bluuebunny/crossref_metadata_2025 huggingface dataset:
Understanding Open Collaboration of Wikipedia Good Articles with Factor Analysis
Authors: Chou Huichen , Lin Donghui , Ishida Toru
Published: May 2022

This research aims at understanding the open collaboration involved in producing Wikipedia Good Articles (GA). To achieve this goal, it is necessary to analyse who contributes to the collaborative creation of GA and how they are involved in the collaboration process. We propose an approach that first employs factor analysis to identify editing abilities and then uses these editing abilities scores to distinguish editors. Then, we generate sequence of editors participating in the work process to analyse the patterns of collaboration. Without loss of generality, we use GA of three Wikipedia categories covering two general topics and a science topic to demonstrate our approach. The result shows that we can successfully generate editor abilities and identify different types of editors. Then we observe the sequence of different editor involved in the creation process. For the three GA categories examined, we found that GA exhibited the characteristic of highly scored content-shaping ability editors involved in the later stage of the collaboration process. The result demonstrates that our approach provides a clearer understanding of how Wikipedia GA are created through open collaboration.
Information-Seeking Behaviour and Knowledge Transfer: A Case Study of Family Business Owners in Kuwait
Authors: AlShakhs Bedour H. , Agarwal Naresh Kumar
Published: May 2022

Information-seeking behaviour is the process of acquiring information from sources in response to a need. The acquired information can then be transferred into knowledge for use, archiving, or sharing. This study investigates the information-seeking behaviour and knowledge transfer among food industry business (fbiz) owners in Kuwait, and how these differ across generations of fbiz owners. Eighteen interviews with 10 large fbiz owners from different generations were carried out. The study found that the information needs of fbiz owners changed at different stages of their business. For information seeking, fbiz members consult a variety of information sources, with the newer generation relying more on online sources than word-of-mouth. Both paper-and-computer-based archiving is used, but information loss remains a threat. Effective knowledge transfer requires better communication between generations and appropriate archiving systems. Each fbiz in Kuwait, irrespective of generation, is required to follow Islamic law. This study brings together the related but differing fields of information behaviour and knowledge management. Most importantly, it contributes two models—a family business information behaviour model and a family business knowledge retention and transfer model that would be useful to the research and practice of information behaviour and knowledge management in family businesses.
Reflections of Community Engagement and Wisdom in the Works of Information Professionals
Authors: Qayyum Muhammad Asim , Khan Arif , Redshaw Sarah
Published: May 2022

Goal/purpose: This study focused on information professionals working in the GLAM (galleries, libraries, archives and museums) sector, and how information was sought and used by them for community engagement and to attain wiser outcomes. The primary purpose was to investigate the information collection, use, reflection and values of professionals in the GLAM sector to determine if wise actions occur that may potentially benefit the community.

Methodology: A qualitative approach was used to conduct this research using the wise action model’s (WAM) wisdom characteristics. Data were collected from information professionals working in managerial positions in the GLAM sector using in-depth interviews. Thematic analysis was used to analyse the data.

Results: The findings indicate that while most participants exhibit some elements of wisdom, there are gaps that need to be addressed before wise functioning is deemed applicable in their roles. While knowledgeable information acquisition and community engagement were very visible, more emphasis on values and stakeholder well-being is recommended for wiser considerations.

Originality/Value: Study of wisdom certainly deserves more attention in knowledge management research as previous studies have indicated. With increasing stresses in the lives of professionals, it is now more important than ever to gain an understanding of how much wisdom prevails in organisational functioning to improve the works of individuals and consequently improve the well-being of impacted communities.
Food Security Assessment: An Exploration of Canadian Offshore Petroleum SEA Practice
Authors: Rohr Veronica , Blakley Jill , Loring Phil
Published: May 2022

Strategic environmental assessment (SEA) has the potential to play a crucial role in addressing global food insecurity. This paper presents the results of an evaluation of 17 recent Canadian SEAs, conducted for offshore petroleum exploration, exploring the extent of consideration for food security in current SEA practice. Document analysis was used to appraise consideration of eight core food security elements and conformity to procedural and analytical elements recommended for effective food security assessment in regional SEA. Performance variation among the SEAs in was observed. Notable deficiencies include lack of explicit consideration for food security and lack of transparency around public participation, as well as limited characterisations of the socio-political environment. Some encouraging findings, however, suggest that food security can be successfully addressed in regional SEA. In particular, the ‘system analysis’ approach typically employed in SEA in the offshore petroleum exploration industry is well-suited to food security assessment. Certain aspects of food security are already indirectly considered and incorporated in SEA; yet, there is considerable scope for improvement of integrating food security effectively in SEA.
Saving, Interest Rates and Finite Horizons
Authors: Tomass Nirai Alexander
Published: May 2022

