bluuebunny/crossref_metadata_2025 huggingface dataset:
Chalkboard 2 - How to Make Clean Hydrogen
Authors: Alia Shaun , Ding Dong , McDaniel Anthony , Toma Francesca M. , Dinh Huyen N.
Published: May 2022

Clean hydrogen is a carbon-free energy carrier that can be produced from water and sustainable energy sources such as wind, solar, and nuclear. Hence, clean hydrogen is one of the best ways to not only decarbonize the energy supply system, but also address the zero-emission challenges specific to large-carbon emitting industries that are difficult to separate from fossil fuels. To help achieve the Biden Administration’s goal of a 100% clean energy economy and net-zero emissions by 2050, several tens of millions of metric tons of clean, low-cost hydrogen will be needed annually. The HydroGEN Advanced Water Splitting Materials (AWSM) Consortium was established in 2016 as part of the Energy Materials Network (EMN) under the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Hydrogen and Fuel Cell Technologies Office to enhance the performance, improve the durability, and reduce the cost of clean hydrogen production technologies, and it is helping to advance the H2@Scale vision.
From Hydrogen Manifesto, through Green Deal and Just Transition, to Clean Energy Act
Authors: Atanassov Plamen , Noto Vito Di , McPhail Stephen
Published: May 2022

The Year 2020 charted a seminal change in the way we see hydrogen technology as the backbone of decarbonization of the economy. And this charter was taken by far most ambitiously by the countries of the European Union. Streaming from their Hydrogen Manifesto, the governments and businesses, political parties and NGOs all stood on the path that leads to the European Green Deal, which starts with the Recovery and Resilience Facility and continues through the Just Transition Platform. The European Commission was the first to declare the official “taxonomy” for hydrogen as “green”, “blue” and “gray” hydrogen. This article will introduce the vision: Fit for 55 as a goal of cutting CO2 emissions by 55% in less than a decade and will touch on some of the regulatory and financial instruments to reach it. What year 2021 will bring is germinated in close to 300 running projects with the contributions from every corner of the European Union.
High-flow nasal cannula compared with continuous positive airway pressure: a bench and physiological study
Authors: Vieira Fernando , Bezerra Frank Silva , Coudroy Remi , Schreiber Annia , Telias Irene , Dubo Sebastián , Cavalot Giulia , Pereira Sergio Martins , Piraino Thomas , Brochard Laurent Jean
Published: May 2022

High-flow nasal cannula generates positive airway pressure and reduces respiratory rate. Our findings confirm these physiological effects when the mouth is kept closed. An increased resistance to breathing induces a longer expiratory phase, which leads to decreased respiratory rate and minute ventilation, and therefore to a decreased respiratory workload, counterbalancing the increased pressure-time product per liter. These effects are less apparent with the mouth open and are not observed with continuous positive airway pressure.
Evaluation of Multimedia Popular Music Teaching Effect Based on Audio Frame Feature Recognition Technology
Authors: Zhao Xuelin
Published: May 2022

Music education should pay attention to popular music that exists in students’ real life and deeply affects them. Moreover, it needs to be combined with “popular classical music” to make them happily learn popular music, appreciate popular music artistically, and feel popular music aesthetically. This study combines the audio frame feature recognition technology to evaluate the effect of multimedia popular music teaching and improve the quality of multimedia popular music teaching. Moreover, this study adaptively revises the speech spectrum technology to construct a multimedia pop music system based on audio frame feature recognition technology. Finally, this study verifies the performance of this system through experimental research. According to the results of experimental research, it can be seen that the effect of the system proposed in this study is very good.
Recognition of Petroleum Origin in the Northern Piedmont Belt of Turpan-Hami Basin and Its Significance
Authors: Hao Bin , Yang Zhanlong , Zhang Jing , Li Shuangwen , Wei Lihua , Shi Jianglong , Li Zaiguang , Yao Jun , Huang Xiaopeng , Wu Qingpeng
Published: May 2022

The Turpan-Hami Basin has been considered as the most typical coal-derived-oil basin in China for a long time. However, with the deepening exploration, this theory has caused increasing controversy and some scholars doubt that Permian or Jurassic dark mudstone may be the main source rocks. The origin uncertainty even restricts deciding the exploration direction. Taking the reservoirs of the northern piedmont belt as an example, this paper analyzed oil sources by the geochemical characteristic comparison of inclusions, crude oil, and source rocks. Combined with the previous studies, the hydrocarbon accumulation model is established. The results show that the geochemical characteristics of the inclusions and oil in most areas are obviously different. Most reservoirs are mixed-source reservoirs. The oil sources varied in different regions. In the area near Bogeda, C19+20TT and C28 sterane content in oil are high, indicating that coal and Permian lacustrine mudstone are main contributors. Far away from Bogeda, bounded by the thick coal seam of Xishanyao Formation, oil sources are quite different. Above it, C19+20TT is high and gammacerane and pregnane are low, C29>>C28>C27sterane, indicating that coal and carbonaceous mudstone are main sources. Under that, C21TT and C23TT content in the inclusions are high, C29≥C27>C28sterane, while C19+20TT and pregnane content in the oil are also high, indicating that it is a mixed oil system mainly derived from Jurassic lacustrine mudstone and coal. Lacustrine mudstone has higher contribution. This phenomenon is mainly related to different fault styles in different zones. Near Bogeda, strong stress caused vertical large faults developed, which connected Jurassic reservoirs and Permian source rocks. Far from Bogeda, the faults sliped along the thick coal seam, It is difficult for deep hydrocarbon to enter the shallow layer. In the future, it should be considered to look for the traps with relatively high-quality reservoir-cap combinations for exploration in the hydrocarbon supply window of effected hydrocarbon kitchens.
Characterization of Acetylation of Histone H3 at Lysine 9 in the Trigeminal Ganglion of a Rat Trigeminal Neuralgia Model
Authors: Wei Wenbin , Liu Yuemin , Qiu Yating , Chen Minjie , Wang Yiwen , Han Zixiang , Chai Ying
Published: May 2022

