bluuebunny/crossref_metadata_2025 huggingface dataset:
Construction and Application of College English Multiple Intelligence Teaching Model Based on Internet of Things
Authors: Zhou Ying
Published: March 2022

An RFID sensor is installed above the classroom door, and the scanning distance is set to 8 m to identify the composite campus cards of incoming and outgoing teachers and students, so as to realize automatic statistics of teachers’ theoretical teaching workload and automatic attendance of students’ theoretical class hours. The system automatically starts the multimedia equipment just 5 minutes before class and conducts self-checks on all devices in advance, reducing teachers’ preclass operation steps. The multimedia management system of all classrooms is connected to the campus network and is centrally controlled by the cloud system. When the multimedia equipment in a classroom fails, it can directly instruct teachers to change to an idle classroom. Using the relevant theories of educational psychology and teaching theory, the WPBL teaching model based on the theory of multiple intelligences is expounded and demonstrated. It focuses on expounding theories and ideas; relationships and structures; and environment and resources and conducts in-depth discussions on relevant design rationales and architectural levels. Research has found that students are more interested in reading English than before. The reason is that in the English reading class of the experimental class, basically every student can have their own teaching activities, and more students like to participate in these activities. Applying the theory of multiple intelligences to English reading teaching has played a positive role in stimulating students’ interest in reading. Multiple intelligence English reading activities play an important role in improving students’ English reading performance. Through various teaching activities, the students in the experimental class are more interested and confident in the English reading class. Applying the theory of multiple intelligences to the English reading class can improve the students’ English reading performance and reading ability. In order to apply the theory of multiple intelligences to actual English reading teaching, when designing personalized English reading activities, teachers should learn to combine the theory with the purpose and content of English reading teaching.
The Power of Delay on a Stochastic Epidemic Model in a Switching Environment
Authors: El Koufi Amine
Published: March 2022

In recent years, the world knew many challenges concerning the propagation of infectious diseases such as avian influenza, Ebola, SARS‐CoV‐2, etc. These epidemics caused a change in the healthy balance of humanity. Also, the epidemics disrupt the economies and social activities of countries around the world. Mathematical modeling is a vital means to represent and control the propagation of infectious diseases. In this paper, we consider a stochastic epidemic model with a Markov process and delay, which generalizes many models existing in the literature. In addition, we show the stochastic threshold for the extinction of the disease. Furthermore, numerical examples are discussed to confirm the theoretical result.
Dynamic vs Nondynamic Assessments: Impacts on Intermediate EFL Learners’ Receptive Skills
Authors: Al-Dawoody Abdulaal Mohammad Awad , Ramadan Khalil Nawroz , Heji Alenazi Maryumah , Robso Wodajo Mengesha
Published: March 2022

Listening and reading skills, which are two of the essential skills in the world of language learning, have established themselves in various academic fields. Many researchers have looked at teaching and developing these two receptive abilities, but less focus has been paid to assessing and testing them. Traditional evaluation has been used to examine learners for a long time, but new teaching methods should introduce new ways to test and assess students. This study attempted to investigate the impact of dynamic assessment (DA) vs. nondynamic assessment (NDA) on Ethiopian intermediate EFL learners’ receptive abilities, which was conceptually grounded by Vygotsky’s (1978) socio-cultural theory (SCT). To this end, 96 intermediate students from a high school participated in this study. Then, they were divided into three equal groups: two experimental groups (EG1 and EG2) and one control group (CG). After administering a pretest, the EG1 and EG2 were taught listening and reading skills through group dynamic assessment, and the control group received traditional instruction. After the treatment, a posttest was administered. The results of one-way ANCOVA revealed that dynamic assessment had significant effects on receptive skills. This study has implications for instructors, students, and material designers in light of the findings. Teachers are encouraged to use DA in their language instruction to help students improve their English language abilities.
Developing a Low‐Cost Safety Improvement Program for Intersections in an Urban Roadway Network: A Case Study
Authors: Saha Promothes
Published: March 2022

In the US, about 40% of all crashes involve intersections. As improving safety at intersections and nonintersections are significantly different, it is important to manage them separately within a limited budget. In this study, a safety improvement program was developed for intersections and implemented in the city of Fort Wayne, Indiana, as a case study. Intersections included in the safety improvement program were selected using the following criteria and constraints: averaging more than 3 crashes per year during the study period, crash rate, and fatal and injury crash rate, limited budget, and safety benefits. Selected intersections were analyzed to characterize their crashes by type and frequency. Countermeasures were proposed and analyzed to address those crash types identified in the crash characterization. Linear integer optimization technique was employed to identify the best set of countermeasures within a limited budget. A safety improvement program was proposed based on this analysis that would cost $81,232 and provide a 5‐year crash reduction benefit of more than $15 million preventing approximately 164 total crashes and 61 fatal or injury crashes.
[Retracted] Multichannel CNN Model for Biomedical Entity Reorganization
Authors: Singh Ajay Kumar , Khan Ihtiram Raza , Khan Shakir , Pant Kumud , Debnath Sandip , Miah Shahajan
Published: March 2022