We study the heterogeneity of interest rate effects on private saving across the age dimension. Taking income and substitution effects as given, we illustrate how in a simple life cycle model, older individuals respond less to interest rate changes than younger ones. This result is driven by the fact that older individuals have a shorter planning horizon, and consequently a lower and less interest sensitive present discounted value of future earnings. However, estimating a dynamic error components model on a global panel of countries spanning the period 1995–2014, we find that there is no evidence for there being a different interest rate effect for countries with higher old age dependency ratios. Our results stand in contrast to recent studies that find effects which are consistent with the theory.
Q-Learning for Shift-Reduce Parsing in Indonesian Tree-LSTM-Based Text Generation
Authors: Hastuti Rochana Prih , Suyanto Yohanes , Sari Anny Kartika
Published: May 2022

Tree-LSTM algorithm accommodates tree structure processing to extract information outside the linear sequence pattern. The use of Tree-LSTM in text generation problems requires the help of an external parser at each generation iteration. Developing a good parser demands the representation of complex features and relies heavily on the grammar of the corpus. The limited corpus results in an insufficient number of vocabs for a grammar-based parser, making it less natural to link the text generation process. This research aims to solve the problem of limited corpus by proposing the use of a Reinforcement Learning algorithm in the formation of constituency trees, which link the sentence generation process given a seed phrase as the input in the Tree-LSTM model. The tree production process is modeled as a Markov’s decision process, where a set of states consists of word embedding vectors, and a set of actions of {Shift, Reduce}. The Deep Q-Network model as an approximator of the Q-Learning algorithm is trained to obtain optimal weights in representing the Q-value function.

The test results on perplexity-based evaluation show that the proposed Tree-LSTM and Q-Learning combination model achieves values 9.60 and 4.60 for two kinds of corpus with 205 and 1,000 sentences, respectively, better than the Shift-All model. Human evaluation of Friedman test and posthoc analysis showed that all five respondents tended to give the same assessment for the combination model of Tree-LSTM and Q-Learning, which on average outperforms two other nongrammar models, i.e., Shift-All and Reduce-All.
Scientific Workflows in IoT Environments: A Data Placement Strategy Based on Heterogeneous Edge-Cloud Computing
Authors: Du Xin , Tang Songtao , Lu Zhihui , Gai Keke , Wu Jie , Hung Patrick C. K.
Published: May 2022

In Industry 4.0 and Internet of Things (IoT) environments, the heterogeneous edge-cloud computing paradigm can provide a more proper solution to deploy scientific workflows compared to cloud computing or other traditional distributed computing. Owing to the different sizes of scientific datasets and the privacy issue concerning some of these datasets, it is essential to find a data placement strategy that can minimize data transmission time. Some state-of-the-art data placement strategies combine edge computing and cloud computing to distribute scientific datasets. However, the dynamic distribution of newly generated datasets to appropriate datacenters and exiting the spent datasets are still a challenge during workflows execution. To address this challenge, this study not only constructs a data placement model that includes shared datasets within the individual and among multiple workflows across various geographical regions, but also proposes a data placement strategy (DYM-RL-DPS) based on algorithms of two stages. First, during the build-time stage of workflows, we use the discrete particle swarm optimization algorithm with differential evolution to pre-allocate initial datasets to proper datacenters. Then, we reformulate the dynamic datasets distribution problem as a Markov decision process and provide a reinforcement learning–based approach to learn the data placement strategy in the runtime stage of scientific workflows. Through using the heterogeneous edge-cloud computing architecture to simulate IoT environments, we designed comprehensive experiments to demonstrate the superiority of DYM-RL-DPS. The results of our strategy can effectively reduce the data transmission time as compared to other strategies.
Enhancement of Glucose Oxidase-Based Bioanode Performance by Comprising Spirulina platensis Microalgae Lysate
Authors: Žalnėravičius Rokas , Ramanavicius Arunas
Published: May 2022

In this study, Spirulina platensis-based lysate was used as a biological redox mediator to design glucose oxidase (GOx) based biofuel cell bioanode. Chemically oxidized multi-walled carbon nanotubes (CNT) were deposited on carbon-electrode and were covered with eco-friendly algae cell-based lysate that facilitated the electron transfer and served as a biocompatible matrix for enzyme immobilization, which reduced the inactivation of GOx by CNT. The designed GC/PEI/CNT/S.p./GOx bioanode exhibited an open circuit potential (OCP) of −262 mV vs Ag/AgCl(3MKCl) in the presence of 12.5 mM of glucose. The maximum power output of the proposed bioanode was 21.8 times higher and reached 3.2 μW cm−2 at −51 mV vs Ag/AgCl(3MKCl) if the S. platensis cell lysate was used for bioanode design. The amperometric responses of GC/PEI/CNT/S.p./GOx bioelectrode towards the addition of glucose were linear at glucose concentrations ranging between 250 μM and 5 mM. These characteristics enable applying this bioanode as a part of biofuel cell and the electrode of an amperometric glucose biosensor, which response within 15 s, with a detection limit of 118 μM and a sensitivity of 15.09 μA mM−1 cm−2.
Palladium Chemical Mechanical Planarization in Packaging and Barrier Level Integration
Authors: Langhout John , Sur Debashish , Bahar Basim G.
Published: May 2022

