bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of Agricultural Product Information Traceability and Customer Preference Based on Blockchain
Authors: Lin Xiuli
Published: June 2022

For traditional agricultural product traceability system, there are some problems, such as information asymmetry and serious centralized storage. To solve the problems, a set of an agricultural product traceability information analysis system based on blockchain is designed. The overall framework of the agricultural product information traceability system is built, and the traceability model and process are designed in detail from the data layer, consensus layer, and contract layer. Collaborative verification function modules are added in the data layer to ensure the authenticity of data on the blockchain. The integral penalty mechanism is introduced to improve the practical Byzantine fault tolerance algorithm (PBFT), which ensures the security of the block network and the validity of data. Smart contracts are adopted to ensure that changes in agricultural information are actually recorded on blockchain. The results show that the designed blockchain-based agricultural product information traceability system solves the problem of difficult sharing and traceability of agricultural product information, which realizes the traceability of agricultural product production information, processing information, transportation information, and transaction query information, and has certain theoretical and practical value for the information traceability of agricultural products and other products.
Study on the Floating of Large Diameter Underwater Shield Tunnel Caused by Synchronous Grouting
Authors: Liang Yu , Huang Xumin , Gao Shijun , Yin Yihao
Published: June 2022

Synchronous grouting is the key factor causing segment floating during the construction of shield tunnel, especially the grout ratio and the control of the grouting pressure. In this paper, the ratio of grout material was optimized through multiple groups of physical and mechanical tests. The results showed that 0.3% content of water reducing agent in grout could improve the ability of water resistance significantly. 2.9% content of bentonite could reduce bleeding rate of grout and grout setting time and improve the fluidity in the meantime. Then, the distribution law of grout along the segment ring in the filling stage was studied based on a typical underwater tunnel in China. The results showed that the theoretical calculation of grouting pressure was between 0.15 MPa and 0.18 MPa, which were in good agreement with the measured data. The grouting pressure distribution is affected by four parts including the lateral earth pressure, foundation reaction, grout shear stress, and gravity.
Lactobacillus pentosus Alleviates Lipopolysaccharide-Induced Neuronal Pyroptosis via Promoting BIRC3-Mediated Inactivation of NLRC4
Authors: Hu Ming , Shao Zhongying
Published: June 2022

Objective. Neurodegenerative disease is a common neurodegenerative disorder. Lactobacillus pentosus (L. pentosus) plays a neuron-protective role. This study aimed to investigate the effects of L. pentosus on neurodegenerative diseases. Methods. Cells were treated with lipopolysaccharide (LPS) to establish neurodegenerative diseases model in vivo and with L. pentosus strain S-PT84. Reverse transcription-quantitative PCR (RT-qPCR) was applied to determine mRNA levels. Western blot was performed to detect protein expression. Cellular behaviors were detected using Cell Counting Kit-8 (CCK-8), flow cytometry, and TdT-mediated dUTP nick-end labeling (TUNEL) assay. The interaction between baculoviral IAP repeat containing 3 (BIRC3) and NLR family CARD domain containing 4 (NLRC4) was predicted by STING and verified by western blot. Result. L. pentosus suppressed LPS-induced pyroptosis and promoted the cell viability of neurons. Additionally, L. pentosus suppressed the release of proinflammatory cytokines (interleukin 1 beta (IL-1β) and IL-18) and the protein expression of pyroptosis biomarkers (cleaved caspase1 (CL-CASP1) and N-terminal fragment gasdermin D (GSDMD-N)). Moreover, L. pentosus upregulated BIRC3, which induced the inactivation of NLRC4. However, BIRC3 knockdown alleviated the effects of L. pentosus and induced neuronal degeneration. Conclusion. L. pentosus may play a neuron-protective role via regulating BIRC3/NLRC4 signaling pathways. Therefore, L. pentosus may be a promising strategy for neurodegenerative diseases.
An Innovative Sensing Machine Learning Technique to Detect Credit Card Frauds in Wireless Communications
Authors: Sasikala G. , Laavanya M. , Sathyasri B. , Supraja C. , Mahalakshmi V. , Mole S. S. Sreeja , Mulerikkal Jaison , Chidambaranathan S. , Arvind C. , Srihari K. , Dejene Minilu
Published: June 2022

There has been an increase in credit card fraud as e-commerce has become more widespread. Financial transactions are essential to our economy, so detecting bank fraud is essential. Experiments on automated and real-time fraud detection are needed here. There are numerous machine learning techniques for identifying credit card fraud, and the most prevalent are support vector machine (SVM), logic regression, and random forest. When models penalise all errors equally during training, the quality of these detection approaches becomes crucial. This paper uses an innovative sensing method to judge the classification algorithm by considering the misclassification cost and at the same time by employing SVM hyperparameter optimization using grid search cross-validation and separating the hyperplane using the theory of reproducing kernels like linear, Gaussian, and polynomial, and the robustness is maintained. Because of this, credit card fraud has been identified significantly more successful than in the past.
Current Research on Complementary and Alternative Medicine in the Treatment of Premature Ovarian Failure: An Update Review
Authors: Li Yue , Yan Meng-Yu , Chen Qiao-Chu , Xie Ya-Ya , Li Chen-Yu , Han Feng-Juan
Published: June 2022

