bluuebunny/crossref_metadata_2025 huggingface dataset:
EFFECTS OF STRESS THEORY ON PSYCHOLOGY AND QUALITY-OF-LIFE IN PATIENTS WITH SPINAL FRACTURE DURING THE PERIOPERATIVE PERIOD
Authors: TIAN XIN , QIU XUZHONG , LI KAI , CHANG JIHUI , TANG DONGMEI , GUO DEHONG , DAI LING , ZHANG SHUANG
Published: September 2022

Objective: This study investigates how a psychological and cognitive intervention based on stress theory affected patients with spinal fractures during the perioperative period, with a focus on mental resilience, self-efficacy, and quality-of-life. Methods: The participants included 50 patients who underwent spinal fracture surgery at our hospital (People’s Hospital of Zhongjiang County) between January and June 2022. They were divided into control (25 cases) and observation (25 cases) groups according to a table of random digits. The control group received a routine intervention, while the observation group received a one-week psychological and cognitive intervention based on stress theory. Before and after the intervention, both groups completed the Connor Davidson Resilience Scale (CD-RISC), general self-efficacy scale (GSES), and MOS 36-item short-form health survey (SF-36), with scores compared. Results: Compared with the preintervention results, both groups had significantly higher postintervention scores on the CD-RISC, GSES, and SF-36. Moreover, the observation group showed much higher scores than the control group ([Formula: see text]). Conclusions: Psychological and cognitive intervention based on stress theory can effectively improve psychological resilience, self-efficacy, and quality-of-life in patients with spinal fractures during the perioperative period. This finding is of high clinical reference value.
Lie symmetry analysis, exact solutions, optimal system and conservation laws for variable-coefficients Kundu–Mukherjee–Nasker equation
Authors: Yan Xinying , Liu Jinzhou , Xin Xiangpeng
Published: September 2022

This paper investigates the (2+1)-dimensional variable coefficients Kundu–Mukherjee–Nasker equation which obtained by some transformations. The infinitesimal generators of the equation are obtained by the Lie group method. Next, the representative elements of the one-dimensional subalgebras optimal system are determined with adjoint representation. Based on the optimal system, (1+1)-dimensional partial differential equations can be obtained by similarity reductions. With the help of [Formula: see text]-expansion method, several exact solutions including hyperbolic function solutions, trigonometric function solutions and rational function solutions of variable coefficients Kundu–Mukherjee–Nasker equation are obtained. Finally, the conservation laws of the variable coefficients Kundu–Mukherjee–Nasker equation can be obtained by using the conservation theorem proposed by Ibragimov.
The Pathways toward Carbon Peak and Carbon Neutrality in China’s Building Sector
Authors: GUO Siyue , JIANG Yi , HU Shan
Published: September 2022

Achieving carbon peaking and carbon neutrality in the building sector is an important component of China’s “dual carbon” goals. In recent years, the country’s direct carbon emissions in the building sector have hit a plateau while the total emissions still grow rapidly. Besides, the building materials for construction and refrigerants leaked during buildings’ operation also result in greenhouse gas emissions. To achieve the targets set for future low-carbon development, the building sector should feature “sufficient demand, decarbonized structure and flexible load.” According to the analysis of the emission reduction approaches adopted by different sectors, China’s building sector should make a ceaseless effort to promote building energy conservation, improve electrification, and load flexibility, reform the energy system in rural areas, optimize the heating structure in northern China’s urban areas, as well as reduce the emissions during construction and the non-CO2 gas emissions. In the 14th Five-Year period, it is suggested to clarify the total energy consumption and carbon emission targets, adjust the energy structure more vigorously, and draw up more measures to reduce the emissions related to construction and refrigerant leakage.
Recent Advances in Acoustic Boundary Element Methods
Authors: Preuss Simone , Gurbuz Caglar , Jelich Christopher , Baydoun Suhaib Koji , Marburg Steffen
Published: September 2022

The modern scope of boundary element methods (BEM) for acoustics is reviewed in this paper. Over the last decades the BEM has gained popularity despite suffering from shortcomings, such as fictitious eigenfrequencies and poor scalability due to its dense and frequency-dependent coefficient matrices. Recent research activities have been focused on alleviating these drawbacks to enhance BEM usability across industry and academia. This paper reviews what is commonly known as direct BEM for linear time-harmonic acoustics. After introducing the boundary integral formulation of the Helmholtz equation for interior and exterior acoustic problems, recommendations are given regarding the boundary meshing and treatment of the non-uniqueness problem. It is shown how frequency sweeps and modal analyses can be carried out with BEM. Further extensions for efficient modeling of large-scale problems, including fast BEM and solutions methods, are surveyed. Additionally, this review paper discusses new application areas for modern BEM, such as viscothermal wave propagation, surface contribution analyses, and simulation of periodically arranged structures as found in acoustic metamaterials.
Mobility Inference on Long-Tailed Sparse Trajectory
Authors: Shi Lei , Luo Yuankai , Ma Shuai , Tong Hanghang , Li Zhetao , Zhang Xiatian , Shan Zhiguang
Published: September 2022

Analyzing the urban trajectory in cities has become an important topic in data mining. How can we model the human mobility consisting of stay and travel states from the raw trajectory data? How can we infer these mobility states from a single user’s trajectory information? How can we further generalize the mobility inference to the real-world trajectory data that span multiple users and are sparsely sampled over time?

