bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Magnetic Field on Electrodeposition and Properties of Cobalt Superalloys
Authors: Yapontseva Yuliya , Kublanovsky Valeriy , Maltseva Tetyana , Gorobets Oksana , Gerasimenko Rostislav , Troshchenkov Yuri , Vyshnevskyi Oleksii
Published: June 2022

The paper presents an effect of applying and directing a constant magnetic field on electrodeposition and magnetic properties of refractory metal alloys (W, Mo, Re) with cobalt deposited from citrate-pyrophosphate electrolytes. A mathematical model is presented that describes the creation of convective flows due to the micro-MHD effect in near-surface layers during electrodeposition of a ferromagnetic alloy in a magnetic field. It has been found that the greatest influence of the magnetic field applying on the electrodeposition of alloys under investigation is observed for rhenium ones, that is, there is a decrease in the rhenium content from 40 to 8 at.% (compared with deposition without magnetic field) and a halving of crystallite sizes. The magnetic properties of the resulting coatings depend on the nature of the refractory metal and can vary over a wide range.
Activated Carbon Tailored by Potassium Hydroxide from Waste Tires as a Supercapacitor Electrode
Authors: Zhang Dazhi , Ma Zhaojie , Zhang Yixin , Xu Yunhui , Liu Honglai , Wu Jianjun , Li Peipei
Published: June 2022

Hard-carbon materials are considered as the most promising anodes in various energy storage system applications including lithium, sodium, potassium ion batteries and supercapacitors. Given the huge bulk of the waste tires produced by the rapid development of automobile industry, recycling waste tires to generate value-added products is crucially important for the development of a more sustainable world. In this work, we demonstrate how waste tire-derived pyrolytic char can be transformed into activated carbon for supercapacitor electrodes. The process consists of the acidification of the waste tire-derived pyrolytic char with mixed acids (HCl and HF) and the followed activation with KOH. The activated carbon exhibited a hierarchical meso-/micro-porous network with specific surface area 524 m2 g−1. A traditional three-electrode system was used to investigate the electrochemical performances of the activated carbon as a supercapacitor electrode material, which displayed a specific capacitance of ∼408 F g−1 at 0.25 A g−1 in an electrolyte of 6 M KOH, with capacitance retention of up to 97% after 10,000 charge/discharge cycles. This work offers an innovative and simple approach to yield higher performance activated carbon from waste tires for use in energy storage devices.
Absolute quantification of plasma mitochondrial DNA by droplet digital PCR marks COVID-19 severity over time during intensive care unit admissions
Authors: Hepokoski Mark L. , Odish Mazen , Lam Michael T. , Coufal Nicole G. , Rolfsen Mark L. , Shadel Gerald S. , Moyzis Alexandra G. , Sainz Alva G. , Takiar Puja G. , Patel Sagar , Leonard Austin J. , Samandari Negin , Hansen Emily , Trescott Samantha , Nguyen Celina , Jepsen Kristen , Cutter Gary , Gillespie Mark N. , Spragg Roger G. , Sasik Roman , Ix Joachim H.
Published: June 2022

Increased plasma mitochondrial DNA concentrations are associated with poor outcomes in multiple critical illnesses, including COVID-19. However, current methods of cell-free mitochondrial DNA quantification in plasma are time-consuming and lack reproducibility. Here, we used next-generation sequencing to characterize the size and genome location of circulating mitochondrial DNA in critically ill subjects with COVID-19 to develop a facile and optimal method of quantification by droplet digital PCR. Sequencing revealed a large percentage of small mitochondrial DNA fragments in plasma with wide variability in coverage by genome location. We identified probes for the mitochondrial DNA genes, cytochrome B and NADH dehydrogenase 1, in regions of relatively high coverage that target small sequences potentially missed by other methods. Serial assessments of absolute mitochondrial DNA concentrations were then determined in plasma from 20 critically ill subjects with COVID-19 without a DNA isolation step. Mitochondrial DNA concentrations on the day of enrollment were increased significantly in patients with moderate or severe acute respiratory distress syndrome (ARDS) compared with those with no or mild ARDS. Comparisons of mitochondrial DNA concentrations over time between patients with no/mild ARDS who survived, patients with moderate/severe ARDS who survived, and nonsurvivors showed the highest concentrations in patients with more severe disease. Absolute mitochondrial DNA quantification by droplet digital PCR is time-efficient and reproducible; thus, we provide a valuable tool and rationale for future studies evaluating mitochondrial DNA as a real-time biomarker to guide clinical decision-making in critically ill subjects with COVID-19.
Changes in intestinal homeostasis and immunity in a cigarette smoke- and LPS-induced murine model for COPD: the lung-gut axis
Authors: Wang Lei , Pelgrim Charlotte E. , Peralta Marzal Lucía N. , Korver Stephanie , van Ark Ingrid , Leusink-Muis Thea , van Helvoort Ardy , Keshavarzian Ali , Kraneveld Aletta D. , Garssen Johan , Henricks Paul A. J. , Folkerts Gert , Braber Saskia
Published: June 2022

