bluuebunny/crossref_metadata_2025 huggingface dataset:
Patient and healthcare team recommended medication adherence strategies for hydroxychloroquine: results of a qualitative study informing intervention development
Authors: Garg Shivani , Chewning Betty , Gazeley David , Gomez Shelby , Kaitz Noah , Weber Amanda C , Rosenthal Ann , Bartels Christie
Published: August 2022

Objective

Patients identified as black and from disadvantaged backgrounds have a twofold higher hydroxychloroquine (HCQ) non-adherence, which contributes to worse lupus outcomes and disparities. Yet, most adherence interventions lack tailored strategies for racially and socioeconomically diverse patients who face unique challenges with HCQ. We aimed to examine a broadly representative group of patients with SLE and physician perspectives on HCQ adherence and adherence strategies to redesign an adherence intervention.

Methods

We conducted four virtual focus groups (90 min each) with 11 racially and socioeconomically diverse patients with SLE recruited from two health systems. Additionally, we hosted two focus group meetings with nine healthcare advisors. In focus groups, patients: (1) shared their perspectives on using HCQ; (2) shared concerns leading to non-adherence; (3) discussed strategies to overcome concerns; (4) prioritised strategies from the most to least valuable to inform an adherence intervention. In two separate focus groups, healthcare advisors gave feedback to optimise an adherence intervention. Using content analysis, we analysed transcripts to redesign our adherence intervention.

Results

Worry about side effects was the most common barrier phrase mentioned by patients. Key themes among patients’ concerns about HCQ included: information gaps, logistical barriers, misbeliefs and medication burden. Finally, patients suggested adherence strategies and ranked those most valuable including co-pay assistance, personal reminders, etc. Patient and healthcare advisors informed designing a laminate version of an adherence intervention to link each barrier category with four to six patient-recommended adherence strategies.

Conclusion

We developed a patient stakeholder-informed and healthcare stakeholder-informed tailored intervention that will target non-adherence at the individual patient level.
Management of Decompensated Cirrhosis in the Surgical ICU: an American Association for the Surgery of Trauma Critical Care Committee Clinical Consensus Document
Authors: Seshadri Anupamaa , Appelbaum Rachel , Carmichael Samuel P , Cuschieri Joseph , Hoth Jason , Kaups Krista L , Kodadek Lisa , Kutcher Matthew E , Pathak Abhijit , Rappold Joseph , Rudnick Sean R , Michetti Christopher P
Published: August 2022

Management of decompensated cirrhosis (DC) can be challenging for the surgical intensivist. Management of DC is often complicated by ascites, coagulopathy, hepatic encephalopathy, gastrointestinal bleeding, hepatorenal syndrome, and difficulty assessing volume status. This Clinical Consensus Document created by the American Association for the Surgery of Trauma Critical Care Committee reviews practical clinical questions about the critical care management of patients with DC to facilitate best practices by the bedside provider.
Pion damping width and pion spectral function in hot pion gas
Authors: Goderidze D. , Friesen A. , Kalinovsky Yu.
Published: August 2022

The temperature behavior of the pion width in the hadronic phase is investigated in the framework of the Nambu–Jona–Lasinio (NJL) model. The contribution to the width from the pion–pion collision is considered with a scalar sigma-meson as an intermediate state. It is shown that the pion width significantly broadens at [Formula: see text][Formula: see text]GeV. Using the two-step iteration method, suggested by Kadanoff and Baym, the pion spectral function in a hot pion gas is calculated at different temperatures.
A Semantic Web-Enabled Approach for Dependency Management
Authors: Eghan Ellis E. , Rilling Juergen
Published: August 2022

The use of external libraries in today’s software projects allows developers to take advantage of features provided by such application programming interfaces (APIs) without having to reinvent the wheel. However, APIs have also introduced new challenges to the software engineering community (e.g. API incompatibilities, software vulnerabilities, and license violations) that extend beyond traditional project boundaries and often involve different software artifacts. One potential solution to these challenges is to provide a technology-independent representation of software dependency semantics and its integration with knowledge from other software artifacts.

In our research, we take advantage of the semantic web (SW) and its technology stack to establish a unified knowledge representation of build and dependency repositories. Given this knowledge base, we can now extend and integrate other (heterogeneous) resources to allow for a flexible and comprehensive global impact analysis approach. To illustrate the applicability of our SW-enabled modeling approach, we discuss two different applications. These applications illustrate how our modeling approach can not only integrate and reuse knowledge from dependency management systems and other software artifacts, but also take advantage of inference services provided by the SW to support novel software analytics services across artifact and project boundaries.
Role of spacetime shear for cosmological gravitational waves, in presence of imperfect fluids
Authors: Mayala Roger M. , Goswami Rituparno , Maharaj Sunil D.
Published: August 2022

