bluuebunny/crossref_metadata_2025 huggingface dataset:
Towards a More Theory-Driven BCI Using Source Reconstructed Dynamics of EEG Time-Series
Authors: Janapati Ravichander , Dalal Vishwas , Sengupta Rakesh , Desai Usha , Raja Shekar P. V. , Kollem Sreedhar
Published: May 2022

Currently, the operational electroencephalography (EEG)-based brain–computer interfaces (BCIs) suffer from problems of BCI latency/lag issues, which restricts the use of interfaces impractical scenarios. One of the reasons behind the present challenges is the application of a purely data-driven approach to the BCI pipeline. Although BCI applications have improved significantly with the research in the fields of artificial intelligence (AI) and machine learning (ML), fundamental issues of data-driven training restrict the latency that can be achieved under current BCI paradigms. This work explores the possibility of future BCI using a combination of data-driven and theory-driven methods. In this study, an EEG-BCI dataset from steady-state visually evoked potentials (SSVEPs) is applied, where the SSVEP signals contain, source components from the occipital, parietal and frontal regions of the brain. Source reconstruction is done with the combination of independent component analysis (ICA) and low-resolution electromagnetic tomography analysis (LORETA). This method was able to predict BCI classification labels 5[Formula: see text]s earlier, based on pre-recorded signals from the scalp. The novelty of the current contribution lies in utilizing the source reconstructed EEG time-series for BCI classification, which allows for retention of classification accuracy up to 70% while working with the reduced data dimensionality. Implementation of this algorithm will allow a significant reduction in lag in online BCIs.
Allocation of Resources for Cloud Survivability in Smart Manufacturing
Authors: Nong Mengxin , Huang Lingfeng , Liu Mingtao
Published: May 2022

With the development of virtualization technology, cloud computing has emerged as a powerful and flexible platform for various services such as online trading. However, there are concerns about the survivability of cloud services in smart manufacturing. Most existing solutions provide a standby
Virtual Machine (VM)
for each running VM. However, this often leads to huge resource waste because VMs do not always run at full capacity. To reduce resource waste, we propose a smart survivability framework to efficiently allocate resources to standby VMs. Our framework contains two novel aspects: (1) a prediction mechanism to predict the resource utilization of each VM in order to reduce the number of standby VMs; and (2) a nested virtualization technology to refine the granularity of standby VMs. We will use an open-source cloud simulation platform named cloudsim, with real-world data, to verify the feasibility of the proposed framework and evaluate its performance. The proposed
Smart Survivable Usable Virtual Machine (SSUVM)
will predict resource utilization of VMs on Rack1 periodically. When errors happen in VMs, the framework will allocate standby resources according to the predicted result. The SSUVM will receive the latest running status of the failed VM and its mirror image to recover the VM's work.
SIGCSE TS 2022 report
Authors: Merkle Larry , Doyle Maureen
Published: May 2022

The SIGCSE Technical Symposium is SIGCSE's flagship conference and this past March we held SIGCSE's 53nd technical symposium. SIGCSE TS 2022 was held March 3-5, 2022, in Providence, Rhode Island and online. Virtual attendees participated through the Pathable platform. SIGCSE TS 2022 was our first hybrid conference, and it opened with some trepidation about stepping into the unknown. However, our community showed patience and support through this adventure, and we thank you.
Koli Calling 2022 call for participation
Authors: Petersen Andrew , Jormanainen Ilkka
Published: May 2022

We invite you to submit a paper or poster to the 22nd Koli Calling International Conference on Computing Education Research (Koli Calling 2022), to be held on 17-20 November 2022.
CSEdResearch.org
Authors: McGill Monica
Published: May 2022

Sharing your survey on social media? Better think again. Bots are ever present and they really, really like to take surveys that are floating around---particularly if they are shared on social media, with Twitter being the most delightful place for bots to swarm. This is especially true if a survey provides incentives. How do we know? We've learned the hard way.
Member spotlight
Authors: Miller Jeffrey , Wallace Charles , Decker Adrienne
Published: May 2022

In this feature of the Bulletin, we highlight members of the SIGCSE community. This issue's spotlight is Adrienne Decker, Assistant Professor in the Department of Engineering Education and Adjunct Assistant Professor in the Department of Computer Science and Engineering at the University at Buffalo.
Machine Learning Aided Predictions for Capacity Fade of Li-Ion Batteries
Authors: Penjuru N. M. Hitesh , Reddy G. Vineeth , R. Nair Manikantan , Sahoo Soumili , Mayank  , Jiang Jason , Ahmed Joinal , Wang Huizhi , Roy Tribeni
Published: May 2022