In this article, based on formal and rigid definitions of the stay/travel mobility, we propose a single trajectory inference algorithm that utilizes a generic long-tailed sparsity pattern in the large-scale trajectory data. The algorithm guarantees a 100% precision in the stay/travel inference with a provable lower bound in the recall metric. Furthermore, we design a transformer-like deep learning architecture on the problem of mobility inference from multiple sparse trajectories. Several adaptations from the standard transformer network structure are introduced, including the singleton design to avoid the negative effect of sparse labels in the decoder side, the customized space-time embedding on features of location records, and the mask apparatus at the output side for loss function correction. Evaluations on three trajectory datasets of 40 million urban users validate the performance guarantees of the proposed inference algorithm and demonstrate the superiority of our deep learning model, in comparison to sequence learning methods in the literature. On extremely sparse trajectories, the deep learning model improves from the single trajectory inference algorithm with more than two times of overall and F1 accuracy. The model also generalizes to large-scale trajectory data from different sources with good scalability.
Effect and Mechanism of Dual-Official Group of Ethanolamines on the Chemical Mechanical Polishing of Monocrystalline Silicon
Authors: Zhang Xinying , Wang Chenwei , Zhou Jianwei , Liu Zhi , Liu Guangyao , Ma Huiping , Li Yue
Published: September 2022

Chemical mechanical polishing (CMP) is a key step in semiconductor technology because it is crucial to produce a defect-free and flat enough surface for further processing of microelectronic devices. Silicon (Si) wafer is widely used in integrated circuit (IC) devices, high-density information storage devices, and other advanced applications. In this paper, the effect of different pH and three ethanolamines, such as monoethanolamine (MEA), diethanolamine (DEA), and triethanolamine (TEA), on the removal rate of Si was studied. The influence mechanism of MEA and its concentration on Si removal rate and surface quality were mainly investigated. The results show that the removal rate increased first and then decreased with increasing pH value. Among the three ethanolamines, the effect of the removal rate of Si is MEA > DEA > TEA. It may be related to the denser passivation film formed on the Si surface by increased hydroxyl groups in ethanolamines. The removal rate first increased and then decreased slowly with the concentration of MEA increased. The removal rate reached the peak value (6800 Å·min−1) when the MEA concentration was 0.15 wt%. The changing trend of the removal rate of Si is mainly due to the Si-N bond being generated on the polished Si surface by MEA and the ionization properties of MEA, which are indicated through the X-ray photoelectron spectroscopy (XPS) and the Zeta potential measurements. Meanwhile, Si surfaces with low surface roughness and ultra-smooth with the increase of MEA concentration were obtained.
Chemical Pressure Effects on the Stokes Shift of Bi3+ Luminescence in Orthorhombic Perovskites
Authors: Srivastava A. M. , Brik M. G. , Beers W. W. , Cohen W.
Published: September 2022

The relationship between the Stokes shift of Bi3+ emission and the volume of the unit-cell in two series of orthorhombic perovskites, LnB
3+O3 (Ln = La, Gd, Y; B
3+ = Al, In, Ga) and AB
4+O3 (A = Ca, Sr; B
4+ = Zr, Sn) is explored. The Stokes shift increases linearly with increasing cell volume. This is explained qualitatively by the lattice chemical pressure acting on the Bi3+ ion. The degree of Bi3+ ion off-centering displacement, which is due to the stereochemical activity of the lone-pair electrons (6 s2), is controlled by the chemical pressure. A small cell suppresses the off-centering displacement to produce a small Stokes shift of emission by limiting the excited state structural distortion. In large cell, the off-centering displacement is more easily accommodated. The elimination of ground state distortion in the excited state gives larger Stokes shift of emission. These qualitative arguments are supplemented by recent first-principles calculations on Bi3+ luminescence in these perovskites. The Bi3+ luminescence in SrZrO3, previously assigned to emission from the D-state, is now assigned to the localized 3P0,1 → 1S0 transition. The energy of the 1S0 → 3P1 transition is correlated with the covalence of the BO6/2 perovskite framework. Discussion on the effective ionic radius of the Bi3+ ion in these perovskites is presented.
Level of Acceptance of Illness and Its Association with Quality of Life among Patients with Epilepsy in North Shewa, Ethiopia
Authors: Teshome Yonas , Solomon Yerukneh , Talargia Feredegn , Worku Negese , Shitaw Abreham , Leminie Abebaye Aragaw
Published: September 2022

Acceptance of illness is regarded as an indicator of functioning and predictor of quality of life. However, quality of life of patients with epilepsy in sub-Saharan countries worsen because of low medication adherence, increased morbidity and mortality, and the stigmatization associated with the disease. This research is aimed at assessing the level of acceptance of illness of patients with epilepsy and associated quality of life in North-East Ethiopia. Methods. A cross-sectional study was conducted from January to June 2021 at the Debre Berhan Referral Hospital, North-East Ethiopia. A total of 78 patients with epilepsy aged more than 18 years were randomly selected and assessed using Quality of Life in Epilepsy Inventory 31 and acceptance of illness scale. In addition, authors owned questionnaire were used to evaluate the sociodemographic and clinical characteristics of the patients.

