bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of New Media Big Data in Visual Performance of Axonometric Illustration
Authors: Zhou Jia
Published: October 2022

With the rapid development of Internet technology today, especially in the fields of new media, digital TV, digital movies, smartphones, smart hardware, mobile Internet and big data, new media forms bring us a shocking sensory experience. Axonometric illustration, a traditional and modern artistic expression, is becoming more and more attractive in the new media era. Today, with the continuous progress of science and technology, the continuous innovation of thinking, and the rapid improvement of public aesthetics, traditional axonometric illustrations have been unable to adapt to the gradual improvement of people’s needs for artistic aesthetics. This paper will start from the research background of “new media” and combine the characteristics of the axonometric illustration industry itself. On the basis of analyzing related theories at home and abroad, the literature research method and algorithm-driven method are used comprehensively. It can not only effectively improve the visual effect of axonometric illustration by 12.3% but also solve the problems and challenges faced by the current China’s axonometric illustration industry.
Docosahexaenoic Acid Alleviates Brain Damage by Promoting Mitophagy in Mice with Ischaemic Stroke
Authors: Sun Eryi , Zhang Jing , Deng Yan , Wang Jun , Wu Qi , Chen Wei , Ma Xiaodong , Chen Siyuan , Xiang Xin , Chen Yujie , Wu Tairong , Yang Yang , Chen Bo
Published: October 2022

Mitophagy, the selective removal of damaged mitochondria through autophagy, is crucial for mitochondrial turnover and quality control. Docosahexaenoic acid (DHA), an essential omega-3 fatty acid, protects mitochondria in various diseases. This study aimed to investigate the neuroprotective role of DHA in ischaemic stroke models in vitro and in vivo and its involvement in mitophagy and mitochondrial dysfunction. A mouse model of ischaemic stroke was established through middle cerebral artery occlusion (MCAO). To simulate ischaemic stroke in vitro, PC12 cells were subjected to oxygen–glucose deprivation (OGD). Immunofluorescence analysis, western blotting (WB), electron microscopy (EM), functional behavioural tests, and Seahorse assay were used for analysis. DHA treatment significantly alleviated the brain infarction volume, neuronal apoptosis, and behavioural dysfunction in mice with ischaemic stroke. In addition, DHA enhanced mitophagy by significantly increasing the number of autophagosomes and LC3-positive mitochondria in neurons. The Seahorse assay revealed that DHA increased glutamate and succinate metabolism in neurons after ischaemic stroke. JC-1 and MitoSox staining, and evaluation of ATP levels indicated that DHA-induced mitophagy alleviated reactive oxygen species (ROS) accumulation and mitochondrial injury. Mechanistically, DHA improved mitochondrial dynamics by increasing the expression of dynamin-related protein 1 (Drp1), LC3, and the mitophagy clearance protein Pink1/Parkin. Mdivi-1, a specific mitophagy inhibitor, abrogated the neuroprotective effects of DHA, indicating that DHA protected neurons by enhancing mitophagy. Therefore, DHA can protect against neuronal apoptosis after stroke by clearing the damaged mitochondria through Pink1/Parkin-mediated mitophagy and by alleviating mitochondrial dysfunction.
Center Loss Guided Prototypical Networks for Unbalance Few-Shot Industrial Fault Diagnosis
Authors: Yu Tong , Guo Haobin , Zhu Yiyi
Published: October 2022

The success of deep learning is based on a large number of tagged data, which is challenging to satisfy on many occasions. Especially in industry fault diagnosis, considering the cost of data collection, the fault data are few and severely unbalanced. Therefore, it is not enough to support a reliable data-driven deep learning model. Few-shot learning effectively solves the few sample problems, but traditional methods pay little attention to the impact of unbalanced data. However, imbalanced data exists in large quantities. At the same time, unbalanced data often causes decision boundaries to be biased towards categories with larger sample sizes, resulting in lower accuracy. This study proposes a prototype network incorporating center loss for diagnosing industrial faults with few-shot samples. Based on the prototypical networks, by adding center loss at the loss level, the mapping points of the samples in the feature space play the role of intraclass contraction and interclass separation, thereby improving the classification effect. The experiment takes the TE process industrial data set as an example. Comparing various current few-shot learning methods reflects the superiority of the method proposed in the few-shot imbalanced scenario.
Game-Theoretical Data Offloading for NOMA-Enabled Urban Internet of Things
Authors: Hu Jintao , Xu Jiajie , Zhao Jie , Chen Ying , Huang Jiwei
Published: October 2022

Urban Internet of Things (IoT) plays an extremely important role in our daily life by deploying smart cities and urban brains. Orthogonal multiple access (OMA) technology has been a commonly used communication method in recent years, but nonorthogonal multiple access (NOMA) attracts the attention of many researchers due to its superiority of successive interference cancellation (SIC) technology. We consider adding the base station (BS) and unmanned aerial vehicle (UAV) to perform collaborative data offloading services with urban IoT devices and introduce the NOMA technology to improve offloading efficiency. In order to solve the data unloading problem in this model cost-effectively, we formulate the model as a game model based on noncooperative competition and propose the iterative game-based data offloading algorithm (GDOA) to obtain the Nash equilibrium (NE) solution. Finally, we use the simulation data to conduct parametric analysis experiments and comparison experiments on GDOA to evaluate its real performance.
Smart Health Monitoring System with Wireless Networks to Detect Kidney Diseases
Authors: Dhanke Jyoti , Rathee Naveen , Vinmathi M.S. , Janu Priya S. , Abidin Shafiqul , Tesfamariam Mikiale
Published: October 2022