Complementary and alternative medicine (CAM) encompasses a wide range of different non-mainstream therapies that have been increasingly used for the treatment or adjunct treatment of various ailments, with premature ovarian failure (POF) being one of the most common conditions treated with CAM. This review updates the progress of CAM in the treatment of POF, and we focus specifically on reviewing the evidence for the efficacy and mechanisms of a range of CAM treatments in POF, including single herbal medicines and their active ingredients, compound Chinese medicines, acupuncture and moxibustion, psychotherapy, exercise, vitamins, massage, and dietary supplements. According to the literature, CAM is very helpful for improving POF symptoms, and we hope to provide some instructive suggestions for clinical treatment and experimental research in the future. However, more clinical trials are needed to prove the safety of CAM.
Analysis of College Art Teaching System under the Background of Video Big Data Technology
Authors: Duan Feifei , Lu Xiawei
Published: June 2022

Art teaching needs not only learning art knowledge but also a lot of practice and aesthetic appreciation. However, traditional teaching methods cannot provide students with a large number of relevant learning materials, which is not conducive to improving students’ classroom enthusiasm. This paper presents the design and implementation of college art teaching system based on video big data technology and combines video recommendation algorithm with the Django teaching video website. The system analyzes the preference needs according to the behavior data of students watching videos and recommends videos for students. At the same time, the system can also evaluate the quality of the video content according to the behavior of students watching videos, reverse classify the video, and then optimize the recommendation results. The video recommendation algorithm model based on user behavior is better than the traditional collaborative filtering recommendation algorithm and fully connected neural network collaborative filtering algorithm. It can reduce the range of users who need similarity calculation and improve the accuracy of recommendation algorithm. The experimental results show that the fully connected neural network collaborative filtering algorithm has good recommendation performance and stability, can reduce the computational complexity, and can improve the recommendation accuracy. The teaching technology integrated through the Internet can greatly improve students’ enthusiasm for art teaching.
Quantitative Analysis of the Teaching Effect of College English Courses Based on Multivariate Matrix Evaluation Model
Authors: Wang Xiaojing
Published: June 2022

In order to carry out a quantitative analysis of the teaching effect of college English courses based on multivariate matrix evaluation model, this paper takes as research objects 87-year 2020-enrolled undergraduate students from a university in Zhengzhou City, Henan Province, central China. On the basis of summarizing and analyzing previous research works, this study expounded the research status and significance of quantitative analysis of the teaching effect of college English courses, elaborated the development background, current status, and future challenges of multivariate matrix evaluation model, introduced the data source and the subjects, contents, and means of teaching effect quantification in this research, analyzed the feedback and guiding function of the teaching effect quantification result of college English courses, discussed the motivation and diagnosis function of the teaching effect quantification result of college English courses, conducted analyses of factors affecting the teaching effect quantification of college English courses, constructed the quantitative dimension of teaching effect of college English courses based on the multivariate matrix evaluation model, and finally designed the quantification system of teaching effect of college English courses based on the multivariate matrix evaluation model. The research results show that the quantitative analysis process of the teaching effect of college English courses has the characteristics of complex structure and many hierarchies, and there are also mutual influences and functions between its subsystems. In order to ensure the rationality and effectiveness of comprehensive quantification, the index system construction of the multivariate matrix evaluation model follows scientific, systematic, and focused principles. The teaching effect quantification process combines four influencing factors of perspective, content, mode, and method with the quantification standard, and constructs a hierarchical quantification structure with target layer, restriction factor layer, and restriction sub-factor layer. The tools it uses usually include observations, interviews, self-evaluation, mutual evaluation, student files, reading notes, project presentations, etc. Teachers adjust teaching goals and plans in time by observing the quantification results of students at all levels, which will help improve students’ enthusiasm for learning and give full play to students’ autonomy and initiative in English courses.
Peptidoglycan-Like Components in Z-100, Extracted from Mycobacterium tuberculosis Strain Aoyama B, Increase IL-12p40 via NOD2
Authors: Horii Takayuki , Orikawa Yuki , Ohira Yuta , Eta Runa , Tominaga Uiko , Sato Takanori , Tanaka Takao
Published: June 2022