Chronic obstructive pulmonary disease (COPD) is often associated with intestinal comorbidities. In this study, changes in intestinal homeostasis and immunity in a cigarette smoke (CS)- and lipopolysaccharide (LPS)-induced COPD model were investigated. Mice were exposed to cigarette smoke or air for 72 days, except days 42, 52, and 62 on which the mice were treated with saline or LPS via intratracheal instillation. Cigarette smoke exposure increased the airway inflammatory cell numbers, mucus production, and different inflammatory mediators, including C-reactive protein (CRP) and keratinocyte-derived chemokine (KC), in bronchoalveolar lavage (BAL) fluid and serum. LPS did not further impact airway inflammatory cell numbers or mucus production but decreased inflammatory mediator levels in BAL fluid. T helper (Th) 1 cells were enhanced in the spleen after cigarette smoke exposure; however, in combination with LPS, cigarette exposure caused an increase in Th1 and Th2 cells. Histomorphological changes were observed in the proximal small intestine after cigarette smoke exposure, and addition of LPS had no effect. Cigarette smoke activated the intestinal immune network for IgA production in the distal small intestine that was associated with increased fecal sIgA levels and enlargement of Peyer’s patches. Cigarette smoke plus LPS decreased fecal sIgA levels and the size of Peyer’s patches. In conclusion, cigarette smoke with or without LPS affects intestinal health as observed by changes in intestinal histomorphology and immune network for IgA production. Elevated systemic mediators might play a role in the lung-gut cross talk. These findings contribute to a better understanding of intestinal disorders related to COPD.
Application Value of Combined Detection of DCE‐MRI and Serum Tumor Markers HE4, Ki67, and HK10 in the Diagnosis of Ovarian Cancer
Authors: Wang Quanzhi , Dong Hui , Zhou Peng
Published: June 2022

Objective. To investigate the application value of the combined detection of DCE‐MRI and serum tumor markers (HE4, Ki67, and HK10) in the diagnosis of ovarian cancer. Methods. The clinical data of 40 patients with advanced ovarian cancer (AOC) confirmed by surgery and pathology in our hospital from February 2019 to February 2020 were retrospectively analyzed. All patients received DCE‐MRI, the detection of serum tumor markers HE4, Ki67, and HK10, and the combined detection of DCE‐MRI and the serum tumor markers (HE4, Ki67, and HK10). The application value of the three detection methods was analyzed. Results. The number of true positives in the single detection (DCE‐MRI detection and the detection of serum HE4, Ki67, and HK10) was notably lower than that in the combined detection. The sensitivity, specificity, and accuracy of the single detection were notably lower compared with the combined detection. The area under the curve in the ROC of the combined detection was notably larger than that of the single detection. The results of the combined detection were better than those of the single detection (P < 0.05), with the highest sensitivity of the combined detection. Conclusion. The combined detection of DCE‐MRI and the serum tumor markers (HE4, Ki67, and HK10) can effectively improve the diagnostic accuracy of AOC patients, with high sensitivity and specificity, which has an important diagnostic value in clinic.
Efficacy and Safety of Salvia miltiorrhiza for Treating Chronic Kidney Diseases: A Systematic Review and Meta-Analysis
Authors: Zhang Wei , Li Jun , Yang Pan , Wang Gaoqiang , Yue Yanli , Zhong Yuanfang , Liu Hanyin , Gui Dingkun , Xu Youhua , Wang Niansong
Published: June 2022

Objective. This meta-analysis evaluated the effects and potential harms of Salvia miltiorrhiza or its extracts Salvianolate and Tanshinone for the treatment of population with a chronic kidney disease (CKD). Methods. We searched for the randomized clinical trials (RCTs) through databases including the Cochrane Library, PubMed, Embase, Web of Science, Current Controlled Trials, China National Knowledge Infrastructure (CNKI), Wanfang Data Knowledge Service Platform (Wanfang Data), China Biology Medicine Disc (SinoMed), and Chinese Clinical Trial Registry (ChiCTR). Meta-analysis was performed with STATA 16 software after data extraction. The risk of bias was assessed with the Cochrane risk-of-bias tool (RoB 2.0), and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework was employed to evaluate the quality of evidence. Result. A total of 32 studies were included involving 2264 participants. Compared to the control group, the treatment group significantly decreased serum creatinine (SCr) (SMD −0.60, 95% CI −0.79 to −0.41,

