bluuebunny/crossref_metadata_2025 huggingface dataset:
The multiple roles that IPv6 addresses can play in today's internet
Authors: Piraux Maxime , Barbette Tom , Rybowski Nicolas , Navarre Louis , Alfroy Thomas , Pelsser Cristel , Michel François , Bonaventure Olivier
Published: September 2022

The Internet use IP addresses to identify and locate network interfaces of connected devices. IPv4 was introduced more than 40 years ago and specifies 32-bit addresses. As the Internet grew, available IPv4 addresses eventually became exhausted more than ten years ago. The IETF designed IPv6 with a much larger addressing space consisting of 128-bit addresses, pushing back the exhaustion problem much further in the future.

In this paper, we argue that this large addressing space allows reconsidering how IP addresses are used and enables improving, simplifying and scaling the Internet. By revisiting the IPv6 addressing paradigm, we demonstrate that it opens up several research opportunities that can be investigated today. Hosts can benefit from several IPv6 addresses to improve their privacy, defeat network scanning, improve the use of several mobile access network and their mobility as well as to increase the performance of multicore servers. Network operators can solve the multihoming problem more efficiently and without putting a burden on the BGP RIB, implement Function Chaining with Segment Routing, differentiate routing inside and outside a domain given particular network metrics and offer more fine-grained multicast services.
Raising out of Finite Clauses (Hyperraising)
Authors: Zyman Erik
Published: September 2022

Classical syntactic theory was designed to permit the type of movement called raising to proceed out of infinitival, but not finite, clauses—a positive result for languages such as English. But crosslinguistic investigation reveals that many languages actually allow raising out of finite clauses (hyperraising), challenging certain commonly assumed locality constraints on movement. This article reviews three types of Minimalist analyses of hyperraising and how they address these challenges, noting the strengths and shortcomings of each. Defectiveness/nonphase analyses commendably tie a clause's ability to launch hyperraising to independent observables, but such analyses struggle to derive the former from the latter. Deactivation analyses boast empirical successes but do not straightforwardly rule out hyperraising in English. Phase-edge analyses also boast empirical successes but face empirical and/or conceptual problems (to which a solution is sketched out) and open questions about learnability. These evaluations are intended to spur syntacticians to develop stronger versions of all three types of analyses, bringing us closer to fully understanding the factors regulating movement, a subcase of the fundamental structure-building operation Merge.
Ultralow Loading Ru-Mo2C on CNT Boosting High Durability Electrocatalyst for Oxygen Reduction Reaction
Authors: Gao Jiangshan , Lian Tongtong , Wang Huanhuan , Liu Zhiming , He Yan
Published: September 2022

The high cost and low stability of Pt-based oxygen reduction reaction (ORR) catalysts have limited their commercial applications. In this paper, we report the microwave synthesis of ultralow loading Ru-Mo2C on carbon nanotubes (CNT) as ORR catalysts to alleviate these above disadvantages. Ru-Mo2C@CNT exhibited excellent oxygen reduction reaction activity with a half-potential of 0.87 V and an onset potential of 0.94 V. It has high stability and palmary anti-methanol capability in alkaline electrolytes. This Ru-Mo2C@CNT may be a promising alternative to Pt-based electrocatalysts in energy conversion and storage.
Rapid Determination of All-Solid-State Battery Performance via Chronoamperometry
Authors: Yanev S. , Auer H. , Heubner C. , Höhn S. , Nikolowski K. , Partsch M. , Michaelis A.
Published: September 2022

All solid-state batteries (ASSBs) are considered among the most promising next-generation energy storage devices but are currently still limited in terms of performance. To advance the development process in an efficient way, appropriate characterization methods are needed. Herein, we demonstrate chronoamperometry to rapidly evaluate the performance of ASSBs. Examples are given using argyrodite solid electrolyte together with various cathode active materials. It is shown that chronoamperometry provides equivalent rate capability information to common galvanostatic testing procedures, while being much simpler and significantly faster (e.g. by a factor between 8 and 33 for the tested materials). The high data density allows accurate model-based analysis to identify the rate limiting mechanism, such as electrical or diffusion limitations, and to determine the active material utilization at very low rates. An effective C-rate is proposed, which describes the rate performance of the utilizable active material. The observed electrode- and active material-specific performance differences are explained by morphological effects, supported by scanning electron microscopy analyses of the cathode cross sections. The results demonstrate the ability of chronoamperometry to rapidly quantify electrochemical performance and provide a deeper understanding of the limitations of ASSBs.
New Calibration Method for Kelvin Probe in Changing Humidity Conditions
Authors: Seeger Lea , Lobnig Renate , Wicinski Mariusz
Published: September 2022