P

value < 0.05 at 95% confidence level was considered to be statistically significant in all the analysis. Result. The study participants’ age varied between 18 and 67 years with the mean age of 28.9 years. Phenobarbital was the most used (73.9%) antiepileptic drug, and 68.7% (

n
=
66

) of the patients seizure was controlled. 72.9% (

n
=
70

) of the patients had medium acceptance of illness (scored 20-30), while 17.7% (

n
=
17

) had low illness acceptance level (scored 8-19), and 9.4% (

n
=
9

) had high acceptance of illness (scored 31-40). The mean of overall acceptance of illness among epileptic patients was

21.04
±
7.21

. The overall score of QOLIE-31 was

79.14
±
25.46

, and the highest mean score was for cognitive (

83.5
±
27.1

), while the lowest mean score was that of medication effect (

72.7
±
28.7

). Five of the seven QOLIE-31 components correlated significantly with level of acceptance of illness. Cognitive domain (

r
=
0.498

,

p
<
0.001

) demonstrated the highest correlation followed by overall quality of life (

r
=
0.489

,

p
<
0.001

), seizure worry (

r
=
0.433

,

p
<
0.001

), energy/fatigue (

r
=
0.342

,

p
<
0.001

), and emotional well-being (

r
=
0.278

,

p
<
0.001

). Conclusion. Patients with epilepsy in the study area had medium acceptance of illness, and nearly half of them had mean and more than the mean quality of life. The patients’ acceptance of illness was significantly associated with overall quality of life, seizure worry, emotional well-being, and cognitive domain of the patients.
A 5G Multimedia Network-Based Analysis of an Intelligent Physical Education Teaching Method
Authors: Ma Yanhui , Madina Zamira
Published: September 2022

This paper examines the delivery of intelligent physical education using a 5G multimedia network. The pupils in four classes have improved significantly in their abilities to “cross,” “drill,” “climb,” and “circle” in the obstacle course once the course is complete after studying the situational teaching approach. The average favorable rate for class 1 is 58.23%, while for class 2 it is 53.83% when the time index is 50. Class 4 has a 57.14 percent average favorable rate, while the average favorable rates for the other three classes are nearly identical. As can be seen, the majority of pupils have a basic understanding of technical motions, and no student has mastered the obstacle course technique. The new mission and new focus of intelligent service research is how to use 5G multimedia network technology, build the application scene model of intelligent physical education teaching, innovate and reconstruct the overall ecological chain of intelligent services, and continuously promote the transformation and upgrading of physical education teaching. With the aid of the 5G multimedia network, a virtual skill training or vocational training environment may be created, allowing students to experience the genuine training setting indoors while also better learning vocational skills.
Design and Application of the Digital-Oriented Interactive System for Teaching Preschool Art Education
Authors: Pan Ru , Cheng Jing
Published: September 2022

In this paper, the design of a teaching interactive system for preschool art education is digitally studied and analyzed, and the teaching interactive system is designed to be applied to the teaching process of preschool art education. It is to design and implement a convenient and feasible art education study and research mutual aid system. The art teaching mutual study and research system is based on the three-layer architecture of NET as the main system structure. The main function of the representation layer is to process the data requested by users and realize the interaction between users. The data layer is mainly to realize the processing of data logic, through the call and operation of the database, to realize the interactive access function of the database. The business logic layer is a relationship in the middle and plays the function of carrying on the top and bottom, realizing the logical processing of the database, and then realizing the business objectives of the system. The design and implementation of the multitier mechanism are of great importance in terms of improving system reliability as well as system compatibility. In the framework of activity theory research, the concept of dynamic integration of digital learning resources is proposed in conjunction with relevant research on digital learning resource integration. The intermediary of the interaction between subjects and digital learning resources in the digital learning process establishes the connection between different subjects through the interaction between elements in the activity system, promotes the accumulation of the number of digital learning resources and the two-way interaction of effective information, and thus realizes the orderly organization and management of the digital learning resource system. The theoretical basis of dynamic integration of digital learning resources, including activity theory, knowledge organization theory, and feedback principle, is discussed in detail in the study to provide a basis for the construction of the theoretical model of dynamic integration of digital learning resources.
A Method of Extracting and Identifying College Students’ Music Psychological Features Based on EEG Signals
Authors: Liang Li
Published: September 2022