P
<
0.0001

), blood urea nitrogen (BUN) (SMD −0.66, 95% CI −0.81 to −0.50,

P
<
0.0001

), Cystatin C (CysC) (SMD −5.16, 95% CI −14.84 to 4.53,

P
=
0.297

), 24 hour urine protein (24 h UPE) (SMD −0.70, 95% CI −1.21 to −0.19,

P
=
0.008

), time to initiation of dialysis (Log RR 0.43, 95% CI 0.23 to 0.81,

P
=
0.0089

), serum total cholesterol (TC) (SMD −0.53, 95% CI −0.88 to −0.17,

P
=
0.0042

,

P
=
0.0035

), plasma fibrinogen (FIB) (SMD −0.79, 95% CI −1.12 to −0.46,

P
<
0.0001

), C-reactive protein (CRP) (SMD −0.56, 95% CI −0.93 to −0.19,

P
=
0.0029

); increased creatinine clearance (Ccr) (SMD 0.92, 95% CI 0.43 to 1.41,

P
=
0.0002

), glomerular filtration rate (GFR) (SMD 0.56, 95% CI 0.30 to 0.83,

P
<
0.001

), effective rate (Log RR 0.30, 95% CI 0.23 to 0.37,

P
<
0.0001

), and hemoglobin (Hb) (SMD 0.42, 95% CI 0.13 to 0.71,

P
=
0.0042

). Moreover, the incidences of adverse effects were similar between the two groups. Conclusions. Salvia miltiorrhiza or its extracts Salvianolate and Tanshinone, as a complementary therapy to conventional medicine, presents potential impacts to improve kidney functions and delay the progression of CKD without obvious adverse effects. However, the certainty of the evidence and the risk of bias are suboptimal and further clinical studies are still required to determine the underlying effects.
Prevalence of Epstein–Barr Virus Infection and Mismatch Repair Protein Deficiency and the Correlation of Immune Markers in Tibetan Patients with Gastric Cancer
Authors: Shi Jie , Yang Xu , Wang Xinmei , Luo Yufeng , Zhou Weixun , Luo Hanhuan , Bianba Zhaxi , Nima Zhuoma , Wang Qian , Wang Han , Liao Ruiqian , Ciren Quzhen , Li Mei , Pang Junyi
Published: June 2022

Background. Gastric cancer (GC) is a major cause of cancer‐related death in China. Immunotherapies based on PD‐1/PD‐L1 inhibitors have improved the survival of some patients with GC. Epstein–Barr virus (EBV) infection, mismatch repair (MMR) deficiency, and tumor immune microenvironment (TIME) markers (such as CD3, CD8, and PD‐L1) may help to identify specific patients who will respond to PD‐1/PD‐L1 inhibitors. Considering racial heterogeneity, the pattern of TIME markers in Tibetan patients with GC is still unclear. We aimed to identify the prevalence of EBV infection and the MMR status and their association with immune markers in Tibetan GC to aid in patient selection for immunotherapy. Materials and Methods. From 2001 to 2015, we retrospectively collected 120 tissue samples from consecutive Tibetan GC patients and constructed tissue microarrays. EBV infection was assessed by Epstein–Barr‐encoded RNA (EBER) in situ hybridization, and MMR protein levels were measured. Immune markers (including CD3 and CD8) in intraepithelial, stromal, and total areas were detected by immunohistochemistry (IHC). PD‐L1 expression was assessed by the combined positive score (CPS). We also analyzed the relationships of EBV infection and MMR status with immune markers. Results. Of the 120 samples, 11 (9.17%) were EBV positive (+), and 6 (5%) were MMR deficient (dMMR). PD‐L1 CPS ≥1% was found in 32.5% (39/120) of Tibetan GC patients. EBV infection was associated with higher numbers of CD3+ T cells (P < 0.05) and CD8+ T cells (P < 0.05) and higher PD‐L1 expression (P < 0.05). For the limited number of dMMR patients, no significant relationship was observed between dMMR and TIME markers (P > 0.05). Conclusions. In Tibetan GC patients, the rates of EBV infection, dMMR, and positive PD‐L1 expression were 9.17%, 5%, and 32.5%, respectively. EBV infection was associated with the numbers of CD3+ T cells and CD8+ T cells and PD‐L1 expression within the tumor. These markers may guide the selection of Tibetan GC patients for immunotherapy.
Complexity Reduction for the Architecture Design of Large-Scale Public Buildings Based on Seismic Structure Simulation Technology
Authors: Hu Xiji , Li Xingquan , Zuo Mingwei , Michalak Wazid
Published: June 2022

In order to improve the seismic effect of large-scale public building architecture design, this paper studies the large-scale public building architecture design with the support of seismic structure simulation technology and improves the large-scale public building architecture design effect through simulation research. Furthermore, on the basis of the construction of the seismic performance evaluation system and the determination of the index weight, this paper assigns the index data to the sample table of the seismic performance checklist and establishes the seismic performance evaluation model based on the gray fixed-weight clustering method. Furthermore, using the seismic structure modeling technique described in this study, this paper assesses the seismic performance of public buildings. Finally, through experimental research, this paper verifies that the design method of large-scale public building architecture based on seismic structure simulation technology has certain practical effects.
Analysis of Animation Peripheral Design Ability Based on Artificial Intelligence
Authors: Lulu Jiang , Xiuhua Li , Wei Feng
Published: June 2022

With the development of communication technology and hardware technology, only continuous innovation in animation production can meet the development needs of the times. Animation has recently received substantial interest in special education. New forms of representation, including animation, multimedia, and virtual reality, are some of the key developments that education technology has made possible. Animation software is an influential mass media, communication, and education platform. Progressive improvements in technical methods along with the expansion of knowledge and skills have resulted in an increase in variety as well as the speed of production of new products for animation. In this study, we propose an Advanced Animation Teaching Model (AATM) based on Design-Oriented Learning Approach (DOLA). Design-based learning is the incorporation of design projects in classrooms so that students can acquire creative solutions and learn curriculum content by participating in actual, cross-curricular challenges. This model keeps pace with the times to meet the needs of the modern market. It combines introduction to animation, color composition, color psychology, composition basis, spatial perspective, animation scene design, and visual art design-related theories to form the theoretical basis for the major. The results showed the trends of animation used in education and the strengths of animation to improve the learning of students and enhance the thinking ability of the students.
Artificial Intelligence-Based Semisupervised Self-Training Algorithm in Pathological Tissue Image Segmentation
Authors: Li Qun , Liu Linlin
Published: June 2022