Future demands high power and high energy density devices that can be sustainably built and easily maintained. It is seen that among various energy storage devices, the demanding role lithium-ion batteries play in powering electronic gadgets to electric vehicles, is highly significant. Hence, the researchers around the world are trying to solve the riddles of the lithium-ion batteries and make it more efficient. One such problem that researchers are trying to solve is battery degradation and capacity fade. In this work, we made a battery forecasting model that can predict the capacity fade using electrochemical impedance spectroscopy (EIS) data. Two machine learning techniques like, support vector regression (SVR) and multi-linear regression (MLR) were utilized to analyse the data and predict the capacity fade for lithium-ion battery. Principal component analysis was also carried out to determine the most relevant feature from the data. From the analysis it was found that that SVR has a better prediction accuracy than MLR or pre-existing Gaussian process regression (GPR) results and among the two kernels of support vector regression, radial basis function (rbf) kernel has better prediction accuracy with R2 score of 0.9194 than the linear kernel with R2 score of 0.6559.
Influences of Impurity Incorporation in Electroplated Cu on the SnAgCu and Ni-Containing SnAgCu Solder Joints
Authors: Chen Po-Kai , Li Yu-Ju , Yen Yee-Wen , Chen Chih-Ming
Published: May 2022

SnAgCu and Ni-containing SnAgCu alloys are Pb-free solders widely used to join with Cu to construct the solder joints. Electrodeposition is a technology commonly used to fabricate Cu but co-deposition of organic impurities originating from additives is an inevitable reliability issue. This study investigates the impurity effect on the voiding propensity in the two solder joints (SnAgCu/Cu and SnAgCu-Ni/Cu) subjected to thermal aging at 200 °C. Results show that a high level of impurity incorporation causes massive void propagation along the SnAgCu/Cu and SnAgCu-Ni/Cu interface. Reduction of the impurity concentration by precise control of the additive formulas can weaken the impurity effect and effectively suppress the void propagation. The weakening phenomenon of the impurity effect is more pronounced in the SnAgCu-Ni/Cu joint, indicating that suppression of the Cu3Sn growth as well as Kirkendall voids by Ni addition is also helpful in reducing the influences of impurities.
Optimization of Pricing and Freshness-Keeping Effort in Fresh e-Commerce Supply Chain considering Online Comments
Authors: Wang Quanli , Gu Bojun , Fu Yufang
Published: May 2022

Considering that online comments play an important role in operational decisions of a fresh e-commerce supply chain, we construct single-stage and two-stage models for fresh produce supply chain consisting of a supplier and a fresh e-commerce platform. Utilizing the Stackelberg game and two-stage repeated game, the profit functions of the supplier and platform are established, and then, the optimal retail price and freshness-keeping effort are derived. In addition, to improve the accuracy of models in describing practical problems, we construct an extended two-stage model and a third-party logistics model. Furthermore, we compare the optimal strategies under different models. Our results show that, firstly, the optimal retail price and freshness-keeping effort of supplier and platform vary in different models and online comments play a positive effect on supplier and platform’s profits. Secondly, compared with the single-stage model, the fresh e-commerce supply chain grabs more market share and profits under the two-stage model. Lastly, online comments vary in different dominance scenarios and may cause competition between supplier and platform for supply chain dominance.
Dual‐Channel Effect of Job Insecurity on Knowledge Workers’ Innovative Behavior
Authors: Li Yuan , Li Zhongwu
Published: May 2022

Job insecurity reflects the desire and expectation of organizational managers for employees’ exhibition of innovative behavior. Ubiquitous and inevitable, it has gradually become a concern psychological problem for job survival and stability. As a key driver of innovation, employee innovation depends heavily on knowledge workers, who are best able to spot problems and identify and capture opportunities. Based upon the transactional theory of stress and coping (TTSC), this paper discusses the influencing mechanism of knowledge workers’ job insecurity and innovative behavior in enterprises, emphatically analyzes the mediating effects of two coping strategies, i.e., proactive work behavior and working withdrawal behavior, and verifies the moderating effect of organizational climate for innovation. With the data from 665 questionnaires of enterprise knowledge workers, this paper shows that job insecurity can influence knowledge workers’ innovative behavior either positively through proactive work behavior or negatively through working withdrawal behavior, thus forming a dual‐channel effect model of influencing their innovative behavior, and that organizational climate for innovation has a moderating effect on the relationship between job insecurity and proactive work behavior/working withdrawal behavior. The organizational innovation climate played a moderating role between job insecurity and proactive work behavior and work withdrawal behavior and detected the value of the boundary where the organizational innovation climate played a mediating role.
Research on the Development Path of Manufacturing Industry and Its Economic Effect Based on Computational Visualization
Authors: Zhou Shiyuan , Liao Zhixiong , Yang Xiaoqin
Published: May 2022

In order to improve the analysis effect of the manufacturing development path and improve the economic benefits of the manufacturing industry, this paper combines the computer visualization technology to analyze the manufacturing development path and its economic effect. Moreover, this paper introduces the minimum ill-posedness criterion in the optimal placement criteria of time-domain sensors and the modal guarantee criterion in the optimal placement criteria for frequency-domain sensors. In addition, in this paper, the optimal arrangement of sensors is carried out based on the above two criteria, and the improved monkey swarm algorithm is applied to the optimization problem of the sensor of the visual system, and an intelligent computer visualization system is constructed. The experimental research results show that the research model of the manufacturing development path and its economic effects based on computational visualization proposed in this paper has certain practical effects.
Nanotechnology Role Development for COVID-19 Pandemic Management
Authors: Owida Hamza Abu , Al-Nabulsi Jamal I. , Turab Nidal M. , Louzi Nawal
Published: May 2022

