bluuebunny/crossref_metadata_2025 huggingface dataset:
Microstructure Characterization of High Explosives by Wavelet Transform
Authors: Jia Xianzhen , Cao Peng , Han Yutong , Zheng Hang , Wu Yushuai , Zheng Junxing
Published: April 2022

The key macro properties of high explosives including sensitivity to shock, the possibility of initiation, and the subsequent chemical reaction are known to be controlled by processes occurring at their microstructure level. However, there is a lack of an easy, effective, and accurate method to quantify the microstructure, termed as fabric, of high explosives despite an abundance of evidence regarding its importance. This study proposes a rotational Haar wavelet transform (RHWT) method to characterize the fabric of high explosives from two-dimensional images, yielding key fabric parameters including rose diagram, fabric direction, and degree of fabric anisotropy. The fabric tensor commonly used in numerical simulations and constitutive models can also be determined by RHWT. The RHWT was implemented on microscopic images of six high explosives captured by various imaging techniques including scanning electrical microscopy, polarized light microscopy, and micro X-ray computed tomography. Despite these variables, the proposed RHWT successfully identifies fabric in these images, demonstrating robustness and validity of RHWT.
Diabetic Retinopathy Is a Predictor of Progression of Diabetic Kidney Disease: A Systematic Review and Meta-Analysis
Authors: Gupta Mansi , Rao Indu Ramachandra , Nagaraju Shankar Prasad , Bhandary Sulatha V. , Gupta Jayanti , Babu Ganesh T. C.
Published: April 2022

Aims and Objectives. This systematic review and meta-analysis aimed to assess the predictive value of diabetic retinopathy (DR) for progression of diabetic kidney disease (DKD). Methods. A systematic search was conducted on PubMed, Embase, and the Google scholar for eligible studies through September 2021. The quality of selected articles was assessed using JBI checklist. Higgins and Thompson’s I2 statistic was used to see the degree of heterogeneity. Based on degree of heterogeneity, fixed or random effects model was used to estimate pooled effect using inverse variance method. Results were expressed as hazard ratios and odds ratios with 95% CIs. Results. After scrutinizing 18017 articles, data from ten relevant studies (seven prospective and three retrospective) was extracted. DR was significantly associated with DKD progression with a pooled HR of 2.42 (95% CI: 1.70–3.45) and a pooled OR of 2.62 (95% CI: 1.76–3.89). There was also a significant association between the severity of DR and risk of progression of DKD with a pooled OR of 2.13 (95% CI: 1.82–2.50) for nonproliferative DR and 2.56 (95% CI: 2.93–.33) for proliferative DR. Conclusion. Our study suggests that presence of DR is a strong predictor of risk of kidney disease progression in DKD patients. Furthermore, the risk of DKD progression increases with DR severity. Screening for retinal vascular changes could potentially help in prognostication and risk-stratification of patients with DKD.
An Efficient Online/Offline Signcryption Scheme for Internet of Things in Smart Home
Authors: Nayab  , Hussain Saddam , Alabrah Amerah , Ullah Syed Sajid , Khattak Hizbullah , Alfakih Taha M. , Ullah Insaf
Published: April 2022

The delivery of unified intelligent services is accomplished through a networked environment comprised of a wide array of electronic devices. Through the use of Internet of Things (IoT) technology, smart homes collect data from their surroundings and use it to improve their tenants’ lives. Remote control, real-time monitoring, and a fire alarm are all characteristics of smart home security. Since smart homes hold personally identifying information about their residents, security is critical to ensure their reliability and prevent data breaches. In this paper, a certificateless online/offline signcryption (COOS) technique for IoT-enabled smart homes is proposed. The proposed solution takes advantage of a resource-constrained smart home device–friendly algorithm known as the Hyperelliptic Curve Cryptosystem (HCC). The suggested approach satisfies the security requirements of unforgeability, confidentiality, resistance to replay attacks, and non-repudiation. The complexity analysis in terms of communicational and computational costs demonstrates the efficiency of the proposed scheme. Finally, we validate the security against Man-In-The-Middle-Attack (MITM) and anti-reply attacks using Automated Validation of Internet Security Protocols and Applications (AVISPA). The data imply that the recommended course of action is safe.
Combined Effect of Compression Ratio and Fuel Injection Pressure on CI Engine Equipped with CRDi System Using Prosopis juliflora Methyl Ester/Diesel Blends
Authors: Ramesh T. , Sathiyagnanam A. P. , De Poures Melvin Victor , Murugan P.
Published: April 2022