In the field of medical image processing, due to the differences in tissues, organs, and imaging methods, obtained medical images have significant differences. With the development of intelligence in medicine, an increasing number of computing optimization algorithms based on AI technology have also been applied to the field of medicine. Because the image segmentation algorithm based on the semisupervised self-training algorithm solves initialization class center large randomness problem in the traditional cluster-based image segmentation algorithm, this article aims to integrate the artificial intelligence semisupervised self-training algorithm into the pathological tissue image segmentation problem. An experimental group is designed to collect sample images and the algorithm proposed in this article is used to perform image segmentation to achieve a better visual experience and images. Although there is no general image segmentation theory, many scholars have been committed to applying new concepts and new methods to image segmentation in recent years and combining specific theoretical image segmentation methods has achieved good application results in image segmentation. For example, wavelet analysis, wavelet transform, neural networks, and genetic algorithms can effectively improve the segmentation effect. The results of the Seg cutting method designed in this article show that, in retinal blood vessel segmentation results on a database of healthy people, the sensitivity value is 0.941633, the false-positive rate is 0.952933, the specificity is 0.956787, and the accuracy rate is 0.96182, which are all higher than those in other methods. Image cutting methods such as FNN, CNN, and AWN have addressed the case tissue image cutting problem. Using the Seg cutting method designed in this article to segment the retinal blood vessels on a diabetes patient database, the sensitivity value is 0.8106, the false-positive rate is 0.0511, the specificity is 0.9712, the accuracy is 0.9421, and the false-positive rate is omitted. The false-positive rate is lower than AWN, and other indicators are higher than FNN, CNN, AWN, and other image cutting methods. The application of artificial intelligence-based semisupervised self-training algorithms in pathological tissue image segmentation is realized.
Machine Vision-Based Ping Pong Ball Rotation Trajectory Tracking Algorithm
Authors: Wang Yilei , Wang Ling
Published: June 2022

Because of the overwhelming characteristics of computer vision technology, the trend of intelligent upgrading in sports industry is obvious. Video technical and tactical data extraction, big data analysis, and match assistance systems have caused profound changes to all aspects of the sports industry. One of the important applications is the playback and analysis of sports videos. People can observe the videos and summarize the experience of sports matches, and in this process, people prefer the computers to also interpret and analyze sports matches, which can not only help coaches in postmatch analysis but also design robots to assist in teaching and training. In this paper, we have examined and designed an automatic detection system for ping pong balls, in which the motion trajectory and rotation information of ping pong balls are mainly detected. To achieve this goal, the detection and tracking algorithm of ping pong balls based on deep neural network is used, and better results are achieved on the data set established by ourselves and the actual system test. After obtaining the position of the ping pong ball in the image, the rotation direction and speed of the ping pong ball are calculated next, and the Fourier transform-based speed measurement method and the CNN-based rotation direction detection method are implemented, which achieve better results in the testing of lower speed datasets. Finally, this paper proposes an LSTM-based trajectory prediction algorithm to lay the foundation for the design of table tennis robot by predicting the trajectory of table tennis. Experimental tests show that the proposed system can better handle the ping pong ball tracking and rotation measurement problems.
Bombyx batryticatus Cocoonase Inhibitor Separation, Purification, and Inhibitory Effect on the Proliferation of SMCC-7721 HeLa-Derived Cells
Authors: Wang Houwei , Xu Lingchuan , Dou Yanling , Wang Jiachao
Published: June 2022

The present study was to isolate and purify Bombyx batryticatus cocoonase inhibitor (BBCI) and to evaluate its inhibitory effect on the proliferation of SMCC-7721 cells. BBCI was purified from the crude proteins of Bombyx batryticatus using affinity chromatography with cocoonase as the ligand, its N-terminal amino acid sequence was determined using the Edman degradation method, and its inhibiting activity on SMCC-7721 cell proliferation was detected in vitro using the MTT method and in vivo in tumor-bearing nude mice. The purified BBCI presented as a single band in SDS-PAGE, the molecular weight determined by time-of-flight mass spectrometry was 13,973.63 Da, and its N-terminal amino acid sequence was VRNKRQSNDD. BBCI was a noncompetitive cocoonase inhibitor with an average Michaelis constant of 76.50, and it inhibited cocoonase activity with an inhibition ratio of 1 : 1 (molar). BBCI could inhibit the proliferation of SMCC-7721 cells in vitro with the IC50 being about 260.52 μg/ml within 36 h of treatment and inhibit the SMCC-7721 tumor growth in nude mice by subcutaneous injection of BBCI around the tumor, where the tumor inhibitory effect was dose dependent. BBCI did not significantly influence the spleen coefficient of the mice. In conclusion, to the best of our knowledge, the present study is the first to report that BBCI, which was purified from Bombyx batryticatus, was a serine proteinase inhibitor with antitumor activity.
Investigation of Curing Mechanism and Mechanical Properties of Polypropylene/Aliphatic Epoxy Composites
Authors: Kumar Raj , Gous Mahmad Ziya , Surakasi Raviteja , Raghuram K. S. , Sunagar Prashant , Kumar Neelam Sanjeev , Pandey Anand K. , Padmavathy S. , Sudhakar M. , Kumar S. Praveen
Published: June 2022