With the development of information technology, music education in universities is also changing. Traditional music education can not effectively explore the feature of students, resulting in the quality of music education being restricted. The rapid development of Electroencephalogram (EEG) signals has brought a new educational model to music education. Through the extraction of students’ psychological features of music by EEG, psychological features can be identified and different educational programs can be formulated according to the results. Multifeature extraction and combination method can improve the accuracy of EEG feature extraction. Using empirical mode decomposition and wavelet packet decomposition of the two kinds of methods to analyze EEG data, respectively, then the average energy, volatility index, sample entropy, and approximate entropy and multiscale features such as permutation entropy and Hurst index, select features in combination, to classify the feature set after the combination, so as to find out the feature of the performance of the optimal combination. The experimental results show that the feature combination of sample entropy and approximate entropy can better represent the main features of EEG psychological characteristic signals after wavelet packet decomposition, and the recognition accuracy is more than 90%.
Bile Reflux Gastritis: Insights into Pathogenesis, Relevant Factors, Carcinomatous Risk, Diagnosis, and Management
Authors: Shi Xiaolan , Chen Zijiao , Yang Yi , Yan Su
Published: September 2022

Bile reflux gastritis (BRG), a kind of gastrointestinal disorder in clinical practice, is characterized by regurgitation and inflammation. However, lack of guidelines leads to simple cognition and even ignorance of this disease for clinicians. Primarily, making the pathogenesis of BRG clear contributes to a correct and general understanding of this disease for physicians. Next, although recently there has been an increasing awareness among researchers in terms of the relevant factors for BRG, further studies involving large samples are still required to certify the relationship between them explicitly. Besides, researches have established that BRG is closely associated with the development of precancerous lesions and gastric cancer. Till now, there is still no golden standard for diagnosis of BRG. Nevertheless, advances in techniques, especially extensive applications of endoscopy and chemical analysis of reflux contents, have improved our ability to identify the occurrence of this disease as well as distinguishing physiological reflux from pathological reflux. Finally, it is fortunate for patients that more and more importance has been attached to the treatment of BRG. From lifestyle modification to drug therapy to surgery, all of them with the view of realizing symptomatic relief are employed for patients with BRG. In this review, we briefly evaluate this disorder based on the best available evidence, offering an overview of its complicated pathogenesis, diverse relevant factors, potential carcinomatous risk, modern diagnostic investigations, and effective therapeutic plans.
Volume Fluctuations in Active and Nonactive Transtibial Prosthetics Users
Authors: Hamzah Nur Afiqah , Razak Nasrul Anuar Abd , Karim Mohd Sayuti Ab , Salleh Siti Zuliana
Published: September 2022

This study aims to evaluate the validity and reliability of the Biosculptor’s Bioscanner system in capturing transtibial residual limb volume fluctuations in active and nonactive amputees during walking activity. Residual limb volume was obtained by measuring the limb circumference after amputees walked for 5 to 25 minutes for five consecutive days. The comparison of mean circumference between Bioscanner and manual measurements (i.e., tape measure) showed that the Bioscanner gave a higher estimation of circumference for the different amputees. Short‐term changes in girth and volume due to an activity such as walking do not fluctuate uniformly. The results reflected as such as nonconsistence circumference change identified at different locations of the circumference profiles. Both amputees experienced a significant increase in circumference at the distal end of the limbs after 5 minutes of walking (7.35% change in nonactive and 8.83% in active amputees), and the measurement decreased as amputees walked longer. At 4‐8 cm below the mid‐patella tendon (pressure tolerant areas), both amputees experienced minor changes in the size of their circumference. The residual limb volume calculation resulted in the percentage difference between the two methods ranging from 2.4% to 9.3%. Pearson coefficient correlation obtained showed a high correlation between the two techniques, ranging from 0.97 to 1. The analysis of the limit of agreements showed that the majority of measurements were closed to the mean, suggesting that Bioscanner and manual techniques may be interchangeable and agree with one another. This study has implied that Bioscanner is comparable to the standard measurement method and may serve as an alternative tool in managing daily residual limb volume change.
Observation of Curative Effect of Lung Recruitment in Patients with Acute Respiratory Distress Syndrome after Cardiopulmonary Bypass Surgery
Authors: Guo Lin , Zeng Jinxiu , Liu Ziyou , Wei Zijie , Wen Caiyun , Zhang Yue , Chen Xu , Xie Heping
Published: September 2022

Recruitment maneuver (RM) has become a routine supplementary maneuver for clinical rescue of severe ARDS with low tidal volume/pressure-limited mechanical ventilation. Recruitment of patients with ARDS mechanical ventilation can improve the lung compliance, promote the opening of collapsed alveoli, improve the ratio of ventilation to blood flow, reduce dead space, reduce shunt flow, and improve oxygenation function. In this paper, the patients were divided into lung recruitment group and conventional treatment group by the random number permutation table method. When the patient’s percutaneous oxygen saturation is less than or equal to 88%, the partial pressure of oxygen in the arterial blood gas is less than or equal to 55 mmHg, or the ventilator tube is disconnected during sputum suction or other accidents, a

CPAP
×
60
−
second

lung recruitment maneuver is required. Then adjust the ventilator parameters in the same way. In the process of lung recruitment, the changes in invasive continuous arterial blood pressure will also be observed. If the blood pressure dropped to ≤90/60 mmHg, one recruitment maneuver was terminated in advance. And both groups of patients used the Dräger- or PB840-imported multifunctional ventilator. The treatment of primary disease and predisposing factors, fluid management strategies, antibiotics and glucocorticoids, nutrition, and metabolic support in the two groups of patients in the study were the same. The PaO2/FiO2 value improved by 51% 10 minutes after recruitment, and the median increased from 111 (IQR, 73-265) before recruitment to 170 (IQR, 102-340) (

