bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of the Relationship between Gut Flora Levels in Childhood Obese Population and Normal Healthy Population Based on Machine Learning
Authors: Feng Yaoqing , Si Xia , Zhu Ruifang , Chen Junxiang , Zhao Wenting , Wang Qian , Han Shifan
Published: August 2022

Aims. To explore the study of the relationship between the level of gut flora in childhood obese people and normal healthy people based on the analysis of machine learning. Materials and Methods. The stools of 54 normal weight, 53 overweight, and 59 obese children from May 2021 to May 2022 were selected. And DNA was extracted, and primers specific for the four bacteria were designed according to the specificity of the four bacteria to the 16 S rDNA gene sequences of the bacteria to be tested, and real-time fluorescence quantitative PCR reactions were performed to compare whether there was any difference in the number of the four bacteria between the three groups. Results. The results of agarose gel electrophoresis showed that the PCR amplification products of all four target bacteria showed clear bands at the corresponding positions, and no nonspecific bands appeared. When compared with the marker, the size matched with the target fragment, indicating good primer specificity. The comparison between normal body recombinant, super recombinant, and obese groups was statistically significant (

P
<
0.05

) for rectal eubacteria, polymorphic anaplasma, bifidobacteria spp., and lactobacilli. The median number of bifidobacteria in the three groups was significantly higher than the median number of rectal eubacteria, polymorphomycetes, and lactobacilli. The difference in comparison was statistically significant (

P
<
0.05

). Stratified analysis of children’s age revealed that normal body composition of Lactobacillus decreased with increasing age, and the difference was statistically significant (

P
<
0.05

). Conclusion. An increase in rectal eubacteria and a decrease in polymorphomycetes, bifidobacteria spp., and lactobacilli may be associated with the development of obesity. The numbers of rectal eubacteria, polymorphic methanobacteria, bifidobacteria spp., and lactobacilli in the intestine of normal weight and obese children were less affected by sex and age.
Development of Risk-Situation Scenario for Autonomous Vehicles on Expressway Using Topic Modeling
Authors: Chae Osung , Kim Junghwa , Jang Jeongah , Yun Hyunjeong , Lee Shinkyung
Published: August 2022

Growing interest has recently been paid to the development of autonomous vehicle scenarios, and corresponding research is being conducted on various methodologies and on the generation of scenarios including technological elements. However, most studies have focused on frequently-occurring accident types or representative accident situations; thus, there is a lack of studies on scenarios considering unpredictable accidents. Proper preparation is required for accident situations because even a small traffic accident that is less likely to occur can lead to fatalities if it is difficult to predict. Accordingly, this study established accident situations based on the Pegasus layer model by using unstructured text data to explain traffic accidents on expressways in Korea. The established accident situations were classified into three types (Typical Traffic/Critical Traffic/Edge Case) according to frequency. Topic modeling was applied to the Edge Case class, i.e., the least likely to occur and thus difficult to predict, to analyze the characteristics of groups and develop risk-situation scenarios for autonomous vehicles based on actual accident data.
Optimal Pricing Model of Environmental Quality Index Futures from the Perspective of Green Finance
Authors: Che Junwen , Zhou Shenghe , Shan Rui , Jia Hui , Liu Zheng
Published: August 2022

In order to establish the optimal price of low-carbon products and set the optimal target carbon emissions in the production cycle so as to maximize profits, this paper proposes the optimal pricing model of environmental quality index futures from the perspective of green finance. This paper mainly studies the optimal pricing and carbon emission strategy of low-carbon products of a single enterprise under the carbon trading system based on the quota system. When enterprises join the carbon trading system, how to optimally determine their target carbon emissions in the production cycle and the optimal price of their low-carbon products in order to maximize their own profits, based on the carbon emission quotas freely allocated by the government in the face of exogenous carbon trading prices and different consumer preferences for low-carbon products in the market, is discussed in detail. The experimental results show that the low marginal cost of emission reduction will urge enterprises to implement low-emission strategies as much as possible, and the marginal cost of a specific size will enable enterprises to implement low-carbon policies with low emissions, and the optimal emissions will decline with the increase of carbon prices. However, from the perspective of 50–300 carbon trading prices, the profits generated are less than those of the minimum emission strategy, and the difference between the two is generally one order of magnitude. Therefore, if the internal conditions permit and the external carbon trading price is reasonable, enterprises should reduce carbon emissions as much as possible. The properties obtained from the model analysis and the numerical conclusions given in the example part reflect the relationship between the enterprise product pricing, the marginal cost of emission reduction, and the target emission decision-making and draw some valuable information for the enterprise and the government decision-making.
Gastric Xylobezoar Treated with Continuous Enteral Coca-Cola® Infusion
Authors: Gangadharan Nambiar Gopinathan , Hanna Eyad , Shelton Julia , Lee Rose
Published: August 2022