Palladium (Pd) is a chemically inert material known for its ability to improve processing cost and reliability for the packaging level microelectronics integration. In addition, it is used as a sacrificial layer for copper (Cu) integration as a barrier material to protect the copper from oxidation. Successful implementation of Pd requires chemical mechanical planarization (CMP) process in both applications, where selectivity is desired between the Cu, tantalum nitride (TaN), and nitride (Ni) films against Pd. This paper focuses on removal rate selectivity tuning for Pd thin films in a commercial silica-based Cu-CMP slurry compared to a baseline silica slurry as a function of the slurry temperature. Detailed analyses of the integrated materials are presented, investigating the effect of temperature on surface wettability and CMP selectivity. Pd passivation is also presented by electrochemical analysis in the presence of an oxidizer for the selected polishing slurries. It is observed that lowering the slurry temperature promotes palladium CMP removal rate selectivity against Ni, Cu, and TaN by modifying slurry viscosity and wafer surface wettability with no detrimental effect observed on the surface defectivity.
User Personalized Recommendation Algorithm Based on GRU Network Model in Social Networks
Authors: Zeng Fangqin , Tang Rong , Wang Yibai
Published: May 2022

Efficient and accurate personalized recommendation algorithms can effectively improve user experience satisfaction, in order to improve the performance of user personalized recommendation algorithm, this study proposes a user personalized recommendation algorithm based on deep learning network. The algorithm uses Gate Recurrent Unit (GRU) network to build the main model of personalized recommendation algorithm to reduce the influence of over fitting of multi-layer network; The attention mechanism is introduced into GRU network, so that the recommendation model can obtain the feature information of user data more accurately and reduce the influence of irrelevant data on the model; At the same time, due to the introduction of variable length mini-batch allocation method, the model training data is more complete and reliable, which can effectively improve the accuracy of user personalized recommendation. The simulation experiment is based on Amazon dataset and MovieLens dataset. The experimental results show that the proposed method has good personalized recommendation ability.
PCAT19 Regulates the Proliferation and Apoptosis of Lung Cancer Cells by Inhibiting miR-25-3p via Targeting the MAP2K4 Signal Axis
Authors: Wang Bing , Yang Shengrong , Jia Yang , Yang Jianru , Du Kun , Luo Yujie , Li Yunhe , Wang Zhenghong , Liu Yi , Zhu Bing
Published: May 2022

Both PCAT19 and miR-25-3p have been reported in lung cancer studies, but whether there is a correlation between the two and whether they jointly regulate the progress of lung cancer have not been reported yet. Therefore, this study carried out a further in-depth research. The expression of PCAT19 was detected in lung cancer (LC) tissues and cells by quantitative real-time polymerase chain reaction (qRT-PCR). The effect of PCAT19 on tumor growth was detected in a tumor-bearing model of nude mice. PCAT19-transfected cells were treated with Honokiol and anisomycin. The effects of PCAT19 on proliferation, apoptosis, and cycle of LC cells were investigated by biomolecule experiments. The effects of PCAT19 on the expressions of mitogen-activated protein kinase- (MAPK-) related proteins were evaluated by western blotting. The expression of PCAT19 was decreased in LC tissues and related to patient survival, tumor size, and pathology. In addition, upregulation of PCAT19 hindered LC cell proliferation, miR-25-3p expression, and the activation of extracellular regulated protein kinases (ERK) 1/2, p38, and c-Jun N-terminal kinase (JNK), while facilitating LC cell apoptosis. Furthermore, upregulation of PCAT19 reversed the effects of Honokiol and anisomycin on promoting cell proliferation and inhibiting cell apoptosis. Collectively, our findings show that upregulated PCAT19 suppresses proliferation yet promotes the apoptosis of LC cells through modulating the miR-25-3p/MAP2K4 signaling axis.
Volatile Constituents of Some Selected Plant Species Traditionally Used as Tea in the Sharri Mountains (Kosovo)
Authors: Hajdari Avni , Kelmendi Nita , Mustafa Genista , Mustafa Behxhet , Nebija Dashnor
Published: May 2022

The study evaluates the chemical composition of the volatile constituents of ten plant species traditionally used as herbal tea in the Sharri Mountain regions (Kosovo and North Macedonia). Volatile constituents responsible for the flavour and fragrance of selected species (Crataegus monogyna, Cydonia oblonga, Malus sylvestris, Matricaria chamomilla, Morus alba, Morus nigra, Rosa canina, Sambucus nigra, Tilia cordata, and Vaccinium myrtillus) were separated and then identified using GC-MS, whereas GC-FID is employed for the quantitative analysis. Experimental data revealed different patterns of volatile constituents depending on plant species. Monoterpenes, sesquiterpenes, diterpenes, and norisoprenoids were the most abundant volatile constituents. Principal component analysis (PCA) was deployed for data analysis and resulted in grouping these ten species in four principal clusters. The combination of various volatile constituents present in specific plant species may play an important role in the specific aroma and taste sensation of these species used as recreational teas.
Teaching Mode Design and Effect Evaluation Method of Visual Communication Design Course from the Perspective of Big Data
Authors: Xiong Ding , Soikun Teddy Marius , Wang Jijun
Published: May 2022