Temperature-sensitive cure kinetics based on bisphenol A oligomeric diglycidyl ether and branching diphenylmethane di-isocyanate, polymer aliphatic or lower molecular weight aromatic amines, and polypropylene and epoxy composites were examined. Polypropylene networks are formed initially, followed by amine hardeners interfering with epoxy oxirane rings to frame linear oligomers. Finally, the system is formed by a reaction between amines obtained in the second phase and epoxy oxirane rings during the curing step. This three-stage treatment was illustrated. The activation energy was calculated using the Flynn-Wall-Ozawa and Kissinger-Akahira-Sunose isoconversational approaches to cure degree. The Ea-to-αcorrelation was determined using these approaches, revealing that the research curing systems exhibited autocatalytic effects. Among the materials studied, compounds with low molecular weight aromatic amines had the strongest and longest-lasting tensile characteristics. There are numerous advantages to slow curing and discrete stages of composite creation, including better mechanical properties.
Perceptual-Cognitive Tasks Affect Landing Performance of Soccer Players at Different Levels of Fatigue
Authors: Ren Yuanyuan , Wang Guodong , Zhang Lei , Lu Aming , Wang Cenyi
Published: June 2022

Background. There is a possible interaction between the underlying mechanisms of perceptual-cognitive tasks and motor control. For example, landing biomechanics changed during perceptual-cognitive tasks undertaken at different levels of fatigue of the athlete. Thus, this study explored the effect of perception-cognitive tasks interventions on male soccer players’ landing mechanisms at different levels of fatigue. Methods. Perceptual-cognitive tasks during games were simulated using classic multiple object tracking (MOT) paradigms, and 15 male soccer players completed MOT tasks under nonfatigue (NF), moderate fatigue (MF), and severe fatigue (SF). Landing-associated indicators were collected and calculated using a Vicon and force measuring platform. Results. Level of fatigue and MOT task significantly affected hip and knee flexion angles, hip and knee extension moments, and vertical ground reaction force. Specifically, hip and knee flexion angles were significantly higher in MOT than non-MOT tasks at all levels of fatigue. In NF state, hip and knee extension moments were significantly smaller during MOT than non-MOT tasks. In SF state, the hip extension moment was larger during MOT than non-MOT tasks. In both MF and SF states, vertical ground reaction force was significantly higher in MOT than non-MOT tasks. Conclusion. Although soccer players landed cautiously when not fatigued, they were significantly less able to do this and handle challenging perceptual-cognitive task movements when fatigued. Thus, landing performance is affected by perceptual-cognitive task interference in fatigue conditions.
The Applications of Blockchain in the Covert Communication
Authors: Du Bangyao , He Debiao , Luo Min , Peng Cong , Feng Qi
Published: June 2022

Covert communication is designed for hiding the subliminal communication which takes place between both of the speakers and their relationship. The traditional covert communication utilizes the centralized channel and the third-party central node or authority to distribute messages which leads to a lack of undetectability, antitraceability, and robustness. In recent years, there have been attempts to apply the blockchain to covert communication solutions, for the characteristics of blockchain such as decentralization, openness, and trustworthiness. In this paper, based on the analysis of the literature and the classification according to the hiding position, we identify four kinds of covert communication: Address Channel, Value Channel, DSA (Digital Signature Algorithm) Channel, and Script Channel, which will help inform future research agenda.
Multiple Attribute Group Decision-Making Based on Intuitionistic Fuzzy Schweizer-Sklar Generalized Power Aggregation Operators
Authors: Khan Qaisar , Khattak Hizbullah , AlZubi Ahmad Ali , Alanazi Jazem Mutared
Published: June 2022

An intuitionistic fuzzy set (IFS) is a valuable tool to execute uncertain and indeterminate information. IFSs are more suitable to identify decision-maker’s evaluation data in decision-making problems. Intuitionistic fuzzy aggregation operators (AOs) are of enormous consequences in multiple attribute group decision-making (MAGDM) problems with an intuitionistic fuzzy environment. Consequently, the main impacts of this article are: firstly, to instigate various new novel generalized power AOs based on Schweizer-Sklar operational rules for IFS. Secondly, the study aims to discuss characteristics and particular cases of AOs. The core edge of proposed AOs is that they can eradicate the influence of uncomfortable data which could be too high or too low, making them more admirable for efficiently solving more and more complex MAGDM problems. Thirdly, we instigate two new algorithms to deal with MAGDM established on the generalized Schweizer-Sklar power AOs. Lastly, we appertain the anticipated method and algorithms to health care waste treatment technology selection (HCW-TT) to show the competence of the anticipated method and algorithms. The prevailing novelties of these items are duplex. Firstly, new generalized AOs established on Schweizer-Sklar operational rules are initiated for IFNs. Secondly, two new approaches for IF MAGDM are initiated, one for known decision-makers (DMs) and attributes weights, while the other for unknown DMs and attributes weights.
Comparison of Conventional Modeling Techniques with the Neural Network Autoregressive Model (NNAR): Application to COVID-19 Data
Authors: Daniyal Muhammad , Tawiah Kassim , Muhammadullah Sara , Opoku-Ameyaw Kwaku
Published: June 2022