Xylobezoar is a rare clinical condition in which undigested paper becomes trapped in the gastrointestinal tract causing varying degrees of gastrointestinal obstruction. This condition can be suspected in children with a history of gastric surgeries, decreased gastrointestinal motility, or pica. Xylobezoar presents with symptoms ranging from chronic abdominal pain to gastrointestinal perforation. Surgical intervention is often required as endoscopic removal is challenging and not always successful. Chemical dissolution has been shown to be effective in treating certain bezoars. Here, we report a case of a pediatric patient with xylobezoar who was successfully treated with continuous enteral Coca-Cola® infusion.
Essential Oils from the Fruits and Leaves of Spondias mombin Linn.: Chemical Composition, Biological Activity, and Molecular Docking Study
Authors: Asante Ampadu Gertrude Adomaa , Mensah Jehoshaphat Oppong , Darko Godfred , Borquaye Lawrence Sheringham
Published: August 2022

This work focused on characterizing the chemical constituents and evaluating the antioxidant and antimicrobial activities of the essential oils obtained from the fruit and leaves of Spondias mombin—a flowering plant of the Anacardiaceae family. Essential oils were extracted through steam distillation and characterized by gas chromatography-mass spectrometry. For the fruit essential oil, 35 compounds were obtained, and 25 compounds were identified in the leaf essential oil. The dominant compounds present in the fruit essential oil were (E)-ethyl cinnamate (14.06%) and benzyl benzoate (12.27%). Methyl salicylate (13.05%) and heptacosane (12.69%) were the abundant compounds in the leaf essential oil. The antioxidant activity of the essential oils was evaluated via phosphomolybdenum, hydrogen peroxide scavenging, 2, 2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging, and thiobarbituric acid reactive substances (TBARS) assays. The total antioxidant capacity of fruit and leaf essential oils was 48.5 ± 0.7 μg/gAAE and 48.5 ± 0.7 μg/g AAE, respectively. The half maximal scavenging concentrations of the essential oils in the hydrogen peroxide; DPPH and TBARS assays ranged from 252.2 μg/mL to 2288 μg/mL. The antimicrobial activity of the essential oils was tested using broth dilution and disc diffusion assays against eight microorganisms. The essential oils exhibited broad-spectrum antimicrobial activity against the microorganisms with minimum inhibitory concentrations of 9.75–50 mg/mL. Also, the zones of inhibition of the oils ranged from 12 mm to 25 mm. The biofilm inhibitory activities of the oils were dose-dependent with BIC50 values of 42.49 ± 0.1 mg/mL and 97.34 ± 0.6 mg/mL for fruit and leaf essential oils, respectively. Molecular docking studies revealed that the antibiofilm action of the fruit and leaf essential oils could be due to inhibition of the quorum sensing protein, LasR. The results suggest a possible application of the oils as antioxidant and antimicrobial agents.
Analysis of Therapeutic Effect of Elderly Patients with Severe Heart Failure Based on LSTM Neural Model
Authors: Chen Shunhong , He Shoudu
Published: August 2022

In recent years, cardiovascular-related diseases have become the “number one killer” threatening human life and health and have received much attention. The timely and accurate detection and diagnosis of arrhythmias and heart failure are relatively common heart diseases, which are of great social value and research significance in improving people’s quality of life by providing early treatment or intervention for those who are at risk. Based on this, this paper proposes a deep learning network architecture based on the combination of long- and short-term memory networks and deep residual neural networks for the automatic detection of heart failure. A total of 60 elderly patients with severe heart failure treated in the emergency department of our hospital from August 2019 to August 2021 were selected as the sample subjects of this study. The treatment outcomes and prognostic quality of life of the two groups of patients were compared and analyzed. Based on the unbiased test method, the accuracy of the proposed method on the authoritative open continuous heart rate database PhysioNet was 99.67% (data length 500), 98.84% (data length 1000), and 96.63% (data length 2000). This indicates that the network model can well extract the high-dimensional features of continuous heart rate and improve the accuracy of the classification model. The LSTM neural model proposed in this paper may be able to provide richer information on heart health status for portable ECG detection systems, which have very important clinical value and social significance.
The Construction of Shared Wisdom Teaching Practice through IoT Based on the Perspective of Industry-Education Integration
Authors: Bao Zhijun , Zhang Xue
Published: August 2022

In this paper, to solve the difficulties of overseeing battling reasonings in cordial projects, we use a training-based insight perspective. Based on previous research, managing the tension between friendly government assistance and business is clearly a vital task for social money managers. Accomplishment. Though the social government helps reasoning and its associated characteristics and practices structure the underpinnings of social endeavours, social finance managers similarly need to ensure that their associations are financially sensible, making it essential to attract business reasoning. To this end, we cultivate an instructive program structure taking into account social practice intelligence to assist understudies in getting reasonable data and capacities, organize social business with venturing targets, and consolidate battling reasonings in inventive and legitimate ways.
The Construction Method of Historical Geographic Information System Based on Mobile Network
Authors: Bai Jiangtao , Pan Wei
Published: August 2022