Trigeminal neuralgia (TN) is a chronic neuropathic pain disorder characterized by spontaneous and elicited paroxysms of electric-shock-like or stabbing pain in a region of the face. The epigenetic regulation of TN is still obscure. In current study, a rat TN model subject to carbamazepine (CBZ) treatment was established, and transcriptome- and genome-scale profiling of H3K9ac and HDAC3 was performed by RNA-seq and ChIP-seq. We observed that H3K9ac levels in the trigeminal ganglion were lower in the TN rats compared with those in the control, and CBZ treatment led to recovery of H3K9ac levels. Further, we found that HDAC3 was overactivated, which interfered with H3K9 acetylation due to higher phosphorylation in TN compared with that in the control. Finally, the phosphokinase leucine-rich repeat kinase 2 (LRRK2) was demonstrated to contribute to HDAC3 activity via the MAPK signaling pathway. Taken together, we identified a regulatory mechanism in which the phosphate groups transferred from activated ERK and LRRK2 to HDAC3 caused genome-scale deacetylation at H3K9 and resulted in the silencing of a large number of genes in TN. The kinases or important enzymes within this regulatory axis may represent important targets for TN therapy and prevention.
Knee Osteoarthritis: Kinesiophobia and Isometric Strength of Quadriceps in Women
Authors: Machado Saulo , Érika Santana  , Brito Victor , Maciel Leonardo , Quintans Júnior Lucindo J. , da Silva Junior Walderi , de Farias Neto Jader , Melo Coutinho Henrique Douglas , Kim Bonglee , Santana Filho Valter J. de
Published: May 2022

Introduction. Osteoarthritis is a disease characterized by progressive wear and tear of the joint, with the knee being the most affected region. These patients have reduced mobility and mobility, among other symptoms. Thus, it is necessary to know the variables that influence the ability to walk. Objective. To analyze how much the gait capacity, in the performance of the six-minute walk test, can be influenced by the maximum isometric strength of the quadriceps or by kinesiophobia in women with knee osteoarthritis. Materials and Methods. This is a cross-sectional study with a sample of 49 women diagnosed with osteoarthritis. The evaluation was carried out in a single moment. Variables studied isometric quadriceps strength, level of fear of movement (kinesiophobia), and ability to walk. Simple linear regression analyzes were performed, with gait ability as the dependent variable and maximum isometric strength and kinesiophobia as independent. Data were presented with mean and standard deviation and were analyzed by the SPSS Statistic 22.0 software, considering

p
<
0.05

as significant. Results. The maximum isometric strength presents a significant difference, directly interfering with the gait ability; as kinesiophobia does not show a statistically significant difference, it does not directly interfere with the ability to walk. Conclusion. Maximal quadriceps isometric strength directly interferes with gait ability in women with knee osteoarthritis, thus suggesting the inclusion of this strategy in treatment programs for this population.
Update on the Use of Nanocarriers and Drug Delivery Systems and Future Directions in Cervical Cancer
Authors: Himiniuc Loredana Maria , Toma Bogdan Florin , Popovici Razvan , Grigore Ana Maria , Hamod Alexandru , Volovat Constantin , Volovat Simona , Nica Irina , Vasincu Decebal , Agop Maricel , Tirnovanu Mihaela , Ochiuz Lacramioara , Negura Anca , Grigore Mihaela
Published: May 2022

Cervical cancer represents a major health problem among females due to its increased mortality rate. The conventional therapies are very aggressive and unsatisfactory when it comes to survival rate, especially in terminal stages, which requires the development of new treatment alternatives. With the use of nanotechnology, various chemotherapeutic drugs can be transported via nanocarriers directly to cervical cancerous cells, thus skipping the hepatic first-pass effect and decreasing the rate of chemotherapy side effects. This review comprises various drug delivery systems that were applied in cervical cancer, such as lipid-based nanocarriers, polymeric and dendrimeric nanoparticles, carbon-based nanoparticles, metallic nanoparticles, inorganic nanoparticles, micellar nanocarriers, and protein and polysaccharide nanoparticles. Nanoparticles have a great therapeutic potential by increasing the pharmacological activity, drug solubility, and bioavailability. Through their mechanisms, they highly increase the toxicity in the targeted cervical tumor cells or tissues by linking to specific ligands. In addition, a nondifferentiable model is proposed through holographic implementation in the dynamics of drug delivery dynamics. As any hologram functions as a deep learning process, the artificial intelligence can be proposed as a new analyzing method in cervical cancer.
A Novel Bitcoin and Gold Prices Prediction Method Using an LSTM-P Neural Network Model
Authors: Zhang Xinchen , Zhang Linghao , Zhou Qincheng , Jin Xu
Published: May 2022