In this paper, we show that a general geometric and thermodynamic but shear-free perturbation of homogeneous and isotropic universes are necessarily silent, without any gravitational waves, in spite of the presence of nonzero electric and magnetic Weyl. We prove this in two steps. First, we establish that a shear-free perturbation of these universes is acceleration-free and the fluid flow geodesics of the background universe map onto themselves in the perturbed universe. This effect then decouples the evolution equations of the electric and magnetic parts of the Weyl tensor in the perturbed spacetimes and the magnetic part no longer contains any tensor modes. Although the electric part that drives the tidal forces does have tensor modes sourced by the anisotropic stress, these modes have homogeneous oscillations at every point on a time slice without any wave propagation. We also show the presence of vorticity vector waves that are sourced by the curl of heat flux. This analysis shows the critical role of the shear tensor in generating cosmological gravitational waves in an expanding universe.
Local price uncertainty principle and time-frequency localization operators for the q-Hankel–Stockwell transform
Authors: Elmonser Hedi , Brahim Kamel
Published: August 2022

In this paper, using the [Formula: see text]-Jackson integral and some elements of the [Formula: see text]-harmonic analysis associated with the [Formula: see text]-Hankel transform, we introduce and study the [Formula: see text]-analogue of the Hankel–Stockwell transform. We give some harmonic analysis properties (Plancherel formula, inversion formula, reproduicing kernel[Formula: see text]). Furthermore, we establish a version of Heisenberg’s uncertainty principles. Last, we study the [Formula: see text]-Hankel–Stockwell transform on subset of finite measure.
20世纪 “文化中国” 的再展演
Authors: 蔡 志祥
Published: August 2022

社区性节日展陈了社会群体的整体。在20世纪，中国和海外华人的社区性节日受到了很多挑战，到了近年才“复兴”起来。作为周期性的活动，社区性节日定期庆祝，因此是社区成员已知和共享的活动。然而，仪式细节以及对节日的解释总是会根据不断变化的宏观环境而进行调整。20世纪是华侨身份由旅居者向定居者转变的时期。这是一个华侨与祖籍地疏远、在东道国定居，以及与中国重新联系的时期。本文将使用三个典型的节日来讨论中国社区性节日作为一种全球现象的延续，特别是探索节日在海外华人社会中仪式结构的演变及其与祖先家乡之间的相互作用。本文认为，中国传统文化，尤其是持续庆祝的社区性节日，不仅是华侨华人建立华人身份认同的工具，有助于重建与祖籍的联系；更重要的是，它们是海外华人利用的一种文化资源，在在地化过程中，塑造为在生活国家中的重要“他者”的身份。“中华文化”是一种生存策略，考验着地方当局的宽容度；同时，通过标准化的仪式，缓和华侨华人的内部差异。
区域华文文学的越界、跨国与主体解/构
Authors: 朱 崇科
Published: August 2022

区域华文文学的产生和发展自有其阶段性和因为时代语境差异带来的不同进度与特色，文学生产的主体性及其身份认同也在发生着巨大变化，尤其是网络媒体的强势崛起也部分消解了固有的身份政治，毋庸讳言，个体物理空间的迁移、身份的转换、宏阔（文化）政治语境的影响等等自然也确立了作者个体及区域文学生产的某种边界乃至界限感，同时也有可能的世界眼光（如李永平），但作者对更大文学场的影响力或名利的追逐又部分消解同时又建构了创作主体新的身份认同（如黄锦树）。
Chrono-contextual issues at open-air Pleistocene vertebrate fossil sites of central and peninsular India and implications for Indian palaeoanthropology
Authors: Chauhan Parth R.
Published: August 2022

Pleistocene vertebrate fossils are prominently known from several regions across the Indian Subcontinent including the Siwalik Hills, the numerous river valleys across India and some cave sites. Unfortunately, most of this evidence is lacking a robust chronological framework and very few fossil specimens have been subjected to absolute dating methods. All of the known fossil evidence is found in diverse sedimentary contexts and these faunal assemblages have mostly been assigned broad or relative age brackets such as Early Pleistocene (i.e. the Pinjore Formation of the Upper Siwalik Subgroup) and Late Pleistocene (almost all the remaining fossil vertebrate fauna in the rest of the Subcontinent). This paper discusses contextual and chronological perspectives and associated interpretative issues of open-air Pleistocene faunal sites south of the Siwalik Hills, such as north-central and peninsular India. For instance, the virtual lack of Early and Middle Pleistocene fauna across most of India requires consideration and explanations beyond just the lack of absolute dates. A general review of the known data demonstrates a critical need for absolute dates for the various fauna as well as more rigorous field and lab methods for Indian palaeontology in general, and to avoid erroneous implications for Indian palaeoanthropology.
Therapeutic Effect of Ultrasound-Guided Peripherally Inserted Central Catheter Combined with Predictive Nursing in Patients with Large-Area Severe Burns
Authors: He Baiyan , Zhang Aiqiong , He Shuting
Published: August 2022