The global outbreak of coronavirus disease has sent an ominous message to the field of innovative and advanced technology research and development (COVID-19). To accomplish this, convectional technology and recent discoveries can be combined, or new research directions can be opened up using nanotechnology. Nanotechnology can be used to prevent, diagnose, and treat SARS-CoV-2 infection. As the pandemic spreads, a thorough examination of nanomaterials' role in pandemic response is highly desirable. According to this comprehensive review article, nanotechnology can be used to prevent, diagnose, and treat COVID-19. This research will be extremely useful during the COVID-19 outbreak in terms of developing rules for designing nanostructure materials to combat the outbreak.
A Cohort Study on the Comparison of Complications, Short‐Term Efficacy, and Quality of Life between Thoracoscopic Surgery and Traditional Surgery in the Treatment of Rib Fractures
Authors: Wang Dongdong , Xu Yongdong , Wang Qingqing , Xu Yueping , Wang Xiaoqi
Published: May 2022

Objective. A case‐control study was conducted, to assess the complications, short‐term effectiveness, and quality of life of video‐assisted thoracoscopic surgery with conventional surgery in the treatment of rib fractures. Methods. From February 2018 to April 2021, 100 patients with rib fractures who required surgical treatment at the hospital were selected. Patients were randomly divided into control and study groups. The study group received thoracoscopy‐assisted rib internal fixation, and the control group received traditional open reduction and internal fixation for rib fractures. The treatment effect, postoperative complication rate, surgery‐related indicators, stress response, blood gas indicators, VAS (visual analog scale) pain score, and SF‐36 quality of life score were compared between the two groups. Results. The total effective rate of the study group was higher than that of the control group, and the difference was statistically significant (P < 0.05). The postoperative complications in the study group were significantly lower than those in the control group (χ2‐5.317; P < 0.05), but there was no significant difference in hospitalization costs between the two groups (P > 0.05). The operation time, intraoperative blood loss, incision length, drainage tube placement time, postoperative activity time, and hospital stay in the study group were significantly lower than those in the control group. The SF‐36 score and VAS score in the study group were higher than those in the control group (P < 0.05). Compared with the two groups after the operation, the levels of PaO2, SaO2, and PaO2/FiO2 in the study group were significantly higher than those in the control group (P < 0.05). Before surgery, there was no significant difference in stress response indicators such as cortisol, blood sugar, and C‐reactive protein between the two groups (P > 0.05), but there was no significant difference in stress response indicators after surgery (P > 0.05). Cortisol, blood sugar, C‐reactive protein, and other indicators were increased in both groups, but compared with the control group, the study group had decreased postoperative cortisol, blood sugar, C‐reactive protein, and other stress response indicators (P < 0.05). Conclusion. There is a significant difference between thoracoscopic surgery and traditional surgery in the treatment of rib fractures. The probability of postoperative complications of thoracoscopic surgery is lower, and the operation time, intraoperative blood loss, and incision length are better. The pain of patients before and after the operation is significantly reduced, the quality of life is improved greatly, and the stress response is weak.
Evaluation of Fatigue Behavior of Asphalt Layers Containing Nanosilica Modified Tack Coat
Authors: Rohani Behrang , Akbari Mahdi , Hosseini Sayyed Ali
Published: May 2022

Generally, the maintenance of asphalt pavements contributes a significant portion of the national capital of the countries. Rutting and cracking cause extensive damage to asphalt pavements, although fatigue cracks are more common in asphalt pavements. Adhesion and bonding between asphalt layers are among the factors that affect the durability of asphalt pavement and play a major function in maintaining the integrity of the pavement. On the other hand, using nanomaterials is regarded as one of the options to improve the properties and performance of bitumen. Therefore, this study aimed to evaluate the fatigue behavior of asphalt layers containing nanosilica modified tack coat (NSMTC). To this aim, it was used a four-point bending (4 PB) beam fatigue test. The loading is the semisinusoidal type with 10 Hz frequency, without rest, and at a temperature of 20°C. The controlled strain state (at three strain levels of 400, 550, and 700 με) is implemented. The results revealed the increased fatigue life in the specimen of asphalt beam containing NSMTC. At different strain levels (i.e., 400, 550, and 700 με), the fatigue life of beams with NSMTC increased by 18, 15, and 57%, respectively. Furthermore, the cumulative dissipated energy of specimens containing NSMTC increased by 37, 42, and 60% compared to specimens containing unmodified tack coat (UMTC) for strain levels of 400, 550, and 700 με, respectively.
Sitagliptin Alleviates Radiation-Induced Intestinal Injury by Activating NRF2-Antioxidant Axis, Mitigating NLRP3 Inf--lammasome Activation, and Reversing Gut Microbiota Disorder
Authors: Huang Shanshan , Huang Yongbiao , Lin Wanling , Wang Lei , Yang Yang , Li Piao , Xiao Lei , Chen Yuan , Chu Qian , Yuan Xianglin
Published: May 2022