The exhaustion of worldwide oil reserves has created an incipient need to find hopeful alternative fuels for the future. Substantial research has been done in this direction, and all studies by researchers have provided results that proved the growing potential of biofuel as a popular alternative in the CI engine. The current investigation explores the biofuel potential derived from the wasteland tree Prosopis juliflora (Karuvalam tree seeds). Experimentation was done using a monocylinder 4-stroke water-cooled six holes CRDi CI engine with electrical loading. The experiment was conducted at three proportions (10%, 20%, and 30% volume basis) of Prosopis juliflora Oil Methyl Ester (PJOME) with diesel using 3 parametric CRs (16, 17.5, and 19) along with three different fuel injection pressure (FIP) (400, 500, and 600 bar). The impact of CR and FIP on fuel utilization BTE, cylinder pressure, net heat release, and exhaust particulates was scrutinized and characterized. The test results demonstrated that increasing the compression ratio from 16 to 19 enhanced the in-cylinder pressure, net heat release (NHR), and BTE for all the (PJOME/Diesel) combinations. With an augmentation in the compression ratio from 16 to 19, carbon monoxide and unburnt hydrocarbon discharge diminished, but the nitrogen oxide discharges augmented. FIP also had an impact of increasing the pressures on the in-cylinder, NHR, brake thermal efficiency, and nitrogen oxide and reducing the emissions of smoke, CO, and UBHC. The current research shows that the use of B20 and CR16 and FIP 600 bar as a combination improved BTE by 33.21%, BSFC by 0.25 kg/kw-hr, cylinder pressure at the maximum to reach 69.28 bar, net heat release of 79.14 J/deg, and exhaust emissions such as UHC at 55 ppm, CO at 0.25%, smoke at 34.33%, and NOx at 2401 ppm. Finally, the BTE and NOx were slightly higher, and the UHC, CO, and smoke values were diminutive compared to other blends.
Model Construction of Urban Public Sports Service System under the Background of Information Technology
Authors: Wang Xin , Zhang Zhihuan
Published: April 2022

The planning and construction of urban public sports are an indispensable guarantee condition for implementing the national fitness plan, further improving the national physique and health status and improving the overall quality of the Chinese nation. With the improvement of Internet technology and various information technologies, urban public sports still publish service information such as consultation and competition through traditional information channels. The distribution channel is relatively single, the degree of informatization is not high, and the level of consulting service is low. In this paper, the model construction of urban public sports service system is studied under the background of information technology. During the period of frequency 30-40, on average, 26.8% of urban residents have participated in various sports training services; during the period of frequency 50-60, 28.6% have received professional fitness guidance services; and during the period of frequency 70-80, 27.5% have participated in professional exercise planning services. Through the model of urban public sports service system built under the background of information technology, the spread range is expanded, and the fixed participants are gradually formed. In this respect, we also enjoy the “technology dividend” of the popularity of network information technology and smart phones, which makes online booking service easier for the audience to use. We should pay attention to the diversified development of public sports service subjects, provide diversified public sports services, actively understand public sports demand, and penetrate the residents’ demand expression mechanism, so as to promote the public sports service system to form a structural state of benign interaction, joint participation, and dynamic communication.
Ideological and Political Education Reform Using Mobile Phones as a Carrier in the Context of Artificial Intelligence
Authors: Sun Qian
Published: April 2022

With the rapid development and transformation of the current society, reform in the education system has reached new heights of development. Also, the evaluation of ideological and political education reform using mobile phones as a carrier for artificial intelligence has become increasingly popular and essential. However, there are some problems in the reform process, though it has many advantages overstanding in a row. The concept of mobile phones as a carrier in artificial intelligence- (AI-) based mobile learning includes a complete teaching and learning process through mobile Internet devices. These Internet of Things (IoT) devices can be tablets, smartphones, and e-readers. In the present scenario, learning on a smartphone is still relatively marginal, while learning on computers and tablets is the subject of many experiments and projects in recent years. Many benefits are regularly put forward to promote mobile Internet technology in education, like more interactivity to enrich the learning, like discussion forums, blog spots, e-classrooms, chatrooms, and learning apps. Reading on mobile phones and in the traditional education system (reading books) improves brain activity. As a result, the concept of mobile phones as a carrier in AI (mobile learning) has more advantages than the traditional educational systems. The present research proposes a set of hypotheses that show mobile learning is way more advantageous than the conventional education system. In this research, remote supervision algorithms with wireless communication technology are proposed to perform the reformation of ideological and political education using mobile phones. The proposed algorithm focuses on the accurate delivery of the online courses, and the algorithm is compared with the existing hybrid K-means method, which has provided 5.03% less accuracy than the proposed method.
Evaluation of Biomechanical and Chemical Properties of Gamma-Irradiated Polycaprolactone Microfilaments for Musculoskeletal Tissue Engineering Applications
Authors: Rojas-Rojas Laura , Ulloa-Fernández Andrea , Castro-Piedra Silvia , Vargas-Segura Walter , Guillén-Girón Teodolito
Published: April 2022