The research of historical geography is inseparable from the construction of historical geographic information systems, but the traditional construction method of historical geographic information systems has certain technical defects in the storage, management, analysis, and data sharing of historical geographic data. Therefore, more innovative and advanced construction methods of historical geographic information systems are needed to continuously improve the construction of historical geographic information systems, to promote the development of historical geographic information research. In contemporary society, a more excellent historical geographic information system construction method is inseparable from the support of science and technology. With the continuous development of science and technology, mobile network technology has emerged. As a combination of mobile communication and the Internet, mobile network has strong functional advantages. It has developed rapidly in recent years and has great market development potential. This paper aims to study the construction method of historical geographic information systems based on mobile network. Combined with the data collection algorithm of mobile network, the historical geographic information system construction experiment was carried out. The experiment concluded that the information integrity of the historical geographic information system constructed based on the mobile network is 18.2% higher than that of the historical geographic information system constructed using traditional methods. This shows that mobile network technology has a certain positive effect on the construction of historical geographic information systems.
Dysregulation of EZH2/miR-138-5p Axis Contributes to Radiosensitivity in Hepatocellular Carcinoma Cell by Downregulating Hypoxia-Inducible Factor 1 Alpha (HIF-1α)
Authors: Bai Bing , Liu Ying , Fu Xue-Mei , Qin Hai-Yan , Li Gao-Kai , Wang Hai-Chen , Sun Shi-Long
Published: August 2022

Enhancer of zeste homolog 2 (EZH2) is a histone methyltransferase involved in cell proliferation, invasion, angiogenesis, and metastasis in various cancers, including hepatocellular carcinoma (HCC). However, the role and molecular mechanisms of EZH2 in HCC radiosensitivity remain unclear. Here, we show that EZH2 is upregulated in HCC cells and the aberrantly overexpressed EZH2 is associated with the poor prognosis of HCC patients. Using miRNA databases, we identified miR-138-5p as a regulator of EZH2. We also found that miR-138-5p was suppressed by EZH2-induced H3K27me3 in HCC cell lines. MiR-138-5p overexpression and EZH2 knockdown enhanced cellular radiosensitivity while inhibiting cell migration, invasion, and epithelial-mesenchymal transition (EMT). Analysis of RNA-seq datasets revealed that the hypoxia-inducible factor-1 (HIF-1) signaling pathway was the main enrichment pathway for differential genes after miR-138-5p overexpression or EZH2 knockdown. Expression level of HIF-1α was significantly suppressed after miR-138-5p overexpression or silencing of EZH2. HIF-1α silencing mitigated resistance of HCC cells and inhibited EMT. This study establishes the EZH2/miR-138-5p/HIF-1α as a potential therapeutic target for sensitizing HCC to radiotherapy.
The Influence of Clusterin Glycosylation Variability on Selected Pathophysiological Processes in the Human Body
Authors: Janiszewska Ewa , Kmieciak Agnieszka , Kacperczyk Monika , Witkowska Aleksandra , Kratz Ewa Maria
Published: August 2022

The present review gathers together the most important information about variability in clusterin molecular structure, its profile, and the degree of glycosylation occurring in human tissues and body fluids in the context of the utility of these characteristics as potential diagnostic biomarkers of selected pathophysiological conditions. The carbohydrate part of clusterin plays a crucial role in many biological processes such as endocytosis and apoptosis. Many pathologies associated with neurodegeneration, carcinogenesis, metabolic diseases, and civilizational diseases (e.g., cardiovascular incidents and male infertility) have been described as causes of homeostasis disturbance, in which the glycan part of clusterin plays a very important role. The results of the discussed studies suggest that glycoproteomic analysis of clusterin may help differentiate the severity of hippocampal atrophy, detect the causes of infertility with an immune background, and monitor the development of cancer. Understanding the mechanism of clusterin (CLU) action and its binding epitopes may enable to indicate new therapeutic goals. The carbohydrate part of clusterin is considered necessary to maintain its proper molecular conformation, structural stability, and proper systemic and/or local biological activity. Taking into account the wide spectrum of CLU action and its participation in many processes in the human body, further studies on clusterin glycosylation variability are needed to better understand the molecular mechanisms of many pathophysiological conditions. They can also provide the opportunity to find new biomarkers and enrich the panel of diagnostic parameters for diseases that still pose a challenge for modern medicine.
An Optimal Round-Trip Route Planning Method for Tourism Based on Improved Genetic Algorithm
Authors: Cao Sha
Published: August 2022

The optimization of the travel route for a round-trip is not only a customized demand made by a large number of independently guided tourists but also an essential practical issue for the development of tourism management and tourism businesses. In light of this, the study presents a genetic algorithm (GA) as a potential solution to the problem of how to visit a number of tourist destinations within a constrained area in order to quickly determine the shortest tourist route. To traverse areas or regions with the least amount of physical exertion, select the correct and shortest route. Examining all potential routes from the starting point to the destination will allow you to determine the quickest route. A condensed explanation of the enhanced GA is provided to start. The second step is to analyze the model’s construction and solution in detail. Next, an enhanced genetic algorithm (IGA) is utilized to determine the optimal travel route for visiting a variety of tourist attractions. In accordance with the optimal travel route, the required number of days and specific travel arrangements are then estimated. In conclusion, the GA is optimized, and a simulation examination of each individual’s average path convergence is conducted. The results of the experiments indicate that the IGA can be effectively applied to the path planning of multiple scenic locations, the selection of the shortest travel route, the reduction of travel expenses, and the saving of travel time. This has important implications for both research and practical applications, as well as a high research significance and practical value.
The Role of the Monocyte-to-Lymphocyte Ratio in Acute Ischemic Stroke Patients with Acute Kidney Injury
Authors: Jiang Fen , Shi Zhen , Liu Xiangyang , Xiang Jiaxuan , Lei Jie , Yang Bo , Lei XiangLi , Li Xuewei
Published: August 2022