This study was aimed to explore the application value of ultrasound-guided peripherally inserted central catheter (PICC) combined with predictive nursing in the treatment of large-area severe burns. 88 patients with large-area severe burns who visited hospital were chosen as the research objects. They were randomly divided into the observation group and the control group, with 44 cases in each. The patients in the observation group were treated with ultrasound-guided PICC combined with predictive nursing, while those in the control group were treated with traditional PICC and nursing methods. Then, the anxiety of patients was compared between groups by the Self-rating Anxiety Scale (SAS), while the depression was compared by the Self-rating Depression Scale (SDS). The pain of the patients was analyzed by the McGill Pain Questionnaire (MPQ), and a self-made nursing satisfaction questionnaire was adopted to evaluate the nursing satisfaction. The surgery-related indicators of the patients were detected and recorded (the success rate of one-time puncture, the success rate of one-time catheter placement, incidence of complications, heart rate, blood pressure, etc.). The success rates of one-time puncture (93% vs. 86%) and of catheter placement (95% vs. 81%) in the observation group were significantly higher than those in the control group,

P
<
0.05

. The pain scores of the observation group were much lower than those of the control group at each time period,

P
<
0.05

. The number of patients with negative emotions such as anxiety and depression in the observation group was markedly less than that in the control group. The incidence of complications in the observation group was notably lower than that in the control group (4.5% vs 18%),

P
<
0.05

. The nursing satisfaction of the observation group was significantly higher than that of the control group (93% vs 79.5%),

P
<
0.05

. In conclusion, ultrasound-guided PICC and predictive nursing had high clinical application values in the treatment of patients with large-area severe burns.
Research on the Construction and Development Prospect of Aided Business English Teaching System Based on Computer Multimedia Technology
Authors: Zhang Baicheng
Published: August 2022

The intervention of multimedia technology has had a profound impact on education, which has led to the renewal of educators’ ideas, the renewal of educational means, and the renewal of educational forms. To some extent, the influence of multimedia technology on educational technology has opened a new chapter in educational reform. It can be said that the powerful advantages of multimedia education technology promote the pace of teaching reform and conform to the needs of the development of the times. This paper mainly analyzes the research on the construction and development prospects of the business English teaching system based on computer multimedia technology, uses the computer vision technology to collect teaching information, and then uses VR for teaching. Computer vision mainly studies how to use video sensing devices and computers to simulate the human visual system to collect and process external visual information, so that machines have the same visual ability as humans and even have the ability to “think.” Through virtual teaching design and research virtual teaching methods, combined with the characteristics of business English subjects, the computer vision technology is connected with business English course teaching to develop new teaching methods for business English subjects; analyze the teaching purpose, content, and feasibility; and investigate the difficulties and needs of students in business English subject learning to determine the educational methods in a smart environment application in actual business English teaching. This article uses literature research method, questionnaire method, experimental research method, and interview method to conduct research. At the same time, this article also uses Maya and other software multidimensional design functions to explain the educational methods in a smart environment; set up a virtual hypothesis experiment to objectively analyze the development prospects of educational methods in an intelligent environment in business English teaching from the aspects of curriculum teaching, classroom effects, and learner efficiency; and summarize the parts that need improvement.
Influence of Urban Atmospheric Ecological Environment on the Development of Outdoor Sports
Authors: Xu Linqiang , Lyu Gia
Published: August 2022

In recent years, the process of urbanization in China has developed rapidly. However, many problems have also appeared, such as a rapid population increase, resource shortage, and deterioration of the ecological environment. The deterioration of the ecological environment has led to increased air pollution and noise pollution, threatening human health, and hindering outdoor sports. This paper takes a certain city outdoor sports venue as the research object and studies the influence of the urban atmospheric ecological environment on the development of outdoor sports through the method of questionnaire survey and mathematical statistics. The results show that the city’s air quality index in 2019 was “excellent” and “good” for a total of 240 days, the greening rate reached 35%, the noise decibels were between 38 dB and 67 dB, and the ecological environment was good. According to statistics, 5.8% of students, 24.23% of middle-aged people, and 37.24% of elderly people in the city who engaged in outdoor sports often experience physical discomfort. After launching outdoor sports in this atmospheric ecological environment, 49.84% of students, 44.59% of office workers, and 39.65% of elderly people feel that their body and mind have improved. A good urban ecological environment can improve the physical and mental health of outdoor sports personnel. Through outdoor sports, the physical and mental health of all sports groups in the ecological environment has been improved. According to the location of this study, the subjects generally said that in the good atmospheric ecological environment of the city, outdoor sports improved physical and mental health.
Some Novel Approaches for Analyzing the Unforced and Forced Duffing–Van der Pol Oscillators
Authors: Salas Alvaro H. , Albalawi Wedad , El-Tantawy S. A. , El-Sherif L. S.
Published: August 2022

