bluuebunny/crossref_metadata_2025 huggingface dataset:
SimNet
Authors: Li Lingda , Pandey Santosh , Flynn Thomas , Liu Hang , Wheeler Noel , Hoisie Adolfy
Published: July 2022

While cycle-accurate simulators are essential tools for architecture research, design, and development, their practicality is limited by an extremely long time-to-solution for realistic applications under investigation. This work describes a concerted effort, where machine learning (ML) is used to accelerate microarchitecture simulation. First, an ML-based instruction latency prediction framework that accounts for both static instruction properties and dynamic processor states is constructed. Then, a GPU-accelerated parallel simulator is implemented based on the proposed instruction latency predictor, and its simulation accuracy and throughput are validated and evaluated against a state-of-the-art simulator. Leveraging modern GPUs, the ML-based simulator outperforms traditional CPU-based simulators significantly.
Prediction of the Resource Consumption of Distributed Deep Learning Systems
Authors: Yang Gyeongsik , Shin Changyong , Lee Jeunghwan , Yoo Yeonho , Yoo Chuck
Published: July 2022

Predicting resource consumption for the distributed training of deep learning models is of paramount importance, as it can inform a priori users of how long their training would take and enable users to manage the cost of training. Yet, no such prediction is available for users because the resource consumption itself varies significantly according to "settings" such as GPU types and also by "workloads" like deep learning models. Previous studies have attempted to derive or model such a prediction, but they fall short of accommodating the various combinations of settings and workloads together. This study presents Driple, which designs graph neural networks to predict the resource consumption of diverse workloads. Driple also designs transfer learning to extend the graph neural networks to adapt to differences in settings. The evaluation results show that Driple effectively predicts a wide range of workloads and settings. In addition, Driple can efficiently reduce the time required to tailor the prediction for different settings by up to 7.3×.
Hierarchical Learning Algorithms for Multi-scale Expert Problems
Authors: Yang Lin , Chen Yu-zhen Janice , Hajiesmaili Mohammad H. , Herbster Mark , Towsley Don
Published: July 2022

In this work,1 we study the multi-scale expert problem, where the rewards of different experts vary in different reward ranges. The performance of existing algorithms for the multi-scale expert problem degrades linearly proportional to the maximum reward range of any expert or the best expert and does not capture the non-uniform heterogeneity in the reward ranges among experts. In this work, we propose learning algorithms that construct a hierarchical tree structure based on the heterogeneity of the reward range of experts and then determine differentiated learning rates based on the reward upper bounds and cumulative empirical feedback over time. We then characterize the regret of the proposed algorithms as a function of non-uniform reward ranges and show that their regrets outperform prior algorithms when the rewards of experts exhibit non-uniform heterogeneity in different ranges. Last, our numerical experiments verify our algorithms' efficiency compared to previous algorithms.
Polyol Synthesis of Ni and Fe Co-Incorporated Tungsten Oxide for Highly Efficient and Durable Oxygen Evolution Reaction
Authors: Takeda Airi , Hiraoka Hidenori , Nakamura Kota , Sakai Arisu , Sakata Yoshihisa , Yoshida Masaaki , Azuma Masanobu , Nakayama Masaharu
Published: July 2022

The development of inexpensive transition metal-based catalysts for water splitting has attracted global attention, which should be accomplished in the simplest and most scalable way feasible. In this study, nickel and iron co-incorporated tungsten oxides (NixFe1-xWO4) were synthesized using a simple polyol method, and the materials achieved a highly efficient and stable oxygen evolution reaction (OER) in an alkaline electrolyte. The product as-synthesized using the polyol method consisted of an undeveloped wolframite structure, which was converted to its complete crystal by heat treatment at 600 °C, with an increase in crystallite size. The OER properties of NixFe1-xWO4 could be controlled by the ratio of Ni and Fe present and heat treatment temperature. A ternary tungsten oxide (Ni0.5Fe0.5WO4) with a Ni:Fe:W molar ratio of 0.5:0.5:1 deposited on a glassy carbon electrode required 297 mV to reach a current density of 10 mA cm−2 in 1.0 M KOH solution. The 10 mA cm−2 electrolysis with the electrode was continued for at least 100 h. This was quite different from a similarly-synthesized NiFe oxide without W, which required an additional 47-mV overpotential to reach 10 mA cm−2 and had inferior durability.
Admission Outcome and Antimicrobial Resistance Pattern of Bacterial Isolates among Neonates with Suspected Sepsis in Neonatal Intensive Care Unit at Dessie Comprehensive Specialized Hospital, Dessie, Northeastern Ethiopia
Authors: Fenta Genet Molla , Woldemariam Hiwot Ketema , Metaferia Yeshi , Seid Abdurahaman , Gebretsadik Daniel
Published: July 2022