The use of the Kelvin probe (KP) to determine Ecorr values is based on the relationship E

corr

= const. + ΔΨ (with ΔΨ = measured value of the KP and const. = constant). The constant const. is determined by calibration above a reference sample with known Ecorr. It has been shown that the constant const. can vary by up to 172+/−18 mV with a probe of nickel and 178 μm probe diameter, when the relative humidity RH varies between 42% and 98%, which must be taken into account when making measurements under changing climatic conditions. It has been shown, theoretically and experimentally, that the RH at the probe tip 40 μm above a saturated salt solution is nearly equal to its critical relative humidity. An experimental procedure is proposed to determine the dependence of const. on RH. For this purpose 4 Cu/saturated Cu-salt half-cells are used. Additionally, a method is proposed to measure the critical relative humidity of a saturated salt solution using KP.
Influences of Ultrasonic Image-Guided Erector Spinae Plane Block on Postoperative Pulmonary Air Content of Lung Carcinoma Patients Undergoing Thoracoscopic Surgery
Authors: Xu Xiuqing , Yang Shengrong , Gao Pei
Published: September 2022

To investigate the influences of ultrasonic image-guided erector spinae plane block (ESPB) on postoperative pulmonary air content of lung carcinoma patients undergoing thoracoscopic surgery, 42 patients performed with thoracoscopic radical surgery for lung carcinoma were selected. The patients in the experimental group were performed with ultrasound-guided unilateral ESPB and intravenous general anesthesia. The patients in the control group only underwent intravenous anesthesia. The changes in postoperative pulmonary air content between the two groups were compared. After that, all included patients were divided into the experimental (senior) group (13 cases), the experimental (adult) group (8 cases), the control (senior) group (11 cases), and the control (adult) group (10 cases) according to age. The changes in postoperative pulmonary air content of patients in the four groups were compared. The results showed that lung ultrasound score (LUS) of patients in experimental group was

6.4
±
3.2

points 0.5 hour after catheter extraction and LUS was

4.1
±
2.3

points 20 to 30 hours. Both scores were remarkably lower than those of patients in control group (

P
<
0.05

). LUS of lower left anterior area, upper left posterior area, lower left posterior area, upper right posterior area, and lower right posterior area of patients in experimental group was all apparently lower than those in control group 0.5 hour after catheter extraction (

P
<
0.05

). LUS of upper left posterior area, lower left posterior area, lower right anterior area, upper right posterior area, and lower right posterior area of patients in experimental group was all remarkably lower than those in control group 20 to 30 hours after surgery (

P
<
0.05

). LUS of senile patients and middle-aged patients in experimental group 0.5 hour after catheter extraction was

8.01
±
2.48

points and

5.93
±
3.91

points, respectively, which were both notably lower than those in control group (

P
<
0.05

). Ultrasound-guided ESPB exerted fewer influences on lung and could effectively improve postoperative pulmonary air content among patients. Hence, it was worthy of clinical promotion.
Clustering Algorithm in English Language Learning Pattern Matching under Big Data Framework
Authors: Zheng Liying
Published: September 2022

The Internet era has brought new challenges and opportunities for English learning and English teaching. At the same time, basic education is fully implementing quality education and respecting students’ individual differences. The same teacher teaches the same content to the same class of students, but some students perform well, and some students perform poorly due to the influence of intellectual and nonintellectual factors. The uneven performance of students in the same class makes it very difficult for teachers to teach. In view of the current situation of university English teaching and the trend of respecting students’ individual development in the new era, this study investigates the basic concept of English language learning pattern matching, its main features, and practical application in the process of university English teaching. The clustering algorithm based on the big data framework is proposed for English language learning pattern matching, which is fault-tolerant and can quickly acquire and process the big data information in English teaching. By analyzing the characteristics of the data mining method of students’ English learning behavior, the method of clustering processing for students’ English learning data mining and the processing method of students’ English learning clustering data are explored. The method is highly adaptable and can be used for actual English language learning pattern matching, and actively explores the main path of English teaching change and innovation.
Influence of Sevoflurane Inhalation Anesthesia on Clinical Outcomes of Morbidly Obese Patients Undergoing Laparoscopic Bariatric Surgery
Authors: Li Wei , Zhang Ying , Lv Jianrui , Zhang Yong , Bai Jie
Published: September 2022

Background. Morbid obesity is one of the fastest-growing subgroups of obesity and is associated with high mortality, with an estimated 2.8 million people dying from obesity each year. Objective. This research sets out to elucidate the impact of sevoflurane (Sevo) inhalation anesthesia on the clinical outcome of morbidly obese (MO) patients undergoing laparoscopic bariatric surgery (LBS). Methods. A retrospective study was conducted on 150 MO patients undergoing LBS in the Second Affiliated Hospital of Xi’an Jiaotong University from November 2019 to November 2021. According to the difference of anesthesia methods, 100 patients with Sevo anesthesia were set as group A, and 50 patients with propofol (P) anesthesia were set as group B. Intergroup comparisons were performed in terms of eye-opening time, tracheal intubation removal time, directional force recovery, heart rate (HR), mean arterial pressure (MAP), peak airway pressure (Ppeak), plateau pressure (Pplat), standard time out of PACU, postoperative food intake (FI), length of stay (LOS), and complication rate. Results. Group A had a shorter time to open eyes, remove tracheal intubation, and restore directional force than Group B, with better recovery of HR, MAP, Ppeak, and Pplat. Group A was also superior to Group B in the standard time out of PACU, postoperative FI, and LOS, with a lower complication rate. Conclusions. Sevo inhalation anesthesia is more effective and safer for MO patients undergoing LBS.
NSSIA: A New Self-Sovereign Identity Scheme with Accountability
Authors: Lyu Qiuyun , Cheng Shaopeng , Li Hao , Liu Junliang , Shen Yanzhao , Wang Zhen
Published: September 2022