In the current investigation, both unforced and forced Duffing–Van der Pol oscillator (DVdPV) oscillators with a strong nonlinearity and external periodic excitations are analyzed and investigated analytically and numerically using some new and improved approaches. The new approach is constructed based on Krylov–Bogoliubov–Metroolsky method (KBMM). One of the most important features of this approach is that we do not need to solve a system of differential equations, but only solve a system of algebraic equations. Moreover, the ease and faster of applying this method gives high‐accurate results and this approach is better than many approaches in the literature. This approach is applied for analyzing (un)forced DVdP oscillators. Also, some improvements are made to He’s frequency‐amplitude formulation in order to solve unforced DVdP oscillator to obtain high‐accurate results. Furthermore, the He’s homotopy perturbation method (He’s HPM) is employed for analyzing unforced DVdP oscillator. The comparison between all mentioned approaches is carried out. The application of our approach is not limited to (un)forced DVdPV oscillators only but can be applied to analyze many higher‐order nonlinearity oscillators for any odd power and it gives more accurate results than other approaches. Both used methods and obtained approximations will help many researchers in general and plasma physicists in particular in the interpretation of their results.
A Deep Learning Method for Intelligent Analysis of Sports Training Postures
Authors: Sun Yuqin , Li Youliang
Published: August 2022

With the further research of artificial intelligence technology, motion recognition technology is widely used in posture analysis of sports training. However, the interference of light, Angle, and distance in real life makes the existing model unable to focus on the expression of human movements. Aiming at the above problems, this paper proposes a motion training attitude analysis method based on a multiscale spatiotemporal graph convolution network. Firstly, the spatiotemporal image of the skeleton is constructed, and then the convolution operation is performed on the spatiotemporal image of the skeleton. Finally, the convolution results are linearly weighted and fused to capture the characteristics of action types with different time lengths. At the same time, the algorithm increases the processing of some important information loss and increases the randomness of the data set. Experimental results show that the proposed algorithm can adapt to the behavior changes of different complexity, and the model performance and recognition accuracy are significantly improved.
Three-Dimensional Dynamic Visualization Simulation of Underground Mining Engineering considering Chaos Optimization of Symmetric Varieties
Authors: Lu Guozhi , Wang Rui , Li Qianshun , Hu Fei
Published: August 2022

Aiming at the complex situation of mine underground engineering, this paper is chaos optimization to design 3D visualization simulation system of mine underground engineering, especially to satisfy the basic functions of 3D dynamic system and chaos optimization algorithm. A symmetric manifold algorithm is adopted. Explanations, transformation methods, and projective transformation methods and optical processing and conventional vector calculation techniques are used for analyzing underground mining engineering cases; it can be seen as follows: chaos-optimized symmetric variety algorithms in real life as an example. It can offer new ideas for optimizing the composition of underground mining engineering.
Kadsura coccinea Lignan Metabolism Based on Metabolome and Transcriptome Analysis
Authors: Liang Zhonghou , Li Xiang , Li Ping , Deng Ye , Zhong Yuan , Yang Hua
Published: August 2022

Kadsura coccinea is an important resource of traditional Chinese medicine. We find out the gene information of enzymes related to lignan biosynthesis and metabolism of Kadsura coccinea, so as to provide a scientific basis for the breeding of new varieties of Kadsura coccinea. In this paper, 2-year-old Kadsura coccinea from Hunan Kadsura coccinea provincial germplasm resource bank was used as the material and its root, stem, and leaf were analyzed by extensive targeted metabolomics combined with transcriptome sequencing. The results showed the following: (1) 51 lignans were detected by metabolome analysis, and the content of lignans in roots was higher than that in stems and leaves. The high content of lignans in roots, stems, and leaves includes ring-opening isolarch phenol-4-o-glucoside, narrow leaf schisandrin E, and schisandrin B. (2) After transcriptome sequencing, 13 classes of 137 Unigenes related to lignan biosynthesis pathway were retrieved. The analysis of differential genes in different parts showed that the overall expression amount and species of Kadsura coccinea lignan synthase gene in stems and leaves were closer than those in roots. CCoAOMT, C3H, and SIDR gene families are mainly expressed in roots and stems. (3) Metabolome combined with transcriptome analysis further screened these genes and obtained 11 genes of enzyme gene families such as HCT, DIR, COMT, CAD, SIDR, and PLR, which are highly correlated in lignan synthesis. Therefore, there are many lignans and their synthase-related genes in Kadsura coccinea roots, stems, and leaves, but the content and expression of different lignans and their synthase-related genes are quite different in each part. In this study, the gene information of the Kadsura coccinea lignan biosynthesis enzyme was obtained for the first time, which laid a good foundation for the cloning and molecular breeding of the key enzyme gene of lignan biosynthesis.
Optimization of Entrepreneurship Education for College Students Based on Improved Random Forest Algorithm
Authors: Jia Dongfeng , Zhao Hui
Published: August 2022