An appropriate and reliable sterilization technique is crucial for tissue engineering scaffolds. Skeletal muscle scaffolds are often fabricated using microfilaments of a wide variety of polymers. One method for sterilization is 25 kGy of gamma irradiation. In addition, sterilization through irradiation should administer a dose within a specific range. Radiation directly affects the chemical and mechanical properties of scaffolds. The accuracy and effects of irradiation are often not considered during sterilization procedures; however, these are important since they provide insight on whether the sterilization procedure is reliable and reproducible. This study focused on the chemical and mechanical characterization of 25 kGy gamma-irradiated scaffold. The accuracy and uncertainty of the irradiation procedure were also obtained. X-ray diffraction (XRD) and differential scanning calorimetry (DSC) analyses were performed to determine whether the crystallinity of the polymer changed after irradiation and whether gamma rays influenced its thermal properties. The tensile parameters of the microfilaments were analyzed by comparing irradiated and nonirradiated scaffolds to determine whether gamma radiation changed their elastic behavior. Dose distribution and uncertainty were recorded with several dosimeters. The results showed that the irradiation process slightly affected the mechanical parameters of the scaffold; however, it did not modify its crystallinity or thermal properties. The irradiation was uniform, since the measured uncertainty was low. The scaffold was pathogen-free after 7 days; this meant sterilization was achieved. These results indicated that gamma-sterilized scaffolds were a promising material for use as a skeletal muscle analog material for tissue-engineering applications because they can be sterilized with gamma rays without changing their chemical structure and mechanical properties. This study provided the dose distribution measurement and uncertainty calculations for the sterilization procedure.
Spatial-Temporal Interpolation of Reference Evapotranspiration for Pakistan
Authors: Saeed Shah Syed Muhammad , El-Morshedy M. , Mansoor Wahidullah
Published: April 2022

The unequal water distribution in the universe has resulted in more than 2 billion people living in water-stressed areas. Globally, withdrawals of water resources are still below the critical level. Pakistan is also affected by this serious problem. In the context of environmental evaluation, irrigation scheduling, and water resource management, evapotranspiration predictions are crucial. The evapotranspiration estimation methods may need to be evaluated daily or monthly to understand the climate change effects in the local areas. This paper investigates spatial-temporal interpolation of evapotranspiration data from 41 Pakistani meteorological stations. To estimate evapotranspiration, we have used the average time series data between 2006 and 2015 on temperature, relative humidity, wind speed, and solar radiation. We developed a new modified Hargreaves equation to estimate evapotranspiration and evaluate the performance of different models. We found that our modified Hargreaves model could perform better than the original Hargreaves model. To analyze trends in different seasons, such as rainy, dry, and annual, FAO-56 Penman-Monteith, Blaney-Criddle, and Hargreaves-Samani models are used. We used Ordinary Kriging for Functional Data to map and predict evapotranspiration spatially and temporally in various locations.
A Hybrid Deep Learning Framework for Network Flow Forecasting of Power Grid Enterprise
Authors: Huang Xin , Hu Ting , Pei Pei , Li Qin , Zhang Xin
Published: April 2022

With the expansion of the digital business line, the network flow behind the digital power grid is also exploding. To prevent network congestion, this article proposes a novel network flow forecasting model, which is composed of variational mode decomposition (VMD), GRU‐xgboost block, and a forecasting adjustment block, to grasp the changing patterns and trends of network flow in advance, and to formulate reasonable and effective flow management strategies and meet the requirements of users for network service quality. The network flow series in power grid enterprise always contain complex patterns and outliers, and VMD is applied to adaptively process complex net flow time series into several subseries with simpler patterns. A GRU‐xgboost block is designed to reconstruct the features of historical series. Then, xgboost model is applied to generate predictions for all decomposed subsignals. For the final predictions, we design a forecasting adjustment block to further remove the influence of random noise. Finally, the empirical results show the superior performance of the proposed model on network flow forecasting task.
Prediction of Air Leakage Rate of Sintering Furnace Based on BP Neural Network Optimized by PSO
Authors: Quan Xiaokai , Zhang Nannan , Yu Guo , Liu Qunfeng , Ma Lianbo
Published: April 2022

Aiming at the difficulty of air leakage detection in the sintering process of the sintering furnace, especially the problems of high detection cost and poor timeliness of detection results when traditional methods are used for detection, we propose an air leakage rate prediction algorithm. Firstly, we use the particle swarm optimization algorithm to optimize the initial parameters of the neural network based on back propagation and get the best set of initial parameters through continuous search. Secondly, the optimized parameters are substituted into the neural network to train them with training data, and the trained parameters are obtained. Finally, the air leakage rate of the test set data is predicted by using the trained parameters. Compared with traditional calculation methods such as gas analysis and calorimetry, the proposed method can greatly simplify the detection process, shorten the detection time, and control the error within 5%, allowing the user to deal with the air leakage problem more timely and improve the overall sintering quality.
Research on Runway Blockage Probability through Simulation
Authors: Wei Wan-Li , Chen Ye-Qing , Wang Zhen-Qing , Wang Jian-Hui , Ren Xin-Jian , Ma Shang
Published: April 2022

The damage and blockade of airport runways are important objectives in modern warfare. The minimum takeoff and landing window is regarded as the damage criterion of an airport runway. On the basis of Mathematica, a simulation is performed by judging whether the inequality group has a solution domain. An improved algorithm for judging whether an airport has a minimum takeoff and landing window is proposed. The algorithm is used to calculate and analyze the blockade probability of an ordinary missile to an airport and the influence of the performance of a guided submunition on the blockade of an airport runway. Results show that increasing the number of submunition, reducing the circular error probable of submunition, and increasing the number of subprojectiles can increase the blocking capability of submunition, while increasing the dispersion radius of subprojectiles will first increase the blocking probability and then decrease it. Through simulation, the inflection point of the blocking efficiency of submunitions is found. This article improves the judgment formula of takeoff and landing window, Compared with the window scanning method, the proposed method solves the problems of error caused by excessively large scanning step and extremely long calculation time caused by considerably small scanning step.
Temporal Relation Extraction with Joint Semantic and Syntactic Attention
Authors: Jin Panpan , Li Feng , Li Xiaoyu , Liu Qing , Liu Kang , Ma Haowei , Dong Pengcheng , Tang Shulin
Published: April 2022

