bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative Efficacy of Chinese Patent Medicines for Clearing Heat and Dampness in the Treatment of NAFLD: A Network Meta-Analysis of Real-World Evidence
Authors: Xu Yuan , Wang Yan , Gou Xiao-jun , Wang Man
Published: July 2022

Background. Nonalcoholic fatty liver disease (NAFLD) has emerged as the most common chronic liver disease, as well as a worldwide medical problem with a substantial socioeconomic burden. In China, Chinese patent medicines (CPMs) have been widely utilized as promising and effective therapy options for NAFLD. Traditional Chinese medicine (TCM) is a particular kind of medical science reliant on real-world clinical practices and evidence. Therefore, using the real-world data extracted from pragmatic randomized controlled trials (PRCTs) have more reference value for the application of CPMs in NAFLD. Method. Six databases were searched from their inception up to March 18, 2022. The methodological quality of the included study was evaluated by the Cochrane risk-of-bias tool. Then, The STATA 13.0 program was then used to do a network meta-analysis (NMA) of real-world studies. The surface under the cumulative ranking curve (SUCRA) probability values were applied to rank the examined treatments. Results. Forty-three PRCTs (4997 cases in total) were identified. Da-Huang-Li-Dan capsule (DHLD), Dan-Ning tablet (DN), Dang-Fei-Li-Gan-Ning capsule (DFLGN), Qiang-Gan capsule (QG), and Hua-Zhi-Rou-Gan granule (HZRG) were among the five CPMs tested. As far as the clinical effective rate of the primary outcome index was concerned, the top three CPMs were DN + CDs: OR = 0.19, 95% CIs: 0.12, 0.31 (SUCRA: 81.8%); DFLGN + CDs: OR = 0.21, 95% CIs: 0.09, 0.46 (SUCRA: 74.9%), and DHLD + CDs: OR = 0.26, 95% CIs: 0.10, 0.67 (SUCRA: 61.1%). In terms of liver function index, DN + CDs ranked first in ALT index: MD = 15.81, 95% CIs: 10.05, 21.57 (SUCRA: 85.5%), DFLGN + CDs ranked first in AST index: MD = 14.94, 95% CIs: 4.77, 25.11 (SUCRA: 83.6%), HZRG + CDs ranked first in TC index: MD = 0.53, 95% CIs: 0.28, 1.03 (SUCRA: 87.1%) and TG index: MD = 1.8, 95% CIs: 1.41, 2.30 (SUCRA: 79.9%). Conclusion. Using CPMs as a coadjuvant treatment might be positive efficacious intervention from which patients with NAFLD will derive benefits. When it came to the clinical effective rate and other outcomes, DN + CDs demonstrated a significant improvement in individuals with NAFLD.
In silico Prediction of Deleterious Single Nucleotide Polymorphism in S100A4 Metastatic Gene: Potential Early Diagnostic Marker
Authors: Farhana Aisha , Kothandan Sangeetha , Alsrhani Abdullah , Mok Pooi Ling , Subbiah Suresh Kumar , Khan Yusuf Saleem
Published: July 2022

S100A4 protein overexpression has been reported in different types of cancer and plays a key role by interacting with the tumor suppressor protein Tp53. Single nucleotide polymorphisms (SNP) in S100A4 could directly influence the biomolecular interaction with the tumor suppressor protein Tp53 due to their aberrant conformations. Hence, the study was designed to predict the deleterious SNP and its effect on the S100A4 protein structure and function. Twenty‐one SNP data sets were screened for nonsynonymous mutations and subsequently subjected to deleterious mutation prediction using different computational tools. The screened deleterious mutations were analyzed for their changes in functionality and their interaction with the tumor suppressor protein Tp53 by protein‐protein docking analysis. The structural effects were studied using the 3DMissense mutation tool to estimate the solvation energy and torsion angle of the screened mutations on the predicted structures. In our study, 21 deleterious nonsynonymous mutations were screened, including F72V, E74G, L5P, D25E, N65S, A28V, A8D, S20L, L58P, and K26N were found to be remarkably conserved by exhibiting the interaction either with the EF‐hand 1 or EF‐hand 2 domain. The solvation and torsion values significantly deviated for the mutant‐type structures with S20L, N65S, and F72L mutations and showed a marked reduction in their binding affinity with the Tp53 protein. Hence, these deleterious mutations might serve as prospective targets for diagnosing and developing personalized treatments for cancer and other related diseases.
Parameter Calibration of Sediment Transport Capacity Formula of the Third Entrance of Xinqiman Reservoir in Tarim River Based on CCHE2D Model
Authors: Geng Yixin , Li Yujian , Mao Liang , An Peng
Published: August 2022

In this study, sediment transport at the third entrance of the Xinqiman Reservoir in the Tarim River was simulated using the CCHE2D model. The flow conditions, the suspended sediment concentration of each grain size, and the boundary grain size of the wash load in the reach were determined. Regressions between the suspended sediment concentration, S, and flow condition, U3/gH, and flow-sediment factor, U3/Rω, were developed, which strongly adhered to the power law and Zhang Ruijin’s formula for the sediment transport capacity. The parameters in Zhang Ruijin’s formula for the target reach were determined. Under the defined flow and sediment conditions, sediment particles ≥0.091 mm and particles ≤0.061 can be regarded as the bed material and wash loads, respectively. Using multivariate linear regression, the sediment transport capacity coefficient (k0) and exponent (m) were determined to be 0.0197 and 0.928, respectively. These results can serve as an important theoretical reference for the calculation of sediment transport at the third entrance of the Xinqiman Reservoir in the Tarim River.
Construction of Digital Platform of Religious and Cultural Resources Using Deep Learning and Its Big Data Analysis
Authors: Sun Qian
Published: July 2022