As we all know, the random forest algorithm has the advantages of high classification intensity and wide application range. Nevertheless, it still has a lot of room for improvement. This paper introduces the basic idea and working principle of classification algorithm and random forest algorithm, so this paper proposes some improved algorithms on the basis of all current research studies. College students, as the most innovative and adaptable group, have gradually become a development direction of China’s education reform to cultivate their innovative employment ability and develop innovative employment education. By constructing a model of the relationship between innovation and entrepreneurship education and college students’ employability, this paper examines the impact of innovation and entrepreneurship education mode on college students’ employment and entrepreneurship. At the same time, the model is tested by improving the random forest algorithm. The process of talent quality evaluation is to select talents with the best comprehensive quality based on various indicators of students’ performance in school, which can be regarded as a classification problem of unbalanced data sets. The improved random forest algorithm proposed in this paper has little difference in precision and recall rate when it is used for talent training evaluation but has a certain degree of improvement in accuracy rate, which meets the design requirements.
Drought Assessment Based on Data Fusion and Deep Learning
Authors: Li Yanling , Wang Bingyu , Gong Yajie
Published: August 2022

Drought is a major factor affecting the sustainable development of society and the economy. Research on drought assessment is of great significance for formulating drought emergency policies and drought risk early warning and enhancing the ability to withstand drought risks. Taking the Yellow River Basin as the object, this paper utilizes data fusion, copula function, entropy theory, and deep learning, fuses the features of meteorological drought and hydrological drought into a drought assessment index, and establishes a long short-term memory (LSTM) network for drought assessment, based on deep learning theory. The results show that (1) after extracting the features of meteorological drought and hydrological drought, the drought convergence index (DCI) built on the fused features by copula function can accurately reflect the start and duration of the drought; (2) the drought assessment indices were effectively screened by judging the causality of the drought system, using the transfer entropy; (3) drawing on the idea of deep learning, LSTM for drought assessment, which was established on DCI and the drought assessment factors, can accurately assess the drought risks of the Yellow River Basin.
Lung X-Ray Image Segmentation Using Heuristic Red Fox Optimization Algorithm
Authors: Jaszcz Antoni , Połap Dawid , Damaševičius Robertas
Published: August 2022

Medical image segmentation identifies an area that should be analyzed later in the processing process, such as for disease recognition and classification. As the image search area is reduced, this action allows for faster computation and analysis. We propose the use of a heuristic red fox heuristic optimization algorithm (RFOA) for medical image segmentation in this paper. The heuristics’ operation was adapted to the analysis of two-dimensional images, with a focus on equation modification and the novel fitness function. The proposed solution analyzes the image by converting the selected pixels to one of two color variants, black or white, based on the threshold value used. Their number is counted, allowing analysis of the chosen threshold. As a result, such analysis results in the automatic selection of the segmentation threshold parameter. Our method propose a new fitness function and the adjustment of RFOA to image analysis. We used a publicly available database of lung X-ray images for evaluation, and based on the results, an accuracy analysis was performed, as well as a discussion of the benefits and drawbacks is presented.
Novel Numerical Estimates of the Pneumonia and Meningitis Epidemic Model via the Nonsingular Kernel with Optimal Analysis
Authors: Rashid Saima , Kanwal Bushra , Ahmad Abdulaziz Garba , Bonyah Ebenezer , Elagan S.K.
Published: August 2022

In this article, we investigated a deterministic model of pneumonia‐meningitis coinfection. Employing the Atangana–Baleanu fractional derivative operator in the Caputo framework, we analyze a seven‐component approach based on ordinary differential equations (DEs). Furthermore, the invariant domain, disease‐free as well as endemic equilibria, and the validity of the model’s potential results are all investigated. According to controller design evaluation and modelling, the modulation technique devised is effective in diminishing the proportion of incidences in various compartments. A fundamental reproducing value is generated by exploiting the next generation matrix to assess the properties of the equilibrium. The system’s reliability is further evaluated. Sensitivity analysis is used to classify the impact of each component on the spread or prevention of illness. Using simulation studies, the impacts of providing therapy have been determined. Additionally, modelling the appropriate configuration demonstrated that lowering the fractional order from 1 necessitates a rapid initiation of the specified control technique at the largest intensity achievable and retaining it for the bulk of the pandemic’s duration.
Construction of Competitive Advantage and Competitive Strategy Model of Sports Enterprises Based on Multicase Study and In-Depth Learning
Authors: Hou Yunyun , Dong Xiaoyan
Published: August 2022

Summary. With the support of national policies and the holding of the 2022 Beijing Winter Olympic Games, China’s sports market presents an unprecedented prosperity, but it also faces many challenges. The market environment in which the sports industry is located is full of uncertainty and complexity. Creative products, competitive sports enterprises, and clear business models are urgently needed. Research purpose. To explore the future development mode and the prospect of China’s sports undertakings and enterprises through the analysis and research on the competitive advantage of China’s sports industry. In this context, since 2016, this study has started with the micromarket players. Research methods. Using the case study method highly praised by the international economic management academic circles, combined with in-depth learning, this study has conducted a systematic and comprehensive study on a total of 50 Chinese sports enterprises by mining and analyzing the unstructured text, video, and other data obtained from public materials and interviews. This paper deeply analyzes the competitive strategy of China's sports enterprises, creates and maintains competitive advantages in the sports industry, and studies the model construction of case studies and analysis. Conclusion. The study found that the product and business model, the leadership of managers, the innovation ability of teams, and the external market environment are the core elements for sports enterprises to formulate competitive strategies and create and maintain competitive advantages. The organic combination of the four eventually forms a competitive advantage that is difficult to replicate and finally forms a value chain through the implementation of competitive strategies so as to realize the value promotion and sustainable development of enterprises.
Levels of Biochar and NPS Fertilizer Rates on Growth, Yield Component, and Yield of Maize (Zea mays L.) at Guto Gida, Western Ethiopia
Authors: Tufa Abdela , Hunduma Adugna , Hasan Mohammad Najmus Saquib , Asefa Fayera , Nandeshwar B. C.
Published: August 2022