As a result of the fast growth of financial technology and artificial intelligence around the world, quantitative algorithms are now being employed in many classic futures and stock trading, as well as hot digital currency trades, among other applications today. Using the historical price series of Bitcoin and gold from 9/11/2016 to 9/10/2021, we investigate an LSTM-P neural network model for predicting the values of Bitcoin and gold in this research. We first employ a noise reduction approach based on the wavelet transform to smooth the fluctuations of the price data, which has been shown to increase the accuracy of subsequent predictions. Second, we apply a wavelet transform to diminish the influence of high-frequency noise components on prices. Third, in the price prediction model, we develop an optimized LSTM prediction model (LSPM-P) and train it using historical price data for gold and Bitcoin to make accurate predictions. As a consequence of our model, we have a high degree of accuracy when projecting future pricing. In addition, our LSTM-P model outperforms both the conventional LSTM models and other time series forecasting models in terms of accuracy and precision.
FSR-Based Smart System for Detection of Wheelchair Sitting Postures Using Machine Learning Algorithms and Techniques
Authors: Jaffery Mujtaba Hussain , Ashraf Muhammad Adil , Almogren Ahmad , Asim Hafiza Mahnoor , Arshad Jehangir , Khan Javed , Rehman Ateeq Ur , Hussen Seada
Published: May 2022

This paper presents an intelligent system containing FSR-based posture detection using machine learning algorithms. This paper is aimed at detecting the sitting posture of a wheelchair user. Individuals using wheelchairs are at increased risk of pressure ulcers when they hold an incorrect position for too long because the blood supply desists at some points of their skin due to increased pressure. The main objective of this research is to find a better configuration combined with the best machine learning algorithm for the detection of posture to prevent pressure ulcers. In the proposed monitoring system, two configurations consisting of a

3
×
3

matrix configuration (9 sensors) and a crossconfiguration (5 sensors) of FSR sensors are embedded on a wheelchair seat to get pressure data generated and collected in a real-time processing unit and then compared. The posture recognition is performed for five sitting positions: ideal, backward-leaning, forward-leaning, right-leaning, and left-leaning based on five machine learning algorithms:

K

-nearest neighbors (

K

-NN), logistic regression (LR), decision tree (DT), support vector machines (SVM), and LightGBM. The research study provides a system to detect a real-time pressure sitting posture on a processing unit (laptop) wirelessly using the ESP32 module. Consequently, a posture classification accuracy of up to 95.41% is accomplished using a

3
×
3

matrix configuration. The proposed system helps prevent pressure ulcers and is valuable in risk assessment related to pressure ulcers. This system describes the relationship between accuracy, different sensor configurations, and performance of the multiple machine learning algorithms.
Influence of Rainfall Infiltration on Stability of Granite Residual Soil High Slope
Authors: Li Songtao , Niu Yongding , Wang Baolin , Gao Yanlong , Zhu Yongchao
Published: May 2022

The seepage evolution characteristics and stability change rule of granite residual soil inside the high cutting slope under the action of rainfall infiltration were studied. Based on the saturated-unsaturated seepage theory, the numerical simulation of the rainwater infiltration path inside the granite residual soil slope was carried out under the condition of rainwater infiltration. The evolution characteristics of the seepage field of the granite residual soil cutting high slope under the condition of rainfall infiltration were revealed, and the influence of the rainwater infiltration on the stability of the granite residual soil slope was mainly studied. The research results show that with the accumulation of rainfall infiltration, the pore water pressure of the granite residual soil slope increases continuously, and the pore water pressure of the soil below the platform increases the fastest. With the increase in elevation, the water content of the slope presents a wave crest distribution. In the early stage of rainfall, the seepage velocity vector distribution on the slope surface is relatively uniform. In the middle stage of rainfall, the seepage velocity vector is the most dense at the platform, and the rainwater migration rate is accelerated. In the later stage of rainfall, the infiltrated rainwater at the slope angle of the first-level slope spreads to the surrounding area. With the continuous rainfall, the slope stability safety factor gradually decreased unevenly, and after the rainfall stopped, it gradually increased with the rainwater infiltration.
DLP-Based 3D Printing for Automated Precision Manufacturing
Authors: Deng Weiping , Xie Deqiao , Liu Fuxi , Zhao Jianfeng , Shen Lida , Tian Zongjun
Published: May 2022