Background. Neonatal sepsis is a major cause of morbidity and mortality globally. The aim of this study was to assess admission outcome and antimicrobial susceptibility pattern of bacterial isolates among neonates with suspected sepsis at the Dessie Comprehensive specialized Hospital (DCSH), Northeastern Ethiopia. Method. Cross-sectional study was conducted from August 2017 to March 2018. Two hundred forty-six neonates were recruited, and each patient’s blood specimen was collected aseptically using bottle containing Brain Heart Infusion for blood culture. Both clinical and laboratory data such as bacterial culture growth and antimicrobial susceptibility pattern were collected from the neonate; clinical data from the mothers were also included. Antimicrobial susceptibility testing was performed using Kirby-Bauer disk diffusion method. The data were analyzed using SPSS version 20. Results. Bacteria were identified from 67 (27.2%) blood cultures. The predominant pathogen was Escherichia coli (35.8%) followed by Staphylococcus aureus (26.8%), and Coagulase Negative Staphylococcus (CoNS) (19.4%). The isolated bacteria showed resistance to Ampicillin 55 (82%), third-generation Cephalosporins 21 (58.3%) and other tested antimicrobials. Overall, 68.6% bacterial isolates demonstrated Multidrug resistance (MDR) and total registered mortality rate was 12/246 (4.8%). Both neonatal factors such as neonatal temperature, septic umbilicus and utilization of indwelling medical device during delivery; and maternal factors such as age, antenatal urinary tract infection (UTI), mode of delivery and prolonged rupture of membrane (PROM) had shown statistically significant association with bacterial sepsis. Conclusion. The rate of bacterial growth was found to be high; E. coli and S. aureus were the predominant organisms. Both maternal and neonatal related data were strong predictors for bacterial infection of the neonate. Therefore, improving infrastructures for screening of bacteremia as well as active surveillance in clinical setting needed to ensure proper empirical therapy.
Design of Faster R-CNN-Based Fault Detection Method for Subway Vehicles
Authors: Ma Hanlin , Yao Mingyang
Published: July 2022

A substantial amount of maintenance and fault data is not properly utilized in the daily maintenance of pantographs in urban metro cars. Pantograph fault analysis can begin with three factors: the external environment, internal flaws, and joint behavior. Based on the analysis of pantograph fault types, corresponding measures are proposed in terms of pantograph fault handling and maintenance strategies, in order to provide safety guarantee for the safe and effective realization of rail transit vehicle speed-up and also provide reference for the maintenance and overhaul of pantographs. For the problem of planned maintenance no longer meeting current pantograph maintenance requirements, a defect diagnosis system based on a combination of faster R-CNN neural networks is presented. The pantograph image features are extracted by introducing an alternative to the original feature extraction module that can extract deep-level image features and achieve feature reuse, and the data transformation operations such as image rotation and enhancement are used to expand the sample set in the experiment to enhance the detection effect. The simulation results demonstrate that the diagnosis procedure is quick and accurate.
Classification of FinTech Patents by Machine Learning and Deep Learning Reveals Trends of FinTech Development in China
Authors: Wang Hao , Chen Xizhuo , Du Jiangze , Lai Kin Keung
Published: July 2022

The development of the financial industry and its integration with information technology have promoted FinTech innovation. China is a major contributor to FinTech innovation, but few studies have systematically summarized FinTech innovation and development in China from the perspective of patents. This lacuna is attributable to the lack of a generally accepted classification of FinTech patents and the unavailability of classified Chinese FinTech patent text data. To fill this research gap, we developed a classification of Chinese FinTech patents and manually annotated a set of patent texts to train machine learning and deep learning models to classify massive Chinese patent application data and identify different types of FinTech innovations. Among the evaluated models, the character-level convolutional neural network (CNN) model and BERT model classified FinTech innovation most accurately. We used the character-level CNN to classify 20,529 Chinese FinTech patent applications from 2013 to 2020. The classified dataset was used to briefly analyze the history of FinTech innovation development in China and its future prospects.
Influence of Adenoid Hypertrophy on Malocclusion and Maxillofacial Development in Children
Authors: Zhang Liping , Liu Hui
Published: July 2022

Objective. To investigate the effect of adenoid hypertrophy on malocclusion and maxillofacial development in children. Methods. Total of 102 children with malocclusion or maxillofacial dysplasia admitted to our hospital from March 2017 to June 2020 were selected as the research subjects. All children were divided into a control group (50 cases with adenoid hypertrophy) and an observation group (52 cases without adenoid hypertrophy) according to the presence or absence of adenoid hypertrophy. The incidence of malocclusion was compared between the two groups, and lateral cranial radiographs were taken in both groups to measure and compare the malocclusion angle, jaw angle, and jaw length indexes between the two groups. Results. The incidence of malocclusion in the observation group (71.15%) was higher than that in the control group (42.00%), and the difference was statistically significant (

P
<
0.05

). The angle between the long axis of the upper central incisor and the nasal root point and the upper alveolar base point (U1-NA), the angle between the long axis of the lower central incisor and the nasal root point and the lower alveolar base point (L1-NB), the angle between mandibular plane and anterior cranial base plane (MP-SN), the angle between the long axis of upper central incisor and anterior cranial base plane (U1-SN), the angle between the long axis of lower central incisor and mandibular plane (L1-MP), the angle of Y axis, the overall height (N-Me), lower height (ANS-Me), overall height/back height (N-Me/S-Go), and lower height/overall height (ANS-Me/N-Me) values in the observation group were higher than those in the control group, while the mandibular length (Go-Gn) values in the observation group were lower than those in the control group (