Background. Z-100 is a hot-water extract of the human-type Mycobacterium tuberculosis strain Aoyama B. While Z-100’s macrophage-mediated immunomodulatory effects have been reported, the mechanistic details have not been fully clarified. Here, we studied the immunomodulatory effects of Z-100 on mouse bone marrow-derived cells, human CD14+ cells, and skin. Methods. Mouse bone marrow-derived cells and CD14+ cells were cultured in the presence of granulocyte-macrophage colony-stimulating factor, differentiated into macrophage-like cells, and then stimulated with Z-100. Furthermore, since Z-100 is subcutaneously administered clinically, we injected Z-100 into mice and measured gene expression in the skin. Results. While Z-100 stimulation increased the production of interleukin- (IL-) 12p40 and IL-1β in mouse bone marrow-derived macrophages, levels of IL-1β were low. In contrast, TNF-α production did not increase. Meanwhile, stimulation of human CD14+ cells with Z-100 increased production of IL-12p40, TNF-α, and IL-1β. Because Z-100 appeared to have the most stable effect on IL-12p40, we examined the components of Z-100 that induce IL-12p40 production. We found that Z-100 contained peptidoglycan-like components. In addition, an siRNA study showed that Z-100 increased the production of IL-12p40 via nucleotide-binding oligomerization domain 2 (NOD2). Further, subcutaneous administration of Z-100 to mice significantly elevated expression of IL-12p40 and IL-1β and showed a trend towards increasing TNF-α in the skin. Conclusion. Z-100 induced the production of immunomodulatory cytokines from various types of macrophages and specifically increased IL-12p40 production through peptidoglycan-like components via NOD2.
Analyzing Welding Performance of Metal Using Artificial Neural Network
Authors: Wu Xiaojun
Published: June 2022

In recent years, the speed of modernization construction in China has been exponentially growing. The trend of high parameters, large capacity, and large-scale development of the welding structure has been promoted. It needs higher requirements on the type and quality of the welding materials. Most of the welding materials are imported to China. The main reason is that China still follows the traditional design method. The quality of the welding materials is also low. The design of metal welding materials involves many factors and properties. There is no fixed-function relationship between the properties and components of the welding materials. This makes it difficult to design metal welding materials. The emergence of neural network algorithms provides a new way to analyze the weldability of metal materials. In this paper, BP (backpropagation) network is used to analyze the welding performance of metals. The tensile test of welded joints is carried out through training test samples. The results show that the tensile strength and yield strength of metal materials are about 500 MPa (megapascals) and 400 MPa, respectively. For further analysis of the influence of welding current, electrode pressure, and power-on time on the tensile and shear strength of metal materials, a shear test and tension test were used. With the increase of welding current, the shear strength of spot welding continuously increased. When the welding current was 10,000A (Ampere), the shear strength decreased rapidly from 24.25 MPa to 18.84 MPa. After prolonging the welding time, at first, both tensile strength and shear strength increase and then decrease. When the welding pressure increases from 32psi to 48psi, the tensile strength increases from 16.47 MPa to 24.52 MPa and then decreases continuously to 17.26 MPa, whereas the shear strength decreases first and then increases.
Interior Design Effectiveness Modelling for Public Buildings with BIM-Based Technology
Authors: Zhu Zhu
Published: June 2022

In recent years, with the continuous development of urbanisation, the proportion of interior design in public buildings has been increasing year by year. At the same time, there is a tendency in many places for the interior spaces of public buildings to be upscale and retro. This indicates that people are paying more and more attention to the spiritual aspect of their lives, in addition to the materialistic pursuit of enjoyment. The current phenomenon of overdecoration in society can lead to excessive luxury and wastefulness. In these wasteful interiors, the beauty of the building itself is lost. In addition, this type of interior design is not only expensive but also poses certain safety risks to some extent. In the modern society, public buildings are essential places for public activities. To be specific, they are closely linked to public services and social management attributes. As a result, public buildings usually play a decisive role in facilitating communication and cooperation between various persons. Thus, the construction requirements of public buildings are currently increasing and the structural shapes of buildings are becoming more complex. In addition, the level of technology and the use of public buildings are becoming increasingly demanding. As a result, it is quite important to examine how modern and emerging technologies can be applied to public building design in order to improve its effectiveness. At the same time, with the continuous and rapid development of China’s economy and the promotion of the concept of environmental protection, the greening of public buildings has become an object of concern and research. There are many different types of existing public buildings in China, and in the design process, the energy consumption of the building throughout its life cycle and its impact on the surrounding environment are not fully considered, resulting in problems such as high energy consumption and poor indoor comfort in the actual use of the building. However, the demolition and reconstruction of buildings can lead to waste of resources and environmental pollution. Therefore, it is feasible and necessary to study the application of green building technologies in the design of public buildings. This study models the effectiveness of public building interior design based on BIM technology from the perspective of integrated design as well as parametric design. This model enables the interior design of public buildings to become energy efficient, emission reducing, and environmentally sustainable. After all, the integration of architecture and interior design can reduce unnecessary decorative waste. In addition, this model can also respond to the government’s efforts to develop an ecological civilisation, creating a new way of living that is resource efficient.
Jinlian Xiaodu Decoction Protects against Bleomycin-Induced Pulmonary Fibrosis in Rats
Authors: Wu Zhiqiang , He Qin , Tao Feibao , Ye Xuxing , Wang Saibin , Zhu Yijun , Zhu Liang , Xu Bin
Published: June 2022

