DP and MGPM-BC have achieved noticeable and satisfactory results compared with the simplex method, dynamic programming method, and a widely used industrial software (Yuanbo) in China.
BERT-Based Clinical Name Entity Reorganization Model for Health Diagnosis
Authors: Borole Yogini Dilip , Agrawal Anurag Vijay , Tesfayohanis Miretab , Thakkar Dhruv , Abonazel Mohamed R. , Awwad Fuad A.
Published: October 2022

The National Health and Family Planning Commission requires medical institutions to use the International Classification of Diseases (ICD) codes. However, due to many commonly used words in clinical disease descriptions, the direct mapping matching rate between the diagnosis names entered in the electronic medical records and the ICD codes is low. In this paper, based on the actual diagnostic data on the regional health platform, a disease term map incorporating standard terms was constructed. Specifically, based on the rule algorithm based on the components of the disease, a data-enhanced BERT (bidirectional encoder representation from transformers) upper and lower relationship recognition algorithm is proposed. Synonymous upper and lower relationships identify diseases, and the hierarchical structure is further integrated. In addition, a task assignment based on the association map of disease departments is also proposed. Methods were used for manual verification, and finally, 94,478 disease entities formed a large-scale disease term map, including 1,460 synonymous relationships and 46,508 hyponymous relationships. Evaluation experiments show that, based on the disease term map and clinical diagnosis, the coverage rate of diagnostic data is 75.31% higher than direct mapping coding based on ICD. In addition, using the disease term map to code diseases automatically will shorten the coding time by about 59.75% compared with manual coding by doctors, and the correct rate is 85%.
Effects of Hyperthyroidism on Venous Thromboembolism: A Mendelian Randomization Study
Authors: Han Fushi , Zhang Chunyang , Xuan Miao , Xie Zhuangli , Zhang Kunming , Li Ying
Published: October 2022

Objective. Observational studies show the correlation between thyroid dysfunction and risk of venous thromboembolism. However, the causal effects remain uncertain. Our study was conducted to evaluate whether thyroid function and dysfunction were causally linked to the risk of venous thromboembolism. Methods. Publicly available summary data of thyrotropin (TSH) and free thyroxine (FT4), hypothyroidism, and hyperthyroidism were obtained from the ThyroidOmics Consortium and the UK Biobank. With single nucleotide polymorphisms (SNPs) as instrumental variables, the casual effects of genetically predicted TSH and FT4 and hypo- and hyperthyroidism on venous thromboembolism outcome were estimated through Mendelian randomization analysis methods (inverse variance weighted (IVW), MR-Egger, weighted median, simple mode, and weighted mode). Cochran’s Q test was performed to evaluate the heterogeneity and horizontal pleiotropy. Results. Our study selected 15 FT4-, 36 TSH-, 3 hyperthyroidism-, and 79 hypothyroidism-associated SNPs as instrumental variables. The IVW analysis results showed that the odds ratio of venous thromboembolism for hyperthyroidism was 1.124 (95% confidence interval: 1.019-1.240;

p
=
0.019

), demonstrating the casual effect of hyperthyroidism not FT4, TSH, and hypothyroidism on venous thromboembolism. No heterogeneity or horizontal pleiotropy was observed according to Cochran’s Q test. Conclusion. Our Mendelian randomization analysis supports the causal effect of hypothyroidism on risk of venous thromboembolism. There is no evidence that genetically predicted TSH, FT4, and hypothyroidism have casual effects on venous thromboembolism. Future studies should be conducted to elucidate the underlying pathophysiological mechanisms.
5G System Overview for Ongoing Smart Applications: Structure, Requirements, and Specifications
Authors: Attar Hani , Issa Haitham , Ababneh Jafar , Abbasi Mahdi , Solyman Ahmed A. A. , Khosravi Mohammad , Said Agieb Ramy
Published: October 2022