Traditional visual communication design teaching courses only use books and courseware for teaching, which greatly limits students understanding and perception of visual communication design art courses. The visual communication design course is different from the teaching of other subjects; it requires students to have a deep understanding of the content of the video and the experience of emotion. Relying on courseware and book teaching methods will not only limit students’ imagination, but also make students tired of learning psychological activities. The teaching of visual communication design technology is to transmit the images, colors, words, and emotions of artworks to students in the form of video, which is a relatively abstract course. With the development of big data technology, this brings new opportunities for the teaching of visual communication design technology courses. In this study, data mining technology will be used to evaluate the effect of visual communication design teaching. And CNN will be used to predict the content characteristics of visual communication design teaching, which is part of the visual communication design teaching system. The research results show that the big data method has better performance in the visual communication design technology course; both the classification and prediction errors are within the acceptable range for the artwork of the visual communication design course. Big data technology can well predict the relevant features in visual communication design; the largest prediction error is only 2.66%, and the smallest error is only 1.21%.
Usefulness of Continuous Low‐Dose Fentanyl in Combination with Dexmedetomidine and Midazolam for Intravenous Sedation: A Randomised Controlled Trial
Authors: Okumura Yoko , Sato (Boku) Aiji , Tachi Naoko , Kanazawa Mayuko , Kawabata Miko , Okuda Masahiro
Published: May 2022

Intravenous dexmedetomidine (DEX) and midazolam (MZ) are currently used to achieve sedation in dental surgery under local anaesthesia. However, the efficacy of low‐dose fentanyl (FEN) in combination with DEX and MZ sedation remains unclear. Therefore, we implemented a prospective randomised controlled trial to investigate the intra‐ and postoperative analgesic effects, intraoperative respiratory and circulatory dynamics, and frequency of intra‐ and postoperative adverse events of continuous low‐dose fentanyl administration with DEX and MZ sedation. Patients aged 20–64 years scheduled for dental surgery under sedation were randomly assigned to the DEX+MZ (DM) or DEX+MZ+FEN (DMF) group. DEX was administered at 4 μg/kg/h for 10 min and then reduced to 0.7 μg/kg/h until the end of surgery. MZ was administered at 0.04 mg/kg upon the initial administration of DEX and 0.02 mg/kg every hour thereafter. In the DMF group, FEN infusion was administered at 2 μg/kg/h during the initial administration of DEX and then reduced to 1 μg/kg/h after 10 min until the end of surgery. Primary outcomes were intra‐ and postoperative analgesic efficacies, whereas secondary outcomes were intraoperative respiratory and circulatory dynamics. The total amount of intraoperative local anaesthetic administered and the heart rate were significantly lower in the DMF group than in the DM group (P = 0.044 and P < 0.01, respectively). No significant difference was observed in the frequency of postoperative administration of analgesics and intra‐ and postoperative adverse events. These findings demonstrated that low‐dose FEN infusion in combination with DEX and MZ sedation in dental surgery provides intraoperative analgesia and suppresses tachycardia with little effect on blood pressure and respiratory dynamics and without effect on postoperative analgesia.
Research on Learner Modeling and Curriculum Recommendation Based on Emotional Factors
Authors: Hua Xin , Zhang Hongchen , Xie Feihong , Wei Juntian , Wei Junjia , Li Huimin
Published: May 2022

With the increasing with the number of courses, learners cannot find the courses they need quickly. Therefore, the primary problem to change the efficiency of online courses is to recommend corresponding courses for a certain group of people according to their needs. Learner characteristics are an important aspect of reflecting learner preferences, and learner models are abstract representations and descriptions of learner characteristics. It is necessary to enhance the use of online courses among students; we must build a relatively comprehensive curriculum model. At present, the construction of learner model is mostly based on cognitive level and learning style, ignoring the emotion expressed by learners to the curriculum, and emotion is a very important characteristic of learners. In order to establish a perfect learner model, it is necessary to incorporate learners’ aspect emotion into the learner model to make the course recommendation process more accurate. Firstly, based on the attention mechanism long-term and short-term memory network, this paper extracts the learner’s aspect emotion to the curriculum from the learner’s curriculum review. At the same time, it studies various characteristics, such as demography, cognitive level, motor behavior, and learning style. By establishing a perfect model integrating researchers’ emotional state, finally, the complex interaction between learner characteristics and curriculum characteristics is modeled by using deep factor natural decomposition, so as to achieve accurate curriculum recommendation. In this study, the learner’s aspect emotion is included in the construction of learner model and enriched and perfected the learner model. It provides a reference for the theoretical research and applied research of learner model and has reference significance. At the same time, combining Deep learning can improve the accuracy of course recommendation, help learners’ learning efficiency and personalized learning quality, and also contribute to the long-term development of online platform. The mathematical modeling in this paper uses learning analysis technology and general factor model based on matrix factorization to calculate and uses factorization machine to reduce the dimension of high-dimensional data, which is efficient and accurate.
Upper Bounds of Radio Number for Triangular Snake and Double Triangular Snake Graphs
Authors: ELrokh Ashraf , Badr Elsayed , Ali Al-Shamiri Mohammed M. , Ramadhan Shimaa
Published: May 2022