Determining the temporal relationship between events has always been a challenging natural language understanding task. Previous research mainly relies on neural networks to learn effective features or artificial language features to extract temporal relationships, which usually fails when the context between two events is complex or extensive. In this paper, we propose our JSSA (Joint Semantic and Syntactic Attention) model, a method that combines both coarse-grained information from semantic level and fine-grained information from syntactic level. We utilize neighbor triples of events on syntactic dependency trees and events triple to construct syntactic attention served as clue information and prior guidance for analyzing the context information. The experiment results on TB-Dense and MATRES datasets have proved the effectiveness of our ideas.
Myoelectric Pattern Recognition Performance Enhancement Using Nonlinear Features
Authors: Islam Md. Johirul , Ahmad Shamim , Haque Fahmida , Ibne Reaz Mamun Bin , Bhuiyan Mohammad A. S. , Minhad Khairun Nisa’ , Islam Md. Rezaul
Published: April 2022

The multichannel electrode array used for electromyogram (EMG) pattern recognition provides good performance, but it has a high cost, is computationally expensive, and is inconvenient to wear. Therefore, researchers try to use as few channels as possible while maintaining improved pattern recognition performance. However, minimizing the number of channels affects the performance due to the least separable margin among the movements possessing weak signal strengths. To meet these challenges, two time-domain features based on nonlinear scaling, the log of the mean absolute value (LMAV) and the nonlinear scaled value (NSV), are proposed. In this study, we validate the proposed features on two datasets, the existing four feature extraction methods, variable window size, and various signal-to-noise ratios (SNR). In addition, we also propose a feature extraction method where the LMAV and NSV are grouped with the existing 11 time-domain features. The proposed feature extraction method enhances accuracy, sensitivity, specificity, precision, and F1 score by 1.00%, 5.01%, 0.55%, 4.71%, and 5.06% for dataset 1, and 1.18%, 5.90%, 0.66%, 5.63%, and 6.04% for dataset 2, respectively. Therefore, the experimental results strongly suggest the proposed feature extraction method, for taking a step forward with regard to improved myoelectric pattern recognition performance.
Label Propagation Community Detection Algorithm Based on Density Peak Optimization
Authors: Yan Ma , Guoqiang Chen
Published: April 2022

Community structure detection in a complex network structure and function is used to understand network relations and find its evolution rule; monitoring and forecasting its evolution behavior have an important theoretical significance; in the epidemic monitoring, network public opinion analysis, recommendation, advertising push and combat terrorism, and safeguard national security, it has wide application prospect. A label propagation algorithm is one of the popular algorithms for community detection in recent years; the community detection algorithm based on tags that spread the biggest advantage is the simple algorithm logic, relative to the module of optimization algorithm, convergence speed is very fast, the clustering process without any optimization function, and the initialization before do not need to specify the number of complex network community. However, the algorithm has some problems such as unstable partitioning results and strong randomness. To solve this problem, this paper proposes an unsupervised label propagation community detection algorithm based on density peak. The proposed algorithm first introduces the density peak to find the clustering center, first determines the prototype of the community, and then fixes the number of communities and the clustering center of the complex network, and then uses the label propagation algorithm to detect the community, which improves the accuracy and robustness of community discovery, reduces the number of iterations, and accelerates the formation of the community. Finally, experiments on synthetic network and real network data sets are carried out with the proposed algorithm, and the results show that the proposed method has better performance.
Clinical Effect of the Treatment of Lumbar Intervertebral Disc Protrusion
Authors: Zhou Yehui , Yang Ming
Published: April 2022

Compared with traditional acupuncture, it is urgently needed for more effective method for the disease to serve the clinical treatment. This paper combines acupuncture and massage to treat lumbar intervertebral disc protrusion, uses a controlled trial to study the clinical effects of acupuncture combined with massage for the treatment of lumbar intervertebral disc protrusion, combines mathematical statistics to test the data, and compares and analyzes the statistical object parameters. Through experimental research, it is known that in the treatment of lumbar intervertebral disc protrusion, in order to obtain a faster and better effect, traditional acupuncture treatment should be combined with massage therapy. On the basis of fully eliminating the pathological factors, the intervertebral disc is reset by mechanical treatment, which makes the patient more likely to heal. Therefore, it is a comprehensive treatment plan that is worth adopting.
Small Area Estimation of Undernutrition under Age Five Children Based on Spatial-Temporal Models
Authors: Yilema Seyifemickael Amare , Shiferaw Yegnanew A , Zewotir Temesgen , Muluneh Essey Kebede
Published: April 2022