Fifth-generation (5G) cellular networks are state-of-the-art wireless technologies revolutionizing all wireless systems. The fundamental goals of 5G are to increase network capacity, improve data rates, and reduce end-to-end latency. Therefore, 5G can support many devices connected to the Internet and realize the Internet of Things (IoT) vision. Though 5 G provides significant features for mobile wireless networks, some challenges still need to be addressed. Although 5 G offers valuable capabilities for mobile wireless networks, specific issues still need to be resolved. This article thoroughly introduces 5G technology, detailing its needs, infrastructure, features, and difficulties. In addition, it summarizes all the requirements and specifications of the 5G network based on the 3rd Generation Partnership Project (3GPP) Releases 15–17. Finally, this study discusses the key specifications challenges of 5G wireless networks.
Improving Wind Speed Forecasting for Urban Air Mobility Using Coupled Simulations
Authors: Chrit Mounir , Majdi Marwa
Published: October 2022

Hazardous weather, turbulence, wind, and thermals pose a ubiquitous challenge to Unmanned Aircraft Systems (UAS) and electric-Vertical Take-Off and Landing (e-VTOL) aircrafts, and the safe integration of UAS into urban area requires accurate high-granularity wind data especially during landing and takeoff phases. Two models, namely, Open-Source Field Operation and Manipulation (OpenFOAM) software package and Weather Research and Forecasting (WRF) model, are used in the present study to simulate airflow over Downtown Oklahoma City, Oklahoma, United States. Results show that computational fluid dynamics wind simulation driven by the atmospheric simulation significantly improves the simulated wind speed because the accurate modeling of the buildings affects wind patterns. The evaluation of different simulations against six Micronet stations shows that WRF-CFD numerical evaluation is a reliable method to understand the complicated wind flow within built-up areas. The comparison of wind distributions of simulations at different resolutions shows better description of wind variability and gusts generated by the urban flows. Simulations assuming anisotropy and isotropy of turbulence show small differences in the predicted wind speeds over Downtown Oklahoma City given the stable atmospheric stratification showing that turbulent eddy scales at the evaluation locations are within the inertial subrange and confirming that turbulence is locally isotropic.
Glutathione Peroxidase 4 Is a Predictor of Diabetic Kidney Disease Progression in Type 2 Diabetes Mellitus
Authors: Wang Yi-hui , Chang Dong-yuan , Zhao Ming-hui , Chen Min
Published: October 2022

Background. Diabetic kidney disease (DKD) represents a heavy burden in type 2 diabetes mellitus (T2DM). Ferroptosis plays an important role in DKD, and it thus provides new perspectives to pursue more related biomarkers to assess the disease severity and prognosis. Glutathione peroxidase 4 (GPX4) is the mainstay in regulating ferroptosis. The current study investigated the predictive value of kidney GPX4 expression level in DKD progression. Methods. We measured GPX4 levels in kidney paraffin sections of 85 biopsy-proven DKD patients by immunohistochemistry staining. The associations between the GPX4 level and clinicopathological parameters as well as renal outcomes were analyzed. Results. GPX4 is mainly expressed in kidney tubulointerstitium, especially in tubular epithelial cells of DKD patients. The GPX4 expression level was significantly lower in DKD patients than healthy controls. Besides, GPX4 level significantly correlated with proteinuria (

r
=
−
0.42

,

p
<
0.001

), urinary albumin-to-creatinine ratio (uACR) (

r
=
−
0.40

,

p
<
0.01

), serum creatinine (Scr) (

r
=
−
0.59

,

p
<
0.001

), estimated glomerular filtration rate (eGFR) (

r
=
0.66

,

p
<
0.001

), and the percentage of sclerosed glomeruli (

r
=
−
0.42

,

p
<
0.001

) in renal specimens. During follow-up, the GPX4 level positively correlated with eGFR slope (

r
=
0.48

,

p
<
0.001

), and GPX4-low patients showed a significantly higher probability of developing end-stage kidney disease (ESKD) compared with GPX4-high patients (

p
<
0.01

). Moreover, after adjusting for other potential predictors, the GPX4 level was still an independent predictor of developing ESKD (HR 2.15, 95% CI 1.08 to 4.28,

p
<
0.05

). Conclusions. Kidney tubulointerstitial GPX4 expression level was associated with the disease severity and progression of DKD.
Deep Learning for Intelligent Assessment of Financial Investment Risk Prediction
Authors: Sun Yang , Li Jiajun
Published: October 2022