Biomedical researchers and biologists often search a large amount of literature to find the relationship between biological entities, such as drug‐drug and compound‐protein. With the proliferation of medical literature and the development of deep learning, the automatic extraction of biological entity interaction relationships from literature has shown great potential. The fundamental scope of this research is that the approach described in this research uses technologies like dynamic word vectors and multichannel convolution to learn a larger variety of relational expression semantics, allowing it to detect more entity connections. The extraction of biological entity relationships is the foundation for achieving intelligent medical care, which may increase the effectiveness of intelligent medical question answering and enhance the development of precision healthcare. In the past, deep learning methods have achieved specific results, but there are the following problems: the model uses static word vectors, which cannot distinguish polysemy; the weight of words is not considered, and the extraction effect of long sentences is poor; the integration of various models can improve the sample imbalance problem, the model is more complex. The purpose of this work is to create a global approach for eliminating different physical entity links, such that the model can effectively extract the interpretation of the expression relationship without having to develop characteristics manually. To this end, a deep multichannel CNN model (MC‐CNN) based on the residual structure is proposed, generating dynamic word vectors through BERT (Bidirectional Encoder Representation from Transformers) to improve the accuracy of lexical semantic representation and uses multihead attention to capture the dependencies of long sentences and by designing the Ranking loss function to replace the multimodel ensemble to reduce the impact of sample imbalance. Tested on multiple datasets, the results show that the proposed method has good performance.
Face Recognition Algorithm Based on Multiscale Feature Fusion Network
Authors: Li Yunquan , Gao Meizhen
Published: March 2022

A face recognition model based on a multiscale feature fusion network is constructed, aiming to make full use of the characteristics of face and to improve the accuracy of face recognition. In addition, three different scale networks are designed to extract global features of faces. Multiscale cross-layer bilinear features of multiple networks are integrated via introducing a hierarchical bilinear pooling layer. By capturing some of the feature relationships between different levels, the model's ability to extract and distinguish subtle facial features is enhanced. Simultaneously, this study uses layer-by-layer deconvolution to fuse multilayer feature information, to solve the problem of losing some key features when extracting features from multilayer convolutional layers and pooled layers. The experimental results show that compared with the recognition accuracy of traditional algorithms, the recognition accuracy of the algorithm on Yale, AR, and ORL face databases is significantly improved.
Multiple Assessments on the Gamma-Ray Protection Properties of Niobium-Doped Borotellurite Glasses: A Wide Range Investigation Using Monte Carlo Simulations
Authors: Tekin H. O. , Ali Fatema T. , Almisned Ghada , Susoy Gulfem , Issa Shams A. M. , Ene Antoaneta , Elshami Wiam , Zakaly Hesham M. H.
Published: March 2022

In this study, the monotonic effect of Ta2O5 and ZrO2 in some selected borotellurite glasses was investigated in terms of their impact on gamma-ray-shielding competencies. Accordingly, three niobium-reinforced borotellurite glasses (S1 : 75TeO2 + 15B2O3 + 10Nb2O5, S2 : 75TeO2 + 15B2O3 + 9Nb2O5 + 1Ta2O5, and S3 : 75TeO2 + 15B2O3 + 8Nb2O5 + 1Ta2O5 + 1ZrO2) were modelled in the general-purpose MCNPX Monte Carlo code. They have been defined as an attenuator sample between the point isotropic gamma-ray source and the detector in terms of determining their attenuation coefficients. To verify the MC results, attenuation coefficients were then compared with the Phy-X/PSD program data. Our findings clearly demonstrate that although some behavioral changes occurred in the shielding qualities, modest improvements occurred in the attenuation properties depending on the modifier variation and its magnitude. However, the replacement of 2% moles of Nb2O5 with 1% mole of Ta2O5 and 1% mole of ZrO2 provided significant improvements in both glass density and attenuation properties against gamma rays. Finally, the HVL values of the S3 sample were compared with some glass- and concrete-shielding materials and the S3 sample was reported for its outstanding properties. As a consequence of this investigation, it can be concluded that the indicated type of additive to be added to borotellurite glasses will provide some advantages, particularly when used in radiation fields, by increasing the shielding qualities moderately.
Analysis of the Coupling and Coordination Relationship between the Evolution of Enterprise Spatial Structure and Economic Development Based on the Deep Learning Model
Authors: Wang Lei , He Yuan , Qi Yao
Published: March 2022