Radiation-induced intestinal injury is a common and critical complication of radiotherapy for pelvic or abdominal tumors, with limited therapeutic strategies and effectiveness. Sitagliptin, a dipeptidyl peptidase IV (DPP4) inhibitor, has previously been reported to alleviate total body irradiation- (TBI-) induced damage of hematopoietic system in mice, but its effect on radiation-induced intestinal injury remains unclear. In this study, we confirmed that Sitagliptin could not only protect mice from death and weight loss caused by whole abdominal irradiation (WAI) but also improve the morphological structure of intestine and the regeneration ability of enterocytes. In addition, Sitagliptin significantly inhibited the production of radiation-induced proinflammatory cytokines and reduced the number of apoptotic intestinal epithelial cells and γ-H2AX expression. In vitro, we demonstrated that Sitagliptin protected HIEC-6 cells from ionizing radiation, resulting in increased cell viability and reduced DNA damage. Mechanistically, the radiation protection of Sitagliptin might be related to the upregulation of NRF2 level and the decrease of NLRP3 inflammasome activity. Importantly, Sitagliptin significantly restored radiation-induced changes in bacterial composition. In conclusion, our results suggested that Sitagliptin could reduce WAI-induced intestinal injury in mice, which may provide novel therapeutic strategy for radiation-induced intestinal injury.
Soil Nutrient Balance and Soil Fertility Status under the Influence of Fertilization in Maize-Wheat Cropping System in Nepal
Authors: Rawal Nabin , Pande Keshab Raj , Shrestha Renuka , Vista Shree Prasad
Published: May 2022

Soil nutrient balance is affected by nutrient management in crops. A poor nutrient management technique results in an imbalance in the soil nutrient status which could have a long-term negative impact on crop production. The current study was carried out to assess the effect of different rates of nitrogen (N), phosphorus (P), and potassium (K) on soil nutrient balance in a maize-wheat cropping system in Cambisols of Khumaltar, Lalitpur, Nepal during 2019/20 and 2020/21. The experiment included three-factor randomized complete block design with three doses of each N, P, and K which was replicated three times. There was a remarkable change in soil pH, soil organic carbon (SOC), and total N, P, and K contents of soil over a period of time with the application of different doses of NPK. Soil pH changed from 5.98 to 5.53, SOC increased from 11.7 to 16.8 g·kg−1, total N decreased from 1264 to 1177 mg·kg−1, available P2O5 declined from 214 to 63.6 mg·kg−1, and available K2O decreased from 71.7 to 24.8 mg·kg−1 with varying rates of NPK after four cropping seasons. Furthermore, partial, apparent, and net N, P, K balance were predominantly negative in all the fertilizer treatments, but the magnitude was lower under higher nutrient rates and positive partial N balance was noticed in higher N levels. The depletion of native P and K pools even at higher application rates was attributed to higher crop removal over time as compared to inputs. Therefore, continuous application of balanced fertilizers is crucial in maintaining the fertility of soil and productivity of crops.
Analysis of Relevant Factors Affecting the Pregnancy Rate of Frozen-Thawed Embryo Transfer Cycle
Authors: Liu Ning , Wang Yuhong , Lu Jing , Zhang Xihui , Zhang Yunjing , Zhao Haijun , Zhang Yijiao , Chang Wenliang
Published: May 2022

Objective. The aim of this study is to explore the relevant factors affecting the pregnancy rate of frozen-thawed embryo transfer cycle. Methods. The clinical data of 931 patients who underwent artificial cycle preparation for endometrial FET from April 2017 to November 2020 in the reproductive center of our hospital were retrospectively analyzed. Results. According to the pregnancy situation, the patients were divided into 450 cases of pregnancy and 481 cases of biochemical pregnancy. The univariate analysis of FET biochemical pregnancy showed that there were statistically significant differences between pregnancy and biochemical pregnancy in terms of years of infertility, age, endometrial thickness, P level, E2/P, and the number of high-quality embryos (

P
<
0.05

). Multivariate analysis of pregnancy showed that age <30 years was a protective factor for biochemical pregnancy and endometrial thickness <8 mm and E2/P < 0.3 were risk factors (

P
<
0.05

). Conclusion. The regulation of endometrial thickness and E2/P serves as the key of treatment for patients undergoing FET using artificial cycle preparation for endometrial transfer, and it contributes to improve the pregnancy rate; also, the patient's age is an important indicator influencing the pregnancy rate.
Credit Risk Assessment Modeling Method Based on Fuzzy Integral and SVM
Authors: Zhou Mingyi
Published: May 2022

With the development of financial globalization and financial market volatility, credit risk has become more prominent and serious, and how to establish an effective enterprise credit evaluation system and bank credit risk evaluation model, provide scientific quantitative decision-making basis for bank decision-making, reduce non-performing loans, and improve the quality of credit assets is a common research topic faced by domestic banks. At present, domestic banks have not been effective to establish risk prevention as the core of credit culture and long-term mechanism, the existence of nonperforming loans is still not fully resolved, new risks continue to appear, and there is a lack of a perfect and effective credit risk evaluation system. With the development of the Internet and financial institutions and the fusion, banks and financial institutions drastically increase the recorded data, and this provides a good prerequisite for the application of intelligent algorithms. In view of the shortcomings of BP neural network in the establishment of credit risk assessment model, such as poor promotion ability and long prediction time, and considering that support vector machine (SVM) can deal with some multi-classification problems, this paper introduces SVM method into the field of bank credit risk assessment and establishes an optimization model of credit risk assessment. This paper discusses the structure and algorithm principle of SVM classification method and proposes an integrated SVM based on fuzzy integral to solve this kind of problem. The results show that the algorithm can effectively improve the prediction accuracy, solve the problem of high computation cost, reduce the occupied memory space, improve the operation efficiency, shorten the training time, and provide a more reliable basis for the rapid and effective evaluation of bank credit risk. On the one hand, the research results expand the application of artificial intelligence technology in the field of economic research; the evaluation model can continuously and accurately measure credit risk is obtained, which provides the necessary basis for upgrading and optimizing credit decision-making, so it has high theoretical value and practical value.
Rice Drought Damage Assessment Using AMSR-E Data Inversion of Surface Temperature
Authors: Wang Ying , Zhang Jianping , Li Guochun
Published: May 2022