The mean flow of direct survey estimates is mainly concerning the sample adequacy fulfillment unless it has been produced large variance estimates, and therefore, the small area estimations are developed to manage this flaw of the path. Small area estimation improved the direct survey estimates by borrowing strength from the census data and at the same time by using historical data from consecutive surveys. In this paper, we applied the spatiotemporal Fay–Herriot (STFH) model for producing fairly reliable disaggregate-level estimates of undernutrition indicators across all zones. The STFH model is an appropriately fitted model to the undernutrition data since it has the lowest information criteria (IC) value. The spatiotemporal estimates improved both the direct and spatial estimates of undernutrition under the FH model and have brought efficiency gain in the percent coefficient of variation (CV). These results may provide useful information to the government’s planners, policymakers, and legislative organs for effective policy formulation and budget allocation in all zones.
A QoS-Based Fairness-Aware BBR Congestion Control Algorithm Using QUIC
Authors: Han Yi , Zuo Mengjie , Yuan Huijun , Zhong Yi , Yuan Zhenhui , Bi Ting
Published: April 2022

Congestion control is a fundamental technology to balance the traffic load and the network. The Internet Engineering Task Force (IETF) Quick UDP Internet Connection (QUIC) protocol has flexible congestion control and at the same time possesses the advantages of high efficiency, low latency, and easy deployment at the application layer. Bottleneck bandwidth and round-trip propagation time (BBR) is an optional congestion control algorithm adopted by QUIC. BBR can significantly increase throughput and reduce latency, in particular over long-haul paths. However, BBR results in high packet loss in low bandwidth and low fairness in multi-stream scenarios. In this article, we propose the enhanced BBR congestion control (eBCC) algorithm, which improves the BBR algorithm in two aspects: (1) 10.87% higher throughput and 74.58% lower packet loss rate in the low-bandwidth scenario and (2) 8.39% higher fairness in the multi-stream scenario. This improvement makes eBCC very suitable for IoT communications to provide better QoS services.
Research on SVR Water Quality Prediction Model Based on Improved Sparrow Search Algorithm
Authors: Su Xuehua , He Xiaolong , Zhang Gang , Chen Yuehua , Li Keyu
Published: April 2022

Multiparameter water quality trend prediction technique is one of the important tools for water environment management and regulation. This study proposes a new water quality prediction model with better prediction performance, which is combined with improved sparrow search algorithm (ISSA) and support vector regression (SVR) machine. For the problems of low population diversity and easily falling into local optimum of sparrow search algorithm (SSA), ISSA is proposed to increase the initial population diversity by introducing Skew-Tent mapping and to help the algorithm jump out of local optimum by using the adaptive elimination mechanism. The optimal values of the penalty factor C and kernel function parameter

g

of the SVR model are selected using ISSA to make the model have better prediction accuracy and generalization performance. The performance of the ISSA-SVR water quality prediction model is compared with BP neural network, SVR model, and other hybrid models by conducting water quality prediction experiments with actual breeding-water quality data. The experimental results showed that the prediction accuracy of the ISSA-SVR model was significantly higher than that of other models, reaching 99.2%; the mean square deviation (MSE) was 0.013, which was 79.37% lower than that of the SVR model and 75% lower than that of SSA-SVR model, and the coefficient of determination

R

2

was 0.98, which was 5.38% higher than that of the SVR model and 7.57% higher than that of the SSA-SVR model, indicating that the ISSA-SVR water quality prediction model has some engineering application value in the field of water body management.
The Effect of Humanistic Care Combined with Predictive Nursing on Negative Emotions and Incidence of Cardiovascular Events in Hemodialysis Patients
Authors: Wang Yanling , Su Changmin
Published: April 2022

Objective. To explore the effect of humanistic care combined with predictive nursing on the negative emotions and incidence of cardiovascular events in hemodialysis patients. Methods. A total of 90 patients undergoing hemodialysis in our hospital from December 2020 to September 2021 were selected as the research subjects and divided into the study group (

n
=
45

) and the control group (

n
=
45

) by the random number table method. The patients in the control group were given routine nursing, and the patients in the study group were given humanistic care combined with predictive nursing. The effects between the two groups were compared. Results. After nursing, cardiac troponin I (cTn I) level, Hamilton Depression Scale (HAMD) scores, and Hamilton Anxiety Scale (HAMA) scores in the two groups decreased, and the scores were lower in the study group than the control group (

P
<
0.05

). The World Health Organization on Quality of Life Brief Scale (WHOQOL-BREF) scores in both groups increased and were higher in the study group than the control group (

P
<
0.05

). The nursing satisfaction in the study group was higher than that in the control group, and the incidence of cardiovascular adverse events in the study group was lower than that in the control group (

P
<
0.05

). Conclusion. In the process of hemodialysis, the application of humanistic care combined with predictive nursing to hemodialysis patients can significantly decrease the cTn I level, reduce the negative emotions of patients, improve the quality of life and nursing satisfaction of patients, and reduce the occurrence of adverse cardiovascular events.
Liraglutide Is Protective against Brain Injury in Mice with Febrile Seizures by Inhibiting Inflammatory Factors
Authors: Wang Xing , Yang Fei , Deng Liling , Qiu Di , Liu Yao , Kang Yang
Published: April 2022