This study is based on the unsupervised learning-based enterprise spatial structure evolution and economic coupling coordination relationship situation assessment method. Pattern recognition has high-precision characteristics, but it is necessary to train the evaluation model for the enterprise spatial structure evolution in advance and then carry out economic coupling coordination based on the trained model. The conclusions are as follows: (1) through the RC1, RC2, RC3, RC4, RC5, and RC6 evaluation indicators to evaluate the situation evaluation method based on the unsupervised learning of the evolution of the enterprise spatial structure and the economic coupling and coordination relationship, it is found that the main component characteristics as a whole meet the standard. The optimal RC is RC6: profit = −0.0885, highest = −0.0809, lowest = −0.0932, WR.WR2 = 0.0038, MA.MA3 = −0.0782, MTM.MTM = −0.0427, OSC.OSC = −0.0355, ROC.MAROC = 0.0105, SKDJ.D = −0.0268, BIAS-QL.BIAS = −0.01, WIDTH.WIDTH = 0.2408, CYD.CYDN = −0.0961, FSL.SWL = −0.0868ADTM.ADTM = −0.0379, ATR.ATR = −0.0278, DMA.DIFMA = −0.0358, DMI.ADX = 0.8516, DMI.ADXR = 0.854, EMV.EMV = −0.0942, VMACD.DIF = 0.3312, and UOS.MAUOS = −0.0846.2. Based on the deep learning model of the coupling and coordination relationship between the evolution of the spatial structure of the enterprise, the time-dependent matrix comparison experiment is divided into directed + self, directed, undirected + self, and undirected time for comparison. The experimental results on directed + self are the best; with various indicators, the upward improvement is above 10%: CP = 0.8611, CR = 0.9353, C–F1 = 0.8967, EP = 0.8865, ER = 0.857, E–F1 = 0.917, OP = 0.856, OR = 0.9845, and O–F1 = 0.99.3. The time cost, profit, and transaction volume data of the company are collected for a certain period of time, and simulation experiments are conducted to get a small difference between the predicted result and the actual data. The January data are closest to the true value: cost = 30.78, profit = 30.11, highest = 30.1, lowest = 29.7, WR.WR1 = 81.21, WR.WR2 = 45.62, AMV.AMV2 = 32.67, AMV.AMV3 = 34.95, and MCST. MCST = 36.08.4. In the model score, the best performance of LSTM data is CP = 0.3829, CR = 0.3664, C–F1 = 0.3744, EP = 0.3726, ER = 0.3004, E–F1 = 0.3326, OP = 0.9155, OR = 0.9316, and O–F1 = 0.9234, which is better than the BiLSTM model with CP = 0.3648, CR = 0.3319, C–F1 = 0.3392, EP = 0.4402, ER = 0.391, E–F1 = 0.4145, OP = 0.9215, OR = 0.9318, and O–F1 = 0.9266.
[Retracted] Experimental Study on Mineral Solid Waste Green Grouting Material Based on Electromagnetic Characteristic Detection
Authors: Wang Xiangpeng , Hu Jin , Zhang Xiang , Wang Kunpeng , Shen Di , Liang Chuntao
Published: March 2022

The production processes for the gypsum‐ and cement‐based materials, which are widely used in civil engineering projects, require the consumption of large amounts of energy and natural resources. At the present time, the main development directions of civil engineering material include realizing solid waste recycling and the applications of green building materials, which can be then used in the fields of disaster treatment and ecological restoration, such as grouting materials. In addition, the grouting quality is always difficult to detect. This study examined the gypsum‐ and cement‐based green grouting materials made from mineral solid waste used in disaster and cloud detection by means of electromagnetic characteristics. According to the requirements of electrical testing of grouting quality, first we designed a material made with solid waste. Then, we studied the resistivity, strength, porosity, and other physical and mechanical properties of the material. The test results of the material and its soaking solution indicate that this material is a green material meeting the environmental safety standards. The experimental results show that the rapid detection of grouting quality can be realized. The following effects on electromagnetic characteristics and mechanical properties of the green materials of gypsum‐ and cement‐based were analyzed. The results showed that the resistivity and strength were related to the ratios of the water content to the modified phosphogypsum; the percentages of cement content in the total amount of modified phosphogypsum and marble powder; the percentages of marble powder in the modified phosphogypsum; the percentages of steel fiber content in the phosphogypsum; and the fineness of the marble powder. The field test results also confirm that the green grouting material can be effectively applied in engineering repair imaging monitoring.
Improving Heat Resistance of Nile Tilapia (Oreochromis niloticus) by Dietary Zinc Supplementation
Authors: Yang Yuanting , Wu Zhiqian , Ren Yanli , Zhou Zhiqing , Wang Wen-Xiong , Huang Yunmao , Shu Xugang
Published: March 2022

In this study, we investigated the effects of zinc threonine supplementation on growth, immunity-related genes, antioxidative stress, and resistance to heat stress (HS) in Nile tilapia. A total of 300 Nile tilapia (

76.69
±
0.11

 g) were randomly allocated into five zinc treatments, with three replicates of 20 fish in each treatment. Based on the control group with zinc-free feeds, dietary zinc levels of 20 or 40 mg/kg diet were added in the form of zinc sulfate (ZnSO4) and zinc threonine (Thr-Zn). After 45 days of feeding, part of the fish was exposed to HS. The highest performance of growth and feed intake was found in fish fed with zinc (ZnSO4 or Thr-Zn) at 40 mg/kg, which also significantly elevated the villus length and absorption area. Additionally, significantly higher values of superoxide dismutase, catalase, and glutathione peroxidase activity but lower value of malondialdehyde both before and after the heat stress were documented in fish fed with zinc at 40 mg/kg in diets. After HS, dietary supplementation with zinc threonine significantly reduced the expression of HSP 70 in the liver but increased the expression of IL-10 and TNF-α. Our study demonstrated that zinc threonine supplementation at 40 mg/kg facilitated the coping of tilapia with HS by improving the growth, intestinal morphology, antioxidative resistance, and immune responses.
miR‐542‐3p‐Targeted PDE4D Regulates cAMP/PKA Signaling Pathway and Improves Cardiomyocyte Injury
Authors: Lu Yu , Wu HuaJun , Deng Min , Huang MingDe , Pan HaiHua , Yang PingShao
Published: March 2022