Self-sovereign identity (SSI) is a new distributed method for identity management, commonly used to address the problem that users are lack of control over their identities. However, the excessive pursuit of self-sovereignty in the most existing SSI schemes hinders sanctions against attackers. To deal with the malicious behavior, a few SSI schemes introduce accountability mechanisms, but they sacrifice users’ privacy. In addition, the digital identities (static strings or updatable chains) in the existing SSI schemes are as inputs to a third-party executable program (mobile app, smart contract, etc.) to achieve identity reading, storing and proving, and users’ self-sovereignty are weakened. To solve the above problems, we present a new self-sovereign identity scheme to strike a balance between privacy and accountability and get rid of the dependence on the third-party program. In our scheme, one and only individual-specific executable code is generated as a digital avatar-i for each human to interact with others in cyberspace without a third-party program, in which the embedding of biometrics enhances uniqueness and user control over their identity. In addition, a joint accountability mechanism, which is based on the shamir (t, n) threshold algorithm and a consortium blockchain, is designed to restrict the power of each regulatory authority and protect users’ privacy. Finally, we analyze the security, SSI properties and conduct detailed experiments in terms of the cost of computation, storage, and blockchain gas. The analysis results indicate that our scheme resists the known attacks and fulfills all the six SSI properties. Compared with the state-of-the-art schemes, the extensive experiment results show that the cost is larger in server storage, blockchain storage, and blockchain gas, but is still low enough for practical situations.
Analysis of the Application Effect of Exercise Rehabilitation Therapy Based on Data Mining in the Prevention and Treatment of Knee Osteoarthritis
Authors: Liu Wei , Wang Congan , Yu Gongchang , Shi Bin , Wang Jingwen
Published: September 2022

Objective. To analyze the application effect of exercise rehabilitation therapy based on data mining in the prevention and treatment of knee osteoarthritis. Methods. Based on clinical data mining technology, that is, using complex network technology and association rules, the medical records of 1612 patients with KOA in the Department of Rheumatology and Immunology of our hospital were retrospectively analyzed, and they were divided into groups according to whether they used exercise rehabilitation therapy (

n
=
786

), and the control treatment group (

n
=
826

), the curative effect, the improvement of inflammatory factors and immune factors, the visual analogue scale (VAS), the knee joint function score (Lysholm), and the quality of life (WOMAC) scale were compared between the two groups score, analyze the relationship between VAS and Lysholm score and prognosis quality of life, and compare the recurrence within 12 months between the two groups. Results. The data mining results showed that the curative effect of the exercise rehabilitation therapy group was significantly higher than that of the control treatment group (

P
<
0.05

); the improvement of VAS and Lysholm scores of the exercise rehabilitation therapy group was significantly better than that of the control treatment group (

P
<
0.05

). The improvement effect of inflammatory indexes and immune cytokines was significantly better than that of the control treatment group (

P
<
0.05

); the improvement of WOMAC in the exercise rehabilitation therapy group was significantly better than that of the control treatment group (

P
<
0.05

); VAS and WOMAC scores were significantly positively correlated (

r
=
0.579

,

P
<
0.05

); Lysholm score was positively correlated with WOMAC score (

r
=
−
0.563

,

P
<
0.05

); the recurrence rate of exercise rehabilitation therapy group was 5.09%, which was significantly lower than that of control treatment group (17.63% (

χ

2

=
11.967

),

P
<
0.05

). Conclusion. Exercise rehabilitation therapy for KOA patients can effectively improve inflammatory and immune factors in patients, enhance knee joint function and prognosis quality of life, and reduce readmission rate, which is worthy of clinical application.
Overall Cost Overrun Estimate in Residential Projects: A Hybrid Dynamics Approach
Authors: Taha Ghada , Sherif Ali , Badawy Mohamed
Published: September 2022

Residential projects are described as complex, dynamic systems that are subject to uncertainty. Cost performance is a fundamental challenge. As a result, project managers must adequately identify risks that might lead to cost overruns in residential construction projects. Simulation is noticed to be a useful technique for dealing with these complications. Therefore, this study developed a hybrid dynamic approach to study the effect of different risks on the cost performance of construction projects. The proposed approach combines system dynamics (SD) and discrete event simulation (DES), which can take into consideration the dynamics of the project environment, which contains various continuous influencing factors as well as the construction operations. The developed hybrid model is validated through serial model structure tests and model behavior tests, with the aid of data collected from a real construction project used in the simulation process. Based on the simulation results, it is concluded that the proposed hybrid dynamic approach is helpful to enhance the process performance by permitting construction managers to identify possible process improvement areas that traditional methods may miss.
Medicinal Plants Used as an Alternative to Treat Gingivitis and Periodontitis
Authors: Rani Neeraj , Singla Rajeev K. , Narwal Sonia , Tanushree  , Kumar Nitish , Rahman Md. Mominur
Published: September 2022