The extreme drought events caused by global warming have become one of the major issues of general concern all over the world. It is estimated that over the past 50 years, the average annual drought-affected area has reached more than 200,000 km2, resulting in a global economic loss of US$6-8 billion, far exceeding other meteorological disasters. Therefore, conducting real-time and effective drought monitoring research is of great significance for issues such as climate change, drought defense, water resources management, and protection in various regions. Rice is the largest food crop in China and plays a pivotal role in food production. Drought is often regarded as one of the most important stress factors. Scientific, accurate, and timely assessment of the impact of drought on rice yield is essential for improving crop drought resistance and ensuring food production. In this study, based on the meteorological data, rice growth period and yield of the main rice planting areas in Chongqing Yangtze River Basin, and based on the drought index of passive microwave remote sensing observation data (AMSR-E), a statistical model of rice meteorological yield and drought index under the influence of drought is established. A rice drought disaster assessment is carried out. The results of the disaster assessment indicate that under the influence of drought, the rice yield reduction rate of representative sites in Chongqing Yangtze River Basin is between 3% and 10%.
Towards Development of Machine Learning Framework for Enhancing Security in Internet of Things
Authors: Paricherla Mutyalaiah , Babu Sallagundla , Phasinam Khongdet , Pallathadka Harikumar , Zamani Abu Sarwar , Narayan Vipul , Shukla Surendra Kumar , Mohammed Hussien Sobahi
Published: May 2022

An IoT system is a smart network that connects all items to the Internet and exchanges data using Internet Engineering Task Force established protocols. As a consequence, everything is instantly accessible from any place and at any time. The Internet of Things (IoT) network is built on the backbone of tiny sensors embedded in common objects. There is no need for human intervention in the interactions of IoT devices. The Internet of Things (IoT) security risk cannot be ignored. Untrusted networks, such as the Internet, are utilized to provide remote access to IoT devices. As a result, IoT systems are susceptible to a broad range of harmful activities, including cyberattacks. If security problems are not addressed, critical information may be hacked at any time. This article describes a feature selection and machine learning-based paradigm for improving security in the Internet of Things. Because network data are inherently abundant, it must be reduced in size before processing. Dimension reduction is the process of constructing a subset of an original data collection that removes superfluous content from the essential data set. Dimension reduction is a data mining approach. To minimize the number of dimensions in a dataset, linear discriminant analysis (LDA) is used. Following that, the data set with fewer dimensions is put into machine learning predictors as a training set. The effectiveness of machine learning approaches has been assessed using a range of criteria.
A Data Collection Method for Mobile Wireless Sensor Networks Based on Improved Dragonfly Algorithm
Authors: Yue Yinggao , Lu Dongwan , Zhang Yong , Xu Minghai , Hu Zhongyi , Li Bo , Wang Shuxin , Ding Haihua
Published: May 2022

For the sensing layer of the Internet of Things, the mobile wireless sensor network has problems such as limited energy of the sensor nodes, unbalanced energy consumption, unreliability, and long transmission delay in the data collection process. It is proved by mathematical derivation and theory that this is a typical multiobjective optimization problem. In this paper, the optimization goal is to minimize the energy consumption and improve the reliability under time-delay constraints and propose a path optimization mechanism to optimize the mobile Sink of mobile wireless sensor networks based on the improved dragonfly optimization algorithm. The algorithm takes full advantage of the abundant storage space, sufficient energy, and strong computing power of the mobile Sink to ensure network connectivity and improve network communication efficiency. Through simulation comparison and analysis, compared with random movement method, artificial bee colony algorithm, and basic dragonfly optimization algorithm, the energy consumption of the network is reduced, the lifespan of the network is increased, and the connectivity and transmission delay of the network are improved. The proposed algorithm balances the energy consumption of the sensors nodes to meet the network service quality and improve the reliability of the network.
Optimizing the Effectiveness of “Internet +” Contest to Deepen the Reform Path of Innovation and Entrepreneurship Education in Colleges and Universities
Authors: Jia Fengzhen , Wang Rong , Huo Jiaofei
Published: May 2022