It is essential to change health services from a hospital to a patient-centric platform since medical costs are steadily growing and new illnesses are emerging on a worldwide scale. This study provides an optimal decision support system based on the cloud and Internet of Things (IoT) for identifying Chronic Kidney Disease (CKD) to provide patients with efficient remote healthcare services. To identify the presence of medical data for CKD, the proposed technique uses an algorithm named Improved Simulated Annealing-Root Mean Square -Logistic Regression (ISA-RMS-LR). The four subprocesses that make up the proposed model are a collection of data, preprocessing, feature selection, and classification. The incorporation of Simulated Annealing (SA) during Feature Selection (FS) enhances the ISA-RMS-LR model’s classifier outputs. Using the CKD benchmark dataset, the ISA-RMS-LR model’s efficacy has been verified. According to the experimental findings, the proposed ISA-RMS-LR model effectively classifies patients with CKD, with high sensitivity at 99.46%, accuracy at 99.26%, Specificity at 98%, F-score at 99.63%, and kappa value at 98.29%. The proposed system has many benefits including the fast transmission of medical data to the medical personnel, real-time tracking, and registration condition of the patient through a medical record. Potential enhancement of the performance measures the provider system’s hospital capacity and monitoring of a significant number of patients with a concentrated average delay.
Multimodal Opera Performance Form Based on Human-Computer Interaction Technology
Authors: Wu Lin
Published: October 2022

“Audience Engagement (AE)” describes how a stage performance affects the audience’s thoughts, provokes a bodily response, and spurs cognitive growth. With little audience involvement, theatre performing arts like opera typically have difficulty keeping audiences’ attention. The brain-computer interaction (BCI) technology could be used in opera performances to alter the audience’s emotional experience. Nevertheless, for such BCI systems to function, they must accurately identify their participants’ present emotional states. Although difficult to evaluate, audience participation is a vital sign of how well an opera performs. Practical methodological approaches for real-time perception and comprehension of audience emotions include psychological and physiological assessments. Hence, a multimodal emotional state detection technique (MESDT) for enhancing the AE in opera performance using BCI has been proposed. Three essential steps make up a conceptual MESDT architecture. An electroencephalogram (EEG) and other biological signs from the audience are first captured. Second, the acquired signals are processed, and the BCI tries to determine the user’s present psychological response. Third, an adaptive performance stimulus (APS) is triggered to enhance AE in opera performance, as determined by a rule base. To give the opera audience a high-quality viewing experience, the immersive theatre performance has been simulated. Fifty individuals have been used in the experimental assessment and performance studies. The findings demonstrated that the proposed technology had been able to accurately identify the decline in AE and that performing stimuli had a good impact on enhancing AE during an opera performance. It has been further shown that the suggested design improves the overall performance of AE by 5.8% when compared to a typical BCI design (one that uses EEG characteristics solely) for the proposed MESDT framework with BCI.
[Retracted] Construction of Mitochondrial Protection and Monitoring Model of Lon Protease Based on Machine Learning under Myocardial Ischemia Environment
Authors: Wang Jinliang , Zhang Yang , Shi Haijiao , Yang Ying , Wang Shuai , Wang Fengrong
Published: October 2022

The localization of a protein’s submitochondrial structure is important for therapeutic design of associated disorders caused by mitochondrial abnormalities because many human diseases are directly tied to mitochondria. When Lon protease expression changes, glycolysis replaces respiratory metabolism in the cell, which is a common occurrence in cancer cells. The fact that protein formation is a dynamic research object makes it impossible to reproduce the unique living environment of proteins in an experimental setting, which surely makes it more challenging to determine protein function through experiments. This research suggests a model of Lon protease‐based mitochondrial protection under myocardial ischemia based on ML (machine learning). To ensure the balance of all submitochondrial proteins, the data set is processed using a random oversampling method, each overlapping fixed‐length subsequence that is created from the protein sequence functions as a channel in the convolution layer. The results demonstrate that applying the oversampling strategy increases the ROC value by 17.6%‐21.3%. Our prediction method is successful as evidenced by the fact that ML prediction outperforms the predictions of other conventional classifiers.
Virtual Simulation Design Facing Smart Payment Screen on the Background of Artificial Intelligence
Authors: Li Yan , Wang Xiao
Published: October 2022