For various ailments, natural remedies have been traditionally used. To defend against common disorders, medicinal plants are progressively used as nutritional supplements. Gingivitis and periodontitis are widespread and can affect most of the world’s population. Gingivitis is a very common, nondestructive inflammatory disease of gums that causes redness and irritation of the gingiva (gums), but periodontitis causes permanent damage to teeth’ subsidiary structures. Herbal medicines are getting popular for the treatment of such types of disorders due to being economical with their medicinal effectiveness, compatibility, and nontoxicity. Traditional chemical therapies can cause cell toxicity along with their disease-curing effects. In this article, we discussed the medicinal plants that can be used as an alternative for the treatment of gingivitis (early-stage gum disease) and periodontitis (chronic-stage gum disease).
A Study on Knowledge Sharing Behavior among IT Engineers: An Extended Theory of Planned Behavior
Authors: Pham Thi Thuy Dung , Duong Nam Tien
Published: September 2022

With the rapid development of information technology (IT) and the advent of globalization, enterprises have entered the knowledge economy era. Thus, knowledge has become a power for future enterprises to win. In practice, the more actively the employees in the organization share knowledge, the more they can exert the value of knowledge. This study adopted the theory of planned behavior (TPB) as the basic theory in the research model. Besides, by reviewing previous studies on knowledge management and knowledge sharing (KS), we found nine exogenous variables and examined their relationships with KS attitude, subjective norm, and perceived behavior control. With a sample of 325 IT engineers in Vietnam, the study used Structural Equation Modeling (SEM) to test the hypotheses. The findings showed that the exogenous variables affecting KS attitude are expected relationship, expected loss, altruism, and task interdependence. The exogenous variables affecting the subjective norm are affect-based trust and task interdependence. An exogenous variable affecting perceived behavioral control is the adequacy of personal resources. In the relationships among endogenous variables in the TPB model, only the causal relationship of subjective norm influencing intention is not supported, and the rest of the causal relationships are supported. In the influence relationship between endogenous variables in the theoretical model of planned behavior, only the causal relationship of subjective norm influencing intention does not exist, and the rest of the causal relationships are established. Finally, findings can serve as references and suggestions for subsequent KS research in academic and practical aspects.
Expression and the Prognostic Value of Biglycan in Gastric Cancer
Authors: Hu Sizhe , Li Peipei , Wang Chenying , Liu Xiyong
Published: September 2022

Background. Biglycan (BGN) is a family member of small leucine-rich repeat proteoglycans. High expression of BGN might enhance the invasion and metastasis in some types of tumors. Here, the prognostic significance of BGN was evaluated in gastric cancer. Material and Methods. Two independent Gene Expression Omnibus (GEO) gastric cancer microarray datasets (

n
=
64

and

n
=
432

) were collected for this study. Kaplan-Meier analysis was applied to evaluate if BGN impacts the outcomes of gastric cancer. Protein-protein interaction (PPI) analysis was performed on gastric cancer-related genes and BGN targets, and those interactions with

confidence
 
interval
 

CI

≥
0.7

were chosen to construct a PPI network. The gene set enrichment analysis (GSEA) was used to explore BGN and cancer-related gene signatures. Gene Transcription Regulation Database (GTRD) and ALGGEN-PROMO predicted the transcription factor binding sites (TFBSs) of the BGN promoter. BGN protein level in gastric cancer tissue was determined by immunohistochemistry (IHC). Bioinformatic analysis predicted the putative TFs of BGN. Results. For gastric cancer, the mRNA expression level of BGN in tumor tissue was significantly higher than that in normal tissue. Kaplan-Meier analysis showed that higher expression of BGN mRNA was significantly associated with more reduced recurrence-free survival (RFS). GSEA results suggested that BGN was significantly enriched in gene signatures related to metastasis and poor prognosis, revealing that BGN might be associated with cell proliferation, poor differentiation, and high invasiveness of gastric cancer. Meanwhile, the putative TFs, including AR, E2F1, and TCF4, were predicted by bioinformatic analysis and also significantly correlated with expression of BGN in mRNA levels. Conclusion. High expression of BGN mRNA was significantly related to poor prognosis, which suggested that BGN was a potential prognostic biomarker and therapeutic target of gastric cancer.
Experimental Study on Gas Permeability Semiempirical Model of Granite after Heat Treatment
Authors: Wu Jinquan
Published: September 2022

High temperature will cause a thermal crack of a rock, thus affecting the permeability change of rock. To explore the effects of temperature on permeability and microstructure of rock microstructure, the granite after 50–800 C thermal treatment was carried out by gas permeability test, combined with computed tomography (CT) scanning technology. The granite internal three‐dimensional reconstruction was conducted after high‐temperature thermal treatment, and the characteristics of the microstructure were also deeply analyzed. On this basis, the applicability of the Costa model under high temperature was discussed. Finally, the temperature‐permeability model of granite after the high temperature was proposed combined with the pore fractal model. The new model was verified with experimental data.
On the Power-Splitting Relaying Protocol for SWIPT with Multiple UAVs in Downlink NOMA-IoT Networks
Authors: Tran Huu Q. , Phan Ca V. , Vien Quoc-Tuan
Published: September 2022