Financial investment promotes the market’s fast economic growth and gradually becomes a new trend of social development in the contemporary era. From the national level, financial risk investment activities directly affect the development process of the information technology industry and social and economic benefits. The management of financial risk investment has received more attention, and the types and difficulties of risks are also gradually increasing. Financial regulatory agencies urgently need to establish a sensitive and scientific economic hazard early alarm system. The perfect earlier alarm system stands based on in-depth scientific theoretical research, so studying financial security evaluation and systemic economic earlier alarm systems is of great practical significance. Taking the systemic financial risk as the research object, this paper analyzes the mechanism of financial systemic risk. After that, deep learning technology in financial investment has been used for the first time to reconstruct the index system of financial security evaluation and early warning. The application of deep learning technology in the early warning of systemic financial risks is realized, which provides a reliable basis for the regulatory authorities to build a financial risk early warning system and makes empirical research.
Human Umbilical Cord Mesenchymal Stem Cell-Derived Exosome Repairs Endometrial Epithelial Cells Injury Induced by Hypoxia via Regulating miR-663a/CDKN2A Axis
Authors: Wang Hanbi , Liu Simiao , Zhang Wanyu , Liu Meizhi , Deng Chengyan
Published: October 2022

Aim. Thin endometrium remains a severe clinical challenge with no effective therapy to date. We aimed at exploring the role and molecular mechanism of human umbilical cord mesenchymal stem cell- (hucMSC-) derived exosomes (hucMSC-Ex) in repairing hypoxic injury of endometrial epithelial cells (EECs). Methods. Exosomes were harvested from the conditioned medium of hucMSC and characterized using western blot, transmission electron microscopy (TEM), flow cytometry, and nanoparticle tracking analysis (NTA). EECs were subjected to hypoxic conditions before cocultured with hucMSC-Ex. Cell viability, apoptosis, and migration were determined with CCK-8, flow cytometry, and wound healing assay, respectively. Apoptosis/EMT-related proteins were detected by western blot. The miRNA profiling was determined by RNA sequencing. The expression of miR-663a and CDKN2A was measured by qRT-PCR. MiR-663a in EECs was overexpressed by transfecting with miR-663a mimics. Results. Mesenchymal stem cells (MSCs) markers CD73, CD90, and CD106 were positively expressed in hucMSCs. Exosome isolated from hucMSC expressed CD63 and TSG101, and were 100–150 nm in diameter. HucMSC-Ex promoted cell proliferation inhibited by hypoxia. And hucMSC-Ex also inhibited hypoxia-induced apoptosis, migration, and EMT of EECs by upregulating the expression of Bcl-2 and E-cadherin and downregulating Bax and N-cadherin levels. Further, bioinformatics research found that hucMSC-Ex coculture can significantly upregulate the expression of miR-663a and decrease the expression of CDKN2A in hypoxia-induced EECs. Furthermore, miR-663a overexpression inhibited CDKN2A expression and increased the expression of Bcl-2 and E-cadherin in hypoxia-induced EECs. Conclusions. HucMSC-Ex promoted cell proliferation, inhibited cell apoptosis, migration, and EMT in hypoxia-induced EECs, thereby alleviating hypoxia-induced EECs injury, which may be related to its regulation of miR-663a/CDKN2A expression. Our study indicated that hucMSC-Ex might benefit for repairing thin endometrium.
Dynamic Resource Allocation in an Adversarial Urban IoBT Environment
Authors: Wu Weiwei , Lin Di
Published: October 2022