In recent years, the rapid development of virtual simulation technology has become a hot topic among thousands of people. Virtual simulation has been used in education, transportation, anti-theft, and other fields, but it has not seen its application in the field of intelligent payment. This study designed an intelligent payment screen based on virtual simulation technology and evaluated the relevant performance. The evaluation results found that compared with the traditional payment screen, the use of smart payment screen for payment had the fastest improvement in security and the slowest improvement in usability, an increase of 4.2%; the youth group believed that the convenience of use of the smart payment screen based on virtual simulation technology has improved the fastest. The elderly group believed that the use of the smart payment screen based on virtual simulation technology had the slowest improvement in ease of use, an increase of 9.4%; the average payment time of each place has decreased, the average payment time of place 4 was the longest, and the average payment time of place 6 was the shortest, and it was concluded that the higher the payment success rate was, the shortest payment time was; in terms of the user’s preference for the smart payment screen, it was concluded that 18:00 was the peak period for users to use the smart payment screen; in terms of risk assessment of using smart payment screens, it was concluded that compared with traditional payment screens, operational risk was reduced by 3.88%, credit risk was reduced by 4.67%, liquidity risk was reduced by 5.06%, and settlement risk was reduced by 6.01%. The design of the smart payment screen makes the user’s payment more secure, and the payment risk is greatly reduced.
Design and Implementation of Continuing Education Online Training System Based on Artificial Intelligence Algorithm
Authors: Zheng Shihua
Published: October 2022

With the continuous development and maturity of artificial intelligence algorithms, there are more cross-concepts in continuing education, so continuing education has begun to develop on the Internet. The continuing education online training system realizes nonreal-time teaching methods, breaks the limitations of time and space, solves the conflict between continuing education engineering and learning, and promotes the sharing of high-quality teaching resources. However, the current continuing education online training system has many defects and imperfections. For example, many continuing education colleges only consider building resources and teaching forms to design online learning systems, and these high-quality resources and teaching forms are difficult to be effectively utilized. Based on this background, this paper establishes a continuing education online training system combined with artificial intelligence algorithms, which is divided into course management, question bank management, learning management, homework management, question-and-answer management, online learning process monitoring management, basic data management, system management, etc. Then, by matching the relevance of the above courses, individual courses are recommended for students to complete the continuing online training education. The system has been highly appraised by the majority of students. The user said that the system can effectively solve practical problems, which is known for the effectiveness of the system design in this paper, thus providing reasonable help for improving the teaching quality. In this paper, we deeply study artificial intelligence algorithms and apply them to the field of continuing education to design a new type of online education system.
A Multiview Deep Learning Method for Brain Functional Connectivity Classification
Authors: Ji Yu , Yang Cuicui , Liang Yuze
Published: October 2022

The brain functional connectivity classification based on deep learning is a research hotspot nowadays. However, the classification performance is far behind the demand of clinical applications. To alleviate the problem, this paper proposes a multiview deep learning method for brain functional connectivity classification. Firstly, the proposed method adopts multiple brain atlases to identify brain regions and thereby builds different brain functional connectivity of different views. Secondly, it uses a multiview feature selection strategy to select out the most discriminative features of each view with the assistance of other views. Then, it trains a stacked autoencoder to extract deep features of the brain functional connectivity of each view. At last, it utilizes a multiview fusion strategy to take full advantage of complementary information of different views for brain functional connectivity classification. The proposed method has been compared with several deep learning-based brain functional connectivity classification methods on three public datasets of neuropsychiatric disorders. The experimental results have validated the superior performance of the proposed method.
Influence of Friction Stir Welding Process on the Mechanical Characteristics of the Hybrid Joints AA2198-T8 to AA2024-T3
Authors: Alemdar Ahmed Samir Anwar , Jalal Shawnim R , Mulapeer Mohammedtaher M Saeed
Published: October 2022

The study presents the hybrid joining of the third generation AA2198-T8 aluminum lithium alloy to AA2024-T3 aluminum copper alloy, which has been highly demanded recently in the aerospace industry. This investigation aims to reduce the cost of production in the industrial sector. As a result, an affordable alternative is to use hybrid designs using AA2198-T8 alloy in crucial parts and AA2024-T3 alloy in the rest of the structure. A joining method is required to create hybrid structures composed of last-generation and standard aluminum alloys. The joining process was successfully friction stir-welded using five different welding travel speeds—36, 76, 102, 146, and 216 mm/min—with an invariable spindle speed of 960 rev/min. Two reversed steps, double-sided friction stir welding (DS-FSW) and single-sided friction stir welding (SS-FSW) techniques with two appropriate tool designs, were employed to investigate the dissimilar material mechanical properties and their morphological changes. The experimental outcomes show that DS-FSW of the reversed steps has a higher joining strength than SS-FSW for all the welding parameters studied. The variation in travel speeds provided the highest strength at 102 mm/min travel welding speeds for DS-FSW. Therefore, it is found that, from the three tensile samples, tensile strength, yield strength, and elongation of the joint were 407.1 MPa, 271.2 MPa, and 9.5%, respectively. The joint efficiency reached 87% compared with the base material tensile strength of AA2024-T3. Furthermore, fractures of the tensile samples were found in the vicinity of the thermomechanically affected zone (TMAZ) of the AA2198-T8 side. The microhardness and morphology results correspondingly have precise predictions for the fracture zone of the joints in this research examination.
Dynamic Performance Analysis of a Curved Cable‐Stayed Bridge Based on the Direct Method and the Sensitivity‐Based Iterative Method
Authors: Fa Guanzhe , He Leqia , Fenu Luigi , Briseghella Bruno
Published: October 2022