In the Internet environment, college innovation and entrepreneurship will face more opportunities and challenges. “Internet +” simply means “Internet + traditional industries.” With the development of science and technology, the use of information and Internet platforms enables the integration of the Internet and traditional industries and uses the advantages and characteristics of the Internet to create new development opportunities. University learners are one of the most important contact groups on the Internet. They are generally familiar with the Internet and are good at using Internet channels and Internet thinking to solve problems. Therefore, they are able to grasp opportunities and achieve breakthroughs. Innovation and entrepreneurship education is aimed at cultivating talents with basic entrepreneurial qualities and pioneering personality, and it is an education to cultivate innovative thinking and entrepreneurial ability for the whole society in stages and at different levels. How to effectively use the dividends of Internet entrepreneurship to realize their own transformation and growth is a topic worth studying. Therefore, this paper takes the life cycle of “Internet +” college students’ innovation and entrepreneurship competition as an example, summarizes the achievements and problems of a university in holding the competition, and puts forward countermeasures and suggestions for optimizing and organizing the competition on this basis. Experiments show that the quality of the competition itself, the relevant rules of the competition, the impact of the external environment, and home-school cooperation will have a greater impact on students’ innovation and entrepreneurship performance.
Clothing Nanometer Antimite and Antibacterial Based on Deep Learning Technology
Authors: Liu Hai
Published: May 2022

With the improvement of people’s living standards, the living conditions and environment of residents have changed, and there are also more and more electrical appliances such as air conditioners, air purifiers, and humidifiers. People’s living environment and office environment are increasingly closed, which makes it easy for mites to breed and multiply. The changes in the living environment have made many people more and more aware of health and safety issues. Under these conditions, it is mainly used in the field of biomedicine. In the high‐tech field, nanomaterials with antimite and antibacterial properties have entered the field of clothing and home textiles. With the advancement and development of science and technology, nanomaterial technology tends to mature and becomes a major player in the field of clothing. However, nanosilver alone has some defects, such as large nanoparticles, poor antimite and antibacterial effect, high cost, easy oxidation, and strong toxicity. Therefore, the preparation of new nanocomposite materials is of great significance for the application of nanotechnology to the field of clothing. In this paper, the antimite and antibacterial properties of different nanomaterials on clothing were explored through deep learning technology combined with experimental methods. According to the experiments in this paper, the Ag/TiO2(ATA) nanocomposites have obvious antibacterial and acarid effects, and the antibacterial and acarid rates are close to 100% under the conditions of visible light and dark light.
Comprehensive Analysis of RELL2 as a Potential Biomarker Associated with Tumor Immune Infiltrating Cells in a Pan-Cancer Analysis
Authors: Musha Kadeerjiang , Ge Xinqi , Ablikim Nuraliya , Lu Bing , Chen Chen , Huang Jianfei
Published: May 2022

Background. Receptor expressed in lymphoid tissues-like 2 (RELL2), which is a member of RELT family, is closely associated with the plasma membrane and acts as a modulator for RELT signaling. Overexpression of RELL2 induces the activation of MAPK14/p38 cascade and apoptosis. However, whether RELL2 contributes to cancers remains unclear. Here, we examined its role in cancer patient prognosis and various tumors. Methods. We used several bioinformatics methods, specifically gene set enrichment analysis (GSEA), ScanNeo, and ESTIMATE, to analyze the CCLE dataset, GTEx dataset, and TCGA dataset. We investigated the possible association of RELL2 with the microsatellite instability (MSI) of various tumors, tumor mutational burden (TMB), immune checkpoint, immune neoantigens, immune microenvironment, and patient prognosis. Result. RELL2 is highly expressed in cancer compared with normal tissues. RELL2 expression is linked with worse progression-free interval and overall survival in numerous cancers. In most cancers, high RELL2 expression was related to a poor prognosis. RELL2 expression was significantly associated with the tumor microenvironment, MSI, and TMB. RELL2 expression is strongly associated with phenotypes that are of major clinical significance, particularly those associated with immune neoantigens and the expression profiles of immune checkpoint genes in pan-cancer. RELL2 expression strongly linked with the expressions of methyltransferases and DNA repair genes. It also significantly correlated with multiple signaling pathways through gene set enrichment analysis. Conclusion. RELL2 may be a prognostic biomarker in pan-cancer and may have an important function in tumorigenesis and progression.
circRNA TCFL5 Promote Esophageal Cancer Progression by Modulating M2 Macrophage Polarization via the miR-543-FMNL2 Axis
Authors: Lin Chengbin , Xi Yong , Yu Hongyan , Wang Zheng , Chen Xiaohan , Shen Weiyu
Published: May 2022