This article analyzes the difficulties associated with the preservation and transmission of religious cultural resources and the difficulties encountered in the new development environment and background. It does so in light of the current state of religious, cultural resources. The protection, growth, and use of religious and cultural resources against the backdrop of the digital era are elaborated upon and critically analyzed in this article. Based on the foregoing discussion, this article conducts a thorough analysis of the development of a digital platform for religious and cultural resources and its big data analysis, and it also suggests an image feature extraction algorithm based on DL. This article develops a clustering CNN based on the network with PCA vector as convolution kernel, which clusters small images and computes principal component vectors according to categories, generating multiple groups of convolution kernels to extract more features so that the input image can select feature extractors adaptively. Simulation and comparative analysis are used in this article to confirm the algorithm’s effectiveness. Compared to the conventional NN algorithm, simulation results indicate that this algorithm is more accurate, with a maximum accuracy of about 95.14 percent. It has some reference value for the research that will be done in relation to the creation of the next digital platform for religious and cultural resources.
Insights on the Dynamics and Toxicity of Nanoparticles in Environmental Matrices
Authors: Devasena T. , Iffath B. , Renjith Kumar R. , Muninathan Natarajan , Baskaran Kuppusamy , Srinivasan T. , John Shani T.
Published: July 2022

The manufacturing rate of nanoparticles (10–100 nm) is steadily increasing due to their extensive applications in the fabrication of nanoproducts related to pharmaceuticals, cosmetics, medical devices, paints and pigments, energy storage etc. An increase in research related to nanotechnology is also a cause for the production and disposal of nanomaterials at the lab scale. As a result, contamination of environmental matrices with nanoparticles becomes inevitable, and the understanding of the risk of nanoecotoxicology is getting larger attention. In this context, focusing on the environmental hazards is essential. Hence, this manuscript aims to review the toxic effects of nanoparticles on soil, water, aquatic, and terrestrial organisms. The effects of toxicity on vertebrates, invertebrates, and plants and the source of exposure, environmental and biological dynamics, and the adverse effects of some nanoparticles are discussed.
Convective Heat Transport in Bidirectional Water Driven Hybrid Nanofluid Using Blade Shaped Cadmium Telluride and Graphite Nanoparticles under Electromagnetohydrodynamics Process
Authors: Ahmad Iftikhar , Zan-Ul-Abadin Qazi , Faisal Muhammad , Loganathan K. , Javed Tariq , Namgyel Ngawang
Published: July 2022

The recent progress in nanotechnology provides the concept of hybrid‐class nano‐fluids having advanced thermal features comparing to regular nanofluids. The idea of a hybrid nanofluid has motivated many researchers because of its convincible performance in thermal systems. The novel theme of the present effort is to scrutinize the consequences of convective heat transfer in bidirectional water driven hybridclass nanofluid involving blade shaped cadmium telluride CdTe and graphite C nanoparticles with electromagnetohydrodynamics (EMHD) process. The transport equations representing the aforementioned topic are firstly nondimensionalized by using scaling‐group transformation and then tackled by the Keller‐box method, numerically. The significant results for pertinent parameters have been simulated and presented graphically as well as in tabular forms. Coefficients of drag forces are diminished with the more loadings of cadmium telluride and graphite nanoparticles and opposite results are noticed in the case of the Nusselt number. Heat transport has been improved significantly with more loadings of nanoparticles from 1 wt% to 10 wt%. A comparison benchmark for a limited version of the investigation is made with the previously published data.
Effect of the Irrigation Interval and Nitrogen Rate on Yield and Yield Components of Onion (Allium cepa L.) at Arba Minch, Southern Ethiopia
Authors: Tadesse Tagay , Sharma Parshotam Datt , Ayele Tuma
Published: July 2022

Onion (Allium cepa L.) is an important cash crop for smallholder farmers in the Central Rift Valley of Ethiopia. However, its productivity is low, owing to a number of factors including inappropriate irrigation water and nitrogen management. A field experiment was, therefore, conducted at Amibara farm, Arba Minch, Ethiopia, during the 2018/19 dry season to determine the effect of the irrigation interval and nitrogen rate on growth, yield, and yield components of onion (Bombay Red variety). The treatments comprised four irrigation intervals (3, 6, 9, and 12 days of crop water requirement, ETc) and four nitrogen levels (0, 50, 100, and 150 kg·N·ha−1). The experiment was laid out in a split-plot design using irrigation intervals as main plots and nitrogen rates as subplots with three replications. The growth parameters, yield components, and final yield of onion were significantly higher with 3 and 6 days irrigation intervals (which were statistically similar) than 9 and 12 days irrigation intervals. The increasing N rate significantly increased the growth and yield components up to 150 kg·N·ha−1, but the response was significant only up to 100 kg·N·ha−1 on the final yield of the crop. The growth and yield contributing parameters, showing enhancement with frequent irrigation and higher N rates, had a significant bearing on the final yield of onion. The irrigation at 6 days interval combined with 100 kg·N·ha−1 gave a higher marketable yield (30.21 t·ha−1), net return (Birr 288,458 ha−1), and marginal rate of return (8586%). As such, irrigation at an interval of 6 days and fertilizer N at the rate of 100·kg·ha−1 may be recommended for higher productivity and profitability of onion at Arba Minch, Gamo Zone, southern Ethiopia.
Design and Research of Computer Network Education and Teaching System Based on Multisensor Information Fusion
Authors: Li Xiang , Fu Yu
Published: July 2022