Mixed application of organic and inorganic fertilizers in mixture improves soil fertility and crop productivity. However, the identification of combined application level is important. Therefore, a field experiment was conducted in 2020 in the Guto Gida district to assess the effect of maize cob biochar levels and inorganic NPS fertilizer rates on the growth and yield of maize. The study was conducted in factorial combinations of five rates of maize cob biochar and three rates of inorganic NPS fertilizer using a randomized complete block design with three replications. The main effect of the biochar level and NPS rate significantly affected crop phenology and biomass yield, whereas the number of kernels ear−1 was affected by the main effect of NPS rate. The combined application of biochar and NPS fertilizer significantly influenced plant height, leaf area index, ear weight, thousand kernel weight, grain yield, and percentage of grain yield. The interaction of biochar at 8 t·ha−1 with 100 kg·ha−1 NPS resulted in highest leaf area index (5.56), grain yield (7.03 t·ha−1), and yield increment (18.11%) followed by 8 t·ha−1  × 50 kg·ha−1 and all biochar levels with 100 kg·ha−1 NPS. In addition, the highest values of ear weight (276 g) and thousand kernel weight (47.81 g) were recorded in plots treated with combined application of biochar and NPS fertilizer at rates of 8 t·ha−1 × 50 kg·ha−1 and 4 t·ha−1 × 100 kg·ha−1, respectively, whereas plots not treated with both biochar and NPS resulted in lowest yield followed by 0 t·ha−1 × 50 kg·ha−1. In conclusion, integrated application of maize cob biochar at 8 t·ha−1 with NPS fertilizer at 50 kg·ha−1 improved the yield of maize by about 16.85% with net benefit of 61700.50 ETB ha−1 and marginal rate of return 733.68%, and therefore, the application of biochar at this rate with mineral NPS fertilizer at 50 kg·ha−1 is considered as suitable for the study area.
Stability Analysis of Blasting Excavation for High Rock Slope of Highway Reconstruction and Expansion
Authors: Zhao Ruixin , Feng Zhongju , Huo Jianwei , Jiang Guan , Wang Fuchun
Published: August 2022

To analyze the stability of high rock slopes under millisecond blasting in the paper, time‐history curves of millisecond blasting dynamic loads are established based on field data from the reconstruction and extension project of the Beijing‐Shanghai Highway. Numerical simulations and field monitoring data are used to study the dynamic response characteristics of the slope stress, displacement, velocity, and safety factor at different times. The results show that the local shear stress near the blasting area is greater than the shear strength of the rock mass, which has a good effect on precracking. Additionally, the peak vibration law of the particles near the blasting area is found to change synchronously with the application of the dynamic blast load; as the distance increases, the law gradually weakens and peak vibration occurs only near the maximum value. Moreover, the safety factor of the slope exhibits a decreasing periodic variation. When the dynamic blast load F reaches the maximum load Fmax and 0.6 Fmax, the corresponding safety factor reaches the minimum load.
Cloud Platform Credibility Assessment System Based on D-S Theory and Blockchain Technology
Authors: Yang Ming , Jia Li , Gao Tilei , He Yuanyuan , Gui Bin , Zhang Tao
Published: August 2022

Even well-known cloud platforms will have sudden credibility problems in the long-term application process. Effectively evaluating the credibility of the cloud platform and providing users with scientific evaluation results can help users reasonably choose a trusted cloud platform. However, there are often conflicting opinions or malicious assessments in the process of assessment. In addition, the personal privacy information of the users participating in the assessment is at risk of being leaked, and the data that the users have evaluated is also easy to be modified. In order to solve the above problems, this paper defines the credibility category and confidence interval of cloud platform, puts forward a quantitative assessment method combined with fuzzy theory, and realizes the fusion of different users’ assessment results based on D-S theory. On this basis, this paper further proposes an effective cloud platform credibility assessment system combined with blockchain technology. Finally, through experimental analysis, this paper shows that the credibility assessment system proposed in this paper is feasible and illustrates the characteristics of the system through method comparison. The system solves the problem of conflicting information in the assessment process, can effectively assess the credibility of the cloud platform, and effectively protects user privacy and the security of assessment data with blockchain technology.
Comprehensive Analysis of Histone Modifications in Hepatocellular Carcinoma Reveals Different Subtypes and Key Prognostic Models
Authors: Li Huikai , Mu Han , Xiao Yajie , Zhao Zhikun , Cui Xiaoli , Wu Dongfang
Published: August 2022