P
<
0.05

). Conclusion. Adenoid hypertrophy can increase the incidence of malocclusion in children and can also increase the steepness and overall height and lower height of the mandible, resulting in the lengthening of the facial shape and the development of the maxillofacial deformity.
[Retracted] On the Ways of Political Philosophy Innovation and Popularization under the Network Environment
Authors: Ma Yan , Li Qi
Published: July 2022

From the perspective of comprehensive modernization, the Sinicization and modernization of Marxism are inseparable from the popularization of Marxism, which will promote the Sinicization and modernization of Marxism and make it more practical and vital. Time has changed, and the traditional ways and methods have faced a new pattern, but they still contain the practical value worth exploring and give full play to the contemporary function of beneficial historical experience. On the basis of drawing on historical experience, we follow the idea of establishing basic principles, focusing on important ways and looking for the development prospects, and discuss the discussion layer by layer in clear guidance, grasping the key points and thinking about the future. In today’s era, with the development of the network, the popularization of Marxist philosophy has ushered in a period of opportunity for development, but at the same time, the development has also encountered some challenges. Based on the actual situation of contemporary China, in recent years, the popularization of Marxism has made great achievements, but it also presents the phenomenon of unbalanced overall development, low operation efficiency, and uneven cooling between the officials and the people. Under these conditions, popularizing network knowledge, developing network culture, improving relevant laws, and making its theories more popular are all important ways to realize the popularization of Marxist philosophy. The research on the popularization of Marxism and the academic level is more profound, while the practical practice is more lacking. In order to correct the bias of emphasizing science and theory, it is of strong practical significance to conduct in‐depth theoretical research and practical discussion from the perspective of “ways and methods.”
Image Target Recognition Based on Improved Convolutional Neural Network
Authors: Wang Jinjuan , Zeng Xiliang , Duan Shan , Zhou Qun , Peng Hao
Published: July 2022

Convolutional neural network (CNN) algorithm is a very important branch of deep learning research, which has been widely applied in many fields and achieved excellent results, especially in computer vision, where convolutional neural network has made breakthroughs in image classification and object detection. Convolutional neural network architecture can realize more efficient network training through the final combination of different modules, and the convolutional neural network training does not need to actively extract image features and can directly carry out end-to-end training and prediction. At first, this paper analyzed some problems of the current image recognition and expounds the progress of convolution neural network in image recognition and then studied the traditional algorithm of target recognition, including traditional recognition algorithm framework of target, the target orientation, feature extraction, classifier classification, etc., and the traditional target recognition algorithm is compared with those of the target recognition algorithm of deep learning. On the basis of the above research, an improved model of CNN is proposed, which focuses on the structural design and network optimization of convolutional neural network and designs a more efficient convolutional neural network. Test experiments verify the effectiveness of the proposed model, which not only achieves lower error rate, but also greatly reduces the number of network parameters and has stronger learning ability.
Golden Cut-Oriented Q-Rung Orthopair Fuzzy Decision-Making Approach to Evaluation of Renewable Energy Alternatives for Microgeneration System Investments
Authors: Dinçer Hasan , Aksoy Tamer , Yüksel Serhat , Hacioglu Umit
Published: July 2022

This study aims to find an appropriate system for microgeneration energy investments and identify optimal renewable energy alternatives for the effectiveness of these projects. In this context, a model is constructed by multi stepwise weight assessment ratio analysis (M-SWARA) and technique for order preference by similarity to ideal solution (TOPSIS) with q-rung orthopair fuzzy sets (q-ROFSs) and golden cut. At the first stage, five different systems are weighted for the effectiveness of the microgeneration energy investments. Secondly, four different renewable energy alternatives are ranked regarding the performance of these projects. In addition, a comparative analysis is also implemented with intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs). The findings are the same in all different fuzzy sets that demonstrates the reliability of the findings. It is determined that grid-connected with battery backup is the most important system choice. On the other hand, solar energy is the most appropriate alternative for microgeneration system investments. Grid-connected system should be implemented for the performance of the microgeneration projects. Hence, providing a sustainable access to the electricity can be possible. Sufficient amount of electricity may not be obtained from wind and solar energy because of the climate changes. In this process, grid-connected system can handle this problem effectively.
Lentinan Enhances the Function of Oxaliplatin on the Esophageal Tumors by Persuading Immunogenic Cell Death
Authors: Huo Xiaolei , Pei Zhen , Wang Weiwei , Liu Yu , Sun Jing , Wang Hui , Ai Nanping
Published: July 2022