Curved cable‐stayed bridges have been regularly accepted due to their ability to cross long spans, and a number of studies have been conducted to investigate the mechanical or dynamic performance of them. Meanwhile, currently just a few studies focus on the curved composite cable‐stayed bridges. In this study, an operational modal testing and finite element model updating of a conventional straight bridge with the steel‐concrete composite girder were conducted to investigate the performance of the potential methods for the model updating, which included the direct method and the sensitivity‐based iterative method. Then, dynamic tests were performed for one typical curved steel‐concrete composite cable‐stayed bridge as the key case study. A highly refined finite element model of the bridge was developed and then calibrated based on the aforementioned methods in reference to the experimental results. Finally, the dynamic behavior of the curved steel‐concrete composite cable‐stayed bridge was studied based on the model. It is found that the solution accuracy of the finite element model can be improved significantly by employing the structural health monitoring technique. Moreover, by using the iterative method, the solutions of the updating parameters are generally more accurate compared with the solutions of the direct method. Nevertheless, when the appropriate choices are made for the algorithmic parameters, both methods can lead to the updated models with satisfactory numerical analysis results as compared to the experimental data.
A New Feature Extraction Method of Marine Ambient Noise Based on Multiscale Dispersion Entropy
Authors: Xiao Leilei
Published: October 2022

Marine ambient noise (AN) is a nonlinear and unstable signal, traditional dispersion entropy can only analyze the marine AN from a single scale, which is easy to cause the loss of information. To address this problem, we introduced multiscale dispersion entropy (MDE), and then a new feature extraction method of marine ambient noise based on MDE is proposed. We used MDE, multiscale permutation entropy (MPE), multiscale permutation Lempel–Ziv complexity (MPLZC), and multi-scale dispersion Lempel–Ziv complexity (MDLZC) to carry out feature extraction and classification recognition experiments for six ANs. The experimental results show that for the feature extraction methods based on MDE, MPE, MDLZC, and MPLZC, with the increase of the number of features, the feature extraction effect becomes better, and the average recognition rate (ARR) becomes higher; compared with other three feature extraction methods, the feature extraction method based on MDE has the best feature extraction effect and the highest ARR for the six ANs under the same feature number.
Antifilarial Activity of the Methanolic Extract of Indigofera tinctoria (Fabaceae) on Bovine Parasites (Onchocerca ochengi)
Authors: Rakwa Enock Enock , Koubala Benoît Bargui , Mando Bertrand Ndou , Djongra Mathieu , Nveikoueing Francis , Ndjonka Dieudonné
Published: October 2022

Onchocerciasis is a major public health problem caused by Onchocerca volvulus parasite and transmitted to humans via black flies (simulium) bites. The control of onchocerciasis relies much on the use of the chemical drug ivermectin, which is only effective against microfilariae and has led to drug resistance. This study was carried out to assess the in vitro antifilarial activity of methanolic extract of Indigofera tinctoria and its most active fractions on adult male O. ochengi worm, the closest model to O. volvulus, after 48 h and 72 h of treatment. Worms’ viability was determined biochemically by MTT/formazan colorimetry assay. The promising plant extract’s acute and subacute oral toxicity were evaluated on both mice and rats. The result revealed a highest antifilarial activity of the methanolic extract (

L

C

50

=
12.28
 
μ
g
/
mL

) compared to ivermectin (

L

C

50

=
26.50
 
μ
g
/
mL

) after 72 h of treatment. Out of the eight (08), chromatographic fractions screened, only three (03) fractions (C, F, and G) revealed the highest anti-Onchocerca activity after 72 h of treatment. An oral administration of the plant extract at a single dose of 2000 mg/kg did not produce any toxicity in mice. After repeated daily administration of methanolic extract of I. tinctoria (250 mg/kg, 500 mg/kg, and 1000 mg/kg) for 28 days, no significant changes in body weight, biochemical, and haematological parameters was observed. Histopathological examination of organs did not reveal any sign of alteration. The phytochemical analysis of the methanolic extract of I. tinctoria revealed the presence of various phenolic compounds. Therefore, this study demonstrated the potential antifilarial activity of Indigofera tinctoria and offered an alternative to treating onchocerciasis. Moreover, further studies could be developed in promising new antifilarial sources of the isolated compound and in vivo antifilarial activity of Indigofera tinctoria in the animal model needs to be studied.
Analysis of Transportation Network Scheduling of Maritime Silk Road and International Digital Trade Potential Based on Improved Genetic Algorithm under Digital Trade Barriers
Authors: Zhang Zhuo , Pan Kunyou
Published: October 2022