With the rapid development of information technology, information network has become the fundamental guarantee of social progress. The network is the basic material foundation of the information society. It is ubiquitous, and human activities are highly dependent on it. Education is also inseparable from the Internet. Online learning is emerging as a new form of basic education. At the same time, it needs to be considered that the information received by the sensor is always incomplete, reflecting the information measured in a particular part of the object but not understanding the total content. Therefore, it is necessary to use multiple sensors to identify an object from multiple angles, obtain additional dimensional information about the object, and combine multidimensional information. This paper introduces the design and implementation of a teaching network system for computer network courses, starting from the overall concept of the system, the selection of development methods and the specific implementation plan of the system, and then introduces the specific content of each module in the teaching system in detail. The recognition success rates of five groups of experiments based on multisensor information fusion are 96.9%, 95.7%, 98.4%, 96.3%, and 98.7%, respectively.
Treatment of Elderly Femoral Intertrochanteric Fracture by InterTan Intramedullary Nail and PFNA
Authors: Su Zhengbing , Yang Minghui , Luo Gang , Liang Linlin , Hao Yong
Published: July 2022

To analyze the treatment of elderly femoral intertrochanteric fracture (EFIF) using InterTan intramedullary nail (InterTanIN) and proximal femoral nail antirotation (PFNA). A total of 75 patients suffering from EFIF receiving intramedullary fixation were retrospectively collected. According to intramedullary fixation methods, the patients were separated into InterTanIN group and PFNA group. Parameters including the surgery time, blood loss, number of X-ray fluoroscopy, hospital stays, bone-healing time, postoperative Harris hip score (HIS) (1 month, 3 months, 6 months, and 12 months), and complications were collected and analyzed. The results showed surgery time, blood loss, and number of X-ray fluoroscopy in InterTanIN group were higher than those in PFNA group (

P
<
0.05

). The mean hospital stay in the InterTanIN group was comparable to that in the PFNA group (

P
>
0.05

). There was no significant difference in bone-healing time between the InterTanIN group and PFNA group (

P
>
0.05

). The postoperative HIS of InterTanIN group was statistically better than PFNA group at the 3rd month and the 6th month (

P
<
0.05

). With the extension of recovery time, the gap between the two groups gradually narrowed. The postoperative implant displacement happened more often in the PFNA group than in the InterTanIN group. EFIF treated with InterTanIN or PFNA could achieve good long-term efficacy. Although InterTanIN has the disadvantages of increased operative time, blood loss, and radiation exposure compared to PFNA, the postoperative hip function recovery of InterTanIN seems to be more reliable and stable than PFNA.
Effect of Image Detection and Analysis and Hospice Nurse Mediated Aromatherapy on Pain in Patients with Advanced Cancer in Intelligent Medical Environment
Authors: Shi Dongmei , Shi YanXia , Li Ying , Hong Jinhua
Published: August 2022

Objective. In order to better alleviate the pain symptoms of patients with advanced cancer, this study adopts image detection and analysis and hospice nurse mediated aromatherapy, so as to comprehensively understand the physical condition of patients with advanced cancer and finally implement the nursing scheme of aromatherapy. Methods. Sixty advanced cancer patients admitted to a tertiary and grade A oncology hospital in Jiangxi Province from December 2020 to March 2022 were selected. This study was randomized into trial and control groups. The control group contained 30 regular treatment patients and 30 regular nursing patients for advanced cancer patients, and the trial group performed a 28‐day hospice care specialist nurse‐mediated aromatherapy based on the control group. Pain and quality of life scores were measured before and after the intervention in both groups. The experimental group consisted of 30 cases, with the mean age of 58.2 years; the control group consisted of 30 cases, with the mean age of 58.6 years. Results. 60 patients with advanced cancer were selected for group comparison. The results showed that the effect of aromatherapy mediated by hospice nurse on pain score, QLQ‐C30, index value of patients with advanced cancer (the experimental group) was better than that of patients with advanced cancer (the control group). Conclusion. Through retrospective analysis, we investigated the patients with advanced cancer and discussed the difference between conventional therapy and aromatherapy. The results showed that aromatherapy based on image detection and analysis and mediated by Anning nurses was helpful to alleviate the physical function of patients with advanced cancer and improve their quality of life, which provided a reference for clinical application.
Evaluation of Neurodevelopmental Outcomes in Premature Twins (Multigestations) with Retinopathy of Prematurity Receiving Anti-VEGF: A Comparison Study
Authors: Ghassemi Fariba , Makateb Ali , Dastjani Farahani Afsar , Mahmoudi Alireza , Bazvand Fatemeh
Published: July 2022