The advances of the Internet of Battlefield Things (IoBT) would improve the flexibility and efficiency of military operations. Without an effective dynamic adversarial mechanism, soldier devices might malfunction, and machine intelligence technologies could hardly support military operations on a battlefield. In this paper, we propose a game theoretical model considering the adversarial and dynamic nature of the urban IoBT environment. Our algorithm is designed to optimize the whole network’s efficiency with the premise that both the attacking and defending parties can maximize their benefit. Meanwhile, we also attempt to consider the interactive effects of channel fading by using a Nakagami distribution based Markov process. The experimental results show that considering the impact of the adversarial and dynamic nature of urban IoBT, our proposed algorithm can improve network performance by 30%-50%.
The Oncogenic and Immunological Roles of Apoptosis Antagonistic Transcription Factors in Human Tumors: A Pan-Cancer Analysis
Authors: Lu Feng , Wu Juan , Zou Hongpeng , Yang Xin , Wu Yongbing , Xu Jianjun
Published: October 2022

Background. Apoptosis-antagonizing transcription factor (AATF) participates in tumor progression in multiple cancer types. However, its role across cancers is not well understood. Methods. Data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Clinical Proteomic Tumor Analysis Consortium (CPTAC), and Human Protein Atlas (HPA) were used to analyze the multiomic roles of AATF in 33 tumor types, including gene and protein expression, survival prognosis, gene mutation, DNA methylation, protein phosphorylation, AATF coexpressed genes and their enrichment analysis, and immunological analysis. Results. In TCGA and GTEx databases, 31 tumors and their corresponding normal tissues had AATF expression data, and it was differentially expressed in 29 of them. AATF was elevated in 27 tumors, decreased in 2 tumors, and was a risk factor for overall survival (OS) in 8 tumors and a risk factor for disease-free survival (DFS) in 4 tumors. AATF expression levels in various cancer types were significantly correlated with the infiltration levels of cancer-associated fibroblasts, endothelial cells, CD4+ T cells, B cells, myeloid dendritic cells, eosinophils, and macrophages. The immune checkpoints PD-1, PD-L1, and CTLA4 were positively correlated with AATF expression in bladder urothelial carcinoma (BLCA), kidney chromophobe (KICH), and prostate adenocarcinoma (PRAD). Conclusion. In cancer, AATF expression is generally higher than that in normal tissue, and it is also associated with immunomodulation-related genes. AATF may be a risk factor for poor prognosis across cancers.
Experimental Study of Hollow RC Beams Strengthened by Steel Fiber under Pure Torsion
Authors: Abdullah Mazin Diwan , Malik Hawraa S.
Published: October 2022

This paper examines the effectiveness of pure torsional loads on hollow reinforced concrete high-strengthened beams. Engineers need to know how much twist a structural member generates when exposed to torsional loads to design it properly. This is done through an experimental investigation of the torsional behavior of reinforced concrete (RC) beams using twelve hollow rectangular beams with varying parameters, such as the spacing of the stirrups, the influence of the steel fiber fraction, and the main reinforcement amount. Four values of fiber volume fractions (0, 0.5%, 0.75%, and 1%), three spacings of transverse reinforcements (60,100, and 150 mm), and various longitudinal reinforcements (8Ф12 mm, 6Ф12 mm, and 4Ф12 mm) have been used. The tested beams had the same length (1000 mm), cross-sections, concrete mixture, and quality control. In the hollow beams, the interior dimensions were 180 mm × 180 mm, while the exterior dimensions were 300 mm × 300 mm. Torsional loads were applied to all the beams using custom-built test equipment. This study highlighted that the structural characteristics of hollow RC beams could be improved by increasing the fiber volume, lowering the stirrup spacing, and increasing the longitudinal reinforcement. Torsion moments rose by 132% when the fractional volume of fiber was increased from 0% to 1%, while they rose by 71.27% when the longitudinal reinforcement was increased from 4 to 8 bars for beams with fractional volumes of fiber of 0.5 percent and the same transverse reinforcement ratios.
Simulation‐Based Multiobjective Optimization of Open‐Pit Mine Haulage System: A Modified‐NBI Method and Meta Modeling Approach
Authors: Abolghasemian Milad , Kanafi Armin Ghane , Daneshmand-Mehr Maryam
Published: October 2022