Objective. The objective of the study was to determine if acute kidney injury (AKI) in patients with acute ischemic stroke was associated with the monocyte-to-lymphocyte ratio (MLR) assessed upon admission to the neurology intensive care unit (NICU) (AIS). We also looked into the MLR’s function in predicting hospital mortality in AIS patients. Methods. This retrospective analysis included 595 adult patients with AIS who were hospitalized to the NICU of the First Affiliated Hospital of South China between January 2017 and December 2019. Clinical signs and imaging studies were used to diagnose AIS. KDIGO criteria were used to define AKI. The ratio of monocytes to lymphocytes was used to compute MLR, the ratio of neutrophils to lymphocytes was used to calculate NLR, and the ratio of platelets to lymphocytes was used to calculate PLR. Result. 361 males and 234 women between the ages of

66.27
±
12.05

years took part in the study. The individuals’ MLR was

0.4729
±
0.3461

and their neutrophil-to-lymphocyte ratio (NLR) was

8.18
±
5.45

. There were notable disparities in MLR and NLR between the AKI and non-AKI groups (

p
<
0.001

). The link between MLR and AKI development risk was enhanced after adjustment, with respective cutoff values of 0.4581 and 9.26. For the MLR-based prediction of AKI incidence, the areas under the receiver-operating characteristic curves (AUCs) were 0.711 (95% CI: 0.663-0.758). And NLR-based prediction of AKI incidence the AUCs was (95% CI: 0.742-0826). Additionally, MLR was associated with a higher rate of in-hospital mortality (2.825, 95% confidence interval: 1.058, 7.545), whereas NLR was associated with a risk of in-hospital mortality of 1.085. (95 percent CI: 1.022, 1.151). An AUC of 0.745 (95% CI: 0.601-0.889,

p
=
0.026

) was obtained for in-hospital mortality based on the MLR, whereas an AUC of 0.724 (95% CI: 0.531-0.916,

p
=
0.042

) was obtained for in-hospital mortality based on the NLR. Conclusion. MLR and neutrophil-to-lymphocyte ratio (NLR) were associated with a higher risk of AKI and in-hospital death in AIS patients.
Training Fatigue and Recovery of Throwing Athletes Based on the Comprehensive Environmental Test of the Field
Authors: Peng Kun
Published: August 2022

Exercise-induced fatigue is a common phenomenon during exercise, and its mechanisms mainly include peripheral and central mechanisms. This article discusses the causes of the throwing athletes’ fatigue and the effective recovery methods used, in order to have a certain reference value for making throwing training plans more scientifically and rationally and participating in competitions. Central fatigue will seriously affect the athletic state of athletes, and environmental factors are one of the important factors affecting the central fatigue of athletes. Because the influence of central fatigue and environmental factors on throwing athletes is more prominent, the correlation between environmental factors and central fatigue in throwing sports is studied, and a general prediction model and grouping prediction model of athletes’ central fatigue under various environmental factors are established based on ANN. Experiments show that the established general prediction model of central fatigue of throwing athletes has good performance, and the correlation coefficient between the prediction results and the actual measured value is 0.68; for different groups of athletes, the established prediction model of central fatigue of throwing athletes has better performance. The prediction accuracy is high, and the correlation coefficient between the prediction result and the actual measurement value is higher than 0.70.
The Relationship between Social Entrepreneurship Capability of SOM Neural Network Algorithm and New Enterprise Performance
Authors: Li Tianhua
Published: August 2022

As an important factor in the creation and growth of new enterprises, social entrepreneurship and new enterprise performance have attracted more and more attention from scholars in recent years. This research analyzes the network relationship of new companies on the basis of existing entrepreneurial network research. This paper proposes social entrepreneurial capabilities and new company performance based on the SOM neural network algorithm to solve these problems and then establishes entrepreneurial networks, organizational learning, and new business performance models. The method of this paper is to study the SOM neural network algorithm and then establish the entrepreneurial ability and enterprise performance evaluation system. The function of these methods is to put forward the meaning and research of venture capital. It also defines the meaning and research of innovation capabilities based on innovation theory, ensuring the scientific nature of the evaluation indicators, evaluation standards, and evaluation processes of innovative enterprises. In this survey, this paper conducted a field survey in Shanxi Province, China, and analyzed the internal impact of the network of social entrepreneurship and new companies on corporate performance. The survey results show that the value of the correlation β between entrepreneurial orientation and entrepreneurial environment dynamics is 0.167 (