Purpose. To assess possible neurodevelopmental delay (NDD) following intravitreal antivascular endothelial growth factor (VEGF) injection in neonates with retinopathy of prematurity (ROP). Methods. In this retrospective cohort study, neurodevelopmental milestones in patients with a history of ROP and intravitreal bevacizumab (IVB) injection were compared with other gestations that received either no treatment or only a laser for treatment. Results. One hundred and twenty-five neonates (of 59 multi-gestation pregnancies) were included in this study (with the range of age 1–7 years old). Sixty-five (51.18%) were male and sixty-two (48.81%) were female. The mean gestational age (GA) and birth weight of all neonates were 29.69 ± 1.57 weeks (ranges: 26–33 weeks) and 1312.50 ± 269.33 grs (ranges: 730–2100 grs). None of the neurodevelopmental outcomes were statistically different when two subgroups in group A (IVB vs. control) were compared. None of the differences between IVB and laser treated subgroups is statistically significant, except for “reaching for toys,” which was delayed in the laser treated subgroup (6.6 ± 2.5 and 6.9 ± 2.5 months in IVB and laser treated subgroups, respectively). Conclusion. In neonates with ROP, there is no linear correlation between intravitreal anti-VEGF injection and neurodevelopmental delay.
Obtaining Parallel Sentences in Low-Resource Language Pairs with Minimal Supervision
Authors: Shi Xiayang , Yue Ping , Liu Xinyi , Xu Chun , Xu Lin
Published: August 2022

Machine translation relies on parallel sentences, the number of which is an important factor affecting the performance of machine translation systems, especially in low-resource languages. Recent advances in learning cross-lingual word representations from nonparallel data by machine learning make a new possibility for obtaining bilingual sentences with minimal supervision in low-resource languages. In this paper, we introduce a novel methodology to obtain parallel sentences via only a small-size bilingual seed lexicon about hundreds of entries. We first obtain bilingual semantic by establishing cross-lingual mapping in monolingual languages via a seed lexicon. Then, we construct a deep learning classifier to extract bilingual parallel sentences. We demonstrate the effectiveness of our methodology by harvesting Uyghur-Chinese parallel sentences and constructing a machine translation system. The experiments indicate that our method can obtain large and high-accuracy bilingual parallel sentences in low-resource language pairs.
Self-Healing and Shortest Path in Optical Fiber Sensor Network
Authors: Hu Xingliu , Si Haifei , Mao Junhui , Wang Yizhi
Published: August 2022

In this study, a new square-based fiber Bragg grating (FBG) sensor network model is proposed to address possible link failures in FBG sensor networks and improve their reliability. Graph theory and optical switching are simultaneously applied to these sensor networks to improve their self-healing ability; the FBG sensor network is regarded as a directed graph. Three commonly used self-short-circuit algorithms are compared in terms of the self-healing capabilities that they provide to the optical fiber sensor network. Among these, the shortest-path faster algorithm achieved a high, nearly 90% repair accuracy and had an average repair time of 0.103 s, the shortest in this study. The newly designed FBG self-healing network can be reorganized and repaired when local damage occurs, thereby improving its reliability.
[Retracted] High‐Temperature‐Resistant, Clean, and Environmental‐Friendly Fracturing Fluid System and Performance Evaluation of Tight Sandstone
Authors: Wang Minghao , Cheng Hanlie , Wei Jianfei , Zhang Ke , Cadasse David , Qin Qiang
Published: August 2022

Hydraulic fracturing, as an oil‐water well stimulation and injection technology, is particularly important in the production and stimulation of low‐permeability oil and gas fields, and the performance of the fracturing fluid directly affects the success of the fracturing operation. Compared with traditional water‐based fracturing fluids, clean fracturing fluids have the advantages of strong sand‐carrying ability and easy gel breaking with no residue. Aiming at the problem of poor temperature resistance and shear resistance of the clean fracturing fluid, based on previous research, this paper selects a high‐temperature‐resistant clean fracturing fluid system and evaluates the performance of the system. The research results show that the system has better rheological properties, better sand‐carrying performance, shorter gel‐breaking time, and less damage to the reservoir.
Anti-Phospholipase A2 Receptor Antibody Expression at Different Stages of Idiopathic Membranous Nephropathy
Authors: Fu Keying , Zhang Pei , Han Yeguang , Wang Ru , Cai Junhong
Published: July 2022

The significance of blood anti-phospholipase A2 receptor (PLA2R) antibodies in the diagnosis of different stages of idiopathic membranous nephropathy (IMN) was investigated. The expression and distribution of anti-PLA2R antibodies in renal biopsy tissue of patients with different stages of IMN were examined by immunohistochemistry. In addition, blood anti-PLA2R antibodies were determined by indirect immunofluorescence for the same patients, and the results were compared with the anti-PLA2R antibody expression in renal biopsy tissue. The positive fluorescence intensities of IMN stages I, IV, and V were mostly ± or + (40/80). There was no significant difference in fluorescence titer between these stages (

p
>
0.05

). These results were consistent with the immunohistochemistry results, and the kappa statistic was 0.95. The positive fluorescence intensities of IMN stages II and III were mostly ++ to ++++ (33/60). There was no significant difference in fluorescence intensities between these two stages (