A large number of engineering problems involve several conflicting objectives, which today are often solved through expensive simulation calculations. Methods based on meta‐models are one of the approaches to solving this group of problems. In this paper, multiobjective optimization in the extraction system of a copper open‐pit mine complex is presented by the modified‐NBI optimization method and regression meta‐model. For this purpose, two objective functions of maximizing the amount of total extraction, which is the sum of the extraction of sulfide, oxide, low‐grade ores, and waste in this mine, and minimizing the transport time of haulage according to the limitation of its storage capacity, transport equipment, and budget are considered. The Central Composite Design (CCD) method is used to build the Design of Experiments (DOE) for the design variables. The considered design variables are the number of trucks of 120 tons, 240 tons, 35 tons, and 100 tons. The number of targets considered in each design combination is considered the response surface. The suitable meta‐model to maximize the total extraction rate and minimize the transport time of the haulage, two modified functions of nonlinear regression have been determined. The accuracy of the models for selection has been done using PRESS and R2 statistics. The most common PRESS error has also been used to validate the meta‐models. Then the multiobjective optimization problem was solved using the modified‐NBI method. Finally, Pareto and optimal solutions using the proposed approach were presented and discussed.
A Comparative Analysis of Methods of Endmember Selection for Use in Subpixel Classification: A Convex Hull Approach
Authors: Sivakumar Vidhya Lakshmi , Ramkumar K. , Vidhya K. , Gobinathan B. , Gietahun Yonas Wudineh
Published: October 2022

Mixed pixels in aerial and satellite images are common, especially near the boundaries of two or more discrete classes; that is, they tend to occur at the transitional region between two classes. Ideally, to decipher the mixed pixel, a soft classification is performed compared to a hard- or a per-pixel classification. Soft or subpixel classification is carried out where the fractional cover of the LULC contained within a pixel is derived. Endmembers are extracted for three VNIR bands of ASTER data for two image datasets using three approaches, namely, principal component analysis (PCA), pixel purity index (PPI), and convex hull-Graham scan (CHGS). On comparing the DN values of the identified endmembers, it is observed that the CHGS method provides the most appropriate end members than the PCA-derived and PPI-derived end members. This is based on deriving the endmembers from two different image conditions. Convex hull implemented using the Graham scan algorithm delineates the pure pixel and pinpoints the exact number of endmembers. These accurate end members would result in accurate proportions of the land cover for better modeling of the terrain.
Identification of a 5-Hydroxymethylation Signature in Circulating Cell-Free DNA for the Noninvasive Detection of Colorectal Cancer
Authors: Liu Hongwei , Tang Tao , Zhang Huixian , Ting Weiren , Zhou Peng , Luo Ying , Qi Huaxing , Liu Yanmei , Liu Yongxin , Zhou Meifang , Yin Weiguo , Lin Jinduan
Published: October 2022