The febrile seizure (FS) is a common disease in emergency pediatrics, and about 30% of patients are children aged between 6 months and 5 years. Therefore, we aim to observe the protective impact of liraglutide (LIR) on brain injury in mice with FS and to explore its relevant mechanisms. Male SD mice were selected, and the FS model was established by heat bath method. The behavioral score was performed on mice with Racine grading, and nerve cells in apoptosis in the hippocampus were determined by TUNEL. The content of glutamate was determined by ELISA. mRNA levels and protein expression of GLP-1, GLP-1R, IL-1β, IL-6, TNF-α, and cleaved-caspase 3 were examined in mice by q-PCR and WB. Protein expression of γ-aminobutyric acid was influenced by WB as well. LIR prolonged the seizure latency and seizure duration in mice with FS. The GLP-1 and GLP-1R in the mouse hippocampus with FS expressed highly and also inhibited the number of nerve cells in apoptosis, decreased glutamate content, and increased γ-aminobutyric acid expression in the mouse hippocampus with FS. In addition, The IL-1β, IL-6, and TNF-α, in the mouse hippocampus with FS expressed to reduce with LIR. LIR is protective against brain injury in mice with FS and protects brain injury by inhibiting inflammatory factors in mice with FS. Our finding provides a reference for mitigating and delaying the development of FS as well as the prevention and treatment of brain injury caused by FS.
The Relevance of Interventional Time and Clinical Outcomes in Patients with NSTEMI Based on the GRACE Score
Authors: Wang Ji-Xiang , Gao Jing , Xiao Jian-Yong , Gao Ming-Dong , Zhang Nan , Lu Peng-Ju , Liu Yin
Published: April 2022

Objective. To investigate the relevance between interventional time and clinical outcomes in non-ST-elevation myocardial infarction (NSTEMI) patients of different risk stratifications, which were divided into different groups according to GRACE scores and the time from admission to percutaneous coronary intervention (PCI). Method. Patients were grouped according to the GRACE score and the time from admission to intervention therapy. The Cox multivariate risk regression model was used to analyze the correlation between the GRACE score and the time from admission to intervention therapy with major adverse cardiovascular events (MACEs). Cox interactive item regression was also used to investigate the correlation between the time of intervention therapy and GRACE risk stratification with clinical outcomes and to evaluate the efficacy of intervention therapy in different risk stratifications of patients with NSTEMI. Results. Interactive item Cox regression analysis and subgroup analysis show that high-risk NSTEMI patients with a GRACE

score
>
140

points and the time from admission to

intervention
<
24
 
h

(

p
=
0.0004

) and 24–72 h (

p
=
0.0143

) have interactive effects on the impact of the MACE event with the reference of intervention

time
>
72
 
h

and GRACE

score
<
108

points. The time from admission to

intervention
<
24
 
h

is an independent protective factor for the occurrence of MACE events (

HR
=
0.166

, 95% CI 0.052-0.532,

p
=
0.0025

). Middle-risk patients with NSTEMI with a GRACE score of 109–140 points and the time from admission to

intervention
<
24
 
h

(

p
=
0.0370

) and 24–72 h (

p
=
0.0471

) have an interactive effect on the impact of MACE. The time from admission to

intervention
>
72
 
h

is an independent protective factor for the occurrence of MACE (

HR
=
0.201

, 95% CI 0.045-0.897,

p
=
0.0355

). Conclusion. The time from admission to

intervention
<
24
 
h

could effectively reduce the risk of MACE events within 1 year in high-risk patients with NSTEMI (GRACE

score
>
140

points); the time from admission to

intervention
>
72
 
h

can reduce the risk of MACE events within 1 year in low-risk patients with NSTEMI (GRACE

score
≤
108

points).
Visual Communication Design in Print Advertising under New Media Environment
Authors: Zhang Yue , Yu Runze , Shi Xuehu , Hong Kyungmin
Published: April 2022

The emergence of too many new media in the information age has also brought about the trouble of complicated information. Every day, people’s eyes are exposed to at least hundreds of advertisements. The audience’s attention is limited, and the number of advertisements is constantly increasing. The public suffers from severe visual fatigue. New media can be seen everywhere in our daily life. In today’s digital world, people cannot leave multimedia technology. This paper is aimed at exploring the visual communication design in print advertising in the new media environment. Aiming at the visual communication technology in print advertisements, this paper describes the stereo vision technology in detail and rationally analyzes the design ideas of visual communication through the stereo vision technology. In addition, this paper conducts on-the-spot investigation and analysis of print advertisements in the media environment, to explore the visual communication design ideas in print advertisements. Experiments show that for different groups of people, the acceptance of print advertisements in the new media environment is not the same. In terms of acquisition methods, television is still the carrier for most people to obtain information, accounting for 40.67%. Secondly, obtaining advertisements through mobile applications is the second, accounting for 33.3%.
Construction of a Digital Platform for Enterprise Financial Management Based on Visual Processing Technology
Authors: Deng Yuenan
Published: April 2022