p
>
0.05

), but there was a significant difference in fluorescence intensities between stages II and III and stages I, IV, and V (

p
<
0.001

). These results were consistent with the immunohistochemistry results, and the kappa statistic was 0.97 (

p
<
0.001

). Therefore, blood anti-PLA2R levels were positively correlated with anti-PLA2R expression in renal biopsy tissue in patients with different stages of IMN. In addition, the fluorescence intensities of IMN stages II and III were significantly different from those of stages I, IV, and V. Therefore, blood anti-PLA2R levels can be used for in vitro differential diagnosis and the monitoring of treatment, as it can distinguish stage II; and III; from stage I, IV, and V IMN.
Digital Twin-Driven Machine Condition Monitoring: A Literature Review
Authors: Liu He , Xia Min , Williams Darren , Sun Jianzhong , Yan Hongsheng
Published: July 2022

Digital twin (DT), aiming to characterise behaviors of physical entities by leveraging the virtual replica in real time, is an emerging technology and paradigm at the forefront of the Industry 4.0 revolution. The implementation of DT in predictive maintenance has facilitated its growth. As a major component of predictive maintenance, condition monitoring (CM) has great potential to combine with DT. To describe the state-of-the-art of DT-driven CM, this paper delivers a systematic review on the theoretical and practical development of DT in advancing CM. The evolution of concepts, main research areas, applied domains, and related key technologies are summarised. The driver of DT for CM is detailed in three aspects: data support, capability enhancement, and maintenance mode shift. The implementation process of DT-driven CM is introduced from the classification of DT modelling and the extension of monitoring algorithms. Finally, current challenges and opportunities for future research are discussed especially concerning the barriers and gaps in data management, high-fidelity modelling, behavior characterisation, framework standardisation, and uncertainty quantification.
An Updated Review of Driving‐Pressure Guided Ventilation Strategy and Its Clinical Application
Authors: Yang Guanyu , Hu Chunhui , Sun Zhentao
Published: August 2022

Traditional lung‐protective ventilation strategies (LPVS) are currently used to reduce the incidence of postoperative pulmonary complications (PPCs), including low tidal volume (VT), positive end‐expiratory pressure (PEEP), low inspiratory plateau pressure (Pplat), permissive hypercapnia, and recruitment maneuver (RM). However, a meta‐analysis showed that high driving pressure was closely associated with the incidence of PPCs, but not with PEEP or VT, which led to the driving pressure‐guided ventilation strategy. Some studies have proved that the driving pressure‐guided ventilation strategy is superior to the traditional LPVS in reducing the incidence of PPCs. The purpose of this review is to present the current research progress and application of driving pressure‐guided ventilation strategy.
Study of PD‐1 Customization and Autoimmune T Cells for Advanced Colorectal Cancer with High MSI Expression
Authors: Li Na , Zhang Xiaojie , Zhang Yinsong , Yang Fang , Zhou Fengju
Published: July 2022

Objective. To evaluate the significance of PD‐1 customization and autoimmune T‐cell therapy for advanced colorectal cancer with high MSI expression. Methods. One hundred and eight patients with advanced colorectal cancer with high MSI expression admitted to our hospital between August 2019 and January 2022 were divided into control and study groups, and PD‐1 customization and autoimmune T‐cell therapy were administered to the two groups, respectively. Trends in immune indexes, PD‐1 exposure, and survival rates were studied in both groups. Results. The treatment efficiency of the study group was 90.74%, which was higher than that of the control group (61.11%) (P < 0. 05); after treatment, the presence of CDl07a, perforin, and GranB cells was significantly higher in both groups compared with that before treatment, but the expression of PD‐1 was more pronounced in the study group (P < 0. 05); that is, the expression of PD‐1 in peripheral T lymphocytes in the study group compared with that of the control group was higher in patients with grade III‐IV, and peripheral T lymphocytes were also higher in patients with grade III‐IV compared with patients with grade I‐II (P < 0. 05). Conclusion. PD‐1 customization combined with autoimmune T‐cell therapy is a novel therapeutic modality that can substantially improve.
Accelerated Aging Effects on Color Change, Translucency Parameter, and Surface Hardness of Resin Composites
Authors: Fidan Muhammet
Published: August 2022

Background. The aging process can induce a change in the surface microstructure of materials, the chemical compositions of matrices, and the filler particles of resin composites. This study is aimed at evaluating the effects of accelerated artificial aging (AAA) on the color change, translucency parameter (TP), and surface hardness of resin composites. Methods. Five resin composite materials (Tetric N‐Ceram, Filtek Z250, Charisma Smart, Herculite Classic, and Escom100) were evaluated. A spectrophotometer was used for color measurements (L∗, a∗, and b∗). TP and color changes (ΔE00) were calculated using the CIEDE2000 formula. The resin materials were subjected to aging for 300 hours. The hardness and TP values were measured before and after AAA. One‐ and two‐way ANOVA and the Tukey test were used. The significance level was accepted as p < 0.05. Results. Escom100 had significantly higher ΔE00 values than the other resin composites, and Charisma Smart had significantly lower ΔE00 values than the other tested materials (p < 0.05). Before and after AAA, Charisma Smart had the lowest TP values, and Filtek Z250 exhibited the highest hardness values (p < 0.05). For TP and surface hardness, the effect size value of the composite material was found to be higher than that of AAA. Conclusions. After AAA, the investigated resin composites had ΔE00 values that were above clinically acceptable thresholds. After aging, the tested materials generally exhibited decreases in L∗ values and a∗ values, while increases in b∗ values were observed. The ΔTP values of the resin composites were similar. AAA significantly increased the surface hardness of the tested materials.
Influence of Zinc-Saturated Zeolite on Portland Cement Hydration Kinetics
Authors: Barbir Damir , Dabic Pero
Published: August 2022