Objective. To investigate the protective effect of miR‐542‐3p on cardiomyocyte injury and related mechanisms. Methods. A cardiomyocyte hypoxia/reoxygenation model was established. The expression levels of miR‐542‐3p and PDE4D were detected using qRT‐PCR; the luciferase reporter assay system was used to detect the targeting relationship between miR‐542‐3p and PDE4D; overexpressing miR‐542‐3p was transfected into cardiomyocytes, and ROS release was detected by immunofluorescence while cellular apoptosis was detected by TUNEL; and the western blot assay was applied to detect the expression of PDE4D, phosphorylated protein kinase A (p‐PKA), and phosphorylated cyclic adenosine monophosphate (cAMP) response element‐binding protein (p‐CREB). Results. Compared with the control group, the miR‐542‐3p expression level was decreased and the PDE4D expression level was increased in the cardiomyocyte hypoxia/reoxygenation model group. The dual‐luciferase reporter assay system confirmed that miR‐542‐3p could target and regulate PDE4D; the transfection with cardiomyocytes using the overexpressing miR‐542‐3p could downregulate PDE4D expression, attenuate ROS release during cardiomyocyte injury, and reduce cellular apoptosis rate, while upregulating the expression of p‐PKA and p‐CREB. Conclusion. The miR‐542‐3p can negatively regulate PDE4D protein expression and attenuate cardiomyocyte injury through a mechanism related to the activation of the cAMP/PKA signaling pathway.
Design and Analysis of Direct Abort Orbits in the Earth-Moon Transfer Phase of Crewed Lunar Exploration Missions
Authors: Lu Lin , Li Haiyang , Zhou Wanmeng , Wu Xinfeng , Cui Huiru
Published: March 2022

A direct abort orbit design method is presented for direct abort missions in the Earth-Moon transfer phase of crewed lunar exploration missions. First, according to the demand of an emergency rescue in the Earth-Moon transfer phase, two direct abort orbit schemes are introduced. Then, a serial orbit design method is proposed for a high-fidelity direct abort orbit. An analytical model is established for the calculation of initial values, and the optimization design is performed in the high-fidelity orbit model to determine a single-impulse abort orbit. A hybrid optimization design process is proposed to generate a two-impulse abort orbit. The results of simulation examples verify the validity and feasibility of the proposed direct abort orbit design method. Finally, extensive simulations are carried out to analyze the characteristics of abort impulse and abort return time and reveal the general rules of direct abort orbits. The research conclusions can provide a reference for the design of emergency rescue schemes in future crewed lunar exploration missions.
Thermodynamics and Mechanism of the Adsorption of Heavy Metal Ions on Keratin Biomasses for Wastewater Detoxification
Authors: Olawale Salaudeen Abdulwasiu , Bonilla-Petriciolet Adrián , Mendoza-Castillo Didilia Ileana , Okafor Chibueze Charles , Sellaoui Lotfi , Badawi Michael
Published: March 2022

The analysis of thermodynamics and mechanism of the adsorption of cadmium, chromium, copper, and lead ions from aqueous solution with two keratin-based biomaterials, namely, human hair and sheep fur, is reported in this paper. The effect of initial ion concentration, temperature, pH, contact time, and biomaterial amount on the removal of these heavy metal ions using these keratinous adsorbents was studied. The adsorption of heavy metal ions was highly dependent on the operating parameters where pH and temperature showed the highest impact. Maximum adsorption capacities of these biomaterials were up to 1.33 and 1.40 mmol/g for chromium ions using human hair and sheep fur, respectively. Adsorption kinetic rates of tested heavy metal ions were calculated via a pseudo-second-order model, and they ranged from 0.054 to 0.261 g/mmol·min. A detailed thermodynamic analysis of lead ion adsorption was performed showing an endothermic removal of this adsorbate with both human hair and sheep fur with adsorption enthalpies of 84.5 and 97.1 kJ/mol, respectively. Statistical physics calculations demonstrated that this heavy metal ion was adsorbed via a multi-interaction mechanism especially for human hair. These keratinous biomaterials showed competitive adsorption capacities especially for chromium ion removal and can outperform commercial activated carbons and other adsorbents reported in literature.
Recent Advances and Next Breakthrough in Immunotherapy for Cancer Treatment
Authors: Yang Ling , Ning Qian , Tang Sheng-song
Published: March 2022

With the huge therapeutic potential, cancer immunotherapy is expected to become the mainstream of cancer treatment. In the current field of cancer immunotherapy, there are mainly five types. Immune checkpoint blockade therapy is one of the most promising directions. Adoptive cell therapy is an important component of cancer immunotherapy. The therapy with the cancer vaccine is promising cancer immunotherapy capable of cancer prevention. Cytokine therapy is one of the pillars of cancer immunotherapy. Oncolytic immunotherapy is a promising novel component of cancer immunotherapy, which with significantly lower incidence of serious adverse reactions. The recent positive results of many clinical trials with cancer immunotherapy may herald good clinical prospects. But there are still many challenges in the broad implementation of immunotherapy. Such as the immunotherapy cannot act on all tumors, and it has serious adverse effects including but not limited to nonspecific and autoimmunity inflammation. Here, we center on recent progress made within the last 5 years in cancer immunotherapy. And we discuss the theoretical background, as well as the opportunities and challenges of cancer immunotherapy.
Effects of the Air Inlet Angle on the Combustion and Ablation Environment of a Hybrid Powder-Solid Ramjet
Authors: Wang Jinjin , Wen Yihao , Zha Bailin , Xu Zhigao , Zhang Tianhao
Published: March 2022