Background. Jinlian Xiaodu Decoction (JXD) was reported to have anti-inflammatory and lung protection effects. This study aimed to explore the role and mechanism of JXD on bleomycin (BLM)-induced pulmonary fibrosis (PF). Methods. The UHPLC-Q/TOF-MS system was applied to analyze JXD composition. The PF model was established by BLM intratracheal administration in Wistar rats. Subsequently, BLM-treated rats were intragastrically administered with dexamethasone (DXM, 1 g/kg/d) or JXD (3.5, 7 or 14 g/kg/d). Next, the lung coefficient was calculated; H&E, Masson, and TUNEL staining were used for lung morphological analysis and apoptosis assessment. Bronchoalveolar lavage fluid (BALF) biochemical analysis was conducted to count the inflammatory cell number. The expression of inflammatory factors mRNA in the lung tissue and BALF were measured by qRT-PCR. The content and activity of oxidative stress-related proteins were detected. The expression of PF-related, apoptosis-related, and TGF-β1 pathway-related protein were assessed by immunohistochemistry or Western blot. Results. Twenty-six compounds were identified from JXD in both negative and positive ion modes. In BLM-induced rats, JXD reduced the lung coefficient and alleviated PF injury. JXD decreased inflammatory cell count and TNF-α, IL-1β, IL-6, and MCP-1 content. Meanwhile, JXD blunted BLM-induced oxidative stress and a high level of HYP. Furthermore, TUNEL analysis found that JXD inhibited cell apoptosis and increased Bcl-2/Bax ratio in BLM-induced lung. Moreover, JXD relieved the role of BLM on α-SMA, TGF-β1, collagen I, fibronectin, E-cadherin protein expression, and the phosphorylation of Smad2/3 in PF rat. Conclusion. This study revealed the protective effect and possible element of JXD on BLM-caused PF.
Understanding How Product Reviews on YouTube Affect Consumers’ Purchase Behaviors in Indonesia: An Exploration Using the Stimulus-Organism-Response Paradigm
Authors: Huang Tsun-Yu , Chen Wen-Kuo , Chen Chien-Wen , Silalahi Andri Dayarana K.
Published: June 2022

Product reviews on YouTube have become highly beneficial to consumers’ decision-making, as they can help consumers judge and experience products before making purchases. Consequently, scholars and managers must understand consumer behaviors regarding product reviews and identify factors influencing consumers’ purchasing decisions. A novel contribution of the study is the introduction of a model based on the stimulus-organism-response paradigm that explains how sensory marketing and information adoption affect parasocial interaction, trust (cognitive and affective), and information usefulness that are correlated with consumers’ responses to stickiness, adoption, and purchase intentions. To empirically evaluate the proposed research model, we conducted an online survey of 611 participants who had purchased products based on YouTube product reviews. We performed data analysis using structural equation modelling and Smart-PLS software, and the results indicated that all hypotheses were supported except for parasocial interaction and information usefulness, which were rejected. This study could provide insights into the antecedents and consequences of purchase intentions in light of YouTube product reviews, thus contributing knowledge of online consumer behaviors to help managers understand consumer behaviors regarding social media and formulate marketing strategies.
Development of Water Culture Tourism of Mountain Ethnic Culture Based on 3D Image Technology
Authors: Guo Chuangle , Shi Xinlu
Published: June 2022

The study of human settlement environment, especially the complete study of human settlement environment in mountainous region, is a huge systematic project, which involves almost all aspects of human knowledge system at the semantic level. It is an important task to establish a systematic cognitive model of human settlement environment and carry out practical verification. In recent years, due to the rise of tourism real estate, mountain tourism real estate, as a type of tourism real estate, has attracted people’s attention, and its hidden economic, social, and ecological benefits make it develop rapidly. The purpose of this study is to improve the theoretical system of tourism real estate landscape planning and mountain landscape resource protection system with 3D image technology, which has important theoretical and practical significance for exploring the sustainable development method of mountain tourism real estate landscape. This study locates the research type of mountain tourism real estate, and it is the first time to study mountain tourism, explores the specific planning of mountain tourism real estate development measures, and preliminary establish the theoretical system of mountain tourism real estate development. It brings a new idea for the development of mountain tourism real estate and puts forward the direction and method of planning.
Assessment of Dynamic Swarm Heterogeneous Clustering in Cognitive Radio Sensor Networks
Authors: Bhatt Ruby , Onyema Edeh Michael , Almuzaini Khalid K. , Iwendi Celestine , Band Shahab S. , Sharma Tripti , Mosavi Amir
Published: June 2022