A radio labeling of a simple connected graph G = (V, E) is a function  h  : V⟶N such that |h(x) − h(y)| ≥ diam(G) + 1 − d(x, y), where diam (G) is the diameter of graph and d(x, y) is the distance between the two vertices. The radio number of G, denoted by rn (G), is the minimum span of a radio labeling for G. In this study, the upper bounds for radio number of the triangular snake and the double triangular snake graphs are introduced. The computational results indicate that the presented upper bounds are better than the results of the mathematical model provided by Badr and Moussa in 2020. On the contrary, these proposed upper bounds are better than the results of algorithms presented by Saha and Panigrahi in 2012 and 2018.
An Ensemble Clustering Approach (Consensus Clustering) for High-Dimensional Data
Authors: Yan Jingdong , Liu Wuwei
Published: May 2022

Due to the plurality of irrelevant attributes, sparse distribution, and complicated calculations in high-dimensional data, traditional clustering algorithms, such as K-means, do not perform well on high-dimensional data. To address the clustering problem of high-dimensional data, this paper studies an integrated clustering method for high-dimensional data. A method of subspace division based on minimum redundancy is proposed to solve the problem of subspace division of high-dimensional data; subspace division is improved by using the K-means algorithm. Additionally, this method uses mutual information between the characteristic variables of the data to replace the calculation in the K-means algorithm. The distance between the characteristic variables of the data is used to divide the data into subspaces according to the mutual information values between the characteristic variables of the data. To achieve high clustering accuracy and diversity based on clustering requirements, this paper uses a genetic algorithm as the consistency integration function. The fitness function is designed according to the clustering fusion target, and the selection operator is designed according to the maximum number of overlapping elements in the base clustering. The experimental results show that the clustering algorithm proposed in this paper outperforms other methods on most datasets and is an effective clustering integration algorithm. The proposed clustering algorithm is compared with other commonly used clustering fusion algorithms on datasets to prove the advantages of the proposed algorithm.
Evaluation of Urban Tourism Carrying Capacity Based on Analytic Hierarchy Process Optimizing BP Neural Network
Authors: Li Jia , Wang Yuan
Published: May 2022

With the rapid development of today’s social economy, tourism has also developed rapidly. According to national statistics, from 2017 to 2019, domestic tourism revenue increased from 4.57 trillion to 5.73 trillion. The tourism economy has made more and more contributions to the national economy, and it has also received more and more attention and attention from society. However, in recent years, the “explosive” growth of tourism has not only promoted economic development but also brought some challenges to society and the economy, such as environmental pollution in tourist cities. Therefore, it is of great significance to evaluate the tourism carrying capacity of a tourist destination city to realize the sustainable development of the city’s tourism. This article aims to study the evaluation of urban tourism carrying capacity based on AHP and an optimized BP neural network. It designs a carrying capacity evaluation system, conducts BP neural network training for the system, and conducts system testing. The results show that the proportion of scientific and technological innovation is obviously higher than that of other aspects in the proportion of carrying capacity indicators in various aspects of each city. Environmental carrying capacity indicators can be divided into resource supply indicators, pollutant containment indicators, and social impact indicators. This article divides the important indicators into economic development, technological innovation, potential competition, environmental support, and development guarantee. Its indicators account for about 50%, with an average of more than 40%. This shows that the system can clearly display the main factors and evaluation indicators that affect the urban tourism carrying capacity and has certain feasibility and reliability.
Empagliflozin-Metformin Combination Has Antioxidative and Anti-Inflammatory Properties that Correlate with Vascular Protection in Adults with Type 1 Diabetes
Authors: Janić Miodrag , Cankar Matej , Šmid Jan , France Štiglic Alenka , Jerin Aleš , Šabovič Mišo , Janež Andrej , Lunder Mojca
Published: May 2022

Background and Aim. Our previous study showed that the empagliflozin-metformin combination significantly improved arterial function; i.e., it improved endothelial function (measured by flow-mediated dilation and reactive hyperaemia index) and reduced arterial stiffness (measured as pulse wave velocity and local carotid artery stiffness) in adults with type 1 diabetes. In the present study, we explored the underlying mechanism by investigating the antioxidative and anti-inflammatory properties of the empagliflozin-metformin combination (compared to the individual drugs or placebo) and its association with improving arterial function. Methods. 40 individuals with type 1 diabetes (average age of

44.7
±
2.5

years) were randomized into four groups: (1) control (placebo), (2) empagliflozin 25 mg daily, (3) metformin 2000 mg daily, and (4) empagliflozin-metformin combination (25 mg and 2000 mg daily, respectively). At inclusion and after 12 weeks of treatment, the blood samples were collected, and the oxidative stress (total antioxidative status (TAS), superoxide dismutase (SOD), glutathione peroxidase (GPx), uric acid, advanced oxidation protein products (AOPP), advanced glycosylation end products ((AGE) and isoprostane), and inflammation (C-reactive protein (CRP) and interleukin-6 (IL-6)) parameters were determined. Results. The empagliflozin-metformin combination increased levels of the antioxidants (TAS, SOD, and GPx up to 1.1-fold;