P
<
0.01

), the improvement of PaO2/FiO2 at 4 hours after recruitment and 12 hours after recruitment was 78% (

P
<
0.05

) and 39% (

P
<
0.01

), respectively, and the median PaO2/FiO2 at 4 hours after recruitment was 198 (IQR, 116-256). The median PaO2/FiO2 became 155 (IQR, 127-235) 12 hours after recruitment. Recruitment can reduce the accumulation of neutrophils in lung tissue, reduce the release of inflammatory factors, reduce pulmonary edema, and reduce pathological damage.
Optimization of Stir-Squeeze Casting Parameters to Analyze the Mechanical Properties of Al7475/B4C/Al2O3/TiB2 Hybrid Composites by the Taguchi Method
Authors: Gugulothu Bhiksha , Anusha P. , Swapna Sri M. Naga , Vijayakumar S. , Periyasamy R. , Seetharaman Suresh
Published: September 2022

Stir-squeeze casting (SSC) is the appropriate and inexpensive technique for producing aluminum hybrid matrix composites as it creates a uniform distribution of reinforcements in the composite with finer grains. Al7475 is a lightweight castable alloy that possesses enough hardness and strength with applications in automotive and aerospace. This research work examines the effect of process parameters for Al7475/Al2O3/B4C/TiB2 hybrid matrix composites produced by the stir-squeeze casting methodology. As per Taguchi design L16, four parameters with four levels were selected in the optimization process of SSC are stir speed (SD) of 300-450 rpm, melting temperature (ME) of 750–900°C, squeeze pressure (SE) of 50-125 MPa, and reinforcement (RT) of 2-8 wt%. The mechanical properties such as tensile strength (TS) and hardness (HN) are studied by the variation of each process parameters levels. The optimization results on TS and HN are predicted by Minitab-17 Software. It is observed that maximum TS of 325 MPa and HN of 130.6 Hv are attained at experiments L1 and L7, respectively. From the SN ratio result, the TS value is improved at the parameter level of RT2-SE4-ME2-SD4. The ANOVA result exposed that reinforcement is the most significant factor for enhancing tensile strength which contributes 38.9%, followed by squeeze pressure of 28.4%, stir speed of 13.6%, and melting temperature of 12.16%.
Prediction of Sports Performance and Analysis of Influencing Factors Based on Machine Learning and Big Data Statistics
Authors: Wang Panpan , Liu Jiangbo , Liao Benlu
Published: September 2022

Performance prediction is one of the important contents of sports future development strategy research. This paper conducts research on sports performance prediction and influencing factor analysis based on machine learning and big data statistics. The purpose of forecasting research is to formulate short-term, medium-term, and long-term sports development planning and policy services for decision-makers of sports development. Advantages and disadvantages make sports workers consciously revise and realize their own sports future plans. First, the analysis of the influencing factors of sports performance is proposed, including the setting and scoring of sports examination items, research on standards, training methods for physical examination items, and physical examination learning. Second, the application of big data statistics based on machine learning algorithms is studied. Based on machine optimization algorithms, it summarizes the naive Bayesian classification algorithm and big data statistical classification algorithm. The theoretical idea of rough set algorithm and finally through the comparative analysis experiment based on big data statistics of male and female sports test scores and the comparison experiment of the accuracy of three algorithms to predict the results, it is concluded that the endurance quality of boys is better than that of girls, which indicates the quality of sustainable development. There is a certain gender gap, there are significant differences in the skills of male and female students, and the machine-optimized algorithm can predict sports performance with the highest accuracy among the three algorithms.
Temperature Changes in Oral All-Ceramic Materials with Different Optical Properties under Er:YAG Laser Irradiation
Authors: Yang Shuo , Yun Zhaoqiang , Zhao Lei , Cheng Mingwei , Zhou Tengfei , Huang Erliang , Guo Yongtong , Xu Yan , Yin Wuwei , Chen Xiao , Wang Junchen , Chu Hongxing
Published: September 2022

Objectives. This in vitro study is aimed at assessing the oral all-ceramic materials energy transmission and temperature changes after Er:YAG laser irradiation of monolithic zirconia all-ceramic materials with varying optical properties. Materials and Methods. Two monolithic zirconia materials, Zenostar T and X-CERA TT (monolithic Zirconia), were studied. Specimens were divided into four groups, with a thickness of 1.0, 1.5, 2.0, and 2.5 mm, respectively. The chemical elemental composition of the two materials was determined using X-ray spectroscopy and Fourier transform infrared spectroscopy. The light transmittance of specimens with different thicknesses was measured using a spectrophotometer at three wavelength ranges: 200–380, 380–780, and 780–2500 nm. Irradiation with Er:YAG laser was performed, and the resultant temperature changes were measured using a thermocouple thermometer. Results. Compositional analysis indicated that Si content in X-CERA TT was higher than that in Zenostar T. The light transmittance of both materials decreased as specimen thickness increased. Er:YAG laser irradiation led to temperature increase at both Zenostar T (26.4°C–81.7°C) and X-CERA TT (23.9°C–53.5°C) specimens. Both optical transmittance and temperature changes after Er:YAG laser irradiation were consistent with exponential distribution against different thickness levels. Conclusion. Er:YAG laser penetration energy and resultant temperature changes were mainly determined by the thickness and composition of the examined monolithic zirconia materials.
Lifestyle Intervention for Patients with Nonalcoholic Fatty Liver Disease: A Randomized Clinical Trial Based on the Theory of Planned Behavior
Authors: Mobasheri Narges , Ghahremani Leila , Fallahzadeh Abarghooee Ebrahim , Hassanzadeh Jafar
Published: September 2022