A hybrid powder-solid ramjet (HPSR) that combined the advantages of a solid rocket ramjet (SRJ) and a powder ramjet engine was investigated in this research. To improve the combustion efficiency and optimize the inner wall thermal protection of the afterburner, the effects of the air inlet angle on the combustion and wall ablation environment were studied. The standard

k

-

ε

model, the eddy-dissipation model (EDM), and the boron particle ignition and combustion model were adopted to simulate the two-phase flow in the afterburners with different air inlet angles (45°, 60°, 75°, and 90°). The results showed that the global flow field and the distribution of the vortexes in the afterburner that had a significant influence on the ablation environment of the inner wall and the combustion efficiency were determined by the impact effect and the squeezing effect of the ram air on the primary fuel gas, which was affected by the air inlet angle. As the air inlet angle increased, the total combustion efficiency of the four cases first increased and then decreased, reaching 80.38%, 81.64%, 84.34%, and 83.26% for angles of 45°, 60°, 75°, and 90°, respectively. At the same time, the inner wall ablation became more severe because both the erosion effect of the condensed phase particles and the gas-flow scouring effect were enhanced, and a large temperature gradient was generated on the inner wall. The study results can provide a reference for designing the air inlet angle of an HPSR.
Deep Neural Network-Based Sports Marketing Video Detection Research
Authors: Xu Longcheng , Choi Deokhwan , Yang Zeyun
Published: March 2022

With the rapid development of short video, the mode of sports marketing has diversified, and the difficulty of accurately detecting marketing videos has increased. Identifying certain key images in the video is the focus of detection, and then, analysis can effectively detect sports marketing videos. The research of video key image detection based on deep neural network is proposed to solve the problem of unclear and unrecognizable boundaries of key images for multiscene recognition. First, the key image detection model of the feedback network is proposed, and ablation experiments are conducted on a simple test set of DAVSOD. The experimental results show that the proposed model achieves better performance in both quantitative evaluation and visual effects and can accurately capture the overall shape of significant objects. The hybrid loss function is also introduced to identify the boundaries of key images, and the experimental results show that the proposed model outperforms or is comparable to the current state-of-the-art video significant object detection models in terms of quantitative evaluation and visual effects.
Digital Music Feature Recognition Based on Wireless Sensing Technology
Authors: Wang Xiaoning , Guo Wei , Tong Weiwei
Published: March 2022

With the rapid development of information technology, digital music is subsequently increasing in large quantities, and how a good integration of vocal input and recognition technology can be transformed into digital music can greatly improve the efficiency of music production while ensuring the quality and effect of music. This paper focuses on the implementation and application of human voice input and recognition technology in digital music creation, enabling users to generate digital music forms by simply humming a melodic fragment of a piece of music into a microphone. The paper begins with an introduction to digital music and speech recognition technology and goes on to describe the respective characteristics of various audio formats, which are selected as data sources for digital music creation based on the advantages of the files in terms of retrieval. Following that, the method of extracting musical information from music is described, and the main melody is successfully extracted from the multitrack file to extract the corresponding musical performance information. The feature extraction of humming input melody is further described in detail. The traditional speech recognition method of using short-time energy and short-time overzero rate features for speech endpoint detection is analyzed. Combining the characteristics of humming music, the method of cutting notes by two-stage cutting mode, i.e., combining energy saliency index, overzero rate, and pitch change, is adopted to cut notes, which leads to a substantial improvement in performance. The algorithm uses the melody extraction algorithm to obtain the melody line, merges the short-time segments of the melody line to reduce the error rate of emotion recognition, uses the melody line to segment the music signal to generate segmented segments, then abstracts the features of the segmented segments through a CNN-based structural model, and inputs the output of the model to the regressor in cascade with the melody contour features of the corresponding segmented segments to finally obtain the emotion

V
/
A

value of the segmented segments.
The Skill Training of Reading Music in the Teaching of Solfeggio and Ear Training in the New Media Environment
Authors: Wang Lin
Published: March 2022

Culture is a powerful spiritual force rooted in the hearts of the Chinese people and guides the direction of the Chinese people. Sight singing and ear training are playing an increasingly important role as an important means of music teaching. The article is aimed at studying the latest application progress of music reading skills in audiovisual ear training in the new media environment. This paper proposes the interactive application of music reading skills that integrate new media to realize the interactive communication between man and machine. The experimental results of this paper show that new media can make greater use of the advantages of music reading skills, enhance students’ musical sensitivity by 20%, and realize musical interaction.
Characterization of Group Behavior of Corruption in Construction Projects Based on Contagion Mechanism
Authors: Li Jingjing , Shen Qiangqiang , Gao Wencan
Published: March 2022