The purpose is to improve the ship scheduling capability of the Maritime Silk Road transportation network and advance the international digital trade capabilities along China’s Maritime Silk Road. The optimization process of ship network scheduling based on a simulated annealing- (SA-) improved genetic algorithm (GA) is studied. Then, according to the time-varying stochastic frontier gravity model, the potential of international digital trade between China and the countries on the western route of the Maritime Silk Road is analyzed. The model is simulated and verified. The results reveal that the improved GA has obvious advantages over other algorithms in the message delivery rate of the high-speed and low-speed TT Controller Area Network (TTCAN) protocol for ship control. Regardless of the external environment and the number of message nodes, the message delivery rate is above 95%, showing a high delivery rate and the best network scheduling effect. The total volume and proportion of trade between China and the countries along the western route of the Maritime Silk Road can represent a good growth trend over time, and the proportion of digital trade exports has increased from 9.75% in 2009 to 45.12% in 2020. China has great potential for the development of the countries along the Silk Road as a whole. The main contribution of the research is to construct the ship network scheduling optimization process of the GA improved by the SA and use the time-varying stochastic frontier gravity model to study the digital trade potential between China and the countries along the Maritime Silk Road. The data information management system for network dispatching of marine ships has been improved, and the optimal dispatching efficiency has been enhanced.
The Impact of C-Peptide and Diabetes Mellitus on Coronary Ectasia and Effect of Coronary Ectasia and C-Peptide on Long-Term Outcomes: A Retrospective Cohort Study
Authors: Toprak Kenan , Kaplangoray Mustafa , Palice Ali
Published: October 2022

Background. Coronary artery ectasia (CAE) is an entity frequently associated with atherosclerotic coronary artery disease (CAD) in clinical practice. Although it has common risk factors with atherosclerotic CAD in its development, the pathophysiology of CAE is not fully known and it is not seen in every CAD suggesting that different determinants may play a pivotal role in the development of CAD. This study aimed to reveal the impact of C-peptide and diabetes mellitus (DM) on CAE and the effect of C-peptide and coronary ectasia on long-term outcomes in patients who underwent coronary angiography. Methods. A total of 6611 patients who underwent coronary angiography were followed up retrospectively, and their major adverse cardiovascular event (MACE) status of an average of sixty months was recorded. According to their angiographic features, the patients were divided into two groups those with and without CAE. MACE development was accepted as the primary endpoint. Results. A total of 552 patients had CAE and MACE developed in 573 patients. Patients with CAE and higher C-peptide levels (Q4 + Q3) showed higher rates of MACE as compared to those without CAE and lower C-peptide levels (Q1 + Q2) (20.8% vs 7.6%; 70.1% vs 29.1%;

p
<
0.001

, for both of them). In multivariate regression analysis, high C-peptide levels were determined as an independent risk factor for CAE (OR 2.417; 95% CI 2.212–2.641;

p
<
0.001

). The Kaplan–Meier cumulative survival curves showed that the risks for MACE increased as the C-peptide levels increased. The Cox regression analysis for 5-years MACE related to the plasma C-peptide levels and presence of CAE, C-peptide, and CAE were found to be independent predictors of MACE (HR = 1.255, 95% CI: 1.164–1.336,

p
<
0.001

and HR = 1.012, 95% CI: 1.002–1.023,

p
=
0.026

, respectively). Conclusion. Our study revealed that a high C-peptide level is an independent risk factor for CAE and that CAE and C-peptide are independent predictors for the development of MACE.
Admission Hypothermia and Factors Associated with Mortality among Admitted Hypothermic Preterm Neonates in Neonatal Intensive Care Units of Public Hospitals of Addis Ababa, Ethiopia
Authors: Getaneh Fekadeselassie Belege , Misganaw Natnael Moges , Mihretie Dires Birhanu , Bitew Zebenay Workneh
Published: October 2022

Background. Limited knowledge on the proportion of admission hypothermia and factors of death in hypothermic preterm neonates is hindering early and appropriate interventions in Ethiopia. Thus, studies on the proportion of admission hypothermia and factors of death in hypothermic preterm neonates are critical to enhancing preterm infants’ survival. Methods. Hospital-based cross-sectional study was conducted on 398 participants using the systematic sampling method from October 10, 2021, to December 15, 2022. A pretested data extraction tool was used to collect data. EpiData version 4.6 and STATA version 16 were used for data entry and analysis. Multivariable logistic regression analysis evaluated the association between independent and outcome variables with a 95% confidence interval (CI). Hosmer and Lemeshow test and variance inflation factor were assessed to check model fitness and collinearity, respectively.

P

value
<
0.05

was considered statistically significant. Result. Of the 398 admitted preterm neonates, 331(83.2%) had hypothermia at admission. Factors that were significantly associated with mortality included outborn babies [Adjusted hazard ratio

AOR

=
2.18
:
95
%

CI (1.03-4.62)], GA less than 32 weeks [

AOR
=
6.64
:
95
%

CI (1.87-13.58)], weight less than 1500 gram [

AOR
=
7.91
:
95
%

CI (1.21-15.38)], thrombocytopenia [

AOR
=
3.36
:
95
%

CI (1.49-7.58)], and kangaroo mother care [

AOR
=
0.38
:
95
%

CI (0.16-0.88)]. Conclusion. The proportion of admission hypothermia was high. Outborn babies, birth weight less than 1500 gram, gestational

age
<
32

weeks, being thrombocytopenic, and lack of kangaroo mother care were identified as risk factors for hypothermic preterm neonatal mortality. Preterm labor prevention, improved inborn delivery, and kangaroo mother care may alleviate the high proportion of admission hypothermia and related mortalities in preterm neonates.
Identification of ATG7 as a Regulator of Proferroptosis and Oxidative Stress in Osteosarcoma
Authors: Jiang Runyi , He Shaohui , Gong Haiyi , Wang Yao , Wei Wei , Chen Jun , Hu Jinbo , Ye Chen , LiuHuang Shuchen , Jin Saiying , Wei Haifeng , Xu Wei , Xiao Jianru
Published: October 2022