This work examines the influence of zeolite saturated with zinc (SZ) on the early hydration of Portland cement. The measurements and results indicate that the microcalorimetric method allows continuous observation and determination of SZ’s influence on kinetic processes in the early stages of hydration. According to the total heat released after 48 hours of hydration, higher SZ content results in lower heat values, while the maximum hydration occurs earlier. As SZ proportion increases, the rate of heat release and the degree of hydration decrease. Measured hydration degrees differ significantly from the calculated values when SZ is added to Portland cement, especially later in the hydration process.
[Retracted] A Novel Method for Parkinson’s Disease Diagnosis Utilizing Treatment Protocols
Authors: Al-Otaibi Shaha , Ayouni Sarra , Khan Md Maruf Haque , Badr Malek
Published: August 2022

It makes no difference whether a person is male or female when it comes to neurodegenerative disorders; both sexes are equally susceptible to their devastating effects. Sometimes, it is unclear why a person in their life got a condition that is well‐known in the world, such as Parkinson’s disease. Other times, it is evident why the individual obtained the ailment (PD). In modern times, a variety of cutting‐edge algorithms that are based on treatment protocols have been developed for the purpose of diagnosing Parkinson’s disease. The approach that is presented in this article is the most current one; it was created using deep learning, and it can predict how severely Parkinson’s disease would affect a patient. In order to diagnose this condition, it is necessary to conduct a comprehensive medical history, a history of any past treatments, physical exams, and certain blood tests and brain films. Because they are less time‐consuming and costly, diagnoses are becoming an increasingly important part of medical practice. The diagnosis of Parkinson’s disease by the physician is supported by the findings of the present research, which analyzed the voices of 253 participants. Preprocessing is done in order to get the most accurate results possible from the data. In order to carry out the technique of balancing, a methodical sampling approach was used to choose the data that would afterwards be evaluated. Using a feature selection approach that was determined by the magnitude of the label’s influence, many data groups were created and organized. DT, SVM, and kNN are three methods that are used in classification algorithms and performance assessment criteria. The model was developed as a result of selecting the classification method and data group that had the greatest performance value. This decision led to the creation of the model. During the process of building the model, the SVM technique was used, and data comprising 45% of the original data set were utilized. The information was arranged in descending order of significance, beginning with the most pertinent. In addition to achieving exceptional outcomes in every other aspect of the project, the performance accuracy target was successfully met at 86 percent. As a consequence of this, it has been decided that the physician will be provided with medical decision support with the assistance of the data set obtained from the speech recordings of the individual who may have Parkinson’s disease and the model that has been developed. This has led to the conclusion that medical decision support will be offered to the physician.
Strategies to Promote Smart City Cultural Scene Construction through Multi-Sensor Fusion Data
Authors: Zhou Ye
Published: July 2022

The improvement of the level of market economy has driven the rapid development of urban culture, and urban cultural space, as one of the components in the overall development of smart cities, plays an irreplaceable and key role in the display of urban spiritual connotation and style. Today’s urban cultural construction is not only limited to cultural individuals but also a comprehensive construction work that needs to be considered and coordinated with the overall development of the city. However, in today’s cultural space construction, there are few cultural space construction strategies that can integrate economic characteristics, spatial characteristics, and cultural characteristics. This paper incorporates multisensor data fusion technology into a strategy for building cultural spaces in smart cities, and the theoretical basis of smart city cultural space construction is combined with multisensor functional model and fuzzy integral algorithm, and the realization of cultural space strategy is studied. And compared with traditional methods, it provides scientific basis for actual construction work in the aspects of collection, analysis, estimation, and integration of urban cultural environment and spatial information of cultural space construction. The final experimental data show that the method in this paper can achieve up to 96.2% integration of the cultural space in the experimental development area, which verifies the effectiveness and feasibility of this method. If it is popularized in the current stage of smart city cultural space construction, it can effectively improve the degree of spatial coordination and spatial effect.
Deep Learning Scoring Model in the Evaluation of Oral English Teaching
Authors: Liu Yamei , Li RongQin
Published: July 2022

This study is aimed at improving the accuracy of oral English recognition and proposing evaluation measures with better performance. This work is based on related theories such as deep learning, speech recognition, and oral English practice. As the literature summarized, the recurrent neural network was the calculation standard, and the oral English speech recognition indicators were the main basis on which an English speech recognition model was constructed. Then, 20 English majors and 5 sets of English sentence patterns were randomly selected as the research objects. The correction standards for English oral errors were introduced into the model to achieve further improvement. The research results showed that the average concordance rate of speech recognition reached 91% through the model test. The concordance rates of words, speech, and intonation in recognition were 89%, 91%, and 86%, respectively. The model could be used as an evaluation system for English speech recognition. Therefore, the application of the deep learning scoring model in the evaluation of oral English teaching was researched in this work, which provided an effective basis for the evaluation of intelligent English teaching.
Reservoir Structure and Remaining Oil Distribution of Meandering River Channels: A Case Study of the Y92-1 Layer in the Jingbian Oilfield, Ordos Basin
Authors: Guo Chun-ling , Fu Guo-min , Liu Jian-Chao , Wang Yang , Wu Yu-feng , Liu Cheng-wen , Wang Long-jun , Qiao Li
Published: August 2022