P
<
0.05

). This shows that improving the entrepreneurial environment and enhancing social entrepreneurial capabilities have a positive impact on corporate performance.
Cybercrime: Identification and Prediction Using Machine Learning Techniques
Authors: Veena K. , Meena K. , Kuppusamy Ramya , Teekaraman Yuvaraja , Angadi Ravi V. , Thelkar Amruth Ramesh
Published: August 2022

In the world of cyber age, cybercrime is spreading its root extensively. Supervised classification methods such as the support vector machine (SVM) and K-nearest neighbor (KNN) models are employed for the classification of cybercrime data. Likewise, the unsupervised mode of classification involves the techniques of K-means clustering, Gaussian mixture model, and cluster quasi-random via fuzzy C-means clustering and fuzzy clustering. Neural networks are employed for determining synthetic identity theft. The formation of clusters takes place using these clustering techniques, which fetches crime data from the overall data. Cybercrime detection employs dataset that is fetched from CBS open data StatLine. The attributes utilized are concerning the crime victims through personal characteristics with total user identity being 1000. For analyzing the performance, different training and testing data undergo variation. Eventually using the best technique, the criminal is identified and the Gaussian mixture model in the unsupervised method reveals enhanced performance using the detection method. 76.56% percentage of accuracy is achieved in detecting the criminal. The accuracy achieved in case of classification via SVM classifier is 89% in the supervised method. Performance metrics for several attributes are being computed in terms of true positive (TP), false positive (FP), true negative (TN), false negative (FN), false alarm rate (FAR), detection rate (DR), accuracy (ACC), recall, precision, specificity, sensitivity, and Fowlkes–Mallows scores. The expectation-maximization (EM) algorithm is employed for assessing the performance of the Gaussian mixture model.
Patients with Autoimmune Thyroid Diseases Have Higher Prevalence of Positive Antiphospholipid Antibodies: A Systematic Review and Meta-Analysis
Authors: Lu Difei , Song Zhibo , Gao Ying , Zhang Junqing , Guo Xiaohui
Published: August 2022

Introduction. Autoimmune thyroid diseases (AITDs) and antiphospholipid syndrome (APS) are commonly seen in childbearing-age women and can lead to recurrent miscarriages. Studies with a relatively small sample size were conducted and concluded inconsistent results on the relationship between AITDs and APS or the presence of antiphospholipid (aPL) antibodies. This meta-analysis aimed to provide evidence on the possible association between AITDs and APL using primary data from all relevant studies. Methods. Literature databases including PubMed, Embase, and Cochrane were searched from the time when the databases were established to March 2022. A total of 7 studies that met all inclusion criteria were selected in this meta-analysis, with 475 AITD patients and 764 healthy controls. After data extraction, the pooled odds ratio (OR) and the 95% confidence interval (95% CI) were calculated. Results. The risk of positive APL in AITD patients was approximately 3 folds higher in AITD patients compared with those in healthy controls (OR 3.41, 95% CI 2.29–5.08,

p
<
0.001

). There was no significant association between the risk of Graves’ disease (GD) and positive APL (OR 9.3, 95% CI 0.10–824.73,

p
=
0.33

). The risk of positive APL in patients with Hashimoto’s thyroiditis (HT) increased over 2 folds compared with healthy controls (OR 3.35, 95% CI 1.55–7.23,

p
=
0.002

). Conclusions. The result of this meta-analysis proved that the presence of APL was significantly increased in patients with AITD compared with healthy individuals, especially in patients with Hashimoto’s thyroiditis.
Effects of Infrared Combined with Methylcobalamin on the Vibratory Sensory Threshold and Nerve Conduction Velocity of the Lower Extremity in Patients with Diabetic Foot Treatment
Authors: Wang Yi , Lin Shaona , Chen Zongcun , Chen Qinghua , Fu Maoxiong
Published: August 2022

Objective. To investigate the effect of infrared combined with methylcobalamin on the vibratory sensory threshold and lower limb nerve conduction velocity of patients with diabetic foot. Methods. One hundred and six patients with diabetic foot in our hospital from February 2018 to December 2020 were enrolled and divided into the study and control groups. The patients in the control group were given methylcobalamin, and the patients in the research group were treated with infrared light on the basis of the control group. The therapeutic effect, vibration sensory threshold, lower limb nerve conduction velocity, and related biochemical index levels before and after treatment in the two groups were counted. Result. The total effective rate of the study group (94.34%) was significantly higher than that of the control group (81.13%). The left/right lower limb vibration sensation threshold decreased in both groups after treatment, and the study group was lower than that of the control group (

P
<
0.05

). The conduction velocity of the left/right common peroneal nerve and tibial nerve increased in both groups after treatment, and the study group was larger than that of the control group (

P
<
0.05

). The bFGF, VEGF, and APN increased in both groups after treatment. VEGF and APN increased and IL-6 and TNF-α decreased in both groups after treatment, and the study group was better than the control group (