Introduction. Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, accounting for about 25% and 33% of the world’s adult population and Iranians, respectively. There is currently no effective therapeutic agent available for the treatment of NAFLD. However, lifestyle modifications aimed at weight loss have been introduced as a cornerstone of NAFLD management. The aim of the present study was to evaluate the effect of educational intervention on lifestyle and anthropometric indices in patients with NAFLD. Methods. The randomized controlled clinical trial was performed on 87 overweight or obese patients with NAFLD, including intervention (n = 42) and control (n = 45) groups. The intervention received 8 training sessions based on theory of planned behavior (TPB), while the control groups received nutritional and physical activity recommendations from their internal specialist and nutritionist. Analyses were carried out based on data collected from TPB constructs and anthropometric indices (weight, body mass index (BMI), waist size, and waist‐hip ratio (WHR)) at three stages (before intervention and two and 12 weeks after the intervention), as well as data obtained from liver enzymes (alanine aminotransferase (ALT) and aspartate aminotransferase (AST)), and ultrasound‐based grading of NAFLD at two stages (before and 12 weeks after the intervention). Results. After the intervention, a significant difference was found between the intervention and control groups, resulting in the increased mean scores of TPB constructs, decreased liver enzymes, and decreased degree of NAFLD ultrasound. In addition, the intervention group experienced more activity and healthy diet as compared with the control group. Anthropometric indices showed only a significant decrease in BMI in the intervention group (p < 0.05). Conclusions. TPB‐based training, as compared with traditional training, is a more effective and cost‐effective strategy for altering nutritional behavior and physical activity of patients with NAFLD.
A Volume Challenge Reveals the Diagnosis of Pediatric Restrictive Cardiomyopathy
Authors: Cohen Elyssa , O’Halloran Conor P. , Thrush Philip T. , Ma T. Marsha , Tannous Paul
Published: September 2022

A healthy 11-year-old girl presented with exercise intolerance of unclear etiology, and her physical exam was notable for a 3/6 systolic ejection murmur at the left upper sternal border with radiation to the back. Extensive noninvasive workup consisted of ECG, transthoracic echocardiogram, and cardiac MRI/MRA, which were all nondiagnostic. She was ultimately referred for cardiac catheterization. Baseline invasive hemodynamics demonstrated a normal cardiac index and pulmonary vascular resistance but was notable for mildly elevated right and left end-diastolic pressures. A diagnosis remained elusive, so a 500 mL volume challenge was performed, which unmasked right and left ventricular waveform transformations to reveal the pathognomonic “square root sign” of restrictive cardiomyopathy with concordant RV/LV respirophasic variation. These findings and her clinical history allowed for the rare pediatric diagnosis of restrictive cardiomyopathy early in her clinical course, prior to the development of overt signs of pathologic myocardial remodeling, such as pulmonary hypertension and biatrial enlargement.
Hypoxia Confers Tumor with a Higher Immune Infiltration but Lower Mutation Burden in Gastrointestinal Cancer
Authors: Hu Junjie , Hu Wangxiong , Yang Yanmei
Published: September 2022

Background. Hypoxia is one of the driving forces of cancer progression, recurrence, and metastasis. However, the association between the tumor hypoxic tumor microenvironment and the tumor mutation burden (TMB) is poorly understood in gastrointestinal cancer. Methods. Approximately 2,000 samples from colorectal cancer (CRC) and stomach adenocarcinoma (STAD) patients were obtained from the gene expression omnibus database and the cancer genome Atlas databases and were clustered and subtyped by nonnegative matrix factorization. Significant differentially expressed genes that were possibly related to survival differences between the hypoxic and normoxic groups were subjected to multivariate Cox regression. Results. Gastrointestinal cancer patients with CRC and STAD were further divided into two subgroups, namely, the hypoxia group and the normoxia group, and hypoxia was correlated with unfavorable outcomes. Notably, hypoxic tumors had lower TMB but significantly higher levels of immune and stromal infiltration. A signature of HEYL and NRP1 selected by LASSO classified gastrointestinal cancer patients into either a low or high-risk group, allowing for the combination of TMB status with markers of hypoxia in future clinical applications. Conclusions. Hypoxia is an independent prognostic factor and a strong immune infiltration indicator in gastrointestinal tumors of different organs, especially for cancers with low TMB.
Improved VMD-+ACO Algorithm Navigation and Positioning Technology for Robot Electric Power Inspection
Authors: Long Yingkai , Du Mingming , Luo Xiaoxiao , Li Siquan , Jiang Xiping
Published: September 2022