With the rapid development of construction projects, more and more engineering corruption problems have emerged. Therefore, this paper proposes a SEIR (susceptible-exposed-infected-recovered) based corruption model to better understand the propagation process of corruption cases in construction projects. In this model, the data samples are collected from the 2018 Engineering Corruption Case Judgment Document, the propagation parameters are obtained through actual case analysis with the help of complex networks, the change process and key influencing factors of actual nodes in engineering corruption cases are simulated by Python. The study results indicate that the personnel conforms to the “4–9 transmission law,” in which the early stage is a period of high incidence of corruption cases. The network of corruption cases is somewhat vulnerable, and its spread is about minus 8 times the change in crackdown rate and 10 times the change in infection rate. The variation range of the susceptible population S and the removed person R in the propagation simulation curve can predict the relationship between corruption infection rate and crackdown rate, which can provide theoretical guidance for preventing the occurrence of corruption.
The Potential Diagnostic and Predictive Role of HbA1c in Diabetic, Septic Patients: A Retrospective Single-Center Study
Authors: Juhász Imre , Juhász Janka , Lörincz Hajnalka , Seres Ildikó , Végh Lilla , Ujfalusi Szilvia , Harangi Mariann , Szabó Zoltán , Paragh György
Published: March 2022

Background. As diabetes mellitus is a major risk factor of sepsis, we aimed to evaluate the possible effects of diabetes mellitus and poor glycemic control on the diagnosis of sepsis. Methods. In our retrospective study, we included diabetic, septic patients—in whom the diagnosis of sepsis was based on the systemic inflammatory response syndrome (SIRS) criteria (n = 112, SIRS group)—who had HbA1c levels measured either in the previous 30 days (n = 39, SIRS 30 d subgroup) or within 24 hours after their emergency department admission (n = 73, SIRS 24 h subgroup). We later selected those patients from the SIRS group, whose sequential organ failure assessment (SOFA) score was ≥2 (n = 55, SOFA group), and these patients were also divided based on the time of HbA1c measurement (n = 21, SOFA 30 d subgroup and n = 34, SOFA 24 h subgroup). We analyzed the relationship between laboratory parameters, length of hospital stay, and HbA1c. Results. We found a significant positive correlation between glucose and HbA1c (

p
<
0.001

,

p
<
0.001

, respectively), significant negative correlations between white blood cell count (WBC) and glucose (

p
=
0.01

,

p
=
0.02

, respectively), WBC and HbA1c levels (

p
=
0.001

,

p
=
0.02

, respectively) in the SIRS 24 h and SOFA 24 h subgroups. Furthermore, there was a significant positive correlation between length of hospital stay and HbA1c in the SOFA 24 h subgroup (

p
=
0.01

). No significant correlations were found in the SIRS 30 d and SOFA 30 d subgroups. Conclusion. Based on our results, normal WBC with elevated HbA1c might be considered a positive SIRS criterium in diabetic, SIRS 24 h patients. Besides this potential diagnostic role, HbA1c might also be an additional prognostic biomarker in diabetic, SOFA 24 h patients.
A Case of Isolated Congenital Stapedial Suprastructure Fixation
Authors: Lee Jeon Mi , Lee Hyun Jin , Kim Sung Huhn
Published: March 2022

We report a case of conductive hearing loss caused by isolated congenital stapedial suprastructure fixation with normal footplate mobility. A 60-year-old woman visited the clinic for right-sided mixed hearing loss. Exploratory tympanotomy revealed a bony synostosis between the stapedial suprastructure and promontory, while all the ossicles were present and normally shaped. As the bony synostosis was separated, the stapes became mobile. This is the first report in the medical literature of this congenital ear anomaly. This case also illustrates that stapedial fixation can occur in the suprastructure as well as in the footplate; thus, one must be mindful of this when performing exploratory tympanotomy for stapes fixation.
Quasi-Static Test Study on Seismic Behavior of Large-Section Fabricated Utility Tunnel
Authors: Zhu Li , Shangguan Shiqing , Yu Haitao , Guo Yawei , Chen Zheng , An Dong
Published: March 2022

Based on the urban utility tunnel project in Xiong’an New Area, to clarify the seismic behavior of the utility tunnel structure, the overall structure model of the four-cabin large-section utility tunnel and the quasi-static test of the joint specimens have been completed. The results show the following. (1) The hysteresis curve of the overall structure is relatively full, showing good ductility and energy consumption. The middle joint has better bending performance. The ductility of the side joint is worse than that of the middle one. (2) The skeleton curve of the joint specimen is divided into three stages: obvious cracking, yielding, and ultimate load. After the overall structure reaches the ultimate load, the load curve basically tends to be horizontal. (3) The stiffness degradation of the overall structure and the joint specimens continues to be uniform during the entire loading process. (4) The structural design of the fabricated utility tunnel can ensure the seismic behavior under normal condition.
Recurrence of Asymptomatic COVID-19 after Recovery among Healthcare Workers
Authors: Cucunawangsih Cucunawangsih , Wijaya Ratna Sari , Hardjo Lugito Nata Pratama , Suriapranata Ivet
Published: March 2022