Background. As a crucial epigenetic modification, DNA 5-hydroxymethylcytosine (5-hmC) plays a key role during colorectal cancer (CRC) carcinogenesis. Nevertheless, the levels of 5-hmC-related genes in the circulating DNA of CRC remain largely unknown. Methods and Results. The GSE81314 dataset from the Gene Expression Omnibus (GEO), which was generated by chemical marking-based low-input shotgun sequencing to detect 5-hmC in circulating cell-free DNA (cfDNA) was used in the present study. The GSE81314 dataset includes data for 8 plasma samples from healthy individuals and 4 plasma samples from CRC patients. The difference in the 5-hmC levels in cfDNA between the CRC group and healthy individuals was analyzed by the differentially expressed genes (DEG) package. Weighted gene coexpression network analysis (WGCNA) was conducted to analyze gene coexpression modules associated with sample characteristics. DEG analysis identified 19 upregulated and 9 downregulated 5-hmC-related genes. WGCNA showed that the pink, purple, and brown modules, which contain 531 genes in total, were significantly correlated with CRC (0.66, 0.61, and -0.59, respectively). We used gene set enrichment analysis (GSEA) software to compare 5-hmC-related genes and pathways between CRC patients and healthy controls. We further performed a protein–protein interaction (PPI) analysis and identified 4 nodes (LCN2, LRG1, S100P, and TACSTD2) that played key roles in the network, and we analyzed the expression of these nodes S100P in the GEPIA database. Consistent with the 5-hmC levels in CRC patient plasma, our external validation results from the GEPIA and UALCAN databases showed that LCN2, LRG1, S100P, and TACSTD2 were highly expressed in CRC tissue compared with controls. The DNA promoter methylation levels of LCN2, LRG1, and S100P were lower in CRC tissue than in normal control tissue. Conclusion. The present findings suggest that abnormality in cell-free DNA hydroxylation in plasma may be associated with CRC. In addition, the 5-hmC levels of LCN2, LRG1, S100P, and TACSTD2 in circulating cfDNA may be used as potential noninvasive markers for CRC.
Role of Intelligent Management Systems in Surgical Punctuality and Quality of Care
Authors: Li Gendi , Huang Shenhui
Published: October 2022

Objective. The main objective is to illustrate the role of intelligent management systems in surgical punctuality and quality of care. Methods. 72 registered nurses were selected from our operating room, and 180 patients who needed surgery were randomly divided into the control group and the observation group for satisfaction survey and satisfaction analysis. Results. The correct rate of surgical clothing distribution and the qualified rate of clothing recovery were improved, and the punctuality rate of the operation was enhanced than before the implementation of the intelligent management system. The accurate positioning of surgical items and the accurate statistics of equipment use time were enhanced than before implementation. The error rate of surgical item preparation after implementation was lessened than before implementation. Both nursing satisfaction and patient satisfaction after implementation were increased than before implementation. Conclusion. The intelligent management system improves the punctuality of surgery and the quality of care in the operating room.
Association between the Triglyceride-Glucose Index and the Risk of Large Artery Atherosclerotic Stroke
Authors: Jiang Mingfei , Wu Huan , Zhang Huiping , Su Fan , Cao Lei , Ren Xia , Tatenda Grace , Hu Jian , Cheng Mingjia , Wen Yufeng
Published: October 2022

The aim of this study is to evaluate the value of the triglyceride-glucose (TyG) index and the risk of large artery atherosclerotic (LAA) stroke. Information on general demographic and clinical characteristics, magnetic resonance angiography (MRA) examination, and blood biochemical index determination were obtained. Based on age stratification, three models to evaluate the odds ratio (OR) and the 95% confidence interval (95% CI) were employed to determine the correlation between the TyG index and the risk of LAA stroke. The most effective TyG index threshold in predicting a high risk of LAA stroke was identified using receiver operating characteristic (ROC) curve analysis. Logistic regression verified the association between the risk of LAA stroke and the TyG index. Both with and without age stratification, logistic regression analysis showed that the TyG index was a significant predictor of the occurrence of LAA stroke (

P
<
0.05

). The maximum Youden index for determining a high risk of LAA stroke was found at a TyG index of 4.60. The area under the ROC curve was 0.69 (95% CI: 0.646–0.742,

P
<
0.05

), sensitivity was 78.0%, and specificity was 63.4%. An elevated TyG index was remarkably associated with a high risk of LAA stroke.
Performance Evaluation of Multiagent Reinforcement Learning Based Training Methods for Swarm Fighting
Authors: Gao Huanli , Cai Yahui , Cai He , Lu Haolin , Lu Jiahui
Published: October 2022