As a new type of rapid prototyping technology, 3D printing technology effectively solves the problems of large errors and waste of resources in traditional manufacturing technology. Compared with other technologies, DLP technology has the following advantages: high reliability, high brightness, rich and gorgeous colors, and is very suitable for portable devices. This article aims to study the application of embedded microprocessor-based DLP3D printing in automated precision manufacturing. This article puts forward the idea of applying DLP3D technology to more automated precision manufacturing. This article introduces the embedded microprocessor, 3D printing technology, and related algorithms in detail. At the same time, this article also conducts experiments on DLP3D printing technology. Through the analysis of samples printed by DLP3D technology, the experimental results show that the material deviation value of DLP3D printing based on embedded microprocessor is generally small, compared with other technology printing the deviation value of the material is also reduced by 15.6%.
Observation of the Effect of Focused Psychological Intervention Combined with Standardized Pain Nursing on Postoperative Pain Levels and Depression and Anxiety in Patients with Intestinal Obstruction
Authors: Yin Mantian , Li Jifang , Wang Jie , Li Minxiang , Li Long , Wang Genmei , Ouyang Yibin , Wang Peiru
Published: May 2022

Objective. The purpose of this study was to investigate the effect of targeted psychological intervention combined with standardized pain care on postoperative pain, depression, and anxiety in patients with intestinal obstruction. Methods. 84 patients with intestinal obstruction hospitalized at our hospital from October 2019 to February 2021 were randomly divided into study and control groups. The patients in the control group were treated with routine nursing, and the patients in the study group were treated with focused psychological intervention combined with standardized pain nursing. The pain degree (VAS), depression and anxiety (SDS, SAS) score, sleep quality (PSQI) score, and nursing satisfaction of the two groups before and after intervention were calculated. Results. Before intervention, no significant differences in VAS score between the study and control groups were observed. The VAS score of 6 h, 12 h, 24 h, and 48 h dry prognosis in the study group was lower than that in the control group. There was no significant difference in the scores of SDS and SAS between two groups. After intervention, the scores of SDS and SAS in the study group were lower than those in the control group. After intervention, the scores of daytime dysfunction, hypnotic drugs, sleep disorders, sleep efficiency, sleep time, and sleep quality in the study group were significantly lower than those in the control group. The scores of nursing state, nursing technique, nurse-patient communication, and inspection observation in the study group were higher than those in the control. Conclusion. The intervention of focused psychological intervention combined with standardized pain nursing on patients with intestinal obstruction can effectively relieve their negative emotion and reduce the degree of postoperative pain. In addition, it can improve patients’ sleep quality and enhance patients’ satisfaction with all kinds of nursing work.
Analysis of Natural Convection in Nanofluid Flow through a Channel with Source/Sink Effect
Authors: Siddique Imran , Sadiq Kashif , Jarad Fahd , Al Mesfer Mohammed K. , Danish Mohd , Yaqoob Sonia
Published: May 2022

In this study, the natural convection nanofluids flow through a channel formed by two vertical parallel plates having distance d between them has been examined under the influence of the ramped velocity. Sodium alginate is considered as base fluid, and nanoparticles of titania (TiO2) and alumina (Al2O3) are added to it. Analytical and semianalytical results for temperature and velocity profiles are obtained with Laplace transform and inverse Laplace algorithms (Tzou, Stehfest, Talbot, Honig and Hirdes, and Fourier series), respectively. Furthermore, the impacts of nanoparticles, Prendtl number, heat absorption, and time on velocity and temperature are drawn graphically and discussed. The outcomes show that the high thermal conductivity of particles increases the temperatures, and the high density of particles decreases the velocities of the nanofluids. The current findings are compared to previous findings in the literature. In the tables, the effect of volume fraction on Nusselt numbers and skin frictions is explored.
The Application of Differing Machine Learning Algorithms and Their Related Performance in Detecting Skin Cancers and Melanomas
Authors: Alkhushayni Suboh , Al-zaleq Du’a , Andradi Luwis , Flynn Patrick
Published: May 2022

Skin cancer, and its less common form melanoma, is a disease affecting a wide variety of people. Since it is usually detected initially by visual inspection, it makes for a good candidate for the application of machine learning. With early detection being key to good outcomes, any method that can enhance the diagnostic accuracy of dermatologists and oncologists is of significant interest. When comparing different existing implementations of machine learning against public datasets and several we seek to create, we attempted to create a more accurate model that can be readily adapted to use in clinical settings. We tested combinations of models, including convolutional neural networks (CNNs), and various layers of data manipulation, such as the application of Gaussian functions and trimming of images to improve accuracy. We also created more traditional data models, including support vector classification, K-nearest neighbor, Naïve Bayes, random forest, and gradient boosting algorithms, and compared them to the CNN-based models we had created. Results had indicated that CNN-based algorithms significantly outperformed other data models we had created. Partial results of this work were presented at the CSET Presentations for Research Month at the Minnesota State University, Mankato.
circZNF91 Promotes the Malignant Phenotype of Chronic Lymphocytic Leukemia Cells by Targeting the miR‐1283/WEE1 Axis
Authors: Li Shaoting , Chen Jing , Fan Ying , Xu Xiaoli , Xiong Minjian , Qi Yonglei , Wu Wenlin , Zhao Ying
Published: May 2022