The coronavirus disease 2019 (COVID-19) pandemic continues to destroy human life around the world. Almost every country throughout the globe suffered from this pandemic, forcing various governments to apply different restrictions to reduce its impact. In this study, we compare different time-series models with the neural network autoregressive model (NNAR). The study used COVID-19 data in Pakistan from February 26, 2020, to February 18, 2022, as a training and testing data set for modeling. Different models were applied and estimated on the training data set, and these models were assessed on the testing data set. Based on the mean absolute scaled error (MAE) and root mean square error (RMSE) for the training and testing data sets, the NNAR model outperformed the autoregressive integrated moving average (ARIMA) model and other competing models indicating that the NNAR model is the most appropriate for forecasting. Forecasts from the NNAR model showed that the cumulative confirmed COVID-19 cases will be 1,597,180 and cumulative confirmed COVID-19 deaths will be 32,628 on April 18, 2022. We encourage the Pakistan Government to boost its immunization policy.
Evaluation and Analysis of Traditional Customary Law Based on the Perspective of Big Data
Authors: Yang Juanjuan , Chuan Tee Boon
Published: June 2022

Today’s rule of law construction in China is walking between the conflict and coordination of factors such as reality and ideals, tradition and modernity, local and foreign, and local knowledge and universal principles, all while continuing to strengthen the unification of the legal system and advance the modernization of the rule of law. Traditional customary law, which is the most representative local resource culture, is unquestionably one of the most important themes in the formation of the rule of law. It has far-reaching significance for the development of ethnic jurisprudence, the reunderstanding of traditional culture, and the construction of ethnic unity and harmonious society. Based on this background, this paper uses big data technology to collect relevant experimental data and proposes a traditional customary law value assessment based on BPNN. The completed work is as follows: (1) this paper clarifies the concept of customary law and the difference between it and related concepts and introduces the domestic relevant research on traditional customary law and the interactive relationship between customary law and national law in dynamic legal practice and puts forward the status and influence of customary law in contemporary legal practice. (2) The related technologies of neural network are introduced, and a traditional customary value evaluation system that can be used for experiments is constructed. (3) Experiment with the designed data set to see if the BP model is feasible. The experimental results suggest that the model proposed in this study has a low error rate and performs well while evaluating traditional common law values.
Antitumor Effect of Pseudolaric Acid B Involving Regulation of Notch1/Akt Signaling Response in Human Hepatoma Cell In Vitro
Authors: Gao Haijun , Zhang Yan , Mo Xiaojin , Huo Lele , Luo Yanping , Zhang Ting , Ma Xingming , Hu Wei , Jing Tao
Published: June 2022

Background. Liver cancer, particularly hepatocellular carcinoma (HCC), is the fourth leading cause of cancer-related death worldwide. Sorafenib is a crucial drug for the treatment of advanced HCC, but it is difficult to meet the challenge of increasing clinical demands due to its severe side effects and drug resistance. Hence, development of novel antitumor drugs is urged. Previous studies showed that pseudolaric acid B (PAB) could reduce the expression of protein kinase B (PKB/Akt), a downstream effector of Notch signaling, facilitating cell apoptosis in HCC. The disruption of Notch signaling was verified to exacerbate malignant progression and drug resistance, however, the antitumor effect of PAB on Notch signaling in HCC remains unclear. Thus, this study aims to investigate the anti-HCC effect of PAB in association with the regulation of Notch1/Akt signaling. Methods. CCK-8 assay and transwell assay were used to examine the cell proliferation and invasion in Huh7 cells after treatment with PAB and a Notch inhibitor DAPT. Moreover, the cell cycle of Huh7 cells after treatment with PAB was analyzed using flow cytometry. Finally, the changes of Notch1, Jagged1, Hes1, and Akt expression at the protein and mRNA level in Notch1/Akt signaling in Huh7 cells after treatment with PAB and DAPT were analyzed using immunofluorescence assay and real-time qPCR. Results. The proliferation rate of Huh7 cells exposed to PAB of 0.5, 1, 2, 4, 8, 10, 20, 40, 80, 100, and 200 μmol/L revealed a time-and dose-dependent decrease in vitro, showing cell cycle arrest at G2/M phase

P
<
0.05

. Furthermore, compared with the untreated group, at the concentration of 40 μmol/L, the proliferation rate and invasion rate of Huh7 cells in PAB, DAPT, and PAB-DAPT combination (PAB + DAPT) group were significantly decreased

P
<
0.05

, but the PAB + DAPT showed no synergistic antiproliferation and anti-invasion effect in comparison with PAB treatment alone

P
>
0.05

. In addition, compared with the untreated group, PAB and DAPT alone significantly downregulated the expression of Notch1, Jagged1, Hes1, Akt mRNA, or/and protein in Huh7 cells

P

<

0.05

, but there was no significant difference in synergistic downregulated effect between the PAB + DAPT group and the PAB group

P
>
0.05

. Conclusion. PAB can suppress proliferation and invasion of HCC cells through downregulating the expression of Notch1/Akt signaling protein and mRNA, and may be a potential novel antitumor drug candidate for the clinical treatment of HCC in the future.
A New Bayesian Network Model for the Risk Assessment of Water Inrush in Karst Tunnels
Authors: Wang Yingchao , Liu Yang , Li Zhaoyang , Jiang Wen
Published: June 2022