In this paper, we conducted a performance evaluation of two multiagent reinforcement learning based training methods for swarm fighting, namely, the multiagent reinforcement learning (MARL) training method, and the combined multiagent reinforcement learning and behavior cloning (MARL-BC) training method. The behavior cloning expert is taken from some well-trained model in the final steady phase by the MARL training method. From the perspective of winning rate, the performances of these two different training methods can be divided into three phases. In the first phase, learning progresses slowly for both these two training methods. As the model trained by the MARL training method grows stronger, the experience of the behavior cloning expert gradually becomes useful, and the second phase kicks off where the MARL-BC training method takes obvious advantage. Surprisingly, the advantage of the MARL-BC training method will disappear as the learning progress goes on because in this final phase the expert of the behavior cloning training method can no longer offer the right strategy in presence of the ever changing environment and opponent.
Apatinib Functioned as Tumor Suppressor of Synovial Sarcoma through Regulating miR-34a-5p/HOXA13 Axis
Authors: Feng Qi , Wang Donglai , Guo Peng , Zhang Zibo , Feng Jiangang
Published: October 2022

Objective. Synovial sarcoma is a rare malignant tumor. The role of apatinib in synovial sarcoma remains unclear. In this study, we aimed to determine the biological functions and the potential molecular mechanism of action of apatinib in synovial sarcoma. Methods. SW982 cells were stimulated with apatinib. The relative expression of the genes was determined by performing qPCR. Protein levels were evaluated by western blot and immunohistochemistry assays. Proliferation, apoptosis, migration, and invasion of SW982 cells were determined by the CCK-8 assay, clone formation assay, flow cytometry, wound healing, and the transwell assay, respectively. Additionally, SW982 cells were injected into mice to induce synovial sarcoma. Results. Apatinib decreased the proliferation, migration, and invasion but increased the apoptosis of SW982 cells. Apatinib repressed tumor growth in vivo and elevated miR-34a-5p in SW982 cells. The inhibition of miR-34a-5p repressed the reduction of proliferation, migration, and invasion and also the elevation of apoptosis in apatinib-treated SW982 cells. The luciferase activity decreased after cotransfection of the miR-34a-5p mimic and the wild-type HOXA13 vector. Additionally, an increase in miR-34a-5p repressed the levels of HOXA13 mRNA and protein. Moreover, HOXA13 reversed these patterns caused by the inhibition of miR-34a-5p in apatinib-treated SW982 cells. Conclusion. Apatinib elevated miR-34a-5p and reduced HOXA13, leading to a significant decrease in proliferation, migration, and invasion, along with an enhancement of apoptosis in SW982 cells. Apatinib suppressed tumorigenesis and tumor growth in SW982 cells in vivo.
Landscape Design of Rural Characteristic Towns Based on Big Data Technology
Authors: Zhang Jian , Sui Yanhui
Published: October 2022

This study explores an effective method for constructing a landscape model of characteristic rural towns. In this study, the landscape pattern index of characteristic rural towns is obtained by calculating the total area, patch density, patch shape index, and average patch fractal dimension of the landscape area of characteristic rural towns. At the same time, this study calculates the minimum function of the three-dimensional rural characteristic town landscape cloud fusion transformation. At the same time, this study uses this function to calculate the 3D translation transformation, the rotation matrix of the 3D model, and the scaling factor transformation of the 3D model to construct the 3D model of the rural characteristic town landscape area. The simulation results show that the above method can reduce the error, reduce the registration time, improve the convergence, and reduce redundancy. This method can enhance the overall effect of constructing a three-dimensional model of a rural characteristic town landscape area.
Knowledge-Based Recurrent Neural Network for TCM Cerebral Palsy Diagnosis
Authors: Li Dongmei , Qu Jintao , Tian Ziwei , Mou Zijun , Zhang Lei , Zhang Xiaoping
Published: October 2022