Unmanned aerial vehicle (UAV) communication and non-orthogonal multiple access (NOMA) are two promising technologies for wireless 5G networks and beyond. The UAVs can be used as flying base stations to form line-of-sight communication links to the Internet of things devices (IDs) and to enhance the performance of usual terrestrial cellular networks. Moreover, the UAVs can also be deployed as flying relay nodes for forwarding data from a base station (BS) to the IDs. On the other hand, non-orthogonal resource sharing for many concurrent users is exploited in NOMA, thus improving spectrum efficiency (SE) and supporting massive connections. The NOMA combined with energy harvesting (EH) in an amplify-and-forward (AF) with cooperative UAV systems is researched. Specifically, the UAVs act as rotary-wing relays to forward data from the BSs to two IDs. This paper focuses on the analysis of outage probabilities (OPs), system throughput, and energy efficiency (EE) for two IDs. Besides, we also do the asymptotic analysis of OPs at high signal-to-noise ratios (SNRs). Furthermore, this paper also inspects the impacts of the UAV-based relaying on the OP, system throughput, and EE of the proposed NOMA scheme. The derived asymptotic expansions show that the suggested model can enhance user fairness and the analytical results match the simulation results.
Identification of Prognostic Signature of Necroptosis-Related lncRNAs and Molecular Subtypes in Glioma
Authors: Zhang Guanghao , Chen Rundong , Zhu Luojiang , Ma Hongyu , Tang Haishuang , Shang Chenghao , Wang Jing , Zhang Deyu , Li Qiang , Liu Jianmin
Published: September 2022

Background. In tumor progression and epigenetic regulation, long non-coding RNA (lncRNA) and necroptosis are crucial regulators. However, in glioma microenvironment, the role of necroptosis-related lncRNAs (NRLs) remains unknown. Method. In this study, the RNA-seq and clinical annotation of glioma patients were analyzed using the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. To investigate prognosis and tumor microenvironment of NRLs in gliomas, we conducted a prediction model based on the training cohort. The accuracy of the model was verified in the verification cohort. Results. A signature composed of 13 NRLs was identified, and all glioma patients were divided into two groups. We found that each group has unique survival outcomes, biological behaviors, and immune infiltrating status. The necroptosis-related lncRNA signature (NRLS) model was found to be an independent risk factor in multivariate Cox analysis. Immunosuppressive microenvironment was positively correlated with the high-risk group. Due to significantly different IC50 between risk groups, NRLS could be used as a guide for chemotherapeutic treatment. Further, the entire cohort was divided into two clusters depending on NRLs. Consensus clustering method and the risk scoring system were basically similar. Survival probability was higher in Cluster 2, while Cluster 1 has stronger immunologic infiltration. Conclusion. The predictive signature could be a prognostic factor independently and serve to detect the role of NRLs in glioma immunotherapy response.
Exploration of the Problems and Solutions Based on the Translation of Computer Software into Japanese Language
Authors: Hu Lian , Hu Jing
Published: September 2022

At present, the research on machine translation mainly focuses on English-Chinese translation, while the research on Japanese college students using Japanese Chinese machine translation software is relatively few. In order to solve the above problems in Chinese Japanese bilingual translation, this paper proposes a phrase translation method based on sequence intersection. This method regards sentences as word sequences and aligns the sequence intersection of all source sentences corresponding to the target sentence in the corpus with Chinese and Japanese sentences containing the phrases to be translated. By fully mining the information of sentence alignment bilingual corpus without word alignment resources, we can obtain high-quality phrase translation, syntactic analysis, and dictionary. Then, we focus on the automatic construction of sentence level aligned bilingual corpus and explore the automatic sentence alignment technology of Chinese and Japanese bilinguals. A ten-year alignment model based on combination cues and core extended square matching is proposed. The preprocessing of the computer corpus and the basic construction of the corpus are completed. This paper also puts forward corresponding countermeasures and approaches to the problems encountered in the construction of computer translation.
Targeting Strategies for Aberrant Lipid Metabolism Reprogramming and the Immune Microenvironment in Esophageal Cancer: A Review
Authors: Cui Meng-Ying , Yi Xing , Cao Zhen-Zhen , Zhu Dan-Xia , Wu Jun
Published: September 2022

Esophageal cancer is of high importance to occurrence, development, and treatment resistance. As evidenced by recent studies, pathways (e.g., Wnt/β-catenin, AMPK, and Hippo) are critical to the proliferation, differentiation, and self-renewal of esophageal cancer. In addition, the above pathways play a certain role in regulating esophageal cancer and act as potential therapeutic targets. Over the past few years, the function of lipid metabolism in controlling tumor cells and immune cells has aroused extensive attention. It has been reported that there are intricate interactions between lipid metabolism reprogramming between immune and esophageal cancer cells, whereas molecular mechanisms should be studied in depth. Immune cells have been commonly recognized as a vital player in the esophageal cancer microenvironment, having complex crosstalk with cancer cells. It is increasingly evidenced that the function of immune cells in the tumor microenvironment (TME) is significantly correlated with abnormal lipid metabolism. In this review, the latest findings in lipid metabolism reprogramming in TME are summarized, and the above findings are linked to esophageal cancer progression. Aberrant lipid metabolism and associated signaling pathways are likely to serve as a novel strategy to treat esophageal cancer through lipid metabolism reprogramming.
Effects of Lysophospholipid Supplementation in Feed with Low Protein or Lipid on Growth Performance, Lipid Metabolism, and Intestinal Flora of Largemouth Bass (Micropterus salmoides)
Authors: Lu Ziye , Yao Chunfeng , Tan Beiping , Dong Xiaohui , Yang Qihui , Liu Hongyu , Zhang Shuang , Chi Shuyan
Published: September 2022