The majority of the Jurassic Yan’an Formation reservoirs in the Jingbian Oilfield of the Ordos Basin have entered the middle and late stages of development, and fine characterization of reservoir heterogeneity and recognition of the remaining oil distribution are the keys to formulating comprehensive adjustment for production. The Y92-1 layer of the Yan’an Formation Y9 reservoir in the LZ area of Jingbian Oilfield is taken as the research object in this paper. Based on logging data, core, and other basic data, the reservoir morphology in the study area is finely characterized. Single-channel units are subdivided, and the reservoir configurations of different hierarchical levels are analyzed qualitatively and quantitatively. Finally, combined with the plane profile consistency analysis of the morphological characteristics of the sand body in layer Y92-1 and the injection production mode, it is concluded that there may be four distribution patterns of the remaining oil in the study area, and the composite river channel sand body dominated by the lateral superimposed mode under the inverse lateral accretion shale bed tendency injection condition is a favorable enrichment area for the remaining oil. This mode is mainly distributed in the boundary part of the different periods of single sand body superposition. These understandings not only deepen the significance of tapping the potential of the remaining oil in frequently rerouted meandering rivers but also could provide effective guidance for the further remaining oil tapping.
Effect of Different Ankle-Foot Immobility on Lateral Gait Stability in the Stance Phase
Authors: Fan Wen , Hatanaka Yasuhiko
Published: August 2022

Background. This study aimed to investigate the effect of limited foot and ankle mobility on the lateral stability of gait through the observation of the mediolateral margin of stability and related kinematic parameters. Methods. Thirty young, healthy participants walked at a fixed gait velocity on a level surface. Participants achieved different degrees of restricted mobility by wearing soft-soled shoes (S), an ankle-foot orthosis with unrestricted dorsiflexion-plantarflexion activity only (A), and an ankle-foot orthosis with unrestricted dorsiflexion-plantarflexion and adjustable horizontal rotation of the foot (OU/OR). Furthermore, the spatiotemporal parameters, mediolateral margin of stability, center of pressure, angle of the fore and hind foot relative to the tibia, and correlation coefficients of the factors were analyzed. Regression analysis was also performed. Results. At right heel strike, group A had a significantly lower mediolateral margin of stability than group S and group OU. Meanwhile, forefoot adduction (0.2 < |r| <0.4) and plantarflexion (0.2 < |r| <0.4), as well as hindfoot internal rotation (0.2 < |r| <0.6) and inversion (0.2 < |r| <0.4), correlated negatively with lateral stability. Regression analysis revealed forefoot dorsiflexion and supination were the main independent variables for group A. At right heel off, groups OU and OR had a significantly lower mediolateral margin of stability than those in groups A and S. Forefoot adduction (0.2 < |r| <0.4) and dorsiflexion (0.4 < |r| <0.6) were correlated with lateral stability, as were hindfoot dorsiflexion (0.2 < |r| <0.4) and inversion (0.2 < |r| <0.4). Regression analysis revealed forefoot abduction and plantarflexion were the main independent variables for groups OU and OR. Conclusions. The present study verified from gait data that forefoot dorsiflexion and supination at the initial contact of the stance phase were relevant factors for the differences in lateral gait stability, whereas abduction and plantar flexion of the forefoot at the terminal stance phase were the main influencing factors of lateral gait stability.
An Approach for Cardiac Coronary Detection of Heart Signal Based on Harris Hawks Optimization and Multichannel Deep Convolutional Learning
Authors: Alsafi Haedar , Munilla Jorge , Rahebi Javad
Published: July 2022

Automatic diagnosis of arrhythmia by electrocardiogram has a significant role to play in preventing and detecting cardiovascular disease at an early stage. In this study, a deep neural network model based on Harris hawks optimization is presented to arrive at a temporal and spatial fusion of information from ECG signals. Compared with the initial model of the multichannel deep neural network mechanism, the proposed model of this research has a flexible input length; the number of parameters is halved and it has a more than 50% reduction in computations in real-time processing. The results of the simulation demonstrate that the approach proposed in this research had a rate of 96.04%, 93.94%, and 95.00% for sensitivity, specificity, and accuracy. Furthermore, the proposed approach has a practical advantage over other similar previous methods.
A Residual Fusion Network for Osteosarcoma MRI Image Segmentation in Developing Countries
Authors: Wu Jia , Zhou Luting , Gou Fangfang , Tan Yanlin
Published: August 2022