P
<
0.05

). Conclusion. Infrared and methylcobalamin combined treatment of diabetic foot can effectively improve lower extremity nerve conduction velocity and vibration sensory threshold, regulate serum bFGF and VEGF levels, reduce the degree of inflammatory response, and help improve the overall treatment effect.
Low Serum Total Testosterone Is Associated with Non-Alcoholic Fatty Liver Disease in Men but Not in Women with Type 2 Diabetes Mellitus
Authors: Zhang Xinxin , Xiao Jinfeng , Liu Qi , Ye Yuanyuan , Guo Weihong , Cui Jingqiu , He Qing , Feng Wenli , Liu Ming
Published: August 2022

Aims/Introduction. Sex steroid hormones play a significant role in the progression of cardiovascular and metabolic diseases, including non-alcoholic fatty liver disease (NAFLD). The aim of this cross-sectional study was to explore the associations of testosterone, androstenedione, dehydroepiandrosterone (DHEA), and dehydroepiandrosterone sulfate (DHEAS), with the risk of NAFLD in patients with type 2 diabetes mellitus (T2DM). Materials and Methods. There were 1155 patients with T2DM included in the analysis. Serum levels of total testosterone and the precursors of androgens, including androstenedione, DHEA, and DHEAS, were quantified using liquid chromatography-tandem mass spectrometry assays. Results. The risk of NAFLD decreased as total testosterone concentration increased in men with T2DM. After adjusting for age, current smoking, current drinking, body mass index, duration of T2DM, diastolic blood pressure, total cholesterol, triglycerides, low-density lipoprotein/high-density lipoprotein cholesterol ratio, uric acid, C-reactive protein, and sex hormones in model 4, the adjusted odds ratio (OR) and 95% confidence interval (CI) of NAFLD for tertile3 vs tertile1 was 0.37 (0.17–0.77;

P
=
0.024

for trend). When taken as a continuous variable, this association was still robust in model 4 (OR, 0.58; 95% CI, 0.42–0.80;

P
<
0.05

). No significant associations were found between increasing levels of the precursors of androgens and the odds of NAFLD in men with T2DM (all

P
>
0.05

). Moreover, women showed no significant associations of total testosterone, androstenedione, DHEA, and DHEAS, with the odds of NAFLD (all

P
>
0.05

). Conclusions. Serum total testosterone was independently associated with the risk of NAFLD among men with T2DM. This study highlights the potential role of testosterone as a risk factor for NAFLD in patients with T2DM.
Extraction of Impervious Surface from High-Resolution Remote Sensing Images Based on a Lightweight Convolutional Neural Network
Authors: Chen Lingling , Zhang Hongmei , Song Yuejun
Published: August 2022

Due to continuous progress of urbanization in China, large area of natural surface has become impervious. Automatic extraction of impervious surface (IS) from high-resolution remote sensing images is important to urban planning and environmental management. Artificial identification of IS is time-consuming and laborious. It is valuable to develop more intelligent recognition patterns. In recent years, semantic segmentation models based on convolutional neural network (CNN) have made great progress in extraction of IS from remote sensing images. However, most existing models focus on improving accuracy and rarely consider computational efficiency. In order to keep balance between computing resource consumption, computing speed, and segmentation accuracy, we propose a lightweight semantic segmentation network model based on CNN, and we named it LWIBNet. LWIBNet uses an efficient encoding-decoding structure as the skeleton and connects the encoding part and the decoding part by the Skip Layer. Moreover, in order to reduce the number of parameters and speed up the calculation, we introduce improved Squeeze-and-Excitation (SE) module, inverted residuals, and depthwise separable convolution to form the Inv-Bottleneck (IB) module and use it as the core to build the LWIBNet model. On the computational complexity, LWIBNet and LWIBNet-TTA have the lowest FLOPs (14.14 G), and SegNet has the second lowest FLOPs, but SegNet is 3.2 times higher than LWIBNet (45.05 G vs 14.14 G). Both the LWIBNet model and classic models are tested and compared on the same data set. The results show that the LWIBNet model achieves a bit higher segmentation accuracy with less computation cost, and its computation speed is faster.
Ghanaian Clay as a Catalyst for Transesterificating Shea Butter Oil as Alternative Feedstock for Green Energy Production
Authors: Takase Mohammed
Published: August 2022

In this study, catalytic transesterification of Shea butter oil with methanol to biodiesel was carried out. The clay particle was first sieved with a 250 ml sieve and then calcined at 800μC for 8 hours in a furnace. The calcined clay was then modified with 5% each of Zn(NO3)2 and SnCl2 separately for 3 h at 60°C using incipient wetness impregnation method. The slurry compositions were then dried at 120°C overnight in an oven. The modified clay catalysts were subsequently calcined for 3 hours at 600°C. The clay that had been modified with SnO2 and ZnO was assigned SD and ZD, respectively, whereas the clay that had not been doped (control) was assigned as AC. The catalysts were characterized using X-ray Diffractometer (XRD), Brunauer Emmett Teller (BET) surface area, and Scanning Electron Microscopy (SEM). Biodiesel was then produced from each of the catalysts under varying conditions of methanol to oil molar ratio, catalyst concentration, reaction temperature, and reaction time. When compared the performances of the catalysts (activated clay modified with SnO2, ZnO, and the control), activated clay modified with SnO2 resulted in an optimal conversion yield of 99.8% under 8 : 1 methanol to oil molar ratio, 1% catalyst concentration, 60°C of reaction time in 60 minutes. The catalytic performance was affected by the basicity and surface area of the catalysts. The biodiesel produced was comparable to American and European Union standards.
Fractal Art Pattern Generation Based on Genetic Algorithm
Authors: Liu Huabai
Published: August 2022