The largemouth bass (Micropterus salmoides) were fed diets with three experimental feeds, a control diet (Control, crude protein (CP): 54.52%, crude lipid (CL): 11.45%), a low-protein diet with lysophospholipid (LP-Ly, CP: 52.46%, CL: 11.36%), and a low-lipid diet with lysophospholipid (LL-Ly, CP: 54.43%, CL: 10.19%), respectively. The LP-Ly and LL-Ly groups represented the addition of 1 g/kg of lysophospholipids in the low-protein and low-lipid groups, respectively. After a 64-day feeding trial, the experimental results showed that the growth performance, hepatosomatic index, and viscerosomatic index of largemouth bass in both the LP-Ly and LL-Ly groups were not significantly different compared to those in the Control group (

P
>
0.05

). The condition factor and CP content of whole fish were significantly higher in the LP-Ly group than those in the Control group (

P
<
0.05

). Compared with the Control group, the serum total cholesterol level and alanine aminotransferase enzyme activity were significantly lower in both the LP-Ly group and the LL-Ly group (

P
<
0.05

). The protease and lipase activities in the liver and intestine of both group LL-Ly and group LP-Ly were significantly higher than those of the Control group (

P
<
0.05

). Compared to both the LL-Ly group and the LP-Ly group, significantly lower liver enzyme activities and gene expression of fatty acid synthase, hormone-sensitive lipase, and carnitine palmitoyltransferase 1 were found in the Control group (

P
<
0.05

). The addition of lysophospholipids increased the abundance of beneficial bacteria (Cetobacterium and Acinetobacter) and decreased the abundance of harmful bacteria (Mycoplasma) in the intestinal flora. In conclusion, the supplementation of lysophospholipids in low-protein or low-lipid diets had no negative effect on the growth performance of largemouth bass, but increased the activity of intestinal digestive enzymes, enhanced the hepatic lipid metabolism, promoted the protein deposition, and regulated the structure and diversity of the intestinal flora.
Experimental Study on the Incipient Movement of Muddy Clay under Different Salinity Conditions
Authors: Zhang Xiaolei , Liu Xin , Wu Haoran , Liu Shuyu , Zhu Yu , Bi Zhengzheng , Xu Zhiheng
Published: September 2022

In order to understand the incipient movement of muddy clay under different salinity conditions, three series of flume tests were performed on incipient movement of muddy clay, including tests on incipient movement of salt-free clay mud under salt water conditions (salt water-salt-free clay mud), incipient movement of salt clay mud under salt water conditions (salt water-salt clay mud), and incipient movement of salt clay mud under freshwater conditions (freshwater-salt clay mud), using a circulating flume, in which the salinity of the water body or cohesive sediment varies from 0 to 40%. Based on the particle image velocimetry system and digital image gray processing technology, the gray curves of water near the clay mud bed surface with the velocity were plotted to quantitatively differentiate the incipient velocity of the sediment for each test. The experimental results showed that the higher the salinity of the water body or cohesive sediments is, the more difficult it is to start moving. There is a logarithmic relationship between the incipient velocity of cohesive sediments and the salinity of the water or cohesive sediments. The incipient velocity increases sharply at a salinity of 0∼10% and slowly at a salinity of 10∼40%. At the same salinity, the incipient velocity of salt clay mud under freshwater conditions is the largest, followed by that of salt clay mud under salt water conditions, while that of salt-free clay mud under salt water conditions is the smallest. In addition, the flow turbulence characteristics were analyzed under the critical conditions of the onset of muddy clay. Ultimately, an empirical formula to calculate the critical incipient velocity of muddy clay is proposed by introducing the salinity. In this study, salinity is included as a reference variable, which expands the research scope of sediment initiation and provides a reference for the study of estuary dynamics.
InSilc Computational Tool for In Silico Optimization of Drug-Eluting Bioresorbable Vascular Scaffolds
Authors: Milosevic Miljan , Anic Milos , Nikolic Dalibor , Milicevic Bogdan , Kojic Milos , Filipovic Nenad
Published: September 2022