Histone modification, an important epigenetic mechanism, is related to the carcinogenesis of hepatocellular carcinoma (HCC). In three datasets, we screened 88 epigenetic-dysregulated PCGs (epi-PCGs) , which were significantly associated with HCC survival and could cluster HCC into three molecular subtypes. These subtypes were associated with prognosis, immunomodulatory alterations, and response to different treatment strategies. Based on 88 epi-PCGs in the TCGA training set, a risk prediction model composed of 4 epi-PCGs was established. The model was closely related to the clinicopathological features and showed a strong predictive ability in different clinical subgroups. In addition, the risk prediction model was an independent prognostic factor for patients with HCC. The significance of epi-PCGs in HCC is revealed by our data analysis.
Application of Laser Raman Spectroscopy of Ferroelectric Nanomaterial BaTiO3 in the Design of Color Spotlight Products on Stage
Authors: Gu Yan , Wang Qi
Published: August 2022

With the improvement of people’s material requirements, the demand for lighting materials is higher and higher. This study mainly discusses the application of the laser Raman spectroscopy of ferroelectric nanomaterial BaTiO3 in the design of color spotlight products on the stage. Firstly, the effects of different electrospinning parameters on BaTiO3 nanofibers were studied. Then, the samples were spun under the best spinning parameters and annealed at 600°C, 650°C, 700°C, and 750°C, and then the phase structure, morphology, and piezoelectric properties of the samples at four different annealing temperatures were characterized. In this study, the laser Raman signal converges to the incident slit of the monochromator through the lens. After grating splitting, the signal is obtained through CCD. Finally, the spectral curve is recorded by the computer-controlled data acquisition software winspec/32 and saved as an .spe file. The spectral data to be processed need to be smoothed. The luminescence intensity of BaTiO3 with flower structure is weak, which is mainly caused by the different crystal forms of the matrix. By analyzing the content of each element, it is found that BA/Ti = 1/2, and it can be inferred that the proportion of BaTiO3 and TiO2 is about 6%. The XRD spectra of the samples obtained at different temperatures (−25, 0, 30, 50, and 70°C) corresponded to the standard card BaTiO3 one-to-one, and no impurity peaks were found, indicating that the obtained samples are pure phases. This research will promote the application of nanomaterials in color spotlight products.
The Impact of Integrated Development of Agriculture and Tourism on Rural Ecological Environment Quality
Authors: Wang Jingjing , Zhou Faming , Xie Ailiang
Published: August 2022

The integrated development of agriculture and tourism plays an important role on the rural ecological environment, which has not absorbed attention of the academic community. From the perspective of stakeholders, the impact mechanism of the agriculture and tourism integration on rural ecological environmental quality was analyzed. Based on three dimension-agricultural production environment, rural living environment, and rural environmental governance, the evaluation index system of rural ecological environment quality was constructed, and the multi-index comprehensive evaluation method was used to measure its level. The coupled system model of physics and entropy method were used to measure the degree of the integrated development level of agriculture and tourism industry. Based on data of 19 provinces in the Yangtze River Economic Belt and Yellow River Economic Belt in China from 2007 to 2019, static and dynamic panel models were used to examine the impact of agriculture and tourism integration on the quality of rural ecological environment and its mechanism. The results show that the integrated development of agriculture and tourism has a significant positive correlation with the quality of rural ecological environment, so the integrated development of agriculture and tourism can play a positive role in improving the quality of rural ecological environment. The rural ecological environment quality of the last period has a significant impact on the rural ecological environment quality of the current period, which indicates that the rural ecological environment quality has a strong inertia. Under the background of the current ecological civilization construction in China, the research result has significant theoretical and practical value.
An Image Deblurring Method Using Improved U-Net Model
Authors: Lian Zuozheng , Wang Haizhen , Zhang Qianjun
Published: August 2022

Deblurring methods in dynamic scenes are a challenging problem. Recently, significant progress has been made for image deblurring methods based on deep learning. However, these methods usually stack ordinary convolutional layers or increase convolution kernel size, resulting in limited receptive fields, an unsatisfying deblurring effect, and a heavy computational burden. Therefore, we propose an improved U-Net (U-shaped Convolutional Neural Network) model to restore the blurred images. We first design the model structure, which mainly includes depth-wise separable convolution, residual depth-wise separable convolution, wavelet transform, inverse wavelet transform, and a DMRFC (dense multireceptive field channel) module. Next, a depth-wise separable convolution is designed, which reduces model calculations and the number of parameters when compared with the standard convolution. A residual depth-wise separable convolution is designed, which allows for propagation of detailed information from different layers when compared with standard convolution and a standard residual block. The wavelet transform realizes downsampling by separating the contextual and texture information of the image. It also reduces model training difficulty. The inverse wavelet transform realizes upsampling, which reduces the loss of image information. Finally, by combining an extensional receptive field and channel attention mechanism, a DMRFC module is proposed to extract detailed image information, which further improves the reconstructed image quality via inverse wavelet transform. Experiments on the public dataset GOPRO show that the image deblurring method in this paper has higher-quality visual effects, while the PSNR (peak signal-to-noise ratio) rises to 30.83 and SSIM (structural similarity) rises to 0.948. Fewer model parameters and a shorter recovery time are needed, which provides a more lightweight image deblurring method.
Multimedia System Design and Data Storage Optimization Based on Machine Learning Algorithm
Authors: Qi Weiqiang , Wang Hongkai , Chen Tong
Published: August 2022