In order to solve the problem in the application and optimization method of fractal art pattern generation, on the basis of the integration of the fractal theory and genetic algorithm, a generation method based on genetic algorithm and composition generation was proposed. The method provided a more stable and convenient supporting environment for the innovative design of artistic patterns, which met the needs of different users for the design of artistic patterns. The experimental results showed that the simplified genetic programming algorithm was optimized in both individual coding complexity and algorithm complexity. The search space was 1023-1026 times larger than the traditional algorithm, and the evaluation times were 2-3 times larger than the traditional algorithm. The results showed that the method could solve the problem that fitness function could not express well and ensure the optimal genetic population.
Decision-Making Research on Tour Lines of Tourist-Dedicated Train Based on Vague Sets and Prospect Theory
Authors: Cui Yuanding , Ma Changxi
Published: August 2022

Tourist-dedicated train is the product of the combination of railway transportation and tourism, and its tour line selection includes the selection of nodes and lines. Based on the principle of decision-making, taking technical factors, tourism factors, regional economic factors, and passenger flow factors as criteria, this paper analyzes the decision-making indices affecting the tour line and establishes the decision-making index system. Subsequently, the prospect theory considering the bounded rationality and psychological factors of decision makers is combined with vague set fuzzy decision theory, and a comprehensive decision method based on vague set and prospect theory is proposed. Finally, the feasibility of the proposed decision method is verified by an example. The research shows that the established decision-making index system is representative, and the proposed decision-making method is scientific and effective for the decision making of tourist lines of tourist-dedicated train. The decision-making results can be used as a reference for the formulation of tour lines and line plans of tourist-dedicated train.
Decision-Making on the Solution of a Stochastic Nonlinear Dynamical System of Kannan-Type in New Sequence Space of Soft Functions
Authors: Alsolmi Meshayil M. , Bakery Awad A.
Published: August 2022

In this paper, we construct and investigate the space of weighted Gamma matrix of order

r

in Nakano sequence space of soft functions. The idealization of the mappings has been achieved through the use of extended

s

-soft functions and this sequence space of soft functions. This new space’s topological and geometric properties, the multiplication mappings that stand in on it, and the mappings’ ideal that correspond to them are discussed. We construct the existence of a fixed point of Kannan contraction mapping acting on this space and its associated prequasi ideal. Interestingly, several numerical experiments are presented to illustrate our results. Additionally, some successful applications to the existence of solutions of nonlinear difference equations of soft functions are introduced.
[Retracted] Nanomaterials for Food and Agriculture in Economic Valuation of the Technology Harvesting Maize Straw for Biogas Production in China
Authors: Fan Zhenqi
Published: August 2022

Maize has a tremendous open door, immensely as a biofuel source. The objective reason for this examination is to break down the capacity of maize straw procured under fluctuating climatic circumstances to be used in biogas handling and the effect on different physicochemical components, for the most part, outstandingly the dry mass substance. This information indicates that corn stalks collected in China and Eastern Europe may exhibit extensive dry matter synthesis. This may be related to prewinter climate change. Regardless of temperature or consistency, corn straws can make incredible (for damp materials) or sublime (for more powdered straws) biogas substrates. With a new mass of methane value of 201207 m3/mg, this material is a much better substrate than the corn silage (about 105 m3/mg FM) which is definitely used in Europe. Corn straws were said to require longer consideration (3642 days) than corn silage (not exactly 30 days). In any case, this distinction is not important, and the biogas plant can remind the manager.
Recommendation Model of Tourist Attractions Based on Deep Learning
Authors: Cheng Xinquan , Su Wenlong
Published: August 2022

In order to solve the problem of tourism information overload caused by the rapid development of tourism and the Internet era, the author proposes a tourist attraction recommendation model based on deep learning. Convolutional Neural Network (CNN) is used to extract the sentiment of text comments, the Pearson similarity formula is used to calculate similar user groups, and the mean absolute error (MAE) is used to evaluate the resulting error. Compare with traditional collaborative filtering methods. Experimental results show that: the MAE value is smaller than the MAE value of the collaborative filtering method, indicating that considering tourists’ behavioral information, contextual information, and emotional factors in comments can effectively improve the accuracy of recommendation, as the data volume of the test set increased from 250 to 2000; although there was an increase in the MAE value, the overall trend showed a downward trend, indicating that the quality of the model can be more fully verified when the data volume is large. The model proposed by the author can effectively reduce the prediction error and improve the efficiency of tourist attractions recommendation.
Investigation of Using Various Quantities of Steelmaking Waste for Scavenging Hydrogen Sulfide in Drilling Fluids
Authors: Ahmed Ashraf , Elkatatny Salaheldin , Onaizi Sagheer A.
Published: August 2022