Stents made by different manufacturers must meet the requirements of standard in vitro mechanical tests performed under different physiological conditions in order to be validated. In addition to in vitro research, there is a need for in silico numerical simulations that can help during the stent prototyping phase. In silico simulations have the ability to give the same stent responses as well as the potential to reduce costs and time needed to carry out experimental tests. The goal of this paper is to show the achievements of the computational platform created as a result of the EU-funded project InSilc, used for numerical testing of most standard tests for validation of preproduction bioresorbable vascular scaffolds (BVSs). Within the platform, an ad hoc simulation protocol has been developed based on the finite element (FE) analysis program PAK and user interface software CAD Field and Solid. Two different designs of two different stents have been numerically simulated using this integrated tool, and the results have been demonstrated. The following standard tests have been performed: longitudinal tensile strength, local compression, kinking, and flex 1-3. Strut thickness and additional pocket holes (slots) in two different scaffolds have been used as representative parameters for comparing the mechanical characteristics of the stents (AB-BVS vs. AB-BVS-thinner and PLLA-prot vs. PLLA-plot-slot). The AB-BVS-thinner prototype shows better overall stress distribution than the AB-BVS, while the PLLA-prot shows better overall stress distribution in comparison to the PLLA-plot-slot. In all cases, the values of the maximum effective stresses are below 220 MPa—the value obtained by in vitro experiment. Despite the presented results, additional considerations should be included before the proposed software can be used as a validation tool for stent prototyping.
Shaking Table Test Study on the Earthquake Behavior of High‐Speed Railway Bridge Pier with Rounded Rectangular Cross Section
Authors: Kang Xin , Zuo Yongjian , Zeng Leqiao , Peng Linna , Wang Qiliang , Wang Xiaoxiang , Deng Libin , Hu Jia , Li Zhuo , Li Likun
Published: September 2022

Rounded rectangular cross section piers were widely used for high‐speed railway (HSR) bridges in China. However, the performance of such piers under seismic scenarios has not been well studied. To study the earthquake behavior and damage of rounded rectangular cross section piers under different intensities of earthquake excitation, nine scaled pier specimens were constructed and tested on the shaking table. Experimental results show that the specimen remains elastic (no or slight damaged) for all experimental earthquake scenarios (from 0.45 g to 0.96 g). Finite element (FE) models were developed and validated by the experimental results. Using this FE model, the damage levels of these specimens under severe earthquake excitations (from 1.05 g to 1.95 g) were quantified. Numerical results show that the specimen in transverse direction shows no or slight damage, while repairable damage can be seen in longitudinal direction as the earthquake intensity increases from 1.05 g to 1.65 g. Repairable and unrepairable damage can be seen in transverse and longitudinal direction, respectively, as the earthquake intensity increases to 1.95 g. Researchers can make good use of these findings for better earthquake design or protection of this type of HSR piers in the future.
Humanized Management of College Students Based on Machine Perspective and Intelligent Monitoring System
Authors: Huang Jianjun
Published: September 2022

In order to improve the effect of humanized management of college students, this article builds a humanized management system for college students based on the machine perspective and intelligent monitoring system, studies its hardware and software systems, and introduces the basic principle of evanescent mode resonators. Moreover, the formulas of the resonant frequency and the unloaded Q value of the resonator are deduced by the equivalent circuit of the evanescent mode resonator, and the variation curve of the unloaded Q value and the resonant frequency of the actual resonator is obtained by HFSS simulation. In addition, this article constructs a humanized management model for college students based on the machine perspective and intelligent monitoring system. The experimental research results show that the intelligent monitoring system based on the machine perspective proposed in this article has good effects and can effectively improve the quality of humanized management of college students.
Tensor Multi-Clustering Parallel Intelligent Computing Method Based on Tensor Chain Decomposition
Authors: Zhang Hongjun , Li Peng , Fan Weibei , Xue Zhuangzhuang , Meng Fanshuo
Published: September 2022

Adaptable methods for representing higher-order data with various features and high dimensionality have been demanded by the increasing usage of multi-sensor technologies and the emergence of large data sets. Arrays of multi-dimensional data, known as tensors, can be found in a variety of applications. Standard data that depicts things from a single point of view lacks the semantic richness, utility, and complexity of multi-dimensional data. Research into multi-clustering has taken off since traditional clustering methods are unable to handle large datasets. There are three main kinds of multi-clustering algorithms: Self-weighted Multiview Clustering (SwMC), Latent Multi-view Subspace Clustering (LMSC), and Multi-view Subspace Clustering with Intactness-Aware Similarity (MSC IAS) that are explored in this paper. To evaluate their performance, we do in-depth tests on seven real-world datasets. The three most important metrics Accuracy (ACC), normalized mutual information (NMI), and purity are grouped. Furthermore, traditional Principal Component Analysis (PCA) cannot uncover hidden components within multi-dimensional data. For this purpose, tensor decomposition algorithms have been presented that are flexible in terms of constraint selection and extract more broad latent components. In this examination, we also go through the various tensor decomposition methods, with an emphasis on the issues that classical PCA is designed to solve. Various tensor models are also tested for dimensionality reduction and supervised learning applications in the experiments presented here.
Automatic Detection of Cases of COVID-19 Pneumonia from Chest X-ray Images and Deep Learning Approaches
Authors: Hajjej Fahima , Ayouni Sarra , Hasan Malek , Abir Tanvir
Published: September 2022