Objective. The mechanism of circRNA on M2 macrophage polarization, which contributes to esophageal cancer, remains unclear. This study is aimed at clarifying the mechanism of circRNA on esophageal cancer by regulating M2 macrophage polarization. Methods. The expression of circRNA TCFL5 and miR-543 was detected by qRT-PCR. Western blot was used to detect the expression of FMNL2 and CD163. CCK-8 and transwell assay was used to detect the proliferation, migration, and invasion of Eca109 and KYSE150, respectively. Flow cytometry was used to detect the CD163 positive cells. The contents of IL-10, TGF-β, TNF-α, IL-6, and IL-1β were detected by ELISA. A dual-luciferase reporter system was used to detect the regulation of miR-543 to circRNA TCFL5 and FMNL2. Results. 156 upregulated circRNAs and 91 downregulated circRNAs in esophageal cancer tissues were identified, and the expression of circRNA TCFL5 showed the most significant upregulation. Overexpression of circRNA TCFL5 promotes proliferation, invasion, and migration of Eca109 and KYSE150 and promotes tumor growth in vivo. circRNA TCFL5 served as a sponge of miR-543, and FMNL2 was a downstream target gene of miR-543. circRNA TCFL5 promotes cell proliferation, migration, and invasion of Eca109 and KYSE150 by modulating the miR-543/FMNL2 axis. Macrophage M2 polarization promoted proliferation, invasion, and migration of Eca109 and KYSE150 cells, and circRNA TCFL5 mediated macrophage M2 polarization by regulating the FMNL2/miR-543 axis. Conclusion. In the present study, we identified that circRNA TCFL5 was dramatically upregulated in esophageal cancer, and circRNA TCFL5 promotes esophageal cancer progression by modulating M2 macrophage polarization via the miR-543-FMNL2 axis, which provides a potential target for the treatment of esophageal cancer.
Design and Construction of Hybrid Music Recommendation System Integrating Music Gene
Authors: Zhao Xuelin
Published: May 2022

In order to improve the effect of mixed music recommendation, this study combines music genes to construct a mixed music recommendation system. From the analysis of the complexity of each joint inference algorithm, GP + RKF has the highest complexity compared with the other three joint inference algorithms. Moreover, this study verifies it through the running time of the simulation experiment, using the growth method as the way of mutation. In addition, while adopting the optimal individual retention strategy, this study makes the eigenvalues of the input matrix IX all fall within the unit circle or unit circumference and makes the maximum fitness value of the individuals in the population equal to the global optimal fitness value. Finally, this study constructs an intelligent system. Through the experimental research, it can be seen that the hybrid music recommendation system based on the fusion of music genes proposed in this study has a good music recommendation effect.
Design of Vocal Music Teaching System Platform for Music Majors Based on Artificial Intelligence
Authors: Wang Xiaoxiang
Published: May 2022

The cyberspace consisting of information technology, artificial intelligence (AI), communication systems, computer systems, automatic control systems, digital devices, and the applications, services, and data they carry is advancing in an unprecedented way. It is no longer a dream to assist the development of pedagogical expert systems to solve the current problems of insufficient teachers and single teaching tools in music pedagogy reform and to realize the sharing of teaching resources. Artificial intelligence system under music education and education not only breaks the traditional music education model but also promotes the development of music education. This paper introduces the principle of artificial intelligence and analyzes the problems faced by university music education, and the implementation method of vocal education system based on artificial intelligence for music majors is also specifically studied in this paper. This mainly involves the design of the system architecture, such as the system architecture, which is designed to meet the requirements of the whole system. A survey of 100 students found that 82% of students preferred computer-based education to traditional music education. An artificial intelligence-based vocal teaching system for music majors is a system with good applications, where teachers keep track of students’ learning through reasoning and analysis, enabling students to learn on their own. Learning music requires constant practice, expanding horizons, and accepting new ways of teaching, and the combination of music and the Internet is the latest option to use resources wisely, optimize them, and provide comprehensive resources. Although a variety of music education aids have emerged, few are actually suitable for music classroom education, so it is important to study and implement AI-based speech education systems for music majors.
The Impact of Internet Use on Corporate Tax Avoidance: Evidence from Chinese Enterprises
Authors: Lin Gaoyi , Zhao Yanyan , Liu Wanmin , Zhou Jianjun
Published: May 2022

Based on the data of Chinese industrial enterprises from 2004 to 2009, a fixed‐effect model is adopted in this paper to analyze the effect and the mechanism of the enterprises using the Internet on tax avoidance. The result shows that using the Internet will produce the peer effect, which enables enterprises to learn tax avoidance strategies on the Internet and makes the degree of tax avoidance between enterprises and other enterprises in the same industry converge. At the same time, using the Internet has a network effect, and the more the enterprises access the Internet, the higher the degree of tax avoidance for enterprises is. In addition, the effect of the Internet on tax avoidance is influenced by the intensity of tax collection and the nature of enterprises. With a further examination, it has been found that enterprises not only acquire the two tax avoidance strategies of underreporting profits and underpaying taxes through the Internet but also master the planning strategy.
Experimental Research on Dehydration Process and Strength of Concrete Influenced by Drying Temperature and Concrete Size
Authors: Chen Xiaoming , Zhang Guohui , Zhou Wei , Liu Hongchuan , Yang Shiqiang
Published: May 2022

Moisture has a significant effect on the properties of concrete, and drying concrete in an oven is a common method to obtain specimens with different moisture content. In this paper, C30 concrete specimens with different sizes were oven-dried at constant temperatures of 60, 80, 105, 120, and 150 °C, respectively. The change of specimen mass, ultrasonic testing, and compressive and splitting tensile strength were tested before and after drying. The size effect and the size effect law (SEL) of concrete were analysed. The results indicated that the maximum drying rate and water loss ratio of the specimens with different sizes under the same drying temperature are basically the same. The larger the size, the longer the drying time. After drying, the concrete compressive and splitting tensile strength have increased to varying degrees, and the smaller the size, the greater the increase. For C30 concrete with different sizes, the drying temperature that has the minimal influence is 105 °C. The SEL was modified by introducing drying temperature, and the formulas were obtained after drying.
Mitochondrial DNA Is a Vital Driving Force in Ischemia-Reperfusion Injury in Cardiovascular Diseases
Authors: Liu Hui , Liu Xin , Zhou Jingxin , Li Tao
Published: May 2022