Background. Circular RNAs (circRNAs) are frequently dysregulated in cancers and are implicated in tumorigenesis and tumor progression. In this study, we investigated the role of circZNF91 in regulating the malignant phenotype of chronic lymphocytic leukemia (CLL) cells and the underlying molecular mechanism. Material/Methods. The expression of circZNF91 was determined by reverse transcription‐quantitative polymerase chain reaction (RT‐qPCR). The binding sequences between circZNF91/miR‐1283 and miR‐1283/WEE1 were predicted by the bioinformatic database. The functional interactions were confirmed by the dual‐luciferase reporter, RT‐qPCR, and Western blot assays. The functional roles of the circZNF91/miR‐1283/WEE1 axis in CLL progression were examined by cell proliferation, apoptosis, and EdU incorporation assays. Results. circZNF91 was upregulated in CLL samples. Silencing circZNF91 attenuated CLL cell proliferation and induced apoptosis and cell cycle arrest. circZNF91 could sponge miR‐1283 to suppress its activity, which in turn upregulated WEE1 expression. Silencing circ‐TTBK2 reduced WEE1 expression, while the inhibitor of miR‐1283 enhanced WEE1 expression. The miR‐1283/WEE1 axis mediated the effects of circZNF91 on cell proliferation and apoptosis, as well as induced cell cycle regulation. Conclusions. The circZNF91/miR‐1283/WEE1 axis is engaged in the pathological phenotypes of CLL cells, which could serve as potential targets for future therapy development.
Wireless Sensor Network Technology-Based Design and Realization of Intelligent Tennis Sports System
Authors: Zhou Yimiao , Shen Heng
Published: May 2022

With the progress of the times and the development of science and technology, the scientific and technological elements infiltrated in various sports fields are increasingly enriched, which greatly improves the skills and technical and tactical levels of sports participants and sports equipment users and the development of sports items. With the increasing importance of education, people have begun to pay attention to physical education. Tennis has also received much attention in recent years. However, there are many problems in traditional tennis, such as untimely detection and irregular movements, so this paper is aimed at studying how to design an intelligent system for tennis based on wireless sensor network technology. With the development of sports, athletes have higher and higher requirements for themselves. However, traditional training has been unable to find their own mistakes in time, and the intelligent tennis system can not only analyze the data information of tennis in the air but also provide users with various sports analysis data to help players find specific problems and achieve the purpose of comprehensively improving tennis skills. This paper presents the development of wireless sensor networks and tennis and introduces the concepts of wireless sensor networks and tennis. From the data of the experiment in the text, we can see that the growth rate of tennis courses offered in colleges and universities increased from about 4% to about 24% in 2019, an increase of 20%. In 2020, the growth rate of tennis courses in colleges and universities increased from about 21% to about 33%, an increase of 12%. It can be seen that in recent years, tennis has been valued by major universities and loved by students. Therefore, it is necessary to take necessary measures for the development of tennis, and it is very meaningful to realize the intelligent system of tennis based on wireless sensor network.
Analysis of the Correlation between Academic Performance and Learning Motivation in English Course under a Corpus-Data-Driven Blended Teaching Model
Authors: Yu Lan , Shen Jun
Published: May 2022

To explore the correlation between academic performance and learning motivation in English course under a corpus-data-driven blended teaching model, this study set research objects as 62 year-2020-enrolled undergraduate students majoring in English from a university in Jinan City, Shandong Province, eastern China. According to their previous frequencies of using information technology to learn English, these 62 students were divided into two groups: practice group with high frequency and control group with low frequency, with 31 students in each group. The two groups of students were taught 3 English lessons per week for a total of 15 weeks by the exact same teachers using a corpus-data-driven blended teaching model. The students’ English academic performances were assessed by well-organized final tests, and their English learning motivations were measured by a motivation scale and questionnaires. The results show that the correlation coefficients between the average score of motivation questionnaires, intrinsic motivation factors, extrinsic motivation factors, and the average score of academic performances in practice group were 0.894, 0.682, and 0.724, respectively, while those in control group were 0.749, 0.836, and 0.904. In all the above correlation analyses, the significance level is 0.01, and all coefficient values are higher than critical value. Hence, there is a positive correlation between learning motivation and academic performance of the two groups of subjects. It is found that the corpus-data-driven blended teaching model has a significant impact on college students’ English academic performance and learning motivation, and it has a positive effect on the improvement of their English academic performance and the cultivation of learning motivation. In general, the key to this teaching model lies in reasoning and acquisition by analyzing the language provided by the corpus, and the whole process of data-driven learning is student-centered. Students are exposed to a large number of authentic language knowledge and cultural information, which promotes the sensitivity to relevant points. The results of this paper provide a reference for further research on the analysis of the correlation between academic performance and learning motivation in English course under the corpus-data-driven blended teaching model.
IRS Backscatter-Assisted Security Transmission against Proactive Eavesdropping
Authors: Wang Jianling
Published: May 2022