Objective. The focus of this research was to look at the effects of the combination of the lentinan (LNT) and oxaliplatin (Oxa) on the apoptosis of human esophageal cancer cells, as well as the underlying mechanism. Methods. LNT and Oxa were used to treat EC-109 human esophageal cancerous cells at various doses, and the cell survival rate was measured using the Cell Counting Kit-8 (CCK-8) assay. In addition, 24 h after treatment of EC-109 cells with a combination of LNT and Oxa, flow cytometry was used to analyze their apoptotic effect on these cells. Additionally, LNT on EC-109 cell apoptotic upshot was assessed via measuring the consequence of LNT on the mRNA and protein expression levels pertaining to immunogenic cell death factors CALR, HSP90, and HSP70 by qPCR (quantitative real-time polymerase chain reaction) and western blot analysis, correspondingly. Results. Cell proliferation was inhibited only when EC-109 cells were added with LNT at 1,200 μg/mL to the maximum concentrations, but the combination of LNT and Oxa at a low dose (800 μg/mL and 20 μM, respectively) significantly increased their sensitivity to Oxa and reduced their proliferation (

P
<
0.05

), and their apoptosis was significantly increased by LNT (

P
<
0.05

). The immunogenic cell death-related genes CALR, HSP90, and HSP70 had dramatically enhanced mRNA and protein expression levels after therapy with a combination of LNT and Oxa (

P
<
0.05

). Conclusion. These data imply that LNT increases the susceptibility of esophageal cancerous cells to Oxa by driving EC-109 cells to display immunogenic death. Therefore, LNT combined with Oxa may be an effective method in esophageal cancer management.
Research on the Application Effect of Strengthening Risk Management in Continuous Renal Replacement Therapy Nursing of Critically Ill Patients
Authors: Yang Huimei , Chen Yan , Fu Mingxia
Published: July 2022

Objective. To evaluate the efficacy of risk management in the nursing of critically ill patients on continuous renal replacement therapy (CRRT). Methods. In this retrospective study, 80 critically ill patients on continuous renal replacement therapy in our hospital from February 2020 to February 2021 were recruited. They were randomly assigned to receive either the risk management treatment (risk management group) or the conventional management treatment (conventional management group) via the random number table method. Outcome measurements included the occurrence of adverse events, complications, psychological status, quality of life, treatment compliance, duration of CRRT, and nursing satisfaction. Results. Risk management treatment was associated with lower incidence of adverse events compared to conventional management treatment (

P

value < 0.05). The risk management group also resulted in a lower incidence of complications compared to the conventional management group (

P

value < 0.05). Patients who received risk management treatments demonstrated a significantly lower anxiety/depression level and a higher World Health Organization Quality of Life Brief Version (WHOQOL-BREF) (

P

value < 0.05). The risk management group resulted in more cases with high compliance and fewer cases with moderate and poor compliance (

P
<
0.05

). Risk management was associated with more cases with a CRRT duration less than 36 hours and 36–48 hours and fewer cases with a duration longer than 48 h (X2 = 2.999,

P

value < 0.05). Patients who were given a risk management treatment had a higher nursing satisfaction compared to conventional management treatment (X2 = 4.501,

P

value < 0.05). Conclusion. Risk management treatment in caring of critically ill patients on CRRT shows better efficacy than conventional management treatments.
Clinical Application of Remifentanil Combined with Sevoflurane in Manual Reduction of Humeral Supracondylar Fracture in Children
Authors: Li Youqing , Yu Jiangping , Zhang Mingmin , Jia Meng
Published: July 2022

Objective. To explore the effect of the combination of remifentanil and sevoflurane on children with humeral supracondylar fractures undergoing manual reduction. Methods. A total of 60 children undergoing manual reduction external fixation due to humeral supracondylar fractures were enrolled between September 2020 and September 2021. According to the random number table method, they were divided into the control group (inhalation of 7% sevoflurane) and the observation group (inhalation of 7% sevoflurane and intravenous infusion of remifentanil). The heart rate (HR), mean arterial pressure (MAP), and blood oxygen saturation (SpO2) in both groups were investigated. The sedation and analgesic effects, fracture reduction, and complications were compared between the two groups. Results. There was no significant difference found in HR, MAP, or SpO2 between the two groups at 3 minutes prior to anesthesia, 2 minutes post anesthesia, and post manual reduction (

P
>
0.05

). The difference in HR, MAP, and SpO2 between the two groups was not statistically significant at any time point (

P
>
0.05

). The good rate of sedation and analgesia in the observation group was 93.33%, which is significantly higher than that in the control group (

P
<
0.05

). The reduction time and success rate of one-time manual reduction in the observation group were higher than those in the control group (

P
<
0.05

). There was no significant difference in fracture healing time between the two groups (

P
>
0.05

). Both groups had airway complications (nausea and vomiting, neurovascular damage and asphyxia, and laryngospasm). Conclusion. The combination of remifentanil and sevoflurane showed good sedative and analgesic effects on children with humeral supracondylar fractures undergoing manual reduction with relatively higher safety.
Synthesis and Characterization of Iron Doped Titanium Dioxide (Fe: TiO2) Nanoprecipitate at Different pH Values for Applications of Self-Cleaning Materials
Authors: Abza Tizazu , Saka Abel , Tesfaye Jule Leta , Gudata Lamessa , Nagaprasad N. , Krishnaraj Ramaswamy
Published: July 2022