Many optimization algorithms have been created to determine the most energy-efficient transmission mode, allowing for lower power consumption during transmission over shorter distances while minimising interference from primary users (PUs). The improved cooperative clustering algorithm (ICCA) performs superior spectrum sensing across groups of multiusers compared to any other method currently available in terms of sensing inaccuracy, power savings, and convergence time than any other method currently available. The proposed ICCA algorithm is employed in this research study to find the optimal numbers of clusters based on its connectivity and the most energy-efficient distributed cluster-based sensing technique available. In this research, many randomly chosen secondary users (SUs) and primary users (PUs) are investigated for potential implementation opportunities. Therefore, as compared to the current optimization strategies, the proposed ICCA algorithm enhanced the convergence speed by integrating the multiuser clustered communication into a single communication channel. Experimental results revealed that the new ICCA algorithm reduced node power by 9.646 percent compared to traditional ways when comparing the novel algorithm to conventional approaches. In a similar vein, as compared to the prior methodologies, the ICCA algorithm reduced the average node power of SUs by 24.23 percent on average. When the SNR is decreased to values below 2 dB, the likelihood of detection improves dramatically, as seen in the figure. ICCA has a low false alarm rate when matched to other optimization algorithms for direct detection, and the proposed method outperforms them all. Following the findings of the simulations, the proposed ICCA technique effectively addresses multimodal optimization difficulties and optimizes network capacity performance in wireless networks. A detailed discussion of SS applications for the IoT and wireless sensor networks, both based on CR, is provided. There is also a thorough discussion of the most recent advancements in spectrum sensing as a facility. IoT or WSN may be essential in feeding the CR networks with spectrum sensing data and the future of spectrum sensing. The use of CR for fifth generation and afar its potential application in frequency allocation are discussed. To stay up with the advancement of communication technology, SS should give additional features to remain competitive, like the capacity to investigate various available channels and accessible places for transmission. Based on present and prospective methods in wireless communications, we highlight the crucial upcoming study paths and difficulty spots in signal processing for cognitive radio and potential solutions (SS-CR).
An Assessment and Analysis Model of Psychological Health of College Students Based on Convolutional Neural Networks
Authors: Li Panpan , Liang Feng
Published: June 2022

Psychological health assessment and psychological problem identification essentially belong to problems of pattern recognition or nonlinear classification; its system contains complex nonlinear interactions among various factors, having basic characteristics of multivariable, multilevel, and strong coupling. An important problem in the field of artificial intelligence solved by convolutional neural networks (CNN) is to simplify complex problems, minimize the number of parameters, and thus greatly improve the algorithm’s performance. Therefore, CNN has outstanding advantages in establishing the assessment and analysis model of college students’ psychological health. This study determined the psychological health standards of college students, selected measurement tools for college students’ psychological state, elaborated the principles of psychological assessment based on text information, performed the sample set data establishment and data processing of the assessment and analysis model of psychological health, conducted network establishment, training, and simulation, carried out a case experiment and its result analysis, explored the cause analysis of college students’ psychological health problems, and finally discussed the prevention and intervention of college students’ psychological problems. The study results show that the input and output of the CNN-based assessment and analysis model of college students’ psychological health are their evaluation data and assessment results, respectively, and the optimal hyperparameters of the model are determined through fold cross-validation analysis to improve the model’s over-fitting problem. After the training is completed, the model can predict the changes in college students’ psychological state in the future through the psychological test data. The CNN uses supervised machine learning method to construct an assessment and analysis model of college students’ psychological health, and establishes the mapping relationship between college students’ personal background and their psychological health. The network error continuously adjusts network connection weight according to gradient descent algorithm to minimize its error, so that the convolutional layer and the pooling layer can learn the optimized feature expression of the input data.
Study on Energy Distribution Law and Numerical Simulation of Mining Roadway Surrounding Rock
Authors: Zhang Guohua , Ju Chao , Duan Yanwei , Wang Yiwei , Qin Tao , Wu Chengjia
Published: June 2022

In underground engineering, the deformation and failure process of the surrounding rock of the roadway is always accompanied by the occurrence of energy. The study of the energy distribution law of the surrounding rock of the roadway plays an important role in its stability. This paper first theoretically analyzes the stress and energy distribution law of the surrounding rock of the roadway, then with the help of numerical simulation method, combined with the existing physical and mechanical parameters, based on the existing support parameters of Dongrong No. 2 Mine, gradually compares and analyzes the distribution of vertical stress and energy under the three support methods of no support, original support, and combined support, and the results found that the vertical stress distribution law under the three support methods is basically the same. High-stress areas appear on the two ribs of the roadway, and low-stress areas appear on the roof and floor. The range of high-stress areas from no support to combined support continues to decrease and becomes more evenly distributed. The energy distribution pattern is basically the same. The overall energy of the coal seam is high. There are high-energy areas at 2 m left and right of the roadway, and the roof and floor energy of the roadway is the smallest. The low energy area extends 5 m up and down, respectively. The range of high-energy areas from no support to combined support is shrinking, and the energy distribution is more uniform.
Risk Prediction Model of Enterprise Financial Data Based upon Sensor Signal Fusion
Authors: Jiang Hua
Published: June 2022