In this paper, we consider the IRS backscatter-assisted physical layer security, aimed at countering smart eavesdroppers capable of sending jamming signals. Specifically, the eavesdropper increases the eavesdropping rate by sending jamming signals and is able to adjust the transmission strategy according to the received beamforming. By using IRS backscatter communication, the jamming signal sent by the eavesdropper is converted into a useful signal and transmitted. By designing the beamforming of the base station and the IRS phase shift matrix, we established the original optimization problem. Since the eavesdropper’s sending strategy is adjusted according to the received signal, we transform the original problem into two subproblems. In the first subproblem, we obtain the eavesdropper’s transmit beamforming; in the second subproblem, we optimize the transmit beam alternately with the IRS phase shift matrix. Simulation results demonstrate the superiority of our proposed scheme.
The Performance Evaluation of IEE in Colleges and Universities Based on AHP Model
Authors: Liang Zhenghan
Published: May 2022

At present, the country strongly encourages all walks of life to innovate, especially in the field of education. China's major colleges and universities have increased the encouragement of innovation and entrepreneurship education (IEE) projects in keeping with the pace of the times, so it is particularly important to reasonably evaluate the actual benefits of the project. On the one hand, it can greatly improve the recognition of all walks of life for emerging education projects. On the other hand, it can realize the timely and accurate application of the financial funds of the project. Based on this background, through the analysis and summary of existing theories and comprehensive consideration at all levels, this paper studies the new education projects from the aspects of teaching environment, conditions, quality, satisfaction, and financial capital and then constructs a set of performance evaluation index system for IEE in major colleges and universities. At the same time, this paper analyzes the actual education environment in China and evaluates the IEE in all kinds of colleges and universities by using analytic hierarchy process (AHP). Judging from the assessment results, the current teaching conditions and the quality of teachers in Chinese universities are very good. But the conclusion from the perspective of students is opposite, and the investment ratio of their financial capital is not optimistic. Therefore, this paper puts forward the optimization suggestions.
Iron Chelators in Treatment of Iron Overload
Authors: Entezari Sarina , Haghi Seyedeh Mona , Norouzkhani Narges , Sahebnazar Barsa , Vosoughian Fatemeh , Akbarzadeh Diba , Islampanah Muhammad , Naghsh Navid , Abbasalizadeh Mohammad , Deravi Niloofar
Published: May 2022

Patients suffering from iron overload can experience serious complications. In such patients, various organs, such as endocrine glands and liver, can be damaged. Although iron is a crucial element for life, iron overload can be potentially toxic for human cells due to its role in generating free radicals. In the past few decades, there has been a major improvement in the survival of patients who suffer from iron overload due to the application of iron chelation therapy in clinical practice. In clinical use, deferoxamine, deferiprone, and deferasirox are the three United States Food and Drug Administration-approved iron chelators. Each of these iron chelators is well known for the treatment of iron overload in various clinical conditions. Based on several up-to-date studies, this study explained iron overload and its clinical symptoms, introduced each of the above-mentioned iron chelators, and evaluated their advantages and disadvantages with an emphasis on combination therapy, which in recent studies seems a promising approach. In numerous clinical conditions, due to the lack of accurate indicators, choosing a standard approach for iron chelation therapy can be difficult; therefore, further studies on the issue are still required. This study aimed to introduce each of these iron chelators, combination therapy, usage doses, specific clinical applications, and their advantages, toxicity, and side effects.
Modified Data Delivery Strategy Based on Stochastic Block Model and Community Detection in Opportunistic Social Networks
Authors: Li Limiao , Gou Fangfang , Wu Jia
Published: May 2022

The nodes in the opportunistic network make up communities according to the relevance between them. Some of the structural characteristics of an opportunistic network can be reflected by the structure of the communities that exist in the network. Therefore, finding community from the network is of great significance for people to better study, use, and transform the network. The overlap of communities is considered to be an important feature of communities. Almost all community discovery algorithms were based on nonoverlapping communities in the past. A node in a nonoverlapping community belongs to only one community. However, there are overlapping and interrelated characteristics between communities, so it is not in line with the actual environment of the network. As a result, the previous algorithms have many shortcomings in the face of practical application scenarios, coupled with the limitation of the computing capacity of mobile devices; data transmission for low delay and the low energy consumption is difficult to meet the requirements. In the study, we formulate the problem of dividing nodes into several communities in the opportunistic social network as how to build communities dynamically according to weight distribution. Then, we propose a modified data delivery strategy based on stochastic block model and community detection (DDBSC). The simulation results show that, compared with other algorithms in the experiments, the strategy proposed in this paper exhibits good performance in terms of overhead, energy consumption, and delivery rate.
ERP System Design for Hydrogen Equipment Manufacturing Industry Based on Low Code Technology
Authors: Wang Long , Guan Shuaipeng , Deng Wei , Lu Ping
Published: May 2022