Machine learning has already been used as a resource for disease detection and health care as a complementary tool to help with various daily health challenges. The advancement of deep learning techniques and a large amount of data-enabled algorithms to outperform medical teams in certain imaging tasks, such as pneumonia detection, skin cancer classification, hemorrhage detection, and arrhythmia detection. Automated diagnostics, which are enabled by images extracted from patient examinations, allow for interesting experiments to be conducted. This research differs from the related studies that were investigated in the experiment. These works are capable of binary categorization into two categories. COVID-Net, for example, was able to identify a positive case of COVID-19 or a healthy person with 93.3% accuracy. Another example is CHeXNet, which has a 95% accuracy rate in detecting cases of pneumonia or a healthy state in a patient. Experiments revealed that the current study was more effective than the previous studies in detecting a greater number of categories and with a higher percentage of accuracy. The results obtained during the model’s development were not only viable but also excellent, with an accuracy of nearly 96% when analyzing a chest X-ray with three possible diagnoses in the two experiments conducted.
The Promotion Effect of Computer-Aided Technology Combined with RBF Neural Network Algorithm on Art Design
Authors: Pan Chunliang , Pan Yuning
Published: September 2022

In order to improve the effect of fractal art pattern design, this study combines RBF neural network algorithm to design and evaluate CAD fractal art pattern to improve the effect of fractal art pattern design. Moreover, this study proposes a dynamic weight-based NSC method. Because noise is ubiquitous in reality, the evolution of system dynamics often cannot be carried out strictly according to the iterative rules. In addition, this study shows the changing rules of the competition relationship and the distribution of competitors under the interference of noise. Finally, this study controls the style of the art pattern design in the spatial domain and uses the mask image pattern to disguise the art style. The experimental study shows that the CAD fractal art pattern design system based on the RBF neural network algorithm proposed in this study has a good effect on fractal art pattern design.
A Framework on Performance Analysis of Mathematical Model-Based Classifiers in Detection of Epileptic Seizure from EEG Signals with Efficient Feature Selection
Authors: Hemachandira V. S. , Viswanathan R.
Published: September 2022

Epilepsy is one of the neurological conditions that are diagnosed in the vast majority of patients. Electroencephalography (EEG) readings are the primary tool that is used in the process of diagnosing and analyzing epilepsy. The epileptic EEG data display the electrical activity of the neurons and provide a significant amount of knowledge on pathology and physiology. As a result of the significant amount of time that this method requires, several automated classification methods have been developed. In this paper, three wavelets such as Haar, dB4, and Sym 8 are employed to extract the features from A–E sets of the Bonn epilepsy dataset. To select the best features of epileptic seizures, a Particle Swarm Optimization (PSO) technique is applied. The extracted features are further classified using seven classifiers like linear regression, nonlinear regression, Gaussian Mixture Modeling (GMM), K-Nearest Neighbor (KNN), Support Vector Machine (SVM-linear), SVM (polynomial), and SVM Radial Basis Function (RBF). Classifier performances are analyzed through the benchmark parameters, such as sensitivity, specificity, accuracy, F1 Score, error rate, and g-means. The SVM classifier with RBF kernel in sym 8 wavelet features with PSO feature selection method attains a higher accuracy rate of 98% with an error rate of 2%. This classifier outperforms all other classifiers.
Structural, Morphological, Optical, and Antibacterial Activities of Zinc Oxide Nanopowders: A Comparative Study of Green and Soft Chemical Synthesis
Authors: Siriya Pushpa K. Catherine , Sakthivel P. , Saravanakumar K. , Anuradha N. , Sankaranarayanan R. K. , Paulraj Mosae Selvakumar
Published: September 2022

Zinc oxide, a well-known inorganic metal oxide in nanoparticle form, has outstanding antibacterial properties. In this work, the authors focus on determining ZnO nanoparticles’ structural, optical, and antibacterial activity. A simple soft chemical route synthesizes C-ZnO nanoparticles chemically, while the green synthesis method is used to prepare G-ZnO nanoparticles. Ocimum tenuiflorum leaf extract was used to prepare G-ZnO nanopowders. These samples are investigated and compared in terms of their structural, morphological, optical, and antibacterial properties. According to XRD investigations, the synthesized ZnO nanopowders possess a hexagonal structure. The particle size of G-ZnO is smaller than that of C-ZnO nanoparticles. The XPS result revealed the binding and interactions between molecules. The FTIR study confirmed the presence of molecules and their vibrations. UV-vis-DRS spectroscopy was used to investigate optical properties such as reflectance and band gap. The grain size of the G-ZnO nanopowders was decreased, and oxygen vacancy was produced. The antibacterial efficiency of plant extracts against two different bacterial strains, S. aureus (Gram-positive) and E.coli (Gram-negative), has been studied and reported.
Multi-DS Strategy for Source Camera Identification in Few-Shot Sample Data Sets
Authors: Wang Bo , Hou Jiayao , Ma Yanyan , Wang Fei , Wei Fei
Published: September 2022

Source camera identification (SCI) is an intriguing problem in digital forensics, which identifies the source device of given images. However, most existing works require sufficient training samples to ensure performance. In this work, we propose a method based on semi-supervised ensemble learning (multi-DS) strategy, which extends labeled data set by multi-distance-based clustering strategy and then calibrate the pseudo-labels through a self-correction mechanism. Next, we iteratively perform the calibration-appending-training process to improve our model. We design comprehensive experiments, and our model achieves satisfactory performance on benchmark public databases (i.e., Dresden, VISION, and SOCRatES).