Fe:TiO2 nano particles were deposited through sol-gel techniques, and the influence of pH values on structural, morphological, optical, and photoluminescence spectral behaviors was studied. Iron doped titanium dioxide nanopowders were analyzed using XRD, SEM, UV–ViS, and PL. Nano crystallized samples of titanium dioxide (72 nm, 77 nm, 78 nm, and 83 nm) were gained from X-Ray diffraction data and showed that there was the creation of unalloyed anatase and ructile segment with tetragonal configuration. The average crystal size was 77.5 nm. pH values provide the alteration of segments from anatase to ructile. The crystal size of prepared iron doped titanium dioxide nanoparticles was greater than before as pH value rises from 2 to 6 while FWHM and scrap sizes declined. Homogeneously disseminated cylindrical forms of iron doped titanium dioxide nanoparticles were perceived from scanning electron microscope graphics and rises in size with growing pH values from 2 to 6 in an acidic medium. Extremely translucent nanopowders are witnessed in the observable region by visible and redshifts near advanced wavelengths with rising pH values because of an increase in the size of particles from XRD data and SEM micrographs. The band gap of energy produced by nano concentrates was reduced with growing pH values that resemble the redshift of optical absorption superiority. The structural behaviors of deposited nanoparticles were also analyzed by Raman spectra and disclosed the existence of tetragonal anatase and ructile segments. EDS results confirmed that the dopant of pH values of the solutions might affect the size distributions of the Fe: TiO2 nanoparticles. The general decrement intensity was witnessed from photoluminescence outcomes.
Analysis of Clinical Effects of Comprehensive Nursing Based on Enhanced Recovery after Surgery in Patients with Embolization for Intracranial Aneurysms
Authors: Liu Jing , Zhang Kunxian , Wang Bei , Hu Qin , Zhang Qing , Wan Lei , Wang Xianpu , Xiong Wenping
Published: July 2022

Objective. This research sets out to elucidate the clinical effect of comprehensive nursing based on the concept of enhanced recovery after surgery (ERAS) in patients with embolization for intracranial aneurysms (IAs). Methods. This study enrolled 119 patients with embolization for IAs in the Zhongnan Hospital of Wuhan University from January 2020 to January 2021 and divided them into two groups according to the perioperative care they received: a control group (

n
=
39

) treated with routine perioperative nursing and an observation group (

n
=
80

) treated with ERAS-based comprehensive nursing. Surgical indicators, neurological function (National Institute of Health Stroke Scale (NIHSS) score; Scandinavian Stroke Scale (SSS) score), anxiety and depression (Self-Rating Anxiety Scale (SAS) score; Self-Rating Depression Scale (SDS) score), incidence of adverse events, and patient satisfaction were compared. Results. The observation group had better surgical indicators and lower scores of NIHSS, SSS, SAS, and SDS than the control group, accompanied by a lower incidence of adverse events and higher patient satisfaction. Conclusions. ERAS-based comprehensive nursing can better promote patients’ neurological recovery after embolization for IAs, relieve unhealthy emotions (depression, anxiety, etc.), and reduce the occurrence of adverse reactions, facilitating patient discharge.
Theaflavin-3,3

′

-Digallate Protects Cartilage from Degradation by Modulating Inflammation and Antioxidant Pathways
Authors: Teng Yun , Jin Zheyu , Ren Weizhi , Lu Minghao , Hou Mingzhuang , Zhou Quan , Wang Wenhao , Yang Huilin , Zou Jun
Published: July 2022

Background. Osteoarthritis (OA) is a common degenerative joint disease that may be closely linked to inflammation and oxidative stress destroying the balance of cartilage matrix. Theaflavin-3,3

′

-digallate (TFDG), a natural substance derived from black tea, has been reported to restrict the activity of inflammatory cytokines and effectively eliminate reactive oxygen species (ROS) in various diseases. However, it is not clear whether TFDG can improve OA. Methods. Chondrocytes were treated with or without IL-1β and 20 μM and 40 μM TFDG. The effect of TFDG on the proliferation of chondrocytes was detected by CCK8. RT-qPCR was used to detect the gene expression of inflammatory factors, extracellular matrix synthesis, and degradation genes. Western blot and immunofluorescence assays were used to detect the protein expression. The fluorescence intensity of reactive oxygen species labeled by DCFH-DA was detected by flow cytometry. We established an OA rat model by performing destabilized medial meniscus (DMM) surgery to observe whether TFDG can protect chondrocytes under arthritis in vivo. Results. TFDG was found to inhibit proinflammatory factors (IL-6, TNF-α, iNOS, and PGE) and matrix-degrading enzymes (MMP13, MMP3, and ADAMTS5) expression and protected extracellular matrix components of chondrocytes (ACAN, COL2, and SOX9). TFDG accelerated the scavenging of ROS caused by IL-1β according to the Nrf2 signaling pathway activation. At the same time, TFDG suppressed the PI3K/AKT/NF-κB and MAPK signaling pathways to delay the inflammatory process. The cartilage of DMM rats receiving TFDG showed lower Osteoarthritis Research Society International (OARSI) scores and expressed higher levels of COL2 and Nrf2 compared with those of rats in the DMM group. Conclusion. TFDG could protect cartilage from degradation and alleviate osteoarthritis in rats, which suggests that TFDG has potential as a drug candidate for OA therapy.
Application of Temperature Programmed Oxidation-Infrared Technique in the Analysis of Sulfur Occurrence and Genesis in Phosphate Rock
Authors: Xu Qiuyuan , Tang Shiyun , Tang Anjiang , Tian Yazhou
Published: July 2022