Research Problem. Aiming at the problems such as fast update and iteration speed, high development cost, and isolated enterprise data in hydrogen equipment manufacturing industry, a low code programming system based on enterprise data center and business center was proposed and designed. Research Method. This paper designs the data center service and business center architecture of hydrogen equipment manufacturing industry. The data center collects, mines, and integrates massive data into unified standard structured data and stores them. The business center provides architectural support for the establishment of enterprise resource management system. With the data center service as the system data interaction center and the business center as the model to build the system architecture, the hydrogen equipment manufacturing industry resource management system is constructed through the steps of data interaction, process modeling, and UI editing. Research Results. According to the specific requirements of hydrogen equipment manufacturing industry, the business process of hydrogen enterprise resource management system is constructed, and the construction and development of low code system are studied and discussed by integrating data center and business center. Conclusions. Low code is not just a tool to increase productivity, it has the potential to be a catalyst for technology and culture to promote enterprise innovation and business agility, and ERP systems for hydrogen equipment manufacturing based on low coding technology are needed for the industry of the future. This article contributes to the hydrogen equipment manufacturing industry of low code programming system, users can according to their own needs, through the combination of components, quickly generate a complete management system, update system iteration, greatly reduce the development cost, solve the problem of enterprise data isolation, reduce the development cost, and realize the seamless integration of modern software development practice, so as to promote enterprise innovation and business agility.
[Retracted] Mate Analysis of Hepatocellular Carcinoma Immune Subtypes and Their Functional Effects Based on Fuzzy Logic and Evolutionary Algorithms
Authors: Chen Qingge , Liu Chaoyi , Huo Yujia
Published: May 2022

Functional analysis of immune subtypes in hepatocellular carcinoma has attracted much attention due to its advantages in solving some optimization problems. At present, the research on the immune subtype of hepatocellular carcinoma is still in its infancy, and the high stability of its system still has problems. Based on fuzzy logic and evolutionary algorithms, this paper constructs a Mate analysis of the optimization problem of immune subtypes and dynamic optimization problems of hepatocellular carcinoma. The model conducts in‐depth analysis and research on the biological immune subtype system, solving the problems of reliable information processing and body defense. Tested with existing test functions, very competitive results were achieved. The simulation results show that the improved algorithm based on data statistics has global search ability, the solution accuracy reaches 0.931, and the stability reaches 88.1%.
The Application of Seepage Flow Prediction in Nuer Dam Based on the Grey Self-Memory Model
Authors: Wang Ai-Feng , Yang Xiu-Tao , Guo Da-Hai
Published: May 2022

The accurate time prediction of seepage pressure in the dam has essential significance for the safety of the dam body and the life and property of people. To predict the time sequence of seepage pressure, the grey self-memory model is introduced at first, and its calculative procedure is analyzed. Then, the engineering overview in the Nuer dam is narrated, and the prediction model of seepage pressure in the Nuer dam is established and analyzed based on the grey self-memory theory. Finally, the conclusions are drawn that relatively to GM (1,1), the grey self-memory model has higher accuracy, and it not only can predict the time sequence of seepage pressure in the Nuer reservoir accurately but also provide a new method for the development trend of seepage flow in the hydraulic engineering in the future.
An Analysis of the Cognitive Ability of Knowledge Mapping Homeschooling Based on the Rasch Model
Authors: Bai Fubao , Wen Yan
Published: May 2022

Family cognition is a representation of the quality of family harmony, so family cognition score is an important exercise at the family level. The research based on the hybrid Rasch model is an important reference point. This study is based on the mixed Rasch model in item response theory. Firstly, descriptive statistical analysis is carried out on the family level, which is sorted according to the total score and specific proportion, and the difficulties and differences of family members in multiple choice questions at different levels are compared. Then, the number of potential categories estimated using the hybrid rush model is discussed in two cases. In one case, the number of categories is known and the categories are more detailed, so as to facilitate comparison and promote the harmony of family members.
Research on Intelligent Bodybuilding System Based on Machine Learning
Authors: Chen Chen
Published: May 2022

In recent years, people’s health is facing many challenges as their workload is increasing and their lives are becoming more and more stressful. In this context, healthy living has become a topic of concern and more and more people are choosing to promote their bodies through fitness. To address these existing problems in action recognition research, this paper designs and implements a machine learning-based intelligent fitness system to monitor three important parameters in physical activity: the type of action, the number of actions, and the period of action. Through the action recognition algorithm and the period calculation method, the three important parameters of action type, number of actions, and action period are calculated to generate a more comprehensive description of the limb actions. Experiments are conducted to show that the proposed deep neural network learns well on small datasets, achieving 97.61% action recognition accuracy and SVM achieving over 96% recognition accuracy.
Assessment of the Effects of Seed Storage Time on Germination Rate and Performance Evaluation of Ethiopian Faba Bean (Vicia faba L.) Varieties for Yield and Related Traits
Authors: Gadissa Fekadu , Kassaye Zemedkun , Abiyu Solomon
Published: May 2022