Water inrush seriously restricts the safe construction of a karst tunnel. Once it occurs, it will cause serious consequences such as economic loss and casualties. Due to the complexity of an underground environment, it is difficult to calculate the probability of karst tunnel water inrush. Therefore, it is of great engineering significance to establish an effective risk assessment model. Based on the Bayesian theory, interpretation structure model, and generative adversarial network, a Bayesian network risk assessment model is established. The results show that firstly, twelve indexes selected can not only characterize the karst tunnel water inrush but also are easy to be counted, which effectively improves the accuracy of the Bayesian risk assessment model. Secondly, the Bayesian network risk assessment model overcomes the shortcomings of other risk assessment models that rely too much on geological data and improves the accuracy through massive data training. Thirdly, the corresponding noninrush samples are generated by the generative adversarial network and analytic hierarchy process, which effectively solve the problem of an unbalanced database. Finally, the Bayesian network risk assessment model is applied to the DK490+373 section of the Shangshan Tunnel. The assessment model is operable, effective, and practical, and it is also suitable for the situation of incomplete index statistics.
Application of Visual Communication Combined with Electrochemistry in Ceramic Carving Product Design
Authors: Geng Jian
Published: June 2022

In order to improve the design of ceramic carving products, the author proposes a visual communication, combined with electrochemistry, laser engraving technology, using superpixel imaging technology, carry out laser engraving ceramic reticulation imaging processing, build a binary laser engraving image model, using image edge feature matching method, carry out the edge contour feature detection of the laser engraved ceramic reticulated image, and extract the local information feature quantity of the laser engraved ceramic mesh image. The fuzzy adaptive segmentation method is used for the extracted features and to perform grid area segmentation. The experimental results show that the greater the laser output power, the deeper the engraving depth. As the laser output power increases, the depth of the hole formed by a single pulse laser is enlarged, the etched area formed by the dense hole group also deepens. However, the experiment found that after the laser power is increased to a certain value (17 A), the temperature of the light spot rises sharply, reach the melting point of ceramics, and produce slag that is not easy to remove on the engraved surface, decrease the effective engraving depth. It proves that visual communication, combined with electrochemistry, can effectively realize the design of ceramic carving products.
Financial Risk Early‐Warning of Neusoft Group Based on Support Vector Machine
Authors: Dai Yuxuan , Yu Chenhui
Published: June 2022

As an emerging development industry, the information technology industry faces the most internal and external problems without effective risk prevention measures, which requires an effective financial risk early‐warning system to be established to control risks. Nowadays, the advantages of support vector machine (SVM) have gradually appeared. The research on financial risk early‐warning using SVM mostly stays in dichotomy. However, the financial risk of an enterprise will not only exist in absolute risk and no risk. There are many other levels of risk categories. Therefore, this paper proposes a new financial warning idea, which extends the support vector machine dichotomous to multidivision. This article focuses on the data modeling based on the financial data of listed companies in China’s A‐share information technology industry and applied to the case company Neusoft Group. First, the principal component analysis method is applied to assign the weights of financial indicators, and then the efficacy coefficient method is applied to comprehensively evaluate risk classification. Finally, the classified data were input into SVM for training and testing, and the model was applied to the financial risk early warning of Neusoft Group. The research results show that the model can better predict the financial risk of Neusoft Group.
Green Logistics Partner Selection Based on Pythagorean Hesitant Fuzzy Set and Multiobjective Optimization
Authors: Guan Tangchun
Published: June 2022

With the deepening of the uncertainty and fuzziness of people’s understanding of things, it becomes more convenient to use fuzzy decision making in evaluating schemes. These schemes not only include quantitative data but also consider more and more uncertainty evaluation information. In fuzzy theory, the Pythagorean fuzzy set is extended, both of which are less than or equal to 1, which increases the scope of application. This paper mainly studies the selection of green logistics. Based on the original TOPSIS principle, this paper introduces a Pythagorean fuzzy symmetric cross entropy to describe the difference between two Pythagorean fuzzy numbers and proves its rationality. The model is applied to the selection of green logistics and compared with the results obtained by other different methods, which also shows the effectiveness and practicability of the model. It extends the use of fuzzy sets and can solve some problems that cannot be solved by intuitionistic fuzzy sets before.
Acupoint Massage plus Recombinant Bovine Basic Fibroblast Growth Factor Ophthalmic Gel and Limbal Stem Cell Transplantation on Visual Quality, Corneal Refraction, and Aesthetic Outcome in Patients with Pterygium
Authors: Zhang Xiaoqin , Wu Yu
Published: June 2022

Objective. To investigate the clinical study of acupoint massage combined with recombinant bovine basic fibroblast growth factor (rbFGF) ophthalmic gel combined with limbal stem cell transplantation on visual quality, corneal refraction, and aesthetic outcome in patients with pterygium. Methods. Sixty patients with pterygium treated in People’s Hospital of Lujiang County from March 2018 to May 2021 were randomized into the control group and the research group by the random number table method, with 30 cases in each group. The control group received rbFGF plus limbal stem cell transplantation. The research group was treated with acupoint massage additionally. Results. The total clinical effective rate in the study group was higher than that in the control group (

P
<
0.05

); after treatment, the modulation transfer function (MTF) cutoff and Strehl ratio (SR) levels in the study group were significantly higher than those in the control group, and the tear film-related objective scatter index (TF-OSI) was significantly lower than that in the control group (

P
<
0.05

); corneal horizontal curvature and corneal vertical curvature in the study group after treatment were significantly higher than those in the control group, and corneal astigmatism degree (CAD) levels were significantly lower than those in the control group (

P
<
0.05

); the levels of the break-up time (BUT) and Schirmer test (SIT) in the study group were significantly higher after treatment, compared with the control group (

P
<
0.05

); and the incidence of adverse manifestations in the study group was significantly lower than that in the control group (