In order to meet the navigation and positioning requirements of force inspection robot, a new technology based on improved VMD- + ACO algorithm is proposed. The main content of this technology is based on the research of improved VMD algorithm and ACO algorithm, through the comparison of VMD algorithm and improved VMD algorithm. By using ACO parameter optimization design and so on, the research means of improving VMD- + ACO algorithm navigation and positioning technology of electric inspection robot is finally established through experiments and analysis. The experiment result shows the following. The minimum iteration number of the improved ACO is 112, which is 24.32% less than that of the basic ACO. The mean value of the worst value and the optimal value of the function are equal to 0. It shows that the improved ACO has higher convergence precision and the number of iterations is significantly reduced. Conclusion. Based on the improved VMD- + ACO algorithm, it can meet the navigation and positioning requirements of electric inspection robot.
A Talent Training Model for Electrical Courses considering Diverse Constraint Models and Knowledge Recognition Algorithms
Authors: Min Fanping
Published: September 2022

In order to improve the talent training effect of electrical courses, this paper proposes a talent training model for electrical courses considering diverse constraint models and knowledge recognition algorithms. In order to obtain better performance of traditional deep learning models, it is usually necessary to increase the parameter scale of traditional deep learning models. Pretrained language models can be trained unsupervised directly using unlabeled corpora to learn vector representations of words without using labeled datasets. In addition, this paper uses the knowledge base and alias dictionary to build a knowledge graph and constructs a teaching model for electrical courses considering diverse constraint models and knowledge recognition algorithms. Through the research, it can be seen that the experimental teaching model of electrical courses proposed in this paper considering diverse constraint models and knowledge recognition algorithms has a very good effect on talent training.
Financial Accounting Information Data Analysis System Based on Internet of Things
Authors: Bi Yulin
Published: September 2022

In order to meet the intelligent demand of modern financial data analysis, this paper proposes a financial accounting information data analysis system based on the Internet of things. Based on the central reinforcement learning architecture, the model uses multiple execution modules to enhance the computing and generalization ability of the single-agent reinforcement learning algorithm. In the selection of reinforcement learning algorithm, the instantaneous time difference algorithm is introduced. The algorithm can synchronize the experience of the previous iteration state in the learning process and does not depend on the final prediction value, which greatly saves the storage cost. In the establishment of the financial data analysis index system, the paper comprehensively considers the enterprise’s operation, development, debt repayment, and other capabilities, ensuring the integrity and rationality of the index system. In order to evaluate the performance of the algorithm, this paper takes the real financial data as the sample and uses BP neural network to conduct a comparative experiment. The experimental results show that the recognition accuracy of the model is better than that of the BP neural network in each experimental scenario, and the recognition accuracy of Experiment 3 is improved by 4.6%. Conclusion. The performance of the distributed reinforcement learning algorithm is better than that of the common back-propagation neural network in the real data set scenario.
[Retracted] Design and Implementation of Mental Health Consultation System for Primary and Secondary School Students Based on Credibility Matching Model
Authors: Li Bo
Published: September 2022

Primary and secondary schools have the enormous responsibility of developing talent over a hundred years, and they should not only be concerned with the moral, ideological, and cultural development of teenagers but also with their mental well‐being. We need to start by making the external environment better, provide in‐depth psychological counseling, and support students as they work to continually increase their psychological adaptability in order to promote the healthy development of their personalities. As the epidemic situation in China has now stabilized into a normal state of prevention and control, it is imperative to provide primary and secondary school students with mental health education. In light of this context, this paper develops a browser‐server network architecture‐based consultation system for the mental health of students in primary and secondary schools. It eliminates the conventional booking mode and substitutes credibility as the characteristic programming parameter. The performance of the original system is improved by the reliability model the most when the parameter is set to 0.2, and the recovery rate rises by 1.32 percent. Compared to the original reliability model, which improved the system’s F value performance by 0.83 percent, the accuracy rate only declines by 0.68 percent while F rises by 0.37 percent. This research is crucial for creating an information campus and raising the standard of psychological counseling.
Study on the Influencing Factors and Willingness to Pay of Consumers Purchasing Ecological Agricultural Products
Authors: Hao Huicheng , Yin Sixuan , Yu Hang , Liu Zemin , Liu Ziyu
Published: September 2022