P
<
0.01

), decreased the levels of prooxidants (AOPP and isoprostanes up to 1.2-fold,

P
<
0.01

; AGE up to 1.5-fold,

P
<
0.01

), and decreased inflammatory parameters (up to 1.5-fold, CRP

P
<
0.01

; IL-6

P
<
0.001

). Antioxidative action was associated with the improvement in arterial function (obtained in the previous study) in the empagliflozin-metformin combination group. Conclusion. Empagliflozin-metformin combination has strong antioxidative and anti-inflammatory capacity, in adults with type 1 diabetes that is greater than that for the individual drugs. Its antioxidative activity at least partially explains the improvement in arterial function. Therefore, it appears that the combination provides the most powerful vascular protection.
Empirical Examination of the Poisson Regression Residuals for the Evaluation of Influential Points
Authors: Khan Aamna , Ullah Muhammad Aman , Amin Muhammad , Muse Abdisalam Hassan , Aldallal Ramy , Mohamed Mohamed S.
Published: May 2022

A common practice is to get reliable regression results in the generalized linear model which is the detection of influential cases. For the identification of influential cases, the present study focuses to compare empirically the performance of various existing residuals for the case of the Poisson regression model. Furthermore, we computed Cook’s distance for the stated residuals. In order to show the effectiveness of proposed methodology, data have been generated by using simulation, and further applicability of methodology is shown with the help of real data that followed the Poisson regression. The comparative analysis of the residuals is carried out for the detection of influential cases.
Novel Phenotype in Unbalanced 7;9 Translocation with Critical Incidental Finding
Authors: Fischer Julie , Rohena Luis
Published: May 2022

This case discusses a now 13-year-old boy who underwent chromosome analysis and fluorescence in situ hybridization (FISH) for subtelomeric rearrangements due to dysmorphic features at birth. This testing revealed a diagnosis of an unbalanced 7;9 translocation resulting in monosomy for 7q34-qter and trisomy for 9pter-p21, which resulted in a very complex medical course. At the age of 12, due to persistent complex neurodevelopmental concerns, the patient was referred by neurology for whole-exome sequencing. This testing revealed an incidental pathogenic heterozygous KCNH2 deletion, which is associated with long QT-syndrome type II. Prior to this point, the patient had no symptoms of long QT syndrome and had multiple EKGs with normal QT intervals. However, due to this association, the patient underwent Holter monitoring, which revealed clinical evidence of long-QT syndrome type II. Preventative treatment was then initiated and the patient remains asymptomatic. This case expands on the phenotype of this patient’s unbalanced 7;9 translocation as well as highlights the importance of secondary findings in genetic testing.
Remote Music Teaching Classroom Based on Machine Learning and 5G Network Station
Authors: Seng Wenli
Published: May 2022

Most recently, the technological impacts are increasing day by day. Artificial intelligence, machine learning, deep learning, and big data are used to acquire enough application feasibility to reduce work pressure for humans. The way information society is being developed in this world will result in some changes in the development of the education system. The impact will result in some changes in the development of the education system. This research focuses on improving remote music teaching following the presence of a 5G network. Data perception handling is considered the central issue in remote communication, which creates some inabilities to achieve better communication between the systems. To avoid this kind of risk management, most schools and colleges have planned to create a separate network working under wireless connections while delivering the course content to a minimum number of students. Another effective integration of this evolution is efficiently building the remote music education system. Here the compatibility should match both the cases, be they students or the teachers. In this case, network speed is considered one of the most significant impacts on students listening to online classes. Therefore, a 5G network might be the best path to take by increasing the network speed and giving a strong impetus. The proposed system utilizes convolutional neural network (CNN) algorithm to train the intelligent system to provide remote music education through wireless 5G networks. The parameters used for analyzing the proposed system with the existing system are compline, uncertainty, unconfirmed, and out-of-place. The proposed algorithm has achieved an overall accuracy of 99.13% than the existing system.
Blockchain-Based Data Audit Mechanism for Integrity over Big Data Environments
Authors: Wu Jianbin , Haider Sami Ahmed , Bhardwaj Manish , Sharma Aditi , Singhal Piyush
Published: May 2022

Recently, data integrity for multiagent-based big data environments has been challenging. This paper presents a blockchain-based Merkle DAG structure (M-DAG) for audit data integrity. M-DAG resolves the problem that arises due to the multicopy of a large data volume in a big data environment. It employed Boneh–Lynn–Shacham’s (BSL) signature to verify the integrity of identical multicopy on big data environments. The proposed M-DAG audit mechanism uses a consortium chain algorithm for decentralized traceability and audit to archive reliable data. The evaluation has been carried out for the efficiency of the data integrity audit.
Analysis of Gastric Diseases and Their Symptoms Based on Indexes of Pepsinogen I (PGI) and Pepsinogen II (PGII): Take 1106 Patients as Samples
Authors: Guo Kuanpeng , Li Zhengqiu , Qiu Bibo , Hu Bin , Yi Suwu
Published: May 2022