P
<
0.05

). Conclusion. Acupoint massage combined with rbFGF ophthalmic gel combined with limbal stem cell transplantation is effective in clinical treatment of pterygium.
The Recommendation System of Innovation and Entrepreneurship Education Resources in Universities Based on Improved Collaborative Filtering Model
Authors: Geng Li
Published: June 2022

In the huge number of online university education resources, it is difficult for learners to quickly locate the resources they need, which leads to “information trek.” Traditional information recommendation methods tend to ignore the characteristics of learners, who are the main subjects of education. In order to improve the recommendation accuracy, a recommendation algorithm based on improved collaborative filtering model is proposed in this paper. Firstly, according to the student behavior data, consider the behavior order to create the behavior graph and behavior route. Then, the path of text type is vectorized by the Keras Tokenizer method. Finally, the similarity between multidimensional behavior path vectors is calculated, and path collaborative filtering recommendations are performed for each dimension separately. The MOOC data of a university in China are introduced to experimentally compare the algorithm of the article as well as the control group algorithm. The results show that the proposed algorithm takes better values in evaluation indexes, thus verifying that this algorithm can improve the effectiveness of innovation and entrepreneurship education resources recommendation in universities.
Improved Nonparametric Control Chart Based on Ranked Set Sampling with Application of Chemical Data Modelling
Authors: Rasheed Zahid , Khan Majid , Abiodun Nafiu Lukman , Anwar Syed Masroor , Khalaf G. , Abbasi Saddam Akber
Published: June 2022

The statistical performance of parametric control charts is questionable when the underlying process does not follow any specified probability distribution. Nonparametric control charts are the best substitute for this situation. On the other hand, the ranked set sampling technique is preferred over the simple random sampling technique because it reduces the variability of process parameters and improves the control chart’s performance. This study aims to offer a nonparametric double homogeneously weighted moving average control chart under Wilcoxon signed-rank test considering the ranked set sampling technique (regarded as

NPDHWMA

RSS

), to further enhance the process location monitoring. The proposed chart’s run-length performance is compared with competing control charts, such as DEWMA-

X
¯

, NPDEWMA-SR, NPRDEWMA-SR, DHWMA, and

NPHWMA

RSS

control charts. The comparison revealed that the proposed

NPDHWMA

RSS

control chart outperformed the other competing control charts, particularly for small to moderate shifts in process location. Finally, a real-life application is also offered for quality practitioners to show the strength of the proposed control chart.
Mechanical Performance Analysis of Steel Beam-Column Joints in Fabricated Multirise Steel Structures after Fire
Authors: Liu Fang , Wang Xiuli , Cai Bin , Li Xuguang , Yang Liqi
Published: June 2022

This study aims to analyze the mechanical properties of fabricated multistory and high-rise steel structures and steel beam-column joints after fire. Considering that the steel structure building has the characteristics of good seismic resistance, flexible structural layout, short construction period, and good safety, first, the thermal and mechanical properties of steel are analyzed. They are thermal conductivity, the thermal expansion coefficient of steel, yield strength, and elastic modulus of ordinary steel. Next, the thermal conduction principle of steel under fire environment is analyzed, including thermal conduction, thermal convection, and thermal radiation. Then, the three-story and three-span reinforced concrete is selected as the experimental object. The local frame calculation model is established through the finite element software Abaqus. It is found that when the axial compression ratio is 1.0 and the fire time of the steel body is 180 min, the vertical deformation speed of the middle column and side column of the frame will increase rapidly. Besides, the bending moment at the bottom of the side column of the frame will increase inversely. The change is not obvious when the axial compression ratio is other values. The axial deformation of the universal beam is obvious under the condition of different fire load ratios. When the load ratio increases, the maximum fire resistance of the universal beam will decrease rapidly. Meanwhile, when the steel body is subjected to the same load ratio, different bearing capacity β has little effect on the fire resistance limit of the steel body. This thesis focuses on a series of changes in the steel of fabricated multistory and high-rise steel buildings after the fire, hoping to provide a reference for the relevant teams of steel construction and make the future housing construction safer.
Deep Learning Image Classification for Fashion Design
Authors: Vijayaraj A. , Vasanth Raj P. T. , Jebakumar R. , Gururama Senthilvel P. , Kumar N. , Suresh Kumar R. , Dhanagopal R.
Published: June 2022

Fashion has always been an essential feature in our daily routine. It also plays a significant role in everyone’s lives. In this research, convolutional neural networks (CNN) were used to train images of different fashion styles, which were attempted to be predicted with a high success rate. Deep learning has been widely applied in a variety of fields recently. A CNN is a deep neural network that delivers the most accurate answers when tackling real-world situations. Apparel manufacturers have employed CNN to tackle various difficulties on their e-commerce sites, including clothing recognition, search, and suggestion. A set of photos from the Fashion-MNIST dataset is used to train a series of CNN-based deep learning architectures to distinguish between photographs. CNN design, batch normalization, and residual skip connections reduce the time it takes to learn. The CNN model’s findings are evaluated using the Fashion-MNIST datasets. In this paper, classification is done with a convolutional layer, filter size, and ultimately connected layers. Experiments are run with different activation functions, optimizers, learning rates, dropout rates, and batch sizes. The results showed that the choice of activation function, optimizer, and dropout rate impacts the correctness of the results.