Along with the continuous socioeconomic growth, more capital injection is needed to meet the daily operating cash flow demand compared to the traditional development model, so it is necessary to study the digital capability of enterprise financial management. Based on the evolutionary logic of financial risk identification, evaluation, and control, this paper summarizes the most suitable feature processing algorithm process for enterprise financial management systems by visual processing technology; for the visual guidance system, it needs to be able to identify artifacts quickly and accurately and compare different visual recognition algorithms experimentally. Considering the accuracy and real time of the visual guidance system, the efficiency of the algorithm is improved as much as possible under the condition of ensuring the accuracy, including the collection of work area features and the filtering preprocessing of data features, edge detection, and feature extraction, and, finally, the coordinate conversion can be carried out effectively to meet the requirements of the system for speed and accuracy. The digital platform for enterprise financial management built in this paper gives risk management strategies and implementation plans in six aspects, including improving the internal environment for risk management, setting control objectives in line with the development of the company, focusing on the response and control of major risks, ensuring efficient communication of information, and strengthening supervision. In terms of profitability risk, we propose to improve asset utilization, establish additional investment risk management departments, enhance capital utilization efficiency, and create core mobile products; in terms of asset operation, we propose to increase asset risk management, expand product sales scale, standardize cash flow system, and use centralized bank accounts.
Clinical Characteristics and Risk Factors for Pulmonary Infection in Emergency ICU Patients
Authors: Zhang Yan , Cao Hui , Gong Xiang , Wu Yang , Gu Peng , Kong Linling , Wu Limeng , Xing Jiali
Published: April 2022

Background. Pulmonary infection in the emergency ICUs increases patient morbidity, hospital stay, treatment costs, and the risk of related adverse events. Methods. This study included 695 patients admitted to our emergency ICU between December 2019 and March 2021. Medical records of emergency ICU patients were reviewed to collect their clinical data, including antibiotic use, history of tracheostomy, history of mechanical ventilation, presence or absence of underlying disease, history of smoking, alcohol consumption, age, gender, and history of shock. Bacterial cultures were performed. The incidence, main clinical features, main pathogens, and risk factors of pulmonary infection in emergency ICU were analyzed. Results. In this study, 69 of the 695 emergency ICU patients (9.93%) developed pulmonary infection. The main clinical features of patients with pulmonary infection included cough and expectoration (97.10%), shortness of breath and chest tightness (95.65%), leukocyte elevation (69.57%), confusion (31.88%), drowsiness (28.99%), persistent fever (27.54%), and nausea and vomiting (10.14%). The main pathogenic bacteria in those with pulmonary infection included Klebsiella pneumoniae (62.32%), Pseudomonas aeruginosa (49.28%), Streptococcus pneumoniae (21.74%), Staphylococcus aureus (39.13%), Candida albicans (7.25%), Pneumococcus pneumoniae (15.95%), Pseudomonas aeruginosa (24.64%), and lung diplococcus inflammatory (13.04%). Univariate analysis showed that there were no significant differences in the occurrence of pulmonary infection with regard to sex, smoking, and alcohol consumption, but there were significant differences with regard to age, basic disease, invasive surgery, and shock. Logistic regression analysis confirmed that

age
≥
80
 
years

, invasive surgery, shock, and

basic
 
diseases
≥
2

were important risk factors for pulmonary infection in emergency ICU patients. Conclusion. Considering the clinical features and risk factors for pulmonary infection in the emergency ICU, preventive and control measures are required to minimize its occurrence and ensure good outcomes.
Topologic Reorganization of White Matter Connectivity Networks in Early-Blind Adolescents
Authors: Zhou Zhifeng , Qian Long , Xu Jinping , Lu Yumin , Hou Fen , Zhou Jingyi , Luo Jinpei , Hou Gangqiang , Jiang Wentao , Li Hengguo , Liu Xia
Published: April 2022

Blindness studies are important models for the comprehension of human brain development and reorganization, after visual deprivation early in life. To investigate the global and local topologic alterations and to identify specific reorganized neural patterns in early-blind adolescents (EBAs), we applied diffusion tensor tractography and graph theory to establish and analyze the white matter connectivity networks in 21 EBAs and 22 age- and sex-matched normal-sighted controls (NSCs). The network profiles were compared between the groups using a linear regression model, and the associations between clinical variables and network profiles were analyzed. Graph theory analysis revealed “small-world” attributes in the structural connection networks of both EBA and NSC cohorts. The EBA cohort exhibited significant lower network density and global and local efficiency, as well as significantly elevated shortest path length, compared to the NSC group. The network efficiencies were markedly reduced in the EBA cohort, with the largest alterations in the default-mode, visual, and limbic areas. Moreover, decreased regional efficiency and increased nodal path length in some visual and default-mode areas were strongly associated with the period of blindness in EBA cohort, suggesting that the function of these areas would gradually weaken in the early-blind brains. Additionally, the differences in hub distribution between the two groups were mainly within the occipital and frontal areas, suggesting that neural reorganization occurred in these brain regions after early visual deprivation during adolescence. This study revealed that the EBA brain structural network undergoes both convergent and divergent topologic reorganizations to circumvent early visual deprivation. Our research will add to the growing knowledge of underlying neural mechanisms that govern brain reorganization and development, under conditions of early visual deprivation.
[Retracted] Discovering Common Pathophysiological Processes between COVID‐19 and Cystic Fibrosis by Differential Gene Expression Pattern Analysis
Authors: Hasan Md. Tanvir , Abdulrazak Lway Faisal , Alam Mohammad Khursheed , Islam Md. Rezwan , Sathi Yeasmin Hena , Al-Zahrani Fahad Ahmed , Ahmed Kawsar , Bui Francis M. , Moni Mohammad Ali
Published: April 2022