In this study, a temperature programmed oxidation-infrared (TPO-IR) technique was improved and applied in the analysis of sulfur occurrence and genesis in phosphate rock. Phosphate rocks from three regions (KYP, ZJP, and WAP) were selected for the detection of sulfur species by TPO-IR combined with XRD, SEM, EDS, and XPS characterization. TPO-IR results show that the total sulfur contents of the three phosphate rocks were 2.14% for KYP, 1.18% for ZJP, and 1.06% for WAP. In the low-temperature area (<1000°C), TPO-IR detected that both KYP and WAP contain FeS with a characteristic temperature of about 513°C and their contents were 9.22‰ and 0.64‰, respectively. In high-temperature areas (>1000°C), the TPO-IR curves suggest that sulfate is the main sulfur species in the three phosphate rocks. Typically, the characteristic temperature near 1070oC belongs to MgSO4, and the characteristic temperature near 1290°C belongs to CaSO4. Due to the incomplete TPO-IR database of sulfur reference materials at present, it is not possible to assign all sulfur species in high-temperature areas. However, in a sense, this research provides theoretical basis and experimental support for the application of the TPO-IR technique for the detection of sulfur species in other solid minerals.
Effects of Network Externalities and Recycling Channels on Closed-loop Supply Chain Operation Incorporating Consumers’ Dual Preferences
Authors: Xie Bo , Li Weizi , Zhao Dan , Jiang Peiyan
Published: July 2022

Consumers’ awareness of environmental protection is gradually strengthened, and they often consider environmental protection characteristics of products during purchasing products. Based on the characteristic of consumers’ dual preferences for product quality and environmental friendliness, this paper constructs a novel closed-loop supply chain with network externalities for new products and remanufactured products under different waste product recycling channel strategies. It discusses the influence of product recycling channel strategies and network externalities on the optimal decision of the company. By establishing the Stackelberg game model, the analysis found that the retail price of new products and remanufactured products is not affected by network externalities and recycling channel strategies, even if the wholesale price of remanufactured products increases with the influence of network externalities. The changing trend of market demand for new products and remanufactured products is different between products with network externalities and without network externalities. When the cost of remanufactured products is within certain range, the existence of network externalities makes the market demand for new products and remanufactured products increase simultaneously. Our study also found that even if products have positive network externalities that increases consumer utility, when the cost of remanufactured products is outside certain range, the company’s profit will be higher when products have no network externalities than that when products have network externalities.
Wireless Sensor Technology-Based Physical Education Teaching Evaluation
Authors: Feng Wei
Published: July 2022

A wireless sensor network (WSN) is a group of geographically scattered and specialized sensors to monitor and record variables related to environmental and storing the obtained data in a vital location. These networks have applications and can be utilized in different research domains including physical education where error prediction is assumed as one of the core issues. Thus, careful attention is required from the researcher to provide reliable and accurate prediction models. Thus, aiming the shortage of large prediction error in the physical education evaluation, which is based on the BP neural network and wireless sensor technology, a combination of AFP and questionnaire survey method is proposed in order to improve the accuracy and predictability of evaluation, according to the characteristics of different evaluation subjects. We select the evaluation index system as the input of wireless sensor technology and then use the principle of genetic algorithm to select the optimal individual and optimize the initial parameters of wireless sensor technology to establish the evaluation model of physical education quality. Through the training and testing of sample data, it is shown that the model greatly improves the accuracy of physical education quality evaluation and has a good application prospect in physical education evaluation.
Identification of a Novel Risk Model: A Five-Gene Prognostic Signature for Pancreatic Cancer
Authors: Wang Xiaoguang , Ni Man , Han Daxiong
Published: July 2022