The prediction of financial distress has always been a topic of concern because it is very important to listed companies, stakeholders, and even a country’s economy. This research mainly discusses the risk prediction model of corporate financial data based on sensor signal fusion. This article analyzes the factors that affect financial risks through the study of related theories. Based on the design principles and qualitative analysis of the predictive index system, this paper constructs the financial risk prediction index system of listed companies from five aspects: profitability, solvency, asset management capability, operating capability, and growth capability. And it verifies the applicability of financial indicators through independent sample t-test. In order to effectively prevent the occurrence of corporate financial risks, this article takes listed companies as the research object. Starting from multiple angles that affect the occurrence of corporate financial risks, this article constructs a comprehensive and effective financial risk prediction index system for listed companies. And it uses sensor signal fusion algorithm to build an effective financial risk prediction model. Through this model, the enterprise's risk management ability can be effectively improved, the enterprise's risk prevention mechanism can be improved, and it can be successfully applied to the actual management of the enterprise, and the enterprise risk management mechanism can be enhanced. In general, the probability of making a type I error is slightly greater than the probability of making a type II error, but the misjudgment rate is below 25%, which is acceptable. This research provides scientific and effective guidance for corporate finance.
Dynamic Analysis of Multicenter Spatial Structure with Big Data in Smart City
Authors: Liu Juan
Published: June 2022

Based on dynamic big data, the multicenter spatial structure of cities is studied, which provides help for scientific planning of urban space and rational use of urban land. Firstly, the research background and significance of this topic is expounded in the Introduction, and then, the related concepts and theories, which lay a theoretical foundation for this research, are summarized. After that, the paper focuses on the design of the scheme of urban multicenter spatial structure and puts forward the method of multicenter identification, method of aggregation feature analysis, and method of spatial structure feature. Finally, the proposed scheme is verified by a case.
Regional Economic Upgrading and Development Based on Digital and Intelligent Innovation
Authors: Shang Rong , Sieng Lai Wei
Published: June 2022

In the development process of the social era at that time, the concept of regional economic upgrading and development was in a very important position. Realizing the conversion of old and new kinetic energy to promote high-quality economic development is the focus of economic work at present and in the future. This study mainly discusses the upgrading and development of regional economy based on digital and intelligent innovation. Through the analysis of the influencing factors of the total economic volume and its growth rate, this study has a preliminary understanding of the development advantages and disadvantages of each district, county, and city in the process of regional economic upgrading. Through the comprehensive evaluation of the regional economic development of the province, it can obtain the distribution of the development degree of each district, county, and city and the comprehensive competitiveness of the regional economy. To sum up, a quantitative analysis has been carried out on the status quo of the provincial regional economic development. It uses a grayscale prediction model to predict the future of digital economic development, intelligent innovation, and regional economic development. The grey prediction model is a prediction method that establishes a mathematical model to make predictions through a small amount of incomplete information. Based on the past and present development laws of objective things, it uses scientific methods to describe and analyze future development trends and conditions and form scientific assumptions and judgments. The study found that province A ranked first in the comprehensive index of digital economy development. With its superior geographical location, it has become the vanguard of reform and opening up. It has been committed to the construction of the national digital economy innovation and development pilot zone and has achieved remarkable results, increasing from 0.6302 in 2017 to 1.317 in 2021. It ranks second in the comprehensive development index of economic growth. Province A increased from 0.4501 in 2017 to 0.8177. Province B ranks second in terms of the comprehensive digital economy development index, increasing from 0.5504 in 2017 to 1.1340 in 2021. Province B, with strong economic strength and prosperous trade, ranked first in the composite economic growth index, increasing from 0.4527 in 2017 to 0.8514. The upgrading of regional economic structure is an important way to achieve high-quality economic development in the new era. In the process of upgrading the regional economic structure, there are changes in factor allocation, resource consumption intensity, input-output efficiency, and environmental quality, which have a certain impact on economic development. This research will help to promote the process of regional economic upgrading and development.
Targeting Therapeutic Resistance and Multinucleate Giant Cells in CCNE1-Amplified HR-Proficient Ovarian Cancer
Authors: Bai Shoumei , Taylor Sarah E. , Jamalruddin Mohd Azrin , McGonigal Stacy , Grimley Edward , Yang Dongli , Bernstein Kara A. , Buckanovich Ronald J.
Published: June 2022

Approximately 20% of high-grade serous ovarian cancers (HGSOC) have CCNE1 amplification. CCNE1-amplified tumors are homologous recombination (HR) proficient and resistant to standard therapies. Therapy resistance is associated with increased numbers of polyploid giant cancer cells (PGCC). We sought to identify new therapeutic approaches for patients with CCNE1-amplified tumors. Using TCGA data, we find that the mTOR, HR, and DNA checkpoint pathways are enriched in CCNE1-amplified ovarian cancers. Furthermore, Interactome Mapping Analysis linked the mTOR activity with upregulation of HR and DNA checkpoint pathways. Indeed, we find that mTOR inhibitors (mTORi) downregulate HR/checkpoint genes in CCNE1-amplified tumors. As CCNE1-amplified tumors are dependent on the HR pathway for viability, mTORi proved selectively effective in CCNE1-amplified tumors. Similarly, via downregulation of HR genes, mTORi increased CCNE1-amplifed HGSOC response to PARPi. In contrast, overexpression of HR/checkpoint proteins (RAD51 or ATR), induced resistance to mTORi. In vivo, mTORi alone potently reduced CCNE1-amplified tumor growth and the combination of mTORi and PARPi increased response and tumor eradication. Tumors treated with mTORi demonstrated a significant reduction in ALDH+ PGCCs. Finally, as a proof of principle, we identified three patients with CCNE1 amplified tumors who were treated with an mTORi. All three obtained clinical benefits from the therapy. Our studies and clinical experience indicate mTORi are a potential therapeutic approach for patients with CCNE1-amplified tumors.
Inhibition of Mtorc1/2 and DNA-PK via CC-115 Synergizes with Carboplatin and Paclitaxel in Lung Squamous Cell Carcinoma
Authors: Castellano Gina M. , Zeeshan Saman , Garbuzenko Olga B. , Sabaawy Hatim E. , Malhotra Jyoti , Minko Tamara , Pine Sharon R.
Published: June 2022