Effective in situ scavenging of hydrogen sulfide (H2S) while drilling a sour formation is critical for limiting the prevalent related impacts and safety hazards. Thus, it is necessary to develop a specialized additive that can selectively react with H2S and remove it without generating harmful byproducts or impairing drilling fluid performance. Additionally, waste management and utilization will transfer the waste from being an environmental and economic burden to a valuable commodity. Accordingly, we report herein the management of steelmaking waste through its utilization as a novel H2S scavenger for water-based drilling fluids, as well as the evaluation of the effects of the steelmaking waste dosage (1, 2, and 3 g) on the mud H2S scavenging capability and key properties. The H2S scavenging capacity of the waste-containing mud was investigated and compared to that of the base mud and fluids containing the commercial scavengers (triazine- and iron gluconate-based materials). In addition, the mud rheology, alkalinity, and filtering performance were studied in the presence and absence of the waste, and the findings were compared to those of commercial scavengers. This study showed that adding 1, 2, and 3 g of the steelmaking waste to the base drilling fluid significantly improved the H2S scavenging capacity by 105, 399, and 503%, respectively, while the triazine- and iron gluconate-based materials increased the capacity by 179 and 131%. Similarly, when the proportion of the steelmaking waste increased, the rheological parameters, comprising apparent viscosity, plastic viscosity, and yield point, slightly increased. The inclusion of the steelmaking waste reduced mud pH to 10.4, 9.8, and 8.5 with a content of 1, 2, and 3 g, respectively, compared to 11.0 for the base mud, 11.1 for triazine-based material, and 7.9 for iron gluconate-based scavenger. When 1 and 2 g of the steelmaking waste were added, the obtained filtrated liquid volume was preferably lower than the base mud and even the commercial scavengers-contained muds. As a result, 2 g of steelmaking waste could be added for enhanced mud performance. Nevertheless, higher amounts of the steelmaking waste could be used instead to achieve maximal H2S scavenging capability, with an extra alkalinity controller added to ensure attaining the practical recommended properties.
The Influence of Sintering Pressure on the Preparation, Friction Properties, and Magnetic Properties of Ti2AlC-TiC and Ti3AlC2-TiC Composites Under High-Pressure and High-Temperature
Authors: Li Liang , Chen Yuqi
Published: August 2022

Due to their high melting point, low density, and affordable price, TiC ceramics have emerged as one of the most promising ultrahigh temperature structural materials. However, its development and usage are severely constrained by its weak mechanical characteristics. The Ti2AlC-TiC and Ti3AlC2-TiC composites were synthesized by using the laminated metal-ceramic Ti2AlC/Ti3AlC2 as the binder, combined with high-temperature and high-pressure sintering technology (GPa order of magnitude confinement system). The thermal analysis shows that the exothermic heat of Ti/1.2Al/2TiC is less than that of 3Ti/1.2Al/2C, 2Ti/1.2Al/C, and 3Ti/1.5Al/C. The ratio of Ti/1.2Al/2TiC can suppress the thermal explosion phenomenon during the sintering process and improve the safety of the high-pressure sintering process. XRD results showed that the main composition of the sintered products was Ti2AlC-TiC at 2∼3.5 GPa and Ti3AlC2-TiC at 4∼5 GPa. As the sintering pressure increased from 2 GPa to 5 GPa, the bonding phase changed from Ti2AlC to Ti3AlC2. The thickness of the synthetic Ti3AlC2 layer is near 0.1 µm under 5 GPa. The average friction coefficient of Ti2AlC-TiC composites sintered 2 GPa with POM is as low as 0.1767, while the average friction coefficient of Ti3AlC2-TiC composites with POM increased to 0.3468∼0.3797. The wear width of Ti2AlC-TiC is lower than that of Ti3AlC2-TiC composites sintered under 4–4.5 GPa. The wear width of Ti3AlC2-TiC composites decreases following the rise of sintering pressure and is reduced to 0.3504 mm under 5 GPa. Ti2AlC-TiC and Ti3AlC2-TiC composites with PP ball counterparts have friction coefficients of 0.375 to 0.45 and worse wear resistance than that of POM balls. Ti3AlC2-TiC composites synthesized at 5 GPa with a Cu ball had the smallest friction coefficient (0.4558) and the smallest wear scar width (0.6289 mm). The friction coefficients and wear widths of synthetics with Al pairs ranged from 0.48–0.697 and 0.851–1.087 mm, respectively, and varied irregularly with increasing sintering pressure. Ti2AlC-TiC composites synthesized at 2 GPa with agate and glass pairs have coefficients of friction of 0.5 and 0.61, respectively. Abrasion widths of Ti2AlC-TiC composites synthesized at 2 GPa with agate and glass pairs were 1.3 mm and 0.72 mm, respectively. The friction coefficient of synthetics with agate and glass pairs increases with increasing sintering pressure. The magnetization and magnetization intensity of the Ti3AlC2-TiC composites are stronger than those of Ti3AlC2. Ti2AlC-TiC and Ti3AlC2-TiC composites held promise to serve in the field of ceramic grinding processing applications.