In this study, preoperative analysis of 1106 gastropathy patients with abdominal pain, vomiting, dyspepsia, and other symptoms was conducted. Independent sample

t

-test and correlation analysis and other ways were used for data cleansing and analysis. Findings were as follows: (1) Samples of different genders showed significance in PGI and PGII. The PGI and PGII values of women were significantly lower than those of men. (2) Age showed a significant positive correlation with PGI and PGII, which indicates that as the age increases, the PGI and PGII values become higher. (3) There was a significant negative correlation between age and abdominal pain. This signified that the younger the patient is, the more likely they will suffer abdominal pain. (4) PGI displayed a positive correlation with abdominal pain in the digestive tract (dyspepsia, gastrointestinal ulcers, gastrointestinal bleeding, etc.). It indicated that the higher the PGI value is, the more likely the patients will suffer abdominal pain and gastrointestinal diseases (dyspepsia, gastrointestinal ulcer, gastrointestinal hemorrhage, etc.). (5) PGII displayed a significant positive correlation with gastrointestinal diseases (dyspepsia, gastrointestinal ulcer, gastrointestinal hemorrhage, etc.) and a negative correlation with gastropathy (acute gastritis, chronic superficial gastritis, gastric ulcer, etc.). It indicated that the higher the value of PGII is, the more likely the patients will suffer symptoms of gastrointestinal diseases (dyspepsia, gastrointestinal ulcer, gastrointestinal hemorrhage, etc.), while less likely the patients will suffer gastropathy (acute gastritis, chronic superficial gastritis, gastric ulcer, etc.).
Research on the Operation of Agricultural Products E-Commerce Platform Based on Cloud Computing
Authors: Liu Lingxiao
Published: May 2022

As a large agricultural country, the three rural areas have always been one of the key areas of concern for national economic development. Among them, agricultural products finance is not only related to the development of agricultural economy, but also related to the poverty alleviation and wealth of thousands of farmers. With the rapid development of big data, cloud computing, blockchain, and other financial technologies, it will be important to build a new model of agricultural products supply chain finance and a special agricultural products O2O cloud service platform by relying on new technologies. Therefore, this paper conducts a study on the operation of agricultural products e-commerce platform based on cloud computing. This paper firstly introduces the advantages and key technologies of cloud computing. Secondly, this paper constructs the revenue models of e-merchants, farmers, and leading enterprises under insurance and risk-sharing modes and analyzes the optimal decisions of e-merchants, farmers, and leading enterprises under each mode and the influencing factors of the optimal decisions, so as to provide a new way of thinking for the construction of agricultural supply chain finance mode.
Effect and Mechanism of Endothelin Receptor A Inhibitor BQ-123 Combined with Electroacupuncture on Tibia Cancer Pain in Rats
Authors: Tang Jie , Sun Zhilu , Wang Yan , Liu Jing , Wang Shuai , Wang Xilian
Published: May 2022

Objective. To research the impact and mechanism of endothelin receptor A inhibitor BQ-123 combined with electroacupuncture on tibia cancer pain in rats. Methods. Sprague-Dawley (SD) rats were randomly divided into sham group (SHAM group) and bone cancer pain model group (BCP group). The behavior of SD rats was measured. The histology of the right tibia was observed by hematoxylin-eosin (HE) staining. The remaining rats were randomly divided into model, BQ-123, electroacupuncture, and BQ-123+ electroacupuncture group. Behavioral tests were performed, and mechanical pain threshold (MWT) and thermal pain threshold (TWL) were measured. The expressions of α-smooth muscle actin (αSMA), ETAR (endothelin A receptor), ETB (End of Transmission Block), P-Phosphatidylinositol 3-kinase (PI3K), and P-Protein kinase B (Akt) were detected by real-time fluorescence quantitative PCR and western blot. Results. In the BCP group, bone structure was severely damaged, local tissue swelling was obvious, bone trabecula was missing, and bone cortex was discontinuous. The optical density of Glial fibrillary acidic protein (GFAP) and CD11b immunoreactive signal in BCP group was significantly increased, and most of the ETAR of endothelin receptor was comapped with NeuN, and a small part of GFAP was comapped with CD11b, but no comapped with CD11b. The AS score of BQ-123+ electroacupuncture group was significantly lower than that of BQ-123 group and electroacupuncture group (

P
<
0.05

), whereas the MWT and TWL values were significantly higher than that of the BQ-123 group and electroacupuncture group (

P
<
0.05

). The mRNA expression of α-SMA and ETAR in BQ-123+ electroacupuncture group was lower than that in BQ-123 and electroacupuncture group, and the protein expression of P-PI3K and P-Akt in BQ-123+ electroacupuncture group was lower as well. Conclusion. BQ-123 may inhibit the activation of PI3K/Akt signal path combined with electroacupuncture to alleviate the effects of tibia cancer pain in rats.
Numerical Analysis of Iterative Fractional Partial Integro‐Differential Equations
Authors: Thabet Hayman , Kendre Subhash , Unhale Subhash
Published: May 2022