Only a small percentage (<1%) of patients with late-stage lung squamous cell carcinoma (LUSC) are eligible for targeted therapy. Because PI3K/AKT/mTOR signaling, particularly Phosphatidylinositol 3-kinase CA (PIK3CA), is dysregulated in two-thirds of LUSC, and DNA damage response pathways are enriched in LUSC, we tested whether CC-115, a dual mTORC1/2 and DNA-PK inhibitor, sensitizes LUSC to chemotherapy. We demonstrate that CC-115 synergizes with carboplatin in six of 14 NSCLC cell lines, primarily PIK3CA-mutant LUSC. Synergy was more common in cell lines that had decreased basal levels of activated AKT and DNA-PK, evidenced by reduced P-S473-AKT, P-Th308-AKT, and P-S2056-DNA-PKcs. CC-115 sensitized LUSC to carboplatin by inhibiting chemotherapy-induced AKT activation and maintaining apoptosis, particularly in PIK3CA-mutant cells lacking wild-type (WT) TP53. In addition, pathway analysis revealed that enrichments in the IFNα and IFNγ pathways were significantly associated with synergy. In multiple LUSC patient-derived xenograft and cell line tumor models, CC-115 plus platinum-based doublet chemotherapy significantly inhibited tumor growth and increased overall survival as compared with either treatment alone at clinically relevant dosing schedules. IHC and immunoblot analysis of CC-115–treated tumors demonstrated decreased P-Th308-AKT, P-S473-AKT, P-S235/236-S6, and P-S2056-DNA-PKcs, showing direct pharmacodynamic evidence of inhibited PI3K/AKT/mTOR signaling cascades. Because PI3K pathway and DNA-PK inhibitors have shown toxicity in clinical trials, we assessed toxicity by examining weight and numerous organs in PRKDC-WT mice, which demonstrated that the combination treatment does not exacerbate the clinically accepted side effects of standard-of-care chemotherapy. This preclinical study provides strong support for the further investigation of CC-115 plus chemotherapy in LUSC.
Necessity of Intraoperative Level IIA Lymph Node Dissection in Patients with Carotid Body Tumors: A Retrospective Study of 126 Cases
Authors: Ma Heng , Wei Minghui , Wang Xiaolei , Bahetibieke Huerman , Liu Wan , Wang Xiaoliang , Zeng Jiaomei
Published: June 2022

Background: Carotid body tumors (CBTs) are relatively uncommon neoplasms that rarely have malignant potential. However, malignant CBTs (MCBTs) are still associated with a poor prognosis and the treatment is still challenging clinically. Therefore, we evaluated the necessity of intraoperative level IIA lymph node dissection in patients with CBT. Methods: The clinical characteristics, intraoperative details, and pathological diagnosis of 126 CBT patients who had undergone surgery were retrospectively reviewed. The patients were divided into 2 groups according to whether level IIA lymph node dissection was performed. The prognosis was analyzed using Kaplan-Meier curves and Cox model multivariate survival analysis. Results: Among the 126 patients, 7 patients (10.3%) in the selective lymph node dissection (SLND) group (68 patients) were diagnosed with MCBTs with evidence of lymph node metastasis. Two patients (3.4%) in the lymph node nondissection (LNND) group (58 patients) were diagnosed with MCBTs later after the second operation because they could not be diagnosed as malignant initially because of the lack of lymph node pathology results although the pathology of the primary lesion showed features of malignancy. The SLND group had a significantly higher relapse-free survival rate than the LNND group (94.1% vs. 79.3%, p = 0.021). Patients with a confirmed diagnosis had a better prognosis than those with insufficient evidence of a malignancy due to the lack of lymph node information. Twenty-nine patients in the SLND group and 26 patients in the LNND group had postoperative nerve injuries, with no significant difference between the groups (p = 0.879). Conclusion: Intraoperative dissection of level IIA lymph nodes around the tumor in CBT patients can help improve the diagnosis and prognosis of MCBTs without causing additional cranial nerve injury.
Niti-S Esophageal Mega-Stent: An Emerging Endoscopic Tool with Different Applications in the Management of Surgical Anastomotic Leaks
Authors: Brito Mariana , Nunes Gonçalo , Luz Carlos , Oliveira Gabriel , Pinto Marques Pedro , Fonseca Jorge
Published: June 2022