Background. Ferroptosis has gained significant attention from oncologists as a vital outcome of oxidative stress. The aim of this study was to develop a prognostic signature that was based on the ferroptosis-related genes (FRGs) for osteosarcoma patients and explore their specific role in osteosarcoma. Methods. The training cohort dataset was extracted from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. Different techniques like the univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, multivariate Cox regression analyses, and the Kaplan-Meier (KM) survival analyses were utilized to develop a prognostic signature. Then, the intrinsic relationship between the developed gene signature and the infiltration levels of the immune cells was further investigated. An external validation dataset from the Gene Expression Omnibus (GEO) database was employed to assess the predictive ability of the developed gene signature. Subsequently, the specific function of potential FRG in affecting the oxidative stress reaction and ferroptosis of osteosarcoma cells was identified. Results. A prognostic signature based on 5 FRGs (CBS, MUC1, ATG7, SOCS1, and PEBP1) was developed, and the patients were classified into the low- and high-risk groups (categories). High-risk patients displayed poor overall survival outcomes. The risk level was seen to be an independent risk factor for determining the prognosis of osteosarcoma patients (

p
<
0.001

, hazard ratio: 7.457, 95% CI: 3.302-16.837). Additionally, the risk level was associated with immune function, which might affect the survival status of osteosarcoma patients. Moreover, the findings of the study indicated that the expression of ATG7 was related to the regulation of oxidative stress in osteosarcoma. Silencing the ATG7 gene promoted the proliferation and migration in osteosarcoma cells, suppressing the oxidative stress and ferroptosis process. Conclusions. A novel FRG signature was developed in this study to predict the prognosis of osteosarcoma patients. The results indicated that ATG7 might regulate the process of oxidative stress and ferroptosis in osteosarcoma cells and could be used as a potential target to develop therapeutic strategies for treating osteosarcoma.
Numerical Simulation and Optimization Control of Precious Metal Jewelry Process Based on VR Virtual Technology
Authors: Li Lu
Published: October 2022

In order to solve the problem that the design direction of precious metal ornaments in virtual reality environment which is complicated and most of them are operated by human, and the speed of obtaining the global optimal design result is not good, this paper proposes the numerical simulation and optimization control of precious metal ornaments process based on VR virtual technology. Through the hierarchical modeling structure design of precious metal jewelry and the coding of jewelry modeling gene, the fitness function is used to evaluate the fitness of individuals and determine the fitness of coding individuals; the evolution of jewelry modeling design scheme is supported by genetic operators. After the artificial participation conditions are met, the design scheme is evaluated manually in the virtual reality environment until a satisfactory scheme is produced. The experimental results show that under the same conditions, the design results of industrial ornaments based on genetic algorithm are 410 times less than those generated by conventional methods. Conclusion. It can accurately converge to the global optimal design result, which indicates that the genetic algorithm converges to the global optimal result faster and better in the industrial jewelry modeling design under the virtual reality environment.
Effects of Diet on Larval Survival, Growth, and Development of the Sea Cucumber Holothuria leucospilota
Authors: Yu Zonghe , Wu Hong , Tu Youkai , Hong Zesen , Luo Jiewen
Published: October 2022

Because most tropical sea cucumbers have been overexploited around the world, the sea cucumber Holothuria leucospilota has become increasingly commercially important in recent years. Restocking and aquaculture of H. leucospilota using hatchery-produced seeds could both enhance declining wild populations and provide sufficient beche-de-mer product to satisfy increasing market demand. Identifying an appropriate diet is important for successful hatchery culture of the H. leucospilota. In this study, we trialed different ratios of microalgae Chaetoceros muelleri (

2.00
–
2.50
×

10

6

cells/mL) and yeast (Saccharomyces cerevisiae,

~
2.00
×

10

6

cells/mL) in diets for H. leucospilota larvae (6 d after fertilization, referred to as “day 0”) at proportions 4 : 0, 3 : 1, 2 : 2, 1 : 3, and 0 : 4 by volume, in 5 treatments (A, B, C, D, and E, respectively). Larval survival rates in these treatments decreased over time, with the survival highest in treatment B (

59.24
±
2.49

%) on day 15 (double that of the lowest rate in treatment E (

28.47
±
4.23

%)). For any sampling event, larval body length in treatment A was always the lowest after day 3, and that for treatment B was always the highest, except on day 15. The maximum percentage of doliolaria larvae occurred in treatment B (23.33%) on day 15, followed by treatments C, D, and E (20.00%, 10.00%, and 6.67%, respectively). No doliolaria larvae occurred in treatment A, and pentactula larvae occurred only in treatment B (3.33%). On day 15 in all treatments, late auricularia larvae had hyaline spheres, but these were not prominent in treatment A. Densities of juveniles attaching to settlement plates varied with treatments, and the values were very low for the larvae only fed microalgae (A,