With the advancement of science and technology, digital technology and Internet of Things network technology have been developed rapidly, and multimedia technology has also been widely used. Multimedia formats such as digital TV and elevator posters are shaking up traditional media. At the same time, many media operation models and multimedia technologies are combined to plan operational strategies, determine operational goals, and change the traditional media structure to achieve commercial profits and society benefit. However, due to limitations in the existing operating model or unreasonable technical solutions, it is not easy to maximize the value of multimedia technology. The XML-based database has been submitted, and it will carry out the business requirements of the transaction network and the business platform of the transaction network. Integrated management mechanism is analyzed and applied. The framework design includes parallel quota processing module, update processing module, result processing module, and storage library and database connection management module. The department runs multiple parts of the system together and completes the database. The development of cloud database is based on cloud computing. It can effectively fill the shortcomings and gaps of traditional database storage and processing, and it can also provide high-reciprocity databases to provide storage and management services. It has high reliability. Cloud servers use fair weighted rounding algorithms to achieve load balancing and use the in-memory database Redis to realize terminal data caching. After a comprehensive test of the system, the system can perform all functions normally, and it has good performance and stable operation.
An Orthogonal Matching Pursuit Variable Screening Algorithm for High-Dimensional Linear Regression Models
Authors: Xie Yanxi , Li Yuewen , Shi Victor , Lu Quan
Published: August 2022

Variable selection plays an important role in data mining. It is crucial to filter useful variables and extract useful information in a high-dimensional setup when the number of predictor variables

d

tends to be much larger than the sample size

n

. Statistical inferences can be more precise after irrelevant variables are moved out by the screening method. This article proposes an orthogonal matching pursuit algorithm for variable screening under the high-dimensional setup. The proposed orthogonal matching pursuit method demonstrates good performance in variable screening. In particular, if the dimension of the true model is finite, OMP might discover all relevant predictors within a finite number of steps. Throughout theoretical analysis and simulations, it is confirmed that the orthogonal matching pursuit algorithm can identify relevant predictors to ensure screening consistency in variable selection. Given the sure screening property, the BIC criterion can be used to practically select the best candidate from the models generated by the OMP algorithm. Compared with the traditional orthogonal matching pursuit method, the resulting model can improve prediction accuracy and reduce computational cost by screening out the relevant variables.
Application of Personal Information Privacy Protection Based on Machine Learning Algorithm
Authors: Lang Fang , Zhong Yunfei
Published: August 2022

Based on a machine learning algorithm, this paper deeply explores the privacy protection of personal information. In this paper, the definition of the machine learning algorithm is put forward, the design idea of privacy protection in joint machine learning platform is studied, and the architecture model and model parameter updating strategy of joint machine learning under privacy protection are designed. To protect the privacy of personal information, this paper also proposes a data homomorphic verification mechanism to prevent the global parameters from being tampered with by malicious cloud servers. In order to verify the performance of the models constructed in this paper, the comparative experiments of different models are carried out. The experimental results show that this algorithm has a fast convergence speed, and the average error rate decreases by 4.17% compared with the traditional algorithm. Moreover, the accuracy of this algorithm reaches 95.37%, which is about 8.76% higher than the previous algorithm. This model is applied to the field of personal information privacy protection, which can provide a safe and reliable environment for personal information privacy and effectively protect the privacy of data owners. And, means and reference value is provided for the development direction of privacy protection.
Internet+ and Smart Wearable Devices for Three-Dimensional Monitoring of Tennis Physical Exercise
Authors: Li Zhenzhong , Li Fen
Published: August 2022

“Internet+” is developing rapidly, and smart wearable technology has gradually advanced, with the support of two major technologies. This paper realizes the conception of three-dimensional monitoring of tennis physical exercise based on two major technologies. This paper firstly organizes and analyzes the research results of scholars on Internet+, smart wearable devices, tennis physical exercise, and three-dimensional monitoring concepts. It summarizes the experience and realizes the construction of this research system. Then, the meaning and characteristics of Internet+, the definition, classification, and future development of smart wearable devices are outlined. In addition, the structure of the three-dimensional monitoring system is expounded, and then, the feasibility of this research is proved by examples and data. Finally, the problems encountered in this research process are discussed, and the experimental process of three-dimensional monitoring is summarized. The survey shows that 216 people in the city feel very comfortable with the bracelet experience, and 393 people have a good experience overall, reaching more than 93% of the surveyed number.