Introduction: Anastomotic leak (AL) is a dangerous complication in the early postoperative period after total gastrectomy or esophagectomy being associated with high mortality. Self-expandable metal stents (SEMS) play a significant role in AL management. Only one case report described the use of Mega-Stent in AL setting. The authors report a two-case series with different applications of a Niti-S esophageal Mega-Stent in AL management. Case Report: Case 1 is a 67-year-old male who underwent an esophagectomy due to a squamous cell carcinoma of the distal esophagus. The early postoperative period was complicated with AL and gastropleural fistula. Initially, an OTSC was deployed in the dehiscence but failed to resolve AL. The esophageal Mega-Stent was further placed in-between the esophagus and the bulbus. Post-stenting contrast studies confirmed no further AL.Case 2 is an 86-year-old woman who underwent total gastrectomy with roux-en-y esophagojejunostomy due to a gastric adenocarcinoma, complicated with AL. A partially covered metal stent (PCMS) was placed to cover the anastomosis. Computed tomography confirmed leakage persistence and a second PCMS was deployed, resolving the AL. Several weeks later, both PCMSs presented ingrowth from granulation tissue. An esophageal Mega-Stent was placed (stent-in-stent technique) and 2 weeks later, all stents were removed, with no AL recurrence. Discussion/Conclusion: SEMS placement for AL is a safe, well-established therapeutic technique. Limitations include stent migration and incomplete cover of large AL. Mega-Stent can be an emerging tool for endoscopic AL management.
The Impact of Donor Risk Index, Recipients’ and Operative Characteristics on Post Liver Transplant One-Year Graft Failure: A Cohort Analysis
Authors: Cardoso Filipe S. , Bagulho Luis , Coelho João S. , Lamelas Jorge , Mateus Élia , Mendes Milena , Glória Helena , Ribeiro Vasco , Mega Raquel , Pena Ana , Marques Hugo P. , Germano Nuno , Nolasco Fernando , Perdigoto Rui , Martins Américo
Published: June 2022

Background and Aims: The donor risk index (DRI) quantifies donor-related characteristics potentially associated with increased risk of early graft failure. We aimed to assess the impact of the DRI, recipient and perioperative factors on post liver transplant (LT) outcomes. Methods: This was a single-center retrospective cohort study including all adult (≥18 years) patients who underwent LT from 01/2019 to 12/2019 at Curry Cabral Hospital, Lisbon, Portugal. Primary endpoint was 1-year graft failure post LT. Associations were studied with logistic regression. Results: A total of 131 cadaveric donor LT procedures were performed in 116 recipients. Recipients’ median (IQR) age was 57 (47–64) years and 101/131 (77.1%) were males. Cirrhosis was the underlying etiology in 95/131 (81.2%) transplants. Based on 8 predefined donors’ characteristics, median (IQR) DRI was 1.96 (1.67–2.16). Following adjustment for MELDNa score pre LT and SOFA score (adjusted odds ratio [aOR], 95% confidence interval [CI] = 0.91 [0.56–1.47]) or lactate (aOR [95% CI] = 2.76 [0.71–10.7]) upon intensive care unit (ICU) admission post LT, DRI was not associated with 1-year graft failure. However, higher SOFA score (aOR [95% CI] = 1.20 [1.05–1.37]) or lactate (aOR [95% CI] = 1.27 [1.10–1.46]) upon ICU admission post LT were independently associated with higher odds of 1-year graft failure. Conclusions: In a recent cohort of patients who underwent LT, DRI, despite being high, was not associated with 1-year graft failure, but SOFA score or lactate upon ICU admission post LT were.
Incentivizing Demand for Supply-Constrained Care: Institutional Birth in India
Authors: Andrew Alison , Vera-Hernández Marcos
Published: June 2022

If overcrowding harms health care quality, the impacts of encouraging more people to use services are not obvious. Impacts will depend on whether marginal entrants benefit and whether they benefit enough to offset the congestion externalities imposed on inframarginal users. We develop a general-equilibrium model that formalizes these ideas. We examine them empirically by studying JSY, a program in India that paid women to give birth in medical facilities. We find evidence that JSY increased perinatal mortality in areas with low health-system capacity, was particularly harmful in more-complex births, reduced the quality of facilities' postnatal care, and generated harmful spillovers onto other services.
Moved to Vote: The Long-Run Effects of Neighborhoods on Political Participation
Authors: Chyn Eric , Haggag Kareem
Published: June 2022

How does one's childhood neighborhood shape political engagement later in life? We study voting rates of children who were displaced by public housing demolitions and moved to higher opportunity areas using housing vouchers. Those displaced during childhood had 11% (2 pp) higher participation in the 2016 Presidential election and were 10% (2.9 pp) more likely to vote in any general election. We argue that the results are unlikely to be driven by changes in incarceration or parental outcomes but rather by political socialization or improvements in education and earnings. These results suggest that housing assistance programs may reduce inequality in political participation.