Many nonlinear phenomena are modeled in terms of differential and integral equations. However, modeling nonlinear phenomena with fractional derivatives provides a better understanding of processes having memory effects. In this paper, we introduce an effective model of iterative fractional partial integro‐differential equations (FPIDEs) with memory terms subject to initial conditions in a Banach space. The convergence, existence, uniqueness, and error analysis are introduced as new theorems. Moreover, an extension of the successive approximations method (SAM) is established to solve FPIDEs in sense of Caputo fractional derivative. Furthermore, new results of stability analysis of solution are also shown.
Influence of Embedded Microprocessor Wireless Communication in the Ankle Joint Proprioception Training on the Prevention of Football Sports Injuries
Authors: Li Siwen
Published: May 2022

This study synthesizes the relevant publications on the therapy of horizontal joint destabilization of the functional ankle and investigates the effect of anterior motion ankle drills on the inability to cause ankle injuries in soccer teams. We chose university soccer teams as the study population and divided them into five men’s and five women’s squads and five control groups. Embedded microcontrollers are also called microcontrollers. Generally, we focus on a specific type of microprocessor center, integrating ROM/EPROM, RAM, Bus Logic, Timer/Counter, Watchdog, I/O, Serial Port, Pulse Width Modulation Output, A/D, D/A, and more. Functions and Devices. Representative embedded microcontrollers include PSIXA, 8051, MCS-251, MCS96/196/296, and C166/167. With the continuous improvement of the processor’s computing power and chip integration, the differences between embedded microprocessors and embedded microprocessors have further increased. Blurred. The test subjects experienced force testing and the trial subjects involved in ankle native sensory drilling. The experimental results show that the average direction has a statistically significant effect on the front, back, left, and right running ability, which increases significantly after 0.017, 0.032, and 0.043 P, respectively, providing a more scientific basis for preventing football injuries.
Diagnostic Value of Magnetic Resonance Imaging Scan, Multislice Spiral Computed Tomography Three‐Dimensional Reconstruction Combined with Plain Film X‐Ray in Spinal Injuries
Authors: Xin Dajiang , Lei Lei
Published: May 2022

Objective. The main objective is to explore the diagnostic value of magnetic resonance imaging (MRI) scan, multislice spiral computed tomography (MSCT) three‐dimensional reconstruction combined with plain film X‐ray in spiral injuries. Methods. By means of retrospective study, the data of 100 patients with spiral injury treated in our hospital from January 2020 to December 2021 were retrospectively analyzed, and all patients received MRI scan, MSCT three‐dimensional reconstruction, and plain film X‐ray examination, and by taking the operation results as the reference, the diagnostic results of different diagnostic modalities were analyzed, and the accordance rates (diagnostic result/surgical result × 100%) of the three diagnostic modalities and their combination were calculated, respectively. Results. Among the 100 patients, 52 cases (52%) had a fracture at the anterior column of the spine, 28 cases (28%) had a fracture at the middle column of the spine, and 20 cases (20%) had a fracture at the posterior column of spine; 24 cases (24%) had simple flexion compression fracture, 60 cases (60%) had burst fracture, 6 cases (6%) had seat belt fracture, and 10 cases (10%) had fracture dislocation. The accordance rate of combined diagnosis for fracture site was 100%, and that for fracture type was 98.0%; MRI could visualize bone marrow injuries, ligamentous injuries, soft tissue injuries, and nerve root injuries that could not be visualized on X‐ray plain films, and 3D reconstruction with MSCT could clearly demonstrate the 3D relationship of spinal fracture displacement, fracture line orientation, and spinal injury. Conclusion. Plain film X‐ray is the basic method for diagnosing spinal injuries, while MRI and MSCT have their unique advantages in this regard, and patients with a negative result of X‐ray plain film can be examined by MRI and MSCT to observe the spinal injury comprehensively.
Metabolomic Mechanisms of Radix Fici Hirtae against Carbon Tetrachloride-Induced Acute Liver Damage in Mice
Authors: Zhou Fang-Yu , Quan Ting , Xiang Shi-Jian , Li Hui , Chen Hui-Yuan , Yang Yu-Xuan , Li Sha-Sha
Published: May 2022

Background. Radix Fici Hirtae (RFH), known as Cantonese ginseng, is an alternative folk medicine that is widely used to treat various diseases in southern China. The aim of this study was to investigate the effect and metabolic mechanisms of pretreatment with RFH on the serum metabolic profiles of carbon tetrachloride (CCl4) induced acute liver injury in mice. Methods. Mice fed with the water extract of RFH at a dose of 1.5 g/kg and 0.75 g/kg for consecutive 7 days, and then serum samples were taken for the metabolomic analysis. Furthermore, the bioinformatics and pathways analysis were measured. Results. The UHPLC-Orbitrap/MS based-metabolomic analysis identified 20 differential metabolic markers in serum of CCl4-induced liver injury mice compared to that of the normal controls, which were mainly related to the metabolism of amino acids and fatty acids. Furthermore, most of these biomarkers contributing to CCl4 induction were ameliorated by RFH, and the bioinformatics and pathways analysis revealed that therapeutic actions of RFH were mainly involved in the regulation of the oxidative stress responses and energy homeostasis. Conclusion. These findings provide potential metabolic mechanism for future study and allow for hypothesis generation about the hepatoprotective effects of Radix Fici Hirtae.