Coronaviruses are a family of viruses that infect mammals and birds. Coronaviruses cause infections of the respiratory system in humans, which can be minor or fatal. A comparative transcriptomic analysis has been performed to establish essential profiles of the gene expression of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS‐CoV‐2) linked to cystic fibrosis (CF). Transcriptomic studies have been carried out in relation to SARS‐CoV‐2 since a number of people have been diagnosed with CF. The recognition of differentially expressed genes demonstrated 8 concordant genes shared between the SARS‐CoV‐2 and CF. Extensive gene ontology analysis and the discovery of pathway enrichment demonstrated SARS‐CoV‐2 response to CF. The gene ontological terms and pathway enrichment mechanisms derived from this research may affect the production of successful drugs, especially for the people with the following disorder. Identification of TF‐miRNA association network reveals the interconnection between TF genes and miRNAs, which may be effective to reveal the other influenced disease that occurs for SARS‐CoV‐2 to CF. The enrichment of pathways reveals SARS‐CoV‐2‐associated CF mostly engaged with the type of innate immune system, Toll‐like receptor signaling pathway, pantothenate and CoA biosynthesis, allograft rejection, graft‐versus‐host disease, intestinal immune network for IgA production, mineral absorption, autoimmune thyroid disease, legionellosis, viral myocarditis, inflammatory bowel disease (IBD), etc. The drug compound identification demonstrates that the drug targets of IMIQUIMOD and raloxifene are the most significant with the significant hub DEGs.
A ceRNA Network Composed of Survival-Related lncRNAs, miRNAs, and mRNAs in Clear Cell Renal Carcinoma
Authors: Lu Wenjun , Liu Hengchen , Zhang Xin , Guo Yujun , Liu Lu , Guo Tieyun , Qu Liqin , Yang Shulong , Li Zhaozhu
Published: April 2022

Clear cell renal carcinoma (ccRCC) is one of the most common renal carcinomas worldwide, which has worse prognosis compared with other subtypes of tumors. We propose a potential RNA regulatory mechanism associated with ccRCC progression. Accordingly, we screened out clinical factors and the expression of RNAs and miRNAs of ccRCC from the TCGA database. 9 lncRNAs (FGF12-AS2, WT1-AS, TRIM36-IT1, AC009093.1, LINC00443, TCL6, COL18A1-AS1, AC110619.1, HOTTIP), 2 miRNAs (mir-155 and mir-21), and 3 mRNAs (COL4A4, ERMP1, PRELID2) were selected from differential expression RNAs and built predictive survival models. The survival models performed very well in predicting prognosis and were found to be highly correlated with tumor stage. In addition, the survival-related lncRNA-miRNA-mRNA (ceRNA) network was constructed by 18 RNAs including 12 mRNAs, 2 miRNAs, and 4 lncRNAs. It is found that the “ECM-receptor interaction,” “Pathways in cancer,” and “Chemokine signaling pathway” as the main pathways in KEGG pathway analysis. Overall, we established predictive survival model and ceRNA network based on multivariate Cox regression analysis. It may open a new approach and potential biomarkers for clinical prognosis and treatment of ccRCC patients.
Analysis of the Electrical Performance of Multituned VLF Thirteen-Tower Umbrella Antennas
Authors: Xu Xiangyu , Xie Hui , Luo Zhiqing , Wan Lu
Published: April 2022

The concept of multituned thirteen-tower umbrella antenna is developed in this study to address the problem that increasing the power capacity of a single-tuned VLF transmitting antenna leads to a decrease in self-resonance. The calculation method of electrical parameters such as input resistance and radiation efficiency is theoretically analyzed based on the radiation resistance of different antenna units in a thirteen-tower umbrella antenna, and the electrical performance of the single-tuned and multituned thirteen-tower umbrella antennas is simulated and compared with the measured results of the Cutler antenna. Under the same antenna structure parameters and input power, the antenna radiation efficiency of the multituned thirteen-tower umbrella antenna is basically the same as that of the single tuned one. However, the multituned antenna has lower input current and higher self-resonance, which can effectively improve the antenna’s safety and broaden its operating frequency range.
Research on the Determination Technology of Key Position of Sealing Holes for Gas Extraction Drilling in Zhangcun Coal Mine
Authors: Li Yaobin , Dong Huanhuan , Guo Xin
Published: April 2022

In view of the problem of how to determine the position of the sealing hole and increase the concentration of gas extraction, this article proposes the use of a high‐pressure gas attenuation method to test the key sealing position and the comparison test of the sealing method using the new sealing position and the traditional sealing position, proposes a method to determine the range of the coal seam roadway loosening belt by measuring the pressure attenuation, and develops a set of devices for rapid determination of the range of the loose belt. Through the field test in Zhangcun Coal Mine, it is shown that when the sealing range is 7.5 m∼18 m, the best effect can be achieved, and when the sealing length is greater than the loose belt, the extraction concentration is higher, and the concentration attenuation and long drilling life are long.