Objective. Biomarkers for pancreatic cancer (PCa) prognosis provide evidence for improving the survival outcome of this disease. This study aimed to identify a prognostic risk model based on gene expression profiling of microarray bioinformatics analysis. Methods. Prognostic immune genes in the TCGA-PAAD cohort were identified using the univariate Cox regression and Kaplan–Meier survival analysis. Multivariate Cox regression (stepAIC) was used to identify prognostic genes from the top 20 hub genes in the protein-protein interaction (PPI) network. A prognostic risk model was established and its performance in predicting the overall survival in PCa was validated in GSE62452. Gene mutations and infiltration immune cells in PCa tumors were analyzed using online databases. Results. Univariate Cox regression and Kaplan–Meier survival analyses identified 128 prognostic genes. Multivariate Cox regression (stepAIC) identified five prognostic genes (PLCG1, MET, TNFSF10, CXCL9, and TLR3) out of the 20 hub genes in the PPI network. A prognostic risk model was established using the signature of five genes. This model had moderate to high accuracies (AUC > 0.700) in predicting 3-year and 5-year overall survival in TCGA and GSE62452 cohorts. The Kaplan–Meier survival analysis showed that high-risk scores were correlated with poor survival outcomes in PCa (

p
<
0.05

). Also, mutations in the five genes were related to poor survival. The five genes were related to multiple immune cells. Conclusions. The prognostic risk model was significantly correlated with the survival in PCa patients. This model modulated PCa tumor progression and prognosis by regulating immune cell infiltration.
[Retracted] Female Colon Cancer Metastasis Pattern and Prognosis: A SEER‐Based Study
Authors: Liu Yurong , Kang Rongbin , Zheng Huida , Wang Pengcheng , Jiang Weixin , Xiong Bin , Chen Jintao , Xu Jianhua
Published: July 2022

The purpose of this study was to compare the metastatic pattern and prognosis of female colon cancer (FCC) to that of male colon cancer (MCC) to ascertain the independent factors impacting the prognosis of patients with FCC. The data of the present study population were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Descriptive analysis, the Kaplan‐Meier method, and the Cox regression were used to evaluated FCC characteristics and factors associated with prognosis. There were 56,442 patients diagnosed with FCC, of whom 8,817 had distant metastases. Compared to patients with nonmetastatic FCC, a greater proportion of metastatic FCC patients was less than 60 years of age, black race, and grade III‐IV. The primary sites were mainly located on the left side and have more possibility to receive chemotherapy and radiotherapy. Compared to metastatic MCC, a higher proportion of metastatic FCC patients ranged over 60 years of age, black race, treated without chemotherapy, and insurance, while the primary site was located on the right side. Liver and lung were the two most common sites of solitary metastases in CC, and among patients with solitary metastases in CC, patients who had lung metastases had a better prognosis than those who developed other types of metastasizes. Patients with FCC with metastases of the liver had a worse prognosis than their MCC counterparts. Cox multivariate regression analysis showed that the risk ratio was higher in metastatic FCC patients compared to those without metastases. We report the survival comparison of metastatic FCC with nonmetastatic FCC through the SEER database. Our results suggest that it has unique clinicopathological features and differs from metastatic MCC. Furthermore, patients with liver metastatic FCC have a worse prognosis than those with MCC. Emphasis on screening for colon cancer in women and additional clinical care should be paid for, especially for patients with FCC with metastatic liver cancer.
Multiplication Processes in High-Density H-11B Fusion
Fuel
Authors: Belloni Fabio , Batani Katarzyna
Published: July 2022

Proton-boron fusion would offer considerable advantages for the purpose
of energy production as the reaction is aneutronic and does not involve
radioactive species. Its exploitation, however, appears to be particularly
challenging due to the low reactivity of the H-11B fuel
at temperatures up to 100 keV. Fusion chain-reaction concepts have been
proposed as possible means to overcome this limitation. Relevant findings
are reviewed in this article. Energy-amplification processes are also
presented, which are of interest for beam-fusion experiments and fast
ignition of H-11B fuel. Directions for further work are
outlined as well.
Open University Chinese Language and Literature Teaching Model Based on NLP Technology and Mobile Edge Computing
Authors: Liu Yan
Published: July 2022

With the further improvement of comprehensive national strength, both cultural soft power and international status have increased significantly. The Chinese language has also become one of the languages eagerly studied in all countries in the world. However, the teaching resources of Chinese as a foreign language are far from enough to meet the rapid growth of learning needs. With the continuous improvement of the network environment of high-performance, low-latency, and high-bandwidth mobile edge computing, using computer network technology to assist Chinese language learning is an effective way to meet the needs. Under this circumstance, this paper proposed to design and build a Chinese language learning system based on NLP (natural language processing) technology. The built system modules could be roughly divided into three parts: the basic module of the system, the learning module, and the tool module combined with NLP technology. And, through the rational use of these three modules, it provided learners with the basic teaching of the Chinese language and also collected a large number of relevant documents on the Chinese language and culture through the system, which was more convenient for learners to learn. Research showed that the learning system basically met the learning needs. According to the data survey on the use of international students, more than 90% of the international students who have used the system believed that the content expressed by the learning system was clear and scientific. The results showed that the design of the Chinese learning system met the learning needs of learners.
Cooperative Control of Multistation Passenger Inflows in Case of Irregular Large-Scale Passenger Flows
Authors: Zhu Wei , Chen Mengfei , Wang Pengling
Published: July 2022