With the steady rise of China’s agricultural production and management level, the market of ecological agricultural products has developed rapidly, and consumers are increasingly concerned about ecological agricultural products. Consumers’ cognition and purchase intention are the keys to determine their future development. This research is aimed at ensuring that consumers have access to high‐quality ecological agricultural products, thereby promoting the supply and production of ecological agricultural products, minimizing agricultural carbon emissions, and providing information on sustainable food pricing. Based on the research status at home and abroad, this study combines the questionnaire survey method to study the influencing factors and willingness to pay of consumers purchasing ecological agricultural products. A total of 601 online questionnaires from consumers in Harbin, a city in northeastern China, were collected, and statistical factor analysis, principal component analysis, and regression analysis were used to study the influencing factors of consumers’ purchase of ecological agricultural products from both positive and negative aspects, and in‐depth analysis of the reasons why consumers refuse to pay, get the most real willingness to pay and related influencing factors, and quantify the influence of various variables on consumers’ purchasing behavior was done. On this basis, a logit model of survival analysis is constructed to study the premium payment level of consumers for ecological agricultural products, and the payment premium is 24.95%. The research results show that married, who have purchased ecological agricultural products, the higher the understanding of ecological agricultural products, the consumers who buy ecological agricultural products in farmers’ markets, Meituan and community group purchases, and the households with higher monthly consumption of agricultural products have a significant positive correlation with consumers’ purchase of ecological agricultural products. The higher the education level, the older the age, and the larger the family size were significantly negatively correlated with consumers’ purchase of ecological agricultural products.
[Retracted] The Understanding of Vital Pulp Therapy in Permanent Teeth: A New Perspective
Authors: Shang Wei , Zhang Zeliang , Zhao Xicong , Dong Qingquan , Schmalz Gerhard , Hu Shaonan
Published: September 2022

The indications of vital pulp therapy (VPT) are expanding, which cases are suitable for VPT, and how to improve the success rate of VPT is a problem that often bothers us. The main purpose of VPT is to eliminate pulpitis by promoting the formation of reparative dentin or calcium bridge, so that it can continue to perform various physiological functions, and finally achieve the purpose of preserving pulp vitality and long‐term preservation of affected teeth. Pulp capping and pulpotomy are the most common methods for VPT. The research field of VPT has attracted the attention of many scholars, who have studied it from many aspects (such as indications, material selection, operation requirements, and long‐term prognosis). This article reviews the recent advances in the techniques of VPT in permanent teeth.
A Machine Learning Model Based on Unsupervised Clustering Multihabitat to Predict the Pathological Grading of Meningiomas
Authors: Wang Xinghao , Li Jia , Sun Jing , Liu Wenjuan , Cai Linkun , Zhao Pengfei , Yang Zhenghan , Lv Han , Wang Zhenchang
Published: September 2022

Purpose. We aim to develop and validate a machine learning model by enhanced MRI to determine the pathological grading of meningiomas with unsupervised clustering image analysis method, which are multihabitat to reflect the inherent heterogeneity of tumors. Materials and Methods. A total of 120 patients with meningiomas confirmed by postoperative pathology were included in the study, including 60 patients with low‐grade meningiomas (WHO grade I) and 60 patients with high‐grade meningiomas (WHO grade II and WHO grade III). All patients underwent complete head enhanced magnetic resonance scans before surgery or any anti‐tumor treatment. Enrolled patients in the group received surgical resection and obtained postoperative pathological data. The patients in the training group (84 people) and the test group (36 people) were randomly divided into two groups according to the ratio of 7 to 3. Multi‐habitat features were extracted from MRI images based on enhanced T1. Machine learning method was used to model, which was used to distinguish high‐grade meningioma from low‐grade meningioma. At the same time, the obtained machine learning model was calibrated and evaluated. Results. In patients with low‐grade meningioma and high‐grade meningioma, we found significant differences in Silhouette coefficient (P<0.05). In the machine learning model, the area under the curve was 0.838 in the training group (sensitivity, 67.65%; specificity, 88.82%) and 0.73 in the test group (sensitivity, 69.05%; specificity, 71.43%). After the analysis of calibration curve and decision curve analysis, the model had shown the potential of great application value. Conclusions. Multi‐habitat analysis based on enhanced MRI (T1) could accurately predict the pathological grading of meningiomas. This unsupervised image‐based method could reflect the direct heterogeneity between high‐grade meningiomas and low‐grade meningiomas, which is of great significance for patients’ treatment and prevention of recurrence.
[Retracted] Cognitive Attitudes of International Mainstream Media to China during the Contaminated Water and Human Health Under Big Data
Authors: Ji Kaixi , Yang Zitong , Zhou Mengqian
Published: September 2022

The water pollution affecting human health is a crisis and big test, which tests the mainstream news media’s ability and level of communication to respond to major public opinions and public emergencies. The contaminated water is a crisis and a major test, which tests the ability and level of communication of major news outlets to respond to important common views and emergencies. It aims to understand the perception and attitude of the international mainstream media towards China during the contaminated water. The work sorted out the mainstream media’s reporting of China from the contaminated water to the present and selected the New York Times, The Times, and the Guardian as examples. We could understand the changes in China’s international image during the water pollution through these mainstream media reports on China. The results show that these media reports on water pollution in China mainly focused on negative public opinion, which accounted for more than 70% of the total number of reports. Western developed countries such as the United Kingdom and the United States are out of consideration for their national interests. Using mainstream media to create public opinion that is not conducive to China, advocating “neo‐colonialism”, “China threat theory” and other false statements, trying to limit China’s influence, due to the difference in cognitive habits and the influence of British and American media hegemony also affects the country The communication and understanding between the two have brought obstacles.