2.39
±
1.95

ind per plate) or yeast (E,

2.13
±
1.05

ind per plate)—only ~5% of the maximum number settling in treatment B (

45.56
±
7.24

ind per plate). Increased larval growth, survival and development, and juvenile attachment indicates that diets combining microalgae and yeast are more nutritionally balanced than single diets for hatchery of H. leucospilota. A combined diet of C. muelleri and S. cerevisiae at a 3 : 1 ratio is optimum for the larvae. Based on our results, we propose a larval rearing protocol to facilitate mass production of H. leucospilota.
LncRNA CARMN Affects Hepatocellular Carcinoma Prognosis by Regulating the miR-192-5p/LOXL2 Axis
Authors: Wang Xiaokang , Wu Shulong , Yang Yi , Zhao Jingjing
Published: October 2022

Background. Hepatocellular carcinoma (HCC) is aggressive cancer with a poor prognosis. It has been suggested that the aberrant expression of LOXL2 is associated with the development of HCC, but the exact mechanism remains unclear. This research is aimed at examining the expression level and prognostic value of LOXL2 in hepatocellular carcinoma and its relationship with immune infiltration and at predicting its upstream noncoding RNAs (ncRNAs). Method. The transcriptome data of HCC was first downloaded from The Cancer Genome Atlas (TCGA) database to investigate the expression and prognosis of LOXL2. Then, the starBase database was used to find the upstream ncRNAs of LOXL2, and correlation analysis and expression analysis were performed. Finally, the Tumor Immune Estimation Resource (TIMER) was used to explore the association between LOXL2 and immune cell infiltration. Result. CARMN was considered to be the potential upstream lncRNA for the hsa-miR-192-5p/LOXL2 axis in HCC. Furthermore, the level LOXL2 was markedly positively associated with tumor immune cell infiltration and immune checkpoint expression in HCC. Conclusion. Higher expression of LOXL2 mediated by microRNA (miRNA) and long noncoding RNAs (lncRNA) is associated with poor overall survival (OS), immune infiltration, and immune checkpoint expression in HCC.
A Literature Review Research on Monitoring Conditions of Mechanical Equipment Based on Edge Computing
Authors: Song Liqiang , Wang Huaiguang , Shi Zhiyong
Published: October 2022

The motivation of this research is to review all methods used in data compression of collected data in monitoring the condition of equipment based on the framework of edge computing. Since a large amount of signal data is collected when monitoring conditions of mechanical equipment, namely, signals of running machines are continuously transmitted to be crunched, compressed data should be handled effectively. However, this process occupies resources since data transmission requires the allocation of a large capacity. To resolve this problem, this article examines the monitoring conditions of equipment based on edge computing. First, the signal is pre-processed by edge computing, so that the fault characteristics can be identified quickly. Second, signals with difficult-to-identify fault characteristics need to be compressed to save transmission resources. Then, different types of signal data collected in mechanical equipment conditions are compressed by various compression methods and uploaded to the cloud. Finally, the cloud platform, which has powerful processing capability, is processed to improve the volume of the data transmission. By examining and analyzing the monitoring conditions and signal compression methods of mechanical equipment, the future development trend is elaborated to provide references and ideas for the contemporary research of data monitoring and data compression algorithms. Consequently, the manuscript presents different compression methods in detail and clarifies the data compression methods used for the signal compression of equipment based on edge computing.
Hybrid Fine-Tuning Strategy for Few-Shot Classification
Authors: Zhao Lei , Ou Zhonghua , Zhang Lixun , Li Shuxiao
Published: October 2022

Few-shot classification aims to enable the network to acquire the ability of feature extraction and label prediction for the target categories given a few numbers of labeled samples. Current few-shot classification methods focus on the pretraining stage while fine-tuning by experience or not at all. No fine-tuning or insufficient fine-tuning may get low accuracy for the given tasks, while excessive fine-tuning will lead to poor generalization for unseen samples. To solve the above problems, this study proposes a hybrid fine-tuning strategy (HFT), including a few-shot linear discriminant analysis module (FSLDA) and an adaptive fine-tuning module (AFT). FSLDA constructs the optimal linear classification function under the few-shot conditions to initialize the last fully connected layer parameters, which fully excavates the professional knowledge of the given tasks and guarantees the lower bound of the model accuracy. AFT adopts an adaptive fine-tuning termination rule to obtain the optimal training epochs to prevent the model from overfitting. AFT is also built on FSLDA and outputs the final optimum hybrid fine-tuning strategy for a given sample size and layer frozen policy. We conducted extensive experiments on mini-ImageNet and tiered-ImageNet to prove the effectiveness of our proposed method. It achieves consistent performance improvements compared to existing fine-tuning methods under different sample sizes, layer frozen policies, and few-shot classification frameworks.
The Palaearctic types of Chrysididae (Insecta, Hymenoptera) deposited in the Linsenmaier collection. Part 3. Elampini: genus Hedychrum Latreille
Authors: ROSA PAOLO , HEIM RENÉ , BERNASCONI MARCO VALERIO
Published: October 2022