Among primary bone cancers, osteosarcoma is the most common, peaking between the ages of a child’s rapid bone growth and adolescence. The diagnosis of osteosarcoma requires observing the radiological appearance of the infected bones. A common approach is MRI, but the manual diagnosis of MRI images is prone to observer bias and inaccuracy and is rather time consuming. The MRI images of osteosarcoma contain semantic messages in several different resolutions, which are often ignored by current segmentation techniques, leading to low generalizability and accuracy. In the meantime, the boundaries between osteosarcoma and bones or other tissues are sometimes too ambiguous to separate, making it a challenging job for inexperienced doctors to draw a line between them. In this paper, we propose using a multiscale residual fusion network to handle the MRI images. We placed a novel subnetwork after the encoders to exchange information between the feature maps of different resolutions, to fuse the information they contain. The outputs are then directed to both the decoders and a shape flow block, used for improving the spatial accuracy of the segmentation map. We tested over 80,000 osteosarcoma MRI images from the PET-CT center of a well-known hospital in China. Our approach can significantly improve the effectiveness of the semantic segmentation of osteosarcoma images. Our method has higher F1, DSC, and IOU compared with other models while maintaining the number of parameters and FLOPS.
Charging Station Distribution Optimization Using Drone Fleet in a Disaster
Authors: Hassan Zohaib , Ali Shah Syed Irtiza , Sarwar Rana Ahsan
Published: July 2022

A disaster is an unforeseen calamity that can cause damage to properties and can bring about a loss of human lives. Usually, many relief supplies, such as clean water, food, and medical supplies, are required by disaster victims. Quick response and rapid distribution of essential relief items into the affected region can save countless lives and prevent or slow down the effects of disasters. In this regard, disaster management comes into play, which is highly dependent on the topography and access of the disaster-hit area. If the disaster-hit site has little or no road connectivity, the use of UAVs/drones becomes essential in delivering health packages to the affected areas to assist with humanitarian aid. Since the battery capacity of the drone is limited, UAVs/drones require charging stations located at various places to carry out the necessary relief work. These charging stations should be transported using road infrastructure and preinstalled in disaster-prone areas, as access to these areas may be denied once the disaster hits. This article presents a novel optimization model to distribute relief items to disaster-hit areas. The objective of this model is to optimize the location and the number of the charging stations. We consider the relative priority of locations where a preference is given to locations with higher priority levels. The optimal number of charging stations and optimal routes has also been determined by using our optimization model. To illustrate the use of our model, numerical examples have been simulated for a different number of targets. Through our numerical simulation, it was observed that the drone’s maximum distance capacity is the key factor in determining the optimal grid size, which directly correlates to the number of charging stations.
Application of Data Encryption Technology in Computer Network Information Security
Authors: Li Lifeng
Published: August 2022

In order to solve the partial optimization problems of the RSA algorithm in computer network security, a method of RSA algorithm optimization based on data encryption was proposed. In the research, the application of data encryption in network information security system was mainly investigated, using RSA as the representative algorithm in the public key cryptosystem. The network information security model on the basis of data encryption was built on the public key cryptosystem in the research. Through the introduction of the RSA algorithm and the corresponding optimization scheme, the experiments for comparison were set up. Through the experiments, the feasibility of the optimization scheme was verified. Experimental results show that the efficiency of the RSA algorithm was about 1.0% to 2% higher than that of the traditional algorithm after a reasonable selection of parameters and the use of an optimized algorithm (also known as the combination algorithm), which improved the efficiency of RSA algorithm to a certain extent and achieved the purpose of improving RSA algorithm. It was proved that the method could effectively improve the budget efficiency of the RSA algorithm and solve the optimization problem of the RSA algorithm in computer network security.
Circular RNA MELK Promotes Chondrocyte Apoptosis and Inhibits Autophagy in Osteoarthritis by Regulating MYD88/NF‐κB Signaling Axis through MicroRNA‐497‐5p
Authors: Zhang Yingchi , Lu Rui , Huang Xiaojian , Yin Enzhi , Yang Yong , Yi Chengla , You Hongbo , Song Xianzhou , Yuan Xuefeng
Published: July 2022

Osteoarthritis (OA) is a rheumatic disease and its pathogenesis involves the dysregulation of noncoding RNAs. Therefore, the regulatory mechanism of circular RNA MELK (circMELK) was specified in this work. OA human cartilage tissue was collected, and circMELK, miR‐497‐5p, and myeloid differentiation factor 88 (MYD88) expression were examined. Human chondrocytes were stimulated with interleukin‐ (IL‐) 1β and interfered with vectors altering circMELK, miR‐497‐5p, and MyD88 expression to observe their effects on cell viability, cell cycle and apoptosis, autophagy, and inflammation. The binding relationship between RNAs was verified. The data presented that OA cartilage tissues presented raised circMELK and MYD88 and inhibited miR‐497‐5p expression. IL‐1β suppressed cell viability, prevented cell cycle, and induced apoptosis, autophagy, and inflammation of chondrocytes. Functionally, IL‐1β‐induced changes of chondrocytes could be attenuated by suppressing circMELK or overexpressing miR‐497‐5p. circMELK acted as a sponge of miR‐497‐5p while miR‐497‐5p was a regulator of MYD88. MYD88 restricted the effect of overexpressing miR‐497‐5p on IL‐1β‐stimulated chondrocytes. MYD88 triggered nuclear factor‐kappaB (NF‐κB) pathway activation. Shortly, CircMELK promotes chondrocyte apoptosis and inhibits autophagy in OA by regulating MYD88/NF‐κB signaling axis through miR‐497‐5p. Our study proposes a new molecular mechanism for the development of OA.