We describe five healthcare workers (HCWs) with a recurrence of asymptomatic SARS-CoV-2 infection at Siloam Teaching Hospital, Indonesia. All cases involved nurses, with an average age of 27 years. The RT-PCR assay confirmed the first and second infection episodes. All cases showed negative RT-PCR results in the period between two infection episodes. The median interval time between two infection episodes was 123 days, ranging from 92 to 158 days. The clinical outcomes for all cases were favourable, with no mortality observed among study cases. Further studies will be required to understand the true nature of this phenomenon.
Hybrid Model: Teaching Learning-Based Optimization of Artificial Neural Network (TLBO-ANN) for the Prediction of Soil Permeability Coefficient
Authors: Bui Quynh-Anh Thi , Al-Ansari Nadhir , Le Hiep Van , Prakash Indra , Pham Binh Thai
Published: March 2022

The permeability coefficient (k-value) of the soil is an important parameter used in the civil engineering design of roads, tunnels, dams, and other structures. However, the determination of k-value by experimental methods in the laboratory or the field is still costly and time-consuming. Moreover, it requires special equipment and special care in the collection of soil samples for laboratory study. Therefore, in this study, we have proposed machine learning (ML) hybrid model: teaching learning-based optimization of artificial neural network (TLBO-ANN) to predict the k-value of soil based on limited parameters (natural water content, void ratio, specific gravity, liquid limit, plastic limit, and clay content) which can be determined easily in the laboratory. Test results of 84 soil samples obtained from the Da Nang-Quang Ngai expressway project in Vietnam are used in the model development. Statistical indicators such as correlation coefficient (R), root mean square error (RMSE), and mean absolute error (MAE) are used to validate and evaluate the accuracy of the model. The results show that the TLBO-ANN model is an effective tool in predicting correctly the k-value (R = 0.905) of soil for the consideration in the design of structures founded on the soil.
Polarization and Conduction Characteristics of Mineral Oil and Natural Ester Mixed with Nanoparticles
Authors: Maneerot Sakda , Pattanadech Norasage , Kittikhuntharadol Yannaphol , Nimsanong Phethai , Bunlaksananusorn Chanin
Published: March 2022

Mineral oil (MO) has been widely used in transformers because of its reasonable price and acceptable properties. Currently, alternative liquid insulations have been proposed with some excellent properties. Therefore, the mineral oil characteristics need to be enhanced for high performance to compete with such alternative liquid insulations. This paper aims to study the power frequency dielectric dissipation factor (tanδ) along with polarization and depolarization current (PDC) characteristics of the mineral oil-based nanofluid and natural ester (NE)-based nanofluid. Besides, Fourier-transform infrared spectroscopy (FT-IR) measurement of the test specimen was performed. Titanium dioxide (TiO2) and zinc oxide (ZnO) with 0.01% and also 0.03% volume concentration were used to mix with the unmodified liquid to create liquid insulation-based nanofluid. Then, unmodified mineral oil, unmodified natural ester, mineral oil-based nanofluid, and natural ester-based nanofluid were comparatively investigated. Tanδ at power frequency and the PDC characteristics of such liquids were examined. For PDC measurement, TiO2 clearly affected the polarization current and conduction loss factor, whereas ZnO evidently impacted the depolarization current and polarization loss factor. In the case of FT-IR test results, there was no significant change when the modified insulating liquid was compared with those of the unmodified insulating liquid.
Type 1 Diabetes (T1D) and Latent Autoimmune Diabetes in Adults (LADA): The Difference Between a Honeymoon and a Holiday
Authors: Marcon Livia M. R. , Fanelli Carmine G. , Calafiore Riccardo
Published: March 2022

Type 1 diabetes mellitus (T1D) is a chronic autoimmune disease in which destruction of the insulin-producing β-cells in the pancreatic islets requires regular lifelong insulin replacement therapy, the only lifesaving treatment available at this time. In young persons with a genetic predisposition, it usually manifests after being exposed to environmental triggers. A subtype of autoimmune diabetes mellitus (ADM) that typically occurs in adulthood is often referred to as latent autoimmune diabetes of adults (LADA). LADA is characterized by a milder process of β-cells destruction and less intensive insulin treatment, which may become necessary even many years after diagnosis. Genetic predisposition of T1D carries an increased risk for other autoimmune diseases, such as autoimmune thyroiditis, the most frequently associated condition, and pernicious anaemia (PA), present in approximately 4% of all individuals with T1D. Here, we describe the case of a 90-year-old woman with vitiligo and a mute medical history who was admitted to our University Hospital in Perugia with hyperglycaemia and severe anaemia due to vitamin B12 (VB12) depletion. A short time after setting the beginning treatment with a basal-bolus insulin regimen, her insulin requirement rapidly declined and treatment with sitagliptin, a dipeptidyl peptidase-4 inhibitor (DPP4), was started. A complete autoimmunity screening panel showed that GAD65 and intrinsic factor autoantibodies were positive.
Blockchain-Based Crowdsourcing Framework with Distributed Task Assignment and Solution Verification
Authors: Li Shasha , Bai Xiaodong , Wei Songjie
Published: March 2022