This study focuses on the large passenger flow control problem, after an operation interruption occurs, to develop a methodology that can efficiently control the passenger inflows of multiple stations and avoid overcrowding inside stations. An early-warning model for irregular large-scale passenger flows (ILSPF) and a dynamic ILSPF control model are proposed. The early-warning model is developed to predict passenger flows in the future with historical data and detect when to start control measures in actual time. The ILSPF cooperative control model focuses on cooperatively controlling the passenger inflows of multiple stations to ensure passenger safety in vehicles and stations, as well as maximize the number of passengers transported and minimize the passengers’ total waiting times. An improved particle swarm optimization algorithm was designed to determine an optimal solution, and a case study on the Chengdu metro in China was carried out to examine the performance of the model. The obtained results verify the effectiveness of the model and algorithm and prove that ILSPF control can regulate the passenger inflow demand, better match the passenger demand and capability on the line, increase the total number of passengers transported, and balance the proportion of passenger boarding at each station.
Optimization and Design of a Sustainable Industrial Grid System
Authors: Iderus Samat , Peter Geno , Praghash K. , Vadde Aruna Rai
Published: July 2022

Electricity is a multifaceted form of energy and is used globally, with a continuously growing demand. Electrical power grids are there for more than 150 years. The generated electrical power is delivered to different industrial, commercial, and residential sectors, thereby fulfilling the ever-growing demand. In this research paper, the design and optimization of an industrial grid for various electrical loads is discussed. The electrical grid ensures a stable power supply to the loads by providing quality power with the minimum total harmonic distortion (THD) possible. A complete study of the short circuit current has been done in two different electrical grid systems, as it is seen that the short circuit current depends on the impedance of the transformer which feeds the load. These two designs of a single diagram will be simulated by using a power system analyzer, the Electrical Transient Analyzer Program (ETAP) software. The different electrical parameters, like choosing the optimised rated generator, cables, and transformers, are done. Load flow analysis is performed on both the design to evaluate the THD, short circuit fault, as well as to choose the right protection circuit for the system.
Integrated Online Order Picking and Vehicle Routing of Food Cold Chain with Demand Surge
Authors: Chen Youhua , Lan Hongjie , Wang Chuan , Jia Xiaoqiong
Published: July 2022

This paper focuses on the effect of demand surge on the food cold chain, where orders arrive online. The demand surge has successively affected the order batching, batch sequencing, and route planning, compared to regular demand. This research studies the integrated optimization of food cold chain order picking and vehicle routing of online orders, where mixed integer programming model is formulated to minimize time-consuming and cost. We firstly use K-means++ algorithm to cluster all customers, and then an online batch processing algorithm is designed in each region. Finally, a genetic algorithm is used to complete the joint optimization of the picking and delivery. We use X enterprise’s e-commerce platform as a case to collect actual operating data to verify the effectiveness of the model and algorithm. And comparing the analysis results between phased optimization and integrated optimization, reasonable suggestions are put forward for management decisions.
Analysis Model Design on the Impact of Foreign Investment on China’s Economic Growth
Authors: Zhang Lintao , Xang Robin H.
Published: July 2022

This research mainly analyzes the influence of foreign investment in the era of big data on China's economic growth, in the process of analyzing the impact of foreign investment on the national economy, based on the analysis of the current situation of foreign investment and error-correction model, etc., through the correlation coefficient matrix to determine the variables data needed to fit the model; after fitting the model, the residual model is extracted, and the stationarity of the residual sequence is tested . On the basis of the above, this paper analyzes the difference of foreign direct investment in different regions, combined with the coastal areas and central region model and actual situation analysis, analyzes the two foreign direct investment (FDI) development speeds, base development speed, and average development speed, at the same time for the two regions in 2017; the specific direction of FDI do a detailed analysis. Finally, a series of conclusions are obtained.
Landscape Preference of Rural Cultural Tourism Tourists Based on GIS Spatial Statistical Technology and Emotion Analysis
Authors: Yang Wenhua
Published: July 2022

How to combine GIS spatial statistics technology to realize the intelligent and efficient classification of tourists’ landscape preferences is a hot spot in the direction of rural cultural tourism. Based on this, this paper studies the emotion analysis strategy based on GIS spatial statistical method in the field of landscape preference of rural cultural tourism tourists. Firstly, an intelligent and efficient classification model based on remote sensing discrete expansion algorithm is proposed. Combined with the observation strategy of common emotional rules in the landscape preference analysis of rural cultural tourism tourists, the landscape preference of rural cultural tourism tourists is processed with high quantitative emotional information, so as to realize the intelligent separation of preference, and then the error of discrete remote sensing data expansion model is corrected. Secondly, the judgment function of emotional rules is constructed, and the commonly used data layer-driven decentralized method is used in preference classification to eliminate the secondary factors in the landscape preference analysis of rural cultural tourism tourists. At the same time, the remote sensing discrete expansion algorithm is used to optimize and improve the emotional rules of high-volume emotional information based on GIS spatial statistical method. Finally, through the design of confirmatory experiments, the results show that the landscape preference analysis model based on GIS spatial statistics method and remote sensing discrete expansion algorithm is more efficient than the conventional preference classification method.