An illustrated catalogue of the Palaearctic types of species and subspecies described by Walter Linsenmaier in the genus Hedychrum Latreille, 1802 is given. Linsenmaier described 14 taxa of Hedychrum; almost all primary types are deposited in the collection, at the Natur Museum (Luzern, Switzerland), with the exception of two holotypes which are deposited at the Natural History Museum (London), and Naturalis (Leiden). Hedychrum mithras Semenov-Tian-Shanskij, 1967 spec. resurr. is revalidated from the previous synonymy with Hedychrum luculentum bytinskii Linsenmaier, 1959. A list of the species described and pictures of the holotypes and allotypes deposited in the collection are given.
A new species of Chiasmocleis Méhely, 1904 (Anura: Microhylidae) from the Peruvian Amazonia
Authors: ROJAS-PADILLA OMAR , GAGLIARDI-URRUTIA GIUSSEPE , RIOS-ALVA EHIKO J. , CASTROVIEJO-FISHER SANTIAGO
Published: October 2022

We describe a new species of Chiasmocleis from the Amazonian forest of Peru. The new species is characterized by its medium size (snout-to-vent length = 18.2–20.8 mm in females, and 16.5 mm in one male), hands and feet with slightly developed fridges in females (more developed in male), and presence of a femoral line in all individuals. We also infer its phylogenetic position using DNA sequences of fragments of the mitochondrial genes for 16S rRNA and cytochrome oxidase subunit 1 (COI), and describe the mineralized skeleton through 3D models generated by computed tomography (CT-scan). Based on our results, we discuss the variation of some osteological characters traditionally used in the systematics of the genus.
Mud shrimps of the genus Wolffogebia Sakai, 1982 (Decapoda: Gebiidea: Upogebiidae) with the description of a new species from the Cần Giớ Mangrove Biosphere Reserve, South Vietnam
Authors: KOLEVATOV VASILY , MARIN IVAN
Published: October 2022

A new species of mud dwelling burrowing shrimp Wolffogebia cangioensis sp. nov. is described from the Soài Rạp River delta in the Cần Giớ Mangrove Biosphere Reserve, South Vietnam. The presence of Wolffogebia inermis Sakai, 1982 in the same area is also confirmed based on the freshly collected male specimen. Thorough morphological descriptions, genetic data (barcoding) and in situ ecological observations are presented for both species. A review of the previous records from Vietnam and Southeastern Asia as well as the taxonomic status of the genus Wolffogebia Sakai, 1982 within the family Upogebiidae are also discussed in the article. The key to all species of the genus is presented.
Revised systematic position of Nasutitermes brevipilus Emerson, 1925 (Isoptera: Termitidae: Nasutitermitinae) and the designation of Hyleotermes gen. nov.
Authors: CUEZZO CAROLINA , SCHEFFRAHN RUDOLF H. , CONSTANTINO REGINALDO
Published: October 2022

A new monotypic nasute termite genus, Hyleotermes gen. nov., is proposed for Nasutitermes brevipilus Emerson, 1925. Hyleotermes brevipilus, comb. nov., is redescribed and illustrated based on the morphology of the imago, soldier, and worker castes. It is expanded into Amazonia. The soldier of Hyleotermes differs from that of Nasutitermes Dudley, 1890 in that the former has a long and cylindrical nasus and the head capsule lacks long setae and is covered with microscopic setae. Unlike the worker of Nasutitermes, the Hyleotermes worker has a short mixed segment and an enteric valve is adorned with narrow spines on conical bases. The phylogenetic position of H. brevipilus comb nov., is reconstructed based on a dataset with two mitochondrial markers (COI and 16SrRNA) for 36 terminals, under maximum likelihood and Bayesian inference. Results corroborate that this species is unrelated to Nasutitermes and should be excluded from the genus.
A Novel Low-Cost Technique to Allow for Jet Ventilation
Authors: Ni Garrett , Shah Arnav , Molin Nicole , Schartel Scott , Soliman Ahmed M. S.
Published: October 2022

Background/Objective:

Traditional jet ventilation requires the use of a catheter that is inserted either through an endotracheal tube or laryngoscope. Specially designed laryngoscopes with a built-in luer lock adapter to which the high-pressure tubing may be attached exist but are not always available. We present our experience with an adapter which allows connection of the high-pressure tubing to the suction side port of suitable laryngoscopes that is easily assembled using readily available materials in the operating room.

Method:

We designed a jet ventilator adapter using a high-pressure jet ventilation tubing assembly and a 3-way stopcock extension set which we have used for the past 13 years. A retrospective case series of all adult patients who underwent direct laryngoscopy and/or bronchoscopy using this jet ventilation adapter between January 2017 and August 2021 was performed.

Result:

A total of 100 consecutive patients underwent laryngoscopy and bronchoscopy using jet ventilation between January 2017 and August 2021 was identified. The mean age was 56.3 years, and the mean BMI was 31.2. The most common diagnoses were idiopathic subglottic/tracheal stenosis (46.4%), acquired tracheal stenosis (34.1%), and acquired subglottic stenosis (14.8%). The median duration of the surgical procedure was 53 minutes with an interquartile range of 23. The CO2 laser was used in all cases. There was no disconnection of the adapter, episodes of postoperative respiratory compromise, or extraluminal air on chest radiography for any of our cases. Oxygen saturations remained above 90% intraoperatively for all cases.

Conclusion:

Our simple jet ventilator adapter connects the jet ventilator to the suction side port of suitable laryngoscopes and eliminates the need for a jet ventilation catheter or specialized laryngoscope at a minimal cost.