In Ethiopia, faba bean (Vicia faba L.) varieties are important and widely used as a source of food and cash source to large number of subsistence farmers. However, their production and productivity is below the world’s average partly because of lack of their sustainable performance in the current scenario of climate change. Therefore, the present study was designed to test the effects of seed storage time and to evaluate the performance of 31 faba bean varieties collected from Holeta, Kulumsa and Sinana agricultural research systems, Ethiopia. The study involved germination test and field experiment that was laid out using randomized complete block design (RCBD) and conducted at multiple test locations. Data were collected on qualitative and quantitative traits and analyzed using SAS version 9.0, and MINITAB® Release 19. Accordingly, most of the varieties showed a promising germination rate regardless of their storage duration suggesting their sustainable performance under suitable storage conditions. Most of the qualitative and quantitative traits showed a wide range of variations revealing their stable performance and better chance for further improvement. Analysis of variance also revealed a highly significant (

p
<
0.001

) variation for several of the traits suggesting maintenance of the original diversity that could be important in further selection breeding. Likewise, high genetic advance coupled with high heritability and genotypic coefficient of variation together with wide range of variations in both PCV and GCV observed in several of the quantitative traits suggest their sustainable performance and significance in further effective selection. Moreover, a promising high yielding varieties such as Dida1, Welki, Hachalu, Ashebeka and Obse have been identified for further use. Clustering grouped the varieties into three clusters implying significant amount of genetic variability among them. Overall, the results generated could be used as a baseline information for improving faba bean production and productivity. However, to exploit more and determine the actual performance of the varieties more markers such as molecular markers (DNA based) are recommended.
Analyzing IoT Attack Feature Association with Threat Actors
Authors: Shafiq Muhammad , Gu Zhaoquan , Nazir Shah , Yadav Rahul
Published: May 2022

Internet of Things (IoT) refers to the interconnection via the Internet of computing devices embedded in everyday objects, enabling them to send and receive data. These devices can be controlled remotely, which makes them susceptible to exploitation or even takeover by an attacker. The lack of security features on many IoT devices makes them easy to access confidential information, issue commands from a distance, or even use the compromised device as part of a DDoS attack against another network. Feature selection is an important part of problem formulation in machine learning. To overcome the above problems, this paper proposes a novel feature selection framework RFS for IoT attack detection using machine learning (ML) techniques. The RFS is based on the concept of effective feature selection and consists of three main stages: feature selection, modeling, and attacks detection. For feature selection, three different models are proposed. Based on these approaches, three different algorithms are proposed. A set of 40 features was included in the model, derived from combinatorial optimization and statistical analysis methods. Our experimental study shows that the proposed frame work significantly improves over state-of-the-art cyberattacks techniques for time series data with outliers.
The Influence of Soil Saturation on the Geotechnical Test Results
Authors: Guo Jianxiang , Wei Xiaobin
Published: May 2022

The consistency limits are important properties of soil. The fall cone test method has a good repeatability, and the operator’s judgement has little effect on the results. This paper presents a new sample preparation method, in which the sedimentation method and consolidation test are combined, to prepare the saturated specimens for fall cone test for determining the consistency limits, and the sample prepared by this new method can be considered completely saturated. For the specimens prepared by the previous sample preparation method, the decrease in the water content leads to a decrease in the degree of saturation of soil. The test results show that the specimens prepared by this new method can reach a low water content, and the minimum penetration depths are as low as 2 mm, and the plastic limit could be obtained directly. In addition, the van shear test results show that the unsaturated specimens have larger values of undrained shear strength than the saturated specimens at the same water content, which could explain the difference of consistency limits obtained from different specimen preparation methods.
Study on the Expression Profile of Autophagy-Related Genes in Colon Adenocarcinoma
Authors: Hou Mingyu , Ma Jiakang , Ma Jun
Published: May 2022

Colon adenocarcinoma (COAD) is a common digestive tract tumor. Autophagy-related genes (ARGs) may play an obbligato role in the biological processes of COAD. This study was aimed at exploring the role of ARGs in COAD. Clinical data and RNA sequencing data of tumor and healthy samples were obtained from The Cancer Genome Atlas (TCGA), and discrepantly expressed ARGs were screened. Statistical differences of ARGs were performed with Gene Ontology (GO) functional annotation and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Eight ARGs were selected by univariate Cox and multivariate Cox regression. Kaplan–Meier (K-M) and multivariate receiver operating characteristic (multi-ROC) were used to check the fitness of the model. Among 398 COAD samples and 39 normal samples obtained from the TCGA database, 37 differentially expressed ARGs were screened. In the training group, eight prognostics-related ARGs (MTMR14, VAMP3, HSPA8, TSC1, DAPK1, CX3CL1, ATG13, and MAP1LC3C) were identified by Cox regression. A gene signature risk prediction model was constructed base on 8 autophagy-related genes. The survival time of the low-risk group was longer than the high-risk group, and the AUC of the model was 0.794. Univariate and multivariate Cox regression analysis showed that age and riskscore were the independent predictor. In conclusion, the prognosis model we built based one ARGs of COAD patients can estimate the prognosis of patients in clinical treatment.