Cerebral palsy is one of the most prevalent neurological disorders and the most frequent cause of disability. Identifying the syndrome by patients’ symptoms is the key to traditional Chinese medicine (TCM) cerebral palsy treatment. Artificial intelligence (AI) is advancing quickly in several sectors, including TCM. AI will considerably enhance the dependability and precision of diagnoses, expanding effective treatment methods’ usage. Thus, for cerebral palsy, it is necessary to build a decision-making model to aid in the syndrome diagnosis process. While the recurrent neural network (RNN) model has the potential to capture the correlation between symptoms and syndromes from electronic medical records (EMRs), it lacks TCM knowledge. To make the model benefit from both TCM knowledge and EMRs, unlike the ordinary training routine, we begin by constructing a knowledge-based RNN (KBRNN) based on the cerebral palsy knowledge graph for domain knowledge. More specifically, we design an evolution algorithm for extracting knowledge in the cerebral palsy knowledge graph. Then, we embed the knowledge into tensors and inject them into the RNN. In addition, the KBRNN can benefit from the labeled EMRs. We use EMRs to fine-tune the KBRNN, which improves prediction accuracy. Our study shows that knowledge injection can effectively improve the model effect. The KBRNN can achieve 79.31% diagnostic accuracy with only knowledge injection. Moreover, the KBRNN can be further trained by the EMRs. The results show that the accuracy of fully trained KBRNN is 83.12%.
Development of Comprehensive Evaluation Model of Free Trade Port Investment under Macroeconomic Support
Authors: Zhang Haitian , Benxue Wang
Published: October 2022

The financial benchmark rate of return is gradually declining, and the free trade port policy is not enough to improve the investment financial benchmark rate of return. Therefore, a comprehensive evaluation model for free trade port investment under the support of macroeconomics is proposed. A theoretical model of free trade port investment price fluctuations and monetary policy response is constructed under the support of macroeconomics, and the model is used to observe the impact of changes in free trade port investment prices on the economic effects of monetary control policies; thus, free trade port investment price fluctuations are constructed and as a result, a theoretical model of investment price fluctuations and interest rate policy responses in the free trade port is constructed to observe the impact of changes in investment prices in the free trade port on the economic effects of interest rate regulation policies; a theoretical model of investment and fiscal and taxation policy responses in the free trade port is constructed to observe the impact of changes in investment in the free trade port on the economic effects of fiscal and taxation policies. Explore the path of optimizing the comprehensive investment evaluation environment in the pilot free trade zone, and realize the development of a comprehensive evaluation model for investment in the free trade port. The experimental results show that the model can realize the comprehensive evaluation of free trade port investment under the support of the macroeconomy and has a good evaluation effect.
The Impact of Neutrophil‐Lymphocyte Ratio in Febrile Seizures: A Systematic Review and Meta‐Analysis
Authors: Hosseini Samaneh , Gharedaghi Hossein , Hassannezhad Sina , Sadeghvand Shahram , Maghari Amirhossein , Dastgiri Saeed , Talebi Mahnaz , Khanzadeh Shokoufeh
Published: October 2022

This meta‐analysis was conducted to determine the relationship between neutrophil to lymphocyte ratio (NLR) and febrile seizure (FS). Our study was registered with the PROSPERO (ID: CRD42021259944). Web of Science, Embase, PubMed, Scopus, and ProQuest Central were searched, and finally, 17 studies were included. Standardized mean difference (SMD) was reported with a 95% confidence interval (CI) for the NLR levels. Compared with the febrile control group, the FS patients’ NLR levels were significantly higher (SMD = 0.49; 95%CI = 0.26 to 0.72, P < 0.001). Furthermore, we conducted a comparison of NLR levels between febrile controls against simple and complex FS cases separately and found that NLR levels of children with either simple or complex FS were higher compared with those of febrile controls (SMD = 0.42, 95%CI = 0.14 to 0.69, P = 0.003 and SMD = 0.90, 95%CI = 0.71 to 1.09, P < 0.001, respectively). Also, in comparison with the NLR levels of the simple FS group, the complex FS patients’ NLR levels were significantly higher (SMD = 0.59, 95%CI = 0.34 to 0.85, P < 0.001). Our study indicated that NLR could be recommended as an inexpensive diagnostic biomarker for FS. In addition, it can be useful when distinguishing between simple FS and complex FS.