According to the latest Global Burden of Disease Study, cardiovascular disease (CVD) is the leading cause of death, and ischemic heart disease and stroke are the cause of death in approximately half of CVD patients. In CVD, mitochondrial dysfunction following ischemia-reperfusion (I/R) injury results in heart failure. The proper functioning of oxidative phosphorylation (OXPHOS) and the mitochondrial life cycle in cardiac mitochondria are closely related to mitochondrial DNA (mtDNA). Following myocardial I/R injury, mitochondria activate multiple repair and clearance mechanisms to repair damaged mtDNA. When these repair mechanisms are insufficient to restore the structure and function of mtDNA, irreversible mtDNA damage occurs, leading to mtDNA mutations. Since mtDNA mutations aggravate OXPHOS dysfunction and affect mitophagy, mtDNA mutation accumulation leads to leakage of mtDNA and proteins outside the mitochondria, inducing an innate immune response, aggravating cardiovascular injury, and leading to the need for external interventions to stop or slow the disease course. On the other hand, mtDNA released into the circulation after cardiac injury can serve as a biomarker for CVD diagnosis and prognosis. This article reviews the pathogenic basis and related research findings of mtDNA oxidative damage and mtDNA leak-triggered innate immune response associated with I/R injury in CVD and summarizes therapeutic options that target mtDNA.
Implementation of Reliability Antecedent Forwarding Technique Using Straddling Path Recovery in Manet
Authors: Rahamat Basha S. , Sharma Chhavi , Sayeed Farrukh , Arularasan A. N. , Pramila P. V. , Shinde Santaji Krishna , Pant Bhasker , Rajaram A. , Yeshitla Alazar
Published: May 2022

In a mobile ad hoc network, packets are lost by interference occurrence in the communication path because there is no backup information for the previous routing process. The communication failure is not efficiently identified. Node protection rate is reduced by the interference that occurs during communication time. So, the proposed reliability antecedent packet forwarding (RAF) technique is applied to approve the reliable routing from the source node to the destination node. The flooding nodes are avoided by this method; the previous routing information is backed up; this backup information is retrieved if any interference occurred in the communication period. To monitor the packet flow rate of every node, the straddling path recovery algorithm is designed to provide an interference free-routing path. This path has more number of nodes to proceed with communication. These nodes have a higher resource level and also used to back up the forwarded data; since sometimes routing breakdowns occurred, data are lost, which is overcome by using a backup process. It improves the network lifetime and reduces the packet loss rate.
Age, Body Mass Index, and Waist-to-Hip Ratio Related Changes in Insulin Secretion  and  Insulin Sensitivity in Women  with Polycystic Ovary Syndrome: Minimal Model Analyses
Authors: Šumarac-Dumanović Mirjana , Stamenković-Pejković Danica , Jeremić Danka , Dumanović Janko , Mandić-Marković Vesna , Žarković Miloš , Micić Dragan
Published: May 2022

Insulin resistance is believed to be an integral component of the polycystic ovary syndrome (PCOS). Beta (ß) cell dysfunction is also found in PCOS. In the study, we determined the influence of age, body mass index (BMI), and waist-to-hip ratio (WHR) on insulin response to oral glucose load (OGTT) and on insulin sensitivity (Si) and ß-cell function in young women with PCOS. One hundred fourteen patients with PCOS and 41 controls with normal basal plasma glucose were studied. A 75-g OGTT was performed to determine glucose tolerance and insulin response. Insulin sensitivity and ß-cell function were studied using a modified frequently sampled IV glucose tolerance test (FISGTT) to determine the acute insulin response (AIRG), as well as Si by minimal model analysis. Si was decreased in PCOS women (2.49 0.18 vs. 3.41 ± 0.36,

p
<
0.05

), but no difference in AIRG existed between the PCOS and control group (75.1 ± 4.6 vs. 63.4 ± 4.6,

p
<
0.05

). BMI and WHR correlated negatively with Si (r = −0.43; r = −0.289,

p
<
0.001

, respectively), but not with AIRG (r = 0.116; r = −0.02,

p
>
0.05

, respectively). Increasing age correlated negatively with AIRG (r = −0.285,

p
<
0.001

). There was a significant interaction between disease (PCOS), BMI, and WHR on Si as well as between age and PCOS on AIRG. Thus, patients below the age of 25 with PCOS showed enhanced AIRG (89.5 ± 7.1 vs. 65.1 ± 6.7,

p
<
0.05

) and decreased Si (2.43 ± 0.25 vs. 4.52 ± 0.62,

p
<
0.05

) compared to age-matched controls. In conclusion, these data suggest that not all patients with PCOS have basal and stimulated hyperinsulinemia, insulin resistance, and impaired glucose tolerance. Based on these data in young PCOS subjects, the development of insulin resistance and T2DM may be prevented with appropriate treatment strategies.