Internet backboned crowdsourcing utilizes network-wide resources to solve complicated and large-scale tasks, which are not accomplishable for independent individuals. Existing crowdsourcing platforms are mostly centralized solutions with reliability and trustworthiness fragile to single-point failures on the central servers. The innovation of distributed ledgers as blockchain inspires us to optimize the traditional crowdsourcing procedure with distributed sustainability. We propose a blockchain-based design of the distributed secure crowdsourcing scheme for task distribution and result verification without relying on any third trusted institution. A preference-based task distribution (PTD) mechanism is presented which guarantees the percentage of task distribution and the satisfaction of the chosen workers. Task works are continuously assessed for reputations based on their historical behaviors. Task completion correctness is verified by blockchain consensus in two different scenarios after workers submit their results with reputations. We implement a prototype system based on the Ethereum chain with PTD and solution verification components. With various tasks and scenarios evaluated in the system, the proposed distributed crowdsourcing framework shows system reliability, data security, and scenario feasibility.
Therapeutic Effect of Bicyclol Coupled with Aspirin Nanopreparation on Liver Function Damage Caused by Epstein‐Barr Virus Infection in Children
Authors: Yi Wenxia , Zhang Chunyan , Xu Chunyan , Tian Wenqiu , Xie Fei , Yue Bin
Published: March 2022

The aim of study effective treatment is to reach the appropriate part of the body and then maintain the required drug concentration at sufficient intervals in order to achieve the clinical therapeutic effect. Problem of the Study. Biological barrier hinders the flow of most drugs from the blood to the focus. Methods of the Study. A novel nanopreparation for inhibition of Epstein‐Barr virus (EBV) was developed based on poly (lactic‐co‐glycolic acid) (PLGA) nanodrug carriers loaded with bicyclic alcohol (BA) and aspirin (Asp) (PLGA‐BA/Asp). Among them, the addition of PLGA can effectively improve the low solubility of BA and poor oral availability. Results have revealed that PLGA‐BA/Asp is a multifunctional therapeutic drug that integrates antivirus, treatment of liver damage, and regulation of the immune system. This discovery provides a new treatment method for the treatment of liver injury in children with EBV infection.
The Relationship between Human Embryo Parameters and De Novo Chromosomal Abnormalities in Preimplantation Genetic Testing Cycles
Authors: Liu Yanli , Shen Junhan , Yang Rujing , Zhang Yuchao , Jia Liting , Guan Yichun
Published: March 2022

Research Question. What is the incidence of de novo chromosome abnormalities (>4 Mb), and are they related to embryo parameters in preimplantation genetic testing for chromosome structural rearrangement (PGT-SR) cycles and preimplantation genetic testing for aneuploidy (PGT-A) cycles? Design. In total, 456 PGT cycles, including 283 PGT-SR cycles and 173 PGT-A cycles, were assessed through comprehensive chromosome screening (CCS) from January 2017 to June 2020 at the Department of Reproductive Medicine of the Third Affiliated Hospital of Zhengzhou University. Trophectoderm (TE) biopsies were sequenced using next-generation sequencing (NGS). The incidence of de novo chromosome abnormalities was calculated, and the relationships between de novo chromosome abnormality rates and maternal age, number of oocytes retrieved, and parameters of cleavage-stage embryos and blastocyst-stage embryos were investigated. Results. The incidence of de novo chromosome abnormalities was 28.0% (318/1,135) in the PGT-SR cycles and 36.3% (214/590) in the PGT-A cycles, which increased with maternal age in both PGT-SR cycles (

P

 = 0.018) and PGT-A cycles (

P

 < 0.001). The incidence of de novo chromosome abnormalities was related to TE grade (

P

 < 0.001), internal cell mass grade (

P

 = 0.002), and development speed (day 5 vs. day 7:

P

 < 0.001) of blastocyst-stage embryos. The incidence of de novo chromosomal abnormalities was irrelevant to the number of oocytes retrieved and the parameters of the embryo at the cleavage stage. Conclusion. Blastocysts with higher morphology scores and faster progression had a lower incidence of de novo chromosome abnormalities, especially complex chromosome abnormalities. De novo chromosome abnormalities may negatively affect the morphological grading of blastocysts. Our findings will provide valuable information to the fertility doctor for embryo selection in non-PGT cycles.
Impact of German Students’ Digital Readiness for Online- Learning on Factors of Challenges and Mediating Role of German Teachers’ Support at Foreign Languages Universities in Myanmar during COVID- 19 Pandemic: Perspectives from Developing Country
Authors: Win Sai Si Thu , Swe Sein U
Published: March 2022

The purpose of this study is to examine the connection between German students’ digital readiness for online learning, their challenges and the support of German teachers at Foreign Languages Universities in Myanmar. The COVID-19 pandemic has impacted educational institutions across the world. In Myanmar, all the learning methods shifted to online instruction. However, there are a limited number of factors that influence students’ online learning. Some of these include digital readiness and support from teachers. In addition, several challenges exist regarding their educational backgrounds. The data for this research were collected through conducting in-depth interviews with German teachers (n=10) and surveys of German students (n=112). This study took an exploratory mixed-method design. In qualitative analysis, the constructivist grounded theory method is used for data collection and the data analysis is also described and justified by Charmaz (2014) as a general guide. In the quantitative analysis, the data were analyzed using descriptive statistics through SPSS 27.0. Findings reveal that German students faced a limited number of challenges and the level of German student’s digital readiness and teachers’ support positively impacted on these factors of challenges for online learning during Covid-19 pandemic. The data analyzed showed that each of their challenges varied according to their perceptions and readiness to technology integration. To sum up, this research offers factors of challenges which significantly correlate with digital readiness and teachers’ support during the corona-crisis in developing country.